blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 467 8.64k | id stringlengths 40 40 | length_bytes int64 515 49.7k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
63f19762c3cd44d05cd3dc51f3cb193ce3e5d93b | [
"routing_table_file = open(routing_table_file_name, 'rb')\nrouting_table = pickle.load(routing_table_file)\nrouting_table_file.close()\nreturn routing_table",
"pickle_file_name = 'picked_routing_table_for_{}_{}'.format(routing_table.x, routing_table.y)\npickle_file_path = os.path.join(binary_directory, pickle_fil... | <|body_start_0|>
routing_table_file = open(routing_table_file_name, 'rb')
routing_table = pickle.load(routing_table_file)
routing_table_file.close()
return routing_table
<|end_body_0|>
<|body_start_1|>
pickle_file_name = 'picked_routing_table_for_{}_{}'.format(routing_table.x, r... | A routing table to be reloaded | ReloadRoutingTable | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReloadRoutingTable:
"""A routing table to be reloaded"""
def reload(routing_table_file_name):
"""Reload a routing table via a pickled filename :param routing_table_file_name: the file name for the pickled routeing table :return: None"""
<|body_0|>
def store(binary_direct... | stack_v2_sparse_classes_10k_train_008900 | 1,109 | permissive | [
{
"docstring": "Reload a routing table via a pickled filename :param routing_table_file_name: the file name for the pickled routeing table :return: None",
"name": "reload",
"signature": "def reload(routing_table_file_name)"
},
{
"docstring": "Store a routing table in pickled form :param binary_d... | 2 | null | Implement the Python class `ReloadRoutingTable` described below.
Class description:
A routing table to be reloaded
Method signatures and docstrings:
- def reload(routing_table_file_name): Reload a routing table via a pickled filename :param routing_table_file_name: the file name for the pickled routeing table :return... | Implement the Python class `ReloadRoutingTable` described below.
Class description:
A routing table to be reloaded
Method signatures and docstrings:
- def reload(routing_table_file_name): Reload a routing table via a pickled filename :param routing_table_file_name: the file name for the pickled routeing table :return... | 04fa1eaf78778edea3ba3afa4c527d20c491718e | <|skeleton|>
class ReloadRoutingTable:
"""A routing table to be reloaded"""
def reload(routing_table_file_name):
"""Reload a routing table via a pickled filename :param routing_table_file_name: the file name for the pickled routeing table :return: None"""
<|body_0|>
def store(binary_direct... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ReloadRoutingTable:
"""A routing table to be reloaded"""
def reload(routing_table_file_name):
"""Reload a routing table via a pickled filename :param routing_table_file_name: the file name for the pickled routeing table :return: None"""
routing_table_file = open(routing_table_file_name, '... | the_stack_v2_python_sparse | src/spinnaker_ros_lsm/venv/lib/python2.7/site-packages/spinn_front_end_common/utilities/reload/reload_routing_table.py | Roboy/LSM_SpiNNaker_MyoArm | train | 2 |
b41b20b5d28d32c03f874c5d84ddb780236ed369 | [
"self.user_pin = user_pin\nself.user_name = user_name\nself.user_pwd = user_pwd\nself.bad_chars = '0123456789!\"@#$%^&*()_=+,<>/?;:[]{}\\\\)'\nself.bad_pwd_chars = '!\"@#$%^&*()_=+,<>/?;:[]{}\\\\)'",
"if self.user_pin:\n if self.user_pin.isnumeric():\n if len(self.user_pin) <= max_length:\n r... | <|body_start_0|>
self.user_pin = user_pin
self.user_name = user_name
self.user_pwd = user_pwd
self.bad_chars = '0123456789!"@#$%^&*()_=+,<>/?;:[]{}\\)'
self.bad_pwd_chars = '!"@#$%^&*()_=+,<>/?;:[]{}\\)'
<|end_body_0|>
<|body_start_1|>
if self.user_pin:
if se... | A class representation of user input validation. Inherits attributes of the Person class. Methods: Constructor: < __init__() > < ID_check > < Name_Checker > All attributes of the class has default value of empty string. | Validator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Validator:
"""A class representation of user input validation. Inherits attributes of the Person class. Methods: Constructor: < __init__() > < ID_check > < Name_Checker > All attributes of the class has default value of empty string."""
def __init__(self, user_pin='', user_name='', user_pwd=... | stack_v2_sparse_classes_10k_train_008901 | 4,203 | no_license | [
{
"docstring": "Initialising attributes for Validator class",
"name": "__init__",
"signature": "def __init__(self, user_pin='', user_name='', user_pwd='')"
},
{
"docstring": "Description: Method checks user ID for maximum length and returns <user ID> . Method returns in event of bad character in... | 4 | stack_v2_sparse_classes_30k_train_007109 | Implement the Python class `Validator` described below.
Class description:
A class representation of user input validation. Inherits attributes of the Person class. Methods: Constructor: < __init__() > < ID_check > < Name_Checker > All attributes of the class has default value of empty string.
Method signatures and d... | Implement the Python class `Validator` described below.
Class description:
A class representation of user input validation. Inherits attributes of the Person class. Methods: Constructor: < __init__() > < ID_check > < Name_Checker > All attributes of the class has default value of empty string.
Method signatures and d... | b4c2072cf51e4ee8523e77a6850f5418b936ceb0 | <|skeleton|>
class Validator:
"""A class representation of user input validation. Inherits attributes of the Person class. Methods: Constructor: < __init__() > < ID_check > < Name_Checker > All attributes of the class has default value of empty string."""
def __init__(self, user_pin='', user_name='', user_pwd=... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Validator:
"""A class representation of user input validation. Inherits attributes of the Person class. Methods: Constructor: < __init__() > < ID_check > < Name_Checker > All attributes of the class has default value of empty string."""
def __init__(self, user_pin='', user_name='', user_pwd=''):
... | the_stack_v2_python_sparse | user.py | Johnnyhashtag/my_work | train | 0 |
2eb340c30d5cd2e26a29c62a11c79a58f7a68bce | [
"request = RequestFactory().get('/')\ncontext = {'request': request}\ncommon_bundle = (chunk for chunk in FAKE_COMMON_BUNDLE)\nget_bundle = Mock(return_value=common_bundle)\nloader = Mock(get_bundle=get_bundle)\nbundle_name = 'bundle_name'\nwith patch('ui.templatetags.render_bundle.get_loader', return_value=loader)... | <|body_start_0|>
request = RequestFactory().get('/')
context = {'request': request}
common_bundle = (chunk for chunk in FAKE_COMMON_BUNDLE)
get_bundle = Mock(return_value=common_bundle)
loader = Mock(get_bundle=get_bundle)
bundle_name = 'bundle_name'
with patch('u... | Tests for render_bundle | TestRenderBundle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestRenderBundle:
"""Tests for render_bundle"""
def test_debug(self):
"""If USE_WEBPACK_DEV_SERVER=True, return a hot reload URL"""
<|body_0|>
def test_production(self):
"""If USE_WEBPACK_DEV_SERVER=False, return a static URL for production"""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_008902 | 3,850 | permissive | [
{
"docstring": "If USE_WEBPACK_DEV_SERVER=True, return a hot reload URL",
"name": "test_debug",
"signature": "def test_debug(self)"
},
{
"docstring": "If USE_WEBPACK_DEV_SERVER=False, return a static URL for production",
"name": "test_production",
"signature": "def test_production(self)"... | 3 | null | Implement the Python class `TestRenderBundle` described below.
Class description:
Tests for render_bundle
Method signatures and docstrings:
- def test_debug(self): If USE_WEBPACK_DEV_SERVER=True, return a hot reload URL
- def test_production(self): If USE_WEBPACK_DEV_SERVER=False, return a static URL for production
-... | Implement the Python class `TestRenderBundle` described below.
Class description:
Tests for render_bundle
Method signatures and docstrings:
- def test_debug(self): If USE_WEBPACK_DEV_SERVER=True, return a hot reload URL
- def test_production(self): If USE_WEBPACK_DEV_SERVER=False, return a static URL for production
-... | d6564caca0b7bbfd31e67a751564107fd17d6eb0 | <|skeleton|>
class TestRenderBundle:
"""Tests for render_bundle"""
def test_debug(self):
"""If USE_WEBPACK_DEV_SERVER=True, return a hot reload URL"""
<|body_0|>
def test_production(self):
"""If USE_WEBPACK_DEV_SERVER=False, return a static URL for production"""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestRenderBundle:
"""Tests for render_bundle"""
def test_debug(self):
"""If USE_WEBPACK_DEV_SERVER=True, return a hot reload URL"""
request = RequestFactory().get('/')
context = {'request': request}
common_bundle = (chunk for chunk in FAKE_COMMON_BUNDLE)
get_bundle... | the_stack_v2_python_sparse | ui/templatetags/render_bundle_test.py | mitodl/micromasters | train | 35 |
67d551dcccde1f32407da6b9c68f8c84f7448b1f | [
"self.id = id\nself.title = title\nself.device_group = device_group\nself.device_type_id = device_type_id\nself.device_brand_id = device_brand_id\nself.create_on = create_on\nself.update_on = update_on\nself.created_by = created_by\nself.updated_by = updated_by\nself.create_on_persian_date = create_on_persian_date\... | <|body_start_0|>
self.id = id
self.title = title
self.device_group = device_group
self.device_type_id = device_type_id
self.device_brand_id = device_brand_id
self.create_on = create_on
self.update_on = update_on
self.created_by = created_by
self.up... | Implementation of the 'DeviceBrandTypes' model. TODO: type model description here. Attributes: id (int): TODO: type description here. title (string): TODO: type description here. device_group (int): TODO: type description here. device_type_id (int): TODO: type description here. device_brand_id (string): TODO: type desc... | DeviceBrandTypes | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceBrandTypes:
"""Implementation of the 'DeviceBrandTypes' model. TODO: type model description here. Attributes: id (int): TODO: type description here. title (string): TODO: type description here. device_group (int): TODO: type description here. device_type_id (int): TODO: type description her... | stack_v2_sparse_classes_10k_train_008903 | 5,769 | permissive | [
{
"docstring": "Constructor for the DeviceBrandTypes class",
"name": "__init__",
"signature": "def __init__(self, id=None, title=None, device_group=None, create_on=None, update_on=None, created_by=None, create_on_persian_date=None, update_on_persian_date=None, device_type_brand_model_title=None, device_... | 2 | stack_v2_sparse_classes_30k_train_001354 | Implement the Python class `DeviceBrandTypes` described below.
Class description:
Implementation of the 'DeviceBrandTypes' model. TODO: type model description here. Attributes: id (int): TODO: type description here. title (string): TODO: type description here. device_group (int): TODO: type description here. device_ty... | Implement the Python class `DeviceBrandTypes` described below.
Class description:
Implementation of the 'DeviceBrandTypes' model. TODO: type model description here. Attributes: id (int): TODO: type description here. title (string): TODO: type description here. device_group (int): TODO: type description here. device_ty... | b574a76a8805b306a423229b572c36dae0159def | <|skeleton|>
class DeviceBrandTypes:
"""Implementation of the 'DeviceBrandTypes' model. TODO: type model description here. Attributes: id (int): TODO: type description here. title (string): TODO: type description here. device_group (int): TODO: type description here. device_type_id (int): TODO: type description her... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DeviceBrandTypes:
"""Implementation of the 'DeviceBrandTypes' model. TODO: type model description here. Attributes: id (int): TODO: type description here. title (string): TODO: type description here. device_group (int): TODO: type description here. device_type_id (int): TODO: type description here. device_bra... | the_stack_v2_python_sparse | easybimehlanding/models/device_brand_types.py | kmelodi/EasyBimehLanding_Python | train | 0 |
44c41be0793e1e44975f1ce6da060a775979e655 | [
"self.group = game.all_sprites\npygame.sprite.Sprite.__init__(self)\nself.layer = 0\nself.group.add(self, layer=self.layer)\nself.game = game\nself.timer = 0\nself.frame = 0\nself.images = images\nself.image = self.images[0]\nself.rect = self.image.get_rect()\nself.rect.center = pos\nself.game = game\nself.pos = po... | <|body_start_0|>
self.group = game.all_sprites
pygame.sprite.Sprite.__init__(self)
self.layer = 0
self.group.add(self, layer=self.layer)
self.game = game
self.timer = 0
self.frame = 0
self.images = images
self.image = self.images[0]
self.re... | This class is base class for effects. Animation is played from images list and destroyed itself. | Effect | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Effect:
"""This class is base class for effects. Animation is played from images list and destroyed itself."""
def __init__(self, game, pos, images, delay):
"""__init__ method for Explosion class Args: game (<class 'Integrate.Game'>): Integrate.Game class object. pos (tuple length 2)... | stack_v2_sparse_classes_10k_train_008904 | 1,620 | no_license | [
{
"docstring": "__init__ method for Explosion class Args: game (<class 'Integrate.Game'>): Integrate.Game class object. pos (tuple length 2): position of the player (x,y). images (<list>): image list from sprites. delay (int): delay between animation images",
"name": "__init__",
"signature": "def __init... | 2 | stack_v2_sparse_classes_30k_train_002807 | Implement the Python class `Effect` described below.
Class description:
This class is base class for effects. Animation is played from images list and destroyed itself.
Method signatures and docstrings:
- def __init__(self, game, pos, images, delay): __init__ method for Explosion class Args: game (<class 'Integrate.G... | Implement the Python class `Effect` described below.
Class description:
This class is base class for effects. Animation is played from images list and destroyed itself.
Method signatures and docstrings:
- def __init__(self, game, pos, images, delay): __init__ method for Explosion class Args: game (<class 'Integrate.G... | 74524cd52988c4c3f720150a418ff283a8d05683 | <|skeleton|>
class Effect:
"""This class is base class for effects. Animation is played from images list and destroyed itself."""
def __init__(self, game, pos, images, delay):
"""__init__ method for Explosion class Args: game (<class 'Integrate.Game'>): Integrate.Game class object. pos (tuple length 2)... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Effect:
"""This class is base class for effects. Animation is played from images list and destroyed itself."""
def __init__(self, game, pos, images, delay):
"""__init__ method for Explosion class Args: game (<class 'Integrate.Game'>): Integrate.Game class object. pos (tuple length 2): position of... | the_stack_v2_python_sparse | effects/Effect.py | ImpulseLimited/momentus-proto | train | 0 |
3e97a639e14dd96e69151acf2c663d770df2d5a2 | [
"filters = {}\nif hasattr(request, 'GET'):\n filters = request.GET.copy()\nfilters.update(kwargs)\ntry:\n user = UserProfile.objects.filter(uuid=uuid_from_uri(filters['user']))\n sub_pk = sorted(chain(user[0].subscriptions(), user))\n im = Image.objects.filter(is_active=True, owner__in=sub_pk)\n wb =... | <|body_start_0|>
filters = {}
if hasattr(request, 'GET'):
filters = request.GET.copy()
filters.update(kwargs)
try:
user = UserProfile.objects.filter(uuid=uuid_from_uri(filters['user']))
sub_pk = sorted(chain(user[0].subscriptions(), user))
... | NewsfeedResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewsfeedResource:
def obj_get_list(self, request=None, **kwargs):
"""A ORM-specific implementation of ``obj_get_list``. Takes an optional ``request`` object, whose ``GET`` dictionary can be used to narrow the query."""
<|body_0|>
def full_dehydrate(self, bundle):
"""... | stack_v2_sparse_classes_10k_train_008905 | 19,893 | no_license | [
{
"docstring": "A ORM-specific implementation of ``obj_get_list``. Takes an optional ``request`` object, whose ``GET`` dictionary can be used to narrow the query.",
"name": "obj_get_list",
"signature": "def obj_get_list(self, request=None, **kwargs)"
},
{
"docstring": "Given a bundle with an obj... | 2 | stack_v2_sparse_classes_30k_train_000154 | Implement the Python class `NewsfeedResource` described below.
Class description:
Implement the NewsfeedResource class.
Method signatures and docstrings:
- def obj_get_list(self, request=None, **kwargs): A ORM-specific implementation of ``obj_get_list``. Takes an optional ``request`` object, whose ``GET`` dictionary ... | Implement the Python class `NewsfeedResource` described below.
Class description:
Implement the NewsfeedResource class.
Method signatures and docstrings:
- def obj_get_list(self, request=None, **kwargs): A ORM-specific implementation of ``obj_get_list``. Takes an optional ``request`` object, whose ``GET`` dictionary ... | 698e027b7f6f4db5c2e9b9a899ba74f4ad4daf8e | <|skeleton|>
class NewsfeedResource:
def obj_get_list(self, request=None, **kwargs):
"""A ORM-specific implementation of ``obj_get_list``. Takes an optional ``request`` object, whose ``GET`` dictionary can be used to narrow the query."""
<|body_0|>
def full_dehydrate(self, bundle):
"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NewsfeedResource:
def obj_get_list(self, request=None, **kwargs):
"""A ORM-specific implementation of ``obj_get_list``. Takes an optional ``request`` object, whose ``GET`` dictionary can be used to narrow the query."""
filters = {}
if hasattr(request, 'GET'):
filters = requ... | the_stack_v2_python_sparse | back-end/website/api/v1/action_resources.py | dchang00/keekaa-back-end | train | 0 | |
1d4bf16cede0f8688702ef4f98dc7ea51d318dc6 | [
"if root is None:\n return 0\nleft_height = self.maxDepth(root.left)\nright_height = self.maxDepth(root.right)\nreturn max(left_height, right_height) + 1",
"stack = []\nif root is not None:\n stack.append((1, root))\ndepth = 0\nwhile stack != []:\n current_depth, root = stack.pop()\n if root is not No... | <|body_start_0|>
if root is None:
return 0
left_height = self.maxDepth(root.left)
right_height = self.maxDepth(root.right)
return max(left_height, right_height) + 1
<|end_body_0|>
<|body_start_1|>
stack = []
if root is not None:
stack.append((1, r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxDepth(self, root: TreeNode) -> int:
"""递归实现 DFS"""
<|body_0|>
def maxDepth2(self, root: TreeNode) -> int:
"""栈实现 DFS 76 ms 14.9 MB"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is None:
return 0
left_he... | stack_v2_sparse_classes_10k_train_008906 | 1,790 | no_license | [
{
"docstring": "递归实现 DFS",
"name": "maxDepth",
"signature": "def maxDepth(self, root: TreeNode) -> int"
},
{
"docstring": "栈实现 DFS 76 ms 14.9 MB",
"name": "maxDepth2",
"signature": "def maxDepth2(self, root: TreeNode) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root: TreeNode) -> int: 递归实现 DFS
- def maxDepth2(self, root: TreeNode) -> int: 栈实现 DFS 76 ms 14.9 MB | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root: TreeNode) -> int: 递归实现 DFS
- def maxDepth2(self, root: TreeNode) -> int: 栈实现 DFS 76 ms 14.9 MB
<|skeleton|>
class Solution:
def maxDepth(self, root... | 40726506802d2d60028fdce206696b1df2f63ece | <|skeleton|>
class Solution:
def maxDepth(self, root: TreeNode) -> int:
"""递归实现 DFS"""
<|body_0|>
def maxDepth2(self, root: TreeNode) -> int:
"""栈实现 DFS 76 ms 14.9 MB"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxDepth(self, root: TreeNode) -> int:
"""递归实现 DFS"""
if root is None:
return 0
left_height = self.maxDepth(root.left)
right_height = self.maxDepth(root.right)
return max(left_height, right_height) + 1
def maxDepth2(self, root: TreeNode) -... | the_stack_v2_python_sparse | 算法/maxDepth.py | 1oser5/LeetCode | train | 0 | |
e538e26a3316f7b60fd55e220443cb05870a4bb3 | [
"if not s:\n return ''\nif len(s) == 1:\n return s\nret = ''\nfor i in range(len(s)):\n l = r = i\n while r < len(s) and s[l] == s[r]:\n r += 1\n if len(ret) < r - l:\n ret = s[l:r]\n l -= 1\n while l >= 0 and r < len(s) and (s[l] == s[r]):\n l -= 1\n r += 1\n if ... | <|body_start_0|>
if not s:
return ''
if len(s) == 1:
return s
ret = ''
for i in range(len(s)):
l = r = i
while r < len(s) and s[l] == s[r]:
r += 1
if len(ret) < r - l:
ret = s[l:r]
l -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
"""Time complexity:O(N*N) Spave complexity:O(N) 验证通过,性能不错 Runtime: 728 ms, faster than 91.18% of Python3 online submissions for Longest Palindromic Substring. Memory Usage: 14.1 MB, less than 76.49% of Python3 online submissions for Longest Palin... | stack_v2_sparse_classes_10k_train_008907 | 3,775 | no_license | [
{
"docstring": "Time complexity:O(N*N) Spave complexity:O(N) 验证通过,性能不错 Runtime: 728 ms, faster than 91.18% of Python3 online submissions for Longest Palindromic Substring. Memory Usage: 14.1 MB, less than 76.49% of Python3 online submissions for Longest Palindromic Substring. :param s: :return:",
"name": "l... | 2 | stack_v2_sparse_classes_30k_test_000014 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): Time complexity:O(N*N) Spave complexity:O(N) 验证通过,性能不错 Runtime: 728 ms, faster than 91.18% of Python3 online submissions for Longest Palindromic S... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): Time complexity:O(N*N) Spave complexity:O(N) 验证通过,性能不错 Runtime: 728 ms, faster than 91.18% of Python3 online submissions for Longest Palindromic S... | 6a7267b8b784283a760de7775089b936a0e97617 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
"""Time complexity:O(N*N) Spave complexity:O(N) 验证通过,性能不错 Runtime: 728 ms, faster than 91.18% of Python3 online submissions for Longest Palindromic Substring. Memory Usage: 14.1 MB, less than 76.49% of Python3 online submissions for Longest Palin... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def longestPalindrome(self, s):
"""Time complexity:O(N*N) Spave complexity:O(N) 验证通过,性能不错 Runtime: 728 ms, faster than 91.18% of Python3 online submissions for Longest Palindromic Substring. Memory Usage: 14.1 MB, less than 76.49% of Python3 online submissions for Longest Palindromic Substri... | the_stack_v2_python_sparse | leetcode/5_longest_palindromic_substring/longest_palindromic_substring.py | liuyanhui/leetcode-py | train | 0 | |
f29dd8f61f0491cf45bc566ff43f6a469032e233 | [
"ret = 'zz'\nfor letter in letters:\n if letter > target:\n ret = min(letter, ret)\nreturn ret if ret != 'zz' else min(letters)",
"for letter in letters:\n if letter > target:\n return letter\nreturn letters[0]",
"if target >= letters[-1]:\n return letters[0]\nstart = 0\nend = len(letters... | <|body_start_0|>
ret = 'zz'
for letter in letters:
if letter > target:
ret = min(letter, ret)
return ret if ret != 'zz' else min(letters)
<|end_body_0|>
<|body_start_1|>
for letter in letters:
if letter > target:
return letter
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextGreatestLetter1(self, letters, target):
""":type letters: List[str] :type target: str :rtype: str"""
<|body_0|>
def nextGreatestLetter2(self, letters, target):
""":type letters: List[str] :type target: str :rtype: str"""
<|body_1|>
def ... | stack_v2_sparse_classes_10k_train_008908 | 1,413 | no_license | [
{
"docstring": ":type letters: List[str] :type target: str :rtype: str",
"name": "nextGreatestLetter1",
"signature": "def nextGreatestLetter1(self, letters, target)"
},
{
"docstring": ":type letters: List[str] :type target: str :rtype: str",
"name": "nextGreatestLetter2",
"signature": "d... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreatestLetter1(self, letters, target): :type letters: List[str] :type target: str :rtype: str
- def nextGreatestLetter2(self, letters, target): :type letters: List[str] ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreatestLetter1(self, letters, target): :type letters: List[str] :type target: str :rtype: str
- def nextGreatestLetter2(self, letters, target): :type letters: List[str] ... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def nextGreatestLetter1(self, letters, target):
""":type letters: List[str] :type target: str :rtype: str"""
<|body_0|>
def nextGreatestLetter2(self, letters, target):
""":type letters: List[str] :type target: str :rtype: str"""
<|body_1|>
def ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def nextGreatestLetter1(self, letters, target):
""":type letters: List[str] :type target: str :rtype: str"""
ret = 'zz'
for letter in letters:
if letter > target:
ret = min(letter, ret)
return ret if ret != 'zz' else min(letters)
def n... | the_stack_v2_python_sparse | python/leetcode_bak/744_Find_Smallest_Letter_Greater_Than_Target.py | bobcaoge/my-code | train | 0 | |
54b64b8d644f496f7399d07a752379e19c2d1b28 | [
"self.s3_conn = s3_conn\nself.cache_dir = cache_dir\nself.s3_path = s3_path\nself.bucket_name, self.prefix = split_s3_path(self.s3_path)",
"full_path = os.path.join(self.cache_dir, filename)\nif os.path.isfile(full_path):\n yield full_path\nelse:\n if not os.path.isdir(self.cache_dir):\n os.mkdir(sel... | <|body_start_0|>
self.s3_conn = s3_conn
self.cache_dir = cache_dir
self.s3_path = s3_path
self.bucket_name, self.prefix = split_s3_path(self.s3_path)
<|end_body_0|>
<|body_start_1|>
full_path = os.path.join(self.cache_dir, filename)
if os.path.isfile(full_path):
... | An object that downloads and caches ONET files from S3 | OnetCache | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OnetCache:
"""An object that downloads and caches ONET files from S3"""
def __init__(self, s3_conn, s3_path, cache_dir):
"""Args: s3_conn: a boto s3 connection s3_path: path to the onet directory cache_dir: directory to cache files"""
<|body_0|>
def ensure_file(self, fil... | stack_v2_sparse_classes_10k_train_008909 | 2,489 | permissive | [
{
"docstring": "Args: s3_conn: a boto s3 connection s3_path: path to the onet directory cache_dir: directory to cache files",
"name": "__init__",
"signature": "def __init__(self, s3_conn, s3_path, cache_dir)"
},
{
"docstring": "Ensures that the given ONET data file is present, either by using a ... | 2 | stack_v2_sparse_classes_30k_train_006213 | Implement the Python class `OnetCache` described below.
Class description:
An object that downloads and caches ONET files from S3
Method signatures and docstrings:
- def __init__(self, s3_conn, s3_path, cache_dir): Args: s3_conn: a boto s3 connection s3_path: path to the onet directory cache_dir: directory to cache f... | Implement the Python class `OnetCache` described below.
Class description:
An object that downloads and caches ONET files from S3
Method signatures and docstrings:
- def __init__(self, s3_conn, s3_path, cache_dir): Args: s3_conn: a boto s3 connection s3_path: path to the onet directory cache_dir: directory to cache f... | feffead90815ccdecf24bf1a995f79683442b046 | <|skeleton|>
class OnetCache:
"""An object that downloads and caches ONET files from S3"""
def __init__(self, s3_conn, s3_path, cache_dir):
"""Args: s3_conn: a boto s3 connection s3_path: path to the onet directory cache_dir: directory to cache files"""
<|body_0|>
def ensure_file(self, fil... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OnetCache:
"""An object that downloads and caches ONET files from S3"""
def __init__(self, s3_conn, s3_path, cache_dir):
"""Args: s3_conn: a boto s3 connection s3_path: path to the onet directory cache_dir: directory to cache files"""
self.s3_conn = s3_conn
self.cache_dir = cache_... | the_stack_v2_python_sparse | skills_ml/datasets/onet_cache.py | workforce-data-initiative/skills-ml | train | 164 |
8d6a9f254f5f172d59c528d8e8f6dd584e13f435 | [
"tk.Tk.__init__(self)\nself.title('CPPN playground')\ncontainer = tk.Frame(self)\ncontainer.pack(side='top', fill='both', expand=True)\ncontainer.grid_rowconfigure(0, weight=1)\ncontainer.grid_columnconfigure(0, weight=1)\nmenubar = tk.Menu(self)\nfilemenu = tk.Menu(menubar)\nfilemenu.add_command(label='Main Page',... | <|body_start_0|>
tk.Tk.__init__(self)
self.title('CPPN playground')
container = tk.Frame(self)
container.pack(side='top', fill='both', expand=True)
container.grid_rowconfigure(0, weight=1)
container.grid_columnconfigure(0, weight=1)
menubar = tk.Menu(self)
... | Main class that contains all handlers for the Tkinter GUI | Playground | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Playground:
"""Main class that contains all handlers for the Tkinter GUI"""
def __init__(self, genotype):
"""Contructer for main GUI container/handler"""
<|body_0|>
def raise_frame(self, page_name, container):
"""Raise a certain frame to the front of the GUI base... | stack_v2_sparse_classes_10k_train_008910 | 11,786 | no_license | [
{
"docstring": "Contructer for main GUI container/handler",
"name": "__init__",
"signature": "def __init__(self, genotype)"
},
{
"docstring": "Raise a certain frame to the front of the GUI based on its page_name",
"name": "raise_frame",
"signature": "def raise_frame(self, page_name, cont... | 2 | stack_v2_sparse_classes_30k_train_006640 | Implement the Python class `Playground` described below.
Class description:
Main class that contains all handlers for the Tkinter GUI
Method signatures and docstrings:
- def __init__(self, genotype): Contructer for main GUI container/handler
- def raise_frame(self, page_name, container): Raise a certain frame to the ... | Implement the Python class `Playground` described below.
Class description:
Main class that contains all handlers for the Tkinter GUI
Method signatures and docstrings:
- def __init__(self, genotype): Contructer for main GUI container/handler
- def raise_frame(self, page_name, container): Raise a certain frame to the ... | 317b615e39df5999f2fd3d5e7dd0af7d54aee6c8 | <|skeleton|>
class Playground:
"""Main class that contains all handlers for the Tkinter GUI"""
def __init__(self, genotype):
"""Contructer for main GUI container/handler"""
<|body_0|>
def raise_frame(self, page_name, container):
"""Raise a certain frame to the front of the GUI base... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Playground:
"""Main class that contains all handlers for the Tkinter GUI"""
def __init__(self, genotype):
"""Contructer for main GUI container/handler"""
tk.Tk.__init__(self)
self.title('CPPN playground')
container = tk.Frame(self)
container.pack(side='top', fill='... | the_stack_v2_python_sparse | FULL_CPPN_playground.py | wolfecameron/CPPN_springopt | train | 4 |
62d6584c2b47f966c964d1875f06e83e47e3bdfa | [
"trie = Trie()\nfor p in products:\n trie.add(p)\nres = []\nprefix = ''\nfor c in searchWord:\n prefix += c\n l = trie.findAll(prefix)\n res.append(sorted(l)[:3])\nreturn res",
"products.sort()\nprefix = ''\nres = []\nfor c in searchWord:\n temp = []\n prefix += c\n i = bisect.bisect_left(pro... | <|body_start_0|>
trie = Trie()
for p in products:
trie.add(p)
res = []
prefix = ''
for c in searchWord:
prefix += c
l = trie.findAll(prefix)
res.append(sorted(l)[:3])
return res
<|end_body_0|>
<|body_start_1|>
produ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def suggestedProducts(self, products: List[str], searchWord: str) -> List[List[str]]:
"""Trie 구현."""
<|body_0|>
def suggestedProducts(self, products: List[str], searchWord: str) -> List[List[str]]:
"""sort 후 binary search."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_10k_train_008911 | 1,844 | no_license | [
{
"docstring": "Trie 구현.",
"name": "suggestedProducts",
"signature": "def suggestedProducts(self, products: List[str], searchWord: str) -> List[List[str]]"
},
{
"docstring": "sort 후 binary search.",
"name": "suggestedProducts",
"signature": "def suggestedProducts(self, products: List[str... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def suggestedProducts(self, products: List[str], searchWord: str) -> List[List[str]]: Trie 구현.
- def suggestedProducts(self, products: List[str], searchWord: str) -> List[List[st... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def suggestedProducts(self, products: List[str], searchWord: str) -> List[List[str]]: Trie 구현.
- def suggestedProducts(self, products: List[str], searchWord: str) -> List[List[st... | c26aef2a59e5cc2d9b0658b9c7386a43267ff8a1 | <|skeleton|>
class Solution:
def suggestedProducts(self, products: List[str], searchWord: str) -> List[List[str]]:
"""Trie 구현."""
