blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
faed9bb27328d9831be61a72b39f60808dd77580 | [
"super(OperationIdsCache, self).__init__()\nself.reservations_list = []\nself.max_size = size",
"super(OperationIdsCache, self).__setitem__(key, value)\nself.reservations_list.append(key)\nto_remove = len(self) - self.max_size\nfor _ in range(to_remove):\n old_key = self.reservations_list.pop(0)\n del self[... | <|body_start_0|>
super(OperationIdsCache, self).__init__()
self.reservations_list = []
self.max_size = size
<|end_body_0|>
<|body_start_1|>
super(OperationIdsCache, self).__setitem__(key, value)
self.reservations_list.append(key)
to_remove = len(self) - self.max_size
... | A cache of recently created operations | OperationIdsCache | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OperationIdsCache:
"""A cache of recently created operations"""
def __init__(self, size=256):
"""Creates new OperationsCache. Args: size: An integer specifying the maximum size of the cache."""
<|body_0|>
def __setitem__(self, key, value):
"""Adds a new operation... | stack_v2_sparse_classes_36k_train_012500 | 836 | permissive | [
{
"docstring": "Creates new OperationsCache. Args: size: An integer specifying the maximum size of the cache.",
"name": "__init__",
"signature": "def __init__(self, size=256)"
},
{
"docstring": "Adds a new operation to the cache. Args: key: A string specifying the operation ID. value: A dictiona... | 2 | null | Implement the Python class `OperationIdsCache` described below.
Class description:
A cache of recently created operations
Method signatures and docstrings:
- def __init__(self, size=256): Creates new OperationsCache. Args: size: An integer specifying the maximum size of the cache.
- def __setitem__(self, key, value):... | Implement the Python class `OperationIdsCache` described below.
Class description:
A cache of recently created operations
Method signatures and docstrings:
- def __init__(self, size=256): Creates new OperationsCache. Args: size: An integer specifying the maximum size of the cache.
- def __setitem__(self, key, value):... | be17e5f658d7b42b5aa7eeb7a5ddd4962f3ea82f | <|skeleton|>
class OperationIdsCache:
"""A cache of recently created operations"""
def __init__(self, size=256):
"""Creates new OperationsCache. Args: size: An integer specifying the maximum size of the cache."""
<|body_0|>
def __setitem__(self, key, value):
"""Adds a new operation... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OperationIdsCache:
"""A cache of recently created operations"""
def __init__(self, size=256):
"""Creates new OperationsCache. Args: size: An integer specifying the maximum size of the cache."""
super(OperationIdsCache, self).__init__()
self.reservations_list = []
self.max_... | the_stack_v2_python_sparse | InfrastructureManager/appscale/infrastructure/operation_ids_cache.py | obino/appscale | train | 1 |
99a2270d59587fcadbf077e9d9ffb83da95939d9 | [
"super().__init__()\nself.l_length = l_length\nself.min_value = min_value\nself.max_value = max_value\nself.distinct_elements = distinct_elements\nself.worst_case = worst_case\nself._construct()",
"new_element = random.randint(a=self.min_value, b=self.max_value)\nwhile new_element in already_used:\n new_elemen... | <|body_start_0|>
super().__init__()
self.l_length = l_length
self.min_value = min_value
self.max_value = max_value
self.distinct_elements = distinct_elements
self.worst_case = worst_case
self._construct()
<|end_body_0|>
<|body_start_1|>
new_element = rand... | InputList | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputList:
def __init__(self, l_length: int=100, min_value: int=0, max_value: int=10000, distinct_elements: bool=True, worst_case: bool=False):
"""Object of input list for algorithms Parameters ---------- l_length (int): Length of the input list min_value (int): Minimal value of the elem... | stack_v2_sparse_classes_36k_train_012501 | 3,885 | permissive | [
{
"docstring": "Object of input list for algorithms Parameters ---------- l_length (int): Length of the input list min_value (int): Minimal value of the elements of the list max_value (int): Maximal value of the elements of the list distinct_elements (bool): distinct elements in the list worst_case (bool): in t... | 3 | stack_v2_sparse_classes_30k_train_004944 | Implement the Python class `InputList` described below.
Class description:
Implement the InputList class.
Method signatures and docstrings:
- def __init__(self, l_length: int=100, min_value: int=0, max_value: int=10000, distinct_elements: bool=True, worst_case: bool=False): Object of input list for algorithms Paramet... | Implement the Python class `InputList` described below.
Class description:
Implement the InputList class.
Method signatures and docstrings:
- def __init__(self, l_length: int=100, min_value: int=0, max_value: int=10000, distinct_elements: bool=True, worst_case: bool=False): Object of input list for algorithms Paramet... | 20d8df6172906337f81583dabb841d66b8f31857 | <|skeleton|>
class InputList:
def __init__(self, l_length: int=100, min_value: int=0, max_value: int=10000, distinct_elements: bool=True, worst_case: bool=False):
"""Object of input list for algorithms Parameters ---------- l_length (int): Length of the input list min_value (int): Minimal value of the elem... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InputList:
def __init__(self, l_length: int=100, min_value: int=0, max_value: int=10000, distinct_elements: bool=True, worst_case: bool=False):
"""Object of input list for algorithms Parameters ---------- l_length (int): Length of the input list min_value (int): Minimal value of the elements of the li... | the_stack_v2_python_sparse | new_algs/Sequence+algorithms/Selection+algorithm/inputs.py | coolsnake/JupyterNotebook | train | 0 | |
00af92de8d7ae98cd5080e9f0bd324a3d3aad1e9 | [
"res = []\n\ndef dfs(root, depth):\n if not root:\n return\n if depth >= len(res):\n res.append(0)\n res[depth] = root.val\n dfs(root.left, depth + 1)\n dfs(root.right, depth + 1)\ndfs(root, 0)\nreturn res",
"from collections import deque\nmax_depth = -1\nq = deque([(root, 0)])\nright... | <|body_start_0|>
res = []
def dfs(root, depth):
if not root:
return
if depth >= len(res):
res.append(0)
res[depth] = root.val
dfs(root.left, depth + 1)
dfs(root.right, depth + 1)
dfs(root, 0)
ret... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rightSideView1(self, root: TreeNode) -> List[int]:
"""dfs"""
<|body_0|>
def rightSideView2(self, root: TreeNode) -> List[int]:
"""bfs"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
def dfs(root, depth):
i... | stack_v2_sparse_classes_36k_train_012502 | 1,667 | no_license | [
{
"docstring": "dfs",
"name": "rightSideView1",
"signature": "def rightSideView1(self, root: TreeNode) -> List[int]"
},
{
"docstring": "bfs",
"name": "rightSideView2",
"signature": "def rightSideView2(self, root: TreeNode) -> List[int]"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rightSideView1(self, root: TreeNode) -> List[int]: dfs
- def rightSideView2(self, root: TreeNode) -> List[int]: bfs | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rightSideView1(self, root: TreeNode) -> List[int]: dfs
- def rightSideView2(self, root: TreeNode) -> List[int]: bfs
<|skeleton|>
class Solution:
def rightSideView1(self... | 40726506802d2d60028fdce206696b1df2f63ece | <|skeleton|>
class Solution:
def rightSideView1(self, root: TreeNode) -> List[int]:
"""dfs"""
<|body_0|>
def rightSideView2(self, root: TreeNode) -> List[int]:
"""bfs"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rightSideView1(self, root: TreeNode) -> List[int]:
"""dfs"""
res = []
def dfs(root, depth):
if not root:
return
if depth >= len(res):
res.append(0)
res[depth] = root.val
dfs(root.left, depth ... | the_stack_v2_python_sparse | 二刷+题解/剑指offer/rightSideView.py | 1oser5/LeetCode | train | 0 | |
9ef01a2b83306d49cc62802196499c1c7f28619e | [
"strlen = len(s)\nmax = 0\nimax = 0\njmax = 0\nif str == '' or strlen == 1:\n return s\ndp = [[0] * (strlen + 1) for j in range(strlen + 1)]\nfor i in range(strlen - 2, -1, -1):\n for j in range(i, strlen):\n if i == j:\n dp[i][j] = 1\n if max < 1:\n max = 1\n ... | <|body_start_0|>
strlen = len(s)
max = 0
imax = 0
jmax = 0
if str == '' or strlen == 1:
return s
dp = [[0] * (strlen + 1) for j in range(strlen + 1)]
for i in range(strlen - 2, -1, -1):
for j in range(i, strlen):
if i == j:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome1(self, s):
"""给定一个字符串 s，找到 s 中最长的回文子串。你可以假设 s 的最大长度为 1000。 :type s: str :rtype: str 动态规划法 最长回文子串"""
<|body_0|>
def longestPalindrome2(self, s):
""":param s: str :return: str 试图使用中心扩展法"""
<|body_1|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_36k_train_012503 | 2,416 | no_license | [
{
"docstring": "给定一个字符串 s，找到 s 中最长的回文子串。你可以假设 s 的最大长度为 1000。 :type s: str :rtype: str 动态规划法 最长回文子串",
"name": "longestPalindrome1",
"signature": "def longestPalindrome1(self, s)"
},
{
"docstring": ":param s: str :return: str 试图使用中心扩展法",
"name": "longestPalindrome2",
"signature": "def long... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome1(self, s): 给定一个字符串 s，找到 s 中最长的回文子串。你可以假设 s 的最大长度为 1000。 :type s: str :rtype: str 动态规划法 最长回文子串
- def longestPalindrome2(self, s): :param s: str :return: str ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome1(self, s): 给定一个字符串 s，找到 s 中最长的回文子串。你可以假设 s 的最大长度为 1000。 :type s: str :rtype: str 动态规划法 最长回文子串
- def longestPalindrome2(self, s): :param s: str :return: str ... | e7a7b7537edbbb8fa35c2dddf2b122cf863e479d | <|skeleton|>
class Solution:
def longestPalindrome1(self, s):
"""给定一个字符串 s，找到 s 中最长的回文子串。你可以假设 s 的最大长度为 1000。 :type s: str :rtype: str 动态规划法 最长回文子串"""
<|body_0|>
def longestPalindrome2(self, s):
""":param s: str :return: str 试图使用中心扩展法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestPalindrome1(self, s):
"""给定一个字符串 s，找到 s 中最长的回文子串。你可以假设 s 的最大长度为 1000。 :type s: str :rtype: str 动态规划法 最长回文子串"""
strlen = len(s)
max = 0
imax = 0
jmax = 0
if str == '' or strlen == 1:
return s
dp = [[0] * (strlen + 1) for j... | the_stack_v2_python_sparse | Dynamic programming/最长回文子串L5.py | QiuHongHao123/Algorithm-Practise | train | 0 | |
af97b5f564546693546ca7660bbd349b93fdc8b0 | [
"if 'sign' in data:\n del data['sign']\ndataList = []\nfor key in sorted(data):\n dataList.append('%s=%s' % (key, data[key]))\nreturn '&'.join(dataList).strip()",
"data = data + api_key.strip()\nmd5 = hashlib.md5()\nmd5.update(data.encode(encoding='UTF-8'))\nreturn md5.hexdigest()",
"if cls.md5_sign(data)... | <|body_start_0|>
if 'sign' in data:
del data['sign']
dataList = []
for key in sorted(data):
dataList.append('%s=%s' % (key, data[key]))
return '&'.join(dataList).strip()
<|end_body_0|>
<|body_start_1|>
data = data + api_key.strip()
md5 = hashlib.m... | MD5签名和验签 | SignatureAndVerification | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignatureAndVerification:
"""MD5签名和验签"""
def data_processing(cls, data):
""":param data: 需要签名的数据，字典类型 :return: 处理后的字符串，格式为：参数名称=参数值，并用&连接"""
<|body_0|>
def md5_sign(cls, data, api_key):
"""MD5签名 :param api_key: MD5签名需要的字符串 :return: 签名后的字符串sign"""
<|body_1... | stack_v2_sparse_classes_36k_train_012504 | 2,421 | no_license | [
{
"docstring": ":param data: 需要签名的数据，字典类型 :return: 处理后的字符串，格式为：参数名称=参数值，并用&连接",
"name": "data_processing",
"signature": "def data_processing(cls, data)"
},
{
"docstring": "MD5签名 :param api_key: MD5签名需要的字符串 :return: 签名后的字符串sign",
"name": "md5_sign",
"signature": "def md5_sign(cls, data, a... | 3 | stack_v2_sparse_classes_30k_train_004004 | Implement the Python class `SignatureAndVerification` described below.
Class description:
MD5签名和验签
Method signatures and docstrings:
- def data_processing(cls, data): :param data: 需要签名的数据，字典类型 :return: 处理后的字符串，格式为：参数名称=参数值，并用&连接
- def md5_sign(cls, data, api_key): MD5签名 :param api_key: MD5签名需要的字符串 :return: 签名后的字符串sig... | Implement the Python class `SignatureAndVerification` described below.
Class description:
MD5签名和验签
Method signatures and docstrings:
- def data_processing(cls, data): :param data: 需要签名的数据，字典类型 :return: 处理后的字符串，格式为：参数名称=参数值，并用&连接
- def md5_sign(cls, data, api_key): MD5签名 :param api_key: MD5签名需要的字符串 :return: 签名后的字符串sig... | 80527bc439395a14a0ff00d773123a6eac2019b7 | <|skeleton|>
class SignatureAndVerification:
"""MD5签名和验签"""
def data_processing(cls, data):
""":param data: 需要签名的数据，字典类型 :return: 处理后的字符串，格式为：参数名称=参数值，并用&连接"""
<|body_0|>
def md5_sign(cls, data, api_key):
"""MD5签名 :param api_key: MD5签名需要的字符串 :return: 签名后的字符串sign"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SignatureAndVerification:
"""MD5签名和验签"""
def data_processing(cls, data):
""":param data: 需要签名的数据，字典类型 :return: 处理后的字符串，格式为：参数名称=参数值，并用&连接"""
if 'sign' in data:
del data['sign']
dataList = []
for key in sorted(data):
dataList.append('%s=%s' % (key, d... | the_stack_v2_python_sparse | MD5method.py | ManT21/SevendAutoTest | train | 0 |
7f645254ced2e1ee7631e6f70b8f62a9707302fb | [
"user_id = self.scope['url_route']['kwargs']['token']\nuser_group_name = f'user_{user_id}'\nawait self.channel_layer.group_add(user_group_name, self.channel_name)\nawait self.accept()",
"task_title = event['task_title']\nuser = event['user_id']\nevaluator = event['evaluator']\nawait self.send(text_data=json.dumps... | <|body_start_0|>
user_id = self.scope['url_route']['kwargs']['token']
user_group_name = f'user_{user_id}'
await self.channel_layer.group_add(user_group_name, self.channel_name)
await self.accept()
<|end_body_0|>
<|body_start_1|>
task_title = event['task_title']
user = ev... | Async consumer to handle notification logic. | NotificationConsumer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationConsumer:
"""Async consumer to handle notification logic."""
async def connect(self):
"""Handle websocket connection asynchronously. Add current user to group by his id. This is done for user take only notification about self solutions, not everyone."""
<|body_0|>... | stack_v2_sparse_classes_36k_train_012505 | 3,843 | no_license | [
{
"docstring": "Handle websocket connection asynchronously. Add current user to group by his id. This is done for user take only notification about self solutions, not everyone.",
"name": "connect",
"signature": "async def connect(self)"
},
{
"docstring": "Receive new message event and send it t... | 2 | null | Implement the Python class `NotificationConsumer` described below.
Class description:
Async consumer to handle notification logic.
Method signatures and docstrings:
- async def connect(self): Handle websocket connection asynchronously. Add current user to group by his id. This is done for user take only notification ... | Implement the Python class `NotificationConsumer` described below.
Class description:
Async consumer to handle notification logic.
Method signatures and docstrings:
- async def connect(self): Handle websocket connection asynchronously. Add current user to group by his id. This is done for user take only notification ... | 0879ade24685b628624dce06698f8a0afd042000 | <|skeleton|>
class NotificationConsumer:
"""Async consumer to handle notification logic."""
async def connect(self):
"""Handle websocket connection asynchronously. Add current user to group by his id. This is done for user take only notification about self solutions, not everyone."""
<|body_0|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotificationConsumer:
"""Async consumer to handle notification logic."""
async def connect(self):
"""Handle websocket connection asynchronously. Add current user to group by his id. This is done for user take only notification about self solutions, not everyone."""
user_id = self.scope['u... | the_stack_v2_python_sparse | camp-python-2021-course-tracker-develop/apps/websockets/consumers.py | rhanmar/oi_projects_summer_2021 | train | 0 |
5716191e2f070ef8397849ff602a1cfa6936bdb1 | [
"data = []\nwith open(file_path, '-r') as f:\n dict_data = json.load(f.read())\n for i in dict_data:\n data.append(tuple(i.values()))\nreturn data",
"page = Home_page(browser)\npage.get(StaticConfig.pchome_url)\nif page.monetate_icon is True:\n page.monetate_icon.click()\nelse:\n pass\npage.sea... | <|body_start_0|>
data = []
with open(file_path, '-r') as f:
dict_data = json.load(f.read())
for i in dict_data:
data.append(tuple(i.values()))
return data
<|end_body_0|>
<|body_start_1|>
page = Home_page(browser)
page.get(StaticConfig.pcho... | 搜索测试 | Test_Search | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_Search:
"""搜索测试"""
def get_data(self, file_path):
"""读取参数化文件"""
<|body_0|>
def test_1search_key_word(self, name, key_words, browser):
"""首页关键字搜索"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = []
with open(file_path, '-r') as... | stack_v2_sparse_classes_36k_train_012506 | 1,360 | no_license | [
{
"docstring": "读取参数化文件",
"name": "get_data",
"signature": "def get_data(self, file_path)"
},
{
"docstring": "首页关键字搜索",
"name": "test_1search_key_word",
"signature": "def test_1search_key_word(self, name, key_words, browser)"
}
] | 2 | null | Implement the Python class `Test_Search` described below.
Class description:
搜索测试
Method signatures and docstrings:
- def get_data(self, file_path): 读取参数化文件
- def test_1search_key_word(self, name, key_words, browser): 首页关键字搜索 | Implement the Python class `Test_Search` described below.
Class description:
搜索测试
Method signatures and docstrings:
- def get_data(self, file_path): 读取参数化文件
- def test_1search_key_word(self, name, key_words, browser): 首页关键字搜索
<|skeleton|>
class Test_Search:
"""搜索测试"""
def get_data(self, file_path):
... | 567836fc9aebcc67acb2816364ba89ffa8d356db | <|skeleton|>
class Test_Search:
"""搜索测试"""
def get_data(self, file_path):
"""读取参数化文件"""
<|body_0|>
def test_1search_key_word(self, name, key_words, browser):
"""首页关键字搜索"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_Search:
"""搜索测试"""
def get_data(self, file_path):
"""读取参数化文件"""
data = []
with open(file_path, '-r') as f:
dict_data = json.load(f.read())
for i in dict_data:
data.append(tuple(i.values()))
return data
def test_1search_key_... | the_stack_v2_python_sparse | pytestFrame/test_case/test_pczh/test_mainsteam.py | JasonTang7/inspiration | train | 0 |
920f7b98e248f836c90086ca7e8d13fc00973ba6 | [
"try:\n org = Organization.objects.get(pk=organization_pk)\nexcept ObjectDoesNotExist:\n return JsonResponse({'status': 'error', 'message': 'Could not retrieve organization at organization_pk = ' + str(organization_pk)}, status=status.HTTP_404_NOT_FOUND)\nusers = []\nfor u in org.organizationuser_set.all():\n... | <|body_start_0|>
try:
org = Organization.objects.get(pk=organization_pk)
except ObjectDoesNotExist:
return JsonResponse({'status': 'error', 'message': 'Could not retrieve organization at organization_pk = ' + str(organization_pk)}, status=status.HTTP_404_NOT_FOUND)
users ... | OrganizationUserViewSet | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrganizationUserViewSet:
def list(self, request, organization_pk):
"""Retrieve all users belonging to an org."""
<|body_0|>
def add(self, request, organization_pk, pk):
"""Adds an existing user to an organization as an owner."""
<|body_1|>
def remove(sel... | stack_v2_sparse_classes_36k_train_012507 | 5,593 | permissive | [
{
"docstring": "Retrieve all users belonging to an org.",
"name": "list",
"signature": "def list(self, request, organization_pk)"
},
{
"docstring": "Adds an existing user to an organization as an owner.",
"name": "add",
"signature": "def add(self, request, organization_pk, pk)"
},
{
... | 3 | null | Implement the Python class `OrganizationUserViewSet` described below.
Class description:
Implement the OrganizationUserViewSet class.
Method signatures and docstrings:
- def list(self, request, organization_pk): Retrieve all users belonging to an org.
- def add(self, request, organization_pk, pk): Adds an existing us... | Implement the Python class `OrganizationUserViewSet` described below.
Class description:
Implement the OrganizationUserViewSet class.
Method signatures and docstrings:
- def list(self, request, organization_pk): Retrieve all users belonging to an org.
- def add(self, request, organization_pk, pk): Adds an existing us... | 680b6a2b45f3c568d779d8ac86553a0b08c384c8 | <|skeleton|>
class OrganizationUserViewSet:
def list(self, request, organization_pk):
"""Retrieve all users belonging to an org."""
<|body_0|>
def add(self, request, organization_pk, pk):
"""Adds an existing user to an organization as an owner."""
<|body_1|>
def remove(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrganizationUserViewSet:
def list(self, request, organization_pk):
"""Retrieve all users belonging to an org."""
try:
org = Organization.objects.get(pk=organization_pk)
except ObjectDoesNotExist:
return JsonResponse({'status': 'error', 'message': 'Could not retr... | the_stack_v2_python_sparse | seed/views/v3/organization_users.py | SEED-platform/seed | train | 108 | |
18d716877f083c49a62db27fb61836cb05c93ddc | [
"l = len(nums)\ni = 0\nwhile i < l:\n j = i + 1\n while j < l:\n if nums[i] == nums[j]:\n return nums[i]\n j += 1\n i += 1\nreturn 0",
"l = len(nums)\nfast = nums[nums[0]]\nslow = nums[0]\nwhile fast != slow:\n fast = nums[nums[fast]]\n slow = nums[slow]\nfast = 0\nwhile fa... | <|body_start_0|>
l = len(nums)
i = 0
while i < l:
j = i + 1
while j < l:
if nums[i] == nums[j]:
return nums[i]
j += 1
i += 1
return 0
<|end_body_0|>
<|body_start_1|>
l = len(nums)
fas... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicate1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
l = len(nums)
i = 0
whil... | stack_v2_sparse_classes_36k_train_012508 | 1,495 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findDuplicate1",
"signature": "def findDuplicate1(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findDuplicate",
"signature": "def findDuplicate(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009594 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate1(self, nums): :type nums: List[int] :rtype: int
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate1(self, nums): :type nums: List[int] :rtype: int
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def findDu... | e5b018493bbd12edcdcd0434f35d9c358106d391 | <|skeleton|>
class Solution:
def findDuplicate1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDuplicate1(self, nums):
""":type nums: List[int] :rtype: int"""
l = len(nums)
i = 0
while i < l:
j = i + 1
while j < l:
if nums[i] == nums[j]:
return nums[i]
j += 1
i += 1
... | the_stack_v2_python_sparse | py/leetcode/287.py | wfeng1991/learnpy | train | 0 | |
2a4d6f68db9b63d5d26253d58fb1b43cdb25206e | [
"last_comment_by = self.data.get('last_comment_by', None)\nif last_comment_by is None:\n last_comment_by = self.BASE_LAST_COMMENT_BY.copy()\nnow = datetime.datetime.utcnow().isoformat()\nif is_public is True:\n last_comment_by['public']['name'] = user.get_initials()\n last_comment_by['public']['date_of'] =... | <|body_start_0|>
last_comment_by = self.data.get('last_comment_by', None)
if last_comment_by is None:
last_comment_by = self.BASE_LAST_COMMENT_BY.copy()
now = datetime.datetime.utcnow().isoformat()
if is_public is True:
last_comment_by['public']['name'] = user.get... | Save the last comment (public|privileged) in the data field | ItemLastCommentByMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItemLastCommentByMixin:
"""Save the last comment (public|privileged) in the data field"""
def set_last_comment_by(self, is_public, user):
"""Save in our data field the appropriate last user info for whoever commented take note that college comments should not be shown to normal users... | stack_v2_sparse_classes_36k_train_012509 | 17,116 | no_license | [
{
"docstring": "Save in our data field the appropriate last user info for whoever commented take note that college comments should not be shown to normal users",
"name": "set_last_comment_by",
"signature": "def set_last_comment_by(self, is_public, user)"
},
{
"docstring": "So get the last commen... | 2 | null | Implement the Python class `ItemLastCommentByMixin` described below.
Class description:
Save the last comment (public|privileged) in the data field
Method signatures and docstrings:
- def set_last_comment_by(self, is_public, user): Save in our data field the appropriate last user info for whoever commented take note ... | Implement the Python class `ItemLastCommentByMixin` described below.
Class description:
Save the last comment (public|privileged) in the data field
Method signatures and docstrings:
- def set_last_comment_by(self, is_public, user): Save in our data field the appropriate last user info for whoever commented take note ... | cdda3dd17a776bf2a07fe093304160bf3c43199b | <|skeleton|>
class ItemLastCommentByMixin:
"""Save the last comment (public|privileged) in the data field"""
def set_last_comment_by(self, is_public, user):
"""Save in our data field the appropriate last user info for whoever commented take note that college comments should not be shown to normal users... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ItemLastCommentByMixin:
"""Save the last comment (public|privileged) in the data field"""
def set_last_comment_by(self, is_public, user):
"""Save in our data field the appropriate last user info for whoever commented take note that college comments should not be shown to normal users"""
l... | the_stack_v2_python_sparse | toolkit/core/item/mixins.py | rosscdh/toolkit | train | 1 |
8fa63dba2eed1fe8f1c1b7c4ec7c6fd169937506 | [
"global knowledge_maintain_page, admin_page\nknowledge_maintain_page = KnowledgeMaintainPage(self.driver)\nadmin_page = AdminPage(self.driver)\nadmin_page.into_subsystem('业务管理')\nadmin_page.select_menu('首页/渠道终端管理/维护知识库')",
"admin_page.select_menu('T维护知识库')\nknowledge_maintain_page.query_knowledge_maintain(device=... | <|body_start_0|>
global knowledge_maintain_page, admin_page
knowledge_maintain_page = KnowledgeMaintainPage(self.driver)
admin_page = AdminPage(self.driver)
admin_page.into_subsystem('业务管理')
admin_page.select_menu('首页/渠道终端管理/维护知识库')
<|end_body_0|>
<|body_start_1|>
admin_... | TestKnowledgeMaintain | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestKnowledgeMaintain:
def set_up(self):
"""前置操作 :return:"""
<|body_0|>
def test_query_knowledge_maintain(self, set_up):
"""知识库维护查询 :return:"""
<|body_1|>
def test_reset_query_knowledge_maintain(self):
"""重置查询 :return:"""
<|body_2|>
... | stack_v2_sparse_classes_36k_train_012510 | 2,029 | no_license | [
{
"docstring": "前置操作 :return:",
"name": "set_up",
"signature": "def set_up(self)"
},
{
"docstring": "知识库维护查询 :return:",
"name": "test_query_knowledge_maintain",
"signature": "def test_query_knowledge_maintain(self, set_up)"
},
{
"docstring": "重置查询 :return:",
"name": "test_res... | 4 | stack_v2_sparse_classes_30k_train_005516 | Implement the Python class `TestKnowledgeMaintain` described below.
Class description:
Implement the TestKnowledgeMaintain class.
Method signatures and docstrings:
- def set_up(self): 前置操作 :return:
- def test_query_knowledge_maintain(self, set_up): 知识库维护查询 :return:
- def test_reset_query_knowledge_maintain(self): 重置查... | Implement the Python class `TestKnowledgeMaintain` described below.
Class description:
Implement the TestKnowledgeMaintain class.
Method signatures and docstrings:
- def set_up(self): 前置操作 :return:
- def test_query_knowledge_maintain(self, set_up): 知识库维护查询 :return:
- def test_reset_query_knowledge_maintain(self): 重置查... | 86d1b085af2d3808ac8472d541f4bf26d26591e0 | <|skeleton|>
class TestKnowledgeMaintain:
def set_up(self):
"""前置操作 :return:"""
<|body_0|>
def test_query_knowledge_maintain(self, set_up):
"""知识库维护查询 :return:"""
<|body_1|>
def test_reset_query_knowledge_maintain(self):
"""重置查询 :return:"""
<|body_2|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestKnowledgeMaintain:
def set_up(self):
"""前置操作 :return:"""
global knowledge_maintain_page, admin_page
knowledge_maintain_page = KnowledgeMaintainPage(self.driver)
admin_page = AdminPage(self.driver)
admin_page.into_subsystem('业务管理')
admin_page.select_menu('首页/... | the_stack_v2_python_sparse | src/cases/business_manage/channel_device_manage/knowledge_manage/test_knowledge_maintain_page_350.py | 102244653/SeleniumByPython | train | 2 | |
bdde52b96920c9784a149e0b3608ec417c5a011e | [
"session = self._factory.create(self._transact)\nsession.start()\n\ndef run():\n result = UserAPI().get([u'anon'])\n session.auth.login(u'anon', result[u'anon']['id'])\n return session\nreturn session.transact.run(run)",
"username = username.decode('utf-8').lower()\npassword = password.decode('utf-8')\nn... | <|body_start_0|>
session = self._factory.create(self._transact)
session.start()
def run():
result = UserAPI().get([u'anon'])
session.auth.login(u'anon', result[u'anon']['id'])
return session
return session.transact.run(run)
<|end_body_0|>
<|body_star... | FacadeAuthMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FacadeAuthMixin:
def createAnonymousSession(self):
"""Create a session for an anonymous user. @return: A C{Deferred} that will fire with an L{AuthenticatedSession}."""
<|body_0|>
def createUserWithPassword(self, session, username, password, name, email):
"""Create a ... | stack_v2_sparse_classes_36k_train_012511 | 7,824 | permissive | [
{
"docstring": "Create a session for an anonymous user. @return: A C{Deferred} that will fire with an L{AuthenticatedSession}.",
"name": "createAnonymousSession",
"signature": "def createAnonymousSession(self)"
},
{
"docstring": "Create a new L{User}. @param session: The L{AuthenticatedSession} ... | 5 | stack_v2_sparse_classes_30k_train_006070 | Implement the Python class `FacadeAuthMixin` described below.
Class description:
Implement the FacadeAuthMixin class.
Method signatures and docstrings:
- def createAnonymousSession(self): Create a session for an anonymous user. @return: A C{Deferred} that will fire with an L{AuthenticatedSession}.
- def createUserWit... | Implement the Python class `FacadeAuthMixin` described below.
Class description:
Implement the FacadeAuthMixin class.
Method signatures and docstrings:
- def createAnonymousSession(self): Create a session for an anonymous user. @return: A C{Deferred} that will fire with an L{AuthenticatedSession}.
- def createUserWit... | b5a8c8349f3eaf3364cc4efba4736c3e33b30d96 | <|skeleton|>
class FacadeAuthMixin:
def createAnonymousSession(self):
"""Create a session for an anonymous user. @return: A C{Deferred} that will fire with an L{AuthenticatedSession}."""
<|body_0|>
def createUserWithPassword(self, session, username, password, name, email):
"""Create a ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FacadeAuthMixin:
def createAnonymousSession(self):
"""Create a session for an anonymous user. @return: A C{Deferred} that will fire with an L{AuthenticatedSession}."""
session = self._factory.create(self._transact)
session.start()
def run():
result = UserAPI().get(... | the_stack_v2_python_sparse | fluiddb/api/authentication.py | fluidinfo/fluiddb | train | 3 | |
70ef6cc43803b8f9174915e716d989a87481d073 | [
"super().__init__(agent)\ndefault_action = default_action or (0,) * len(action_mask)\nif len(action_mask) != len(default_action):\n error_format = 'Action mask size {} and default action size {} ' + 'should be the same.'\n raise ValueError(error_format.format(len(action_mask), len(default_action)))\nself.acti... | <|body_start_0|>
super().__init__(agent)
default_action = default_action or (0,) * len(action_mask)
if len(action_mask) != len(default_action):
error_format = 'Action mask size {} and default action size {} ' + 'should be the same.'
raise ValueError(error_format.format(le... | An agent that turns a masked action into it's unmasked form. | UnmaskedActionAgent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnmaskedActionAgent:
"""An agent that turns a masked action into it's unmasked form."""
def __init__(self, agent: RLAgent, action_mask: Tuple[bool, ...], default_action: Optional[Tuple[float, ...]]):
"""Creates the unmasked action wrapper over the agent. Args: agent: The agent to wra... | stack_v2_sparse_classes_36k_train_012512 | 2,179 | permissive | [
{
"docstring": "Creates the unmasked action wrapper over the agent. Args: agent: The agent to wrap. action_mask: A mask that the given actions use. default_action: The default values for the action, by default a vector of zeros.",
"name": "__init__",
"signature": "def __init__(self, agent: RLAgent, acti... | 2 | null | Implement the Python class `UnmaskedActionAgent` described below.
Class description:
An agent that turns a masked action into it's unmasked form.
Method signatures and docstrings:
- def __init__(self, agent: RLAgent, action_mask: Tuple[bool, ...], default_action: Optional[Tuple[float, ...]]): Creates the unmasked act... | Implement the Python class `UnmaskedActionAgent` described below.
Class description:
An agent that turns a masked action into it's unmasked form.
