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value | star_events_count int64 0 209k |
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4064ed106fadaa742a34723a1c84a69e82620870 | [
"global task_tree\n\ndef simulation():\n return None\nself.suspended_tree = task_tree\nself.world_state, self.objects2attached = BulletWorld.current_bullet_world.save_state()\nself.simulated_root = TaskTreeNode(code=Code(simulation))\ntask_tree = self.simulated_root\npybullet.addUserDebugText('Simulating...', [0... | <|body_start_0|>
global task_tree
def simulation():
return None
self.suspended_tree = task_tree
self.world_state, self.objects2attached = BulletWorld.current_bullet_world.save_state()
self.simulated_root = TaskTreeNode(code=Code(simulation))
task_tree = self.... | TaskTree for execution in a 'new' simulation. | SimulatedTaskTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimulatedTaskTree:
"""TaskTree for execution in a 'new' simulation."""
def __enter__(self):
"""At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are then available inside the with statement."""
<|bod... | stack_v2_sparse_classes_10k_train_002700 | 11,387 | no_license | [
{
"docstring": "At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are then available inside the with statement.",
"name": "__enter__",
"signature": "def __enter__(self)"
},
{
"docstring": "Restore the old state at the e... | 2 | stack_v2_sparse_classes_30k_train_006993 | Implement the Python class `SimulatedTaskTree` described below.
Class description:
TaskTree for execution in a 'new' simulation.
Method signatures and docstrings:
- def __enter__(self): At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are t... | Implement the Python class `SimulatedTaskTree` described below.
Class description:
TaskTree for execution in a 'new' simulation.
Method signatures and docstrings:
- def __enter__(self): At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are t... | f9ef666d6d4685660c9517652f2c568ed2c9367c | <|skeleton|>
class SimulatedTaskTree:
"""TaskTree for execution in a 'new' simulation."""
def __enter__(self):
"""At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are then available inside the with statement."""
<|bod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SimulatedTaskTree:
"""TaskTree for execution in a 'new' simulation."""
def __enter__(self):
"""At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are then available inside the with statement."""
global task_tree
... | the_stack_v2_python_sparse | src/pycram/task.py | cram2/pycram | train | 12 |
b6ddebe8dc5e5e78ff829ed644eb53446b0c43b4 | [
"if not len(nums):\n return\nindex = len(nums) - 2\nwhile index >= 0 and nums[index] >= nums[index + 1]:\n index -= 1\nif index >= 0:\n i = index + 1\n while i < len(nums) and nums[i] > nums[index]:\n i += 1\n nums[i - 1], nums[index] = (nums[index], nums[i - 1])\nleft, right = (index + 1, len... | <|body_start_0|>
if not len(nums):
return
index = len(nums) - 2
while index >= 0 and nums[index] >= nums[index + 1]:
index -= 1
if index >= 0:
i = index + 1
while i < len(nums) and nums[i] > nums[index]:
i += 1
n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextPermutation(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k_train_002701 | 1,580 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.",
"name": "nextPermutation",
"signature": "def nextPermutation(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "permuteUnique",
"signature": "d... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextPermutation(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def permuteUnique(self, nums): :type nums: List[int] :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextPermutation(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def permuteUnique(self, nums): :type nums: List[int] :... | 9b82e3bd1b404e3cff31469986577ceec3924f73 | <|skeleton|>
class Solution:
def nextPermutation(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def nextPermutation(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
if not len(nums):
return
index = len(nums) - 2
while index >= 0 and nums[index] >= nums[index + 1]:
index -= 1
... | the_stack_v2_python_sparse | Python/47PermutationsII.py | Qiumy/leetcode | train | 0 | |
ea0e3eafbbd443920d6add021877bd4d85b9d0bf | [
"self.exist = False\nif address is not None:\n self.exist = True\n if len(address) == 7:\n if address[0] == 1:\n self.universe, self.address_start, balance = ((address[4], address[5], cut_little_ledstrip), (address[1], address[2], 0))[idx_led < cut_little_ledstrip]\n self.address_... | <|body_start_0|>
self.exist = False
if address is not None:
self.exist = True
if len(address) == 7:
if address[0] == 1:
self.universe, self.address_start, balance = ((address[4], address[5], cut_little_ledstrip), (address[1], address[2], 0))[id... | Represent a led of the cube | Led | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Led:
"""Represent a led of the cube"""
def __init__(self, address, idx_led):
"""Constructor of led :param address: tuple of led address :param idx_led: led index"""
<|body_0|>
def show(self, brightness):
"""Illuminate the led with brightness :param brightness: in... | stack_v2_sparse_classes_10k_train_002702 | 3,537 | no_license | [
{
"docstring": "Constructor of led :param address: tuple of led address :param idx_led: led index",
"name": "__init__",
"signature": "def __init__(self, address, idx_led)"
},
{
"docstring": "Illuminate the led with brightness :param brightness: int between 0 and 15 include :raise exception",
... | 2 | stack_v2_sparse_classes_30k_train_003014 | Implement the Python class `Led` described below.
Class description:
Represent a led of the cube
Method signatures and docstrings:
- def __init__(self, address, idx_led): Constructor of led :param address: tuple of led address :param idx_led: led index
- def show(self, brightness): Illuminate the led with brightness ... | Implement the Python class `Led` described below.
Class description:
Represent a led of the cube
Method signatures and docstrings:
- def __init__(self, address, idx_led): Constructor of led :param address: tuple of led address :param idx_led: led index
- def show(self, brightness): Illuminate the led with brightness ... | de1408317d5071b7e0c6b2fea6f281660115d728 | <|skeleton|>
class Led:
"""Represent a led of the cube"""
def __init__(self, address, idx_led):
"""Constructor of led :param address: tuple of led address :param idx_led: led index"""
<|body_0|>
def show(self, brightness):
"""Illuminate the led with brightness :param brightness: in... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Led:
"""Represent a led of the cube"""
def __init__(self, address, idx_led):
"""Constructor of led :param address: tuple of led address :param idx_led: led index"""
self.exist = False
if address is not None:
self.exist = True
if len(address) == 7:
... | the_stack_v2_python_sparse | api/package/cube/led.py | HE-Arc/Extrusion---web-interface | train | 4 |
91425a498569e7a7513dbf0e04d734cbc4aff1bb | [
"dict.__init__(data)\nself.data = data\nfor cate in data:\n for arg in cate:\n if not isinstance(data[cate][arg], types.ListType):\n continue\n if not (isinstance(data[cate][arg][1], IntVar) or isinstance(data[cate][arg][1], StringVar)):\n continue\n value = data[cate][... | <|body_start_0|>
dict.__init__(data)
self.data = data
for cate in data:
for arg in cate:
if not isinstance(data[cate][arg], types.ListType):
continue
if not (isinstance(data[cate][arg][1], IntVar) or isinstance(data[cate][arg][1], S... | dataStream | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class dataStream:
def __init__(self, data):
"""a datastream manager depend on python's dict"""
<|body_0|>
def synchro(self):
"""synchro the dataStream from Tkinter *Var to string/int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dict.__init__(data)
... | stack_v2_sparse_classes_10k_train_002703 | 1,263 | no_license | [
{
"docstring": "a datastream manager depend on python's dict",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "synchro the dataStream from Tkinter *Var to string/int",
"name": "synchro",
"signature": "def synchro(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000141 | Implement the Python class `dataStream` described below.
Class description:
Implement the dataStream class.
Method signatures and docstrings:
- def __init__(self, data): a datastream manager depend on python's dict
- def synchro(self): synchro the dataStream from Tkinter *Var to string/int | Implement the Python class `dataStream` described below.
Class description:
Implement the dataStream class.
Method signatures and docstrings:
- def __init__(self, data): a datastream manager depend on python's dict
- def synchro(self): synchro the dataStream from Tkinter *Var to string/int
<|skeleton|>
class dataStr... | 8f2af73f6bfe0c6d4d1d0d9a8572b31e4f91e66c | <|skeleton|>
class dataStream:
def __init__(self, data):
"""a datastream manager depend on python's dict"""
<|body_0|>
def synchro(self):
"""synchro the dataStream from Tkinter *Var to string/int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class dataStream:
def __init__(self, data):
"""a datastream manager depend on python's dict"""
dict.__init__(data)
self.data = data
for cate in data:
for arg in cate:
if not isinstance(data[cate][arg], types.ListType):
continue
... | the_stack_v2_python_sparse | dataStream.py | humanfans/ncep-displayer | train | 0 | |
8eac60ad69e7215271e1d35ee0d5a51f4a7283f9 | [
"stack, ret = ([], 0)\nfor p in prices:\n while stack and stack[-1] > p:\n stack.pop()\n if stack == []:\n stack.append(p)\n else:\n ret = max(ret, p - stack[-1])\nreturn ret",
"minPrice, maxProfit = (float('inf'), 0)\nfor i in xrange(len(prices)):\n minPrice = min(minPrice, price... | <|body_start_0|>
stack, ret = ([], 0)
for p in prices:
while stack and stack[-1] > p:
stack.pop()
if stack == []:
stack.append(p)
else:
ret = max(ret, p - stack[-1])
return ret
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
stack, ret = ([], 0)
for p in pri... | stack_v2_sparse_classes_10k_train_002704 | 892 | no_license | [
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit",
"signature": "def maxProfit(self, prices)"
},
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit",
"signature": "def maxProfit(self, prices)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005528 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, prices): :type prices: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, prices): :type prices: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxProf... | 1a0dbcabb0f454a4fdcc31af9b919f5d30664335 | <|skeleton|>
class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
stack, ret = ([], 0)
for p in prices:
while stack and stack[-1] > p:
stack.pop()
if stack == []:
stack.append(p)
else:
re... | the_stack_v2_python_sparse | 121. Best Time to Buy and Sell Stock.py | haomingchan0811/Leetcode | train | 0 | |
4cf6b2cf2af79f78d078e16810cd2c856a6c769e | [
"def mid_recur(root):\n nonlocal recorder\n if root:\n if not mid_recur(root.left):\n return False\n if recorder is not None and root.val <= recorder:\n return False\n else:\n recorder = root.val\n if not mid_recur(root.right):\n return F... | <|body_start_0|>
def mid_recur(root):
nonlocal recorder
if root:
if not mid_recur(root.left):
return False
if recorder is not None and root.val <= recorder:
return False
else:
reco... | BSTTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BSTTree:
def isValidBST(root):
"""98.mid_验证二叉搜索树.py 判断是否合法二叉树（中序遍历，必须是递增序列！）"""
<|body_0|>
def isSameTree(p, q):
"""100.easy_相同的树.py 判断两个树是否完全一样"""
<|body_1|>
def searchBST(root, val):
"""700.easy_二叉搜索树中的搜索.py 在二叉树中搜索某个值 ，若不存在返回None"""
<|... | stack_v2_sparse_classes_10k_train_002705 | 3,601 | no_license | [
{
"docstring": "98.mid_验证二叉搜索树.py 判断是否合法二叉树（中序遍历，必须是递增序列！）",
"name": "isValidBST",
"signature": "def isValidBST(root)"
},
{
"docstring": "100.easy_相同的树.py 判断两个树是否完全一样",
"name": "isSameTree",
"signature": "def isSameTree(p, q)"
},
{
"docstring": "700.easy_二叉搜索树中的搜索.py 在二叉树中搜索某个值 ，... | 5 | null | Implement the Python class `BSTTree` described below.
Class description:
Implement the BSTTree class.
Method signatures and docstrings:
- def isValidBST(root): 98.mid_验证二叉搜索树.py 判断是否合法二叉树（中序遍历，必须是递增序列！）
- def isSameTree(p, q): 100.easy_相同的树.py 判断两个树是否完全一样
- def searchBST(root, val): 700.easy_二叉搜索树中的搜索.py 在二叉树中搜索某个值 ，... | Implement the Python class `BSTTree` described below.
Class description:
Implement the BSTTree class.
Method signatures and docstrings:
- def isValidBST(root): 98.mid_验证二叉搜索树.py 判断是否合法二叉树（中序遍历，必须是递增序列！）
- def isSameTree(p, q): 100.easy_相同的树.py 判断两个树是否完全一样
- def searchBST(root, val): 700.easy_二叉搜索树中的搜索.py 在二叉树中搜索某个值 ，... | 576de9b993f7763789d25a995702b40c9bc6fa57 | <|skeleton|>
class BSTTree:
def isValidBST(root):
"""98.mid_验证二叉搜索树.py 判断是否合法二叉树（中序遍历，必须是递增序列！）"""
<|body_0|>
def isSameTree(p, q):
"""100.easy_相同的树.py 判断两个树是否完全一样"""
<|body_1|>
def searchBST(root, val):
"""700.easy_二叉搜索树中的搜索.py 在二叉树中搜索某个值 ，若不存在返回None"""
<|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BSTTree:
def isValidBST(root):
"""98.mid_验证二叉搜索树.py 判断是否合法二叉树（中序遍历，必须是递增序列！）"""
def mid_recur(root):
nonlocal recorder
if root:
if not mid_recur(root.left):
return False
if recorder is not None and root.val <= recorder... | the_stack_v2_python_sparse | 0.leetcode/3.刷题/1.数据结构系列/2.树形结构/1.二叉查找树/bsttree.py | GMwang550146647/network | train | 0 | |
c2db422cc7a9bb4ec61ea1f37c28c02e9da345ff | [
"try:\n with datastore_services.get_ndb_context():\n question_summary = question_services.get_question_summary_from_model(question_summary_model)\n question_summary.version = question_version\n question_summary.validate()\nexcept Exception as e:\n logging.exception(e)\n return result.Err((ques... | <|body_start_0|>
try:
with datastore_services.get_ndb_context():
question_summary = question_services.get_question_summary_from_model(question_summary_model)
question_summary.version = question_version
question_summary.validate()
except Exception as e:... | Job that audits PopulateQuestionSummaryVersionOneOffJob. | AuditPopulateQuestionSummaryVersionOneOffJob | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuditPopulateQuestionSummaryVersionOneOffJob:
"""Job that audits PopulateQuestionSummaryVersionOneOffJob."""
def _update_and_validate_summary_model(question_version: int, question_summary_model: question_models.QuestionSummaryModel) -> result.Result[Tuple[str, question_models.QuestionSummary... | stack_v2_sparse_classes_10k_train_002706 | 12,101 | permissive | [
{
"docstring": "Transform question summary model into question summary object, add a version field and return the populated summary model. Args: question_version: int. The version number in the corresponding question domain object. question_summary_model: QuestionSummaryModel. The question summary model to migr... | 2 | stack_v2_sparse_classes_30k_train_004538 | Implement the Python class `AuditPopulateQuestionSummaryVersionOneOffJob` described below.
Class description:
Job that audits PopulateQuestionSummaryVersionOneOffJob.
Method signatures and docstrings:
- def _update_and_validate_summary_model(question_version: int, question_summary_model: question_models.QuestionSumma... | Implement the Python class `AuditPopulateQuestionSummaryVersionOneOffJob` described below.
Class description:
Job that audits PopulateQuestionSummaryVersionOneOffJob.
Method signatures and docstrings:
- def _update_and_validate_summary_model(question_version: int, question_summary_model: question_models.QuestionSumma... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class AuditPopulateQuestionSummaryVersionOneOffJob:
"""Job that audits PopulateQuestionSummaryVersionOneOffJob."""
def _update_and_validate_summary_model(question_version: int, question_summary_model: question_models.QuestionSummaryModel) -> result.Result[Tuple[str, question_models.QuestionSummary... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AuditPopulateQuestionSummaryVersionOneOffJob:
"""Job that audits PopulateQuestionSummaryVersionOneOffJob."""
def _update_and_validate_summary_model(question_version: int, question_summary_model: question_models.QuestionSummaryModel) -> result.Result[Tuple[str, question_models.QuestionSummaryModel], Tuple... | the_stack_v2_python_sparse | core/jobs/batch_jobs/question_migration_jobs.py | oppia/oppia | train | 6,172 |
87c34a5ceb0c54dde76385d13c44a47e4f08876a | [
"username = 'test@test.com'\npassword = 'toto'\nself.client.post(reverse(register), {'username': username, 'password': password})\nresponse = self.client.post(reverse(obtain_auth_token), {'username': username, 'password': password}, format='json')\nself.token = json.loads(response.content)['token']",
"self.client... | <|body_start_0|>
username = 'test@test.com'
password = 'toto'
self.client.post(reverse(register), {'username': username, 'password': password})
response = self.client.post(reverse(obtain_auth_token), {'username': username, 'password': password}, format='json')
self.token = json.l... | Test access to API for users with API rights. | TestAPIAccess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAPIAccess:
"""Test access to API for users with API rights."""
def setUp(self):
"""First register a user (automatically registered to free plan)."""
<|body_0|>
def test_api_access_ok(self):
"""Test API access by looking up for siemens.com."""
<|body_1... | stack_v2_sparse_classes_10k_train_002707 | 8,751 | no_license | [
{
"docstring": "First register a user (automatically registered to free plan).",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test API access by looking up for siemens.com.",
"name": "test_api_access_ok",
"signature": "def test_api_access_ok(self)"
},
{
"doc... | 4 | stack_v2_sparse_classes_30k_train_003402 | Implement the Python class `TestAPIAccess` described below.
Class description:
Test access to API for users with API rights.
Method signatures and docstrings:
- def setUp(self): First register a user (automatically registered to free plan).
- def test_api_access_ok(self): Test API access by looking up for siemens.com... | Implement the Python class `TestAPIAccess` described below.
Class description:
Test access to API for users with API rights.
Method signatures and docstrings:
- def setUp(self): First register a user (automatically registered to free plan).
- def test_api_access_ok(self): Test API access by looking up for siemens.com... | 9c0027b84d8dee6044ff28362e2b2b90c1759b90 | <|skeleton|>
class TestAPIAccess:
"""Test access to API for users with API rights."""
def setUp(self):
"""First register a user (automatically registered to free plan)."""
<|body_0|>
def test_api_access_ok(self):
"""Test API access by looking up for siemens.com."""
<|body_1... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestAPIAccess:
"""Test access to API for users with API rights."""
def setUp(self):
"""First register a user (automatically registered to free plan)."""
username = 'test@test.com'
password = 'toto'
self.client.post(reverse(register), {'username': username, 'password': pass... | the_stack_v2_python_sparse | django_project/api_core/tests.py | juliensalinas/python-django-api-reactjs-frontend-slate-documentation-various-client-libs | train | 3 |
85f30c89e58ba7e8b1be0a5d5b405614dd7e6806 | [
"self.nb_sub_images = nb_sub_images\nself.window_size = window_size\nself.recovery = recovery\nself.image_horiz_size = image_horiz_size",
"if idx < self.nb_sub_images - 1:\n pixel_step = self.window_size - self.recovery\n return (idx * pixel_step, idx * pixel_step + self.window_size)\nelif idx == self.nb_su... | <|body_start_0|>
self.nb_sub_images = nb_sub_images
self.window_size = window_size
self.recovery = recovery
self.image_horiz_size = image_horiz_size
<|end_body_0|>
<|body_start_1|>
if idx < self.nb_sub_images - 1:
pixel_step = self.window_size - self.recovery
... | Class that returns the limits of the slice of a lane. | LaneIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LaneIterator:
"""Class that returns the limits of the slice of a lane."""
def __init__(self, nb_sub_images, window_size, recovery, image_horiz_size):
"""Construct the lane iterator. Args: nb_sub_images (integer): the number of sub-images that has been sliced. window_size (integer): t... | stack_v2_sparse_classes_10k_train_002708 | 2,071 | no_license | [
{
"docstring": "Construct the lane iterator. Args: nb_sub_images (integer): the number of sub-images that has been sliced. window_size (integer): the width of the sub-image. recovery (integer): the number of pixels to be taken twice per sub-image. image_horiz_size (integer): the horizontal size of the original ... | 2 | stack_v2_sparse_classes_30k_train_003298 | Implement the Python class `LaneIterator` described below.
Class description:
Class that returns the limits of the slice of a lane.
Method signatures and docstrings:
- def __init__(self, nb_sub_images, window_size, recovery, image_horiz_size): Construct the lane iterator. Args: nb_sub_images (integer): the number of ... | Implement the Python class `LaneIterator` described below.
Class description:
Class that returns the limits of the slice of a lane.
Method signatures and docstrings:
- def __init__(self, nb_sub_images, window_size, recovery, image_horiz_size): Construct the lane iterator. Args: nb_sub_images (integer): the number of ... | 237ca81580db43525d8945017c0565b9722046ad | <|skeleton|>
class LaneIterator:
"""Class that returns the limits of the slice of a lane."""
def __init__(self, nb_sub_images, window_size, recovery, image_horiz_size):
"""Construct the lane iterator. Args: nb_sub_images (integer): the number of sub-images that has been sliced. window_size (integer): t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LaneIterator:
"""Class that returns the limits of the slice of a lane."""
def __init__(self, nb_sub_images, window_size, recovery, image_horiz_size):
"""Construct the lane iterator. Args: nb_sub_images (integer): the number of sub-images that has been sliced. window_size (integer): the width of t... | the_stack_v2_python_sparse | src/d5_model_evaluation/slice_lane/image_magnifier/lane_iterator.py | remingtonCarmi/TrackingSwimmingENPC | train | 0 |
55b5e2f7bf8b0a8465c3027cc138873c0433ffad | [
"job_thread = JobThread(queue_name, sleep_time, from_right)\njob_thread.setDaemon(True)\njob_thread.start()\nself.threads[job_thread.getName()] = job_thread\nsys.stdout.write('start a job thread, name: %s, ident: %s, queue_name: %s\\n' % (job_thread.getName(), job_thread.ident, queue_name))",
"if not job_name in ... | <|body_start_0|>
job_thread = JobThread(queue_name, sleep_time, from_right)
job_thread.setDaemon(True)
job_thread.start()
self.threads[job_thread.getName()] = job_thread
sys.stdout.write('start a job thread, name: %s, ident: %s, queue_name: %s\n' % (job_thread.getName(), job_thre... | 管理工作线程， 开启/停止工作线程 | JobThreadManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobThreadManager:
"""管理工作线程， 开启/停止工作线程"""
def add(self, queue_name, sleep_time, from_right=True):
"""开启一个工作线程"""
<|body_0|>
def stop(self, job_name):
"""安全的停止一个工作线程 正在转换中的时候，会等待转换完成后自动退出"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
job_thread... | stack_v2_sparse_classes_10k_train_002709 | 2,159 | no_license | [
{
"docstring": "开启一个工作线程",
"name": "add",
"signature": "def add(self, queue_name, sleep_time, from_right=True)"
},
{
"docstring": "安全的停止一个工作线程 正在转换中的时候，会等待转换完成后自动退出",
"name": "stop",
"signature": "def stop(self, job_name)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007042 | Implement the Python class `JobThreadManager` described below.
Class description:
管理工作线程， 开启/停止工作线程
Method signatures and docstrings:
- def add(self, queue_name, sleep_time, from_right=True): 开启一个工作线程
- def stop(self, job_name): 安全的停止一个工作线程 正在转换中的时候，会等待转换完成后自动退出 | Implement the Python class `JobThreadManager` described below.
Class description:
管理工作线程， 开启/停止工作线程
Method signatures and docstrings:
- def add(self, queue_name, sleep_time, from_right=True): 开启一个工作线程
- def stop(self, job_name): 安全的停止一个工作线程 正在转换中的时候，会等待转换完成后自动退出
<|skeleton|>
class JobThreadManager:
"""管理工作线程， 开启... | 05dae4225db1fedbe738d317bf44aca8604c9eed | <|skeleton|>
class JobThreadManager:
"""管理工作线程， 开启/停止工作线程"""
def add(self, queue_name, sleep_time, from_right=True):
"""开启一个工作线程"""
<|body_0|>
def stop(self, job_name):
"""安全的停止一个工作线程 正在转换中的时候，会等待转换完成后自动退出"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class JobThreadManager:
"""管理工作线程， 开启/停止工作线程"""
def add(self, queue_name, sleep_time, from_right=True):
"""开启一个工作线程"""
job_thread = JobThread(queue_name, sleep_time, from_right)
job_thread.setDaemon(True)
job_thread.start()
self.threads[job_thread.getName()] = job_thread... | the_stack_v2_python_sparse | Python/PythonC++Scala/script/.svn/pristine/55/55b5e2f7bf8b0a8465c3027cc138873c0433ffad.svn-base | cash2one/dataMining-1 | train | 0 |
ce4f3652ea3f9af32a181eb52fa9f879083b2c91 | [
"orig_query = self.request.get('query')\nlogging.debug('Received raw query %r', orig_query)\nif not self.QUERY_LIMIT_RE.search(orig_query):\n orig_query += ' LIMIT 30'\nquery = orig_query\nquery, columns = self._RemoveSelectFromQuery(query)\nif query == orig_query and columns == self.DEFAULT_COLUMNS:\n orig_q... | <|body_start_0|>
orig_query = self.request.get('query')
logging.debug('Received raw query %r', orig_query)
if not self.QUERY_LIMIT_RE.search(orig_query):
orig_query += ' LIMIT 30'
query = orig_query
query, columns = self._RemoveSelectFromQuery(query)
if query ... | Provide interface for interacting with DB. | MainPage | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainPage:
"""Provide interface for interacting with DB."""
def get(self):
"""Support GET to stats page."""
<|body_0|>
def _RemoveSelectFromQuery(self, query):
"""Remove SELECT clause from |query|, return tuple (new_query, columns)."""
<|body_1|>
def ... | stack_v2_sparse_classes_10k_train_002710 | 9,774 | permissive | [
{
"docstring": "Support GET to stats page.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Remove SELECT clause from |query|, return tuple (new_query, columns).",
"name": "_RemoveSelectFromQuery",
"signature": "def _RemoveSelectFromQuery(self, query)"
},
{
"docst... | 5 | null | Implement the Python class `MainPage` described below.
Class description:
Provide interface for interacting with DB.
Method signatures and docstrings:
- def get(self): Support GET to stats page.
- def _RemoveSelectFromQuery(self, query): Remove SELECT clause from |query|, return tuple (new_query, columns).
- def _Adj... | Implement the Python class `MainPage` described below.
Class description:
Provide interface for interacting with DB.
Method signatures and docstrings:
- def get(self): Support GET to stats page.
- def _RemoveSelectFromQuery(self, query): Remove SELECT clause from |query|, return tuple (new_query, columns).
- def _Adj... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class MainPage:
"""Provide interface for interacting with DB."""
def get(self):
"""Support GET to stats page."""
<|body_0|>
def _RemoveSelectFromQuery(self, query):
"""Remove SELECT clause from |query|, return tuple (new_query, columns)."""
<|body_1|>
def ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MainPage:
"""Provide interface for interacting with DB."""
def get(self):
"""Support GET to stats page."""
orig_query = self.request.get('query')
logging.debug('Received raw query %r', orig_query)
if not self.QUERY_LIMIT_RE.search(orig_query):
orig_query += ' L... | the_stack_v2_python_sparse | third_party/chromite/appengine/chromiumos-build-stats/stats.py | metux/chromium-suckless | train | 5 |
b36fcfe7d6d5350afb995f1862d974729d01e333 | [
"parser.add_argument('appname', help='The sample app name, e.g. \"finance\".')\nparser.add_argument('--instance-id', required=True, type=str, help='The Cloud Spanner instance ID for the sample app.')\nparser.add_argument('--database-id', type=str, help='ID of the new Cloud Spanner database to create for the sample ... | <|body_start_0|>
parser.add_argument('appname', help='The sample app name, e.g. "finance".')
parser.add_argument('--instance-id', required=True, type=str, help='The Cloud Spanner instance ID for the sample app.')
parser.add_argument('--database-id', type=str, help='ID of the new Cloud Spanner da... | Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application. | Init | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Init:
"""Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args... | stack_v2_sparse_classes_10k_train_002711 | 9,146 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are allowed.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring"... | 2 | stack_v2_sparse_classes_30k_val_000148 | Implement the Python class `Init` described below.
Class description:
Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application.
Method signatures and docstrings:
- def Args(parser): Args is call... | Implement the Python class `Init` described below.
Class description:
Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application.
Method signatures and docstrings:
- def Args(parser): Args is call... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class Init:
"""Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Init:
"""Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An ... | the_stack_v2_python_sparse | lib/surface/spanner/samples/init.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
bb0c5155111e0c6ad0be0dcc95af68e9fde7e24b | [
"response = self.client.get(reverse('education:index'))\nself.assertEqual(response.status_code, 200)\nself.assertEqual(response.context.get('json_data'), None)\nself.assertContains(response, 'High School Graduation')\nself.assertContains(response, 'How Rates Were Calculated')\nself.assertContains(response, 'Home')\... | <|body_start_0|>
response = self.client.get(reverse('education:index'))
self.assertEqual(response.status_code, 200)
self.assertEqual(response.context.get('json_data'), None)
self.assertContains(response, 'High School Graduation')
self.assertContains(response, 'How Rates Were Calc... | EducationIndexViewTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EducationIndexViewTests:
def test_no_data(self):
"""If no data is in the database, no content is displayed but there is no map of graudation rates."""
<|body_0|>
def test_with_data(self):
"""If state data is in the database, make sure the conents renders and a graph ... | stack_v2_sparse_classes_10k_train_002712 | 9,266 | no_license | [
{
"docstring": "If no data is in the database, no content is displayed but there is no map of graudation rates.",
"name": "test_no_data",
"signature": "def test_no_data(self)"
},
{
"docstring": "If state data is in the database, make sure the conents renders and a graph of the graudation rates i... | 2 | stack_v2_sparse_classes_30k_train_003805 | Implement the Python class `EducationIndexViewTests` described below.
Class description:
Implement the EducationIndexViewTests class.
Method signatures and docstrings:
- def test_no_data(self): If no data is in the database, no content is displayed but there is no map of graudation rates.
- def test_with_data(self): ... | Implement the Python class `EducationIndexViewTests` described below.
Class description:
Implement the EducationIndexViewTests class.
Method signatures and docstrings:
- def test_no_data(self): If no data is in the database, no content is displayed but there is no map of graudation rates.
- def test_with_data(self): ... | 2a8e2dc4e9b3cb92d4d437b37e61940a9486b81f | <|skeleton|>
class EducationIndexViewTests:
def test_no_data(self):
"""If no data is in the database, no content is displayed but there is no map of graudation rates."""
<|body_0|>
def test_with_data(self):
"""If state data is in the database, make sure the conents renders and a graph ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EducationIndexViewTests:
def test_no_data(self):
"""If no data is in the database, no content is displayed but there is no map of graudation rates."""
response = self.client.get(reverse('education:index'))
self.assertEqual(response.status_code, 200)
self.assertEqual(response.co... | the_stack_v2_python_sparse | education/tests.py | smeds1/mysite | train | 1 | |
959c5ba910b87b05bc1cdf67bfbd126391f5caaf | [
"super().__init__()\nself.input_channel_size = input_channels\nself.output_channel_size = output_channels\nself.num_nodes = num_nodes\nGraphConv.global_count += 1\nself.name = name if name else 'Graph_{}'.format(GraphConv.global_count)\nvalue = math.sqrt(6 / (input_channels + output_channels))\nmat_weights = []\nid... | <|body_start_0|>
super().__init__()
self.input_channel_size = input_channels
self.output_channel_size = output_channels
self.num_nodes = num_nodes
GraphConv.global_count += 1
self.name = name if name else 'Graph_{}'.format(GraphConv.global_count)
value = math.sqrt... | Graph Conv layer. See: https://arxiv.org/abs/1609.02907 | GraphConv | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GraphConv:
"""Graph Conv layer. See: https://arxiv.org/abs/1609.02907"""
def __init__(self, input_channels, output_channels, num_nodes, bias=True, activation=lbann.Relu, name=None):
"""Initialize Graph layer Args: input_channels (int): The size of the input node features output_chann... | stack_v2_sparse_classes_10k_train_002713 | 4,744 | permissive | [
{
"docstring": "Initialize Graph layer Args: input_channels (int): The size of the input node features output_channels (int): The output size of the node features num_nodes (int): Number of vertices in the graph bias (bool): Whether to apply biases after weights transform activation (type): Activation layer for... | 2 | null | Implement the Python class `GraphConv` described below.