<|body_0|>
def suggestedProducts(self, products: List[str], searchWord: str) -> List[List[str]]:
"""sort 후 binary search."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def suggestedProducts(self, products: List[str], searchWord: str) -> List[List[str]]:
"""Trie 구현."""
trie = Trie()
for p in products:
trie.add(p)
res = []
prefix = ''
for c in searchWord:
prefix += c
l = trie.findAll... | the_stack_v2_python_sparse | Leetcode/1268.py | hanwgyu/algorithm_problem_solving | train | 5 | |
edc81c749fb9780625a96a3f24be57a1a5028743 | [
"cm = {}\nwm = {}\nfor c, w in itertools.zip_longest(pattern, s.split()):\n if c is None or w is None or (c in cm and cm[c] != w) or (w in wm and wm[w] != c):\n return False\n cm[c] = w\n wm[w] = c\nreturn True",
"pw = {}\nwp = {}\nfor p, w in itertools.zip_longest(pattern, s.split()):\n if p i... | <|body_start_0|>
cm = {}
wm = {}
for c, w in itertools.zip_longest(pattern, s.split()):
if c is None or w is None or (c in cm and cm[c] != w) or (w in wm and wm[w] != c):
return False
cm[c] = w
wm[w] = c
return True
<|end_body_0|>
<|bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wordPattern(self, pattern: str, s: str) -> bool:
"""Jan 31, 2022 13:02"""
<|body_0|>
def wordPattern(self, pattern: str, s: str) -> bool:
"""Mar 04, 2023 20:08"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cm = {}
wm = {}
... | stack_v2_sparse_classes_10k_train_008912 | 2,226 | no_license | [
{
"docstring": "Jan 31, 2022 13:02",
"name": "wordPattern",
"signature": "def wordPattern(self, pattern: str, s: str) -> bool"
},
{
"docstring": "Mar 04, 2023 20:08",
"name": "wordPattern",
"signature": "def wordPattern(self, pattern: str, s: str) -> bool"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordPattern(self, pattern: str, s: str) -> bool: Jan 31, 2022 13:02
- def wordPattern(self, pattern: str, s: str) -> bool: Mar 04, 2023 20:08 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordPattern(self, pattern: str, s: str) -> bool: Jan 31, 2022 13:02
- def wordPattern(self, pattern: str, s: str) -> bool: Mar 04, 2023 20:08
<|skeleton|>
class Solution:
... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def wordPattern(self, pattern: str, s: str) -> bool:
"""Jan 31, 2022 13:02"""
<|body_0|>
def wordPattern(self, pattern: str, s: str) -> bool:
"""Mar 04, 2023 20:08"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def wordPattern(self, pattern: str, s: str) -> bool:
"""Jan 31, 2022 13:02"""
cm = {}
wm = {}
for c, w in itertools.zip_longest(pattern, s.split()):
if c is None or w is None or (c in cm and cm[c] != w) or (w in wm and wm[w] != c):
return F... | the_stack_v2_python_sparse | leetcode/solved/290_Word_Pattern/solution.py | sungminoh/algorithms | train | 0 | |
0a8ac351d92f30d2694341ff6977d3a26435cef4 | [
"q1 = [node]\nans = Node(node.val, [])\nq2 = [ans]\nvisited = set()\nwhile q1:\n cur1 = q1.pop()\n cur2 = q2.pop()\n visited.add(cur1)\n for neighbor in cur1.neighbors:\n if neighbor in visited:\n continue\n if neighbor not in q1:\n q1.append(neighbor)\n ne... | <|body_start_0|>
q1 = [node]
ans = Node(node.val, [])
q2 = [ans]
visited = set()
while q1:
cur1 = q1.pop()
cur2 = q2.pop()
visited.add(cur1)
for neighbor in cur1.neighbors:
if neighbor in visited:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def cloneGraph(self, node: 'Node') -> 'Node':
"""bfs"""
<|body_0|>
def cloneGraph1(self, node: 'Node') -> 'Node':
"""dfs"""
<|body_1|>
def cloneGraph2(self, node: 'Node') -> 'Node':
"""非递归 dfs"""
<|body_2|>
def cloneGraph3(... | stack_v2_sparse_classes_10k_train_008913 | 2,567 | no_license | [
{
"docstring": "bfs",
"name": "cloneGraph",
"signature": "def cloneGraph(self, node: 'Node') -> 'Node'"
},
{
"docstring": "dfs",
"name": "cloneGraph1",
"signature": "def cloneGraph1(self, node: 'Node') -> 'Node'"
},
{
"docstring": "非递归 dfs",
"name": "cloneGraph2",
"signat... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cloneGraph(self, node: 'Node') -> 'Node': bfs
- def cloneGraph1(self, node: 'Node') -> 'Node': dfs
- def cloneGraph2(self, node: 'Node') -> 'Node': 非递归 dfs
- def cloneGraph3(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cloneGraph(self, node: 'Node') -> 'Node': bfs
- def cloneGraph1(self, node: 'Node') -> 'Node': dfs
- def cloneGraph2(self, node: 'Node') -> 'Node': 非递归 dfs
- def cloneGraph3(... | e2fecd266bfced6208694b19a2d81182b13dacd6 | <|skeleton|>
class Solution:
def cloneGraph(self, node: 'Node') -> 'Node':
"""bfs"""
<|body_0|>
def cloneGraph1(self, node: 'Node') -> 'Node':
"""dfs"""
<|body_1|>
def cloneGraph2(self, node: 'Node') -> 'Node':
"""非递归 dfs"""
<|body_2|>
def cloneGraph3(... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def cloneGraph(self, node: 'Node') -> 'Node':
"""bfs"""
q1 = [node]
ans = Node(node.val, [])
q2 = [ans]
visited = set()
while q1:
cur1 = q1.pop()
cur2 = q2.pop()
visited.add(cur1)
for neighbor in cur1.nei... | the_stack_v2_python_sparse | cloneGraph.py | HuipengXu/leetcode | train | 0 | |
47b1e796708ee421f462e4a68b1e71be170df340 | [
"super().__init__(**kwargs)\nself.identifier_required = identifier_required\nself.disallowed_asset_types = disallowed_asset_types\nself.coingecko_obj = coingecko\nself.cryptocompare_obj = cryptocompare",
"asset_type = data.pop('asset_type')\nif self.disallowed_asset_types is not None and asset_type in self.disall... | <|body_start_0|>
super().__init__(**kwargs)
self.identifier_required = identifier_required
self.disallowed_asset_types = disallowed_asset_types
self.coingecko_obj = coingecko
self.cryptocompare_obj = cryptocompare
<|end_body_0|>
<|body_start_1|>
asset_type = data.pop('as... | AssetSchema | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssetSchema:
def __init__(self, identifier_required: bool, disallowed_asset_types: Optional[list[AssetType]]=None, coingecko: Optional['Coingecko']=None, cryptocompare: Optional['Cryptocompare']=None, **kwargs: Any) -> None:
"""Initializes an asset schema depending on the given asset typ... | stack_v2_sparse_classes_10k_train_008914 | 13,942 | permissive | [
{
"docstring": "Initializes an asset schema depending on the given asset type. If identifier_required is True then the identifier field is required. Provided asset_type must not be in disallowed_asset_types list. If coingecko is not None then the coingecko identifier has to be valid. If cryptocompare is not Non... | 2 | null | Implement the Python class `AssetSchema` described below.
Class description:
Implement the AssetSchema class.
Method signatures and docstrings:
- def __init__(self, identifier_required: bool, disallowed_asset_types: Optional[list[AssetType]]=None, coingecko: Optional['Coingecko']=None, cryptocompare: Optional['Crypto... | Implement the Python class `AssetSchema` described below.
Class description:
Implement the AssetSchema class.
Method signatures and docstrings:
- def __init__(self, identifier_required: bool, disallowed_asset_types: Optional[list[AssetType]]=None, coingecko: Optional['Coingecko']=None, cryptocompare: Optional['Crypto... | 496948458b89afc41458f19d1cba0e971ab67c8b | <|skeleton|>
class AssetSchema:
def __init__(self, identifier_required: bool, disallowed_asset_types: Optional[list[AssetType]]=None, coingecko: Optional['Coingecko']=None, cryptocompare: Optional['Cryptocompare']=None, **kwargs: Any) -> None:
"""Initializes an asset schema depending on the given asset typ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AssetSchema:
def __init__(self, identifier_required: bool, disallowed_asset_types: Optional[list[AssetType]]=None, coingecko: Optional['Coingecko']=None, cryptocompare: Optional['Cryptocompare']=None, **kwargs: Any) -> None:
"""Initializes an asset schema depending on the given asset type. If identifi... | the_stack_v2_python_sparse | rotkehlchen/serialization/schemas.py | LefterisJP/rotkehlchen | train | 0 | |
57075916f7e244c45d7b3e3fe373e4ebfa04e094 | [
"w = AddText(None)\nyield w\nw.close()",
"assert isinstance(widget, QtWidgets.QDialog)\nassert isinstance(widget._font, QtGui.QFont)\nassert widget._color == 'black'",
"font_1 = QtGui.QFont('Helvetica', 15)\nmocker.patch.object(QtWidgets.QFontDialog, 'getFont', return_value=(font_1, True))\nwidget.onFontChange(... | <|body_start_0|>
w = AddText(None)
yield w
w.close()
<|end_body_0|>
<|body_start_1|>
assert isinstance(widget, QtWidgets.QDialog)
assert isinstance(widget._font, QtGui.QFont)
assert widget._color == 'black'
<|end_body_1|>
<|body_start_2|>
font_1 = QtGui.QFont('H... | Test the AddText | AddTextTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddTextTest:
"""Test the AddText"""
def widget(self, qapp):
"""Create/Destroy the AddText"""
<|body_0|>
def testDefaults(self, widget):
"""Test the GUI in its default state"""
<|body_1|>
def testOnFontChange(self, widget, mocker):
"""Test the... | stack_v2_sparse_classes_10k_train_008915 | 1,950 | permissive | [
{
"docstring": "Create/Destroy the AddText",
"name": "widget",
"signature": "def widget(self, qapp)"
},
{
"docstring": "Test the GUI in its default state",
"name": "testDefaults",
"signature": "def testDefaults(self, widget)"
},
{
"docstring": "Test the QFontDialog output",
"... | 4 | stack_v2_sparse_classes_30k_train_003700 | Implement the Python class `AddTextTest` described below.
Class description:
Test the AddText
Method signatures and docstrings:
- def widget(self, qapp): Create/Destroy the AddText
- def testDefaults(self, widget): Test the GUI in its default state
- def testOnFontChange(self, widget, mocker): Test the QFontDialog ou... | Implement the Python class `AddTextTest` described below.
Class description:
Test the AddText
Method signatures and docstrings:
- def widget(self, qapp): Create/Destroy the AddText
- def testDefaults(self, widget): Test the GUI in its default state
- def testOnFontChange(self, widget, mocker): Test the QFontDialog ou... | 55b1e9f6db58e33729f2a93b7dd1d8bf255b46f7 | <|skeleton|>
class AddTextTest:
"""Test the AddText"""
def widget(self, qapp):
"""Create/Destroy the AddText"""
<|body_0|>
def testDefaults(self, widget):
"""Test the GUI in its default state"""
<|body_1|>
def testOnFontChange(self, widget, mocker):
"""Test the... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AddTextTest:
"""Test the AddText"""
def widget(self, qapp):
"""Create/Destroy the AddText"""
w = AddText(None)
yield w
w.close()
def testDefaults(self, widget):
"""Test the GUI in its default state"""
assert isinstance(widget, QtWidgets.QDialog)
... | the_stack_v2_python_sparse | src/sas/qtgui/Plotting/UnitTesting/AddTextTest.py | SasView/sasview | train | 48 |
71e5ec9f0105511cb33dd5bbec9e2789017b92b4 | [
"self.id = id\nself.provider_id = provider_id\nself.server_time = server_time\nself.active_from = active_from\nself.active_to = active_to\nself.rpm_over_value = rpm_over_value\nself.over_speed_value = over_speed_value\nself.excess_speed_value = excess_speed_value\nself.long_idle_value = long_idle_value\nself.hi_thr... | <|body_start_0|>
self.id = id
self.provider_id = provider_id
self.server_time = server_time
self.active_from = active_from
self.active_to = active_to
self.rpm_over_value = rpm_over_value
self.over_speed_value = over_speed_value
self.excess_speed_value = ex... | Implementation of the 'Performance Thresholds' model. TODO: type model description here. Attributes: id (string): The unique identifier for the specific Entity object in the system. provider_id (string): The unique 'Provider ID' of the TSP server_time (string): Date and time when this object was received at the TSP act... | PerformanceThresholds | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PerformanceThresholds:
"""Implementation of the 'Performance Thresholds' model. TODO: type model description here. Attributes: id (string): The unique identifier for the specific Entity object in the system. provider_id (string): The unique 'Provider ID' of the TSP server_time (string): Date and ... | stack_v2_sparse_classes_10k_train_008916 | 4,395 | permissive | [
{
"docstring": "Constructor for the PerformanceThresholds class",
"name": "__init__",
"signature": "def __init__(self, id=None, provider_id=None, server_time=None, active_from=None, active_to=None, rpm_over_value=None, over_speed_value=None, excess_speed_value=None, long_idle_value=None, hi_throttle_val... | 2 | stack_v2_sparse_classes_30k_train_003984 | Implement the Python class `PerformanceThresholds` described below.
Class description:
Implementation of the 'Performance Thresholds' model. TODO: type model description here. Attributes: id (string): The unique identifier for the specific Entity object in the system. provider_id (string): The unique 'Provider ID' of ... | Implement the Python class `PerformanceThresholds` described below.
Class description:
Implementation of the 'Performance Thresholds' model. TODO: type model description here. Attributes: id (string): The unique identifier for the specific Entity object in the system. provider_id (string): The unique 'Provider ID' of ... | 729e9391879e273545a4818558677b2e47261f08 | <|skeleton|>
class PerformanceThresholds:
"""Implementation of the 'Performance Thresholds' model. TODO: type model description here. Attributes: id (string): The unique identifier for the specific Entity object in the system. provider_id (string): The unique 'Provider ID' of the TSP server_time (string): Date and ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PerformanceThresholds:
"""Implementation of the 'Performance Thresholds' model. TODO: type model description here. Attributes: id (string): The unique identifier for the specific Entity object in the system. provider_id (string): The unique 'Provider ID' of the TSP server_time (string): Date and time when thi... | the_stack_v2_python_sparse | sdk/python/v0.1-rc.4/opentelematicsapi/models/performance_thresholds.py | nmfta-repo/nmfta-opentelematics-prototype | train | 2 |
35db5a3db506d34cba4fb78ae0fd15ce29c7f519 | [
"if self.app.pargs.download is None:\n download_type = []\nelse:\n download_type = self.app.pargs.download.split(',')\n download_type = list(filter(lambda x: x in all_download_type, download_type))\nreturn download_type",
"help = None\nfun = getattr(self, func_name, None)\nif fun and getattr(fun, '__ceme... | <|body_start_0|>
if self.app.pargs.download is None:
download_type = []
else:
download_type = self.app.pargs.download.split(',')
download_type = list(filter(lambda x: x in all_download_type, download_type))
return download_type
<|end_body_0|>
<|body_start_1|>... | NXSpiderBaseController | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NXSpiderBaseController:
def parse_download(self):
"""lost of spider function will parse -dw param, this will do it :return:"""
<|body_0|>
def param_check(self, params, func_name):
"""this will check param inputted and require is complete or not, and print help help w... | stack_v2_sparse_classes_10k_train_008917 | 1,707 | permissive | [
{
"docstring": "lost of spider function will parse -dw param, this will do it :return:",
"name": "parse_download",
"signature": "def parse_download(self)"
},
{
"docstring": "this will check param inputted and require is complete or not, and print help help will be in expose(help='...'), and got ... | 2 | stack_v2_sparse_classes_30k_val_000146 | Implement the Python class `NXSpiderBaseController` described below.
Class description:
Implement the NXSpiderBaseController class.
Method signatures and docstrings:
- def parse_download(self): lost of spider function will parse -dw param, this will do it :return:
- def param_check(self, params, func_name): this will... | Implement the Python class `NXSpiderBaseController` described below.
Class description:
Implement the NXSpiderBaseController class.
Method signatures and docstrings:
- def parse_download(self): lost of spider function will parse -dw param, this will do it :return:
- def param_check(self, params, func_name): this will... | 68e588c0612d0ab2af3a820ff88ca24d698ceeb7 | <|skeleton|>
class NXSpiderBaseController:
def parse_download(self):
"""lost of spider function will parse -dw param, this will do it :return:"""
<|body_0|>
def param_check(self, params, func_name):
"""this will check param inputted and require is complete or not, and print help help w... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NXSpiderBaseController:
def parse_download(self):
"""lost of spider function will parse -dw param, this will do it :return:"""
if self.app.pargs.download is None:
download_type = []
else:
download_type = self.app.pargs.download.split(',')
download_ty... | the_stack_v2_python_sparse | NXSpider/bin/base_ctrl.py | Z-Shuming/NXSpider | train | 0 | |
331f9cb2f5f8a1fbd220da40d09faf981bb3c4b1 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn KubernetesClusterEvidence()",
"from .alert_evidence import AlertEvidence\nfrom .kubernetes_platform import KubernetesPlatform\nfrom .alert_evidence import AlertEvidence\nfrom .kubernetes_platform import KubernetesPlatform\nfields: Dict... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return KubernetesClusterEvidence()
<|end_body_0|>
<|body_start_1|>
from .alert_evidence import AlertEvidence
from .kubernetes_platform import KubernetesPlatform
from .alert_evidence imp... | KubernetesClusterEvidence | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KubernetesClusterEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> KubernetesClusterEvidence:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and c... | stack_v2_sparse_classes_10k_train_008918 | 3,403 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: KubernetesClusterEvidence",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrim... | 3 | stack_v2_sparse_classes_30k_train_006652 | Implement the Python class `KubernetesClusterEvidence` described below.
Class description:
Implement the KubernetesClusterEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> KubernetesClusterEvidence: Creates a new instance of the appropriat... | Implement the Python class `KubernetesClusterEvidence` described below.
Class description:
Implement the KubernetesClusterEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> KubernetesClusterEvidence: Creates a new instance of the appropriat... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class KubernetesClusterEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> KubernetesClusterEvidence:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and c... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KubernetesClusterEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> KubernetesClusterEvidence:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the obje... | the_stack_v2_python_sparse | msgraph/generated/models/security/kubernetes_cluster_evidence.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
666544a592026b46ada7e2ff54a92c105001fc02 | [
"if self.entity.exists:\n return self.entity['Owner'].get_entity()\nelse:\n return None",
"if self.entity.exists:\n with self.entity['Owner'].open() as collection:\n collection.clear()\nelse:\n self.entity['Owner'].ClearBindings()"
] | <|body_start_0|>
if self.entity.exists:
return self.entity['Owner'].get_entity()
else:
return None
<|end_body_0|>
<|body_start_1|>
if self.entity.exists:
with self.entity['Owner'].open() as collection:
collection.clear()
else:
... | MultiTenantSession | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiTenantSession:
def get_owner(self):
"""Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be confused with a user associated with the session via an LTI launch. If there is no owner, None is returned."""... | stack_v2_sparse_classes_10k_train_008919 | 18,986 | permissive | [
{
"docstring": "Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be confused with a user associated with the session via an LTI launch. If there is no owner, None is returned.",
"name": "get_owner",
"signature": "def get_o... | 2 | stack_v2_sparse_classes_30k_train_006112 | Implement the Python class `MultiTenantSession` described below.
Class description:
Implement the MultiTenantSession class.
Method signatures and docstrings:
- def get_owner(self): Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be con... | Implement the Python class `MultiTenantSession` described below.
Class description:
Implement the MultiTenantSession class.
Method signatures and docstrings:
- def get_owner(self): Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be con... | ef27dd6bb6fbd6d47687a349508cd4ab2989a0ad | <|skeleton|>
class MultiTenantSession:
def get_owner(self):
"""Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be confused with a user associated with the session via an LTI launch. If there is no owner, None is returned."""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MultiTenantSession:
def get_owner(self):
"""Returns the owner of the session The owner is the person logged in to the root of the application. It may be None. This should not be confused with a user associated with the session via an LTI launch. If there is no owner, None is returned."""
if se... | the_stack_v2_python_sparse | samples/noticeboard/mtnoticeboard.py | j5int/pyslet | train | 2 | |
bed8b673f07f36960439a0bb7e016e92bff5deb6 | [
"tortoise = hare = head\nwhile hare and hare.next:\n tortoise = tortoise.next\n hare = hare.next.next\n if tortoise == hare:\n return hare\nreturn None",
"if not head:\n return head\nmeeting_point = self.get_intersection(head)\nif not meeting_point:\n return None\npointer_1 = head\npointer_2... | <|body_start_0|>
tortoise = hare = head
while hare and hare.next:
tortoise = tortoise.next
hare = hare.next.next
if tortoise == hare:
return hare
return None
<|end_body_0|>
<|body_start_1|>
if not head:
return head
... | ListCycle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListCycle:
def get_intersection(self, head: 'ListNode'):
"""Gets the intersection point of slow and fast. or hare and tortoise. :param head: :return:"""
<|body_0|>
def get_node(self, head: 'ListNode') -> 'ListNode':
"""Approach: Floyd's tortoise and hare Time Complex... | stack_v2_sparse_classes_10k_train_008920 | 1,598 | no_license | [
{
"docstring": "Gets the intersection point of slow and fast. or hare and tortoise. :param head: :return:",
"name": "get_intersection",
"signature": "def get_intersection(self, head: 'ListNode')"
},
{
"docstring": "Approach: Floyd's tortoise and hare Time Complexity: O(N) Space Complexity: O(1) ... | 3 | null | Implement the Python class `ListCycle` described below.
Class description:
Implement the ListCycle class.
Method signatures and docstrings:
- def get_intersection(self, head: 'ListNode'): Gets the intersection point of slow and fast. or hare and tortoise. :param head: :return:
- def get_node(self, head: 'ListNode') -... | Implement the Python class `ListCycle` described below.
Class description:
Implement the ListCycle class.
Method signatures and docstrings:
- def get_intersection(self, head: 'ListNode'): Gets the intersection point of slow and fast. or hare and tortoise. :param head: :return:
- def get_node(self, head: 'ListNode') -... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class ListCycle:
def get_intersection(self, head: 'ListNode'):
"""Gets the intersection point of slow and fast. or hare and tortoise. :param head: :return:"""
<|body_0|>
def get_node(self, head: 'ListNode') -> 'ListNode':
"""Approach: Floyd's tortoise and hare Time Complex... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ListCycle:
def get_intersection(self, head: 'ListNode'):
"""Gets the intersection point of slow and fast. or hare and tortoise. :param head: :return:"""
tortoise = hare = head
while hare and hare.next:
tortoise = tortoise.next
hare = hare.next.next
i... | the_stack_v2_python_sparse | revisited/linked_list/list_cycle_ii.py | Shiv2157k/leet_code | train | 1 | |
d05983623662d8d6065188dda19c26ec61ad0cd0 | [
"keyboard = ['qwertyuiopQWERTYUIOP', 'asdfghjklASDFGHJKL', 'zxcvbnmZXCVBNM']\nres = []\nfor word in words:\n pos = []\n for w in word:\n for index, key in enumerate(keyboard):\n if w in key:\n pos.append(index)\n break\n if len(set(pos)) == 1:\n res.ap... | <|body_start_0|>
keyboard = ['qwertyuiopQWERTYUIOP', 'asdfghjklASDFGHJKL', 'zxcvbnmZXCVBNM']
res = []
for word in words:
pos = []
for w in word:
for index, key in enumerate(keyboard):
if w in key:
pos.append(inde... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findWords(self, words):
""":type words: List[str] :rtype: List[str]"""
<|body_0|>
def _findWords(self, words):
""":type words: List[str] :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
keyboard = ['qwertyuiopQWERTYUIO... | stack_v2_sparse_classes_10k_train_008921 | 1,800 | permissive | [
{
"docstring": ":type words: List[str] :rtype: List[str]",
"name": "findWords",
"signature": "def findWords(self, words)"
},
{
"docstring": ":type words: List[str] :rtype: List[str]",
"name": "_findWords",
"signature": "def _findWords(self, words)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006502 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findWords(self, words): :type words: List[str] :rtype: List[str]
- def _findWords(self, words): :type words: List[str] :rtype: List[str] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findWords(self, words): :type words: List[str] :rtype: List[str]
- def _findWords(self, words): :type words: List[str] :rtype: List[str]
<|skeleton|>
class Solution:
de... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def findWords(self, words):
""":type words: List[str] :rtype: List[str]"""
<|body_0|>
def _findWords(self, words):
""":type words: List[str] :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findWords(self, words):
""":type words: List[str] :rtype: List[str]"""
keyboard = ['qwertyuiopQWERTYUIOP', 'asdfghjklASDFGHJKL', 'zxcvbnmZXCVBNM']
res = []
for word in words:
pos = []
for w in word:
for index, key in enumera... | the_stack_v2_python_sparse | 500.keyboard-row.py | windard/leeeeee | train | 0 | |
b0057acdc0e2755c710d7497fef4414b7a2a71dd | [
"self.svc_name = svc_name\nself.set_name = set_name\nself.min = int(min)\nself.max = int(max)\nself.isContinuous = True\nself.vals = None",
"self.isContinuous = False\nself.vals = [int(val) for val in vals]\nself.min = min(self.vals)\nself.max = max(self.vals)"
] | <|body_start_0|>
self.svc_name = svc_name
self.set_name = set_name
self.min = int(min)
self.max = int(max)
self.isContinuous = True
self.vals = None
<|end_body_0|>
<|body_start_1|>
self.isContinuous = False
self.vals = [int(val) for val in vals]
s... | a knob setting with max and min settings. It's the smallest unit for RAPID-C | Knob | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Knob:
"""a knob setting with max and min settings. It's the smallest unit for RAPID-C"""
def __init__(self, svc_name, set_name, min, max):
"""Initialization :param svc_name: name of service :param set_name: name of setting :param min: lower bound :param max: upper bound"""
<|... | stack_v2_sparse_classes_10k_train_008922 | 5,554 | no_license | [
{
"docstring": "Initialization :param svc_name: name of service :param set_name: name of setting :param min: lower bound :param max: upper bound",
"name": "__init__",
"signature": "def __init__(self, svc_name, set_name, min, max)"
},
{
"docstring": "Trasform to a knob with vals (discrete)",
... | 2 | stack_v2_sparse_classes_30k_train_004379 | Implement the Python class `Knob` described below.
Class description:
a knob setting with max and min settings. It's the smallest unit for RAPID-C
Method signatures and docstrings:
- def __init__(self, svc_name, set_name, min, max): Initialization :param svc_name: name of service :param set_name: name of setting :par... | Implement the Python class `Knob` described below.
Class description:
a knob setting with max and min settings. It's the smallest unit for RAPID-C
Method signatures and docstrings:
- def __init__(self, svc_name, set_name, min, max): Initialization :param svc_name: name of service :param set_name: name of setting :par... | 63b50cc32c6f647ea34b5512f48688149f949a3c | <|skeleton|>
class Knob:
"""a knob setting with max and min settings. It's the smallest unit for RAPID-C"""
def __init__(self, svc_name, set_name, min, max):
"""Initialization :param svc_name: name of service :param set_name: name of setting :param min: lower bound :param max: upper bound"""
<|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Knob:
"""a knob setting with max and min settings. It's the smallest unit for RAPID-C"""
def __init__(self, svc_name, set_name, min, max):
"""Initialization :param svc_name: name of service :param set_name: name of setting :param min: lower bound :param max: upper bound"""
self.svc_name =... | the_stack_v2_python_sparse | modelConstr/Rapids/Rapids_Classes/KDG.py | niuye8911/rapidlib-linux | train | 0 |
5a79ae9a7a59f3365740a0fdf8a389177daa53cb | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn AppleManagedIdentityProvider()",
"from .identity_provider_base import IdentityProviderBase\nfrom .identity_provider_base import IdentityProviderBase\nfields: Dict[str, Callable[[Any], None]] = {'certificateData': lambda n: setattr(self... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return AppleManagedIdentityProvider()
<|end_body_0|>
<|body_start_1|>
from .identity_provider_base import IdentityProviderBase
from .identity_provider_base import IdentityProviderBase
f... | AppleManagedIdentityProvider | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AppleManagedIdentityProvider:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AppleManagedIdentityProvider:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value... | stack_v2_sparse_classes_10k_train_008923 | 2,952 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: AppleManagedIdentityProvider",
"name": "create_from_discriminator_value",
"signature": "def create_from_disc... | 3 | stack_v2_sparse_classes_30k_train_005807 | Implement the Python class `AppleManagedIdentityProvider` described below.
Class description:
Implement the AppleManagedIdentityProvider class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AppleManagedIdentityProvider: Creates a new instance of the a... | Implement the Python class `AppleManagedIdentityProvider` described below.
Class description:
Implement the AppleManagedIdentityProvider class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AppleManagedIdentityProvider: Creates a new instance of the a... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AppleManagedIdentityProvider:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AppleManagedIdentityProvider:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AppleManagedIdentityProvider:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AppleManagedIdentityProvider:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create th... | the_stack_v2_python_sparse | msgraph/generated/models/apple_managed_identity_provider.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
06ca5f88badc833510d948f797ba3ffa9d1729b7 | [
"def write(root):\n if not root:\n return\n res.append(str(root.val))\n for child in root.children:\n write(child)\n res.append('#')\nres = []\nwrite(root)\nreturn ' '.join(res)",
"if not data:\n return None\ndata = collections.deque(data.split(' '))\nroot = Node(int(data.popleft()), ... | <|body_start_0|>
def write(root):
if not root:
return
res.append(str(root.val))
for child in root.children:
write(child)
res.append('#')
res = []
write(root)
return ' '.join(res)
<|end_body_0|>
<|body_start_... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_10k_train_008924 | 1,306 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: Node :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: Node",
"name": "deserialize",
"signature": "def deserialize(self, ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: Nod... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: Nod... | 431b763bf3019bac7c08619d7ffef37e638940e8 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
def write(root):
if not root:
return
res.append(str(root.val))
for child in root.children:
write(child)
res.ap... | the_stack_v2_python_sparse | notes/0428/0428.py | PaulGuo5/Leetcode-notes | train | 1 | |
5ea39dda1400833d7ab14640a7ec1cc996ba5494 | [
"self.app_server_id = app_server_id\nself.backup_supported = backup_supported\nself.backup_unsupported_reasons = backup_unsupported_reasons\nself.created_time_msecs = created_time_msecs\nself.database_state = database_state\nself.db_size_bytes = db_size_bytes\nself.dbguid = dbguid\nself.name = name\nself.owner_id =... | <|body_start_0|>
self.app_server_id = app_server_id
self.backup_supported = backup_supported
self.backup_unsupported_reasons = backup_unsupported_reasons
self.created_time_msecs = created_time_msecs
self.database_state = database_state
self.db_size_bytes = db_size_bytes
... | Implementation of the 'ExchangeDatabaseInfo' model. Specifies the information about the Exchange Database. Attributes: app_server_id (long|int): Specifies the entity id of the Exchange Application Server which has this database copy. backup_supported (bool): Specifies if backup is supported for the Exchange database co... | ExchangeDatabaseInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExchangeDatabaseInfo:
"""Implementation of the 'ExchangeDatabaseInfo' model. Specifies the information about the Exchange Database. Attributes: app_server_id (long|int): Specifies the entity id of the Exchange Application Server which has this database copy. backup_supported (bool): Specifies if ... | stack_v2_sparse_classes_10k_train_008925 | 4,567 | permissive | [
{
"docstring": "Constructor for the ExchangeDatabaseInfo class",
"name": "__init__",
"signature": "def __init__(self, app_server_id=None, backup_supported=None, backup_unsupported_reasons=None, created_time_msecs=None, database_state=None, db_size_bytes=None, dbguid=None, name=None, owner_id=None, utc_o... | 2 | null | Implement the Python class `ExchangeDatabaseInfo` described below.
Class description:
Implementation of the 'ExchangeDatabaseInfo' model. Specifies the information about the Exchange Database. Attributes: app_server_id (long|int): Specifies the entity id of the Exchange Application Server which has this database copy.... | Implement the Python class `ExchangeDatabaseInfo` described below.
Class description:
Implementation of the 'ExchangeDatabaseInfo' model. Specifies the information about the Exchange Database. Attributes: app_server_id (long|int): Specifies the entity id of the Exchange Application Server which has this database copy.... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ExchangeDatabaseInfo:
"""Implementation of the 'ExchangeDatabaseInfo' model. Specifies the information about the Exchange Database. Attributes: app_server_id (long|int): Specifies the entity id of the Exchange Application Server which has this database copy. backup_supported (bool): Specifies if ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExchangeDatabaseInfo:
"""Implementation of the 'ExchangeDatabaseInfo' model. Specifies the information about the Exchange Database. Attributes: app_server_id (long|int): Specifies the entity id of the Exchange Application Server which has this database copy. backup_supported (bool): Specifies if backup is sup... | the_stack_v2_python_sparse | cohesity_management_sdk/models/exchange_database_info.py | cohesity/management-sdk-python | train | 24 |
61b8186209dbcb0c14734399d2c312c571c12a9e | [
"try:\n client.containers.get(name_or_id).remove(force=force)\nexcept docker.errors.NotFound as not_found:\n if not ignore_container_not_found:\n raise not_found",
"try:\n client.images.remove(name_or_id, force=force)\nexcept docker.errors.ImageNotFound as not_found:\n if not ignore_image_not_f... | <|body_start_0|>
try:
client.containers.get(name_or_id).remove(force=force)
except docker.errors.NotFound as not_found:
if not ignore_container_not_found:
raise not_found
<|end_body_0|>
<|body_start_1|>
try:
client.images.remove(name_or_id, fo... | docker extra tools that will be usefully also as stand alone commands | DockerTools | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DockerTools:
"""docker extra tools that will be usefully also as stand alone commands"""
def remove_container(name_or_id: str, ignore_container_not_found: bool=True, force: bool=False):
"""Examples docker rm MyTestContainer can be replaced with DockerTools.remove_container("MyTestCon... | stack_v2_sparse_classes_10k_train_008926 | 6,497 | permissive | [
{
"docstring": "Examples docker rm MyTestContainer can be replaced with DockerTools.remove_container(\"MyTestContainer\") in your code Args: name_or_id: the name or id of the container ignore_container_not_found: don't raise an exception in case the container already removed force: same as the -f option in the ... | 2 | stack_v2_sparse_classes_30k_train_003144 | Implement the Python class `DockerTools` described below.
