blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
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values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
f34a29071aabec3b4f322d461488c8f4bf9b805c | [
"super(ResNets, self).__init__()\nself.ResNet_name = ResNet_name\nself.classes_num = classes_num\nself.block_class = self.cfg[ResNet_name][0]\nself.num_blocks = self.cfg[ResNet_name][1]\nself.expansion = self.block_class.expansion\nself.in_channels = 64\nself.conv = nn.Sequential(nn.Conv3d(in_channels=3, out_channe... | <|body_start_0|>
super(ResNets, self).__init__()
self.ResNet_name = ResNet_name
self.classes_num = classes_num
self.block_class = self.cfg[ResNet_name][0]
self.num_blocks = self.cfg[ResNet_name][1]
self.expansion = self.block_class.expansion
self.in_channels = 64
... | ResNets神经网络搭建，部分优化 | ResNets | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResNets:
"""ResNets神经网络搭建，部分优化"""
def __init__(self, ResNet_name, classes_num):
"""网络初始化 :param: ResNet_name 选用的ResNet模型名字 :param: classes_num 分类数"""
<|body_0|>
def _make_layer(self, out_channels, num_block, stride):
"""搭建对应的残差块集合网络 输入通道数类内全局化, 因为in_channels到第二块才... | stack_v2_sparse_classes_75kplus_train_069200 | 28,867 | no_license | [
{
"docstring": "网络初始化 :param: ResNet_name 选用的ResNet模型名字 :param: classes_num 分类数",
"name": "__init__",
"signature": "def __init__(self, ResNet_name, classes_num)"
},
{
"docstring": "搭建对应的残差块集合网络 输入通道数类内全局化, 因为in_channels到第二块才改为out_channels * expansion, 为方便定义将其全局化 :param: out_channels 输出通道数 :param... | 3 | stack_v2_sparse_classes_30k_train_014937 | Implement the Python class `ResNets` described below.
Class description:
ResNets神经网络搭建，部分优化
Method signatures and docstrings:
- def __init__(self, ResNet_name, classes_num): 网络初始化 :param: ResNet_name 选用的ResNet模型名字 :param: classes_num 分类数
- def _make_layer(self, out_channels, num_block, stride): 搭建对应的残差块集合网络 输入通道数类内全局... | Implement the Python class `ResNets` described below.
Class description:
ResNets神经网络搭建，部分优化
Method signatures and docstrings:
- def __init__(self, ResNet_name, classes_num): 网络初始化 :param: ResNet_name 选用的ResNet模型名字 :param: classes_num 分类数
- def _make_layer(self, out_channels, num_block, stride): 搭建对应的残差块集合网络 输入通道数类内全局... | 2a68fd854bc5b1806319dfc40e36e084f9c4c5d0 | <|skeleton|>
class ResNets:
"""ResNets神经网络搭建，部分优化"""
def __init__(self, ResNet_name, classes_num):
"""网络初始化 :param: ResNet_name 选用的ResNet模型名字 :param: classes_num 分类数"""
<|body_0|>
def _make_layer(self, out_channels, num_block, stride):
"""搭建对应的残差块集合网络 输入通道数类内全局化, 因为in_channels到第二块才... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResNets:
"""ResNets神经网络搭建，部分优化"""
def __init__(self, ResNet_name, classes_num):
"""网络初始化 :param: ResNet_name 选用的ResNet模型名字 :param: classes_num 分类数"""
super(ResNets, self).__init__()
self.ResNet_name = ResNet_name
self.classes_num = classes_num
self.block_class = se... | the_stack_v2_python_sparse | code_keh/Pytorch_nets3d.py | ruichen9/3DCTLungDiseaseDiagnosis | train | 0 |
9403e1fa60a7528020e303aa6c5d1ce6c3fcc0cd | [
"ll_a_length = Solution.get_link_list_length(self, headA)\nll_b_length = Solution.get_link_list_length(self, headB)\ndiff_length = abs(ll_a_length - ll_b_length)\ntemp_short = []\ntemp_long = []\nif ll_a_length <= ll_b_length:\n temp_short = headA\n temp_long = headB\nelse:\n temp_short = headB\n temp_l... | <|body_start_0|>
ll_a_length = Solution.get_link_list_length(self, headA)
ll_b_length = Solution.get_link_list_length(self, headB)
diff_length = abs(ll_a_length - ll_b_length)
temp_short = []
temp_long = []
if ll_a_length <= ll_b_length:
temp_short = headA
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getIntersectionNode(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_0|>
def get_link_list_length(self, ll):
""":type ll: ListNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ll_a_length =... | stack_v2_sparse_classes_75kplus_train_069201 | 1,303 | no_license | [
{
"docstring": ":type head1, head1: ListNode :rtype: ListNode",
"name": "getIntersectionNode",
"signature": "def getIntersectionNode(self, headA, headB)"
},
{
"docstring": ":type ll: ListNode :rtype: int",
"name": "get_link_list_length",
"signature": "def get_link_list_length(self, ll)"
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode(self, headA, headB): :type head1, head1: ListNode :rtype: ListNode
- def get_link_list_length(self, ll): :type ll: ListNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode(self, headA, headB): :type head1, head1: ListNode :rtype: ListNode
- def get_link_list_length(self, ll): :type ll: ListNode :rtype: int
<|skeleton|>
clas... | ac0f517d4e68d46f0e4cbf5795c7a4752e2c6bc3 | <|skeleton|>
class Solution:
def getIntersectionNode(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_0|>
def get_link_list_length(self, ll):
""":type ll: ListNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def getIntersectionNode(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
ll_a_length = Solution.get_link_list_length(self, headA)
ll_b_length = Solution.get_link_list_length(self, headB)
diff_length = abs(ll_a_length - ll_b_length)
temp... | the_stack_v2_python_sparse | Algorithms_questions/ez/linked_list_intersection.py | Nirol/LeetCodeTests | train | 0 | |
f883e6a880abb00f919217d18f267ad42e5f8ff9 | [
"self.__self = '_' + type(self).__name__\nself.__ai = baidu_ai\nself.__Set_Token()",
"host = f'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={self.__ai.Ak}&client_secret={self.__ai.Sk}'\nhtml = requests.get(host)\nself.__token = html.json().get('access_token')",
"video = cv2.V... | <|body_start_0|>
self.__self = '_' + type(self).__name__
self.__ai = baidu_ai
self.__Set_Token()
<|end_body_0|>
<|body_start_1|>
host = f'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={self.__ai.Ak}&client_secret={self.__ai.Sk}'
html = requests... | 百度AI工具 | BAIDU_AI_TOOLS | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BAIDU_AI_TOOLS:
"""百度AI工具"""
def __init__(self, baidu_ai: BAIDU_AI):
"""BAIDU_AI_TOOLS(baidu_ai: BAIDU_AI) 初始化 Args: baidu_ai: 百度AI"""
<|body_0|>
def __Set_Token(self) -> None:
"""__Set_Token() -> None 获取设置token Returns: None"""
<|body_1|>
def Cut(cl... | stack_v2_sparse_classes_75kplus_train_069202 | 3,183 | permissive | [
{
"docstring": "BAIDU_AI_TOOLS(baidu_ai: BAIDU_AI) 初始化 Args: baidu_ai: 百度AI",
"name": "__init__",
"signature": "def __init__(self, baidu_ai: BAIDU_AI)"
},
{
"docstring": "__Set_Token() -> None 获取设置token Returns: None",
"name": "__Set_Token",
"signature": "def __Set_Token(self) -> None"
... | 4 | stack_v2_sparse_classes_30k_train_024696 | Implement the Python class `BAIDU_AI_TOOLS` described below.
Class description:
百度AI工具
Method signatures and docstrings:
- def __init__(self, baidu_ai: BAIDU_AI): BAIDU_AI_TOOLS(baidu_ai: BAIDU_AI) 初始化 Args: baidu_ai: 百度AI
- def __Set_Token(self) -> None: __Set_Token() -> None 获取设置token Returns: None
- def Cut(cls, v... | Implement the Python class `BAIDU_AI_TOOLS` described below.
Class description:
百度AI工具
Method signatures and docstrings:
- def __init__(self, baidu_ai: BAIDU_AI): BAIDU_AI_TOOLS(baidu_ai: BAIDU_AI) 初始化 Args: baidu_ai: 百度AI
- def __Set_Token(self) -> None: __Set_Token() -> None 获取设置token Returns: None
- def Cut(cls, v... | 9e2a023917b86460fb02984aed9fe638c3d38dd4 | <|skeleton|>
class BAIDU_AI_TOOLS:
"""百度AI工具"""
def __init__(self, baidu_ai: BAIDU_AI):
"""BAIDU_AI_TOOLS(baidu_ai: BAIDU_AI) 初始化 Args: baidu_ai: 百度AI"""
<|body_0|>
def __Set_Token(self) -> None:
"""__Set_Token() -> None 获取设置token Returns: None"""
<|body_1|>
def Cut(cl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BAIDU_AI_TOOLS:
"""百度AI工具"""
def __init__(self, baidu_ai: BAIDU_AI):
"""BAIDU_AI_TOOLS(baidu_ai: BAIDU_AI) 初始化 Args: baidu_ai: 百度AI"""
self.__self = '_' + type(self).__name__
self.__ai = baidu_ai
self.__Set_Token()
def __Set_Token(self) -> None:
"""__Set_Token... | the_stack_v2_python_sparse | inside/Baidu_AI/Baidu_AI_Tools.py | lifansama/learning-power | train | 1 |
541c5eb6806e56ff161929305e0102a4e7bad8d1 | [
"super().__init__()\nself._backend = backend\nself._cache = None\nself._dtype = dtype\nself._thread = thread\nif dtype == data_types.cpu_float:\n self._array_builder = arrays.darray\nelif dtype == data_types.cpu_int:\n self._array_builder = arrays.iarray\nelif dtype == data_types.cpu_bool:\n self._array_bu... | <|body_start_0|>
super().__init__()
self._backend = backend
self._cache = None
self._dtype = dtype
self._thread = thread
if dtype == data_types.cpu_float:
self._array_builder = arrays.darray
elif dtype == data_types.cpu_int:
self._array_bui... | ArrayCacheManager | [
"MIT",
"MIT-0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArrayCacheManager:
def __init__(self, backend, thread, dtype):
"""Object that keeps array in the GPU device in order to avoid creating and destroying them many times, and calls functions with them. :param dtype: data type of the output arrays. :type dtype: numpy.dtype :raises ValueError:... | stack_v2_sparse_classes_75kplus_train_069203 | 9,270 | permissive | [
{
"docstring": "Object that keeps array in the GPU device in order to avoid creating and destroying them many times, and calls functions with them. :param dtype: data type of the output arrays. :type dtype: numpy.dtype :raises ValueError: If the data type is not supported.",
"name": "__init__",
"signatu... | 3 | stack_v2_sparse_classes_30k_train_028981 | Implement the Python class `ArrayCacheManager` described below.
Class description:
Implement the ArrayCacheManager class.
Method signatures and docstrings:
- def __init__(self, backend, thread, dtype): Object that keeps array in the GPU device in order to avoid creating and destroying them many times, and calls funct... | Implement the Python class `ArrayCacheManager` described below.
Class description:
Implement the ArrayCacheManager class.
Method signatures and docstrings:
- def __init__(self, backend, thread, dtype): Object that keeps array in the GPU device in order to avoid creating and destroying them many times, and calls funct... | fa6808a6ca8063751da92f683f2b810a0690a462 | <|skeleton|>
class ArrayCacheManager:
def __init__(self, backend, thread, dtype):
"""Object that keeps array in the GPU device in order to avoid creating and destroying them many times, and calls functions with them. :param dtype: data type of the output arrays. :type dtype: numpy.dtype :raises ValueError:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ArrayCacheManager:
def __init__(self, backend, thread, dtype):
"""Object that keeps array in the GPU device in order to avoid creating and destroying them many times, and calls functions with them. :param dtype: data type of the output arrays. :type dtype: numpy.dtype :raises ValueError: If the data t... | the_stack_v2_python_sparse | minkit/backends/gpu_cache.py | mramospe/minkit | train | 0 | |
36a8e5327e1820d4c46ae5a382ec24bd5c917933 | [
"if not array:\n return -1\nif n < 10:\n return n\ndigits = 1\nwhile True:\n if n <= self.helper1(digits) * digits:\n start_num = 10 ** (digits - 1)\n num = start_num + (n + digits - 1) // digits - 1\n for i in range(digits - n % digits):\n num //= 10\n return num % 1... | <|body_start_0|>
if not array:
return -1
if n < 10:
return n
digits = 1
while True:
if n <= self.helper1(digits) * digits:
start_num = 10 ** (digits - 1)
num = start_num + (n + digits - 1) // digits - 1
f... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def test(self, array, n):
"""一个无限的整数数组[1,2,3,4,....], 找出其第n位数，比如[1,2,3,4,5,6,7,8,9,10,11], 第10位数为1，第11位数为0"""
<|body_0|>
def helper1(self, digits):
"""统计digits位数共有多少个"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not array:
... | stack_v2_sparse_classes_75kplus_train_069204 | 1,294 | no_license | [
{
"docstring": "一个无限的整数数组[1,2,3,4,....], 找出其第n位数，比如[1,2,3,4,5,6,7,8,9,10,11], 第10位数为1，第11位数为0",
"name": "test",
"signature": "def test(self, array, n)"
},
{
"docstring": "统计digits位数共有多少个",
"name": "helper1",
"signature": "def helper1(self, digits)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def test(self, array, n): 一个无限的整数数组[1,2,3,4,....], 找出其第n位数，比如[1,2,3,4,5,6,7,8,9,10,11], 第10位数为1，第11位数为0
- def helper1(self, digits): 统计digits位数共有多少个 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def test(self, array, n): 一个无限的整数数组[1,2,3,4,....], 找出其第n位数，比如[1,2,3,4,5,6,7,8,9,10,11], 第10位数为1，第11位数为0
- def helper1(self, digits): 统计digits位数共有多少个
<|skeleton|>
class Solution:... | ef6aee94c7990d734271c204034ec273b665226d | <|skeleton|>
class Solution:
def test(self, array, n):
"""一个无限的整数数组[1,2,3,4,....], 找出其第n位数，比如[1,2,3,4,5,6,7,8,9,10,11], 第10位数为1，第11位数为0"""
<|body_0|>
def helper1(self, digits):
"""统计digits位数共有多少个"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def test(self, array, n):
"""一个无限的整数数组[1,2,3,4,....], 找出其第n位数，比如[1,2,3,4,5,6,7,8,9,10,11], 第10位数为1，第11位数为0"""
if not array:
return -1
if n < 10:
return n
digits = 1
while True:
if n <= self.helper1(digits) * digits:
... | the_stack_v2_python_sparse | 剑指offer/数字序列中某一位数字.py | godzzbboss/leetcode | train | 0 | |
dd4723cf274bf0e148288fa0433d9a7cfdc310ef | [
"requestor = Requestor(local_api_key=api_key)\nurl = '%s/%s' % (cls.class_url(), 'create_and_buy')\nwrapped_params = {cls.snakecase_name(): params}\nresponse, api_key = requestor.request(method=RequestMethod.POST, url=url, params=wrapped_params)\nreturn convert_to_easypost_object(response=response, api_key=api_key)... | <|body_start_0|>
requestor = Requestor(local_api_key=api_key)
url = '%s/%s' % (cls.class_url(), 'create_and_buy')
wrapped_params = {cls.snakecase_name(): params}
response, api_key = requestor.request(method=RequestMethod.POST, url=url, params=wrapped_params)
return convert_to_eas... | Batch | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Batch:
def create_and_buy(cls, api_key: Optional[str]=None, **params) -> 'Batch':
"""Create and buy a Batch."""
<|body_0|>
def buy(self, **params) -> 'Batch':
"""Buy a batch."""
<|body_1|>
def label(self, **params) -> 'Batch':
"""Create a batch l... | stack_v2_sparse_classes_75kplus_train_069205 | 2,679 | permissive | [
{
"docstring": "Create and buy a Batch.",
"name": "create_and_buy",
"signature": "def create_and_buy(cls, api_key: Optional[str]=None, **params) -> 'Batch'"
},
{
"docstring": "Buy a batch.",
"name": "buy",
"signature": "def buy(self, **params) -> 'Batch'"
},
{
"docstring": "Creat... | 6 | null | Implement the Python class `Batch` described below.
Class description:
Implement the Batch class.
Method signatures and docstrings:
- def create_and_buy(cls, api_key: Optional[str]=None, **params) -> 'Batch': Create and buy a Batch.
- def buy(self, **params) -> 'Batch': Buy a batch.
- def label(self, **params) -> 'Ba... | Implement the Python class `Batch` described below.
Class description:
Implement the Batch class.
Method signatures and docstrings:
- def create_and_buy(cls, api_key: Optional[str]=None, **params) -> 'Batch': Create and buy a Batch.
- def buy(self, **params) -> 'Batch': Buy a batch.
- def label(self, **params) -> 'Ba... | c8f7a3f2472ae5fea13a5b596b4618bd55f3be0c | <|skeleton|>
class Batch:
def create_and_buy(cls, api_key: Optional[str]=None, **params) -> 'Batch':
"""Create and buy a Batch."""
<|body_0|>
def buy(self, **params) -> 'Batch':
"""Buy a batch."""
<|body_1|>
def label(self, **params) -> 'Batch':
"""Create a batch l... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Batch:
def create_and_buy(cls, api_key: Optional[str]=None, **params) -> 'Batch':
"""Create and buy a Batch."""
requestor = Requestor(local_api_key=api_key)
url = '%s/%s' % (cls.class_url(), 'create_and_buy')
wrapped_params = {cls.snakecase_name(): params}
response, api... | the_stack_v2_python_sparse | easypost/batch.py | dsanders11/easypost-python | train | 0 | |
7613e90773658c32af5d2cbe793149c42cbf7fc7 | [
"super(output_layer, self).__init__()\nself.num_of_vertices = num_of_vertices\nself.history = history\nself.in_dim = in_dim\nself.hidden_dim = hidden_dim\nself.horizon = horizon\nself.FC1 = nn.Linear(self.in_dim * self.history, self.hidden_dim, bias=True)\nself.FC2 = nn.Linear(self.hidden_dim, self.horizon, bias=Tr... | <|body_start_0|>
super(output_layer, self).__init__()
self.num_of_vertices = num_of_vertices
self.history = history
self.in_dim = in_dim
self.hidden_dim = hidden_dim
self.horizon = horizon
self.FC1 = nn.Linear(self.in_dim * self.history, self.hidden_dim, bias=True... | output_layer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class output_layer:
def __init__(self, num_of_vertices, history, in_dim, hidden_dim=128, horizon=12):
"""预测层，注意在作者的实验中是对每一个预测时间step做处理的，也即他会令horizon=1 :param num_of_vertices:节点数 :param history:输入时间步长 :param in_dim: 输入维度 :param hidden_dim:中间层维度 :param horizon:预测时间步长"""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus_train_069206 | 12,020 | no_license | [
{
"docstring": "预测层，注意在作者的实验中是对每一个预测时间step做处理的，也即他会令horizon=1 :param num_of_vertices:节点数 :param history:输入时间步长 :param in_dim: 输入维度 :param hidden_dim:中间层维度 :param horizon:预测时间步长",
"name": "__init__",
"signature": "def __init__(self, num_of_vertices, history, in_dim, hidden_dim=128, horizon=12)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_028557 | Implement the Python class `output_layer` described below.
Class description:
Implement the output_layer class.
Method signatures and docstrings:
- def __init__(self, num_of_vertices, history, in_dim, hidden_dim=128, horizon=12): 预测层，注意在作者的实验中是对每一个预测时间step做处理的，也即他会令horizon=1 :param num_of_vertices:节点数 :param history:... | Implement the Python class `output_layer` described below.
Class description:
Implement the output_layer class.
Method signatures and docstrings:
- def __init__(self, num_of_vertices, history, in_dim, hidden_dim=128, horizon=12): 预测层，注意在作者的实验中是对每一个预测时间step做处理的，也即他会令horizon=1 :param num_of_vertices:节点数 :param history:... | 87c8adbf0db2e24d2ffa2ecac11da7a36bcae51c | <|skeleton|>
class output_layer:
def __init__(self, num_of_vertices, history, in_dim, hidden_dim=128, horizon=12):
"""预测层，注意在作者的实验中是对每一个预测时间step做处理的，也即他会令horizon=1 :param num_of_vertices:节点数 :param history:输入时间步长 :param in_dim: 输入维度 :param hidden_dim:中间层维度 :param horizon:预测时间步长"""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class output_layer:
def __init__(self, num_of_vertices, history, in_dim, hidden_dim=128, horizon=12):
"""预测层，注意在作者的实验中是对每一个预测时间step做处理的，也即他会令horizon=1 :param num_of_vertices:节点数 :param history:输入时间步长 :param in_dim: 输入维度 :param hidden_dim:中间层维度 :param horizon:预测时间步长"""
super(output_layer, self).__ini... | the_stack_v2_python_sparse | model.py | airissky/STSGCN_Pytorch | train | 0 | |
1fe89e0523c9160939709328d164a6fb22522b9e | [
"counter = 0\nwhile head:\n counter += 1\n head = head.next\nreturn counter",
"for i in range(size - 1):\n if not head:\n break\n head = head.next\nif not head:\n return None\nnext_start, head.next = (head.next, None)\nreturn next_start",
"curr = dummy_start\nwhile l1 and l2:\n if l1.va... | <|body_start_0|>
counter = 0
while head:
counter += 1
head = head.next
return counter
<|end_body_0|>
<|body_start_1|>
for i in range(size - 1):
if not head:
break
head = head.next
if not head:
return Non... | Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is repeated for a sublist of size 2. In this way, we iteratively split the list in... | Solution2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution2:
"""Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is repeated for a sublist of size 2. In this ... | stack_v2_sparse_classes_75kplus_train_069207 | 4,593 | permissive | [
{
"docstring": "Count the length of the linked list",
"name": "get_size",
"signature": "def get_size(self, head: ListNode) -> int"
},
{
"docstring": "Given the head & size, return the start node of the next chunk",
"name": "split",
"signature": "def split(self, head: ListNode, size: int)... | 4 | stack_v2_sparse_classes_30k_train_013424 | Implement the Python class `Solution2` described below.
Class description:
Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is rep... | Implement the Python class `Solution2` described below.
Class description:
Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is rep... | 9f66d352c805fcdd9930aaa18c93d7546768287c | <|skeleton|>
class Solution2:
"""Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is repeated for a sublist of size 2. In this ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution2:
"""Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is repeated for a sublist of size 2. In this way, we itera... | the_stack_v2_python_sparse | medium/148_sort_list.py | niki4/leetcode_py3 | train | 0 |
31575b5931f31b96e854d3d86d136f26e0ca19dc | [
"_query_builder = Configuration.base_uri\n_query_builder += '/messages/provisioning/subscriptions'\n_query_url = APIHelper.clean_url(_query_builder)\n_headers = {'accept': 'application/json'}\n_request = self.http_client.get(_query_url, headers=_headers)\nOAuth2.apply(_request)\n_context = self.execute_request(_req... | <|body_start_0|>
_query_builder = Configuration.base_uri
_query_builder += '/messages/provisioning/subscriptions'
_query_url = APIHelper.clean_url(_query_builder)
_headers = {'accept': 'application/json'}
_request = self.http_client.get(_query_url, headers=_headers)
OAuth... | A Controller to access Endpoints in the pythonwithgittest API. | ProvisioningController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProvisioningController:
"""A Controller to access Endpoints in the pythonwithgittest API."""
def get_subscription(self):
"""Does a GET request to /messages/provisioning/subscriptions. Get mobile number subscription for an account Returns: ProvisionNumberResponse: Response from the AP... | stack_v2_sparse_classes_75kplus_train_069208 | 8,123 | no_license | [
{
"docstring": "Does a GET request to /messages/provisioning/subscriptions. Get mobile number subscription for an account Returns: ProvisionNumberResponse: Response from the API. Success Raises: APIException: When an error occurs while fetching the data from the remote API. This exception includes the HTTP Resp... | 3 | stack_v2_sparse_classes_30k_train_021368 | Implement the Python class `ProvisioningController` described below.
Class description:
A Controller to access Endpoints in the pythonwithgittest API.
Method signatures and docstrings:
- def get_subscription(self): Does a GET request to /messages/provisioning/subscriptions. Get mobile number subscription for an accou... | Implement the Python class `ProvisioningController` described below.
Class description:
A Controller to access Endpoints in the pythonwithgittest API.
Method signatures and docstrings:
- def get_subscription(self): Does a GET request to /messages/provisioning/subscriptions. Get mobile number subscription for an accou... | c5d8eefa4f7fa20adad9380a19ba1bec55bf7ab2 | <|skeleton|>
class ProvisioningController:
"""A Controller to access Endpoints in the pythonwithgittest API."""
def get_subscription(self):
"""Does a GET request to /messages/provisioning/subscriptions. Get mobile number subscription for an account Returns: ProvisionNumberResponse: Response from the AP... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProvisioningController:
"""A Controller to access Endpoints in the pythonwithgittest API."""
def get_subscription(self):
"""Does a GET request to /messages/provisioning/subscriptions. Get mobile number subscription for an account Returns: ProvisionNumberResponse: Response from the API. Success Ra... | the_stack_v2_python_sparse | venv/Lib/site-packages/pythonwithgittest/controllers/provisioning_controller.py | OT-seven/HKCostPlatformTest | train | 0 |
9dc63efdb34df2faf109aee4ba309a2fd58705ae | [
"CGestionSav.__init__(self, bdd, logger, isHeritage, nbEssaiBdd, dureeEntreEssaiBdd)\nfonction = 'CGestionSavThread.CThreadMemBdd:self.__init__()'\nself.__codeAction = codeAction\nself.__dateHeure = dateHeure\nthreading.Thread.__init__(self)\nmessage = \"Création d'un objet 'CThreadMemBdd' avec lien à bdd et logger... | <|body_start_0|>
CGestionSav.__init__(self, bdd, logger, isHeritage, nbEssaiBdd, dureeEntreEssaiBdd)
fonction = 'CGestionSavThread.CThreadMemBdd:self.__init__()'
self.__codeAction = codeAction
self.__dateHeure = dateHeure
threading.Thread.__init__(self)
message = "Créatio... | Thread permettant de mettre en base un enregistrement. En cas d'échec, le thread essaiera le nombre de fois défini cette opération avec une durée d'attente définie entre chaque essai. | CThreadMemBdd | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CThreadMemBdd:
"""Thread permettant de mettre en base un enregistrement. En cas d'échec, le thread essaiera le nombre de fois défini cette opération avec une durée d'attente définie entre chaque essai."""
def __init__(self, bdd, logger, isHeritage=True, codeAction='0', nbEssaiBdd=5, dureeEnt... | stack_v2_sparse_classes_75kplus_train_069209 | 45,947 | no_license | [
{
"docstring": "constructeur bdd : référence à un objet \"connexion bdd\" logger : référence à un objet \"logger console et fichier rotatif\" isHeritage : boolean, différencie un objet créé par la classe mère de la classe fille, utile pour le debug (affichage création objet) False : objet classe mère True : obj... | 2 | stack_v2_sparse_classes_30k_train_044605 | Implement the Python class `CThreadMemBdd` described below.
Class description:
Thread permettant de mettre en base un enregistrement. En cas d'échec, le thread essaiera le nombre de fois défini cette opération avec une durée d'attente définie entre chaque essai.
Method signatures and docstrings:
- def __init__(self, ... | Implement the Python class `CThreadMemBdd` described below.
Class description:
Thread permettant de mettre en base un enregistrement. En cas d'échec, le thread essaiera le nombre de fois défini cette opération avec une durée d'attente définie entre chaque essai.
Method signatures and docstrings:
- def __init__(self, ... | 1a64f0b0a6a3bcf1dd7e6e59a2b5faeb7cae67a8 | <|skeleton|>
class CThreadMemBdd:
"""Thread permettant de mettre en base un enregistrement. En cas d'échec, le thread essaiera le nombre de fois défini cette opération avec une durée d'attente définie entre chaque essai."""
def __init__(self, bdd, logger, isHeritage=True, codeAction='0', nbEssaiBdd=5, dureeEnt... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CThreadMemBdd:
"""Thread permettant de mettre en base un enregistrement. En cas d'échec, le thread essaiera le nombre de fois défini cette opération avec une durée d'attente définie entre chaque essai."""
def __init__(self, bdd, logger, isHeritage=True, codeAction='0', nbEssaiBdd=5, dureeEntreEssaiBdd=5,... | the_stack_v2_python_sparse | prog_python/gestion_sav__bdd_thread_initiation/CGestionSavThread.py | HerveDugast/public_hervedugast_stfelix_lasalle | train | 0 |
63fc2dec0300362b409b05205fc35826294a4b2b | [
"super(type(self), self).__init__()\nwriter_module_name = 'grit.format.policy_templates.writers.' + writer_name + '_writer'\n__import__(writer_module_name)\nself._writer_module = sys.modules[writer_module_name]",
"self._lang = lang\nself._config = writer_configuration.GetConfigurationForBuild(item.defines)\nself.... | <|body_start_0|>
super(type(self), self).__init__()
writer_module_name = 'grit.format.policy_templates.writers.' + writer_name + '_writer'
__import__(writer_module_name)
self._writer_module = sys.modules[writer_module_name]
<|end_body_0|>
<|body_start_1|>
self._lang = lang
... | Creates a template file corresponding to an <output> node of the grit tree. More precisely, processes the whole grit tree for a given <output> node whose type is 'adm'. TODO(gfeher) add new types here The result of processing is a policy template file with the given type and language of the <output> node. A new instanc... | TemplateFormatter | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplateFormatter:
"""Creates a template file corresponding to an <output> node of the grit tree. More precisely, processes the whole grit tree for a given <output> node whose type is 'adm'. TODO(gfeher) add new types here The result of processing is a policy template file with the given type and... | stack_v2_sparse_classes_75kplus_train_069210 | 3,721 | permissive | [
{
"docstring": "Initializes this formatter to output messages with a given writer. Args: writer_name: A string identifying the TemplateWriter subclass used for generating the output. If writer name is 'adm', then the class from module 'writers.adm_writer' will be used.",
"name": "__init__",
"signature":... | 4 | null | Implement the Python class `TemplateFormatter` described below.
Class description:
Creates a template file corresponding to an <output> node of the grit tree. More precisely, processes the whole grit tree for a given <output> node whose type is 'adm'. TODO(gfeher) add new types here The result of processing is a polic... | Implement the Python class `TemplateFormatter` described below.
Class description:
Creates a template file corresponding to an <output> node of the grit tree. More precisely, processes the whole grit tree for a given <output> node whose type is 'adm'. TODO(gfeher) add new types here The result of processing is a polic... | 232638c56378a8b2e621e8403be939d34d3c91a0 | <|skeleton|>
class TemplateFormatter:
"""Creates a template file corresponding to an <output> node of the grit tree. More precisely, processes the whole grit tree for a given <output> node whose type is 'adm'. TODO(gfeher) add new types here The result of processing is a policy template file with the given type and... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TemplateFormatter:
"""Creates a template file corresponding to an <output> node of the grit tree. More precisely, processes the whole grit tree for a given <output> node whose type is 'adm'. TODO(gfeher) add new types here The result of processing is a policy template file with the given type and language of ... | the_stack_v2_python_sparse | tools/grit/grit/format/policy_templates/template_formatter.py | Chingliu/WTL-DUI | train | 1 |
12b0cdd344ebe336e37775ad511db77962c2afdd | [
"logging.info(u'测试 枚举 选项的取值')\nassert Platform() == [(1, 'IOS'), (2, 'ANDROID'), (3, 'WP')]\nassert Platform._items == [(1, 'IOS'), (2, 'ANDROID'), (3, 'WP')]\nassert LocationType() == [('America', '美洲'), ('Asia', u'亚洲'), ('Australia', '澳洲'), ('Europe', u'欧洲')]\nassert LocationType._items == [('America', '美洲'), ('A... | <|body_start_0|>
logging.info(u'测试 枚举 选项的取值')
assert Platform() == [(1, 'IOS'), (2, 'ANDROID'), (3, 'WP')]
assert Platform._items == [(1, 'IOS'), (2, 'ANDROID'), (3, 'WP')]
assert LocationType() == [('America', '美洲'), ('Asia', u'亚洲'), ('Australia', '澳洲'), ('Europe', u'欧洲')]
asser... | TestConst | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestConst:
def test_items(self):
"""返回数值列表 测试"""
<|body_0|>
def test_key(self):
"""获取键 测试"""
<|body_1|>
def test_value(self):
"""获取展示值 测试"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
logging.info(u'测试 枚举 选项的取值')
asser... | stack_v2_sparse_classes_75kplus_train_069211 | 3,426 | no_license | [
{
"docstring": "返回数值列表 测试",
"name": "test_items",
"signature": "def test_items(self)"
},
{
"docstring": "获取键 测试",
"name": "test_key",
"signature": "def test_key(self)"
},
{
"docstring": "获取展示值 测试",
"name": "test_value",
"signature": "def test_value(self)"
}
] | 3 | null | Implement the Python class `TestConst` described below.
