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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
e20cc79a39f64264daf119aa31d195a2aa7528df | [
"self.minheap = []\nself.size = k\nfor i in nums:\n self.add(i)",
"if len(self.minheap) < self.size:\n heapq.heappush(self.minheap, val)\nelif self.minheap[0] < val:\n heapq.heappop(self.minheap)\n heapq.heappush(self.minheap, val)\nreturn self.minheap[0]"
] | <|body_start_0|>
self.minheap = []
self.size = k
for i in nums:
self.add(i)
<|end_body_0|>
<|body_start_1|>
if len(self.minheap) < self.size:
heapq.heappush(self.minheap, val)
elif self.minheap[0] < val:
heapq.heappop(self.minheap)
... | KthLargest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.minheap = []
self.size = k
for i in n... | stack_v2_sparse_classes_36k_train_032700 | 722 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015374 | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | 89316f5260996d4cacba0d42182026387add1ef9 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.minheap = []
self.size = k
for i in nums:
self.add(i)
def add(self, val):
""":type val: int :rtype: int"""
if len(self.minheap) < self.size:
heapq... | the_stack_v2_python_sparse | leetcode/KthlargestwithMinHeap.py | changlongG/Algorithms | train | 0 | |
670668abdddc2dd770e06293ba3a94900b38cf06 | [
"nd_names = states_df.columns\nord_nodes = [BayesNode(k, nd_names[k]) for k in range(len(nd_names))]\nbnet = BayesNet(set(ord_nodes))\nself.is_quantum = is_quantum\nself.bnet = bnet\nself.states_df = states_df\nself.ord_nodes = ord_nodes\nif not vtx_to_states:\n bnet.learn_nd_state_names(states_df)\nelse:\n b... | <|body_start_0|>
nd_names = states_df.columns
ord_nodes = [BayesNode(k, nd_names[k]) for k in range(len(nd_names))]
bnet = BayesNet(set(ord_nodes))
self.is_quantum = is_quantum
self.bnet = bnet
self.states_df = states_df
self.ord_nodes = ord_nodes
if not v... | Learning a Bayesian Network is usually done in two steps (1) learning the structure (i.e. the graph or skeleton) (2) learning the parameters ( i.e., the pots). NetStrucLner (Net Structure Learner) is a super class for all classes that learn the structure of a net based on empirical data about states given in a pandas d... | NetStrucLner | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetStrucLner:
"""Learning a Bayesian Network is usually done in two steps (1) learning the structure (i.e. the graph or skeleton) (2) learning the parameters ( i.e., the pots). NetStrucLner (Net Structure Learner) is a super class for all classes that learn the structure of a net based on empiric... | stack_v2_sparse_classes_36k_train_032701 | 3,273 | permissive | [
{
"docstring": "Constructor Parameters ---------- is_quantum : bool states_df : pandas.DataFrame vtx_to_states : dict[str, list[str]] A dictionary mapping each node name to a list of its state names. This information will be stored in self.bnet. If vtx_to_states=None, constructor will learn vtx_to_states from s... | 2 | stack_v2_sparse_classes_30k_train_009396 | Implement the Python class `NetStrucLner` described below.
Class description:
Learning a Bayesian Network is usually done in two steps (1) learning the structure (i.e. the graph or skeleton) (2) learning the parameters ( i.e., the pots). NetStrucLner (Net Structure Learner) is a super class for all classes that learn ... | Implement the Python class `NetStrucLner` described below.
Class description:
Learning a Bayesian Network is usually done in two steps (1) learning the structure (i.e. the graph or skeleton) (2) learning the parameters ( i.e., the pots). NetStrucLner (Net Structure Learner) is a super class for all classes that learn ... | 5b4a3055ea14c2ee9c80c339f759fe2b9c8c51e2 | <|skeleton|>
class NetStrucLner:
"""Learning a Bayesian Network is usually done in two steps (1) learning the structure (i.e. the graph or skeleton) (2) learning the parameters ( i.e., the pots). NetStrucLner (Net Structure Learner) is a super class for all classes that learn the structure of a net based on empiric... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NetStrucLner:
"""Learning a Bayesian Network is usually done in two steps (1) learning the structure (i.e. the graph or skeleton) (2) learning the parameters ( i.e., the pots). NetStrucLner (Net Structure Learner) is a super class for all classes that learn the structure of a net based on empirical data about... | the_stack_v2_python_sparse | learning/NetStrucLner.py | artiste-qb-net/quantum-fog | train | 95 |
27f5f1f1b7a38544d0a826d763b46b74f1f9330b | [
"if row is None:\n results = self._calculate_row(feature_resource)\n try:\n results = zip(*results)\n except TypeError:\n results = [tuple([results])]\n rows = []\n status = []\n for j in results:\n row = tuple(feature_resource)\n if isinstance(j, list) is True:\n ... | <|body_start_0|>
if row is None:
results = self._calculate_row(feature_resource)
try:
results = zip(*results)
except TypeError:
results = [tuple([results])]
rows = []
status = []
for j in results:
... | Generates rows to be placed into the uncached tables | WorkDirRows | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkDirRows:
"""Generates rows to be placed into the uncached tables"""
def construct_row(self, feature, feature_resource, row=None):
"""If row is nothing a feature is calculated otherwise the row is formated in the workdir table format @param: feature - @param: feature_resource - @p... | stack_v2_sparse_classes_36k_train_032702 | 22,952 | permissive | [
{
"docstring": "If row is nothing a feature is calculated otherwise the row is formated in the workdir table format @param: feature - @param: feature_resource - @param: row - row for a workdir table (default: None) @return: rows",
"name": "construct_row",
"signature": "def construct_row(self, feature, f... | 3 | stack_v2_sparse_classes_30k_train_011268 | Implement the Python class `WorkDirRows` described below.
Class description:
Generates rows to be placed into the uncached tables
Method signatures and docstrings:
- def construct_row(self, feature, feature_resource, row=None): If row is nothing a feature is calculated otherwise the row is formated in the workdir tab... | Implement the Python class `WorkDirRows` described below.
Class description:
Generates rows to be placed into the uncached tables
Method signatures and docstrings:
- def construct_row(self, feature, feature_resource, row=None): If row is nothing a feature is calculated otherwise the row is formated in the workdir tab... | be337668b090de83a5b539b0e89b0ea8292166da | <|skeleton|>
class WorkDirRows:
"""Generates rows to be placed into the uncached tables"""
def construct_row(self, feature, feature_resource, row=None):
"""If row is nothing a feature is calculated otherwise the row is formated in the workdir table format @param: feature - @param: feature_resource - @p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkDirRows:
"""Generates rows to be placed into the uncached tables"""
def construct_row(self, feature, feature_resource, row=None):
"""If row is nothing a feature is calculated otherwise the row is formated in the workdir table format @param: feature - @param: feature_resource - @param: row - r... | the_stack_v2_python_sparse | source/bqfeature/bq/features/controllers/TablesInterface.py | UCSB-VRL/bisqueUCSB | train | 40 |
a649a01280390c08cca32d35e574d5a16db8f9d5 | [
"try:\n keywords = request.GET.get('keywords', None)\n if keywords is not None:\n keywords = keywords.strip()\n query_project = Project.objects.filter(title__icontains=keywords).order_by('id')\n paginator = StandardResultsSetPagination()\n project_list = paginator.paginate_queryset... | <|body_start_0|>
try:
keywords = request.GET.get('keywords', None)
if keywords is not None:
keywords = keywords.strip()
query_project = Project.objects.filter(title__icontains=keywords).order_by('id')
paginator = StandardResultsSetPaginatio... | QueryProjectView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueryProjectView:
def get(self, request, *args, **kwargs):
"""/api/v1/project/query :param request: :param args: :param kwargs: :return:"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""根据项目名称查询 :param request: :param args: :param kwargs: :return:"""
... | stack_v2_sparse_classes_36k_train_032703 | 3,643 | no_license | [
{
"docstring": "/api/v1/project/query :param request: :param args: :param kwargs: :return:",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "根据项目名称查询 :param request: :param args: :param kwargs: :return:",
"name": "post",
"signature": "def post(sel... | 2 | stack_v2_sparse_classes_30k_train_004466 | Implement the Python class `QueryProjectView` described below.
Class description:
Implement the QueryProjectView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): /api/v1/project/query :param request: :param args: :param kwargs: :return:
- def post(self, request, *args, **kwargs): 根据... | Implement the Python class `QueryProjectView` described below.
Class description:
Implement the QueryProjectView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): /api/v1/project/query :param request: :param args: :param kwargs: :return:
- def post(self, request, *args, **kwargs): 根据... | 6b9b809c4a3d12dac0fe188d52ce351147c27857 | <|skeleton|>
class QueryProjectView:
def get(self, request, *args, **kwargs):
"""/api/v1/project/query :param request: :param args: :param kwargs: :return:"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""根据项目名称查询 :param request: :param args: :param kwargs: :return:"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QueryProjectView:
def get(self, request, *args, **kwargs):
"""/api/v1/project/query :param request: :param args: :param kwargs: :return:"""
try:
keywords = request.GET.get('keywords', None)
if keywords is not None:
keywords = keywords.strip()
... | the_stack_v2_python_sparse | api/views/project.py | loveqx/devops-api | train | 0 | |
eba94bc2d5c5c8474948afec4ef725809f540735 | [
"self.row = 0\nself.col = -1\nself.matrix = vec2d",
"if self.hasNext():\n self.col += 1\n return self.matrix[self.row][self.col]\nelse:\n return None",
"if self.row >= len(self.matrix):\n return False\nif self.col >= len(self.matrix[self.row]) - 1:\n self.row += 1\n while self.row < len(self.m... | <|body_start_0|>
self.row = 0
self.col = -1
self.matrix = vec2d
<|end_body_0|>
<|body_start_1|>
if self.hasNext():
self.col += 1
return self.matrix[self.row][self.col]
else:
return None
<|end_body_1|>
<|body_start_2|>
if self.row >= l... | 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_032704 | 795 | 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 | null | 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... | 15f012927dc34b5d751af6633caa5e8882d26ff7 | <|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.row = 0
self.col = -1
self.matrix = vec2d
def next(self):
""":rtype: int"""
if self.hasNext():
self.col += 1
return sel... | the_stack_v2_python_sparse | python/251.Flatten2DVector.py | MaxPoon/Leetcode | train | 15 | |
c31bf061e8642b93daaa97ddbba78fc092ae8cbc | [
"self.__frameData = []\n_cfg = ConfigData.ConfigData()\n_path = _cfg.GetYVectorFilePath() + filename + '/' + str(frame) + '.yvector'\nwith open(_path) as f:\n for line in f.xreadlines():\n self.__frameData.append(line[:-1].split(','))\n_len = len(self.__frameData)\ndel self.__frameData[_len - 1]\ndel self... | <|body_start_0|>
self.__frameData = []
_cfg = ConfigData.ConfigData()
_path = _cfg.GetYVectorFilePath() + filename + '/' + str(frame) + '.yvector'
with open(_path) as f:
for line in f.xreadlines():
self.__frameData.append(line[:-1].split(','))
_len = l... | 获取每帧的特征提取 | GetSingleFrameSampling | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetSingleFrameSampling:
"""获取每帧的特征提取"""
def getFrameFileData(self, frame, filename):
"""获取文件数据"""
<|body_0|>
def GetSingleSampling(self, frame, filename, region, unit):
"""获取一个帧的特征提取，以字符串形式输出"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.... | stack_v2_sparse_classes_36k_train_032705 | 1,491 | no_license | [
{
"docstring": "获取文件数据",
"name": "getFrameFileData",
"signature": "def getFrameFileData(self, frame, filename)"
},
{
"docstring": "获取一个帧的特征提取，以字符串形式输出",
"name": "GetSingleSampling",
"signature": "def GetSingleSampling(self, frame, filename, region, unit)"
}
] | 2 | null | Implement the Python class `GetSingleFrameSampling` described below.
Class description:
获取每帧的特征提取
Method signatures and docstrings:
- def getFrameFileData(self, frame, filename): 获取文件数据
- def GetSingleSampling(self, frame, filename, region, unit): 获取一个帧的特征提取，以字符串形式输出 | Implement the Python class `GetSingleFrameSampling` described below.
Class description:
获取每帧的特征提取
Method signatures and docstrings:
- def getFrameFileData(self, frame, filename): 获取文件数据
- def GetSingleSampling(self, frame, filename, region, unit): 获取一个帧的特征提取，以字符串形式输出
<|skeleton|>
class GetSingleFrameSampling:
""... | 42ba71e5c134295c54d22cda73dd03af3af739e4 | <|skeleton|>
class GetSingleFrameSampling:
"""获取每帧的特征提取"""
def getFrameFileData(self, frame, filename):
"""获取文件数据"""
<|body_0|>
def GetSingleSampling(self, frame, filename, region, unit):
"""获取一个帧的特征提取，以字符串形式输出"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetSingleFrameSampling:
"""获取每帧的特征提取"""
def getFrameFileData(self, frame, filename):
"""获取文件数据"""
self.__frameData = []
_cfg = ConfigData.ConfigData()
_path = _cfg.GetYVectorFilePath() + filename + '/' + str(frame) + '.yvector'
with open(_path) as f:
fo... | the_stack_v2_python_sparse | VideoSampling/GetSingleFrameSampling.py | oneApple/NewNetWorkDepartMent | train | 1 |
4a566a17a251ee6f7b954408180f6f00046edef1 | [
"try:\n member = await get_data_from_req(self.request).spaces.update_member(space_id, member_id, data)\nexcept ResourceNotFoundError:\n raise NotFound\nreturn json_response(member)",
"try:\n await get_data_from_req(self.request).spaces.remove_member(space_id, member_id)\nexcept ResourceNotFoundError:\n ... | <|body_start_0|>
try:
member = await get_data_from_req(self.request).spaces.update_member(space_id, member_id, data)
except ResourceNotFoundError:
raise NotFound
return json_response(member)
<|end_body_0|>
<|body_start_1|>
try:
await get_data_from_req... | SpaceMemberView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpaceMemberView:
async def patch(self, space_id: int, member_id: Union[int, str], /, data: UpdateMemberRequest) -> Union[r200[UpdateMemberResponse], r404]:
"""Update a member. Changes the roles of the space member. Status Codes: 200: Successful operation 404: User not found"""
<|... | stack_v2_sparse_classes_36k_train_032706 | 4,595 | permissive | [
{
"docstring": "Update a member. Changes the roles of the space member. Status Codes: 200: Successful operation 404: User not found",
"name": "patch",
"signature": "async def patch(self, space_id: int, member_id: Union[int, str], /, data: UpdateMemberRequest) -> Union[r200[UpdateMemberResponse], r404]"
... | 2 | null | Implement the Python class `SpaceMemberView` described below.
Class description:
Implement the SpaceMemberView class.
Method signatures and docstrings:
- async def patch(self, space_id: int, member_id: Union[int, str], /, data: UpdateMemberRequest) -> Union[r200[UpdateMemberResponse], r404]: Update a member. Changes ... | Implement the Python class `SpaceMemberView` described below.
Class description:
Implement the SpaceMemberView class.
Method signatures and docstrings:
- async def patch(self, space_id: int, member_id: Union[int, str], /, data: UpdateMemberRequest) -> Union[r200[UpdateMemberResponse], r404]: Update a member. Changes ... | 1d17d2ba570cf5487e7514bec29250a5b368bb0a | <|skeleton|>
class SpaceMemberView:
async def patch(self, space_id: int, member_id: Union[int, str], /, data: UpdateMemberRequest) -> Union[r200[UpdateMemberResponse], r404]:
"""Update a member. Changes the roles of the space member. Status Codes: 200: Successful operation 404: User not found"""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpaceMemberView:
async def patch(self, space_id: int, member_id: Union[int, str], /, data: UpdateMemberRequest) -> Union[r200[UpdateMemberResponse], r404]:
"""Update a member. Changes the roles of the space member. Status Codes: 200: Successful operation 404: User not found"""
try:
... | the_stack_v2_python_sparse | virtool/spaces/api.py | virtool/virtool | train | 45 | |
c3d62925118f0efa5ad6e18c967e9e15892c5fdc | [
"data = request.GET.get('search_data')\nlogger.info('系统参数配置列表，搜索数据:{}'.format(data))\ntry:\n if data:\n search_data = {}\n data = eval(data)\n for key, value in data.items():\n if bool(key) and bool(value):\n search_data[key] = data[key]\n roles = VersionForP... | <|body_start_0|>
data = request.GET.get('search_data')
logger.info('系统参数配置列表，搜索数据:{}'.format(data))
try:
if data:
search_data = {}
data = eval(data)
for key, value in data.items():
if bool(key) and bool(value):
... | @Author: 朱孟彤 @desc: 版本号相关接口 | VersionApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VersionApi:
"""@Author: 朱孟彤 @desc: 版本号相关接口"""
def get(self, request):
"""项目的版本号配置，列表和搜索 :param request: :return:"""
<|body_0|>
def post(self, request):
"""新增项目的版本号配置 :param request: :return:"""
<|body_1|>
def put(self, request):
"""更改项目的版本号配置... | stack_v2_sparse_classes_36k_train_032707 | 18,561 | no_license | [
{
"docstring": "项目的版本号配置，列表和搜索 :param request: :return:",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "新增项目的版本号配置 :param request: :return:",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "更改项目的版本号配置 :param request: :return:",
... | 3 | stack_v2_sparse_classes_30k_train_017148 | Implement the Python class `VersionApi` described below.
Class description:
@Author: 朱孟彤 @desc: 版本号相关接口
Method signatures and docstrings:
- def get(self, request): 项目的版本号配置，列表和搜索 :param request: :return:
- def post(self, request): 新增项目的版本号配置 :param request: :return:
- def put(self, request): 更改项目的版本号配置 :param request... | Implement the Python class `VersionApi` described below.
Class description:
@Author: 朱孟彤 @desc: 版本号相关接口
Method signatures and docstrings:
- def get(self, request): 项目的版本号配置，列表和搜索 :param request: :return:
- def post(self, request): 新增项目的版本号配置 :param request: :return:
- def put(self, request): 更改项目的版本号配置 :param request... | c6e9c2f5aa0c9c42e023050f30176007214431ed | <|skeleton|>
class VersionApi:
"""@Author: 朱孟彤 @desc: 版本号相关接口"""
def get(self, request):
"""项目的版本号配置，列表和搜索 :param request: :return:"""
<|body_0|>
def post(self, request):
"""新增项目的版本号配置 :param request: :return:"""
<|body_1|>
def put(self, request):
"""更改项目的版本号配置... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VersionApi:
"""@Author: 朱孟彤 @desc: 版本号相关接口"""
def get(self, request):
"""项目的版本号配置，列表和搜索 :param request: :return:"""
data = request.GET.get('search_data')
logger.info('系统参数配置列表，搜索数据:{}'.format(data))
try:
if data:
search_data = {}
... | the_stack_v2_python_sparse | PlatApp/RestFulForApp/BaseRestFul.py | QGuten/First_Try | train | 0 |
cc0b36428e21a392ba04c6f31e97140d306df458 | [
"self.IO = IO\nself.GR = GR\nself.PF_MLI = PF_MLI\nself.CF_MLI = CF_MLI\nself.ltp_inc = ltp_inc\nself.max_weight = max_weight\nself.ltp_bins = int(window / defaultclock.dt)\nSpikeMonitor.__init__(self, IO)",
"if len(spikes):\n mli_inds = PF_MLI_LTP.postsynaptic_indexes(spikes, self.CF_MLI)\n gr_inds = PF_ML... | <|body_start_0|>
self.IO = IO
self.GR = GR
self.PF_MLI = PF_MLI
self.CF_MLI = CF_MLI
self.ltp_inc = ltp_inc
self.max_weight = max_weight
self.ltp_bins = int(window / defaultclock.dt)
SpikeMonitor.__init__(self, IO)
<|end_body_0|>
<|body_start_1|>
... | Implements additive LTP on PF-MLI synapses driven by CF activity | PF_MLI_LTP | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PF_MLI_LTP:
"""Implements additive LTP on PF-MLI synapses driven by CF activity"""
def __init__(self, IO, GR, PF_MLI, CF_MLI, ltp_inc, max_weight, window=50 * ms):
"""IO: NeuronGroup of inferior olive neurons GR: NeuronGroup of granule cells PF_MLI: Synapses object of PF-MLI synapses... | stack_v2_sparse_classes_36k_train_032708 | 5,461 | no_license | [
{
"docstring": "IO: NeuronGroup of inferior olive neurons GR: NeuronGroup of granule cells PF_MLI: Synapses object of PF-MLI synapses CF_MLI: Synapses object of CF-MLI synapses ltp_inc: the additive constant to increment PF-MLI synapses by window: the time window to depress PF-PKJ synapses for GR spikes that pr... | 2 | stack_v2_sparse_classes_30k_train_000003 | Implement the Python class `PF_MLI_LTP` described below.
Class description:
Implements additive LTP on PF-MLI synapses driven by CF activity
Method signatures and docstrings:
- def __init__(self, IO, GR, PF_MLI, CF_MLI, ltp_inc, max_weight, window=50 * ms): IO: NeuronGroup of inferior olive neurons GR: NeuronGroup of... | Implement the Python class `PF_MLI_LTP` described below.
Class description:
Implements additive LTP on PF-MLI synapses driven by CF activity
Method signatures and docstrings:
- def __init__(self, IO, GR, PF_MLI, CF_MLI, ltp_inc, max_weight, window=50 * ms): IO: NeuronGroup of inferior olive neurons GR: NeuronGroup of... | 6579a4d9636332267d0f26d8d4c8226e4fecf85d | <|skeleton|>
class PF_MLI_LTP:
"""Implements additive LTP on PF-MLI synapses driven by CF activity"""
def __init__(self, IO, GR, PF_MLI, CF_MLI, ltp_inc, max_weight, window=50 * ms):
"""IO: NeuronGroup of inferior olive neurons GR: NeuronGroup of granule cells PF_MLI: Synapses object of PF-MLI synapses... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PF_MLI_LTP:
"""Implements additive LTP on PF-MLI synapses driven by CF activity"""
def __init__(self, IO, GR, PF_MLI, CF_MLI, ltp_inc, max_weight, window=50 * ms):
"""IO: NeuronGroup of inferior olive neurons GR: NeuronGroup of granule cells PF_MLI: Synapses object of PF-MLI synapses CF_MLI: Syna... | the_stack_v2_python_sparse | neuron_models/cf_learning.py | blennon/research | train | 0 |
13b6f1708e8eae4a0ba73b4f17ad4ffdc0d265f1 | [
"place = PlaceTrend(date_begin=None, date_end=None)\nprovinces = place.get_provinces()\nreturn provinces",
"assert re.match('\\\\w{2,10}省$', province), 'the format of province is wrong ,the right format such as \"广东省\" '\nplace = PlaceTrend(date_begin=None, date_end=None)\ncitys = place.get_citys(province)\nretur... | <|body_start_0|>
place = PlaceTrend(date_begin=None, date_end=None)
provinces = place.get_provinces()
return provinces
<|end_body_0|>
<|body_start_1|>
assert re.match('\\w{2,10}省$', province), 'the format of province is wrong ,the right format such as "广东省" '
place = PlaceTrend(... | PositiongParent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PositiongParent:
def get_all_province(self) -> list:
"""获取可以监测的省份 :return 省份列表 [广东省，广西省.....]"""
<|body_0|>
def get_all_city(self, province: str) -> list:
"""获取该省份下可以监测的城市 :return 城市列表"""
<|body_1|>
def get_all_place(self, province: str, city: str) -> li... | stack_v2_sparse_classes_36k_train_032709 | 1,525 | no_license | [
{
"docstring": "获取可以监测的省份 :return 省份列表 [广东省，广西省.....]",
"name": "get_all_province",
"signature": "def get_all_province(self) -> list"
},
{
"docstring": "获取该省份下可以监测的城市 :return 城市列表",
"name": "get_all_city",
"signature": "def get_all_city(self, province: str) -> list"
},
{
"docstri... | 3 | stack_v2_sparse_classes_30k_train_000345 | Implement the Python class `PositiongParent` described below.
Class description:
Implement the PositiongParent class.
Method signatures and docstrings:
- def get_all_province(self) -> list: 获取可以监测的省份 :return 省份列表 [广东省，广西省.....]
- def get_all_city(self, province: str) -> list: 获取该省份下可以监测的城市 :return 城市列表
- def get_all_... | Implement the Python class `PositiongParent` described below.
Class description:
Implement the PositiongParent class.
Method signatures and docstrings:
- def get_all_province(self) -> list: 获取可以监测的省份 :return 省份列表 [广东省，广西省.....]
- def get_all_city(self, province: str) -> list: 获取该省份下可以监测的城市 :return 城市列表
- def get_all_... | 5e34873cd13950dd3b5dc6341aad144522af0eae | <|skeleton|>
class PositiongParent:
def get_all_province(self) -> list:
"""获取可以监测的省份 :return 省份列表 [广东省，广西省.....]"""
<|body_0|>
def get_all_city(self, province: str) -> list:
"""获取该省份下可以监测的城市 :return 城市列表"""
<|body_1|>
def get_all_place(self, province: str, city: str) -> li... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PositiongParent:
def get_all_province(self) -> list:
"""获取可以监测的省份 :return 省份列表 [广东省，广西省.....]"""
place = PlaceTrend(date_begin=None, date_end=None)
provinces = place.get_provinces()
return provinces
def get_all_city(self, province: str) -> list:
"""获取该省份下可以监测的城市 :r... | the_stack_v2_python_sparse | spyderpro/function/people_function/_positioning_parent.py | LianZS/spyderpro | train | 8 | |
ccbe48d5b49a060038f846c1e0daf778fb293263 | [
"hashmap = dict()\nfor x in nums:\n hashmap[x] = hashmap.get(x, 0) + 1\nresult = []\nfor k in hashmap:\n if hashmap[k] == 2:\n result.append(k)\nreturn result",
"result = []\nfor i in range(len(nums)):\n index = abs(nums[i]) - 1\n if nums[index] < 0:\n result.append(abs(nums[i]))\n nu... | <|body_start_0|>
hashmap = dict()
for x in nums:
hashmap[x] = hashmap.get(x, 0) + 1
result = []
for k in hashmap:
if hashmap[k] == 2:
result.append(k)
return result
<|end_body_0|>
<|body_start_1|>
result = []
for i in range... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicates(self, nums):
"""哈希表 :param list[int] nums: :return: list[int]"""
<|body_0|>
def findDuplicates2(self, nums):
"""1. 找到数字i时，将位置i-1处的数字翻转为负数。 2. 如果位置i-1 上的数字已经为负，则i是出现两次的数字。 :param list[int] nums: :return: list[int]"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k_train_032710 | 1,543 | no_license | [
{
"docstring": "哈希表 :param list[int] nums: :return: list[int]",
"name": "findDuplicates",
"signature": "def findDuplicates(self, nums)"
},
{
"docstring": "1. 找到数字i时，将位置i-1处的数字翻转为负数。 2. 如果位置i-1 上的数字已经为负，则i是出现两次的数字。 :param list[int] nums: :return: list[int]",
"name": "findDuplicates2",
"si... | 2 | stack_v2_sparse_classes_30k_train_009947 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicates(self, nums): 哈希表 :param list[int] nums: :return: list[int]
- def findDuplicates2(self, nums): 1. 找到数字i时，将位置i-1处的数字翻转为负数。 2. 如果位置i-1 上的数字已经为负，则i是出现两次的数字。 :param... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicates(self, nums): 哈希表 :param list[int] nums: :return: list[int]
- def findDuplicates2(self, nums): 1. 找到数字i时，将位置i-1处的数字翻转为负数。 2. 如果位置i-1 上的数字已经为负，则i是出现两次的数字。 :param... | 837957ea22aa07ce28a6c23ea0419bd2011e1f88 | <|skeleton|>
class Solution:
def findDuplicates(self, nums):
"""哈希表 :param list[int] nums: :return: list[int]"""
<|body_0|>
def findDuplicates2(self, nums):
"""1. 找到数字i时，将位置i-1处的数字翻转为负数。 2. 如果位置i-1 上的数字已经为负，则i是出现两次的数字。 :param list[int] nums: :return: list[int]"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDuplicates(self, nums):
"""哈希表 :param list[int] nums: :return: list[int]"""
hashmap = dict()
for x in nums:
hashmap[x] = hashmap.get(x, 0) + 1
result = []
for k in hashmap:
if hashmap[k] == 2:
result.append(k)
... | the_stack_v2_python_sparse | 华为题库/数组中重复的数据.py | 2226171237/Algorithmpractice | train | 0 | |
583831e75af3bcc0eb02847a81b3def88139a26a | [
"self.head = head\ncheckPointer = head\nself.llLength = 0\nwhile checkPointer:\n self.llLength += 1\n checkPointer = checkPointer.next",
"pointer = self.head\nfor i in range(1, randint(1, self.llLength)):\n pointer = pointer.next\nreturn pointer.val"
] | <|body_start_0|>
self.head = head
checkPointer = head
self.llLength = 0
while checkPointer:
self.llLength += 1
checkPointer = checkPointer.next
<|end_body_0|>
<|body_start_1|>
pointer = self.head
for i in range(1, randint(1, self.llLength)):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, head):
"""@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode"""
<|body_0|>
def getRandom(self):
"""Returns a random node's value. :rtype: int"""
... | stack_v2_sparse_classes_36k_train_032711 | 1,107 | no_license | [
{
"docstring": "@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode",
"name": "__init__",
"signature": "def __init__(self, head)"
},
{
"docstring": "Returns a random node's value. :rtype: int",
"name": "g... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, head): @param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode
- def getRan... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, head): @param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode
- def getRan... | 5deff070bb9f6b19a1cfc0a6086ac155496fbb78 | <|skeleton|>
class Solution:
def __init__(self, head):
"""@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode"""
<|body_0|>
def getRandom(self):
"""Returns a random node's value. :rtype: int"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, head):
"""@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode"""
self.head = head
checkPointer = head
self.llLength = 0
while checkPointer:
s... | the_stack_v2_python_sparse | lc_linked_list_random_node.py | vincentt117/coding_challenge | train | 1 | |
6308c615f1eaf57354b82a4af1a81cc9abd796b1 | [
"self.__function = function\nself.__args = args\nself.__kwargs = kwargs\nself.__status = False\nself.__thread = False\nself.__lock = _thread.allocate_lock()",
"self.__lock.acquire()\nself.__status = True\nif not self.__thread:\n self.__thread = True\n _thread.start_new_thread(self.__run, ())\nself.__lock.re... | <|body_start_0|>
self.__function = function
self.__args = args
self.__kwargs = kwargs
self.__status = False
self.__thread = False
self.__lock = _thread.allocate_lock()
<|end_body_0|>
<|body_start_1|>
self.__lock.acquire()
self.__status = True
if n... | Mille_Timer(function, *args, **kwargs) -> Mille Timer | Mille_Timer | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mille_Timer:
"""Mille_Timer(function, *args, **kwargs) -> Mille Timer"""
def __init__(self, function, *args, **kwargs):
"""Initialize the Mille_Timer object."""
<|body_0|>
def start(self):
"""Start the Mille_Timer object."""
<|body_1|>
def stop(self)... | stack_v2_sparse_classes_36k_train_032712 | 3,709 | permissive | [
{
"docstring": "Initialize the Mille_Timer object.",
"name": "__init__",
"signature": "def __init__(self, function, *args, **kwargs)"
},
{
"docstring": "Start the Mille_Timer object.",
"name": "start",
"signature": "def start(self)"
},
{
"docstring": "Stop the Mille_Timer object.... | 4 | stack_v2_sparse_classes_30k_train_008513 | Implement the Python class `Mille_Timer` described below.
Class description:
Mille_Timer(function, *args, **kwargs) -> Mille Timer
Method signatures and docstrings:
- def __init__(self, function, *args, **kwargs): Initialize the Mille_Timer object.
- def start(self): Start the Mille_Timer object.
- def stop(self): St... | Implement the Python class `Mille_Timer` described below.
Class description:
Mille_Timer(function, *args, **kwargs) -> Mille Timer
Method signatures and docstrings:
- def __init__(self, function, *args, **kwargs): Initialize the Mille_Timer object.
- def start(self): Start the Mille_Timer object.
- def stop(self): St... | d097ca0ad6a6aee2180d32dce6a3322621f655fd | <|skeleton|>
class Mille_Timer:
"""Mille_Timer(function, *args, **kwargs) -> Mille Timer"""
def __init__(self, function, *args, **kwargs):
"""Initialize the Mille_Timer object."""
<|body_0|>
def start(self):
"""Start the Mille_Timer object."""