Class description:
Graph Conv layer. See: https://arxiv.org/abs/1609.02907
Method signatures and docstrings:
- def __init__(self, input_channels, output_channels, num_nodes, bias=True, activation=lbann.Relu, name=None): Initialize Graph layer Args: input_channel... | Implement the Python class `GraphConv` described below.
Class description:
Graph Conv layer. See: https://arxiv.org/abs/1609.02907
Method signatures and docstrings:
- def __init__(self, input_channels, output_channels, num_nodes, bias=True, activation=lbann.Relu, name=None): Initialize Graph layer Args: input_channel... | e8cf85eed2acbd3383892bf7cb2d88b44c194f4f | <|skeleton|>
class GraphConv:
"""Graph Conv layer. See: https://arxiv.org/abs/1609.02907"""
def __init__(self, input_channels, output_channels, num_nodes, bias=True, activation=lbann.Relu, name=None):
"""Initialize Graph layer Args: input_channels (int): The size of the input node features output_chann... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GraphConv:
"""Graph Conv layer. See: https://arxiv.org/abs/1609.02907"""
def __init__(self, input_channels, output_channels, num_nodes, bias=True, activation=lbann.Relu, name=None):
"""Initialize Graph layer Args: input_channels (int): The size of the input node features output_channels (int): Th... | the_stack_v2_python_sparse | python/lbann/modules/graph/sparse/GraphConv.py | LLNL/lbann | train | 225 |
03290573509782957b78362f1e42cfa560d5a89b | [
"Parametre.__init__(self, 'conquérir', 'conquer')\nself.tronquer = True\nself.aide_courte = 'conquit un navire et équipage'\nself.aide_longue = \"Cette commande permet de conquérir un navire adverse : si vous en avez le droit, vous en deviendrez son propriétaire. Vous aurez également les droits de commander les mat... | <|body_start_0|>
Parametre.__init__(self, 'conquérir', 'conquer')
self.tronquer = True
self.aide_courte = 'conquit un navire et équipage'
self.aide_longue = "Cette commande permet de conquérir un navire adverse : si vous en avez le droit, vous en deviendrez son propriétaire. Vous aurez é... | Commande 'équipage conquérir'. | PrmConquerir | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmConquerir:
"""Commande 'équipage conquérir'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Para... | stack_v2_sparse_classes_10k_train_002714 | 4,608 | permissive | [
{
"docstring": "Constructeur du paramètre",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Interprétation du paramètre",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | null | Implement the Python class `PrmConquerir` described below.
Class description:
Commande 'équipage conquérir'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre | Implement the Python class `PrmConquerir` described below.
Class description:
Commande 'équipage conquérir'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre
<|skeleton|>
class PrmConquerir:
"""Commande... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmConquerir:
"""Commande 'équipage conquérir'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PrmConquerir:
"""Commande 'équipage conquérir'."""
def __init__(self):
"""Constructeur du paramètre"""
Parametre.__init__(self, 'conquérir', 'conquer')
self.tronquer = True
self.aide_courte = 'conquit un navire et équipage'
self.aide_longue = "Cette commande permet... | the_stack_v2_python_sparse | src/secondaires/navigation/commandes/equipage/conquerir.py | vincent-lg/tsunami | train | 5 |
2786c897b3bfa47724930c4c6540cd8794f9efd3 | [
"assert isinstance(output_size, (int, tuple))\nif isinstance(output_size, int):\n self.output_size = (output_size, output_size)\nelse:\n assert len(output_size) == 2\n self.output_size = output_size",
"imidx, image, label = (sample['imidx'], sample['image'], sample['label'])\nif random.random() >= 0.5:\n... | <|body_start_0|>
assert isinstance(output_size, (int, tuple))
if isinstance(output_size, int):
self.output_size = (output_size, output_size)
else:
assert len(output_size) == 2
self.output_size = output_size
<|end_body_0|>
<|body_start_1|>
imidx, image... | RandomCrop operation | RandomCrop | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomCrop:
"""RandomCrop operation"""
def __init__(self, output_size):
"""RandomCrop definition"""
<|body_0|>
def __call__(self, sample):
"""RandomCrop compute"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
assert isinstance(output_size, (int,... | stack_v2_sparse_classes_10k_train_002715 | 14,055 | permissive | [
{
"docstring": "RandomCrop definition",
"name": "__init__",
"signature": "def __init__(self, output_size)"
},
{
"docstring": "RandomCrop compute",
"name": "__call__",
"signature": "def __call__(self, sample)"
}
] | 2 | null | Implement the Python class `RandomCrop` described below.
Class description:
RandomCrop operation
Method signatures and docstrings:
- def __init__(self, output_size): RandomCrop definition
- def __call__(self, sample): RandomCrop compute | Implement the Python class `RandomCrop` described below.
Class description:
RandomCrop operation
Method signatures and docstrings:
- def __init__(self, output_size): RandomCrop definition
- def __call__(self, sample): RandomCrop compute
<|skeleton|>
class RandomCrop:
"""RandomCrop operation"""
def __init__(... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class RandomCrop:
"""RandomCrop operation"""
def __init__(self, output_size):
"""RandomCrop definition"""
<|body_0|>
def __call__(self, sample):
"""RandomCrop compute"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RandomCrop:
"""RandomCrop operation"""
def __init__(self, output_size):
"""RandomCrop definition"""
assert isinstance(output_size, (int, tuple))
if isinstance(output_size, int):
self.output_size = (output_size, output_size)
else:
assert len(output_s... | the_stack_v2_python_sparse | research/cv/u2net/src/data_loader.py | mindspore-ai/models | train | 301 |
fc6ce3b5da8592f44271f6622bb653bbe1aba0c9 | [
"super(Envelope, self).__init__()\nself.p = exponent\nself.a = -(self.p + 1) * (self.p + 2) / 2\nself.b = self.p * (self.p + 2)\nself.c = -self.p * (self.p + 1) / 2",
"p, a, b, c = (self.p, self.a, self.b, self.c)\nx_pow_p0 = x.pow(p)\nx_pow_p1 = x_pow_p0 * x\nenv_val = 1.0 / x + a * x_pow_p0 + b * x_pow_p1 + c *... | <|body_start_0|>
super(Envelope, self).__init__()
self.p = exponent
self.a = -(self.p + 1) * (self.p + 2) / 2
self.b = self.p * (self.p + 2)
self.c = -self.p * (self.p + 1) / 2
<|end_body_0|>
<|body_start_1|>
p, a, b, c = (self.p, self.a, self.b, self.c)
x_pow_p0... | Envelope. | Envelope | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Envelope:
"""Envelope."""
def __init__(self, exponent) -> None:
"""Initialize envelope. Args: exponent: exponent of the envelope."""
<|body_0|>
def forward(self, x):
"""Forward pass. Args: x: input. Returns: Envelope of x."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_10k_train_002716 | 34,044 | permissive | [
{
"docstring": "Initialize envelope. Args: exponent: exponent of the envelope.",
"name": "__init__",
"signature": "def __init__(self, exponent) -> None"
},
{
"docstring": "Forward pass. Args: x: input. Returns: Envelope of x.",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004763 | Implement the Python class `Envelope` described below.
Class description:
Envelope.
Method signatures and docstrings:
- def __init__(self, exponent) -> None: Initialize envelope. Args: exponent: exponent of the envelope.
- def forward(self, x): Forward pass. Args: x: input. Returns: Envelope of x. | Implement the Python class `Envelope` described below.
Class description:
Envelope.
Method signatures and docstrings:
- def __init__(self, exponent) -> None: Initialize envelope. Args: exponent: exponent of the envelope.
- def forward(self, x): Forward pass. Args: x: input. Returns: Envelope of x.
<|skeleton|>
class... | 0b69b7d5b261f2f9af3984793c1295b9b80cd01a | <|skeleton|>
class Envelope:
"""Envelope."""
def __init__(self, exponent) -> None:
"""Initialize envelope. Args: exponent: exponent of the envelope."""
<|body_0|>
def forward(self, x):
"""Forward pass. Args: x: input. Returns: Envelope of x."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Envelope:
"""Envelope."""
def __init__(self, exponent) -> None:
"""Initialize envelope. Args: exponent: exponent of the envelope."""
super(Envelope, self).__init__()
self.p = exponent
self.a = -(self.p + 1) * (self.p + 2) / 2
self.b = self.p * (self.p + 2)
... | the_stack_v2_python_sparse | src/gt4sd/frameworks/gflownet/ml/models/mxmnet.py | GT4SD/gt4sd-core | train | 239 |
a1f62f9554d8a41caffb18e10b9127c43dbecbe3 | [
"for i in range(len(shifts) - 1)[::-1]:\n shifts[i] += shifts[i + 1]\nreturn ''.join([chr((ord(c) - 97 + s) % 26 + 97) for c, s in zip(S, shifts)])",
"s = [ord(c) for c in S]\nfor i, shift in enumerate(shifts):\n for j in range(i + 1):\n s[j] += shift % 26\nreturn ''.join([chr((n - 97) % 26 + 97) for... | <|body_start_0|>
for i in range(len(shifts) - 1)[::-1]:
shifts[i] += shifts[i + 1]
return ''.join([chr((ord(c) - 97 + s) % 26 + 97) for c, s in zip(S, shifts)])
<|end_body_0|>
<|body_start_1|>
s = [ord(c) for c in S]
for i, shift in enumerate(shifts):
for j in ra... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shiftingLetters(self, S, shifts):
""":type S: str :type shifts: List[int] :rtype: str"""
<|body_0|>
def shiftingLetters_TLE(self, S, shifts):
""":type S: str :type shifts: List[int] :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_002717 | 2,168 | no_license | [
{
"docstring": ":type S: str :type shifts: List[int] :rtype: str",
"name": "shiftingLetters",
"signature": "def shiftingLetters(self, S, shifts)"
},
{
"docstring": ":type S: str :type shifts: List[int] :rtype: str",
"name": "shiftingLetters_TLE",
"signature": "def shiftingLetters_TLE(sel... | 2 | stack_v2_sparse_classes_30k_train_006052 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shiftingLetters(self, S, shifts): :type S: str :type shifts: List[int] :rtype: str
- def shiftingLetters_TLE(self, S, shifts): :type S: str :type shifts: List[int] :rtype: st... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shiftingLetters(self, S, shifts): :type S: str :type shifts: List[int] :rtype: str
- def shiftingLetters_TLE(self, S, shifts): :type S: str :type shifts: List[int] :rtype: st... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def shiftingLetters(self, S, shifts):
""":type S: str :type shifts: List[int] :rtype: str"""
<|body_0|>
def shiftingLetters_TLE(self, S, shifts):
""":type S: str :type shifts: List[int] :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def shiftingLetters(self, S, shifts):
""":type S: str :type shifts: List[int] :rtype: str"""
for i in range(len(shifts) - 1)[::-1]:
shifts[i] += shifts[i + 1]
return ''.join([chr((ord(c) - 97 + s) % 26 + 97) for c, s in zip(S, shifts)])
def shiftingLetters_TL... | the_stack_v2_python_sparse | src/lt_848.py | oxhead/CodingYourWay | train | 0 | |
da2f89f2c3d6dcff588b6b25b7dde4721b9db986 | [
"V = np.ones((neu_dim, x_dim)) / 2\nW = np.ones((output_dim, neu_dim)) / 2\nY = np.zeros(output_dim)\nV = normalization_all(V)\nself.V = V\nself.W = W\nself.Y = Y\nself.lr = lr\nself.lr_out = lr_out",
"z_layer = np.dot(self.V, x.T)\nargmax = np.argmax(z_layer)\nreturn argmax",
"self.V[argmax] = self.V[argmax] +... | <|body_start_0|>
V = np.ones((neu_dim, x_dim)) / 2
W = np.ones((output_dim, neu_dim)) / 2
Y = np.zeros(output_dim)
V = normalization_all(V)
self.V = V
self.W = W
self.Y = Y
self.lr = lr
self.lr_out = lr_out
<|end_body_0|>
<|body_start_1|>
... | competitive_network | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class competitive_network:
def __init__(self, x_dim, neu_dim, output_dim, lr, lr_out):
"""类参数初始化"""
<|body_0|>
def forward_propagation(self, x):
"""前向传播 input:self(object):类参数 x(mat):一个训练样本 output:argmax(int):被激活的权重向量指针"""
<|body_1|>
def back_propagation(self,... | stack_v2_sparse_classes_10k_train_002718 | 4,419 | no_license | [
{
"docstring": "类参数初始化",
"name": "__init__",
"signature": "def __init__(self, x_dim, neu_dim, output_dim, lr, lr_out)"
},
{
"docstring": "前向传播 input:self(object):类参数 x(mat):一个训练样本 output:argmax(int):被激活的权重向量指针",
"name": "forward_propagation",
"signature": "def forward_propagation(self, x... | 6 | stack_v2_sparse_classes_30k_train_005041 | Implement the Python class `competitive_network` described below.
Class description:
Implement the competitive_network class.
Method signatures and docstrings:
- def __init__(self, x_dim, neu_dim, output_dim, lr, lr_out): 类参数初始化
- def forward_propagation(self, x): 前向传播 input:self(object):类参数 x(mat):一个训练样本 output:argm... | Implement the Python class `competitive_network` described below.
Class description:
Implement the competitive_network class.
Method signatures and docstrings:
- def __init__(self, x_dim, neu_dim, output_dim, lr, lr_out): 类参数初始化
- def forward_propagation(self, x): 前向传播 input:self(object):类参数 x(mat):一个训练样本 output:argm... | 97e69c71af972f22c38b714b659a374d04c08b84 | <|skeleton|>
class competitive_network:
def __init__(self, x_dim, neu_dim, output_dim, lr, lr_out):
"""类参数初始化"""
<|body_0|>
def forward_propagation(self, x):
"""前向传播 input:self(object):类参数 x(mat):一个训练样本 output:argmax(int):被激活的权重向量指针"""
<|body_1|>
def back_propagation(self,... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class competitive_network:
def __init__(self, x_dim, neu_dim, output_dim, lr, lr_out):
"""类参数初始化"""
V = np.ones((neu_dim, x_dim)) / 2
W = np.ones((output_dim, neu_dim)) / 2
Y = np.zeros(output_dim)
V = normalization_all(V)
self.V = V
self.W = W
self.Y ... | the_stack_v2_python_sparse | HW2/Hermit_7.py | gavinatthu/ANN_course | train | 3 | |
05668b57bdb7acb5d38f6d265e74ea38e2cb1b71 | [
"try:\n plugin = module.Plugin\nexcept AttributeError:\n return False\ncommand = data[invocation_length:]\ntry:\n result = plugin.run(self, command)\nexcept TypeError:\n result = plugin().run(self, command)\nplugin_ran = True\nreturn (plugin_ran, result)",
"if plugin_list:\n plugin_ran = False\n ... | <|body_start_0|>
try:
plugin = module.Plugin
except AttributeError:
return False
command = data[invocation_length:]
try:
result = plugin.run(self, command)
except TypeError:
result = plugin().run(self, command)
plugin_ran = ... | PluginRunner | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PluginRunner:
def run_plugin(self, module, data, invocation_length):
"""Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:"""
<|body_0|>
def process_plugins(self, plugin_list, data, help_mode_on=False):
"""... | stack_v2_sparse_classes_10k_train_002719 | 4,870 | no_license | [
{
"docstring": "Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:",
"name": "run_plugin",
"signature": "def run_plugin(self, module, data, invocation_length)"
},
{
"docstring": "Process plugins to see if the data should be intercepted... | 2 | stack_v2_sparse_classes_30k_train_004665 | Implement the Python class `PluginRunner` described below.
Class description:
Implement the PluginRunner class.
Method signatures and docstrings:
- def run_plugin(self, module, data, invocation_length): Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:
- d... | Implement the Python class `PluginRunner` described below.
Class description:
Implement the PluginRunner class.
Method signatures and docstrings:
- def run_plugin(self, module, data, invocation_length): Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:
- d... | fb0aa92ea05dc05416a0a2cf3cc7a698b25f1d38 | <|skeleton|>
class PluginRunner:
def run_plugin(self, module, data, invocation_length):
"""Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:"""
<|body_0|>
def process_plugins(self, plugin_list, data, help_mode_on=False):
"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PluginRunner:
def run_plugin(self, module, data, invocation_length):
"""Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:"""
try:
plugin = module.Plugin
except AttributeError:
return False
com... | the_stack_v2_python_sparse | common.py | RattleyCooper/Oyster | train | 2 | |
5c9508b93bd508833fd8ef0ebaa2b275eb015812 | [
"self.previous = datetime.datetime.now()\nself.servo_0 = Servo(servos[0], initial_positions[0], 5)\nself.servo_1 = Servo(servos[1], initial_positions[1], 5)\nself.servo_2 = Servo(servos[2], initial_positions[2], 5)\nself.servos = [self.servo_0, self.servo_1, self.servo_2]\nself.reposition = False\nself.grabbed = Fa... | <|body_start_0|>
self.previous = datetime.datetime.now()
self.servo_0 = Servo(servos[0], initial_positions[0], 5)
self.servo_1 = Servo(servos[1], initial_positions[1], 5)
self.servo_2 = Servo(servos[2], initial_positions[2], 5)
self.servos = [self.servo_0, self.servo_1, self.serv... | Base class for grabber which directly implements servo | Grabber | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Grabber:
"""Base class for grabber which directly implements servo"""
def __init__(self, servos, initial_positions):
"""Constructor for grabber class :param servos: Array of grabber servo id`s :param initial_positions: Array of servo positions"""
<|body_0|>
def grab(self... | stack_v2_sparse_classes_10k_train_002720 | 4,112 | permissive | [
{
"docstring": "Constructor for grabber class :param servos: Array of grabber servo id`s :param initial_positions: Array of servo positions",
"name": "__init__",
"signature": "def __init__(self, servos, initial_positions)"
},
{
"docstring": "Function that contains commands to close grabber :para... | 6 | stack_v2_sparse_classes_30k_train_000203 | Implement the Python class `Grabber` described below.
Class description:
Base class for grabber which directly implements servo
Method signatures and docstrings:
- def __init__(self, servos, initial_positions): Constructor for grabber class :param servos: Array of grabber servo id`s :param initial_positions: Array of... | Implement the Python class `Grabber` described below.
Class description:
Base class for grabber which directly implements servo
Method signatures and docstrings:
- def __init__(self, servos, initial_positions): Constructor for grabber class :param servos: Array of grabber servo id`s :param initial_positions: Array of... | c8898bef493618c19ba9f3c564ee25481fd4695e | <|skeleton|>
class Grabber:
"""Base class for grabber which directly implements servo"""
def __init__(self, servos, initial_positions):
"""Constructor for grabber class :param servos: Array of grabber servo id`s :param initial_positions: Array of servo positions"""
<|body_0|>
def grab(self... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Grabber:
"""Base class for grabber which directly implements servo"""
def __init__(self, servos, initial_positions):
"""Constructor for grabber class :param servos: Array of grabber servo id`s :param initial_positions: Array of servo positions"""
self.previous = datetime.datetime.now()
... | the_stack_v2_python_sparse | src/entities/movement/grabber.py | DwarfExop/IDP | train | 0 |
5821076a103befe2a060e9d1e26b59ce44188ccd | [
"log = MissionClockEvent(user=self.user1, team_on_clock=True, team_on_timeout=False)\nlog.save()\nself.assertIsNotNone(log.__unicode__())",
"log = MissionClockEvent(user=self.user1, team_on_clock=False, team_on_timeout=False)\nlog.save()\nlog = MissionClockEvent(user=self.user2, team_on_clock=True, team_on_timeou... | <|body_start_0|>
log = MissionClockEvent(user=self.user1, team_on_clock=True, team_on_timeout=False)
log.save()
self.assertIsNotNone(log.__unicode__())
<|end_body_0|>
<|body_start_1|>
log = MissionClockEvent(user=self.user1, team_on_clock=False, team_on_timeout=False)
log.save()... | Tests the MissionClockEvent model. | TestMissionClockEventModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestMissionClockEventModel:
"""Tests the MissionClockEvent model."""
def test_unicode(self):
"""Tests the unicode method executes."""
<|body_0|>
def test_user_on_clock(self):
"""Tests the user_on_clock method."""
<|body_1|>
def test_user_on_timeout(s... | stack_v2_sparse_classes_10k_train_002721 | 3,380 | permissive | [
{
"docstring": "Tests the unicode method executes.",
"name": "test_unicode",
"signature": "def test_unicode(self)"
},
{
"docstring": "Tests the user_on_clock method.",
"name": "test_user_on_clock",
"signature": "def test_user_on_clock(self)"
},
{
"docstring": "Tests the user_on_t... | 4 | stack_v2_sparse_classes_30k_train_003209 | Implement the Python class `TestMissionClockEventModel` described below.
Class description:
Tests the MissionClockEvent model.
Method signatures and docstrings:
- def test_unicode(self): Tests the unicode method executes.
- def test_user_on_clock(self): Tests the user_on_clock method.
- def test_user_on_timeout(self)... | Implement the Python class `TestMissionClockEventModel` described below.
Class description:
Tests the MissionClockEvent model.
Method signatures and docstrings:
- def test_unicode(self): Tests the unicode method executes.
- def test_user_on_clock(self): Tests the user_on_clock method.
- def test_user_on_timeout(self)... | 509f36562fc895433fcd01da755a35dd04581025 | <|skeleton|>
class TestMissionClockEventModel:
"""Tests the MissionClockEvent model."""
def test_unicode(self):
"""Tests the unicode method executes."""
<|body_0|>
def test_user_on_clock(self):
"""Tests the user_on_clock method."""
<|body_1|>
def test_user_on_timeout(s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestMissionClockEventModel:
"""Tests the MissionClockEvent model."""
def test_unicode(self):
"""Tests the unicode method executes."""
log = MissionClockEvent(user=self.user1, team_on_clock=True, team_on_timeout=False)
log.save()
self.assertIsNotNone(log.__unicode__())
... | the_stack_v2_python_sparse | server/auvsi_suas/models/mission_clock_event_test.py | matcheydj/interop | train | 1 |
ebf76420f3873e687371e29f074708814bb132ff | [
"option_view = '\\n 1. 列出所有学生\\n 2. 查询\\n '\nprint('学生信息系统'.center(cls.width, '='))\nprint(option_view)\nnumber = input('请选择(Ctrl + c 退出):')\nfunc_dict = {'1': cls.list_student, '2': cls.search}\nif number not in func_dict.keys():\n raise Exception('【提示】:输入有误, 请重新选择')\nfunc = func_dict[numbe... | <|body_start_0|>
option_view = '\n 1. 列出所有学生\n 2. 查询\n '
print('学生信息系统'.center(cls.width, '='))
print(option_view)
number = input('请选择(Ctrl + c 退出):')
func_dict = {'1': cls.list_student, '2': cls.search}
if number not in func_dict.keys():
... | View | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class View:
def menu(cls):
"""主菜单"""
<|body_0|>
def list_student(cls):
"""列出所有学生"""
<|body_1|>
def search(cls):
"""查询"""
<|body_2|>
def search_student(cls):
"""查询学生信息"""
<|body_3|>
def search_score(cls):
"""查询成... | stack_v2_sparse_classes_10k_train_002722 | 3,327 | no_license | [
{
"docstring": "主菜单",
"name": "menu",
"signature": "def menu(cls)"
},
{
"docstring": "列出所有学生",
"name": "list_student",
"signature": "def list_student(cls)"
},
{
"docstring": "查询",
"name": "search",
"signature": "def search(cls)"
},
{
"docstring": "查询学生信息",
"na... | 5 | stack_v2_sparse_classes_30k_train_001072 | Implement the Python class `View` described below.
Class description:
Implement the View class.
Method signatures and docstrings:
- def menu(cls): 主菜单
- def list_student(cls): 列出所有学生
- def search(cls): 查询
- def search_student(cls): 查询学生信息
- def search_score(cls): 查询成绩 | Implement the Python class `View` described below.
Class description:
Implement the View class.
Method signatures and docstrings:
- def menu(cls): 主菜单
- def list_student(cls): 列出所有学生
- def search(cls): 查询
- def search_student(cls): 查询学生信息
- def search_score(cls): 查询成绩
<|skeleton|>
class View:
def menu(cls):
... | b7f29743883739e3b298d49a170f367944ee0d9a | <|skeleton|>
class View:
def menu(cls):
"""主菜单"""
<|body_0|>
def list_student(cls):
"""列出所有学生"""
<|body_1|>
def search(cls):
"""查询"""
<|body_2|>
def search_student(cls):
"""查询学生信息"""
<|body_3|>
def search_score(cls):
"""查询成... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class View:
def menu(cls):
"""主菜单"""
option_view = '\n 1. 列出所有学生\n 2. 查询\n '
print('学生信息系统'.center(cls.width, '='))
print(option_view)
number = input('请选择(Ctrl + c 退出):')
func_dict = {'1': cls.list_student, '2': cls.search}
if number not i... | the_stack_v2_python_sparse | 16-17/01_界面/src/view.py | ucookie/basic-python | train | 0 | |
5233f8f4300c916a7730fd5d82b380c62cabd9bb | [
"portal_types = getToolByName(self.context, 'portal_types')\ntransaction = self.context\nentries = transaction.entries()\nif not transaction.canUndoOrReverse():\n raise AccessControl_Unauthorized('No permission to create transactionentries, or there are no entries to reverse')\ntransaction_folder = transaction.g... | <|body_start_0|>
portal_types = getToolByName(self.context, 'portal_types')
transaction = self.context
entries = transaction.entries()
if not transaction.canUndoOrReverse():
raise AccessControl_Unauthorized('No permission to create transactionentries, or there are no entries ... | Transaction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transaction:
def reverse_transaction(self):
"""Reverse a transaction - create a debit for a credit and a credit for a debit for each transaction entry"""
<|body_0|>
def undo_transaction(self):
"""Undo a transaction - remove the reference to the transaction, and do a ... | stack_v2_sparse_classes_10k_train_002723 | 2,892 | no_license | [
{
"docstring": "Reverse a transaction - create a debit for a credit and a credit for a debit for each transaction entry",
"name": "reverse_transaction",
"signature": "def reverse_transaction(self)"
},
{
"docstring": "Undo a transaction - remove the reference to the transaction, and do a debit/cr... | 2 | stack_v2_sparse_classes_30k_train_000812 | Implement the Python class `Transaction` described below.
Class description:
Implement the Transaction class.
Method signatures and docstrings:
- def reverse_transaction(self): Reverse a transaction - create a debit for a credit and a credit for a debit for each transaction entry
- def undo_transaction(self): Undo a ... | Implement the Python class `Transaction` described below.
Class description:
Implement the Transaction class.
Method signatures and docstrings:
- def reverse_transaction(self): Reverse a transaction - create a debit for a credit and a credit for a debit for each transaction entry
- def undo_transaction(self): Undo a ... | 77abccb6f7454f09a11e17841ba2049d4f11915c | <|skeleton|>
class Transaction:
def reverse_transaction(self):
"""Reverse a transaction - create a debit for a credit and a credit for a debit for each transaction entry"""
<|body_0|>
def undo_transaction(self):
"""Undo a transaction - remove the reference to the transaction, and do a ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Transaction:
def reverse_transaction(self):
"""Reverse a transaction - create a debit for a credit and a credit for a debit for each transaction entry"""
portal_types = getToolByName(self.context, 'portal_types')
transaction = self.context
entries = transaction.entries()
... | the_stack_v2_python_sparse | Products/UpfrontAccounting/browser/transaction.py | rochecompaan/Products.UpfrontAccounting | train | 0 | |
7a87f9c55b7753fd63557ef72ee8a5708aa00ffb | [
"super(EncoderMix, self).__init__()\ntyp = etype.lstrip('vgg').rstrip('p')\nif typ not in ['lstm', 'gru', 'blstm', 'bgru']:\n logging.error('Error: need to specify an appropriate encoder architecture')\nif etype.startswith('vgg'):\n if etype[-1] == 'p':\n self.enc_mix = torch.nn.ModuleList([VGG2L(in_ch... | <|body_start_0|>
super(EncoderMix, self).__init__()
typ = etype.lstrip('vgg').rstrip('p')
if typ not in ['lstm', 'gru', 'blstm', 'bgru']:
logging.error('Error: need to specify an appropriate encoder architecture')
if etype.startswith('vgg'):
if etype[-1] == 'p':
... | Encoder module for the case of multi-speaker mixture speech. :param str etype: type of encoder network :param int idim: number of dimensions of encoder network :param int elayers_sd: number of layers of speaker differentiate part in encoder network :param int elayers_rec: number of layers of shared recognition part in ... | EncoderMix | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderMix:
"""Encoder module for the case of multi-speaker mixture speech. :param str etype: type of encoder network :param int idim: number of dimensions of encoder network :param int elayers_sd: number of layers of speaker differentiate part in encoder network :param int elayers_rec: number of... | stack_v2_sparse_classes_10k_train_002724 | 30,819 | permissive | [
{
"docstring": "Initialize the encoder of single-channel multi-speaker ASR.",
"name": "__init__",
"signature": "def __init__(self, etype, idim, elayers_sd, elayers_rec, eunits, eprojs, subsample, dropout, num_spkrs=2, in_channel=1)"
},
{
"docstring": "Encodermix forward. :param torch.Tensor xs_p... | 2 | stack_v2_sparse_classes_30k_train_004238 | Implement the Python class `EncoderMix` described below.
Class description:
Encoder module for the case of multi-speaker mixture speech. :param str etype: type of encoder network :param int idim: number of dimensions of encoder network :param int elayers_sd: number of layers of speaker differentiate part in encoder ne... | Implement the Python class `EncoderMix` described below.