Class description:
Implement the TestConst class.
Method signatures and docstrings:
- def test_items(self): 返回数值列表 测试
- def test_key(self): 获取键 测试
- def test_value(self): 获取展示值 测试 | Implement the Python class `TestConst` described below.
Class description:
Implement the TestConst class.
Method signatures and docstrings:
- def test_items(self): 返回数值列表 测试
- def test_key(self): 获取键 测试
- def test_value(self): 获取展示值 测试
<|skeleton|>
class TestConst:
def test_items(self):
"""返回数值列表 测试"""
... | ad65bc3b711ec00844da7493fc55e5445d58639f | <|skeleton|>
class TestConst:
def test_items(self):
"""返回数值列表 测试"""
<|body_0|>
def test_key(self):
"""获取键 测试"""
<|body_1|>
def test_value(self):
"""获取展示值 测试"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestConst:
def test_items(self):
"""返回数值列表 测试"""
logging.info(u'测试 枚举 选项的取值')
assert Platform() == [(1, 'IOS'), (2, 'ANDROID'), (3, 'WP')]
assert Platform._items == [(1, 'IOS'), (2, 'ANDROID'), (3, 'WP')]
assert LocationType() == [('America', '美洲'), ('Asia', u'亚洲'), ('A... | the_stack_v2_python_sparse | cheatsheet/编程笔记/_util/python/libs_my_test/test_enum.py | wangfuli217/ld_note | train | 5 | |
e6c1db56f8a2e134896c17f833fc5d42da49ab27 | [
"super().__init__()\nself.kickh = -25 / 1000\nself.kickv = +20 / 1000\nself.wait_bbb = 9\nself.currents = _np.arange(0.05, 2.1, 0.1)",
"dtmp = '{0:10s} = {1:9d} {2:s}\\n'.format\nftmp = '{0:10s} = {1:9.3f} {2:s}\\n'.format\nltmp = '{0:6.3f},'.format\nstg = ''\nstg += ftmp('kickh', self.kickh, '[mrad]')\nstg += ... | <|body_start_0|>
super().__init__()
self.kickh = -25 / 1000
self.kickv = +20 / 1000
self.wait_bbb = 9
self.currents = _np.arange(0.05, 2.1, 0.1)
<|end_body_0|>
<|body_start_1|>
dtmp = '{0:10s} = {1:9d} {2:s}\n'.format
ftmp = '{0:10s} = {1:9.3f} {2:s}\n'.format
... | . | TuneShiftParams | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TuneShiftParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__()
self.kickh = -25 / 1000
self.kickv = +20 / 1000
self.wait_bbb = 9
... | stack_v2_sparse_classes_75kplus_train_069212 | 45,488 | permissive | [
{
"docstring": ".",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ".",
"name": "__str__",
"signature": "def __str__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_048891 | Implement the Python class `TuneShiftParams` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self): .
- def __str__(self): . | Implement the Python class `TuneShiftParams` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self): .
- def __str__(self): .
<|skeleton|>
class TuneShiftParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
... | 39644161d98964a3a3d80d63269201f0a1712e82 | <|skeleton|>
class TuneShiftParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TuneShiftParams:
"""."""
def __init__(self):
"""."""
super().__init__()
self.kickh = -25 / 1000
self.kickv = +20 / 1000
self.wait_bbb = 9
self.currents = _np.arange(0.05, 2.1, 0.1)
def __str__(self):
"""."""
dtmp = '{0:10s} = {1:9d} {2... | the_stack_v2_python_sparse | apsuite/commisslib/measure_bbb_data.py | lnls-fac/apsuite | train | 1 |
4fc5b8a135c695c5b24b11096175f6145308383b | [
"\"\"\"\n :type name: str \n :rtype: int\n \"\"\"\nself.name = name",
"self.prob = prob\nself.R = R\nif self.name == 'Binomial':\n return np.where(self.prob <= 1 - self.R, 1, 0)\nelse:\n print('Not available!')\n return []"
] | <|body_start_0|>
"""
:type name: str
:rtype: int
"""
self.name = name
<|end_body_0|>
<|body_start_1|>
self.prob = prob
self.R = R
if self.name == 'Binomial':
return np.where(self.prob <= 1 - self.R, 1, 0)
else:... | Indicator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Indicator:
def __init__(self, name):
"""Constructor for this class."""
<|body_0|>
def Binary_Indicator(self, prob, R):
""":type pi: float :type R: float :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
"""
:type name: str ... | stack_v2_sparse_classes_75kplus_train_069213 | 771 | permissive | [
{
"docstring": "Constructor for this class.",
"name": "__init__",
"signature": "def __init__(self, name)"
},
{
"docstring": ":type pi: float :type R: float :rtype: int",
"name": "Binary_Indicator",
"signature": "def Binary_Indicator(self, prob, R)"
}
] | 2 | stack_v2_sparse_classes_30k_train_036885 | Implement the Python class `Indicator` described below.
Class description:
Implement the Indicator class.
Method signatures and docstrings:
- def __init__(self, name): Constructor for this class.
- def Binary_Indicator(self, prob, R): :type pi: float :type R: float :rtype: int | Implement the Python class `Indicator` described below.
Class description:
Implement the Indicator class.
Method signatures and docstrings:
- def __init__(self, name): Constructor for this class.
- def Binary_Indicator(self, prob, R): :type pi: float :type R: float :rtype: int
<|skeleton|>
class Indicator:
def ... | 0517780d05443cb77ce339db1854c298b87681e3 | <|skeleton|>
class Indicator:
def __init__(self, name):
"""Constructor for this class."""
<|body_0|>
def Binary_Indicator(self, prob, R):
""":type pi: float :type R: float :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Indicator:
def __init__(self, name):
"""Constructor for this class."""
"""
:type name: str
:rtype: int
"""
self.name = name
def Binary_Indicator(self, prob, R):
""":type pi: float :type R: float :rtype: int"""
self.p... | the_stack_v2_python_sparse | brdt/Indicator.py | ericchen12377/BRDT-Python | train | 2 | |
b3f8547044db5d63dfe2785460a0003540075783 | [
"super(GroupAttention, self).__init__(**kwargs)\nif n_group < 1:\n raise ValueError('The number of groups (`n_group`) must be an integer greater than 0.')\nself.n_group = n_group\nif n_dim < 1:\n raise ValueError('The dimensionality (`n_dim`) must be an integer greater than 0.')\nself.n_dim = n_dim\nif embedd... | <|body_start_0|>
super(GroupAttention, self).__init__(**kwargs)
if n_group < 1:
raise ValueError('The number of groups (`n_group`) must be an integer greater than 0.')
self.n_group = n_group
if n_dim < 1:
raise ValueError('The dimensionality (`n_dim`) must be an i... | Group-specific attention weights. | GroupAttention | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupAttention:
"""Group-specific attention weights."""
def __init__(self, n_group=1, n_dim=None, fit_group=None, embeddings_initializer=None, embeddings_regularizer=None, embeddings_constraint=None, **kwargs):
"""Initialize. Arguments: n_dim: An integer indicating the dimensionality... | stack_v2_sparse_classes_75kplus_train_069214 | 31,603 | permissive | [
{
"docstring": "Initialize. Arguments: n_dim: An integer indicating the dimensionality of the embeddings. Must be equal to or greater than one. n_group (optional): An integer indicating the number of different population groups in the embedding. A separate set of attention weights will be inferred for each grou... | 3 | null | Implement the Python class `GroupAttention` described below.
Class description:
Group-specific attention weights.
Method signatures and docstrings:
- def __init__(self, n_group=1, n_dim=None, fit_group=None, embeddings_initializer=None, embeddings_regularizer=None, embeddings_constraint=None, **kwargs): Initialize. A... | Implement the Python class `GroupAttention` described below.
Class description:
Group-specific attention weights.
Method signatures and docstrings:
- def __init__(self, n_group=1, n_dim=None, fit_group=None, embeddings_initializer=None, embeddings_regularizer=None, embeddings_constraint=None, **kwargs): Initialize. A... | 4f05348cf43d2d53ff9cc6dee633de385df883e3 | <|skeleton|>
class GroupAttention:
"""Group-specific attention weights."""
def __init__(self, n_group=1, n_dim=None, fit_group=None, embeddings_initializer=None, embeddings_regularizer=None, embeddings_constraint=None, **kwargs):
"""Initialize. Arguments: n_dim: An integer indicating the dimensionality... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GroupAttention:
"""Group-specific attention weights."""
def __init__(self, n_group=1, n_dim=None, fit_group=None, embeddings_initializer=None, embeddings_regularizer=None, embeddings_constraint=None, **kwargs):
"""Initialize. Arguments: n_dim: An integer indicating the dimensionality of the embed... | the_stack_v2_python_sparse | psiz/keras/layers/.ipynb_checkpoints/kernel-checkpoint.py | asuiconlab/psiz | train | 0 |
c1be3ab695e01e93b25fd5f012554ea0436675cd | [
"assert linkage.shape[1] == 4, 'a linkage matrix is needed to choose thresholds'\nsz = np.mean(linkage[:, 3])\nthresholds = linkage[linkage[:, 3] > sz, 2]\nthresholds = np.unique(thresholds)\nthresholds = np.sort(thresholds)[::-1]\nlogger.info('Obtained %d thresholds', len(thresholds))\nreturn thresholds",
"logge... | <|body_start_0|>
assert linkage.shape[1] == 4, 'a linkage matrix is needed to choose thresholds'
sz = np.mean(linkage[:, 3])
thresholds = linkage[linkage[:, 3] > sz, 2]
thresholds = np.unique(thresholds)
thresholds = np.sort(thresholds)[::-1]
logger.info('Obtained %d thre... | SceneClustering | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SceneClustering:
def choose_thresholds(self, linkage):
"""Chooses thresholds where two or more clusters where merged Args: lnk: numpy matrix (n x 4) that is the result from linkage. N is the number of clusterings Returns: thresholds: a list of thresholds (float) Assertions: AssertError w... | stack_v2_sparse_classes_75kplus_train_069215 | 2,032 | no_license | [
{
"docstring": "Chooses thresholds where two or more clusters where merged Args: lnk: numpy matrix (n x 4) that is the result from linkage. N is the number of clusterings Returns: thresholds: a list of thresholds (float) Assertions: AssertError when lnk has the incorrect shape",
"name": "choose_thresholds",... | 2 | stack_v2_sparse_classes_30k_train_017950 | Implement the Python class `SceneClustering` described below.
Class description:
Implement the SceneClustering class.
Method signatures and docstrings:
- def choose_thresholds(self, linkage): Chooses thresholds where two or more clusters where merged Args: lnk: numpy matrix (n x 4) that is the result from linkage. N ... | Implement the Python class `SceneClustering` described below.
Class description:
Implement the SceneClustering class.
Method signatures and docstrings:
- def choose_thresholds(self, linkage): Chooses thresholds where two or more clusters where merged Args: lnk: numpy matrix (n x 4) that is the result from linkage. N ... | 2f9c33c4e1a26b3e9e699210ac974047936f49e1 | <|skeleton|>
class SceneClustering:
def choose_thresholds(self, linkage):
"""Chooses thresholds where two or more clusters where merged Args: lnk: numpy matrix (n x 4) that is the result from linkage. N is the number of clusterings Returns: thresholds: a list of thresholds (float) Assertions: AssertError w... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SceneClustering:
def choose_thresholds(self, linkage):
"""Chooses thresholds where two or more clusters where merged Args: lnk: numpy matrix (n x 4) that is the result from linkage. N is the number of clusterings Returns: thresholds: a list of thresholds (float) Assertions: AssertError when lnk has th... | the_stack_v2_python_sparse | vision/scene/discovery/clustering.py | winkash/image-classification | train | 0 | |
49c12560293527b6f4f7984d4192c5c725235773 | [
"self.auth = auth\nif isinstance(tid, PracticeTag):\n self.tag = tid\nelse:\n self.tag = self.get_tag_model(tid)",
"if not tid:\n return None\ntag = PracticeTag.objects.get_once(tid)\nif not tag:\n raise not PracticeTagInfoExcept.tag_is_not_exists()\nreturn tag",
"if not self.tag:\n return {}\nre... | <|body_start_0|>
self.auth = auth
if isinstance(tid, PracticeTag):
self.tag = tid
else:
self.tag = self.get_tag_model(tid)
<|end_body_0|>
<|body_start_1|>
if not tid:
return None
tag = PracticeTag.objects.get_once(tid)
if not tag:
... | TagLogic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagLogic:
def __init__(self, auth, tid):
"""INIT :param auth: :param tid:"""
<|body_0|>
def get_tag_model(self, tid):
"""获取标签model :param tid: :return:"""
<|body_1|>
def get_tag_info(self):
"""获取标签信息 :return:"""
<|body_2|>
def is_not... | stack_v2_sparse_classes_75kplus_train_069216 | 1,466 | no_license | [
{
"docstring": "INIT :param auth: :param tid:",
"name": "__init__",
"signature": "def __init__(self, auth, tid)"
},
{
"docstring": "获取标签model :param tid: :return:",
"name": "get_tag_model",
"signature": "def get_tag_model(self, tid)"
},
{
"docstring": "获取标签信息 :return:",
"name... | 4 | stack_v2_sparse_classes_30k_train_001690 | Implement the Python class `TagLogic` described below.
Class description:
Implement the TagLogic class.
Method signatures and docstrings:
- def __init__(self, auth, tid): INIT :param auth: :param tid:
- def get_tag_model(self, tid): 获取标签model :param tid: :return:
- def get_tag_info(self): 获取标签信息 :return:
- def is_not... | Implement the Python class `TagLogic` described below.
Class description:
Implement the TagLogic class.
Method signatures and docstrings:
- def __init__(self, auth, tid): INIT :param auth: :param tid:
- def get_tag_model(self, tid): 获取标签model :param tid: :return:
- def get_tag_info(self): 获取标签信息 :return:
- def is_not... | 7467cd66e1fc91f0b3a264f8fc9b93f22f09fe7b | <|skeleton|>
class TagLogic:
def __init__(self, auth, tid):
"""INIT :param auth: :param tid:"""
<|body_0|>
def get_tag_model(self, tid):
"""获取标签model :param tid: :return:"""
<|body_1|>
def get_tag_info(self):
"""获取标签信息 :return:"""
<|body_2|>
def is_not... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TagLogic:
def __init__(self, auth, tid):
"""INIT :param auth: :param tid:"""
self.auth = auth
if isinstance(tid, PracticeTag):
self.tag = tid
else:
self.tag = self.get_tag_model(tid)
def get_tag_model(self, tid):
"""获取标签model :param tid: :re... | the_stack_v2_python_sparse | FireHydrant/server/practice/logics/tag.py | shoogoome/FireHydrant | train | 4 | |
f96effe90b6f755a40e8bd43799a13543eb81529 | [
"super().__init__()\nself.embedding_part = nn.Embedding(num_embeddings=len(vocab.id2char), embedding_dim=e_char, padding_idx=vocab.pad_index)\nself.dropout_part = nn.Dropout(p=dropout_p)\nself.cnn_part = CNN(e_char=e_char, filter_num=filter_num, window_size=window_size, padding=padding)\nparameter_init.init_embeddi... | <|body_start_0|>
super().__init__()
self.embedding_part = nn.Embedding(num_embeddings=len(vocab.id2char), embedding_dim=e_char, padding_idx=vocab.pad_index)
self.dropout_part = nn.Dropout(p=dropout_p)
self.cnn_part = CNN(e_char=e_char, filter_num=filter_num, window_size=window_size, padd... | CharCNNEmbedding | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CharCNNEmbedding:
def __init__(self, e_char: int, filter_num: int, window_size: int, padding: int, dropout_p: float, vocab: CharVocab):
""":param e_char: char 的向量维数 :param filter_num: cnn filter 数目，也是 char cnn 的输出维度（每个 word 的对应向量维数） :param dropout_p: p :param window_size: cnn filter 的窗口大... | stack_v2_sparse_classes_75kplus_train_069217 | 3,826 | no_license | [
{
"docstring": ":param e_char: char 的向量维数 :param filter_num: cnn filter 数目，也是 char cnn 的输出维度（每个 word 的对应向量维数） :param dropout_p: p :param window_size: cnn filter 的窗口大小 :param padding: cnn padding :param vocab: CharVocab object. See vocab.py for documentation. 全局共享即可",
"name": "__init__",
"signature": "de... | 2 | null | Implement the Python class `CharCNNEmbedding` described below.
Class description:
Implement the CharCNNEmbedding class.
Method signatures and docstrings:
- def __init__(self, e_char: int, filter_num: int, window_size: int, padding: int, dropout_p: float, vocab: CharVocab): :param e_char: char 的向量维数 :param filter_num:... | Implement the Python class `CharCNNEmbedding` described below.
Class description:
Implement the CharCNNEmbedding class.
Method signatures and docstrings:
- def __init__(self, e_char: int, filter_num: int, window_size: int, padding: int, dropout_p: float, vocab: CharVocab): :param e_char: char 的向量维数 :param filter_num:... | 29dc4aa0ebd3f610135ceb88f62634b4597b564a | <|skeleton|>
class CharCNNEmbedding:
def __init__(self, e_char: int, filter_num: int, window_size: int, padding: int, dropout_p: float, vocab: CharVocab):
""":param e_char: char 的向量维数 :param filter_num: cnn filter 数目，也是 char cnn 的输出维度（每个 word 的对应向量维数） :param dropout_p: p :param window_size: cnn filter 的窗口大... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CharCNNEmbedding:
def __init__(self, e_char: int, filter_num: int, window_size: int, padding: int, dropout_p: float, vocab: CharVocab):
""":param e_char: char 的向量维数 :param filter_num: cnn filter 数目，也是 char cnn 的输出维度（每个 word 的对应向量维数） :param dropout_p: p :param window_size: cnn filter 的窗口大小 :param paddi... | the_stack_v2_python_sparse | task04/modules/char_cnn.py | yjqiang/nlp-beginner | train | 2 | |
9ea6a21cb69bea2dde6d2504583fb38c175a5d65 | [
"for filename in self.changes.get_files():\n log.debug('Looking whether %s was actually uploaded' % filename)\n if os.path.isfile(os.path.join(config['debexpo.upload.incoming'], filename)):\n log.debug('%s is present' % filename)\n self.passed('file-is-present', filename, constants.PLUGIN_SEVERI... | <|body_start_0|>
for filename in self.changes.get_files():
log.debug('Looking whether %s was actually uploaded' % filename)
if os.path.isfile(os.path.join(config['debexpo.upload.incoming'], filename)):
log.debug('%s is present' % filename)
self.passed('fil... | CheckFilesPlugin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckFilesPlugin:
def test_files_present(self):
"""Check whether each file listed in the changes file is present."""
<|body_0|>
def test_md5sum(self):
"""Check each file's md5sum and make sure the md5sum in the changes file is the same as the actual file's md5sum."""... | stack_v2_sparse_classes_75kplus_train_069218 | 3,751 | no_license | [
{
"docstring": "Check whether each file listed in the changes file is present.",
"name": "test_files_present",
"signature": "def test_files_present(self)"
},
{
"docstring": "Check each file's md5sum and make sure the md5sum in the changes file is the same as the actual file's md5sum.",
"name... | 2 | stack_v2_sparse_classes_30k_train_046088 | Implement the Python class `CheckFilesPlugin` described below.
Class description:
Implement the CheckFilesPlugin class.
Method signatures and docstrings:
- def test_files_present(self): Check whether each file listed in the changes file is present.
- def test_md5sum(self): Check each file's md5sum and make sure the m... | Implement the Python class `CheckFilesPlugin` described below.
Class description:
Implement the CheckFilesPlugin class.
Method signatures and docstrings:
- def test_files_present(self): Check whether each file listed in the changes file is present.
- def test_md5sum(self): Check each file's md5sum and make sure the m... | 04c09606daca2fceccffaed0b9df777efad375bb | <|skeleton|>
class CheckFilesPlugin:
def test_files_present(self):
"""Check whether each file listed in the changes file is present."""
<|body_0|>
def test_md5sum(self):
"""Check each file's md5sum and make sure the md5sum in the changes file is the same as the actual file's md5sum."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CheckFilesPlugin:
def test_files_present(self):
"""Check whether each file listed in the changes file is present."""
for filename in self.changes.get_files():
log.debug('Looking whether %s was actually uploaded' % filename)
if os.path.isfile(os.path.join(config['debexpo... | the_stack_v2_python_sparse | debexpo/plugins/checkfiles.py | certik/debexpo | train | 1 | |
5a3e77ed905eb5336b7117a3c08e681b279bf8ed | [
"X = check_array(X, dtype=np.float32, accept_sparse='csc')\nif quantile is None:\n return super(BaseTreeQuantileRegressor, self).predict(X, check_input=check_input)\nquantiles = np.zeros(X.shape[0])\nX_leaves = self.apply(X)\nunique_leaves = np.unique(X_leaves)\nfor leaf in unique_leaves:\n quantiles[X_leaves... | <|body_start_0|>
X = check_array(X, dtype=np.float32, accept_sparse='csc')
if quantile is None:
return super(BaseTreeQuantileRegressor, self).predict(X, check_input=check_input)
quantiles = np.zeros(X.shape[0])
X_leaves = self.apply(X)
unique_leaves = np.unique(X_leav... | BaseTreeQuantileRegressor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseTreeQuantileRegressor:
def predict(self, X, quantile=None, check_input=False):
"""Predict regression value for X. Parameters ---------- X : array-like or sparse matrix of shape = [n_samples, n_features] The input samples. Internally, it will be converted to ``dtype=np.float32`` and i... | stack_v2_sparse_classes_75kplus_train_069219 | 36,172 | permissive | [
{
"docstring": "Predict regression value for X. Parameters ---------- X : array-like or sparse matrix of shape = [n_samples, n_features] The input samples. Internally, it will be converted to ``dtype=np.float32`` and if a sparse matrix is provided to a sparse ``csr_matrix``. quantile : int, optional Value rangi... | 2 | stack_v2_sparse_classes_30k_train_012561 | Implement the Python class `BaseTreeQuantileRegressor` described below.
Class description:
Implement the BaseTreeQuantileRegressor class.
Method signatures and docstrings:
- def predict(self, X, quantile=None, check_input=False): Predict regression value for X. Parameters ---------- X : array-like or sparse matrix of... | Implement the Python class `BaseTreeQuantileRegressor` described below.
Class description:
Implement the BaseTreeQuantileRegressor class.
Method signatures and docstrings:
- def predict(self, X, quantile=None, check_input=False): Predict regression value for X. Parameters ---------- X : array-like or sparse matrix of... | 6af92e149491f6e5062495d87306b3625d12d992 | <|skeleton|>
class BaseTreeQuantileRegressor:
def predict(self, X, quantile=None, check_input=False):
"""Predict regression value for X. Parameters ---------- X : array-like or sparse matrix of shape = [n_samples, n_features] The input samples. Internally, it will be converted to ``dtype=np.float32`` and i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseTreeQuantileRegressor:
def predict(self, X, quantile=None, check_input=False):
"""Predict regression value for X. Parameters ---------- X : array-like or sparse matrix of shape = [n_samples, n_features] The input samples. Internally, it will be converted to ``dtype=np.float32`` and if a sparse mat... | the_stack_v2_python_sparse | tabular/src/autogluon/tabular/models/rf/rf_quantile.py | stjordanis/autogluon | train | 0 | |
128aab7fa24b33e80ed4f862e142677ba13e6dd7 | [
"self.sarr = sarr\nself.alpha = alpha\nself.gamma = gamma",
"a = self.sarr.steer(angle)\nphase = np.random.random() * np.pi * 2\nsignal = np.exp(1j * np.pi * phase)\ny = signal * a\nnoise = salphas_cplx(self.alpha, self.gamma, size=y.shape)\ny += noise\nreturn y",
"nsnapshots = angles.size\nphase = np.random.ra... | <|body_start_0|>
self.sarr = sarr
self.alpha = alpha
self.gamma = gamma
<|end_body_0|>
<|body_start_1|>
a = self.sarr.steer(angle)
phase = np.random.random() * np.pi * 2
signal = np.exp(1j * np.pi * phase)
y = signal * a
noise = salphas_cplx(self.alpha, s... | Generating and yielding signals. See the reference for definition and form of signal. Reference --------- Zhong, X., Prekumar, A. B., and Madhukumar, A. S., "Particle filtering for acoustic source tracking in impulsive noise with alpha-stable process", IEEE Sensors Journal, Feb. 2013, Vol. 13 No. 2: 589-600. | SignalYielder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignalYielder:
"""Generating and yielding signals. See the reference for definition and form of signal. Reference --------- Zhong, X., Prekumar, A. B., and Madhukumar, A. S., "Particle filtering for acoustic source tracking in impulsive noise with alpha-stable process", IEEE Sensors Journal, Feb.... | stack_v2_sparse_classes_75kplus_train_069220 | 2,828 | no_license | [
{
"docstring": "Parameters ---------- sarr : DOAArray Instance of sensor array. alpha : float Alpha coefficient (characteristic exponent) of S-alpha-S distribution. gamma : float Gamma coefficient (dispersion parameter) of S-alpha-S distribution.",
"name": "__init__",
"signature": "def __init__(self, sa... | 3 | null | Implement the Python class `SignalYielder` described below.
Class description:
Generating and yielding signals. See the reference for definition and form of signal. Reference --------- Zhong, X., Prekumar, A. B., and Madhukumar, A. S., "Particle filtering for acoustic source tracking in impulsive noise with alpha-stab... | Implement the Python class `SignalYielder` described below.
Class description:
Generating and yielding signals. See the reference for definition and form of signal. Reference --------- Zhong, X., Prekumar, A. B., and Madhukumar, A. S., "Particle filtering for acoustic source tracking in impulsive noise with alpha-stab... | 4cbb2eba87c6ffd79e474014584ee31c893ade13 | <|skeleton|>
class SignalYielder:
"""Generating and yielding signals. See the reference for definition and form of signal. Reference --------- Zhong, X., Prekumar, A. B., and Madhukumar, A. S., "Particle filtering for acoustic source tracking in impulsive noise with alpha-stable process", IEEE Sensors Journal, Feb.... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SignalYielder:
"""Generating and yielding signals. See the reference for definition and form of signal. Reference --------- Zhong, X., Prekumar, A. B., and Madhukumar, A. S., "Particle filtering for acoustic source tracking in impulsive noise with alpha-stable process", IEEE Sensors Journal, Feb. 2013, Vol. 1... | the_stack_v2_python_sparse | signalyielder.py | qrqiuren/particle | train | 5 |
0ad0e087b5794c4e6fa536447cfd3b7a71a79818 | [
"self.wifi_mac = wifi_mac\nself.id = id\nself.serial = serial\nself.pin = pin",
"if dictionary is None:\n return None\nwifi_mac = dictionary.get('wifiMac')\nid = dictionary.get('id')\nserial = dictionary.get('serial')\npin = dictionary.get('pin')\nreturn cls(wifi_mac, id, serial, pin)"
] | <|body_start_0|>
self.wifi_mac = wifi_mac
self.id = id
self.serial = serial
self.pin = pin
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
wifi_mac = dictionary.get('wifiMac')
id = dictionary.get('id')
serial = dictionary.ge... | Implementation of the 'wipeNetworkSmDevice' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be wiped. id (string): The id of the device to be wiped. serial (string): The serial of the device to be wiped. pin (int): The pin number (a six digit value) for wiping a mac... | WipeNetworkSmDeviceModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WipeNetworkSmDeviceModel:
"""Implementation of the 'wipeNetworkSmDevice' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be wiped. id (string): The id of the device to be wiped. serial (string): The serial of the device to be wiped. pin (int):... | stack_v2_sparse_classes_75kplus_train_069221 | 2,124 | permissive | [
{
"docstring": "Constructor for the WipeNetworkSmDeviceModel class",
"name": "__init__",
"signature": "def __init__(self, wifi_mac=None, id=None, serial=None, pin=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representat... | 2 | stack_v2_sparse_classes_30k_train_035580 | Implement the Python class `WipeNetworkSmDeviceModel` described below.
Class description:
Implementation of the 'wipeNetworkSmDevice' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be wiped. id (string): The id of the device to be wiped. serial (string): The seria... | Implement the Python class `WipeNetworkSmDeviceModel` described below.
Class description:
Implementation of the 'wipeNetworkSmDevice' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be wiped. id (string): The id of the device to be wiped. serial (string): The seria... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class WipeNetworkSmDeviceModel:
"""Implementation of the 'wipeNetworkSmDevice' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be wiped. id (string): The id of the device to be wiped. serial (string): The serial of the device to be wiped. pin (int):... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WipeNetworkSmDeviceModel:
"""Implementation of the 'wipeNetworkSmDevice' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be wiped. id (string): The id of the device to be wiped. serial (string): The serial of the device to be wiped. pin (int): The pin numb... | the_stack_v2_python_sparse | meraki_sdk/models/wipe_network_sm_device_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
aba10745d92b974d920aaf4fd3118041e5186fdc | [
"self.cache = {}\nrecord = defaultdict(list)\nfor x, y in richer:\n record[y].append(x)\nresult = []\nfor i in xrange(len(quiet)):\n result.append(self.helper(record, i, quiet))\nreturn result",
"if idx not in record:\n return idx\nif idx not in self.cache:\n r = idx\n for i in xrange(len(record[id... | <|body_start_0|>
self.cache = {}
record = defaultdict(list)
for x, y in richer:
record[y].append(x)
result = []
for i in xrange(len(quiet)):
result.append(self.helper(record, i, quiet))
return result
<|end_body_0|>
<|body_start_1|>
if idx ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def loudAndRich(self, richer, quiet):
""":type richer: List[List[int]] :type quiet: List[int] :rtype: List[int]"""
<|body_0|>
def helper(self, record, idx, quiet):
"""return index of person that is richer than idx and is the least quiet"""
<|body_1|... | stack_v2_sparse_classes_75kplus_train_069222 | 1,952 | no_license | [
{
"docstring": ":type richer: List[List[int]] :type quiet: List[int] :rtype: List[int]",
"name": "loudAndRich",
"signature": "def loudAndRich(self, richer, quiet)"
},
{
"docstring": "return index of person that is richer than idx and is the least quiet",
"name": "helper",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_039462 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def loudAndRich(self, richer, quiet): :type richer: List[List[int]] :type quiet: List[int] :rtype: List[int]
- def helper(self, record, idx, quiet): return index of person that i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def loudAndRich(self, richer, quiet): :type richer: List[List[int]] :type quiet: List[int] :rtype: List[int]
- def helper(self, record, idx, quiet): return index of person that i... | ee79d3437cf47b26a4bca0ec798dc54d7b623453 | <|skeleton|>
class Solution:
def loudAndRich(self, richer, quiet):
""":type richer: List[List[int]] :type quiet: List[int] :rtype: List[int]"""
<|body_0|>
def helper(self, record, idx, quiet):
"""return index of person that is richer than idx and is the least quiet"""
<|body_1|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def loudAndRich(self, richer, quiet):
""":type richer: List[List[int]] :type quiet: List[int] :rtype: List[int]"""
self.cache = {}
record = defaultdict(list)
for x, y in richer:
record[y].append(x)
result = []
for i in xrange(len(quiet)):
... | the_stack_v2_python_sparse | Algorithm/Python/851. Loud and Rich.py | WuLC/LeetCode | train | 29 | |
b3e87975a505a0082bf88f5c44bd6a39ca71666a | [
"super(SentinelClient, self).__init__(server, params, backend)\nself._client_write = None\nself._client_read = None\nself._connection_string = server",
"try:\n connection_params = constring.split('/')\n master_name = connection_params[0]\n servers = [host_port.split(':') for host_port in connection_param... | <|body_start_0|>
super(SentinelClient, self).__init__(server, params, backend)
self._client_write = None
self._client_read = None
self._connection_string = server
<|end_body_0|>
<|body_start_1|>
try:
connection_params = constring.split('/')
master_name = ... | Sentinel client object extending django-redis DefaultClient | SentinelClient | [
"MIT",
"LGPL-2.1-or-later",
"LGPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentinelClient:
"""Sentinel client object extending django-redis DefaultClient"""
def __init__(self, server, params, backend):
"""Slightly different logic than connection to multiple Redis servers. Reserve only one write and read descriptors, as they will be closed on exit anyway."""... | stack_v2_sparse_classes_75kplus_train_069223 | 5,721 | permissive | [
{
"docstring": "Slightly different logic than connection to multiple Redis servers. Reserve only one write and read descriptors, as they will be closed on exit anyway.",
"name": "__init__",
"signature": "def __init__(self, server, params, backend)"
},
{
"docstring": "Parse connection string in f... | 5 | stack_v2_sparse_classes_30k_train_041446 | Implement the Python class `SentinelClient` described below.
Class description:
Sentinel client object extending django-redis DefaultClient
Method signatures and docstrings:
- def __init__(self, server, params, backend): Slightly different logic than connection to multiple Redis servers. Reserve only one write and re... | Implement the Python class `SentinelClient` described below.
