blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
971732a3eb9197bc8edc5506f5308d2615bd7cea | [
"max_count = 0\ninvalid_index = -1\nstack = []\nfor i in range(len(s)):\n if s[i] == '(':\n stack.append(i)\n elif stack:\n stack.pop()\n start_index = stack[-1] if stack else invalid_index\n max_count = max(max_count, i - start_index)\n else:\n invalid_index = i\nreturn ... | <|body_start_0|>
max_count = 0
invalid_index = -1
stack = []
for i in range(len(s)):
if s[i] == '(':
stack.append(i)
elif stack:
stack.pop()
start_index = stack[-1] if stack else invalid_index
max_cou... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestValidParentheses(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def longestValidParentheses_failed(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
max_count = 0
invalid_index = ... | stack_v2_sparse_classes_75kplus_train_065000 | 2,271 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "longestValidParentheses",
"signature": "def longestValidParentheses(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "longestValidParentheses_failed",
"signature": "def longestValidParentheses_failed(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009584 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestValidParentheses(self, s): :type s: str :rtype: int
- def longestValidParentheses_failed(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestValidParentheses(self, s): :type s: str :rtype: int
- def longestValidParentheses_failed(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def long... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def longestValidParentheses(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def longestValidParentheses_failed(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def longestValidParentheses(self, s):
""":type s: str :rtype: int"""
max_count = 0
invalid_index = -1
stack = []
for i in range(len(s)):
if s[i] == '(':
stack.append(i)
elif stack:
stack.pop()
... | the_stack_v2_python_sparse | src/lt_32.py | oxhead/CodingYourWay | train | 0 | |
849ee7756b4a2a7a10b4f607728664cad457cc32 | [
"try:\n return get_app_name(i)\nexcept CatalogError as e:\n raise EntityNameError('Unable to find name for app id: {}'.format(i))",
"try:\n return get_app_names(ids)\nexcept CatalogError as e:\n raise EntityNameError('Unable to find app names: {}'.format(str(e)))",
"try:\n return get_app_name(i) ... | <|body_start_0|>
try:
return get_app_name(i)
except CatalogError as e:
raise EntityNameError('Unable to find name for app id: {}'.format(i))
<|end_body_0|>
<|body_start_1|>
try:
return get_app_names(ids)
except CatalogError as e:
raise Ent... | AppType | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AppType:
def get_name_from_id(i: str, token: str) -> str:
"""Should return the name as a str. If a fail happens, raise an EntityNameError"""
<|body_0|>
def get_names_from_ids(ids: List[str], token: str) -> Dict[str, str]:
"""Should return a dict with keys -> values =... | stack_v2_sparse_classes_75kplus_train_065001 | 1,266 | permissive | [
{
"docstring": "Should return the name as a str. If a fail happens, raise an EntityNameError",
"name": "get_name_from_id",
"signature": "def get_name_from_id(i: str, token: str) -> str"
},
{
"docstring": "Should return a dict with keys -> values = ids -> names. If any of them fail, set id -> Non... | 3 | stack_v2_sparse_classes_30k_train_028334 | Implement the Python class `AppType` described below.
Class description:
Implement the AppType class.
Method signatures and docstrings:
- def get_name_from_id(i: str, token: str) -> str: Should return the name as a str. If a fail happens, raise an EntityNameError
- def get_names_from_ids(ids: List[str], token: str) -... | Implement the Python class `AppType` described below.
Class description:
Implement the AppType class.
Method signatures and docstrings:
- def get_name_from_id(i: str, token: str) -> str: Should return the name as a str. If a fail happens, raise an EntityNameError
- def get_names_from_ids(ids: List[str], token: str) -... | a2ed4cb88120aeb10a295919cb0fba85e13d462d | <|skeleton|>
class AppType:
def get_name_from_id(i: str, token: str) -> str:
"""Should return the name as a str. If a fail happens, raise an EntityNameError"""
<|body_0|>
def get_names_from_ids(ids: List[str], token: str) -> Dict[str, str]:
"""Should return a dict with keys -> values =... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AppType:
def get_name_from_id(i: str, token: str) -> str:
"""Should return the name as a str. If a fail happens, raise an EntityNameError"""
try:
return get_app_name(i)
except CatalogError as e:
raise EntityNameError('Unable to find name for app id: {}'.format(i... | the_stack_v2_python_sparse | feeds/entity/types/app.py | kbase/feeds | train | 0 | |
ebd1beec3027159b644104cbb2efc334f13b0c69 | [
"self.person = person\nperson.manager = self\nself.career = ManagerCareer(manager=self)\nself.team = team\nself.strategy = Strategy(owner=self)",
"positions = ('P', 'C', '1B', '2B', '3B', 'SS', 'LF', 'CF', 'RF')\npositions_already_covered = {p.position for p in self.team.players}\ntry:\n return next((p for p i... | <|body_start_0|>
self.person = person
person.manager = self
self.career = ManagerCareer(manager=self)
self.team = team
self.strategy = Strategy(owner=self)
<|end_body_0|>
<|body_start_1|>
positions = ('P', 'C', '1B', '2B', '3B', 'SS', 'LF', 'CF', 'RF')
positions_... | The baseball-manager layer of a person's being. | Manager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Manager:
"""The baseball-manager layer of a person's being."""
def __init__(self, person, team):
"""Initialize a Manager object."""
<|body_0|>
def decide_position_of_greatest_need(self):
"""Return the team's position of greatest need in the opinion of this manage... | stack_v2_sparse_classes_75kplus_train_065002 | 1,124 | no_license | [
{
"docstring": "Initialize a Manager object.",
"name": "__init__",
"signature": "def __init__(self, person, team)"
},
{
"docstring": "Return the team's position of greatest need in the opinion of this manager, given their strategy and other concerns.",
"name": "decide_position_of_greatest_ne... | 2 | stack_v2_sparse_classes_30k_train_008073 | Implement the Python class `Manager` described below.
Class description:
The baseball-manager layer of a person's being.
Method signatures and docstrings:
- def __init__(self, person, team): Initialize a Manager object.
- def decide_position_of_greatest_need(self): Return the team's position of greatest need in the o... | Implement the Python class `Manager` described below.
Class description:
The baseball-manager layer of a person's being.
Method signatures and docstrings:
- def __init__(self, person, team): Initialize a Manager object.
- def decide_position_of_greatest_need(self): Return the team's position of greatest need in the o... | 78a9df3ff66d4956f817397c82be0b4e4176e73d | <|skeleton|>
class Manager:
"""The baseball-manager layer of a person's being."""
def __init__(self, person, team):
"""Initialize a Manager object."""
<|body_0|>
def decide_position_of_greatest_need(self):
"""Return the team's position of greatest need in the opinion of this manage... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Manager:
"""The baseball-manager layer of a person's being."""
def __init__(self, person, team):
"""Initialize a Manager object."""
self.person = person
person.manager = self
self.career = ManagerCareer(manager=self)
self.team = team
self.strategy = Strateg... | the_stack_v2_python_sparse | baseball/manager.py | hanok2/national_pastime | train | 1 |
a79b236c599dd279e73918862a4bc6bd08b56819 | [
"super().__init__(arg)\nself.headers = headers\nself.path = path\nself.path_params = path_params\nself.query_params = query_params\nself.accepted: bool = False\n'Whether the message was ever accepted by the server'\nself.close: Optional[Tuple[Sender, int]] = None\n'The sender who closed the connection, along with t... | <|body_start_0|>
super().__init__(arg)
self.headers = headers
self.path = path
self.path_params = path_params
self.query_params = query_params
self.accepted: bool = False
'Whether the message was ever accepted by the server'
self.close: Optional[Tuple[Send... | A transcript of a single websocket connection | RecordedWSTranscript | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecordedWSTranscript:
"""A transcript of a single websocket connection"""
def __init__(self, arg: Iterable[RecordedWSMessage], headers: Dict[bytes, List[bytes]], path: str, path_params: Dict[str, Any], query_params: Dict[str, List[str]]):
"""Args: arg: forwarded to super (List) heade... | stack_v2_sparse_classes_75kplus_train_065003 | 20,254 | permissive | [
{
"docstring": "Args: arg: forwarded to super (List) headers: the headers of the connection path: the path of the connection request path_params: the path params of the connection request, as specified by the route's starlette rule string query_params: the query params of the connection request",
"name": "_... | 2 | stack_v2_sparse_classes_30k_train_040446 | Implement the Python class `RecordedWSTranscript` described below.
Class description:
A transcript of a single websocket connection
Method signatures and docstrings:
- def __init__(self, arg: Iterable[RecordedWSMessage], headers: Dict[bytes, List[bytes]], path: str, path_params: Dict[str, Any], query_params: Dict[str... | Implement the Python class `RecordedWSTranscript` described below.
Class description:
A transcript of a single websocket connection
Method signatures and docstrings:
- def __init__(self, arg: Iterable[RecordedWSMessage], headers: Dict[bytes, List[bytes]], path: str, path_params: Dict[str, Any], query_params: Dict[str... | 1914e42f33f8758d25cc985d672aaa3855ee9261 | <|skeleton|>
class RecordedWSTranscript:
"""A transcript of a single websocket connection"""
def __init__(self, arg: Iterable[RecordedWSMessage], headers: Dict[bytes, List[bytes]], path: str, path_params: Dict[str, Any], query_params: Dict[str, List[str]]):
"""Args: arg: forwarded to super (List) heade... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RecordedWSTranscript:
"""A transcript of a single websocket connection"""
def __init__(self, arg: Iterable[RecordedWSMessage], headers: Dict[bytes, List[bytes]], path: str, path_params: Dict[str, Any], query_params: Dict[str, List[str]]):
"""Args: arg: forwarded to super (List) headers: the heade... | the_stack_v2_python_sparse | yellowbox/extras/webserver/ws_request_capture.py | nx6110a5100/yellowbox | train | 0 |
3dc151b6b2f3e52e809cc8fbecb3d9c507e61fd5 | [
"assert trainable in ('lpips', 'net', 'both', False)\nif trainable and back_prop != True:\n raise Exception('Enable back_prop for training.')\nconfig.validate()\nself.config = config\nif config.metric in ('vgg', 'squeeze', 'vgg_ensemble', 'squeeze_ensemble_maxpool'):\n self.network = pnetlin.PNetLin(pnet_type... | <|body_start_0|>
assert trainable in ('lpips', 'net', 'both', False)
if trainable and back_prop != True:
raise Exception('Enable back_prop for training.')
config.validate()
self.config = config
if config.metric in ('vgg', 'squeeze', 'vgg_ensemble', 'squeeze_ensemble_m... | Metric | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Metric:
def __init__(self, config, back_prop=True, trainable=False, use_lpips_dropout=False, custom_lpips_weights=None, custom_net_weights=None, custom_sample_ensemble=None):
"""Perceptual image distance metric. PARAMS: config: Metric configuration. One of: elpips.elpips_vgg(), elpips.el... | stack_v2_sparse_classes_75kplus_train_065004 | 11,615 | permissive | [
{
"docstring": "Perceptual image distance metric. PARAMS: config: Metric configuration. One of: elpips.elpips_vgg(), elpips.elpips_squeeze_maxpool(), elpips.lpips_vgg(), elpips.lpips_squeeze(). back_prop: Whether to store data for back_prop. trainable: Whether to make weights trainable. Options: 'lpips', 'net',... | 2 | stack_v2_sparse_classes_30k_train_043133 | Implement the Python class `Metric` described below.
Class description:
Implement the Metric class.
Method signatures and docstrings:
- def __init__(self, config, back_prop=True, trainable=False, use_lpips_dropout=False, custom_lpips_weights=None, custom_net_weights=None, custom_sample_ensemble=None): Perceptual imag... | Implement the Python class `Metric` described below.
Class description:
Implement the Metric class.
Method signatures and docstrings:
- def __init__(self, config, back_prop=True, trainable=False, use_lpips_dropout=False, custom_lpips_weights=None, custom_net_weights=None, custom_sample_ensemble=None): Perceptual imag... | 5f14208f00fdd69e99e8b055ffe5fd3c11a6e2b6 | <|skeleton|>
class Metric:
def __init__(self, config, back_prop=True, trainable=False, use_lpips_dropout=False, custom_lpips_weights=None, custom_net_weights=None, custom_sample_ensemble=None):
"""Perceptual image distance metric. PARAMS: config: Metric configuration. One of: elpips.elpips_vgg(), elpips.el... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Metric:
def __init__(self, config, back_prop=True, trainable=False, use_lpips_dropout=False, custom_lpips_weights=None, custom_net_weights=None, custom_sample_ensemble=None):
"""Perceptual image distance metric. PARAMS: config: Metric configuration. One of: elpips.elpips_vgg(), elpips.elpips_squeeze_m... | the_stack_v2_python_sparse | SeaAsiaDX11/SeaAisa/SeaAisa/ngpt/reconstruct/elpips/elpips.py | ChengGongXTU/SeaAsia | train | 8 | |
f8e5679c49ff1f700cc97bc9e6ca4d2d23d27725 | [
"n, m = (len(matrix), len(matrix[0]))\nfor i in range(n):\n for j in range(m):\n if i == j or i > j:\n continue\n matrix[i][j], matrix[j][i] = (matrix[j][i], matrix[i][j])\nfor i in range(n):\n for j in range(m // 2):\n matrix[i][j], matrix[i][m - j - 1] = (matrix[i][m - j - 1]... | <|body_start_0|>
n, m = (len(matrix), len(matrix[0]))
for i in range(n):
for j in range(m):
if i == j or i > j:
continue
matrix[i][j], matrix[j][i] = (matrix[j][i], matrix[i][j])
for i in range(n):
for j in range(m // 2)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate_traverse_flip(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate_intuition(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead.... | stack_v2_sparse_classes_75kplus_train_065005 | 1,068 | no_license | [
{
"docstring": "Do not return anything, modify matrix in-place instead.",
"name": "rotate_traverse_flip",
"signature": "def rotate_traverse_flip(self, matrix: List[List[int]]) -> None"
},
{
"docstring": "Do not return anything, modify matrix in-place instead.",
"name": "rotate_intuition",
... | 2 | stack_v2_sparse_classes_30k_val_001551 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate_traverse_flip(self, matrix: List[List[int]]) -> None: Do not return anything, modify matrix in-place instead.
- def rotate_intuition(self, matrix: List[List[int]]) -> ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate_traverse_flip(self, matrix: List[List[int]]) -> None: Do not return anything, modify matrix in-place instead.
- def rotate_intuition(self, matrix: List[List[int]]) -> ... | 5ed070f22f4bc29777ee5cbb01bb9583726d8799 | <|skeleton|>
class Solution:
def rotate_traverse_flip(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate_intuition(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead.... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rotate_traverse_flip(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
n, m = (len(matrix), len(matrix[0]))
for i in range(n):
for j in range(m):
if i == j or i > j:
contin... | the_stack_v2_python_sparse | 48_rotate_image.py | zdadadaz/coding_practice | train | 0 | |
59fc9fc694531d6db268d0c6ab66198e306b1a0e | [
"game = small.BiasedGame(seed)\nrandom = np.random.RandomState(seed)\nsuccesses = []\nfor _ in range(trials):\n dirichlet_alpha = np.ones(game.num_strategies()[0])\n dist = random.dirichlet(dirichlet_alpha)\n sample_best_responses = np.argmax(game.payoff_tensor()[0], axis=0)\n estimated_best_response = ... | <|body_start_0|>
game = small.BiasedGame(seed)
random = np.random.RandomState(seed)
successes = []
for _ in range(trials):
dirichlet_alpha = np.ones(game.num_strategies()[0])
dist = random.dirichlet(dirichlet_alpha)
sample_best_responses = np.argmax(ga... | SmallTest | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmallTest:
def test_biased_game(self, trials=100, atol=1e-05, rtol=1e-05, seed=1234):
"""Test best responses to sampled opp. actions in BiasedGame are biased."""
<|body_0|>
def simp_to_euc(a, b, center):
"""Transforms a point [a, b] on the simplex to Euclidean space.... | stack_v2_sparse_classes_75kplus_train_065006 | 3,917 | permissive | [
{
"docstring": "Test best responses to sampled opp. actions in BiasedGame are biased.",
"name": "test_biased_game",
"signature": "def test_biased_game(self, trials=100, atol=1e-05, rtol=1e-05, seed=1234)"
},
{
"docstring": "Transforms a point [a, b] on the simplex to Euclidean space. /\\\\ ^ b /... | 3 | stack_v2_sparse_classes_30k_train_028778 | Implement the Python class `SmallTest` described below.
Class description:
Implement the SmallTest class.
Method signatures and docstrings:
- def test_biased_game(self, trials=100, atol=1e-05, rtol=1e-05, seed=1234): Test best responses to sampled opp. actions in BiasedGame are biased.
- def simp_to_euc(a, b, center)... | Implement the Python class `SmallTest` described below.
Class description:
Implement the SmallTest class.
Method signatures and docstrings:
- def test_biased_game(self, trials=100, atol=1e-05, rtol=1e-05, seed=1234): Test best responses to sampled opp. actions in BiasedGame are biased.
- def simp_to_euc(a, b, center)... | ee149736f7d85e16c119a463eee338c6d4c2ceb0 | <|skeleton|>
class SmallTest:
def test_biased_game(self, trials=100, atol=1e-05, rtol=1e-05, seed=1234):
"""Test best responses to sampled opp. actions in BiasedGame are biased."""
<|body_0|>
def simp_to_euc(a, b, center):
"""Transforms a point [a, b] on the simplex to Euclidean space.... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SmallTest:
def test_biased_game(self, trials=100, atol=1e-05, rtol=1e-05, seed=1234):
"""Test best responses to sampled opp. actions in BiasedGame are biased."""
game = small.BiasedGame(seed)
random = np.random.RandomState(seed)
successes = []
for _ in range(trials):
... | the_stack_v2_python_sparse | open_spiel/python/algorithms/adidas_utils/games/small_test.py | lanctot/open_spiel | train | 1 | |
e7921796297175c154cdabe5b5b2595aed7fc8ca | [
"if sample_kwargs is None:\n sample_kwargs = {}\nsuper().__init__(sample_ext=sample_ext, sample_fn=sample_fn, dtype=dtype, normalize=normalize, norm_fn=norm_fn, **sample_kwargs)\nself._label_ext = label_ext\nself._label_fn = label_fn\nself._label_kwargs = kwargs",
"sample_dict = super().__call__(path)\nlabel_d... | <|body_start_0|>
if sample_kwargs is None:
sample_kwargs = {}
super().__init__(sample_ext=sample_ext, sample_fn=sample_fn, dtype=dtype, normalize=normalize, norm_fn=norm_fn, **sample_kwargs)
self._label_ext = label_ext
self._label_fn = label_fn
self._label_kwargs = kw... | LoadSampleLabel | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoadSampleLabel:
def __init__(self, sample_ext: dict, sample_fn: collections.abc.Callable, label_ext: str, label_fn: collections.abc.Callable, dtype: dict=None, normalize: tuple=(), norm_fn=norm_range('-1,1'), sample_kwargs=None, **kwargs):
"""Load sample and label from folder Parameters... | stack_v2_sparse_classes_75kplus_train_065007 | 9,192 | permissive | [
{
"docstring": "Load sample and label from folder Parameters ---------- sample_ext : dict of list Defines the data _sample_ext. The dict key defines the position of the sample inside the returned data dict, while the list defines the the files which should be loaded inside the data dict. Passed to LoadSample. s... | 2 | stack_v2_sparse_classes_30k_train_044651 | Implement the Python class `LoadSampleLabel` described below.
Class description:
Implement the LoadSampleLabel class.
Method signatures and docstrings:
- def __init__(self, sample_ext: dict, sample_fn: collections.abc.Callable, label_ext: str, label_fn: collections.abc.Callable, dtype: dict=None, normalize: tuple=(),... | Implement the Python class `LoadSampleLabel` described below.
Class description:
Implement the LoadSampleLabel class.
Method signatures and docstrings:
- def __init__(self, sample_ext: dict, sample_fn: collections.abc.Callable, label_ext: str, label_fn: collections.abc.Callable, dtype: dict=None, normalize: tuple=(),... | 024a4028856661ac8328443ef3cf3d456a30991c | <|skeleton|>
class LoadSampleLabel:
def __init__(self, sample_ext: dict, sample_fn: collections.abc.Callable, label_ext: str, label_fn: collections.abc.Callable, dtype: dict=None, normalize: tuple=(), norm_fn=norm_range('-1,1'), sample_kwargs=None, **kwargs):
"""Load sample and label from folder Parameters... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LoadSampleLabel:
def __init__(self, sample_ext: dict, sample_fn: collections.abc.Callable, label_ext: str, label_fn: collections.abc.Callable, dtype: dict=None, normalize: tuple=(), norm_fn=norm_range('-1,1'), sample_kwargs=None, **kwargs):
"""Load sample and label from folder Parameters ---------- sa... | the_stack_v2_python_sparse | delira/data_loading/load_utils.py | LTHODAVDOPL/delira | train | 1 | |
9575c09184ee2f111d688de7e502e9cbcff30a87 | [
"try:\n authenticator = TokenAuthenticator(token=config['secret_key'])\n stream = Customers(authenticator=authenticator, start_date=config['start_date'])\n records = stream.read_records(sync_mode=SyncMode.full_refresh)\n next(records)\n return (True, None)\nexcept StopIteration:\n return (True, No... | <|body_start_0|>
try:
authenticator = TokenAuthenticator(token=config['secret_key'])
stream = Customers(authenticator=authenticator, start_date=config['start_date'])
records = stream.read_records(sync_mode=SyncMode.full_refresh)
next(records)
return (T... | SourcePaystack | [
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"Elastic-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourcePaystack:
def check_connection(self, logger, config) -> Tuple[bool, any]:
"""Check connection by fetching customers :param config: the user-input config object conforming to the connector's spec.json :param logger: logger object :return Tuple[bool, any]: (True, None) if the input c... | stack_v2_sparse_classes_75kplus_train_065008 | 2,274 | permissive | [
{
"docstring": "Check connection by fetching customers :param config: the user-input config object conforming to the connector's spec.json :param logger: logger object :return Tuple[bool, any]: (True, None) if the input config can be used to connect to the API successfully, (False, error) otherwise.",
"name... | 2 | stack_v2_sparse_classes_30k_train_040157 | Implement the Python class `SourcePaystack` described below.
Class description:
Implement the SourcePaystack class.
Method signatures and docstrings:
- def check_connection(self, logger, config) -> Tuple[bool, any]: Check connection by fetching customers :param config: the user-input config object conforming to the c... | Implement the Python class `SourcePaystack` described below.
Class description:
Implement the SourcePaystack class.
Method signatures and docstrings:
- def check_connection(self, logger, config) -> Tuple[bool, any]: Check connection by fetching customers :param config: the user-input config object conforming to the c... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class SourcePaystack:
def check_connection(self, logger, config) -> Tuple[bool, any]:
"""Check connection by fetching customers :param config: the user-input config object conforming to the connector's spec.json :param logger: logger object :return Tuple[bool, any]: (True, None) if the input c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SourcePaystack:
def check_connection(self, logger, config) -> Tuple[bool, any]:
"""Check connection by fetching customers :param config: the user-input config object conforming to the connector's spec.json :param logger: logger object :return Tuple[bool, any]: (True, None) if the input config can be u... | the_stack_v2_python_sparse | dts/airbyte/airbyte-integrations/connectors/source-paystack/source_paystack/source.py | alldatacenter/alldata | train | 774 | |
3b48ea9592b0dbbec16092364032cfa22d4503c3 | [
"try:\n if type(file_name) == str and type(data) == list:\n with open(file_name, 'wb') as f:\n pickle.dump(data, f)\n print(f'The TRAIN_DATA has been pickled as file: {file_name}')\n else:\n raise ValueError('Please ensure that two arguments are string and list')\nexcept ValueE... | <|body_start_0|>
try:
if type(file_name) == str and type(data) == list:
with open(file_name, 'wb') as f:
pickle.dump(data, f)
print(f'The TRAIN_DATA has been pickled as file: {file_name}')
else:
raise ValueError('Please ... | NerStats | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NerStats:
def save_labelled_data(file_name: str, data: list):
"""Pickle or save labelled dataset ------- print the name of the file to the console. :param file_name: :param data: :return:"""
<|body_0|>
def load_labelled_data(file_name: str) -> list:
"""load labelled ... | stack_v2_sparse_classes_75kplus_train_065009 | 2,647 | permissive | [
{
"docstring": "Pickle or save labelled dataset ------- print the name of the file to the console. :param file_name: :param data: :return:",
"name": "save_labelled_data",
"signature": "def save_labelled_data(file_name: str, data: list)"
},
{
"docstring": "load labelled data for use Parameters: -... | 4 | stack_v2_sparse_classes_30k_train_053850 | Implement the Python class `NerStats` described below.
Class description:
Implement the NerStats class.
Method signatures and docstrings:
- def save_labelled_data(file_name: str, data: list): Pickle or save labelled dataset ------- print the name of the file to the console. :param file_name: :param data: :return:
- d... | Implement the Python class `NerStats` described below.
Class description:
Implement the NerStats class.
Method signatures and docstrings:
- def save_labelled_data(file_name: str, data: list): Pickle or save labelled dataset ------- print the name of the file to the console. :param file_name: :param data: :return:
- d... | e2c8fe5f68e92d70249d37cd6eb13a3ab046a891 | <|skeleton|>
class NerStats:
def save_labelled_data(file_name: str, data: list):
"""Pickle or save labelled dataset ------- print the name of the file to the console. :param file_name: :param data: :return:"""
<|body_0|>
def load_labelled_data(file_name: str) -> list:
"""load labelled ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NerStats:
def save_labelled_data(file_name: str, data: list):
"""Pickle or save labelled dataset ------- print the name of the file to the console. :param file_name: :param data: :return:"""
try:
if type(file_name) == str and type(data) == list:
with open(file_name,... | the_stack_v2_python_sparse | src/textlabelling/nerstats.py | aakinlalu/textlabelling | train | 2 | |
8fac3d402238a500e69c94077201ea26c70e40cc | [
"for i in range(len(nums) - 1, -1, -1):\n if nums[i] == 0:\n j = i\n while j + 1 <= len(nums) - 1 and nums[j + 1] != 0:\n nums[j], nums[j + 1] = (nums[j + 1], nums[j])\n j += 1",
"idx = 0\nfor n in nums:\n if n != 0:\n nums[idx] = n\n idx += 1\nwhile idx < l... | <|body_start_0|>
for i in range(len(nums) - 1, -1, -1):
if nums[i] == 0:
j = i
while j + 1 <= len(nums) - 1 and nums[j + 1] != 0:
nums[j], nums[j + 1] = (nums[j + 1], nums[j])
j += 1
<|end_body_0|>
<|body_start_1|>
idx ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def moveZeroes2(self, nums: List[int]) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def moveZeroes(self, nums: List[int]) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_75kplus_train_065010 | 760 | no_license | [
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "moveZeroes2",
"signature": "def moveZeroes2(self, nums: List[int]) -> None"
},
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "moveZeroes",
"signature": "def moveZeroes(self,... | 2 | stack_v2_sparse_classes_30k_train_017057 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveZeroes2(self, nums: List[int]) -> None: Do not return anything, modify nums in-place instead.
- def moveZeroes(self, nums: List[int]) -> None: Do not return anything, mod... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveZeroes2(self, nums: List[int]) -> None: Do not return anything, modify nums in-place instead.
- def moveZeroes(self, nums: List[int]) -> None: Do not return anything, mod... | fe30d8ca54309caff975684648495ea953022048 | <|skeleton|>
class Solution:
def moveZeroes2(self, nums: List[int]) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def moveZeroes(self, nums: List[int]) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def moveZeroes2(self, nums: List[int]) -> None:
"""Do not return anything, modify nums in-place instead."""
for i in range(len(nums) - 1, -1, -1):
if nums[i] == 0:
j = i
while j + 1 <= len(nums) - 1 and nums[j + 1] != 0:
... | the_stack_v2_python_sparse | algorithm/leetCode/0283_move_zeroes.py | dictator-x/practise_as | train | 0 | |
b1e1e32bee6df4aeb9ea0c5766d136e28ef5cbee | [
"self.game_referee = game_referee\nself.game_board = game_board\nself.players = players",
"current_player = self.players[0]\nother_player = self.players[1]\nwinner = None\nwhile winner is None:\n winner, proposed_move = self.game_referee.ask_for_move(self.game_board, current_player, other_player)\n current_... | <|body_start_0|>
self.game_referee = game_referee
self.game_board = game_board
self.players = players
<|end_body_0|>
<|body_start_1|>
current_player = self.players[0]
other_player = self.players[1]
winner = None
while winner is None:
winner, proposed_... | Game | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Game:
def __init__(self, game_referee=referee.Referee(), game_board=board.Board(), players=[player.Player(), player.Player()]):
"""The game constructor declares a new board, referee, and two players. First player should be listed first. Args: referee : the current game referee board : th... | stack_v2_sparse_classes_75kplus_train_065011 | 1,481 | no_license | [
{
"docstring": "The game constructor declares a new board, referee, and two players. First player should be listed first. Args: referee : the current game referee board : the game board players : the list of players",
"name": "__init__",
"signature": "def __init__(self, game_referee=referee.Referee(), g... | 2 | stack_v2_sparse_classes_30k_train_035829 | Implement the Python class `Game` described below.
Class description:
Implement the Game class.
Method signatures and docstrings:
- def __init__(self, game_referee=referee.Referee(), game_board=board.Board(), players=[player.Player(), player.Player()]): The game constructor declares a new board, referee, and two play... | Implement the Python class `Game` described below.
Class description:
Implement the Game class.
Method signatures and docstrings:
- def __init__(self, game_referee=referee.Referee(), game_board=board.Board(), players=[player.Player(), player.Player()]): The game constructor declares a new board, referee, and two play... | 4ec458d10bc6a377df212ebffe60562ee281c678 | <|skeleton|>
class Game:
def __init__(self, game_referee=referee.Referee(), game_board=board.Board(), players=[player.Player(), player.Player()]):
"""The game constructor declares a new board, referee, and two players. First player should be listed first. Args: referee : the current game referee board : th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Game:
def __init__(self, game_referee=referee.Referee(), game_board=board.Board(), players=[player.Player(), player.Player()]):
"""The game constructor declares a new board, referee, and two players. First player should be listed first. Args: referee : the current game referee board : the game board p... | the_stack_v2_python_sparse | simple_games/generic_classes/game.py | andrewpenland/TwoPlayerGames | train | 0 | |
a90c7bc9ef903d79cd82af5d14a69dcb9263b38f | [
"self.rate = rate\nself.random_seed = random_seed\nself.scope = scope\nself.device_spec = get_device_spec(default_gpu_id, num_gpus)",
"with tf.variable_scope(self.scope, reuse=tf.AUTO_REUSE), tf.device(self.device_spec):\n if self.rate > 0.0:\n output_dropout = tf.layers.dropout(input_data, self.rate, s... | <|body_start_0|>
self.rate = rate
self.random_seed = random_seed
self.scope = scope
self.device_spec = get_device_spec(default_gpu_id, num_gpus)
<|end_body_0|>
<|body_start_1|>
with tf.variable_scope(self.scope, reuse=tf.AUTO_REUSE), tf.device(self.device_spec):
if s... | dropout layer | Dropout | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dropout:
"""dropout layer"""
def __init__(self, rate, num_gpus=1, default_gpu_id=0, random_seed=0, scope='dropout'):
"""initialize dropout layer"""
<|body_0|>
def __call__(self, input_data, input_mask):
"""call dropout layer"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus_train_065012 | 2,850 | permissive | [
{
"docstring": "initialize dropout layer",
"name": "__init__",
"signature": "def __init__(self, rate, num_gpus=1, default_gpu_id=0, random_seed=0, scope='dropout')"
},
{
"docstring": "call dropout layer",
"name": "__call__",
"signature": "def __call__(self, input_data, input_mask)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000792 | Implement the Python class `Dropout` described below.
Class description:
dropout layer
Method signatures and docstrings:
- def __init__(self, rate, num_gpus=1, default_gpu_id=0, random_seed=0, scope='dropout'): initialize dropout layer
- def __call__(self, input_data, input_mask): call dropout layer | Implement the Python class `Dropout` described below.
