blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 467 8.64k | id stringlengths 40 40 | length_bytes int64 515 49.7k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
64fe7e624a47662c42b5c6cd7c74b4a4671cf300 | [
"d_collected_int = math.floor(days_collected)\nend_time = end_time or datetime.utcnow()\nearliest = end_time - timedelta(days=days_collected)\nself.avg_calculatable: bool = d_collected_int > HourlyResult.DAYS_NONE\nself.denom: List[float] = []\nif self.avg_calculatable:\n add_one_end = end_time.hour\n if earl... | <|body_start_0|>
d_collected_int = math.floor(days_collected)
end_time = end_time or datetime.utcnow()
earliest = end_time - timedelta(days=days_collected)
self.avg_calculatable: bool = d_collected_int > HourlyResult.DAYS_NONE
self.denom: List[float] = []
if self.avg_calc... | Base hourly result object. **Fields** ``avg_calculatable`` If this result can be used to calculate daily average. ``denom`` Denominators to divide the accumulated result number. Will be an empty list if ``avg_calculatable`` is ``False``. | HourlyResult | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HourlyResult:
"""Base hourly result object. **Fields** ``avg_calculatable`` If this result can be used to calculate daily average. ``denom`` Denominators to divide the accumulated result number. Will be an empty list if ``avg_calculatable`` is ``False``."""
def __init__(self, days_collected:... | stack_v2_sparse_classes_10k_train_008300 | 6,459 | permissive | [
{
"docstring": "Initalizing method of :class:`HourlyResult`. :param days_collected: \"claimed\" days collected of the data :param end_time: end time of the data. current time in UTC if not given",
"name": "__init__",
"signature": "def __init__(self, days_collected: float, *, end_time: Optional[datetime]... | 2 | stack_v2_sparse_classes_30k_train_001415 | Implement the Python class `HourlyResult` described below.
Class description:
Base hourly result object. **Fields** ``avg_calculatable`` If this result can be used to calculate daily average. ``denom`` Denominators to divide the accumulated result number. Will be an empty list if ``avg_calculatable`` is ``False``.
Me... | Implement the Python class `HourlyResult` described below.
Class description:
Base hourly result object. **Fields** ``avg_calculatable`` If this result can be used to calculate daily average. ``denom`` Denominators to divide the accumulated result number. Will be an empty list if ``avg_calculatable`` is ``False``.
Me... | c7da1e91783dce3a2b71b955b3a22b68db9056cf | <|skeleton|>
class HourlyResult:
"""Base hourly result object. **Fields** ``avg_calculatable`` If this result can be used to calculate daily average. ``denom`` Denominators to divide the accumulated result number. Will be an empty list if ``avg_calculatable`` is ``False``."""
def __init__(self, days_collected:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HourlyResult:
"""Base hourly result object. **Fields** ``avg_calculatable`` If this result can be used to calculate daily average. ``denom`` Denominators to divide the accumulated result number. Will be an empty list if ``avg_calculatable`` is ``False``."""
def __init__(self, days_collected: float, *, en... | the_stack_v2_python_sparse | models/stats/base.py | RxJellyBot/Jelly-Bot | train | 5 |
a24fd9e3332d60a70c72263725aa8fc42f9bb77c | [
"queue = deque()\nif root:\n queue.append(root)\ns = []\nwhile len(queue) > 0:\n node = queue.popleft()\n if node is None:\n s.append('null')\n else:\n s.append(str(node.val))\n queue.append(node.left)\n queue.append(node.right)\nreturn ','.join(s)",
"ss = data.split(',')\n... | <|body_start_0|>
queue = deque()
if root:
queue.append(root)
s = []
while len(queue) > 0:
node = queue.popleft()
if node is None:
s.append('null')
else:
s.append(str(node.val))
queue.append(no... | Codec_BFS | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec_BFS:
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|>
<|b... | stack_v2_sparse_classes_10k_train_008301 | 5,078 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec_BFS` described below.
Class description:
Implement the Codec_BFS 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... | Implement the Python class `Codec_BFS` described below.
Class description:
Implement the Codec_BFS 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... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Codec_BFS:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec_BFS:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
queue = deque()
if root:
queue.append(root)
s = []
while len(queue) > 0:
node = queue.popleft()
if node is None:
... | the_stack_v2_python_sparse | code297SerializeAndDeserializeBinaryTree.py | cybelewang/leetcode-python | train | 0 | |
02e059cf0d98f794d181458bfc60acc71721c38a | [
"assert isinstance(entityCount, int)\nassert entityCount >= 2\nself.entityCount = entityCount\nassert acceptedEntityTypes is None or isinstance(acceptedEntityTypes, list)\nif acceptedEntityTypes is None:\n self.acceptedEntityTypes = None\nelse:\n for acceptedEntityType in acceptedEntityTypes:\n assert ... | <|body_start_0|>
assert isinstance(entityCount, int)
assert entityCount >= 2
self.entityCount = entityCount
assert acceptedEntityTypes is None or isinstance(acceptedEntityTypes, list)
if acceptedEntityTypes is None:
self.acceptedEntityTypes = None
else:
... | Generates set of all possible relations in corpus. :ivar entityCount: Number of entities in each relation (default=2) :ivar acceptedEntityTypes: Tuples of entities that candidate relations must match. Each entity should be the same length as entityCount. None will match all candidate relations. | CandidateBuilder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CandidateBuilder:
"""Generates set of all possible relations in corpus. :ivar entityCount: Number of entities in each relation (default=2) :ivar acceptedEntityTypes: Tuples of entities that candidate relations must match. Each entity should be the same length as entityCount. None will match all c... | stack_v2_sparse_classes_10k_train_008302 | 2,967 | permissive | [
{
"docstring": "Constructor :param entityCount: Number of entities in each relation (default=2) :param acceptedEntityTypes: Tuples of entities that candidate relations must match. Each entity should be the same length as entityCount. None will match all candidate relations. :type entityCount: int :type accepted... | 2 | stack_v2_sparse_classes_30k_train_005090 | Implement the Python class `CandidateBuilder` described below.
