blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
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value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0ec0239c51b93ec9596ca82f66fdf8f2775d49cb | [
"data = np.zeros((2, 2, 2, 2), dtype=np.float32)\nself.wg_perc = 50.0\nself.ws_perc = 95.0\nself.cube_wg = create_wind_percentile_cube(data=data, perc_values=[self.wg_perc, 90.0])",
"plugin = WindGustDiagnostic(self.wg_perc, self.ws_perc)\nresult, perc_coord = plugin.extract_percentile_data(self.cube_wg, self.wg_... | <|body_start_0|>
data = np.zeros((2, 2, 2, 2), dtype=np.float32)
self.wg_perc = 50.0
self.ws_perc = 95.0
self.cube_wg = create_wind_percentile_cube(data=data, perc_values=[self.wg_perc, 90.0])
<|end_body_0|>
<|body_start_1|>
plugin = WindGustDiagnostic(self.wg_perc, self.ws_perc... | Test the extract_percentile_data method. | Test_extract_percentile_data | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_extract_percentile_data:
"""Test the extract_percentile_data method."""
def setUp(self):
"""Create a wind-speed and wind-gust cube with percentile coord."""
<|body_0|>
def test_basic(self):
"""Test that the function returns a Cube and Coord."""
<|bod... | stack_v2_sparse_classes_75kplus_train_001100 | 11,962 | permissive | [
{
"docstring": "Create a wind-speed and wind-gust cube with percentile coord.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test that the function returns a Cube and Coord.",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring": "Test ... | 6 | null | Implement the Python class `Test_extract_percentile_data` described below.
Class description:
Test the extract_percentile_data method.
Method signatures and docstrings:
- def setUp(self): Create a wind-speed and wind-gust cube with percentile coord.
- def test_basic(self): Test that the function returns a Cube and Co... | Implement the Python class `Test_extract_percentile_data` described below.
Class description:
Test the extract_percentile_data method.
Method signatures and docstrings:
- def setUp(self): Create a wind-speed and wind-gust cube with percentile coord.
- def test_basic(self): Test that the function returns a Cube and Co... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_extract_percentile_data:
"""Test the extract_percentile_data method."""
def setUp(self):
"""Create a wind-speed and wind-gust cube with percentile coord."""
<|body_0|>
def test_basic(self):
"""Test that the function returns a Cube and Coord."""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_extract_percentile_data:
"""Test the extract_percentile_data method."""
def setUp(self):
"""Create a wind-speed and wind-gust cube with percentile coord."""
data = np.zeros((2, 2, 2, 2), dtype=np.float32)
self.wg_perc = 50.0
self.ws_perc = 95.0
self.cube_wg = ... | the_stack_v2_python_sparse | improver_tests/wind_calculations/wind_gust_diagnostic/test_WindGustDiagnostic.py | metoppv/improver | train | 101 |
a10ba72ceb7669164f1067115b1e9cc31704f7fb | [
"try:\n return int(str_val)\nexcept ValueError:\n return None",
"if str_val == 'False':\n return False\nreturn True"
] | <|body_start_0|>
try:
return int(str_val)
except ValueError:
return None
<|end_body_0|>
<|body_start_1|>
if str_val == 'False':
return False
return True
<|end_body_1|>
| converters | Converter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Converter:
"""converters"""
def str_to_int(str_val):
"""convert string to int :param str_val: the source string value :returns: the target integer value :raises ValueError: trigs when user provide an error str_val"""
<|body_0|>
def str_to_bool(str_val):
"""conver... | stack_v2_sparse_classes_75kplus_train_001101 | 694 | no_license | [
{
"docstring": "convert string to int :param str_val: the source string value :returns: the target integer value :raises ValueError: trigs when user provide an error str_val",
"name": "str_to_int",
"signature": "def str_to_int(str_val)"
},
{
"docstring": "convert string to boolean :param str_val... | 2 | null | Implement the Python class `Converter` described below.
Class description:
converters
Method signatures and docstrings:
- def str_to_int(str_val): convert string to int :param str_val: the source string value :returns: the target integer value :raises ValueError: trigs when user provide an error str_val
- def str_to_... | Implement the Python class `Converter` described below.
Class description:
converters
Method signatures and docstrings:
- def str_to_int(str_val): convert string to int :param str_val: the source string value :returns: the target integer value :raises ValueError: trigs when user provide an error str_val
- def str_to_... | 59bb703824ca08dfac1550c1e28fc3bc1028e123 | <|skeleton|>
class Converter:
"""converters"""
def str_to_int(str_val):
"""convert string to int :param str_val: the source string value :returns: the target integer value :raises ValueError: trigs when user provide an error str_val"""
<|body_0|>
def str_to_bool(str_val):
"""conver... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Converter:
"""converters"""
def str_to_int(str_val):
"""convert string to int :param str_val: the source string value :returns: the target integer value :raises ValueError: trigs when user provide an error str_val"""
try:
return int(str_val)
except ValueError:
... | the_stack_v2_python_sparse | venv/lib/python3.8/site-packages/eggit/converters.py | scottwedge/reporting-system | train | 0 |
23cd0953204e0b55805680051edfb1690b9c8ac2 | [
"self._renderer = renderer\nself._width = self._renderer.width\nself._height = self._renderer.height\nself._small = int(self._height / 20)\nself._extra_small = int(self._height / 25)\nself._lines = []",
"row = 1\nfor save in saves:\n txt = f'{save.nickname} - {save.progress}% - CREATED: {save.created_at} ( pre... | <|body_start_0|>
self._renderer = renderer
self._width = self._renderer.width
self._height = self._renderer.height
self._small = int(self._height / 20)
self._extra_small = int(self._height / 25)
self._lines = []
<|end_body_0|>
<|body_start_1|>
row = 1
for... | A class to represent load game view of UI. Attributes: renderer: Renderer object. | LoadGameView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoadGameView:
"""A class to represent load game view of UI. Attributes: renderer: Renderer object."""
def __init__(self, renderer):
"""Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_001102 | 1,967 | no_license | [
{
"docstring": "Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display.",
"name": "__init__",
"signature": "def __init__(self, renderer)"
},
{
"docstring": "Prepares all information to show for the renderer object. Informatio... | 2 | null | Implement the Python class `LoadGameView` described below.
Class description:
A class to represent load game view of UI. Attributes: renderer: Renderer object.
Method signatures and docstrings:
- def __init__(self, renderer): Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer... | Implement the Python class `LoadGameView` described below.
Class description:
A class to represent load game view of UI. Attributes: renderer: Renderer object.
Method signatures and docstrings:
- def __init__(self, renderer): Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer... | 29cd15dddff620de068a479595a5cb9aba855343 | <|skeleton|>
class LoadGameView:
"""A class to represent load game view of UI. Attributes: renderer: Renderer object."""
def __init__(self, renderer):
"""Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LoadGameView:
"""A class to represent load game view of UI. Attributes: renderer: Renderer object."""
def __init__(self, renderer):
"""Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display."""
self._renderer = rendere... | the_stack_v2_python_sparse | src/ui/load_game_view.py | TopiasHarjunpaa/ot-harjoitustyo | train | 0 |
055c4d78c1de2906bc018d6082e9f7222fc16ab6 | [
"if not hasattr(self, '_dimensions_cache'):\n self._dimensions_cache = self.get_image_dimensions()\nreturn self._dimensions_cache",
"close = self.closed\ntry:\n self.open()\n image = willow.Image.open(self)\n return image.get_size()\nfinally:\n if close:\n self.close()\n else:\n se... | <|body_start_0|>
if not hasattr(self, '_dimensions_cache'):
self._dimensions_cache = self.get_image_dimensions()
return self._dimensions_cache
<|end_body_0|>
<|body_start_1|>
close = self.closed
try:
self.open()
image = willow.Image.open(self)
... | Override the ImageFieldFile in order to use Willow instead of Pillow. | WagtailImageFieldFile | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WagtailImageFieldFile:
"""Override the ImageFieldFile in order to use Willow instead of Pillow."""
def _get_image_dimensions(self):
"""override _get_image_dimensions to call our own get_image_dimensions."""
<|body_0|>
def get_image_dimensions(self):
"""The upstre... | stack_v2_sparse_classes_75kplus_train_001103 | 42,364 | permissive | [
{
"docstring": "override _get_image_dimensions to call our own get_image_dimensions.",
"name": "_get_image_dimensions",
"signature": "def _get_image_dimensions(self)"
},
{
"docstring": "The upstream ImageFieldFile calls a local function get_image_dimensions. In this implementation we've made get... | 2 | stack_v2_sparse_classes_30k_train_047273 | Implement the Python class `WagtailImageFieldFile` described below.
Class description:
Override the ImageFieldFile in order to use Willow instead of Pillow.
Method signatures and docstrings:
- def _get_image_dimensions(self): override _get_image_dimensions to call our own get_image_dimensions.
- def get_image_dimensi... | Implement the Python class `WagtailImageFieldFile` described below.
Class description:
Override the ImageFieldFile in order to use Willow instead of Pillow.
Method signatures and docstrings:
- def _get_image_dimensions(self): override _get_image_dimensions to call our own get_image_dimensions.
- def get_image_dimensi... | 06a7bc6124bf62675c09fbe0a4ed9bbac183e025 | <|skeleton|>
class WagtailImageFieldFile:
"""Override the ImageFieldFile in order to use Willow instead of Pillow."""
def _get_image_dimensions(self):
"""override _get_image_dimensions to call our own get_image_dimensions."""
<|body_0|>
def get_image_dimensions(self):
"""The upstre... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WagtailImageFieldFile:
"""Override the ImageFieldFile in order to use Willow instead of Pillow."""
def _get_image_dimensions(self):
"""override _get_image_dimensions to call our own get_image_dimensions."""
if not hasattr(self, '_dimensions_cache'):
self._dimensions_cache = se... | the_stack_v2_python_sparse | wagtail/images/models.py | wagtail/wagtail | train | 12,974 |
59978cfa0309fc7502029c8c73b9a9963e0ca9e6 | [
"import heapq\n\ndef gcd(A, B):\n if B == 0:\n return A\n return gcd(B, A % B)\nif A < B:\n A, B = (B, A)\nc = gcd(A, B)\nmaxmin = A * B // c\nt1 = maxmin // A + maxmin // B - 1\nd = N // t1\nr = N % t1\ns = d * maxmin\nprint(d, r, maxmin, s)\nif r == 0:\n return s % (10 ** 9 + 7)\nh = [s + B, s ... | <|body_start_0|>
import heapq
def gcd(A, B):
if B == 0:
return A
return gcd(B, A % B)
if A < B:
A, B = (B, A)
c = gcd(A, B)
maxmin = A * B // c
t1 = maxmin // A + maxmin // B - 1
d = N // t1
r = N % t1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nthMagicalNumber(self, N, A, B):
""":type N: int :type A: int :type B: int :rtype: int 144 ms"""
<|body_0|>
def nthMagicalNumber_1(self, N, A, B):
"""28MS :param N: :param A: :param B: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_001104 | 2,205 | no_license | [
{
"docstring": ":type N: int :type A: int :type B: int :rtype: int 144 ms",
"name": "nthMagicalNumber",
"signature": "def nthMagicalNumber(self, N, A, B)"
},
{
"docstring": "28MS :param N: :param A: :param B: :return:",
"name": "nthMagicalNumber_1",
"signature": "def nthMagicalNumber_1(s... | 2 | stack_v2_sparse_classes_30k_train_016686 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nthMagicalNumber(self, N, A, B): :type N: int :type A: int :type B: int :rtype: int 144 ms
- def nthMagicalNumber_1(self, N, A, B): 28MS :param N: :param A: :param B: :return... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nthMagicalNumber(self, N, A, B): :type N: int :type A: int :type B: int :rtype: int 144 ms
- def nthMagicalNumber_1(self, N, A, B): 28MS :param N: :param A: :param B: :return... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def nthMagicalNumber(self, N, A, B):
""":type N: int :type A: int :type B: int :rtype: int 144 ms"""
<|body_0|>
def nthMagicalNumber_1(self, N, A, B):
"""28MS :param N: :param A: :param B: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def nthMagicalNumber(self, N, A, B):
""":type N: int :type A: int :type B: int :rtype: int 144 ms"""
import heapq
def gcd(A, B):
if B == 0:
return A
return gcd(B, A % B)
if A < B:
A, B = (B, A)
c = gcd(A, B)... | the_stack_v2_python_sparse | NthMagicalNumber_HARD_878.py | 953250587/leetcode-python | train | 2 | |
ed62a18590d04c2e0abd79169cc74f77220acd95 | [
"self.nuts = [Coconut(variety) for variety in ['middle eastern', 'south asian', 'american']]\nself.weights = [2.5, 3.0, 3.5]\nfor i in range(0, 3):\n self.assertEqual(self.nuts[i]._Coconut__weight, self.weights[i], 'The weight is wrong')",
"varieties = [Coconut(variety) for variety in ['middle eastern', 'south... | <|body_start_0|>
self.nuts = [Coconut(variety) for variety in ['middle eastern', 'south asian', 'american']]
self.weights = [2.5, 3.0, 3.5]
for i in range(0, 3):
self.assertEqual(self.nuts[i]._Coconut__weight, self.weights[i], 'The weight is wrong')
<|end_body_0|>
<|body_start_1|>
... | TestCoconuts | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCoconuts:
def test_weight(self):
"""Tests that different coconut types each have a different weight"""
<|body_0|>
def test_total_weight(self):
"""Tests that the sum of a specified number of coconuts of each type returned matches the expected total"""
<|bo... | stack_v2_sparse_classes_75kplus_train_001105 | 2,241 | no_license | [
{
"docstring": "Tests that different coconut types each have a different weight",
"name": "test_weight",
"signature": "def test_weight(self)"
},
{
"docstring": "Tests that the sum of a specified number of coconuts of each type returned matches the expected total",
"name": "test_total_weight"... | 3 | stack_v2_sparse_classes_30k_train_012118 | Implement the Python class `TestCoconuts` described below.
Class description:
Implement the TestCoconuts class.
Method signatures and docstrings:
- def test_weight(self): Tests that different coconut types each have a different weight
- def test_total_weight(self): Tests that the sum of a specified number of coconuts... | Implement the Python class `TestCoconuts` described below.
Class description:
Implement the TestCoconuts class.
Method signatures and docstrings:
- def test_weight(self): Tests that different coconut types each have a different weight
- def test_total_weight(self): Tests that the sum of a specified number of coconuts... | 4ca74dd054be17e7a57da891c5d239e3f915d3f1 | <|skeleton|>
class TestCoconuts:
def test_weight(self):
"""Tests that different coconut types each have a different weight"""
<|body_0|>
def test_total_weight(self):
"""Tests that the sum of a specified number of coconuts of each type returned matches the expected total"""
<|bo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestCoconuts:
def test_weight(self):
"""Tests that different coconut types each have a different weight"""
self.nuts = [Coconut(variety) for variety in ['middle eastern', 'south asian', 'american']]
self.weights = [2.5, 3.0, 3.5]
for i in range(0, 3):
self.assertEqu... | the_stack_v2_python_sparse | Lesson 2 - Converting Data Into Structured Objects/project/attempt_1/test_coconuts.py | jmwoloso/Python_3 | train | 0 | |
6e3d45fa4b81340a1eeea23533780054804ca0b7 | [
"if isinstance(data, str):\n data = json.loads(data)\ntry:\n customer = QueryCustomersModel.objects.get(id=data['id'])\n customer.update(name=data.get('name', customer.name), phone=data.get('phone', customer.phone), email=data.get('email', customer.email), full_name=data.get('full_name', customer.full_name... | <|body_start_0|>
if isinstance(data, str):
data = json.loads(data)
try:
customer = QueryCustomersModel.objects.get(id=data['id'])
customer.update(name=data.get('name', customer.name), phone=data.get('phone', customer.phone), email=data.get('email', customer.email), fu... | Query | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Query:
def normalize_db(self, data):
"""with the incoming payload: check to see if the record already exists in the query database if so, updated it with the new replicated values, otherwise add the record to the query database"""
<|body_0|>
def list(self, num_page=1, limit=... | stack_v2_sparse_classes_75kplus_train_001106 | 12,821 | no_license | [
{
"docstring": "with the incoming payload: check to see if the record already exists in the query database if so, updated it with the new replicated values, otherwise add the record to the query database",
"name": "normalize_db",
"signature": "def normalize_db(self, data)"
},
{
"docstring": "ret... | 3 | stack_v2_sparse_classes_30k_train_051041 | Implement the Python class `Query` described below.
Class description:
Implement the Query class.
Method signatures and docstrings:
- def normalize_db(self, data): with the incoming payload: check to see if the record already exists in the query database if so, updated it with the new replicated values, otherwise add... | Implement the Python class `Query` described below.
Class description:
Implement the Query class.
Method signatures and docstrings:
- def normalize_db(self, data): with the incoming payload: check to see if the record already exists in the query database if so, updated it with the new replicated values, otherwise add... | 3f4c93c631e5d5b52acd2ce11e220ff3fbec07b6 | <|skeleton|>
class Query:
def normalize_db(self, data):
"""with the incoming payload: check to see if the record already exists in the query database if so, updated it with the new replicated values, otherwise add the record to the query database"""
<|body_0|>
def list(self, num_page=1, limit=... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Query:
def normalize_db(self, data):
"""with the incoming payload: check to see if the record already exists in the query database if so, updated it with the new replicated values, otherwise add the record to the query database"""
if isinstance(data, str):
data = json.loads(data)
... | the_stack_v2_python_sparse | customers/customers/service.py | bsmi021/eahub_shopco | train | 0 | |
81a8a2cb11688874d8203235090f5aab4e337ab4 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn AuthenticationStrengthRoot()",
"from .authentication_method_mode_detail import AuthenticationMethodModeDetail\nfrom .authentication_method_modes import AuthenticationMethodModes\nfrom .authentication_strength_policy import Authenticati... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return AuthenticationStrengthRoot()
<|end_body_0|>
<|body_start_1|>
from .authentication_method_mode_detail import AuthenticationMethodModeDetail
from .authentication_method_modes import Authen... | AuthenticationStrengthRoot | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthenticationStrengthRoot:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationStrengthRoot:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and... | stack_v2_sparse_classes_75kplus_train_001107 | 3,660 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: AuthenticationStrengthRoot",
"name": "create_from_discriminator_value",
"signature": "def create_from_discri... | 3 | stack_v2_sparse_classes_30k_train_045602 | Implement the Python class `AuthenticationStrengthRoot` described below.
Class description:
Implement the AuthenticationStrengthRoot class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationStrengthRoot: Creates a new instance of the appropr... | Implement the Python class `AuthenticationStrengthRoot` described below.
Class description:
Implement the AuthenticationStrengthRoot class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationStrengthRoot: Creates a new instance of the appropr... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AuthenticationStrengthRoot:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationStrengthRoot:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AuthenticationStrengthRoot:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationStrengthRoot:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ob... | the_stack_v2_python_sparse | msgraph/generated/models/authentication_strength_root.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
c5c8881bd0be191f11f319032efc6f9d1dd40f21 | [
"res = defaultdict(list)\nfor s in strs:\n res[tuple(sorted(s))].append(s)\nreturn list(res.values())",
"res = defaultdict(list)\nfor s in strs:\n count = [0] * 26\n for c in s:\n count[ord(c) - ord('a')] += 1\n res[tuple(count)].append(s)\nreturn list(res.values())"
] | <|body_start_0|>
res = defaultdict(list)
for s in strs:
res[tuple(sorted(s))].append(s)
return list(res.values())
<|end_body_0|>
<|body_start_1|>
res = defaultdict(list)
for s in strs:
count = [0] * 26
for c in s:
count[ord(c) ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def groupAnagrams(self, strs: list[str]) -> list[str]:
"""方法一：排序数组分类 思路 当且仅当它们的排序字符串相等时，两个字符串是字母异位词"""
<|body_0|>
def fun2(self, strs):
"""方法二：按计数分类 思路 当且仅当它们的字符计数（每个字符的出现次数）相同时，两个字符串是字母异位词。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_001108 | 858 | no_license | [
{
"docstring": "方法一：排序数组分类 思路 当且仅当它们的排序字符串相等时，两个字符串是字母异位词",
"name": "groupAnagrams",
"signature": "def groupAnagrams(self, strs: list[str]) -> list[str]"
},
{
"docstring": "方法二：按计数分类 思路 当且仅当它们的字符计数（每个字符的出现次数）相同时，两个字符串是字母异位词。",
"name": "fun2",
"signature": "def fun2(self, strs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_042378 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams(self, strs: list[str]) -> list[str]: 方法一：排序数组分类 思路 当且仅当它们的排序字符串相等时，两个字符串是字母异位词
- def fun2(self, strs): 方法二：按计数分类 思路 当且仅当它们的字符计数（每个字符的出现次数）相同时，两个字符串是字母异位词。 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams(self, strs: list[str]) -> list[str]: 方法一：排序数组分类 思路 当且仅当它们的排序字符串相等时，两个字符串是字母异位词
- def fun2(self, strs): 方法二：按计数分类 思路 当且仅当它们的字符计数（每个字符的出现次数）相同时，两个字符串是字母异位词。
<|sk... | 0b10f5731690da7998add288e4b0b87d5d71a97e | <|skeleton|>
class Solution:
def groupAnagrams(self, strs: list[str]) -> list[str]:
"""方法一：排序数组分类 思路 当且仅当它们的排序字符串相等时，两个字符串是字母异位词"""
<|body_0|>
def fun2(self, strs):
"""方法二：按计数分类 思路 当且仅当它们的字符计数（每个字符的出现次数）相同时，两个字符串是字母异位词。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def groupAnagrams(self, strs: list[str]) -> list[str]:
"""方法一：排序数组分类 思路 当且仅当它们的排序字符串相等时，两个字符串是字母异位词"""
res = defaultdict(list)
for s in strs:
res[tuple(sorted(s))].append(s)
return list(res.values())
def fun2(self, strs):
"""方法二：按计数分类 思路 当且仅当它... | the_stack_v2_python_sparse | leetcode/leetcode/49.字母异位词分组.py | GGL12/myStudy | train | 0 | |
f4c9340eefcb732230114ea40ac0669179df6f2f | [
"self.domain = domain\nself.web_messaging = web_messaging\nself.height = height\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\ndomain = dictionary.get('Domain')\nweb_messaging = dictionary.get('WebMessaging')\nheight = dictionary.get('Height')\nfor key in cls._name... | <|body_start_0|>
self.domain = domain
self.web_messaging = web_messaging
self.height = height
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
domain = dictionary.get('Domain')
web_m... | Implementation of the 'iFrameSettings' model. iFrame settings REMARK! If using iframe the parent site have to be on https Attributes: domain (string): The domain of the site hosting the iFrame, this is used for the CSP policy and must be correct. web_messaging (bool): Should WebMessaging be used for redirect of the iFr... | IFrameSettings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IFrameSettings:
"""Implementation of the 'iFrameSettings' model. iFrame settings REMARK! If using iframe the parent site have to be on https Attributes: domain (string): The domain of the site hosting the iFrame, this is used for the CSP policy and must be correct. web_messaging (bool): Should We... | stack_v2_sparse_classes_75kplus_train_001109 | 2,722 | permissive | [
{
"docstring": "Constructor for the IFrameSettings class",
"name": "__init__",
"signature": "def __init__(self, domain=None, web_messaging=None, height=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A diction... | 2 | null | Implement the Python class `IFrameSettings` described below.
Class description:
Implementation of the 'iFrameSettings' model. iFrame settings REMARK! If using iframe the parent site have to be on https Attributes: domain (string): The domain of the site hosting the iFrame, this is used for the CSP policy and must be c... | Implement the Python class `IFrameSettings` described below.
Class description:
Implementation of the 'iFrameSettings' model. iFrame settings REMARK! If using iframe the parent site have to be on https Attributes: domain (string): The domain of the site hosting the iFrame, this is used for the CSP policy and must be c... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class IFrameSettings:
"""Implementation of the 'iFrameSettings' model. iFrame settings REMARK! If using iframe the parent site have to be on https Attributes: domain (string): The domain of the site hosting the iFrame, this is used for the CSP policy and must be correct. web_messaging (bool): Should We... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IFrameSettings:
"""Implementation of the 'iFrameSettings' model. iFrame settings REMARK! If using iframe the parent site have to be on https Attributes: domain (string): The domain of the site hosting the iFrame, this is used for the CSP policy and must be correct. web_messaging (bool): Should WebMessaging be... | the_stack_v2_python_sparse | idfy_rest_client/models/i_frame_settings.py | dealflowteam/Idfy | train | 0 |
114dd65d8d613ffa225a4399c84274f74e7e5fde | [
"self.onefuzz._warn_preview(PreviewFeature.job_templates)\nself.onefuzz.logger.debug('listing job templates')\nreturn self._req_model_list('GET', JobTemplateIndex, data=JobTemplateGet(name=None))",
"self.onefuzz._warn_preview(PreviewFeature.job_templates)\nself.onefuzz.logger.debug('get job template')\nreturn sel... | <|body_start_0|>
self.onefuzz._warn_preview(PreviewFeature.job_templates)
self.onefuzz.logger.debug('listing job templates')
return self._req_model_list('GET', JobTemplateIndex, data=JobTemplateGet(name=None))
<|end_body_0|>
<|body_start_1|>
self.onefuzz._warn_preview(PreviewFeature.job... | Manage Job Templates | Manage | [
"LicenseRef-scancode-generic-cla",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Manage:
"""Manage Job Templates"""
def list(self) -> List[JobTemplateIndex]:
"""List templates"""
<|body_0|>
def get(self, name: str) -> JobTemplate:
"""Get an existing Job Template"""
<|body_1|>
def upload(self, name: str, template: JobTemplate) -> ... | stack_v2_sparse_classes_75kplus_train_001110 | 1,790 | permissive | [
{
"docstring": "List templates",
"name": "list",
"signature": "def list(self) -> List[JobTemplateIndex]"
},
{
"docstring": "Get an existing Job Template",
"name": "get",
"signature": "def get(self, name: str) -> JobTemplate"
},
{
"docstring": "Upload a Job Template",
"name": ... | 4 | stack_v2_sparse_classes_30k_train_014198 | Implement the Python class `Manage` described below.
Class description:
Manage Job Templates
Method signatures and docstrings:
- def list(self) -> List[JobTemplateIndex]: List templates
- def get(self, name: str) -> JobTemplate: Get an existing Job Template
- def upload(self, name: str, template: JobTemplate) -> Bool... | Implement the Python class `Manage` described below.
Class description:
Manage Job Templates
Method signatures and docstrings:
- def list(self) -> List[JobTemplateIndex]: List templates
- def get(self, name: str) -> JobTemplate: Get an existing Job Template
- def upload(self, name: str, template: JobTemplate) -> Bool... | f141050bbbf7ddc6f42881cb82ded38e2924fdb3 | <|skeleton|>
class Manage:
"""Manage Job Templates"""
def list(self) -> List[JobTemplateIndex]:
"""List templates"""
<|body_0|>
def get(self, name: str) -> JobTemplate:
"""Get an existing Job Template"""
<|body_1|>
def upload(self, name: str, template: JobTemplate) -> ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Manage:
"""Manage Job Templates"""
def list(self) -> List[JobTemplateIndex]:
"""List templates"""
self.onefuzz._warn_preview(PreviewFeature.job_templates)
self.onefuzz.logger.debug('listing job templates')
return self._req_model_list('GET', JobTemplateIndex, data=JobTempla... | the_stack_v2_python_sparse | src/cli/onefuzz/job_templates/manage.py | microsoft/onefuzz | train | 2,998 |
341a71566b9a7ccdb72765b6112b42e696647dc0 | [
"if architecture not in _OUTPUT_DIM.keys():\n raise ValueError('Architecture {} is not supported.'.format(architecture))\nsuper(GlobalFeatureNet, self).__init__()\ndim = _OUTPUT_DIM[architecture]\nif pretrained:\n net_in = getattr(tf.keras.applications, architecture)(include_top=False, weights='imagenet')\nel... | <|body_start_0|>
if architecture not in _OUTPUT_DIM.keys():
raise ValueError('Architecture {} is not supported.'.format(architecture))
super(GlobalFeatureNet, self).__init__()
dim = _OUTPUT_DIM[architecture]
if pretrained:
net_in = getattr(tf.keras.applications, a... | Instantiates global model for image retrieval. This class implements the [GlobalFeatureNet]( https://arxiv.org/abs/1711.02512) for image retrieval. The model uses a user-defined model as a backbone. | GlobalFeatureNet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GlobalFeatureNet:
"""Instantiates global model for image retrieval. This class implements the [GlobalFeatureNet]( https://arxiv.org/abs/1711.02512) for image retrieval. The model uses a user-defined model as a backbone."""
def __init__(self, architecture='ResNet101', pooling='gem', whitening... | stack_v2_sparse_classes_75kplus_train_001111 | 10,634 | permissive | [
{
"docstring": "GlobalFeatureNet network initialization. Args: architecture: Network backbone. pooling: Pooling method used 'mac'/'spoc'/'gem'. whitening: Bool, whether to use whitening. pretrained: Bool, whether to initialize the network with the weights pretrained on ImageNet. data_root: String, path to the d... | 3 | stack_v2_sparse_classes_30k_train_013946 | Implement the Python class `GlobalFeatureNet` described below.
Class description:
Instantiates global model for image retrieval. This class implements the [GlobalFeatureNet]( https://arxiv.org/abs/1711.02512) for image retrieval. The model uses a user-defined model as a backbone.
Method signatures and docstrings:
- d... | Implement the Python class `GlobalFeatureNet` described below.
Class description:
Instantiates global model for image retrieval. This class implements the [GlobalFeatureNet]( https://arxiv.org/abs/1711.02512) for image retrieval. The model uses a user-defined model as a backbone.
Method signatures and docstrings:
- d... | d3507b550a3ade40cade60a79eb5b8978b56c7ae | <|skeleton|>
class GlobalFeatureNet:
"""Instantiates global model for image retrieval. This class implements the [GlobalFeatureNet]( https://arxiv.org/abs/1711.02512) for image retrieval. The model uses a user-defined model as a backbone."""
def __init__(self, architecture='ResNet101', pooling='gem', whitening... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GlobalFeatureNet:
"""Instantiates global model for image retrieval. This class implements the [GlobalFeatureNet]( https://arxiv.org/abs/1711.02512) for image retrieval. The model uses a user-defined model as a backbone."""
def __init__(self, architecture='ResNet101', pooling='gem', whitening=False, pretr... | the_stack_v2_python_sparse | research/delf/delf/python/training/model/global_model.py | jianzhnie/models | train | 2 |
4621d21bed8d7a6cee75c40f3b148beced6c1c80 | [
"from mercury.plugin import AbstractFactory, PUMappingStrategy\nself.edc_id: str = edc_config.edc_id\nself.srv_priority: list[str] = srv_priority\nself.pu_twins: list[ProcessingUnit] = list()\nfor pu_id, pu_config in edc_config.pu_configs.items():\n self.pu_twins.append(ProcessingUnit(f'{pu_id}_slicer', pu_id, p... | <|body_start_0|>
from mercury.plugin import AbstractFactory, PUMappingStrategy
self.edc_id: str = edc_config.edc_id
self.srv_priority: list[str] = srv_priority
self.pu_twins: list[ProcessingUnit] = list()
for pu_id, pu_config in edc_config.pu_configs.items():
self.pu_... | EDCResourceSlicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EDCResourceSlicer:
def __init__(self, edc_config: EdgeDataCenterConfig, srv_priority: list[str]):
"""Edge Data Center resource slicer. :param srv_priority: list of services in decreasing priority order. The resource slicer will allocate first resources for the services with higher priori... | stack_v2_sparse_classes_75kplus_train_001112 | 2,763 | permissive | [
{
"docstring": "Edge Data Center resource slicer. :param srv_priority: list of services in decreasing priority order. The resource slicer will allocate first resources for the services with higher priority. :param edc_config: configuration parameters of the EDC.",
"name": "__init__",
"signature": "def _... | 2 | stack_v2_sparse_classes_30k_train_006601 | Implement the Python class `EDCResourceSlicer` described below.
Class description:
Implement the EDCResourceSlicer class.
Method signatures and docstrings:
- def __init__(self, edc_config: EdgeDataCenterConfig, srv_priority: list[str]): Edge Data Center resource slicer. :param srv_priority: list of services in decrea... | Implement the Python class `EDCResourceSlicer` described below.
Class description:
Implement the EDCResourceSlicer class.