Class description:
Encoder module for the case of multi-speaker mixture speech. :param str etype: type of encoder network :param int idim: number of dimensions of encoder network :param int elayers_sd: number of layers of speaker differentiate part in encoder ne... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class EncoderMix:
"""Encoder module for the case of multi-speaker mixture speech. :param str etype: type of encoder network :param int idim: number of dimensions of encoder network :param int elayers_sd: number of layers of speaker differentiate part in encoder network :param int elayers_rec: number of... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EncoderMix:
"""Encoder module for the case of multi-speaker mixture speech. :param str etype: type of encoder network :param int idim: number of dimensions of encoder network :param int elayers_sd: number of layers of speaker differentiate part in encoder network :param int elayers_rec: number of layers of sh... | the_stack_v2_python_sparse | espnet/nets/pytorch_backend/e2e_asr_mix.py | espnet/espnet | train | 7,242 |
9fcf56722eb12d308e917e9dc1fd65371bb3ecfd | [
"self.account_id = account_id\nself.conference_id = conference_id\nself.name = name\nself.recording_id = recording_id\nself.duration = duration\nself.channels = channels\nself.start_time = APIHelper.RFC3339DateTime(start_time) if start_time else None\nself.end_time = APIHelper.RFC3339DateTime(end_time) if end_time ... | <|body_start_0|>
self.account_id = account_id
self.conference_id = conference_id
self.name = name
self.recording_id = recording_id
self.duration = duration
self.channels = channels
self.start_time = APIHelper.RFC3339DateTime(start_time) if start_time else None
... | Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TODO: type description here. recording_id (string): TODO: type description here. duration (strin... | ConferenceRecordingMetadata | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConferenceRecordingMetadata:
"""Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TODO: type description here. recording_id... | stack_v2_sparse_classes_10k_train_002725 | 4,419 | permissive | [
{
"docstring": "Constructor for the ConferenceRecordingMetadata class",
"name": "__init__",
"signature": "def __init__(self, account_id=None, conference_id=None, name=None, recording_id=None, duration=None, channels=None, start_time=None, end_time=None, file_format=None, status=None, media_url=None)"
... | 2 | stack_v2_sparse_classes_30k_train_000364 | Implement the Python class `ConferenceRecordingMetadata` described below.
Class description:
Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TO... | Implement the Python class `ConferenceRecordingMetadata` described below.
Class description:
Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TO... | 447df3cc8cb7acaf3361d842630c432a9c31ce6e | <|skeleton|>
class ConferenceRecordingMetadata:
"""Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TODO: type description here. recording_id... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ConferenceRecordingMetadata:
"""Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TODO: type description here. recording_id (string): TO... | the_stack_v2_python_sparse | bandwidth/voice/models/conference_recording_metadata.py | Bandwidth/python-sdk | train | 10 |
4dc8223b3c0d9b54b669b139449a49bd4c4e5fc5 | [
"Frame.__init__(self, spec.FRAME_HEADER, channel_number)\nself.body_size = body_size\nself.properties = props",
"pieces = self.properties.encode()\npieces.insert(0, struct.pack('>HxxQ', self.properties.INDEX, self.body_size))\nreturn self._marshal(pieces)"
] | <|body_start_0|>
Frame.__init__(self, spec.FRAME_HEADER, channel_number)
self.body_size = body_size
self.properties = props
<|end_body_0|>
<|body_start_1|>
pieces = self.properties.encode()
pieces.insert(0, struct.pack('>HxxQ', self.properties.INDEX, self.body_size))
ret... | Header frame object mapping. AMQP content header frames are mapped on top of this class for creating or accessing their data and attributes. | Header | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Header:
"""Header frame object mapping. AMQP content header frames are mapped on top of this class for creating or accessing their data and attributes."""
def __init__(self, channel_number, body_size, props):
"""Parameters: - channel_number: int - body_size: int - props: spec.BasicPr... | stack_v2_sparse_classes_10k_train_002726 | 12,681 | no_license | [
{
"docstring": "Parameters: - channel_number: int - body_size: int - props: spec.BasicProperties object",
"name": "__init__",
"signature": "def __init__(self, channel_number, body_size, props)"
},
{
"docstring": "Return the AMQP binary encoded value of the frame",
"name": "marshal",
"sig... | 2 | null | Implement the Python class `Header` described below.
Class description:
Header frame object mapping. AMQP content header frames are mapped on top of this class for creating or accessing their data and attributes.
Method signatures and docstrings:
- def __init__(self, channel_number, body_size, props): Parameters: - c... | Implement the Python class `Header` described below.
Class description:
Header frame object mapping. AMQP content header frames are mapped on top of this class for creating or accessing their data and attributes.
Method signatures and docstrings:
- def __init__(self, channel_number, body_size, props): Parameters: - c... | a427d8b2790350b524b66ac14534fd836ae10476 | <|skeleton|>
class Header:
"""Header frame object mapping. AMQP content header frames are mapped on top of this class for creating or accessing their data and attributes."""
def __init__(self, channel_number, body_size, props):
"""Parameters: - channel_number: int - body_size: int - props: spec.BasicPr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Header:
"""Header frame object mapping. AMQP content header frames are mapped on top of this class for creating or accessing their data and attributes."""
def __init__(self, channel_number, body_size, props):
"""Parameters: - channel_number: int - body_size: int - props: spec.BasicProperties obje... | the_stack_v2_python_sparse | scripts/autoland/vendor/lib/python/pika/frame.py | lsblakk/tools | train | 1 |
e7ae9b564fa3d46691c6ca7e722d41e511f4cbd0 | [
"tmp_date = pendulum.parse(self.date.name)\nplan_date = tmp_date.format('YYYY-MM-DD')\nrecord = self.env['metro_park_maintenance.day_plan'].create([{'plan_name': self.name, 'plan_date': plan_date, 'state': 'draft', 'week_plan_id': self.week_plan_id.id, 'pms_work_class_info': self.pms_work_class_info.id, 'run_trains... | <|body_start_0|>
tmp_date = pendulum.parse(self.date.name)
plan_date = tmp_date.format('YYYY-MM-DD')
record = self.env['metro_park_maintenance.day_plan'].create([{'plan_name': self.name, 'plan_date': plan_date, 'state': 'draft', 'week_plan_id': self.week_plan_id.id, 'pms_work_class_info': self.p... | 重写onok函数，每条线路各自实现各自的 | DayPlanWizard | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DayPlanWizard:
"""重写onok函数，每条线路各自实现各自的"""
def on_ok(self):
"""点击确定按扭, 创建的时候就把当日的运行图数据放进去，这样便于修改 :return:"""
<|body_0|>
def get_day_plan_action(self):
"""取得日计划动作 :return:"""
<|body_1|>
def get_parent_plan_data(self):
"""获取上一级计划的检修计划数据 :return:... | stack_v2_sparse_classes_10k_train_002727 | 3,982 | no_license | [
{
"docstring": "点击确定按扭, 创建的时候就把当日的运行图数据放进去，这样便于修改 :return:",
"name": "on_ok",
"signature": "def on_ok(self)"
},
{
"docstring": "取得日计划动作 :return:",
"name": "get_day_plan_action",
"signature": "def get_day_plan_action(self)"
},
{
"docstring": "获取上一级计划的检修计划数据 :return:",
"name": ... | 3 | null | Implement the Python class `DayPlanWizard` described below.
Class description:
重写onok函数，每条线路各自实现各自的
Method signatures and docstrings:
- def on_ok(self): 点击确定按扭, 创建的时候就把当日的运行图数据放进去，这样便于修改 :return:
- def get_day_plan_action(self): 取得日计划动作 :return:
- def get_parent_plan_data(self): 获取上一级计划的检修计划数据 :return: | Implement the Python class `DayPlanWizard` described below.
Class description:
重写onok函数，每条线路各自实现各自的
Method signatures and docstrings:
- def on_ok(self): 点击确定按扭, 创建的时候就把当日的运行图数据放进去，这样便于修改 :return:
- def get_day_plan_action(self): 取得日计划动作 :return:
- def get_parent_plan_data(self): 获取上一级计划的检修计划数据 :return:
<|skeleton|>
... | 13b428a5c4ade6278e3e5e996ef10d9fb0fea4b9 | <|skeleton|>
class DayPlanWizard:
"""重写onok函数，每条线路各自实现各自的"""
def on_ok(self):
"""点击确定按扭, 创建的时候就把当日的运行图数据放进去，这样便于修改 :return:"""
<|body_0|>
def get_day_plan_action(self):
"""取得日计划动作 :return:"""
<|body_1|>
def get_parent_plan_data(self):
"""获取上一级计划的检修计划数据 :return:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DayPlanWizard:
"""重写onok函数，每条线路各自实现各自的"""
def on_ok(self):
"""点击确定按扭, 创建的时候就把当日的运行图数据放进去，这样便于修改 :return:"""
tmp_date = pendulum.parse(self.date.name)
plan_date = tmp_date.format('YYYY-MM-DD')
record = self.env['metro_park_maintenance.day_plan'].create([{'plan_name': self.n... | the_stack_v2_python_sparse | mdias_addons/metro_park_base_data_6/models/day_plan_wizard.py | rezaghanimi/main_mdias | train | 0 |
61ea60970f9ac454e652c8b6092c027e6e76996e | [
"super(DecoderBlock, self).__init__()\nself.mha1 = MultiHeadAttention(dm, h)\nself.mha2 = MultiHeadAttention(dm, h)\nself.dense_hidden = tf.keras.layers.Dense(hidden, activation='relu')\nself.dense_output = tf.keras.layers.Dense(dm)\nself.dropout1 = tf.keras.layers.Dropout(drop_rate)\nself.dropout2 = tf.keras.layer... | <|body_start_0|>
super(DecoderBlock, self).__init__()
self.mha1 = MultiHeadAttention(dm, h)
self.mha2 = MultiHeadAttention(dm, h)
self.dense_hidden = tf.keras.layers.Dense(hidden, activation='relu')
self.dense_output = tf.keras.layers.Dense(dm)
self.dropout1 = tf.keras.la... | Transformer Decoder Block | DecoderBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderBlock:
"""Transformer Decoder Block"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""[ Class constructor] Args: dm ([type]): [the dimensionality of the model] h ([type]): [the number of heads] hidden ([type]): [# of hidden units in the fully connected layer] drop_rate (... | stack_v2_sparse_classes_10k_train_002728 | 3,778 | no_license | [
{
"docstring": "[ Class constructor] Args: dm ([type]): [the dimensionality of the model] h ([type]): [the number of heads] hidden ([type]): [# of hidden units in the fully connected layer] drop_rate (float, optional): [dropout rate]. Defaults to 0.1. Public instance attributes: - mha1: the first MultiHeadAtten... | 2 | null | Implement the Python class `DecoderBlock` described below.
Class description:
Transformer Decoder Block
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): [ Class constructor] Args: dm ([type]): [the dimensionality of the model] h ([type]): [the number of heads] hidden ([type]): [# ... | Implement the Python class `DecoderBlock` described below.
Class description:
Transformer Decoder Block
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): [ Class constructor] Args: dm ([type]): [the dimensionality of the model] h ([type]): [the number of heads] hidden ([type]): [# ... | eb47cd4d12e2f0627bb5e5af28cc0802ff13d0d9 | <|skeleton|>
class DecoderBlock:
"""Transformer Decoder Block"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""[ Class constructor] Args: dm ([type]): [the dimensionality of the model] h ([type]): [the number of heads] hidden ([type]): [# of hidden units in the fully connected layer] drop_rate (... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DecoderBlock:
"""Transformer Decoder Block"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""[ Class constructor] Args: dm ([type]): [the dimensionality of the model] h ([type]): [the number of heads] hidden ([type]): [# of hidden units in the fully connected layer] drop_rate (float, option... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/8-transformer_decoder_block.py | rodrigocruz13/holbertonschool-machine_learning | train | 4 |
75aaa95b5105e4e0f18431fbb86be30af07c3e5e | [
"if not email:\n raise ValueError('Users must have an email address')\nuser = self.model(email=self.normalize_email(email))\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(email, password=password)\nuser.is_admin = True\nuser.save(using=self._db)\nreturn user"
] | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=self.normalize_email(email))
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = self.create_user(... | TrixUserManager | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrixUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email and password."""
<|body_0|>
def create_superuser(self, email, password):
"""Creates and saves a superuser with the given email and password."""
<|bo... | stack_v2_sparse_classes_10k_train_002729 | 9,283 | permissive | [
{
"docstring": "Creates and saves a User with the given email and password.",
"name": "create_user",
"signature": "def create_user(self, email, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email and password.",
"name": "create_superuser",
"signature": "... | 2 | stack_v2_sparse_classes_30k_test_000223 | Implement the Python class `TrixUserManager` described below.
Class description:
Implement the TrixUserManager class.
Method signatures and docstrings:
- def create_user(self, email, password=None): Creates and saves a User with the given email and password.
- def create_superuser(self, email, password): Creates and ... | Implement the Python class `TrixUserManager` described below.
Class description:
Implement the TrixUserManager class.
Method signatures and docstrings:
- def create_user(self, email, password=None): Creates and saves a User with the given email and password.
- def create_superuser(self, email, password): Creates and ... | 22d315a99c7f914a85f070c0639e056ec4fe8757 | <|skeleton|>
class TrixUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email and password."""
<|body_0|>
def create_superuser(self, email, password):
"""Creates and saves a superuser with the given email and password."""
<|bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TrixUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email and password."""
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=self.normalize_email(email))
user.set_password(... | the_stack_v2_python_sparse | trix/trix_core/models.py | devilry/trix2 | train | 2 | |
971b033fc41126b850d323387751a1624d6e78e1 | [
"app.config.setdefault('SQLALCHEMY_DATABASE_URI', app.config.get('CLASSIC_DATABASE_URI', 'sqlite://'))\napp.config.setdefault('SQLALCHEMY_TRACK_MODIFICATIONS', False)\nsuper(ClassicSQLAlchemy, self).init_app(app)",
"super(ClassicSQLAlchemy, self).apply_pool_defaults(app, options)\nif app.config['SQLALCHEMY_DATABA... | <|body_start_0|>
app.config.setdefault('SQLALCHEMY_DATABASE_URI', app.config.get('CLASSIC_DATABASE_URI', 'sqlite://'))
app.config.setdefault('SQLALCHEMY_TRACK_MODIFICATIONS', False)
super(ClassicSQLAlchemy, self).init_app(app)
<|end_body_0|>
<|body_start_1|>
super(ClassicSQLAlchemy, sel... | SQLAlchemy integration for the classic database. | ClassicSQLAlchemy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassicSQLAlchemy:
"""SQLAlchemy integration for the classic database."""
def init_app(self, app: Flask) -> None:
"""Set default configuration."""
<|body_0|>
def apply_pool_defaults(self, app: Flask, options: Any) -> None:
"""Set options for create_engine()."""
... | stack_v2_sparse_classes_10k_train_002730 | 3,561 | permissive | [
{
"docstring": "Set default configuration.",
"name": "init_app",
"signature": "def init_app(self, app: Flask) -> None"
},
{
"docstring": "Set options for create_engine().",
"name": "apply_pool_defaults",
"signature": "def apply_pool_defaults(self, app: Flask, options: Any) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_005641 | Implement the Python class `ClassicSQLAlchemy` described below.
Class description:
SQLAlchemy integration for the classic database.
Method signatures and docstrings:
- def init_app(self, app: Flask) -> None: Set default configuration.
- def apply_pool_defaults(self, app: Flask, options: Any) -> None: Set options for ... | Implement the Python class `ClassicSQLAlchemy` described below.
Class description:
SQLAlchemy integration for the classic database.
Method signatures and docstrings:
- def init_app(self, app: Flask) -> None: Set default configuration.
- def apply_pool_defaults(self, app: Flask, options: Any) -> None: Set options for ... | 6077ce4e0685d67ce7010800083a898857158112 | <|skeleton|>
class ClassicSQLAlchemy:
"""SQLAlchemy integration for the classic database."""
def init_app(self, app: Flask) -> None:
"""Set default configuration."""
<|body_0|>
def apply_pool_defaults(self, app: Flask, options: Any) -> None:
"""Set options for create_engine()."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ClassicSQLAlchemy:
"""SQLAlchemy integration for the classic database."""
def init_app(self, app: Flask) -> None:
"""Set default configuration."""
app.config.setdefault('SQLALCHEMY_DATABASE_URI', app.config.get('CLASSIC_DATABASE_URI', 'sqlite://'))
app.config.setdefault('SQLALCHEM... | the_stack_v2_python_sparse | core/arxiv/submission/services/classic/util.py | arXiv/arxiv-submission-core | train | 14 |
892cbc07a1524f47caaf9eddeb1e1485bb79c915 | [
"data = form.cleaned_data\nif validate_token(self.request, data['token'], allow_test=True):\n self.success_url = reverse('questions', kwargs={'course': data['course'].id})\n return super().form_valid(form)\nmessages.warning(self.request, 'Invalid Token. Please try again. Note: Tokens are caSE SensITive')\nret... | <|body_start_0|>
data = form.cleaned_data
if validate_token(self.request, data['token'], allow_test=True):
self.success_url = reverse('questions', kwargs={'course': data['course'].id})
return super().form_valid(form)
messages.warning(self.request, 'Invalid Token. Please t... | This view allows the user to choose which examination to take. Renders a self explanatory form and all fields are required. Redirects to questions view if choices are valid otherwise, returns the form with error message(s) for corrections. If the user account is inactive, they're redirected to the Home Page. | ChooseQuestionView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChooseQuestionView:
"""This view allows the user to choose which examination to take. Renders a self explanatory form and all fields are required. Redirects to questions view if choices are valid otherwise, returns the form with error message(s) for corrections. If the user account is inactive, t... | stack_v2_sparse_classes_10k_train_002731 | 29,759 | no_license | [
{
"docstring": "Validate exam Token and other requirements.",
"name": "form_valid",
"signature": "def form_valid(self, form)"
},
{
"docstring": "Return the data used in the templates rendering.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000094 | Implement the Python class `ChooseQuestionView` described below.
Class description:
This view allows the user to choose which examination to take. Renders a self explanatory form and all fields are required. Redirects to questions view if choices are valid otherwise, returns the form with error message(s) for correcti... | Implement the Python class `ChooseQuestionView` described below.
Class description:
This view allows the user to choose which examination to take. Renders a self explanatory form and all fields are required. Redirects to questions view if choices are valid otherwise, returns the form with error message(s) for correcti... | 06bc577d01d3dbf6c425e03dcb903977a38e377c | <|skeleton|>
class ChooseQuestionView:
"""This view allows the user to choose which examination to take. Renders a self explanatory form and all fields are required. Redirects to questions view if choices are valid otherwise, returns the form with error message(s) for corrections. If the user account is inactive, t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ChooseQuestionView:
"""This view allows the user to choose which examination to take. Renders a self explanatory form and all fields are required. Redirects to questions view if choices are valid otherwise, returns the form with error message(s) for corrections. If the user account is inactive, they're redire... | the_stack_v2_python_sparse | cbt/views.py | Festusali/CBTest | train | 6 |
65af988e10bdc94a5c147884d4f93bc35c01ffee | [
"length = len(nums)\nif length <= 1:\n return length\ndp = [1] * length\nfor i in range(1, length):\n if nums[i] > nums[i - 1]:\n dp[i] = dp[i - 1] + 1\nreturn max(dp)",
"if not nums:\n return 0\nl = len(nums)\nres = 0\ntmp = nums[0] - 1\ncount = 0\nfor x in range(l):\n if nums[x] > tmp:\n ... | <|body_start_0|>
length = len(nums)
if length <= 1:
return length
dp = [1] * length
for i in range(1, length):
if nums[i] > nums[i - 1]:
dp[i] = dp[i - 1] + 1
return max(dp)
<|end_body_0|>
<|body_start_1|>
if not nums:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findLengthOfLCIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findLengthOfLCIS2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
length = len(nums)
if leng... | stack_v2_sparse_classes_10k_train_002732 | 1,878 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findLengthOfLCIS",
"signature": "def findLengthOfLCIS(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findLengthOfLCIS2",
"signature": "def findLengthOfLCIS2(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLengthOfLCIS(self, nums): :type nums: List[int] :rtype: int
- def findLengthOfLCIS2(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 findLengthOfLCIS(self, nums): :type nums: List[int] :rtype: int
- def findLengthOfLCIS2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def ... | b0f498ebe84e46b7e17e94759dd462891dcc8f85 | <|skeleton|>
class Solution:
def findLengthOfLCIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findLengthOfLCIS2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findLengthOfLCIS(self, nums):
""":type nums: List[int] :rtype: int"""
length = len(nums)
if length <= 1:
return length
dp = [1] * length
for i in range(1, length):
if nums[i] > nums[i - 1]:
dp[i] = dp[i - 1] + 1
... | the_stack_v2_python_sparse | 字节跳动/array-and-sorting_4.py | wulinlw/leetcode_cn | train | 0 | |
e382713dbf6209d3d754f3a0e1e13855f155fb67 | [
"request = data_set.get('request')\nuser = data_set.get('user')\nif user:\n username = cls.analyze(user, uuid)\n driver = cls.analyze_class.get_user(username)\n CompatAPPDriver.driver = driver\nelse:\n user = data_set.get('session')\n driver = cls.session_class.get_session(user)\nfor step in request:... | <|body_start_0|>
request = data_set.get('request')
user = data_set.get('user')
if user:
username = cls.analyze(user, uuid)
driver = cls.analyze_class.get_user(username)
CompatAPPDriver.driver = driver
else:
user = data_set.get('session')
... | APPDriver | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class APPDriver:
def run(cls, data_set, uuid, host, **kwargs):
"""Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { "path": "/login", "user": "user1", "version": 2, "request": [ {"eventName": "元素点击", "event": "click", "locations": ["css selector", "#kw"], "input": "输入内容"}, {"eventName": ... | stack_v2_sparse_classes_10k_train_002733 | 6,213 | permissive | [
{
"docstring": "Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { \"path\": \"/login\", \"user\": \"user1\", \"version\": 2, \"request\": [ {\"eventName\": \"元素点击\", \"event\": \"click\", \"locations\": [\"css selector\", \"#kw\"], \"input\": \"输入内容\"}, {\"eventName\": \"元素名称\", \"event\": \"click\", \"lo... | 2 | stack_v2_sparse_classes_30k_train_003521 | Implement the Python class `APPDriver` described below.
Class description:
Implement the APPDriver class.
Method signatures and docstrings:
- def run(cls, data_set, uuid, host, **kwargs): Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { "path": "/login", "user": "user1", "version": 2, "request": [ {"eventName"... | Implement the Python class `APPDriver` described below.
Class description:
Implement the APPDriver class.
Method signatures and docstrings:
- def run(cls, data_set, uuid, host, **kwargs): Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { "path": "/login", "user": "user1", "version": 2, "request": [ {"eventName"... | 5ecae8652c9f71aaa78cc0fd181d431cb130cab1 | <|skeleton|>
class APPDriver:
def run(cls, data_set, uuid, host, **kwargs):
"""Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { "path": "/login", "user": "user1", "version": 2, "request": [ {"eventName": "元素点击", "event": "click", "locations": ["css selector", "#kw"], "input": "输入内容"}, {"eventName": ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class APPDriver:
def run(cls, data_set, uuid, host, **kwargs):
"""Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { "path": "/login", "user": "user1", "version": 2, "request": [ {"eventName": "元素点击", "event": "click", "locations": ["css selector", "#kw"], "input": "输入内容"}, {"eventName": "元素名称", "event... | the_stack_v2_python_sparse | giantstar/drivers/appDriver.py | DaoSen-v/giantstar | train | 0 | |
9c0565a7a799b4d983060bea22a4462692fd3731 | [
"if key:\n if cls.objects.filter(key=key).exists():\n return cls.objects.filter(key=key).first()\nif cls.objects.filter(key=None).exists():\n return cls.objects.filter(key=None).first()\nreturn None",
"if self.is_default_value:\n if self.key is None and self.__class__.objects.exclude(pk=self.pk).f... | <|body_start_0|>
if key:
if cls.objects.filter(key=key).exists():
return cls.objects.filter(key=key).first()
if cls.objects.filter(key=None).exists():
return cls.objects.filter(key=None).first()
return None
<|end_body_0|>
<|body_start_1|>
if self.... | Mixin for storing value with a unique default value for all and a unique default value for each item associated by key | StoreDataWithDefaultValueByKey | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StoreDataWithDefaultValueByKey:
"""Mixin for storing value with a unique default value for all and a unique default value for each item associated by key"""
def default_value(cls, key=None):
"""Return default value which is: - default value for the key if exists - else generic defaul... | stack_v2_sparse_classes_10k_train_002734 | 2,174 | no_license | [
{
"docstring": "Return default value which is: - default value for the key if exists - else generic default value if exists - else None",
"name": "default_value",
"signature": "def default_value(cls, key=None)"
},
{
"docstring": "verify that: - an unique value exists without a key - an unique va... | 2 | null | Implement the Python class `StoreDataWithDefaultValueByKey` described below.
Class description:
Mixin for storing value with a unique default value for all and a unique default value for each item associated by key
Method signatures and docstrings:
- def default_value(cls, key=None): Return default value which is: - ... | Implement the Python class `StoreDataWithDefaultValueByKey` described below.
Class description:
Mixin for storing value with a unique default value for all and a unique default value for each item associated by key
Method signatures and docstrings:
- def default_value(cls, key=None): Return default value which is: - ... | 95d21cd6036a99c5f399b700a5426e9e2e17e878 | <|skeleton|>
class StoreDataWithDefaultValueByKey:
"""Mixin for storing value with a unique default value for all and a unique default value for each item associated by key"""
def default_value(cls, key=None):
"""Return default value which is: - default value for the key if exists - else generic defaul... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StoreDataWithDefaultValueByKey:
"""Mixin for storing value with a unique default value for all and a unique default value for each item associated by key"""
def default_value(cls, key=None):
"""Return default value which is: - default value for the key if exists - else generic default value if ex... | the_stack_v2_python_sparse | helpers/mixins/store_data_with_default_value_by_key.py | alexandrenorman/mixeur | train | 0 |
81da77d8ade9f28e3235c0fb4f2cf51b5d1c0fde | [
"super().__init__()\nself.document_store: Optional[KeywordDocumentStore] = document_store\nself.top_k = top_k\nself.custom_query = custom_query\nself.all_terms_must_match = all_terms_must_match\nself.scale_score = scale_score",
"document_store = document_store or self.document_store\nif document_store is None:\n ... | <|body_start_0|>
super().__init__()
self.document_store: Optional[KeywordDocumentStore] = document_store
self.top_k = top_k
self.custom_query = custom_query
self.all_terms_must_match = all_terms_must_match
self.scale_score = scale_score
<|end_body_0|>
<|body_start_1|>
... | BM25Retriever | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BM25Retriever:
def __init__(self, document_store: Optional[KeywordDocumentStore]=None, top_k: int=10, all_terms_must_match: bool=False, custom_query: Optional[str]=None, scale_score: bool=True):
""":param document_store: An instance of one of the following DocumentStores to retrieve from... | stack_v2_sparse_classes_10k_train_002735 | 35,145 | permissive | [
{
"docstring": ":param document_store: An instance of one of the following DocumentStores to retrieve from: InMemoryDocumentStore, ElasticsearchDocumentStore and OpenSearchDocumentStore. If None, a document store must be passed to the retrieve method for this Retriever to work. :param all_terms_must_match: Whet... | 3 | null | Implement the Python class `BM25Retriever` described below.
Class description:
Implement the BM25Retriever class.
Method signatures and docstrings:
- def __init__(self, document_store: Optional[KeywordDocumentStore]=None, top_k: int=10, all_terms_must_match: bool=False, custom_query: Optional[str]=None, scale_score: ... | Implement the Python class `BM25Retriever` described below.
Class description:
Implement the BM25Retriever class.
Method signatures and docstrings:
- def __init__(self, document_store: Optional[KeywordDocumentStore]=None, top_k: int=10, all_terms_must_match: bool=False, custom_query: Optional[str]=None, scale_score: ... | 5f1256ac7e5734c2ea481e72cb7e02c34baf8c43 | <|skeleton|>
class BM25Retriever:
def __init__(self, document_store: Optional[KeywordDocumentStore]=None, top_k: int=10, all_terms_must_match: bool=False, custom_query: Optional[str]=None, scale_score: bool=True):
""":param document_store: An instance of one of the following DocumentStores to retrieve from... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BM25Retriever:
def __init__(self, document_store: Optional[KeywordDocumentStore]=None, top_k: int=10, all_terms_must_match: bool=False, custom_query: Optional[str]=None, scale_score: bool=True):
""":param document_store: An instance of one of the following DocumentStores to retrieve from: InMemoryDocu... | the_stack_v2_python_sparse | haystack/nodes/retriever/sparse.py | deepset-ai/haystack | train | 10,599 | |
f33f764617eb62dc99f6da5d7e4f03a484289520 | [
"d = departmentmanage(self.driver)\nd.open_departmentmanage()\nself.assertEqual(d.verify(), True)\nd.delete()\nself.assertEqual(d.reason(), '请选择一条数据')\nfunction.screenshot(self.driver, 'department_unselect.jpg')",
"d = departmentmanage(self.driver)\nd.open_departmentmanage()\nself.assertEqual(d.verify(), True)\nd... | <|body_start_0|>
d = departmentmanage(self.driver)
d.open_departmentmanage()
self.assertEqual(d.verify(), True)
d.delete()
self.assertEqual(d.reason(), '请选择一条数据')
function.screenshot(self.driver, 'department_unselect.jpg')
<|end_body_0|>
<|body_start_1|>
d = depa... | Test030_Deparment_List_Error | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test030_Deparment_List_Error:
def test_unselect(self):
"""不选择任何部门"""
<|body_0|>
def test_multiselect(self):
"""选择两个部门"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
d = departmentmanage(self.driver)
d.open_departmentmanage()
self.as... | stack_v2_sparse_classes_10k_train_002736 | 966 | no_license | [
{
"docstring": "不选择任何部门",
"name": "test_unselect",
"signature": "def test_unselect(self)"
},
{
"docstring": "选择两个部门",
"name": "test_multiselect",
"signature": "def test_multiselect(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001611 | Implement the Python class `Test030_Deparment_List_Error` described below.
Class description:
Implement the Test030_Deparment_List_Error class.
Method signatures and docstrings:
- def test_unselect(self): 不选择任何部门
- def test_multiselect(self): 选择两个部门 | Implement the Python class `Test030_Deparment_List_Error` described below.
Class description:
Implement the Test030_Deparment_List_Error class.