Class description:
Generates set of all possible relations in corpus. :ivar entityCount: Number of entities in each relation (default=2) :ivar acceptedEntityTypes: Tuples of entities that candidate relations must match. Each entity should be the same lengt... | Implement the Python class `CandidateBuilder` described below.
Class description:
Generates set of all possible relations in corpus. :ivar entityCount: Number of entities in each relation (default=2) :ivar acceptedEntityTypes: Tuples of entities that candidate relations must match. Each entity should be the same lengt... | b6eac60fa40086b4c44e98e0baa34b760310d284 | <|skeleton|>
class CandidateBuilder:
"""Generates set of all possible relations in corpus. :ivar entityCount: Number of entities in each relation (default=2) :ivar acceptedEntityTypes: Tuples of entities that candidate relations must match. Each entity should be the same length as entityCount. None will match all c... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CandidateBuilder:
"""Generates set of all possible relations in corpus. :ivar entityCount: Number of entities in each relation (default=2) :ivar acceptedEntityTypes: Tuples of entities that candidate relations must match. Each entity should be the same length as entityCount. None will match all candidate rela... | the_stack_v2_python_sparse | kindred/CandidateBuilder.py | jakelever/kindred | train | 158 |
2b3d9dee1a08c017f17e621e995a8ecd1e8aed43 | [
"mol = Chem.MolFromSmiles(smiles)\nengine = ScaffoldGenerator(include_chirality=include_chirality)\nscaffold = engine.get_scaffold(mol)\nreturn scaffold",
"np.testing.assert_almost_equal(frac_train + frac_valid + frac_test, 1.0)\nscaffolds = {}\nlog('About to generate scaffolds', self.verbose)\ndata_len = len(dat... | <|body_start_0|>
mol = Chem.MolFromSmiles(smiles)
engine = ScaffoldGenerator(include_chirality=include_chirality)
scaffold = engine.get_scaffold(mol)
return scaffold
<|end_body_0|>
<|body_start_1|>
np.testing.assert_almost_equal(frac_train + frac_valid + frac_test, 1.0)
... | Class for doing data splits based on the scaffold of small molecules. | ScaffoldSplitter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScaffoldSplitter:
"""Class for doing data splits based on the scaffold of small molecules."""
def generate_scaffold(self, smiles, include_chirality=False):
"""Compute the Bemis-Murcko scaffold for a SMILES string."""
<|body_0|>
def split(self, dataset, frac_train=0.5, fr... | stack_v2_sparse_classes_10k_train_008303 | 3,303 | no_license | [
{
"docstring": "Compute the Bemis-Murcko scaffold for a SMILES string.",
"name": "generate_scaffold",
"signature": "def generate_scaffold(self, smiles, include_chirality=False)"
},
{
"docstring": "Splits internal compounds into train/validation/test by scaffold.",
"name": "split",
"signa... | 2 | stack_v2_sparse_classes_30k_train_004625 | Implement the Python class `ScaffoldSplitter` described below.
Class description:
Class for doing data splits based on the scaffold of small molecules.
Method signatures and docstrings:
- def generate_scaffold(self, smiles, include_chirality=False): Compute the Bemis-Murcko scaffold for a SMILES string.
- def split(s... | Implement the Python class `ScaffoldSplitter` described below.
Class description:
Class for doing data splits based on the scaffold of small molecules.
Method signatures and docstrings:
- def generate_scaffold(self, smiles, include_chirality=False): Compute the Bemis-Murcko scaffold for a SMILES string.
- def split(s... | 57e40d04181059ca39890d22361606edfadcc930 | <|skeleton|>
class ScaffoldSplitter:
"""Class for doing data splits based on the scaffold of small molecules."""
def generate_scaffold(self, smiles, include_chirality=False):
"""Compute the Bemis-Murcko scaffold for a SMILES string."""
<|body_0|>
def split(self, dataset, frac_train=0.5, fr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ScaffoldSplitter:
"""Class for doing data splits based on the scaffold of small molecules."""
def generate_scaffold(self, smiles, include_chirality=False):
"""Compute the Bemis-Murcko scaffold for a SMILES string."""