Class description:
Sentinel client object extending django-redis DefaultClient
Method signatures and docstrings:
- def __init__(self, server, params, backend): Slightly different logic than connection to multiple Redis servers. Reserve only one write and re... | 2d708bd0d869d391456e0fb8d644af3b9f031acf | <|skeleton|>
class SentinelClient:
"""Sentinel client object extending django-redis DefaultClient"""
def __init__(self, server, params, backend):
"""Slightly different logic than connection to multiple Redis servers. Reserve only one write and read descriptors, as they will be closed on exit anyway."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SentinelClient:
"""Sentinel client object extending django-redis DefaultClient"""
def __init__(self, server, params, backend):
"""Slightly different logic than connection to multiple Redis servers. Reserve only one write and read descriptors, as they will be closed on exit anyway."""
supe... | the_stack_v2_python_sparse | itsm/component/data/sentinel.py | TencentBlueKing/bk-itsm | train | 100 |
731bfd429312fdc84c8a4cb85f6ec57cbfa537db | [
"self.population = population\nself.selection = selection\nself.crossover = crossover\nself.mutation = mutation\nself.fun_fitness = fun_fitness",
"self.population.initialize()\nfor i in range(0, gen):\n fitness, _ = self.population.fitness(fun_evaluation, self.fun_fitness)\n self.selection.select(self.popul... | <|body_start_0|>
self.population = population
self.selection = selection
self.crossover = crossover
self.mutation = mutation
self.fun_fitness = fun_fitness
<|end_body_0|>
<|body_start_1|>
self.population.initialize()
for i in range(0, gen):
fitness, _... | Simple Genetic Algorithm | GA | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GA:
"""Simple Genetic Algorithm"""
def __init__(self, population, selection, crossover, mutation, fun_fitness=lambda x: np.arctan(-x) + np.pi):
"""fun_fitness: fitness based on objective values. minimize the objective by default"""
<|body_0|>
def run(self, fun_evaluation... | stack_v2_sparse_classes_75kplus_train_069224 | 1,255 | permissive | [
{
"docstring": "fun_fitness: fitness based on objective values. minimize the objective by default",
"name": "__init__",
"signature": "def __init__(self, population, selection, crossover, mutation, fun_fitness=lambda x: np.arctan(-x) + np.pi)"
},
{
"docstring": "solve the problem based on Simple ... | 2 | null | Implement the Python class `GA` described below.
Class description:
Simple Genetic Algorithm
Method signatures and docstrings:
- def __init__(self, population, selection, crossover, mutation, fun_fitness=lambda x: np.arctan(-x) + np.pi): fun_fitness: fitness based on objective values. minimize the objective by defaul... | Implement the Python class `GA` described below.
Class description:
Simple Genetic Algorithm
Method signatures and docstrings:
- def __init__(self, population, selection, crossover, mutation, fun_fitness=lambda x: np.arctan(-x) + np.pi): fun_fitness: fitness based on objective values. minimize the objective by defaul... | a25b03a4e654bdf3c468fffc36efc5b1b6d3c158 | <|skeleton|>
class GA:
"""Simple Genetic Algorithm"""
def __init__(self, population, selection, crossover, mutation, fun_fitness=lambda x: np.arctan(-x) + np.pi):
"""fun_fitness: fitness based on objective values. minimize the objective by default"""
<|body_0|>
def run(self, fun_evaluation... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GA:
"""Simple Genetic Algorithm"""
def __init__(self, population, selection, crossover, mutation, fun_fitness=lambda x: np.arctan(-x) + np.pi):
"""fun_fitness: fitness based on objective values. minimize the objective by default"""
self.population = population
self.selection = sel... | the_stack_v2_python_sparse | GA/GA.py | zxhyJack/opt | train | 0 |
6c07884cb9cf653755ceee5748d26b379c236eaf | [
"author = get_object_or_404(models.Author, id=author_id)\ndata = {'author': author, 'form': forms.AuthorForm(instance=author)}\nreturn TemplateResponse(request, 'author/edit_author.html', data)",
"author = get_object_or_404(models.Author, id=author_id)\nform = forms.AuthorForm(request.POST, request.FILES, instanc... | <|body_start_0|>
author = get_object_or_404(models.Author, id=author_id)
data = {'author': author, 'form': forms.AuthorForm(instance=author)}
return TemplateResponse(request, 'author/edit_author.html', data)
<|end_body_0|>
<|body_start_1|>
author = get_object_or_404(models.Author, id=au... | edit author info | EditAuthor | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EditAuthor:
"""edit author info"""
def get(self, request, author_id):
"""info about a book"""
<|body_0|>
def post(self, request, author_id):
"""edit a author cool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
author = get_object_or_404(models.... | stack_v2_sparse_classes_75kplus_train_069225 | 3,215 | no_license | [
{
"docstring": "info about a book",
"name": "get",
"signature": "def get(self, request, author_id)"
},
{
"docstring": "edit a author cool",
"name": "post",
"signature": "def post(self, request, author_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021906 | Implement the Python class `EditAuthor` described below.
Class description:
edit author info
Method signatures and docstrings:
- def get(self, request, author_id): info about a book
- def post(self, request, author_id): edit a author cool | Implement the Python class `EditAuthor` described below.
Class description:
edit author info
Method signatures and docstrings:
- def get(self, request, author_id): info about a book
- def post(self, request, author_id): edit a author cool
<|skeleton|>
class EditAuthor:
"""edit author info"""
def get(self, r... | 0f8da5b738047f3c34d60d93f59bdedd8f797224 | <|skeleton|>
class EditAuthor:
"""edit author info"""
def get(self, request, author_id):
"""info about a book"""
<|body_0|>
def post(self, request, author_id):
"""edit a author cool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EditAuthor:
"""edit author info"""
def get(self, request, author_id):
"""info about a book"""
author = get_object_or_404(models.Author, id=author_id)
data = {'author': author, 'form': forms.AuthorForm(instance=author)}
return TemplateResponse(request, 'author/edit_author.h... | the_stack_v2_python_sparse | bookwyrm/views/author.py | bookwyrm-social/bookwyrm | train | 1,398 |
26414571f4b8a9629940400cbeff1387fdfe08db | [
"self.path1 = path\nself.path2 = path2\nself.d1 = defaultdict(str)\nself.d2 = defaultdict(int)\nself.dfinal = defaultdict(list)\nself.analyze_files()",
"for line in file_reading_gen(self.path1, 4, sep='|', header=True):\n self.d1[line[1]] = line[3]\n self.d2[line[1]] += +1\nself.dfinal = {k: [self.d1[k], se... | <|body_start_0|>
self.path1 = path
self.path2 = path2
self.d1 = defaultdict(str)
self.d2 = defaultdict(int)
self.dfinal = defaultdict(list)
self.analyze_files()
<|end_body_0|>
<|body_start_1|>
for line in file_reading_gen(self.path1, 4, sep='|', header=True):
... | Instructor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Instructor:
def __init__(self, path, path2):
"""self function"""
<|body_0|>
def analyze_files(self):
"""File analyze function. amost of the operetions are performed here"""
<|body_1|>
def pretty_print(self):
"""prints prettytable"""
<|bod... | stack_v2_sparse_classes_75kplus_train_069226 | 6,468 | no_license | [
{
"docstring": "self function",
"name": "__init__",
"signature": "def __init__(self, path, path2)"
},
{
"docstring": "File analyze function. amost of the operetions are performed here",
"name": "analyze_files",
"signature": "def analyze_files(self)"
},
{
"docstring": "prints pret... | 3 | null | Implement the Python class `Instructor` described below.
Class description:
Implement the Instructor class.
Method signatures and docstrings:
- def __init__(self, path, path2): self function
- def analyze_files(self): File analyze function. amost of the operetions are performed here
- def pretty_print(self): prints p... | Implement the Python class `Instructor` described below.
Class description:
Implement the Instructor class.
Method signatures and docstrings:
- def __init__(self, path, path2): self function
- def analyze_files(self): File analyze function. amost of the operetions are performed here
- def pretty_print(self): prints p... | 9fae4c459f4718411530c9917f30c03b05a4d753 | <|skeleton|>
class Instructor:
def __init__(self, path, path2):
"""self function"""
<|body_0|>
def analyze_files(self):
"""File analyze function. amost of the operetions are performed here"""
<|body_1|>
def pretty_print(self):
"""prints prettytable"""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Instructor:
def __init__(self, path, path2):
"""self function"""
self.path1 = path
self.path2 = path2
self.d1 = defaultdict(str)
self.d2 = defaultdict(int)
self.dfinal = defaultdict(list)
self.analyze_files()
def analyze_files(self):
"""File... | the_stack_v2_python_sparse | HW10_Ameya_Desai.py | Ameya221/hello-world | train | 0 | |
63cfb61ea82d11af274acd160ae070c6992fb9d6 | [
"self._deferred = deferred\nself._buff = []\nself._uid = None\nself._key = createKey()",
"if not self._uid:\n if not definition.validateSuffix(line):\n raise ValueError('Received address suffix is not valid.')\n self._uid = line\n self.transport.write('{0}{1}{1}'.format(dumpCertReq(createCertReq(s... | <|body_start_0|>
self._deferred = deferred
self._buff = []
self._uid = None
self._key = createKey()
<|end_body_0|>
<|body_start_1|>
if not self._uid:
if not definition.validateSuffix(line):
raise ValueError('Received address suffix is not valid.')
... | Protocol which is used by a client to retrieve a new UID and certificate for a machine. | _SSLClientProtocol | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _SSLClientProtocol:
"""Protocol which is used by a client to retrieve a new UID and certificate for a machine."""
def __init__(self, deferred):
"""Initialize SSLClientProtocol. @param deferred: Deferred which should be called with the received UID, certificate and private key. @type ... | stack_v2_sparse_classes_75kplus_train_069227 | 18,143 | permissive | [
{
"docstring": "Initialize SSLClientProtocol. @param deferred: Deferred which should be called with the received UID, certificate and private key. @type deferred: Deferred",
"name": "__init__",
"signature": "def __init__(self, deferred)"
},
{
"docstring": "Callback which is called by twisted whe... | 3 | stack_v2_sparse_classes_30k_train_024018 | Implement the Python class `_SSLClientProtocol` described below.
Class description:
Protocol which is used by a client to retrieve a new UID and certificate for a machine.
Method signatures and docstrings:
- def __init__(self, deferred): Initialize SSLClientProtocol. @param deferred: Deferred which should be called w... | Implement the Python class `_SSLClientProtocol` described below.
Class description:
Protocol which is used by a client to retrieve a new UID and certificate for a machine.
Method signatures and docstrings:
- def __init__(self, deferred): Initialize SSLClientProtocol. @param deferred: Deferred which should be called w... | c277efd809fce8f0f18b009fb3b9c7f785cc3739 | <|skeleton|>
class _SSLClientProtocol:
"""Protocol which is used by a client to retrieve a new UID and certificate for a machine."""
def __init__(self, deferred):
"""Initialize SSLClientProtocol. @param deferred: Deferred which should be called with the received UID, certificate and private key. @type ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _SSLClientProtocol:
"""Protocol which is used by a client to retrieve a new UID and certificate for a machine."""
def __init__(self, deferred):
"""Initialize SSLClientProtocol. @param deferred: Deferred which should be called with the received UID, certificate and private key. @type deferred: Def... | the_stack_v2_python_sparse | framework/core/machine.py | LCROBOT/rce | train | 0 |
11e94eeb40ae1fa9cfed981bf3ec3dca7011550c | [
"def backtrace(s, visited, path):\n repeat = []\n if len(path) == len(s):\n res.append(''.join(path))\n return\n for i in range(0, len(s)):\n if s[i] in repeat or visited[i] == True:\n continue\n path.append(s[i])\n repeat.append(s[i])\n visited[i] = Tru... | <|body_start_0|>
def backtrace(s, visited, path):
repeat = []
if len(path) == len(s):
res.append(''.join(path))
return
for i in range(0, len(s)):
if s[i] in repeat or visited[i] == True:
continue
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def permutation(self, s):
""":type s: str :rtype: List[str]"""
<|body_0|>
def permutation(self, s):
""":type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def backtrace(s, visited, path):
repeat = []
... | stack_v2_sparse_classes_75kplus_train_069228 | 1,998 | no_license | [
{
"docstring": ":type s: str :rtype: List[str]",
"name": "permutation",
"signature": "def permutation(self, s)"
},
{
"docstring": ":type s: str :rtype: List[str]",
"name": "permutation",
"signature": "def permutation(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_025403 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permutation(self, s): :type s: str :rtype: List[str]
- def permutation(self, s): :type s: str :rtype: List[str] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permutation(self, s): :type s: str :rtype: List[str]
- def permutation(self, s): :type s: str :rtype: List[str]
<|skeleton|>
class Solution:
def permutation(self, s):
... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def permutation(self, s):
""":type s: str :rtype: List[str]"""
<|body_0|>
def permutation(self, s):
""":type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def permutation(self, s):
""":type s: str :rtype: List[str]"""
def backtrace(s, visited, path):
repeat = []
if len(path) == len(s):
res.append(''.join(path))
return
for i in range(0, len(s)):
if s[i] ... | the_stack_v2_python_sparse | 剑指 Offer 38. 字符串的排列.py | yangyuxiang1996/leetcode | train | 0 | |
8665338f7d30dd5317ae9f0a28e287f17106eea3 | [
"args = parser.parse_args()\ntask_id = args.get('task_id')\nrely_task_id = args.get('rely_task_id')\nrequest_id = args.get('request_id')\nsubmitter = args.get('submitter')\npgnum = args.get('pgnum')\nif not pgnum:\n pgnum = 1\noptions = {'page': pgnum, 'task_id': task_id, 'rely_task_id': rely_task_id, 'request_i... | <|body_start_0|>
args = parser.parse_args()
task_id = args.get('task_id')
rely_task_id = args.get('rely_task_id')
request_id = args.get('request_id')
submitter = args.get('submitter')
pgnum = args.get('pgnum')
if not pgnum:
pgnum = 1
options = ... | LogTask | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogTask:
def get(self):
"""获取任务日志信息 --- tags: - logs summary: Add a new pet to the store parameters: - in: query name: task_id type: string description: 任务id - in: query name: rely_task_id type: string description: 依赖任务id - in: query name: pgnum type: int description: 页码 - name: submitte... | stack_v2_sparse_classes_75kplus_train_069229 | 4,993 | no_license | [
{
"docstring": "获取任务日志信息 --- tags: - logs summary: Add a new pet to the store parameters: - in: query name: task_id type: string description: 任务id - in: query name: rely_task_id type: string description: 依赖任务id - in: query name: pgnum type: int description: 页码 - name: submitter type: string in: query descriptio... | 2 | null | Implement the Python class `LogTask` described below.
Class description:
Implement the LogTask class.
Method signatures and docstrings:
- def get(self): 获取任务日志信息 --- tags: - logs summary: Add a new pet to the store parameters: - in: query name: task_id type: string description: 任务id - in: query name: rely_task_id typ... | Implement the Python class `LogTask` described below.
Class description:
Implement the LogTask class.
Method signatures and docstrings:
- def get(self): 获取任务日志信息 --- tags: - logs summary: Add a new pet to the store parameters: - in: query name: task_id type: string description: 任务id - in: query name: rely_task_id typ... | d25871dc66dfbd9f04e3d4d95843e39de286cfc8 | <|skeleton|>
class LogTask:
def get(self):
"""获取任务日志信息 --- tags: - logs summary: Add a new pet to the store parameters: - in: query name: task_id type: string description: 任务id - in: query name: rely_task_id type: string description: 依赖任务id - in: query name: pgnum type: int description: 页码 - name: submitte... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LogTask:
def get(self):
"""获取任务日志信息 --- tags: - logs summary: Add a new pet to the store parameters: - in: query name: task_id type: string description: 任务id - in: query name: rely_task_id type: string description: 依赖任务id - in: query name: pgnum type: int description: 页码 - name: submitter type: string... | the_stack_v2_python_sparse | app/main/base/apis/task_logs.py | zcl-organization/naguan | train | 0 | |
81568dc2bb21ab0a42087a4a17a118f8f9673a7f | [
"if not root:\n return True\nnLeft = self.NodeDepth(root.left)\nnRight = self.NodeDepth(root.right)\nif nLeft - nRight > 1 or nRight - nLeft > 1:\n return False\nreturn self.isBalanced(root.left) and self.isBalanced(root.right)",
"if not node:\n return 0\nreturn max(self.NodeDepth(node.left), self.NodeDe... | <|body_start_0|>
if not root:
return True
nLeft = self.NodeDepth(root.left)
nRight = self.NodeDepth(root.right)
if nLeft - nRight > 1 or nRight - nLeft > 1:
return False
return self.isBalanced(root.left) and self.isBalanced(root.right)
<|end_body_0|>
<|bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isBalanced(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def NodeDepth(self, node):
"""DP获取树的节点深度，同104题 :type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return ... | stack_v2_sparse_classes_75kplus_train_069230 | 1,232 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isBalanced",
"signature": "def isBalanced(self, root)"
},
{
"docstring": "DP获取树的节点深度，同104题 :type root: TreeNode :rtype: int",
"name": "NodeDepth",
"signature": "def NodeDepth(self, node)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010069 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isBalanced(self, root): :type root: TreeNode :rtype: bool
- def NodeDepth(self, node): DP获取树的节点深度，同104题 :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isBalanced(self, root): :type root: TreeNode :rtype: bool
- def NodeDepth(self, node): DP获取树的节点深度，同104题 :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
de... | f012740215568768794a019153af0b6e4c77b91b | <|skeleton|>
class Solution:
def isBalanced(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def NodeDepth(self, node):
"""DP获取树的节点深度，同104题 :type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isBalanced(self, root):
""":type root: TreeNode :rtype: bool"""
if not root:
return True
nLeft = self.NodeDepth(root.left)
nRight = self.NodeDepth(root.right)
if nLeft - nRight > 1 or nRight - nLeft > 1:
return False
return ... | the_stack_v2_python_sparse | No.110_BalancedBinaryTree.py | wh279813/LeetCode | train | 0 | |
5e5f8576e7a302675499af2023afb21453ddaad7 | [
"self.total = num_rows * num_columns\nself.row_names = row_index_names\nif row_index_names:\n data_frame = pd.DataFrame(index=np.arange(num_rows), columns=['index'] + column_names)\n data_frame['index'] = row_index_names\n self.row_index_to_row_name_map = self.map_row_names()\nelse:\n data_frame = pd.Da... | <|body_start_0|>
self.total = num_rows * num_columns
self.row_names = row_index_names
if row_index_names:
data_frame = pd.DataFrame(index=np.arange(num_rows), columns=['index'] + column_names)
data_frame['index'] = row_index_names
self.row_index_to_row_name_ma... | Datatable object synced with a server session that updates on the bokeh server every time update_table is called. | DataTable | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataTable:
"""Datatable object synced with a server session that updates on the bokeh server every time update_table is called."""
def __init__(self, num_rows: int, num_columns: int, column_names: list, bokeh_document: Optional[BokehDocument], row_index_names: list=None):
""":param n... | stack_v2_sparse_classes_75kplus_train_069231 | 14,891 | permissive | [
{
"docstring": ":param num_rows: number of records in the table :param num_columns: number of columns to create :param column_names: list containing column headers :param bokeh_document: bokeh document to which to add the table if provided :param row_index_names: list containing unique index names for each reco... | 3 | stack_v2_sparse_classes_30k_train_038228 | Implement the Python class `DataTable` described below.
Class description:
Datatable object synced with a server session that updates on the bokeh server every time update_table is called.
Method signatures and docstrings:
- def __init__(self, num_rows: int, num_columns: int, column_names: list, bokeh_document: Optio... | Implement the Python class `DataTable` described below.
Class description:
Datatable object synced with a server session that updates on the bokeh server every time update_table is called.
Method signatures and docstrings:
- def __init__(self, num_rows: int, num_columns: int, column_names: list, bokeh_document: Optio... | 5a406e657082b6a4f6e4bf48f0e46e085cb1e351 | <|skeleton|>
class DataTable:
"""Datatable object synced with a server session that updates on the bokeh server every time update_table is called."""
def __init__(self, num_rows: int, num_columns: int, column_names: list, bokeh_document: Optional[BokehDocument], row_index_names: list=None):
""":param n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataTable:
"""Datatable object synced with a server session that updates on the bokeh server every time update_table is called."""
def __init__(self, num_rows: int, num_columns: int, column_names: list, bokeh_document: Optional[BokehDocument], row_index_names: list=None):
""":param num_rows: numb... | the_stack_v2_python_sparse | TrainingExtensions/common/src/python/aimet_common/bokeh_plots.py | quic/aimet | train | 1,676 |
1cc1487eb70f0cbeac5b58fa51dde279d08579ce | [
"MD = '100'\nops, cts = tu.splitMD(MD)\nassert ops == ['M']\nassert cts == [100]",
"MD = '48T42G8'\nops, cts = tu.splitMD(MD)\nassert ops == ['M', 'X', 'M', 'X', 'M']\nassert cts == [48, 1, 42, 1, 8]",
"MD = '56^ACG45'\nops, cts = tu.splitMD(MD)\nassert ops == ['M', 'D', 'M']\nassert cts == [56, 3, 45]",
"MD ... | <|body_start_0|>
MD = '100'
ops, cts = tu.splitMD(MD)
assert ops == ['M']
assert cts == [100]
<|end_body_0|>
<|body_start_1|>
MD = '48T42G8'
ops, cts = tu.splitMD(MD)
assert ops == ['M', 'X', 'M', 'X', 'M']
assert cts == [48, 1, 42, 1, 8]
<|end_body_1|>
... | TestSplitMD | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSplitMD:
def test_splitMD(self):
"""Easy case- full match"""
<|body_0|>
def test_with_mismatches(self):
"""MD tag with mismatches in it"""
<|body_1|>
def test_with_deletion(self):
"""MD tag with deletions in it"""
<|body_2|>
def ... | stack_v2_sparse_classes_75kplus_train_069232 | 992 | permissive | [
{
"docstring": "Easy case- full match",
"name": "test_splitMD",
"signature": "def test_splitMD(self)"
},
{
"docstring": "MD tag with mismatches in it",
"name": "test_with_mismatches",
"signature": "def test_with_mismatches(self)"
},
{
"docstring": "MD tag with deletions in it",
... | 4 | stack_v2_sparse_classes_30k_train_037992 | Implement the Python class `TestSplitMD` described below.
Class description:
Implement the TestSplitMD class.
Method signatures and docstrings:
- def test_splitMD(self): Easy case- full match
- def test_with_mismatches(self): MD tag with mismatches in it
- def test_with_deletion(self): MD tag with deletions in it
- d... | Implement the Python class `TestSplitMD` described below.
Class description:
Implement the TestSplitMD class.
Method signatures and docstrings:
- def test_splitMD(self): Easy case- full match
- def test_with_mismatches(self): MD tag with mismatches in it
- def test_with_deletion(self): MD tag with deletions in it
- d... | 8014faed5f982e5e106ec05239e47d65878e76c3 | <|skeleton|>
class TestSplitMD:
def test_splitMD(self):
"""Easy case- full match"""
<|body_0|>
def test_with_mismatches(self):
"""MD tag with mismatches in it"""
<|body_1|>
def test_with_deletion(self):
"""MD tag with deletions in it"""
<|body_2|>
def ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestSplitMD:
def test_splitMD(self):
"""Easy case- full match"""
MD = '100'
ops, cts = tu.splitMD(MD)
assert ops == ['M']
assert cts == [100]
def test_with_mismatches(self):
"""MD tag with mismatches in it"""
MD = '48T42G8'
ops, cts = tu.spl... | the_stack_v2_python_sparse | testing_suite/test_splitMD.py | kopardev/TALON | train | 0 | |
4c2a1444247262272dd7b14a9c8ff112d330332f | [
"if not self.root:\n self.root = Node(value)\n\ndef add_helper(root):\n if value < root.value:\n if root.left is None:\n root.left = Node(value)\n else:\n add_helper(root.left)\n elif value > root.value:\n if root.right is None:\n root.right = Node(valu... | <|body_start_0|>
if not self.root:
self.root = Node(value)
def add_helper(root):
if value < root.value:
if root.left is None:
root.left = Node(value)
else:
add_helper(root.left)
elif value > root... | Binary Search Tree class. Inherits from BinaryTree. | BinarySearchTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinarySearchTree:
"""Binary Search Tree class. Inherits from BinaryTree."""
def add(self, value):
"""Add a value to the tree Args: value (any): value to add"""
<|body_0|>
def contains(self, value):
"""Checks if given value exists in the tree Args: value (any): va... | stack_v2_sparse_classes_75kplus_train_069233 | 3,725 | no_license | [
{
"docstring": "Add a value to the tree Args: value (any): value to add",
"name": "add",
"signature": "def add(self, value)"
},
{
"docstring": "Checks if given value exists in the tree Args: value (any): value to check Returns: bool: True if value exists",
"name": "contains",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_006385 | Implement the Python class `BinarySearchTree` described below.
Class description:
Binary Search Tree class. Inherits from BinaryTree.
Method signatures and docstrings:
- def add(self, value): Add a value to the tree Args: value (any): value to add
- def contains(self, value): Checks if given value exists in the tree ... | Implement the Python class `BinarySearchTree` described below.
Class description:
Binary Search Tree class. Inherits from BinaryTree.
Method signatures and docstrings:
- def add(self, value): Add a value to the tree Args: value (any): value to add
- def contains(self, value): Checks if given value exists in the tree ... | d923132849f799985440dd5c510e932d731b82d1 | <|skeleton|>
class BinarySearchTree:
"""Binary Search Tree class. Inherits from BinaryTree."""
def add(self, value):
"""Add a value to the tree Args: value (any): value to add"""
<|body_0|>
def contains(self, value):
"""Checks if given value exists in the tree Args: value (any): va... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BinarySearchTree:
"""Binary Search Tree class. Inherits from BinaryTree."""
def add(self, value):
"""Add a value to the tree Args: value (any): value to add"""
if not self.root:
self.root = Node(value)
def add_helper(root):
if value < root.value:
... | the_stack_v2_python_sparse | python/data_structures/tree/tree.py | okayjones/data-structures-and-algorithms | train | 0 |
9e61d3ba723e396ab2899ec04aa876bbca17b467 | [
"for id, op in vars(cls).items():\n if isinstance(op, UnaryOperation) and op.is_valid(operator, operand):\n return op.build(operand)",
"for id, op in vars(cls).items():\n if isinstance(op, UnaryOperation) and op.operator is operator:\n return op",
"for id, op in vars(cls).items():\n if ty... | <|body_start_0|>
for id, op in vars(cls).items():
if isinstance(op, UnaryOperation) and op.is_valid(operator, operand):
return op.build(operand)
<|end_body_0|>
<|body_start_1|>
for id, op in vars(cls).items():
if isinstance(op, UnaryOperation) and op.operator is ... | UnaryOp | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnaryOp:
def validate_type(cls, operator: Operator, operand: IType) -> Optional[UnaryOperation]:
"""Gets a unary operation given the operator and the operand type. :param operator: unary operator :param operand: type of the operand :return: The operation if exists. None otherwise; :rtype... | stack_v2_sparse_classes_75kplus_train_069234 | 1,937 | permissive | [
{
"docstring": "Gets a unary operation given the operator and the operand type. :param operator: unary operator :param operand: type of the operand :return: The operation if exists. None otherwise; :rtype: UnaryOperation or None",
"name": "validate_type",
"signature": "def validate_type(cls, operator: O... | 3 | stack_v2_sparse_classes_30k_train_046659 | Implement the Python class `UnaryOp` described below.
Class description:
Implement the UnaryOp class.
Method signatures and docstrings:
- def validate_type(cls, operator: Operator, operand: IType) -> Optional[UnaryOperation]: Gets a unary operation given the operator and the operand type. :param operator: unary opera... | Implement the Python class `UnaryOp` described below.
Class description:
Implement the UnaryOp class.
Method signatures and docstrings:
- def validate_type(cls, operator: Operator, operand: IType) -> Optional[UnaryOperation]: Gets a unary operation given the operator and the operand type. :param operator: unary opera... | e4ef340744b5bd25ade26f847eac50789b97f3e9 | <|skeleton|>
class UnaryOp:
def validate_type(cls, operator: Operator, operand: IType) -> Optional[UnaryOperation]:
"""Gets a unary operation given the operator and the operand type. :param operator: unary operator :param operand: type of the operand :return: The operation if exists. None otherwise; :rtype... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UnaryOp:
def validate_type(cls, operator: Operator, operand: IType) -> Optional[UnaryOperation]:
"""Gets a unary operation given the operator and the operand type. :param operator: unary operator :param operand: type of the operand :return: The operation if exists. None otherwise; :rtype: UnaryOperati... | the_stack_v2_python_sparse | boa3/model/operation/unaryop.py | DanPopa46/neo3-boa | train | 0 | |
208f18b877d83e98f5c728a926808e43aa01fde2 | [
"if not client:\n client = utils.create_datastore_client()\nself.kind = kind\nself.client = client\nself.id_field = id_field",
"if not entity_id and (not make_new):\n raise ValueError('entity_id is None and make_new is False')\nif not entity_id:\n entity = datastore.Entity(self._get_key(utils.get_id()))\... | <|body_start_0|>
if not client:
client = utils.create_datastore_client()
self.kind = kind
self.client = client
self.id_field = id_field
<|end_body_0|>
<|body_start_1|>
if not entity_id and (not make_new):
raise ValueError('entity_id is None and make_new i... | Base class for a Database service that stores some kind of entities using Google Cloud Datastore for storage. New datastore Entity objects must be created using get(make_new=True). The datastore Client will attempt to infer credentials based on host environment. See https://cloud.google.com/docs/authentication/producti... | BaseDatabase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseDatabase:
"""Base class for a Database service that stores some kind of entities using Google Cloud Datastore for storage. New datastore Entity objects must be created using get(make_new=True). The datastore Client will attempt to infer credentials based on host environment. See https://cloud... | stack_v2_sparse_classes_75kplus_train_069235 | 5,117 | permissive | [
{
"docstring": "Constructs an BaseDatabase. Args: kind: Kind of entities stored client: Client to communicate with Datastore. id_field: Name of the ID field of an entity as a string. Every operation checks if id_field is not already a field in the entity. If not, it will be added to the entity with the value of... | 5 | stack_v2_sparse_classes_30k_val_000222 | Implement the Python class `BaseDatabase` described below.
Class description:
Base class for a Database service that stores some kind of entities using Google Cloud Datastore for storage. New datastore Entity objects must be created using get(make_new=True). The datastore Client will attempt to infer credentials based... | Implement the Python class `BaseDatabase` described below.
Class description:
Base class for a Database service that stores some kind of entities using Google Cloud Datastore for storage. New datastore Entity objects must be created using get(make_new=True). The datastore Client will attempt to infer credentials based... | 6b32c869f426a8a5ba1b99edd324cc0c77bbd4ad | <|skeleton|>
class BaseDatabase:
"""Base class for a Database service that stores some kind of entities using Google Cloud Datastore for storage. New datastore Entity objects must be created using get(make_new=True). The datastore Client will attempt to infer credentials based on host environment. See https://cloud... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseDatabase:
"""Base class for a Database service that stores some kind of entities using Google Cloud Datastore for storage. New datastore Entity objects must be created using get(make_new=True). The datastore Client will attempt to infer credentials based on host environment. See https://cloud.google.com/d... | the_stack_v2_python_sparse | import-automation/import-progress-dashboard-api/app/service/base_database.py | wh1210/data | train | 1 |
a2d5ba4a37c7f1b6b066eaa2b252e070df19ea64 | [
"super().__init__()\nself.q_proj = nn.Linear(q_dim, h_dim)\nself.s_proj = nn.Linear(s_dim, h_dim)\nself.linear = nn.Linear(h_dim, 1)\nself.out = nn.Linear(s_dim, out_dim)",
"q_proj = self.q_proj(q).unsqueeze(2)\ns_proj = self.s_proj(s).unsqueeze(1)\nout = torch.tanh(q_proj + s_proj)\nattn_score = self.linear(out)... | <|body_start_0|>
super().__init__()
self.q_proj = nn.Linear(q_dim, h_dim)
self.s_proj = nn.Linear(s_dim, h_dim)
self.linear = nn.Linear(h_dim, 1)
self.out = nn.Linear(s_dim, out_dim)
<|end_body_0|>
<|body_start_1|>
q_proj = self.q_proj(q).unsqueeze(2)
s_proj = se... | Bahdanau attention score = v*tanh(W1*q + W2*s) | AdditiveAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdditiveAttention:
"""Bahdanau attention score = v*tanh(W1*q + W2*s)"""
def __init__(self, q_dim, s_dim, h_dim, out_dim):
"""params: q_dim: query dim s_dim: source dim h_dim: attn hidden dim out_dim: final out dim"""
<|body_0|>
def forward(self, q, s, mask):
"""q... | stack_v2_sparse_classes_75kplus_train_069236 | 4,057 | no_license | [
{
"docstring": "params: q_dim: query dim s_dim: source dim h_dim: attn hidden dim out_dim: final out dim",
"name": "__init__",
"signature": "def __init__(self, q_dim, s_dim, h_dim, out_dim)"
},
{
"docstring": "q: [B, q_len, q_dim] s: [B, s_len, s_dim] mask: [B, 1, s_len]",
"name": "forward",... | 2 | stack_v2_sparse_classes_30k_train_047338 | Implement the Python class `AdditiveAttention` described below.