Class description:
dropout layer
Method signatures and docstrings:
- def __init__(self, rate, num_gpus=1, default_gpu_id=0, random_seed=0, scope='dropout'): initialize dropout layer
- def __call__(self, input_data, input_mask): call dropout layer
<|skeleton|>
cla... | 05fcbec15e359e3db86af6c3798c13be8a6c58ee | <|skeleton|>
class Dropout:
"""dropout layer"""
def __init__(self, rate, num_gpus=1, default_gpu_id=0, random_seed=0, scope='dropout'):
"""initialize dropout layer"""
<|body_0|>
def __call__(self, input_data, input_mask):
"""call dropout layer"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Dropout:
"""dropout layer"""
def __init__(self, rate, num_gpus=1, default_gpu_id=0, random_seed=0, scope='dropout'):
"""initialize dropout layer"""
self.rate = rate
self.random_seed = random_seed
self.scope = scope
self.device_spec = get_device_spec(default_gpu_id,... | the_stack_v2_python_sparse | sequence_labeling/layer/basic.py | stevezheng23/sequence_labeling_tf | train | 18 |
5c8c027969dfdcea5c18ff866fccdcdefabfaefe | [
"NF = NoiseFigure(value=list((l.noise.value for l in self.chain)))\ngain = PhysicalDimension(value=list((l.gain.dB().value for l in self.chain))[:-1], scale='dB')\nreturn friis(NF, gain)",
"gain = np.zeros(self.chain[0].gain.shape)\nfor l in self.chain:\n gain += l.gain.dB().value\nprint(gain)\nreturn sum(gain... | <|body_start_0|>
NF = NoiseFigure(value=list((l.noise.value for l in self.chain)))
gain = PhysicalDimension(value=list((l.gain.dB().value for l in self.chain))[:-1], scale='dB')
return friis(NF, gain)
<|end_body_0|>
<|body_start_1|>
gain = np.zeros(self.chain[0].gain.shape)
for ... | class used to size rf line-up | RFLineUp | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RFLineUp:
"""class used to size rf line-up"""
def NF(self):
"""return the noise figure of the global line-up."""
<|body_0|>
def gain(self):
"""return the gain of the global line-up."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
NF = NoiseFigur... | stack_v2_sparse_classes_75kplus_train_065013 | 2,133 | permissive | [
{
"docstring": "return the noise figure of the global line-up.",
"name": "NF",
"signature": "def NF(self)"
},
{
"docstring": "return the gain of the global line-up.",
"name": "gain",
"signature": "def gain(self)"
}
] | 2 | null | Implement the Python class `RFLineUp` described below.
Class description:
class used to size rf line-up
Method signatures and docstrings:
- def NF(self): return the noise figure of the global line-up.
- def gain(self): return the gain of the global line-up. | Implement the Python class `RFLineUp` described below.
Class description:
class used to size rf line-up
Method signatures and docstrings:
- def NF(self): return the noise figure of the global line-up.
- def gain(self): return the gain of the global line-up.
<|skeleton|>
class RFLineUp:
"""class used to size rf l... | da7e40005c67202ccd99f19cf49d90fa771e3fcf | <|skeleton|>
class RFLineUp:
"""class used to size rf line-up"""
def NF(self):
"""return the noise figure of the global line-up."""
<|body_0|>
def gain(self):
"""return the gain of the global line-up."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RFLineUp:
"""class used to size rf line-up"""
def NF(self):
"""return the noise figure of the global line-up."""
NF = NoiseFigure(value=list((l.noise.value for l in self.chain)))
gain = PhysicalDimension(value=list((l.gain.dB().value for l in self.chain))[:-1], scale='dB')
... | the_stack_v2_python_sparse | passive_auto_design/system/rf_line_up.py | Patarimi/PassiveAutoDesign | train | 1 |
cecc99a6ef1afc631b2c50575e8da470a7efecd6 | [
"assert config_path.parent.exists(), f'directory {config_path.parent} does not exist'\n\ndef convert_dict(data):\n for key, val in data.items():\n if isinstance(val, pathlib.Path):\n data[key] = str(val)\n if isinstance(val, dict):\n data[key] = convert_dict(val)\n return d... | <|body_start_0|>
assert config_path.parent.exists(), f'directory {config_path.parent} does not exist'
def convert_dict(data):
for key, val in data.items():
if isinstance(val, pathlib.Path):
data[key] = str(val)
if isinstance(val, dict):
... | YamlConfig | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class YamlConfig:
def save(self, config_path: pathlib.Path):
"""Export config as YAML file"""
<|body_0|>
def load(cls, config_path: pathlib.Path):
"""Load config from YAML file"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
assert config_path.parent.exis... | stack_v2_sparse_classes_75kplus_train_065014 | 1,564 | no_license | [
{
"docstring": "Export config as YAML file",
"name": "save",
"signature": "def save(self, config_path: pathlib.Path)"
},
{
"docstring": "Load config from YAML file",
"name": "load",
"signature": "def load(cls, config_path: pathlib.Path)"
}
] | 2 | null | Implement the Python class `YamlConfig` described below.
Class description:
Implement the YamlConfig class.
Method signatures and docstrings:
- def save(self, config_path: pathlib.Path): Export config as YAML file
- def load(cls, config_path: pathlib.Path): Load config from YAML file | Implement the Python class `YamlConfig` described below.
Class description:
Implement the YamlConfig class.
Method signatures and docstrings:
- def save(self, config_path: pathlib.Path): Export config as YAML file
- def load(cls, config_path: pathlib.Path): Load config from YAML file
<|skeleton|>
class YamlConfig:
... | e3381c67988f607f2ebb684ed88d3864dee2f38c | <|skeleton|>
class YamlConfig:
def save(self, config_path: pathlib.Path):
"""Export config as YAML file"""
<|body_0|>
def load(cls, config_path: pathlib.Path):
"""Load config from YAML file"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class YamlConfig:
def save(self, config_path: pathlib.Path):
"""Export config as YAML file"""
assert config_path.parent.exists(), f'directory {config_path.parent} does not exist'
def convert_dict(data):
for key, val in data.items():
if isinstance(val, pathlib.Pat... | the_stack_v2_python_sparse | gan_based_anomaly_detection/src/utils/yaml_config.py | TMdiesel/pytorch-implementation | train | 0 | |
4c172779b2a28c3498570c131f46fec27394a61e | [
"self.molecule = mol_to_mol_graph(molecule)\nif isinstance(job_type, str):\n if job_type.lower() not in job_type_mapping:\n raise ValueError('Job type {} unknown!'.format(job_type))\n self.job_type = job_type_mapping[job_type.lower()]\nelse:\n self.job_type = job_type\nif isinstance(path, Path):\n ... | <|body_start_0|>
self.molecule = mol_to_mol_graph(molecule)
if isinstance(job_type, str):
if job_type.lower() not in job_type_mapping:
raise ValueError('Job type {} unknown!'.format(job_type))
self.job_type = job_type_mapping[job_type.lower()]
else:
... | A helper class to prepare and execute Jaguar calculations. | JaguarJob | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JaguarJob:
"""A helper class to prepare and execute Jaguar calculations."""
def __init__(self, molecule: Union[Molecule, MoleculeGraph], job_type: Union[str, JaguarJobType], path: Union[str, Path], schrodinger_dir: Optional[Union[str, Path]]='SCHRODINGER', job_name: Optional[str]=None, num_c... | stack_v2_sparse_classes_75kplus_train_065015 | 30,590 | no_license | [
{
"docstring": ":param molecule: :param job_type: :param path: :param schrodinger_dir: :param job_name: :param num_cores: :param host: :param save_scratch: :param input_params:",
"name": "__init__",
"signature": "def __init__(self, molecule: Union[Molecule, MoleculeGraph], job_type: Union[str, JaguarJob... | 3 | stack_v2_sparse_classes_30k_train_053757 | Implement the Python class `JaguarJob` described below.
Class description:
A helper class to prepare and execute Jaguar calculations.
Method signatures and docstrings:
- def __init__(self, molecule: Union[Molecule, MoleculeGraph], job_type: Union[str, JaguarJobType], path: Union[str, Path], schrodinger_dir: Optional[... | Implement the Python class `JaguarJob` described below.
Class description:
A helper class to prepare and execute Jaguar calculations.
Method signatures and docstrings:
- def __init__(self, molecule: Union[Molecule, MoleculeGraph], job_type: Union[str, JaguarJobType], path: Union[str, Path], schrodinger_dir: Optional[... | c21e4eb86d9118365e17166c852f3ba6d36dd674 | <|skeleton|>
class JaguarJob:
"""A helper class to prepare and execute Jaguar calculations."""
def __init__(self, molecule: Union[Molecule, MoleculeGraph], job_type: Union[str, JaguarJobType], path: Union[str, Path], schrodinger_dir: Optional[Union[str, Path]]='SCHRODINGER', job_name: Optional[str]=None, num_c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class JaguarJob:
"""A helper class to prepare and execute Jaguar calculations."""
def __init__(self, molecule: Union[Molecule, MoleculeGraph], job_type: Union[str, JaguarJobType], path: Union[str, Path], schrodinger_dir: Optional[Union[str, Path]]='SCHRODINGER', job_name: Optional[str]=None, num_cores: Optiona... | the_stack_v2_python_sparse | mpcat/automate/generate_calcs.py | espottesmith/MPcat | train | 10 |
4c598df0b0989bdf2e546d04e5be15b20a622175 | [
"serialized = []\n\ndef preorder(node):\n if not node:\n return\n serialized.append(str(node.val))\n for child in node.children:\n preorder(child)\n serialized.append('#')\npreorder(root)\nreturn ' '.join(serialized)",
"tokens = deque(data.split())\nif len(tokens) == 0:\n return None\... | <|body_start_0|>
serialized = []
def preorder(node):
if not node:
return
serialized.append(str(node.val))
for child in node.children:
preorder(child)
serialized.append('#')
preorder(root)
return ' '.join(ser... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> 'Node':
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|e... | stack_v2_sparse_classes_75kplus_train_065016 | 1,306 | permissive | [
{
"docstring": "Encodes a tree to a single string. :type root: Node :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root: 'Node') -> str"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: Node",
"name": "deserialize",
"signature": "def des... | 2 | stack_v2_sparse_classes_30k_train_012061 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to tre... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to tre... | fd4cf122cfd4920f3bd8dce40ba7487a170a1b57 | <|skeleton|>
class Codec:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> 'Node':
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|e... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
serialized = []
def preorder(node):
if not node:
return
serialized.append(str(node.val))
for child in node.childre... | the_stack_v2_python_sparse | 0428_Serialize_and_Deserialize_N-ary_Tree.py | coldmanck/leetcode-python | train | 6 | |
86ad00ff5a24d6fef6a809e9f9e237c02c2d0648 | [
"self.coord_names = tuple(coord_names)\nself.name = name\nself.coord_dtype = coord_dtype",
"if name is None:\n name = self.name\nif coord_dtype is None:\n coord_dtype = self.coord_dtype\nif N > len(self.coord_names):\n raise CoordSysMakerError('Not enough axis names (have %d, you asked for %d)' % (len(se... | <|body_start_0|>
self.coord_names = tuple(coord_names)
self.name = name
self.coord_dtype = coord_dtype
<|end_body_0|>
<|body_start_1|>
if name is None:
name = self.name
if coord_dtype is None:
coord_dtype = self.coord_dtype
if N > len(self.coord_n... | Class to create similar coordinate maps of different dimensions | CoordSysMaker | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoordSysMaker:
"""Class to create similar coordinate maps of different dimensions"""
def __init__(self, coord_names, name='', coord_dtype=np.float64):
"""Create a coordsys maker with given axis `coord_names` Parameters ---------- coord_names : iterable A sequence of coordinate names.... | stack_v2_sparse_classes_75kplus_train_065017 | 16,745 | permissive | [
{
"docstring": "Create a coordsys maker with given axis `coord_names` Parameters ---------- coord_names : iterable A sequence of coordinate names. name : string, optional The name of the coordinate system coord_dtype : np.dtype, optional The dtype of the coord_names. This should be a built-in numpy scalar dtype... | 2 | null | Implement the Python class `CoordSysMaker` described below.
Class description:
Class to create similar coordinate maps of different dimensions
Method signatures and docstrings:
- def __init__(self, coord_names, name='', coord_dtype=np.float64): Create a coordsys maker with given axis `coord_names` Parameters --------... | Implement the Python class `CoordSysMaker` described below.
Class description:
Class to create similar coordinate maps of different dimensions
Method signatures and docstrings:
- def __init__(self, coord_names, name='', coord_dtype=np.float64): Create a coordsys maker with given axis `coord_names` Parameters --------... | 7eede02471567487e454016c1e7cf637d3afac9e | <|skeleton|>
class CoordSysMaker:
"""Class to create similar coordinate maps of different dimensions"""
def __init__(self, coord_names, name='', coord_dtype=np.float64):
"""Create a coordsys maker with given axis `coord_names` Parameters ---------- coord_names : iterable A sequence of coordinate names.... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CoordSysMaker:
"""Class to create similar coordinate maps of different dimensions"""
def __init__(self, coord_names, name='', coord_dtype=np.float64):
"""Create a coordsys maker with given axis `coord_names` Parameters ---------- coord_names : iterable A sequence of coordinate names. name : strin... | the_stack_v2_python_sparse | nipy/core/reference/coordinate_system.py | nipy/nipy | train | 275 |
aa9d56bc710b5079229c14ed8db5ca34a28e85b1 | [
"node = TreeNode(5)\nleftNode = TreeNode(4)\nrightNode = TreeNode(5)\nnode.left = leftNode\nnode.right = rightNode\nthirdLevelLeftNode1 = TreeNode(1)\nthirdLevelLeftNode2 = TreeNode(1)\nthirdLevelRightNode1 = TreeNode(5)\nleftNode.left = thirdLevelLeftNode1\nleftNode.right = thirdLevelLeftNode2\nrightNode.right = t... | <|body_start_0|>
node = TreeNode(5)
leftNode = TreeNode(4)
rightNode = TreeNode(5)
node.left = leftNode
node.right = rightNode
thirdLevelLeftNode1 = TreeNode(1)
thirdLevelLeftNode2 = TreeNode(1)
thirdLevelRightNode1 = TreeNode(5)
leftNode.left = th... | TestSolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSolution:
def test_LongestUnivalueCase1(self):
"""5 / 4 5 / \\ / 1 1 5"""
<|body_0|>
def test_LongestUnivalueCase2(self):
"""1 / 4 5 / \\ / 4 4 5"""
<|body_1|>
def test_LongestUnivalueCase3(self):
"""5 / 5 5 / \\ / 5 4 5"""
<|body_2|>... | stack_v2_sparse_classes_75kplus_train_065018 | 2,303 | no_license | [
{
"docstring": "5 / 4 5 / \\\\ / 1 1 5",
"name": "test_LongestUnivalueCase1",
"signature": "def test_LongestUnivalueCase1(self)"
},
{
"docstring": "1 / 4 5 / \\\\ / 4 4 5",
"name": "test_LongestUnivalueCase2",
"signature": "def test_LongestUnivalueCase2(self)"
},
{
"docstring": "... | 3 | stack_v2_sparse_classes_30k_train_031701 | Implement the Python class `TestSolution` described below.
Class description:
Implement the TestSolution class.
Method signatures and docstrings:
- def test_LongestUnivalueCase1(self): 5 / 4 5 / \\ / 1 1 5
- def test_LongestUnivalueCase2(self): 1 / 4 5 / \\ / 4 4 5
- def test_LongestUnivalueCase3(self): 5 / 5 5 / \\ ... | Implement the Python class `TestSolution` described below.
Class description:
Implement the TestSolution class.
Method signatures and docstrings:
- def test_LongestUnivalueCase1(self): 5 / 4 5 / \\ / 1 1 5
- def test_LongestUnivalueCase2(self): 1 / 4 5 / \\ / 4 4 5
- def test_LongestUnivalueCase3(self): 5 / 5 5 / \\ ... | 7fa160362ebb58e7286b490012542baa2d51e5c9 | <|skeleton|>
class TestSolution:
def test_LongestUnivalueCase1(self):
"""5 / 4 5 / \\ / 1 1 5"""
<|body_0|>
def test_LongestUnivalueCase2(self):
"""1 / 4 5 / \\ / 4 4 5"""
<|body_1|>
def test_LongestUnivalueCase3(self):
"""5 / 5 5 / \\ / 5 4 5"""
<|body_2|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestSolution:
def test_LongestUnivalueCase1(self):
"""5 / 4 5 / \\ / 1 1 5"""
node = TreeNode(5)
leftNode = TreeNode(4)
rightNode = TreeNode(5)
node.left = leftNode
node.right = rightNode
thirdLevelLeftNode1 = TreeNode(1)
thirdLevelLeftNode2 = Tr... | the_stack_v2_python_sparse | tree/test_longestUnivaluePath.py | gerrycfchang/leetcode-python | train | 2 | |
1a9cbfbf24c4b3ced7a45dad5323f6f11d355e85 | [
"self.cache = {}\nself.head = Node(None, None)\nself.tail = Node(None, None)\nself.head.next = self.tail\nself.tail.pre = self.head\nself.cap = capacity\nself.size = 0",
"if key not in self.cache:\n return -1\nnode = self.cache[key]\nval = node.val\nself.remove_node(node)\nself.add_to_first(node)\nreturn val",... | <|body_start_0|>
self.cache = {}
self.head = Node(None, None)
self.tail = Node(None, None)
self.head.next = self.tail
self.tail.pre = self.head
self.cap = capacity
self.size = 0
<|end_body_0|>
<|body_start_1|>
if key not in self.cache:
return ... | Hash Map + Doubly Linked List | LRUCache | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
"""Hash Map + Doubly Linked List"""
def __init__(self, capacity: int):
"""cache - dictionary cache[key] = Node(val) DLL - doubly linked list head <-> node <-> node <-> ... <-> tail"""
<|body_0|>
def get(self, key: int) -> int:
"""1 - Key does not exist.... | stack_v2_sparse_classes_75kplus_train_065019 | 2,890 | permissive | [
{
"docstring": "cache - dictionary cache[key] = Node(val) DLL - doubly linked list head <-> node <-> node <-> ... <-> tail",
"name": "__init__",
"signature": "def __init__(self, capacity: int)"
},
{
"docstring": "1 - Key does not exist. 2 - Find the Key-Node pair in self.cache. 3 - Remove this n... | 5 | null | Implement the Python class `LRUCache` described below.
Class description:
Hash Map + Doubly Linked List
Method signatures and docstrings:
- def __init__(self, capacity: int): cache - dictionary cache[key] = Node(val) DLL - doubly linked list head <-> node <-> node <-> ... <-> tail
- def get(self, key: int) -> int: 1 ... | Implement the Python class `LRUCache` described below.
Class description:
Hash Map + Doubly Linked List
Method signatures and docstrings:
- def __init__(self, capacity: int): cache - dictionary cache[key] = Node(val) DLL - doubly linked list head <-> node <-> node <-> ... <-> tail
- def get(self, key: int) -> int: 1 ... | 3c18b8809c5a21a62903060eef659654e0595036 | <|skeleton|>
class LRUCache:
"""Hash Map + Doubly Linked List"""
def __init__(self, capacity: int):
"""cache - dictionary cache[key] = Node(val) DLL - doubly linked list head <-> node <-> node <-> ... <-> tail"""
<|body_0|>
def get(self, key: int) -> int:
"""1 - Key does not exist.... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LRUCache:
"""Hash Map + Doubly Linked List"""
def __init__(self, capacity: int):
"""cache - dictionary cache[key] = Node(val) DLL - doubly linked list head <-> node <-> node <-> ... <-> tail"""
self.cache = {}
self.head = Node(None, None)
self.tail = Node(None, None)
... | the_stack_v2_python_sparse | OOD/146. LRU Cache.py | xli1110/LC | train | 2 |
9a70ad1cdb033df60a45c8d3b1c29a795994e93d | [
"self.exclusive_maximum = exclusive_maximum\nself.exclusive_minimum = exclusive_minimum\nself.id = id\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nexclusive_maximum = dictionary.get('exclusiveMaximum')\nexclusive_minimum = dictionary.get('exclusiveMinimum')\nid =... | <|body_start_0|>
self.exclusive_maximum = exclusive_maximum
self.exclusive_minimum = exclusive_minimum
self.id = id
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
exclusive_maximum = dicti... | Implementation of the 'Attributes' model. TODO: type model description here. Attributes: exclusive_maximum (bool): TODO: type description here. exclusive_minimum (bool): TODO: type description here. id (string): TODO: type description here. | Attributes | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Attributes:
"""Implementation of the 'Attributes' model. TODO: type model description here. Attributes: exclusive_maximum (bool): TODO: type description here. exclusive_minimum (bool): TODO: type description here. id (string): TODO: type description here."""
def __init__(self, exclusive_maxi... | stack_v2_sparse_classes_75kplus_train_065020 | 2,258 | permissive | [
{
"docstring": "Constructor for the Attributes class",
"name": "__init__",
"signature": "def __init__(self, exclusive_maximum=None, exclusive_minimum=None, id=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A ... | 2 | null | Implement the Python class `Attributes` described below.
Class description:
Implementation of the 'Attributes' model. TODO: type model description here. Attributes: exclusive_maximum (bool): TODO: type description here. exclusive_minimum (bool): TODO: type description here. id (string): TODO: type description here.
M... | Implement the Python class `Attributes` described below.
Class description:
Implementation of the 'Attributes' model. TODO: type model description here. Attributes: exclusive_maximum (bool): TODO: type description here. exclusive_minimum (bool): TODO: type description here. id (string): TODO: type description here.
M... | 49acc3d416a1dde7ea43b178d070484baf1b7f2b | <|skeleton|>
class Attributes:
"""Implementation of the 'Attributes' model. TODO: type model description here. Attributes: exclusive_maximum (bool): TODO: type description here. exclusive_minimum (bool): TODO: type description here. id (string): TODO: type description here."""
def __init__(self, exclusive_maxi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Attributes:
"""Implementation of the 'Attributes' model. TODO: type model description here. Attributes: exclusive_maximum (bool): TODO: type description here. exclusive_minimum (bool): TODO: type description here. id (string): TODO: type description here."""
def __init__(self, exclusive_maximum=None, exc... | the_stack_v2_python_sparse | PYTHON_GENERIC_LIB/tester/models/attributes.py | MaryamAdnan3/Tester1 | train | 0 |
165e7c10fdf95aba4c92114f8754229b6432d980 | [
"self.log = TastLogger(self.__class__.__name__)\nself.log.debug('LocalEndpoint: Creating new %s instance...' % self.__class__.__name__)\nsuper(LocalEndpoint, self).__init__(fqdn, username, password, type, version)\nself.viewer_type = viewer_type\nself.viewer_id = viewer_id\nself.connection_interface = None\nself._l... | <|body_start_0|>
self.log = TastLogger(self.__class__.__name__)
self.log.debug('LocalEndpoint: Creating new %s instance...' % self.__class__.__name__)
super(LocalEndpoint, self).__init__(fqdn, username, password, type, version)
self.viewer_type = viewer_type
self.viewer_id = view... | LocalEndpoint class provides functions for managing local PCoIP endpoint. | LocalEndpoint | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocalEndpoint:
"""LocalEndpoint class provides functions for managing local PCoIP endpoint."""
def __init__(self, fqdn, username, password, type, version, viewer_type, viewer_id):
"""Arguments: fqdn: same as for Endpoint username: same as for Endpoint password: same as for Endpoint t... | stack_v2_sparse_classes_75kplus_train_065021 | 6,754 | no_license | [
{
"docstring": "Arguments: fqdn: same as for Endpoint username: same as for Endpoint password: same as for Endpoint type: one of LocalEndpointType values version: same as for Endpoint viewer_type: 'kvmoip' or 'dp-dvi' viewer_id: type specific, for 'kvmoip' switch it is fqdn or ipaddr of the kvmoip device",
... | 3 | stack_v2_sparse_classes_30k_train_007983 | Implement the Python class `LocalEndpoint` described below.
Class description:
LocalEndpoint class provides functions for managing local PCoIP endpoint.
Method signatures and docstrings:
- def __init__(self, fqdn, username, password, type, version, viewer_type, viewer_id): Arguments: fqdn: same as for Endpoint userna... | Implement the Python class `LocalEndpoint` described below.
Class description:
LocalEndpoint class provides functions for managing local PCoIP endpoint.
Method signatures and docstrings:
- def __init__(self, fqdn, username, password, type, version, viewer_type, viewer_id): Arguments: fqdn: same as for Endpoint userna... | f199aae9467c80b57c43070728d4939f405c347a | <|skeleton|>
class LocalEndpoint:
"""LocalEndpoint class provides functions for managing local PCoIP endpoint."""
def __init__(self, fqdn, username, password, type, version, viewer_type, viewer_id):
"""Arguments: fqdn: same as for Endpoint username: same as for Endpoint password: same as for Endpoint t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LocalEndpoint:
"""LocalEndpoint class provides functions for managing local PCoIP endpoint."""
def __init__(self, fqdn, username, password, type, version, viewer_type, viewer_id):
"""Arguments: fqdn: same as for Endpoint username: same as for Endpoint password: same as for Endpoint type: one of L... | the_stack_v2_python_sparse | factory/endpoint/endpoint-001/local_endpoint.py | dragan-nikolic/python_ex | train | 0 |
fadf50b0e0f72d673f9251da18ea61435d646376 | [
"code = ''\nfor i in range(self.dimensions):\n code += '{neighbor}{i} = {coord}{i}{delta};\\n'.format(neighbor=neighbor_prefix, i=i, coord=coord_prefix, delta=self._delta2str[self._neighbor_deltas[index][i]])\nreturn code",
"cell_index = self.topology.lattice.coord_to_index_code(coord_prefix)\ncell_index += ' ... | <|body_start_0|>
code = ''
for i in range(self.dimensions):
code += '{neighbor}{i} = {coord}{i}{delta};\n'.format(neighbor=neighbor_prefix, i=i, coord=coord_prefix, delta=self._delta2str[self._neighbor_deltas[index][i]])
return code
<|end_body_0|>
<|body_start_1|>
cell_index... | The base class for neighborhoods on an orthogonal lattice. It is implementing all necessary :class:`Neighborhood` abstract methods, the only thing you should override is :meth:`dimensions` setter. In :meth:`dimensions`, you should correctly set ``num_neighbors`` and ``_neighbor_deltas`` attributes. | OrthogonalNeighborhood | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrthogonalNeighborhood:
"""The base class for neighborhoods on an orthogonal lattice. It is implementing all necessary :class:`Neighborhood` abstract methods, the only thing you should override is :meth:`dimensions` setter. In :meth:`dimensions`, you should correctly set ``num_neighbors`` and ``_... | stack_v2_sparse_classes_75kplus_train_065022 | 6,400 | permissive | [
{
"docstring": "Generate the C code to obtain neighbor coordinates by its index. See :meth:`Neighborhood.neighbor_coords` for details.",
"name": "neighbor_coords",
"signature": "def neighbor_coords(self, index, coord_prefix, neighbor_prefix)"
},
{
"docstring": "Generate the C code to obtain a ne... | 2 | null | Implement the Python class `OrthogonalNeighborhood` described below.
Class description:
The base class for neighborhoods on an orthogonal lattice. It is implementing all necessary :class:`Neighborhood` abstract methods, the only thing you should override is :meth:`dimensions` setter. In :meth:`dimensions`, you should ... | Implement the Python class `OrthogonalNeighborhood` described below.
Class description:
The base class for neighborhoods on an orthogonal lattice. It is implementing all necessary :class:`Neighborhood` abstract methods, the only thing you should override is :meth:`dimensions` setter. In :meth:`dimensions`, you should ... | a5f736f5478205316898aaa810df9eab949b55f7 | <|skeleton|>
class OrthogonalNeighborhood:
"""The base class for neighborhoods on an orthogonal lattice. It is implementing all necessary :class:`Neighborhood` abstract methods, the only thing you should override is :meth:`dimensions` setter. In :meth:`dimensions`, you should correctly set ``num_neighbors`` and ``_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OrthogonalNeighborhood:
"""The base class for neighborhoods on an orthogonal lattice. It is implementing all necessary :class:`Neighborhood` abstract methods, the only thing you should override is :meth:`dimensions` setter. In :meth:`dimensions`, you should correctly set ``num_neighbors`` and ``_neighbor_delt... | the_stack_v2_python_sparse | xentica/core/topology/neighborhood.py | irthomasthomas/xentica | train | 0 |
ca7badec766cb7eb514a64eeacb031c96540450b | [
"m = len(triangle)\ndp = [[float('inf')] * (m + 1) for _ in range(m + 1)]\ndp[0][1] = 0\nfor i in range(1, m + 1):\n for j in range(1, i + 1):\n dp[i][j] = min(dp[i - 1][j] + triangle[i - 1][j - 1], dp[i - 1][j - 1] + triangle[i - 1][j - 1])\nreturn min(dp[-1])",
"m = len(triangle)\ndp = [float('inf')] ... | <|body_start_0|>
m = len(triangle)
dp = [[float('inf')] * (m + 1) for _ in range(m + 1)]
dp[0][1] = 0
for i in range(1, m + 1):
for j in range(1, i + 1):
dp[i][j] = min(dp[i - 1][j] + triangle[i - 1][j - 1], dp[i - 1][j - 1] + triangle[i - 1][j - 1])
r... | Soluton | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Soluton:
def minimumTotal(self, triangle: list) -> int:
"""dp dp[i][j] 从triangle[0][0] 到 triangle[i][j] 最小路径 dp[i][j] = min(dp[i-1_最短回文串.py][j] + tri[i-1_最短回文串.py][j-1_最短回文串.py], dp[i-1_最短回文串.py][j-1_最短回文串.py] + tri[i-1_最短回文串.py][j-1_最短回文串.py]) dp[0][j] = 'inf' dp[i][0] = 'inf' dp[0][0] ... | stack_v2_sparse_classes_75kplus_train_065023 | 1,782 | no_license | [
{
"docstring": "dp dp[i][j] 从triangle[0][0] 到 triangle[i][j] 最小路径 dp[i][j] = min(dp[i-1_最短回文串.py][j] + tri[i-1_最短回文串.py][j-1_最短回文串.py], dp[i-1_最短回文串.py][j-1_最短回文串.py] + tri[i-1_最短回文串.py][j-1_最短回文串.py]) dp[0][j] = 'inf' dp[i][0] = 'inf' dp[0][0] = 0 res = max(dp[-1_最短回文串.py]) 空间 O(m^2) 时间 O(m)",
"name": "min... | 2 | stack_v2_sparse_classes_30k_train_003647 | Implement the Python class `Soluton` described below.
Class description:
Implement the Soluton class.
Method signatures and docstrings:
- def minimumTotal(self, triangle: list) -> int: dp dp[i][j] 从triangle[0][0] 到 triangle[i][j] 最小路径 dp[i][j] = min(dp[i-1_最短回文串.py][j] + tri[i-1_最短回文串.py][j-1_最短回文串.py], dp[i-1_最短回文串.... | Implement the Python class `Soluton` described below.
Class description:
Implement the Soluton class.
Method signatures and docstrings:
- def minimumTotal(self, triangle: list) -> int: dp dp[i][j] 从triangle[0][0] 到 triangle[i][j] 最小路径 dp[i][j] = min(dp[i-1_最短回文串.py][j] + tri[i-1_最短回文串.py][j-1_最短回文串.py], dp[i-1_最短回文串.... | 57f303aa6e76f7c5292fa60bffdfddcb4ff9ddfb | <|skeleton|>
class Soluton:
def minimumTotal(self, triangle: list) -> int:
"""dp dp[i][j] 从triangle[0][0] 到 triangle[i][j] 最小路径 dp[i][j] = min(dp[i-1_最短回文串.py][j] + tri[i-1_最短回文串.py][j-1_最短回文串.py], dp[i-1_最短回文串.py][j-1_最短回文串.py] + tri[i-1_最短回文串.py][j-1_最短回文串.py]) dp[0][j] = 'inf' dp[i][0] = 'inf' dp[0][0] ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Soluton:
def minimumTotal(self, triangle: list) -> int:
"""dp dp[i][j] 从triangle[0][0] 到 triangle[i][j] 最小路径 dp[i][j] = min(dp[i-1_最短回文串.py][j] + tri[i-1_最短回文串.py][j-1_最短回文串.py], dp[i-1_最短回文串.py][j-1_最短回文串.py] + tri[i-1_最短回文串.py][j-1_最短回文串.py]) dp[0][j] = 'inf' dp[i][0] = 'inf' dp[0][0] = 0 res = max(... | the_stack_v2_python_sparse | 4_LEETCODE/2_DP/网格问题/120._三角形最小路径和.py | fzingithub/SwordRefers2Offer | train | 1 | |
55985167491ac63bb4049ec33e7dbf677eb205fb | [
"if not isinstance(value, list):\n raise XRPLBinaryCodecException(f'Invalid type to construct a Path: expected list, received {value.__class__.__name__}.')\nbuffer: bytes = b''\nfor PathStep_dict in value:\n pathstep = PathStep.from_value(PathStep_dict)\n buffer += bytes(pathstep)\nreturn Path(buffer)",
... | <|body_start_0|>
if not isinstance(value, list):
raise XRPLBinaryCodecException(f'Invalid type to construct a Path: expected list, received {value.__class__.__name__}.')
buffer: bytes = b''
for PathStep_dict in value:
pathstep = PathStep.from_value(PathStep_dict)
... | Class for serializing/deserializing Paths. | Path | [
"ISC",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Path:
"""Class for serializing/deserializing Paths."""
def from_value(cls: Type[Path], value: List[Dict[str, str]]) -> Path:
"""Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to construct a Path object from. Returns: The Path constructed f... | stack_v2_sparse_classes_75kplus_train_065024 | 9,067 | permissive | [
{
"docstring": "Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to construct a Path object from. Returns: The Path constructed from value. Raises: XRPLBinaryCodecException: If the supplied value is of the wrong type.",
"name": "from_value",
"signature": "def f... | 3 | stack_v2_sparse_classes_30k_train_025605 | Implement the Python class `Path` described below.
Class description:
Class for serializing/deserializing Paths.