mol = Chem.MolFromSmiles(smiles)
engine = ScaffoldGenerator(incl... | the_stack_v2_python_sparse | utils/splitter/scaffoldsplitter.py | moguizhizi/Adaptive-Graph-Convolutional-Network | train | 0 |
7c3f55e49c21ef73190fc2778eb1d36ff10ffde9 | [
"def dfs(i, remains: List[int]):\n if i == n + 1:\n return 1\n cnt = 0\n for j in range(1, n + 1):\n if remains[j] is None and (i % j == 0 or j % i == 0):\n remains[j] = i\n cnt += dfs(i + 1, remains)\n remains[j] = None\n return cnt\nreturn dfs(1, [None] *... | <|body_start_0|>
def dfs(i, remains: List[int]):
if i == n + 1:
return 1
cnt = 0
for j in range(1, n + 1):
if remains[j] is None and (i % j == 0 or j % i == 0):
remains[j] = i
cnt += dfs(i + 1, remains)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countArrangement(self, n: int) -> int:
"""DFS using a list"""
<|body_0|>
def countArrangement(self, n: int) -> int:
"""DFS using a binary number to make argument hashable for caching"""
<|body_1|>
def countArrangement(self, n: int) -> int:
... | stack_v2_sparse_classes_10k_train_008304 | 2,867 | no_license | [
{
"docstring": "DFS using a list",
"name": "countArrangement",
"signature": "def countArrangement(self, n: int) -> int"
},
{
"docstring": "DFS using a binary number to make argument hashable for caching",
"name": "countArrangement",
"signature": "def countArrangement(self, n: int) -> int... | 3 | stack_v2_sparse_classes_30k_val_000246 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countArrangement(self, n: int) -> int: DFS using a list
- def countArrangement(self, n: int) -> int: DFS using a binary number to make argument hashable for caching
- def cou... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countArrangement(self, n: int) -> int: DFS using a list
- def countArrangement(self, n: int) -> int: DFS using a binary number to make argument hashable for caching
- def cou... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def countArrangement(self, n: int) -> int:
"""DFS using a list"""
<|body_0|>
def countArrangement(self, n: int) -> int:
"""DFS using a binary number to make argument hashable for caching"""
<|body_1|>
def countArrangement(self, n: int) -> int:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def countArrangement(self, n: int) -> int:
"""DFS using a list"""
def dfs(i, remains: List[int]):
if i == n + 1:
return 1
cnt = 0
for j in range(1, n + 1):
if remains[j] is None and (i % j == 0 or j % i == 0):
... | the_stack_v2_python_sparse | leetcode/solved/526_Beautiful_Arrangement/solution.py | sungminoh/algorithms | train | 0 | |
ba9c3d93f21944a4b7f6dbf60a31d7663516af06 | [
"email_account_map = collections.defaultdict(list)\nfor i, account in enumerate(accounts):\n for email in account[1:]:\n email_account_map[email].append(i)\n\ndef dfs(i, emails, visited):\n if visited[i]:\n return\n visited[i] = True\n for email in accounts[i][1:]:\n emails.add(emai... | <|body_start_0|>
email_account_map = collections.defaultdict(list)
for i, account in enumerate(accounts):
for email in account[1:]:
email_account_map[email].append(i)
def dfs(i, emails, visited):
if visited[i]:
return
visited[i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def accountsMerge1(self, accounts: List[List[str]]) -> List[List[str]]:
"""graph + dfs: account -> email time: O(Sum((N_i)log(N_i))) space: O(Sum(N_i))"""
<|body_0|>
def accountsMerge1(self, accounts: List[List[str]]) -> List[List[str]]:
"""union-find"""
... | stack_v2_sparse_classes_10k_train_008305 | 4,358 | no_license | [
{
"docstring": "graph + dfs: account -> email time: O(Sum((N_i)log(N_i))) space: O(Sum(N_i))",
"name": "accountsMerge1",
"signature": "def accountsMerge1(self, accounts: List[List[str]]) -> List[List[str]]"
},
{
"docstring": "union-find",
"name": "accountsMerge1",
"signature": "def accou... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def accountsMerge1(self, accounts: List[List[str]]) -> List[List[str]]: graph + dfs: account -> email time: O(Sum((N_i)log(N_i))) space: O(Sum(N_i))
- def accountsMerge1(self, ac... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def accountsMerge1(self, accounts: List[List[str]]) -> List[List[str]]: graph + dfs: account -> email time: O(Sum((N_i)log(N_i))) space: O(Sum(N_i))
- def accountsMerge1(self, ac... | 6ff1941ff213a843013100ac7033e2d4f90fbd6a | <|skeleton|>
class Solution:
def accountsMerge1(self, accounts: List[List[str]]) -> List[List[str]]:
"""graph + dfs: account -> email time: O(Sum((N_i)log(N_i))) space: O(Sum(N_i))"""
<|body_0|>
def accountsMerge1(self, accounts: List[List[str]]) -> List[List[str]]:
"""union-find"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def accountsMerge1(self, accounts: List[List[str]]) -> List[List[str]]:
"""graph + dfs: account -> email time: O(Sum((N_i)log(N_i))) space: O(Sum(N_i))"""
email_account_map = collections.defaultdict(list)
for i, account in enumerate(accounts):
for email in account... | the_stack_v2_python_sparse | Leetcode 0721. Accounts Merge.py | Chaoran-sjsu/leetcode | train | 0 | |
8f4e820e2ef8e7ea9487dcfe55779e6de9fd418d | [
"testcase = TestCaseTable(**request.json)\ndb.session.add(testcase)\ndb.session.commit()\nreturn 'OK'\nabort(404)",
"if 'name' in request.json:\n testcase = TestCaseTable.query.filter_by(name=request.json.get('name')).first()\n testcase.content = request.json.get('content')\n testcase.description = reque... | <|body_start_0|>
testcase = TestCaseTable(**request.json)
db.session.add(testcase)
db.session.commit()
return 'OK'
abort(404)
<|end_body_0|>
<|body_start_1|>
if 'name' in request.json:
testcase = TestCaseTable.query.filter_by(name=request.json.get('name')).fi... | TestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCase:
def post(self):
"""存储用例 :return:"""
<|body_0|>
def put(self):
"""更新用例 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
testcase = TestCaseTable(**request.json)
db.session.add(testcase)
db.session.commit()
re... | stack_v2_sparse_classes_10k_train_008306 | 6,802 | no_license | [
{
"docstring": "存储用例 :return:",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "更新用例 :return:",
"name": "put",
"signature": "def put(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006568 | Implement the Python class `TestCase` described below.
Class description:
Implement the TestCase class.
