blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
bc0faf3d68d2fbcb70948a28e9775500e22cb58b | [
"super(AddPrepositions, self).__init__(scenario, args)\nif self.language is None:\n raise LoadingException('Language must be defined!')",
"match = re.match('^(?:n|adj):(.+)[+]', tnode.formeme)\nif not match:\n return None\nreturn match.group(1).split('_')",
"tchildren = tnode.get_children(preceding_only=T... | <|body_start_0|>
super(AddPrepositions, self).__init__(scenario, args)
if self.language is None:
raise LoadingException('Language must be defined!')
<|end_body_0|>
<|body_start_1|>
match = re.match('^(?:n|adj):(.+)[+]', tnode.formeme)
if not match:
return None
... | Add prepositional a-nodes according to formemes. Arguments: language: the language of the target tree selector: the selector of the target tree | AddPrepositions | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddPrepositions:
"""Add prepositional a-nodes according to formemes. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__(self, scenario, args):
"""Constructor, just checking the argument values"""
<|body_0|>
def ... | stack_v2_sparse_classes_36k_train_026100 | 1,962 | permissive | [
{
"docstring": "Constructor, just checking the argument values",
"name": "__init__",
"signature": "def __init__(self, scenario, args)"
},
{
"docstring": "Find prepositional nodes to be created.",
"name": "get_aux_forms",
"signature": "def get_aux_forms(self, tnode)"
},
{
"docstri... | 4 | null | Implement the Python class `AddPrepositions` described below.
Class description:
Add prepositional a-nodes according to formemes. Arguments: language: the language of the target tree selector: the selector of the target tree
Method signatures and docstrings:
- def __init__(self, scenario, args): Constructor, just che... | Implement the Python class `AddPrepositions` described below.
Class description:
Add prepositional a-nodes according to formemes. Arguments: language: the language of the target tree selector: the selector of the target tree
Method signatures and docstrings:
- def __init__(self, scenario, args): Constructor, just che... | 73af644ec35c8a1cd0c37cd478c2afc1db717e0b | <|skeleton|>
class AddPrepositions:
"""Add prepositional a-nodes according to formemes. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__(self, scenario, args):
"""Constructor, just checking the argument values"""
<|body_0|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddPrepositions:
"""Add prepositional a-nodes according to formemes. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__(self, scenario, args):
"""Constructor, just checking the argument values"""
super(AddPrepositions, self).__in... | the_stack_v2_python_sparse | alex/components/nlg/tectotpl/block/t2a/cs/addprepositions.py | oplatek/alex | train | 0 |
eb665d6473397346e5ff452ad47375f12e54c900 | [
"if numRows < 2 or not s or numRows >= len(s):\n return s\nlth = len(s)\nwidth = -(-lth / numRows) * (numRows - 1)\nheight = numRows\nrecord = [[''] * width for _ in range(height)]\ndown = True\ni, j = (0, 0)\nfor c in s:\n record[i][j] = c\n if down and i == height - 1:\n down = False\n elif not... | <|body_start_0|>
if numRows < 2 or not s or numRows >= len(s):
return s
lth = len(s)
width = -(-lth / numRows) * (numRows - 1)
height = numRows
record = [[''] * width for _ in range(height)]
down = True
i, j = (0, 0)
for c in s:
rec... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def convert_1(self, s, numRows):
""":type s: str :type numRows: int :rtype: str"""
<|body_0|>
def convert_2(self, s, numRows):
""":type s: str :type numRows: int :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if numRows < 2 or... | stack_v2_sparse_classes_36k_train_026101 | 1,985 | no_license | [
{
"docstring": ":type s: str :type numRows: int :rtype: str",
"name": "convert_1",
"signature": "def convert_1(self, s, numRows)"
},
{
"docstring": ":type s: str :type numRows: int :rtype: str",
"name": "convert_2",
"signature": "def convert_2(self, s, numRows)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def convert_1(self, s, numRows): :type s: str :type numRows: int :rtype: str
- def convert_2(self, s, numRows): :type s: str :type numRows: int :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def convert_1(self, s, numRows): :type s: str :type numRows: int :rtype: str
- def convert_2(self, s, numRows): :type s: str :type numRows: int :rtype: str
<|skeleton|>
class So... | 0e99f9a5226507706b3ee66fd04bae813755ef40 | <|skeleton|>
class Solution:
def convert_1(self, s, numRows):
""":type s: str :type numRows: int :rtype: str"""
<|body_0|>
def convert_2(self, s, numRows):
""":type s: str :type numRows: int :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def convert_1(self, s, numRows):
""":type s: str :type numRows: int :rtype: str"""
if numRows < 2 or not s or numRows >= len(s):
return s
lth = len(s)
width = -(-lth / numRows) * (numRows - 1)
height = numRows
record = [[''] * width for _ i... | the_stack_v2_python_sparse | medium/arrayandstring/test_6_ZigZag_Conversion.py | wuxu1019/leetcode_sophia | train | 1 | |
3d52ad8fde6c4856c597c9cf9b40301c74a7f5af | [
"super().__init__(coordinator, device_info, room_name, shade.id)\nself._shade_name = shade_name\nself._shade = shade",
"device_info = {'identifiers': {(DOMAIN, self._shade.id)}, 'name': self._shade_name, 'suggested_area': self._room_name, 'manufacturer': MANUFACTURER, 'model': self._shade.raw_data[ATTR_TYPE], 'vi... | <|body_start_0|>
super().__init__(coordinator, device_info, room_name, shade.id)
self._shade_name = shade_name
self._shade = shade
<|end_body_0|>
<|body_start_1|>
device_info = {'identifiers': {(DOMAIN, self._shade.id)}, 'name': self._shade_name, 'suggested_area': self._room_name, 'manu... | Base class for hunter douglas shade entities. | ShadeEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShadeEntity:
"""Base class for hunter douglas shade entities."""
def __init__(self, coordinator, device_info, room_name, shade, shade_name):
"""Initialize the shade."""
<|body_0|>
def device_info(self):
"""Return the device_info of the device."""
<|body_1... | stack_v2_sparse_classes_36k_train_026102 | 2,930 | permissive | [
{
"docstring": "Initialize the shade.",
"name": "__init__",
"signature": "def __init__(self, coordinator, device_info, room_name, shade, shade_name)"
},
{
"docstring": "Return the device_info of the device.",
"name": "device_info",
"signature": "def device_info(self)"
}
] | 2 | null | Implement the Python class `ShadeEntity` described below.
Class description:
Base class for hunter douglas shade entities.
Method signatures and docstrings:
- def __init__(self, coordinator, device_info, room_name, shade, shade_name): Initialize the shade.
- def device_info(self): Return the device_info of the device... | Implement the Python class `ShadeEntity` described below.
Class description:
Base class for hunter douglas shade entities.
Method signatures and docstrings:
- def __init__(self, coordinator, device_info, room_name, shade, shade_name): Initialize the shade.
- def device_info(self): Return the device_info of the device... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class ShadeEntity:
"""Base class for hunter douglas shade entities."""
def __init__(self, coordinator, device_info, room_name, shade, shade_name):
"""Initialize the shade."""
<|body_0|>
def device_info(self):
"""Return the device_info of the device."""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShadeEntity:
"""Base class for hunter douglas shade entities."""
def __init__(self, coordinator, device_info, room_name, shade, shade_name):
"""Initialize the shade."""
super().__init__(coordinator, device_info, room_name, shade.id)
self._shade_name = shade_name
self._shad... | the_stack_v2_python_sparse | homeassistant/components/hunterdouglas_powerview/entity.py | BenWoodford/home-assistant | train | 11 |
2b1f50089e57aa15008055ed5be78d6de98c8f2d | [
"used_ids = model_admin.model.objects.values_list(field.attname, flat=True).distinct()\nqs = field.related_model.objects.filter(pk__in=used_ids)\nchoice_ids = field.related_model.objects.get_queryset_ancestors(qs, include_self=True).values_list('id', flat=True).distinct()\nordering = self.field_admin_ordering(field... | <|body_start_0|>
used_ids = model_admin.model.objects.values_list(field.attname, flat=True).distinct()
qs = field.related_model.objects.filter(pk__in=used_ids)
choice_ids = field.related_model.objects.get_queryset_ancestors(qs, include_self=True).values_list('id', flat=True).distinct()
o... | TreeModelFieldListFilter | [
"CC0-1.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TreeModelFieldListFilter:
def field_choices(self, field, request, model_admin):
"""Return only choices, which are actually used. Include children of selected object in the results"""
<|body_0|>
def queryset(self, request, queryset):
"""Remove old filter and replace i... | stack_v2_sparse_classes_36k_train_026103 | 14,210 | permissive | [
{
"docstring": "Return only choices, which are actually used. Include children of selected object in the results",
"name": "field_choices",
"signature": "def field_choices(self, field, request, model_admin)"
},
{
"docstring": "Remove old filter and replace it with a filter that includes children... | 2 | stack_v2_sparse_classes_30k_train_017041 | Implement the Python class `TreeModelFieldListFilter` described below.
Class description:
Implement the TreeModelFieldListFilter class.
Method signatures and docstrings:
- def field_choices(self, field, request, model_admin): Return only choices, which are actually used. Include children of selected object in the res... | Implement the Python class `TreeModelFieldListFilter` described below.
Class description:
Implement the TreeModelFieldListFilter class.
Method signatures and docstrings:
- def field_choices(self, field, request, model_admin): Return only choices, which are actually used. Include children of selected object in the res... | aef660099fa251b66c5a8c56214a09e9b52bcc57 | <|skeleton|>
class TreeModelFieldListFilter:
def field_choices(self, field, request, model_admin):
"""Return only choices, which are actually used. Include children of selected object in the results"""
<|body_0|>
def queryset(self, request, queryset):
"""Remove old filter and replace i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TreeModelFieldListFilter:
def field_choices(self, field, request, model_admin):
"""Return only choices, which are actually used. Include children of selected object in the results"""
used_ids = model_admin.model.objects.values_list(field.attname, flat=True).distinct()
qs = field.relate... | the_stack_v2_python_sparse | traffic_control/admin/utils.py | City-of-Helsinki/city-infrastructure-platform | train | 5 | |
51cee148528959e58f43a270a584048594784560 | [
"super().__init__()\nself.fwd = decomposition_resolver.make(query=decomposition, pos_kwargs=decomposition_kwargs, input_dim=input_dim, output_dim=output_dim, num_relations=num_relations)\nself.bwd = decomposition_resolver.make(query=decomposition, pos_kwargs=decomposition_kwargs, input_dim=input_dim, output_dim=out... | <|body_start_0|>
super().__init__()
self.fwd = decomposition_resolver.make(query=decomposition, pos_kwargs=decomposition_kwargs, input_dim=input_dim, output_dim=output_dim, num_relations=num_relations)
self.bwd = decomposition_resolver.make(query=decomposition, pos_kwargs=decomposition_kwargs, i... | An RGCN layer from [schlichtkrull2018]_ updated to match the official implementation. This layer uses separate decompositions for forward and backward edges (i.e., "normal" and implicitly created inverse relations), as well as a separate transformation for self-loops. Ignoring dropouts, decomposition and normalization,... | RGCNLayer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RGCNLayer:
"""An RGCN layer from [schlichtkrull2018]_ updated to match the official implementation. This layer uses separate decompositions for forward and backward edges (i.e., "normal" and implicitly created inverse relations), as well as a separate transformation for self-loops. Ignoring dropo... | stack_v2_sparse_classes_36k_train_026104 | 29,396 | permissive | [
{
"docstring": "Initialize the layer. :param input_dim: >0 the input dimension :param num_relations: the number of relations :param output_dim: >0 the output dimension. If none is given, use the input dimension. :param use_bias: whether to use a trainable bias :param activation: the activation function to use. ... | 2 | null | Implement the Python class `RGCNLayer` described below.
Class description:
An RGCN layer from [schlichtkrull2018]_ updated to match the official implementation. This layer uses separate decompositions for forward and backward edges (i.e., "normal" and implicitly created inverse relations), as well as a separate transf... | Implement the Python class `RGCNLayer` described below.
Class description:
An RGCN layer from [schlichtkrull2018]_ updated to match the official implementation. This layer uses separate decompositions for forward and backward edges (i.e., "normal" and implicitly created inverse relations), as well as a separate transf... | 5ff3597b18ab9a220e34361d3c3f262060811df1 | <|skeleton|>
class RGCNLayer:
"""An RGCN layer from [schlichtkrull2018]_ updated to match the official implementation. This layer uses separate decompositions for forward and backward edges (i.e., "normal" and implicitly created inverse relations), as well as a separate transformation for self-loops. Ignoring dropo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RGCNLayer:
"""An RGCN layer from [schlichtkrull2018]_ updated to match the official implementation. This layer uses separate decompositions for forward and backward edges (i.e., "normal" and implicitly created inverse relations), as well as a separate transformation for self-loops. Ignoring dropouts, decompos... | the_stack_v2_python_sparse | src/pykeen/nn/message_passing.py | pykeen/pykeen | train | 1,308 |
9640f1f4dfa642d258e2ac2bb13f40e38cbf99d7 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | This file describes an API for collecting and viewing traces and spans within a trace. A Trace is a collection of spans corresponding to a single operation or set of operations for an application. A span is an individual timed event which forms a node of the trace tree. A single trace may contain span(s) from multiple ... | TraceServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TraceServiceServicer:
"""This file describes an API for collecting and viewing traces and spans within a trace. A Trace is a collection of spans corresponding to a single operation or set of operations for an application. A span is an individual timed event which forms a node of the trace tree. A... | stack_v2_sparse_classes_36k_train_026105 | 3,567 | permissive | [
{
"docstring": "Sends new spans to new or existing traces. You cannot update existing spans.",
"name": "BatchWriteSpans",
"signature": "def BatchWriteSpans(self, request, context)"
},
{
"docstring": "Creates a new span.",
"name": "CreateSpan",
"signature": "def CreateSpan(self, request, ... | 2 | stack_v2_sparse_classes_30k_train_012309 | Implement the Python class `TraceServiceServicer` described below.
Class description:
This file describes an API for collecting and viewing traces and spans within a trace. A Trace is a collection of spans corresponding to a single operation or set of operations for an application. A span is an individual timed event ... | Implement the Python class `TraceServiceServicer` described below.
Class description:
This file describes an API for collecting and viewing traces and spans within a trace. A Trace is a collection of spans corresponding to a single operation or set of operations for an application. A span is an individual timed event ... | d897d56bce03d1fda98b79afb08264e51d46c421 | <|skeleton|>
class TraceServiceServicer:
"""This file describes an API for collecting and viewing traces and spans within a trace. A Trace is a collection of spans corresponding to a single operation or set of operations for an application. A span is an individual timed event which forms a node of the trace tree. A... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TraceServiceServicer:
"""This file describes an API for collecting and viewing traces and spans within a trace. A Trace is a collection of spans corresponding to a single operation or set of operations for an application. A span is an individual timed event which forms a node of the trace tree. A single trace... | the_stack_v2_python_sparse | trace/google/cloud/trace_v2/proto/tracing_pb2_grpc.py | tswast/google-cloud-python | train | 1 |
446673c23c6df008d27813a75a718b499c6e50b5 | [
"m = 100\nctx.save_for_backward(k)\nk = k.double()\nanswer = (m / 2 - 1) * torch.log(k) - torch.log(scipy.special.ive(m / 2 - 1, k.cpu())) - k - m / 2 * np.log(2 * np.pi)\nanswer = answer.float()\nreturn answer",
"k, = ctx.saved_tensors\nm = 100\nk = k.double()\nx = -(scipy.special.ive(m / 2, k.cpu()) / scipy.spe... | <|body_start_0|>
m = 100
ctx.save_for_backward(k)
k = k.double()
answer = (m / 2 - 1) * torch.log(k) - torch.log(scipy.special.ive(m / 2 - 1, k.cpu())) - k - m / 2 * np.log(2 * np.pi)
answer = answer.float()
return answer
<|end_body_0|>
<|body_start_1|>
k, = ctx.... | The exponentially scaled modified Bessel function of the first kind | Logcmk | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Logcmk:
"""The exponentially scaled modified Bessel function of the first kind"""
def forward(ctx, k):
"""In the forward pass we receive a Tensor containing the input and return a Tensor containing the output. ctx is a context object that can be used to stash information for backward... | stack_v2_sparse_classes_36k_train_026106 | 11,289 | no_license | [
{
"docstring": "In the forward pass we receive a Tensor containing the input and return a Tensor containing the output. ctx is a context object that can be used to stash information for backward computation. You can cache arbitrary objects for use in the backward pass using the ctx.save_for_backward method.",
... | 2 | stack_v2_sparse_classes_30k_train_000237 | Implement the Python class `Logcmk` described below.
Class description:
The exponentially scaled modified Bessel function of the first kind
Method signatures and docstrings:
- def forward(ctx, k): In the forward pass we receive a Tensor containing the input and return a Tensor containing the output. ctx is a context ... | Implement the Python class `Logcmk` described below.
Class description:
The exponentially scaled modified Bessel function of the first kind
Method signatures and docstrings:
- def forward(ctx, k): In the forward pass we receive a Tensor containing the input and return a Tensor containing the output. ctx is a context ... | 251142b2e704e595e664031f5a469ebad6de8333 | <|skeleton|>
class Logcmk:
"""The exponentially scaled modified Bessel function of the first kind"""
def forward(ctx, k):
"""In the forward pass we receive a Tensor containing the input and return a Tensor containing the output. ctx is a context object that can be used to stash information for backward... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Logcmk:
"""The exponentially scaled modified Bessel function of the first kind"""
def forward(ctx, k):
"""In the forward pass we receive a Tensor containing the input and return a Tensor containing the output. ctx is a context object that can be used to stash information for backward computation.... | the_stack_v2_python_sparse | contrastive_vmf.py | dheeraj7596/Coarse2Fine | train | 1 |
b41ec46cf9c2113467c51e9c4fb656d9a9f1a320 | [
"data = parsers.parse_key(file_key='icrf2_non_vcs').as_dict()\ndata.update(parsers.parse_key(file_key='icrf2_vcs_only').as_dict())\nreturn data",
"source_info = self.data[source]\nvector = Direction(ra=source_info['ra'], dec=source_info['dec'], time=self.time)\nreturn np.squeeze(vector)"
] | <|body_start_0|>
data = parsers.parse_key(file_key='icrf2_non_vcs').as_dict()
data.update(parsers.parse_key(file_key='icrf2_vcs_only').as_dict())
return data
<|end_body_0|>
<|body_start_1|>
source_info = self.data[source]
vector = Direction(ra=source_info['ra'], dec=source_info[... | A class to provide information from radio sources defined in ICRF2 | Icrf2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Icrf2:
"""A class to provide information from radio sources defined in ICRF2"""
def _read_data(self):
"""Read data needed by this Celestial Reference Frame for calculating positions of sources Returns: Dict: Dictionary containing data about each source defined in this reference frame... | stack_v2_sparse_classes_36k_train_026107 | 1,419 | permissive | [
{
"docstring": "Read data needed by this Celestial Reference Frame for calculating positions of sources Returns: Dict: Dictionary containing data about each source defined in this reference frame.",
"name": "_read_data",
"signature": "def _read_data(self)"
},
{
"docstring": "Calculate position f... | 2 | null | Implement the Python class `Icrf2` described below.
Class description:
A class to provide information from radio sources defined in ICRF2
Method signatures and docstrings:
- def _read_data(self): Read data needed by this Celestial Reference Frame for calculating positions of sources Returns: Dict: Dictionary containi... | Implement the Python class `Icrf2` described below.
Class description:
A class to provide information from radio sources defined in ICRF2
Method signatures and docstrings:
- def _read_data(self): Read data needed by this Celestial Reference Frame for calculating positions of sources Returns: Dict: Dictionary containi... | 0c8c5c68adca08f97e22cab1bce10e382a7fbf77 | <|skeleton|>
class Icrf2:
"""A class to provide information from radio sources defined in ICRF2"""
def _read_data(self):
"""Read data needed by this Celestial Reference Frame for calculating positions of sources Returns: Dict: Dictionary containing data about each source defined in this reference frame... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Icrf2:
"""A class to provide information from radio sources defined in ICRF2"""
def _read_data(self):
"""Read data needed by this Celestial Reference Frame for calculating positions of sources Returns: Dict: Dictionary containing data about each source defined in this reference frame."""
... | the_stack_v2_python_sparse | where/apriori/crf/icrf2.py | kartverket/where | train | 21 |
e563081bd06de46d07aa505d6e7670695d9dda24 | [
"self.res = 0\nself.dfs(root)\nreturn self.res",
"if not root:\n return 0\nleft = self.dfs(root.left)\nright = self.dfs(root.right)\nif root.left and root.left.val == root.val:\n left += 1\nelse:\n left = 0\nif root.right and root.right.val == root.val:\n right += 1\nelse:\n right = 0\nself.res = m... | <|body_start_0|>
self.res = 0
self.dfs(root)
return self.res
<|end_body_0|>
<|body_start_1|>
if not root:
return 0
left = self.dfs(root.left)
right = self.dfs(root.right)
if root.left and root.left.val == root.val:
left += 1
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestUnivaluePath(self, root):
"""Args: root: TreeNode Return: int"""
<|body_0|>
def dfs(self, root):
"""Args: root: TreeNode Return: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.res = 0
self.dfs(root)
ret... | stack_v2_sparse_classes_36k_train_026108 | 1,692 | no_license | [
{
"docstring": "Args: root: TreeNode Return: int",
"name": "longestUnivaluePath",
"signature": "def longestUnivaluePath(self, root)"
},
{
"docstring": "Args: root: TreeNode Return: int",
"name": "dfs",
"signature": "def dfs(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017115 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestUnivaluePath(self, root): Args: root: TreeNode Return: int
- def dfs(self, root): Args: root: TreeNode Return: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestUnivaluePath(self, root): Args: root: TreeNode Return: int
- def dfs(self, root): Args: root: TreeNode Return: int
<|skeleton|>
class Solution:
def longestUnival... | 101bce2fac8b188a4eb2f5e017293d21ad0ecb21 | <|skeleton|>
class Solution:
def longestUnivaluePath(self, root):
"""Args: root: TreeNode Return: int"""
<|body_0|>
def dfs(self, root):
"""Args: root: TreeNode Return: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestUnivaluePath(self, root):
"""Args: root: TreeNode Return: int"""
self.res = 0
self.dfs(root)
return self.res
def dfs(self, root):
"""Args: root: TreeNode Return: int"""
if not root:
return 0
left = self.dfs(root.left... | the_stack_v2_python_sparse | code/687. 最长同值路径.py | AiZhanghan/Leetcode | train | 0 | |
13b59db3f2968efaadf006a57e566787a23a11d2 | [
"site = get_current_site()\nnew_node = cms_models.TreeNode(site=site)\nif self.parent:\n return self.parent.node.add_child(instance=new_node)\nreturn cms_models.TreeNode.add_root(instance=new_node)",
"super()._after_postgeneration(instance, create, results=results)\ninstance.rescan_placeholders()\nif results.g... | <|body_start_0|>
site = get_current_site()
new_node = cms_models.TreeNode(site=site)
if self.parent:
return self.parent.node.add_child(instance=new_node)
return cms_models.TreeNode.add_root(instance=new_node)
<|end_body_0|>
<|body_start_1|>
super()._after_postgenerat... | Create random CMS pages. | PageFactory | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PageFactory:
"""Create random CMS pages."""
def node(self):
"""Create a node for the page (under its parent if applicable)."""
<|body_0|>
def _after_postgeneration(cls, instance, create, results=None):
"""This hook method is called last when generating an instanc... | stack_v2_sparse_classes_36k_train_026109 | 11,346 | permissive | [
{
"docstring": "Create a node for the page (under its parent if applicable).",
"name": "node",
"signature": "def node(self)"
},
{
"docstring": "This hook method is called last when generating an instance from a factory. The super method saves the instance one last time after all the \"post_gener... | 3 | null | Implement the Python class `PageFactory` described below.
Class description:
Create random CMS pages.
Method signatures and docstrings:
- def node(self): Create a node for the page (under its parent if applicable).
- def _after_postgeneration(cls, instance, create, results=None): This hook method is called last when ... | Implement the Python class `PageFactory` described below.
Class description:
Create random CMS pages.
Method signatures and docstrings:
- def node(self): Create a node for the page (under its parent if applicable).
- def _after_postgeneration(cls, instance, create, results=None): This hook method is called last when ... | f2d46fc46b271eb3b4d565039a29c15ba15f027c | <|skeleton|>
class PageFactory:
"""Create random CMS pages."""
def node(self):
"""Create a node for the page (under its parent if applicable)."""
<|body_0|>
def _after_postgeneration(cls, instance, create, results=None):
"""This hook method is called last when generating an instanc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PageFactory:
"""Create random CMS pages."""
def node(self):
"""Create a node for the page (under its parent if applicable)."""
site = get_current_site()
new_node = cms_models.TreeNode(site=site)
if self.parent:
return self.parent.node.add_child(instance=new_nod... | the_stack_v2_python_sparse | src/richie/apps/core/factories.py | openfun/richie | train | 238 |
d336959fdd9497f2acabeef683885824f8ce7414 | [
"if x < 0:\n return False\nreturn self.reverse(x) == x",
"if x == 0:\n return 0\nsign = 1 if x > 0 else -1\nx = x * sign\nrev = 0\nwhile x != 0:\n x, rev = (x // 10, rev * 10 + x % 10)\nrev = rev * sign\nreturn rev"
] | <|body_start_0|>
if x < 0:
return False
return self.reverse(x) == x
<|end_body_0|>
<|body_start_1|>
if x == 0:
return 0
sign = 1 if x > 0 else -1
x = x * sign
rev = 0
while x != 0:
x, rev = (x // 10, rev * 10 + x % 10)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
<|body_0|>
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if x < 0:
return False
return self.reverse(x) == x
... | stack_v2_sparse_classes_36k_train_026110 | 1,138 | no_license | [
{
"docstring": ":type x: int :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "reverse",
"signature": "def reverse(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003173 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, x): :type x: int :rtype: bool
- def reverse(self, x): :type x: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, x): :type x: int :rtype: bool
- def reverse(self, x): :type x: int :rtype: int
<|skeleton|>
class Solution:
def isPalindrome(self, x):
""":ty... | 4af44f7364c6fb4d95309056f7a7853de779b3bb | <|skeleton|>
class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
<|body_0|>
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
if x < 0:
return False
return self.reverse(x) == x
def reverse(self, x):
""":type x: int :rtype: int"""
if x == 0:
return 0
sign = 1 if x > 0 else -1
x = x ... | the_stack_v2_python_sparse | codes_python/0009_Palindrome_Number.py | mondler/leetcode | train | 0 | |
327d3a88a0f4e25c719c7b1b1113866183ccf6f4 | [
"if not cls.data[symbol].truncate(after=Clock.curr_time).tail(1).empty:\n return cls.data[symbol].truncate(after=Clock.curr_time).tail(1)\nelse:\n return pd.DataFrame()",
"if not cls.data[symbol].truncate(after=Clock.curr_time).tail(lookback).empty:\n return cls.data[symbol].truncate(after=Clock.curr_tim... | <|body_start_0|>
if not cls.data[symbol].truncate(after=Clock.curr_time).tail(1).empty:
return cls.data[symbol].truncate(after=Clock.curr_time).tail(1)
else:
return pd.DataFrame()
<|end_body_0|>
<|body_start_1|>
if not cls.data[symbol].truncate(after=Clock.curr_time).tai... | Data | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Data:
def current(cls, symbol: str, end: str, timeframe: str='1Min'):
"""Get the current barset at end date :param symbols: asset to look up :param end: end date ("current" date) :param timeframe: One of minute, 1Min, 5Min, 15Min, day or 1D. minute is an alias of 1Min. Similarly, day is ... | stack_v2_sparse_classes_36k_train_026111 | 7,137 | no_license | [
{
"docstring": "Get the current barset at end date :param symbols: asset to look up :param end: end date (\"current\" date) :param timeframe: One of minute, 1Min, 5Min, 15Min, day or 1D. minute is an alias of 1Min. Similarly, day is of 1D. :return: pd.Series of length 1",
"name": "current",
"signature":... | 2 | stack_v2_sparse_classes_30k_train_001371 | Implement the Python class `Data` described below.
Class description:
Implement the Data class.
Method signatures and docstrings:
- def current(cls, symbol: str, end: str, timeframe: str='1Min'): Get the current barset at end date :param symbols: asset to look up :param end: end date ("current" date) :param timeframe... | Implement the Python class `Data` described below.
Class description:
Implement the Data class.
Method signatures and docstrings:
- def current(cls, symbol: str, end: str, timeframe: str='1Min'): Get the current barset at end date :param symbols: asset to look up :param end: end date ("current" date) :param timeframe... | 07af1702057ca1e2c8dcca1ad29fcb78d9d72bc1 | <|skeleton|>
class Data:
def current(cls, symbol: str, end: str, timeframe: str='1Min'):
"""Get the current barset at end date :param symbols: asset to look up :param end: end date ("current" date) :param timeframe: One of minute, 1Min, 5Min, 15Min, day or 1D. minute is an alias of 1Min. Similarly, day is ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Data:
def current(cls, symbol: str, end: str, timeframe: str='1Min'):
"""Get the current barset at end date :param symbols: asset to look up :param end: end date ("current" date) :param timeframe: One of minute, 1Min, 5Min, 15Min, day or 1D. minute is an alias of 1Min. Similarly, day is of 1D. :return... | the_stack_v2_python_sparse | venv/Lib/Backtest/run.py | peiranhu1997/stock-trade | train | 0 | |
795153bb130e4176e5034a201746d31595325472 | [
"if dut_node['type'] == NodeType.DUT:\n adj_mac0, adj_mac1 = L3fwdTest.get_adj_mac(nodes_info, dut_node, dut_if1, dut_if2)\n list_cores = [int(item) for item in lcores_list.split(',')]\n nb_cores = int(nb_cores)\n index = 0\n port_config = ''\n for port in range(0, 2):\n for queue in range(... | <|body_start_0|>
if dut_node['type'] == NodeType.DUT:
adj_mac0, adj_mac1 = L3fwdTest.get_adj_mac(nodes_info, dut_node, dut_if1, dut_if2)
list_cores = [int(item) for item in lcores_list.split(',')]
nb_cores = int(nb_cores)
index = 0
port_config = ''
... | Test the DPDK l3fwd performance. | L3fwdTest | [
"CC-BY-4.0",
"Apache-2.0",
"LicenseRef-scancode-dco-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class L3fwdTest:
"""Test the DPDK l3fwd performance."""
def start_the_l3fwd_test(nodes_info, dut_node, dut_if1, dut_if2, nb_cores, lcores_list, queue_nums, jumbo_frames):
"""Execute the l3fwd on the dut_node. :param nodes_info: All the nodes info in the topology file. :param dut_node: Will... | stack_v2_sparse_classes_36k_train_026112 | 5,529 | permissive | [
{
"docstring": "Execute the l3fwd on the dut_node. :param nodes_info: All the nodes info in the topology file. :param dut_node: Will execute the l3fwd on this node :param dut_if1: The test link interface 1. :param dut_if2: The test link interface 2. :param nb_cores: The cores number for the forwarding :param lc... | 3 | null | Implement the Python class `L3fwdTest` described below.
Class description:
Test the DPDK l3fwd performance.
Method signatures and docstrings:
- def start_the_l3fwd_test(nodes_info, dut_node, dut_if1, dut_if2, nb_cores, lcores_list, queue_nums, jumbo_frames): Execute the l3fwd on the dut_node. :param nodes_info: All t... | Implement the Python class `L3fwdTest` described below.
Class description:
Test the DPDK l3fwd performance.