Method signatures and docstrings:
- def __init__(self, edc_config: EdgeDataCenterConfig, srv_priority: list[str]): Edge Data Center resource slicer. :param srv_priority: list of services in decrea... | cb425605de3341d27ce43fb326b300cb8ac781f6 | <|skeleton|>
class EDCResourceSlicer:
def __init__(self, edc_config: EdgeDataCenterConfig, srv_priority: list[str]):
"""Edge Data Center resource slicer. :param srv_priority: list of services in decreasing priority order. The resource slicer will allocate first resources for the services with higher priori... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EDCResourceSlicer:
def __init__(self, edc_config: EdgeDataCenterConfig, srv_priority: list[str]):
"""Edge Data Center resource slicer. :param srv_priority: list of services in decreasing priority order. The resource slicer will allocate first resources for the services with higher priority. :param edc... | the_stack_v2_python_sparse | mercury/model/edcs/edc/r_manager/slicer.py | greenlsi/mercury_mso_framework | train | 2 | |
7ca47e81214e5546d9461b862e88b271a5d86ded | [
"if not isinstance(user, User):\n raise TypeError()\nq = self._klass.gql('WHERE user = :1 AND has = \"done:T\" ORDER BY modified DESC', user)\np = PagedQuery(q, id=query_id)\nreturn [p.id, p.fetch_page(page)]",
"if not isinstance(user, User):\n raise TypeError()\nq = self._klass.gql('WHERE user = :1 AND has... | <|body_start_0|>
if not isinstance(user, User):
raise TypeError()
q = self._klass.gql('WHERE user = :1 AND has = "done:T" ORDER BY modified DESC', user)
p = PagedQuery(q, id=query_id)
return [p.id, p.fetch_page(page)]
<|end_body_0|>
<|body_start_1|>
if not isinstance... | AlertHelper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlertHelper:
def get_by_user_done(self, user, page=1, query_id=None):
"""Obtiene una lista con todos los Eventos de un usuario"""
<|body_0|>
def get_by_user_undone(self, user, page=1, query_id=None):
"""Obtiene una lista con todos los Eventos de un usuario"""
... | stack_v2_sparse_classes_75kplus_train_001113 | 3,112 | no_license | [
{
"docstring": "Obtiene una lista con todos los Eventos de un usuario",
"name": "get_by_user_done",
"signature": "def get_by_user_done(self, user, page=1, query_id=None)"
},
{
"docstring": "Obtiene una lista con todos los Eventos de un usuario",
"name": "get_by_user_undone",
"signature":... | 2 | null | Implement the Python class `AlertHelper` described below.
Class description:
Implement the AlertHelper class.
Method signatures and docstrings:
- def get_by_user_done(self, user, page=1, query_id=None): Obtiene una lista con todos los Eventos de un usuario
- def get_by_user_undone(self, user, page=1, query_id=None): ... | Implement the Python class `AlertHelper` described below.
Class description:
Implement the AlertHelper class.
Method signatures and docstrings:
- def get_by_user_done(self, user, page=1, query_id=None): Obtiene una lista con todos los Eventos de un usuario
- def get_by_user_undone(self, user, page=1, query_id=None): ... | f8315a2d37db6dca26c8b4af100fd6f1d6fcae20 | <|skeleton|>
class AlertHelper:
def get_by_user_done(self, user, page=1, query_id=None):
"""Obtiene una lista con todos los Eventos de un usuario"""
<|body_0|>
def get_by_user_undone(self, user, page=1, query_id=None):
"""Obtiene una lista con todos los Eventos de un usuario"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AlertHelper:
def get_by_user_done(self, user, page=1, query_id=None):
"""Obtiene una lista con todos los Eventos de un usuario"""
if not isinstance(user, User):
raise TypeError()
q = self._klass.gql('WHERE user = :1 AND has = "done:T" ORDER BY modified DESC', user)
... | the_stack_v2_python_sparse | trunk/src/webapp/geoalert/helpers.py | hhkaos/GeoRemindMe_Web | train | 0 | |
01d74009f652435a584d412cb72f39071a096ce0 | [
"self._targets_and_priorities = targets_and_priorities\nself._queue_name = queue_name\nsuper(NotificationPikaPoller, self).__init__(pika_engine, batch_size, batch_timeout, prefetch_count, pika_drv_msg.PikaIncomingMessage)",
"queues_to_consume = []\nfor target, priority in self._targets_and_priorities:\n routin... | <|body_start_0|>
self._targets_and_priorities = targets_and_priorities
self._queue_name = queue_name
super(NotificationPikaPoller, self).__init__(pika_engine, batch_size, batch_timeout, prefetch_count, pika_drv_msg.PikaIncomingMessage)
<|end_body_0|>
<|body_start_1|>
queues_to_consume =... | PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific | NotificationPikaPoller | [
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationPikaPoller:
"""PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific"""
def __init__(self, pika_engine, targets_and_priorities, batch_size, batch_timeout, prefetch_count, queue_name=None):
"""Adds targ... | stack_v2_sparse_classes_75kplus_train_001114 | 22,231 | permissive | [
{
"docstring": "Adds targets_and_priorities and queue_name parameter for declaring exchanges and queues used for notification delivery :param pika_engine: PikaEngine, shared object with configuration and shared driver functionality :param targets_and_priorities: list of (target, priority), defines default queue... | 2 | stack_v2_sparse_classes_30k_train_030872 | Implement the Python class `NotificationPikaPoller` described below.
Class description:
PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific
Method signatures and docstrings:
- def __init__(self, pika_engine, targets_and_priorities, batch_size, b... | Implement the Python class `NotificationPikaPoller` described below.
Class description:
PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific
Method signatures and docstrings:
- def __init__(self, pika_engine, targets_and_priorities, batch_size, b... | c01951b33e278de9e769c2d0609c0be61d2cb26b | <|skeleton|>
class NotificationPikaPoller:
"""PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific"""
def __init__(self, pika_engine, targets_and_priorities, batch_size, batch_timeout, prefetch_count, queue_name=None):
"""Adds targ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NotificationPikaPoller:
"""PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific"""
def __init__(self, pika_engine, targets_and_priorities, batch_size, batch_timeout, prefetch_count, queue_name=None):
"""Adds targets_and_prior... | the_stack_v2_python_sparse | filesystems/vnx_rootfs_lxc_ubuntu64-16.04-v025-openstack-compute/rootfs/usr/lib/python2.7/dist-packages/oslo_messaging/_drivers/pika_driver/pika_poller.py | juancarlosdiaztorres/Ansible-OpenStack | train | 0 |
c0a26c4ee40c5e7a1bc91eb030c4c311b14be04b | [
"self._filter_configuration = filter_configuration\nself._output_format = output_format\nself.max_reports_per_category = max_reports_per_category\nself.min_confidence = min_confidence\nself.stderr_write = stderr_write",
"if confidence_in_error < self.min_confidence:\n return False\nreturn self._filter_configur... | <|body_start_0|>
self._filter_configuration = filter_configuration
self._output_format = output_format
self.max_reports_per_category = max_reports_per_category
self.min_confidence = min_confidence
self.stderr_write = stderr_write
<|end_body_0|>
<|body_start_1|>
if confid... | Stores configuration values for the StyleProcessor class. Attributes: min_confidence: An integer between 1 and 5 inclusive that is the minimum confidence level of style errors to report. max_reports_per_category: The maximum number of errors to report per category, per file. stderr_write: A function that takes a string... | StyleProcessorConfiguration | [
"LGPL-2.0-or-later",
"LicenseRef-scancode-warranty-disclaimer",
"LGPL-2.1-only",
"GPL-1.0-or-later",
"GPL-2.0-only",
"LGPL-2.0-only",
"BSD-2-Clause",
"LicenseRef-scancode-other-copyleft",
"BSD-3-Clause",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StyleProcessorConfiguration:
"""Stores configuration values for the StyleProcessor class. Attributes: min_confidence: An integer between 1 and 5 inclusive that is the minimum confidence level of style errors to report. max_reports_per_category: The maximum number of errors to report per category,... | stack_v2_sparse_classes_75kplus_train_001115 | 23,775 | permissive | [
{
"docstring": "Create a StyleProcessorConfiguration instance. Args: filter_configuration: A FilterConfiguration instance. The default is the \"empty\" filter configuration, which means that all errors should be checked. max_reports_per_category: The maximum number of errors to report per category, per file. mi... | 3 | stack_v2_sparse_classes_30k_train_037513 | Implement the Python class `StyleProcessorConfiguration` described below.
Class description:
Stores configuration values for the StyleProcessor class. Attributes: min_confidence: An integer between 1 and 5 inclusive that is the minimum confidence level of style errors to report. max_reports_per_category: The maximum n... | Implement the Python class `StyleProcessorConfiguration` described below.
Class description:
Stores configuration values for the StyleProcessor class. Attributes: min_confidence: An integer between 1 and 5 inclusive that is the minimum confidence level of style errors to report. max_reports_per_category: The maximum n... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class StyleProcessorConfiguration:
"""Stores configuration values for the StyleProcessor class. Attributes: min_confidence: An integer between 1 and 5 inclusive that is the minimum confidence level of style errors to report. max_reports_per_category: The maximum number of errors to report per category,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StyleProcessorConfiguration:
"""Stores configuration values for the StyleProcessor class. Attributes: min_confidence: An integer between 1 and 5 inclusive that is the minimum confidence level of style errors to report. max_reports_per_category: The maximum number of errors to report per category, per file. st... | the_stack_v2_python_sparse | third_party/blink/tools/blinkpy/style/checker.py | chromium/chromium | train | 17,408 |
6cfee43b0338e9d172c4ca80bc8a6451963240fd | [
"super().__init__()\nself.conv1 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True)\nself.conv2 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True)\nself.relu = nn.ReLU(inplace=True)",
"out = self.relu(x)\nout = self.conv1(out)\nout = self.relu(out)\nout = sel... | <|body_start_0|>
super().__init__()
self.conv1 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True)
self.conv2 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True)
self.relu = nn.ReLU(inplace=True)
<|end_body_0|>
<|body_start_1|>
... | Residual convolution module. | ResidualConvUnit | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResidualConvUnit:
"""Residual convolution module."""
def __init__(self, features):
"""Init. Args: features (int): number of features"""
<|body_0|>
def forward(self, x):
"""Forward pass. Args: x (tensor): input Returns: tensor: output"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus_train_001116 | 17,410 | permissive | [
{
"docstring": "Init. Args: features (int): number of features",
"name": "__init__",
"signature": "def __init__(self, features)"
},
{
"docstring": "Forward pass. Args: x (tensor): input Returns: tensor: output",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_031580 | Implement the Python class `ResidualConvUnit` described below.
Class description:
Residual convolution module.
Method signatures and docstrings:
- def __init__(self, features): Init. Args: features (int): number of features
- def forward(self, x): Forward pass. Args: x (tensor): input Returns: tensor: output | Implement the Python class `ResidualConvUnit` described below.
Class description:
Residual convolution module.
Method signatures and docstrings:
- def __init__(self, features): Init. Args: features (int): number of features
- def forward(self, x): Forward pass. Args: x (tensor): input Returns: tensor: output
<|skele... | a00c3619bf4042e446e1919087f0b09fe9fa3a65 | <|skeleton|>
class ResidualConvUnit:
"""Residual convolution module."""
def __init__(self, features):
"""Init. Args: features (int): number of features"""
<|body_0|>
def forward(self, x):
"""Forward pass. Args: x (tensor): input Returns: tensor: output"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResidualConvUnit:
"""Residual convolution module."""
def __init__(self, features):
"""Init. Args: features (int): number of features"""
super().__init__()
self.conv1 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True)
self.conv2 = nn.Conv2d(featu... | the_stack_v2_python_sparse | nasws/cnn/search_space/monodepth/models/blocks.py | kcyu2014/nas-landmarkreg | train | 10 |
d925d5d9b898cc2875db4b9bf2c51221e80f63be | [
"self.fat_tensor, paths = torch.load(os.path.join('..', visual_features_pth))\nself.mapper = dict(zip(paths, range(len(paths))))\nassert len(paths) == self.fat_tensor.size(0)\nself.pad = [0.0] * 4096\nself.max_len_images = max_len_images",
"images = [self.fat_tensor[self.mapper[p]].numpy().tolist() for p in image... | <|body_start_0|>
self.fat_tensor, paths = torch.load(os.path.join('..', visual_features_pth))
self.mapper = dict(zip(paths, range(len(paths))))
assert len(paths) == self.fat_tensor.size(0)
self.pad = [0.0] * 4096
self.max_len_images = max_len_images
<|end_body_0|>
<|body_start_1... | ImagesUnit | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImagesUnit:
def __init__(self, visual_features_pth: str, max_len_images: int):
"""Parameters ---------- visual_features_pth: str the path to pre-extracted features from images max_len_images: str the maxinum number of images used"""
<|body_0|>
def transform(self, images: str... | stack_v2_sparse_classes_75kplus_train_001117 | 7,523 | permissive | [
{
"docstring": "Parameters ---------- visual_features_pth: str the path to pre-extracted features from images max_len_images: str the maxinum number of images used",
"name": "__init__",
"signature": "def __init__(self, visual_features_pth: str, max_len_images: int)"
},
{
"docstring": "Process in... | 2 | stack_v2_sparse_classes_30k_train_040974 | Implement the Python class `ImagesUnit` described below.
Class description:
Implement the ImagesUnit class.
Method signatures and docstrings:
- def __init__(self, visual_features_pth: str, max_len_images: int): Parameters ---------- visual_features_pth: str the path to pre-extracted features from images max_len_image... | Implement the Python class `ImagesUnit` described below.
Class description:
Implement the ImagesUnit class.
Method signatures and docstrings:
- def __init__(self, visual_features_pth: str, max_len_images: int): Parameters ---------- visual_features_pth: str the path to pre-extracted features from images max_len_image... | db101beed691a0e399f9b0b19fb59c7dc8b16760 | <|skeleton|>
class ImagesUnit:
def __init__(self, visual_features_pth: str, max_len_images: int):
"""Parameters ---------- visual_features_pth: str the path to pre-extracted features from images max_len_images: str the maxinum number of images used"""
<|body_0|>
def transform(self, images: str... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImagesUnit:
def __init__(self, visual_features_pth: str, max_len_images: int):
"""Parameters ---------- visual_features_pth: str the path to pre-extracted features from images max_len_images: str the maxinum number of images used"""
self.fat_tensor, paths = torch.load(os.path.join('..', visual... | the_stack_v2_python_sparse | matchzoo/preprocessors/bow_preprocessor.py | nguyenvo09/LearningFromFactCheckers | train | 11 | |
a881f03c97164a6b8f92672d82326919fa0743ed | [
"parser = ArgumentParser()\nparser.add_argument('--version', '-v')\nparser.add_argument('--model', '-m')\nargs, unknown = parser.parse_known_args(shlex.split(arg_line))\nif args.model is None:\n raise ValueError(\"The parameter 'model' is required.\")\nif args.version is None:\n raise ValueError(\"The paramet... | <|body_start_0|>
parser = ArgumentParser()
parser.add_argument('--version', '-v')
parser.add_argument('--model', '-m')
args, unknown = parser.parse_known_args(shlex.split(arg_line))
if args.model is None:
raise ValueError("The parameter 'model' is required.")
... | InputParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputParser:
def parse_set_device_info_args(self, arg_line):
""":type arg_line: string :rtype: DeviceInfo"""
<|body_0|>
def parse_list_args(self, arg_line):
""":type arg_line: string :rtype: (string, DataSource, DeviceInfo)"""
<|body_1|>
def parse_execut... | stack_v2_sparse_classes_75kplus_train_001118 | 4,574 | no_license | [
{
"docstring": ":type arg_line: string :rtype: DeviceInfo",
"name": "parse_set_device_info_args",
"signature": "def parse_set_device_info_args(self, arg_line)"
},
{
"docstring": ":type arg_line: string :rtype: (string, DataSource, DeviceInfo)",
"name": "parse_list_args",
"signature": "de... | 5 | stack_v2_sparse_classes_30k_train_004746 | Implement the Python class `InputParser` described below.
Class description:
Implement the InputParser class.
Method signatures and docstrings:
- def parse_set_device_info_args(self, arg_line): :type arg_line: string :rtype: DeviceInfo
- def parse_list_args(self, arg_line): :type arg_line: string :rtype: (string, Dat... | Implement the Python class `InputParser` described below.
Class description:
Implement the InputParser class.
Method signatures and docstrings:
- def parse_set_device_info_args(self, arg_line): :type arg_line: string :rtype: DeviceInfo
- def parse_list_args(self, arg_line): :type arg_line: string :rtype: (string, Dat... | 88b773fc3516db70d7f61de8fc5317dc8702df13 | <|skeleton|>
class InputParser:
def parse_set_device_info_args(self, arg_line):
""":type arg_line: string :rtype: DeviceInfo"""
<|body_0|>
def parse_list_args(self, arg_line):
""":type arg_line: string :rtype: (string, DataSource, DeviceInfo)"""
<|body_1|>
def parse_execut... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InputParser:
def parse_set_device_info_args(self, arg_line):
""":type arg_line: string :rtype: DeviceInfo"""
parser = ArgumentParser()
parser.add_argument('--version', '-v')
parser.add_argument('--model', '-m')
args, unknown = parser.parse_known_args(shlex.split(arg_lin... | the_stack_v2_python_sparse | components/input_parser.py | juandiana/android-inspector | train | 0 | |
ae0c89122b0b25bb91f45d8b43586a5d87704185 | [
"res = []\nself.dfs(root, res)\nreturn res",
"if root:\n self.dfs(root.left, res)\n self.dfs(root.right, res)\n res.append(root.val)",
"if not root:\n return []\nstack, res = ([root], [])\nwhile stack:\n node = stack.pop()\n if node.left:\n stack.append(node.left)\n if node.right:\n ... | <|body_start_0|>
res = []
self.dfs(root, res)
return res
<|end_body_0|>
<|body_start_1|>
if root:
self.dfs(root.left, res)
self.dfs(root.right, res)
res.append(root.val)
<|end_body_1|>
<|body_start_2|>
if not root:
return []
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def dfs(self, root, res):
""":type root: TreeNode :type res: List[int] :rtype: None"""
<|body_1|>
def postorderTraversal_1(self, root):
""":type... | stack_v2_sparse_classes_75kplus_train_001119 | 2,233 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "postorderTraversal",
"signature": "def postorderTraversal(self, root)"
},
{
"docstring": ":type root: TreeNode :type res: List[int] :rtype: None",
"name": "dfs",
"signature": "def dfs(self, root, res)"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_052921 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def postorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def dfs(self, root, res): :type root: TreeNode :type res: List[int] :rtype: None
- def postorderTrave... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def postorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def dfs(self, root, res): :type root: TreeNode :type res: List[int] :rtype: None
- def postorderTrave... | 3d9e0ad2f6ed92ec969556f75d97c51ea4854719 | <|skeleton|>
class Solution:
def postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def dfs(self, root, res):
""":type root: TreeNode :type res: List[int] :rtype: None"""
<|body_1|>
def postorderTraversal_1(self, root):
""":type... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
res = []
self.dfs(root, res)
return res
def dfs(self, root, res):
""":type root: TreeNode :type res: List[int] :rtype: None"""
if root:
self.dfs(root.left... | the_stack_v2_python_sparse | Solutions/0145_postorderTraversal.py | YoupengLi/leetcode-sorting | train | 3 | |
2170a6771d53b47cd8e37244b64a00f93f8f27b9 | [
"def filter(d, max):\n \"\"\" filters dataset by max_len \"\"\"\n return tf.math.less(d, max)\nself.batch_size = batch_size\ntrain = tfds.load('ted_hrlr_translate/pt_to_en', split='train', as_supervised=True)\nself.tokenizer_pt, self.tokenizer_en = self.tokenize_dataset(train)\nself.data_train = train.map(sel... | <|body_start_0|>
def filter(d, max):
""" filters dataset by max_len """
return tf.math.less(d, max)
self.batch_size = batch_size
train = tfds.load('ted_hrlr_translate/pt_to_en', split='train', as_supervised=True)
self.tokenizer_pt, self.tokenizer_en = self.tokeniz... | loads and preps a dataset for machine translation | Dataset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataset:
"""loads and preps a dataset for machine translation"""
def __init__(self, batch_size, max_len):
"""batch_size is the batch size for training/validation max_len is the maximum number of tokens allowed per example sentence data_train, which contains the ted_hrlr_translate/pt_... | stack_v2_sparse_classes_75kplus_train_001120 | 5,014 | no_license | [
{
"docstring": "batch_size is the batch size for training/validation max_len is the maximum number of tokens allowed per example sentence data_train, which contains the ted_hrlr_translate/pt_to en tf.data.Dataset train split, loaded as_supervided data_valid, which contains the ted_hrlr_translate/pt to_en tf.dat... | 4 | stack_v2_sparse_classes_30k_train_009887 | Implement the Python class `Dataset` described below.
Class description:
loads and preps a dataset for machine translation
Method signatures and docstrings:
- def __init__(self, batch_size, max_len): batch_size is the batch size for training/validation max_len is the maximum number of tokens allowed per example sente... | Implement the Python class `Dataset` described below.
Class description:
loads and preps a dataset for machine translation
Method signatures and docstrings:
- def __init__(self, batch_size, max_len): batch_size is the batch size for training/validation max_len is the maximum number of tokens allowed per example sente... | 5114f884241b3406940b00450d8c71f55d5d6a70 | <|skeleton|>
class Dataset:
"""loads and preps a dataset for machine translation"""
def __init__(self, batch_size, max_len):
"""batch_size is the batch size for training/validation max_len is the maximum number of tokens allowed per example sentence data_train, which contains the ted_hrlr_translate/pt_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Dataset:
"""loads and preps a dataset for machine translation"""
def __init__(self, batch_size, max_len):
"""batch_size is the batch size for training/validation max_len is the maximum number of tokens allowed per example sentence data_train, which contains the ted_hrlr_translate/pt_to en tf.data... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/3-dataset.py | icculp/holbertonschool-machine_learning | train | 0 |
386421f654c08464b1b39fe6b7b4242629c9d255 | [
"self._recv_packet = []\nself.packet_buffer = []\nself.buf = []\nself.is_new_packet = False\nself.num_packets = 0\nself.comm_object = None",
"self.num_packets = 0\nself.is_new_packet = False\nfor i in range(0, 6):\n if len(self.buf) < 8:\n return self.num_packets\n try:\n packet_end = self.buf... | <|body_start_0|>
self._recv_packet = []
self.packet_buffer = []
self.buf = []
self.is_new_packet = False
self.num_packets = 0
self.comm_object = None
<|end_body_0|>
<|body_start_1|>
self.num_packets = 0
self.is_new_packet = False
for i in range(0,... | class to handle low-level work of processing FlightGear packets out of a data stream from some input source This is a worker super-class, you should use the inherited classes which implement a specific interface (UDP or TCP) | FlightGearParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlightGearParser:
"""class to handle low-level work of processing FlightGear packets out of a data stream from some input source This is a worker super-class, you should use the inherited classes which implement a specific interface (UDP or TCP)"""
def __init__(self):
"""constructor ... | stack_v2_sparse_classes_75kplus_train_001121 | 6,640 | permissive | [
{
"docstring": "constructor intializes the parser variable Args: no args Returns: FlightGearParser instance",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "parse the buffer to find packets searches buffer for packets, returns the number of packets found Args: no args R... | 3 | null | Implement the Python class `FlightGearParser` described below.
Class description:
class to handle low-level work of processing FlightGear packets out of a data stream from some input source This is a worker super-class, you should use the inherited classes which implement a specific interface (UDP or TCP)
Method sign... | Implement the Python class `FlightGearParser` described below.
Class description:
class to handle low-level work of processing FlightGear packets out of a data stream from some input source This is a worker super-class, you should use the inherited classes which implement a specific interface (UDP or TCP)
Method sign... | 6827886916e36432ce1d806f0a78edef6c9270d9 | <|skeleton|>
class FlightGearParser:
"""class to handle low-level work of processing FlightGear packets out of a data stream from some input source This is a worker super-class, you should use the inherited classes which implement a specific interface (UDP or TCP)"""
def __init__(self):
"""constructor ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FlightGearParser:
"""class to handle low-level work of processing FlightGear packets out of a data stream from some input source This is a worker super-class, you should use the inherited classes which implement a specific interface (UDP or TCP)"""
def __init__(self):
"""constructor intializes th... | the_stack_v2_python_sparse | pybots/src/communications/flightgear_protocol.py | aivian/robots | train | 0 |
2c098de81b15cc4f5fbadce22c067bdf2320bd46 | [
"_logger.info('sync var')\nif not isinstance(ids, list):\n ids = [ids]\nsync_date = datetime.now().strftime('%Y-%m-%d %H:%M:%S')\nproduct_model = self.pool.get('product.product')\npartner_model = self.pool.get('res.partner')\nproduct_lines = []\nfor ebiz_stock in self.read(cr, uid, ids, ['product_id', 'var_qty',... | <|body_start_0|>
_logger.info('sync var')
if not isinstance(ids, list):
ids = [ids]
sync_date = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
product_model = self.pool.get('product.product')
partner_model = self.pool.get('res.partner')
product_lines = []
... | ebiz_stock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ebiz_stock:
def sync_stock_var(self, cr, uid, ids, context=None):
"""库存增量同步"""
<|body_0|>
def sync_stock_qty(self, cr, uid, ids, context=None):
"""库存全量同步"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
_logger.info('sync var')
if not isinsta... | stack_v2_sparse_classes_75kplus_train_001122 | 3,970 | no_license | [
{
"docstring": "库存增量同步",
"name": "sync_stock_var",
"signature": "def sync_stock_var(self, cr, uid, ids, context=None)"
},
{
"docstring": "库存全量同步",
"name": "sync_stock_qty",
"signature": "def sync_stock_qty(self, cr, uid, ids, context=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001649 | Implement the Python class `ebiz_stock` described below.
Class description:
Implement the ebiz_stock class.
Method signatures and docstrings:
- def sync_stock_var(self, cr, uid, ids, context=None): 库存增量同步
- def sync_stock_qty(self, cr, uid, ids, context=None): 库存全量同步 | Implement the Python class `ebiz_stock` described below.
Class description:
Implement the ebiz_stock class.
Method signatures and docstrings:
- def sync_stock_var(self, cr, uid, ids, context=None): 库存增量同步
- def sync_stock_qty(self, cr, uid, ids, context=None): 库存全量同步
<|skeleton|>
class ebiz_stock:
def sync_stoc... | 96186dfac9a10cd47079de226f6f1d0761928a84 | <|skeleton|>
class ebiz_stock:
def sync_stock_var(self, cr, uid, ids, context=None):
"""库存增量同步"""
<|body_0|>
def sync_stock_qty(self, cr, uid, ids, context=None):
"""库存全量同步"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ebiz_stock:
def sync_stock_var(self, cr, uid, ids, context=None):
"""库存增量同步"""
_logger.info('sync var')
if not isinstance(ids, list):
ids = [ids]
sync_date = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
product_model = self.pool.get('product.product')
... | the_stack_v2_python_sparse | bysun_stock_product_V2/models/ebiz.py | luohuayong/addons8 | train | 0 | |
caa3646eedd5885e6711b34be659cd68fa5707a9 | [
"self.elems_dict = elems_dict\nself.unit_length = unit_length\nself.filename = filename",
"if os.path.isfile(self.filename):\n os.remove(self.filename)\nlat = open(self.filename, 'w')\nheader = '? VERSION = 1.0\\n'\nheader += '? UNITLENGTH = ' + str(self.unit_length) + '\\n'\nlat.write(header)\nquad_label = '#... | <|body_start_0|>
self.elems_dict = elems_dict
self.unit_length = unit_length
self.filename = filename
<|end_body_0|>
<|body_start_1|>
if os.path.isfile(self.filename):
os.remove(self.filename)
lat = open(self.filename, 'w')
header = '? VERSION = 1.0\n'
... | Class for generating a properly formatted Genesis1.3 .lat file. | GenLatFile | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenLatFile:
"""Class for generating a properly formatted Genesis1.3 .lat file."""
def __init__(self, filename, elems_dict, unit_length):
"""Class constructor Args: filename (string): the name of the file the lattice is to be exported as elems_dict (string): a dictionary of the elemen... | stack_v2_sparse_classes_75kplus_train_001123 | 2,279 | permissive | [
{
"docstring": "Class constructor Args: filename (string): the name of the file the lattice is to be exported as elems_dict (string): a dictionary of the elements for the genesis lattice unit_length (float): the unit length for genesis, usually the undulator period",
"name": "__init__",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_train_049521 | Implement the Python class `GenLatFile` described below.
Class description:
Class for generating a properly formatted Genesis1.3 .lat file.
Method signatures and docstrings:
- def __init__(self, filename, elems_dict, unit_length): Class constructor Args: filename (string): the name of the file the lattice is to be ex... | Implement the Python class `GenLatFile` described below.
Class description:
Class for generating a properly formatted Genesis1.3 .lat file.
Method signatures and docstrings:
- def __init__(self, filename, elems_dict, unit_length): Class constructor Args: filename (string): the name of the file the lattice is to be ex... | e984b5828b1fc8f93bdaa9575dd16f519f44a288 | <|skeleton|>
class GenLatFile:
"""Class for generating a properly formatted Genesis1.3 .lat file."""
def __init__(self, filename, elems_dict, unit_length):
"""Class constructor Args: filename (string): the name of the file the lattice is to be exported as elems_dict (string): a dictionary of the elemen... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GenLatFile:
"""Class for generating a properly formatted Genesis1.3 .lat file."""
def __init__(self, filename, elems_dict, unit_length):
"""Class constructor Args: filename (string): the name of the file the lattice is to be exported as elems_dict (string): a dictionary of the elements for the ge... | the_stack_v2_python_sparse | radtrack/genesis/rbGenLatFile.py | lynch829/radtrack | train | 1 |
ae8a5357d5876fc7d58a95e26c3c1ccc6c59ff53 | [
"expected_checksum, checksum_object = sync_helpers._get_expected_checksum(response, self._get_headers, self.media_url, checksum_type=self.checksum)\nlocal_checksum_object = _add_decoder(response, checksum_object)\nasync for chunk in response.content.iter_chunked(_request_helpers._SINGLE_GET_CHUNK_SIZE):\n self._... | <|body_start_0|>
expected_checksum, checksum_object = sync_helpers._get_expected_checksum(response, self._get_headers, self.media_url, checksum_type=self.checksum)
local_checksum_object = _add_decoder(response, checksum_object)
async for chunk in response.content.iter_chunked(_request_helpers._S... | Helper to manage downloading a resource from a Google API. "Slices" of the resource can be retrieved by specifying a range with ``start`` and / or ``end``. However, in typical usage, neither ``start`` nor ``end`` is expected to be provided. Args: media_url (str): The URL containing the media to be downloaded. stream (I... | Download | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Download:
"""Helper to manage downloading a resource from a Google API. "Slices" of the resource can be retrieved by specifying a range with ``start`` and / or ``end``. However, in typical usage, neither ``start`` nor ``end`` is expected to be provided. Args: media_url (str): The URL containing t... | stack_v2_sparse_classes_75kplus_train_001124 | 18,751 | permissive | [
{
"docstring": "Write response body to a write-able stream. .. note: This method assumes that the ``_stream`` attribute is set on the current download. Args: response (~requests.Response): The HTTP response object. Raises: ~google.resumable_media.common.DataCorruption: If the download's checksum doesn't agree w... | 2 | null | Implement the Python class `Download` described below.
Class description:
Helper to manage downloading a resource from a Google API. "Slices" of the resource can be retrieved by specifying a range with ``start`` and / or ``end``. However, in typical usage, neither ``start`` nor ``end`` is expected to be provided. Args... | Implement the Python class `Download` described below.
Class description:
Helper to manage downloading a resource from a Google API. "Slices" of the resource can be retrieved by specifying a range with ``start`` and / or ``end``. However, in typical usage, neither ``start`` nor ``end`` is expected to be provided. Args... | a02d814ed75d367f0e4047f1982bb79ea970e181 | <|skeleton|>
class Download:
"""Helper to manage downloading a resource from a Google API. "Slices" of the resource can be retrieved by specifying a range with ``start`` and / or ``end``. However, in typical usage, neither ``start`` nor ``end`` is expected to be provided. Args: media_url (str): The URL containing t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Download:
"""Helper to manage downloading a resource from a Google API. "Slices" of the resource can be retrieved by specifying a range with ``start`` and / or ``end``. However, in typical usage, neither ``start`` nor ``end`` is expected to be provided. Args: media_url (str): The URL containing the media to b... | the_stack_v2_python_sparse | google/_async_resumable_media/requests/download.py | googleapis/google-resumable-media-python | train | 42 |
b8ca325f77e298a8750cbf50f8324eb99f53d67a | [
"result = is_leap(1990)\nself.assertEquals(result, False)\nreturn",
"result = is_leap(2000)\nself.assertEquals(result, True)\nreturn",
"result = is_leap(2400)\nself.assertEquals(result, True)\nreturn"
] | <|body_start_0|>
result = is_leap(1990)
self.assertEquals(result, False)
return
<|end_body_0|>
<|body_start_1|>
result = is_leap(2000)
self.assertEquals(result, True)
return
<|end_body_1|>
<|body_start_2|>
result = is_leap(2400)
self.assertEquals(result,... | Description | TestWriteAFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestWriteAFunction:
"""Description"""
def test_hackerrank_sample1(self):
"""Verify provided test case."""