Method signatures and docstrings:
- def post(self): 存储用例 :return:
- def put(self): 更新用例 :return: | Implement the Python class `TestCase` described below.
Class description:
Implement the TestCase class.
Method signatures and docstrings:
- def post(self): 存储用例 :return:
- def put(self): 更新用例 :return:
<|skeleton|>
class TestCase:
def post(self):
"""存储用例 :return:"""
<|body_0|>
def put(self):... | 5ff767243f7d7f698997633f39ecd4c4ebcc998a | <|skeleton|>
class TestCase:
def post(self):
"""存储用例 :return:"""
<|body_0|>
def put(self):
"""更新用例 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestCase:
def post(self):
"""存储用例 :return:"""
testcase = TestCaseTable(**request.json)
db.session.add(testcase)
db.session.commit()
return 'OK'
abort(404)
def put(self):
"""更新用例 :return:"""
if 'name' in request.json:
testcase = T... | the_stack_v2_python_sparse | backend/server.py | ceshiren/HogwartsSDET16 | train | 16 | |
703232a621d6c94a7c084dfac8099e2a409e4695 | [
"osutils.Touch(os.path.join(self.deploy.options.build_dir, 'envoy_shell'), makedirs=True)\nself.deploy._CheckDeployType()\nself.assertTrue(self.getCopyPath('envoy_shell'))\nself.assertFalse(self.getCopyPath('app_shell'))\nself.assertFalse(self.getCopyPath('chrome'))",
"osutils.Touch(os.path.join(self.deploy.optio... | <|body_start_0|>
osutils.Touch(os.path.join(self.deploy.options.build_dir, 'envoy_shell'), makedirs=True)
self.deploy._CheckDeployType()
self.assertTrue(self.getCopyPath('envoy_shell'))
self.assertFalse(self.getCopyPath('app_shell'))
self.assertFalse(self.getCopyPath('chrome'))
<... | Test detection of deployment type using build dir. | TestDeploymentType | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-public-domain",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDeploymentType:
"""Test detection of deployment type using build dir."""
def testEnvoyDetection(self):
"""Check for an envoy deployment"""
<|body_0|>
def testAppShellDetection(self):
"""Check for an app_shell deployment"""
<|body_1|>
def testChro... | stack_v2_sparse_classes_10k_train_008307 | 13,041 | permissive | [
{
"docstring": "Check for an envoy deployment",
"name": "testEnvoyDetection",
"signature": "def testEnvoyDetection(self)"
},
{
"docstring": "Check for an app_shell deployment",
"name": "testAppShellDetection",
"signature": "def testAppShellDetection(self)"
},
{
"docstring": "Chec... | 4 | null | Implement the Python class `TestDeploymentType` described below.
Class description:
Test detection of deployment type using build dir.
Method signatures and docstrings:
- def testEnvoyDetection(self): Check for an envoy deployment
- def testAppShellDetection(self): Check for an app_shell deployment
- def testChromeAn... | Implement the Python class `TestDeploymentType` described below.
Class description:
Test detection of deployment type using build dir.
Method signatures and docstrings:
- def testEnvoyDetection(self): Check for an envoy deployment
- def testAppShellDetection(self): Check for an app_shell deployment
- def testChromeAn... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class TestDeploymentType:
"""Test detection of deployment type using build dir."""
def testEnvoyDetection(self):
"""Check for an envoy deployment"""
<|body_0|>
def testAppShellDetection(self):
"""Check for an app_shell deployment"""
<|body_1|>
def testChro... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestDeploymentType:
"""Test detection of deployment type using build dir."""
def testEnvoyDetection(self):
"""Check for an envoy deployment"""
osutils.Touch(os.path.join(self.deploy.options.build_dir, 'envoy_shell'), makedirs=True)
self.deploy._CheckDeployType()
self.asser... | the_stack_v2_python_sparse | third_party/chromite/scripts/deploy_chrome_unittest.py | metux/chromium-suckless | train | 5 |
1f2011aa16b4793522f6d81e1fd09a5007f0b3c4 | [
"if not root:\n return ''\nqueue = deque()\nqueue.append(root)\nresult = ''\nwhile queue:\n node = queue.popleft()\n if node:\n result += str(node.val) + ','\n queue.append(node.left)\n queue.append(node.right)\n else:\n result += '#,'\nresult = result[:-1]\nreturn result",
... | <|body_start_0|>
if not root:
return ''
queue = deque()
queue.append(root)
result = ''
while queue:
node = queue.popleft()
if node:
result += str(node.val) + ','
queue.append(node.left)
queue.appe... | 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_10k_train_008308 | 2,640 | 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_003656 | 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:... | b62862b90886f85c33271b881ac1365871731dcc | <|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_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
queue = deque()
queue.append(root)
result = ''
while queue:
node = queue.popleft()
if node:
... | the_stack_v2_python_sparse | serialize_tree.py | ashutosh-narkar/LeetCode | train | 0 | |
2dba7ede63cbf51a867ad6f5923b6dcce4c5c905 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn RelatedContact()",
"from .contact_relationship import ContactRelationship\nfrom .contact_relationship import ContactRelationship\nfields: Dict[str, Callable[[Any], None]] = {'accessConsent': lambda n: setattr(self, 'access_consent', n.... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return RelatedContact()
<|end_body_0|>
<|body_start_1|>
from .contact_relationship import ContactRelationship
from .contact_relationship import ContactRelationship
fields: Dict[str, Cal... | RelatedContact | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelatedContact:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RelatedContact:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Retur... | stack_v2_sparse_classes_10k_train_008309 | 3,694 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: RelatedContact",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_valu... | 3 | null | Implement the Python class `RelatedContact` described below.