Method signatures and docstrings:
- def test_unselect(self): 不选择任何部门
- def test_multiselect(self): 选择两个部门
<|skeleton|>
class Test030_Deparment_List_Error:
def test_unse... | 6f42c25249fc642cecc270578a180820988d45b5 | <|skeleton|>
class Test030_Deparment_List_Error:
def test_unselect(self):
"""不选择任何部门"""
<|body_0|>
def test_multiselect(self):
"""选择两个部门"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test030_Deparment_List_Error:
def test_unselect(self):
"""不选择任何部门"""
d = departmentmanage(self.driver)
d.open_departmentmanage()
self.assertEqual(d.verify(), True)
d.delete()
self.assertEqual(d.reason(), '请选择一条数据')
function.screenshot(self.driver, 'depar... | the_stack_v2_python_sparse | GlxssLive_web/TestCase/Manage_Department/Test030_department_list_error.py | rrmiracle/GlxssLive | train | 0 | |
02eaaaa47a370e3bf2f2849f22dd1479e4fcd13d | [
"self.capacity = capacity\nself.length = 0\nself.dict = collections.OrderedDict()",
"if key in self.dict:\n val = self.dict[key]\n del self.dict[key]\n self.dict[key] = val\n return val\nelse:\n return -1",
"if key in self.dict:\n del self.dict[key]\n self.dict[key] = value\nelse:\n if s... | <|body_start_0|>
self.capacity = capacity
self.length = 0
self.dict = collections.OrderedDict()
<|end_body_0|>
<|body_start_1|>
if key in self.dict:
val = self.dict[key]
del self.dict[key]
self.dict[key] = val
return val
else:
... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_10k_train_002737 | 2,645 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: nothing",
"name": "set",
"sig... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing
<|skeleton|>
cla... | 56383c2b07448a9017a7a707afb66e08b403ee76 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.capacity = capacity
self.length = 0
self.dict = collections.OrderedDict()
def get(self, key):
""":rtype: int"""
if key in self.dict:
val = self.dict[key]
del self... | the_stack_v2_python_sparse | ALL_SOLUTIONS/146_OO_LRU_Cache.py | jamiezeminzhang/Leetcode_Python | train | 2 | |
70f558bb745f952980e493d930e815bf2081db3e | [
"self.game_active = False\nself.al_settings = al_settings\nself.reset_stats()\nself.high_score = 0",
"self.ships_left = self.al_settings.ship_limit\nself.score = 0\nself.level = 1"
] | <|body_start_0|>
self.game_active = False
self.al_settings = al_settings
self.reset_stats()
self.high_score = 0
<|end_body_0|>
<|body_start_1|>
self.ships_left = self.al_settings.ship_limit
self.score = 0
self.level = 1
<|end_body_1|>
| 跟踪游戏的统计信息 | GameStats | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameStats:
"""跟踪游戏的统计信息"""
def __init__(self, al_settings):
"""初始化统计信息"""
<|body_0|>
def reset_stats(self):
"""初始化在游戏运行期间可能改变的统计信息"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.game_active = False
self.al_settings = al_settings
... | stack_v2_sparse_classes_10k_train_002738 | 594 | no_license | [
{
"docstring": "初始化统计信息",
"name": "__init__",
"signature": "def __init__(self, al_settings)"
},
{
"docstring": "初始化在游戏运行期间可能改变的统计信息",
"name": "reset_stats",
"signature": "def reset_stats(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005212 | Implement the Python class `GameStats` described below.
Class description:
跟踪游戏的统计信息
Method signatures and docstrings:
- def __init__(self, al_settings): 初始化统计信息
- def reset_stats(self): 初始化在游戏运行期间可能改变的统计信息 | Implement the Python class `GameStats` described below.
Class description:
跟踪游戏的统计信息
Method signatures and docstrings:
- def __init__(self, al_settings): 初始化统计信息
- def reset_stats(self): 初始化在游戏运行期间可能改变的统计信息
<|skeleton|>
class GameStats:
"""跟踪游戏的统计信息"""
def __init__(self, al_settings):
"""初始化统计信息"""
... | bef0e99939b9fd4885b25ffea360b5745e7cc809 | <|skeleton|>
class GameStats:
"""跟踪游戏的统计信息"""
def __init__(self, al_settings):
"""初始化统计信息"""
<|body_0|>
def reset_stats(self):
"""初始化在游戏运行期间可能改变的统计信息"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GameStats:
"""跟踪游戏的统计信息"""
def __init__(self, al_settings):
"""初始化统计信息"""
self.game_active = False
self.al_settings = al_settings
self.reset_stats()
self.high_score = 0
def reset_stats(self):
"""初始化在游戏运行期间可能改变的统计信息"""
self.ships_left = self.al_... | the_stack_v2_python_sparse | game_stats.py | ssf-czh/alien_invision | train | 0 |
d29e9d9caa306fa9ecdf502a9a4b7203fdc637e2 | [
"self.logger = Log()\nself.logger.info('########################### TestCertification START ###########################')\nconfig = ReadYaml(FileUtil.getProjectObsPath() + '/config/config.yaml').getValue()\napp_package = config['appPackage_chezhu']\napp_activity = config['appActivity_chezhu']\nself.db = DbOperation... | <|body_start_0|>
self.logger = Log()
self.logger.info('########################### TestCertification START ###########################')
config = ReadYaml(FileUtil.getProjectObsPath() + '/config/config.yaml').getValue()
app_package = config['appPackage_chezhu']
app_activity = con... | 凯京车主APP 身份认证 | TestCertification | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCertification:
"""凯京车主APP 身份认证"""
def setUp(self):
"""前置条件准备"""
<|body_0|>
def tearDown(self):
"""测试环境重置"""
<|body_1|>
def test_bvt_certification(self):
"""身份认证"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
self.logger... | stack_v2_sparse_classes_10k_train_002739 | 2,842 | no_license | [
{
"docstring": "前置条件准备",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "测试环境重置",
"name": "tearDown",
"signature": "def tearDown(self)"
},
{
"docstring": "身份认证",
"name": "test_bvt_certification",
"signature": "def test_bvt_certification(self)"
}
] | 3 | stack_v2_sparse_classes_30k_train_002969 | Implement the Python class `TestCertification` described below.
Class description:
凯京车主APP 身份认证
Method signatures and docstrings:
- def setUp(self): 前置条件准备
- def tearDown(self): 测试环境重置
- def test_bvt_certification(self): 身份认证 | Implement the Python class `TestCertification` described below.
Class description:
凯京车主APP 身份认证
Method signatures and docstrings:
- def setUp(self): 前置条件准备
- def tearDown(self): 测试环境重置
- def test_bvt_certification(self): 身份认证
<|skeleton|>
class TestCertification:
"""凯京车主APP 身份认证"""
def setUp(self):
... | 4112ee34827a68289ba95a30518c4b1ecf38a3b2 | <|skeleton|>
class TestCertification:
"""凯京车主APP 身份认证"""
def setUp(self):
"""前置条件准备"""
<|body_0|>
def tearDown(self):
"""测试环境重置"""
<|body_1|>
def test_bvt_certification(self):
"""身份认证"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestCertification:
"""凯京车主APP 身份认证"""
def setUp(self):
"""前置条件准备"""
self.logger = Log()
self.logger.info('########################### TestCertification START ###########################')
config = ReadYaml(FileUtil.getProjectObsPath() + '/config/config.yaml').getValue()
... | the_stack_v2_python_sparse | BVT/chezhuAPP/driver_unregister/test_case/test_certification_chezhu.py | penny1205/AppUI | train | 0 |
414066553086dd0ceb7e4a5861656b1c1695ed38 | [
"assert instance is None\nsuper(UserApplicationCreationForm, self).__init__(data=data, initial=initial, instance=instance)\nself.user = user\nself.fields['local_site'].queryset = LocalSite.objects.filter(users=user)",
"instance = super(UserApplicationCreationForm, self).save(commit=False)\ninstance.user = self.us... | <|body_start_0|>
assert instance is None
super(UserApplicationCreationForm, self).__init__(data=data, initial=initial, instance=instance)
self.user = user
self.fields['local_site'].queryset = LocalSite.objects.filter(users=user)
<|end_body_0|>
<|body_start_1|>
instance = super(U... | A form for an end user to update an Application. | UserApplicationCreationForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserApplicationCreationForm:
"""A form for an end user to update an Application."""
def __init__(self, user, data, initial=None, instance=None):
"""Initialize the form. Args: user (django.contrib.auth.models.User): The user changing the form. Ignored, but included to match :py:meth:`... | stack_v2_sparse_classes_10k_train_002740 | 13,782 | permissive | [
{
"docstring": "Initialize the form. Args: user (django.contrib.auth.models.User): The user changing the form. Ignored, but included to match :py:meth:`UserApplicationCreationForm.__init__`. data (dict): The provided data. initial (dict, optional): The initial form values. instance (reviewboard.oauth.models.App... | 2 | stack_v2_sparse_classes_30k_train_005745 | Implement the Python class `UserApplicationCreationForm` described below.
Class description:
A form for an end user to update an Application.
Method signatures and docstrings:
- def __init__(self, user, data, initial=None, instance=None): Initialize the form. Args: user (django.contrib.auth.models.User): The user cha... | Implement the Python class `UserApplicationCreationForm` described below.
Class description:
A form for an end user to update an Application.
Method signatures and docstrings:
- def __init__(self, user, data, initial=None, instance=None): Initialize the form. Args: user (django.contrib.auth.models.User): The user cha... | c3a991f1e9d7682239a1ab0e8661cee6da01d537 | <|skeleton|>
class UserApplicationCreationForm:
"""A form for an end user to update an Application."""
def __init__(self, user, data, initial=None, instance=None):
"""Initialize the form. Args: user (django.contrib.auth.models.User): The user changing the form. Ignored, but included to match :py:meth:`... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserApplicationCreationForm:
"""A form for an end user to update an Application."""
def __init__(self, user, data, initial=None, instance=None):
"""Initialize the form. Args: user (django.contrib.auth.models.User): The user changing the form. Ignored, but included to match :py:meth:`UserApplicati... | the_stack_v2_python_sparse | reviewboard/oauth/forms.py | reviewboard/reviewboard | train | 1,141 |
b9d676a34e4a83f592580247ecde07aa85750585 | [
"params = dict(request.query_params)\nparams.update(dict(request.data))\nqueryset = kwargs.get('queryset', None)\nagg_field, group_fields, date_part = self.validate_request(params, queryset)\nif not params.get('show_null_groups', False) and (not params.get('show_nulls', False)):\n q_object = Q()\n for field i... | <|body_start_0|>
params = dict(request.query_params)
params.update(dict(request.data))
queryset = kwargs.get('queryset', None)
agg_field, group_fields, date_part = self.validate_request(params, queryset)
if not params.get('show_null_groups', False) and (not params.get('show_nulls... | Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method). | AggregateQuerysetMixin | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AggregateQuerysetMixin:
"""Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method)."""
def aggregate(self, request, *args, **kwargs):
"""Perform an aggregate function on a Djang... | stack_v2_sparse_classes_10k_train_002741 | 10,956 | permissive | [
{
"docstring": "Perform an aggregate function on a Django queryset with an optional group by field.",
"name": "aggregate",
"signature": "def aggregate(self, request, *args, **kwargs)"
},
{
"docstring": "F-expression of col, wrapped if needed with SQL function call Assumes that there's an SQL fun... | 3 | stack_v2_sparse_classes_30k_train_000813 | Implement the Python class `AggregateQuerysetMixin` described below.
Class description:
Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method).
Method signatures and docstrings:
- def aggregate(self, request, *... | Implement the Python class `AggregateQuerysetMixin` described below.
Class description:
Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method).
Method signatures and docstrings:
- def aggregate(self, request, *... | 38f920438697930ae3ac57bbcaae9034877d8fb7 | <|skeleton|>
class AggregateQuerysetMixin:
"""Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method)."""
def aggregate(self, request, *args, **kwargs):
"""Perform an aggregate function on a Djang... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AggregateQuerysetMixin:
"""Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method)."""
def aggregate(self, request, *args, **kwargs):
"""Perform an aggregate function on a Django queryset wi... | the_stack_v2_python_sparse | usaspending_api/common/mixins.py | fedspendingtransparency/usaspending-api | train | 276 |
3a14029ec4b6b63ca761985e8e6950028285728d | [
"if target == 0:\n res.append(tem_res)\n return\nif index >= len(candidates) or target < candidates[index]:\n return\nfor i in range(index, len(candidates)):\n if i > index and candidates[i] == candidates[i - 1]:\n continue\n if target < candidates[i]:\n break\n self.curSum(self, can... | <|body_start_0|>
if target == 0:
res.append(tem_res)
return
if index >= len(candidates) or target < candidates[index]:
return
for i in range(index, len(candidates)):
if i > index and candidates[i] == candidates[i - 1]:
continue
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def curSum(self, candidates, index, target, tem_res, res):
""":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果"""
<|body_0|>
def combinationSum(self, candidates, target):
""":type candidates: List[int] :type target: ... | stack_v2_sparse_classes_10k_train_002742 | 1,196 | no_license | [
{
"docstring": ":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果",
"name": "curSum",
"signature": "def curSum(self, candidates, index, target, tem_res, res)"
},
{
"docstring": ":type candidates: List[int] :type target: int :rtype: List[List[int]] :组合相加",
... | 2 | stack_v2_sparse_classes_30k_train_004172 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def curSum(self, candidates, index, target, tem_res, res): :param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果
- def combinationSum(self, ca... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def curSum(self, candidates, index, target, tem_res, res): :param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果
- def combinationSum(self, ca... | 45fafcc5dd8f3a9dd26984dc6e82441cc2e8f8d7 | <|skeleton|>
class Solution:
def curSum(self, candidates, index, target, tem_res, res):
""":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果"""
<|body_0|>
def combinationSum(self, candidates, target):
""":type candidates: List[int] :type target: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def curSum(self, candidates, index, target, tem_res, res):
""":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果"""
if target == 0:
res.append(tem_res)
return
if index >= len(candidates) or target < candidates[ind... | the_stack_v2_python_sparse | T40.py | zhanggyang/leedcode | train | 0 | |
68b52a74cae7391bac16318b84b53373aa6afdd0 | [
"h = {}\ni = 0\nc = 0\ncc = 0\nwhile i < len(s):\n if s[i] not in h:\n h[s[i]] = i\n cc += 1\n i += 1\n else:\n i = h[s[i]] + 1\n h = {}\n c = max(cc, c)\n cc = 0\nc = max(cc, c)\nreturn c",
"h = {}\ni = 0\nc = 0\ncc = 0\nt = -1\nwhile i < len(s):\n if s[i... | <|body_start_0|>
h = {}
i = 0
c = 0
cc = 0
while i < len(s):
if s[i] not in h:
h[s[i]] = i
cc += 1
i += 1
else:
i = h[s[i]] + 1
h = {}
c = max(cc, c)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def lengthOfLongestSubstring1(self, s):
""":type s: str :rtype: int"""
<|body_1|>
def lengthOfLongestSubstring2(self, s):
""":type s: str :rtype: int"""
... | stack_v2_sparse_classes_10k_train_002743 | 1,723 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "lengthOfLongestSubstring",
"signature": "def lengthOfLongestSubstring(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "lengthOfLongestSubstring1",
"signature": "def lengthOfLongestSubstring1(self, s)"
},
{
"docst... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring1(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring2(self, s): :type... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring1(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring2(self, s): :type... | 5b535795cdd742b7810ea163e0868b022736647d | <|skeleton|>
class Solution:
def lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def lengthOfLongestSubstring1(self, s):
""":type s: str :rtype: int"""
<|body_1|>
def lengthOfLongestSubstring2(self, s):
""":type s: str :rtype: int"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
h = {}
i = 0
c = 0
cc = 0
while i < len(s):
if s[i] not in h:
h[s[i]] = i
cc += 1
i += 1
else:
... | the_stack_v2_python_sparse | Leetcode_Longest_Substring_wo_rep_chars.py | Cbkhare/Codes | train | 0 | |
90eb0741763786791b3bb7a0bda0ba3851097594 | [
"col = self.db.tag_ware\nvals = col.find()\nkey = [item['total'] for item in vals]\nres = {'tag': key}\nlogger.info('获取所有标签')\nreturn BackstageHTTPResponse(message=u'成功获取所有标签', data=res).to_response()",
"collection = self.db.tag_ware\ndata = self.request_data(request)\nname = data['name']\ntag = data['tag']\ntag_... | <|body_start_0|>
col = self.db.tag_ware
vals = col.find()
key = [item['total'] for item in vals]
res = {'tag': key}
logger.info('获取所有标签')
return BackstageHTTPResponse(message=u'成功获取所有标签', data=res).to_response()
<|end_body_0|>
<|body_start_1|>
collection = self.d... | ManualTagView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManualTagView:
def get(self, request):
"""获取所有标签 --- :param request: :return:"""
<|body_0|>
def post(self, request):
"""新增一个标签 --- parameters: - name: name description: 名称 type: string paramType: form required: true - name: tag description: 标签 type: string paramType:... | stack_v2_sparse_classes_10k_train_002744 | 7,342 | no_license | [
{
"docstring": "获取所有标签 --- :param request: :return:",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "新增一个标签 --- parameters: - name: name description: 名称 type: string paramType: form required: true - name: tag description: 标签 type: string paramType: form required: true - ... | 4 | null | Implement the Python class `ManualTagView` described below.
Class description:
Implement the ManualTagView class.
Method signatures and docstrings:
- def get(self, request): 获取所有标签 --- :param request: :return:
- def post(self, request): 新增一个标签 --- parameters: - name: name description: 名称 type: string paramType: form ... | Implement the Python class `ManualTagView` described below.
Class description:
Implement the ManualTagView class.
Method signatures and docstrings:
- def get(self, request): 获取所有标签 --- :param request: :return:
- def post(self, request): 新增一个标签 --- parameters: - name: name description: 名称 type: string paramType: form ... | c50def8cde58fd4663032b860eb058302cbac6da | <|skeleton|>
class ManualTagView:
def get(self, request):
"""获取所有标签 --- :param request: :return:"""
<|body_0|>
def post(self, request):
"""新增一个标签 --- parameters: - name: name description: 名称 type: string paramType: form required: true - name: tag description: 标签 type: string paramType:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ManualTagView:
def get(self, request):
"""获取所有标签 --- :param request: :return:"""
col = self.db.tag_ware
vals = col.find()
key = [item['total'] for item in vals]
res = {'tag': key}
logger.info('获取所有标签')
return BackstageHTTPResponse(message=u'成功获取所有标签', da... | the_stack_v2_python_sparse | src/api/backstage/views/manual_tags.py | fan1018wen/Alpha | train | 0 | |
ad7ba22445301b9385ebed15e19b5233c9d39bae | [
"if is_callable(type_):\n callable_args = type_.__args__\n argument_types = [PredicateType.get_type(t) for t in callable_args[:-1]]\n return_type = PredicateType.get_type(callable_args[-1])\n return FunctionType(argument_types, return_type)\nelif is_generic(type_):\n name = get_generic_name(type_)\ne... | <|body_start_0|>
if is_callable(type_):
callable_args = type_.__args__
argument_types = [PredicateType.get_type(t) for t in callable_args[:-1]]
return_type = PredicateType.get_type(callable_args[-1])
return FunctionType(argument_types, return_type)
elif is... | A base class for `types` in a domain language. This serves much the same purpose as ``typing.Type``, but we add a few conveniences to these types, so we construct separate classes for them and group them together under ``PredicateType`` to have a good type annotation for these types. | PredicateType | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PredicateType:
"""A base class for `types` in a domain language. This serves much the same purpose as ``typing.Type``, but we add a few conveniences to these types, so we construct separate classes for them and group them together under ``PredicateType`` to have a good type annotation for these t... | stack_v2_sparse_classes_10k_train_002745 | 39,954 | permissive | [
{
"docstring": "Converts a python ``Type`` (as you might get from a type annotation) into a ``PredicateType``. If the ``Type`` is callable, this will return a ``FunctionType``; otherwise, it will return a ``BasicType``. ``BasicTypes`` have a single ``name`` parameter - we typically get this from ``type_.__name_... | 2 | null | Implement the Python class `PredicateType` described below.
Class description:
A base class for `types` in a domain language. This serves much the same purpose as ``typing.Type``, but we add a few conveniences to these types, so we construct separate classes for them and group them together under ``PredicateType`` to ... | Implement the Python class `PredicateType` described below.
Class description:
A base class for `types` in a domain language. This serves much the same purpose as ``typing.Type``, but we add a few conveniences to these types, so we construct separate classes for them and group them together under ``PredicateType`` to ... | ccf60824b28f0ce8ceda44a7ce52a0d117669115 | <|skeleton|>
class PredicateType:
"""A base class for `types` in a domain language. This serves much the same purpose as ``typing.Type``, but we add a few conveniences to these types, so we construct separate classes for them and group them together under ``PredicateType`` to have a good type annotation for these t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PredicateType:
"""A base class for `types` in a domain language. This serves much the same purpose as ``typing.Type``, but we add a few conveniences to these types, so we construct separate classes for them and group them together under ``PredicateType`` to have a good type annotation for these types."""
... | the_stack_v2_python_sparse | allennlp/allennlp/semparse/domain_languages/domain_language.py | ethanjperez/convince | train | 27 |
74f1111f9ecdaf80c30922405f488a499f7bda05 | [
"super(Net, self).__init__()\nself.input_dim = input_dim\nself.hidden_size = hidden_size\nself.output_dim = output_dim\nself.num_layers = num_layers\nself.layer_type = layer_type\nself.output_activation = output_activation\nself.internal_batch_norm = internal_batch_norm\nself.skip_connection = skip_connection\nself... | <|body_start_0|>
super(Net, self).__init__()
self.input_dim = input_dim
self.hidden_size = hidden_size
self.output_dim = output_dim
self.num_layers = num_layers
self.layer_type = layer_type
self.output_activation = output_activation
self.internal_batch_nor... | RealNVP neural network definitions. | Net | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Net:
"""RealNVP neural network definitions."""
def __init__(self, input_dim: int, hidden_size: int, output_dim: int=None, num_layers: int=3, layer_type: Literal['s', 't']='s', output_activation: Literal['tanh', 'lrelu']='tanh', internal_batch_norm: bool=False, skip_connection: bool=False) ->... | stack_v2_sparse_classes_10k_train_002746 | 8,028 | permissive | [
{
"docstring": "RealNVP neural network definition. :param input_dim: Data input dimension. :param hidden_size: Neural network hidden size. :param output_dim: Output dimension. :param num_layers: Number of linear layers. :param layer_type: \"s\" vs \"t\" type layer. :param output_activation: \"s\" network output... | 2 | stack_v2_sparse_classes_30k_train_006143 | Implement the Python class `Net` described below.
Class description:
RealNVP neural network definitions.
Method signatures and docstrings:
- def __init__(self, input_dim: int, hidden_size: int, output_dim: int=None, num_layers: int=3, layer_type: Literal['s', 't']='s', output_activation: Literal['tanh', 'lrelu']='tan... | Implement the Python class `Net` described below.
Class description:
RealNVP neural network definitions.
Method signatures and docstrings:
- def __init__(self, input_dim: int, hidden_size: int, output_dim: int=None, num_layers: int=3, layer_type: Literal['s', 't']='s', output_activation: Literal['tanh', 'lrelu']='tan... | f470849d5b7b90dc5a65bab8a536de1d57c1021a | <|skeleton|>
class Net:
"""RealNVP neural network definitions."""
def __init__(self, input_dim: int, hidden_size: int, output_dim: int=None, num_layers: int=3, layer_type: Literal['s', 't']='s', output_activation: Literal['tanh', 'lrelu']='tanh', internal_batch_norm: bool=False, skip_connection: bool=False) ->... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Net:
"""RealNVP neural network definitions."""
def __init__(self, input_dim: int, hidden_size: int, output_dim: int=None, num_layers: int=3, layer_type: Literal['s', 't']='s', output_activation: Literal['tanh', 'lrelu']='tanh', internal_batch_norm: bool=False, skip_connection: bool=False) -> None:
... | the_stack_v2_python_sparse | conformation/model.py | ks8/conformation | train | 1 |
579a0b07dad117162c119cc43c9ae6f84a3085f4 | [
"mock_settings.ENABLE_NOTIFICATIONS = True\n\n@do_maybe_notification\ndef create_split():\n Splits = namedtuple('Splits', 'data')\n return Splits([{'id': 1}, {'id': 2}])\ncreate_split()\nmock_queue.add.assert_has_calls([mock.call(params={'split': 1}, url='/notifications/notify/'), mock.call(params={'split': 2... | <|body_start_0|>
mock_settings.ENABLE_NOTIFICATIONS = True
@do_maybe_notification
def create_split():
Splits = namedtuple('Splits', 'data')
return Splits([{'id': 1}, {'id': 2}])
create_split()
mock_queue.add.assert_has_calls([mock.call(params={'split': 1}... | NotifyTestCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotifyTestCase:
def test_task_queue_decorator(self, mock_queue, mock_settings):
"""Test the decorator that puts message tasks in the queue."""
<|body_0|>
def test_notify_endpoint(self, mock_send):
"""Test sending an update message from a post to /notify."""
<... | stack_v2_sparse_classes_10k_train_002747 | 2,183 | permissive | [
{
"docstring": "Test the decorator that puts message tasks in the queue.",
"name": "test_task_queue_decorator",
"signature": "def test_task_queue_decorator(self, mock_queue, mock_settings)"
},
{
"docstring": "Test sending an update message from a post to /notify.",
"name": "test_notify_endpo... | 2 | stack_v2_sparse_classes_30k_train_005396 | Implement the Python class `NotifyTestCase` described below.
Class description:
Implement the NotifyTestCase class.
Method signatures and docstrings:
- def test_task_queue_decorator(self, mock_queue, mock_settings): Test the decorator that puts message tasks in the queue.
- def test_notify_endpoint(self, mock_send): ... | Implement the Python class `NotifyTestCase` described below.
Class description:
Implement the NotifyTestCase class.
Method signatures and docstrings:
- def test_task_queue_decorator(self, mock_queue, mock_settings): Test the decorator that puts message tasks in the queue.
- def test_notify_endpoint(self, mock_send): ... | 46c4a1fe409a45e8595210a5cf242425d40d4b41 | <|skeleton|>
class NotifyTestCase:
def test_task_queue_decorator(self, mock_queue, mock_settings):
"""Test the decorator that puts message tasks in the queue."""
<|body_0|>
def test_notify_endpoint(self, mock_send):
"""Test sending an update message from a post to /notify."""
<... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NotifyTestCase:
def test_task_queue_decorator(self, mock_queue, mock_settings):
"""Test the decorator that puts message tasks in the queue."""
mock_settings.ENABLE_NOTIFICATIONS = True
@do_maybe_notification
def create_split():
Splits = namedtuple('Splits', 'data')... | the_stack_v2_python_sparse | apps/notifications/tests.py | tractiming/trac-gae | train | 5 | |
6f1bcea99af09f0bd30fab0cc486c8e6fe043792 | [
"self.center = center\nself.indices = indices\nself.score = score\nself.left = None\nself.right = None",
"self.left = _BisectingTree(indices=self.indices[labels == 0], center=centers[0], score=scores[0])\nself.right = _BisectingTree(indices=self.indices[labels == 1], center=centers[1], score=scores[1])\nself.indi... | <|body_start_0|>
self.center = center
self.indices = indices
self.score = score
self.left = None
self.right = None
<|end_body_0|>
<|body_start_1|>
self.left = _BisectingTree(indices=self.indices[labels == 0], center=centers[0], score=scores[0])
self.right = _Bise... | Tree structure representing the hierarchical clusters of BisectingKMeans. | _BisectingTree | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _BisectingTree:
"""Tree structure representing the hierarchical clusters of BisectingKMeans."""
def __init__(self, center, indices, score):
"""Create a new cluster node in the tree. The node holds the center of this cluster and the indices of the data points that belong to it."""
... | stack_v2_sparse_classes_10k_train_002748 | 18,882 | permissive | [
{
"docstring": "Create a new cluster node in the tree. The node holds the center of this cluster and the indices of the data points that belong to it.",
"name": "__init__",
"signature": "def __init__(self, center, indices, score)"
},
{
"docstring": "Split the cluster node into two subclusters.",... | 4 | null | Implement the Python class `_BisectingTree` described below.
Class description:
Tree structure representing the hierarchical clusters of BisectingKMeans.
Method signatures and docstrings:
- def __init__(self, center, indices, score): Create a new cluster node in the tree. The node holds the center of this cluster and... | Implement the Python class `_BisectingTree` described below.
Class description:
Tree structure representing the hierarchical clusters of BisectingKMeans.
Method signatures and docstrings:
- def __init__(self, center, indices, score): Create a new cluster node in the tree. The node holds the center of this cluster and... | 061f8777b48e5491b0c57bb8e0bc7067c103079d | <|skeleton|>
class _BisectingTree:
"""Tree structure representing the hierarchical clusters of BisectingKMeans."""
def __init__(self, center, indices, score):
"""Create a new cluster node in the tree. The node holds the center of this cluster and the indices of the data points that belong to it."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _BisectingTree:
"""Tree structure representing the hierarchical clusters of BisectingKMeans."""
def __init__(self, center, indices, score):
"""Create a new cluster node in the tree. The node holds the center of this cluster and the indices of the data points that belong to it."""
self.cen... | the_stack_v2_python_sparse | sklearn/cluster/_bisect_k_means.py | scikit-learn/scikit-learn | train | 58,456 |
33ec09ba13f6846d5027bb4199082f3bab99bd67 | [
"if not l or not r or r < l:\n return list()\nt = list()\nfor i in range(l, r + 1, 1):\n if self.is_self_dividing(i):\n t.append(i)\nreturn t",
"if not i:\n return False\np = i\nwhile p > 0:\n p, d = divmod(p, 10)\n if d == 0 or i % d != 0:\n return False\nreturn True"
] | <|body_start_0|>
if not l or not r or r < l:
return list()
t = list()
for i in range(l, r + 1, 1):
if self.is_self_dividing(i):
t.append(i)
return t
<|end_body_0|>
<|body_start_1|>
if not i:
return False
p = i
w... | Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range | Solution2 | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution2:
"""Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range"""
def find_self_dividing_nums(self, l, r):
"""Determines all self-dividing numbers... | stack_v2_sparse_classes_10k_train_002749 | 3,918 | permissive | [
{
"docstring": "Determines all self-dividing numbers within target limits (inclusive). :param int l: lower limit of target range :param int r: upper limit of target range :return: array of all self-dividing numbers in range :rtype: list[int]",
"name": "find_self_dividing_nums",
"signature": "def find_se... | 2 | stack_v2_sparse_classes_30k_train_004466 | Implement the Python class `Solution2` described below.
Class description:
Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range
Method signatures and docstrings:
- def find_self_dividi... | Implement the Python class `Solution2` described below.