Class description:
docker extra tools that will be usefully also as stand alone commands
Method signatures and docstrings:
- def remove_container(name_or_id: str, ignore_container_not_found: bool=True, force: bool=False): Examples docker rm MyTestContainer can... | Implement the Python class `DockerTools` described below.
Class description:
docker extra tools that will be usefully also as stand alone commands
Method signatures and docstrings:
- def remove_container(name_or_id: str, ignore_container_not_found: bool=True, force: bool=False): Examples docker rm MyTestContainer can... | 59d99cf4b5016be8a4a333c2541418e1612549e1 | <|skeleton|>
class DockerTools:
"""docker extra tools that will be usefully also as stand alone commands"""
def remove_container(name_or_id: str, ignore_container_not_found: bool=True, force: bool=False):
"""Examples docker rm MyTestContainer can be replaced with DockerTools.remove_container("MyTestCon... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DockerTools:
"""docker extra tools that will be usefully also as stand alone commands"""
def remove_container(name_or_id: str, ignore_container_not_found: bool=True, force: bool=False):
"""Examples docker rm MyTestContainer can be replaced with DockerTools.remove_container("MyTestContainer") in y... | the_stack_v2_python_sparse | demisto_sdk/commands/common/docker_util.py | kfirstri/demisto-sdk | train | 1 |
d5efa6ff0d0bc190951eab8e986435d63f523567 | [
"super(ErrorCalculator, self).__init__()\nself.report_cer = report_cer\nself.report_wer = report_wer\nself.char_list = char_list\nself.space = sym_space\nself.blank = sym_blank\nif self.blank in self.char_list:\n self.idx_blank = self.char_list.index(self.blank)\nelse:\n self.idx_blank = None\nif self.space i... | <|body_start_0|>
super(ErrorCalculator, self).__init__()
self.report_cer = report_cer
self.report_wer = report_wer
self.char_list = char_list
self.space = sym_space
self.blank = sym_blank
if self.blank in self.char_list:
self.idx_blank = self.char_list... | Calculate CER and WER for E2E_ASR and CTC models during training. :param y_hats: numpy array with predicted text :param y_pads: numpy array with true (target) text :param char_list: :param sym_space: :param sym_blank: :return: | ErrorCalculator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ErrorCalculator:
"""Calculate CER and WER for E2E_ASR and CTC models during training. :param y_hats: numpy array with predicted text :param y_pads: numpy array with true (target) text :param char_list: :param sym_space: :param sym_blank: :return:"""
def __init__(self, char_list, sym_space, s... | stack_v2_sparse_classes_10k_train_008927 | 8,773 | permissive | [
{
"docstring": "Construct an ErrorCalculator object.",
"name": "__init__",
"signature": "def __init__(self, char_list, sym_space, sym_blank, report_cer=False, report_wer=False)"
},
{
"docstring": "Calculate sentence-level WER/CER score. :param torch.Tensor ys_hat: prediction (batch, seqlen) :par... | 6 | null | Implement the Python class `ErrorCalculator` described below.
Class description:
Calculate CER and WER for E2E_ASR and CTC models during training. :param y_hats: numpy array with predicted text :param y_pads: numpy array with true (target) text :param char_list: :param sym_space: :param sym_blank: :return:
Method sig... | Implement the Python class `ErrorCalculator` described below.
Class description:
Calculate CER and WER for E2E_ASR and CTC models during training. :param y_hats: numpy array with predicted text :param y_pads: numpy array with true (target) text :param char_list: :param sym_space: :param sym_blank: :return:
Method sig... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class ErrorCalculator:
"""Calculate CER and WER for E2E_ASR and CTC models during training. :param y_hats: numpy array with predicted text :param y_pads: numpy array with true (target) text :param char_list: :param sym_space: :param sym_blank: :return:"""
def __init__(self, char_list, sym_space, s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ErrorCalculator:
"""Calculate CER and WER for E2E_ASR and CTC models during training. :param y_hats: numpy array with predicted text :param y_pads: numpy array with true (target) text :param char_list: :param sym_space: :param sym_blank: :return:"""
def __init__(self, char_list, sym_space, sym_blank, rep... | the_stack_v2_python_sparse | espnet/nets/e2e_asr_common.py | espnet/espnet | train | 7,242 |
9253f01e88adce33444245fcf2b4fbd744be6a7d | [
"errors = []\nif not file_path or file_path.isspace():\n errors.append(VerifierError(subject=self, local_error='Gromacs file name is white space.', global_error='Gromacs file not specified.'))\nif ext is not None:\n if not file_path.endswith('.{}'.format(ext)):\n errors.append(VerifierError(subject=sel... | <|body_start_0|>
errors = []
if not file_path or file_path.isspace():
errors.append(VerifierError(subject=self, local_error='Gromacs file name is white space.', global_error='Gromacs file not specified.'))
if ext is not None:
if not file_path.endswith('.{}'.format(ext)):
... | Class containing all input parameters for a single molecular fragment in a Gromacs simulation | FragmentDataSourceModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FragmentDataSourceModel:
"""Class containing all input parameters for a single molecular fragment in a Gromacs simulation"""
def _file_check(self, file_path, ext=None):
"""Performs a series of checks on selected Gromacs file located at file_path Parameters ---------- file_path: str F... | stack_v2_sparse_classes_10k_train_008928 | 2,768 | permissive | [
{
"docstring": "Performs a series of checks on selected Gromacs file located at file_path Parameters ---------- file_path: str File path for Gromacs input file ext: str, optional Expected extension of Gromacs input file",
"name": "_file_check",
"signature": "def _file_check(self, file_path, ext=None)"
... | 2 | stack_v2_sparse_classes_30k_train_002439 | Implement the Python class `FragmentDataSourceModel` described below.
Class description:
Class containing all input parameters for a single molecular fragment in a Gromacs simulation
Method signatures and docstrings:
- def _file_check(self, file_path, ext=None): Performs a series of checks on selected Gromacs file lo... | Implement the Python class `FragmentDataSourceModel` described below.
Class description:
Class containing all input parameters for a single molecular fragment in a Gromacs simulation
Method signatures and docstrings:
- def _file_check(self, file_path, ext=None): Performs a series of checks on selected Gromacs file lo... | 1518185e4cdab824d57570bc5df6c719f1f11bea | <|skeleton|>
class FragmentDataSourceModel:
"""Class containing all input parameters for a single molecular fragment in a Gromacs simulation"""
def _file_check(self, file_path, ext=None):
"""Performs a series of checks on selected Gromacs file located at file_path Parameters ---------- file_path: str F... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FragmentDataSourceModel:
"""Class containing all input parameters for a single molecular fragment in a Gromacs simulation"""
def _file_check(self, file_path, ext=None):
"""Performs a series of checks on selected Gromacs file located at file_path Parameters ---------- file_path: str File path for ... | the_stack_v2_python_sparse | force_gromacs/data_sources/fragment/fragment_model.py | force-h2020/force-bdss-plugin-gromacs | train | 0 |
d9c2eb175d70fb3920a078fc581b3fa19f51beac | [
"self.copy_task_uid = copy_task_uid\nself.job_run_id = job_run_id\nself.task_id_list = task_id_list",
"if dictionary is None:\n return None\ncopy_task_uid = cohesity_management_sdk.models.universal_id.UniversalId.from_dictionary(dictionary.get('copyTaskUid')) if dictionary.get('copyTaskUid') else None\njob_run... | <|body_start_0|>
self.copy_task_uid = copy_task_uid
self.job_run_id = job_run_id
self.task_id_list = task_id_list
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
copy_task_uid = cohesity_management_sdk.models.universal_id.UniversalId.from_dictionar... | Implementation of the 'CancelProtectionJobRunParam' model. TODO: type description here. Attributes: copy_task_uid (UniversalId): CopyTaskUid is the Uid of a copy task. If a particular copy task is to be cancelled, this field should be set to the id of that particular copy task. For example, if replication task is to be... | CancelProtectionJobRunParam | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CancelProtectionJobRunParam:
"""Implementation of the 'CancelProtectionJobRunParam' model. TODO: type description here. Attributes: copy_task_uid (UniversalId): CopyTaskUid is the Uid of a copy task. If a particular copy task is to be cancelled, this field should be set to the id of that particul... | stack_v2_sparse_classes_10k_train_008929 | 2,888 | permissive | [
{
"docstring": "Constructor for the CancelProtectionJobRunParam class",
"name": "__init__",
"signature": "def __init__(self, copy_task_uid=None, job_run_id=None, task_id_list=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary... | 2 | null | Implement the Python class `CancelProtectionJobRunParam` described below.
Class description:
Implementation of the 'CancelProtectionJobRunParam' model. TODO: type description here. Attributes: copy_task_uid (UniversalId): CopyTaskUid is the Uid of a copy task. If a particular copy task is to be cancelled, this field s... | Implement the Python class `CancelProtectionJobRunParam` described below.
Class description:
Implementation of the 'CancelProtectionJobRunParam' model. TODO: type description here. Attributes: copy_task_uid (UniversalId): CopyTaskUid is the Uid of a copy task. If a particular copy task is to be cancelled, this field s... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class CancelProtectionJobRunParam:
"""Implementation of the 'CancelProtectionJobRunParam' model. TODO: type description here. Attributes: copy_task_uid (UniversalId): CopyTaskUid is the Uid of a copy task. If a particular copy task is to be cancelled, this field should be set to the id of that particul... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CancelProtectionJobRunParam:
"""Implementation of the 'CancelProtectionJobRunParam' model. TODO: type description here. Attributes: copy_task_uid (UniversalId): CopyTaskUid is the Uid of a copy task. If a particular copy task is to be cancelled, this field should be set to the id of that particular copy task.... | the_stack_v2_python_sparse | cohesity_management_sdk/models/cancel_protection_job_run_param.py | cohesity/management-sdk-python | train | 24 |
2d86d4782d610f3d325c06000d3846a6b9879646 | [
"try:\n try:\n pObject = PTJInfo.objects.get(id=pid)\n except:\n return JsonResponse({'status': False, 'err': '内容不存在'}, status=404)\n ptjResult = model_to_dict(pObject)\n return JsonResponse({'status': True, 'ptj': ptjResult})\nexcept:\n return JsonResponse({'status': False, 'err': '出现未... | <|body_start_0|>
try:
try:
pObject = PTJInfo.objects.get(id=pid)
except:
return JsonResponse({'status': False, 'err': '内容不存在'}, status=404)
ptjResult = model_to_dict(pObject)
return JsonResponse({'status': True, 'ptj': ptjResult})
... | PTJInfoView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PTJInfoView:
def get(self, requests, pid):
"""获得兼职消息详情 :param requests: :param pid: ptj id :return:"""
<|body_0|>
def delete(self, requests, pid):
"""删除兼职消息 :param requests: :param pid: :return:"""
<|body_1|>
def post(self, requests):
"""新增兼职信息 :... | stack_v2_sparse_classes_10k_train_008930 | 2,987 | no_license | [
{
"docstring": "获得兼职消息详情 :param requests: :param pid: ptj id :return:",
"name": "get",
"signature": "def get(self, requests, pid)"
},
{
"docstring": "删除兼职消息 :param requests: :param pid: :return:",
"name": "delete",
"signature": "def delete(self, requests, pid)"
},
{
"docstring": ... | 3 | stack_v2_sparse_classes_30k_train_001578 | Implement the Python class `PTJInfoView` described below.
Class description:
Implement the PTJInfoView class.
Method signatures and docstrings:
- def get(self, requests, pid): 获得兼职消息详情 :param requests: :param pid: ptj id :return:
- def delete(self, requests, pid): 删除兼职消息 :param requests: :param pid: :return:
- def po... | Implement the Python class `PTJInfoView` described below.
Class description:
Implement the PTJInfoView class.
Method signatures and docstrings:
- def get(self, requests, pid): 获得兼职消息详情 :param requests: :param pid: ptj id :return:
- def delete(self, requests, pid): 删除兼职消息 :param requests: :param pid: :return:
- def po... | 526dea540048fc92260bce611c520c50af744e0b | <|skeleton|>
class PTJInfoView:
def get(self, requests, pid):
"""获得兼职消息详情 :param requests: :param pid: ptj id :return:"""
<|body_0|>
def delete(self, requests, pid):
"""删除兼职消息 :param requests: :param pid: :return:"""
<|body_1|>
def post(self, requests):
"""新增兼职信息 :... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PTJInfoView:
def get(self, requests, pid):
"""获得兼职消息详情 :param requests: :param pid: ptj id :return:"""
try:
try:
pObject = PTJInfo.objects.get(id=pid)
except:
return JsonResponse({'status': False, 'err': '内容不存在'}, status=404)
... | the_stack_v2_python_sparse | apps/PTJ/views/PTJInfo.py | DICKQI/ALGYunXS | train | 0 | |
d009b74557a1af19f1ed38b28804c4b3d0fe5231 | [
"if root is None:\n return [0]\nsums = []\ncounts = []\n\ndef dfs(node, level):\n if len(sums) == level:\n sums.append(0)\n counts.append(0)\n sums[level] += node.val\n counts[level] += 1\n if node.left:\n dfs(node.left, level + 1)\n if node.right:\n dfs(node.right, lev... | <|body_start_0|>
if root is None:
return [0]
sums = []
counts = []
def dfs(node, level):
if len(sums) == level:
sums.append(0)
counts.append(0)
sums[level] += node.val
counts[level] += 1
if node.... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def averageOfLevels(self, root) -> List[float]:
"""DFS, Time: O(n), Space: O(n)"""
<|body_0|>
def averageOfLevels(self, root) -> List[float]:
"""BFS, Time: O(n), Space: O(n)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is None:
... | stack_v2_sparse_classes_10k_train_008931 | 1,288 | no_license | [
{
"docstring": "DFS, Time: O(n), Space: O(n)",
"name": "averageOfLevels",
"signature": "def averageOfLevels(self, root) -> List[float]"
},
{
"docstring": "BFS, Time: O(n), Space: O(n)",
"name": "averageOfLevels",
"signature": "def averageOfLevels(self, root) -> List[float]"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def averageOfLevels(self, root) -> List[float]: DFS, Time: O(n), Space: O(n)
- def averageOfLevels(self, root) -> List[float]: BFS, Time: O(n), Space: O(n) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def averageOfLevels(self, root) -> List[float]: DFS, Time: O(n), Space: O(n)
- def averageOfLevels(self, root) -> List[float]: BFS, Time: O(n), Space: O(n)
<|skeleton|>
class So... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def averageOfLevels(self, root) -> List[float]:
"""DFS, Time: O(n), Space: O(n)"""
<|body_0|>
def averageOfLevels(self, root) -> List[float]:
"""BFS, Time: O(n), Space: O(n)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def averageOfLevels(self, root) -> List[float]:
"""DFS, Time: O(n), Space: O(n)"""
if root is None:
return [0]
sums = []
counts = []
def dfs(node, level):
if len(sums) == level:
sums.append(0)
counts.app... | the_stack_v2_python_sparse | python/637-Average of Levels in Binary Tree.py | cwza/leetcode | train | 0 | |
624a0723b90324fdc737f34bb8ec9d0fe32a5e20 | [
"v = utils.splitpath_root_file_ext('F:\\\\foo\\\\bar.py')\nself.assertEqual(v, ('F:\\\\foo', 'bar', '.py'))\nv = utils.splitpath_root_file_ext('J:\\\\spam.py')\nself.assertEqual(v, ('J:\\\\', 'spam', '.py'))",
"v = utils.splitpath_root_file_ext('C:\\\\foo\\\\bar')\nself.assertEqual(v, ('C:\\\\foo', 'bar', ''))\nv... | <|body_start_0|>
v = utils.splitpath_root_file_ext('F:\\foo\\bar.py')
self.assertEqual(v, ('F:\\foo', 'bar', '.py'))
v = utils.splitpath_root_file_ext('J:\\spam.py')
self.assertEqual(v, ('J:\\', 'spam', '.py'))
<|end_body_0|>
<|body_start_1|>
v = utils.splitpath_root_file_ext('C... | TestSplitRootFileExt | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSplitRootFileExt:
def testRegularPath(self):
"""Test the method's behavior on regular paths."""
<|body_0|>
def testDirOnly(self):
"""Test behavior when passed a path only."""
<|body_1|>
def testFileOnly(self):
"""Test behavior when passed a f... | stack_v2_sparse_classes_10k_train_008932 | 2,610 | permissive | [
{
"docstring": "Test the method's behavior on regular paths.",
"name": "testRegularPath",
"signature": "def testRegularPath(self)"
},
{
"docstring": "Test behavior when passed a path only.",
"name": "testDirOnly",
"signature": "def testDirOnly(self)"
},
{
"docstring": "Test behav... | 3 | stack_v2_sparse_classes_30k_train_002937 | Implement the Python class `TestSplitRootFileExt` described below.
Class description:
Implement the TestSplitRootFileExt class.
Method signatures and docstrings:
- def testRegularPath(self): Test the method's behavior on regular paths.
- def testDirOnly(self): Test behavior when passed a path only.
- def testFileOnly... | Implement the Python class `TestSplitRootFileExt` described below.
Class description:
Implement the TestSplitRootFileExt class.
Method signatures and docstrings:
- def testRegularPath(self): Test the method's behavior on regular paths.
- def testDirOnly(self): Test behavior when passed a path only.
- def testFileOnly... | 679397c86992fe434e3aabff7edf4f6867424bc9 | <|skeleton|>
class TestSplitRootFileExt:
def testRegularPath(self):
"""Test the method's behavior on regular paths."""
<|body_0|>
def testDirOnly(self):
"""Test behavior when passed a path only."""
<|body_1|>
def testFileOnly(self):
"""Test behavior when passed a f... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestSplitRootFileExt:
def testRegularPath(self):
"""Test the method's behavior on regular paths."""
v = utils.splitpath_root_file_ext('F:\\foo\\bar.py')
self.assertEqual(v, ('F:\\foo', 'bar', '.py'))
v = utils.splitpath_root_file_ext('J:\\spam.py')
self.assertEqual(v, (... | the_stack_v2_python_sparse | pynocle-0.3.2/build/lib.linux-x86_64-2.7/pynocle/test_utils.py | 1147279/SoftwareProject | train | 0 | |
c863db94ef5227e48b68e93afe0b1ce404c392a8 | [
"super().__init__(data, device)\nself.entity_description = description\nself._attr_unique_id = f'{device.device_uuid}-{description.key}'\nif description.key == CONST.TEMP_STATUS_KEY:\n self._attr_native_unit_of_measurement = device.temp_unit\nelif description.key == CONST.HUMI_STATUS_KEY:\n self._attr_native_... | <|body_start_0|>
super().__init__(data, device)
self.entity_description = description
self._attr_unique_id = f'{device.device_uuid}-{description.key}'
if description.key == CONST.TEMP_STATUS_KEY:
self._attr_native_unit_of_measurement = device.temp_unit
elif descriptio... | A sensor implementation for Abode devices. | AbodeSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbodeSensor:
"""A sensor implementation for Abode devices."""
def __init__(self, data: AbodeSystem, device: AbodeSense, description: SensorEntityDescription) -> None:
"""Initialize a sensor for an Abode device."""
<|body_0|>
def native_value(self) -> float | None:
... | stack_v2_sparse_classes_10k_train_008933 | 2,873 | permissive | [
{
"docstring": "Initialize a sensor for an Abode device.",
"name": "__init__",
"signature": "def __init__(self, data: AbodeSystem, device: AbodeSense, description: SensorEntityDescription) -> None"
},
{
"docstring": "Return the state of the sensor.",
"name": "native_value",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_007054 | Implement the Python class `AbodeSensor` described below.
Class description:
A sensor implementation for Abode devices.
Method signatures and docstrings:
- def __init__(self, data: AbodeSystem, device: AbodeSense, description: SensorEntityDescription) -> None: Initialize a sensor for an Abode device.
- def native_val... | Implement the Python class `AbodeSensor` described below.
Class description:
A sensor implementation for Abode devices.
Method signatures and docstrings:
- def __init__(self, data: AbodeSystem, device: AbodeSense, description: SensorEntityDescription) -> None: Initialize a sensor for an Abode device.
- def native_val... | 2e65b77b2b5c17919939481f327963abdfdc53f0 | <|skeleton|>
class AbodeSensor:
"""A sensor implementation for Abode devices."""
def __init__(self, data: AbodeSystem, device: AbodeSense, description: SensorEntityDescription) -> None:
"""Initialize a sensor for an Abode device."""
<|body_0|>
def native_value(self) -> float | None:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AbodeSensor:
"""A sensor implementation for Abode devices."""
def __init__(self, data: AbodeSystem, device: AbodeSense, description: SensorEntityDescription) -> None:
"""Initialize a sensor for an Abode device."""
super().__init__(data, device)
self.entity_description = descriptio... | the_stack_v2_python_sparse | homeassistant/components/abode/sensor.py | konnected-io/home-assistant | train | 24 |
353968c3a6343a5c194548a6c34c8e34bf14885a | [
"super(Psi, self).__init__()\nself.in_emb_dims = in_emb_dims\nself.upsamp = nn.UpsamplingBilinear2d(scale_factor=(2, 2))\nself.upsamp_time = nn.UpsamplingBilinear2d(size=(T, 1))\nout_c = min(in_emb_dims)\nself.c1 = nn.Conv2d(in_emb_dims[0], out_c, kernel_size=3, padding='same')\nself.c2 = nn.Conv2d(in_emb_dims[1], ... | <|body_start_0|>
super(Psi, self).__init__()
self.in_emb_dims = in_emb_dims
self.upsamp = nn.UpsamplingBilinear2d(scale_factor=(2, 2))
self.upsamp_time = nn.UpsamplingBilinear2d(size=(T, 1))
out_c = min(in_emb_dims)
self.c1 = nn.Conv2d(in_emb_dims[0], out_c, kernel_size=3... | Convolutional Layers to estimate NMF Activations from Classifier Representations Arguments --------- n_comp : int Number of NMF components (or equivalently number of neurons at the output per timestep) T: int The targeted length along the time dimension in_emb_dims: List with int elements A list with length 3 that cont... | Psi | [
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference",
"GPL-1.0-or-later",
"LicenseRef-scancode-other-permissive"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Psi:
"""Convolutional Layers to estimate NMF Activations from Classifier Representations Arguments --------- n_comp : int Number of NMF components (or equivalently number of neurons at the output per timestep) T: int The targeted length along the time dimension in_emb_dims: List with int elements... | stack_v2_sparse_classes_10k_train_008934 | 11,147 | permissive | [
{
"docstring": "Computes NMF activations given classifier hidden representations",
"name": "__init__",
"signature": "def __init__(self, n_comp=100, T=431, in_emb_dims=[2048, 1024, 512])"
},
{
"docstring": "This forward function returns the NMF time activations given classifier activations Argume... | 2 | null | Implement the Python class `Psi` described below.
Class description:
Convolutional Layers to estimate NMF Activations from Classifier Representations Arguments --------- n_comp : int Number of NMF components (or equivalently number of neurons at the output per timestep) T: int The targeted length along the time dimens... | Implement the Python class `Psi` described below.
Class description:
Convolutional Layers to estimate NMF Activations from Classifier Representations Arguments --------- n_comp : int Number of NMF components (or equivalently number of neurons at the output per timestep) T: int The targeted length along the time dimens... | 92acc188d3a0f634de58463b6676e70df83ef808 | <|skeleton|>
class Psi:
"""Convolutional Layers to estimate NMF Activations from Classifier Representations Arguments --------- n_comp : int Number of NMF components (or equivalently number of neurons at the output per timestep) T: int The targeted length along the time dimension in_emb_dims: List with int elements... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Psi:
"""Convolutional Layers to estimate NMF Activations from Classifier Representations Arguments --------- n_comp : int Number of NMF components (or equivalently number of neurons at the output per timestep) T: int The targeted length along the time dimension in_emb_dims: List with int elements A list with ... | the_stack_v2_python_sparse | PyTorch/dev/perf/speechbrain-tdnn/speechbrain/lobes/models/L2I.py | Ascend/ModelZoo-PyTorch | train | 23 |
34289ca0ce5ec0431cbe4dbfe9942e3e5fa84c72 | [
"if not value:\n return []\ndelimters = '[, \\\\-!?:\\t]+'\nreturn list(filter(None, re.split(delimters, value)))",
"super(MultiPriceField, self).validate(value)\nif len(value) > 0 and len(value) != 11:\n raise ValidationError('Must have 11 values, separated by commas, spaces or tabs.')\nfor price in value:... | <|body_start_0|>
if not value:
return []
delimters = '[, \\-!?:\t]+'
return list(filter(None, re.split(delimters, value)))
<|end_body_0|>
<|body_start_1|>
super(MultiPriceField, self).validate(value)
if len(value) > 0 and len(value) != 11:
raise Validatio... | MultiPriceField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiPriceField:
def to_python(self, value):
"""Normalize data to a list of strings."""
<|body_0|>
def validate(self, value):
"""Check if value consists only of valid emails."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not value:
... | stack_v2_sparse_classes_10k_train_008935 | 6,902 | no_license | [
{
"docstring": "Normalize data to a list of strings.",
"name": "to_python",
"signature": "def to_python(self, value)"
},
{
"docstring": "Check if value consists only of valid emails.",
"name": "validate",
"signature": "def validate(self, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000280 | Implement the Python class `MultiPriceField` described below.
Class description:
Implement the MultiPriceField class.
Method signatures and docstrings:
- def to_python(self, value): Normalize data to a list of strings.
- def validate(self, value): Check if value consists only of valid emails. | Implement the Python class `MultiPriceField` described below.
Class description:
Implement the MultiPriceField class.
Method signatures and docstrings:
- def to_python(self, value): Normalize data to a list of strings.
- def validate(self, value): Check if value consists only of valid emails.
<|skeleton|>
class Mult... | ebff02b1e6c95b653f027f0e05125b754c6af5af | <|skeleton|>
class MultiPriceField:
def to_python(self, value):
"""Normalize data to a list of strings."""
<|body_0|>
def validate(self, value):
"""Check if value consists only of valid emails."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MultiPriceField:
def to_python(self, value):
"""Normalize data to a list of strings."""
if not value:
return []
delimters = '[, \\-!?:\t]+'
return list(filter(None, re.split(delimters, value)))
def validate(self, value):
"""Check if value consists only ... | the_stack_v2_python_sparse | lcf/forms.py | gamzatti/lcf | train | 0 | |
5cdf4f096f3d83c2a7fc7243e48c06cf07fd4358 | [
"super().setupUI(Form)\nself.label_4 = QtWidgets.QLabel(self.verticalLayoutWidget)\nself.label_4.setToolTip('')\nself.label_4.setAlignment(QtCore.Qt.AlignCenter)\nself.label_4.setObjectName('label_4')\nself.verticalLayout_2.addWidget(self.label_4)\nself.label_8 = QtWidgets.QLabel(self.verticalLayoutWidget)\nself.la... | <|body_start_0|>
super().setupUI(Form)
self.label_4 = QtWidgets.QLabel(self.verticalLayoutWidget)
self.label_4.setToolTip('')
self.label_4.setAlignment(QtCore.Qt.AlignCenter)
self.label_4.setObjectName('label_4')
self.verticalLayout_2.addWidget(self.label_4)
self.... | TMTWindowWidget | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TMTWindowWidget:
def setupUi(self, Form):
"""Método empleado para especificar el contenido de la Interfáz gráfica, es generado por pyuic5. Args: Form: Ventana en la que se deplegará la interfáz gráfica (es un tipo de dato QtWidget.QWidget)"""
<|body_0|>
def retranslateUi(sel... | stack_v2_sparse_classes_10k_train_008936 | 2,685 | no_license | [
{
"docstring": "Método empleado para especificar el contenido de la Interfáz gráfica, es generado por pyuic5. Args: Form: Ventana en la que se deplegará la interfáz gráfica (es un tipo de dato QtWidget.QWidget)",
"name": "setupUi",
"signature": "def setupUi(self, Form)"
},
{
"docstring": "Método... | 2 | stack_v2_sparse_classes_30k_train_004697 | Implement the Python class `TMTWindowWidget` described below.
Class description:
Implement the TMTWindowWidget class.
Method signatures and docstrings:
- def setupUi(self, Form): Método empleado para especificar el contenido de la Interfáz gráfica, es generado por pyuic5. Args: Form: Ventana en la que se deplegará la... | Implement the Python class `TMTWindowWidget` described below.
Class description:
Implement the TMTWindowWidget class.
Method signatures and docstrings:
- def setupUi(self, Form): Método empleado para especificar el contenido de la Interfáz gráfica, es generado por pyuic5. Args: Form: Ventana en la que se deplegará la... | 5d1d68fc4476ed866ecfc305112854d9a49c3876 | <|skeleton|>
class TMTWindowWidget:
def setupUi(self, Form):
"""Método empleado para especificar el contenido de la Interfáz gráfica, es generado por pyuic5. Args: Form: Ventana en la que se deplegará la interfáz gráfica (es un tipo de dato QtWidget.QWidget)"""
<|body_0|>
def retranslateUi(sel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TMTWindowWidget:
def setupUi(self, Form):
"""Método empleado para especificar el contenido de la Interfáz gráfica, es generado por pyuic5. Args: Form: Ventana en la que se deplegará la interfáz gráfica (es un tipo de dato QtWidget.QWidget)"""
super().setupUI(Form)
self.label_4 = QtWidg... | the_stack_v2_python_sparse | src/main/python/vistas/TMTWindowWidget.py | ProyectoIntegrador2018/reportes-neurociencias | train | 1 | |
d70113f927a7cf062be3fa9350b0e2d074ff5909 | [
"self.pump = Pump('127.0.0.1', 8000)\nself.pump.set_state = MagicMock(return_value=True)\nself.new_sensor = Sensor('127.0.0.1', 8000)\nself.new_decider = Decider(100, 0.1)\nself.new_controller = Controller(self.new_sensor, self.pump, self.new_decider)\nself.actions = {'PUMP_IN': self.pump.PUMP_IN, 'PUMP_OUT': self.... | <|body_start_0|>
self.pump = Pump('127.0.0.1', 8000)
self.pump.set_state = MagicMock(return_value=True)
self.new_sensor = Sensor('127.0.0.1', 8000)
self.new_decider = Decider(100, 0.1)
self.new_controller = Controller(self.new_sensor, self.pump, self.new_decider)
self.act... | Unit tests for the Controller class | ControllerTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ControllerTests:
"""Unit tests for the Controller class"""
def setUp(self):
"""Sets the necessary varialbles to test the Controller class"""
<|body_0|>
def test_controller_tick(self):
"""Tests each of the behaviors defined in the Controller class"""
<|bod... | stack_v2_sparse_classes_10k_train_008937 | 5,129 | no_license | [
{
"docstring": "Sets the necessary varialbles to test the Controller class",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Tests each of the behaviors defined in the Controller class",
"name": "test_controller_tick",
"signature": "def test_controller_tick(self)"
}
... | 2 | null | Implement the Python class `ControllerTests` described below.
Class description:
Unit tests for the Controller class
Method signatures and docstrings:
- def setUp(self): Sets the necessary varialbles to test the Controller class
- def test_controller_tick(self): Tests each of the behaviors defined in the Controller c... | Implement the Python class `ControllerTests` described below.
Class description:
Unit tests for the Controller class
Method signatures and docstrings:
- def setUp(self): Sets the necessary varialbles to test the Controller class
- def test_controller_tick(self): Tests each of the behaviors defined in the Controller c... | b1fea0309b3495b3e1dc167d7029bc9e4b6f00f1 | <|skeleton|>
class ControllerTests:
"""Unit tests for the Controller class"""
def setUp(self):
"""Sets the necessary varialbles to test the Controller class"""
<|body_0|>
def test_controller_tick(self):
"""Tests each of the behaviors defined in the Controller class"""
<|bod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ControllerTests:
"""Unit tests for the Controller class"""
def setUp(self):
"""Sets the necessary varialbles to test the Controller class"""
self.pump = Pump('127.0.0.1', 8000)
self.pump.set_state = MagicMock(return_value=True)
self.new_sensor = Sensor('127.0.0.1', 8000)
... | the_stack_v2_python_sparse | students/rob_sanchez/lesson_06/Water_Regulation/waterregulation/test.py | UWPCE-PythonCert-ClassRepos/SP_Online_Course2_2018 | train | 4 |
af2524f76b65ebca9fda2884b50c2495fd1745f5 | [
"s = croc_scan.Scanner()\nself.assertEqual(s.re_token.pattern, '#')\nself.assertEqual(s.comment_to_eol, ['#'])\nself.assertEqual(s.comment_start, None)\nself.assertEqual(s.comment_end, None)",
"s = croc_scan.Scanner()\ns.re_token = re.compile('([\\\\:\\\\\"\\\\(\\\\)])')\ns.comment_to_eol = [':']\ns.comment_start... | <|body_start_0|>
s = croc_scan.Scanner()
self.assertEqual(s.re_token.pattern, '#')
self.assertEqual(s.comment_to_eol, ['#'])
self.assertEqual(s.comment_start, None)
self.assertEqual(s.comment_end, None)
<|end_body_0|>
<|body_start_1|>
s = croc_scan.Scanner()
s.re... | Tests for croc_scan.Scanner. | TestScanner | [
"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 TestScanner:
"""Tests for croc_scan.Scanner."""
def testInit(self):
"""Test __init()__."""