Class description:
Implement the RelatedContact class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RelatedContact: Creates a new instance of the appropriate class based on discriminator va... | Implement the Python class `RelatedContact` described below.
Class description:
Implement the RelatedContact class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RelatedContact: Creates a new instance of the appropriate class based on discriminator va... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class RelatedContact:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RelatedContact:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Retur... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RelatedContact:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RelatedContact:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: RelatedCon... | the_stack_v2_python_sparse | msgraph/generated/models/related_contact.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
987960badf80458cb3cde7066c2171e61b49b579 | [
"b_values = self._encoding(max_log_scale, embedding_size, num_inputs)\na_values = torch.ones(b_values.shape[1])\nsuper().__init__(num_inputs, num_outputs, a_values, b_values, [num_channels] * num_layers)",
"embedding_size = embedding_size // num_inputs\nfrequencies_matrix = 2.0 ** torch.linspace(0, max_log_scale,... | <|body_start_0|>
b_values = self._encoding(max_log_scale, embedding_size, num_inputs)
a_values = torch.ones(b_values.shape[1])
super().__init__(num_inputs, num_outputs, a_values, b_values, [num_channels] * num_layers)
<|end_body_0|>
<|body_start_1|>
embedding_size = embedding_size // nu... | Version of FFN with positional encoding. | PositionalFMLP | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PositionalFMLP:
"""Version of FFN with positional encoding."""
def __init__(self, num_inputs: int, num_outputs: int, max_log_scale: float, num_layers=3, num_channels=256, embedding_size=256):
"""Constructor. Args: num_inputs (int): Number of dimensions in the input num_outputs (int):... | stack_v2_sparse_classes_10k_train_008310 | 8,060 | permissive | [
{
"docstring": "Constructor. Args: num_inputs (int): Number of dimensions in the input num_outputs (int): Number of dimensions in the output max_log_scale (float): Maximum log scale for embedding num_layers (int, optional): Number of layers in the MLP. Defaults to 4. num_channels (int, optional): Number of chan... | 2 | stack_v2_sparse_classes_30k_train_000862 | Implement the Python class `PositionalFMLP` described below.
Class description:
Version of FFN with positional encoding.
Method signatures and docstrings:
- def __init__(self, num_inputs: int, num_outputs: int, max_log_scale: float, num_layers=3, num_channels=256, embedding_size=256): Constructor. Args: num_inputs (i... | Implement the Python class `PositionalFMLP` described below.
Class description:
Version of FFN with positional encoding.
Method signatures and docstrings:
- def __init__(self, num_inputs: int, num_outputs: int, max_log_scale: float, num_layers=3, num_channels=256, embedding_size=256): Constructor. Args: num_inputs (i... | 94a402cab47a2bd6241608308371490079af4d53 | <|skeleton|>
class PositionalFMLP:
"""Version of FFN with positional encoding."""
def __init__(self, num_inputs: int, num_outputs: int, max_log_scale: float, num_layers=3, num_channels=256, embedding_size=256):
"""Constructor. Args: num_inputs (int): Number of dimensions in the input num_outputs (int):... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PositionalFMLP:
"""Version of FFN with positional encoding."""
def __init__(self, num_inputs: int, num_outputs: int, max_log_scale: float, num_layers=3, num_channels=256, embedding_size=256):
"""Constructor. Args: num_inputs (int): Number of dimensions in the input num_outputs (int): Number of di... | the_stack_v2_python_sparse | draugr/torch_utilities/architectures/mlp_variants/fourier.py | cnheider/draugr | train | 4 |
5983b54aba73962c78575d99b22dca29054791bf | [
"super(LabelSmoothingLoss, self).__init__()\nself.criterion = nn.KLDivLoss(reduction='none')\nself.padding_idx = padding_idx\nself.confidence = 1.0 - smoothing\nself.smoothing = smoothing\nself.size = size\nself.normalize_length = normalize_length",
"assert x.size(2) == self.size\nbatch_size = x.size(0)\nx = x.vi... | <|body_start_0|>
super(LabelSmoothingLoss, self).__init__()
self.criterion = nn.KLDivLoss(reduction='none')
self.padding_idx = padding_idx
self.confidence = 1.0 - smoothing
self.smoothing = smoothing
self.size = size
self.normalize_length = normalize_length
<|end_... | Label-smoothing loss. In a standard CE loss, the label's data distribution is: [0,1,2] -> [ [1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], ] In the smoothing version CE Loss,some probabilities are taken from the true label prob (1.0) and are divided among other labels. e.g. smoothing=0.1 [0,1,2] -> [ [0.9, 0.05, 0.... | LabelSmoothingLoss | [
"GPL-1.0-or-later",
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LabelSmoothingLoss:
"""Label-smoothing loss. In a standard CE loss, the label's data distribution is: [0,1,2] -> [ [1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], ] In the smoothing version CE Loss,some probabilities are taken from the true label prob (1.0) and are divided among other labels. ... | stack_v2_sparse_classes_10k_train_008311 | 3,459 | permissive | [
{
"docstring": "Construct an LabelSmoothingLoss object.",
"name": "__init__",
"signature": "def __init__(self, size: int, padding_idx: int, smoothing: float, normalize_length: bool=False)"
},
{
"docstring": "Compute loss between x and target. The model outputs and data labels tensors are flatten... | 2 | null | Implement the Python class `LabelSmoothingLoss` described below.
Class description:
Label-smoothing loss. In a standard CE loss, the label's data distribution is: [0,1,2] -> [ [1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], ] In the smoothing version CE Loss,some probabilities are taken from the true label prob (1.... | Implement the Python class `LabelSmoothingLoss` described below.