Class description:
Bahdanau attention score = v*tanh(W1*q + W2*s)
Method signatures and docstrings:
- def __init__(self, q_dim, s_dim, h_dim, out_dim): params: q_dim: query dim s_dim: source dim h_dim: attn hidden dim out_dim: final out dim
- def forward... | Implement the Python class `AdditiveAttention` described below.
Class description:
Bahdanau attention score = v*tanh(W1*q + W2*s)
Method signatures and docstrings:
- def __init__(self, q_dim, s_dim, h_dim, out_dim): params: q_dim: query dim s_dim: source dim h_dim: attn hidden dim out_dim: final out dim
- def forward... | 54dcd23112d452b856e4f8000cf697d352cfec05 | <|skeleton|>
class AdditiveAttention:
"""Bahdanau attention score = v*tanh(W1*q + W2*s)"""
def __init__(self, q_dim, s_dim, h_dim, out_dim):
"""params: q_dim: query dim s_dim: source dim h_dim: attn hidden dim out_dim: final out dim"""
<|body_0|>
def forward(self, q, s, mask):
"""q... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AdditiveAttention:
"""Bahdanau attention score = v*tanh(W1*q + W2*s)"""
def __init__(self, q_dim, s_dim, h_dim, out_dim):
"""params: q_dim: query dim s_dim: source dim h_dim: attn hidden dim out_dim: final out dim"""
super().__init__()
self.q_proj = nn.Linear(q_dim, h_dim)
... | the_stack_v2_python_sparse | models/rnn/attention.py | khanrc/pt.seq2seq | train | 3 |
b24b6ef3b75a05ec0e17f4a57ff9b8d434e42e2d | [
"code = Utils.code_to_symbol(code)\ncalc_date = Utils.to_date(calc_date)\nttm_fin_data_latest = Utils.get_ttm_fin_basic_data(code, calc_date)\nif ttm_fin_data_latest is None:\n return None\ntry:\n pre_date = datetime.datetime(calc_date.year - 1, calc_date.month, calc_date.day)\nexcept ValueError:\n pre_dat... | <|body_start_0|>
code = Utils.code_to_symbol(code)
calc_date = Utils.to_date(calc_date)
ttm_fin_data_latest = Utils.get_ttm_fin_basic_data(code, calc_date)
if ttm_fin_data_latest is None:
return None
try:
pre_date = datetime.datetime(calc_date.year - 1, ca... | 成长类因子 -------- 包含：npg_ttm(净利润增长率_TTM), opg_ttm(营业收入增长率_TTM) -------- | Growth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Growth:
"""成长类因子 -------- 包含：npg_ttm(净利润增长率_TTM), opg_ttm(营业收入增长率_TTM) --------"""
def _calc_factor_loading(cls, code, calc_date):
"""计算指定日期、指定个股的成长因子，包含npg_ttm, opg_ttm Parameters: -------- :param code: str 个股代码，如600000或SH600000 :param calc_date: datetime-like or str 计算日期，格式YYYY-MM-... | stack_v2_sparse_classes_75kplus_train_069237 | 7,265 | no_license | [
{
"docstring": "计算指定日期、指定个股的成长因子，包含npg_ttm, opg_ttm Parameters: -------- :param code: str 个股代码，如600000或SH600000 :param calc_date: datetime-like or str 计算日期，格式YYYY-MM-DD, YYYYMMDD :return: pd.Series -------- 成长类因子值 0. id: 证券代码 1. npg_ttm: 净利润增长率_TTM 2. opg_ttm: 营业收入增长率_TTM 若计算失败, 返回None",
"name": "_calc_fact... | 3 | stack_v2_sparse_classes_30k_train_035739 | Implement the Python class `Growth` described below.
Class description:
成长类因子 -------- 包含：npg_ttm(净利润增长率_TTM), opg_ttm(营业收入增长率_TTM) --------
Method signatures and docstrings:
- def _calc_factor_loading(cls, code, calc_date): 计算指定日期、指定个股的成长因子，包含npg_ttm, opg_ttm Parameters: -------- :param code: str 个股代码，如600000或SH6000... | Implement the Python class `Growth` described below.
Class description:
成长类因子 -------- 包含：npg_ttm(净利润增长率_TTM), opg_ttm(营业收入增长率_TTM) --------
Method signatures and docstrings:
- def _calc_factor_loading(cls, code, calc_date): 计算指定日期、指定个股的成长因子，包含npg_ttm, opg_ttm Parameters: -------- :param code: str 个股代码，如600000或SH6000... | c796951a7200af5ea247a505bbc7d456f43f9922 | <|skeleton|>
class Growth:
"""成长类因子 -------- 包含：npg_ttm(净利润增长率_TTM), opg_ttm(营业收入增长率_TTM) --------"""
def _calc_factor_loading(cls, code, calc_date):
"""计算指定日期、指定个股的成长因子，包含npg_ttm, opg_ttm Parameters: -------- :param code: str 个股代码，如600000或SH600000 :param calc_date: datetime-like or str 计算日期，格式YYYY-MM-... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Growth:
"""成长类因子 -------- 包含：npg_ttm(净利润增长率_TTM), opg_ttm(营业收入增长率_TTM) --------"""
def _calc_factor_loading(cls, code, calc_date):
"""计算指定日期、指定个股的成长因子，包含npg_ttm, opg_ttm Parameters: -------- :param code: str 个股代码，如600000或SH600000 :param calc_date: datetime-like or str 计算日期，格式YYYY-MM-DD, YYYYMMDD ... | the_stack_v2_python_sparse | src/factors/Growth.py | fan1018wen/MultiFactor | train | 0 |
6c534ab421dd312248fcb969e0c085ccd8f7d7b9 | [
"if freezer_type is not FreezerPropertyFreezer:\n assert issubclass(freezer_type, Freezer)\n if not on_freeze is on_thaw is do_nothing:\n raise Exception(\"You've passed a `freezer_type` argument, so you're not allowed to pass `on_freeze` or `on_thaw` arguments. The freeze/thaw handlers should be defin... | <|body_start_0|>
if freezer_type is not FreezerPropertyFreezer:
assert issubclass(freezer_type, Freezer)
if not on_freeze is on_thaw is do_nothing:
raise Exception("You've passed a `freezer_type` argument, so you're not allowed to pass `on_freeze` or `on_thaw` arguments. ... | A property which lazy-creates a freezer. A freezer is used as a context manager to "freeze" and "thaw" an object. See documentation of `Freezer` in this package for more info. The advantages of using a `FreezerProperty` instead of creating a freezer attribute for each instance: - The `.on_freeze` and `.on_thaw` decorat... | FreezerProperty | [
"BSD-3-Clause",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FreezerProperty:
"""A property which lazy-creates a freezer. A freezer is used as a context manager to "freeze" and "thaw" an object. See documentation of `Freezer` in this package for more info. The advantages of using a `FreezerProperty` instead of creating a freezer attribute for each instance... | stack_v2_sparse_classes_75kplus_train_069238 | 3,931 | permissive | [
{
"docstring": "Create the `FreezerProperty`. All arguments are optional: You may pass in freeze/thaw handlers as `on_freeze` and `on_thaw`, but you don't have to. You may choose a specific freezer type to use as `freezer_type`, in which case you can't use either the `on_freeze`/`on_thaw` arguments nor the deco... | 4 | stack_v2_sparse_classes_30k_train_006932 | Implement the Python class `FreezerProperty` described below.
Class description:
A property which lazy-creates a freezer. A freezer is used as a context manager to "freeze" and "thaw" an object. See documentation of `Freezer` in this package for more info. The advantages of using a `FreezerProperty` instead of creatin... | Implement the Python class `FreezerProperty` described below.
Class description:
A property which lazy-creates a freezer. A freezer is used as a context manager to "freeze" and "thaw" an object. See documentation of `Freezer` in this package for more info. The advantages of using a `FreezerProperty` instead of creatin... | cb9ef64b48f1d03275484d707dc5079b6701ad0c | <|skeleton|>
class FreezerProperty:
"""A property which lazy-creates a freezer. A freezer is used as a context manager to "freeze" and "thaw" an object. See documentation of `Freezer` in this package for more info. The advantages of using a `FreezerProperty` instead of creating a freezer attribute for each instance... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FreezerProperty:
"""A property which lazy-creates a freezer. A freezer is used as a context manager to "freeze" and "thaw" an object. See documentation of `Freezer` in this package for more info. The advantages of using a `FreezerProperty` instead of creating a freezer attribute for each instance: - The `.on_... | the_stack_v2_python_sparse | python_toolbox/freezing/freezer_property.py | cool-RR/python_toolbox | train | 130 |
bd0113a620af4243dc01c49558ab8b5d01229913 | [
"if nums is None or target is None:\n return []\nlength = len(nums)\nif length < 2:\n return []\nrvt = sorted(enumerate(nums), key=lambda x: x[1])\nleft = 0\nright = length - 1\nwhile left < right:\n sum = rvt[left][1] + rvt[right][1]\n if sum == target:\n return sorted([rvt[left][0], rvt[right][... | <|body_start_0|>
if nums is None or target is None:
return []
length = len(nums)
if length < 2:
return []
rvt = sorted(enumerate(nums), key=lambda x: x[1])
left = 0
right = length - 1
while left < right:
sum = rvt[left][1] + rvt... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def findTarget(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if ... | stack_v2_sparse_classes_75kplus_train_069239 | 1,777 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def twoSum(self, nums, target)"
},
{
"docstring": ":type root: TreeNode :type k: int :rtype: bool",
"name": "findTarget",
"signature": "def findTarget(self, root, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021405 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def findTarget(self, root, k): :type root: TreeNode :type k: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def findTarget(self, root, k): :type root: TreeNode :type k: int :rtype: bool
<|skele... | c1f27c0cec80585095ce98a678ab85079e1a4c46 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def findTarget(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
if nums is None or target is None:
return []
length = len(nums)
if length < 2:
return []
rvt = sorted(enumerate(nums), key=lambda x: x[1])
... | the_stack_v2_python_sparse | Leetcode/1_TwoSum.py | wbq9224/Leetcode_Python | train | 0 | |
f0a1f12694e99ba46af996e444ef32d7ebce0b22 | [
"if model._meta.app_label == 'researcherquery':\n return 'safedb'\nreturn None",
"if model._meta.app_label == 'researcherquery':\n return 'safedb'\nreturn None",
"if obj1._meta.app_label == 'researcherquery' and obj2._meta.app_label == 'researcherquery':\n return True\nreturn None",
"if app_label == ... | <|body_start_0|>
if model._meta.app_label == 'researcherquery':
return 'safedb'
return None
<|end_body_0|>
<|body_start_1|>
if model._meta.app_label == 'researcherquery':
return 'safedb'
return None
<|end_body_1|>
<|body_start_2|>
if obj1._meta.app_label... | A router to control all database operations on models in the researcherquery application. | ResearcherqueryRouter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResearcherqueryRouter:
"""A router to control all database operations on models in the researcherquery application."""
def db_for_read(self, model, **hints):
"""Attempts to read researcherquery models go to safedb."""
<|body_0|>
def db_for_write(self, model, **hints):
... | stack_v2_sparse_classes_75kplus_train_069240 | 1,295 | no_license | [
{
"docstring": "Attempts to read researcherquery models go to safedb.",
"name": "db_for_read",
"signature": "def db_for_read(self, model, **hints)"
},
{
"docstring": "Attempts to write researcherquery models go to safedb.",
"name": "db_for_write",
"signature": "def db_for_write(self, mod... | 4 | stack_v2_sparse_classes_30k_train_046843 | Implement the Python class `ResearcherqueryRouter` described below.
Class description:
A router to control all database operations on models in the researcherquery application.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read researcherquery models go to safedb.
- def db_for... | Implement the Python class `ResearcherqueryRouter` described below.
Class description:
A router to control all database operations on models in the researcherquery application.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read researcherquery models go to safedb.
- def db_for... | 685c2b9d40fb24ca1735352846a39fdf5d3728eb | <|skeleton|>
class ResearcherqueryRouter:
"""A router to control all database operations on models in the researcherquery application."""
def db_for_read(self, model, **hints):
"""Attempts to read researcherquery models go to safedb."""
<|body_0|>
def db_for_write(self, model, **hints):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResearcherqueryRouter:
"""A router to control all database operations on models in the researcherquery application."""
def db_for_read(self, model, **hints):
"""Attempts to read researcherquery models go to safedb."""
if model._meta.app_label == 'researcherquery':
return 'safe... | the_stack_v2_python_sparse | researcherquery/router.py | guekling/ifs4205team1 | train | 0 |
6c09bcd71368d11f3c310a97834a919bd6d36c5b | [
"if name in dir(self):\n raise ValueError(f'{name} is already registered')\nelif inspect.isclass(item) and issubclass(item, SimpleBase):\n setattr(self, name, item)\nelif isinstance(item, SimpleBase):\n setattr(self, name, item.__class__)\nelse:\n raise TypeError(f'item must be a SimpleBase')\nreturn se... | <|body_start_0|>
if name in dir(self):
raise ValueError(f'{name} is already registered')
elif inspect.isclass(item) and issubclass(item, SimpleBase):
setattr(self, name, item)
elif isinstance(item, SimpleBase):
setattr(self, name, item.__class__)
else:... | Stores base classes in siMpLify. | SimpleBases | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleBases:
"""Stores base classes in siMpLify."""
def register(self, name: str, item: Union[Type, object]) -> None:
"""[summary] Args: name (str): [description] item (Union[Type, object]): [description] Raises: ValueError: [description] TypeError: [description] Returns: [type]: [de... | stack_v2_sparse_classes_75kplus_train_069241 | 10,643 | permissive | [
{
"docstring": "[summary] Args: name (str): [description] item (Union[Type, object]): [description] Raises: ValueError: [description] TypeError: [description] Returns: [type]: [description]",
"name": "register",
"signature": "def register(self, name: str, item: Union[Type, object]) -> None"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_017759 | Implement the Python class `SimpleBases` described below.
Class description:
Stores base classes in siMpLify.
Method signatures and docstrings:
- def register(self, name: str, item: Union[Type, object]) -> None: [summary] Args: name (str): [description] item (Union[Type, object]): [description] Raises: ValueError: [d... | Implement the Python class `SimpleBases` described below.
Class description:
Stores base classes in siMpLify.
Method signatures and docstrings:
- def register(self, name: str, item: Union[Type, object]) -> None: [summary] Args: name (str): [description] item (Union[Type, object]): [description] Raises: ValueError: [d... | 5302da8bf4944ac518d22cc37c181e5a09baaabe | <|skeleton|>
class SimpleBases:
"""Stores base classes in siMpLify."""
def register(self, name: str, item: Union[Type, object]) -> None:
"""[summary] Args: name (str): [description] item (Union[Type, object]): [description] Raises: ValueError: [description] TypeError: [description] Returns: [type]: [de... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleBases:
"""Stores base classes in siMpLify."""
def register(self, name: str, item: Union[Type, object]) -> None:
"""[summary] Args: name (str): [description] item (Union[Type, object]): [description] Raises: ValueError: [description] TypeError: [description] Returns: [type]: [description]"""... | the_stack_v2_python_sparse | simplify/core/base.py | WithPrecedent/simplify | train | 1 |
5f252570411540b0b71662f845169d8b9454ae95 | [
"if type(capacity) != int or capacity <= 0:\n raise Exception('Capacity Error')\n'@helpDescription(When the CircularQueue class is initialized, a list is initalized which acts as the queue. The capacity, count (number of items in the queue), head (index of the first item in the queue) and tail (index of the last... | <|body_start_0|>
if type(capacity) != int or capacity <= 0:
raise Exception('Capacity Error')
'@helpDescription(When the CircularQueue class is initialized, a list is initalized which acts as the queue. The capacity, count (number of items in the queue), head (index of the first item in the ... | @helpDescription(The capacity, or the maximum length allowed in the queue, is passed in as an integer when the CircularQueue class is initialized.) | CircularQueue | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CircularQueue:
"""@helpDescription(The capacity, or the maximum length allowed in the queue, is passed in as an integer when the CircularQueue class is initialized.)"""
def __init__(self, capacity):
"""@helpDescription(The value passed in for capacity of a queue must be a positive in... | stack_v2_sparse_classes_75kplus_train_069242 | 6,664 | no_license | [
{
"docstring": "@helpDescription(The value passed in for capacity of a queue must be a positive integer. If the value is not, an exception with the line 'Capacity Error' is rasied.)",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": "@helpDescription(If the queue... | 5 | stack_v2_sparse_classes_30k_test_002623 | Implement the Python class `CircularQueue` described below.
Class description:
@helpDescription(The capacity, or the maximum length allowed in the queue, is passed in as an integer when the CircularQueue class is initialized.)
Method signatures and docstrings:
- def __init__(self, capacity): @helpDescription(The valu... | Implement the Python class `CircularQueue` described below.
Class description:
@helpDescription(The capacity, or the maximum length allowed in the queue, is passed in as an integer when the CircularQueue class is initialized.)
Method signatures and docstrings:
- def __init__(self, capacity): @helpDescription(The valu... | 688638f6c3fa3d31c4f8be6391147d773e1aa9dd | <|skeleton|>
class CircularQueue:
"""@helpDescription(The capacity, or the maximum length allowed in the queue, is passed in as an integer when the CircularQueue class is initialized.)"""
def __init__(self, capacity):
"""@helpDescription(The value passed in for capacity of a queue must be a positive in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CircularQueue:
"""@helpDescription(The capacity, or the maximum length allowed in the queue, is passed in as an integer when the CircularQueue class is initialized.)"""
def __init__(self, capacity):
"""@helpDescription(The value passed in for capacity of a queue must be a positive integer. If the... | the_stack_v2_python_sparse | python/py_queue_class/queue_class.py | cskamil/PcExParser | train | 1 |
8a8847b00bf0ad4a96fbb9c153776356939fcf58 | [
"length = len(nums)\nleft, right = (0, length - 1)\nwhile left <= right:\n if nums[left] == val:\n nums[left] = nums[right]\n right -= 1\n else:\n left += 1\nreturn left",
"slow = 0\nfor fast in range(len(nums)):\n if nums[fast] != val:\n nums[slow] = nums[fast]\n slow ... | <|body_start_0|>
length = len(nums)
left, right = (0, length - 1)
while left <= right:
if nums[left] == val:
nums[left] = nums[right]
right -= 1
else:
left += 1
return left
<|end_body_0|>
<|body_start_1|>
sl... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeElement1(self, nums: List[int], val: int) -> int:
"""First of all, use two points $left, $right which points to the beginnning and the end. As long as $left <= $right, we keeping doing the followings. If the left num equals the target $val, copy the right num to the l... | stack_v2_sparse_classes_75kplus_train_069243 | 2,401 | no_license | [
{
"docstring": "First of all, use two points $left, $right which points to the beginnning and the end. As long as $left <= $right, we keeping doing the followings. If the left num equals the target $val, copy the right num to the left num and decrease $right by one. Otherwise, increase $left by one. In the end,... | 2 | stack_v2_sparse_classes_30k_train_041901 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElement1(self, nums: List[int], val: int) -> int: First of all, use two points $left, $right which points to the beginnning and the end. As long as $left <= $right, we ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElement1(self, nums: List[int], val: int) -> int: First of all, use two points $left, $right which points to the beginnning and the end. As long as $left <= $right, we ... | 9bdbe3232faedc5b23caeb0c47baeb0bda9d313d | <|skeleton|>
class Solution:
def removeElement1(self, nums: List[int], val: int) -> int:
"""First of all, use two points $left, $right which points to the beginnning and the end. As long as $left <= $right, we keeping doing the followings. If the left num equals the target $val, copy the right num to the l... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def removeElement1(self, nums: List[int], val: int) -> int:
"""First of all, use two points $left, $right which points to the beginnning and the end. As long as $left <= $right, we keeping doing the followings. If the left num equals the target $val, copy the right num to the left num and de... | the_stack_v2_python_sparse | TwoPointers/27_RemoveElement.py | ideaqiwang/leetcode | train | 0 | |
f5f7eacb720d20b1c48c8905d5c4f3f16125de62 | [
"def get_list_element(nlis):\n res = []\n for elem in nlis:\n if elem.isInteger():\n res.append(elem.getInteger())\n else:\n res.extend(get_list_element(elem.getList()))\n return res\nself.iterator = get_list_element(nestedList)",
"if self.hasNext:\n res = self.iter... | <|body_start_0|>
def get_list_element(nlis):
res = []
for elem in nlis:
if elem.isInteger():
res.append(elem.getInteger())
else:
res.extend(get_list_element(elem.getList()))
return res
self.iterat... | NestedIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NestedIterator:
def __init__(self, nestedList):
"""Initialize your data structure here. :type nestedList: List[NestedInteger]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|e... | stack_v2_sparse_classes_75kplus_train_069244 | 2,774 | no_license | [
{
"docstring": "Initialize your data structure here. :type nestedList: List[NestedInteger]",
"name": "__init__",
"signature": "def __init__(self, nestedList)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"nam... | 3 | stack_v2_sparse_classes_30k_train_019154 | Implement the Python class `NestedIterator` described below.
Class description:
Implement the NestedIterator class.
Method signatures and docstrings:
- def __init__(self, nestedList): Initialize your data structure here. :type nestedList: List[NestedInteger]
- def next(self): :rtype: int
- def hasNext(self): :rtype: ... | Implement the Python class `NestedIterator` described below.
Class description:
Implement the NestedIterator class.
Method signatures and docstrings:
- def __init__(self, nestedList): Initialize your data structure here. :type nestedList: List[NestedInteger]
- def next(self): :rtype: int
- def hasNext(self): :rtype: ... | ee59b82125f100970c842d5e1245287c484d6649 | <|skeleton|>
class NestedIterator:
def __init__(self, nestedList):
"""Initialize your data structure here. :type nestedList: List[NestedInteger]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|e... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NestedIterator:
def __init__(self, nestedList):
"""Initialize your data structure here. :type nestedList: List[NestedInteger]"""
def get_list_element(nlis):
res = []
for elem in nlis:
if elem.isInteger():
res.append(elem.getInteger())... | the_stack_v2_python_sparse | _CodeTopics/LeetCode/201-400/000341/000341.py | BIAOXYZ/variousCodes | train | 0 | |
a3b5b67bccd916f09f37fb18587f6d9f64adf8da | [
"super().__init__()\nif backbone not in FLEXUNET_BACKBONE.register_dict:\n raise ValueError(f'invalid model_name {backbone} found, must be one of {FLEXUNET_BACKBONE.register_dict.keys()}.')\nif spatial_dims not in (2, 3):\n raise ValueError('spatial_dims can only be 2 or 3.')\nencoder = FLEXUNET_BACKBONE.regi... | <|body_start_0|>
super().__init__()
if backbone not in FLEXUNET_BACKBONE.register_dict:
raise ValueError(f'invalid model_name {backbone} found, must be one of {FLEXUNET_BACKBONE.register_dict.keys()}.')
if spatial_dims not in (2, 3):
raise ValueError('spatial_dims can onl... | A flexible implementation of UNet-like encoder-decoder architecture. | FlexibleUNet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlexibleUNet:
"""A flexible implementation of UNet-like encoder-decoder architecture."""
def __init__(self, in_channels: int, out_channels: int, backbone: str, pretrained: bool=False, decoder_channels: tuple=(256, 128, 64, 32, 16), spatial_dims: int=2, norm: str | tuple=('batch', {'eps': 0.0... | stack_v2_sparse_classes_75kplus_train_069245 | 14,147 | permissive | [
{
"docstring": "A flexible implement of UNet, in which the backbone/encoder can be replaced with any efficient network. Currently the input must have a 2 or 3 spatial dimension and the spatial size of each dimension must be a multiple of 32 if is_pad parameter is False. Please notice each output of backbone mus... | 2 | stack_v2_sparse_classes_30k_train_007669 | Implement the Python class `FlexibleUNet` described below.
Class description:
A flexible implementation of UNet-like encoder-decoder architecture.
Method signatures and docstrings:
- def __init__(self, in_channels: int, out_channels: int, backbone: str, pretrained: bool=False, decoder_channels: tuple=(256, 128, 64, 3... | Implement the Python class `FlexibleUNet` described below.
Class description:
A flexible implementation of UNet-like encoder-decoder architecture.
Method signatures and docstrings:
- def __init__(self, in_channels: int, out_channels: int, backbone: str, pretrained: bool=False, decoder_channels: tuple=(256, 128, 64, 3... | e48c3e2c741fa3fc705c4425d17ac4a5afac6c47 | <|skeleton|>
class FlexibleUNet:
"""A flexible implementation of UNet-like encoder-decoder architecture."""
def __init__(self, in_channels: int, out_channels: int, backbone: str, pretrained: bool=False, decoder_channels: tuple=(256, 128, 64, 32, 16), spatial_dims: int=2, norm: str | tuple=('batch', {'eps': 0.0... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FlexibleUNet:
"""A flexible implementation of UNet-like encoder-decoder architecture."""
def __init__(self, in_channels: int, out_channels: int, backbone: str, pretrained: bool=False, decoder_channels: tuple=(256, 128, 64, 32, 16), spatial_dims: int=2, norm: str | tuple=('batch', {'eps': 0.001, 'momentum... | the_stack_v2_python_sparse | monai/networks/nets/flexible_unet.py | Project-MONAI/MONAI | train | 4,805 |
af76bd56c70a5114c2653097226efa9b0f2f7067 | [
"n = len(stones)\nmemo = [[[-1] * 2 for _ in range(n)] for j in range(n)]\nsm = sum(stones)\n\ndef helper(l, r, ID, left):\n if r < l:\n return 0\n if memo[l][r][ID] != -1:\n return memo[l][r][ID]\n ne = 1 if ID == 0 else 0\n if ID == 1:\n memo[l][r][ID] = max(left - stones[l] + hel... | <|body_start_0|>
n = len(stones)
memo = [[[-1] * 2 for _ in range(n)] for j in range(n)]
sm = sum(stones)
def helper(l, r, ID, left):
if r < l:
return 0
if memo[l][r][ID] != -1:
return memo[l][r][ID]
ne = 1 if ID == 0 e... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def stoneGameVIITLE(self, stones):
""":type stones: List[int] :rtype: int"""
<|body_0|>
def stoneGameVII(self, stones):
""":type stones: List[int] :rtype: int"""
<|body_1|>
def stoneGameVIIDP(self, stones):
""":type stones: List[int] :r... | stack_v2_sparse_classes_75kplus_train_069246 | 4,232 | no_license | [
{
"docstring": ":type stones: List[int] :rtype: int",
"name": "stoneGameVIITLE",
"signature": "def stoneGameVIITLE(self, stones)"
},
{
"docstring": ":type stones: List[int] :rtype: int",
"name": "stoneGameVII",
"signature": "def stoneGameVII(self, stones)"
},
{
"docstring": ":typ... | 3 | stack_v2_sparse_classes_30k_train_021344 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def stoneGameVIITLE(self, stones): :type stones: List[int] :rtype: int
- def stoneGameVII(self, stones): :type stones: List[int] :rtype: int
- def stoneGameVIIDP(self, stones): :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def stoneGameVIITLE(self, stones): :type stones: List[int] :rtype: int
- def stoneGameVII(self, stones): :type stones: List[int] :rtype: int
- def stoneGameVIIDP(self, stones): :... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def stoneGameVIITLE(self, stones):
""":type stones: List[int] :rtype: int"""
<|body_0|>
def stoneGameVII(self, stones):
""":type stones: List[int] :rtype: int"""
<|body_1|>
def stoneGameVIIDP(self, stones):
""":type stones: List[int] :r... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def stoneGameVIITLE(self, stones):
""":type stones: List[int] :rtype: int"""
n = len(stones)
memo = [[[-1] * 2 for _ in range(n)] for j in range(n)]
sm = sum(stones)
def helper(l, r, ID, left):
if r < l:
return 0
if mem... | the_stack_v2_python_sparse | S/StoneGameVII.py | bssrdf/pyleet | train | 2 | |
33a00c7915633944ff9ad5ca88e58e1f8ef8aa52 | [
"driver.get(url)\nloginButton = WebDriverWait(driver, 5, 0.5).until(EC.presence_of_element_located((By.NAME, 'username')))\nloginButton.clear()\nloginButton.send_keys(username)\ndriver.implicitly_wait(1.5)\ndriver.find_element_by_name('password').clear()\ndriver.find_element_by_name('password').send_keys(password)\... | <|body_start_0|>
driver.get(url)
loginButton = WebDriverWait(driver, 5, 0.5).until(EC.presence_of_element_located((By.NAME, 'username')))
loginButton.clear()
loginButton.send_keys(username)
driver.implicitly_wait(1.5)
driver.find_element_by_name('password').clear()
... | Action | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Action:
def loginG(self, driver, username, password, url):
""":param driver: webdriver userd :param username: login name required :param password: auth password :param url: login url :return:"""
<|body_0|>
def logoutG(self, driver):
"""此时应该用户是登陆状态的 写一个类似与 login_requi... | stack_v2_sparse_classes_75kplus_train_069247 | 2,363 | no_license | [
{
"docstring": ":param driver: webdriver userd :param username: login name required :param password: auth password :param url: login url :return:",
"name": "loginG",
"signature": "def loginG(self, driver, username, password, url)"
},
{
"docstring": "此时应该用户是登陆状态的 写一个类似与 login_requied() 语法糖 装饰器 :p... | 2 | stack_v2_sparse_classes_30k_train_034018 | Implement the Python class `Action` described below.
Class description:
Implement the Action class.
Method signatures and docstrings:
- def loginG(self, driver, username, password, url): :param driver: webdriver userd :param username: login name required :param password: auth password :param url: login url :return:
-... | Implement the Python class `Action` described below.
Class description:
Implement the Action class.
Method signatures and docstrings:
- def loginG(self, driver, username, password, url): :param driver: webdriver userd :param username: login name required :param password: auth password :param url: login url :return:
-... | 508d9c5949588e66802cc06377d43be8fdc3e35d | <|skeleton|>
class Action:
def loginG(self, driver, username, password, url):
""":param driver: webdriver userd :param username: login name required :param password: auth password :param url: login url :return:"""
<|body_0|>
def logoutG(self, driver):
"""此时应该用户是登陆状态的 写一个类似与 login_requi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Action:
def loginG(self, driver, username, password, url):
""":param driver: webdriver userd :param username: login name required :param password: auth password :param url: login url :return:"""
driver.get(url)
loginButton = WebDriverWait(driver, 5, 0.5).until(EC.presence_of_element_lo... | the_stack_v2_python_sparse | EmpireCMS/Moduledriver/parameterizationG.py | Onebigbera/CrawlerTest | train | 1 | |
6713abb09de37e0f79ed7dc0233161525f0f5698 | [
"try:\n data = PolicyManager.get_object_assignments(user_id=user_id, policy_id=uuid, object_id=perimeter_id, category_id=category_id)\nexcept Exception as e:\n LOG.error(e, exc_info=True)\n return ({'result': False, 'error': str(e)}, 500)\nreturn {'object_assignments': data}",
"try:\n data_id = reques... | <|body_start_0|>
try:
data = PolicyManager.get_object_assignments(user_id=user_id, policy_id=uuid, object_id=perimeter_id, category_id=category_id)
except Exception as e:
LOG.error(e, exc_info=True)
return ({'result': False, 'error': str(e)}, 500)
return {'obj... | Endpoint for object assignment requests | ObjectAssignments | [
"Apache-2.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObjectAssignments:
"""Endpoint for object assignment requests"""
def get(self, uuid=None, perimeter_id=None, category_id=None, data_id=None, user_id=None):
"""Retrieve all object assignment or a specific one for a given policy :param uuid: uuid of the policy :param perimeter_id: uuid... | stack_v2_sparse_classes_75kplus_train_069248 | 14,093 | permissive | [
{
"docstring": "Retrieve all object assignment or a specific one for a given policy :param uuid: uuid of the policy :param perimeter_id: uuid of the object :param category_id: uuid of the object category :param data_id: uuid of the object scope :param user_id: user ID who do the request :return: { \"object_data... | 3 | stack_v2_sparse_classes_30k_train_002299 | Implement the Python class `ObjectAssignments` described below.
Class description:
Endpoint for object assignment requests
Method signatures and docstrings:
- def get(self, uuid=None, perimeter_id=None, category_id=None, data_id=None, user_id=None): Retrieve all object assignment or a specific one for a given policy ... | Implement the Python class `ObjectAssignments` described below.