<|body_1|>
def stop(self)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Mille_Timer:
"""Mille_Timer(function, *args, **kwargs) -> Mille Timer"""
def __init__(self, function, *args, **kwargs):
"""Initialize the Mille_Timer object."""
self.__function = function
self.__args = args
self.__kwargs = kwargs
self.__status = False
self.... | the_stack_v2_python_sparse | recipes/Python/502238_Aens_Time/recipe-502238.py | betty29/code-1 | train | 0 |
ea00a492226e7fdd85c43a7aaac4543a7d627f5f | [
"strfpn = 'simple.test-myversion1:ascii:mydb#1'\nfpn = ccm.FourPartName(strfpn)\nassert fpn.name == 'simple.test'\nassert fpn.version == 'myversion1'\nassert fpn.type == 'ascii'\nassert fpn.instance == 'mydb#1'\nassert strfpn == str(fpn)\nassert strfpn == fpn.objectname",
"strfpn = 'simple test.ext - myversion1 :... | <|body_start_0|>
strfpn = 'simple.test-myversion1:ascii:mydb#1'
fpn = ccm.FourPartName(strfpn)
assert fpn.name == 'simple.test'
assert fpn.version == 'myversion1'
assert fpn.type == 'ascii'
assert fpn.instance == 'mydb#1'
assert strfpn == str(fpn)
assert s... | Unit test case for testing four part name of a ccm project | FourPartNameTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FourPartNameTest:
"""Unit test case for testing four part name of a ccm project"""
def testSimpleFourPartNameParsing(self):
"""Test the parsing of a simple four part name"""
<|body_0|>
def testSpacesFourPartNameParsing(self):
"""Test the parsing of a four part na... | stack_v2_sparse_classes_36k_train_032713 | 5,649 | no_license | [
{
"docstring": "Test the parsing of a simple four part name",
"name": "testSimpleFourPartNameParsing",
"signature": "def testSimpleFourPartNameParsing(self)"
},
{
"docstring": "Test the parsing of a four part name that contains spaces",
"name": "testSpacesFourPartNameParsing",
"signature... | 6 | stack_v2_sparse_classes_30k_train_013507 | Implement the Python class `FourPartNameTest` described below.
Class description:
Unit test case for testing four part name of a ccm project
Method signatures and docstrings:
- def testSimpleFourPartNameParsing(self): Test the parsing of a simple four part name
- def testSpacesFourPartNameParsing(self): Test the pars... | Implement the Python class `FourPartNameTest` described below.
Class description:
Unit test case for testing four part name of a ccm project
Method signatures and docstrings:
- def testSimpleFourPartNameParsing(self): Test the parsing of a simple four part name
- def testSpacesFourPartNameParsing(self): Test the pars... | f458a4ce83f74d603362fe6b71eaa647ccc62fee | <|skeleton|>
class FourPartNameTest:
"""Unit test case for testing four part name of a ccm project"""
def testSimpleFourPartNameParsing(self):
"""Test the parsing of a simple four part name"""
<|body_0|>
def testSpacesFourPartNameParsing(self):
"""Test the parsing of a four part na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FourPartNameTest:
"""Unit test case for testing four part name of a ccm project"""
def testSimpleFourPartNameParsing(self):
"""Test the parsing of a simple four part name"""
strfpn = 'simple.test-myversion1:ascii:mydb#1'
fpn = ccm.FourPartName(strfpn)
assert fpn.name == 's... | the_stack_v2_python_sparse | buildframework/helium/sf/python/pythoncore/lib/pythoncoretests/test_ccm_4pn.py | anagovitsyn/oss.FCL.sftools.dev.build | train | 0 |
082d127377253de077469e704d5fff2dde4b68c6 | [
"d = {i: i ** 2 for i in range(0, 10)}\nrecord = [n]\nwhile n != 1:\n new_n = 0\n while n != 0:\n new_n += d[n % 10]\n n //= 10\n if new_n in record:\n return False\n else:\n record.append(new_n)\n n = new_n\nreturn True",
"def new_number(n):\n total = 0\n whil... | <|body_start_0|>
d = {i: i ** 2 for i in range(0, 10)}
record = [n]
while n != 1:
new_n = 0
while n != 0:
new_n += d[n % 10]
n //= 10
if new_n in record:
return False
else:
record.appe... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isHappy(self, n):
""":type n: int :rtype: bool"""
<|body_0|>
def isHappy2(self, n):
""":type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
d = {i: i ** 2 for i in range(0, 10)}
record = [n]
while n... | stack_v2_sparse_classes_36k_train_032714 | 1,123 | no_license | [
{
"docstring": ":type n: int :rtype: bool",
"name": "isHappy",
"signature": "def isHappy(self, n)"
},
{
"docstring": ":type n: int :rtype: bool",
"name": "isHappy2",
"signature": "def isHappy2(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011985 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isHappy(self, n): :type n: int :rtype: bool
- def isHappy2(self, n): :type n: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isHappy(self, n): :type n: int :rtype: bool
- def isHappy2(self, n): :type n: int :rtype: bool
<|skeleton|>
class Solution:
def isHappy(self, n):
""":type n: in... | ac53dd9bf2c4c9d17c9dc5f7fdda32e386658fdd | <|skeleton|>
class Solution:
def isHappy(self, n):
""":type n: int :rtype: bool"""
<|body_0|>
def isHappy2(self, n):
""":type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isHappy(self, n):
""":type n: int :rtype: bool"""
d = {i: i ** 2 for i in range(0, 10)}
record = [n]
while n != 1:
new_n = 0
while n != 0:
new_n += d[n % 10]
n //= 10
if new_n in record:
... | the_stack_v2_python_sparse | random/happy_number.py | hwc1824/LeetCodeSolution | train | 0 | |
06cf7d943386aae8856e2ed875a8becd2816a943 | [
"if len(prices) < 2:\n return 0\ndp = [[0 for _ in range(2)] for _ in range(len(prices))]\ndp[0][0] = 0\ndp[0][1] = -prices[0]\nfor i in range(1, len(prices)):\n dp[i][0] = max(dp[i - 1][1] + prices[i], dp[i - 1][0])\n dp[i][1] = max(dp[i - 1][1], -prices[i])\nreturn dp[-1][0]",
"if len(prices) < 2:\n ... | <|body_start_0|>
if len(prices) < 2:
return 0
dp = [[0 for _ in range(2)] for _ in range(len(prices))]
dp[0][0] = 0
dp[0][1] = -prices[0]
for i in range(1, len(prices)):
dp[i][0] = max(dp[i - 1][1] + prices[i], dp[i - 1][0])
dp[i][1] = max(dp[i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""最大股票收益 dp[i][0] = max(dp[i - 1][1] + prices[i], dp[i - 1][0]) dp[i][1] = max(dp[i - 1][1], -prices[i]) :param prices: :return:"""
<|body_0|>
def maxProfit1(self, prices: List[int]) -> int:
"""空间优化 :param pri... | stack_v2_sparse_classes_36k_train_032715 | 1,849 | no_license | [
{
"docstring": "最大股票收益 dp[i][0] = max(dp[i - 1][1] + prices[i], dp[i - 1][0]) dp[i][1] = max(dp[i - 1][1], -prices[i]) :param prices: :return:",
"name": "maxProfit",
"signature": "def maxProfit(self, prices: List[int]) -> int"
},
{
"docstring": "空间优化 :param prices: :return:",
"name": "maxPro... | 2 | stack_v2_sparse_classes_30k_train_010088 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 最大股票收益 dp[i][0] = max(dp[i - 1][1] + prices[i], dp[i - 1][0]) dp[i][1] = max(dp[i - 1][1], -prices[i]) :param prices: :return:
- de... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 最大股票收益 dp[i][0] = max(dp[i - 1][1] + prices[i], dp[i - 1][0]) dp[i][1] = max(dp[i - 1][1], -prices[i]) :param prices: :return:
- de... | 9acba92695c06406f12f997a720bfe1deb9464a8 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""最大股票收益 dp[i][0] = max(dp[i - 1][1] + prices[i], dp[i - 1][0]) dp[i][1] = max(dp[i - 1][1], -prices[i]) :param prices: :return:"""
<|body_0|>
def maxProfit1(self, prices: List[int]) -> int:
"""空间优化 :param pri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""最大股票收益 dp[i][0] = max(dp[i - 1][1] + prices[i], dp[i - 1][0]) dp[i][1] = max(dp[i - 1][1], -prices[i]) :param prices: :return:"""
if len(prices) < 2:
return 0
dp = [[0 for _ in range(2)] for _ in range(len(prices))... | the_stack_v2_python_sparse | datastructure/dp_exercise/MaxProfit.py | yinhuax/leet_code | train | 0 | |
b958414938ae9c1d9dff5805e3af523dad365175 | [
"try:\n from bs4 import BeautifulSoup\nexcept ImportError:\n raise ValueError('Could not import python packages. Please install it with `pip install beautifulsoup4`. ')\ntry:\n _ = BeautifulSoup('<html><body>Parser builder library test.</body></html>', **kwargs)\nexcept Exception as e:\n raise ValueErro... | <|body_start_0|>
try:
from bs4 import BeautifulSoup
except ImportError:
raise ValueError('Could not import python packages. Please install it with `pip install beautifulsoup4`. ')
try:
_ = BeautifulSoup('<html><body>Parser builder library test.</body></html>',... | Loader that loads ReadTheDocs documentation directory dump. | ReadTheDocsLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReadTheDocsLoader:
"""Loader that loads ReadTheDocs documentation directory dump."""
def __init__(self, path: str, encoding: Optional[str]=None, errors: Optional[str]=None, **kwargs: Optional[Any]):
"""Initialize path."""
<|body_0|>
def load(self) -> List[Document]:
... | stack_v2_sparse_classes_36k_train_032716 | 2,094 | no_license | [
{
"docstring": "Initialize path.",
"name": "__init__",
"signature": "def __init__(self, path: str, encoding: Optional[str]=None, errors: Optional[str]=None, **kwargs: Optional[Any])"
},
{
"docstring": "Load documents.",
"name": "load",
"signature": "def load(self) -> List[Document]"
}
... | 2 | stack_v2_sparse_classes_30k_train_014478 | Implement the Python class `ReadTheDocsLoader` described below.
Class description:
Loader that loads ReadTheDocs documentation directory dump.
Method signatures and docstrings:
- def __init__(self, path: str, encoding: Optional[str]=None, errors: Optional[str]=None, **kwargs: Optional[Any]): Initialize path.
- def lo... | Implement the Python class `ReadTheDocsLoader` described below.
Class description:
Loader that loads ReadTheDocs documentation directory dump.
Method signatures and docstrings:
- def __init__(self, path: str, encoding: Optional[str]=None, errors: Optional[str]=None, **kwargs: Optional[Any]): Initialize path.
- def lo... | b7aaa920a52613e3f1f04fa5cd7568ad37302d11 | <|skeleton|>
class ReadTheDocsLoader:
"""Loader that loads ReadTheDocs documentation directory dump."""
def __init__(self, path: str, encoding: Optional[str]=None, errors: Optional[str]=None, **kwargs: Optional[Any]):
"""Initialize path."""
<|body_0|>
def load(self) -> List[Document]:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReadTheDocsLoader:
"""Loader that loads ReadTheDocs documentation directory dump."""
def __init__(self, path: str, encoding: Optional[str]=None, errors: Optional[str]=None, **kwargs: Optional[Any]):
"""Initialize path."""
try:
from bs4 import BeautifulSoup
except Impor... | the_stack_v2_python_sparse | openai/venv/lib/python3.10/site-packages/langchain/document_loaders/readthedocs.py | henrymendez/garage | train | 0 |
f6a2d84c6c26292b2622a9487cde697bf4f90517 | [
"if self.action in ['retrieve', 'list', 'add_view']:\n permission_classes = [AllowAny]\nelse:\n permission_classes = [IsAdminUser]\nreturn [permission() for permission in permission_classes]",
"queryset = super().get_queryset()\nif self.request.user.is_authenticated and self.request.user.is_staff:\n retu... | <|body_start_0|>
if self.action in ['retrieve', 'list', 'add_view']:
permission_classes = [AllowAny]
else:
permission_classes = [IsAdminUser]
return [permission() for permission in permission_classes]
<|end_body_0|>
<|body_start_1|>
queryset = super().get_queryse... | Provide all methods for manage Story. | StoryViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StoryViewSet:
"""Provide all methods for manage Story."""
def get_permissions(self):
"""Instantiates and returns the list of permissions that this view requires."""
<|body_0|>
def get_queryset(self):
"""Customize the queryset according to the current user."""
... | stack_v2_sparse_classes_36k_train_032717 | 3,643 | no_license | [
{
"docstring": "Instantiates and returns the list of permissions that this view requires.",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "Customize the queryset according to the current user.",
"name": "get_queryset",
"signature": "def get_queryse... | 4 | stack_v2_sparse_classes_30k_train_002934 | Implement the Python class `StoryViewSet` described below.
Class description:
Provide all methods for manage Story.
Method signatures and docstrings:
- def get_permissions(self): Instantiates and returns the list of permissions that this view requires.
- def get_queryset(self): Customize the queryset according to the... | Implement the Python class `StoryViewSet` described below.
Class description:
Provide all methods for manage Story.
Method signatures and docstrings:
- def get_permissions(self): Instantiates and returns the list of permissions that this view requires.
- def get_queryset(self): Customize the queryset according to the... | 617f6c990845d233efa64c9f0b309f5afef17590 | <|skeleton|>
class StoryViewSet:
"""Provide all methods for manage Story."""
def get_permissions(self):
"""Instantiates and returns the list of permissions that this view requires."""
<|body_0|>
def get_queryset(self):
"""Customize the queryset according to the current user."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StoryViewSet:
"""Provide all methods for manage Story."""
def get_permissions(self):
"""Instantiates and returns the list of permissions that this view requires."""
if self.action in ['retrieve', 'list', 'add_view']:
permission_classes = [AllowAny]
else:
pe... | the_stack_v2_python_sparse | apps/story/views.py | patate-et-cornichon/patateetcornichon-api | train | 3 |
e7a1209972b3effdd905a692fbd251690bb9b1b8 | [
"sender = super()._get_sender(mlist, msg, msgdata)\nif msgdata.get('verp', False):\n log.debug('VERPing %s', msg.get('message-id'))\n recipient = msgdata['recipient']\n sender_mailbox, sender_domain = split_email(sender)\n recipient_mailbox, recipient_domain = split_email(recipient)\n if recipient_do... | <|body_start_0|>
sender = super()._get_sender(mlist, msg, msgdata)
if msgdata.get('verp', False):
log.debug('VERPing %s', msg.get('message-id'))
recipient = msgdata['recipient']
sender_mailbox, sender_domain = split_email(sender)
recipient_mailbox, recipie... | Mixin for VERP functionality. This works by overriding the base class's _get_sender() method to return the VERP'd envelope sender. It expects the individual recipient's address to be squirreled away in the message metadata. | VERPMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VERPMixin:
"""Mixin for VERP functionality. This works by overriding the base class's _get_sender() method to return the VERP'd envelope sender. It expects the individual recipient's address to be squirreled away in the message metadata."""
def _get_sender(self, mlist, msg, msgdata):
... | stack_v2_sparse_classes_36k_train_032718 | 3,636 | no_license | [
{
"docstring": "Return the recipient's address VERP encoded in the sender. :param mlist: The mailing list being delivered to. :type mlist: `IMailingList` :param msg: The original message being delivered. :type msg: `Message` :param msgdata: Additional message metadata for this delivery. :type msgdata: dictionar... | 2 | null | Implement the Python class `VERPMixin` described below.
Class description:
Mixin for VERP functionality. This works by overriding the base class's _get_sender() method to return the VERP'd envelope sender. It expects the individual recipient's address to be squirreled away in the message metadata.
Method signatures a... | Implement the Python class `VERPMixin` described below.
Class description:
Mixin for VERP functionality. This works by overriding the base class's _get_sender() method to return the VERP'd envelope sender. It expects the individual recipient's address to be squirreled away in the message metadata.
Method signatures a... | 7edf8148e34b9f73ca6433ceb43a1770f4fa32c1 | <|skeleton|>
class VERPMixin:
"""Mixin for VERP functionality. This works by overriding the base class's _get_sender() method to return the VERP'd envelope sender. It expects the individual recipient's address to be squirreled away in the message metadata."""
def _get_sender(self, mlist, msg, msgdata):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VERPMixin:
"""Mixin for VERP functionality. This works by overriding the base class's _get_sender() method to return the VERP'd envelope sender. It expects the individual recipient's address to be squirreled away in the message metadata."""
def _get_sender(self, mlist, msg, msgdata):
"""Return th... | the_stack_v2_python_sparse | libs/Mailman/mailman/mta/verp.py | masomel/py-import-analysis | train | 1 |
c3e4d59f2675a4c6c25e67ed6e09ae55142033c1 | [
"time_string = self._GetRowValue(query_hash, row, value_name)\nif time_string is None:\n return None\ndate_time = dfdatetime_time_elements.TimeElements()\ndate_time.CopyFromDateTimeString(time_string)\nreturn date_time",
"query_hash = hash(query)\nevent_data = KodiVideoEventData()\nevent_data.filename = self._... | <|body_start_0|>
time_string = self._GetRowValue(query_hash, row, value_name)
if time_string is None:
return None
date_time = dfdatetime_time_elements.TimeElements()
date_time.CopyFromDateTimeString(time_string)
return date_time
<|end_body_0|>
<|body_start_1|>
... | SQLite parser plugin for Kodi videos database files. The Kodi videos database file is typically stored in: MyVideos.db | KodiMyVideosPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KodiMyVideosPlugin:
"""SQLite parser plugin for Kodi videos database files. The Kodi videos database file is typically stored in: MyVideos.db"""
def _GetDateTimeRowValue(self, query_hash, row, value_name):
"""Retrieves a date and time value from the row. Args: query_hash (int): hash ... | stack_v2_sparse_classes_36k_train_032719 | 8,988 | permissive | [
{
"docstring": "Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, that uniquely identifies the query that produced the row. row (sqlite3.Row): row. value_name (str): name of the value. Returns: dfdatetime.CocoaTime: date and time value or None if not available.",
"name... | 2 | stack_v2_sparse_classes_30k_train_007442 | Implement the Python class `KodiMyVideosPlugin` described below.
Class description:
SQLite parser plugin for Kodi videos database files. The Kodi videos database file is typically stored in: MyVideos.db
Method signatures and docstrings:
- def _GetDateTimeRowValue(self, query_hash, row, value_name): Retrieves a date a... | Implement the Python class `KodiMyVideosPlugin` described below.
Class description:
SQLite parser plugin for Kodi videos database files. The Kodi videos database file is typically stored in: MyVideos.db
Method signatures and docstrings:
- def _GetDateTimeRowValue(self, query_hash, row, value_name): Retrieves a date a... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class KodiMyVideosPlugin:
"""SQLite parser plugin for Kodi videos database files. The Kodi videos database file is typically stored in: MyVideos.db"""
def _GetDateTimeRowValue(self, query_hash, row, value_name):
"""Retrieves a date and time value from the row. Args: query_hash (int): hash ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KodiMyVideosPlugin:
"""SQLite parser plugin for Kodi videos database files. The Kodi videos database file is typically stored in: MyVideos.db"""
def _GetDateTimeRowValue(self, query_hash, row, value_name):
"""Retrieves a date and time value from the row. Args: query_hash (int): hash of the query,... | the_stack_v2_python_sparse | plaso/parsers/sqlite_plugins/kodi.py | log2timeline/plaso | train | 1,506 |
b6d87621a4424a994a6b9e1f360dcab5c6438f8c | [
"self.url = url\nself.content = []\nself.spider_path = []\nif static:\n self.static_web_spider()\nelse:\n self.time_step = time_step\n self.scroll_time = scroll_time\n self.dynamic_web_spider()",
"driver = webdriver.Firefox(executable_path='src/geckodriver')\ndriver.get(self.url)\nfor i in range(int(s... | <|body_start_0|>
self.url = url
self.content = []
self.spider_path = []
if static:
self.static_web_spider()
else:
self.time_step = time_step
self.scroll_time = scroll_time
self.dynamic_web_spider()
<|end_body_0|>
<|body_start_1|>
... | Tree_spider will automatically get html from a given url. If the website is dynamic, argument static should be False. Then Tree_spider will use selenium to simulate browser (Firefox) to get html from dynamic website. | Tree_spider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tree_spider:
"""Tree_spider will automatically get html from a given url. If the website is dynamic, argument static should be False. Then Tree_spider will use selenium to simulate browser (Firefox) to get html from dynamic website."""
def __init__(self, url, static=True, time_step=0.2, scro... | stack_v2_sparse_classes_36k_train_032720 | 3,777 | no_license | [
{
"docstring": ":param url: the url of website that going to be crawled :param static: If website is dynamic website like IGN, static should be False :param time_step: scroll the page every 0.2 second in order to load the whole dynamic website :param scroll_time: total scroll time. For example, scroll_time is 3... | 5 | stack_v2_sparse_classes_30k_train_017683 | Implement the Python class `Tree_spider` described below.
Class description:
Tree_spider will automatically get html from a given url. If the website is dynamic, argument static should be False. Then Tree_spider will use selenium to simulate browser (Firefox) to get html from dynamic website.
Method signatures and do... | Implement the Python class `Tree_spider` described below.
Class description:
Tree_spider will automatically get html from a given url. If the website is dynamic, argument static should be False. Then Tree_spider will use selenium to simulate browser (Firefox) to get html from dynamic website.
Method signatures and do... | 60594e87175e68fc2953b7045628e3fa7b8c259c | <|skeleton|>
class Tree_spider:
"""Tree_spider will automatically get html from a given url. If the website is dynamic, argument static should be False. Then Tree_spider will use selenium to simulate browser (Firefox) to get html from dynamic website."""
def __init__(self, url, static=True, time_step=0.2, scro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tree_spider:
"""Tree_spider will automatically get html from a given url. If the website is dynamic, argument static should be False. Then Tree_spider will use selenium to simulate browser (Firefox) to get html from dynamic website."""
def __init__(self, url, static=True, time_step=0.2, scroll_time=300):... | the_stack_v2_python_sparse | src/util.py | tuosun98/Steam-game-reviews-DSCI510 | train | 0 |
7ab4c02a258c75c71d36646af7990d9d92d6a655 | [
"gtk.Fixed.__init__(self)\nself._lst_labels = [u'λ<sub>b</sub>:', u'π<sub>Q</sub>:', u'π<sub>E</sub>:']\nself._dtc_data_controller = controller\nself._hardware_id = kwargs['hardware_id']\nself._subcategory_id = kwargs['subcategory_id']\nself._lblModel = ramstk.RAMSTKLabel('', tooltip=_(u'The assessment model used t... | <|body_start_0|>
gtk.Fixed.__init__(self)
self._lst_labels = [u'λ<sub>b</sub>:', u'π<sub>Q</sub>:', u'π<sub>E</sub>:']
self._dtc_data_controller = controller
self._hardware_id = kwargs['hardware_id']
self._subcategory_id = kwargs['subcategory_id']
self._lblModel = ramstk.... | Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 parts count and MIL-HDBK-217FN2 part stress methods. The attributes of a Hardware asse... | AssessmentResults | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssessmentResults:
"""Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 parts count and MIL-HDBK-217FN2 part stre... | stack_v2_sparse_classes_36k_train_032721 | 35,514 | permissive | [
{
"docstring": "Initialize an instance of the Hardware assessment result view. :param controller: the hardware data controller instance. :type controller: :class:`ramstk.hardware.Controller.HardwareBoMDataController` :param int hardware_id: the hardware ID of the currently selected hardware item. :param int sub... | 4 | stack_v2_sparse_classes_30k_train_015782 | Implement the Python class `AssessmentResults` described below.
Class description:
Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 pa... | Implement the Python class `AssessmentResults` described below.
Class description:
Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 pa... | 488ffed8b842399ddcae93007de6c6f1dda23d05 | <|skeleton|>
class AssessmentResults:
"""Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 parts count and MIL-HDBK-217FN2 part stre... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AssessmentResults:
"""Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 parts count and MIL-HDBK-217FN2 part stress methods. T... | the_stack_v2_python_sparse | src/ramstk/gui/gtk/workviews/components/Component.py | JmiXIII/ramstk | train | 0 |
f1c4c0d942bd6af416c893bc13fd5b7352aebe21 | [
"self.value = value\nself.identifier = identifier\nself.hint = hint",
"hint = self.hint\nif isinstance(hint, type):\n type_hint = hint.__name__\nelif hint == ():\n type_hint = \"'no type'\"\nelif isinstance(hint, tuple):\n type_hint = ', '.join([type_.__name__ for type_ in hint])\nelse:\n type_hint = ... | <|body_start_0|>
self.value = value
self.identifier = identifier
self.hint = hint
<|end_body_0|>
<|body_start_1|>
hint = self.hint
if isinstance(hint, type):
type_hint = hint.__name__
elif hint == ():
type_hint = "'no type'"
elif isinstanc... | An argument or value is not of the specified type. `DoxhooksTypeError` extends `DoxhooksDataError`. Magic Methods ------------- __str__ Override `DoxhooksDataError.__str__` to compose a message. | DoxhooksTypeError | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoxhooksTypeError:
"""An argument or value is not of the specified type. `DoxhooksTypeError` extends `DoxhooksDataError`. Magic Methods ------------- __str__ Override `DoxhooksDataError.__str__` to compose a message."""
def __init__(self, value, identifier, hint):
"""Initialise the e... | stack_v2_sparse_classes_36k_train_032722 | 10,728 | permissive | [
{
"docstring": "Initialise the error with parameters of the error message. The `DoxhooksTypeError` constructor overrides the `DoxhooksDataError` constructor with parameters of the error message. Parameters ---------- value The value that caused the error. identifier : str An identifier that the user associates ... | 2 | stack_v2_sparse_classes_30k_train_011376 | Implement the Python class `DoxhooksTypeError` described below.
Class description:
An argument or value is not of the specified type. `DoxhooksTypeError` extends `DoxhooksDataError`. Magic Methods ------------- __str__ Override `DoxhooksDataError.__str__` to compose a message.
Method signatures and docstrings:
- def ... | Implement the Python class `DoxhooksTypeError` described below.
Class description:
An argument or value is not of the specified type. `DoxhooksTypeError` extends `DoxhooksDataError`. Magic Methods ------------- __str__ Override `DoxhooksDataError.__str__` to compose a message.
Method signatures and docstrings:
- def ... | 8cb346fb1830a24af5640b948a85a578cc905db6 | <|skeleton|>
class DoxhooksTypeError:
"""An argument or value is not of the specified type. `DoxhooksTypeError` extends `DoxhooksDataError`. Magic Methods ------------- __str__ Override `DoxhooksDataError.__str__` to compose a message."""
def __init__(self, value, identifier, hint):
"""Initialise the e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DoxhooksTypeError:
"""An argument or value is not of the specified type. `DoxhooksTypeError` extends `DoxhooksDataError`. Magic Methods ------------- __str__ Override `DoxhooksDataError.__str__` to compose a message."""
def __init__(self, value, identifier, hint):
"""Initialise the error with par... | the_stack_v2_python_sparse | doxhooks/errors.py | nre/Doxhooks | train | 1 |
520f7af5b9edd656b45ceec1f489f717575ae2a3 | [
"super(VideoSessionManager, self).__init__()\nself.getters.update({'assignment': 'get_foreign_key', 'date_completed': 'get_time', 'date_started': 'get_time', 'user': 'get_foreign_key', 'video': 'get_foreign_key'})\nself.setters.update({'date_completed': 'set_time', 'date_started': 'set_time'})\nself.my_django_model... | <|body_start_0|>
super(VideoSessionManager, self).__init__()
self.getters.update({'assignment': 'get_foreign_key', 'date_completed': 'get_time', 'date_started': 'get_time', 'user': 'get_foreign_key', 'video': 'get_foreign_key'})
self.setters.update({'date_completed': 'set_time', 'date_started': ... | Manage VideoSessions in the Power Reg system | VideoSessionManager | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VideoSessionManager:
"""Manage VideoSessions in the Power Reg system"""
def __init__(self):
"""constructor"""
<|body_0|>
def create(self, auth_token, assignment):
"""Create a new VideoSession object. @param auth_token The authentication token of the acting user @... | stack_v2_sparse_classes_36k_train_032723 | 6,633 | permissive | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Create a new VideoSession object. @param auth_token The authentication token of the acting user @type auth_token facade.models.AuthToken @param assignment FK for an assignment @type assignment ... | 5 | null | Implement the Python class `VideoSessionManager` described below.
Class description:
Manage VideoSessions in the Power Reg system
Method signatures and docstrings:
- def __init__(self): constructor
- def create(self, auth_token, assignment): Create a new VideoSession object. @param auth_token The authentication token... | Implement the Python class `VideoSessionManager` described below.
Class description:
Manage VideoSessions in the Power Reg system
Method signatures and docstrings:
- def __init__(self): constructor
- def create(self, auth_token, assignment): Create a new VideoSession object. @param auth_token The authentication token... | a59457bc37f0501aea1f54d006a6de94ff80511c | <|skeleton|>
class VideoSessionManager:
"""Manage VideoSessions in the Power Reg system"""
def __init__(self):
"""constructor"""
<|body_0|>
def create(self, auth_token, assignment):
"""Create a new VideoSession object. @param auth_token The authentication token of the acting user @... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VideoSessionManager:
"""Manage VideoSessions in the Power Reg system"""
def __init__(self):
"""constructor"""
super(VideoSessionManager, self).__init__()
self.getters.update({'assignment': 'get_foreign_key', 'date_completed': 'get_time', 'date_started': 'get_time', 'user': 'get_fo... | the_stack_v2_python_sparse | vod_aws/managers/video_session_manager.py | ninemoreminutes/openassign-server | train | 0 |
c69634bd8c4fb735a84aa5372bad10da12fba4be | [
"movie_obj = Movie(movie_id=movie_id, movie_title=movie_title, movie_type=movie_type, movie_description=movie_description)\ntry:\n self._repository.insert(movie_obj)\nexcept RepositoryException as e:\n Session.set_message(e.message)\n return False\nreturn True",
"movie = self._repository.select_by_id(mov... | <|body_start_0|>
movie_obj = Movie(movie_id=movie_id, movie_title=movie_title, movie_type=movie_type, movie_description=movie_description)
try:
self._repository.insert(movie_obj)
except RepositoryException as e:
Session.set_message(e.message)
return False
... | MovieController | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovieController:
def store(self, movie_id, movie_title, movie_type, movie_description):
"""Store a new movie Time complexity: O(1) Input: instance - an object Output: True - success False - failure Raises:"""
<|body_0|>
def update(self, movie_id, movie_title='', movie_type='... | stack_v2_sparse_classes_36k_train_032724 | 4,064 | permissive | [
{
"docstring": "Store a new movie Time complexity: O(1) Input: instance - an object Output: True - success False - failure Raises:",
"name": "store",
"signature": "def store(self, movie_id, movie_title, movie_type, movie_description)"
},
{
"docstring": "Update a movie by id Time complexity: O(1)... | 3 | stack_v2_sparse_classes_30k_train_010146 | Implement the Python class `MovieController` described below.
Class description:
Implement the MovieController class.
Method signatures and docstrings:
- def store(self, movie_id, movie_title, movie_type, movie_description): Store a new movie Time complexity: O(1) Input: instance - an object Output: True - success Fa... | Implement the Python class `MovieController` described below.
Class description:
Implement the MovieController class.
Method signatures and docstrings:
- def store(self, movie_id, movie_title, movie_type, movie_description): Store a new movie Time complexity: O(1) Input: instance - an object Output: True - success Fa... | 9496cb63594dcf1cc2cec8650b8eee603f85fdab | <|skeleton|>
class MovieController:
def store(self, movie_id, movie_title, movie_type, movie_description):
"""Store a new movie Time complexity: O(1) Input: instance - an object Output: True - success False - failure Raises:"""
<|body_0|>
def update(self, movie_id, movie_title='', movie_type='... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MovieController:
def store(self, movie_id, movie_title, movie_type, movie_description):
"""Store a new movie Time complexity: O(1) Input: instance - an object Output: True - success False - failure Raises:"""
movie_obj = Movie(movie_id=movie_id, movie_title=movie_title, movie_type=movie_type, ... | the_stack_v2_python_sparse | fundamentals-of-programming/labs/lab_5-11/controller/movie.py | vampy/university | train | 1 | |
416a5c535c5e982ff5c2c298e30c932670c3f604 | [
"super().__init__(name='policy_value_network')\nif not isinstance(num_actions, int):\n raise ValueError(f'num_actions must be of type int, but was of type {type(num_actions)}.')\nself._policy_layer = snt.Sequential([snt.Linear(hidden_size), activation, snt.Linear(num_actions)])\nself._value_layer = snt.Sequentia... | <|body_start_0|>
super().__init__(name='policy_value_network')
if not isinstance(num_actions, int):
raise ValueError(f'num_actions must be of type int, but was of type {type(num_actions)}.')
self._policy_layer = snt.Sequential([snt.Linear(hidden_size), activation, snt.Linear(num_acti... | A network with linear layers, for policy and value respectively. | PolicyValueHead | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PolicyValueHead:
"""A network with linear layers, for policy and value respectively."""
def __init__(self, num_actions: int, hidden_size: int=256, activation=tf.nn.relu):
"""Initializes the PolicyValueHead module. Args: num_actions: Number of actions in discrete action space. hidden_... | stack_v2_sparse_classes_36k_train_032725 | 1,702 | no_license | [
{
"docstring": "Initializes the PolicyValueHead module. Args: num_actions: Number of actions in discrete action space. hidden_size: Size of hidden layers (between input and output layers). activation: Activation function to be used by this module (between hidden and output layers). Raises: ValueError: If shapes... | 2 | stack_v2_sparse_classes_30k_train_017491 | Implement the Python class `PolicyValueHead` described below.