Method signatures and docstrings:
- def __init__(self, agent: RLAgent, action_mask: Tuple[bool, ...], default_action: Optional[Tuple[float, ...]]): Creates the unmasked act... | cde3be1c69bfd76fe4a78fa529e851d0a78318c7 | <|skeleton|>
class UnmaskedActionAgent:
"""An agent that turns a masked action into it's unmasked form."""
def __init__(self, agent: RLAgent, action_mask: Tuple[bool, ...], default_action: Optional[Tuple[float, ...]]):
"""Creates the unmasked action wrapper over the agent. Args: agent: The agent to wra... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UnmaskedActionAgent:
"""An agent that turns a masked action into it's unmasked form."""
def __init__(self, agent: RLAgent, action_mask: Tuple[bool, ...], default_action: Optional[Tuple[float, ...]]):
"""Creates the unmasked action wrapper over the agent. Args: agent: The agent to wrap. action_mas... | the_stack_v2_python_sparse | hlrl/torch/agents/wrappers/unmasked_action_agent.py | Chainso/HLRL | train | 3 |
69d86528506dcd6bd4ba6c8b111bf7c5bcc68e39 | [
"self.criteria = got3.manager.TweetCriteria()\nself.manager = got3.manager.TweetManager()\nself.helper = Utility.Helper(rootPath)",
"if username:\n criteria = self.criteria.setUsername(username)\nelse:\n criteria = self.criteria.setQuerySearch(query).setSince(start).setUntil(end).setMaxTweets(maxTweets)\nre... | <|body_start_0|>
self.criteria = got3.manager.TweetCriteria()
self.manager = got3.manager.TweetManager()
self.helper = Utility.Helper(rootPath)
<|end_body_0|>
<|body_start_1|>
if username:
criteria = self.criteria.setUsername(username)
else:
criteria = se... | Use GetOldTweets-python to crawl the Twitter data. | GetTwitterData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetTwitterData:
"""Use GetOldTweets-python to crawl the Twitter data."""
def __init__(self, rootPath):
"""Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manager object for got module helper (object): the helper objec... | stack_v2_sparse_classes_36k_train_012513 | 2,216 | no_license | [
{
"docstring": "Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manager object for got module helper (object): the helper object for Utility.Helper module",
"name": "__init__",
"signature": "def __init__(self, rootPath)"
},
{
"do... | 3 | stack_v2_sparse_classes_30k_train_011628 | Implement the Python class `GetTwitterData` described below.
Class description:
Use GetOldTweets-python to crawl the Twitter data.
Method signatures and docstrings:
- def __init__(self, rootPath): Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manage... | Implement the Python class `GetTwitterData` described below.
Class description:
Use GetOldTweets-python to crawl the Twitter data.
Method signatures and docstrings:
- def __init__(self, rootPath): Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manage... | e2cdf786fd11f0fc3dbd393cad02383d3a206bf7 | <|skeleton|>
class GetTwitterData:
"""Use GetOldTweets-python to crawl the Twitter data."""
def __init__(self, rootPath):
"""Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manager object for got module helper (object): the helper objec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetTwitterData:
"""Use GetOldTweets-python to crawl the Twitter data."""
def __init__(self, rootPath):
"""Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manager object for got module helper (object): the helper object for Utility... | the_stack_v2_python_sparse | Twitter/GetTwitterData.py | sxhmilyoyo/Rudetect34 | train | 0 |
ddc304c2429249dcd6e6d556229135bbbf3c478e | [
"if not words:\n return -1\nstart = 0\nend = len(words) - 1\nwhile start + 1 < end:\n mid = end + (start - end) / 2\n compare_result = self.compare(prefix, words[mid])\n if compare_result == 0:\n end = mid\n if compare_result > 0:\n start = mid\n else:\n end = mid\nif self.com... | <|body_start_0|>
if not words:
return -1
start = 0
end = len(words) - 1
while start + 1 < end:
mid = end + (start - end) / 2
compare_result = self.compare(prefix, words[mid])
if compare_result == 0:
end = mid
if ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def search_first(self, prefix, words):
"""Search the first prefix from a list of words."""
<|body_0|>
def compare(self, prefix, word):
"""Compare prefix with word. :return int: 0 if prefix is a prefix or word 1 if prefix is lexically larger than word -1 oth... | stack_v2_sparse_classes_36k_train_012514 | 1,881 | no_license | [
{
"docstring": "Search the first prefix from a list of words.",
"name": "search_first",
"signature": "def search_first(self, prefix, words)"
},
{
"docstring": "Compare prefix with word. :return int: 0 if prefix is a prefix or word 1 if prefix is lexically larger than word -1 otherwise (if prefix... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def search_first(self, prefix, words): Search the first prefix from a list of words.
- def compare(self, prefix, word): Compare prefix with word. :return int: 0 if prefix is a pr... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def search_first(self, prefix, words): Search the first prefix from a list of words.
- def compare(self, prefix, word): Compare prefix with word. :return int: 0 if prefix is a pr... | d634941087bc51869f43c0d8044db09b7bdbaf58 | <|skeleton|>
class Solution:
def search_first(self, prefix, words):
"""Search the first prefix from a list of words."""
<|body_0|>
def compare(self, prefix, word):
"""Compare prefix with word. :return int: 0 if prefix is a prefix or word 1 if prefix is lexically larger than word -1 oth... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def search_first(self, prefix, words):
"""Search the first prefix from a list of words."""
if not words:
return -1
start = 0
end = len(words) - 1
while start + 1 < end:
mid = end + (start - end) / 2
compare_result = self.com... | the_stack_v2_python_sparse | Twitter_Find_First_Prefix_Match_From_a_Sorted_String_Array.py | susunini/leetcode | train | 1 | |
f1bd9715d132746b0d658375c57ed3ed0ef8e10e | [
"self.entity_description = description\nself._client = htu21d_client\nself._attr_name = f'{name}_{description.key}'",
"await self.hass.async_add_executor_job(self._client.update)\nif self._client.sensor.sample_ok:\n if self.entity_description.key == SENSOR_TEMPERATURE:\n value = round(self._client.senso... | <|body_start_0|>
self.entity_description = description
self._client = htu21d_client
self._attr_name = f'{name}_{description.key}'
<|end_body_0|>
<|body_start_1|>
await self.hass.async_add_executor_job(self._client.update)
if self._client.sensor.sample_ok:
if self.ent... | Implementation of the HTU21D sensor. | HTU21DSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HTU21DSensor:
"""Implementation of the HTU21D sensor."""
def __init__(self, htu21d_client, name, description: SensorEntityDescription):
"""Initialize the sensor."""
<|body_0|>
async def async_update(self):
"""Get the latest data from the HTU21D sensor and update ... | stack_v2_sparse_classes_36k_train_012515 | 3,360 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, htu21d_client, name, description: SensorEntityDescription)"
},
{
"docstring": "Get the latest data from the HTU21D sensor and update the state.",
"name": "async_update",
"signature": "async def ... | 2 | stack_v2_sparse_classes_30k_train_004703 | Implement the Python class `HTU21DSensor` described below.
Class description:
Implementation of the HTU21D sensor.
Method signatures and docstrings:
- def __init__(self, htu21d_client, name, description: SensorEntityDescription): Initialize the sensor.
- async def async_update(self): Get the latest data from the HTU2... | Implement the Python class `HTU21DSensor` described below.
Class description:
Implementation of the HTU21D sensor.
Method signatures and docstrings:
- def __init__(self, htu21d_client, name, description: SensorEntityDescription): Initialize the sensor.
- async def async_update(self): Get the latest data from the HTU2... | 8de7966104911bca6f855a1755a6d71a07afb9de | <|skeleton|>
class HTU21DSensor:
"""Implementation of the HTU21D sensor."""
def __init__(self, htu21d_client, name, description: SensorEntityDescription):
"""Initialize the sensor."""
<|body_0|>
async def async_update(self):
"""Get the latest data from the HTU21D sensor and update ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HTU21DSensor:
"""Implementation of the HTU21D sensor."""
def __init__(self, htu21d_client, name, description: SensorEntityDescription):
"""Initialize the sensor."""
self.entity_description = description
self._client = htu21d_client
self._attr_name = f'{name}_{description.k... | the_stack_v2_python_sparse | homeassistant/components/htu21d/sensor.py | AlexxIT/home-assistant | train | 9 |
464981c5fb9ad2168bf1c6cd20cee6b33580630e | [
"N, channel, height, width = X.shape\nPheight, Pwidth = self.pooling\nassert (height - Pheight) % self.stride[0] == 0\nassert (width - Pwidth) % self.stride[1] == 0\nout_height = np.uint32(1 + (height - Pheight) / self.stride[0])\nout_width = np.uint32(1 + (width - Pwidth) / self.stride[1])\nA = np.zeros((N, channe... | <|body_start_0|>
N, channel, height, width = X.shape
Pheight, Pwidth = self.pooling
assert (height - Pheight) % self.stride[0] == 0
assert (width - Pwidth) % self.stride[1] == 0
out_height = np.uint32(1 + (height - Pheight) / self.stride[0])
out_width = np.uint32(1 + (wid... | MaxPool2DNaive | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaxPool2DNaive:
def forward_npdl(self, X, **kwargs):
"""Effectue la propagation avant d'une couche MaxPool2D Arguments: X {ndarray} -- Sortie de la couche précédente. Returns: ndarray -- Scores de la couche"""
<|body_0|>
def backward_npdl(self, dA, **kwargs):
"""Effe... | stack_v2_sparse_classes_36k_train_012516 | 6,145 | no_license | [
{
"docstring": "Effectue la propagation avant d'une couche MaxPool2D Arguments: X {ndarray} -- Sortie de la couche précédente. Returns: ndarray -- Scores de la couche",
"name": "forward_npdl",
"signature": "def forward_npdl(self, X, **kwargs)"
},
{
"docstring": "Effectue la rétro-propagation. Ar... | 2 | stack_v2_sparse_classes_30k_train_003157 | Implement the Python class `MaxPool2DNaive` described below.
Class description:
Implement the MaxPool2DNaive class.
Method signatures and docstrings:
- def forward_npdl(self, X, **kwargs): Effectue la propagation avant d'une couche MaxPool2D Arguments: X {ndarray} -- Sortie de la couche précédente. Returns: ndarray -... | Implement the Python class `MaxPool2DNaive` described below.
Class description:
Implement the MaxPool2DNaive class.
Method signatures and docstrings:
- def forward_npdl(self, X, **kwargs): Effectue la propagation avant d'une couche MaxPool2D Arguments: X {ndarray} -- Sortie de la couche précédente. Returns: ndarray -... | 4d1fdfa2e5f9f9e09a812a42029ceaa27d42e734 | <|skeleton|>
class MaxPool2DNaive:
def forward_npdl(self, X, **kwargs):
"""Effectue la propagation avant d'une couche MaxPool2D Arguments: X {ndarray} -- Sortie de la couche précédente. Returns: ndarray -- Scores de la couche"""
<|body_0|>
def backward_npdl(self, dA, **kwargs):
"""Effe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MaxPool2DNaive:
def forward_npdl(self, X, **kwargs):
"""Effectue la propagation avant d'une couche MaxPool2D Arguments: X {ndarray} -- Sortie de la couche précédente. Returns: ndarray -- Scores de la couche"""
N, channel, height, width = X.shape
Pheight, Pwidth = self.pooling
a... | the_stack_v2_python_sparse | layers/MaxPool.py | plparent/NPDL | train | 0 | |
3428254ebd03184863b551679e9fd7b823dd5d10 | [
"super().__init__(**kwargs)\nself.server_url = server_url.rstrip('/')\nself.repo_name = repo\nself.branch = branch\nself.client = Github(login_or_token=token, base_url=self.server_url)\ntry:\n self.github_repository = self.client.get_repo(self.repo_name)\nexcept GithubException as e:\n self.log.error(f\"Error... | <|body_start_0|>
super().__init__(**kwargs)
self.server_url = server_url.rstrip('/')
self.repo_name = repo
self.branch = branch
self.client = Github(login_or_token=token, base_url=self.server_url)
try:
self.github_repository = self.client.get_repo(self.repo_na... | GithubClient | [
"Apache-2.0",
"CC-BY-4.0",
"LicenseRef-scancode-unknown-license-reference",
"CC-BY-SA-4.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GithubClient:
def __init__(self, token: str, repo: str, branch: Optional[str]=None, server_url: Optional[str]='https://api.github.com', **kwargs):
"""Creates a Github Client for Elyra :param token: Personal Access Token for use with Github See https://docs.github.com/en/github/authentica... | stack_v2_sparse_classes_36k_train_012517 | 4,901 | permissive | [
{
"docstring": "Creates a Github Client for Elyra :param token: Personal Access Token for use with Github See https://docs.github.com/en/github/authenticating-to-github/creating-a-personal-access-token :param repo: Github Repository to use. Use Form : [Github Username/Org]/[Repository Name] e.g. elyra/examples ... | 3 | null | Implement the Python class `GithubClient` described below.
Class description:
Implement the GithubClient class.
Method signatures and docstrings:
- def __init__(self, token: str, repo: str, branch: Optional[str]=None, server_url: Optional[str]='https://api.github.com', **kwargs): Creates a Github Client for Elyra :pa... | Implement the Python class `GithubClient` described below.
Class description:
Implement the GithubClient class.
Method signatures and docstrings:
- def __init__(self, token: str, repo: str, branch: Optional[str]=None, server_url: Optional[str]='https://api.github.com', **kwargs): Creates a Github Client for Elyra :pa... | 3c27ada25a27b719529e88268bed38d135e40805 | <|skeleton|>
class GithubClient:
def __init__(self, token: str, repo: str, branch: Optional[str]=None, server_url: Optional[str]='https://api.github.com', **kwargs):
"""Creates a Github Client for Elyra :param token: Personal Access Token for use with Github See https://docs.github.com/en/github/authentica... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GithubClient:
def __init__(self, token: str, repo: str, branch: Optional[str]=None, server_url: Optional[str]='https://api.github.com', **kwargs):
"""Creates a Github Client for Elyra :param token: Personal Access Token for use with Github See https://docs.github.com/en/github/authenticating-to-github... | the_stack_v2_python_sparse | elyra/util/github.py | elyra-ai/elyra | train | 1,707 | |
6845fce1ba34338edc7609910045926ad84d205c | [
"super(amgx, self).__init__(**kwargs)\nself.__branch = kwargs.pop('branch', 'master')\nself.__cmake_opts = kwargs.pop('cmake_opts', [])\nself.__ospackages = kwargs.pop('ospackages', ['git', 'make'])\nself.__prefix = kwargs.pop('prefix', '/usr/local/amgx')\nself.__repository = kwargs.pop('repository', 'https://githu... | <|body_start_0|>
super(amgx, self).__init__(**kwargs)
self.__branch = kwargs.pop('branch', 'master')
self.__cmake_opts = kwargs.pop('cmake_opts', [])
self.__ospackages = kwargs.pop('ospackages', ['git', 'make'])
self.__prefix = kwargs.pop('prefix', '/usr/local/amgx')
self... | The `amgx` building block downloads, configures, builds, and installs the [AMGX](https://developer.nvidia.com/amgx) component. The [CMake](#cmake) building block should be installed prior to this building block. Installing an MPI building block before this one is optional and will build the [AMGX](https://developer.nvi... | amgx | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class amgx:
"""The `amgx` building block downloads, configures, builds, and installs the [AMGX](https://developer.nvidia.com/amgx) component. The [CMake](#cmake) building block should be installed prior to this building block. Installing an MPI building block before this one is optional and will build ... | stack_v2_sparse_classes_36k_train_012518 | 5,713 | permissive | [
{
"docstring": "Initialize building block",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Generate the set of instructions to install the runtime specific components from a build in a previous stage. # Examples ```python a = amgx(...) Stage0 += a Stage1 += a.... | 2 | stack_v2_sparse_classes_30k_train_008496 | Implement the Python class `amgx` described below.
Class description:
The `amgx` building block downloads, configures, builds, and installs the [AMGX](https://developer.nvidia.com/amgx) component. The [CMake](#cmake) building block should be installed prior to this building block. Installing an MPI building block befo... | Implement the Python class `amgx` described below.
Class description:
The `amgx` building block downloads, configures, builds, and installs the [AMGX](https://developer.nvidia.com/amgx) component. The [CMake](#cmake) building block should be installed prior to this building block. Installing an MPI building block befo... | 60fd2a51c171258a6b3f93c2523101cb7018ba1b | <|skeleton|>
class amgx:
"""The `amgx` building block downloads, configures, builds, and installs the [AMGX](https://developer.nvidia.com/amgx) component. The [CMake](#cmake) building block should be installed prior to this building block. Installing an MPI building block before this one is optional and will build ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class amgx:
"""The `amgx` building block downloads, configures, builds, and installs the [AMGX](https://developer.nvidia.com/amgx) component. The [CMake](#cmake) building block should be installed prior to this building block. Installing an MPI building block before this one is optional and will build the [AMGX](ht... | the_stack_v2_python_sparse | hpccm/building_blocks/amgx.py | NVIDIA/hpc-container-maker | train | 419 |
7da043b6c9f50050315a84a9df3f27ed613581ce | [
"for module in self.register_module():\n sig_env = list(filter(lambda _sig: not callable(_sig) and (_sig.startswith('g_') or _sig.startswith('_g_')), dir(module)))\n module_name = module.__name__\n for sig in sig_env:\n setattr(self, '{}_{}'.format(module_name, sig), module.__dict__[sig])",
"from ... | <|body_start_0|>
for module in self.register_module():
sig_env = list(filter(lambda _sig: not callable(_sig) and (_sig.startswith('g_') or _sig.startswith('_g_')), dir(module)))
module_name = module.__name__
for sig in sig_env:
setattr(self, '{}_{}'.format(mod... | 多任务主进程内存设置拷贝执行者类 | AbuEnvProcess | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbuEnvProcess:
"""多任务主进程内存设置拷贝执行者类"""
def __init__(self):
"""迭代注册了的需要拷贝内存设置的模块，通过筛选模块中以g_或者_g_开头的属性，将这些属性拷贝为类属性变量"""
<|body_0|>
def register_module(self):
"""注册需要拷贝内存的模块，不要全局模块注册，否则很多交叉引用，也不要做为类变量存储否则多进程传递pickle时会出错 :return:"""
<|body_1|>
def copy_pr... | stack_v2_sparse_classes_36k_train_012519 | 6,236 | permissive | [
{
"docstring": "迭代注册了的需要拷贝内存设置的模块，通过筛选模块中以g_或者_g_开头的属性，将这些属性拷贝为类属性变量",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "注册需要拷贝内存的模块，不要全局模块注册，否则很多交叉引用，也不要做为类变量存储否则多进程传递pickle时会出错 :return:",
"name": "register_module",
"signature": "def register_module(self)"
},
... | 4 | stack_v2_sparse_classes_30k_train_019818 | Implement the Python class `AbuEnvProcess` described below.
Class description:
多任务主进程内存设置拷贝执行者类
Method signatures and docstrings:
- def __init__(self): 迭代注册了的需要拷贝内存设置的模块，通过筛选模块中以g_或者_g_开头的属性，将这些属性拷贝为类属性变量
- def register_module(self): 注册需要拷贝内存的模块，不要全局模块注册，否则很多交叉引用，也不要做为类变量存储否则多进程传递pickle时会出错 :return:
- def copy_proces... | Implement the Python class `AbuEnvProcess` described below.
Class description:
多任务主进程内存设置拷贝执行者类
Method signatures and docstrings:
- def __init__(self): 迭代注册了的需要拷贝内存设置的模块，通过筛选模块中以g_或者_g_开头的属性，将这些属性拷贝为类属性变量
- def register_module(self): 注册需要拷贝内存的模块，不要全局模块注册，否则很多交叉引用，也不要做为类变量存储否则多进程传递pickle时会出错 :return:
- def copy_proces... | 2e5ab17f2d20deb3c68c927f6208ea89db7c639d | <|skeleton|>
class AbuEnvProcess:
"""多任务主进程内存设置拷贝执行者类"""
def __init__(self):
"""迭代注册了的需要拷贝内存设置的模块，通过筛选模块中以g_或者_g_开头的属性，将这些属性拷贝为类属性变量"""
<|body_0|>
def register_module(self):
"""注册需要拷贝内存的模块，不要全局模块注册，否则很多交叉引用，也不要做为类变量存储否则多进程传递pickle时会出错 :return:"""
<|body_1|>
def copy_pr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AbuEnvProcess:
"""多任务主进程内存设置拷贝执行者类"""
def __init__(self):
"""迭代注册了的需要拷贝内存设置的模块，通过筛选模块中以g_或者_g_开头的属性，将这些属性拷贝为类属性变量"""
for module in self.register_module():
sig_env = list(filter(lambda _sig: not callable(_sig) and (_sig.startswith('g_') or _sig.startswith('_g_')), dir(module)))... | the_stack_v2_python_sparse | abupy/CoreBu/ABuEnvProcess.py | luqin/firefly | train | 1 |
682f3971891ee784eb77dbe2ae7e337b6693e3a5 | [
"def _initial_placefield_computation(active_session, pf_computation_config, prev_output_result: ComputationResult):\n prev_output_result.computed_data['pf1D'], prev_output_result.computed_data['pf2D'] = perform_compute_placefields(active_session.spikes_df, active_session.position, pf_computation_config, None, No... | <|body_start_0|>
def _initial_placefield_computation(active_session, pf_computation_config, prev_output_result: ComputationResult):
prev_output_result.computed_data['pf1D'], prev_output_result.computed_data['pf2D'] = perform_compute_placefields(active_session.spikes_df, active_session.position, pf_c... | PlacefieldComputations | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlacefieldComputations:
def _perform_baseline_placefield_computation(computation_result: ComputationResult, debug_print=False):
"""Builds the initial 1D and 2D placefields Provides"""
<|body_0|>
def _perform_time_dependent_placefield_computation(computation_result: Computati... | stack_v2_sparse_classes_36k_train_012520 | 4,390 | permissive | [
{
"docstring": "Builds the initial 1D and 2D placefields Provides",
"name": "_perform_baseline_placefield_computation",
"signature": "def _perform_baseline_placefield_computation(computation_result: ComputationResult, debug_print=False)"
},
{
"docstring": "Builds the time-dependent 2D placefield... | 2 | null | Implement the Python class `PlacefieldComputations` described below.
Class description:
Implement the PlacefieldComputations class.
Method signatures and docstrings:
- def _perform_baseline_placefield_computation(computation_result: ComputationResult, debug_print=False): Builds the initial 1D and 2D placefields Provi... | Implement the Python class `PlacefieldComputations` described below.
Class description:
Implement the PlacefieldComputations class.
Method signatures and docstrings:
- def _perform_baseline_placefield_computation(computation_result: ComputationResult, debug_print=False): Builds the initial 1D and 2D placefields Provi... | 212399d826284b394fce8894ff1a93133aef783f | <|skeleton|>
class PlacefieldComputations:
def _perform_baseline_placefield_computation(computation_result: ComputationResult, debug_print=False):
"""Builds the initial 1D and 2D placefields Provides"""
<|body_0|>
def _perform_time_dependent_placefield_computation(computation_result: Computati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PlacefieldComputations:
def _perform_baseline_placefield_computation(computation_result: ComputationResult, debug_print=False):
"""Builds the initial 1D and 2D placefields Provides"""
def _initial_placefield_computation(active_session, pf_computation_config, prev_output_result: ComputationResu... | the_stack_v2_python_sparse | src/pyphoplacecellanalysis/General/Pipeline/Stages/ComputationFunctions/PlacefieldComputations.py | CommanderPho/pyPhoPlaceCellAnalysis | train | 1 | |
967f07f17bd7592ae11624adf5b5570d48232120 | [
"nodes = dict()\nfor c in set([c for w in words for c in w]):\n nodes[c] = Node(c)\nfor w1, w2 in zip(words, words[1:]):\n for c1, c2 in zip(w1, w2):\n if c1 != c2:\n n1 = nodes[c1]\n if c2 not in n1.edges:\n n1.edges.add(c2)\n nodes[c2].in_degree += ... | <|body_start_0|>
nodes = dict()
for c in set([c for w in words for c in w]):
nodes[c] = Node(c)
for w1, w2 in zip(words, words[1:]):
for c1, c2 in zip(w1, w2):
if c1 != c2:
n1 = nodes[c1]
if c2 not in n1.edges:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def alienOrder_v1(self, words: List[str]) -> str:
"""Use a Node structure to store the graph data."""
<|body_0|>
def alienOrder_v2(self, words: List[str]) -> str:
"""Use two structures (dict and Counter) to store the information."""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k_train_012521 | 5,541 | no_license | [
{
"docstring": "Use a Node structure to store the graph data.",
"name": "alienOrder_v1",
"signature": "def alienOrder_v1(self, words: List[str]) -> str"
},
{
"docstring": "Use two structures (dict and Counter) to store the information.",
"name": "alienOrder_v2",
"signature": "def alienOr... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def alienOrder_v1(self, words: List[str]) -> str: Use a Node structure to store the graph data.
- def alienOrder_v2(self, words: List[str]) -> str: Use two structures (dict and C... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def alienOrder_v1(self, words: List[str]) -> str: Use a Node structure to store the graph data.
- def alienOrder_v2(self, words: List[str]) -> str: Use two structures (dict and C... | 97a2386f5e3adbd7138fd123810c3232bdf7f622 | <|skeleton|>
class Solution:
def alienOrder_v1(self, words: List[str]) -> str:
"""Use a Node structure to store the graph data."""
<|body_0|>
def alienOrder_v2(self, words: List[str]) -> str:
"""Use two structures (dict and Counter) to store the information."""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def alienOrder_v1(self, words: List[str]) -> str:
"""Use a Node structure to store the graph data."""
nodes = dict()
for c in set([c for w in words for c in w]):
nodes[c] = Node(c)
for w1, w2 in zip(words, words[1:]):
for c1, c2 in zip(w1, w2):... | the_stack_v2_python_sparse | python3/trees_and_graphs/alien_dictionary.py | victorchu/algorithms | train | 0 | |
56707e053eb99c55a1d3ff79d03f75e669f887c8 | [
"if 'title' not in validated_data:\n raise ValidationError({'title': ['This field is required.']})\nquestion = Question.create(validated_data['title'], validated_data['user'], keywords=validated_data.get('keywords', None))\nif 'answer' in validated_data and validated_data['answer'] != '':\n Answer.create(vali... | <|body_start_0|>
if 'title' not in validated_data:
raise ValidationError({'title': ['This field is required.']})
question = Question.create(validated_data['title'], validated_data['user'], keywords=validated_data.get('keywords', None))
if 'answer' in validated_data and validated_data... | Serialize question | QuestionSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionSerializer:
"""Serialize question"""
def create(self, validated_data):
"""Create new question from validated_data"""
<|body_0|>
def update(self, instance, validated_data):
"""Update existing question by validated_data"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k_train_012522 | 7,932 | no_license | [
{
"docstring": "Create new question from validated_data",
"name": "create",
"signature": "def create(self, validated_data)"
},
{
"docstring": "Update existing question by validated_data",
"name": "update",
"signature": "def update(self, instance, validated_data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019519 | Implement the Python class `QuestionSerializer` described below.
Class description:
Serialize question
Method signatures and docstrings:
- def create(self, validated_data): Create new question from validated_data
- def update(self, instance, validated_data): Update existing question by validated_data | Implement the Python class `QuestionSerializer` described below.
Class description:
Serialize question
Method signatures and docstrings:
- def create(self, validated_data): Create new question from validated_data
- def update(self, instance, validated_data): Update existing question by validated_data
<|skeleton|>
cl... | 670752a3b48619eeba2fa9f2cf133e6050737a73 | <|skeleton|>
class QuestionSerializer:
"""Serialize question"""
def create(self, validated_data):
"""Create new question from validated_data"""
<|body_0|>
def update(self, instance, validated_data):
"""Update existing question by validated_data"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuestionSerializer:
"""Serialize question"""
def create(self, validated_data):
"""Create new question from validated_data"""
if 'title' not in validated_data:
raise ValidationError({'title': ['This field is required.']})
question = Question.create(validated_data['title... | the_stack_v2_python_sparse | controller/src/api/serializers.py | Sapunov/qua | train | 1 |
051a4a20994cba91e2de1bdbf1fa5da6a4c37bbe | [
"super(QIntSpinner3DS, self).__init__(parent)\nself.size = size\nself.step = step\nself.default_value = default_value\nself.mouseStartPosY = 0\nself.startValue = 0\nself.current_value = 0\nself.setMaximumSize(self.size)\nself.setSingleStep(self.step)\nself.setValue(self.default_value)",
"if event.type() == qtc.QE... | <|body_start_0|>
super(QIntSpinner3DS, self).__init__(parent)
self.size = size
self.step = step
self.default_value = default_value
self.mouseStartPosY = 0
self.startValue = 0
self.current_value = 0
self.setMaximumSize(self.size)
self.setSingleStep(... | Custom QDoubleSpinBox widget mimicking 3dsMax style "UI Spinner Controls" initialize with : size, step, default_value, parent | QIntSpinner3DS | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QIntSpinner3DS:
"""Custom QDoubleSpinBox widget mimicking 3dsMax style "UI Spinner Controls" initialize with : size, step, default_value, parent"""
def __init__(self, size, step=1, default_value=0, parent=None):
"""Initialization"""
<|body_0|>
def mousePressEvent(self, e... | stack_v2_sparse_classes_36k_train_012523 | 4,069 | no_license | [
{
"docstring": "Initialization",
"name": "__init__",
"signature": "def __init__(self, size, step=1, default_value=0, parent=None)"
},
{
"docstring": "Re-define mousePressEvent to implement right-click/left-click",
"name": "mousePressEvent",
"signature": "def mousePressEvent(self, event)"... | 4 | stack_v2_sparse_classes_30k_train_012479 | Implement the Python class `QIntSpinner3DS` described below.
Class description:
Custom QDoubleSpinBox widget mimicking 3dsMax style "UI Spinner Controls" initialize with : size, step, default_value, parent
Method signatures and docstrings:
- def __init__(self, size, step=1, default_value=0, parent=None): Initializati... | Implement the Python class `QIntSpinner3DS` described below.
Class description:
Custom QDoubleSpinBox widget mimicking 3dsMax style "UI Spinner Controls" initialize with : size, step, default_value, parent
Method signatures and docstrings:
- def __init__(self, size, step=1, default_value=0, parent=None): Initializati... | 6537d2f4a62afa0b5ea745a93193d1bc1379a24d | <|skeleton|>
class QIntSpinner3DS:
"""Custom QDoubleSpinBox widget mimicking 3dsMax style "UI Spinner Controls" initialize with : size, step, default_value, parent"""
def __init__(self, size, step=1, default_value=0, parent=None):
"""Initialization"""
<|body_0|>
def mousePressEvent(self, e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QIntSpinner3DS:
"""Custom QDoubleSpinBox widget mimicking 3dsMax style "UI Spinner Controls" initialize with : size, step, default_value, parent"""
def __init__(self, size, step=1, default_value=0, parent=None):
"""Initialization"""
super(QIntSpinner3DS, self).__init__(parent)
sel... | the_stack_v2_python_sparse | Custom_Widgets/Custom_3dsMaxStyleSpinner.py | LucasPancarte/learning_PySide2 | train | 0 |
dce69a502b7ba635b7f1ce3554d89c7c59c7fa41 | [
"super().__init__()\nself.client = 'localhost'\nself.folder = '/home/sirius/shared/screens-iocs/data_by_day/'\nself.folder += '2023-02-23-SI_nonlinear_optics_opt_RCDS_matlab/'\nself.folder += 'run1/'\nself.input_fname = 'input.mat'\nself.output_fname = 'output.mat'\nself.onaxis_rf_phase = 0\nself.offaxis_rf_phase =... | <|body_start_0|>
super().__init__()
self.client = 'localhost'
self.folder = '/home/sirius/shared/screens-iocs/data_by_day/'
self.folder += '2023-02-23-SI_nonlinear_optics_opt_RCDS_matlab/'
self.folder += 'run1/'
self.input_fname = 'input.mat'
self.output_fname = '... | . | DynapServerParams | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DynapServerParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__()
self.client = 'localhost'
self.folder = '/home/sirius/shared/screens-ioc... | stack_v2_sparse_classes_36k_train_012524 | 25,073 | permissive | [
{
"docstring": ".",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ".",
"name": "__str__",
"signature": "def __str__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000036 | Implement the Python class `DynapServerParams` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self): .
- def __str__(self): . | Implement the Python class `DynapServerParams` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self): .
- def __str__(self): .
<|skeleton|>
class DynapServerParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
... | 39644161d98964a3a3d80d63269201f0a1712e82 | <|skeleton|>
class DynapServerParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DynapServerParams:
"""."""
def __init__(self):
"""."""
super().__init__()
self.client = 'localhost'
self.folder = '/home/sirius/shared/screens-iocs/data_by_day/'
self.folder += '2023-02-23-SI_nonlinear_optics_opt_RCDS_matlab/'
self.folder += 'run1/'
... | the_stack_v2_python_sparse | apsuite/commisslib/dynap_opt_rcds.py | lnls-fac/apsuite | train | 1 |
e1503bdc515cff30f2d36cedff0c87f37cd12b73 | [
"Bar.__init__(self, w, h)\nself.character = character\nself._colour = HP_GREEN",
"self._base.fill(DARK_PURPLE)\nratio = self.character.curr_hp / self.character.max_hp\nif ratio > 0.5:\n self._colour = HP_GREEN\nelif ratio < 0.2:\n self._colour = HP_RED\nelse:\n self._colour = HP_YELLOW\nnew_w = int(ratio... | <|body_start_0|>
Bar.__init__(self, w, h)
self.character = character
self._colour = HP_GREEN
<|end_body_0|>
<|body_start_1|>
self._base.fill(DARK_PURPLE)
ratio = self.character.curr_hp / self.character.max_hp
if ratio > 0.5:
self._colour = HP_GREEN
el... | Class for drawing health bars in a battle screen. | HPBar | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HPBar:
"""Class for drawing health bars in a battle screen."""
def __init__(self, w, h, character):
"""Class constructor for HP bars. args: character: Character object; specifies the character associated with the bar colour: colour tuple; colour of the bar"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_012525 | 3,427 | no_license | [
{
"docstring": "Class constructor for HP bars. args: character: Character object; specifies the character associated with the bar colour: colour tuple; colour of the bar",
"name": "__init__",
"signature": "def __init__(self, w, h, character)"
},
{
"docstring": "Updates the bar based on current H... | 2 | stack_v2_sparse_classes_30k_train_016237 | Implement the Python class `HPBar` described below.