Class description:
Endpoint for object assignment requests
Method signatures and docstrings:
- def get(self, uuid=None, perimeter_id=None, category_id=None, data_id=None, user_id=None): Retrieve all object assignment or a specific one for a given policy ... | daaba34fa2ed4426bc0fde359e54a5e1b872208c | <|skeleton|>
class ObjectAssignments:
"""Endpoint for object assignment requests"""
def get(self, uuid=None, perimeter_id=None, category_id=None, data_id=None, user_id=None):
"""Retrieve all object assignment or a specific one for a given policy :param uuid: uuid of the policy :param perimeter_id: uuid... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ObjectAssignments:
"""Endpoint for object assignment requests"""
def get(self, uuid=None, perimeter_id=None, category_id=None, data_id=None, user_id=None):
"""Retrieve all object assignment or a specific one for a given policy :param uuid: uuid of the policy :param perimeter_id: uuid of the objec... | the_stack_v2_python_sparse | moonv4/moon_manager/moon_manager/api/assignments.py | hashnfv/hashnfv-moon | train | 0 |
8c144b11d41557879fbd37e0a970bdbb166ef3bd | [
"super().__init__(dataset_reader, data_iterator, evaluation_command, model, batch_size)\nself.k = k\nself.threads = threads\nself.give_up = give_up\nif give_up_k_1 is None:\n self.give_up_k_1 = give_up\nelse:\n self.give_up_k_1 = give_up_k_1",
"assert self.model, 'model must be given, either to the construc... | <|body_start_0|>
super().__init__(dataset_reader, data_iterator, evaluation_command, model, batch_size)
self.k = k
self.threads = threads
self.give_up = give_up
if give_up_k_1 is None:
self.give_up_k_1 = give_up
else:
self.give_up_k_1 = give_up_k_1... | Predictor that calls the fixed-tree decoder. | AMconllPredictor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AMconllPredictor:
"""Predictor that calls the fixed-tree decoder."""
def __init__(self, dataset_reader: DatasetReader, k: int, give_up: float, threads: int=4, data_iterator: DataIterator=None, evaluation_command: BaseEvaluationCommand=None, model: Model=None, batch_size: int=64, give_up_k_1:... | stack_v2_sparse_classes_75kplus_train_069249 | 11,088 | permissive | [
{
"docstring": "Creates a predictor from an AMConllDatasetReader, optionally takes an AllenNLP model. The model can also be given later using set_model. If evaluation is required, en evaluation_command can be supplied as well. :param dataset_reader: an AMConllDatasetReader :param k: number of supertags to be us... | 2 | null | Implement the Python class `AMconllPredictor` described below.
Class description:
Predictor that calls the fixed-tree decoder.
Method signatures and docstrings:
- def __init__(self, dataset_reader: DatasetReader, k: int, give_up: float, threads: int=4, data_iterator: DataIterator=None, evaluation_command: BaseEvaluat... | Implement the Python class `AMconllPredictor` described below.
Class description:
Predictor that calls the fixed-tree decoder.
Method signatures and docstrings:
- def __init__(self, dataset_reader: DatasetReader, k: int, give_up: float, threads: int=4, data_iterator: DataIterator=None, evaluation_command: BaseEvaluat... | 81432b9e3c165f8c0efb84a23e5a0d0493717e63 | <|skeleton|>
class AMconllPredictor:
"""Predictor that calls the fixed-tree decoder."""
def __init__(self, dataset_reader: DatasetReader, k: int, give_up: float, threads: int=4, data_iterator: DataIterator=None, evaluation_command: BaseEvaluationCommand=None, model: Model=None, batch_size: int=64, give_up_k_1:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AMconllPredictor:
"""Predictor that calls the fixed-tree decoder."""
def __init__(self, dataset_reader: DatasetReader, k: int, give_up: float, threads: int=4, data_iterator: DataIterator=None, evaluation_command: BaseEvaluationCommand=None, model: Model=None, batch_size: int=64, give_up_k_1: float=None):... | the_stack_v2_python_sparse | graph_dependency_parser/components/evaluation/predictors.py | coli-saar/am-parser | train | 30 |
131ff3d947bda5c81fa027b6f071c80c28d235e3 | [
"test_env = {'OAUTH_CLIENT_ID': 'id', 'OAUTH_CLIENT_SECRET': 'shhh', 'FOUNDATION': 'foundation', 'CC_URL': 'e/f/g/h'}\nwith patch.dict(os.environ, test_env) as mock_env:\n param = parameters.SysParams()\nself.assertEqual(param, test_env)",
"make_missing = 'FOUNDATION'\ntest_env = {'OAUTH_CLIENT_ID': 'id', 'OAU... | <|body_start_0|>
test_env = {'OAUTH_CLIENT_ID': 'id', 'OAUTH_CLIENT_SECRET': 'shhh', 'FOUNDATION': 'foundation', 'CC_URL': 'e/f/g/h'}
with patch.dict(os.environ, test_env) as mock_env:
param = parameters.SysParams()
self.assertEqual(param, test_env)
<|end_body_0|>
<|body_start_1|>
... | Test basic operation of the class. | TestParams | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestParams:
"""Test basic operation of the class."""
def testParamOK(self):
"""Test the Sysparams object 'happy' path"""
<|body_0|>
def testParamMissing(self):
"""Test the Sysparams object 'sad' path"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_069250 | 1,332 | no_license | [
{
"docstring": "Test the Sysparams object 'happy' path",
"name": "testParamOK",
"signature": "def testParamOK(self)"
},
{
"docstring": "Test the Sysparams object 'sad' path",
"name": "testParamMissing",
"signature": "def testParamMissing(self)"
}
] | 2 | null | Implement the Python class `TestParams` described below.
Class description:
Test basic operation of the class.
Method signatures and docstrings:
- def testParamOK(self): Test the Sysparams object 'happy' path
- def testParamMissing(self): Test the Sysparams object 'sad' path | Implement the Python class `TestParams` described below.
Class description:
Test basic operation of the class.
Method signatures and docstrings:
- def testParamOK(self): Test the Sysparams object 'happy' path
- def testParamMissing(self): Test the Sysparams object 'sad' path
<|skeleton|>
class TestParams:
"""Tes... | 3173fd1f4e4a54a286ced2734ca30b1d9a918206 | <|skeleton|>
class TestParams:
"""Test basic operation of the class."""
def testParamOK(self):
"""Test the Sysparams object 'happy' path"""
<|body_0|>
def testParamMissing(self):
"""Test the Sysparams object 'sad' path"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestParams:
"""Test basic operation of the class."""
def testParamOK(self):
"""Test the Sysparams object 'happy' path"""
test_env = {'OAUTH_CLIENT_ID': 'id', 'OAUTH_CLIENT_SECRET': 'shhh', 'FOUNDATION': 'foundation', 'CC_URL': 'e/f/g/h'}
with patch.dict(os.environ, test_env) as mo... | the_stack_v2_python_sparse | unit_tests/test_parameters.py | halm90/cf-diff | train | 0 |
454383a4bfdd6c9891e8f6068757f54657e817cf | [
"self.facility = self.request.user.profile.instrument.facility\nself.instrument = self.request.user.profile.instrument\nself.catalog = Catalog(facility=self.facility.name, technique=self.instrument.technique, instrument=self.instrument.catalog_name, request=self.request)\nreturn super(CatalogMixin, self).dispatch(r... | <|body_start_0|>
self.facility = self.request.user.profile.instrument.facility
self.instrument = self.request.user.profile.instrument
self.catalog = Catalog(facility=self.facility.name, technique=self.instrument.technique, instrument=self.instrument.catalog_name, request=self.request)
re... | Context enhancer for the Catalog | CatalogMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CatalogMixin:
"""Context enhancer for the Catalog"""
def dispatch(self, request, *args, **kwargs):
"""First method being called Usefull for debug and set member variables"""
<|body_0|>
def get_template_names(self):
"""Let's override this function. Returns a list ... | stack_v2_sparse_classes_75kplus_train_069251 | 9,842 | no_license | [
{
"docstring": "First method being called Usefull for debug and set member variables",
"name": "dispatch",
"signature": "def dispatch(self, request, *args, **kwargs)"
},
{
"docstring": "Let's override this function. Returns a list of priority templates to render. From specific to general. facili... | 2 | stack_v2_sparse_classes_30k_train_015674 | Implement the Python class `CatalogMixin` described below.
Class description:
Context enhancer for the Catalog
Method signatures and docstrings:
- def dispatch(self, request, *args, **kwargs): First method being called Usefull for debug and set member variables
- def get_template_names(self): Let's override this func... | Implement the Python class `CatalogMixin` described below.
Class description:
Context enhancer for the Catalog
Method signatures and docstrings:
- def dispatch(self, request, *args, **kwargs): First method being called Usefull for debug and set member variables
- def get_template_names(self): Let's override this func... | 507ff81617abf583edd4ef4858985daefc0afcbe | <|skeleton|>
class CatalogMixin:
"""Context enhancer for the Catalog"""
def dispatch(self, request, *args, **kwargs):
"""First method being called Usefull for debug and set member variables"""
<|body_0|>
def get_template_names(self):
"""Let's override this function. Returns a list ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CatalogMixin:
"""Context enhancer for the Catalog"""
def dispatch(self, request, *args, **kwargs):
"""First method being called Usefull for debug and set member variables"""
self.facility = self.request.user.profile.instrument.facility
self.instrument = self.request.user.profile.i... | the_stack_v2_python_sparse | src/server/apps/catalog/views.py | bidochon/WebReduction | train | 0 |
004619dceb3e980ce9c1bd74ce32051d3cbd1c83 | [
"suff_words = {}\nfor w in words:\n n = len(w)\n for i in range(n - 1):\n tmp_w = w[n - i - 1:]\n if tmp_w not in suff_words:\n suff_words[tmp_w] = False\n suff_words[w] = True\nself.words = suff_words\nself.len = max((len(w) for w in words))\nself.queries = ''",
"self.queries +=... | <|body_start_0|>
suff_words = {}
for w in words:
n = len(w)
for i in range(n - 1):
tmp_w = w[n - i - 1:]
if tmp_w not in suff_words:
suff_words[tmp_w] = False
suff_words[w] = True
self.words = suff_words
... | StreamChecker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StreamChecker:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def query(self, letter):
""":type letter: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
suff_words = {}
for w in words:
n = len(... | stack_v2_sparse_classes_75kplus_train_069252 | 1,467 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type letter: str :rtype: bool",
"name": "query",
"signature": "def query(self, letter)"
}
] | 2 | null | Implement the Python class `StreamChecker` described below.
Class description:
Implement the StreamChecker class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def query(self, letter): :type letter: str :rtype: bool | Implement the Python class `StreamChecker` described below.
Class description:
Implement the StreamChecker class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def query(self, letter): :type letter: str :rtype: bool
<|skeleton|>
class StreamChecker:
def __init__(self, w... | 80e44f4e9d3a5b592fdebe0bf16d1df54e99991e | <|skeleton|>
class StreamChecker:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def query(self, letter):
""":type letter: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StreamChecker:
def __init__(self, words):
""":type words: List[str]"""
suff_words = {}
for w in words:
n = len(w)
for i in range(n - 1):
tmp_w = w[n - i - 1:]
if tmp_w not in suff_words:
suff_words[tmp_w] = Fal... | the_stack_v2_python_sparse | Python/1032 - Stream of Characters/1032_stream-of-characters.py | aptend/leetcode-rua | train | 2 | |
146659f63d3690b47d02d12ff2d70764a4026972 | [
"self.num_ends = {}\nself.milestones = []\nif A:\n size = 0\n for i in xrange(0, len(A), 2):\n if A[i] > 0:\n size += A[i]\n self.num_ends[size] = A[i + 1]\n self.milestones.append(size)\nself.start = 0\nself.milestone = 0",
"self.start += n\nif self.start > self.mile... | <|body_start_0|>
self.num_ends = {}
self.milestones = []
if A:
size = 0
for i in xrange(0, len(A), 2):
if A[i] > 0:
size += A[i]
self.num_ends[size] = A[i + 1]
self.milestones.append(size)
... | RLEIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.num_ends = {}
self.milestones = []
if A:
size = 0... | stack_v2_sparse_classes_75kplus_train_069253 | 997 | no_license | [
{
"docstring": ":type A: List[int]",
"name": "__init__",
"signature": "def __init__(self, A)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "next",
"signature": "def next(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_033804 | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int
<|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: Lis... | ea10ce7fe465431399e444c6ecb0b7560b17e1e4 | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
self.num_ends = {}
self.milestones = []
if A:
size = 0
for i in xrange(0, len(A), 2):
if A[i] > 0:
size += A[i]
self.num_ends[size] = A[i... | the_stack_v2_python_sparse | leetcode_python2/lc900_RLE_iterator.py | garderobin/Leetcode | train | 0 | |
a71517ecc347a27c1a1f3f922084e1fa913fab41 | [
"global dic\ndic = {}\n\ndef find(s, i, j):\n \"\"\"\n :type s: str\n :type i: int\n :rtype: str\n \"\"\"\n if j == len(s) - 1:\n dic[len(s[i:j + 1])] = s[i:j + 1]\n return\n if i == 0 and i != j:\n dic[len(s[i:j + 1])] = s[i:j + 1]\n ... | <|body_start_0|>
global dic
dic = {}
def find(s, i, j):
"""
:type s: str
:type i: int
:rtype: str
"""
if j == len(s) - 1:
dic[len(s[i:j + 1])] = s[i:j + 1]
ret... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome1(self, s):
"""Method_one : Dynamic Programming :type s: str :rtype: str"""
<|body_0|>
def longestPalindrome2(self, s):
"""Method_two : Expand Around Center :type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_75kplus_train_069254 | 1,656 | no_license | [
{
"docstring": "Method_one : Dynamic Programming :type s: str :rtype: str",
"name": "longestPalindrome1",
"signature": "def longestPalindrome1(self, s)"
},
{
"docstring": "Method_two : Expand Around Center :type s: str :rtype: str",
"name": "longestPalindrome2",
"signature": "def longest... | 2 | stack_v2_sparse_classes_30k_val_002392 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome1(self, s): Method_one : Dynamic Programming :type s: str :rtype: str
- def longestPalindrome2(self, s): Method_two : Expand Around Center :type s: str :rtyp... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome1(self, s): Method_one : Dynamic Programming :type s: str :rtype: str
- def longestPalindrome2(self, s): Method_two : Expand Around Center :type s: str :rtyp... | 030f2d48d20341a16f6ca57715ff1f06a59a20ec | <|skeleton|>
class Solution:
def longestPalindrome1(self, s):
"""Method_one : Dynamic Programming :type s: str :rtype: str"""
<|body_0|>
def longestPalindrome2(self, s):
"""Method_two : Expand Around Center :type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def longestPalindrome1(self, s):
"""Method_one : Dynamic Programming :type s: str :rtype: str"""
global dic
dic = {}
def find(s, i, j):
"""
:type s: str
:type i: int
:rtype: str
... | the_stack_v2_python_sparse | Code/Longest Palindromic Substring.py | zolars/LeetCode-Solution | train | 0 | |
78431501d605fdfece6777ab9f0739692c418e01 | [
"self.content = ''\nself.fd = None\nself.ctype = ''\nfilename = ''\nif file[0] == '/':\n filename = file[1:]\nelse:\n filename = file\ntry:\n resource = managers.resource_manager.get_resource(application_id, filename)\n if not resource:\n raise VDOM_exception('Resource not found')\n self.fd = ... | <|body_start_0|>
self.content = ''
self.fd = None
self.ctype = ''
filename = ''
if file[0] == '/':
filename = file[1:]
else:
filename = file
try:
resource = managers.resource_manager.get_resource(application_id, filename)
... | resource module class | VDOM_module_resource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VDOM_module_resource:
"""resource module class"""
def getfile(self, application_id, file):
"""read file"""
<|body_0|>
def run(self, request_object, request_type):
"""process request"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.content = ... | stack_v2_sparse_classes_75kplus_train_069255 | 2,571 | no_license | [
{
"docstring": "read file",
"name": "getfile",
"signature": "def getfile(self, application_id, file)"
},
{
"docstring": "process request",
"name": "run",
"signature": "def run(self, request_object, request_type)"
}
] | 2 | null | Implement the Python class `VDOM_module_resource` described below.
Class description:
resource module class
Method signatures and docstrings:
- def getfile(self, application_id, file): read file
- def run(self, request_object, request_type): process request | Implement the Python class `VDOM_module_resource` described below.
Class description:
resource module class
Method signatures and docstrings:
- def getfile(self, application_id, file): read file
- def run(self, request_object, request_type): process request
<|skeleton|>
class VDOM_module_resource:
"""resource mo... | cb9932f5f75d5c6d7889f26d58aee079b4127299 | <|skeleton|>
class VDOM_module_resource:
"""resource module class"""
def getfile(self, application_id, file):
"""read file"""
<|body_0|>
def run(self, request_object, request_type):
"""process request"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VDOM_module_resource:
"""resource module class"""
def getfile(self, application_id, file):
"""read file"""
self.content = ''
self.fd = None
self.ctype = ''
filename = ''
if file[0] == '/':
filename = file[1:]
else:
filename =... | the_stack_v2_python_sparse | sources/module/resource.py | VDOMBoxGroup/runtime2.0 | train | 0 |
129442ef12a0a44da273b12d30c2ccfa8ec40681 | [
"with warnings.catch_warnings():\n warnings.simplefilter('ignore')\n resolver_options = {'place': {'allow_unknown_locations': True}}\n self.geotagger = get_resolver(options=resolver_options)\n self.geotagger.load_locations()\n self.location_resolver = LocationEncoder()\nsuper().__init__(*args, **kwar... | <|body_start_0|>
with warnings.catch_warnings():
warnings.simplefilter('ignore')
resolver_options = {'place': {'allow_unknown_locations': True}}
self.geotagger = get_resolver(options=resolver_options)
self.geotagger.load_locations()
self.location_resol... | Class that will attempt to geotag a tweet. | GeoCoding | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeoCoding:
"""Class that will attempt to geotag a tweet."""
def __init__(self, *args, **kwargs) -> None:
"""Setup Carmen geotagging options, then init super."""
<|body_0|>
def process_tweet(self, tweet_json: Dict[str, Any]) -> Dict[str, Any]:
"""Attempt to geotag... | stack_v2_sparse_classes_75kplus_train_069256 | 3,134 | permissive | [
{
"docstring": "Setup Carmen geotagging options, then init super.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs) -> None"
},
{
"docstring": "Attempt to geotag the tweet data. Returns the tweet with new data if any was resolved and will set geotagged according to success ... | 2 | stack_v2_sparse_classes_30k_train_047416 | Implement the Python class `GeoCoding` described below.
Class description:
Class that will attempt to geotag a tweet.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs) -> None: Setup Carmen geotagging options, then init super.
- def process_tweet(self, tweet_json: Dict[str, Any]) -> Dict[str, An... | Implement the Python class `GeoCoding` described below.
Class description:
Class that will attempt to geotag a tweet.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs) -> None: Setup Carmen geotagging options, then init super.
- def process_tweet(self, tweet_json: Dict[str, Any]) -> Dict[str, An... | 8aec35117f943dc4579db4a448ef0bea013b3f5b | <|skeleton|>
class GeoCoding:
"""Class that will attempt to geotag a tweet."""
def __init__(self, *args, **kwargs) -> None:
"""Setup Carmen geotagging options, then init super."""
<|body_0|>
def process_tweet(self, tweet_json: Dict[str, Any]) -> Dict[str, Any]:
"""Attempt to geotag... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GeoCoding:
"""Class that will attempt to geotag a tweet."""
def __init__(self, *args, **kwargs) -> None:
"""Setup Carmen geotagging options, then init super."""
with warnings.catch_warnings():
warnings.simplefilter('ignore')
resolver_options = {'place': {'allow_unk... | the_stack_v2_python_sparse | containers/ingress/ingress/data_processing/geocode.py | martsa1/twitterELK | train | 0 |
f63f790b42b9446ca7ab69bef9b3481725721a79 | [
"ip = self.get_argument('ip')\nresponse = (yield self.get_ip_info(ip))\nif response['code'] == 0:\n self.write(response)\nelse:\n self.write('查询ip地址失败！')\nself.finish()",
"http = tornado.httpclient.AsyncHTTPClient()\nresponse = (yield http.fetch(request='http://ip.taobao.com/service/getIpInfo.php?ip={}'.for... | <|body_start_0|>
ip = self.get_argument('ip')
response = (yield self.get_ip_info(ip))
if response['code'] == 0:
self.write(response)
else:
self.write('查询ip地址失败！')
self.finish()
<|end_body_0|>
<|body_start_1|>
http = tornado.httpclient.AsyncHTTPCli... | 首页handler类 | IndexHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexHandler:
"""首页handler类"""
def get(self):
"""异步请求客户端"""
<|body_0|>
def get_ip_info(self, ip):
"""将异步web请求单独出来"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ip = self.get_argument('ip')
response = (yield self.get_ip_info(ip))
... | stack_v2_sparse_classes_75kplus_train_069257 | 2,195 | no_license | [
{
"docstring": "异步请求客户端",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "将异步web请求单独出来",
"name": "get_ip_info",
"signature": "def get_ip_info(self, ip)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008745 | Implement the Python class `IndexHandler` described below.
Class description:
首页handler类
Method signatures and docstrings:
- def get(self): 异步请求客户端
- def get_ip_info(self, ip): 将异步web请求单独出来 | Implement the Python class `IndexHandler` described below.
Class description:
首页handler类
Method signatures and docstrings:
- def get(self): 异步请求客户端
- def get_ip_info(self, ip): 将异步web请求单独出来
<|skeleton|>
class IndexHandler:
"""首页handler类"""
def get(self):
"""异步请求客户端"""
<|body_0|>
def get... | 34021339fea059ef1ba1d562cf091f3f07aeedc9 | <|skeleton|>
class IndexHandler:
"""首页handler类"""
def get(self):
"""异步请求客户端"""
<|body_0|>
def get_ip_info(self, ip):
"""将异步web请求单独出来"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IndexHandler:
"""首页handler类"""
def get(self):
"""异步请求客户端"""
ip = self.get_argument('ip')
response = (yield self.get_ip_info(ip))
if response['code'] == 0:
self.write(response)
else:
self.write('查询ip地址失败！')
self.finish()
def get_... | the_stack_v2_python_sparse | 4_异步与Websocket/06_tornado协程异步.py | Sbwillbealier/tornado_study | train | 0 |
7f81a579aabf2d2fd369b88fd0cdd0bd864d5a34 | [
"self.data_dict: typing.Dict[str, DataStruct] = {}\nself.index_dict: typing.Dict[str, int] = {}\nself.datetime: typing.Union[str, datetime] = None\n_symbol_dict.clear()\nfor k, v in _register_dict.items():\n symbol = _fetcher.fetchSymbol(_tradingday, **v.toKwargs())\n if symbol is None:\n continue\n ... | <|body_start_0|>
self.data_dict: typing.Dict[str, DataStruct] = {}
self.index_dict: typing.Dict[str, int] = {}
self.datetime: typing.Union[str, datetime] = None
_symbol_dict.clear()
for k, v in _register_dict.items():
symbol = _fetcher.fetchSymbol(_tradingday, **v.toK... | JUST FOR BACKTEST !!! | DataGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataGenerator:
"""JUST FOR BACKTEST !!!"""
def __init__(self, _tradingday: str, _register_dict: typing.Dict[str, RegisterAbstract], _symbol_dict: typing.Dict[str, typing.Set[str]], _fetcher: FetchAbstract):
"""fetch data according to market registers, and pop tick data by happentime ... | stack_v2_sparse_classes_75kplus_train_069258 | 5,578 | permissive | [
{
"docstring": "fetch data according to market registers, and pop tick data by happentime :param _tradingday: the day to fetch :param _register_dict: :param _symbol_dict:",
"name": "__init__",
"signature": "def __init__(self, _tradingday: str, _register_dict: typing.Dict[str, RegisterAbstract], _symbol_... | 2 | null | Implement the Python class `DataGenerator` described below.
Class description:
JUST FOR BACKTEST !!!
Method signatures and docstrings:
- def __init__(self, _tradingday: str, _register_dict: typing.Dict[str, RegisterAbstract], _symbol_dict: typing.Dict[str, typing.Set[str]], _fetcher: FetchAbstract): fetch data accord... | Implement the Python class `DataGenerator` described below.
Class description:
JUST FOR BACKTEST !!!
Method signatures and docstrings:
- def __init__(self, _tradingday: str, _register_dict: typing.Dict[str, RegisterAbstract], _symbol_dict: typing.Dict[str, typing.Set[str]], _fetcher: FetchAbstract): fetch data accord... | 2c4024e60b14bf630fd141ccd4c77f197b7c901a | <|skeleton|>
class DataGenerator:
"""JUST FOR BACKTEST !!!"""
def __init__(self, _tradingday: str, _register_dict: typing.Dict[str, RegisterAbstract], _symbol_dict: typing.Dict[str, typing.Set[str]], _fetcher: FetchAbstract):
"""fetch data according to market registers, and pop tick data by happentime ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataGenerator:
"""JUST FOR BACKTEST !!!"""
def __init__(self, _tradingday: str, _register_dict: typing.Dict[str, RegisterAbstract], _symbol_dict: typing.Dict[str, typing.Set[str]], _fetcher: FetchAbstract):
"""fetch data according to market registers, and pop tick data by happentime :param _tradi... | the_stack_v2_python_sparse | ParadoxTrading/EngineExt/BacktestMarketSupply.py | ppaanngggg/ParadoxTrading | train | 96 |
4eeb5f3a039348c101787a022a52a2da53770be0 | [
"super(AuViSubNet, self).__init__()\nself.rnn = nn.LSTM(in_size, hidden_size, num_layers=num_layers, dropout=dropout, bidirectional=bidirectional, batch_first=True)\nself.dropout = nn.Dropout(dropout)\nself.linear_1 = nn.Linear(hidden_size, out_size)",
"_, final_states = self.rnn(x)\nh = self.dropout(final_states... | <|body_start_0|>
super(AuViSubNet, self).__init__()
self.rnn = nn.LSTM(in_size, hidden_size, num_layers=num_layers, dropout=dropout, bidirectional=bidirectional, batch_first=True)
self.dropout = nn.Dropout(dropout)
self.linear_1 = nn.Linear(hidden_size, out_size)
<|end_body_0|>
<|body_s... | AuViSubNet | [
"GPL-1.0-or-later",
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuViSubNet:
def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False):
"""Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers of LSTMs. dropout: dropout probability bidirectional: specify usa... | stack_v2_sparse_classes_75kplus_train_069259 | 7,016 | permissive | [
{
"docstring": "Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers of LSTMs. dropout: dropout probability bidirectional: specify usage of bidirectional LSTM Output: (return value in forward) a tensor of shape (batch_size, out_size)",
"name": "__init__... | 2 | stack_v2_sparse_classes_30k_train_036335 | Implement the Python class `AuViSubNet` described below.
Class description:
Implement the AuViSubNet class.
Method signatures and docstrings:
- def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False): Args: in_size: input dimension hidden_size: hidden layer dimension num_lay... | Implement the Python class `AuViSubNet` described below.
Class description:
Implement the AuViSubNet class.
Method signatures and docstrings:
- def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False): Args: in_size: input dimension hidden_size: hidden layer dimension num_lay... | 92acc188d3a0f634de58463b6676e70df83ef808 | <|skeleton|>
class AuViSubNet:
def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False):
"""Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers of LSTMs. dropout: dropout probability bidirectional: specify usa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AuViSubNet:
def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False):
"""Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers of LSTMs. dropout: dropout probability bidirectional: specify usage of bidirect... | the_stack_v2_python_sparse | PyTorch/contrib/others/MMSA_ID2979_for_PyTorch/models/multiTask/SELF_MM.py | Ascend/ModelZoo-PyTorch | train | 23 | |
cdfcf00a2b59490e729b8733ff4471a0ea73d610 | [
"super().__init__()\nself.n_target_frames = n_target_frames\nself.loss_type = loss_type\nself.loss = None\nif loss_type == 'l1':\n self.loss = nn.L1Loss()\nelif loss_type == 'l2':\n self.loss = nn.MSELoss()\nelif loss_type == 'tversky':\n self.loss = cross_entropy_tversky_weighted_loss\nelse:\n raise Va... | <|body_start_0|>
super().__init__()
self.n_target_frames = n_target_frames
self.loss_type = loss_type
self.loss = None
if loss_type == 'l1':
self.loss = nn.L1Loss()
elif loss_type == 'l2':
self.loss = nn.MSELoss()
elif loss_type == 'tversky... | AutoregressiveCriterion | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoregressiveCriterion:
def __init__(self, n_target_frames: int=1, loss_type: str='tversky'):
"""Multi frames loss which backpropagate loss error through time"""
<|body_0|>
def forward(self, inputs, targets):
"""inputs shape is (B, T, C, H, W) where C is 23 targets ... | stack_v2_sparse_classes_75kplus_train_069260 | 5,809 | permissive | [
{
"docstring": "Multi frames loss which backpropagate loss error through time",
"name": "__init__",
"signature": "def __init__(self, n_target_frames: int=1, loss_type: str='tversky')"
},
{
"docstring": "inputs shape is (B, T, C, H, W) where C is 23 targets shape is (B, T, C, H, W) where C is 1",... | 2 | stack_v2_sparse_classes_30k_train_015644 | Implement the Python class `AutoregressiveCriterion` described below.
Class description:
Implement the AutoregressiveCriterion class.
Method signatures and docstrings:
- def __init__(self, n_target_frames: int=1, loss_type: str='tversky'): Multi frames loss which backpropagate loss error through time
- def forward(se... | Implement the Python class `AutoregressiveCriterion` described below.
Class description:
Implement the AutoregressiveCriterion class.
Method signatures and docstrings:
- def __init__(self, n_target_frames: int=1, loss_type: str='tversky'): Multi frames loss which backpropagate loss error through time
- def forward(se... | 37a273ff393e4f43c38c7fff9271218efe1d3bd1 | <|skeleton|>
class AutoregressiveCriterion:
def __init__(self, n_target_frames: int=1, loss_type: str='tversky'):
"""Multi frames loss which backpropagate loss error through time"""
<|body_0|>
def forward(self, inputs, targets):
"""inputs shape is (B, T, C, H, W) where C is 23 targets ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AutoregressiveCriterion:
def __init__(self, n_target_frames: int=1, loss_type: str='tversky'):
"""Multi frames loss which backpropagate loss error through time"""
super().__init__()
self.n_target_frames = n_target_frames
self.loss_type = loss_type
self.loss = None
... | the_stack_v2_python_sparse | PMoE/trainer/loss.py | iasbs-isg/PMoE | train | 0 | |
b1fe5806dc28bd18b47f1798b1f4e4e8b3bf12e1 | [
"if not history:\n return\nhistory = self._history_dt_fmt(dt=history)\nvalid_dates = history_dates.value[asset_type]\nif history not in valid_dates:\n known = '\\n ' + '\\n '.join(list(valid_dates))\n expl = 'known history dates'\n err = f'Unknown history date {history!r}'\n msg = f'{err}, {expl}: ... | <|body_start_0|>
if not history:
return
history = self._history_dt_fmt(dt=history)
valid_dates = history_dates.value[asset_type]
if history not in valid_dates:
known = '\n ' + '\n '.join(list(valid_dates))
expl = 'known history dates'
err... | Pass. | AssetMixins | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssetMixins:
"""Pass."""
def set_history(self, history: Union[str, datetime.timedelta, datetime.datetime], history_dates: DictValue, asset_type: str) -> str:
"""Pass."""
<|body_0|>
def _history_dt_fmt(dt: Union[str, datetime.timedelta, datetime.datetime], tmpl: str='%Y-%... | stack_v2_sparse_classes_75kplus_train_069261 | 16,427 | permissive | [
{
"docstring": "Pass.",
"name": "set_history",
"signature": "def set_history(self, history: Union[str, datetime.timedelta, datetime.datetime], history_dates: DictValue, asset_type: str) -> str"
},
{
"docstring": "Parse a string into the format used by the REST API. Args: dt: date time to parse u... | 2 | stack_v2_sparse_classes_30k_train_003728 | Implement the Python class `AssetMixins` described below.
Class description:
Pass.
Method signatures and docstrings:
- def set_history(self, history: Union[str, datetime.timedelta, datetime.datetime], history_dates: DictValue, asset_type: str) -> str: Pass.
- def _history_dt_fmt(dt: Union[str, datetime.timedelta, dat... | Implement the Python class `AssetMixins` described below.
Class description:
Pass.
Method signatures and docstrings:
- def set_history(self, history: Union[str, datetime.timedelta, datetime.datetime], history_dates: DictValue, asset_type: str) -> str: Pass.
- def _history_dt_fmt(dt: Union[str, datetime.timedelta, dat... | 8321788df279ffb7794f179a4bd8943fe1ac44c4 | <|skeleton|>
class AssetMixins:
"""Pass."""
def set_history(self, history: Union[str, datetime.timedelta, datetime.datetime], history_dates: DictValue, asset_type: str) -> str:
"""Pass."""