Method signatures and docstrings:
- def from_value(cls: Type[Path], value: List[Dict[str, str]]) -> Path: Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to cons... | Implement the Python class `Path` described below.
Class description:
Class for serializing/deserializing Paths.
Method signatures and docstrings:
- def from_value(cls: Type[Path], value: List[Dict[str, str]]) -> Path: Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to cons... | e5bbdf458ad83e6670a4ebf3df63e17fed8b099f | <|skeleton|>
class Path:
"""Class for serializing/deserializing Paths."""
def from_value(cls: Type[Path], value: List[Dict[str, str]]) -> Path:
"""Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to construct a Path object from. Returns: The Path constructed f... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Path:
"""Class for serializing/deserializing Paths."""
def from_value(cls: Type[Path], value: List[Dict[str, str]]) -> Path:
"""Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to construct a Path object from. Returns: The Path constructed from value. Ra... | the_stack_v2_python_sparse | xrpl/core/binarycodec/types/path_set.py | yyolk/xrpl-py | train | 1 |
3c26419e5d29474b3dff3181b455a9518d5c97ad | [
"storage = get_storage()\nauth0_id = get_auth0_id_of_user(email)\nuser_id = storage.read_user_id(auth0_id)\nreturn super().post(user_id, role_id)",
"storage = get_storage()\nauth0_id = get_auth0_id_of_user(email)\ntry:\n user_id = storage.read_user_id(auth0_id)\nexcept StorageAuthError:\n return ('', 204)\n... | <|body_start_0|>
storage = get_storage()
auth0_id = get_auth0_id_of_user(email)
user_id = storage.read_user_id(auth0_id)
return super().post(user_id, role_id)
<|end_body_0|>
<|body_start_1|>
storage = get_storage()
auth0_id = get_auth0_id_of_user(email)
try:
... | UserRolesManagementByEmailView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRolesManagementByEmailView:
def post(self, email, role_id):
"""--- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Roles responses: 204: description: Role Added Successfully. 401: $ref: '#/components/responses/401-Unauthorized' 404: $ref... | stack_v2_sparse_classes_75kplus_train_065025 | 12,608 | permissive | [
{
"docstring": "--- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Roles responses: 204: description: Role Added Successfully. 401: $ref: '#/components/responses/401-Unauthorized' 404: $ref: '#/components/responses/404-NotFound'",
"name": "post",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_029085 | Implement the Python class `UserRolesManagementByEmailView` described below.
Class description:
Implement the UserRolesManagementByEmailView class.
Method signatures and docstrings:
- def post(self, email, role_id): --- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Rol... | Implement the Python class `UserRolesManagementByEmailView` described below.
Class description:
Implement the UserRolesManagementByEmailView class.
Method signatures and docstrings:
- def post(self, email, role_id): --- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Rol... | 280800c73eb7cfd49029462b352887e78f1ff91b | <|skeleton|>
class UserRolesManagementByEmailView:
def post(self, email, role_id):
"""--- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Roles responses: 204: description: Role Added Successfully. 401: $ref: '#/components/responses/401-Unauthorized' 404: $ref... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserRolesManagementByEmailView:
def post(self, email, role_id):
"""--- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Roles responses: 204: description: Role Added Successfully. 401: $ref: '#/components/responses/401-Unauthorized' 404: $ref: '#/component... | the_stack_v2_python_sparse | sfa_api/users.py | SolarArbiter/solarforecastarbiter-api | train | 9 | |
58ac35541d30e1e96a6a242ea29e29c3f8cba894 | [
"super().__init__()\nassert len(transforms_list) > 0, 'Argument transforms_list cannot be empty.'\nassert num_sample_op > 0, 'Need to sample at least one transform.'\nassert num_sample_op <= len(transforms_list), 'Argument num_sample_op cannot be greater than number of available transforms.'\nif transforms_prob is ... | <|body_start_0|>
super().__init__()
assert len(transforms_list) > 0, 'Argument transforms_list cannot be empty.'
assert num_sample_op > 0, 'Need to sample at least one transform.'
assert num_sample_op <= len(transforms_list), 'Argument num_sample_op cannot be greater than number of avail... | Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input. | OpSampler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpSampler:
"""Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input."""
def __init__(self, transforms_list: List[Callable], transforms_prob: Optional[List[float]]=None, num_sample_op: int=1, rando... | stack_v2_sparse_classes_75kplus_train_065026 | 10,994 | permissive | [
{
"docstring": "Args: transforms_list (List[Callable]): A list of tuples of all available transforms to sample from. transforms_prob (Optional[List[float]]): The probabilities associated with each transform in transforms_list. If not provided, the sampler assumes a uniform distribution over all transforms. They... | 2 | stack_v2_sparse_classes_30k_train_033148 | Implement the Python class `OpSampler` described below.
Class description:
Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input.
Method signatures and docstrings:
- def __init__(self, transforms_list: List[Callable], tran... | Implement the Python class `OpSampler` described below.
Class description:
Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input.
Method signatures and docstrings:
- def __init__(self, transforms_list: List[Callable], tran... | 16f2abf2f8aa174915316007622bbb260215dee8 | <|skeleton|>
class OpSampler:
"""Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input."""
def __init__(self, transforms_list: List[Callable], transforms_prob: Optional[List[float]]=None, num_sample_op: int=1, rando... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OpSampler:
"""Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input."""
def __init__(self, transforms_list: List[Callable], transforms_prob: Optional[List[float]]=None, num_sample_op: int=1, randomly_sample_de... | the_stack_v2_python_sparse | pytorchvideo/transforms/transforms.py | xchani/pytorchvideo | train | 0 |
2d697450b617fd6843744cacf27a082f64bdceed | [
"def buildChildTree(preIndex, inIndex, length):\n if length == 0:\n return None\n root = TreeNode(preorder[preIndex])\n count = 0\n while inorder[inIndex + count] != preorder[preIndex]:\n count += 1\n root.left = buildChildTree(preIndex + 1, inIndex, count)\n root.right = buildChildT... | <|body_start_0|>
def buildChildTree(preIndex, inIndex, length):
if length == 0:
return None
root = TreeNode(preorder[preIndex])
count = 0
while inorder[inIndex + count] != preorder[preIndex]:
count += 1
root.left = build... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def buildTree(self, preorder, inorder):
""":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
<|body_0|>
def buildTree2(self, preorder, inorder):
""":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
<|body_1|... | stack_v2_sparse_classes_75kplus_train_065027 | 1,314 | permissive | [
{
"docstring": ":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode",
"name": "buildTree",
"signature": "def buildTree(self, preorder, inorder)"
},
{
"docstring": ":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode",
"name": "buildTree2",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_train_054573 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, preorder, inorder): :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode
- def buildTree2(self, preorder, inorder): :type preorder: List[int] :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, preorder, inorder): :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode
- def buildTree2(self, preorder, inorder): :type preorder: List[int] :... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|skeleton|>
class Solution:
def buildTree(self, preorder, inorder):
""":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
<|body_0|>
def buildTree2(self, preorder, inorder):
""":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
<|body_1|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def buildTree(self, preorder, inorder):
""":type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
def buildChildTree(preIndex, inIndex, length):
if length == 0:
return None
root = TreeNode(preorder[preIndex])
count =... | the_stack_v2_python_sparse | 101-200/101-110/105-binaryTreeFromPreInOrder/binaryTreeFromPreInOrder.py | xuychen/Leetcode | train | 0 | |
677988a15d69f2bb63e8f51085cdde6de1ec7860 | [
"start = timezone.now()\ntest_case = rfactories.TestCaseF.create()\nrfactories.TestCaseStepF.create(testcase=test_case)\nrfactories.TestCaseStepF.create(testcase=test_case)\ntest_case.run(test_case.testrun)\nself.assertEqual(2, rmodels.TestCaseStep.run.call_count)\nself.assertObjectUpdated(test_case, start_date__gt... | <|body_start_0|>
start = timezone.now()
test_case = rfactories.TestCaseF.create()
rfactories.TestCaseStepF.create(testcase=test_case)
rfactories.TestCaseStepF.create(testcase=test_case)
test_case.run(test_case.testrun)
self.assertEqual(2, rmodels.TestCaseStep.run.call_cou... | TestCaseModelTestCase | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCaseModelTestCase:
def test_run_runs_all_test_steps(self):
"""Test case should run all TestCaseSteps and mark self as success."""
<|body_0|>
def test_run_without_test_steps(self):
"""Test case should be runnable without TestCaseSteps (and should be success)."""
... | stack_v2_sparse_classes_75kplus_train_065028 | 27,107 | permissive | [
{
"docstring": "Test case should run all TestCaseSteps and mark self as success.",
"name": "test_run_runs_all_test_steps",
"signature": "def test_run_runs_all_test_steps(self)"
},
{
"docstring": "Test case should be runnable without TestCaseSteps (and should be success).",
"name": "test_run_... | 4 | stack_v2_sparse_classes_30k_train_001615 | Implement the Python class `TestCaseModelTestCase` described below.
Class description:
Implement the TestCaseModelTestCase class.
Method signatures and docstrings:
- def test_run_runs_all_test_steps(self): Test case should run all TestCaseSteps and mark self as success.
- def test_run_without_test_steps(self): Test c... | Implement the Python class `TestCaseModelTestCase` described below.
Class description:
Implement the TestCaseModelTestCase class.
Method signatures and docstrings:
- def test_run_runs_all_test_steps(self): Test case should run all TestCaseSteps and mark self as success.
- def test_run_without_test_steps(self): Test c... | 57f5e7d16185d91a06fc3ad9ecd26fbef1c0a84d | <|skeleton|>
class TestCaseModelTestCase:
def test_run_runs_all_test_steps(self):
"""Test case should run all TestCaseSteps and mark self as success."""
<|body_0|>
def test_run_without_test_steps(self):
"""Test case should be runnable without TestCaseSteps (and should be success)."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestCaseModelTestCase:
def test_run_runs_all_test_steps(self):
"""Test case should run all TestCaseSteps and mark self as success."""
start = timezone.now()
test_case = rfactories.TestCaseF.create()
rfactories.TestCaseStepF.create(testcase=test_case)
rfactories.TestCase... | the_stack_v2_python_sparse | fortuitus/frunner/tests.py | elegion/djangodash2012 | train | 0 | |
46f3766c8d9dfc196e8bc12f4beda75ccde47c95 | [
"if not root:\n return 'null'\nmessage = []\n\ndef build_message(root):\n if root is None:\n message.append('null')\n else:\n message.append(str(root.val))\n build_message(root.left)\n build_message(root.right)\nbuild_message(root)\nreturn ','.join(message)",
"queue = collecti... | <|body_start_0|>
if not root:
return 'null'
message = []
def build_message(root):
if root is None:
message.append('null')
else:
message.append(str(root.val))
build_message(root.left)
build_messag... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
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_065029 | 1,635 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_031047 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 9d0ff0f8705451947a6605ab5ef92bb3e27a7147 | <|skeleton|>
class Codec:
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 Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return 'null'
message = []
def build_message(root):
if root is None:
message.append('null')
else:
... | the_stack_v2_python_sparse | premium/amazon/design/serialize_and_deserialize_bst.py | rayt579/leetcode | train | 0 | |
43879ca3aef1ae28c37716e2c2f4fd66486cf481 | [
"\"\"\"找出所有的pair, 如果符合条件，计数器加1 O(n^2)\"\"\"\ncount = 0\nfor i in range(len(nums)):\n for j in range(i + 1, len(nums)):\n if abs(nums[i] - nums[j]) == k:\n count += 1\nreturn count",
"\"\"\"\n 思路：如果k不等于零的话，那就是nums和nums数组每个数加k集合的交，如果k等于零的话，那就统计数组中相同的数字即可\n 区分开k=0的情况\n \... | <|body_start_0|>
"""找出所有的pair, 如果符合条件，计数器加1 O(n^2)"""
count = 0
for i in range(len(nums)):
for j in range(i + 1, len(nums)):
if abs(nums[i] - nums[j]) == k:
count += 1
return count
<|end_body_0|>
<|body_start_1|>
"""
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findPairs_simple(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def findPairs_map(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
def findPairs_pointer(self, nums, k):
... | stack_v2_sparse_classes_75kplus_train_065030 | 2,289 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "findPairs_simple",
"signature": "def findPairs_simple(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "findPairs_map",
"signature": "def findPairs_map(self, nums, k)"
}... | 3 | stack_v2_sparse_classes_30k_train_006789 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPairs_simple(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def findPairs_map(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def findP... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPairs_simple(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def findPairs_map(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def findP... | a0f270c1adce25be11df92877813037f2e73e28b | <|skeleton|>
class Solution:
def findPairs_simple(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def findPairs_map(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
def findPairs_pointer(self, nums, k):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findPairs_simple(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
"""找出所有的pair, 如果符合条件，计数器加1 O(n^2)"""
count = 0
for i in range(len(nums)):
for j in range(i + 1, len(nums)):
if abs(nums[i] - nums[j]) == k:
... | the_stack_v2_python_sparse | leetcode/532_k_diff_pairs_in_an_array.py | lvraikkonen/GoodCode | train | 0 | |
33edaf0aab6fb21a88a46bc8dd88fc8ae98f76c9 | [
"c = Company(name='PCT')\np = annualTimePeriod(1, start_period='2012')\nc.set_current_period(p)\nc.capital_program.generate_expenditures()\nself.assertEqual(c.capital_program.expenditures.cost_of_sales, 1000)\nself.assertEqual(c.capital_program.expenditures.interest, 1000)",
"c = Company(name='PCT')\np = annualTi... | <|body_start_0|>
c = Company(name='PCT')
p = annualTimePeriod(1, start_period='2012')
c.set_current_period(p)
c.capital_program.generate_expenditures()
self.assertEqual(c.capital_program.expenditures.cost_of_sales, 1000)
self.assertEqual(c.capital_program.expenditures.int... | Tests for determining if the Company correctly calculates the period expenditures for projects | ProjectExpendituresTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectExpendituresTests:
"""Tests for determining if the Company correctly calculates the period expenditures for projects"""
def testSingleCapitalProjectExpenditures(self):
"""For a single capital project, the Company should correctly calculate the expenditures for the current peri... | stack_v2_sparse_classes_75kplus_train_065031 | 12,467 | no_license | [
{
"docstring": "For a single capital project, the Company should correctly calculate the expenditures for the current period",
"name": "testSingleCapitalProjectExpenditures",
"signature": "def testSingleCapitalProjectExpenditures(self)"
},
{
"docstring": "For a given list of capital projects, th... | 5 | stack_v2_sparse_classes_30k_train_013388 | Implement the Python class `ProjectExpendituresTests` described below.
Class description:
Tests for determining if the Company correctly calculates the period expenditures for projects
Method signatures and docstrings:
- def testSingleCapitalProjectExpenditures(self): For a single capital project, the Company should ... | Implement the Python class `ProjectExpendituresTests` described below.
Class description:
Tests for determining if the Company correctly calculates the period expenditures for projects
Method signatures and docstrings:
- def testSingleCapitalProjectExpenditures(self): For a single capital project, the Company should ... | 5a49c7c9885f453828b5e43cd27564e3f4c95b23 | <|skeleton|>
class ProjectExpendituresTests:
"""Tests for determining if the Company correctly calculates the period expenditures for projects"""
def testSingleCapitalProjectExpenditures(self):
"""For a single capital project, the Company should correctly calculate the expenditures for the current peri... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProjectExpendituresTests:
"""Tests for determining if the Company correctly calculates the period expenditures for projects"""
def testSingleCapitalProjectExpenditures(self):
"""For a single capital project, the Company should correctly calculate the expenditures for the current period"""
... | the_stack_v2_python_sparse | company_test.py | SundropFuels/project-finance | train | 0 |
14bf3295d4b8eb60dfc5643d85db80b743727066 | [
"stats = kwargs['stats']\nif day == 0 or not stats:\n return '<td class=\"noday\"> </td>'\nstat = next((stat for stat in stats if stat.date == dt.date(kwargs['theyear'], kwargs['themonth'], day)), None)\nif not stat:\n return '<td class=\"noday\"> </td>'\nparams = dict(defaults.units, **stat.dict)\n... | <|body_start_0|>
stats = kwargs['stats']
if day == 0 or not stats:
return '<td class="noday"> </td>'
stat = next((stat for stat in stats if stat.date == dt.date(kwargs['theyear'], kwargs['themonth'], day)), None)
if not stat:
return '<td class="noday"> <... | Генератор html-календаря с погодой | CalendarMaker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalendarMaker:
"""Генератор html-календаря с погодой"""
def formatday(self, day, weekday, **kwargs):
"""Возвращает HTML код ячейки календаря :param day: день месяца :param weekday: день недели :param kwargs: в кваргах передаётся stats - список объектов класса Stats :return: str Html ... | stack_v2_sparse_classes_75kplus_train_065032 | 11,050 | no_license | [
{
"docstring": "Возвращает HTML код ячейки календаря :param day: день месяца :param weekday: день недели :param kwargs: в кваргах передаётся stats - список объектов класса Stats :return: str Html код ячейки календаря с прогнозом",
"name": "formatday",
"signature": "def formatday(self, day, weekday, **kw... | 5 | stack_v2_sparse_classes_30k_train_016200 | Implement the Python class `CalendarMaker` described below.
Class description:
Генератор html-календаря с погодой
Method signatures and docstrings:
- def formatday(self, day, weekday, **kwargs): Возвращает HTML код ячейки календаря :param day: день месяца :param weekday: день недели :param kwargs: в кваргах передаётс... | Implement the Python class `CalendarMaker` described below.
Class description:
Генератор html-календаря с погодой
Method signatures and docstrings:
- def formatday(self, day, weekday, **kwargs): Возвращает HTML код ячейки календаря :param day: день месяца :param weekday: день недели :param kwargs: в кваргах передаётс... | d2c0014dffccadb8232a1034e4ea9b427016a1d1 | <|skeleton|>
class CalendarMaker:
"""Генератор html-календаря с погодой"""
def formatday(self, day, weekday, **kwargs):
"""Возвращает HTML код ячейки календаря :param day: день месяца :param weekday: день недели :param kwargs: в кваргах передаётся stats - список объектов класса Stats :return: str Html ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CalendarMaker:
"""Генератор html-календаря с погодой"""
def formatday(self, day, weekday, **kwargs):
"""Возвращает HTML код ячейки календаря :param day: день месяца :param weekday: день недели :param kwargs: в кваргах передаётся stats - список объектов класса Stats :return: str Html код ячейки ка... | the_stack_v2_python_sparse | lesson_016/engine/image_maker.py | glotyuids/skillbox_learning | train | 0 |
606fe49355ebb3a7d8390a051094369338d7ae8e | [
"metadata_status = Status('Extracted submission metadata.', 'Extracting submission metadata.', 'white')\nmetadata_status.start()\nskeleton = {'scrape_settings': {'n_results': int(limit) if int(limit) > 0 else 'all', 'style': 'structured' if not args.raw else 'raw', 'url': url}, 'data': {'submission_metadata': {'aut... | <|body_start_0|>
metadata_status = Status('Extracted submission metadata.', 'Extracting submission metadata.', 'white')
metadata_status.start()
skeleton = {'scrape_settings': {'n_results': int(limit) if int(limit) > 0 else 'all', 'style': 'structured' if not args.raw else 'raw', 'url': url}, 'da... | Methods for writing scraped comments to CSV or JSON. | Write | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Write:
"""Methods for writing scraped comments to CSV or JSON."""
def _make_json_skeleton(args, limit, submission, url):
"""Create a skeleton for JSON export. Include scrape details at the top. Parameters ---------- args: Namespace Namespace object containing all arguments that were ... | stack_v2_sparse_classes_75kplus_train_065033 | 14,112 | permissive | [
{
"docstring": "Create a skeleton for JSON export. Include scrape details at the top. Parameters ---------- args: Namespace Namespace object containing all arguments that were defined in the CLI limit: str Integer of string type denoting n_results or RAW format submission: PRAW submission object url: str String... | 3 | stack_v2_sparse_classes_30k_train_006348 | Implement the Python class `Write` described below.
Class description:
Methods for writing scraped comments to CSV or JSON.
Method signatures and docstrings:
- def _make_json_skeleton(args, limit, submission, url): Create a skeleton for JSON export. Include scrape details at the top. Parameters ---------- args: Names... | Implement the Python class `Write` described below.
Class description:
Methods for writing scraped comments to CSV or JSON.
Method signatures and docstrings:
- def _make_json_skeleton(args, limit, submission, url): Create a skeleton for JSON export. Include scrape details at the top. Parameters ---------- args: Names... | 9f8cf3a3adb9aa5079dfc7bfd7832b53358ee40f | <|skeleton|>
class Write:
"""Methods for writing scraped comments to CSV or JSON."""
def _make_json_skeleton(args, limit, submission, url):
"""Create a skeleton for JSON export. Include scrape details at the top. Parameters ---------- args: Namespace Namespace object containing all arguments that were ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Write:
"""Methods for writing scraped comments to CSV or JSON."""
def _make_json_skeleton(args, limit, submission, url):
"""Create a skeleton for JSON export. Include scrape details at the top. Parameters ---------- args: Namespace Namespace object containing all arguments that were defined in th... | the_stack_v2_python_sparse | urs/praw_scrapers/static_scrapers/Comments.py | shilezi/URS | train | 0 |
0396aee9be9fb2f95172367c6f72288641864231 | [
"self.main_bin = Queue()\nfor num in num_list:\n self.main_bin.enqueue(num)\nself.bin_0 = Queue()\nself.bin_1 = Queue()\nself.bin_2 = Queue()\nself.bin_3 = Queue()\nself.bin_4 = Queue()\nself.bin_5 = Queue()\nself.bin_6 = Queue()\nself.bin_7 = Queue()\nself.bin_8 = Queue()\nself.bin_9 = Queue()",
"while self.m... | <|body_start_0|>
self.main_bin = Queue()
for num in num_list:
self.main_bin.enqueue(num)
self.bin_0 = Queue()
self.bin_1 = Queue()
self.bin_2 = Queue()
self.bin_3 = Queue()
self.bin_4 = Queue()
self.bin_5 = Queue()
self.bin_6 = Queue()
... | RadixSort | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RadixSort:
def __init__(self, num_list):
"""Sort a number list using a radix sort, takes a list of ints and sorts them from smallest to largest. Will not work if numbers are larger than 3 digits. :param num_list: :return:"""
<|body_0|>
def radix_sort(self):
"""Combin... | stack_v2_sparse_classes_75kplus_train_065034 | 4,261 | no_license | [
{
"docstring": "Sort a number list using a radix sort, takes a list of ints and sorts them from smallest to largest. Will not work if numbers are larger than 3 digits. :param num_list: :return:",
"name": "__init__",
"signature": "def __init__(self, num_list)"
},
{
"docstring": "Combines the Radi... | 4 | stack_v2_sparse_classes_30k_train_034067 | Implement the Python class `RadixSort` described below.
Class description:
Implement the RadixSort class.
Method signatures and docstrings:
- def __init__(self, num_list): Sort a number list using a radix sort, takes a list of ints and sorts them from smallest to largest. Will not work if numbers are larger than 3 di... | Implement the Python class `RadixSort` described below.
Class description:
Implement the RadixSort class.
Method signatures and docstrings:
- def __init__(self, num_list): Sort a number list using a radix sort, takes a list of ints and sorts them from smallest to largest. Will not work if numbers are larger than 3 di... | b36aa897a83a21560a5e80674dd10f5a00d97fa4 | <|skeleton|>
class RadixSort:
def __init__(self, num_list):
"""Sort a number list using a radix sort, takes a list of ints and sorts them from smallest to largest. Will not work if numbers are larger than 3 digits. :param num_list: :return:"""
<|body_0|>
def radix_sort(self):
"""Combin... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RadixSort:
def __init__(self, num_list):
"""Sort a number list using a radix sort, takes a list of ints and sorts them from smallest to largest. Will not work if numbers are larger than 3 digits. :param num_list: :return:"""
self.main_bin = Queue()
for num in num_list:
self... | the_stack_v2_python_sparse | DataStructure/week 4/radix_speed.py | Himanshudhir50/Himanshudhir50.github.io | train | 0 | |
0102b4a85f0076319eaef6bd0a742fb0d22167ff | [
"dev = qml.device('default.qubit', wires=3)\nparams = [1.0, 1.0, 1.0]\nwith JacobianTape() as tape:\n qml.RX(params[0], wires=[0])\n qml.RY(params[1], wires=[1])\n qml.RZ(params[2], wires=[2])\n qml.CNOT(wires=[0, 1])\n qml.probs(wires=0)\n qml.probs(wires=[1, 2])\nres = tape.jacobian(dev)\nassert... | <|body_start_0|>
dev = qml.device('default.qubit', wires=3)
params = [1.0, 1.0, 1.0]
with JacobianTape() as tape:
qml.RX(params[0], wires=[0])
qml.RY(params[1], wires=[1])
qml.RZ(params[2], wires=[2])
qml.CNOT(wires=[0, 1])
qml.probs(wi... | Integration tests for the Jacobian method | TestJacobianIntegration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestJacobianIntegration:
"""Integration tests for the Jacobian method"""
def test_ragged_output(self):
"""Test that the Jacobian is correctly returned for a tape with ragged output"""
<|body_0|>
def test_single_expectation_value(self, tol):
"""Tests correct outpu... | stack_v2_sparse_classes_75kplus_train_065035 | 25,459 | permissive | [
{
"docstring": "Test that the Jacobian is correctly returned for a tape with ragged output",
"name": "test_ragged_output",
"signature": "def test_ragged_output(self)"
},
{
"docstring": "Tests correct output shape and evaluation for a tape with a single expval output",
"name": "test_single_ex... | 5 | stack_v2_sparse_classes_30k_train_007932 | Implement the Python class `TestJacobianIntegration` described below.
Class description:
Integration tests for the Jacobian method
Method signatures and docstrings:
- def test_ragged_output(self): Test that the Jacobian is correctly returned for a tape with ragged output
- def test_single_expectation_value(self, tol)... | Implement the Python class `TestJacobianIntegration` described below.
Class description:
Integration tests for the Jacobian method
Method signatures and docstrings:
- def test_ragged_output(self): Test that the Jacobian is correctly returned for a tape with ragged output
- def test_single_expectation_value(self, tol)... | 0c1c805fd5dfce465a8955ee3faf81037023a23e | <|skeleton|>
class TestJacobianIntegration:
"""Integration tests for the Jacobian method"""
def test_ragged_output(self):
"""Test that the Jacobian is correctly returned for a tape with ragged output"""
<|body_0|>
def test_single_expectation_value(self, tol):
"""Tests correct outpu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestJacobianIntegration:
"""Integration tests for the Jacobian method"""
def test_ragged_output(self):
"""Test that the Jacobian is correctly returned for a tape with ragged output"""
dev = qml.device('default.qubit', wires=3)
params = [1.0, 1.0, 1.0]
with JacobianTape() a... | the_stack_v2_python_sparse | artifacts/old_dataset_versions/original_commits_backup/pennylane/pennylane#1349/after/test_jacobian_tape.py | MattePalte/Bugs-Quantum-Computing-Platforms | train | 4 |
90aa90e677a5de86568e842f6e8e083faeac00c4 | [
"avatar = self.cleaned_data.get('avatar', None)\nif avatar is not None:\n avatar_size = len(avatar) * 3 / 4 - avatar.count('=', -2)\n if avatar_size > settings.MAX_FILE_SIZES['avatar']:\n raise forms.ValidationError(_('Image file too large'))\nreturn avatar",
"user = info.context.user\ntouched = Fals... | <|body_start_0|>
avatar = self.cleaned_data.get('avatar', None)
if avatar is not None:
avatar_size = len(avatar) * 3 / 4 - avatar.count('=', -2)
if avatar_size > settings.MAX_FILE_SIZES['avatar']:
raise forms.ValidationError(_('Image file too large'))
retu... | For used by profile settings mutation. | ProfileSettingsForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfileSettingsForm:
"""For used by profile settings mutation."""
def clean_avatar(self) -> str:
"""Add some custom validation to our avatar field"""
<|body_0|>
def save(self, info, commit: bool=True) -> User:
"""Saves the changes made to the database (if any)"""... | stack_v2_sparse_classes_75kplus_train_065036 | 10,299 | no_license | [
{
"docstring": "Add some custom validation to our avatar field",
"name": "clean_avatar",
"signature": "def clean_avatar(self) -> str"
},
{
"docstring": "Saves the changes made to the database (if any)",
"name": "save",
"signature": "def save(self, info, commit: bool=True) -> User"
}
] | 2 | stack_v2_sparse_classes_30k_val_002901 | Implement the Python class `ProfileSettingsForm` described below.
Class description:
For used by profile settings mutation.
Method signatures and docstrings:
- def clean_avatar(self) -> str: Add some custom validation to our avatar field
- def save(self, info, commit: bool=True) -> User: Saves the changes made to the... | Implement the Python class `ProfileSettingsForm` described below.
Class description:
For used by profile settings mutation.
Method signatures and docstrings:
- def clean_avatar(self) -> str: Add some custom validation to our avatar field
- def save(self, info, commit: bool=True) -> User: Saves the changes made to the... | fe24d0bd08952647d27940a336bd0504af1bae0c | <|skeleton|>
class ProfileSettingsForm:
"""For used by profile settings mutation."""
def clean_avatar(self) -> str:
"""Add some custom validation to our avatar field"""
<|body_0|>
def save(self, info, commit: bool=True) -> User:
"""Saves the changes made to the database (if any)"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProfileSettingsForm:
"""For used by profile settings mutation."""
def clean_avatar(self) -> str:
"""Add some custom validation to our avatar field"""
avatar = self.cleaned_data.get('avatar', None)
if avatar is not None:
avatar_size = len(avatar) * 3 / 4 - avatar.count(... | the_stack_v2_python_sparse | accounts/graphql/mutations.py | ApyMajul/Zola-Backend | train | 0 |
5d8454bfa5f13c22b42d77e0a410eb3b9bcbe75a | [
"self.log = LogHandler(logger=logger)\ntry:\n self._wavemeterdll = ctypes.windll.LoadLibrary('wlmData.dll')\nexcept:\n msg_str = 'High-Finesse WS7 Wavemeter is not properly installed on this computer'\n self.log.error(msg_str)\n raise WavemeterError(msg_str)\nself._wavemeterdll.GetWLMVersion.restype = c... | <|body_start_0|>
self.log = LogHandler(logger=logger)
try:
self._wavemeterdll = ctypes.windll.LoadLibrary('wlmData.dll')
except:
msg_str = 'High-Finesse WS7 Wavemeter is not properly installed on this computer'
self.log.error(msg_str)
raise Wavemet... | Hardware class to control High Finesse Wavemeter. | Driver | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Driver:
"""Hardware class to control High Finesse Wavemeter."""
def __init__(self, logger=None):
"""Instantiate wavemeter :param logger: instance of LogClient class (optional)"""
<|body_0|>
def get_wavelength(self, channel=1, units='Frequency (THz)'):
"""Returns ... | stack_v2_sparse_classes_75kplus_train_065037 | 2,446 | permissive | [
{
"docstring": "Instantiate wavemeter :param logger: instance of LogClient class (optional)",
"name": "__init__",
"signature": "def __init__(self, logger=None)"
},
{
"docstring": "Returns the wavelength in specified units for a given channel :param channel: Channel number from 1-8 :param units: ... | 2 | stack_v2_sparse_classes_30k_train_039570 | Implement the Python class `Driver` described below.
Class description:
Hardware class to control High Finesse Wavemeter.
Method signatures and docstrings:
- def __init__(self, logger=None): Instantiate wavemeter :param logger: instance of LogClient class (optional)
- def get_wavelength(self, channel=1, units='Freque... | Implement the Python class `Driver` described below.
Class description:
Hardware class to control High Finesse Wavemeter.
Method signatures and docstrings:
- def __init__(self, logger=None): Instantiate wavemeter :param logger: instance of LogClient class (optional)
- def get_wavelength(self, channel=1, units='Freque... | c8794a342d30119a6be93b2dd30ea61b5c946d8a | <|skeleton|>
class Driver:
"""Hardware class to control High Finesse Wavemeter."""
def __init__(self, logger=None):
"""Instantiate wavemeter :param logger: instance of LogClient class (optional)"""
<|body_0|>
def get_wavelength(self, channel=1, units='Frequency (THz)'):
"""Returns ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Driver:
"""Hardware class to control High Finesse Wavemeter."""
def __init__(self, logger=None):
"""Instantiate wavemeter :param logger: instance of LogClient class (optional)"""
self.log = LogHandler(logger=logger)
try:
self._wavemeterdll = ctypes.windll.LoadLibrary('... | the_stack_v2_python_sparse | pylabnet/hardware/wavemeter/high_finesse_ws7.py | lukingroup/pylabnet | train | 15 |
2e84eef0e9d645b22303d95301b8a63f355bc663 | [
"res = super(account_voucher, self).proforma_voucher()\ncommission_payment_rcs = self.env['commission.payment'].search([('payment_id', '=', self.id)])\nif commission_payment_rcs:\n commission_payment_rcs.wkf_done()\nreturn res",
"res = super(account_voucher, self).cancel_voucher()\ncm_obj = self.env['commissio... | <|body_start_0|>
res = super(account_voucher, self).proforma_voucher()
commission_payment_rcs = self.env['commission.payment'].search([('payment_id', '=', self.id)])
if commission_payment_rcs:
commission_payment_rcs.wkf_done()
return res
<|end_body_0|>
<|body_start_1|>
... | account_voucher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class account_voucher:
def proforma_voucher(self):
"""Surcharge pour lier l'écriture comptable du paiement à la commission"""
<|body_0|>
def cancel_voucher(self):
"""Surchage de la fonction d'annulation du paiement Permet de remettre la commission à valider si elle est ter... | stack_v2_sparse_classes_75kplus_train_065038 | 6,577 | no_license | [
{
"docstring": "Surcharge pour lier l'écriture comptable du paiement à la commission",
"name": "proforma_voucher",
"signature": "def proforma_voucher(self)"
},
{
"docstring": "Surchage de la fonction d'annulation du paiement Permet de remettre la commission à valider si elle est terminée",
"... | 2 | stack_v2_sparse_classes_30k_train_010028 | Implement the Python class `account_voucher` described below.