Class description:
Class for drawing health bars in a battle screen.
Method signatures and docstrings:
- def __init__(self, w, h, character): Class constructor for HP bars. args: character: Character object; specifies the character associated with the bar colour: co... | Implement the Python class `HPBar` described below.
Class description:
Class for drawing health bars in a battle screen.
Method signatures and docstrings:
- def __init__(self, w, h, character): Class constructor for HP bars. args: character: Character object; specifies the character associated with the bar colour: co... | e86420c145c1d929649ac5d4c98a4d1b75e218a7 | <|skeleton|>
class HPBar:
"""Class for drawing health bars in a battle screen."""
def __init__(self, w, h, character):
"""Class constructor for HP bars. args: character: Character object; specifies the character associated with the bar colour: colour tuple; colour of the bar"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HPBar:
"""Class for drawing health bars in a battle screen."""
def __init__(self, w, h, character):
"""Class constructor for HP bars. args: character: Character object; specifies the character associated with the bar colour: colour tuple; colour of the bar"""
Bar.__init__(self, w, h)
... | the_stack_v2_python_sparse | src/entities/bar.py | nuclearkittens/ot-projekti | train | 0 |
d03ee669190088afdd6989a640d3c5450b48c37e | [
"if not isinstance(cath_id, CathID):\n cath_id = CathID(cath_id)\ndepth = cath_id.depth\nfiltered_entries = [c for c in self.entries if c.cath_id_to_depth(depth) == cath_id]\nreturn self.__class__(entries=filtered_entries)",
"sorted_entries = sorted(self.entries)\nreps = {}\nfor entry in sorted_entries:\n r... | <|body_start_0|>
if not isinstance(cath_id, CathID):
cath_id = CathID(cath_id)
depth = cath_id.depth
filtered_entries = [c for c in self.entries if c.cath_id_to_depth(depth) == cath_id]
return self.__class__(entries=filtered_entries)
<|end_body_0|>
<|body_start_1|>
s... | Mixin for container classes that have entries with :class:`HasCathIDMixin` | HasEntriesWithCathIDMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HasEntriesWithCathIDMixin:
"""Mixin for container classes that have entries with :class:`HasCathIDMixin`"""
def filter_cath_id(self, cath_id):
"""Returns a new container after filtering to only include entries within a given CATH ID"""
<|body_0|>
def filter_reps(self, de... | stack_v2_sparse_classes_36k_train_012526 | 14,116 | permissive | [
{
"docstring": "Returns a new container after filtering to only include entries within a given CATH ID",
"name": "filter_cath_id",
"signature": "def filter_cath_id(self, cath_id)"
},
{
"docstring": "Returns a new container after filtering to only include one rep at a given depth",
"name": "f... | 2 | stack_v2_sparse_classes_30k_train_002839 | Implement the Python class `HasEntriesWithCathIDMixin` described below.
Class description:
Mixin for container classes that have entries with :class:`HasCathIDMixin`
Method signatures and docstrings:
- def filter_cath_id(self, cath_id): Returns a new container after filtering to only include entries within a given CA... | Implement the Python class `HasEntriesWithCathIDMixin` described below.
Class description:
Mixin for container classes that have entries with :class:`HasCathIDMixin`
Method signatures and docstrings:
- def filter_cath_id(self, cath_id): Returns a new container after filtering to only include entries within a given CA... | 39de100ebc18eac2c4da10e4b5fd22b6926b69a4 | <|skeleton|>
class HasEntriesWithCathIDMixin:
"""Mixin for container classes that have entries with :class:`HasCathIDMixin`"""
def filter_cath_id(self, cath_id):
"""Returns a new container after filtering to only include entries within a given CATH ID"""
<|body_0|>
def filter_reps(self, de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HasEntriesWithCathIDMixin:
"""Mixin for container classes that have entries with :class:`HasCathIDMixin`"""
def filter_cath_id(self, cath_id):
"""Returns a new container after filtering to only include entries within a given CATH ID"""
if not isinstance(cath_id, CathID):
cath_... | the_stack_v2_python_sparse | cathpy/core/release.py | UCL/cathpy | train | 12 |
e06e5b1453e576aee5d5b87a3bcbfe2762deb1f5 | [
"if self.state_model.op_state in [DevState.FAULT, DevState.UNKNOWN]:\n tango.Except.throw_exception(f'Command TelescopeOn is not allowed in current state {self.state_model.op_state}.', 'Failed to invoke On command on CspMasterLeafNode.', 'CspMasterLeafNode.TelescopeOn()', tango.ErrSeverity.ERR)\nreturn True",
... | <|body_start_0|>
if self.state_model.op_state in [DevState.FAULT, DevState.UNKNOWN]:
tango.Except.throw_exception(f'Command TelescopeOn is not allowed in current state {self.state_model.op_state}.', 'Failed to invoke On command on CspMasterLeafNode.', 'CspMasterLeafNode.TelescopeOn()', tango.ErrSeve... | A class for CSP Subarray's TelescopeOn() command. Invokes method to start Delay Calculation. | TelescopeOn | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TelescopeOn:
"""A class for CSP Subarray's TelescopeOn() command. Invokes method to start Delay Calculation."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device st... | stack_v2_sparse_classes_36k_train_012527 | 3,692 | permissive | [
{
"docstring": "Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device state :rtype: boolean :raises: DevFailed if this command is not allowed to be run in current device state",
"name": "check_allowed",
"signature": ... | 3 | null | Implement the Python class `TelescopeOn` described below.
Class description:
A class for CSP Subarray's TelescopeOn() command. Invokes method to start Delay Calculation.
Method signatures and docstrings:
- def check_allowed(self): Checks whether this command is allowed to be run in current device state :return: True ... | Implement the Python class `TelescopeOn` described below.
Class description:
A class for CSP Subarray's TelescopeOn() command. Invokes method to start Delay Calculation.
Method signatures and docstrings:
- def check_allowed(self): Checks whether this command is allowed to be run in current device state :return: True ... | 7ee65a9c8dada9b28893144b372a398bd0646195 | <|skeleton|>
class TelescopeOn:
"""A class for CSP Subarray's TelescopeOn() command. Invokes method to start Delay Calculation."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device st... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TelescopeOn:
"""A class for CSP Subarray's TelescopeOn() command. Invokes method to start Delay Calculation."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device state :rtype: b... | the_stack_v2_python_sparse | temp_src/ska_tmc_cspsubarrayleafnode_mid/telescope_on_command.py | ska-telescope/tmc-prototype | train | 4 |
559bb1c3225d860b471acd76df31dfd3acb0f954 | [
"self.batcher = Batcher(config, input_type, tokenizer, labeled_file)\nself.input_type = input_type\nself.list_k = list_k\nif self.input_type == 'dev':\n self.best_dev_score = 0\n self.score_filename = os.path.join(exp_dir, 'dev_scores.json')\n self.best_model_filename = os.path.join(exp_dir, 'best_model')\... | <|body_start_0|>
self.batcher = Batcher(config, input_type, tokenizer, labeled_file)
self.input_type = input_type
self.list_k = list_k
if self.input_type == 'dev':
self.best_dev_score = 0
self.score_filename = os.path.join(exp_dir, 'dev_scores.json')
s... | Evaluator | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Evaluator:
def __init__(self, config, vocab, tokenizer, input_type, exp_dir, list_k, labeled_file=None, output_file=None):
"""param config: configuration to use for evaluation param vocab: vocabulary to use param tokenizer: tokenizer to use param input_type: input type of either dev/test... | stack_v2_sparse_classes_36k_train_012528 | 3,893 | permissive | [
{
"docstring": "param config: configuration to use for evaluation param vocab: vocabulary to use param tokenizer: tokenizer to use param input_type: input type of either dev/test param exp_dir: experiment directory to save output param list_k: list of k to evaluate hits@k param labeled_file: labeled file to use... | 2 | stack_v2_sparse_classes_30k_train_018257 | Implement the Python class `Evaluator` described below.
Class description:
Implement the Evaluator class.
Method signatures and docstrings:
- def __init__(self, config, vocab, tokenizer, input_type, exp_dir, list_k, labeled_file=None, output_file=None): param config: configuration to use for evaluation param vocab: v... | Implement the Python class `Evaluator` described below.
Class description:
Implement the Evaluator class.
Method signatures and docstrings:
- def __init__(self, config, vocab, tokenizer, input_type, exp_dir, list_k, labeled_file=None, output_file=None): param config: configuration to use for evaluation param vocab: v... | b33977257ed3e6f95d95da570367e099ea24161f | <|skeleton|>
class Evaluator:
def __init__(self, config, vocab, tokenizer, input_type, exp_dir, list_k, labeled_file=None, output_file=None):
"""param config: configuration to use for evaluation param vocab: vocabulary to use param tokenizer: tokenizer to use param input_type: input type of either dev/test... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Evaluator:
def __init__(self, config, vocab, tokenizer, input_type, exp_dir, list_k, labeled_file=None, output_file=None):
"""param config: configuration to use for evaluation param vocab: vocabulary to use param tokenizer: tokenizer to use param input_type: input type of either dev/test param exp_dir... | the_stack_v2_python_sparse | src/main/objects/Evaluator.py | fgregg/stance | train | 0 | |
31ffd7044c3a9e7b8704136acf1e536397557f2d | [
"self.num = 0\nself.n = n\nself.prices = {}\nself.discount = discount\nfor i, id_of_product in enumerate(products):\n self.prices[id_of_product] = prices[i]",
"ret = 0\nself.num += 1\nfor i, id_of_product in enumerate(product):\n ret += self.prices[id_of_product] * amount[i]\nif self.num == self.n:\n ret... | <|body_start_0|>
self.num = 0
self.n = n
self.prices = {}
self.discount = discount
for i, id_of_product in enumerate(products):
self.prices[id_of_product] = prices[i]
<|end_body_0|>
<|body_start_1|>
ret = 0
self.num += 1
for i, id_of_product i... | Cashier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
<|body_0|>
def getBill(self, product, amount):
""":type product: List[int] :type amount: List[int] :rtype: float"""
... | stack_v2_sparse_classes_36k_train_012529 | 943 | no_license | [
{
"docstring": ":type n: int :type discount: int :type products: List[int] :type prices: List[int]",
"name": "__init__",
"signature": "def __init__(self, n, discount, products, prices)"
},
{
"docstring": ":type product: List[int] :type amount: List[int] :rtype: float",
"name": "getBill",
... | 2 | stack_v2_sparse_classes_30k_train_017390 | Implement the Python class `Cashier` described below.
Class description:
Implement the Cashier class.
Method signatures and docstrings:
- def __init__(self, n, discount, products, prices): :type n: int :type discount: int :type products: List[int] :type prices: List[int]
- def getBill(self, product, amount): :type pr... | Implement the Python class `Cashier` described below.
Class description:
Implement the Cashier class.
Method signatures and docstrings:
- def __init__(self, n, discount, products, prices): :type n: int :type discount: int :type products: List[int] :type prices: List[int]
- def getBill(self, product, amount): :type pr... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
<|body_0|>
def getBill(self, product, amount):
""":type product: List[int] :type amount: List[int] :rtype: float"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
self.num = 0
self.n = n
self.prices = {}
self.discount = discount
for i, id_of_product in enumerate(products):
... | the_stack_v2_python_sparse | python/leetcode/1357_Apply_Discount_Every_n_Orders.py | bobcaoge/my-code | train | 0 | |
1880cd4df327820ff9cb4000834099a742d9e20b | [
"collection_name_to_id_dict = {}\ncollections_stream = CollectionsList(authenticator=authenticator, site_id=site_id)\ncollections_records = collections_stream.read_records(sync_mode='full_refresh')\nfor collection_obj in collections_records:\n collection_name_to_id_dict[collection_obj['name']] = collection_obj['... | <|body_start_0|>
collection_name_to_id_dict = {}
collections_stream = CollectionsList(authenticator=authenticator, site_id=site_id)
collections_records = collections_stream.read_records(sync_mode='full_refresh')
for collection_obj in collections_records:
collection_name_to_id... | This is the main class that defines the methods that will be called by Airbyte infrastructure | SourceWebflow | [
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"Elastic-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourceWebflow:
"""This is the main class that defines the methods that will be called by Airbyte infrastructure"""
def _get_collection_name_to_id_dict(authenticator: str=None, site_id: str=None) -> Mapping[str, str]:
"""Most of the Webflow APIs require the collection id, but the stre... | stack_v2_sparse_classes_36k_train_012530 | 14,515 | permissive | [
{
"docstring": "Most of the Webflow APIs require the collection id, but the streams that we are generating use the collection name. This function will return a dictionary containing collection_name: collection_id entries.",
"name": "_get_collection_name_to_id_dict",
"signature": "def _get_collection_nam... | 5 | null | Implement the Python class `SourceWebflow` described below.
Class description:
This is the main class that defines the methods that will be called by Airbyte infrastructure
Method signatures and docstrings:
- def _get_collection_name_to_id_dict(authenticator: str=None, site_id: str=None) -> Mapping[str, str]: Most of... | Implement the Python class `SourceWebflow` described below.
Class description:
This is the main class that defines the methods that will be called by Airbyte infrastructure
Method signatures and docstrings:
- def _get_collection_name_to_id_dict(authenticator: str=None, site_id: str=None) -> Mapping[str, str]: Most of... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class SourceWebflow:
"""This is the main class that defines the methods that will be called by Airbyte infrastructure"""
def _get_collection_name_to_id_dict(authenticator: str=None, site_id: str=None) -> Mapping[str, str]:
"""Most of the Webflow APIs require the collection id, but the stre... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SourceWebflow:
"""This is the main class that defines the methods that will be called by Airbyte infrastructure"""
def _get_collection_name_to_id_dict(authenticator: str=None, site_id: str=None) -> Mapping[str, str]:
"""Most of the Webflow APIs require the collection id, but the streams that we a... | the_stack_v2_python_sparse | dts/airbyte/airbyte-integrations/connectors/source-webflow/source_webflow/source.py | alldatacenter/alldata | train | 774 |
e3cfe059b3b47304dd36f2076b1eb158cf6383f9 | [
"question = 'What language did you first learn speak?'\nmy_servey = AnonymousSurvey(question)\nmy_servey.store_response('English')\nself.assertIn('English', my_servey.responses)",
"question = 'What language did you first learn speak?'\nmy_servey = AnonymousSurvey(question)\nresponses = ['English', 'Spanish', 'Man... | <|body_start_0|>
question = 'What language did you first learn speak?'
my_servey = AnonymousSurvey(question)
my_servey.store_response('English')
self.assertIn('English', my_servey.responses)
<|end_body_0|>
<|body_start_1|>
question = 'What language did you first learn speak?'
... | Тесты для класса AnonymousSurvey | TestAnonymousSurvey | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAnonymousSurvey:
"""Тесты для класса AnonymousSurvey"""
def test_store_single_response(self):
"""Проверяет, что один ответ сохранён правильно."""
<|body_0|>
def test_store_three_responses(self):
"""Проверяет, что три ответа были созранены правильно."""
... | stack_v2_sparse_classes_36k_train_012531 | 4,185 | no_license | [
{
"docstring": "Проверяет, что один ответ сохранён правильно.",
"name": "test_store_single_response",
"signature": "def test_store_single_response(self)"
},
{
"docstring": "Проверяет, что три ответа были созранены правильно.",
"name": "test_store_three_responses",
"signature": "def test_... | 2 | null | Implement the Python class `TestAnonymousSurvey` described below.
Class description:
Тесты для класса AnonymousSurvey
Method signatures and docstrings:
- def test_store_single_response(self): Проверяет, что один ответ сохранён правильно.
- def test_store_three_responses(self): Проверяет, что три ответа были созранены... | Implement the Python class `TestAnonymousSurvey` described below.
Class description:
Тесты для класса AnonymousSurvey
Method signatures and docstrings:
- def test_store_single_response(self): Проверяет, что один ответ сохранён правильно.
- def test_store_three_responses(self): Проверяет, что три ответа были созранены... | b87319409a94e26faf084c22b1eb6a1d55458282 | <|skeleton|>
class TestAnonymousSurvey:
"""Тесты для класса AnonymousSurvey"""
def test_store_single_response(self):
"""Проверяет, что один ответ сохранён правильно."""
<|body_0|>
def test_store_three_responses(self):
"""Проверяет, что три ответа были созранены правильно."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAnonymousSurvey:
"""Тесты для класса AnonymousSurvey"""
def test_store_single_response(self):
"""Проверяет, что один ответ сохранён правильно."""
question = 'What language did you first learn speak?'
my_servey = AnonymousSurvey(question)
my_servey.store_response('Engli... | the_stack_v2_python_sparse | python_learning/chapter_11/f_test_survey.py | DanilWH/Python | train | 0 |
c8d60afff504245edf0668c4fbfb985f725afdc6 | [
"data = ConfigStore.get_config()\nif 'power_profiles' not in data:\n raise NotFound('No power profiles in config file')\nfor power in data['power_profiles']:\n if not power['id'] == int(profile_id):\n continue\n return (power, 200)\nraise NotFound('Power profile ' + str(profile_id) + ' not found in ... | <|body_start_0|>
data = ConfigStore.get_config()
if 'power_profiles' not in data:
raise NotFound('No power profiles in config file')
for power in data['power_profiles']:
if not power['id'] == int(profile_id):
continue
return (power, 200)
... | Handles /power_profiles/<profile_id> HTTP requests | Power | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Power:
"""Handles /power_profiles/<profile_id> HTTP requests"""
def get(profile_id):
"""Handles HTTP GET /power_profiles/<profile_id> request. Retrieve single power profile Raises NotFound Parameters: profile_id: Id of power profile to retrieve Returns: response, status code"""
... | stack_v2_sparse_classes_36k_train_012532 | 7,986 | permissive | [
{
"docstring": "Handles HTTP GET /power_profiles/<profile_id> request. Retrieve single power profile Raises NotFound Parameters: profile_id: Id of power profile to retrieve Returns: response, status code",
"name": "get",
"signature": "def get(profile_id)"
},
{
"docstring": "Handles HTTP DELETE /... | 3 | stack_v2_sparse_classes_30k_train_014518 | Implement the Python class `Power` described below.
Class description:
Handles /power_profiles/<profile_id> HTTP requests
Method signatures and docstrings:
- def get(profile_id): Handles HTTP GET /power_profiles/<profile_id> request. Retrieve single power profile Raises NotFound Parameters: profile_id: Id of power pr... | Implement the Python class `Power` described below.
Class description:
Handles /power_profiles/<profile_id> HTTP requests
Method signatures and docstrings:
- def get(profile_id): Handles HTTP GET /power_profiles/<profile_id> request. Retrieve single power profile Raises NotFound Parameters: profile_id: Id of power pr... | 86883b2b5cc71ee543b39878f37b5a6f533594fa | <|skeleton|>
class Power:
"""Handles /power_profiles/<profile_id> HTTP requests"""
def get(profile_id):
"""Handles HTTP GET /power_profiles/<profile_id> request. Retrieve single power profile Raises NotFound Parameters: profile_id: Id of power profile to retrieve Returns: response, status code"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Power:
"""Handles /power_profiles/<profile_id> HTTP requests"""
def get(profile_id):
"""Handles HTTP GET /power_profiles/<profile_id> request. Retrieve single power profile Raises NotFound Parameters: profile_id: Id of power profile to retrieve Returns: response, status code"""
data = Con... | the_stack_v2_python_sparse | appqos/appqos/rest/rest_power.py | intel/intel-cmt-cat | train | 528 |
045900bf89057e4fae9a7a2120d5c3e602de28d0 | [
"super().__init__()\nself.head = head\nself.member = member",
"if not struct_ctype or not struct_ctype.is_struct_union():\n err = 'request for member in something not a structure or union'\n raise CompilerError(err, self.r)\noffset, ctype = struct_ctype.get_offset(self.member.content)\nif offset is None:\n ... | <|body_start_0|>
super().__init__()
self.head = head
self.member = member
<|end_body_0|>
<|body_start_1|>
if not struct_ctype or not struct_ctype.is_struct_union():
err = 'request for member in something not a structure or union'
raise CompilerError(err, self.r)
... | Struct/union object lookup (. or ->) | _ObjLookup | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ObjLookup:
"""Struct/union object lookup (. or ->)"""
def __init__(self, head, member):
"""Initialize node."""
<|body_0|>
def get_offset_info(self, struct_ctype):
"""Given a struct ctype, return the member offset and ctype. If the given ctype is None, emits the ... | stack_v2_sparse_classes_36k_train_012533 | 45,651 | permissive | [
{
"docstring": "Initialize node.",
"name": "__init__",
"signature": "def __init__(self, head, member)"
},
{
"docstring": "Given a struct ctype, return the member offset and ctype. If the given ctype is None, emits the error for requesting a member in something not a structure or union.",
"na... | 2 | stack_v2_sparse_classes_30k_train_012631 | Implement the Python class `_ObjLookup` described below.
Class description:
Struct/union object lookup (. or ->)
Method signatures and docstrings:
- def __init__(self, head, member): Initialize node.
- def get_offset_info(self, struct_ctype): Given a struct ctype, return the member offset and ctype. If the given ctyp... | Implement the Python class `_ObjLookup` described below.
Class description:
Struct/union object lookup (. or ->)
Method signatures and docstrings:
- def __init__(self, head, member): Initialize node.
- def get_offset_info(self, struct_ctype): Given a struct ctype, return the member offset and ctype. If the given ctyp... | 6232136be38a29e8c18beae3d23e49ecfb7906fd | <|skeleton|>
class _ObjLookup:
"""Struct/union object lookup (. or ->)"""
def __init__(self, head, member):
"""Initialize node."""
<|body_0|>
def get_offset_info(self, struct_ctype):
"""Given a struct ctype, return the member offset and ctype. If the given ctype is None, emits the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _ObjLookup:
"""Struct/union object lookup (. or ->)"""
def __init__(self, head, member):
"""Initialize node."""
super().__init__()
self.head = head
self.member = member
def get_offset_info(self, struct_ctype):
"""Given a struct ctype, return the member offset ... | the_stack_v2_python_sparse | shivyc/tree/expr_nodes.py | ShivamSarodia/ShivyC | train | 1,072 |
b17200050cf0a563da67949e330d8ee1fe0d8028 | [
"self._sock = socket\nself._timeout_cb = timeout_cb\nself._send_period = Waldo._default_values['heartbeat_send_period']\nself._timeout = Waldo._default_values['heartbeat_timeout_period']\nself._lock = threading.Lock()\nself._partner_alive = True",
"self._time_since_last_beat = time.time()\nself._send_thread = thr... | <|body_start_0|>
self._sock = socket
self._timeout_cb = timeout_cb
self._send_period = Waldo._default_values['heartbeat_send_period']
self._timeout = Waldo._default_values['heartbeat_timeout_period']
self._lock = threading.Lock()
self._partner_alive = True
<|end_body_0|>
... | Implementation of a simple endpoint to endpoint heartbeat. Periodically sends heartbeats to the partner endpoint and listens for heartbeats from the partner endpoint. It is meant to be integrated within the Waldo endpoint and to use the same socket being used by the endpoint to communicate with its partner. | Heartbeat | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Heartbeat:
"""Implementation of a simple endpoint to endpoint heartbeat. Periodically sends heartbeats to the partner endpoint and listens for heartbeats from the partner endpoint. It is meant to be integrated within the Waldo endpoint and to use the same socket being used by the endpoint to comm... | stack_v2_sparse_classes_36k_train_012534 | 3,604 | no_license | [
{
"docstring": "Initializes the Heartbeat object. @param socket Python socket object. Should already be connected. @param timeout_cb Callback function which is invoked upon timeout. @param send_period Time (in seconds) representing how often to send heartbeats to the partner endpoint. The default period is 5 se... | 5 | stack_v2_sparse_classes_30k_train_016180 | Implement the Python class `Heartbeat` described below.
Class description:
Implementation of a simple endpoint to endpoint heartbeat. Periodically sends heartbeats to the partner endpoint and listens for heartbeats from the partner endpoint. It is meant to be integrated within the Waldo endpoint and to use the same so... | Implement the Python class `Heartbeat` described below.
Class description:
Implementation of a simple endpoint to endpoint heartbeat. Periodically sends heartbeats to the partner endpoint and listens for heartbeats from the partner endpoint. It is meant to be integrated within the Waldo endpoint and to use the same so... | 729a51f04d540111af01c283b1c17ad1489b664a | <|skeleton|>
class Heartbeat:
"""Implementation of a simple endpoint to endpoint heartbeat. Periodically sends heartbeats to the partner endpoint and listens for heartbeats from the partner endpoint. It is meant to be integrated within the Waldo endpoint and to use the same socket being used by the endpoint to comm... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Heartbeat:
"""Implementation of a simple endpoint to endpoint heartbeat. Periodically sends heartbeats to the partner endpoint and listens for heartbeats from the partner endpoint. It is meant to be integrated within the Waldo endpoint and to use the same socket being used by the endpoint to communicate with ... | the_stack_v2_python_sparse | waldo/lib/waldoHeartbeat.py | bmistree/Waldo | train | 0 |
71b451a96fb3ec06fbb539955938c8fe47bf8701 | [
"super(ActorNetwork, self).__init__()\nif norm_in:\n self.in_fn = nn.BatchNorm1d(input_dim)\n self.in_fn.weight.data.fill_(1)\n self.in_fn.bias.data.fill_(0)\nelse:\n self.in_fn = lambda x: x\nself.fc1 = nn.Linear(input_dim, hidden_dim)\nself.fc2 = nn.Linear(hidden_dim, hidden_dim)\nself.fc3 = nn.Linear... | <|body_start_0|>
super(ActorNetwork, self).__init__()
if norm_in:
self.in_fn = nn.BatchNorm1d(input_dim)
self.in_fn.weight.data.fill_(1)
self.in_fn.bias.data.fill_(0)
else:
self.in_fn = lambda x: x
self.fc1 = nn.Linear(input_dim, hidden_dim... | Deep Actor/Policy-Network choosing action based on individual observation | ActorNetwork | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActorNetwork:
"""Deep Actor/Policy-Network choosing action based on individual observation"""
def __init__(self, input_dim, output_dim, hidden_dim=64, dropout_p=0.0, discrete_actions=True, nonlin=F.relu, norm_in=True):
"""Initialize parameters and build model. :param input_dim: dimen... | stack_v2_sparse_classes_36k_train_012535 | 3,561 | no_license | [
{
"docstring": "Initialize parameters and build model. :param input_dim: dimension of network input :param output_dim: dimension of last layer :param dropout_p: dropout probability :param discrete_actions: flag indicating if actions are discrete :param nonlin: nonlinearity to use :param norm_in: normalise input... | 2 | stack_v2_sparse_classes_30k_train_019915 | Implement the Python class `ActorNetwork` described below.
Class description:
Deep Actor/Policy-Network choosing action based on individual observation
Method signatures and docstrings:
- def __init__(self, input_dim, output_dim, hidden_dim=64, dropout_p=0.0, discrete_actions=True, nonlin=F.relu, norm_in=True): Initi... | Implement the Python class `ActorNetwork` described below.
Class description:
Deep Actor/Policy-Network choosing action based on individual observation
Method signatures and docstrings:
- def __init__(self, input_dim, output_dim, hidden_dim=64, dropout_p=0.0, discrete_actions=True, nonlin=F.relu, norm_in=True): Initi... | 2afa0a9d83bd66a151c1a19242c5ef22cf4eb1f6 | <|skeleton|>
class ActorNetwork:
"""Deep Actor/Policy-Network choosing action based on individual observation"""
def __init__(self, input_dim, output_dim, hidden_dim=64, dropout_p=0.0, discrete_actions=True, nonlin=F.relu, norm_in=True):
"""Initialize parameters and build model. :param input_dim: dimen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActorNetwork:
"""Deep Actor/Policy-Network choosing action based on individual observation"""
def __init__(self, input_dim, output_dim, hidden_dim=64, dropout_p=0.0, discrete_actions=True, nonlin=F.relu, norm_in=True):
"""Initialize parameters and build model. :param input_dim: dimension of netwo... | the_stack_v2_python_sparse | marl_algorithms/maddpg/model.py | Jarvis-K/MSc_Curiosity_MARL | train | 0 |
50bfa94f976ed95b12dd2a8d1f81271675ce2246 | [
"try:\n collection = []\n for doc in Collection.objects(id=id):\n collection.append({'_id': str(ObjectId(doc['id'])), 'name': doc['name'], 'owner': doc['owner']['username'], 'private': doc['private'], 'snippets_id': [{'label': i['title'], 'value': str(ObjectId(i['id']))} for i in doc['snippets']], 'sni... | <|body_start_0|>
try:
collection = []
for doc in Collection.objects(id=id):
collection.append({'_id': str(ObjectId(doc['id'])), 'name': doc['name'], 'owner': doc['owner']['username'], 'private': doc['private'], 'snippets_id': [{'label': i['title'], 'value': str(ObjectId(i... | Requests against the Collection model to `api/collections/<id>` (singular) | CollectionApi | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectionApi:
"""Requests against the Collection model to `api/collections/<id>` (singular)"""
def get(self, id):
"""Retrieve one Collection object with a matching id. Yields: Identify a Collection object against a Collection model Flags: If it doesn't exist. Returns: [{dict}] mappa... | stack_v2_sparse_classes_36k_train_012536 | 9,315 | permissive | [
{
"docstring": "Retrieve one Collection object with a matching id. Yields: Identify a Collection object against a Collection model Flags: If it doesn't exist. Returns: [{dict}] mappable JSON Flask Response, 200, with dereferenced nested fields full of data, as an array even for one document to keep the frontend... | 3 | stack_v2_sparse_classes_30k_train_004082 | Implement the Python class `CollectionApi` described below.
Class description:
Requests against the Collection model to `api/collections/<id>` (singular)
Method signatures and docstrings:
- def get(self, id): Retrieve one Collection object with a matching id. Yields: Identify a Collection object against a Collection ... | Implement the Python class `CollectionApi` described below.
Class description:
Requests against the Collection model to `api/collections/<id>` (singular)
Method signatures and docstrings:
- def get(self, id): Retrieve one Collection object with a matching id. Yields: Identify a Collection object against a Collection ... | 76fa490b6b3e5c4f5d554df4498c485f974c7581 | <|skeleton|>
class CollectionApi:
"""Requests against the Collection model to `api/collections/<id>` (singular)"""
def get(self, id):
"""Retrieve one Collection object with a matching id. Yields: Identify a Collection object against a Collection model Flags: If it doesn't exist. Returns: [{dict}] mappa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CollectionApi:
"""Requests against the Collection model to `api/collections/<id>` (singular)"""
def get(self, id):
"""Retrieve one Collection object with a matching id. Yields: Identify a Collection object against a Collection model Flags: If it doesn't exist. Returns: [{dict}] mappable JSON Flas... | the_stack_v2_python_sparse | backend/resources/collection.py | taralika/cheathub | train | 0 |
24ae75f360d4f19452fffb23b28050a4897969d0 | [
"kwargs['is_master'] = False\nconnection_kwargs = dict(self.connection_kwargs)\nconnection_kwargs.update(kwargs)\nbase_args = inspect.getargspec(redis.client.Redis.__init__).args\nbase_args.append('is_master')\nbase_args.append('check_connection')\nextra_kwargs = {key: connection_kwargs[key] for key in connection_k... | <|body_start_0|>
kwargs['is_master'] = False
connection_kwargs = dict(self.connection_kwargs)
connection_kwargs.update(kwargs)
base_args = inspect.getargspec(redis.client.Redis.__init__).args
base_args.append('is_master')
base_args.append('check_connection')
extra... | self Sentinel class. | MySentinel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MySentinel:
"""self Sentinel class."""
def slave_for(self, service_name, redis_class=Redis, connection_pool_obj=None, connection_pool_class=SentinelConnectionPool, **kwargs):
"""overwrite slave_for to split the connection_kwargs to the redis_class."""
<|body_0|>
def mast... | stack_v2_sparse_classes_36k_train_012537 | 7,378 | no_license | [
{
"docstring": "overwrite slave_for to split the connection_kwargs to the redis_class.",
"name": "slave_for",
"signature": "def slave_for(self, service_name, redis_class=Redis, connection_pool_obj=None, connection_pool_class=SentinelConnectionPool, **kwargs)"
},
{
"docstring": "overwrite master_... | 2 | stack_v2_sparse_classes_30k_train_012992 | Implement the Python class `MySentinel` described below.
Class description:
self Sentinel class.
Method signatures and docstrings:
- def slave_for(self, service_name, redis_class=Redis, connection_pool_obj=None, connection_pool_class=SentinelConnectionPool, **kwargs): overwrite slave_for to split the connection_kwarg... | Implement the Python class `MySentinel` described below.
Class description:
self Sentinel class.
Method signatures and docstrings:
- def slave_for(self, service_name, redis_class=Redis, connection_pool_obj=None, connection_pool_class=SentinelConnectionPool, **kwargs): overwrite slave_for to split the connection_kwarg... | bcbd1abefe1d79d633327f80eb52688299ffbd90 | <|skeleton|>
class MySentinel:
"""self Sentinel class."""
def slave_for(self, service_name, redis_class=Redis, connection_pool_obj=None, connection_pool_class=SentinelConnectionPool, **kwargs):
"""overwrite slave_for to split the connection_kwargs to the redis_class."""