Method signatures and docstrings:
- def start_the_l3fwd_test(nodes_info, dut_node, dut_if1, dut_if2, nb_cores, lcores_list, queue_nums, jumbo_frames): Execute the l3fwd on the dut_node. :param nodes_info: All t... | 3151c98618c78e3782e48bbe4d9c8f906c126f69 | <|skeleton|>
class L3fwdTest:
"""Test the DPDK l3fwd performance."""
def start_the_l3fwd_test(nodes_info, dut_node, dut_if1, dut_if2, nb_cores, lcores_list, queue_nums, jumbo_frames):
"""Execute the l3fwd on the dut_node. :param nodes_info: All the nodes info in the topology file. :param dut_node: Will... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class L3fwdTest:
"""Test the DPDK l3fwd performance."""
def start_the_l3fwd_test(nodes_info, dut_node, dut_if1, dut_if2, nb_cores, lcores_list, queue_nums, jumbo_frames):
"""Execute the l3fwd on the dut_node. :param nodes_info: All the nodes info in the topology file. :param dut_node: Will execute the ... | the_stack_v2_python_sparse | resources/libraries/python/DPDK/L3fwdTest.py | preym17/csit | train | 0 |
f4c83df86710cab187ff272df237ae5067e5e0d7 | [
"values = board_config_string.split(delimiter)\ncount = len(values)\nif not values[0]:\n raise ValueError('board_config_string')\nself.name = values[0]\ntry:\n self.difficulty = Difficulty[values[1]]\nexcept:\n self.difficulty = Difficulty.default\ntry:\n self.attribute = CharacterAttribute[values[2]]\n... | <|body_start_0|>
values = board_config_string.split(delimiter)
count = len(values)
if not values[0]:
raise ValueError('board_config_string')
self.name = values[0]
try:
self.difficulty = Difficulty[values[1]]
except:
self.difficulty = Di... | Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (scriptabit.Difficulty): the default difficulty for this board. attribute (script... | BoardConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BoardConfig:
"""Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (scriptabit.Difficulty): the default diffi... | stack_v2_sparse_classes_36k_train_026113 | 2,453 | permissive | [
{
"docstring": "Initialises the BoardConfig instance. Args: board_config_string (str): The board configuration string. This is a packed string containing up to four options, delimited by `delimiter`. E.G.:: 'board_name|difficulty|attribute|user' If the user field is not specified, then it defaults to `all_cards... | 2 | stack_v2_sparse_classes_30k_train_019085 | Implement the Python class `BoardConfig` described below.
Class description:
Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (sc... | Implement the Python class `BoardConfig` described below.
Class description:
Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (sc... | 0d0cf71814e98954850891fa0887bdcffcf7147d | <|skeleton|>
class BoardConfig:
"""Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (scriptabit.Difficulty): the default diffi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BoardConfig:
"""Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (scriptabit.Difficulty): the default difficulty for thi... | the_stack_v2_python_sparse | scriptabit/plugins/trello/board_config.py | DC23/scriptabit | train | 10 |
7c9075be0612ac805de36f0c5bef5cb542047334 | [
"self.trie = Trie()\nfor w, wo in enumerate(words):\n wo += '#'\n for i in range(len(wo)):\n cur = self.trie\n cur[WEIGHT] = w\n for j in range(i, 2 * len(wo) - 1):\n cur = cur[wo[j % len(wo)]]\n cur[WEIGHT] = w",
"cur = self.trie\nfor le in suffix + '#' + prefix:\... | <|body_start_0|>
self.trie = Trie()
for w, wo in enumerate(words):
wo += '#'
for i in range(len(wo)):
cur = self.trie
cur[WEIGHT] = w
for j in range(i, 2 * len(wo) - 1):
cur = cur[wo[j % len(wo)]]
... | WordFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordFilter:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def f(self, prefix, suffix):
""":type prefix: str :type suffix: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.trie = Trie()
for w, wo in en... | stack_v2_sparse_classes_36k_train_026114 | 962 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type prefix: str :type suffix: str :rtype: int",
"name": "f",
"signature": "def f(self, prefix, suffix)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000112 | Implement the Python class `WordFilter` described below.
Class description:
Implement the WordFilter class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def f(self, prefix, suffix): :type prefix: str :type suffix: str :rtype: int | Implement the Python class `WordFilter` described below.
Class description:
Implement the WordFilter class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def f(self, prefix, suffix): :type prefix: str :type suffix: str :rtype: int
<|skeleton|>
class WordFilter:
def __in... | 20623defecf65cbc35b194d8b60d8b211816ee4f | <|skeleton|>
class WordFilter:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def f(self, prefix, suffix):
""":type prefix: str :type suffix: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WordFilter:
def __init__(self, words):
""":type words: List[str]"""
self.trie = Trie()
for w, wo in enumerate(words):
wo += '#'
for i in range(len(wo)):
cur = self.trie
cur[WEIGHT] = w
for j in range(i, 2 * len(wo)... | the_stack_v2_python_sparse | in_Python_v2/0745 Prefix and Suffix Search.py | YangLiyli131/Leetcode2020 | train | 0 | |
4d37508937b388abae7d546805e83ec0a8352902 | [
"def construct(r, lt, rt):\n if r is None:\n return r\n root = TreeNode(r)\n lroot = max(lt + [None])\n rroot = max(rt + [None])\n root.left = construct(lroot, lt[:lt.index(lroot)], lt[lt.index(lroot) + 1:]) if lroot is not None else None\n root.right = construct(rroot, rt[:rt.index(rroot)]... | <|body_start_0|>
def construct(r, lt, rt):
if r is None:
return r
root = TreeNode(r)
lroot = max(lt + [None])
rroot = max(rt + [None])
root.left = construct(lroot, lt[:lt.index(lroot)], lt[lt.index(lroot) + 1:]) if lroot is not None els... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_0|>
def rewrite(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def construct(r, lt, rt)... | stack_v2_sparse_classes_36k_train_026115 | 2,854 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: TreeNode",
"name": "constructMaximumBinaryTree",
"signature": "def constructMaximumBinaryTree(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: TreeNode",
"name": "rewrite",
"signature": "def rewrite(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode
- def rewrite(self, nums): :type nums: List[int] :rtype: TreeNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode
- def rewrite(self, nums): :type nums: List[int] :rtype: TreeNode
<|skeleton|>
class Solution:... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_0|>
def rewrite(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
def construct(r, lt, rt):
if r is None:
return r
root = TreeNode(r)
lroot = max(lt + [None])
rroot = max(rt + [None])
r... | the_stack_v2_python_sparse | tree/654_Maximum_Binary_Tree.py | vsdrun/lc_public | train | 6 | |
3175fb9349588bb3e7cca403342792cf0ad2e144 | [
"self.client_subnet_whitelist_vec = client_subnet_whitelist_vec\nself.disable_nfs_access = disable_nfs_access\nself.protocol_access_info = protocol_access_info\nself.qos_mapping_vec = qos_mapping_vec\nself.storage_policy_override = storage_policy_override\nself.view_description = view_description\nself.worm_lock_ex... | <|body_start_0|>
self.client_subnet_whitelist_vec = client_subnet_whitelist_vec
self.disable_nfs_access = disable_nfs_access
self.protocol_access_info = protocol_access_info
self.qos_mapping_vec = qos_mapping_vec
self.storage_policy_override = storage_policy_override
self... | Implementation of the 'ViewParams' model. TODO: type description here. Attributes: client_subnet_whitelist_vec (list of ClusterConfigProto_Subnet): List of external client subnets from where requests will be received for the new view. disable_nfs_access (bool): Whether to disable NFS access in the new view. protocol_ac... | ViewParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViewParams:
"""Implementation of the 'ViewParams' model. TODO: type description here. Attributes: client_subnet_whitelist_vec (list of ClusterConfigProto_Subnet): List of external client subnets from where requests will be received for the new view. disable_nfs_access (bool): Whether to disable N... | stack_v2_sparse_classes_36k_train_026116 | 5,235 | permissive | [
{
"docstring": "Constructor for the ViewParams class",
"name": "__init__",
"signature": "def __init__(self, client_subnet_whitelist_vec=None, disable_nfs_access=None, protocol_access_info=None, qos_mapping_vec=None, storage_policy_override=None, view_description=None, worm_lock_expiry_usecs=None)"
},
... | 2 | null | Implement the Python class `ViewParams` described below.
Class description:
Implementation of the 'ViewParams' model. TODO: type description here. Attributes: client_subnet_whitelist_vec (list of ClusterConfigProto_Subnet): List of external client subnets from where requests will be received for the new view. disable_... | Implement the Python class `ViewParams` described below.
Class description:
Implementation of the 'ViewParams' model. TODO: type description here. Attributes: client_subnet_whitelist_vec (list of ClusterConfigProto_Subnet): List of external client subnets from where requests will be received for the new view. disable_... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ViewParams:
"""Implementation of the 'ViewParams' model. TODO: type description here. Attributes: client_subnet_whitelist_vec (list of ClusterConfigProto_Subnet): List of external client subnets from where requests will be received for the new view. disable_nfs_access (bool): Whether to disable N... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ViewParams:
"""Implementation of the 'ViewParams' model. TODO: type description here. Attributes: client_subnet_whitelist_vec (list of ClusterConfigProto_Subnet): List of external client subnets from where requests will be received for the new view. disable_nfs_access (bool): Whether to disable NFS access in ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/view_params.py | cohesity/management-sdk-python | train | 24 |
6de48c4c16f0af448e8807bcc9091b96682764c8 | [
"m = len(grid)\nn = len(grid[0])\nfor i in range(1, n):\n grid[0][i] += grid[0][i - 1]\nfor i in range(1, m):\n grid[i][0] += grid[i - 1][0]\nfor i in range(1, m):\n for j in range(1, n):\n grid[i][j] = min(grid[i][j] + grid[i - 1][j], grid[i][j] + grid[i][j - 1])\nreturn grid[m - 1][n - 1]",
"res... | <|body_start_0|>
m = len(grid)
n = len(grid[0])
for i in range(1, n):
grid[0][i] += grid[0][i - 1]
for i in range(1, m):
grid[i][0] += grid[i - 1][0]
for i in range(1, m):
for j in range(1, n):
grid[i][j] = min(grid[i][j] + grid... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def minPathSum1(self, grid):
"""不修改grid,用一个新的list保存每一行的结果 :param grid: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
m = len(grid)
n = ... | stack_v2_sparse_classes_36k_train_026117 | 1,332 | no_license | [
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "minPathSum",
"signature": "def minPathSum(self, grid)"
},
{
"docstring": "不修改grid,用一个新的list保存每一行的结果 :param grid: :return:",
"name": "minPathSum1",
"signature": "def minPathSum1(self, grid)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008718 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minPathSum(self, grid): :type grid: List[List[int]] :rtype: int
- def minPathSum1(self, grid): 不修改grid,用一个新的list保存每一行的结果 :param grid: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minPathSum(self, grid): :type grid: List[List[int]] :rtype: int
- def minPathSum1(self, grid): 不修改grid,用一个新的list保存每一行的结果 :param grid: :return:
<|skeleton|>
class Solution:
... | 11ad9d3841de09c0b4dc3a667e7e63c3558656a5 | <|skeleton|>
class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def minPathSum1(self, grid):
"""不修改grid,用一个新的list保存每一行的结果 :param grid: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
m = len(grid)
n = len(grid[0])
for i in range(1, n):
grid[0][i] += grid[0][i - 1]
for i in range(1, m):
grid[i][0] += grid[i - 1][0]
for i in range(1, m):... | the_stack_v2_python_sparse | minimum-path-sum.py | ganlanshu/leetcode | train | 0 | |
2cb9d8f7283ad29fff2a4732f8e29636e4e8ff2f | [
"num_cases, num_dim = X.shape\noutput_df = pd.DataFrame()\nfor dim in range(num_dim):\n dim_data = X.iloc[:, dim]\n out = self.row_wise_get_der(dim_data)\n output_df['der_dim_' + str(dim)] = pd.Series(out)\nreturn output_df",
"def get_der(x):\n der = []\n for i in range(1, len(x) - 1):\n der... | <|body_start_0|>
num_cases, num_dim = X.shape
output_df = pd.DataFrame()
for dim in range(num_dim):
dim_data = X.iloc[:, dim]
out = self.row_wise_get_der(dim_data)
output_df['der_dim_' + str(dim)] = pd.Series(out)
return output_df
<|end_body_0|>
<|bod... | Derivative slope transformer. | DerivativeSlopeTransformer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DerivativeSlopeTransformer:
"""Derivative slope transformer."""
def _transform(self, X, y=None):
"""Transform X."""
<|body_0|>
def row_wise_get_der(X):
"""Get derivatives."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
num_cases, num_dim = X.sh... | stack_v2_sparse_classes_36k_train_026118 | 16,453 | permissive | [
{
"docstring": "Transform X.",
"name": "_transform",
"signature": "def _transform(self, X, y=None)"
},
{
"docstring": "Get derivatives.",
"name": "row_wise_get_der",
"signature": "def row_wise_get_der(X)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002000 | Implement the Python class `DerivativeSlopeTransformer` described below.
Class description:
Derivative slope transformer.
Method signatures and docstrings:
- def _transform(self, X, y=None): Transform X.
- def row_wise_get_der(X): Get derivatives. | Implement the Python class `DerivativeSlopeTransformer` described below.
Class description:
Derivative slope transformer.
Method signatures and docstrings:
- def _transform(self, X, y=None): Transform X.
- def row_wise_get_der(X): Get derivatives.
<|skeleton|>
class DerivativeSlopeTransformer:
"""Derivative slop... | 70b2bfaaa597eb31bc3a1032366dcc0e1f4c8a9f | <|skeleton|>
class DerivativeSlopeTransformer:
"""Derivative slope transformer."""
def _transform(self, X, y=None):
"""Transform X."""
<|body_0|>
def row_wise_get_der(X):
"""Get derivatives."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DerivativeSlopeTransformer:
"""Derivative slope transformer."""
def _transform(self, X, y=None):
"""Transform X."""
num_cases, num_dim = X.shape
output_df = pd.DataFrame()
for dim in range(num_dim):
dim_data = X.iloc[:, dim]
out = self.row_wise_get_... | the_stack_v2_python_sparse | sktime/transformations/panel/summarize/_extract.py | sktime/sktime | train | 1,117 |
c1e0bf539cc4247efe1dcd41b12e6d60ce6416cb | [
"self.name = name\nself.number = number\nself.collectioin = show_collection",
"lst = []\nfor i in self.collectioin:\n if i.cast_contains(actor):\n lst.append(i)\nreturn lst"
] | <|body_start_0|>
self.name = name
self.number = number
self.collectioin = show_collection
<|end_body_0|>
<|body_start_1|>
lst = []
for i in self.collectioin:
if i.cast_contains(actor):
lst.append(i)
return lst
<|end_body_1|>
| Channel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Channel:
def __init__(self, name, number, show_collection):
"""Constructor -- creates an channel object Parameters: self -- the current piece object name -- channel name, String number == channel number, integer show_collection -- a list of shows that the channel has"""
<|body_0|... | stack_v2_sparse_classes_36k_train_026119 | 924 | no_license | [
{
"docstring": "Constructor -- creates an channel object Parameters: self -- the current piece object name -- channel name, String number == channel number, integer show_collection -- a list of shows that the channel has",
"name": "__init__",
"signature": "def __init__(self, name, number, show_collectio... | 2 | stack_v2_sparse_classes_30k_train_000311 | Implement the Python class `Channel` described below.
Class description:
Implement the Channel class.
Method signatures and docstrings:
- def __init__(self, name, number, show_collection): Constructor -- creates an channel object Parameters: self -- the current piece object name -- channel name, String number == chan... | Implement the Python class `Channel` described below.
Class description:
Implement the Channel class.
Method signatures and docstrings:
- def __init__(self, name, number, show_collection): Constructor -- creates an channel object Parameters: self -- the current piece object name -- channel name, String number == chan... | 79a13f3152c7e61d8d6cc10da2213a15c8a364e5 | <|skeleton|>
class Channel:
def __init__(self, name, number, show_collection):
"""Constructor -- creates an channel object Parameters: self -- the current piece object name -- channel name, String number == channel number, integer show_collection -- a list of shows that the channel has"""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Channel:
def __init__(self, name, number, show_collection):
"""Constructor -- creates an channel object Parameters: self -- the current piece object name -- channel name, String number == channel number, integer show_collection -- a list of shows that the channel has"""
self.name = name
... | the_stack_v2_python_sparse | Labs/Lab10/channel.py | Johnspeanut/Computer_science_fundation_course | train | 0 | |
892cbc07a1524f47caaf9eddeb1e1485bb79c915 | [
"data = form.cleaned_data\nself.success_url = reverse('level_result', kwargs={'level': int(data['level'])})\nreturn super().form_valid(form)",
"context = super().get_context_data(**kwargs)\ncontext['title_text'] = 'Choose Level Result To Display'\ncontext['detail_text'] = 'Please select the <strong>Level/Session\... | <|body_start_0|>
data = form.cleaned_data
self.success_url = reverse('level_result', kwargs={'level': int(data['level'])})
return super().form_valid(form)
<|end_body_0|>
<|body_start_1|>
context = super().get_context_data(**kwargs)
context['title_text'] = 'Choose Level Result To... | View for choosing which level/session result to display. Check that the user's account is still active. Redirects to level_result view on form valid. | ShowLevelResultView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShowLevelResultView:
"""View for choosing which level/session result to display. Check that the user's account is still active. Redirects to level_result view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_026120 | 29,759 | no_license | [
{
"docstring": "Compute the success URL and call super.form_valid()",
"name": "form_valid",
"signature": "def form_valid(self, form)"
},
{
"docstring": "Return the data used in the templates rendering.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
}
... | 2 | stack_v2_sparse_classes_30k_train_003303 | Implement the Python class `ShowLevelResultView` described below.
Class description:
View for choosing which level/session result to display. Check that the user's account is still active. Redirects to level_result view on form valid.
Method signatures and docstrings:
- def form_valid(self, form): Compute the success... | Implement the Python class `ShowLevelResultView` described below.
Class description:
View for choosing which level/session result to display. Check that the user's account is still active. Redirects to level_result view on form valid.
Method signatures and docstrings:
- def form_valid(self, form): Compute the success... | 06bc577d01d3dbf6c425e03dcb903977a38e377c | <|skeleton|>
class ShowLevelResultView:
"""View for choosing which level/session result to display. Check that the user's account is still active. Redirects to level_result view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShowLevelResultView:
"""View for choosing which level/session result to display. Check that the user's account is still active. Redirects to level_result view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
data = form.cleaned_data
... | the_stack_v2_python_sparse | cbt/views.py | Festusali/CBTest | train | 6 |
17b09a181aaca5ee5ae190d34d65806695eca136 | [
"self.root = path\nself.params = params\nself.ruby_version = ruby_version\nself.entrypoint = entrypoint\nself.packages = packages\nif params.deploy:\n self.notify = log.info\nelse:\n self.notify = log.status.Print",
"all_config_files = []\nif not self.params.appinfo:\n all_config_files.append(self._Gener... | <|body_start_0|>
self.root = path
self.params = params
self.ruby_version = ruby_version
self.entrypoint = entrypoint
self.packages = packages
if params.deploy:
self.notify = log.info
else:
self.notify = log.status.Print
<|end_body_0|>
<|bo... | Generates configuration for a Ruby app. | RubyConfigurator | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RubyConfigurator:
"""Generates configuration for a Ruby app."""
def __init__(self, path, params, ruby_version, entrypoint, packages):
"""Constructor. Args: path: (str) Root path of the source tree. params: (ext_runtime.Params) Parameters passed through to the fingerprinters. ruby_ver... | stack_v2_sparse_classes_36k_train_026121 | 18,608 | permissive | [
{
"docstring": "Constructor. Args: path: (str) Root path of the source tree. params: (ext_runtime.Params) Parameters passed through to the fingerprinters. ruby_version: (str) The ruby interpreter in rbenv format entrypoint: (str) The entrypoint command packages: ([str, ...]) A set of packages to install",
"... | 6 | null | Implement the Python class `RubyConfigurator` described below.
Class description:
Generates configuration for a Ruby app.
Method signatures and docstrings:
- def __init__(self, path, params, ruby_version, entrypoint, packages): Constructor. Args: path: (str) Root path of the source tree. params: (ext_runtime.Params) ... | Implement the Python class `RubyConfigurator` described below.
Class description:
Generates configuration for a Ruby app.
Method signatures and docstrings:
- def __init__(self, path, params, ruby_version, entrypoint, packages): Constructor. Args: path: (str) Root path of the source tree. params: (ext_runtime.Params) ... | c98b58aeb0994e011df960163541e9379ae7ea06 | <|skeleton|>
class RubyConfigurator:
"""Generates configuration for a Ruby app."""
def __init__(self, path, params, ruby_version, entrypoint, packages):
"""Constructor. Args: path: (str) Root path of the source tree. params: (ext_runtime.Params) Parameters passed through to the fingerprinters. ruby_ver... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RubyConfigurator:
"""Generates configuration for a Ruby app."""
def __init__(self, path, params, ruby_version, entrypoint, packages):
"""Constructor. Args: path: (str) Root path of the source tree. params: (ext_runtime.Params) Parameters passed through to the fingerprinters. ruby_version: (str) T... | the_stack_v2_python_sparse | google-cloud-sdk/.install/.backup/lib/googlecloudsdk/api_lib/app/runtimes/ruby.py | KaranToor/MA450 | train | 1 |
117667b9b4a865829ff4d17242d43b146b12c307 | [
"dxf = super().load_dxf_attribs(processor)\nif processor:\n processor.simple_dxfattribs_loader(dxf, acdb_entity_group_codes)\nreturn dxf",
"super().export_entity(tagwriter)\nif tagwriter.dxfversion > DXF12:\n tagwriter.write_tag2(SUBCLASS_MARKER, acdb_entity.name)\nif self.dxf.hasattr('paperspace'):\n ta... | <|body_start_0|>
dxf = super().load_dxf_attribs(processor)
if processor:
processor.simple_dxfattribs_loader(dxf, acdb_entity_group_codes)
return dxf
<|end_body_0|>
<|body_start_1|>
super().export_entity(tagwriter)
if tagwriter.dxfversion > DXF12:
tagwrite... | DXF ENDBLK entity | EndBlk | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EndBlk:
"""DXF ENDBLK entity"""
def load_dxf_attribs(self, processor: Optional[SubclassProcessor]=None) -> DXFNamespace:
"""Loading interface. (internal API)"""
<|body_0|>
def export_entity(self, tagwriter: AbstractTagWriter) -> None:
"""Export entity specific da... | stack_v2_sparse_classes_36k_train_026122 | 8,611 | permissive | [
{
"docstring": "Loading interface. (internal API)",
"name": "load_dxf_attribs",
"signature": "def load_dxf_attribs(self, processor: Optional[SubclassProcessor]=None) -> DXFNamespace"
},
{
"docstring": "Export entity specific data as DXF tags.",
"name": "export_entity",
"signature": "def ... | 2 | null | Implement the Python class `EndBlk` described below.
Class description:
DXF ENDBLK entity
Method signatures and docstrings:
- def load_dxf_attribs(self, processor: Optional[SubclassProcessor]=None) -> DXFNamespace: Loading interface. (internal API)
- def export_entity(self, tagwriter: AbstractTagWriter) -> None: Expo... | Implement the Python class `EndBlk` described below.
Class description:
DXF ENDBLK entity
Method signatures and docstrings:
- def load_dxf_attribs(self, processor: Optional[SubclassProcessor]=None) -> DXFNamespace: Loading interface. (internal API)
- def export_entity(self, tagwriter: AbstractTagWriter) -> None: Expo... | ba6ab0264dcb6833173042a37b1b5ae878d75113 | <|skeleton|>
class EndBlk:
"""DXF ENDBLK entity"""
def load_dxf_attribs(self, processor: Optional[SubclassProcessor]=None) -> DXFNamespace:
"""Loading interface. (internal API)"""
<|body_0|>
def export_entity(self, tagwriter: AbstractTagWriter) -> None:
"""Export entity specific da... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EndBlk:
"""DXF ENDBLK entity"""
def load_dxf_attribs(self, processor: Optional[SubclassProcessor]=None) -> DXFNamespace:
"""Loading interface. (internal API)"""
dxf = super().load_dxf_attribs(processor)
if processor:
processor.simple_dxfattribs_loader(dxf, acdb_entity_... | the_stack_v2_python_sparse | src/ezdxf/entities/block.py | mozman/ezdxf | train | 750 |
2d2cee9d7cc51dbc4f3941f4006cc7a7b57a3ad9 | [
"with Database() as db:\n data = db.get_all('SELECT * FROM tbl_building_contact WHERE id_building=%s;', (id_building,))\nreturn {'data': data}",
"with Database() as db:\n db.execute('INSERT INTO tbl_building_contact (\\n\\t\\t\\t\\t\\t\\t\\tid_building_contact, id_building, first_name, last_name, phone_numb... | <|body_start_0|>
with Database() as db:
data = db.get_all('SELECT * FROM tbl_building_contact WHERE id_building=%s;', (id_building,))
return {'data': data}
<|end_body_0|>
<|body_start_1|>
with Database() as db:
db.execute('INSERT INTO tbl_building_contact (\n\t\t\t\t\t\t... | BuildingContact | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BuildingContact:
def get(self, id_building):
"""Return all contact for one building :param id_building: UUID"""
<|body_0|>
def assign(self, body):
"""Assign new contact to building :param body: { id_building: UUID, first_name: STRING, last_name: STRING, phone_number:... | stack_v2_sparse_classes_36k_train_026123 | 2,702 | no_license | [
{
"docstring": "Return all contact for one building :param id_building: UUID",
"name": "get",
"signature": "def get(self, id_building)"
},
{
"docstring": "Assign new contact to building :param body: { id_building: UUID, first_name: STRING, last_name: STRING, phone_number: INTEGER, phone_extensio... | 4 | null | Implement the Python class `BuildingContact` described below.
Class description:
Implement the BuildingContact class.
Method signatures and docstrings:
- def get(self, id_building): Return all contact for one building :param id_building: UUID
- def assign(self, body): Assign new contact to building :param body: { id_... | Implement the Python class `BuildingContact` described below.
Class description:
Implement the BuildingContact class.
Method signatures and docstrings:
- def get(self, id_building): Return all contact for one building :param id_building: UUID
- def assign(self, body): Assign new contact to building :param body: { id_... | 43bd57c466a5cd3b133ddc437cb4a6b9f007d267 | <|skeleton|>
class BuildingContact:
def get(self, id_building):
"""Return all contact for one building :param id_building: UUID"""
<|body_0|>
def assign(self, body):
"""Assign new contact to building :param body: { id_building: UUID, first_name: STRING, last_name: STRING, phone_number:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BuildingContact:
def get(self, id_building):
"""Return all contact for one building :param id_building: UUID"""
with Database() as db:
data = db.get_all('SELECT * FROM tbl_building_contact WHERE id_building=%s;', (id_building,))
return {'data': data}
def assign(self, b... | the_stack_v2_python_sparse | resturls/buildingcontact.py | CAUCA-9-1-1/survip-api | train | 1 | |
846edef5d5b25f5bc49a12da17b9731c7a20e8c0 | [
"if x < 0:\n x = int(str(x)[::-1][-1] + str(x)[::-1][:-1])\nelse:\n x = int(str(x)[::-1])\nif abs(x) > 2147483647:\n return 0\nelse:\n return x",
"result = 0\npos_int = abs(x)\nwhile pos_int:\n result = result * 10 + pos_int % 10\n pos_int = pos_int // 10\nif result <= 2147483647:\n if x < 0:... | <|body_start_0|>
if x < 0:
x = int(str(x)[::-1][-1] + str(x)[::-1][:-1])
else:
x = int(str(x)[::-1])
if abs(x) > 2147483647:
return 0
else:
return x
<|end_body_0|>
<|body_start_1|>
result = 0
pos_int = abs(x)
while ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse1(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def reverse2(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if x < 0:
x = int(str(x)[::-1][-1] + str(x)[::-1][:-1])
... | stack_v2_sparse_classes_36k_train_026124 | 1,475 | no_license | [
{
"docstring": ":type x: int :rtype: int",
"name": "reverse1",
"signature": "def reverse1(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "reverse2",
"signature": "def reverse2(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015659 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse1(self, x): :type x: int :rtype: int
- def reverse2(self, x): :type x: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse1(self, x): :type x: int :rtype: int
- def reverse2(self, x): :type x: int :rtype: int
<|skeleton|>
class Solution:
def reverse1(self, x):
""":type x: in... | 96dd15210bcf9efe1f8cf31ce0566a7eabb3e221 | <|skeleton|>
class Solution:
def reverse1(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def reverse2(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverse1(self, x):
""":type x: int :rtype: int"""
if x < 0:
x = int(str(x)[::-1][-1] + str(x)[::-1][:-1])
else:
x = int(str(x)[::-1])
if abs(x) > 2147483647:
return 0
else:
return x
def reverse2(self, x)... | the_stack_v2_python_sparse | Python/ReverseInteger.py | abhi-verma/LeetCode-Algo | train | 0 | |
098ee1fdb9e6211c1e98e97e726b125f48b0bb1e | [
"if not head:\n return None\nif head.next and head.val == head.next.val:\n while head.next and head.val == head.next.val:\n head = head.next\n return self.deleteDuplicates_recursive(head.next)\nhead.next = self.deleteDuplicates_recursive(head.next)\nreturn head",
"if not head:\n return None\nfa... | <|body_start_0|>
if not head:
return None
if head.next and head.val == head.next.val:
while head.next and head.val == head.next.val:
head = head.next
return self.deleteDuplicates_recursive(head.next)
head.next = self.deleteDuplicates_recursive(... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deleteDuplicates_recursive(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def deleteDuplicates_iterative(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not ... | stack_v2_sparse_classes_36k_train_026125 | 1,802 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "deleteDuplicates_recursive",
"signature": "def deleteDuplicates_recursive(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "deleteDuplicates_iterative",
"signature": "def deleteDuplicates_iter... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteDuplicates_recursive(self, head): :type head: ListNode :rtype: ListNode
- def deleteDuplicates_iterative(self, head): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteDuplicates_recursive(self, head): :type head: ListNode :rtype: ListNode
- def deleteDuplicates_iterative(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|... | 9ac54720f571a4bea09d0cceb0039381a78df9e8 | <|skeleton|>
class Solution:
def deleteDuplicates_recursive(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def deleteDuplicates_iterative(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def deleteDuplicates_recursive(self, head):
""":type head: ListNode :rtype: ListNode"""
if not head:
return None
if head.next and head.val == head.next.val:
while head.next and head.val == head.next.val:
head = head.next
ret... | the_stack_v2_python_sparse | code/082_remove-duplicates-from-sorted-list-ii.py | linhdvu14/leetcode-solutions | train | 2 | |
9f90abb3bdcaf58118bf3455587e27a8fccc0069 | [
"super(EncoderImageFull, self).__init__()\nself.embed_size = embed_size\nself.no_imgnorm = no_imgnorm\nself.use_abs = use_abs\nmodel = get_model(name=cnn_type, num_classes=5607)\nmodel = torch.nn.DataParallel(model)\nmodel.to('cuda')\ncheckpoint = torch.load('/mnt/data2/betty/webvision_train/results/resnet50/5000cl... | <|body_start_0|>
super(EncoderImageFull, self).__init__()
self.embed_size = embed_size
self.no_imgnorm = no_imgnorm
self.use_abs = use_abs
model = get_model(name=cnn_type, num_classes=5607)
model = torch.nn.DataParallel(model)
model.to('cuda')
checkpoint =... | EncoderImageFull | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderImageFull:
def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False):
"""Load pretrained VGG19 and replace top fc layer."""