Class description:
Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range
Method signatures and docstrings:
- def find_self_dividi... | 69f90877c5466927e8b081c4268cbcda074813ec | <|skeleton|>
class Solution2:
"""Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range"""
def find_self_dividing_nums(self, l, r):
"""Determines all self-dividing numbers... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution2:
"""Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range"""
def find_self_dividing_nums(self, l, r):
"""Determines all self-dividing numbers within targe... | the_stack_v2_python_sparse | 0728_self_dividing_numbers/python_source.py | arthurdysart/LeetCode | train | 0 |
7576348745a1722575e4c4a2164b05aeca070a5f | [
"s1, s2 = ('', '')\nwhile l1:\n s1 = s1 + str(l1.val)\n l1 = l1.next\nwhile l2:\n s2 = s2 + str(l2.val)\n l2 = l2.next\nnum = int(s1[::-1]) + int(s2[::-1])\nnum = str(num)[::-1]\npivot = head = ListNode(num[0])\nfor x in num[1:]:\n head.next = ListNode(int(x))\n head = head.next\nreturn pivot",
... | <|body_start_0|>
s1, s2 = ('', '')
while l1:
s1 = s1 + str(l1.val)
l1 = l1.next
while l2:
s2 = s2 + str(l2.val)
l2 = l2.next
num = int(s1[::-1]) + int(s2[::-1])
num = str(num)[::-1]
pivot = head = ListNode(num[0])
fo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def addTwoNumbers1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""先遍历生成int,求值后再生成链表。"""
<|body_0|>
def addTwoNumbers2(self, l1: ListNode, l2: ListNode) -> ListNode:
"""内置函数divmod() x,y = divmod(m,n) x = m//n y = m%n"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k_train_002750 | 2,266 | no_license | [
{
"docstring": "先遍历生成int,求值后再生成链表。",
"name": "addTwoNumbers1",
"signature": "def addTwoNumbers1(self, l1: ListNode, l2: ListNode) -> ListNode"
},
{
"docstring": "内置函数divmod() x,y = divmod(m,n) x = m//n y = m%n",
"name": "addTwoNumbers2",
"signature": "def addTwoNumbers2(self, l1: ListNod... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addTwoNumbers1(self, l1: ListNode, l2: ListNode) -> ListNode: 先遍历生成int,求值后再生成链表。
- def addTwoNumbers2(self, l1: ListNode, l2: ListNode) -> ListNode: 内置函数divmod() x,y = divmod... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addTwoNumbers1(self, l1: ListNode, l2: ListNode) -> ListNode: 先遍历生成int,求值后再生成链表。
- def addTwoNumbers2(self, l1: ListNode, l2: ListNode) -> ListNode: 内置函数divmod() x,y = divmod... | 2bbb1640589aab34f2bc42489283033cc11fb885 | <|skeleton|>
class Solution:
def addTwoNumbers1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""先遍历生成int,求值后再生成链表。"""
<|body_0|>
def addTwoNumbers2(self, l1: ListNode, l2: ListNode) -> ListNode:
"""内置函数divmod() x,y = divmod(m,n) x = m//n y = m%n"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def addTwoNumbers1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""先遍历生成int,求值后再生成链表。"""
s1, s2 = ('', '')
while l1:
s1 = s1 + str(l1.val)
l1 = l1.next
while l2:
s2 = s2 + str(l2.val)
l2 = l2.next
num = int(s1[... | the_stack_v2_python_sparse | 002_add-two-numbers.py | helloocc/algorithm | train | 1 | |
70716cd42162faaa4fb32feda47f1aea36b63610 | [
"schema = getattr(cls, '__schema__')\nif schema is None:\n raise Exception(f'{cls.__name__}: not serializable; missing schema')\nreturn schema",
"d = self.schema().dump(self) if camel_case else {humps.decamelize(k): v for k, v in self.schema().dump(self).items()}\nif drop_nulls:\n d = _drop_nulls(d)\ns = js... | <|body_start_0|>
schema = getattr(cls, '__schema__')
if schema is None:
raise Exception(f'{cls.__name__}: not serializable; missing schema')
return schema
<|end_body_0|>
<|body_start_1|>
d = self.schema().dump(self) if camel_case else {humps.decamelize(k): v for k, v in self... | Marks that a class is serializeable to JSON. | Serializable | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Serializable:
"""Marks that a class is serializeable to JSON."""
def schema(cls):
"""Gets the marshmallow serializer for the implementing class."""
<|body_0|>
def to_json(self, camel_case: bool=True, pretty_print: bool=True, drop_nulls: bool=False) -> str:
"""Con... | stack_v2_sparse_classes_10k_train_002751 | 2,677 | permissive | [
{
"docstring": "Gets the marshmallow serializer for the implementing class.",
"name": "schema",
"signature": "def schema(cls)"
},
{
"docstring": "Convert an implementing instance to JSON. Parameters ---------- camel_case : bool (default True) If True, the keys of the returned dict will be camel-... | 3 | stack_v2_sparse_classes_30k_train_003597 | Implement the Python class `Serializable` described below.
Class description:
Marks that a class is serializeable to JSON.
Method signatures and docstrings:
- def schema(cls): Gets the marshmallow serializer for the implementing class.
- def to_json(self, camel_case: bool=True, pretty_print: bool=True, drop_nulls: bo... | Implement the Python class `Serializable` described below.
Class description:
Marks that a class is serializeable to JSON.
Method signatures and docstrings:
- def schema(cls): Gets the marshmallow serializer for the implementing class.
- def to_json(self, camel_case: bool=True, pretty_print: bool=True, drop_nulls: bo... | dca436188e062fd07dfe589ee61e8bb97aa3ea98 | <|skeleton|>
class Serializable:
"""Marks that a class is serializeable to JSON."""
def schema(cls):
"""Gets the marshmallow serializer for the implementing class."""
<|body_0|>
def to_json(self, camel_case: bool=True, pretty_print: bool=True, drop_nulls: bool=False) -> str:
"""Con... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Serializable:
"""Marks that a class is serializeable to JSON."""
def schema(cls):
"""Gets the marshmallow serializer for the implementing class."""
schema = getattr(cls, '__schema__')
if schema is None:
raise Exception(f'{cls.__name__}: not serializable; missing schema... | the_stack_v2_python_sparse | core/json.py | clohr/model-service | train | 1 |
49e2e64348c5563e3bedafceb853bf9ffc423d4a | [
"if isinstance(final_states, Qobj) or final_states is None:\n self.final_states = [final_states]\n self.probabilities = [probabilities]\n if cbits:\n self.cbits = [cbits]\nelse:\n inds = list(filter(lambda x: final_states[x] is not None, range(len(final_states))))\n self.final_states = [final_... | <|body_start_0|>
if isinstance(final_states, Qobj) or final_states is None:
self.final_states = [final_states]
self.probabilities = [probabilities]
if cbits:
self.cbits = [cbits]
else:
inds = list(filter(lambda x: final_states[x] is not Non... | Result of a quantum circuit simulation. | CircuitResult | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CircuitResult:
"""Result of a quantum circuit simulation."""
def __init__(self, final_states, probabilities, cbits=None):
"""Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output kets or density matrices. probabilities: list of float. List... | stack_v2_sparse_classes_10k_train_002752 | 23,944 | permissive | [
{
"docstring": "Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output kets or density matrices. probabilities: list of float. List of probabilities of obtaining each output state. cbits: list of list of int, optional List of cbits for each output.",
"name": "__in... | 4 | stack_v2_sparse_classes_30k_train_002433 | Implement the Python class `CircuitResult` described below.
Class description:
Result of a quantum circuit simulation.
Method signatures and docstrings:
- def __init__(self, final_states, probabilities, cbits=None): Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output ket... | Implement the Python class `CircuitResult` described below.
Class description:
Result of a quantum circuit simulation.
Method signatures and docstrings:
- def __init__(self, final_states, probabilities, cbits=None): Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output ket... | a5e97023cc84ba7509b0ee65d742b8a0ae19fdf0 | <|skeleton|>
class CircuitResult:
"""Result of a quantum circuit simulation."""
def __init__(self, final_states, probabilities, cbits=None):
"""Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output kets or density matrices. probabilities: list of float. List... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CircuitResult:
"""Result of a quantum circuit simulation."""
def __init__(self, final_states, probabilities, cbits=None):
"""Store result of CircuitSimulator. Parameters ---------- final_states: list of Qobj. List of output kets or density matrices. probabilities: list of float. List of probabili... | the_stack_v2_python_sparse | src/qutip_qip/circuit/circuitsimulator.py | qutip/qutip-qip | train | 84 |
cefbd0464db5762ad670394baf0502c961302603 | [
"self.caffe = Caffe.objects.create(name='kafo', city='Gliwice', street='Wieczorka', house_number='14', postal_code='44-100')\nself.filtry = Caffe.objects.create(name='filtry', city='Warszawa', street='Filry', house_number='14', postal_code='44-100')\nfirst_cat = Category.objects.create(name='first', caffe=self.caff... | <|body_start_0|>
self.caffe = Caffe.objects.create(name='kafo', city='Gliwice', street='Wieczorka', house_number='14', postal_code='44-100')
self.filtry = Caffe.objects.create(name='filtry', city='Warszawa', street='Filry', house_number='14', postal_code='44-100')
first_cat = Category.objects.cr... | FullProduct tests. | FullProductModelTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FullProductModelTest:
"""FullProduct tests."""
def setUp(self):
"""Test data setup."""
<|body_0|>
def test_full_product(self):
"""Test creating FullProducts."""
<|body_1|>
def test_fullproduct_validation(self):
"""Check if FullProduct has pro... | stack_v2_sparse_classes_10k_train_002753 | 14,711 | permissive | [
{
"docstring": "Test data setup.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test creating FullProducts.",
"name": "test_full_product",
"signature": "def test_full_product(self)"
},
{
"docstring": "Check if FullProduct has proper validation.",
"name":... | 3 | stack_v2_sparse_classes_30k_train_000532 | Implement the Python class `FullProductModelTest` described below.
Class description:
FullProduct tests.
Method signatures and docstrings:
- def setUp(self): Test data setup.
- def test_full_product(self): Test creating FullProducts.
- def test_fullproduct_validation(self): Check if FullProduct has proper validation. | Implement the Python class `FullProductModelTest` described below.
Class description:
FullProduct tests.
Method signatures and docstrings:
- def setUp(self): Test data setup.
- def test_full_product(self): Test creating FullProducts.
- def test_fullproduct_validation(self): Check if FullProduct has proper validation.... | cdb7f5edb29255c7e874eaa6231621063210a8b0 | <|skeleton|>
class FullProductModelTest:
"""FullProduct tests."""
def setUp(self):
"""Test data setup."""
<|body_0|>
def test_full_product(self):
"""Test creating FullProducts."""
<|body_1|>
def test_fullproduct_validation(self):
"""Check if FullProduct has pro... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FullProductModelTest:
"""FullProduct tests."""
def setUp(self):
"""Test data setup."""
self.caffe = Caffe.objects.create(name='kafo', city='Gliwice', street='Wieczorka', house_number='14', postal_code='44-100')
self.filtry = Caffe.objects.create(name='filtry', city='Warszawa', str... | the_stack_v2_python_sparse | caffe/reports/test_models.py | VirrageS/io-kawiarnie | train | 3 |
9495ccc6c21bd33d4569f3b40b22860e6fc2821b | [
"if not self.ITEM_MODEL:\n raise NotImplementedError(f'ITEM_MODEL attribute not defined for {__class__}')\nids = []\nfor k in [self.ITEM_KEY + x for x in ['', '[]', 's', 's[]']]:\n if (ids := self.request.query_params.getlist(k, [])):\n break\nvalid_ids = []\nfor id in ids:\n try:\n valid_ids... | <|body_start_0|>
if not self.ITEM_MODEL:
raise NotImplementedError(f'ITEM_MODEL attribute not defined for {__class__}')
ids = []
for k in [self.ITEM_KEY + x for x in ['', '[]', 's', 's[]']]:
if (ids := self.request.query_params.getlist(k, [])):
break
... | Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which provides a generic implementation to return a list of matching database model instances | ReportFilterMixin | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReportFilterMixin:
"""Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which provides a generic implementation to return... | stack_v2_sparse_classes_10k_train_002754 | 19,444 | permissive | [
{
"docstring": "Return a list of database objects from query parameters",
"name": "get_items",
"signature": "def get_items(self)"
},
{
"docstring": "Filter the queryset based on the provided report ID values. As each 'report' instance may optionally define its own filters, the resulting queryset... | 2 | stack_v2_sparse_classes_30k_test_000162 | Implement the Python class `ReportFilterMixin` described below.
Class description:
Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which prov... | Implement the Python class `ReportFilterMixin` described below.
Class description:
Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which prov... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class ReportFilterMixin:
"""Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which provides a generic implementation to return... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ReportFilterMixin:
"""Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which provides a generic implementation to return a list of ma... | the_stack_v2_python_sparse | InvenTree/report/api.py | inventree/InvenTree | train | 3,077 |
273e47b6b21f6bb431b5e18a3d1cf31a782263b3 | [
"super(LeNetRegressorMLP, self).__init__()\nself.fc2 = nn.Linear(input_dims, 1)\nself.restored = False",
"out = F.dropout(F.relu(feat), training=self.training)\nout = F.sigmoid(self.fc2(out))\nreturn out"
] | <|body_start_0|>
super(LeNetRegressorMLP, self).__init__()
self.fc2 = nn.Linear(input_dims, 1)
self.restored = False
<|end_body_0|>
<|body_start_1|>
out = F.dropout(F.relu(feat), training=self.training)
out = F.sigmoid(self.fc2(out))
return out
<|end_body_1|>
| LeNet classifier model for ADDA. | LeNetRegressorMLP | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LeNetRegressorMLP:
"""LeNet classifier model for ADDA."""
def __init__(self, input_dims):
"""Init LeNet encoder."""
<|body_0|>
def forward(self, feat):
"""Forward the LeNet classifier."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(LeNetR... | stack_v2_sparse_classes_10k_train_002755 | 1,889 | no_license | [
{
"docstring": "Init LeNet encoder.",
"name": "__init__",
"signature": "def __init__(self, input_dims)"
},
{
"docstring": "Forward the LeNet classifier.",
"name": "forward",
"signature": "def forward(self, feat)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000159 | Implement the Python class `LeNetRegressorMLP` described below.
Class description:
LeNet classifier model for ADDA.
Method signatures and docstrings:
- def __init__(self, input_dims): Init LeNet encoder.
- def forward(self, feat): Forward the LeNet classifier. | Implement the Python class `LeNetRegressorMLP` described below.
Class description:
LeNet classifier model for ADDA.
Method signatures and docstrings:
- def __init__(self, input_dims): Init LeNet encoder.
- def forward(self, feat): Forward the LeNet classifier.
<|skeleton|>
class LeNetRegressorMLP:
"""LeNet class... | 44557a9b79d4ae9ac3c90f726c1e7cb82346f95d | <|skeleton|>
class LeNetRegressorMLP:
"""LeNet classifier model for ADDA."""
def __init__(self, input_dims):
"""Init LeNet encoder."""
<|body_0|>
def forward(self, feat):
"""Forward the LeNet classifier."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LeNetRegressorMLP:
"""LeNet classifier model for ADDA."""
def __init__(self, input_dims):
"""Init LeNet encoder."""
super(LeNetRegressorMLP, self).__init__()
self.fc2 = nn.Linear(input_dims, 1)
self.restored = False
def forward(self, feat):
"""Forward the LeNe... | the_stack_v2_python_sparse | models/adda_models/MPL.py | abr-98/FADACS_Parking_Prediction | train | 0 |
ba742a4109302b4a02b092c8a0a3da2d63fa7074 | [
"self.d = {}\nself.cap = capacity\nself.head = Node(-1, -1, None)\nList.initHead(self.head)",
"if key not in self.d:\n return -1\nself.d[key].hit()\nreturn self.d[key].value",
"if self.cap == 0:\n return\nif key in self.d:\n self.d[key].hit()\n self.d[key].value = value\nelse:\n if len(self.d) >=... | <|body_start_0|>
self.d = {}
self.cap = capacity
self.head = Node(-1, -1, None)
List.initHead(self.head)
<|end_body_0|>
<|body_start_1|>
if key not in self.d:
return -1
self.d[key].hit()
return self.d[key].value
<|end_body_1|>
<|body_start_2|>
... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_10k_train_002756 | 1,549 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: nothing",
"name": "set",
"sig... | 3 | stack_v2_sparse_classes_30k_train_001022 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing
<|skeleton|>
cla... | 929dde1723fb2f54870c8a9badc80fc23e8400d3 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.d = {}
self.cap = capacity
self.head = Node(-1, -1, None)
List.initHead(self.head)
def get(self, key):
""":rtype: int"""
if key not in self.d:
return -1
self.... | the_stack_v2_python_sparse | _algorithms_challenges/leetcode/lc-all-solutions/146.lru-cache/lru-cache.py | syurskyi/Algorithms_and_Data_Structure | train | 4 | |
4f4874928b6577a830d552dc4adebfaab0ca441c | [
"QtWidgets.QWidget.__init__(self, *args, **kargs)\nif constraints_dict == None:\n constraints_dict = {}\nself.constants_manager = constants_manager\nself.constraints_dict = self.constants_manager.constrains\nself.widget_dict = {}\nlayout = QtWidgets.QFormLayout()\nfor k in list(self.constants_manager.keys()):\n ... | <|body_start_0|>
QtWidgets.QWidget.__init__(self, *args, **kargs)
if constraints_dict == None:
constraints_dict = {}
self.constants_manager = constants_manager
self.constraints_dict = self.constants_manager.constrains
self.widget_dict = {}
layout = QtWidgets.Q... | CMWidget | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CMWidget:
def __init__(self, constants_manager, constraints_dict=None, key_list=None, *args, **kargs):
"""This class will manage the constants with a gui interface. Each value is caracterized by its name (called key), its type, its initial value and its description. These information are... | stack_v2_sparse_classes_10k_train_002757 | 5,116 | no_license | [
{
"docstring": "This class will manage the constants with a gui interface. Each value is caracterized by its name (called key), its type, its initial value and its description. These information are given in values_dict. - constants_manager : the constant manager instance to represent",
"name": "__init__",
... | 4 | stack_v2_sparse_classes_30k_val_000347 | Implement the Python class `CMWidget` described below.
Class description:
Implement the CMWidget class.
Method signatures and docstrings:
- def __init__(self, constants_manager, constraints_dict=None, key_list=None, *args, **kargs): This class will manage the constants with a gui interface. Each value is caracterized... | Implement the Python class `CMWidget` described below.
Class description:
Implement the CMWidget class.
Method signatures and docstrings:
- def __init__(self, constants_manager, constraints_dict=None, key_list=None, *args, **kargs): This class will manage the constants with a gui interface. Each value is caracterized... | 14c9e51fa31fd3ff4113f33e26619d07c9f1dc7c | <|skeleton|>
class CMWidget:
def __init__(self, constants_manager, constraints_dict=None, key_list=None, *args, **kargs):
"""This class will manage the constants with a gui interface. Each value is caracterized by its name (called key), its type, its initial value and its description. These information are... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CMWidget:
def __init__(self, constants_manager, constraints_dict=None, key_list=None, *args, **kargs):
"""This class will manage the constants with a gui interface. Each value is caracterized by its name (called key), its type, its initial value and its description. These information are given in valu... | the_stack_v2_python_sparse | ConstantsManager/ConstantsManagerWidget.py | grumpfou/AthenaWriter | train | 0 | |
7dccaef5ad5037d3ae6870574e63861d9cf8f585 | [
"self.curl_buffer = CurlBuffer()\nself.curl = pycurl.Curl()\nself.curl.setopt(self.curl.VERBOSE, 0)\nself.curl.setopt(self.curl.WRITEFUNCTION, self.curl_buffer.body_callback)\nself.curl.setopt(self.curl.URL, self.url)\nself.curl.perform()",
"query_string = '?sensor=false&address=%s' % urlquote(address)\nself.url ... | <|body_start_0|>
self.curl_buffer = CurlBuffer()
self.curl = pycurl.Curl()
self.curl.setopt(self.curl.VERBOSE, 0)
self.curl.setopt(self.curl.WRITEFUNCTION, self.curl_buffer.body_callback)
self.curl.setopt(self.curl.URL, self.url)
self.curl.perform()
<|end_body_0|>
<|body... | Retrieve latitude/longitude coordinate for an address. Production uses Google's geocoding service. Test mode uses Open Street Maps' geocoding service. Option (for performance boost) to allow Jenkins to return static location. | GeocodeLocation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeocodeLocation:
"""Retrieve latitude/longitude coordinate for an address. Production uses Google's geocoding service. Test mode uses Open Street Maps' geocoding service. Option (for performance boost) to allow Jenkins to return static location."""
def _execute_curl(self):
"""Use cur... | stack_v2_sparse_classes_10k_train_002758 | 4,650 | no_license | [
{
"docstring": "Use curl to submit request to geocoder service.",
"name": "_execute_curl",
"signature": "def _execute_curl(self)"
},
{
"docstring": "Use google API to retrieve lat/long coords for this address.",
"name": "_google_service",
"signature": "def _google_service(self, address)"... | 5 | stack_v2_sparse_classes_30k_train_000453 | Implement the Python class `GeocodeLocation` described below.
Class description:
Retrieve latitude/longitude coordinate for an address. Production uses Google's geocoding service. Test mode uses Open Street Maps' geocoding service. Option (for performance boost) to allow Jenkins to return static location.
Method sign... | Implement the Python class `GeocodeLocation` described below.
Class description:
Retrieve latitude/longitude coordinate for an address. Production uses Google's geocoding service. Test mode uses Open Street Maps' geocoding service. Option (for performance boost) to allow Jenkins to return static location.
Method sign... | a780ccdc3350d4b5c7990c65d1af8d71060c62cc | <|skeleton|>
class GeocodeLocation:
"""Retrieve latitude/longitude coordinate for an address. Production uses Google's geocoding service. Test mode uses Open Street Maps' geocoding service. Option (for performance boost) to allow Jenkins to return static location."""
def _execute_curl(self):
"""Use cur... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GeocodeLocation:
"""Retrieve latitude/longitude coordinate for an address. Production uses Google's geocoding service. Test mode uses Open Street Maps' geocoding service. Option (for performance boost) to allow Jenkins to return static location."""
def _execute_curl(self):
"""Use curl to submit r... | the_stack_v2_python_sparse | geolocation/geocode_address.py | wcirillo/ten | train | 0 |
6f8f3fafedd4d67f38afac40fd5f50399532339a | [
"if overlays is None:\n raise ValueError('Must specify overlays.')\nself._toolchains = []\nself._require_explicit_default_toolchain = True\nself._require_explicit_default_toolchain = False\nfor overlay_path in overlays:\n self._AddToolchainsFromOverlayDir(overlay_path)",
"config_path = os.path.join(overlay_... | <|body_start_0|>
if overlays is None:
raise ValueError('Must specify overlays.')
self._toolchains = []
self._require_explicit_default_toolchain = True
self._require_explicit_default_toolchain = False
for overlay_path in overlays:
self._AddToolchainsFromOve... | Represents a list of toolchains. | ToolchainList | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ToolchainList:
"""Represents a list of toolchains."""
def __init__(self, overlays):
"""Construct an instance. Args: overlays: list of overlay directories to add toolchains from."""
<|body_0|>
def _AddToolchainsFromOverlayDir(self, overlay_dir):
"""Add toolchains ... | stack_v2_sparse_classes_10k_train_002759 | 4,300 | permissive | [
{
"docstring": "Construct an instance. Args: overlays: list of overlay directories to add toolchains from.",
"name": "__init__",
"signature": "def __init__(self, overlays)"
},
{
"docstring": "Add toolchains to |self| from the given overlay. Does not include overlays that this overlay depends on.... | 4 | null | Implement the Python class `ToolchainList` described below.
Class description:
Represents a list of toolchains.
Method signatures and docstrings:
- def __init__(self, overlays): Construct an instance. Args: overlays: list of overlay directories to add toolchains from.
- def _AddToolchainsFromOverlayDir(self, overlay_... | Implement the Python class `ToolchainList` described below.
Class description:
Represents a list of toolchains.
Method signatures and docstrings:
- def __init__(self, overlays): Construct an instance. Args: overlays: list of overlay directories to add toolchains from.
- def _AddToolchainsFromOverlayDir(self, overlay_... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class ToolchainList:
"""Represents a list of toolchains."""
def __init__(self, overlays):
"""Construct an instance. Args: overlays: list of overlay directories to add toolchains from."""
<|body_0|>
def _AddToolchainsFromOverlayDir(self, overlay_dir):
"""Add toolchains ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ToolchainList:
"""Represents a list of toolchains."""
def __init__(self, overlays):
"""Construct an instance. Args: overlays: list of overlay directories to add toolchains from."""
if overlays is None:
raise ValueError('Must specify overlays.')
self._toolchains = []
... | the_stack_v2_python_sparse | third_party/chromite/lib/toolchain_list.py | metux/chromium-suckless | train | 5 |
e63f6accc744295ac34222e1e8b5c59f05dc8d3d | [
"if not email:\n raise ValueError('Users must have an email address')\nuser = self.model(email=self.normalize_email(email))\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(email, password=password)\nuser.is_admin = True\nuser.save(using=self._db)\nreturn user"
] | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=self.normalize_email(email))
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = self.create_user(... | MyUserManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, password=None):
"""Creates and saves a superuser with the given email, date of bi... | stack_v2_sparse_classes_10k_train_002760 | 4,400 | permissive | [
{
"docstring": "Creates and saves a User with the given email, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, email, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email, date of birth and password.",
"name": "create_... | 2 | stack_v2_sparse_classes_30k_train_002358 | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, email, password=Non... | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, email, password=Non... | 0b61f67ce3158cf727d3570daf60bff1b0417360 | <|skeleton|>
class MyUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, password=None):
"""Creates and saves a superuser with the given email, date of bi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MyUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=self.normalize_email(email))
user.... | the_stack_v2_python_sparse | Business_Coaching_Platform/user/models.py | SDOS2020/Team_1_Business_Coaching_Platform | train | 0 | |
ee34a45dfaf26346c0d07dad02df79e8308c93fc | [
"n = n_sersic\nx_red = self._x_reduced(x, y, n, R_sersic, center_x, center_y)\nb = self.b_n(n)\nhyper2f2_bx = util.hyper2F2_array(2 * n, 2 * n, 1 + 2 * n, 1 + 2 * n, -b * x_red)\nf_eff = np.exp(b) * R_sersic ** 2 / 2.0 * k_eff\nf_ = f_eff * x_red ** (2 * n) * hyper2f2_bx\nreturn f_",
"x_ = x - center_x\ny_ = y - ... | <|body_start_0|>
n = n_sersic
x_red = self._x_reduced(x, y, n, R_sersic, center_x, center_y)
b = self.b_n(n)
hyper2f2_bx = util.hyper2F2_array(2 * n, 2 * n, 1 + 2 * n, 1 + 2 * n, -b * x_red)
f_eff = np.exp(b) * R_sersic ** 2 / 2.0 * k_eff
f_ = f_eff * x_red ** (2 * n) * h... | this class contains functions to evaluate a Sersic mass profile: https://arxiv.org/pdf/astro-ph/0311559.pdf .. math:: \\kappa(R) = \\kappa_{\\rm eff} \\exp \\left[ -b_n (R/R_{\\rm Sersic})^{\\frac{1}{n}}\\right] with :math:`b_{n}\\approx 1.999n-0.327` Examples -------- Example for converting physical mass units into co... | Sersic | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sersic:
"""this class contains functions to evaluate a Sersic mass profile: https://arxiv.org/pdf/astro-ph/0311559.pdf .. math:: \\kappa(R) = \\kappa_{\\rm eff} \\exp \\left[ -b_n (R/R_{\\rm Sersic})^{\\frac{1}{n}}\\right] with :math:`b_{n}\\approx 1.999n-0.327` Examples -------- Example for conv... | stack_v2_sparse_classes_10k_train_002761 | 4,388 | permissive | [
{
"docstring": ":param x: x-coordinate :param y: y-coordinate :param n_sersic: Sersic index :param R_sersic: half light radius :param k_eff: convergence at half light radius :param center_x: x-center :param center_y: y-center :return:",
"name": "function",
"signature": "def function(self, x, y, n_sersic... | 3 | stack_v2_sparse_classes_30k_train_004630 | Implement the Python class `Sersic` described below.
Class description:
this class contains functions to evaluate a Sersic mass profile: https://arxiv.org/pdf/astro-ph/0311559.pdf .. math:: \\kappa(R) = \\kappa_{\\rm eff} \\exp \\left[ -b_n (R/R_{\\rm Sersic})^{\\frac{1}{n}}\\right] with :math:`b_{n}\\approx 1.999n-0.... | Implement the Python class `Sersic` described below.
Class description:
this class contains functions to evaluate a Sersic mass profile: https://arxiv.org/pdf/astro-ph/0311559.pdf .. math:: \\kappa(R) = \\kappa_{\\rm eff} \\exp \\left[ -b_n (R/R_{\\rm Sersic})^{\\frac{1}{n}}\\right] with :math:`b_{n}\\approx 1.999n-0.... | 73c9645f26f6983fe7961104075ebe8bf7a4b54c | <|skeleton|>
class Sersic:
"""this class contains functions to evaluate a Sersic mass profile: https://arxiv.org/pdf/astro-ph/0311559.pdf .. math:: \\kappa(R) = \\kappa_{\\rm eff} \\exp \\left[ -b_n (R/R_{\\rm Sersic})^{\\frac{1}{n}}\\right] with :math:`b_{n}\\approx 1.999n-0.327` Examples -------- Example for conv... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Sersic:
"""this class contains functions to evaluate a Sersic mass profile: https://arxiv.org/pdf/astro-ph/0311559.pdf .. math:: \\kappa(R) = \\kappa_{\\rm eff} \\exp \\left[ -b_n (R/R_{\\rm Sersic})^{\\frac{1}{n}}\\right] with :math:`b_{n}\\approx 1.999n-0.327` Examples -------- Example for converting physic... | the_stack_v2_python_sparse | lenstronomy/LensModel/Profiles/sersic.py | lenstronomy/lenstronomy | train | 41 |
3e56e0bc6a88cfed99a3b9a024311f14daa90b10 | [
"super(Group_RDB, self).__init__()\nself.InChan = InChannel\nself.OutChan = OutChannel\nself.G = growRate\nself.C = nConvLayers\nif self.InChan != self.G:\n self.InConv = nn.Conv2d(self.InChan, self.G, 1, padding=0, stride=1)\nif self.OutChan != self.G and self.OutChan != self.InChan:\n self.OutConv = nn.Conv... | <|body_start_0|>
super(Group_RDB, self).__init__()
self.InChan = InChannel
self.OutChan = OutChannel
self.G = growRate
self.C = nConvLayers
if self.InChan != self.G:
self.InConv = nn.Conv2d(self.InChan, self.G, 1, padding=0, stride=1)
if self.OutChan !... | Group residual dense block. | Group_RDB | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Group_RDB:
"""Group residual dense block."""
def __init__(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3):
"""Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel: int :param growRat... | stack_v2_sparse_classes_10k_train_002762 | 13,650 | permissive | [
{
"docstring": "Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel: int :param growRate: growth rate of block :type growRate: int :param nConvLayers: the number of convlution layer :type nConvLayers: int :param kSize: ker... | 2 | null | Implement the Python class `Group_RDB` described below.
Class description:
Group residual dense block.
Method signatures and docstrings:
- def __init__(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3): Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: chan... | Implement the Python class `Group_RDB` described below.
Class description:
Group residual dense block.
Method signatures and docstrings:
- def __init__(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3): Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: chan... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class Group_RDB:
"""Group residual dense block."""
def __init__(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3):
"""Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel: int :param growRat... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Group_RDB:
"""Group residual dense block."""
def __init__(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3):
"""Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel: int :param growRate: growth rat... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/search_space/networks/pytorch/esrbodys/erdb_esr.py | Huawei-Ascend/modelzoo | train | 1 |
38f3a4f431116540174ad959300bfcbb07efd330 | [
"self._source = source\nself._time_provider = time_provider\nself._storage_engine = storage_engine",
"if slack_task.archived:\n return\nasync with self._storage_engine.get_unit_of_work() as uow:\n slack_task_collection = await uow.slack_task_collection_repository.load_by_id(slack_task.slack_task_collection_... | <|body_start_0|>
self._source = source
self._time_provider = time_provider
self._storage_engine = storage_engine
<|end_body_0|>
<|body_start_1|>
if slack_task.archived:
return
async with self._storage_engine.get_unit_of_work() as uow:
slack_task_collectio... | Shared service for archiving a slack task. | SlackTaskArchiveService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SlackTaskArchiveService:
"""Shared service for archiving a slack task."""
def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None:
"""Constructor."""
<|body_0|>
async def do_it(self, progress_reporter: ProgressRep... | stack_v2_sparse_classes_10k_train_002763 | 2,869 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None"
},
{
"docstring": "Execute the service's action.",
"name": "do_it",
"signature": "async def do_it(self, prog... | 2 | stack_v2_sparse_classes_30k_train_003169 | Implement the Python class `SlackTaskArchiveService` described below.