<|body_0|>
def _history_dt_fmt(dt: Union[str, datetime.timedelta, datetime.datetime], tmpl: str='%Y-%... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AssetMixins:
"""Pass."""
def set_history(self, history: Union[str, datetime.timedelta, datetime.datetime], history_dates: DictValue, asset_type: str) -> str:
"""Pass."""
if not history:
return
history = self._history_dt_fmt(dt=history)
valid_dates = history_dat... | the_stack_v2_python_sparse | axonius_api_client/api/json_api/assets.py | zahediss/axonius_api_client | train | 0 |
f08127dd5fe1ced51a5c5633d8edf332e04ec7f1 | [
"query = \"SELECT {1} FROM {0} WHERE {1} = '{2}'\".format(table, value, item)\ndata = QuestionerDB.fetch_one(query)\nif data:\n return (jsonify({'status': 409, 'error': '{} already exists'.format(item)}), 409)\nelse:\n return False",
"query = 'SELECT username FROM {0} WHERE meetup_id = {1}'.format(table, me... | <|body_start_0|>
query = "SELECT {1} FROM {0} WHERE {1} = '{2}'".format(table, value, item)
data = QuestionerDB.fetch_one(query)
if data:
return (jsonify({'status': 409, 'error': '{} already exists'.format(item)}), 409)
else:
return False
<|end_body_0|>
<|body_st... | This class contains validation methods | Validations | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Validations:
"""This class contains validation methods"""
def check_exist(self, table, value, item):
"""Method to check if a value exists in the database"""
<|body_0|>
def made_rsvp(self, table, meetup_id, username):
"""method to check if user made a rsvp"""
... | stack_v2_sparse_classes_75kplus_train_069262 | 2,608 | no_license | [
{
"docstring": "Method to check if a value exists in the database",
"name": "check_exist",
"signature": "def check_exist(self, table, value, item)"
},
{
"docstring": "method to check if user made a rsvp",
"name": "made_rsvp",
"signature": "def made_rsvp(self, table, meetup_id, username)"... | 6 | stack_v2_sparse_classes_30k_train_032079 | Implement the Python class `Validations` described below.
Class description:
This class contains validation methods
Method signatures and docstrings:
- def check_exist(self, table, value, item): Method to check if a value exists in the database
- def made_rsvp(self, table, meetup_id, username): method to check if use... | Implement the Python class `Validations` described below.
Class description:
This class contains validation methods
Method signatures and docstrings:
- def check_exist(self, table, value, item): Method to check if a value exists in the database
- def made_rsvp(self, table, meetup_id, username): method to check if use... | 607257db910f9b44fb4497e25de8b295cd2fcdcb | <|skeleton|>
class Validations:
"""This class contains validation methods"""
def check_exist(self, table, value, item):
"""Method to check if a value exists in the database"""
<|body_0|>
def made_rsvp(self, table, meetup_id, username):
"""method to check if user made a rsvp"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Validations:
"""This class contains validation methods"""
def check_exist(self, table, value, item):
"""Method to check if a value exists in the database"""
query = "SELECT {1} FROM {0} WHERE {1} = '{2}'".format(table, value, item)
data = QuestionerDB.fetch_one(query)
if d... | the_stack_v2_python_sparse | app/api/v2/utils/validations.py | misocho/questioner | train | 0 |
ddb40de01b1021f099a8bb44814afc55866e6ce6 | [
"self._gis = gis\nself._portal = gis._portal\nself._is_portal = self._gis.properties.isPortal\nself._workdir = tempfile.gettempdir()",
"access = kwargs.pop('access', None)\nfiles = None\nif key is None and path:\n key = os.path.basename(path)\nelif key is None and path is None:\n raise ValueError('key must ... | <|body_start_0|>
self._gis = gis
self._portal = gis._portal
self._is_portal = self._gis.properties.isPortal
self._workdir = tempfile.gettempdir()
<|end_body_0|>
<|body_start_1|>
access = kwargs.pop('access', None)
files = None
if key is None and path:
... | Helper class to manage a GIS' resources ================ =============================================================== **Argument** **Description** ---------------- --------------------------------------------------------------- gis required GIS, connection to ArcGIS Online or ArcGIS Enterprise ================ =====... | PortalResourceManager | [
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PortalResourceManager:
"""Helper class to manage a GIS' resources ================ =============================================================== **Argument** **Description** ---------------- --------------------------------------------------------------- gis required GIS, connection to ArcGIS O... | stack_v2_sparse_classes_75kplus_train_069263 | 7,275 | permissive | [
{
"docstring": "Creates helper object to manage custom roles in the GIS",
"name": "__init__",
"signature": "def __init__(self, gis)"
},
{
"docstring": "The add resource operation allows the administrator to add a file resource, for example, the organization's logo or custom banner. The resource ... | 5 | null | Implement the Python class `PortalResourceManager` described below.
Class description:
Helper class to manage a GIS' resources ================ =============================================================== **Argument** **Description** ---------------- --------------------------------------------------------------- g... | Implement the Python class `PortalResourceManager` described below.
Class description:
Helper class to manage a GIS' resources ================ =============================================================== **Argument** **Description** ---------------- --------------------------------------------------------------- g... | a874fe7e5c95196e4de68db2da0e2a05eb70e5d8 | <|skeleton|>
class PortalResourceManager:
"""Helper class to manage a GIS' resources ================ =============================================================== **Argument** **Description** ---------------- --------------------------------------------------------------- gis required GIS, connection to ArcGIS O... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PortalResourceManager:
"""Helper class to manage a GIS' resources ================ =============================================================== **Argument** **Description** ---------------- --------------------------------------------------------------- gis required GIS, connection to ArcGIS Online or ArcG... | the_stack_v2_python_sparse | arcpyenv/arcgispro-py3-clone/Lib/site-packages/arcgis/gis/admin/_resources.py | SherbazHashmi/HackathonServer | train | 3 |
3332f40223004e1be18d1012f79910850736edf9 | [
"defined_fields = self.form.used_field_names\nrequired_fields = self.form.get_required_field_names()\nmissing_fields = []\nfor field in required_fields:\n if field not in defined_fields:\n missing_fields.append(field)\nif len(missing_fields) > 0:\n raise ValidationError('The save instance handler can o... | <|body_start_0|>
defined_fields = self.form.used_field_names
required_fields = self.form.get_required_field_names()
missing_fields = []
for field in required_fields:
if field not in defined_fields:
missing_fields.append(field)
if len(missing_fields) > ... | Handler for saving the form instance | OmniFormSaveInstanceHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OmniFormSaveInstanceHandler:
"""Handler for saving the form instance"""
def assert_has_all_required_fields(self):
"""Property that determines whether or not the associated form defines all of the required fields :raises: ValidationError"""
<|body_0|>
def clean(self):
... | stack_v2_sparse_classes_75kplus_train_069264 | 47,532 | permissive | [
{
"docstring": "Property that determines whether or not the associated form defines all of the required fields :raises: ValidationError",
"name": "assert_has_all_required_fields",
"signature": "def assert_has_all_required_fields(self)"
},
{
"docstring": "Cleans the handler for saving a model ins... | 3 | stack_v2_sparse_classes_30k_train_023510 | Implement the Python class `OmniFormSaveInstanceHandler` described below.
Class description:
Handler for saving the form instance
Method signatures and docstrings:
- def assert_has_all_required_fields(self): Property that determines whether or not the associated form defines all of the required fields :raises: Valida... | Implement the Python class `OmniFormSaveInstanceHandler` described below.
Class description:
Handler for saving the form instance
Method signatures and docstrings:
- def assert_has_all_required_fields(self): Property that determines whether or not the associated form defines all of the required fields :raises: Valida... | 0c96162445f8b5ddf7f326f6b0a2e6ec239c4bd5 | <|skeleton|>
class OmniFormSaveInstanceHandler:
"""Handler for saving the form instance"""
def assert_has_all_required_fields(self):
"""Property that determines whether or not the associated form defines all of the required fields :raises: ValidationError"""
<|body_0|>
def clean(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OmniFormSaveInstanceHandler:
"""Handler for saving the form instance"""
def assert_has_all_required_fields(self):
"""Property that determines whether or not the associated form defines all of the required fields :raises: ValidationError"""
defined_fields = self.form.used_field_names
... | the_stack_v2_python_sparse | omniforms/models.py | omni-digital/omni-forms | train | 6 |
9f051cc4f04772819c8207608b1f7d5f69f4f996 | [
"super(FPN, self).__init__()\nself.inner_blocks = []\nself.layer_blocks = []\nfor idx, in_channels in enumerate(in_channels_list, 1):\n inner_block = 'fpn_inner{}'.format(idx)\n layer_block = 'fpn_layer{}'.format(idx)\n if in_channels == 0:\n continue\n inner_block_module = conv_block(in_channels... | <|body_start_0|>
super(FPN, self).__init__()
self.inner_blocks = []
self.layer_blocks = []
for idx, in_channels in enumerate(in_channels_list, 1):
inner_block = 'fpn_inner{}'.format(idx)
layer_block = 'fpn_layer{}'.format(idx)
if in_channels == 0:
... | Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive | FPN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FPN:
"""Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive"""
def __init__(self, in_channels_list, out_channels, conv_block, top_blocks=None):
"""Arguments: in_channels_list (list[int... | stack_v2_sparse_classes_75kplus_train_069265 | 10,890 | permissive | [
{
"docstring": "Arguments: in_channels_list (list[int]): number of channels for each feature map that will be fed out_channels (int): number of channels of the FPN representation top_blocks (nn.Module or None): if provided, an extra operation will be performed on the output of the last (smallest resolution) FPN... | 2 | stack_v2_sparse_classes_30k_train_054677 | Implement the Python class `FPN` described below.
Class description:
Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive
Method signatures and docstrings:
- def __init__(self, in_channels_list, out_channels, conv_block... | Implement the Python class `FPN` described below.
Class description:
Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive
Method signatures and docstrings:
- def __init__(self, in_channels_list, out_channels, conv_block... | 54e0821e73f67be5360c36f01229a123c34ab3b3 | <|skeleton|>
class FPN:
"""Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive"""
def __init__(self, in_channels_list, out_channels, conv_block, top_blocks=None):
"""Arguments: in_channels_list (list[int... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FPN:
"""Module that adds FPN on top of a list of feature maps. The feature maps are currently supposed to be in increasing depth order, and must be consecutive"""
def __init__(self, in_channels_list, out_channels, conv_block, top_blocks=None):
"""Arguments: in_channels_list (list[int]): number of... | the_stack_v2_python_sparse | AnchorFree/FCOS/models/asff.py | Le1kk/ObjectDetection | train | 0 |
9a98e6e35aa15c8807db1b00942dbce6948b5bb4 | [
"self.name = 'compare'\nsuper(CompareTable, self).__init__(results, best_results, options, group_dir, pp_locations, table_name)\nself.has_pp = True\nself.pp_filenames = [os.path.relpath(pp, group_dir) for pp in pp_locations]",
"abs_value = {}\nrel_value = {}\nfor key, value in results_dict.items():\n acc_abs_v... | <|body_start_0|>
self.name = 'compare'
super(CompareTable, self).__init__(results, best_results, options, group_dir, pp_locations, table_name)
self.has_pp = True
self.pp_filenames = [os.path.relpath(pp, group_dir) for pp in pp_locations]
<|end_body_0|>
<|body_start_1|>
abs_value... | The combined results show the accuracy in the first line of the cell and the runtime on the second line of the cell. | CompareTable | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompareTable:
"""The combined results show the accuracy in the first line of the cell and the runtime on the second line of the cell."""
def __init__(self, results, best_results, options, group_dir, pp_locations, table_name):
"""Initialise the compare table which shows both accuracy ... | stack_v2_sparse_classes_75kplus_train_069266 | 5,289 | permissive | [
{
"docstring": "Initialise the compare table which shows both accuracy and runtime results :param results: results nested array of objects :type results: list of list of fitbenchmarking.utils.fitbm_result.FittingResult :param best_results: best result for each problem :type best_results: list of fitbenchmarking... | 4 | null | Implement the Python class `CompareTable` described below.
Class description:
The combined results show the accuracy in the first line of the cell and the runtime on the second line of the cell.
Method signatures and docstrings:
- def __init__(self, results, best_results, options, group_dir, pp_locations, table_name)... | Implement the Python class `CompareTable` described below.
Class description:
The combined results show the accuracy in the first line of the cell and the runtime on the second line of the cell.
Method signatures and docstrings:
- def __init__(self, results, best_results, options, group_dir, pp_locations, table_name)... | edae46c0361568bc537de2425d603e7b271eabe7 | <|skeleton|>
class CompareTable:
"""The combined results show the accuracy in the first line of the cell and the runtime on the second line of the cell."""
def __init__(self, results, best_results, options, group_dir, pp_locations, table_name):
"""Initialise the compare table which shows both accuracy ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CompareTable:
"""The combined results show the accuracy in the first line of the cell and the runtime on the second line of the cell."""
def __init__(self, results, best_results, options, group_dir, pp_locations, table_name):
"""Initialise the compare table which shows both accuracy and runtime r... | the_stack_v2_python_sparse | fitbenchmarking/results_processing/compare_table.py | dsotiropoulos/fitbenchmarking | train | 0 |
05a102057641d96c56c77c41542f77eaa4345d6e | [
"super(IdentityResidualBlock, self).__init__()\nself.dist_bn = dist_bn\nif len(channels) != 2 and len(channels) != 3:\n raise ValueError('channels must contain either two or three values')\nif len(channels) == 2 and groups != 1:\n raise ValueError('groups > 1 are only valid if len(channels) == 3')\nis_bottlen... | <|body_start_0|>
super(IdentityResidualBlock, self).__init__()
self.dist_bn = dist_bn
if len(channels) != 2 and len(channels) != 3:
raise ValueError('channels must contain either two or three values')
if len(channels) == 2 and groups != 1:
raise ValueError('groups... | Identity Residual Block for WideResnet | IdentityResidualBlock | [
"GPL-1.0-or-later",
"BSD-3-Clause",
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IdentityResidualBlock:
"""Identity Residual Block for WideResnet"""
def __init__(self, in_channels, channels, stride=1, dilation=1, groups=1, norm_act=bnrelu, dropout=None, dist_bn=False):
"""Configurable identity-mapping residual block Parameters ---------- in_channels : int Number ... | stack_v2_sparse_classes_75kplus_train_069267 | 15,930 | permissive | [
{
"docstring": "Configurable identity-mapping residual block Parameters ---------- in_channels : int Number of input channels. channels : list of int Number of channels in the internal feature maps. Can either have two or three elements: if three construct a residual block with two `3 x 3` convolutions, otherwi... | 2 | stack_v2_sparse_classes_30k_train_016276 | Implement the Python class `IdentityResidualBlock` described below.
Class description:
Identity Residual Block for WideResnet
Method signatures and docstrings:
- def __init__(self, in_channels, channels, stride=1, dilation=1, groups=1, norm_act=bnrelu, dropout=None, dist_bn=False): Configurable identity-mapping resid... | Implement the Python class `IdentityResidualBlock` described below.
Class description:
Identity Residual Block for WideResnet
Method signatures and docstrings:
- def __init__(self, in_channels, channels, stride=1, dilation=1, groups=1, norm_act=bnrelu, dropout=None, dist_bn=False): Configurable identity-mapping resid... | 92acc188d3a0f634de58463b6676e70df83ef808 | <|skeleton|>
class IdentityResidualBlock:
"""Identity Residual Block for WideResnet"""
def __init__(self, in_channels, channels, stride=1, dilation=1, groups=1, norm_act=bnrelu, dropout=None, dist_bn=False):
"""Configurable identity-mapping residual block Parameters ---------- in_channels : int Number ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IdentityResidualBlock:
"""Identity Residual Block for WideResnet"""
def __init__(self, in_channels, channels, stride=1, dilation=1, groups=1, norm_act=bnrelu, dropout=None, dist_bn=False):
"""Configurable identity-mapping residual block Parameters ---------- in_channels : int Number of input chan... | the_stack_v2_python_sparse | PyTorch/contrib/cv/semantic_segmentation/HRnet-OCR/network/wider_resnet.py | Ascend/ModelZoo-PyTorch | train | 23 |
76bb4b22bf861ce99460ba72b2d5ca1d7a3216ba | [
"if opus is None:\n raise RuntimeError(f'{cls.__name__} cannot be created if opus is not loaded.')\nreturn Exception.__new__(cls)",
"self.code = code\nmsg = opus.opus_strerror(code).decode('utf-8')\nException.__init__(self, msg)"
] | <|body_start_0|>
if opus is None:
raise RuntimeError(f'{cls.__name__} cannot be created if opus is not loaded.')
return Exception.__new__(cls)
<|end_body_0|>
<|body_start_1|>
self.code = code
msg = opus.opus_strerror(code).decode('utf-8')
Exception.__init__(self, msg... | Exception raised by lib-opus related methods. Attributes ---------- code : `int` Returned error code by lib-opus. | OpusError | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpusError:
"""Exception raised by lib-opus related methods. Attributes ---------- code : `int` Returned error code by lib-opus."""
def __new__(cls, code):
"""Raises ----- RuntimeError If opus is not loaded."""
<|body_0|>
def __init__(self, code):
"""Creates an ``... | stack_v2_sparse_classes_75kplus_train_069268 | 17,943 | permissive | [
{
"docstring": "Raises ----- RuntimeError If opus is not loaded.",
"name": "__new__",
"signature": "def __new__(cls, code)"
},
{
"docstring": "Creates an ``OpusError`` Parameters ---------- code : `int` Returned error code by lib-opus.",
"name": "__init__",
"signature": "def __init__(sel... | 2 | null | Implement the Python class `OpusError` described below.
Class description:
Exception raised by lib-opus related methods. Attributes ---------- code : `int` Returned error code by lib-opus.
Method signatures and docstrings:
- def __new__(cls, code): Raises ----- RuntimeError If opus is not loaded.
- def __init__(self,... | Implement the Python class `OpusError` described below.
Class description:
Exception raised by lib-opus related methods. Attributes ---------- code : `int` Returned error code by lib-opus.
Method signatures and docstrings:
- def __new__(cls, code): Raises ----- RuntimeError If opus is not loaded.
- def __init__(self,... | 53f24fdb38459dc5a4fd04f11bdbfee8295b76a4 | <|skeleton|>
class OpusError:
"""Exception raised by lib-opus related methods. Attributes ---------- code : `int` Returned error code by lib-opus."""
def __new__(cls, code):
"""Raises ----- RuntimeError If opus is not loaded."""
<|body_0|>
def __init__(self, code):
"""Creates an ``... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OpusError:
"""Exception raised by lib-opus related methods. Attributes ---------- code : `int` Returned error code by lib-opus."""
def __new__(cls, code):
"""Raises ----- RuntimeError If opus is not loaded."""
if opus is None:
raise RuntimeError(f'{cls.__name__} cannot be crea... | the_stack_v2_python_sparse | hata/discord/voice/opus.py | HuyaneMatsu/hata | train | 3 |
152aff2507e410d3883eb54100d6d8551b621fb7 | [
"self.user = user\nself.client = client\nself.key = key\nself.secret = secret\nself.endpoint = endpoint\nself.cred_type = cred_type\nself.token_properties = token_properties",
"credentials_path = expanduser(expandvars(path))\nif not exists(credentials_path):\n raise HereCredentialsException('Unable to find cre... | <|body_start_0|>
self.user = user
self.client = client
self.key = key
self.secret = secret
self.endpoint = endpoint
self.cred_type = cred_type
self.token_properties = token_properties
<|end_body_0|>
<|body_start_1|>
credentials_path = expanduser(expandvar... | HereCredentials | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HereCredentials:
def __init__(self, user: str, client: str, key: str, secret: str, endpoint: str='https://account.api.here.com/oauth2/token', cred_type: str='DEFAULT', token_properties: dict=None):
"""Instantiate the credentials object. :param user: the HERE user id :param client: the HE... | stack_v2_sparse_classes_75kplus_train_069269 | 2,705 | permissive | [
{
"docstring": "Instantiate the credentials object. :param user: the HERE user id :param client: the HERE client id :param key: the HERE access key id :param secret: there HERE access key secret :param endpoint: the URL of the HERE account service :param cred_type: the type of credentials eg: DEFAULT, TOKEN :to... | 2 | stack_v2_sparse_classes_30k_train_039343 | Implement the Python class `HereCredentials` described below.
Class description:
Implement the HereCredentials class.
Method signatures and docstrings:
- def __init__(self, user: str, client: str, key: str, secret: str, endpoint: str='https://account.api.here.com/oauth2/token', cred_type: str='DEFAULT', token_propert... | Implement the Python class `HereCredentials` described below.
Class description:
Implement the HereCredentials class.
Method signatures and docstrings:
- def __init__(self, user: str, client: str, key: str, secret: str, endpoint: str='https://account.api.here.com/oauth2/token', cred_type: str='DEFAULT', token_propert... | e45f6c578733b3adce5a32dba575884ff76274b3 | <|skeleton|>
class HereCredentials:
def __init__(self, user: str, client: str, key: str, secret: str, endpoint: str='https://account.api.here.com/oauth2/token', cred_type: str='DEFAULT', token_properties: dict=None):
"""Instantiate the credentials object. :param user: the HERE user id :param client: the HE... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HereCredentials:
def __init__(self, user: str, client: str, key: str, secret: str, endpoint: str='https://account.api.here.com/oauth2/token', cred_type: str='DEFAULT', token_properties: dict=None):
"""Instantiate the credentials object. :param user: the HERE user id :param client: the HERE client id :... | the_stack_v2_python_sparse | XYZHubConnector/xyz_qgis/common/here_credentials.py | heremaps/xyz-qgis-plugin | train | 23 | |
92f282ef6400ca269ce88e21c196b15206f78fcd | [
"self.characters = characters\nself.combinationLength = combinationLength\nself.length = len(self.characters)\nself.cur = [1] * self.combinationLength + [0] * (self.length - self.combinationLength)\nself.start = True",
"if self.start:\n self.start = False\nelse:\n zero_idx = 0\n for i in range(self.lengt... | <|body_start_0|>
self.characters = characters
self.combinationLength = combinationLength
self.length = len(self.characters)
self.cur = [1] * self.combinationLength + [0] * (self.length - self.combinationLength)
self.start = True
<|end_body_0|>
<|body_start_1|>
if self.st... | CombinationIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CombinationIterator:
def __init__(self, characters, combinationLength):
""":type characters: str :type combinationLength: int"""
<|body_0|>
def next(self):
""":rtype: str"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|e... | stack_v2_sparse_classes_75kplus_train_069270 | 2,328 | no_license | [
{
"docstring": ":type characters: str :type combinationLength: int",
"name": "__init__",
"signature": "def __init__(self, characters, combinationLength)"
},
{
"docstring": ":rtype: str",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "... | 3 | stack_v2_sparse_classes_30k_train_034429 | Implement the Python class `CombinationIterator` described below.
Class description:
Implement the CombinationIterator class.
Method signatures and docstrings:
- def __init__(self, characters, combinationLength): :type characters: str :type combinationLength: int
- def next(self): :rtype: str
- def hasNext(self): :rt... | Implement the Python class `CombinationIterator` described below.
Class description:
Implement the CombinationIterator class.
Method signatures and docstrings:
- def __init__(self, characters, combinationLength): :type characters: str :type combinationLength: int
- def next(self): :rtype: str
- def hasNext(self): :rt... | 80940738f9eab7f641efb2df9bce8b7bc888a4eb | <|skeleton|>
class CombinationIterator:
def __init__(self, characters, combinationLength):
""":type characters: str :type combinationLength: int"""
<|body_0|>
def next(self):
""":rtype: str"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|e... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CombinationIterator:
def __init__(self, characters, combinationLength):
""":type characters: str :type combinationLength: int"""
self.characters = characters
self.combinationLength = combinationLength
self.length = len(self.characters)
self.cur = [1] * self.combinationL... | the_stack_v2_python_sparse | 1286. 字母组合迭代器.py | half-empty/LeetCode | train | 0 | |
37e1f8a22b076af4ebfd5bb33cca051c2ffd3c7f | [
"role_id = g.account_obj.role_id\nmenus = list()\nif role_id in site.role_menus:\n role_menus = site.role_menus[role_id]\n for menu_name in role_menus:\n menus.append(site.menus[menu_name])\nreturn self.return_success(menus)",
"store_article_category_form = StoreArticleCategoryForm.from_json(self.req... | <|body_start_0|>
role_id = g.account_obj.role_id
menus = list()
if role_id in site.role_menus:
role_menus = site.role_menus[role_id]
for menu_name in role_menus:
menus.append(site.menus[menu_name])
return self.return_success(menus)
<|end_body_0|>
... | Site | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Site:
def get_menus(self):
"""@description: 获取权限菜单 @return: list 菜单列表"""
<|body_0|>
def store_article_category(self):
"""@descripttion: 新增文章分类 @param {type} @return:"""
<|body_1|>
def index_article_category(self):
"""@descripttion: 获取文章分类列表 @retu... | stack_v2_sparse_classes_75kplus_train_069271 | 3,184 | no_license | [
{
"docstring": "@description: 获取权限菜单 @return: list 菜单列表",
"name": "get_menus",
"signature": "def get_menus(self)"
},
{
"docstring": "@descripttion: 新增文章分类 @param {type} @return:",
"name": "store_article_category",
"signature": "def store_article_category(self)"
},
{
"docstring": ... | 4 | stack_v2_sparse_classes_30k_train_020188 | Implement the Python class `Site` described below.
Class description:
Implement the Site class.
Method signatures and docstrings:
- def get_menus(self): @description: 获取权限菜单 @return: list 菜单列表
- def store_article_category(self): @descripttion: 新增文章分类 @param {type} @return:
- def index_article_category(self): @descrip... | Implement the Python class `Site` described below.
Class description:
Implement the Site class.
Method signatures and docstrings:
- def get_menus(self): @description: 获取权限菜单 @return: list 菜单列表
- def store_article_category(self): @descripttion: 新增文章分类 @param {type} @return:
- def index_article_category(self): @descrip... | 12ebf7caad8e8884e2f35bbad16314b8716b105b | <|skeleton|>
class Site:
def get_menus(self):
"""@description: 获取权限菜单 @return: list 菜单列表"""
<|body_0|>
def store_article_category(self):
"""@descripttion: 新增文章分类 @param {type} @return:"""
<|body_1|>
def index_article_category(self):
"""@descripttion: 获取文章分类列表 @retu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Site:
def get_menus(self):
"""@description: 获取权限菜单 @return: list 菜单列表"""
role_id = g.account_obj.role_id
menus = list()
if role_id in site.role_menus:
role_menus = site.role_menus[role_id]
for menu_name in role_menus:
menus.append(site.me... | the_stack_v2_python_sparse | lingkblog/services/admin/site.py | GGGanon/lingkblog-service | train | 3 | |
ebf6968ea4adeae4b9828e8186b810ad8c081722 | [
"super().__init__(images, class_dict, args)\nassert self.image_channels == 3\nassert np.shape(self.image_data)[-1] == self.image_channels",
"index, tag = meta_index\nlabel, seed = tag\nimage = self.image_data[index]\nh, w, c = image.shape\nimage = Image.fromarray(np.uint8(image)).convert('RGB')\nimage = self.tran... | <|body_start_0|>
super().__init__(images, class_dict, args)
assert self.image_channels == 3
assert np.shape(self.image_data)[-1] == self.image_channels
<|end_body_0|>
<|body_start_1|>
index, tag = meta_index
label, seed = tag
image = self.image_data[index]
h, w, ... | ColorDatasetInMemory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ColorDatasetInMemory:
def __init__(self, images, class_dict, args):
"""Constructor of DatasetInMemory for datasets that can fit in memory. Use DatasetOnDrive to load images from hard drive. :param images: All images in a single array or list already loaded in memory :param class_dict: Di... | stack_v2_sparse_classes_75kplus_train_069272 | 9,434 | permissive | [
{
"docstring": "Constructor of DatasetInMemory for datasets that can fit in memory. Use DatasetOnDrive to load images from hard drive. :param images: All images in a single array or list already loaded in memory :param class_dict: Dictionary mapping class names to a list of indices of images belonging to the cl... | 3 | stack_v2_sparse_classes_30k_train_000320 | Implement the Python class `ColorDatasetInMemory` described below.
Class description:
Implement the ColorDatasetInMemory class.
Method signatures and docstrings:
- def __init__(self, images, class_dict, args): Constructor of DatasetInMemory for datasets that can fit in memory. Use DatasetOnDrive to load images from h... | Implement the Python class `ColorDatasetInMemory` described below.
Class description:
Implement the ColorDatasetInMemory class.
Method signatures and docstrings:
- def __init__(self, images, class_dict, args): Constructor of DatasetInMemory for datasets that can fit in memory. Use DatasetOnDrive to load images from h... | d654a9898e19bf4278af8a4bfcebef5950c615e0 | <|skeleton|>
class ColorDatasetInMemory:
def __init__(self, images, class_dict, args):
"""Constructor of DatasetInMemory for datasets that can fit in memory. Use DatasetOnDrive to load images from hard drive. :param images: All images in a single array or list already loaded in memory :param class_dict: Di... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ColorDatasetInMemory:
def __init__(self, images, class_dict, args):
"""Constructor of DatasetInMemory for datasets that can fit in memory. Use DatasetOnDrive to load images from hard drive. :param images: All images in a single array or list already loaded in memory :param class_dict: Dictionary mappi... | the_stack_v2_python_sparse | src/datasets/dataset_template.py | licj1/imbalanced_fsl_public | train | 0 | |
cf603d1c032ffc9d726595322cf4115167caa7c5 | [
"if N == 1:\n return 10\ntemp = 10 ** 9 + 7\ndp = [[0] * 10 for _ in range(N)]\nfor i in range(10):\n dp[0][i] = 1\nfor i in range(1, N):\n dp[i][0] = (dp[i - 1][4] + dp[i - 1][6]) % temp\n dp[i][1] = (dp[i - 1][6] + dp[i - 1][8]) % temp\n dp[i][2] = (dp[i - 1][7] + dp[i - 1][9]) % temp\n dp[i][3]... | <|body_start_0|>
if N == 1:
return 10
temp = 10 ** 9 + 7
dp = [[0] * 10 for _ in range(N)]
for i in range(10):
dp[0][i] = 1
for i in range(1, N):
dp[i][0] = (dp[i - 1][4] + dp[i - 1][6]) % temp
dp[i][1] = (dp[i - 1][6] + dp[i - 1][8... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def knightDialer(self, N):
""":type N: int :rtype: int 552 ms"""
<|body_0|>
def knightDialer_1(self, N):
""":type N: int :rtype: int 80ms 矩阵乘法，斐波那契数列的方法！！！！"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if N == 1:
return 10
... | stack_v2_sparse_classes_75kplus_train_069273 | 2,749 | no_license | [
{
"docstring": ":type N: int :rtype: int 552 ms",
"name": "knightDialer",
"signature": "def knightDialer(self, N)"
},
{
"docstring": ":type N: int :rtype: int 80ms 矩阵乘法，斐波那契数列的方法！！！！",
"name": "knightDialer_1",
"signature": "def knightDialer_1(self, N)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003517 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def knightDialer(self, N): :type N: int :rtype: int 552 ms
- def knightDialer_1(self, N): :type N: int :rtype: int 80ms 矩阵乘法，斐波那契数列的方法！！！！ | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def knightDialer(self, N): :type N: int :rtype: int 552 ms
- def knightDialer_1(self, N): :type N: int :rtype: int 80ms 矩阵乘法，斐波那契数列的方法！！！！
<|skeleton|>
class Solution:
def ... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def knightDialer(self, N):
""":type N: int :rtype: int 552 ms"""
<|body_0|>
def knightDialer_1(self, N):
""":type N: int :rtype: int 80ms 矩阵乘法，斐波那契数列的方法！！！！"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def knightDialer(self, N):
""":type N: int :rtype: int 552 ms"""
if N == 1:
return 10
temp = 10 ** 9 + 7
dp = [[0] * 10 for _ in range(N)]
for i in range(10):
dp[0][i] = 1
for i in range(1, N):
dp[i][0] = (dp[i - 1][... | the_stack_v2_python_sparse | KnightDialer_MID_935.py | 953250587/leetcode-python | train | 2 | |
46225ea435305b631646589cffb2fcd472da70c0 | [
"if dedent:\n template = _textwrap.dedent(template).lstrip()\nif rstrip:\n template = template.rstrip()\nself._template = template",
"if args:\n if kwargs:\n raise TypeError('Both args and kwargs given')\n return self._template % args\nelif kwargs:\n return self._template % kwargs\nreturn se... | <|body_start_0|>
if dedent:
template = _textwrap.dedent(template).lstrip()
if rstrip:
template = template.rstrip()
self._template = template
<|end_body_0|>
<|body_start_1|>
if args:
if kwargs:
raise TypeError('Both args and kwargs give... | Template container Attributes: _template (str): Template string | Template | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Template:
"""Template container Attributes: _template (str): Template string"""
def __init__(self, template, dedent=True, rstrip=True):
"""Initialization Parameters: template (str): Template string dedent (bool): Dedent automatically? rstrip (bool): rstrip the template automatically?... | stack_v2_sparse_classes_75kplus_train_069274 | 2,184 | permissive | [
{
"docstring": "Initialization Parameters: template (str): Template string dedent (bool): Dedent automatically? rstrip (bool): rstrip the template automatically?",
"name": "__init__",
"signature": "def __init__(self, template, dedent=True, rstrip=True)"
},
{
"docstring": "Expand the template Eit... | 2 | stack_v2_sparse_classes_30k_train_029428 | Implement the Python class `Template` described below.