<|body_0|>
def mast... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MySentinel:
"""self Sentinel class."""
def slave_for(self, service_name, redis_class=Redis, connection_pool_obj=None, connection_pool_class=SentinelConnectionPool, **kwargs):
"""overwrite slave_for to split the connection_kwargs to the redis_class."""
kwargs['is_master'] = False
c... | the_stack_v2_python_sparse | fab_admin/myredis.py | cw1427/fab-admin | train | 9 |
61f94f4e3f247da315ad8791f541dea72160ca8c | [
"width = [root]\nval = [root.val]\ni = 0\nwhile i < len(width):\n cur = width[i]\n if cur.left is not None:\n width.append(cur.left)\n val.append(cur.left.val)\n if cur.right is not None:\n width.append(cur.right)\n val.append(cur.right.val)\n i += 1\nval.sort()\nreturn val[k... | <|body_start_0|>
width = [root]
val = [root.val]
i = 0
while i < len(width):
cur = width[i]
if cur.left is not None:
width.append(cur.left)
val.append(cur.left.val)
if cur.right is not None:
width.append(... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def kthSmallest(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
<|body_0|>
def kthSmallest2(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
width = [root]... | stack_v2_sparse_classes_36k_train_012538 | 1,763 | no_license | [
{
"docstring": ":type root: TreeNode :type k: int :rtype: int",
"name": "kthSmallest",
"signature": "def kthSmallest(self, root, k)"
},
{
"docstring": ":type root: TreeNode :type k: int :rtype: int",
"name": "kthSmallest2",
"signature": "def kthSmallest2(self, root, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012568 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthSmallest(self, root, k): :type root: TreeNode :type k: int :rtype: int
- def kthSmallest2(self, root, k): :type root: TreeNode :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthSmallest(self, root, k): :type root: TreeNode :type k: int :rtype: int
- def kthSmallest2(self, root, k): :type root: TreeNode :type k: int :rtype: int
<|skeleton|>
class... | 90d07a53a537212f41740adb8e65c4e30c3c4f64 | <|skeleton|>
class Solution:
def kthSmallest(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
<|body_0|>
def kthSmallest2(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def kthSmallest(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
width = [root]
val = [root.val]
i = 0
while i < len(width):
cur = width[i]
if cur.left is not None:
width.append(cur.left)
... | the_stack_v2_python_sparse | 排序与搜索和二叉树/二叉搜索树中第K小的元素.py | xianytt/LeetCode | train | 0 | |
4566c329e13a252d9f7624fe3e7d45cdd4a30bec | [
"i = n\ncnt = 0\nwhile i > 0:\n print('i is {0},n is {1}'.format(i, n))\n sq = math.sqrt(i)\n if sq - sq // 1 == 0:\n n -= i\n i = n\n cnt += 1\n else:\n i -= 1\nreturn cnt",
"dq = deque()\ndq.append(n)\nstep = 0\nwhile dq:\n for i in range(len(dq)):\n pop = dq.po... | <|body_start_0|>
i = n
cnt = 0
while i > 0:
print('i is {0},n is {1}'.format(i, n))
sq = math.sqrt(i)
if sq - sq // 1 == 0:
n -= i
i = n
cnt += 1
else:
i -= 1
return cnt
<|end_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numSquares_failed(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def numSquares_slow(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def numSquares(self, n):
""":type n: int :rtype: int"""
<|body_2|>
<|end_skeleton... | stack_v2_sparse_classes_36k_train_012539 | 2,586 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "numSquares_failed",
"signature": "def numSquares_failed(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "numSquares_slow",
"signature": "def numSquares_slow(self, n)"
},
{
"docstring": ":type n: int :rtype: int",... | 3 | stack_v2_sparse_classes_30k_train_009545 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSquares_failed(self, n): :type n: int :rtype: int
- def numSquares_slow(self, n): :type n: int :rtype: int
- def numSquares(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSquares_failed(self, n): :type n: int :rtype: int
- def numSquares_slow(self, n): :type n: int :rtype: int
- def numSquares(self, n): :type n: int :rtype: int
<|skeleton|... | 93266095329e2e8e949a72371b88b07382a60e0d | <|skeleton|>
class Solution:
def numSquares_failed(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def numSquares_slow(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def numSquares(self, n):
""":type n: int :rtype: int"""
<|body_2|>
<|end_skeleton... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numSquares_failed(self, n):
""":type n: int :rtype: int"""
i = n
cnt = 0
while i > 0:
print('i is {0},n is {1}'.format(i, n))
sq = math.sqrt(i)
if sq - sq // 1 == 0:
n -= i
i = n
c... | the_stack_v2_python_sparse | numSquares.py | shivangi-prog/leetcode | train | 0 | |
e09eca9387b3fae4b74f7f48c362b8b3d40da401 | [
"if not a1 or not a2:\n return list()\nif len(a1) < len(a2):\n u = list(set(a1))\n v = list(set(a2))\nelse:\n u = list(set(a2))\n v = list(set(a1))\nu.sort()\nr = [x for x in v if self.is_present(x, u)]\nreturn r",
"l = 0\nr = len(u) - 1\nwhile l <= r:\n m = l + (r - l) // 2\n if u[m] == x:\n... | <|body_start_0|>
if not a1 or not a2:
return list()
if len(a1) < len(a2):
u = list(set(a1))
v = list(set(a2))
else:
u = list(set(a2))
v = list(set(a1))
u.sort()
r = [x for x in v if self.is_present(x, u)]
return ... | Iteration over all elements of smaller input array with binary search. Time complexity: O(min(len(n), len(m))) - Traverse all elements of smaller input array Space complexity: O(min(len(n), len(m))) - Amortized collect all elements of smaller input array | Solution2 | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution2:
"""Iteration over all elements of smaller input array with binary search. Time complexity: O(min(len(n), len(m))) - Traverse all elements of smaller input array Space complexity: O(min(len(n), len(m))) - Amortized collect all elements of smaller input array"""
def find_intersectio... | stack_v2_sparse_classes_36k_train_012540 | 3,821 | permissive | [
{
"docstring": "Determines common elements in both input arrays. :param list[int] a1: first input array :param list[int] a2: second input array :return: array of elements common to both input arrays :rtype: list[int]",
"name": "find_intersection",
"signature": "def find_intersection(self, a1, a2)"
},
... | 2 | null | Implement the Python class `Solution2` described below.
Class description:
Iteration over all elements of smaller input array with binary search. Time complexity: O(min(len(n), len(m))) - Traverse all elements of smaller input array Space complexity: O(min(len(n), len(m))) - Amortized collect all elements of smaller i... | Implement the Python class `Solution2` described below.
Class description:
Iteration over all elements of smaller input array with binary search. Time complexity: O(min(len(n), len(m))) - Traverse all elements of smaller input array Space complexity: O(min(len(n), len(m))) - Amortized collect all elements of smaller i... | 69f90877c5466927e8b081c4268cbcda074813ec | <|skeleton|>
class Solution2:
"""Iteration over all elements of smaller input array with binary search. Time complexity: O(min(len(n), len(m))) - Traverse all elements of smaller input array Space complexity: O(min(len(n), len(m))) - Amortized collect all elements of smaller input array"""
def find_intersectio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution2:
"""Iteration over all elements of smaller input array with binary search. Time complexity: O(min(len(n), len(m))) - Traverse all elements of smaller input array Space complexity: O(min(len(n), len(m))) - Amortized collect all elements of smaller input array"""
def find_intersection(self, a1, a... | the_stack_v2_python_sparse | 0349_intersection_two_arrays/python_source.py | arthurdysart/LeetCode | train | 0 |
ea17631ac4dd76bd8f9486f65c6a1478b87d973c | [
"self._pubsub = pubsub_bus\nself._player = player_\nbuilder = Gtk.Builder.new_from_string(resources.read_text('pepper_music_player.ui', 'player_status_position_slider.glade'), length=-1)\nself.widget = builder.get_object('container')\nalignment.set_direction_recursive(self.widget, Gtk.TextDirection.LTR)\nself._posi... | <|body_start_0|>
self._pubsub = pubsub_bus
self._player = player_
builder = Gtk.Builder.new_from_string(resources.read_text('pepper_music_player.ui', 'player_status_position_slider.glade'), length=-1)
self.widget = builder.get_object('container')
alignment.set_direction_recursive... | Position slider, including labels for the current position and duration. Attributes: widget: Widget containing the slider and labels. slider: Slider for seeking. This is public for use in tests only. | PositionSlider | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PositionSlider:
"""Position slider, including labels for the current position and duration. Attributes: widget: Widget containing the slider and labels. slider: Slider for seeking. This is public for use in tests only."""
def __init__(self, *, pubsub_bus: pubsub.PubSub, player_: player.Playe... | stack_v2_sparse_classes_36k_train_012541 | 7,252 | permissive | [
{
"docstring": "Initializer. Args: pubsub_bus: PubSub message bus. player_: Player.",
"name": "__init__",
"signature": "def __init__(self, *, pubsub_bus: pubsub.PubSub, player_: player.Player) -> None"
},
{
"docstring": "Handler for PlayStatus updates.",
"name": "_handle_play_status",
"s... | 3 | stack_v2_sparse_classes_30k_train_020995 | Implement the Python class `PositionSlider` described below.
Class description:
Position slider, including labels for the current position and duration. Attributes: widget: Widget containing the slider and labels. slider: Slider for seeking. This is public for use in tests only.
Method signatures and docstrings:
- de... | Implement the Python class `PositionSlider` described below.
Class description:
Position slider, including labels for the current position and duration. Attributes: widget: Widget containing the slider and labels. slider: Slider for seeking. This is public for use in tests only.
Method signatures and docstrings:
- de... | 2a45aef6deb6247c42d63b5f7475ec5517ea9321 | <|skeleton|>
class PositionSlider:
"""Position slider, including labels for the current position and duration. Attributes: widget: Widget containing the slider and labels. slider: Slider for seeking. This is public for use in tests only."""
def __init__(self, *, pubsub_bus: pubsub.PubSub, player_: player.Playe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PositionSlider:
"""Position slider, including labels for the current position and duration. Attributes: widget: Widget containing the slider and labels. slider: Slider for seeking. This is public for use in tests only."""
def __init__(self, *, pubsub_bus: pubsub.PubSub, player_: player.Player) -> None:
... | the_stack_v2_python_sparse | pepper_music_player/ui/player_status.py | EmDBaum/pepper-music-player | train | 0 |
0a01aa7280ddbe8bb01c13de47e1fd3683f53f12 | [
"self.list_heap = []\nself.size = 0\nif iterable:\n for val in iterable:\n self.push(val)",
"while val // 2 > 0:\n if self.list_heap[val] < self.list_heap[val // 2]:\n temp = self.list_heap[val // 2]\n self.list_heap[val // 2] = self.list_heap[val]\n self.list_heap[val] = temp\n ... | <|body_start_0|>
self.list_heap = []
self.size = 0
if iterable:
for val in iterable:
self.push(val)
<|end_body_0|>
<|body_start_1|>
while val // 2 > 0:
if self.list_heap[val] < self.list_heap[val // 2]:
temp = self.list_heap[val //... | The Binary Heap Class. __init__([iterable]): takes an optional iterable object when instantiating the class. _perc_ip(val): Send the value up the heap as it is pushed in. push(val): Append a value to the end of the list, increase list size, push the index that is equal to size, up the list. _perc_down(val): Send a valu... | BBinnyHeap | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BBinnyHeap:
"""The Binary Heap Class. __init__([iterable]): takes an optional iterable object when instantiating the class. _perc_ip(val): Send the value up the heap as it is pushed in. push(val): Append a value to the end of the list, increase list size, push the index that is equal to size, up ... | stack_v2_sparse_classes_36k_train_012542 | 3,124 | permissive | [
{
"docstring": "Take an optional iterable object when instantiating the class. Initialize size to zero.",
"name": "__init__",
"signature": "def __init__(self, iterable=None)"
},
{
"docstring": "Send the value up the heap as it is pushed in.",
"name": "_perc_up",
"signature": "def _perc_u... | 6 | stack_v2_sparse_classes_30k_train_008735 | Implement the Python class `BBinnyHeap` described below.
Class description:
The Binary Heap Class. __init__([iterable]): takes an optional iterable object when instantiating the class. _perc_ip(val): Send the value up the heap as it is pushed in. push(val): Append a value to the end of the list, increase list size, pu... | Implement the Python class `BBinnyHeap` described below.
Class description:
The Binary Heap Class. __init__([iterable]): takes an optional iterable object when instantiating the class. _perc_ip(val): Send the value up the heap as it is pushed in. push(val): Append a value to the end of the list, increase list size, pu... | 7951b0f0a880edd9fae5de1edc8d9290746cdbc4 | <|skeleton|>
class BBinnyHeap:
"""The Binary Heap Class. __init__([iterable]): takes an optional iterable object when instantiating the class. _perc_ip(val): Send the value up the heap as it is pushed in. push(val): Append a value to the end of the list, increase list size, push the index that is equal to size, up ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BBinnyHeap:
"""The Binary Heap Class. __init__([iterable]): takes an optional iterable object when instantiating the class. _perc_ip(val): Send the value up the heap as it is pushed in. push(val): Append a value to the end of the list, increase list size, push the index that is equal to size, up the list. _pe... | the_stack_v2_python_sparse | src/binheap.py | Copenbacon/data-structures | train | 0 |
872203336420d05f7776ca38a46f0947a0c0de1e | [
"self.source = source\nself.line_num = 0\nreturn",
"s = self.source.readline()\nself.line_num += 1\nreturn s"
] | <|body_start_0|>
self.source = source
self.line_num = 0
return
<|end_body_0|>
<|body_start_1|>
s = self.source.readline()
self.line_num += 1
return s
<|end_body_1|>
| FileWithLineNum | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileWithLineNum:
def __init__(self, source):
"""start at line 0"""
<|body_0|>
def read(self, bytes):
"""read the next line and inc the line number"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.source = source
self.line_num = 0
... | stack_v2_sparse_classes_36k_train_012543 | 1,785 | no_license | [
{
"docstring": "start at line 0",
"name": "__init__",
"signature": "def __init__(self, source)"
},
{
"docstring": "read the next line and inc the line number",
"name": "read",
"signature": "def read(self, bytes)"
}
] | 2 | null | Implement the Python class `FileWithLineNum` described below.
Class description:
Implement the FileWithLineNum class.
Method signatures and docstrings:
- def __init__(self, source): start at line 0
- def read(self, bytes): read the next line and inc the line number | Implement the Python class `FileWithLineNum` described below.
Class description:
Implement the FileWithLineNum class.
Method signatures and docstrings:
- def __init__(self, source): start at line 0
- def read(self, bytes): read the next line and inc the line number
<|skeleton|>
class FileWithLineNum:
def __init... | eba6c1489b503fdcf040a126942643b355867bcd | <|skeleton|>
class FileWithLineNum:
def __init__(self, source):
"""start at line 0"""
<|body_0|>
def read(self, bytes):
"""read the next line and inc the line number"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileWithLineNum:
def __init__(self, source):
"""start at line 0"""
self.source = source
self.line_num = 0
return
def read(self, bytes):
"""read the next line and inc the line number"""
s = self.source.readline()
self.line_num += 1
return s
| the_stack_v2_python_sparse | src/ibm/teal/util/xml_file_reader.py | ppjsand/pyteal | train | 1 | |
716ec896226449afe3205e7c147ad000e9181a5d | [
"self.tiles = self._create_tiles(map_data)\nself._connect_tiles()\nself.start = self.tiles[0][0]",
"tiles = []\nfor i in range(len(map_data)):\n new_row = []\n for k in range(len(map_data[i])):\n icon = map_data[i][k]\n new_row.append(Tile(k, i, icon, TILE_DESCS[icon]))\n tiles.append(new_r... | <|body_start_0|>
self.tiles = self._create_tiles(map_data)
self._connect_tiles()
self.start = self.tiles[0][0]
<|end_body_0|>
<|body_start_1|>
tiles = []
for i in range(len(map_data)):
new_row = []
for k in range(len(map_data[i])):
icon = ... | A class to represent a map made of several connected tiles. | Map | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Map:
"""A class to represent a map made of several connected tiles."""
def __init__(self, map_data: list):
"""Given a list of lists representing map data, construct Tiles to represent each location, connect adjacent tiles, and assign a starting point. In a valid map, the starting poi... | stack_v2_sparse_classes_36k_train_012544 | 9,181 | no_license | [
{
"docstring": "Given a list of lists representing map data, construct Tiles to represent each location, connect adjacent tiles, and assign a starting point. In a valid map, the starting point will NOT be a wall, and every gem in the map will be accessible through up/down/left/right movements, beginning from th... | 5 | null | Implement the Python class `Map` described below.
Class description:
A class to represent a map made of several connected tiles.
Method signatures and docstrings:
- def __init__(self, map_data: list): Given a list of lists representing map data, construct Tiles to represent each location, connect adjacent tiles, and ... | Implement the Python class `Map` described below.
Class description:
A class to represent a map made of several connected tiles.
Method signatures and docstrings:
- def __init__(self, map_data: list): Given a list of lists representing map data, construct Tiles to represent each location, connect adjacent tiles, and ... | c7437d387dc2b9a8039c60d8786373899c2e28bd | <|skeleton|>
class Map:
"""A class to represent a map made of several connected tiles."""
def __init__(self, map_data: list):
"""Given a list of lists representing map data, construct Tiles to represent each location, connect adjacent tiles, and assign a starting point. In a valid map, the starting poi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Map:
"""A class to represent a map made of several connected tiles."""
def __init__(self, map_data: list):
"""Given a list of lists representing map data, construct Tiles to represent each location, connect adjacent tiles, and assign a starting point. In a valid map, the starting point will NOT b... | the_stack_v2_python_sparse | CSC148/A2/part1/final drillbot.py | xxcocoymlxx/Study-Notes | train | 2 |
e4ba491480cf19ca86f43be06ede87e7ec90a56a | [
"self.config = Config.parse(config_entry)\nself.config_entry = config_entry\n_LOGGER.debug(f'{DOMAIN} EufySecurityOptionFlowHandler - {config_entry.options}')\nself.schema = vol.Schema({vol.Optional(ConfigField.sync_interval.name, default=self.config.sync_interval): int, vol.Optional(ConfigField.rtsp_server_address... | <|body_start_0|>
self.config = Config.parse(config_entry)
self.config_entry = config_entry
_LOGGER.debug(f'{DOMAIN} EufySecurityOptionFlowHandler - {config_entry.options}')
self.schema = vol.Schema({vol.Optional(ConfigField.sync_interval.name, default=self.config.sync_interval): int, vol... | Option flow handler for integration | EufySecurityOptionFlowHandler | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EufySecurityOptionFlowHandler:
"""Option flow handler for integration"""
def __init__(self, config_entry: ConfigEntry) -> None:
"""Initialize option flow handler"""
<|body_0|>
async def async_step_init(self, user_input=None):
"""Form handler"""
<|body_1|>... | stack_v2_sparse_classes_36k_train_012545 | 6,892 | permissive | [
{
"docstring": "Initialize option flow handler",
"name": "__init__",
"signature": "def __init__(self, config_entry: ConfigEntry) -> None"
},
{
"docstring": "Form handler",
"name": "async_step_init",
"signature": "async def async_step_init(self, user_input=None)"
}
] | 2 | null | Implement the Python class `EufySecurityOptionFlowHandler` described below.
Class description:
Option flow handler for integration
Method signatures and docstrings:
- def __init__(self, config_entry: ConfigEntry) -> None: Initialize option flow handler
- async def async_step_init(self, user_input=None): Form handler | Implement the Python class `EufySecurityOptionFlowHandler` described below.
Class description:
Option flow handler for integration
Method signatures and docstrings:
- def __init__(self, config_entry: ConfigEntry) -> None: Initialize option flow handler
- async def async_step_init(self, user_input=None): Form handler
... | 8548d9999ddd54f13d6a307e013abcb8c897a74e | <|skeleton|>
class EufySecurityOptionFlowHandler:
"""Option flow handler for integration"""
def __init__(self, config_entry: ConfigEntry) -> None:
"""Initialize option flow handler"""
<|body_0|>
async def async_step_init(self, user_input=None):
"""Form handler"""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EufySecurityOptionFlowHandler:
"""Option flow handler for integration"""
def __init__(self, config_entry: ConfigEntry) -> None:
"""Initialize option flow handler"""
self.config = Config.parse(config_entry)
self.config_entry = config_entry
_LOGGER.debug(f'{DOMAIN} EufySecur... | the_stack_v2_python_sparse | custom_components/eufy_security/config_flow.py | bacco007/HomeAssistantConfig | train | 98 |
96533c1d9d89100cfdc726bb1c499b87ac46db3c | [
"self.lists = [v1, v2]\nself.pointer_list = [0] * 2\nself.cur_list = 0\nself.total_size = sum((len(i) for i in self.lists))\nself.got = 0",
"if self.hasNext():\n v = self.lists[self.cur_list][self.pointer_list[self.cur_list]]\n self.pointer_list[self.cur_list] += 1\n self.cur_list = (self.cur_list + 1) %... | <|body_start_0|>
self.lists = [v1, v2]
self.pointer_list = [0] * 2
self.cur_list = 0
self.total_size = sum((len(i) for i in self.lists))
self.got = 0
<|end_body_0|>
<|body_start_1|>
if self.hasNext():
v = self.lists[self.cur_list][self.pointer_list[self.cur_l... | ZigzagIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZigzagIterator:
def __init__(self, v1, v2):
"""Initialize your data structure here. :type v1: List[int] :type v2: List[int]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end... | stack_v2_sparse_classes_36k_train_012546 | 1,202 | no_license | [
{
"docstring": "Initialize your data structure here. :type v1: List[int] :type v2: List[int]",
"name": "__init__",
"signature": "def __init__(self, v1, v2)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name"... | 3 | null | Implement the Python class `ZigzagIterator` described below.
Class description:
Implement the ZigzagIterator class.
Method signatures and docstrings:
- def __init__(self, v1, v2): Initialize your data structure here. :type v1: List[int] :type v2: List[int]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bo... | Implement the Python class `ZigzagIterator` described below.
Class description:
Implement the ZigzagIterator class.
Method signatures and docstrings:
- def __init__(self, v1, v2): Initialize your data structure here. :type v1: List[int] :type v2: List[int]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bo... | 490c38a9478838ff23c9f910cc950633b1e3f994 | <|skeleton|>
class ZigzagIterator:
def __init__(self, v1, v2):
"""Initialize your data structure here. :type v1: List[int] :type v2: List[int]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZigzagIterator:
def __init__(self, v1, v2):
"""Initialize your data structure here. :type v1: List[int] :type v2: List[int]"""
self.lists = [v1, v2]
self.pointer_list = [0] * 2
self.cur_list = 0
self.total_size = sum((len(i) for i in self.lists))
self.got = 0
... | the_stack_v2_python_sparse | Zigzag Iterator/solution.py | normanyahq/LeetCodeSolution | train | 0 | |
bb1c16e7f0a35a17ac50abf264c020c1bd2ea353 | [
"self.open('https://www.baidu.com')\nself.find_element('#kw')\nself.send_values(search_key, css='#kw')\nself.click_element(css='#su')\nif fun == 'test2':\n self.assertEqual(1, 2)",
"self.open('https://www.baidu.com')\nfor i in range(5):\n with self.subTest(parrern=i):\n self.send_values(i, css='#kw')... | <|body_start_0|>
self.open('https://www.baidu.com')
self.find_element('#kw')
self.send_values(search_key, css='#kw')
self.click_element(css='#su')
if fun == 'test2':
self.assertEqual(1, 2)
<|end_body_0|>
<|body_start_1|>
self.open('https://www.baidu.com')
... | This is Test a | DemoTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DemoTest:
"""This is Test a"""
def test_login(self, fun, search_key):
"""test_login_1"""
<|body_0|>
def test_subtest(self):
"""test subtest_1"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.open('https://www.baidu.com')
self.find_el... | stack_v2_sparse_classes_36k_train_012547 | 1,275 | no_license | [
{
"docstring": "test_login_1",
"name": "test_login",
"signature": "def test_login(self, fun, search_key)"
},
{
"docstring": "test subtest_1",
"name": "test_subtest",
"signature": "def test_subtest(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007815 | Implement the Python class `DemoTest` described below.
Class description:
This is Test a
Method signatures and docstrings:
- def test_login(self, fun, search_key): test_login_1
- def test_subtest(self): test subtest_1 | Implement the Python class `DemoTest` described below.
Class description:
This is Test a
Method signatures and docstrings:
- def test_login(self, fun, search_key): test_login_1
- def test_subtest(self): test subtest_1
<|skeleton|>
class DemoTest:
"""This is Test a"""
def test_login(self, fun, search_key):
... | c38e5e21001325878be824c0858f3060df184d48 | <|skeleton|>
class DemoTest:
"""This is Test a"""
def test_login(self, fun, search_key):
"""test_login_1"""
<|body_0|>
def test_subtest(self):
"""test subtest_1"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DemoTest:
"""This is Test a"""
def test_login(self, fun, search_key):
"""test_login_1"""
self.open('https://www.baidu.com')
self.find_element('#kw')
self.send_values(search_key, css='#kw')
self.click_element(css='#su')
if fun == 'test2':
self.as... | the_stack_v2_python_sparse | demo/testcases/normal_test/test_1.py | 670662282/SelenPyTest | train | 0 |
1807cd4c53499022753c9d87b4717ca0d4f92e2a | [
"for e in submission.elements.values():\n posed_corners = e.pose.transform_all_from(e.bounds.corners())\n e.posed_bbox = ComputeBbox().from_point_cloud(posed_corners)\nfor e in ground_truth.elements.values():\n posed_corners = e.pose.transform_all_from(e.bounds.corners())\n e.posed_bbox = ComputeBbox().... | <|body_start_0|>
for e in submission.elements.values():
posed_corners = e.pose.transform_all_from(e.bounds.corners())
e.posed_bbox = ComputeBbox().from_point_cloud(posed_corners)
for e in ground_truth.elements.values():
posed_corners = e.pose.transform_all_from(e.boun... | Algorithm to evaluate a submission for the bounding box track. | BBEvaluator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BBEvaluator:
"""Algorithm to evaluate a submission for the bounding box track."""
def __init__(self, submission, ground_truth, settings=None):
"""Constructor. Computes similarity between all elements in the submission and ground_truth and also computes data association caches. Inputs... | stack_v2_sparse_classes_36k_train_012548 | 4,356 | permissive | [
{
"docstring": "Constructor. Computes similarity between all elements in the submission and ground_truth and also computes data association caches. Inputs: submission (ProjectScene) - Submitted scene to be evaluated ground_truth (ProjectScene) - The ground truth scene settings (dict) - configuration for the eva... | 3 | stack_v2_sparse_classes_30k_train_017425 | Implement the Python class `BBEvaluator` described below.
Class description:
Algorithm to evaluate a submission for the bounding box track.
Method signatures and docstrings:
- def __init__(self, submission, ground_truth, settings=None): Constructor. Computes similarity between all elements in the submission and groun... | Implement the Python class `BBEvaluator` described below.
Class description:
Algorithm to evaluate a submission for the bounding box track.
Method signatures and docstrings:
- def __init__(self, submission, ground_truth, settings=None): Constructor. Computes similarity between all elements in the submission and groun... | 073811351a7259ccabd145e2307f1656c50552cf | <|skeleton|>
class BBEvaluator:
"""Algorithm to evaluate a submission for the bounding box track."""
def __init__(self, submission, ground_truth, settings=None):
"""Constructor. Computes similarity between all elements in the submission and ground_truth and also computes data association caches. Inputs... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BBEvaluator:
"""Algorithm to evaluate a submission for the bounding box track."""
def __init__(self, submission, ground_truth, settings=None):
"""Constructor. Computes similarity between all elements in the submission and ground_truth and also computes data association caches. Inputs: submission ... | the_stack_v2_python_sparse | sumo/metrics/bb_evaluator.py | RishabhJain2018/sumo-challenge | train | 0 |
a8f2962b8b197f638ee917f9c175e551197e0a26 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UserExperienceAnalyticsWorkFromAnywhereHardwareReadinessMetric()",
"from .entity import Entity\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {'osCheckFailedPercentage': lambda n: setattr(self, 'os_check_failed... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UserExperienceAnalyticsWorkFromAnywhereHardwareReadinessMetric()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .entity import Entity
fields: Dict[str, Callable[... | The user experience analytics hardware readiness entity contains account level information about hardware blockers for windows upgrade. | UserExperienceAnalyticsWorkFromAnywhereHardwareReadinessMetric | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserExperienceAnalyticsWorkFromAnywhereHardwareReadinessMetric:
"""The user experience analytics hardware readiness entity contains account level information about hardware blockers for windows upgrade."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExper... | stack_v2_sparse_classes_36k_train_012549 | 7,532 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: UserExperienceAnalyticsWorkFromAnywhereHardwareReadinessMetric",
"name": "create_from_discriminator_value",
... | 3 | stack_v2_sparse_classes_30k_train_019698 | Implement the Python class `UserExperienceAnalyticsWorkFromAnywhereHardwareReadinessMetric` described below.
Class description:
The user experience analytics hardware readiness entity contains account level information about hardware blockers for windows upgrade.
Method signatures and docstrings:
- def create_from_di... | Implement the Python class `UserExperienceAnalyticsWorkFromAnywhereHardwareReadinessMetric` described below.
Class description:
The user experience analytics hardware readiness entity contains account level information about hardware blockers for windows upgrade.
Method signatures and docstrings:
- def create_from_di... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UserExperienceAnalyticsWorkFromAnywhereHardwareReadinessMetric:
"""The user experience analytics hardware readiness entity contains account level information about hardware blockers for windows upgrade."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExper... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserExperienceAnalyticsWorkFromAnywhereHardwareReadinessMetric:
"""The user experience analytics hardware readiness entity contains account level information about hardware blockers for windows upgrade."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalytic... | the_stack_v2_python_sparse | msgraph/generated/models/user_experience_analytics_work_from_anywhere_hardware_readiness_metric.py | microsoftgraph/msgraph-sdk-python | train | 135 |
c3e45acad087ed28cd648d637fb225c4e8709c60 | [
"user = User.objects.create(username='testuser', password='qwerty12345Q!')\nrecruiter = User.objects.create(username='recruiter2', first_name='first_recruiter', last_name='last_recruiter', email='recruiter@mail.com')\ncandidate = User.objects.create(username='candidate2', first_name='first_candidate', last_name='la... | <|body_start_0|>
user = User.objects.create(username='testuser', password='qwerty12345Q!')
recruiter = User.objects.create(username='recruiter2', first_name='first_recruiter', last_name='last_recruiter', email='recruiter@mail.com')
candidate = User.objects.create(username='candidate2', first_nam... | Test POST request Interviews app | InterviewsPostTestCases | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InterviewsPostTestCases:
"""Test POST request Interviews app"""
def setUp(self):
"""Create new data in in linked tables"""
<|body_0|>
def test_post_create_interviews(self):
"""Test for POST Interviews"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_012550 | 6,694 | no_license | [
{
"docstring": "Create new data in in linked tables",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test for POST Interviews",
"name": "test_post_create_interviews",
"signature": "def test_post_create_interviews(self)"
}
] | 2 | null | Implement the Python class `InterviewsPostTestCases` described below.
Class description:
Test POST request Interviews app
Method signatures and docstrings:
- def setUp(self): Create new data in in linked tables
- def test_post_create_interviews(self): Test for POST Interviews | Implement the Python class `InterviewsPostTestCases` described below.
Class description:
Test POST request Interviews app
Method signatures and docstrings:
- def setUp(self): Create new data in in linked tables
- def test_post_create_interviews(self): Test for POST Interviews
<|skeleton|>
class InterviewsPostTestCas... | f448ec0453818d55c5c9d30aaa4f19e1d7ca5867 | <|skeleton|>
class InterviewsPostTestCases:
"""Test POST request Interviews app"""
def setUp(self):
"""Create new data in in linked tables"""
<|body_0|>
def test_post_create_interviews(self):
"""Test for POST Interviews"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InterviewsPostTestCases:
"""Test POST request Interviews app"""
def setUp(self):
"""Create new data in in linked tables"""
user = User.objects.create(username='testuser', password='qwerty12345Q!')
recruiter = User.objects.create(username='recruiter2', first_name='first_recruiter',... | the_stack_v2_python_sparse | Portfolio/tech-interview/techinterview/interviews/test_interviews.py | HeCToR74/Python | train | 1 |
b0f7473b5387043ecb040ede04506630850022a2 | [
"super(PPO_CriticNetwork, self).__init__()\nxp_input = L.Placeholder((None, D_obs))\nxp = L.Linear(hidden_sizes[0])(xp_input)\nxp = L.ReLU()(xp)\nxp = L.Linear(hidden_sizes[1])(xp)\nxp = L.ReLU()(xp)\nxp = L.Linear(1)(xp)\nself.model = L.Functional(inputs=xp_input, outputs=xp)\nself.model.build((None, D_obs))",
"... | <|body_start_0|>
super(PPO_CriticNetwork, self).__init__()
xp_input = L.Placeholder((None, D_obs))
xp = L.Linear(hidden_sizes[0])(xp_input)
xp = L.ReLU()(xp)
xp = L.Linear(hidden_sizes[1])(xp)
xp = L.ReLU()(xp)
xp = L.Linear(1)(xp)
self.model = L.Functiona... | PPO custom critic network structure | PPO_CriticNetwork | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PPO_CriticNetwork:
"""PPO custom critic network structure"""
def __init__(self, D_obs, hidden_sizes=[64, 64]):
"""Constructor for PPO critic network Args: D_obs: observation space dimension, scalar hidden_sizes: list of fully connected dimension"""
<|body_0|>
def forward... | stack_v2_sparse_classes_36k_train_012551 | 5,859 | permissive | [
{
"docstring": "Constructor for PPO critic network Args: D_obs: observation space dimension, scalar hidden_sizes: list of fully connected dimension",
"name": "__init__",
"signature": "def __init__(self, D_obs, hidden_sizes=[64, 64])"
},
{
"docstring": "Forward pass of actor network. Input assume... | 2 | stack_v2_sparse_classes_30k_train_006883 | Implement the Python class `PPO_CriticNetwork` described below.