<|body_0|>
def testScanLines(self):
"""Test ScanLines()."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s = croc_scan.Scanner()
self.assertEqual(... | stack_v2_sparse_classes_10k_train_008938 | 7,181 | permissive | [
{
"docstring": "Test __init()__.",
"name": "testInit",
"signature": "def testInit(self)"
},
{
"docstring": "Test ScanLines().",
"name": "testScanLines",
"signature": "def testScanLines(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004501 | Implement the Python class `TestScanner` described below.
Class description:
Tests for croc_scan.Scanner.
Method signatures and docstrings:
- def testInit(self): Test __init()__.
- def testScanLines(self): Test ScanLines(). | Implement the Python class `TestScanner` described below.
Class description:
Tests for croc_scan.Scanner.
Method signatures and docstrings:
- def testInit(self): Test __init()__.
- def testScanLines(self): Test ScanLines().
<|skeleton|>
class TestScanner:
"""Tests for croc_scan.Scanner."""
def testInit(self... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class TestScanner:
"""Tests for croc_scan.Scanner."""
def testInit(self):
"""Test __init()__."""
<|body_0|>
def testScanLines(self):
"""Test ScanLines()."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestScanner:
"""Tests for croc_scan.Scanner."""
def testInit(self):
"""Test __init()__."""
s = croc_scan.Scanner()
self.assertEqual(s.re_token.pattern, '#')
self.assertEqual(s.comment_to_eol, ['#'])
self.assertEqual(s.comment_start, None)
self.assertEqual(s... | the_stack_v2_python_sparse | tools/code_coverage/croc_scan_test.py | metux/chromium-suckless | train | 5 |
a40e36424bdf0dac7ef3b258ce27876cfa3de4de | [
"self.host = host\nself.integral_volume_names = integral_volume_names\nself.password = password\nself.port = port\nself.share_type = share_type\nself.use_https = use_https\nself.username = username",
"if dictionary is None:\n return None\nhost = dictionary.get('host')\nintegral_volume_names = dictionary.get('i... | <|body_start_0|>
self.host = host
self.integral_volume_names = integral_volume_names
self.password = password
self.port = port
self.share_type = share_type
self.use_https = use_https
self.username = username
<|end_body_0|>
<|body_start_1|>
if dictionary i... | Implementation of the 'QStarServerCredentials' model. Specifies the server credentials to connect to a QStar service to manage the media Vault. Attributes: host (string): Specifies the IP address or DNS name of the server where QStar service is running. integral_volume_names (list of string): Array of Integral Volume N... | QStarServerCredentials | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QStarServerCredentials:
"""Implementation of the 'QStarServerCredentials' model. Specifies the server credentials to connect to a QStar service to manage the media Vault. Attributes: host (string): Specifies the IP address or DNS name of the server where QStar service is running. integral_volume_... | stack_v2_sparse_classes_10k_train_008939 | 3,345 | permissive | [
{
"docstring": "Constructor for the QStarServerCredentials class",
"name": "__init__",
"signature": "def __init__(self, host=None, integral_volume_names=None, password=None, port=None, share_type=None, use_https=None, username=None)"
},
{
"docstring": "Creates an instance of this model from a di... | 2 | null | Implement the Python class `QStarServerCredentials` described below.
Class description:
Implementation of the 'QStarServerCredentials' model. Specifies the server credentials to connect to a QStar service to manage the media Vault. Attributes: host (string): Specifies the IP address or DNS name of the server where QSt... | Implement the Python class `QStarServerCredentials` described below.
Class description:
Implementation of the 'QStarServerCredentials' model. Specifies the server credentials to connect to a QStar service to manage the media Vault. Attributes: host (string): Specifies the IP address or DNS name of the server where QSt... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class QStarServerCredentials:
"""Implementation of the 'QStarServerCredentials' model. Specifies the server credentials to connect to a QStar service to manage the media Vault. Attributes: host (string): Specifies the IP address or DNS name of the server where QStar service is running. integral_volume_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QStarServerCredentials:
"""Implementation of the 'QStarServerCredentials' model. Specifies the server credentials to connect to a QStar service to manage the media Vault. Attributes: host (string): Specifies the IP address or DNS name of the server where QStar service is running. integral_volume_names (list o... | the_stack_v2_python_sparse | cohesity_management_sdk/models/q_star_server_credentials.py | cohesity/management-sdk-python | train | 24 |
a466d4e73543c0124692b9e4c4b8ad714b5a82ec | [
"interval = self.coordinator.data[self.entity_description.key][self.channel_type]\nif interval.channel_type == ChannelType.FEED_IN:\n return format_cents_to_dollars(interval.per_kwh) * -1\nreturn format_cents_to_dollars(interval.per_kwh)",
"interval = self.coordinator.data[self.entity_description.key][self.cha... | <|body_start_0|>
interval = self.coordinator.data[self.entity_description.key][self.channel_type]
if interval.channel_type == ChannelType.FEED_IN:
return format_cents_to_dollars(interval.per_kwh) * -1
return format_cents_to_dollars(interval.per_kwh)
<|end_body_0|>
<|body_start_1|>
... | Amber Price Sensor. | AmberPriceSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AmberPriceSensor:
"""Amber Price Sensor."""
def native_value(self) -> float | None:
"""Return the current price in $/kWh."""
<|body_0|>
def extra_state_attributes(self) -> Mapping[str, Any] | None:
"""Return additional pieces of information about the price."""
... | stack_v2_sparse_classes_10k_train_008940 | 9,224 | permissive | [
{
"docstring": "Return the current price in $/kWh.",
"name": "native_value",
"signature": "def native_value(self) -> float | None"
},
{
"docstring": "Return additional pieces of information about the price.",
"name": "extra_state_attributes",
"signature": "def extra_state_attributes(self... | 2 | stack_v2_sparse_classes_30k_train_000274 | Implement the Python class `AmberPriceSensor` described below.
Class description:
Amber Price Sensor.
Method signatures and docstrings:
- def native_value(self) -> float | None: Return the current price in $/kWh.
- def extra_state_attributes(self) -> Mapping[str, Any] | None: Return additional pieces of information a... | Implement the Python class `AmberPriceSensor` described below.
Class description:
Amber Price Sensor.
Method signatures and docstrings:
- def native_value(self) -> float | None: Return the current price in $/kWh.
- def extra_state_attributes(self) -> Mapping[str, Any] | None: Return additional pieces of information a... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class AmberPriceSensor:
"""Amber Price Sensor."""
def native_value(self) -> float | None:
"""Return the current price in $/kWh."""
<|body_0|>
def extra_state_attributes(self) -> Mapping[str, Any] | None:
"""Return additional pieces of information about the price."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AmberPriceSensor:
"""Amber Price Sensor."""
def native_value(self) -> float | None:
"""Return the current price in $/kWh."""
interval = self.coordinator.data[self.entity_description.key][self.channel_type]
if interval.channel_type == ChannelType.FEED_IN:
return format_... | the_stack_v2_python_sparse | homeassistant/components/amberelectric/sensor.py | home-assistant/core | train | 35,501 |
e4d45fe7dbdcd1656deed30e63b78e90b9b129cb | [
"params = super().get_default_params(with_embedding=True, with_multi_layer_perceptron=True)\nparams.add(Param(name='lstm_hidden_size', value=5, desc='Integer, the hidden size of the bi-directional LSTM layer.'))\nparams.add(Param(name='lstm_num', value=3, desc='Integer, number of LSTM units'))\nparams.add(Param(nam... | <|body_start_0|>
params = super().get_default_params(with_embedding=True, with_multi_layer_perceptron=True)
params.add(Param(name='lstm_hidden_size', value=5, desc='Integer, the hidden size of the bi-directional LSTM layer.'))
params.add(Param(name='lstm_num', value=3, desc='Integer, number of L... | HBMP model. Examples: >>> model = HBMP() >>> model.params['embedding_input_dim'] = 200 >>> model.params['embedding_output_dim'] = 100 >>> model.params['mlp_num_layers'] = 1 >>> model.params['mlp_num_units'] = 10 >>> model.params['mlp_num_fan_out'] = 10 >>> model.params['mlp_activation_func'] = nn.LeakyReLU(0.1) >>> mod... | HBMP | [
"MIT",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-proprietary-license",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference",
"LGPL-2.1-or-later",
"Apache-2.0",
"LicenseRef-scancode-public-domain",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HBMP:
"""HBMP model. Examples: >>> model = HBMP() >>> model.params['embedding_input_dim'] = 200 >>> model.params['embedding_output_dim'] = 100 >>> model.params['mlp_num_layers'] = 1 >>> model.params['mlp_num_units'] = 10 >>> model.params['mlp_num_fan_out'] = 10 >>> model.params['mlp_activation_fu... | stack_v2_sparse_classes_10k_train_008941 | 4,584 | permissive | [
{
"docstring": ":return: model default parameters.",
"name": "get_default_params",
"signature": "def get_default_params(cls) -> ParamTable"
},
{
"docstring": "Build model structure. HBMP use Siamese arthitecture.",
"name": "build",
"signature": "def build(self)"
},
{
"docstring":... | 3 | stack_v2_sparse_classes_30k_train_000194 | Implement the Python class `HBMP` described below.
Class description:
HBMP model. Examples: >>> model = HBMP() >>> model.params['embedding_input_dim'] = 200 >>> model.params['embedding_output_dim'] = 100 >>> model.params['mlp_num_layers'] = 1 >>> model.params['mlp_num_units'] = 10 >>> model.params['mlp_num_fan_out'] =... | Implement the Python class `HBMP` described below.
Class description:
HBMP model. Examples: >>> model = HBMP() >>> model.params['embedding_input_dim'] = 200 >>> model.params['embedding_output_dim'] = 100 >>> model.params['mlp_num_layers'] = 1 >>> model.params['mlp_num_units'] = 10 >>> model.params['mlp_num_fan_out'] =... | 4198ebce942f4afe7ddca6a96ab6f4464ade4518 | <|skeleton|>
class HBMP:
"""HBMP model. Examples: >>> model = HBMP() >>> model.params['embedding_input_dim'] = 200 >>> model.params['embedding_output_dim'] = 100 >>> model.params['mlp_num_layers'] = 1 >>> model.params['mlp_num_units'] = 10 >>> model.params['mlp_num_fan_out'] = 10 >>> model.params['mlp_activation_fu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HBMP:
"""HBMP model. Examples: >>> model = HBMP() >>> model.params['embedding_input_dim'] = 200 >>> model.params['embedding_output_dim'] = 100 >>> model.params['mlp_num_layers'] = 1 >>> model.params['mlp_num_units'] = 10 >>> model.params['mlp_num_fan_out'] = 10 >>> model.params['mlp_activation_func'] = nn.Lea... | the_stack_v2_python_sparse | poset_decoding/traversal_path_prediction/MatchZoo-py/matchzoo/models/hbmp.py | microsoft/ContextualSP | train | 332 |
e89a149388e0a425974768dfe727f30a495ec9f8 | [
"value = '<div>'\nclase = 'actions_fase'\ncontroller = './'\nif UrlParser.parse_nombre(request.url, 'post_buscar'):\n controller = '../'\nid_fase = UrlParser.parse_id(request.url, 'fases')\nid = str(obj.id_lb)\nif PoseePermiso('abrir-cerrar lb', id_fase=id_fase).is_met(request.environ):\n if obj.estado in [u'... | <|body_start_0|>
value = '<div>'
clase = 'actions_fase'
controller = './'
if UrlParser.parse_nombre(request.url, 'post_buscar'):
controller = '../'
id_fase = UrlParser.parse_id(request.url, 'fases')
id = str(obj.id_lb)
if PoseePermiso('abrir-cerrar lb'... | LineaBaseTableFiller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LineaBaseTableFiller:
def __actions__(self, obj):
"""Links de acciones para un registro dado"""
<|body_0|>
def _do_get_provider_count_and_objs(self, id_fase=None, id_lb=None, **kw):
"""Recupera las lineas bases de una fase, o aquellas para las que tenemos algún permi... | stack_v2_sparse_classes_10k_train_008942 | 21,724 | no_license | [
{
"docstring": "Links de acciones para un registro dado",
"name": "__actions__",
"signature": "def __actions__(self, obj)"
},
{
"docstring": "Recupera las lineas bases de una fase, o aquellas para las que tenemos algún permiso.",
"name": "_do_get_provider_count_and_objs",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_006739 | Implement the Python class `LineaBaseTableFiller` described below.
Class description:
Implement the LineaBaseTableFiller class.
Method signatures and docstrings:
- def __actions__(self, obj): Links de acciones para un registro dado
- def _do_get_provider_count_and_objs(self, id_fase=None, id_lb=None, **kw): Recupera ... | Implement the Python class `LineaBaseTableFiller` described below.
Class description:
Implement the LineaBaseTableFiller class.
Method signatures and docstrings:
- def __actions__(self, obj): Links de acciones para un registro dado
- def _do_get_provider_count_and_objs(self, id_fase=None, id_lb=None, **kw): Recupera ... | 997531e130d1951b483f4a6a67f2df7467cd9fd1 | <|skeleton|>
class LineaBaseTableFiller:
def __actions__(self, obj):
"""Links de acciones para un registro dado"""
<|body_0|>
def _do_get_provider_count_and_objs(self, id_fase=None, id_lb=None, **kw):
"""Recupera las lineas bases de una fase, o aquellas para las que tenemos algún permi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LineaBaseTableFiller:
def __actions__(self, obj):
"""Links de acciones para un registro dado"""
value = '<div>'
clase = 'actions_fase'
controller = './'
if UrlParser.parse_nombre(request.url, 'post_buscar'):
controller = '../'
id_fase = UrlParser.par... | the_stack_v2_python_sparse | lpm/controllers/lineabase.py | jorgeramirez/LPM | train | 1 | |
f0fb1b4387b455604fa3d01f6c93bdedb8d29991 | [
"shape = np.array([2, 3, 4])\ndata = np.zeros(shape)\ngraph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges, update_nodes_attributes=[('data_node', {'shape': shape, 'value': data})])\ngraph_ref = build_graph_with_attrs(nodes_with_attrs=self.nodes + self.new_nodes, edges_with_attrs=... | <|body_start_0|>
shape = np.array([2, 3, 4])
data = np.zeros(shape)
graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges, update_nodes_attributes=[('data_node', {'shape': shape, 'value': data})])
graph_ref = build_graph_with_attrs(nodes_with_attrs=self.... | CreateConstNodesReplacementTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateConstNodesReplacementTest:
def test_one_node(self):
"""We should add Const node and data node."""
<|body_0|>
def test_one_bin_node(self):
"""Nothing should happen."""
<|body_1|>
def test_two_nodes_with_bin(self):
"""Test case for data node ... | stack_v2_sparse_classes_10k_train_008943 | 4,410 | permissive | [
{
"docstring": "We should add Const node and data node.",
"name": "test_one_node",
"signature": "def test_one_node(self)"
},
{
"docstring": "Nothing should happen.",
"name": "test_one_bin_node",
"signature": "def test_one_bin_node(self)"
},
{
"docstring": "Test case for data node... | 4 | null | Implement the Python class `CreateConstNodesReplacementTest` described below.
Class description:
Implement the CreateConstNodesReplacementTest class.
Method signatures and docstrings:
- def test_one_node(self): We should add Const node and data node.
- def test_one_bin_node(self): Nothing should happen.
- def test_tw... | Implement the Python class `CreateConstNodesReplacementTest` described below.
Class description:
Implement the CreateConstNodesReplacementTest class.
Method signatures and docstrings:
- def test_one_node(self): We should add Const node and data node.
- def test_one_bin_node(self): Nothing should happen.
- def test_tw... | e4bed7a31c9f00d8afbfcabee3f64f55496ae56a | <|skeleton|>
class CreateConstNodesReplacementTest:
def test_one_node(self):
"""We should add Const node and data node."""
<|body_0|>
def test_one_bin_node(self):
"""Nothing should happen."""
<|body_1|>
def test_two_nodes_with_bin(self):
"""Test case for data node ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CreateConstNodesReplacementTest:
def test_one_node(self):
"""We should add Const node and data node."""
shape = np.array([2, 3, 4])
data = np.zeros(shape)
graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges, update_nodes_attributes=[('data_no... | the_stack_v2_python_sparse | tools/mo/unit_tests/mo/back/SpecialNodesFinalization_test.py | openvinotoolkit/openvino | train | 3,953 | |
c1523587f90bc9a42b5173aea128d555c4bb7912 | [
"super().__init__(**kwargs)\nself.magnitude = magnitude\nself.n_transforms = n_transforms\nself._max_magnitude = 10.0\nself._max_x_shift = 0.1\nself._max_y_shift = 0.2\nself._max_angle = 30\nself._max_contrast = 1\nself._max_brightness = 1",
"level = self.magnitude / self._max_magnitude\nangle = self.randomly_neg... | <|body_start_0|>
super().__init__(**kwargs)
self.magnitude = magnitude
self.n_transforms = n_transforms
self._max_magnitude = 10.0
self._max_x_shift = 0.1
self._max_y_shift = 0.2
self._max_angle = 30
self._max_contrast = 1
self._max_brightness = 1
... | Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additional transformations for images are brightness adjustment and contrast adjustment. | RandAugmentSlice | [
"MIT",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandAugmentSlice:
"""Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additional transformations for images are bri... | stack_v2_sparse_classes_10k_train_008944 | 19,979 | permissive | [
{
"docstring": ":param magnitude: magnitude to apply to the transformations as defined in the RandAugment paper. 1 means a weak transform, 10 is the strongest transform. :param n_transforms: number of transformation to sample for each image.",
"name": "__init__",
"signature": "def __init__(self, magnitu... | 3 | stack_v2_sparse_classes_30k_train_000108 | Implement the Python class `RandAugmentSlice` described below.
Class description:
Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additi... | Implement the Python class `RandAugmentSlice` described below.
Class description:
Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additi... | 12b496093097ef48d5ac8880985c04918d7f76fe | <|skeleton|>
class RandAugmentSlice:
"""Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additional transformations for images are bri... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RandAugmentSlice:
"""Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additional transformations for images are brightness adjus... | the_stack_v2_python_sparse | InnerEye/ML/utils/augmentation.py | MaxCodeXTC/InnerEye-DeepLearning | train | 1 |
c8b07211370c3be9387017c9972b29c7c02acdc7 | [
"super(Net, self).__init__()\nself.cfgs = cfgs\nself.simclr = SimCLR(cfgs)\nself.backbone = BAN(cfgs)\nlayers = [weight_norm(nn.Linear(cfgs.hidden_size, cfgs.flat_out_size), dim=None), nn.ReLU(), nn.Dropout(cfgs.classifer_dropout_r, inplace=True)]\nself.flatten = nn.Sequential(*layers)\nlayers_classifer = [weight_n... | <|body_start_0|>
super(Net, self).__init__()
self.cfgs = cfgs
self.simclr = SimCLR(cfgs)
self.backbone = BAN(cfgs)
layers = [weight_norm(nn.Linear(cfgs.hidden_size, cfgs.flat_out_size), dim=None), nn.ReLU(), nn.Dropout(cfgs.classifer_dropout_r, inplace=True)]
self.flatten... | Net | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Net:
def __init__(self, cfgs):
""":param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table."""
<|body_0|>
def forward(self, que_emb, dia_f, opt_emb, dia_matrix, dia_node_emb, cfg):
""":param que_ix: the index of ques... | stack_v2_sparse_classes_10k_train_008945 | 2,507 | no_license | [
{
"docstring": ":param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table.",
"name": "__init__",
"signature": "def __init__(self, cfgs)"
},
{
"docstring": ":param que_ix: the index of questions :param opt_ix: the index of options :param dia: the ... | 2 | stack_v2_sparse_classes_30k_train_000257 | Implement the Python class `Net` described below.
Class description:
Implement the Net class.
Method signatures and docstrings:
- def __init__(self, cfgs): :param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table.
- def forward(self, que_emb, dia_f, opt_emb, dia_matr... | Implement the Python class `Net` described below.
Class description:
Implement the Net class.
Method signatures and docstrings:
- def __init__(self, cfgs): :param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table.
- def forward(self, que_emb, dia_f, opt_emb, dia_matr... | 7b2d913fa70e3520d9055c9493ca640cf30892b9 | <|skeleton|>
class Net:
def __init__(self, cfgs):
""":param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table."""
<|body_0|>
def forward(self, que_emb, dia_f, opt_emb, dia_matrix, dia_node_emb, cfg):
""":param que_ix: the index of ques... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Net:
def __init__(self, cfgs):
""":param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table."""
super(Net, self).__init__()
self.cfgs = cfgs
self.simclr = SimCLR(cfgs)
self.backbone = BAN(cfgs)
layers = [weight_n... | the_stack_v2_python_sparse | model/ban_csdia/net.py | dr-majie/2019-mytqa | train | 3 | |
5387360372fa674be695cc9aa2ef1c0cb4c8a047 | [
"seq1 = 'AAAA'\nres = geneutil.sequenceEntropy(seq1)\nself.assertAlmostEqual(res.entropy, 0.0)\nself.assertTrue(res.counts['A'] == 4)",
"seq1 = 'ACDEFGHIKLMNPQRSTVWY'\nres = geneutil.sequenceEntropy(seq1, base=20)\nself.assertAlmostEqual(res.entropy, 1.0)\nfor aa in seq1:\n self.assertTrue(res.counts[aa] == 1)... | <|body_start_0|>
seq1 = 'AAAA'
res = geneutil.sequenceEntropy(seq1)
self.assertAlmostEqual(res.entropy, 0.0)
self.assertTrue(res.counts['A'] == 4)
<|end_body_0|>
<|body_start_1|>
seq1 = 'ACDEFGHIKLMNPQRSTVWY'
res = geneutil.sequenceEntropy(seq1, base=20)
self.ass... | test004 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test004:
def test_entropy(self):
"""Entropy of a homopolymer"""
<|body_0|>
def test_max_entropy(self):
"""Maximum possible entropy"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
seq1 = 'AAAA'
res = geneutil.sequenceEntropy(seq1)
sel... | stack_v2_sparse_classes_10k_train_008946 | 2,692 | no_license | [
{
"docstring": "Entropy of a homopolymer",
"name": "test_entropy",
"signature": "def test_entropy(self)"
},
{
"docstring": "Maximum possible entropy",
"name": "test_max_entropy",
"signature": "def test_max_entropy(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000209 | Implement the Python class `test004` described below.
Class description:
Implement the test004 class.
Method signatures and docstrings:
- def test_entropy(self): Entropy of a homopolymer
- def test_max_entropy(self): Maximum possible entropy | Implement the Python class `test004` described below.
Class description:
Implement the test004 class.
Method signatures and docstrings:
- def test_entropy(self): Entropy of a homopolymer
- def test_max_entropy(self): Maximum possible entropy
<|skeleton|>
class test004:
def test_entropy(self):
"""Entropy... | d7ddd2b585a841c6d986974a24a53e4d1abe71ba | <|skeleton|>
class test004:
def test_entropy(self):
"""Entropy of a homopolymer"""
<|body_0|>
def test_max_entropy(self):
"""Maximum possible entropy"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class test004:
def test_entropy(self):
"""Entropy of a homopolymer"""
seq1 = 'AAAA'
res = geneutil.sequenceEntropy(seq1)
self.assertAlmostEqual(res.entropy, 0.0)
self.assertTrue(res.counts['A'] == 4)
def test_max_entropy(self):
"""Maximum possible entropy"""
... | the_stack_v2_python_sparse | src/geneutil_test.py | dad/base | train | 0 | |
abe63f9aa466b4d1cff570cff8aceede68f93805 | [
"self.res = 0\nself.nums = sorted(nums, reverse=True)\n\ndef deeper(target_sum, current_index):\n print(target_sum, current_index)\n if current_index == len(self.nums):\n if target_sum == 0:\n self.res += 1\n cache[target_sum, current_index] = True\n return True\n ... | <|body_start_0|>
self.res = 0
self.nums = sorted(nums, reverse=True)
def deeper(target_sum, current_index):
print(target_sum, current_index)
if current_index == len(self.nums):
if target_sum == 0:
self.res += 1
cach... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findTargetSumWays1(self, nums, S):
""":type nums: List[int] :type S: int :rtype: int"""
<|body_0|>
def findTargetSumWays(self, nums, S):
"""第二次做的时候发现上面那个结果不对了是什么鬼"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.res = 0
sel... | stack_v2_sparse_classes_10k_train_008947 | 2,364 | no_license | [
{
"docstring": ":type nums: List[int] :type S: int :rtype: int",
"name": "findTargetSumWays1",
"signature": "def findTargetSumWays1(self, nums, S)"
},
{
"docstring": "第二次做的时候发现上面那个结果不对了是什么鬼",
"name": "findTargetSumWays",
"signature": "def findTargetSumWays(self, nums, S)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTargetSumWays1(self, nums, S): :type nums: List[int] :type S: int :rtype: int
- def findTargetSumWays(self, nums, S): 第二次做的时候发现上面那个结果不对了是什么鬼 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTargetSumWays1(self, nums, S): :type nums: List[int] :type S: int :rtype: int
- def findTargetSumWays(self, nums, S): 第二次做的时候发现上面那个结果不对了是什么鬼
<|skeleton|>
class Solution:... | 97533d53c8892b6519e99f344489fa4fd4c9ab93 | <|skeleton|>
class Solution:
def findTargetSumWays1(self, nums, S):
""":type nums: List[int] :type S: int :rtype: int"""
<|body_0|>
def findTargetSumWays(self, nums, S):
"""第二次做的时候发现上面那个结果不对了是什么鬼"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findTargetSumWays1(self, nums, S):
""":type nums: List[int] :type S: int :rtype: int"""
self.res = 0
self.nums = sorted(nums, reverse=True)
def deeper(target_sum, current_index):
print(target_sum, current_index)
if current_index == len(sel... | the_stack_v2_python_sparse | 2. DFS/494.py | proTao/leetcode | train | 0 | |
1151650be6e24ccde1faed55433809427ce2bc60 | [
"super().__init__()\nself.embed_dim = embed_dim\nself.k_embed_size = kdim if kdim else embed_dim\nself.v_embed_size = vdim if vdim else embed_dim\nself.num_heads = num_attn_heads\nself.attention_dropout = dropout\nself.head_embed_size = embed_dim // num_attn_heads\nself.head_scaling = math.sqrt(self.head_embed_size... | <|body_start_0|>
super().__init__()
self.embed_dim = embed_dim
self.k_embed_size = kdim if kdim else embed_dim
self.v_embed_size = vdim if vdim else embed_dim
self.num_heads = num_attn_heads
self.attention_dropout = dropout
self.head_embed_size = embed_dim // num_... | Multi-Head Attention | MultiHeadAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadAttention:
"""Multi-Head Attention"""
def __init__(self, embed_dim, num_attn_heads, kdim=None, vdim=None, dropout=0.0, self_attention=False, encoder_decoder_attention=False):
"""___QUESTION-7-MULTIHEAD-ATTENTION-NOTE You shouldn't need to change the __init__ of this class fo... | stack_v2_sparse_classes_10k_train_008948 | 28,210 | no_license | [
{
"docstring": "___QUESTION-7-MULTIHEAD-ATTENTION-NOTE You shouldn't need to change the __init__ of this class for your attention implementation",
"name": "__init__",
"signature": "def __init__(self, embed_dim, num_attn_heads, kdim=None, vdim=None, dropout=0.0, self_attention=False, encoder_decoder_atte... | 2 | stack_v2_sparse_classes_30k_train_000990 | Implement the Python class `MultiHeadAttention` described below.
Class description:
Multi-Head Attention
Method signatures and docstrings:
- def __init__(self, embed_dim, num_attn_heads, kdim=None, vdim=None, dropout=0.0, self_attention=False, encoder_decoder_attention=False): ___QUESTION-7-MULTIHEAD-ATTENTION-NOTE Y... | Implement the Python class `MultiHeadAttention` described below.
Class description:
Multi-Head Attention
Method signatures and docstrings:
- def __init__(self, embed_dim, num_attn_heads, kdim=None, vdim=None, dropout=0.0, self_attention=False, encoder_decoder_attention=False): ___QUESTION-7-MULTIHEAD-ATTENTION-NOTE Y... | 7f109bcf3cc17d2c669e18fb2ad3357aa4e0fc2e | <|skeleton|>
class MultiHeadAttention:
"""Multi-Head Attention"""
def __init__(self, embed_dim, num_attn_heads, kdim=None, vdim=None, dropout=0.0, self_attention=False, encoder_decoder_attention=False):
"""___QUESTION-7-MULTIHEAD-ATTENTION-NOTE You shouldn't need to change the __init__ of this class fo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MultiHeadAttention:
"""Multi-Head Attention"""
def __init__(self, embed_dim, num_attn_heads, kdim=None, vdim=None, dropout=0.0, self_attention=False, encoder_decoder_attention=False):
"""___QUESTION-7-MULTIHEAD-ATTENTION-NOTE You shouldn't need to change the __init__ of this class for your attent... | the_stack_v2_python_sparse | NLG/table/modules/Transformer.py | Lyz1213/msc_dissertation | train | 2 |
fe6f208cddc84bea8d5bca52e0bc3c6d2764cfcc | [
"tests = ['KIF.test1', 'KIF.test2']\nexpected = 'NAME:test1|test2'\nself.assertEqual(test_runner.get_kif_test_filter(tests), expected)",
"tests = ['KIF.test1', 'KIF.test2']\nexpected = '-NAME:test1|test2'\nself.assertEqual(test_runner.get_kif_test_filter(tests, invert=True), expected)"
] | <|body_start_0|>
tests = ['KIF.test1', 'KIF.test2']
expected = 'NAME:test1|test2'
self.assertEqual(test_runner.get_kif_test_filter(tests), expected)
<|end_body_0|>
<|body_start_1|>
tests = ['KIF.test1', 'KIF.test2']
expected = '-NAME:test1|test2'
self.assertEqual(test_ru... | Tests for test_runner.get_kif_test_filter. | GetKIFTestFilterTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetKIFTestFilterTest:
"""Tests for test_runner.get_kif_test_filter."""
def test_correct(self):
"""Ensures correctness of filter."""
<|body_0|>
def test_correct_inverted(self):
"""Ensures correctness of inverted filter."""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_10k_train_008949 | 19,298 | permissive | [
{
"docstring": "Ensures correctness of filter.",
"name": "test_correct",
"signature": "def test_correct(self)"
},
{
"docstring": "Ensures correctness of inverted filter.",
"name": "test_correct_inverted",
"signature": "def test_correct_inverted(self)"
}
] | 2 | null | Implement the Python class `GetKIFTestFilterTest` described below.
Class description:
Tests for test_runner.get_kif_test_filter.
Method signatures and docstrings:
- def test_correct(self): Ensures correctness of filter.
- def test_correct_inverted(self): Ensures correctness of inverted filter. | Implement the Python class `GetKIFTestFilterTest` described below.
Class description:
Tests for test_runner.get_kif_test_filter.
Method signatures and docstrings:
- def test_correct(self): Ensures correctness of filter.
- def test_correct_inverted(self): Ensures correctness of inverted filter.
<|skeleton|>
class Get... | 4896f732fc747dfdcfcbac3d442f2d2d42df264a | <|skeleton|>
class GetKIFTestFilterTest:
"""Tests for test_runner.get_kif_test_filter."""
def test_correct(self):
"""Ensures correctness of filter."""