<|body_0|>
def load_state_dict(self, load_path):
"""Handle the models saved before commit... | stack_v2_sparse_classes_36k_train_026126 | 22,197 | no_license | [
{
"docstring": "Load pretrained VGG19 and replace top fc layer.",
"name": "__init__",
"signature": "def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False)"
},
{
"docstring": "Handle the models saved before commit pytorch/vision@989d52a",
"nam... | 4 | stack_v2_sparse_classes_30k_train_019190 | Implement the Python class `EncoderImageFull` described below.
Class description:
Implement the EncoderImageFull class.
Method signatures and docstrings:
- def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False): Load pretrained VGG19 and replace top fc layer.
- def lo... | Implement the Python class `EncoderImageFull` described below.
Class description:
Implement the EncoderImageFull class.
Method signatures and docstrings:
- def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False): Load pretrained VGG19 and replace top fc layer.
- def lo... | 4779d33a921be0c0adaf5971ec853317eb072af1 | <|skeleton|>
class EncoderImageFull:
def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False):
"""Load pretrained VGG19 and replace top fc layer."""
<|body_0|>
def load_state_dict(self, load_path):
"""Handle the models saved before commit... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncoderImageFull:
def __init__(self, embed_size=256, finetune=False, cnn_type='resnet50', use_abs=False, no_imgnorm=False):
"""Load pretrained VGG19 and replace top fc layer."""
super(EncoderImageFull, self).__init__()
self.embed_size = embed_size
self.no_imgnorm = no_imgnorm
... | the_stack_v2_python_sparse | cnn/encoder.py | bledem/webvision | train | 0 | |
7092c532c79feb18b6296cd3c9a95c8c33cbb0df | [
"if value is None:\n return default_value\nif not isinstance(value, int) and (not isinstance(value, float)):\n raise ValidationException(f'Parameter {name} must be a number')\nif value < 0:\n raise ValidationException(f'Parameter {name} cannot be lower than 0')\nreturn value",
"value = self.validate_numb... | <|body_start_0|>
if value is None:
return default_value
if not isinstance(value, int) and (not isinstance(value, float)):
raise ValidationException(f'Parameter {name} must be a number')
if value < 0:
raise ValidationException(f'Parameter {name} cannot be lower... | Class for validating API options. | OptionsValidator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptionsValidator:
"""Class for validating API options."""
def validate_number(self, value: int or float or None, default_value: int or float, name: str):
"""Validates a number parameter. Args: value: Value to validate. default_value: Default value for an option. name: Option name. Re... | stack_v2_sparse_classes_36k_train_026127 | 2,079 | no_license | [
{
"docstring": "Validates a number parameter. Args: value: Value to validate. default_value: Default value for an option. name: Option name. Returns: Validated value. Raises: ValidationException: If value is invalid.",
"name": "validate_number",
"signature": "def validate_number(self, value: int or floa... | 3 | null | Implement the Python class `OptionsValidator` described below.
Class description:
Class for validating API options.
Method signatures and docstrings:
- def validate_number(self, value: int or float or None, default_value: int or float, name: str): Validates a number parameter. Args: value: Value to validate. default_... | Implement the Python class `OptionsValidator` described below.
Class description:
Class for validating API options.
Method signatures and docstrings:
- def validate_number(self, value: int or float or None, default_value: int or float, name: str): Validates a number parameter. Args: value: Value to validate. default_... | b410e4c6bc4b11fc6ed85c91aca43e07fcd5fd2c | <|skeleton|>
class OptionsValidator:
"""Class for validating API options."""
def validate_number(self, value: int or float or None, default_value: int or float, name: str):
"""Validates a number parameter. Args: value: Value to validate. default_value: Default value for an option. name: Option name. Re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OptionsValidator:
"""Class for validating API options."""
def validate_number(self, value: int or float or None, default_value: int or float, name: str):
"""Validates a number parameter. Args: value: Value to validate. default_value: Default value for an option. name: Option name. Returns: Valida... | the_stack_v2_python_sparse | lib/clients/optionsValidator.py | alading241/metaapi-python-sdk | train | 0 |
b8a7284ede1736ed8b7dad09018242b411d9b883 | [
"integration_id = request.GET.get('integrationId')\nqueryset = RepositoryProjectPathConfig.objects.all()\nif integration_id:\n org_integration = self.get_organization_integration(organization, integration_id)\n queryset = queryset.filter(organization_integration=org_integration)\nelse:\n projects = self.ge... | <|body_start_0|>
integration_id = request.GET.get('integrationId')
queryset = RepositoryProjectPathConfig.objects.all()
if integration_id:
org_integration = self.get_organization_integration(organization, integration_id)
queryset = queryset.filter(organization_integration... | OrganizationCodeMappingsEndpoint | [
"Apache-2.0",
"BUSL-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrganizationCodeMappingsEndpoint:
def get(self, request: Request, organization) -> Response:
"""Get the list of repository project path configs :pparam string organization_slug: the slug of the organization the team should be created for. :qparam int integrationId: the optional integrati... | stack_v2_sparse_classes_36k_train_026128 | 7,699 | permissive | [
{
"docstring": "Get the list of repository project path configs :pparam string organization_slug: the slug of the organization the team should be created for. :qparam int integrationId: the optional integration id. :qparam int project: Optional. Pass \"-1\" to filter to 'all projects user has access to'. Omit t... | 2 | stack_v2_sparse_classes_30k_train_011211 | Implement the Python class `OrganizationCodeMappingsEndpoint` described below.
Class description:
Implement the OrganizationCodeMappingsEndpoint class.
Method signatures and docstrings:
- def get(self, request: Request, organization) -> Response: Get the list of repository project path configs :pparam string organiza... | Implement the Python class `OrganizationCodeMappingsEndpoint` described below.
Class description:
Implement the OrganizationCodeMappingsEndpoint class.
Method signatures and docstrings:
- def get(self, request: Request, organization) -> Response: Get the list of repository project path configs :pparam string organiza... | d9dd4f382f96b5c4576b64cbf015db651556c18b | <|skeleton|>
class OrganizationCodeMappingsEndpoint:
def get(self, request: Request, organization) -> Response:
"""Get the list of repository project path configs :pparam string organization_slug: the slug of the organization the team should be created for. :qparam int integrationId: the optional integrati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrganizationCodeMappingsEndpoint:
def get(self, request: Request, organization) -> Response:
"""Get the list of repository project path configs :pparam string organization_slug: the slug of the organization the team should be created for. :qparam int integrationId: the optional integration id. :qparam... | the_stack_v2_python_sparse | src/sentry/api/endpoints/organization_code_mappings.py | nagyist/sentry | train | 0 | |
58fcf1f3ede0f8d2ab808178f27b949d8fcd6d49 | [
"question = '你喜欢的女朋友有什么样的气质?'\nmy_survey = AnonymousSurvey(question)\nmy_survey.store_respond('温柔')\nassert '温柔', my_survey.responses",
"question = '你喜欢的女朋友有什么样的气质?'\nmy_survey = AnonymousSurvey(question)\nresponses = ['温柔', '聪明', '美丽']\nfor response in responses:\n my_survey.store_respond(response)\n asser... | <|body_start_0|>
question = '你喜欢的女朋友有什么样的气质?'
my_survey = AnonymousSurvey(question)
my_survey.store_respond('温柔')
assert '温柔', my_survey.responses
<|end_body_0|>
<|body_start_1|>
question = '你喜欢的女朋友有什么样的气质?'
my_survey = AnonymousSurvey(question)
responses = ['温柔'... | 针对AnonymousSurvey类的测试 | TestAnonymousSurvey | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAnonymousSurvey:
"""针对AnonymousSurvey类的测试"""
def test_single_response(self):
"""测试单个答案会被妥善的存储"""
<|body_0|>
def test_store_three_response(self):
"""测试三个答案会被被妥善地存储"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
question = '你喜欢的女朋友有什么样的气质?'
... | stack_v2_sparse_classes_36k_train_026129 | 911 | no_license | [
{
"docstring": "测试单个答案会被妥善的存储",
"name": "test_single_response",
"signature": "def test_single_response(self)"
},
{
"docstring": "测试三个答案会被被妥善地存储",
"name": "test_store_three_response",
"signature": "def test_store_three_response(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002105 | Implement the Python class `TestAnonymousSurvey` described below.
Class description:
针对AnonymousSurvey类的测试
Method signatures and docstrings:
- def test_single_response(self): 测试单个答案会被妥善的存储
- def test_store_three_response(self): 测试三个答案会被被妥善地存储 | Implement the Python class `TestAnonymousSurvey` described below.
Class description:
针对AnonymousSurvey类的测试
Method signatures and docstrings:
- def test_single_response(self): 测试单个答案会被妥善的存储
- def test_store_three_response(self): 测试三个答案会被被妥善地存储
<|skeleton|>
class TestAnonymousSurvey:
"""针对AnonymousSurvey类的测试"""
... | 8fb4224c6b7464086e874a654ca5e8e6a6b26029 | <|skeleton|>
class TestAnonymousSurvey:
"""针对AnonymousSurvey类的测试"""
def test_single_response(self):
"""测试单个答案会被妥善的存储"""
<|body_0|>
def test_store_three_response(self):
"""测试三个答案会被被妥善地存储"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAnonymousSurvey:
"""针对AnonymousSurvey类的测试"""
def test_single_response(self):
"""测试单个答案会被妥善的存储"""
question = '你喜欢的女朋友有什么样的气质?'
my_survey = AnonymousSurvey(question)
my_survey.store_respond('温柔')
assert '温柔', my_survey.responses
def test_store_three_response... | the_stack_v2_python_sparse | src/chapter7unit/class_examples/test_survey.py | lindafanglizhi/pytest_book1 | train | 0 |
b4f09c87f6d20b9e70d512b5bac383b9cd070388 | [
"even_arr, odd_arr = ([], [])\nfor i in A:\n if i % 2 == 0:\n even_arr.append(i)\n else:\n odd_arr.append(i)\nreturn even_arr + odd_arr",
"l, r = (0, len(A) - 1)\nwhile r >= l:\n if A[l] % 2 == 0:\n l += 1\n else:\n A[l], A[r] = (A[r], A[l])\n r -= 1\nreturn A"
] | <|body_start_0|>
even_arr, odd_arr = ([], [])
for i in A:
if i % 2 == 0:
even_arr.append(i)
else:
odd_arr.append(i)
return even_arr + odd_arr
<|end_body_0|>
<|body_start_1|>
l, r = (0, len(A) - 1)
while r >= l:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortArrayByParity_sol1(self, A):
""":type: A: List[int] :rtype: List[int]"""
<|body_0|>
def sortArrayByParity_sol2(self, A):
""":type: A: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
even_arr, odd_arr = (... | stack_v2_sparse_classes_36k_train_026130 | 665 | no_license | [
{
"docstring": ":type: A: List[int] :rtype: List[int]",
"name": "sortArrayByParity_sol1",
"signature": "def sortArrayByParity_sol1(self, A)"
},
{
"docstring": ":type: A: List[int] :rtype: List[int]",
"name": "sortArrayByParity_sol2",
"signature": "def sortArrayByParity_sol2(self, A)"
}... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortArrayByParity_sol1(self, A): :type: A: List[int] :rtype: List[int]
- def sortArrayByParity_sol2(self, A): :type: A: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortArrayByParity_sol1(self, A): :type: A: List[int] :rtype: List[int]
- def sortArrayByParity_sol2(self, A): :type: A: List[int] :rtype: List[int]
<|skeleton|>
class Soluti... | 885a9af8a7bee3c228c7ae4e295dca810bd91d01 | <|skeleton|>
class Solution:
def sortArrayByParity_sol1(self, A):
""":type: A: List[int] :rtype: List[int]"""
<|body_0|>
def sortArrayByParity_sol2(self, A):
""":type: A: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortArrayByParity_sol1(self, A):
""":type: A: List[int] :rtype: List[int]"""
even_arr, odd_arr = ([], [])
for i in A:
if i % 2 == 0:
even_arr.append(i)
else:
odd_arr.append(i)
return even_arr + odd_arr
d... | the_stack_v2_python_sparse | Python/905.py | kevin851066/Leetcode | train | 0 | |
bb007a35f89b932c40a56e404cd5e508a968c0b3 | [
"current = head\nnthPrev = None\nnodeToDelete = None\nstep = 1\nwhile current.next:\n current = current.next\n if step + 1 == n:\n nodeToDelete = head\n elif nodeToDelete:\n nodeToDelete = nodeToDelete.next\n if step == n:\n nthPrev = head\n elif nthPrev:\n nthPrev = nthPr... | <|body_start_0|>
current = head
nthPrev = None
nodeToDelete = None
step = 1
while current.next:
current = current.next
if step + 1 == n:
nodeToDelete = head
elif nodeToDelete:
nodeToDelete = nodeToDelete.next
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_0|>
def removeNthFromEndTmp(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_026131 | 2,713 | no_license | [
{
"docstring": ":type head: ListNode :type n: int :rtype: ListNode",
"name": "removeNthFromEnd",
"signature": "def removeNthFromEnd(self, head, n)"
},
{
"docstring": ":type head: ListNode :type n: int :rtype: ListNode",
"name": "removeNthFromEndTmp",
"signature": "def removeNthFromEndTmp... | 2 | stack_v2_sparse_classes_30k_train_004085 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeNthFromEnd(self, head, n): :type head: ListNode :type n: int :rtype: ListNode
- def removeNthFromEndTmp(self, head, n): :type head: ListNode :type n: int :rtype: ListNo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeNthFromEnd(self, head, n): :type head: ListNode :type n: int :rtype: ListNode
- def removeNthFromEndTmp(self, head, n): :type head: ListNode :type n: int :rtype: ListNo... | 507d4982eb4fc1d3afa5dfdc0e7b6830ff8594ad | <|skeleton|>
class Solution:
def removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_0|>
def removeNthFromEndTmp(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
current = head
nthPrev = None
nodeToDelete = None
step = 1
while current.next:
current = current.next
if step + 1 == n:
... | the_stack_v2_python_sparse | remove-nth-node-from-end-of-list.py | igor-nov/algorithms | train | 0 | |
1fdd31a738eb85ea71093a3f65f9185e7b1e9691 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn BrowserSite()",
"from .browser_site_compatibility_mode import BrowserSiteCompatibilityMode\nfrom .browser_site_history import BrowserSiteHistory\nfrom .browser_site_merge_type import BrowserSiteMergeType\nfrom .browser_site_status impo... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return BrowserSite()
<|end_body_0|>
<|body_start_1|>
from .browser_site_compatibility_mode import BrowserSiteCompatibilityMode
from .browser_site_history import BrowserSiteHistory
from ... | Singleton entity which is used to specify IE mode site metadata | BrowserSite | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrowserSite:
"""Singleton entity which is used to specify IE mode site metadata"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BrowserSite:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse nod... | stack_v2_sparse_classes_36k_train_026132 | 6,396 | 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: BrowserSite",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(p... | 3 | null | Implement the Python class `BrowserSite` described below.
Class description:
Singleton entity which is used to specify IE mode site metadata
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BrowserSite: Creates a new instance of the appropriate class bas... | Implement the Python class `BrowserSite` described below.
Class description:
Singleton entity which is used to specify IE mode site metadata
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BrowserSite: Creates a new instance of the appropriate class bas... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class BrowserSite:
"""Singleton entity which is used to specify IE mode site metadata"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BrowserSite:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse nod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BrowserSite:
"""Singleton entity which is used to specify IE mode site metadata"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BrowserSite:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to r... | the_stack_v2_python_sparse | msgraph/generated/models/browser_site.py | microsoftgraph/msgraph-sdk-python | train | 135 |
20918df95b835cb3e568f3dbfaeb26dbc538c9c2 | [
"try:\n _lat = Decimal(lat.strip())\n _lng = Decimal(lng.strip())\n if (_lat > 90 or _lat < -90) or (_lng > 180 or _lng < -180):\n return None\n else:\n return Location(_lat, _lng)\nexcept ValueError:\n return None",
"p1 = (location1.Latitude, location1.Longitude)\np2 = (location2.Lat... | <|body_start_0|>
try:
_lat = Decimal(lat.strip())
_lng = Decimal(lng.strip())
if (_lat > 90 or _lat < -90) or (_lng > 180 or _lng < -180):
return None
else:
return Location(_lat, _lng)
except ValueError:
return N... | A helper class which provides helper methods for location based operations | CoordinateHelper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoordinateHelper:
"""A helper class which provides helper methods for location based operations"""
def CastString2Coordinates(lat, lng):
"""Returns a Location object from given string parameters."""
<|body_0|>
def GetDistanceMeters(location1, location2):
"""Calcu... | stack_v2_sparse_classes_36k_train_026133 | 1,303 | no_license | [
{
"docstring": "Returns a Location object from given string parameters.",
"name": "CastString2Coordinates",
"signature": "def CastString2Coordinates(lat, lng)"
},
{
"docstring": "Calculates the distance between points represented by two Location objects",
"name": "GetDistanceMeters",
"si... | 3 | stack_v2_sparse_classes_30k_train_002808 | Implement the Python class `CoordinateHelper` described below.
Class description:
A helper class which provides helper methods for location based operations
Method signatures and docstrings:
- def CastString2Coordinates(lat, lng): Returns a Location object from given string parameters.
- def GetDistanceMeters(locatio... | Implement the Python class `CoordinateHelper` described below.
Class description:
A helper class which provides helper methods for location based operations
Method signatures and docstrings:
- def CastString2Coordinates(lat, lng): Returns a Location object from given string parameters.
- def GetDistanceMeters(locatio... | 63a1f25876c5d72e515099beb9379ac92a59168c | <|skeleton|>
class CoordinateHelper:
"""A helper class which provides helper methods for location based operations"""
def CastString2Coordinates(lat, lng):
"""Returns a Location object from given string parameters."""
<|body_0|>
def GetDistanceMeters(location1, location2):
"""Calcu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoordinateHelper:
"""A helper class which provides helper methods for location based operations"""
def CastString2Coordinates(lat, lng):
"""Returns a Location object from given string parameters."""
try:
_lat = Decimal(lat.strip())
_lng = Decimal(lng.strip())
... | the_stack_v2_python_sparse | server/coordinateHelper.py | flaskmc/challenge | train | 0 |
953d30b4e14a697e78887ebe837ff05bdda87a1d | [
"if xml is None:\n self.defaultInit()\nelse:\n self.fromXml(xml)",
"self.GPU = Size(XYstr='256x256')\nself.CPU = Size(XYstr='32x32')\nself.BI = Size(XYstr='256x256')",
"self.GPU = Size(xml=xml.find('GPU'))\nself.CPU = Size(xml=xml.find('CPU'))\nself.BI = Size(xml=xml.find('BI'))",
"txt = '<tilesSet>\\n'... | <|body_start_0|>
if xml is None:
self.defaultInit()
else:
self.fromXml(xml)
<|end_body_0|>
<|body_start_1|>
self.GPU = Size(XYstr='256x256')
self.CPU = Size(XYstr='32x32')
self.BI = Size(XYstr='256x256')
<|end_body_1|>
<|body_start_2|>
self.GPU =... | class to manage tiles sizes | Tiles | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tiles:
"""class to manage tiles sizes"""
def __init__(self, xml=None):
"""initialize tiles sizes with default value or values extracted from an xml object"""
<|body_0|>
def defaultInit(self):
"""initialize tiles sizes with default value"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_026134 | 2,352 | permissive | [
{
"docstring": "initialize tiles sizes with default value or values extracted from an xml object",
"name": "__init__",
"signature": "def __init__(self, xml=None)"
},
{
"docstring": "initialize tiles sizes with default value",
"name": "defaultInit",
"signature": "def defaultInit(self)"
... | 6 | stack_v2_sparse_classes_30k_train_009605 | Implement the Python class `Tiles` described below.
Class description:
class to manage tiles sizes
Method signatures and docstrings:
- def __init__(self, xml=None): initialize tiles sizes with default value or values extracted from an xml object
- def defaultInit(self): initialize tiles sizes with default value
- def... | Implement the Python class `Tiles` described below.
Class description:
class to manage tiles sizes
Method signatures and docstrings:
- def __init__(self, xml=None): initialize tiles sizes with default value or values extracted from an xml object
- def defaultInit(self): initialize tiles sizes with default value
- def... | 39082e7833383bbe7dd414381f1b295e3b778439 | <|skeleton|>
class Tiles:
"""class to manage tiles sizes"""
def __init__(self, xml=None):
"""initialize tiles sizes with default value or values extracted from an xml object"""
<|body_0|>
def defaultInit(self):
"""initialize tiles sizes with default value"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tiles:
"""class to manage tiles sizes"""
def __init__(self, xml=None):
"""initialize tiles sizes with default value or values extracted from an xml object"""
if xml is None:
self.defaultInit()
else:
self.fromXml(xml)
def defaultInit(self):
"""i... | the_stack_v2_python_sparse | Preferences/Tiles.py | chankeh/Blender-Render-Manager | train | 0 |
a1d20d62b14e63c0ebe0a7fe8e17f38e4a4834d6 | [
"self.stages = stages\nself.steps = np.cumsum([stage.steps for stage in self.stages])\nself.total_steps = self.steps[-1]\nself.stage_idx = -1\nself.min_steps = 0\nself.max_steps = 0\nself.stage = None",
"epoch = max(min(epoch, self.total_steps), 0)\nwhile epoch >= self.max_steps and self.max_steps < self.total_st... | <|body_start_0|>
self.stages = stages
self.steps = np.cumsum([stage.steps for stage in self.stages])
self.total_steps = self.steps[-1]
self.stage_idx = -1
self.min_steps = 0
self.max_steps = 0
self.stage = None
<|end_body_0|>
<|body_start_1|>
epoch = max(... | Container for multiple stages of LinearDecay. Obtain the value corresponding to the `i`-th step by calling an instance of this class with the value `i`. # Parameters stages: List of `LinearDecay` objects to be sequentially applied for the number of steps in each stage. | MultiLinearDecay | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiLinearDecay:
"""Container for multiple stages of LinearDecay. Obtain the value corresponding to the `i`-th step by calling an instance of this class with the value `i`. # Parameters stages: List of `LinearDecay` objects to be sequentially applied for the number of steps in each stage."""
... | stack_v2_sparse_classes_36k_train_026135 | 44,726 | permissive | [
{
"docstring": "Initializer. See class documentation for parameter definitions.",
"name": "__init__",
"signature": "def __init__(self, stages: Sequence[LinearDecay]) -> None"
},
{
"docstring": "Get the decayed value factor for `epoch` number of steps. # Parameters epoch : The number of steps. # ... | 2 | null | Implement the Python class `MultiLinearDecay` described below.
Class description:
Container for multiple stages of LinearDecay. Obtain the value corresponding to the `i`-th step by calling an instance of this class with the value `i`. # Parameters stages: List of `LinearDecay` objects to be sequentially applied for th... | Implement the Python class `MultiLinearDecay` described below.
Class description:
Container for multiple stages of LinearDecay. Obtain the value corresponding to the `i`-th step by calling an instance of this class with the value `i`. # Parameters stages: List of `LinearDecay` objects to be sequentially applied for th... | 9772eeeb7eacc1f9a83c90d1cf549a3f7e783c12 | <|skeleton|>
class MultiLinearDecay:
"""Container for multiple stages of LinearDecay. Obtain the value corresponding to the `i`-th step by calling an instance of this class with the value `i`. # Parameters stages: List of `LinearDecay` objects to be sequentially applied for the number of steps in each stage."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiLinearDecay:
"""Container for multiple stages of LinearDecay. Obtain the value corresponding to the `i`-th step by calling an instance of this class with the value `i`. # Parameters stages: List of `LinearDecay` objects to be sequentially applied for the number of steps in each stage."""
def __init_... | the_stack_v2_python_sparse | allenact/utils/experiment_utils.py | allenai/allenact | train | 266 |
4811413eb13e50bcabf208dbdfd24fc974a9f124 | [
"self.defect_type = defect_type\nself.atom = atom\nself.chem_pot_input = chem_pot\nif defect_type == 'Vacancy':\n atomic_species = atom[0].split()[0]\n self.name = 'V_{' + atomic_species + '}'\n self.ID = 'Vac_' + atom[0].replace(' ', '')\n self.n = +1\n self.chem_pot = chem_pot[0]\n self.populati... | <|body_start_0|>
self.defect_type = defect_type
self.atom = atom
self.chem_pot_input = chem_pot
if defect_type == 'Vacancy':
atomic_species = atom[0].split()[0]
self.name = 'V_{' + atomic_species + '}'
self.ID = 'Vac_' + atom[0].replace(' ', '')
... | Object containing various data on a defect | Defect | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Defect:
"""Object containing various data on a defect"""
def __init__(self, defect_type, atom, chem_pot):
""":param defect_type: Type of defect ('Vacancy', 'Interstitial' or 'Substitutional') :param atom: list of atom(s) affected by the defect with the following pattern for each "ato... | stack_v2_sparse_classes_36k_train_026136 | 3,637 | no_license | [
{
"docstring": ":param defect_type: Type of defect ('Vacancy', 'Interstitial' or 'Substitutional') :param atom: list of atom(s) affected by the defect with the following pattern for each \"atomic_species + space + ( + atom_number + )\". The atom number depends on the defect_type: Vacancy : with respect to all a... | 2 | stack_v2_sparse_classes_30k_train_005443 | Implement the Python class `Defect` described below.
Class description:
Object containing various data on a defect
Method signatures and docstrings:
- def __init__(self, defect_type, atom, chem_pot): :param defect_type: Type of defect ('Vacancy', 'Interstitial' or 'Substitutional') :param atom: list of atom(s) affect... | Implement the Python class `Defect` described below.
Class description:
Object containing various data on a defect
Method signatures and docstrings:
- def __init__(self, defect_type, atom, chem_pot): :param defect_type: Type of defect ('Vacancy', 'Interstitial' or 'Substitutional') :param atom: list of atom(s) affect... | 1881be4f7a54defd307c62c3a3c634255181a6cb | <|skeleton|>
class Defect:
"""Object containing various data on a defect"""
def __init__(self, defect_type, atom, chem_pot):
""":param defect_type: Type of defect ('Vacancy', 'Interstitial' or 'Substitutional') :param atom: list of atom(s) affected by the defect with the following pattern for each "ato... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Defect:
"""Object containing various data on a defect"""
def __init__(self, defect_type, atom, chem_pot):
""":param defect_type: Type of defect ('Vacancy', 'Interstitial' or 'Substitutional') :param atom: list of atom(s) affected by the defect with the following pattern for each "atomic_species +... | the_stack_v2_python_sparse | Previous versions/PyDEF 1.0.0/PyDEF 1.0.0 source code/pydef_core/defect.py | zhenming-xu/PyDEF | train | 0 |
740b465b6ac9e75c9d5812b173476c924de4255e | [
"self.pa1_is_control = pa1_is_control\nself.flipped_by_0 = flipped_by_0\nassert pa1.size == 2 & pa2.size == 2, \"The parent nodes of the CNot don't both have size 2\"\nassert pa1.state_names == ['0', '1'], 'parent1 states not 0,1'\nassert pa2.state_names == ['0', '1'], 'parent2 states not 0,1'\nBayesNode.__init__(s... | <|body_start_0|>
self.pa1_is_control = pa1_is_control
self.flipped_by_0 = flipped_by_0
assert pa1.size == 2 & pa2.size == 2, "The parent nodes of the CNot don't both have size 2"
assert pa1.state_names == ['0', '1'], 'parent1 states not 0,1'
assert pa2.state_names == ['0', '1'], ... | The Constructor of this class builds a BayesNode that has a transition matrix appropriate for a CNot (Controlled Not) The following is expected: * the focus node has exactly two parent nodes, * the parent nodes each has 2 states named, 0 and 1, in that order. Suppose M1, M2, N1, N2 are elements of {0,1}. Say M1 is the ... | CNot | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CNot:
"""The Constructor of this class builds a BayesNode that has a transition matrix appropriate for a CNot (Controlled Not) The following is expected: * the focus node has exactly two parent nodes, * the parent nodes each has 2 states named, 0 and 1, in that order. Suppose M1, M2, N1, N2 are e... | stack_v2_sparse_classes_36k_train_026137 | 4,466 | permissive | [
{
"docstring": "Constructor Parameters ---------- id_num : int id number of self (focus node) name : str name of self (focus node) is_quantum : bool pa1 : BayesNode parent 1 pa2 : BayesNode parent 2 pa1_is_control : bool True (False) when parent 1 (parent 2) is control flipped_by_0 : bool True (False) when targ... | 2 | null | Implement the Python class `CNot` described below.
Class description:
The Constructor of this class builds a BayesNode that has a transition matrix appropriate for a CNot (Controlled Not) The following is expected: * the focus node has exactly two parent nodes, * the parent nodes each has 2 states named, 0 and 1, in t... | Implement the Python class `CNot` described below.
Class description:
The Constructor of this class builds a BayesNode that has a transition matrix appropriate for a CNot (Controlled Not) The following is expected: * the focus node has exactly two parent nodes, * the parent nodes each has 2 states named, 0 and 1, in t... | 5b4a3055ea14c2ee9c80c339f759fe2b9c8c51e2 | <|skeleton|>
class CNot:
"""The Constructor of this class builds a BayesNode that has a transition matrix appropriate for a CNot (Controlled Not) The following is expected: * the focus node has exactly two parent nodes, * the parent nodes each has 2 states named, 0 and 1, in that order. Suppose M1, M2, N1, N2 are e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CNot:
"""The Constructor of this class builds a BayesNode that has a transition matrix appropriate for a CNot (Controlled Not) The following is expected: * the focus node has exactly two parent nodes, * the parent nodes each has 2 states named, 0 and 1, in that order. Suppose M1, M2, N1, N2 are elements of {0... | the_stack_v2_python_sparse | prefabricated_nodes/CNot.py | artiste-qb-net/quantum-fog | train | 95 |
2a8b743b2f6bf620fe1080888a54ee19fbab46ec | [
"super().__init__(('', port), handler)\nself.delete_kv_lock = threading.Lock()\nself.delete_kv = {}\nself.kv_lock = threading.Lock()\nself.kv = {}",
"ret = 0\nwith self.delete_kv_lock:\n ret = len(self.delete_kv.get(key, set()))\nreturn ret"
] | <|body_start_0|>
super().__init__(('', port), handler)
self.delete_kv_lock = threading.Lock()
self.delete_kv = {}
self.kv_lock = threading.Lock()
self.kv = {}
<|end_body_0|>
<|body_start_1|>
ret = 0
with self.delete_kv_lock:
ret = len(self.delete_kv.g... | it is a http server storing kv pairs. | KVHTTPServer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KVHTTPServer:
"""it is a http server storing kv pairs."""
def __init__(self, port, handler):
"""Init."""
<|body_0|>
def get_deleted_size(self, key):
"""get deleted size in key."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__((''... | stack_v2_sparse_classes_36k_train_026138 | 5,744 | permissive | [
{
"docstring": "Init.",
"name": "__init__",
"signature": "def __init__(self, port, handler)"
},
{
"docstring": "get deleted size in key.",
"name": "get_deleted_size",
"signature": "def get_deleted_size(self, key)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003578 | Implement the Python class `KVHTTPServer` described below.
Class description:
it is a http server storing kv pairs.
Method signatures and docstrings:
- def __init__(self, port, handler): Init.
- def get_deleted_size(self, key): get deleted size in key. | Implement the Python class `KVHTTPServer` described below.
Class description:
it is a http server storing kv pairs.
Method signatures and docstrings:
- def __init__(self, port, handler): Init.
- def get_deleted_size(self, key): get deleted size in key.
<|skeleton|>
class KVHTTPServer:
"""it is a http server stor... | 22a11a60e0e3d10a3cf610077a3d9942a6f964cb | <|skeleton|>
class KVHTTPServer:
"""it is a http server storing kv pairs."""
def __init__(self, port, handler):
"""Init."""