Class description:
Implement the account_voucher class.
Method signatures and docstrings:
- def proforma_voucher(self): Surcharge pour lier l'écriture comptable du paiement à la commission
- def cancel_voucher(self): Surchage de la fonction d'annulation du... | Implement the Python class `account_voucher` described below.
Class description:
Implement the account_voucher class.
Method signatures and docstrings:
- def proforma_voucher(self): Surcharge pour lier l'écriture comptable du paiement à la commission
- def cancel_voucher(self): Surchage de la fonction d'annulation du... | eb394e1f79ba1995da2dcd81adfdd511c22caff9 | <|skeleton|>
class account_voucher:
def proforma_voucher(self):
"""Surcharge pour lier l'écriture comptable du paiement à la commission"""
<|body_0|>
def cancel_voucher(self):
"""Surchage de la fonction d'annulation du paiement Permet de remettre la commission à valider si elle est ter... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class account_voucher:
def proforma_voucher(self):
"""Surcharge pour lier l'écriture comptable du paiement à la commission"""
res = super(account_voucher, self).proforma_voucher()
commission_payment_rcs = self.env['commission.payment'].search([('payment_id', '=', self.id)])
if commis... | the_stack_v2_python_sparse | OpenPROD/openprod-addons/commission/account_invoice.py | kazacube-mziouadi/ceci | train | 0 | |
0bce7840dfef2323601c70fe40f26e8002036161 | [
"if week < 0:\n raise ValueError('Invalid week number')\nif second >= cls.SECONDS_PER_WEEK:\n raise ValueError('Bad second number')\nweekday, daysec = divmod(second + cls.GPS_LEAP_OFFSET, cls.SECONDS_PER_DAY)\ndaynum = week * cls.NUM_WEEKDAYS + weekday\ndays, seconds = xdatetime.TAIDaySecsToUTCDaySecs(daynum ... | <|body_start_0|>
if week < 0:
raise ValueError('Invalid week number')
if second >= cls.SECONDS_PER_WEEK:
raise ValueError('Bad second number')
weekday, daysec = divmod(second + cls.GPS_LEAP_OFFSET, cls.SECONDS_PER_DAY)
daynum = week * cls.NUM_WEEKDAYS + weekday
... | Date/time object. | datetime | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class datetime:
"""Date/time object."""
def from_gps_week_sec(cls, week, second=0, nanosecond=0):
"""Create new datetime object from GPS week, second and nanosecond."""
<|body_0|>
def gps_week_sec_nano(self, roundofs=0):
"""Get GPS week, second, and nanosecond from dat... | stack_v2_sparse_classes_75kplus_train_065039 | 3,139 | no_license | [
{
"docstring": "Create new datetime object from GPS week, second and nanosecond.",
"name": "from_gps_week_sec",
"signature": "def from_gps_week_sec(cls, week, second=0, nanosecond=0)"
},
{
"docstring": "Get GPS week, second, and nanosecond from datetime object.",
"name": "gps_week_sec_nano",... | 2 | stack_v2_sparse_classes_30k_train_000002 | Implement the Python class `datetime` described below.
Class description:
Date/time object.
Method signatures and docstrings:
- def from_gps_week_sec(cls, week, second=0, nanosecond=0): Create new datetime object from GPS week, second and nanosecond.
- def gps_week_sec_nano(self, roundofs=0): Get GPS week, second, an... | Implement the Python class `datetime` described below.
Class description:
Date/time object.
Method signatures and docstrings:
- def from_gps_week_sec(cls, week, second=0, nanosecond=0): Create new datetime object from GPS week, second and nanosecond.
- def gps_week_sec_nano(self, roundofs=0): Get GPS week, second, an... | 1a6471dfbd7ec27f3d9f42b49173d18761a8f5aa | <|skeleton|>
class datetime:
"""Date/time object."""
def from_gps_week_sec(cls, week, second=0, nanosecond=0):
"""Create new datetime object from GPS week, second and nanosecond."""
<|body_0|>
def gps_week_sec_nano(self, roundofs=0):
"""Get GPS week, second, and nanosecond from dat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class datetime:
"""Date/time object."""
def from_gps_week_sec(cls, week, second=0, nanosecond=0):
"""Create new datetime object from GPS week, second and nanosecond."""
if week < 0:
raise ValueError('Invalid week number')
if second >= cls.SECONDS_PER_WEEK:
raise ... | the_stack_v2_python_sparse | fwgnss/systems/xdatetime.py | fhgwright/fwgnss | train | 2 |
ae6d48bd9082c413d186669848a66600f5efa740 | [
"super(CriticModel, self).__init__()\nself.seed = torch.manual_seed(seed)\nself.fcs1 = nn.Linear(state_size, fc1_units)\nself.fc2 = nn.Linear(fc1_units + action_size, fc2_units)\nself.fc3 = nn.Linear(fc2_units, fc3_units)\nself.fc4 = nn.Linear(fc3_units, 1)",
"xs = F.leaky_relu(self.fcs1(state))\nx = torch.cat((x... | <|body_start_0|>
super(CriticModel, self).__init__()
self.seed = torch.manual_seed(seed)
self.fcs1 = nn.Linear(state_size, fc1_units)
self.fc2 = nn.Linear(fc1_units + action_size, fc2_units)
self.fc3 = nn.Linear(fc2_units, fc3_units)
self.fc4 = nn.Linear(fc3_units, 1)
<|e... | CriticModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CriticModel:
def __init__(self, state_size, action_size, seed, fc1_units=256, fc2_units=256, fc3_units=128):
"""estimate Q value"""
<|body_0|>
def forward(self, state, action):
"""Params: input: [state, action]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_75kplus_train_065040 | 2,012 | no_license | [
{
"docstring": "estimate Q value",
"name": "__init__",
"signature": "def __init__(self, state_size, action_size, seed, fc1_units=256, fc2_units=256, fc3_units=128)"
},
{
"docstring": "Params: input: [state, action]",
"name": "forward",
"signature": "def forward(self, state, action)"
}
... | 2 | null | Implement the Python class `CriticModel` described below.
Class description:
Implement the CriticModel class.
Method signatures and docstrings:
- def __init__(self, state_size, action_size, seed, fc1_units=256, fc2_units=256, fc3_units=128): estimate Q value
- def forward(self, state, action): Params: input: [state, ... | Implement the Python class `CriticModel` described below.
Class description:
Implement the CriticModel class.
Method signatures and docstrings:
- def __init__(self, state_size, action_size, seed, fc1_units=256, fc2_units=256, fc3_units=128): estimate Q value
- def forward(self, state, action): Params: input: [state, ... | df85d6b4a22b7904c45139a358a606b92406cd1f | <|skeleton|>
class CriticModel:
def __init__(self, state_size, action_size, seed, fc1_units=256, fc2_units=256, fc3_units=128):
"""estimate Q value"""
<|body_0|>
def forward(self, state, action):
"""Params: input: [state, action]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CriticModel:
def __init__(self, state_size, action_size, seed, fc1_units=256, fc2_units=256, fc3_units=128):
"""estimate Q value"""
super(CriticModel, self).__init__()
self.seed = torch.manual_seed(seed)
self.fcs1 = nn.Linear(state_size, fc1_units)
self.fc2 = nn.Linear(... | the_stack_v2_python_sparse | DDPG/model.py | jiemingChen/RL | train | 0 | |
519d8d428a05e407267b3acf7b29ef3992a0bb32 | [
"if matrix == [] or matrix[0] == []:\n return []\nrows = len(matrix)\ncolomns = len(matrix[0])\ntotal = rows * colomns\nvisitied = [[False] * colomns for _ in range(rows)]\nans = [0] * total\ndirections = [[0, 1], [1, 0], [0, -1], [-1, 0]]\ndirec_idx = 0\nrow, colomn = (0, 0)\nfor i in range(total):\n ans[i] ... | <|body_start_0|>
if matrix == [] or matrix[0] == []:
return []
rows = len(matrix)
colomns = len(matrix[0])
total = rows * colomns
visitied = [[False] * colomns for _ in range(rows)]
ans = [0] * total
directions = [[0, 1], [1, 0], [0, -1], [-1, 0]]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def spiralOrder(self, matrix):
"""方法一：模拟 可以模拟螺旋矩阵的路径。初始位置是矩阵的左上角，初始方向是向右，当路径超出界限或者进入之前访问过的位置时，则顺时针旋转，进入下一个方向。 判断路径是否进入之前访问过的位置需要使用一个与输入矩阵大小相同的辅助矩阵 visited extit{visited}visited，其中的每个元素表示该位置 是否被访问过。当一个元素被访问时，将 visited extit{visited}visited 中的对应位置的元素设为已访问。 如何判断路径是否结束？由于矩阵中的每个元素都被... | stack_v2_sparse_classes_75kplus_train_065041 | 5,333 | no_license | [
{
"docstring": "方法一：模拟 可以模拟螺旋矩阵的路径。初始位置是矩阵的左上角，初始方向是向右，当路径超出界限或者进入之前访问过的位置时，则顺时针旋转，进入下一个方向。 判断路径是否进入之前访问过的位置需要使用一个与输入矩阵大小相同的辅助矩阵 visited extit{visited}visited，其中的每个元素表示该位置 是否被访问过。当一个元素被访问时，将 visited extit{visited}visited 中的对应位置的元素设为已访问。 如何判断路径是否结束？由于矩阵中的每个元素都被访问一次，因此路径的长度即为矩阵中的元素数量，当路径的长度达到矩阵中的元素数量时即为完整路 径，将该路径... | 2 | stack_v2_sparse_classes_30k_train_007517 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def spiralOrder(self, matrix): 方法一：模拟 可以模拟螺旋矩阵的路径。初始位置是矩阵的左上角，初始方向是向右，当路径超出界限或者进入之前访问过的位置时，则顺时针旋转，进入下一个方向。 判断路径是否进入之前访问过的位置需要使用一个与输入矩阵大小相同的辅助矩阵 visited extit{visited}visited，其中的每... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def spiralOrder(self, matrix): 方法一：模拟 可以模拟螺旋矩阵的路径。初始位置是矩阵的左上角，初始方向是向右，当路径超出界限或者进入之前访问过的位置时，则顺时针旋转，进入下一个方向。 判断路径是否进入之前访问过的位置需要使用一个与输入矩阵大小相同的辅助矩阵 visited extit{visited}visited，其中的每... | 85f71621c54f6b0029f3a2746f022f89dd7419d9 | <|skeleton|>
class Solution:
def spiralOrder(self, matrix):
"""方法一：模拟 可以模拟螺旋矩阵的路径。初始位置是矩阵的左上角，初始方向是向右，当路径超出界限或者进入之前访问过的位置时，则顺时针旋转，进入下一个方向。 判断路径是否进入之前访问过的位置需要使用一个与输入矩阵大小相同的辅助矩阵 visited extit{visited}visited，其中的每个元素表示该位置 是否被访问过。当一个元素被访问时，将 visited extit{visited}visited 中的对应位置的元素设为已访问。 如何判断路径是否结束？由于矩阵中的每个元素都被... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def spiralOrder(self, matrix):
"""方法一：模拟 可以模拟螺旋矩阵的路径。初始位置是矩阵的左上角，初始方向是向右，当路径超出界限或者进入之前访问过的位置时，则顺时针旋转，进入下一个方向。 判断路径是否进入之前访问过的位置需要使用一个与输入矩阵大小相同的辅助矩阵 visited extit{visited}visited，其中的每个元素表示该位置 是否被访问过。当一个元素被访问时，将 visited extit{visited}visited 中的对应位置的元素设为已访问。 如何判断路径是否结束？由于矩阵中的每个元素都被访问一次，因此路径的长度即为... | the_stack_v2_python_sparse | LeetCode/Offer/顺时针打印矩阵.py | XyK0907/for_work | train | 0 | |
e7b347ad603ff2baca675f7b5c22c06d00aa1673 | [
"self.repo_path = repo_path\nself.logger = logger\nself.secret = secret",
"assert command and len(command)\ncommand = ['git'] + list(command)\nif self.logger:\n command_str = ' '.join(map(pipes.quote, command))\n if self.secret:\n command_str = command_str.replace(self.secret, 'xxx')\n self.logger... | <|body_start_0|>
self.repo_path = repo_path
self.logger = logger
self.secret = secret
<|end_body_0|>
<|body_start_1|>
assert command and len(command)
command = ['git'] + list(command)
if self.logger:
command_str = ' '.join(map(pipes.quote, command))
... | Helper class for running git commands | GitCommand | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GitCommand:
"""Helper class for running git commands"""
def __init__(self, repo_path, secret=None):
""":param repo_path: the full path to the git repo. :param logger: if set the command executed will be logged with level info. :param secret: this string will be replaced with 'xxx' wh... | stack_v2_sparse_classes_75kplus_train_065042 | 3,785 | no_license | [
{
"docstring": ":param repo_path: the full path to the git repo. :param logger: if set the command executed will be logged with level info. :param secret: this string will be replaced with 'xxx' when logging.",
"name": "__init__",
"signature": "def __init__(self, repo_path, secret=None)"
},
{
"d... | 3 | stack_v2_sparse_classes_30k_train_013153 | Implement the Python class `GitCommand` described below.
Class description:
Helper class for running git commands
Method signatures and docstrings:
- def __init__(self, repo_path, secret=None): :param repo_path: the full path to the git repo. :param logger: if set the command executed will be logged with level info. ... | Implement the Python class `GitCommand` described below.
Class description:
Helper class for running git commands
Method signatures and docstrings:
- def __init__(self, repo_path, secret=None): :param repo_path: the full path to the git repo. :param logger: if set the command executed will be logged with level info. ... | 8ef71a98892473434dbd903647a11b6903b3c92a | <|skeleton|>
class GitCommand:
"""Helper class for running git commands"""
def __init__(self, repo_path, secret=None):
""":param repo_path: the full path to the git repo. :param logger: if set the command executed will be logged with level info. :param secret: this string will be replaced with 'xxx' wh... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GitCommand:
"""Helper class for running git commands"""
def __init__(self, repo_path, secret=None):
""":param repo_path: the full path to the git repo. :param logger: if set the command executed will be logged with level info. :param secret: this string will be replaced with 'xxx' when logging.""... | the_stack_v2_python_sparse | vcssync/mozvcssync/gitutil.py | mjzffr/version-control-tools | train | 1 |
66c4659fd093b940f682fe026b124b960fad6512 | [
"self.language = language\nself.compiler = language.get_compiler()\nself.plugin_stub = language.plugin_stub",
"if not os.path.exists(self.language.get_build_directory()):\n os.makedirs(self.language.get_build_directory())\nif not os.path.exists(self.language.get_output_directory()):\n os.makedirs(self.langu... | <|body_start_0|>
self.language = language
self.compiler = language.get_compiler()
self.plugin_stub = language.plugin_stub
<|end_body_0|>
<|body_start_1|>
if not os.path.exists(self.language.get_build_directory()):
os.makedirs(self.language.get_build_directory())
if n... | Object which builds Python plugins. Attributes: plugin_stub: madz.plugin.PythonPluginStub object | Builder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Builder:
"""Object which builds Python plugins. Attributes: plugin_stub: madz.plugin.PythonPluginStub object"""
def __init__(self, language):
"""Constructor for Python Builder. Args: language: A Language object"""
<|body_0|>
def prep(self):
"""Performs any pre-co... | stack_v2_sparse_classes_75kplus_train_065043 | 1,494 | no_license | [
{
"docstring": "Constructor for Python Builder. Args: language: A Language object",
"name": "__init__",
"signature": "def __init__(self, language)"
},
{
"docstring": "Performs any pre-compile stage prep work for plugin.",
"name": "prep",
"signature": "def prep(self)"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_045074 | Implement the Python class `Builder` described below.
Class description:
Object which builds Python plugins. Attributes: plugin_stub: madz.plugin.PythonPluginStub object
Method signatures and docstrings:
- def __init__(self, language): Constructor for Python Builder. Args: language: A Language object
- def prep(self)... | Implement the Python class `Builder` described below.
Class description:
Object which builds Python plugins. Attributes: plugin_stub: madz.plugin.PythonPluginStub object
Method signatures and docstrings:
- def __init__(self, language): Constructor for Python Builder. Args: language: A Language object
- def prep(self)... | b3fd3ebb4f63957c0cb6a9f1577d8556dc554bda | <|skeleton|>
class Builder:
"""Object which builds Python plugins. Attributes: plugin_stub: madz.plugin.PythonPluginStub object"""
def __init__(self, language):
"""Constructor for Python Builder. Args: language: A Language object"""
<|body_0|>
def prep(self):
"""Performs any pre-co... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Builder:
"""Object which builds Python plugins. Attributes: plugin_stub: madz.plugin.PythonPluginStub object"""
def __init__(self, language):
"""Constructor for Python Builder. Args: language: A Language object"""
self.language = language
self.compiler = language.get_compiler()
... | the_stack_v2_python_sparse | madz/language/python/build.py | OffByOneStudios/massive-dangerzone | train | 0 |
90b61c67022ddea582804ac8952d825dac68f539 | [
"items = []\nfilter_shared = request.GET.get('filter_shared', False)\nif request.GET.get('all_projects') == 'true':\n result = api.neutron.network_list(request, **request.GET)\n rest_utils.ensure_tenant_name(request, result)\n for item in result:\n item_dict = item.to_dict()\n if hasattr(item... | <|body_start_0|>
items = []
filter_shared = request.GET.get('filter_shared', False)
if request.GET.get('all_projects') == 'true':
result = api.neutron.network_list(request, **request.GET)
rest_utils.ensure_tenant_name(request, result)
for item in result:
... | API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html | Networks | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Networks:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of networks for a project The listing result is an object with property "items". Each item is a network."""
<|body_0|>
def post(self, ... | stack_v2_sparse_classes_75kplus_train_065044 | 30,067 | permissive | [
{
"docstring": "Get a list of networks for a project The listing result is an object with property \"items\". Each item is a network.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Create a network :param admin_state_up (optional): The administrative state of the netwo... | 2 | stack_v2_sparse_classes_30k_train_040872 | Implement the Python class `Networks` described below.
Class description:
API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html
Method signatures and docstrings:
- def get(self, request): Get a list of networks for a project The listing result is an object with property "items". Each item... | Implement the Python class `Networks` described below.
Class description:
API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html
Method signatures and docstrings:
- def get(self, request): Get a list of networks for a project The listing result is an object with property "items". Each item... | 9524f1952461c83db485d5d1702c350b158d7ce0 | <|skeleton|>
class Networks:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of networks for a project The listing result is an object with property "items". Each item is a network."""
<|body_0|>
def post(self, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Networks:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of networks for a project The listing result is an object with property "items". Each item is a network."""
items = []
filter_shared = request.G... | the_stack_v2_python_sparse | easystack_dashboard/api/rest/neutron.py | oksbsb/horizon-acc | train | 0 |
001ede22b8ae447983de1d08f2d81ee5f4159f76 | [
"super(Local, self).__init__()\nself.name = 'Local Storage'\nself._logger = logging.getLogger(__name__)\nself._path = ''\nself._filename = ''",
"if not isinstance(data, dict):\n raise TypeError('incorrect data type to store, dict required')\nif not os.path.isfile(self._filename):\n with open(self._filename,... | <|body_start_0|>
super(Local, self).__init__()
self.name = 'Local Storage'
self._logger = logging.getLogger(__name__)
self._path = ''
self._filename = ''
<|end_body_0|>
<|body_start_1|>
if not isinstance(data, dict):
raise TypeError('incorrect data type to st... | Storage API Provides abstract class for various storage options to implement as plugin to storage api | Local | [
"CC-BY-4.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Local:
"""Storage API Provides abstract class for various storage options to implement as plugin to storage api"""
def __init__(self):
"""Initialization function"""
<|body_0|>
def store(self, data):
"""stores ``data``, ``data`` should be a dict :param data: dict ... | stack_v2_sparse_classes_75kplus_train_065045 | 3,869 | permissive | [
{
"docstring": "Initialization function",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "stores ``data``, ``data`` should be a dict :param data: dict object to store",
"name": "store",
"signature": "def store(self, data)"
},
{
"docstring": "Load all requ... | 3 | stack_v2_sparse_classes_30k_train_031782 | Implement the Python class `Local` described below.
Class description:
Storage API Provides abstract class for various storage options to implement as plugin to storage api
Method signatures and docstrings:
- def __init__(self): Initialization function
- def store(self, data): stores ``data``, ``data`` should be a di... | Implement the Python class `Local` described below.
Class description:
Storage API Provides abstract class for various storage options to implement as plugin to storage api
Method signatures and docstrings:
- def __init__(self): Initialization function
- def store(self, data): stores ``data``, ``data`` should be a di... | 4743d6120a9afe077e3666e3128e16808cb04c09 | <|skeleton|>
class Local:
"""Storage API Provides abstract class for various storage options to implement as plugin to storage api"""
def __init__(self):
"""Initialization function"""
<|body_0|>
def store(self, data):
"""stores ``data``, ``data`` should be a dict :param data: dict ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Local:
"""Storage API Provides abstract class for various storage options to implement as plugin to storage api"""
def __init__(self):
"""Initialization function"""
super(Local, self).__init__()
self.name = 'Local Storage'
self._logger = logging.getLogger(__name__)
... | the_stack_v2_python_sparse | sdv/docker/sdvstate/tools/result_api/storage/local/local.py | adi0509/cirv-sdv | train | 0 |
9c0b18fb5510ad478e35e98030b0a2faefea1264 | [
"self.h = Heap()\nself.hash_map = {}\nself.ts_generator = 0\nself.cap = capacity",
"if key in self.hash_map:\n self.hash_map[key].freq += 1\n self.hash_map[key].ts = self.ts_generator\n self.ts_generator += 1\n self.h.heapupdate(self.hash_map[key].idx)\n return self.hash_map[key].v\nelse:\n retu... | <|body_start_0|>
self.h = Heap()
self.hash_map = {}
self.ts_generator = 0
self.cap = capacity
<|end_body_0|>
<|body_start_1|>
if key in self.hash_map:
self.hash_map[key].freq += 1
self.hash_map[key].ts = self.ts_generator
self.ts_generator += ... | LFUCache | [
"MIT"
] | 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 put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus_train_065046 | 3,971 | permissive | [
{
"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: None",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_train_052796 | 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 put(self, key, value): :type key: int :type value: int :rtype: None | 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 put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | fc5b1744af7be93f4dd01d6ad58d2bd12f7ed33f | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|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.h = Heap()
self.hash_map = {}
self.ts_generator = 0
self.cap = capacity
def get(self, key):
""":type key: int :rtype: int"""
if key in self.hash_map:
self.hash_map[ke... | the_stack_v2_python_sparse | 460.LFU-Cache.py | mickey0524/leetcode | train | 27 | |
dd4173abacb17f666c625341dd484862c3420e71 | [
"if not isinstance(p, float):\n raise TypeError(f'Please pass float, not {type(p)}.')\nself._p = np.clip(p, 0.0, 1.0)",
"verify_aligned_info(sequence)\naligned_seq, non_active_sites, active_sites, all_seqs = extract_active_sites_info(sequence)\norder = list(range(len(active_sites)))\nfor pos in range(len(order... | <|body_start_0|>
if not isinstance(p, float):
raise TypeError(f'Please pass float, not {type(p)}.')
self._p = np.clip(p, 0.0, 1.0)
<|end_body_0|>
<|body_start_1|>
verify_aligned_info(sequence)
aligned_seq, non_active_sites, active_sites, all_seqs = extract_active_sites_info(... | Augment a protein sequence by randomly swapping neighboring subsequences. | ProteinAugmentSwapSubstrs | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProteinAugmentSwapSubstrs:
"""Augment a protein sequence by randomly swapping neighboring subsequences."""
def __init__(self, p: float=0.2) -> None:
"""Args: p (float): Probability that any substr switches places with its "neighbour"."""
<|body_0|>
def __call__(self, seq... | stack_v2_sparse_classes_75kplus_train_065047 | 11,629 | permissive | [
{
"docstring": "Args: p (float): Probability that any substr switches places with its \"neighbour\".",
"name": "__init__",
"signature": "def __init__(self, p: float=0.2) -> None"
},
{
"docstring": "Apply the transform. Args: sequence (str): an aligned sequence (example: abCDefGHi). Returns: str:... | 2 | stack_v2_sparse_classes_30k_train_000422 | Implement the Python class `ProteinAugmentSwapSubstrs` described below.
Class description:
Augment a protein sequence by randomly swapping neighboring subsequences.
Method signatures and docstrings:
- def __init__(self, p: float=0.2) -> None: Args: p (float): Probability that any substr switches places with its "neig... | Implement the Python class `ProteinAugmentSwapSubstrs` described below.
Class description:
Augment a protein sequence by randomly swapping neighboring subsequences.
Method signatures and docstrings:
- def __init__(self, p: float=0.2) -> None: Args: p (float): Probability that any substr switches places with its "neig... | 27ca3f8c5b5463cd081be5abdea04f5bfa076f39 | <|skeleton|>
class ProteinAugmentSwapSubstrs:
"""Augment a protein sequence by randomly swapping neighboring subsequences."""
def __init__(self, p: float=0.2) -> None:
"""Args: p (float): Probability that any substr switches places with its "neighbour"."""
<|body_0|>
def __call__(self, seq... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProteinAugmentSwapSubstrs:
"""Augment a protein sequence by randomly swapping neighboring subsequences."""
def __init__(self, p: float=0.2) -> None:
"""Args: p (float): Probability that any substr switches places with its "neighbour"."""
if not isinstance(p, float):
raise Type... | the_stack_v2_python_sparse | pytoda/proteins/transforms.py | PaccMann/paccmann_datasets | train | 22 |
83e8f2578846eaf00ecb799a95af1d26ee238427 | [
"self.all_smb_mount_paths = all_smb_mount_paths\nself.enable_filer_audit_log = enable_filer_audit_log\nself.enable_smb_encryption = enable_smb_encryption\nself.enable_smb_view_discovery = enable_smb_view_discovery\nself.enforce_smb_encryption = enforce_smb_encryption\nself.nfs_mount_path = nfs_mount_path\nself.path... | <|body_start_0|>
self.all_smb_mount_paths = all_smb_mount_paths
self.enable_filer_audit_log = enable_filer_audit_log
self.enable_smb_encryption = enable_smb_encryption
self.enable_smb_view_discovery = enable_smb_view_discovery
self.enforce_smb_encryption = enforce_smb_encryption
... | Implementation of the 'Share' model. Specifies the share details when request is made for list of shares filtered by ShareName parameter. Attributes: all_smb_mount_paths (list of string): Array of SMB Paths. Specifies the possible paths that can be used to mount this Share as a SMB share. If Active Directory has multip... | Share | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Share:
"""Implementation of the 'Share' model. Specifies the share details when request is made for list of shares filtered by ShareName parameter. Attributes: all_smb_mount_paths (list of string): Array of SMB Paths. Specifies the possible paths that can be used to mount this Share as a SMB shar... | stack_v2_sparse_classes_75kplus_train_065048 | 7,179 | permissive | [
{
"docstring": "Constructor for the Share class",
"name": "__init__",
"signature": "def __init__(self, all_smb_mount_paths=None, enable_filer_audit_log=None, enable_smb_encryption=None, enable_smb_view_discovery=None, enforce_smb_encryption=None, nfs_mount_path=None, path=None, s3_access_path=None, shar... | 2 | null | Implement the Python class `Share` described below.
Class description:
Implementation of the 'Share' model. Specifies the share details when request is made for list of shares filtered by ShareName parameter. Attributes: all_smb_mount_paths (list of string): Array of SMB Paths. Specifies the possible paths that can be... | Implement the Python class `Share` described below.
Class description:
Implementation of the 'Share' model. Specifies the share details when request is made for list of shares filtered by ShareName parameter. Attributes: all_smb_mount_paths (list of string): Array of SMB Paths. Specifies the possible paths that can be... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class Share:
"""Implementation of the 'Share' model. Specifies the share details when request is made for list of shares filtered by ShareName parameter. Attributes: all_smb_mount_paths (list of string): Array of SMB Paths. Specifies the possible paths that can be used to mount this Share as a SMB shar... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Share:
"""Implementation of the 'Share' model. Specifies the share details when request is made for list of shares filtered by ShareName parameter. Attributes: all_smb_mount_paths (list of string): Array of SMB Paths. Specifies the possible paths that can be used to mount this Share as a SMB share. If Active ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/share.py | cohesity/management-sdk-python | train | 24 |
aa878c3ff2d54b82730fa2cf385a742cd5efb16e | [
"snap = super(ScrollArea, self).snapshot()\nsnap['horizontal_policy'] = self.horizontal_policy\nsnap['vertical_policy'] = self.vertical_policy\nsnap['widget_resizable'] = self.widget_resizable\nreturn snap",
"super(ScrollArea, self).bind()\nattrs = ('horizontal_policy', 'vertical_policy', 'widget_resizable')\nsel... | <|body_start_0|>
snap = super(ScrollArea, self).snapshot()
snap['horizontal_policy'] = self.horizontal_policy
snap['vertical_policy'] = self.vertical_policy
snap['widget_resizable'] = self.widget_resizable
return snap
<|end_body_0|>
<|body_start_1|>
super(ScrollArea, sel... | A widget which displays a single child in a scrollable area. A ScrollArea has at most a single child Container widget. | ScrollArea | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScrollArea:
"""A widget which displays a single child in a scrollable area. A ScrollArea has at most a single child Container widget."""
def snapshot(self):
"""Return a dictionary which contains all the state necessary to initialize a client widget."""
<|body_0|>
def bin... | stack_v2_sparse_classes_75kplus_train_065049 | 2,901 | permissive | [
{
"docstring": "Return a dictionary which contains all the state necessary to initialize a client widget.",
"name": "snapshot",
"signature": "def snapshot(self)"
},
{
"docstring": "Bind the change handlers for this widget.",
"name": "bind",
"signature": "def bind(self)"
},
{
"doc... | 3 | null | Implement the Python class `ScrollArea` described below.
Class description:
A widget which displays a single child in a scrollable area. A ScrollArea has at most a single child Container widget.
Method signatures and docstrings:
- def snapshot(self): Return a dictionary which contains all the state necessary to initi... | Implement the Python class `ScrollArea` described below.
Class description:
A widget which displays a single child in a scrollable area. A ScrollArea has at most a single child Container widget.
Method signatures and docstrings:
- def snapshot(self): Return a dictionary which contains all the state necessary to initi... | 424bba29219de58fe9e47196de6763de8b2009f2 | <|skeleton|>
class ScrollArea:
"""A widget which displays a single child in a scrollable area. A ScrollArea has at most a single child Container widget."""
def snapshot(self):
"""Return a dictionary which contains all the state necessary to initialize a client widget."""
<|body_0|>
def bin... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ScrollArea:
"""A widget which displays a single child in a scrollable area. A ScrollArea has at most a single child Container widget."""
def snapshot(self):
"""Return a dictionary which contains all the state necessary to initialize a client widget."""
snap = super(ScrollArea, self).snaps... | the_stack_v2_python_sparse | enaml/widgets/scroll_area.py | enthought/enaml | train | 17 |
2061194404c40d47ff3ad902b784e6df77e60d7f | [
"if not root:\n return 'x'\nreturn ','.join([str(root.val), self.serialize(root.left), self.serialize(root.right)])",
"self.data = input_data\nif self.data[0] == 'x':\n return None\nnode = TreeNode(self.data[:self.data.find(',')], None, None)\nnode.left = self.deserialize(self.data[self.data.find(',') + 1:]... | <|body_start_0|>
if not root:
return 'x'
return ','.join([str(root.val), self.serialize(root.left), self.serialize(root.right)])
<|end_body_0|>
<|body_start_1|>
self.data = input_data
if self.data[0] == 'x':
return None
node = TreeNode(self.data[:self.dat... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, input_data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_75kplus_train_065050 | 4,141 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_047129 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, input_data): Decodes your encoded data to tree. :type data: str :... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, input_data): Decodes your encoded data to tree. :type data: str :... | c875ff69ed2b5dfaa5b2d7f37354456542f1ceea | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, input_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 Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return 'x'
return ','.join([str(root.val), self.serialize(root.left), self.serialize(root.right)])
def deserialize(self, input_data):
"""Dec... | the_stack_v2_python_sparse | DailyChallenge/LC_297.py | linxixu-1/Leetcode | train | 0 | |
cf559b5c0966fc31016507766b68fecc09144653 | [
"self.app = QtWidgets.QApplication(sys.argv)\nself.set_color_theme(self.app, 'light')\nMainWindow = QtWidgets.QMainWindow()\nself.main_ui = Ui_Segmentation()\nself.main_ui.setupUi(MainWindow)\nself.source_dir_opener = FileDialog()\nself.main_ui.centralwidget.setFocusPolicy(Qt.NoFocus)\nself.main_app = MicroTomograp... | <|body_start_0|>
self.app = QtWidgets.QApplication(sys.argv)
self.set_color_theme(self.app, 'light')
MainWindow = QtWidgets.QMainWindow()
self.main_ui = Ui_Segmentation()
self.main_ui.setupUi(MainWindow)
self.source_dir_opener = FileDialog()
self.main_ui.centralwi... | Main | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Main:
def __init__(self):
"""Initializes program. Starts app, creates window and implements functions accessible via action bar."""