Class description:
PPO custom critic network structure
Method signatures and docstrings:
- def __init__(self, D_obs, hidden_sizes=[64, 64]): Constructor for PPO critic network Args: D_obs: observation space dimension, scalar hidden_sizes: list of fully c... | Implement the Python class `PPO_CriticNetwork` described below.
Class description:
PPO custom critic network structure
Method signatures and docstrings:
- def __init__(self, D_obs, hidden_sizes=[64, 64]): Constructor for PPO critic network Args: D_obs: observation space dimension, scalar hidden_sizes: list of fully c... | 2556bd9c362a53e0a94da914ba59b5d4621c4081 | <|skeleton|>
class PPO_CriticNetwork:
"""PPO custom critic network structure"""
def __init__(self, D_obs, hidden_sizes=[64, 64]):
"""Constructor for PPO critic network Args: D_obs: observation space dimension, scalar hidden_sizes: list of fully connected dimension"""
<|body_0|>
def forward... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PPO_CriticNetwork:
"""PPO custom critic network structure"""
def __init__(self, D_obs, hidden_sizes=[64, 64]):
"""Constructor for PPO critic network Args: D_obs: observation space dimension, scalar hidden_sizes: list of fully connected dimension"""
super(PPO_CriticNetwork, self).__init__(... | the_stack_v2_python_sparse | surreal/model/model_builders/builders.py | PeihongYu/surreal | train | 0 |
156d0ef95d585b74975a6d0822c3636faf6e7a03 | [
"super().__init__()\nself.conv_name = conv_name\nif conv_name in self.conv_dict:\n self.conv_layer = self.conv_dict[conv_name]\nelse:\n raise KeyError(f'Unknown model name \"{conv_name}\".Available models are: {str(self.conv_dict.keys())}')\nself.conv_layers = torch.nn.ModuleList()\ndefault_conv_hparams = sel... | <|body_start_0|>
super().__init__()
self.conv_name = conv_name
if conv_name in self.conv_dict:
self.conv_layer = self.conv_dict[conv_name]
else:
raise KeyError(f'Unknown model name "{conv_name}".Available models are: {str(self.conv_dict.keys())}')
self.con... | GNN Regressor model | GNNRegressor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GNNRegressor:
"""GNN Regressor model"""
def __init__(self, in_channels, out_channels, conv_name, conv_hparams, num_layers, hidden_channels, num_layers_fc, hidden_channels_fc, hidden_channels_flows, num_transforms):
"""Arguments: - in_channels: [int] number of input channels - out_cha... | stack_v2_sparse_classes_36k_train_012552 | 3,796 | permissive | [
{
"docstring": "Arguments: - in_channels: [int] number of input channels - out_channels: [int] number of output channels - conv_name [str]: name of the GNN layer - conv_hparams: [dict] dictionary with extra kargs for GNN layer - num_layers: [int] number of GNN hidden layers - hidden_channels: [int] number of GN... | 2 | stack_v2_sparse_classes_30k_train_008200 | Implement the Python class `GNNRegressor` described below.
Class description:
GNN Regressor model
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, conv_name, conv_hparams, num_layers, hidden_channels, num_layers_fc, hidden_channels_fc, hidden_channels_flows, num_transforms): Arguments... | Implement the Python class `GNNRegressor` described below.
Class description:
GNN Regressor model
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, conv_name, conv_hparams, num_layers, hidden_channels, num_layers_fc, hidden_channels_fc, hidden_channels_flows, num_transforms): Arguments... | bfafeff3354cc760f35f34aca19bdd50e5998054 | <|skeleton|>
class GNNRegressor:
"""GNN Regressor model"""
def __init__(self, in_channels, out_channels, conv_name, conv_hparams, num_layers, hidden_channels, num_layers_fc, hidden_channels_fc, hidden_channels_flows, num_transforms):
"""Arguments: - in_channels: [int] number of input channels - out_cha... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GNNRegressor:
"""GNN Regressor model"""
def __init__(self, in_channels, out_channels, conv_name, conv_hparams, num_layers, hidden_channels, num_layers_fc, hidden_channels_fc, hidden_channels_flows, num_transforms):
"""Arguments: - in_channels: [int] number of input channels - out_channels: [int] ... | the_stack_v2_python_sparse | src/dsphs_gnn/gnn.py | trivnguyen/dsphs_gnn | train | 2 |
e3f6f6f8928b32d5e3c6235d92e58fae2bb0f5d9 | [
"out = io.BytesIO()\nwith gzip.GzipFile(fileobj=out, mode='w') as fo:\n fo.write(_str.encode())\nbytes_obj = out.getvalue()\nreturn bytes_obj",
"tf.logging.info('Writing file: {}'.format(file_path))\nif content_encoding not in {None, 'gzip'}:\n raise ValueError('content_coding {} not supported in write_to_f... | <|body_start_0|>
out = io.BytesIO()
with gzip.GzipFile(fileobj=out, mode='w') as fo:
fo.write(_str.encode())
bytes_obj = out.getvalue()
return bytes_obj
<|end_body_0|>
<|body_start_1|>
tf.logging.info('Writing file: {}'.format(file_path))
if content_encoding ... | Definition of data utility functions | DataUtils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataUtils:
"""Definition of data utility functions"""
def gzip_str(_str: str) -> bytes:
"""Encode string to compressed bytes Arguments: _str {str} -- string to be compressed Returns: bytes -- compressed bytes"""
<|body_0|>
def write_to_file(self, str_content: str, file_p... | stack_v2_sparse_classes_36k_train_012553 | 2,331 | permissive | [
{
"docstring": "Encode string to compressed bytes Arguments: _str {str} -- string to be compressed Returns: bytes -- compressed bytes",
"name": "gzip_str",
"signature": "def gzip_str(_str: str) -> bytes"
},
{
"docstring": "Write string to a (compressed) file Arguments: str_content {str} -- strin... | 3 | stack_v2_sparse_classes_30k_train_005377 | Implement the Python class `DataUtils` described below.
Class description:
Definition of data utility functions
Method signatures and docstrings:
- def gzip_str(_str: str) -> bytes: Encode string to compressed bytes Arguments: _str {str} -- string to be compressed Returns: bytes -- compressed bytes
- def write_to_fil... | Implement the Python class `DataUtils` described below.
Class description:
Definition of data utility functions
Method signatures and docstrings:
- def gzip_str(_str: str) -> bytes: Encode string to compressed bytes Arguments: _str {str} -- string to be compressed Returns: bytes -- compressed bytes
- def write_to_fil... | baa6689a6344f417758d4d8b4e6c6e966a510b32 | <|skeleton|>
class DataUtils:
"""Definition of data utility functions"""
def gzip_str(_str: str) -> bytes:
"""Encode string to compressed bytes Arguments: _str {str} -- string to be compressed Returns: bytes -- compressed bytes"""
<|body_0|>
def write_to_file(self, str_content: str, file_p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataUtils:
"""Definition of data utility functions"""
def gzip_str(_str: str) -> bytes:
"""Encode string to compressed bytes Arguments: _str {str} -- string to be compressed Returns: bytes -- compressed bytes"""
out = io.BytesIO()
with gzip.GzipFile(fileobj=out, mode='w') as fo:
... | the_stack_v2_python_sparse | lib/data_utils.py | tmaone/s3vdc | train | 0 |
ce0051d6d7d1be360862cda89b738f7f972c66a6 | [
"widget = self._widget\nif not widget:\n return self._default_size\nreturn widget.GetMaxSize()",
"if self._widget is not widget:\n self.Clear(deleteWindows=False)\n old = self._widget\n if old:\n old.Hide()\n self._widget = widget\n if widget:\n widget.Show()\n res = super(w... | <|body_start_0|>
widget = self._widget
if not widget:
return self._default_size
return widget.GetMaxSize()
<|end_body_0|>
<|body_start_1|>
if self._widget is not widget:
self.Clear(deleteWindows=False)
old = self._widget
if old:
... | A custom wx Sizer for sizing a single child widget. There can only be one widget in this sizer at a time and it should be added via the .Add(...) method. Old items will be removed automatically (but not destroyed). | wxSingleWidgetSizer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class wxSingleWidgetSizer:
"""A custom wx Sizer for sizing a single child widget. There can only be one widget in this sizer at a time and it should be added via the .Add(...) method. Old items will be removed automatically (but not destroyed)."""
def CalcMax(self):
"""A method to compute ... | stack_v2_sparse_classes_36k_train_012554 | 2,025 | permissive | [
{
"docstring": "A method to compute the maximum size allowed by the sizer. This is not a native wx sizer method, but is included for convenience.",
"name": "CalcMax",
"signature": "def CalcMax(self)"
},
{
"docstring": "Adds the given widget to the sizer, removing the old widget if present. The o... | 4 | null | Implement the Python class `wxSingleWidgetSizer` described below.
Class description:
A custom wx Sizer for sizing a single child widget. There can only be one widget in this sizer at a time and it should be added via the .Add(...) method. Old items will be removed automatically (but not destroyed).
Method signatures ... | Implement the Python class `wxSingleWidgetSizer` described below.
Class description:
A custom wx Sizer for sizing a single child widget. There can only be one widget in this sizer at a time and it should be added via the .Add(...) method. Old items will be removed automatically (but not destroyed).
Method signatures ... | 15c20b035a73187e8e66fa20a43c3a4372d008bd | <|skeleton|>
class wxSingleWidgetSizer:
"""A custom wx Sizer for sizing a single child widget. There can only be one widget in this sizer at a time and it should be added via the .Add(...) method. Old items will be removed automatically (but not destroyed)."""
def CalcMax(self):
"""A method to compute ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class wxSingleWidgetSizer:
"""A custom wx Sizer for sizing a single child widget. There can only be one widget in this sizer at a time and it should be added via the .Add(...) method. Old items will be removed automatically (but not destroyed)."""
def CalcMax(self):
"""A method to compute the maximum s... | the_stack_v2_python_sparse | enaml/wx/wx_single_widget_sizer.py | ContinuumIO/enaml | train | 2 |
201baff64043997c3684f8a68b37ce77190717e7 | [
"for i in orm.Item.objects.all():\n try:\n i.status.remove(orm.Status.objects.get(name='Usable'))\n i.save()\n except ObjectDoesNotExist:\n pass\ntry:\n orm.Status.delete(orm.Status.objects.get(name='Usable'))\nexcept ObjectDoesNotExist:\n pass",
"try:\n usable = orm.Status.obj... | <|body_start_0|>
for i in orm.Item.objects.all():
try:
i.status.remove(orm.Status.objects.get(name='Usable'))
i.save()
except ObjectDoesNotExist:
pass
try:
orm.Status.delete(orm.Status.objects.get(name='Usable'))
... | Migration | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Migration:
def forwards(self, orm):
"""Loop through all items and delete the Usable status At the end remove 'Usable' status from Status"""
<|body_0|>
def backwards(self, orm):
"""Add 'Usable' status to Status. Loop through all items and add the Usable status if not ... | stack_v2_sparse_classes_36k_train_012555 | 12,509 | permissive | [
{
"docstring": "Loop through all items and delete the Usable status At the end remove 'Usable' status from Status",
"name": "forwards",
"signature": "def forwards(self, orm)"
},
{
"docstring": "Add 'Usable' status to Status. Loop through all items and add the Usable status if not exist",
"na... | 2 | stack_v2_sparse_classes_30k_train_018437 | Implement the Python class `Migration` described below.
Class description:
Implement the Migration class.
Method signatures and docstrings:
- def forwards(self, orm): Loop through all items and delete the Usable status At the end remove 'Usable' status from Status
- def backwards(self, orm): Add 'Usable' status to St... | Implement the Python class `Migration` described below.
Class description:
Implement the Migration class.
Method signatures and docstrings:
- def forwards(self, orm): Loop through all items and delete the Usable status At the end remove 'Usable' status from Status
- def backwards(self, orm): Add 'Usable' status to St... | 7096ff360a6161118bb454b2874318eade69c6df | <|skeleton|>
class Migration:
def forwards(self, orm):
"""Loop through all items and delete the Usable status At the end remove 'Usable' status from Status"""
<|body_0|>
def backwards(self, orm):
"""Add 'Usable' status to Status. Loop through all items and add the Usable status if not ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Migration:
def forwards(self, orm):
"""Loop through all items and delete the Usable status At the end remove 'Usable' status from Status"""
for i in orm.Item.objects.all():
try:
i.status.remove(orm.Status.objects.get(name='Usable'))
i.save()
... | the_stack_v2_python_sparse | Machine/migrations/0008_remove_usable_status.py | abztrakt/labtracker | train | 0 | |
9ecd0f30fa882e48d8ccf2fa684ec5047c70c450 | [
"super(GilbertElliott, self).__init__(PacketLoss.__name__)\nif prhk is None:\n p = float(GilbertElliott.__DEFAULT_P)\n r = float(GilbertElliott.__DEFAULT_R)\n b = float(1.0 - GilbertElliott.__DEFAULT_H)\n g = float(1.0 - GilbertElliott.__DEFAULT_K)\nelse:\n for param in range(4):\n check_argum... | <|body_start_0|>
super(GilbertElliott, self).__init__(PacketLoss.__name__)
if prhk is None:
p = float(GilbertElliott.__DEFAULT_P)
r = float(GilbertElliott.__DEFAULT_R)
b = float(1.0 - GilbertElliott.__DEFAULT_H)
g = float(1.0 - GilbertElliott.__DEFAULT_K)
... | This class implements the Gilbert-Elliott packet loss model. | GilbertElliott | [
"MIT",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GilbertElliott:
"""This class implements the Gilbert-Elliott packet loss model."""
def __init__(self, prhk=None):
"""*Parameters*: - **prhk** (`tuple`): a `tuple` that contains four model parameters: :math:`0\\leqslant p,r,h,k\\leqslant 1`, respectively (each of type `float`). The pa... | stack_v2_sparse_classes_36k_train_012556 | 6,499 | permissive | [
{
"docstring": "*Parameters*: - **prhk** (`tuple`): a `tuple` that contains four model parameters: :math:`0\\\\leqslant p,r,h,k\\\\leqslant 1`, respectively (each of type `float`). The parameters default to the following values: * :math:`p=0.00001333`, * :math:`r=0.00601795`, * :math:`h=0.55494900`, * :math:`k=... | 2 | stack_v2_sparse_classes_30k_train_003678 | Implement the Python class `GilbertElliott` described below.
Class description:
This class implements the Gilbert-Elliott packet loss model.
Method signatures and docstrings:
- def __init__(self, prhk=None): *Parameters*: - **prhk** (`tuple`): a `tuple` that contains four model parameters: :math:`0\\leqslant p,r,h,k\... | Implement the Python class `GilbertElliott` described below.
Class description:
This class implements the Gilbert-Elliott packet loss model.
Method signatures and docstrings:
- def __init__(self, prhk=None): *Parameters*: - **prhk** (`tuple`): a `tuple` that contains four model parameters: :math:`0\\leqslant p,r,h,k\... | ed93d1e3067c569dd4194658b0d02da6b0ab4bed | <|skeleton|>
class GilbertElliott:
"""This class implements the Gilbert-Elliott packet loss model."""
def __init__(self, prhk=None):
"""*Parameters*: - **prhk** (`tuple`): a `tuple` that contains four model parameters: :math:`0\\leqslant p,r,h,k\\leqslant 1`, respectively (each of type `float`). The pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GilbertElliott:
"""This class implements the Gilbert-Elliott packet loss model."""
def __init__(self, prhk=None):
"""*Parameters*: - **prhk** (`tuple`): a `tuple` that contains four model parameters: :math:`0\\leqslant p,r,h,k\\leqslant 1`, respectively (each of type `float`). The parameters defa... | the_stack_v2_python_sparse | sim2net/packet_loss/gilbert_elliott.py | mkalewski/sim2net | train | 14 |
bfda53fbb253e99a8aa1086af9e69c1c83720e8e | [
"def traverse_longest(row, col, prev_num):\n if not (0 <= row < m and 0 <= col < n):\n return 0\n current_num = matrix[row][col]\n if current_num <= prev_num:\n return 0\n up = traverse_longest(row - 1, col, current_num)\n down = traverse_longest(row + 1, col, current_num)\n left = t... | <|body_start_0|>
def traverse_longest(row, col, prev_num):
if not (0 <= row < m and 0 <= col < n):
return 0
current_num = matrix[row][col]
if current_num <= prev_num:
return 0
up = traverse_longest(row - 1, col, current_num)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestIncreasingPath(self, matrix: list[list[int]]) -> int:
"""DFS"""
<|body_0|>
def longestIncreasingPath(self, matrix: List[List[int]]) -> int:
"""memoization"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def traverse_longest(row,... | stack_v2_sparse_classes_36k_train_012557 | 1,958 | no_license | [
{
"docstring": "DFS",
"name": "longestIncreasingPath",
"signature": "def longestIncreasingPath(self, matrix: list[list[int]]) -> int"
},
{
"docstring": "memoization",
"name": "longestIncreasingPath",
"signature": "def longestIncreasingPath(self, matrix: List[List[int]]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_021196 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestIncreasingPath(self, matrix: list[list[int]]) -> int: DFS
- def longestIncreasingPath(self, matrix: List[List[int]]) -> int: memoization | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestIncreasingPath(self, matrix: list[list[int]]) -> int: DFS
- def longestIncreasingPath(self, matrix: List[List[int]]) -> int: memoization
<|skeleton|>
class Solution:
... | e50dc0642f087f37ab3234390be3d8a0ed48fe62 | <|skeleton|>
class Solution:
def longestIncreasingPath(self, matrix: list[list[int]]) -> int:
"""DFS"""
<|body_0|>
def longestIncreasingPath(self, matrix: List[List[int]]) -> int:
"""memoization"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestIncreasingPath(self, matrix: list[list[int]]) -> int:
"""DFS"""
def traverse_longest(row, col, prev_num):
if not (0 <= row < m and 0 <= col < n):
return 0
current_num = matrix[row][col]
if current_num <= prev_num:
... | the_stack_v2_python_sparse | Leetcode/329. Longest Increasing Path in a Matrix.py | brlala/Educative-Grokking-Coding-Exercise | train | 3 | |
0db12b209c223fd9f22bf09d9ba9a6d0971f6016 | [
"self.days = days\nself.end_time = end_time\nself.is_all_day = is_all_day\nself.start_time = start_time",
"if dictionary is None:\n return None\ndays = dictionary.get('days')\nend_time = cohesity_management_sdk.models.time_of_day.TimeOfDay.from_dictionary(dictionary.get('endTime')) if dictionary.get('endTime')... | <|body_start_0|>
self.days = days
self.end_time = end_time
self.is_all_day = is_all_day
self.start_time = start_time
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
days = dictionary.get('days')
end_time = cohesity_management_sdk.mo... | Implementation of the 'TimeOfAWeek' model. Specifies a time period by specifying a single daily time period and one or more days of the week, for example 9 AM - 5 PM on Monday, Wednesday or Friday. If different time periods are required on different days, then multiple instances of this Weekly Time Period must be speci... | TimeOfAWeek | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeOfAWeek:
"""Implementation of the 'TimeOfAWeek' model. Specifies a time period by specifying a single daily time period and one or more days of the week, for example 9 AM - 5 PM on Monday, Wednesday or Friday. If different time periods are required on different days, then multiple instances o... | stack_v2_sparse_classes_36k_train_012558 | 2,834 | permissive | [
{
"docstring": "Constructor for the TimeOfAWeek class",
"name": "__init__",
"signature": "def __init__(self, days=None, end_time=None, is_all_day=None, start_time=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representat... | 2 | stack_v2_sparse_classes_30k_train_002807 | Implement the Python class `TimeOfAWeek` described below.
Class description:
Implementation of the 'TimeOfAWeek' model. Specifies a time period by specifying a single daily time period and one or more days of the week, for example 9 AM - 5 PM on Monday, Wednesday or Friday. If different time periods are required on di... | Implement the Python class `TimeOfAWeek` described below.
Class description:
Implementation of the 'TimeOfAWeek' model. Specifies a time period by specifying a single daily time period and one or more days of the week, for example 9 AM - 5 PM on Monday, Wednesday or Friday. If different time periods are required on di... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class TimeOfAWeek:
"""Implementation of the 'TimeOfAWeek' model. Specifies a time period by specifying a single daily time period and one or more days of the week, for example 9 AM - 5 PM on Monday, Wednesday or Friday. If different time periods are required on different days, then multiple instances o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimeOfAWeek:
"""Implementation of the 'TimeOfAWeek' model. Specifies a time period by specifying a single daily time period and one or more days of the week, for example 9 AM - 5 PM on Monday, Wednesday or Friday. If different time periods are required on different days, then multiple instances of this Weekly... | the_stack_v2_python_sparse | cohesity_management_sdk/models/time_of_a_week.py | cohesity/management-sdk-python | train | 24 |
b2cdd5f1a09aa4ef54d733b74cc4eed06b3835e1 | [
"s = sessionmanage(self.driver)\ns.open_sessionmanage()\nself.assertEqual(s.verify(), True)\ns.check()\nself.assertEqual(s.reason(), '请选择一条数据')\nfunction.screenshot(self.driver, 'session_unselect.jpg')",
"s = sessionmanage(self.driver)\ns.open_sessionmanage()\nself.assertEqual(s.verify(), True)\ns.multi_select()\... | <|body_start_0|>
s = sessionmanage(self.driver)
s.open_sessionmanage()
self.assertEqual(s.verify(), True)
s.check()
self.assertEqual(s.reason(), '请选择一条数据')
function.screenshot(self.driver, 'session_unselect.jpg')
<|end_body_0|>
<|body_start_1|>
s = sessionmanage(... | Test049_Session_List_Error | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test049_Session_List_Error:
def test_unselect(self):
"""不选择任何会话"""
<|body_0|>
def test_multiselect(self):
"""选择两条会话"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s = sessionmanage(self.driver)
s.open_sessionmanage()
self.assertEqua... | stack_v2_sparse_classes_36k_train_012559 | 939 | no_license | [
{
"docstring": "不选择任何会话",
"name": "test_unselect",
"signature": "def test_unselect(self)"
},
{
"docstring": "选择两条会话",
"name": "test_multiselect",
"signature": "def test_multiselect(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000044 | Implement the Python class `Test049_Session_List_Error` described below.
Class description:
Implement the Test049_Session_List_Error class.
Method signatures and docstrings:
- def test_unselect(self): 不选择任何会话
- def test_multiselect(self): 选择两条会话 | Implement the Python class `Test049_Session_List_Error` described below.
Class description:
Implement the Test049_Session_List_Error class.
Method signatures and docstrings:
- def test_unselect(self): 不选择任何会话
- def test_multiselect(self): 选择两条会话
<|skeleton|>
class Test049_Session_List_Error:
def test_unselect(s... | 6f42c25249fc642cecc270578a180820988d45b5 | <|skeleton|>
class Test049_Session_List_Error:
def test_unselect(self):
"""不选择任何会话"""
<|body_0|>
def test_multiselect(self):
"""选择两条会话"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test049_Session_List_Error:
def test_unselect(self):
"""不选择任何会话"""
s = sessionmanage(self.driver)
s.open_sessionmanage()
self.assertEqual(s.verify(), True)
s.check()
self.assertEqual(s.reason(), '请选择一条数据')
function.screenshot(self.driver, 'session_unsele... | the_stack_v2_python_sparse | GlxssLive_web/TestCase/Manage_Session/Test049_session_list_error.py | rrmiracle/GlxssLive | train | 0 | |
91d49558ef3d3d5b8092493a8a375b3df14f9147 | [
"new_dtype = src_array.dtype.descr + [dtype]\nnew_array = np.array([list(x) for x in src_array])\nadd = []\nfor i in add_row:\n add.append([i])\nnew_array = np.append(new_array, add, 1)\nnew_array = np.array([tuple(x) for x in new_array], dtype=new_dtype)\nreturn new_array",
"new_dtype = []\nfor key, dtype in ... | <|body_start_0|>
new_dtype = src_array.dtype.descr + [dtype]
new_array = np.array([list(x) for x in src_array])
add = []
for i in add_row:
add.append([i])
new_array = np.append(new_array, add, 1)
new_array = np.array([tuple(x) for x in new_array], dtype=new_dt... | numpy array関連 | Array | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Array:
"""numpy array関連"""
def add_data(src_array, add_row, dtype):
"""ラベル付きarrayに新しい一次元dataを加える⇒commopy行き??"""
<|body_0|>
def extract(src_array, *labels):
"""labelsのデータのみを抽出してarrayをreturn"""
<|body_1|>
def trim(array, label, value):
"""label... | stack_v2_sparse_classes_36k_train_012560 | 17,123 | no_license | [
{
"docstring": "ラベル付きarrayに新しい一次元dataを加える⇒commopy行き??",
"name": "add_data",
"signature": "def add_data(src_array, add_row, dtype)"
},
{
"docstring": "labelsのデータのみを抽出してarrayをreturn",
"name": "extract",
"signature": "def extract(src_array, *labels)"
},
{
"docstring": "labelsのデータがva... | 6 | stack_v2_sparse_classes_30k_val_000630 | Implement the Python class `Array` described below.
Class description:
numpy array関連
Method signatures and docstrings:
- def add_data(src_array, add_row, dtype): ラベル付きarrayに新しい一次元dataを加える⇒commopy行き??
- def extract(src_array, *labels): labelsのデータのみを抽出してarrayをreturn
- def trim(array, label, value): labelsのデータがvalueと等しい... | Implement the Python class `Array` described below.
Class description:
numpy array関連
Method signatures and docstrings:
- def add_data(src_array, add_row, dtype): ラベル付きarrayに新しい一次元dataを加える⇒commopy行き??
- def extract(src_array, *labels): labelsのデータのみを抽出してarrayをreturn
- def trim(array, label, value): labelsのデータがvalueと等しい... | d210cf6f8fb370ff6deecc949c7dcb3df653d1ca | <|skeleton|>
class Array:
"""numpy array関連"""
def add_data(src_array, add_row, dtype):
"""ラベル付きarrayに新しい一次元dataを加える⇒commopy行き??"""
<|body_0|>
def extract(src_array, *labels):
"""labelsのデータのみを抽出してarrayをreturn"""
<|body_1|>
def trim(array, label, value):
"""label... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Array:
"""numpy array関連"""
def add_data(src_array, add_row, dtype):
"""ラベル付きarrayに新しい一次元dataを加える⇒commopy行き??"""
new_dtype = src_array.dtype.descr + [dtype]
new_array = np.array([list(x) for x in src_array])
add = []
for i in add_row:
add.append([i])
... | the_stack_v2_python_sparse | module/commopy.py | buriedwood/00_workSpace | train | 0 |
8b59d4d402404d30eb3b476e64efde8f3277f06b | [
"cookies = []\nfor pairs in split_header(string):\n for name, value in pairs:\n if name.startswith('$'):\n continue\n cookies.append(self.new(name=name, value=notnone(value, '')))\nreturn cookies",
"name = str(notnone(self.name, ''))\nif not name:\n return ''\nvalue = str(notnone(se... | <|body_start_0|>
cookies = []
for pairs in split_header(string):
for name, value in pairs:
if name.startswith('$'):
continue
cookies.append(self.new(name=name, value=notnone(value, '')))
return cookies
<|end_body_0|>
<|body_start_1... | :mod:`Pyjo.Cookie.Request` inherits all attributes and methods from :mod:`Pyjo.Cookie` and implements the following new ones. | Pyjo_Cookie_Request | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pyjo_Cookie_Request:
""":mod:`Pyjo.Cookie.Request` inherits all attributes and methods from :mod:`Pyjo.Cookie` and implements the following new ones."""
def parse(self, string=''):
""":: cookies = Pyjo.Cookie.Request.parse('f=b; g=a') Parse cookies."""
<|body_0|>
def to_... | stack_v2_sparse_classes_36k_train_012561 | 1,565 | no_license | [
{
"docstring": ":: cookies = Pyjo.Cookie.Request.parse('f=b; g=a') Parse cookies.",
"name": "parse",
"signature": "def parse(self, string='')"
},
{
"docstring": ":: string = cookie.to_str() Render cookie.",
"name": "to_str",
"signature": "def to_str(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016594 | Implement the Python class `Pyjo_Cookie_Request` described below.
Class description:
:mod:`Pyjo.Cookie.Request` inherits all attributes and methods from :mod:`Pyjo.Cookie` and implements the following new ones.
Method signatures and docstrings:
- def parse(self, string=''): :: cookies = Pyjo.Cookie.Request.parse('f=b... | Implement the Python class `Pyjo_Cookie_Request` described below.
Class description:
:mod:`Pyjo.Cookie.Request` inherits all attributes and methods from :mod:`Pyjo.Cookie` and implements the following new ones.
Method signatures and docstrings:
- def parse(self, string=''): :: cookies = Pyjo.Cookie.Request.parse('f=b... | 31197cd2765d12fdf0d508bc0981743e5fb58e87 | <|skeleton|>
class Pyjo_Cookie_Request:
""":mod:`Pyjo.Cookie.Request` inherits all attributes and methods from :mod:`Pyjo.Cookie` and implements the following new ones."""
def parse(self, string=''):
""":: cookies = Pyjo.Cookie.Request.parse('f=b; g=a') Parse cookies."""
<|body_0|>
def to_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Pyjo_Cookie_Request:
""":mod:`Pyjo.Cookie.Request` inherits all attributes and methods from :mod:`Pyjo.Cookie` and implements the following new ones."""
def parse(self, string=''):
""":: cookies = Pyjo.Cookie.Request.parse('f=b; g=a') Parse cookies."""
cookies = []
for pairs in sp... | the_stack_v2_python_sparse | Pyjo/Cookie/Request.py | dex4er/Pyjoyment | train | 0 |
8b45521141ccdbb54aff80605ac945d79988821a | [
"logger.info('Check 角色管理 begin')\nAPI().assertElementByName(self.testcase, self.driver, self.logger, Name.role_management)\nlogger.info('Check 角色管理 end')",
"logger.info('Check 角色列表 begin')\nname = API().getTextByXpath(self.testcase, self.driver, self.logger, Xpath.role_management_name)\ncreator = API().getTextByX... | <|body_start_0|>
logger.info('Check 角色管理 begin')
API().assertElementByName(self.testcase, self.driver, self.logger, Name.role_management)
logger.info('Check 角色管理 end')
<|end_body_0|>
<|body_start_1|>
logger.info('Check 角色列表 begin')
name = API().getTextByXpath(self.testcase, self... | RoleManagementPage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoleManagementPage:
def validSelf(self):
"""验证角色列表页面 :return:"""
<|body_0|>
def checkRoleList(self):
"""检查角色列表是否为空 :return:"""
<|body_1|>
def clickOnNewRoleButton(self):
"""点击新建角色按钮 :return:"""
<|body_2|>
def validNewRolePage(self):
... | stack_v2_sparse_classes_36k_train_012562 | 4,182 | no_license | [
{
"docstring": "验证角色列表页面 :return:",
"name": "validSelf",
"signature": "def validSelf(self)"
},
{
"docstring": "检查角色列表是否为空 :return:",
"name": "checkRoleList",
"signature": "def checkRoleList(self)"
},
{
"docstring": "点击新建角色按钮 :return:",
"name": "clickOnNewRoleButton",
"sig... | 5 | stack_v2_sparse_classes_30k_train_011075 | Implement the Python class `RoleManagementPage` described below.
Class description:
Implement the RoleManagementPage class.
Method signatures and docstrings:
- def validSelf(self): 验证角色列表页面 :return:
- def checkRoleList(self): 检查角色列表是否为空 :return:
- def clickOnNewRoleButton(self): 点击新建角色按钮 :return:
- def validNewRolePa... | Implement the Python class `RoleManagementPage` described below.
Class description:
Implement the RoleManagementPage class.