Class description:
Template container Attributes: _template (str): Template string
Method signatures and docstrings:
- def __init__(self, template, dedent=True, rstrip=True): Initialization Parameters: template (str): Template string dedent (bool): Dedent automat... | Implement the Python class `Template` described below.
Class description:
Template container Attributes: _template (str): Template string
Method signatures and docstrings:
- def __init__(self, template, dedent=True, rstrip=True): Initialization Parameters: template (str): Template string dedent (bool): Dedent automat... | 69b94193f6a12e6b52b44ff2eb9d82468883b318 | <|skeleton|>
class Template:
"""Template container Attributes: _template (str): Template string"""
def __init__(self, template, dedent=True, rstrip=True):
"""Initialization Parameters: template (str): Template string dedent (bool): Dedent automatically? rstrip (bool): rstrip the template automatically?... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Template:
"""Template container Attributes: _template (str): Template string"""
def __init__(self, template, dedent=True, rstrip=True):
"""Initialization Parameters: template (str): Template string dedent (bool): Dedent automatically? rstrip (bool): rstrip the template automatically?"""
i... | the_stack_v2_python_sparse | gensaschema/_template.py | ndparker/gensaschema | train | 3 |
28c0a2cf713e50e00759627afbfeedf338c757ba | [
"self.original_fn = original_fn\nself.is_method = isinstance(self.original_fn, types.MethodType)\nself.pack_fn_name = f'_{original_fn.__name__}_pack'\nself._generate_pack_op()",
"if self.is_method:\n sig = inspect.signature(self.original_fn.pack_fn)\n arg_num = len(sig.parameters) - 1\n arg_str = ', '.jo... | <|body_start_0|>
self.original_fn = original_fn
self.is_method = isinstance(self.original_fn, types.MethodType)
self.pack_fn_name = f'_{original_fn.__name__}_pack'
self._generate_pack_op()
<|end_body_0|>
<|body_start_1|>
if self.is_method:
sig = inspect.signature(sel... | Generation Pack Python code by method | _PackSourceBuilder | [
"Apache-2.0",
"LicenseRef-scancode-proprietary-license",
"MPL-1.0",
"OpenSSL",
"LGPL-3.0-only",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-3-Clause-Open-MPI",
"MIT",
"MPL-2.0-no-copyleft-exception",
"NTP",
"BSD-3-Clause",
"GPL-1.0-or-later",
"0BSD",
"MPL-2.0",
"LicenseRef-scancode-f... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _PackSourceBuilder:
"""Generation Pack Python code by method"""
def __init__(self, original_fn):
"""Initialize the _PackSourceBuilder"""
<|body_0|>
def get_code_source(self):
"""Return Pack Python code"""
<|body_1|>
def _generate_pack_op(self):
... | stack_v2_sparse_classes_75kplus_train_069275 | 7,643 | permissive | [
{
"docstring": "Initialize the _PackSourceBuilder",
"name": "__init__",
"signature": "def __init__(self, original_fn)"
},
{
"docstring": "Return Pack Python code",
"name": "get_code_source",
"signature": "def get_code_source(self)"
},
{
"docstring": "Generate the pack operation a... | 3 | stack_v2_sparse_classes_30k_test_002939 | Implement the Python class `_PackSourceBuilder` described below.
Class description:
Generation Pack Python code by method
Method signatures and docstrings:
- def __init__(self, original_fn): Initialize the _PackSourceBuilder
- def get_code_source(self): Return Pack Python code
- def _generate_pack_op(self): Generate ... | Implement the Python class `_PackSourceBuilder` described below.
Class description:
Generation Pack Python code by method
Method signatures and docstrings:
- def __init__(self, original_fn): Initialize the _PackSourceBuilder
- def get_code_source(self): Return Pack Python code
- def _generate_pack_op(self): Generate ... | 54acb15d435533c815ee1bd9f6dc0b56b4d4cf83 | <|skeleton|>
class _PackSourceBuilder:
"""Generation Pack Python code by method"""
def __init__(self, original_fn):
"""Initialize the _PackSourceBuilder"""
<|body_0|>
def get_code_source(self):
"""Return Pack Python code"""
<|body_1|>
def _generate_pack_op(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _PackSourceBuilder:
"""Generation Pack Python code by method"""
def __init__(self, original_fn):
"""Initialize the _PackSourceBuilder"""
self.original_fn = original_fn
self.is_method = isinstance(self.original_fn, types.MethodType)
self.pack_fn_name = f'_{original_fn.__nam... | the_stack_v2_python_sparse | mindspore/python/mindspore/ops/_tracefunc.py | mindspore-ai/mindspore | train | 4,178 |
ff6868c40b4bd30e0e3d2654f6f0ff7f5eb29cda | [
"try:\n dhcpController = DhcpController()\n json_data = json.dumps(dhcpController.get_dhcp_server_configuration_default_lease_time())\n resp = Response(json_data, status=200, mimetype='application/json')\n return resp\nexcept ValueError as ve:\n return Response(json.dumps(str(ve)), status=404, mimety... | <|body_start_0|>
try:
dhcpController = DhcpController()
json_data = json.dumps(dhcpController.get_dhcp_server_configuration_default_lease_time())
resp = Response(json_data, status=200, mimetype='application/json')
return resp
except ValueError as ve:
... | DhcpServer_Configuration_DefaultLeaseTime | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DhcpServer_Configuration_DefaultLeaseTime:
def get(self):
"""Gets the default lease time parameter"""
<|body_0|>
def put(self):
"""Update the default lease time parameter"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
dhcpControlle... | stack_v2_sparse_classes_75kplus_train_069276 | 20,424 | no_license | [
{
"docstring": "Gets the default lease time parameter",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Update the default lease time parameter",
"name": "put",
"signature": "def put(self)"
}
] | 2 | null | Implement the Python class `DhcpServer_Configuration_DefaultLeaseTime` described below.
Class description:
Implement the DhcpServer_Configuration_DefaultLeaseTime class.
Method signatures and docstrings:
- def get(self): Gets the default lease time parameter
- def put(self): Update the default lease time parameter | Implement the Python class `DhcpServer_Configuration_DefaultLeaseTime` described below.
Class description:
Implement the DhcpServer_Configuration_DefaultLeaseTime class.
Method signatures and docstrings:
- def get(self): Gets the default lease time parameter
- def put(self): Update the default lease time parameter
<... | 6070e3cb6bf957e04f5d8267db11f3296410e18e | <|skeleton|>
class DhcpServer_Configuration_DefaultLeaseTime:
def get(self):
"""Gets the default lease time parameter"""
<|body_0|>
def put(self):
"""Update the default lease time parameter"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DhcpServer_Configuration_DefaultLeaseTime:
def get(self):
"""Gets the default lease time parameter"""
try:
dhcpController = DhcpController()
json_data = json.dumps(dhcpController.get_dhcp_server_configuration_default_lease_time())
resp = Response(json_data, ... | the_stack_v2_python_sparse | configuration-agent/dhcp/rest_api/resources/dhcp_server.py | ReliableLion/frog4-configurable-vnf | train | 0 | |
fbb3e9a85636144fde65b43bc6441221acfeba7d | [
"self.name = name\nself.x = pos[0]\nself.y = pos[1]\nself.width = width\nself.height = height\nself.color = color\nself.show = True\nself.image = pygame.Surface((width, height))\nself.rect = self.image.get_rect(center=pos)\nself.image.fill(self.color)",
"self.x = x\nself.y = y\nself.rect.center = (x, y)"
] | <|body_start_0|>
self.name = name
self.x = pos[0]
self.y = pos[1]
self.width = width
self.height = height
self.color = color
self.show = True
self.image = pygame.Surface((width, height))
self.rect = self.image.get_rect(center=pos)
self.imag... | Rectangle. | Rectangle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rectangle:
"""Rectangle."""
def __init__(self, name, pos, width, height, color):
"""Initialize Rectangle Sprite. Args: name (string): The name of the sprite pos (tuple): Position of the sprite width (int): Width of the sprite height (int): Height of the sprite color (tuple): Color of... | stack_v2_sparse_classes_75kplus_train_069277 | 1,033 | no_license | [
{
"docstring": "Initialize Rectangle Sprite. Args: name (string): The name of the sprite pos (tuple): Position of the sprite width (int): Width of the sprite height (int): Height of the sprite color (tuple): Color of the sprite",
"name": "__init__",
"signature": "def __init__(self, name, pos, width, hei... | 2 | null | Implement the Python class `Rectangle` described below.
Class description:
Rectangle.
Method signatures and docstrings:
- def __init__(self, name, pos, width, height, color): Initialize Rectangle Sprite. Args: name (string): The name of the sprite pos (tuple): Position of the sprite width (int): Width of the sprite h... | Implement the Python class `Rectangle` described below.
Class description:
Rectangle.
Method signatures and docstrings:
- def __init__(self, name, pos, width, height, color): Initialize Rectangle Sprite. Args: name (string): The name of the sprite pos (tuple): Position of the sprite width (int): Width of the sprite h... | d2e70a820b6e7388657912912d16c917d8ef020a | <|skeleton|>
class Rectangle:
"""Rectangle."""
def __init__(self, name, pos, width, height, color):
"""Initialize Rectangle Sprite. Args: name (string): The name of the sprite pos (tuple): Position of the sprite width (int): Width of the sprite height (int): Height of the sprite color (tuple): Color of... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Rectangle:
"""Rectangle."""
def __init__(self, name, pos, width, height, color):
"""Initialize Rectangle Sprite. Args: name (string): The name of the sprite pos (tuple): Position of the sprite width (int): Width of the sprite height (int): Height of the sprite color (tuple): Color of the sprite""... | the_stack_v2_python_sparse | 8_Directional/CollectCoins/rectangle.py | JushBJJ/Pygame-Examples | train | 0 |
6396d4fb00467611541cf92bb9b118ade7d42b08 | [
"if '\\\\' in key:\n key = key.replace('\\\\', '/')\ncleaned_parts = [part for part in key.split('/') if part]\nreturn '/'.join(cleaned_parts)",
"if not value:\n lazy_value = path.normpath('{0}{1}{2}'.format(self.caching_dir, os.sep, key))\n if path.isfile(lazy_value):\n value = lazy_value\n el... | <|body_start_0|>
if '\\' in key:
key = key.replace('\\', '/')
cleaned_parts = [part for part in key.split('/') if part]
return '/'.join(cleaned_parts)
<|end_body_0|>
<|body_start_1|>
if not value:
lazy_value = path.normpath('{0}{1}{2}'.format(self.caching_dir, os... | Artifactory Cache System | ArtifactoryCacheManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArtifactoryCacheManager:
"""Artifactory Cache System"""
def get_key(key):
"""Here we want to ensure uniqueness of the key :param key: :type key: str :return: the processed key if implemented :rtype: str"""
<|body_0|>
def add(self, key, value=None):
"""Add an Entr... | stack_v2_sparse_classes_75kplus_train_069278 | 25,285 | permissive | [
{
"docstring": "Here we want to ensure uniqueness of the key :param key: :type key: str :return: the processed key if implemented :rtype: str",
"name": "get_key",
"signature": "def get_key(key)"
},
{
"docstring": "Add an Entry to the Cache if not already there * Create the Entry from given key/v... | 4 | stack_v2_sparse_classes_30k_train_039582 | Implement the Python class `ArtifactoryCacheManager` described below.
Class description:
Artifactory Cache System
Method signatures and docstrings:
- def get_key(key): Here we want to ensure uniqueness of the key :param key: :type key: str :return: the processed key if implemented :rtype: str
- def add(self, key, val... | Implement the Python class `ArtifactoryCacheManager` described below.
Class description:
Artifactory Cache System
Method signatures and docstrings:
- def get_key(key): Here we want to ensure uniqueness of the key :param key: :type key: str :return: the processed key if implemented :rtype: str
- def add(self, key, val... | 7bf09f20f117fc74d02b7635305ce664b65cdcba | <|skeleton|>
class ArtifactoryCacheManager:
"""Artifactory Cache System"""
def get_key(key):
"""Here we want to ensure uniqueness of the key :param key: :type key: str :return: the processed key if implemented :rtype: str"""
<|body_0|>
def add(self, key, value=None):
"""Add an Entr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ArtifactoryCacheManager:
"""Artifactory Cache System"""
def get_key(key):
"""Here we want to ensure uniqueness of the key :param key: :type key: str :return: the processed key if implemented :rtype: str"""
if '\\' in key:
key = key.replace('\\', '/')
cleaned_parts = [p... | the_stack_v2_python_sparse | acs/acs/UtilitiesFWK/Caching.py | intel/test-framework-and-suites-for-android | train | 9 |
2a6b0eb8101ae5273772b7adc4aa03d592f8edad | [
"LDC_Info.__init__(self)\nself.setTitle(self.name)\nself.status = compat_res[0]\nui = Ui_MotherboardFrame()\nui.setupUi(self.frame)\nself.__fill_frame(ui, info_res, compat_res, diag_res)",
"ui.modelLineEdit.setText(QtGui.QApplication.translate('MotherboardFrame', self._check_invalid_values(info_res.model), None, ... | <|body_start_0|>
LDC_Info.__init__(self)
self.setTitle(self.name)
self.status = compat_res[0]
ui = Ui_MotherboardFrame()
ui.setupUi(self.frame)
self.__fill_frame(ui, info_res, compat_res, diag_res)
<|end_body_0|>
<|body_start_1|>
ui.modelLineEdit.setText(QtGui.QA... | Estende a classe 'LDC_Info'. Classe que define a interface gráfica de exibição dos resultados para a placa mãe | GUIMotherboard | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GUIMotherboard:
"""Estende a classe 'LDC_Info'. Classe que define a interface gráfica de exibição dos resultados para a placa mãe"""
def __init__(self, info_res, compat_res, diag_res):
"""Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResMother... | stack_v2_sparse_classes_75kplus_train_069279 | 3,833 | no_license | [
{
"docstring": "Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResMotherboard') compat_res -- Lista com as tuples de resultado de compatibilidade [(True, msg)] diag_res -- Lista com os resultados do diagnóstico (nesse caso não existe teste de diagnóstico, recebe-se uma li... | 2 | stack_v2_sparse_classes_30k_train_005535 | Implement the Python class `GUIMotherboard` described below.
Class description:
Estende a classe 'LDC_Info'. Classe que define a interface gráfica de exibição dos resultados para a placa mãe
Method signatures and docstrings:
- def __init__(self, info_res, compat_res, diag_res): Construtor Parâmetros: info_res -- list... | Implement the Python class `GUIMotherboard` described below.
Class description:
Estende a classe 'LDC_Info'. Classe que define a interface gráfica de exibição dos resultados para a placa mãe
Method signatures and docstrings:
- def __init__(self, info_res, compat_res, diag_res): Construtor Parâmetros: info_res -- list... | bda0c2c8977dd1246339f1f0f4718d29e8795f21 | <|skeleton|>
class GUIMotherboard:
"""Estende a classe 'LDC_Info'. Classe que define a interface gráfica de exibição dos resultados para a placa mãe"""
def __init__(self, info_res, compat_res, diag_res):
"""Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResMother... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GUIMotherboard:
"""Estende a classe 'LDC_Info'. Classe que define a interface gráfica de exibição dos resultados para a placa mãe"""
def __init__(self, info_res, compat_res, diag_res):
"""Construtor Parâmetros: info_res -- lista com os resultados informativos (lista de 'InfoResMotherboard') compa... | the_stack_v2_python_sparse | src/libs/motherboard/gui_motherboard.py | adrianomelo/ldc-desktop | train | 1 |
6076e495a26499e95b0952b09fe798175f6c299c | [
"super().validate_order_by(value)\nvalidate_field(self, 'order_by', OrderBySerializer, value)\nreturn value",
"valid_delta = 'usage'\nrequest = self.context.get('request')\nif request and 'costs' in request.path:\n valid_delta = 'cost_total'\n if value == 'cost':\n return valid_delta\nif value != val... | <|body_start_0|>
super().validate_order_by(value)
validate_field(self, 'order_by', OrderBySerializer, value)
return value
<|end_body_0|>
<|body_start_1|>
valid_delta = 'usage'
request = self.context.get('request')
if request and 'costs' in request.path:
valid... | Serializer for handling cost query parameters. | OCPCostQueryParamSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OCPCostQueryParamSerializer:
"""Serializer for handling cost query parameters."""
def validate_order_by(self, value):
"""Validate incoming order_by data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): if order_by field inputs are in... | stack_v2_sparse_classes_75kplus_train_069280 | 8,402 | permissive | [
{
"docstring": "Validate incoming order_by data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): if order_by field inputs are invalid",
"name": "validate_order_by",
"signature": "def validate_order_by(self, value)"
},
{
"docstring": "Validate in... | 2 | null | Implement the Python class `OCPCostQueryParamSerializer` described below.
Class description:
Serializer for handling cost query parameters.
Method signatures and docstrings:
- def validate_order_by(self, value): Validate incoming order_by data. Args: data (Dict): data to be validated Returns: (Dict): Validated data R... | Implement the Python class `OCPCostQueryParamSerializer` described below.
Class description:
Serializer for handling cost query parameters.
Method signatures and docstrings:
- def validate_order_by(self, value): Validate incoming order_by data. Args: data (Dict): data to be validated Returns: (Dict): Validated data R... | 2979f03fbdd1c20c3abc365a963a1282b426f321 | <|skeleton|>
class OCPCostQueryParamSerializer:
"""Serializer for handling cost query parameters."""
def validate_order_by(self, value):
"""Validate incoming order_by data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): if order_by field inputs are in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OCPCostQueryParamSerializer:
"""Serializer for handling cost query parameters."""
def validate_order_by(self, value):
"""Validate incoming order_by data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): if order_by field inputs are invalid"""
... | the_stack_v2_python_sparse | koku/api/report/ocp/serializers.py | luisfdez/koku | train | 0 |
b1d217c48da1f80ffbbea6749dd6d83afb775db1 | [
"include_inactive = request.args.get('include_inactive', '0') != '0'\nget_users_response = InternalApi().get(url_for('flexmeasures_api_v2_0.get_users', include_inactive=include_inactive))\nusers = [process_internal_api_response(user, make_obj=True) for user in get_users_response.json()]\nreturn render_flexmeasures_... | <|body_start_0|>
include_inactive = request.args.get('include_inactive', '0') != '0'
get_users_response = InternalApi().get(url_for('flexmeasures_api_v2_0.get_users', include_inactive=include_inactive))
users = [process_internal_api_response(user, make_obj=True) for user in get_users_response.js... | UserCrudUI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserCrudUI:
def index(self):
"""/users"""
<|body_0|>
def get(self, id: str):
"""GET from /users/<id>"""
<|body_1|>
def toggle_active(self, id: str):
"""Toggle activation status via /users/toggle_active/<id>"""
<|body_2|>
def reset_pa... | stack_v2_sparse_classes_75kplus_train_069281 | 4,885 | permissive | [
{
"docstring": "/users",
"name": "index",
"signature": "def index(self)"
},
{
"docstring": "GET from /users/<id>",
"name": "get",
"signature": "def get(self, id: str)"
},
{
"docstring": "Toggle activation status via /users/toggle_active/<id>",
"name": "toggle_active",
"si... | 4 | stack_v2_sparse_classes_30k_train_037940 | Implement the Python class `UserCrudUI` described below.
Class description:
Implement the UserCrudUI class.
Method signatures and docstrings:
- def index(self): /users
- def get(self, id: str): GET from /users/<id>
- def toggle_active(self, id: str): Toggle activation status via /users/toggle_active/<id>
- def reset_... | Implement the Python class `UserCrudUI` described below.
Class description:
Implement the UserCrudUI class.
Method signatures and docstrings:
- def index(self): /users
- def get(self, id: str): GET from /users/<id>
- def toggle_active(self, id: str): Toggle activation status via /users/toggle_active/<id>
- def reset_... | 6ba518bae7e9b8a715b9a05f6fae19f5e4ade791 | <|skeleton|>
class UserCrudUI:
def index(self):
"""/users"""
<|body_0|>
def get(self, id: str):
"""GET from /users/<id>"""
<|body_1|>
def toggle_active(self, id: str):
"""Toggle activation status via /users/toggle_active/<id>"""
<|body_2|>
def reset_pa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserCrudUI:
def index(self):
"""/users"""
include_inactive = request.args.get('include_inactive', '0') != '0'
get_users_response = InternalApi().get(url_for('flexmeasures_api_v2_0.get_users', include_inactive=include_inactive))
users = [process_internal_api_response(user, make_... | the_stack_v2_python_sparse | flexmeasures/ui/crud/users.py | meeseeksmachine/flexmeasures | train | 0 | |
ceb0059d25d7aa4c8fd6106c115f0ba2f873661e | [
"Precondition.is_string(dataset_csv_file_path, 'Invalid dataset_csv_file_path')\nself.dataset_csv_file_path = dataset_csv_file_path\nself.logger = logger\nself.data_array = []\nif should_load:\n self.load(self.dataset_csv_file_path)",
"if self.logger:\n self.logger.trace('Loading dataset: {0} with a delimit... | <|body_start_0|>
Precondition.is_string(dataset_csv_file_path, 'Invalid dataset_csv_file_path')
self.dataset_csv_file_path = dataset_csv_file_path
self.logger = logger
self.data_array = []
if should_load:
self.load(self.dataset_csv_file_path)
<|end_body_0|>
<|body_st... | A class to load and access csv dataset and it's fields | CsvDataset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CsvDataset:
"""A class to load and access csv dataset and it's fields"""
def __init__(self, dataset_csv_file_path, logger=None, should_load=True):
"""Init Args: dataset_csv_file_path: absolute path to the csv file logger: shared logger (could be null) should_load: should the dataset ... | stack_v2_sparse_classes_75kplus_train_069282 | 2,784 | no_license | [
{
"docstring": "Init Args: dataset_csv_file_path: absolute path to the csv file logger: shared logger (could be null) should_load: should the dataset (default = True) Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self, dataset_csv_file_path, logger=None, should_load=True)"
... | 4 | stack_v2_sparse_classes_30k_train_050039 | Implement the Python class `CsvDataset` described below.
Class description:
A class to load and access csv dataset and it's fields
Method signatures and docstrings:
- def __init__(self, dataset_csv_file_path, logger=None, should_load=True): Init Args: dataset_csv_file_path: absolute path to the csv file logger: share... | Implement the Python class `CsvDataset` described below.
Class description:
A class to load and access csv dataset and it's fields
Method signatures and docstrings:
- def __init__(self, dataset_csv_file_path, logger=None, should_load=True): Init Args: dataset_csv_file_path: absolute path to the csv file logger: share... | d90b19eb68a599a4b6bcff3290aaba0881ebb23d | <|skeleton|>
class CsvDataset:
"""A class to load and access csv dataset and it's fields"""
def __init__(self, dataset_csv_file_path, logger=None, should_load=True):
"""Init Args: dataset_csv_file_path: absolute path to the csv file logger: shared logger (could be null) should_load: should the dataset ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CsvDataset:
"""A class to load and access csv dataset and it's fields"""
def __init__(self, dataset_csv_file_path, logger=None, should_load=True):
"""Init Args: dataset_csv_file_path: absolute path to the csv file logger: shared logger (could be null) should_load: should the dataset (default = Tr... | the_stack_v2_python_sparse | common/dataset/csv_dataset.py | santhosh-kumar/DataScienceToolbox | train | 2 |
4936a198b564c2680863123cb37f76b979a6b332 | [
"super(Albert, self).__init__()\nself.expanddims = P.ExpandDims()\nself.cast = P.Cast()\nself.sub = P.Sub()\nself.mul = P.Mul()\nself.gather = P.Gather()\nself.add = P.Add()\nself.layernorm_1_weight = Parameter(Tensor(np.random.uniform(0, 1, (128,)).astype(np.float32)), name=None)\nself.layernorm_1_bias = Parameter... | <|body_start_0|>
super(Albert, self).__init__()
self.expanddims = P.ExpandDims()
self.cast = P.Cast()
self.sub = P.Sub()
self.mul = P.Mul()
self.gather = P.Gather()
self.add = P.Add()
self.layernorm_1_weight = Parameter(Tensor(np.random.uniform(0, 1, (128,... | Albert model for rerank | Albert | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Albert:
"""Albert model for rerank"""
def __init__(self, batch_size):
"""init function"""
<|body_0|>
def construct(self, input_ids, attention_mask, token_type_ids):
"""construct function"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(Albe... | stack_v2_sparse_classes_75kplus_train_069283 | 12,912 | permissive | [
{
"docstring": "init function",
"name": "__init__",
"signature": "def __init__(self, batch_size)"
},
{
"docstring": "construct function",
"name": "construct",
"signature": "def construct(self, input_ids, attention_mask, token_type_ids)"
}
] | 2 | stack_v2_sparse_classes_30k_train_024380 | Implement the Python class `Albert` described below.
Class description:
Albert model for rerank
Method signatures and docstrings:
- def __init__(self, batch_size): init function
- def construct(self, input_ids, attention_mask, token_type_ids): construct function | Implement the Python class `Albert` described below.
Class description:
Albert model for rerank
Method signatures and docstrings:
- def __init__(self, batch_size): init function
- def construct(self, input_ids, attention_mask, token_type_ids): construct function
<|skeleton|>
class Albert:
"""Albert model for rer... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class Albert:
"""Albert model for rerank"""
def __init__(self, batch_size):
"""init function"""
<|body_0|>
def construct(self, input_ids, attention_mask, token_type_ids):
"""construct function"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Albert:
"""Albert model for rerank"""
def __init__(self, batch_size):
"""init function"""
super(Albert, self).__init__()
self.expanddims = P.ExpandDims()
self.cast = P.Cast()
self.sub = P.Sub()
self.mul = P.Mul()
self.gather = P.Gather()
sel... | the_stack_v2_python_sparse | research/nlp/tprr/src/albert.py | mindspore-ai/models | train | 301 |
b24607c000e916e6f6618946d56e6c255bb15044 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | DualToRActiveServicer | [
"LicenseRef-scancode-generic-cla",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DualToRActiveServicer:
"""Missing associated documentation comment in .proto file."""
def QueryAdminForwardingPortState(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def SetAdminForwardingPortState(self, request, conte... | stack_v2_sparse_classes_75kplus_train_069284 | 12,711 | permissive | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "QueryAdminForwardingPortState",
"signature": "def QueryAdminForwardingPortState(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "SetAdminForwardi... | 6 | stack_v2_sparse_classes_30k_train_026117 | Implement the Python class `DualToRActiveServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def QueryAdminForwardingPortState(self, request, context): Missing associated documentation comment in .proto file.
- def SetAdminForwardi... | Implement the Python class `DualToRActiveServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def QueryAdminForwardingPortState(self, request, context): Missing associated documentation comment in .proto file.
- def SetAdminForwardi... | a86f0e5b1742d01b8d8a28a537f79bf608955695 | <|skeleton|>
class DualToRActiveServicer:
"""Missing associated documentation comment in .proto file."""
def QueryAdminForwardingPortState(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def SetAdminForwardingPortState(self, request, conte... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DualToRActiveServicer:
"""Missing associated documentation comment in .proto file."""
def QueryAdminForwardingPortState(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Meth... | the_stack_v2_python_sparse | ansible/dualtor/nic_simulator/nic_simulator_grpc_service_pb2_grpc.py | ramakristipati/sonic-mgmt | train | 2 |
d160947cae3f8e94af729f6776fd10ca44d92225 | [
"self.candidate_classes = candidate_classes if isinstance(candidate_classes, (list, tuple)) else [candidate_classes]\nself.throttlers = throttlers if isinstance(throttlers, (list, tuple)) else [throttlers]\nself.nested_relations = nested_relations\nself.self_relations = self_relations\nself.symmetric_relations = sy... | <|body_start_0|>
self.candidate_classes = candidate_classes if isinstance(candidate_classes, (list, tuple)) else [candidate_classes]
self.throttlers = throttlers if isinstance(throttlers, (list, tuple)) else [throttlers]
self.nested_relations = nested_relations
self.self_relations = self... | UDF for performing candidate extraction. | CandidateExtractorUDF | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CandidateExtractorUDF:
"""UDF for performing candidate extraction."""
def __init__(self, candidate_classes: Union[Type[Candidate], List[Type[Candidate]]], throttlers: Union[Throttler, List[Throttler]], self_relations: bool, nested_relations: bool, symmetric_relations: bool, **kwargs: Any) ->... | stack_v2_sparse_classes_75kplus_train_069285 | 12,265 | permissive | [
{
"docstring": "Initialize the CandidateExtractorUDF.",
"name": "__init__",
"signature": "def __init__(self, candidate_classes: Union[Type[Candidate], List[Type[Candidate]]], throttlers: Union[Throttler, List[Throttler]], self_relations: bool, nested_relations: bool, symmetric_relations: bool, **kwargs:... | 2 | stack_v2_sparse_classes_30k_train_017947 | Implement the Python class `CandidateExtractorUDF` described below.
Class description:
UDF for performing candidate extraction.
Method signatures and docstrings:
- def __init__(self, candidate_classes: Union[Type[Candidate], List[Type[Candidate]]], throttlers: Union[Throttler, List[Throttler]], self_relations: bool, ... | Implement the Python class `CandidateExtractorUDF` described below.
Class description:
UDF for performing candidate extraction.
Method signatures and docstrings:
- def __init__(self, candidate_classes: Union[Type[Candidate], List[Type[Candidate]]], throttlers: Union[Throttler, List[Throttler]], self_relations: bool, ... | e857285867f01536192524a195b02cbffe40c4b2 | <|skeleton|>
class CandidateExtractorUDF:
"""UDF for performing candidate extraction."""
def __init__(self, candidate_classes: Union[Type[Candidate], List[Type[Candidate]]], throttlers: Union[Throttler, List[Throttler]], self_relations: bool, nested_relations: bool, symmetric_relations: bool, **kwargs: Any) ->... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CandidateExtractorUDF:
"""UDF for performing candidate extraction."""
def __init__(self, candidate_classes: Union[Type[Candidate], List[Type[Candidate]]], throttlers: Union[Throttler, List[Throttler]], self_relations: bool, nested_relations: bool, symmetric_relations: bool, **kwargs: Any) -> None:
... | the_stack_v2_python_sparse | src/fonduer/candidates/candidates.py | HiromuHota/fonduer | train | 0 |
5b1951ca4052c764fabe5b2de4fc4aef32f6bd68 | [
"if n == 1:\n return '1'\nif n == 2:\n return '11'\nresult = '11'\nflag = 2\nwhile flag < n:\n result = self.count(result)\n flag += 1\nreturn result",
"index = []\ncount = []\nindex.append(input[0])\ncount.append(1)\nfor i in range(1, len(input)):\n if input[i] == input[i - 1]:\n count[-1] ... | <|body_start_0|>
if n == 1:
return '1'
if n == 2:
return '11'
result = '11'
flag = 2
while flag < n:
result = self.count(result)
flag += 1
return result
<|end_body_0|>
<|body_start_1|>
index = []
count = []
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countAndSay(self, n: int) -> str:
"""主函数，控制遍历描述函数的次数 :param n: :return:"""
<|body_0|>
def count(self, input):
"""对上一次结果描述的函数 :param input: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n == 1:
return '1'
... | stack_v2_sparse_classes_75kplus_train_069286 | 2,116 | no_license | [
{
"docstring": "主函数，控制遍历描述函数的次数 :param n: :return:",
"name": "countAndSay",
"signature": "def countAndSay(self, n: int) -> str"
},
{
"docstring": "对上一次结果描述的函数 :param input: :return:",
"name": "count",
"signature": "def count(self, input)"
}
] | 2 | stack_v2_sparse_classes_30k_test_002764 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countAndSay(self, n: int) -> str: 主函数，控制遍历描述函数的次数 :param n: :return:
- def count(self, input): 对上一次结果描述的函数 :param input: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countAndSay(self, n: int) -> str: 主函数，控制遍历描述函数的次数 :param n: :return:
- def count(self, input): 对上一次结果描述的函数 :param input: :return:
<|skeleton|>
class Solution:
def count... | fa45cd44c3d4e7b0205833efcdc708d1638cbbe4 | <|skeleton|>
class Solution:
def countAndSay(self, n: int) -> str:
"""主函数，控制遍历描述函数的次数 :param n: :return:"""
<|body_0|>
def count(self, input):
"""对上一次结果描述的函数 :param input: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def countAndSay(self, n: int) -> str:
"""主函数，控制遍历描述函数的次数 :param n: :return:"""
if n == 1:
return '1'
if n == 2:
return '11'
result = '11'
flag = 2
while flag < n:
result = self.count(result)
flag += 1
... | the_stack_v2_python_sparse | Python/t38.py | g-lyc/LeetCode | train | 15 | |
03ec0f020726295e01791edcdb7fe6a72f38cc03 | [
"self.head = head\nc = head\nlength = 0\nwhile c:\n length += 1\n c = c.next\nself.length = length",
"c = self.head\nrand_index = randrange(0, self.length)\nwhile rand_index:\n c = c.next\n rand_index -= 1\nreturn c.val"
] | <|body_start_0|>
self.head = head
c = head
length = 0
while c:
length += 1
c = c.next
self.length = length
<|end_body_0|>
<|body_start_1|>
c = self.head
rand_index = randrange(0, self.length)
while rand_index:
c = c.nex... | 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_75kplus_train_069287 | 1,038 | 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 | stack_v2_sparse_classes_30k_train_022923 | 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... | 97533d53c8892b6519e99f344489fa4fd4c9ab93 | <|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_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | 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
c = head
length = 0
while c:
length += 1
c = c.... | the_stack_v2_python_sparse | 12. ReserviorSampling/382.py | proTao/leetcode | train | 0 | |
87afac5d563560c732ee67f5a3bdb97735b196f8 | [
"self.batch_size = 0\nself.games = np.asarray([])\nself.max_steps = game_config.game.duration * game_config.game.fps\nself.game_config = game_config\nself.pop_config = pop_config",
"genome_id, genome = genome\nstates = np.asarray([g.reset()[D_SENSOR_LIST] for g in self.games])\nfinished = np.repeat(False, self.ba... | <|body_start_0|>
self.batch_size = 0
self.games = np.asarray([])
self.max_steps = game_config.game.duration * game_config.game.fps
self.game_config = game_config
self.pop_config = pop_config
<|end_body_0|>
<|body_start_1|>
genome_id, genome = genome
states = np.a... | This class provides an environment to evaluate a single genome on multiple games. | MultiEnvironment | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiEnvironment:
"""This class provides an environment to evaluate a single genome on multiple games."""
def __init__(self, game_config: Config, pop_config: Config):
"""Create an environment in which the genomes get evaluated across different games. :param game_config: Config file f... | stack_v2_sparse_classes_75kplus_train_069288 | 7,283 | permissive | [
{
"docstring": "Create an environment in which the genomes get evaluated across different games. :param game_config: Config file for game-creation :param pop_config: Config file specifying how genome's network will be made",
"name": "__init__",
"signature": "def __init__(self, game_config: Config, pop_c... | 4 | stack_v2_sparse_classes_30k_train_054331 | Implement the Python class `MultiEnvironment` described below.