Class description:
Label-smoothing loss. In a standard CE loss, the label's data distribution is: [0,1,2] -> [ [1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], ] In the smoothing version CE Loss,some probabilities are taken from the true label prob (1.... | 92acc188d3a0f634de58463b6676e70df83ef808 | <|skeleton|>
class LabelSmoothingLoss:
"""Label-smoothing loss. In a standard CE loss, the label's data distribution is: [0,1,2] -> [ [1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], ] In the smoothing version CE Loss,some probabilities are taken from the true label prob (1.0) and are divided among other labels. ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LabelSmoothingLoss:
"""Label-smoothing loss. In a standard CE loss, the label's data distribution is: [0,1,2] -> [ [1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0], ] In the smoothing version CE Loss,some probabilities are taken from the true label prob (1.0) and are divided among other labels. e.g. smoothin... | the_stack_v2_python_sparse | PyTorch/built-in/audio/Wenet_Conformer_for_Pytorch/wenet/transformer/label_smoothing_loss.py | Ascend/ModelZoo-PyTorch | train | 23 |
f4024a3136f0a56071238bd8822c94c61a10c346 | [
"if output_md is None:\n output_md = metadata_info.ClassificationTensorMd(name=_OUTPUT_NAME, description=_OUTPUT_DESCRIPTION)\nreturn cls.create_from_metadata_info_for_multihead(model_buffer, general_md, input_md, [output_md])",
"if general_md is None:\n general_md = metadata_info.GeneralMd(name=_MODEL_NAME... | <|body_start_0|>
if output_md is None:
output_md = metadata_info.ClassificationTensorMd(name=_OUTPUT_NAME, description=_OUTPUT_DESCRIPTION)
return cls.create_from_metadata_info_for_multihead(model_buffer, general_md, input_md, [output_md])
<|end_body_0|>
<|body_start_1|>
if general_... | Writes metadata into an audio classifier. | MetadataWriter | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause",
"GPL-1.0-or-later",
"MIT",
"LGPL-2.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetadataWriter:
"""Writes metadata into an audio classifier."""
def create_from_metadata_info(cls, model_buffer: bytearray, general_md: Optional[metadata_info.GeneralMd]=None, input_md: Optional[metadata_info.InputAudioTensorMd]=None, output_md: Optional[metadata_info.ClassificationTensorMd]... | stack_v2_sparse_classes_10k_train_008312 | 7,060 | permissive | [
{
"docstring": "Creates MetadataWriter based on general/input/output information. Args: model_buffer: valid buffer of the model file. general_md: general information about the model. If not specified, default general metadata will be generated. input_md: input audio tensor informaton. If not specified, default ... | 3 | null | Implement the Python class `MetadataWriter` described below.
Class description:
Writes metadata into an audio classifier.
Method signatures and docstrings:
- def create_from_metadata_info(cls, model_buffer: bytearray, general_md: Optional[metadata_info.GeneralMd]=None, input_md: Optional[metadata_info.InputAudioTenso... | Implement the Python class `MetadataWriter` described below.
Class description:
Writes metadata into an audio classifier.
Method signatures and docstrings:
- def create_from_metadata_info(cls, model_buffer: bytearray, general_md: Optional[metadata_info.GeneralMd]=None, input_md: Optional[metadata_info.InputAudioTenso... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class MetadataWriter:
"""Writes metadata into an audio classifier."""
def create_from_metadata_info(cls, model_buffer: bytearray, general_md: Optional[metadata_info.GeneralMd]=None, input_md: Optional[metadata_info.InputAudioTensorMd]=None, output_md: Optional[metadata_info.ClassificationTensorMd]... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MetadataWriter:
"""Writes metadata into an audio classifier."""
def create_from_metadata_info(cls, model_buffer: bytearray, general_md: Optional[metadata_info.GeneralMd]=None, input_md: Optional[metadata_info.InputAudioTensorMd]=None, output_md: Optional[metadata_info.ClassificationTensorMd]=None):
... | the_stack_v2_python_sparse | third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/audio_classifier.py | chromium/chromium | train | 17,408 |
fd5afd07ad8325ff4df2f0d9a54f82b5bb11a342 | [
"if len(nums) == 0:\n return 0\nnums = [0] + nums\nf = [0 for _ in range(len(nums))]\nf[1] = nums[1]\nfor i in range(2, len(nums)):\n f[i] = max(nums[i] + f[i - 2], f[i - 1])\nreturn f[-1]",
"if len(nums) == 0:\n return 0\nif len(nums) == 1:\n return nums[0]\nreturn max(self.rob_origin(nums[1:]), self... | <|body_start_0|>
if len(nums) == 0:
return 0
nums = [0] + nums
f = [0 for _ in range(len(nums))]
f[1] = nums[1]
for i in range(2, len(nums)):
f[i] = max(nums[i] + f[i - 2], f[i - 1])
return f[-1]
<|end_body_0|>
<|body_start_1|>
if len(nums... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rob_origin(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(nums) == 0:
return 0
nums =... | stack_v2_sparse_classes_10k_train_008313 | 743 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob_origin",
"signature": "def rob_origin(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob",
"signature": "def rob(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob_origin(self, nums): :type nums: List[int] :rtype: int
- def rob(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob_origin(self, nums): :type nums: List[int] :rtype: int
- def rob(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def rob_origin(self, num... | c2b01374942dcba7fbbe7865d13d7599bbc083f3 | <|skeleton|>
class Solution:
def rob_origin(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def rob_origin(self, nums):
""":type nums: List[int] :rtype: int"""
if len(nums) == 0:
return 0
nums = [0] + nums
f = [0 for _ in range(len(nums))]
f[1] = nums[1]
for i in range(2, len(nums)):
f[i] = max(nums[i] + f[i - 2], f[i ... | the_stack_v2_python_sparse | P0213.py | chenjiahui1991/LeetCode | train | 0 | |
2c12afdc1e69d238023ae3865f7eee477a864361 | [
"if file_path is None:\n return False\ntry:\n if os.path.exists(file_path):\n os.remove(file_path)\nexcept Exception as ex:\n if ignore_errors:\n return False\n raise ex\nreturn True",
"if directory_path is None:\n return False\ntry:\n if os.path.exists(directory_path):\n sh... | <|body_start_0|>
if file_path is None:
return False
try:
if os.path.exists(file_path):
os.remove(file_path)
except Exception as ex:
if ignore_errors:
return False
raise ex
return True
<|end_body_0|>
<|body_s... | Utilities for reading/writing to and from files. | CommonIOUtils | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommonIOUtils:
"""Utilities for reading/writing to and from files."""