<|body_0|>
def test_hackerrank_sample2(self):
"""Verify provided test case."""
<|body_1|>
def test_hackerrank_sample3(self):
"""Verify p... | stack_v2_sparse_classes_75kplus_train_001125 | 707 | no_license | [
{
"docstring": "Verify provided test case.",
"name": "test_hackerrank_sample1",
"signature": "def test_hackerrank_sample1(self)"
},
{
"docstring": "Verify provided test case.",
"name": "test_hackerrank_sample2",
"signature": "def test_hackerrank_sample2(self)"
},
{
"docstring": "... | 3 | stack_v2_sparse_classes_30k_train_050110 | Implement the Python class `TestWriteAFunction` described below.
Class description:
Description
Method signatures and docstrings:
- def test_hackerrank_sample1(self): Verify provided test case.
- def test_hackerrank_sample2(self): Verify provided test case.
- def test_hackerrank_sample3(self): Verify provided test ca... | Implement the Python class `TestWriteAFunction` described below.
Class description:
Description
Method signatures and docstrings:
- def test_hackerrank_sample1(self): Verify provided test case.
- def test_hackerrank_sample2(self): Verify provided test case.
- def test_hackerrank_sample3(self): Verify provided test ca... | fcf3755b62fe0644af763875e3a00be962941a6d | <|skeleton|>
class TestWriteAFunction:
"""Description"""
def test_hackerrank_sample1(self):
"""Verify provided test case."""
<|body_0|>
def test_hackerrank_sample2(self):
"""Verify provided test case."""
<|body_1|>
def test_hackerrank_sample3(self):
"""Verify p... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestWriteAFunction:
"""Description"""
def test_hackerrank_sample1(self):
"""Verify provided test case."""
result = is_leap(1990)
self.assertEquals(result, False)
return
def test_hackerrank_sample2(self):
"""Verify provided test case."""
result = is_lea... | the_stack_v2_python_sparse | python3/write_a_function/test_write_a_function.py | ayazhemani/hackerrank-py | train | 0 |
e62a825fc930d50875e5756d9a82cab964d6a5f2 | [
"self.data = data\nself.plot_title = plot_title\nself.label_names = label_names",
"try:\n assert isinstance(title, str)\n self.plot_title = title\nexcept AssertionError:\n print('the add_title method requires a sting input')\n print(\"therefore not changing plot's title\")",
"try:\n if not isinst... | <|body_start_0|>
self.data = data
self.plot_title = plot_title
self.label_names = label_names
<|end_body_0|>
<|body_start_1|>
try:
assert isinstance(title, str)
self.plot_title = title
except AssertionError:
print('the add_title method require... | Generic plotting class used in the grapher module | Plotter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Plotter:
"""Generic plotting class used in the grapher module"""
def __init__(self, data, plot_title=None, label_names=None):
"""Initializes plotting class with an optional plot title and label Parameters ---------- data : pandas.DataFrame the Pandas Dataframe to be plotted plot_titl... | stack_v2_sparse_classes_75kplus_train_001126 | 4,793 | permissive | [
{
"docstring": "Initializes plotting class with an optional plot title and label Parameters ---------- data : pandas.DataFrame the Pandas Dataframe to be plotted plot_title : str, optional (default = None) the plot title label_names : str tuple, optional (default = None) the x-axis and y-axis titles (x-axis is ... | 5 | stack_v2_sparse_classes_30k_val_002837 | Implement the Python class `Plotter` described below.
Class description:
Generic plotting class used in the grapher module
Method signatures and docstrings:
- def __init__(self, data, plot_title=None, label_names=None): Initializes plotting class with an optional plot title and label Parameters ---------- data : pand... | Implement the Python class `Plotter` described below.
Class description:
Generic plotting class used in the grapher module
Method signatures and docstrings:
- def __init__(self, data, plot_title=None, label_names=None): Initializes plotting class with an optional plot title and label Parameters ---------- data : pand... | 8fbcf41d579be76eadf0ac980f4c9cbe30d60d93 | <|skeleton|>
class Plotter:
"""Generic plotting class used in the grapher module"""
def __init__(self, data, plot_title=None, label_names=None):
"""Initializes plotting class with an optional plot title and label Parameters ---------- data : pandas.DataFrame the Pandas Dataframe to be plotted plot_titl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Plotter:
"""Generic plotting class used in the grapher module"""
def __init__(self, data, plot_title=None, label_names=None):
"""Initializes plotting class with an optional plot title and label Parameters ---------- data : pandas.DataFrame the Pandas Dataframe to be plotted plot_title : str, opti... | the_stack_v2_python_sparse | quickscreen/plot/plotter.py | mqharris/533_lab2 | train | 0 |
23a97525b6c1ca0734babed8602ad52db72ca9b7 | [
"if A is None or B is None:\n return None\nm, n, l = (len(A), len(A[0]), len(B[0]))\nif len(B) != n:\n raise Exception(\"A's column number must be equal to B's row number.\")\nC = [[0 for _ in range(l)] for _ in range(m)]\nfor i, row in enumerate(A):\n for k, eleA in enumerate(row):\n if eleA:\n ... | <|body_start_0|>
if A is None or B is None:
return None
m, n, l = (len(A), len(A[0]), len(B[0]))
if len(B) != n:
raise Exception("A's column number must be equal to B's row number.")
C = [[0 for _ in range(l)] for _ in range(m)]
for i, row in enumerate(A):... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def multiply(self, A, B):
""":type A: List[List[int]] :type B: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def multiply2(self, A, B):
""":type A: List[List[int]] :type B: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_75kplus_train_001127 | 5,317 | no_license | [
{
"docstring": ":type A: List[List[int]] :type B: List[List[int]] :rtype: List[List[int]]",
"name": "multiply",
"signature": "def multiply(self, A, B)"
},
{
"docstring": ":type A: List[List[int]] :type B: List[List[int]] :rtype: List[List[int]]",
"name": "multiply2",
"signature": "def mu... | 2 | stack_v2_sparse_classes_30k_train_042970 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def multiply(self, A, B): :type A: List[List[int]] :type B: List[List[int]] :rtype: List[List[int]]
- def multiply2(self, A, B): :type A: List[List[int]] :type B: List[List[int]]... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def multiply(self, A, B): :type A: List[List[int]] :type B: List[List[int]] :rtype: List[List[int]]
- def multiply2(self, A, B): :type A: List[List[int]] :type B: List[List[int]]... | 4c0cfe857f5d78a44c1a3bfb2571d72da4911d97 | <|skeleton|>
class Solution:
def multiply(self, A, B):
""":type A: List[List[int]] :type B: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def multiply2(self, A, B):
""":type A: List[List[int]] :type B: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def multiply(self, A, B):
""":type A: List[List[int]] :type B: List[List[int]] :rtype: List[List[int]]"""
if A is None or B is None:
return None
m, n, l = (len(A), len(A[0]), len(B[0]))
if len(B) != n:
raise Exception("A's column number must be... | the_stack_v2_python_sparse | 311-SparseMatrixMultiplication.py | minseoch/algorithm | train | 0 | |
62cdd31e6ee267ed423286c7bdec43a68a3955e9 | [
"self.result = {}\nself.timeouts = {}\nself.time = datetime.now()\nself.timeout = timeout\nself.file = file",
"def wrapper(*a, **k):\n uid = a[0].uid\n if k.get('recache', 0):\n self.result[uid] = ''\n del k['recache']\n if self.timedout(uid):\n self.result[uid] = ''\n if not self... | <|body_start_0|>
self.result = {}
self.timeouts = {}
self.time = datetime.now()
self.timeout = timeout
self.file = file
<|end_body_0|>
<|body_start_1|>
def wrapper(*a, **k):
uid = a[0].uid
if k.get('recache', 0):
self.result[uid] =... | a decorator | CachedInstance | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CachedInstance:
"""a decorator"""
def __init__(self, timeout=0, file=''):
"""timeout: int seconds file='string path to store result'"""
<|body_0|>
def __call__(self, fn):
"""wrap our function"""
<|body_1|>
def timedout(self, uid):
"""returns ... | stack_v2_sparse_classes_75kplus_train_001128 | 2,764 | permissive | [
{
"docstring": "timeout: int seconds file='string path to store result'",
"name": "__init__",
"signature": "def __init__(self, timeout=0, file='')"
},
{
"docstring": "wrap our function",
"name": "__call__",
"signature": "def __call__(self, fn)"
},
{
"docstring": "returns True if ... | 3 | stack_v2_sparse_classes_30k_val_002533 | Implement the Python class `CachedInstance` described below.
Class description:
a decorator
Method signatures and docstrings:
- def __init__(self, timeout=0, file=''): timeout: int seconds file='string path to store result'
- def __call__(self, fn): wrap our function
- def timedout(self, uid): returns True if we have... | Implement the Python class `CachedInstance` described below.
Class description:
a decorator
Method signatures and docstrings:
- def __init__(self, timeout=0, file=''): timeout: int seconds file='string path to store result'
- def __call__(self, fn): wrap our function
- def timedout(self, uid): returns True if we have... | 430d6dfd719f8c88a4c3de2b735f8736187ff19b | <|skeleton|>
class CachedInstance:
"""a decorator"""
def __init__(self, timeout=0, file=''):
"""timeout: int seconds file='string path to store result'"""
<|body_0|>
def __call__(self, fn):
"""wrap our function"""
<|body_1|>
def timedout(self, uid):
"""returns ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CachedInstance:
"""a decorator"""
def __init__(self, timeout=0, file=''):
"""timeout: int seconds file='string path to store result'"""
self.result = {}
self.timeouts = {}
self.time = datetime.now()
self.timeout = timeout
self.file = file
def __call__(... | the_stack_v2_python_sparse | evoke/serve/cached_instance.py | howiemac/evoke | train | 0 |
110f306a6f2c0aa3489cf469818ce57045991e22 | [
"if not requires_filters or not isinstance(requires_filters, dict):\n return configs\nnew_requirements = {}\nfor field, config in configs.items():\n requirement, key, allow_none = config\n try:\n explicit_filter = requires_filters[field]\n requirement_copy = requirement.copy()\n requir... | <|body_start_0|>
if not requires_filters or not isinstance(requires_filters, dict):
return configs
new_requirements = {}
for field, config in configs.items():
requirement, key, allow_none = config
try:
explicit_filter = requires_filters[field]
... | Factory service for service registration handlers | _HandlerFactory | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _HandlerFactory:
"""Factory service for service registration handlers"""
def _prepare_requirements(configs, requires_filters):
"""Overrides the filters specified in the decorator with the given ones :param configs: Field → (Requirement, key, allow_none) dictionary :param requires_fil... | stack_v2_sparse_classes_75kplus_train_001129 | 21,139 | permissive | [
{
"docstring": "Overrides the filters specified in the decorator with the given ones :param configs: Field → (Requirement, key, allow_none) dictionary :param requires_filters: Content of the 'requires.filter' component property (field → string) :return: The new configuration dictionary",
"name": "_prepare_r... | 2 | stack_v2_sparse_classes_30k_train_041699 | Implement the Python class `_HandlerFactory` described below.
Class description:
Factory service for service registration handlers
Method signatures and docstrings:
- def _prepare_requirements(configs, requires_filters): Overrides the filters specified in the decorator with the given ones :param configs: Field → (Req... | Implement the Python class `_HandlerFactory` described below.
Class description:
Factory service for service registration handlers
Method signatures and docstrings:
- def _prepare_requirements(configs, requires_filters): Overrides the filters specified in the decorator with the given ones :param configs: Field → (Req... | 1d0add361ca219da8fdf72bb9ba8cb0ade01ad2f | <|skeleton|>
class _HandlerFactory:
"""Factory service for service registration handlers"""
def _prepare_requirements(configs, requires_filters):
"""Overrides the filters specified in the decorator with the given ones :param configs: Field → (Requirement, key, allow_none) dictionary :param requires_fil... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _HandlerFactory:
"""Factory service for service registration handlers"""
def _prepare_requirements(configs, requires_filters):
"""Overrides the filters specified in the decorator with the given ones :param configs: Field → (Requirement, key, allow_none) dictionary :param requires_filters: Content... | the_stack_v2_python_sparse | pelix/ipopo/handlers/requiresmap.py | tcalmant/ipopo | train | 67 |
b3511fc20828fc0cfd9f8519ab892786164bb15a | [
"i = 0\nproduct_sum = 1\nadd_sum = 0\nfor eary_month_benchmark in benchmark_monthly:\n if eary_month_benchmark >= 0:\n product_sum = product_sum * (benchmark_monthly[i] + 1)\n add_sum += 1\n i += 1\nucr_x = pow(product_sum, 1 / add_sum) - 1\nreturn ucr_x",
"ucr_y = UpwardCapture.upward_capture... | <|body_start_0|>
i = 0
product_sum = 1
add_sum = 0
for eary_month_benchmark in benchmark_monthly:
if eary_month_benchmark >= 0:
product_sum = product_sum * (benchmark_monthly[i] + 1)
add_sum += 1
i += 1
ucr_x = pow(product_s... | UplinkCapture | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UplinkCapture:
def ucr_x(benchmark_monthly: list):
"""ucr_x计算，需要传基金月度收益率列表和基准月度收益率列表"""
<|body_0|>
def uplink_capture(monthly_fund_field: list, benchmark_monthly: list):
"""上行捕获率计算，上行捕获收益率(ucr_y)除以ucrx,计算需要传入基金月度收益率列表和基准月度收益率列表"""
<|body_1|>
<|end_skeleton|>... | stack_v2_sparse_classes_75kplus_train_001130 | 2,161 | no_license | [
{
"docstring": "ucr_x计算，需要传基金月度收益率列表和基准月度收益率列表",
"name": "ucr_x",
"signature": "def ucr_x(benchmark_monthly: list)"
},
{
"docstring": "上行捕获率计算，上行捕获收益率(ucr_y)除以ucrx,计算需要传入基金月度收益率列表和基准月度收益率列表",
"name": "uplink_capture",
"signature": "def uplink_capture(monthly_fund_field: list, benchmark_m... | 2 | stack_v2_sparse_classes_30k_train_039480 | Implement the Python class `UplinkCapture` described below.
Class description:
Implement the UplinkCapture class.
Method signatures and docstrings:
- def ucr_x(benchmark_monthly: list): ucr_x计算，需要传基金月度收益率列表和基准月度收益率列表
- def uplink_capture(monthly_fund_field: list, benchmark_monthly: list): 上行捕获率计算，上行捕获收益率(ucr_y)除以ucrx... | Implement the Python class `UplinkCapture` described below.
Class description:
Implement the UplinkCapture class.
Method signatures and docstrings:
- def ucr_x(benchmark_monthly: list): ucr_x计算，需要传基金月度收益率列表和基准月度收益率列表
- def uplink_capture(monthly_fund_field: list, benchmark_monthly: list): 上行捕获率计算，上行捕获收益率(ucr_y)除以ucrx... | eae782a78ffde1276a0812a43d7deefb0bdedeb4 | <|skeleton|>
class UplinkCapture:
def ucr_x(benchmark_monthly: list):
"""ucr_x计算，需要传基金月度收益率列表和基准月度收益率列表"""
<|body_0|>
def uplink_capture(monthly_fund_field: list, benchmark_monthly: list):
"""上行捕获率计算，上行捕获收益率(ucr_y)除以ucrx,计算需要传入基金月度收益率列表和基准月度收益率列表"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UplinkCapture:
def ucr_x(benchmark_monthly: list):
"""ucr_x计算，需要传基金月度收益率列表和基准月度收益率列表"""
i = 0
product_sum = 1
add_sum = 0
for eary_month_benchmark in benchmark_monthly:
if eary_month_benchmark >= 0:
product_sum = product_sum * (benchmark_mont... | the_stack_v2_python_sparse | public_method/indicator_calculation_method/uplink_capture.py | liufubin-git/python | train | 0 | |
224e05850e26d30e7e3be47255af498784dd0fc6 | [
"parser = super(CancelVnfLcmOp, self).get_parser(prog_name)\nparser.add_argument(_VNF_LCM_OP_OCC_ID, metavar='<vnf-lcm-op-occ-id>', help=_('VNF lifecycle management operation occurrence ID.'))\nparser.add_argument('--cancel-mode', default='GRACEFUL', metavar='<cancel-mode>', choices=['GRACEFUL', 'FORCEFUL'], help=_... | <|body_start_0|>
parser = super(CancelVnfLcmOp, self).get_parser(prog_name)
parser.add_argument(_VNF_LCM_OP_OCC_ID, metavar='<vnf-lcm-op-occ-id>', help=_('VNF lifecycle management operation occurrence ID.'))
parser.add_argument('--cancel-mode', default='GRACEFUL', metavar='<cancel-mode>', choice... | CancelVnfLcmOp | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CancelVnfLcmOp:
def get_parser(self, prog_name):
"""Add arguments to parser. Args: prog_name ([type]): program name Returns: parser([ArgumentParser]):"""
<|body_0|>
def take_action(self, parsed_args):
"""Execute cancel_vnf_instance and output comment. Args: parsed_ar... | stack_v2_sparse_classes_75kplus_train_001131 | 11,909 | permissive | [
{
"docstring": "Add arguments to parser. Args: prog_name ([type]): program name Returns: parser([ArgumentParser]):",
"name": "get_parser",
"signature": "def get_parser(self, prog_name)"
},
{
"docstring": "Execute cancel_vnf_instance and output comment. Args: parsed_args ([Namespace]): arguments ... | 2 | stack_v2_sparse_classes_30k_val_002018 | Implement the Python class `CancelVnfLcmOp` described below.
Class description:
Implement the CancelVnfLcmOp class.
Method signatures and docstrings:
- def get_parser(self, prog_name): Add arguments to parser. Args: prog_name ([type]): program name Returns: parser([ArgumentParser]):
- def take_action(self, parsed_arg... | Implement the Python class `CancelVnfLcmOp` described below.
Class description:
Implement the CancelVnfLcmOp class.
Method signatures and docstrings:
- def get_parser(self, prog_name): Add arguments to parser. Args: prog_name ([type]): program name Returns: parser([ArgumentParser]):
- def take_action(self, parsed_arg... | e8460be8c53ad5dfbac720367cf0ae2c3291dc3b | <|skeleton|>
class CancelVnfLcmOp:
def get_parser(self, prog_name):
"""Add arguments to parser. Args: prog_name ([type]): program name Returns: parser([ArgumentParser]):"""
<|body_0|>
def take_action(self, parsed_args):
"""Execute cancel_vnf_instance and output comment. Args: parsed_ar... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CancelVnfLcmOp:
def get_parser(self, prog_name):
"""Add arguments to parser. Args: prog_name ([type]): program name Returns: parser([ArgumentParser]):"""
parser = super(CancelVnfLcmOp, self).get_parser(prog_name)
parser.add_argument(_VNF_LCM_OP_OCC_ID, metavar='<vnf-lcm-op-occ-id>', he... | the_stack_v2_python_sparse | tackerclient/osc/v1/vnflcm/vnflcm_op_occs.py | openstack/python-tackerclient | train | 21 | |
608eda567b1c98079ef6384daee47e21bb89f84b | [
"writer = KvDbWriter(KvDbClient(**config))\nfor configured_stream in configured_catalog.streams:\n if configured_stream.destination_sync_mode == DestinationSyncMode.overwrite:\n writer.delete_stream_entries(configured_stream.stream.name)\nfor message in input_messages:\n if message.type == Type.STATE:\... | <|body_start_0|>
writer = KvDbWriter(KvDbClient(**config))
for configured_stream in configured_catalog.streams:
if configured_stream.destination_sync_mode == DestinationSyncMode.overwrite:
writer.delete_stream_entries(configured_stream.stream.name)
for message in inpu... | DestinationKvdb | [
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"Elastic-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DestinationKvdb:
def write(self, config: Mapping[str, Any], configured_catalog: ConfiguredAirbyteCatalog, input_messages: Iterable[AirbyteMessage]) -> Iterable[AirbyteMessage]:
"""Reads the input stream of messages, config, and catalog to write data to the destination. This method return... | stack_v2_sparse_classes_75kplus_train_001132 | 3,439 | permissive | [
{
"docstring": "Reads the input stream of messages, config, and catalog to write data to the destination. This method returns an iterable (typically a generator of AirbyteMessages via yield) containing state messages received in the input message stream. Outputting a state message means that every AirbyteRecord... | 2 | stack_v2_sparse_classes_30k_train_040109 | Implement the Python class `DestinationKvdb` described below.
Class description:
Implement the DestinationKvdb class.
Method signatures and docstrings:
- def write(self, config: Mapping[str, Any], configured_catalog: ConfiguredAirbyteCatalog, input_messages: Iterable[AirbyteMessage]) -> Iterable[AirbyteMessage]: Read... | Implement the Python class `DestinationKvdb` described below.
Class description:
Implement the DestinationKvdb class.
Method signatures and docstrings:
- def write(self, config: Mapping[str, Any], configured_catalog: ConfiguredAirbyteCatalog, input_messages: Iterable[AirbyteMessage]) -> Iterable[AirbyteMessage]: Read... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class DestinationKvdb:
def write(self, config: Mapping[str, Any], configured_catalog: ConfiguredAirbyteCatalog, input_messages: Iterable[AirbyteMessage]) -> Iterable[AirbyteMessage]:
"""Reads the input stream of messages, config, and catalog to write data to the destination. This method return... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DestinationKvdb:
def write(self, config: Mapping[str, Any], configured_catalog: ConfiguredAirbyteCatalog, input_messages: Iterable[AirbyteMessage]) -> Iterable[AirbyteMessage]:
"""Reads the input stream of messages, config, and catalog to write data to the destination. This method returns an iterable ... | the_stack_v2_python_sparse | dts/airbyte/airbyte-integrations/connectors/destination-kvdb/destination_kvdb/destination.py | alldatacenter/alldata | train | 774 | |
1cf4f8a86c1d161204c22447b7026d96507c4192 | [
"self.userId = userId\nself.question = question\nself.comment = comment",
"commnt = dict(userId=self.userId, question=self.question, comment=self.comment)\ncommentData = {'comment': 'comment'}\ntable = 'comments'\ncolumns = ', '.join(commnt.keys())\nvalues = \"', '\".join(map(str, commnt.values()))\ndetails = ','... | <|body_start_0|>
self.userId = userId
self.question = question
self.comment = comment
<|end_body_0|>
<|body_start_1|>
commnt = dict(userId=self.userId, question=self.question, comment=self.comment)
commentData = {'comment': 'comment'}
table = 'comments'
columns =... | Class for comments CRUD operations | CommentModels | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommentModels:
"""Class for comments CRUD operations"""
def __init__(self, userId, question, comment):
"""Initialize the comment models"""
<|body_0|>
def create_comment(self):
"""method for posting comments"""
<|body_1|>
def fetch_quest(self, questio... | stack_v2_sparse_classes_75kplus_train_001133 | 2,329 | no_license | [
{
"docstring": "Initialize the comment models",
"name": "__init__",
"signature": "def __init__(self, userId, question, comment)"
},
{
"docstring": "method for posting comments",
"name": "create_comment",
"signature": "def create_comment(self)"
},
{
"docstring": "Method to fetch q... | 5 | stack_v2_sparse_classes_30k_train_000919 | Implement the Python class `CommentModels` described below.
Class description:
Class for comments CRUD operations
Method signatures and docstrings:
- def __init__(self, userId, question, comment): Initialize the comment models
- def create_comment(self): method for posting comments
- def fetch_quest(self, questionId)... | Implement the Python class `CommentModels` described below.
Class description:
Class for comments CRUD operations
Method signatures and docstrings:
- def __init__(self, userId, question, comment): Initialize the comment models
- def create_comment(self): method for posting comments
- def fetch_quest(self, questionId)... | 93c7aeb54c240b6312e6164859acd2c878e85825 | <|skeleton|>
class CommentModels:
"""Class for comments CRUD operations"""
def __init__(self, userId, question, comment):
"""Initialize the comment models"""
<|body_0|>
def create_comment(self):
"""method for posting comments"""
<|body_1|>
def fetch_quest(self, questio... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CommentModels:
"""Class for comments CRUD operations"""
def __init__(self, userId, question, comment):
"""Initialize the comment models"""
self.userId = userId
self.question = question
self.comment = comment
def create_comment(self):
"""method for posting comm... | the_stack_v2_python_sparse | app/api/v2/models/comment_models.py | matthenge/Questioner-api-v2 | train | 0 |
855b21380e26916be92250eee201b437aa9dc315 | [
"action_space = Bag([])\naction_space.seed(seed=seed)\nsuper().__init__(initial_state=initial_state, default_reward=default_reward, seed=seed, columns=columns, action_space=action_space)",
"x, y = position\nif action == self.actions['RIGHT']:\n x += 1\nelif action == self.actions['DOWN']:\n y += 1\nnext_pos... | <|body_start_0|>
action_space = Bag([])
action_space.seed(seed=seed)
super().__init__(initial_state=initial_state, default_reward=default_reward, seed=seed, columns=columns, action_space=action_space)
<|end_body_0|>
<|body_start_1|>
x, y = position
if action == self.actions['RIG... | DeepSeaTreasureRightDown | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepSeaTreasureRightDown:
def __init__(self, initial_state: tuple=(0, 0), default_reward: tuple=(0,), seed: int=0, columns: int=10):
""":param initial_state: Initial state where start the agent. :param default_reward: (time_inverted, treasure_value) :param seed: Seed used for np.random.R... | stack_v2_sparse_classes_75kplus_train_001134 | 4,417 | no_license | [
{
"docstring": ":param initial_state: Initial state where start the agent. :param default_reward: (time_inverted, treasure_value) :param seed: Seed used for np.random.RandomState method. :param columns: Number of columns to be used to build this environment (allows experimenting with an identical environment, b... | 4 | stack_v2_sparse_classes_30k_train_050180 | Implement the Python class `DeepSeaTreasureRightDown` described below.
Class description:
Implement the DeepSeaTreasureRightDown class.
Method signatures and docstrings:
- def __init__(self, initial_state: tuple=(0, 0), default_reward: tuple=(0,), seed: int=0, columns: int=10): :param initial_state: Initial state whe... | Implement the Python class `DeepSeaTreasureRightDown` described below.
Class description:
Implement the DeepSeaTreasureRightDown class.
Method signatures and docstrings:
- def __init__(self, initial_state: tuple=(0, 0), default_reward: tuple=(0,), seed: int=0, columns: int=10): :param initial_state: Initial state whe... | b51c64c867e15356c9f978839fd0040182324edd | <|skeleton|>
class DeepSeaTreasureRightDown:
def __init__(self, initial_state: tuple=(0, 0), default_reward: tuple=(0,), seed: int=0, columns: int=10):
""":param initial_state: Initial state where start the agent. :param default_reward: (time_inverted, treasure_value) :param seed: Seed used for np.random.R... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeepSeaTreasureRightDown:
def __init__(self, initial_state: tuple=(0, 0), default_reward: tuple=(0,), seed: int=0, columns: int=10):
""":param initial_state: Initial state where start the agent. :param default_reward: (time_inverted, treasure_value) :param seed: Seed used for np.random.RandomState met... | the_stack_v2_python_sparse | environments/deep_sea_treasure_right_down.py | Pozas91/tiadas | train | 1 | |
6db837e1bcaea8cf9b304017d511826394e1a2f3 | [
"userdb = CombaUser()\nif userdb.hasPassword(username, password):\n return userdb.getUser(username)\nelse:\n return False",
"valid_user = self.check_auth(username, password)\nif valid_user:\n group = None\n groupcreated = None\n try:\n user = User.objects.get(username=username)\n except U... | <|body_start_0|>
userdb = CombaUser()
if userdb.hasPassword(username, password):
return userdb.getUser(username)
else:
return False
<|end_body_0|>
<|body_start_1|>
valid_user = self.check_auth(username, password)
if valid_user:
group = None
... | Provides authentication via comba_lib | RedisBackend | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RedisBackend:
"""Provides authentication via comba_lib"""
def check_auth(self, username, password):
"""check user and password in redis db :param username: :param password: :return:"""
<|body_0|>
def authenticate(self, username=None, password=None):
"""Overwrite ... | stack_v2_sparse_classes_75kplus_train_001135 | 3,013 | no_license | [
{
"docstring": "check user and password in redis db :param username: :param password: :return:",
"name": "check_auth",
"signature": "def check_auth(self, username, password)"
},
{
"docstring": "Overwrite the parent authenticate method :param username: :param password: :return:",
"name": "aut... | 3 | stack_v2_sparse_classes_30k_test_000859 | Implement the Python class `RedisBackend` described below.
Class description:
Provides authentication via comba_lib
Method signatures and docstrings:
- def check_auth(self, username, password): check user and password in redis db :param username: :param password: :return:
- def authenticate(self, username=None, passw... | Implement the Python class `RedisBackend` described below.
Class description:
Provides authentication via comba_lib
Method signatures and docstrings:
- def check_auth(self, username, password): check user and password in redis db :param username: :param password: :return:
- def authenticate(self, username=None, passw... | eb6b8bca4f782f7aa8fbabd4fddbfddaae769252 | <|skeleton|>
class RedisBackend:
"""Provides authentication via comba_lib"""
def check_auth(self, username, password):
"""check user and password in redis db :param username: :param password: :return:"""
<|body_0|>
def authenticate(self, username=None, password=None):
"""Overwrite ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RedisBackend:
"""Provides authentication via comba_lib"""
def check_auth(self, username, password):
"""check user and password in redis db :param username: :param password: :return:"""
userdb = CombaUser()
if userdb.hasPassword(username, password):
return userdb.getUse... | the_stack_v2_python_sparse | comba_web/redisbackend.py | combaos/comba_web | train | 0 |
58b582a0f06ce719f0e92f0b51b9ff61d70899da | [
"if obj.id:\n url = reverse('admin:{}_{}_upvote'.format(self.model._meta.app_label, self.model._meta.model_name), args=(obj.id,))\nelse:\n url = '#'\nreturn mark_safe('<a href=\"{}\"><div class=\"arrow-up\"></div></a>'.format(url))",
"if obj.id:\n url = reverse('admin:{}_{}_downvote'.format(self.model._m... | <|body_start_0|>
if obj.id:
url = reverse('admin:{}_{}_upvote'.format(self.model._meta.app_label, self.model._meta.model_name), args=(obj.id,))
else:
url = '#'
return mark_safe('<a href="{}"><div class="arrow-up"></div></a>'.format(url))
<|end_body_0|>
<|body_start_1|>
... | Admin support for voteable models. | VoteableModelAdmin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VoteableModelAdmin:
"""Admin support for voteable models."""
def upvote(self, obj):
"""Provide a button to upvote instance."""
<|body_0|>
def downvote(self, obj):
"""Provide a button to downvote instance."""
<|body_1|>
def upvote_view(self, request, ... | stack_v2_sparse_classes_75kplus_train_001136 | 3,959 | permissive | [
{
"docstring": "Provide a button to upvote instance.",
"name": "upvote",
"signature": "def upvote(self, obj)"
},
{
"docstring": "Provide a button to downvote instance.",
"name": "downvote",
"signature": "def downvote(self, obj)"
},
{
"docstring": "Admin view to upvote object.",
... | 5 | stack_v2_sparse_classes_30k_train_046786 | Implement the Python class `VoteableModelAdmin` described below.
Class description:
Admin support for voteable models.
Method signatures and docstrings:
- def upvote(self, obj): Provide a button to upvote instance.
- def downvote(self, obj): Provide a button to downvote instance.
- def upvote_view(self, request, obj_... | Implement the Python class `VoteableModelAdmin` described below.
Class description:
Admin support for voteable models.
Method signatures and docstrings:
- def upvote(self, obj): Provide a button to upvote instance.
- def downvote(self, obj): Provide a button to downvote instance.