<|body_0|>
def get_deleted_size(self, key):
"""get deleted size in key."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KVHTTPServer:
"""it is a http server storing kv pairs."""
def __init__(self, port, handler):
"""Init."""
super().__init__(('', port), handler)
self.delete_kv_lock = threading.Lock()
self.delete_kv = {}
self.kv_lock = threading.Lock()
self.kv = {}
def g... | the_stack_v2_python_sparse | python/paddle/distributed/fleet/utils/http_server.py | PaddlePaddle/Paddle | train | 20,414 |
15efae4a45a5d99e3ec4902eb9a4988a80fd1b46 | [
"if not isinstance(input_shape, Iterable):\n input_shape = (input_shape,)\nself.input_shape = input_shape\nself.steps = steps\nself.history = np.zeros((steps,) + input_shape)",
"if isinstance(x, jnp.ndarray):\n self.history = jnp.roll(self.history, shift=1, axis=0)\n self.history = self.history.at[0].set... | <|body_start_0|>
if not isinstance(input_shape, Iterable):
input_shape = (input_shape,)
self.input_shape = input_shape
self.steps = steps
self.history = np.zeros((steps,) + input_shape)
<|end_body_0|>
<|body_start_1|>
if isinstance(x, jnp.ndarray):
self.h... | Predict last value | PredictLast | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PredictLast:
"""Predict last value"""
def __init__(self, input_shape=1, steps=1):
"""init"""
<|body_0|>
def __call__(self, x):
"""call"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not isinstance(input_shape, Iterable):
input_sh... | stack_v2_sparse_classes_36k_train_026139 | 1,431 | permissive | [
{
"docstring": "init",
"name": "__init__",
"signature": "def __init__(self, input_shape=1, steps=1)"
},
{
"docstring": "call",
"name": "__call__",
"signature": "def __call__(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020461 | Implement the Python class `PredictLast` described below.
Class description:
Predict last value
Method signatures and docstrings:
- def __init__(self, input_shape=1, steps=1): init
- def __call__(self, x): call | Implement the Python class `PredictLast` described below.
Class description:
Predict last value
Method signatures and docstrings:
- def __init__(self, input_shape=1, steps=1): init
- def __call__(self, x): call
<|skeleton|>
class PredictLast:
"""Predict last value"""
def __init__(self, input_shape=1, steps=... | 5be08e2fa4ef8cad9a3c1d4134c13acf4c68637f | <|skeleton|>
class PredictLast:
"""Predict last value"""
def __init__(self, input_shape=1, steps=1):
"""init"""
<|body_0|>
def __call__(self, x):
"""call"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PredictLast:
"""Predict last value"""
def __init__(self, input_shape=1, steps=1):
"""init"""
if not isinstance(input_shape, Iterable):
input_shape = (input_shape,)
self.input_shape = input_shape
self.steps = steps
self.history = np.zeros((steps,) + inpu... | the_stack_v2_python_sparse | timecast/modules/_predict_last.py | NeoTim/timecast | train | 0 |
43bbf56f80407f5494ca83052d1386aaf2432760 | [
"acl.enforce('dynamic_actions:create', context.ctx())\nLOG.debug('Creating dynamic action [action=%s]', dyn_action)\nif not dyn_action.code_source_id and (not dyn_action.code_source_name):\n raise exc.InputException(\"Either 'code_source_id' or 'code_source_name' must be provided.\")\ncode_source = db_api.get_co... | <|body_start_0|>
acl.enforce('dynamic_actions:create', context.ctx())
LOG.debug('Creating dynamic action [action=%s]', dyn_action)
if not dyn_action.code_source_id and (not dyn_action.code_source_name):
raise exc.InputException("Either 'code_source_id' or 'code_source_name' must be p... | DynamicActionsController | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DynamicActionsController:
def post(self, dyn_action):
"""Creates new dynamic action. :param dyn_action: Dynamic action to create."""
<|body_0|>
def put(self, dyn_action):
"""Update dynamic action. :param dyn_action: Dynamic action to create."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_026140 | 9,796 | permissive | [
{
"docstring": "Creates new dynamic action. :param dyn_action: Dynamic action to create.",
"name": "post",
"signature": "def post(self, dyn_action)"
},
{
"docstring": "Update dynamic action. :param dyn_action: Dynamic action to create.",
"name": "put",
"signature": "def put(self, dyn_act... | 5 | stack_v2_sparse_classes_30k_train_020540 | Implement the Python class `DynamicActionsController` described below.
Class description:
Implement the DynamicActionsController class.
Method signatures and docstrings:
- def post(self, dyn_action): Creates new dynamic action. :param dyn_action: Dynamic action to create.
- def put(self, dyn_action): Update dynamic a... | Implement the Python class `DynamicActionsController` described below.
Class description:
Implement the DynamicActionsController class.
Method signatures and docstrings:
- def post(self, dyn_action): Creates new dynamic action. :param dyn_action: Dynamic action to create.
- def put(self, dyn_action): Update dynamic a... | 7baff017d0cf01d19c44055ad201ca59131b9f94 | <|skeleton|>
class DynamicActionsController:
def post(self, dyn_action):
"""Creates new dynamic action. :param dyn_action: Dynamic action to create."""
<|body_0|>
def put(self, dyn_action):
"""Update dynamic action. :param dyn_action: Dynamic action to create."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DynamicActionsController:
def post(self, dyn_action):
"""Creates new dynamic action. :param dyn_action: Dynamic action to create."""
acl.enforce('dynamic_actions:create', context.ctx())
LOG.debug('Creating dynamic action [action=%s]', dyn_action)
if not dyn_action.code_source_i... | the_stack_v2_python_sparse | mistral/api/controllers/v2/dynamic_action.py | openstack/mistral | train | 214 | |
d61c2fd6ee9ffae01da70f7e27dcf212cbe8b779 | [
"self.list = vec2d\nself.cur = 0\nself.iter = iter(vec2d[0]) if len(vec2d) else iter(vec2d)",
"while True:\n try:\n return next(self.iter)\n except StopIteration as e:\n self.cur += 1\n if self.cur >= len(self.list):\n raise StopIteration()\n self.iter = iter(self.list... | <|body_start_0|>
self.list = vec2d
self.cur = 0
self.iter = iter(vec2d[0]) if len(vec2d) else iter(vec2d)
<|end_body_0|>
<|body_start_1|>
while True:
try:
return next(self.iter)
except StopIteration as e:
self.cur += 1
... | Vector2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_026141 | 1,089 | no_license | [
{
"docstring": "Initialize your data structure here. :type vec2d: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, vec2d)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",... | 3 | stack_v2_sparse_classes_30k_train_014441 | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool
<|skeleton|>
class V... | 8a6954928acb0961ec3b65d7b7882305c0e617cf | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
self.list = vec2d
self.cur = 0
self.iter = iter(vec2d[0]) if len(vec2d) else iter(vec2d)
def next(self):
""":rtype: int"""
while True:
t... | the_stack_v2_python_sparse | flatten_2d_vector/flatten.py | yinxx/leetcode | train | 0 | |
873570f47c53dd46e7146554863e49d89deee314 | [
"super().__init__()\nself.checkpoint_file = checkpoint_dir / 'checkpoint.tf_model'\nself.best_metrics_so_far: Dict[Text, Any] = {}",
"if self._does_model_improve(logs):\n logger.debug(f'Creating model checkpoint at epoch={epoch + 1} ...')\n self.model.save_weights(self.checkpoint_file, overwrite=True, save_... | <|body_start_0|>
super().__init__()
self.checkpoint_file = checkpoint_dir / 'checkpoint.tf_model'
self.best_metrics_so_far: Dict[Text, Any] = {}
<|end_body_0|>
<|body_start_1|>
if self._does_model_improve(logs):
logger.debug(f'Creating model checkpoint at epoch={epoch + 1} .... | Callback for saving intermediate model checkpoints. | RasaModelCheckpoint | [
"LicenseRef-scancode-generic-cla",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RasaModelCheckpoint:
"""Callback for saving intermediate model checkpoints."""
def __init__(self, checkpoint_dir: Path) -> None:
"""Initializes the callback. Args: checkpoint_dir: Directory to store checkpoints to."""
<|body_0|>
def on_epoch_end(self, epoch: int, logs: O... | stack_v2_sparse_classes_36k_train_026142 | 4,036 | permissive | [
{
"docstring": "Initializes the callback. Args: checkpoint_dir: Directory to store checkpoints to.",
"name": "__init__",
"signature": "def __init__(self, checkpoint_dir: Path) -> None"
},
{
"docstring": "Save the model on epoch end if the model has improved. Args: epoch: The current epoch. logs:... | 3 | null | Implement the Python class `RasaModelCheckpoint` described below.
Class description:
Callback for saving intermediate model checkpoints.
Method signatures and docstrings:
- def __init__(self, checkpoint_dir: Path) -> None: Initializes the callback. Args: checkpoint_dir: Directory to store checkpoints to.
- def on_epo... | Implement the Python class `RasaModelCheckpoint` described below.
Class description:
Callback for saving intermediate model checkpoints.
Method signatures and docstrings:
- def __init__(self, checkpoint_dir: Path) -> None: Initializes the callback. Args: checkpoint_dir: Directory to store checkpoints to.
- def on_epo... | 50857610bdf0c26dc61f3203a6cbb4bcf193768c | <|skeleton|>
class RasaModelCheckpoint:
"""Callback for saving intermediate model checkpoints."""
def __init__(self, checkpoint_dir: Path) -> None:
"""Initializes the callback. Args: checkpoint_dir: Directory to store checkpoints to."""
<|body_0|>
def on_epoch_end(self, epoch: int, logs: O... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RasaModelCheckpoint:
"""Callback for saving intermediate model checkpoints."""
def __init__(self, checkpoint_dir: Path) -> None:
"""Initializes the callback. Args: checkpoint_dir: Directory to store checkpoints to."""
super().__init__()
self.checkpoint_file = checkpoint_dir / 'che... | the_stack_v2_python_sparse | rasa/utils/tensorflow/callback.py | RasaHQ/rasa | train | 13,167 |
9c91186c1338ed6652693e36961593fc788b37ba | [
"departments = Service.objects.filter(status=1, parent_id=0)\nserializer = ServiceSerializer(departments, many=True)\nreturn Response({'status': True, 'message': '成功', 'data': serializer.data})",
"request.data['parent_id'] = 0\nserializer = ServiceSerializer(data=request.data)\nif not serializer.is_valid():\n ... | <|body_start_0|>
departments = Service.objects.filter(status=1, parent_id=0)
serializer = ServiceSerializer(departments, many=True)
return Response({'status': True, 'message': '成功', 'data': serializer.data})
<|end_body_0|>
<|body_start_1|>
request.data['parent_id'] = 0
serialize... | 查询所有dubbo接口部门提供方 | DepartmentList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DepartmentList:
"""查询所有dubbo接口部门提供方"""
def get(self, request):
"""返回所有dubbo接口部门提供方"""
<|body_0|>
def post(self, request):
"""新增一个部门"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
departments = Service.objects.filter(status=1, parent_id=0)
... | stack_v2_sparse_classes_36k_train_026143 | 2,513 | no_license | [
{
"docstring": "返回所有dubbo接口部门提供方",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "新增一个部门",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008498 | Implement the Python class `DepartmentList` described below.
Class description:
查询所有dubbo接口部门提供方
Method signatures and docstrings:
- def get(self, request): 返回所有dubbo接口部门提供方
- def post(self, request): 新增一个部门 | Implement the Python class `DepartmentList` described below.
Class description:
查询所有dubbo接口部门提供方
Method signatures and docstrings:
- def get(self, request): 返回所有dubbo接口部门提供方
- def post(self, request): 新增一个部门
<|skeleton|>
class DepartmentList:
"""查询所有dubbo接口部门提供方"""
def get(self, request):
"""返回所有dub... | 1621ee90681a7796da7ad7173cc2a9b67494ed03 | <|skeleton|>
class DepartmentList:
"""查询所有dubbo接口部门提供方"""
def get(self, request):
"""返回所有dubbo接口部门提供方"""
<|body_0|>
def post(self, request):
"""新增一个部门"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DepartmentList:
"""查询所有dubbo接口部门提供方"""
def get(self, request):
"""返回所有dubbo接口部门提供方"""
departments = Service.objects.filter(status=1, parent_id=0)
serializer = ServiceSerializer(departments, many=True)
return Response({'status': True, 'message': '成功', 'data': serializer.dat... | the_stack_v2_python_sparse | at_server-master/dubbo/views_department.py | xiaominwanglast/reactjs | train | 1 |
8e43691036f9dcded320b1e2f45e9f7698c44438 | [
"super().__init__(model_dir, *args, **kwargs)\nself.model_dir: str = model_dir\nself.sequence_length = kwargs.pop('sequence_length', 512)\nself.tokenizer = AutoTokenizer.from_pretrained(model_dir, use_fast=True)",
"text = data\noutput = self.tokenizer([text], return_tensors='pt')\nreturn {'text': text, 'input_ids... | <|body_start_0|>
super().__init__(model_dir, *args, **kwargs)
self.model_dir: str = model_dir
self.sequence_length = kwargs.pop('sequence_length', 512)
self.tokenizer = AutoTokenizer.from_pretrained(model_dir, use_fast=True)
<|end_body_0|>
<|body_start_1|>
text = data
ou... | The relation extraction preprocessor used in normal RE task. | RelationExtractionPreprocessor | [
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelationExtractionPreprocessor:
"""The relation extraction preprocessor used in normal RE task."""
def __init__(self, model_dir: str, *args, **kwargs):
"""preprocess the data Args: model_dir (str): model path"""
<|body_0|>
def __call__(self, data: str) -> Dict[str, Any]:... | stack_v2_sparse_classes_36k_train_026144 | 1,650 | permissive | [
{
"docstring": "preprocess the data Args: model_dir (str): model path",
"name": "__init__",
"signature": "def __init__(self, model_dir: str, *args, **kwargs)"
},
{
"docstring": "process the raw input data Args: data (str): a sentence Example: 'you are so handsome.' Returns: Dict[str, Any]: the p... | 2 | stack_v2_sparse_classes_30k_train_006287 | Implement the Python class `RelationExtractionPreprocessor` described below.
Class description:
The relation extraction preprocessor used in normal RE task.
Method signatures and docstrings:
- def __init__(self, model_dir: str, *args, **kwargs): preprocess the data Args: model_dir (str): model path
- def __call__(sel... | Implement the Python class `RelationExtractionPreprocessor` described below.
Class description:
The relation extraction preprocessor used in normal RE task.
Method signatures and docstrings:
- def __init__(self, model_dir: str, *args, **kwargs): preprocess the data Args: model_dir (str): model path
- def __call__(sel... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class RelationExtractionPreprocessor:
"""The relation extraction preprocessor used in normal RE task."""
def __init__(self, model_dir: str, *args, **kwargs):
"""preprocess the data Args: model_dir (str): model path"""
<|body_0|>
def __call__(self, data: str) -> Dict[str, Any]:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RelationExtractionPreprocessor:
"""The relation extraction preprocessor used in normal RE task."""
def __init__(self, model_dir: str, *args, **kwargs):
"""preprocess the data Args: model_dir (str): model path"""
super().__init__(model_dir, *args, **kwargs)
self.model_dir: str = mo... | the_stack_v2_python_sparse | ai/modelscope/modelscope/preprocessors/nlp/relation_extraction_preprocessor.py | alldatacenter/alldata | train | 774 |
a18dced4b99aec0b86db3fd353198a86a4582dcf | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UserExperienceAnalyticsAppHealthDevicePerformance()",
"from .entity import Entity\nfrom .user_experience_analytics_health_state import UserExperienceAnalyticsHealthState\nfrom .entity import Entity\nfrom .user_experience_analytics_heal... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UserExperienceAnalyticsAppHealthDevicePerformance()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .user_experience_analytics_health_state import UserExperienceAnalytics... | The user experience analytics device performance entity contains device performance details. | UserExperienceAnalyticsAppHealthDevicePerformance | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserExperienceAnalyticsAppHealthDevicePerformance:
"""The user experience analytics device performance entity contains device performance details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsAppHealthDevicePerformance:
"""Cre... | stack_v2_sparse_classes_36k_train_026145 | 6,373 | 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: UserExperienceAnalyticsAppHealthDevicePerformance",
"name": "create_from_discriminator_value",
"signature": ... | 3 | null | Implement the Python class `UserExperienceAnalyticsAppHealthDevicePerformance` described below.
Class description:
The user experience analytics device performance entity contains device performance details.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) ... | Implement the Python class `UserExperienceAnalyticsAppHealthDevicePerformance` described below.
Class description:
The user experience analytics device performance entity contains device performance details.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) ... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UserExperienceAnalyticsAppHealthDevicePerformance:
"""The user experience analytics device performance entity contains device performance details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsAppHealthDevicePerformance:
"""Cre... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserExperienceAnalyticsAppHealthDevicePerformance:
"""The user experience analytics device performance entity contains device performance details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsAppHealthDevicePerformance:
"""Creates a new in... | the_stack_v2_python_sparse | msgraph/generated/models/user_experience_analytics_app_health_device_performance.py | microsoftgraph/msgraph-sdk-python | train | 135 |
3e4df263d8590c3e383f063d4a4d066555a3cb44 | [
"num_nodes = connectivity_matrix.shape[0]\nexc_mass_params = self._prepare_mass_params(exc_mass_params, num_nodes)\ninh_mass_params = self._prepare_mass_params(inh_mass_params, num_nodes)\nexc_lin_nonlin_transfer_function_filename = self._prepare_mass_params(exc_lin_nonlin_transfer_function_filename, num_nodes, nat... | <|body_start_0|>
num_nodes = connectivity_matrix.shape[0]
exc_mass_params = self._prepare_mass_params(exc_mass_params, num_nodes)
inh_mass_params = self._prepare_mass_params(inh_mass_params, num_nodes)
exc_lin_nonlin_transfer_function_filename = self._prepare_mass_params(exc_lin_nonlin_t... | Whole brain network of adaptive exponential integrate-and-fire mean-field excitatory and inhibitory nodes. | ALNNetwork | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ALNNetwork:
"""Whole brain network of adaptive exponential integrate-and-fire mean-field excitatory and inhibitory nodes."""
def __init__(self, connectivity_matrix, delay_matrix, exc_mass_params=None, inh_mass_params=None, exc_lin_nonlin_transfer_function_filename=None, inh_lin_nonlin_transf... | stack_v2_sparse_classes_36k_train_026146 | 35,756 | permissive | [
{
"docstring": ":param connectivity_matrix: connectivity matrix for coupling between nodes, defined as [from, to] :type connectivity_matrix: np.ndarray :param delay_matrix: delay matrix between nodes, if None, delays are all zeros, in ms, defined as [from, to] :type delay_matrix: np.ndarray|None :param exc_mass... | 2 | stack_v2_sparse_classes_30k_train_005987 | Implement the Python class `ALNNetwork` described below.
Class description:
Whole brain network of adaptive exponential integrate-and-fire mean-field excitatory and inhibitory nodes.
Method signatures and docstrings:
- def __init__(self, connectivity_matrix, delay_matrix, exc_mass_params=None, inh_mass_params=None, e... | Implement the Python class `ALNNetwork` described below.
Class description:
Whole brain network of adaptive exponential integrate-and-fire mean-field excitatory and inhibitory nodes.
Method signatures and docstrings:
- def __init__(self, connectivity_matrix, delay_matrix, exc_mass_params=None, inh_mass_params=None, e... | bec8fbc5ffa7c3b45a266e21549cf392a6263136 | <|skeleton|>
class ALNNetwork:
"""Whole brain network of adaptive exponential integrate-and-fire mean-field excitatory and inhibitory nodes."""
def __init__(self, connectivity_matrix, delay_matrix, exc_mass_params=None, inh_mass_params=None, exc_lin_nonlin_transfer_function_filename=None, inh_lin_nonlin_transf... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ALNNetwork:
"""Whole brain network of adaptive exponential integrate-and-fire mean-field excitatory and inhibitory nodes."""
def __init__(self, connectivity_matrix, delay_matrix, exc_mass_params=None, inh_mass_params=None, exc_lin_nonlin_transfer_function_filename=None, inh_lin_nonlin_transfer_function_f... | the_stack_v2_python_sparse | neurolib/models/multimodel/builder/aln.py | neurolib-dev/neurolib | train | 363 |
23ca73cee025fb7658d3524a431659ca6d9d41af | [
"result = find_angle(10, 10)\nself.assertEqual(result, '45°')\nreturn",
"result = find_angle(5, 5)\nself.assertEqual(result, '45°')\nreturn"
] | <|body_start_0|>
result = find_angle(10, 10)
self.assertEqual(result, '45°')
return
<|end_body_0|>
<|body_start_1|>
result = find_angle(5, 5)
self.assertEqual(result, '45°')
return
<|end_body_1|>
| Test angle MBC | TestFindAngle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestFindAngle:
"""Test angle MBC"""
def test_hackerrank_sample1(self):
"""Verify provided test case."""
<|body_0|>
def test_hackerrank_sample2(self):
"""Verify provided test case."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = find_ang... | stack_v2_sparse_classes_36k_train_026147 | 564 | no_license | [
{
"docstring": "Verify provided test case.",
"name": "test_hackerrank_sample1",
"signature": "def test_hackerrank_sample1(self)"
},
{
"docstring": "Verify provided test case.",
"name": "test_hackerrank_sample2",
"signature": "def test_hackerrank_sample2(self)"
}
] | 2 | null | Implement the Python class `TestFindAngle` described below.
Class description:
Test angle MBC
Method signatures and docstrings:
- def test_hackerrank_sample1(self): Verify provided test case.
- def test_hackerrank_sample2(self): Verify provided test case. | Implement the Python class `TestFindAngle` described below.
Class description:
Test angle MBC
Method signatures and docstrings:
- def test_hackerrank_sample1(self): Verify provided test case.
- def test_hackerrank_sample2(self): Verify provided test case.
<|skeleton|>
class TestFindAngle:
"""Test angle MBC"""
... | fcf3755b62fe0644af763875e3a00be962941a6d | <|skeleton|>
class TestFindAngle:
"""Test angle MBC"""
def test_hackerrank_sample1(self):
"""Verify provided test case."""
<|body_0|>
def test_hackerrank_sample2(self):
"""Verify provided test case."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestFindAngle:
"""Test angle MBC"""
def test_hackerrank_sample1(self):
"""Verify provided test case."""
result = find_angle(10, 10)
self.assertEqual(result, '45°')
return
def test_hackerrank_sample2(self):
"""Verify provided test case."""
result = find... | the_stack_v2_python_sparse | python3/find_angle/test_find_angle.py | ayazhemani/hackerrank-py | train | 0 |
ba169b4c35fcb6fbd2b53ad4fc4a629926b55d36 | [
"if self.state_model.op_state in [DevState.UNKNOWN, DevState.DISABLE]:\n log_msg = f'ObsReset() is not allowed in {self.state_model.op_state}'\n tango.Except.throw_exception(log_msg, 'Failed to invoke ObsReset command on MccsSubarrayLeafNode.', 'mccssubarrayleafnode.ObsReset()', tango.ErrSeverity.ERR)\nself.t... | <|body_start_0|>
if self.state_model.op_state in [DevState.UNKNOWN, DevState.DISABLE]:
log_msg = f'ObsReset() is not allowed in {self.state_model.op_state}'
tango.Except.throw_exception(log_msg, 'Failed to invoke ObsReset command on MccsSubarrayLeafNode.', 'mccssubarrayleafnode.ObsReset(... | A class for MccsSubarrayLeafNode's ObsReset() command. Command to reset the MCCS subarray and bring it to its RESETTING state. | ObsReset | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObsReset:
"""A class for MccsSubarrayLeafNode's ObsReset() command. Command to reset the MCCS subarray and bring it to its RESETTING state."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current device state :return: True if this command is allowed... | stack_v2_sparse_classes_36k_train_026148 | 4,408 | permissive | [
{
"docstring": "Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device state :rtype: boolean :raises: DevFailed if this command is not allowed to be run in current device state",
"name": "check_allowed",
"signature": ... | 3 | null | Implement the Python class `ObsReset` described below.
Class description:
A class for MccsSubarrayLeafNode's ObsReset() command. Command to reset the MCCS subarray and bring it to its RESETTING state.
Method signatures and docstrings:
- def check_allowed(self): Checks whether this command is allowed to be run in curr... | Implement the Python class `ObsReset` described below.
Class description:
A class for MccsSubarrayLeafNode's ObsReset() command. Command to reset the MCCS subarray and bring it to its RESETTING state.
Method signatures and docstrings:
- def check_allowed(self): Checks whether this command is allowed to be run in curr... | 7ee65a9c8dada9b28893144b372a398bd0646195 | <|skeleton|>
class ObsReset:
"""A class for MccsSubarrayLeafNode's ObsReset() command. Command to reset the MCCS subarray and bring it to its RESETTING state."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current device state :return: True if this command is allowed... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObsReset:
"""A class for MccsSubarrayLeafNode's ObsReset() command. Command to reset the MCCS subarray and bring it to its RESETTING state."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in... | the_stack_v2_python_sparse | temp_src/ska_tmc_mccssubarrayleafnode_low/obsreset_command.py | ska-telescope/tmc-prototype | train | 4 |
fd04ed736e9a1f3f73c4b833d4151ff0f73fcf89 | [
"time.sleep(2)\nRegistPage(web_page).regist(data['username'], data['code'], data['password'])\nlogging.info('开始断言')\ntime.sleep(3)\ntry:\n assert RegistPage(web_page).login_success() == data['check']\n assert 1 == 1\n logging.info('登录成功')\nexcept:\n print('登录失败')\n common.save_screenShot(web_page, mo... | <|body_start_0|>
time.sleep(2)
RegistPage(web_page).regist(data['username'], data['code'], data['password'])
logging.info('开始断言')
time.sleep(3)
try:
assert RegistPage(web_page).login_success() == data['check']
assert 1 == 1
logging.info('登录成功')... | TestRegist | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestRegist:
def test_regist_success(self, data, web_page):
"""成功登录"""
<|body_0|>
def test_user_phone_err(self, data, web_page):
"""手机号码错误"""
<|body_1|>
def test_user_code_err(self, data, web_page):
"""验证码错误"""
<|body_2|>
def test_use... | stack_v2_sparse_classes_36k_train_026149 | 3,500 | no_license | [
{
"docstring": "成功登录",
"name": "test_regist_success",
"signature": "def test_regist_success(self, data, web_page)"
},
{
"docstring": "手机号码错误",
"name": "test_user_phone_err",
"signature": "def test_user_phone_err(self, data, web_page)"
},
{
"docstring": "验证码错误",
"name": "test_... | 5 | null | Implement the Python class `TestRegist` described below.
Class description:
Implement the TestRegist class.
Method signatures and docstrings:
- def test_regist_success(self, data, web_page): 成功登录
- def test_user_phone_err(self, data, web_page): 手机号码错误
- def test_user_code_err(self, data, web_page): 验证码错误
- def test_u... | Implement the Python class `TestRegist` described below.
Class description:
Implement the TestRegist class.
Method signatures and docstrings:
- def test_regist_success(self, data, web_page): 成功登录
- def test_user_phone_err(self, data, web_page): 手机号码错误
- def test_user_code_err(self, data, web_page): 验证码错误
- def test_u... | b262c13e55a6e9eae1d4fa11d50b71814028261c | <|skeleton|>
class TestRegist:
def test_regist_success(self, data, web_page):
"""成功登录"""
<|body_0|>
def test_user_phone_err(self, data, web_page):
"""手机号码错误"""
<|body_1|>
def test_user_code_err(self, data, web_page):
"""验证码错误"""
<|body_2|>
def test_use... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestRegist:
def test_regist_success(self, data, web_page):
"""成功登录"""
time.sleep(2)
RegistPage(web_page).regist(data['username'], data['code'], data['password'])
logging.info('开始断言')
time.sleep(3)
try:
assert RegistPage(web_page).login_success() == d... | the_stack_v2_python_sparse | TestCase/test_C_web/test_regist.py | xjx985426946/Test_UI | train | 0 | |
ea9a9fa10e4b7a94a57fe2e8f0ea4cd47c546d8c | [
"follow = 0\nfor byte in data:\n if not byte & 128:\n if follow:\n return False\n elif byte & 192 == 128:\n if not follow:\n return False\n follow -= 1\n elif byte & 224 == 192:\n if follow:\n return False\n follow = 1\n elif byte & 240... | <|body_start_0|>
follow = 0
for byte in data:
if not byte & 128:
if follow:
return False
elif byte & 192 == 128:
if not follow:
return False
follow -= 1
elif byte & 224 == 192:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def validUtf8(self, data):
""":type data: List[int] :rtype: bool"""
<|body_0|>
def rewrite(self, data):
""":type data: List[int] :rtype: bool"""
<|body_1|>
def rewrite2(self, data):
""":type data: List[int] :rtype: bool"""
<|bod... | stack_v2_sparse_classes_36k_train_026150 | 6,087 | no_license | [
{
"docstring": ":type data: List[int] :rtype: bool",
"name": "validUtf8",
"signature": "def validUtf8(self, data)"
},
{
"docstring": ":type data: List[int] :rtype: bool",
"name": "rewrite",
"signature": "def rewrite(self, data)"
},
{
"docstring": ":type data: List[int] :rtype: bo... | 3 | stack_v2_sparse_classes_30k_train_006082 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validUtf8(self, data): :type data: List[int] :rtype: bool
- def rewrite(self, data): :type data: List[int] :rtype: bool
- def rewrite2(self, data): :type data: List[int] :rty... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validUtf8(self, data): :type data: List[int] :rtype: bool
- def rewrite(self, data): :type data: List[int] :rtype: bool
- def rewrite2(self, data): :type data: List[int] :rty... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def validUtf8(self, data):
""":type data: List[int] :rtype: bool"""
<|body_0|>
def rewrite(self, data):
""":type data: List[int] :rtype: bool"""
<|body_1|>
def rewrite2(self, data):
""":type data: List[int] :rtype: bool"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def validUtf8(self, data):
""":type data: List[int] :rtype: bool"""
follow = 0
for byte in data:
if not byte & 128:
if follow:
return False
elif byte & 192 == 128:
if not follow:
r... | the_stack_v2_python_sparse | co_fb/393_UTF-8_Validation.py | vsdrun/lc_public | train | 6 | |
3ba98098466b472909ac637a0b4118f66025cc13 | [
"if not self._saved_mail_backend:\n self._saved_mail_backend = smtp.EmailBackend(SMTP_HOST, SMTP_PORT)\nreturn self._saved_mail_backend",
"emails = params\nif not emails:\n log.error('Invalid email address from params: %s' % params)\n raise gen.Return()\nsubject = 'Warning! %s has an alert!' % path\nbody... | <|body_start_0|>
if not self._saved_mail_backend:
self._saved_mail_backend = smtp.EmailBackend(SMTP_HOST, SMTP_PORT)
return self._saved_mail_backend
<|end_body_0|>
<|body_start_1|>
emails = params
if not emails:
log.error('Invalid email address from params: %s' %... | Simple Email-based Alerter Object This object handles incoming alert calls from the main zk_monitor.alerts.Dispatcher class and converts them into email messages. Your zk_monitor YAML configuration file must include (for each path) a configured 'alerter' section like this: /services/foo/min_1: alerter: email: you@home.... | EmailAlerter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmailAlerter:
"""Simple Email-based Alerter Object This object handles incoming alert calls from the main zk_monitor.alerts.Dispatcher class and converts them into email messages. Your zk_monitor YAML configuration file must include (for each path) a configured 'alerter' section like this: /servi... | stack_v2_sparse_classes_36k_train_026151 | 4,661 | no_license | [
{
"docstring": "Returns a single EmailBackend object every time its called",
"name": "_mail_backend",
"signature": "def _mail_backend(self)"
},
{
"docstring": "Send an email alert. args: path: String of the path that is being alerted. state: String of the monitor.states for given path. message: ... | 2 | stack_v2_sparse_classes_30k_train_006965 | Implement the Python class `EmailAlerter` described below.