Class description:
Shared service for archiving a slack task.
Method signatures and docstrings:
- def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None: Constructor.
- async def do_it(self... | Implement the Python class `SlackTaskArchiveService` described below.
Class description:
Shared service for archiving a slack task.
Method signatures and docstrings:
- def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None: Constructor.
- async def do_it(self... | 911ecd560142a9b4e57498f2b090f9469a0718a1 | <|skeleton|>
class SlackTaskArchiveService:
"""Shared service for archiving a slack task."""
def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None:
"""Constructor."""
<|body_0|>
async def do_it(self, progress_reporter: ProgressRep... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SlackTaskArchiveService:
"""Shared service for archiving a slack task."""
def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None:
"""Constructor."""
self._source = source
self._time_provider = time_provider
self._s... | the_stack_v2_python_sparse | src/core/jupiter/core/domain/push_integrations/slack/service/archive_service.py | horia141/jupiter | train | 16 |
8901fcce99cdfd94525b3892d9f5d2948c0e33ca | [
"results_per_page = min(max(results_per_page, 1), 50)\nquery = models.Event.query\nif since_id:\n after = first_or_abort(models.Event.query.filter(models.Event.id == since_id), 409)\n query = query.filter(models.Event.cursor > after.cursor)\nelif max_id:\n before = first_or_abort(models.Event.query.filter(... | <|body_start_0|>
results_per_page = min(max(results_per_page, 1), 50)
query = models.Event.query
if since_id:
after = first_or_abort(models.Event.query.filter(models.Event.id == since_id), 409)
query = query.filter(models.Event.cursor > after.cursor)
elif max_id:
... | Events | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Events:
def get(self, results_per_page=50, event_type_slug=None, since_id=None, max_id=None):
"""--- description: Retrieve a collection of event types. parameters: - api_version - results_per_page - in: query name: event_type_slug type: string description: slug of event_type this event c... | stack_v2_sparse_classes_10k_train_002764 | 15,999 | no_license | [
{
"docstring": "--- description: Retrieve a collection of event types. parameters: - api_version - results_per_page - in: query name: event_type_slug type: string description: slug of event_type this event conforms to. - in: query name: since_id type: string format: uuid description: get all events since this e... | 2 | stack_v2_sparse_classes_30k_train_004251 | Implement the Python class `Events` described below.
Class description:
Implement the Events class.
Method signatures and docstrings:
- def get(self, results_per_page=50, event_type_slug=None, since_id=None, max_id=None): --- description: Retrieve a collection of event types. parameters: - api_version - results_per_p... | Implement the Python class `Events` described below.
Class description:
Implement the Events class.
Method signatures and docstrings:
- def get(self, results_per_page=50, event_type_slug=None, since_id=None, max_id=None): --- description: Retrieve a collection of event types. parameters: - api_version - results_per_p... | dbba9f3b292ffef6ea924608fa54237171f0aaeb | <|skeleton|>
class Events:
def get(self, results_per_page=50, event_type_slug=None, since_id=None, max_id=None):
"""--- description: Retrieve a collection of event types. parameters: - api_version - results_per_page - in: query name: event_type_slug type: string description: slug of event_type this event c... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Events:
def get(self, results_per_page=50, event_type_slug=None, since_id=None, max_id=None):
"""--- description: Retrieve a collection of event types. parameters: - api_version - results_per_page - in: query name: event_type_slug type: string description: slug of event_type this event conforms to. - ... | the_stack_v2_python_sparse | apis/event/directorofme_event/resources.py | DirectorOfMe/directorof.me | train | 0 | |
4cf4eee6ef3bc0ec8202263745620a13f0b25227 | [
"input_len = len(input_ids)\nif not (input_len == len(input_mask) and input_len == len(segment_ids) and (input_len == len(labels_mask)) and (input_len == len(tag_labels)) and (input_len == len(semiotic_labels))):\n raise ValueError('All feature lists should have the same length ({})'.format(input_len))\nself.fea... | <|body_start_0|>
input_len = len(input_ids)
if not (input_len == len(input_mask) and input_len == len(segment_ids) and (input_len == len(labels_mask)) and (input_len == len(tag_labels)) and (input_len == len(semiotic_labels))):
raise ValueError('All feature lists should have the same length ... | Class for training and inference examples for BERT. Attributes: editing_task: The EditingTask from which this example was created. Needed when realizing labels predicted for this example. features: Feature dictionary. | BertExample | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BertExample:
"""Class for training and inference examples for BERT. Attributes: editing_task: The EditingTask from which this example was created. Needed when realizing labels predicted for this example. features: Feature dictionary."""
def __init__(self, input_ids: List[int], input_mask: Li... | stack_v2_sparse_classes_10k_train_002765 | 15,095 | permissive | [
{
"docstring": "Inputs to the example wrapper Args: input_ids: indices of tokens which constitute batches of masked text segments input_mask: bool tensor with 0s in place of source tokens to be masked segment_ids: bool tensor with 0's and 1's to denote the text segment type tag_labels: indices of tokens which s... | 3 | null | Implement the Python class `BertExample` described below.
Class description:
Class for training and inference examples for BERT. Attributes: editing_task: The EditingTask from which this example was created. Needed when realizing labels predicted for this example. features: Feature dictionary.
Method signatures and d... | Implement the Python class `BertExample` described below.
Class description:
Class for training and inference examples for BERT. Attributes: editing_task: The EditingTask from which this example was created. Needed when realizing labels predicted for this example. features: Feature dictionary.
Method signatures and d... | c20a16ea8aa2a9d8e31a98eb22178ddb9d5935e7 | <|skeleton|>
class BertExample:
"""Class for training and inference examples for BERT. Attributes: editing_task: The EditingTask from which this example was created. Needed when realizing labels predicted for this example. features: Feature dictionary."""
def __init__(self, input_ids: List[int], input_mask: Li... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BertExample:
"""Class for training and inference examples for BERT. Attributes: editing_task: The EditingTask from which this example was created. Needed when realizing labels predicted for this example. features: Feature dictionary."""
def __init__(self, input_ids: List[int], input_mask: List[int], segm... | the_stack_v2_python_sparse | nemo/collections/nlp/data/text_normalization_as_tagging/bert_example.py | NVIDIA/NeMo | train | 7,957 |
019a1bc2ec210a47c12e13b9deaba9791ba4caa3 | [
"self.input_dist = [5, 25, 15, 10, 15]\nself.input_fuel = [1, 2, 1, 0, 3]\nself.mpg = 10\nself.output = 4\nreturn (self.input_dist, self.input_fuel, self.mpg, self.output)",
"input_dist, input_fuel, mpg, proper_output = self.setUp()\noutput = ValidStartingCity.validStartingCity(input_dist, input_fuel, mpg)\nself.... | <|body_start_0|>
self.input_dist = [5, 25, 15, 10, 15]
self.input_fuel = [1, 2, 1, 0, 3]
self.mpg = 10
self.output = 4
return (self.input_dist, self.input_fuel, self.mpg, self.output)
<|end_body_0|>
<|body_start_1|>
input_dist, input_fuel, mpg, proper_output = self.setUp... | Class with unittests for ValidStartingCity.py | test_ValidStartingCity | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test_ValidStartingCity:
"""Class with unittests for ValidStartingCity.py"""
def setUp(self):
"""SetUp values for tests."""
<|body_0|>
def test_ExpectedOutput(self):
"""Checks if returned output is as expected."""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_10k_train_002766 | 1,003 | no_license | [
{
"docstring": "SetUp values for tests.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Checks if returned output is as expected.",
"name": "test_ExpectedOutput",
"signature": "def test_ExpectedOutput(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004790 | Implement the Python class `test_ValidStartingCity` described below.
Class description:
Class with unittests for ValidStartingCity.py
Method signatures and docstrings:
- def setUp(self): SetUp values for tests.
- def test_ExpectedOutput(self): Checks if returned output is as expected. | Implement the Python class `test_ValidStartingCity` described below.
Class description:
Class with unittests for ValidStartingCity.py
Method signatures and docstrings:
- def setUp(self): SetUp values for tests.
- def test_ExpectedOutput(self): Checks if returned output is as expected.
<|skeleton|>
class test_ValidSt... | 3aa62ad36c3b06b2a3b05f1f8e2a9e21d68b371f | <|skeleton|>
class test_ValidStartingCity:
"""Class with unittests for ValidStartingCity.py"""
def setUp(self):
"""SetUp values for tests."""
<|body_0|>
def test_ExpectedOutput(self):
"""Checks if returned output is as expected."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class test_ValidStartingCity:
"""Class with unittests for ValidStartingCity.py"""
def setUp(self):
"""SetUp values for tests."""
self.input_dist = [5, 25, 15, 10, 15]
self.input_fuel = [1, 2, 1, 0, 3]
self.mpg = 10
self.output = 4
return (self.input_dist, self.in... | the_stack_v2_python_sparse | AlgoExpert_algorithms/Medium/ValidStartingCity/test_ValidStartingCity.py | JakubKazimierski/PythonPortfolio | train | 9 |
6dbefce93d59ca47e7188e8ce3229f0797609d94 | [
"arcpy.AddMessage(u'\\t1. Verificando disponibilidad de licencia SPATIAL ANALYST')\nlicense = arcpy.CheckExtension('spatial')\nif license != 'Available':\n raise RuntimeError('\\tError: %s' % license)\narcpy.AddMessage(u'\\t2. Enviando informacion a la GEODATABASE')\narcpy.CheckOutExtension('spatial')\ngeoquimic... | <|body_start_0|>
arcpy.AddMessage(u'\t1. Verificando disponibilidad de licencia SPATIAL ANALYST')
license = arcpy.CheckExtension('spatial')
if license != 'Available':
raise RuntimeError('\tError: %s' % license)
arcpy.AddMessage(u'\t2. Enviando informacion a la GEODATABASE')
... | Clase que contiene el procesamiento para el tratamiento de la variable geoquimica | Geoquimica | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Geoquimica:
"""Clase que contiene el procesamiento para el tratamiento de la variable geoquimica"""
def process(self):
"""Enviando el raster ingresado al File Geodatabase :return:"""
<|body_0|>
def main(self):
"""Funcion principal del proceso :return:"""
... | stack_v2_sparse_classes_10k_train_002767 | 1,567 | no_license | [
{
"docstring": "Enviando el raster ingresado al File Geodatabase :return:",
"name": "process",
"signature": "def process(self)"
},
{
"docstring": "Funcion principal del proceso :return:",
"name": "main",
"signature": "def main(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000557 | Implement the Python class `Geoquimica` described below.
Class description:
Clase que contiene el procesamiento para el tratamiento de la variable geoquimica
Method signatures and docstrings:
- def process(self): Enviando el raster ingresado al File Geodatabase :return:
- def main(self): Funcion principal del proceso... | Implement the Python class `Geoquimica` described below.
Class description:
Clase que contiene el procesamiento para el tratamiento de la variable geoquimica
Method signatures and docstrings:
- def process(self): Enviando el raster ingresado al File Geodatabase :return:
- def main(self): Funcion principal del proceso... | 89bcea828bc8720fc1dcf82439b06b1f272bb096 | <|skeleton|>
class Geoquimica:
"""Clase que contiene el procesamiento para el tratamiento de la variable geoquimica"""
def process(self):
"""Enviando el raster ingresado al File Geodatabase :return:"""
<|body_0|>
def main(self):
"""Funcion principal del proceso :return:"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Geoquimica:
"""Clase que contiene el procesamiento para el tratamiento de la variable geoquimica"""
def process(self):
"""Enviando el raster ingresado al File Geodatabase :return:"""
arcpy.AddMessage(u'\t1. Verificando disponibilidad de licencia SPATIAL ANALYST')
license = arcpy.C... | the_stack_v2_python_sparse | Install/dev/scripts/pmmGeoquimica.py | ryali93/addinPotencialMinero | train | 0 |
1dc25f3e8bd1e2a153e5e3147c1941088acffc95 | [
"info = OrderedDict({})\ntry:\n info_editors = OrderedDict({})\n for instance in obj.editors.all():\n info_editors[instance.pk] = instance.pen_name\n info['editors'] = info_editors\nexcept Editor.DoesNotExist as e:\n info['editors'] = str(e)\ntry:\n info['domain'] = domain.DOMAIN_DICT[obj.doma... | <|body_start_0|>
info = OrderedDict({})
try:
info_editors = OrderedDict({})
for instance in obj.editors.all():
info_editors[instance.pk] = instance.pen_name
info['editors'] = info_editors
except Editor.DoesNotExist as e:
info['edito... | Problem Base Serializer | ProblemBaseSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProblemBaseSerializer:
"""Problem Base Serializer"""
def get_info_data(self, obj, *args, **kwargs):
"""Get Information Data :param obj: :param args: :param kwargs: :return:"""
<|body_0|>
def get_links_url(self, obj, *args, **kwargs):
"""Get links url :param obj: ... | stack_v2_sparse_classes_10k_train_002768 | 6,316 | no_license | [
{
"docstring": "Get Information Data :param obj: :param args: :param kwargs: :return:",
"name": "get_info_data",
"signature": "def get_info_data(self, obj, *args, **kwargs)"
},
{
"docstring": "Get links url :param obj: :param args: :param kwargs: :return:",
"name": "get_links_url",
"sign... | 2 | stack_v2_sparse_classes_30k_train_002625 | Implement the Python class `ProblemBaseSerializer` described below.
Class description:
Problem Base Serializer
Method signatures and docstrings:
- def get_info_data(self, obj, *args, **kwargs): Get Information Data :param obj: :param args: :param kwargs: :return:
- def get_links_url(self, obj, *args, **kwargs): Get l... | Implement the Python class `ProblemBaseSerializer` described below.
Class description:
Problem Base Serializer
Method signatures and docstrings:
- def get_info_data(self, obj, *args, **kwargs): Get Information Data :param obj: :param args: :param kwargs: :return:
- def get_links_url(self, obj, *args, **kwargs): Get l... | acd31a2f43d7ea83fc9bb34627f5dca94763eade | <|skeleton|>
class ProblemBaseSerializer:
"""Problem Base Serializer"""
def get_info_data(self, obj, *args, **kwargs):
"""Get Information Data :param obj: :param args: :param kwargs: :return:"""
<|body_0|>
def get_links_url(self, obj, *args, **kwargs):
"""Get links url :param obj: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProblemBaseSerializer:
"""Problem Base Serializer"""
def get_info_data(self, obj, *args, **kwargs):
"""Get Information Data :param obj: :param args: :param kwargs: :return:"""
info = OrderedDict({})
try:
info_editors = OrderedDict({})
for instance in obj.ed... | the_stack_v2_python_sparse | problem/serializers.py | JoenyBui/mywaterbuffalo | train | 0 |
0f9c22d0619771241895bda5077b516105d52d89 | [
"self.x = x\nself.M = np.shape(x)[0]\nself.N = np.shape(x)[1]",
"X = np.zeros([self.M, self.N], dtype=np.complex)\nfor m in range(self.M):\n for n in range(self.N):\n for i in range(self.M):\n for j in range(self.N):\n X[m, n] = X[m, n] + self.x[i, j] / np.sqrt(self.M * self.N)... | <|body_start_0|>
self.x = x
self.M = np.shape(x)[0]
self.N = np.shape(x)[1]
<|end_body_0|>
<|body_start_1|>
X = np.zeros([self.M, self.N], dtype=np.complex)
for m in range(self.M):
for n in range(self.N):
for i in range(self.M):
fo... | 2-D DFT | DFT_2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DFT_2D:
"""2-D DFT"""
def __init__(self, x):
"""input time-domain signal x"""
<|body_0|>
def solve(self):
"""\\\\\\ METHOD: Compute DFT of x"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.x = x
self.M = np.shape(x)[0]
self.... | stack_v2_sparse_classes_10k_train_002769 | 4,947 | no_license | [
{
"docstring": "input time-domain signal x",
"name": "__init__",
"signature": "def __init__(self, x)"
},
{
"docstring": "\\\\\\\\\\\\ METHOD: Compute DFT of x",
"name": "solve",
"signature": "def solve(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006030 | Implement the Python class `DFT_2D` described below.
Class description:
2-D DFT
Method signatures and docstrings:
- def __init__(self, x): input time-domain signal x
- def solve(self): \\\\\\ METHOD: Compute DFT of x | Implement the Python class `DFT_2D` described below.
Class description:
2-D DFT
Method signatures and docstrings:
- def __init__(self, x): input time-domain signal x
- def solve(self): \\\\\\ METHOD: Compute DFT of x
<|skeleton|>
class DFT_2D:
"""2-D DFT"""
def __init__(self, x):
"""input time-domai... | b72322cfc6d81c996117cea2160ee312da62d3ed | <|skeleton|>
class DFT_2D:
"""2-D DFT"""
def __init__(self, x):
"""input time-domain signal x"""
<|body_0|>
def solve(self):
"""\\\\\\ METHOD: Compute DFT of x"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DFT_2D:
"""2-D DFT"""
def __init__(self, x):
"""input time-domain signal x"""
self.x = x
self.M = np.shape(x)[0]
self.N = np.shape(x)[1]
def solve(self):
"""\\\\\\ METHOD: Compute DFT of x"""
X = np.zeros([self.M, self.N], dtype=np.complex)
for... | the_stack_v2_python_sparse | 2D Signal Processing and Image De-noising/discrete_signal.py | FG-14/Signals-and-Information-Processing-DSP- | train | 0 |
3f83768c5a7eedde914eed225b6aca5165f1d72b | [
"slide = openslide.OpenSlide(wsi_name)\ndimensions = slide.dimensions\nlevels = slide.level_count\nlevel = levels - 1\ndownsample = slide.level_downsamples[level]\nprint(level, downsample)\nthumbnail_rgb = cv2.cvtColor(np.asarray(slide.read_region((0, 0), level, slide.level_dimensions[level]).convert('RGB')), cv2.C... | <|body_start_0|>
slide = openslide.OpenSlide(wsi_name)
dimensions = slide.dimensions
levels = slide.level_count
level = levels - 1
downsample = slide.level_downsamples[level]
print(level, downsample)
thumbnail_rgb = cv2.cvtColor(np.asarray(slide.read_region((0, 0)... | WSIROI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WSIROI:
def __init__(self, wsi_name):
"""get a circle roi of wsi file, it should encampus almost all the cells area :param wsi_name: wsi full file name :return dimensions: slide width,height in level 0 :return center: center x,y of roi circle :return radius: radius of roi circle"""
... | stack_v2_sparse_classes_10k_train_002770 | 5,710 | no_license | [
{
"docstring": "get a circle roi of wsi file, it should encampus almost all the cells area :param wsi_name: wsi full file name :return dimensions: slide width,height in level 0 :return center: center x,y of roi circle :return radius: radius of roi circle",
"name": "__init__",
"signature": "def __init__(... | 2 | stack_v2_sparse_classes_30k_train_006138 | Implement the Python class `WSIROI` described below.
Class description:
Implement the WSIROI class.
Method signatures and docstrings:
- def __init__(self, wsi_name): get a circle roi of wsi file, it should encampus almost all the cells area :param wsi_name: wsi full file name :return dimensions: slide width,height in... | Implement the Python class `WSIROI` described below.
Class description:
Implement the WSIROI class.
Method signatures and docstrings:
- def __init__(self, wsi_name): get a circle roi of wsi file, it should encampus almost all the cells area :param wsi_name: wsi full file name :return dimensions: slide width,height in... | d77cec4438364deab94c37b45bdfde3e0b03b879 | <|skeleton|>
class WSIROI:
def __init__(self, wsi_name):
"""get a circle roi of wsi file, it should encampus almost all the cells area :param wsi_name: wsi full file name :return dimensions: slide width,height in level 0 :return center: center x,y of roi circle :return radius: radius of roi circle"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WSIROI:
def __init__(self, wsi_name):
"""get a circle roi of wsi file, it should encampus almost all the cells area :param wsi_name: wsi full file name :return dimensions: slide width,height in level 0 :return center: center x,y of roi circle :return radius: radius of roi circle"""
slide = ope... | the_stack_v2_python_sparse | train_c1/roi_extract/WSI_ROI.py | liyu10000/tct | train | 15 | |
8ef19b4e017591febff6a92fa907b75b0377db43 | [
"l = len(nums)\nif l <= 1:\n return 0\na = str(max(nums))\nk = len(a)\n\ndef radixSort(A, k):\n for k in range(k):\n s = [[] for i in range(10)]\n for i in A:\n s[i // 10 ** k % 10].append(i)\n A = [a for b in s for a in b]\n print(A)\n return A\nnums = radixSort(nums, k)... | <|body_start_0|>
l = len(nums)
if l <= 1:
return 0
a = str(max(nums))
k = len(a)
def radixSort(A, k):
for k in range(k):
s = [[] for i in range(10)]
for i in A:
s[i // 10 ** k % 10].append(i)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maximumGap(self, nums):
""":type nums: List[int] :rtype: int 66ms"""
<|body_0|>
def maximumGap_1(self, nums):
""":type nums: List[int] :rtype: int 49ms"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
l = len(nums)
if l <= 1:
... | stack_v2_sparse_classes_10k_train_002771 | 1,855 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int 66ms",
"name": "maximumGap",
"signature": "def maximumGap(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int 49ms",
"name": "maximumGap_1",
"signature": "def maximumGap_1(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000346 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximumGap(self, nums): :type nums: List[int] :rtype: int 66ms
- def maximumGap_1(self, nums): :type nums: List[int] :rtype: int 49ms | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximumGap(self, nums): :type nums: List[int] :rtype: int 66ms
- def maximumGap_1(self, nums): :type nums: List[int] :rtype: int 49ms
<|skeleton|>
class Solution:
def m... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def maximumGap(self, nums):
""":type nums: List[int] :rtype: int 66ms"""
<|body_0|>
def maximumGap_1(self, nums):
""":type nums: List[int] :rtype: int 49ms"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maximumGap(self, nums):
""":type nums: List[int] :rtype: int 66ms"""
l = len(nums)
if l <= 1:
return 0
a = str(max(nums))
k = len(a)
def radixSort(A, k):
for k in range(k):
s = [[] for i in range(10)]
... | the_stack_v2_python_sparse | MaximumGap_HARD_164.py | 953250587/leetcode-python | train | 2 | |
fefe4314a7e38bd4b026125831965d044fe2c171 | [
"self.list = nums\nself.dic = {}\nself.k = len(nums)\nfor i, n in enumerate(self.list):\n self.dic[i] = n",
"for i in range(self.k):\n self.list[i] = self.dic[i]\nreturn self.list",
"index = list(range(self.k))\nrandom.shuffle(index)\nfor i, j in enumerate(index):\n self.list[i] = self.dic[j]\nreturn s... | <|body_start_0|>
self.list = nums
self.dic = {}
self.k = len(nums)
for i, n in enumerate(self.list):
self.dic[i] = n
<|end_body_0|>
<|body_start_1|>
for i in range(self.k):
self.list[i] = self.dic[i]
return self.list
<|end_body_1|>
<|body_start_2... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def reset(self):
"""Resets the array to its original configuration and return it. :rtype: List[int]"""
<|body_1|>
def shuffle(self):
"""Returns a random shuffling of the a... | stack_v2_sparse_classes_10k_train_002772 | 954 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": "Resets the array to its original configuration and return it. :rtype: List[int]",
"name": "reset",
"signature": "def reset(self)"
},
{
"docstring": "Returns a ra... | 3 | stack_v2_sparse_classes_30k_train_004659 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def reset(self): Resets the array to its original configuration and return it. :rtype: List[int]
- def shuffle(self): Returns a ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def reset(self): Resets the array to its original configuration and return it. :rtype: List[int]
- def shuffle(self): Returns a ... | 2f46f85e1e297b0a50fdb66956b1d05622a4063d | <|skeleton|>
class Solution:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def reset(self):
"""Resets the array to its original configuration and return it. :rtype: List[int]"""
<|body_1|>
def shuffle(self):
"""Returns a random shuffling of the a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, nums):
""":type nums: List[int]"""
self.list = nums
self.dic = {}
self.k = len(nums)
for i, n in enumerate(self.list):
self.dic[i] = n
def reset(self):
"""Resets the array to its original configuration and return it.... | the_stack_v2_python_sparse | dan/Problems/Medium/Array/384. Shuffle an Array/solution.py | xudaaaaan/Leetcode | train | 0 | |
0f375f0f5bc5ff81b28b2302bee2d5b5a5954aac | [
"def preOrder(node):\n if not node:\n return ['None']\n return [str(node.val)] + preOrder(node.left) + preOrder(node.right)\nreturn ' '.join(preOrder(root))",
"def preOrder(it):\n v = next(it)\n if v == 'None':\n return None\n node = TreeNode(int(v))\n node.left = preOrder(it)\n ... | <|body_start_0|>
def preOrder(node):
if not node:
return ['None']
return [str(node.val)] + preOrder(node.left) + preOrder(node.right)
return ' '.join(preOrder(root))
<|end_body_0|>
<|body_start_1|>
def preOrder(it):
v = next(it)
if... | Codec3 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec3:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_10k_train_002773 | 4,842 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_005730 | Implement the Python class `Codec3` described below.
Class description:
Implement the Codec3 class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtyp... | Implement the Python class `Codec3` described below.
Class description:
Implement the Codec3 class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtyp... | 63120dbaabd7c3c19633ebe952bcee4cf826b0e0 | <|skeleton|>
class Codec3:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec3:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def preOrder(node):
if not node:
return ['None']
return [str(node.val)] + preOrder(node.left) + preOrder(node.right)
return ' '.join(preO... | the_stack_v2_python_sparse | 297. Serialize and Deserialize Binary Tree _ tee.py | CaizhiXu/LeetCode-Python-Solutions | train | 0 | |
cdda8a14090380a17b41430e97cd910c05171aed | [
"self.kv = {keys[i]: values[i] for i in range(len(keys))}\nself.vk = defaultdict(list)\nfor i in range(len(keys)):\n vk[values[i]].append(keys[i])\nself.d = Trie()\nfor word in dictionary:\n self.d.insert(word)",
"res = []\nfor ch in word1:\n res.append(self.kv[ch])\nreturn ''.join(res)",
"res = []\nfo... | <|body_start_0|>
self.kv = {keys[i]: values[i] for i in range(len(keys))}
self.vk = defaultdict(list)
for i in range(len(keys)):
vk[values[i]].append(keys[i])
self.d = Trie()
for word in dictionary:
self.d.insert(word)
<|end_body_0|>
<|body_start_1|>
... | Encrypter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encrypter:
def __init__(self, keys, values, dictionary):
""":type keys: List[str] :type values: List[str] :type dictionary: List[str]"""
<|body_0|>
def encrypt(self, word1):
""":type word1: str :rtype: str"""
<|body_1|>
def decrypt(self, word2):
... | stack_v2_sparse_classes_10k_train_002774 | 2,665 | no_license | [
{
"docstring": ":type keys: List[str] :type values: List[str] :type dictionary: List[str]",
"name": "__init__",
"signature": "def __init__(self, keys, values, dictionary)"
},
{
"docstring": ":type word1: str :rtype: str",
"name": "encrypt",
"signature": "def encrypt(self, word1)"
},
... | 3 | null | Implement the Python class `Encrypter` described below.
Class description:
Implement the Encrypter class.
Method signatures and docstrings:
- def __init__(self, keys, values, dictionary): :type keys: List[str] :type values: List[str] :type dictionary: List[str]
- def encrypt(self, word1): :type word1: str :rtype: str... | Implement the Python class `Encrypter` described below.
Class description:
Implement the Encrypter class.
Method signatures and docstrings:
- def __init__(self, keys, values, dictionary): :type keys: List[str] :type values: List[str] :type dictionary: List[str]
- def encrypt(self, word1): :type word1: str :rtype: str... | ee59b82125f100970c842d5e1245287c484d6649 | <|skeleton|>
class Encrypter:
def __init__(self, keys, values, dictionary):
""":type keys: List[str] :type values: List[str] :type dictionary: List[str]"""
<|body_0|>
def encrypt(self, word1):
""":type word1: str :rtype: str"""
<|body_1|>
def decrypt(self, word2):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Encrypter:
def __init__(self, keys, values, dictionary):
""":type keys: List[str] :type values: List[str] :type dictionary: List[str]"""
self.kv = {keys[i]: values[i] for i in range(len(keys))}
self.vk = defaultdict(list)
for i in range(len(keys)):
vk[values[i]].app... | the_stack_v2_python_sparse | _CodeTopics/LeetCode_contest/weekly/weekly2022/287/unfinished--287_4.py | BIAOXYZ/variousCodes | train | 0 | |
d205a0585ccfdbb1075d2b33e40a4b0bbbd1cd71 | [
"super().__init__()\nself.decoder = nn.Sequential(nn.Conv2d(512, 512, kernel_size=1), nn.ReLU(inplace=True), nn.Dropout(0.8), nn.Conv2d(512, 512, kernel_size=1), nn.ReLU(inplace=True))\nself.layer = nn.ConvTranspose2d(1280, num_classes, kernel_size=2, stride=2, dilation=1)",
"pool_3, pool_4 = pools\nx = self.deco... | <|body_start_0|>
super().__init__()
self.decoder = nn.Sequential(nn.Conv2d(512, 512, kernel_size=1), nn.ReLU(inplace=True), nn.Dropout(0.8), nn.Conv2d(512, 512, kernel_size=1), nn.ReLU(inplace=True))
self.layer = nn.ConvTranspose2d(1280, num_classes, kernel_size=2, stride=2, dilation=1)
<|end_bo... | Column Decoder. | ColumnDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ColumnDecoder:
"""Column Decoder."""
def __init__(self, num_classes: int):
"""Initialize Column Decoder. Args: num_classes (int): Number of classes per point."""
<|body_0|>
def forward(self, x, pools):
"""Forward pass. Args: x (tensor): Batch of images to perform... | stack_v2_sparse_classes_10k_train_002775 | 5,468 | no_license | [
{
"docstring": "Initialize Column Decoder. Args: num_classes (int): Number of classes per point.",
"name": "__init__",
"signature": "def __init__(self, num_classes: int)"
},
{
"docstring": "Forward pass. Args: x (tensor): Batch of images to perform forward-pass. pools (Tuple[tensor, tensor]): Th... | 2 | null | Implement the Python class `ColumnDecoder` described below.
Class description:
Column Decoder.
Method signatures and docstrings:
- def __init__(self, num_classes: int): Initialize Column Decoder. Args: num_classes (int): Number of classes per point.
- def forward(self, x, pools): Forward pass. Args: x (tensor): Batch... | Implement the Python class `ColumnDecoder` described below.
Class description:
Column Decoder.
Method signatures and docstrings:
- def __init__(self, num_classes: int): Initialize Column Decoder. Args: num_classes (int): Number of classes per point.
- def forward(self, x, pools): Forward pass. Args: x (tensor): Batch... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class ColumnDecoder:
"""Column Decoder."""
def __init__(self, num_classes: int):
"""Initialize Column Decoder. Args: num_classes (int): Number of classes per point."""
