blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
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value | snapshot_source_dir stringclasses 1
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value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0914beece2c2431f064261b90e0eab0ae9dc573a | [
"interactions = interaction_registry.Registry.get_all_interactions()\nobject_default_vals = object_registry.get_default_object_values()\nfor interaction in interactions:\n for rule_name in interaction.rules_dict:\n param_list = interaction.get_rule_param_list(rule_name)\n for _, param_obj_type in p... | <|body_start_0|>
interactions = interaction_registry.Registry.get_all_interactions()
object_default_vals = object_registry.get_default_object_values()
for interaction in interactions:
for rule_name in interaction.rules_dict:
param_list = interaction.get_rule_param_lis... | Test that the default value of objects recorded in extensions/objects/object_defaults.json correspond to the defined default values in objects.py for all objects that are used in rules. | ObjectDefaultValuesUnitTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObjectDefaultValuesUnitTests:
"""Test that the default value of objects recorded in extensions/objects/object_defaults.json correspond to the defined default values in objects.py for all objects that are used in rules."""
def test_all_rule_input_fields_have_default_values(self) -> None:
... | stack_v2_sparse_classes_36k_train_006400 | 3,831 | permissive | [
{
"docstring": "Checks that all rule input fields have a default value, and this is provided in get_default_values().",
"name": "test_all_rule_input_fields_have_default_values",
"signature": "def test_all_rule_input_fields_have_default_values(self) -> None"
},
{
"docstring": "Checks that the def... | 2 | null | Implement the Python class `ObjectDefaultValuesUnitTests` described below.
Class description:
Test that the default value of objects recorded in extensions/objects/object_defaults.json correspond to the defined default values in objects.py for all objects that are used in rules.
Method signatures and docstrings:
- de... | Implement the Python class `ObjectDefaultValuesUnitTests` described below.
Class description:
Test that the default value of objects recorded in extensions/objects/object_defaults.json correspond to the defined default values in objects.py for all objects that are used in rules.
Method signatures and docstrings:
- de... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class ObjectDefaultValuesUnitTests:
"""Test that the default value of objects recorded in extensions/objects/object_defaults.json correspond to the defined default values in objects.py for all objects that are used in rules."""
def test_all_rule_input_fields_have_default_values(self) -> None:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObjectDefaultValuesUnitTests:
"""Test that the default value of objects recorded in extensions/objects/object_defaults.json correspond to the defined default values in objects.py for all objects that are used in rules."""
def test_all_rule_input_fields_have_default_values(self) -> None:
"""Checks... | the_stack_v2_python_sparse | core/domain/object_registry_test.py | oppia/oppia | train | 6,172 |
4cfe4bad63704830383142db801fb210d0391b68 | [
"if not root:\n return None\nif root.left and root.right:\n left = self.invertTree(root.left)\n right = self.invertTree(root.right)\n root.left = right\n root.right = left\n return root\nif root.left and root.right == None:\n left = self.invertTree(root.left)\n root.left = None\n root.rig... | <|body_start_0|>
if not root:
return None
if root.left and root.right:
left = self.invertTree(root.left)
right = self.invertTree(root.right)
root.left = right
root.right = left
return root
if root.left and root.right == None... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def invertTree(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_0|>
def invertTree2(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_1|>
def invertTree3(self, root):
""":type root: TreeNode :rtype: TreeNode... | stack_v2_sparse_classes_36k_train_006401 | 2,594 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: TreeNode",
"name": "invertTree",
"signature": "def invertTree(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: TreeNode",
"name": "invertTree2",
"signature": "def invertTree2(self, root)"
},
{
"docstring": ":type root: Tree... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def invertTree(self, root): :type root: TreeNode :rtype: TreeNode
- def invertTree2(self, root): :type root: TreeNode :rtype: TreeNode
- def invertTree3(self, root): :type root: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def invertTree(self, root): :type root: TreeNode :rtype: TreeNode
- def invertTree2(self, root): :type root: TreeNode :rtype: TreeNode
- def invertTree3(self, root): :type root: ... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def invertTree(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_0|>
def invertTree2(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_1|>
def invertTree3(self, root):
""":type root: TreeNode :rtype: TreeNode... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def invertTree(self, root):
""":type root: TreeNode :rtype: TreeNode"""
if not root:
return None
if root.left and root.right:
left = self.invertTree(root.left)
right = self.invertTree(root.right)
root.left = right
ro... | the_stack_v2_python_sparse | 226. Invert Binary Tree/invert.py | Macielyoung/LeetCode | train | 1 | |
29b65a1f0bee220dada6a4a0c65e8e565ae998a6 | [
"assert len(self.rotated_data) == len(other.rotated_data)\ndata = [self_row + other_row for self_row, other_row in zip(self.rotated_data, other.rotated_data)]\nreturn AssembledImage(data)",
"assert len(self.rotated_data[0]) == len(other.rotated_data[0])\ndata = self.rotated_data + other.rotated_data\nreturn Assem... | <|body_start_0|>
assert len(self.rotated_data) == len(other.rotated_data)
data = [self_row + other_row for self_row, other_row in zip(self.rotated_data, other.rotated_data)]
return AssembledImage(data)
<|end_body_0|>
<|body_start_1|>
assert len(self.rotated_data[0]) == len(other.rotated... | The assembled image Public Class Methods: from_image_piece: Create instance from an image piece | AssembledImage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssembledImage:
"""The assembled image Public Class Methods: from_image_piece: Create instance from an image piece"""
def __add__(self, other: AssembledImage) -> AssembledImage:
"""Horizontal concatenation"""
<|body_0|>
def __mul__(self, other: AssembledImage) -> Assembl... | stack_v2_sparse_classes_36k_train_006402 | 6,417 | no_license | [
{
"docstring": "Horizontal concatenation",
"name": "__add__",
"signature": "def __add__(self, other: AssembledImage) -> AssembledImage"
},
{
"docstring": "Vertical concatenation",
"name": "__mul__",
"signature": "def __mul__(self, other: AssembledImage) -> AssembledImage"
},
{
"d... | 3 | stack_v2_sparse_classes_30k_train_012114 | Implement the Python class `AssembledImage` described below.
Class description:
The assembled image Public Class Methods: from_image_piece: Create instance from an image piece
Method signatures and docstrings:
- def __add__(self, other: AssembledImage) -> AssembledImage: Horizontal concatenation
- def __mul__(self, o... | Implement the Python class `AssembledImage` described below.
Class description:
The assembled image Public Class Methods: from_image_piece: Create instance from an image piece
Method signatures and docstrings:
- def __add__(self, other: AssembledImage) -> AssembledImage: Horizontal concatenation
- def __mul__(self, o... | bcca26134e0764f965a8486e67f61894dde3ba35 | <|skeleton|>
class AssembledImage:
"""The assembled image Public Class Methods: from_image_piece: Create instance from an image piece"""
def __add__(self, other: AssembledImage) -> AssembledImage:
"""Horizontal concatenation"""
<|body_0|>
def __mul__(self, other: AssembledImage) -> Assembl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AssembledImage:
"""The assembled image Public Class Methods: from_image_piece: Create instance from an image piece"""
def __add__(self, other: AssembledImage) -> AssembledImage:
"""Horizontal concatenation"""
assert len(self.rotated_data) == len(other.rotated_data)
data = [self_ro... | the_stack_v2_python_sparse | Day_20/utils/image.py | Mushinako/Advent-of-Code-2020 | train | 0 |
c5e0498f20e7218292b5325e00c741931e2a2b78 | [
"self.windowSize = size\nself.queue = collections.deque()\nself.sum = 0.0",
"if len(self.queue) == self.windowSize:\n self.sum -= self.queue.popleft()\nself.queue.append(val)\nself.sum += val\nreturn self.sum / len(self.queue)"
] | <|body_start_0|>
self.windowSize = size
self.queue = collections.deque()
self.sum = 0.0
<|end_body_0|>
<|body_start_1|>
if len(self.queue) == self.windowSize:
self.sum -= self.queue.popleft()
self.queue.append(val)
self.sum += val
return self.sum / le... | MovingAverage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.windowSize = size
self.q... | stack_v2_sparse_classes_36k_train_006403 | 831 | no_license | [
{
"docstring": "Initialize your data structure here. :type size: int",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": ":type val: int :rtype: float",
"name": "next",
"signature": "def next(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006050 | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float
<|skeleton|>
class MovingAverage:
... | 7134780687acfc2934562d8c7582fd33dfbefdf1 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
self.windowSize = size
self.queue = collections.deque()
self.sum = 0.0
def next(self, val):
""":type val: int :rtype: float"""
if len(self.queue) == self.win... | the_stack_v2_python_sparse | LeetCode/movingAverageFromDataStream.py | dixitomkar1809/Coding-Python | train | 0 | |
7f837fd05ab9f4d25e0a40af9b3f269b8dd807c2 | [
"table = {}\nfor index in range(len(nums)):\n if table.keys().__contains__(nums[index]):\n old_places = table[nums[index]]\n if index - old_places <= k:\n return True\n table[nums[index]] = index\n else:\n table[nums[index]] = index\nprint(table)\nreturn False",
"s = s... | <|body_start_0|>
table = {}
for index in range(len(nums)):
if table.keys().__contains__(nums[index]):
old_places = table[nums[index]]
if index - old_places <= k:
return True
table[nums[index]] = index
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def containsNearbyDuplicate1(self, nums, k):
"""超时 :type nums: List[int] :type k: int :rtype: bool"""
<|body_0|>
def containsNearbyDuplicate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_006404 | 1,174 | no_license | [
{
"docstring": "超时 :type nums: List[int] :type k: int :rtype: bool",
"name": "containsNearbyDuplicate1",
"signature": "def containsNearbyDuplicate1(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: bool",
"name": "containsNearbyDuplicate",
"signature": "def co... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def containsNearbyDuplicate1(self, nums, k): 超时 :type nums: List[int] :type k: int :rtype: bool
- def containsNearbyDuplicate(self, nums, k): :type nums: List[int] :type k: int :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def containsNearbyDuplicate1(self, nums, k): 超时 :type nums: List[int] :type k: int :rtype: bool
- def containsNearbyDuplicate(self, nums, k): :type nums: List[int] :type k: int :... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def containsNearbyDuplicate1(self, nums, k):
"""超时 :type nums: List[int] :type k: int :rtype: bool"""
<|body_0|>
def containsNearbyDuplicate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def containsNearbyDuplicate1(self, nums, k):
"""超时 :type nums: List[int] :type k: int :rtype: bool"""
table = {}
for index in range(len(nums)):
if table.keys().__contains__(nums[index]):
old_places = table[nums[index]]
if index - ol... | the_stack_v2_python_sparse | python/leetcode/219_Contains_Duplicate_II.py | bobcaoge/my-code | train | 0 | |
e25fab7c14a8ec487c117e48e4a7c55e5b285c36 | [
"inSpec = super(FastFourierTransform, cls).getInputSpecification()\ninSpec.addSub(InputData.parameterInputFactory('target', contentType=InputTypes.StringListType, strictMode=True))\nreturn inSpec",
"super().__init__()\nself.dynamic = True\nself.targets = None\nself.indices = None",
"super()._handleInput(paramIn... | <|body_start_0|>
inSpec = super(FastFourierTransform, cls).getInputSpecification()
inSpec.addSub(InputData.parameterInputFactory('target', contentType=InputTypes.StringListType, strictMode=True))
return inSpec
<|end_body_0|>
<|body_start_1|>
super().__init__()
self.dynamic = Tru... | Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target | FastFourierTransform | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FastFourierTransform:
"""Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target"""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the ... | stack_v2_sparse_classes_36k_train_006405 | 6,142 | permissive | [
{
"docstring": "Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for which we are retrieving the specification @ Out, inputSpecification, InputData.ParameterInput, class to use for specifying input of cls.",
"name": "getInputSpecification",
"signatur... | 6 | stack_v2_sparse_classes_30k_train_013115 | Implement the Python class `FastFourierTransform` described below.
Class description:
Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target
Method signatures and docstrings:
- def getInputSpecification(cls): Method to get a reference to a class tha... | Implement the Python class `FastFourierTransform` described below.
Class description:
Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target
Method signatures and docstrings:
- def getInputSpecification(cls): Method to get a reference to a class tha... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class FastFourierTransform:
"""Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target"""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FastFourierTransform:
"""Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target"""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for whi... | the_stack_v2_python_sparse | ravenframework/Models/PostProcessors/FastFourierTransform.py | idaholab/raven | train | 201 |
815599e0ab255ea1e72d08e65ee5eb5a5d4d9ed3 | [
"super(WordTokenizer, self).__init__()\nself.msg_printer = Printer()\nself.tokenizer = tokenizer\nself.allowed_tokenizers = ['spacy', 'nltk', 'vanilla', 'spacy-whitespace']\nassert self.tokenizer in self.allowed_tokenizers, AssertionError(f'The word tokenizer can be {self.allowed_tokenizers}')\nif self.tokenizer ==... | <|body_start_0|>
super(WordTokenizer, self).__init__()
self.msg_printer = Printer()
self.tokenizer = tokenizer
self.allowed_tokenizers = ['spacy', 'nltk', 'vanilla', 'spacy-whitespace']
assert self.tokenizer in self.allowed_tokenizers, AssertionError(f'The word tokenizer can be {... | WordTokenizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordTokenizer:
def __init__(self, tokenizer: str='spacy'):
"""WordTokenizers split the text into tokens Parameters ---------- tokenizer : str The type of tokenizer. spacy Tokenizer from spact nltk NLTK based tokenizer vanilla Tokenize words according to space spacy-whtiespace Same as van... | stack_v2_sparse_classes_36k_train_006406 | 2,563 | permissive | [
{
"docstring": "WordTokenizers split the text into tokens Parameters ---------- tokenizer : str The type of tokenizer. spacy Tokenizer from spact nltk NLTK based tokenizer vanilla Tokenize words according to space spacy-whtiespace Same as vanilla but implemented using custom white space tokenizer from spacy",
... | 3 | null | Implement the Python class `WordTokenizer` described below.
Class description:
Implement the WordTokenizer class.
Method signatures and docstrings:
- def __init__(self, tokenizer: str='spacy'): WordTokenizers split the text into tokens Parameters ---------- tokenizer : str The type of tokenizer. spacy Tokenizer from ... | Implement the Python class `WordTokenizer` described below.
Class description:
Implement the WordTokenizer class.
Method signatures and docstrings:
- def __init__(self, tokenizer: str='spacy'): WordTokenizers split the text into tokens Parameters ---------- tokenizer : str The type of tokenizer. spacy Tokenizer from ... | 1c061b99a35a9d8b565d9762aaaf5db979b50112 | <|skeleton|>
class WordTokenizer:
def __init__(self, tokenizer: str='spacy'):
"""WordTokenizers split the text into tokens Parameters ---------- tokenizer : str The type of tokenizer. spacy Tokenizer from spact nltk NLTK based tokenizer vanilla Tokenize words according to space spacy-whtiespace Same as van... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WordTokenizer:
def __init__(self, tokenizer: str='spacy'):
"""WordTokenizers split the text into tokens Parameters ---------- tokenizer : str The type of tokenizer. spacy Tokenizer from spact nltk NLTK based tokenizer vanilla Tokenize words according to space spacy-whtiespace Same as vanilla but imple... | the_stack_v2_python_sparse | sciwing/tokenizers/word_tokenizer.py | abhinavkashyap/sciwing | train | 58 | |
04e10d8620976a6a415dda66ef606185f2343e9d | [
"self.ids = ids\nself.ida = ida\nself.gr = int(gr)",
"\"\"\"\n if self.ida=='0':\n return 'The Student: '+str(self.ids)+'\nAssignment '+'\nStatus: Not Given'\n elif self.gr==0:\n return 'The Student: '+str(self.ids)+'\nAssignment: '+str(self.ida)+'\nStatus: Given \nGrade: Ungra... | <|body_start_0|>
self.ids = ids
self.ida = ida
self.gr = int(gr)
<|end_body_0|>
<|body_start_1|>
"""
if self.ida=='0':
return 'The Student: '+str(self.ids)+'
Assignment '+'
Status: Not Given'
elif self.gr==0:
... | This class will define a grade. | grade | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class grade:
"""This class will define a grade."""
def __init__(self, ids, ida, gr):
"""Constructor"""
<|body_0|>
def __str__(self):
"""The grade wil be returned as for exemple : The Student: 1 Assignment: 2 Grade: Ungraded Grade is "Ungraded" if self.gr=0 and it means... | stack_v2_sparse_classes_36k_train_006407 | 1,331 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, ids, ida, gr)"
},
{
"docstring": "The grade wil be returned as for exemple : The Student: 1 Assignment: 2 Grade: Ungraded Grade is \"Ungraded\" if self.gr=0 and it means that assignment is not finished yet. The St... | 2 | stack_v2_sparse_classes_30k_train_007751 | Implement the Python class `grade` described below.
Class description:
This class will define a grade.
Method signatures and docstrings:
- def __init__(self, ids, ida, gr): Constructor
- def __str__(self): The grade wil be returned as for exemple : The Student: 1 Assignment: 2 Grade: Ungraded Grade is "Ungraded" if s... | Implement the Python class `grade` described below.
Class description:
This class will define a grade.
Method signatures and docstrings:
- def __init__(self, ids, ida, gr): Constructor
- def __str__(self): The grade wil be returned as for exemple : The Student: 1 Assignment: 2 Grade: Ungraded Grade is "Ungraded" if s... | e956d7399f0b2b47f6ce539ac1672492250ee013 | <|skeleton|>
class grade:
"""This class will define a grade."""
def __init__(self, ids, ida, gr):
"""Constructor"""
<|body_0|>
def __str__(self):
"""The grade wil be returned as for exemple : The Student: 1 Assignment: 2 Grade: Ungraded Grade is "Ungraded" if self.gr=0 and it means... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class grade:
"""This class will define a grade."""
def __init__(self, ids, ida, gr):
"""Constructor"""
self.ids = ids
self.ida = ida
self.gr = int(gr)
def __str__(self):
"""The grade wil be returned as for exemple : The Student: 1 Assignment: 2 Grade: Ungraded Grade... | the_stack_v2_python_sparse | StudentsCatalog/Student Lab Assignments/Assignment 5-7/domain_grade.py | FarcasiuRazvan/Python-Projects | train | 0 |
f87344acd34b93217062e4a82faa0fb70a5b66ef | [
"lgas = set()\ncounts = Counter()\nfor row in Clinic.objects.values('lga', 'type').annotate(facilities=Count('id')):\n lgas.add(row['lga'])\n counts[row['type']] += row['facilities']\ncounts['lga'] = len(lgas)\nreturn counts",
"staff = Visit.objects.values('sender').distinct()\nsent = Visit.objects.values('... | <|body_start_0|>
lgas = set()
counts = Counter()
for row in Clinic.objects.values('lga', 'type').annotate(facilities=Count('id')):
lgas.add(row['lga'])
counts[row['type']] += row['facilities']
counts['lga'] = len(lgas)
return counts
<|end_body_0|>
<|body_... | Home | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Home:
def get_facility_counts(self):
"""Returns the total count of facilities, grouped by type, and the count of LGAs."""
<|body_0|>
def get_progress_to_date(self):
"""Returns a dictionary used to populate the "Progress to Date" view on the home page."""
<|bo... | stack_v2_sparse_classes_36k_train_006408 | 1,696 | permissive | [
{
"docstring": "Returns the total count of facilities, grouped by type, and the count of LGAs.",
"name": "get_facility_counts",
"signature": "def get_facility_counts(self)"
},
{
"docstring": "Returns a dictionary used to populate the \"Progress to Date\" view on the home page.",
"name": "get... | 2 | stack_v2_sparse_classes_30k_val_000912 | Implement the Python class `Home` described below.
Class description:
Implement the Home class.
Method signatures and docstrings:
- def get_facility_counts(self): Returns the total count of facilities, grouped by type, and the count of LGAs.
- def get_progress_to_date(self): Returns a dictionary used to populate the ... | Implement the Python class `Home` described below.
Class description:
Implement the Home class.
Method signatures and docstrings:
- def get_facility_counts(self): Returns the total count of facilities, grouped by type, and the count of LGAs.
- def get_progress_to_date(self): Returns a dictionary used to populate the ... | d8e7a36041429641ef956687c99cf3a1757b22b8 | <|skeleton|>
class Home:
def get_facility_counts(self):
"""Returns the total count of facilities, grouped by type, and the count of LGAs."""
<|body_0|>
def get_progress_to_date(self):
"""Returns a dictionary used to populate the "Progress to Date" view on the home page."""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Home:
def get_facility_counts(self):
"""Returns the total count of facilities, grouped by type, and the count of LGAs."""
lgas = set()
counts = Counter()
for row in Clinic.objects.values('lga', 'type').annotate(facilities=Count('id')):
lgas.add(row['lga'])
... | the_stack_v2_python_sparse | myvoice/core/views.py | myvoice-nigeria/myvoice | train | 1 | |
ea35731087791823e2425ed5f017911b372feed0 | [
"res = [0] * (len(nums) + 1)\nfor each in nums:\n res[each] = each\nif 0 in res[1:]:\n return res.index(0, 1)\nelse:\n return 0",
"length = len(nums)\nexpected_sum = length * (length + 1) // 2\nactual_sum = sum(nums)\nreturn expected_sum - actual_sum",
"nums.sort()\nif nums[-1] != len(nums):\n retur... | <|body_start_0|>
res = [0] * (len(nums) + 1)
for each in nums:
res[each] = each
if 0 in res[1:]:
return res.index(0, 1)
else:
return 0
<|end_body_0|>
<|body_start_1|>
length = len(nums)
expected_sum = length * (length + 1) // 2
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def missingNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def missingNumber_gauss(self, nums):
"""time O(n) space O(1) :type nums: List[int] :rtype: int"""
<|body_1|>
def missingNumber_sorting(self, nums):
"""tim... | stack_v2_sparse_classes_36k_train_006409 | 1,981 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "missingNumber",
"signature": "def missingNumber(self, nums)"
},
{
"docstring": "time O(n) space O(1) :type nums: List[int] :rtype: int",
"name": "missingNumber_gauss",
"signature": "def missingNumber_gauss(self, nums)"
},
{... | 5 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def missingNumber(self, nums): :type nums: List[int] :rtype: int
- def missingNumber_gauss(self, nums): time O(n) space O(1) :type nums: List[int] :rtype: int
- def missingNumber... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def missingNumber(self, nums): :type nums: List[int] :rtype: int
- def missingNumber_gauss(self, nums): time O(n) space O(1) :type nums: List[int] :rtype: int
- def missingNumber... | 85f71621c54f6b0029f3a2746f022f89dd7419d9 | <|skeleton|>
class Solution:
def missingNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def missingNumber_gauss(self, nums):
"""time O(n) space O(1) :type nums: List[int] :rtype: int"""
<|body_1|>
def missingNumber_sorting(self, nums):
"""tim... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def missingNumber(self, nums):
""":type nums: List[int] :rtype: int"""
res = [0] * (len(nums) + 1)
for each in nums:
res[each] = each
if 0 in res[1:]:
return res.index(0, 1)
else:
return 0
def missingNumber_gauss(self, ... | the_stack_v2_python_sparse | LeetCode/Array/268_missing_number.py | XyK0907/for_work | train | 0 | |
dc7fd4bfaf71b59844f909bef7fcb9b6527c3299 | [
"if not len(args) == 2:\n raise exceptions.FunctionArgumentException(\"'%s': expected exactly two arguments (string separator andlist of strings), got: '%s'.\" % (self.name, args))\nif not isinstance(args[0], str):\n raise exceptions.FunctionArgumentException(\"First argument of joining function '%s' must be... | <|body_start_0|>
if not len(args) == 2:
raise exceptions.FunctionArgumentException("'%s': expected exactly two arguments (string separator andlist of strings), got: '%s'." % (self.name, args))
if not isinstance(args[0], str):
raise exceptions.FunctionArgumentException("First argu... | JoinFunction is the base class for all function which join their provided arguments. It takes the form: " 'JoinFunction': [ "delimiter", ['elem1', 'elem2', ...] ] " It simply joins all of the elements it is provided with the given delimiter. | JoinFunction | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JoinFunction:
"""JoinFunction is the base class for all function which join their provided arguments. It takes the form: " 'JoinFunction': [ "delimiter", ['elem1', 'elem2', ...] ] " It simply joins all of the elements it is provided with the given delimiter."""
def _check_args(self, args):
... | stack_v2_sparse_classes_36k_train_006410 | 2,400 | permissive | [
{
"docstring": "_check_args validates the provided set of arguments.",
"name": "_check_args",
"signature": "def _check_args(self, args)"
},
{
"docstring": "apply applies the function to the given set of arguments and returns the result.",
"name": "apply",
"signature": "def apply(self, ar... | 2 | null | Implement the Python class `JoinFunction` described below.
Class description:
JoinFunction is the base class for all function which join their provided arguments. It takes the form: " 'JoinFunction': [ "delimiter", ['elem1', 'elem2', ...] ] " It simply joins all of the elements it is provided with the given delimiter.... | Implement the Python class `JoinFunction` described below.
Class description:
JoinFunction is the base class for all function which join their provided arguments. It takes the form: " 'JoinFunction': [ "delimiter", ['elem1', 'elem2', ...] ] " It simply joins all of the elements it is provided with the given delimiter.... | 83472c7a4af3496e28c1b7b4021e31c373f37784 | <|skeleton|>
class JoinFunction:
"""JoinFunction is the base class for all function which join their provided arguments. It takes the form: " 'JoinFunction': [ "delimiter", ['elem1', 'elem2', ...] ] " It simply joins all of the elements it is provided with the given delimiter."""
def _check_args(self, args):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JoinFunction:
"""JoinFunction is the base class for all function which join their provided arguments. It takes the form: " 'JoinFunction': [ "delimiter", ['elem1', 'elem2', ...] ] " It simply joins all of the elements it is provided with the given delimiter."""
def _check_args(self, args):
"""_ch... | the_stack_v2_python_sparse | heat2arm/parser/common/functions/join_function.py | travlaw/heat2arm | train | 0 |
1dc9ede2c51686593a2e93c3715934571636e051 | [
"super(MLP, self).__init__()\nassert type(input_dim) == int\nassert type(output_dim) == int\nassert type(hidden_layer_sizes) == list\nassert all((type(n) is int for n in hidden_layer_sizes))\nself._mlp = nn.Sequential()\nself._mlp.add_module('fc0', nn.Linear(input_dim, hidden_layer_sizes[0]))\nself._mlp.add_module(... | <|body_start_0|>
super(MLP, self).__init__()
assert type(input_dim) == int
assert type(output_dim) == int
assert type(hidden_layer_sizes) == list
assert all((type(n) is int for n in hidden_layer_sizes))
self._mlp = nn.Sequential()
self._mlp.add_module('fc0', nn.Li... | A Multi-layer Perceptron. | MLP | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MLP:
"""A Multi-layer Perceptron."""
def __init__(self, input_dim: int, output_dim: int, hidden_layer_sizes: List[int], nonlinearity: nn.Module, dropout: Optional[float]=None, batchnorm: Optional[bool]=False) -> None:
"""Initialize the MLP. Activations are softpluses. Parameters ----... | stack_v2_sparse_classes_36k_train_006411 | 13,993 | permissive | [
{
"docstring": "Initialize the MLP. Activations are softpluses. Parameters ---------- input_dim : int Dimension of the input. output_dim : int Dimension of the output variable. hidden_layer_sizes : List[int] List of sizes of all hidden layers. nonlinearity : torch.nn.Module A the nonlinearity to use (must be a ... | 2 | stack_v2_sparse_classes_30k_train_012334 | Implement the Python class `MLP` described below.
Class description:
A Multi-layer Perceptron.
Method signatures and docstrings:
- def __init__(self, input_dim: int, output_dim: int, hidden_layer_sizes: List[int], nonlinearity: nn.Module, dropout: Optional[float]=None, batchnorm: Optional[bool]=False) -> None: Initia... | Implement the Python class `MLP` described below.
Class description:
A Multi-layer Perceptron.
Method signatures and docstrings:
- def __init__(self, input_dim: int, output_dim: int, hidden_layer_sizes: List[int], nonlinearity: nn.Module, dropout: Optional[float]=None, batchnorm: Optional[bool]=False) -> None: Initia... | 184b1537c22ebc2f614677be8fe171de785bda42 | <|skeleton|>
class MLP:
"""A Multi-layer Perceptron."""
def __init__(self, input_dim: int, output_dim: int, hidden_layer_sizes: List[int], nonlinearity: nn.Module, dropout: Optional[float]=None, batchnorm: Optional[bool]=False) -> None:
"""Initialize the MLP. Activations are softpluses. Parameters ----... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MLP:
"""A Multi-layer Perceptron."""
def __init__(self, input_dim: int, output_dim: int, hidden_layer_sizes: List[int], nonlinearity: nn.Module, dropout: Optional[float]=None, batchnorm: Optional[bool]=False) -> None:
"""Initialize the MLP. Activations are softpluses. Parameters ---------- input_... | the_stack_v2_python_sparse | dynamics_learning/networks/models.py | cristovaoiglesias/replay-overshooting | train | 0 |
e52e73b953676e81bc858081f21ad203aa833f10 | [
"super(YOLOHead, self).__init__()\nac_type = cfg.HEAD.ACTIVATION_FN\nout_channel = (cfg.DATASET.NUM_CLASSES + 5) * 3\nself.conv1_1 = ConvBnActivation(128, 256, 3, 1, 1, ac_type)\nself.conv1_2 = nn.Conv2d(256, out_channel, 1, 1, 0)\nself.conv2_1 = ConvBnActivation(256, 512, 3, 1, 1, ac_type)\nself.conv2_2 = nn.Conv2... | <|body_start_0|>
super(YOLOHead, self).__init__()
ac_type = cfg.HEAD.ACTIVATION_FN
out_channel = (cfg.DATASET.NUM_CLASSES + 5) * 3
self.conv1_1 = ConvBnActivation(128, 256, 3, 1, 1, ac_type)
self.conv1_2 = nn.Conv2d(256, out_channel, 1, 1, 0)
self.conv2_1 = ConvBnActivati... | YOLOHead | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class YOLOHead:
def __init__(self, cfg):
"""Args: cfg: 配置文件"""
<|body_0|>
def forward(self, x1, x2, x3):
"""Args: x1, x2, x3: neck的输出"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(YOLOHead, self).__init__()
ac_type = cfg.HEAD.ACTIVATION_FN... | stack_v2_sparse_classes_36k_train_006412 | 1,347 | no_license | [
{
"docstring": "Args: cfg: 配置文件",
"name": "__init__",
"signature": "def __init__(self, cfg)"
},
{
"docstring": "Args: x1, x2, x3: neck的输出",
"name": "forward",
"signature": "def forward(self, x1, x2, x3)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003307 | Implement the Python class `YOLOHead` described below.
Class description:
Implement the YOLOHead class.
Method signatures and docstrings:
- def __init__(self, cfg): Args: cfg: 配置文件
- def forward(self, x1, x2, x3): Args: x1, x2, x3: neck的输出 | Implement the Python class `YOLOHead` described below.
Class description:
Implement the YOLOHead class.