Class description:
A network with linear layers, for policy and value respectively.
Method signatures and docstrings:
- def __init__(self, num_actions: int, hidden_size: int=256, activation=tf.nn.relu): Initializes the PolicyValueHead module. Args: num_act... | Implement the Python class `PolicyValueHead` described below.
Class description:
A network with linear layers, for policy and value respectively.
Method signatures and docstrings:
- def __init__(self, num_actions: int, hidden_size: int=256, activation=tf.nn.relu): Initializes the PolicyValueHead module. Args: num_act... | 1c2b2768f2c5996c8cc998d0271f3857949bdaeb | <|skeleton|>
class PolicyValueHead:
"""A network with linear layers, for policy and value respectively."""
def __init__(self, num_actions: int, hidden_size: int=256, activation=tf.nn.relu):
"""Initializes the PolicyValueHead module. Args: num_actions: Number of actions in discrete action space. hidden_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PolicyValueHead:
"""A network with linear layers, for policy and value respectively."""
def __init__(self, num_actions: int, hidden_size: int=256, activation=tf.nn.relu):
"""Initializes the PolicyValueHead module. Args: num_actions: Number of actions in discrete action space. hidden_size: Size of... | the_stack_v2_python_sparse | ftw/tf/networks/policy_value.py | RaoulDrake/ftw | train | 3 |
18cbed40f7a46a466e5fda0df9700bbde38ecdc9 | [
"super().__init__()\nself.conv = nn.Conv1d(in_channels=embedding_size, out_channels=filter_num, kernel_size=window_size, padding=padding)\nself.relu = nn.ReLU()\nself.max_pool = nn.MaxPool1d(kernel_size=max_sentence_length - window_size + 1 + padding * 2)",
"c = self.relu(self.conv(x))\nc_hat = self.max_pool(c).s... | <|body_start_0|>
super().__init__()
self.conv = nn.Conv1d(in_channels=embedding_size, out_channels=filter_num, kernel_size=window_size, padding=padding)
self.relu = nn.ReLU()
self.max_pool = nn.MaxPool1d(kernel_size=max_sentence_length - window_size + 1 + padding * 2)
<|end_body_0|>
<|b... | 仅仅实现了一个 CNN 部分 | CNNLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CNNLayer:
"""仅仅实现了一个 CNN 部分"""
def __init__(self, embedding_size: int, filter_num: int, window_size: int, max_sentence_length: int, padding: int=0):
"""通过一个本模块后，我们对每个句子（用 N 表示句子数）得到了 filters_nums 个特征 :param embedding_size: 词向量维度 :param filter_num: 卷积个数（几个滤波器） :param window_size: 窗口大小... | stack_v2_sparse_classes_36k_train_032726 | 6,607 | no_license | [
{
"docstring": "通过一个本模块后，我们对每个句子（用 N 表示句子数）得到了 filters_nums 个特征 :param embedding_size: 词向量维度 :param filter_num: 卷积个数（几个滤波器） :param window_size: 窗口大小，对应论文中的 h :param padding: 两边填充 :param max_sentence_length: 每个句子有多少单词（已经根据这个参数进行了填充或截断），对应论文中的 n",
"name": "__init__",
"signature": "def __init__(self, embed... | 2 | stack_v2_sparse_classes_30k_train_020956 | Implement the Python class `CNNLayer` described below.
Class description:
仅仅实现了一个 CNN 部分
Method signatures and docstrings:
- def __init__(self, embedding_size: int, filter_num: int, window_size: int, max_sentence_length: int, padding: int=0): 通过一个本模块后，我们对每个句子（用 N 表示句子数）得到了 filters_nums 个特征 :param embedding_size: 词向量维... | Implement the Python class `CNNLayer` described below.
Class description:
仅仅实现了一个 CNN 部分
Method signatures and docstrings:
- def __init__(self, embedding_size: int, filter_num: int, window_size: int, max_sentence_length: int, padding: int=0): 通过一个本模块后，我们对每个句子（用 N 表示句子数）得到了 filters_nums 个特征 :param embedding_size: 词向量维... | 29dc4aa0ebd3f610135ceb88f62634b4597b564a | <|skeleton|>
class CNNLayer:
"""仅仅实现了一个 CNN 部分"""
def __init__(self, embedding_size: int, filter_num: int, window_size: int, max_sentence_length: int, padding: int=0):
"""通过一个本模块后，我们对每个句子（用 N 表示句子数）得到了 filters_nums 个特征 :param embedding_size: 词向量维度 :param filter_num: 卷积个数（几个滤波器） :param window_size: 窗口大小... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CNNLayer:
"""仅仅实现了一个 CNN 部分"""
def __init__(self, embedding_size: int, filter_num: int, window_size: int, max_sentence_length: int, padding: int=0):
"""通过一个本模块后，我们对每个句子（用 N 表示句子数）得到了 filters_nums 个特征 :param embedding_size: 词向量维度 :param filter_num: 卷积个数（几个滤波器） :param window_size: 窗口大小，对应论文中的 h :pa... | the_stack_v2_python_sparse | task02/modules/cnn.py | yjqiang/nlp-beginner | train | 2 |
0d2305cd39b47e2c0c04713de03dec7a2d38176d | [
"args = self._base_args_copy()\nargs += ['-p', project.filename]\nargs += ['-c', config.name]\nargs += ['--verbose']\nreturn args",
"super(UbuildBuilder, self)._run_builder(project, config)\nargs = self._construct_ubuild_args(project, config)\nif not ubuild(args):\n raise BuildError('Failed to build {}'.format... | <|body_start_0|>
args = self._base_args_copy()
args += ['-p', project.filename]
args += ['-c', config.name]
args += ['--verbose']
return args
<|end_body_0|>
<|body_start_1|>
super(UbuildBuilder, self)._run_builder(project, config)
args = self._construct_ubuild_ar... | UbuildBuilder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UbuildBuilder:
def _construct_ubuild_args(self, project, config):
"""Build the arguments list for passing to ubuild"""
<|body_0|>
def _run_builder(self, project, config):
"""Call the ubuild module to perform the actual build."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_032727 | 762 | no_license | [
{
"docstring": "Build the arguments list for passing to ubuild",
"name": "_construct_ubuild_args",
"signature": "def _construct_ubuild_args(self, project, config)"
},
{
"docstring": "Call the ubuild module to perform the actual build.",
"name": "_run_builder",
"signature": "def _run_buil... | 2 | stack_v2_sparse_classes_30k_train_020964 | Implement the Python class `UbuildBuilder` described below.
Class description:
Implement the UbuildBuilder class.
Method signatures and docstrings:
- def _construct_ubuild_args(self, project, config): Build the arguments list for passing to ubuild
- def _run_builder(self, project, config): Call the ubuild module to p... | Implement the Python class `UbuildBuilder` described below.
Class description:
Implement the UbuildBuilder class.
Method signatures and docstrings:
- def _construct_ubuild_args(self, project, config): Build the arguments list for passing to ubuild
- def _run_builder(self, project, config): Call the ubuild module to p... | bff2d8c9e5e1ead4018f63098c1adea0e0c28184 | <|skeleton|>
class UbuildBuilder:
def _construct_ubuild_args(self, project, config):
"""Build the arguments list for passing to ubuild"""
<|body_0|>
def _run_builder(self, project, config):
"""Call the ubuild module to perform the actual build."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UbuildBuilder:
def _construct_ubuild_args(self, project, config):
"""Build the arguments list for passing to ubuild"""
args = self._base_args_copy()
args += ['-p', project.filename]
args += ['-c', config.name]
args += ['--verbose']
return args
def _run_buil... | the_stack_v2_python_sparse | adk/tools/packages/workspace_builders/ubuild_builder.py | litterstar7/Qualcomm_BT_Audio | train | 4 | |
c6279cc21a1ec016804560794bfa1e8dcda9b4d6 | [
"for data_type in subquery['forecast']:\n if kwargs['result'] == 1:\n sub_context_block[data_type]['value'] = sub_context_block[data_type]['value'].cumsum()\n if kwargs['forecast'] == 0 and data_type == 'Actual':\n sub_context_block[data_type]['value'].loc[sub_context_block[data_type]['v... | <|body_start_0|>
for data_type in subquery['forecast']:
if kwargs['result'] == 1:
sub_context_block[data_type]['value'] = sub_context_block[data_type]['value'].cumsum()
if kwargs['forecast'] == 0 and data_type == 'Actual':
sub_context_block[data_ty... | Manager create necessary table information for indicator. | ValueRowManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValueRowManager:
"""Manager create necessary table information for indicator."""
def result_handler(self, sub_context_block, kwargs, subquery):
"""Method for monthly or cumulative values representation."""
<|body_0|>
def indicator_handler(self, df_block, kwargs, subquery... | stack_v2_sparse_classes_36k_train_032728 | 1,983 | no_license | [
{
"docstring": "Method for monthly or cumulative values representation.",
"name": "result_handler",
"signature": "def result_handler(self, sub_context_block, kwargs, subquery)"
},
{
"docstring": "Calculate indicator row values.",
"name": "indicator_handler",
"signature": "def indicator_h... | 3 | stack_v2_sparse_classes_30k_train_017152 | Implement the Python class `ValueRowManager` described below.
Class description:
Manager create necessary table information for indicator.
Method signatures and docstrings:
- def result_handler(self, sub_context_block, kwargs, subquery): Method for monthly or cumulative values representation.
- def indicator_handler(... | Implement the Python class `ValueRowManager` described below.
Class description:
Manager create necessary table information for indicator.
Method signatures and docstrings:
- def result_handler(self, sub_context_block, kwargs, subquery): Method for monthly or cumulative values representation.
- def indicator_handler(... | b8f2a377ca2f0f55ddf2b1ace05402d2dfacf4cd | <|skeleton|>
class ValueRowManager:
"""Manager create necessary table information for indicator."""
def result_handler(self, sub_context_block, kwargs, subquery):
"""Method for monthly or cumulative values representation."""
<|body_0|>
def indicator_handler(self, df_block, kwargs, subquery... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValueRowManager:
"""Manager create necessary table information for indicator."""
def result_handler(self, sub_context_block, kwargs, subquery):
"""Method for monthly or cumulative values representation."""
for data_type in subquery['forecast']:
if kwargs['result'] == 1:
... | the_stack_v2_python_sparse | indicator/calc_value_indicator.py | diagon555/KPI-presentation | train | 0 |
9900dc120c93a8f245c2be866bca42c710bb7cd4 | [
"self.skew_detection_config = skew_detection_config\nself.drift_detection_config = drift_detection_config\nself.explanation_config = explanation_config\nself._config_for_bp = False",
"training_dataset = None\nif self.skew_detection_config is not None:\n training_dataset = gca_model_monitoring.ModelMonitoringOb... | <|body_start_0|>
self.skew_detection_config = skew_detection_config
self.drift_detection_config = drift_detection_config
self.explanation_config = explanation_config
self._config_for_bp = False
<|end_body_0|>
<|body_start_1|>
training_dataset = None
if self.skew_detectio... | _ObjectiveConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ObjectiveConfig:
def __init__(self, skew_detection_config: Optional['gca_model_monitoring._SkewDetectionConfig']=None, drift_detection_config: Optional['gca_model_monitoring._DriftDetectionConfig']=None, explanation_config: Optional['gca_model_monitoring._ExplanationConfig']=None):
"""B... | stack_v2_sparse_classes_36k_train_032729 | 17,467 | permissive | [
{
"docstring": "Base class for ObjectiveConfig. Args: skew_detection_config (_SkewDetectionConfig): Optional. An instance of _SkewDetectionConfig. drift_detection_config (_DriftDetectionConfig): Optional. An instance of _DriftDetectionConfig. explanation_config (_ExplanationConfig): Optional. An instance of _Ex... | 2 | stack_v2_sparse_classes_30k_train_014253 | Implement the Python class `_ObjectiveConfig` described below.
Class description:
Implement the _ObjectiveConfig class.
Method signatures and docstrings:
- def __init__(self, skew_detection_config: Optional['gca_model_monitoring._SkewDetectionConfig']=None, drift_detection_config: Optional['gca_model_monitoring._Drif... | Implement the Python class `_ObjectiveConfig` described below.
Class description:
Implement the _ObjectiveConfig class.
Method signatures and docstrings:
- def __init__(self, skew_detection_config: Optional['gca_model_monitoring._SkewDetectionConfig']=None, drift_detection_config: Optional['gca_model_monitoring._Drif... | 76b95b92c1d3b87c72d754d8c02b1bca652b9a27 | <|skeleton|>
class _ObjectiveConfig:
def __init__(self, skew_detection_config: Optional['gca_model_monitoring._SkewDetectionConfig']=None, drift_detection_config: Optional['gca_model_monitoring._DriftDetectionConfig']=None, explanation_config: Optional['gca_model_monitoring._ExplanationConfig']=None):
"""B... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _ObjectiveConfig:
def __init__(self, skew_detection_config: Optional['gca_model_monitoring._SkewDetectionConfig']=None, drift_detection_config: Optional['gca_model_monitoring._DriftDetectionConfig']=None, explanation_config: Optional['gca_model_monitoring._ExplanationConfig']=None):
"""Base class for ... | the_stack_v2_python_sparse | google/cloud/aiplatform/model_monitoring/objective.py | googleapis/python-aiplatform | train | 418 | |
77e3d562df9d9fcbfa5e8058db904decf2df2dba | [
"for i in self._inOrderGen(self.root):\n if re.match(str(string), i[0].treestr()):\n yield i[1]",
"def generate(root):\n if root:\n yield list(generate(root.left))\n yield (root.key.treestr(), root.val, root.height)\n yield list(generate(root.right))\nreturn str(list(generate(sel... | <|body_start_0|>
for i in self._inOrderGen(self.root):
if re.match(str(string), i[0].treestr()):
yield i[1]
<|end_body_0|>
<|body_start_1|>
def generate(root):
if root:
yield list(generate(root.left))
yield (root.key.treestr(), roo... | Attribute_Date_AVL | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Attribute_Date_AVL:
def simsearch(self, string):
"""Simple similarity search for Date tree Time complexity: O(n)"""
<|body_0|>
def treestr(self):
"""Returns string of nested lists(with custom Date treestr) that can be used to build the tree"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_032730 | 9,078 | no_license | [
{
"docstring": "Simple similarity search for Date tree Time complexity: O(n)",
"name": "simsearch",
"signature": "def simsearch(self, string)"
},
{
"docstring": "Returns string of nested lists(with custom Date treestr) that can be used to build the tree",
"name": "treestr",
"signature": ... | 3 | stack_v2_sparse_classes_30k_train_018480 | Implement the Python class `Attribute_Date_AVL` described below.
Class description:
Implement the Attribute_Date_AVL class.
Method signatures and docstrings:
- def simsearch(self, string): Simple similarity search for Date tree Time complexity: O(n)
- def treestr(self): Returns string of nested lists(with custom Date... | Implement the Python class `Attribute_Date_AVL` described below.
Class description:
Implement the Attribute_Date_AVL class.
Method signatures and docstrings:
- def simsearch(self, string): Simple similarity search for Date tree Time complexity: O(n)
- def treestr(self): Returns string of nested lists(with custom Date... | ec7d6fc488f7b82c35a073fe3ea374de2aa0b16a | <|skeleton|>
class Attribute_Date_AVL:
def simsearch(self, string):
"""Simple similarity search for Date tree Time complexity: O(n)"""
<|body_0|>
def treestr(self):
"""Returns string of nested lists(with custom Date treestr) that can be used to build the tree"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Attribute_Date_AVL:
def simsearch(self, string):
"""Simple similarity search for Date tree Time complexity: O(n)"""
for i in self._inOrderGen(self.root):
if re.match(str(string), i[0].treestr()):
yield i[1]
def treestr(self):
"""Returns string of nested... | the_stack_v2_python_sparse | CEP Y3/Unit 2.10 Final Project/cds_attributetrees.py | HTY2003/CEP-Stuff | train | 0 | |
64bfede34314aee498c898eedce8aac282af522f | [
"print_info('Creating kafka producer')\ntry:\n self.kafka_producer = KafkaProducer(**configs)\nexcept KafkaError as exc:\n print_error('kafka producer - Exception during connecting to broker - {}'.format(exc))",
"partition = kwargs.get('partition', None)\nheaders = kwargs.get('headers', None)\ntimestamp = k... | <|body_start_0|>
print_info('Creating kafka producer')
try:
self.kafka_producer = KafkaProducer(**configs)
except KafkaError as exc:
print_error('kafka producer - Exception during connecting to broker - {}'.format(exc))
<|end_body_0|>
<|body_start_1|>
partition =... | This class contains all kafka producer methods | WarriorKafkaProducer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WarriorKafkaProducer:
"""This class contains all kafka producer methods"""
def __init__(self, **configs):
"""Create kafka producer object"""
<|body_0|>
def send_messages(self, topic, value=None, **kwargs):
"""Publish messages to the desired topic Arguments: topic... | stack_v2_sparse_classes_36k_train_032731 | 11,178 | permissive | [
{
"docstring": "Create kafka producer object",
"name": "__init__",
"signature": "def __init__(self, **configs)"
},
{
"docstring": "Publish messages to the desired topic Arguments: topic(str): topic name to publish messages partition(int): partition nubmer key(str): key name value(str): message t... | 2 | null | Implement the Python class `WarriorKafkaProducer` described below.
Class description:
This class contains all kafka producer methods
Method signatures and docstrings:
- def __init__(self, **configs): Create kafka producer object
- def send_messages(self, topic, value=None, **kwargs): Publish messages to the desired t... | Implement the Python class `WarriorKafkaProducer` described below.
Class description:
This class contains all kafka producer methods
Method signatures and docstrings:
- def __init__(self, **configs): Create kafka producer object
- def send_messages(self, topic, value=None, **kwargs): Publish messages to the desired t... | 685761cf044182ec88ce86a942d4be1e150a1256 | <|skeleton|>
class WarriorKafkaProducer:
"""This class contains all kafka producer methods"""
def __init__(self, **configs):
"""Create kafka producer object"""
<|body_0|>
def send_messages(self, topic, value=None, **kwargs):
"""Publish messages to the desired topic Arguments: topic... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WarriorKafkaProducer:
"""This class contains all kafka producer methods"""
def __init__(self, **configs):
"""Create kafka producer object"""
print_info('Creating kafka producer')
try:
self.kafka_producer = KafkaProducer(**configs)
except KafkaError as exc:
... | the_stack_v2_python_sparse | warrior/Framework/ClassUtils/kafka_utils_class.py | warriorframework/warriorframework | train | 25 |
f5d80cc6a801e905af28630f91ba6ad41eb5e76c | [
"if not self.rig.node().hasAttr('shapeInfo'):\n self.rig.node().addAttr('shapeInfo', dt='string')\n self.rig.node().shapeInfo.set('{}')\nif not self.rig.built_successfully():\n return\ndata_sets = list()\nfor node in self.rig.control_org().getChildren(ad=True, type='transform'):\n if node.name().startsw... | <|body_start_0|>
if not self.rig.node().hasAttr('shapeInfo'):
self.rig.node().addAttr('shapeInfo', dt='string')
self.rig.node().shapeInfo.set('{}')
if not self.rig.built_successfully():
return
data_sets = list()
for node in self.rig.control_org().getCh... | This is an example only plugin showing what a process plugin might be used for. In this case, we're going to snapshot all the NurbsCurve shape nodes within the rig and store that information in a string attribute allowing us to re-apply the sames post build. This mechanism allows a rigger to make control shape adjustme... | ShapeStoreProcess | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShapeStoreProcess:
"""This is an example only plugin showing what a process plugin might be used for. In this case, we're going to snapshot all the NurbsCurve shape nodes within the rig and store that information in a string attribute allowing us to re-apply the sames post build. This mechanism a... | stack_v2_sparse_classes_36k_train_032732 | 5,865 | permissive | [
{
"docstring": "This is called before the control rig is destroyed, so we will store all the control information here. :return:",
"name": "snapshot",
"signature": "def snapshot(self)"
},
{
"docstring": "This is called after the entire rig has been built, so we will attempt to re-apply the shape ... | 2 | stack_v2_sparse_classes_30k_train_020835 | Implement the Python class `ShapeStoreProcess` described below.
Class description:
This is an example only plugin showing what a process plugin might be used for. In this case, we're going to snapshot all the NurbsCurve shape nodes within the rig and store that information in a string attribute allowing us to re-apply... | Implement the Python class `ShapeStoreProcess` described below.
Class description:
This is an example only plugin showing what a process plugin might be used for. In this case, we're going to snapshot all the NurbsCurve shape nodes within the rig and store that information in a string attribute allowing us to re-apply... | 5b034fc76150dcc613e69d08d0d807c5461c265b | <|skeleton|>
class ShapeStoreProcess:
"""This is an example only plugin showing what a process plugin might be used for. In this case, we're going to snapshot all the NurbsCurve shape nodes within the rig and store that information in a string attribute allowing us to re-apply the sames post build. This mechanism a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShapeStoreProcess:
"""This is an example only plugin showing what a process plugin might be used for. In this case, we're going to snapshot all the NurbsCurve shape nodes within the rig and store that information in a string attribute allowing us to re-apply the sames post build. This mechanism allows a rigge... | the_stack_v2_python_sparse | crab/plugins/processes/shapes.py | mikemalinowski/crab | train | 25 |
19b68af59ed76a5ab7098f5499dada678b3c939c | [
"size = len(nums)\nif size == 0:\n return 0\nreturn self.__helper(nums, k + 1) - self.__helper(nums, k)",
"size = len(nums)\nif size == 0:\n return 0\nl = 0\nr = size\nwhile l < r:\n mid = l + (r - l) // 2\n if nums[mid] >= k:\n r = mid\n else:\n assert nums[mid] < k\n l = mid ... | <|body_start_0|>
size = len(nums)
if size == 0:
return 0
return self.__helper(nums, k + 1) - self.__helper(nums, k)
<|end_body_0|>
<|body_start_1|>
size = len(nums)
if size == 0:
return 0
l = 0
r = size
while l < r:
mid... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getNumberOfK(self, nums, k):
""":type nums: list[int] :type k: int :rtype: int"""
<|body_0|>
def __helper(self, nums, k):
"""返回大于等于 k 的第一个数的索引 :param nums: :param k: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
size = len(n... | stack_v2_sparse_classes_36k_train_032733 | 1,431 | no_license | [
{
"docstring": ":type nums: list[int] :type k: int :rtype: int",
"name": "getNumberOfK",
"signature": "def getNumberOfK(self, nums, k)"
},
{
"docstring": "返回大于等于 k 的第一个数的索引 :param nums: :param k: :return:",
"name": "__helper",
"signature": "def __helper(self, nums, k)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getNumberOfK(self, nums, k): :type nums: list[int] :type k: int :rtype: int
- def __helper(self, nums, k): 返回大于等于 k 的第一个数的索引 :param nums: :param k: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getNumberOfK(self, nums, k): :type nums: list[int] :type k: int :rtype: int
- def __helper(self, nums, k): 返回大于等于 k 的第一个数的索引 :param nums: :param k: :return:
<|skeleton|>
cla... | 4c57462cbaa365b07341bb6ed20d21a4f0389f33 | <|skeleton|>
class Solution:
def getNumberOfK(self, nums, k):
""":type nums: list[int] :type k: int :rtype: int"""
<|body_0|>
def __helper(self, nums, k):
"""返回大于等于 k 的第一个数的索引 :param nums: :param k: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def getNumberOfK(self, nums, k):
""":type nums: list[int] :type k: int :rtype: int"""
size = len(nums)
if size == 0:
return 0
return self.__helper(nums, k + 1) - self.__helper(nums, k)
def __helper(self, nums, k):
"""返回大于等于 k 的第一个数的索引 :param n... | the_stack_v2_python_sparse | codes/python/56-数字在排序数组中出现的次数（解法2）.py | lxyxl0216/sword-for-offer-solution | train | 0 | |
04a2d68b4ba3b006910f369f3bd9dcad443e68b9 | [
"process = state[:state.rfind('_')]\nif process in cls.processes:\n return process\nreturn ''",
"if state[:state.rfind('_')] in cls.processes or state == 'idle':\n return True\nreturn False",
"object_methods = [method_name for method_name in dir(obj) if callable(getattr(obj, method_name))]\ncategories = [... | <|body_start_0|>
process = state[:state.rfind('_')]
if process in cls.processes:
return process
return ''
<|end_body_0|>
<|body_start_1|>
if state[:state.rfind('_')] in cls.processes or state == 'idle':
return True
return False
<|end_body_1|>
<|body_star... | Configuration for robot state machine to handle SAP EWM warehouse orders. | RobotEWMConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RobotEWMConfig:
"""Configuration for robot state machine to handle SAP EWM warehouse orders."""
def get_process_type(cls, state: str) -> str:
"""Get process type for the state."""
<|body_0|>
def is_new_work_state(cls, state: str) -> bool:
"""Identify if request f... | stack_v2_sparse_classes_36k_train_032734 | 15,806 | permissive | [
{
"docstring": "Get process type for the state.",
"name": "get_process_type",
"signature": "def get_process_type(cls, state: str) -> str"
},
{
"docstring": "Identify if request for work has to be created with requestnewwho parameter set.",
"name": "is_new_work_state",
"signature": "def i... | 3 | stack_v2_sparse_classes_30k_train_020678 | Implement the Python class `RobotEWMConfig` described below.
Class description:
Configuration for robot state machine to handle SAP EWM warehouse orders.
Method signatures and docstrings:
- def get_process_type(cls, state: str) -> str: Get process type for the state.
- def is_new_work_state(cls, state: str) -> bool: ... | Implement the Python class `RobotEWMConfig` described below.
Class description:
Configuration for robot state machine to handle SAP EWM warehouse orders.
Method signatures and docstrings:
- def get_process_type(cls, state: str) -> str: Get process type for the state.
- def is_new_work_state(cls, state: str) -> bool: ... | 80be05b5bc81a5e3ffd89279e2f49023bd71b478 | <|skeleton|>
class RobotEWMConfig:
"""Configuration for robot state machine to handle SAP EWM warehouse orders."""
def get_process_type(cls, state: str) -> str:
"""Get process type for the state."""
<|body_0|>
def is_new_work_state(cls, state: str) -> bool:
"""Identify if request f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RobotEWMConfig:
"""Configuration for robot state machine to handle SAP EWM warehouse orders."""
def get_process_type(cls, state: str) -> str:
"""Get process type for the state."""
process = state[:state.rfind('_')]
if process in cls.processes:
return process
re... | the_stack_v2_python_sparse | python-modules/robcoewmtypes/robcoewmtypes/statemachine_config.py | SAP/ewm-cloud-robotics | train | 29 |
3e8201cad357ce1b1cb72cc9c60be3fef88fa4f2 | [
"if self.config is not None:\n cfg = self.config\n for key in LARGE_ARTEFACTS:\n if key in cfg and hasattr(self._nested_detector, key):\n cfg[key] = getattr(self._nested_detector, key)\n preprocess_at_init = getattr(self._nested_detector, 'preprocess_at_init', True)\n cfg['x_ref_prepro... | <|body_start_0|>
if self.config is not None:
cfg = self.config
for key in LARGE_ARTEFACTS:
if key in cfg and hasattr(self._nested_detector, key):
cfg[key] = getattr(self._nested_detector, key)
preprocess_at_init = getattr(self._nested_detec... | A mixin class containing methods related to a drift detector's configuration dictionary. | DriftConfigMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DriftConfigMixin:
"""A mixin class containing methods related to a drift detector's configuration dictionary."""
def get_config(self) -> dict:
"""Get the detector's configuration dictionary. Returns ------- The detector's configuration dictionary."""
<|body_0|>
def from_... | stack_v2_sparse_classes_36k_train_032735 | 8,321 | permissive | [
{
"docstring": "Get the detector's configuration dictionary. Returns ------- The detector's configuration dictionary.",
"name": "get_config",
"signature": "def get_config(self) -> dict"
},
{
"docstring": "Instantiate a drift detector from a fully resolved (and validated) config dictionary. Param... | 4 | stack_v2_sparse_classes_30k_train_014960 | Implement the Python class `DriftConfigMixin` described below.
Class description:
A mixin class containing methods related to a drift detector's configuration dictionary.
Method signatures and docstrings:
- def get_config(self) -> dict: Get the detector's configuration dictionary. Returns ------- The detector's confi... | Implement the Python class `DriftConfigMixin` described below.
Class description:
A mixin class containing methods related to a drift detector's configuration dictionary.
Method signatures and docstrings:
- def get_config(self) -> dict: Get the detector's configuration dictionary. Returns ------- The detector's confi... | 4a1b4f74a8590117965421e86c2295bff0f33e89 | <|skeleton|>
class DriftConfigMixin:
"""A mixin class containing methods related to a drift detector's configuration dictionary."""
def get_config(self) -> dict:
"""Get the detector's configuration dictionary. Returns ------- The detector's configuration dictionary."""
<|body_0|>
def from_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DriftConfigMixin:
"""A mixin class containing methods related to a drift detector's configuration dictionary."""
def get_config(self) -> dict:
"""Get the detector's configuration dictionary. Returns ------- The detector's configuration dictionary."""
if self.config is not None:
... | the_stack_v2_python_sparse | alibi_detect/base.py | SeldonIO/alibi-detect | train | 1,922 |
db12ec198b267c4877cd03b3ec3b3659c70de6c0 | [
"super(AlmostAllFeatureExtractor, self).__init__(src_paths, dst_dir)\nlogger = logging.getLogger('AlmostAllFeatureExtractor')\nlogger.setLevel(logging.DEBUG)\nlogging.basicConfig()\nself.logger = logger\npass",
"self.logger.info('extract starts')\nst = time.time()\nself._delete_old_data()\nuser_log_paths = glob.g... | <|body_start_0|>
super(AlmostAllFeatureExtractor, self).__init__(src_paths, dst_dir)
logger = logging.getLogger('AlmostAllFeatureExtractor')
logger.setLevel(logging.DEBUG)
logging.basicConfig()
self.logger = logger
pass
<|end_body_0|>
<|body_start_1|>
self.logger... | Almost All Feature Extractor Feature Extractor extracts labeled feature from the validated json log with the following format. --- y_1,x_01,x_02,...,x_0d y_2,x_11,x_12,...,x_1d ... y_n,x_n1,x_n2,...,x_nd --- features are ordered in 1. applaunch features - MFU ranking with dimension of K which is the number of applicati... | AlmostAllFeatureExtractor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlmostAllFeatureExtractor:
"""Almost All Feature Extractor Feature Extractor extracts labeled feature from the validated json log with the following format. --- y_1,x_01,x_02,...,x_0d y_2,x_11,x_12,...,x_1d ... y_n,x_n1,x_n2,...,x_nd --- features are ordered in 1. applaunch features - MFU ranking... | stack_v2_sparse_classes_36k_train_032736 | 26,322 | no_license | [
{
"docstring": "Arguments: - `src_paths`: source paths in which logs of a user are assembled to one file. - `dst_dir`: distination directory",
"name": "__init__",
"signature": "def __init__(self, src_paths=BasicFeatureExtractor.src_paths, dst_dir=dst_dir)"
},
{
"docstring": "extract feature from... | 3 | null | Implement the Python class `AlmostAllFeatureExtractor` described below.
Class description:
Almost All Feature Extractor Feature Extractor extracts labeled feature from the validated json log with the following format. --- y_1,x_01,x_02,...,x_0d y_2,x_11,x_12,...,x_1d ... y_n,x_n1,x_n2,...,x_nd --- features are ordered... | Implement the Python class `AlmostAllFeatureExtractor` described below.
Class description:
Almost All Feature Extractor Feature Extractor extracts labeled feature from the validated json log with the following format. --- y_1,x_01,x_02,...,x_0d y_2,x_11,x_12,...,x_1d ... y_n,x_n1,x_n2,...,x_nd --- features are ordered... | e3268f0f7ff4f5a4a68931e28c483184bbf8e926 | <|skeleton|>
class AlmostAllFeatureExtractor:
"""Almost All Feature Extractor Feature Extractor extracts labeled feature from the validated json log with the following format. --- y_1,x_01,x_02,...,x_0d y_2,x_11,x_12,...,x_1d ... y_n,x_n1,x_n2,...,x_nd --- features are ordered in 1. applaunch features - MFU ranking... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlmostAllFeatureExtractor:
"""Almost All Feature Extractor Feature Extractor extracts labeled feature from the validated json log with the following format. --- y_1,x_01,x_02,...,x_0d y_2,x_11,x_12,...,x_1d ... y_n,x_n1,x_n2,...,x_nd --- features are ordered in 1. applaunch features - MFU ranking with dimensi... | the_stack_v2_python_sparse | external_attachements/src/data_management/extractor/almost_all_feature_extractor.py | khalilhajji/discovering_user_habbits_from_smartphone_logs | train | 0 |
c8c853392ee573013a8b6c0d0da6c010fde2b69b | [
"if 'git_uri' not in self.user_params:\n raise ValueError(f'{self.__class__.__name__} instance has no source (no git_uri in user params)')\nreturn source.GitSource(provider='git', uri=self.user_params['git_uri'], provider_params={'git_commit': self.user_params.get('git_ref'), 'git_commit_depth': self.user_params... | <|body_start_0|>
if 'git_uri' not in self.user_params:
raise ValueError(f'{self.__class__.__name__} instance has no source (no git_uri in user params)')
return source.GitSource(provider='git', uri=self.user_params['git_uri'], provider_params={'git_commit': self.user_params.get('git_ref'), 'g... | Task parameters (coming from CLI arguments). | TaskParams | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskParams:
"""Task parameters (coming from CLI arguments)."""
def source(self) -> source.Source:
"""Source for the input files the task will operate on (e.g. a git repo)."""