- def upvote_view(self, request, obj_... | 5f2ad4a15dc62160c6d03c87c121e934cacb8228 | <|skeleton|>
class VoteableModelAdmin:
"""Admin support for voteable models."""
def upvote(self, obj):
"""Provide a button to upvote instance."""
<|body_0|>
def downvote(self, obj):
"""Provide a button to downvote instance."""
<|body_1|>
def upvote_view(self, request, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VoteableModelAdmin:
"""Admin support for voteable models."""
def upvote(self, obj):
"""Provide a button to upvote instance."""
if obj.id:
url = reverse('admin:{}_{}_upvote'.format(self.model._meta.app_label, self.model._meta.model_name), args=(obj.id,))
else:
... | the_stack_v2_python_sparse | quotetron/admin.py | CMU-Robotics-Club/roboticsclub.org | train | 0 |
5cb2a47095bcd1a84838323141c695c7e8167725 | [
"if isinstance(value, str) and value.replace(' ', '') == '':\n raise InvalidEmptyValue(field_name=field.name)\nreturn value",
"ti_utils = ThreatIntelUtil(session_tc=registry.session_tc)\ngroup_types = cls.group_types or ti_utils.group_types\nif value.lower() not in [i.lower() for i in group_types]:\n raise ... | <|body_start_0|>
if isinstance(value, str) and value.replace(' ', '') == '':
raise InvalidEmptyValue(field_name=field.name)
return value
<|end_body_0|>
<|body_start_1|>
ti_utils = ThreatIntelUtil(session_tc=registry.session_tc)
group_types = cls.group_types or ti_utils.group... | Group Entity Field (Model) Type | GroupEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupEntity:
"""Group Entity Field (Model) Type"""
def is_empty(cls, value: str, field: ModelField) -> str:
"""Validate that the value is a non-empty string."""
<|body_0|>
def is_type(cls, value: str, field: ModelField) -> str:
"""Validate that the value is a non... | stack_v2_sparse_classes_75kplus_train_001137 | 2,435 | permissive | [
{
"docstring": "Validate that the value is a non-empty string.",
"name": "is_empty",
"signature": "def is_empty(cls, value: str, field: ModelField) -> str"
},
{
"docstring": "Validate that the value is a non-empty string. Without the always and pre args, None values will validated before this va... | 2 | stack_v2_sparse_classes_30k_train_015219 | Implement the Python class `GroupEntity` described below.
Class description:
Group Entity Field (Model) Type
Method signatures and docstrings:
- def is_empty(cls, value: str, field: ModelField) -> str: Validate that the value is a non-empty string.
- def is_type(cls, value: str, field: ModelField) -> str: Validate th... | Implement the Python class `GroupEntity` described below.
Class description:
Group Entity Field (Model) Type
Method signatures and docstrings:
- def is_empty(cls, value: str, field: ModelField) -> str: Validate that the value is a non-empty string.
- def is_type(cls, value: str, field: ModelField) -> str: Validate th... | 30dc147e40d63d1082ec2a5e6c62005b60c29c37 | <|skeleton|>
class GroupEntity:
"""Group Entity Field (Model) Type"""
def is_empty(cls, value: str, field: ModelField) -> str:
"""Validate that the value is a non-empty string."""
<|body_0|>
def is_type(cls, value: str, field: ModelField) -> str:
"""Validate that the value is a non... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GroupEntity:
"""Group Entity Field (Model) Type"""
def is_empty(cls, value: str, field: ModelField) -> str:
"""Validate that the value is a non-empty string."""
if isinstance(value, str) and value.replace(' ', '') == '':
raise InvalidEmptyValue(field_name=field.name)
r... | the_stack_v2_python_sparse | tcex/input/field_type/group_entity.py | ThreatConnect-Inc/tcex | train | 24 |
675f1fd78983342da841d16e51b55d1771cd228a | [
"if journey is None:\n return self.filter(Q(journey__template__user=user) | Q(journey__passengers__user=user))\nif not journey.is_messenger_allowed(user):\n return self.none()\nreturn self.filter(journey=journey)",
"if not journey.is_messenger_allowed(user):\n raise UserNotAllowed()\nreturn self.create(u... | <|body_start_0|>
if journey is None:
return self.filter(Q(journey__template__user=user) | Q(journey__passengers__user=user))
if not journey.is_messenger_allowed(user):
return self.none()
return self.filter(journey=journey)
<|end_body_0|>
<|body_start_1|>
if not j... | Manager to handle messages. | MessageManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MessageManager:
"""Manager to handle messages."""
def list(self, user, journey=None):
"""Gets the list of all messages the given user could read. :param user: :param journey:"""
<|body_0|>
def send(self, user, message, journey):
"""User tries send 'message' to 'j... | stack_v2_sparse_classes_75kplus_train_001138 | 9,126 | no_license | [
{
"docstring": "Gets the list of all messages the given user could read. :param user: :param journey:",
"name": "list",
"signature": "def list(self, user, journey=None)"
},
{
"docstring": "User tries send 'message' to 'journey' group.",
"name": "send",
"signature": "def send(self, user, ... | 2 | stack_v2_sparse_classes_30k_train_013773 | Implement the Python class `MessageManager` described below.
Class description:
Manager to handle messages.
Method signatures and docstrings:
- def list(self, user, journey=None): Gets the list of all messages the given user could read. :param user: :param journey:
- def send(self, user, message, journey): User tries... | Implement the Python class `MessageManager` described below.
Class description:
Manager to handle messages.
Method signatures and docstrings:
- def list(self, user, journey=None): Gets the list of all messages the given user could read. :param user: :param journey:
- def send(self, user, message, journey): User tries... | 1713bb544bbddacda34b7d7dbd6e422872546776 | <|skeleton|>
class MessageManager:
"""Manager to handle messages."""
def list(self, user, journey=None):
"""Gets the list of all messages the given user could read. :param user: :param journey:"""
<|body_0|>
def send(self, user, message, journey):
"""User tries send 'message' to 'j... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MessageManager:
"""Manager to handle messages."""
def list(self, user, journey=None):
"""Gets the list of all messages the given user could read. :param user: :param journey:"""
if journey is None:
return self.filter(Q(journey__template__user=user) | Q(journey__passengers__use... | the_stack_v2_python_sparse | upvcarshare/journeys/managers.py | marcosgabarda/upvcarshare | train | 0 |
61265c35eb9602d885e82c8387d9f81606bf6f9d | [
"help_width = get_help_width()\nself._boot_arg = dict()\nself.deprecated_bootargs = []\nself.bootarg_prefix = kwargs.pop('bootarg_prefix', '')\nself.require_prefix = kwargs.pop('require_prefix', True)\nArgumentParser.__init__(self, *args, description=DESCRIPTION, formatter_class=lambda prog: HelpFormatter(prog, max... | <|body_start_0|>
help_width = get_help_width()
self._boot_arg = dict()
self.deprecated_bootargs = []
self.bootarg_prefix = kwargs.pop('bootarg_prefix', '')
self.require_prefix = kwargs.pop('require_prefix', True)
ArgumentParser.__init__(self, *args, description=DESCRIPTIO... | Subclass of ArgumentParser that also examines boot arguments. | AnacondaArgumentParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnacondaArgumentParser:
"""Subclass of ArgumentParser that also examines boot arguments."""
def __init__(self, *args, **kwargs):
"""If the "bootarg_prefix" keyword argument is set, it's assumed that all bootargs will start with that prefix. "require_prefix" is a bool: False: accept t... | stack_v2_sparse_classes_75kplus_train_001139 | 13,877 | no_license | [
{
"docstring": "If the \"bootarg_prefix\" keyword argument is set, it's assumed that all bootargs will start with that prefix. \"require_prefix\" is a bool: False: accept the argument with or without the prefix. True: ignore the argument without the prefix. (default)",
"name": "__init__",
"signature": "... | 5 | null | Implement the Python class `AnacondaArgumentParser` described below.
Class description:
Subclass of ArgumentParser that also examines boot arguments.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): If the "bootarg_prefix" keyword argument is set, it's assumed that all bootargs will start with... | Implement the Python class `AnacondaArgumentParser` described below.
Class description:
Subclass of ArgumentParser that also examines boot arguments.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): If the "bootarg_prefix" keyword argument is set, it's assumed that all bootargs will start with... | 6976d7e1d8af45b1432cbf4f1461076ca04349e0 | <|skeleton|>
class AnacondaArgumentParser:
"""Subclass of ArgumentParser that also examines boot arguments."""
def __init__(self, *args, **kwargs):
"""If the "bootarg_prefix" keyword argument is set, it's assumed that all bootargs will start with that prefix. "require_prefix" is a bool: False: accept t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AnacondaArgumentParser:
"""Subclass of ArgumentParser that also examines boot arguments."""
def __init__(self, *args, **kwargs):
"""If the "bootarg_prefix" keyword argument is set, it's assumed that all bootargs will start with that prefix. "require_prefix" is a bool: False: accept the argument w... | the_stack_v2_python_sparse | rootfs/usr/lib64/python2.7/site-packages/pyanaconda/anaconda_argparse.py | outstanding-mjy/make_rootfs | train | 0 |
d675ffb926b6f8f2fb131440c062b5fa10eee2f4 | [
"super().__init__()\nself.up = nn.ConvTranspose2d(in_channels, in_channels, kernel_size=2, stride=2)\nself.conv = nn.Conv2d(in_channels, out_channels, kernel_size=3, padding=1)",
"x = self.up(x)\nx = self.conv(x)\nx = F.relu(x)\nreturn x"
] | <|body_start_0|>
super().__init__()
self.up = nn.ConvTranspose2d(in_channels, in_channels, kernel_size=2, stride=2)
self.conv = nn.Conv2d(in_channels, out_channels, kernel_size=3, padding=1)
<|end_body_0|>
<|body_start_1|>
x = self.up(x)
x = self.conv(x)
x = F.relu(x)
... | Transpose convolutional block to upscale input. 2x2 Transpoe convolution followed by a convolutional layer with 3x3 kernel with 1 padding, Max pooling and Relu activations. Channels must be specified by user. | UpConvBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpConvBlock:
"""Transpose convolutional block to upscale input. 2x2 Transpoe convolution followed by a convolutional layer with 3x3 kernel with 1 padding, Max pooling and Relu activations. Channels must be specified by user."""
def __init__(self, in_channels, out_channels):
"""Init. ... | stack_v2_sparse_classes_75kplus_train_001140 | 10,936 | no_license | [
{
"docstring": "Init. Args: in_channels(int): Input channels. out_channels(int): Output channels.",
"name": "__init__",
"signature": "def __init__(self, in_channels, out_channels)"
},
{
"docstring": "Forward pass. Args: x(torch.Tensor): Input data. Returns: torch.Tensor: Activations.",
"name... | 2 | stack_v2_sparse_classes_30k_train_039141 | Implement the Python class `UpConvBlock` described below.
Class description:
Transpose convolutional block to upscale input. 2x2 Transpoe convolution followed by a convolutional layer with 3x3 kernel with 1 padding, Max pooling and Relu activations. Channels must be specified by user.
Method signatures and docstrings... | Implement the Python class `UpConvBlock` described below.
Class description:
Transpose convolutional block to upscale input. 2x2 Transpoe convolution followed by a convolutional layer with 3x3 kernel with 1 padding, Max pooling and Relu activations. Channels must be specified by user.
Method signatures and docstrings... | 9027b529eaa4cf0a38f25512141810f92db99639 | <|skeleton|>
class UpConvBlock:
"""Transpose convolutional block to upscale input. 2x2 Transpoe convolution followed by a convolutional layer with 3x3 kernel with 1 padding, Max pooling and Relu activations. Channels must be specified by user."""
def __init__(self, in_channels, out_channels):
"""Init. ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UpConvBlock:
"""Transpose convolutional block to upscale input. 2x2 Transpoe convolution followed by a convolutional layer with 3x3 kernel with 1 padding, Max pooling and Relu activations. Channels must be specified by user."""
def __init__(self, in_channels, out_channels):
"""Init. Args: in_chan... | the_stack_v2_python_sparse | grae/models/torch_modules.py | jakerhodes/GRAE | train | 0 |
25abc94b08d5c5fcc5839375fb347f399eade309 | [
"spus = Brand.objects.all()\nspus_serial = BrandSerializer(spus, many=True)\nreturn Response(spus_serial.data)",
"spus = GoodsCategory.objects.get(id=pk).subs.all()\nspus_serial = GoodsCategorySerializer(spus, many=True)\nreturn Response(spus_serial.data)",
"spus = GoodsCategory.objects.all()\nspus_serial = Goo... | <|body_start_0|>
spus = Brand.objects.all()
spus_serial = BrandSerializer(spus, many=True)
return Response(spus_serial.data)
<|end_body_0|>
<|body_start_1|>
spus = GoodsCategory.objects.get(id=pk).subs.all()
spus_serial = GoodsCategorySerializer(spus, many=True)
return R... | SPU管理 | SPUView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SPUView:
"""SPU管理"""
def simple(self, request):
"""获取商品品牌"""
<|body_0|>
def category_23(self, request, pk):
"""获取二三级分类"""
<|body_1|>
def category_1(self, request, pk=None):
"""获取一级分类"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_001141 | 1,328 | no_license | [
{
"docstring": "获取商品品牌",
"name": "simple",
"signature": "def simple(self, request)"
},
{
"docstring": "获取二三级分类",
"name": "category_23",
"signature": "def category_23(self, request, pk)"
},
{
"docstring": "获取一级分类",
"name": "category_1",
"signature": "def category_1(self, r... | 3 | null | Implement the Python class `SPUView` described below.
Class description:
SPU管理
Method signatures and docstrings:
- def simple(self, request): 获取商品品牌
- def category_23(self, request, pk): 获取二三级分类
- def category_1(self, request, pk=None): 获取一级分类 | Implement the Python class `SPUView` described below.
Class description:
SPU管理
Method signatures and docstrings:
- def simple(self, request): 获取商品品牌
- def category_23(self, request, pk): 获取二三级分类
- def category_1(self, request, pk=None): 获取一级分类
<|skeleton|>
class SPUView:
"""SPU管理"""
def simple(self, request... | e3976cbb9e96a1558f4e00abed1c61d887f915b1 | <|skeleton|>
class SPUView:
"""SPU管理"""
def simple(self, request):
"""获取商品品牌"""
<|body_0|>
def category_23(self, request, pk):
"""获取二三级分类"""
<|body_1|>
def category_1(self, request, pk=None):
"""获取一级分类"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SPUView:
"""SPU管理"""
def simple(self, request):
"""获取商品品牌"""
spus = Brand.objects.all()
spus_serial = BrandSerializer(spus, many=True)
return Response(spus_serial.data)
def category_23(self, request, pk):
"""获取二三级分类"""
spus = GoodsCategory.objects.get(... | the_stack_v2_python_sparse | meiduo_mall/meiduo_mall/apps/meiduo_admin/views/spus.py | yi0506/meiduo | train | 0 |
09edf147777f1ff5956cb528ee35ae9c7e033b25 | [
"super(TaskTarget, self).__init__()\nself.service_name = service_name\nself.job_name = job_name\nself.region = region\nself.hostname = hostname\nself.task_num = task_num\nself._fields = ('service_name', 'job_name', 'region', 'hostname', 'task_num')",
"collection.task.service_name = self.service_name\ncollection.t... | <|body_start_0|>
super(TaskTarget, self).__init__()
self.service_name = service_name
self.job_name = job_name
self.region = region
self.hostname = hostname
self.task_num = task_num
self._fields = ('service_name', 'job_name', 'region', 'hostname', 'task_num')
<|end... | Monitoring interface class for monitoring active jobs or processes. | TaskTarget | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskTarget:
"""Monitoring interface class for monitoring active jobs or processes."""
def __init__(self, service_name, job_name, region, hostname, task_num=0):
"""Create a Target object exporting info about a specific task. Args: service_name (str): service of which this task is a pa... | stack_v2_sparse_classes_75kplus_train_001142 | 4,448 | permissive | [
{
"docstring": "Create a Target object exporting info about a specific task. Args: service_name (str): service of which this task is a part. job_name (str): specific name of this task. region (str): general region in which this task is running. hostname (str): specific machine on which this task is running. tas... | 2 | stack_v2_sparse_classes_30k_train_051944 | Implement the Python class `TaskTarget` described below.
Class description:
Monitoring interface class for monitoring active jobs or processes.
Method signatures and docstrings:
- def __init__(self, service_name, job_name, region, hostname, task_num=0): Create a Target object exporting info about a specific task. Arg... | Implement the Python class `TaskTarget` described below.
Class description:
Monitoring interface class for monitoring active jobs or processes.
Method signatures and docstrings:
- def __init__(self, service_name, job_name, region, hostname, task_num=0): Create a Target object exporting info about a specific task. Arg... | 53102de187a48ac2cfc241fef54dcbc29c453a8e | <|skeleton|>
class TaskTarget:
"""Monitoring interface class for monitoring active jobs or processes."""
def __init__(self, service_name, job_name, region, hostname, task_num=0):
"""Create a Target object exporting info about a specific task. Args: service_name (str): service of which this task is a pa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TaskTarget:
"""Monitoring interface class for monitoring active jobs or processes."""
def __init__(self, service_name, job_name, region, hostname, task_num=0):
"""Create a Target object exporting info about a specific task. Args: service_name (str): service of which this task is a part. job_name ... | the_stack_v2_python_sparse | third_party/gae_ts_mon/gae_ts_mon/common/targets.py | catapult-project/catapult | train | 2,032 |
3f5fc35bed313825a2b58d9dc200dd1315d4914a | [
"this_target_matrix = standalone_utils.do_2d_convolution(feature_matrix=TARGET_MATRIX, kernel_matrix=WEIGHT_MATRIX_SIZE0, pad_edges=True, stride_length_px=1)\nself.assertTrue(numpy.allclose(this_target_matrix, TARGET_MATRIX, atol=TOLERANCE))\nthis_prediction_matrix = standalone_utils.do_2d_convolution(feature_matri... | <|body_start_0|>
this_target_matrix = standalone_utils.do_2d_convolution(feature_matrix=TARGET_MATRIX, kernel_matrix=WEIGHT_MATRIX_SIZE0, pad_edges=True, stride_length_px=1)
self.assertTrue(numpy.allclose(this_target_matrix, TARGET_MATRIX, atol=TOLERANCE))
this_prediction_matrix = standalone_uti... | Each method is a unit test for standalone_utils.py. | StandaloneUtilsTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StandaloneUtilsTests:
"""Each method is a unit test for standalone_utils.py."""
def test_do_2d_convolution_size0(self):
"""Ensures correct output from do_2d_convolution. In this case, half-window size is 0 pixels."""
<|body_0|>
def test_do_2d_convolution_size1(self):
... | stack_v2_sparse_classes_75kplus_train_001143 | 4,632 | no_license | [
{
"docstring": "Ensures correct output from do_2d_convolution. In this case, half-window size is 0 pixels.",
"name": "test_do_2d_convolution_size0",
"signature": "def test_do_2d_convolution_size0(self)"
},
{
"docstring": "Ensures correct output from do_2d_convolution. In this case, half-window s... | 3 | null | Implement the Python class `StandaloneUtilsTests` described below.
Class description:
Each method is a unit test for standalone_utils.py.
Method signatures and docstrings:
- def test_do_2d_convolution_size0(self): Ensures correct output from do_2d_convolution. In this case, half-window size is 0 pixels.
- def test_do... | Implement the Python class `StandaloneUtilsTests` described below.
Class description:
Each method is a unit test for standalone_utils.py.
Method signatures and docstrings:
- def test_do_2d_convolution_size0(self): Ensures correct output from do_2d_convolution. In this case, half-window size is 0 pixels.
- def test_do... | cf5e9682bc3182305274132ae246bc72d994308f | <|skeleton|>
class StandaloneUtilsTests:
"""Each method is a unit test for standalone_utils.py."""
def test_do_2d_convolution_size0(self):
"""Ensures correct output from do_2d_convolution. In this case, half-window size is 0 pixels."""
<|body_0|>
def test_do_2d_convolution_size1(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StandaloneUtilsTests:
"""Each method is a unit test for standalone_utils.py."""
def test_do_2d_convolution_size0(self):
"""Ensures correct output from do_2d_convolution. In this case, half-window size is 0 pixels."""
this_target_matrix = standalone_utils.do_2d_convolution(feature_matrix=T... | the_stack_v2_python_sparse | ml4convection/machine_learning/standalone_utils_test.py | thunderhoser/ml4convection | train | 14 |
9059e5efda6ca76153784e9dd736cc896b348a89 | [
"self.screen_width = 1200\nself.screen_height = 800\nself.bg_color = (230, 230, 230)\nself.ship_speed_factor = 1.5\nself.ship_limit = 1\nself.bullet_speed_factor = 10\nself.bullet_width = 500\nself.bullet_height = 15\nself.bullet_color = (192, 14, 235)\nself.bullets_allowed = 30\nself.alien_speed_factor = 1\nself.f... | <|body_start_0|>
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
self.ship_speed_factor = 1.5
self.ship_limit = 1
self.bullet_speed_factor = 10
self.bullet_width = 500
self.bullet_height = 15
self.bullet_color = (1... | 存储《外星人入侵》的所有设置的类 | Settings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的设置"""
<|body_0|>
def initialize_dynamic_settings(self):
"""初始化随游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_75kplus_train_001144 | 1,663 | no_license | [
{
"docstring": "初始化游戏的设置",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "初始化随游戏进行而变化的设置",
"name": "initialize_dynamic_settings",
"signature": "def initialize_dynamic_settings(self)"
},
{
"docstring": "提高速度设置",
"name": "increase_speed",
"signatur... | 3 | stack_v2_sparse_classes_30k_train_002976 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》的所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏的设置
- def initialize_dynamic_settings(self): 初始化随游戏进行而变化的设置
- def increase_speed(self): 提高速度设置 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》的所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏的设置
- def initialize_dynamic_settings(self): 初始化随游戏进行而变化的设置
- def increase_speed(self): 提高速度设置
<|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __ini... | 53073a7e6b393f92f5737edaa917c9100b7e0a5e | <|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的设置"""
<|body_0|>
def initialize_dynamic_settings(self):
"""初始化随游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的设置"""
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
self.ship_speed_factor = 1.5
self.ship_limit = 1
self.bullet_speed_factor = 10
self.bullet_... | the_stack_v2_python_sparse | python/AllienGame/settings.py | amorcc/code | train | 0 |
c9940f4dc7155ad37b68d220ae4e8beddf19646a | [
"args_parser = RequestParser()\nargs_parser.add_argument('page', type=inputs.positive, required=False, location='args')\nargs_parser.add_argument('per_page', type=inputs.int_range(constants.PER_PAGE_MIN, constants.PER_PAGE_MAX, 'per_page'), required=False, location='args')\nargs_parser.add_argument('word', location... | <|body_start_0|>
args_parser = RequestParser()
args_parser.add_argument('page', type=inputs.positive, required=False, location='args')
args_parser.add_argument('per_page', type=inputs.int_range(constants.PER_PAGE_MIN, constants.PER_PAGE_MAX, 'per_page'), required=False, location='args')
... | 敏感词 | SensitiveWordListResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SensitiveWordListResource:
"""敏感词"""
def get(self):
"""获取敏感词列表"""
<|body_0|>
def post(self):
"""添加敏感词"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args_parser = RequestParser()
args_parser.add_argument('page', type=inputs.positive, re... | stack_v2_sparse_classes_75kplus_train_001145 | 5,331 | no_license | [
{
"docstring": "获取敏感词列表",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "添加敏感词",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_024774 | Implement the Python class `SensitiveWordListResource` described below.
Class description:
敏感词
Method signatures and docstrings:
- def get(self): 获取敏感词列表
- def post(self): 添加敏感词 | Implement the Python class `SensitiveWordListResource` described below.
Class description:
敏感词
Method signatures and docstrings:
- def get(self): 获取敏感词列表
- def post(self): 添加敏感词
<|skeleton|>
class SensitiveWordListResource:
"""敏感词"""
def get(self):
"""获取敏感词列表"""
<|body_0|>
def post(self... | c9703a9c57a98babf8d1e41b227aada9ef4bfe15 | <|skeleton|>
class SensitiveWordListResource:
"""敏感词"""
def get(self):
"""获取敏感词列表"""
<|body_0|>
def post(self):
"""添加敏感词"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SensitiveWordListResource:
"""敏感词"""
def get(self):
"""获取敏感词列表"""
args_parser = RequestParser()
args_parser.add_argument('page', type=inputs.positive, required=False, location='args')
args_parser.add_argument('per_page', type=inputs.int_range(constants.PER_PAGE_MIN, consta... | the_stack_v2_python_sparse | mis/resources/recommend/sensitive.py | Yaooooooooooooo/toutiao-backend | train | 0 |
49da06c27a279978a29d115758ac6cec5aebf1c6 | [
"serializer = TJWSerializer(settings.SECRET_KEY, 3600 * 24)\ndata = {'username': self.username, 'email': self.email}\ntoken = serializer.dumps(data).decode()\nverify_url = settings.EMAIL_VERIFY_URL + '?token=' + token\nreturn verify_url",
"serializer = TJWSerializer(settings.SECRET_KEY, 3600 * 24)\ntry:\n data... | <|body_start_0|>
serializer = TJWSerializer(settings.SECRET_KEY, 3600 * 24)
data = {'username': self.username, 'email': self.email}
token = serializer.dumps(data).decode()
verify_url = settings.EMAIL_VERIFY_URL + '?token=' + token
return verify_url
<|end_body_0|>
<|body_start_1|... | User | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class User:
def generate_email_verify_url(self):
"""生成邮箱激活连接"""
<|body_0|>
def check_verify_email_token(token):
"""对token解密，并查询对应的user"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
serializer = TJWSerializer(settings.SECRET_KEY, 3600 * 24)
data ... | stack_v2_sparse_classes_75kplus_train_001146 | 2,521 | no_license | [
{
"docstring": "生成邮箱激活连接",
"name": "generate_email_verify_url",
"signature": "def generate_email_verify_url(self)"
},
{
"docstring": "对token解密，并查询对应的user",
"name": "check_verify_email_token",
"signature": "def check_verify_email_token(token)"
}
] | 2 | null | Implement the Python class `User` described below.
Class description:
Implement the User class.
Method signatures and docstrings:
- def generate_email_verify_url(self): 生成邮箱激活连接
- def check_verify_email_token(token): 对token解密，并查询对应的user | Implement the Python class `User` described below.
Class description:
Implement the User class.
Method signatures and docstrings:
- def generate_email_verify_url(self): 生成邮箱激活连接
- def check_verify_email_token(token): 对token解密，并查询对应的user
<|skeleton|>
class User:
def generate_email_verify_url(self):
"""生成... | 94d1ea40fdcdbb6288f9ed547d22d4f3111cd264 | <|skeleton|>
class User:
def generate_email_verify_url(self):
"""生成邮箱激活连接"""
<|body_0|>
def check_verify_email_token(token):
"""对token解密，并查询对应的user"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class User:
def generate_email_verify_url(self):
"""生成邮箱激活连接"""
serializer = TJWSerializer(settings.SECRET_KEY, 3600 * 24)
data = {'username': self.username, 'email': self.email}
token = serializer.dumps(data).decode()
verify_url = settings.EMAIL_VERIFY_URL + '?token=' + toke... | the_stack_v2_python_sparse | dada_mall/dada_mall/apps/user/models.py | dingshenghao/dada_mall | train | 0 | |
ac960c5200912432220c41002eaa00ee8d86af63 | [
"if response_status.lower() == 'success':\n assert f'Response status: {response_status}'\nelif response_status != 'success':\n assert False, f'Response status: {response_status}'\nelse:\n assert False, 'Something wrong'",
"if response_status_code == 200:\n assert f'Response status code: {response_stat... | <|body_start_0|>
if response_status.lower() == 'success':
assert f'Response status: {response_status}'
elif response_status != 'success':
assert False, f'Response status: {response_status}'
else:
assert False, 'Something wrong'
<|end_body_0|>
<|body_start_1|>... | TestDog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDog:
def test_response_status(self, response_status):
"""Тест проверяет текст успешности ответа сервера для запроса произвольно выбранного изображения собаки"""
<|body_0|>
def test_response_status_code(self, response_status_code):
"""Тест проверяет код успешности... | stack_v2_sparse_classes_75kplus_train_001147 | 2,869 | no_license | [
{
"docstring": "Тест проверяет текст успешности ответа сервера для запроса произвольно выбранного изображения собаки",
"name": "test_response_status",
"signature": "def test_response_status(self, response_status)"
},
{
"docstring": "Тест проверяет код успешности ответа сервера для запроса произв... | 5 | stack_v2_sparse_classes_30k_train_006459 | Implement the Python class `TestDog` described below.
Class description:
Implement the TestDog class.
Method signatures and docstrings:
- def test_response_status(self, response_status): Тест проверяет текст успешности ответа сервера для запроса произвольно выбранного изображения собаки
- def test_response_status_cod... | Implement the Python class `TestDog` described below.
Class description:
Implement the TestDog class.
Method signatures and docstrings:
- def test_response_status(self, response_status): Тест проверяет текст успешности ответа сервера для запроса произвольно выбранного изображения собаки
- def test_response_status_cod... | 54467b2334b33ae48b5fa5a65cab47fdf03967be | <|skeleton|>
class TestDog:
def test_response_status(self, response_status):
"""Тест проверяет текст успешности ответа сервера для запроса произвольно выбранного изображения собаки"""
<|body_0|>
def test_response_status_code(self, response_status_code):
"""Тест проверяет код успешности... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestDog:
def test_response_status(self, response_status):
"""Тест проверяет текст успешности ответа сервера для запроса произвольно выбранного изображения собаки"""
if response_status.lower() == 'success':
assert f'Response status: {response_status}'
elif response_status !=... | the_stack_v2_python_sparse | 03_REST_API/dog_api/test_dog_api.py | vamotest/qa_automation | train | 4 | |
115e070509a3f9c3e7c618263faedf6b4e97bff3 | [
"self.c = capacity\nself.used = []\nself.f = {}\nself.m = {}",
"if key not in self.m:\n return -1\nself.f[key] += 1\nself.used.remove(key)\nself.used.append(key)\nreturn self.m[key]",
"if self.c == 0:\n return\nif key in self.f:\n self.f[key] += 1\n self.used.remove(key)\n self.used.append(key)\n... | <|body_start_0|>
self.c = capacity
self.used = []
self.f = {}
self.m = {}
<|end_body_0|>
<|body_start_1|>
if key not in self.m:
return -1
self.f[key] += 1
self.used.remove(key)
self.used.append(key)
return self.m[key]
<|end_body_1|>
<... | LFUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus_train_001148 | 1,544 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: void",
"name": "se... | 3 | stack_v2_sparse_classes_30k_train_049752 | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: void | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: void
<|sk... | fa1a63cb192666fc6aa5c7c72130993818ea58d0 | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.c = capacity
self.used = []
self.f = {}
self.m = {}
def get(self, key):
""":type key: int :rtype: int"""
if key not in self.m:
return -1
self.f[key] += 1
... | the_stack_v2_python_sparse | q460.py | gitttttt/lc | train | 0 | |
aeb3ab99d75b26bd66743ad4a6bee3666807a4ab | [
"fmt = 'PO-{abc:02f}-{ref:04d}-{date}-???'\ninfo = InvenTree.format.parse_format_string(fmt)\nself.assertIn('abc', info)\nself.assertIn('ref', info)\nself.assertIn('date', info)\nfor fmt in ['PO-{{xyz}', 'PO-{xyz}}', 'PO-{xyz}-{']:\n with self.assertRaises(ValueError):\n InvenTree.format.parse_format_stri... | <|body_start_0|>
fmt = 'PO-{abc:02f}-{ref:04d}-{date}-???'
info = InvenTree.format.parse_format_string(fmt)
self.assertIn('abc', info)
self.assertIn('ref', info)
self.assertIn('date', info)
for fmt in ['PO-{{xyz}', 'PO-{xyz}}', 'PO-{xyz}-{']:
with self.assertR... | Unit tests for custom string formatting functionality | FormatTest | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FormatTest:
"""Unit tests for custom string formatting functionality"""
def test_parse(self):
"""Tests for the 'parse_format_string' function"""
<|body_0|>
def test_create_regex(self):
"""Test function for creating a regex from a format string"""
<|body_1... | stack_v2_sparse_classes_75kplus_train_001149 | 41,191 | permissive | [
{
"docstring": "Tests for the 'parse_format_string' function",
"name": "test_parse",
"signature": "def test_parse(self)"
},
{
"docstring": "Test function for creating a regex from a format string",
"name": "test_create_regex",
"signature": "def test_create_regex(self)"
},
{
"docs... | 4 | stack_v2_sparse_classes_30k_train_016399 | Implement the Python class `FormatTest` described below.