Class description:
Simple Email-based Alerter Object This object handles incoming alert calls from the main zk_monitor.alerts.Dispatcher class and converts them into email messages. Your zk_monitor YAML configuration file must include (for each path) a configu... | Implement the Python class `EmailAlerter` described below.
Class description:
Simple Email-based Alerter Object This object handles incoming alert calls from the main zk_monitor.alerts.Dispatcher class and converts them into email messages. Your zk_monitor YAML configuration file must include (for each path) a configu... | d33720eeec274396435896ed4fb1c71025344fc1 | <|skeleton|>
class EmailAlerter:
"""Simple Email-based Alerter Object This object handles incoming alert calls from the main zk_monitor.alerts.Dispatcher class and converts them into email messages. Your zk_monitor YAML configuration file must include (for each path) a configured 'alerter' section like this: /servi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmailAlerter:
"""Simple Email-based Alerter Object This object handles incoming alert calls from the main zk_monitor.alerts.Dispatcher class and converts them into email messages. Your zk_monitor YAML configuration file must include (for each path) a configured 'alerter' section like this: /services/foo/min_1... | the_stack_v2_python_sparse | zk_monitor/alerts/email.py | Nextdoor/zkmonitor | train | 4 |
964d7983595e9259e4dd682969d10c67599b2ad7 | [
"self.transitions_C = transitions_C\nself.transitions_D = transitions_D\nself.emission_probabilities = emission_probabilities\nself.state = initial_state\nself._cache_C = dict()\nself._cache_D = dict()\nself._cache_deterministic_transitions()\nself._random = None",
"for state in range(len(self.transitions_C)):\n ... | <|body_start_0|>
self.transitions_C = transitions_C
self.transitions_D = transitions_D
self.emission_probabilities = emission_probabilities
self.state = initial_state
self._cache_C = dict()
self._cache_D = dict()
self._cache_deterministic_transitions()
sel... | Implementation of a basic Hidden Markov Model. We assume that the transition matrix is conditioned on the opponent's last action, so there are two transition matrices. Emission distributions are stored as Bernoulli probabilities for each state. This is essentially a stochastic FSM. https://en.wikipedia.org/wiki/Hidden_... | SimpleHMM | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleHMM:
"""Implementation of a basic Hidden Markov Model. We assume that the transition matrix is conditioned on the opponent's last action, so there are two transition matrices. Emission distributions are stored as Bernoulli probabilities for each state. This is essentially a stochastic FSM. ... | stack_v2_sparse_classes_36k_train_026152 | 16,774 | permissive | [
{
"docstring": "Params ------ transitions_C and transitions_D are square stochastic matrices: lists of lists with all values in [0, 1] and rows that sum to 1. emission_probabilities is a vector of values in [0, 1] initial_state is an element of range(0, len(emission_probabilities))",
"name": "__init__",
... | 5 | stack_v2_sparse_classes_30k_train_018582 | Implement the Python class `SimpleHMM` described below.
Class description:
Implementation of a basic Hidden Markov Model. We assume that the transition matrix is conditioned on the opponent's last action, so there are two transition matrices. Emission distributions are stored as Bernoulli probabilities for each state.... | Implement the Python class `SimpleHMM` described below.
Class description:
Implementation of a basic Hidden Markov Model. We assume that the transition matrix is conditioned on the opponent's last action, so there are two transition matrices. Emission distributions are stored as Bernoulli probabilities for each state.... | fa748627cd4f0333bb2dbfcb1454372a78a9098a | <|skeleton|>
class SimpleHMM:
"""Implementation of a basic Hidden Markov Model. We assume that the transition matrix is conditioned on the opponent's last action, so there are two transition matrices. Emission distributions are stored as Bernoulli probabilities for each state. This is essentially a stochastic FSM. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimpleHMM:
"""Implementation of a basic Hidden Markov Model. We assume that the transition matrix is conditioned on the opponent's last action, so there are two transition matrices. Emission distributions are stored as Bernoulli probabilities for each state. This is essentially a stochastic FSM. https://en.wi... | the_stack_v2_python_sparse | axelrod/strategies/hmm.py | Axelrod-Python/Axelrod | train | 673 |
1aeef0fbf8c657de5582c2fe43b9d8806e6909f1 | [
"d = {'resourceType': 'Intervention'}\nfor attr in ('name', 'description', 'card_html', 'link_label', 'status_text', 'public_access', 'display_rank'):\n if getattr(self, attr, None) is not None:\n d[attr] = getattr(self, attr)\nreturn d",
"if not 'name' in data:\n raise ValueError(\"required 'name' f... | <|body_start_0|>
d = {'resourceType': 'Intervention'}
for attr in ('name', 'description', 'card_html', 'link_label', 'status_text', 'public_access', 'display_rank'):
if getattr(self, attr, None) is not None:
d[attr] = getattr(self, attr)
return d
<|end_body_0|>
<|bod... | Intervention | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Intervention:
def as_json(self):
"""Returns the 'safe to export' portions of an intervention The client_id and link_url are non-portable between systems. The id is also independent - return the rest of the not null fields as a simple json dict."""
<|body_0|>
def from_json(cl... | stack_v2_sparse_classes_36k_train_026153 | 10,034 | permissive | [
{
"docstring": "Returns the 'safe to export' portions of an intervention The client_id and link_url are non-portable between systems. The id is also independent - return the rest of the not null fields as a simple json dict.",
"name": "as_json",
"signature": "def as_json(self)"
},
{
"docstring":... | 5 | stack_v2_sparse_classes_30k_train_014767 | Implement the Python class `Intervention` described below.
Class description:
Implement the Intervention class.
Method signatures and docstrings:
- def as_json(self): Returns the 'safe to export' portions of an intervention The client_id and link_url are non-portable between systems. The id is also independent - retu... | Implement the Python class `Intervention` described below.
Class description:
Implement the Intervention class.
Method signatures and docstrings:
- def as_json(self): Returns the 'safe to export' portions of an intervention The client_id and link_url are non-portable between systems. The id is also independent - retu... | c756147b24cbc6988ac61c601491e4604074c3a7 | <|skeleton|>
class Intervention:
def as_json(self):
"""Returns the 'safe to export' portions of an intervention The client_id and link_url are non-portable between systems. The id is also independent - return the rest of the not null fields as a simple json dict."""
<|body_0|>
def from_json(cl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Intervention:
def as_json(self):
"""Returns the 'safe to export' portions of an intervention The client_id and link_url are non-portable between systems. The id is also independent - return the rest of the not null fields as a simple json dict."""
d = {'resourceType': 'Intervention'}
f... | the_stack_v2_python_sparse | portal/models/intervention.py | jmillr/true_nth_usa_portal | train | 0 | |
3c55a0f73a5023cf7cbd2e3af41f1532948a4068 | [
"if not root:\n return []\nres = [root.val]\nlevel = [root]\nwhile level:\n tem = []\n for l in level:\n if l:\n for child in [l.left, l.right]:\n tem.append(child)\n res.extend((i.val if i else None for i in tem))\n level = tem\nreturn res",
"if not data:\n retu... | <|body_start_0|>
if not root:
return []
res = [root.val]
level = [root]
while level:
tem = []
for l in level:
if l:
for child in [l.left, l.right]:
tem.append(child)
res.extend((i.... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_026154 | 1,788 | 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 | stack_v2_sparse_classes_30k_train_003612 | 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:... | 409d7db811d41dbcc7ce8cda82b77eff35585657 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return []
res = [root.val]
level = [root]
while level:
tem = []
for l in level:
if l:
... | the_stack_v2_python_sparse | Serialize and Deserialize Binary Tree.py | Windsooon/LeetCode | train | 1 | |
532d47c088fffdb36565d40832b6f2489bacd8f1 | [
"super(DPSR, self).__init__()\nself.res = res\nself.sig = sig\nself.dim = len(res)\nself.denom = np.prod(res)\nG = spec_gaussian_filter(res=res, sig=sig).float()\nself.omega = fftfreqs(res, dtype=torch.float32)\nself.scale = scale\nself.shift = shift\nself.register_buffer('G', G)",
"assert V.shape == N.shape\nras... | <|body_start_0|>
super(DPSR, self).__init__()
self.res = res
self.sig = sig
self.dim = len(res)
self.denom = np.prod(res)
G = spec_gaussian_filter(res=res, sig=sig).float()
self.omega = fftfreqs(res, dtype=torch.float32)
self.scale = scale
self.shi... | DPSR | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DPSR:
def __init__(self, res, sig=10, scale=True, shift=True):
""":param res: tuple of output field resolution. eg., (128,128) :param sig: degree of gaussian smoothing"""
<|body_0|>
def forward(self, V, N):
""":param V: (batch, nv, 2 or 3) tensor for point cloud coor... | stack_v2_sparse_classes_36k_train_026155 | 2,955 | permissive | [
{
"docstring": ":param res: tuple of output field resolution. eg., (128,128) :param sig: degree of gaussian smoothing",
"name": "__init__",
"signature": "def __init__(self, res, sig=10, scale=True, shift=True)"
},
{
"docstring": ":param V: (batch, nv, 2 or 3) tensor for point cloud coordinates :... | 2 | stack_v2_sparse_classes_30k_train_016469 | Implement the Python class `DPSR` described below.
Class description:
Implement the DPSR class.
Method signatures and docstrings:
- def __init__(self, res, sig=10, scale=True, shift=True): :param res: tuple of output field resolution. eg., (128,128) :param sig: degree of gaussian smoothing
- def forward(self, V, N): ... | Implement the Python class `DPSR` described below.
Class description:
Implement the DPSR class.
Method signatures and docstrings:
- def __init__(self, res, sig=10, scale=True, shift=True): :param res: tuple of output field resolution. eg., (128,128) :param sig: degree of gaussian smoothing
- def forward(self, V, N): ... | 54c2783479c9514190af956b6e9dac25221a64c1 | <|skeleton|>
class DPSR:
def __init__(self, res, sig=10, scale=True, shift=True):
""":param res: tuple of output field resolution. eg., (128,128) :param sig: degree of gaussian smoothing"""
<|body_0|>
def forward(self, V, N):
""":param V: (batch, nv, 2 or 3) tensor for point cloud coor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DPSR:
def __init__(self, res, sig=10, scale=True, shift=True):
""":param res: tuple of output field resolution. eg., (128,128) :param sig: degree of gaussian smoothing"""
super(DPSR, self).__init__()
self.res = res
self.sig = sig
self.dim = len(res)
self.denom =... | the_stack_v2_python_sparse | src/dpsr.py | liruihui/shape_as_points | train | 0 | |
db670d2e7a76904bab5e226b1e3e4e92db484354 | [
"self.X = X\nself.U_int = U[0]\nself.U_ext = U[1]\nself.P = P if P is not None else uc.UncertaintySet()",
"u_max = self.U_ext.V[np.argmax([la.norm(u) for u in self.U_ext.V])]\nx_max = self.X.V[np.argmax([la.norm(x) for x in self.X.V])]\nR = np.eye(0)\nr = np.array([])\nj = 0\nfor i in range(len(self.P.sets)):\n ... | <|body_start_0|>
self.X = X
self.U_int = U[0]
self.U_ext = U[1]
self.P = P if P is not None else uc.UncertaintySet()
<|end_body_0|>
<|body_start_1|>
u_max = self.U_ext.V[np.argmax([la.norm(u) for u in self.U_ext.V])]
x_max = self.X.V[np.argmax([la.norm(x) for x in self.X... | Control problem specifications. | Specifications | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Specifications:
"""Control problem specifications."""
def __init__(self, X, U, P=None):
"""Parameters ---------- X : Polytope Set of allowed states. U : tuple of Polytope Tuple (U_int,U_ext) such that the admissible inputs are \\in U_ext \\setminus U_int. Both U_int and U_ext are ass... | stack_v2_sparse_classes_36k_train_026156 | 2,232 | no_license | [
{
"docstring": "Parameters ---------- X : Polytope Set of allowed states. U : tuple of Polytope Tuple (U_int,U_ext) such that the admissible inputs are \\\\in U_ext \\\\setminus U_int. Both U_int and U_ext are assumed to be Polytope type. P : UncertaintySet, optional Set of uncertainties. If ommitted, an empty ... | 2 | stack_v2_sparse_classes_30k_train_005963 | Implement the Python class `Specifications` described below.
Class description:
Control problem specifications.
Method signatures and docstrings:
- def __init__(self, X, U, P=None): Parameters ---------- X : Polytope Set of allowed states. U : tuple of Polytope Tuple (U_int,U_ext) such that the admissible inputs are ... | Implement the Python class `Specifications` described below.
Class description:
Control problem specifications.
Method signatures and docstrings:
- def __init__(self, X, U, P=None): Parameters ---------- X : Polytope Set of allowed states. U : tuple of Polytope Tuple (U_int,U_ext) such that the admissible inputs are ... | 858f2b673bedbec39fca9bdc9c825a3c2fefe513 | <|skeleton|>
class Specifications:
"""Control problem specifications."""
def __init__(self, X, U, P=None):
"""Parameters ---------- X : Polytope Set of allowed states. U : tuple of Polytope Tuple (U_int,U_ext) such that the admissible inputs are \\in U_ext \\setminus U_int. Both U_int and U_ext are ass... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Specifications:
"""Control problem specifications."""
def __init__(self, X, U, P=None):
"""Parameters ---------- X : Polytope Set of allowed states. U : tuple of Polytope Tuple (U_int,U_ext) such that the admissible inputs are \\in U_ext \\setminus U_int. Both U_int and U_ext are assumed to be Po... | the_stack_v2_python_sparse | lib/specifications.py | roguextech/DanyloMalyuta-explicit_hybrid_mpc | train | 0 |
7b3b414f98866b1366f26d9fa557e1e11a2699dd | [
"self.cipher = cipher\nself.dukpt = dukpt\nself.tags = tags",
"if dictionary is None:\n return None\ncipher = dictionary.get('cipher')\ntags = None\nif dictionary.get('tags') != None:\n tags = list()\n for structure in dictionary.get('tags'):\n tags.append(mundiapi.models.create_emv_data_tlv_decry... | <|body_start_0|>
self.cipher = cipher
self.dukpt = dukpt
self.tags = tags
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
cipher = dictionary.get('cipher')
tags = None
if dictionary.get('tags') != None:
tags = list()
... | Implementation of the 'CreateEmvDataDecryptRequest' model. TODO: type model description here. Attributes: cipher (string): Emv Decrypt cipher type dukpt (CreateEmvDataDukptDecryptRequest): TODO: type description here. tags (list of CreateEmvDataTlvDecryptRequest): Encrypted tags list | CreateEmvDataDecryptRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateEmvDataDecryptRequest:
"""Implementation of the 'CreateEmvDataDecryptRequest' model. TODO: type model description here. Attributes: cipher (string): Emv Decrypt cipher type dukpt (CreateEmvDataDukptDecryptRequest): TODO: type description here. tags (list of CreateEmvDataTlvDecryptRequest): ... | stack_v2_sparse_classes_36k_train_026157 | 2,397 | permissive | [
{
"docstring": "Constructor for the CreateEmvDataDecryptRequest class",
"name": "__init__",
"signature": "def __init__(self, cipher=None, tags=None, dukpt=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of t... | 2 | stack_v2_sparse_classes_30k_train_015940 | Implement the Python class `CreateEmvDataDecryptRequest` described below.
Class description:
Implementation of the 'CreateEmvDataDecryptRequest' model. TODO: type model description here. Attributes: cipher (string): Emv Decrypt cipher type dukpt (CreateEmvDataDukptDecryptRequest): TODO: type description here. tags (li... | Implement the Python class `CreateEmvDataDecryptRequest` described below.
Class description:
Implementation of the 'CreateEmvDataDecryptRequest' model. TODO: type model description here. Attributes: cipher (string): Emv Decrypt cipher type dukpt (CreateEmvDataDukptDecryptRequest): TODO: type description here. tags (li... | 95c80c35dd57bb2a238faeaf30d1e3b4544d2298 | <|skeleton|>
class CreateEmvDataDecryptRequest:
"""Implementation of the 'CreateEmvDataDecryptRequest' model. TODO: type model description here. Attributes: cipher (string): Emv Decrypt cipher type dukpt (CreateEmvDataDukptDecryptRequest): TODO: type description here. tags (list of CreateEmvDataTlvDecryptRequest): ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateEmvDataDecryptRequest:
"""Implementation of the 'CreateEmvDataDecryptRequest' model. TODO: type model description here. Attributes: cipher (string): Emv Decrypt cipher type dukpt (CreateEmvDataDukptDecryptRequest): TODO: type description here. tags (list of CreateEmvDataTlvDecryptRequest): Encrypted tag... | the_stack_v2_python_sparse | mundiapi/models/create_emv_data_decrypt_request.py | mundipagg/MundiAPI-PYTHON | train | 10 |
73fd9bf479cc61b02d821ad345a11a8a49b5f166 | [
"cmd = 'fleetrun dist_queuedataset1.py'\npro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\nout, err = pro.communicate()\nprint(out)\npro.wait()\npro.returncode == 0",
"cmd = 'fleetrun dist_queuedataset2.py'\npro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, std... | <|body_start_0|>
cmd = 'fleetrun dist_queuedataset1.py'
pro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out, err = pro.communicate()
print(out)
pro.wait()
pro.returncode == 0
<|end_body_0|>
<|body_start_1|>
cmd = 'fleetrun ... | TestDistQueueDataSetApi | TestDistQueueDataSetApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDistQueueDataSetApi:
"""TestDistQueueDataSetApi"""
def test_queuedataset1(self):
"""test_queuedataset1"""
<|body_0|>
def test_queuedataset2(self):
"""test_queuedataset2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cmd = 'fleetrun dist_que... | stack_v2_sparse_classes_36k_train_026158 | 881 | no_license | [
{
"docstring": "test_queuedataset1",
"name": "test_queuedataset1",
"signature": "def test_queuedataset1(self)"
},
{
"docstring": "test_queuedataset2",
"name": "test_queuedataset2",
"signature": "def test_queuedataset2(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006488 | Implement the Python class `TestDistQueueDataSetApi` described below.
Class description:
TestDistQueueDataSetApi
Method signatures and docstrings:
- def test_queuedataset1(self): test_queuedataset1
- def test_queuedataset2(self): test_queuedataset2 | Implement the Python class `TestDistQueueDataSetApi` described below.
Class description:
TestDistQueueDataSetApi
Method signatures and docstrings:
- def test_queuedataset1(self): test_queuedataset1
- def test_queuedataset2(self): test_queuedataset2
<|skeleton|>
class TestDistQueueDataSetApi:
"""TestDistQueueData... | e3562ab40b574f06bba68df6895a055fa31a085d | <|skeleton|>
class TestDistQueueDataSetApi:
"""TestDistQueueDataSetApi"""
def test_queuedataset1(self):
"""test_queuedataset1"""
<|body_0|>
def test_queuedataset2(self):
"""test_queuedataset2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDistQueueDataSetApi:
"""TestDistQueueDataSetApi"""
def test_queuedataset1(self):
"""test_queuedataset1"""
cmd = 'fleetrun dist_queuedataset1.py'
pro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out, err = pro.communicate()
... | the_stack_v2_python_sparse | dist_cts/dist_fleet_pipeline/test_dist_fleet_queue_dataset.py | gentelyang/scripts | train | 0 |
36fdcc5cd16aedc4ba3f9aefe11afcc6532b4dd0 | [
"if os.path.exists(os.path.join(self.detectorModel, self.detectorModel + '.xml')):\n LOG.notice('Found detector model: %s' % os.path.join(self.detectorModel, self.detectorModel + '.xml'))\n return S_OK(os.path.join(self.detectorModel, self.detectorModel + '.xml'))\nelif os.path.exists(self.detectorModel + '.z... | <|body_start_0|>
if os.path.exists(os.path.join(self.detectorModel, self.detectorModel + '.xml')):
LOG.notice('Found detector model: %s' % os.path.join(self.detectorModel, self.detectorModel + '.xml'))
return S_OK(os.path.join(self.detectorModel, self.detectorModel + '.xml'))
eli... | mixin class for DD4hep functionality | DD4hepMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DD4hepMixin:
"""mixin class for DD4hep functionality"""
def _getDetectorXML(self):
"""returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detector xml files :returns: S_OK(PathToXMLFile), S_ERROR"""
... | stack_v2_sparse_classes_36k_train_026159 | 3,493 | no_license | [
{
"docstring": "returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detector xml files :returns: S_OK(PathToXMLFile), S_ERROR",
"name": "_getDetectorXML",
"signature": "def _getDetectorXML(self)"
},
{
"docstring":... | 3 | null | Implement the Python class `DD4hepMixin` described below.
Class description:
mixin class for DD4hep functionality
Method signatures and docstrings:
- def _getDetectorXML(self): returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detect... | Implement the Python class `DD4hepMixin` described below.
Class description:
mixin class for DD4hep functionality
Method signatures and docstrings:
- def _getDetectorXML(self): returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detect... | 9c366957fdd680a284df675c318989cb88e5959c | <|skeleton|>
class DD4hepMixin:
"""mixin class for DD4hep functionality"""
def _getDetectorXML(self):
"""returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detector xml files :returns: S_OK(PathToXMLFile), S_ERROR"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DD4hepMixin:
"""mixin class for DD4hep functionality"""
def _getDetectorXML(self):
"""returns the path to the detector XML file Checks the Configuration System for the Path to DetectorModels or extracts the input sandbox detector xml files :returns: S_OK(PathToXMLFile), S_ERROR"""
if os.p... | the_stack_v2_python_sparse | Workflow/Utilities/DD4hepMixin.py | LCDsoft/ILCDIRAC | train | 1 |
178858c1a430110d0cdb753b18ea9cf4685bd5a7 | [
"self.time = 0\nself.IDToUser = {}\nself.IDToTweet = {}",
"if userId not in self.IDToUser:\n self.IDToUser[userId] = User(userId)\nuser = self.IDToUser[userId]\nself.time += 1\nnewTweet = Tweet(tweetId, self.time, userId)\nuser.tweets.add(newTweet)\nfor followee in user.followees:\n followee.newsFeed.add(ne... | <|body_start_0|>
self.time = 0
self.IDToUser = {}
self.IDToTweet = {}
<|end_body_0|>
<|body_start_1|>
if userId not in self.IDToUser:
self.IDToUser[userId] = User(userId)
user = self.IDToUser[userId]
self.time += 1
newTweet = Tweet(tweetId, self.time,... | Twitter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: None"""
<|body_1|>
def getNewsFeed(self, userId):
"""Ret... | stack_v2_sparse_classes_36k_train_026160 | 3,616 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compose a new tweet. :type userId: int :type tweetId: int :rtype: None",
"name": "postTweet",
"signature": "def postTweet(self, userId, tweetId)"
},
{
"... | 5 | null | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId, tweetId): Compose a new tweet. :type userId: int :type tweetId: int :rtype: None
- def getNew... | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId, tweetId): Compose a new tweet. :type userId: int :type tweetId: int :rtype: None
- def getNew... | 1d8821da01c9c200732a6b7037b8631689e2f7e7 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: None"""
<|body_1|>
def getNewsFeed(self, userId):
"""Ret... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Twitter:
def __init__(self):
"""Initialize your data structure here."""
self.time = 0
self.IDToUser = {}
self.IDToTweet = {}
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: None"""
if userId not in ... | the_stack_v2_python_sparse | Leetcode0355.py | xiaojinghu/Leetcode | train | 0 | |
3a02966fa268a6b6572ea85fe61b4cd461866dc1 | [
"RadianceMaterial.__init__(self, name, materialType='light', modifier='void')\nself.red = red\n'A positive value for the Red channel of the light'\nself.green = green\n'A positive value for the Green channel of the light'\nself.blue = blue\n'A positive value for the Blue channel of the light'",
"__baseString = se... | <|body_start_0|>
RadianceMaterial.__init__(self, name, materialType='light', modifier='void')
self.red = red
'A positive value for the Red channel of the light'
self.green = green
'A positive value for the Green channel of the light'
self.blue = blue
'A positive v... | LightMaterial | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LightMaterial:
def __init__(self, name, red=0, green=0, blue=0):
"""Create light material Attributes: name: Material name as a string. The name should not have whitespaces or special characters. red: A positive value for the Red channel of the light green: A positive value for the Green ... | stack_v2_sparse_classes_36k_train_026161 | 1,559 | permissive | [
{
"docstring": "Create light material Attributes: name: Material name as a string. The name should not have whitespaces or special characters. red: A positive value for the Red channel of the light green: A positive value for the Green channel of the light blue: A positive value for the Blue channel of the ligh... | 2 | null | Implement the Python class `LightMaterial` described below.
Class description:
Implement the LightMaterial class.
Method signatures and docstrings:
- def __init__(self, name, red=0, green=0, blue=0): Create light material Attributes: name: Material name as a string. The name should not have whitespaces or special cha... | Implement the Python class `LightMaterial` described below.
Class description:
Implement the LightMaterial class.
Method signatures and docstrings:
- def __init__(self, name, red=0, green=0, blue=0): Create light material Attributes: name: Material name as a string. The name should not have whitespaces or special cha... | 983fccc934e5546082557f6c2d1f2d9e00eba332 | <|skeleton|>
class LightMaterial:
def __init__(self, name, red=0, green=0, blue=0):
"""Create light material Attributes: name: Material name as a string. The name should not have whitespaces or special characters. red: A positive value for the Red channel of the light green: A positive value for the Green ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LightMaterial:
def __init__(self, name, red=0, green=0, blue=0):
"""Create light material Attributes: name: Material name as a string. The name should not have whitespaces or special characters. red: A positive value for the Red channel of the light green: A positive value for the Green channel of the... | the_stack_v2_python_sparse | honeybee/radiance/material/light.py | ladybug-tools/honeybee-server | train | 7 | |
44330ff170aadd8d8b8b5c2c0fb7ece56cb69b39 | [
"class dummy_manager(object):\n\n def communicator(self):\n return Communicate()\n\n def perspective(self):\n return MyPerspective()\nf = DroppableDataLoadWidget(None, guimanager=dummy_manager())\nself.mime_data = QtCore.QMimeData()\nself.testfile = 'testfile.txt'\nself.mime_data.setUrls([QtCore... | <|body_start_0|>
class dummy_manager(object):
def communicator(self):
return Communicate()
def perspective(self):
return MyPerspective()
f = DroppableDataLoadWidget(None, guimanager=dummy_manager())
self.mime_data = QtCore.QMimeData()
... | Test the DroppableDataLoadWidget GUI | DroppableDataLoadWidgetTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DroppableDataLoadWidgetTest:
"""Test the DroppableDataLoadWidget GUI"""
def form(self, qapp):
"""Create/Destroy the DroppableDataLoadWidget"""
<|body_0|>
def testDragIsOK(self, form):
"""Test the item being dragged over the load widget"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_026162 | 2,643 | permissive | [
{
"docstring": "Create/Destroy the DroppableDataLoadWidget",
"name": "form",
"signature": "def form(self, qapp)"
},
{
"docstring": "Test the item being dragged over the load widget",
"name": "testDragIsOK",
"signature": "def testDragIsOK(self, form)"
},
{
"docstring": "Test what ... | 3 | null | Implement the Python class `DroppableDataLoadWidgetTest` described below.
Class description:
Test the DroppableDataLoadWidget GUI
Method signatures and docstrings:
- def form(self, qapp): Create/Destroy the DroppableDataLoadWidget
- def testDragIsOK(self, form): Test the item being dragged over the load widget
- def ... | Implement the Python class `DroppableDataLoadWidgetTest` described below.
Class description:
Test the DroppableDataLoadWidget GUI
Method signatures and docstrings:
- def form(self, qapp): Create/Destroy the DroppableDataLoadWidget
- def testDragIsOK(self, form): Test the item being dragged over the load widget
- def ... | 55b1e9f6db58e33729f2a93b7dd1d8bf255b46f7 | <|skeleton|>
class DroppableDataLoadWidgetTest:
"""Test the DroppableDataLoadWidget GUI"""
def form(self, qapp):
"""Create/Destroy the DroppableDataLoadWidget"""
<|body_0|>
def testDragIsOK(self, form):
"""Test the item being dragged over the load widget"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DroppableDataLoadWidgetTest:
"""Test the DroppableDataLoadWidget GUI"""
def form(self, qapp):
"""Create/Destroy the DroppableDataLoadWidget"""
class dummy_manager(object):
def communicator(self):
return Communicate()
def perspective(self):
... | the_stack_v2_python_sparse | src/sas/qtgui/MainWindow/UnitTesting/DroppableDataLoadWidgetTest.py | SasView/sasview | train | 48 |
243b4a17e32fcf653187c6bc45f397e5bf1a89e6 | [
"super(FlowData, self).__init__()\nself.filename_flow = 'trash can flow meter.xls'\nself.start_rowx = 2\nself.end_rowx = 17\nself.poly_order = 2\nself.trash_volume = 0.0776\nself.P = 100.0",
"worksheet = xlrd.open_workbook(filename=self.filename_flow).sheet_by_index(0)\nself.corrected_reading = np.array(worksheet... | <|body_start_0|>
super(FlowData, self).__init__()
self.filename_flow = 'trash can flow meter.xls'
self.start_rowx = 2
self.end_rowx = 17
self.poly_order = 2
self.trash_volume = 0.0776
self.P = 100.0
<|end_body_0|>
<|body_start_1|>
worksheet = xlrd.open_wo... | Class for handling flow rate and pressure drop data. | FlowData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlowData:
"""Class for handling flow rate and pressure drop data."""
def __init__(self):
"""Sets default file name, start row, and end row."""
<|body_0|>
def import_flow_data(self):
"""Imports data and stores it in numpy arrays."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k_train_026163 | 7,912 | no_license | [
{
"docstring": "Sets default file name, start row, and end row.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Imports data and stores it in numpy arrays.",
"name": "import_flow_data",
"signature": "def import_flow_data(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005780 | Implement the Python class `FlowData` described below.
Class description:
Class for handling flow rate and pressure drop data.
Method signatures and docstrings:
- def __init__(self): Sets default file name, start row, and end row.
- def import_flow_data(self): Imports data and stores it in numpy arrays. | Implement the Python class `FlowData` described below.
Class description:
Class for handling flow rate and pressure drop data.
Method signatures and docstrings:
- def __init__(self): Sets default file name, start row, and end row.
- def import_flow_data(self): Imports data and stores it in numpy arrays.
<|skeleton|>... | d619b66b1f16557e06c94eee1c16d4ee2a9e896a | <|skeleton|>
class FlowData:
"""Class for handling flow rate and pressure drop data."""
def __init__(self):
"""Sets default file name, start row, and end row."""
<|body_0|>
def import_flow_data(self):
"""Imports data and stores it in numpy arrays."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlowData:
"""Class for handling flow rate and pressure drop data."""
def __init__(self):
"""Sets default file name, start row, and end row."""
super(FlowData, self).__init__()
self.filename_flow = 'trash can flow meter.xls'
self.start_rowx = 2
self.end_rowx = 17
... | the_stack_v2_python_sparse | exp_data.py | hfateh/TE_Model-1 | train | 0 |
ef316b1346de0ca0cc18f92dc54f1d67019712ba | [
"if not emails:\n return []\nreturn [email.strip() for email in emails.split(',')]",
"super().validate(emails)\nfor email in emails:\n validate_email(email)"
] | <|body_start_0|>
if not emails:
return []
return [email.strip() for email in emails.split(',')]
<|end_body_0|>
<|body_start_1|>
super().validate(emails)
for email in emails:
validate_email(email)
<|end_body_1|>
| MultiEmailField | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiEmailField:
def to_python(self, emails: Optional[str]) -> List[str]:
"""Normalize data to a list of strings."""