<|body_0|>
def forward(self, x, pools):
"""Forward pass. Args: x (tensor): Batch of images to perform... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ColumnDecoder:
"""Column Decoder."""
def __init__(self, num_classes: int):
"""Initialize Column Decoder. Args: num_classes (int): Number of classes per point."""
super().__init__()
self.decoder = nn.Sequential(nn.Conv2d(512, 512, kernel_size=1), nn.ReLU(inplace=True), nn.Dropout(0... | the_stack_v2_python_sparse | generated/test_tomassosorio_OCR_tablenet.py | jansel/pytorch-jit-paritybench | train | 35 |
44159b0a3772fe353e137cb16998a13b41e49740 | [
"super(ScatterConnection, self).__init__()\nself.scatter_type = scatter_type\nassert self.scatter_type in ['cover', 'add']",
"device = x.device\nB, M, N = x.shape\nH, W = spatial_size\nindex = location.view(-1, 2)\nbias = torch.arange(B).mul_(H * W).unsqueeze(1).repeat(1, M).view(-1).to(device)\nindex = index[:, ... | <|body_start_0|>
super(ScatterConnection, self).__init__()
self.scatter_type = scatter_type
assert self.scatter_type in ['cover', 'add']
<|end_body_0|>
<|body_start_1|>
device = x.device
B, M, N = x.shape
H, W = spatial_size
index = location.view(-1, 2)
b... | Overview: Scatter feature to its corresponding location In AlphaStar, each entity is embedded into a tensor, and these tensors are scattered into a feature map with map size. | ScatterConnection | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScatterConnection:
"""Overview: Scatter feature to its corresponding location In AlphaStar, each entity is embedded into a tensor, and these tensors are scattered into a feature map with map size."""
def __init__(self, scatter_type: str) -> None:
"""Overview: Init class Arguments: - ... | stack_v2_sparse_classes_10k_train_002776 | 3,626 | permissive | [
{
"docstring": "Overview: Init class Arguments: - scatter_type (:obj:`str`): Supports ['add', 'cover']. If two entities have the same location, \\\\ scatter_type decides the first one should be covered or added to second one",
"name": "__init__",
"signature": "def __init__(self, scatter_type: str) -> No... | 2 | null | Implement the Python class `ScatterConnection` described below.
Class description:
Overview: Scatter feature to its corresponding location In AlphaStar, each entity is embedded into a tensor, and these tensors are scattered into a feature map with map size.
Method signatures and docstrings:
- def __init__(self, scatt... | Implement the Python class `ScatterConnection` described below.
Class description:
Overview: Scatter feature to its corresponding location In AlphaStar, each entity is embedded into a tensor, and these tensors are scattered into a feature map with map size.
Method signatures and docstrings:
- def __init__(self, scatt... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class ScatterConnection:
"""Overview: Scatter feature to its corresponding location In AlphaStar, each entity is embedded into a tensor, and these tensors are scattered into a feature map with map size."""
def __init__(self, scatter_type: str) -> None:
"""Overview: Init class Arguments: - ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ScatterConnection:
"""Overview: Scatter feature to its corresponding location In AlphaStar, each entity is embedded into a tensor, and these tensors are scattered into a feature map with map size."""
def __init__(self, scatter_type: str) -> None:
"""Overview: Init class Arguments: - scatter_type ... | the_stack_v2_python_sparse | ding/torch_utils/network/scatter_connection.py | shengxuesun/DI-engine | train | 1 |
b73ffda33853681d59c795061ab508641444e095 | [
"if len(s) == 0:\n self.answer = True\ncur_string = ''\nfor i in range(min(max_len, len(s))):\n cur_string += s[i]\n if cur_string in words:\n self.is_word_break(s[i + 1:], words, max_len)",
"if len(wordDict) == 0:\n return False\nself.answer = False\nmax_len = len(max(wordDict, key=len))\nself... | <|body_start_0|>
if len(s) == 0:
self.answer = True
cur_string = ''
for i in range(min(max_len, len(s))):
cur_string += s[i]
if cur_string in words:
self.is_word_break(s[i + 1:], words, max_len)
<|end_body_0|>
<|body_start_1|>
if len(w... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def is_word_break(self, s, words, max_len):
"""s: string words: set with words"""
<|body_0|>
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(s)... | stack_v2_sparse_classes_10k_train_002777 | 1,243 | no_license | [
{
"docstring": "s: string words: set with words",
"name": "is_word_break",
"signature": "def is_word_break(self, s, words, max_len)"
},
{
"docstring": ":type s: str :type wordDict: List[str] :rtype: bool",
"name": "wordBreak",
"signature": "def wordBreak(self, s, wordDict)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005777 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def is_word_break(self, s, words, max_len): s: string words: set with words
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def is_word_break(self, s, words, max_len): s: string words: set with words
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
<|skeleton|>
... | 98f02403996e62d358d7ca589902698346ac91ec | <|skeleton|>
class Solution:
def is_word_break(self, s, words, max_len):
"""s: string words: set with words"""
<|body_0|>
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def is_word_break(self, s, words, max_len):
"""s: string words: set with words"""
if len(s) == 0:
self.answer = True
cur_string = ''
for i in range(min(max_len, len(s))):
cur_string += s[i]
if cur_string in words:
se... | the_stack_v2_python_sparse | onsite_solutions/139_word_break.py | owoshch/LeetCode | train | 1 | |
22d0c183a8fd94a53b7c172bb6955cc73a7b9aa1 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('jkmoy_mfflynn', 'jkmoy_mfflynn')\nurl = 'http://gis.cityofboston.gov/arcgis/rest/services/PublicSafety/OpenData/MapServer/2/query?where=1%3D1&outFields=*&outSR=4326&f=json'\nresponse = urllib.request.url... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('jkmoy_mfflynn', 'jkmoy_mfflynn')
url = 'http://gis.cityofboston.gov/arcgis/rest/services/PublicSafety/OpenData/MapServer/2/query?where=1%3D1&outFields=*&o... | fire_departments | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class fire_departments:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everyth... | stack_v2_sparse_classes_10k_train_002778 | 3,941 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | null | Implement the Python class `fire_departments` described below.
Class description:
Implement the fire_departments class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=N... | Implement the Python class `fire_departments` described below.
Class description:
Implement the fire_departments class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=N... | 90284cf3debbac36eead07b8d2339cdd191b86cf | <|skeleton|>
class fire_departments:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everyth... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class fire_departments:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('jkmoy_mfflynn', 'jkmoy_mfflynn')
... | the_stack_v2_python_sparse | jkmoy_mfflynn/fire_departments.py | maximega/course-2019-spr-proj | train | 2 | |
1d80b38b793fdd2f0e6cc0ed08f9d1c0bdd385a0 | [
"self.comparer_title = ComparerTitle()\nself.comparer_desciption = ComparerDescription()\nself.comparer_text = ComparerText()\nself.comparer_author = ComparerAuthor()\nself.comparer_date = ComparerDate()",
"result = ArticleCandidate()\nresult.title = self.comparer_title.extract(item, article_candidates)\nresult.d... | <|body_start_0|>
self.comparer_title = ComparerTitle()
self.comparer_desciption = ComparerDescription()
self.comparer_text = ComparerText()
self.comparer_author = ComparerAuthor()
self.comparer_date = ComparerDate()
<|end_body_0|>
<|body_start_1|>
result = ArticleCandida... | Sends the list of ArticleCandidates to the subcomparer and saves the result in Article. | Comparer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Comparer:
"""Sends the list of ArticleCandidates to the subcomparer and saves the result in Article."""
def __init__(self):
"""Initializes the Comparer classes with an object each."""
<|body_0|>
def compare(self, item, article_candidates):
"""Compares the article... | stack_v2_sparse_classes_10k_train_002779 | 1,833 | no_license | [
{
"docstring": "Initializes the Comparer classes with an object each.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compares the article candidates using the different submodules and saves the best results in new ArticleCandidate object :param item: The NewscrawlerIt... | 2 | stack_v2_sparse_classes_30k_train_007164 | Implement the Python class `Comparer` described below.
Class description:
Sends the list of ArticleCandidates to the subcomparer and saves the result in Article.
Method signatures and docstrings:
- def __init__(self): Initializes the Comparer classes with an object each.
- def compare(self, item, article_candidates):... | Implement the Python class `Comparer` described below.
Class description:
Sends the list of ArticleCandidates to the subcomparer and saves the result in Article.
Method signatures and docstrings:
- def __init__(self): Initializes the Comparer classes with an object each.
- def compare(self, item, article_candidates):... | 733a48b20fbe45fe86f656d6a40afdc41be2c223 | <|skeleton|>
class Comparer:
"""Sends the list of ArticleCandidates to the subcomparer and saves the result in Article."""
def __init__(self):
"""Initializes the Comparer classes with an object each."""
<|body_0|>
def compare(self, item, article_candidates):
"""Compares the article... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Comparer:
"""Sends the list of ArticleCandidates to the subcomparer and saves the result in Article."""
def __init__(self):
"""Initializes the Comparer classes with an object each."""
self.comparer_title = ComparerTitle()
self.comparer_desciption = ComparerDescription()
se... | the_stack_v2_python_sparse | archive_crawling (as on Neo)/pipeline/extractor/comparer/comparer.py | Anacoder1/archive_crawling | train | 0 |
fce2acde174d06ee3dd4886fd72a3d7152b13e55 | [
"max_area = 0\nn = len(height)\nh_prev = 0\nfor i in range(0, n - 1):\n hi = height[i]\n if hi <= h_prev:\n continue\n for j in range(i + 1, n):\n hj = height[j]\n h = min(hi, hj)\n area = (j - i) * h\n if area > max_area:\n max_area = area\n h_prev ... | <|body_start_0|>
max_area = 0
n = len(height)
h_prev = 0
for i in range(0, n - 1):
hi = height[i]
if hi <= h_prev:
continue
for j in range(i + 1, n):
hj = height[j]
h = min(hi, hj)
area = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxArea_v1(self, height: List[int]) -> int:
"""A simple solution."""
<|body_0|>
def maxArea_v2(self, height: List[int]) -> int:
"""Use two pointers. Move the one with shorter height."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
max_... | stack_v2_sparse_classes_10k_train_002780 | 2,035 | no_license | [
{
"docstring": "A simple solution.",
"name": "maxArea_v1",
"signature": "def maxArea_v1(self, height: List[int]) -> int"
},
{
"docstring": "Use two pointers. Move the one with shorter height.",
"name": "maxArea_v2",
"signature": "def maxArea_v2(self, height: List[int]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_001723 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea_v1(self, height: List[int]) -> int: A simple solution.
- def maxArea_v2(self, height: List[int]) -> int: Use two pointers. Move the one with shorter height. | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea_v1(self, height: List[int]) -> int: A simple solution.
- def maxArea_v2(self, height: List[int]) -> int: Use two pointers. Move the one with shorter height.
<|skelet... | 97a2386f5e3adbd7138fd123810c3232bdf7f622 | <|skeleton|>
class Solution:
def maxArea_v1(self, height: List[int]) -> int:
"""A simple solution."""
<|body_0|>
def maxArea_v2(self, height: List[int]) -> int:
"""Use two pointers. Move the one with shorter height."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxArea_v1(self, height: List[int]) -> int:
"""A simple solution."""
max_area = 0
n = len(height)
h_prev = 0
for i in range(0, n - 1):
hi = height[i]
if hi <= h_prev:
continue
for j in range(i + 1, n):
... | the_stack_v2_python_sparse | python3/string_array/container_with_most_water.py | victorchu/algorithms | train | 0 | |
d0622ec9a9fb891ae2c9a0a875e3f0e5666725ed | [
"super().__init__()\nself.cfg = cfg\nself.task_queue = task_queue\nself.result_queue = result_queue\nself.gpu_id = gpu_id\nself.device = torch.device('cuda:{}'.format(self.gpu_id)) if self.cfg.NUM_GPUS else 'cpu'",
"model = Predictor(self.cfg, gpu_id=self.gpu_id)\nwhile True:\n task = self.task_queue.get()\n ... | <|body_start_0|>
super().__init__()
self.cfg = cfg
self.task_queue = task_queue
self.result_queue = result_queue
self.gpu_id = gpu_id
self.device = torch.device('cuda:{}'.format(self.gpu_id)) if self.cfg.NUM_GPUS else 'cpu'
<|end_body_0|>
<|body_start_1|>
model =... | _Predictor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Predictor:
def __init__(self, cfg, task_queue, result_queue, gpu_id=None):
"""Predict Worker for Detectron2. Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.py task_queue (mp.Queue): a shared queue for incoming task. result_queue (mp.Queue): a shared queue... | stack_v2_sparse_classes_10k_train_002781 | 9,808 | permissive | [
{
"docstring": "Predict Worker for Detectron2. Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.py task_queue (mp.Queue): a shared queue for incoming task. result_queue (mp.Queue): a shared queue for predicted results. gpu_id (int): index of the GPU device for the current child pro... | 2 | stack_v2_sparse_classes_30k_train_001441 | Implement the Python class `_Predictor` described below.
Class description:
Implement the _Predictor class.
Method signatures and docstrings:
- def __init__(self, cfg, task_queue, result_queue, gpu_id=None): Predict Worker for Detectron2. Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.... | Implement the Python class `_Predictor` described below.
Class description:
Implement the _Predictor class.
Method signatures and docstrings:
- def __init__(self, cfg, task_queue, result_queue, gpu_id=None): Predict Worker for Detectron2. Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.... | 6092dad7be32bb1d6b71fe1bade258dc8b492fe3 | <|skeleton|>
class _Predictor:
def __init__(self, cfg, task_queue, result_queue, gpu_id=None):
"""Predict Worker for Detectron2. Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.py task_queue (mp.Queue): a shared queue for incoming task. result_queue (mp.Queue): a shared queue... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _Predictor:
def __init__(self, cfg, task_queue, result_queue, gpu_id=None):
"""Predict Worker for Detectron2. Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.py task_queue (mp.Queue): a shared queue for incoming task. result_queue (mp.Queue): a shared queue for predicted... | the_stack_v2_python_sparse | slowfast/visualization/async_predictor.py | facebookresearch/SlowFast | train | 6,221 | |
6851f6320b96f8defc30e40b99b7cb387ac6c84f | [
"self.places = {}\nself.transitions = {}\nself.successful_firings = []\nself.a = {}",
"pn_copy = PetriNetModel()\nfor place in petri_net_model.places.values():\n pn_copy.add_place(place.tokens, place.place_id, place.label)\nfor t in petri_net_model.transitions.values():\n input_place_ids = [arc.place.place_... | <|body_start_0|>
self.places = {}
self.transitions = {}
self.successful_firings = []
self.a = {}
<|end_body_0|>
<|body_start_1|>
pn_copy = PetriNetModel()
for place in petri_net_model.places.values():
pn_copy.add_place(place.tokens, place.place_id, place.labe... | PetriNetModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PetriNetModel:
def __init__(self):
"""Initialize an empty Petri net."""
<|body_0|>
def make_copy_of(petri_net_model):
"""Makes a deep copy of a PetriNetModel instance. Args: petri_net_model: instance of PetriNetModel to be copied"""
<|body_1|>
def add_pl... | stack_v2_sparse_classes_10k_train_002782 | 27,136 | no_license | [
{
"docstring": "Initialize an empty Petri net.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Makes a deep copy of a PetriNetModel instance. Args: petri_net_model: instance of PetriNetModel to be copied",
"name": "make_copy_of",
"signature": "def make_copy_of(... | 5 | stack_v2_sparse_classes_30k_train_003333 | Implement the Python class `PetriNetModel` described below.
Class description:
Implement the PetriNetModel class.
Method signatures and docstrings:
- def __init__(self): Initialize an empty Petri net.
- def make_copy_of(petri_net_model): Makes a deep copy of a PetriNetModel instance. Args: petri_net_model: instance o... | Implement the Python class `PetriNetModel` described below.
Class description:
Implement the PetriNetModel class.
Method signatures and docstrings:
- def __init__(self): Initialize an empty Petri net.
- def make_copy_of(petri_net_model): Makes a deep copy of a PetriNetModel instance. Args: petri_net_model: instance o... | 8e9a3a8151069757475808c48511c9d7486ea334 | <|skeleton|>
class PetriNetModel:
def __init__(self):
"""Initialize an empty Petri net."""
<|body_0|>
def make_copy_of(petri_net_model):
"""Makes a deep copy of a PetriNetModel instance. Args: petri_net_model: instance of PetriNetModel to be copied"""
<|body_1|>
def add_pl... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PetriNetModel:
def __init__(self):
"""Initialize an empty Petri net."""
self.places = {}
self.transitions = {}
self.successful_firings = []
self.a = {}
def make_copy_of(petri_net_model):
"""Makes a deep copy of a PetriNetModel instance. Args: petri_net_mode... | the_stack_v2_python_sparse | Stochasticity-Net/Stochastic_PN_Architecture_v2.py | PN-Alzheimers-Parkinsons/PN_Alzheimers_Parkinsons | train | 0 | |
728950db8566de00e1ed17390c14d5bdabba0c12 | [
"super(CAServerCert, self).__init__(None, config.kubeconfig, verbose)\nself.config = config\nself.verbose = verbose",
"cert = self.config.config_options['cert']['value']\nif cert and os.path.exists(cert):\n return open(cert).read()\nreturn None",
"if self.config.config_options['backup']['value']:\n import... | <|body_start_0|>
super(CAServerCert, self).__init__(None, config.kubeconfig, verbose)
self.config = config
self.verbose = verbose
<|end_body_0|>
<|body_start_1|>
cert = self.config.config_options['cert']['value']
if cert and os.path.exists(cert):
return open(cert).re... | Class to wrap the oc adm ca create-server-cert command line | CAServerCert | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CAServerCert:
"""Class to wrap the oc adm ca create-server-cert command line"""
def __init__(self, config, verbose=False):
"""Constructor for oadm ca"""
<|body_0|>
def get(self):
"""get the current cert file If a file exists by the same name in the specified loca... | stack_v2_sparse_classes_10k_train_002783 | 6,137 | permissive | [
{
"docstring": "Constructor for oadm ca",
"name": "__init__",
"signature": "def __init__(self, config, verbose=False)"
},
{
"docstring": "get the current cert file If a file exists by the same name in the specified location then the cert exists",
"name": "get",
"signature": "def get(self... | 5 | null | Implement the Python class `CAServerCert` described below.
Class description:
Class to wrap the oc adm ca create-server-cert command line
Method signatures and docstrings:
- def __init__(self, config, verbose=False): Constructor for oadm ca
- def get(self): get the current cert file If a file exists by the same name ... | Implement the Python class `CAServerCert` described below.
Class description:
Class to wrap the oc adm ca create-server-cert command line
Method signatures and docstrings:
- def __init__(self, config, verbose=False): Constructor for oadm ca
- def get(self): get the current cert file If a file exists by the same name ... | e342f6659a4ef1a188ff403e2fc6b06ac6d119c7 | <|skeleton|>
class CAServerCert:
"""Class to wrap the oc adm ca create-server-cert command line"""
def __init__(self, config, verbose=False):
"""Constructor for oadm ca"""
<|body_0|>
def get(self):
"""get the current cert file If a file exists by the same name in the specified loca... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CAServerCert:
"""Class to wrap the oc adm ca create-server-cert command line"""
def __init__(self, config, verbose=False):
"""Constructor for oadm ca"""
super(CAServerCert, self).__init__(None, config.kubeconfig, verbose)
self.config = config
self.verbose = verbose
de... | the_stack_v2_python_sparse | openshift/installer/vendored/openshift-ansible-3.9.14-1/roles/lib_openshift/src/class/oc_adm_ca_server_cert.py | openshift/openshift-tools | train | 170 |
51f6da55b44ef8565b8294046b1a8ac99c0f79ab | [
"lifecycle_arg = self.args[0]\nurl_args = self.args[1:]\nif not UrlsAreForSingleProvider(url_args):\n raise CommandException('\"%s\" command spanning providers not allowed.' % self.command_name)\nlifecycle_file = open(lifecycle_arg, 'r')\nlifecycle_txt = lifecycle_file.read()\nlifecycle_file.close()\nsome_matche... | <|body_start_0|>
lifecycle_arg = self.args[0]
url_args = self.args[1:]
if not UrlsAreForSingleProvider(url_args):
raise CommandException('"%s" command spanning providers not allowed.' % self.command_name)
lifecycle_file = open(lifecycle_arg, 'r')
lifecycle_txt = lifec... | Implementation of gsutil lifecycle command. | LifecycleCommand | [
"BSD-3-Clause",
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LifecycleCommand:
"""Implementation of gsutil lifecycle command."""
def _SetLifecycleConfig(self):
"""Sets lifecycle configuration for a Google Cloud Storage bucket."""
<|body_0|>
def _GetLifecycleConfig(self):
"""Gets lifecycle configuration for a Google Cloud S... | stack_v2_sparse_classes_10k_train_002784 | 7,415 | permissive | [
{
"docstring": "Sets lifecycle configuration for a Google Cloud Storage bucket.",
"name": "_SetLifecycleConfig",
"signature": "def _SetLifecycleConfig(self)"
},
{
"docstring": "Gets lifecycle configuration for a Google Cloud Storage bucket.",
"name": "_GetLifecycleConfig",
"signature": "... | 3 | null | Implement the Python class `LifecycleCommand` described below.
Class description:
Implementation of gsutil lifecycle command.
Method signatures and docstrings:
- def _SetLifecycleConfig(self): Sets lifecycle configuration for a Google Cloud Storage bucket.
- def _GetLifecycleConfig(self): Gets lifecycle configuration... | Implement the Python class `LifecycleCommand` described below.
Class description:
Implementation of gsutil lifecycle command.
Method signatures and docstrings:
- def _SetLifecycleConfig(self): Sets lifecycle configuration for a Google Cloud Storage bucket.
- def _GetLifecycleConfig(self): Gets lifecycle configuration... | 53102de187a48ac2cfc241fef54dcbc29c453a8e | <|skeleton|>
class LifecycleCommand:
"""Implementation of gsutil lifecycle command."""
def _SetLifecycleConfig(self):
"""Sets lifecycle configuration for a Google Cloud Storage bucket."""
<|body_0|>
def _GetLifecycleConfig(self):
"""Gets lifecycle configuration for a Google Cloud S... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LifecycleCommand:
"""Implementation of gsutil lifecycle command."""
def _SetLifecycleConfig(self):
"""Sets lifecycle configuration for a Google Cloud Storage bucket."""
lifecycle_arg = self.args[0]
url_args = self.args[1:]
if not UrlsAreForSingleProvider(url_args):
... | the_stack_v2_python_sparse | third_party/gsutil/gslib/commands/lifecycle.py | catapult-project/catapult | train | 2,032 |
d675ffb926b6f8f2fb131440c062b5fa10eee2f4 | [
"super().__init__()\nfull_list = [input_dim] + list(hidden_dims) + [z_dim]\nself.encoder = MLP(dim_list=full_list)\nfull_list.reverse()\nself.decoder = MLP(dim_list=full_list)\nself.noise = noise",
"z = self.encoder(x)\nif self.noise > 0:\n z_decoder = z + self.noise * torch.randn_like(z)\nelse:\n z_decoder... | <|body_start_0|>
super().__init__()
full_list = [input_dim] + list(hidden_dims) + [z_dim]
self.encoder = MLP(dim_list=full_list)
full_list.reverse()
self.decoder = MLP(dim_list=full_list)
self.noise = noise
<|end_body_0|>
<|body_start_1|>
z = self.encoder(x)
... | Vanilla Autoencoder torch module | AutoencoderModule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoencoderModule:
"""Vanilla Autoencoder torch module"""
def __init__(self, input_dim, hidden_dims, z_dim, noise=0):
"""Init. Args: input_dim(int): Dimension of the input data. hidden_dims(List[int]): List of hidden dimensions. Do not include dimensions of the input layer and the bo... | stack_v2_sparse_classes_10k_train_002785 | 10,936 | no_license | [
{
"docstring": "Init. Args: input_dim(int): Dimension of the input data. hidden_dims(List[int]): List of hidden dimensions. Do not include dimensions of the input layer and the bottleneck. See MLP for example. z_dim(int): Bottleneck dimension. noise(float): Variance of the gaussian noise applied to the latent s... | 2 | stack_v2_sparse_classes_30k_train_007008 | Implement the Python class `AutoencoderModule` described below.
Class description:
Vanilla Autoencoder torch module
Method signatures and docstrings:
- def __init__(self, input_dim, hidden_dims, z_dim, noise=0): Init. Args: input_dim(int): Dimension of the input data. hidden_dims(List[int]): List of hidden dimensions... | Implement the Python class `AutoencoderModule` described below.
Class description:
Vanilla Autoencoder torch module
Method signatures and docstrings:
- def __init__(self, input_dim, hidden_dims, z_dim, noise=0): Init. Args: input_dim(int): Dimension of the input data. hidden_dims(List[int]): List of hidden dimensions... | 9027b529eaa4cf0a38f25512141810f92db99639 | <|skeleton|>
class AutoencoderModule:
"""Vanilla Autoencoder torch module"""
def __init__(self, input_dim, hidden_dims, z_dim, noise=0):
"""Init. Args: input_dim(int): Dimension of the input data. hidden_dims(List[int]): List of hidden dimensions. Do not include dimensions of the input layer and the bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AutoencoderModule:
"""Vanilla Autoencoder torch module"""
def __init__(self, input_dim, hidden_dims, z_dim, noise=0):
"""Init. Args: input_dim(int): Dimension of the input data. hidden_dims(List[int]): List of hidden dimensions. Do not include dimensions of the input layer and the bottleneck. See... | the_stack_v2_python_sparse | grae/models/torch_modules.py | jakerhodes/GRAE | train | 0 |
5a9f8dd7fbfc5d15af38965d539cddb9db9eec21 | [
"name = input('请输入增加的课程名称：')\nif name in Data.courses_dict:\n print('课程已存在，请使用其他课程名称')\n return self.add_course()\nteacher = input('请输入授课老师：')\nlimit = input('请输入人数：')\ntimes = input('请输入课程时长：')\nscore = input('请输入分数：')\ndes = input('请输入课程描述：')\ncourse = Course(name, teacher, limit, times, score, des)\ncourse... | <|body_start_0|>
name = input('请输入增加的课程名称：')
if name in Data.courses_dict:
print('课程已存在，请使用其他课程名称')
return self.add_course()
teacher = input('请输入授课老师：')
limit = input('请输入人数：')
times = input('请输入课程时长：')
score = input('请输入分数：')
des = input('... | 管理员类 | Admin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Admin:
"""管理员类"""
def add_course(self):
"""添加课程"""
<|body_0|>
def check_course(self):
"""查看课程"""
<|body_1|>
def update_course(self):
"""修改课程"""
<|body_2|>
def delete_course(self):
"""删除课程"""
<|body_3|>
<|end_skel... | stack_v2_sparse_classes_10k_train_002786 | 4,039 | no_license | [
{
"docstring": "添加课程",
"name": "add_course",
"signature": "def add_course(self)"
},
{
"docstring": "查看课程",
"name": "check_course",
"signature": "def check_course(self)"
},
{
"docstring": "修改课程",
"name": "update_course",
"signature": "def update_course(self)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_000411 | Implement the Python class `Admin` described below.
Class description:
管理员类
Method signatures and docstrings:
- def add_course(self): 添加课程
- def check_course(self): 查看课程
- def update_course(self): 修改课程
- def delete_course(self): 删除课程 | Implement the Python class `Admin` described below.
Class description:
管理员类
Method signatures and docstrings:
- def add_course(self): 添加课程
- def check_course(self): 查看课程
- def update_course(self): 修改课程
- def delete_course(self): 删除课程
<|skeleton|>
class Admin:
"""管理员类"""
def add_course(self):
"""添加课程... | e11f5fcb10f37a0f0663e4c746ca862b076f9aee | <|skeleton|>
class Admin:
"""管理员类"""
def add_course(self):
"""添加课程"""
<|body_0|>
def check_course(self):
"""查看课程"""
<|body_1|>
def update_course(self):
"""修改课程"""
<|body_2|>
def delete_course(self):
"""删除课程"""
<|body_3|>
<|end_skel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Admin:
"""管理员类"""
def add_course(self):
"""添加课程"""
name = input('请输入增加的课程名称：')
if name in Data.courses_dict:
print('课程已存在，请使用其他课程名称')
return self.add_course()
teacher = input('请输入授课老师：')
limit = input('请输入人数：')
times = input('请输入课程时长... | the_stack_v2_python_sparse | dmeo/day12/code/demo_01homework.py | liujiang9/python0421 | train | 1 |
471d2f791f86f996fa061967d95ecb388b1d6f8f | [
"self.algorithm = algorithm\nself.mode = mode\nself.data_key_length = data_key_length\nself.iv_length = iv_length\nself.auth_length = self.tag_len = auth_length\nself.auth_key_length = auth_key_length",
"if kdf.input_length is None:\n return True\nif self.data_key_length > kdf.input_length(self):\n raise In... | <|body_start_0|>
self.algorithm = algorithm
self.mode = mode
self.data_key_length = data_key_length
self.iv_length = iv_length
self.auth_length = self.tag_len = auth_length
self.auth_key_length = auth_key_length
<|end_body_0|>
<|body_start_1|>
if kdf.input_length... | Static definition of encryption algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: Encryption algorithm to use :type algorithm: cryptography.io ciphers algorithm object :param mode: Encryption mode in which to operate :type mode: cryptography.io ciphers modes... | EncryptionSuite | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncryptionSuite:
"""Static definition of encryption algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: Encryption algorithm to use :type algorithm: cryptography.io ciphers algorithm object :param mode: Encryption mode in which to operat... | stack_v2_sparse_classes_10k_train_002787 | 14,661 | permissive | [
{
"docstring": "Prepare a new EncryptionSuite.",
"name": "__init__",
"signature": "def __init__(self, algorithm, mode, data_key_length, iv_length, auth_length, auth_key_length=0)"
},
{
"docstring": "Determine whether a KDFSuite can be used with this EncryptionSuite. :param kdf: KDFSuite to evalu... | 2 | stack_v2_sparse_classes_30k_train_006913 | Implement the Python class `EncryptionSuite` described below.
Class description:
Static definition of encryption algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: Encryption algorithm to use :type algorithm: cryptography.io ciphers algorithm object :param m... | Implement the Python class `EncryptionSuite` described below.