Class description:
Unit tests for custom string formatting functionality
Method signatures and docstrings:
- def test_parse(self): Tests for the 'parse_format_string' function
- def test_create_regex(self): Test function for creating a regex from a format strin... | Implement the Python class `FormatTest` described below.
Class description:
Unit tests for custom string formatting functionality
Method signatures and docstrings:
- def test_parse(self): Tests for the 'parse_format_string' function
- def test_create_regex(self): Test function for creating a regex from a format strin... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class FormatTest:
"""Unit tests for custom string formatting functionality"""
def test_parse(self):
"""Tests for the 'parse_format_string' function"""
<|body_0|>
def test_create_regex(self):
"""Test function for creating a regex from a format string"""
<|body_1... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FormatTest:
"""Unit tests for custom string formatting functionality"""
def test_parse(self):
"""Tests for the 'parse_format_string' function"""
fmt = 'PO-{abc:02f}-{ref:04d}-{date}-???'
info = InvenTree.format.parse_format_string(fmt)
self.assertIn('abc', info)
se... | the_stack_v2_python_sparse | InvenTree/InvenTree/tests.py | inventree/InvenTree | train | 3,077 |
d994fc32514f8166a35f40972a7fc640054a3b88 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Retrieves analysis results of Cloud components such as Docker container images. The Container Analysis API is an implementation of the [Grafeas](https://grafeas.io) API. Analysis results are stored as a series of occurrences. An `Occurrence` contains information about a specific analysis instance on a resource. An occu... | ContainerAnalysisServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContainerAnalysisServicer:
"""Retrieves analysis results of Cloud components such as Docker container images. The Container Analysis API is an implementation of the [Grafeas](https://grafeas.io) API. Analysis results are stored as a series of occurrences. An `Occurrence` contains information abou... | stack_v2_sparse_classes_75kplus_train_001150 | 6,187 | permissive | [
{
"docstring": "Sets the access control policy on the specified note or occurrence. Requires `containeranalysis.notes.setIamPolicy` or `containeranalysis.occurrences.setIamPolicy` permission if the resource is a note or an occurrence, respectively. The resource takes the format `projects/[PROJECT_ID]/notes/[NOT... | 3 | stack_v2_sparse_classes_30k_train_046647 | Implement the Python class `ContainerAnalysisServicer` described below.
Class description:
Retrieves analysis results of Cloud components such as Docker container images. The Container Analysis API is an implementation of the [Grafeas](https://grafeas.io) API. Analysis results are stored as a series of occurrences. An... | Implement the Python class `ContainerAnalysisServicer` described below.
Class description:
Retrieves analysis results of Cloud components such as Docker container images. The Container Analysis API is an implementation of the [Grafeas](https://grafeas.io) API. Analysis results are stored as a series of occurrences. An... | d897d56bce03d1fda98b79afb08264e51d46c421 | <|skeleton|>
class ContainerAnalysisServicer:
"""Retrieves analysis results of Cloud components such as Docker container images. The Container Analysis API is an implementation of the [Grafeas](https://grafeas.io) API. Analysis results are stored as a series of occurrences. An `Occurrence` contains information abou... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ContainerAnalysisServicer:
"""Retrieves analysis results of Cloud components such as Docker container images. The Container Analysis API is an implementation of the [Grafeas](https://grafeas.io) API. Analysis results are stored as a series of occurrences. An `Occurrence` contains information about a specific ... | the_stack_v2_python_sparse | containeranalysis/google/cloud/devtools/containeranalysis_v1/proto/containeranalysis_pb2_grpc.py | tswast/google-cloud-python | train | 1 |
6d813bb102040147e9879520800106159d9225b8 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UserTrainingStatusInfo()",
"from .training_status import TrainingStatus\nfrom .training_status import TrainingStatus\nfields: Dict[str, Callable[[Any], None]] = {'assignedDateTime': lambda n: setattr(self, 'assigned_date_time', n.get_d... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UserTrainingStatusInfo()
<|end_body_0|>
<|body_start_1|>
from .training_status import TrainingStatus
from .training_status import TrainingStatus
fields: Dict[str, Callable[[Any],... | UserTrainingStatusInfo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserTrainingStatusInfo:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserTrainingStatusInfo:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create ... | stack_v2_sparse_classes_75kplus_train_001151 | 3,696 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: UserTrainingStatusInfo",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrimina... | 3 | stack_v2_sparse_classes_30k_train_012894 | Implement the Python class `UserTrainingStatusInfo` described below.
Class description:
Implement the UserTrainingStatusInfo class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserTrainingStatusInfo: Creates a new instance of the appropriate class b... | Implement the Python class `UserTrainingStatusInfo` described below.
Class description:
Implement the UserTrainingStatusInfo class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserTrainingStatusInfo: Creates a new instance of the appropriate class b... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UserTrainingStatusInfo:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserTrainingStatusInfo:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserTrainingStatusInfo:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserTrainingStatusInfo:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Ret... | the_stack_v2_python_sparse | msgraph/generated/models/user_training_status_info.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
d0e49691d01165326447f346c7624fdbf6e7f72d | [
"self.domain = domain or config.Master.master_domain\nself.permitted_domains = permitted_domains or config.Master.permitted_domains\nif self.permitted_domains:\n assert isinstance(self.permitted_domains, tuple), 'permitted_domains must be a tuple, now it is a %s (value: %s)' % (type(self.permitted_domains), self... | <|body_start_0|>
self.domain = domain or config.Master.master_domain
self.permitted_domains = permitted_domains or config.Master.permitted_domains
if self.permitted_domains:
assert isinstance(self.permitted_domains, tuple), 'permitted_domains must be a tuple, now it is a %s (value: %... | Similar to buildbot.mail.Domain but permits filtering out people we don't want to spam. Also loads default values from chromium_config. | FilterDomain | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilterDomain:
"""Similar to buildbot.mail.Domain but permits filtering out people we don't want to spam. Also loads default values from chromium_config."""
def __init__(self, domain=None, permitted_domains=None):
"""domain is the default domain to append when only the naked username ... | stack_v2_sparse_classes_75kplus_train_001152 | 27,927 | permissive | [
{
"docstring": "domain is the default domain to append when only the naked username is available. permitted_domains is a whitelist of domains that emails will be sent to.",
"name": "__init__",
"signature": "def __init__(self, domain=None, permitted_domains=None)"
},
{
"docstring": "If name is al... | 2 | stack_v2_sparse_classes_30k_train_027888 | Implement the Python class `FilterDomain` described below.
Class description:
Similar to buildbot.mail.Domain but permits filtering out people we don't want to spam. Also loads default values from chromium_config.
Method signatures and docstrings:
- def __init__(self, domain=None, permitted_domains=None): domain is t... | Implement the Python class `FilterDomain` described below.
Class description:
Similar to buildbot.mail.Domain but permits filtering out people we don't want to spam. Also loads default values from chromium_config.
Method signatures and docstrings:
- def __init__(self, domain=None, permitted_domains=None): domain is t... | f8e42c70146c1b668421ee6358dc550a955770a3 | <|skeleton|>
class FilterDomain:
"""Similar to buildbot.mail.Domain but permits filtering out people we don't want to spam. Also loads default values from chromium_config."""
def __init__(self, domain=None, permitted_domains=None):
"""domain is the default domain to append when only the naked username ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FilterDomain:
"""Similar to buildbot.mail.Domain but permits filtering out people we don't want to spam. Also loads default values from chromium_config."""
def __init__(self, domain=None, permitted_domains=None):
"""domain is the default domain to append when only the naked username is available.... | the_stack_v2_python_sparse | scripts/master/master_utils.py | mcgreevy/chromium-build | train | 0 |
1e15e54e6f32fd3b7a97542a8a025be3e74543fe | [
"if target <= 1:\n raise ValueError(f'Target iteration of ETA must be > 1, got {target}')\nself.targetIteration = target\nself._ti = None\nself._xi = None",
"if self._ti is None:\n if current > 0:\n self._ti = time.time()\n self._xi = current\n return None\nif current <= self._xi:\n retu... | <|body_start_0|>
if target <= 1:
raise ValueError(f'Target iteration of ETA must be > 1, got {target}')
self.targetIteration = target
self._ti = None
self._xi = None
<|end_body_0|>
<|body_start_1|>
if self._ti is None:
if current > 0:
self... | ! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterations but gives a good estimate for mostly stable durations. The start ... | ETA | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ETA:
"""! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterations but gives a good estimate for most... | stack_v2_sparse_classes_75kplus_train_001153 | 29,663 | permissive | [
{
"docstring": "!Initialize with a given target iteration number.",
"name": "__init__",
"signature": "def __init__(self, target)"
},
{
"docstring": "! Estimate the time of arrival given a current iteration. \\\\param current Iteration number the loop is currently at. \\\\returns - Estimated time... | 3 | stack_v2_sparse_classes_30k_train_027683 | Implement the Python class `ETA` described below.
Class description:
! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterat... | Implement the Python class `ETA` described below.
Class description:
! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterat... | 41557db1965bf3801bfadf9ece39ec1dab9b7660 | <|skeleton|>
class ETA:
"""! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterations but gives a good estimate for most... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ETA:
"""! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterations but gives a good estimate for mostly stable dur... | the_stack_v2_python_sparse | src/isle/cli.py | evanberkowitz/isle | train | 3 |
03dbcca9c17893d472412f1d71ca1b7d2362c564 | [
"filter_parser = reqparse.RequestParser(bundle_errors=True)\nfilter_parser.add_argument('last_pk', type=int, default=0, location='args')\nfilter_parser.add_argument('limit_num', type=int, default=20, location='args')\nfilter_parser_args = filter_parser.parse_args()\ndata = get_customer_limit_rows_by_last_id(**filte... | <|body_start_0|>
filter_parser = reqparse.RequestParser(bundle_errors=True)
filter_parser.add_argument('last_pk', type=int, default=0, location='args')
filter_parser.add_argument('limit_num', type=int, default=20, location='args')
filter_parser_args = filter_parser.parse_args()
d... | CustomerListResource | CustomerListResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomerListResource:
"""CustomerListResource"""
def get(self):
"""Example: curl http://0.0.0.0:5000/bearings/customers curl http://0.0.0.0:5000/bearings/customers?last_pk=2&limit_num=2 :return:"""
<|body_0|>
def post(self):
"""Example: curl http://0.0.0.0:5000/b... | stack_v2_sparse_classes_75kplus_train_001154 | 5,730 | permissive | [
{
"docstring": "Example: curl http://0.0.0.0:5000/bearings/customers curl http://0.0.0.0:5000/bearings/customers?last_pk=2&limit_num=2 :return:",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Example: curl http://0.0.0.0:5000/bearings/customers -H \"Content-Type: application/jso... | 2 | null | Implement the Python class `CustomerListResource` described below.
Class description:
CustomerListResource
Method signatures and docstrings:
- def get(self): Example: curl http://0.0.0.0:5000/bearings/customers curl http://0.0.0.0:5000/bearings/customers?last_pk=2&limit_num=2 :return:
- def post(self): Example: curl ... | Implement the Python class `CustomerListResource` described below.
Class description:
CustomerListResource
Method signatures and docstrings:
- def get(self): Example: curl http://0.0.0.0:5000/bearings/customers curl http://0.0.0.0:5000/bearings/customers?last_pk=2&limit_num=2 :return:
- def post(self): Example: curl ... | 6ef54f3f7efbbaff6169e963dcf45ab25e11e593 | <|skeleton|>
class CustomerListResource:
"""CustomerListResource"""
def get(self):
"""Example: curl http://0.0.0.0:5000/bearings/customers curl http://0.0.0.0:5000/bearings/customers?last_pk=2&limit_num=2 :return:"""
<|body_0|>
def post(self):
"""Example: curl http://0.0.0.0:5000/b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomerListResource:
"""CustomerListResource"""
def get(self):
"""Example: curl http://0.0.0.0:5000/bearings/customers curl http://0.0.0.0:5000/bearings/customers?last_pk=2&limit_num=2 :return:"""
filter_parser = reqparse.RequestParser(bundle_errors=True)
filter_parser.add_argume... | the_stack_v2_python_sparse | web_api/bearings/resources/customer.py | zhanghe06/flask_restful | train | 2 |
7bfc64407fc6fd15028b7b3ec82751a623ef652e | [
"context = super(DeleteStatusMessageView, self).get_context_data(**kwargs)\nstatus = StatusMessage.objects.get(pk=self.kwargs['status_pk'])\ncontext['status'] = status\nreturn context",
"profile_pk = self.kwargs['profile_pk']\nstatus_pk = self.kwargs['status_pk']\nstatus = StatusMessage.objects.get(pk=status_pk)\... | <|body_start_0|>
context = super(DeleteStatusMessageView, self).get_context_data(**kwargs)
status = StatusMessage.objects.get(pk=self.kwargs['status_pk'])
context['status'] = status
return context
<|end_body_0|>
<|body_start_1|>
profile_pk = self.kwargs['profile_pk']
sta... | a view to delete a quote | DeleteStatusMessageView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeleteStatusMessageView:
"""a view to delete a quote"""
def get_context_data(self, **kwargs):
"""Return the context data (a dictionary) to be used in the template."""
<|body_0|>
def get_object(self, **kwargs):
"""return a single instance of a quote object, select... | stack_v2_sparse_classes_75kplus_train_001155 | 5,336 | no_license | [
{
"docstring": "Return the context data (a dictionary) to be used in the template.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
},
{
"docstring": "return a single instance of a quote object, selected at random",
"name": "get_object",
"signature": "def... | 3 | stack_v2_sparse_classes_30k_train_052706 | Implement the Python class `DeleteStatusMessageView` described below.
Class description:
a view to delete a quote
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Return the context data (a dictionary) to be used in the template.
- def get_object(self, **kwargs): return a single instance of a... | Implement the Python class `DeleteStatusMessageView` described below.
Class description:
a view to delete a quote
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Return the context data (a dictionary) to be used in the template.
- def get_object(self, **kwargs): return a single instance of a... | 7490df5c5c074493cad65a043364c673d49ace65 | <|skeleton|>
class DeleteStatusMessageView:
"""a view to delete a quote"""
def get_context_data(self, **kwargs):
"""Return the context data (a dictionary) to be used in the template."""
<|body_0|>
def get_object(self, **kwargs):
"""return a single instance of a quote object, select... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeleteStatusMessageView:
"""a view to delete a quote"""
def get_context_data(self, **kwargs):
"""Return the context data (a dictionary) to be used in the template."""
context = super(DeleteStatusMessageView, self).get_context_data(**kwargs)
status = StatusMessage.objects.get(pk=se... | the_stack_v2_python_sparse | mini_fb/views.py | askap-bu/askap-bu | train | 0 |
2c3e15131d0fddb7764d02213f2e87be4c270b7b | [
"res = []\nuf = UnionFind(n)\nfor user1, user2 in requests:\n root1, root2 = (uf.find(user1), uf.find(user2))\n if root1 == root2:\n res.append(True)\n else:\n for user3, user4 in restrictions:\n root3, root4 = (uf.find(user3), uf.find(user4))\n if root1 == root3 and roo... | <|body_start_0|>
res = []
uf = UnionFind(n)
for user1, user2 in requests:
root1, root2 = (uf.find(user1), uf.find(user2))
if root1 == root2:
res.append(True)
else:
for user3, user4 in restrictions:
root3, roo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]:
"""并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)"""
<|body_0|>
def friendRequests2(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List... | stack_v2_sparse_classes_75kplus_train_001156 | 3,693 | no_license | [
{
"docstring": "并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)",
"name": "friendRequests",
"signature": "def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]"
},
{
"docstring": "可撤销并查集",
"name": "friendRequests2",
"signature": "def friendRe... | 2 | stack_v2_sparse_classes_30k_train_014117 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]: 并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)
- def friendRequests2(self, n... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]: 并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)
- def friendRequests2(self, n... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]:
"""并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)"""
<|body_0|>
def friendRequests2(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def friendRequests(self, n: int, restrictions: List[List[int]], requests: List[List[int]]) -> List[bool]:
"""并查集，连接之前遍历限制找到对应组的边，如果边重合，那么就不能连这条边 O(n^2)"""
res = []
uf = UnionFind(n)
for user1, user2 in requests:
root1, root2 = (uf.find(user1), uf.find(user... | the_stack_v2_python_sparse | 14_并查集/经典题/2076. 处理含限制条件的好友请求.py | 981377660LMT/algorithm-study | train | 225 | |
723b88ebb01c603955e1ebc4df95994caad0585f | [
"assert schema is not None, 'The `schema` argument must be provided.'\nif not schema.coerce:\n return check_obj\nerror_handler = SchemaErrorHandler(lazy=True)\ncoerced_multi_index = {}\nfor i, index in enumerate(schema.indexes):\n if all((x is None for x in schema.names)):\n index_levels = [i]\n els... | <|body_start_0|>
assert schema is not None, 'The `schema` argument must be provided.'
if not schema.coerce:
return check_obj
error_handler = SchemaErrorHandler(lazy=True)
coerced_multi_index = {}
for i, index in enumerate(schema.indexes):
if all((x is None... | Backend implementation for pandas multiindex. | MultiIndexBackend | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiIndexBackend:
"""Backend implementation for pandas multiindex."""
def coerce_dtype(self, check_obj: pd.MultiIndex, schema=None) -> pd.MultiIndex:
"""Coerce type of a pd.Series by type specified in dtype. :param obj: multi-index to coerce. :returns: ``MultiIndex`` with coerced da... | stack_v2_sparse_classes_75kplus_train_001157 | 19,001 | permissive | [
{
"docstring": "Coerce type of a pd.Series by type specified in dtype. :param obj: multi-index to coerce. :returns: ``MultiIndex`` with coerced data type",
"name": "coerce_dtype",
"signature": "def coerce_dtype(self, check_obj: pd.MultiIndex, schema=None) -> pd.MultiIndex"
},
{
"docstring": "Val... | 4 | stack_v2_sparse_classes_30k_train_023069 | Implement the Python class `MultiIndexBackend` described below.
Class description:
Backend implementation for pandas multiindex.
Method signatures and docstrings:
- def coerce_dtype(self, check_obj: pd.MultiIndex, schema=None) -> pd.MultiIndex: Coerce type of a pd.Series by type specified in dtype. :param obj: multi-... | Implement the Python class `MultiIndexBackend` described below.
Class description:
Backend implementation for pandas multiindex.
Method signatures and docstrings:
- def coerce_dtype(self, check_obj: pd.MultiIndex, schema=None) -> pd.MultiIndex: Coerce type of a pd.Series by type specified in dtype. :param obj: multi-... | 850dcf8e59632d54bc9a6df47b9ca08afa089a27 | <|skeleton|>
class MultiIndexBackend:
"""Backend implementation for pandas multiindex."""
def coerce_dtype(self, check_obj: pd.MultiIndex, schema=None) -> pd.MultiIndex:
"""Coerce type of a pd.Series by type specified in dtype. :param obj: multi-index to coerce. :returns: ``MultiIndex`` with coerced da... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiIndexBackend:
"""Backend implementation for pandas multiindex."""
def coerce_dtype(self, check_obj: pd.MultiIndex, schema=None) -> pd.MultiIndex:
"""Coerce type of a pd.Series by type specified in dtype. :param obj: multi-index to coerce. :returns: ``MultiIndex`` with coerced data type"""
... | the_stack_v2_python_sparse | pandera/backends/pandas/components.py | unionai-oss/pandera | train | 997 |
e4e16aaaa13dc523c00a4720626e7317a8ddadcd | [
"super().__init__(mol, cuda)\nself.order = order\nself.fc = nn.Linear(order, 1, bias=False)\nself.fc.weight.data *= 0.0\nself.fc.weight.data[0, 0] = 0.0001",
"original_shape = ree.shape\nx = ree.reshape(-1, 1)\nx = x.repeat(1, self.order)\nx = x.cumprod(dim=-1)\nx = self.fc(x)\nx = x.reshape(*original_shape)\nret... | <|body_start_0|>
super().__init__(mol, cuda)
self.order = order
self.fc = nn.Linear(order, 1, bias=False)
self.fc.weight.data *= 0.0
self.fc.weight.data[0, 0] = 0.0001
<|end_body_0|>
<|body_start_1|>
original_shape = ree.shape
x = ree.reshape(-1, 1)
x = x... | BackFlowKernelPowerSum | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BackFlowKernelPowerSum:
def __init__(self, mol, cuda, order=2):
"""Compute the back flow kernel, i.e. the function f(rij) where rij is the distance between electron i and j This kernel is used in the backflow transformation .. math: q_i = r_i + \\sum_{j\\neq i} f(r_{ij}) (r_i-r_j)"""
... | stack_v2_sparse_classes_75kplus_train_001158 | 1,060 | permissive | [
{
"docstring": "Compute the back flow kernel, i.e. the function f(rij) where rij is the distance between electron i and j This kernel is used in the backflow transformation .. math: q_i = r_i + \\\\sum_{j\\\\neq i} f(r_{ij}) (r_i-r_j)",
"name": "__init__",
"signature": "def __init__(self, mol, cuda, ord... | 2 | stack_v2_sparse_classes_30k_train_034270 | Implement the Python class `BackFlowKernelPowerSum` described below.
Class description:
Implement the BackFlowKernelPowerSum class.
Method signatures and docstrings:
- def __init__(self, mol, cuda, order=2): Compute the back flow kernel, i.e. the function f(rij) where rij is the distance between electron i and j This... | Implement the Python class `BackFlowKernelPowerSum` described below.
Class description:
Implement the BackFlowKernelPowerSum class.
Method signatures and docstrings:
- def __init__(self, mol, cuda, order=2): Compute the back flow kernel, i.e. the function f(rij) where rij is the distance between electron i and j This... | 439a79e97ee63057e3032d28a1a5ebafd2d5b5e4 | <|skeleton|>
class BackFlowKernelPowerSum:
def __init__(self, mol, cuda, order=2):
"""Compute the back flow kernel, i.e. the function f(rij) where rij is the distance between electron i and j This kernel is used in the backflow transformation .. math: q_i = r_i + \\sum_{j\\neq i} f(r_{ij}) (r_i-r_j)"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BackFlowKernelPowerSum:
def __init__(self, mol, cuda, order=2):
"""Compute the back flow kernel, i.e. the function f(rij) where rij is the distance between electron i and j This kernel is used in the backflow transformation .. math: q_i = r_i + \\sum_{j\\neq i} f(r_{ij}) (r_i-r_j)"""
super()._... | the_stack_v2_python_sparse | qmctorch/wavefunction/orbitals/backflow/kernels/backflow_kernel_power_sum.py | NLESC-JCER/QMCTorch | train | 22 | |
324c91d4a4726c8fc90533c8d404843988cd2fff | [
"arr = []\nstack = [root]\nwhile stack:\n root = stack.pop()\n if not root:\n continue\n arr.append(root.val)\n stack.append(root.right)\n stack.append(root.left)\nreturn arr",
"arr = []\nstack = []\nwhile root or stack:\n while root:\n stack.append(root)\n root = root.left\... | <|body_start_0|>
arr = []
stack = [root]
while stack:
root = stack.pop()
if not root:
continue
arr.append(root.val)
stack.append(root.right)
stack.append(root.left)
return arr
<|end_body_0|>
<|body_start_1|>
... | 非递归法实现前、中、后序遍历 | Solution2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution2:
"""非递归法实现前、中、后序遍历"""
def pre_order(self, root):
"""前序遍历"""
<|body_0|>
def in_order(self, root):
"""中序遍历"""
<|body_1|>
def post_order(self, root):
"""后序遍历"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
arr = []
... | stack_v2_sparse_classes_75kplus_train_001159 | 2,354 | no_license | [
{
"docstring": "前序遍历",
"name": "pre_order",
"signature": "def pre_order(self, root)"
},
{
"docstring": "中序遍历",
"name": "in_order",
"signature": "def in_order(self, root)"
},
{
"docstring": "后序遍历",
"name": "post_order",
"signature": "def post_order(self, root)"
}
] | 3 | stack_v2_sparse_classes_30k_train_035469 | Implement the Python class `Solution2` described below.
Class description:
非递归法实现前、中、后序遍历
Method signatures and docstrings:
- def pre_order(self, root): 前序遍历
- def in_order(self, root): 中序遍历
- def post_order(self, root): 后序遍历 | Implement the Python class `Solution2` described below.
Class description:
非递归法实现前、中、后序遍历
Method signatures and docstrings:
- def pre_order(self, root): 前序遍历
- def in_order(self, root): 中序遍历
- def post_order(self, root): 后序遍历
<|skeleton|>
class Solution2:
"""非递归法实现前、中、后序遍历"""
def pre_order(self, root):
... | cbdb055bfdf34ce2e143ab10af90372422984008 | <|skeleton|>
class Solution2:
"""非递归法实现前、中、后序遍历"""
def pre_order(self, root):
"""前序遍历"""
<|body_0|>
def in_order(self, root):
"""中序遍历"""
<|body_1|>
def post_order(self, root):
"""后序遍历"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution2:
"""非递归法实现前、中、后序遍历"""
def pre_order(self, root):
"""前序遍历"""
arr = []
stack = [root]
while stack:
root = stack.pop()
if not root:
continue
arr.append(root.val)
stack.append(root.right)
sta... | the_stack_v2_python_sparse | 18_tree_iterate.py | turbobin/algorithm_learning | train | 0 |
ab3006fe41b68bdecd862b9fad7e15178d645949 | [
"if not root:\n return ''\nseq = ''\nlevel = [root]\nwhile level:\n next_level = []\n flag = False\n for node in level:\n if node is None:\n next_level.extend([None, None])\n seq += '#'\n else:\n next_level.extend([node.left, node.right])\n seq +... | <|body_start_0|>
if not root:
return ''
seq = ''
level = [root]
while level:
next_level = []
flag = False
for node in level:
if node is None:
next_level.extend([None, None])
seq += '#'... | Codec1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec1:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_75kplus_train_001160 | 5,549 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec1` described below.
Class description:
Implement the Codec1 class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtyp... | Implement the Python class `Codec1` described below.
Class description:
Implement the Codec1 class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtyp... | 052bd7915257679877dbe55b60ed1abb7528eaa2 | <|skeleton|>
class Codec1:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec1:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
seq = ''
level = [root]
while level:
next_level = []
flag = False
for node in level:
... | the_stack_v2_python_sparse | python_solution/Tree/297_SerializeAndDeserializeBinaryTree.py | Dimen61/leetcode | train | 4 | |
6da4425102b6b5847d98115febd4c17c7c8654bf | [
"if HAVE_PY26_SSL:\n self.sslobj = ssl.wrap_socket(self.sock)\n self.sslobj.do_handshake()\nelse:\n self.sslobj = socket.ssl(self.sock)",
"result = self.sslobj.read(n)\nwhile len(result) < n:\n s = self.sslobj.read(n - len(result))\n if not s:\n raise IOError('Socket closed')\n result += ... | <|body_start_0|>
if HAVE_PY26_SSL:
self.sslobj = ssl.wrap_socket(self.sock)
self.sslobj.do_handshake()
else:
self.sslobj = socket.ssl(self.sock)
<|end_body_0|>
<|body_start_1|>
result = self.sslobj.read(n)
while len(result) < n:
s = self.s... | Transport that works over SSL | SSLTransport | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SSLTransport:
"""Transport that works over SSL"""
def _setup_transport(self):
"""Wrap the socket in an SSL object, either the new Python 2.6 version, or the older Python 2.5 and lower version."""
<|body_0|>
def _read(self, n):
"""It seems that SSL Objects read() ... | stack_v2_sparse_classes_75kplus_train_001161 | 5,384 | permissive | [
{
"docstring": "Wrap the socket in an SSL object, either the new Python 2.6 version, or the older Python 2.5 and lower version.",
"name": "_setup_transport",
"signature": "def _setup_transport(self)"
},
{
"docstring": "It seems that SSL Objects read() method may not supply as much as you're aski... | 3 | stack_v2_sparse_classes_30k_train_022001 | Implement the Python class `SSLTransport` described below.
Class description:
Transport that works over SSL
Method signatures and docstrings:
- def _setup_transport(self): Wrap the socket in an SSL object, either the new Python 2.6 version, or the older Python 2.5 and lower version.
- def _read(self, n): It seems tha... | Implement the Python class `SSLTransport` described below.
Class description:
Transport that works over SSL
Method signatures and docstrings:
- def _setup_transport(self): Wrap the socket in an SSL object, either the new Python 2.6 version, or the older Python 2.5 and lower version.
- def _read(self, n): It seems tha... | 37444fb16b36743c439b0d6c3cac2347e0cc0a94 | <|skeleton|>
class SSLTransport:
"""Transport that works over SSL"""
def _setup_transport(self):
"""Wrap the socket in an SSL object, either the new Python 2.6 version, or the older Python 2.5 and lower version."""
<|body_0|>
def _read(self, n):
"""It seems that SSL Objects read() ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SSLTransport:
"""Transport that works over SSL"""
def _setup_transport(self):
"""Wrap the socket in an SSL object, either the new Python 2.6 version, or the older Python 2.5 and lower version."""
if HAVE_PY26_SSL:
self.sslobj = ssl.wrap_socket(self.sock)
self.sslob... | the_stack_v2_python_sparse | vendor/amqplib/client_0_8/transport.py | bopopescu/cc-2 | train | 0 |
863777be6a8136dd8144abda04eea8a9265533b8 | [
"if not data:\n data = 0\nif not size:\n size = 1\nmax_size = 2 ** (size * 8)\nif data >= max_size:\n data = max_size - 1\nreturn data.to_bytes(size, byteorder='big')",
"if not size:\n size = 1\nif len(payload) < size:\n return (payload, None)\nreturn (payload[size:], int.from_bytes(payload[:size],... | <|body_start_0|>
if not data:
data = 0
if not size:
size = 1
max_size = 2 ** (size * 8)
if data >= max_size:
data = max_size - 1
return data.to_bytes(size, byteorder='big')
<|end_body_0|>
<|body_start_1|>
if not size:
size ... | INT data encode in x bytes. | SMPayloadTypeINT | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SMPayloadTypeINT:
"""INT data encode in x bytes."""
def encode(data, size=1):
"""Encode integer into binary string :Example: >>> SMPayloadTypeINT.encode(2, size=2) b'\\x00\\x02' >>> SMPayloadTypeINT.encode(123456789, size=4) b'\\x07[\\xcd\\x15' >>> # Return the max is size exceed >>>... | stack_v2_sparse_classes_75kplus_train_001162 | 14,049 | permissive | [
{
"docstring": "Encode integer into binary string :Example: >>> SMPayloadTypeINT.encode(2, size=2) b'\\\\x00\\\\x02' >>> SMPayloadTypeINT.encode(123456789, size=4) b'\\\\x07[\\\\xcd\\\\x15' >>> # Return the max is size exceed >>> SMPayloadTypeINT.encode(5165165, size=2) b'\\\\xff\\\\xff'",
"name": "encode",... | 2 | stack_v2_sparse_classes_30k_train_004661 | Implement the Python class `SMPayloadTypeINT` described below.
Class description:
INT data encode in x bytes.
Method signatures and docstrings:
- def encode(data, size=1): Encode integer into binary string :Example: >>> SMPayloadTypeINT.encode(2, size=2) b'\\x00\\x02' >>> SMPayloadTypeINT.encode(123456789, size=4) b'... | Implement the Python class `SMPayloadTypeINT` described below.
Class description:
INT data encode in x bytes.