Method signatures and docstrings:
- def __init__(self, cfg): Args: cfg: 配置文件
- def forward(self, x1, x2, x3): Args: x1, x2, x3: neck的输出
<|skeleton|>
class YOLOHead:
def __init__(self, cfg):
"""Args: c... | b28636c6b13466049d1b21234e21781129c5f7a2 | <|skeleton|>
class YOLOHead:
def __init__(self, cfg):
"""Args: cfg: 配置文件"""
<|body_0|>
def forward(self, x1, x2, x3):
"""Args: x1, x2, x3: neck的输出"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class YOLOHead:
def __init__(self, cfg):
"""Args: cfg: 配置文件"""
super(YOLOHead, self).__init__()
ac_type = cfg.HEAD.ACTIVATION_FN
out_channel = (cfg.DATASET.NUM_CLASSES + 5) * 3
self.conv1_1 = ConvBnActivation(128, 256, 3, 1, 1, ac_type)
self.conv1_2 = nn.Conv2d(256, o... | the_stack_v2_python_sparse | yolo/head/head.py | YohannXu/pytorch_yolov4 | train | 1 | |
ddd106a90cbba4a360f3564696d069d85cfb4ff5 | [
"self.db = db\nself.config = config\nself.slides = self.db[self.config['db_collection']]",
"image = self.slides.find_one({'_id': ObjectId(id)})\npath = image['path']\nosr = OpenSlide(path)\ndim = (int(self.config['macro_width']), int(self.config['macro_height']))\nif 'label' in osr.associated_images.keys():\n ... | <|body_start_0|>
self.db = db
self.config = config
self.slides = self.db[self.config['db_collection']]
<|end_body_0|>
<|body_start_1|>
image = self.slides.find_one({'_id': ObjectId(id)})
path = image['path']
osr = OpenSlide(path)
dim = (int(self.config['macro_wid... | LabelImage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LabelImage:
def __init__(self, db, config):
"""initialize Thumbnail resource Args: db: mongo db connection config: application configurations opt: deep zoom configurations Returns: None"""
<|body_0|>
def get(self, id):
"""Get slide label image --- tags: - Label Image... | stack_v2_sparse_classes_36k_train_006413 | 1,922 | permissive | [
{
"docstring": "initialize Thumbnail resource Args: db: mongo db connection config: application configurations opt: deep zoom configurations Returns: None",
"name": "__init__",
"signature": "def __init__(self, db, config)"
},
{
"docstring": "Get slide label image --- tags: - Label Image paramete... | 2 | stack_v2_sparse_classes_30k_train_017949 | Implement the Python class `LabelImage` described below.
Class description:
Implement the LabelImage class.
Method signatures and docstrings:
- def __init__(self, db, config): initialize Thumbnail resource Args: db: mongo db connection config: application configurations opt: deep zoom configurations Returns: None
- d... | Implement the Python class `LabelImage` described below.
Class description:
Implement the LabelImage class.
Method signatures and docstrings:
- def __init__(self, db, config): initialize Thumbnail resource Args: db: mongo db connection config: application configurations opt: deep zoom configurations Returns: None
- d... | 86f89f08dcfdab00ca295a6009820c02d84f7074 | <|skeleton|>
class LabelImage:
def __init__(self, db, config):
"""initialize Thumbnail resource Args: db: mongo db connection config: application configurations opt: deep zoom configurations Returns: None"""
<|body_0|>
def get(self, id):
"""Get slide label image --- tags: - Label Image... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LabelImage:
def __init__(self, db, config):
"""initialize Thumbnail resource Args: db: mongo db connection config: application configurations opt: deep zoom configurations Returns: None"""
self.db = db
self.config = config
self.slides = self.db[self.config['db_collection']]
... | the_stack_v2_python_sparse | api/routes/v1/LabelImage.py | dgutman/ADRCPathViewer | train | 1 | |
ff6d3c8c63d7c0e939c988edca6e41b59e06ec8a | [
"address = quote_plus(address, safe=',')\nmaps_address = 'http://maps.apple.com/?address=' + address\nwebbrowser.open(maps_address)",
"name = kwargs.get('name', 'Selected Location')\nmaps_address = 'http://maps.apple.com/?ll={},{}&q={}'.format(latitude, longitude, name)\nwebbrowser.open(maps_address)",
"latitud... | <|body_start_0|>
address = quote_plus(address, safe=',')
maps_address = 'http://maps.apple.com/?address=' + address
webbrowser.open(maps_address)
<|end_body_0|>
<|body_start_1|>
name = kwargs.get('name', 'Selected Location')
maps_address = 'http://maps.apple.com/?ll={},{}&q={}'.... | Implementation of iOS Maps API. | iOSMaps | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class iOSMaps:
"""Implementation of iOS Maps API."""
def _open_by_address(self, address, **kwargs):
""":param address: An address string that geolocation can understand."""
<|body_0|>
def _open_by_lat_long(self, latitude, longitude, **kwargs):
"""Open a coordinate span... | stack_v2_sparse_classes_36k_train_006414 | 2,264 | permissive | [
{
"docstring": ":param address: An address string that geolocation can understand.",
"name": "_open_by_address",
"signature": "def _open_by_address(self, address, **kwargs)"
},
{
"docstring": "Open a coordinate span denoting a latitudinal delta and a longitudinal delta (similar to MKCoordinateSp... | 4 | null | Implement the Python class `iOSMaps` described below.
Class description:
Implementation of iOS Maps API.
Method signatures and docstrings:
- def _open_by_address(self, address, **kwargs): :param address: An address string that geolocation can understand.
- def _open_by_lat_long(self, latitude, longitude, **kwargs): O... | Implement the Python class `iOSMaps` described below.
Class description:
Implementation of iOS Maps API.
Method signatures and docstrings:
- def _open_by_address(self, address, **kwargs): :param address: An address string that geolocation can understand.
- def _open_by_lat_long(self, latitude, longitude, **kwargs): O... | d8a2b3d16b12fc54667744a092a453ad007c9448 | <|skeleton|>
class iOSMaps:
"""Implementation of iOS Maps API."""
def _open_by_address(self, address, **kwargs):
""":param address: An address string that geolocation can understand."""
<|body_0|>
def _open_by_lat_long(self, latitude, longitude, **kwargs):
"""Open a coordinate span... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class iOSMaps:
"""Implementation of iOS Maps API."""
def _open_by_address(self, address, **kwargs):
""":param address: An address string that geolocation can understand."""
address = quote_plus(address, safe=',')
maps_address = 'http://maps.apple.com/?address=' + address
webbrow... | the_stack_v2_python_sparse | plyer/platforms/ios/maps.py | kivy/plyer | train | 1,516 |
b956596338ec082f9ab18daa3abece65b6978826 | [
"employees = []\ntry:\n with transaction.atomic():\n for employee in data['employees']:\n user = self.find_or_create_user(employee['email'])\n token, _ = Token.objects.get_or_create(user=user)\n company = Company.objects.get(id=data['company_id'])\n self.__creat... | <|body_start_0|>
employees = []
try:
with transaction.atomic():
for employee in data['employees']:
user = self.find_or_create_user(employee['email'])
token, _ = Token.objects.get_or_create(user=user)
company = Compan... | Employees serializer list. | EmployeesSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmployeesSerializer:
"""Employees serializer list."""
def create(self, data):
"""Create employees."""
<|body_0|>
def to_representation(self, instance):
"""Represent serializer data."""
<|body_1|>
def find_or_create_user(self, email):
"""Find ... | stack_v2_sparse_classes_36k_train_006415 | 3,659 | no_license | [
{
"docstring": "Create employees.",
"name": "create",
"signature": "def create(self, data)"
},
{
"docstring": "Represent serializer data.",
"name": "to_representation",
"signature": "def to_representation(self, instance)"
},
{
"docstring": "Find or create user by email.",
"na... | 5 | null | Implement the Python class `EmployeesSerializer` described below.
Class description:
Employees serializer list.
Method signatures and docstrings:
- def create(self, data): Create employees.
- def to_representation(self, instance): Represent serializer data.
- def find_or_create_user(self, email): Find or create user ... | Implement the Python class `EmployeesSerializer` described below.
Class description:
Employees serializer list.
Method signatures and docstrings:
- def create(self, data): Create employees.
- def to_representation(self, instance): Represent serializer data.
- def find_or_create_user(self, email): Find or create user ... | 252b0ebd77eefbcc945a0efc3068cc3421f46d5f | <|skeleton|>
class EmployeesSerializer:
"""Employees serializer list."""
def create(self, data):
"""Create employees."""
<|body_0|>
def to_representation(self, instance):
"""Represent serializer data."""
<|body_1|>
def find_or_create_user(self, email):
"""Find ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmployeesSerializer:
"""Employees serializer list."""
def create(self, data):
"""Create employees."""
employees = []
try:
with transaction.atomic():
for employee in data['employees']:
user = self.find_or_create_user(employee['email']... | the_stack_v2_python_sparse | app/companies/serializers/employees_serializer.py | vsokoltsov/Interview360Server | train | 2 |
7ae19a18b4c5fb7d095a1bca020a7ca7d3230f86 | [
"precheck_mock = self.StartPatcher(ChromiumOSPreCheckMock())\nwith remote_access.ChromiumOSDeviceHandler('1.1.1.1') as device:\n CrOS_AU = auto_updater.ChromiumOSFlashUpdater(device, self.payload_dir)\n CrOS_AU.RunUpdate()\n self.assertTrue(precheck_mock.patched['CheckRestoreStateful'].called)",
"with re... | <|body_start_0|>
precheck_mock = self.StartPatcher(ChromiumOSPreCheckMock())
with remote_access.ChromiumOSDeviceHandler('1.1.1.1') as device:
CrOS_AU = auto_updater.ChromiumOSFlashUpdater(device, self.payload_dir)
CrOS_AU.RunUpdate()
self.assertTrue(precheck_mock.patc... | Test precheck function. | ChromiumOSUpdatePreCheckTest | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChromiumOSUpdatePreCheckTest:
"""Test precheck function."""
def testCheckRestoreStateful(self):
"""Test whether CheckRestoreStateful is called in update process."""
<|body_0|>
def testCheckRestoreStatefulError(self):
"""Test CheckRestoreStateful fails with raisin... | stack_v2_sparse_classes_36k_train_006416 | 20,190 | permissive | [
{
"docstring": "Test whether CheckRestoreStateful is called in update process.",
"name": "testCheckRestoreStateful",
"signature": "def testCheckRestoreStateful(self)"
},
{
"docstring": "Test CheckRestoreStateful fails with raising ChromiumOSUpdateError.",
"name": "testCheckRestoreStatefulErr... | 3 | null | Implement the Python class `ChromiumOSUpdatePreCheckTest` described below.
Class description:
Test precheck function.
Method signatures and docstrings:
- def testCheckRestoreStateful(self): Test whether CheckRestoreStateful is called in update process.
- def testCheckRestoreStatefulError(self): Test CheckRestoreState... | Implement the Python class `ChromiumOSUpdatePreCheckTest` described below.
Class description:
Test precheck function.
Method signatures and docstrings:
- def testCheckRestoreStateful(self): Test whether CheckRestoreStateful is called in update process.
- def testCheckRestoreStatefulError(self): Test CheckRestoreState... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class ChromiumOSUpdatePreCheckTest:
"""Test precheck function."""
def testCheckRestoreStateful(self):
"""Test whether CheckRestoreStateful is called in update process."""
<|body_0|>
def testCheckRestoreStatefulError(self):
"""Test CheckRestoreStateful fails with raisin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChromiumOSUpdatePreCheckTest:
"""Test precheck function."""
def testCheckRestoreStateful(self):
"""Test whether CheckRestoreStateful is called in update process."""
precheck_mock = self.StartPatcher(ChromiumOSPreCheckMock())
with remote_access.ChromiumOSDeviceHandler('1.1.1.1') as... | the_stack_v2_python_sparse | third_party/chromite/lib/auto_updater_unittest.py | metux/chromium-suckless | train | 5 |
133a0951072c3169b75f56e52111ce1e80507009 | [
"if len(powers) != len(periods):\n raise ValueError('Power levels and periods must be equal in length')\nreturn Workout(intervals=[*zip(powers, periods)], **kwargs)",
"if start > stop:\n raise ValueError('Start power must be less than stop power')\nif stop < start:\n raise ValueError('Stop power must be ... | <|body_start_0|>
if len(powers) != len(periods):
raise ValueError('Power levels and periods must be equal in length')
return Workout(intervals=[*zip(powers, periods)], **kwargs)
<|end_body_0|>
<|body_start_1|>
if start > stop:
raise ValueError('Start power must be less t... | Workout to use with FE device | Workout | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Workout:
"""Workout to use with FE device"""
def from_arrays(powers: List[int], periods: List[float], **kwargs):
"""Create workout from arrays of powers and periods :param powers List[int]: power setpoints :param periods List[float]: period to hold each power (s) :raises ValueError: ... | stack_v2_sparse_classes_36k_train_006417 | 13,647 | permissive | [
{
"docstring": "Create workout from arrays of powers and periods :param powers List[int]: power setpoints :param periods List[float]: period to hold each power (s) :raises ValueError: powers and periods not equal length >>> Workout.from_arrays([100, 200, 300, 400], [5, 5.5, 10.2, 11.1]) Workout(intervals=[(100,... | 2 | stack_v2_sparse_classes_30k_train_014434 | Implement the Python class `Workout` described below.
Class description:
Workout to use with FE device
Method signatures and docstrings:
- def from_arrays(powers: List[int], periods: List[float], **kwargs): Create workout from arrays of powers and periods :param powers List[int]: power setpoints :param periods List[f... | Implement the Python class `Workout` described below.
Class description:
Workout to use with FE device
Method signatures and docstrings:
- def from_arrays(powers: List[int], periods: List[float], **kwargs): Create workout from arrays of powers and periods :param powers List[int]: power setpoints :param periods List[f... | afe3a1236a48476b092fb68f477c3a8118c1d5e0 | <|skeleton|>
class Workout:
"""Workout to use with FE device"""
def from_arrays(powers: List[int], periods: List[float], **kwargs):
"""Create workout from arrays of powers and periods :param powers List[int]: power setpoints :param periods List[float]: period to hold each power (s) :raises ValueError: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Workout:
"""Workout to use with FE device"""
def from_arrays(powers: List[int], periods: List[float], **kwargs):
"""Create workout from arrays of powers and periods :param powers List[int]: power setpoints :param periods List[float]: period to hold each power (s) :raises ValueError: powers and pe... | the_stack_v2_python_sparse | openant/devices/fitness_equipment.py | Tigge/openant | train | 150 |
888fe82b483a24c97ff26a521d7bd8dca6e887ab | [
"width = car.w\nratio = Classyfication.get_ratio()\nreturn width * ratio",
"height = car.h\nratio = Classyfication.get_ratio()\nreturn height * ratio",
"contours = ContourDetector.find(mask)\ncnt = SizeMeasurment.__find_biggest_contour(contours)\narea = ContourDetector.area(cnt)\nratio = Classyfication.get_rati... | <|body_start_0|>
width = car.w
ratio = Classyfication.get_ratio()
return width * ratio
<|end_body_0|>
<|body_start_1|>
height = car.h
ratio = Classyfication.get_ratio()
return height * ratio
<|end_body_1|>
<|body_start_2|>
contours = ContourDetector.find(mask)
... | SizeMeasurment | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SizeMeasurment:
def calculate_width(car: Vehicle):
"""Wylicza szerokość(długość) samochodu w metrach. :param Vehicle car: Obiekt reprezenetujący samochód. :return: Szerkość wyrażona w metrach. :rtype: float"""
<|body_0|>
def calculate_height(car: Vehicle):
"""Wylicza... | stack_v2_sparse_classes_36k_train_006418 | 14,920 | no_license | [
{
"docstring": "Wylicza szerokość(długość) samochodu w metrach. :param Vehicle car: Obiekt reprezenetujący samochód. :return: Szerkość wyrażona w metrach. :rtype: float",
"name": "calculate_width",
"signature": "def calculate_width(car: Vehicle)"
},
{
"docstring": "Wylicza wysokośc samochodu w m... | 6 | stack_v2_sparse_classes_30k_train_006069 | Implement the Python class `SizeMeasurment` described below.
Class description:
Implement the SizeMeasurment class.
Method signatures and docstrings:
- def calculate_width(car: Vehicle): Wylicza szerokość(długość) samochodu w metrach. :param Vehicle car: Obiekt reprezenetujący samochód. :return: Szerkość wyrażona w m... | Implement the Python class `SizeMeasurment` described below.
Class description:
Implement the SizeMeasurment class.
Method signatures and docstrings:
- def calculate_width(car: Vehicle): Wylicza szerokość(długość) samochodu w metrach. :param Vehicle car: Obiekt reprezenetujący samochód. :return: Szerkość wyrażona w m... | c8d6be403f12e01d3a2c0ea671363f20eeb08ce4 | <|skeleton|>
class SizeMeasurment:
def calculate_width(car: Vehicle):
"""Wylicza szerokość(długość) samochodu w metrach. :param Vehicle car: Obiekt reprezenetujący samochód. :return: Szerkość wyrażona w metrach. :rtype: float"""
<|body_0|>
def calculate_height(car: Vehicle):
"""Wylicza... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SizeMeasurment:
def calculate_width(car: Vehicle):
"""Wylicza szerokość(długość) samochodu w metrach. :param Vehicle car: Obiekt reprezenetujący samochód. :return: Szerkość wyrażona w metrach. :rtype: float"""
width = car.w
ratio = Classyfication.get_ratio()
return width * rati... | the_stack_v2_python_sparse | src/classify.py | djgrasss/videodetection | train | 0 | |
3b2bc19f855c2e67c0a136371cd606ff4db49ba1 | [
"ret = []\nlp = len(pattern)\nfor word in words:\n if len(word) != lp:\n continue\n if self.findPattern(word, pattern):\n ret.append(word)\nprint(ret)\nreturn ret",
"d = {}\nfor i in range(0, len(pattern)):\n k = pattern[i]\n if k not in d.keys():\n d[k] = word[i]\n if word... | <|body_start_0|>
ret = []
lp = len(pattern)
for word in words:
if len(word) != lp:
continue
if self.findPattern(word, pattern):
ret.append(word)
print(ret)
return ret
<|end_body_0|>
<|body_start_1|>
d = {}
f... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findAndReplacePattern(self, words: List[str], pattern: str) -> List[str]:
"""if word is one to one map return the word"""
<|body_0|>
def findPattern(self, word: str, pattern: str) -> bool:
"""judge if word is one to one map"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k_train_006419 | 974 | no_license | [
{
"docstring": "if word is one to one map return the word",
"name": "findAndReplacePattern",
"signature": "def findAndReplacePattern(self, words: List[str], pattern: str) -> List[str]"
},
{
"docstring": "judge if word is one to one map",
"name": "findPattern",
"signature": "def findPatte... | 2 | stack_v2_sparse_classes_30k_train_012663 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findAndReplacePattern(self, words: List[str], pattern: str) -> List[str]: if word is one to one map return the word
- def findPattern(self, word: str, pattern: str) -> bool: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findAndReplacePattern(self, words: List[str], pattern: str) -> List[str]: if word is one to one map return the word
- def findPattern(self, word: str, pattern: str) -> bool: ... | 48384483a55e120caf5d8d353e9aa287fce3cf4a | <|skeleton|>
class Solution:
def findAndReplacePattern(self, words: List[str], pattern: str) -> List[str]:
"""if word is one to one map return the word"""
<|body_0|>
def findPattern(self, word: str, pattern: str) -> bool:
"""judge if word is one to one map"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findAndReplacePattern(self, words: List[str], pattern: str) -> List[str]:
"""if word is one to one map return the word"""
ret = []
lp = len(pattern)
for word in words:
if len(word) != lp:
continue
if self.findPattern(word, p... | the_stack_v2_python_sparse | problems/0890_Find_And_Replace_Pattern/16_klgentle.py | yychuyu/LeetCode | train | 134 | |
94bf4620aabaaa87e2b5c36d0f113099f86a9ff1 | [
"if not citations:\n return 0\nn = len(citations)\nd = [0 for i in xrange(n + 1)]\nfor i, ai in enumerate(citations):\n if ai >= n:\n d[n] += 1\n else:\n d[ai] += 1\ns = 0\nfor i in reversed(xrange(n + 1)):\n s += d[i]\n if s >= i:\n return i\nreturn 0",
"if not citations:\n ... | <|body_start_0|>
if not citations:
return 0
n = len(citations)
d = [0 for i in xrange(n + 1)]
for i, ai in enumerate(citations):
if ai >= n:
d[n] += 1
else:
d[ai] += 1
s = 0
for i in reversed(xrange(n + 1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hIndex(self, citations):
""":type citations: List[int] :rtype: int"""
<|body_0|>
def hIndex_binary_search(self, citations):
""":type citations: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not citations:
... | stack_v2_sparse_classes_36k_train_006420 | 1,980 | no_license | [
{
"docstring": ":type citations: List[int] :rtype: int",
"name": "hIndex",
"signature": "def hIndex(self, citations)"
},
{
"docstring": ":type citations: List[int] :rtype: int",
"name": "hIndex_binary_search",
"signature": "def hIndex_binary_search(self, citations)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hIndex(self, citations): :type citations: List[int] :rtype: int
- def hIndex_binary_search(self, citations): :type citations: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hIndex(self, citations): :type citations: List[int] :rtype: int
- def hIndex_binary_search(self, citations): :type citations: List[int] :rtype: int
<|skeleton|>
class Soluti... | 0a7aa09a2b95e4caca5b5123fb735ceb5c01e992 | <|skeleton|>
class Solution:
def hIndex(self, citations):
""":type citations: List[int] :rtype: int"""
<|body_0|>
def hIndex_binary_search(self, citations):
""":type citations: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hIndex(self, citations):
""":type citations: List[int] :rtype: int"""
if not citations:
return 0
n = len(citations)
d = [0 for i in xrange(n + 1)]
for i, ai in enumerate(citations):
if ai >= n:
d[n] += 1
... | the_stack_v2_python_sparse | h-index.py | onestarshang/leetcode | train | 0 | |
fddbc04b84992f8d35d7b4b27ecd64e7a3243f4b | [
"super(AutoregressionLoss, self).__init__()\nself.cpd_channels = cpd_channels\nself.eps = np.finfo(float).eps",
"z_d = z.detach()\nz_dist = F.softmax(z_dist, dim=1)\nz_d = z_d.view(len(z_d), -1).contiguous()\nz_dist = z_dist.view(len(z_d), self.cpd_channels, -1).contiguous()\nz_dist = torch.clamp(z_dist, self.eps... | <|body_start_0|>
super(AutoregressionLoss, self).__init__()
self.cpd_channels = cpd_channels
self.eps = np.finfo(float).eps
<|end_body_0|>
<|body_start_1|>
z_d = z.detach()
z_dist = F.softmax(z_dist, dim=1)
z_d = z_d.view(len(z_d), -1).contiguous()
z_dist = z_dis... | Implements the autoregression loss. Given a representation and the estimated cpds, provides the log-likelihood of the representation under the estimated prior. | AutoregressionLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoregressionLoss:
"""Implements the autoregression loss. Given a representation and the estimated cpds, provides the log-likelihood of the representation under the estimated prior."""
def __init__(self, cpd_channels):
"""Class constructor. :param cpd_channels: number of bins in whi... | stack_v2_sparse_classes_36k_train_006421 | 2,703 | permissive | [
{
"docstring": "Class constructor. :param cpd_channels: number of bins in which the multinomial works.",
"name": "__init__",
"signature": "def __init__(self, cpd_channels)"
},
{
"docstring": "Forward propagation. :param z: the batch of latent representations. :param z_dist: the batch of estimate... | 2 | stack_v2_sparse_classes_30k_train_019354 | Implement the Python class `AutoregressionLoss` described below.
Class description:
Implements the autoregression loss. Given a representation and the estimated cpds, provides the log-likelihood of the representation under the estimated prior.
Method signatures and docstrings:
- def __init__(self, cpd_channels): Clas... | Implement the Python class `AutoregressionLoss` described below.
Class description:
Implements the autoregression loss. Given a representation and the estimated cpds, provides the log-likelihood of the representation under the estimated prior.
Method signatures and docstrings:
- def __init__(self, cpd_channels): Clas... | 99384094b5b7213e7669ad492f1b56216045b190 | <|skeleton|>
class AutoregressionLoss:
"""Implements the autoregression loss. Given a representation and the estimated cpds, provides the log-likelihood of the representation under the estimated prior."""
def __init__(self, cpd_channels):
"""Class constructor. :param cpd_channels: number of bins in whi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutoregressionLoss:
"""Implements the autoregression loss. Given a representation and the estimated cpds, provides the log-likelihood of the representation under the estimated prior."""
def __init__(self, cpd_channels):
"""Class constructor. :param cpd_channels: number of bins in which the multin... | the_stack_v2_python_sparse | models/loss_functions/autoregression_loss.py | ppalaupuigdevall/moments-vae | train | 1 |
cb5f3e7c8f7cad3572650e3dfdf9e712e6a240a6 | [
"account = self.request.user\nif account.is_authenticated:\n return rol_mag_wisselen(self.request)",
"context = super().get_context_data(**kwargs)\ncontext['url_handleiding_leden'] = settings.URL_PDF_HANDLEIDING_LEDEN\ncontext['url_handleiding_beheerders'] = settings.URL_PDF_HANDLEIDING_BEHEERDERS\ncontext['ur... | <|body_start_0|>
account = self.request.user
if account.is_authenticated:
return rol_mag_wisselen(self.request)
<|end_body_0|>
<|body_start_1|>
context = super().get_context_data(**kwargs)
context['url_handleiding_leden'] = settings.URL_PDF_HANDLEIDING_LEDEN
context[... | Django class-based view voor toegang tot de Handleidingen | HandleidingenView | [
"BSD-3-Clause-Clear"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HandleidingenView:
"""Django class-based view voor toegang tot de Handleidingen"""
def test_func(self):
"""called by the UserPassesTestMixin to verify the user has permissions to use this view"""
<|body_0|>
def get_context_data(self, **kwargs):
"""called by the t... | stack_v2_sparse_classes_36k_train_006422 | 8,698 | permissive | [
{
"docstring": "called by the UserPassesTestMixin to verify the user has permissions to use this view",
"name": "test_func",
"signature": "def test_func(self)"
},
{
"docstring": "called by the template system to get the context data for the template",
"name": "get_context_data",
"signatu... | 2 | null | Implement the Python class `HandleidingenView` described below.
Class description:
Django class-based view voor toegang tot de Handleidingen
Method signatures and docstrings:
- def test_func(self): called by the UserPassesTestMixin to verify the user has permissions to use this view
- def get_context_data(self, **kwa... | Implement the Python class `HandleidingenView` described below.
Class description:
Django class-based view voor toegang tot de Handleidingen
Method signatures and docstrings:
- def test_func(self): called by the UserPassesTestMixin to verify the user has permissions to use this view
- def get_context_data(self, **kwa... | 5ed38165a231f0caa56f67e8faf2dd074916e500 | <|skeleton|>
class HandleidingenView:
"""Django class-based view voor toegang tot de Handleidingen"""
def test_func(self):
"""called by the UserPassesTestMixin to verify the user has permissions to use this view"""
<|body_0|>
def get_context_data(self, **kwargs):
"""called by the t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HandleidingenView:
"""Django class-based view voor toegang tot de Handleidingen"""
def test_func(self):
"""called by the UserPassesTestMixin to verify the user has permissions to use this view"""
account = self.request.user
if account.is_authenticated:
return rol_mag_w... | the_stack_v2_python_sparse | Plein/views.py | RamonvdW/nhb-apps | train | 2 |
300807ca340381ed02b2f1ca77674a4080ebac22 | [
"if not head or not head.next:\n return head\nfast, slow = (head.next, head)\nwhile fast and fast.next:\n fast = fast.next.next\n slow = slow.next\nsecond = slow.next\nslow.next = None\nl = self.sortList(head)\nr = self.sortList(second)\nreturn self.merge(l, r)",
"if not l or not r:\n return l or r\ni... | <|body_start_0|>
if not head or not head.next:
return head
fast, slow = (head.next, head)
while fast and fast.next:
fast = fast.next.next
slow = slow.next
second = slow.next
slow.next = None
l = self.sortList(head)
r = self.sort... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def merge(self, l, r):
""":type l: ListNode :type r: ListNode :rtype: ListNode"""
<|body_1|>
def sortList_1(self, head):
""":type head: ListNode :rtype: Li... | stack_v2_sparse_classes_36k_train_006423 | 4,222 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "sortList",
"signature": "def sortList(self, head)"
},
{
"docstring": ":type l: ListNode :type r: ListNode :rtype: ListNode",
"name": "merge",
"signature": "def merge(self, l, r)"
},
{
"docstring": ":type head: ListN... | 5 | stack_v2_sparse_classes_30k_train_009466 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortList(self, head): :type head: ListNode :rtype: ListNode
- def merge(self, l, r): :type l: ListNode :type r: ListNode :rtype: ListNode
- def sortList_1(self, head): :type ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortList(self, head): :type head: ListNode :rtype: ListNode
- def merge(self, l, r): :type l: ListNode :type r: ListNode :rtype: ListNode
- def sortList_1(self, head): :type ... | 3d9e0ad2f6ed92ec969556f75d97c51ea4854719 | <|skeleton|>
class Solution:
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def merge(self, l, r):
""":type l: ListNode :type r: ListNode :rtype: ListNode"""
<|body_1|>
def sortList_1(self, head):
""":type head: ListNode :rtype: Li... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
if not head or not head.next:
return head
fast, slow = (head.next, head)
while fast and fast.next:
fast = fast.next.next
slow = slow.next
second = slow.ne... | the_stack_v2_python_sparse | Solutions/0148_sortList.py | YoupengLi/leetcode-sorting | train | 3 | |
62faaccf74199d4800fa9dd50b65ab42be2e855f | [
"self.num_parallel_calls = tf.convert_to_tensor(num_parallel_calls, tf.int32)\nself.coord_feed = coord_feed\nself.dim_feed = self.coord_feed.feed.map(self.correct_dims, num_parallel_calls=self.num_parallel_calls)\nself.feed = self.dim_feed",
"N = tf.shape(X)[0]\nN_slice = tf.reduce_prod(self.coord_feed.dims[1:])\... | <|body_start_0|>
self.num_parallel_calls = tf.convert_to_tensor(num_parallel_calls, tf.int32)
self.coord_feed = coord_feed
self.dim_feed = self.coord_feed.feed.map(self.correct_dims, num_parallel_calls=self.num_parallel_calls)
self.feed = self.dim_feed
<|end_body_0|>
<|body_start_1|>
... | CoordinateDimFeed | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoordinateDimFeed:
def __init__(self, coord_feed: CoordinateFeed, num_parallel_calls=10):
"""Create a coordinate dimension feed that correctly incorperates partial batches. :param coord_feed: CoordinateFeed :param num_parallel_calls: int"""
<|body_0|>
def correct_dims(self, ... | stack_v2_sparse_classes_36k_train_006424 | 18,860 | permissive | [
{
"docstring": "Create a coordinate dimension feed that correctly incorperates partial batches. :param coord_feed: CoordinateFeed :param num_parallel_calls: int",
"name": "__init__",
"signature": "def __init__(self, coord_feed: CoordinateFeed, num_parallel_calls=10)"
},
{
"docstring": "Correct f... | 2 | stack_v2_sparse_classes_30k_train_018464 | Implement the Python class `CoordinateDimFeed` described below.
Class description:
Implement the CoordinateDimFeed class.
Method signatures and docstrings:
- def __init__(self, coord_feed: CoordinateFeed, num_parallel_calls=10): Create a coordinate dimension feed that correctly incorperates partial batches. :param co... | Implement the Python class `CoordinateDimFeed` described below.
Class description:
Implement the CoordinateDimFeed class.