Method signatures and docstrings:
- def validSelf(self): 验证角色列表页面 :return:
- def checkRoleList(self): 检查角色列表是否为空 :return:
- def clickOnNewRoleButton(self): 点击新建角色按钮 :return:
- def validNewRolePa... | 67e2acc9a99da81022e286e8d8ec7ccb12636ff3 | <|skeleton|>
class RoleManagementPage:
def validSelf(self):
"""验证角色列表页面 :return:"""
<|body_0|>
def checkRoleList(self):
"""检查角色列表是否为空 :return:"""
<|body_1|>
def clickOnNewRoleButton(self):
"""点击新建角色按钮 :return:"""
<|body_2|>
def validNewRolePage(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoleManagementPage:
def validSelf(self):
"""验证角色列表页面 :return:"""
logger.info('Check 角色管理 begin')
API().assertElementByName(self.testcase, self.driver, self.logger, Name.role_management)
logger.info('Check 角色管理 end')
def checkRoleList(self):
"""检查角色列表是否为空 :return:""... | the_stack_v2_python_sparse | pages/ios/shanghu/roleManagementPage.py | liu111xiao111/UItest | train | 1 | |
91bd2fc96977683de140f76944af0733510f0a17 | [
"super().__init__()\nself.gmm_size = gmm_size\nself.sample_size = sample_size\nself.input_slice = input_slice\nself.target_slice = target_slice\nself.stdout = stdout\nself.save_plots = save_plots\nos.makedirs(plot_dir, exist_ok=True)\nself.plot_dir = plot_dir",
"random.seed(datetime.now())\nsample_indexes = rando... | <|body_start_0|>
super().__init__()
self.gmm_size = gmm_size
self.sample_size = sample_size
self.input_slice = input_slice
self.target_slice = target_slice
self.stdout = stdout
self.save_plots = save_plots
os.makedirs(plot_dir, exist_ok=True)
self.... | DecypherAll | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecypherAll:
def __init__(self, gmm_size=1, sample_size=3, input_slice=lambda x: x[0:1], target_slice=lambda x: x[1:2], stdout=False, save_plots=True, plot_dir='plots'):
"""Class constructor that instantiates with a few vital settings in order to decypher the output :type target_slice: o... | stack_v2_sparse_classes_36k_train_012563 | 3,310 | permissive | [
{
"docstring": "Class constructor that instantiates with a few vital settings in order to decypher the output :type target_slice: object :param gmm_size: size as an integer of the gaussian mixture model :param sample_size: size as an integer of the number of samples to log :param stdout: boolean whether or not ... | 2 | stack_v2_sparse_classes_30k_train_012436 | Implement the Python class `DecypherAll` described below.
Class description:
Implement the DecypherAll class.
Method signatures and docstrings:
- def __init__(self, gmm_size=1, sample_size=3, input_slice=lambda x: x[0:1], target_slice=lambda x: x[1:2], stdout=False, save_plots=True, plot_dir='plots'): Class construct... | Implement the Python class `DecypherAll` described below.
Class description:
Implement the DecypherAll class.
Method signatures and docstrings:
- def __init__(self, gmm_size=1, sample_size=3, input_slice=lambda x: x[0:1], target_slice=lambda x: x[1:2], stdout=False, save_plots=True, plot_dir='plots'): Class construct... | 6ade84c0ac1197b21d189f905ec559505ca15159 | <|skeleton|>
class DecypherAll:
def __init__(self, gmm_size=1, sample_size=3, input_slice=lambda x: x[0:1], target_slice=lambda x: x[1:2], stdout=False, save_plots=True, plot_dir='plots'):
"""Class constructor that instantiates with a few vital settings in order to decypher the output :type target_slice: o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecypherAll:
def __init__(self, gmm_size=1, sample_size=3, input_slice=lambda x: x[0:1], target_slice=lambda x: x[1:2], stdout=False, save_plots=True, plot_dir='plots'):
"""Class constructor that instantiates with a few vital settings in order to decypher the output :type target_slice: object :param g... | the_stack_v2_python_sparse | model/topoml_util/PyplotLogger.py | Empythy/geometry-learning | train | 0 | |
fd370e017757197189a3d98a241114b6c8ffc0c0 | [
"super(Critic, self).__init__()\nself.state_size = state_size\nself.action_size = action_size\nself.linear1 = nn.Linear(self.state_size + self.action_size, 128)\nself.linear2 = nn.Linear(128, 256)\nself.linear3 = nn.Linear(256, 1)\nself.relu = nn.ReLU()\nself.weight_init()",
"model_input = torch.cat([state, actio... | <|body_start_0|>
super(Critic, self).__init__()
self.state_size = state_size
self.action_size = action_size
self.linear1 = nn.Linear(self.state_size + self.action_size, 128)
self.linear2 = nn.Linear(128, 256)
self.linear3 = nn.Linear(256, 1)
self.relu = nn.ReLU()
... | Critic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Critic:
def __init__(self, state_size, action_size):
"""init function Args: - state_size: int - action_size: int"""
<|body_0|>
def forward(self, state, action):
"""forward function Args: - state: torch.FloatTensor, shape==[batch_size, state_size] - action: torch.Floa... | stack_v2_sparse_classes_36k_train_012564 | 2,778 | no_license | [
{
"docstring": "init function Args: - state_size: int - action_size: int",
"name": "__init__",
"signature": "def __init__(self, state_size, action_size)"
},
{
"docstring": "forward function Args: - state: torch.FloatTensor, shape==[batch_size, state_size] - action: torch.FloatTensor, shape==[bat... | 3 | stack_v2_sparse_classes_30k_val_000475 | Implement the Python class `Critic` described below.
Class description:
Implement the Critic class.
Method signatures and docstrings:
- def __init__(self, state_size, action_size): init function Args: - state_size: int - action_size: int
- def forward(self, state, action): forward function Args: - state: torch.FloatT... | Implement the Python class `Critic` described below.
Class description:
Implement the Critic class.
Method signatures and docstrings:
- def __init__(self, state_size, action_size): init function Args: - state_size: int - action_size: int
- def forward(self, state, action): forward function Args: - state: torch.FloatT... | 2c622764bc1197e0ec5b1b3c30a9d12611b25738 | <|skeleton|>
class Critic:
def __init__(self, state_size, action_size):
"""init function Args: - state_size: int - action_size: int"""
<|body_0|>
def forward(self, state, action):
"""forward function Args: - state: torch.FloatTensor, shape==[batch_size, state_size] - action: torch.Floa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Critic:
def __init__(self, state_size, action_size):
"""init function Args: - state_size: int - action_size: int"""
super(Critic, self).__init__()
self.state_size = state_size
self.action_size = action_size
self.linear1 = nn.Linear(self.state_size + self.action_size, 12... | the_stack_v2_python_sparse | DDPG/model.py | keiiti975/RL_sample | train | 0 | |
bf373e2ca5851e71b9eb14437d6ef66fab794c53 | [
"MAX_INT = pow(2, 31)\nrev = 0\nt = x\nwhile t != 0:\n rev = rev * 10 + t % 10\n if rev > MAX_INT:\n return 0\n t = t // 10\nreturn rev",
"if x < 0:\n return False\nxrev = self.reverse(x)\nif x == xrev:\n return True\nelse:\n return False"
] | <|body_start_0|>
MAX_INT = pow(2, 31)
rev = 0
t = x
while t != 0:
rev = rev * 10 + t % 10
if rev > MAX_INT:
return 0
t = t // 10
return rev
<|end_body_0|>
<|body_start_1|>
if x < 0:
return False
xrev... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
MAX_INT = pow(2, 31)
rev = 0
t = x
while t != 0... | stack_v2_sparse_classes_36k_train_012565 | 1,171 | no_license | [
{
"docstring": ":type x: int :rtype: int",
"name": "reverse",
"signature": "def reverse(self, x)"
},
{
"docstring": ":type x: int :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000281 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x): :type x: int :rtype: int
- def isPalindrome(self, x): :type x: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x): :type x: int :rtype: int
- def isPalindrome(self, x): :type x: int :rtype: bool
<|skeleton|>
class Solution:
def reverse(self, x):
""":type x:... | 0901a144f2ea058523a8e45ffc9af4648163b0e4 | <|skeleton|>
class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
MAX_INT = pow(2, 31)
rev = 0
t = x
while t != 0:
rev = rev * 10 + t % 10
if rev > MAX_INT:
return 0
t = t // 10
return rev
def isPalindrome(se... | the_stack_v2_python_sparse | _9-PalindromeNumber/PalindromeNumber2.py | q1003722295/WeonLeetcode | train | 1 | |
b956596338ec082f9ab18daa3abece65b6978826 | [
"if self.context['user'].email == value:\n raise serializers.ValidationError(\"You can't add yourself to the company\")\nreturn value",
"if str(value) not in roles:\n raise serializers.ValidationError({'role': 'Role {} does not exist'.format(value)})\nreturn value"
] | <|body_start_0|>
if self.context['user'].email == value:
raise serializers.ValidationError("You can't add yourself to the company")
return value
<|end_body_0|>
<|body_start_1|>
if str(value) not in roles:
raise serializers.ValidationError({'role': 'Role {} does not exist... | Serializer params class. | EmployeeParamsSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmployeeParamsSerializer:
"""Serializer params class."""
def validate_email(self, value):
"""Employee parameter validation."""
<|body_0|>
def validate_role(self, value):
"""Employee role validation."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_012566 | 3,659 | no_license | [
{
"docstring": "Employee parameter validation.",
"name": "validate_email",
"signature": "def validate_email(self, value)"
},
{
"docstring": "Employee role validation.",
"name": "validate_role",
"signature": "def validate_role(self, value)"
}
] | 2 | null | Implement the Python class `EmployeeParamsSerializer` described below.
Class description:
Serializer params class.
Method signatures and docstrings:
- def validate_email(self, value): Employee parameter validation.
- def validate_role(self, value): Employee role validation. | Implement the Python class `EmployeeParamsSerializer` described below.
Class description:
Serializer params class.
Method signatures and docstrings:
- def validate_email(self, value): Employee parameter validation.
- def validate_role(self, value): Employee role validation.
<|skeleton|>
class EmployeeParamsSerialize... | 252b0ebd77eefbcc945a0efc3068cc3421f46d5f | <|skeleton|>
class EmployeeParamsSerializer:
"""Serializer params class."""
def validate_email(self, value):
"""Employee parameter validation."""
<|body_0|>
def validate_role(self, value):
"""Employee role validation."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmployeeParamsSerializer:
"""Serializer params class."""
def validate_email(self, value):
"""Employee parameter validation."""
if self.context['user'].email == value:
raise serializers.ValidationError("You can't add yourself to the company")
return value
def valid... | the_stack_v2_python_sparse | app/companies/serializers/employees_serializer.py | vsokoltsov/Interview360Server | train | 2 |
eb3d706448ad8185b656449b7fd56946ce62a17b | [
"self.is_valid = True\npsp = {}\nfor skey in self.SPECS:\n psp[skey] = ''\nfor field in input_fields:\n key, value = re.split(':', field)\n psp[key.upper()] = value\nself.psp = psp",
"for skey in self.SPECS:\n if self.psp[skey] == '' and skey != 'CID':\n return False\nreturn True",
"for skey ... | <|body_start_0|>
self.is_valid = True
psp = {}
for skey in self.SPECS:
psp[skey] = ''
for field in input_fields:
key, value = re.split(':', field)
psp[key.upper()] = value
self.psp = psp
<|end_body_0|>
<|body_start_1|>
for skey in self... | Validates passport based on the required fields. Input fields: byr (Birth Year) - four digits; at least 1920 and at most 2002. iyr (Issue Year) - four digits; at least 2010 and at most 2020. eyr (Expiration Year) - four digits; at least 2020 and at most 2030. hgt (Height) - a number followed by either cm or in: If cm, ... | PassportValidator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PassportValidator:
"""Validates passport based on the required fields. Input fields: byr (Birth Year) - four digits; at least 1920 and at most 2002. iyr (Issue Year) - four digits; at least 2010 and at most 2020. eyr (Expiration Year) - four digits; at least 2020 and at most 2030. hgt (Height) - ... | stack_v2_sparse_classes_36k_train_012567 | 3,972 | no_license | [
{
"docstring": "Args: input_fields (list): All available input fields.",
"name": "__init__",
"signature": "def __init__(self, input_fields)"
},
{
"docstring": "Validate passport entries. Args: Returns: bool: Valid or not.",
"name": "validate_4a",
"signature": "def validate_4a(self)"
},... | 3 | stack_v2_sparse_classes_30k_train_017649 | Implement the Python class `PassportValidator` described below.
Class description:
Validates passport based on the required fields. Input fields: byr (Birth Year) - four digits; at least 1920 and at most 2002. iyr (Issue Year) - four digits; at least 2010 and at most 2020. eyr (Expiration Year) - four digits; at least... | Implement the Python class `PassportValidator` described below.
Class description:
Validates passport based on the required fields. Input fields: byr (Birth Year) - four digits; at least 1920 and at most 2002. iyr (Issue Year) - four digits; at least 2010 and at most 2020. eyr (Expiration Year) - four digits; at least... | 7c2a69f2ea5fe8b6b9d73e31ba394798fce60217 | <|skeleton|>
class PassportValidator:
"""Validates passport based on the required fields. Input fields: byr (Birth Year) - four digits; at least 1920 and at most 2002. iyr (Issue Year) - four digits; at least 2010 and at most 2020. eyr (Expiration Year) - four digits; at least 2020 and at most 2030. hgt (Height) - ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PassportValidator:
"""Validates passport based on the required fields. Input fields: byr (Birth Year) - four digits; at least 1920 and at most 2002. iyr (Issue Year) - four digits; at least 2010 and at most 2020. eyr (Expiration Year) - four digits; at least 2020 and at most 2030. hgt (Height) - a number foll... | the_stack_v2_python_sparse | 2020/d04.py | hchkrdtn/advent-of-code | train | 0 |
2cee45fee9f5157adcc3d25658527508e0281eb5 | [
"next_service_obj = self.env['next.service.days']\nservice_obj = self.env['fleet.vehicle.log.services']\nincre_obj = self.env['next.increment.number']\nservice_active_id = service_obj.browse(self._context['active_id'])\nnext_service_obj.create({'vehicle_id': self.vehicle_id and self.vehicle_id.id or False, 'days': ... | <|body_start_0|>
next_service_obj = self.env['next.service.days']
service_obj = self.env['fleet.vehicle.log.services']
incre_obj = self.env['next.increment.number']
service_active_id = service_obj.browse(self._context['active_id'])
next_service_obj.create({'vehicle_id': self.vehi... | Added Next Service and Odometer Increment. | UpdateNextServiceConfig | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNextServiceConfig:
"""Added Next Service and Odometer Increment."""
def action_done(self):
"""Method to set Next Service Day and Odometer Increment."""
<|body_0|>
def default_get(self, default_fields):
"""Method is used to set Vehicle Id."""
<|body_... | stack_v2_sparse_classes_36k_train_012568 | 1,726 | no_license | [
{
"docstring": "Method to set Next Service Day and Odometer Increment.",
"name": "action_done",
"signature": "def action_done(self)"
},
{
"docstring": "Method is used to set Vehicle Id.",
"name": "default_get",
"signature": "def default_get(self, default_fields)"
}
] | 2 | null | Implement the Python class `UpdateNextServiceConfig` described below.
Class description:
Added Next Service and Odometer Increment.
Method signatures and docstrings:
- def action_done(self): Method to set Next Service Day and Odometer Increment.
- def default_get(self, default_fields): Method is used to set Vehicle I... | Implement the Python class `UpdateNextServiceConfig` described below.
Class description:
Added Next Service and Odometer Increment.
Method signatures and docstrings:
- def action_done(self): Method to set Next Service Day and Odometer Increment.
- def default_get(self, default_fields): Method is used to set Vehicle I... | 7618a365ac78c0f59390a3a6b5fcdd9f76a5ddec | <|skeleton|>
class UpdateNextServiceConfig:
"""Added Next Service and Odometer Increment."""
def action_done(self):
"""Method to set Next Service Day and Odometer Increment."""
<|body_0|>
def default_get(self, default_fields):
"""Method is used to set Vehicle Id."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateNextServiceConfig:
"""Added Next Service and Odometer Increment."""
def action_done(self):
"""Method to set Next Service Day and Odometer Increment."""
next_service_obj = self.env['next.service.days']
service_obj = self.env['fleet.vehicle.log.services']
incre_obj = s... | the_stack_v2_python_sparse | fleet_operations/wizard/update_next_service.py | JayVora-SerpentCS/fleet_management | train | 29 |
59f807542b550a07d64ae0ac56cfc8b5e9582621 | [
"if value is None or self.MIN_PRIORITY <= value <= self.MAX_PRIORITY:\n return value\nerr_args = (key, self.MIN_PRIORITY, self.MAX_PRIORITY, value)\nraise ValueError('%s must be between %s and %s, got %s instead' % err_args)",
"if value is None or value >= 0:\n return value\nraise ValueError('%s cannot be l... | <|body_start_0|>
if value is None or self.MIN_PRIORITY <= value <= self.MAX_PRIORITY:
return value
err_args = (key, self.MIN_PRIORITY, self.MAX_PRIORITY, value)
raise ValueError('%s must be between %s and %s, got %s instead' % err_args)
<|end_body_0|>
<|body_start_1|>
if val... | Mixin that adds a `state` column and uses a class level `STATE_ENUM` attribute to assist in validation. | ValidatePriorityMixin | [
"BSD-3-Clause",
"Apache-2.0",
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidatePriorityMixin:
"""Mixin that adds a `state` column and uses a class level `STATE_ENUM` attribute to assist in validation."""
def validate_priority(self, key, value):
"""ensures the value provided to priority is valid"""
<|body_0|>
def validate_attempts(self, key,... | stack_v2_sparse_classes_36k_train_012569 | 16,227 | permissive | [
{
"docstring": "ensures the value provided to priority is valid",
"name": "validate_priority",
"signature": "def validate_priority(self, key, value)"
},
{
"docstring": "ensures the number of attempts provided is valid",
"name": "validate_attempts",
"signature": "def validate_attempts(sel... | 2 | stack_v2_sparse_classes_30k_train_009419 | Implement the Python class `ValidatePriorityMixin` described below.
Class description:
Mixin that adds a `state` column and uses a class level `STATE_ENUM` attribute to assist in validation.
Method signatures and docstrings:
- def validate_priority(self, key, value): ensures the value provided to priority is valid
- ... | Implement the Python class `ValidatePriorityMixin` described below.
Class description:
Mixin that adds a `state` column and uses a class level `STATE_ENUM` attribute to assist in validation.
Method signatures and docstrings:
- def validate_priority(self, key, value): ensures the value provided to priority is valid
- ... | ea04bbcb807eb669415c569417b4b1b68e75d29d | <|skeleton|>
class ValidatePriorityMixin:
"""Mixin that adds a `state` column and uses a class level `STATE_ENUM` attribute to assist in validation."""
def validate_priority(self, key, value):
"""ensures the value provided to priority is valid"""
<|body_0|>
def validate_attempts(self, key,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValidatePriorityMixin:
"""Mixin that adds a `state` column and uses a class level `STATE_ENUM` attribute to assist in validation."""
def validate_priority(self, key, value):
"""ensures the value provided to priority is valid"""
if value is None or self.MIN_PRIORITY <= value <= self.MAX_PR... | the_stack_v2_python_sparse | pyfarm/models/core/mixins.py | pyfarm/pyfarm-master | train | 2 |
1a695f96d59e0b7e5ece1c7563a7f2e76e5d647e | [
"phone = self.data.get('phone')\nif not re.match('^1[3-9]\\\\d{9}$', phone):\n raise forms.ValidationError(u'无效的手机号码')\nreturn phone",
"data = self.data\nphone = data.get('phone')\npassword = data.get('password')\nif password not in cache.get(u'pwds_{}'.format(phone), []):\n raise forms.ValidationError(u'动态... | <|body_start_0|>
phone = self.data.get('phone')
if not re.match('^1[3-9]\\d{9}$', phone):
raise forms.ValidationError(u'无效的手机号码')
return phone
<|end_body_0|>
<|body_start_1|>
data = self.data
phone = data.get('phone')
password = data.get('password')
i... | Form for user login with phone | PhoneLoginForm | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhoneLoginForm:
"""Form for user login with phone"""
def clean_phone(self):
"""Check phone number"""
<|body_0|>
def clean(self):
"""Check phone and password"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
phone = self.data.get('phone')
i... | stack_v2_sparse_classes_36k_train_012570 | 4,670 | permissive | [
{
"docstring": "Check phone number",
"name": "clean_phone",
"signature": "def clean_phone(self)"
},
{
"docstring": "Check phone and password",
"name": "clean",
"signature": "def clean(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014702 | Implement the Python class `PhoneLoginForm` described below.
Class description:
Form for user login with phone
Method signatures and docstrings:
- def clean_phone(self): Check phone number
- def clean(self): Check phone and password | Implement the Python class `PhoneLoginForm` described below.
Class description:
Form for user login with phone
Method signatures and docstrings:
- def clean_phone(self): Check phone number
- def clean(self): Check phone and password
<|skeleton|>
class PhoneLoginForm:
"""Form for user login with phone"""
def... | 0ea016745d92054bd4df8d934c1b67fd61b6f845 | <|skeleton|>
class PhoneLoginForm:
"""Form for user login with phone"""
def clean_phone(self):
"""Check phone number"""
<|body_0|>
def clean(self):
"""Check phone and password"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PhoneLoginForm:
"""Form for user login with phone"""
def clean_phone(self):
"""Check phone number"""
phone = self.data.get('phone')
if not re.match('^1[3-9]\\d{9}$', phone):
raise forms.ValidationError(u'无效的手机号码')
return phone
def clean(self):
"""C... | the_stack_v2_python_sparse | accounts/forms.py | ygrass/handsome | train | 0 |
0385c7f0deeb55f6c38847633693a9160f816003 | [
"super(CnnEncoder, self).__init__()\nself.cnn = nn.Sequential()\nfor i in range(args.layer_num):\n if i == 0:\n input_dim = args.embedding_dim\n else:\n input_dim = args.hidden_dim\n self.cnn.add_module('conv_layer{:d}'.format(i), nn.Conv1d(in_channels=input_dim, out_channels=args.hidden_dim,... | <|body_start_0|>
super(CnnEncoder, self).__init__()
self.cnn = nn.Sequential()
for i in range(args.layer_num):
if i == 0:
input_dim = args.embedding_dim
else:
input_dim = args.hidden_dim
self.cnn.add_module('conv_layer{:d}'.form... | Basic CNN encoder module, input embeddings and output hidden states. | CnnEncoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CnnEncoder:
"""Basic CNN encoder module, input embeddings and output hidden states."""
def __init__(self, args):
"""args.hidden_dim -- dimension of filters. args.kernel_size -- kernel size of the conv1d. args.layer_num -- number of CNN layers. args.embedding_dim -- dimension of word ... | stack_v2_sparse_classes_36k_train_012571 | 6,319 | no_license | [
{
"docstring": "args.hidden_dim -- dimension of filters. args.kernel_size -- kernel size of the conv1d. args.layer_num -- number of CNN layers. args.embedding_dim -- dimension of word embeddings.",
"name": "__init__",
"signature": "def __init__(self, args)"
},
{
"docstring": "Inputs: e -- input ... | 2 | stack_v2_sparse_classes_30k_train_015994 | Implement the Python class `CnnEncoder` described below.
Class description:
Basic CNN encoder module, input embeddings and output hidden states.
Method signatures and docstrings:
- def __init__(self, args): args.hidden_dim -- dimension of filters. args.kernel_size -- kernel size of the conv1d. args.layer_num -- numbe... | Implement the Python class `CnnEncoder` described below.
Class description:
Basic CNN encoder module, input embeddings and output hidden states.
Method signatures and docstrings:
- def __init__(self, args): args.hidden_dim -- dimension of filters. args.kernel_size -- kernel size of the conv1d. args.layer_num -- numbe... | e79606e24ecc6fd713b481afb527c34eec7d5d66 | <|skeleton|>
class CnnEncoder:
"""Basic CNN encoder module, input embeddings and output hidden states."""
def __init__(self, args):
"""args.hidden_dim -- dimension of filters. args.kernel_size -- kernel size of the conv1d. args.layer_num -- number of CNN layers. args.embedding_dim -- dimension of word ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CnnEncoder:
"""Basic CNN encoder module, input embeddings and output hidden states."""
def __init__(self, args):
"""args.hidden_dim -- dimension of filters. args.kernel_size -- kernel size of the conv1d. args.layer_num -- number of CNN layers. args.embedding_dim -- dimension of word embeddings.""... | the_stack_v2_python_sparse | rationalize/models/encoder.py | anshiquanshu66/factcheck-acl2021 | train | 0 |
b2c86791cb35f668eb8e29f3fbbb2ac6b348c0a1 | [
"def dfs(num):\n if num <= 9:\n return num\n return dfs(dfs(num // 10) + num % 10)\nres = dfs(num)\nreturn res",
"if not num:\n return 0\nreturn (num - 1) % 9 + 1"
] | <|body_start_0|>
def dfs(num):
if num <= 9:
return num
return dfs(dfs(num // 10) + num % 10)
res = dfs(num)
return res
<|end_body_0|>
<|body_start_1|>
if not num:
return 0
return (num - 1) % 9 + 1
<|end_body_1|>
| Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def addDigits(self, num: int) -> int:
"""方法一：递归 @param num: @return:"""
<|body_0|>
def addDigits(self, num: int) -> int:
"""方法二：数学O(1) @param num: @return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def dfs(num):
if num <=... | stack_v2_sparse_classes_36k_train_012572 | 1,039 | no_license | [
{
"docstring": "方法一：递归 @param num: @return:",
"name": "addDigits",
"signature": "def addDigits(self, num: int) -> int"
},
{
"docstring": "方法二：数学O(1) @param num: @return:",
"name": "addDigits",
"signature": "def addDigits(self, num: int) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addDigits(self, num: int) -> int: 方法一：递归 @param num: @return:
- def addDigits(self, num: int) -> int: 方法二：数学O(1) @param num: @return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addDigits(self, num: int) -> int: 方法一：递归 @param num: @return:
- def addDigits(self, num: int) -> int: 方法二：数学O(1) @param num: @return:
<|skeleton|>
class Solution:
def a... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def addDigits(self, num: int) -> int:
"""方法一：递归 @param num: @return:"""
<|body_0|>
def addDigits(self, num: int) -> int:
"""方法二：数学O(1) @param num: @return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def addDigits(self, num: int) -> int:
"""方法一：递归 @param num: @return:"""
def dfs(num):
if num <= 9:
return num
return dfs(dfs(num // 10) + num % 10)
res = dfs(num)
return res
def addDigits(self, num: int) -> int:
"""... | the_stack_v2_python_sparse | LeetCode/数学/258. 各位相加.py | yiming1012/MyLeetCode | train | 2 | |
c74217be9f7714ab14d92844a4b4d4cedc75bfe4 | [
"a = np.exp(x - np.max(x))\nf = a / (1 + a)\nreturn f",
"f = logit.f(x)\ndf = f * (1 - f)\nreturn df"
] | <|body_start_0|>
a = np.exp(x - np.max(x))
f = a / (1 + a)
return f
<|end_body_0|>
<|body_start_1|>
f = logit.f(x)
df = f * (1 - f)
return df
<|end_body_1|>
| Class for the logit function. | logit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class logit:
"""Class for the logit function."""
def f(x):
"""The logit function."""
<|body_0|>
def df(x):
"""The derivative of the logit function."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
a = np.exp(x - np.max(x))
f = a / (1 + a)
... | stack_v2_sparse_classes_36k_train_012573 | 12,501 | no_license | [
{
"docstring": "The logit function.",
"name": "f",
"signature": "def f(x)"
},
{
"docstring": "The derivative of the logit function.",
"name": "df",
"signature": "def df(x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009475 | Implement the Python class `logit` described below.
Class description:
Class for the logit function.
Method signatures and docstrings:
- def f(x): The logit function.
- def df(x): The derivative of the logit function. | Implement the Python class `logit` described below.
Class description:
Class for the logit function.
Method signatures and docstrings:
- def f(x): The logit function.
- def df(x): The derivative of the logit function.
<|skeleton|>
class logit:
"""Class for the logit function."""
def f(x):
"""The log... | 5bbd2dc3fa274f6e48b2d4ef387b3939483cafe8 | <|skeleton|>
class logit:
"""Class for the logit function."""
def f(x):
"""The logit function."""
<|body_0|>
def df(x):
"""The derivative of the logit function."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class logit:
"""Class for the logit function."""
def f(x):
"""The logit function."""
a = np.exp(x - np.max(x))
f = a / (1 + a)
return f
def df(x):
"""The derivative of the logit function."""
f = logit.f(x)
df = f * (1 - f)
return df
| the_stack_v2_python_sparse | Project2/neural_network.py | fridalarsen/FYS-STK4155 | train | 0 |
28d63dbe16b78bd3f1936921f44496b263b0ea2c | [
"if x is None or y is None:\n raise ValueError('Any observation variable cannot be None')\nif category_id is not None:\n category_id = int(category_id)\nreturn Observation(float(x), float(y), category_id)",
"if len(values) != 3:\n raise ValueError('Invalid observation structure')\nreturn ObservationFacto... | <|body_start_0|>
if x is None or y is None:
raise ValueError('Any observation variable cannot be None')
if category_id is not None:
category_id = int(category_id)
return Observation(float(x), float(y), category_id)
<|end_body_0|>
<|body_start_1|>
if len(values) !... | Factory for creation Observation instances | ObservationFactory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObservationFactory:
"""Factory for creation Observation instances"""
def create_observation(x, y, category_id=None):
"""Creates new instance of Observation based on x, y"""
<|body_0|>
def create_observation_from_tuple(values):
"""Creates new instance of Observati... | stack_v2_sparse_classes_36k_train_012574 | 2,463 | no_license | [
{
"docstring": "Creates new instance of Observation based on x, y",
"name": "create_observation",
"signature": "def create_observation(x, y, category_id=None)"
},
{
"docstring": "Creates new instance of Observation based on a tuple",
"name": "create_observation_from_tuple",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_012906 | Implement the Python class `ObservationFactory` described below.
Class description:
Factory for creation Observation instances
Method signatures and docstrings:
- def create_observation(x, y, category_id=None): Creates new instance of Observation based on x, y
- def create_observation_from_tuple(values): Creates new ... | Implement the Python class `ObservationFactory` described below.
Class description:
Factory for creation Observation instances
Method signatures and docstrings:
- def create_observation(x, y, category_id=None): Creates new instance of Observation based on x, y
- def create_observation_from_tuple(values): Creates new ... | 6354e3640bcbb09544084d017dd0e0f0d2f398c0 | <|skeleton|>
class ObservationFactory:
"""Factory for creation Observation instances"""
def create_observation(x, y, category_id=None):
"""Creates new instance of Observation based on x, y"""
<|body_0|>
def create_observation_from_tuple(values):
"""Creates new instance of Observati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObservationFactory:
"""Factory for creation Observation instances"""
def create_observation(x, y, category_id=None):
"""Creates new instance of Observation based on x, y"""
if x is None or y is None:
raise ValueError('Any observation variable cannot be None')
if catego... | the_stack_v2_python_sparse | domain/shared/observation.py | jasphall/k_nearest_neighbours | train | 0 |
a22ed3e64460539683906e2d6e3218494c17a836 | [
"queryset = self.get_child_qs(graph_id)\nserializer = self.get_serializer(queryset, many=True)\nreturn response.Response(serializer.data)",
"graph_id = self.request.resolver_match.kwargs['graph_id']\ngraph = self.get_graph(graph_id)\nserializer.save(graph=graph)"
] | <|body_start_0|>
queryset = self.get_child_qs(graph_id)
serializer = self.get_serializer(queryset, many=True)
return response.Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
graph_id = self.request.resolver_match.kwargs['graph_id']
graph = self.get_graph(graph_id)
... | A ListCreateAPIView mixin for graph children objects. E.g. NodeViews and EdgeViews Child here refers to node or edge object | GraphChildListCreateViewMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GraphChildListCreateViewMixin:
"""A ListCreateAPIView mixin for graph children objects. E.g. NodeViews and EdgeViews Child here refers to node or edge object"""
def list_(self, request, graph_id):
"""Return all the children of a given graph"""
<|body_0|>
def perform_crea... | stack_v2_sparse_classes_36k_train_012575 | 1,932 | no_license | [
{
"docstring": "Return all the children of a given graph",
"name": "list_",
"signature": "def list_(self, request, graph_id)"
},
{
"docstring": "Add the graph to the child object.",
"name": "perform_create_",
"signature": "def perform_create_(self, serializer)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000744 | Implement the Python class `GraphChildListCreateViewMixin` described below.
Class description:
A ListCreateAPIView mixin for graph children objects. E.g. NodeViews and EdgeViews Child here refers to node or edge object
Method signatures and docstrings:
- def list_(self, request, graph_id): Return all the children of ... | Implement the Python class `GraphChildListCreateViewMixin` described below.
Class description:
A ListCreateAPIView mixin for graph children objects. E.g. NodeViews and EdgeViews Child here refers to node or edge object
Method signatures and docstrings:
- def list_(self, request, graph_id): Return all the children of ... | 9e01ff8ab73f6d9d16606ec1c8b7c91cdfa9cd2c | <|skeleton|>
class GraphChildListCreateViewMixin:
"""A ListCreateAPIView mixin for graph children objects. E.g. NodeViews and EdgeViews Child here refers to node or edge object"""
def list_(self, request, graph_id):
"""Return all the children of a given graph"""
<|body_0|>
def perform_crea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GraphChildListCreateViewMixin:
"""A ListCreateAPIView mixin for graph children objects. E.g. NodeViews and EdgeViews Child here refers to node or edge object"""
def list_(self, request, graph_id):
"""Return all the children of a given graph"""
queryset = self.get_child_qs(graph_id)
... | the_stack_v2_python_sparse | server/utils/views/mixins.py | Aviemusca/bjj-digraph | train | 0 |
f92db47e58f45f4d4ad588403506197b1d8e26f2 | [
"self.data = data\nself.progress = progress\nself.loglevel = loglevel\nself.logname = logname\nself._check_required_attributes()\nself.logger = logging.getLogger(f'{self.logname} {self.data}')\nself.logger.setLevel(self.loglevel)\nself.logformat = '[%(name)s %(levelname)s] %(message)s'\nhandler = logging.StreamHand... | <|body_start_0|>
self.data = data
self.progress = progress
self.loglevel = loglevel
self.logname = logname
self._check_required_attributes()
self.logger = logging.getLogger(f'{self.logname} {self.data}')
self.logger.setLevel(self.loglevel)
self.logformat =... | Abstract base class for all cclib method classes. Subclasses defined by cclib: CDA - charde decomposition analysis CSPA - C-squared population analysis Density - density matrix calculation FragmentAnalysis - fragment analysis for ADF output LPA - Löwdin population analysis MBO - Mayer's bond orders Moments - multipole ... | Method | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Method:
"""Abstract base class for all cclib method classes. Subclasses defined by cclib: CDA - charde decomposition analysis CSPA - C-squared population analysis Density - density matrix calculation FragmentAnalysis - fragment analysis for ADF output LPA - Löwdin population analysis MBO - Mayer'... | stack_v2_sparse_classes_36k_train_012576 | 2,470 | permissive | [
{
"docstring": "Initialise the Logfile object. This constructor is typically called by the constructor of a subclass.",
"name": "__init__",
"signature": "def __init__(self, data: 'cclib.parser.data.ccData', progress: Optional[Progress]=None, loglevel: int=logging.INFO, logname: str='Log') -> None"
},
... | 2 | stack_v2_sparse_classes_30k_train_011561 | Implement the Python class `Method` described below.