<|body_0|>
def set_color_theme(self, app, color):
"""Set ui color scheme to either dark or bright Args: app: PyQt App the color scheme ... | stack_v2_sparse_classes_75kplus_train_065051 | 27,085 | no_license | [
{
"docstring": "Initializes program. Starts app, creates window and implements functions accessible via action bar.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Set ui color scheme to either dark or bright Args: app: PyQt App the color scheme is applied to color: St... | 5 | null | Implement the Python class `Main` described below.
Class description:
Implement the Main class.
Method signatures and docstrings:
- def __init__(self): Initializes program. Starts app, creates window and implements functions accessible via action bar.
- def set_color_theme(self, app, color): Set ui color scheme to ei... | Implement the Python class `Main` described below.
Class description:
Implement the Main class.
Method signatures and docstrings:
- def __init__(self): Initializes program. Starts app, creates window and implements functions accessible via action bar.
- def set_color_theme(self, app, color): Set ui color scheme to ei... | fb462691e14a650a0d55cd059721b13ece589105 | <|skeleton|>
class Main:
def __init__(self):
"""Initializes program. Starts app, creates window and implements functions accessible via action bar."""
<|body_0|>
def set_color_theme(self, app, color):
"""Set ui color scheme to either dark or bright Args: app: PyQt App the color scheme ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Main:
def __init__(self):
"""Initializes program. Starts app, creates window and implements functions accessible via action bar."""
self.app = QtWidgets.QApplication(sys.argv)
self.set_color_theme(self.app, 'light')
MainWindow = QtWidgets.QMainWindow()
self.main_ui = Ui... | the_stack_v2_python_sparse | segmentation_cpg/segmentation.py | elerator/capillary_effects_aluminum | train | 0 | |
cc2b11a5423c0a22227250d7864cb64f00955fb1 | [
"self.filepath = bpy.path.abspath('//')\nself.current_filename = bpy.path.display_name_from_filepath(bpy.data.filepath)\nself.current_filename = current_filename.rsplit('.', 1)\nself.does_file_exist = None\nself.file_exists = True\nself.next_numeric = 0\nself.new_filename = ''\nself.new_suffix = ''\nself.non_numeri... | <|body_start_0|>
self.filepath = bpy.path.abspath('//')
self.current_filename = bpy.path.display_name_from_filepath(bpy.data.filepath)
self.current_filename = current_filename.rsplit('.', 1)
self.does_file_exist = None
self.file_exists = True
self.next_numeric = 0
... | Save incremental version of file | SaveIncrementalFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaveIncrementalFile:
"""Save incremental version of file"""
def __init__(self):
"""Initialize"""
<|body_0|>
def execute(self):
"""Execute"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.filepath = bpy.path.abspath('//')
self.current... | stack_v2_sparse_classes_75kplus_train_065052 | 44,083 | no_license | [
{
"docstring": "Initialize",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Execute",
"name": "execute",
"signature": "def execute(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_041172 | Implement the Python class `SaveIncrementalFile` described below.
Class description:
Save incremental version of file
Method signatures and docstrings:
- def __init__(self): Initialize
- def execute(self): Execute | Implement the Python class `SaveIncrementalFile` described below.
Class description:
Save incremental version of file
Method signatures and docstrings:
- def __init__(self): Initialize
- def execute(self): Execute
<|skeleton|>
class SaveIncrementalFile:
"""Save incremental version of file"""
def __init__(se... | 0788f00283d7c8c083aa5d554eb1f32c201adbd6 | <|skeleton|>
class SaveIncrementalFile:
"""Save incremental version of file"""
def __init__(self):
"""Initialize"""
<|body_0|>
def execute(self):
"""Execute"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SaveIncrementalFile:
"""Save incremental version of file"""
def __init__(self):
"""Initialize"""
self.filepath = bpy.path.abspath('//')
self.current_filename = bpy.path.display_name_from_filepath(bpy.data.filepath)
self.current_filename = current_filename.rsplit('.', 1)
... | the_stack_v2_python_sparse | repos/blender_addons/internal/2.7.x/addon_customprops_preset.py | BlenderCN-Org/working_files | train | 0 |
d192ee19acfa1fe7574c69fb686e5ffc6437a772 | [
"self.destination_module_globals = globals()\nself.family = family\nif not isinstance(self.family, list) and (not isinstance(self.family, tuple)):\n self.family = [family]",
"for family in self.family:\n new_klass, klass_name = self._create_interface(klass, family)\n self.destination_module_globals[klass... | <|body_start_0|>
self.destination_module_globals = globals()
self.family = family
if not isinstance(self.family, list) and (not isinstance(self.family, tuple)):
self.family = [family]
<|end_body_0|>
<|body_start_1|>
for family in self.family:
new_klass, klass_nam... | Decorator to determine the networks that need to be warped in the Deep Leanring interface environment. In order to make the class publicly accessible, we assign the result of the function to a variable dynamically using globals(). | DeepLearningDecorator | [
"LicenseRef-scancode-cecill-b-en"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepLearningDecorator:
"""Decorator to determine the networks that need to be warped in the Deep Leanring interface environment. In order to make the class publicly accessible, we assign the result of the function to a variable dynamically using globals()."""
def __init__(self, family):
... | stack_v2_sparse_classes_75kplus_train_065053 | 8,565 | permissive | [
{
"docstring": "Initialize the ValidationDecorator class. Parameters ---------- family: str or list of str the families associated to the network.",
"name": "__init__",
"signature": "def __init__(self, family)"
},
{
"docstring": "Create the validator. Parameters ---------- function: callable the... | 3 | stack_v2_sparse_classes_30k_train_019719 | Implement the Python class `DeepLearningDecorator` described below.
Class description:
Decorator to determine the networks that need to be warped in the Deep Leanring interface environment. In order to make the class publicly accessible, we assign the result of the function to a variable dynamically using globals().
... | Implement the Python class `DeepLearningDecorator` described below.
Class description:
Decorator to determine the networks that need to be warped in the Deep Leanring interface environment. In order to make the class publicly accessible, we assign the result of the function to a variable dynamically using globals().
... | 7a807ed690929563ce36086eaf0998d0e8856aea | <|skeleton|>
class DeepLearningDecorator:
"""Decorator to determine the networks that need to be warped in the Deep Leanring interface environment. In order to make the class publicly accessible, we assign the result of the function to a variable dynamically using globals()."""
def __init__(self, family):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeepLearningDecorator:
"""Decorator to determine the networks that need to be warped in the Deep Leanring interface environment. In order to make the class publicly accessible, we assign the result of the function to a variable dynamically using globals()."""
def __init__(self, family):
"""Initia... | the_stack_v2_python_sparse | pynet/interfaces.py | Duplums/pynet | train | 0 |
e34e31f941b5e0cb939b7b8e9a1e51d6a1af2a2c | [
"self.attributes = attributes\nself.end_of_range = end_of_range\nself.range_type = range_type\nself.start_of_range = start_of_range",
"if dictionary is None:\n return None\nattributes = cohesity_management_sdk.models.oracle_archive_log_info_oracle_archive_log_range_range_attributes.OracleArchiveLogInfo_OracleA... | <|body_start_0|>
self.attributes = attributes
self.end_of_range = end_of_range
self.range_type = range_type
self.start_of_range = start_of_range
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
attributes = cohesity_management_sdk.models.ora... | Implementation of the 'OracleArchiveLogInfo_OracleArchiveLogRange' model. TODO: type description here. Attributes: attributes (OracleArchiveLogInfo_OracleArchiveLogRange_RangeAttributes): TODO: Type description here. end_of_range (long|int): End value of the range range_type (int): Type of range provided. start_of_rang... | OracleArchiveLogInfo_OracleArchiveLogRange | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OracleArchiveLogInfo_OracleArchiveLogRange:
"""Implementation of the 'OracleArchiveLogInfo_OracleArchiveLogRange' model. TODO: type description here. Attributes: attributes (OracleArchiveLogInfo_OracleArchiveLogRange_RangeAttributes): TODO: Type description here. end_of_range (long|int): End valu... | stack_v2_sparse_classes_75kplus_train_065054 | 2,708 | permissive | [
{
"docstring": "Constructor for the OracleArchiveLogInfo_OracleArchiveLogRange class",
"name": "__init__",
"signature": "def __init__(self, attributes=None, end_of_range=None, range_type=None, start_of_range=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dict... | 2 | stack_v2_sparse_classes_30k_train_010143 | Implement the Python class `OracleArchiveLogInfo_OracleArchiveLogRange` described below.
Class description:
Implementation of the 'OracleArchiveLogInfo_OracleArchiveLogRange' model. TODO: type description here. Attributes: attributes (OracleArchiveLogInfo_OracleArchiveLogRange_RangeAttributes): TODO: Type description ... | Implement the Python class `OracleArchiveLogInfo_OracleArchiveLogRange` described below.
Class description:
Implementation of the 'OracleArchiveLogInfo_OracleArchiveLogRange' model. TODO: type description here. Attributes: attributes (OracleArchiveLogInfo_OracleArchiveLogRange_RangeAttributes): TODO: Type description ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class OracleArchiveLogInfo_OracleArchiveLogRange:
"""Implementation of the 'OracleArchiveLogInfo_OracleArchiveLogRange' model. TODO: type description here. Attributes: attributes (OracleArchiveLogInfo_OracleArchiveLogRange_RangeAttributes): TODO: Type description here. end_of_range (long|int): End valu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OracleArchiveLogInfo_OracleArchiveLogRange:
"""Implementation of the 'OracleArchiveLogInfo_OracleArchiveLogRange' model. TODO: type description here. Attributes: attributes (OracleArchiveLogInfo_OracleArchiveLogRange_RangeAttributes): TODO: Type description here. end_of_range (long|int): End value of the rang... | the_stack_v2_python_sparse | cohesity_management_sdk/models/oracle_archive_log_info_oracle_archive_log_range.py | cohesity/management-sdk-python | train | 24 |
e47423e500ba0d60b033720a408bc2bd0fe7fb33 | [
"super().__init__()\nself.out_channels = out_channels if out_channels is not None else in_channels\nmixer_name = mixer_kwargs['token_mixer']\nself.patch_embed = ContiguousEmbed(**embed_kwargs, flatten=not RESHAPE_LOOKUP[mixer_name])\nself.proj_dim = self.patch_embed.proj_dim\nself.mixer = TokenMixerBlock(**mixer_kw... | <|body_start_0|>
super().__init__()
self.out_channels = out_channels if out_channels is not None else in_channels
mixer_name = mixer_kwargs['token_mixer']
self.patch_embed = ContiguousEmbed(**embed_kwargs, flatten=not RESHAPE_LOOKUP[mixer_name])
self.proj_dim = self.patch_embed.p... | MetaFormer | [
"MIT",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetaFormer:
def __init__(self, in_channels: int, embed_kwargs: Dict[str, Any], mixer_kwargs: Dict[str, Any], mlp_kwargs: Dict[str, Any], out_channels: int=None, layer_scale: bool=False, dropout: float=0.0, **kwargs) -> None:
"""Create a generic Metaformer block with any token-mixer avail... | stack_v2_sparse_classes_75kplus_train_065055 | 6,927 | permissive | [
{
"docstring": "Create a generic Metaformer block with any token-mixer available. Input shape: (B, in_channels, H, W) Output shape: (B, out_channels, H, W) Parameters ---------- in_channels : int Number of input channels. embed_kwargs : Dict[str, Any] Key-word arguments for the patch embedding block. mixer_kwar... | 2 | stack_v2_sparse_classes_30k_val_001089 | Implement the Python class `MetaFormer` described below.
Class description:
Implement the MetaFormer class.
Method signatures and docstrings:
- def __init__(self, in_channels: int, embed_kwargs: Dict[str, Any], mixer_kwargs: Dict[str, Any], mlp_kwargs: Dict[str, Any], out_channels: int=None, layer_scale: bool=False, ... | Implement the Python class `MetaFormer` described below.
Class description:
Implement the MetaFormer class.
Method signatures and docstrings:
- def __init__(self, in_channels: int, embed_kwargs: Dict[str, Any], mixer_kwargs: Dict[str, Any], mlp_kwargs: Dict[str, Any], out_channels: int=None, layer_scale: bool=False, ... | 7f79405012eb934b419bbdba8de23f35e840ca85 | <|skeleton|>
class MetaFormer:
def __init__(self, in_channels: int, embed_kwargs: Dict[str, Any], mixer_kwargs: Dict[str, Any], mlp_kwargs: Dict[str, Any], out_channels: int=None, layer_scale: bool=False, dropout: float=0.0, **kwargs) -> None:
"""Create a generic Metaformer block with any token-mixer avail... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MetaFormer:
def __init__(self, in_channels: int, embed_kwargs: Dict[str, Any], mixer_kwargs: Dict[str, Any], mlp_kwargs: Dict[str, Any], out_channels: int=None, layer_scale: bool=False, dropout: float=0.0, **kwargs) -> None:
"""Create a generic Metaformer block with any token-mixer available. Input sh... | the_stack_v2_python_sparse | cellseg_models_pytorch/modules/metaformer.py | okunator/cellseg_models.pytorch | train | 43 | |
b944d90d4784de8c2f92b8ac1bae26e5718db186 | [
"super(jfcEncoderNet, self).__init__()\ndense = []\nfor i in range(num_layers):\n input_dim = np.product(in_dim) if i == 0 else hidden_dim\n dense.extend([nn.Linear(input_dim, hidden_dim), nn.Tanh()])\nself.dense = nn.Sequential(*dense)\nself.reshape_ = hidden_dim\nself.fc11 = nn.Linear(self.reshape_, latent_... | <|body_start_0|>
super(jfcEncoderNet, self).__init__()
dense = []
for i in range(num_layers):
input_dim = np.product(in_dim) if i == 0 else hidden_dim
dense.extend([nn.Linear(input_dim, hidden_dim), nn.Tanh()])
self.dense = nn.Sequential(*dense)
self.resha... | Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & translations by default) num_layers: number of NN layers... | jfcEncoderNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class jfcEncoderNet:
"""Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & translations by... | stack_v2_sparse_classes_75kplus_train_065056 | 28,462 | permissive | [
{
"docstring": "Initializes network parameters",
"name": "__init__",
"signature": "def __init__(self, in_dim: Tuple[int], latent_dim: int=2, discrete_dim: List=[1], num_layers: int=2, hidden_dim: int=32, **kwargs: bool) -> None"
},
{
"docstring": "Forward pass",
"name": "forward",
"signa... | 2 | stack_v2_sparse_classes_30k_train_041921 | Implement the Python class `jfcEncoderNet` described below.
Class description:
Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent... | Implement the Python class `jfcEncoderNet` described below.
Class description:
Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent... | 6d187296074143d017ca8fc60302364cd946b180 | <|skeleton|>
class jfcEncoderNet:
"""Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & translations by... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class jfcEncoderNet:
"""Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & translations by default) num... | the_stack_v2_python_sparse | atomai/nets/ed.py | pycroscopy/atomai | train | 157 |
14111f31d02a5272747019078e08e245fbab4399 | [
"log.msg('connectionLost')\nlog.err(reason)\nreactor.callLater(5, shutdown)",
"defer = DBPOOL.runInteraction(real_parser, data)\ndefer.addCallback(write_memcache)\ndefer.addErrback(common.email_error, data)\ndefer.addErrback(log.err)"
] | <|body_start_0|>
log.msg('connectionLost')
log.err(reason)
reactor.callLater(5, shutdown)
<|end_body_0|>
<|body_start_1|>
defer = DBPOOL.runInteraction(real_parser, data)
defer.addCallback(write_memcache)
defer.addErrback(common.email_error, data)
defer.addErrbac... | I receive products from ldmbridge and process them 1 by 1 :) | MyProductIngestor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyProductIngestor:
"""I receive products from ldmbridge and process them 1 by 1 :)"""
def connectionLost(self, reason):
"""called when the connection is lost"""
<|body_0|>
def process_data(self, data):
"""Process the product"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus_train_065057 | 3,601 | permissive | [
{
"docstring": "called when the connection is lost",
"name": "connectionLost",
"signature": "def connectionLost(self, reason)"
},
{
"docstring": "Process the product",
"name": "process_data",
"signature": "def process_data(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_044281 | Implement the Python class `MyProductIngestor` described below.
Class description:
I receive products from ldmbridge and process them 1 by 1 :)
Method signatures and docstrings:
- def connectionLost(self, reason): called when the connection is lost
- def process_data(self, data): Process the product | Implement the Python class `MyProductIngestor` described below.
Class description:
I receive products from ldmbridge and process them 1 by 1 :)
Method signatures and docstrings:
- def connectionLost(self, reason): called when the connection is lost
- def process_data(self, data): Process the product
<|skeleton|>
cla... | e9ca4c4ad0a6e5a6e6479a84d86fd21ad2a0be00 | <|skeleton|>
class MyProductIngestor:
"""I receive products from ldmbridge and process them 1 by 1 :)"""
def connectionLost(self, reason):
"""called when the connection is lost"""
<|body_0|>
def process_data(self, data):
"""Process the product"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MyProductIngestor:
"""I receive products from ldmbridge and process them 1 by 1 :)"""
def connectionLost(self, reason):
"""called when the connection is lost"""
log.msg('connectionLost')
log.err(reason)
reactor.callLater(5, shutdown)
def process_data(self, data):
... | the_stack_v2_python_sparse | parsers/afos_dump.py | xlia/pyWWA | train | 0 |
5613767004b318d3177e27172d8585b4c7d3a669 | [
"VoxelTimeSeries.__init__(self, overlay, overlayList, displayCtx, plotCanvas)\nself.parentTs = parentTs\nself.contrast = contrast\nself.fitType = fitType\nself.idx = idx",
"opts = self.displayCtx.getOpts(self.overlay)\ncoords = opts.getVoxel()\nif coords is None:\n return None\nreturn self.overlay.partialFit(s... | <|body_start_0|>
VoxelTimeSeries.__init__(self, overlay, overlayList, displayCtx, plotCanvas)
self.parentTs = parentTs
self.contrast = contrast
self.fitType = fitType
self.idx = idx
<|end_body_0|>
<|body_start_1|>
opts = self.displayCtx.getOpts(self.overlay)
coor... | A :class:`VoxelTimeSeries` class which represents the partial model fit of an EV or contrast from a FEAT analysis at a specific voxel. Instances of this class are created by the :class:`FEATTimeSeries` class. | FEATPartialFitTimeSeries | [
"Apache-2.0",
"CC-BY-3.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FEATPartialFitTimeSeries:
"""A :class:`VoxelTimeSeries` class which represents the partial model fit of an EV or contrast from a FEAT analysis at a specific voxel. Instances of this class are created by the :class:`FEATTimeSeries` class."""
def __init__(self, overlay, overlayList, displayCtx... | stack_v2_sparse_classes_75kplus_train_065058 | 29,239 | permissive | [
{
"docstring": "Create a ``FEATPartialFitTimeSeries``. :arg overlay: The :class:`.FEATImage` instance to extract the data from. :arg overlayList: The :class:`.OverlayList` instance. :arg displayCtx: The :class:`.DisplayContext` instance. :arg plotCanvas: The :class:`TimeSeriesPanel` which owns this ``FEATPartia... | 2 | null | Implement the Python class `FEATPartialFitTimeSeries` described below.
Class description:
A :class:`VoxelTimeSeries` class which represents the partial model fit of an EV or contrast from a FEAT analysis at a specific voxel. Instances of this class are created by the :class:`FEATTimeSeries` class.
Method signatures a... | Implement the Python class `FEATPartialFitTimeSeries` described below.
Class description:
A :class:`VoxelTimeSeries` class which represents the partial model fit of an EV or contrast from a FEAT analysis at a specific voxel. Instances of this class are created by the :class:`FEATTimeSeries` class.
Method signatures a... | 37b45d034d60660b6de3e4bdf5dd6349ed6d853b | <|skeleton|>
class FEATPartialFitTimeSeries:
"""A :class:`VoxelTimeSeries` class which represents the partial model fit of an EV or contrast from a FEAT analysis at a specific voxel. Instances of this class are created by the :class:`FEATTimeSeries` class."""
def __init__(self, overlay, overlayList, displayCtx... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FEATPartialFitTimeSeries:
"""A :class:`VoxelTimeSeries` class which represents the partial model fit of an EV or contrast from a FEAT analysis at a specific voxel. Instances of this class are created by the :class:`FEATTimeSeries` class."""
def __init__(self, overlay, overlayList, displayCtx, plotCanvas,... | the_stack_v2_python_sparse | fsleyes/plotting/timeseries.py | CGSchwarzMayo/fsleyes | train | 0 |
9796a40d6b3946ffeeb4989b72535ce12509c877 | [
"super(HopeNet, self).__init__()\nself.inplanes = 64\nself.conv1 = nn.Conv2d(3, 64, kernel_size=7, stride=2, padding=3, bias=False)\nself.bn1 = nn.BatchNorm2d(64)\nself.relu = nn.ReLU(inplace=True)\nself.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)\nself.layer1 = self._make_layer(block, 64, layers[0])... | <|body_start_0|>
super(HopeNet, self).__init__()
self.inplanes = 64
self.conv1 = nn.Conv2d(3, 64, kernel_size=7, stride=2, padding=3, bias=False)
self.bn1 = nn.BatchNorm2d(64)
self.relu = nn.ReLU(inplace=True)
self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1... | Implements HopeNet, used for estimating the head pose from media (images and videos). | HopeNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HopeNet:
"""Implements HopeNet, used for estimating the head pose from media (images and videos)."""
def __init__(self, block, layers, n_bins):
"""Instantiates a HopeNet object used for estimating head pose from media. Parameters ---------- block : layers : list (of ints) List of lay... | stack_v2_sparse_classes_75kplus_train_065059 | 9,784 | no_license | [
{
"docstring": "Instantiates a HopeNet object used for estimating head pose from media. Parameters ---------- block : layers : list (of ints) List of layer sizes for each ``block`` object. n_bins : int The number of bins in the yaw, pitch, and roll outputs. Increase this number to have a finer estimate. Returns... | 3 | stack_v2_sparse_classes_30k_train_014650 | Implement the Python class `HopeNet` described below.
Class description:
Implements HopeNet, used for estimating the head pose from media (images and videos).
Method signatures and docstrings:
- def __init__(self, block, layers, n_bins): Instantiates a HopeNet object used for estimating head pose from media. Paramete... | Implement the Python class `HopeNet` described below.
Class description:
Implements HopeNet, used for estimating the head pose from media (images and videos).
Method signatures and docstrings:
- def __init__(self, block, layers, n_bins): Instantiates a HopeNet object used for estimating head pose from media. Paramete... | a7c30481822ecb945e3ff6ad184d104361a40ed1 | <|skeleton|>
class HopeNet:
"""Implements HopeNet, used for estimating the head pose from media (images and videos)."""
def __init__(self, block, layers, n_bins):
"""Instantiates a HopeNet object used for estimating head pose from media. Parameters ---------- block : layers : list (of ints) List of lay... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HopeNet:
"""Implements HopeNet, used for estimating the head pose from media (images and videos)."""
def __init__(self, block, layers, n_bins):
"""Instantiates a HopeNet object used for estimating head pose from media. Parameters ---------- block : layers : list (of ints) List of layer sizes for ... | the_stack_v2_python_sparse | cheapfake/hopenet/models.py | hu-simon/cheapfake | train | 0 |
fed2ef5e3435f98360094a247a05bcc1b7fade80 | [
"super().__init__(self.PROBLEM_NAME)\nself.input_graph = input_graph\nself.source = source",
"print('Solving {} problem ...'.format(self.PROBLEM_NAME))\ndistance = [float('Inf')] * self.input_graph.get_vertices_count()\ndistance[self.source] = 0\nadjacency_list = self.input_graph.get_adjacency_list()\nfor _ in ra... | <|body_start_0|>
super().__init__(self.PROBLEM_NAME)
self.input_graph = input_graph
self.source = source
<|end_body_0|>
<|body_start_1|>
print('Solving {} problem ...'.format(self.PROBLEM_NAME))
distance = [float('Inf')] * self.input_graph.get_vertices_count()
distance[s... | ShortestPathBellmanFordAlgorithm | ShortestPathBellmanFordAlgorithm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShortestPathBellmanFordAlgorithm:
"""ShortestPathBellmanFordAlgorithm"""
def __init__(self, input_graph, source):
"""Compute Shortest Path (Bellman Ford's Algorithm) Args: input_graph: Graph for which to find the shortest paths source: vertex Returns: None Raises: None"""
<|b... | stack_v2_sparse_classes_75kplus_train_065060 | 2,813 | no_license | [
{
"docstring": "Compute Shortest Path (Bellman Ford's Algorithm) Args: input_graph: Graph for which to find the shortest paths source: vertex Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self, input_graph, source)"
},
{
"docstring": "Solve the problem Note: O(VE) (... | 2 | stack_v2_sparse_classes_30k_train_008939 | Implement the Python class `ShortestPathBellmanFordAlgorithm` described below.
Class description:
ShortestPathBellmanFordAlgorithm
Method signatures and docstrings:
- def __init__(self, input_graph, source): Compute Shortest Path (Bellman Ford's Algorithm) Args: input_graph: Graph for which to find the shortest paths... | Implement the Python class `ShortestPathBellmanFordAlgorithm` described below.
Class description:
ShortestPathBellmanFordAlgorithm
Method signatures and docstrings:
- def __init__(self, input_graph, source): Compute Shortest Path (Bellman Ford's Algorithm) Args: input_graph: Graph for which to find the shortest paths... | 11f4d25cb211740514c119a60962d075a0817abd | <|skeleton|>
class ShortestPathBellmanFordAlgorithm:
"""ShortestPathBellmanFordAlgorithm"""
def __init__(self, input_graph, source):
"""Compute Shortest Path (Bellman Ford's Algorithm) Args: input_graph: Graph for which to find the shortest paths source: vertex Returns: None Raises: None"""
<|b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ShortestPathBellmanFordAlgorithm:
"""ShortestPathBellmanFordAlgorithm"""
def __init__(self, input_graph, source):
"""Compute Shortest Path (Bellman Ford's Algorithm) Args: input_graph: Graph for which to find the shortest paths source: vertex Returns: None Raises: None"""
super().__init__... | the_stack_v2_python_sparse | python/problems/graphs/shortest_path_bellman_ford.py | santhosh-kumar/AlgorithmsAndDataStructures | train | 2 |
9ad523a355f031dd2ff4c99b8e61cc6a9cdd1ec3 | [
"super(Router, self).__init__()\nself.key_function = key_function\nself.routing_table = routing_table",
"k = self.key_function(msg)\nkey = k[0] if isinstance(k, (tuple, list)) else k\nreturn self.routing_table[key]",
"k = self.key_function(msg)\nif isinstance(k, (tuple, list)):\n key, args, kwargs = {1: tupl... | <|body_start_0|>
super(Router, self).__init__()
self.key_function = key_function
self.routing_table = routing_table
<|end_body_0|>
<|body_start_1|>
k = self.key_function(msg)
key = k[0] if isinstance(k, (tuple, list)) else k
return self.routing_table[key]
<|end_body_1|>
... | Map a message to a handler function, using a **key function** and a **routing table** (dictionary). A *key function* digests a message down to a value. This value is treated as a key to the *routing table* to look up a corresponding handler function. | Router | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Router:
"""Map a message to a handler function, using a **key function** and a **routing table** (dictionary). A *key function* digests a message down to a value. This value is treated as a key to the *routing table* to look up a corresponding handler function."""
def __init__(self, key_func... | stack_v2_sparse_classes_75kplus_train_065061 | 40,889 | permissive | [
{
"docstring": ":param key_function: A function that takes one argument (the message) and returns one of the following: - a key to the routing table - a 1-tuple (key,) - a 2-tuple (key, (positional, arguments, ...)) - a 3-tuple (key, (positional, arguments, ...), {keyword: arguments, ...}) Extra arguments, if r... | 3 | stack_v2_sparse_classes_30k_train_032460 | Implement the Python class `Router` described below.
Class description:
Map a message to a handler function, using a **key function** and a **routing table** (dictionary). A *key function* digests a message down to a value. This value is treated as a key to the *routing table* to look up a corresponding handler functi... | Implement the Python class `Router` described below.
Class description:
Map a message to a handler function, using a **key function** and a **routing table** (dictionary). A *key function* digests a message down to a value. This value is treated as a key to the *routing table* to look up a corresponding handler functi... | 979ec1c7d50786939eb65ff779e3e03be950d595 | <|skeleton|>
class Router:
"""Map a message to a handler function, using a **key function** and a **routing table** (dictionary). A *key function* digests a message down to a value. This value is treated as a key to the *routing table* to look up a corresponding handler function."""
def __init__(self, key_func... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Router:
"""Map a message to a handler function, using a **key function** and a **routing table** (dictionary). A *key function* digests a message down to a value. This value is treated as a key to the *routing table* to look up a corresponding handler function."""
def __init__(self, key_function, routing... | the_stack_v2_python_sparse | amanobot/helper.py | AmanoTeam/amanobot | train | 25 |
1182017ca6457de74cef9da88f0af5c1d32bf68c | [
"if len(arr) == arr[-1]:\n return arr[-1] + k\ncnt = 0\nfor i in range(1, arr[-1]):\n if i not in arr:\n cnt += 1\n if cnt == k:\n return i\nreturn arr[-1] + (k - cnt)",
"for i in range(len(arr)):\n distance = arr[i] - i\n if k < distance:\n return arr[i] - (distance - k)\nretu... | <|body_start_0|>
if len(arr) == arr[-1]:
return arr[-1] + k
cnt = 0
for i in range(1, arr[-1]):
if i not in arr:
cnt += 1
if cnt == k:
return i
return arr[-1] + (k - cnt)
<|end_body_0|>
<|body_start_1|>
for i in... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findKthPositive(self, arr, k):
""":type arr: List[int] :type k: int :rtype: int"""
<|body_0|>
def findKthPositive(self, arr, k):
""":type arr: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(ar... | stack_v2_sparse_classes_75kplus_train_065062 | 750 | no_license | [
{
"docstring": ":type arr: List[int] :type k: int :rtype: int",
"name": "findKthPositive",
"signature": "def findKthPositive(self, arr, k)"
},
{
"docstring": ":type arr: List[int] :type k: int :rtype: int",
"name": "findKthPositive",
"signature": "def findKthPositive(self, arr, k)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findKthPositive(self, arr, k): :type arr: List[int] :type k: int :rtype: int
- def findKthPositive(self, arr, k): :type arr: List[int] :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findKthPositive(self, arr, k): :type arr: List[int] :type k: int :rtype: int
- def findKthPositive(self, arr, k): :type arr: List[int] :type k: int :rtype: int
<|skeleton|>
... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def findKthPositive(self, arr, k):
""":type arr: List[int] :type k: int :rtype: int"""
<|body_0|>
def findKthPositive(self, arr, k):
""":type arr: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findKthPositive(self, arr, k):
""":type arr: List[int] :type k: int :rtype: int"""
if len(arr) == arr[-1]:
return arr[-1] + k
cnt = 0
for i in range(1, arr[-1]):
if i not in arr:
cnt += 1
if cnt == k:
... | the_stack_v2_python_sparse | 1539_Kth_Missing_Positive_Number.py | bingli8802/leetcode | train | 0 | |
f77b6a9e7797025c53c119de9cf16e45322e76a9 | [
"url_parsing = urlparse(url)\nallowed = ['docs.google', 'onedrive.live', 'pdf']\nif url_parsing.scheme and url_parsing.netloc:\n if not any((match in url for match in allowed)):\n pass\nelse:\n return 0\nreturn 1",
"now = datetime.datetime.now()\nif int(now.year) - int(date.year) < 0:\n return 0\n... | <|body_start_0|>
url_parsing = urlparse(url)
allowed = ['docs.google', 'onedrive.live', 'pdf']
if url_parsing.scheme and url_parsing.netloc:
if not any((match in url for match in allowed)):
pass
else:
return 0
return 1
<|end_body_0|>
<|bod... | Validator for common fields of material model | MaterialValidator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaterialValidator:
"""Validator for common fields of material model"""
def validate_material_link(cls, url):
"""Validates material's link that it presents a vaild, pdf file not a broken url. 1 -> All is good. 0 -> Provided url is either not valid or broken. -1 -> Provided url should ... | stack_v2_sparse_classes_75kplus_train_065063 | 1,681 | permissive | [
{
"docstring": "Validates material's link that it presents a vaild, pdf file not a broken url. 1 -> All is good. 0 -> Provided url is either not valid or broken. -1 -> Provided url should lead to pdf or doc file.",
"name": "validate_material_link",
"signature": "def validate_material_link(cls, url)"
}... | 2 | null | Implement the Python class `MaterialValidator` described below.