Method signatures and docstrings:
- def __init__(self, coord_feed: CoordinateFeed, num_parallel_calls=10): Create a coordinate dimension feed that correctly incorperates partial batches. :param co... | 2997d60d8cf07f875e42c0b5f07944e9ab7e9d33 | <|skeleton|>
class CoordinateDimFeed:
def __init__(self, coord_feed: CoordinateFeed, num_parallel_calls=10):
"""Create a coordinate dimension feed that correctly incorperates partial batches. :param coord_feed: CoordinateFeed :param num_parallel_calls: int"""
<|body_0|>
def correct_dims(self, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoordinateDimFeed:
def __init__(self, coord_feed: CoordinateFeed, num_parallel_calls=10):
"""Create a coordinate dimension feed that correctly incorperates partial batches. :param coord_feed: CoordinateFeed :param num_parallel_calls: int"""
self.num_parallel_calls = tf.convert_to_tensor(num_pa... | the_stack_v2_python_sparse | bayes_filter/feeds.py | Joshuaalbert/bayes_filter | train | 0 | |
5d6142f85da94de9f03aa096e3e2037932f1f3ea | [
"timestamp = plist_key.get(plist_value_name, None)\nif timestamp is None:\n return None\nreturn dfdatetime_cocoa_time.CocoaTime(timestamp=timestamp)",
"for _, process_name, process_values in self._RecurseKey(top_level, depth=1):\n if process_name == 'CacheVersion':\n continue\n for apple_identifie... | <|body_start_0|>
timestamp = plist_key.get(plist_value_name, None)
if timestamp is None:
return None
return dfdatetime_cocoa_time.CocoaTime(timestamp=timestamp)
<|end_body_0|>
<|body_start_1|>
for _, process_name, process_values in self._RecurseKey(top_level, depth=1):
... | Plist parser plugin for identity services status cache files. Identity services status cache plist files are typically named: com.apple.identityservices.idstatuscache.plist | IOSIdstatusachePlistPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IOSIdstatusachePlistPlugin:
"""Plist parser plugin for identity services status cache files. Identity services status cache plist files are typically named: com.apple.identityservices.idstatuscache.plist"""
def _GetDateTimeValueFromPlistKey(self, plist_key, plist_value_name):
"""Retr... | stack_v2_sparse_classes_36k_train_006425 | 2,979 | permissive | [
{
"docstring": "Retrieves a date and time value from a specific value in a plist key. Args: plist_key (object): plist key. plist_value_name (str): name of the value in the plist key. Returns: dfdatetime.TimeElementsInMicroseconds: date and time or None if not available.",
"name": "_GetDateTimeValueFromPlist... | 2 | stack_v2_sparse_classes_30k_train_011403 | Implement the Python class `IOSIdstatusachePlistPlugin` described below.
Class description:
Plist parser plugin for identity services status cache files. Identity services status cache plist files are typically named: com.apple.identityservices.idstatuscache.plist
Method signatures and docstrings:
- def _GetDateTimeV... | Implement the Python class `IOSIdstatusachePlistPlugin` described below.
Class description:
Plist parser plugin for identity services status cache files. Identity services status cache plist files are typically named: com.apple.identityservices.idstatuscache.plist
Method signatures and docstrings:
- def _GetDateTimeV... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class IOSIdstatusachePlistPlugin:
"""Plist parser plugin for identity services status cache files. Identity services status cache plist files are typically named: com.apple.identityservices.idstatuscache.plist"""
def _GetDateTimeValueFromPlistKey(self, plist_key, plist_value_name):
"""Retr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IOSIdstatusachePlistPlugin:
"""Plist parser plugin for identity services status cache files. Identity services status cache plist files are typically named: com.apple.identityservices.idstatuscache.plist"""
def _GetDateTimeValueFromPlistKey(self, plist_key, plist_value_name):
"""Retrieves a date ... | the_stack_v2_python_sparse | plaso/parsers/plist_plugins/ios_identityservices.py | log2timeline/plaso | train | 1,506 |
6f394b769cc36094c919f015912e5169d87266b1 | [
"if not intervals:\n return intervals\nresults = []\nintervals = sorted(intervals, cmp=self.interval_comp)\nresults.append(intervals[0])\nfor i in xrange(1, len(intervals)):\n if results[-1].end >= intervals[i].start:\n results[-1].end = max(results[-1].end, intervals[i].end)\n else:\n result... | <|body_start_0|>
if not intervals:
return intervals
results = []
intervals = sorted(intervals, cmp=self.interval_comp)
results.append(intervals[0])
for i in xrange(1, len(intervals)):
if results[-1].end >= intervals[i].start:
results[-1].en... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def merge(self, intervals):
""":type intervals: List[Interval] :rtype: List[Interval] Given a collection of intervals, merge all overlapping intervals. For example, Given [1,3],[2,6],[8,10],[15,18], return [1,6],[8,10],[15,18]."""
<|body_0|>
def interval_comp(self,... | stack_v2_sparse_classes_36k_train_006426 | 1,147 | no_license | [
{
"docstring": ":type intervals: List[Interval] :rtype: List[Interval] Given a collection of intervals, merge all overlapping intervals. For example, Given [1,3],[2,6],[8,10],[15,18], return [1,6],[8,10],[15,18].",
"name": "merge",
"signature": "def merge(self, intervals)"
},
{
"docstring": "对节点... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, intervals): :type intervals: List[Interval] :rtype: List[Interval] Given a collection of intervals, merge all overlapping intervals. For example, Given [1,3],[2,6... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, intervals): :type intervals: List[Interval] :rtype: List[Interval] Given a collection of intervals, merge all overlapping intervals. For example, Given [1,3],[2,6... | 350f28cad5ec384df476f6403cb7a7db419de329 | <|skeleton|>
class Solution:
def merge(self, intervals):
""":type intervals: List[Interval] :rtype: List[Interval] Given a collection of intervals, merge all overlapping intervals. For example, Given [1,3],[2,6],[8,10],[15,18], return [1,6],[8,10],[15,18]."""
<|body_0|>
def interval_comp(self,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def merge(self, intervals):
""":type intervals: List[Interval] :rtype: List[Interval] Given a collection of intervals, merge all overlapping intervals. For example, Given [1,3],[2,6],[8,10],[15,18], return [1,6],[8,10],[15,18]."""
if not intervals:
return intervals
... | the_stack_v2_python_sparse | leetcode/mergeintervals.py | wanglinjie/coding | train | 0 | |
0e126b37e59623155c6c2fb8d4bbf9035a7d4d9e | [
"max_index = 0\nfor idx, n in enumerate(nums):\n if idx > max_index:\n return False\n max_index = max(max_index, idx + nums[idx])\nreturn True",
"start, destination = (0, len(nums) - 1)\nfrontier_backtrack_index = destination\nfor idx in range(len(nums) - 2, -1, -1):\n if idx + nums[idx] >= fronti... | <|body_start_0|>
max_index = 0
for idx, n in enumerate(nums):
if idx > max_index:
return False
max_index = max(max_index, idx + nums[idx])
return True
<|end_body_0|>
<|body_start_1|>
start, destination = (0, len(nums) - 1)
frontier_backtra... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canJump(self, nums: list[int]) -> bool:
"""Greedy :param nums: :return:"""
<|body_0|>
def canJump(self, nums: list[int]) -> bool:
"""Back tracking :param nums: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
max_index = 0
... | stack_v2_sparse_classes_36k_train_006427 | 894 | no_license | [
{
"docstring": "Greedy :param nums: :return:",
"name": "canJump",
"signature": "def canJump(self, nums: list[int]) -> bool"
},
{
"docstring": "Back tracking :param nums: :return:",
"name": "canJump",
"signature": "def canJump(self, nums: list[int]) -> bool"
}
] | 2 | stack_v2_sparse_classes_30k_train_007392 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canJump(self, nums: list[int]) -> bool: Greedy :param nums: :return:
- def canJump(self, nums: list[int]) -> bool: Back tracking :param nums: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canJump(self, nums: list[int]) -> bool: Greedy :param nums: :return:
- def canJump(self, nums: list[int]) -> bool: Back tracking :param nums: :return:
<|skeleton|>
class Sol... | e50dc0642f087f37ab3234390be3d8a0ed48fe62 | <|skeleton|>
class Solution:
def canJump(self, nums: list[int]) -> bool:
"""Greedy :param nums: :return:"""
<|body_0|>
def canJump(self, nums: list[int]) -> bool:
"""Back tracking :param nums: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canJump(self, nums: list[int]) -> bool:
"""Greedy :param nums: :return:"""
max_index = 0
for idx, n in enumerate(nums):
if idx > max_index:
return False
max_index = max(max_index, idx + nums[idx])
return True
def canJum... | the_stack_v2_python_sparse | Leetcode/55. Jump Game.py | brlala/Educative-Grokking-Coding-Exercise | train | 3 | |
18ba4a81a55611cce2ccac6aa0aaa6174a1e4ac5 | [
"self.log_dir = log_dir\nself.arrow_writers = {}\nself.columnLength = columnLength\nself.chunkRows = 96\nself.step = 0\nself.dfs = {}",
"logger.info('Writing to arrow file')\nfor obj_type in powerflow_output:\n df = pd.DataFrame(data=powerflow_output[obj_type], index=[0])\n df['TimeStep'] = float(currenttim... | <|body_start_0|>
self.log_dir = log_dir
self.arrow_writers = {}
self.columnLength = columnLength
self.chunkRows = 96
self.step = 0
self.dfs = {}
<|end_body_0|>
<|body_start_1|>
logger.info('Writing to arrow file')
for obj_type in powerflow_output:
... | Class that handles writing simulation results to arrow files. | ArrowWriter | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArrowWriter:
"""Class that handles writing simulation results to arrow files."""
def __init__(self, log_dir, columnLength=10):
"""Constructor"""
<|body_0|>
def write(self, fed_name, currenttime, powerflow_output, index):
"""Writes the status of BES assets at a pa... | stack_v2_sparse_classes_36k_train_006428 | 2,616 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, log_dir, columnLength=10)"
},
{
"docstring": "Writes the status of BES assets at a particular timestep to an arrow file. :param fed_name: name of BES federate :param log_fields: list of objects to log :param curre... | 2 | null | Implement the Python class `ArrowWriter` described below.
Class description:
Class that handles writing simulation results to arrow files.
Method signatures and docstrings:
- def __init__(self, log_dir, columnLength=10): Constructor
- def write(self, fed_name, currenttime, powerflow_output, index): Writes the status ... | Implement the Python class `ArrowWriter` described below.
Class description:
Class that handles writing simulation results to arrow files.
Method signatures and docstrings:
- def __init__(self, log_dir, columnLength=10): Constructor
- def write(self, fed_name, currenttime, powerflow_output, index): Writes the status ... | def06b01195a152292a7182b9002d3a950f1fa40 | <|skeleton|>
class ArrowWriter:
"""Class that handles writing simulation results to arrow files."""
def __init__(self, log_dir, columnLength=10):
"""Constructor"""
<|body_0|>
def write(self, fed_name, currenttime, powerflow_output, index):
"""Writes the status of BES assets at a pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArrowWriter:
"""Class that handles writing simulation results to arrow files."""
def __init__(self, log_dir, columnLength=10):
"""Constructor"""
self.log_dir = log_dir
self.arrow_writers = {}
self.columnLength = columnLength
self.chunkRows = 96
self.step = ... | the_stack_v2_python_sparse | PyDSS/api/src/app/arrow_writer.py | TimberJ99/PyDSS | train | 0 |
40b37e7e96924811468d9e0e368beb798c02949a | [
"self.parser = argparse.ArgumentParser(prog='switchmap-ng-cli', description=additional_help, formatter_class=argparse.RawTextHelpFormatter)\nsubparsers = self.parser.add_subparsers(dest='action')\n_Show(subparsers)\n_Start(subparsers)\n_Stop(subparsers)\n_Restart(subparsers)\n_Test(subparsers)\nself.args = self.par... | <|body_start_0|>
self.parser = argparse.ArgumentParser(prog='switchmap-ng-cli', description=additional_help, formatter_class=argparse.RawTextHelpFormatter)
subparsers = self.parser.add_subparsers(dest='action')
_Show(subparsers)
_Start(subparsers)
_Stop(subparsers)
_Resta... | Class that manages the CLI. | CLI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CLI:
"""Class that manages the CLI."""
def __init__(self, additional_help=''):
"""Method initializing the class. Args: additional_help: String for additional help information Returns: None"""
<|body_0|>
def process(self):
"""Act on CLI arguments. Args: None Retur... | stack_v2_sparse_classes_36k_train_006429 | 14,010 | permissive | [
{
"docstring": "Method initializing the class. Args: additional_help: String for additional help information Returns: None",
"name": "__init__",
"signature": "def __init__(self, additional_help='')"
},
{
"docstring": "Act on CLI arguments. Args: None Returns: None",
"name": "process",
"s... | 2 | null | Implement the Python class `CLI` described below.
Class description:
Class that manages the CLI.
Method signatures and docstrings:
- def __init__(self, additional_help=''): Method initializing the class. Args: additional_help: String for additional help information Returns: None
- def process(self): Act on CLI argume... | Implement the Python class `CLI` described below.
Class description:
Class that manages the CLI.
Method signatures and docstrings:
- def __init__(self, additional_help=''): Method initializing the class. Args: additional_help: String for additional help information Returns: None
- def process(self): Act on CLI argume... | ae82589fbbab77fef6d6be09c1fcca5846f595a8 | <|skeleton|>
class CLI:
"""Class that manages the CLI."""
def __init__(self, additional_help=''):
"""Method initializing the class. Args: additional_help: String for additional help information Returns: None"""
<|body_0|>
def process(self):
"""Act on CLI arguments. Args: None Retur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CLI:
"""Class that manages the CLI."""
def __init__(self, additional_help=''):
"""Method initializing the class. Args: additional_help: String for additional help information Returns: None"""
self.parser = argparse.ArgumentParser(prog='switchmap-ng-cli', description=additional_help, forma... | the_stack_v2_python_sparse | switchmap/cli/cli.py | PalisadoesFoundation/switchmap-ng | train | 8 |
2c534120308e0ac4045dcb707dbdf02a11a399f1 | [
"self.getFollow = dict()\nself.Tweets = []\nself.tweetNums = 0",
"self.Tweets.append((userId, tweetId))\nself.tweetNums += 1\nif userId not in self.getFollow:\n self.getFollow[userId] = []",
"if userId not in self.getFollow.keys():\n return\nret = []\nnums = 0\nfor i in range(self.tweetNums - 1, -1, -1):\... | <|body_start_0|>
self.getFollow = dict()
self.Tweets = []
self.tweetNums = 0
<|end_body_0|>
<|body_start_1|>
self.Tweets.append((userId, tweetId))
self.tweetNums += 1
if userId not in self.getFollow:
self.getFollow[userId] = []
<|end_body_1|>
<|body_start_2|... | Twitter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
<|body_1|>
def getNewsFeed(self, userId: int):
"""Retrieve the 10 most recent tw... | stack_v2_sparse_classes_36k_train_006430 | 3,220 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compose a new tweet.",
"name": "postTweet",
"signature": "def postTweet(self, userId: int, tweetId: int) -> None"
},
{
"docstring": "Retrieve the 10 mos... | 5 | null | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId: int, tweetId: int) -> None: Compose a new tweet.
- def getNewsFeed(self, userId: int): Retrie... | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId: int, tweetId: int) -> None: Compose a new tweet.
- def getNewsFeed(self, userId: int): Retrie... | 0cc970aaa03aa9300319a1e39e052e4beeec6698 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
<|body_1|>
def getNewsFeed(self, userId: int):
"""Retrieve the 10 most recent tw... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Twitter:
def __init__(self):
"""Initialize your data structure here."""
self.getFollow = dict()
self.Tweets = []
self.tweetNums = 0
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
self.Tweets.append((userId, tweetId))
... | the_stack_v2_python_sparse | leetcode.355. 设计推特.py | NonCover/- | train | 2 | |
c20a67d98c0905f5a4fe73147e23be123f30b367 | [
"if audit_info:\n audit = Audit()\n audit.audit_type = audit_info['audit_type']\n audit.audit_type_id = audit_info.get('audit_type_id')\n audit.sub_type = audit_info.get('sub_type')\n audit.sub_type_id = audit_info.get('sub_type_id')\n audit.field = audit_info['field']\n audit.old_value = audit... | <|body_start_0|>
if audit_info:
audit = Audit()
audit.audit_type = audit_info['audit_type']
audit.audit_type_id = audit_info.get('audit_type_id')
audit.sub_type = audit_info.get('sub_type')
audit.sub_type_id = audit_info.get('sub_type_id')
... | This class manages audit. | Audit | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Audit:
"""This class manages audit."""
def create_from_dict(cls, audit_info: dict):
"""Create audit from the dict."""
<|body_0|>
def create_from_list(cls, audit_list: list):
"""Create audit from the list."""
<|body_1|>
def find_project_status(cls, pr... | stack_v2_sparse_classes_36k_train_006431 | 3,503 | permissive | [
{
"docstring": "Create audit from the dict.",
"name": "create_from_dict",
"signature": "def create_from_dict(cls, audit_info: dict)"
},
{
"docstring": "Create audit from the list.",
"name": "create_from_list",
"signature": "def create_from_list(cls, audit_list: list)"
},
{
"docst... | 3 | null | Implement the Python class `Audit` described below.
Class description:
This class manages audit.
Method signatures and docstrings:
- def create_from_dict(cls, audit_info: dict): Create audit from the dict.
- def create_from_list(cls, audit_list: list): Create audit from the list.
- def find_project_status(cls, projec... | Implement the Python class `Audit` described below.
Class description:
This class manages audit.
Method signatures and docstrings:
- def create_from_dict(cls, audit_info: dict): Create audit from the dict.
- def create_from_list(cls, audit_list: list): Create audit from the list.
- def find_project_status(cls, projec... | 3bfe09c100a0f5b98d61228324336d5f45ad93ad | <|skeleton|>
class Audit:
"""This class manages audit."""
def create_from_dict(cls, audit_info: dict):
"""Create audit from the dict."""
<|body_0|>
def create_from_list(cls, audit_list: list):
"""Create audit from the list."""
<|body_1|>
def find_project_status(cls, pr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Audit:
"""This class manages audit."""
def create_from_dict(cls, audit_info: dict):
"""Create audit from the dict."""
if audit_info:
audit = Audit()
audit.audit_type = audit_info['audit_type']
audit.audit_type_id = audit_info.get('audit_type_id')
... | the_stack_v2_python_sparse | selfservice-api/src/selfservice_api/models/audit.py | bcgov/BCSC-SS | train | 2 |
a93a704b800997be083f1830aa44fbcf179a9322 | [
"self.mutually_exclusive = set(kwargs.pop('mutually_exclusive', []))\nhelp_ = kwargs.get('help', '')\nif self.mutually_exclusive:\n ex_str = ', '.join(self.mutually_exclusive)\n kwargs['help'] = help_ + (' NOTE: This argument is mutually exclusive with arguments: [' + ex_str + '].')\nsuper().__init__(*args, ... | <|body_start_0|>
self.mutually_exclusive = set(kwargs.pop('mutually_exclusive', []))
help_ = kwargs.get('help', '')
if self.mutually_exclusive:
ex_str = ', '.join(self.mutually_exclusive)
kwargs['help'] = help_ + (' NOTE: This argument is mutually exclusive with argument... | Represent a mutually exclusive option. | MutuallyExclusiveOption | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MutuallyExclusiveOption:
"""Represent a mutually exclusive option."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
"""Initialize the option."""
<|body_0|>
def handle_parse_result(self, ctx: Context, opts: Mapping[str, Any], args: List[Any]) -> Tuple[Any, List[s... | stack_v2_sparse_classes_36k_train_006432 | 8,209 | permissive | [
{
"docstring": "Initialize the option.",
"name": "__init__",
"signature": "def __init__(self, *args: Any, **kwargs: Any) -> None"
},
{
"docstring": "Handle parse result. :param ctx: the click context. :param opts: the options. :param args: the list of arguments (to be forwarded to the parent cla... | 2 | null | Implement the Python class `MutuallyExclusiveOption` described below.
Class description:
Represent a mutually exclusive option.
Method signatures and docstrings:
- def __init__(self, *args: Any, **kwargs: Any) -> None: Initialize the option.
- def handle_parse_result(self, ctx: Context, opts: Mapping[str, Any], args:... | Implement the Python class `MutuallyExclusiveOption` described below.
Class description:
Represent a mutually exclusive option.
Method signatures and docstrings:
- def __init__(self, *args: Any, **kwargs: Any) -> None: Initialize the option.
- def handle_parse_result(self, ctx: Context, opts: Mapping[str, Any], args:... | bec49adaeba661d8d0f03ac9935dc89f39d95a0d | <|skeleton|>
class MutuallyExclusiveOption:
"""Represent a mutually exclusive option."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
"""Initialize the option."""
<|body_0|>
def handle_parse_result(self, ctx: Context, opts: Mapping[str, Any], args: List[Any]) -> Tuple[Any, List[s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MutuallyExclusiveOption:
"""Represent a mutually exclusive option."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
"""Initialize the option."""
self.mutually_exclusive = set(kwargs.pop('mutually_exclusive', []))
help_ = kwargs.get('help', '')
if self.mutually_exc... | the_stack_v2_python_sparse | aea/cli/utils/click_utils.py | fetchai/agents-aea | train | 192 |
a26e541444bf78217fdf77a2ae20bf3ec645591d | [
"self.environment = mls.rl.common.Environment()\nself.environment.game = mls.rl.common.Game(max_step=max_step)\nself.environment.current_state = self.environment.game.init_state(self.environment)",
"observation = self.environment.get_observation_for_agent()\nfor ag in self.environment.agents:\n ag.observation ... | <|body_start_0|>
self.environment = mls.rl.common.Environment()
self.environment.game = mls.rl.common.Game(max_step=max_step)
self.environment.current_state = self.environment.game.init_state(self.environment)
<|end_body_0|>
<|body_start_1|>
observation = self.environment.get_observatio... | Engine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Engine:
def __init__(self, max_step=-1):
"""initialization of the engine :param max_step maximum step of the environment. temporary. will be change when adding Game"""
<|body_0|>
def execute(self):
"""Main loop of the application."""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_006433 | 1,269 | permissive | [
{
"docstring": "initialization of the engine :param max_step maximum step of the environment. temporary. will be change when adding Game",
"name": "__init__",
"signature": "def __init__(self, max_step=-1)"
},
{
"docstring": "Main loop of the application.",
"name": "execute",
"signature":... | 2 | stack_v2_sparse_classes_30k_test_000760 | Implement the Python class `Engine` described below.
Class description:
Implement the Engine class.
Method signatures and docstrings:
- def __init__(self, max_step=-1): initialization of the engine :param max_step maximum step of the environment. temporary. will be change when adding Game
- def execute(self): Main lo... | Implement the Python class `Engine` described below.
Class description:
Implement the Engine class.
Method signatures and docstrings:
- def __init__(self, max_step=-1): initialization of the engine :param max_step maximum step of the environment. temporary. will be change when adding Game
- def execute(self): Main lo... | 373598d067c7f0930ba13fe8da9756ce26eecbaf | <|skeleton|>
class Engine:
def __init__(self, max_step=-1):
"""initialization of the engine :param max_step maximum step of the environment. temporary. will be change when adding Game"""
<|body_0|>
def execute(self):
"""Main loop of the application."""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Engine:
def __init__(self, max_step=-1):
"""initialization of the engine :param max_step maximum step of the environment. temporary. will be change when adding Game"""
self.environment = mls.rl.common.Environment()
self.environment.game = mls.rl.common.Game(max_step=max_step)
s... | the_stack_v2_python_sparse | mlsurvey/rl/engine/engine.py | jlaumonier/mlsurvey | train | 0 | |
8c92b85d7fd65836ccfebdc63523d73953e6148f | [
"if not root:\n return []\nres = []\n\ndef digui(root):\n if root:\n for i in root.children:\n digui(i)\n res.append(root.val)\ndigui(root)\nreturn res",
"if not root:\n return []\nres = []\nstack = [root]\nwhile stack:\n node = stack.pop()\n for i in node.children:\n ... | <|body_start_0|>
if not root:
return []
res = []
def digui(root):
if root:
for i in root.children:
digui(i)
res.append(root.val)
digui(root)
return res
<|end_body_0|>
<|body_start_1|>
if not roo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def postorder(self, root: 'Node') -> List[int]:
"""递归"""
<|body_0|>
def postorder1(self, root: 'Node') -> List[int]:
"""迭代"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return []
res = []
def dig... | stack_v2_sparse_classes_36k_train_006434 | 1,058 | no_license | [
{
"docstring": "递归",
"name": "postorder",
"signature": "def postorder(self, root: 'Node') -> List[int]"
},
{
"docstring": "迭代",
"name": "postorder1",
"signature": "def postorder1(self, root: 'Node') -> List[int]"
}
] | 2 | stack_v2_sparse_classes_30k_train_001599 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def postorder(self, root: 'Node') -> List[int]: 递归
- def postorder1(self, root: 'Node') -> List[int]: 迭代 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def postorder(self, root: 'Node') -> List[int]: 递归
- def postorder1(self, root: 'Node') -> List[int]: 迭代
<|skeleton|>
class Solution:
def postorder(self, root: 'Node') -> L... | 069bb0b751ef7f469036b9897436eb5d138ffa24 | <|skeleton|>
class Solution:
def postorder(self, root: 'Node') -> List[int]:
"""递归"""
<|body_0|>
def postorder1(self, root: 'Node') -> List[int]:
"""迭代"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def postorder(self, root: 'Node') -> List[int]:
"""递归"""
if not root:
return []
res = []
def digui(root):
if root:
for i in root.children:
digui(i)
res.append(root.val)
digui(root)
... | the_stack_v2_python_sparse | 算法/Week_02/590. N叉树的后序遍历.py | RichieSong/algorithm | train | 0 | |
099331659c5d011698fa1b456115bf323e2e4885 | [
"book = self.open_excel_book()\nids = self.create_checks(self.sheet_to_array(book.sheet_by_index(0)), book.datemode)\nreturn {'name': 'Cheques importados', 'res_model': 'account.third.check', 'type': 'ir.actions.act_window', 'domain': [('id', 'in', ids)], 'views': [[False, 'tree'], [False, 'form']]}",
"import xlr... | <|body_start_0|>
book = self.open_excel_book()
ids = self.create_checks(self.sheet_to_array(book.sheet_by_index(0)), book.datemode)
return {'name': 'Cheques importados', 'res_model': 'account.third.check', 'type': 'ir.actions.act_window', 'domain': [('id', 'in', ids)], 'views': [[False, 'tree'],... | ThirdCheckImportWizard | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThirdCheckImportWizard:
def import_file(self):
"""Importo el archivo cargado en el formulario (uso api.multi para devolver una vista despues) :return: una tree (con form) que muestra los cheques creados"""
<|body_0|>
def create_checks(self, array, datemode):
"""Crea ... | stack_v2_sparse_classes_36k_train_006435 | 6,176 | no_license | [
{
"docstring": "Importo el archivo cargado en el formulario (uso api.multi para devolver una vista despues) :return: una tree (con form) que muestra los cheques creados",
"name": "import_file",
"signature": "def import_file(self)"
},
{
"docstring": "Crea cheques a partir de un array con datos :p... | 4 | null | Implement the Python class `ThirdCheckImportWizard` described below.
Class description:
Implement the ThirdCheckImportWizard class.
Method signatures and docstrings:
- def import_file(self): Importo el archivo cargado en el formulario (uso api.multi para devolver una vista despues) :return: una tree (con form) que mu... | Implement the Python class `ThirdCheckImportWizard` described below.
Class description:
Implement the ThirdCheckImportWizard class.
Method signatures and docstrings:
- def import_file(self): Importo el archivo cargado en el formulario (uso api.multi para devolver una vista despues) :return: una tree (con form) que mu... | 77921b4d965f2e4c081d523b373eb306a450a873 | <|skeleton|>
class ThirdCheckImportWizard:
def import_file(self):
"""Importo el archivo cargado en el formulario (uso api.multi para devolver una vista despues) :return: una tree (con form) que muestra los cheques creados"""
<|body_0|>
def create_checks(self, array, datemode):
"""Crea ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThirdCheckImportWizard:
def import_file(self):
"""Importo el archivo cargado en el formulario (uso api.multi para devolver una vista despues) :return: una tree (con form) que muestra los cheques creados"""
book = self.open_excel_book()
ids = self.create_checks(self.sheet_to_array(book.... | the_stack_v2_python_sparse | odoo_addons_others/opyme_third_check_import/wizard/models/third_check_import_wizard.py | test-odoorosario/opt | train | 0 | |
db2f26f22b9fe06fd311fec406ab416a4453f74a | [
"Inventory.__init__(self, product_code, description, market_price, rental_price)\nself.brand = brand\nself.voltage = voltage",
"output_dict = Inventory.return_as_dictionary(self)\noutput_dict['brand'] = self.brand\noutput_dict['voltage'] = self.voltage\nreturn output_dict"
] | <|body_start_0|>
Inventory.__init__(self, product_code, description, market_price, rental_price)
self.brand = brand
self.voltage = voltage
<|end_body_0|>
<|body_start_1|>
output_dict = Inventory.return_as_dictionary(self)
output_dict['brand'] = self.brand
output_dict['vo... | Class for electric appliances | ElectricAppliances | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElectricAppliances:
"""Class for electric appliances"""
def __init__(self, product_code, description, market_price, rental_price, brand, voltage):
"""Initializes electric appliances class"""
<|body_0|>
def return_as_dictionary(self):
"""Returns a dictionary with ... | stack_v2_sparse_classes_36k_train_006436 | 922 | no_license | [
{
"docstring": "Initializes electric appliances class",
"name": "__init__",
"signature": "def __init__(self, product_code, description, market_price, rental_price, brand, voltage)"
},
{
"docstring": "Returns a dictionary with attributes",
"name": "return_as_dictionary",
"signature": "def... | 2 | null | Implement the Python class `ElectricAppliances` described below.
Class description:
Class for electric appliances
Method signatures and docstrings:
- def __init__(self, product_code, description, market_price, rental_price, brand, voltage): Initializes electric appliances class
- def return_as_dictionary(self): Retur... | Implement the Python class `ElectricAppliances` described below.
Class description:
Class for electric appliances
Method signatures and docstrings:
- def __init__(self, product_code, description, market_price, rental_price, brand, voltage): Initializes electric appliances class
- def return_as_dictionary(self): Retur... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class ElectricAppliances:
"""Class for electric appliances"""
def __init__(self, product_code, description, market_price, rental_price, brand, voltage):
"""Initializes electric appliances class"""
<|body_0|>
def return_as_dictionary(self):
"""Returns a dictionary with ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ElectricAppliances:
"""Class for electric appliances"""
def __init__(self, product_code, description, market_price, rental_price, brand, voltage):
"""Initializes electric appliances class"""
Inventory.__init__(self, product_code, description, market_price, rental_price)
self.brand... | the_stack_v2_python_sparse | students/ramkumar_rajanbabu/lesson_01/assignment/inventory_management/electric_appliances_class.py | JavaRod/SP_Python220B_2019 | train | 1 |
30e806612b3a115e336479378bf6298293080c11 | [
"Document = current_app_ils.document_record_cls\ntry:\n Document.get_record_by_pid(document_pid)\nexcept PIDDoesNotExistError:\n raise DocumentNotFoundError(document_pid)",
"super().validate(record, **kwargs)\ndocument_pid = record['document_pid']\nself.ensure_document_exists(document_pid)"
] | <|body_start_0|>
Document = current_app_ils.document_record_cls
try:
Document.get_record_by_pid(document_pid)
except PIDDoesNotExistError:
raise DocumentNotFoundError(document_pid)
<|end_body_0|>
<|body_start_1|>
super().validate(record, **kwargs)
documen... | EItem record validator. | EItemValidator | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EItemValidator:
"""EItem record validator."""
def ensure_document_exists(self, document_pid):
"""Ensure document exists or raise."""