<|body_0|>
def validate(self, emails: List[str]) -> None:
"""Check if value consists only of valid emails."""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_026164 | 23,582 | permissive | [
{
"docstring": "Normalize data to a list of strings.",
"name": "to_python",
"signature": "def to_python(self, emails: Optional[str]) -> List[str]"
},
{
"docstring": "Check if value consists only of valid emails.",
"name": "validate",
"signature": "def validate(self, emails: List[str]) ->... | 2 | stack_v2_sparse_classes_30k_train_005591 | Implement the Python class `MultiEmailField` described below.
Class description:
Implement the MultiEmailField class.
Method signatures and docstrings:
- def to_python(self, emails: Optional[str]) -> List[str]: Normalize data to a list of strings.
- def validate(self, emails: List[str]) -> None: Check if value consis... | Implement the Python class `MultiEmailField` described below.
Class description:
Implement the MultiEmailField class.
Method signatures and docstrings:
- def to_python(self, emails: Optional[str]) -> List[str]: Normalize data to a list of strings.
- def validate(self, emails: List[str]) -> None: Check if value consis... | 965a25d91b6ee2db54038f5df855215fa25146b0 | <|skeleton|>
class MultiEmailField:
def to_python(self, emails: Optional[str]) -> List[str]:
"""Normalize data to a list of strings."""
<|body_0|>
def validate(self, emails: List[str]) -> None:
"""Check if value consists only of valid emails."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiEmailField:
def to_python(self, emails: Optional[str]) -> List[str]:
"""Normalize data to a list of strings."""
if not emails:
return []
return [email.strip() for email in emails.split(',')]
def validate(self, emails: List[str]) -> None:
"""Check if value ... | the_stack_v2_python_sparse | zerver/forms.py | zulip/zulip | train | 20,239 | |
e944924f06776adce205340fdb95884385004029 | [
"template = PartParameterTemplate.objects.create(name='My Template', description='A template with choices', choices='red, blue, green')\npass_values = ['red', 'blue', 'green']\nfail_values = ['rod', 'bleu', 'grene']\npart = Part.objects.all().first()\nfor value in pass_values:\n param = PartParameter(part=part, ... | <|body_start_0|>
template = PartParameterTemplate.objects.create(name='My Template', description='A template with choices', choices='red, blue, green')
pass_values = ['red', 'blue', 'green']
fail_values = ['rod', 'bleu', 'grene']
part = Part.objects.all().first()
for value in pas... | Unit tests for parameter validation | ParameterTests | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParameterTests:
"""Unit tests for parameter validation"""
def test_choice_validation(self):
"""Test that parameter choices are correctly validated"""
<|body_0|>
def test_unit_validation(self):
"""Test validation of 'units' field for PartParameterTemplate"""
... | stack_v2_sparse_classes_36k_train_026165 | 12,864 | permissive | [
{
"docstring": "Test that parameter choices are correctly validated",
"name": "test_choice_validation",
"signature": "def test_choice_validation(self)"
},
{
"docstring": "Test validation of 'units' field for PartParameterTemplate",
"name": "test_unit_validation",
"signature": "def test_u... | 4 | stack_v2_sparse_classes_30k_train_014121 | Implement the Python class `ParameterTests` described below.
Class description:
Unit tests for parameter validation
Method signatures and docstrings:
- def test_choice_validation(self): Test that parameter choices are correctly validated
- def test_unit_validation(self): Test validation of 'units' field for PartParam... | Implement the Python class `ParameterTests` described below.
Class description:
Unit tests for parameter validation
Method signatures and docstrings:
- def test_choice_validation(self): Test that parameter choices are correctly validated
- def test_unit_validation(self): Test validation of 'units' field for PartParam... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class ParameterTests:
"""Unit tests for parameter validation"""
def test_choice_validation(self):
"""Test that parameter choices are correctly validated"""
<|body_0|>
def test_unit_validation(self):
"""Test validation of 'units' field for PartParameterTemplate"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParameterTests:
"""Unit tests for parameter validation"""
def test_choice_validation(self):
"""Test that parameter choices are correctly validated"""
template = PartParameterTemplate.objects.create(name='My Template', description='A template with choices', choices='red, blue, green')
... | the_stack_v2_python_sparse | InvenTree/part/test_param.py | inventree/InvenTree | train | 3,077 |
6bc0ec8fb7f4a4d42c05529196d55f207d4ccf23 | [
"path = os.path.dirname(os.path.abspath(__file__))\nuv_symmetry_transforms_path = tf.resource_loader.get_path_to_datafile(os.path.join(path, '..', 'dataset_tools', 'densepose', 'UV_symmetry_transforms.mat'))\ntf.logging.info('Loading DensePose symmetry transforms file from {}'.format(uv_symmetry_transforms_path))\n... | <|body_start_0|>
path = os.path.dirname(os.path.abspath(__file__))
uv_symmetry_transforms_path = tf.resource_loader.get_path_to_datafile(os.path.join(path, '..', 'dataset_tools', 'densepose', 'UV_symmetry_transforms.mat'))
tf.logging.info('Loading DensePose symmetry transforms file from {}'.form... | Class responsible for horizontal flipping of parts and surface coords. | DensePoseHorizontalFlip | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DensePoseHorizontalFlip:
"""Class responsible for horizontal flipping of parts and surface coords."""
def __init__(self):
"""Constructor."""
<|body_0|>
def flip_parts_and_coords(self, part_ids, vu):
"""Flips part ids and coordinates. Args: part_ids: a [num_instan... | stack_v2_sparse_classes_36k_train_026166 | 16,315 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Flips part ids and coordinates. Args: part_ids: a [num_instances, num_points] int32 tensor with pre-flipped part ids. These part_ids are 0-indexed, where the first non-background part has inde... | 2 | stack_v2_sparse_classes_30k_test_001126 | Implement the Python class `DensePoseHorizontalFlip` described below.
Class description:
Class responsible for horizontal flipping of parts and surface coords.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def flip_parts_and_coords(self, part_ids, vu): Flips part ids and coordinates. Args: pa... | Implement the Python class `DensePoseHorizontalFlip` described below.
Class description:
Class responsible for horizontal flipping of parts and surface coords.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def flip_parts_and_coords(self, part_ids, vu): Flips part ids and coordinates. Args: pa... | 06531dae14365986c86baf735fd149317f4bb67a | <|skeleton|>
class DensePoseHorizontalFlip:
"""Class responsible for horizontal flipping of parts and surface coords."""
def __init__(self):
"""Constructor."""
<|body_0|>
def flip_parts_and_coords(self, part_ids, vu):
"""Flips part ids and coordinates. Args: part_ids: a [num_instan... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DensePoseHorizontalFlip:
"""Class responsible for horizontal flipping of parts and surface coords."""
def __init__(self):
"""Constructor."""
path = os.path.dirname(os.path.abspath(__file__))
uv_symmetry_transforms_path = tf.resource_loader.get_path_to_datafile(os.path.join(path, '... | the_stack_v2_python_sparse | inference_api/src/main/object_detection/core/densepose_ops.py | BMW-InnovationLab/BMW-TensorFlow-Training-GUI | train | 1,030 |
f17007e4c40668705dee89d3b8a301a95f8e9a82 | [
"set_map, result = (list(), list())\nfor str in strs:\n ss = list(str)\n ss.sort()\n flag = False\n for i, value in enumerate(set_map):\n if value == ss:\n result[i].append(str)\n flag = True\n break\n if not flag:\n set_map.append(ss)\n result.ap... | <|body_start_0|>
set_map, result = (list(), list())
for str in strs:
ss = list(str)
ss.sort()
flag = False
for i, value in enumerate(set_map):
if value == ss:
result[i].append(str)
flag = True
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def groupAnagrams(self, strs):
""":type strs: List[str] :rtype: List[List[str]] 时间击败8.57%，内存击败8.57%"""
<|body_0|>
def groupAnagrams1(self, strs):
""":type strs: List[str] :rtype: List[List[str]] 排序 由于互为变位词的两个字符串包含的字母相同，因此对两个字符串分别进行排序之后得到的字符串一定是相同的，故可以将排序之后的... | stack_v2_sparse_classes_36k_train_026167 | 2,910 | no_license | [
{
"docstring": ":type strs: List[str] :rtype: List[List[str]] 时间击败8.57%，内存击败8.57%",
"name": "groupAnagrams",
"signature": "def groupAnagrams(self, strs)"
},
{
"docstring": ":type strs: List[str] :rtype: List[List[str]] 排序 由于互为变位词的两个字符串包含的字母相同，因此对两个字符串分别进行排序之后得到的字符串一定是相同的，故可以将排序之后的字符串作为哈希表的键。 时间击... | 3 | stack_v2_sparse_classes_30k_train_009448 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams(self, strs): :type strs: List[str] :rtype: List[List[str]] 时间击败8.57%，内存击败8.57%
- def groupAnagrams1(self, strs): :type strs: List[str] :rtype: List[List[str]] 排... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams(self, strs): :type strs: List[str] :rtype: List[List[str]] 时间击败8.57%，内存击败8.57%
- def groupAnagrams1(self, strs): :type strs: List[str] :rtype: List[List[str]] 排... | 2dc982e690b153c33bc7e27a63604f754a0df90c | <|skeleton|>
class Solution:
def groupAnagrams(self, strs):
""":type strs: List[str] :rtype: List[List[str]] 时间击败8.57%，内存击败8.57%"""
<|body_0|>
def groupAnagrams1(self, strs):
""":type strs: List[str] :rtype: List[List[str]] 排序 由于互为变位词的两个字符串包含的字母相同，因此对两个字符串分别进行排序之后得到的字符串一定是相同的，故可以将排序之后的... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def groupAnagrams(self, strs):
""":type strs: List[str] :rtype: List[List[str]] 时间击败8.57%，内存击败8.57%"""
set_map, result = (list(), list())
for str in strs:
ss = list(str)
ss.sort()
flag = False
for i, value in enumerate(set_map):... | the_stack_v2_python_sparse | 10.02.group-anagrams-lcci.py | 95275059/Algorithm | train | 0 | |
b06471ea69e977aab902665a64e7f390d9545e29 | [
"self._x = x\nself._y = y\nself._r = r\nself._visible = False\nself._color = color",
"t.pencolor(color)\nt.up()\nt.setpos(self._x, self._y - self._r)\nt.down()\nt.circle(self._r)\nt.up()",
"if not self._visible:\n self._visible = True\n self._draw(self._color)",
"if self._visible:\n self._visible = F... | <|body_start_0|>
self._x = x
self._y = y
self._r = r
self._visible = False
self._color = color
<|end_body_0|>
<|body_start_1|>
t.pencolor(color)
t.up()
t.setpos(self._x, self._y - self._r)
t.down()
t.circle(self._r)
t.up()
<|end_bo... | Клас Коло | Circle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Circle:
"""Клас Коло"""
def __init__(self, x, y, r, color):
"""Конструктор Ініціалізує положення кола, його радіус і колір :param x: координата x центру кола :param y: координата y центру кола :param r: радіус кола :param color: колір кола"""
<|body_0|>
def _draw(self, c... | stack_v2_sparse_classes_36k_train_026168 | 2,288 | no_license | [
{
"docstring": "Конструктор Ініціалізує положення кола, його радіус і колір :param x: координата x центру кола :param y: координата y центру кола :param r: радіус кола :param color: колір кола",
"name": "__init__",
"signature": "def __init__(self, x, y, r, color)"
},
{
"docstring": "Допоміжний м... | 5 | stack_v2_sparse_classes_30k_train_021447 | Implement the Python class `Circle` described below.
Class description:
Клас Коло
Method signatures and docstrings:
- def __init__(self, x, y, r, color): Конструктор Ініціалізує положення кола, його радіус і колір :param x: координата x центру кола :param y: координата y центру кола :param r: радіус кола :param color... | Implement the Python class `Circle` described below.
Class description:
Клас Коло
Method signatures and docstrings:
- def __init__(self, x, y, r, color): Конструктор Ініціалізує положення кола, його радіус і колір :param x: координата x центру кола :param y: координата y центру кола :param r: радіус кола :param color... | cb3acb5547659cc52e7e5d99dded7dee2992a56c | <|skeleton|>
class Circle:
"""Клас Коло"""
def __init__(self, x, y, r, color):
"""Конструктор Ініціалізує положення кола, його радіус і колір :param x: координата x центру кола :param y: координата y центру кола :param r: радіус кола :param color: колір кола"""
<|body_0|>
def _draw(self, c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Circle:
"""Клас Коло"""
def __init__(self, x, y, r, color):
"""Конструктор Ініціалізує положення кола, його радіус і колір :param x: координата x центру кола :param y: координата y центру кола :param r: радіус кола :param color: колір кола"""
self._x = x
self._y = y
self._... | the_stack_v2_python_sparse | source/P_01/L14_turtle_Сircle .py | krenevych/oop | train | 4 |
c2819ce3fed42b7ac39af9b2f25cd5695d5b7a39 | [
"l, r = (0, 0)\nmax_len = 0\nlen_s = len(s)\nfor i in range(len_s):\n if s[i] == '(':\n l += 1\n else:\n r += 1\n if l == r:\n max_len = max(max_len, 2 * r)\n elif r > l:\n l = r = 0\nl = r = 0\nfor i in range(len_s - 1, -1, -1):\n if s[i] == '(':\n l += 1\n else... | <|body_start_0|>
l, r = (0, 0)
max_len = 0
len_s = len(s)
for i in range(len_s):
if s[i] == '(':
l += 1
else:
r += 1
if l == r:
max_len = max(max_len, 2 * r)
elif r > l:
l = r ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestValidParentheses1(self, s: str) -> int:
"""执行用时： 68 ms , 在所有 Python3 提交中击败了 15.72% 的用户 内存消耗： 15 MB , 在所有 Python3 提交中击败了 81.39% 的用户"""
<|body_0|>
def longestValidParentheses(self, s: str) -> int:
"""执行用时： 76 ms , 在所有 Python3 提交中击败了 7.61% 的用户 内存消耗：... | stack_v2_sparse_classes_36k_train_026169 | 3,080 | no_license | [
{
"docstring": "执行用时： 68 ms , 在所有 Python3 提交中击败了 15.72% 的用户 内存消耗： 15 MB , 在所有 Python3 提交中击败了 81.39% 的用户",
"name": "longestValidParentheses1",
"signature": "def longestValidParentheses1(self, s: str) -> int"
},
{
"docstring": "执行用时： 76 ms , 在所有 Python3 提交中击败了 7.61% 的用户 内存消耗： 15.4 MB , 在所有 Python3... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestValidParentheses1(self, s: str) -> int: 执行用时： 68 ms , 在所有 Python3 提交中击败了 15.72% 的用户 内存消耗： 15 MB , 在所有 Python3 提交中击败了 81.39% 的用户
- def longestValidParentheses(self, s: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestValidParentheses1(self, s: str) -> int: 执行用时： 68 ms , 在所有 Python3 提交中击败了 15.72% 的用户 内存消耗： 15 MB , 在所有 Python3 提交中击败了 81.39% 的用户
- def longestValidParentheses(self, s: ... | d613ed8a5a2c15ace7d513965b372d128845d66a | <|skeleton|>
class Solution:
def longestValidParentheses1(self, s: str) -> int:
"""执行用时： 68 ms , 在所有 Python3 提交中击败了 15.72% 的用户 内存消耗： 15 MB , 在所有 Python3 提交中击败了 81.39% 的用户"""
<|body_0|>
def longestValidParentheses(self, s: str) -> int:
"""执行用时： 76 ms , 在所有 Python3 提交中击败了 7.61% 的用户 内存消耗：... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestValidParentheses1(self, s: str) -> int:
"""执行用时： 68 ms , 在所有 Python3 提交中击败了 15.72% 的用户 内存消耗： 15 MB , 在所有 Python3 提交中击败了 81.39% 的用户"""
l, r = (0, 0)
max_len = 0
len_s = len(s)
for i in range(len_s):
if s[i] == '(':
l += 1
... | the_stack_v2_python_sparse | 最长有效括号.py | nomboy/leetcode | train | 0 | |
041d858ee08c418eb48215abc95cf8e83e8c30cb | [
"try:\n log.info('%s %r' % (request.remote_addr, request))\n users = ModelOperations.user_list()\n if not users:\n response = jsonify(users=[])\n response.status_code = 404\n return response\n response = [{'id': user[0], 'username': user[1], 'created': user[2]} for user in users]\n ... | <|body_start_0|>
try:
log.info('%s %r' % (request.remote_addr, request))
users = ModelOperations.user_list()
if not users:
response = jsonify(users=[])
response.status_code = 404
return response
response = [{'id': us... | Handles API users | ApiUserList | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApiUserList:
"""Handles API users"""
def get(self):
"""Get List of users. :return:"""
<|body_0|>
def post(self):
"""Creates a new user. New user requires a valid username and password. Password is clear text. API uses HTTPS hence password should be unreadable if ... | stack_v2_sparse_classes_36k_train_026170 | 23,973 | permissive | [
{
"docstring": "Get List of users. :return:",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Creates a new user. New user requires a valid username and password. Password is clear text. API uses HTTPS hence password should be unreadable if intercepted. :return:",
"name": "pos... | 2 | stack_v2_sparse_classes_30k_train_017201 | Implement the Python class `ApiUserList` described below.
Class description:
Handles API users
Method signatures and docstrings:
- def get(self): Get List of users. :return:
- def post(self): Creates a new user. New user requires a valid username and password. Password is clear text. API uses HTTPS hence password sho... | Implement the Python class `ApiUserList` described below.
Class description:
Handles API users
Method signatures and docstrings:
- def get(self): Get List of users. :return:
- def post(self): Creates a new user. New user requires a valid username and password. Password is clear text. API uses HTTPS hence password sho... | c27812e6b846eb1e28ec0c6e8508e18886e37617 | <|skeleton|>
class ApiUserList:
"""Handles API users"""
def get(self):
"""Get List of users. :return:"""
<|body_0|>
def post(self):
"""Creates a new user. New user requires a valid username and password. Password is clear text. API uses HTTPS hence password should be unreadable if ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ApiUserList:
"""Handles API users"""
def get(self):
"""Get List of users. :return:"""
try:
log.info('%s %r' % (request.remote_addr, request))
users = ModelOperations.user_list()
if not users:
response = jsonify(users=[])
... | the_stack_v2_python_sparse | api/version1_0/application/api_main.py | gogasca/news_ml | train | 4 |
108f43c66759048a97dae04fec1ee194899ac6f6 | [
"param_names = ['C10', 'C01', 'D1']\nself.params = {}\nfor param_name in param_names:\n value = parameters.pop(param_name, 0.0)\n self.params[param_name] = value\nif parameters:\n unused = ', '.join(parameters.keys())\n logger.warning('Unused parameters: {0}'.format(unused))\nC10 = self.params['C10']\nC... | <|body_start_0|>
param_names = ['C10', 'C01', 'D1']
self.params = {}
for param_name in param_names:
value = parameters.pop(param_name, 0.0)
self.params[param_name] = value
if parameters:
unused = ', '.join(parameters.keys())
logger.warning(... | MooneyRivlinMaterial | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MooneyRivlinMaterial:
def __init__(self, **parameters):
"""Set up the Mooney Rivlin material"""
<|body_0|>
def eval(self, time, dtime, temp, dtemp, F0, F, stran, d, stress, statev, **kwargs):
"""Compute updated stress given the updated deformation"""
<|body_1... | stack_v2_sparse_classes_36k_train_026171 | 2,427 | permissive | [
{
"docstring": "Set up the Mooney Rivlin material",
"name": "__init__",
"signature": "def __init__(self, **parameters)"
},
{
"docstring": "Compute updated stress given the updated deformation",
"name": "eval",
"signature": "def eval(self, time, dtime, temp, dtemp, F0, F, stran, d, stress... | 2 | stack_v2_sparse_classes_30k_train_013691 | Implement the Python class `MooneyRivlinMaterial` described below.
Class description:
Implement the MooneyRivlinMaterial class.
Method signatures and docstrings:
- def __init__(self, **parameters): Set up the Mooney Rivlin material
- def eval(self, time, dtime, temp, dtemp, F0, F, stran, d, stress, statev, **kwargs):... | Implement the Python class `MooneyRivlinMaterial` described below.
Class description:
Implement the MooneyRivlinMaterial class.
Method signatures and docstrings:
- def __init__(self, **parameters): Set up the Mooney Rivlin material
- def eval(self, time, dtime, temp, dtemp, F0, F, stran, d, stress, statev, **kwargs):... | e411b010eead10d74825589ba94ab5e99368acef | <|skeleton|>
class MooneyRivlinMaterial:
def __init__(self, **parameters):
"""Set up the Mooney Rivlin material"""
<|body_0|>
def eval(self, time, dtime, temp, dtemp, F0, F, stran, d, stress, statev, **kwargs):
"""Compute updated stress given the updated deformation"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MooneyRivlinMaterial:
def __init__(self, **parameters):
"""Set up the Mooney Rivlin material"""
param_names = ['C10', 'C01', 'D1']
self.params = {}
for param_name in param_names:
value = parameters.pop(param_name, 0.0)
self.params[param_name] = value
... | the_stack_v2_python_sparse | matmodlab2/materials/mooney_rivlin.py | matmodlab/matmodlab2 | train | 9 | |
cd79eb3b9adb66ee678f9d9a265e40d9de3a57ea | [
"nums = first_line(filename)\nfor _ in range(40):\n nums = expand(nums)\nreturn len(nums)",
"nums = first_line(filename)\nfor _ in range(50):\n nums = expand(nums)\nreturn len(nums)"
] | <|body_start_0|>
nums = first_line(filename)
for _ in range(40):
nums = expand(nums)
return len(nums)
<|end_body_0|>
<|body_start_1|>
nums = first_line(filename)
for _ in range(50):
nums = expand(nums)
return len(nums)
<|end_body_1|>
| AoC 2015 Day 10 | Day10 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Day10:
"""AoC 2015 Day 10"""
def part1(filename: str) -> int:
"""Given a filename, solve 2015 day 10 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2015 day 10 part 2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_026172 | 947 | no_license | [
{
"docstring": "Given a filename, solve 2015 day 10 part 1",
"name": "part1",
"signature": "def part1(filename: str) -> int"
},
{
"docstring": "Given a filename, solve 2015 day 10 part 2",
"name": "part2",
"signature": "def part2(filename: str) -> int"
}
] | 2 | null | Implement the Python class `Day10` described below.
Class description:
AoC 2015 Day 10
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2015 day 10 part 1
- def part2(filename: str) -> int: Given a filename, solve 2015 day 10 part 2 | Implement the Python class `Day10` described below.
Class description:
AoC 2015 Day 10
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2015 day 10 part 1
- def part2(filename: str) -> int: Given a filename, solve 2015 day 10 part 2
<|skeleton|>
class Day10:
"""AoC 201... | e89db235837d2d05848210a18c9c2a4456085570 | <|skeleton|>
class Day10:
"""AoC 2015 Day 10"""
def part1(filename: str) -> int:
"""Given a filename, solve 2015 day 10 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2015 day 10 part 2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Day10:
"""AoC 2015 Day 10"""
def part1(filename: str) -> int:
"""Given a filename, solve 2015 day 10 part 1"""
nums = first_line(filename)
for _ in range(40):
nums = expand(nums)
return len(nums)
def part2(filename: str) -> int:
"""Given a filename... | the_stack_v2_python_sparse | 2015/python2015/aoc/day10.py | mreishus/aoc | train | 16 |
92f51d1ff3cb023652acb0fd95747702c23e4970 | [
"super().__init__()\nself.nlp = load_spacy_lexeme_prob(nlp)\nself.perturb_opts: Union[Dict, None] = perturb_opts\nself.words: List = []\nself.punctuation: List = []\nself.positions: List = []",
"processed = self.nlp(text)\nself.words = [x.text for x in processed]\nself.positions = [x.idx for x in processed]\nself... | <|body_start_0|>
super().__init__()
self.nlp = load_spacy_lexeme_prob(nlp)
self.perturb_opts: Union[Dict, None] = perturb_opts
self.words: List = []
self.punctuation: List = []
self.positions: List = []
<|end_body_0|>
<|body_start_1|>
processed = self.nlp(text)
... | UnknownSampler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnknownSampler:
def __init__(self, nlp: 'spacy.language.Language', perturb_opts: Dict):
"""Initialize unknown sampler. This sampler replaces word with the `UNK` token. Parameters ---------- nlp `spaCy` object. perturb_opts Perturbation options."""
<|body_0|>
def set_text(sel... | stack_v2_sparse_classes_36k_train_026173 | 16,961 | permissive | [
{
"docstring": "Initialize unknown sampler. This sampler replaces word with the `UNK` token. Parameters ---------- nlp `spaCy` object. perturb_opts Perturbation options.",
"name": "__init__",
"signature": "def __init__(self, nlp: 'spacy.language.Language', perturb_opts: Dict)"
},
{
"docstring": ... | 4 | null | Implement the Python class `UnknownSampler` described below.
Class description:
Implement the UnknownSampler class.
Method signatures and docstrings:
- def __init__(self, nlp: 'spacy.language.Language', perturb_opts: Dict): Initialize unknown sampler. This sampler replaces word with the `UNK` token. Parameters ------... | Implement the Python class `UnknownSampler` described below.
Class description:
Implement the UnknownSampler class.
Method signatures and docstrings:
- def __init__(self, nlp: 'spacy.language.Language', perturb_opts: Dict): Initialize unknown sampler. This sampler replaces word with the `UNK` token. Parameters ------... | 54d0c957fb01c7ebba4e2a0d28fcbde52d9c6718 | <|skeleton|>
class UnknownSampler:
def __init__(self, nlp: 'spacy.language.Language', perturb_opts: Dict):
"""Initialize unknown sampler. This sampler replaces word with the `UNK` token. Parameters ---------- nlp `spaCy` object. perturb_opts Perturbation options."""
<|body_0|>
def set_text(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UnknownSampler:
def __init__(self, nlp: 'spacy.language.Language', perturb_opts: Dict):
"""Initialize unknown sampler. This sampler replaces word with the `UNK` token. Parameters ---------- nlp `spaCy` object. perturb_opts Perturbation options."""
super().__init__()
self.nlp = load_spa... | the_stack_v2_python_sparse | alibi/explainers/anchors/text_samplers.py | SeldonIO/alibi | train | 2,143 | |
c34a9956a5c34457a5a84eb44044219751221ea4 | [
"graph_def = sess.graph_def\ntoco_flags = toco_flags_pb2.TocoFlags()\ntoco_flags.input_format = toco_flags_pb2.TENSORFLOW_GRAPHDEF\ntoco_flags.output_format = toco_flags_pb2.TFLITE\ntoco_flags.inference_input_type = types_pb2.FLOAT\ntoco_flags.inference_type = types_pb2.FLOAT\ntoco_flags.allow_custom_ops = True\nmo... | <|body_start_0|>
graph_def = sess.graph_def
toco_flags = toco_flags_pb2.TocoFlags()
toco_flags.input_format = toco_flags_pb2.TENSORFLOW_GRAPHDEF
toco_flags.output_format = toco_flags_pb2.TFLITE
toco_flags.inference_input_type = types_pb2.FLOAT
toco_flags.inference_type = ... | TocoFromProtosTest | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TocoFromProtosTest:
def _run(self, sess, in_tensor, out_tensor, should_succeed):
"""Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow session containing graph. in_tensor: TensorFlow tensor to use as input. out_tensor: TensorFlow tensor to use as o... | stack_v2_sparse_classes_36k_train_026174 | 3,767 | permissive | [
{
"docstring": "Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow session containing graph. in_tensor: TensorFlow tensor to use as input. out_tensor: TensorFlow tensor to use as output. should_succeed: Whether this is a valid conversion.",
"name": "_run",
"signat... | 2 | stack_v2_sparse_classes_30k_train_002288 | Implement the Python class `TocoFromProtosTest` described below.
Class description:
Implement the TocoFromProtosTest class.
Method signatures and docstrings:
- def _run(self, sess, in_tensor, out_tensor, should_succeed): Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow sessio... | Implement the Python class `TocoFromProtosTest` described below.
Class description:
Implement the TocoFromProtosTest class.
Method signatures and docstrings:
- def _run(self, sess, in_tensor, out_tensor, should_succeed): Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow sessio... | a7f3934a67900720af3d3b15389551483bee50b8 | <|skeleton|>
class TocoFromProtosTest:
def _run(self, sess, in_tensor, out_tensor, should_succeed):
"""Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow session containing graph. in_tensor: TensorFlow tensor to use as input. out_tensor: TensorFlow tensor to use as o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TocoFromProtosTest:
def _run(self, sess, in_tensor, out_tensor, should_succeed):
"""Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow session containing graph. in_tensor: TensorFlow tensor to use as input. out_tensor: TensorFlow tensor to use as output. should_... | the_stack_v2_python_sparse | tensorflow/lite/toco/python/toco_from_protos_test.py | tensorflow/tensorflow | train | 208,740 | |
1db500821af8f97a36c71e60c3941f935c34e839 | [
"resource = Monitor_Resource()\nresource.ip = ip\nresource.process_isalive = process_isalive\nresource.process_cpu_use = process_cpu_use\nresource.process_mem_use = process_mem_use\nresource.cpu_total_use = cpu_total_use\nresource.mem_free = mem_free\nresource.disk_read = disk_read\nresource.disk_write = disk_write... | <|body_start_0|>
resource = Monitor_Resource()
resource.ip = ip
resource.process_isalive = process_isalive
resource.process_cpu_use = process_cpu_use
resource.process_mem_use = process_mem_use
resource.cpu_total_use = cpu_total_use
resource.mem_free = mem_free
... | Monitor_Resource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Monitor_Resource:
def create_or_replace(cls, ip, process_isalive, process_cpu_use, process_mem_use, cpu_total_use, mem_free, disk_read, disk_write, network_upload, network_download, volume):
"""发现一台新主机的监控资源 :param ip: ip地址 :param process_isalive: 进程是否存在 :param process_cpu_use: 进程的cpu使用情况... | stack_v2_sparse_classes_36k_train_026175 | 13,402 | no_license | [
{
"docstring": "发现一台新主机的监控资源 :param ip: ip地址 :param process_isalive: 进程是否存在 :param process_cpu_use: 进程的cpu使用情况 :param process_mem_use: 进程的内存使用情况 :param cpu_total_use: 总cpu使用率 :param mem_free: 内存可用量 :param disk_read: 磁盘读 :param disk_write: 磁盘写 :param network_upload: 网络上传 :param network_download: 网络下载 :param volu... | 2 | stack_v2_sparse_classes_30k_train_003174 | Implement the Python class `Monitor_Resource` described below.
Class description:
Implement the Monitor_Resource class.
Method signatures and docstrings:
- def create_or_replace(cls, ip, process_isalive, process_cpu_use, process_mem_use, cpu_total_use, mem_free, disk_read, disk_write, network_upload, network_download... | Implement the Python class `Monitor_Resource` described below.
Class description:
Implement the Monitor_Resource class.