<|body_0|>
def from_cli_args(cls, args: dict):
"""Create a TaskParams instance from CLI ... | stack_v2_sparse_classes_36k_train_032737 | 4,580 | permissive | [
{
"docstring": "Source for the input files the task will operate on (e.g. a git repo).",
"name": "source",
"signature": "def source(self) -> source.Source"
},
{
"docstring": "Create a TaskParams instance from CLI arguments.",
"name": "from_cli_args",
"signature": "def from_cli_args(cls, ... | 2 | stack_v2_sparse_classes_30k_train_019360 | Implement the Python class `TaskParams` described below.
Class description:
Task parameters (coming from CLI arguments).
Method signatures and docstrings:
- def source(self) -> source.Source: Source for the input files the task will operate on (e.g. a git repo).
- def from_cli_args(cls, args: dict): Create a TaskPara... | Implement the Python class `TaskParams` described below.
Class description:
Task parameters (coming from CLI arguments).
Method signatures and docstrings:
- def source(self) -> source.Source: Source for the input files the task will operate on (e.g. a git repo).
- def from_cli_args(cls, args: dict): Create a TaskPara... | 0ed6e07d848db7090332a18ef8ace3585dd314ac | <|skeleton|>
class TaskParams:
"""Task parameters (coming from CLI arguments)."""
def source(self) -> source.Source:
"""Source for the input files the task will operate on (e.g. a git repo)."""
<|body_0|>
def from_cli_args(cls, args: dict):
"""Create a TaskParams instance from CLI ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TaskParams:
"""Task parameters (coming from CLI arguments)."""
def source(self) -> source.Source:
"""Source for the input files the task will operate on (e.g. a git repo)."""
if 'git_uri' not in self.user_params:
raise ValueError(f'{self.__class__.__name__} instance has no sou... | the_stack_v2_python_sparse | atomic_reactor/tasks/common.py | fr34k8/atomic-reactor | train | 1 |
23721ffe77c1012c5535614b99606f88b78dbb7d | [
"assert False, logger.error('Joint generator not functional')\nself.config = config\nself.is_sub_model = is_sub_model\nself.step = 0\nself.stage = stage\nself.train = self.stage == 'train'\nself.teacher_forcing = teacher_forcing\nself.word_embedding = word_embedding\nassert self.stage in ['train', 'test', 'val', 'i... | <|body_start_0|>
assert False, logger.error('Joint generator not functional')
self.config = config
self.is_sub_model = is_sub_model
self.step = 0
self.stage = stage
self.train = self.stage == 'train'
self.teacher_forcing = teacher_forcing
self.word_embeddi... | @NOT FUNCTIONAL! @brief: The conditional generator. In the first edition, let's assume the image embedding vector is conditioned to generate the text, and the text vector is conditioned to generate the image (we have more options though) @components: def __init__ def build_models | joint_generator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class joint_generator:
"""@NOT FUNCTIONAL! @brief: The conditional generator. In the first edition, let's assume the image embedding vector is conditioned to generate the text, and the text vector is conditioned to generate the image (we have more options though) @components: def __init__ def build_mod... | stack_v2_sparse_classes_36k_train_032738 | 15,550 | no_license | [
{
"docstring": "@brief: The initialization of the model. we use a config file to store the information of configuration",
"name": "__init__",
"signature": "def __init__(self, config, stage='train', is_sub_model=True, teacher_forcing=True, word_embedding=None)"
},
{
"docstring": "@brief: build th... | 2 | stack_v2_sparse_classes_30k_train_005801 | Implement the Python class `joint_generator` described below.
Class description:
@NOT FUNCTIONAL! @brief: The conditional generator. In the first edition, let's assume the image embedding vector is conditioned to generate the text, and the text vector is conditioned to generate the image (we have more options though) ... | Implement the Python class `joint_generator` described below.
Class description:
@NOT FUNCTIONAL! @brief: The conditional generator. In the first edition, let's assume the image embedding vector is conditioned to generate the text, and the text vector is conditioned to generate the image (we have more options though) ... | 71bf42b89308b56113c12096d2280c02abad9e84 | <|skeleton|>
class joint_generator:
"""@NOT FUNCTIONAL! @brief: The conditional generator. In the first edition, let's assume the image embedding vector is conditioned to generate the text, and the text vector is conditioned to generate the image (we have more options though) @components: def __init__ def build_mod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class joint_generator:
"""@NOT FUNCTIONAL! @brief: The conditional generator. In the first edition, let's assume the image embedding vector is conditioned to generate the text, and the text vector is conditioned to generate the image (we have more options though) @components: def __init__ def build_models"""
d... | the_stack_v2_python_sparse | model/network.py | WilsonWangTHU/gan_playground | train | 0 |
1ff5cf19221fcaf3017c0cc3f48325da8afe2ce5 | [
"args = entity_parser.parse_args()\npage = args['page']\nper_page = args['per_page']\nsort_order = args['order']\nif per_page > 100:\n per_page = 100\ndescending = sort_order == 'desc'\nstart = per_page * (page - 1)\nstop = start + per_page\nkwargs = {'start': start, 'stop': stop, 'descending': descending, 'sess... | <|body_start_0|>
args = entity_parser.parse_args()
page = args['page']
per_page = args['per_page']
sort_order = args['order']
if per_page > 100:
per_page = 100
descending = sort_order == 'desc'
start = per_page * (page - 1)
stop = start + per_p... | SeriesSeasonsAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SeriesSeasonsAPI:
def get(self, show_id, session):
"""Get seasons by show ID"""
<|body_0|>
def delete(self, show_id, session):
"""Deletes all seasons of a show"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args = entity_parser.parse_args()
... | stack_v2_sparse_classes_36k_train_032739 | 47,001 | permissive | [
{
"docstring": "Get seasons by show ID",
"name": "get",
"signature": "def get(self, show_id, session)"
},
{
"docstring": "Deletes all seasons of a show",
"name": "delete",
"signature": "def delete(self, show_id, session)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017671 | Implement the Python class `SeriesSeasonsAPI` described below.
Class description:
Implement the SeriesSeasonsAPI class.
Method signatures and docstrings:
- def get(self, show_id, session): Get seasons by show ID
- def delete(self, show_id, session): Deletes all seasons of a show | Implement the Python class `SeriesSeasonsAPI` described below.
Class description:
Implement the SeriesSeasonsAPI class.
Method signatures and docstrings:
- def get(self, show_id, session): Get seasons by show ID
- def delete(self, show_id, session): Deletes all seasons of a show
<|skeleton|>
class SeriesSeasonsAPI:
... | ea95ff60041beaea9aacbc2d93549e3a6b981dc5 | <|skeleton|>
class SeriesSeasonsAPI:
def get(self, show_id, session):
"""Get seasons by show ID"""
<|body_0|>
def delete(self, show_id, session):
"""Deletes all seasons of a show"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SeriesSeasonsAPI:
def get(self, show_id, session):
"""Get seasons by show ID"""
args = entity_parser.parse_args()
page = args['page']
per_page = args['per_page']
sort_order = args['order']
if per_page > 100:
per_page = 100
descending = sort_o... | the_stack_v2_python_sparse | flexget/components/series/api.py | BrutuZ/Flexget | train | 1 | |
70ff702a6c0d7164c49ff4deff2e6722f477ebf2 | [
"loss_input = self._user_power_curve_input()\nif not loss_input:\n return\nwind_resource, weights = self.wind_resource_from_input()\npower_curve = self.input_power_curve\nif (wind_resource <= power_curve.cutin_wind_speed).all():\n msg = 'All wind speeds for site {} are below the wind speed cutin ({} m/s). No ... | <|body_start_0|>
loss_input = self._user_power_curve_input()
if not loss_input:
return
wind_resource, weights = self.wind_resource_from_input()
power_curve = self.input_power_curve
if (wind_resource <= power_curve.cutin_wind_speed).all():
msg = 'All wind s... | Mixin class for :class:`reV.SAM.generation.AbstractSamWind`. Warnings -------- Using this class for anything except as a mixin for :class:`~reV.SAM.generation.AbstractSamWind` may result in unexpected results and/or errors. | PowerCurveLossesMixin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PowerCurveLossesMixin:
"""Mixin class for :class:`reV.SAM.generation.AbstractSamWind`. Warnings -------- Using this class for anything except as a mixin for :class:`~reV.SAM.generation.AbstractSamWind` may result in unexpected results and/or errors."""
def add_power_curve_losses(self):
... | stack_v2_sparse_classes_36k_train_032740 | 40,707 | permissive | [
{
"docstring": "Adjust power curve in SAM config file to account for losses. This function reads the information in the ``reV_power_curve_losses`` key of the ``sam_sys_inputs`` dictionary and computes a new power curve that accounts for the loss percentage specified from that input. If no power curve loss info ... | 6 | null | Implement the Python class `PowerCurveLossesMixin` described below.
Class description:
Mixin class for :class:`reV.SAM.generation.AbstractSamWind`. Warnings -------- Using this class for anything except as a mixin for :class:`~reV.SAM.generation.AbstractSamWind` may result in unexpected results and/or errors.
Method ... | Implement the Python class `PowerCurveLossesMixin` described below.
Class description:
Mixin class for :class:`reV.SAM.generation.AbstractSamWind`. Warnings -------- Using this class for anything except as a mixin for :class:`~reV.SAM.generation.AbstractSamWind` may result in unexpected results and/or errors.
Method ... | 497bb7d172197e09a9e14b1b1ca891b8c828b80a | <|skeleton|>
class PowerCurveLossesMixin:
"""Mixin class for :class:`reV.SAM.generation.AbstractSamWind`. Warnings -------- Using this class for anything except as a mixin for :class:`~reV.SAM.generation.AbstractSamWind` may result in unexpected results and/or errors."""
def add_power_curve_losses(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PowerCurveLossesMixin:
"""Mixin class for :class:`reV.SAM.generation.AbstractSamWind`. Warnings -------- Using this class for anything except as a mixin for :class:`~reV.SAM.generation.AbstractSamWind` may result in unexpected results and/or errors."""
def add_power_curve_losses(self):
"""Adjust ... | the_stack_v2_python_sparse | reV/losses/power_curve.py | NREL/reV | train | 53 |
5cef97412c72d1c86070c90020e5b4a598009787 | [
"fast = slow = head\nwhile fast and fast.next:\n fast = fast.next.next\n slow = slow.next\n if fast == slow:\n slow = head\n while slow != fast:\n slow = slow.next\n fast = fast.next\n return slow\nreturn None",
"slow = head\nfast = head.next\nwhile fast and fas... | <|body_start_0|>
fast = slow = head
while fast and fast.next:
fast = fast.next.next
slow = slow.next
if fast == slow:
slow = head
while slow != fast:
slow = slow.next
fast = fast.next
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def detectCycle_v2(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
fast = slow = head
while f... | stack_v2_sparse_classes_36k_train_032741 | 2,800 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "detectCycle",
"signature": "def detectCycle(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "detectCycle_v2",
"signature": "def detectCycle_v2(self, head)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def detectCycle(self, head): :type head: ListNode :rtype: ListNode
- def detectCycle_v2(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 detectCycle(self, head): :type head: ListNode :rtype: ListNode
- def detectCycle_v2(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
def ... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def detectCycle_v2(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 detectCycle(self, head):
""":type head: ListNode :rtype: ListNode"""
fast = slow = head
while fast and fast.next:
fast = fast.next.next
slow = slow.next
if fast == slow:
slow = head
while slow != fast:
... | the_stack_v2_python_sparse | src/lt_142.py | oxhead/CodingYourWay | train | 0 | |
a562f0fd7ff8c80c17e6b9c408c4d19cfc868a2f | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('raykatz_nedg_gaudiosi', 'raykatz_nedg_gaudiosi')\nurl = 'https://data.cityofboston.gov/resource/crime.json'\nresponse = urllib.request.urlopen(url).read().decode('utf-8')\nresult = json.loads(response)\n... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('raykatz_nedg_gaudiosi', 'raykatz_nedg_gaudiosi')
url = 'https://data.cityofboston.gov/resource/crime.json'
response = urllib.request.urlopen(url).... | crime | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class crime:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happeni... | stack_v2_sparse_classes_36k_train_032742 | 4,605 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | null | Implement the Python class `crime` described below.
Class description:
Implement the crime class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): Cr... | Implement the Python class `crime` described below.
Class description:
Implement the crime class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): Cr... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class crime:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happeni... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class crime:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('raykatz_nedg_gaudiosi', 'raykatz_nedg_gaudios... | the_stack_v2_python_sparse | raykatz_nedg_gaudiosi/crime.py | ROODAY/course-2017-fal-proj | train | 3 | |
4eebcdbd096b1a340fe95da36da02a835cef770a | [
"stream_data = dict(get_data(stream))\nsheet = list(stream_data.keys())[0] if len(stream_data) == 1 else None\nif sheet is None or sheet != 'Data':\n raise ParseError('XLS parse error - spreadsheet should contain one sheet named `Data`')\nstream_data = stream_data[sheet]\nheaders = stream_data[0]\ndata = []\ntry... | <|body_start_0|>
stream_data = dict(get_data(stream))
sheet = list(stream_data.keys())[0] if len(stream_data) == 1 else None
if sheet is None or sheet != 'Data':
raise ParseError('XLS parse error - spreadsheet should contain one sheet named `Data`')
stream_data = stream_data[... | XLSParser | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XLSParser:
def parse(self, stream, media_type=None, parser_context=None):
"""Parses the incoming bytestream as XLS and return resulting data"""
<|body_0|>
def _json_loads(self, val):
"""Attempt to load the value as json"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_032743 | 3,110 | permissive | [
{
"docstring": "Parses the incoming bytestream as XLS and return resulting data",
"name": "parse",
"signature": "def parse(self, stream, media_type=None, parser_context=None)"
},
{
"docstring": "Attempt to load the value as json",
"name": "_json_loads",
"signature": "def _json_loads(self... | 2 | null | Implement the Python class `XLSParser` described below.
Class description:
Implement the XLSParser class.
Method signatures and docstrings:
- def parse(self, stream, media_type=None, parser_context=None): Parses the incoming bytestream as XLS and return resulting data
- def _json_loads(self, val): Attempt to load the... | Implement the Python class `XLSParser` described below.
Class description:
Implement the XLSParser class.
Method signatures and docstrings:
- def parse(self, stream, media_type=None, parser_context=None): Parses the incoming bytestream as XLS and return resulting data
- def _json_loads(self, val): Attempt to load the... | 85102bb41aa0d558a3fa088e4fd6f51613599ad0 | <|skeleton|>
class XLSParser:
def parse(self, stream, media_type=None, parser_context=None):
"""Parses the incoming bytestream as XLS and return resulting data"""
<|body_0|>
def _json_loads(self, val):
"""Attempt to load the value as json"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XLSParser:
def parse(self, stream, media_type=None, parser_context=None):
"""Parses the incoming bytestream as XLS and return resulting data"""
stream_data = dict(get_data(stream))
sheet = list(stream_data.keys())[0] if len(stream_data) == 1 else None
if sheet is None or sheet ... | the_stack_v2_python_sparse | orchestrator/core/orc_server/backup/utils/xls.py | g2-inc/openc2-oif-orchestrator | train | 1 | |
7340da8e9ddd2ab4fcb9b8103c88967cab920cda | [
"if self.disk_template in constants.DTS_INT_MIRROR:\n return 2\nelse:\n return 1",
"for d in self.disks:\n d[constants.IDISK_TYPE] = self.disk_template\ndisk_space = gmi.ComputeDiskSize(self.disks)\nreturn {'name': self.name, 'disk_template': self.disk_template, 'group_name': self.group_name, 'tags': sel... | <|body_start_0|>
if self.disk_template in constants.DTS_INT_MIRROR:
return 2
else:
return 1
<|end_body_0|>
<|body_start_1|>
for d in self.disks:
d[constants.IDISK_TYPE] = self.disk_template
disk_space = gmi.ComputeDiskSize(self.disks)
return {... | An instance allocation request. | IAReqInstanceAlloc | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IAReqInstanceAlloc:
"""An instance allocation request."""
def RequiredNodes(self):
"""Calculates the required nodes based on the disk_template."""
<|body_0|>
def GetRequest(self, cfg):
"""Requests a new instance. The checks for the completeness of the opcode must... | stack_v2_sparse_classes_36k_train_032744 | 29,971 | permissive | [
{
"docstring": "Calculates the required nodes based on the disk_template.",
"name": "RequiredNodes",
"signature": "def RequiredNodes(self)"
},
{
"docstring": "Requests a new instance. The checks for the completeness of the opcode must have already been done.",
"name": "GetRequest",
"sign... | 3 | stack_v2_sparse_classes_30k_train_014576 | Implement the Python class `IAReqInstanceAlloc` described below.
Class description:
An instance allocation request.
Method signatures and docstrings:
- def RequiredNodes(self): Calculates the required nodes based on the disk_template.
- def GetRequest(self, cfg): Requests a new instance. The checks for the completene... | Implement the Python class `IAReqInstanceAlloc` described below.
Class description:
An instance allocation request.
Method signatures and docstrings:
- def RequiredNodes(self): Calculates the required nodes based on the disk_template.
- def GetRequest(self, cfg): Requests a new instance. The checks for the completene... | 456ea285a7583183c2c8e5bcffe9006ec8a9d658 | <|skeleton|>
class IAReqInstanceAlloc:
"""An instance allocation request."""
def RequiredNodes(self):
"""Calculates the required nodes based on the disk_template."""
<|body_0|>
def GetRequest(self, cfg):
"""Requests a new instance. The checks for the completeness of the opcode must... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IAReqInstanceAlloc:
"""An instance allocation request."""
def RequiredNodes(self):
"""Calculates the required nodes based on the disk_template."""
if self.disk_template in constants.DTS_INT_MIRROR:
return 2
else:
return 1
def GetRequest(self, cfg):
... | the_stack_v2_python_sparse | lib/masterd/iallocator.py | ganeti/ganeti | train | 465 |
788b4e5e41538470f9af98cb2da9c30eab75a6cc | [
"self.scraper_class = scraper_class\nself.output_errors_only = output_errors_only\nif checks:\n self.checks = checks\nelse:\n self.checks = (CheckBaseURL,)",
"errors = 0\nfor check_class in self.checks:\n if check_class(self.scraper_class).run_check():\n errors += 1"
] | <|body_start_0|>
self.scraper_class = scraper_class
self.output_errors_only = output_errors_only
if checks:
self.checks = checks
else:
self.checks = (CheckBaseURL,)
<|end_body_0|>
<|body_start_1|>
errors = 0
for check_class in self.checks:
... | ScraperChecker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScraperChecker:
def __init__(self, scraper_class, checks=None, output_errors_only=True):
"""A class for checking the quality of a Scraper Class. :param output_errors_only: (optional) Boolean. :param scraper_class: A :class:`ScraperBase` subclass."""
<|body_0|>
def run_checks... | stack_v2_sparse_classes_36k_train_032745 | 1,650 | permissive | [
{
"docstring": "A class for checking the quality of a Scraper Class. :param output_errors_only: (optional) Boolean. :param scraper_class: A :class:`ScraperBase` subclass.",
"name": "__init__",
"signature": "def __init__(self, scraper_class, checks=None, output_errors_only=True)"
},
{
"docstring"... | 2 | stack_v2_sparse_classes_30k_train_017974 | Implement the Python class `ScraperChecker` described below.
Class description:
Implement the ScraperChecker class.
Method signatures and docstrings:
- def __init__(self, scraper_class, checks=None, output_errors_only=True): A class for checking the quality of a Scraper Class. :param output_errors_only: (optional) Bo... | Implement the Python class `ScraperChecker` described below.
Class description:
Implement the ScraperChecker class.
Method signatures and docstrings:
- def __init__(self, scraper_class, checks=None, output_errors_only=True): A class for checking the quality of a Scraper Class. :param output_errors_only: (optional) Bo... | 13d9c9d11cf4fc3afc4ae52ac439ee4fec926ba3 | <|skeleton|>
class ScraperChecker:
def __init__(self, scraper_class, checks=None, output_errors_only=True):
"""A class for checking the quality of a Scraper Class. :param output_errors_only: (optional) Boolean. :param scraper_class: A :class:`ScraperBase` subclass."""
<|body_0|>
def run_checks... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScraperChecker:
def __init__(self, scraper_class, checks=None, output_errors_only=True):
"""A class for checking the quality of a Scraper Class. :param output_errors_only: (optional) Boolean. :param scraper_class: A :class:`ScraperBase` subclass."""
self.scraper_class = scraper_class
s... | the_stack_v2_python_sparse | lgsf/scrapers/checks.py | DemocracyClub/LGSF | train | 4 | |
cdf48beee0cf678ba991e5d51490a58e1dc3767e | [
"self.root = root\nself._id = ''\nself.name = ''\nself.slide_details = ''\nself.lesson = Lesson(self._id, self.name)\nself.slides = []\nself.build()",
"slides = self.slide_details.get()\nself.lesson._id = self._id.get()\nself.lesson.name = self.name.get()\nself.lesson.published = published\nfor slide in slides:\n... | <|body_start_0|>
self.root = root
self._id = ''
self.name = ''
self.slide_details = ''
self.lesson = Lesson(self._id, self.name)
self.slides = []
self.build()
<|end_body_0|>
<|body_start_1|>
slides = self.slide_details.get()
self.lesson._id = self... | This class is responsible for providing a GUI through which a user can create a lesson. | LessonCreate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LessonCreate:
"""This class is responsible for providing a GUI through which a user can create a lesson."""
def __init__(self, root):
"""Construct create lesson window. @param {tkinter object} root @return {void}"""
<|body_0|>
def save(self, published=False):
"""... | stack_v2_sparse_classes_36k_train_032746 | 3,308 | no_license | [
{
"docstring": "Construct create lesson window. @param {tkinter object} root @return {void}",
"name": "__init__",
"signature": "def __init__(self, root)"
},
{
"docstring": "Save the lesson object to the lesson store once populated with the users data. @return {void}",
"name": "save",
"si... | 3 | stack_v2_sparse_classes_30k_train_008926 | Implement the Python class `LessonCreate` described below.
Class description:
This class is responsible for providing a GUI through which a user can create a lesson.
Method signatures and docstrings:
- def __init__(self, root): Construct create lesson window. @param {tkinter object} root @return {void}
- def save(sel... | Implement the Python class `LessonCreate` described below.
Class description:
This class is responsible for providing a GUI through which a user can create a lesson.
Method signatures and docstrings:
- def __init__(self, root): Construct create lesson window. @param {tkinter object} root @return {void}
- def save(sel... | 775c2972bc7dad77831321489c0a884bd01c458d | <|skeleton|>
class LessonCreate:
"""This class is responsible for providing a GUI through which a user can create a lesson."""
def __init__(self, root):
"""Construct create lesson window. @param {tkinter object} root @return {void}"""
<|body_0|>
def save(self, published=False):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LessonCreate:
"""This class is responsible for providing a GUI through which a user can create a lesson."""
def __init__(self, root):
"""Construct create lesson window. @param {tkinter object} root @return {void}"""
self.root = root
self._id = ''
self.name = ''
sel... | the_stack_v2_python_sparse | lesson_create/view.py | taylorrees/studybook | train | 0 |
9f5e8d6bcd491bd52a6ba17842dacf17a58fa550 | [
"if self.shell is None:\n return None\nreturn self.shell.user_ns",
"if self.shell is None:\n\n class EmptyClass:\n\n def __init__(self):\n self.user_ns = {}\n self.shell = EmptyClass()\nfor k, v in context.items():\n self.shell.user_ns[k] = v",
"res = MagicClassWithHelpers._parser_... | <|body_start_0|>
if self.shell is None:
return None
return self.shell.user_ns
<|end_body_0|>
<|body_start_1|>
if self.shell is None:
class EmptyClass:
def __init__(self):
self.user_ns = {}
self.shell = EmptyClass()
... | Provides some functions reused in others classes inherited from *Magics*. The class should not be registered as it is but should be used as an ancestor for another class. It can be registered this way:: def register_file_magics(): from IPython import get_ipython ip = get_ipython() ip.register_magics(MagicFile) | MagicClassWithHelpers | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MagicClassWithHelpers:
"""Provides some functions reused in others classes inherited from *Magics*. The class should not be registered as it is but should be used as an ancestor for another class. It can be registered this way:: def register_file_magics(): from IPython import get_ipython ip = get... | stack_v2_sparse_classes_36k_train_032747 | 3,075 | permissive | [
{
"docstring": "return the context or None",
"name": "Context",
"signature": "def Context(self)"
},
{
"docstring": "add context to the class, mostly for debug purpose @param context dictionary",
"name": "add_context",
"signature": "def add_context(self, context)"
},
{
"docstring"... | 4 | null | Implement the Python class `MagicClassWithHelpers` described below.
Class description:
Provides some functions reused in others classes inherited from *Magics*. The class should not be registered as it is but should be used as an ancestor for another class. It can be registered this way:: def register_file_magics(): f... | Implement the Python class `MagicClassWithHelpers` described below.
Class description:
Provides some functions reused in others classes inherited from *Magics*. The class should not be registered as it is but should be used as an ancestor for another class. It can be registered this way:: def register_file_magics(): f... | 860ec5b9a53bae4fc616076c0b52dbe2a1153d30 | <|skeleton|>
class MagicClassWithHelpers:
"""Provides some functions reused in others classes inherited from *Magics*. The class should not be registered as it is but should be used as an ancestor for another class. It can be registered this way:: def register_file_magics(): from IPython import get_ipython ip = get... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MagicClassWithHelpers:
"""Provides some functions reused in others classes inherited from *Magics*. The class should not be registered as it is but should be used as an ancestor for another class. It can be registered this way:: def register_file_magics(): from IPython import get_ipython ip = get_ipython() ip... | the_stack_v2_python_sparse | src/pyquickhelper/ipythonhelper/magic_class.py | Pandinosaurus/pyquickhelper | train | 0 |
9e228db3324cd172bbea850b528bb89d8db00247 | [
"self.val = int(x)\nself.next = next\nself.random = random",
"res, node = ([], self)\nwhile node:\n rand = node.random.val if node.random else None\n res.append([node.val, rand])\n node = node.next\nreturn res"
] | <|body_start_0|>
self.val = int(x)
self.next = next
self.random = random
<|end_body_0|>
<|body_start_1|>
res, node = ([], self)
while node:
rand = node.random.val if node.random else None
res.append([node.val, rand])
node = node.next
r... | Node | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Node:
def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None):
"""Provided by LeetCode."""
<|body_0|>
def _path(self):
"""Used for testing. Returns the path of the linked list. Each element is the node's value, and the value of it's random node."""
... | stack_v2_sparse_classes_36k_train_032748 | 1,851 | no_license | [
{
"docstring": "Provided by LeetCode.",
"name": "__init__",
"signature": "def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None)"
},
{
"docstring": "Used for testing. Returns the path of the linked list. Each element is the node's value, and the value of it's random node.",
"name... | 2 | stack_v2_sparse_classes_30k_train_017713 | Implement the Python class `Node` described below.
Class description:
Implement the Node class.
Method signatures and docstrings:
- def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None): Provided by LeetCode.
- def _path(self): Used for testing. Returns the path of the linked list. Each element is the no... | Implement the Python class `Node` described below.
Class description:
Implement the Node class.
Method signatures and docstrings:
- def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None): Provided by LeetCode.
- def _path(self): Used for testing. Returns the path of the linked list. Each element is the no... | c6d600bc74afd14e00d4f0ffed40696192b229c3 | <|skeleton|>
class Node:
def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None):
"""Provided by LeetCode."""
<|body_0|>
def _path(self):
"""Used for testing. Returns the path of the linked list. Each element is the node's value, and the value of it's random node."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Node:
def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None):
"""Provided by LeetCode."""
self.val = int(x)
self.next = next
self.random = random
def _path(self):
"""Used for testing. Returns the path of the linked list. Each element is the node's value... | the_stack_v2_python_sparse | python/Monthly/Feb2021/listrandompointerdeepcopy.py | Hilldrupca/LeetCode | train | 0 | |
80efd3ed992ac764b7badc68fdbb04fd18549805 | [
"if not isinstance(data, np.ndarray) or len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nif data.shape[1] < 2:\n raise ValueError('data must contain multiple data points')\nd, n = data.shape\nself.mean = np.mean(data, axis=1, keepdims=True)\nX_mean = data - self.mean\nself.cov = np.... | <|body_start_0|>
if not isinstance(data, np.ndarray) or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
if data.shape[1] < 2:
raise ValueError('data must contain multiple data points')
d, n = data.shape
self.mean = np.mean(data, axis=1, ke... | represents a Multivariate Normal distribution | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""represents a Multivariate Normal distribution"""
def __init__(self, data):
"""* data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of data points - d is the number of dimensions in each data point * If data is not a 2D numpy.ndarray, ra... | stack_v2_sparse_classes_36k_train_032749 | 2,405 | no_license | [
{
"docstring": "* data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of data points - d is the number of dimensions in each data point * If data is not a 2D numpy.ndarray, raise a TypeError with the message data must be a 2D numpy.ndarray * If n is less than 2, raise a ValueError... | 2 | null | Implement the Python class `MultiNormal` described below.
Class description:
represents a Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): * data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of data points - d is the number of dimensions i... | Implement the Python class `MultiNormal` described below.
Class description:
represents a Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): * data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of data points - d is the number of dimensions i... | 8ad4c2594ff78b345dbd92e9d54d2a143ac4071a | <|skeleton|>
class MultiNormal:
"""represents a Multivariate Normal distribution"""
def __init__(self, data):
"""* data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of data points - d is the number of dimensions in each data point * If data is not a 2D numpy.ndarray, ra... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""represents a Multivariate Normal distribution"""
def __init__(self, data):
"""* data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of data points - d is the number of dimensions in each data point * If data is not a 2D numpy.ndarray, raise a TypeErr... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | jorgezafra94/holbertonschool-machine_learning | train | 1 |
d7c3cf82b70fcafc7a62d9e3984dbc2b9db9f933 | [
"queue = QueueCache.get_from_params(params)\ntry:\n with ServerLogger.hide_output():\n queue.status(params['job_id'])\nexcept (tej.JobNotFound, tej.QueueDoesntExist):\n pass\nelse:\n return params\ndirectory = self.interpreter.filePool.create_directory(prefix='vt_tmp_shelljob_').name\nsource = urlli... | <|body_start_0|>
queue = QueueCache.get_from_params(params)
try:
with ServerLogger.hide_output():
queue.status(params['job_id'])
except (tej.JobNotFound, tej.QueueDoesntExist):
pass
else:
return params
directory = self.interpret... | Submits a shell script. | SubmitShellJob | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubmitShellJob:
"""Submits a shell script."""
def job_start(self, params):
"""Creates a temporary job with the given source, upload and submit it."""
<|body_0|>
def job_set_results(self, params):
"""Gets stderr and stdout."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_032750 | 19,579 | permissive | [
{
"docstring": "Creates a temporary job with the given source, upload and submit it.",
"name": "job_start",
"signature": "def job_start(self, params)"
},
{
"docstring": "Gets stderr and stdout.",
"name": "job_set_results",
"signature": "def job_set_results(self, params)"
}
] | 2 | null | Implement the Python class `SubmitShellJob` described below.
Class description:
Submits a shell script.
Method signatures and docstrings:
- def job_start(self, params): Creates a temporary job with the given source, upload and submit it.
- def job_set_results(self, params): Gets stderr and stdout. | Implement the Python class `SubmitShellJob` described below.
Class description:
Submits a shell script.
Method signatures and docstrings:
- def job_start(self, params): Creates a temporary job with the given source, upload and submit it.
- def job_set_results(self, params): Gets stderr and stdout.
<|skeleton|>
class... | 9b42ca9b3550b599467b0c7dfa56f57bbd97a4f2 | <|skeleton|>
class SubmitShellJob:
"""Submits a shell script."""
def job_start(self, params):
"""Creates a temporary job with the given source, upload and submit it."""