Class description:
Validator for common fields of material model
Method signatures and docstrings:
- def validate_material_link(cls, url): Validates material's link that it presents a vaild, pdf file not a broken url. 1 -> All is good. 0 -> Provided url ... | Implement the Python class `MaterialValidator` described below.
Class description:
Validator for common fields of material model
Method signatures and docstrings:
- def validate_material_link(cls, url): Validates material's link that it presents a vaild, pdf file not a broken url. 1 -> All is good. 0 -> Provided url ... | 70638c121ea85ff0e6a650c5f2641b0b3b04d6d0 | <|skeleton|>
class MaterialValidator:
"""Validator for common fields of material model"""
def validate_material_link(cls, url):
"""Validates material's link that it presents a vaild, pdf file not a broken url. 1 -> All is good. 0 -> Provided url is either not valid or broken. -1 -> Provided url should ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MaterialValidator:
"""Validator for common fields of material model"""
def validate_material_link(cls, url):
"""Validates material's link that it presents a vaild, pdf file not a broken url. 1 -> All is good. 0 -> Provided url is either not valid or broken. -1 -> Provided url should lead to pdf o... | the_stack_v2_python_sparse | cms/validators.py | Ibrahem3amer/bala7 | train | 0 |
2daa2037932cee130dc8a01ea030622a8b29e20d | [
"region = Region.query.filter_by(id=id).first()\nif region is None:\n return ({'message': 'Region does not exist'}, 404)\nreturn region_schema.dump(region)",
"req = api.payload\nregion = Region.query.filter_by(id=id).first()\nif region is None:\n return ({'message': 'Region does not exist'}, 404)\ntry:\n ... | <|body_start_0|>
region = Region.query.filter_by(id=id).first()
if region is None:
return ({'message': 'Region does not exist'}, 404)
return region_schema.dump(region)
<|end_body_0|>
<|body_start_1|>
req = api.payload
region = Region.query.filter_by(id=id).first()
... | SingleRegion | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SingleRegion:
def get(self, id):
"""Get Region by id"""
<|body_0|>
def put(self, id):
"""Update a Region"""
<|body_1|>
def delete(self, id):
"""Delete a Region by id"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
region = Regio... | stack_v2_sparse_classes_75kplus_train_065064 | 3,943 | no_license | [
{
"docstring": "Get Region by id",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "Update a Region",
"name": "put",
"signature": "def put(self, id)"
},
{
"docstring": "Delete a Region by id",
"name": "delete",
"signature": "def delete(self, id)"
}
] | 3 | stack_v2_sparse_classes_30k_train_036834 | Implement the Python class `SingleRegion` described below.
Class description:
Implement the SingleRegion class.
Method signatures and docstrings:
- def get(self, id): Get Region by id
- def put(self, id): Update a Region
- def delete(self, id): Delete a Region by id | Implement the Python class `SingleRegion` described below.
Class description:
Implement the SingleRegion class.
Method signatures and docstrings:
- def get(self, id): Get Region by id
- def put(self, id): Update a Region
- def delete(self, id): Delete a Region by id
<|skeleton|>
class SingleRegion:
def get(self... | ae78fff9888b0f68d9403d7f65cba086dabb3802 | <|skeleton|>
class SingleRegion:
def get(self, id):
"""Get Region by id"""
<|body_0|>
def put(self, id):
"""Update a Region"""
<|body_1|>
def delete(self, id):
"""Delete a Region by id"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SingleRegion:
def get(self, id):
"""Get Region by id"""
region = Region.query.filter_by(id=id).first()
if region is None:
return ({'message': 'Region does not exist'}, 404)
return region_schema.dump(region)
def put(self, id):
"""Update a Region"""
... | the_stack_v2_python_sparse | api/v1/regions.py | mythril-io/flask-api | train | 0 | |
99af2325f23ead0a1ce015fa615ae957c2d1d0e5 | [
"orders_serializer = OrdersSerializer(data=request.data)\nif orders_serializer.is_valid():\n logging.debug('The order is valid with the data {}'.format(request.data))\n order_object = orders_serializer.save()\n json_response = json.dumps({'order_id': order_object.id}, separators=(':', ','))\n return Res... | <|body_start_0|>
orders_serializer = OrdersSerializer(data=request.data)
if orders_serializer.is_valid():
logging.debug('The order is valid with the data {}'.format(request.data))
order_object = orders_serializer.save()
json_response = json.dumps({'order_id': order_ob... | This is the CRUD for Order models. | CRUDOrder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CRUDOrder:
"""This is the CRUD for Order models."""
def post(self, request, format=None):
"""Insert a order in a database"""
<|body_0|>
def get(self, request, format=None):
"""Get all orders in database"""
<|body_1|>
def delete(self, request, format=... | stack_v2_sparse_classes_75kplus_train_065065 | 2,875 | no_license | [
{
"docstring": "Insert a order in a database",
"name": "post",
"signature": "def post(self, request, format=None)"
},
{
"docstring": "Get all orders in database",
"name": "get",
"signature": "def get(self, request, format=None)"
},
{
"docstring": "Delete a order in the database",... | 4 | null | Implement the Python class `CRUDOrder` described below.
Class description:
This is the CRUD for Order models.
Method signatures and docstrings:
- def post(self, request, format=None): Insert a order in a database
- def get(self, request, format=None): Get all orders in database
- def delete(self, request, format=None... | Implement the Python class `CRUDOrder` described below.
Class description:
This is the CRUD for Order models.
Method signatures and docstrings:
- def post(self, request, format=None): Insert a order in a database
- def get(self, request, format=None): Get all orders in database
- def delete(self, request, format=None... | de3f616a28574816f4570b28ae9abb8fcd22188b | <|skeleton|>
class CRUDOrder:
"""This is the CRUD for Order models."""
def post(self, request, format=None):
"""Insert a order in a database"""
<|body_0|>
def get(self, request, format=None):
"""Get all orders in database"""
<|body_1|>
def delete(self, request, format=... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CRUDOrder:
"""This is the CRUD for Order models."""
def post(self, request, format=None):
"""Insert a order in a database"""
orders_serializer = OrdersSerializer(data=request.data)
if orders_serializer.is_valid():
logging.debug('The order is valid with the data {}'.for... | the_stack_v2_python_sparse | tasker/Orders/views/order.py | Desenho-2018-2/Tasker | train | 0 |
3a8b2cf6d3f36cfe05234b8088f2db3fb8254e99 | [
"self._logger = logger\nself._no_run = False\nif not is_exe(exe_path):\n self._logger.error('No trim_quality script available (exiting)')\n sys.exit(1)\nself._exe_path = exe_path\nself.format = 'fastq'",
"self.__build_cmd(infname, outdir)\nmsg = ['Running...', '\\t%s' % self._cmd]\nfor m in msg:\n self._... | <|body_start_0|>
self._logger = logger
self._no_run = False
if not is_exe(exe_path):
self._logger.error('No trim_quality script available (exiting)')
sys.exit(1)
self._exe_path = exe_path
self.format = 'fastq'
<|end_body_0|>
<|body_start_1|>
self.... | Class for working with trim_quality | Trim_Quality | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trim_Quality:
"""Class for working with trim_quality"""
def __init__(self, exe_path, logger):
"""Instantiate with location of executable"""
<|body_0|>
def run(self, infname, outdir):
"""Run trim_quality on the passed file"""
<|body_1|>
def __build_cm... | stack_v2_sparse_classes_75kplus_train_065066 | 3,597 | permissive | [
{
"docstring": "Instantiate with location of executable",
"name": "__init__",
"signature": "def __init__(self, exe_path, logger)"
},
{
"docstring": "Run trim_quality on the passed file",
"name": "run",
"signature": "def run(self, infname, outdir)"
},
{
"docstring": "Build a comma... | 3 | stack_v2_sparse_classes_30k_train_033833 | Implement the Python class `Trim_Quality` described below.
Class description:
Class for working with trim_quality
Method signatures and docstrings:
- def __init__(self, exe_path, logger): Instantiate with location of executable
- def run(self, infname, outdir): Run trim_quality on the passed file
- def __build_cmd(se... | Implement the Python class `Trim_Quality` described below.
Class description:
Class for working with trim_quality
Method signatures and docstrings:
- def __init__(self, exe_path, logger): Instantiate with location of executable
- def run(self, infname, outdir): Run trim_quality on the passed file
- def __build_cmd(se... | a3c64198aad3709a5c4d969f48ae0af11fdc25db | <|skeleton|>
class Trim_Quality:
"""Class for working with trim_quality"""
def __init__(self, exe_path, logger):
"""Instantiate with location of executable"""
<|body_0|>
def run(self, infname, outdir):
"""Run trim_quality on the passed file"""
<|body_1|>
def __build_cm... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Trim_Quality:
"""Class for working with trim_quality"""
def __init__(self, exe_path, logger):
"""Instantiate with location of executable"""
self._logger = logger
self._no_run = False
if not is_exe(exe_path):
self._logger.error('No trim_quality script available ... | the_stack_v2_python_sparse | metapy/pycits/seq_crumbs.py | peterthorpe5/public_scripts | train | 35 |
fd13c3e8ec5c1d0a9671f41c60fd35fcc20f2be9 | [
"node = self.generic_visit(node)\nif isinstance(node.func, ast.Name):\n fc_name = node.func.id\n new_name = fc_name\n integer = self.parse_integer.search(fc_name)\n if integer is not None:\n size = int(integer.groups()[0])\n new_name = 'ExprInt'\n node.func.id = new_name\n no... | <|body_start_0|>
node = self.generic_visit(node)
if isinstance(node.func, ast.Name):
fc_name = node.func.id
new_name = fc_name
integer = self.parse_integer.search(fc_name)
if integer is not None:
size = int(integer.groups()[0])
... | AST visitor translating DSL to Miasm expression memX[Y] -> ExprMem(Y, X) iX(Y) -> ExprIntX(Y) X if Y else Z -> ExprCond(Y, X, Z) 'X'(Y) -> ExprOp('X', Y) ('X' % Y)(Z) -> ExprOp('X' % Y, Z) {a, b} -> ExprCompose(((a, 0, a.size), (b, a.size, a.size + b.size))) | MiasmTransformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MiasmTransformer:
"""AST visitor translating DSL to Miasm expression memX[Y] -> ExprMem(Y, X) iX(Y) -> ExprIntX(Y) X if Y else Z -> ExprCond(Y, X, Z) 'X'(Y) -> ExprOp('X', Y) ('X' % Y)(Z) -> ExprOp('X' % Y, Z) {a, b} -> ExprCompose(((a, 0, a.size), (b, a.size, a.size + b.size)))"""
def visit... | stack_v2_sparse_classes_75kplus_train_065067 | 12,978 | no_license | [
{
"docstring": "iX(Y) -> ExprIntX(Y), 'X'(Y) -> ExprOp('X', Y), ('X' % Y)(Z) -> ExprOp('X' % Y, Z)",
"name": "visit_Call",
"signature": "def visit_Call(self, node)"
},
{
"docstring": "memX[Y] -> ExprMem(Y, X)",
"name": "visit_Subscript",
"signature": "def visit_Subscript(self, node)"
}... | 4 | stack_v2_sparse_classes_30k_train_013439 | Implement the Python class `MiasmTransformer` described below.
Class description:
AST visitor translating DSL to Miasm expression memX[Y] -> ExprMem(Y, X) iX(Y) -> ExprIntX(Y) X if Y else Z -> ExprCond(Y, X, Z) 'X'(Y) -> ExprOp('X', Y) ('X' % Y)(Z) -> ExprOp('X' % Y, Z) {a, b} -> ExprCompose(((a, 0, a.size), (b, a.siz... | Implement the Python class `MiasmTransformer` described below.
Class description:
AST visitor translating DSL to Miasm expression memX[Y] -> ExprMem(Y, X) iX(Y) -> ExprIntX(Y) X if Y else Z -> ExprCond(Y, X, Z) 'X'(Y) -> ExprOp('X', Y) ('X' % Y)(Z) -> ExprOp('X' % Y, Z) {a, b} -> ExprCompose(((a, 0, a.size), (b, a.siz... | b71431045339a2e031950d2f8d99bfce30a44e99 | <|skeleton|>
class MiasmTransformer:
"""AST visitor translating DSL to Miasm expression memX[Y] -> ExprMem(Y, X) iX(Y) -> ExprIntX(Y) X if Y else Z -> ExprCond(Y, X, Z) 'X'(Y) -> ExprOp('X', Y) ('X' % Y)(Z) -> ExprOp('X' % Y, Z) {a, b} -> ExprCompose(((a, 0, a.size), (b, a.size, a.size + b.size)))"""
def visit... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MiasmTransformer:
"""AST visitor translating DSL to Miasm expression memX[Y] -> ExprMem(Y, X) iX(Y) -> ExprIntX(Y) X if Y else Z -> ExprCond(Y, X, Z) 'X'(Y) -> ExprOp('X', Y) ('X' % Y)(Z) -> ExprOp('X' % Y, Z) {a, b} -> ExprCompose(((a, 0, a.size), (b, a.size, a.size + b.size)))"""
def visit_Call(self, n... | the_stack_v2_python_sparse | miasm2/core/sembuilder.py | buptsseGJ/VulSeeker | train | 97 |
92b7e85c3726232f52a212ba133965134926bb68 | [
"try:\n from pynao import tddft_iter\nexcept ModuleNotFoundError as err:\n msg = 'running lrtddft with Siesta calculator requires pynao package'\n raise ModuleNotFoundError(msg) from err\nself.initialize = initialize\nself.lrtddft_params = kw\nself.tddft = None\nif 'iter_broadening' in self.lrtddft_params:... | <|body_start_0|>
try:
from pynao import tddft_iter
except ModuleNotFoundError as err:
msg = 'running lrtddft with Siesta calculator requires pynao package'
raise ModuleNotFoundError(msg) from err
self.initialize = initialize
self.lrtddft_params = kw
... | Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/references.html) | SiestaLRTDDFT | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SiestaLRTDDFT:
"""Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/references.html)"""
def __init__(self, in... | stack_v2_sparse_classes_75kplus_train_065068 | 6,483 | no_license | [
{
"docstring": "Parameters ---------- initialize: bool To initialize the tddft calculations before calculating the polarizability Can be useful to calculate multiple frequency range without the need to recalculate the kernel kw: dictionary keywords for the tddft_iter function from PyNAO",
"name": "__init__"... | 3 | stack_v2_sparse_classes_30k_train_045978 | Implement the Python class `SiestaLRTDDFT` described below.
Class description:
Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/referen... | Implement the Python class `SiestaLRTDDFT` described below.
Class description:
Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/referen... | 6299b76c0504c5a7f7e94271aba9907a8ce77719 | <|skeleton|>
class SiestaLRTDDFT:
"""Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/references.html)"""
def __init__(self, in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SiestaLRTDDFT:
"""Interface for linear response TDDFT for Siesta via [PyNAO](https://mbarbry.website.fr.to/pynao/doc/html/) When using PyNAO please cite the papers indicated at in the PyNAO [documentation](https://mbarbry.website.fr.to/pynao/doc/html/references.html)"""
def __init__(self, initialize=Fals... | the_stack_v2_python_sparse | venv/Lib/site-packages/ase/calculators/siesta/siesta_lrtddft.py | Pratiksha1317/e-shop | train | 0 |
2e52af42e6fbe8e48b25fb304ed057549e216a5e | [
"cursor = '0'\nwhile cursor != 0:\n cursor, data = await self.scan(cursor=cursor, match=match, count=count)\n for item in data:\n yield item",
"cursor = '0'\nwhile cursor != 0:\n cursor, data = await self.sscan(name, cursor=cursor, match=match, count=count)\n for item in data:\n yield it... | <|body_start_0|>
cursor = '0'
while cursor != 0:
cursor, data = await self.scan(cursor=cursor, match=match, count=count)
for item in data:
yield item
<|end_body_0|>
<|body_start_1|>
cursor = '0'
while cursor != 0:
cursor, data = await ... | convenient function of scan iter, make it a class separately because yield can not be used in async function in Python3.6 | IterCommandMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IterCommandMixin:
"""convenient function of scan iter, make it a class separately because yield can not be used in async function in Python3.6"""
async def scan_iter(self, match=None, count=None):
"""Make an iterator using the SCAN command so that the client doesn't need to remember ... | stack_v2_sparse_classes_75kplus_train_065069 | 3,468 | permissive | [
{
"docstring": "Make an iterator using the SCAN command so that the client doesn't need to remember the cursor position. ``match`` allows for filtering the keys by pattern ``count`` allows for hint the minimum number of returns",
"name": "scan_iter",
"signature": "async def scan_iter(self, match=None, c... | 4 | stack_v2_sparse_classes_30k_train_003474 | Implement the Python class `IterCommandMixin` described below.
Class description:
convenient function of scan iter, make it a class separately because yield can not be used in async function in Python3.6
Method signatures and docstrings:
- async def scan_iter(self, match=None, count=None): Make an iterator using the ... | Implement the Python class `IterCommandMixin` described below.
Class description:
convenient function of scan iter, make it a class separately because yield can not be used in async function in Python3.6
Method signatures and docstrings:
- async def scan_iter(self, match=None, count=None): Make an iterator using the ... | 3a7f80bf41bf9df6f9d4d97a2327368bcc1941cb | <|skeleton|>
class IterCommandMixin:
"""convenient function of scan iter, make it a class separately because yield can not be used in async function in Python3.6"""
async def scan_iter(self, match=None, count=None):
"""Make an iterator using the SCAN command so that the client doesn't need to remember ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IterCommandMixin:
"""convenient function of scan iter, make it a class separately because yield can not be used in async function in Python3.6"""
async def scan_iter(self, match=None, count=None):
"""Make an iterator using the SCAN command so that the client doesn't need to remember the cursor po... | the_stack_v2_python_sparse | aredis/commands/iter.py | DalavanCloud/aredis | train | 1 |
3bc21c1ce1f351aec8aac44b3f4194ef74e94be0 | [
"super(focal_loss, self).__init__()\nself.size_average = size_average\nif isinstance(alpha, list):\n assert len(alpha) == num_classes\n self.alpha = torch.Tensor(alpha)\nelse:\n assert alpha < 1\n self.alpha = torch.zeros(num_classes)\n self.alpha[0] += alpha\n self.alpha[1:] += 1 - alpha\nself.ga... | <|body_start_0|>
super(focal_loss, self).__init__()
self.size_average = size_average
if isinstance(alpha, list):
assert len(alpha) == num_classes
self.alpha = torch.Tensor(alpha)
else:
assert alpha < 1
self.alpha = torch.zeros(num_classes)
... | focal_loss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class focal_loss:
def __init__(self, alpha=0.25, gamma=2, num_classes=3, size_average=True):
"""focal_loss损失函数, -α(1-yi)**γ *ce_loss(xi,yi) 步骤详细的实现了 focal_loss损失函数. :param alpha: 阿尔法α,类别权重. 当α是列表时,为各类别权重,当α为常数时,类别权重为[α, 1-α, 1-α, ....],常用于 目标检测算法中抑制背景类 , retainnet中设置为0.25 :param gamma: 伽马γ,难易样... | stack_v2_sparse_classes_75kplus_train_065070 | 12,665 | no_license | [
{
"docstring": "focal_loss损失函数, -α(1-yi)**γ *ce_loss(xi,yi) 步骤详细的实现了 focal_loss损失函数. :param alpha: 阿尔法α,类别权重. 当α是列表时,为各类别权重,当α为常数时,类别权重为[α, 1-α, 1-α, ....],常用于 目标检测算法中抑制背景类 , retainnet中设置为0.25 :param gamma: 伽马γ,难易样本调节参数. retainnet中设置为2 :param num_classes: 类别数量 :param size_average: 损失计算方式,默认取均值",
"name": "__... | 2 | stack_v2_sparse_classes_30k_train_046986 | Implement the Python class `focal_loss` described below.
Class description:
Implement the focal_loss class.
Method signatures and docstrings:
- def __init__(self, alpha=0.25, gamma=2, num_classes=3, size_average=True): focal_loss损失函数, -α(1-yi)**γ *ce_loss(xi,yi) 步骤详细的实现了 focal_loss损失函数. :param alpha: 阿尔法α,类别权重. 当α是列表... | Implement the Python class `focal_loss` described below.
Class description:
Implement the focal_loss class.
Method signatures and docstrings:
- def __init__(self, alpha=0.25, gamma=2, num_classes=3, size_average=True): focal_loss损失函数, -α(1-yi)**γ *ce_loss(xi,yi) 步骤详细的实现了 focal_loss损失函数. :param alpha: 阿尔法α,类别权重. 当α是列表... | 3d3e07974a8ba1ffb7c79765aaf37cdb435a611f | <|skeleton|>
class focal_loss:
def __init__(self, alpha=0.25, gamma=2, num_classes=3, size_average=True):
"""focal_loss损失函数, -α(1-yi)**γ *ce_loss(xi,yi) 步骤详细的实现了 focal_loss损失函数. :param alpha: 阿尔法α,类别权重. 当α是列表时,为各类别权重,当α为常数时,类别权重为[α, 1-α, 1-α, ....],常用于 目标检测算法中抑制背景类 , retainnet中设置为0.25 :param gamma: 伽马γ,难易样... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class focal_loss:
def __init__(self, alpha=0.25, gamma=2, num_classes=3, size_average=True):
"""focal_loss损失函数, -α(1-yi)**γ *ce_loss(xi,yi) 步骤详细的实现了 focal_loss损失函数. :param alpha: 阿尔法α,类别权重. 当α是列表时,为各类别权重,当α为常数时,类别权重为[α, 1-α, 1-α, ....],常用于 目标检测算法中抑制背景类 , retainnet中设置为0.25 :param gamma: 伽马γ,难易样本调节参数. retainn... | the_stack_v2_python_sparse | code_zjx_round2/model/model_axial.py | Waterbearbear/spark-competition | train | 0 | |
c704ba7e09d5b635926f3f81fe2620e89f8f5c84 | [
"self.src = src\nself.dst = dst\nself.smtp = None\nself.default_message = 'Your post processsing job has completed successfully'\nself.default_status = 'SUCCEESS'",
"if not msg:\n msg = self.default_message\nif not status:\n status = self.default_status\nself.smtp = smtplib.SMTP('localhost')\nmessage = MIME... | <|body_start_0|>
self.src = src
self.dst = dst
self.smtp = None
self.default_message = 'Your post processsing job has completed successfully'
self.default_status = 'SUCCEESS'
<|end_body_0|>
<|body_start_1|>
if not msg:
msg = self.default_message
if no... | A simple class for sending email | Mailer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mailer:
"""A simple class for sending email"""
def __init__(self, src, dst):
"""Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email address"""
<|body_0|>
def send(self, status=None... | stack_v2_sparse_classes_75kplus_train_065071 | 1,584 | permissive | [
{
"docstring": "Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email address",
"name": "__init__",
"signature": "def __init__(self, src, dst)"
},
{
"docstring": "Send the email with contents = msg and subje... | 2 | stack_v2_sparse_classes_30k_train_048454 | Implement the Python class `Mailer` described below.
Class description:
A simple class for sending email
Method signatures and docstrings:
- def __init__(self, src, dst): Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email addr... | Implement the Python class `Mailer` described below.
Class description:
A simple class for sending email
Method signatures and docstrings:
- def __init__(self, src, dst): Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email addr... | 84110cab08f7897d1489a6dc925258580a5d2bff | <|skeleton|>
class Mailer:
"""A simple class for sending email"""
def __init__(self, src, dst):
"""Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email address"""
<|body_0|>
def send(self, status=None... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Mailer:
"""A simple class for sending email"""
def __init__(self, src, dst):
"""Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email address"""
self.src = src
self.dst = dst
self.smtp... | the_stack_v2_python_sparse | processflow/lib/mailer.py | E3SM-Project/processflow | train | 4 |
66fc6764c600ab9ad1a83a1a09c2a72f350c8f5a | [
"self.enable_logging = enable_logging\nself.user_emails = user_emails\nself._config_for_bp = False",
"if self._config_for_bp:\n gca_model_monitoring = gca_model_monitoring_v1beta1\nelse:\n gca_model_monitoring = gca_model_monitoring_v1\nuser_email_alert_config = gca_model_monitoring.ModelMonitoringAlertConf... | <|body_start_0|>
self.enable_logging = enable_logging
self.user_emails = user_emails
self._config_for_bp = False
<|end_body_0|>
<|body_start_1|>
if self._config_for_bp:
gca_model_monitoring = gca_model_monitoring_v1beta1
else:
gca_model_monitoring = gca_m... | EmailAlertConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmailAlertConfig:
def __init__(self, user_emails: List[str]=[], enable_logging: Optional[bool]=False):
"""Initializer for EmailAlertConfig. Args: user_emails (List[str]): The email addresses to send the alert to. enable_logging (bool): Optional. Defaults to False. Streams detected anomal... | stack_v2_sparse_classes_75kplus_train_065072 | 2,668 | permissive | [
{
"docstring": "Initializer for EmailAlertConfig. Args: user_emails (List[str]): The email addresses to send the alert to. enable_logging (bool): Optional. Defaults to False. Streams detected anomalies to Cloud Logging. The anomalies will be put into json payload encoded from proto [google.cloud.aiplatform.logg... | 2 | stack_v2_sparse_classes_30k_train_033477 | Implement the Python class `EmailAlertConfig` described below.
Class description:
Implement the EmailAlertConfig class.
Method signatures and docstrings:
- def __init__(self, user_emails: List[str]=[], enable_logging: Optional[bool]=False): Initializer for EmailAlertConfig. Args: user_emails (List[str]): The email ad... | Implement the Python class `EmailAlertConfig` described below.
Class description:
Implement the EmailAlertConfig class.
Method signatures and docstrings:
- def __init__(self, user_emails: List[str]=[], enable_logging: Optional[bool]=False): Initializer for EmailAlertConfig. Args: user_emails (List[str]): The email ad... | 76b95b92c1d3b87c72d754d8c02b1bca652b9a27 | <|skeleton|>
class EmailAlertConfig:
def __init__(self, user_emails: List[str]=[], enable_logging: Optional[bool]=False):
"""Initializer for EmailAlertConfig. Args: user_emails (List[str]): The email addresses to send the alert to. enable_logging (bool): Optional. Defaults to False. Streams detected anomal... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EmailAlertConfig:
def __init__(self, user_emails: List[str]=[], enable_logging: Optional[bool]=False):
"""Initializer for EmailAlertConfig. Args: user_emails (List[str]): The email addresses to send the alert to. enable_logging (bool): Optional. Defaults to False. Streams detected anomalies to Cloud L... | the_stack_v2_python_sparse | google/cloud/aiplatform/model_monitoring/alert.py | googleapis/python-aiplatform | train | 418 | |
71b4ba13e85dad5800089b4efe0d300d5185f144 | [
"names = set()\nconnections = list()\nwith open(filename, 'r') as myfile:\n for line in myfile.readlines():\n con = line.strip().split(',')\n connections.append(con)\n names.add(con[0])\n names.add(con[1])\nself.names = sorted(list(names))\nn = len(self.names)\nself.n = n\nA = np.zero... | <|body_start_0|>
names = set()
connections = list()
with open(filename, 'r') as myfile:
for line in myfile.readlines():
con = line.strip().split(',')
connections.append(con)
names.add(con[0])
names.add(con[1])
se... | Predict links between nodes of a network. | LinkPredictor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkPredictor:
"""Predict links between nodes of a network."""
def __init__(self, filename='social_network.csv'):
"""Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The name of a file containing graph data."""
<|body_0|>... | stack_v2_sparse_classes_75kplus_train_065073 | 6,778 | no_license | [
{
"docstring": "Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The name of a file containing graph data.",
"name": "__init__",
"signature": "def __init__(self, filename='social_network.csv')"
},
{
"docstring": "Predict the next link, eithe... | 3 | stack_v2_sparse_classes_30k_train_044198 | Implement the Python class `LinkPredictor` described below.
Class description:
Predict links between nodes of a network.
Method signatures and docstrings:
- def __init__(self, filename='social_network.csv'): Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The na... | Implement the Python class `LinkPredictor` described below.
Class description:
Predict links between nodes of a network.
Method signatures and docstrings:
- def __init__(self, filename='social_network.csv'): Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The na... | 6e969de3a8337b0bd9bb4ba7abac722ab5c065ab | <|skeleton|>
class LinkPredictor:
"""Predict links between nodes of a network."""
def __init__(self, filename='social_network.csv'):
"""Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The name of a file containing graph data."""
<|body_0|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LinkPredictor:
"""Predict links between nodes of a network."""
def __init__(self, filename='social_network.csv'):
"""Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The name of a file containing graph data."""
names = set()
c... | the_stack_v2_python_sparse | Class/ACME_Volume_1-Python/DrazinInverse/drazin.py | scj1420/Class-Projects-Research | train | 0 |
c0c6aea8e298c52e99e367bcb4a56fb04d49abbc | [
"super().__init__(task_params, num_shards)\nloss_fn_name = self.task_params.get('main_loss', None)\nif loss_fn_name is None:\n if self.dataset.meta_data['num_classes'] == 1:\n loss_fn_name = 'sigmoid_cross_entropy'\n else:\n loss_fn_name = 'categorical_cross_entropy'\nself.main_loss_fn = functoo... | <|body_start_0|>
super().__init__(task_params, num_shards)
loss_fn_name = self.task_params.get('main_loss', None)
if loss_fn_name is None:
if self.dataset.meta_data['num_classes'] == 1:
loss_fn_name = 'sigmoid_cross_entropy'
else:
loss_fn_n... | Classification Task. | ClassificationTask | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassificationTask:
"""Classification Task."""
def __init__(self, task_params, num_shards):
"""Initializing Classification based Tasks. Args: task_params: configdict; Hyperparameters of the task. num_shards: int; Number of deviced that we shard the batch over."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_065074 | 44,080 | permissive | [
{
"docstring": "Initializing Classification based Tasks. Args: task_params: configdict; Hyperparameters of the task. num_shards: int; Number of deviced that we shard the batch over.",
"name": "__init__",
"signature": "def __init__(self, task_params, num_shards)"
},
{
"docstring": "Calculates met... | 3 | stack_v2_sparse_classes_30k_train_038313 | Implement the Python class `ClassificationTask` described below.
Class description:
Classification Task.
Method signatures and docstrings:
- def __init__(self, task_params, num_shards): Initializing Classification based Tasks. Args: task_params: configdict; Hyperparameters of the task. num_shards: int; Number of devi... | Implement the Python class `ClassificationTask` described below.
Class description:
Classification Task.
Method signatures and docstrings:
- def __init__(self, task_params, num_shards): Initializing Classification based Tasks. Args: task_params: configdict; Hyperparameters of the task. num_shards: int; Number of devi... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class ClassificationTask:
"""Classification Task."""
def __init__(self, task_params, num_shards):
"""Initializing Classification based Tasks. Args: task_params: configdict; Hyperparameters of the task. num_shards: int; Number of deviced that we shard the batch over."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClassificationTask:
"""Classification Task."""
def __init__(self, task_params, num_shards):
"""Initializing Classification based Tasks. Args: task_params: configdict; Hyperparameters of the task. num_shards: int; Number of deviced that we shard the batch over."""
super().__init__(task_par... | the_stack_v2_python_sparse | gift/tasks/task.py | Jimmy-INL/google-research | train | 1 |
1db7c70561305e5cfdb03827c0d88d10e90df498 | [
"super().__init__()\nself.mha = MultiHeadAttention(dm, h)\nself.ffn = point_wise_feed_forward_network(dm, hidden)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernorm2 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.dropout1 = tf.keras.layers.Dropout(drop_rate)\nself.dropou... | <|body_start_0|>
super().__init__()
self.mha = MultiHeadAttention(dm, h)
self.ffn = point_wise_feed_forward_network(dm, hidden)
self.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)
self.layernorm2 = tf.keras.layers.LayerNormalization(epsilon=1e-06)
self.dro... | class Encoder | EncoderBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderBlock:
"""class Encoder"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Init"""
<|body_0|>
def call(self, x, training, mask=None):
"""call method"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__()
self.mha ... | stack_v2_sparse_classes_75kplus_train_065075 | 8,707 | no_license | [
{
"docstring": "Init",
"name": "__init__",
"signature": "def __init__(self, dm, h, hidden, drop_rate=0.1)"
},
{
"docstring": "call method",
"name": "call",
"signature": "def call(self, x, training, mask=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_048527 | Implement the Python class `EncoderBlock` described below.
Class description:
class Encoder
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): Init
- def call(self, x, training, mask=None): call method | Implement the Python class `EncoderBlock` described below.