Method signatures and docstrings:
- def create_or_replace(cls, ip, process_isalive, process_cpu_use, process_mem_use, cpu_total_use, mem_free, disk_read, disk_write, network_upload, network_download... | 4febccac57bfa5f7ef46f5f57e52206c8b0a57ac | <|skeleton|>
class Monitor_Resource:
def create_or_replace(cls, ip, process_isalive, process_cpu_use, process_mem_use, cpu_total_use, mem_free, disk_read, disk_write, network_upload, network_download, volume):
"""发现一台新主机的监控资源 :param ip: ip地址 :param process_isalive: 进程是否存在 :param process_cpu_use: 进程的cpu使用情况... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Monitor_Resource:
def create_or_replace(cls, ip, process_isalive, process_cpu_use, process_mem_use, cpu_total_use, mem_free, disk_read, disk_write, network_upload, network_download, volume):
"""发现一台新主机的监控资源 :param ip: ip地址 :param process_isalive: 进程是否存在 :param process_cpu_use: 进程的cpu使用情况 :param proces... | the_stack_v2_python_sparse | item/dev/cmdb/asset/models.py | soulorman/Python | train | 0 | |
4481388672ccf9ad4b8b0fa70b1840565dbc2bb5 | [
"if not nums:\n return 0\nn = len(nums)\nif n < 3:\n return 0\nret = {}\nnums.sort()\nfor i in range(n):\n left, right = (i + 1, n - 1)\n while left < right:\n sums = nums[i] + nums[left] + nums[right]\n dist = abs(target - sums)\n ret[sums] = dist\n if sums == target:\n ... | <|body_start_0|>
if not nums:
return 0
n = len(nums)
if n < 3:
return 0
ret = {}
nums.sort()
for i in range(n):
left, right = (i + 1, n - 1)
while left < right:
sums = nums[i] + nums[left] + nums[right]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeSumClosest(self, nums: list, target: int) -> int:
"""类似三数之和的解法 用字典保存每次的三数之和以及和target的距离(绝对值) 再将字典排序，得到结果"""
<|body_0|>
def threeSumClosest_2(self, nums: list, target: int) -> int:
"""1. 若nums的长度 n < 3，则直接返回 2. 将nums排序，并定义res为无穷大，表示最小距离的和 3. 定义left，... | stack_v2_sparse_classes_36k_train_026176 | 2,755 | no_license | [
{
"docstring": "类似三数之和的解法 用字典保存每次的三数之和以及和target的距离(绝对值) 再将字典排序，得到结果",
"name": "threeSumClosest",
"signature": "def threeSumClosest(self, nums: list, target: int) -> int"
},
{
"docstring": "1. 若nums的长度 n < 3，则直接返回 2. 将nums排序，并定义res为无穷大，表示最小距离的和 3. 定义left，right分别表示三数中的第二个数和第三个数，其中left = i + 1, rig... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSumClosest(self, nums: list, target: int) -> int: 类似三数之和的解法 用字典保存每次的三数之和以及和target的距离(绝对值) 再将字典排序，得到结果
- def threeSumClosest_2(self, nums: list, target: int) -> int: 1. 若... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSumClosest(self, nums: list, target: int) -> int: 类似三数之和的解法 用字典保存每次的三数之和以及和target的距离(绝对值) 再将字典排序，得到结果
- def threeSumClosest_2(self, nums: list, target: int) -> int: 1. 若... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def threeSumClosest(self, nums: list, target: int) -> int:
"""类似三数之和的解法 用字典保存每次的三数之和以及和target的距离(绝对值) 再将字典排序，得到结果"""
<|body_0|>
def threeSumClosest_2(self, nums: list, target: int) -> int:
"""1. 若nums的长度 n < 3，则直接返回 2. 将nums排序，并定义res为无穷大，表示最小距离的和 3. 定义left，... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def threeSumClosest(self, nums: list, target: int) -> int:
"""类似三数之和的解法 用字典保存每次的三数之和以及和target的距离(绝对值) 再将字典排序，得到结果"""
if not nums:
return 0
n = len(nums)
if n < 3:
return 0
ret = {}
nums.sort()
for i in range(n):
... | the_stack_v2_python_sparse | algorithm/leetcode/list/12-最接近的三数之和.py | lxconfig/UbuntuCode_bak | train | 0 | |
fe9d6b3c6340af4d67c5e5e7e1c01e05b1d52a01 | [
"if len(nums) <= 0:\n return nums\nres = []\nfor i in range(len(nums) - k + 1):\n window = nums[i:i + k]\n window = sorted(window)\n if k % 2 == 1:\n res.append(window[k / 2])\n else:\n res.append((window[(k - 1) / 2] + window[k / 2]) / 2)\nreturn res",
"res = []\nimport bisect\nif le... | <|body_start_0|>
if len(nums) <= 0:
return nums
res = []
for i in range(len(nums) - k + 1):
window = nums[i:i + k]
window = sorted(window)
if k % 2 == 1:
res.append(window[k / 2])
else:
res.append((window... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def medianSlidingWindow_fore_brute(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[float]"""
<|body_0|>
def medianSlidingWindow(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[float]"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_026177 | 1,322 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: List[float]",
"name": "medianSlidingWindow_fore_brute",
"signature": "def medianSlidingWindow_fore_brute(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: List[float]",
"name": "medianSlidingWindow",
"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def medianSlidingWindow_fore_brute(self, nums, k): :type nums: List[int] :type k: int :rtype: List[float]
- def medianSlidingWindow(self, nums, k): :type nums: List[int] :type k:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def medianSlidingWindow_fore_brute(self, nums, k): :type nums: List[int] :type k: int :rtype: List[float]
- def medianSlidingWindow(self, nums, k): :type nums: List[int] :type k:... | 176cc1db3291843fb068f06d0180766dd8c3122c | <|skeleton|>
class Solution:
def medianSlidingWindow_fore_brute(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[float]"""
<|body_0|>
def medianSlidingWindow(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[float]"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def medianSlidingWindow_fore_brute(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[float]"""
if len(nums) <= 0:
return nums
res = []
for i in range(len(nums) - k + 1):
window = nums[i:i + k]
window = sorted(window... | the_stack_v2_python_sparse | 2019/sliding_window/sliding_window_median_480.py | yehongyu/acode | train | 0 | |
1c4e2fd34033973c51d13e82d5ea3f5609ce3716 | [
"category = EnvironmentType.objects.all()\nserializer = EnvironmentTypeSerializer(category, many=True)\nreturn Response(serializer.data)",
"serializer = EnvironmentTypeSerializer(data=request.data)\nif serializer.is_valid():\n serializer.save()\n return Response(serializer.data, status=status.HTTP_201_CREAT... | <|body_start_0|>
category = EnvironmentType.objects.all()
serializer = EnvironmentTypeSerializer(category, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
serializer = EnvironmentTypeSerializer(data=request.data)
if serializer.is_valid():
... | List all EnvironmentType, or create a new EnvironmentType. | EnvironmentTypeList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnvironmentTypeList:
"""List all EnvironmentType, or create a new EnvironmentType."""
def get(self, request, format=None):
"""The default get method, i.e on page load"""
<|body_0|>
def post(self, request, format=None):
"""The default post method."""
<|bod... | stack_v2_sparse_classes_36k_train_026178 | 15,222 | permissive | [
{
"docstring": "The default get method, i.e on page load",
"name": "get",
"signature": "def get(self, request, format=None)"
},
{
"docstring": "The default post method.",
"name": "post",
"signature": "def post(self, request, format=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005518 | Implement the Python class `EnvironmentTypeList` described below.
Class description:
List all EnvironmentType, or create a new EnvironmentType.
Method signatures and docstrings:
- def get(self, request, format=None): The default get method, i.e on page load
- def post(self, request, format=None): The default post met... | Implement the Python class `EnvironmentTypeList` described below.
Class description:
List all EnvironmentType, or create a new EnvironmentType.
Method signatures and docstrings:
- def get(self, request, format=None): The default get method, i.e on page load
- def post(self, request, format=None): The default post met... | b0635e72338e14dad24f1ee0329212cd60a3e83a | <|skeleton|>
class EnvironmentTypeList:
"""List all EnvironmentType, or create a new EnvironmentType."""
def get(self, request, format=None):
"""The default get method, i.e on page load"""
<|body_0|>
def post(self, request, format=None):
"""The default post method."""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnvironmentTypeList:
"""List all EnvironmentType, or create a new EnvironmentType."""
def get(self, request, format=None):
"""The default get method, i.e on page load"""
category = EnvironmentType.objects.all()
serializer = EnvironmentTypeSerializer(category, many=True)
re... | the_stack_v2_python_sparse | environment/views.py | faisaltheparttimecoder/carelogBackend | train | 1 |
f5b546f2a15477fab799579cc7dd514f283b001d | [
"if component_config:\n return False\nreturn isinstance(component_executor_spec, executor_spec.ExecutorClassSpec)",
"executor_class_spec = cast(executor_spec.ExecutorClassSpec, self._component_executor_spec)\nif issubclass(executor_class_spec.executor_class, base_beam_executor.BaseBeamExecutor):\n executor_... | <|body_start_0|>
if component_config:
return False
return isinstance(component_executor_spec, executor_spec.ExecutorClassSpec)
<|end_body_0|>
<|body_start_1|>
executor_class_spec = cast(executor_spec.ExecutorClassSpec, self._component_executor_spec)
if issubclass(executor_cl... | Responsible for launching a python executor. The executor will be launched in the same process of the rest of the component, i.e. its driver and publisher. | InProcessComponentLauncher | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InProcessComponentLauncher:
"""Responsible for launching a python executor. The executor will be launched in the same process of the rest of the component, i.e. its driver and publisher."""
def can_launch(cls, component_executor_spec: executor_spec.ExecutorSpec, component_config: base_compon... | stack_v2_sparse_classes_36k_train_026179 | 3,187 | permissive | [
{
"docstring": "Checks if the launcher can launch the executor spec.",
"name": "can_launch",
"signature": "def can_launch(cls, component_executor_spec: executor_spec.ExecutorSpec, component_config: base_component_config.BaseComponentConfig) -> bool"
},
{
"docstring": "Execute underlying componen... | 2 | stack_v2_sparse_classes_30k_train_000210 | Implement the Python class `InProcessComponentLauncher` described below.
Class description:
Responsible for launching a python executor. The executor will be launched in the same process of the rest of the component, i.e. its driver and publisher.
Method signatures and docstrings:
- def can_launch(cls, component_exec... | Implement the Python class `InProcessComponentLauncher` described below.
Class description:
Responsible for launching a python executor. The executor will be launched in the same process of the rest of the component, i.e. its driver and publisher.
Method signatures and docstrings:
- def can_launch(cls, component_exec... | 1b328504fa08a70388691e4072df76f143631325 | <|skeleton|>
class InProcessComponentLauncher:
"""Responsible for launching a python executor. The executor will be launched in the same process of the rest of the component, i.e. its driver and publisher."""
def can_launch(cls, component_executor_spec: executor_spec.ExecutorSpec, component_config: base_compon... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InProcessComponentLauncher:
"""Responsible for launching a python executor. The executor will be launched in the same process of the rest of the component, i.e. its driver and publisher."""
def can_launch(cls, component_executor_spec: executor_spec.ExecutorSpec, component_config: base_component_config.Ba... | the_stack_v2_python_sparse | tfx/orchestration/launcher/in_process_component_launcher.py | tensorflow/tfx | train | 2,116 |
90b61c67022ddea582804ac8952d825dac68f539 | [
"items = []\nfilter_shared = request.GET.get('filter_shared', False)\nif request.GET.get('all_projects') == 'true':\n result = api.neutron.network_list(request, **request.GET)\n rest_utils.ensure_tenant_name(request, result)\n for item in result:\n item_dict = item.to_dict()\n if hasattr(item... | <|body_start_0|>
items = []
filter_shared = request.GET.get('filter_shared', False)
if request.GET.get('all_projects') == 'true':
result = api.neutron.network_list(request, **request.GET)
rest_utils.ensure_tenant_name(request, result)
for item in result:
... | API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html | Networks | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Networks:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of networks for a project The listing result is an object with property "items". Each item is a network."""
<|body_0|>
def post(self, ... | stack_v2_sparse_classes_36k_train_026180 | 30,067 | permissive | [
{
"docstring": "Get a list of networks for a project The listing result is an object with property \"items\". Each item is a network.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Create a network :param admin_state_up (optional): The administrative state of the netwo... | 2 | null | Implement the Python class `Networks` described below.
Class description:
API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html
Method signatures and docstrings:
- def get(self, request): Get a list of networks for a project The listing result is an object with property "items". Each item... | Implement the Python class `Networks` described below.
Class description:
API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html
Method signatures and docstrings:
- def get(self, request): Get a list of networks for a project The listing result is an object with property "items". Each item... | 9524f1952461c83db485d5d1702c350b158d7ce0 | <|skeleton|>
class Networks:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of networks for a project The listing result is an object with property "items". Each item is a network."""
<|body_0|>
def post(self, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Networks:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of networks for a project The listing result is an object with property "items". Each item is a network."""
items = []
filter_shared = request.G... | the_stack_v2_python_sparse | easystack_dashboard/api/rest/neutron.py | oksbsb/horizon-acc | train | 0 |
cd09f000df2d924d535ca44d285ec780068ab9a2 | [
"self.domain_name = domain_name\nself.encrypted_password = encrypted_password\nself.kdc = kdc\nself.password = password\nself.protocol = protocol\nself.username = username",
"if dictionary is None:\n return None\ndomain_name = dictionary.get('domainName')\nencrypted_password = dictionary.get('encryptedPassword... | <|body_start_0|>
self.domain_name = domain_name
self.encrypted_password = encrypted_password
self.kdc = kdc
self.password = password
self.protocol = protocol
self.username = username
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
... | Implementation of the 'NasMountCredentials' model. TODO: type description here. Attributes: domain_name (string): The name of the domain which the NAS mount credentials belong to. encrypted_password (list of long|int): AES256 encrypted password. The key for encryption should be obtained from KMS. kdc (string): KDC host... | NasMountCredentials | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NasMountCredentials:
"""Implementation of the 'NasMountCredentials' model. TODO: type description here. Attributes: domain_name (string): The name of the domain which the NAS mount credentials belong to. encrypted_password (list of long|int): AES256 encrypted password. The key for encryption shou... | stack_v2_sparse_classes_36k_train_026181 | 2,953 | permissive | [
{
"docstring": "Constructor for the NasMountCredentials class",
"name": "__init__",
"signature": "def __init__(self, domain_name=None, encrypted_password=None, kdc=None, password=None, protocol=None, username=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dic... | 2 | stack_v2_sparse_classes_30k_test_000011 | Implement the Python class `NasMountCredentials` described below.
Class description:
Implementation of the 'NasMountCredentials' model. TODO: type description here. Attributes: domain_name (string): The name of the domain which the NAS mount credentials belong to. encrypted_password (list of long|int): AES256 encrypte... | Implement the Python class `NasMountCredentials` described below.
Class description:
Implementation of the 'NasMountCredentials' model. TODO: type description here. Attributes: domain_name (string): The name of the domain which the NAS mount credentials belong to. encrypted_password (list of long|int): AES256 encrypte... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class NasMountCredentials:
"""Implementation of the 'NasMountCredentials' model. TODO: type description here. Attributes: domain_name (string): The name of the domain which the NAS mount credentials belong to. encrypted_password (list of long|int): AES256 encrypted password. The key for encryption shou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NasMountCredentials:
"""Implementation of the 'NasMountCredentials' model. TODO: type description here. Attributes: domain_name (string): The name of the domain which the NAS mount credentials belong to. encrypted_password (list of long|int): AES256 encrypted password. The key for encryption should be obtaine... | the_stack_v2_python_sparse | cohesity_management_sdk/models/nas_mount_credentials.py | cohesity/management-sdk-python | train | 24 |
161f2a74ca7be6d3a43c2102b9499cdcc129fc8c | [
"super().__init__()\nself.num_atoms = num_atoms\ntau_min = 1 / (2 * self.num_atoms)\ntau_max = 1 - tau_min\nself.tau = torch.linspace(start=tau_min, end=tau_max, steps=self.num_atoms)\nself.criterion = HuberLossV0(clip_delta=clip_delta)",
"atoms_diff = targets[:, None, :] - outputs[:, :, None]\ndelta_atoms_diff =... | <|body_start_0|>
super().__init__()
self.num_atoms = num_atoms
tau_min = 1 / (2 * self.num_atoms)
tau_max = 1 - tau_min
self.tau = torch.linspace(start=tau_min, end=tau_max, steps=self.num_atoms)
self.criterion = HuberLossV0(clip_delta=clip_delta)
<|end_body_0|>
<|body_s... | QuantileRegressionLoss | QuantileRegressionLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuantileRegressionLoss:
"""QuantileRegressionLoss"""
def __init__(self, num_atoms: int=51, clip_delta: float=1.0):
"""Init."""
<|body_0|>
def forward(self, outputs: torch.Tensor, targets: torch.Tensor) -> torch.Tensor:
"""Compute the loss. Args: outputs (torch.Te... | stack_v2_sparse_classes_36k_train_026182 | 4,457 | permissive | [
{
"docstring": "Init.",
"name": "__init__",
"signature": "def __init__(self, num_atoms: int=51, clip_delta: float=1.0)"
},
{
"docstring": "Compute the loss. Args: outputs (torch.Tensor): predicted atoms, shape: [bs; num_atoms] targets (torch.Tensor): target atoms, shape: [bs; num_atoms] Returns:... | 2 | stack_v2_sparse_classes_30k_train_013040 | Implement the Python class `QuantileRegressionLoss` described below.
Class description:
QuantileRegressionLoss
Method signatures and docstrings:
- def __init__(self, num_atoms: int=51, clip_delta: float=1.0): Init.
- def forward(self, outputs: torch.Tensor, targets: torch.Tensor) -> torch.Tensor: Compute the loss. Ar... | Implement the Python class `QuantileRegressionLoss` described below.
Class description:
QuantileRegressionLoss
Method signatures and docstrings:
- def __init__(self, num_atoms: int=51, clip_delta: float=1.0): Init.
- def forward(self, outputs: torch.Tensor, targets: torch.Tensor) -> torch.Tensor: Compute the loss. Ar... | e99f90655d0efcf22559a46e928f0f98c9807ebf | <|skeleton|>
class QuantileRegressionLoss:
"""QuantileRegressionLoss"""
def __init__(self, num_atoms: int=51, clip_delta: float=1.0):
"""Init."""
<|body_0|>
def forward(self, outputs: torch.Tensor, targets: torch.Tensor) -> torch.Tensor:
"""Compute the loss. Args: outputs (torch.Te... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuantileRegressionLoss:
"""QuantileRegressionLoss"""
def __init__(self, num_atoms: int=51, clip_delta: float=1.0):
"""Init."""
super().__init__()
self.num_atoms = num_atoms
tau_min = 1 / (2 * self.num_atoms)
tau_max = 1 - tau_min
self.tau = torch.linspace(s... | the_stack_v2_python_sparse | catalyst/contrib/losses/regression.py | catalyst-team/catalyst | train | 3,038 |
b67a4d96730a71119af965f6afbb0e684fe02e4a | [
"self.subcmd = 'agent'\nself.subcmd_args = []\nself.kwargs = {'color': 'false'}\nself.args = []\npuppet_config = __salt__['cmd.run']('puppet config print --render-as yaml vardir rundir confdir')\nconf = salt.utils.yaml.safe_load(puppet_config)\nself.vardir = conf['vardir']\nself.rundir = conf['rundir']\nself.confdi... | <|body_start_0|>
self.subcmd = 'agent'
self.subcmd_args = []
self.kwargs = {'color': 'false'}
self.args = []
puppet_config = __salt__['cmd.run']('puppet config print --render-as yaml vardir rundir confdir')
conf = salt.utils.yaml.safe_load(puppet_config)
self.vard... | Puppet helper class. Used to format command for execution. | _Puppet | [
"Apache-2.0",
"MIT",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Puppet:
"""Puppet helper class. Used to format command for execution."""
def __init__(self):
"""Setup a puppet instance, based on the premis that default usage is to run 'puppet agent --test'. Configuration and run states are stored in the default locations."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_026183 | 11,161 | permissive | [
{
"docstring": "Setup a puppet instance, based on the premis that default usage is to run 'puppet agent --test'. Configuration and run states are stored in the default locations.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Format the command string to executed usin... | 3 | null | Implement the Python class `_Puppet` described below.
Class description:
Puppet helper class. Used to format command for execution.
Method signatures and docstrings:
- def __init__(self): Setup a puppet instance, based on the premis that default usage is to run 'puppet agent --test'. Configuration and run states are ... | Implement the Python class `_Puppet` described below.
Class description:
Puppet helper class. Used to format command for execution.
Method signatures and docstrings:
- def __init__(self): Setup a puppet instance, based on the premis that default usage is to run 'puppet agent --test'. Configuration and run states are ... | 1ef90cbdc7203f97775edb7666db86a41eb9fc15 | <|skeleton|>
class _Puppet:
"""Puppet helper class. Used to format command for execution."""
def __init__(self):
"""Setup a puppet instance, based on the premis that default usage is to run 'puppet agent --test'. Configuration and run states are stored in the default locations."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _Puppet:
"""Puppet helper class. Used to format command for execution."""
def __init__(self):
"""Setup a puppet instance, based on the premis that default usage is to run 'puppet agent --test'. Configuration and run states are stored in the default locations."""
self.subcmd = 'agent'
... | the_stack_v2_python_sparse | salt/modules/puppet.py | saltstack/salt | train | 11,026 |
00715fd902c00a250461844d54fd9f4cf925c054 | [
"super(File, self).__init__(name, **kwargs)\nself.modulename = modulename\nself.content = content",
"if inline:\n if 'source' in self:\n raise ValueError(\"source tarballs can't be dumped as strings.\")\n if getattr(self, 'content', None) is not None:\n self['content'] = self.content\n ... | <|body_start_0|>
super(File, self).__init__(name, **kwargs)
self.modulename = modulename
self.content = content
<|end_body_0|>
<|body_start_1|>
if inline:
if 'source' in self:
raise ValueError("source tarballs can't be dumped as strings.")
if geta... | Puppet file resource. | File | [
"BSD-2-Clause-Views",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class File:
"""Puppet file resource."""
def __init__(self, name, modulename=None, content=None, **kwargs):
"""File resources handle their content explicitly because in some cases it is not written as a normal parameter."""
<|body_0|>
def dumps(self, inline=False, tab=''):
... | stack_v2_sparse_classes_36k_train_026184 | 20,994 | permissive | [
{
"docstring": "File resources handle their content explicitly because in some cases it is not written as a normal parameter.",
"name": "__init__",
"signature": "def __init__(self, name, modulename=None, content=None, **kwargs)"
},
{
"docstring": "Treat the content as a normal parameter if and o... | 2 | stack_v2_sparse_classes_30k_train_006865 | Implement the Python class `File` described below.
Class description:
Puppet file resource.
Method signatures and docstrings:
- def __init__(self, name, modulename=None, content=None, **kwargs): File resources handle their content explicitly because in some cases it is not written as a normal parameter.
- def dumps(s... | Implement the Python class `File` described below.
Class description:
Puppet file resource.
Method signatures and docstrings:
- def __init__(self, name, modulename=None, content=None, **kwargs): File resources handle their content explicitly because in some cases it is not written as a normal parameter.
- def dumps(s... | dffdcd0792a9c66ec218f0a2baf416292e59afcd | <|skeleton|>
class File:
"""Puppet file resource."""
def __init__(self, name, modulename=None, content=None, **kwargs):
"""File resources handle their content explicitly because in some cases it is not written as a normal parameter."""
<|body_0|>
def dumps(self, inline=False, tab=''):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class File:
"""Puppet file resource."""
def __init__(self, name, modulename=None, content=None, **kwargs):
"""File resources handle their content explicitly because in some cases it is not written as a normal parameter."""
super(File, self).__init__(name, **kwargs)
self.modulename = mod... | the_stack_v2_python_sparse | blueprint/frontend/puppet.py | sarguru/blueprint | train | 1 |
648de80ed7d9efe6f88acab191d01b9e7164cad3 | [
"self.acropolis_params = acropolis_params\nself.app_entity_id_vec = app_entity_id_vec\nself.aws_native_params = aws_native_params\nself.aws_snapshot_manager_params = aws_snapshot_manager_params\nself.gcp_native_params = gcp_native_params\nself.hyperv_params = hyperv_params\nself.oracle_params = oracle_params\nself.... | <|body_start_0|>
self.acropolis_params = acropolis_params
self.app_entity_id_vec = app_entity_id_vec
self.aws_native_params = aws_native_params
self.aws_snapshot_manager_params = aws_snapshot_manager_params
self.gcp_native_params = gcp_native_params
self.hyperv_params = h... | Implementation of the 'BackupSourceParams' model. Message to capture any additional backup params at the source level. Attributes: acropolis_params (AcropolisBackupSourceParams): This is applicable to sources of type kVirtualMachine (kAcropolis environment). app_entity_id_vec (list of long|int): If we are backing up an... | BackupSourceParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BackupSourceParams:
"""Implementation of the 'BackupSourceParams' model. Message to capture any additional backup params at the source level. Attributes: acropolis_params (AcropolisBackupSourceParams): This is applicable to sources of type kVirtualMachine (kAcropolis environment). app_entity_id_v... | stack_v2_sparse_classes_36k_train_026185 | 8,847 | permissive | [
{
"docstring": "Constructor for the BackupSourceParams class",
"name": "__init__",
"signature": "def __init__(self, acropolis_params=None, app_entity_id_vec=None, aws_native_params=None, aws_snapshot_manager_params=None, gcp_native_params=None, hyperv_params=None, oracle_params=None, physical_params=Non... | 2 | null | Implement the Python class `BackupSourceParams` described below.
Class description:
Implementation of the 'BackupSourceParams' model. Message to capture any additional backup params at the source level. Attributes: acropolis_params (AcropolisBackupSourceParams): This is applicable to sources of type kVirtualMachine (k... | Implement the Python class `BackupSourceParams` described below.
Class description:
Implementation of the 'BackupSourceParams' model. Message to capture any additional backup params at the source level. Attributes: acropolis_params (AcropolisBackupSourceParams): This is applicable to sources of type kVirtualMachine (k... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class BackupSourceParams:
"""Implementation of the 'BackupSourceParams' model. Message to capture any additional backup params at the source level. Attributes: acropolis_params (AcropolisBackupSourceParams): This is applicable to sources of type kVirtualMachine (kAcropolis environment). app_entity_id_v... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BackupSourceParams:
"""Implementation of the 'BackupSourceParams' model. Message to capture any additional backup params at the source level. Attributes: acropolis_params (AcropolisBackupSourceParams): This is applicable to sources of type kVirtualMachine (kAcropolis environment). app_entity_id_vec (list of l... | the_stack_v2_python_sparse | cohesity_management_sdk/models/backup_source_params.py | cohesity/management-sdk-python | train | 24 |
9337c48b67d1d779f77eb40ccd3be8df5b9f06b8 | [
"super(FileSystemWinRegistryFileReader, self).__init__()\nself._file_system = file_system\nself._path_resolver = windows_path_resolver.WindowsPathResolver(file_system, mount_point)\nif path_attributes:\n for attribute_name, attribute_value in iter(path_attributes.items()):\n if attribute_name == u'systemr... | <|body_start_0|>
super(FileSystemWinRegistryFileReader, self).__init__()
self._file_system = file_system
self._path_resolver = windows_path_resolver.WindowsPathResolver(file_system, mount_point)
if path_attributes:
for attribute_name, attribute_value in iter(path_attributes.i... | A file system-based Windows Registry file reader. | FileSystemWinRegistryFileReader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileSystemWinRegistryFileReader:
"""A file system-based Windows Registry file reader."""
def __init__(self, file_system, mount_point, path_attributes=None):
"""Initializes a Windows Registry file reader object. Args: file_system (dfvfs.FileSytem): file system. mount_point (dfvfs.Path... | stack_v2_sparse_classes_36k_train_026186 | 9,000 | permissive | [
{
"docstring": "Initializes a Windows Registry file reader object. Args: file_system (dfvfs.FileSytem): file system. mount_point (dfvfs.PathSpec): mount point path specification. path_attributes (Optional[dict[str, str]]): path attributes e.g. {'SystemRoot': '\\\\Windows'}",
"name": "__init__",
"signatu... | 3 | stack_v2_sparse_classes_30k_train_008815 | Implement the Python class `FileSystemWinRegistryFileReader` described below.
Class description:
A file system-based Windows Registry file reader.
Method signatures and docstrings:
- def __init__(self, file_system, mount_point, path_attributes=None): Initializes a Windows Registry file reader object. Args: file_syste... | Implement the Python class `FileSystemWinRegistryFileReader` described below.
Class description:
A file system-based Windows Registry file reader.
Method signatures and docstrings:
- def __init__(self, file_system, mount_point, path_attributes=None): Initializes a Windows Registry file reader object. Args: file_syste... | 0ee446ebf03d17c515f76a666bd3795e91a2dd17 | <|skeleton|>
class FileSystemWinRegistryFileReader:
"""A file system-based Windows Registry file reader."""
def __init__(self, file_system, mount_point, path_attributes=None):
"""Initializes a Windows Registry file reader object. Args: file_system (dfvfs.FileSytem): file system. mount_point (dfvfs.Path... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileSystemWinRegistryFileReader:
"""A file system-based Windows Registry file reader."""
def __init__(self, file_system, mount_point, path_attributes=None):
"""Initializes a Windows Registry file reader object. Args: file_system (dfvfs.FileSytem): file system. mount_point (dfvfs.PathSpec): mount ... | the_stack_v2_python_sparse | plaso/preprocessors/manager.py | aarontp/plaso | train | 1 |
80389afa393eb20ebc3429fcae5962fffb1f7523 | [
"self.name = name\nself.kernel_regularizer = kernel_regularizer\nself.bias_regularizer = bias_regularizer",
"func_name = 'get_critic_logits'\nnetwork = X\nprint_obj('\\n' + func_name, 'network', network)\nwith tf.variable_scope('critic', reuse=tf.AUTO_REUSE):\n for i in range(len(params['critic_num_filters']))... | <|body_start_0|>
self.name = name
self.kernel_regularizer = kernel_regularizer
self.bias_regularizer = bias_regularizer
<|end_body_0|>
<|body_start_1|>
func_name = 'get_critic_logits'
network = X
print_obj('\n' + func_name, 'network', network)
with tf.variable_sc... | Critic that takes image input and outputs logits. Fields: name: str, name of `Critic`. kernel_regularizer: `l1_l2_regularizer` object, regularizar for kernel variables. bias_regularizer: `l1_l2_regularizer` object, regularizar for bias variables. | Critic | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Critic:
"""Critic that takes image input and outputs logits. Fields: name: str, name of `Critic`. kernel_regularizer: `l1_l2_regularizer` object, regularizar for kernel variables. bias_regularizer: `l1_l2_regularizer` object, regularizar for bias variables."""
def __init__(self, kernel_regul... | stack_v2_sparse_classes_36k_train_026187 | 6,232 | permissive | [
{
"docstring": "Instantiates and builds critic network. Args: kernel_regularizer: `l1_l2_regularizer` object, regularizar for kernel variables. bias_regularizer: `l1_l2_regularizer` object, regularizar for bias variables. name: str, name of critic.",
"name": "__init__",
"signature": "def __init__(self, ... | 3 | stack_v2_sparse_classes_30k_train_004676 | Implement the Python class `Critic` described below.
Class description:
Critic that takes image input and outputs logits. Fields: name: str, name of `Critic`. kernel_regularizer: `l1_l2_regularizer` object, regularizar for kernel variables. bias_regularizer: `l1_l2_regularizer` object, regularizar for bias variables.
... | Implement the Python class `Critic` described below.
Class description:
Critic that takes image input and outputs logits. Fields: name: str, name of `Critic`. kernel_regularizer: `l1_l2_regularizer` object, regularizar for kernel variables. bias_regularizer: `l1_l2_regularizer` object, regularizar for bias variables.