<|body_0|>
def validate(self, record, **kwargs):
"""Validate record before create and commit."""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_006437 | 3,816 | permissive | [
{
"docstring": "Ensure document exists or raise.",
"name": "ensure_document_exists",
"signature": "def ensure_document_exists(self, document_pid)"
},
{
"docstring": "Validate record before create and commit.",
"name": "validate",
"signature": "def validate(self, record, **kwargs)"
}
] | 2 | null | Implement the Python class `EItemValidator` described below.
Class description:
EItem record validator.
Method signatures and docstrings:
- def ensure_document_exists(self, document_pid): Ensure document exists or raise.
- def validate(self, record, **kwargs): Validate record before create and commit. | Implement the Python class `EItemValidator` described below.
Class description:
EItem record validator.
Method signatures and docstrings:
- def ensure_document_exists(self, document_pid): Ensure document exists or raise.
- def validate(self, record, **kwargs): Validate record before create and commit.
<|skeleton|>
c... | 1c36526e85510100c5f64059518d1b716d87ac10 | <|skeleton|>
class EItemValidator:
"""EItem record validator."""
def ensure_document_exists(self, document_pid):
"""Ensure document exists or raise."""
<|body_0|>
def validate(self, record, **kwargs):
"""Validate record before create and commit."""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EItemValidator:
"""EItem record validator."""
def ensure_document_exists(self, document_pid):
"""Ensure document exists or raise."""
Document = current_app_ils.document_record_cls
try:
Document.get_record_by_pid(document_pid)
except PIDDoesNotExistError:
... | the_stack_v2_python_sparse | invenio_app_ils/eitems/api.py | inveniosoftware/invenio-app-ils | train | 64 |
f41d9aa5ce5dcd04cc01b1109a73dcee668ac3df | [
"super(BahandauAttention, self).__init__()\nself.W1 = tf.keras.layers.Dense(units=units)\nself.W2 = tf.keras.layers.Dense(units=units)\nself.V = tf.keras.layers.Dense(units=1)",
"hidden_state_with_time_axis = tf.expand_dims(hidden_state, 1)\nscore = self.V(tf.nn.tanh(self.W1(hidden_state_with_time_axis) + self.W2... | <|body_start_0|>
super(BahandauAttention, self).__init__()
self.W1 = tf.keras.layers.Dense(units=units)
self.W2 = tf.keras.layers.Dense(units=units)
self.V = tf.keras.layers.Dense(units=1)
<|end_body_0|>
<|body_start_1|>
hidden_state_with_time_axis = tf.expand_dims(hidden_state,... | The attention layer with bahandau score. | BahandauAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BahandauAttention:
"""The attention layer with bahandau score."""
def __init__(self, units):
"""The structure function. Args: units: The units number of attention hidden layer."""
<|body_0|>
def call(self, inputs, hidden_state):
"""The Args: inputs: The inputs. h... | stack_v2_sparse_classes_36k_train_006438 | 20,417 | no_license | [
{
"docstring": "The structure function. Args: units: The units number of attention hidden layer.",
"name": "__init__",
"signature": "def __init__(self, units)"
},
{
"docstring": "The Args: inputs: The inputs. hidden_state: The rnn hidden layer state. Returns: The context vectors and attention we... | 2 | stack_v2_sparse_classes_30k_train_003311 | Implement the Python class `BahandauAttention` described below.
Class description:
The attention layer with bahandau score.
Method signatures and docstrings:
- def __init__(self, units): The structure function. Args: units: The units number of attention hidden layer.
- def call(self, inputs, hidden_state): The Args: ... | Implement the Python class `BahandauAttention` described below.
Class description:
The attention layer with bahandau score.
Method signatures and docstrings:
- def __init__(self, units): The structure function. Args: units: The units number of attention hidden layer.
- def call(self, inputs, hidden_state): The Args: ... | d1b70b2a954f4665b628ba252b03c1a74b95559f | <|skeleton|>
class BahandauAttention:
"""The attention layer with bahandau score."""
def __init__(self, units):
"""The structure function. Args: units: The units number of attention hidden layer."""
<|body_0|>
def call(self, inputs, hidden_state):
"""The Args: inputs: The inputs. h... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BahandauAttention:
"""The attention layer with bahandau score."""
def __init__(self, units):
"""The structure function. Args: units: The units number of attention hidden layer."""
super(BahandauAttention, self).__init__()
self.W1 = tf.keras.layers.Dense(units=units)
self.W... | the_stack_v2_python_sparse | NeuralNetworks-tensorflow/RNN/nmt_with_attention/nmt.py | zhaocc1106/machine_learn | train | 15 |
a3b480e5dba83500dcbbef20424d7f2e21969f94 | [
"ret_str = str(self.id)\nif self.title:\n ret_str += f' ({self.title})'\nreturn ret_str",
"super().clean()\nif self.image and self.youtube_id:\n raise ValidationError(ugettext('A media resource may not contain both an image and a YouTube video.'))\nif not self.image and (not self.youtube_id):\n raise Val... | <|body_start_0|>
ret_str = str(self.id)
if self.title:
ret_str += f' ({self.title})'
return ret_str
<|end_body_0|>
<|body_start_1|>
super().clean()
if self.image and self.youtube_id:
raise ValidationError(ugettext('A media resource may not contain both an... | A container for a single media object such as an image or video. | MediaResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MediaResource:
"""A container for a single media object such as an image or video."""
def __str__(self):
"""Returns: A user readable string describing the instance."""
<|body_0|>
def clean(self):
"""Ensure that the resource contains exactly one type of media."""
... | stack_v2_sparse_classes_36k_train_006439 | 6,917 | permissive | [
{
"docstring": "Returns: A user readable string describing the instance.",
"name": "__str__",
"signature": "def __str__(self)"
},
{
"docstring": "Ensure that the resource contains exactly one type of media.",
"name": "clean",
"signature": "def clean(self)"
},
{
"docstring": "Retu... | 3 | stack_v2_sparse_classes_30k_val_000407 | Implement the Python class `MediaResource` described below.
Class description:
A container for a single media object such as an image or video.
Method signatures and docstrings:
- def __str__(self): Returns: A user readable string describing the instance.
- def clean(self): Ensure that the resource contains exactly o... | Implement the Python class `MediaResource` described below.
Class description:
A container for a single media object such as an image or video.
Method signatures and docstrings:
- def __str__(self): Returns: A user readable string describing the instance.
- def clean(self): Ensure that the resource contains exactly o... | a4bc1f4adee7ecfba840ad45da22513f88acbbd0 | <|skeleton|>
class MediaResource:
"""A container for a single media object such as an image or video."""
def __str__(self):
"""Returns: A user readable string describing the instance."""
<|body_0|>
def clean(self):
"""Ensure that the resource contains exactly one type of media."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MediaResource:
"""A container for a single media object such as an image or video."""
def __str__(self):
"""Returns: A user readable string describing the instance."""
ret_str = str(self.id)
if self.title:
ret_str += f' ({self.title})'
return ret_str
def c... | the_stack_v2_python_sparse | darksite/cms/models.py | UNCDarkside/DarksiteAPI | train | 0 |
6bed9e02e9f1444770bb7b56efb38e34543fd3a7 | [
"self.year = year\nself.month = month\nself.course_id = course_id\nself.user_type = user_type\nsuper(Calendar, self).__init__()",
"events_per_day = events.filter(eventDate__day=day)\nd = ''\nfor event in events_per_day:\n d += f'<li> {event.get_html_url} </li>'\nif day != 0:\n return f\"<td><span class='dat... | <|body_start_0|>
self.year = year
self.month = month
self.course_id = course_id
self.user_type = user_type
super(Calendar, self).__init__()
<|end_body_0|>
<|body_start_1|>
events_per_day = events.filter(eventDate__day=day)
d = ''
for event in events_per_d... | Calendar | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Calendar:
def __init__(self, year=None, month=None, course_id=None, user_type=None):
"""calendar initialisation .. note::This code was made by following this tutorial "https://www.huiwenteo.com/normal/2018/07/24/django-calendar.html". Some part of the code is change in order to be able t... | stack_v2_sparse_classes_36k_train_006440 | 3,320 | no_license | [
{
"docstring": "calendar initialisation .. note::This code was made by following this tutorial \"https://www.huiwenteo.com/normal/2018/07/24/django-calendar.html\". Some part of the code is change in order to be able to be integrated to the webapp :param self: object that contains metadata about the request. :p... | 4 | stack_v2_sparse_classes_30k_test_000326 | Implement the Python class `Calendar` described below.
Class description:
Implement the Calendar class.
Method signatures and docstrings:
- def __init__(self, year=None, month=None, course_id=None, user_type=None): calendar initialisation .. note::This code was made by following this tutorial "https://www.huiwenteo.c... | Implement the Python class `Calendar` described below.
Class description:
Implement the Calendar class.
Method signatures and docstrings:
- def __init__(self, year=None, month=None, course_id=None, user_type=None): calendar initialisation .. note::This code was made by following this tutorial "https://www.huiwenteo.c... | f003cc8721d78abe9eb6279818ecef287689bb72 | <|skeleton|>
class Calendar:
def __init__(self, year=None, month=None, course_id=None, user_type=None):
"""calendar initialisation .. note::This code was made by following this tutorial "https://www.huiwenteo.com/normal/2018/07/24/django-calendar.html". Some part of the code is change in order to be able t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Calendar:
def __init__(self, year=None, month=None, course_id=None, user_type=None):
"""calendar initialisation .. note::This code was made by following this tutorial "https://www.huiwenteo.com/normal/2018/07/24/django-calendar.html". Some part of the code is change in order to be able to be integrate... | the_stack_v2_python_sparse | IPC/utils.py | erikmudkip/finalProject | train | 0 | |
7a02d49108d79b2075ab25f1edbb3626dee48182 | [
"super().__init__(parent)\nself.items = items\nself.initUi()",
"width = 150\nheight = 70\nroundness = 20\ncolor = qRgb(154, 179, 174)\nstyle = '\\n QLabel {\\n color: black;\\n font-weight: bold;\\n font-size: 30pt;\\n font-family: Asap;\\n ... | <|body_start_0|>
super().__init__(parent)
self.items = items
self.initUi()
<|end_body_0|>
<|body_start_1|>
width = 150
height = 70
roundness = 20
color = qRgb(154, 179, 174)
style = '\n QLabel {\n color: black;\n f... | Food Menu widget. | Tabs | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tabs:
"""Food Menu widget."""
def __init__(self, items, parent=None):
"""Init."""
<|body_0|>
def initUi(self):
"""Ui Setup."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__(parent)
self.items = items
self.initUi()... | stack_v2_sparse_classes_36k_train_006441 | 2,585 | no_license | [
{
"docstring": "Init.",
"name": "__init__",
"signature": "def __init__(self, items, parent=None)"
},
{
"docstring": "Ui Setup.",
"name": "initUi",
"signature": "def initUi(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006087 | Implement the Python class `Tabs` described below.
Class description:
Food Menu widget.
Method signatures and docstrings:
- def __init__(self, items, parent=None): Init.
- def initUi(self): Ui Setup. | Implement the Python class `Tabs` described below.
Class description:
Food Menu widget.
Method signatures and docstrings:
- def __init__(self, items, parent=None): Init.
- def initUi(self): Ui Setup.
<|skeleton|>
class Tabs:
"""Food Menu widget."""
def __init__(self, items, parent=None):
"""Init."""... | a5d18593e689123cac34af552628ed2818ca5d59 | <|skeleton|>
class Tabs:
"""Food Menu widget."""
def __init__(self, items, parent=None):
"""Init."""
<|body_0|>
def initUi(self):
"""Ui Setup."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tabs:
"""Food Menu widget."""
def __init__(self, items, parent=None):
"""Init."""
super().__init__(parent)
self.items = items
self.initUi()
def initUi(self):
"""Ui Setup."""
width = 150
height = 70
roundness = 20
color = qRgb(15... | the_stack_v2_python_sparse | Menu.py | edgary777/lonchepos | train | 0 |
dc32d9e620f1bec5cb404a7ce702f4b26d02de5e | [
"self.job_id = job_id\nself.cloud_target_type = cloud_target_type\nself.expiry_time_usecs = expiry_time_usecs\nself.target_id = target_id\nself.target_name = target_name\nself.total_snapshots = total_snapshots\nself.mtype = mtype",
"if dictionary is None:\n return None\njob_id = dictionary.get('JobId')\ncloud_... | <|body_start_0|>
self.job_id = job_id
self.cloud_target_type = cloud_target_type
self.expiry_time_usecs = expiry_time_usecs
self.target_id = target_id
self.target_name = target_name
self.total_snapshots = total_snapshots
self.mtype = mtype
<|end_body_0|>
<|body_s... | Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type (string): Specifies the cloud deploy target type. For example 'kAzure','kAWS', ... | GdprCopyTask | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GdprCopyTask:
"""Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type (string): Specifies the cloud deploy ta... | stack_v2_sparse_classes_36k_train_006442 | 3,218 | permissive | [
{
"docstring": "Constructor for the GdprCopyTask class",
"name": "__init__",
"signature": "def __init__(self, job_id=None, cloud_target_type=None, expiry_time_usecs=None, target_id=None, target_name=None, total_snapshots=None, mtype=None)"
},
{
"docstring": "Creates an instance of this model fro... | 2 | stack_v2_sparse_classes_30k_train_005789 | Implement the Python class `GdprCopyTask` described below.
Class description:
Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type ... | Implement the Python class `GdprCopyTask` described below.
Class description:
Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class GdprCopyTask:
"""Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type (string): Specifies the cloud deploy ta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GdprCopyTask:
"""Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type (string): Specifies the cloud deploy target type. Fo... | the_stack_v2_python_sparse | cohesity_management_sdk/models/gdpr_copy_task.py | cohesity/management-sdk-python | train | 24 |
325c32215a9def40e1776540593a190e8eb8ae57 | [
"color = self.color\nif color is not None:\n glColorMaterial(GL_FRONT_AND_BACK, GL_DIFFUSE)\n glEnable(GL_COLOR_MATERIAL)\n glEnableClientState(GL_COLOR_ARRAY)\n color.bind()\n try:\n glColorPointer(3, GL_FLOAT, 0, color)\n finally:\n color.unbind()\n return 1\nelse:\n return 0... | <|body_start_0|>
color = self.color
if color is not None:
glColorMaterial(GL_FRONT_AND_BACK, GL_DIFFUSE)
glEnable(GL_COLOR_MATERIAL)
glEnableClientState(GL_COLOR_ARRAY)
color.bind()
try:
glColorPointer(3, GL_FLOAT, 0, color)
... | VBO-based holder | VBOHolder | [
"GPL-1.0-or-later",
"MIT",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-other-copyleft",
"LGPL-2.1-or-later",
"GPL-3.0-only",
"LGPL-2.0-or-later",
"GPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VBOHolder:
"""VBO-based holder"""
def _enableColors(self, node):
"""Enable the colour array if possible"""
<|body_0|>
def _enableNormals(self, node):
"""Enable the normal array if possible"""
<|body_1|>
def _enableTextures(self, node):
"""Ena... | stack_v2_sparse_classes_36k_train_006443 | 12,165 | permissive | [
{
"docstring": "Enable the colour array if possible",
"name": "_enableColors",
"signature": "def _enableColors(self, node)"
},
{
"docstring": "Enable the normal array if possible",
"name": "_enableNormals",
"signature": "def _enableNormals(self, node)"
},
{
"docstring": "Enable t... | 4 | null | Implement the Python class `VBOHolder` described below.
Class description:
VBO-based holder
Method signatures and docstrings:
- def _enableColors(self, node): Enable the colour array if possible
- def _enableNormals(self, node): Enable the normal array if possible
- def _enableTextures(self, node): Enable the normal ... | Implement the Python class `VBOHolder` described below.
Class description:
VBO-based holder
Method signatures and docstrings:
- def _enableColors(self, node): Enable the colour array if possible
- def _enableNormals(self, node): Enable the normal array if possible
- def _enableTextures(self, node): Enable the normal ... | 7f600ad153270feff12aa7aa86d7ed0a49ebc71c | <|skeleton|>
class VBOHolder:
"""VBO-based holder"""
def _enableColors(self, node):
"""Enable the colour array if possible"""
<|body_0|>
def _enableNormals(self, node):
"""Enable the normal array if possible"""
<|body_1|>
def _enableTextures(self, node):
"""Ena... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VBOHolder:
"""VBO-based holder"""
def _enableColors(self, node):
"""Enable the colour array if possible"""
color = self.color
if color is not None:
glColorMaterial(GL_FRONT_AND_BACK, GL_DIFFUSE)
glEnable(GL_COLOR_MATERIAL)
glEnableClientState(GL... | the_stack_v2_python_sparse | pythonAnimations/pyOpenGLChess/engineDirectory/oglc-env/lib/python2.7/site-packages/OpenGLContext/scenegraph/indexedpolygons.py | alexus37/AugmentedRealityChess | train | 1 |
edf923aa25dbe41f4ecf41a0c5ccb434f74230aa | [
"matches = []\nif isinstance(obj, dict):\n if len(obj) == 1:\n for key_name, _ in obj.items():\n if key_name not in self.supported_functions:\n message = 'FindInMap only supports [{0}] functions at {1}'\n matches.append(RuleMatch(tree[:] + [key_name], message.forma... | <|body_start_0|>
matches = []
if isinstance(obj, dict):
if len(obj) == 1:
for key_name, _ in obj.items():
if key_name not in self.supported_functions:
message = 'FindInMap only supports [{0}] functions at {1}'
... | Check if FindInMap values are correct | FindInMap | [
"MIT-0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FindInMap:
"""Check if FindInMap values are correct"""
def check_dict(self, obj, tree):
"""Check that obj is a dict with Ref as the only key Mappings only support Ref inside them"""
<|body_0|>
def map_name(self, map_name, mappings, tree):
"""Check the map name"""... | stack_v2_sparse_classes_36k_train_006444 | 5,093 | permissive | [
{
"docstring": "Check that obj is a dict with Ref as the only key Mappings only support Ref inside them",
"name": "check_dict",
"signature": "def check_dict(self, obj, tree)"
},
{
"docstring": "Check the map name",
"name": "map_name",
"signature": "def map_name(self, map_name, mappings, ... | 5 | null | Implement the Python class `FindInMap` described below.
Class description:
Check if FindInMap values are correct
Method signatures and docstrings:
- def check_dict(self, obj, tree): Check that obj is a dict with Ref as the only key Mappings only support Ref inside them
- def map_name(self, map_name, mappings, tree): ... | Implement the Python class `FindInMap` described below.
Class description:
Check if FindInMap values are correct
Method signatures and docstrings:
- def check_dict(self, obj, tree): Check that obj is a dict with Ref as the only key Mappings only support Ref inside them
- def map_name(self, map_name, mappings, tree): ... | 5176573c2f4cb7313998b4bc0bcb0716b58ea380 | <|skeleton|>
class FindInMap:
"""Check if FindInMap values are correct"""
def check_dict(self, obj, tree):
"""Check that obj is a dict with Ref as the only key Mappings only support Ref inside them"""
<|body_0|>
def map_name(self, map_name, mappings, tree):
"""Check the map name"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FindInMap:
"""Check if FindInMap values are correct"""
def check_dict(self, obj, tree):
"""Check that obj is a dict with Ref as the only key Mappings only support Ref inside them"""
matches = []
if isinstance(obj, dict):
if len(obj) == 1:
for key_name, ... | the_stack_v2_python_sparse | src/cfnlint/rules/functions/FindInMap.py | rene84/cfn-python-lint | train | 1 |
4ffe360107579f25d35c3e89c5b11bfa5f08e841 | [
"self.root = None\nself.region = region.copy()\nxmin2k = smaller2k(self.region.x_min)\nymin2k = smaller2k(self.region.y_min)\nxmax2k = larger2k(self.region.x_max)\nymax2k = larger2k(self.region.y_max)\nself.region.x_min = self.region.y_min = min(xmin2k, ymin2k)\nself.region.x_max = self.region.y_max = max(xmax2k, y... | <|body_start_0|>
self.root = None
self.region = region.copy()
xmin2k = smaller2k(self.region.x_min)
ymin2k = smaller2k(self.region.y_min)
xmax2k = larger2k(self.region.x_max)
ymax2k = larger2k(self.region.y_max)
self.region.x_min = self.region.y_min = min(xmin2k, ... | QuadTree | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuadTree:
def __init__(self, region):
"""Create QuadTree defined over existing rectangular region. Assume that (0,0) is the lower left coordinate and the half-length side of any square in quadtree is power of 2. If incoming region is too small, this expands accordingly."""
<|body... | stack_v2_sparse_classes_36k_train_006445 | 7,418 | permissive | [
{
"docstring": "Create QuadTree defined over existing rectangular region. Assume that (0,0) is the lower left coordinate and the half-length side of any square in quadtree is power of 2. If incoming region is too small, this expands accordingly.",
"name": "__init__",
"signature": "def __init__(self, reg... | 5 | stack_v2_sparse_classes_30k_train_017890 | Implement the Python class `QuadTree` described below.
Class description:
Implement the QuadTree class.
Method signatures and docstrings:
- def __init__(self, region): Create QuadTree defined over existing rectangular region. Assume that (0,0) is the lower left coordinate and the half-length side of any square in qua... | Implement the Python class `QuadTree` described below.
Class description:
Implement the QuadTree class.
Method signatures and docstrings:
- def __init__(self, region): Create QuadTree defined over existing rectangular region. Assume that (0,0) is the lower left coordinate and the half-length side of any square in qua... | f0dd93a4099f363580fe1b36216f808be31a0f17 | <|skeleton|>
class QuadTree:
def __init__(self, region):
"""Create QuadTree defined over existing rectangular region. Assume that (0,0) is the lower left coordinate and the half-length side of any square in quadtree is power of 2. If incoming region is too small, this expands accordingly."""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuadTree:
def __init__(self, region):
"""Create QuadTree defined over existing rectangular region. Assume that (0,0) is the lower left coordinate and the half-length side of any square in quadtree is power of 2. If incoming region is too small, this expands accordingly."""
self.root = None
... | the_stack_v2_python_sparse | Quadtree/quadtree/quad_point.py | kmsnyder/python-quadtree-webinar | train | 0 | |
03e55c6015649e55a16894753259fd73bc1df896 | [
"if filter_id is not None:\n f = Filter.get_if_accessible_by(filter_id, self.current_user, raise_if_none=True, options=[joinedload(Filter.stream)])\n self.verify_and_commit()\n return self.success(data=f)\nfilters = Filter.get_records_accessible_by(self.current_user)\nself.verify_and_commit()\nreturn self.... | <|body_start_0|>
if filter_id is not None:
f = Filter.get_if_accessible_by(filter_id, self.current_user, raise_if_none=True, options=[joinedload(Filter.stream)])
self.verify_and_commit()
return self.success(data=f)
filters = Filter.get_records_accessible_by(self.curre... | FilterHandler | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilterHandler:
def get(self, filter_id=None):
"""--- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleFilter 400: content: application/json: schema: ... | stack_v2_sparse_classes_36k_train_006446 | 4,760 | permissive | [
{
"docstring": "--- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleFilter 400: content: application/json: schema: Error multiple: description: Retrieve all filters tags: -... | 4 | stack_v2_sparse_classes_30k_train_012171 | Implement the Python class `FilterHandler` described below.
Class description:
Implement the FilterHandler class.
Method signatures and docstrings:
- def get(self, filter_id=None): --- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer re... | Implement the Python class `FilterHandler` described below.
Class description:
Implement the FilterHandler class.
Method signatures and docstrings:
- def get(self, filter_id=None): --- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer re... | 2433d5ae0b2f41faac3c76ed4ae8d9a4da5522fb | <|skeleton|>
class FilterHandler:
def get(self, filter_id=None):
"""--- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleFilter 400: content: application/json: schema: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FilterHandler:
def get(self, filter_id=None):
"""--- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleFilter 400: content: application/json: schema: Error multiple... | the_stack_v2_python_sparse | skyportal/handlers/api/filter.py | dmitryduev/skyportal | train | 1 | |
631de2942d6f0b78ea75799a7cdf87ae27958f39 | [
"super().__init__()\nif not callable(raysampler):\n raise ValueError('\"raysampler\" has to be a \"Callable\" object.')\nif not callable(raymarcher):\n raise ValueError('\"raymarcher\" has to be a \"Callable\" object.')\nself.raysampler = raysampler\nself.raymarcher = raymarcher",
"if not callable(volumetri... | <|body_start_0|>
super().__init__()
if not callable(raysampler):
raise ValueError('"raysampler" has to be a "Callable" object.')
if not callable(raymarcher):
raise ValueError('"raymarcher" has to be a "Callable" object.')
self.raysampler = raysampler
self.... | A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input the rendering cameras as well as the `volumetric_function` `Callable`, which defines ... | ImplicitRenderer | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImplicitRenderer:
"""A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input the rendering cameras as well as the `vol... | stack_v2_sparse_classes_36k_train_006447 | 17,111 | permissive | [
{
"docstring": "Args: raysampler: A `Callable` that takes as input scene cameras (an instance of `CamerasBase`) and returns a RayBundle or HeterogeneousRayBundle, that describes the rays emitted from the cameras. raymarcher: A `Callable` that receives the response of the `volumetric_function` (an input to `self... | 2 | stack_v2_sparse_classes_30k_test_000407 | Implement the Python class `ImplicitRenderer` described below.
Class description:
A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input th... | Implement the Python class `ImplicitRenderer` described below.
Class description:
A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input th... | a3d99cab6bf5eb69be8d5eb48895da6edd859565 | <|skeleton|>
class ImplicitRenderer:
"""A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input the rendering cameras as well as the `vol... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImplicitRenderer:
"""A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input the rendering cameras as well as the `volumetric_funct... | the_stack_v2_python_sparse | pytorch3d/renderer/implicit/renderer.py | facebookresearch/pytorch3d | train | 7,964 |
7e09de1c5dc520c79c269c897db4b3fe602bd1f3 | [
"assert isinstance(response, scrapy.http.response.html.HtmlResponse)\nurls = [response.url]\nposts_per_page = 50\nlast_page = response.selector.xpath('//a[contains(@title, \"Click to jump to page\")]/strong[2]/text()').extract_first()\nif last_page:\n last_page = read_number(last_page)\nelse:\n last_page = 0\... | <|body_start_0|>
assert isinstance(response, scrapy.http.response.html.HtmlResponse)
urls = [response.url]
posts_per_page = 50
last_page = response.selector.xpath('//a[contains(@title, "Click to jump to page")]/strong[2]/text()').extract_first()
if last_page:
last_pag... | scrape images from angling addicts forum | SeaAnglingIrelandArchives | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SeaAnglingIrelandArchives:
"""scrape images from angling addicts forum"""
def parse(self, response):
"""get links to report boards yields: http://www.sea-angling-ireland.org/forum/viewforum.php?f=62 http://www.sea-angling-ireland.org/forum/viewforum.php?f=62&start=50"""
<|bod... | stack_v2_sparse_classes_36k_train_006448 | 5,577 | no_license | [
{
"docstring": "get links to report boards yields: http://www.sea-angling-ireland.org/forum/viewforum.php?f=62 http://www.sea-angling-ireland.org/forum/viewforum.php?f=62&start=50",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "get links to all reports from boards ... | 3 | null | Implement the Python class `SeaAnglingIrelandArchives` described below.
Class description:
scrape images from angling addicts forum
Method signatures and docstrings:
- def parse(self, response): get links to report boards yields: http://www.sea-angling-ireland.org/forum/viewforum.php?f=62 http://www.sea-angling-irela... | Implement the Python class `SeaAnglingIrelandArchives` described below.
Class description:
scrape images from angling addicts forum
Method signatures and docstrings:
- def parse(self, response): get links to report boards yields: http://www.sea-angling-ireland.org/forum/viewforum.php?f=62 http://www.sea-angling-irela... | 9123aa6baf538b662143b9098d963d55165e8409 | <|skeleton|>
class SeaAnglingIrelandArchives:
"""scrape images from angling addicts forum"""
def parse(self, response):
"""get links to report boards yields: http://www.sea-angling-ireland.org/forum/viewforum.php?f=62 http://www.sea-angling-ireland.org/forum/viewforum.php?f=62&start=50"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SeaAnglingIrelandArchives:
"""scrape images from angling addicts forum"""
def parse(self, response):
"""get links to report boards yields: http://www.sea-angling-ireland.org/forum/viewforum.php?f=62 http://www.sea-angling-ireland.org/forum/viewforum.php?f=62&start=50"""
assert isinstance(... | the_stack_v2_python_sparse | imgscrape/spiders/seaanglingireland.py | gmonkman/python | train | 0 |
6738ec6de0db9d7f9d515f9ee57d99976b112383 | [
"self.version = ''\nself.datafile = ''\nself.command = ''\nself.alphabet = ''\nself.sequences = []",
"if isinstance(key, str):\n for motif in self:\n if motif.name == key:\n return motif\nelse:\n return list.__getitem__(self, key)"
] | <|body_start_0|>
self.version = ''
self.datafile = ''
self.command = ''
self.alphabet = ''
self.sequences = []
<|end_body_0|>
<|body_start_1|>
if isinstance(key, str):
for motif in self:
if motif.name == key:
return motif
... | A class for holding the results of a MEME run. A meme.Record is an object that holds the results from running MEME. It implements no methods of its own. The meme.Record class inherits from list, so you can access individual motifs in the record by their index. Alternatively, you can find a motif by its name: >>> from B... | Record | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Record:
"""A class for holding the results of a MEME run. A meme.Record is an object that holds the results from running MEME. It implements no methods of its own. The meme.Record class inherits from list, so you can access individual motifs in the record by their index. Alternatively, you can fi... | stack_v2_sparse_classes_36k_train_006449 | 6,706 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Return the motif of index key.",
"name": "__getitem__",
"signature": "def __getitem__(self, key)"
}
] | 2 | null | Implement the Python class `Record` described below.
Class description:
A class for holding the results of a MEME run. A meme.Record is an object that holds the results from running MEME. It implements no methods of its own. The meme.Record class inherits from list, so you can access individual motifs in the record by... | Implement the Python class `Record` described below.