Class description:
class Encoder
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): Init
- def call(self, x, training, mask=None): call method
<|skeleton|>
class EncoderBlock:
"""class Encoder"""
def __init__(self,... | e8a98d85b3bfd5665cb04bec9ee8c3eb23d6bd58 | <|skeleton|>
class EncoderBlock:
"""class Encoder"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Init"""
<|body_0|>
def call(self, x, training, mask=None):
"""call method"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EncoderBlock:
"""class Encoder"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Init"""
super().__init__()
self.mha = MultiHeadAttention(dm, h)
self.ffn = point_wise_feed_forward_network(dm, hidden)
self.layernorm1 = tf.keras.layers.LayerNormalization(epsilo... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/5-transformer.py | AndrewMiranda/holbertonschool-machine_learning-1 | train | 0 |
4c0cc5bfc4be026c8692210a441330302f70c42b | [
"\"\"\"在初始化冰激凌的属性\"\"\"\nsuper().__init__(restaurant_name, cuisine_type)\nself.flavors = ['酸甜', '草莓味', '芒果味', '西瓜味']",
"displays = self.flavors\nprint('冰激凌的口味有：')\nfor a in displays:\n print(a)"
] | <|body_start_0|>
"""在初始化冰激凌的属性"""
super().__init__(restaurant_name, cuisine_type)
self.flavors = ['酸甜', '草莓味', '芒果味', '西瓜味']
<|end_body_0|>
<|body_start_1|>
displays = self.flavors
print('冰激凌的口味有：')
for a in displays:
print(a)
<|end_body_1|>
| 冰激凌小店的日常 | IceCreamStand | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IceCreamStand:
"""冰激凌小店的日常"""
def __init__(self, restaurant_name, cuisine_type):
"""初始化父类的属性"""
<|body_0|>
def display(self):
"""显示各种冰激凌"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
"""在初始化冰激凌的属性"""
super().__init__(restaurant_name, c... | stack_v2_sparse_classes_75kplus_train_065076 | 1,650 | no_license | [
{
"docstring": "初始化父类的属性",
"name": "__init__",
"signature": "def __init__(self, restaurant_name, cuisine_type)"
},
{
"docstring": "显示各种冰激凌",
"name": "display",
"signature": "def display(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007958 | Implement the Python class `IceCreamStand` described below.
Class description:
冰激凌小店的日常
Method signatures and docstrings:
- def __init__(self, restaurant_name, cuisine_type): 初始化父类的属性
- def display(self): 显示各种冰激凌 | Implement the Python class `IceCreamStand` described below.
Class description:
冰激凌小店的日常
Method signatures and docstrings:
- def __init__(self, restaurant_name, cuisine_type): 初始化父类的属性
- def display(self): 显示各种冰激凌
<|skeleton|>
class IceCreamStand:
"""冰激凌小店的日常"""
def __init__(self, restaurant_name, cuisine_ty... | 0e18c1711a07bd8583a9f74eacfb0b48b5a76216 | <|skeleton|>
class IceCreamStand:
"""冰激凌小店的日常"""
def __init__(self, restaurant_name, cuisine_type):
"""初始化父类的属性"""
<|body_0|>
def display(self):
"""显示各种冰激凌"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IceCreamStand:
"""冰激凌小店的日常"""
def __init__(self, restaurant_name, cuisine_type):
"""初始化父类的属性"""
"""在初始化冰激凌的属性"""
super().__init__(restaurant_name, cuisine_type)
self.flavors = ['酸甜', '草莓味', '芒果味', '西瓜味']
def display(self):
"""显示各种冰激凌"""
displays = self... | the_stack_v2_python_sparse | Python_World/9-6.py | qyl1006/MyGitHub | train | 0 |
b723536260d0739ea6a1b67fc29f591d07cd3c5f | [
"super().__init__()\nself.receiver = RCReceiver(read_pin_config(mock_bbio=mock_bbio))\nself.keep_reading = True\nself.read_interval = read_interval()",
"while True:\n self.receiver.send_inputs()\n sleep(self.read_interval)"
] | <|body_start_0|>
super().__init__()
self.receiver = RCReceiver(read_pin_config(mock_bbio=mock_bbio))
self.keep_reading = True
self.read_interval = read_interval()
<|end_body_0|>
<|body_start_1|>
while True:
self.receiver.send_inputs()
sleep(self.read_inte... | A separate thread to manage reading the RC inputs and broadcasting the data to the system. Should accept multiple boat configurations, and should be general enough to allow for easy extension. | RCInputThread | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RCInputThread:
"""A separate thread to manage reading the RC inputs and broadcasting the data to the system. Should accept multiple boat configurations, and should be general enough to allow for easy extension."""
def __init__(self, mock_bbio=None):
"""Builds a new RC input thread.""... | stack_v2_sparse_classes_75kplus_train_065077 | 849 | permissive | [
{
"docstring": "Builds a new RC input thread.",
"name": "__init__",
"signature": "def __init__(self, mock_bbio=None)"
},
{
"docstring": "Starts a regular input read interval.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003988 | Implement the Python class `RCInputThread` described below.
Class description:
A separate thread to manage reading the RC inputs and broadcasting the data to the system. Should accept multiple boat configurations, and should be general enough to allow for easy extension.
Method signatures and docstrings:
- def __init... | Implement the Python class `RCInputThread` described below.
Class description:
A separate thread to manage reading the RC inputs and broadcasting the data to the system. Should accept multiple boat configurations, and should be general enough to allow for easy extension.
Method signatures and docstrings:
- def __init... | b5d75cb82e4bc3e9c4e428a288c6ac98a4aa2c52 | <|skeleton|>
class RCInputThread:
"""A separate thread to manage reading the RC inputs and broadcasting the data to the system. Should accept multiple boat configurations, and should be general enough to allow for easy extension."""
def __init__(self, mock_bbio=None):
"""Builds a new RC input thread.""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RCInputThread:
"""A separate thread to manage reading the RC inputs and broadcasting the data to the system. Should accept multiple boat configurations, and should be general enough to allow for easy extension."""
def __init__(self, mock_bbio=None):
"""Builds a new RC input thread."""
sup... | the_stack_v2_python_sparse | src/rc_input/rc_input_thread.py | vt-sailbot/sailbot-21 | train | 5 |
eef5af9c32764e1c1601a983e0d6fb66b5681b91 | [
"super().__init__(**kwargs)\nself.factory = factory\nself.activity = activity",
"challenge_translations = self.get_yaml_translations(CHALLENGES_FILENAME, required_fields=['question'])\nfor challenge_order_number, challenge_data in challenge_translations.items():\n translations = self.get_blank_translation_dict... | <|body_start_0|>
super().__init__(**kwargs)
self.factory = factory
self.activity = activity
<|end_body_0|>
<|body_start_1|>
challenge_translations = self.get_yaml_translations(CHALLENGES_FILENAME, required_fields=['question'])
for challenge_order_number, challenge_data in challe... | Custom loader for loading activity challenges. | ChallengeLoader | [
"LicenseRef-scancode-secret-labs-2011",
"MIT",
"OFL-1.1",
"LGPL-2.0-or-later",
"AGPL-3.0-only",
"CC-BY-4.0",
"Apache-2.0",
"BSD-3-Clause",
"CC-BY-SA-4.0",
"LicenseRef-scancode-public-domain",
"LicenseRef-scancode-other-copyleft",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChallengeLoader:
"""Custom loader for loading activity challenges."""
def __init__(self, factory, activity, **kwargs):
"""Create the loader for loading activity challenges. Args: factory: LoaderFactory object for creating loaders (LoaderFactory). activty: Object of related activity m... | stack_v2_sparse_classes_75kplus_train_065078 | 2,892 | permissive | [
{
"docstring": "Create the loader for loading activity challenges. Args: factory: LoaderFactory object for creating loaders (LoaderFactory). activty: Object of related activity model (Activity).",
"name": "__init__",
"signature": "def __init__(self, factory, activity, **kwargs)"
},
{
"docstring"... | 2 | stack_v2_sparse_classes_30k_val_001879 | Implement the Python class `ChallengeLoader` described below.
Class description:
Custom loader for loading activity challenges.
Method signatures and docstrings:
- def __init__(self, factory, activity, **kwargs): Create the loader for loading activity challenges. Args: factory: LoaderFactory object for creating loade... | Implement the Python class `ChallengeLoader` described below.
Class description:
Custom loader for loading activity challenges.
Method signatures and docstrings:
- def __init__(self, factory, activity, **kwargs): Create the loader for loading activity challenges. Args: factory: LoaderFactory object for creating loade... | 363e281ff17cefdef0ec61078b1718eef2eaf71a | <|skeleton|>
class ChallengeLoader:
"""Custom loader for loading activity challenges."""
def __init__(self, factory, activity, **kwargs):
"""Create the loader for loading activity challenges. Args: factory: LoaderFactory object for creating loaders (LoaderFactory). activty: Object of related activity m... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ChallengeLoader:
"""Custom loader for loading activity challenges."""
def __init__(self, factory, activity, **kwargs):
"""Create the loader for loading activity challenges. Args: factory: LoaderFactory object for creating loaders (LoaderFactory). activty: Object of related activity model (Activit... | the_stack_v2_python_sparse | csunplugged/at_home/management/commands/_ChallengeLoader.py | uccser/cs-unplugged | train | 200 |
e38b23625f8c0e790bd69312e37441d8b1528afe | [
"super(MacAppFirewallParser, self).__init__()\nself._last_month = 0\nself._previous_structure = None\nself._year_use = 0",
"time_elements_tuple = self._GetValueFromStructure(structure, 'date_time')\nmonth, day, hours, minutes, seconds = time_elements_tuple\nmonth = timelib.MONTH_DICT.get(month.lower(), 0)\nif mon... | <|body_start_0|>
super(MacAppFirewallParser, self).__init__()
self._last_month = 0
self._previous_structure = None
self._year_use = 0
<|end_body_0|>
<|body_start_1|>
time_elements_tuple = self._GetValueFromStructure(structure, 'date_time')
month, day, hours, minutes, sec... | Parser for MacOS Application firewall log (appfirewall.log) files. | MacAppFirewallParser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MacAppFirewallParser:
"""Parser for MacOS Application firewall log (appfirewall.log) files."""
def __init__(self):
"""Initializes a parser."""
<|body_0|>
def _GetTimeElementsTuple(self, structure):
"""Retrieves a time elements tuple from the structure. Args: stru... | stack_v2_sparse_classes_75kplus_train_065079 | 8,331 | permissive | [
{
"docstring": "Initializes a parser.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Retrieves a time elements tuple from the structure. Args: structure (pyparsing.ParseResults): structure of tokens derived from a line of a text file. Returns: tuple: containing: year ... | 5 | null | Implement the Python class `MacAppFirewallParser` described below.
Class description:
Parser for MacOS Application firewall log (appfirewall.log) files.
Method signatures and docstrings:
- def __init__(self): Initializes a parser.
- def _GetTimeElementsTuple(self, structure): Retrieves a time elements tuple from the ... | Implement the Python class `MacAppFirewallParser` described below.
Class description:
Parser for MacOS Application firewall log (appfirewall.log) files.
Method signatures and docstrings:
- def __init__(self): Initializes a parser.
- def _GetTimeElementsTuple(self, structure): Retrieves a time elements tuple from the ... | c69b2952b608cfce47ff8fd0d1409d856be35cb1 | <|skeleton|>
class MacAppFirewallParser:
"""Parser for MacOS Application firewall log (appfirewall.log) files."""
def __init__(self):
"""Initializes a parser."""
<|body_0|>
def _GetTimeElementsTuple(self, structure):
"""Retrieves a time elements tuple from the structure. Args: stru... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MacAppFirewallParser:
"""Parser for MacOS Application firewall log (appfirewall.log) files."""
def __init__(self):
"""Initializes a parser."""
super(MacAppFirewallParser, self).__init__()
self._last_month = 0
self._previous_structure = None
self._year_use = 0
... | the_stack_v2_python_sparse | plaso/parsers/mac_appfirewall.py | cyb3rfox/plaso | train | 3 |
96d4e8f8ac1033e53caf9f17c9320fa125744395 | [
"threading.Thread.__init__(self)\nself.client: socket.socket = client\nself.address = address",
"request = self.client.recv(1024)\ntry:\n request = Request.decode(request)\nexcept:\n response = Response(status=400)\nelse:\n response = self.respond(request)\nself.client.send(response.encode())\nself.clien... | <|body_start_0|>
threading.Thread.__init__(self)
self.client: socket.socket = client
self.address = address
<|end_body_0|>
<|body_start_1|>
request = self.client.recv(1024)
try:
request = Request.decode(request)
except:
response = Response(status=... | ServerThread | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServerThread:
def __init__(self, client, address):
"""Constructor"""
<|body_0|>
def run(self):
"""Serve client's request."""
<|body_1|>
def respond(self, request: Request) -> Response:
"""Respond to a HTTP request. :param request: The request. :r... | stack_v2_sparse_classes_75kplus_train_065080 | 7,546 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, client, address)"
},
{
"docstring": "Serve client's request.",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "Respond to a HTTP request. :param request: The request. :return: The co... | 3 | null | Implement the Python class `ServerThread` described below.
Class description:
Implement the ServerThread class.
Method signatures and docstrings:
- def __init__(self, client, address): Constructor
- def run(self): Serve client's request.
- def respond(self, request: Request) -> Response: Respond to a HTTP request. :p... | Implement the Python class `ServerThread` described below.
Class description:
Implement the ServerThread class.
Method signatures and docstrings:
- def __init__(self, client, address): Constructor
- def run(self): Serve client's request.
- def respond(self, request: Request) -> Response: Respond to a HTTP request. :p... | aad20f17ab99f86fb30dbc1f4d13ce5fab6633d2 | <|skeleton|>
class ServerThread:
def __init__(self, client, address):
"""Constructor"""
<|body_0|>
def run(self):
"""Serve client's request."""
<|body_1|>
def respond(self, request: Request) -> Response:
"""Respond to a HTTP request. :param request: The request. :r... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ServerThread:
def __init__(self, client, address):
"""Constructor"""
threading.Thread.__init__(self)
self.client: socket.socket = client
self.address = address
def run(self):
"""Serve client's request."""
request = self.client.recv(1024)
try:
... | the_stack_v2_python_sparse | CSCI_4760/pj01/web_server.py | dsluo-archive/notes | train | 0 | |
59285e5510e2cefdddc5a6a1d28d19b35b5559c6 | [
"self.entity_description = description\nself._tc_object = tc_object\nself._update_devices = update_devices\nself._attr_name = f'{tc_object.name} {description.name}'",
"self._update_devices()\nsensor_type = self.entity_description.key\nif sensor_type == 'battery':\n self._attr_native_value = self._tc_object.bat... | <|body_start_0|>
self.entity_description = description
self._tc_object = tc_object
self._update_devices = update_devices
self._attr_name = f'{tc_object.name} {description.name}'
<|end_body_0|>
<|body_start_1|>
self._update_devices()
sensor_type = self.entity_description.... | Representation of a ThinkingCleaner Sensor. | ThinkingCleanerSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThinkingCleanerSensor:
"""Representation of a ThinkingCleaner Sensor."""
def __init__(self, tc_object, update_devices, description: SensorEntityDescription) -> None:
"""Initialize the ThinkingCleaner."""
<|body_0|>
def update(self) -> None:
"""Update the sensor."... | stack_v2_sparse_classes_75kplus_train_065081 | 3,910 | permissive | [
{
"docstring": "Initialize the ThinkingCleaner.",
"name": "__init__",
"signature": "def __init__(self, tc_object, update_devices, description: SensorEntityDescription) -> None"
},
{
"docstring": "Update the sensor.",
"name": "update",
"signature": "def update(self) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_031553 | Implement the Python class `ThinkingCleanerSensor` described below.
Class description:
Representation of a ThinkingCleaner Sensor.
Method signatures and docstrings:
- def __init__(self, tc_object, update_devices, description: SensorEntityDescription) -> None: Initialize the ThinkingCleaner.
- def update(self) -> None... | Implement the Python class `ThinkingCleanerSensor` described below.
Class description:
Representation of a ThinkingCleaner Sensor.
Method signatures and docstrings:
- def __init__(self, tc_object, update_devices, description: SensorEntityDescription) -> None: Initialize the ThinkingCleaner.
- def update(self) -> None... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ThinkingCleanerSensor:
"""Representation of a ThinkingCleaner Sensor."""
def __init__(self, tc_object, update_devices, description: SensorEntityDescription) -> None:
"""Initialize the ThinkingCleaner."""
<|body_0|>
def update(self) -> None:
"""Update the sensor."... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ThinkingCleanerSensor:
"""Representation of a ThinkingCleaner Sensor."""
def __init__(self, tc_object, update_devices, description: SensorEntityDescription) -> None:
"""Initialize the ThinkingCleaner."""
self.entity_description = description
self._tc_object = tc_object
sel... | the_stack_v2_python_sparse | homeassistant/components/thinkingcleaner/sensor.py | home-assistant/core | train | 35,501 |
df0c8cf3c3c37c68ee71c47f57af1675f15ec9dc | [
"args = args or {}\nkwargs = kwargs or {}\ncall_args = getcallargs(self.run, *args, **kwargs)\nif isinstance(call_args.get('self'), celery.Task):\n del call_args['self']\nkeys = sorted(self.mutex_lock_keys) if type(self.mutex_lock_keys) is list else [self.mutex_lock_keys]\naccum = []\nfor key in keys:\n accum... | <|body_start_0|>
args = args or {}
kwargs = kwargs or {}
call_args = getcallargs(self.run, *args, **kwargs)
if isinstance(call_args.get('self'), celery.Task):
del call_args['self']
keys = sorted(self.mutex_lock_keys) if type(self.mutex_lock_keys) is list else [self.mu... | Represents repeatable task that can be run only once. Any additional calls to the task would be rejected. Class-wise arguments: continue_exceptions -- Set of exceptions that shouldn't break the schedule. terminate_exceptions -- Set of exceptions that would finish the schedule after the task returns. mutex_max_exec_time... | RepeatableMutexTask | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RepeatableMutexTask:
"""Represents repeatable task that can be run only once. Any additional calls to the task would be rejected. Class-wise arguments: continue_exceptions -- Set of exceptions that shouldn't break the schedule. terminate_exceptions -- Set of exceptions that would finish the sched... | stack_v2_sparse_classes_75kplus_train_065082 | 12,527 | no_license | [
{
"docstring": "Build a lock key based on the task name and its arguments",
"name": "get_key",
"signature": "def get_key(self, args, kwargs)"
},
{
"docstring": "Lock the given redis key, making another instances of the task with the same arguments unable to run. If the lock already exists, excep... | 5 | null | Implement the Python class `RepeatableMutexTask` described below.
Class description:
Represents repeatable task that can be run only once. Any additional calls to the task would be rejected. Class-wise arguments: continue_exceptions -- Set of exceptions that shouldn't break the schedule. terminate_exceptions -- Set of... | Implement the Python class `RepeatableMutexTask` described below.
Class description:
Represents repeatable task that can be run only once. Any additional calls to the task would be rejected. Class-wise arguments: continue_exceptions -- Set of exceptions that shouldn't break the schedule. terminate_exceptions -- Set of... | d2366c4a22a83ef28f008520f862a2f2cd8a29c6 | <|skeleton|>
class RepeatableMutexTask:
"""Represents repeatable task that can be run only once. Any additional calls to the task would be rejected. Class-wise arguments: continue_exceptions -- Set of exceptions that shouldn't break the schedule. terminate_exceptions -- Set of exceptions that would finish the sched... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RepeatableMutexTask:
"""Represents repeatable task that can be run only once. Any additional calls to the task would be rejected. Class-wise arguments: continue_exceptions -- Set of exceptions that shouldn't break the schedule. terminate_exceptions -- Set of exceptions that would finish the schedule after the... | the_stack_v2_python_sparse | source/matrix_bot/tasks.py | a13xmt/matrixstats.org | train | 8 |
0b906215988f6c1c66143f05efc138ea77e4a0c8 | [
"album_list = []\nmethod_uri = '/getalbums/{{service_token}}/' + library_id\nif include_inactive:\n method_uri += '/IncludeInactive'\nxml_root = _client.get_xml(method_uri)\nalbums = xml_root.find('albums').getchildren()\nfor album_element in albums:\n album = Album._from_xml(album_element, _client=_client)\n... | <|body_start_0|>
album_list = []
method_uri = '/getalbums/{{service_token}}/' + library_id
if include_inactive:
method_uri += '/IncludeInactive'
xml_root = _client.get_xml(method_uri)
albums = xml_root.find('albums').getchildren()
for album_element in albums:
... | Performs calls for the :class:`Album` model, also useful in a static context. Available at `Album.query` or `album_instance.query` | AlbumQuery | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlbumQuery:
"""Performs calls for the :class:`Album` model, also useful in a static context. Available at `Album.query` or `album_instance.query`"""
def get_albums_for_library(self, library_id, _client, include_inactive=False):
"""Gets all of the albums for a particular library. :par... | stack_v2_sparse_classes_75kplus_train_065083 | 3,756 | permissive | [
{
"docstring": "Gets all of the albums for a particular library. :param library_id: The Harvest Media library identifer :param _client: An initialized instance of :class:`harvestmedia.api.client.Client`",
"name": "get_albums_for_library",
"signature": "def get_albums_for_library(self, library_id, _clien... | 2 | stack_v2_sparse_classes_30k_train_019043 | Implement the Python class `AlbumQuery` described below.
Class description:
Performs calls for the :class:`Album` model, also useful in a static context. Available at `Album.query` or `album_instance.query`
Method signatures and docstrings:
- def get_albums_for_library(self, library_id, _client, include_inactive=Fals... | Implement the Python class `AlbumQuery` described below.
Class description:
Performs calls for the :class:`Album` model, also useful in a static context. Available at `Album.query` or `album_instance.query`
Method signatures and docstrings:
- def get_albums_for_library(self, library_id, _client, include_inactive=Fals... | f2aa8d4b4296fefdc5b66905d22c8fe7de970dd8 | <|skeleton|>
class AlbumQuery:
"""Performs calls for the :class:`Album` model, also useful in a static context. Available at `Album.query` or `album_instance.query`"""
def get_albums_for_library(self, library_id, _client, include_inactive=False):
"""Gets all of the albums for a particular library. :par... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AlbumQuery:
"""Performs calls for the :class:`Album` model, also useful in a static context. Available at `Album.query` or `album_instance.query`"""
def get_albums_for_library(self, library_id, _client, include_inactive=False):
"""Gets all of the albums for a particular library. :param library_id... | the_stack_v2_python_sparse | harvestmedia/api/album.py | ralfonso/harvestmedia | train | 1 |
e5f1d88083142ba4c6047d8dfdb5e94c92dc5330 | [
"super(SmallUpSampler, self).__init__()\nself.conv = conv(n_feats, upsize * upsize * n_feats, 3, has_bias)\nself.reshape = P.Reshape()\nself.upsize = upsize\nself.pixelsf = _pixelsf_",
"x = self.conv(x)\noutput = self.pixelsf(x, self.upsize)\nreturn output"
] | <|body_start_0|>
super(SmallUpSampler, self).__init__()
self.conv = conv(n_feats, upsize * upsize * n_feats, 3, has_bias)
self.reshape = P.Reshape()
self.upsize = upsize
self.pixelsf = _pixelsf_
<|end_body_0|>
<|body_start_1|>
x = self.conv(x)
output = self.pixel... | edsr | SmallUpSampler | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmallUpSampler:
"""edsr"""
def __init__(self, conv, upsize, n_feats, has_bias=True):
"""edsr"""
<|body_0|>
def construct(self, x):
"""edsr"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(SmallUpSampler, self).__init__()
self.conv =... | stack_v2_sparse_classes_75kplus_train_065084 | 5,893 | permissive | [
{
"docstring": "edsr",
"name": "__init__",
"signature": "def __init__(self, conv, upsize, n_feats, has_bias=True)"
},
{
"docstring": "edsr",
"name": "construct",
"signature": "def construct(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_053866 | Implement the Python class `SmallUpSampler` described below.
Class description:
edsr
Method signatures and docstrings:
- def __init__(self, conv, upsize, n_feats, has_bias=True): edsr
- def construct(self, x): edsr | Implement the Python class `SmallUpSampler` described below.
Class description:
edsr
Method signatures and docstrings:
- def __init__(self, conv, upsize, n_feats, has_bias=True): edsr
- def construct(self, x): edsr
<|skeleton|>
class SmallUpSampler:
"""edsr"""
def __init__(self, conv, upsize, n_feats, has_b... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class SmallUpSampler:
"""edsr"""
def __init__(self, conv, upsize, n_feats, has_bias=True):
"""edsr"""
<|body_0|>
def construct(self, x):
"""edsr"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SmallUpSampler:
"""edsr"""
def __init__(self, conv, upsize, n_feats, has_bias=True):
"""edsr"""
super(SmallUpSampler, self).__init__()
self.conv = conv(n_feats, upsize * upsize * n_feats, 3, has_bias)
self.reshape = P.Reshape()
self.upsize = upsize
self.pix... | the_stack_v2_python_sparse | research/cv/csd/src/edsr_model.py | mindspore-ai/models | train | 301 |
de2c7fe33201066931f0976c53c663619b00fe22 | [
"self.port = config['logging']['port'] or logging.handlers.DEFAULT_TCP_LOGGING_PORT\nself.host = 'localhost'\nself.config = config\nself.multi = multi",
"if self.multi:\n logger = MultiFileLogger(self.config)\nelse:\n logger = SingleFileLogger(self.config, 'mistamover')\ntcpserver = LogReceiver.LogRecordSoc... | <|body_start_0|>
self.port = config['logging']['port'] or logging.handlers.DEFAULT_TCP_LOGGING_PORT
self.host = 'localhost'
self.config = config
self.multi = multi
<|end_body_0|>
<|body_start_1|>
if self.multi:
logger = MultiFileLogger(self.config)
else:
... | A top level logger server, which will receive messages on a port and pass them to either SingleFileLogger or MultiFileLogger | LoggerServer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoggerServer:
"""A top level logger server, which will receive messages on a port and pass them to either SingleFileLogger or MultiFileLogger"""
def __init__(self, config, multi=True):
"""instantiate with GlobalConfig / DatasetConfig object set "multi" to True/False depending whether... | stack_v2_sparse_classes_75kplus_train_065085 | 5,340 | permissive | [
{
"docstring": "instantiate with GlobalConfig / DatasetConfig object set \"multi\" to True/False depending whether single file or multi file logging is wanted",
"name": "__init__",
"signature": "def __init__(self, config, multi=True)"
},
{
"docstring": "Main loop.",
"name": "serve",
"sig... | 2 | stack_v2_sparse_classes_30k_train_006383 | Implement the Python class `LoggerServer` described below.
Class description:
A top level logger server, which will receive messages on a port and pass them to either SingleFileLogger or MultiFileLogger
Method signatures and docstrings:
- def __init__(self, config, multi=True): instantiate with GlobalConfig / Dataset... | Implement the Python class `LoggerServer` described below.
Class description:
A top level logger server, which will receive messages on a port and pass them to either SingleFileLogger or MultiFileLogger
Method signatures and docstrings:
- def __init__(self, config, multi=True): instantiate with GlobalConfig / Dataset... | 37ad31c4c66658c4c77340efc783040f94df3f3f | <|skeleton|>
class LoggerServer:
"""A top level logger server, which will receive messages on a port and pass them to either SingleFileLogger or MultiFileLogger"""
def __init__(self, config, multi=True):
"""instantiate with GlobalConfig / DatasetConfig object set "multi" to True/False depending whether... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LoggerServer:
"""A top level logger server, which will receive messages on a port and pass them to either SingleFileLogger or MultiFileLogger"""
def __init__(self, config, multi=True):
"""instantiate with GlobalConfig / DatasetConfig object set "multi" to True/False depending whether single file ... | the_stack_v2_python_sparse | lib/LoggerServer.py | cedadev/mistamover | train | 0 |
58781760828835a42cfa4ecf36cc6f3df265ab28 | [
"html = helpers.get_content(url)\nif not html:\n return None\nsoup = BeautifulSoup(html)\na = soup.find('title')\nk = a.text.split('-')\nheadline = k[0]\ndate = k[1]\nc = soup.findAll('p', attrs={'class': 'zn-body__paragraph'})\nbody = ''\nfor paragraph in c:\n try:\n body += paragraph.text.decode('utf... | <|body_start_0|>
html = helpers.get_content(url)
if not html:
return None
soup = BeautifulSoup(html)
a = soup.find('title')
k = a.text.split('-')
headline = k[0]
date = k[1]
c = soup.findAll('p', attrs={'class': 'zn-body__paragraph'})
b... | Methods for interacting with the CNN website. | CNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CNN:
"""Methods for interacting with the CNN website."""
def get_article(self, url):
"""Implementation for getting an article from CNN. Args: url: A URL in the www.cnn.* domain. Returns: The Article representing the article at that url."""
<|body_0|>
def get_query_result... | stack_v2_sparse_classes_75kplus_train_065086 | 1,861 | no_license | [
{
"docstring": "Implementation for getting an article from CNN. Args: url: A URL in the www.cnn.* domain. Returns: The Article representing the article at that url.",
"name": "get_article",
"signature": "def get_article(self, url)"
},
{
"docstring": "Implementation for keyword searches from CNN.... | 2 | stack_v2_sparse_classes_30k_train_038950 | Implement the Python class `CNN` described below.
Class description:
Methods for interacting with the CNN website.
Method signatures and docstrings:
- def get_article(self, url): Implementation for getting an article from CNN. Args: url: A URL in the www.cnn.* domain. Returns: The Article representing the article at ... | Implement the Python class `CNN` described below.
Class description:
Methods for interacting with the CNN website.
Method signatures and docstrings:
- def get_article(self, url): Implementation for getting an article from CNN. Args: url: A URL in the www.cnn.* domain. Returns: The Article representing the article at ... | b1adf7d582eb78623a44611dc07749823da84d5f | <|skeleton|>
class CNN:
"""Methods for interacting with the CNN website."""
def get_article(self, url):
"""Implementation for getting an article from CNN. Args: url: A URL in the www.cnn.* domain. Returns: The Article representing the article at that url."""
<|body_0|>
def get_query_result... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CNN:
"""Methods for interacting with the CNN website."""
def get_article(self, url):
"""Implementation for getting an article from CNN. Args: url: A URL in the www.cnn.* domain. Returns: The Article representing the article at that url."""
html = helpers.get_content(url)
if not ht... | the_stack_v2_python_sparse | analysis/scraping/cnn.py | pandrewhk/perspectives | train | 0 |
bc07131ea149006a74120c4bfb2dedbaef8abd60 | [
"try:\n for field in dataclasses.fields(self):\n setattr(self, field.name, field.type(env_file))\nexcept ValidationError as err:\n config_field = None\n first_error = err.errors()[0]\n loc: str = first_error['loc'][0]\n if loc != '__root__':\n settings_model = cast(BaseSettings, err.mod... | <|body_start_0|>
try:
for field in dataclasses.fields(self):
setattr(self, field.name, field.type(env_file))
except ValidationError as err:
config_field = None
first_error = err.errors()[0]
loc: str = first_error['loc'][0]
if lo... | Globally manage environment variables configuration options. | Settings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""Globally manage environment variables configuration options."""
def __init__(self, env_file: Optional[Path]=None) -> None:
"""Checks the validity of each configuration option. Args: env_file: Path to a file defining environment variables. Raises: ConfigError: A configura... | stack_v2_sparse_classes_75kplus_train_065087 | 6,638 | permissive | [
{
"docstring": "Checks the validity of each configuration option. Args: env_file: Path to a file defining environment variables. Raises: ConfigError: A configuration option is not valid.",
"name": "__init__",
"signature": "def __init__(self, env_file: Optional[Path]=None) -> None"
},
{
"docstrin... | 2 | stack_v2_sparse_classes_30k_train_021855 | Implement the Python class `Settings` described below.
Class description:
Globally manage environment variables configuration options.
Method signatures and docstrings:
- def __init__(self, env_file: Optional[Path]=None) -> None: Checks the validity of each configuration option. Args: env_file: Path to a file definin... | Implement the Python class `Settings` described below.
Class description:
Globally manage environment variables configuration options.
Method signatures and docstrings:
- def __init__(self, env_file: Optional[Path]=None) -> None: Checks the validity of each configuration option. Args: env_file: Path to a file definin... | 9e3370a7656b415058acf2d39a690a72f6eb343f | <|skeleton|>
class Settings:
"""Globally manage environment variables configuration options."""
def __init__(self, env_file: Optional[Path]=None) -> None:
"""Checks the validity of each configuration option. Args: env_file: Path to a file defining environment variables. Raises: ConfigError: A configura... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Settings:
"""Globally manage environment variables configuration options."""
def __init__(self, env_file: Optional[Path]=None) -> None:
"""Checks the validity of each configuration option. Args: env_file: Path to a file defining environment variables. Raises: ConfigError: A configuration option i... | the_stack_v2_python_sparse | src/opcua_webhmi_bridge/config.py | renovate-tests/opcua-webhmi-bridge | train | 0 |
d74496e1b176070fcd5d91b200a480c79cf17240 | [
"self.pairs = pairs\nself.change_types = change_types\nself.func = None\nself.funcname = None",
"assert isinstance(func, FunctionType), 'func must be a function'\nself.func = func\nreturn self",
"clone = type(self)(self.pairs, self.change_types)\nclone.func = self.func\nreturn clone"
] | <|body_start_0|>
self.pairs = pairs
self.change_types = change_types
self.func = None
self.funcname = None
<|end_body_0|>
<|body_start_1|>
assert isinstance(func, FunctionType), 'func must be a function'
self.func = func
return self
<|end_body_1|>
<|body_start_2... | An object used to temporarily store observe decorator state. | ObserveHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObserveHandler:
"""An object used to temporarily store observe decorator state."""
def __init__(self, pairs: List[Tuple[str, Optional[str]]], change_types: ChangeType=ChangeType.ANY) -> None:
"""Initialize an ObserveHandler. Parameters ---------- pairs : list The list of 2-tuples whi... | stack_v2_sparse_classes_75kplus_train_065088 | 5,816 | permissive | [
{
"docstring": "Initialize an ObserveHandler. Parameters ---------- pairs : list The list of 2-tuples which stores the pair information for the observers.",
"name": "__init__",
"signature": "def __init__(self, pairs: List[Tuple[str, Optional[str]]], change_types: ChangeType=ChangeType.ANY) -> None"
},... | 3 | stack_v2_sparse_classes_30k_train_007015 | Implement the Python class `ObserveHandler` described below.