Class description:
This class provides an environment to evaluate a single genome on multiple games.
Method signatures and docstrings:
- def __init__(self, game_config: Config, pop_config: Config): Create an environment in which the genomes get evaluated ... | Implement the Python class `MultiEnvironment` described below.
Class description:
This class provides an environment to evaluate a single genome on multiple games.
Method signatures and docstrings:
- def __init__(self, game_config: Config, pop_config: Config): Create an environment in which the genomes get evaluated ... | 818a4ce941536611c0f1780f7c4a6238f0e1884e | <|skeleton|>
class MultiEnvironment:
"""This class provides an environment to evaluate a single genome on multiple games."""
def __init__(self, game_config: Config, pop_config: Config):
"""Create an environment in which the genomes get evaluated across different games. :param game_config: Config file f... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiEnvironment:
"""This class provides an environment to evaluate a single genome on multiple games."""
def __init__(self, game_config: Config, pop_config: Config):
"""Create an environment in which the genomes get evaluated across different games. :param game_config: Config file for game-creat... | the_stack_v2_python_sparse | environment/env_multi.py | RubenPants/EvolvableRNN | train | 1 |
dd1f7203f1b2a149d773c5488bb6726d1bd17e7e | [
"super(IntermediateClassifier, self).__init__()\nself.num_channels = num_channels\nself.num_classes = num_classes\nself.device = 'cuda'\nkernel_size = global_pooling_size\nself.features = nn.Sequential(nn.AvgPool2d(kernel_size=(kernel_size, kernel_size)), nn.Dropout(p=0.2, inplace=False)).to(self.device)\nself.clas... | <|body_start_0|>
super(IntermediateClassifier, self).__init__()
self.num_channels = num_channels
self.num_classes = num_classes
self.device = 'cuda'
kernel_size = global_pooling_size
self.features = nn.Sequential(nn.AvgPool2d(kernel_size=(kernel_size, kernel_size)), nn.Dr... | IntermediateClassifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IntermediateClassifier:
def __init__(self, global_pooling_size, num_channels, num_classes):
"""Classifier of a cifar10/100 image. :param num_channels: Number of input channels to the classifier :param num_classes: Number of classes to classify"""
<|body_0|>
def forward(self,... | stack_v2_sparse_classes_75kplus_train_069289 | 9,744 | no_license | [
{
"docstring": "Classifier of a cifar10/100 image. :param num_channels: Number of input channels to the classifier :param num_classes: Number of classes to classify",
"name": "__init__",
"signature": "def __init__(self, global_pooling_size, num_channels, num_classes)"
},
{
"docstring": "Drive fe... | 2 | null | Implement the Python class `IntermediateClassifier` described below.
Class description:
Implement the IntermediateClassifier class.
Method signatures and docstrings:
- def __init__(self, global_pooling_size, num_channels, num_classes): Classifier of a cifar10/100 image. :param num_channels: Number of input channels t... | Implement the Python class `IntermediateClassifier` described below.
Class description:
Implement the IntermediateClassifier class.
Method signatures and docstrings:
- def __init__(self, global_pooling_size, num_channels, num_classes): Classifier of a cifar10/100 image. :param num_channels: Number of input channels t... | fd5d3595129140e36411f7abc055b30b233da653 | <|skeleton|>
class IntermediateClassifier:
def __init__(self, global_pooling_size, num_channels, num_classes):
"""Classifier of a cifar10/100 image. :param num_channels: Number of input channels to the classifier :param num_classes: Number of classes to classify"""
<|body_0|>
def forward(self,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IntermediateClassifier:
def __init__(self, global_pooling_size, num_channels, num_classes):
"""Classifier of a cifar10/100 image. :param num_channels: Number of input channels to the classifier :param num_classes: Number of classes to classify"""
super(IntermediateClassifier, self).__init__()
... | the_stack_v2_python_sparse | models/Elastic_SqueezeNet.py | essdev24/elastic-neural-networks-for-classification | train | 0 | |
51736f0c2ce8961e02cc2cf06318e6f0903acfad | [
"import apache_beam as beam\nfrom google.datalab.utils import LambdaJob\nfrom . import _preprocess\nif checkpoint is None:\n checkpoint = _util._DEFAULT_CHECKPOINT_GSURL\njob_id = 'preprocess-image-classification-' + datetime.datetime.now().strftime('%y%m%d-%H%M%S')\noptions = {'project': _util.default_project()... | <|body_start_0|>
import apache_beam as beam
from google.datalab.utils import LambdaJob
from . import _preprocess
if checkpoint is None:
checkpoint = _util._DEFAULT_CHECKPOINT_GSURL
job_id = 'preprocess-image-classification-' + datetime.datetime.now().strftime('%y%m%d-... | Class for local training, preprocessing and prediction. | Local | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Local:
"""Class for local training, preprocessing and prediction."""
def preprocess(train_dataset, output_dir, eval_dataset, checkpoint):
"""Preprocess data locally."""
<|body_0|>
def train(input_dir, batch_size, max_steps, output_dir, checkpoint):
"""Train model... | stack_v2_sparse_classes_75kplus_train_069290 | 3,681 | permissive | [
{
"docstring": "Preprocess data locally.",
"name": "preprocess",
"signature": "def preprocess(train_dataset, output_dir, eval_dataset, checkpoint)"
},
{
"docstring": "Train model locally.",
"name": "train",
"signature": "def train(input_dir, batch_size, max_steps, output_dir, checkpoint)... | 4 | stack_v2_sparse_classes_30k_train_053668 | Implement the Python class `Local` described below.
Class description:
Class for local training, preprocessing and prediction.
Method signatures and docstrings:
- def preprocess(train_dataset, output_dir, eval_dataset, checkpoint): Preprocess data locally.
- def train(input_dir, batch_size, max_steps, output_dir, che... | Implement the Python class `Local` described below.
Class description:
Class for local training, preprocessing and prediction.
Method signatures and docstrings:
- def preprocess(train_dataset, output_dir, eval_dataset, checkpoint): Preprocess data locally.
- def train(input_dir, batch_size, max_steps, output_dir, che... | 8bf007da3e43096aa3a3dca158fc56b286ba6f5c | <|skeleton|>
class Local:
"""Class for local training, preprocessing and prediction."""
def preprocess(train_dataset, output_dir, eval_dataset, checkpoint):
"""Preprocess data locally."""
<|body_0|>
def train(input_dir, batch_size, max_steps, output_dir, checkpoint):
"""Train model... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Local:
"""Class for local training, preprocessing and prediction."""
def preprocess(train_dataset, output_dir, eval_dataset, checkpoint):
"""Preprocess data locally."""
import apache_beam as beam
from google.datalab.utils import LambdaJob
from . import _preprocess
... | the_stack_v2_python_sparse | solutionbox/image_classification/mltoolbox/image/classification/_local.py | googledatalab/pydatalab | train | 200 |
ba6cf20004e4b9c543a487e4bc16c4dbd5b57dbd | [
"def cal(s1: str, s2: str) -> int:\n res = 0\n curSum, curSumWithS2 = (0, -int(1e+18))\n for char in s:\n if char == s1:\n curSum += 1\n curSumWithS2 += 1\n elif char == s2:\n curSum -= 1\n curSumWithS2 = curSum\n if curSum < 0:\n ... | <|body_start_0|>
def cal(s1: str, s2: str) -> int:
res = 0
curSum, curSumWithS2 = (0, -int(1e+18))
for char in s:
if char == s1:
curSum += 1
curSumWithS2 += 1
elif char == s2:
curSum -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestVariance(self, s: str) -> int:
"""时间复杂度O(26*26*n)"""
<|body_0|>
def largestVariance2(self, s: str) -> int:
"""时间复杂度O(26*n)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def cal(s1: str, s2: str) -> int:
res = 0
... | stack_v2_sparse_classes_75kplus_train_069291 | 2,204 | no_license | [
{
"docstring": "时间复杂度O(26*26*n)",
"name": "largestVariance",
"signature": "def largestVariance(self, s: str) -> int"
},
{
"docstring": "时间复杂度O(26*n)",
"name": "largestVariance2",
"signature": "def largestVariance2(self, s: str) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_000867 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestVariance(self, s: str) -> int: 时间复杂度O(26*26*n)
- def largestVariance2(self, s: str) -> int: 时间复杂度O(26*n) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestVariance(self, s: str) -> int: 时间复杂度O(26*26*n)
- def largestVariance2(self, s: str) -> int: 时间复杂度O(26*n)
<|skeleton|>
class Solution:
def largestVariance(self, s... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def largestVariance(self, s: str) -> int:
"""时间复杂度O(26*26*n)"""
<|body_0|>
def largestVariance2(self, s: str) -> int:
"""时间复杂度O(26*n)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def largestVariance(self, s: str) -> int:
"""时间复杂度O(26*26*n)"""
def cal(s1: str, s2: str) -> int:
res = 0
curSum, curSumWithS2 = (0, -int(1e+18))
for char in s:
if char == s1:
curSum += 1
curS... | the_stack_v2_python_sparse | 11_动态规划/子数组/最大子数组和/6069. 最大波动的子字符串-kanade.py | 981377660LMT/algorithm-study | train | 225 | |
924db1e689a1e67ca2cd0b7a1e9b1ce183cdb833 | [
"create_l7policy_flow = linear_flow.Flow(constants.CREATE_L7POLICY_FLOW)\ncreate_l7policy_flow.add(lifecycle_tasks.L7PolicyToErrorOnRevertTask(requires=[constants.L7POLICY, constants.LISTENERS, constants.LOADBALANCER_ID]))\ncreate_l7policy_flow.add(database_tasks.MarkL7PolicyPendingCreateInDB(requires=constants.L7P... | <|body_start_0|>
create_l7policy_flow = linear_flow.Flow(constants.CREATE_L7POLICY_FLOW)
create_l7policy_flow.add(lifecycle_tasks.L7PolicyToErrorOnRevertTask(requires=[constants.L7POLICY, constants.LISTENERS, constants.LOADBALANCER_ID]))
create_l7policy_flow.add(database_tasks.MarkL7PolicyPendin... | L7PolicyFlows | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class L7PolicyFlows:
def get_create_l7policy_flow(self):
"""Create a flow to create an L7 policy :returns: The flow for creating an L7 policy"""
<|body_0|>
def get_delete_l7policy_flow(self):
"""Create a flow to delete an L7 policy :returns: The flow for deleting an L7 pol... | stack_v2_sparse_classes_75kplus_train_069292 | 4,109 | permissive | [
{
"docstring": "Create a flow to create an L7 policy :returns: The flow for creating an L7 policy",
"name": "get_create_l7policy_flow",
"signature": "def get_create_l7policy_flow(self)"
},
{
"docstring": "Create a flow to delete an L7 policy :returns: The flow for deleting an L7 policy",
"na... | 3 | stack_v2_sparse_classes_30k_train_011593 | Implement the Python class `L7PolicyFlows` described below.
Class description:
Implement the L7PolicyFlows class.
Method signatures and docstrings:
- def get_create_l7policy_flow(self): Create a flow to create an L7 policy :returns: The flow for creating an L7 policy
- def get_delete_l7policy_flow(self): Create a flo... | Implement the Python class `L7PolicyFlows` described below.
Class description:
Implement the L7PolicyFlows class.
Method signatures and docstrings:
- def get_create_l7policy_flow(self): Create a flow to create an L7 policy :returns: The flow for creating an L7 policy
- def get_delete_l7policy_flow(self): Create a flo... | 0426285a41464a5015494584f109eed35a0d44db | <|skeleton|>
class L7PolicyFlows:
def get_create_l7policy_flow(self):
"""Create a flow to create an L7 policy :returns: The flow for creating an L7 policy"""
<|body_0|>
def get_delete_l7policy_flow(self):
"""Create a flow to delete an L7 policy :returns: The flow for deleting an L7 pol... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class L7PolicyFlows:
def get_create_l7policy_flow(self):
"""Create a flow to create an L7 policy :returns: The flow for creating an L7 policy"""
create_l7policy_flow = linear_flow.Flow(constants.CREATE_L7POLICY_FLOW)
create_l7policy_flow.add(lifecycle_tasks.L7PolicyToErrorOnRevertTask(requir... | the_stack_v2_python_sparse | octavia/controller/worker/v2/flows/l7policy_flows.py | openstack/octavia | train | 147 | |
076f9b66354cf8d6be88c56dea6d576c8271042e | [
"self.stack = []\nself.l = nestedList\nself.i = 0",
"if self.hasNext():\n v = self.l[self.i]\n self.i += 1\n return v.getInteger()\nelse:\n return None",
"while True:\n while self.i == len(self.l):\n if self.stack:\n self.l, self.i = self.stack.pop()\n self.i += 1\n ... | <|body_start_0|>
self.stack = []
self.l = nestedList
self.i = 0
<|end_body_0|>
<|body_start_1|>
if self.hasNext():
v = self.l[self.i]
self.i += 1
return v.getInteger()
else:
return None
<|end_body_1|>
<|body_start_2|>
whil... | NestedIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NestedIterator:
def __init__(self, nestedList):
"""Initialize your data structure here. :type nestedList: List[NestedInteger]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|e... | stack_v2_sparse_classes_75kplus_train_069293 | 2,819 | no_license | [
{
"docstring": "Initialize your data structure here. :type nestedList: List[NestedInteger]",
"name": "__init__",
"signature": "def __init__(self, nestedList)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"nam... | 3 | stack_v2_sparse_classes_30k_train_049253 | Implement the Python class `NestedIterator` described below.
Class description:
Implement the NestedIterator class.
Method signatures and docstrings:
- def __init__(self, nestedList): Initialize your data structure here. :type nestedList: List[NestedInteger]
- def next(self): :rtype: int
- def hasNext(self): :rtype: ... | Implement the Python class `NestedIterator` described below.
Class description:
Implement the NestedIterator class.
Method signatures and docstrings:
- def __init__(self, nestedList): Initialize your data structure here. :type nestedList: List[NestedInteger]
- def next(self): :rtype: int
- def hasNext(self): :rtype: ... | d6b9f07e2d1437681fa77fee0687ea9b83cab135 | <|skeleton|>
class NestedIterator:
def __init__(self, nestedList):
"""Initialize your data structure here. :type nestedList: List[NestedInteger]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|e... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NestedIterator:
def __init__(self, nestedList):
"""Initialize your data structure here. :type nestedList: List[NestedInteger]"""
self.stack = []
self.l = nestedList
self.i = 0
def next(self):
""":rtype: int"""
if self.hasNext():
v = self.l[self.... | the_stack_v2_python_sparse | python/algorithm/leetcode/341.py | yanxurui/keepcoding | train | 1 | |
fe85a295c6a01d1ba18c185bd8bf8ce9b3b37003 | [
"from nestedworld_api.db import UserFriend as DbUserFriend\nfriends = DbUserFriend.query.filter(DbUserFriend.user_id == current_session.user.id).all()\nreturn friends",
"from nestedworld_api.db import db\nfrom nestedworld_api.db import User as DbUser\nfrom nestedworld_api.db import UserFriend as DbUserFriend\nfri... | <|body_start_0|>
from nestedworld_api.db import UserFriend as DbUserFriend
friends = DbUserFriend.query.filter(DbUserFriend.user_id == current_session.user.id).all()
return friends
<|end_body_0|>
<|body_start_1|>
from nestedworld_api.db import db
from nestedworld_api.db import U... | UserFriends | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserFriends:
def get(self):
"""Retrieve current user's friends list. This request is used by a user for retrieve his own friends list."""
<|body_0|>
def post(self, data):
"""Add an user in to current user's friends list This request is used by a user for create a lin... | stack_v2_sparse_classes_75kplus_train_069294 | 3,764 | no_license | [
{
"docstring": "Retrieve current user's friends list. This request is used by a user for retrieve his own friends list.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Add an user in to current user's friends list This request is used by a user for create a link between him and ... | 2 | null | Implement the Python class `UserFriends` described below.
Class description:
Implement the UserFriends class.
Method signatures and docstrings:
- def get(self): Retrieve current user's friends list. This request is used by a user for retrieve his own friends list.
- def post(self, data): Add an user in to current use... | Implement the Python class `UserFriends` described below.
Class description:
Implement the UserFriends class.
Method signatures and docstrings:
- def get(self): Retrieve current user's friends list. This request is used by a user for retrieve his own friends list.
- def post(self, data): Add an user in to current use... | af2262742b04c823d2cf6e0fa40fa0fc6456671e | <|skeleton|>
class UserFriends:
def get(self):
"""Retrieve current user's friends list. This request is used by a user for retrieve his own friends list."""
<|body_0|>
def post(self, data):
"""Add an user in to current user's friends list This request is used by a user for create a lin... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserFriends:
def get(self):
"""Retrieve current user's friends list. This request is used by a user for retrieve his own friends list."""
from nestedworld_api.db import UserFriend as DbUserFriend
friends = DbUserFriend.query.filter(DbUserFriend.user_id == current_session.user.id).all()... | the_stack_v2_python_sparse | nestedworld_api/views/api/v1/user/friends.py | NestedWorld/NestedWorld-Server-API | train | 1 | |
007bb8e3830951b43655a4d04d853741e20b540d | [
"GaussianClassifier.train(self, trainingData)\ncovariance = numpy.zeros(self.classes[0].stats.cov.shape, numpy.float)\nnsamples = np.sum((cl.stats.nsamples for cl in self.classes))\nfor cl in self.classes:\n covariance += cl.stats.nsamples / float(nsamples) * cl.stats.cov\nself.background = GaussianStats(cov=cov... | <|body_start_0|>
GaussianClassifier.train(self, trainingData)
covariance = numpy.zeros(self.classes[0].stats.cov.shape, numpy.float)
nsamples = np.sum((cl.stats.nsamples for cl in self.classes))
for cl in self.classes:
covariance += cl.stats.nsamples / float(nsamples) * cl.st... | A Classifier using Mahalanobis distance for class discrimination | MahalanobisDistanceClassifier | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MahalanobisDistanceClassifier:
"""A Classifier using Mahalanobis distance for class discrimination"""
def train(self, trainingData):
"""Trains the classifier on the given training data. Arguments: `trainingData` (:class:`~spectral.algorithms.TrainingClassSet`): Data for the training ... | stack_v2_sparse_classes_75kplus_train_069295 | 16,400 | permissive | [
{
"docstring": "Trains the classifier on the given training data. Arguments: `trainingData` (:class:`~spectral.algorithms.TrainingClassSet`): Data for the training classes.",
"name": "train",
"signature": "def train(self, trainingData)"
},
{
"docstring": "Classifies a pixel into one of the train... | 3 | stack_v2_sparse_classes_30k_train_043963 | Implement the Python class `MahalanobisDistanceClassifier` described below.
Class description:
A Classifier using Mahalanobis distance for class discrimination
Method signatures and docstrings:
- def train(self, trainingData): Trains the classifier on the given training data. Arguments: `trainingData` (:class:`~spect... | Implement the Python class `MahalanobisDistanceClassifier` described below.
Class description:
A Classifier using Mahalanobis distance for class discrimination
Method signatures and docstrings:
- def train(self, trainingData): Trains the classifier on the given training data. Arguments: `trainingData` (:class:`~spect... | 0659ee71614455d99a80ffd4f5f5edd8d032608c | <|skeleton|>
class MahalanobisDistanceClassifier:
"""A Classifier using Mahalanobis distance for class discrimination"""
def train(self, trainingData):
"""Trains the classifier on the given training data. Arguments: `trainingData` (:class:`~spectral.algorithms.TrainingClassSet`): Data for the training ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MahalanobisDistanceClassifier:
"""A Classifier using Mahalanobis distance for class discrimination"""
def train(self, trainingData):
"""Trains the classifier on the given training data. Arguments: `trainingData` (:class:`~spectral.algorithms.TrainingClassSet`): Data for the training classes."""
... | the_stack_v2_python_sparse | spectral/algorithms/classifiers.py | spectralpython/spectral | train | 527 |
615c9d91e1d3a4c36cbc59cf315d8765b06bcd35 | [
"View.__init__(self, *args, **kwargs)\nself._plot = PlotWidget()\nself.addWidget(self._plot)\nself.setTitle('PlotView')\nself._pen = {'width': 5}",
"assert type(args) is dict, 'PlotView did not receive a dict while calling update.'\nassert 'xAxis' in args, 'PlotView did not receive an x-axis'\nassert 'yAxis' in a... | <|body_start_0|>
View.__init__(self, *args, **kwargs)
self._plot = PlotWidget()
self.addWidget(self._plot)
self.setTitle('PlotView')
self._pen = {'width': 5}
<|end_body_0|>
<|body_start_1|>
assert type(args) is dict, 'PlotView did not receive a dict while calling update.... | classdocs | PlotView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlotView:
"""classdocs"""
def __init__(self, *args, **kwargs):
"""Constructor"""
<|body_0|>
def update_slot(self, args):
"""Method called to update the plot. In this case, arguments to specify how to draw a line plot. Parameters: - args (:class:`dict`) : a `dict`... | stack_v2_sparse_classes_75kplus_train_069296 | 1,613 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Method called to update the plot. In this case, arguments to specify how to draw a line plot. Parameters: - args (:class:`dict`) : a `dict` with at least two fields - \"xAxis\"... | 2 | null | Implement the Python class `PlotView` described below.
Class description:
classdocs
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Constructor
- def update_slot(self, args): Method called to update the plot. In this case, arguments to specify how to draw a line plot. Parameters: - args (:cla... | Implement the Python class `PlotView` described below.
Class description:
classdocs
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Constructor
- def update_slot(self, args): Method called to update the plot. In this case, arguments to specify how to draw a line plot. Parameters: - args (:cla... | 520f2ed49d381e8d64d7b433e40a2fb42bff85e8 | <|skeleton|>
class PlotView:
"""classdocs"""
def __init__(self, *args, **kwargs):
"""Constructor"""
<|body_0|>
def update_slot(self, args):
"""Method called to update the plot. In this case, arguments to specify how to draw a line plot. Parameters: - args (:class:`dict`) : a `dict`... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PlotView:
"""classdocs"""
def __init__(self, *args, **kwargs):
"""Constructor"""
View.__init__(self, *args, **kwargs)
self._plot = PlotWidget()
self.addWidget(self._plot)
self.setTitle('PlotView')
self._pen = {'width': 5}
def update_slot(self, args):
... | the_stack_v2_python_sparse | src/app/views/PlotView.py | JordanKoeller/MirageOld | train | 0 |
ad115ebc46a0ddff71fcdee2a880a1e7fbe05c72 | [
"component_spc = kwargs['spc'] if 'spc' in kwargs else spc.SPC\nobject.iqObject.__init__(self, parent=parent, resource=resource, spc=component_spc, context=context)\ndb_engine_choice.iqDBEngineChoiceManager.__init__(self, *args, **kwargs)",
"filename = self.getAttribute('filename')\nif filename is None:\n file... | <|body_start_0|>
component_spc = kwargs['spc'] if 'spc' in kwargs else spc.SPC
object.iqObject.__init__(self, parent=parent, resource=resource, spc=component_spc, context=context)
db_engine_choice.iqDBEngineChoiceManager.__init__(self, *args, **kwargs)
<|end_body_0|>
<|body_start_1|>
fi... | Data engine choice component. | iqDataEngineChoice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class iqDataEngineChoice:
"""Data engine choice component."""
def __init__(self, parent=None, resource=None, context=None, *args, **kwargs):
"""Standard component constructor. :param parent: Parent object. :param resource: Object resource dictionary. :param context: Context dictionary."""
... | stack_v2_sparse_classes_75kplus_train_069297 | 1,209 | no_license | [
{
"docstring": "Standard component constructor. :param parent: Parent object. :param resource: Object resource dictionary. :param context: Context dictionary.",
"name": "__init__",
"signature": "def __init__(self, parent=None, resource=None, context=None, *args, **kwargs)"
},
{
"docstring": "Get... | 2 | null | Implement the Python class `iqDataEngineChoice` described below.
Class description:
Data engine choice component.
Method signatures and docstrings:
- def __init__(self, parent=None, resource=None, context=None, *args, **kwargs): Standard component constructor. :param parent: Parent object. :param resource: Object res... | Implement the Python class `iqDataEngineChoice` described below.
Class description:
Data engine choice component.
Method signatures and docstrings:
- def __init__(self, parent=None, resource=None, context=None, *args, **kwargs): Standard component constructor. :param parent: Parent object. :param resource: Object res... | 7550e242746cb2fb1219474463f8db21f8e3e114 | <|skeleton|>
class iqDataEngineChoice:
"""Data engine choice component."""
def __init__(self, parent=None, resource=None, context=None, *args, **kwargs):
"""Standard component constructor. :param parent: Parent object. :param resource: Object resource dictionary. :param context: Context dictionary."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class iqDataEngineChoice:
"""Data engine choice component."""
def __init__(self, parent=None, resource=None, context=None, *args, **kwargs):
"""Standard component constructor. :param parent: Parent object. :param resource: Object resource dictionary. :param context: Context dictionary."""
compo... | the_stack_v2_python_sparse | iq/components/data_engine_choice/component.py | XHermitOne/iq_framework | train | 1 |
323186cdc3c6115d56a4296c6aa248023d06e0d1 | [
"self.__name = '{}_{}'.format(type(self).__name__, id(self))\nself.__overlayList = overlayList\nself.__displayCtx = displayCtx\nself.__target = target\nself.__propNames = propNames\nself.__currentOverlay = None\nself.__cache = {}\nself.__overlayList.addListener('overlays', self.__name, self.__selectedOverlayChanged... | <|body_start_0|>
self.__name = '{}_{}'.format(type(self).__name__, id(self))
self.__overlayList = overlayList
self.__displayCtx = displayCtx
self.__target = target
self.__propNames = propNames
self.__currentOverlay = None
self.__cache = {}
self.__overlayLi... | Deprecated - use :class:`fsleyes_props.PropCache` instead. A little convenience class which can be used to track and cache property values, related to each overlay in the :class:`.OverlayList`, on some :class:`.HasProperties` object. Whenever the selected overlay changes, the property values of the previously selected ... | PropCache | [
"BSD-3-Clause",
"CC-BY-3.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PropCache:
"""Deprecated - use :class:`fsleyes_props.PropCache` instead. A little convenience class which can be used to track and cache property values, related to each overlay in the :class:`.OverlayList`, on some :class:`.HasProperties` object. Whenever the selected overlay changes, the proper... | stack_v2_sparse_classes_75kplus_train_069298 | 18,637 | permissive | [
{
"docstring": "Create a ``PropCache``. :arg overlayList: The :class:`.OverlayList`. :arg displayCtx: The :class:`.DisplayContext` instance. :arg target: The :class:`.HasProperties` instance containing the properties that are to be cached. :arg propNames: List containing the names of ``target`` properties to be... | 5 | stack_v2_sparse_classes_30k_train_039745 | Implement the Python class `PropCache` described below.
Class description:
Deprecated - use :class:`fsleyes_props.PropCache` instead. A little convenience class which can be used to track and cache property values, related to each overlay in the :class:`.OverlayList`, on some :class:`.HasProperties` object. Whenever t... | Implement the Python class `PropCache` described below.
Class description:
Deprecated - use :class:`fsleyes_props.PropCache` instead. A little convenience class which can be used to track and cache property values, related to each overlay in the :class:`.OverlayList`, on some :class:`.HasProperties` object. Whenever t... | 46ccb4fe2b2346eb57576247f49714032b61307a | <|skeleton|>
class PropCache:
"""Deprecated - use :class:`fsleyes_props.PropCache` instead. A little convenience class which can be used to track and cache property values, related to each overlay in the :class:`.OverlayList`, on some :class:`.HasProperties` object. Whenever the selected overlay changes, the proper... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PropCache:
"""Deprecated - use :class:`fsleyes_props.PropCache` instead. A little convenience class which can be used to track and cache property values, related to each overlay in the :class:`.OverlayList`, on some :class:`.HasProperties` object. Whenever the selected overlay changes, the property values of ... | the_stack_v2_python_sparse | fsleyes/overlay.py | sanjayankur31/fsleyes | train | 1 |
bf424c2992dfc90eaead1edb7d06a374a0ec57ee | [
"disableCSRFProtection()\nif language is None:\n language = os.environ.get('LANGUAGE') or 'en'\nregistry = getUtility(IRegistry)\nsettings = registry.forInterface(ILanguageSchema, prefix='plone')\nsettings.default_language = language",
"for arg in [x for x in args if '=' in x]:\n name, value = arg.split('='... | <|body_start_0|>
disableCSRFProtection()
if language is None:
language = os.environ.get('LANGUAGE') or 'en'
registry = getUtility(IRegistry)
settings = registry.forInterface(ILanguageSchema, prefix='plone')
settings.default_language = language
<|end_body_0|>
<|body_s... | I18N | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class I18N:
def set_default_language(self, language=None):
"""Change portal default language"""
<|body_0|>
def translate(self, msgid, *args, **kwargs):
"""Return localized string for given msgid"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
disableCSRFP... | stack_v2_sparse_classes_75kplus_train_069299 | 2,068 | no_license | [
{
"docstring": "Change portal default language",
"name": "set_default_language",
"signature": "def set_default_language(self, language=None)"
},
{
"docstring": "Return localized string for given msgid",
"name": "translate",
"signature": "def translate(self, msgid, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_027234 | Implement the Python class `I18N` described below.
Class description:
Implement the I18N class.
Method signatures and docstrings:
- def set_default_language(self, language=None): Change portal default language
- def translate(self, msgid, *args, **kwargs): Return localized string for given msgid | Implement the Python class `I18N` described below.
Class description:
Implement the I18N class.
Method signatures and docstrings:
- def set_default_language(self, language=None): Change portal default language
- def translate(self, msgid, *args, **kwargs): Return localized string for given msgid
<|skeleton|>
class I... | c67a08671050f3c0ed156b09b44902ad1544b382 | <|skeleton|>
class I18N:
def set_default_language(self, language=None):
"""Change portal default language"""
<|body_0|>
def translate(self, msgid, *args, **kwargs):
"""Return localized string for given msgid"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class I18N:
def set_default_language(self, language=None):
"""Change portal default language"""
disableCSRFProtection()
if language is None:
language = os.environ.get('LANGUAGE') or 'en'
registry = getUtility(IRegistry)
settings = registry.forInterface(ILanguageSc... | the_stack_v2_python_sparse | src/plone/app/robotframework/i18n.py | plone/plone.app.robotframework | train | 9 |
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