Class description:
Static definition of encryption algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: Encryption algorithm to use :type algorithm: cryptography.io ciphers algorithm object :param m... | 3ba8019681ed95c41bb9448f0c3897d1aecc7559 | <|skeleton|>
class EncryptionSuite:
"""Static definition of encryption algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: Encryption algorithm to use :type algorithm: cryptography.io ciphers algorithm object :param mode: Encryption mode in which to operat... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EncryptionSuite:
"""Static definition of encryption algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: Encryption algorithm to use :type algorithm: cryptography.io ciphers algorithm object :param mode: Encryption mode in which to operate :type mode:... | the_stack_v2_python_sparse | src/aws_encryption_sdk/identifiers.py | aws/aws-encryption-sdk-python | train | 137 |
ba47d5cff5803b1ab354517493b6c1d14210dc85 | [
"self._cache_whitelist = set(benchmark_setup['cache_whitelist'])\nself._original_requests = set(cache_validation_result['effective_encoded_data_lengths'].keys())\nself._original_post_requests = set(cache_validation_result['effective_post_requests'])\nself._original_cached_requests = self._original_requests.intersec... | <|body_start_0|>
self._cache_whitelist = set(benchmark_setup['cache_whitelist'])
self._original_requests = set(cache_validation_result['effective_encoded_data_lengths'].keys())
self._original_post_requests = set(cache_validation_result['effective_post_requests'])
self._original_cached_re... | Object to verify benchmark run from traces and WPR log stored in the runner output directory. | _RunOutputVerifier | [
"BSD-3-Clause",
"LGPL-2.0-or-later",
"LicenseRef-scancode-unknown-license-reference",
"GPL-2.0-only",
"Apache-2.0",
"LicenseRef-scancode-unknown",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _RunOutputVerifier:
"""Object to verify benchmark run from traces and WPR log stored in the runner output directory."""
def __init__(self, cache_validation_result, benchmark_setup):
"""Constructor. Args: cache_validation_result: JSON of the cache validation task. benchmark_setup: JSO... | stack_v2_sparse_classes_10k_train_002788 | 28,927 | permissive | [
{
"docstring": "Constructor. Args: cache_validation_result: JSON of the cache validation task. benchmark_setup: JSON of the benchmark setup.",
"name": "__init__",
"signature": "def __init__(self, cache_validation_result, benchmark_setup)"
},
{
"docstring": "Verifies a trace with the cache valida... | 3 | stack_v2_sparse_classes_30k_train_006206 | Implement the Python class `_RunOutputVerifier` described below.
Class description:
Object to verify benchmark run from traces and WPR log stored in the runner output directory.
Method signatures and docstrings:
- def __init__(self, cache_validation_result, benchmark_setup): Constructor. Args: cache_validation_result... | Implement the Python class `_RunOutputVerifier` described below.
Class description:
Object to verify benchmark run from traces and WPR log stored in the runner output directory.
Method signatures and docstrings:
- def __init__(self, cache_validation_result, benchmark_setup): Constructor. Args: cache_validation_result... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class _RunOutputVerifier:
"""Object to verify benchmark run from traces and WPR log stored in the runner output directory."""
def __init__(self, cache_validation_result, benchmark_setup):
"""Constructor. Args: cache_validation_result: JSON of the cache validation task. benchmark_setup: JSO... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _RunOutputVerifier:
"""Object to verify benchmark run from traces and WPR log stored in the runner output directory."""
def __init__(self, cache_validation_result, benchmark_setup):
"""Constructor. Args: cache_validation_result: JSON of the cache validation task. benchmark_setup: JSON of the benc... | the_stack_v2_python_sparse | tools/android/loading/sandwich_prefetch.py | metux/chromium-suckless | train | 5 |
d249acb48540e89f3c55617851d80935a2de8fb3 | [
"def backTrack(n, res, tmp, flag, row):\n if row == n:\n z = []\n for t in tmp:\n z.append(''.join(t))\n res.append(z)\n else:\n for col in range(n):\n if flag[row] and flag[n + col] and flag[2 * n + row + col] and flag[5 * n - 2 + col - row]:\n ... | <|body_start_0|>
def backTrack(n, res, tmp, flag, row):
if row == n:
z = []
for t in tmp:
z.append(''.join(t))
res.append(z)
else:
for col in range(n):
if flag[row] and flag[n + col] a... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def totalNQueens(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def totalNQueens0(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def backTrack(n, res, tmp, flag, row):
if row == n:
... | stack_v2_sparse_classes_10k_train_002789 | 2,109 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "totalNQueens",
"signature": "def totalNQueens(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "totalNQueens0",
"signature": "def totalNQueens0(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001691 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def totalNQueens(self, n): :type n: int :rtype: int
- def totalNQueens0(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 totalNQueens(self, n): :type n: int :rtype: int
- def totalNQueens0(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def totalNQueens(self, n):
"... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def totalNQueens(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def totalNQueens0(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def totalNQueens(self, n):
""":type n: int :rtype: int"""
def backTrack(n, res, tmp, flag, row):
if row == n:
z = []
for t in tmp:
z.append(''.join(t))
res.append(z)
else:
for ... | the_stack_v2_python_sparse | PythonCode/src/0052_N-Queens_II.py | oneyuan/CodeforFun | train | 0 | |
e8757510f01e318dba95862d835874c69e97286d | [
"low, high = (0, len(height) - 1)\nret = 0\nwhile low < high:\n ret = max(min(height[low], height[high]) * (high - low), ret)\n if height[low] <= height[high]:\n low += 1\n else:\n high -= 1\nreturn ret",
"i = 0\nj = len(height) - 1\nmax_value = 0\ntop = max(height)\nwhile i < j:\n if to... | <|body_start_0|>
low, high = (0, len(height) - 1)
ret = 0
while low < high:
ret = max(min(height[low], height[high]) * (high - low), ret)
if height[low] <= height[high]:
low += 1
else:
high -= 1
return ret
<|end_body_0|>... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxArea(self, height: List[int]) -> int:
"""Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0 <= height[i] <= 10^4 :param height: :return:"""
<|body_0|>
def maxArea2(self, heigh... | stack_v2_sparse_classes_10k_train_002790 | 1,839 | permissive | [
{
"docstring": "Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0 <= height[i] <= 10^4 :param height: :return:",
"name": "maxArea",
"signature": "def maxArea(self, height: List[int]) -> int"
},
{
"docstring": "Up... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height: List[int]) -> int: Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height: List[int]) -> int: Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def maxArea(self, height: List[int]) -> int:
"""Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0 <= height[i] <= 10^4 :param height: :return:"""
<|body_0|>
def maxArea2(self, heigh... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxArea(self, height: List[int]) -> int:
"""Updated at 2022/01/04 Runtime: 1491 ms, faster than 5.01% Memory Usage: 27.6 MB, less than 22.34% n == height.length 2 <= n <= 10^5 0 <= height[i] <= 10^4 :param height: :return:"""
low, high = (0, len(height) - 1)
ret = 0
... | the_stack_v2_python_sparse | src/11-ContainerWithMostWater.py | Jiezhi/myleetcode | train | 1 | |
24c3fa2ed01e9e9a7a05aaf3eb9d54c95726ba31 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Proto file describing the keyword plan ad group keyword service. Service to manage Keyword Plan ad group keywords. KeywordPlanAdGroup is required to add ad group keywords. Positive and negative keywords are supported. A maximum of 10,000 positive keywords are allowed per keyword plan. A maximum of 1,000 negative keywor... | KeywordPlanAdGroupKeywordServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KeywordPlanAdGroupKeywordServiceServicer:
"""Proto file describing the keyword plan ad group keyword service. Service to manage Keyword Plan ad group keywords. KeywordPlanAdGroup is required to add ad group keywords. Positive and negative keywords are supported. A maximum of 10,000 positive keywo... | stack_v2_sparse_classes_10k_train_002791 | 7,403 | permissive | [
{
"docstring": "Returns the requested Keyword Plan ad group keyword in full detail.",
"name": "GetKeywordPlanAdGroupKeyword",
"signature": "def GetKeywordPlanAdGroupKeyword(self, request, context)"
},
{
"docstring": "Creates, updates, or removes Keyword Plan ad group keywords. Operation statuses... | 2 | stack_v2_sparse_classes_30k_train_004575 | Implement the Python class `KeywordPlanAdGroupKeywordServiceServicer` described below.
Class description:
Proto file describing the keyword plan ad group keyword service. Service to manage Keyword Plan ad group keywords. KeywordPlanAdGroup is required to add ad group keywords. Positive and negative keywords are suppor... | Implement the Python class `KeywordPlanAdGroupKeywordServiceServicer` described below.
Class description:
Proto file describing the keyword plan ad group keyword service. Service to manage Keyword Plan ad group keywords. KeywordPlanAdGroup is required to add ad group keywords. Positive and negative keywords are suppor... | 969eff5b6c3cec59d21191fa178cffb6270074c3 | <|skeleton|>
class KeywordPlanAdGroupKeywordServiceServicer:
"""Proto file describing the keyword plan ad group keyword service. Service to manage Keyword Plan ad group keywords. KeywordPlanAdGroup is required to add ad group keywords. Positive and negative keywords are supported. A maximum of 10,000 positive keywo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KeywordPlanAdGroupKeywordServiceServicer:
"""Proto file describing the keyword plan ad group keyword service. Service to manage Keyword Plan ad group keywords. KeywordPlanAdGroup is required to add ad group keywords. Positive and negative keywords are supported. A maximum of 10,000 positive keywords are allow... | the_stack_v2_python_sparse | google/ads/google_ads/v6/proto/services/keyword_plan_ad_group_keyword_service_pb2_grpc.py | VincentFritzsche/google-ads-python | train | 0 |
b7125ee4085eaa9bb16722583bf045bf9c6f40b6 | [
"from django.conf.urls import patterns, url\nurls = super(RecurrenceRuleAdmin, self).get_urls()\nmy_urls = patterns('', url('^preview/$', self.admin_site.admin_view(self.preview), name='icekit_events_recurrencerule_preview'))\nreturn my_urls + urls",
"recurrence_rule = request.POST.get('recurrence_rule')\nlimit =... | <|body_start_0|>
from django.conf.urls import patterns, url
urls = super(RecurrenceRuleAdmin, self).get_urls()
my_urls = patterns('', url('^preview/$', self.admin_site.admin_view(self.preview), name='icekit_events_recurrencerule_preview'))
return my_urls + urls
<|end_body_0|>
<|body_sta... | RecurrenceRuleAdmin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecurrenceRuleAdmin:
def get_urls(self):
"""Add a preview URL."""
<|body_0|>
def preview(self, request):
"""Return a occurrences in JSON format up until the configured limit."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
from django.conf.urls impo... | stack_v2_sparse_classes_10k_train_002792 | 14,586 | permissive | [
{
"docstring": "Add a preview URL.",
"name": "get_urls",
"signature": "def get_urls(self)"
},
{
"docstring": "Return a occurrences in JSON format up until the configured limit.",
"name": "preview",
"signature": "def preview(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003793 | Implement the Python class `RecurrenceRuleAdmin` described below.
Class description:
Implement the RecurrenceRuleAdmin class.
Method signatures and docstrings:
- def get_urls(self): Add a preview URL.
- def preview(self, request): Return a occurrences in JSON format up until the configured limit. | Implement the Python class `RecurrenceRuleAdmin` described below.
Class description:
Implement the RecurrenceRuleAdmin class.
Method signatures and docstrings:
- def get_urls(self): Add a preview URL.
- def preview(self, request): Return a occurrences in JSON format up until the configured limit.
<|skeleton|>
class ... | c507ea5b1864303732c53ad7c5800571fca5fa94 | <|skeleton|>
class RecurrenceRuleAdmin:
def get_urls(self):
"""Add a preview URL."""
<|body_0|>
def preview(self, request):
"""Return a occurrences in JSON format up until the configured limit."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RecurrenceRuleAdmin:
def get_urls(self):
"""Add a preview URL."""
from django.conf.urls import patterns, url
urls = super(RecurrenceRuleAdmin, self).get_urls()
my_urls = patterns('', url('^preview/$', self.admin_site.admin_view(self.preview), name='icekit_events_recurrencerule_... | the_stack_v2_python_sparse | icekit_events/admin.py | ic-labs/django-icekit | train | 53 | |
c4ccf1752680a47b6be2c06ac2209b125daa556e | [
"s1 = list(map(int, version1.split('.')))\ns2 = list(map(int, version2.split('.')))\nif len(s1) > len(s2):\n s2.extend([0] * (len(s1) - len(s2)))\nelif len(s1) < len(s2):\n s1.extend([0] * (len(s2) - len(s1)))\nif s1 > s2:\n return 1\nelif s1 < s2:\n return -1\nelse:\n return 0",
"s1 = list(map(int... | <|body_start_0|>
s1 = list(map(int, version1.split('.')))
s2 = list(map(int, version2.split('.')))
if len(s1) > len(s2):
s2.extend([0] * (len(s1) - len(s2)))
elif len(s1) < len(s2):
s1.extend([0] * (len(s2) - len(s1)))
if s1 > s2:
return 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def compareVersion(self, version1, version2):
""":type version1: str :type version2: str :rtype: int"""
<|body_0|>
def compareVersion_1(self, version1, version2):
""":type version1: str :type version2: str :rtype: int"""
<|body_1|>
<|end_skeleton|>... | stack_v2_sparse_classes_10k_train_002793 | 3,635 | no_license | [
{
"docstring": ":type version1: str :type version2: str :rtype: int",
"name": "compareVersion",
"signature": "def compareVersion(self, version1, version2)"
},
{
"docstring": ":type version1: str :type version2: str :rtype: int",
"name": "compareVersion_1",
"signature": "def compareVersio... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def compareVersion(self, version1, version2): :type version1: str :type version2: str :rtype: int
- def compareVersion_1(self, version1, version2): :type version1: str :type vers... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def compareVersion(self, version1, version2): :type version1: str :type version2: str :rtype: int
- def compareVersion_1(self, version1, version2): :type version1: str :type vers... | 3d9e0ad2f6ed92ec969556f75d97c51ea4854719 | <|skeleton|>
class Solution:
def compareVersion(self, version1, version2):
""":type version1: str :type version2: str :rtype: int"""
<|body_0|>
def compareVersion_1(self, version1, version2):
""":type version1: str :type version2: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def compareVersion(self, version1, version2):
""":type version1: str :type version2: str :rtype: int"""
s1 = list(map(int, version1.split('.')))
s2 = list(map(int, version2.split('.')))
if len(s1) > len(s2):
s2.extend([0] * (len(s1) - len(s2)))
eli... | the_stack_v2_python_sparse | Solutions/0165_compareVersion.py | YoupengLi/leetcode-sorting | train | 3 | |
fbe664acda29fa4f09813d4a03f0baa3fb8597d1 | [
"if 'event_uuid' in self.kwargs:\n self.event_proposal = get_object_or_404(models.EventProposal, uuid=self.kwargs['event_uuid'], user=request.user)\nelif 'speaker_uuid' in self.kwargs:\n self.speaker_proposal = get_object_or_404(models.SpeakerProposal, uuid=self.kwargs['speaker_uuid'], user=request.user)\nels... | <|body_start_0|>
if 'event_uuid' in self.kwargs:
self.event_proposal = get_object_or_404(models.EventProposal, uuid=self.kwargs['event_uuid'], user=request.user)
elif 'speaker_uuid' in self.kwargs:
self.speaker_proposal = get_object_or_404(models.SpeakerProposal, uuid=self.kwargs... | Mixin with code shared between all the Url views | UrlViewMixin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UrlViewMixin:
"""Mixin with code shared between all the Url views"""
def dispatch(self, request, *args, **kwargs):
"""Check that we have a valid SpeakerProposal or EventProposal and that it belongs to the current user"""
<|body_0|>
def get_context_data(self, **kwargs):
... | stack_v2_sparse_classes_10k_train_002794 | 7,691 | permissive | [
{
"docstring": "Check that we have a valid SpeakerProposal or EventProposal and that it belongs to the current user",
"name": "dispatch",
"signature": "def dispatch(self, request, *args, **kwargs)"
},
{
"docstring": "Include the proposal in the template context",
"name": "get_context_data",
... | 3 | stack_v2_sparse_classes_30k_train_006518 | Implement the Python class `UrlViewMixin` described below.
Class description:
Mixin with code shared between all the Url views
Method signatures and docstrings:
- def dispatch(self, request, *args, **kwargs): Check that we have a valid SpeakerProposal or EventProposal and that it belongs to the current user
- def get... | Implement the Python class `UrlViewMixin` described below.
Class description:
Mixin with code shared between all the Url views
Method signatures and docstrings:
- def dispatch(self, request, *args, **kwargs): Check that we have a valid SpeakerProposal or EventProposal and that it belongs to the current user
- def get... | 767deb7f58429e9162e0c2ef79be9f0f38f37ce1 | <|skeleton|>
class UrlViewMixin:
"""Mixin with code shared between all the Url views"""
def dispatch(self, request, *args, **kwargs):
"""Check that we have a valid SpeakerProposal or EventProposal and that it belongs to the current user"""
<|body_0|>
def get_context_data(self, **kwargs):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UrlViewMixin:
"""Mixin with code shared between all the Url views"""
def dispatch(self, request, *args, **kwargs):
"""Check that we have a valid SpeakerProposal or EventProposal and that it belongs to the current user"""
if 'event_uuid' in self.kwargs:
self.event_proposal = ge... | the_stack_v2_python_sparse | src/program/mixins.py | bornhack/bornhack-website | train | 9 |
46aa752faeaf6715f7310e1134068c8bb0897a25 | [
"super(LSTM, self).__init__()\nself.input_dim = input_dim\nself.hidden_dim = hidden_dim\nself.num_layers = num_layers\nself.learning_rate = learning_rate\nself.num_epochs = num_epochs\nself.lstm = nn.LSTM(self.input_dim, self.hidden_dim, self.num_layers, batch_first=True)\nself.linear = nn.Linear(self.hidden_dim, o... | <|body_start_0|>
super(LSTM, self).__init__()
self.input_dim = input_dim
self.hidden_dim = hidden_dim
self.num_layers = num_layers
self.learning_rate = learning_rate
self.num_epochs = num_epochs
self.lstm = nn.LSTM(self.input_dim, self.hidden_dim, self.num_layers,... | Class for LSTM | LSTM | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSTM:
"""Class for LSTM"""
def __init__(self, input_dim, output_dim=1, hidden_dim=10, num_layers=2, learning_rate=0.001, num_epochs=100):
"""Initilize LSTM model Args: input_dim: int -- dimension of expected features in input X output_dim: int -- dimension of the output feature, for ... | stack_v2_sparse_classes_10k_train_002795 | 3,540 | no_license | [
{
"docstring": "Initilize LSTM model Args: input_dim: int -- dimension of expected features in input X output_dim: int -- dimension of the output feature, for regrssion problem, the output_dim = 1 hidden_dim: int -- number of hidden units for LSTM num_layers: int -- number of stacked recurrent layers. num_epoch... | 4 | stack_v2_sparse_classes_30k_train_001664 | Implement the Python class `LSTM` described below.
Class description:
Class for LSTM
Method signatures and docstrings:
- def __init__(self, input_dim, output_dim=1, hidden_dim=10, num_layers=2, learning_rate=0.001, num_epochs=100): Initilize LSTM model Args: input_dim: int -- dimension of expected features in input X... | Implement the Python class `LSTM` described below.
Class description:
Class for LSTM
Method signatures and docstrings:
- def __init__(self, input_dim, output_dim=1, hidden_dim=10, num_layers=2, learning_rate=0.001, num_epochs=100): Initilize LSTM model Args: input_dim: int -- dimension of expected features in input X... | d7e651024b07587b46497183d90934561a4839e2 | <|skeleton|>
class LSTM:
"""Class for LSTM"""
def __init__(self, input_dim, output_dim=1, hidden_dim=10, num_layers=2, learning_rate=0.001, num_epochs=100):
"""Initilize LSTM model Args: input_dim: int -- dimension of expected features in input X output_dim: int -- dimension of the output feature, for ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LSTM:
"""Class for LSTM"""
def __init__(self, input_dim, output_dim=1, hidden_dim=10, num_layers=2, learning_rate=0.001, num_epochs=100):
"""Initilize LSTM model Args: input_dim: int -- dimension of expected features in input X output_dim: int -- dimension of the output feature, for regrssion pro... | the_stack_v2_python_sparse | model/recnet.py | SSF-climate/SSF | train | 7 |
269fe995e823f8a01f6c561d2b476b449a47f3e6 | [
"if ip_version not in (u'ip4', u'ip6'):\n raise ValueError(u'IP version is not in correct format')\ncmd = u'adl_allowlist_enable_disable'\nerr_msg = f\"Failed to add ADL allowlist on interface {interface} on host {node[u'host']}\"\nargs = dict(sw_if_index=Topology.get_interface_sw_index(node, interface), fib_id=... | <|body_start_0|>
if ip_version not in (u'ip4', u'ip6'):
raise ValueError(u'IP version is not in correct format')
cmd = u'adl_allowlist_enable_disable'
err_msg = f"Failed to add ADL allowlist on interface {interface} on host {node[u'host']}"
args = dict(sw_if_index=Topology.ge... | ADL utilities. | Adl | [
"GPL-1.0-or-later",
"CC-BY-4.0",
"Apache-2.0",
"LicenseRef-scancode-dco-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Adl:
"""ADL utilities."""
def adl_add_allowlist_entry(node, interface, ip_version, fib_id, default_adl=0):
"""Add adl allowlisted entry. :param node: Node to add ADL allowlist on. :param interface: Interface of the node where the ADL is added. :param ip_version: IP version. 'ip4' and... | stack_v2_sparse_classes_10k_train_002796 | 3,282 | permissive | [
{
"docstring": "Add adl allowlisted entry. :param node: Node to add ADL allowlist on. :param interface: Interface of the node where the ADL is added. :param ip_version: IP version. 'ip4' and 'ip6' are valid values. :param fib_id: Specify the fib table ID. :param default_adl: 1 => enable non-ip4, non-ip6 filtrat... | 2 | stack_v2_sparse_classes_30k_train_002893 | Implement the Python class `Adl` described below.
Class description:
ADL utilities.
Method signatures and docstrings:
- def adl_add_allowlist_entry(node, interface, ip_version, fib_id, default_adl=0): Add adl allowlisted entry. :param node: Node to add ADL allowlist on. :param interface: Interface of the node where t... | Implement the Python class `Adl` described below.
Class description:
ADL utilities.
Method signatures and docstrings:
- def adl_add_allowlist_entry(node, interface, ip_version, fib_id, default_adl=0): Add adl allowlisted entry. :param node: Node to add ADL allowlist on. :param interface: Interface of the node where t... | 947057d7310cd1602119258c6b82fbb25fe1b79d | <|skeleton|>
class Adl:
"""ADL utilities."""
def adl_add_allowlist_entry(node, interface, ip_version, fib_id, default_adl=0):
"""Add adl allowlisted entry. :param node: Node to add ADL allowlist on. :param interface: Interface of the node where the ADL is added. :param ip_version: IP version. 'ip4' and... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Adl:
"""ADL utilities."""
def adl_add_allowlist_entry(node, interface, ip_version, fib_id, default_adl=0):
"""Add adl allowlisted entry. :param node: Node to add ADL allowlist on. :param interface: Interface of the node where the ADL is added. :param ip_version: IP version. 'ip4' and 'ip6' are va... | the_stack_v2_python_sparse | resources/libraries/python/Adl.py | FDio/csit | train | 28 |
f4bc479ce6564f62a032c892a5f4afbfa832db78 | [
"self.host = host\nself.header = header\nself.postSite = requests.session()\nself.rf = ManageConfig().getConfig('pds')",
"try:\n if r.status_code == 302 and self.rf['pds'] in r.headers['location']:\n header = json.loads(self.header)\n header['cookie'] = self.rf['pdscookie']\n self.postSite... | <|body_start_0|>
self.host = host
self.header = header
self.postSite = requests.session()
self.rf = ManageConfig().getConfig('pds')
<|end_body_0|>
<|body_start_1|>
try:
if r.status_code == 302 and self.rf['pds'] in r.headers['location']:
header = json... | 发送请求类 | sendRequest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sendRequest:
"""发送请求类"""
def __init__(self, host, header):
"""请求数据初始化 @host：请求的地址前缀 @header：请求头信息"""
<|body_0|>
def hooks(self, r, *args, **kwargs):
"""为解决302跨域跳转到pds时，不传cookie实现的钩子方法，人为指定cookie并去请求302跳转连接 :param r: 原始请求的响应信息 :param args: :param kwargs: :return: ... | stack_v2_sparse_classes_10k_train_002797 | 2,867 | no_license | [
{
"docstring": "请求数据初始化 @host：请求的地址前缀 @header：请求头信息",
"name": "__init__",
"signature": "def __init__(self, host, header)"
},
{
"docstring": "为解决302跨域跳转到pds时，不传cookie实现的钩子方法，人为指定cookie并去请求302跳转连接 :param r: 原始请求的响应信息 :param args: :param kwargs: :return: and \"Set-Cookie\" in r.headers.keys()",
... | 3 | stack_v2_sparse_classes_30k_train_005516 | Implement the Python class `sendRequest` described below.
Class description:
发送请求类
Method signatures and docstrings:
- def __init__(self, host, header): 请求数据初始化 @host：请求的地址前缀 @header：请求头信息
- def hooks(self, r, *args, **kwargs): 为解决302跨域跳转到pds时，不传cookie实现的钩子方法，人为指定cookie并去请求302跳转连接 :param r: 原始请求的响应信息 :param args: :pa... | Implement the Python class `sendRequest` described below.
Class description:
发送请求类
Method signatures and docstrings:
- def __init__(self, host, header): 请求数据初始化 @host：请求的地址前缀 @header：请求头信息
- def hooks(self, r, *args, **kwargs): 为解决302跨域跳转到pds时，不传cookie实现的钩子方法，人为指定cookie并去请求302跳转连接 :param r: 原始请求的响应信息 :param args: :pa... | c3af12063eea585afbfb97d1ef933a41f110c919 | <|skeleton|>
class sendRequest:
"""发送请求类"""
def __init__(self, host, header):
"""请求数据初始化 @host：请求的地址前缀 @header：请求头信息"""
<|body_0|>
def hooks(self, r, *args, **kwargs):
"""为解决302跨域跳转到pds时，不传cookie实现的钩子方法，人为指定cookie并去请求302跳转连接 :param r: 原始请求的响应信息 :param args: :param kwargs: :return: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class sendRequest:
"""发送请求类"""
def __init__(self, host, header):
"""请求数据初始化 @host：请求的地址前缀 @header：请求头信息"""
self.host = host
self.header = header
self.postSite = requests.session()
self.rf = ManageConfig().getConfig('pds')
def hooks(self, r, *args, **kwargs):
... | the_stack_v2_python_sparse | Webservice/BaseAutomationTestFramework_HB/util/HttpMethod.py | Simonluepang/Upgrading-is-the-happiest-thing | train | 1 |
6925179f89cbc157740e9df21a43e6a9d4bc5539 | [
"allure.dynamic.title('Testing invite_more_women function (positive)')\nallure.dynamic.severity(allure.severity_level.NORMAL)\nallure.dynamic.description_html('<h3>Codewars badge:</h3><img src=\"https://www.codewars.com/users/myFirstCode/badges/large\"><h3>Test Description:</h3><p></p>')\nwith allure.step('Enter te... | <|body_start_0|>
allure.dynamic.title('Testing invite_more_women function (positive)')
allure.dynamic.severity(allure.severity_level.NORMAL)
allure.dynamic.description_html('<h3>Codewars badge:</h3><img src="https://www.codewars.com/users/myFirstCode/badges/large"><h3>Test Description:</h3><p></... | Simple Fun #152: Invite More Women? Testing invite_more_women function | InviteMoreWomenTestCase | [
"Unlicense",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InviteMoreWomenTestCase:
"""Simple Fun #152: Invite More Women? Testing invite_more_women function"""
def test_invite_more_women_positive(self):
"""Simple Fun #152: Invite More Women? Testing invite_more_women function (positive) :return:"""
<|body_0|>
def test_invite_mo... | stack_v2_sparse_classes_10k_train_002798 | 2,818 | permissive | [
{
"docstring": "Simple Fun #152: Invite More Women? Testing invite_more_women function (positive) :return:",
"name": "test_invite_more_women_positive",
"signature": "def test_invite_more_women_positive(self)"
},
{
"docstring": "Simple Fun #152: Invite More Women? Testing invite_more_women functi... | 2 | null | Implement the Python class `InviteMoreWomenTestCase` described below.
Class description:
Simple Fun #152: Invite More Women? Testing invite_more_women function
Method signatures and docstrings:
- def test_invite_more_women_positive(self): Simple Fun #152: Invite More Women? Testing invite_more_women function (positiv... | Implement the Python class `InviteMoreWomenTestCase` described below.
Class description:
Simple Fun #152: Invite More Women? Testing invite_more_women function
Method signatures and docstrings:
- def test_invite_more_women_positive(self): Simple Fun #152: Invite More Women? Testing invite_more_women function (positiv... | ba3ea81125b6082d867f0ae34c6c9be15e153966 | <|skeleton|>
class InviteMoreWomenTestCase:
"""Simple Fun #152: Invite More Women? Testing invite_more_women function"""
def test_invite_more_women_positive(self):
"""Simple Fun #152: Invite More Women? Testing invite_more_women function (positive) :return:"""
<|body_0|>
def test_invite_mo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InviteMoreWomenTestCase:
"""Simple Fun #152: Invite More Women? Testing invite_more_women function"""
def test_invite_more_women_positive(self):
"""Simple Fun #152: Invite More Women? Testing invite_more_women function (positive) :return:"""
allure.dynamic.title('Testing invite_more_women... | the_stack_v2_python_sparse | kyu_7/simple_fun_152/test_invite_more_women.py | qamine-test/codewars | train | 0 |
9a271f9b08b3c1b6fd0d99f87872cbeb78d93115 | [
"if db_field.name == 'user':\n kwargs['queryset'] = User.objects.filter(id=request.user.id)\n kwargs['initial'] = request.user.id\nelif db_field.name == 'topic' and (not request.user.is_superuser):\n kwargs['queryset'] = Topic.objects.filter(id__in=request.user.profile.topics.all())\nreturn super(TaskAdmin... | <|body_start_0|>
if db_field.name == 'user':
kwargs['queryset'] = User.objects.filter(id=request.user.id)
kwargs['initial'] = request.user.id
elif db_field.name == 'topic' and (not request.user.is_superuser):
kwargs['queryset'] = Topic.objects.filter(id__in=request.us... | TaskAdmin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""Assigns default value for User field. limits Topics field to user's topics."""
<|body_0|>
def formfield_for_manytomany(self, db_field, request, **kwargs):
"""Limits the choices of professo... | stack_v2_sparse_classes_10k_train_002799 | 9,167 | permissive | [
{
"docstring": "Assigns default value for User field. limits Topics field to user's topics.",
"name": "formfield_for_foreignkey",
"signature": "def formfield_for_foreignkey(self, db_field, request, **kwargs)"
},
{
"docstring": "Limits the choices of professors for the limit of user.",
"name"... | 3 | stack_v2_sparse_classes_30k_train_004323 | Implement the Python class `TaskAdmin` described below.
Class description:
Implement the TaskAdmin class.
Method signatures and docstrings:
- def formfield_for_foreignkey(self, db_field, request, **kwargs): Assigns default value for User field. limits Topics field to user's topics.
- def formfield_for_manytomany(self... | Implement the Python class `TaskAdmin` described below.
Class description:
Implement the TaskAdmin class.
Method signatures and docstrings:
- def formfield_for_foreignkey(self, db_field, request, **kwargs): Assigns default value for User field. limits Topics field to user's topics.
- def formfield_for_manytomany(self... | 70638c121ea85ff0e6a650c5f2641b0b3b04d6d0 | <|skeleton|>
class TaskAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""Assigns default value for User field. limits Topics field to user's topics."""
<|body_0|>
def formfield_for_manytomany(self, db_field, request, **kwargs):
"""Limits the choices of professo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TaskAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""Assigns default value for User field. limits Topics field to user's topics."""
if db_field.name == 'user':
kwargs['queryset'] = User.objects.filter(id=request.user.id)
kwargs['initial'] = req... | the_stack_v2_python_sparse | cms/admin.py | Ibrahem3amer/bala7 | train | 0 |
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