<|body_0|>
def test_correct_inverted(self):
"""Ensures correctness of inverted filter."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GetKIFTestFilterTest:
"""Tests for test_runner.get_kif_test_filter."""
def test_correct(self):
"""Ensures correctness of filter."""
tests = ['KIF.test1', 'KIF.test2']
expected = 'NAME:test1|test2'
self.assertEqual(test_runner.get_kif_test_filter(tests), expected)
def ... | the_stack_v2_python_sparse | ios/build/bots/scripts/test_runner_test.py | Samsung/Castanets | train | 58 |
ae2442c4d6ad0fb664be80d134e8bc7feeee63a7 | [
"if decay_time <= datetime.timedelta(0):\n raise ValueError('decay_time must have positive duration')\nself.decay_time = decay_time\nself.decay_factor = decay_factor",
"timestamp, x = value\nif now is None:\n now = datetime.datetime.utcnow()\ndelta = now - timestamp\nif delta < datetime.timedelta(seconds=0)... | <|body_start_0|>
if decay_time <= datetime.timedelta(0):
raise ValueError('decay_time must have positive duration')
self.decay_time = decay_time
self.decay_factor = decay_factor
<|end_body_0|>
<|body_start_1|>
timestamp, x = value
if now is None:
now = da... | TimeDecay class. Helps to update counters that require a time decay | TimeDecay | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeDecay:
"""TimeDecay class. Helps to update counters that require a time decay"""
def __init__(self, decay_time, decay_factor=2.0):
"""decay_time is timedelta"""
<|body_0|>
def update_value(self, value, now=None):
"""Computes the updated value for the given ha... | stack_v2_sparse_classes_10k_train_008950 | 1,847 | permissive | [
{
"docstring": "decay_time is timedelta",
"name": "__init__",
"signature": "def __init__(self, decay_time, decay_factor=2.0)"
},
{
"docstring": "Computes the updated value for the given half-life. Args: value (tuple(datetime.datetime, numeric_type)): tuple with the numeric value we wish to updat... | 2 | stack_v2_sparse_classes_30k_val_000097 | Implement the Python class `TimeDecay` described below.
Class description:
TimeDecay class. Helps to update counters that require a time decay
Method signatures and docstrings:
- def __init__(self, decay_time, decay_factor=2.0): decay_time is timedelta
- def update_value(self, value, now=None): Computes the updated v... | Implement the Python class `TimeDecay` described below.
Class description:
TimeDecay class. Helps to update counters that require a time decay
Method signatures and docstrings:
- def __init__(self, decay_time, decay_factor=2.0): decay_time is timedelta
- def update_value(self, value, now=None): Computes the updated v... | 70280110ec342a6f6db1c102e96756fcc3c3c01b | <|skeleton|>
class TimeDecay:
"""TimeDecay class. Helps to update counters that require a time decay"""
def __init__(self, decay_time, decay_factor=2.0):
"""decay_time is timedelta"""
<|body_0|>
def update_value(self, value, now=None):
"""Computes the updated value for the given ha... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TimeDecay:
"""TimeDecay class. Helps to update counters that require a time decay"""
def __init__(self, decay_time, decay_factor=2.0):
"""decay_time is timedelta"""
if decay_time <= datetime.timedelta(0):
raise ValueError('decay_time must have positive duration')
self.... | the_stack_v2_python_sparse | pylib/util/time_decay.py | room77/py77 | train | 0 |
6d9edcf9b1f284086145d9c9b78943b0aca8dbe8 | [
"if last_state is not None and last_state.state is not None:\n if last_state.state == STATE_ON:\n self._attr_is_on = True\n elif last_state.state == STATE_OFF:\n self._attr_is_on = False\n elif last_state.state == STATE_UNAVAILABLE:\n self._attr_available = False",
"new_state = None\... | <|body_start_0|>
if last_state is not None and last_state.state is not None:
if last_state.state == STATE_ON:
self._attr_is_on = True
elif last_state.state == STATE_OFF:
self._attr_is_on = False
elif last_state.state == STATE_UNAVAILABLE:
... | Class for SIA Binary Sensors. | SIABinarySensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SIABinarySensor:
"""Class for SIA Binary Sensors."""
def handle_last_state(self, last_state: State | None) -> None:
"""Handle the last state."""
<|body_0|>
def update_state(self, sia_event: SIAEvent) -> bool:
"""Update the state of the binary sensor. Return True ... | stack_v2_sparse_classes_10k_train_008951 | 4,615 | permissive | [
{
"docstring": "Handle the last state.",
"name": "handle_last_state",
"signature": "def handle_last_state(self, last_state: State | None) -> None"
},
{
"docstring": "Update the state of the binary sensor. Return True if the event was relevant for this entity.",
"name": "update_state",
"s... | 2 | null | Implement the Python class `SIABinarySensor` described below.
Class description:
Class for SIA Binary Sensors.
Method signatures and docstrings:
- def handle_last_state(self, last_state: State | None) -> None: Handle the last state.
- def update_state(self, sia_event: SIAEvent) -> bool: Update the state of the binary... | Implement the Python class `SIABinarySensor` described below.
Class description:
Class for SIA Binary Sensors.
Method signatures and docstrings:
- def handle_last_state(self, last_state: State | None) -> None: Handle the last state.
- def update_state(self, sia_event: SIAEvent) -> bool: Update the state of the binary... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class SIABinarySensor:
"""Class for SIA Binary Sensors."""
def handle_last_state(self, last_state: State | None) -> None:
"""Handle the last state."""
<|body_0|>
def update_state(self, sia_event: SIAEvent) -> bool:
"""Update the state of the binary sensor. Return True ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SIABinarySensor:
"""Class for SIA Binary Sensors."""
def handle_last_state(self, last_state: State | None) -> None:
"""Handle the last state."""
if last_state is not None and last_state.state is not None:
if last_state.state == STATE_ON:
self._attr_is_on = True... | the_stack_v2_python_sparse | homeassistant/components/sia/binary_sensor.py | home-assistant/core | train | 35,501 |
284d223fc8b651d190bd014dfcfafc922ef7c9b7 | [
"hs = set()\nq = []\nq.append(root)\nwhile q:\n sz = len(q)\n for i in range(sz):\n cur = q.pop(0)\n if k - cur.val in hs:\n return True\n hs.add(cur.val)\n if cur.left:\n q.append(cur.left)\n if cur.right:\n q.append(cur.right)\nreturn False... | <|body_start_0|>
hs = set()
q = []
q.append(root)
while q:
sz = len(q)
for i in range(sz):
cur = q.pop(0)
if k - cur.val in hs:
return True
hs.add(cur.val)
if cur.left:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findTarget(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool BFS+HashSet"""
<|body_0|>
def findTarget1(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool 先中序遍历，再双指针"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_10k_train_008952 | 1,886 | no_license | [
{
"docstring": ":type root: TreeNode :type k: int :rtype: bool BFS+HashSet",
"name": "findTarget",
"signature": "def findTarget(self, root, k)"
},
{
"docstring": ":type root: TreeNode :type k: int :rtype: bool 先中序遍历，再双指针",
"name": "findTarget1",
"signature": "def findTarget1(self, root, ... | 2 | stack_v2_sparse_classes_30k_train_003583 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTarget(self, root, k): :type root: TreeNode :type k: int :rtype: bool BFS+HashSet
- def findTarget1(self, root, k): :type root: TreeNode :type k: int :rtype: bool 先中序遍历，再... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTarget(self, root, k): :type root: TreeNode :type k: int :rtype: bool BFS+HashSet
- def findTarget1(self, root, k): :type root: TreeNode :type k: int :rtype: bool 先中序遍历，再... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def findTarget(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool BFS+HashSet"""
<|body_0|>
def findTarget1(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool 先中序遍历，再双指针"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findTarget(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool BFS+HashSet"""
hs = set()
q = []
q.append(root)
while q:
sz = len(q)
for i in range(sz):
cur = q.pop(0)
if k - cur.val in h... | the_stack_v2_python_sparse | out/production/leetcode/653.两数之和-iv-输入-bst.py | yangyuxiang1996/leetcode | train | 0 | |
83c0b70fcf56401f49bfb8cc4801d338245a861e | [
"collaboration = db.Collaboration.get(id)\nif not collaboration:\n return ({'msg': 'collaboration having collaboration_id={} can not be found'.format(id)}, HTTPStatus.NOT_FOUND)\norg_schema = OrganizationSchema()\nreturn (org_schema.dump(collaboration.organizations, many=True).data, HTTPStatus.OK)",
"collabora... | <|body_start_0|>
collaboration = db.Collaboration.get(id)
if not collaboration:
return ({'msg': 'collaboration having collaboration_id={} can not be found'.format(id)}, HTTPStatus.NOT_FOUND)
org_schema = OrganizationSchema()
return (org_schema.dump(collaboration.organizations... | Resource for /api/collaboration/<int:id>/organization. | CollaborationOrganization | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollaborationOrganization:
"""Resource for /api/collaboration/<int:id>/organization."""
def get(self, id):
"""Return organizations for a specific collaboration."""
<|body_0|>
def post(self, id):
"""Add an organizations to a specific collaboration."""
<|bo... | stack_v2_sparse_classes_10k_train_008953 | 14,133 | permissive | [
{
"docstring": "Return organizations for a specific collaboration.",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "Add an organizations to a specific collaboration.",
"name": "post",
"signature": "def post(self, id)"
},
{
"docstring": "Removes an organization... | 3 | stack_v2_sparse_classes_30k_train_000149 | Implement the Python class `CollaborationOrganization` described below.
Class description:
Resource for /api/collaboration/<int:id>/organization.
Method signatures and docstrings:
- def get(self, id): Return organizations for a specific collaboration.
- def post(self, id): Add an organizations to a specific collabora... | Implement the Python class `CollaborationOrganization` described below.
Class description:
Resource for /api/collaboration/<int:id>/organization.
Method signatures and docstrings:
- def get(self, id): Return organizations for a specific collaboration.
- def post(self, id): Add an organizations to a specific collabora... | a64827981db26b34dd1dcea1cb2282d03dd4545d | <|skeleton|>
class CollaborationOrganization:
"""Resource for /api/collaboration/<int:id>/organization."""
def get(self, id):
"""Return organizations for a specific collaboration."""
<|body_0|>
def post(self, id):
"""Add an organizations to a specific collaboration."""
<|bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CollaborationOrganization:
"""Resource for /api/collaboration/<int:id>/organization."""
def get(self, id):
"""Return organizations for a specific collaboration."""
collaboration = db.Collaboration.get(id)
if not collaboration:
return ({'msg': 'collaboration having coll... | the_stack_v2_python_sparse | vantage6/server/resource/collaboration.py | mindrenee/vantage6-server | train | 0 |
03844b3080cdaff41534beaf3f68ec40f7475a22 | [
"super().__init__(name, mode, session, options)\nif options is None:\n options = _DEFAULT_FLOWDRONET_OPTS\nself.ds = dataset\nself.dronet_graph = None\nself.dronet_x_tnsr = None\nself.dronet_y_tnsr = None\nself.dronet_sess = None\nself.set_dronet_graph(options['dronet_model_path'])",
"try:\n with tf.gfile.G... | <|body_start_0|>
super().__init__(name, mode, session, options)
if options is None:
options = _DEFAULT_FLOWDRONET_OPTS
self.ds = dataset
self.dronet_graph = None
self.dronet_x_tnsr = None
self.dronet_y_tnsr = None
self.dronet_sess = None
self.s... | ModelFlowDroNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelFlowDroNet:
def __init__(self, name='flowdronet', mode='train', session=None, options=None, dataset=None):
"""Initialize the ModelFloDroNet object Args: name: Model name mode: Possible values: 'train', 'val', 'test' session: optional TF session options: see _DEFAULT_PWCNET_TRAIN_OPT... | stack_v2_sparse_classes_10k_train_008954 | 9,033 | permissive | [
{
"docstring": "Initialize the ModelFloDroNet object Args: name: Model name mode: Possible values: 'train', 'val', 'test' session: optional TF session options: see _DEFAULT_PWCNET_TRAIN_OPTIONS comments dataset: Dataset loader Training Ref: See original PWC-Net Model",
"name": "__init__",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_002474 | Implement the Python class `ModelFlowDroNet` described below.
Class description:
Implement the ModelFlowDroNet class.
Method signatures and docstrings:
- def __init__(self, name='flowdronet', mode='train', session=None, options=None, dataset=None): Initialize the ModelFloDroNet object Args: name: Model name mode: Pos... | Implement the Python class `ModelFlowDroNet` described below.
Class description:
Implement the ModelFlowDroNet class.
Method signatures and docstrings:
- def __init__(self, name='flowdronet', mode='train', session=None, options=None, dataset=None): Initialize the ModelFloDroNet object Args: name: Model name mode: Pos... | a2281a37b4cc6482eb87546fa414fdaa38ec04e5 | <|skeleton|>
class ModelFlowDroNet:
def __init__(self, name='flowdronet', mode='train', session=None, options=None, dataset=None):
"""Initialize the ModelFloDroNet object Args: name: Model name mode: Possible values: 'train', 'val', 'test' session: optional TF session options: see _DEFAULT_PWCNET_TRAIN_OPT... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ModelFlowDroNet:
def __init__(self, name='flowdronet', mode='train', session=None, options=None, dataset=None):
"""Initialize the ModelFloDroNet object Args: name: Model name mode: Possible values: 'train', 'val', 'test' session: optional TF session options: see _DEFAULT_PWCNET_TRAIN_OPTIONS comments ... | the_stack_v2_python_sparse | DroNeTello/tfoptflow/tfoptflow/model_flowdronet.py | MISTLab/of-obstacledetection | train | 13 | |
6479c06810459e14a4eccaebfa64d5cafab14b76 | [
"prev_min = prev_max = global_max = nums[0]\nfor num in nums[1:]:\n minn, maxx = (min(num, prev_max * num, prev_min * num), max(num, prev_max * num, prev_min * num))\n prev_min, prev_max, global_max = (minn, maxx, max(global_max, maxx))\nreturn global_max",
"front_max = front_min = global_max = nums[0]\nfor... | <|body_start_0|>
prev_min = prev_max = global_max = nums[0]
for num in nums[1:]:
minn, maxx = (min(num, prev_max * num, prev_min * num), max(num, prev_max * num, prev_min * num))
prev_min, prev_max, global_max = (minn, maxx, max(global_max, maxx))
return global_max
<|end_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProduct(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxProduct_1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def maxProduct_2(self, nums):
""":type nums: List[int] :rtype: int"""
... | stack_v2_sparse_classes_10k_train_008955 | 3,237 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxProduct",
"signature": "def maxProduct(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxProduct_1",
"signature": "def maxProduct_1(self, nums)"
},
{
"docstring": ":type nums: List[int] ... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct(self, nums): :type nums: List[int] :rtype: int
- def maxProduct_1(self, nums): :type nums: List[int] :rtype: int
- def maxProduct_2(self, nums): :type nums: List[i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct(self, nums): :type nums: List[int] :rtype: int
- def maxProduct_1(self, nums): :type nums: List[int] :rtype: int
- def maxProduct_2(self, nums): :type nums: List[i... | 3d9e0ad2f6ed92ec969556f75d97c51ea4854719 | <|skeleton|>
class Solution:
def maxProduct(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxProduct_1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def maxProduct_2(self, nums):
""":type nums: List[int] :rtype: int"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProduct(self, nums):
""":type nums: List[int] :rtype: int"""
prev_min = prev_max = global_max = nums[0]
for num in nums[1:]:
minn, maxx = (min(num, prev_max * num, prev_min * num), max(num, prev_max * num, prev_min * num))
prev_min, prev_max, gl... | the_stack_v2_python_sparse | Solutions/0152_maxProduct.py | YoupengLi/leetcode-sorting | train | 3 | |
8fb19d8590fe4071c00fc36b6ce2f053654701ce | [
"empty = UniqueKeyFunction.FLAG_EMPTY_REGISTER\ncollision = UniqueKeyFunction.FLAG_COLLIDED_REGISTER\nif x == empty and y == empty:\n return empty\nif x == collision or y == collision:\n return collision\nif x == empty:\n return y\nif y == empty:\n return x\nif x == y:\n return x\nreturn collision",
... | <|body_start_0|>
empty = UniqueKeyFunction.FLAG_EMPTY_REGISTER
collision = UniqueKeyFunction.FLAG_COLLIDED_REGISTER
if x == empty and y == empty:
return empty
if x == collision or y == collision:
return collision
if x == empty:
return y
... | ValueFunction to track the state of unique key of a register. | UniqueKeyFunction | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UniqueKeyFunction:
"""ValueFunction to track the state of unique key of a register."""
def __call__(self, x, y):
"""ValueFunction to track the state of unique key of a register. Args: x: A state of unique key. It can be either a real key (hashed ID) indicating the unique key in the r... | stack_v2_sparse_classes_10k_train_008956 | 13,872 | permissive | [
{
"docstring": "ValueFunction to track the state of unique key of a register. Args: x: A state of unique key. It can be either a real key (hashed ID) indicating the unique key in the register, or FLAG_EMPTY_REGISTER indicating that the register is empty, or FLAG_COLLIDED_REGISTER indicating that the register al... | 2 | stack_v2_sparse_classes_30k_train_003791 | Implement the Python class `UniqueKeyFunction` described below.
Class description:
ValueFunction to track the state of unique key of a register.
Method signatures and docstrings:
- def __call__(self, x, y): ValueFunction to track the state of unique key of a register. Args: x: A state of unique key. It can be either ... | Implement the Python class `UniqueKeyFunction` described below.
Class description:
ValueFunction to track the state of unique key of a register.
Method signatures and docstrings:
- def __call__(self, x, y): ValueFunction to track the state of unique key of a register. Args: x: A state of unique key. It can be either ... | 1727e9545a8f219b543c1b67da6b6653e36d931e | <|skeleton|>
class UniqueKeyFunction:
"""ValueFunction to track the state of unique key of a register."""
def __call__(self, x, y):
"""ValueFunction to track the state of unique key of a register. Args: x: A state of unique key. It can be either a real key (hashed ID) indicating the unique key in the r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UniqueKeyFunction:
"""ValueFunction to track the state of unique key of a register."""
def __call__(self, x, y):
"""ValueFunction to track the state of unique key of a register. Args: x: A state of unique key. It can be either a real key (hashed ID) indicating the unique key in the register, or F... | the_stack_v2_python_sparse | src/estimators/any_sketch.py | world-federation-of-advertisers/cardinality_estimation_evaluation_framework | train | 21 |
7fa1f11e0ed3ad74d66fb62d86a4720ed925e146 | [
"bad_lines = []\nif not content:\n raise SkipComponent('Empty content.')\nif len(content) < 5:\n raise ParseException(\"Wrong content in table: '{0}'.\".format(content))\ndata = {}\nfor _l in content[3:-1]:\n l = _l.strip()\n if not (l.startswith('|') and l.endswith('|')):\n bad_lines.append(_l)\... | <|body_start_0|>
bad_lines = []
if not content:
raise SkipComponent('Empty content.')
if len(content) < 5:
raise ParseException("Wrong content in table: '{0}'.".format(content))
data = {}
for _l in content[3:-1]:
l = _l.strip()
if n... | The output of command ``/bin/mysqladmin variables`` is in mysql table format, contains 'Variable_name' and 'Value' two columns. This parser will parse the table and set each variable as an class attribute. The unparsable lines are stored in the ``bad_lines`` property list. Example: >>> output.get('version') '5.5.56-Mar... | MysqladminVars | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MysqladminVars:
"""The output of command ``/bin/mysqladmin variables`` is in mysql table format, contains 'Variable_name' and 'Value' two columns. This parser will parse the table and set each variable as an class attribute. The unparsable lines are stored in the ``bad_lines`` property list. Exam... | stack_v2_sparse_classes_10k_train_008957 | 4,351 | permissive | [
{
"docstring": "Parse output content table of command ``/bin/mysqladmin variables``. Set each variable as an class attribute.",
"name": "parse_content",
"signature": "def parse_content(self, content)"
},
{
"docstring": "Get value for specified keyword, use default if keyword not found. Example: ... | 2 | null | Implement the Python class `MysqladminVars` described below.
Class description:
The output of command ``/bin/mysqladmin variables`` is in mysql table format, contains 'Variable_name' and 'Value' two columns. This parser will parse the table and set each variable as an class attribute. The unparsable lines are stored i... | Implement the Python class `MysqladminVars` described below.
Class description:
The output of command ``/bin/mysqladmin variables`` is in mysql table format, contains 'Variable_name' and 'Value' two columns. This parser will parse the table and set each variable as an class attribute. The unparsable lines are stored i... | b0ea07fc3f4dd8801b505fe70e9b36e628152c4a | <|skeleton|>
class MysqladminVars:
"""The output of command ``/bin/mysqladmin variables`` is in mysql table format, contains 'Variable_name' and 'Value' two columns. This parser will parse the table and set each variable as an class attribute. The unparsable lines are stored in the ``bad_lines`` property list. Exam... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MysqladminVars:
"""The output of command ``/bin/mysqladmin variables`` is in mysql table format, contains 'Variable_name' and 'Value' two columns. This parser will parse the table and set each variable as an class attribute. The unparsable lines are stored in the ``bad_lines`` property list. Example: >>> outp... | the_stack_v2_python_sparse | insights/parsers/mysqladmin.py | RedHatInsights/insights-core | train | 144 |
74e3565f82b2a7eb54cdf3d676b33f0c4d62fc49 | [
"self.screen_width = 1200\nself.screen_height = 800\nself.bg_color = (230, 230, 230)\nself.ship_limit = 3\nself.bullet_width = 10\nself.bullet_height = 15\nself.bullet_color = (60, 60, 60)\nself.bullets_allowed = 6\nself.fleet_drop_speed = 20\nself.speedup_scale = 1.1\nself.score_scale = 1.5\nself.initialize_dynami... | <|body_start_0|>
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
self.ship_limit = 3
self.bullet_width = 10
self.bullet_height = 15
self.bullet_color = (60, 60, 60)
self.bullets_allowed = 6
self.fleet_drop_speed = ... | 存储《外星人入侵》的所有设置的类 | Settings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的静态设置"""
<|body_0|>
def initialize_dynamic_settings(self):
"""初始化随着游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置"""
<|body_2|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_10k_train_008958 | 1,704 | no_license | [
{
"docstring": "初始化游戏的静态设置",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "初始化随着游戏进行而变化的设置",
"name": "initialize_dynamic_settings",
"signature": "def initialize_dynamic_settings(self)"
},
{
"docstring": "提高速度设置",
"name": "increase_speed",
"signa... | 3 | stack_v2_sparse_classes_30k_train_006756 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》的所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏的静态设置
- def initialize_dynamic_settings(self): 初始化随着游戏进行而变化的设置
- def increase_speed(self): 提高速度设置 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》的所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏的静态设置
- def initialize_dynamic_settings(self): 初始化随着游戏进行而变化的设置
- def increase_speed(self): 提高速度设置
<|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __... | 61e92d51227962d361123109d5d4a2b460175069 | <|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的静态设置"""
<|body_0|>
def initialize_dynamic_settings(self):
"""初始化随着游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的静态设置"""
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
self.ship_limit = 3
self.bullet_width = 10
self.bullet_height = 15
self.bullet_color = (6... | the_stack_v2_python_sparse | aliens/settings.py | yangrencong/pythonstudy | train | 0 |
d834cc82efc874f4528b3cff0f219f67b7e376a3 | [
"cur = 60 * int(time[:2]) + int(time[3:])\nallowed = {int(x) for x in time if x != ':'}\nwhile True:\n cur = (cur + 1) % (24 * 60)\n if all((digit in allowed for block in divmod(cur, 60) for digit in divmod(block, 10))):\n return '{:02d}:{:02d}'.format(*divmod(cur, 60))",
"ans = start = 60 * int(time... | <|body_start_0|>
cur = 60 * int(time[:2]) + int(time[3:])
allowed = {int(x) for x in time if x != ':'}
while True:
cur = (cur + 1) % (24 * 60)
if all((digit in allowed for block in divmod(cur, 60) for digit in divmod(block, 10))):
return '{:02d}:{:02d}'.fo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextClosestTime(self, time):
"""Approach #1: Simulation [Accepted] Intuition and Algorithm Simulate the clock going forward by one minute. Each time it moves forward, if all the digits are allowed, then return the current time. The natural way to represent the time is as an... | stack_v2_sparse_classes_10k_train_008959 | 3,527 | no_license | [
{
"docstring": "Approach #1: Simulation [Accepted] Intuition and Algorithm Simulate the clock going forward by one minute. Each time it moves forward, if all the digits are allowed, then return the current time. The natural way to represent the time is as an integer t in the range 0 <= t < 24 * 60. Then the hou... | 2 | stack_v2_sparse_classes_30k_train_000104 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextClosestTime(self, time): Approach #1: Simulation [Accepted] Intuition and Algorithm Simulate the clock going forward by one minute. Each time it moves forward, if all the... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextClosestTime(self, time): Approach #1: Simulation [Accepted] Intuition and Algorithm Simulate the clock going forward by one minute. Each time it moves forward, if all the... | 11d6bf2ba7b50c07e048df37c4e05c8f46b92241 | <|skeleton|>
class Solution:
def nextClosestTime(self, time):
"""Approach #1: Simulation [Accepted] Intuition and Algorithm Simulate the clock going forward by one minute. Each time it moves forward, if all the digits are allowed, then return the current time. The natural way to represent the time is as an... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def nextClosestTime(self, time):
"""Approach #1: Simulation [Accepted] Intuition and Algorithm Simulate the clock going forward by one minute. Each time it moves forward, if all the digits are allowed, then return the current time. The natural way to represent the time is as an integer t in ... | the_stack_v2_python_sparse | LeetCodes/Google/NextClosestTime.py | chutianwen/LeetCodes | train | 0 | |
5e03adcad67aef73b6801d5bf8aad51652f4b4eb | [
"n = logits.shape[-1]\nbin1, bin2, w2 = self._calc_bin(logits, target)\nw = F.one_hot(bin1, num_classes=n).to(logits.dtype)\nw = 1 - w.cumsum(dim=-1)\nB = _get_indexer(target.shape)\nw[B + (bin2,)] = w2\nw[B + (bin1,)] = 1\ncross_entropy = F.binary_cross_entropy_with_logits(logits, w, reduction='none')\nkld = cross... | <|body_start_0|>
n = logits.shape[-1]
bin1, bin2, w2 = self._calc_bin(logits, target)
w = F.one_hot(bin1, num_classes=n).to(logits.dtype)
w = 1 - w.cumsum(dim=-1)
B = _get_indexer(target.shape)
w[B + (bin2,)] = w2
w[B + (bin1,)] = 1
cross_entropy = F.binar... | A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being greater than or equal to each of these ``n`` values. If a target value y is not an integer, it is treated as havin... | OrderedDiscreteRegressionLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderedDiscreteRegressionLoss:
"""A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being greater than or equal to each of these ``n`` values. If a... | stack_v2_sparse_classes_10k_train_008960 | 31,133 | permissive | [
{
"docstring": "Caculate the loss. Args: logits: shape is [B, n] target: the shape is [B] Returns: loss with the same shape as target",
"name": "__call__",
"signature": "def __call__(self, logits: torch.Tensor, target: torch.Tensor)"
},
{
"docstring": "Calculate the expected predition in the unt... | 3 | stack_v2_sparse_classes_30k_train_000794 | Implement the Python class `OrderedDiscreteRegressionLoss` described below.
Class description:
A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being greater than or eq... | Implement the Python class `OrderedDiscreteRegressionLoss` described below.
Class description:
A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being greater than or eq... | b00ff2fa5e660de31020338ba340263183fbeaa4 | <|skeleton|>
class OrderedDiscreteRegressionLoss:
"""A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being greater than or equal to each of these ``n`` values. If a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OrderedDiscreteRegressionLoss:
"""A loss for predicting the distribution of a scalar. The target is assumed to be in the range ``[-(n-1)//2, n//2]``, where ``n=logits.shape[-1]``. The logits are used to calculate the probabilities of being greater than or equal to each of these ``n`` values. If a target value... | the_stack_v2_python_sparse | alf/utils/losses.py | HorizonRobotics/alf | train | 288 |
3741bf53a69284f089f7a83e209b33de91b3751f | [
"event = cls.objects.create(event_type=event_type, **kwargs)\nif inventory_changes:\n event._process_by_event_type(inventory_changes)\nreturn event",
"processes = EVENT_TYPE_PROCESS[self.event_type]\nfor process in processes:\n for inventorychange in inventory_changes:\n product_id = inventorychange.... | <|body_start_0|>
event = cls.objects.create(event_type=event_type, **kwargs)
if inventory_changes:
event._process_by_event_type(inventory_changes)
return event
<|end_body_0|>
<|body_start_1|>
processes = EVENT_TYPE_PROCESS[self.event_type]
for process in processes:
... | EventMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventMixin:
def create_instance(cls, event_type, inventory_changes=None, **kwargs):
"""이벤트 인스턴스 생성"""
<|body_0|>
def _process_by_event_type(self, inventory_changes) -> None:
"""이벤트타입에 따른 재고 처리"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
event = ... | stack_v2_sparse_classes_10k_train_008961 | 2,069 | no_license | [
{
"docstring": "이벤트 인스턴스 생성",
"name": "create_instance",
"signature": "def create_instance(cls, event_type, inventory_changes=None, **kwargs)"
},
{
"docstring": "이벤트타입에 따른 재고 처리",
"name": "_process_by_event_type",
"signature": "def _process_by_event_type(self, inventory_changes) -> None"... | 2 | stack_v2_sparse_classes_30k_train_001217 | Implement the Python class `EventMixin` described below.
Class description:
Implement the EventMixin class.
Method signatures and docstrings:
- def create_instance(cls, event_type, inventory_changes=None, **kwargs): 이벤트 인스턴스 생성
- def _process_by_event_type(self, inventory_changes) -> None: 이벤트타입에 따른 재고 처리 | Implement the Python class `EventMixin` described below.
Class description:
Implement the EventMixin class.
Method signatures and docstrings:
- def create_instance(cls, event_type, inventory_changes=None, **kwargs): 이벤트 인스턴스 생성
- def _process_by_event_type(self, inventory_changes) -> None: 이벤트타입에 따른 재고 처리
<|skeleton... | 7b994f34837cf7c9f3e87684ddbf9aa61bee64f5 | <|skeleton|>
class EventMixin:
def create_instance(cls, event_type, inventory_changes=None, **kwargs):
"""이벤트 인스턴스 생성"""
<|body_0|>
def _process_by_event_type(self, inventory_changes) -> None:
"""이벤트타입에 따른 재고 처리"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EventMixin:
def create_instance(cls, event_type, inventory_changes=None, **kwargs):
"""이벤트 인스턴스 생성"""
event = cls.objects.create(event_type=event_type, **kwargs)
if inventory_changes:
event._process_by_event_type(inventory_changes)
return event
def _process_by_... | the_stack_v2_python_sparse | server/events/mixins/model_mixins.py | jinimong/inventory-manager | train | 0 | |
037d5658e5e85f09b18e9b0cab84902de5aed6fe | [
"super().__init__()\nself.fft_size = fft_size\nif win_length is None:\n self.win_length = fft_size\nelse:\n self.win_length = win_length\nself.hop_size = hop_size\nself.center = center\nself.normalized = normalized\nself.onesided = onesided\nif window is not None and (not hasattr(signal.windows, f'{window}'))... | <|body_start_0|>
super().__init__()
self.fft_size = fft_size
if win_length is None:
self.win_length = fft_size
else:
self.win_length = win_length
self.hop_size = hop_size
self.center = center
self.normalized = normalized
self.onesid... | Calculate Mel-spectrogram. | MelSpectrogram | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MelSpectrogram:
"""Calculate Mel-spectrogram."""
def __init__(self, fs=22050, fft_size=1024, hop_size=256, win_length=None, window='hann', num_mels=80, fmin=80, fmax=7600, center=True, normalized=False, onesided=True, eps=1e-10, log_base=10.0):
"""Initialize MelSpectrogram module."""... | stack_v2_sparse_classes_10k_train_008962 | 46,210 | permissive | [
{
"docstring": "Initialize MelSpectrogram module.",
"name": "__init__",
"signature": "def __init__(self, fs=22050, fft_size=1024, hop_size=256, win_length=None, window='hann', num_mels=80, fmin=80, fmax=7600, center=True, normalized=False, onesided=True, eps=1e-10, log_base=10.0)"
},
{
"docstrin... | 2 | stack_v2_sparse_classes_30k_train_000554 | Implement the Python class `MelSpectrogram` described below.
Class description:
Calculate Mel-spectrogram.
Method signatures and docstrings:
- def __init__(self, fs=22050, fft_size=1024, hop_size=256, win_length=None, window='hann', num_mels=80, fmin=80, fmax=7600, center=True, normalized=False, onesided=True, eps=1e... | Implement the Python class `MelSpectrogram` described below.
Class description:
Calculate Mel-spectrogram.