Method signatures and docstrings:
- def encode(data, size=1): Encode integer into binary string :Example: >>> SMPayloadTypeINT.encode(2, size=2) b'\\x00\\x02' >>> SMPayloadTypeINT.encode(123456789, size=4) b'... | cf20b363ed3d7bcb75101b17870e876a857ecd66 | <|skeleton|>
class SMPayloadTypeINT:
"""INT data encode in x bytes."""
def encode(data, size=1):
"""Encode integer into binary string :Example: >>> SMPayloadTypeINT.encode(2, size=2) b'\\x00\\x02' >>> SMPayloadTypeINT.encode(123456789, size=4) b'\\x07[\\xcd\\x15' >>> # Return the max is size exceed >>>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SMPayloadTypeINT:
"""INT data encode in x bytes."""
def encode(data, size=1):
"""Encode integer into binary string :Example: >>> SMPayloadTypeINT.encode(2, size=2) b'\\x00\\x02' >>> SMPayloadTypeINT.encode(123456789, size=4) b'\\x07[\\xcd\\x15' >>> # Return the max is size exceed >>> SMPayloadTyp... | the_stack_v2_python_sparse | smserver/smutils/smpacket/smencoder.py | Moutix/stepmania-server | train | 4 |
700c103ddd91c17558f5ad3c125ee3ebe22f3fd3 | [
"dp = list(range(1, n + 2))\nfor _ in range(3):\n dp = list(itertools.accumulate(dp))\nreturn dp[-1]",
"n_combos = 1\nfor i in range(2, n + 2):\n n_combos += sum((a * b for a, b in zip(range(1, i + 1), range(i, 0, -1))))\nreturn n_combos",
"n += 1\nn_combos = 0\nsum_first_i = 0\nfor i in range(1, n + 1):\... | <|body_start_0|>
dp = list(range(1, n + 2))
for _ in range(3):
dp = list(itertools.accumulate(dp))
return dp[-1]
<|end_body_0|>
<|body_start_1|>
n_combos = 1
for i in range(2, n + 2):
n_combos += sum((a * b for a, b in zip(range(1, i + 1), range(i, 0, -1)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countVowelStringsDP(self, n: int) -> int:
"""Count the number of combinations using dp. Observe that if we know the quantity of a, i, o, e, u in a string, then there is a unique string that contains such letters in a lexicographical order. :param n: the target length of the... | stack_v2_sparse_classes_75kplus_train_001163 | 3,743 | no_license | [
{
"docstring": "Count the number of combinations using dp. Observe that if we know the quantity of a, i, o, e, u in a string, then there is a unique string that contains such letters in a lexicographical order. :param n: the target length of the strings :return: number of combos of strings length n made from vo... | 3 | stack_v2_sparse_classes_30k_train_049289 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countVowelStringsDP(self, n: int) -> int: Count the number of combinations using dp. Observe that if we know the quantity of a, i, o, e, u in a string, then there is a unique... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countVowelStringsDP(self, n: int) -> int: Count the number of combinations using dp. Observe that if we know the quantity of a, i, o, e, u in a string, then there is a unique... | ee8237b66975fb5584a3d68b311e762c0462c8aa | <|skeleton|>
class Solution:
def countVowelStringsDP(self, n: int) -> int:
"""Count the number of combinations using dp. Observe that if we know the quantity of a, i, o, e, u in a string, then there is a unique string that contains such letters in a lexicographical order. :param n: the target length of the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def countVowelStringsDP(self, n: int) -> int:
"""Count the number of combinations using dp. Observe that if we know the quantity of a, i, o, e, u in a string, then there is a unique string that contains such letters in a lexicographical order. :param n: the target length of the strings :retu... | the_stack_v2_python_sparse | LC1641-Count-Sorted-Vowel-Strings.py | kate-melnykova/LeetCode-solutions | train | 2 | |
1ebfeaaa2546f48c1a172bc63c5d69f25b4fd122 | [
"PinshCmd.PinshCmd.__init__(self, 'PackageField')\nself.help_text = '<PackageField>\\tA package name that comes from machine status'\nself.action_type = action_type\nself.cmd_owner = 0\nself.machine_name_index = 1",
"complete_machine_name = command_line[self.machine_name_index]\nincomplete_package_name = command_... | <|body_start_0|>
PinshCmd.PinshCmd.__init__(self, 'PackageField')
self.help_text = '<PackageField>\tA package name that comes from machine status'
self.action_type = action_type
self.cmd_owner = 0
self.machine_name_index = 1
<|end_body_0|>
<|body_start_1|>
complete_machi... | Some times you want to maintain package status data on a machine. | PackageField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PackageField:
"""Some times you want to maintain package status data on a machine."""
def __init__(self, action_type):
"""action_type -- FIXABLE or PURGABLE machine_name_index -- which token in the set of arguments passed to preferred_names is the machine name package_name_index -- w... | stack_v2_sparse_classes_75kplus_train_001164 | 7,256 | no_license | [
{
"docstring": "action_type -- FIXABLE or PURGABLE machine_name_index -- which token in the set of arguments passed to preferred_names is the machine name package_name_index -- which token is the package_name to be completed",
"name": "__init__",
"signature": "def __init__(self, action_type)"
},
{
... | 6 | null | Implement the Python class `PackageField` described below.
Class description:
Some times you want to maintain package status data on a machine.
Method signatures and docstrings:
- def __init__(self, action_type): action_type -- FIXABLE or PURGABLE machine_name_index -- which token in the set of arguments passed to pr... | Implement the Python class `PackageField` described below.
Class description:
Some times you want to maintain package status data on a machine.
Method signatures and docstrings:
- def __init__(self, action_type): action_type -- FIXABLE or PURGABLE machine_name_index -- which token in the set of arguments passed to pr... | bb528eed464a63e0f6772fa27a9d472ef3a407aa | <|skeleton|>
class PackageField:
"""Some times you want to maintain package status data on a machine."""
def __init__(self, action_type):
"""action_type -- FIXABLE or PURGABLE machine_name_index -- which token in the set of arguments passed to preferred_names is the machine name package_name_index -- w... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PackageField:
"""Some times you want to maintain package status data on a machine."""
def __init__(self, action_type):
"""action_type -- FIXABLE or PURGABLE machine_name_index -- which token in the set of arguments passed to preferred_names is the machine name package_name_index -- which token is... | the_stack_v2_python_sparse | cli/lib/PackageField.py | psbanka/bombardier | train | 0 |
7b7b351eac046dd4e65e40114a10ebf39e26bd39 | [
"super(VAELoss, self).__init__()\nself.sample_z = sample_z\nself.bce_loss = nn.BCELoss(size_average=True)\nself.reg_weight = reg_weight",
"model_out_x, mu, log_var = model_out\nbatch_size = target_x.size()[0]\nseq_len = target_x.size()[1]\nz_size = mu.size()[1]\nmodel_out_x = F.softmax(model_out_x, dim=2)\nBCE = ... | <|body_start_0|>
super(VAELoss, self).__init__()
self.sample_z = sample_z
self.bce_loss = nn.BCELoss(size_average=True)
self.reg_weight = reg_weight
<|end_body_0|>
<|body_start_1|>
model_out_x, mu, log_var = model_out
batch_size = target_x.size()[0]
seq_len = tar... | VAELoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VAELoss:
def __init__(self, grammar=None, sample_z=False, reg_weight=0.01):
""":param masks: array of allowed transition rules from a given symbol"""
<|body_0|>
def forward(self, model_out, target_x):
"""gives the batch normalized Variational Error."""
<|body... | stack_v2_sparse_classes_75kplus_train_001165 | 2,556 | permissive | [
{
"docstring": ":param masks: array of allowed transition rules from a given symbol",
"name": "__init__",
"signature": "def __init__(self, grammar=None, sample_z=False, reg_weight=0.01)"
},
{
"docstring": "gives the batch normalized Variational Error.",
"name": "forward",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_053514 | Implement the Python class `VAELoss` described below.
Class description:
Implement the VAELoss class.
Method signatures and docstrings:
- def __init__(self, grammar=None, sample_z=False, reg_weight=0.01): :param masks: array of allowed transition rules from a given symbol
- def forward(self, model_out, target_x): giv... | Implement the Python class `VAELoss` described below.
Class description:
Implement the VAELoss class.
Method signatures and docstrings:
- def __init__(self, grammar=None, sample_z=False, reg_weight=0.01): :param masks: array of allowed transition rules from a given symbol
- def forward(self, model_out, target_x): giv... | 5c336dfbd14235e4fd97b21778842a650e733275 | <|skeleton|>
class VAELoss:
def __init__(self, grammar=None, sample_z=False, reg_weight=0.01):
""":param masks: array of allowed transition rules from a given symbol"""
<|body_0|>
def forward(self, model_out, target_x):
"""gives the batch normalized Variational Error."""
<|body... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VAELoss:
def __init__(self, grammar=None, sample_z=False, reg_weight=0.01):
""":param masks: array of allowed transition rules from a given symbol"""
super(VAELoss, self).__init__()
self.sample_z = sample_z
self.bce_loss = nn.BCELoss(size_average=True)
self.reg_weight =... | the_stack_v2_python_sparse | src/generative_playground/models/losses/vae_loss.py | JGU-dev/generative_playground | train | 0 | |
3c0a68e399548287377fbf4f5d4e646524722057 | [
"if not kwargs.get('auth_plugin') and (not kwargs.get('session')):\n kwargs['auth_plugin'] = monitoringclient.get_auth_plugin(*args, **kwargs)\nself.auth_plugin = kwargs.get('auth_plugin')\nself.http_client = monitoringclient._construct_http_client(**kwargs)\nself.alarm_client = self._get_alarm_client(**kwargs)\... | <|body_start_0|>
if not kwargs.get('auth_plugin') and (not kwargs.get('session')):
kwargs['auth_plugin'] = monitoringclient.get_auth_plugin(*args, **kwargs)
self.auth_plugin = kwargs.get('auth_plugin')
self.http_client = monitoringclient._construct_http_client(**kwargs)
self.... | Client for the Ceilometer v2 API. :param session: a keystoneauth session object :type session: keystoneauth1.session.Session :param str service_type: The default service_type for URL discovery :param str service_name: The default service_name for URL discovery :param str interface: The default interface for URL discove... | Client | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Client:
"""Client for the Ceilometer v2 API. :param session: a keystoneauth session object :type session: keystoneauth1.session.Session :param str service_type: The default service_type for URL discovery :param str service_name: The default service_name for URL discovery :param str interface: The... | stack_v2_sparse_classes_75kplus_train_001166 | 5,420 | permissive | [
{
"docstring": "Initialize a new client for the Ceilometer v2 API.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Get client for alarm manager that redirect to aodh.",
"name": "_get_alarm_client",
"signature": "def _get_alarm_client(**ceilo_kw... | 2 | stack_v2_sparse_classes_30k_train_033942 | Implement the Python class `Client` described below.
Class description:
Client for the Ceilometer v2 API. :param session: a keystoneauth session object :type session: keystoneauth1.session.Session :param str service_type: The default service_type for URL discovery :param str service_name: The default service_name for ... | Implement the Python class `Client` described below.
Class description:
Client for the Ceilometer v2 API. :param session: a keystoneauth session object :type session: keystoneauth1.session.Session :param str service_type: The default service_type for URL discovery :param str service_name: The default service_name for ... | 5e88cf438b4d24b92f996ae31907d44bd736c7f1 | <|skeleton|>
class Client:
"""Client for the Ceilometer v2 API. :param session: a keystoneauth session object :type session: keystoneauth1.session.Session :param str service_type: The default service_type for URL discovery :param str service_name: The default service_name for URL discovery :param str interface: The... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Client:
"""Client for the Ceilometer v2 API. :param session: a keystoneauth session object :type session: keystoneauth1.session.Session :param str service_type: The default service_type for URL discovery :param str service_name: The default service_name for URL discovery :param str interface: The default inte... | the_stack_v2_python_sparse | eclcli/monitoring/monitoringclient/v2/client.py | nttcom/eclcli | train | 32 |
01df8692e21fe49797094a037353a3c6391d2651 | [
"self.conn_info = {}\nwith open('mongo_secret', 'r') as secret:\n lines = secret.readlines()\n self.conn_info['username'] = lines[0].strip()\n self.conn_info['password'] = lines[1].strip()\n self.conn_info['conn_str'] = lines[2].strip()\nassert cfg_mongo['datastore'] in ['gridfs', 'numpy', 'adios2']\nse... | <|body_start_0|>
self.conn_info = {}
with open('mongo_secret', 'r') as secret:
lines = secret.readlines()
self.conn_info['username'] = lines[0].strip()
self.conn_info['password'] = lines[1].strip()
self.conn_info['conn_str'] = lines[2].strip()
asse... | Abstraction for mongo_connection using context manager. | mongo_connection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class mongo_connection:
"""Abstraction for mongo_connection using context manager."""
def __init__(self, cfg_mongo):
"""Initializes context."""
<|body_0|>
def __enter__(self):
"""Instantiate a new MongoClient and return the collection."""
<|body_1|>
def __... | stack_v2_sparse_classes_75kplus_train_001167 | 10,764 | no_license | [
{
"docstring": "Initializes context.",
"name": "__init__",
"signature": "def __init__(self, cfg_mongo)"
},
{
"docstring": "Instantiate a new MongoClient and return the collection.",
"name": "__enter__",
"signature": "def __enter__(self)"
},
{
"docstring": "Close connection to Mon... | 3 | null | Implement the Python class `mongo_connection` described below.
Class description:
Abstraction for mongo_connection using context manager.
Method signatures and docstrings:
- def __init__(self, cfg_mongo): Initializes context.
- def __enter__(self): Instantiate a new MongoClient and return the collection.
- def __exit... | Implement the Python class `mongo_connection` described below.
Class description:
Abstraction for mongo_connection using context manager.
Method signatures and docstrings:
- def __init__(self, cfg_mongo): Initializes context.
- def __enter__(self): Instantiate a new MongoClient and return the collection.
- def __exit... | 7ce63705e18c427f448c8d720c950a54add07966 | <|skeleton|>
class mongo_connection:
"""Abstraction for mongo_connection using context manager."""
def __init__(self, cfg_mongo):
"""Initializes context."""
<|body_0|>
def __enter__(self):
"""Instantiate a new MongoClient and return the collection."""
<|body_1|>
def __... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class mongo_connection:
"""Abstraction for mongo_connection using context manager."""
def __init__(self, cfg_mongo):
"""Initializes context."""
self.conn_info = {}
with open('mongo_secret', 'r') as secret:
lines = secret.readlines()
self.conn_info['username'] = l... | the_stack_v2_python_sparse | delta/storage/backend_mongodb.py | rkube/delta | train | 7 |
a5e9c3845327dd96502dd05ced5491fc55fdd43c | [
"self.__region_points = region_points\nself.__min = None\nself.__max = None",
"if self.__min is None:\n self.__compute()\nreturn self.__min",
"if self.__max is None:\n self.__compute()\nreturn self.__max",
"for k, v in self.__region_points.items():\n for p in v:\n if self.__min is None:\n ... | <|body_start_0|>
self.__region_points = region_points
self.__min = None
self.__max = None
<|end_body_0|>
<|body_start_1|>
if self.__min is None:
self.__compute()
return self.__min
<|end_body_1|>
<|body_start_2|>
if self.__max is None:
self.__comp... | Axis aligned bounding box. | BBox | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BBox:
"""Axis aligned bounding box."""
def __init__(self, region_points):
"""Initializer."""
<|body_0|>
def min(self):
"""Get min point (in upper left corner). :return: Minimum point describing the bbox"""
<|body_1|>
def max(self):
"""Get max... | stack_v2_sparse_classes_75kplus_train_001168 | 1,417 | permissive | [
{
"docstring": "Initializer.",
"name": "__init__",
"signature": "def __init__(self, region_points)"
},
{
"docstring": "Get min point (in upper left corner). :return: Minimum point describing the bbox",
"name": "min",
"signature": "def min(self)"
},
{
"docstring": "Get max point (... | 4 | stack_v2_sparse_classes_30k_train_015601 | Implement the Python class `BBox` described below.
Class description:
Axis aligned bounding box.
Method signatures and docstrings:
- def __init__(self, region_points): Initializer.
- def min(self): Get min point (in upper left corner). :return: Minimum point describing the bbox
- def max(self): Get max point (in lowe... | Implement the Python class `BBox` described below.
Class description:
Axis aligned bounding box.
Method signatures and docstrings:
- def __init__(self, region_points): Initializer.
- def min(self): Get min point (in upper left corner). :return: Minimum point describing the bbox
- def max(self): Get max point (in lowe... | 44246265f1e0b269fa69eaf6988cd2f1464c2344 | <|skeleton|>
class BBox:
"""Axis aligned bounding box."""
def __init__(self, region_points):
"""Initializer."""
<|body_0|>
def min(self):
"""Get min point (in upper left corner). :return: Minimum point describing the bbox"""
<|body_1|>
def max(self):
"""Get max... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BBox:
"""Axis aligned bounding box."""
def __init__(self, region_points):
"""Initializer."""
self.__region_points = region_points
self.__min = None
self.__max = None
def min(self):
"""Get min point (in upper left corner). :return: Minimum point describing the ... | the_stack_v2_python_sparse | tools/mapgen/svg/math/bbox.py | cpppwner/NoRiskNoFun | train | 1 |
a9e64e69fb3e1ccffd7c6b2938afb6c82c67c5e5 | [
"self.num_days_to_keep = num_days_to_keep\nself.num_secs_to_keep = num_secs_to_keep\nself.worm_retention = worm_retention",
"if dictionary is None:\n return None\nnum_days_to_keep = dictionary.get('numDaysToKeep')\nnum_secs_to_keep = dictionary.get('numSecsToKeep')\nworm_retention = cohesity_management_sdk.mod... | <|body_start_0|>
self.num_days_to_keep = num_days_to_keep
self.num_secs_to_keep = num_secs_to_keep
self.worm_retention = worm_retention
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
num_days_to_keep = dictionary.get('numDaysToKeep')
num_s... | Implementation of the 'RetentionPolicyProto' model. Message that specifies the retention policy for backup snapshots. Attributes: num_days_to_keep (long|int): The number of days to keep the snapshots for a backup run. num_secs_to_keep (int): The number of seconds to keep the snapshots for a backup run. worm_retention (... | RetentionPolicyProto | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RetentionPolicyProto:
"""Implementation of the 'RetentionPolicyProto' model. Message that specifies the retention policy for backup snapshots. Attributes: num_days_to_keep (long|int): The number of days to keep the snapshots for a backup run. num_secs_to_keep (int): The number of seconds to keep ... | stack_v2_sparse_classes_75kplus_train_001169 | 2,976 | permissive | [
{
"docstring": "Constructor for the RetentionPolicyProto class",
"name": "__init__",
"signature": "def __init__(self, num_days_to_keep=None, num_secs_to_keep=None, worm_retention=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictio... | 2 | stack_v2_sparse_classes_30k_train_041508 | Implement the Python class `RetentionPolicyProto` described below.
Class description:
Implementation of the 'RetentionPolicyProto' model. Message that specifies the retention policy for backup snapshots. Attributes: num_days_to_keep (long|int): The number of days to keep the snapshots for a backup run. num_secs_to_kee... | Implement the Python class `RetentionPolicyProto` described below.
Class description:
Implementation of the 'RetentionPolicyProto' model. Message that specifies the retention policy for backup snapshots. Attributes: num_days_to_keep (long|int): The number of days to keep the snapshots for a backup run. num_secs_to_kee... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RetentionPolicyProto:
"""Implementation of the 'RetentionPolicyProto' model. Message that specifies the retention policy for backup snapshots. Attributes: num_days_to_keep (long|int): The number of days to keep the snapshots for a backup run. num_secs_to_keep (int): The number of seconds to keep ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RetentionPolicyProto:
"""Implementation of the 'RetentionPolicyProto' model. Message that specifies the retention policy for backup snapshots. Attributes: num_days_to_keep (long|int): The number of days to keep the snapshots for a backup run. num_secs_to_keep (int): The number of seconds to keep the snapshots... | the_stack_v2_python_sparse | cohesity_management_sdk/models/retention_policy_proto.py | cohesity/management-sdk-python | train | 24 |
e3b6256a39d11024c89e871880a2b27923d4e112 | [
"partitions = HiveUtil.get_table_partitions(spark, table_name)\nnewest_partition = partitions[0] if partitions else None\nreturn newest_partition",
"partitions = HiveUtil.get_table_partitions(spark, table_name)\nif not partitions:\n print(f'====table {table_name} has no partition')\n return None\nfor partit... | <|body_start_0|>
partitions = HiveUtil.get_table_partitions(spark, table_name)
newest_partition = partitions[0] if partitions else None
return newest_partition
<|end_body_0|>
<|body_start_1|>
partitions = HiveUtil.get_table_partitions(spark, table_name)
if not partitions:
... | HiveUtil | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HiveUtil:
def newest_partition(spark: SparkSession, table_name: str):
"""get newest partition for hive table error happened if table not exist or spark session is not activate :param spark: current spark session :param table_name: :return: newest partition or None"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_001170 | 3,181 | no_license | [
{
"docstring": "get newest partition for hive table error happened if table not exist or spark session is not activate :param spark: current spark session :param table_name: :return: newest partition or None",
"name": "newest_partition",
"signature": "def newest_partition(spark: SparkSession, table_name... | 4 | null | Implement the Python class `HiveUtil` described below.
Class description:
Implement the HiveUtil class.
Method signatures and docstrings:
- def newest_partition(spark: SparkSession, table_name: str): get newest partition for hive table error happened if table not exist or spark session is not activate :param spark: c... | Implement the Python class `HiveUtil` described below.
Class description:
Implement the HiveUtil class.
Method signatures and docstrings:
- def newest_partition(spark: SparkSession, table_name: str): get newest partition for hive table error happened if table not exist or spark session is not activate :param spark: c... | 9ac20619c426a3240cac08c7e68fc3eeca948c7b | <|skeleton|>
class HiveUtil:
def newest_partition(spark: SparkSession, table_name: str):
"""get newest partition for hive table error happened if table not exist or spark session is not activate :param spark: current spark session :param table_name: :return: newest partition or None"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HiveUtil:
def newest_partition(spark: SparkSession, table_name: str):
"""get newest partition for hive table error happened if table not exist or spark session is not activate :param spark: current spark session :param table_name: :return: newest partition or None"""
partitions = HiveUtil.get_... | the_stack_v2_python_sparse | rose/scwgj/proj_common/hive_util.py | HGrey-EVE/spark_submit | train | 0 | |
296f9b295faa57fbf30195d4f8f71a9aec2c8c3a | [
"if not phone:\n raise ValueError('Users must have a phone')\nif not name:\n raise ValueError('Users must have a name')\nif not type:\n raise ValueError('Users must have a type of Personal or Agent')\nuser = self.model(phone=phone, name=name, type=type)\nuser.set_password(password)\nuser.save(using=self._d... | <|body_start_0|>
if not phone:
raise ValueError('Users must have a phone')
if not name:
raise ValueError('Users must have a name')
if not type:
raise ValueError('Users must have a type of Personal or Agent')
user = self.model(phone=phone, name=name, ty... | AccountManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountManager:
def create_user(self, phone, name, type, password=None):
"""Creates and saves a User with the given email and password."""
<|body_0|>
def create_superuser(self, phone, name, password):
"""Creates and saves a superuser with the given email and password... | stack_v2_sparse_classes_75kplus_train_001171 | 2,600 | no_license | [
{
"docstring": "Creates and saves a User with the given email and password.",
"name": "create_user",
"signature": "def create_user(self, phone, name, type, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email and password.",
"name": "create_superuser",
"s... | 2 | stack_v2_sparse_classes_30k_train_022171 | Implement the Python class `AccountManager` described below.
Class description:
Implement the AccountManager class.
Method signatures and docstrings:
- def create_user(self, phone, name, type, password=None): Creates and saves a User with the given email and password.
- def create_superuser(self, phone, name, passwor... | Implement the Python class `AccountManager` described below.
Class description:
Implement the AccountManager class.
Method signatures and docstrings:
- def create_user(self, phone, name, type, password=None): Creates and saves a User with the given email and password.
- def create_superuser(self, phone, name, passwor... | 55b59edf5735af4f1c2c1544e4e3e545f779239f | <|skeleton|>
class AccountManager:
def create_user(self, phone, name, type, password=None):
"""Creates and saves a User with the given email and password."""
<|body_0|>
def create_superuser(self, phone, name, password):
"""Creates and saves a superuser with the given email and password... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AccountManager:
def create_user(self, phone, name, type, password=None):
"""Creates and saves a User with the given email and password."""
if not phone:
raise ValueError('Users must have a phone')
if not name:
raise ValueError('Users must have a name')
i... | the_stack_v2_python_sparse | accounts/models.py | matir-bank/matirbank-django | train | 0 | |
53207fbb49532c4da6d3d8c8a185a800fbe6a3f7 | [
"self.na_dict = {}\nfor name in self.cont_names:\n if pd.isnull(df[name]).sum():\n if self.add_col:\n df[name + '_na'] = pd.isnull(df[name])\n if name + '_na' not in self.cat_names:\n self.cat_names.append(name + '_na')\n if self.fill_strategy == FillStrategy.ME... | <|body_start_0|>
self.na_dict = {}
for name in self.cont_names:
if pd.isnull(df[name]).sum():
if self.add_col:
df[name + '_na'] = pd.isnull(df[name])
if name + '_na' not in self.cat_names:
self.cat_names.append(n... | Fill the missing values in continuous columns. | FillMissing | [
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FillMissing:
"""Fill the missing values in continuous columns."""
def apply_train(self, df: DataFrame):
"""Fill missing values in `self.cont_names` according to `self.fill_strategy`."""
<|body_0|>
def apply_test(self, df: DataFrame):
"""Fill missing values in `se... | stack_v2_sparse_classes_75kplus_train_001172 | 9,761 | permissive | [
{
"docstring": "Fill missing values in `self.cont_names` according to `self.fill_strategy`.",
"name": "apply_train",
"signature": "def apply_train(self, df: DataFrame)"
},
{
"docstring": "Fill missing values in `self.cont_names` like in `apply_train`.",
"name": "apply_test",
"signature":... | 2 | stack_v2_sparse_classes_30k_train_012264 | Implement the Python class `FillMissing` described below.
Class description:
Fill the missing values in continuous columns.
Method signatures and docstrings:
- def apply_train(self, df: DataFrame): Fill missing values in `self.cont_names` according to `self.fill_strategy`.
- def apply_test(self, df: DataFrame): Fill ... | Implement the Python class `FillMissing` described below.
Class description:
Fill the missing values in continuous columns.
Method signatures and docstrings:
- def apply_train(self, df: DataFrame): Fill missing values in `self.cont_names` according to `self.fill_strategy`.
- def apply_test(self, df: DataFrame): Fill ... | 141e873e42eb5e40665d20349f4b8e9a267ba1c4 | <|skeleton|>
class FillMissing:
"""Fill the missing values in continuous columns."""
def apply_train(self, df: DataFrame):
"""Fill missing values in `self.cont_names` according to `self.fill_strategy`."""
<|body_0|>
def apply_test(self, df: DataFrame):
"""Fill missing values in `se... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FillMissing:
"""Fill the missing values in continuous columns."""
def apply_train(self, df: DataFrame):
"""Fill missing values in `self.cont_names` according to `self.fill_strategy`."""
self.na_dict = {}
for name in self.cont_names:
if pd.isnull(df[name]).sum():
... | the_stack_v2_python_sparse | fastai/tabular/transform.py | jantic/DeOldify | train | 17,137 |
0d1e59ee5c9a339e86b002e5a6ef51efb5b5f1f2 | [
"scale_initializer = kwargs.pop('scale_initializer', None)\nif scale_initializer is None:\n scale_initializer = tf.keras.initializers.RandomNormal(0.3, 0.01)\nsuper(EmbeddingLogitNormalDiag, self).__init__(input_dim, output_dim, scale_initializer=scale_initializer, **kwargs)",
"self.untransformed_loc = self.ad... | <|body_start_0|>
scale_initializer = kwargs.pop('scale_initializer', None)
if scale_initializer is None:
scale_initializer = tf.keras.initializers.RandomNormal(0.3, 0.01)
super(EmbeddingLogitNormalDiag, self).__init__(input_dim, output_dim, scale_initializer=scale_initializer, **kwar... | A distribution-based embedding. Each embedding point is characterized by LogitNormal distribution with a diagonal scale matrix. | EmbeddingLogitNormalDiag | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmbeddingLogitNormalDiag:
"""A distribution-based embedding. Each embedding point is characterized by LogitNormal distribution with a diagonal scale matrix."""
def __init__(self, input_dim, output_dim, **kwargs):
"""Initialize."""
<|body_0|>
def _build_embeddings_distrib... | stack_v2_sparse_classes_75kplus_train_001173 | 32,786 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, input_dim, output_dim, **kwargs)"
},
{
"docstring": "Build embeddings distribution.",
"name": "_build_embeddings_distribution",
"signature": "def _build_embeddings_distribution(self, dtype)"
},
{
"... | 3 | stack_v2_sparse_classes_30k_train_030858 | Implement the Python class `EmbeddingLogitNormalDiag` described below.
Class description:
A distribution-based embedding. Each embedding point is characterized by LogitNormal distribution with a diagonal scale matrix.
Method signatures and docstrings:
- def __init__(self, input_dim, output_dim, **kwargs): Initialize.... | Implement the Python class `EmbeddingLogitNormalDiag` described below.
Class description:
A distribution-based embedding. Each embedding point is characterized by LogitNormal distribution with a diagonal scale matrix.
Method signatures and docstrings:
- def __init__(self, input_dim, output_dim, **kwargs): Initialize.... | 4f05348cf43d2d53ff9cc6dee633de385df883e3 | <|skeleton|>
class EmbeddingLogitNormalDiag:
"""A distribution-based embedding. Each embedding point is characterized by LogitNormal distribution with a diagonal scale matrix."""
def __init__(self, input_dim, output_dim, **kwargs):
"""Initialize."""
<|body_0|>
def _build_embeddings_distrib... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EmbeddingLogitNormalDiag:
"""A distribution-based embedding. Each embedding point is characterized by LogitNormal distribution with a diagonal scale matrix."""
def __init__(self, input_dim, output_dim, **kwargs):
"""Initialize."""
scale_initializer = kwargs.pop('scale_initializer', None)
... | the_stack_v2_python_sparse | psiz/keras/layers/embeddings.py | asuiconlab/psiz | train | 0 |
b4aac92bcdbd1ff770f0ed3c766697e9e0d81fcc | [
"self.players = []\nfor i in range(num_players):\n player = TrainablePlayer()\n if i == trainable_index:\n player.is_trainable = True\n self.players.append(player)\nself.trainer = Trainer(self.players[0], self.players[1], trainable_player='player{}'.format(trainable_index + 1), **trainer_args)",
"... | <|body_start_0|>
self.players = []
for i in range(num_players):
player = TrainablePlayer()
if i == trainable_index:
player.is_trainable = True
self.players.append(player)
self.trainer = Trainer(self.players[0], self.players[1], trainable_player... | test the train module which controls multi-hole and multi-game matches | TestTrainer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestTrainer:
"""test the train module which controls multi-hole and multi-game matches"""
def _setup_players_and_trainer(self, trainable_index=0, num_players=2, trainer_args={}):
"""Setup players - with the option to make them trainable"""
<|body_0|>
def test_creation_pa... | stack_v2_sparse_classes_75kplus_train_001174 | 6,447 | no_license | [
{
"docstring": "Setup players - with the option to make them trainable",
"name": "_setup_players_and_trainer",
"signature": "def _setup_players_and_trainer(self, trainable_index=0, num_players=2, trainer_args={})"
},
{
"docstring": "Test the initialization of params for the trainer class",
"... | 5 | null | Implement the Python class `TestTrainer` described below.
Class description:
test the train module which controls multi-hole and multi-game matches
Method signatures and docstrings:
- def _setup_players_and_trainer(self, trainable_index=0, num_players=2, trainer_args={}): Setup players - with the option to make them ... | Implement the Python class `TestTrainer` described below.
Class description:
test the train module which controls multi-hole and multi-game matches
Method signatures and docstrings:
- def _setup_players_and_trainer(self, trainable_index=0, num_players=2, trainer_args={}): Setup players - with the option to make them ... | fd5dc391c04083cccaa3e2eea23619494b60ce0c | <|skeleton|>
class TestTrainer:
"""test the train module which controls multi-hole and multi-game matches"""
def _setup_players_and_trainer(self, trainable_index=0, num_players=2, trainer_args={}):
"""Setup players - with the option to make them trainable"""
<|body_0|>
def test_creation_pa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestTrainer:
"""test the train module which controls multi-hole and multi-game matches"""
def _setup_players_and_trainer(self, trainable_index=0, num_players=2, trainer_args={}):
"""Setup players - with the option to make them trainable"""
self.players = []
for i in range(num_play... | the_stack_v2_python_sparse | golf/unit_tests/test_trainer.py | RaymondKlass/golf-reinforcement | train | 0 |
7f65df1744c71553f605286898749eb0e1510eae | [
"super().__init__()\nassert latent_size != 0 and latent_size & latent_size - 1 == 0, 'latent size not a power of 2'\nif depth >= 4:\n assert latent_size >= np.power(2, depth - 4), 'latent size will diminish to zero'\nself.use_eql = use_eql\nself.depth = depth\nself.latent_size = latent_size\nself.initial_block =... | <|body_start_0|>
super().__init__()
assert latent_size != 0 and latent_size & latent_size - 1 == 0, 'latent size not a power of 2'
if depth >= 4:
assert latent_size >= np.power(2, depth - 4), 'latent size will diminish to zero'
self.use_eql = use_eql
self.depth = dept... | Generator | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Generator:
def __init__(self, depth=7, latent_size=512, use_eql=True):
"""constructor for the Generator class :param depth: required depth of the Network :param latent_size: size of the latent manifold :param use_eql: whether to use equalized learning rate"""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus_train_001175 | 10,883 | permissive | [
{
"docstring": "constructor for the Generator class :param depth: required depth of the Network :param latent_size: size of the latent manifold :param use_eql: whether to use equalized learning rate",
"name": "__init__",
"signature": "def __init__(self, depth=7, latent_size=512, use_eql=True)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_036312 | Implement the Python class `Generator` described below.