<|body_0|>
def job_set_results(self, params):
"""Gets stderr and stdout."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubmitShellJob:
"""Submits a shell script."""
def job_start(self, params):
"""Creates a temporary job with the given source, upload and submit it."""
queue = QueueCache.get_from_params(params)
try:
with ServerLogger.hide_output():
queue.status(params['j... | the_stack_v2_python_sparse | vistrails/packages/tej/init.py | MaritimeResearchInstituteNetherlands/VisTrails | train | 0 |
c16bff94f801433e3cce914c023117f47059cdf5 | [
"bill = self.get_object()\ncustomer = User.objects.get(profile__phone_no=bill.customer_no)\nif self.request.user == customer or self.request.user.store == bill.store:\n return self.request.user\nelse:\n return None",
"context = super(BillDetailView, self).get_context_data(**kwargs)\nreferer = self.request.M... | <|body_start_0|>
bill = self.get_object()
customer = User.objects.get(profile__phone_no=bill.customer_no)
if self.request.user == customer or self.request.user.store == bill.store:
return self.request.user
else:
return None
<|end_body_0|>
<|body_start_1|>
... | Individual bill details | BillDetailView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BillDetailView:
"""Individual bill details"""
def test_func(self):
"""Only allows the customer and the store of the bill to access the details"""
<|body_0|>
def get_context_data(self, **kwargs):
"""1) Checks if the user is coming from the notifications page. 2) I... | stack_v2_sparse_classes_36k_train_032751 | 6,404 | no_license | [
{
"docstring": "Only allows the customer and the store of the bill to access the details",
"name": "test_func",
"signature": "def test_func(self)"
},
{
"docstring": "1) Checks if the user is coming from the notifications page. 2) If the user is coming from the notifications page, check the `pk` ... | 2 | stack_v2_sparse_classes_30k_train_015308 | Implement the Python class `BillDetailView` described below.
Class description:
Individual bill details
Method signatures and docstrings:
- def test_func(self): Only allows the customer and the store of the bill to access the details
- def get_context_data(self, **kwargs): 1) Checks if the user is coming from the not... | Implement the Python class `BillDetailView` described below.
Class description:
Individual bill details
Method signatures and docstrings:
- def test_func(self): Only allows the customer and the store of the bill to access the details
- def get_context_data(self, **kwargs): 1) Checks if the user is coming from the not... | 76f16616073ecc101fbbbe9fe49173b9638f597c | <|skeleton|>
class BillDetailView:
"""Individual bill details"""
def test_func(self):
"""Only allows the customer and the store of the bill to access the details"""
<|body_0|>
def get_context_data(self, **kwargs):
"""1) Checks if the user is coming from the notifications page. 2) I... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BillDetailView:
"""Individual bill details"""
def test_func(self):
"""Only allows the customer and the store of the bill to access the details"""
bill = self.get_object()
customer = User.objects.get(profile__phone_no=bill.customer_no)
if self.request.user == customer or se... | the_stack_v2_python_sparse | bills/views.py | mayankkushal/go-green-v1 | train | 2 |
0e5802b0c29271bac19e6bef6d1ab89b247a6dd7 | [
"if n == 1 or n == 0:\n return n\na, b = (1, 2)\nfor _ in range(2, n):\n tmp = a + b\n a = b\n b = tmp\nreturn b",
"if n == 0 or n == 1:\n return n\na = [1, 2]\nfor i in range(2, n):\n a.append(a[i - 1] + a[i - 2])\nreturn a[-1]",
"if n == 1 or n == 0:\n return n\nif n == 2:\n return 2\n... | <|body_start_0|>
if n == 1 or n == 0:
return n
a, b = (1, 2)
for _ in range(2, n):
tmp = a + b
a = b
b = tmp
return b
<|end_body_0|>
<|body_start_1|>
if n == 0 or n == 1:
return n
a = [1, 2]
for i in ran... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def dynamic_method(self, n):
"""和上面用斐波那契数列方法本质是一样的 :param n: :return:"""
<|body_1|>
def recursive_method(self, n):
"""这个方法超时了 :param n: :return:"""
<|body_2|>
... | stack_v2_sparse_classes_36k_train_032752 | 1,078 | permissive | [
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs",
"signature": "def climbStairs(self, n)"
},
{
"docstring": "和上面用斐波那契数列方法本质是一样的 :param n: :return:",
"name": "dynamic_method",
"signature": "def dynamic_method(self, n)"
},
{
"docstring": "这个方法超时了 :param n: :return:"... | 3 | stack_v2_sparse_classes_30k_train_015602 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n): :type n: int :rtype: int
- def dynamic_method(self, n): 和上面用斐波那契数列方法本质是一样的 :param n: :return:
- def recursive_method(self, n): 这个方法超时了 :param n: :return... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n): :type n: int :rtype: int
- def dynamic_method(self, n): 和上面用斐波那契数列方法本质是一样的 :param n: :return:
- def recursive_method(self, n): 这个方法超时了 :param n: :return... | f71118e8e05d4bcdcfb2dfc42187c73961b8b926 | <|skeleton|>
class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def dynamic_method(self, n):
"""和上面用斐波那契数列方法本质是一样的 :param n: :return:"""
<|body_1|>
def recursive_method(self, n):
"""这个方法超时了 :param n: :return:"""
<|body_2|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
if n == 1 or n == 0:
return n
a, b = (1, 2)
for _ in range(2, n):
tmp = a + b
a = b
b = tmp
return b
def dynamic_method(self, n):
"""和上面用斐波那契数... | the_stack_v2_python_sparse | leetcode-algorithms/070. Climbing Stairs/solution.py | bbruceyuan/algorithms-and-oj | train | 11 | |
e37b3879bddef56f193cab10594f322ce4b27499 | [
"self.credentials = credentials\nself.project_id = project_id\nself.region = region\nself.config = terrascript.Terrascript()\nself.config += terrascript.provider.google(credentials=self.credentials, project=self.project_id, region=self.region)\nwith open('main.tf.json', 'w') as main_config:\n json.dump(self.conf... | <|body_start_0|>
self.credentials = credentials
self.project_id = project_id
self.region = region
self.config = terrascript.Terrascript()
self.config += terrascript.provider.google(credentials=self.credentials, project=self.project_id, region=self.region)
with open('main.... | This class defines automates the spinning up of Google Cloud Instances | GoogleCloud | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GoogleCloud:
"""This class defines automates the spinning up of Google Cloud Instances"""
def __init__(self, credentials, project_id, region):
"""args: credentials: Path to the credentials json file project_id: project_id of your project in GCP region: region of your GCP project"""
... | stack_v2_sparse_classes_36k_train_032753 | 3,926 | permissive | [
{
"docstring": "args: credentials: Path to the credentials json file project_id: project_id of your project in GCP region: region of your GCP project",
"name": "__init__",
"signature": "def __init__(self, credentials, project_id, region)"
},
{
"docstring": "args: name: name of the compute instan... | 4 | null | Implement the Python class `GoogleCloud` described below.
Class description:
This class defines automates the spinning up of Google Cloud Instances
Method signatures and docstrings:
- def __init__(self, credentials, project_id, region): args: credentials: Path to the credentials json file project_id: project_id of yo... | Implement the Python class `GoogleCloud` described below.
Class description:
This class defines automates the spinning up of Google Cloud Instances
Method signatures and docstrings:
- def __init__(self, credentials, project_id, region): args: credentials: Path to the credentials json file project_id: project_id of yo... | cc4765bed880ad38a02505834f63df39e0815328 | <|skeleton|>
class GoogleCloud:
"""This class defines automates the spinning up of Google Cloud Instances"""
def __init__(self, credentials, project_id, region):
"""args: credentials: Path to the credentials json file project_id: project_id of your project in GCP region: region of your GCP project"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GoogleCloud:
"""This class defines automates the spinning up of Google Cloud Instances"""
def __init__(self, credentials, project_id, region):
"""args: credentials: Path to the credentials json file project_id: project_id of your project in GCP region: region of your GCP project"""
self.c... | the_stack_v2_python_sparse | syft/grid/autoscale/gcloud.py | tudorcebere/PySyft | train | 2 |
f301aab6605856e4497f2ab543147222cff3e6e2 | [
"notes = Note.objects.order_by(F('published').desc(), F('created').desc()).prefetch_related(Prefetch('subjects', queryset=Locator.objects.order_by('notesubject__sequence')))\nif self.series:\n notes = notes.filter(series=self.series)\nif self.kwargs.get('drafts') and self.request.user.is_authenticated:\n seri... | <|body_start_0|>
notes = Note.objects.order_by(F('published').desc(), F('created').desc()).prefetch_related(Prefetch('subjects', queryset=Locator.objects.order_by('notesubject__sequence')))
if self.series:
notes = notes.filter(series=self.series)
if self.kwargs.get('drafts') and self... | Get notes as the main query set with correct visibility and ordering. (Includes SeriesRequiredMixin hence also acquires series from request.) | NotesMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotesMixin:
"""Get notes as the main query set with correct visibility and ordering. (Includes SeriesRequiredMixin hence also acquires series from request.)"""
def get_queryset(self, **kwargs):
"""Acquire the relevant series and return the notes in that series."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_032754 | 12,479 | no_license | [
{
"docstring": "Acquire the relevant series and return the notes in that series.",
"name": "get_queryset",
"signature": "def get_queryset(self, **kwargs)"
},
{
"docstring": "Add the series to the context.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
... | 2 | stack_v2_sparse_classes_30k_train_010656 | Implement the Python class `NotesMixin` described below.
Class description:
Get notes as the main query set with correct visibility and ordering. (Includes SeriesRequiredMixin hence also acquires series from request.)
Method signatures and docstrings:
- def get_queryset(self, **kwargs): Acquire the relevant series an... | Implement the Python class `NotesMixin` described below.
Class description:
Get notes as the main query set with correct visibility and ordering. (Includes SeriesRequiredMixin hence also acquires series from request.)
Method signatures and docstrings:
- def get_queryset(self, **kwargs): Acquire the relevant series an... | 0075ea457f764cbb67acecb584e927bf58d2e7a8 | <|skeleton|>
class NotesMixin:
"""Get notes as the main query set with correct visibility and ordering. (Includes SeriesRequiredMixin hence also acquires series from request.)"""
def get_queryset(self, **kwargs):
"""Acquire the relevant series and return the notes in that series."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotesMixin:
"""Get notes as the main query set with correct visibility and ordering. (Includes SeriesRequiredMixin hence also acquires series from request.)"""
def get_queryset(self, **kwargs):
"""Acquire the relevant series and return the notes in that series."""
notes = Note.objects.ord... | the_stack_v2_python_sparse | linotak/notes/views.py | pdc/linotak | train | 0 |
77b3858c687b0a5fb341028860e723b4317f972b | [
"self._device_key = config.get(CONF_DEVICE_KEY)\nself._event = config.get(CONF_EVENT)\nself._password = config.get(CONF_PASSWORD)\nself._salt = config.get(CONF_SALT)",
"title = kwargs.get(ATTR_TITLE, ATTR_TITLE_DEFAULT)\nif self._password:\n send_encrypted(self._device_key, self._password, self._salt, title, m... | <|body_start_0|>
self._device_key = config.get(CONF_DEVICE_KEY)
self._event = config.get(CONF_EVENT)
self._password = config.get(CONF_PASSWORD)
self._salt = config.get(CONF_SALT)
<|end_body_0|>
<|body_start_1|>
title = kwargs.get(ATTR_TITLE, ATTR_TITLE_DEFAULT)
if self._... | Implementation of the notification service for Simplepush. | SimplePushNotificationService | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimplePushNotificationService:
"""Implementation of the notification service for Simplepush."""
def __init__(self, config):
"""Initialize the Simplepush notification service."""
<|body_0|>
def send_message(self, message='', **kwargs):
"""Send a message to a Simpl... | stack_v2_sparse_classes_36k_train_032755 | 1,785 | permissive | [
{
"docstring": "Initialize the Simplepush notification service.",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Send a message to a Simplepush user.",
"name": "send_message",
"signature": "def send_message(self, message='', **kwargs)"
}
] | 2 | null | Implement the Python class `SimplePushNotificationService` described below.
Class description:
Implementation of the notification service for Simplepush.
Method signatures and docstrings:
- def __init__(self, config): Initialize the Simplepush notification service.
- def send_message(self, message='', **kwargs): Send... | Implement the Python class `SimplePushNotificationService` described below.
Class description:
Implementation of the notification service for Simplepush.
Method signatures and docstrings:
- def __init__(self, config): Initialize the Simplepush notification service.
- def send_message(self, message='', **kwargs): Send... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class SimplePushNotificationService:
"""Implementation of the notification service for Simplepush."""
def __init__(self, config):
"""Initialize the Simplepush notification service."""
<|body_0|>
def send_message(self, message='', **kwargs):
"""Send a message to a Simpl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimplePushNotificationService:
"""Implementation of the notification service for Simplepush."""
def __init__(self, config):
"""Initialize the Simplepush notification service."""
self._device_key = config.get(CONF_DEVICE_KEY)
self._event = config.get(CONF_EVENT)
self._passw... | the_stack_v2_python_sparse | homeassistant/components/simplepush/notify.py | BenWoodford/home-assistant | train | 11 |
683859b8ebbb5d83222e3e406b7333fa266a277e | [
"t = [0.1, 0.2, a]\nres = fn.diag(t)\nassert fn.get_interface(res) == interface\nassert fn.allclose(res, onp.diag([0.1, 0.2, 0.5]))",
"t = np.array([0.1, 0.2, 0.3])\nres = fn.diag(t)\nassert isinstance(res, np.ndarray)\nassert fn.allclose(res, onp.diag([0.1, 0.2, 0.3]))\nres = fn.diag(t, k=1)\nassert fn.allclose(... | <|body_start_0|>
t = [0.1, 0.2, a]
res = fn.diag(t)
assert fn.get_interface(res) == interface
assert fn.allclose(res, onp.diag([0.1, 0.2, 0.5]))
<|end_body_0|>
<|body_start_1|>
t = np.array([0.1, 0.2, 0.3])
res = fn.diag(t)
assert isinstance(res, np.ndarray)
... | Tests for the diag function | TestDiag | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDiag:
"""Tests for the diag function"""
def test_sequence(self, a, interface):
"""Test that a sequence is automatically converted into a diagonal tensor"""
<|body_0|>
def test_array(self):
"""Test that a NumPy array is automatically converted into a diagonal ... | stack_v2_sparse_classes_36k_train_032756 | 47,600 | permissive | [
{
"docstring": "Test that a sequence is automatically converted into a diagonal tensor",
"name": "test_sequence",
"signature": "def test_sequence(self, a, interface)"
},
{
"docstring": "Test that a NumPy array is automatically converted into a diagonal tensor",
"name": "test_array",
"sig... | 5 | null | Implement the Python class `TestDiag` described below.
Class description:
Tests for the diag function
Method signatures and docstrings:
- def test_sequence(self, a, interface): Test that a sequence is automatically converted into a diagonal tensor
- def test_array(self): Test that a NumPy array is automatically conve... | Implement the Python class `TestDiag` described below.
Class description:
Tests for the diag function
Method signatures and docstrings:
- def test_sequence(self, a, interface): Test that a sequence is automatically converted into a diagonal tensor
- def test_array(self): Test that a NumPy array is automatically conve... | 0c1c805fd5dfce465a8955ee3faf81037023a23e | <|skeleton|>
class TestDiag:
"""Tests for the diag function"""
def test_sequence(self, a, interface):
"""Test that a sequence is automatically converted into a diagonal tensor"""
<|body_0|>
def test_array(self):
"""Test that a NumPy array is automatically converted into a diagonal ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDiag:
"""Tests for the diag function"""
def test_sequence(self, a, interface):
"""Test that a sequence is automatically converted into a diagonal tensor"""
t = [0.1, 0.2, a]
res = fn.diag(t)
assert fn.get_interface(res) == interface
assert fn.allclose(res, onp.... | the_stack_v2_python_sparse | artifacts/old_dataset_versions/original_commits_backup/pennylane/pennylane#1081/before/test_functions.py | MattePalte/Bugs-Quantum-Computing-Platforms | train | 4 |
90924ca0af879fb01271742ad4796a6646ae5b7e | [
"project_id, board_id = util.project_or_object(project, board, section_name=DOCK_NAME_MESSAGE_BOARD)\ndata = {'subject': subject, 'status': status}\nif content is not None:\n data['content'] = content\nif category is not None:\n data['category_id'] = int(category)\nurl = self.CREATE_URL.format(base_url=self.u... | <|body_start_0|>
project_id, board_id = util.project_or_object(project, board, section_name=DOCK_NAME_MESSAGE_BOARD)
data = {'subject': subject, 'status': status}
if content is not None:
data['content'] = content
if category is not None:
data['category_id'] = int(... | Messages | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Messages:
def create(self, subject, content=None, status='active', category=None, project=None, board=None):
"""Create a new Message object. Either a project ID and MessageBoard ID must be given or just a MessageBoard object. :param subject: the subject (title) of this message :type subj... | stack_v2_sparse_classes_36k_train_032757 | 6,252 | permissive | [
{
"docstring": "Create a new Message object. Either a project ID and MessageBoard ID must be given or just a MessageBoard object. :param subject: the subject (title) of this message :type subject: str :param content: the content (body) of this message. Can be HTML. :type content: str :param status: the status o... | 4 | stack_v2_sparse_classes_30k_train_011692 | Implement the Python class `Messages` described below.
Class description:
Implement the Messages class.
Method signatures and docstrings:
- def create(self, subject, content=None, status='active', category=None, project=None, board=None): Create a new Message object. Either a project ID and MessageBoard ID must be gi... | Implement the Python class `Messages` described below.
Class description:
Implement the Messages class.
Method signatures and docstrings:
- def create(self, subject, content=None, status='active', category=None, project=None, board=None): Create a new Message object. Either a project ID and MessageBoard ID must be gi... | bece72d06b91de0e33afd2181c59b895dbe7ae1f | <|skeleton|>
class Messages:
def create(self, subject, content=None, status='active', category=None, project=None, board=None):
"""Create a new Message object. Either a project ID and MessageBoard ID must be given or just a MessageBoard object. :param subject: the subject (title) of this message :type subj... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Messages:
def create(self, subject, content=None, status='active', category=None, project=None, board=None):
"""Create a new Message object. Either a project ID and MessageBoard ID must be given or just a MessageBoard object. :param subject: the subject (title) of this message :type subject: str :para... | the_stack_v2_python_sparse | basecampy3/endpoints/messages.py | phistrom/basecampy3 | train | 34 | |
0134d263001470822ad18f2a2184130c073b56ee | [
"start = max(start1, start2)\nend = min(end1, end2)\nif start > end:\n return (None, None)\nreturn (start, end)",
"for row in rows:\n for key_start_date, key_end_date in keys:\n if key_start_date not in [self._key_start_date, self._key_end_date]:\n row[key_start_date] = self._date2int(row[... | <|body_start_0|>
start = max(start1, start2)
end = min(end1, end2)
if start > end:
return (None, None)
return (start, end)
<|end_body_0|>
<|body_start_1|>
for row in rows:
for key_start_date, key_end_date in keys:
if key_start_date not in ... | A helper class for joining data sets with date intervals. | Type2JoinHelper | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Type2JoinHelper:
"""A helper class for joining data sets with date intervals."""
def _intersect(start1, end1, start2, end2):
"""Returns the intersection of two intervals. Returns (None,None) if the intersection is empty. :param int start1: The start date of the first interval. :param... | stack_v2_sparse_classes_36k_train_032758 | 4,436 | permissive | [
{
"docstring": "Returns the intersection of two intervals. Returns (None,None) if the intersection is empty. :param int start1: The start date of the first interval. :param int end1: The end date of the first interval. :param int start2: The start date of the second interval. :param int end2: The end date of th... | 4 | stack_v2_sparse_classes_30k_val_000054 | Implement the Python class `Type2JoinHelper` described below.
Class description:
A helper class for joining data sets with date intervals.
Method signatures and docstrings:
- def _intersect(start1, end1, start2, end2): Returns the intersection of two intervals. Returns (None,None) if the intersection is empty. :param... | Implement the Python class `Type2JoinHelper` described below.
Class description:
A helper class for joining data sets with date intervals.
Method signatures and docstrings:
- def _intersect(start1, end1, start2, end2): Returns the intersection of two intervals. Returns (None,None) if the intersection is empty. :param... | 542e4d1dc974dad60f4e338a334c932a40b45ee2 | <|skeleton|>
class Type2JoinHelper:
"""A helper class for joining data sets with date intervals."""
def _intersect(start1, end1, start2, end2):
"""Returns the intersection of two intervals. Returns (None,None) if the intersection is empty. :param int start1: The start date of the first interval. :param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Type2JoinHelper:
"""A helper class for joining data sets with date intervals."""
def _intersect(start1, end1, start2, end2):
"""Returns the intersection of two intervals. Returns (None,None) if the intersection is empty. :param int start1: The start date of the first interval. :param int end1: Th... | the_stack_v2_python_sparse | etlt/helper/Type2JoinHelper.py | PyETLT/etlt | train | 1 |
cbc91a97ce80a3fe4bc7a9fa14fb844f3a4cd2f2 | [
"self.device_id = device_id\nself.rule_id = rule_id\nself.timestamp_start = APIHelper.RFC3339DateTime(timestamp_start) if timestamp_start else None\nself.timestamp_end = APIHelper.RFC3339DateTime(timestamp_end) if timestamp_end else None\nself.message = message\nself.comment = comment\nself.description = descriptio... | <|body_start_0|>
self.device_id = device_id
self.rule_id = rule_id
self.timestamp_start = APIHelper.RFC3339DateTime(timestamp_start) if timestamp_start else None
self.timestamp_end = APIHelper.RFC3339DateTime(timestamp_end) if timestamp_end else None
self.message = message
... | Implementation of the 'AlertItem' model. An alert generated for a device based on a rule. Attributes: device_id (int): The id of the device the alert was generated for. rule_id (int): The id of the rule the alert is based on. timestamp_start (datetime): The timestamp when the alert began. The timestamp is in the time z... | AlertItem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlertItem:
"""Implementation of the 'AlertItem' model. An alert generated for a device based on a rule. Attributes: device_id (int): The id of the device the alert was generated for. rule_id (int): The id of the rule the alert is based on. timestamp_start (datetime): The timestamp when the alert ... | stack_v2_sparse_classes_36k_train_032759 | 3,801 | permissive | [
{
"docstring": "Constructor for the AlertItem class",
"name": "__init__",
"signature": "def __init__(self, device_id=None, rule_id=None, timestamp_start=None, timestamp_end=None, message=None, comment=None, description=None, details=None)"
},
{
"docstring": "Creates an instance of this model fro... | 2 | stack_v2_sparse_classes_30k_train_001151 | Implement the Python class `AlertItem` described below.
Class description:
Implementation of the 'AlertItem' model. An alert generated for a device based on a rule. Attributes: device_id (int): The id of the device the alert was generated for. rule_id (int): The id of the rule the alert is based on. timestamp_start (d... | Implement the Python class `AlertItem` described below.
Class description:
Implementation of the 'AlertItem' model. An alert generated for a device based on a rule. Attributes: device_id (int): The id of the device the alert was generated for. rule_id (int): The id of the rule the alert is based on. timestamp_start (d... | 6835ee1f6a667b5c7827c5248391081f06b75513 | <|skeleton|>
class AlertItem:
"""Implementation of the 'AlertItem' model. An alert generated for a device based on a rule. Attributes: device_id (int): The id of the device the alert was generated for. rule_id (int): The id of the rule the alert is based on. timestamp_start (datetime): The timestamp when the alert ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlertItem:
"""Implementation of the 'AlertItem' model. An alert generated for a device based on a rule. Attributes: device_id (int): The id of the device the alert was generated for. rule_id (int): The id of the rule the alert is based on. timestamp_start (datetime): The timestamp when the alert began. The ti... | the_stack_v2_python_sparse | greenbyteapi/models/alert_item.py | charlie9578/greenbyte-api-sdk | train | 0 |
387f43812e7915303ce56c77a28359ebf732f746 | [
"self.page = page\nself.url = url\nself.history = history\nself.header = {'Accept': 'text/xml,application/xml,application/xhtml+xml,text/html;q=0.9,text/plain;q=0.8,image/png,*/*;q=0.5', 'Accept-Language': 'de-de,de;q=0.8,en-us;q=0.5,en;q=0.3', 'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.7', 'Keep-Alive': '30',... | <|body_start_0|>
self.page = page
self.url = url
self.history = history
self.header = {'Accept': 'text/xml,application/xml,application/xhtml+xml,text/html;q=0.9,text/plain;q=0.8,image/png,*/*;q=0.5', 'Accept-Language': 'de-de,de;q=0.8,en-us;q=0.5,en;q=0.3', 'Accept-Charset': 'ISO-8859-1,... | A thread responsible for checking one URL. After checking the page, it will die. | LinkCheckThread | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkCheckThread:
"""A thread responsible for checking one URL. After checking the page, it will die."""
def __init__(self, page, url, history, http_ignores, day) -> None:
"""Initializer."""
<|body_0|>
def get_delay(cls, name: str) -> float:
"""Determine delay fro... | stack_v2_sparse_classes_36k_train_032760 | 25,993 | permissive | [
{
"docstring": "Initializer.",
"name": "__init__",
"signature": "def __init__(self, page, url, history, http_ignores, day) -> None"
},
{
"docstring": "Determine delay from class attribute. Store the last call for a given hostname with an offset of 6 seconds to ensure there are no more than 10 ca... | 3 | stack_v2_sparse_classes_30k_train_000936 | Implement the Python class `LinkCheckThread` described below.
Class description:
A thread responsible for checking one URL. After checking the page, it will die.
Method signatures and docstrings:
- def __init__(self, page, url, history, http_ignores, day) -> None: Initializer.
- def get_delay(cls, name: str) -> float... | Implement the Python class `LinkCheckThread` described below.
Class description:
A thread responsible for checking one URL. After checking the page, it will die.
Method signatures and docstrings:
- def __init__(self, page, url, history, http_ignores, day) -> None: Initializer.
- def get_delay(cls, name: str) -> float... | 5c01e6bfcd328bc6eae643e661f1a0ae57612808 | <|skeleton|>
class LinkCheckThread:
"""A thread responsible for checking one URL. After checking the page, it will die."""
def __init__(self, page, url, history, http_ignores, day) -> None:
"""Initializer."""
<|body_0|>
def get_delay(cls, name: str) -> float:
"""Determine delay fro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkCheckThread:
"""A thread responsible for checking one URL. After checking the page, it will die."""
def __init__(self, page, url, history, http_ignores, day) -> None:
"""Initializer."""
self.page = page
self.url = url
self.history = history
self.header = {'Acce... | the_stack_v2_python_sparse | scripts/weblinkchecker.py | wikimedia/pywikibot | train | 432 |
73eb9de748e1e504846b654b92369ae7f00c1e55 | [
"if not s:\n return 0\nhead = 0\ntail = 0\nres = 1\nn = len(s)\nwhile tail + 1 < n:\n tail += 1\n if s[tail] not in s[head:tail]:\n res = max(tail - head + 1, res)\n else:\n while s[tail] in s[head:tail]:\n head += 1\nreturn res",
"if not s:\n return 0\ndic = {}\nres = 0\ni... | <|body_start_0|>
if not s:
return 0
head = 0
tail = 0
res = 1
n = len(s)
while tail + 1 < n:
tail += 1
if s[tail] not in s[head:tail]:
res = max(tail - head + 1, res)
else:
while s[tail] in s[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring(self, s):
"""首先想到暴力解法，嵌套的遍历找到所有字符串时间复杂度n**2， 对于每一个字符串利用hashset遍历一次看是否有重复字符，时间复杂度n 整体时间复杂度n**3 空间复杂度：m大小的hashset，所有可能出现的字符 :param s: :return:"""
<|body_0|>
def lengthOfLongestSubstring_v2(self, s):
"""滑动窗口+哈希表 :param s: :return:"... | stack_v2_sparse_classes_36k_train_032761 | 2,241 | no_license | [
{
"docstring": "首先想到暴力解法，嵌套的遍历找到所有字符串时间复杂度n**2， 对于每一个字符串利用hashset遍历一次看是否有重复字符，时间复杂度n 整体时间复杂度n**3 空间复杂度：m大小的hashset，所有可能出现的字符 :param s: :return:",
"name": "lengthOfLongestSubstring",
"signature": "def lengthOfLongestSubstring(self, s)"
},
{
"docstring": "滑动窗口+哈希表 :param s: :return:",
"name": ... | 2 | stack_v2_sparse_classes_30k_train_005590 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring(self, s): 首先想到暴力解法，嵌套的遍历找到所有字符串时间复杂度n**2， 对于每一个字符串利用hashset遍历一次看是否有重复字符，时间复杂度n 整体时间复杂度n**3 空间复杂度：m大小的hashset，所有可能出现的字符 :param s: :return:
- def lengt... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring(self, s): 首先想到暴力解法，嵌套的遍历找到所有字符串时间复杂度n**2， 对于每一个字符串利用hashset遍历一次看是否有重复字符，时间复杂度n 整体时间复杂度n**3 空间复杂度：m大小的hashset，所有可能出现的字符 :param s: :return:
- def lengt... | f1bbd6b3197cd9ac4f0d35a37539c11b02272065 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring(self, s):
"""首先想到暴力解法，嵌套的遍历找到所有字符串时间复杂度n**2， 对于每一个字符串利用hashset遍历一次看是否有重复字符，时间复杂度n 整体时间复杂度n**3 空间复杂度：m大小的hashset，所有可能出现的字符 :param s: :return:"""
<|body_0|>
def lengthOfLongestSubstring_v2(self, s):
"""滑动窗口+哈希表 :param s: :return:"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLongestSubstring(self, s):
"""首先想到暴力解法，嵌套的遍历找到所有字符串时间复杂度n**2， 对于每一个字符串利用hashset遍历一次看是否有重复字符，时间复杂度n 整体时间复杂度n**3 空间复杂度：m大小的hashset，所有可能出现的字符 :param s: :return:"""
if not s:
return 0
head = 0
tail = 0
res = 1
n = len(s)
whi... | the_stack_v2_python_sparse | offer/动态规划/48. 最长不含重复字符的字符串/lengthOfLongestSubstring.py | guohaoyuan/algorithms-for-work | train | 2 | |
f34e291d37e57dc602c62d47000df76508559087 | [
"self.mostVotedByTime = dict()\nself.mostVoted = dict()\nmaxVotes = 0\nperson = 0\nfor i, t in enumerate(times):\n if persons[i] not in self.mostVoted.keys():\n self.mostVoted[persons[i]] = 1\n else:\n self.mostVoted[persons[i]] += 1\n if maxVotes <= self.mostVoted[persons[i]]:\n maxVo... | <|body_start_0|>
self.mostVotedByTime = dict()
self.mostVoted = dict()
maxVotes = 0
person = 0
for i, t in enumerate(times):
if persons[i] not in self.mostVoted.keys():
self.mostVoted[persons[i]] = 1
else:
self.mostVoted[per... | TopVotedCandidate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
<|body_0|>
def q(self, t):
""":type t: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.mostVotedByTime = dict()
... | stack_v2_sparse_classes_36k_train_032762 | 2,534 | no_license | [
{
"docstring": ":type persons: List[int] :type times: List[int]",
"name": "__init__",
"signature": "def __init__(self, persons, times)"
},
{
"docstring": ":type t: int :rtype: int",
"name": "q",
"signature": "def q(self, t)"
}
] | 2 | null | Implement the Python class `TopVotedCandidate` described below.
Class description:
Implement the TopVotedCandidate class.
Method signatures and docstrings:
- def __init__(self, persons, times): :type persons: List[int] :type times: List[int]
- def q(self, t): :type t: int :rtype: int | Implement the Python class `TopVotedCandidate` described below.
Class description:
Implement the TopVotedCandidate class.
Method signatures and docstrings:
- def __init__(self, persons, times): :type persons: List[int] :type times: List[int]
- def q(self, t): :type t: int :rtype: int
<|skeleton|>
class TopVotedCandi... | 4d7e675c795c841f99ca95b8b60c4995bcb632fb | <|skeleton|>
class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
<|body_0|>
def q(self, t):
""":type t: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
self.mostVotedByTime = dict()
self.mostVoted = dict()
maxVotes = 0
person = 0
for i, t in enumerate(times):
if persons[i] not in self.mostVot... | the_stack_v2_python_sparse | 911_Online Election.py | stephenchenxj/myLeetCode | train | 0 | |
e45bdd713e59a6b642a30c1d31923a205e1b1325 | [
"momentum = kwargs.pop('momentum', 0.9)\nupdate_vars = tf.trainable_variables()\nreturn tf.train.MomentumOptimizer(self.learning_rate_placeholder, momentum, use_nesterov=False).minimize(self.model.loss, var_list=update_vars)",
"learning_rate_patience = kwargs.pop('learning_rate_patience', 10)\nlearning_rate_decay... | <|body_start_0|>
momentum = kwargs.pop('momentum', 0.9)
update_vars = tf.trainable_variables()
return tf.train.MomentumOptimizer(self.learning_rate_placeholder, momentum, use_nesterov=False).minimize(self.model.loss, var_list=update_vars)
<|end_body_0|>
<|body_start_1|>
learning_rate_pa... | 모멘텀 알고리즘을 포함한 경사 하강 optimizer 클래스. | MomentumOptimizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MomentumOptimizer:
"""모멘텀 알고리즘을 포함한 경사 하강 optimizer 클래스."""
def _optimize_op(self, **kwargs):
"""경사 하강 업데이트를 위한 tf.train.MomentumOptimizer.minimize Op. :param kwargs: dict, optimizer의 추가 인자. - momentum: float, 모멘텀 계수. :return tf.Operation."""