Method signatures and docstrings:
- def __init__(self, fs=22050, fft_size=1024, hop_size=256, win_length=None, window='hann', num_mels=80, fmin=80, fmax=7600, center=True, normalized=False, onesided=True, eps=1e... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class MelSpectrogram:
"""Calculate Mel-spectrogram."""
def __init__(self, fs=22050, fft_size=1024, hop_size=256, win_length=None, window='hann', num_mels=80, fmin=80, fmax=7600, center=True, normalized=False, onesided=True, eps=1e-10, log_base=10.0):
"""Initialize MelSpectrogram module."""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MelSpectrogram:
"""Calculate Mel-spectrogram."""
def __init__(self, fs=22050, fft_size=1024, hop_size=256, win_length=None, window='hann', num_mels=80, fmin=80, fmax=7600, center=True, normalized=False, onesided=True, eps=1e-10, log_base=10.0):
"""Initialize MelSpectrogram module."""
supe... | the_stack_v2_python_sparse | paddlespeech/t2s/modules/losses.py | anniyanvr/DeepSpeech-1 | train | 0 |
092bdb9a602ae0f2f00413fa5729592b6f90b7ca | [
"prop = typeFor(ref)\nif not isinstance(prop, TypeProperty):\n return False\nassert isinstance(prop, TypeProperty)\nassert isinstance(prop.parent, TypeContainer), 'Invalid parent for %s' % prop\nif prop.parent.isValid(self):\n descriptor, _clazz = getAttrAndClass(self.__class__, prop.name)\n if not isinsta... | <|body_start_0|>
prop = typeFor(ref)
if not isinstance(prop, TypeProperty):
return False
assert isinstance(prop, TypeProperty)
assert isinstance(prop.parent, TypeContainer), 'Invalid parent for %s' % prop
if prop.parent.isValid(self):
descriptor, _clazz = ... | Support class for containers. | Container | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Container:
"""Support class for containers."""
def __contains__(self, ref):
"""Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @return: boolean True if a value for the reference is prese... | stack_v2_sparse_classes_10k_train_008963 | 16,647 | no_license | [
{
"docstring": "Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @return: boolean True if a value for the reference is present, false otherwise.",
"name": "__contains__",
"signature": "def __contains__(self,... | 2 | null | Implement the Python class `Container` described below.
Class description:
Support class for containers.
Method signatures and docstrings:
- def __contains__(self, ref): Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @r... | Implement the Python class `Container` described below.
Class description:
Support class for containers.
Method signatures and docstrings:
- def __contains__(self, ref): Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @r... | e0b3466b34d31548996d57be4a9dac134d904380 | <|skeleton|>
class Container:
"""Support class for containers."""
def __contains__(self, ref):
"""Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @return: boolean True if a value for the reference is prese... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Container:
"""Support class for containers."""
def __contains__(self, ref):
"""Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @return: boolean True if a value for the reference is present, false oth... | the_stack_v2_python_sparse | components/ally-api/ally/api/operator/descriptor.py | cristidomsa/Ally-Py | train | 0 |
44555fba81f56524330a9195180a06f99ea1b950 | [
"self.title = 'Convert Miles to KM Program'\nself.root = Builder.load_file('convert_miles_km.kv')\nreturn self.root",
"miles = self.get_valid_miles()\nkm = miles * MILES_TO_KM\nself.root.ids.km_output.text = str(km)",
"new_miles = self.get_valid_miles() + increment\nself.root.ids.miles_input.text = str(new_mile... | <|body_start_0|>
self.title = 'Convert Miles to KM Program'
self.root = Builder.load_file('convert_miles_km.kv')
return self.root
<|end_body_0|>
<|body_start_1|>
miles = self.get_valid_miles()
km = miles * MILES_TO_KM
self.root.ids.km_output.text = str(km)
<|end_body_1|>... | ConvertMilesToKMProgram is a KIVY GUI program for converting miles to km. | ConvertMilesToKMProgram | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvertMilesToKMProgram:
"""ConvertMilesToKMProgram is a KIVY GUI program for converting miles to km."""
def build(self):
"""Build app using Kivy app from kv file"""
<|body_0|>
def calculate_miles_to_km(self):
"""Calculates miles to km and outputs to GUI"""
... | stack_v2_sparse_classes_10k_train_008964 | 1,212 | no_license | [
{
"docstring": "Build app using Kivy app from kv file",
"name": "build",
"signature": "def build(self)"
},
{
"docstring": "Calculates miles to km and outputs to GUI",
"name": "calculate_miles_to_km",
"signature": "def calculate_miles_to_km(self)"
},
{
"docstring": "Handle increme... | 4 | stack_v2_sparse_classes_30k_train_000962 | Implement the Python class `ConvertMilesToKMProgram` described below.
Class description:
ConvertMilesToKMProgram is a KIVY GUI program for converting miles to km.
Method signatures and docstrings:
- def build(self): Build app using Kivy app from kv file
- def calculate_miles_to_km(self): Calculates miles to km and ou... | Implement the Python class `ConvertMilesToKMProgram` described below.
Class description:
ConvertMilesToKMProgram is a KIVY GUI program for converting miles to km.
Method signatures and docstrings:
- def build(self): Build app using Kivy app from kv file
- def calculate_miles_to_km(self): Calculates miles to km and ou... | 6c47affda245b594e25accdcd04fbf65facd53da | <|skeleton|>
class ConvertMilesToKMProgram:
"""ConvertMilesToKMProgram is a KIVY GUI program for converting miles to km."""
def build(self):
"""Build app using Kivy app from kv file"""
<|body_0|>
def calculate_miles_to_km(self):
"""Calculates miles to km and outputs to GUI"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ConvertMilesToKMProgram:
"""ConvertMilesToKMProgram is a KIVY GUI program for converting miles to km."""
def build(self):
"""Build app using Kivy app from kv file"""
self.title = 'Convert Miles to KM Program'
self.root = Builder.load_file('convert_miles_km.kv')
return self... | the_stack_v2_python_sparse | prac_07/convert_miles_km.py | CamA-JCU/cp1404practicals | train | 0 |
4097e81aaba8e4244df1ecf5284b098ff00cd90d | [
"if not root:\n return\ncallback(root.val)\ncls.preorder_traverse(root.left, callback=callback)\ncls.preorder_traverse(root.right, callback=callback)",
"if not root:\n return\ncls.inorder_traverse(root.left, callback=callback)\ncallback(root.val)\ncls.inorder_traverse(root.right, callback=callback)",
"if ... | <|body_start_0|>
if not root:
return
callback(root.val)
cls.preorder_traverse(root.left, callback=callback)
cls.preorder_traverse(root.right, callback=callback)
<|end_body_0|>
<|body_start_1|>
if not root:
return
cls.inorder_traverse(root.left, ca... | RecursiveTraversal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecursiveTraversal:
def preorder_traverse(cls, root, callback=None):
""":type root: TreeNode :type callback: function :rtype: void"""
<|body_0|>
def inorder_traverse(cls, root, callback=None):
""":type root: TreeNode :type callback: function :rtype: void"""
<... | stack_v2_sparse_classes_10k_train_008965 | 1,182 | no_license | [
{
"docstring": ":type root: TreeNode :type callback: function :rtype: void",
"name": "preorder_traverse",
"signature": "def preorder_traverse(cls, root, callback=None)"
},
{
"docstring": ":type root: TreeNode :type callback: function :rtype: void",
"name": "inorder_traverse",
"signature"... | 3 | null | Implement the Python class `RecursiveTraversal` described below.
Class description:
Implement the RecursiveTraversal class.
Method signatures and docstrings:
- def preorder_traverse(cls, root, callback=None): :type root: TreeNode :type callback: function :rtype: void
- def inorder_traverse(cls, root, callback=None): ... | Implement the Python class `RecursiveTraversal` described below.
Class description:
Implement the RecursiveTraversal class.
Method signatures and docstrings:
- def preorder_traverse(cls, root, callback=None): :type root: TreeNode :type callback: function :rtype: void
- def inorder_traverse(cls, root, callback=None): ... | 91892fd64281d96b8a9d5c0d57b938c314ae71be | <|skeleton|>
class RecursiveTraversal:
def preorder_traverse(cls, root, callback=None):
""":type root: TreeNode :type callback: function :rtype: void"""
<|body_0|>
def inorder_traverse(cls, root, callback=None):
""":type root: TreeNode :type callback: function :rtype: void"""
<... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RecursiveTraversal:
def preorder_traverse(cls, root, callback=None):
""":type root: TreeNode :type callback: function :rtype: void"""
if not root:
return
callback(root.val)
cls.preorder_traverse(root.left, callback=callback)
cls.preorder_traverse(root.right,... | the_stack_v2_python_sparse | topic/traversal/python/recursive_traversal.py | jaychsu/algorithm | train | 143 | |
2d0291479ba802c4944a356d7d2b12936a30165a | [
"if not isinstance(gate, Gate):\n raise TypeError('Expected gate object, got %s' % type(gate))\nself.gate = gate\nself.tag = tag\nself.name = 'Tagged(%s:%s)' % (gate.get_name(), tag)\nself.num_params = gate.get_num_params()\nself.size = gate.get_size()\nself.radixes = gate.get_radixes()\nif self.num_params == 0:... | <|body_start_0|>
if not isinstance(gate, Gate):
raise TypeError('Expected gate object, got %s' % type(gate))
self.gate = gate
self.tag = tag
self.name = 'Tagged(%s:%s)' % (gate.get_name(), tag)
self.num_params = gate.get_num_params()
self.size = gate.get_size(... | The TaggedGate Class. Allows a user to place a tag on a gate. | TaggedGate | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaggedGate:
"""The TaggedGate Class. Allows a user to place a tag on a gate."""
def __init__(self, gate: Gate, tag: Any) -> None:
"""Associate `tag` with `gate`."""
<|body_0|>
def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix:
"""Returns the unit... | stack_v2_sparse_classes_10k_train_008966 | 2,289 | permissive | [
{
"docstring": "Associate `tag` with `gate`.",
"name": "__init__",
"signature": "def __init__(self, gate: Gate, tag: Any) -> None"
},
{
"docstring": "Returns the unitary for this gate, see Unitary for more info.",
"name": "get_unitary",
"signature": "def get_unitary(self, params: Sequenc... | 4 | stack_v2_sparse_classes_30k_train_003015 | Implement the Python class `TaggedGate` described below.
Class description:
The TaggedGate Class. Allows a user to place a tag on a gate.
Method signatures and docstrings:
- def __init__(self, gate: Gate, tag: Any) -> None: Associate `tag` with `gate`.
- def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMat... | Implement the Python class `TaggedGate` described below.
Class description:
The TaggedGate Class. Allows a user to place a tag on a gate.
Method signatures and docstrings:
- def __init__(self, gate: Gate, tag: Any) -> None: Associate `tag` with `gate`.
- def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMat... | 3083218c2f4e3c3ce4ba027d12caa30c384d7665 | <|skeleton|>
class TaggedGate:
"""The TaggedGate Class. Allows a user to place a tag on a gate."""
def __init__(self, gate: Gate, tag: Any) -> None:
"""Associate `tag` with `gate`."""
<|body_0|>
def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix:
"""Returns the unit... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TaggedGate:
"""The TaggedGate Class. Allows a user to place a tag on a gate."""
def __init__(self, gate: Gate, tag: Any) -> None:
"""Associate `tag` with `gate`."""
if not isinstance(gate, Gate):
raise TypeError('Expected gate object, got %s' % type(gate))
self.gate = ... | the_stack_v2_python_sparse | bqskit/ir/gates/composed/tagged.py | mtreinish/bqskit | train | 0 |
41cbcd356e023e3b87e5ea368aab2176b78ce1ff | [
"self.set_status(200)\nself.set_header('Content-Type', 'application/x-mplane+json')\nself.write(mplane.model.unparse_json(msg))\nself.finish()",
"self.set_status(code)\nif text is not None:\n self.set_header('Content-Type', 'text/plain')\n self.write(text)\nself.finish()",
"self.set_status(code)\nif text ... | <|body_start_0|>
self.set_status(200)
self.set_header('Content-Type', 'application/x-mplane+json')
self.write(mplane.model.unparse_json(msg))
self.finish()
<|end_body_0|>
<|body_start_1|>
self.set_status(code)
if text is not None:
self.set_header('Content-Typ... | Abstract tornado RequestHandler that allows a handler to respond with an mPlane Message. | MPlaneHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MPlaneHandler:
"""Abstract tornado RequestHandler that allows a handler to respond with an mPlane Message."""
def _respond_message(self, msg):
"""Returns an HTTP response containing a JSON message"""
<|body_0|>
def _respond_plain_text(self, code, text=None):
"""R... | stack_v2_sparse_classes_10k_train_008967 | 37,893 | no_license | [
{
"docstring": "Returns an HTTP response containing a JSON message",
"name": "_respond_message",
"signature": "def _respond_message(self, msg)"
},
{
"docstring": "Returns an HTTP response containing a plain text message",
"name": "_respond_plain_text",
"signature": "def _respond_plain_te... | 3 | stack_v2_sparse_classes_30k_test_000216 | Implement the Python class `MPlaneHandler` described below.
Class description:
Abstract tornado RequestHandler that allows a handler to respond with an mPlane Message.
Method signatures and docstrings:
- def _respond_message(self, msg): Returns an HTTP response containing a JSON message
- def _respond_plain_text(self... | Implement the Python class `MPlaneHandler` described below.
Class description:
Abstract tornado RequestHandler that allows a handler to respond with an mPlane Message.
Method signatures and docstrings:
- def _respond_message(self, msg): Returns an HTTP response containing a JSON message
- def _respond_plain_text(self... | 25f11a1bb6c0fc6eb95935be2a2afc2fa3be9beb | <|skeleton|>
class MPlaneHandler:
"""Abstract tornado RequestHandler that allows a handler to respond with an mPlane Message."""
def _respond_message(self, msg):
"""Returns an HTTP response containing a JSON message"""
<|body_0|>
def _respond_plain_text(self, code, text=None):
"""R... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MPlaneHandler:
"""Abstract tornado RequestHandler that allows a handler to respond with an mPlane Message."""
def _respond_message(self, msg):
"""Returns an HTTP response containing a JSON message"""
self.set_status(200)
self.set_header('Content-Type', 'application/x-mplane+json')... | the_stack_v2_python_sparse | mplane/client.py | mami-project/mplane-sdk | train | 1 |
aa876ff752c87ba050211cd7def0415b28d91afb | [
"super(MulticastRange, self).__init__()\nself.schema_class = 'vsm_multicast_range_schema.MulticastRangeSchema'\nself.set_connection(vsm.get_connection())\nif scope is None or scope is '':\n self.set_create_endpoint('/vdn/config/multicasts')\nelse:\n self.set_create_endpoint('/vdn/config/multicasts?isUniversal... | <|body_start_0|>
super(MulticastRange, self).__init__()
self.schema_class = 'vsm_multicast_range_schema.MulticastRangeSchema'
self.set_connection(vsm.get_connection())
if scope is None or scope is '':
self.set_create_endpoint('/vdn/config/multicasts')
else:
... | MulticastRange | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MulticastRange:
def __init__(self, vsm=None, scope=None):
"""Constructor to create MulticastRange managed object @param vsm : vsm object on which this managed object needs to be configured"""
<|body_0|>
def create(self, schema_object):
"""Creates multicast range with... | stack_v2_sparse_classes_10k_train_008968 | 1,989 | no_license | [
{
"docstring": "Constructor to create MulticastRange managed object @param vsm : vsm object on which this managed object needs to be configured",
"name": "__init__",
"signature": "def __init__(self, vsm=None, scope=None)"
},
{
"docstring": "Creates multicast range with specified parameters @para... | 2 | null | Implement the Python class `MulticastRange` described below.
Class description:
Implement the MulticastRange class.
Method signatures and docstrings:
- def __init__(self, vsm=None, scope=None): Constructor to create MulticastRange managed object @param vsm : vsm object on which this managed object needs to be configu... | Implement the Python class `MulticastRange` described below.
Class description:
Implement the MulticastRange class.
Method signatures and docstrings:
- def __init__(self, vsm=None, scope=None): Constructor to create MulticastRange managed object @param vsm : vsm object on which this managed object needs to be configu... | 5b55817c050b637e2747084290f6206d2e622938 | <|skeleton|>
class MulticastRange:
def __init__(self, vsm=None, scope=None):
"""Constructor to create MulticastRange managed object @param vsm : vsm object on which this managed object needs to be configured"""
<|body_0|>
def create(self, schema_object):
"""Creates multicast range with... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MulticastRange:
def __init__(self, vsm=None, scope=None):
"""Constructor to create MulticastRange managed object @param vsm : vsm object on which this managed object needs to be configured"""
super(MulticastRange, self).__init__()
self.schema_class = 'vsm_multicast_range_schema.Multica... | the_stack_v2_python_sparse | SystemTesting/pylib/nsx/vsm/multicast_range/vsm_multicast_range.py | Cloudxtreme/MyProject | train | 0 | |
b118f558b174ec499dc5d820ac8aaffe6520cc55 | [
"self.exploration_vs_exploitation = exploration_vs_exploitation\nself.decomposition_funcs = decomposition_funcs\nself.preprocessors = preprocessors\nself.nbits = nbits\nself.seed = seed\nself.estimators = [SGDRegressor(penalty='elasticnet') for _ in range(n_estimators)]",
"coefs = [est.coef_ for est in self.estim... | <|body_start_0|>
self.exploration_vs_exploitation = exploration_vs_exploitation
self.decomposition_funcs = decomposition_funcs
self.preprocessors = preprocessors
self.nbits = nbits
self.seed = seed
self.estimators = [SGDRegressor(penalty='elasticnet') for _ in range(n_est... | ScoreEstimator. | GraphLinearScoreEstimator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GraphLinearScoreEstimator:
"""ScoreEstimator."""
def __init__(self, n_estimators=100, exploration_vs_exploitation=0, decomposition_funcs=None, preprocessors=None, nbits=14, seed=1):
"""init."""
<|body_0|>
def predict_gradient(self, graphs):
"""predict_gradient.""... | stack_v2_sparse_classes_10k_train_008969 | 21,013 | permissive | [
{
"docstring": "init.",
"name": "__init__",
"signature": "def __init__(self, n_estimators=100, exploration_vs_exploitation=0, decomposition_funcs=None, preprocessors=None, nbits=14, seed=1)"
},
{
"docstring": "predict_gradient.",
"name": "predict_gradient",
"signature": "def predict_grad... | 2 | stack_v2_sparse_classes_30k_train_002293 | Implement the Python class `GraphLinearScoreEstimator` described below.
Class description:
ScoreEstimator.
Method signatures and docstrings:
- def __init__(self, n_estimators=100, exploration_vs_exploitation=0, decomposition_funcs=None, preprocessors=None, nbits=14, seed=1): init.
- def predict_gradient(self, graphs)... | Implement the Python class `GraphLinearScoreEstimator` described below.
Class description:
ScoreEstimator.
Method signatures and docstrings:
- def __init__(self, n_estimators=100, exploration_vs_exploitation=0, decomposition_funcs=None, preprocessors=None, nbits=14, seed=1): init.
- def predict_gradient(self, graphs)... | d89e88183cce1ff24dca9333c09fa11597a45c7a | <|skeleton|>
class GraphLinearScoreEstimator:
"""ScoreEstimator."""
def __init__(self, n_estimators=100, exploration_vs_exploitation=0, decomposition_funcs=None, preprocessors=None, nbits=14, seed=1):
"""init."""
<|body_0|>
def predict_gradient(self, graphs):
"""predict_gradient.""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GraphLinearScoreEstimator:
"""ScoreEstimator."""
def __init__(self, n_estimators=100, exploration_vs_exploitation=0, decomposition_funcs=None, preprocessors=None, nbits=14, seed=1):
"""init."""
self.exploration_vs_exploitation = exploration_vs_exploitation
self.decomposition_funcs... | the_stack_v2_python_sparse | ego/optimization/score_estimator.py | smautner/EGO | train | 0 |
fdb9af6308e60b7f913135329713a002b28acc66 | [
"elem = deepcopy(elem)\nyld = elem.find('./YIELD')\nif yld is not None:\n yld.tag = 'YLD'\nreturn super(STOCKINFO, STOCKINFO).groom(elem)",
"elem = deepcopy(elem)\nyld = elem.find('./YLD')\nif yld is not None:\n yld.tag = 'YIELD'\nreturn super(STOCKINFO, STOCKINFO).ungroom(elem)"
] | <|body_start_0|>
elem = deepcopy(elem)
yld = elem.find('./YIELD')
if yld is not None:
yld.tag = 'YLD'
return super(STOCKINFO, STOCKINFO).groom(elem)
<|end_body_0|>
<|body_start_1|>
elem = deepcopy(elem)
yld = elem.find('./YLD')
if yld is not None:
... | OFX Section 13.8.5.6 | STOCKINFO | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class STOCKINFO:
"""OFX Section 13.8.5.6"""
def groom(elem):
"""Rename all Elements tagged YIELD (reserved Python keyword) to YLD"""
<|body_0|>
def ungroom(elem):
"""Rename YLD back to YLD"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
elem = deepcop... | stack_v2_sparse_classes_10k_train_008970 | 6,031 | no_license | [
{
"docstring": "Rename all Elements tagged YIELD (reserved Python keyword) to YLD",
"name": "groom",
"signature": "def groom(elem)"
},
{
"docstring": "Rename YLD back to YLD",
"name": "ungroom",
"signature": "def ungroom(elem)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002773 | Implement the Python class `STOCKINFO` described below.
Class description:
OFX Section 13.8.5.6
Method signatures and docstrings:
- def groom(elem): Rename all Elements tagged YIELD (reserved Python keyword) to YLD
- def ungroom(elem): Rename YLD back to YLD | Implement the Python class `STOCKINFO` described below.
Class description:
OFX Section 13.8.5.6
Method signatures and docstrings:
- def groom(elem): Rename all Elements tagged YIELD (reserved Python keyword) to YLD
- def ungroom(elem): Rename YLD back to YLD
<|skeleton|>
class STOCKINFO:
"""OFX Section 13.8.5.6"... | 67e688ea6510853657736c3804969d029c672c5c | <|skeleton|>
class STOCKINFO:
"""OFX Section 13.8.5.6"""
def groom(elem):
"""Rename all Elements tagged YIELD (reserved Python keyword) to YLD"""
<|body_0|>
def ungroom(elem):
"""Rename YLD back to YLD"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class STOCKINFO:
"""OFX Section 13.8.5.6"""
def groom(elem):
"""Rename all Elements tagged YIELD (reserved Python keyword) to YLD"""
elem = deepcopy(elem)
yld = elem.find('./YIELD')
if yld is not None:
yld.tag = 'YLD'
return super(STOCKINFO, STOCKINFO).groom(... | the_stack_v2_python_sparse | env/lib/python3.6/site-packages/ofxtools/models/invest/securities.py | yetaai/batchaccounting | train | 0 |
c9c5dd27228805e6c3b1ec4329574202a657d5de | [
"if 'ServiceRole' in usr_model['Configurations']:\n service_role = usr_model['Configurations']['ServiceRole'].split('/')[-1]\n try:\n get_role(service_role)\n except (NotFoundError, ServiceError):\n raise InvalidOptionsError(strings['lifecycle.invalidrole'].replace('{role}', service_role))\nr... | <|body_start_0|>
if 'ServiceRole' in usr_model['Configurations']:
service_role = usr_model['Configurations']['ServiceRole'].split('/')[-1]
try:
get_role(service_role)
except (NotFoundError, ServiceError):
raise InvalidOptionsError(strings['life... | LifecycleConfiguration | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LifecycleConfiguration:
def collect_changes(self, usr_model):
"""Because we can't remove options from the lifecycle config we can only add to them so we just take the direct user model and apply that. :param usr_model: User model, key-value style :return: api_model"""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_008971 | 3,127 | permissive | [
{
"docstring": "Because we can't remove options from the lifecycle config we can only add to them so we just take the direct user model and apply that. :param usr_model: User model, key-value style :return: api_model",
"name": "collect_changes",
"signature": "def collect_changes(self, usr_model)"
},
... | 2 | stack_v2_sparse_classes_30k_train_005770 | Implement the Python class `LifecycleConfiguration` described below.
Class description:
Implement the LifecycleConfiguration class.
Method signatures and docstrings:
- def collect_changes(self, usr_model): Because we can't remove options from the lifecycle config we can only add to them so we just take the direct use... | Implement the Python class `LifecycleConfiguration` described below.
Class description:
Implement the LifecycleConfiguration class.
Method signatures and docstrings:
- def collect_changes(self, usr_model): Because we can't remove options from the lifecycle config we can only add to them so we just take the direct use... | 252101641a7b6acb5de17fafd6adf8b96418426f | <|skeleton|>
class LifecycleConfiguration:
def collect_changes(self, usr_model):
"""Because we can't remove options from the lifecycle config we can only add to them so we just take the direct user model and apply that. :param usr_model: User model, key-value style :return: api_model"""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LifecycleConfiguration:
def collect_changes(self, usr_model):
"""Because we can't remove options from the lifecycle config we can only add to them so we just take the direct user model and apply that. :param usr_model: User model, key-value style :return: api_model"""
if 'ServiceRole' in usr_m... | the_stack_v2_python_sparse | ebcli/objects/lifecycleconfiguration.py | aws/aws-elastic-beanstalk-cli | train | 149 | |
856e8bbad431c81045a84fd91c33c105405fff45 | [
"if num1 == num2:\n return\nif len(str(num2)) > len(str(num1)):\n return\nnum1_str = str(num1)\nnum1_dict = defaultdict(int)\nnum1_max_digit = float('-inf')\nnum1_min_digit = float('inf')\ni = 0\nwhile i < len(num1_str):\n n1 = int(num1_str[i])\n num1_dict[n1] += 1\n if n1 > num1_max_digit:\n ... | <|body_start_0|>
if num1 == num2:
return
if len(str(num2)) > len(str(num1)):
return
num1_str = str(num1)
num1_dict = defaultdict(int)
num1_max_digit = float('-inf')
num1_min_digit = float('inf')
i = 0
while i < len(num1_str):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def biggerNum(self, num1, num2):
"""input num1: num input num2: num return: num num1 = 23888 numDict = { 8: 3, 3: 1, 2: 1 } sortedKeys = [8, 3, 2] 88832"""
<|body_0|>
def newNum(self, num1_dict, num1_max_digit, num1_min_digit):
"""input num1_dict: {int: int... | stack_v2_sparse_classes_10k_train_008972 | 4,728 | no_license | [
{
"docstring": "input num1: num input num2: num return: num num1 = 23888 numDict = { 8: 3, 3: 1, 2: 1 } sortedKeys = [8, 3, 2] 88832",
"name": "biggerNum",
"signature": "def biggerNum(self, num1, num2)"
},
{
"docstring": "input num1_dict: {int: int} input num1_max_digit: int input num1_min_digit... | 2 | stack_v2_sparse_classes_30k_train_002756 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def biggerNum(self, num1, num2): input num1: num input num2: num return: num num1 = 23888 numDict = { 8: 3, 3: 1, 2: 1 } sortedKeys = [8, 3, 2] 88832
- def newNum(self, num1_dict... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def biggerNum(self, num1, num2): input num1: num input num2: num return: num num1 = 23888 numDict = { 8: 3, 3: 1, 2: 1 } sortedKeys = [8, 3, 2] 88832
- def newNum(self, num1_dict... | bf98c8fa31043a45b3d21cfe78d4e08f9cac9de6 | <|skeleton|>
class Solution:
def biggerNum(self, num1, num2):
"""input num1: num input num2: num return: num num1 = 23888 numDict = { 8: 3, 3: 1, 2: 1 } sortedKeys = [8, 3, 2] 88832"""
<|body_0|>
def newNum(self, num1_dict, num1_max_digit, num1_min_digit):
"""input num1_dict: {int: int... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def biggerNum(self, num1, num2):
"""input num1: num input num2: num return: num num1 = 23888 numDict = { 8: 3, 3: 1, 2: 1 } sortedKeys = [8, 3, 2] 88832"""
if num1 == num2:
return
if len(str(num2)) > len(str(num1)):
return
num1_str = str(num1)
... | the_stack_v2_python_sparse | string/create_a_bigger_num.py | mistrydarshan99/Leetcode-3 | train | 0 | |
7e9daaf777de38f4b168931a6674724a54138ade | [
"self.device = device\nself.layer_output_size = layer_output_size\nself.model_name = model\nself.model, self.extraction_layer = self._get_model_and_layer(model, layer, model_path)\nself.model = self.model.to(self.device)\nself.model.eval()\nself.scaler = transforms.Resize((224, 224))\nself.normalize = transforms.No... | <|body_start_0|>
self.device = device
self.layer_output_size = layer_output_size
self.model_name = model
self.model, self.extraction_layer = self._get_model_and_layer(model, layer, model_path)
self.model = self.model.to(self.device)
self.model.eval()
self.scaler =... | Img2Vec | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Img2Vec:
def __init__(self, model_path, model='resnet-18', layer='default', layer_output_size=512, device='cuda'):
"""Img2Vec :param model: String name of requested model :param layer: String or Int depending on model. See more docs: https://github.com/christiansafka/img2vec.git :param l... | stack_v2_sparse_classes_10k_train_008973 | 4,647 | permissive | [
{
"docstring": "Img2Vec :param model: String name of requested model :param layer: String or Int depending on model. See more docs: https://github.com/christiansafka/img2vec.git :param layer_output_size: Int depicting the output size of the requested layer :param device: String that lets us decide between using... | 3 | stack_v2_sparse_classes_30k_val_000176 | Implement the Python class `Img2Vec` described below.
Class description:
Implement the Img2Vec class.
Method signatures and docstrings:
- def __init__(self, model_path, model='resnet-18', layer='default', layer_output_size=512, device='cuda'): Img2Vec :param model: String name of requested model :param layer: String ... | Implement the Python class `Img2Vec` described below.
Class description:
Implement the Img2Vec class.
Method signatures and docstrings:
- def __init__(self, model_path, model='resnet-18', layer='default', layer_output_size=512, device='cuda'): Img2Vec :param model: String name of requested model :param layer: String ... | e97f11cee15a522a09cab325ee943526f19c7d71 | <|skeleton|>
class Img2Vec:
def __init__(self, model_path, model='resnet-18', layer='default', layer_output_size=512, device='cuda'):
"""Img2Vec :param model: String name of requested model :param layer: String or Int depending on model. See more docs: https://github.com/christiansafka/img2vec.git :param l... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Img2Vec:
def __init__(self, model_path, model='resnet-18', layer='default', layer_output_size=512, device='cuda'):
"""Img2Vec :param model: String name of requested model :param layer: String or Int depending on model. See more docs: https://github.com/christiansafka/img2vec.git :param layer_output_si... | the_stack_v2_python_sparse | distil/utils.py | uncharted-distil/distil-primitives | train | 4 | |
91c999d23c956d727251bf14e2dcd48a6137d532 | [
"self.xk_hat = x0\nself.Pk = Pk0\nself.Gk = np.array([0])\nself.Q = Q\nself.R = R\nself.A = np.eye(self.xk_hat.shape[0])\nself.B = np.zeros(self.xk_hat.shape[0])\nself.C = np.eye(self.xk_hat.shape[0])",
"self.xk_hat = self.A @ self.xk_hat + self.B @ np.array(uk)\nself.Pk = self.A @ self.Pk @ self.A.T + self.Q\nse... | <|body_start_0|>
self.xk_hat = x0
self.Pk = Pk0
self.Gk = np.array([0])
self.Q = Q
self.R = R
self.A = np.eye(self.xk_hat.shape[0])
self.B = np.zeros(self.xk_hat.shape[0])
self.C = np.eye(self.xk_hat.shape[0])
<|end_body_0|>
<|body_start_1|>
self.... | KalmanFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KalmanFilter:
def __init__(self, x0=np.array([0]), Pk0=np.array([0]), Q=np.array([0.01]), R=np.array([0.01])):
"""Initializes Kalman Filter. :param x0: (float vector) initial state estimate :param Pk0: (float 2d array) initial filter gain :param Q: (float 2d array) process noise :param R... | stack_v2_sparse_classes_10k_train_008974 | 1,311 | no_license | [
{
"docstring": "Initializes Kalman Filter. :param x0: (float vector) initial state estimate :param Pk0: (float 2d array) initial filter gain :param Q: (float 2d array) process noise :param R: (float 2d array) sensor uncertainties",
"name": "__init__",
"signature": "def __init__(self, x0=np.array([0]), P... | 2 | stack_v2_sparse_classes_30k_test_000253 | Implement the Python class `KalmanFilter` described below.
Class description:
Implement the KalmanFilter class.
Method signatures and docstrings:
- def __init__(self, x0=np.array([0]), Pk0=np.array([0]), Q=np.array([0.01]), R=np.array([0.01])): Initializes Kalman Filter. :param x0: (float vector) initial state estima... | Implement the Python class `KalmanFilter` described below.
Class description:
Implement the KalmanFilter class.