Class description:
Implement the Generator class.
Method signatures and docstrings:
- def __init__(self, depth=7, latent_size=512, use_eql=True): constructor for the Generator class :param depth: required depth of the Network :param latent_size: size of the late... | Implement the Python class `Generator` described below.
Class description:
Implement the Generator class.
Method signatures and docstrings:
- def __init__(self, depth=7, latent_size=512, use_eql=True): constructor for the Generator class :param depth: required depth of the Network :param latent_size: size of the late... | 30e7404924070f63b68e73f33f2b42ea8be22f65 | <|skeleton|>
class Generator:
def __init__(self, depth=7, latent_size=512, use_eql=True):
"""constructor for the Generator class :param depth: required depth of the Network :param latent_size: size of the latent manifold :param use_eql: whether to use equalized learning rate"""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Generator:
def __init__(self, depth=7, latent_size=512, use_eql=True):
"""constructor for the Generator class :param depth: required depth of the Network :param latent_size: size of the latent manifold :param use_eql: whether to use equalized learning rate"""
super().__init__()
assert ... | the_stack_v2_python_sparse | model/pggan/utils/Networks.py | TrendingTechnology/MTV-TSA | train | 0 | |
093be06cf49b3ee130d3c67e3fd9aa17f7233f02 | [
"repo = values['repo']\nif repo:\n if isinstance(v, dict):\n v.setdefault('tag', repo)\n elif isinstance(v, DockerImageBuildApiOptions) and (not v.tag):\n v.tag = repo\nreturn v",
"if v and isinstance(v, dict):\n return ElasticContainerRegistryRepository.parse_obj({'repo_name': v.get('repo_... | <|body_start_0|>
repo = values['repo']
if repo:
if isinstance(v, dict):
v.setdefault('tag', repo)
elif isinstance(v, DockerImageBuildApiOptions) and (not v.tag):
v.tag = repo
return v
<|end_body_0|>
<|body_start_1|>
if v and isinst... | Args passed to image.build. | ImageBuildArgs | [
"BSD-2-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageBuildArgs:
"""Args passed to image.build."""
def _set_docker(cls, v: Union[Dict[str, Any], DockerImageBuildApiOptions, Any], values: Dict[str, Any]) -> Any:
"""Set the value of ``docker``."""
<|body_0|>
def _set_ecr_repo(cls, v: Any, values: Dict[str, Any]) -> Any:
... | stack_v2_sparse_classes_75kplus_train_001176 | 6,815 | permissive | [
{
"docstring": "Set the value of ``docker``.",
"name": "_set_docker",
"signature": "def _set_docker(cls, v: Union[Dict[str, Any], DockerImageBuildApiOptions, Any], values: Dict[str, Any]) -> Any"
},
{
"docstring": "Set the value of ``ecr_repo``.",
"name": "_set_ecr_repo",
"signature": "d... | 4 | stack_v2_sparse_classes_30k_train_010560 | Implement the Python class `ImageBuildArgs` described below.
Class description:
Args passed to image.build.
Method signatures and docstrings:
- def _set_docker(cls, v: Union[Dict[str, Any], DockerImageBuildApiOptions, Any], values: Dict[str, Any]) -> Any: Set the value of ``docker``.
- def _set_ecr_repo(cls, v: Any, ... | Implement the Python class `ImageBuildArgs` described below.
Class description:
Args passed to image.build.
Method signatures and docstrings:
- def _set_docker(cls, v: Union[Dict[str, Any], DockerImageBuildApiOptions, Any], values: Dict[str, Any]) -> Any: Set the value of ``docker``.
- def _set_ecr_repo(cls, v: Any, ... | 0763b06aee07d2cf3f037a49ca0cb81a048c5deb | <|skeleton|>
class ImageBuildArgs:
"""Args passed to image.build."""
def _set_docker(cls, v: Union[Dict[str, Any], DockerImageBuildApiOptions, Any], values: Dict[str, Any]) -> Any:
"""Set the value of ``docker``."""
<|body_0|>
def _set_ecr_repo(cls, v: Any, values: Dict[str, Any]) -> Any:
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImageBuildArgs:
"""Args passed to image.build."""
def _set_docker(cls, v: Union[Dict[str, Any], DockerImageBuildApiOptions, Any], values: Dict[str, Any]) -> Any:
"""Set the value of ``docker``."""
repo = values['repo']
if repo:
if isinstance(v, dict):
v... | the_stack_v2_python_sparse | runway/cfngin/hooks/docker/image/_build.py | onicagroup/runway | train | 156 |
522410df50463b49e0b5852197fb2d922a8a4c2f | [
"self.token = token\nheaders = {'X-RFToken': token, 'User-Agent': header}\nself.session = requests.Session()\nself.session.headers.update(headers)\nself.helper = helper",
"enrichment = self._enrich(entity, type_)\nlinks = self._get_links(enrichment['entity']['id'])\nenrichment['links'] = links\nreturn enrichment"... | <|body_start_0|>
self.token = token
headers = {'X-RFToken': token, 'User-Agent': header}
self.session = requests.Session()
self.session.headers.update(headers)
self.helper = helper
<|end_body_0|>
<|body_start_1|>
enrichment = self._enrich(entity, type_)
links = s... | class for talking to the RF API, specifically for enriching indicators | RFClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RFClient:
"""class for talking to the RF API, specifically for enriching indicators"""
def __init__(self, token, helper, header='OpenCTI-Enrichment/2.0'):
"""Inits function"""
<|body_0|>
def full_enrichment(self, entity, type_):
"""Enrich an individual IOC"""
... | stack_v2_sparse_classes_75kplus_train_001177 | 2,351 | permissive | [
{
"docstring": "Inits function",
"name": "__init__",
"signature": "def __init__(self, token, helper, header='OpenCTI-Enrichment/2.0')"
},
{
"docstring": "Enrich an individual IOC",
"name": "full_enrichment",
"signature": "def full_enrichment(self, entity, type_)"
},
{
"docstring"... | 4 | stack_v2_sparse_classes_30k_train_041834 | Implement the Python class `RFClient` described below.
Class description:
class for talking to the RF API, specifically for enriching indicators
Method signatures and docstrings:
- def __init__(self, token, helper, header='OpenCTI-Enrichment/2.0'): Inits function
- def full_enrichment(self, entity, type_): Enrich an ... | Implement the Python class `RFClient` described below.
Class description:
class for talking to the RF API, specifically for enriching indicators
Method signatures and docstrings:
- def __init__(self, token, helper, header='OpenCTI-Enrichment/2.0'): Inits function
- def full_enrichment(self, entity, type_): Enrich an ... | d00a0243946ded25b5d06bdefd9b40015dea9b80 | <|skeleton|>
class RFClient:
"""class for talking to the RF API, specifically for enriching indicators"""
def __init__(self, token, helper, header='OpenCTI-Enrichment/2.0'):
"""Inits function"""
<|body_0|>
def full_enrichment(self, entity, type_):
"""Enrich an individual IOC"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RFClient:
"""class for talking to the RF API, specifically for enriching indicators"""
def __init__(self, token, helper, header='OpenCTI-Enrichment/2.0'):
"""Inits function"""
self.token = token
headers = {'X-RFToken': token, 'User-Agent': header}
self.session = requests.S... | the_stack_v2_python_sparse | internal-enrichment/recordedfuture-enrichment/src/rflib/rf_client.py | OpenCTI-Platform/connectors | train | 254 |
6a48537f508272e8be4fbe70366bbeccb4ab8ab9 | [
"super(Model, self).__init__(model_proto, is_training)\nif not isinstance(model_proto, vse_model_pb2.VSEModel):\n raise ValueError('The model_proto has to be an instance of VSEModel.')\nself._stmt_encoder = builder.build(model_proto.stmt_encoder, is_training)\nself._mining_fn = triplet_loss.build_mining_func(mod... | <|body_start_0|>
super(Model, self).__init__(model_proto, is_training)
if not isinstance(model_proto, vse_model_pb2.VSEModel):
raise ValueError('The model_proto has to be an instance of VSEModel.')
self._stmt_encoder = builder.build(model_proto.stmt_encoder, is_training)
self... | VSEModel. | Model | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
"""VSEModel."""
def __init__(self, model_proto, is_training=False):
"""Initializes ads model. Args: model_proto: an instance of vse_model_pb2.VSEModel. is_training: if True, training graph would be built."""
<|body_0|>
def build_inference_graph(self, examples, **k... | stack_v2_sparse_classes_75kplus_train_001178 | 4,530 | no_license | [
{
"docstring": "Initializes ads model. Args: model_proto: an instance of vse_model_pb2.VSEModel. is_training: if True, training graph would be built.",
"name": "__init__",
"signature": "def __init__(self, model_proto, is_training=False)"
},
{
"docstring": "Builds tensorflow graph for inference. ... | 3 | null | Implement the Python class `Model` described below.
Class description:
VSEModel.
Method signatures and docstrings:
- def __init__(self, model_proto, is_training=False): Initializes ads model. Args: model_proto: an instance of vse_model_pb2.VSEModel. is_training: if True, training graph would be built.
- def build_inf... | Implement the Python class `Model` described below.
Class description:
VSEModel.
Method signatures and docstrings:
- def __init__(self, model_proto, is_training=False): Initializes ads model. Args: model_proto: an instance of vse_model_pb2.VSEModel. is_training: if True, training graph would be built.
- def build_inf... | 2ea5e1405b1ab178b95f9c2cd9158b16847ac6a3 | <|skeleton|>
class Model:
"""VSEModel."""
def __init__(self, model_proto, is_training=False):
"""Initializes ads model. Args: model_proto: an instance of vse_model_pb2.VSEModel. is_training: if True, training graph would be built."""
<|body_0|>
def build_inference_graph(self, examples, **k... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Model:
"""VSEModel."""
def __init__(self, model_proto, is_training=False):
"""Initializes ads model. Args: model_proto: an instance of vse_model_pb2.VSEModel. is_training: if True, training graph would be built."""
super(Model, self).__init__(model_proto, is_training)
if not isins... | the_stack_v2_python_sparse | models/vse_model.py | yekeren/ADVISE-Image_ads_understanding | train | 22 |
7b96372c84777c99f59c36bc55cfb7e89cc53a9b | [
"str_list = []\nself._html_print_obj(obj_json, str_list, 0)\nstr_list.append('<button class=\"btn btn-secondary sodar-list-btn sodar-copy-btn sodar-tl-copy-btn\" data-clipboard-target=\"#data-to-clipboard\" title=\"Copy to clipboard\" data-toggle=\"tooltip\"><i class=\"iconify\" data-icon=\"mdi:clipboard-multiple-o... | <|body_start_0|>
str_list = []
self._html_print_obj(obj_json, str_list, 0)
str_list.append('<button class="btn btn-secondary sodar-list-btn sodar-copy-btn sodar-tl-copy-btn" data-clipboard-target="#data-to-clipboard" title="Copy to clipboard" data-toggle="tooltip"><i class="iconify" data-icon="m... | Mixin for event extra data retrieval helpers | EventExtraDataMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventExtraDataMixin:
"""Mixin for event extra data retrieval helpers"""
def _json_to_html(self, obj_json):
"""Return HTML representation of JSON object"""
<|body_0|>
def _html_print_obj(self, obj_json, str_list: list, indent):
"""Print JSON object to HTML string ... | stack_v2_sparse_classes_75kplus_train_001179 | 10,045 | permissive | [
{
"docstring": "Return HTML representation of JSON object",
"name": "_json_to_html",
"signature": "def _json_to_html(self, obj_json)"
},
{
"docstring": "Print JSON object to HTML string list",
"name": "_html_print_obj",
"signature": "def _html_print_obj(self, obj_json, str_list: list, in... | 5 | stack_v2_sparse_classes_30k_train_018369 | Implement the Python class `EventExtraDataMixin` described below.
Class description:
Mixin for event extra data retrieval helpers
Method signatures and docstrings:
- def _json_to_html(self, obj_json): Return HTML representation of JSON object
- def _html_print_obj(self, obj_json, str_list: list, indent): Print JSON o... | Implement the Python class `EventExtraDataMixin` described below.
Class description:
Mixin for event extra data retrieval helpers
Method signatures and docstrings:
- def _json_to_html(self, obj_json): Return HTML representation of JSON object
- def _html_print_obj(self, obj_json, str_list: list, indent): Print JSON o... | 6156b6409af01828fca506796a736b4f4669f33e | <|skeleton|>
class EventExtraDataMixin:
"""Mixin for event extra data retrieval helpers"""
def _json_to_html(self, obj_json):
"""Return HTML representation of JSON object"""
<|body_0|>
def _html_print_obj(self, obj_json, str_list: list, indent):
"""Print JSON object to HTML string ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EventExtraDataMixin:
"""Mixin for event extra data retrieval helpers"""
def _json_to_html(self, obj_json):
"""Return HTML representation of JSON object"""
str_list = []
self._html_print_obj(obj_json, str_list, 0)
str_list.append('<button class="btn btn-secondary sodar-list... | the_stack_v2_python_sparse | timeline/views_ajax.py | bihealth/sodar-core | train | 7 |
d7f8fd57a0f023836d53a919b0c7c432daa5e943 | [
"self.value = value\nif atom1 is not None and atom2 is not None:\n self.atoms = array([atom1, atom2])\nif orbital1 is not None and orbital2 is not None:\n self.orbitals = array([orbital1, orbital2])\nif spin1 is not None and spin2 is not None:\n self.spins = array([spin1, spin2])\nif atoms is not None:\n ... | <|body_start_0|>
self.value = value
if atom1 is not None and atom2 is not None:
self.atoms = array([atom1, atom2])
if orbital1 is not None and orbital2 is not None:
self.orbitals = array([orbital1, orbital2])
if spin1 is not None and spin2 is not None:
... | This class assumes part of a systematic description of a general quadratic term. Attributes: value: float or complex The overall coefficient of the index pack. atoms: 1D ndarray of integers with len==2 The atom indices for the quadratic term. orbitals: 1D ndarray of integers with len==2 The orbital indices for the quad... | IndexPackage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexPackage:
"""This class assumes part of a systematic description of a general quadratic term. Attributes: value: float or complex The overall coefficient of the index pack. atoms: 1D ndarray of integers with len==2 The atom indices for the quadratic term. orbitals: 1D ndarray of integers with... | stack_v2_sparse_classes_75kplus_train_001180 | 9,705 | no_license | [
{
"docstring": "Constructor. It can be used in two different ways: 1) IndexPackage(value,atom1=...,atom2=...,orbital1=...,orbital2=...,spin1=...,spin2=...) 2) IndexPackage(value,atoms=...,orbitals=...,spins=...) Parameters: value: float or complex The overall coefficient of the index pack atom1,atom2: integer,o... | 5 | stack_v2_sparse_classes_30k_train_014850 | Implement the Python class `IndexPackage` described below.
Class description:
This class assumes part of a systematic description of a general quadratic term. Attributes: value: float or complex The overall coefficient of the index pack. atoms: 1D ndarray of integers with len==2 The atom indices for the quadratic term... | Implement the Python class `IndexPackage` described below.
Class description:
This class assumes part of a systematic description of a general quadratic term. Attributes: value: float or complex The overall coefficient of the index pack. atoms: 1D ndarray of integers with len==2 The atom indices for the quadratic term... | c985d0e5c70b08ef396dd591180c493b60b268ee | <|skeleton|>
class IndexPackage:
"""This class assumes part of a systematic description of a general quadratic term. Attributes: value: float or complex The overall coefficient of the index pack. atoms: 1D ndarray of integers with len==2 The atom indices for the quadratic term. orbitals: 1D ndarray of integers with... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IndexPackage:
"""This class assumes part of a systematic description of a general quadratic term. Attributes: value: float or complex The overall coefficient of the index pack. atoms: 1D ndarray of integers with len==2 The atom indices for the quadratic term. orbitals: 1D ndarray of integers with len==2 The o... | the_stack_v2_python_sparse | Core/BasicClass/IndexPackagePy.py | Farewell1989/Hamiltonian-Generator | train | 0 |
d2c96ccf6a11c9696b42cbfd369fdeb1ab1336e1 | [
"kb.initialize(prefix='/rosplan_knowledge_base')\nrospy.init_node('hectic_knowledge_deriving', anonymous=True)\nrospy.Subscriber('sound_recognised', RecognisedSounds, self.sound_recognised)\nself.notified = False\nrospy.spin()",
"sounds = sounds.sounds\nringing = False\nfor elem in sounds:\n if elem.sound == '... | <|body_start_0|>
kb.initialize(prefix='/rosplan_knowledge_base')
rospy.init_node('hectic_knowledge_deriving', anonymous=True)
rospy.Subscriber('sound_recognised', RecognisedSounds, self.sound_recognised)
self.notified = False
rospy.spin()
<|end_body_0|>
<|body_start_1|>
... | DoorbellKnowledgeDeriving | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoorbellKnowledgeDeriving:
def __init__(self):
"""This will derive knowledge when an alarm bell rings"""
<|body_0|>
def sound_recognised(self, sounds):
"""When an alarm bell rings, put it into the knowledge base"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_75kplus_train_001181 | 1,455 | no_license | [
{
"docstring": "This will derive knowledge when an alarm bell rings",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "When an alarm bell rings, put it into the knowledge base",
"name": "sound_recognised",
"signature": "def sound_recognised(self, sounds)"
}
] | 2 | null | Implement the Python class `DoorbellKnowledgeDeriving` described below.
Class description:
Implement the DoorbellKnowledgeDeriving class.
Method signatures and docstrings:
- def __init__(self): This will derive knowledge when an alarm bell rings
- def sound_recognised(self, sounds): When an alarm bell rings, put it i... | Implement the Python class `DoorbellKnowledgeDeriving` described below.
Class description:
Implement the DoorbellKnowledgeDeriving class.
Method signatures and docstrings:
- def __init__(self): This will derive knowledge when an alarm bell rings
- def sound_recognised(self, sounds): When an alarm bell rings, put it i... | 132c126005451349a045fb46823611caebe74c72 | <|skeleton|>
class DoorbellKnowledgeDeriving:
def __init__(self):
"""This will derive knowledge when an alarm bell rings"""
<|body_0|>
def sound_recognised(self, sounds):
"""When an alarm bell rings, put it into the knowledge base"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DoorbellKnowledgeDeriving:
def __init__(self):
"""This will derive knowledge when an alarm bell rings"""
kb.initialize(prefix='/rosplan_knowledge_base')
rospy.init_node('hectic_knowledge_deriving', anonymous=True)
rospy.Subscriber('sound_recognised', RecognisedSounds, self.soun... | the_stack_v2_python_sparse | src/knowledge_deriving/src/doorbell_knowledge_deriving.py | jonascuypers/spontaneous-robot-reactions | train | 0 | |
7137ac767111ebd62ed8ea5498bca3bc9237270f | [
"response = BaseResponse()\ntry:\n shell_cmd = 'dmidecode -t system'\n output = self.exec_shell_cmd(shell_cmd)\n response.data = self.parse(output)\nexcept Exception as e:\n msg = '%s linux main board plugin error:%s' % (self.host_ip, traceback.format_exc())\n self.logger.log(msg, mode=False)\n re... | <|body_start_0|>
response = BaseResponse()
try:
shell_cmd = 'dmidecode -t system'
output = self.exec_shell_cmd(shell_cmd)
response.data = self.parse(output)
except Exception as e:
msg = '%s linux main board plugin error:%s' % (self.host_ip, traceba... | 获取主板信息 | BoardPlugin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BoardPlugin:
"""获取主板信息"""
def linux(self):
"""执行获取主板命令"""
<|body_0|>
def parse(content):
"""解析shell命令结果 :param self: :param content:shell命令结果 :return: 解析后的结果"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
response = BaseResponse()
try:
... | stack_v2_sparse_classes_75kplus_train_001182 | 1,853 | no_license | [
{
"docstring": "执行获取主板命令",
"name": "linux",
"signature": "def linux(self)"
},
{
"docstring": "解析shell命令结果 :param self: :param content:shell命令结果 :return: 解析后的结果",
"name": "parse",
"signature": "def parse(content)"
}
] | 2 | stack_v2_sparse_classes_30k_val_002453 | Implement the Python class `BoardPlugin` described below.
Class description:
获取主板信息
Method signatures and docstrings:
- def linux(self): 执行获取主板命令
- def parse(content): 解析shell命令结果 :param self: :param content:shell命令结果 :return: 解析后的结果 | Implement the Python class `BoardPlugin` described below.
Class description:
获取主板信息
Method signatures and docstrings:
- def linux(self): 执行获取主板命令
- def parse(content): 解析shell命令结果 :param self: :param content:shell命令结果 :return: 解析后的结果
<|skeleton|>
class BoardPlugin:
"""获取主板信息"""
def linux(self):
"""执... | 73602f72e0ec7f6b49040d38f1591b2245292e3b | <|skeleton|>
class BoardPlugin:
"""获取主板信息"""
def linux(self):
"""执行获取主板命令"""
<|body_0|>
def parse(content):
"""解析shell命令结果 :param self: :param content:shell命令结果 :return: 解析后的结果"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BoardPlugin:
"""获取主板信息"""
def linux(self):
"""执行获取主板命令"""
response = BaseResponse()
try:
shell_cmd = 'dmidecode -t system'
output = self.exec_shell_cmd(shell_cmd)
response.data = self.parse(output)
except Exception as e:
msg ... | the_stack_v2_python_sparse | FhywClient/src/cmdb/board.py | shisanjun/fhyw | train | 0 |
73d3d2465bc2e4e6d86d2cb99dcda7f206940575 | [
"self._db = 'strategy'\nself._collection = 'asset'\nsuper(AssetData, self).__init__(self._db, self._collection)",
"d = {'platform': platform, 'account': account}\nfor key, value in asset.items():\n d[key] = value\nasset_id = await self.insert(d)\nreturn asset_id",
"spec = {'platform': platform, 'account': ac... | <|body_start_0|>
self._db = 'strategy'
self._collection = 'asset'
super(AssetData, self).__init__(self._db, self._collection)
<|end_body_0|>
<|body_start_1|>
d = {'platform': platform, 'account': account}
for key, value in asset.items():
d[key] = value
asset_... | 资产数据存储 资产数据结构: {} | AssetData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssetData:
"""资产数据存储 资产数据结构: {}"""
def __init__(self):
"""初始化"""
<|body_0|>
async def create_new_asset(self, platform, account, asset):
"""创建新的资产信息 @param platform 交易平台 @param account 账户 @param asset 资产详情"""
<|body_1|>
async def update_asset(self, pl... | stack_v2_sparse_classes_75kplus_train_001183 | 12,604 | permissive | [
{
"docstring": "初始化",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "创建新的资产信息 @param platform 交易平台 @param account 账户 @param asset 资产详情",
"name": "create_new_asset",
"signature": "async def create_new_asset(self, platform, account, asset)"
},
{
"docstring... | 4 | null | Implement the Python class `AssetData` described below.
Class description:
资产数据存储 资产数据结构: {}
Method signatures and docstrings:
- def __init__(self): 初始化
- async def create_new_asset(self, platform, account, asset): 创建新的资产信息 @param platform 交易平台 @param account 账户 @param asset 资产详情
- async def update_asset(self, platfo... | Implement the Python class `AssetData` described below.
Class description:
资产数据存储 资产数据结构: {}
Method signatures and docstrings:
- def __init__(self): 初始化
- async def create_new_asset(self, platform, account, asset): 创建新的资产信息 @param platform 交易平台 @param account 账户 @param asset 资产详情
- async def update_asset(self, platfo... | b0b9d60439a916bc4b1980f908f648aa863d5918 | <|skeleton|>
class AssetData:
"""资产数据存储 资产数据结构: {}"""
def __init__(self):
"""初始化"""
<|body_0|>
async def create_new_asset(self, platform, account, asset):
"""创建新的资产信息 @param platform 交易平台 @param account 账户 @param asset 资产详情"""
<|body_1|>
async def update_asset(self, pl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AssetData:
"""资产数据存储 资产数据结构: {}"""
def __init__(self):
"""初始化"""
self._db = 'strategy'
self._collection = 'asset'
super(AssetData, self).__init__(self._db, self._collection)
async def create_new_asset(self, platform, account, asset):
"""创建新的资产信息 @param platfor... | the_stack_v2_python_sparse | quant/data.py | 51bitquant/thenextquant | train | 6 |
def0cd3f64ecc41f25c829404d61c113a2690896 | [
"with open(os.path.join(TESTDATA_DIR, 'get_playable_class__10.json')) as f:\n cls.MONK_CLASS_DATA = json.load(f)\ncls.MONK_SPECS_DATA = {}\nwith open(os.path.join(TESTDATA_DIR, 'get_playable_spec__268.json')) as f:\n cls.MONK_SPECS_DATA[268] = json.load(f)\nwith open(os.path.join(TESTDATA_DIR, 'get_playable_s... | <|body_start_0|>
with open(os.path.join(TESTDATA_DIR, 'get_playable_class__10.json')) as f:
cls.MONK_CLASS_DATA = json.load(f)
cls.MONK_SPECS_DATA = {}
with open(os.path.join(TESTDATA_DIR, 'get_playable_spec__268.json')) as f:
cls.MONK_SPECS_DATA[268] = json.load(f)
... | Checks creation of a wow playable spec. | TestWowPlayableClassModel | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestWowPlayableClassModel:
"""Checks creation of a wow playable spec."""
def setUpClass(cls):
"""Load test data."""
<|body_0|>
def create_mock_api(self) -> unittest.mock.MagicMock:
"""Creates a mock API providing data about the Monk class."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_001184 | 5,861 | permissive | [
{
"docstring": "Load test data.",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Creates a mock API providing data about the Monk class.",
"name": "create_mock_api",
"signature": "def create_mock_api(self) -> unittest.mock.MagicMock"
},
{
"docstring":... | 5 | stack_v2_sparse_classes_30k_train_013438 | Implement the Python class `TestWowPlayableClassModel` described below.
Class description:
Checks creation of a wow playable spec.
Method signatures and docstrings:
- def setUpClass(cls): Load test data.
- def create_mock_api(self) -> unittest.mock.MagicMock: Creates a mock API providing data about the Monk class.
- ... | Implement the Python class `TestWowPlayableClassModel` described below.
Class description:
Checks creation of a wow playable spec.
Method signatures and docstrings:
- def setUpClass(cls): Load test data.
- def create_mock_api(self) -> unittest.mock.MagicMock: Creates a mock API providing data about the Monk class.
- ... | 709dd307b046158ddf9e49a559852d486168a94f | <|skeleton|>
class TestWowPlayableClassModel:
"""Checks creation of a wow playable spec."""
def setUpClass(cls):
"""Load test data."""
<|body_0|>
def create_mock_api(self) -> unittest.mock.MagicMock:
"""Creates a mock API providing data about the Monk class."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestWowPlayableClassModel:
"""Checks creation of a wow playable spec."""
def setUpClass(cls):
"""Load test data."""
with open(os.path.join(TESTDATA_DIR, 'get_playable_class__10.json')) as f:
cls.MONK_CLASS_DATA = json.load(f)
cls.MONK_SPECS_DATA = {}
with open(... | the_stack_v2_python_sparse | api/mod_wow/static_test.py | FunkySayu/discord-event-manager | train | 6 |
99ec9eea977b63fa6bc30eb49ff79122b177b0d0 | [
"self.input_size = input_size\nself.output_size = output_size\nself.alpha = 0.01\nself.alpha_decay = 0.01\nself.gamma = 1",
"neural_net = Sequential()\nneural_net.add(Dense(52, input_dim=self.input_size, activation='tanh'))\nneural_net.add(Dense(128, activation='tanh'))\nneural_net.add(Dense(self.output_size * 2 ... | <|body_start_0|>
self.input_size = input_size
self.output_size = output_size
self.alpha = 0.01
self.alpha_decay = 0.01
self.gamma = 1
<|end_body_0|>
<|body_start_1|>
neural_net = Sequential()
neural_net.add(Dense(52, input_dim=self.input_size, activation='tanh'))... | 'Controller' class that manages the updating of neural networks for a list of agents. | Controller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
"""'Controller' class that manages the updating of neural networks for a list of agents."""
def __init__(self, input_size: int, output_size: int):
"""Initialise the class with learning parameters."""
<|body_0|>
def make_agent(self):
"""Create agent us... | stack_v2_sparse_classes_75kplus_train_001185 | 4,546 | no_license | [
{
"docstring": "Initialise the class with learning parameters.",
"name": "__init__",
"signature": "def __init__(self, input_size: int, output_size: int)"
},
{
"docstring": "Create agent using Keras neural network.",
"name": "make_agent",
"signature": "def make_agent(self)"
},
{
"... | 4 | stack_v2_sparse_classes_30k_train_053920 | Implement the Python class `Controller` described below.
Class description:
'Controller' class that manages the updating of neural networks for a list of agents.
Method signatures and docstrings:
- def __init__(self, input_size: int, output_size: int): Initialise the class with learning parameters.
- def make_agent(s... | Implement the Python class `Controller` described below.
Class description:
'Controller' class that manages the updating of neural networks for a list of agents.
Method signatures and docstrings:
- def __init__(self, input_size: int, output_size: int): Initialise the class with learning parameters.
- def make_agent(s... | c72db39f7e49bd2c4ba9d8446f6ac7b3678928fd | <|skeleton|>
class Controller:
"""'Controller' class that manages the updating of neural networks for a list of agents."""
def __init__(self, input_size: int, output_size: int):
"""Initialise the class with learning parameters."""
<|body_0|>
def make_agent(self):
"""Create agent us... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Controller:
"""'Controller' class that manages the updating of neural networks for a list of agents."""
def __init__(self, input_size: int, output_size: int):
"""Initialise the class with learning parameters."""
self.input_size = input_size
self.output_size = output_size
s... | the_stack_v2_python_sparse | Machine_Learning/DeepQ/RLController.py | JamesNunns/Robotics-Group-Studies | train | 8 |
d2e31fc712762b4ffe2364ea3aacf761c6d3a21a | [
"try:\n entry = db.get_entry_by_id(list_id=list_id, entry_id=entry_id, session=session)\nexcept NoResultFound:\n raise NotFoundError('could not find entry with id %d in list %d' % (entry_id, list_id))\nreturn jsonify(entry.to_dict())",
"try:\n entry = db.get_entry_by_id(list_id=list_id, entry_id=entry_id... | <|body_start_0|>
try:
entry = db.get_entry_by_id(list_id=list_id, entry_id=entry_id, session=session)
except NoResultFound:
raise NotFoundError('could not find entry with id %d in list %d' % (entry_id, list_id))
return jsonify(entry.to_dict())
<|end_body_0|>
<|body_start... | EntryListEntryAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntryListEntryAPI:
def get(self, list_id, entry_id, session=None):
"""Get an entry by list ID and entry ID"""
<|body_0|>
def delete(self, list_id, entry_id, session=None):
"""Delete an entry by list ID and entry ID"""
<|body_1|>
def put(self, list_id, en... | stack_v2_sparse_classes_75kplus_train_001186 | 11,181 | permissive | [
{
"docstring": "Get an entry by list ID and entry ID",
"name": "get",
"signature": "def get(self, list_id, entry_id, session=None)"
},
{
"docstring": "Delete an entry by list ID and entry ID",
"name": "delete",
"signature": "def delete(self, list_id, entry_id, session=None)"
},
{
... | 3 | stack_v2_sparse_classes_30k_val_001281 | Implement the Python class `EntryListEntryAPI` described below.
Class description:
Implement the EntryListEntryAPI class.
Method signatures and docstrings:
- def get(self, list_id, entry_id, session=None): Get an entry by list ID and entry ID
- def delete(self, list_id, entry_id, session=None): Delete an entry by lis... | Implement the Python class `EntryListEntryAPI` described below.
Class description:
Implement the EntryListEntryAPI class.