<|body_0|>
def _update_learn... | stack_v2_sparse_classes_36k_train_032763 | 2,122 | no_license | [
{
"docstring": "경사 하강 업데이트를 위한 tf.train.MomentumOptimizer.minimize Op. :param kwargs: dict, optimizer의 추가 인자. - momentum: float, 모멘텀 계수. :return tf.Operation.",
"name": "_optimize_op",
"signature": "def _optimize_op(self, **kwargs)"
},
{
"docstring": "성능 평가 점수 상에 개선이 없을 때, 현 학습률 값을 업데이트함. :param... | 2 | stack_v2_sparse_classes_30k_train_017260 | Implement the Python class `MomentumOptimizer` described below.
Class description:
모멘텀 알고리즘을 포함한 경사 하강 optimizer 클래스.
Method signatures and docstrings:
- def _optimize_op(self, **kwargs): 경사 하강 업데이트를 위한 tf.train.MomentumOptimizer.minimize Op. :param kwargs: dict, optimizer의 추가 인자. - momentum: float, 모멘텀 계수. :return t... | Implement the Python class `MomentumOptimizer` described below.
Class description:
모멘텀 알고리즘을 포함한 경사 하강 optimizer 클래스.
Method signatures and docstrings:
- def _optimize_op(self, **kwargs): 경사 하강 업데이트를 위한 tf.train.MomentumOptimizer.minimize Op. :param kwargs: dict, optimizer의 추가 인자. - momentum: float, 모멘텀 계수. :return t... | af58878beb9f94ba4d6afd628ddb0a6ac6c41746 | <|skeleton|>
class MomentumOptimizer:
"""모멘텀 알고리즘을 포함한 경사 하강 optimizer 클래스."""
def _optimize_op(self, **kwargs):
"""경사 하강 업데이트를 위한 tf.train.MomentumOptimizer.minimize Op. :param kwargs: dict, optimizer의 추가 인자. - momentum: float, 모멘텀 계수. :return tf.Operation."""
<|body_0|>
def _update_learn... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MomentumOptimizer:
"""모멘텀 알고리즘을 포함한 경사 하강 optimizer 클래스."""
def _optimize_op(self, **kwargs):
"""경사 하강 업데이트를 위한 tf.train.MomentumOptimizer.minimize Op. :param kwargs: dict, optimizer의 추가 인자. - momentum: float, 모멘텀 계수. :return tf.Operation."""
momentum = kwargs.pop('momentum', 0.9)
... | the_stack_v2_python_sparse | source/optimizer/MomentumOptimizer.py | mmecoco/Workshop_AI | train | 0 |
2f3a43ab7610f3425b5a914020cd5e9b7bb41dd5 | [
"ContextLemmatizer.__init__(self, context_to_lemmatize, backoff)\nself.include = include\nself._context_to_tag = context_to_lemmatize if context_to_lemmatize else {}",
"from cltk.tag.pos import POSTag\ntagger = POSTag('latin')\ntokens = ' '.join(tokens)\ntags = tagger.tag_ngram_123_backoff(tokens)\ntags = [tag[1]... | <|body_start_0|>
ContextLemmatizer.__init__(self, context_to_lemmatize, backoff)
self.include = include
self._context_to_tag = context_to_lemmatize if context_to_lemmatize else {}
<|end_body_0|>
<|body_start_1|>
from cltk.tag.pos import POSTag
tagger = POSTag('latin')
to... | Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatizer is included here as proof of concept that lemma disambiguation can be made based on t... | ContextPOSLemmatizer | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContextPOSLemmatizer:
"""Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatizer is included here as proof of concept ... | stack_v2_sparse_classes_36k_train_032764 | 23,254 | permissive | [
{
"docstring": "Setup ContextPOSLemmatizer(). :param context_to_lemmatize: List of tuples of the form (TOKEN, LEMMA); this should be 'gold standard' data that can be used to train on a given context, e.g. unigrams, bigrams, etc. :param include: List of tokens to include, all other tokens return None from choose... | 4 | stack_v2_sparse_classes_30k_train_004301 | Implement the Python class `ContextPOSLemmatizer` described below.
Class description:
Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatize... | Implement the Python class `ContextPOSLemmatizer` described below.
Class description:
Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatize... | 085420eaed7055fbcb311714eebb67861fd1b241 | <|skeleton|>
class ContextPOSLemmatizer:
"""Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatizer is included here as proof of concept ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContextPOSLemmatizer:
"""Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatizer is included here as proof of concept that lemma di... | the_stack_v2_python_sparse | cltk/lemmatize/latin/backoff.py | jerryfrancis-97/cltk | train | 1 |
fbb76fddb17bdf935ccb515f2bad2025f2391a9e | [
"self.comm = comm\nself.model = model\nself.auto_copy = auto_copy\nif auto_copy:\n self.copy_aero_mesh()\nreturn",
"for body in self.model.bodies:\n aero_id = np.arange(1, body.get_num_struct_nodes() + 1)\n body.initialize_aero_nodes(body.struct_X, aero_id)\nreturn self"
] | <|body_start_0|>
self.comm = comm
self.model = model
self.auto_copy = auto_copy
if auto_copy:
self.copy_aero_mesh()
return
<|end_body_0|>
<|body_start_1|>
for body in self.model.bodies:
aero_id = np.arange(1, body.get_num_struct_nodes() + 1)
... | NullAerodynamicSolver | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NullAerodynamicSolver:
def __init__(self, comm, model, auto_copy=False):
"""This class provides the functionality that FUNtoFEM expects from an aerodynamic solver, except no aerodynamics is performed here. All solver interface routines we just do nothing and those methods come from the s... | stack_v2_sparse_classes_36k_train_032765 | 45,431 | permissive | [
{
"docstring": "This class provides the functionality that FUNtoFEM expects from an aerodynamic solver, except no aerodynamics is performed here. All solver interface routines we just do nothing and those methods come from the super class SolverInterface Parameters ---------- comm: MPI.comm MPI communicator mod... | 2 | null | Implement the Python class `NullAerodynamicSolver` described below.
Class description:
Implement the NullAerodynamicSolver class.
Method signatures and docstrings:
- def __init__(self, comm, model, auto_copy=False): This class provides the functionality that FUNtoFEM expects from an aerodynamic solver, except no aero... | Implement the Python class `NullAerodynamicSolver` described below.
Class description:
Implement the NullAerodynamicSolver class.
Method signatures and docstrings:
- def __init__(self, comm, model, auto_copy=False): This class provides the functionality that FUNtoFEM expects from an aerodynamic solver, except no aero... | 4c11b61397100f9d8b455f7d20cf3b507a15c1e9 | <|skeleton|>
class NullAerodynamicSolver:
def __init__(self, comm, model, auto_copy=False):
"""This class provides the functionality that FUNtoFEM expects from an aerodynamic solver, except no aerodynamics is performed here. All solver interface routines we just do nothing and those methods come from the s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NullAerodynamicSolver:
def __init__(self, comm, model, auto_copy=False):
"""This class provides the functionality that FUNtoFEM expects from an aerodynamic solver, except no aerodynamics is performed here. All solver interface routines we just do nothing and those methods come from the super class Sol... | the_stack_v2_python_sparse | funtofem/interface/test_solver.py | gjkennedy/funtofem | train | 0 | |
b6d751bee3e871bce59453d32b8c4bb19b1aa645 | [
"self.parser = reqparse.RequestParser()\nself.parser.add_argument('name')\nself.parser.add_argument('token')\nsuper(CtaStrategyStop, self).__init__()",
"args = self.parser.parse_args()\ntoken = args['token']\nname = 'strategyHedge_syt'\nengine = me.getApp('CtaStrategy')\nif not name:\n engine.stopAll()\nelse:\... | <|body_start_0|>
self.parser = reqparse.RequestParser()
self.parser.add_argument('name')
self.parser.add_argument('token')
super(CtaStrategyStop, self).__init__()
<|end_body_0|>
<|body_start_1|>
args = self.parser.parse_args()
token = args['token']
name = 'strate... | 停止策略 | CtaStrategyStop | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CtaStrategyStop:
"""停止策略"""
def __init__(self):
"""初始化"""
<|body_0|>
def post(self):
"""订阅"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.parser = reqparse.RequestParser()
self.parser.add_argument('name')
self.parser.add_ar... | stack_v2_sparse_classes_36k_train_032766 | 24,002 | permissive | [
{
"docstring": "初始化",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "订阅",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020528 | Implement the Python class `CtaStrategyStop` described below.
Class description:
停止策略
Method signatures and docstrings:
- def __init__(self): 初始化
- def post(self): 订阅 | Implement the Python class `CtaStrategyStop` described below.
Class description:
停止策略
Method signatures and docstrings:
- def __init__(self): 初始化
- def post(self): 订阅
<|skeleton|>
class CtaStrategyStop:
"""停止策略"""
def __init__(self):
"""初始化"""
<|body_0|>
def post(self):
"""订阅"""... | c316649161086da2543d39bf0455d0f793cdd08f | <|skeleton|>
class CtaStrategyStop:
"""停止策略"""
def __init__(self):
"""初始化"""
<|body_0|>
def post(self):
"""订阅"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CtaStrategyStop:
"""停止策略"""
def __init__(self):
"""初始化"""
self.parser = reqparse.RequestParser()
self.parser.add_argument('name')
self.parser.add_argument('token')
super(CtaStrategyStop, self).__init__()
def post(self):
"""订阅"""
args = self.par... | the_stack_v2_python_sparse | WebTrader/webServer.py | webclinic017/riskBacktestingPlatform | train | 0 |
dc56a785b396db4c4aa8f21e42f29f82600d7095 | [
"if not root:\n return None\nstack = []\nstack.append(root)\nstring = ''\nwhile len(stack) != 0:\n node = stack.pop()\n if not node:\n string += 'N '\n else:\n string += str(node.val) + ' '\n if node.right or node.left:\n stack.append(node.right)\n stack.append... | <|body_start_0|>
if not root:
return None
stack = []
stack.append(root)
string = ''
while len(stack) != 0:
node = stack.pop()
if not node:
string += 'N '
else:
string += str(node.val) + ' '
... | 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_032767 | 2,146 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 85415872711c7c4b646f71ba44b5ef9200c03f5e | <|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 None
stack = []
stack.append(root)
string = ''
while len(stack) != 0:
node = stack.pop()
if not no... | the_stack_v2_python_sparse | 449.py | ninini976/yf_leetcode_problems | train | 0 | |
4685d1a18814c82150870909f3aa70f954e21be9 | [
"super().__init__(device=device, quantize=False, min_transformers_version='4.12.3')\nself.pipeline = pipeline('text-classification', model='cardiffnlp/twitter-roberta-base-sentiment', device=self.device_to_id(), **kwargs)\nself.mapping = {'LABEL_0': 'NEGATIVE', 'LABEL_1': 'NEUTRAL', 'LABEL_2': 'POSITIVE'}",
"str_... | <|body_start_0|>
super().__init__(device=device, quantize=False, min_transformers_version='4.12.3')
self.pipeline = pipeline('text-classification', model='cardiffnlp/twitter-roberta-base-sentiment', device=self.device_to_id(), **kwargs)
self.mapping = {'LABEL_0': 'NEGATIVE', 'LABEL_1': 'NEUTRAL'... | interface to Sentiment Analyzer | SentimentAnalyzer | [
"Apache-2.0",
"CC-BY-NC-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentimentAnalyzer:
"""interface to Sentiment Analyzer"""
def __init__(self, device=None, **kwargs):
"""``` ImageCaptioner constructor Args: device(str): device to use (e.g., 'cuda', 'cpu') ```"""
<|body_0|>
def predict(self, texts: Union[str, list], return_all_scores=Fal... | stack_v2_sparse_classes_36k_train_032768 | 2,245 | permissive | [
{
"docstring": "``` ImageCaptioner constructor Args: device(str): device to use (e.g., 'cuda', 'cpu') ```",
"name": "__init__",
"signature": "def __init__(self, device=None, **kwargs)"
},
{
"docstring": "``` Performs sentiment analysis This method accepts a list of texts and predicts their senti... | 3 | stack_v2_sparse_classes_30k_train_018623 | Implement the Python class `SentimentAnalyzer` described below.
Class description:
interface to Sentiment Analyzer
Method signatures and docstrings:
- def __init__(self, device=None, **kwargs): ``` ImageCaptioner constructor Args: device(str): device to use (e.g., 'cuda', 'cpu') ```
- def predict(self, texts: Union[s... | Implement the Python class `SentimentAnalyzer` described below.
Class description:
interface to Sentiment Analyzer
Method signatures and docstrings:
- def __init__(self, device=None, **kwargs): ``` ImageCaptioner constructor Args: device(str): device to use (e.g., 'cuda', 'cpu') ```
- def predict(self, texts: Union[s... | ab03ae68053b727cb8907e08c35f265531d1cb3a | <|skeleton|>
class SentimentAnalyzer:
"""interface to Sentiment Analyzer"""
def __init__(self, device=None, **kwargs):
"""``` ImageCaptioner constructor Args: device(str): device to use (e.g., 'cuda', 'cpu') ```"""
<|body_0|>
def predict(self, texts: Union[str, list], return_all_scores=Fal... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SentimentAnalyzer:
"""interface to Sentiment Analyzer"""
def __init__(self, device=None, **kwargs):
"""``` ImageCaptioner constructor Args: device(str): device to use (e.g., 'cuda', 'cpu') ```"""
super().__init__(device=device, quantize=False, min_transformers_version='4.12.3')
se... | the_stack_v2_python_sparse | ktrain/text/sentiment/core.py | amaiya/ktrain | train | 1,217 |
1de01e443900874fadb022cb8d4337c11d378ad5 | [
"assert 0.0 <= cutmix_prob <= 1.0, 'cutmix_prob should be between 0.0 and 1.0'\nsuper().__init__()\nself.cutmix_prob = cutmix_prob\nself.mixup = MixUp(alpha=mixup_alpha, label_smoothing=label_smoothing, num_classes=num_classes)\nself.cutmix = CutMix(alpha=cutmix_alpha, label_smoothing=label_smoothing, num_classes=n... | <|body_start_0|>
assert 0.0 <= cutmix_prob <= 1.0, 'cutmix_prob should be between 0.0 and 1.0'
super().__init__()
self.cutmix_prob = cutmix_prob
self.mixup = MixUp(alpha=mixup_alpha, label_smoothing=label_smoothing, num_classes=num_classes)
self.cutmix = CutMix(alpha=cutmix_alpha... | Stochastically applies either MixUp or CutMix to the input video. | MixVideo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MixVideo:
"""Stochastically applies either MixUp or CutMix to the input video."""
def __init__(self, cutmix_prob: float=0.5, mixup_alpha: float=1.0, cutmix_alpha: float=1.0, label_smoothing: float=0.0, num_classes: int=400):
"""Args: cutmix_prob (float): Probability of using CutMix. ... | stack_v2_sparse_classes_36k_train_032769 | 7,161 | permissive | [
{
"docstring": "Args: cutmix_prob (float): Probability of using CutMix. MixUp will be used with probability 1 - cutmix_prob. If cutmix_prob is 0, then MixUp is always used. If cutmix_prob is 1, then CutMix is always used. mixup_alpha (float): MixUp alpha value. cutmix_alpha (float): CutMix alpha value. label_sm... | 2 | stack_v2_sparse_classes_30k_train_016213 | Implement the Python class `MixVideo` described below.
Class description:
Stochastically applies either MixUp or CutMix to the input video.
Method signatures and docstrings:
- def __init__(self, cutmix_prob: float=0.5, mixup_alpha: float=1.0, cutmix_alpha: float=1.0, label_smoothing: float=0.0, num_classes: int=400):... | Implement the Python class `MixVideo` described below.
Class description:
Stochastically applies either MixUp or CutMix to the input video.
Method signatures and docstrings:
- def __init__(self, cutmix_prob: float=0.5, mixup_alpha: float=1.0, cutmix_alpha: float=1.0, label_smoothing: float=0.0, num_classes: int=400):... | 16f2abf2f8aa174915316007622bbb260215dee8 | <|skeleton|>
class MixVideo:
"""Stochastically applies either MixUp or CutMix to the input video."""
def __init__(self, cutmix_prob: float=0.5, mixup_alpha: float=1.0, cutmix_alpha: float=1.0, label_smoothing: float=0.0, num_classes: int=400):
"""Args: cutmix_prob (float): Probability of using CutMix. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MixVideo:
"""Stochastically applies either MixUp or CutMix to the input video."""
def __init__(self, cutmix_prob: float=0.5, mixup_alpha: float=1.0, cutmix_alpha: float=1.0, label_smoothing: float=0.0, num_classes: int=400):
"""Args: cutmix_prob (float): Probability of using CutMix. MixUp will be... | the_stack_v2_python_sparse | pytorchvideo/transforms/mix.py | xchani/pytorchvideo | train | 0 |
fb8950ec16af1f232f6be7b3262e0b8da5413090 | [
"super(Application, self).__init__(master)\nself.grid()\nself.create_widgets()",
"Label(self, text='Укажите ваш любимый жанр кино.').grid(row=0, column=0, sticky=W)\nLabel(self, text='Выберите ровно 1:').grid(row=1, column=0, sticky=W)\nself.favorite = StringVar()\nself.favorite.set(None)\nRadiobutton(self, text=... | <|body_start_0|>
super(Application, self).__init__(master)
self.grid()
self.create_widgets()
<|end_body_0|>
<|body_start_1|>
Label(self, text='Укажите ваш любимый жанр кино.').grid(row=0, column=0, sticky=W)
Label(self, text='Выберите ровно 1:').grid(row=1, column=0, sticky=W)
... | GUI-Приложение, позволяющее выбрать только один жанр | Application | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Application:
"""GUI-Приложение, позволяющее выбрать только один жанр"""
def __init__(self, master):
"""Инициализируем рамку"""
<|body_0|>
def create_widgets(self):
"""Создает элементы, с помощью которых пользователь будет выбирать"""
<|body_1|>
def u... | stack_v2_sparse_classes_36k_train_032770 | 2,726 | no_license | [
{
"docstring": "Инициализируем рамку",
"name": "__init__",
"signature": "def __init__(self, master)"
},
{
"docstring": "Создает элементы, с помощью которых пользователь будет выбирать",
"name": "create_widgets",
"signature": "def create_widgets(self)"
},
{
"docstring": "Обновляет... | 3 | stack_v2_sparse_classes_30k_train_015031 | Implement the Python class `Application` described below.
Class description:
GUI-Приложение, позволяющее выбрать только один жанр
Method signatures and docstrings:
- def __init__(self, master): Инициализируем рамку
- def create_widgets(self): Создает элементы, с помощью которых пользователь будет выбирать
- def updat... | Implement the Python class `Application` described below.
Class description:
GUI-Приложение, позволяющее выбрать только один жанр
Method signatures and docstrings:
- def __init__(self, master): Инициализируем рамку
- def create_widgets(self): Создает элементы, с помощью которых пользователь будет выбирать
- def updat... | 5c3342fca0ad705a7719770894ee2480b62bf593 | <|skeleton|>
class Application:
"""GUI-Приложение, позволяющее выбрать только один жанр"""
def __init__(self, master):
"""Инициализируем рамку"""
<|body_0|>
def create_widgets(self):
"""Создает элементы, с помощью которых пользователь будет выбирать"""
<|body_1|>
def u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Application:
"""GUI-Приложение, позволяющее выбрать только один жанр"""
def __init__(self, master):
"""Инициализируем рамку"""
super(Application, self).__init__(master)
self.grid()
self.create_widgets()
def create_widgets(self):
"""Создает элементы, с помощью ... | the_stack_v2_python_sparse | Chapter_10/movie_chooser2.py | BlackJin1/FirstProgramm | train | 0 |
a63d3728fdaa2cbdf96e6a4fbb7197237db32968 | [
"context = {'ingestion_request_id': ingestion_request_id}\ntry:\n ingestion_request = models.IngestionRequest.objects.get(pk=ingestion_request_id)\nexcept models.IngestionRequest.DoesNotExist:\n return redirect('/data_cube_manager/ingestion/subset')\nfiltering_options = {key: getattr(ingestion_request, key) f... | <|body_start_0|>
context = {'ingestion_request_id': ingestion_request_id}
try:
ingestion_request = models.IngestionRequest.objects.get(pk=ingestion_request_id)
except models.IngestionRequest.DoesNotExist:
return redirect('/data_cube_manager/ingestion/subset')
filt... | Status page for an ingestion request | CheckIngestionRequestStatus | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckIngestionRequestStatus:
"""Status page for an ingestion request"""
def get(self, request, ingestion_request_id):
"""Check the status of an ingestion request and update the model Returns a rendered html response containing a non-editable form displaying the ingestion request data... | stack_v2_sparse_classes_36k_train_032771 | 19,958 | permissive | [
{
"docstring": "Check the status of an ingestion request and update the model Returns a rendered html response containing a non-editable form displaying the ingestion request data, instructions, and a progress bar.",
"name": "get",
"signature": "def get(self, request, ingestion_request_id)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_020274 | Implement the Python class `CheckIngestionRequestStatus` described below.
Class description:
Status page for an ingestion request
Method signatures and docstrings:
- def get(self, request, ingestion_request_id): Check the status of an ingestion request and update the model Returns a rendered html response containing ... | Implement the Python class `CheckIngestionRequestStatus` described below.
Class description:
Status page for an ingestion request
Method signatures and docstrings:
- def get(self, request, ingestion_request_id): Check the status of an ingestion request and update the model Returns a rendered html response containing ... | ef50e918df89313f130d735e7cb7c0a069da410e | <|skeleton|>
class CheckIngestionRequestStatus:
"""Status page for an ingestion request"""
def get(self, request, ingestion_request_id):
"""Check the status of an ingestion request and update the model Returns a rendered html response containing a non-editable form displaying the ingestion request data... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckIngestionRequestStatus:
"""Status page for an ingestion request"""
def get(self, request, ingestion_request_id):
"""Check the status of an ingestion request and update the model Returns a rendered html response containing a non-editable form displaying the ingestion request data, instruction... | the_stack_v2_python_sparse | apps/data_cube_manager/views/ingestion.py | ceos-seo/data_cube_ui | train | 47 |
6fdbd4f2ac1a5749953d0d38515d4b7fdf53b04b | [
"super().__init__(n_head, n_feat, dropout_rate)\nself.zero_triu = zero_triu\nself.linear_pos = nn.Linear(n_feat, n_feat, bias_attr=False)\nself.pos_bias_u = paddle.create_parameter(shape=(self.h, self.d_k), dtype='float32', default_initializer=paddle.nn.initializer.XavierUniform())\nself.pos_bias_v = paddle.create_... | <|body_start_0|>
super().__init__(n_head, n_feat, dropout_rate)
self.zero_triu = zero_triu
self.linear_pos = nn.Linear(n_feat, n_feat, bias_attr=False)
self.pos_bias_u = paddle.create_parameter(shape=(self.h, self.d_k), dtype='float32', default_initializer=paddle.nn.initializer.XavierUni... | Multi-Head Attention layer with relative position encoding (old version). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of heads. n_feat (int): The number of features. dropout_rate (float): Dropout rate. zero_triu (bool): Wheth... | LegacyRelPositionMultiHeadedAttention | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LegacyRelPositionMultiHeadedAttention:
"""Multi-Head Attention layer with relative position encoding (old version). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of heads. n_feat (int): The number of feat... | stack_v2_sparse_classes_36k_train_032772 | 13,512 | permissive | [
{
"docstring": "Construct an RelPositionMultiHeadedAttention object.",
"name": "__init__",
"signature": "def __init__(self, n_head, n_feat, dropout_rate, zero_triu=False)"
},
{
"docstring": "Compute relative positional encoding. Args: x(Tensor): Input tensor (batch, head, time1, time2). Returns:... | 3 | null | Implement the Python class `LegacyRelPositionMultiHeadedAttention` described below.
Class description:
Multi-Head Attention layer with relative position encoding (old version). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of ... | Implement the Python class `LegacyRelPositionMultiHeadedAttention` described below.
Class description:
Multi-Head Attention layer with relative position encoding (old version). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of ... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class LegacyRelPositionMultiHeadedAttention:
"""Multi-Head Attention layer with relative position encoding (old version). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of heads. n_feat (int): The number of feat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LegacyRelPositionMultiHeadedAttention:
"""Multi-Head Attention layer with relative position encoding (old version). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of heads. n_feat (int): The number of features. dropout... | the_stack_v2_python_sparse | paddlespeech/t2s/modules/transformer/attention.py | anniyanvr/DeepSpeech-1 | train | 0 |
0a5c9dc448b7c035fc8fa798f2834cfafa6134e5 | [
"while True:\n yield c\npass",
"gna = GNA.LinearCongruentialGenerator(seed=seed)\nwhile True:\n u1 = gna.next()\n u2 = gna.next()\n Z = math.sqrt(-2 * math.log(u1))\n if Z1:\n Z *= math.cos(2 * math.pi * u2)\n else:\n Z *= math.sin(2 * math.pi * u2)\n yield (media + desvio_padra... | <|body_start_0|>
while True:
yield c
pass
<|end_body_0|>
<|body_start_1|>
gna = GNA.LinearCongruentialGenerator(seed=seed)
while True:
u1 = gna.next()
u2 = gna.next()
Z = math.sqrt(-2 * math.log(u1))
if Z1:
Z *=... | Classe responsável pela geração de variáveis aleatórias. | FGVA | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FGVA:
"""Classe responsável pela geração de variáveis aleatórias."""
def Constante(c):
"""Criador de um gerador de valores constante. @param c: valor constante a ser retornada pelo gerador. @return: um gerador de valores constantes"""
<|body_0|>
def Normal(media, desvio_... | stack_v2_sparse_classes_36k_train_032773 | 3,436 | no_license | [
{
"docstring": "Criador de um gerador de valores constante. @param c: valor constante a ser retornada pelo gerador. @return: um gerador de valores constantes",
"name": "Constante",
"signature": "def Constante(c)"
},
{
"docstring": "Criador de um gerador de valores seguindo uma distribuição norma... | 5 | stack_v2_sparse_classes_30k_train_005525 | Implement the Python class `FGVA` described below.
Class description:
Classe responsável pela geração de variáveis aleatórias.
Method signatures and docstrings:
- def Constante(c): Criador de um gerador de valores constante. @param c: valor constante a ser retornada pelo gerador. @return: um gerador de valores consta... | Implement the Python class `FGVA` described below.
Class description:
Classe responsável pela geração de variáveis aleatórias.
Method signatures and docstrings:
- def Constante(c): Criador de um gerador de valores constante. @param c: valor constante a ser retornada pelo gerador. @return: um gerador de valores consta... | f914f50ab02f222b13aa35ae2dc0be30ba309925 | <|skeleton|>
class FGVA:
"""Classe responsável pela geração de variáveis aleatórias."""
def Constante(c):
"""Criador de um gerador de valores constante. @param c: valor constante a ser retornada pelo gerador. @return: um gerador de valores constantes"""
<|body_0|>
def Normal(media, desvio_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FGVA:
"""Classe responsável pela geração de variáveis aleatórias."""
def Constante(c):
"""Criador de um gerador de valores constante. @param c: valor constante a ser retornada pelo gerador. @return: um gerador de valores constantes"""
while True:
yield c
pass
def ... | the_stack_v2_python_sparse | src/Simulador/FGVA.py | cesarecorrea94/MeS.py | train | 0 |
1169bf240529f94428de44cebaa6591999db49b8 | [
"super(DyEmb, self).__init__()\nself.fnames = fnames\nself.max_idxs = max_idxs\nself.embedding_size = embedding_size\nself.use_cuda = use_cuda\nself.embeddings = nn.ModuleList([Meta_Embedding(max_idx + 1, self.embedding_size) for max_idx in self.max_idxs.values()])",
"concat_embeddings = []\nfor i, key in enumera... | <|body_start_0|>
super(DyEmb, self).__init__()
self.fnames = fnames
self.max_idxs = max_idxs
self.embedding_size = embedding_size
self.use_cuda = use_cuda
self.embeddings = nn.ModuleList([Meta_Embedding(max_idx + 1, self.embedding_size) for max_idx in self.max_idxs.values... | DyEmb | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DyEmb:
def __init__(self, fnames, max_idxs, embedding_size=4, use_cuda=True):
"""fnames: feature names max_idxs: array of max_idx of each feature embedding_size: size of embedding dropout: prob for dropout, set None if no dropout method: 'avg' or 'sum' use_cuda: bool, True for gpu or Fal... | stack_v2_sparse_classes_36k_train_032774 | 9,497 | permissive | [
{
"docstring": "fnames: feature names max_idxs: array of max_idx of each feature embedding_size: size of embedding dropout: prob for dropout, set None if no dropout method: 'avg' or 'sum' use_cuda: bool, True for gpu or False for cpu",
"name": "__init__",
"signature": "def __init__(self, fnames, max_idx... | 2 | stack_v2_sparse_classes_30k_train_010176 | Implement the Python class `DyEmb` described below.
Class description:
Implement the DyEmb class.
Method signatures and docstrings:
- def __init__(self, fnames, max_idxs, embedding_size=4, use_cuda=True): fnames: feature names max_idxs: array of max_idx of each feature embedding_size: size of embedding dropout: prob ... | Implement the Python class `DyEmb` described below.
Class description:
Implement the DyEmb class.
Method signatures and docstrings:
- def __init__(self, fnames, max_idxs, embedding_size=4, use_cuda=True): fnames: feature names max_idxs: array of max_idx of each feature embedding_size: size of embedding dropout: prob ... | 2969ed6c740d04283aa54af4e2c267cb980c96fe | <|skeleton|>
class DyEmb:
def __init__(self, fnames, max_idxs, embedding_size=4, use_cuda=True):
"""fnames: feature names max_idxs: array of max_idx of each feature embedding_size: size of embedding dropout: prob for dropout, set None if no dropout method: 'avg' or 'sum' use_cuda: bool, True for gpu or Fal... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DyEmb:
def __init__(self, fnames, max_idxs, embedding_size=4, use_cuda=True):
"""fnames: feature names max_idxs: array of max_idx of each feature embedding_size: size of embedding dropout: prob for dropout, set None if no dropout method: 'avg' or 'sum' use_cuda: bool, True for gpu or False for cpu"""
... | the_stack_v2_python_sparse | Application/audience expansion/model.py | easezyc/deep-transfer-learning | train | 801 | |
c233744f76c41f9d82f1afcc9bce35d9a86f836b | [
"def deal_with_debate(debate, meeting_section=None):\n debate_section = orm.Section.objects.create(title=debate.title, parent=meeting_section, instance=debate.instance, level=0, lft=0, rght=0, tree_id=0)\n for speech in debate.speech_set.all():\n speech.section = debate_section\n speech.save()\n... | <|body_start_0|>
def deal_with_debate(debate, meeting_section=None):
debate_section = orm.Section.objects.create(title=debate.title, parent=meeting_section, instance=debate.instance, level=0, lft=0, rght=0, tree_id=0)
for speech in debate.speech_set.all():
speech.section ... | Migration | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
<|body_0|>
def backwards(self, orm):
"""Write your backwards methods here."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def deal_with_debate(debate, meeting_section=None)... | stack_v2_sparse_classes_36k_train_032775 | 14,216 | no_license | [
{
"docstring": "Write your forwards methods here.",
"name": "forwards",
"signature": "def forwards(self, orm)"
},
{
"docstring": "Write your backwards methods here.",
"name": "backwards",
"signature": "def backwards(self, orm)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017200 | Implement the Python class `Migration` described below.
Class description:
Implement the Migration class.
Method signatures and docstrings:
- def forwards(self, orm): Write your forwards methods here.
- def backwards(self, orm): Write your backwards methods here. | Implement the Python class `Migration` described below.
Class description:
Implement the Migration class.
Method signatures and docstrings:
- def forwards(self, orm): Write your forwards methods here.
- def backwards(self, orm): Write your backwards methods here.
<|skeleton|>
class Migration:
def forwards(self,... | ff5f41ba62f50060641b0d5955e2be96b559321b | <|skeleton|>
class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
<|body_0|>
def backwards(self, orm):
"""Write your backwards methods here."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
def deal_with_debate(debate, meeting_section=None):
debate_section = orm.Section.objects.create(title=debate.title, parent=meeting_section, instance=debate.instance, level=0, lft=0, rght=0, tree_id=0)
... | the_stack_v2_python_sparse | speeches/south_migrations/0024_create_sections_from_meetings_and_debates.py | KohoVolit/sayit.parldata.eu | train | 1 | |
f5de43e4ee5fb189bcbfceb7e487bd84451c45ec | [
"print('Нужно ввести метод для поиска нового локатора (id/xpath...) !!!')\nglobal method\nwhile True:\n for cmd in ['Quit - Закрыть и не добавлять данные', 'YES - Добавить данные']:\n print(' %s - %s' % (cmd[:1], cmd))\n cmd = input('Пожалуйста, введите команду (Q/Y) ').upper()[:1]\n if cmd == 'Q':... | <|body_start_0|>
print('Нужно ввести метод для поиска нового локатора (id/xpath...) !!!')
global method
while True:
for cmd in ['Quit - Закрыть и не добавлять данные', 'YES - Добавить данные']:
print(' %s - %s' % (cmd[:1], cmd))
cmd = input('Пожалуйста, в... | DataBaseInterface | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataBaseInterface:
def set_method(self, table_name: str, key: str):
"""Запись метода для поиска локатора в таблицу :param table_name: название таблицы :param key: ключ (название элемента) :rtype str :return: метод для поиска локатора"""
<|body_0|>
def set_value(self, table_n... | stack_v2_sparse_classes_36k_train_032776 | 2,667 | no_license | [
{
"docstring": "Запись метода для поиска локатора в таблицу :param table_name: название таблицы :param key: ключ (название элемента) :rtype str :return: метод для поиска локатора",
"name": "set_method",
"signature": "def set_method(self, table_name: str, key: str)"
},
{
"docstring": "Запись знач... | 2 | stack_v2_sparse_classes_30k_train_006811 | Implement the Python class `DataBaseInterface` described below.