Method signatures and docstrings:
- def __init__(self, x0=np.array([0]), Pk0=np.array([0]), Q=np.array([0.01]), R=np.array([0.01])): Initializes Kalman Filter. :param x0: (float vector) initial state estima... | e6c9686c440486831ce5ea246ab05af5b4f6ea01 | <|skeleton|>
class KalmanFilter:
def __init__(self, x0=np.array([0]), Pk0=np.array([0]), Q=np.array([0.01]), R=np.array([0.01])):
"""Initializes Kalman Filter. :param x0: (float vector) initial state estimate :param Pk0: (float 2d array) initial filter gain :param Q: (float 2d array) process noise :param R... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KalmanFilter:
def __init__(self, x0=np.array([0]), Pk0=np.array([0]), Q=np.array([0.01]), R=np.array([0.01])):
"""Initializes Kalman Filter. :param x0: (float vector) initial state estimate :param Pk0: (float 2d array) initial filter gain :param Q: (float 2d array) process noise :param R: (float 2d ar... | the_stack_v2_python_sparse | IMU/KalmanFilter.py | augustusellis/balance_bot | train | 1 | |
aa066272064ae6d8963e1367bc71819e5fbdea45 | [
"super().__init__()\nself.in_features = in_features\nself.scan_weight = torch.nn.Parameter(torch.zeros(in_features, 1))\nself.apply(initialise_layer_weights)",
"item = input[0]\nB, C, Z, Y, X = item.shape\nf_avg_2d = torch.nn.functional.avg_pool3d(item, [1, Y, X])\nnormalized_weight = TF.softmax(self.scan_weight,... | <|body_start_0|>
super().__init__()
self.in_features = in_features
self.scan_weight = torch.nn.Parameter(torch.zeros(in_features, 1))
self.apply(initialise_layer_weights)
<|end_body_0|>
<|body_start_1|>
item = input[0]
B, C, Z, Y, X = item.shape
f_avg_2d = torch.... | Performs 3D average pooling with custom weighting along the Z dimension. In short: extract the 2d average for each B-scan. Learn a weighting for averaging these features over all B-Scans. | ZAdaptive3dAvgLayer | [
"MIT",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZAdaptive3dAvgLayer:
"""Performs 3D average pooling with custom weighting along the Z dimension. In short: extract the 2d average for each B-scan. Learn a weighting for averaging these features over all B-Scans."""
def __init__(self, in_features: int) -> None:
""":param in_features: ... | stack_v2_sparse_classes_10k_train_008975 | 4,772 | permissive | [
{
"docstring": ":param in_features: number of B-scan",
"name": "__init__",
"signature": "def __init__(self, in_features: int) -> None"
},
{
"docstring": ":param input: batch of size [B, C, Z, X, Y]",
"name": "forward",
"signature": "def forward(self, *input: torch.Tensor, **kwargs: Any) ... | 2 | null | Implement the Python class `ZAdaptive3dAvgLayer` described below.
Class description:
Performs 3D average pooling with custom weighting along the Z dimension. In short: extract the 2d average for each B-scan. Learn a weighting for averaging these features over all B-Scans.
Method signatures and docstrings:
- def __ini... | Implement the Python class `ZAdaptive3dAvgLayer` described below.
Class description:
Performs 3D average pooling with custom weighting along the Z dimension. In short: extract the 2d average for each B-scan. Learn a weighting for averaging these features over all B-Scans.
Method signatures and docstrings:
- def __ini... | 2877002d50d3a34d80f647c18cb561025d9066cc | <|skeleton|>
class ZAdaptive3dAvgLayer:
"""Performs 3D average pooling with custom weighting along the Z dimension. In short: extract the 2d average for each B-scan. Learn a weighting for averaging these features over all B-Scans."""
def __init__(self, in_features: int) -> None:
""":param in_features: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ZAdaptive3dAvgLayer:
"""Performs 3D average pooling with custom weighting along the Z dimension. In short: extract the 2d average for each B-scan. Learn a weighting for averaging these features over all B-Scans."""
def __init__(self, in_features: int) -> None:
""":param in_features: number of B-s... | the_stack_v2_python_sparse | InnerEye/ML/models/layers/pooling_layers.py | microsoft/InnerEye-DeepLearning | train | 511 |
c01ac6f0b059d2dd4fe85d2dac1454ca3d6bd08e | [
"if len(values) == 0 or len(weights) == 0:\n return 0\ntable = []\nfor i in range(limit + 1):\n table.append([0] * (len(values) + 1))\nfor max_weights in range(limit + 1):\n for i in range(len(values) + 1):\n if max_weights == 0:\n table[max_weights][i] = 0\n elif i == 0:\n ... | <|body_start_0|>
if len(values) == 0 or len(weights) == 0:
return 0
table = []
for i in range(limit + 1):
table.append([0] * (len(values) + 1))
for max_weights in range(limit + 1):
for i in range(len(values) + 1):
if max_weights == 0:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def knapsack(self, values, weights, limit):
"""input: string source, string target return: int"""
<|body_0|>
def knapsack2(self, values, weights, limit):
"""input: string source, string target return: int"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_10k_train_008976 | 3,832 | no_license | [
{
"docstring": "input: string source, string target return: int",
"name": "knapsack",
"signature": "def knapsack(self, values, weights, limit)"
},
{
"docstring": "input: string source, string target return: int",
"name": "knapsack2",
"signature": "def knapsack2(self, values, weights, lim... | 2 | stack_v2_sparse_classes_30k_train_004216 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def knapsack(self, values, weights, limit): input: string source, string target return: int
- def knapsack2(self, values, weights, limit): input: string source, string target ret... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def knapsack(self, values, weights, limit): input: string source, string target return: int
- def knapsack2(self, values, weights, limit): input: string source, string target ret... | 8d9eb98fa5e897602eae9c37b47fd8abae72b1dc | <|skeleton|>
class Solution:
def knapsack(self, values, weights, limit):
"""input: string source, string target return: int"""
<|body_0|>
def knapsack2(self, values, weights, limit):
"""input: string source, string target return: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def knapsack(self, values, weights, limit):
"""input: string source, string target return: int"""
if len(values) == 0 or len(weights) == 0:
return 0
table = []
for i in range(limit + 1):
table.append([0] * (len(values) + 1))
for max_wei... | the_stack_v2_python_sparse | misc/knapsack.py | wanlipu/coding-python | train | 0 | |
5ead8ee283fd6ed0ccbd0adaaf4504ef0b306a7a | [
"im = Image.open(cls.infile)\nout = im.resize((width, height), Image.ANTIALIAS)\nout.save(cls.outfile)",
"im = Image.open(cls.infile)\nx, y = im.size\nx_s = x\ny_s = x / w_divide_h\nout = im.resize((x_s, y_s), Image.ANTIALIAS)\nout.save(cls.outfile)",
"im = Image.open(cls.infile)\nx, y = im.size\nx_s = y * w_di... | <|body_start_0|>
im = Image.open(cls.infile)
out = im.resize((width, height), Image.ANTIALIAS)
out.save(cls.outfile)
<|end_body_0|>
<|body_start_1|>
im = Image.open(cls.infile)
x, y = im.size
x_s = x
y_s = x / w_divide_h
out = im.resize((x_s, y_s), Image.... | Graphics | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Graphics:
def fixed_size(cls, width, height):
"""按照固定尺寸处理图片"""
<|body_0|>
def resize_by_width(cls, w_divide_h):
"""按照宽度进行所需比例缩放"""
<|body_1|>
def resize_by_height(cls, w_divide_h):
"""按照高度进行所需比例缩放"""
<|body_2|>
def resize_by_size(cls... | stack_v2_sparse_classes_10k_train_008977 | 2,331 | no_license | [
{
"docstring": "按照固定尺寸处理图片",
"name": "fixed_size",
"signature": "def fixed_size(cls, width, height)"
},
{
"docstring": "按照宽度进行所需比例缩放",
"name": "resize_by_width",
"signature": "def resize_by_width(cls, w_divide_h)"
},
{
"docstring": "按照高度进行所需比例缩放",
"name": "resize_by_height",
... | 5 | stack_v2_sparse_classes_30k_train_005530 | Implement the Python class `Graphics` described below.
Class description:
Implement the Graphics class.
Method signatures and docstrings:
- def fixed_size(cls, width, height): 按照固定尺寸处理图片
- def resize_by_width(cls, w_divide_h): 按照宽度进行所需比例缩放
- def resize_by_height(cls, w_divide_h): 按照高度进行所需比例缩放
- def resize_by_size(cls... | Implement the Python class `Graphics` described below.
Class description:
Implement the Graphics class.
Method signatures and docstrings:
- def fixed_size(cls, width, height): 按照固定尺寸处理图片
- def resize_by_width(cls, w_divide_h): 按照宽度进行所需比例缩放
- def resize_by_height(cls, w_divide_h): 按照高度进行所需比例缩放
- def resize_by_size(cls... | 53a4d00752eb7134397b230d1d3eaeb056de32ef | <|skeleton|>
class Graphics:
def fixed_size(cls, width, height):
"""按照固定尺寸处理图片"""
<|body_0|>
def resize_by_width(cls, w_divide_h):
"""按照宽度进行所需比例缩放"""
<|body_1|>
def resize_by_height(cls, w_divide_h):
"""按照高度进行所需比例缩放"""
<|body_2|>
def resize_by_size(cls... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Graphics:
def fixed_size(cls, width, height):
"""按照固定尺寸处理图片"""
im = Image.open(cls.infile)
out = im.resize((width, height), Image.ANTIALIAS)
out.save(cls.outfile)
def resize_by_width(cls, w_divide_h):
"""按照宽度进行所需比例缩放"""
im = Image.open(cls.infile)
x... | the_stack_v2_python_sparse | src/reXXXX/Graphics.py | happyxuwork/data-preprocess | train | 1 | |
a6469d7b56a33f527b7834646c2f6a4a7ce5f66e | [
"if context:\n if context.get('default_tally_location_ept', False):\n location_id = context.get('default_tally_location_ept')\n return location_id\nreturn super(stock_inventory_line_ept, self)._default_stock_location(cr, uid, context)",
"if not product:\n return {'value': {'product_qty': 0.0, ... | <|body_start_0|>
if context:
if context.get('default_tally_location_ept', False):
location_id = context.get('default_tally_location_ept')
return location_id
return super(stock_inventory_line_ept, self)._default_stock_location(cr, uid, context)
<|end_body_0|>
... | stock_inventory_line_ept | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stock_inventory_line_ept:
def _default_stock_location(self, cr, uid, context=None):
"""it will set default location for stone."""
<|body_0|>
def on_change_product_id(self, cr, uid, ids, location_id, product, uom=False, to_date=False, amount=0.0):
"""set default amoun... | stack_v2_sparse_classes_10k_train_008978 | 30,102 | no_license | [
{
"docstring": "it will set default location for stone.",
"name": "_default_stock_location",
"signature": "def _default_stock_location(self, cr, uid, context=None)"
},
{
"docstring": "set default amount(product_qty)",
"name": "on_change_product_id",
"signature": "def on_change_product_id... | 2 | stack_v2_sparse_classes_30k_test_000396 | Implement the Python class `stock_inventory_line_ept` described below.
Class description:
Implement the stock_inventory_line_ept class.
Method signatures and docstrings:
- def _default_stock_location(self, cr, uid, context=None): it will set default location for stone.
- def on_change_product_id(self, cr, uid, ids, l... | Implement the Python class `stock_inventory_line_ept` described below.
Class description:
Implement the stock_inventory_line_ept class.
Method signatures and docstrings:
- def _default_stock_location(self, cr, uid, context=None): it will set default location for stone.
- def on_change_product_id(self, cr, uid, ids, l... | b8615b70c33b79d8b2454cef4151d3f83c3bc77f | <|skeleton|>
class stock_inventory_line_ept:
def _default_stock_location(self, cr, uid, context=None):
"""it will set default location for stone."""
<|body_0|>
def on_change_product_id(self, cr, uid, ids, location_id, product, uom=False, to_date=False, amount=0.0):
"""set default amoun... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class stock_inventory_line_ept:
def _default_stock_location(self, cr, uid, context=None):
"""it will set default location for stone."""
if context:
if context.get('default_tally_location_ept', False):
location_id = context.get('default_tally_location_ept')
... | the_stack_v2_python_sparse | product_stone_search_ept/py/product.py | arpanv/pansuriya | train | 0 | |
66c68f37af977b34b03765b3fd8e7a51f9c3243c | [
"try:\n self.object = User.objects.get(username=self.request.user)\n print(self.object)\n return self.object\nexcept:\n return None",
"obj = self.get_object()\nprint(obj)\nif obj is not None:\n initial_data = model_to_dict(obj)\n print(initial_data)\n initial_data.update(model_to_dict(obj))\n... | <|body_start_0|>
try:
self.object = User.objects.get(username=self.request.user)
print(self.object)
return self.object
except:
return None
<|end_body_0|>
<|body_start_1|>
obj = self.get_object()
print(obj)
if obj is not None:
... | Edit_Profile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Edit_Profile:
def get_object(self):
"""Check if data already exists"""
<|body_0|>
def get_initial(self):
"""Pre-fill the form if data exists"""
<|body_1|>
def form_valid(self, form):
"""Save to the database. If data exists, update else create new... | stack_v2_sparse_classes_10k_train_008979 | 6,927 | no_license | [
{
"docstring": "Check if data already exists",
"name": "get_object",
"signature": "def get_object(self)"
},
{
"docstring": "Pre-fill the form if data exists",
"name": "get_initial",
"signature": "def get_initial(self)"
},
{
"docstring": "Save to the database. If data exists, upda... | 3 | stack_v2_sparse_classes_30k_train_004026 | Implement the Python class `Edit_Profile` described below.
Class description:
Implement the Edit_Profile class.
Method signatures and docstrings:
- def get_object(self): Check if data already exists
- def get_initial(self): Pre-fill the form if data exists
- def form_valid(self, form): Save to the database. If data e... | Implement the Python class `Edit_Profile` described below.
Class description:
Implement the Edit_Profile class.
Method signatures and docstrings:
- def get_object(self): Check if data already exists
- def get_initial(self): Pre-fill the form if data exists
- def form_valid(self, form): Save to the database. If data e... | 4e466eefaac29d9aebd162a320be32785f221d24 | <|skeleton|>
class Edit_Profile:
def get_object(self):
"""Check if data already exists"""
<|body_0|>
def get_initial(self):
"""Pre-fill the form if data exists"""
<|body_1|>
def form_valid(self, form):
"""Save to the database. If data exists, update else create new... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Edit_Profile:
def get_object(self):
"""Check if data already exists"""
try:
self.object = User.objects.get(username=self.request.user)
print(self.object)
return self.object
except:
return None
def get_initial(self):
"""Pre-fi... | the_stack_v2_python_sparse | SocialNetwork/dashboard/views.py | Nitu22499/SocialMediaClone | train | 0 | |
91a8c173d38077969ad7e6248ed289583bc40360 | [
"command = config.editor\nif jumpIndex:\n line = text[:jumpIndex].count('\\n')\n column = jumpIndex - (text[:jumpIndex].rfind('\\n') + 1)\nelse:\n line = column = 0\nif config.editor.startswith('kate'):\n command += ' -l %i -c %i' % (line + 1, column + 1)\nelif config.editor.startswith('gedit'):\n co... | <|body_start_0|>
command = config.editor
if jumpIndex:
line = text[:jumpIndex].count('\n')
column = jumpIndex - (text[:jumpIndex].rfind('\n') + 1)
else:
line = column = 0
if config.editor.startswith('kate'):
command += ' -l %i -c %i' % (lin... | Text editor. | TextEditor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextEditor:
"""Text editor."""
def command(self, tempFilename, text, jumpIndex=None):
"""Return editor selected in user-config.py."""
<|body_0|>
def convertLinebreaks(self, text):
"""Convert line-breaks."""
<|body_1|>
def restoreLinebreaks(self, text... | stack_v2_sparse_classes_10k_train_008980 | 4,743 | permissive | [
{
"docstring": "Return editor selected in user-config.py.",
"name": "command",
"signature": "def command(self, tempFilename, text, jumpIndex=None)"
},
{
"docstring": "Convert line-breaks.",
"name": "convertLinebreaks",
"signature": "def convertLinebreaks(self, text)"
},
{
"docstr... | 4 | stack_v2_sparse_classes_30k_train_006223 | Implement the Python class `TextEditor` described below.
Class description:
Text editor.
Method signatures and docstrings:
- def command(self, tempFilename, text, jumpIndex=None): Return editor selected in user-config.py.
- def convertLinebreaks(self, text): Convert line-breaks.
- def restoreLinebreaks(self, text): R... | Implement the Python class `TextEditor` described below.
Class description:
Text editor.
Method signatures and docstrings:
- def command(self, tempFilename, text, jumpIndex=None): Return editor selected in user-config.py.
- def convertLinebreaks(self, text): Convert line-breaks.
- def restoreLinebreaks(self, text): R... | 2461ccc6d24153790a1b1c0378348f99997c4eca | <|skeleton|>
class TextEditor:
"""Text editor."""
def command(self, tempFilename, text, jumpIndex=None):
"""Return editor selected in user-config.py."""
<|body_0|>
def convertLinebreaks(self, text):
"""Convert line-breaks."""
<|body_1|>
def restoreLinebreaks(self, text... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TextEditor:
"""Text editor."""
def command(self, tempFilename, text, jumpIndex=None):
"""Return editor selected in user-config.py."""
command = config.editor
if jumpIndex:
line = text[:jumpIndex].count('\n')
column = jumpIndex - (text[:jumpIndex].rfind('\n'... | the_stack_v2_python_sparse | pywikibot/editor.py | speedydeletion/pywikibot | train | 1 |
fc6507c3beadb96e406358a7d00a98ea7d3fb3d4 | [
"logs.debug('INSTALLERS: Instantiating Endpoint object')\nif os == 'Darwin':\n logs.debug(f'INSTALLERS: Operating system: {os}')\n self._docker_mac(logs=logs)\nelse:\n msg = f'Docker installation is not automated for this operating system: {os}:\\n If docker is already installed on yous system, ... | <|body_start_0|>
logs.debug('INSTALLERS: Instantiating Endpoint object')
if os == 'Darwin':
logs.debug(f'INSTALLERS: Operating system: {os}')
self._docker_mac(logs=logs)
else:
msg = f'Docker installation is not automated for this operating system: {os}:\n ... | Class wrapper for Docker installation procedures | Installers | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Installers:
"""Class wrapper for Docker installation procedures"""
def __init__(self, os: str, logs: logging.Logger) -> None:
"""Instantiation of Installers object. Parameters ---------- logs: logging.Logger object Logger object to manage DHTK logs"""
<|body_0|>
def _doc... | stack_v2_sparse_classes_10k_train_008981 | 21,202 | no_license | [
{
"docstring": "Instantiation of Installers object. Parameters ---------- logs: logging.Logger object Logger object to manage DHTK logs",
"name": "__init__",
"signature": "def __init__(self, os: str, logs: logging.Logger) -> None"
},
{
"docstring": "Method to create Docker installation pipeline ... | 3 | stack_v2_sparse_classes_30k_train_003768 | Implement the Python class `Installers` described below.
Class description:
Class wrapper for Docker installation procedures
Method signatures and docstrings:
- def __init__(self, os: str, logs: logging.Logger) -> None: Instantiation of Installers object. Parameters ---------- logs: logging.Logger object Logger objec... | Implement the Python class `Installers` described below.
Class description:
Class wrapper for Docker installation procedures
Method signatures and docstrings:
- def __init__(self, os: str, logs: logging.Logger) -> None: Instantiation of Installers object. Parameters ---------- logs: logging.Logger object Logger objec... | 54d9104c8b04af0fb368a499372d7ea0337be3d2 | <|skeleton|>
class Installers:
"""Class wrapper for Docker installation procedures"""
def __init__(self, os: str, logs: logging.Logger) -> None:
"""Instantiation of Installers object. Parameters ---------- logs: logging.Logger object Logger object to manage DHTK logs"""
<|body_0|>
def _doc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Installers:
"""Class wrapper for Docker installation procedures"""
def __init__(self, os: str, logs: logging.Logger) -> None:
"""Instantiation of Installers object. Parameters ---------- logs: logging.Logger object Logger object to manage DHTK logs"""
logs.debug('INSTALLERS: Instantiating... | the_stack_v2_python_sparse | venv/Lib/site-packages/dhtk/core/client.py | sorchawalsh/semanticweb | train | 0 |
5ee3eeb6f8f4704e64c30e68ded2d75eaa9585af | [
"if len(matrix) <= 1:\n return\nfor i in range(len(matrix)):\n for j in range(i + 1, len(matrix)):\n matrix[i][j], matrix[j][i] = (matrix[j][i], matrix[i][j])\nfor k in range(len(matrix)):\n matrix[k] = matrix[k][::-1]",
"if len(matrix) <= 1:\n return\nfor i in range(len(matrix)):\n for j in... | <|body_start_0|>
if len(matrix) <= 1:
return
for i in range(len(matrix)):
for j in range(i + 1, len(matrix)):
matrix[i][j], matrix[j][i] = (matrix[j][i], matrix[i][j])
for k in range(len(matrix)):
matrix[k] = matrix[k][::-1]
<|end_body_0|>
<|b... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate1(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-p... | stack_v2_sparse_classes_10k_train_008982 | 918 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.",
"name": "rotate",
"signature": "def rotate(self, matrix)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.",
... | 2 | stack_v2_sparse_classes_30k_train_005404 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def rotate1(self, matrix): :type matrix: List[List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def rotate1(self, matrix): :type matrix: List[List[... | b8ec1350e904665f1375c29a53f443ecf262d723 | <|skeleton|>
class Solution:
def rotate(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate1(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-p... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
if len(matrix) <= 1:
return
for i in range(len(matrix)):
for j in range(i + 1, len(matrix)):
matrix[i][j]... | the_stack_v2_python_sparse | leetcode/048旋转图像.py | ShawDa/Coding | train | 0 | |
bd1a9b9d54a1c15e3cf7769fd8823aafc6754247 | [
"quizTakerId = kwargs['pk']\nquizTaker = QuizTakers.objects.filter(id=quizTakerId).first()\nresponse = StudentResponse.objects.filter(quiztaker=quizTaker)\nserializer = ResponseSerializer(response, many=True)\nreturn Response(serializer.data)",
"quizTakerId = kwargs['pk']\nquizTaker = QuizTakers.objects.filter(id... | <|body_start_0|>
quizTakerId = kwargs['pk']
quizTaker = QuizTakers.objects.filter(id=quizTakerId).first()
response = StudentResponse.objects.filter(quiztaker=quizTaker)
serializer = ResponseSerializer(response, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_st... | ListCreateResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListCreateResponse:
def get(self, request, *args, **kwargs):
"""return quiz taker answers"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""add quiz taker answers"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
quizTakerId = kwargs['pk']
... | stack_v2_sparse_classes_10k_train_008983 | 1,434 | permissive | [
{
"docstring": "return quiz taker answers",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "add quiz taker answers",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003214 | Implement the Python class `ListCreateResponse` described below.
Class description:
Implement the ListCreateResponse class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): return quiz taker answers
- def post(self, request, *args, **kwargs): add quiz taker answers | Implement the Python class `ListCreateResponse` described below.
Class description:
Implement the ListCreateResponse class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): return quiz taker answers
- def post(self, request, *args, **kwargs): add quiz taker answers
<|skeleton|>
class List... | bebeff8d055ea769773cd1c749f42408aa83f5b9 | <|skeleton|>
class ListCreateResponse:
def get(self, request, *args, **kwargs):
"""return quiz taker answers"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""add quiz taker answers"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ListCreateResponse:
def get(self, request, *args, **kwargs):
"""return quiz taker answers"""
quizTakerId = kwargs['pk']
quizTaker = QuizTakers.objects.filter(id=quizTakerId).first()
response = StudentResponse.objects.filter(quiztaker=quizTaker)
serializer = ResponseSeri... | the_stack_v2_python_sparse | backend/quiz/api/views/response.py | mahmoud-batman/quizz-app | train | 0 | |
0c7a1a5b96126d09e5945b798b8f16a5c95957cd | [
"super().__init__(*args, **kwargs)\nself.command_q = command_q\nself.signal_q = signal_q\nself.sphere_args = sphere_args\nself.fname = fname\nself.file_lock = file_lock",
"try:\n self._main()\nexcept:\n print('-' * 60)\n traceback.print_exc()\n print('-' * 60)",
"sphere = EwaldSphere(data_file=self.... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.command_q = command_q
self.signal_q = signal_q
self.sphere_args = sphere_args
self.fname = fname
self.file_lock = file_lock
<|end_body_0|>
<|body_start_1|>
try:
self._main()
except:
... | Base class for wrangler processes. Subclasses should extend _main, NOT run. _main is run in a try except clause which ensures errors are printed. attributes: command_q: mp.Queue, queue for commands from parent thread. file_lock: mp.Condition, process safe lock for file access fname: str, path to data file signal_q: que... | wranglerProcess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class wranglerProcess:
"""Base class for wrangler processes. Subclasses should extend _main, NOT run. _main is run in a try except clause which ensures errors are printed. attributes: command_q: mp.Queue, queue for commands from parent thread. file_lock: mp.Condition, process safe lock for file access ... | stack_v2_sparse_classes_10k_train_008984 | 8,377 | no_license | [
{
"docstring": "command_q: mp.Queue, queue for commands from parent thread. signal_q: queue to place signals back to parent thread. sphere_args: dict, used as **kwargs in sphere initialization. see EwaldSphere. fname: str, path to data file file_lock: mp.Condition, process safe lock for file access",
"name"... | 3 | stack_v2_sparse_classes_30k_train_002497 | Implement the Python class `wranglerProcess` described below.
Class description:
Base class for wrangler processes. Subclasses should extend _main, NOT run. _main is run in a try except clause which ensures errors are printed. attributes: command_q: mp.Queue, queue for commands from parent thread. file_lock: mp.Condit... | Implement the Python class `wranglerProcess` described below.
Class description:
Base class for wrangler processes. Subclasses should extend _main, NOT run. _main is run in a try except clause which ensures errors are printed. attributes: command_q: mp.Queue, queue for commands from parent thread. file_lock: mp.Condit... | f145e757d092d85b5a21dc4c36d99f82d55f7037 | <|skeleton|>
class wranglerProcess:
"""Base class for wrangler processes. Subclasses should extend _main, NOT run. _main is run in a try except clause which ensures errors are printed. attributes: command_q: mp.Queue, queue for commands from parent thread. file_lock: mp.Condition, process safe lock for file access ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class wranglerProcess:
"""Base class for wrangler processes. Subclasses should extend _main, NOT run. _main is run in a try except clause which ensures errors are printed. attributes: command_q: mp.Queue, queue for commands from parent thread. file_lock: mp.Condition, process safe lock for file access fname: str, p... | the_stack_v2_python_sparse | xdart/gui/tabs/static_scan/wranglers/wrangler_widget.py | rwalroth/xdart | train | 2 |
6c39e0d144ae45bb76ee7f90bccef400bc802762 | [
"count = 0\nsorted_array = sorted(arr)\ns1 = s2 = 0\nfor num1, num2 in zip(arr, sorted_array):\n s1 += num1\n s2 += num2\n if s1 == s2:\n count += 1\nreturn count",
"count = max_value = 0\nfor i in range(len(arr)):\n max_value = max(max_value, arr[i])\n if max_value == i:\n count += 1... | <|body_start_0|>
count = 0
sorted_array = sorted(arr)
s1 = s2 = 0
for num1, num2 in zip(arr, sorted_array):
s1 += num1
s2 += num2
if s1 == s2:
count += 1
return count
<|end_body_0|>
<|body_start_1|>
count = max_value = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxChunksToSorted(self, arr: List[int]) -> int:
"""sorting and compare sum"""
<|body_0|>
def maxChunksToSorted(self, arr: List[int]) -> int:
"""use index"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
count = 0
sorted_array = ... | stack_v2_sparse_classes_10k_train_008985 | 905 | no_license | [
{
"docstring": "sorting and compare sum",
"name": "maxChunksToSorted",
"signature": "def maxChunksToSorted(self, arr: List[int]) -> int"
},
{
"docstring": "use index",
"name": "maxChunksToSorted",
"signature": "def maxChunksToSorted(self, arr: List[int]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_004836 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxChunksToSorted(self, arr: List[int]) -> int: sorting and compare sum
- def maxChunksToSorted(self, arr: List[int]) -> int: use index | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxChunksToSorted(self, arr: List[int]) -> int: sorting and compare sum
- def maxChunksToSorted(self, arr: List[int]) -> int: use index
<|skeleton|>
class Solution:
def... | fce451090ecaf5471aab5a9413ac0675639ace5d | <|skeleton|>
class Solution:
def maxChunksToSorted(self, arr: List[int]) -> int:
"""sorting and compare sum"""
<|body_0|>
def maxChunksToSorted(self, arr: List[int]) -> int:
"""use index"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxChunksToSorted(self, arr: List[int]) -> int:
"""sorting and compare sum"""
count = 0
sorted_array = sorted(arr)
s1 = s2 = 0
for num1, num2 in zip(arr, sorted_array):
s1 += num1
s2 += num2
if s1 == s2:
... | the_stack_v2_python_sparse | array_stack_queue/769MaxChunksToMakeSorted.py | kidexp/91leetcode | train | 0 | |
0cd66ab4a8c2b5a1c4847b517486b38540457e69 | [
"self.rotateByDegrees_(angle)\ntf = NSAffineTransform.transform()\ntf.rotateByDegrees_(-angle)\noldPt = tf.transformPoint_(point)\noldPt.x -= point.x\noldPt.y -= point.y\nself.translateXBy_yBy_(oldPt.x, oldPt.y)",
"self.rotateByRadians_(angle)\ntf = NSAffineTransform.transform()\ntf.rotateByRadians_(-angle)\noldP... | <|body_start_0|>
self.rotateByDegrees_(angle)
tf = NSAffineTransform.transform()
tf.rotateByDegrees_(-angle)
oldPt = tf.transformPoint_(point)
oldPt.x -= point.x
oldPt.y -= point.y
self.translateXBy_yBy_(oldPt.x, oldPt.y)
<|end_body_0|>
<|body_start_1|>
s... | NSAffineTransform | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NSAffineTransform:
def rotateByDegrees_atPoint_(self, angle, point):
"""Rotate the coordinatespace ``angle`` degrees around ``point``."""
<|body_0|>
def rotateByRadians_atPoint_(self, angle, point):
"""Rotate the coordinatespace ``angle`` radians around ``point``."""... | stack_v2_sparse_classes_10k_train_008986 | 1,027 | permissive | [
{
"docstring": "Rotate the coordinatespace ``angle`` degrees around ``point``.",
"name": "rotateByDegrees_atPoint_",
"signature": "def rotateByDegrees_atPoint_(self, angle, point)"
},
{
"docstring": "Rotate the coordinatespace ``angle`` radians around ``point``.",
"name": "rotateByRadians_at... | 2 | stack_v2_sparse_classes_30k_train_006841 | Implement the Python class `NSAffineTransform` described below.
Class description:
Implement the NSAffineTransform class.
Method signatures and docstrings:
- def rotateByDegrees_atPoint_(self, angle, point): Rotate the coordinatespace ``angle`` degrees around ``point``.
- def rotateByRadians_atPoint_(self, angle, poi... | Implement the Python class `NSAffineTransform` described below.
Class description:
Implement the NSAffineTransform class.
Method signatures and docstrings:
- def rotateByDegrees_atPoint_(self, angle, point): Rotate the coordinatespace ``angle`` degrees around ``point``.
- def rotateByRadians_atPoint_(self, angle, poi... | 375ab43104712c5e1c782e5ea5f04073b5f8916c | <|skeleton|>
class NSAffineTransform:
def rotateByDegrees_atPoint_(self, angle, point):
"""Rotate the coordinatespace ``angle`` degrees around ``point``."""
<|body_0|>
def rotateByRadians_atPoint_(self, angle, point):
"""Rotate the coordinatespace ``angle`` radians around ``point``."""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NSAffineTransform:
def rotateByDegrees_atPoint_(self, angle, point):
"""Rotate the coordinatespace ``angle`` degrees around ``point``."""
self.rotateByDegrees_(angle)
tf = NSAffineTransform.transform()
tf.rotateByDegrees_(-angle)
oldPt = tf.transformPoint_(point)
... | the_stack_v2_python_sparse | venv/lib/python3.7/site-packages/PyObjCTools/FndCategories.py | ykhade/Advent_Of_Code_2019 | train | 1 | |
029e5f6f34691e3d3f7ad351588495e13dd5834c | [
"session.query(DbFunction).filter_by(kb=db_kb).delete()\nfor func in func_manager.values():\n db_func = DbFunction(kb=db_kb, addr=func.addr, blob=func.serialize())\n session.add(db_func)",
"funcs = FunctionManager(kb)\ndb_funcs = session.query(DbFunction).filter_by(kb=db_kb)\nall_func_addrs = set(map(lambda... | <|body_start_0|>
session.query(DbFunction).filter_by(kb=db_kb).delete()
for func in func_manager.values():
db_func = DbFunction(kb=db_kb, addr=func.addr, blob=func.serialize())
session.add(db_func)
<|end_body_0|>
<|body_start_1|>
funcs = FunctionManager(kb)
db_fu... | Serialize/unserialize a function manager and its functions. | FunctionManagerSerializer | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FunctionManagerSerializer:
"""Serialize/unserialize a function manager and its functions."""
def dump(session, db_kb: 'DbKnowledgeBase', func_manager: FunctionManager):
""":param session: :param DbKnowledgeBase db_kb: :param FunctionManager func_manager: :return:"""
<|body_0|... | stack_v2_sparse_classes_10k_train_008987 | 1,696 | permissive | [
{
"docstring": ":param session: :param DbKnowledgeBase db_kb: :param FunctionManager func_manager: :return:",
"name": "dump",
"signature": "def dump(session, db_kb: 'DbKnowledgeBase', func_manager: FunctionManager)"
},
{
"docstring": ":param session: :param DbKnowledgeBase db_kb: :param Knowledg... | 2 | null | Implement the Python class `FunctionManagerSerializer` described below.