Class description:
Abstract base class for all cclib method classes. Subclasses defined by cclib: CDA - charde decomposition analysis CSPA - C-squared population analysis Density - density matrix calculation FragmentAnalysis - fragment analysis for ADF output LPA - ... | Implement the Python class `Method` described below.
Class description:
Abstract base class for all cclib method classes. Subclasses defined by cclib: CDA - charde decomposition analysis CSPA - C-squared population analysis Density - density matrix calculation FragmentAnalysis - fragment analysis for ADF output LPA - ... | b8d42a163ce9bafd4b660e2a933f56a8cc54fd9b | <|skeleton|>
class Method:
"""Abstract base class for all cclib method classes. Subclasses defined by cclib: CDA - charde decomposition analysis CSPA - C-squared population analysis Density - density matrix calculation FragmentAnalysis - fragment analysis for ADF output LPA - Löwdin population analysis MBO - Mayer'... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Method:
"""Abstract base class for all cclib method classes. Subclasses defined by cclib: CDA - charde decomposition analysis CSPA - C-squared population analysis Density - density matrix calculation FragmentAnalysis - fragment analysis for ADF output LPA - Löwdin population analysis MBO - Mayer's bond orders... | the_stack_v2_python_sparse | cclib/method/calculationmethod.py | cclib/cclib | train | 285 |
bb0c5155111e0c6ad0be0dcc95af68e9fde7e24b | [
"for s in STATES:\n response = self.client.get(reverse('education:state_detail', args=(s,)))\n self.assertEqual(response.status_code, 200)\n self.assertNotEqual(response.context.get('message'), None)\n self.assertContains(response, 'Error: No data for state {}'.format(s))",
"create_null_states()\nfor ... | <|body_start_0|>
for s in STATES:
response = self.client.get(reverse('education:state_detail', args=(s,)))
self.assertEqual(response.status_code, 200)
self.assertNotEqual(response.context.get('message'), None)
self.assertContains(response, 'Error: No data for stat... | EducationStateDetailsViewTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EducationStateDetailsViewTest:
def test_no_data(self):
"""Make sure each state page renders if there is no database data."""
<|body_0|>
def test_with_null_data(self):
"""Make sure each state page renders if there is data in the database."""
<|body_1|>
de... | stack_v2_sparse_classes_36k_train_012577 | 9,266 | no_license | [
{
"docstring": "Make sure each state page renders if there is no database data.",
"name": "test_no_data",
"signature": "def test_no_data(self)"
},
{
"docstring": "Make sure each state page renders if there is data in the database.",
"name": "test_with_null_data",
"signature": "def test_w... | 3 | stack_v2_sparse_classes_30k_test_000202 | Implement the Python class `EducationStateDetailsViewTest` described below.
Class description:
Implement the EducationStateDetailsViewTest class.
Method signatures and docstrings:
- def test_no_data(self): Make sure each state page renders if there is no database data.
- def test_with_null_data(self): Make sure each ... | Implement the Python class `EducationStateDetailsViewTest` described below.
Class description:
Implement the EducationStateDetailsViewTest class.
Method signatures and docstrings:
- def test_no_data(self): Make sure each state page renders if there is no database data.
- def test_with_null_data(self): Make sure each ... | 2a8e2dc4e9b3cb92d4d437b37e61940a9486b81f | <|skeleton|>
class EducationStateDetailsViewTest:
def test_no_data(self):
"""Make sure each state page renders if there is no database data."""
<|body_0|>
def test_with_null_data(self):
"""Make sure each state page renders if there is data in the database."""
<|body_1|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EducationStateDetailsViewTest:
def test_no_data(self):
"""Make sure each state page renders if there is no database data."""
for s in STATES:
response = self.client.get(reverse('education:state_detail', args=(s,)))
self.assertEqual(response.status_code, 200)
... | the_stack_v2_python_sparse | education/tests.py | smeds1/mysite | train | 1 | |
e8936994808e6f1a18a7dabbcf92d1570ab6efee | [
"super(AdaptiveParameterizedStrategy, self).__init__(network, bound)\nself.size = size\nself.history = history\nself.remainder = remainder\nself.sigma = sigma\nself.strategies = [np.random.uniform(-self.bound, self.bound, size=FeatureMatrix.TOTAL_FEATURES) for _ in range(self.size)]\nself.strategy = self.strategies... | <|body_start_0|>
super(AdaptiveParameterizedStrategy, self).__init__(network, bound)
self.size = size
self.history = history
self.remainder = remainder
self.sigma = sigma
self.strategies = [np.random.uniform(-self.bound, self.bound, size=FeatureMatrix.TOTAL_FEATURES) for ... | A adaptive and parameterized neuron selection strategy. Adaptive and parameterized neuron selection strategy is a strategy that changes the parameterized neuron selection strategy adaptively with respect to the model, data, or even time. These updates are done in online; in other words, the strategies are updated while... | AdaptiveParameterizedStrategy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdaptiveParameterizedStrategy:
"""A adaptive and parameterized neuron selection strategy. Adaptive and parameterized neuron selection strategy is a strategy that changes the parameterized neuron selection strategy adaptively with respect to the model, data, or even time. These updates are done in... | stack_v2_sparse_classes_36k_train_012578 | 17,144 | permissive | [
{
"docstring": "Create a adaptive parameterized strategy, and initialize its variables. Args: network: A wrapped Keras model with `adapt.Network`. bound: A floating point number indicates the absolute value of minimum and maximum bounds. size: A positive integer. The number of strategies to create at once. hist... | 4 | stack_v2_sparse_classes_30k_train_012949 | Implement the Python class `AdaptiveParameterizedStrategy` described below.
Class description:
A adaptive and parameterized neuron selection strategy. Adaptive and parameterized neuron selection strategy is a strategy that changes the parameterized neuron selection strategy adaptively with respect to the model, data, ... | Implement the Python class `AdaptiveParameterizedStrategy` described below.
Class description:
A adaptive and parameterized neuron selection strategy. Adaptive and parameterized neuron selection strategy is a strategy that changes the parameterized neuron selection strategy adaptively with respect to the model, data, ... | 0b801d2d2e828ac480d1097cb3bdd82b1e25c15b | <|skeleton|>
class AdaptiveParameterizedStrategy:
"""A adaptive and parameterized neuron selection strategy. Adaptive and parameterized neuron selection strategy is a strategy that changes the parameterized neuron selection strategy adaptively with respect to the model, data, or even time. These updates are done in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdaptiveParameterizedStrategy:
"""A adaptive and parameterized neuron selection strategy. Adaptive and parameterized neuron selection strategy is a strategy that changes the parameterized neuron selection strategy adaptively with respect to the model, data, or even time. These updates are done in online; in o... | the_stack_v2_python_sparse | code/deep/ReMoS/CV_adv/DNNtest/strategy/adapt.py | jindongwang/transferlearning | train | 12,773 |
e4f42b7f890dd3329982db3f90e5d757abff2762 | [
"dp = [float('inf')] * (n + 1)\ndp[0] = 0\nfor i in range(1, n + 1):\n for j in range(1, int(sqrt(i)) + 1):\n square = j * j\n if i >= square:\n dp[i] = min(dp[i], dp[i - square] + 1)\nreturn dp[-1]",
"memo = dict()\n\ndef dfs(target):\n if target in memo:\n return memo[targe... | <|body_start_0|>
dp = [float('inf')] * (n + 1)
dp[0] = 0
for i in range(1, n + 1):
for j in range(1, int(sqrt(i)) + 1):
square = j * j
if i >= square:
dp[i] = min(dp[i], dp[i - square] + 1)
return dp[-1]
<|end_body_0|>
<|bo... | 四平方定理： 任何一个正整数都可以表示成不超过四个整数的平方之和。 推论：满足四数平方和定理的数n（四个整数的情况），必定满足 n = 4 ^ a * (8b + 7) | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""四平方定理： 任何一个正整数都可以表示成不超过四个整数的平方之和。 推论：满足四数平方和定理的数n（四个整数的情况），必定满足 n = 4 ^ a * (8b + 7)"""
def numSquares1(self, n: int) -> int:
"""DP: 类似题目322 coin change. 本题的'coin'就是平方数"""
<|body_0|>
def numSquares2(self, n: int) -> int:
"""DFS会超时"""
<|body_1... | stack_v2_sparse_classes_36k_train_012579 | 2,859 | no_license | [
{
"docstring": "DP: 类似题目322 coin change. 本题的'coin'就是平方数",
"name": "numSquares1",
"signature": "def numSquares1(self, n: int) -> int"
},
{
"docstring": "DFS会超时",
"name": "numSquares2",
"signature": "def numSquares2(self, n: int) -> int"
},
{
"docstring": "BFS：类似于寻找最短路径 从根节点开始像下逐层延... | 3 | null | Implement the Python class `Solution` described below.
Class description:
四平方定理： 任何一个正整数都可以表示成不超过四个整数的平方之和。 推论：满足四数平方和定理的数n（四个整数的情况），必定满足 n = 4 ^ a * (8b + 7)
Method signatures and docstrings:
- def numSquares1(self, n: int) -> int: DP: 类似题目322 coin change. 本题的'coin'就是平方数
- def numSquares2(self, n: int) -> int: DFS会超... | Implement the Python class `Solution` described below.
Class description:
四平方定理： 任何一个正整数都可以表示成不超过四个整数的平方之和。 推论：满足四数平方和定理的数n（四个整数的情况），必定满足 n = 4 ^ a * (8b + 7)
Method signatures and docstrings:
- def numSquares1(self, n: int) -> int: DP: 类似题目322 coin change. 本题的'coin'就是平方数
- def numSquares2(self, n: int) -> int: DFS会超... | 2bbb1640589aab34f2bc42489283033cc11fb885 | <|skeleton|>
class Solution:
"""四平方定理： 任何一个正整数都可以表示成不超过四个整数的平方之和。 推论：满足四数平方和定理的数n（四个整数的情况），必定满足 n = 4 ^ a * (8b + 7)"""
def numSquares1(self, n: int) -> int:
"""DP: 类似题目322 coin change. 本题的'coin'就是平方数"""
<|body_0|>
def numSquares2(self, n: int) -> int:
"""DFS会超时"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""四平方定理： 任何一个正整数都可以表示成不超过四个整数的平方之和。 推论：满足四数平方和定理的数n（四个整数的情况），必定满足 n = 4 ^ a * (8b + 7)"""
def numSquares1(self, n: int) -> int:
"""DP: 类似题目322 coin change. 本题的'coin'就是平方数"""
dp = [float('inf')] * (n + 1)
dp[0] = 0
for i in range(1, n + 1):
for j in r... | the_stack_v2_python_sparse | 279_perfect-squares.py | helloocc/algorithm | train | 1 |
3b69fce22acd93cf3477ddaee8089e73ddee32a4 | [
"svm = SVC(kernel=kernel_type, gamma='auto')\nprint('Fitting SVM to training data....')\nsvm = svm.fit(training_data_vecs, train_labels[col_name])\nreturn svm",
"result = model.predict(test_vector)\noutput = pd.DataFrame(data={'id': test_data['id'], test_col_name: result})\noutput.to_csv(output_name, index=False,... | <|body_start_0|>
svm = SVC(kernel=kernel_type, gamma='auto')
print('Fitting SVM to training data....')
svm = svm.fit(training_data_vecs, train_labels[col_name])
return svm
<|end_body_0|>
<|body_start_1|>
result = model.predict(test_vector)
output = pd.DataFrame(data={'id... | RunSVM | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunSVM:
def train_svm(self, training_data_vecs, train_labels, col_name, kernel_type):
"""Return SVM model"""
<|body_0|>
def predict_svm(self, model, test_vector, test_data, test_id_col, test_col_name, output_name):
"""Return output of SVM prediction and save to csv""... | stack_v2_sparse_classes_36k_train_012580 | 697 | no_license | [
{
"docstring": "Return SVM model",
"name": "train_svm",
"signature": "def train_svm(self, training_data_vecs, train_labels, col_name, kernel_type)"
},
{
"docstring": "Return output of SVM prediction and save to csv",
"name": "predict_svm",
"signature": "def predict_svm(self, model, test_... | 2 | stack_v2_sparse_classes_30k_test_001121 | Implement the Python class `RunSVM` described below.
Class description:
Implement the RunSVM class.
Method signatures and docstrings:
- def train_svm(self, training_data_vecs, train_labels, col_name, kernel_type): Return SVM model
- def predict_svm(self, model, test_vector, test_data, test_id_col, test_col_name, outp... | Implement the Python class `RunSVM` described below.
Class description:
Implement the RunSVM class.
Method signatures and docstrings:
- def train_svm(self, training_data_vecs, train_labels, col_name, kernel_type): Return SVM model
- def predict_svm(self, model, test_vector, test_data, test_id_col, test_col_name, outp... | 141fa19637bd34854fe07b670a6103f69c085700 | <|skeleton|>
class RunSVM:
def train_svm(self, training_data_vecs, train_labels, col_name, kernel_type):
"""Return SVM model"""
<|body_0|>
def predict_svm(self, model, test_vector, test_data, test_id_col, test_col_name, output_name):
"""Return output of SVM prediction and save to csv""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RunSVM:
def train_svm(self, training_data_vecs, train_labels, col_name, kernel_type):
"""Return SVM model"""
svm = SVC(kernel=kernel_type, gamma='auto')
print('Fitting SVM to training data....')
svm = svm.fit(training_data_vecs, train_labels[col_name])
return svm
d... | the_stack_v2_python_sparse | RunSVM.py | ianovski/customer-review-sentiment | train | 0 | |
c3487c9498a8753a39e8449b8ff603f967bbf513 | [
"self.app = app\nself.script_name = script_name\nself.scheme = scheme\nself.server = server",
"script_name = environ.get('HTTP_X_SCRIPT_NAME', '') or self.script_name\nif script_name:\n environ['SCRIPT_NAME'] = script_name\n path_info = environ['PATH_INFO']\n if path_info.startswith(script_name):\n ... | <|body_start_0|>
self.app = app
self.script_name = script_name
self.scheme = scheme
self.server = server
<|end_body_0|>
<|body_start_1|>
script_name = environ.get('HTTP_X_SCRIPT_NAME', '') or self.script_name
if script_name:
environ['SCRIPT_NAME'] = script_na... | Allow to use a reverse proxy. http://blog.macuyiko.com/post/2016/fixing-flask-url_for-when-behind-mod_proxy.html | ReverseProxied | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReverseProxied:
"""Allow to use a reverse proxy. http://blog.macuyiko.com/post/2016/fixing-flask-url_for-when-behind-mod_proxy.html"""
def __init__(self, app, script_name=None, scheme=None, server=None):
"""Create a new wrapper for Flask."""
<|body_0|>
def __call__(self,... | stack_v2_sparse_classes_36k_train_012581 | 1,794 | permissive | [
{
"docstring": "Create a new wrapper for Flask.",
"name": "__init__",
"signature": "def __init__(self, app, script_name=None, scheme=None, server=None)"
},
{
"docstring": "Set environment for Flask.",
"name": "__call__",
"signature": "def __call__(self, environ, start_response)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009651 | Implement the Python class `ReverseProxied` described below.
Class description:
Allow to use a reverse proxy. http://blog.macuyiko.com/post/2016/fixing-flask-url_for-when-behind-mod_proxy.html
Method signatures and docstrings:
- def __init__(self, app, script_name=None, scheme=None, server=None): Create a new wrapper... | Implement the Python class `ReverseProxied` described below.
Class description:
Allow to use a reverse proxy. http://blog.macuyiko.com/post/2016/fixing-flask-url_for-when-behind-mod_proxy.html
Method signatures and docstrings:
- def __init__(self, app, script_name=None, scheme=None, server=None): Create a new wrapper... | 47e1c99e3be3c1b099d3772bc077f5666020eb0b | <|skeleton|>
class ReverseProxied:
"""Allow to use a reverse proxy. http://blog.macuyiko.com/post/2016/fixing-flask-url_for-when-behind-mod_proxy.html"""
def __init__(self, app, script_name=None, scheme=None, server=None):
"""Create a new wrapper for Flask."""
<|body_0|>
def __call__(self,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReverseProxied:
"""Allow to use a reverse proxy. http://blog.macuyiko.com/post/2016/fixing-flask-url_for-when-behind-mod_proxy.html"""
def __init__(self, app, script_name=None, scheme=None, server=None):
"""Create a new wrapper for Flask."""
self.app = app
self.script_name = scrip... | the_stack_v2_python_sparse | sacredboard/app/webapi/proxy.py | nagyist/sacredboard | train | 0 |
af214953f110d8307d05885141edf65d0251fab0 | [
"schools_profiles_urls_xpath1 = '//*[@id=\"FindSchoolContainer\"]/div[5]/div[3]/div[2]/div/div/a/@href'\nschools_profiles_urls_xpath2 = '//*[@id=\"FindSchoolContainer\"]/div[5]/div[6]/div[2]/div/div/a/@href'\ndriver = webdriver.Chrome()\ndriver.get(response.url)\ntime.sleep(5)\ndom = lxml.html.fromstring(driver.pag... | <|body_start_0|>
schools_profiles_urls_xpath1 = '//*[@id="FindSchoolContainer"]/div[5]/div[3]/div[2]/div/div/a/@href'
schools_profiles_urls_xpath2 = '//*[@id="FindSchoolContainer"]/div[5]/div[6]/div[2]/div/div/a/@href'
driver = webdriver.Chrome()
driver.get(response.url)
time.sle... | a scrapy spider to crawl csviamonde.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found | CsviamondeSpiderSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CsviamondeSpiderSpider:
"""a scrapy spider to crawl csviamonde.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def parse(self, response):
"""extr... | stack_v2_sparse_classes_36k_train_012582 | 4,277 | no_license | [
{
"docstring": "extract schools_profiles_urls from the two sections Elementary Schools and Secondary Schools",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "parse school profile page to get all the item data",
"name": "parse_school_profile",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_009887 | Implement the Python class `CsviamondeSpiderSpider` described below.
Class description:
a scrapy spider to crawl csviamonde.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found
Method sig... | Implement the Python class `CsviamondeSpiderSpider` described below.
Class description:
a scrapy spider to crawl csviamonde.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found
Method sig... | 350264cf6da323692c2838d8cb235ef61085851b | <|skeleton|>
class CsviamondeSpiderSpider:
"""a scrapy spider to crawl csviamonde.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def parse(self, response):
"""extr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CsviamondeSpiderSpider:
"""a scrapy spider to crawl csviamonde.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def parse(self, response):
"""extract schools_p... | the_stack_v2_python_sparse | school_scraping/spiders/csviamonde_spider.py | ramadanmostafa/canada_school_scraping | train | 0 |
aacbae6dca7e6b62df3e57d03bba8c84b375ccd0 | [
"if 'line_item' in self.request.GET:\n try:\n part_id = self.request.GET.get('line_item')\n part = SalesOrderLineItem.objects.get(id=part_id).part\n except Part.DoesNotExist:\n return None\nelif 'pk' in self.request.POST:\n try:\n part_id = self.request.POST.get('pk')\n p... | <|body_start_0|>
if 'line_item' in self.request.GET:
try:
part_id = self.request.GET.get('line_item')
part = SalesOrderLineItem.objects.get(id=part_id).part
except Part.DoesNotExist:
return None
elif 'pk' in self.request.POST:
... | View for inspecting part pricing information. | LineItemPricing | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LineItemPricing:
"""View for inspecting part pricing information."""
def get_part(self, id=False):
"""Return the Part instance associated with this view"""
<|body_0|>
def get_so(self, pk=False):
"""Return the SalesOrderLineItem associated with this view"""
... | stack_v2_sparse_classes_36k_train_012583 | 14,977 | permissive | [
{
"docstring": "Return the Part instance associated with this view",
"name": "get_part",
"signature": "def get_part(self, id=False)"
},
{
"docstring": "Return the SalesOrderLineItem associated with this view",
"name": "get_so",
"signature": "def get_so(self, pk=False)"
},
{
"docs... | 5 | null | Implement the Python class `LineItemPricing` described below.
Class description:
View for inspecting part pricing information.
Method signatures and docstrings:
- def get_part(self, id=False): Return the Part instance associated with this view
- def get_so(self, pk=False): Return the SalesOrderLineItem associated wit... | Implement the Python class `LineItemPricing` described below.
Class description:
View for inspecting part pricing information.
Method signatures and docstrings:
- def get_part(self, id=False): Return the Part instance associated with this view
- def get_so(self, pk=False): Return the SalesOrderLineItem associated wit... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class LineItemPricing:
"""View for inspecting part pricing information."""
def get_part(self, id=False):
"""Return the Part instance associated with this view"""
<|body_0|>
def get_so(self, pk=False):
"""Return the SalesOrderLineItem associated with this view"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LineItemPricing:
"""View for inspecting part pricing information."""
def get_part(self, id=False):
"""Return the Part instance associated with this view"""
if 'line_item' in self.request.GET:
try:
part_id = self.request.GET.get('line_item')
part... | the_stack_v2_python_sparse | InvenTree/order/views.py | inventree/InvenTree | train | 3,077 |
960dfa1fe7919376001a2906ffefde75b7bbc77f | [
"super(SurnameGenerationModel, self).__init__()\nself.char_emb = nn.Embedding(num_embeddings=char_vocab_size, embedding_dim=char_embedding_size, padding_idx=padding_idx)\nself.rnn = nn.GRU(input_size=char_embedding_size, hidden_size=rnn_hidden_size, batch_first=batch_first)\nself.fc = nn.Linear(in_features=rnn_hidd... | <|body_start_0|>
super(SurnameGenerationModel, self).__init__()
self.char_emb = nn.Embedding(num_embeddings=char_vocab_size, embedding_dim=char_embedding_size, padding_idx=padding_idx)
self.rnn = nn.GRU(input_size=char_embedding_size, hidden_size=rnn_hidden_size, batch_first=batch_first)
... | SurnameGenerationModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SurnameGenerationModel:
def __init__(self, char_embedding_size, char_vocab_size, rnn_hidden_size, batch_first=True, padding_idx=0, dropout_p=0.5):
"""Args: char_embedding_size (int): The size of the character embeddings char_vocab_size (int): The number of characters to embed rnn_hidden_... | stack_v2_sparse_classes_36k_train_012584 | 28,880 | no_license | [
{
"docstring": "Args: char_embedding_size (int): The size of the character embeddings char_vocab_size (int): The number of characters to embed rnn_hidden_size (int): The size of the RNN's hidden state batch_first (bool): Informs whether the input tensors will have batch or the sequence on the 0th dimension padd... | 2 | stack_v2_sparse_classes_30k_train_019378 | Implement the Python class `SurnameGenerationModel` described below.
Class description:
Implement the SurnameGenerationModel class.
Method signatures and docstrings:
- def __init__(self, char_embedding_size, char_vocab_size, rnn_hidden_size, batch_first=True, padding_idx=0, dropout_p=0.5): Args: char_embedding_size (... | Implement the Python class `SurnameGenerationModel` described below.
Class description:
Implement the SurnameGenerationModel class.
Method signatures and docstrings:
- def __init__(self, char_embedding_size, char_vocab_size, rnn_hidden_size, batch_first=True, padding_idx=0, dropout_p=0.5): Args: char_embedding_size (... | ba8feae92c875c1e65ad5a25a2363393ab0daf79 | <|skeleton|>
class SurnameGenerationModel:
def __init__(self, char_embedding_size, char_vocab_size, rnn_hidden_size, batch_first=True, padding_idx=0, dropout_p=0.5):
"""Args: char_embedding_size (int): The size of the character embeddings char_vocab_size (int): The number of characters to embed rnn_hidden_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SurnameGenerationModel:
def __init__(self, char_embedding_size, char_vocab_size, rnn_hidden_size, batch_first=True, padding_idx=0, dropout_p=0.5):
"""Args: char_embedding_size (int): The size of the character embeddings char_vocab_size (int): The number of characters to embed rnn_hidden_size (int): Th... | the_stack_v2_python_sparse | chapter_7/unconditioned_surname_gen.py | kerenskybr/nlp_pytorch_book | train | 0 | |
c49741e88d6666702907653723254268e92b73bd | [
"s_index = f_index = 0\nmin_length = float('inf')\nwhile f_index < len(nums):\n sub_sum = sum(nums[s_index:f_index + 1])\n if sub_sum < s:\n f_index += 1\n elif sub_sum > s:\n if min_length > f_index - s_index + 1:\n min_length = f_index - s_index + 1\n s_index += 1\n els... | <|body_start_0|>
s_index = f_index = 0
min_length = float('inf')
while f_index < len(nums):
sub_sum = sum(nums[s_index:f_index + 1])
if sub_sum < s:
f_index += 1
elif sub_sum > s:
if min_length > f_index - s_index + 1:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minSubArrayLen(self, s, nums):
""":type s: int :type nums: List[int] :rtype: int"""
<|body_0|>
def minSubArrayLen_II(self, s, nums):
""":type s: int :type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s_in... | stack_v2_sparse_classes_36k_train_012585 | 1,418 | no_license | [
{
"docstring": ":type s: int :type nums: List[int] :rtype: int",
"name": "minSubArrayLen",
"signature": "def minSubArrayLen(self, s, nums)"
},
{
"docstring": ":type s: int :type nums: List[int] :rtype: int",
"name": "minSubArrayLen_II",
"signature": "def minSubArrayLen_II(self, s, nums)"... | 2 | stack_v2_sparse_classes_30k_train_001987 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minSubArrayLen(self, s, nums): :type s: int :type nums: List[int] :rtype: int
- def minSubArrayLen_II(self, s, nums): :type s: int :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minSubArrayLen(self, s, nums): :type s: int :type nums: List[int] :rtype: int
- def minSubArrayLen_II(self, s, nums): :type s: int :type nums: List[int] :rtype: int
<|skelet... | 1461b10b8910fa90a311939c6df9082a8526f9b1 | <|skeleton|>
class Solution:
def minSubArrayLen(self, s, nums):
""":type s: int :type nums: List[int] :rtype: int"""
<|body_0|>
def minSubArrayLen_II(self, s, nums):
""":type s: int :type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minSubArrayLen(self, s, nums):
""":type s: int :type nums: List[int] :rtype: int"""
s_index = f_index = 0
min_length = float('inf')
while f_index < len(nums):
sub_sum = sum(nums[s_index:f_index + 1])
if sub_sum < s:
f_index ... | the_stack_v2_python_sparse | Medium/209_minimumSizeSubArraySum.py | Yucheng7713/CodingPracticeByYuch | train | 0 | |
7bf94723357d75790a5614d990d0a1c7e3b1b865 | [
"kwargs['default'] = default\nkwargs['types'] = (tuple, list)\nsuper().__init__(**kwargs)",
"if isinstance(value, (list, tuple)) and all((isinstance(x, (int, float)) for x in value)):\n return value\nvalue = super().parse(value)\nif value is None or value is UNDEF:\n return value\nif callable(value):\n r... | <|body_start_0|>
kwargs['default'] = default
kwargs['types'] = (tuple, list)
super().__init__(**kwargs)
<|end_body_0|>
<|body_start_1|>
if isinstance(value, (list, tuple)) and all((isinstance(x, (int, float)) for x in value)):
return value
value = super().parse(value... | Defines a line dash property. The value must be provided as a list or tuple of numbers defining the length of lines and spaces in-between. | DashProperty | [
"LicenseRef-scancode-philippe-de-muyter",
"LicenseRef-scancode-commercial-license",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DashProperty:
"""Defines a line dash property. The value must be provided as a list or tuple of numbers defining the length of lines and spaces in-between."""
def __init__(self, default=UNDEF, **kwargs):
"""Initializes a new instance of DashProperty."""
<|body_0|>
def pa... | stack_v2_sparse_classes_36k_train_012586 | 4,576 | permissive | [
{
"docstring": "Initializes a new instance of DashProperty.",
"name": "__init__",
"signature": "def __init__(self, default=UNDEF, **kwargs)"
},
{
"docstring": "Validates and converts given value.",
"name": "parse",
"signature": "def parse(self, value)"
}
] | 2 | null | Implement the Python class `DashProperty` described below.
Class description:
Defines a line dash property. The value must be provided as a list or tuple of numbers defining the length of lines and spaces in-between.
Method signatures and docstrings:
- def __init__(self, default=UNDEF, **kwargs): Initializes a new in... | Implement the Python class `DashProperty` described below.
Class description:
Defines a line dash property. The value must be provided as a list or tuple of numbers defining the length of lines and spaces in-between.
Method signatures and docstrings:
- def __init__(self, default=UNDEF, **kwargs): Initializes a new in... | d59b1bc056f3037b7b7ab635b6deb41120612965 | <|skeleton|>
class DashProperty:
"""Defines a line dash property. The value must be provided as a list or tuple of numbers defining the length of lines and spaces in-between."""
def __init__(self, default=UNDEF, **kwargs):
"""Initializes a new instance of DashProperty."""
<|body_0|>
def pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DashProperty:
"""Defines a line dash property. The value must be provided as a list or tuple of numbers defining the length of lines and spaces in-between."""
def __init__(self, default=UNDEF, **kwargs):
"""Initializes a new instance of DashProperty."""
kwargs['default'] = default
... | the_stack_v2_python_sparse | pero/properties/special.py | xxao/pero | train | 31 |
f7b5d7eaa64b76249b580d82a7e821f923b2a2a2 | [
"lesson = Lessons.query.filter_by(id=self.lesson.data).first()\nacademy = Academy.query.filter_by(name=self.academy.data).first()\nstudent = Student.query.filter_by(academy_id=academy.id).filter_by(name=self.name.data).first()\nif student is not None:\n raise ValidationError('Student name is already in the syste... | <|body_start_0|>
lesson = Lessons.query.filter_by(id=self.lesson.data).first()
academy = Academy.query.filter_by(name=self.academy.data).first()
student = Student.query.filter_by(academy_id=academy.id).filter_by(name=self.name.data).first()
if student is not None:
raise Valid... | Form for getting initial student data | CreateStudentForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateStudentForm:
"""Form for getting initial student data"""
def validate_name(self, name):
"""Validate name has yet to be used within the academy"""
<|body_0|>
def validate_phone2(self, phone):
"""Validate phone is unique"""
<|body_1|>
def validat... | stack_v2_sparse_classes_36k_train_012587 | 19,666 | no_license | [
{
"docstring": "Validate name has yet to be used within the academy",
"name": "validate_name",
"signature": "def validate_name(self, name)"
},
{
"docstring": "Validate phone is unique",
"name": "validate_phone2",
"signature": "def validate_phone2(self, phone)"
},
{
"docstring": "... | 4 | stack_v2_sparse_classes_30k_train_005002 | Implement the Python class `CreateStudentForm` described below.
Class description:
Form for getting initial student data
Method signatures and docstrings:
- def validate_name(self, name): Validate name has yet to be used within the academy
- def validate_phone2(self, phone): Validate phone is unique
- def validate_ph... | Implement the Python class `CreateStudentForm` described below.