Class description:
Implement the DataBaseInterface class.
Method signatures and docstrings:
- def set_method(self, table_name: str, key: str): Запись метода для поиска локатора в таблицу :param table_name: название таблицы :param key: ключ (название элем... | Implement the Python class `DataBaseInterface` described below.
Class description:
Implement the DataBaseInterface class.
Method signatures and docstrings:
- def set_method(self, table_name: str, key: str): Запись метода для поиска локатора в таблицу :param table_name: название таблицы :param key: ключ (название элем... | 3eabb10c2aff74c4808bd0476c2622c01e491350 | <|skeleton|>
class DataBaseInterface:
def set_method(self, table_name: str, key: str):
"""Запись метода для поиска локатора в таблицу :param table_name: название таблицы :param key: ключ (название элемента) :rtype str :return: метод для поиска локатора"""
<|body_0|>
def set_value(self, table_n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataBaseInterface:
def set_method(self, table_name: str, key: str):
"""Запись метода для поиска локатора в таблицу :param table_name: название таблицы :param key: ключ (название элемента) :rtype str :return: метод для поиска локатора"""
print('Нужно ввести метод для поиска нового локатора (id/... | the_stack_v2_python_sparse | mobileAutoTestsBasicFramework/model/database_model/database_interface.py | Yelisey/testsAppPy | train | 0 | |
9fa6c0d4f132f0be7c7556c0df79074321a0411d | [
"super(FastRCNN, self).__init__()\nself.classifier = classifier\nself.cls_layer = nn.Linear(4096, n_class)\nself.reg_layer = nn.Linear(4096, n_class * 4)\nnormal_init(self.cls_layer, mean=0, stddev=0.001)\nnormal_init(self.reg_layer, mean=0, stddev=0.01)\nself.n_class = n_class\nself.roi_size = roi_size\nself.spati... | <|body_start_0|>
super(FastRCNN, self).__init__()
self.classifier = classifier
self.cls_layer = nn.Linear(4096, n_class)
self.reg_layer = nn.Linear(4096, n_class * 4)
normal_init(self.cls_layer, mean=0, stddev=0.001)
normal_init(self.reg_layer, mean=0, stddev=0.01)
... | FastRCNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FastRCNN:
def __init__(self, n_class, roi_size, spatial_scale, classifier):
"""function description: 将rpn网络提供的roi"投射"到vgg16的featuremap上, 进行相应的切割并maxpooling(RoI maxpooling), 再将其展开从2d变为1d,投入两个fc层,然后再分别带入两个分支fc层，作为cls和reg的输出 :param n_class: 分类的总数 :param roi_size: RoIPooling2D之后的维度 :param sp... | stack_v2_sparse_classes_36k_train_032777 | 2,637 | no_license | [
{
"docstring": "function description: 将rpn网络提供的roi\"投射\"到vgg16的featuremap上, 进行相应的切割并maxpooling(RoI maxpooling), 再将其展开从2d变为1d,投入两个fc层,然后再分别带入两个分支fc层，作为cls和reg的输出 :param n_class: 分类的总数 :param roi_size: RoIPooling2D之后的维度 :param spatial_scale: roi(rpn推荐的区域-原图上的区域)投射在feature map后需要缩小的比例, 这个个人感觉应该对应感受野大小 :param class... | 2 | stack_v2_sparse_classes_30k_train_005455 | Implement the Python class `FastRCNN` described below.
Class description:
Implement the FastRCNN class.
Method signatures and docstrings:
- def __init__(self, n_class, roi_size, spatial_scale, classifier): function description: 将rpn网络提供的roi"投射"到vgg16的featuremap上, 进行相应的切割并maxpooling(RoI maxpooling), 再将其展开从2d变为1d,投入两个f... | Implement the Python class `FastRCNN` described below.
Class description:
Implement the FastRCNN class.
Method signatures and docstrings:
- def __init__(self, n_class, roi_size, spatial_scale, classifier): function description: 将rpn网络提供的roi"投射"到vgg16的featuremap上, 进行相应的切割并maxpooling(RoI maxpooling), 再将其展开从2d变为1d,投入两个f... | b4fb6ff7af6c9f906eabd836c6727ab7d9f18576 | <|skeleton|>
class FastRCNN:
def __init__(self, n_class, roi_size, spatial_scale, classifier):
"""function description: 将rpn网络提供的roi"投射"到vgg16的featuremap上, 进行相应的切割并maxpooling(RoI maxpooling), 再将其展开从2d变为1d,投入两个fc层,然后再分别带入两个分支fc层，作为cls和reg的输出 :param n_class: 分类的总数 :param roi_size: RoIPooling2D之后的维度 :param sp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FastRCNN:
def __init__(self, n_class, roi_size, spatial_scale, classifier):
"""function description: 将rpn网络提供的roi"投射"到vgg16的featuremap上, 进行相应的切割并maxpooling(RoI maxpooling), 再将其展开从2d变为1d,投入两个fc层,然后再分别带入两个分支fc层，作为cls和reg的输出 :param n_class: 分类的总数 :param roi_size: RoIPooling2D之后的维度 :param spatial_scale: r... | the_stack_v2_python_sparse | nets/fast_rcnn.py | xiguanlezz/Faster-RCNN | train | 13 | |
b5773deb1210f2b601be84ad429209722783a316 | [
"with self.Session() as session:\n if stream_id is not None:\n s = session.scalars(Stream.select(session.user_or_token).where(Stream.id == stream_id)).first()\n if s is None:\n return self.error(f'Could not retrieve stream with ID {stream_id}.')\n return self.success(data=s)\n ... | <|body_start_0|>
with self.Session() as session:
if stream_id is not None:
s = session.scalars(Stream.select(session.user_or_token).where(Stream.id == stream_id)).first()
if s is None:
return self.error(f'Could not retrieve stream with ID {stream_i... | StreamHandler | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StreamHandler:
def get(self, stream_id=None):
"""--- single: description: Retrieve a stream tags: - streams parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleStream 400: content: application/json: schema: ... | stack_v2_sparse_classes_36k_train_032778 | 8,804 | permissive | [
{
"docstring": "--- single: description: Retrieve a stream tags: - streams parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleStream 400: content: application/json: schema: Error multiple: description: Retrieve all streams tags: -... | 4 | null | Implement the Python class `StreamHandler` described below.
Class description:
Implement the StreamHandler class.
Method signatures and docstrings:
- def get(self, stream_id=None): --- single: description: Retrieve a stream tags: - streams parameters: - in: path name: filter_id required: true schema: type: integer re... | Implement the Python class `StreamHandler` described below.
Class description:
Implement the StreamHandler class.
Method signatures and docstrings:
- def get(self, stream_id=None): --- single: description: Retrieve a stream tags: - streams parameters: - in: path name: filter_id required: true schema: type: integer re... | 161d3532ba3ba059446addcdac58ca96f39e9636 | <|skeleton|>
class StreamHandler:
def get(self, stream_id=None):
"""--- single: description: Retrieve a stream tags: - streams parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleStream 400: content: application/json: schema: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StreamHandler:
def get(self, stream_id=None):
"""--- single: description: Retrieve a stream tags: - streams parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleStream 400: content: application/json: schema: Error multiple... | the_stack_v2_python_sparse | skyportal/handlers/api/stream.py | skyportal/skyportal | train | 80 | |
697041b720df1090f140541e32552ce907a3e02f | [
"A, B = (set([0]), set(graph[0]))\ni = 1\nwhile i < len(graph):\n if i in A or any((node in B for node in graph[i])):\n A.add(i)\n B.update(graph[i])\n else:\n B.add(i)\n A.update(graph[i])\n i += 1\n if A & B:\n return False\nreturn True",
"states = {}\nfor node in ... | <|body_start_0|>
A, B = (set([0]), set(graph[0]))
i = 1
while i < len(graph):
if i in A or any((node in B for node in graph[i])):
A.add(i)
B.update(graph[i])
else:
B.add(i)
A.update(graph[i])
i +=... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isBipartite_2(self, graph: List[List[int]]) -> bool:
"""将节点i和其连接点集graph[i]，依次添加到不同的两个集合，这两个集合不应该相交！ TODO: 解答错误"""
<|body_0|>
def isBipartite(self, graph: List[List[int]]) -> bool:
"""记录节点属于集合A还是集合B"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_032779 | 3,274 | no_license | [
{
"docstring": "将节点i和其连接点集graph[i]，依次添加到不同的两个集合，这两个集合不应该相交！ TODO: 解答错误",
"name": "isBipartite_2",
"signature": "def isBipartite_2(self, graph: List[List[int]]) -> bool"
},
{
"docstring": "记录节点属于集合A还是集合B",
"name": "isBipartite",
"signature": "def isBipartite(self, graph: List[List[int]]) ... | 2 | stack_v2_sparse_classes_30k_train_001727 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isBipartite_2(self, graph: List[List[int]]) -> bool: 将节点i和其连接点集graph[i]，依次添加到不同的两个集合，这两个集合不应该相交！ TODO: 解答错误
- def isBipartite(self, graph: List[List[int]]) -> bool: 记录节点属于集合A... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isBipartite_2(self, graph: List[List[int]]) -> bool: 将节点i和其连接点集graph[i]，依次添加到不同的两个集合，这两个集合不应该相交！ TODO: 解答错误
- def isBipartite(self, graph: List[List[int]]) -> bool: 记录节点属于集合A... | 4732fb80710a08a715c3e7080c394f5298b8326d | <|skeleton|>
class Solution:
def isBipartite_2(self, graph: List[List[int]]) -> bool:
"""将节点i和其连接点集graph[i]，依次添加到不同的两个集合，这两个集合不应该相交！ TODO: 解答错误"""
<|body_0|>
def isBipartite(self, graph: List[List[int]]) -> bool:
"""记录节点属于集合A还是集合B"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isBipartite_2(self, graph: List[List[int]]) -> bool:
"""将节点i和其连接点集graph[i]，依次添加到不同的两个集合，这两个集合不应该相交！ TODO: 解答错误"""
A, B = (set([0]), set(graph[0]))
i = 1
while i < len(graph):
if i in A or any((node in B for node in graph[i])):
A.add(i)
... | the_stack_v2_python_sparse | .leetcode/785.判断二分图.py | xiaoruijiang/algorithm | train | 0 | |
bd9567adb5d9eea689f47afbbf8733a5aeb6d267 | [
"self.end_time = end_time\nself.error_message = error_message\nself.execution_start_time_usecs = execution_start_time_usecs\nself.files_processed = files_processed\nself.map_done_time_usecs = map_done_time_usecs\nself.map_input_bytes = map_input_bytes\nself.mappers_spawned = mappers_spawned\nself.num_map_outputs = ... | <|body_start_0|>
self.end_time = end_time
self.error_message = error_message
self.execution_start_time_usecs = execution_start_time_usecs
self.files_processed = files_processed
self.map_done_time_usecs = map_done_time_usecs
self.map_input_bytes = map_input_bytes
s... | Implementation of the 'MapReduceInstance_RunInfo' model. TODO: type description here. Attributes: end_time (long|int): Time when map redcue job completed. error_message (string): If this run failed, then error message for failure. execution_start_time_usecs (long|int): Time (in usecs) when job was picked up for executi... | MapReduceInstance_RunInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MapReduceInstance_RunInfo:
"""Implementation of the 'MapReduceInstance_RunInfo' model. TODO: type description here. Attributes: end_time (long|int): Time when map redcue job completed. error_message (string): If this run failed, then error message for failure. execution_start_time_usecs (long|int... | stack_v2_sparse_classes_36k_train_032780 | 6,787 | permissive | [
{
"docstring": "Constructor for the MapReduceInstance_RunInfo class",
"name": "__init__",
"signature": "def __init__(self, end_time=None, error_message=None, execution_start_time_usecs=None, files_processed=None, map_done_time_usecs=None, map_input_bytes=None, mappers_spawned=None, num_map_outputs=None,... | 2 | stack_v2_sparse_classes_30k_train_003527 | Implement the Python class `MapReduceInstance_RunInfo` described below.
Class description:
Implementation of the 'MapReduceInstance_RunInfo' model. TODO: type description here. Attributes: end_time (long|int): Time when map redcue job completed. error_message (string): If this run failed, then error message for failur... | Implement the Python class `MapReduceInstance_RunInfo` described below.
Class description:
Implementation of the 'MapReduceInstance_RunInfo' model. TODO: type description here. Attributes: end_time (long|int): Time when map redcue job completed. error_message (string): If this run failed, then error message for failur... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class MapReduceInstance_RunInfo:
"""Implementation of the 'MapReduceInstance_RunInfo' model. TODO: type description here. Attributes: end_time (long|int): Time when map redcue job completed. error_message (string): If this run failed, then error message for failure. execution_start_time_usecs (long|int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MapReduceInstance_RunInfo:
"""Implementation of the 'MapReduceInstance_RunInfo' model. TODO: type description here. Attributes: end_time (long|int): Time when map redcue job completed. error_message (string): If this run failed, then error message for failure. execution_start_time_usecs (long|int): Time (in u... | the_stack_v2_python_sparse | cohesity_management_sdk/models/map_reduce_instance_run_info.py | cohesity/management-sdk-python | train | 24 |
57ce33e2220b93272686d53ce7fc3ad0fbab6886 | [
"self.config = ConfigUtil.ConfigUtil()\nself.config.loadConfigData()\nself.actuator = ActuatorData.ActuatorData()\nself.actuator.setName('Temperature Actuator Data')\nself.actuatorAdapter = MultiActuatorAdapter.MultiActuatorAdapter()\nself.smtpConnector = SmtpClientConnector.MyClass()",
"if type(sensor_data) != S... | <|body_start_0|>
self.config = ConfigUtil.ConfigUtil()
self.config.loadConfigData()
self.actuator = ActuatorData.ActuatorData()
self.actuator.setName('Temperature Actuator Data')
self.actuatorAdapter = MultiActuatorAdapter.MultiActuatorAdapter()
self.smtpConnector = SmtpC... | This class is responsible for Managing the SensorData instance This class reads a SensorData instance and then changes an ActuatorData instance as required, and then proceeds to Actuate using the ActuatorAdapter | SensorDataManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SensorDataManager:
"""This class is responsible for Managing the SensorData instance This class reads a SensorData instance and then changes an ActuatorData instance as required, and then proceeds to Actuate using the ActuatorAdapter"""
def __init__(self):
"""Constructor"""
<... | stack_v2_sparse_classes_36k_train_032781 | 3,774 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Function to handle and parse the data stored in an SensorData instance Takes a sensorData instance and the mail body string as input",
"name": "handleSensorData",
"signature": "def hand... | 3 | null | Implement the Python class `SensorDataManager` described below.
Class description:
This class is responsible for Managing the SensorData instance This class reads a SensorData instance and then changes an ActuatorData instance as required, and then proceeds to Actuate using the ActuatorAdapter
Method signatures and d... | Implement the Python class `SensorDataManager` described below.
Class description:
This class is responsible for Managing the SensorData instance This class reads a SensorData instance and then changes an ActuatorData instance as required, and then proceeds to Actuate using the ActuatorAdapter
Method signatures and d... | dfd5fd8c757cae8b1306ae3e4eb2cfc9bf124fee | <|skeleton|>
class SensorDataManager:
"""This class is responsible for Managing the SensorData instance This class reads a SensorData instance and then changes an ActuatorData instance as required, and then proceeds to Actuate using the ActuatorAdapter"""
def __init__(self):
"""Constructor"""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SensorDataManager:
"""This class is responsible for Managing the SensorData instance This class reads a SensorData instance and then changes an ActuatorData instance as required, and then proceeds to Actuate using the ActuatorAdapter"""
def __init__(self):
"""Constructor"""
self.config = ... | the_stack_v2_python_sparse | apps/labs/module04/SensorDataManager.py | mnk400/iot-device | train | 0 |
dca124a6c768faea689a05d8c1dffc3f670b8467 | [
"super(DecoderBlock, self).__init__()\nself.mha1 = MultiHeadAttention(dm, h)\nself.mha2 = MultiHeadAttention(dm, h)\nself.dense_hidden = tf.keras.layers.Dense(units=hidden, activation='relu')\nself.dense_output = tf.keras.layers.Dense(units=dm)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\ns... | <|body_start_0|>
super(DecoderBlock, self).__init__()
self.mha1 = MultiHeadAttention(dm, h)
self.mha2 = MultiHeadAttention(dm, h)
self.dense_hidden = tf.keras.layers.Dense(units=hidden, activation='relu')
self.dense_output = tf.keras.layers.Dense(units=dm)
self.layernorm1... | Class representation of a decoder block for a transformer | DecoderBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderBlock:
"""Class representation of a decoder block for a transformer"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""dm: Dimensionality of the model h: Number of heads hidden: Number of hidden units in the fully connected layer drop_rate: Dropout rate"""
<|body_... | stack_v2_sparse_classes_36k_train_032782 | 2,892 | no_license | [
{
"docstring": "dm: Dimensionality of the model h: Number of heads hidden: Number of hidden units in the fully connected layer drop_rate: Dropout rate",
"name": "__init__",
"signature": "def __init__(self, dm, h, hidden, drop_rate=0.1)"
},
{
"docstring": "x: tensor of shape (batch, target_seq_le... | 2 | stack_v2_sparse_classes_30k_train_004180 | Implement the Python class `DecoderBlock` described below.
Class description:
Class representation of a decoder block for a transformer
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): dm: Dimensionality of the model h: Number of heads hidden: Number of hidden units in the fully c... | Implement the Python class `DecoderBlock` described below.
Class description:
Class representation of a decoder block for a transformer
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): dm: Dimensionality of the model h: Number of heads hidden: Number of hidden units in the fully c... | 2757c8526290197d45a4de33cda71e686ddcbf1c | <|skeleton|>
class DecoderBlock:
"""Class representation of a decoder block for a transformer"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""dm: Dimensionality of the model h: Number of heads hidden: Number of hidden units in the fully connected layer drop_rate: Dropout rate"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecoderBlock:
"""Class representation of a decoder block for a transformer"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""dm: Dimensionality of the model h: Number of heads hidden: Number of hidden units in the fully connected layer drop_rate: Dropout rate"""
super(DecoderBlock, ... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/8-transformer_decoder_block.py | 95ktsmith/holbertonschool-machine_learning | train | 0 |
33f01f6a41f63f4a22c9c3457d71ed2d44853e5e | [
"super(InTriggerRegion, self).__init__(name)\nself.logger.debug('%s.__init__()' % self.__class__.__name__)\nself._actor = actor\nself._min_x = min_x\nself._max_x = max_x\nself._min_y = min_y\nself._max_y = max_y",
"new_status = py_trees.common.Status.RUNNING\nlocation = CarlaDataProvider.get_location(self._actor)... | <|body_start_0|>
super(InTriggerRegion, self).__init__(name)
self.logger.debug('%s.__init__()' % self.__class__.__name__)
self._actor = actor
self._min_x = min_x
self._max_x = max_x
self._min_y = min_y
self._max_y = max_y
<|end_body_0|>
<|body_start_1|>
n... | This class contains the trigger region (condition) of a scenario | InTriggerRegion | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InTriggerRegion:
"""This class contains the trigger region (condition) of a scenario"""
def __init__(self, actor, min_x, max_x, min_y, max_y, name='TriggerRegion'):
"""Setup trigger region (rectangle provided by [min_x,min_y] and [max_x,max_y]"""
<|body_0|>
def update(se... | stack_v2_sparse_classes_36k_train_032783 | 25,380 | permissive | [
{
"docstring": "Setup trigger region (rectangle provided by [min_x,min_y] and [max_x,max_y]",
"name": "__init__",
"signature": "def __init__(self, actor, min_x, max_x, min_y, max_y, name='TriggerRegion')"
},
{
"docstring": "Check if the _actor location is within trigger region",
"name": "upd... | 2 | stack_v2_sparse_classes_30k_train_006262 | Implement the Python class `InTriggerRegion` described below.
Class description:
This class contains the trigger region (condition) of a scenario
Method signatures and docstrings:
- def __init__(self, actor, min_x, max_x, min_y, max_y, name='TriggerRegion'): Setup trigger region (rectangle provided by [min_x,min_y] a... | Implement the Python class `InTriggerRegion` described below.
Class description:
This class contains the trigger region (condition) of a scenario
Method signatures and docstrings:
- def __init__(self, actor, min_x, max_x, min_y, max_y, name='TriggerRegion'): Setup trigger region (rectangle provided by [min_x,min_y] a... | 1d3e8339f8e60f7bdcaefeff49ec238b1746b047 | <|skeleton|>
class InTriggerRegion:
"""This class contains the trigger region (condition) of a scenario"""
def __init__(self, actor, min_x, max_x, min_y, max_y, name='TriggerRegion'):
"""Setup trigger region (rectangle provided by [min_x,min_y] and [max_x,max_y]"""
<|body_0|>
def update(se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InTriggerRegion:
"""This class contains the trigger region (condition) of a scenario"""
def __init__(self, actor, min_x, max_x, min_y, max_y, name='TriggerRegion'):
"""Setup trigger region (rectangle provided by [min_x,min_y] and [max_x,max_y]"""
super(InTriggerRegion, self).__init__(name... | the_stack_v2_python_sparse | srunner/scenariomanager/atomic_scenario_behavior.py | chauvinSimon/scenario_runner | train | 2 |
7effc7c8715224ecc8e03e5a3a3ba5c3d36b2db8 | [
"self.logger = logging.getLogger(__name__)\nself.username = username\nself.url = url\nself.automatic_login_url = urljoin(self.url, AUTOMATIC_LOGIN_POSTFIX)\nself.interactive_login_url = urljoin(self.url, INTERACTIVE_LOGIN_POSTFIX)\nif not interactive and (username is None or password is None):\n return\nif usern... | <|body_start_0|>
self.logger = logging.getLogger(__name__)
self.username = username
self.url = url
self.automatic_login_url = urljoin(self.url, AUTOMATIC_LOGIN_POSTFIX)
self.interactive_login_url = urljoin(self.url, INTERACTIVE_LOGIN_POSTFIX)
if not interactive and (usern... | HTTP Resolwe Authentication for Request object. :param str username: user's email :param str password: user's password :param str url: Resolwe server address :param str cookies: user's sessionid and csrftoken cookies | ResAuth | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResAuth:
"""HTTP Resolwe Authentication for Request object. :param str username: user's email :param str password: user's password :param str url: Resolwe server address :param str cookies: user's sessionid and csrftoken cookies"""
def __init__(self, username: Optional[str]=None, password: O... | stack_v2_sparse_classes_36k_train_032784 | 20,535 | permissive | [
{
"docstring": "Authenticate user on Resolwe server.",
"name": "__init__",
"signature": "def __init__(self, username: Optional[str]=None, password: Optional[str]=None, url: str=DEFAULT_URL, interactive: bool=False)"
},
{
"docstring": "Attempt to perform automatic SAML login. :returns: authentica... | 4 | stack_v2_sparse_classes_30k_train_006750 | Implement the Python class `ResAuth` described below.
Class description:
HTTP Resolwe Authentication for Request object. :param str username: user's email :param str password: user's password :param str url: Resolwe server address :param str cookies: user's sessionid and csrftoken cookies
Method signatures and docstr... | Implement the Python class `ResAuth` described below.
Class description:
HTTP Resolwe Authentication for Request object. :param str username: user's email :param str password: user's password :param str url: Resolwe server address :param str cookies: user's sessionid and csrftoken cookies
Method signatures and docstr... | eecd829f3a4bd2868493486f91f198ae0f449830 | <|skeleton|>
class ResAuth:
"""HTTP Resolwe Authentication for Request object. :param str username: user's email :param str password: user's password :param str url: Resolwe server address :param str cookies: user's sessionid and csrftoken cookies"""
def __init__(self, username: Optional[str]=None, password: O... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResAuth:
"""HTTP Resolwe Authentication for Request object. :param str username: user's email :param str password: user's password :param str url: Resolwe server address :param str cookies: user's sessionid and csrftoken cookies"""
def __init__(self, username: Optional[str]=None, password: Optional[str]=... | the_stack_v2_python_sparse | src/resdk/resolwe.py | genialis/resolwe-bio-py | train | 4 |
a66d7e55d9d8a0d1ef4be039653a7afbe3d3ed21 | [
"self.relaxed = relaxed\nself.structType = structType\nself.interstitType = interstitType\nself.cellDims = cellDims\nself.runCalcs = runCalcs",
"cellStr = '_'.join([str(x) for x in self.cellDims])\noutObj = refDataStruct.getSelfInterstitialPlaneWaveStruct(self.structType, self.interstitType, self.relaxed, cellStr... | <|body_start_0|>
self.relaxed = relaxed
self.structType = structType
self.interstitType = interstitType
self.cellDims = cellDims
self.runCalcs = runCalcs
<|end_body_0|>
<|body_start_1|>
cellStr = '_'.join([str(x) for x in self.cellDims])
outObj = refDataStruct.ge... | Defines a type of interstitial independent of element and method used. | InterstitialType | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InterstitialType:
"""Defines a type of interstitial independent of element and method used."""
def __init__(self, relaxed, structType, interstitType, cellDims, runCalcs):
"""Description of function Args: relaxed: str, unrelaxed/relaxed_constant_p/relaxed_constant_v structType: str, t... | stack_v2_sparse_classes_36k_train_032785 | 5,576 | no_license | [
{
"docstring": "Description of function Args: relaxed: str, unrelaxed/relaxed_constant_p/relaxed_constant_v structType: str, the base crystal type (hcp/bcc/fcc) interstitType: str describing the deformation (e.g. octahedral) cellDims: iter(3 element), number of unit cells in each direction runCalcs: Bool, Wheth... | 2 | null | Implement the Python class `InterstitialType` described below.
Class description:
Defines a type of interstitial independent of element and method used.
Method signatures and docstrings:
- def __init__(self, relaxed, structType, interstitType, cellDims, runCalcs): Description of function Args: relaxed: str, unrelaxed... | Implement the Python class `InterstitialType` described below.
Class description:
Defines a type of interstitial independent of element and method used.
Method signatures and docstrings:
- def __init__(self, relaxed, structType, interstitType, cellDims, runCalcs): Description of function Args: relaxed: str, unrelaxed... | 8469a51c1580b923ca35a56811e92c065b424d68 | <|skeleton|>
class InterstitialType:
"""Defines a type of interstitial independent of element and method used."""
def __init__(self, relaxed, structType, interstitType, cellDims, runCalcs):
"""Description of function Args: relaxed: str, unrelaxed/relaxed_constant_p/relaxed_constant_v structType: str, t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InterstitialType:
"""Defines a type of interstitial independent of element and method used."""
def __init__(self, relaxed, structType, interstitType, cellDims, runCalcs):
"""Description of function Args: relaxed: str, unrelaxed/relaxed_constant_p/relaxed_constant_v structType: str, the base cryst... | the_stack_v2_python_sparse | gen_basis_helpers/job_utils/interstit_helpers.py | RFogarty1/plato_gen_basis_helpers | train | 3 |
7353c6d9d00e879cdbfdee5e340d9f3b6c4bacda | [
"if self.power == 1 and (not self.is_conjugated()) and self.is_transposed():\n return PowerMatrixGate.T(self, inplace=inplace)\nelse:\n return PowerMatrixGate.conj(self, inplace=inplace)",
"if self.power == 1 and self.is_conjugated() and (not self.is_transposed()):\n return PowerMatrixGate.conj(self, inp... | <|body_start_0|>
if self.power == 1 and (not self.is_conjugated()) and self.is_transposed():
return PowerMatrixGate.T(self, inplace=inplace)
else:
return PowerMatrixGate.conj(self, inplace=inplace)
<|end_body_0|>
<|body_start_1|>
if self.power == 1 and self.is_conjugated... | SelfAdjointUnitaryGate | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAdjointUnitaryGate:
def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate:
"""Apply conjugation to self.matrix()."""
<|body_0|>
def T(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate:
"""Apply transposition to self.matrix()."""
<|body_1|... | stack_v2_sparse_classes_36k_train_032786 | 31,759 | permissive | [
{
"docstring": "Apply conjugation to self.matrix().",
"name": "conj",
"signature": "def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate"
},
{
"docstring": "Apply transposition to self.matrix().",
"name": "T",
"signature": "def T(self, *, inplace: bool=False) -> SelfAdjointUn... | 3 | stack_v2_sparse_classes_30k_train_010938 | Implement the Python class `SelfAdjointUnitaryGate` described below.
Class description:
Implement the SelfAdjointUnitaryGate class.
Method signatures and docstrings:
- def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate: Apply conjugation to self.matrix().
- def T(self, *, inplace: bool=False) -> SelfAdj... | Implement the Python class `SelfAdjointUnitaryGate` described below.
Class description:
Implement the SelfAdjointUnitaryGate class.
Method signatures and docstrings:
- def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate: Apply conjugation to self.matrix().
- def T(self, *, inplace: bool=False) -> SelfAdj... | 42f2998a059e5615dce6ccdbf7ae6dc4954bbce9 | <|skeleton|>
class SelfAdjointUnitaryGate:
def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate:
"""Apply conjugation to self.matrix()."""
<|body_0|>
def T(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate:
"""Apply transposition to self.matrix()."""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelfAdjointUnitaryGate:
def conj(self, *, inplace: bool=False) -> SelfAdjointUnitaryGate:
"""Apply conjugation to self.matrix()."""
if self.power == 1 and (not self.is_conjugated()) and self.is_transposed():
return PowerMatrixGate.T(self, inplace=inplace)
else:
... | the_stack_v2_python_sparse | hybridq/gate/property.py | jsmarsha11/hybridq-nasa | train | 0 | |
4056743ea5fa42f82439e8c8c0ab8eb0d8410d83 | [
"logger.debug('Get repo: %s/%s permissions for team %s', namespace_name, repository_name, teamname)\nrole = model.get_repo_role_for_team(teamname, namespace_name, repository_name)\nreturn role.to_dict()",
"new_permission = request.get_json()\nlogger.debug('Setting permission to: %s for team %s', new_permission['r... | <|body_start_0|>
logger.debug('Get repo: %s/%s permissions for team %s', namespace_name, repository_name, teamname)
role = model.get_repo_role_for_team(teamname, namespace_name, repository_name)
return role.to_dict()
<|end_body_0|>
<|body_start_1|>
new_permission = request.get_json()
... | Resource for managing individual team permissions. | RepositoryTeamPermission | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RepositoryTeamPermission:
"""Resource for managing individual team permissions."""
def get(self, namespace_name, repository_name, teamname):
"""Fetch the permission for the specified team."""
<|body_0|>
def put(self, namespace_name, repository_name, teamname):
""... | stack_v2_sparse_classes_36k_train_032787 | 8,862 | permissive | [
{
"docstring": "Fetch the permission for the specified team.",
"name": "get",
"signature": "def get(self, namespace_name, repository_name, teamname)"
},
{
"docstring": "Update the existing team permission.",
"name": "put",
"signature": "def put(self, namespace_name, repository_name, team... | 3 | stack_v2_sparse_classes_30k_train_013800 | Implement the Python class `RepositoryTeamPermission` described below.
Class description:
Resource for managing individual team permissions.
Method signatures and docstrings:
- def get(self, namespace_name, repository_name, teamname): Fetch the permission for the specified team.
- def put(self, namespace_name, reposi... | Implement the Python class `RepositoryTeamPermission` described below.
Class description:
Resource for managing individual team permissions.
Method signatures and docstrings:
- def get(self, namespace_name, repository_name, teamname): Fetch the permission for the specified team.
- def put(self, namespace_name, reposi... | e400a0c22c5f89dd35d571654b13d262b1f6e3b3 | <|skeleton|>
class RepositoryTeamPermission:
"""Resource for managing individual team permissions."""
def get(self, namespace_name, repository_name, teamname):
"""Fetch the permission for the specified team."""