Class description:
A class for holding the results of a MEME run. A meme.Record is an object that holds the results from running MEME. It implements no methods of its own. The meme.Record class inherits from list, so you can access individual motifs in the record by... | 595c5c46794ae08a1f19716636eac7430cededa1 | <|skeleton|>
class Record:
"""A class for holding the results of a MEME run. A meme.Record is an object that holds the results from running MEME. It implements no methods of its own. The meme.Record class inherits from list, so you can access individual motifs in the record by their index. Alternatively, you can fi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Record:
"""A class for holding the results of a MEME run. A meme.Record is an object that holds the results from running MEME. It implements no methods of its own. The meme.Record class inherits from list, so you can access individual motifs in the record by their index. Alternatively, you can find a motif by... | the_stack_v2_python_sparse | .venv/Lib/site-packages/Bio/motifs/meme.py | abner-lucas/tp-cruzi-db | train | 2 |
a3196eba68381137ee1cb0edc35f2a3abcafe563 | [
"a, b, c = sorted(amount)\nif c >= a + b:\n return c\nreturn ceil((a + b + c) / 2)",
"pq = []\nfor num in amount:\n if num > 0:\n heappush(pq, -num)\nres = 0\nwhile len(pq) >= 2:\n a, b = (-heappop(pq), -heappop(pq))\n a, b = (a - 1, b - 1)\n if a > 0:\n heappush(pq, -a)\n if b > 0... | <|body_start_0|>
a, b, c = sorted(amount)
if c >= a + b:
return c
return ceil((a + b + c) / 2)
<|end_body_0|>
<|body_start_1|>
pq = []
for num in amount:
if num > 0:
heappush(pq, -num)
res = 0
while len(pq) >= 2:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fillCups(self, amount: List[int]) -> int:
"""贪心 一种是有一种水特别多，那么答案就是这种水的数量。 否则，一定可以匹配到只剩一杯，或匹配完。"""
<|body_0|>
def fillCups2(self, amount: List[int]) -> int:
"""优先队列模拟 每次取两个最大的消去"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
a, b, c = s... | stack_v2_sparse_classes_36k_train_006450 | 1,425 | no_license | [
{
"docstring": "贪心 一种是有一种水特别多，那么答案就是这种水的数量。 否则，一定可以匹配到只剩一杯，或匹配完。",
"name": "fillCups",
"signature": "def fillCups(self, amount: List[int]) -> int"
},
{
"docstring": "优先队列模拟 每次取两个最大的消去",
"name": "fillCups2",
"signature": "def fillCups2(self, amount: List[int]) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fillCups(self, amount: List[int]) -> int: 贪心 一种是有一种水特别多，那么答案就是这种水的数量。 否则，一定可以匹配到只剩一杯，或匹配完。
- def fillCups2(self, amount: List[int]) -> int: 优先队列模拟 每次取两个最大的消去 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fillCups(self, amount: List[int]) -> int: 贪心 一种是有一种水特别多，那么答案就是这种水的数量。 否则，一定可以匹配到只剩一杯，或匹配完。
- def fillCups2(self, amount: List[int]) -> int: 优先队列模拟 每次取两个最大的消去
<|skeleton|>
cl... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def fillCups(self, amount: List[int]) -> int:
"""贪心 一种是有一种水特别多，那么答案就是这种水的数量。 否则，一定可以匹配到只剩一杯，或匹配完。"""
<|body_0|>
def fillCups2(self, amount: List[int]) -> int:
"""优先队列模拟 每次取两个最大的消去"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def fillCups(self, amount: List[int]) -> int:
"""贪心 一种是有一种水特别多，那么答案就是这种水的数量。 否则，一定可以匹配到只剩一杯，或匹配完。"""
a, b, c = sorted(amount)
if c >= a + b:
return c
return ceil((a + b + c) / 2)
def fillCups2(self, amount: List[int]) -> int:
"""优先队列模拟 每次取两个最大... | the_stack_v2_python_sparse | 12_贪心算法/经典题/倒水问题/6112. 装满杯子需要的最短总时长.py | 981377660LMT/algorithm-study | train | 225 | |
f28fe9e01812afc15a1270ad7c3b3a355fbf5e1f | [
"dic, q = (['0', '1', 'abc', 'def', 'ghi', 'jkl', 'mno', 'pqrs', 'tuv', 'wxyz'], [])\nif len(digits) == 0 or not digits:\n return q\nq.append('')\nfor i in range(len(digits)):\n dic_index = int(digits[i])\n while len(q[0]) == i:\n temp = q.pop(0)\n for c in dic[dic_index]:\n q.appe... | <|body_start_0|>
dic, q = (['0', '1', 'abc', 'def', 'ghi', 'jkl', 'mno', 'pqrs', 'tuv', 'wxyz'], [])
if len(digits) == 0 or not digits:
return q
q.append('')
for i in range(len(digits)):
dic_index = int(digits[i])
while len(q[0]) == i:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def letterCombinations(self, digits):
""":type digits: str :rtype: List[str]"""
<|body_0|>
def letterCombinations_1(self, digits):
""":type digits: str :rtype: List[str]"""
<|body_1|>
def letterCombinations_2(self, digits):
""":type dig... | stack_v2_sparse_classes_36k_train_006451 | 2,318 | no_license | [
{
"docstring": ":type digits: str :rtype: List[str]",
"name": "letterCombinations",
"signature": "def letterCombinations(self, digits)"
},
{
"docstring": ":type digits: str :rtype: List[str]",
"name": "letterCombinations_1",
"signature": "def letterCombinations_1(self, digits)"
},
{
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def letterCombinations(self, digits): :type digits: str :rtype: List[str]
- def letterCombinations_1(self, digits): :type digits: str :rtype: List[str]
- def letterCombinations_2... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def letterCombinations(self, digits): :type digits: str :rtype: List[str]
- def letterCombinations_1(self, digits): :type digits: str :rtype: List[str]
- def letterCombinations_2... | 9d9e0c08992ef7dbd9ac517821faa9de17f49b0e | <|skeleton|>
class Solution:
def letterCombinations(self, digits):
""":type digits: str :rtype: List[str]"""
<|body_0|>
def letterCombinations_1(self, digits):
""":type digits: str :rtype: List[str]"""
<|body_1|>
def letterCombinations_2(self, digits):
""":type dig... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def letterCombinations(self, digits):
""":type digits: str :rtype: List[str]"""
dic, q = (['0', '1', 'abc', 'def', 'ghi', 'jkl', 'mno', 'pqrs', 'tuv', 'wxyz'], [])
if len(digits) == 0 or not digits:
return q
q.append('')
for i in range(len(digits))... | the_stack_v2_python_sparse | 017-letter-combinations-of-a-phone-number.py | floydchenchen/leetcode | train | 0 | |
8cb5ee0e7fa87bca8beeb005f6cc9b75065fc694 | [
"mile_rule = self.env.ref('metro_park_base_data_10.repair_rule_l')\nfor record in self:\n if record.rule and record.rule.id == mile_rule.id:\n record.is_mile = True",
"if len(self) == 0:\n return\nfor record in self:\n if not record.plan_id or not record.dev:\n continue\n pre_date_train_... | <|body_start_0|>
mile_rule = self.env.ref('metro_park_base_data_10.repair_rule_l')
for record in self:
if record.rule and record.rule.id == mile_rule.id:
record.is_mile = True
<|end_body_0|>
<|body_start_1|>
if len(self) == 0:
return
for record in... | 日计划设备检修信息，包含计划内容和日常维护及运行内容 | RuleInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RuleInfo:
"""日计划设备检修信息，包含计划内容和日常维护及运行内容"""
def _compute_is_mile(self):
"""计算是否为公里数 :return:"""
<|body_0|>
def _compute_last_repair_info(self):
"""计算上次里程修信息 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
mile_rule = self.env.ref('metro_... | stack_v2_sparse_classes_36k_train_006452 | 1,559 | no_license | [
{
"docstring": "计算是否为公里数 :return:",
"name": "_compute_is_mile",
"signature": "def _compute_is_mile(self)"
},
{
"docstring": "计算上次里程修信息 :return:",
"name": "_compute_last_repair_info",
"signature": "def _compute_last_repair_info(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019932 | Implement the Python class `RuleInfo` described below.
Class description:
日计划设备检修信息，包含计划内容和日常维护及运行内容
Method signatures and docstrings:
- def _compute_is_mile(self): 计算是否为公里数 :return:
- def _compute_last_repair_info(self): 计算上次里程修信息 :return: | Implement the Python class `RuleInfo` described below.
Class description:
日计划设备检修信息，包含计划内容和日常维护及运行内容
Method signatures and docstrings:
- def _compute_is_mile(self): 计算是否为公里数 :return:
- def _compute_last_repair_info(self): 计算上次里程修信息 :return:
<|skeleton|>
class RuleInfo:
"""日计划设备检修信息，包含计划内容和日常维护及运行内容"""
def _... | 13b428a5c4ade6278e3e5e996ef10d9fb0fea4b9 | <|skeleton|>
class RuleInfo:
"""日计划设备检修信息，包含计划内容和日常维护及运行内容"""
def _compute_is_mile(self):
"""计算是否为公里数 :return:"""
<|body_0|>
def _compute_last_repair_info(self):
"""计算上次里程修信息 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RuleInfo:
"""日计划设备检修信息，包含计划内容和日常维护及运行内容"""
def _compute_is_mile(self):
"""计算是否为公里数 :return:"""
mile_rule = self.env.ref('metro_park_base_data_10.repair_rule_l')
for record in self:
if record.rule and record.rule.id == mile_rule.id:
record.is_mile = True... | the_stack_v2_python_sparse | mdias_addons/metro_park_base_data_10/models/plan_date_rule_info.py | rezaghanimi/main_mdias | train | 0 |
b94ee346b3b81a27026c223ab788ae242b99f3fd | [
"parser.add_argument('BOMName', type=str, help='Provide a BillOfMaterial Name which was used for Asset')\nparser.add_argument('Quantity', type=int, help='Number of Asset to be created')\nparser.add_argument('ProductName', type=str, help='Provide a Product Name')\nparser.add_argument('WarehouseName', type=str, help=... | <|body_start_0|>
parser.add_argument('BOMName', type=str, help='Provide a BillOfMaterial Name which was used for Asset')
parser.add_argument('Quantity', type=int, help='Number of Asset to be created')
parser.add_argument('ProductName', type=str, help='Provide a Product Name')
parser.add_... | . | Command | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Command:
"""."""
def add_arguments(self, parser):
"""Mandatory Arguments."""
<|body_0|>
def handle(self, *args, **options):
"""."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
parser.add_argument('BOMName', type=str, help='Provide a BillOfMater... | stack_v2_sparse_classes_36k_train_006453 | 3,898 | no_license | [
{
"docstring": "Mandatory Arguments.",
"name": "add_arguments",
"signature": "def add_arguments(self, parser)"
},
{
"docstring": ".",
"name": "handle",
"signature": "def handle(self, *args, **options)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018505 | Implement the Python class `Command` described below.
Class description:
.
Method signatures and docstrings:
- def add_arguments(self, parser): Mandatory Arguments.
- def handle(self, *args, **options): . | Implement the Python class `Command` described below.
Class description:
.
Method signatures and docstrings:
- def add_arguments(self, parser): Mandatory Arguments.
- def handle(self, *args, **options): .
<|skeleton|>
class Command:
"""."""
def add_arguments(self, parser):
"""Mandatory Arguments."""... | 0c9c041624b1133d04c0389a9270140b68c10b21 | <|skeleton|>
class Command:
"""."""
def add_arguments(self, parser):
"""Mandatory Arguments."""
<|body_0|>
def handle(self, *args, **options):
"""."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Command:
"""."""
def add_arguments(self, parser):
"""Mandatory Arguments."""
parser.add_argument('BOMName', type=str, help='Provide a BillOfMaterial Name which was used for Asset')
parser.add_argument('Quantity', type=int, help='Number of Asset to be created')
parser.add_a... | the_stack_v2_python_sparse | aims/inventory/management/commands/create_assets.py | anmolsrivastava18/ERP_Repository | train | 0 |
bc4609361c3cf4afec0a8f65fa06c956c45e5ba2 | [
"self.x = array_check(x)\nself.y = array_check(y)\nself._coef = None\nself._intercept = None\nself._pvalues = None\nself._f_statistics = None\nself._r_squared = None\nself.__m = OLS(self.y, sm.add_constant(self.x))",
"result = self.__m.fit()\nself._intercept, *self._coef = result.params\nself._pvalues = result.f_... | <|body_start_0|>
self.x = array_check(x)
self.y = array_check(y)
self._coef = None
self._intercept = None
self._pvalues = None
self._f_statistics = None
self._r_squared = None
self.__m = OLS(self.y, sm.add_constant(self.x))
<|end_body_0|>
<|body_start_1|>... | Linear regression for single variable or multi-variable. | LinearRegression | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearRegression:
"""Linear regression for single variable or multi-variable."""
def __init__(self, x: array_like, y: array_like) -> None:
""":param x: array_like N-D array with (n-sample, n-feature) :param y: array_like"""
<|body_0|>
def fit(self) -> LinearRegressionPar... | stack_v2_sparse_classes_36k_train_006454 | 4,947 | no_license | [
{
"docstring": ":param x: array_like N-D array with (n-sample, n-feature) :param y: array_like",
"name": "__init__",
"signature": "def __init__(self, x: array_like, y: array_like) -> None"
},
{
"docstring": "Fit the self.x and self.y, then get fitting params. :return: class LinearRegressionParam... | 4 | stack_v2_sparse_classes_30k_test_000734 | Implement the Python class `LinearRegression` described below.
Class description:
Linear regression for single variable or multi-variable.
Method signatures and docstrings:
- def __init__(self, x: array_like, y: array_like) -> None: :param x: array_like N-D array with (n-sample, n-feature) :param y: array_like
- def ... | Implement the Python class `LinearRegression` described below.
Class description:
Linear regression for single variable or multi-variable.
Method signatures and docstrings:
- def __init__(self, x: array_like, y: array_like) -> None: :param x: array_like N-D array with (n-sample, n-feature) :param y: array_like
- def ... | 1c8d5fbf3676dc81e9f143e93ee2564359519b11 | <|skeleton|>
class LinearRegression:
"""Linear regression for single variable or multi-variable."""
def __init__(self, x: array_like, y: array_like) -> None:
""":param x: array_like N-D array with (n-sample, n-feature) :param y: array_like"""
<|body_0|>
def fit(self) -> LinearRegressionPar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinearRegression:
"""Linear regression for single variable or multi-variable."""
def __init__(self, x: array_like, y: array_like) -> None:
""":param x: array_like N-D array with (n-sample, n-feature) :param y: array_like"""
self.x = array_check(x)
self.y = array_check(y)
s... | the_stack_v2_python_sparse | statistics/regression.py | qliu0/PythonInAirSeaScience | train | 0 |
c3ae9ba7ad2c5c3460f2bb4e281835bf267f2ef8 | [
"np.random.seed(6589)\nn = 100\ndtypes = [np.float32, np.float64]\nfor dtype in dtypes:\n volatilities = np.exp(np.random.randn(n) / 2)\n forwards = np.exp(np.random.randn(n))\n strikes = forwards * (1 + (np.random.rand(n) - 0.5) * 0.2)\n expiries = np.exp(np.random.randn(n))\n prices = self.evaluate... | <|body_start_0|>
np.random.seed(6589)
n = 100
dtypes = [np.float32, np.float64]
for dtype in dtypes:
volatilities = np.exp(np.random.randn(n) / 2)
forwards = np.exp(np.random.randn(n))
strikes = forwards * (1 + (np.random.rand(n) - 0.5) * 0.2)
... | Tests for methods in implied_vol module. | ImpliedVolTest | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImpliedVolTest:
"""Tests for methods in implied_vol module."""
def test_implied_vol(self):
"""Basic test of the implied vol calculation."""
<|body_0|>
def test_validate(self):
"""Test the algorithm doesn't raise where it shouldn't."""
<|body_1|>
def ... | stack_v2_sparse_classes_36k_train_006455 | 4,993 | permissive | [
{
"docstring": "Basic test of the implied vol calculation.",
"name": "test_implied_vol",
"signature": "def test_implied_vol(self)"
},
{
"docstring": "Test the algorithm doesn't raise where it shouldn't.",
"name": "test_validate",
"signature": "def test_validate(self)"
},
{
"docst... | 3 | stack_v2_sparse_classes_30k_train_007992 | Implement the Python class `ImpliedVolTest` described below.
Class description:
Tests for methods in implied_vol module.
Method signatures and docstrings:
- def test_implied_vol(self): Basic test of the implied vol calculation.
- def test_validate(self): Test the algorithm doesn't raise where it shouldn't.
- def test... | Implement the Python class `ImpliedVolTest` described below.
Class description:
Tests for methods in implied_vol module.
Method signatures and docstrings:
- def test_implied_vol(self): Basic test of the implied vol calculation.
- def test_validate(self): Test the algorithm doesn't raise where it shouldn't.
- def test... | 0d3a2193c0f2d320b65e602cf01d7a617da484df | <|skeleton|>
class ImpliedVolTest:
"""Tests for methods in implied_vol module."""
def test_implied_vol(self):
"""Basic test of the implied vol calculation."""
<|body_0|>
def test_validate(self):
"""Test the algorithm doesn't raise where it shouldn't."""
<|body_1|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImpliedVolTest:
"""Tests for methods in implied_vol module."""
def test_implied_vol(self):
"""Basic test of the implied vol calculation."""
np.random.seed(6589)
n = 100
dtypes = [np.float32, np.float64]
for dtype in dtypes:
volatilities = np.exp(np.rand... | the_stack_v2_python_sparse | tf_quant_finance/black_scholes/implied_vol_lib_test.py | google/tf-quant-finance | train | 4,165 |
b91ee64dc7ee589c7c29bce5a64d50805a82521a | [
"if 'SF' in user_id:\n res = assoc_db.read_one_associate_by_query({'salesforce_id': user_id})\nelse:\n res = assoc_db.read_one_associate_by_query({'email': user_id})\nif res['swot']:\n for swot in res['swot']:\n swot['date_created'] = converter(swot['date_created'])\nelse:\n res['swot'] = [{'auth... | <|body_start_0|>
if 'SF' in user_id:
res = assoc_db.read_one_associate_by_query({'salesforce_id': user_id})
else:
res = assoc_db.read_one_associate_by_query({'email': user_id})
if res['swot']:
for swot in res['swot']:
swot['date_created'] = con... | Class for routing employee/user_id requests | EmployeeIdRoute | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmployeeIdRoute:
"""Class for routing employee/user_id requests"""
def get(self, user_id):
"""Retrieves associate information for a designated associate vai salesforce id or email"""
<|body_0|>
def post(self, user_id):
"""Adds a SWOT to a designated associate via... | stack_v2_sparse_classes_36k_train_006456 | 4,872 | no_license | [
{
"docstring": "Retrieves associate information for a designated associate vai salesforce id or email",
"name": "get",
"signature": "def get(self, user_id)"
},
{
"docstring": "Adds a SWOT to a designated associate via their salesforce id or email",
"name": "post",
"signature": "def post(... | 2 | stack_v2_sparse_classes_30k_val_000211 | Implement the Python class `EmployeeIdRoute` described below.
Class description:
Class for routing employee/user_id requests
Method signatures and docstrings:
- def get(self, user_id): Retrieves associate information for a designated associate vai salesforce id or email
- def post(self, user_id): Adds a SWOT to a des... | Implement the Python class `EmployeeIdRoute` described below.
Class description:
Class for routing employee/user_id requests
Method signatures and docstrings:
- def get(self, user_id): Retrieves associate information for a designated associate vai salesforce id or email
- def post(self, user_id): Adds a SWOT to a des... | d376039c1d08f573fde536978ffce0e44a05922c | <|skeleton|>
class EmployeeIdRoute:
"""Class for routing employee/user_id requests"""
def get(self, user_id):
"""Retrieves associate information for a designated associate vai salesforce id or email"""
<|body_0|>
def post(self, user_id):
"""Adds a SWOT to a designated associate via... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmployeeIdRoute:
"""Class for routing employee/user_id requests"""
def get(self, user_id):
"""Retrieves associate information for a designated associate vai salesforce id or email"""
if 'SF' in user_id:
res = assoc_db.read_one_associate_by_query({'salesforce_id': user_id})
... | the_stack_v2_python_sparse | src/router/employees.py | revaturelabs/csm-backend | train | 2 |
03edae5b99f73df1fc223201f5dc6c2e4b64d227 | [
"file_id = self.get_argument('file_id', default=None)\nchunk = self.get_argument('chunk', default=None)\nverify = self.get_argument('verify', default='').lower() == 'true'\nif file_id is None:\n raise ValueError('Cannot fetch a file or chunk without a file ID.')\nresponse = await self.client(Operation(operation_... | <|body_start_0|>
file_id = self.get_argument('file_id', default=None)
chunk = self.get_argument('chunk', default=None)
verify = self.get_argument('verify', default='').lower() == 'true'
if file_id is None:
raise ValueError('Cannot fetch a file or chunk without a file ID.')
... | FileChunkAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileChunkAPI:
async def get(self):
"""--- summary: Retrieve a File or FileChunk parameters: - name: file_id in: query required: true description: The ID of the file type: string - name: chunk in: query required: false description: The chunk number requested type: integer - name: verify i... | stack_v2_sparse_classes_36k_train_006457 | 8,203 | permissive | [
{
"docstring": "--- summary: Retrieve a File or FileChunk parameters: - name: file_id in: query required: true description: The ID of the file type: string - name: chunk in: query required: false description: The chunk number requested type: integer - name: verify in: query required: false description: Flag tha... | 3 | null | Implement the Python class `FileChunkAPI` described below.
Class description:
Implement the FileChunkAPI class.
Method signatures and docstrings:
- async def get(self): --- summary: Retrieve a File or FileChunk parameters: - name: file_id in: query required: true description: The ID of the file type: string - name: c... | Implement the Python class `FileChunkAPI` described below.
Class description:
Implement the FileChunkAPI class.
Method signatures and docstrings:
- async def get(self): --- summary: Retrieve a File or FileChunk parameters: - name: file_id in: query required: true description: The ID of the file type: string - name: c... | a5fd2dcc2444409e243d3fdaa43d86695e5cb142 | <|skeleton|>
class FileChunkAPI:
async def get(self):
"""--- summary: Retrieve a File or FileChunk parameters: - name: file_id in: query required: true description: The ID of the file type: string - name: chunk in: query required: false description: The chunk number requested type: integer - name: verify i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileChunkAPI:
async def get(self):
"""--- summary: Retrieve a File or FileChunk parameters: - name: file_id in: query required: true description: The ID of the file type: string - name: chunk in: query required: false description: The chunk number requested type: integer - name: verify in: query requi... | the_stack_v2_python_sparse | src/app/beer_garden/api/http/handlers/vbeta/chunk.py | beer-garden/beer-garden | train | 254 | |
4211e47e5d84f2f86018686a325dc62e4fb52e08 | [
"global DCHECKER\nself.groups = 0\nself.dictgroups = []\ncheckdict = CHECK_DICT_OBRACKET.search(istring)\nif checkdict:\n if not DCHECKER:\n import alt_hunspell\n DCHECKER = alt_hunspell.Hunspell()\n brcheck = OPEN_BRACKET.search(istring, 0)\n i = 0\n while brcheck:\n start = brchec... | <|body_start_0|>
global DCHECKER
self.groups = 0
self.dictgroups = []
checkdict = CHECK_DICT_OBRACKET.search(istring)
if checkdict:
if not DCHECKER:
import alt_hunspell
DCHECKER = alt_hunspell.Hunspell()
brcheck = OPEN_BRACK... | Matching part of P2P rule. | Condition | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Condition:
"""Matching part of P2P rule."""
def __init__(self, istring, flags):
"""Create an instance of P2P condition."""
<|body_0|>
def finditer(self, iline):
"""Return all possible matches of condition of given rule."""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_006458 | 17,033 | permissive | [
{
"docstring": "Create an instance of P2P condition.",
"name": "__init__",
"signature": "def __init__(self, istring, flags)"
},
{
"docstring": "Return all possible matches of condition of given rule.",
"name": "finditer",
"signature": "def finditer(self, iline)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007491 | Implement the Python class `Condition` described below.
Class description:
Matching part of P2P rule.
Method signatures and docstrings:
- def __init__(self, istring, flags): Create an instance of P2P condition.
- def finditer(self, iline): Return all possible matches of condition of given rule. | Implement the Python class `Condition` described below.
Class description:
Matching part of P2P rule.
Method signatures and docstrings:
- def __init__(self, istring, flags): Create an instance of P2P condition.
- def finditer(self, iline): Return all possible matches of condition of given rule.
<|skeleton|>
class Co... | ac645fb41260b86491b17fbc50e5ea3300dc28b7 | <|skeleton|>
class Condition:
"""Matching part of P2P rule."""
def __init__(self, istring, flags):
"""Create an instance of P2P condition."""
<|body_0|>
def finditer(self, iline):
"""Return all possible matches of condition of given rule."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Condition:
"""Matching part of P2P rule."""
def __init__(self, istring, flags):
"""Create an instance of P2P condition."""
global DCHECKER
self.groups = 0
self.dictgroups = []
checkdict = CHECK_DICT_OBRACKET.search(istring)
if checkdict:
if not ... | the_stack_v2_python_sparse | scripts/lib/python/ld/p2p.py | WladimirSidorenko/TextNormalization | train | 1 |
1c4e2fd34033973c51d13e82d5ea3f5609ce3716 | [
"try:\n return EnvironmentInstanceProduct.objects.get(pk=pk)\nexcept EnvironmentInstanceProduct.DoesNotExist:\n raise Http404",
"env_product = self.get_object(pk)\nserializer = EnvironmentInstanceProductSerializer(env_product)\nreturn Response(serializer.data)",
"env_product = self.get_object(pk)\nseriali... | <|body_start_0|>
try:
return EnvironmentInstanceProduct.objects.get(pk=pk)
except EnvironmentInstanceProduct.DoesNotExist:
raise Http404
<|end_body_0|>
<|body_start_1|>
env_product = self.get_object(pk)
serializer = EnvironmentInstanceProductSerializer(env_produc... | Retrieve, update or delete a EnvironmentInstanceProduct instance. | EnvironmentInstanceProductDetails | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnvironmentInstanceProductDetails:
"""Retrieve, update or delete a EnvironmentInstanceProduct instance."""
def get_object(self, pk):
"""Get the particular row from the table."""
<|body_0|>
def get(self, request, pk, format=None):
"""We are going to add the contac... | stack_v2_sparse_classes_36k_train_006459 | 15,222 | permissive | [
{
"docstring": "Get the particular row from the table.",
"name": "get_object",
"signature": "def get_object(self, pk)"
},
{
"docstring": "We are going to add the contact info content along with this pull request",
"name": "get",
"signature": "def get(self, request, pk, format=None)"
},... | 4 | stack_v2_sparse_classes_30k_train_009373 | Implement the Python class `EnvironmentInstanceProductDetails` described below.
Class description:
Retrieve, update or delete a EnvironmentInstanceProduct instance.
Method signatures and docstrings:
- def get_object(self, pk): Get the particular row from the table.
- def get(self, request, pk, format=None): We are go... | Implement the Python class `EnvironmentInstanceProductDetails` described below.
Class description:
Retrieve, update or delete a EnvironmentInstanceProduct instance.
Method signatures and docstrings:
- def get_object(self, pk): Get the particular row from the table.
- def get(self, request, pk, format=None): We are go... | b0635e72338e14dad24f1ee0329212cd60a3e83a | <|skeleton|>
class EnvironmentInstanceProductDetails:
"""Retrieve, update or delete a EnvironmentInstanceProduct instance."""
def get_object(self, pk):
"""Get the particular row from the table."""
<|body_0|>
def get(self, request, pk, format=None):
"""We are going to add the contac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnvironmentInstanceProductDetails:
"""Retrieve, update or delete a EnvironmentInstanceProduct instance."""
def get_object(self, pk):
"""Get the particular row from the table."""
try:
return EnvironmentInstanceProduct.objects.get(pk=pk)
except EnvironmentInstanceProduct... | the_stack_v2_python_sparse | environment/views.py | faisaltheparttimecoder/carelogBackend | train | 1 |
abf103845299e7eb8edd6df81b7b2244f466e5d9 | [
"tf.reset_default_graph()\noptim = tf.train.GradientDescentOptimizer(0.001)\nglobal_step = tf.train.get_or_create_global_step()\nsparse_optim = sparse_optimizers.SparseRigLOptimizer(optim, start_iter, end_iter, freq_iter, drop_fraction=drop_frac)\nx = tf.ones((1, n_inp))\ny = layers.masked_fully_connected(x, n_out,... | <|body_start_0|>
tf.reset_default_graph()
optim = tf.train.GradientDescentOptimizer(0.001)
global_step = tf.train.get_or_create_global_step()
sparse_optim = sparse_optimizers.SparseRigLOptimizer(optim, start_iter, end_iter, freq_iter, drop_fraction=drop_frac)
x = tf.ones((1, n_in... | SparseRigLOptimizerTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SparseRigLOptimizerTest:
def _setup_graph(self, n_inp, n_out, drop_frac, start_iter=1, end_iter=4, freq_iter=2):
"""Setups a trivial training procedure for sparse training."""
<|body_0|>
def testMaskedGradientCalculation(self, n_inp, n_out):
"""Checking whether maske... | stack_v2_sparse_classes_36k_train_006460 | 25,606 | permissive | [
{
"docstring": "Setups a trivial training procedure for sparse training.",
"name": "_setup_graph",
"signature": "def _setup_graph(self, n_inp, n_out, drop_frac, start_iter=1, end_iter=4, freq_iter=2)"
},
{
"docstring": "Checking whether masked_grad is calculated after apply_gradients.",
"nam... | 3 | null | Implement the Python class `SparseRigLOptimizerTest` described below.
Class description:
Implement the SparseRigLOptimizerTest class.
Method signatures and docstrings:
- def _setup_graph(self, n_inp, n_out, drop_frac, start_iter=1, end_iter=4, freq_iter=2): Setups a trivial training procedure for sparse training.
- d... | Implement the Python class `SparseRigLOptimizerTest` described below.
Class description:
Implement the SparseRigLOptimizerTest class.
Method signatures and docstrings:
- def _setup_graph(self, n_inp, n_out, drop_frac, start_iter=1, end_iter=4, freq_iter=2): Setups a trivial training procedure for sparse training.
- d... | d39fc7d46505cb3196cb1edeb32ed0b6dd44c0f9 | <|skeleton|>
class SparseRigLOptimizerTest:
def _setup_graph(self, n_inp, n_out, drop_frac, start_iter=1, end_iter=4, freq_iter=2):
"""Setups a trivial training procedure for sparse training."""
<|body_0|>
def testMaskedGradientCalculation(self, n_inp, n_out):
"""Checking whether maske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SparseRigLOptimizerTest:
def _setup_graph(self, n_inp, n_out, drop_frac, start_iter=1, end_iter=4, freq_iter=2):
"""Setups a trivial training procedure for sparse training."""
tf.reset_default_graph()
optim = tf.train.GradientDescentOptimizer(0.001)
global_step = tf.train.get_o... | the_stack_v2_python_sparse | rigl/sparse_optimizers_test.py | google-research/rigl | train | 324 | |
df878db7dd510848d81e27e3642e20ab691b3cc3 | [
"self.config = {}\nself.config['db'] = {}\nself.config['db']['host'] = 'web40'\nself.config['db']['port'] = 27017\nself.config['db']['db'] = 'd4dchallenge'\nself.config['db']['collection'] = 'traces'\nself.traces = self.__get_collection(self.config)",
"connection = Connection(config['db']['host'], config['db']['p... | <|body_start_0|>
self.config = {}
self.config['db'] = {}
self.config['db']['host'] = 'web40'
self.config['db']['port'] = 27017
self.config['db']['db'] = 'd4dchallenge'
self.config['db']['collection'] = 'traces'
self.traces = self.__get_collection(self.config)
<|en... | SpaceTemporalModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpaceTemporalModel:
def __init__(self):
"""Load and retieve collection pointer from MongoDB"""
<|body_0|>
def __get_collection(self, config):
"""Return collection from MongoDB with a specific configuration"""
<|body_1|>
def retieve_data_and_create_model(... | stack_v2_sparse_classes_36k_train_006461 | 5,480 | no_license | [
{
"docstring": "Load and retieve collection pointer from MongoDB",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Return collection from MongoDB with a specific configuration",
"name": "__get_collection",
"signature": "def __get_collection(self, config)"
},
... | 5 | stack_v2_sparse_classes_30k_train_006233 | Implement the Python class `SpaceTemporalModel` described below.
Class description:
Implement the SpaceTemporalModel class.
Method signatures and docstrings:
- def __init__(self): Load and retieve collection pointer from MongoDB
- def __get_collection(self, config): Return collection from MongoDB with a specific conf... | Implement the Python class `SpaceTemporalModel` described below.
Class description:
Implement the SpaceTemporalModel class.