Class description:
Serialize/unserialize a function manager and its functions.
Method signatures and docstrings:
- def dump(session, db_kb: 'DbKnowledgeBase', func_manager: FunctionManager): :param session: :param DbKnowledgeBase db_kb: :param Fu... | Implement the Python class `FunctionManagerSerializer` described below.
Class description:
Serialize/unserialize a function manager and its functions.
Method signatures and docstrings:
- def dump(session, db_kb: 'DbKnowledgeBase', func_manager: FunctionManager): :param session: :param DbKnowledgeBase db_kb: :param Fu... | 37e8ca1c3308ec601ad1d7c6bc8081ff38a7cffd | <|skeleton|>
class FunctionManagerSerializer:
"""Serialize/unserialize a function manager and its functions."""
def dump(session, db_kb: 'DbKnowledgeBase', func_manager: FunctionManager):
""":param session: :param DbKnowledgeBase db_kb: :param FunctionManager func_manager: :return:"""
<|body_0|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FunctionManagerSerializer:
"""Serialize/unserialize a function manager and its functions."""
def dump(session, db_kb: 'DbKnowledgeBase', func_manager: FunctionManager):
""":param session: :param DbKnowledgeBase db_kb: :param FunctionManager func_manager: :return:"""
session.query(DbFuncti... | the_stack_v2_python_sparse | angr/angrdb/serializers/funcs.py | angr/angr | train | 7,184 |
9589a47bd34b78dc096b895378410a6fe6eaf639 | [
"if not str(uuid).isdigit() or int(uuid) <= 0:\n api.logger.error(f'[{datetime.now()}], movies, put, \"id\": {uuid}, Error: \"Wrong movie ID')\n return ({'Error': 'Wrong movie ID'}, 404)\nuuid = int(uuid)\nmovie = Movie.query.filter_by(id=uuid).first()\nif not movie:\n api.logger.error(f'[{datetime.now()}]... | <|body_start_0|>
if not str(uuid).isdigit() or int(uuid) <= 0:
api.logger.error(f'[{datetime.now()}], movies, put, "id": {uuid}, Error: "Wrong movie ID')
return ({'Error': 'Wrong movie ID'}, 404)
uuid = int(uuid)
movie = Movie.query.filter_by(id=uuid).first()
if n... | Movie Api | MovieApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovieApi:
"""Movie Api"""
def get(self, uuid=None):
"""Output a single movie"""
<|body_0|>
def put(self, uuid: int):
"""Changing a movie"""
<|body_1|>
def delete(uuid: int):
"""Delete a movie"""
<|body_2|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_10k_train_008988 | 12,285 | no_license | [
{
"docstring": "Output a single movie",
"name": "get",
"signature": "def get(self, uuid=None)"
},
{
"docstring": "Changing a movie",
"name": "put",
"signature": "def put(self, uuid: int)"
},
{
"docstring": "Delete a movie",
"name": "delete",
"signature": "def delete(uuid:... | 3 | stack_v2_sparse_classes_30k_train_000265 | Implement the Python class `MovieApi` described below.
Class description:
Movie Api
Method signatures and docstrings:
- def get(self, uuid=None): Output a single movie
- def put(self, uuid: int): Changing a movie
- def delete(uuid: int): Delete a movie | Implement the Python class `MovieApi` described below.
Class description:
Movie Api
Method signatures and docstrings:
- def get(self, uuid=None): Output a single movie
- def put(self, uuid: int): Changing a movie
- def delete(uuid: int): Delete a movie
<|skeleton|>
class MovieApi:
"""Movie Api"""
def get(se... | b3a021bff8112a3eb81f553b3eb0df751a488adb | <|skeleton|>
class MovieApi:
"""Movie Api"""
def get(self, uuid=None):
"""Output a single movie"""
<|body_0|>
def put(self, uuid: int):
"""Changing a movie"""
<|body_1|>
def delete(uuid: int):
"""Delete a movie"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MovieApi:
"""Movie Api"""
def get(self, uuid=None):
"""Output a single movie"""
if not str(uuid).isdigit() or int(uuid) <= 0:
api.logger.error(f'[{datetime.now()}], movies, put, "id": {uuid}, Error: "Wrong movie ID')
return ({'Error': 'Wrong movie ID'}, 404)
... | the_stack_v2_python_sparse | app/resources/movies.py | cyr1z/api-movie-library- | train | 1 |
9b3cb5f9ed083599534f3d4a073815d643880cc1 | [
"self.create_new_group = create_new_group\nself.ms_groups_vec = ms_groups_vec\nself.restore_original_owners_members = restore_original_owners_members\nself.restore_to_original = restore_to_original\nself.target_group = target_group\nself.target_group_name = target_group_name\nself.target_group_owner = target_group_... | <|body_start_0|>
self.create_new_group = create_new_group
self.ms_groups_vec = ms_groups_vec
self.restore_original_owners_members = restore_original_owners_members
self.restore_to_original = restore_to_original
self.target_group = target_group
self.target_group_name = tar... | Implementation of the 'RestoreO365GroupsParams' model. TODO: type description here. Attributes: create_new_group (bool): Bool which specifies, if we have to create a new group if it doesn't exist. ms_groups_vec (list of RestoreO365GroupsParams_MSGroupInfo): List of groups getting restored. restore_original_owners_membe... | RestoreO365GroupsParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestoreO365GroupsParams:
"""Implementation of the 'RestoreO365GroupsParams' model. TODO: type description here. Attributes: create_new_group (bool): Bool which specifies, if we have to create a new group if it doesn't exist. ms_groups_vec (list of RestoreO365GroupsParams_MSGroupInfo): List of gro... | stack_v2_sparse_classes_10k_train_008989 | 4,068 | permissive | [
{
"docstring": "Constructor for the RestoreO365GroupsParams class",
"name": "__init__",
"signature": "def __init__(self, create_new_group=None, ms_groups_vec=None, restore_original_owners_members=None, restore_to_original=None, target_group=None, target_group_name=None, target_group_owner=None)"
},
... | 2 | stack_v2_sparse_classes_30k_train_002390 | Implement the Python class `RestoreO365GroupsParams` described below.
Class description:
Implementation of the 'RestoreO365GroupsParams' model. TODO: type description here. Attributes: create_new_group (bool): Bool which specifies, if we have to create a new group if it doesn't exist. ms_groups_vec (list of RestoreO36... | Implement the Python class `RestoreO365GroupsParams` described below.
Class description:
Implementation of the 'RestoreO365GroupsParams' model. TODO: type description here. Attributes: create_new_group (bool): Bool which specifies, if we have to create a new group if it doesn't exist. ms_groups_vec (list of RestoreO36... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestoreO365GroupsParams:
"""Implementation of the 'RestoreO365GroupsParams' model. TODO: type description here. Attributes: create_new_group (bool): Bool which specifies, if we have to create a new group if it doesn't exist. ms_groups_vec (list of RestoreO365GroupsParams_MSGroupInfo): List of gro... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RestoreO365GroupsParams:
"""Implementation of the 'RestoreO365GroupsParams' model. TODO: type description here. Attributes: create_new_group (bool): Bool which specifies, if we have to create a new group if it doesn't exist. ms_groups_vec (list of RestoreO365GroupsParams_MSGroupInfo): List of groups getting r... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_o_365_groups_params.py | cohesity/management-sdk-python | train | 24 |
373f7d1380b1773e5921521e75257f3befa159ac | [
"if source == 'auxiliary_file':\n logger.debug('Creating an auxiliary FileStoreItem')\n item = self.create(sharename=sharename, filetype=filetype)\n return item\nif not source:\n logger.error('Source is required but was not provided')\n return None\nitem = self.create(source=map_source(source), share... | <|body_start_0|>
if source == 'auxiliary_file':
logger.debug('Creating an auxiliary FileStoreItem')
item = self.create(sharename=sharename, filetype=filetype)
return item
if not source:
logger.error('Source is required but was not provided')
re... | Custom model manager to handle creation and retrieval of FileStoreItems | _FileStoreItemManager | [
"LicenseRef-scancode-warranty-disclaimer",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _FileStoreItemManager:
"""Custom model manager to handle creation and retrieval of FileStoreItems"""
def create_item(self, source, sharename='', filetype=''):
"""A "constructor" for FileStoreItem. :param source: URL or absolute file system path to a file. :type source: str. :returns:... | stack_v2_sparse_classes_10k_train_008990 | 23,458 | permissive | [
{
"docstring": "A \"constructor\" for FileStoreItem. :param source: URL or absolute file system path to a file. :type source: str. :returns: FileStoreItem -- if success, None if failure.",
"name": "create_item",
"signature": "def create_item(self, source, sharename='', filetype='')"
},
{
"docstr... | 2 | stack_v2_sparse_classes_30k_train_003625 | Implement the Python class `_FileStoreItemManager` described below.
Class description:
Custom model manager to handle creation and retrieval of FileStoreItems
Method signatures and docstrings:
- def create_item(self, source, sharename='', filetype=''): A "constructor" for FileStoreItem. :param source: URL or absolute... | Implement the Python class `_FileStoreItemManager` described below.
Class description:
Custom model manager to handle creation and retrieval of FileStoreItems
Method signatures and docstrings:
- def create_item(self, source, sharename='', filetype=''): A "constructor" for FileStoreItem. :param source: URL or absolute... | fca97c904be407c6619608e13437f25a9fc9e979 | <|skeleton|>
class _FileStoreItemManager:
"""Custom model manager to handle creation and retrieval of FileStoreItems"""
def create_item(self, source, sharename='', filetype=''):
"""A "constructor" for FileStoreItem. :param source: URL or absolute file system path to a file. :type source: str. :returns:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _FileStoreItemManager:
"""Custom model manager to handle creation and retrieval of FileStoreItems"""
def create_item(self, source, sharename='', filetype=''):
"""A "constructor" for FileStoreItem. :param source: URL or absolute file system path to a file. :type source: str. :returns: FileStoreIte... | the_stack_v2_python_sparse | refinery/file_store/models.py | ShuhratBek/refinery-platform | train | 1 |
cc860b29375d98cbbad73336b6919396ffa08e9c | [
"if not check_exist(file):\n assert False, 'Cannot find the KPOINTS file. Check the path: ' + file\nelse:\n self.kpoints = open(file, 'r').readlines()",
"plane = self.kpoints[0].split()[-5]\nkrange = np.float64(self.kpoints[0].split()[-4:-2])\nnpoint = np.int64(self.kpoints[0].split()[-2:])\nreturn (plane, ... | <|body_start_0|>
if not check_exist(file):
assert False, 'Cannot find the KPOINTS file. Check the path: ' + file
else:
self.kpoints = open(file, 'r').readlines()
<|end_body_0|>
<|body_start_1|>
plane = self.kpoints[0].split()[-5]
krange = np.float64(self.kpoints[... | KPOINTS | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KPOINTS:
def __init__(self, file='KPOINTS'):
"""Read KPOINTS TODO: extend it to Selective dynamics"""
<|body_0|>
def get_spin_kmesh(self):
"""Read the kmesh header"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not check_exist(file):
... | stack_v2_sparse_classes_10k_train_008991 | 31,019 | permissive | [
{
"docstring": "Read KPOINTS TODO: extend it to Selective dynamics",
"name": "__init__",
"signature": "def __init__(self, file='KPOINTS')"
},
{
"docstring": "Read the kmesh header",
"name": "get_spin_kmesh",
"signature": "def get_spin_kmesh(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000749 | Implement the Python class `KPOINTS` described below.
Class description:
Implement the KPOINTS class.
Method signatures and docstrings:
- def __init__(self, file='KPOINTS'): Read KPOINTS TODO: extend it to Selective dynamics
- def get_spin_kmesh(self): Read the kmesh header | Implement the Python class `KPOINTS` described below.
Class description:
Implement the KPOINTS class.
Method signatures and docstrings:
- def __init__(self, file='KPOINTS'): Read KPOINTS TODO: extend it to Selective dynamics
- def get_spin_kmesh(self): Read the kmesh header
<|skeleton|>
class KPOINTS:
def __ini... | 42945ee15465caa6fad1983597e23beac78b774d | <|skeleton|>
class KPOINTS:
def __init__(self, file='KPOINTS'):
"""Read KPOINTS TODO: extend it to Selective dynamics"""
<|body_0|>
def get_spin_kmesh(self):
"""Read the kmesh header"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KPOINTS:
def __init__(self, file='KPOINTS'):
"""Read KPOINTS TODO: extend it to Selective dynamics"""
if not check_exist(file):
assert False, 'Cannot find the KPOINTS file. Check the path: ' + file
else:
self.kpoints = open(file, 'r').readlines()
def get_sp... | the_stack_v2_python_sparse | mcu/vasp/vasp_io.py | hungpham2017/mcu | train | 44 | |
0771dde3c88db872a004e7b7d169c40014b13677 | [
"self.dataframe = df\nself.rows_count = None\nself.variables_count = None\nself.has_error = False\nself.error_messages = []\nself.final_output = OrderedDict()\nself.set_values()",
"if self.dataframe is not None:\n self.rows_count = self.dataframe.shape[0]\n self.variables_count = len(self.dataframe.columns)... | <|body_start_0|>
self.dataframe = df
self.rows_count = None
self.variables_count = None
self.has_error = False
self.error_messages = []
self.final_output = OrderedDict()
self.set_values()
<|end_body_0|>
<|body_start_1|>
if self.dataframe is not None:
... | DatasetLevelInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatasetLevelInfo:
def __init__(self, df):
"""This class sets the dataset level info of the preprocess file."""
<|body_0|>
def set_values(self):
""""dataset": { "row_cnt": 1000, "variable_cnt": 25 }"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sel... | stack_v2_sparse_classes_10k_train_008992 | 1,809 | permissive | [
{
"docstring": "This class sets the dataset level info of the preprocess file.",
"name": "__init__",
"signature": "def __init__(self, df)"
},
{
"docstring": "\"dataset\": { \"row_cnt\": 1000, \"variable_cnt\": 25 }",
"name": "set_values",
"signature": "def set_values(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006781 | Implement the Python class `DatasetLevelInfo` described below.
Class description:
Implement the DatasetLevelInfo class.
Method signatures and docstrings:
- def __init__(self, df): This class sets the dataset level info of the preprocess file.
- def set_values(self): "dataset": { "row_cnt": 1000, "variable_cnt": 25 } | Implement the Python class `DatasetLevelInfo` described below.
Class description:
Implement the DatasetLevelInfo class.
Method signatures and docstrings:
- def __init__(self, df): This class sets the dataset level info of the preprocess file.
- def set_values(self): "dataset": { "row_cnt": 1000, "variable_cnt": 25 }
... | 9461522219f5ef0f4877f24c8f5923e462bd9557 | <|skeleton|>
class DatasetLevelInfo:
def __init__(self, df):
"""This class sets the dataset level info of the preprocess file."""
<|body_0|>
def set_values(self):
""""dataset": { "row_cnt": 1000, "variable_cnt": 25 }"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DatasetLevelInfo:
def __init__(self, df):
"""This class sets the dataset level info of the preprocess file."""
self.dataframe = df
self.rows_count = None
self.variables_count = None
self.has_error = False
self.error_messages = []
self.final_output = Orde... | the_stack_v2_python_sparse | preprocess/raven_preprocess/dataset_level_info_util.py | TwoRavens/raven-metadata-service | train | 0 | |
1f2f968a0a62f1cda6f947114cc5d6512544c8e4 | [
"self.rect = rect\nself.function = function\nself.overlay = overlay if not isinstance(overlay, str) else ButtonFont.render(overlay, True, KDS.Colors.White)\nself.button_default_color = button_default_color\nself.button_highlighted_color = button_highlighted_color\nself.button_pressed_color = button_pressed_color\ns... | <|body_start_0|>
self.rect = rect
self.function = function
self.overlay = overlay if not isinstance(overlay, str) else ButtonFont.render(overlay, True, KDS.Colors.White)
self.button_default_color = button_default_color
self.button_highlighted_color = button_highlighted_color
... | Button | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Button:
def __init__(self, rect: pygame.Rect, function: Callable, overlay: Union[pygame.Surface, str]=None, button_default_color: Tuple[int, int, int]=(100, 100, 100), button_highlighted_color: Tuple[int, int, int]=(115, 115, 115), button_pressed_color: Tuple[int, int, int]=(90, 90, 90), button_... | stack_v2_sparse_classes_10k_train_008993 | 18,129 | no_license | [
{
"docstring": "Instantiates a new Button Args: rect (Rect): The rect where the button will be drawn. function (Callable): A function to be called when the button is pressed. overlay (Surface, optional): Any surface you want to write on top of the button. Defaults to None. button_default_color (Tuple[int, int, ... | 2 | stack_v2_sparse_classes_30k_train_005126 | Implement the Python class `Button` described below.
Class description:
Implement the Button class.
Method signatures and docstrings:
- def __init__(self, rect: pygame.Rect, function: Callable, overlay: Union[pygame.Surface, str]=None, button_default_color: Tuple[int, int, int]=(100, 100, 100), button_highlighted_col... | Implement the Python class `Button` described below.
Class description:
Implement the Button class.
Method signatures and docstrings:
- def __init__(self, rect: pygame.Rect, function: Callable, overlay: Union[pygame.Surface, str]=None, button_default_color: Tuple[int, int, int]=(100, 100, 100), button_highlighted_col... | 641695c56ea2d2a02cca1077b6289988ec9eeb3d | <|skeleton|>
class Button:
def __init__(self, rect: pygame.Rect, function: Callable, overlay: Union[pygame.Surface, str]=None, button_default_color: Tuple[int, int, int]=(100, 100, 100), button_highlighted_color: Tuple[int, int, int]=(115, 115, 115), button_pressed_color: Tuple[int, int, int]=(90, 90, 90), button_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Button:
def __init__(self, rect: pygame.Rect, function: Callable, overlay: Union[pygame.Surface, str]=None, button_default_color: Tuple[int, int, int]=(100, 100, 100), button_highlighted_color: Tuple[int, int, int]=(115, 115, 115), button_pressed_color: Tuple[int, int, int]=(90, 90, 90), button_disabled_color... | the_stack_v2_python_sparse | KDS/UI.py | KL-Corporation/Koponen-Dating-Simulator | train | 0 | |
75ca7e6efd65bc041187450c85762d1a1bb98f87 | [
"user = User.objects.get(email=email)\ntoken = Token.objects.get(user_id=user.id)\nurl = 'https://' if self.request.is_secure() else 'http://'\nurl += get_current_site(self.request).domain\nurl += '/en/activate/' + str(user.id) + '/' + str(token) + '/'\nreturn url",
"contact_list = [env_var('DEFAULT_TO_EMAIL')]\n... | <|body_start_0|>
user = User.objects.get(email=email)
token = Token.objects.get(user_id=user.id)
url = 'https://' if self.request.is_secure() else 'http://'
url += get_current_site(self.request).domain
url += '/en/activate/' + str(user.id) + '/' + str(token) + '/'
return ... | SendEmailViewMixin | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SendEmailViewMixin:
def activation_url(self, email):
"""Function will get the User ID and Token and generate a URL."""
<|body_0|>
def send_activation(self, email):
"""Function will send to the inputted email the URL that needs to be accessed to activate the account."... | stack_v2_sparse_classes_10k_train_008994 | 2,444 | permissive | [
{
"docstring": "Function will get the User ID and Token and generate a URL.",
"name": "activation_url",
"signature": "def activation_url(self, email)"
},
{
"docstring": "Function will send to the inputted email the URL that needs to be accessed to activate the account.",
"name": "send_activa... | 2 | stack_v2_sparse_classes_30k_train_006073 | Implement the Python class `SendEmailViewMixin` described below.
Class description:
Implement the SendEmailViewMixin class.
Method signatures and docstrings:
- def activation_url(self, email): Function will get the User ID and Token and generate a URL.
- def send_activation(self, email): Function will send to the inp... | Implement the Python class `SendEmailViewMixin` described below.
Class description:
Implement the SendEmailViewMixin class.
Method signatures and docstrings:
- def activation_url(self, email): Function will get the User ID and Token and generate a URL.
- def send_activation(self, email): Function will send to the inp... | 053973b5ff0b997c52bfaca8daf8e07db64a877c | <|skeleton|>
class SendEmailViewMixin:
def activation_url(self, email):
"""Function will get the User ID and Token and generate a URL."""
<|body_0|>
def send_activation(self, email):
"""Function will send to the inputted email the URL that needs to be accessed to activate the account."... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SendEmailViewMixin:
def activation_url(self, email):
"""Function will get the User ID and Token and generate a URL."""
user = User.objects.get(email=email)
token = Token.objects.get(user_id=user.id)
url = 'https://' if self.request.is_secure() else 'http://'
url += get_... | the_stack_v2_python_sparse | api/views/authentication/emailactivation.py | smegurus/smegurus-django | train | 1 | |
ee2163444009e02b30dd264718be56eeedbe166b | [
"self.num_classes = num_classes\nself.num_shots = num_shots\nself.num_queries = num_queries\nself.shape_x = shape_x\nself.dataset = dataset\nself.batch_size = batch_size\nself.rng = np.random.RandomState(706)",
"num_classes = self.num_classes\nnum_shots = self.num_shots\nnum_queries = self.num_queries\nshape_x = ... | <|body_start_0|>
self.num_classes = num_classes
self.num_shots = num_shots
self.num_queries = num_queries
self.shape_x = shape_x
self.dataset = dataset
self.batch_size = batch_size
self.rng = np.random.RandomState(706)
<|end_body_0|>
<|body_start_1|>
num_... | DataGenerator | [
"BSD-3-Clause",
"MIT",
"LicenseRef-scancode-proprietary-license",
"Apache-2.0",
"CC-BY-NC-4.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataGenerator:
def __init__(self, num_classes, num_shots, num_queries, shape_x, dataset, batch_size):
"""Create episode function Args: num_classes (int): number of support classes, generally called n_way in one-shot literatuer num_shots (int): number of shots per class num_queries (int):... | stack_v2_sparse_classes_10k_train_008995 | 3,834 | permissive | [
{
"docstring": "Create episode function Args: num_classes (int): number of support classes, generally called n_way in one-shot literatuer num_shots (int): number of shots per class num_queries (int): numper of queries per class. shape_x (tuple): dimension of the input image. dataset(nd_array): nd_array of (clas... | 2 | stack_v2_sparse_classes_30k_train_003328 | Implement the Python class `DataGenerator` described below.
Class description:
Implement the DataGenerator class.
Method signatures and docstrings:
- def __init__(self, num_classes, num_shots, num_queries, shape_x, dataset, batch_size): Create episode function Args: num_classes (int): number of support classes, gener... | Implement the Python class `DataGenerator` described below.
Class description:
Implement the DataGenerator class.
Method signatures and docstrings:
- def __init__(self, num_classes, num_shots, num_queries, shape_x, dataset, batch_size): Create episode function Args: num_classes (int): number of support classes, gener... | 41f71faa6efff7774a76bbd5af3198322a90a6ab | <|skeleton|>
class DataGenerator:
def __init__(self, num_classes, num_shots, num_queries, shape_x, dataset, batch_size):
"""Create episode function Args: num_classes (int): number of support classes, generally called n_way in one-shot literatuer num_shots (int): number of shots per class num_queries (int):... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DataGenerator:
def __init__(self, num_classes, num_shots, num_queries, shape_x, dataset, batch_size):
"""Create episode function Args: num_classes (int): number of support classes, generally called n_way in one-shot literatuer num_shots (int): number of shots per class num_queries (int): numper of que... | the_stack_v2_python_sparse | meta-learning/maml/data_generator_maml.py | sony/nnabla-examples | train | 308 | |
2540f2153f6c6bb0a6f4398e49bd1954bde0b3fa | [
"self.df_trinary = df_trinary\ndf_valid = self.df_trinary.applymap(lambda v: 1 if v in [-1, 0, 1] else np.nan)\nif np.isnan(df_valid.sum().sum()):\n raise ValueError('Argument is not a trinary dataframe')\nself.columns = df_trinary.columns\nself.num_col = len(self.columns)\nself.indices = self.df_trinary.index\n... | <|body_start_0|>
self.df_trinary = df_trinary
df_valid = self.df_trinary.applymap(lambda v: 1 if v in [-1, 0, 1] else np.nan)
if np.isnan(df_valid.sum().sum()):
raise ValueError('Argument is not a trinary dataframe')
self.columns = df_trinary.columns
self.num_col = le... | TrinaryDistance | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrinaryDistance:
def __init__(self, df_trinary):
"""Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1"""
<|body_0|>
def calcDistance(self):
"""Calculates the distance between all pairs of column vectors."""
<|... | stack_v2_sparse_classes_10k_train_008996 | 2,227 | permissive | [
{
"docstring": "Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1",
"name": "__init__",
"signature": "def __init__(self, df_trinary)"
},
{
"docstring": "Calculates the distance between all pairs of column vectors.",
"name": "calcDistance",
... | 2 | stack_v2_sparse_classes_30k_train_005246 | Implement the Python class `TrinaryDistance` described below.
Class description:
Implement the TrinaryDistance class.
Method signatures and docstrings:
- def __init__(self, df_trinary): Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1
- def calcDistance(self): Calcul... | Implement the Python class `TrinaryDistance` described below.
Class description:
Implement the TrinaryDistance class.
Method signatures and docstrings:
- def __init__(self, df_trinary): Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1
- def calcDistance(self): Calcul... | a57542245f117fe6c835cc9d7ad570b9853b7e6c | <|skeleton|>
class TrinaryDistance:
def __init__(self, df_trinary):
"""Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1"""
<|body_0|>
def calcDistance(self):
"""Calculates the distance between all pairs of column vectors."""
<|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TrinaryDistance:
def __init__(self, df_trinary):
"""Parameters ---------- df_trinary: DataFrame columns: vector names index: instances values: -1, 0, 1"""
self.df_trinary = df_trinary
df_valid = self.df_trinary.applymap(lambda v: 1 if v in [-1, 0, 1] else np.nan)
if np.isnan(df... | the_stack_v2_python_sparse | common_python/classifier/trinary_distance.py | ScienceStacks/common_python | train | 1 | |
d6b65b6bffc5b0a58a5bec5cc0b150e2ba349eb0 | [
"faster = lower = head\nfor _ in range(n):\n faster = faster.next\nif not faster:\n return head.next\nwhile faster:\n faster = faster.next\n if not faster:\n break\n lower = lower.next\nlower.next = lower.next.next\nreturn head",
"length = 0\nsource = head\nwhile head:\n head = head.next\... | <|body_start_0|>
faster = lower = head
for _ in range(n):
faster = faster.next
if not faster:
return head.next
while faster:
faster = faster.next
if not faster:
break
lower = lower.next
lower.next = lower... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_0|>
def removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_008997 | 2,050 | permissive | [
{
"docstring": ":type head: ListNode :type n: int :rtype: ListNode",
"name": "_removeNthFromEnd",
"signature": "def _removeNthFromEnd(self, head, n)"
},
{
"docstring": ":type head: ListNode :type n: int :rtype: ListNode",
"name": "removeNthFromEnd",
"signature": "def removeNthFromEnd(sel... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _removeNthFromEnd(self, head, n): :type head: ListNode :type n: int :rtype: ListNode
- def removeNthFromEnd(self, head, n): :type head: ListNode :type n: int :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _removeNthFromEnd(self, head, n): :type head: ListNode :type n: int :rtype: ListNode
- def removeNthFromEnd(self, head, n): :type head: ListNode :type n: int :rtype: ListNode... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_0|>
def removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def _removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
faster = lower = head
for _ in range(n):
faster = faster.next
if not faster:
return head.next
while faster:
faster = faster.next
... | the_stack_v2_python_sparse | 19.remove-nth-node-from-end-of-list.py | windard/leeeeee | train | 0 | |
d0c44c99119ac2e02260ff2f0b0d23a3c6d45be4 | [
"super().__init__()\ntotal_size = input_size + prev_input_size\nself.proj = nn.Linear(total_size, input_size)\nself.transform = nn.Linear(total_size, input_size)\nself.transform.bias.data.fill_(-2.0)",
"concat_inputs = torch.cat((current, previous), 1)\nproj_result = F.relu(self.proj(concat_inputs))\nproj_gate = ... | <|body_start_0|>
super().__init__()
total_size = input_size + prev_input_size
self.proj = nn.Linear(total_size, input_size)
self.transform = nn.Linear(total_size, input_size)
self.transform.bias.data.fill_(-2.0)
<|end_body_0|>
<|body_start_1|>
concat_inputs = torch.cat((... | The Highway update layer from [srivastava2015]_. .. [srivastava2015] Srivastava, R. K., *et al.* (2015). `Highway Networks <http://arxiv.org/abs/1505.00387>`_. *arXiv*, 1505.00387. | Highway | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Highway:
"""The Highway update layer from [srivastava2015]_. .. [srivastava2015] Srivastava, R. K., *et al.* (2015). `Highway Networks <http://arxiv.org/abs/1505.00387>`_. *arXiv*, 1505.00387."""
def __init__(self, input_size: int, prev_input_size: int):
"""Instantiate the Highway up... | stack_v2_sparse_classes_10k_train_008998 | 25,672 | no_license | [
{
"docstring": "Instantiate the Highway update layer. :param input_size: Current representation size. :param prev_input_size: Size of the representation obtained by the previous convolutional layer.",
"name": "__init__",
"signature": "def __init__(self, input_size: int, prev_input_size: int)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_001615 | Implement the Python class `Highway` described below.
Class description:
The Highway update layer from [srivastava2015]_. .. [srivastava2015] Srivastava, R. K., *et al.* (2015). `Highway Networks <http://arxiv.org/abs/1505.00387>`_. *arXiv*, 1505.00387.
Method signatures and docstrings:
- def __init__(self, input_siz... | Implement the Python class `Highway` described below.
Class description:
The Highway update layer from [srivastava2015]_. .. [srivastava2015] Srivastava, R. K., *et al.* (2015). `Highway Networks <http://arxiv.org/abs/1505.00387>`_. *arXiv*, 1505.00387.
Method signatures and docstrings:
- def __init__(self, input_siz... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class Highway:
"""The Highway update layer from [srivastava2015]_. .. [srivastava2015] Srivastava, R. K., *et al.* (2015). `Highway Networks <http://arxiv.org/abs/1505.00387>`_. *arXiv*, 1505.00387."""
def __init__(self, input_size: int, prev_input_size: int):
"""Instantiate the Highway up... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Highway:
"""The Highway update layer from [srivastava2015]_. .. [srivastava2015] Srivastava, R. K., *et al.* (2015). `Highway Networks <http://arxiv.org/abs/1505.00387>`_. *arXiv*, 1505.00387."""
def __init__(self, input_size: int, prev_input_size: int):
"""Instantiate the Highway update layer. :... | the_stack_v2_python_sparse | generated/test_AstraZeneca_chemicalx.py | jansel/pytorch-jit-paritybench | train | 35 |
669ba5d3ddcb833f1e01465ccec198b7daee4b80 | [
"super(BertLayerNorm, self).__init__()\nself.reducemean = P.ReduceMean(keep_dims=True)\nself.sub = P.Sub()\nself.pow = P.Pow()\nself.add = P.Add()\nself.sqrt = P.Sqrt()\nself.div = P.Div()\nself.mul = P.Mul()\nself.variance_epsilon = eps\nself.bert_layer_norm_weight = Parameter(Tensor(np.random.uniform(0, 1, bert_l... | <|body_start_0|>
super(BertLayerNorm, self).__init__()
self.reducemean = P.ReduceMean(keep_dims=True)
self.sub = P.Sub()
self.pow = P.Pow()
self.add = P.Add()
self.sqrt = P.Sqrt()
self.div = P.Div()
self.mul = P.Mul()
self.variance_epsilon = eps
... | Normalization module of reader downstream | BertLayerNorm | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BertLayerNorm:
"""Normalization module of reader downstream"""
def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12):
"""init function"""
<|body_0|>
def construct(self, x):
"""construct function"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_10k_train_008999 | 9,011 | permissive | [
{
"docstring": "init function",
"name": "__init__",
"signature": "def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12)"
},
{
"docstring": "construct function",
"name": "construct",
"signature": "def construct(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000261 | Implement the Python class `BertLayerNorm` described below.
Class description:
Normalization module of reader downstream
Method signatures and docstrings:
- def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12): init function
- def construct(self, x): construct function | Implement the Python class `BertLayerNorm` described below.
Class description:
Normalization module of reader downstream
Method signatures and docstrings:
- def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12): init function
- def construct(self, x): construct function
<|skeleton|>... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class BertLayerNorm:
"""Normalization module of reader downstream"""
def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12):
"""init function"""
<|body_0|>
def construct(self, x):
"""construct function"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BertLayerNorm:
"""Normalization module of reader downstream"""
def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12):
"""init function"""
super(BertLayerNorm, self).__init__()
self.reducemean = P.ReduceMean(keep_dims=True)
self.sub = P.Sub... | the_stack_v2_python_sparse | research/nlp/tprr/src/reader_downstream.py | mindspore-ai/models | train | 301 |
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