def delete_file(file_path: str, ignore_errors: bool=False) -> bool:
"""delete_file(file_path, ignore_errors=False) Delete a file. :param file_path: The file to delete. :type file_path: str :param ignore_errors: If ... | stack_v2_sparse_classes_10k_train_008314 | 4,270 | permissive | [
{
"docstring": "delete_file(file_path, ignore_errors=False) Delete a file. :param file_path: The file to delete. :type file_path: str :param ignore_errors: If True, any exceptions thrown will be ignored (Useful in preventing infinite loops) :type ignore_errors: bool, optional :return: True if successful. False ... | 4 | null | Implement the Python class `CommonIOUtils` described below.
Class description:
Utilities for reading/writing to and from files.
Method signatures and docstrings:
- def delete_file(file_path: str, ignore_errors: bool=False) -> bool: delete_file(file_path, ignore_errors=False) Delete a file. :param file_path: The file ... | Implement the Python class `CommonIOUtils` described below.
Class description:
Utilities for reading/writing to and from files.
Method signatures and docstrings:
- def delete_file(file_path: str, ignore_errors: bool=False) -> bool: delete_file(file_path, ignore_errors=False) Delete a file. :param file_path: The file ... | b59ea7e5f4bd01d3b3bd7603843d525a9c179867 | <|skeleton|>
class CommonIOUtils:
"""Utilities for reading/writing to and from files."""
def delete_file(file_path: str, ignore_errors: bool=False) -> bool:
"""delete_file(file_path, ignore_errors=False) Delete a file. :param file_path: The file to delete. :type file_path: str :param ignore_errors: If ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CommonIOUtils:
"""Utilities for reading/writing to and from files."""
def delete_file(file_path: str, ignore_errors: bool=False) -> bool:
"""delete_file(file_path, ignore_errors=False) Delete a file. :param file_path: The file to delete. :type file_path: str :param ignore_errors: If True, any exc... | the_stack_v2_python_sparse | src/sims4communitylib/utils/common_io_utils.py | velocist/TS4CheatsInfo | train | 1 |
7f3ea4aeceac9362b57fa35cad570abe55c4032e | [
"assert isinstance(msg, str), 'Invalid message %s' % msg\nself.data = data\nself.messageByType = {}\nself.messages = []\nself.update(msg, *items)\nsuper().__init__()",
"for item in items:\n if isinstance(item, str):\n self.messages.append(item)\n else:\n typ = typeFor(item)\n assert isi... | <|body_start_0|>
assert isinstance(msg, str), 'Invalid message %s' % msg
self.data = data
self.messageByType = {}
self.messages = []
self.update(msg, *items)
super().__init__()
<|end_body_0|>
<|body_start_1|>
for item in items:
if isinstance(item, str... | Exception to be raised when the input is invalid. | InputError | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputError:
"""Exception to be raised when the input is invalid."""
def __init__(self, msg, *items, **data):
"""Initializes the exception based on the items(s). ex: raise InputError('No idea what is wrong %(reason)s', reason='blame Gabriel') # The message is not associated with any t... | stack_v2_sparse_classes_10k_train_008315 | 5,632 | no_license | [
{
"docstring": "Initializes the exception based on the items(s). ex: raise InputError('No idea what is wrong %(reason)s', reason='blame Gabriel') # The message is not associated with any type. raise InputError('Something wrong with the id', Entity.Id) # The message is associated with the entity id. raise InputE... | 3 | stack_v2_sparse_classes_30k_train_004444 | Implement the Python class `InputError` described below.
Class description:
Exception to be raised when the input is invalid.
Method signatures and docstrings:
- def __init__(self, msg, *items, **data): Initializes the exception based on the items(s). ex: raise InputError('No idea what is wrong %(reason)s', reason='b... | Implement the Python class `InputError` described below.
Class description:
Exception to be raised when the input is invalid.