Method signatures and docstrings:
- def __init__(self): Load and retieve collection pointer from MongoDB
- def __get_collection(self, config): Return collection from MongoDB with a specific conf... | 86ebaf8382327d4e982916fc3bf83b189ecdb138 | <|skeleton|>
class SpaceTemporalModel:
def __init__(self):
"""Load and retieve collection pointer from MongoDB"""
<|body_0|>
def __get_collection(self, config):
"""Return collection from MongoDB with a specific configuration"""
<|body_1|>
def retieve_data_and_create_model(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpaceTemporalModel:
def __init__(self):
"""Load and retieve collection pointer from MongoDB"""
self.config = {}
self.config['db'] = {}
self.config['db']['host'] = 'web40'
self.config['db']['port'] = 27017
self.config['db']['db'] = 'd4dchallenge'
self.con... | the_stack_v2_python_sparse | service/space_temporal.py | sjsnjnu/d4d-challenge | train | 0 | |
a60a9d1d7b4bed0bfd34ee413200b467037d3910 | [
"self.backoff = backoff\nself.random_jitter_range = random_jitter_range\nsuper(LinearRetry, self).__init__(retry_total=retry_total, retry_to_secondary=retry_to_secondary, **kwargs)",
"random_generator = random.Random()\nrandom_range_start = self.backoff - self.random_jitter_range if self.backoff > self.random_jit... | <|body_start_0|>
self.backoff = backoff
self.random_jitter_range = random_jitter_range
super(LinearRetry, self).__init__(retry_total=retry_total, retry_to_secondary=retry_to_secondary, **kwargs)
<|end_body_0|>
<|body_start_1|>
random_generator = random.Random()
random_range_star... | Linear retry. | LinearRetry | [
"MIT",
"LicenseRef-scancode-generic-cla",
"LGPL-2.1-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearRetry:
"""Linear retry."""
def __init__(self, backoff=15, retry_total=3, retry_to_secondary=False, random_jitter_range=3, **kwargs):
"""Constructs a Linear retry object. :param int backoff: The backoff interval, in seconds, between retries. :param int max_attempts: The maximum ... | stack_v2_sparse_classes_36k_train_006462 | 26,717 | permissive | [
{
"docstring": "Constructs a Linear retry object. :param int backoff: The backoff interval, in seconds, between retries. :param int max_attempts: The maximum number of retry attempts. :param bool retry_to_secondary: Whether the request should be retried to secondary, if able. This should only be enabled of RA-G... | 2 | stack_v2_sparse_classes_30k_train_002708 | Implement the Python class `LinearRetry` described below.
Class description:
Linear retry.
Method signatures and docstrings:
- def __init__(self, backoff=15, retry_total=3, retry_to_secondary=False, random_jitter_range=3, **kwargs): Constructs a Linear retry object. :param int backoff: The backoff interval, in second... | Implement the Python class `LinearRetry` described below.
Class description:
Linear retry.
Method signatures and docstrings:
- def __init__(self, backoff=15, retry_total=3, retry_to_secondary=False, random_jitter_range=3, **kwargs): Constructs a Linear retry object. :param int backoff: The backoff interval, in second... | c2ca191e736bb06bfbbbc9493e8325763ba990bb | <|skeleton|>
class LinearRetry:
"""Linear retry."""
def __init__(self, backoff=15, retry_total=3, retry_to_secondary=False, random_jitter_range=3, **kwargs):
"""Constructs a Linear retry object. :param int backoff: The backoff interval, in seconds, between retries. :param int max_attempts: The maximum ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinearRetry:
"""Linear retry."""
def __init__(self, backoff=15, retry_total=3, retry_to_secondary=False, random_jitter_range=3, **kwargs):
"""Constructs a Linear retry object. :param int backoff: The backoff interval, in seconds, between retries. :param int max_attempts: The maximum number of ret... | the_stack_v2_python_sparse | sdk/eventhub/azure-eventhub-checkpointstoreblob-aio/azure/eventhub/extensions/checkpointstoreblobaio/_vendor/storage/blob/_shared/policies.py | Azure/azure-sdk-for-python | train | 4,046 |
ceb8d0980c5ba00bd956b4737d89408705ef3e63 | [
"assert Q.shape == (4,), Q\nw, x, y, z = Q\nxx = x * x\nxy = x * y\nyy = y * y\nxz = x * z\nyz = y * z\nzz = z * z\nxw = x * w\nyw = y * w\nzw = z * w\nreturn np.array([[1 - 2 * (yy + zz), 2 * (xy + zw), 2 * (xz - yw)], [2 * (xy - zw), 1 - 2 * (xx + zz), 2 * (yz + xw)], [2 * (xz + yw), 2 * (yz - xw), 1 - 2 * (xx + ... | <|body_start_0|>
assert Q.shape == (4,), Q
w, x, y, z = Q
xx = x * x
xy = x * y
yy = y * y
xz = x * z
yz = y * z
zz = z * z
xw = x * w
yw = y * w
zw = z * w
return np.array([[1 - 2 * (yy + zz), 2 * (xy + zw), 2 * (xz - yw)],... | WXYZ | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WXYZ:
def to_rotation_matrix(Q: np.ndarray) -> np.ndarray:
"""See http://www.j3d.org/matrix_faq/matrfaq_latest.html#Q54 Note: the returned matrix is row-major."""
<|body_0|>
def from_rotation_matrix(R: np.ndarray) -> np.ndarray:
"""See http://www.j3d.org/matrix_faq/m... | stack_v2_sparse_classes_36k_train_006463 | 10,562 | no_license | [
{
"docstring": "See http://www.j3d.org/matrix_faq/matrfaq_latest.html#Q54 Note: the returned matrix is row-major.",
"name": "to_rotation_matrix",
"signature": "def to_rotation_matrix(Q: np.ndarray) -> np.ndarray"
},
{
"docstring": "See http://www.j3d.org/matrix_faq/matrfaq_latest.html#Q55 Note: ... | 2 | stack_v2_sparse_classes_30k_train_015316 | Implement the Python class `WXYZ` described below.
Class description:
Implement the WXYZ class.
Method signatures and docstrings:
- def to_rotation_matrix(Q: np.ndarray) -> np.ndarray: See http://www.j3d.org/matrix_faq/matrfaq_latest.html#Q54 Note: the returned matrix is row-major.
- def from_rotation_matrix(R: np.nd... | Implement the Python class `WXYZ` described below.
Class description:
Implement the WXYZ class.
Method signatures and docstrings:
- def to_rotation_matrix(Q: np.ndarray) -> np.ndarray: See http://www.j3d.org/matrix_faq/matrfaq_latest.html#Q54 Note: the returned matrix is row-major.
- def from_rotation_matrix(R: np.nd... | bac774e1f7b3131f559ee3ff1662836c424ebaa5 | <|skeleton|>
class WXYZ:
def to_rotation_matrix(Q: np.ndarray) -> np.ndarray:
"""See http://www.j3d.org/matrix_faq/matrfaq_latest.html#Q54 Note: the returned matrix is row-major."""
<|body_0|>
def from_rotation_matrix(R: np.ndarray) -> np.ndarray:
"""See http://www.j3d.org/matrix_faq/m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WXYZ:
def to_rotation_matrix(Q: np.ndarray) -> np.ndarray:
"""See http://www.j3d.org/matrix_faq/matrfaq_latest.html#Q54 Note: the returned matrix is row-major."""
assert Q.shape == (4,), Q
w, x, y, z = Q
xx = x * x
xy = x * y
yy = y * y
xz = x * z
... | the_stack_v2_python_sparse | src/ie/meshroomy.py | laurelkeys/ff | train | 1 | |
58483fd26ded2eef48506baf01f41c8d30f8086e | [
"super().__init__(env_spec)\nself.state_des = state_des\nself.limit_rad = 0.5236\nself.kp_servo = 14.0\nself.Kp, self.Kd = (None, None)\nself.init_param(kp, kd)",
"th_x, th_y, x, y, _, _, x_dot, y_dot = obs\nerr = to.tensor([self.state_des[0] - x, self.state_des[1] - y])\nerr_dot = to.tensor([0.0 - x_dot, 0.0 - y... | <|body_start_0|>
super().__init__(env_spec)
self.state_des = state_des
self.limit_rad = 0.5236
self.kp_servo = 14.0
self.Kp, self.Kd = (None, None)
self.init_param(kp, kd)
<|end_body_0|>
<|body_start_1|>
th_x, th_y, x, y, _, _, x_dot, y_dot = obs
err = to... | PD-controller for the Quanser Ball Balancer. The only but significant difference of this controller to the other PD controller is the clipping of the actions. .. note:: This class's desired state specification deviates from the Pyrado policies which interact with a `Task`. | QBallBalancerPDCtrl | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QBallBalancerPDCtrl:
"""PD-controller for the Quanser Ball Balancer. The only but significant difference of this controller to the other PD controller is the clipping of the actions. .. note:: This class's desired state specification deviates from the Pyrado policies which interact with a `Task`.... | stack_v2_sparse_classes_36k_train_006464 | 25,612 | permissive | [
{
"docstring": "Constructor :param env_spec: environment specification :param state_des: tensor of desired x and y ball position [m] :param kp: 2x2 tensor of constant controller feedback coefficients for error [V/m] :param kd: 2x2 tensor of constant controller feedback coefficients for error time derivative [Vs... | 4 | stack_v2_sparse_classes_30k_train_002467 | Implement the Python class `QBallBalancerPDCtrl` described below.
Class description:
PD-controller for the Quanser Ball Balancer. The only but significant difference of this controller to the other PD controller is the clipping of the actions. .. note:: This class's desired state specification deviates from the Pyrado... | Implement the Python class `QBallBalancerPDCtrl` described below.
Class description:
PD-controller for the Quanser Ball Balancer. The only but significant difference of this controller to the other PD controller is the clipping of the actions. .. note:: This class's desired state specification deviates from the Pyrado... | a6c982862e2ab39a9f65d1c09aa59d9a8b7ac6c5 | <|skeleton|>
class QBallBalancerPDCtrl:
"""PD-controller for the Quanser Ball Balancer. The only but significant difference of this controller to the other PD controller is the clipping of the actions. .. note:: This class's desired state specification deviates from the Pyrado policies which interact with a `Task`.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QBallBalancerPDCtrl:
"""PD-controller for the Quanser Ball Balancer. The only but significant difference of this controller to the other PD controller is the clipping of the actions. .. note:: This class's desired state specification deviates from the Pyrado policies which interact with a `Task`."""
def ... | the_stack_v2_python_sparse | Pyrado/pyrado/policies/environment_specific.py | jacarvalho/SimuRLacra | train | 0 |
da693becd45b726478b01c075df233acff71672f | [
"self.current_dir = os.getcwd()\nnow = datetime.now().strftime('%I%p_%m_%d_%Y')\ntest_name = self.__class__.__name__\nself.tempdir = '{}_{}'.format(test_name, now)\nif not os.path.isdir(self.tempdir):\n os.mkdir(self.tempdir)\nos.chdir(self.tempdir)\nopen('test.pdb', 'w').write(test_pdb_str)",
"params_phil = i... | <|body_start_0|>
self.current_dir = os.getcwd()
now = datetime.now().strftime('%I%p_%m_%d_%Y')
test_name = self.__class__.__name__
self.tempdir = '{}_{}'.format(test_name, now)
if not os.path.isdir(self.tempdir):
os.mkdir(self.tempdir)
os.chdir(self.tempdir)
... | TestPDBinterpretationNCSSearch | [
"BSD-3-Clause-LBNL",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestPDBinterpretationNCSSearch:
def setUp(self):
"""Create temporary folder for temp files produced during test"""
<|body_0|>
def test_calling_pdb_interpretation(self):
"""Make sure can create NCS object and change search parameters"""
<|body_1|>
def tea... | stack_v2_sparse_classes_36k_train_006465 | 6,330 | permissive | [
{
"docstring": "Create temporary folder for temp files produced during test",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Make sure can create NCS object and change search parameters",
"name": "test_calling_pdb_interpretation",
"signature": "def test_calling_pdb_in... | 3 | stack_v2_sparse_classes_30k_train_018492 | Implement the Python class `TestPDBinterpretationNCSSearch` described below.
Class description:
Implement the TestPDBinterpretationNCSSearch class.
Method signatures and docstrings:
- def setUp(self): Create temporary folder for temp files produced during test
- def test_calling_pdb_interpretation(self): Make sure ca... | Implement the Python class `TestPDBinterpretationNCSSearch` described below.
Class description:
Implement the TestPDBinterpretationNCSSearch class.
Method signatures and docstrings:
- def setUp(self): Create temporary folder for temp files produced during test
- def test_calling_pdb_interpretation(self): Make sure ca... | 77d66c719b5746f37af51ad593e2941ed6fbba17 | <|skeleton|>
class TestPDBinterpretationNCSSearch:
def setUp(self):
"""Create temporary folder for temp files produced during test"""
<|body_0|>
def test_calling_pdb_interpretation(self):
"""Make sure can create NCS object and change search parameters"""
<|body_1|>
def tea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestPDBinterpretationNCSSearch:
def setUp(self):
"""Create temporary folder for temp files produced during test"""
self.current_dir = os.getcwd()
now = datetime.now().strftime('%I%p_%m_%d_%Y')
test_name = self.__class__.__name__
self.tempdir = '{}_{}'.format(test_name, ... | the_stack_v2_python_sparse | modules/cctbx_project/mmtbx/monomer_library/tst_pdb_interpretation_ncs_processing.py | jorgediazjr/dials-dev20191018 | train | 0 | |
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_36k_train_006466 | 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 | stack_v2_sparse_classes_30k_val_000803 | 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_36k | 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 | |
7fa56bbc0d870d32bf47bd7f6c884a9273d26b8a | [
"super(LimitConsumer, self).__init__(columns=columns, consumer=consumer)\nself.limit = limit\nself.count = 0",
"if self.count < self.limit:\n self.count += 1\n return row\nelse:\n raise StopIteration()"
] | <|body_start_0|>
super(LimitConsumer, self).__init__(columns=columns, consumer=consumer)
self.limit = limit
self.count = 0
<|end_body_0|>
<|body_start_1|>
if self.count < self.limit:
self.count += 1
return row
else:
raise StopIteration()
<|end... | Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached. | LimitConsumer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LimitConsumer:
"""Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached."""
def __init__(self, columns: DatasetSchema, limit: int, consumer: Optional[StreamConsumer]=None):
"""Initi... | stack_v2_sparse_classes_36k_train_006467 | 4,564 | permissive | [
{
"docstring": "Initialize the row limit and the downstream consumer. Parameters ---------- columns: list of string Names of columns for the rows that the consumer will receive. limit: int Maximum number of rows that are passed on to the downstream consumer. consumer: openclean.data.stream.base.StreamConsumer, ... | 2 | stack_v2_sparse_classes_30k_train_016555 | Implement the Python class `LimitConsumer` described below.
Class description:
Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached.
Method signatures and docstrings:
- def __init__(self, columns: DatasetSchema, li... | Implement the Python class `LimitConsumer` described below.
Class description:
Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached.
Method signatures and docstrings:
- def __init__(self, columns: DatasetSchema, li... | e3d0e04f90468c49f29ca53edc2feb12465c24d5 | <|skeleton|>
class LimitConsumer:
"""Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached."""
def __init__(self, columns: DatasetSchema, limit: int, consumer: Optional[StreamConsumer]=None):
"""Initi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LimitConsumer:
"""Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached."""
def __init__(self, columns: DatasetSchema, limit: int, consumer: Optional[StreamConsumer]=None):
"""Initialize the row... | the_stack_v2_python_sparse | openclean/operator/transform/limit.py | Denisfench/openclean-core | train | 0 |
b9888866f41fdf12510ca8e7a4c80074023b3009 | [
"super().__init__(model_type, task, **kwargs)\nself.nb_classes = None\nself.set_task(task)",
"if type(task) != thelper.tasks.Classification:\n raise AssertionError(\"task passed to ExternalClassifModule should be 'thelper.tasks.Classification'\")\nself.nb_classes = len(self.task.class_names)\nimport torchvisio... | <|body_start_0|>
super().__init__(model_type, task, **kwargs)
self.nb_classes = None
self.set_task(task)
<|end_body_0|>
<|body_start_1|>
if type(task) != thelper.tasks.Classification:
raise AssertionError("task passed to ExternalClassifModule should be 'thelper.tasks.Classif... | External model interface specialization for classification tasks. This interface will try to 'rewire' the last fully connected layer of the models it instantiates to match the number of classes to predict defined in the task object. .. seealso:: | :class:`thelper.nn.utils.Module` | :class:`thelper.nn.utils.ExternalModu... | ExternalClassifModule | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExternalClassifModule:
"""External model interface specialization for classification tasks. This interface will try to 'rewire' the last fully connected layer of the models it instantiates to match the number of classes to predict defined in the task object. .. seealso:: | :class:`thelper.nn.util... | stack_v2_sparse_classes_36k_train_006468 | 22,198 | permissive | [
{
"docstring": "Receives a task object to hold internally for model specialization, and tries to rewire the last 'fc' layer.",
"name": "__init__",
"signature": "def __init__(self, model_type, task, **kwargs)"
},
{
"docstring": "Rewires the last fully connected layer of the wrapped network to fit... | 2 | null | Implement the Python class `ExternalClassifModule` described below.
Class description:
External model interface specialization for classification tasks. This interface will try to 'rewire' the last fully connected layer of the models it instantiates to match the number of classes to predict defined in the task object.... | Implement the Python class `ExternalClassifModule` described below.
Class description:
External model interface specialization for classification tasks. This interface will try to 'rewire' the last fully connected layer of the models it instantiates to match the number of classes to predict defined in the task object.... | d91c50d4e3755c4779ef882967519aaa9d863ff4 | <|skeleton|>
class ExternalClassifModule:
"""External model interface specialization for classification tasks. This interface will try to 'rewire' the last fully connected layer of the models it instantiates to match the number of classes to predict defined in the task object. .. seealso:: | :class:`thelper.nn.util... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExternalClassifModule:
"""External model interface specialization for classification tasks. This interface will try to 'rewire' the last fully connected layer of the models it instantiates to match the number of classes to predict defined in the task object. .. seealso:: | :class:`thelper.nn.utils.Module` | :... | the_stack_v2_python_sparse | thelper/nn/utils.py | plstcharles/thelper | train | 19 |
4b8ddb08bbed17e2a90d22dd97820c76448f25ca | [
"if n == 0 or n == 1:\n return n\nsum = 0\nfor i in range(1, n + 1):\n sum += self.numTrees(i - 1) + self.numTrees(n - i)\nreturn sum",
"if n == 0 or n == 1:\n return 1\nsum = 0\nfor i in range(1, n + 1):\n sum += self.numTrees(i - 1) * self.numTrees(n - i)\nreturn sum",
"if n in self.result:\n r... | <|body_start_0|>
if n == 0 or n == 1:
return n
sum = 0
for i in range(1, n + 1):
sum += self.numTrees(i - 1) + self.numTrees(n - i)
return sum
<|end_body_0|>
<|body_start_1|>
if n == 0 or n == 1:
return 1
sum = 0
for i in range... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numTrees(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def numTrees(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def numTrees(self, n):
""":type n: int :rtype: int"""
<|body_2|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_006469 | 909 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "numTrees",
"signature": "def numTrees(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "numTrees",
"signature": "def numTrees(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "numTrees",
"si... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numTrees(self, n): :type n: int :rtype: int
- def numTrees(self, n): :type n: int :rtype: int
- def numTrees(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numTrees(self, n): :type n: int :rtype: int
- def numTrees(self, n): :type n: int :rtype: int
- def numTrees(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
... | d953abe2c9680f636563e76287d2f907e90ced63 | <|skeleton|>
class Solution:
def numTrees(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def numTrees(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def numTrees(self, n):
""":type n: int :rtype: int"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numTrees(self, n):
""":type n: int :rtype: int"""
if n == 0 or n == 1:
return n
sum = 0
for i in range(1, n + 1):
sum += self.numTrees(i - 1) + self.numTrees(n - i)
return sum
def numTrees(self, n):
""":type n: int :rty... | the_stack_v2_python_sparse | Python_leetcode/96_unique_binary_search_tress.py | xiangcao/Leetcode | train | 0 | |
10516341a745c5ee11067a8e5b94ac40e3571304 | [
"self.logger = AntiVirusLogger(__name__, debug=debug)\nif config_path is not None:\n self._CONFIG_PATH = config_path\nelse:\n self.logger.log('Configuration file path not found.', logtype='error')\n sys.exit(0)\nif file_list:\n self.file_list = file_list\nelse:\n self.file_list = []\nself.hash_scanne... | <|body_start_0|>
self.logger = AntiVirusLogger(__name__, debug=debug)
if config_path is not None:
self._CONFIG_PATH = config_path
else:
self.logger.log('Configuration file path not found.', logtype='error')
sys.exit(0)
if file_list:
self.fi... | ScannerEngine class. | ScannerEngine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScannerEngine:
"""ScannerEngine class."""
def __init__(self, debug=False, config_path=None, vt_api_key=None, file_list=None):
"""Initialize ScannerEngine. Args: debug (bool): Log on terminal or not config_path (str): Configuration JSON file path vt_api_key (str): VirusTotal API Key f... | stack_v2_sparse_classes_36k_train_006470 | 4,932 | permissive | [
{
"docstring": "Initialize ScannerEngine. Args: debug (bool): Log on terminal or not config_path (str): Configuration JSON file path vt_api_key (str): VirusTotal API Key file_list (list): List of files to scan Raises: None Returns: None",
"name": "__init__",
"signature": "def __init__(self, debug=False,... | 2 | stack_v2_sparse_classes_30k_train_005500 | Implement the Python class `ScannerEngine` described below.
Class description:
ScannerEngine class.
Method signatures and docstrings:
- def __init__(self, debug=False, config_path=None, vt_api_key=None, file_list=None): Initialize ScannerEngine. Args: debug (bool): Log on terminal or not config_path (str): Configurat... | Implement the Python class `ScannerEngine` described below.
Class description:
ScannerEngine class.
Method signatures and docstrings:
- def __init__(self, debug=False, config_path=None, vt_api_key=None, file_list=None): Initialize ScannerEngine. Args: debug (bool): Log on terminal or not config_path (str): Configurat... | 43dec187e5848b9ced8a6b4957b6e9028d4d43cd | <|skeleton|>
class ScannerEngine:
"""ScannerEngine class."""
def __init__(self, debug=False, config_path=None, vt_api_key=None, file_list=None):
"""Initialize ScannerEngine. Args: debug (bool): Log on terminal or not config_path (str): Configuration JSON file path vt_api_key (str): VirusTotal API Key f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScannerEngine:
"""ScannerEngine class."""
def __init__(self, debug=False, config_path=None, vt_api_key=None, file_list=None):
"""Initialize ScannerEngine. Args: debug (bool): Log on terminal or not config_path (str): Configuration JSON file path vt_api_key (str): VirusTotal API Key file_list (lis... | the_stack_v2_python_sparse | securetea/lib/antivirus/scanner/scanner_engine.py | rejahrehim/SecureTea-Project | train | 1 |
09664f8a4cce173651142202ebfab6d36a157a55 | [
"encrypted_data = [ord(i) for i in data]\nencrypted_data = [str(i) + ' ' for i in encrypted_data]\nencrypted_data = ''.join(encrypted_data)\nprint(f'Writing encrypted {data} as {encrypted_data}')\nsuper().write(encrypted_data)\nprint(f'Finished writing encrypted data {encrypted_data}')",
"print('reading encrypte... | <|body_start_0|>
encrypted_data = [ord(i) for i in data]
encrypted_data = [str(i) + ' ' for i in encrypted_data]
encrypted_data = ''.join(encrypted_data)
print(f'Writing encrypted {data} as {encrypted_data}')
super().write(encrypted_data)
print(f'Finished writing encrypt... | This is a decorator (read: wrapper) that adds an encryption/decryption behaviour to a datasource. This decorator can wrap around a concrete DataSource (like FileDataSource) or it can also wrap around another Decorator. The encryption converts each letter to its ASCII code, while the decryption algorithm does the same. | EncryptedDataSourceDecorator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncryptedDataSourceDecorator:
"""This is a decorator (read: wrapper) that adds an encryption/decryption behaviour to a datasource. This decorator can wrap around a concrete DataSource (like FileDataSource) or it can also wrap around another Decorator. The encryption converts each letter to its AS... | stack_v2_sparse_classes_36k_train_006471 | 6,195 | no_license | [
{
"docstring": "Encrypts the given data and calls the write function of the DataSource that is being wrapped around. :param data: a string :return: None",
"name": "write",
"signature": "def write(self, data)"
},
{
"docstring": "Reads data from a data source and decrypts it to a string value. :pr... | 2 | stack_v2_sparse_classes_30k_train_010158 | Implement the Python class `EncryptedDataSourceDecorator` described below.
Class description:
This is a decorator (read: wrapper) that adds an encryption/decryption behaviour to a datasource. This decorator can wrap around a concrete DataSource (like FileDataSource) or it can also wrap around another Decorator. The en... | Implement the Python class `EncryptedDataSourceDecorator` described below.
Class description:
This is a decorator (read: wrapper) that adds an encryption/decryption behaviour to a datasource. This decorator can wrap around a concrete DataSource (like FileDataSource) or it can also wrap around another Decorator. The en... | 68ad3a22646c5433e395fbee2c1fbb972b805c09 | <|skeleton|>
class EncryptedDataSourceDecorator:
"""This is a decorator (read: wrapper) that adds an encryption/decryption behaviour to a datasource. This decorator can wrap around a concrete DataSource (like FileDataSource) or it can also wrap around another Decorator. The encryption converts each letter to its AS... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncryptedDataSourceDecorator:
"""This is a decorator (read: wrapper) that adds an encryption/decryption behaviour to a datasource. This decorator can wrap around a concrete DataSource (like FileDataSource) or it can also wrap around another Decorator. The encryption converts each letter to its ASCII code, whi... | the_stack_v2_python_sparse | Lectures/1028/decorator_example.py | usop7/Python_OOP_Projects | train | 0 |
0f94febad3196146faaf287bf8870b439dd4f3b5 | [
"print('In bl | User | create User method')\ntry:\n is_user_exists = FacadeAdmin.is_exist_by_login(entity['login'])\nexcept Exception as e:\n raise ServiceException('ADMIN_USER_DATABASE_QUERY_FAIL', 'Fail to verify if the user already exist.', str(e))\nif is_user_exists:\n raise ServiceException('ADMIN_USE... | <|body_start_0|>
print('In bl | User | create User method')
try:
is_user_exists = FacadeAdmin.is_exist_by_login(entity['login'])
except Exception as e:
raise ServiceException('ADMIN_USER_DATABASE_QUERY_FAIL', 'Fail to verify if the user already exist.', str(e))
if... | Allow user management systems | Admin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Admin:
"""Allow user management systems"""
def create_user(entity):
"""Create a new admin user :param entity: A Entity object with required values email: The email associated to this user [String, Required] password: The password associated to this user [String, Required] email: The ... | stack_v2_sparse_classes_36k_train_006472 | 5,356 | no_license | [
{
"docstring": "Create a new admin user :param entity: A Entity object with required values email: The email associated to this user [String, Required] password: The password associated to this user [String, Required] email: The email associated to this user [String, Required] firstname: The first name of the u... | 3 | stack_v2_sparse_classes_30k_train_016842 | Implement the Python class `Admin` described below.
Class description:
Allow user management systems
Method signatures and docstrings:
- def create_user(entity): Create a new admin user :param entity: A Entity object with required values email: The email associated to this user [String, Required] password: The passwo... | Implement the Python class `Admin` described below.
Class description:
Allow user management systems
Method signatures and docstrings:
- def create_user(entity): Create a new admin user :param entity: A Entity object with required values email: The email associated to this user [String, Required] password: The passwo... | 8dd3118eab24ee3992bc345573f4bb427930b30c | <|skeleton|>
class Admin:
"""Allow user management systems"""
def create_user(entity):
"""Create a new admin user :param entity: A Entity object with required values email: The email associated to this user [String, Required] password: The password associated to this user [String, Required] email: The ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Admin:
"""Allow user management systems"""
def create_user(entity):
"""Create a new admin user :param entity: A Entity object with required values email: The email associated to this user [String, Required] password: The password associated to this user [String, Required] email: The email associa... | the_stack_v2_python_sparse | admin/bl/admin_user.py | amityadav17/catalog | train | 0 |
e3716ba33ee1433ca3e9da1c588c71cc54fba45c | [
"serializer = self.login_serializer_class(data=request.data)\nif serializer.is_valid():\n return self.__login_user(serializer.data)\nelse:\n return self.json_failed_response(errors=serializer.errors)",
"try:\n user = authenticate(username=data[EMAIL], password=data[PASSWORD])\n return self.json_succes... | <|body_start_0|>
serializer = self.login_serializer_class(data=request.data)
if serializer.is_valid():
return self.__login_user(serializer.data)
else:
return self.json_failed_response(errors=serializer.errors)
<|end_body_0|>
<|body_start_1|>
try:
user... | View for login_service user | LoginView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginView:
"""View for login_service user"""
def post(self, request: Request, *args, **kwargs) -> Response:
"""request params: - email - password :return json response http response codes: 200 - ok, login_service success 400 - login_service failed - view errors in errors key keys: su... | stack_v2_sparse_classes_36k_train_006473 | 1,914 | no_license | [
{
"docstring": "request params: - email - password :return json response http response codes: 200 - ok, login_service success 400 - login_service failed - view errors in errors key keys: success - true if login_service was success and false otherwise errors - json of login_service errors if success if false tok... | 2 | stack_v2_sparse_classes_30k_train_000797 | Implement the Python class `LoginView` described below.
Class description:
View for login_service user
Method signatures and docstrings:
- def post(self, request: Request, *args, **kwargs) -> Response: request params: - email - password :return json response http response codes: 200 - ok, login_service success 400 - ... | Implement the Python class `LoginView` described below.
Class description:
View for login_service user
Method signatures and docstrings:
- def post(self, request: Request, *args, **kwargs) -> Response: request params: - email - password :return json response http response codes: 200 - ok, login_service success 400 - ... | bab909324aa2e4c1c8fff72093d3fcf44aaf4963 | <|skeleton|>
class LoginView:
"""View for login_service user"""
def post(self, request: Request, *args, **kwargs) -> Response:
"""request params: - email - password :return json response http response codes: 200 - ok, login_service success 400 - login_service failed - view errors in errors key keys: su... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginView:
"""View for login_service user"""
def post(self, request: Request, *args, **kwargs) -> Response:
"""request params: - email - password :return json response http response codes: 200 - ok, login_service success 400 - login_service failed - view errors in errors key keys: success - true ... | the_stack_v2_python_sparse | crm/views/login/login_view.py | vovapasko/crm | train | 0 |
67b8c381ab3e85c8c39229f626375b11d4acdfe2 | [
"super(MultiboxLoss, self).__init__()\nself.iou_threshold = iou_threshold\nself.neg_pos_ratio = neg_pos_ratio\nself.center_variance = center_variance\nself.size_variance = size_variance\nself.priors = priors\nself.priors",
"num_classes = confidence.size(2)\nwith torch.no_grad():\n loss = -F.log_softmax(confide... | <|body_start_0|>
super(MultiboxLoss, self).__init__()
self.iou_threshold = iou_threshold
self.neg_pos_ratio = neg_pos_ratio
self.center_variance = center_variance
self.size_variance = size_variance
self.priors = priors
self.priors
<|end_body_0|>
<|body_start_1|>
... | MultiboxLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiboxLoss:
def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device):
"""Implement SSD Multibox Loss. Basically, Multibox loss combines classification loss and Smooth L1 regression loss."""
<|body_0|>
def forward(self, confidence, pr... | stack_v2_sparse_classes_36k_train_006474 | 33,668 | no_license | [
{
"docstring": "Implement SSD Multibox Loss. Basically, Multibox loss combines classification loss and Smooth L1 regression loss.",
"name": "__init__",
"signature": "def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device)"
},
{
"docstring": "Compute class... | 2 | stack_v2_sparse_classes_30k_train_003736 | Implement the Python class `MultiboxLoss` described below.