... | f7c21af221f366b075d351deeeb00a1b266ac3e3 | <|skeleton|>
class Critic:
"""Critic that takes image input and outputs logits. Fields: name: str, name of `Critic`. kernel_regularizer: `l1_l2_regularizer` object, regularizar for kernel variables. bias_regularizer: `l1_l2_regularizer` object, regularizar for bias variables."""
def __init__(self, kernel_regul... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Critic:
"""Critic that takes image input and outputs logits. Fields: name: str, name of `Critic`. kernel_regularizer: `l1_l2_regularizer` object, regularizar for kernel variables. bias_regularizer: `l1_l2_regularizer` object, regularizar for bias variables."""
def __init__(self, kernel_regularizer, bias_... | the_stack_v2_python_sparse | machine_learning/gan/wgan/tf_wgan/wgan_module/trainer/critic.py | ryangillard/artificial_intelligence | train | 4 |
3b2de93dde6067a53a07372b751a86c7c2211d08 | [
"n = len(matrix)\nfor i in range(n // 2):\n for j in range(n):\n matrix[i][j], matrix[n - 1 - i][j] = (matrix[n - 1 - i][j], matrix[i][j])\nfor i in range(n):\n for j in range(i):\n matrix[i][j], matrix[j][i] = (matrix[j][i], matrix[i][j])",
"n = len(matrix)\nfor i in range(n // 2):\n for j... | <|body_start_0|>
n = len(matrix)
for i in range(n // 2):
for j in range(n):
matrix[i][j], matrix[n - 1 - i][j] = (matrix[n - 1 - i][j], matrix[i][j])
for i in range(n):
for j in range(i):
matrix[i][j], matrix[j][i] = (matrix[j][i], matrix[i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""两次翻转：水平 + 主对角线"""
<|body_0|>
def rotateonce(self, matrix: List[List[int]]) -> None:
"""一次旋转"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(matrix)
for i in range(n // 2... | stack_v2_sparse_classes_36k_train_026188 | 1,239 | no_license | [
{
"docstring": "两次翻转：水平 + 主对角线",
"name": "rotate",
"signature": "def rotate(self, matrix: List[List[int]]) -> None"
},
{
"docstring": "一次旋转",
"name": "rotateonce",
"signature": "def rotateonce(self, matrix: List[List[int]]) -> None"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix: List[List[int]]) -> None: 两次翻转：水平 + 主对角线
- def rotateonce(self, matrix: List[List[int]]) -> None: 一次旋转 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix: List[List[int]]) -> None: 两次翻转：水平 + 主对角线
- def rotateonce(self, matrix: List[List[int]]) -> None: 一次旋转
<|skeleton|>
class Solution:
def rotate(self... | 52756b30e9d51794591aca030bc918e707f473f1 | <|skeleton|>
class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""两次翻转：水平 + 主对角线"""
<|body_0|>
def rotateonce(self, matrix: List[List[int]]) -> None:
"""一次旋转"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""两次翻转：水平 + 主对角线"""
n = len(matrix)
for i in range(n // 2):
for j in range(n):
matrix[i][j], matrix[n - 1 - i][j] = (matrix[n - 1 - i][j], matrix[i][j])
for i in range(n):
for ... | the_stack_v2_python_sparse | 48.旋转图像/solution.py | QtTao/daily_leetcode | train | 0 | |
ea571de280fb5e1b4fab16906006c6b490442841 | [
"first = self.findFirst(nums, target)\nlast = self.findLast(nums, target)\nif first <= last:\n return [first, last]\nelse:\n return [-1, -1]",
"left, mid, right = (0, 0, len(nums) - 1)\nwhile left <= right:\n mid = (left + right) // 2\n if nums[mid] < target:\n left = mid + 1\n else:\n ... | <|body_start_0|>
first = self.findFirst(nums, target)
last = self.findLast(nums, target)
if first <= last:
return [first, last]
else:
return [-1, -1]
<|end_body_0|>
<|body_start_1|>
left, mid, right = (0, 0, len(nums) - 1)
while left <= right:
... | Time Complexity: O(logn). Space Complexity: O(1). | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Time Complexity: O(logn). Space Complexity: O(1)."""
def searchRange(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def findFirst(self, nums, target):
""":type nums: List[int] :type target: int :rtype:... | stack_v2_sparse_classes_36k_train_026189 | 3,937 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "searchRange",
"signature": "def searchRange(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "findFirst",
"signature": "def findFirst(self, nums, targ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Time Complexity: O(logn). Space Complexity: O(1).
Method signatures and docstrings:
- def searchRange(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def findFirst(self, nums, target): :type nums: List[int] :typ... | Implement the Python class `Solution` described below.
Class description:
Time Complexity: O(logn). Space Complexity: O(1).
Method signatures and docstrings:
- def searchRange(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def findFirst(self, nums, target): :type nums: List[int] :typ... | 551cd3b4616c16a6562eb7c577ce671b419f0616 | <|skeleton|>
class Solution:
"""Time Complexity: O(logn). Space Complexity: O(1)."""
def searchRange(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def findFirst(self, nums, target):
""":type nums: List[int] :type target: int :rtype:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Time Complexity: O(logn). Space Complexity: O(1)."""
def searchRange(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
first = self.findFirst(nums, target)
last = self.findLast(nums, target)
if first <= last:
retu... | the_stack_v2_python_sparse | python/array/0034_Find_First_and_Last_Position_of_Element_in_Sorted_Array.py | lizzzcai/leetcode | train | 1 |
c20b5dcfd91a3d4ff20fe320b6c62a56e6fb5d53 | [
"try:\n init_connection = await ConnRecord.retrieve_by_id(session, init_connection_id)\nexcept StorageNotFoundError:\n raise IntroductionError(f'Initiator connection {init_connection_id} not found')\nif ConnRecord.State.get(init_connection.state) is not ConnRecord.State.COMPLETED:\n raise IntroductionError... | <|body_start_0|>
try:
init_connection = await ConnRecord.retrieve_by_id(session, init_connection_id)
except StorageNotFoundError:
raise IntroductionError(f'Initiator connection {init_connection_id} not found')
if ConnRecord.State.get(init_connection.state) is not ConnReco... | Service handler for allowing connections to exchange invitations. | DemoIntroductionService | [
"LicenseRef-scancode-dco-1.1",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DemoIntroductionService:
"""Service handler for allowing connections to exchange invitations."""
async def start_introduction(self, init_connection_id: str, target_connection_id: str, message: str, session: ProfileSession, outbound_handler):
"""Start the introduction process between ... | stack_v2_sparse_classes_36k_train_026190 | 4,951 | permissive | [
{
"docstring": "Start the introduction process between two connections. Args: init_connection_id: The connection initiating the request target_connection_id: The connection which is asked for an invitation outbound_handler: The outbound handler coroutine for sending a message session: Profile session to use for... | 2 | null | Implement the Python class `DemoIntroductionService` described below.
Class description:
Service handler for allowing connections to exchange invitations.
Method signatures and docstrings:
- async def start_introduction(self, init_connection_id: str, target_connection_id: str, message: str, session: ProfileSession, o... | Implement the Python class `DemoIntroductionService` described below.
Class description:
Service handler for allowing connections to exchange invitations.
Method signatures and docstrings:
- async def start_introduction(self, init_connection_id: str, target_connection_id: str, message: str, session: ProfileSession, o... | 39cac36d8937ce84a9307ce100aaefb8bc05ec04 | <|skeleton|>
class DemoIntroductionService:
"""Service handler for allowing connections to exchange invitations."""
async def start_introduction(self, init_connection_id: str, target_connection_id: str, message: str, session: ProfileSession, outbound_handler):
"""Start the introduction process between ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DemoIntroductionService:
"""Service handler for allowing connections to exchange invitations."""
async def start_introduction(self, init_connection_id: str, target_connection_id: str, message: str, session: ProfileSession, outbound_handler):
"""Start the introduction process between two connectio... | the_stack_v2_python_sparse | aries_cloudagent/protocols/introduction/v0_1/demo_service.py | hyperledger/aries-cloudagent-python | train | 370 |
0724bdf4d66098c72e149758b00fb7edfe51d810 | [
"self.id = id\nself.gallery_type = gallery_type\nself.title = title\nself.alt = alt\nself.description = description\nself.is_active = is_active\nself.is_main = is_main\nself.is_attach_file = is_attach_file\nself.sort_priority = sort_priority\nself.create_on_persian_date = create_on_persian_date\nself.meta_media_fil... | <|body_start_0|>
self.id = id
self.gallery_type = gallery_type
self.title = title
self.alt = alt
self.description = description
self.is_active = is_active
self.is_main = is_main
self.is_attach_file = is_attach_file
self.sort_priority = sort_priorit... | Implementation of the 'VideoGallery' model. TODO: type model description here. Attributes: id (int): TODO: type description here. gallery_type (int): TODO: type description here. title (string): TODO: type description here. alt (string): TODO: type description here. description (string): TODO: type description here. is... | VideoGallery | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VideoGallery:
"""Implementation of the 'VideoGallery' model. TODO: type model description here. Attributes: id (int): TODO: type description here. gallery_type (int): TODO: type description here. title (string): TODO: type description here. alt (string): TODO: type description here. description (... | stack_v2_sparse_classes_36k_train_026191 | 5,356 | permissive | [
{
"docstring": "Constructor for the VideoGallery class",
"name": "__init__",
"signature": "def __init__(self, id=None, gallery_type=None, title=None, is_active=None, is_main=None, is_attach_file=None, create_on_persian_date=None, meta_media_file_id=None, meta_media_file_url=None, popup_image_galleryies=... | 2 | stack_v2_sparse_classes_30k_train_018763 | Implement the Python class `VideoGallery` described below.
Class description:
Implementation of the 'VideoGallery' model. TODO: type model description here. Attributes: id (int): TODO: type description here. gallery_type (int): TODO: type description here. title (string): TODO: type description here. alt (string): TOD... | Implement the Python class `VideoGallery` described below.
Class description:
Implementation of the 'VideoGallery' model. TODO: type model description here. Attributes: id (int): TODO: type description here. gallery_type (int): TODO: type description here. title (string): TODO: type description here. alt (string): TOD... | b574a76a8805b306a423229b572c36dae0159def | <|skeleton|>
class VideoGallery:
"""Implementation of the 'VideoGallery' model. TODO: type model description here. Attributes: id (int): TODO: type description here. gallery_type (int): TODO: type description here. title (string): TODO: type description here. alt (string): TODO: type description here. description (... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VideoGallery:
"""Implementation of the 'VideoGallery' model. TODO: type model description here. Attributes: id (int): TODO: type description here. gallery_type (int): TODO: type description here. title (string): TODO: type description here. alt (string): TODO: type description here. description (string): TODO... | the_stack_v2_python_sparse | easybimehlanding/models/video_gallery.py | kmelodi/EasyBimehLanding_Python | train | 0 |
4cfec4c036af9ea970a3ca8fe8b5d4ba0cb55353 | [
"self.mod_df = mod_df\noptions = [opts_dd(column, column) for column in self.mod_df.columns]\nif self.show_filter:\n filter_elements = dbc.Row([dbc.Col([dbc.Form([dcc.Input(id=ids[self.get(self.id_filter_input)], placeholder='Enter filter query', style={'width': '100%'}), dbc.Button('Apply', color='secondary', i... | <|body_start_0|>
self.mod_df = mod_df
options = [opts_dd(column, column) for column in self.mod_df.columns]
if self.show_filter:
filter_elements = dbc.Row([dbc.Col([dbc.Form([dcc.Input(id=ids[self.get(self.id_filter_input)], placeholder='Enter filter query', style={'width': '100%'}),... | Modular Dash data table with column selection and filter. | ModuleFilteredTable | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModuleFilteredTable:
"""Modular Dash data table with column selection and filter."""
def return_layout(self, ids, mod_df):
"""Return Dash application layout. Args: ids: `self._il` from base application mod_df: dataframe for Returns: dict: Dash HTML object"""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_026192 | 10,244 | permissive | [
{
"docstring": "Return Dash application layout. Args: ids: `self._il` from base application mod_df: dataframe for Returns: dict: Dash HTML object",
"name": "return_layout",
"signature": "def return_layout(self, ids, mod_df)"
},
{
"docstring": "Register callbacks to handle user interaction. Args:... | 5 | stack_v2_sparse_classes_30k_train_020846 | Implement the Python class `ModuleFilteredTable` described below.
Class description:
Modular Dash data table with column selection and filter.
Method signatures and docstrings:
- def return_layout(self, ids, mod_df): Return Dash application layout. Args: ids: `self._il` from base application mod_df: dataframe for Ret... | Implement the Python class `ModuleFilteredTable` described below.
Class description:
Modular Dash data table with column selection and filter.
Method signatures and docstrings:
- def return_layout(self, ids, mod_df): Return Dash application layout. Args: ids: `self._il` from base application mod_df: dataframe for Ret... | fe784f4224136e6854d9ce67628976f17a2d9433 | <|skeleton|>
class ModuleFilteredTable:
"""Modular Dash data table with column selection and filter."""
def return_layout(self, ids, mod_df):
"""Return Dash application layout. Args: ids: `self._il` from base application mod_df: dataframe for Returns: dict: Dash HTML object"""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModuleFilteredTable:
"""Modular Dash data table with column selection and filter."""
def return_layout(self, ids, mod_df):
"""Return Dash application layout. Args: ids: `self._il` from base application mod_df: dataframe for Returns: dict: Dash HTML object"""
self.mod_df = mod_df
o... | the_stack_v2_python_sparse | dash_charts/modules_datatable.py | KyleKing/dash_charts | train | 20 |
b9d676a34e4a83f592580247ecde07aa85750585 | [
"queryset = kwargs.get('queryset')\nfilters = None\nfilter_map = kwargs.get('filter_map', {})\nfg = FilterGenerator(queryset.model, filter_map=filter_map)\nif len(request.data):\n fg = FilterGenerator(queryset.model)\n filters = fg.create_from_request_body(request.data)\nelse:\n filters = Q(**fg.create_fro... | <|body_start_0|>
queryset = kwargs.get('queryset')
filters = None
filter_map = kwargs.get('filter_map', {})
fg = FilterGenerator(queryset.model, filter_map=filter_map)
if len(request.data):
fg = FilterGenerator(queryset.model)
filters = fg.create_from_requ... | Handles queryset filtering. | FilterQuerysetMixin | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilterQuerysetMixin:
"""Handles queryset filtering."""
def filter_records(self, request, *args, **kwargs):
"""Filter a queryset based on request parameters"""
<|body_0|>
def order_records(self, request, *args, **kwargs):
"""Order a queryset based on request param... | stack_v2_sparse_classes_36k_train_026193 | 10,956 | permissive | [
{
"docstring": "Filter a queryset based on request parameters",
"name": "filter_records",
"signature": "def filter_records(self, request, *args, **kwargs)"
},
{
"docstring": "Order a queryset based on request parameters.",
"name": "order_records",
"signature": "def order_records(self, re... | 3 | stack_v2_sparse_classes_30k_train_003580 | Implement the Python class `FilterQuerysetMixin` described below.
Class description:
Handles queryset filtering.
Method signatures and docstrings:
- def filter_records(self, request, *args, **kwargs): Filter a queryset based on request parameters
- def order_records(self, request, *args, **kwargs): Order a queryset b... | Implement the Python class `FilterQuerysetMixin` described below.
Class description:
Handles queryset filtering.
Method signatures and docstrings:
- def filter_records(self, request, *args, **kwargs): Filter a queryset based on request parameters
- def order_records(self, request, *args, **kwargs): Order a queryset b... | 38f920438697930ae3ac57bbcaae9034877d8fb7 | <|skeleton|>
class FilterQuerysetMixin:
"""Handles queryset filtering."""
def filter_records(self, request, *args, **kwargs):
"""Filter a queryset based on request parameters"""
<|body_0|>
def order_records(self, request, *args, **kwargs):
"""Order a queryset based on request param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FilterQuerysetMixin:
"""Handles queryset filtering."""
def filter_records(self, request, *args, **kwargs):
"""Filter a queryset based on request parameters"""
queryset = kwargs.get('queryset')
filters = None
filter_map = kwargs.get('filter_map', {})
fg = FilterGene... | the_stack_v2_python_sparse | usaspending_api/common/mixins.py | fedspendingtransparency/usaspending-api | train | 276 |
d97de1797a8f6fd2c8d495aa144edbf2e8c1a33a | [
"is_existed = validated_data['is_existed']\ncode = validated_data['code']\nnew_phone = validated_data['phone']\nif is_existed:\n old_phone = validated_data['old_phone']\n is_success = cache.check_code(old_phone, code)\nelse:\n is_success = cache.check_code(new_phone, code)\nif is_success:\n instance.pho... | <|body_start_0|>
is_existed = validated_data['is_existed']
code = validated_data['code']
new_phone = validated_data['phone']
if is_existed:
old_phone = validated_data['old_phone']
is_success = cache.check_code(old_phone, code)
else:
is_success ... | 绑定（改绑）用户邮箱或者手机号 需发送验证码验证 | BindEmailOrPhone | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BindEmailOrPhone:
"""绑定（改绑）用户邮箱或者手机号 需发送验证码验证"""
def bind_phone(cache, instance, validated_data):
"""改绑手机号"""
<|body_0|>
def bind_email(cache, instance, validated_data):
"""改绑邮箱"""
<|body_1|>
def factory(self, way, validated_data, instance):
... | stack_v2_sparse_classes_36k_train_026194 | 28,563 | permissive | [
{
"docstring": "改绑手机号",
"name": "bind_phone",
"signature": "def bind_phone(cache, instance, validated_data)"
},
{
"docstring": "改绑邮箱",
"name": "bind_email",
"signature": "def bind_email(cache, instance, validated_data)"
},
{
"docstring": "简单工厂管理手机号和邮箱的改绑",
"name": "factory",
... | 4 | stack_v2_sparse_classes_30k_train_002912 | Implement the Python class `BindEmailOrPhone` described below.
Class description:
绑定（改绑）用户邮箱或者手机号 需发送验证码验证
Method signatures and docstrings:
- def bind_phone(cache, instance, validated_data): 改绑手机号
- def bind_email(cache, instance, validated_data): 改绑邮箱
- def factory(self, way, validated_data, instance): 简单工厂管理手机号和邮箱... | Implement the Python class `BindEmailOrPhone` described below.
Class description:
绑定（改绑）用户邮箱或者手机号 需发送验证码验证
Method signatures and docstrings:
- def bind_phone(cache, instance, validated_data): 改绑手机号
- def bind_email(cache, instance, validated_data): 改绑邮箱
- def factory(self, way, validated_data, instance): 简单工厂管理手机号和邮箱... | 13cb59130d15e782f78bc5148409bef0f1c516e0 | <|skeleton|>
class BindEmailOrPhone:
"""绑定（改绑）用户邮箱或者手机号 需发送验证码验证"""
def bind_phone(cache, instance, validated_data):
"""改绑手机号"""
<|body_0|>
def bind_email(cache, instance, validated_data):
"""改绑邮箱"""
<|body_1|>
def factory(self, way, validated_data, instance):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BindEmailOrPhone:
"""绑定（改绑）用户邮箱或者手机号 需发送验证码验证"""
def bind_phone(cache, instance, validated_data):
"""改绑手机号"""
is_existed = validated_data['is_existed']
code = validated_data['code']
new_phone = validated_data['phone']
if is_existed:
old_phone = validate... | the_stack_v2_python_sparse | user_app/views/personal_api.py | lmyfzx/Django-Mall | train | 0 |
b331ca12b914add65c8be2a4846964f335c4ccbc | [
"bands = {'U': 0, 'B': 1, 'V': 2, 'K': 3, 'g': 4, 'r': 5, 'i': 6, 'z': 7}\nnband = bands[band]\npos = self.snapshot_set.get_data(4, 'Position', segment=fn).astype(np.float32)\nhh = hhmult * np.ones(np.shape(pos)[0], dtype=np.float32)\nind = self.particles_near_lines(pos, hh, self.axis, self.cofm)\nif np.size(ind) =... | <|body_start_0|>
bands = {'U': 0, 'B': 1, 'V': 2, 'K': 3, 'g': 4, 'r': 5, 'i': 6, 'z': 7}
nband = bands[band]
pos = self.snapshot_set.get_data(4, 'Position', segment=fn).astype(np.float32)
hh = hhmult * np.ones(np.shape(pos)[0], dtype=np.float32)
ind = self.particles_near_lines(p... | Class to compute the emission from stars in B band around the DLA spectrum | EmissionSpectra | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmissionSpectra:
"""Class to compute the emission from stars in B band around the DLA spectrum"""
def _read_stellar_data(self, fn, band, hhmult=10.0):
"""Read the particle data for a single interpolation"""
<|body_0|>
def get_emflux(self, band, pixelsz=1):
"""Get... | stack_v2_sparse_classes_36k_train_026195 | 6,065 | permissive | [
{
"docstring": "Read the particle data for a single interpolation",
"name": "_read_stellar_data",
"signature": "def _read_stellar_data(self, fn, band, hhmult=10.0)"
},
{
"docstring": "Get the density weighted flux in each pixel for a given species. band: rest-frame optical band observed in pixel... | 3 | stack_v2_sparse_classes_30k_test_000949 | Implement the Python class `EmissionSpectra` described below.
Class description:
Class to compute the emission from stars in B band around the DLA spectrum
Method signatures and docstrings:
- def _read_stellar_data(self, fn, band, hhmult=10.0): Read the particle data for a single interpolation
- def get_emflux(self, ... | Implement the Python class `EmissionSpectra` described below.
Class description:
Class to compute the emission from stars in B band around the DLA spectrum
Method signatures and docstrings:
- def _read_stellar_data(self, fn, band, hhmult=10.0): Read the particle data for a single interpolation
- def get_emflux(self, ... | be5b9d6e7b25dc5e978e3f926f0882889417c4a8 | <|skeleton|>
class EmissionSpectra:
"""Class to compute the emission from stars in B band around the DLA spectrum"""
def _read_stellar_data(self, fn, band, hhmult=10.0):
"""Read the particle data for a single interpolation"""
<|body_0|>
def get_emflux(self, band, pixelsz=1):
"""Get... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmissionSpectra:
"""Class to compute the emission from stars in B band around the DLA spectrum"""
def _read_stellar_data(self, fn, band, hhmult=10.0):
"""Read the particle data for a single interpolation"""
bands = {'U': 0, 'B': 1, 'V': 2, 'K': 3, 'g': 4, 'r': 5, 'i': 6, 'z': 7}
n... | the_stack_v2_python_sparse | fake_spectra/emission.py | sbird/fake_spectra | train | 10 |
ab4d7520b260dd4c19a6fa0abab01fcbd97b0a88 | [
"super().__init__()\nself.p = p\nif p_mode != 'per_batch':\n raise ValueError(f'p_mode = \"{p_mode}\" is not supported')\nself.p_mode = p_mode\nself.shuffle = shuffle\nself.are_parameters_frozen = False\nif output_type is None:\n warnings.warn(f\"Transforms now expect an `output_type` argument that currently ... | <|body_start_0|>
super().__init__()
self.p = p
if p_mode != 'per_batch':
raise ValueError(f'p_mode = "{p_mode}" is not supported')
self.p_mode = p_mode
self.shuffle = shuffle
self.are_parameters_frozen = False
if output_type is None:
warnin... | This class can apply a sequence of transforms to waveforms. | BaseCompose | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseCompose:
"""This class can apply a sequence of transforms to waveforms."""
def __init__(self, transforms: List[torch.nn.Module], shuffle: bool=False, p: float=1.0, p_mode='per_batch', output_type: Optional[str]=None):
""":param transforms: List of waveform transform instances :pa... | stack_v2_sparse_classes_36k_train_026196 | 31,221 | no_license | [
{
"docstring": ":param transforms: List of waveform transform instances :param shuffle: Should the order of transforms be shuffled? :param p: The probability of applying the Compose to the given batch. :param p_mode: Only \"per_batch\" is supported at the moment. :param output_type: This optional argument can b... | 4 | null | Implement the Python class `BaseCompose` described below.
Class description:
This class can apply a sequence of transforms to waveforms.
Method signatures and docstrings:
- def __init__(self, transforms: List[torch.nn.Module], shuffle: bool=False, p: float=1.0, p_mode='per_batch', output_type: Optional[str]=None): :p... | Implement the Python class `BaseCompose` described below.
Class description:
This class can apply a sequence of transforms to waveforms.
Method signatures and docstrings:
- def __init__(self, transforms: List[torch.nn.Module], shuffle: bool=False, p: float=1.0, p_mode='per_batch', output_type: Optional[str]=None): :p... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class BaseCompose:
"""This class can apply a sequence of transforms to waveforms."""
def __init__(self, transforms: List[torch.nn.Module], shuffle: bool=False, p: float=1.0, p_mode='per_batch', output_type: Optional[str]=None):
""":param transforms: List of waveform transform instances :pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseCompose:
"""This class can apply a sequence of transforms to waveforms."""
def __init__(self, transforms: List[torch.nn.Module], shuffle: bool=False, p: float=1.0, p_mode='per_batch', output_type: Optional[str]=None):
""":param transforms: List of waveform transform instances :param shuffle: ... | the_stack_v2_python_sparse | generated/test_asteroid_team_torch_audiomentations.py | jansel/pytorch-jit-paritybench | train | 35 |
1497f7442f6063be560803022fa58bda48ed1b2f | [
"def binary_search(nums, target, comparator):\n left, right = (0, len(nums) - 1)\n while left <= right:\n mid = left + (right - left) // 2\n if comparator(nums[mid], target):\n left = mid + 1\n else:\n right = mid - 1\n return left\nleft = binary_search(nums, targ... | <|body_start_0|>
def binary_search(nums, target, comparator):
left, right = (0, len(nums) - 1)
while left <= right:
mid = left + (right - left) // 2
if comparator(nums[mid], target):
left = mid + 1
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchRange(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def searchRange_v2(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
def searchRange_l... | stack_v2_sparse_classes_36k_train_026197 | 2,883 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "searchRange",
"signature": "def searchRange(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "searchRange_v2",
"signature": "def searchRange_v2(... | 3 | stack_v2_sparse_classes_30k_train_013487 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchRange(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def searchRange_v2(self, nums, target): :type nums: List[int] :type target: int :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchRange(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def searchRange_v2(self, nums, target): :type nums: List[int] :type target: int :... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def searchRange(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def searchRange_v2(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
def searchRange_l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def searchRange(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
def binary_search(nums, target, comparator):
left, right = (0, len(nums) - 1)
while left <= right:
mid = left + (right - left) // 2
... | the_stack_v2_python_sparse | src/lt_34.py | oxhead/CodingYourWay | train | 0 | |
fe26f067060659ce6fe991b23286025bff38467f | [
"self._embeddings_index = {}\nself.embedding_dimension = embedding_dimension\nself.embedding_matrix = np.zeros((len(word_idx) + 1, self.embedding_dimension))\nself.__read_vectors__()\nself.__populate_embedding__(word_idx)",
"path = get_file(self.__GLOVE_FILE__, origin=self.__URL__, cache_subdir=self.__EMBEDDING_C... | <|body_start_0|>
self._embeddings_index = {}
self.embedding_dimension = embedding_dimension
self.embedding_matrix = np.zeros((len(word_idx) + 1, self.embedding_dimension))
self.__read_vectors__()
self.__populate_embedding__(word_idx)
<|end_body_0|>
<|body_start_1|>
path ... | GloveLoader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GloveLoader:
def __init__(self, word_idx, embedding_dimension=100):
"""Read glove vectors from file. It creates a cache on home folder using Keras function :param embedding_dimension: (dimensions of glove 50,100,)"""
<|body_0|>
def __read_vectors__(self):
"""Read vec... | stack_v2_sparse_classes_36k_train_026198 | 1,919 | permissive | [
{
"docstring": "Read glove vectors from file. It creates a cache on home folder using Keras function :param embedding_dimension: (dimensions of glove 50,100,)",
"name": "__init__",
"signature": "def __init__(self, word_idx, embedding_dimension=100)"
},
{
"docstring": "Read vectors from glove",
... | 3 | stack_v2_sparse_classes_30k_test_001155 | Implement the Python class `GloveLoader` described below.
Class description:
Implement the GloveLoader class.
Method signatures and docstrings:
- def __init__(self, word_idx, embedding_dimension=100): Read glove vectors from file. It creates a cache on home folder using Keras function :param embedding_dimension: (dim... | Implement the Python class `GloveLoader` described below.
Class description:
Implement the GloveLoader class.
Method signatures and docstrings:
- def __init__(self, word_idx, embedding_dimension=100): Read glove vectors from file. It creates a cache on home folder using Keras function :param embedding_dimension: (dim... | 01214cf44f9e69b64c341c4b6676db73e5ca7966 | <|skeleton|>
class GloveLoader:
def __init__(self, word_idx, embedding_dimension=100):
"""Read glove vectors from file. It creates a cache on home folder using Keras function :param embedding_dimension: (dimensions of glove 50,100,)"""
<|body_0|>
def __read_vectors__(self):
"""Read vec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GloveLoader:
def __init__(self, word_idx, embedding_dimension=100):
"""Read glove vectors from file. It creates a cache on home folder using Keras function :param embedding_dimension: (dimensions of glove 50,100,)"""
self._embeddings_index = {}
self.embedding_dimension = embedding_dime... | the_stack_v2_python_sparse | pypagai/util/glove.py | gcouti/pypagAI | train | 1 | |
e3876a5cd38e7fac9a759dccb6292b624bba5118 | [
"first_name = self.cleaned_data['first_name']\nif first_name.strip(letters):\n raise forms.ValidationError('First Name is invalid')\nreturn first_name",
"last_name = self.cleaned_data['last_name']\nif last_name.strip(letters):\n raise forms.ValidationError('Last Name is invalid')\nreturn last_name",
"user... | <|body_start_0|>
first_name = self.cleaned_data['first_name']
if first_name.strip(letters):
raise forms.ValidationError('First Name is invalid')
return first_name
<|end_body_0|>
<|body_start_1|>
last_name = self.cleaned_data['last_name']
if last_name.strip(letters):
... | User Registration form | UserRegisterForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRegisterForm:
"""User Registration form"""
def clean_first_name(self):
"""Validation"""
<|body_0|>
def clean_last_name(self):
"""Validation"""
<|body_1|>
def clean_email(self):
"""Validation"""
<|body_2|>
def save(self):
... | stack_v2_sparse_classes_36k_train_026199 | 8,285 | no_license | [
{
"docstring": "Validation",
"name": "clean_first_name",
"signature": "def clean_first_name(self)"
},
{
"docstring": "Validation",
"name": "clean_last_name",
"signature": "def clean_last_name(self)"
},
{
"docstring": "Validation",
"name": "clean_email",
"signature": "def ... | 4 | stack_v2_sparse_classes_30k_train_010091 | Implement the Python class `UserRegisterForm` described below.
Class description:
User Registration form
Method signatures and docstrings:
- def clean_first_name(self): Validation
- def clean_last_name(self): Validation
- def clean_email(self): Validation
- def save(self): Validation | Implement the Python class `UserRegisterForm` described below.
Class description:
User Registration form
Method signatures and docstrings:
- def clean_first_name(self): Validation
- def clean_last_name(self): Validation
- def clean_email(self): Validation
- def save(self): Validation
<|skeleton|>
class UserRegisterF... | 65d9aa549a0d76f58cb89cac5da4a3085a2efd97 | <|skeleton|>
class UserRegisterForm:
"""User Registration form"""
def clean_first_name(self):
"""Validation"""
<|body_0|>
def clean_last_name(self):
"""Validation"""
<|body_1|>
def clean_email(self):
"""Validation"""
<|body_2|>
def save(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserRegisterForm:
"""User Registration form"""
def clean_first_name(self):
"""Validation"""
first_name = self.cleaned_data['first_name']
if first_name.strip(letters):
raise forms.ValidationError('First Name is invalid')
return first_name
def clean_last_nam... | the_stack_v2_python_sparse | nitortest/forms.py | ManishSinghFartyal/InternalGit | train | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.