Class description:
Form for getting initial student data
Method signatures and docstrings:
- def validate_name(self, name): Validate name has yet to be used within the academy
- def validate_phone2(self, phone): Validate phone is unique
- def validate_ph... | e2404fef23258448764aaf9fabb36b6575ddf163 | <|skeleton|>
class CreateStudentForm:
"""Form for getting initial student data"""
def validate_name(self, name):
"""Validate name has yet to be used within the academy"""
<|body_0|>
def validate_phone2(self, phone):
"""Validate phone is unique"""
<|body_1|>
def validat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateStudentForm:
"""Form for getting initial student data"""
def validate_name(self, name):
"""Validate name has yet to be used within the academy"""
lesson = Lessons.query.filter_by(id=self.lesson.data).first()
academy = Academy.query.filter_by(name=self.academy.data).first()
... | the_stack_v2_python_sparse | app/students/forms.py | Kwsswart/Academy | train | 0 |
e3500b582d897d9d4b9fa0e8bdf95199c1775ca3 | [
"dp = [0] + [sys.maxsize] * amount\nfor i in range(amount):\n for cent in coins:\n if cent + i > amount:\n continue\n else:\n dp[i + cent] = min(dp[i] + 1, dp[i + cent])\nprint(dp)\nreturn dp[-1] if dp[-1] != sys.maxsize else -1",
"minCoins, coinsUsed = self.dpMakeChange(coi... | <|body_start_0|>
dp = [0] + [sys.maxsize] * amount
for i in range(amount):
for cent in coins:
if cent + i > amount:
continue
else:
dp[i + cent] = min(dp[i] + 1, dp[i + cent])
print(dp)
return dp[-1] if dp... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def coinChange(self, coins, amount):
"""Worked :type coins: List[int] :type amount: int :rtype: int"""
<|body_0|>
def coinChange2(self, coins, amount):
"""This solution and it's helper function were not accepted by leetcode judge. :type coins: List[int] :ty... | stack_v2_sparse_classes_36k_train_012588 | 2,354 | no_license | [
{
"docstring": "Worked :type coins: List[int] :type amount: int :rtype: int",
"name": "coinChange",
"signature": "def coinChange(self, coins, amount)"
},
{
"docstring": "This solution and it's helper function were not accepted by leetcode judge. :type coins: List[int] :type amount: int :rtype: i... | 3 | stack_v2_sparse_classes_30k_train_017190 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def coinChange(self, coins, amount): Worked :type coins: List[int] :type amount: int :rtype: int
- def coinChange2(self, coins, amount): This solution and it's helper function we... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def coinChange(self, coins, amount): Worked :type coins: List[int] :type amount: int :rtype: int
- def coinChange2(self, coins, amount): This solution and it's helper function we... | e319481834d0d0519d50bbf00e4f46374bbcf091 | <|skeleton|>
class Solution:
def coinChange(self, coins, amount):
"""Worked :type coins: List[int] :type amount: int :rtype: int"""
<|body_0|>
def coinChange2(self, coins, amount):
"""This solution and it's helper function were not accepted by leetcode judge. :type coins: List[int] :ty... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def coinChange(self, coins, amount):
"""Worked :type coins: List[int] :type amount: int :rtype: int"""
dp = [0] + [sys.maxsize] * amount
for i in range(amount):
for cent in coins:
if cent + i > amount:
continue
e... | the_stack_v2_python_sparse | coin_change_322.py | raghavgr/Leetcode | train | 1 | |
09555195b025a37cd8a10ab0fe9d0e4427648e79 | [
"self.is_email_otp_setup_done = is_email_otp_setup_done\nself.is_totp_setup_done = is_totp_setup_done\nself.is_user_exempt_from_mfa = is_user_exempt_from_mfa",
"if dictionary is None:\n return None\nis_email_otp_setup_done = dictionary.get('isEmailOtpSetupDone')\nis_totp_setup_done = dictionary.get('isTotpSetu... | <|body_start_0|>
self.is_email_otp_setup_done = is_email_otp_setup_done
self.is_totp_setup_done = is_totp_setup_done
self.is_user_exempt_from_mfa = is_user_exempt_from_mfa
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
is_email_otp_setup_done = di... | Implementation of the 'MfaInfo' model. Specifies information about MFA. Attributes: is_email_otp_setup_done (bool): Specifies if email OTP setup is done on the user. is_totp_setup_done (bool): Specifies if TOTP setup is done on the user. is_user_exempt_from_mfa (bool): Specifies if MFA is disabled on the user. | MfaInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MfaInfo:
"""Implementation of the 'MfaInfo' model. Specifies information about MFA. Attributes: is_email_otp_setup_done (bool): Specifies if email OTP setup is done on the user. is_totp_setup_done (bool): Specifies if TOTP setup is done on the user. is_user_exempt_from_mfa (bool): Specifies if MF... | stack_v2_sparse_classes_36k_train_012589 | 2,122 | permissive | [
{
"docstring": "Constructor for the MfaInfo class",
"name": "__init__",
"signature": "def __init__(self, is_email_otp_setup_done=None, is_totp_setup_done=None, is_user_exempt_from_mfa=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A d... | 2 | null | Implement the Python class `MfaInfo` described below.
Class description:
Implementation of the 'MfaInfo' model. Specifies information about MFA. Attributes: is_email_otp_setup_done (bool): Specifies if email OTP setup is done on the user. is_totp_setup_done (bool): Specifies if TOTP setup is done on the user. is_user_... | Implement the Python class `MfaInfo` described below.
Class description:
Implementation of the 'MfaInfo' model. Specifies information about MFA. Attributes: is_email_otp_setup_done (bool): Specifies if email OTP setup is done on the user. is_totp_setup_done (bool): Specifies if TOTP setup is done on the user. is_user_... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class MfaInfo:
"""Implementation of the 'MfaInfo' model. Specifies information about MFA. Attributes: is_email_otp_setup_done (bool): Specifies if email OTP setup is done on the user. is_totp_setup_done (bool): Specifies if TOTP setup is done on the user. is_user_exempt_from_mfa (bool): Specifies if MF... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MfaInfo:
"""Implementation of the 'MfaInfo' model. Specifies information about MFA. Attributes: is_email_otp_setup_done (bool): Specifies if email OTP setup is done on the user. is_totp_setup_done (bool): Specifies if TOTP setup is done on the user. is_user_exempt_from_mfa (bool): Specifies if MFA is disabled... | the_stack_v2_python_sparse | cohesity_management_sdk/models/mfa_info.py | cohesity/management-sdk-python | train | 24 |
27628ab0aba9c31805f0d7fae5bba47058b3a066 | [
"memo = dict()\n\ndef dfs(node):\n if not node:\n return 0\n if node in memo.keys():\n return memo[node]\n money = node.val\n if node.left:\n money += dfs(node.left.left) + dfs(node.left.right)\n if node.right:\n money += dfs(node.right.left) + dfs(node.right.right)\n r... | <|body_start_0|>
memo = dict()
def dfs(node):
if not node:
return 0
if node in memo.keys():
return memo[node]
money = node.val
if node.left:
money += dfs(node.left.left) + dfs(node.left.right)
if... | 分析：爷爷偷的钱 + 4个孙子偷的钱 VS 两个儿子偷的钱，哪个组合钱多，就当做当前节点能偷的最大钱数。 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""分析：爷爷偷的钱 + 4个孙子偷的钱 VS 两个儿子偷的钱，哪个组合钱多，就当做当前节点能偷的最大钱数。"""
def rob1(self, root: TreeNode) -> int:
"""DFS记忆优化，无需重复计算"""
<|body_0|>
def rob2(self, root: TreeNode) -> int:
"""DP树形版本 1. 定义状态: dp[node][j] 表示node结点能够获得的最大值。 a) j = 0 表示 node 结点不偷取 b) j = 1 表示 ... | stack_v2_sparse_classes_36k_train_012590 | 2,676 | no_license | [
{
"docstring": "DFS记忆优化，无需重复计算",
"name": "rob1",
"signature": "def rob1(self, root: TreeNode) -> int"
},
{
"docstring": "DP树形版本 1. 定义状态: dp[node][j] 表示node结点能够获得的最大值。 a) j = 0 表示 node 结点不偷取 b) j = 1 表示 node 结点偷取 2. 状态转移方程: 根据当前结点偷或者不偷，就决定了需要从哪些子结点里的对应的状态转移过来。 a) 如果当前结点偷，左右子结点均不能偷。 b) 如果当前结点不偷，左右... | 2 | stack_v2_sparse_classes_30k_train_011616 | Implement the Python class `Solution` described below.
Class description:
分析：爷爷偷的钱 + 4个孙子偷的钱 VS 两个儿子偷的钱，哪个组合钱多，就当做当前节点能偷的最大钱数。
Method signatures and docstrings:
- def rob1(self, root: TreeNode) -> int: DFS记忆优化，无需重复计算
- def rob2(self, root: TreeNode) -> int: DP树形版本 1. 定义状态: dp[node][j] 表示node结点能够获得的最大值。 a) j = 0 表示 no... | Implement the Python class `Solution` described below.
Class description:
分析：爷爷偷的钱 + 4个孙子偷的钱 VS 两个儿子偷的钱，哪个组合钱多，就当做当前节点能偷的最大钱数。
Method signatures and docstrings:
- def rob1(self, root: TreeNode) -> int: DFS记忆优化，无需重复计算
- def rob2(self, root: TreeNode) -> int: DP树形版本 1. 定义状态: dp[node][j] 表示node结点能够获得的最大值。 a) j = 0 表示 no... | 2bbb1640589aab34f2bc42489283033cc11fb885 | <|skeleton|>
class Solution:
"""分析：爷爷偷的钱 + 4个孙子偷的钱 VS 两个儿子偷的钱，哪个组合钱多，就当做当前节点能偷的最大钱数。"""
def rob1(self, root: TreeNode) -> int:
"""DFS记忆优化，无需重复计算"""
<|body_0|>
def rob2(self, root: TreeNode) -> int:
"""DP树形版本 1. 定义状态: dp[node][j] 表示node结点能够获得的最大值。 a) j = 0 表示 node 结点不偷取 b) j = 1 表示 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""分析：爷爷偷的钱 + 4个孙子偷的钱 VS 两个儿子偷的钱，哪个组合钱多，就当做当前节点能偷的最大钱数。"""
def rob1(self, root: TreeNode) -> int:
"""DFS记忆优化，无需重复计算"""
memo = dict()
def dfs(node):
if not node:
return 0
if node in memo.keys():
return memo[node]
... | the_stack_v2_python_sparse | 337_house-robber-iii.py | helloocc/algorithm | train | 1 |
22c8885b8c2db9ce65e0d8454cb7fd7a7ab4ad18 | [
"self.dgate_shape = dgate.get('shape')\nself.dgate_dtype = dgate.get('dtype')\nself.w_shape = input_weight.get('shape')\nself.w_dtype = input_weight.get('dtype')\nif dropout_mask:\n self.dropout_mask_shape = dropout_mask.get('shape')\n self.dropout_mask_dtype = dropout_mask.get('dtype')\nelse:\n self.dropo... | <|body_start_0|>
self.dgate_shape = dgate.get('shape')
self.dgate_dtype = dgate.get('dtype')
self.w_shape = input_weight.get('shape')
self.w_dtype = input_weight.get('dtype')
if dropout_mask:
self.dropout_mask_shape = dropout_mask.get('shape')
self.dropout... | Class: use to store LstmCellGradInput input parameters Modify : 2019-12-28 | LstmCellGradInput | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LstmCellGradInput:
"""Class: use to store LstmCellGradInput input parameters Modify : 2019-12-28"""
def __init__(self, dgate, input_weight, dropout_mask, dxt, dht, keep_prob, kernel_name):
"""init LstmCellGradInput base parameters Parameters ---------- dgate: dict the gradient of fou... | stack_v2_sparse_classes_36k_train_012591 | 19,409 | no_license | [
{
"docstring": "init LstmCellGradInput base parameters Parameters ---------- dgate: dict the gradient of four gate input_weight: dict weight dropout_mask: dict the mask of dropout keep_prob: dict the keep prob kernel_name: str op kernel name Returns ------- None",
"name": "__init__",
"signature": "def _... | 3 | null | Implement the Python class `LstmCellGradInput` described below.
Class description:
Class: use to store LstmCellGradInput input parameters Modify : 2019-12-28
Method signatures and docstrings:
- def __init__(self, dgate, input_weight, dropout_mask, dxt, dht, keep_prob, kernel_name): init LstmCellGradInput base paramet... | Implement the Python class `LstmCellGradInput` described below.
Class description:
Class: use to store LstmCellGradInput input parameters Modify : 2019-12-28
Method signatures and docstrings:
- def __init__(self, dgate, input_weight, dropout_mask, dxt, dht, keep_prob, kernel_name): init LstmCellGradInput base paramet... | 148511a31bfd195df889291946c43bb585acb546 | <|skeleton|>
class LstmCellGradInput:
"""Class: use to store LstmCellGradInput input parameters Modify : 2019-12-28"""
def __init__(self, dgate, input_weight, dropout_mask, dxt, dht, keep_prob, kernel_name):
"""init LstmCellGradInput base parameters Parameters ---------- dgate: dict the gradient of fou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LstmCellGradInput:
"""Class: use to store LstmCellGradInput input parameters Modify : 2019-12-28"""
def __init__(self, dgate, input_weight, dropout_mask, dxt, dht, keep_prob, kernel_name):
"""init LstmCellGradInput base parameters Parameters ---------- dgate: dict the gradient of four gate input_... | the_stack_v2_python_sparse | convertor/huawei/impl/basic_lstm_cell_input_grad.py | jizhuoran/caffe-huawei-atlas-convertor | train | 4 |
ec282bdb0904c758eb2cd13ceabfd6efa0a64df2 | [
"dp = BIT3(1010)\nteam = sorted(zip(scores, ages))\nfor score, age in team:\n preMax = dp.query(age)\n dp.update(age, preMax + score)\nreturn dp.query(1010)",
"n = len(scores)\nteam = sorted(zip(ages, scores))\ndp = [score for _, score in team]\nfor i in range(1, n):\n for j in range(i):\n if team... | <|body_start_0|>
dp = BIT3(1010)
team = sorted(zip(scores, ages))
for score, age in team:
preMax = dp.query(age)
dp.update(age, preMax + score)
return dp.query(1010)
<|end_body_0|>
<|body_start_1|>
n = len(scores)
team = sorted(zip(ages, scores))
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def bestTeamScore1(self, scores: List[int], ages: List[int]) -> int:
"""O(nlogn) 树状数组记录"""
<|body_0|>
def bestTeamScore2(self, scores: List[int], ages: List[int]) -> int:
"""O(n^2)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dp = BIT3(... | stack_v2_sparse_classes_36k_train_012592 | 2,692 | no_license | [
{
"docstring": "O(nlogn) 树状数组记录",
"name": "bestTeamScore1",
"signature": "def bestTeamScore1(self, scores: List[int], ages: List[int]) -> int"
},
{
"docstring": "O(n^2)",
"name": "bestTeamScore2",
"signature": "def bestTeamScore2(self, scores: List[int], ages: List[int]) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def bestTeamScore1(self, scores: List[int], ages: List[int]) -> int: O(nlogn) 树状数组记录
- def bestTeamScore2(self, scores: List[int], ages: List[int]) -> int: O(n^2) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def bestTeamScore1(self, scores: List[int], ages: List[int]) -> int: O(nlogn) 树状数组记录
- def bestTeamScore2(self, scores: List[int], ages: List[int]) -> int: O(n^2)
<|skeleton|>
c... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def bestTeamScore1(self, scores: List[int], ages: List[int]) -> int:
"""O(nlogn) 树状数组记录"""
<|body_0|>
def bestTeamScore2(self, scores: List[int], ages: List[int]) -> int:
"""O(n^2)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def bestTeamScore1(self, scores: List[int], ages: List[int]) -> int:
"""O(nlogn) 树状数组记录"""
dp = BIT3(1010)
team = sorted(zip(scores, ages))
for score, age in team:
preMax = dp.query(age)
dp.update(age, preMax + score)
return dp.query(10... | the_stack_v2_python_sparse | 11_动态规划/lis最长上升子序列问题/dp变形/1626. 无矛盾的最佳球队-分数和最大的LIS.py | 981377660LMT/algorithm-study | train | 225 | |
4afa32d14c64d257bf334a82061d307cda2fde20 | [
"self.access_key_id = access_key_id\nself.access_key_secret = access_key_secret\nself.region_id = region_id\nself.client = AcsClient(self.access_key_id, self.access_key_secret, self.region_id)",
"request = action_model()\nresponse = self.client.do_action_with_exception(request)\nresult = json.loads(response.decod... | <|body_start_0|>
self.access_key_id = access_key_id
self.access_key_secret = access_key_secret
self.region_id = region_id
self.client = AcsClient(self.access_key_id, self.access_key_secret, self.region_id)
<|end_body_0|>
<|body_start_1|>
request = action_model()
response... | 通过阿里云SDK获取API返回数据 | AliyunAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AliyunAPI:
"""通过阿里云SDK获取API返回数据"""
def __init__(self, access_key_id=settings.AccessKeyId, access_key_secret=settings.AccessKeySecret, region_id='cn-shenzhen'):
"""实例化 传入AccessKeyId ，AccessKeySecret，RegionId :param access_key_id: :param access_key_secret: :param region_id:"""
... | stack_v2_sparse_classes_36k_train_012593 | 3,689 | no_license | [
{
"docstring": "实例化 传入AccessKeyId ，AccessKeySecret，RegionId :param access_key_id: :param access_key_secret: :param region_id:",
"name": "__init__",
"signature": "def __init__(self, access_key_id=settings.AccessKeyId, access_key_secret=settings.AccessKeySecret, region_id='cn-shenzhen')"
},
{
"doc... | 6 | stack_v2_sparse_classes_30k_train_014134 | Implement the Python class `AliyunAPI` described below.
Class description:
通过阿里云SDK获取API返回数据
Method signatures and docstrings:
- def __init__(self, access_key_id=settings.AccessKeyId, access_key_secret=settings.AccessKeySecret, region_id='cn-shenzhen'): 实例化 传入AccessKeyId ，AccessKeySecret，RegionId :param access_key_id... | Implement the Python class `AliyunAPI` described below.
Class description:
通过阿里云SDK获取API返回数据
Method signatures and docstrings:
- def __init__(self, access_key_id=settings.AccessKeyId, access_key_secret=settings.AccessKeySecret, region_id='cn-shenzhen'): 实例化 传入AccessKeyId ，AccessKeySecret，RegionId :param access_key_id... | 57eeaa273c006af941be41499d2294d93105cf50 | <|skeleton|>
class AliyunAPI:
"""通过阿里云SDK获取API返回数据"""
def __init__(self, access_key_id=settings.AccessKeyId, access_key_secret=settings.AccessKeySecret, region_id='cn-shenzhen'):
"""实例化 传入AccessKeyId ，AccessKeySecret，RegionId :param access_key_id: :param access_key_secret: :param region_id:"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AliyunAPI:
"""通过阿里云SDK获取API返回数据"""
def __init__(self, access_key_id=settings.AccessKeyId, access_key_secret=settings.AccessKeySecret, region_id='cn-shenzhen'):
"""实例化 传入AccessKeyId ，AccessKeySecret，RegionId :param access_key_id: :param access_key_secret: :param region_id:"""
self.access_k... | the_stack_v2_python_sparse | utils/aliyun_sdk.py | hardyxia/AutoOps | train | 3 |
b56a033581dd529f285a21ea85b11b295499f7c2 | [
"recovery_hash = kwargs['recovery_hash']\nuser = Hasher.reverse_hash(recovery_hash)\nif user is not None:\n if user.is_active:\n request.session['recovery_user_pk'] = user.pk\n context = {'page_title': 'Reset Password', 'reset_password_form': ResetPasswordForm(auto_id=True)}\n context.update... | <|body_start_0|>
recovery_hash = kwargs['recovery_hash']
user = Hasher.reverse_hash(recovery_hash)
if user is not None:
if user.is_active:
request.session['recovery_user_pk'] = user.pk
context = {'page_title': 'Reset Password', 'reset_password_form': R... | This class allows user to reset password from recovery email. | ResetPasswordView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResetPasswordView:
"""This class allows user to reset password from recovery email."""
def get(self, request, *args, **kwargs):
"""Handles GET requests to 'account_reset_password' named route. Resets user password. Returns: HttpResponse with reset_password template if user is active ... | stack_v2_sparse_classes_36k_train_012594 | 17,941 | permissive | [
{
"docstring": "Handles GET requests to 'account_reset_password' named route. Resets user password. Returns: HttpResponse with reset_password template if user is active otherwise, flashes 'Account not activated' error to the session.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)... | 2 | null | Implement the Python class `ResetPasswordView` described below.
Class description:
This class allows user to reset password from recovery email.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Handles GET requests to 'account_reset_password' named route. Resets user password. Returns: Htt... | Implement the Python class `ResetPasswordView` described below.
Class description:
This class allows user to reset password from recovery email.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Handles GET requests to 'account_reset_password' named route. Resets user password. Returns: Htt... | 3704cbe6e69ba3e4c53401d3bbc339208e9ebccd | <|skeleton|>
class ResetPasswordView:
"""This class allows user to reset password from recovery email."""
def get(self, request, *args, **kwargs):
"""Handles GET requests to 'account_reset_password' named route. Resets user password. Returns: HttpResponse with reset_password template if user is active ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResetPasswordView:
"""This class allows user to reset password from recovery email."""
def get(self, request, *args, **kwargs):
"""Handles GET requests to 'account_reset_password' named route. Resets user password. Returns: HttpResponse with reset_password template if user is active otherwise, fl... | the_stack_v2_python_sparse | troupon/authentication/views.py | morristech/troupon | train | 0 |
a32d00fec978d9851d70d62bba109da632218e8b | [
"super(ODEFunc, self).__init__()\nself.l1 = nn.Linear(3, num_hidden)\nself.l2 = nn.Linear(num_hidden, num_hidden)\nself.l3 = nn.Linear(num_hidden, num_hidden)\nself.l4 = nn.Linear(num_hidden, 3)\nself.cond = nn.Linear(latent_len, num_hidden)\nself.tanh = nn.Tanh()\nself.relu = nn.ReLU()\nself.nfe = 0\nself.zeros = ... | <|body_start_0|>
super(ODEFunc, self).__init__()
self.l1 = nn.Linear(3, num_hidden)
self.l2 = nn.Linear(num_hidden, num_hidden)
self.l3 = nn.Linear(num_hidden, num_hidden)
self.l4 = nn.Linear(num_hidden, 3)
self.cond = nn.Linear(latent_len, num_hidden)
self.tanh =... | This refers to the dynamics function f(x,t) in a IVP defined as dh(x,t)/dt = f(x,t). For a given location (t) on point (x) trajectory, it returns the direction of 'flow'. Refer to Section 3 (Dynamics Equation) in the paper for details. | ODEFunc | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ODEFunc:
"""This refers to the dynamics function f(x,t) in a IVP defined as dh(x,t)/dt = f(x,t). For a given location (t) on point (x) trajectory, it returns the direction of 'flow'. Refer to Section 3 (Dynamics Equation) in the paper for details."""
def __init__(self, num_hidden=512, latent... | stack_v2_sparse_classes_36k_train_012595 | 17,869 | permissive | [
{
"docstring": "Initialization. num_hidden: number of nodes in a hidden layer latent_len: size of the latent code being used",
"name": "__init__",
"signature": "def __init__(self, num_hidden=512, latent_len=512)"
},
{
"docstring": "t: Torch tensor of shape (1,) xz: Torch tensor of shape (N, #pts... | 2 | stack_v2_sparse_classes_30k_train_004288 | Implement the Python class `ODEFunc` described below.
Class description:
This refers to the dynamics function f(x,t) in a IVP defined as dh(x,t)/dt = f(x,t). For a given location (t) on point (x) trajectory, it returns the direction of 'flow'. Refer to Section 3 (Dynamics Equation) in the paper for details.
Method si... | Implement the Python class `ODEFunc` described below.
Class description:
This refers to the dynamics function f(x,t) in a IVP defined as dh(x,t)/dt = f(x,t). For a given location (t) on point (x) trajectory, it returns the direction of 'flow'. Refer to Section 3 (Dynamics Equation) in the paper for details.
Method si... | 429c3d431b36358e43c61692e0d02df3ea255635 | <|skeleton|>
class ODEFunc:
"""This refers to the dynamics function f(x,t) in a IVP defined as dh(x,t)/dt = f(x,t). For a given location (t) on point (x) trajectory, it returns the direction of 'flow'. Refer to Section 3 (Dynamics Equation) in the paper for details."""
def __init__(self, num_hidden=512, latent... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ODEFunc:
"""This refers to the dynamics function f(x,t) in a IVP defined as dh(x,t)/dt = f(x,t). For a given location (t) on point (x) trajectory, it returns the direction of 'flow'. Refer to Section 3 (Dynamics Equation) in the paper for details."""
def __init__(self, num_hidden=512, latent_len=512):
... | the_stack_v2_python_sparse | model/meshflow.py | kierannp/3dsnet | train | 0 |
5e4198dcc9da98e7c4922d426edff324a07f9969 | [
"@self.router.get('/info', response_model=Dict[str, Info], response_model_exclude={'minzoom', 'maxzoom', 'center'}, response_model_exclude_none=True, responses={200: {'description': \"Return dataset's basic info or the list of available assets.\"}})\ndef info(src_path=Depends(self.path_dependency), asset_params=Dep... | <|body_start_0|>
@self.router.get('/info', response_model=Dict[str, Info], response_model_exclude={'minzoom', 'maxzoom', 'center'}, response_model_exclude_none=True, responses={200: {'description': "Return dataset's basic info or the list of available assets."}})
def info(src_path=Depends(self.path_depe... | Custom Tiler Factory for MultiBaseReader classes. Note: To be able to use the rio_tiler.io.MultiBaseReader we need to be able to pass a `assets` argument to most of its methods. By using the `AssetsBidxExprParams` for the `layer_dependency`, the .tile(), .point(), .preview() and the .part() methods will receive assets,... | MultiBaseTilerFactory | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiBaseTilerFactory:
"""Custom Tiler Factory for MultiBaseReader classes. Note: To be able to use the rio_tiler.io.MultiBaseReader we need to be able to pass a `assets` argument to most of its methods. By using the `AssetsBidxExprParams` for the `layer_dependency`, the .tile(), .point(), .previ... | stack_v2_sparse_classes_36k_train_012596 | 48,399 | permissive | [
{
"docstring": "Register /info endpoint.",
"name": "info",
"signature": "def info(self)"
},
{
"docstring": "Register /metadata endpoint.",
"name": "metadata",
"signature": "def metadata(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000007 | Implement the Python class `MultiBaseTilerFactory` described below.
Class description:
Custom Tiler Factory for MultiBaseReader classes. Note: To be able to use the rio_tiler.io.MultiBaseReader we need to be able to pass a `assets` argument to most of its methods. By using the `AssetsBidxExprParams` for the `layer_dep... | Implement the Python class `MultiBaseTilerFactory` described below.
Class description:
Custom Tiler Factory for MultiBaseReader classes. Note: To be able to use the rio_tiler.io.MultiBaseReader we need to be able to pass a `assets` argument to most of its methods. By using the `AssetsBidxExprParams` for the `layer_dep... | 2168c9284b39a46c4d1a095542c77addc690a738 | <|skeleton|>
class MultiBaseTilerFactory:
"""Custom Tiler Factory for MultiBaseReader classes. Note: To be able to use the rio_tiler.io.MultiBaseReader we need to be able to pass a `assets` argument to most of its methods. By using the `AssetsBidxExprParams` for the `layer_dependency`, the .tile(), .point(), .previ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiBaseTilerFactory:
"""Custom Tiler Factory for MultiBaseReader classes. Note: To be able to use the rio_tiler.io.MultiBaseReader we need to be able to pass a `assets` argument to most of its methods. By using the `AssetsBidxExprParams` for the `layer_dependency`, the .tile(), .point(), .preview() and the ... | the_stack_v2_python_sparse | src/titiler/core/titiler/core/factory.py | kylebarron/titiler | train | 0 |
77954a077f38705c155e2227989ef72a48571399 | [
"try:\n if isinstance(number, float) and (not number.is_integer()):\n raise ValueError\n number = int(number)\nexcept (TypeError, ValueError):\n raise PageNotAnInteger(_('That page number is not an integer'))\nif number < 1:\n raise EmptyPage(_('That page number is less than 1'))\nreturn number",... | <|body_start_0|>
try:
if isinstance(number, float) and (not number.is_integer()):
raise ValueError
number = int(number)
except (TypeError, ValueError):
raise PageNotAnInteger(_('That page number is not an integer'))
if number < 1:
r... | Paginator for `SumoSearch` classes. Inherits from the default django paginator with a few adjustments. The default paginator attempts to call len() on the `object_list` first, and then query for an individual page. However, since elasticsearch returns the total number of results at the same time as querying for a singl... | SumoSearchPaginator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SumoSearchPaginator:
"""Paginator for `SumoSearch` classes. Inherits from the default django paginator with a few adjustments. The default paginator attempts to call len() on the `object_list` first, and then query for an individual page. However, since elasticsearch returns the total number of r... | stack_v2_sparse_classes_36k_train_012597 | 16,315 | permissive | [
{
"docstring": "Validate the given 1-based page number, without checking if the number is greater than the total number of pages.",
"name": "pre_validate_number",
"signature": "def pre_validate_number(self, number)"
},
{
"docstring": "Return a Page object for the given 1-based page number.",
... | 2 | stack_v2_sparse_classes_30k_train_018215 | Implement the Python class `SumoSearchPaginator` described below.
Class description:
Paginator for `SumoSearch` classes. Inherits from the default django paginator with a few adjustments. The default paginator attempts to call len() on the `object_list` first, and then query for an individual page. However, since elas... | Implement the Python class `SumoSearchPaginator` described below.
Class description:
Paginator for `SumoSearch` classes. Inherits from the default django paginator with a few adjustments. The default paginator attempts to call len() on the `object_list` first, and then query for an individual page. However, since elas... | 67ec527bfc32c715bf9f29d5e01362c4903aebd2 | <|skeleton|>
class SumoSearchPaginator:
"""Paginator for `SumoSearch` classes. Inherits from the default django paginator with a few adjustments. The default paginator attempts to call len() on the `object_list` first, and then query for an individual page. However, since elasticsearch returns the total number of r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SumoSearchPaginator:
"""Paginator for `SumoSearch` classes. Inherits from the default django paginator with a few adjustments. The default paginator attempts to call len() on the `object_list` first, and then query for an individual page. However, since elasticsearch returns the total number of results at the... | the_stack_v2_python_sparse | kitsune/search/base.py | mozilla/kitsune | train | 1,218 |
8d3fbc72f95891fe45b86724380600c7616d8be8 | [
"super(Actor, self).__init__()\nself.log_std_min = log_std_min\nself.log_std_max = log_std_max\nself.hidden = nn.Linear(in_dim, 32)\nself.mu_layer = nn.Linear(32, out_dim)\nself.mu_layer = init_layer_uniform(self.mu_layer)\nself.log_std_layer = nn.Linear(32, out_dim)\nself.log_std_layer = init_layer_uniform(self.lo... | <|body_start_0|>
super(Actor, self).__init__()
self.log_std_min = log_std_min
self.log_std_max = log_std_max
self.hidden = nn.Linear(in_dim, 32)
self.mu_layer = nn.Linear(32, out_dim)
self.mu_layer = init_layer_uniform(self.mu_layer)
self.log_std_layer = nn.Linear... | Actor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Actor:
def __init__(self, in_dim: int, out_dim: int, log_std_min: int=-20, log_std_max: int=0):
"""Initialize."""
<|body_0|>
def forward(self, state: torch.Tensor) -> torch.Tensor:
"""Forward method implementation."""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_012598 | 13,315 | no_license | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, in_dim: int, out_dim: int, log_std_min: int=-20, log_std_max: int=0)"
},
{
"docstring": "Forward method implementation.",
"name": "forward",
"signature": "def forward(self, state: torch.Tensor) -> torch.Te... | 2 | stack_v2_sparse_classes_30k_train_013510 | Implement the Python class `Actor` described below.
Class description:
Implement the Actor class.
Method signatures and docstrings:
- def __init__(self, in_dim: int, out_dim: int, log_std_min: int=-20, log_std_max: int=0): Initialize.
- def forward(self, state: torch.Tensor) -> torch.Tensor: Forward method implementa... | Implement the Python class `Actor` described below.
Class description:
Implement the Actor class.
Method signatures and docstrings:
- def __init__(self, in_dim: int, out_dim: int, log_std_min: int=-20, log_std_max: int=0): Initialize.
- def forward(self, state: torch.Tensor) -> torch.Tensor: Forward method implementa... | 14ddfb81295c349acc2ede7588ebc73c235246c0 | <|skeleton|>
class Actor:
def __init__(self, in_dim: int, out_dim: int, log_std_min: int=-20, log_std_max: int=0):
"""Initialize."""
<|body_0|>
def forward(self, state: torch.Tensor) -> torch.Tensor:
"""Forward method implementation."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Actor:
def __init__(self, in_dim: int, out_dim: int, log_std_min: int=-20, log_std_max: int=0):
"""Initialize."""
super(Actor, self).__init__()
self.log_std_min = log_std_min
self.log_std_max = log_std_max
self.hidden = nn.Linear(in_dim, 32)
self.mu_layer = nn.L... | the_stack_v2_python_sparse | PPO_GAE_TEST/PPO_gae_test2.py | namjiwon1023/Reinforcement_learning | train | 2 | |
82642c71d32ee2f4d612e7684df97cf930b112eb | [
"errors = {}\nif user_input is not None:\n try:\n device = await self._async_get_device(user_input[CONF_HOST])\n except GridNetConnectionError:\n errors['base'] = 'cannot_connect'\n else:\n await self.async_set_unique_id(device.n2g_id, raise_on_progress=False)\n self._abort_if_u... | <|body_start_0|>
errors = {}
if user_input is not None:
try:
device = await self._async_get_device(user_input[CONF_HOST])
except GridNetConnectionError:
errors['base'] = 'cannot_connect'
else:
await self.async_set_unique... | Config flow for Pure Energie integration. | PureEnergieFlowHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PureEnergieFlowHandler:
"""Config flow for Pure Energie integration."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle a flow initialized by the user."""
<|body_0|>
async def async_step_zeroconf(self, discovery_info: zero... | stack_v2_sparse_classes_36k_train_012599 | 3,686 | permissive | [
{
"docstring": "Handle a flow initialized by the user.",
"name": "async_step_user",
"signature": "async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult"
},
{
"docstring": "Handle zeroconf discovery.",
"name": "async_step_zeroconf",
"signature": "async def ... | 4 | null | Implement the Python class `PureEnergieFlowHandler` described below.
Class description:
Config flow for Pure Energie integration.
Method signatures and docstrings:
- async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult: Handle a flow initialized by the user.
- async def async_step_zer... | Implement the Python class `PureEnergieFlowHandler` described below.
Class description:
Config flow for Pure Energie integration.
Method signatures and docstrings:
- async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult: Handle a flow initialized by the user.
- async def async_step_zer... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class PureEnergieFlowHandler:
"""Config flow for Pure Energie integration."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle a flow initialized by the user."""
<|body_0|>
async def async_step_zeroconf(self, discovery_info: zero... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PureEnergieFlowHandler:
"""Config flow for Pure Energie integration."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle a flow initialized by the user."""
errors = {}
if user_input is not None:
try:
devic... | the_stack_v2_python_sparse | homeassistant/components/pure_energie/config_flow.py | home-assistant/core | train | 35,501 |
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