Class description:
Implement the MultiboxLoss class.
Method signatures and docstrings:
- def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device): Implement SSD Multibox Loss. Basically, Multibox loss combines classific... | Implement the Python class `MultiboxLoss` described below.
Class description:
Implement the MultiboxLoss class.
Method signatures and docstrings:
- def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device): Implement SSD Multibox Loss. Basically, Multibox loss combines classific... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class MultiboxLoss:
def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device):
"""Implement SSD Multibox Loss. Basically, Multibox loss combines classification loss and Smooth L1 regression loss."""
<|body_0|>
def forward(self, confidence, pr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiboxLoss:
def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device):
"""Implement SSD Multibox Loss. Basically, Multibox loss combines classification loss and Smooth L1 regression loss."""
super(MultiboxLoss, self).__init__()
self.iou_threshol... | the_stack_v2_python_sparse | generated/test_qfgaohao_pytorch_ssd.py | jansel/pytorch-jit-paritybench | train | 35 | |
1b47dde160bbb90b746c4f017de069f0a0251a0b | [
"len1, len2 = (len(nums1), len(nums2))\nnums3 = []\ni, j, k = (0, 0, 0)\nwhile i < len1 and j < len2:\n if nums1[i] <= nums2[j]:\n nums3.append(nums1[i])\n i += 1\n else:\n nums3.append(nums2[j])\n j += 1\nif i < len1:\n nums3.extend(nums1[i:])\nif j < len2:\n nums3.extend(nu... | <|body_start_0|>
len1, len2 = (len(nums1), len(nums2))
nums3 = []
i, j, k = (0, 0, 0)
while i < len1 and j < len2:
if nums1[i] <= nums2[j]:
nums3.append(nums1[i])
i += 1
else:
nums3.append(nums2[j])
j... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
<|body_0|>
def find_median_sorted_arrays(self, nums1, nums2):
"""bin-search :type nums1: List[int] :type nums2: List[int] :rtype: float"""
... | stack_v2_sparse_classes_36k_train_006475 | 3,158 | no_license | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: float",
"name": "findMedianSortedArrays",
"signature": "def findMedianSortedArrays(self, nums1, nums2)"
},
{
"docstring": "bin-search :type nums1: List[int] :type nums2: List[int] :rtype: float",
"name": "find_median_sorte... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMedianSortedArrays(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: float
- def find_median_sorted_arrays(self, nums1, nums2): bin-search :type ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMedianSortedArrays(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: float
- def find_median_sorted_arrays(self, nums1, nums2): bin-search :type ... | 215d513b3564a7a76db3d2b29e4acc341a68e8ee | <|skeleton|>
class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
<|body_0|>
def find_median_sorted_arrays(self, nums1, nums2):
"""bin-search :type nums1: List[int] :type nums2: List[int] :rtype: float"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
len1, len2 = (len(nums1), len(nums2))
nums3 = []
i, j, k = (0, 0, 0)
while i < len1 and j < len2:
if nums1[i] <= nums2[j]:
... | the_stack_v2_python_sparse | python/bin-search/median-of-two-sorted.py | euxuoh/leetcode | train | 0 | |
41cf2a8a364fe9efc69f720ea53eee1bcea41def | [
"entries = self.model_cls.published.none()\nif self.request.GET:\n self.pattern = self.request.GET.get('q', '')\n if len(self.pattern) < 3:\n self.error = _('The pattern is too short')\n else:\n query_parsed = QUERY.parseString(self.pattern)\n entries = self.model_cls.published.filter(... | <|body_start_0|>
entries = self.model_cls.published.none()
if self.request.GET:
self.pattern = self.request.GET.get('q', '')
if len(self.pattern) < 3:
self.error = _('The pattern is too short')
else:
query_parsed = QUERY.parseString(sel... | Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern. | EntrySearchMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntrySearchMixin:
"""Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern."""
def get_queryset(self):
"""Overridde the ... | stack_v2_sparse_classes_36k_train_006476 | 3,025 | no_license | [
{
"docstring": "Overridde the get_queryset method to do some validations and build the search queryset.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Add error and pattern in context.",
"name": "get_context_data",
"signature": "def get_context_data(se... | 2 | stack_v2_sparse_classes_30k_train_019447 | Implement the Python class `EntrySearchMixin` described below.
Class description:
Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern.
Method signatures... | Implement the Python class `EntrySearchMixin` described below.
Class description:
Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern.
Method signatures... | 80e5a36154d1e2ffdc08c7f0563e8e887efb017d | <|skeleton|>
class EntrySearchMixin:
"""Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern."""
def get_queryset(self):
"""Overridde the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EntrySearchMixin:
"""Mixin providing the behavior of the entry search view, by returning in the context the pattern searched, the error if something wrong has happened and finally the the queryset of published entries matching the pattern."""
def get_queryset(self):
"""Overridde the get_queryset ... | the_stack_v2_python_sparse | apps/mp_blog/views/mixins.py | ivansons/mp_cms | train | 0 |
74bce0dbec2c1a92c40a962f3a099097be735c96 | [
"super().__init__()\nself.input_size = input_size\nself.d_model = d_model\nif input_size != d_model:\n self.proj = nn.Linear(input_size, d_model)\nlayer = TransformerEncoderLayer(d_model, nhead, dim_feedforward, dropout)\nself.layers = nn.ModuleList([copy.deepcopy(layer) for _ in range(num_layers)])\nself.num_la... | <|body_start_0|>
super().__init__()
self.input_size = input_size
self.d_model = d_model
if input_size != d_model:
self.proj = nn.Linear(input_size, d_model)
layer = TransformerEncoderLayer(d_model, nhead, dim_feedforward, dropout)
self.layers = nn.ModuleList([... | TransformerEncoder is a stack of N encoder layers. | TransformerEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerEncoder:
"""TransformerEncoder is a stack of N encoder layers."""
def __init__(self, input_size: int=512, d_model: int=512, nhead: int=8, num_layers: int=6, dim_feedforward: int=2048, dropout: float=0.1) -> None:
"""Initialize the TransformerEncoder. Parameters --------- i... | stack_v2_sparse_classes_36k_train_006477 | 20,460 | permissive | [
{
"docstring": "Initialize the TransformerEncoder. Parameters --------- input_size : int The embedding dimension of the model. If different from d_model, a linear projection layer is added. d_model : int the number of expected features in encoder/decoder inputs. Default ``512``. nhead : int, optional the number... | 3 | stack_v2_sparse_classes_30k_train_007371 | Implement the Python class `TransformerEncoder` described below.
Class description:
TransformerEncoder is a stack of N encoder layers.
Method signatures and docstrings:
- def __init__(self, input_size: int=512, d_model: int=512, nhead: int=8, num_layers: int=6, dim_feedforward: int=2048, dropout: float=0.1) -> None: ... | Implement the Python class `TransformerEncoder` described below.
Class description:
TransformerEncoder is a stack of N encoder layers.
Method signatures and docstrings:
- def __init__(self, input_size: int=512, d_model: int=512, nhead: int=8, num_layers: int=6, dim_feedforward: int=2048, dropout: float=0.1) -> None: ... | 0dc2f5b2b286694defe8abf450fe5be9ae12c097 | <|skeleton|>
class TransformerEncoder:
"""TransformerEncoder is a stack of N encoder layers."""
def __init__(self, input_size: int=512, d_model: int=512, nhead: int=8, num_layers: int=6, dim_feedforward: int=2048, dropout: float=0.1) -> None:
"""Initialize the TransformerEncoder. Parameters --------- i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransformerEncoder:
"""TransformerEncoder is a stack of N encoder layers."""
def __init__(self, input_size: int=512, d_model: int=512, nhead: int=8, num_layers: int=6, dim_feedforward: int=2048, dropout: float=0.1) -> None:
"""Initialize the TransformerEncoder. Parameters --------- input_size : i... | the_stack_v2_python_sparse | flambe/nn/transformer.py | cle-ros/flambe | train | 1 |
e068b101bd9b0e305d987c95d480733fa1c628f3 | [
"url = 'https://raw.githubusercontent.com/elhenrico/covid19-Brazil-timeseries/master/confirmed-cases.csv'\nlogger.debug('Fetching Brazil province-level confirmed cases from BRA_MSHM')\nreturn pd.read_csv(url)",
"url = 'https://raw.githubusercontent.com/elhenrico/covid19-Brazil-timeseries/master/deaths.csv'\nlogge... | <|body_start_0|>
url = 'https://raw.githubusercontent.com/elhenrico/covid19-Brazil-timeseries/master/confirmed-cases.csv'
logger.debug('Fetching Brazil province-level confirmed cases from BRA_MSHM')
return pd.read_csv(url)
<|end_body_0|>
<|body_start_1|>
url = 'https://raw.githubusercon... | BRA_MSHMFetcher | [
"Apache-2.0",
"CC-BY-NC-ND-4.0",
"CC-BY-NC-4.0",
"CC0-1.0",
"CC-BY-SA-3.0",
"LicenseRef-scancode-unknown-license-reference",
"Unlicense",
"GPL-3.0-only",
"LicenseRef-scancode-proprietary-license",
"CC-BY-4.0",
"CC-BY-NC-SA-4.0",
"LicenseRef-scancode-public-domain",
"OGL-UK-3.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BRA_MSHMFetcher:
def province_confirmed_fetch(self):
"""This url mainly provide cumulative data of confirmed cases on the province-level."""
<|body_0|>
def province_dead_fetch(self):
"""This url mainly provide cumulative data of death data on the province-level."""
... | stack_v2_sparse_classes_36k_train_006478 | 5,057 | permissive | [
{
"docstring": "This url mainly provide cumulative data of confirmed cases on the province-level.",
"name": "province_confirmed_fetch",
"signature": "def province_confirmed_fetch(self)"
},
{
"docstring": "This url mainly provide cumulative data of death data on the province-level.",
"name": ... | 3 | stack_v2_sparse_classes_30k_train_013790 | Implement the Python class `BRA_MSHMFetcher` described below.
Class description:
Implement the BRA_MSHMFetcher class.
Method signatures and docstrings:
- def province_confirmed_fetch(self): This url mainly provide cumulative data of confirmed cases on the province-level.
- def province_dead_fetch(self): This url main... | Implement the Python class `BRA_MSHMFetcher` described below.
Class description:
Implement the BRA_MSHMFetcher class.
Method signatures and docstrings:
- def province_confirmed_fetch(self): This url mainly provide cumulative data of confirmed cases on the province-level.
- def province_dead_fetch(self): This url main... | aecbea09d684201f122fba931f764e8b88a82fe7 | <|skeleton|>
class BRA_MSHMFetcher:
def province_confirmed_fetch(self):
"""This url mainly provide cumulative data of confirmed cases on the province-level."""
<|body_0|>
def province_dead_fetch(self):
"""This url mainly provide cumulative data of death data on the province-level."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BRA_MSHMFetcher:
def province_confirmed_fetch(self):
"""This url mainly provide cumulative data of confirmed cases on the province-level."""
url = 'https://raw.githubusercontent.com/elhenrico/covid19-Brazil-timeseries/master/confirmed-cases.csv'
logger.debug('Fetching Brazil province-l... | the_stack_v2_python_sparse | src/plugins/BRA_MSHM/fetcher.py | covid19db/fetchers-python | train | 4 | |
f0f3bdc3d9e98670d652e37d67ec6a640cdde081 | [
"correlationIterable = self._mergeCorrelationIterable(correlationIterable)\nif self._maximumValueCountThreshold is not None:\n correlationIterable = self._removeNodesWithTooManyValues(correlationIterable, self._maximumValueCountThreshold)\nreturn correlationIterable",
"lastCorrelation = None\nfor correlation i... | <|body_start_0|>
correlationIterable = self._mergeCorrelationIterable(correlationIterable)
if self._maximumValueCountThreshold is not None:
correlationIterable = self._removeNodesWithTooManyValues(correlationIterable, self._maximumValueCountThreshold)
return correlationIterable
<|end... | Takes care of merging correlations | CorrelationMergeDelegate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CorrelationMergeDelegate:
"""Takes care of merging correlations"""
def mergeCorrelationIterable(self, correlationIterable):
""":type correlationIterable: Iterable"""
<|body_0|>
def _mergeCorrelationIterable(self, correlationIterable):
""":type correlationIterable... | stack_v2_sparse_classes_36k_train_006479 | 7,995 | no_license | [
{
"docstring": ":type correlationIterable: Iterable",
"name": "mergeCorrelationIterable",
"signature": "def mergeCorrelationIterable(self, correlationIterable)"
},
{
"docstring": ":type correlationIterable: Iterable",
"name": "_mergeCorrelationIterable",
"signature": "def _mergeCorrelati... | 5 | stack_v2_sparse_classes_30k_train_012393 | Implement the Python class `CorrelationMergeDelegate` described below.
Class description:
Takes care of merging correlations
Method signatures and docstrings:
- def mergeCorrelationIterable(self, correlationIterable): :type correlationIterable: Iterable
- def _mergeCorrelationIterable(self, correlationIterable): :typ... | Implement the Python class `CorrelationMergeDelegate` described below.
Class description:
Takes care of merging correlations
Method signatures and docstrings:
- def mergeCorrelationIterable(self, correlationIterable): :type correlationIterable: Iterable
- def _mergeCorrelationIterable(self, correlationIterable): :typ... | 7915b67d07288145a2fa46a7fce3e47edad4e6c7 | <|skeleton|>
class CorrelationMergeDelegate:
"""Takes care of merging correlations"""
def mergeCorrelationIterable(self, correlationIterable):
""":type correlationIterable: Iterable"""
<|body_0|>
def _mergeCorrelationIterable(self, correlationIterable):
""":type correlationIterable... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CorrelationMergeDelegate:
"""Takes care of merging correlations"""
def mergeCorrelationIterable(self, correlationIterable):
""":type correlationIterable: Iterable"""
correlationIterable = self._mergeCorrelationIterable(correlationIterable)
if self._maximumValueCountThreshold is no... | the_stack_v2_python_sparse | modsecurity_exception_factory/correlation/correlation_merge_delegate.py | akadata/modsecurity-exception-factory | train | 0 |
ad20d6063cd8bb82fcff88a30eec3ab76fe3ce07 | [
"print('Inside __init__()')\nself.arg1 = arg1\nself.arg2 = arg2\nself.arg3 = arg3",
"print('Inside __call__()')\n\ndef wrapped_f(*args):\n print('Inside wrapped_f()')\n print('Decorator arguments:', self.arg1, self.arg2, self.arg3)\n f(*args)\n print('After f(*args)')\nreturn wrapped_f"
] | <|body_start_0|>
print('Inside __init__()')
self.arg1 = arg1
self.arg2 = arg2
self.arg3 = arg3
<|end_body_0|>
<|body_start_1|>
print('Inside __call__()')
def wrapped_f(*args):
print('Inside wrapped_f()')
print('Decorator arguments:', self.arg1, s... | decoratorWithArguments | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class decoratorWithArguments:
def __init__(self, arg1, arg2, arg3):
"""If there are decorator arguments, the function to be decorated is not passed to the constructor!"""
<|body_0|>
def __call__(self, f):
"""If there are decorator arguments, __call__() is only called once,... | stack_v2_sparse_classes_36k_train_006480 | 2,403 | no_license | [
{
"docstring": "If there are decorator arguments, the function to be decorated is not passed to the constructor!",
"name": "__init__",
"signature": "def __init__(self, arg1, arg2, arg3)"
},
{
"docstring": "If there are decorator arguments, __call__() is only called once, as part of the decoratio... | 2 | null | Implement the Python class `decoratorWithArguments` described below.
Class description:
Implement the decoratorWithArguments class.
Method signatures and docstrings:
- def __init__(self, arg1, arg2, arg3): If there are decorator arguments, the function to be decorated is not passed to the constructor!
- def __call__(... | Implement the Python class `decoratorWithArguments` described below.
Class description:
Implement the decoratorWithArguments class.
Method signatures and docstrings:
- def __init__(self, arg1, arg2, arg3): If there are decorator arguments, the function to be decorated is not passed to the constructor!
- def __call__(... | 836fcdd3f5c1b150122302685104fe51b5ebe1a3 | <|skeleton|>
class decoratorWithArguments:
def __init__(self, arg1, arg2, arg3):
"""If there are decorator arguments, the function to be decorated is not passed to the constructor!"""
<|body_0|>
def __call__(self, f):
"""If there are decorator arguments, __call__() is only called once,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class decoratorWithArguments:
def __init__(self, arg1, arg2, arg3):
"""If there are decorator arguments, the function to be decorated is not passed to the constructor!"""
print('Inside __init__()')
self.arg1 = arg1
self.arg2 = arg2
self.arg3 = arg3
def __call__(self, f):... | the_stack_v2_python_sparse | 05PythonCookbook/ch9Metaprogramming/i94parameter_arugment.py | greatabel/PythonRepository | train | 33 | |
dfeb17bc31c7e83c8708f6d68f2ff97b0a635c2d | [
"super(HybridRecommender, self).__init__()\nif not all((x.shape == Similarities_list[0].shape for x in Similarities_list)):\n raise ValueError('ItemKNNSimilarityHybridRecommender: similarities have different size')\nself.Similarities_list = []\nfor matrix in Similarities_list:\n self.Similarities_list.append(... | <|body_start_0|>
super(HybridRecommender, self).__init__()
if not all((x.shape == Similarities_list[0].shape for x in Similarities_list)):
raise ValueError('ItemKNNSimilarityHybridRecommender: similarities have different size')
self.Similarities_list = []
for matrix in Simila... | Hybrid recommender weights : list topK : number number of member : The number of recommenders involved in this one. | HybridRecommender | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HybridRecommender:
"""Hybrid recommender weights : list topK : number number of member : The number of recommenders involved in this one."""
def __init__(self, URM_train, Similarities_list, sparse_weights=True):
""":param URM_train: :param Similarities_list: The list of Similarities ... | stack_v2_sparse_classes_36k_train_006481 | 2,133 | no_license | [
{
"docstring": ":param URM_train: :param Similarities_list: The list of Similarities Matrices originating from their recommender :param weights_list: The list of weights we assign to each recommender :param sparse_weights:",
"name": "__init__",
"signature": "def __init__(self, URM_train, Similarities_li... | 2 | stack_v2_sparse_classes_30k_train_011079 | Implement the Python class `HybridRecommender` described below.
Class description:
Hybrid recommender weights : list topK : number number of member : The number of recommenders involved in this one.
Method signatures and docstrings:
- def __init__(self, URM_train, Similarities_list, sparse_weights=True): :param URM_t... | Implement the Python class `HybridRecommender` described below.
Class description:
Hybrid recommender weights : list topK : number number of member : The number of recommenders involved in this one.
Method signatures and docstrings:
- def __init__(self, URM_train, Similarities_list, sparse_weights=True): :param URM_t... | a543f2ec5e26273d44f8222c92aac16254d10a13 | <|skeleton|>
class HybridRecommender:
"""Hybrid recommender weights : list topK : number number of member : The number of recommenders involved in this one."""
def __init__(self, URM_train, Similarities_list, sparse_weights=True):
""":param URM_train: :param Similarities_list: The list of Similarities ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HybridRecommender:
"""Hybrid recommender weights : list topK : number number of member : The number of recommenders involved in this one."""
def __init__(self, URM_train, Similarities_list, sparse_weights=True):
""":param URM_train: :param Similarities_list: The list of Similarities Matrices orig... | the_stack_v2_python_sparse | Hybrid/HybridRecommender.py | BlancNicolas/RecSys_challenge | train | 0 |
50f58fc7a3ec71ecec2a24106ddcbd21efe73f9f | [
"Point.__init__(self, decisions, problem)\nself.rank = 0\nself.dominated = []\nself.dominating = 0\nself.norm_objectives = None\nself.perpendicular = None\nself.reference_id = None",
"new = NSGAPoint(self.decisions)\nnew.objectives = self.objectives[:]\nif self.norm_objectives:\n new.norm_objectives = self.nor... | <|body_start_0|>
Point.__init__(self, decisions, problem)
self.rank = 0
self.dominated = []
self.dominating = 0
self.norm_objectives = None
self.perpendicular = None
self.reference_id = None
<|end_body_0|>
<|body_start_1|>
new = NSGAPoint(self.decisions)
... | NSGAPoint | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NSGAPoint:
def __init__(self, decisions, problem=None):
"""Represents a point in the frontier for NSGA :param decisions: Set of decisions :param problem: Instance of the problem"""
<|body_0|>
def clone(self):
"""Method to clone a point :return:"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_006482 | 11,661 | permissive | [
{
"docstring": "Represents a point in the frontier for NSGA :param decisions: Set of decisions :param problem: Instance of the problem",
"name": "__init__",
"signature": "def __init__(self, decisions, problem=None)"
},
{
"docstring": "Method to clone a point :return:",
"name": "clone",
"... | 2 | stack_v2_sparse_classes_30k_train_018625 | Implement the Python class `NSGAPoint` described below.
Class description:
Implement the NSGAPoint class.
Method signatures and docstrings:
- def __init__(self, decisions, problem=None): Represents a point in the frontier for NSGA :param decisions: Set of decisions :param problem: Instance of the problem
- def clone(... | Implement the Python class `NSGAPoint` described below.
Class description:
Implement the NSGAPoint class.
Method signatures and docstrings:
- def __init__(self, decisions, problem=None): Represents a point in the frontier for NSGA :param decisions: Set of decisions :param problem: Instance of the problem
- def clone(... | dcd4a13f08f8c1bd68740e81f472ff6ac76addca | <|skeleton|>
class NSGAPoint:
def __init__(self, decisions, problem=None):
"""Represents a point in the frontier for NSGA :param decisions: Set of decisions :param problem: Instance of the problem"""
<|body_0|>
def clone(self):
"""Method to clone a point :return:"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NSGAPoint:
def __init__(self, decisions, problem=None):
"""Represents a point in the frontier for NSGA :param decisions: Set of decisions :param problem: Instance of the problem"""
Point.__init__(self, decisions, problem)
self.rank = 0
self.dominated = []
self.dominatin... | the_stack_v2_python_sparse | algorithms/nsga3/nsga3.py | bigfatnoob/optima | train | 7 | |
1f34d74651fa36c9b718f2711405b84507e08a6b | [
"if not root:\n return 0\nreturn self.counter(root, sum) + self.pathSum(root.left, sum) + self.pathSum(root.right, sum)",
"res = 0\nif not root:\n return res\nif root.val == sum:\n res += 1\nres += self.counter(root.left, sum - root.val)\nres += self.counter(root.right, sum - root.val)\nreturn res"
] | <|body_start_0|>
if not root:
return 0
return self.counter(root, sum) + self.pathSum(root.left, sum) + self.pathSum(root.right, sum)
<|end_body_0|>
<|body_start_1|>
res = 0
if not root:
return res
if root.val == sum:
res += 1
res += se... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_0|>
def counter(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
... | stack_v2_sparse_classes_36k_train_006483 | 1,266 | no_license | [
{
"docstring": ":type root: TreeNode :type sum: int :rtype: int",
"name": "pathSum",
"signature": "def pathSum(self, root, sum)"
},
{
"docstring": ":type root: TreeNode :type sum: int :rtype: int",
"name": "counter",
"signature": "def counter(self, root, sum)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: int
- def counter(self, root, sum): :type root: TreeNode :type sum: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: int
- def counter(self, root, sum): :type root: TreeNode :type sum: int :rtype: int
<|skeleton|>
class ... | af28e4070e3cab859bfcdc45aca3f31c1e3325fe | <|skeleton|>
class Solution:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_0|>
def counter(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
if not root:
return 0
return self.counter(root, sum) + self.pathSum(root.left, sum) + self.pathSum(root.right, sum)
def counter(self, root, sum):
""":type root: TreeNo... | the_stack_v2_python_sparse | pathSumIII.py | Jill1627/lc-notes | train | 0 | |
371f3e653f814971e608598bae17264de5b2add1 | [
"for res in self:\n if res.assessment_type in ['quarter', 'semiannual', 'probation']:\n raise UserError('当前版本仅支持类型为月度或年度，如需其他类型请购买完整版！')\n if res.assessment_type:\n res.evaluation_ids = [(2, 0, res.evaluation_ids.ids)]\n return {'domain': {'evaluation_ids': [('cycle_type', '=', self.asses... | <|body_start_0|>
for res in self:
if res.assessment_type in ['quarter', 'semiannual', 'probation']:
raise UserError('当前版本仅支持类型为月度或年度，如需其他类型请购买完整版！')
if res.assessment_type:
res.evaluation_ids = [(2, 0, res.evaluation_ids.ids)]
return {'doma... | InitiatePerformanceAssessment | [
"Apache-2.0",
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InitiatePerformanceAssessment:
def _onchange_assessment_type(self):
""":return:"""
<|body_0|>
def initiate_performance(self):
"""发起考核 :return:"""
<|body_1|>
def send_email_now(self, performance_object):
"""发送员工通知邮件，通过邮件：EMail队列管理器进行发送 :return:"""... | stack_v2_sparse_classes_36k_train_006484 | 6,241 | permissive | [
{
"docstring": ":return:",
"name": "_onchange_assessment_type",
"signature": "def _onchange_assessment_type(self)"
},
{
"docstring": "发起考核 :return:",
"name": "initiate_performance",
"signature": "def initiate_performance(self)"
},
{
"docstring": "发送员工通知邮件，通过邮件：EMail队列管理器进行发送 :ret... | 4 | null | Implement the Python class `InitiatePerformanceAssessment` described below.
Class description:
Implement the InitiatePerformanceAssessment class.
Method signatures and docstrings:
- def _onchange_assessment_type(self): :return:
- def initiate_performance(self): 发起考核 :return:
- def send_email_now(self, performance_obj... | Implement the Python class `InitiatePerformanceAssessment` described below.
Class description:
Implement the InitiatePerformanceAssessment class.
Method signatures and docstrings:
- def _onchange_assessment_type(self): :return:
- def initiate_performance(self): 发起考核 :return:
- def send_email_now(self, performance_obj... | 8608aaeae7a8c86d53b68ce26b7b308f779c3dd8 | <|skeleton|>
class InitiatePerformanceAssessment:
def _onchange_assessment_type(self):
""":return:"""
<|body_0|>
def initiate_performance(self):
"""发起考核 :return:"""
<|body_1|>
def send_email_now(self, performance_object):
"""发送员工通知邮件，通过邮件：EMail队列管理器进行发送 :return:"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InitiatePerformanceAssessment:
def _onchange_assessment_type(self):
""":return:"""
for res in self:
if res.assessment_type in ['quarter', 'semiannual', 'probation']:
raise UserError('当前版本仅支持类型为月度或年度，如需其他类型请购买完整版！')
if res.assessment_type:
... | the_stack_v2_python_sparse | odoo_performance_manage/wizard/initiate_performance.py | niulinlnc/odooExtModel | train | 4 | |
40156aeda5db65df5bac7d87240906e4c30c5f1b | [
"super().__init__(num_heads, block, different_layout_per_head)\nself.num_random_blocks = num_random_blocks\nself.num_sliding_window_blocks = num_sliding_window_blocks\nself.num_global_blocks = num_global_blocks\nif attention != 'unidirectional' and attention != 'bidirectional':\n raise NotImplementedError('only ... | <|body_start_0|>
super().__init__(num_heads, block, different_layout_per_head)
self.num_random_blocks = num_random_blocks
self.num_sliding_window_blocks = num_sliding_window_blocks
self.num_global_blocks = num_global_blocks
if attention != 'unidirectional' and attention != 'bidir... | Configuration class to store `BigBird` sparsity configuration. For more details about this sparsity config, please see `Big Bird: Transformers for Longer Sequences`: https://arxiv.org/pdf/2007.14062.pdf This class extends parent class of `SparsityConfig` and customizes it for `BigBird` sparsity. | BigBirdSparsityConfig | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BigBirdSparsityConfig:
"""Configuration class to store `BigBird` sparsity configuration. For more details about this sparsity config, please see `Big Bird: Transformers for Longer Sequences`: https://arxiv.org/pdf/2007.14062.pdf This class extends parent class of `SparsityConfig` and customizes i... | stack_v2_sparse_classes_36k_train_006485 | 42,463 | permissive | [
{
"docstring": "Initialize the BigBird Sparsity Pattern Config. For usage example please see, TODO DeepSpeed Sparse Transformer Tutorial Arguments: num_heads: required: an integer determining number of attention heads of the layer. block: optional: an integer determining the block size. Current implementation o... | 5 | null | Implement the Python class `BigBirdSparsityConfig` described below.
Class description:
Configuration class to store `BigBird` sparsity configuration. For more details about this sparsity config, please see `Big Bird: Transformers for Longer Sequences`: https://arxiv.org/pdf/2007.14062.pdf This class extends parent cla... | Implement the Python class `BigBirdSparsityConfig` described below.
Class description:
Configuration class to store `BigBird` sparsity configuration. For more details about this sparsity config, please see `Big Bird: Transformers for Longer Sequences`: https://arxiv.org/pdf/2007.14062.pdf This class extends parent cla... | 55d9964c59c0c6e23158b5789a5c36c28939a7b0 | <|skeleton|>
class BigBirdSparsityConfig:
"""Configuration class to store `BigBird` sparsity configuration. For more details about this sparsity config, please see `Big Bird: Transformers for Longer Sequences`: https://arxiv.org/pdf/2007.14062.pdf This class extends parent class of `SparsityConfig` and customizes i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BigBirdSparsityConfig:
"""Configuration class to store `BigBird` sparsity configuration. For more details about this sparsity config, please see `Big Bird: Transformers for Longer Sequences`: https://arxiv.org/pdf/2007.14062.pdf This class extends parent class of `SparsityConfig` and customizes it for `BigBir... | the_stack_v2_python_sparse | deepspeed/ops/sparse_attention/sparsity_config.py | microsoft/DeepSpeed | train | 27,557 |
c7dd6d09117cc8686eddbd1a7ea10d88a5909a25 | [
"transactions = get_transactions_by_gifts(None)\nresult = TransactionSchema(many=True).dump(transactions).data\nreturn (result, 200)",
"transactions = get_transactions_by_gifts(request.json['searchable_ids'])\nresult = TransactionSchema(many=True).dump(transactions).data\nreturn (result, 200)"
] | <|body_start_0|>
transactions = get_transactions_by_gifts(None)
result = TransactionSchema(many=True).dump(transactions).data
return (result, 200)
<|end_body_0|>
<|body_start_1|>
transactions = get_transactions_by_gifts(request.json['searchable_ids'])
result = TransactionSchema(... | Flask-RESTful resource endpoints for TransactionModel by gift searchable ID's. | TransactionsByGifts | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransactionsByGifts:
"""Flask-RESTful resource endpoints for TransactionModel by gift searchable ID's."""
def get(self):
"""Simple endpoint to retrieve all rows from table."""
<|body_0|>
def post(self):
"""Simple endpoint to return several rows from table given a... | stack_v2_sparse_classes_36k_train_006486 | 4,727 | no_license | [
{
"docstring": "Simple endpoint to retrieve all rows from table.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Simple endpoint to return several rows from table given a list of gift searchable ID's.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `TransactionsByGifts` described below.
Class description:
Flask-RESTful resource endpoints for TransactionModel by gift searchable ID's.
Method signatures and docstrings:
- def get(self): Simple endpoint to retrieve all rows from table.
- def post(self): Simple endpoint to return several ro... | Implement the Python class `TransactionsByGifts` described below.
Class description:
Flask-RESTful resource endpoints for TransactionModel by gift searchable ID's.
Method signatures and docstrings:
- def get(self): Simple endpoint to retrieve all rows from table.