Class description:
An object used to temporarily store observe decorator state.
Method signatures and docstrings:
- def __init__(self, pairs: List[Tuple[str, Optional[str]]], change_types: ChangeType=ChangeType.ANY) -> None: Initialize an ObserveHandler. Pa... | Implement the Python class `ObserveHandler` described below.
Class description:
An object used to temporarily store observe decorator state.
Method signatures and docstrings:
- def __init__(self, pairs: List[Tuple[str, Optional[str]]], change_types: ChangeType=ChangeType.ANY) -> None: Initialize an ObserveHandler. Pa... | 761a52821d8c77b5718216256963682d11599c1e | <|skeleton|>
class ObserveHandler:
"""An object used to temporarily store observe decorator state."""
def __init__(self, pairs: List[Tuple[str, Optional[str]]], change_types: ChangeType=ChangeType.ANY) -> None:
"""Initialize an ObserveHandler. Parameters ---------- pairs : list The list of 2-tuples whi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ObserveHandler:
"""An object used to temporarily store observe decorator state."""
def __init__(self, pairs: List[Tuple[str, Optional[str]]], change_types: ChangeType=ChangeType.ANY) -> None:
"""Initialize an ObserveHandler. Parameters ---------- pairs : list The list of 2-tuples which stores the... | the_stack_v2_python_sparse | atom/meta/observation.py | nucleic/atom | train | 251 |
fb31f14f3ff2b131f0fd7567f3d88a9125495202 | [
"assert isinstance(nb_topics, int)\nassert nb_topics > 0\nself.nb_topics = nb_topics",
"vectorizer = TfidfVectorizer(sublinear_tf=True, max_df=0.5, stop_words='english')\nbow = vectorizer.fit_transform(dataset.data)\nself.lda_model = LatentDirichletAllocation(n_components=self.nb_topics, random_state=0)\nX = self... | <|body_start_0|>
assert isinstance(nb_topics, int)
assert nb_topics > 0
self.nb_topics = nb_topics
<|end_body_0|>
<|body_start_1|>
vectorizer = TfidfVectorizer(sublinear_tf=True, max_df=0.5, stop_words='english')
bow = vectorizer.fit_transform(dataset.data)
self.lda_mode... | BOW_TopicModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BOW_TopicModel:
def __init__(self, nb_topics=10):
"""Class constructor. Args: nb_topics (int, optional): Number of topics for LDA."""
<|body_0|>
def extract_features(self, dataset):
"""Extract features using Bag-of-Words and then LDA (topic models). Each document is ... | stack_v2_sparse_classes_75kplus_train_065089 | 8,035 | no_license | [
{
"docstring": "Class constructor. Args: nb_topics (int, optional): Number of topics for LDA.",
"name": "__init__",
"signature": "def __init__(self, nb_topics=10)"
},
{
"docstring": "Extract features using Bag-of-Words and then LDA (topic models). Each document is represented as a n-dimensional ... | 2 | stack_v2_sparse_classes_30k_train_042590 | Implement the Python class `BOW_TopicModel` described below.
Class description:
Implement the BOW_TopicModel class.
Method signatures and docstrings:
- def __init__(self, nb_topics=10): Class constructor. Args: nb_topics (int, optional): Number of topics for LDA.
- def extract_features(self, dataset): Extract feature... | Implement the Python class `BOW_TopicModel` described below.
Class description:
Implement the BOW_TopicModel class.
Method signatures and docstrings:
- def __init__(self, nb_topics=10): Class constructor. Args: nb_topics (int, optional): Number of topics for LDA.
- def extract_features(self, dataset): Extract feature... | bfe9f8cb6eb7341c156131c62eaba96dbfe0adbb | <|skeleton|>
class BOW_TopicModel:
def __init__(self, nb_topics=10):
"""Class constructor. Args: nb_topics (int, optional): Number of topics for LDA."""
<|body_0|>
def extract_features(self, dataset):
"""Extract features using Bag-of-Words and then LDA (topic models). Each document is ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BOW_TopicModel:
def __init__(self, nb_topics=10):
"""Class constructor. Args: nb_topics (int, optional): Number of topics for LDA."""
assert isinstance(nb_topics, int)
assert nb_topics > 0
self.nb_topics = nb_topics
def extract_features(self, dataset):
"""Extract f... | the_stack_v2_python_sparse | feature_extraction/feature_extraction.py | LLNL/al_nlp | train | 11 | |
034b92b1e5caa2de4d4956e9849ba3439745074e | [
"super(RandPointCNN, self).__init__()\nself.pointcnn = PointCNN(cin, cout, dims, K, D, P)\nself.P = P\nif self.P > 0:\n self.sampler = FurthestPointSampler(self.P)",
"pts, fts = x\nif 0 < self.P < pts.size()[1]:\n rep_pts = self.sampler(pts)\nelse:\n rep_pts = pts\nrep_pts_fts = self.pointcnn((rep_pts, p... | <|body_start_0|>
super(RandPointCNN, self).__init__()
self.pointcnn = PointCNN(cin, cout, dims, K, D, P)
self.P = P
if self.P > 0:
self.sampler = FurthestPointSampler(self.P)
<|end_body_0|>
<|body_start_1|>
pts, fts = x
if 0 < self.P < pts.size()[1]:
... | PointCNN with randomly subsampled representative points. | RandPointCNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandPointCNN:
"""PointCNN with randomly subsampled representative points."""
def __init__(self, cin: int, cout: int, dims: int, K: int, D: int, P: int) -> None:
"""See documentation for PointCNN."""
<|body_0|>
def execute(self, x):
"""Given a point cloud, and its... | stack_v2_sparse_classes_75kplus_train_065090 | 18,458 | no_license | [
{
"docstring": "See documentation for PointCNN.",
"name": "__init__",
"signature": "def __init__(self, cin: int, cout: int, dims: int, K: int, D: int, P: int) -> None"
},
{
"docstring": "Given a point cloud, and its corresponding features, return a new set of randomly-sampled representative poin... | 2 | null | Implement the Python class `RandPointCNN` described below.
Class description:
PointCNN with randomly subsampled representative points.
Method signatures and docstrings:
- def __init__(self, cin: int, cout: int, dims: int, K: int, D: int, P: int) -> None: See documentation for PointCNN.
- def execute(self, x): Given a... | Implement the Python class `RandPointCNN` described below.
Class description:
PointCNN with randomly subsampled representative points.
Method signatures and docstrings:
- def __init__(self, cin: int, cout: int, dims: int, K: int, D: int, P: int) -> None: See documentation for PointCNN.
- def execute(self, x): Given a... | c0018e21ee1a93c0d9df2dde25144585d6e3ab49 | <|skeleton|>
class RandPointCNN:
"""PointCNN with randomly subsampled representative points."""
def __init__(self, cin: int, cout: int, dims: int, K: int, D: int, P: int) -> None:
"""See documentation for PointCNN."""
<|body_0|>
def execute(self, x):
"""Given a point cloud, and its... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RandPointCNN:
"""PointCNN with randomly subsampled representative points."""
def __init__(self, cin: int, cout: int, dims: int, K: int, D: int, P: int) -> None:
"""See documentation for PointCNN."""
super(RandPointCNN, self).__init__()
self.pointcnn = PointCNN(cin, cout, dims, K, ... | the_stack_v2_python_sparse | ops/layers.py | xiaoxTM/jittor-pcl | train | 0 |
6be83c96ffb945d97afdd6436caff882fe536388 | [
"super(BerkJones, self).__init__()\nassert 'direction' in kwargs.keys()\nassert 'alpha' in kwargs.keys()\nself.kwargs = kwargs",
"assert 'alpha' in self.kwargs.keys(), 'Warning: calling bj score without alpha'\nalpha = self.kwargs['alpha']\nif q < alpha:\n q = alpha\nassert q > 0, 'Warning: calling compute_sco... | <|body_start_0|>
super(BerkJones, self).__init__()
assert 'direction' in kwargs.keys()
assert 'alpha' in kwargs.keys()
self.kwargs = kwargs
<|end_body_0|>
<|body_start_1|>
assert 'alpha' in self.kwargs.keys(), 'Warning: calling bj score without alpha'
alpha = self.kwargs... | BerkJones | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BerkJones:
def __init__(self, **kwargs):
"""Berk-Jones score function is a non parametric expectatation based scan statistic that also satisfies the ALTSS property; Non-parametric scoring functions do not make parametric assumptions about the model or outcome [1]. kwargs must contain 'di... | stack_v2_sparse_classes_75kplus_train_065091 | 4,161 | permissive | [
{
"docstring": "Berk-Jones score function is a non parametric expectatation based scan statistic that also satisfies the ALTSS property; Non-parametric scoring functions do not make parametric assumptions about the model or outcome [1]. kwargs must contain 'direction (str)' - direction of the severity; could be... | 4 | null | Implement the Python class `BerkJones` described below.
Class description:
Implement the BerkJones class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Berk-Jones score function is a non parametric expectatation based scan statistic that also satisfies the ALTSS property; Non-parametric scoring fu... | Implement the Python class `BerkJones` described below.
Class description:
Implement the BerkJones class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Berk-Jones score function is a non parametric expectatation based scan statistic that also satisfies the ALTSS property; Non-parametric scoring fu... | 0ddf84fbe456feef0570dfe0d714d6656a18d9ca | <|skeleton|>
class BerkJones:
def __init__(self, **kwargs):
"""Berk-Jones score function is a non parametric expectatation based scan statistic that also satisfies the ALTSS property; Non-parametric scoring functions do not make parametric assumptions about the model or outcome [1]. kwargs must contain 'di... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BerkJones:
def __init__(self, **kwargs):
"""Berk-Jones score function is a non parametric expectatation based scan statistic that also satisfies the ALTSS property; Non-parametric scoring functions do not make parametric assumptions about the model or outcome [1]. kwargs must contain 'direction (str)'... | the_stack_v2_python_sparse | aif360/metrics/mdss/ScoringFunctions/BerkJones.py | SumaiyaSaima05/AIF360 | train | 1 | |
afbf0983e90d9efac98652276eec985fadbb9700 | [
"super(RelativePosition, self).__init__()\nself.num_units = num_units\nself.device = device\nself.max_relative_position = max_relative_position\nself.embeddings_table = nn.Parameter(torch.Tensor(max_relative_position * 2 + 1, num_units))\nnn.init.xavier_uniform_(self.embeddings_table)",
"range_vec_q = torch.arang... | <|body_start_0|>
super(RelativePosition, self).__init__()
self.num_units = num_units
self.device = device
self.max_relative_position = max_relative_position
self.embeddings_table = nn.Parameter(torch.Tensor(max_relative_position * 2 + 1, num_units))
nn.init.xavier_uniform... | RelativePosition | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelativePosition:
def __init__(self, num_units, max_relative_position, device=None):
""":param num_units: d_a :param max_relative_position: k"""
<|body_0|>
def forward(self, length_q, length_k):
"""for self-att: length_q == length_k == length_x return: embeddings: le... | stack_v2_sparse_classes_75kplus_train_065092 | 1,268 | no_license | [
{
"docstring": ":param num_units: d_a :param max_relative_position: k",
"name": "__init__",
"signature": "def __init__(self, num_units, max_relative_position, device=None)"
},
{
"docstring": "for self-att: length_q == length_k == length_x return: embeddings: length_q x length_k x d_a",
"name... | 2 | stack_v2_sparse_classes_30k_train_017706 | Implement the Python class `RelativePosition` described below.
Class description:
Implement the RelativePosition class.
Method signatures and docstrings:
- def __init__(self, num_units, max_relative_position, device=None): :param num_units: d_a :param max_relative_position: k
- def forward(self, length_q, length_k): ... | Implement the Python class `RelativePosition` described below.
Class description:
Implement the RelativePosition class.
Method signatures and docstrings:
- def __init__(self, num_units, max_relative_position, device=None): :param num_units: d_a :param max_relative_position: k
- def forward(self, length_q, length_k): ... | 1bfff12c6b03f64f57d118b435c0040431befcdf | <|skeleton|>
class RelativePosition:
def __init__(self, num_units, max_relative_position, device=None):
""":param num_units: d_a :param max_relative_position: k"""
<|body_0|>
def forward(self, length_q, length_k):
"""for self-att: length_q == length_k == length_x return: embeddings: le... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RelativePosition:
def __init__(self, num_units, max_relative_position, device=None):
""":param num_units: d_a :param max_relative_position: k"""
super(RelativePosition, self).__init__()
self.num_units = num_units
self.device = device
self.max_relative_position = max_rel... | the_stack_v2_python_sparse | nag/modules/relative_position.py | liu-hz18/Non-Autoregressive-Neural-Dialogue-Generation | train | 0 | |
433543da97e5ffe525fb8081ad2d368aa34e01bf | [
"self.spectrum = spectrum\nself.possiblePeptides = []\nself.aaMass = {'G': 57, 'A': 71, 'S': 87, 'P': 97, 'V': 99, 'T': 101, 'C': 103, 'I': 113, 'L': 113, 'N': 114, 'D': 115, 'K': 128, 'Q': 128, 'E': 129, 'M': 131, 'H': 137, 'F': 147, 'R': 156, 'Y': 163, 'W': 186}\nself.aaList = list(self.aaMass)",
"sortedSpectru... | <|body_start_0|>
self.spectrum = spectrum
self.possiblePeptides = []
self.aaMass = {'G': 57, 'A': 71, 'S': 87, 'P': 97, 'V': 99, 'T': 101, 'C': 103, 'I': 113, 'L': 113, 'N': 114, 'D': 115, 'K': 128, 'Q': 128, 'E': 129, 'M': 131, 'H': 137, 'F': 147, 'R': 156, 'Y': 163, 'W': 186}
self.aaLi... | Program to find a Cyclic Peptide with a Theoretical Spectrum Matching an Ideal Spectrum given A collection of (possibly repeated) integers Spectrum corresponding to an ideal experimental spectrum. | TheoPepCyclic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TheoPepCyclic:
"""Program to find a Cyclic Peptide with a Theoretical Spectrum Matching an Ideal Spectrum given A collection of (possibly repeated) integers Spectrum corresponding to an ideal experimental spectrum."""
def __init__(self, spectrum):
"""Create a constructor to hold impo... | stack_v2_sparse_classes_75kplus_train_065093 | 7,890 | no_license | [
{
"docstring": "Create a constructor to hold important data and tables.",
"name": "__init__",
"signature": "def __init__(self, spectrum)"
},
{
"docstring": "Create possible peptide strings given the input spectrum",
"name": "matchTheoretical",
"signature": "def matchTheoretical(self)"
... | 6 | null | Implement the Python class `TheoPepCyclic` described below.
Class description:
Program to find a Cyclic Peptide with a Theoretical Spectrum Matching an Ideal Spectrum given A collection of (possibly repeated) integers Spectrum corresponding to an ideal experimental spectrum.
Method signatures and docstrings:
- def __... | Implement the Python class `TheoPepCyclic` described below.
Class description:
Program to find a Cyclic Peptide with a Theoretical Spectrum Matching an Ideal Spectrum given A collection of (possibly repeated) integers Spectrum corresponding to an ideal experimental spectrum.
Method signatures and docstrings:
- def __... | efe83914cbe193c151504a1b2fe81b8b53055816 | <|skeleton|>
class TheoPepCyclic:
"""Program to find a Cyclic Peptide with a Theoretical Spectrum Matching an Ideal Spectrum given A collection of (possibly repeated) integers Spectrum corresponding to an ideal experimental spectrum."""
def __init__(self, spectrum):
"""Create a constructor to hold impo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TheoPepCyclic:
"""Program to find a Cyclic Peptide with a Theoretical Spectrum Matching an Ideal Spectrum given A collection of (possibly repeated) integers Spectrum corresponding to an ideal experimental spectrum."""
def __init__(self, spectrum):
"""Create a constructor to hold important data an... | the_stack_v2_python_sparse | cyclicPepTheoIdeal.py | zmmason/BINF | train | 6 |
e936fa99361410dd4af805eacb81c0ed88056446 | [
"tf.compat.v1.logging.info('Initializing Subtokenizer from file %s.' % vocab_file)\nif reserved_tokens is None:\n reserved_tokens = RESERVED_TOKENS\nself.subtoken_list = _load_vocab_file(vocab_file, reserved_tokens)\nself.alphabet = _generate_alphabet_dict(self.subtoken_list)\nself.subtoken_to_id_dict = _list_to... | <|body_start_0|>
tf.compat.v1.logging.info('Initializing Subtokenizer from file %s.' % vocab_file)
if reserved_tokens is None:
reserved_tokens = RESERVED_TOKENS
self.subtoken_list = _load_vocab_file(vocab_file, reserved_tokens)
self.alphabet = _generate_alphabet_dict(self.sub... | Encodes and decodes strings to/from integer IDs. | Subtokenizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Subtokenizer:
"""Encodes and decodes strings to/from integer IDs."""
def __init__(self, vocab_file, reserved_tokens=None):
"""Initializes class, creating a vocab file if data_files is provided."""
<|body_0|>
def init_from_files(vocab_file, files, target_vocab_size, thres... | stack_v2_sparse_classes_75kplus_train_065094 | 22,774 | permissive | [
{
"docstring": "Initializes class, creating a vocab file if data_files is provided.",
"name": "__init__",
"signature": "def __init__(self, vocab_file, reserved_tokens=None)"
},
{
"docstring": "Create subtoken vocabulary based on files, and save vocab to file. Args: vocab_file: String name of voc... | 6 | stack_v2_sparse_classes_30k_train_005548 | Implement the Python class `Subtokenizer` described below.
Class description:
Encodes and decodes strings to/from integer IDs.
Method signatures and docstrings:
- def __init__(self, vocab_file, reserved_tokens=None): Initializes class, creating a vocab file if data_files is provided.
- def init_from_files(vocab_file,... | Implement the Python class `Subtokenizer` described below.
Class description:
Encodes and decodes strings to/from integer IDs.
Method signatures and docstrings:
- def __init__(self, vocab_file, reserved_tokens=None): Initializes class, creating a vocab file if data_files is provided.
- def init_from_files(vocab_file,... | 9304c9f59fde013f158ac338fc80171c0e8cda5d | <|skeleton|>
class Subtokenizer:
"""Encodes and decodes strings to/from integer IDs."""
def __init__(self, vocab_file, reserved_tokens=None):
"""Initializes class, creating a vocab file if data_files is provided."""
<|body_0|>
def init_from_files(vocab_file, files, target_vocab_size, thres... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Subtokenizer:
"""Encodes and decodes strings to/from integer IDs."""
def __init__(self, vocab_file, reserved_tokens=None):
"""Initializes class, creating a vocab file if data_files is provided."""
tf.compat.v1.logging.info('Initializing Subtokenizer from file %s.' % vocab_file)
if... | the_stack_v2_python_sparse | models/language_translation/tensorflow/transformer_mlperf/inference/int8/transformer/utils/tokenizer.py | IntelAI/models | train | 609 |
582bb4478416b2b8adee7f63908cb3a9f47d2224 | [
"self.cfg = ConfigParser.ConfigParser()\nself.configfile = configfile\nself.profile_name = profile_name\nself.args = args\nif self.profile_name != 'default':\n self.profile_name = 'profile ' + profile_name\nself.options = {'action': 'create', 'audit': 'NoopAudit', 'audit_output': None, 'output': 'BaseOutput', 'p... | <|body_start_0|>
self.cfg = ConfigParser.ConfigParser()
self.configfile = configfile
self.profile_name = profile_name
self.args = args
if self.profile_name != 'default':
self.profile_name = 'profile ' + profile_name
self.options = {'action': 'create', 'audit':... | Config class responsible to assemble config from files, defaults and command line arguments. | PMCFConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PMCFConfig:
"""Config class responsible to assemble config from files, defaults and command line arguments."""
def __init__(self, configfile, profile_name, args):
"""Constructor :param configfile: Path to configuration file :type configfile: str. :param profile_name: Profile in confi... | stack_v2_sparse_classes_75kplus_train_065095 | 3,945 | permissive | [
{
"docstring": "Constructor :param configfile: Path to configuration file :type configfile: str. :param profile_name: Profile in configuration file :type profile_name: str. :param args: command line arguments :type args: dict.",
"name": "__init__",
"signature": "def __init__(self, configfile, profile_na... | 3 | null | Implement the Python class `PMCFConfig` described below.
Class description:
Config class responsible to assemble config from files, defaults and command line arguments.
Method signatures and docstrings:
- def __init__(self, configfile, profile_name, args): Constructor :param configfile: Path to configuration file :ty... | Implement the Python class `PMCFConfig` described below.
Class description:
Config class responsible to assemble config from files, defaults and command line arguments.
Method signatures and docstrings:
- def __init__(self, configfile, profile_name, args): Constructor :param configfile: Path to configuration file :ty... | ce504286546c78fdd28145d8c413635e5df6f2bc | <|skeleton|>
class PMCFConfig:
"""Config class responsible to assemble config from files, defaults and command line arguments."""
def __init__(self, configfile, profile_name, args):
"""Constructor :param configfile: Path to configuration file :type configfile: str. :param profile_name: Profile in confi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PMCFConfig:
"""Config class responsible to assemble config from files, defaults and command line arguments."""
def __init__(self, configfile, profile_name, args):
"""Constructor :param configfile: Path to configuration file :type configfile: str. :param profile_name: Profile in configuration file... | the_stack_v2_python_sparse | pmcf/config/config.py | ktechmidas/pmcf | train | 0 |
078188bde352e46d3c871a6e7fee54c9afae3677 | [
"user = User.objects.get(pk=int(request.data['id']))\nif models.MovieRating.objects.filter(rating_user=user.movie_user, movie=Movie.objects.get(pk=int(request.data['movie']))).exists():\n movie_rating = models.MovieRating.objects.get(rating_user=user.movie_user, movie=Movie.objects.get(pk=int(request.data['movie... | <|body_start_0|>
user = User.objects.get(pk=int(request.data['id']))
if models.MovieRating.objects.filter(rating_user=user.movie_user, movie=Movie.objects.get(pk=int(request.data['movie']))).exists():
movie_rating = models.MovieRating.objects.get(rating_user=user.movie_user, movie=Movie.obje... | MovieRatingViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovieRatingViewSet:
def new(self, request):
"""Adds a new rating for the user on the given media. Updates the user model embedding which updates the user's predictions. :param request: /movies/ratings/new/ -- 'id': int (user id), 'movie': int (movieId), 'rating': float :return Response w... | stack_v2_sparse_classes_75kplus_train_065096 | 4,372 | no_license | [
{
"docstring": "Adds a new rating for the user on the given media. Updates the user model embedding which updates the user's predictions. :param request: /movies/ratings/new/ -- 'id': int (user id), 'movie': int (movieId), 'rating': float :return Response with status",
"name": "new",
"signature": "def n... | 2 | null | Implement the Python class `MovieRatingViewSet` described below.
Class description:
Implement the MovieRatingViewSet class.
Method signatures and docstrings:
- def new(self, request): Adds a new rating for the user on the given media. Updates the user model embedding which updates the user's predictions. :param reque... | Implement the Python class `MovieRatingViewSet` described below.
Class description:
Implement the MovieRatingViewSet class.
Method signatures and docstrings:
- def new(self, request): Adds a new rating for the user on the given media. Updates the user model embedding which updates the user's predictions. :param reque... | 0f9bbea2eef25a58bf80433ae8c8960684bdfbfa | <|skeleton|>
class MovieRatingViewSet:
def new(self, request):
"""Adds a new rating for the user on the given media. Updates the user model embedding which updates the user's predictions. :param request: /movies/ratings/new/ -- 'id': int (user id), 'movie': int (movieId), 'rating': float :return Response w... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MovieRatingViewSet:
def new(self, request):
"""Adds a new rating for the user on the given media. Updates the user model embedding which updates the user's predictions. :param request: /movies/ratings/new/ -- 'id': int (user id), 'movie': int (movieId), 'rating': float :return Response with status"""
... | the_stack_v2_python_sparse | MediaRecommendationServer/app/ratings/views.py | sorennelson/MediaRecommendation | train | 0 | |
0041e6accad1eebd88a6aebd56eec5978ba9b777 | [
"low, high = (0, len(nums) - 1)\nwhile low <= high:\n mid = low + (high - low) // 2\n if nums[mid] == target:\n return mid\n elif nums[mid] > target:\n high = mid - 1\n else:\n low = mid + 1\nreturn None",
"if len(nums) <= 1:\n return 0\nlow, high = (0, len(nums) - 1)\nwhile lo... | <|body_start_0|>
low, high = (0, len(nums) - 1)
while low <= high:
mid = low + (high - low) // 2
if nums[mid] == target:
return mid
elif nums[mid] > target:
high = mid - 1
else:
low = mid + 1
return N... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def binary_search(self, nums, target):
"""二分查找 :param nums: :param target: :return:"""
<|body_0|>
def find_rotate_index(self, nums):
"""二分法查找分割点 :param nums: :return:"""
<|body_1|>
def search(self, nums, target):
""":type nums: List[int... | stack_v2_sparse_classes_75kplus_train_065097 | 2,319 | no_license | [
{
"docstring": "二分查找 :param nums: :param target: :return:",
"name": "binary_search",
"signature": "def binary_search(self, nums, target)"
},
{
"docstring": "二分法查找分割点 :param nums: :return:",
"name": "find_rotate_index",
"signature": "def find_rotate_index(self, nums)"
},
{
"docstr... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def binary_search(self, nums, target): 二分查找 :param nums: :param target: :return:
- def find_rotate_index(self, nums): 二分法查找分割点 :param nums: :return:
- def search(self, nums, targ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def binary_search(self, nums, target): 二分查找 :param nums: :param target: :return:
- def find_rotate_index(self, nums): 二分法查找分割点 :param nums: :return:
- def search(self, nums, targ... | 3b13b36f37eb364410b3b5b4f10a1808d8b1111e | <|skeleton|>
class Solution:
def binary_search(self, nums, target):
"""二分查找 :param nums: :param target: :return:"""
<|body_0|>
def find_rotate_index(self, nums):
"""二分法查找分割点 :param nums: :return:"""
<|body_1|>
def search(self, nums, target):
""":type nums: List[int... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def binary_search(self, nums, target):
"""二分查找 :param nums: :param target: :return:"""
low, high = (0, len(nums) - 1)
while low <= high:
mid = low + (high - low) // 2
if nums[mid] == target:
return mid
elif nums[mid] > targe... | the_stack_v2_python_sparse | leetcode/33.py | yanggelinux/algorithm-data-structure | train | 0 | |
2fda368ca43c860a7eb63f90972ade3e30a66517 | [
"ana_id = super(hr_department, self).create(vals)\nif self.manager_id.id != False and self.analytic_account_id.id != False:\n self.analytic_account_id.write({'user_id': self.manager_id.user_id.id})\nreturn ana_id",
"ana_id = super(hr_department, self).write(vals)\nif self.manager_id.id != False and self.analyt... | <|body_start_0|>
ana_id = super(hr_department, self).create(vals)
if self.manager_id.id != False and self.analytic_account_id.id != False:
self.analytic_account_id.write({'user_id': self.manager_id.user_id.id})
return ana_id
<|end_body_0|>
<|body_start_1|>
ana_id = super(hr_... | inherit hr.department model | hr_department | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class hr_department:
"""inherit hr.department model"""
def create(self, vals):
"""override create function to set resposeble of department's analytic account equals to department's manager"""
<|body_0|>
def write(self, vals):
"""override write function to set resposebl... | stack_v2_sparse_classes_75kplus_train_065098 | 926 | no_license | [
{
"docstring": "override create function to set resposeble of department's analytic account equals to department's manager",
"name": "create",
"signature": "def create(self, vals)"
},
{
"docstring": "override write function to set resposeble of department's analytic account equals to department'... | 2 | stack_v2_sparse_classes_30k_train_033948 | Implement the Python class `hr_department` described below.
Class description:
inherit hr.department model
Method signatures and docstrings:
- def create(self, vals): override create function to set resposeble of department's analytic account equals to department's manager
- def write(self, vals): override write func... | Implement the Python class `hr_department` described below.
Class description:
inherit hr.department model
Method signatures and docstrings:
- def create(self, vals): override create function to set resposeble of department's analytic account equals to department's manager
- def write(self, vals): override write func... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class hr_department:
"""inherit hr.department model"""
def create(self, vals):
"""override create function to set resposeble of department's analytic account equals to department's manager"""
<|body_0|>
def write(self, vals):
"""override write function to set resposebl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class hr_department:
"""inherit hr.department model"""
def create(self, vals):
"""override create function to set resposeble of department's analytic account equals to department's manager"""
ana_id = super(hr_department, self).create(vals)
if self.manager_id.id != False and self.analyt... | the_stack_v2_python_sparse | v_11/EBS-SVN/trunk/account_budget_ebs/models/departmentAccount_custom.py | musabahmed/baba | train | 0 |
b39ab5d569f8cafa772dd4f557213bc1879d4603 | [
"self._GoalFrameId = '/map'\nself._GoalsFilePath = filePath\nwith open(filePath, 'r') as file:\n goals = []\n while True:\n goal = self._ReadNextGoalSection(file)\n if goal is None:\n break\n goals.append(goal)\n file.readline()\nreturn (self._GoalFrameId, goals)",
"fo... | <|body_start_0|>
self._GoalFrameId = '/map'
self._GoalsFilePath = filePath
with open(filePath, 'r') as file:
goals = []
while True:
goal = self._ReadNextGoalSection(file)
if goal is None:
break
goals.appe... | Helper class for extracting goals from a text file that contains the output of the ros topic /move_base/goal: rostopic echo /move_base/goal > ./goals.txt Content looks like this: header: seq: 5 stamp: secs: 1327888889 nsecs: 905062316 frame_id: '' goal_id: stamp: secs: 0 nsecs: 0 id: '' goal: target_pose: header: seq: ... | RecordedGoalsParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecordedGoalsParser:
"""Helper class for extracting goals from a text file that contains the output of the ros topic /move_base/goal: rostopic echo /move_base/goal > ./goals.txt Content looks like this: header: seq: 5 stamp: secs: 1327888889 nsecs: 905062316 frame_id: '' goal_id: stamp: secs: 0 n... | stack_v2_sparse_classes_75kplus_train_065099 | 11,034 | permissive | [
{
"docstring": "Parses the specified file and returns the extracted frame id and the array of goal poses: (frame_id, [(x,y,theta)])",
"name": "Parse",
"signature": "def Parse(self, filePath)"
},
{
"docstring": "Reads a section of the file that needs to be structured like this: header: seq: 5 sta... | 3 | stack_v2_sparse_classes_30k_val_002574 | Implement the Python class `RecordedGoalsParser` described below.
Class description:
Helper class for extracting goals from a text file that contains the output of the ros topic /move_base/goal: rostopic echo /move_base/goal > ./goals.txt Content looks like this: header: seq: 5 stamp: secs: 1327888889 nsecs: 905062316... | Implement the Python class `RecordedGoalsParser` described below.
Class description:
Helper class for extracting goals from a text file that contains the output of the ros topic /move_base/goal: rostopic echo /move_base/goal > ./goals.txt Content looks like this: header: seq: 5 stamp: secs: 1327888889 nsecs: 905062316... | 48d9144293d1b604969ca1208fb813939e935ed9 | <|skeleton|>
class RecordedGoalsParser:
"""Helper class for extracting goals from a text file that contains the output of the ros topic /move_base/goal: rostopic echo /move_base/goal > ./goals.txt Content looks like this: header: seq: 5 stamp: secs: 1327888889 nsecs: 905062316 frame_id: '' goal_id: stamp: secs: 0 n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RecordedGoalsParser:
"""Helper class for extracting goals from a text file that contains the output of the ros topic /move_base/goal: rostopic echo /move_base/goal > ./goals.txt Content looks like this: header: seq: 5 stamp: secs: 1327888889 nsecs: 905062316 frame_id: '' goal_id: stamp: secs: 0 nsecs: 0 id: '... | the_stack_v2_python_sparse | Chapter09/chefbot_code/chefbot_bringup/scripts/bkup_working/GoalsSequencer.py | PacktPublishing/ROS-Robotics-Projects | train | 149 |
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