<|body_0|>
def put(self, namespace_name, repository_name, teamname):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RepositoryTeamPermission:
"""Resource for managing individual team permissions."""
def get(self, namespace_name, repository_name, teamname):
"""Fetch the permission for the specified team."""
logger.debug('Get repo: %s/%s permissions for team %s', namespace_name, repository_name, teamname... | the_stack_v2_python_sparse | endpoints/api/permission.py | quay/quay | train | 2,363 |
c62b12a839f4f1e3fd0300a39c350181e8f54eaf | [
"parser = VisParser()\ntree = parser.parse(vis_expr)\nsecret_tree = SecretVisTree(tree.root, vis_expr, secret=secret)\nsecret_tree.compute_shares()\nSecretVisTreeEncryptor._encrypt_secret_shares(secret_tree.root, key_container, leaf_class)\nreturn secret_tree.print_shares(encrypted=True)",
"if node.type == NodeTy... | <|body_start_0|>
parser = VisParser()
tree = parser.parse(vis_expr)
secret_tree = SecretVisTree(tree.root, vis_expr, secret=secret)
secret_tree.compute_shares()
SecretVisTreeEncryptor._encrypt_secret_shares(secret_tree.root, key_container, leaf_class)
return secret_tree.p... | Logic for dealing with secret sharing according to visibility labels, this includes encrypting and decrypting shares: To encrypt: Build it from an existing visibility tree with a chosen secret to share. Then it is possible to call encrypt on the visibility tree to encrypt the shares under corresponding attributes. This... | SecretVisTreeEncryptor | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecretVisTreeEncryptor:
"""Logic for dealing with secret sharing according to visibility labels, this includes encrypting and decrypting shares: To encrypt: Build it from an existing visibility tree with a chosen secret to share. Then it is possible to call encrypt on the visibility tree to encry... | stack_v2_sparse_classes_36k_train_032788 | 24,145 | permissive | [
{
"docstring": "Arguments: vis_expr - (string) vis_expr to be parsed and shares created secret - (bytestring) the secret to be shared key_container - (Keytor) key_id for the particular algorithm and key_object to look up keys. Throws PKILookupError if the algorithm or attribute is not present for that particula... | 4 | null | Implement the Python class `SecretVisTreeEncryptor` described below.
Class description:
Logic for dealing with secret sharing according to visibility labels, this includes encrypting and decrypting shares: To encrypt: Build it from an existing visibility tree with a chosen secret to share. Then it is possible to call ... | Implement the Python class `SecretVisTreeEncryptor` described below.
Class description:
Logic for dealing with secret sharing according to visibility labels, this includes encrypting and decrypting shares: To encrypt: Build it from an existing visibility tree with a chosen secret to share. Then it is possible to call ... | eb61250886e51647bd1edb6d8f4fa7f83eb0bc81 | <|skeleton|>
class SecretVisTreeEncryptor:
"""Logic for dealing with secret sharing according to visibility labels, this includes encrypting and decrypting shares: To encrypt: Build it from an existing visibility tree with a chosen secret to share. Then it is possible to call encrypt on the visibility tree to encry... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SecretVisTreeEncryptor:
"""Logic for dealing with secret sharing according to visibility labels, this includes encrypting and decrypting shares: To encrypt: Build it from an existing visibility tree with a chosen secret to share. Then it is possible to call encrypt on the visibility tree to encrypt the shares... | the_stack_v2_python_sparse | pace/encryption/visibility/secret_vis_tree.py | Global-localhost/PACE-python | train | 0 |
8ac9f8f9d927ebde91f4997c243e4d86a77c005f | [
"sex_string = self.sex\nif sex_string == '1':\n return 'male'\nelif sex_string == '2':\n return 'female'\nelse:\n return 'unknown'",
"phenotype = self.phenotype\nif phenotype == '1':\n return False\nelif phenotype == '2':\n return True\nelse:\n return False"
] | <|body_start_0|>
sex_string = self.sex
if sex_string == '1':
return 'male'
elif sex_string == '2':
return 'female'
else:
return 'unknown'
<|end_body_0|>
<|body_start_1|>
phenotype = self.phenotype
if phenotype == '1':
retur... | PedigreeHumanMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PedigreeHumanMixin:
def sex_human(self):
"""Return a human readable string for the sex."""
<|body_0|>
def is_affected(self):
"""Boolean for telling if the sample is affected."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sex_string = self.sex
... | stack_v2_sparse_classes_36k_train_032789 | 632 | permissive | [
{
"docstring": "Return a human readable string for the sex.",
"name": "sex_human",
"signature": "def sex_human(self)"
},
{
"docstring": "Boolean for telling if the sample is affected.",
"name": "is_affected",
"signature": "def is_affected(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016491 | Implement the Python class `PedigreeHumanMixin` described below.
Class description:
Implement the PedigreeHumanMixin class.
Method signatures and docstrings:
- def sex_human(self): Return a human readable string for the sex.
- def is_affected(self): Boolean for telling if the sample is affected. | Implement the Python class `PedigreeHumanMixin` described below.
Class description:
Implement the PedigreeHumanMixin class.
Method signatures and docstrings:
- def sex_human(self): Return a human readable string for the sex.
- def is_affected(self): Boolean for telling if the sample is affected.
<|skeleton|>
class P... | 20f2521306492722fc035b5db18927578f1eae4a | <|skeleton|>
class PedigreeHumanMixin:
def sex_human(self):
"""Return a human readable string for the sex."""
<|body_0|>
def is_affected(self):
"""Boolean for telling if the sample is affected."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PedigreeHumanMixin:
def sex_human(self):
"""Return a human readable string for the sex."""
sex_string = self.sex
if sex_string == '1':
return 'male'
elif sex_string == '2':
return 'female'
else:
return 'unknown'
def is_affected(s... | the_stack_v2_python_sparse | puzzle/models/mixins.py | J35P312/PuzzleWin | train | 1 | |
cb9c86f5e3f00ad8afaa3ec6519bd594a10e3fae | [
"variation_id = variation['_id']\nidentifier = valid_result.identifier\ntoken_type = valid_result.classification_token.token_type\ntoken_type_l = token_type.lower()\nvrs_ref_allele_seq = None\nif 'uncertain' in token_type_l:\n warnings = ['Ambiguous regions cannot be normalized']\nelif 'range' not in token_type_... | <|body_start_0|>
variation_id = variation['_id']
identifier = valid_result.identifier
token_type = valid_result.classification_token.token_type
token_type_l = token_type.lower()
vrs_ref_allele_seq = None
if 'uncertain' in token_type_l:
warnings = ['Ambiguous r... | Class for represnting VRSATILE objects | ToVRSATILE | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ToVRSATILE:
"""Class for represnting VRSATILE objects"""
def get_variation_descriptor(self, label: str, variation: Dict, valid_result: ValidationResult, _id: str, warnings: List, gene: Optional[str]=None) -> Tuple[VariationDescriptor, List]:
"""Return variation descriptor and warning... | stack_v2_sparse_classes_36k_train_032790 | 3,637 | permissive | [
{
"docstring": "Return variation descriptor and warnings :param str label: Initial input query :param Dict variation: VRS variation object :param ValidationResult valid_result: Valid result for query :param str _id: _id field for variation descriptor :param List warnings: List of warnings :param Optional[str] g... | 2 | stack_v2_sparse_classes_30k_train_015376 | Implement the Python class `ToVRSATILE` described below.
Class description:
Class for represnting VRSATILE objects
Method signatures and docstrings:
- def get_variation_descriptor(self, label: str, variation: Dict, valid_result: ValidationResult, _id: str, warnings: List, gene: Optional[str]=None) -> Tuple[VariationD... | Implement the Python class `ToVRSATILE` described below.
Class description:
Class for represnting VRSATILE objects
Method signatures and docstrings:
- def get_variation_descriptor(self, label: str, variation: Dict, valid_result: ValidationResult, _id: str, warnings: List, gene: Optional[str]=None) -> Tuple[VariationD... | 4614e6dd0b3b5612d48f1e69be4e1476977aafba | <|skeleton|>
class ToVRSATILE:
"""Class for represnting VRSATILE objects"""
def get_variation_descriptor(self, label: str, variation: Dict, valid_result: ValidationResult, _id: str, warnings: List, gene: Optional[str]=None) -> Tuple[VariationDescriptor, List]:
"""Return variation descriptor and warning... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ToVRSATILE:
"""Class for represnting VRSATILE objects"""
def get_variation_descriptor(self, label: str, variation: Dict, valid_result: ValidationResult, _id: str, warnings: List, gene: Optional[str]=None) -> Tuple[VariationDescriptor, List]:
"""Return variation descriptor and warnings :param str ... | the_stack_v2_python_sparse | variation/to_vrsatile.py | cancervariants/variation-normalization | train | 4 |
d6362758649634a60deb35074ced6840a9586ab6 | [
"super().__init__(**kwargs)\nself.options = Options()\nself.options.add_experimental_option('prefs', DOWNLOAD_PREFERENCES)\nself.options.add_argument(HEADLESS_OPTIONS['headless'])\nself.options.add_argument(HEADLESS_OPTIONS['window_size'])\nself.driver = webdriver.Chrome(desired_capabilities=BINARY_LOCATION, chrome... | <|body_start_0|>
super().__init__(**kwargs)
self.options = Options()
self.options.add_experimental_option('prefs', DOWNLOAD_PREFERENCES)
self.options.add_argument(HEADLESS_OPTIONS['headless'])
self.options.add_argument(HEADLESS_OPTIONS['window_size'])
self.driver = webdri... | DspAdvisorKhoj | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DspAdvisorKhoj:
def __init__(self, **kwargs):
"""This constructor sets up the required settings for the Headless Selenium Chrome browser. :param kwargs: Keyword arguments"""
<|body_0|>
def parse(self, response, **kwargs):
"""This function will loop through the Dictio... | stack_v2_sparse_classes_36k_train_032791 | 3,665 | no_license | [
{
"docstring": "This constructor sets up the required settings for the Headless Selenium Chrome browser. :param kwargs: Keyword arguments",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "This function will loop through the Dictionary and gets the Response from... | 2 | stack_v2_sparse_classes_30k_train_008194 | Implement the Python class `DspAdvisorKhoj` described below.
Class description:
Implement the DspAdvisorKhoj class.
Method signatures and docstrings:
- def __init__(self, **kwargs): This constructor sets up the required settings for the Headless Selenium Chrome browser. :param kwargs: Keyword arguments
- def parse(se... | Implement the Python class `DspAdvisorKhoj` described below.
Class description:
Implement the DspAdvisorKhoj class.
Method signatures and docstrings:
- def __init__(self, **kwargs): This constructor sets up the required settings for the Headless Selenium Chrome browser. :param kwargs: Keyword arguments
- def parse(se... | 946e1c35b785bfc3ea31d5903e021d4bc99fe302 | <|skeleton|>
class DspAdvisorKhoj:
def __init__(self, **kwargs):
"""This constructor sets up the required settings for the Headless Selenium Chrome browser. :param kwargs: Keyword arguments"""
<|body_0|>
def parse(self, response, **kwargs):
"""This function will loop through the Dictio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DspAdvisorKhoj:
def __init__(self, **kwargs):
"""This constructor sets up the required settings for the Headless Selenium Chrome browser. :param kwargs: Keyword arguments"""
super().__init__(**kwargs)
self.options = Options()
self.options.add_experimental_option('prefs', DOWNLO... | the_stack_v2_python_sparse | FundRatingAMCFiles/fund_rating_file_extraction/fund_rating_file_extraction/spiders/dsp.py | pavithra-ft/ft-automation | train | 0 | |
25becb4e524fe382bd8575e62ff27f91f71b5e6f | [
"Frame.__init__(self)\nself.master.title('Blackjack')\nself.grid()\nself._hitButton = Button(self, text='Hit', command=self._hit)\nself._hitButton.grid(row=0, column=0)\nself._passButton = Button(self, text='Pass', command=self._pass)\nself._passButton.grid(row=0, column=1)\nself._newGameButton = Button(self, text=... | <|body_start_0|>
Frame.__init__(self)
self.master.title('Blackjack')
self.grid()
self._hitButton = Button(self, text='Hit', command=self._hit)
self._hitButton.grid(row=0, column=0)
self._passButton = Button(self, text='Pass', command=self._pass)
self._passButton.g... | BlackjackGUI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BlackjackGUI:
def __init__(self):
"""Sets up the window and widgets and instantiates the data model."""
<|body_0|>
def _newGame(self):
"""Instantiates the model and refreshes the GUI."""
<|body_1|>
def _hit(self):
"""Hits the player in the data m... | stack_v2_sparse_classes_36k_train_032792 | 4,167 | no_license | [
{
"docstring": "Sets up the window and widgets and instantiates the data model.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Instantiates the model and refreshes the GUI.",
"name": "_newGame",
"signature": "def _newGame(self)"
},
{
"docstring": "Hits... | 4 | stack_v2_sparse_classes_30k_train_001513 | Implement the Python class `BlackjackGUI` described below.
Class description:
Implement the BlackjackGUI class.
Method signatures and docstrings:
- def __init__(self): Sets up the window and widgets and instantiates the data model.
- def _newGame(self): Instantiates the model and refreshes the GUI.
- def _hit(self): ... | Implement the Python class `BlackjackGUI` described below.
Class description:
Implement the BlackjackGUI class.
Method signatures and docstrings:
- def __init__(self): Sets up the window and widgets and instantiates the data model.
- def _newGame(self): Instantiates the model and refreshes the GUI.
- def _hit(self): ... | a955c48d3c7209ed61c08f2e950da1967d730c1d | <|skeleton|>
class BlackjackGUI:
def __init__(self):
"""Sets up the window and widgets and instantiates the data model."""
<|body_0|>
def _newGame(self):
"""Instantiates the model and refreshes the GUI."""
<|body_1|>
def _hit(self):
"""Hits the player in the data m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BlackjackGUI:
def __init__(self):
"""Sets up the window and widgets and instantiates the data model."""
Frame.__init__(self)
self.master.title('Blackjack')
self.grid()
self._hitButton = Button(self, text='Hit', command=self._hit)
self._hitButton.grid(row=0, colu... | the_stack_v2_python_sparse | WA170 - Programming with Python/WA170_exercise_solutions/9781111822705_Solutions_ch09/Ch_09_Projects/9.4/blackjackgui.py | janesferr/WADD-Courses | train | 3 | |
d0c44c99119ac2e02260ff2f0b0d23a3c6d45be4 | [
"super().__init__()\nself.temperature = np.sqrt(input_channels)\nself.key_projection = nn.Linear(input_channels, input_channels, bias=False)\nself.value_projection = nn.Linear(input_channels, input_channels, bias=False)\nnn.init.xavier_normal_(self.key_projection.weight)\nnn.init.xavier_normal_(self.value_projectio... | <|body_start_0|>
super().__init__()
self.temperature = np.sqrt(input_channels)
self.key_projection = nn.Linear(input_channels, input_channels, bias=False)
self.value_projection = nn.Linear(input_channels, input_channels, bias=False)
nn.init.xavier_normal_(self.key_projection.weig... | The co-attention network for MHCADDI model. | CoAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoAttention:
"""The co-attention network for MHCADDI model."""
def __init__(self, input_channels: int, output_channels: int, dropout: float=0.1):
"""Instantiate the co-attention network. :param input_channels: The number of atom features. :param output_channels: The number of output ... | stack_v2_sparse_classes_36k_train_032793 | 25,672 | no_license | [
{
"docstring": "Instantiate the co-attention network. :param input_channels: The number of atom features. :param output_channels: The number of output features. :param dropout: Dropout probability.",
"name": "__init__",
"signature": "def __init__(self, input_channels: int, output_channels: int, dropout:... | 3 | stack_v2_sparse_classes_30k_train_012051 | Implement the Python class `CoAttention` described below.
Class description:
The co-attention network for MHCADDI model.
Method signatures and docstrings:
- def __init__(self, input_channels: int, output_channels: int, dropout: float=0.1): Instantiate the co-attention network. :param input_channels: The number of ato... | Implement the Python class `CoAttention` described below.
Class description:
The co-attention network for MHCADDI model.
Method signatures and docstrings:
- def __init__(self, input_channels: int, output_channels: int, dropout: float=0.1): Instantiate the co-attention network. :param input_channels: The number of ato... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class CoAttention:
"""The co-attention network for MHCADDI model."""
def __init__(self, input_channels: int, output_channels: int, dropout: float=0.1):
"""Instantiate the co-attention network. :param input_channels: The number of atom features. :param output_channels: The number of output ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoAttention:
"""The co-attention network for MHCADDI model."""
def __init__(self, input_channels: int, output_channels: int, dropout: float=0.1):
"""Instantiate the co-attention network. :param input_channels: The number of atom features. :param output_channels: The number of output features. :pa... | the_stack_v2_python_sparse | generated/test_AstraZeneca_chemicalx.py | jansel/pytorch-jit-paritybench | train | 35 |
7d00943a696010b12dadccb1b2ba06c27fda9849 | [
"self.a = 6378137\nself.b = 6356752.3142\nself.f = 0.00335281067183099\nself.ecc = 0.08181919092890633\nself.e2 = 0.006694380004260828\nself.secEcc = 0.08209443803685426\nself.secEccSqr = 0.006739496756586904\nself.mu = 398600441800000.0\nself.omega = 7.292115e-05\nself.J2 = 0.001082629989\nself.J3 = -2.53881e-06\n... | <|body_start_0|>
self.a = 6378137
self.b = 6356752.3142
self.f = 0.00335281067183099
self.ecc = 0.08181919092890633
self.e2 = 0.006694380004260828
self.secEcc = 0.08209443803685426
self.secEccSqr = 0.006739496756586904
self.mu = 398600441800000.0
s... | Geodetic and related coordinate transforms | Geodesy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Geodesy:
"""Geodetic and related coordinate transforms"""
def __init__(self):
"""WGS-84 constants"""
<|body_0|>
def geodetic2ECEF(self, latitude: float, longitude: float, altitude: float) -> vector:
"""@ rc : float"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_032794 | 2,460 | permissive | [
{
"docstring": "WGS-84 constants",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "@ rc : float",
"name": "geodetic2ECEF",
"signature": "def geodetic2ECEF(self, latitude: float, longitude: float, altitude: float) -> vector"
}
] | 2 | stack_v2_sparse_classes_30k_train_010965 | Implement the Python class `Geodesy` described below.
Class description:
Geodetic and related coordinate transforms
Method signatures and docstrings:
- def __init__(self): WGS-84 constants
- def geodetic2ECEF(self, latitude: float, longitude: float, altitude: float) -> vector: @ rc : float | Implement the Python class `Geodesy` described below.
Class description:
Geodetic and related coordinate transforms
Method signatures and docstrings:
- def __init__(self): WGS-84 constants
- def geodetic2ECEF(self, latitude: float, longitude: float, altitude: float) -> vector: @ rc : float
<|skeleton|>
class Geodesy... | f5713f9ed9a24c1382875d8ebdec00100f39e3a5 | <|skeleton|>
class Geodesy:
"""Geodetic and related coordinate transforms"""
def __init__(self):
"""WGS-84 constants"""
<|body_0|>
def geodetic2ECEF(self, latitude: float, longitude: float, altitude: float) -> vector:
"""@ rc : float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Geodesy:
"""Geodetic and related coordinate transforms"""
def __init__(self):
"""WGS-84 constants"""
self.a = 6378137
self.b = 6356752.3142
self.f = 0.00335281067183099
self.ecc = 0.08181919092890633
self.e2 = 0.006694380004260828
self.secEcc = 0.08... | the_stack_v2_python_sparse | Python/src/polynomialfiltering/Geodesy.py | lintondf/MorrisonPolynomialFiltering | train | 0 |
a0cf17b65302483f6916874da90581afc6713806 | [
"self.init_config(app)\nif app.config['SENTRY_DSN'] is None:\n return\nself.install_handler(app)\napp.extensions['invenio-logging-sentry'] = self",
"for k in dir(config):\n if k.startswith('LOGGING_SENTRY') or k.startswith('SENTRY_DSN'):\n app.config.setdefault(k, getattr(config, k))",
"from raven.... | <|body_start_0|>
self.init_config(app)
if app.config['SENTRY_DSN'] is None:
return
self.install_handler(app)
app.extensions['invenio-logging-sentry'] = self
<|end_body_0|>
<|body_start_1|>
for k in dir(config):
if k.startswith('LOGGING_SENTRY') or k.start... | Invenio-Logging extension for Sentry. | InvenioLoggingSentry | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InvenioLoggingSentry:
"""Invenio-Logging extension for Sentry."""
def init_app(self, app):
"""Flask application initialization."""
<|body_0|>
def init_config(self, app):
"""Initialize configuration."""
<|body_1|>
def install_handler(self, app):
... | stack_v2_sparse_classes_36k_train_032795 | 3,539 | no_license | [
{
"docstring": "Flask application initialization.",
"name": "init_app",
"signature": "def init_app(self, app)"
},
{
"docstring": "Initialize configuration.",
"name": "init_config",
"signature": "def init_config(self, app)"
},
{
"docstring": "Install log handler.",
"name": "in... | 3 | null | Implement the Python class `InvenioLoggingSentry` described below.
Class description:
Invenio-Logging extension for Sentry.
Method signatures and docstrings:
- def init_app(self, app): Flask application initialization.
- def init_config(self, app): Initialize configuration.
- def install_handler(self, app): Install l... | Implement the Python class `InvenioLoggingSentry` described below.
Class description:
Invenio-Logging extension for Sentry.
Method signatures and docstrings:
- def init_app(self, app): Flask application initialization.
- def init_config(self, app): Initialize configuration.
- def install_handler(self, app): Install l... | 54eb34c7e1594cc50a5347ba93e12a991ba8b7f3 | <|skeleton|>
class InvenioLoggingSentry:
"""Invenio-Logging extension for Sentry."""
def init_app(self, app):
"""Flask application initialization."""
<|body_0|>
def init_config(self, app):
"""Initialize configuration."""
<|body_1|>
def install_handler(self, app):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InvenioLoggingSentry:
"""Invenio-Logging extension for Sentry."""
def init_app(self, app):
"""Flask application initialization."""
self.init_config(app)
if app.config['SENTRY_DSN'] is None:
return
self.install_handler(app)
app.extensions['invenio-loggin... | the_stack_v2_python_sparse | .virtualenvs/invenio/lib/python2.7/site-packages/invenio_logging/sentry.py | N03/invenio | train | 0 |
bb49219ea05f2f189cb85232ba346895c5f707fc | [
"self.app_restore_progress_monitor_subtask_path = app_restore_progress_monitor_subtask_path\nself.child_restore_app_params_vec = child_restore_app_params_vec\nself.last_finished_log_backup_start_time_usecs = last_finished_log_backup_start_time_usecs\nself.restore_app_params = restore_app_params",
"if dictionary i... | <|body_start_0|>
self.app_restore_progress_monitor_subtask_path = app_restore_progress_monitor_subtask_path
self.child_restore_app_params_vec = child_restore_app_params_vec
self.last_finished_log_backup_start_time_usecs = last_finished_log_backup_start_time_usecs
self.restore_app_params ... | Implementation of the 'RestoreAppTaskStateProto' model. TODO: type description here. Attributes: app_restore_progress_monitor_subtask_path (string): The Pulse task path to the application restore task sub tree. If the application restore has to wait on other tasks (for example, a SQL db restore may wait for a tail log ... | RestoreAppTaskStateProto | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestoreAppTaskStateProto:
"""Implementation of the 'RestoreAppTaskStateProto' model. TODO: type description here. Attributes: app_restore_progress_monitor_subtask_path (string): The Pulse task path to the application restore task sub tree. If the application restore has to wait on other tasks (fo... | stack_v2_sparse_classes_36k_train_032796 | 3,935 | permissive | [
{
"docstring": "Constructor for the RestoreAppTaskStateProto class",
"name": "__init__",
"signature": "def __init__(self, app_restore_progress_monitor_subtask_path=None, child_restore_app_params_vec=None, last_finished_log_backup_start_time_usecs=None, restore_app_params=None)"
},
{
"docstring":... | 2 | null | Implement the Python class `RestoreAppTaskStateProto` described below.
Class description:
Implementation of the 'RestoreAppTaskStateProto' model. TODO: type description here. Attributes: app_restore_progress_monitor_subtask_path (string): The Pulse task path to the application restore task sub tree. If the application... | Implement the Python class `RestoreAppTaskStateProto` described below.
Class description:
Implementation of the 'RestoreAppTaskStateProto' model. TODO: type description here. Attributes: app_restore_progress_monitor_subtask_path (string): The Pulse task path to the application restore task sub tree. If the application... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestoreAppTaskStateProto:
"""Implementation of the 'RestoreAppTaskStateProto' model. TODO: type description here. Attributes: app_restore_progress_monitor_subtask_path (string): The Pulse task path to the application restore task sub tree. If the application restore has to wait on other tasks (fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestoreAppTaskStateProto:
"""Implementation of the 'RestoreAppTaskStateProto' model. TODO: type description here. Attributes: app_restore_progress_monitor_subtask_path (string): The Pulse task path to the application restore task sub tree. If the application restore has to wait on other tasks (for example, a ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_app_task_state_proto.py | cohesity/management-sdk-python | train | 24 |
6bf00dcef6bb9cca25219a2bcd0ccad0008d24f1 | [
"super().__init__(model_config)\nself.model = model\nself.epoch = epoch\nself.pipeline_id = pipeline_id\nmodel.eval()",
"model_and_info = model_util.load_from_checkpoint_and_adjust(config, path_to_checkpoint)\nif model_and_info.model is None or model_and_info.checkpoint_epoch is None:\n logging.warning(f'Could... | <|body_start_0|>
super().__init__(model_config)
self.model = model
self.epoch = epoch
self.pipeline_id = pipeline_id
model.eval()
<|end_body_0|>
<|body_start_1|>
model_and_info = model_util.load_from_checkpoint_and_adjust(config, path_to_checkpoint)
if model_and_... | Pipeline for inference from a single model on classification tasks. | ScalarInferencePipeline | [
"MIT",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScalarInferencePipeline:
"""Pipeline for inference from a single model on classification tasks."""
def __init__(self, model: BaseModelOrDataParallelModel, model_config: ScalarModelBase, epoch: int, pipeline_id: int) -> None:
""":param model: Model recovered from the checkpoint. :para... | stack_v2_sparse_classes_36k_train_032797 | 10,504 | permissive | [
{
"docstring": ":param model: Model recovered from the checkpoint. :param model_config: Model configuration information. :param epoch: Epoch of the checkpoint which was recovered. :param pipeline_id: ID for this pipeline (useful for ensembles). :return:",
"name": "__init__",
"signature": "def __init__(s... | 3 | stack_v2_sparse_classes_30k_test_000906 | Implement the Python class `ScalarInferencePipeline` described below.
Class description:
Pipeline for inference from a single model on classification tasks.
Method signatures and docstrings:
- def __init__(self, model: BaseModelOrDataParallelModel, model_config: ScalarModelBase, epoch: int, pipeline_id: int) -> None:... | Implement the Python class `ScalarInferencePipeline` described below.
Class description:
Pipeline for inference from a single model on classification tasks.
Method signatures and docstrings:
- def __init__(self, model: BaseModelOrDataParallelModel, model_config: ScalarModelBase, epoch: int, pipeline_id: int) -> None:... | 12b496093097ef48d5ac8880985c04918d7f76fe | <|skeleton|>
class ScalarInferencePipeline:
"""Pipeline for inference from a single model on classification tasks."""
def __init__(self, model: BaseModelOrDataParallelModel, model_config: ScalarModelBase, epoch: int, pipeline_id: int) -> None:
""":param model: Model recovered from the checkpoint. :para... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScalarInferencePipeline:
"""Pipeline for inference from a single model on classification tasks."""
def __init__(self, model: BaseModelOrDataParallelModel, model_config: ScalarModelBase, epoch: int, pipeline_id: int) -> None:
""":param model: Model recovered from the checkpoint. :param model_confi... | the_stack_v2_python_sparse | InnerEye/ML/pipelines/scalar_inference.py | MaxCodeXTC/InnerEye-DeepLearning | train | 1 |
74740fad7b96eeb46118e5d97bf81abef5df8f6e | [
"super().__init__(coordinator, device, 'extra', 'Extra meter', f'extra_{dev_type}')\nself._type = dev_type\nself._attr_name = f'Extra {dev_type}'",
"if self.coordinator.data.extra_meter is None:\n return None\nreturn getattr(self.coordinator.data.extra_meter, f'_{self._type}', None)"
] | <|body_start_0|>
super().__init__(coordinator, device, 'extra', 'Extra meter', f'extra_{dev_type}')
self._type = dev_type
self._attr_name = f'Extra {dev_type}'
<|end_body_0|>
<|body_start_1|>
if self.coordinator.data.extra_meter is None:
return None
return getattr(se... | The Youless extra meter value sensor (s0). | ExtraMeterSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtraMeterSensor:
"""The Youless extra meter value sensor (s0)."""
def __init__(self, coordinator: DataUpdateCoordinator[YoulessAPI], device: str, dev_type: str) -> None:
"""Instantiate an extra meter sensor."""
<|body_0|>
def get_sensor(self) -> YoulessSensor | None:
... | stack_v2_sparse_classes_36k_train_032798 | 11,812 | permissive | [
{
"docstring": "Instantiate an extra meter sensor.",
"name": "__init__",
"signature": "def __init__(self, coordinator: DataUpdateCoordinator[YoulessAPI], device: str, dev_type: str) -> None"
},
{
"docstring": "Get the sensor for providing the value.",
"name": "get_sensor",
"signature": "... | 2 | null | Implement the Python class `ExtraMeterSensor` described below.
Class description:
The Youless extra meter value sensor (s0).
Method signatures and docstrings:
- def __init__(self, coordinator: DataUpdateCoordinator[YoulessAPI], device: str, dev_type: str) -> None: Instantiate an extra meter sensor.
- def get_sensor(s... | Implement the Python class `ExtraMeterSensor` described below.
Class description:
The Youless extra meter value sensor (s0).
Method signatures and docstrings:
- def __init__(self, coordinator: DataUpdateCoordinator[YoulessAPI], device: str, dev_type: str) -> None: Instantiate an extra meter sensor.
- def get_sensor(s... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ExtraMeterSensor:
"""The Youless extra meter value sensor (s0)."""
def __init__(self, coordinator: DataUpdateCoordinator[YoulessAPI], device: str, dev_type: str) -> None:
"""Instantiate an extra meter sensor."""
<|body_0|>
def get_sensor(self) -> YoulessSensor | None:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExtraMeterSensor:
"""The Youless extra meter value sensor (s0)."""
def __init__(self, coordinator: DataUpdateCoordinator[YoulessAPI], device: str, dev_type: str) -> None:
"""Instantiate an extra meter sensor."""
super().__init__(coordinator, device, 'extra', 'Extra meter', f'extra_{dev_ty... | the_stack_v2_python_sparse | homeassistant/components/youless/sensor.py | home-assistant/core | train | 35,501 |
1e55f46ba2cf43aa4c74a0c43072c0448095f921 | [
"testName = 'test_validatePolygon'\ntry:\n log.print_test_begin(testName)\n x_coords = np.asarray([550, 455, 491, 609, 645])\n y_coords = np.asarray([450, 519, 631, 631, 510])\n try:\n sc.Polygon(x_coords, y_coords)\n except ValueError as e:\n pass\n log.print_test_success(testName)\... | <|body_start_0|>
testName = 'test_validatePolygon'
try:
log.print_test_begin(testName)
x_coords = np.asarray([550, 455, 491, 609, 645])
y_coords = np.asarray([450, 519, 631, 631, 510])
try:
sc.Polygon(x_coords, y_coords)
except ... | TestCalculations_Polygon | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCalculations_Polygon:
def test_validatePolygon(self):
"""Does invalid polygon coordinates raise a ValueError exception?"""
<|body_0|>
def test_setPolyArea(self):
"""Is the Polygon Area calculated correctly?"""
<|body_1|>
def test_setPolyCentroid(self... | stack_v2_sparse_classes_36k_train_032799 | 4,814 | permissive | [
{
"docstring": "Does invalid polygon coordinates raise a ValueError exception?",
"name": "test_validatePolygon",
"signature": "def test_validatePolygon(self)"
},
{
"docstring": "Is the Polygon Area calculated correctly?",
"name": "test_setPolyArea",
"signature": "def test_setPolyArea(sel... | 4 | stack_v2_sparse_classes_30k_train_017776 | Implement the Python class `TestCalculations_Polygon` described below.
Class description:
Implement the TestCalculations_Polygon class.
Method signatures and docstrings:
- def test_validatePolygon(self): Does invalid polygon coordinates raise a ValueError exception?
- def test_setPolyArea(self): Is the Polygon Area c... | Implement the Python class `TestCalculations_Polygon` described below.
Class description:
Implement the TestCalculations_Polygon class.
Method signatures and docstrings:
- def test_validatePolygon(self): Does invalid polygon coordinates raise a ValueError exception?
- def test_setPolyArea(self): Is the Polygon Area c... | 6a5bfbb459f5a1309fdace4e38b44e8274c497db | <|skeleton|>
class TestCalculations_Polygon:
def test_validatePolygon(self):
"""Does invalid polygon coordinates raise a ValueError exception?"""
<|body_0|>
def test_setPolyArea(self):
"""Is the Polygon Area calculated correctly?"""
<|body_1|>
def test_setPolyCentroid(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCalculations_Polygon:
def test_validatePolygon(self):
"""Does invalid polygon coordinates raise a ValueError exception?"""
testName = 'test_validatePolygon'
try:
log.print_test_begin(testName)
x_coords = np.asarray([550, 455, 491, 609, 645])
y_co... | the_stack_v2_python_sparse | testCalculations/polygon.py | sativa/SPEED | train | 0 |
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