- def post(self): Simple endpoint to return several ro... | d5ffcc5d276692d1578cea704125b1b3952beb1c | <|skeleton|>
class TransactionsByGifts:
"""Flask-RESTful resource endpoints for TransactionModel by gift searchable ID's."""
def get(self):
"""Simple endpoint to retrieve all rows from table."""
<|body_0|>
def post(self):
"""Simple endpoint to return several rows from table given a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransactionsByGifts:
"""Flask-RESTful resource endpoints for TransactionModel by gift searchable ID's."""
def get(self):
"""Simple endpoint to retrieve all rows from table."""
transactions = get_transactions_by_gifts(None)
result = TransactionSchema(many=True).dump(transactions).d... | the_stack_v2_python_sparse | application/resources/transaction.py | transreductionist/API-Project-1 | train | 0 |
5b2c9a88ce2ab06dda2f3824d6c5b7a0591a25c0 | [
"self.adafruit_sht = adafruit_sht\nself.temperature: float | None = None\nself.humidity: float | None = None",
"temperature, humidity = self.adafruit_sht.read_temperature_humidity()\nif math.isnan(temperature) or math.isnan(humidity):\n _LOGGER.warning('Bad sample from sensor SHT31')\n return\nself.temperat... | <|body_start_0|>
self.adafruit_sht = adafruit_sht
self.temperature: float | None = None
self.humidity: float | None = None
<|end_body_0|>
<|body_start_1|>
temperature, humidity = self.adafruit_sht.read_temperature_humidity()
if math.isnan(temperature) or math.isnan(humidity):
... | Get the latest data from the SHT sensor. | SHTClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SHTClient:
"""Get the latest data from the SHT sensor."""
def __init__(self, adafruit_sht):
"""Initialize the sensor."""
<|body_0|>
def update(self):
"""Get the latest data from the SHT sensor."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sel... | stack_v2_sparse_classes_36k_train_006487 | 4,258 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, adafruit_sht)"
},
{
"docstring": "Get the latest data from the SHT sensor.",
"name": "update",
"signature": "def update(self)"
}
] | 2 | null | Implement the Python class `SHTClient` described below.
Class description:
Get the latest data from the SHT sensor.
Method signatures and docstrings:
- def __init__(self, adafruit_sht): Initialize the sensor.
- def update(self): Get the latest data from the SHT sensor. | Implement the Python class `SHTClient` described below.
Class description:
Get the latest data from the SHT sensor.
Method signatures and docstrings:
- def __init__(self, adafruit_sht): Initialize the sensor.
- def update(self): Get the latest data from the SHT sensor.
<|skeleton|>
class SHTClient:
"""Get the la... | 8de7966104911bca6f855a1755a6d71a07afb9de | <|skeleton|>
class SHTClient:
"""Get the latest data from the SHT sensor."""
def __init__(self, adafruit_sht):
"""Initialize the sensor."""
<|body_0|>
def update(self):
"""Get the latest data from the SHT sensor."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SHTClient:
"""Get the latest data from the SHT sensor."""
def __init__(self, adafruit_sht):
"""Initialize the sensor."""
self.adafruit_sht = adafruit_sht
self.temperature: float | None = None
self.humidity: float | None = None
def update(self):
"""Get the late... | the_stack_v2_python_sparse | homeassistant/components/sht31/sensor.py | AlexxIT/home-assistant | train | 9 |
5e2f2255de96dec5a0bff573f08f65b13a47bd0d | [
"self.cap = 10007\nself.size = 0\nself.d = [LinkedListNode(0) for _ in xrange(self.cap)]",
"prev = dummy = self.d[key % self.cap]\ncurr = dummy.next\nwhile curr:\n if curr.val[0] == key:\n break\n prev = curr\n curr = curr.next\nif not curr:\n curr = LinkedListNode((key, value))\n curr.prev,... | <|body_start_0|>
self.cap = 10007
self.size = 0
self.d = [LinkedListNode(0) for _ in xrange(self.cap)]
<|end_body_0|>
<|body_start_1|>
prev = dummy = self.d[key % self.cap]
curr = dummy.next
while curr:
if curr.val[0] == key:
break
... | MyHashMap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def put(self, key, value):
"""value will always be non-negative. :type key: int :type value: int :rtype: void"""
<|body_1|>
def get(self, key):
"""Returns the va... | stack_v2_sparse_classes_36k_train_006488 | 2,146 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "value will always be non-negative. :type key: int :type value: int :rtype: void",
"name": "put",
"signature": "def put(self, key, value)"
},
{
"docstrin... | 4 | stack_v2_sparse_classes_30k_train_008567 | Implement the Python class `MyHashMap` described below.
Class description:
Implement the MyHashMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def put(self, key, value): value will always be non-negative. :type key: int :type value: int :rtype: void
- def get(... | Implement the Python class `MyHashMap` described below.
Class description:
Implement the MyHashMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def put(self, key, value): value will always be non-negative. :type key: int :type value: int :rtype: void
- def get(... | 6fec95b9b4d735727160905e754a698513bfb7d8 | <|skeleton|>
class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def put(self, key, value):
"""value will always be non-negative. :type key: int :type value: int :rtype: void"""
<|body_1|>
def get(self, key):
"""Returns the va... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
self.cap = 10007
self.size = 0
self.d = [LinkedListNode(0) for _ in xrange(self.cap)]
def put(self, key, value):
"""value will always be non-negative. :type key: int :type value: int :rtype: ... | the_stack_v2_python_sparse | leetcode/design/design-hashmap.py | jwyx3/practices | train | 2 | |
67fde1c2bb2e041b9a0d5ba2b2bb9aab02982488 | [
"updated_grid = [[self.update_cell(row, col) for col in range(self.get_grid_width())] for row in range(self.get_grid_height())]\nfor col in range(self.get_grid_width()):\n for row in range(self.get_grid_height()):\n if updated_grid[row][col] == EMPTY:\n self.set_empty(row, col)\n else:\n... | <|body_start_0|>
updated_grid = [[self.update_cell(row, col) for col in range(self.get_grid_width())] for row in range(self.get_grid_height())]
for col in range(self.get_grid_width()):
for row in range(self.get_grid_height()):
if updated_grid[row][col] == EMPTY:
... | Extend Grid class to support Game of Life | GameOfLife | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameOfLife:
"""Extend Grid class to support Game of Life"""
def update_gol(self):
"""Function that performs one step of the Game of Life"""
<|body_0|>
def update_cell(self, row, col):
"""Function that computes the update for one cell in the Game of Life"""
... | stack_v2_sparse_classes_36k_train_006489 | 1,456 | no_license | [
{
"docstring": "Function that performs one step of the Game of Life",
"name": "update_gol",
"signature": "def update_gol(self)"
},
{
"docstring": "Function that computes the update for one cell in the Game of Life",
"name": "update_cell",
"signature": "def update_cell(self, row, col)"
... | 2 | null | Implement the Python class `GameOfLife` described below.
Class description:
Extend Grid class to support Game of Life
Method signatures and docstrings:
- def update_gol(self): Function that performs one step of the Game of Life
- def update_cell(self, row, col): Function that computes the update for one cell in the G... | Implement the Python class `GameOfLife` described below.
Class description:
Extend Grid class to support Game of Life
Method signatures and docstrings:
- def update_gol(self): Function that performs one step of the Game of Life
- def update_cell(self, row, col): Function that computes the update for one cell in the G... | 8d3000467be6ccef812dec0d9e95e108551f8b3b | <|skeleton|>
class GameOfLife:
"""Extend Grid class to support Game of Life"""
def update_gol(self):
"""Function that performs one step of the Game of Life"""
<|body_0|>
def update_cell(self, row, col):
"""Function that computes the update for one cell in the Game of Life"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GameOfLife:
"""Extend Grid class to support Game of Life"""
def update_gol(self):
"""Function that performs one step of the Game of Life"""
updated_grid = [[self.update_cell(row, col) for col in range(self.get_grid_width())] for row in range(self.get_grid_height())]
for col in ran... | the_stack_v2_python_sparse | principles_of_computing/pj5/gameoflife.py | creasyw/Courses | train | 2 |
dfda78681fe7f41c8f6aecdce8fffbffdbf9448f | [
"self.explanation_type = explanation_type\nself._internal_obj = internal_obj\nself.feature_names = feature_names\nself.feature_types = feature_types\nself.name = name\nself.selector = selector",
"if key is None:\n return self._internal_obj['overall']\nreturn None",
"from ..visual.plot import plot_density\nda... | <|body_start_0|>
self.explanation_type = explanation_type
self._internal_obj = internal_obj
self.feature_names = feature_names
self.feature_types = feature_types
self.name = name
self.selector = selector
<|end_body_0|>
<|body_start_1|>
if key is None:
... | Produces explanation specific to regression metrics. | RegressionExplanation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegressionExplanation:
"""Produces explanation specific to regression metrics."""
def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None):
"""Initializes class. Args: explanation_type: Type of explanation. internal_obj: A j... | stack_v2_sparse_classes_36k_train_006490 | 5,223 | permissive | [
{
"docstring": "Initializes class. Args: explanation_type: Type of explanation. internal_obj: A jsonable object that backs the explanation. feature_names: List of feature names. feature_types: List of feature types. name: User-defined name of explanation. selector: A dataframe whose indices correspond to explan... | 3 | stack_v2_sparse_classes_30k_test_000486 | Implement the Python class `RegressionExplanation` described below.
Class description:
Produces explanation specific to regression metrics.
Method signatures and docstrings:
- def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None): Initializes class. Args:... | Implement the Python class `RegressionExplanation` described below.
Class description:
Produces explanation specific to regression metrics.
Method signatures and docstrings:
- def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None): Initializes class. Args:... | e6f38ea195aecbbd9d28c7183a83c65ada16e1ae | <|skeleton|>
class RegressionExplanation:
"""Produces explanation specific to regression metrics."""
def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None):
"""Initializes class. Args: explanation_type: Type of explanation. internal_obj: A j... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegressionExplanation:
"""Produces explanation specific to regression metrics."""
def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None):
"""Initializes class. Args: explanation_type: Type of explanation. internal_obj: A jsonable objec... | the_stack_v2_python_sparse | python/interpret-core/interpret/perf/_regression.py | interpretml/interpret | train | 3,731 |
83a8f33f1e130c8e392c79c943b2cc4f12ff4d28 | [
"if not prices or len(prices) < 1:\n return 0\nn = len(prices)\nbuy = [0] * (n + 1)\nsell = [0] * (n + 1)\nbuy[1] = -prices[0]\nfor i in range(2, n + 1):\n price = prices[i - 1]\n buy[i] = max(sell[i - 2] - price, buy[i - 1])\n sell[i] = max(buy[i - 1] + price, sell[i - 1])\nreturn sell[n]",
"n = len(... | <|body_start_0|>
if not prices or len(prices) < 1:
return 0
n = len(prices)
buy = [0] * (n + 1)
sell = [0] * (n + 1)
buy[1] = -prices[0]
for i in range(2, n + 1):
price = prices[i - 1]
buy[i] = max(sell[i - 2] - price, buy[i - 1])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int On any i-th day, we can buy, sell or cooldown buy[i]: The maximum profit can be made if the first i days end with buy or wait. E.g "buy, sell, buy" or "buy, cooldown, cooldown" sell[i]: The maximum profit can b... | stack_v2_sparse_classes_36k_train_006491 | 3,095 | no_license | [
{
"docstring": ":type prices: List[int] :rtype: int On any i-th day, we can buy, sell or cooldown buy[i]: The maximum profit can be made if the first i days end with buy or wait. E.g \"buy, sell, buy\" or \"buy, cooldown, cooldown\" sell[i]: The maximum profit can be made if the first i days end with sell or wa... | 2 | stack_v2_sparse_classes_30k_train_018869 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices): :type prices: List[int] :rtype: int On any i-th day, we can buy, sell or cooldown buy[i]: The maximum profit can be made if the first i days end with... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices): :type prices: List[int] :rtype: int On any i-th day, we can buy, sell or cooldown buy[i]: The maximum profit can be made if the first i days end with... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int On any i-th day, we can buy, sell or cooldown buy[i]: The maximum profit can be made if the first i days end with buy or wait. E.g "buy, sell, buy" or "buy, cooldown, cooldown" sell[i]: The maximum profit can b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int On any i-th day, we can buy, sell or cooldown buy[i]: The maximum profit can be made if the first i days end with buy or wait. E.g "buy, sell, buy" or "buy, cooldown, cooldown" sell[i]: The maximum profit can be made if the ... | the_stack_v2_python_sparse | B/BestTimetoBuyandSellStockWithCooldown.py | bssrdf/pyleet | train | 2 | |
bbbae4d58c8d219796a3b57516c379f085cc076b | [
"super(VisualShape, self).__init__()\nself.filename = filename\nself.scale = scale",
"visual_id = p.createVisualShape(p.GEOM_MESH, fileName=self.filename, meshScale=[self.scale] * 3)\nbody_id = p.createMultiBody(baseCollisionShapeIndex=-1, baseVisualShapeIndex=visual_id)\nreturn body_id"
] | <|body_start_0|>
super(VisualShape, self).__init__()
self.filename = filename
self.scale = scale
<|end_body_0|>
<|body_start_1|>
visual_id = p.createVisualShape(p.GEOM_MESH, fileName=self.filename, meshScale=[self.scale] * 3)
body_id = p.createMultiBody(baseCollisionShapeIndex=-... | Visual shape created with mesh file | VisualShape | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VisualShape:
"""Visual shape created with mesh file"""
def __init__(self, filename, scale=1.0):
"""Create a visual shape to show in pybullet and MeshRenderer :param filename: obj filename"""
<|body_0|>
def _load(self):
"""Load the object into pybullet"""
... | stack_v2_sparse_classes_36k_train_006492 | 891 | permissive | [
{
"docstring": "Create a visual shape to show in pybullet and MeshRenderer :param filename: obj filename",
"name": "__init__",
"signature": "def __init__(self, filename, scale=1.0)"
},
{
"docstring": "Load the object into pybullet",
"name": "_load",
"signature": "def _load(self)"
}
] | 2 | null | Implement the Python class `VisualShape` described below.
Class description:
Visual shape created with mesh file
Method signatures and docstrings:
- def __init__(self, filename, scale=1.0): Create a visual shape to show in pybullet and MeshRenderer :param filename: obj filename
- def _load(self): Load the object into... | Implement the Python class `VisualShape` described below.
Class description:
Visual shape created with mesh file
Method signatures and docstrings:
- def __init__(self, filename, scale=1.0): Create a visual shape to show in pybullet and MeshRenderer :param filename: obj filename
- def _load(self): Load the object into... | db08f35fd645cae52d44b9696aedc905067bde13 | <|skeleton|>
class VisualShape:
"""Visual shape created with mesh file"""
def __init__(self, filename, scale=1.0):
"""Create a visual shape to show in pybullet and MeshRenderer :param filename: obj filename"""
<|body_0|>
def _load(self):
"""Load the object into pybullet"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VisualShape:
"""Visual shape created with mesh file"""
def __init__(self, filename, scale=1.0):
"""Create a visual shape to show in pybullet and MeshRenderer :param filename: obj filename"""
super(VisualShape, self).__init__()
self.filename = filename
self.scale = scale
... | the_stack_v2_python_sparse | igibson/objects/visual_shape.py | junyaoshi/iGibson | train | 1 |
79d8d649ec9ce5c99a240baa4178591ef8e8dbef | [
"CtrlDev.__init__(self, parent)\nself._diag = DiagWebcam(self)\nself._compat = CompatWebcam(self)\nself._guiClass = GUIWebcam",
"try:\n self._callInfo()\n self._callCompat()\n runDiag = False\n for i in self._compatRes:\n runDiag = runDiag | (not i[0])\n if runDiag:\n self._callDiag()... | <|body_start_0|>
CtrlDev.__init__(self, parent)
self._diag = DiagWebcam(self)
self._compat = CompatWebcam(self)
self._guiClass = GUIWebcam
<|end_body_0|>
<|body_start_1|>
try:
self._callInfo()
self._callCompat()
runDiag = False
for... | Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade e cria a tela de exibição. | CtrlWebcam | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CtrlWebcam:
"""Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade e cria a tela de exibição."""
def __init__(self, parent):
"""Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe base 'CtrlDev'.... | stack_v2_sparse_classes_36k_train_006493 | 1,399 | no_license | [
{
"docstring": "Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe base 'CtrlDev'.",
"name": "__init__",
"signature": "def __init__(self, parent)"
},
{
"docstring": "Executa o info, compat e diag (dependendo do resultado do compatibilidade) e cria as tela... | 2 | null | Implement the Python class `CtrlWebcam` described below.
Class description:
Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade e cria a tela de exibição.
Method signatures and docstrings:
- def __init__(self, parent): Construtor que inicializa os atributos '_diag', '_... | Implement the Python class `CtrlWebcam` described below.
Class description:
Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade e cria a tela de exibição.
Method signatures and docstrings:
- def __init__(self, parent): Construtor que inicializa os atributos '_diag', '_... | bda0c2c8977dd1246339f1f0f4718d29e8795f21 | <|skeleton|>
class CtrlWebcam:
"""Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade e cria a tela de exibição."""
def __init__(self, parent):
"""Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe base 'CtrlDev'.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CtrlWebcam:
"""Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade e cria a tela de exibição."""
def __init__(self, parent):
"""Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe base 'CtrlDev'."""
C... | the_stack_v2_python_sparse | src/libs/webcam/ctrl_webcam.py | adrianomelo/ldc-desktop | train | 1 |
f5fe0f7fea601c7891aed905f664d022b8727b6c | [
"if not root:\n return []\nret = []\nstack = []\ncur = root\nwhile cur:\n ret.append(cur.val)\n stack.append(cur)\n cur = cur.left\n while not cur and stack:\n cur = stack.pop().right\nreturn ret",
"def traverse(n):\n if not n:\n return\n yield n.val\n yield from traverse(n.l... | <|body_start_0|>
if not root:
return []
ret = []
stack = []
cur = root
while cur:
ret.append(cur.val)
stack.append(cur)
cur = cur.left
while not cur and stack:
cur = stack.pop().right
return ret
<... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
"""Jul 26, 2018 06:43"""
<|body_0|>
def preorderTraversal(self, root: Optional[TreeNode]) -> List[int]:
"""Mar 05, 2023 14:14"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
retur... | stack_v2_sparse_classes_36k_train_006494 | 1,892 | no_license | [
{
"docstring": "Jul 26, 2018 06:43",
"name": "preorderTraversal",
"signature": "def preorderTraversal(self, root)"
},
{
"docstring": "Mar 05, 2023 14:14",
"name": "preorderTraversal",
"signature": "def preorderTraversal(self, root: Optional[TreeNode]) -> List[int]"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): Jul 26, 2018 06:43
- def preorderTraversal(self, root: Optional[TreeNode]) -> List[int]: Mar 05, 2023 14:14 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): Jul 26, 2018 06:43
- def preorderTraversal(self, root: Optional[TreeNode]) -> List[int]: Mar 05, 2023 14:14
<|skeleton|>
class Solution:
... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
"""Jul 26, 2018 06:43"""
<|body_0|>
def preorderTraversal(self, root: Optional[TreeNode]) -> List[int]:
"""Mar 05, 2023 14:14"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def preorderTraversal(self, root):
"""Jul 26, 2018 06:43"""
if not root:
return []
ret = []
stack = []
cur = root
while cur:
ret.append(cur.val)
stack.append(cur)
cur = cur.left
while not cur ... | the_stack_v2_python_sparse | leetcode/solved/144_Binary_Tree_Preorder_Traversal/solution.py | sungminoh/algorithms | train | 0 | |
b8f78be36e80b18f38ff260de07d9748cec55b2b | [
"super().__init__()\nself.mode = mode\nself.qubit_names = qubit_names",
"if self.mode == FilterMode.INCLUDE:\n return not all([qb_name in self.qubit_names for qb_name in qubit_names])\nelif self.mode == FilterMode.EXCLUDE:\n return not any([qb_name in self.qubit_names for qb_name in qubit_names])",
"if no... | <|body_start_0|>
super().__init__()
self.mode = mode
self.qubit_names = qubit_names
<|end_body_0|>
<|body_start_1|>
if self.mode == FilterMode.INCLUDE:
return not all([qb_name in self.qubit_names for qb_name in qubit_names])
elif self.mode == FilterMode.EXCLUDE:
... | A filter class to filter based on value nodes' `qubit` field | QubitFilter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QubitFilter:
"""A filter class to filter based on value nodes' `qubit` field"""
def __init__(self, mode: FilterMode=FilterMode.EXCLUDE, qubit_names=[]):
"""Creates a QubitFilter instance All qubit names in a node's `qubits` field must be in/or not in `self.qubit_names`; based on `mod... | stack_v2_sparse_classes_36k_train_006495 | 7,968 | permissive | [
{
"docstring": "Creates a QubitFilter instance All qubit names in a node's `qubits` field must be in/or not in `self.qubit_names`; based on `mode`. For example, if `mode=FilterMode.INCLUDE`, a value node will be filtered if any qubit name in `node['qubits']` is not in `qubit_names`. Args: mode (Filtermode, opti... | 3 | null | Implement the Python class `QubitFilter` described below.
Class description:
A filter class to filter based on value nodes' `qubit` field
Method signatures and docstrings:
- def __init__(self, mode: FilterMode=FilterMode.EXCLUDE, qubit_names=[]): Creates a QubitFilter instance All qubit names in a node's `qubits` fie... | Implement the Python class `QubitFilter` described below.
Class description:
A filter class to filter based on value nodes' `qubit` field
Method signatures and docstrings:
- def __init__(self, mode: FilterMode=FilterMode.EXCLUDE, qubit_names=[]): Creates a QubitFilter instance All qubit names in a node's `qubits` fie... | bc6733d774fe31a23f4c7e73e5eb0beed8d30e7d | <|skeleton|>
class QubitFilter:
"""A filter class to filter based on value nodes' `qubit` field"""
def __init__(self, mode: FilterMode=FilterMode.EXCLUDE, qubit_names=[]):
"""Creates a QubitFilter instance All qubit names in a node's `qubits` field must be in/or not in `self.qubit_names`; based on `mod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QubitFilter:
"""A filter class to filter based on value nodes' `qubit` field"""
def __init__(self, mode: FilterMode=FilterMode.EXCLUDE, qubit_names=[]):
"""Creates a QubitFilter instance All qubit names in a node's `qubits` field must be in/or not in `self.qubit_names`; based on `mode`. For examp... | the_stack_v2_python_sparse | pycqed/utilities/devicedb/filters.py | QudevETH/PycQED_py3 | train | 8 |
8d083100fee44589cc3da7b1acee55d86f120838 | [
"res = nums.copy()\nlength = len(nums)\nfor i in range(2, k + 1):\n for j in range(length - i + 1):\n res[j] = max(res[j], nums[j + i - 1])\nreturn res[:length - k + 1]",
"res = []\nmaxVal, maxPos = (float('-inf'), None)\nfor i, num in enumerate(nums[:k]):\n if num >= maxVal:\n maxVal, maxPos ... | <|body_start_0|>
res = nums.copy()
length = len(nums)
for i in range(2, k + 1):
for j in range(length - i + 1):
res[j] = max(res[j], nums[j + i - 1])
return res[:length - k + 1]
<|end_body_0|>
<|body_start_1|>
res = []
maxVal, maxPos = (float(... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]:
"""借鉴 shell sort ，从winsize=1 逐步扩张到 winsize=k ，每次只需要比较 新入windows的num 和原winsize_max 之间的大小即可 O(kn) But LTE"""
<|body_0|>
def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]:
"""滑动窗口... | stack_v2_sparse_classes_36k_train_006496 | 7,153 | permissive | [
{
"docstring": "借鉴 shell sort ，从winsize=1 逐步扩张到 winsize=k ，每次只需要比较 新入windows的num 和原winsize_max 之间的大小即可 O(kn) But LTE",
"name": "maxSlidingWindow",
"signature": "def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]"
},
{
"docstring": "滑动窗口法， 每次滑动 - first + last ，然后判断 max(windows) O(nk... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]: 借鉴 shell sort ，从winsize=1 逐步扩张到 winsize=k ，每次只需要比较 新入windows的num 和原winsize_max 之间的大小即可 O(kn) But LTE
- def maxSl... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]: 借鉴 shell sort ，从winsize=1 逐步扩张到 winsize=k ，每次只需要比较 新入windows的num 和原winsize_max 之间的大小即可 O(kn) But LTE
- def maxSl... | 65549f72c565d9f11641c86d6cef9c7988805817 | <|skeleton|>
class Solution:
def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]:
"""借鉴 shell sort ，从winsize=1 逐步扩张到 winsize=k ，每次只需要比较 新入windows的num 和原winsize_max 之间的大小即可 O(kn) But LTE"""
<|body_0|>
def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]:
"""滑动窗口... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]:
"""借鉴 shell sort ，从winsize=1 逐步扩张到 winsize=k ，每次只需要比较 新入windows的num 和原winsize_max 之间的大小即可 O(kn) But LTE"""
res = nums.copy()
length = len(nums)
for i in range(2, k + 1):
for j in range(lengt... | the_stack_v2_python_sparse | src/239.sliding-window-maximum.py | wisesky/LeetCode-Practice | train | 0 | |
61fb61379af3f23f6e053eaf8d7c1e5904a72afa | [
"if qca_passwd is None:\n qca_passwd = os.environ.get('QCAUSR', None)\nself.qc_spec = qc_spec\nself.client = FractalClient(address, username='user', password=qca_passwd, verify=False)\ntry:\n self.coll = base_class.from_server(name=coll_name, client=self.client)\nexcept KeyError as ex:\n if create:\n ... | <|body_start_0|>
if qca_passwd is None:
qca_passwd = os.environ.get('QCAUSR', None)
self.qc_spec = qc_spec
self.client = FractalClient(address, username='user', password=qca_passwd, verify=False)
try:
self.coll = base_class.from_server(name=coll_name, client=self.... | Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate XYZ coordinates to allow for a 'just add this SMILES'), using a consistent identifi... | QCFractalWrapper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QCFractalWrapper:
"""Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate XYZ coordinates to allow for a 'just ad... | stack_v2_sparse_classes_36k_train_006497 | 29,582 | no_license | [
{
"docstring": "Open the geometry computation dataset Args: address: Address for the QCFractal server base_class: Type of the collection qc_spec: Name of the QC specification coll_name: Name of the collection holding the data qca_passwd: Password for the QCFractal server create: Whether creating a new collectio... | 2 | stack_v2_sparse_classes_30k_train_021253 | Implement the Python class `QCFractalWrapper` described below.
Class description:
Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate ... | Implement the Python class `QCFractalWrapper` described below.
Class description:
Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate ... | ef9e586e89053d1f6bea541717db8be43dbce0a4 | <|skeleton|>
class QCFractalWrapper:
"""Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate XYZ coordinates to allow for a 'just ad... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QCFractalWrapper:
"""Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate XYZ coordinates to allow for a 'just add this SMILES... | the_stack_v2_python_sparse | moldesign/simulate/qcfractal.py | exalearn/electrolyte-design | train | 4 |
34553c79d3ced37c5e55a96fe3eccb5b18c29ec5 | [
"self.Kd = Kd\nself.Kp = Kp\nself.Ki = Ki\nself.setpoint = setpoint\nself.output_limits = output_limits\nself.integral = 0\nself.last_error = 0\nself.last_value = 0\npass",
"self.integral = 0\nself.last_error = 0\nself.last_value = 0",
"error = self.setpoint - measurement\nderivative = error - self.last_error\n... | <|body_start_0|>
self.Kd = Kd
self.Kp = Kp
self.Ki = Ki
self.setpoint = setpoint
self.output_limits = output_limits
self.integral = 0
self.last_error = 0
self.last_value = 0
pass
<|end_body_0|>
<|body_start_1|>
self.integral = 0
se... | Useful reusable PID class | PID | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PID:
"""Useful reusable PID class"""
def __init__(self, Kd: float, Kp: float, Ki: float, setpoint=0.0, output_limits=None):
"""Initializes the PID controller :param Kd: The derivative portion of the PID controller :param Kp: The proportial portion of the PID controller :param Ki: The... | stack_v2_sparse_classes_36k_train_006498 | 1,854 | permissive | [
{
"docstring": "Initializes the PID controller :param Kd: The derivative portion of the PID controller :param Kp: The proportial portion of the PID controller :param Ki: The integral portion of the PID controller :param setpoint: The point that the PID is set to :param output_limits: Max and minimum setting for... | 3 | null | Implement the Python class `PID` described below.
Class description:
Useful reusable PID class
Method signatures and docstrings:
- def __init__(self, Kd: float, Kp: float, Ki: float, setpoint=0.0, output_limits=None): Initializes the PID controller :param Kd: The derivative portion of the PID controller :param Kp: Th... | Implement the Python class `PID` described below.
Class description:
Useful reusable PID class
Method signatures and docstrings:
- def __init__(self, Kd: float, Kp: float, Ki: float, setpoint=0.0, output_limits=None): Initializes the PID controller :param Kd: The derivative portion of the PID controller :param Kp: Th... | 5509c07931d85583b0d99606f66817afb6fbcbe1 | <|skeleton|>
class PID:
"""Useful reusable PID class"""
def __init__(self, Kd: float, Kp: float, Ki: float, setpoint=0.0, output_limits=None):
"""Initializes the PID controller :param Kd: The derivative portion of the PID controller :param Kp: The proportial portion of the PID controller :param Ki: The... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PID:
"""Useful reusable PID class"""
def __init__(self, Kd: float, Kp: float, Ki: float, setpoint=0.0, output_limits=None):
"""Initializes the PID controller :param Kd: The derivative portion of the PID controller :param Kp: The proportial portion of the PID controller :param Ki: The integral por... | the_stack_v2_python_sparse | soccer_common/src/soccer_common/pid.py | utra-robosoccer/soccerbot | train | 118 |
c3641d4e7463259190934193429f3317fc44c06d | [
"size = len(matrix)\nfor i in range(size):\n self.rotate_row(matrix, i)\nreturn",
"size = len(matrix)\nfor j, v in enumerate(matrix[n][n:size - n - 1]):\n temp, i, j = self.exchange(matrix, size, n, j + n, matrix[n][j + n])\n temp, i, j = self.exchange(matrix, size, i, j, temp)\n temp, i, j = self.exc... | <|body_start_0|>
size = len(matrix)
for i in range(size):
self.rotate_row(matrix, i)
return
<|end_body_0|>
<|body_start_1|>
size = len(matrix)
for j, v in enumerate(matrix[n][n:size - n - 1]):
temp, i, j = self.exchange(matrix, size, n, j + n, matrix[n][j... | Solution | [
"WTFPL"
] | 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 rotate_row(self, matrix, n):
"""n is the row index"""
<|body_1|>
def exchange(self, matrix, size, ... | stack_v2_sparse_classes_36k_train_006499 | 1,081 | permissive | [
{
"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": "n is the row index",
"name": "rotate_row",
"signature": "def rotate_row(self, matrix, n)"
},... | 3 | stack_v2_sparse_classes_30k_train_008017 | 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 rotate_row(self, matrix, n): n is the row index... | 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 rotate_row(self, matrix, n): n is the row index... | 2677b6d26bedb9bc6c6137a2392d0afaceb91ec2 | <|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 rotate_row(self, matrix, n):
"""n is the row index"""
<|body_1|>
def exchange(self, matrix, size, ... | stack_v2_sparse_classes_36k | 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."""
size = len(matrix)
for i in range(size):
self.rotate_row(matrix, i)
return
def rotate_row(self, matrix, n):
"""n... | the_stack_v2_python_sparse | rotate_image/solution.py | haotianzhu/Questions_Solutions | train | 0 |
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