Method signatures and docstrings:
- def get(self, list_id, entry_id, session=None): Get an entry by list ID and entry ID
- def delete(self, list_id, entry_id, session=None): Delete an entry by lis... | 2b7e8314d103c94cf4552bd0152699eeca0ad159 | <|skeleton|>
class EntryListEntryAPI:
def get(self, list_id, entry_id, session=None):
"""Get an entry by list ID and entry ID"""
<|body_0|>
def delete(self, list_id, entry_id, session=None):
"""Delete an entry by list ID and entry ID"""
<|body_1|>
def put(self, list_id, en... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EntryListEntryAPI:
def get(self, list_id, entry_id, session=None):
"""Get an entry by list ID and entry ID"""
try:
entry = db.get_entry_by_id(list_id=list_id, entry_id=entry_id, session=session)
except NoResultFound:
raise NotFoundError('could not find entry wit... | the_stack_v2_python_sparse | flexget/components/managed_lists/lists/entry_list/api.py | BrutuZ/Flexget | train | 1 | |
5a9b0798d7c7ffb85babad224f395cc8b4bfb9ec | [
"self.full_path = search_path\nself.directory_contents = listdir(self.full_path)\nself.config_filenames = []\nself.comp_filenames = []\nself.vi_list = []\nself._extract_config_filenames()",
"for filename in self.directory_contents:\n if fnmatch(filename, '*.conf'):\n self.config_filenames.append(filenam... | <|body_start_0|>
self.full_path = search_path
self.directory_contents = listdir(self.full_path)
self.config_filenames = []
self.comp_filenames = []
self.vi_list = []
self._extract_config_filenames()
<|end_body_0|>
<|body_start_1|>
for filename in self.directory_c... | Reads SECI configuration files and extracts VI names | ReadConfigFiles | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReadConfigFiles:
"""Reads SECI configuration files and extracts VI names"""
def __init__(self, search_path):
"""create lists for filenames and initialise to empty lists call methods for reading directory contents and searching for config filenames :param search_path: the search path ... | stack_v2_sparse_classes_75kplus_train_001187 | 3,583 | no_license | [
{
"docstring": "create lists for filenames and initialise to empty lists call methods for reading directory contents and searching for config filenames :param search_path: the search path for files",
"name": "__init__",
"signature": "def __init__(self, search_path)"
},
{
"docstring": "extract SE... | 6 | stack_v2_sparse_classes_30k_train_039664 | Implement the Python class `ReadConfigFiles` described below.
Class description:
Reads SECI configuration files and extracts VI names
Method signatures and docstrings:
- def __init__(self, search_path): create lists for filenames and initialise to empty lists call methods for reading directory contents and searching ... | Implement the Python class `ReadConfigFiles` described below.
Class description:
Reads SECI configuration files and extracts VI names
Method signatures and docstrings:
- def __init__(self, search_path): create lists for filenames and initialise to empty lists call methods for reading directory contents and searching ... | bcc5cf19773731979f3e3123a4f585a0bf723c1b | <|skeleton|>
class ReadConfigFiles:
"""Reads SECI configuration files and extracts VI names"""
def __init__(self, search_path):
"""create lists for filenames and initialise to empty lists call methods for reading directory contents and searching for config filenames :param search_path: the search path ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ReadConfigFiles:
"""Reads SECI configuration files and extracts VI names"""
def __init__(self, search_path):
"""create lists for filenames and initialise to empty lists call methods for reading directory contents and searching for config filenames :param search_path: the search path for files"""
... | the_stack_v2_python_sparse | SECI_Config_Analyser/Directory_Operations.py | ISISComputingGroup/ibex_utils | train | 0 |
e1c0538e51c22b15efb5aa83ab6d516d907d66ac | [
"if nr_processes is None:\n available_processors = cpu_count()\n self.processes = available_processors\n print('BatchRunner MP will use {} processors.'.format(self.processes))\nelse:\n self.processes = nr_processes\nsuper().__init__(model_cls, **kwargs)\nself.pool = Pool(self.processes)",
"total_itera... | <|body_start_0|>
if nr_processes is None:
available_processors = cpu_count()
self.processes = available_processors
print('BatchRunner MP will use {} processors.'.format(self.processes))
else:
self.processes = nr_processes
super().__init__(model_cls... | Child class of BatchRunner, extended with multiprocessing support. | BatchRunnerMP | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BatchRunnerMP:
"""Child class of BatchRunner, extended with multiprocessing support."""
def __init__(self, model_cls, nr_processes=None, **kwargs):
"""Create a new BatchRunnerMP for a given model with the given parameters. model_cls: The class of model to batch-run. nr_processes: int... | stack_v2_sparse_classes_75kplus_train_001188 | 21,332 | permissive | [
{
"docstring": "Create a new BatchRunnerMP for a given model with the given parameters. model_cls: The class of model to batch-run. nr_processes: int the number of separate processes the BatchRunner should start, all running in parallel. kwargs: the kwargs required for the parent BatchRunner class",
"name":... | 5 | null | Implement the Python class `BatchRunnerMP` described below.
Class description:
Child class of BatchRunner, extended with multiprocessing support.
Method signatures and docstrings:
- def __init__(self, model_cls, nr_processes=None, **kwargs): Create a new BatchRunnerMP for a given model with the given parameters. mode... | Implement the Python class `BatchRunnerMP` described below.
Class description:
Child class of BatchRunner, extended with multiprocessing support.
Method signatures and docstrings:
- def __init__(self, model_cls, nr_processes=None, **kwargs): Create a new BatchRunnerMP for a given model with the given parameters. mode... | 39efe4007fba2b12b75c72f7795827a1f74d640b | <|skeleton|>
class BatchRunnerMP:
"""Child class of BatchRunner, extended with multiprocessing support."""
def __init__(self, model_cls, nr_processes=None, **kwargs):
"""Create a new BatchRunnerMP for a given model with the given parameters. model_cls: The class of model to batch-run. nr_processes: int... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BatchRunnerMP:
"""Child class of BatchRunner, extended with multiprocessing support."""
def __init__(self, model_cls, nr_processes=None, **kwargs):
"""Create a new BatchRunnerMP for a given model with the given parameters. model_cls: The class of model to batch-run. nr_processes: int the number o... | the_stack_v2_python_sparse | venv/Lib/site-packages/mesa/batchrunner.py | tpike3/SugarScape | train | 11 |
58690e25a79d411293a0eeb743dda16024c9a731 | [
"self.next_link = next_link\nself.total_links = total_links\nself.list = list\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nnext_link = dictionary.get('NextLink')\ntotal_links = dictionary.get('TotalLinks')\nlist = None\nif dictionary.get('List') != None:\n lis... | <|body_start_0|>
self.next_link = next_link
self.total_links = total_links
self.list = list
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
next_link = dictionary.get('NextLink')
to... | Implementation of the 'ListResult[IdentificationLogItem]' model. TODO: type model description here. Attributes: next_link (string): Link to the next results if not set there are less then the return limit of 1000 total_links (int): The total amount of links (pages) for the list list (list of IdentificationLogItem): Lis... | ListResultIdentificationLogItem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListResultIdentificationLogItem:
"""Implementation of the 'ListResult[IdentificationLogItem]' model. TODO: type model description here. Attributes: next_link (string): Link to the next results if not set there are less then the return limit of 1000 total_links (int): The total amount of links (pa... | stack_v2_sparse_classes_75kplus_train_001189 | 2,729 | permissive | [
{
"docstring": "Constructor for the ListResultIdentificationLogItem class",
"name": "__init__",
"signature": "def __init__(self, next_link=None, total_links=None, list=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictio... | 2 | stack_v2_sparse_classes_30k_train_050561 | Implement the Python class `ListResultIdentificationLogItem` described below.
Class description:
Implementation of the 'ListResult[IdentificationLogItem]' model. TODO: type model description here. Attributes: next_link (string): Link to the next results if not set there are less then the return limit of 1000 total_lin... | Implement the Python class `ListResultIdentificationLogItem` described below.
Class description:
Implementation of the 'ListResult[IdentificationLogItem]' model. TODO: type model description here. Attributes: next_link (string): Link to the next results if not set there are less then the return limit of 1000 total_lin... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class ListResultIdentificationLogItem:
"""Implementation of the 'ListResult[IdentificationLogItem]' model. TODO: type model description here. Attributes: next_link (string): Link to the next results if not set there are less then the return limit of 1000 total_links (int): The total amount of links (pa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ListResultIdentificationLogItem:
"""Implementation of the 'ListResult[IdentificationLogItem]' model. TODO: type model description here. Attributes: next_link (string): Link to the next results if not set there are less then the return limit of 1000 total_links (int): The total amount of links (pages) for the ... | the_stack_v2_python_sparse | idfy_rest_client/models/list_result_identification_log_item.py | dealflowteam/Idfy | train | 0 |
3eee3c20521da9edd15910b1581b27b1cb60cd9a | [
"super(SplitterBlock, self).__init__()\nassert len(sections) == 2\nself.sections = sections\nself.header['out_1'] = {}\nself.header['out_1']['dtype'] = str(np.float32)\nself.header['out_1']['nbit'] = 32\nself.header['out_1']['shape'] = sections[0]\nself.header['out_2'] = self.header['out_1']\nself.header['out_2']['... | <|body_start_0|>
super(SplitterBlock, self).__init__()
assert len(sections) == 2
self.sections = sections
self.header['out_1'] = {}
self.header['out_1']['dtype'] = str(np.float32)
self.header['out_1']['nbit'] = 32
self.header['out_1']['shape'] = sections[0]
... | Block which splits up a ring into two | SplitterBlock | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SplitterBlock:
"""Block which splits up a ring into two"""
def __init__(self, sections):
"""@param[in] sections List of two lists - each list is a 1D array of integers indicating sections of the ring to cut. Like numpy slicing indices."""
<|body_0|>
def load_settings(sel... | stack_v2_sparse_classes_75kplus_train_001190 | 49,813 | permissive | [
{
"docstring": "@param[in] sections List of two lists - each list is a 1D array of integers indicating sections of the ring to cut. Like numpy slicing indices.",
"name": "__init__",
"signature": "def __init__(self, sections)"
},
{
"docstring": "Set the gulp sizes appropriate to the input ring",
... | 3 | stack_v2_sparse_classes_30k_train_026046 | Implement the Python class `SplitterBlock` described below.
Class description:
Block which splits up a ring into two
Method signatures and docstrings:
- def __init__(self, sections): @param[in] sections List of two lists - each list is a 1D array of integers indicating sections of the ring to cut. Like numpy slicing ... | Implement the Python class `SplitterBlock` described below.
Class description:
Block which splits up a ring into two
Method signatures and docstrings:
- def __init__(self, sections): @param[in] sections List of two lists - each list is a 1D array of integers indicating sections of the ring to cut. Like numpy slicing ... | 5a93e5d4e906694cf754ac4f1015640a710ffc02 | <|skeleton|>
class SplitterBlock:
"""Block which splits up a ring into two"""
def __init__(self, sections):
"""@param[in] sections List of two lists - each list is a 1D array of integers indicating sections of the ring to cut. Like numpy slicing indices."""
<|body_0|>
def load_settings(sel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SplitterBlock:
"""Block which splits up a ring into two"""
def __init__(self, sections):
"""@param[in] sections List of two lists - each list is a 1D array of integers indicating sections of the ring to cut. Like numpy slicing indices."""
super(SplitterBlock, self).__init__()
asse... | the_stack_v2_python_sparse | python/bifrost/block.py | ledatelescope/bifrost | train | 66 |
d1cf2693d6534155191cf92b85d6544d2c307cd2 | [
"data = np.array([[1, 2, 3], [2, 4, 6], [5, 10, 15]])\nself.cube = set_up_variable_cube(data, 'wind_speed', 'm s-1', 'equalarea')\nself.plugin = DifferenceBetweenAdjacentGridSquares()",
"expected = np.array([[1, 1], [2, 2], [5, 5]])\nresult = self.plugin.calculate_difference(self.cube, self.cube.coord(axis='x').n... | <|body_start_0|>
data = np.array([[1, 2, 3], [2, 4, 6], [5, 10, 15]])
self.cube = set_up_variable_cube(data, 'wind_speed', 'm s-1', 'equalarea')
self.plugin = DifferenceBetweenAdjacentGridSquares()
<|end_body_0|>
<|body_start_1|>
expected = np.array([[1, 1], [2, 2], [5, 5]])
res... | Test the calculate_difference method. | Test_calculate_difference | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_calculate_difference:
"""Test the calculate_difference method."""
def setUp(self):
"""Set up cube."""
<|body_0|>
def test_x_dimension(self):
"""Test differences calculated along the x dimension."""
<|body_1|>
def test_y_dimension(self):
... | stack_v2_sparse_classes_75kplus_train_001191 | 8,701 | permissive | [
{
"docstring": "Set up cube.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test differences calculated along the x dimension.",
"name": "test_x_dimension",
"signature": "def test_x_dimension(self)"
},
{
"docstring": "Test differences calculated along the y ... | 5 | stack_v2_sparse_classes_30k_train_012526 | Implement the Python class `Test_calculate_difference` described below.
Class description:
Test the calculate_difference method.
Method signatures and docstrings:
- def setUp(self): Set up cube.
- def test_x_dimension(self): Test differences calculated along the x dimension.
- def test_y_dimension(self): Test differe... | Implement the Python class `Test_calculate_difference` described below.
Class description:
Test the calculate_difference method.
Method signatures and docstrings:
- def setUp(self): Set up cube.
- def test_x_dimension(self): Test differences calculated along the x dimension.
- def test_y_dimension(self): Test differe... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_calculate_difference:
"""Test the calculate_difference method."""
def setUp(self):
"""Set up cube."""
<|body_0|>
def test_x_dimension(self):
"""Test differences calculated along the x dimension."""
<|body_1|>
def test_y_dimension(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_calculate_difference:
"""Test the calculate_difference method."""
def setUp(self):
"""Set up cube."""
data = np.array([[1, 2, 3], [2, 4, 6], [5, 10, 15]])
self.cube = set_up_variable_cube(data, 'wind_speed', 'm s-1', 'equalarea')
self.plugin = DifferenceBetweenAdjacen... | the_stack_v2_python_sparse | improver_tests/utilities/test_DifferenceBetweenAdjacentGridSquares.py | metoppv/improver | train | 101 |
1b40b2a03ceb5f1bcc60171f6bf2dda7398d7a49 | [
"self.logger = logging.getLogger('portfolio_manager')\nself.logger.info('Starting portfolio manager...')\nself.config = json.loads(open(config_file, 'r').read())\nself.logger.debug('Config loaded')\nself.HOST = self.config['host']\nself.PORT = self.config['port']\nself.REFRESH_TIMEOUT = self.config['refresh_timeout... | <|body_start_0|>
self.logger = logging.getLogger('portfolio_manager')
self.logger.info('Starting portfolio manager...')
self.config = json.loads(open(config_file, 'r').read())
self.logger.debug('Config loaded')
self.HOST = self.config['host']
self.PORT = self.config['port... | Manages the whole Hydra system. Keeps a list of market interfaces and strategies, and assigns resources. It also send initialization and various lifecycle signals to the strategy. Starts a server which handles incoming requests to the manager. | PortfolioManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PortfolioManager:
"""Manages the whole Hydra system. Keeps a list of market interfaces and strategies, and assigns resources. It also send initialization and various lifecycle signals to the strategy. Starts a server which handles incoming requests to the manager."""
def __init__(self, confi... | stack_v2_sparse_classes_75kplus_train_001192 | 4,282 | no_license | [
{
"docstring": "Initialize manager and start manager server :param config_file: filename of the config file containing the necessary info",
"name": "__init__",
"signature": "def __init__(self, config_file='config.json')"
},
{
"docstring": "Cycle that periodically checks registered strategies and... | 2 | stack_v2_sparse_classes_30k_train_002086 | Implement the Python class `PortfolioManager` described below.
Class description:
Manages the whole Hydra system. Keeps a list of market interfaces and strategies, and assigns resources. It also send initialization and various lifecycle signals to the strategy. Starts a server which handles incoming requests to the ma... | Implement the Python class `PortfolioManager` described below.
Class description:
Manages the whole Hydra system. Keeps a list of market interfaces and strategies, and assigns resources. It also send initialization and various lifecycle signals to the strategy. Starts a server which handles incoming requests to the ma... | b036fe92acd8d158a177f5b3b8021797b9ebc24a | <|skeleton|>
class PortfolioManager:
"""Manages the whole Hydra system. Keeps a list of market interfaces and strategies, and assigns resources. It also send initialization and various lifecycle signals to the strategy. Starts a server which handles incoming requests to the manager."""
def __init__(self, confi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PortfolioManager:
"""Manages the whole Hydra system. Keeps a list of market interfaces and strategies, and assigns resources. It also send initialization and various lifecycle signals to the strategy. Starts a server which handles incoming requests to the manager."""
def __init__(self, config_file='confi... | the_stack_v2_python_sparse | portfolio_manager/manager.py | Danis98/Hydra | train | 7 |
00ad209f236b1433a31f17c00d35af216b630163 | [
"del kwargs\ninstance_dict = self._get_instance_dict(context)\nfor gi, s in settings.items():\n s = deepcopy(s)\n try:\n gi.enable(**s)\n instance_dict[gi.name] = gi\n except AttributeError:\n self.machine.gis[gi].enable(**s)\n instance_dict[gi] = self.machine.gis[gi]",
"value... | <|body_start_0|>
del kwargs
instance_dict = self._get_instance_dict(context)
for gi, s in settings.items():
s = deepcopy(s)
try:
gi.enable(**s)
instance_dict[gi.name] = gi
except AttributeError:
self.machine.gis[... | Enables GIs based on config. | GiPlayer | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GiPlayer:
"""Enables GIs based on config."""
def play(self, settings, context, calling_context, priority=0, **kwargs):
"""Enable GIs."""
<|body_0|>
def get_express_config(self, value):
"""Parse express config."""
<|body_1|>
def clear_context(self, co... | stack_v2_sparse_classes_75kplus_train_001193 | 1,312 | permissive | [
{
"docstring": "Enable GIs.",
"name": "play",
"signature": "def play(self, settings, context, calling_context, priority=0, **kwargs)"
},
{
"docstring": "Parse express config.",
"name": "get_express_config",
"signature": "def get_express_config(self, value)"
},
{
"docstring": "Dis... | 3 | null | Implement the Python class `GiPlayer` described below.
Class description:
Enables GIs based on config.
Method signatures and docstrings:
- def play(self, settings, context, calling_context, priority=0, **kwargs): Enable GIs.
- def get_express_config(self, value): Parse express config.
- def clear_context(self, contex... | Implement the Python class `GiPlayer` described below.
Class description:
Enables GIs based on config.
Method signatures and docstrings:
- def play(self, settings, context, calling_context, priority=0, **kwargs): Enable GIs.
- def get_express_config(self, value): Parse express config.
- def clear_context(self, contex... | 00937ab2ff51b1dc668bf465282ffa8ff1eebbd8 | <|skeleton|>
class GiPlayer:
"""Enables GIs based on config."""
def play(self, settings, context, calling_context, priority=0, **kwargs):
"""Enable GIs."""
<|body_0|>
def get_express_config(self, value):
"""Parse express config."""
<|body_1|>
def clear_context(self, co... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GiPlayer:
"""Enables GIs based on config."""
def play(self, settings, context, calling_context, priority=0, **kwargs):
"""Enable GIs."""
del kwargs
instance_dict = self._get_instance_dict(context)
for gi, s in settings.items():
s = deepcopy(s)
try:
... | the_stack_v2_python_sparse | mpf/config_players/gi_player.py | vgrillot/mpf | train | 0 |
6bb164861316ce0e8cd53a7bf584b50ab695464d | [
"self.nums = nums\nself.lens = len(nums)\nself.BIT = [0] * (self.lens + 1)\nfor i in range(self.lens):\n k = i + 1\n while k <= self.lens:\n self.BIT[k] += nums[i]\n k += k & -k",
"diff = val - self.nums[i]\nself.nums[i] = val\ni += 1\nwhile i <= self.lens:\n self.BIT[i] += diff\n i += i... | <|body_start_0|>
self.nums = nums
self.lens = len(nums)
self.BIT = [0] * (self.lens + 1)
for i in range(self.lens):
k = i + 1
while k <= self.lens:
self.BIT[k] += nums[i]
k += k & -k
<|end_body_0|>
<|body_start_1|>
diff = v... | NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def update(self, i, val):
""":type i: int :type val: int :rtype: void"""
<|body_1|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_2|... | stack_v2_sparse_classes_75kplus_train_001194 | 1,866 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type i: int :type val: int :rtype: void",
"name": "update",
"signature": "def update(self, i, val)"
},
{
"docstring": ":type i: int :type j: int :rtype: int",
... | 3 | stack_v2_sparse_classes_30k_train_004251 | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def update(self, i, val): :type i: int :type val: int :rtype: void
- def sumRange(self, i, j): :type i: int :type j: int :rtype:... | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def update(self, i, val): :type i: int :type val: int :rtype: void
- def sumRange(self, i, j): :type i: int :type j: int :rtype:... | 212f8b83d6ac22db1a777f980075d9e12ce521d2 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def update(self, i, val):
""":type i: int :type val: int :rtype: void"""
<|body_1|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_2|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
self.nums = nums
self.lens = len(nums)
self.BIT = [0] * (self.lens + 1)
for i in range(self.lens):
k = i + 1
while k <= self.lens:
self.BIT[k] += nums[i]
... | the_stack_v2_python_sparse | LeetCode/python/307_(Binary Indexed Tree)_hard_Range Sum Query - Mutable.py | FrankieZhen/Lookoop | train | 1 | |
32440e864510ab2c887fd215e7f98ec94d9c97e0 | [
"length = len(nums)\nif k >= length:\n k = k % length\nstep = 0\nwhile step < k:\n lats_num = nums[length - 1]\n end_index = length - 1\n while end_index > 0:\n nums[end_index] = nums[end_index - 1]\n end_index = end_index - 1\n nums[0] = lats_num\n step += 1\nreturn nums",
"n = le... | <|body_start_0|>
length = len(nums)
if k >= length:
k = k % length
step = 0
while step < k:
lats_num = nums[length - 1]
end_index = length - 1
while end_index > 0:
nums[end_index] = nums[end_index - 1]
end_in... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def over_rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: None Do not return anything, modi... | stack_v2_sparse_classes_75kplus_train_001195 | 1,182 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: None Do not return anything, modify nums in-place instead.",
"name": "over_rotate",
"signature": "def over_rotate(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: None Do not return anything, modify nums in-p... | 2 | stack_v2_sparse_classes_30k_train_001771 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def over_rotate(self, nums, k): :type nums: List[int] :type k: int :rtype: None Do not return anything, modify nums in-place instead.
- def rotate(self, nums, k): :type nums: Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def over_rotate(self, nums, k): :type nums: List[int] :type k: int :rtype: None Do not return anything, modify nums in-place instead.
- def rotate(self, nums, k): :type nums: Lis... | f43d70cac56bdf6377b22b865174af822902ff78 | <|skeleton|>
class Solution:
def over_rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: None Do not return anything, modi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def over_rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: None Do not return anything, modify nums in-place instead."""
length = len(nums)
if k >= length:
k = k % length
step = 0
while step < k:
lats_num = nums[lengt... | the_stack_v2_python_sparse | 数组/LeetCode189_旋转数组.py | ltzp/LeetCode | train | 0 | |
05501b6ce329db9dde3d1a76567473870b817b25 | [
"try:\n response_text = response.read()\nexcept AttributeError:\n response_text = response\nself.version, self.status, self.error_type, self.message = (None, None, None, None)\ntry:\n response = json.loads(response_text)\n self.version = response['version']\n self.status = response['status']\n sel... | <|body_start_0|>
try:
response_text = response.read()
except AttributeError:
response_text = response
self.version, self.status, self.error_type, self.message = (None, None, None, None)
try:
response = json.loads(response_text)
self.version... | Object representation of a response received from the Resolve API See http://developer.factual.com/display/docs/Places+API+-+Resolve for details. | ResolveResponse | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResolveResponse:
"""Object representation of a response received from the Resolve API See http://developer.factual.com/display/docs/Places+API+-+Resolve for details."""
def __init__(self, response):
"""response can be string or file-like object"""
<|body_0|>
def get_reso... | stack_v2_sparse_classes_75kplus_train_001196 | 4,243 | no_license | [
{
"docstring": "response can be string or file-like object",
"name": "__init__",
"signature": "def __init__(self, response)"
},
{
"docstring": "Returns the one and only \"resolved\" result, if it exists. Return False if it doesnt. Return value is a dict containing place components as well as res... | 2 | stack_v2_sparse_classes_30k_train_040260 | Implement the Python class `ResolveResponse` described below.
Class description:
Object representation of a response received from the Resolve API See http://developer.factual.com/display/docs/Places+API+-+Resolve for details.
Method signatures and docstrings:
- def __init__(self, response): response can be string or... | Implement the Python class `ResolveResponse` described below.
Class description:
Object representation of a response received from the Resolve API See http://developer.factual.com/display/docs/Places+API+-+Resolve for details.
Method signatures and docstrings:
- def __init__(self, response): response can be string or... | baad13c5812f541478b914575ffba42128edce65 | <|skeleton|>
class ResolveResponse:
"""Object representation of a response received from the Resolve API See http://developer.factual.com/display/docs/Places+API+-+Resolve for details."""
def __init__(self, response):
"""response can be string or file-like object"""
<|body_0|>
def get_reso... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResolveResponse:
"""Object representation of a response received from the Resolve API See http://developer.factual.com/display/docs/Places+API+-+Resolve for details."""
def __init__(self, response):
"""response can be string or file-like object"""
try:
response_text = response... | the_stack_v2_python_sparse | outsourcing/apitools/factual.py | Crockcharterings/onlyinpgh | train | 0 |
e016a92d441f4b2e04ef1f442ee7cc9411b01ba8 | [
"import re\nself.dataset_urls_file_path = dataset_urls_file_path\nself._category_regex = re.compile('[A-Za-z]+:')\nself._document_regex = re.compile('.*,http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*(),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+')",
"import IOUtilities, os\nwith open(self.dataset_urls_file_path, 'r') as f:\n ... | <|body_start_0|>
import re
self.dataset_urls_file_path = dataset_urls_file_path
self._category_regex = re.compile('[A-Za-z]+:')
self._document_regex = re.compile('.*,http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*(),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+')
<|end_body_0|>
<|body_start_1|>
im... | Can be used to create a dataset_utilities for text device_classification. This is done by downloading texts in a specified file and placing them in folders corresponding to their text device_classification category. | DataSetCreator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataSetCreator:
"""Can be used to create a dataset_utilities for text device_classification. This is done by downloading texts in a specified file and placing them in folders corresponding to their text device_classification category."""
def __init__(self, dataset_urls_file_path: str):
... | stack_v2_sparse_classes_75kplus_train_001197 | 3,112 | no_license | [
{
"docstring": ":param dataset_urls_file_path: Filename for a .txt file which consists of category name,text names and urls.",
"name": "__init__",
"signature": "def __init__(self, dataset_urls_file_path: str)"
},
{
"docstring": "From the given dataset_utilities url file, reach document is retrie... | 2 | stack_v2_sparse_classes_30k_train_042526 | Implement the Python class `DataSetCreator` described below.
Class description:
Can be used to create a dataset_utilities for text device_classification. This is done by downloading texts in a specified file and placing them in folders corresponding to their text device_classification category.
Method signatures and ... | Implement the Python class `DataSetCreator` described below.
Class description:
Can be used to create a dataset_utilities for text device_classification. This is done by downloading texts in a specified file and placing them in folders corresponding to their text device_classification category.
Method signatures and ... | e79acd95d02f981aae13b4d6e55e8bdf65dc268c | <|skeleton|>
class DataSetCreator:
"""Can be used to create a dataset_utilities for text device_classification. This is done by downloading texts in a specified file and placing them in folders corresponding to their text device_classification category."""
def __init__(self, dataset_urls_file_path: str):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataSetCreator:
"""Can be used to create a dataset_utilities for text device_classification. This is done by downloading texts in a specified file and placing them in folders corresponding to their text device_classification category."""
def __init__(self, dataset_urls_file_path: str):
""":param ... | the_stack_v2_python_sparse | dataset_utilities/data_set_creation.py | MDThomsen/DBAC-Device-Detection | train | 0 |
0e24f3163912ad1e2fd3656f60a154da16d91d56 | [
"self._model = model\nself._beam_size = beam_size\nself._start_token = start_token\nself._end_token = end_token\nself._max_steps = max_steps",
"enc_top_states, dec_in_state = self._model.encode_top_state(sess, enc_inputs, enc_seqlen)\nhyps = [Hypothesis([self._start_token], 0.0, dec_in_state)] * self._beam_size\n... | <|body_start_0|>
self._model = model
self._beam_size = beam_size
self._start_token = start_token
self._end_token = end_token
self._max_steps = max_steps
<|end_body_0|>
<|body_start_1|>
enc_top_states, dec_in_state = self._model.encode_top_state(sess, enc_inputs, enc_seql... | Beam search. Beam search takes the top K results from the model, predicts the K results for each of the previous K result, getting K*K results. Pick the top K results from K*K results, and start over again until certain number of results are fully decoded | BeamSearch | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BeamSearch:
"""Beam search. Beam search takes the top K results from the model, predicts the K results for each of the previous K result, getting K*K results. Pick the top K results from K*K results, and start over again until certain number of results are fully decoded"""
def __init__(self,... | stack_v2_sparse_classes_75kplus_train_001198 | 5,217 | no_license | [
{
"docstring": "Creates BeamSearch object :param model: Seq2SeqAttentionModel :param beam_size: int :param start_token: int, id of the token to start decoding with :param end_token: int, id of the token that completes an hypothesis :param max_steps: int, upper limit on the size of the hypothesis",
"name": "... | 3 | null | Implement the Python class `BeamSearch` described below.
Class description:
Beam search. Beam search takes the top K results from the model, predicts the K results for each of the previous K result, getting K*K results. Pick the top K results from K*K results, and start over again until certain number of results are f... | Implement the Python class `BeamSearch` described below.
Class description:
Beam search. Beam search takes the top K results from the model, predicts the K results for each of the previous K result, getting K*K results. Pick the top K results from K*K results, and start over again until certain number of results are f... | ee7ecedd55ce544b127be8009e026ac2cdc3f71b | <|skeleton|>
class BeamSearch:
"""Beam search. Beam search takes the top K results from the model, predicts the K results for each of the previous K result, getting K*K results. Pick the top K results from K*K results, and start over again until certain number of results are fully decoded"""
def __init__(self,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BeamSearch:
"""Beam search. Beam search takes the top K results from the model, predicts the K results for each of the previous K result, getting K*K results. Pick the top K results from K*K results, and start over again until certain number of results are fully decoded"""
def __init__(self, model, beam_... | the_stack_v2_python_sparse | model_tensorflow/textsum_model/beam_search.py | ZouJoshua/dl_project | train | 9 |
b024ce790f1a0c6ce1cc0e1f34202313fcedc8a0 | [
"super().__init__()\nself.graph, self.session = parse_tf_model_bytes(model_bytes, device, session_config)\nself.label_map = parse_dataset_metadata_bytes(metadata_bytes)\nself.input_image = self.graph.get_tensor_by_name('input')\nself.segmented_tensor = self.graph.get_tensor_by_name('output_prediction')",
"feed = ... | <|body_start_0|>
super().__init__()
self.graph, self.session = parse_tf_model_bytes(model_bytes, device, session_config)
self.label_map = parse_dataset_metadata_bytes(metadata_bytes)
self.input_image = self.graph.get_tensor_by_name('input')
self.segmented_tensor = self.graph.get_... | Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch prediction TODO: Is this true? | Segmenter | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Segmenter:
"""Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch prediction TODO: Is this true?"""
def __ini... | stack_v2_sparse_classes_75kplus_train_001199 | 2,521 | permissive | [
{
"docstring": ":param model_bytes: Model file data, likely a loaded *.pb file :param metadata_bytes: The dataset metadata file data, likely named \"dataset_metadata.json\" :param device: The device to run the model on :param session_config: Model configuration options",
"name": "__init__",
"signature":... | 2 | stack_v2_sparse_classes_30k_train_007648 | Implement the Python class `Segmenter` described below.
Class description:
Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch predictio... | Implement the Python class `Segmenter` described below.
Class description:
Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch predictio... | 7412902fed8f91c9c82bd42b0180e07673c38bf1 | <|skeleton|>
class Segmenter:
"""Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch prediction TODO: Is this true?"""
def __ini... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Segmenter:
"""Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch prediction TODO: Is this true?"""
def __init__(self, mod... | the_stack_v2_python_sparse | vcap_utils/vcap_utils/backends/segmentation.py | opencv/open_vision_capsules | train | 124 |
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