Method signatures and docstrings:
- def __init__(self, msg, *items, **data): Initializes the exception based on the items(s). ex: raise InputError('No idea what is wrong %(reason)s', reason='b... | e0b3466b34d31548996d57be4a9dac134d904380 | <|skeleton|>
class InputError:
"""Exception to be raised when the input is invalid."""
def __init__(self, msg, *items, **data):
"""Initializes the exception based on the items(s). ex: raise InputError('No idea what is wrong %(reason)s', reason='blame Gabriel') # The message is not associated with any t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InputError:
"""Exception to be raised when the input is invalid."""
def __init__(self, msg, *items, **data):
"""Initializes the exception based on the items(s). ex: raise InputError('No idea what is wrong %(reason)s', reason='blame Gabriel') # The message is not associated with any type. raise In... | the_stack_v2_python_sparse | components/ally-api/ally/api/error.py | cristidomsa/Ally-Py | train | 0 |
f46874aae652fa3eb63244fb046e91dd42da42aa | [
"self.chap_file_name = chap_file_name\nself.epub = epub\nself.nlp: dict[str, Language] = self.epub.nlp\nself.pipe: dict[str, TranslationPipelineCache] = self.epub.pipe\nself.lang_orig: str = self.epub.lang_orig\nself.lang_dest: str = self.epub.lang_dest\nself.soup = BeautifulSoup(chap_content, features='html.parser... | <|body_start_0|>
self.chap_file_name = chap_file_name
self.epub = epub
self.nlp: dict[str, Language] = self.epub.nlp
self.pipe: dict[str, TranslationPipelineCache] = self.epub.pipe
self.lang_orig: str = self.epub.lang_orig
self.lang_dest: str = self.epub.lang_dest
... | Chapter class. Parse the chapter content to find the Paragraphs in <p> tags. | Chapter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Chapter:
"""Chapter class. Parse the chapter content to find the Paragraphs in <p> tags."""
def __init__(self, chap_content: bytes, chap_file_name: str, epub: 'EPub') -> None:
"""Initialize a chapter. TODO: Pass lang tags?"""
<|body_0|>
def build_index(self):
"""... | stack_v2_sparse_classes_10k_train_008316 | 10,849 | no_license | [
{
"docstring": "Initialize a chapter. TODO: Pass lang tags?",
"name": "__init__",
"signature": "def __init__(self, chap_content: bytes, chap_file_name: str, epub: 'EPub') -> None"
},
{
"docstring": "Build maps to go from ``sent_in_chap_id`` to ``(par_id, sent_in_par_id)`` and vice-versa.",
"... | 6 | stack_v2_sparse_classes_30k_train_005241 | Implement the Python class `Chapter` described below.
Class description:
Chapter class. Parse the chapter content to find the Paragraphs in <p> tags.
Method signatures and docstrings:
- def __init__(self, chap_content: bytes, chap_file_name: str, epub: 'EPub') -> None: Initialize a chapter. TODO: Pass lang tags?
- de... | Implement the Python class `Chapter` described below.
Class description:
Chapter class. Parse the chapter content to find the Paragraphs in <p> tags.
Method signatures and docstrings:
- def __init__(self, chap_content: bytes, chap_file_name: str, epub: 'EPub') -> None: Initialize a chapter. TODO: Pass lang tags?
- de... | 1d7e5657014b00612cde87b78d5506a9e8b6adfc | <|skeleton|>
class Chapter:
"""Chapter class. Parse the chapter content to find the Paragraphs in <p> tags."""
def __init__(self, chap_content: bytes, chap_file_name: str, epub: 'EPub') -> None:
"""Initialize a chapter. TODO: Pass lang tags?"""
<|body_0|>
def build_index(self):
"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Chapter:
"""Chapter class. Parse the chapter content to find the Paragraphs in <p> tags."""
def __init__(self, chap_content: bytes, chap_file_name: str, epub: 'EPub') -> None:
"""Initialize a chapter. TODO: Pass lang tags?"""
self.chap_file_name = chap_file_name
self.epub = epub
... | the_stack_v2_python_sparse | python/streamlit-sample/align-epub/epub.py | Pitrified/snippet | train | 2 |
afcf4094b8bc6cc883ff27e95c3d60484828c11a | [
"if self.game_id[0:2] == NBA_GAME_ID_PREFIX:\n return NBA_STRING\nelif self.game_id[0:2] == G_LEAGUE_GAME_ID_PREFIX:\n return D_LEAGUE_STRING\nelif self.game_id[0:2] == WNBA_GAME_ID_PREFIX:\n return WNBA_STRING",
"if self.game_id[3] == '9':\n return '19' + self.game_id[3] + self.game_id[4]\nelse:\n ... | <|body_start_0|>
if self.game_id[0:2] == NBA_GAME_ID_PREFIX:
return NBA_STRING
elif self.game_id[0:2] == G_LEAGUE_GAME_ID_PREFIX:
return D_LEAGUE_STRING
elif self.game_id[0:2] == WNBA_GAME_ID_PREFIX:
return WNBA_STRING
<|end_body_0|>
<|body_start_1|>
... | Base Class for all data.nba.com data loaders This class should not be instantiated directly | DataNbaLoaderBase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataNbaLoaderBase:
"""Base Class for all data.nba.com data loaders This class should not be instantiated directly"""
def league(self):
"""Returns League for game id. First 2 in game id represent league - 00 for nba, 10 for wnba, 20 for g-league"""
<|body_0|>
def season(s... | stack_v2_sparse_classes_10k_train_008317 | 1,242 | permissive | [
{
"docstring": "Returns League for game id. First 2 in game id represent league - 00 for nba, 10 for wnba, 20 for g-league",
"name": "league",
"signature": "def league(self)"
},
{
"docstring": "Returns year in which season starts for game id 4th and 5th characters in game id represent season yea... | 2 | stack_v2_sparse_classes_30k_train_006819 | Implement the Python class `DataNbaLoaderBase` described below.
Class description:
Base Class for all data.nba.com data loaders This class should not be instantiated directly
Method signatures and docstrings:
- def league(self): Returns League for game id. First 2 in game id represent league - 00 for nba, 10 for wnba... | Implement the Python class `DataNbaLoaderBase` described below.
Class description:
Base Class for all data.nba.com data loaders This class should not be instantiated directly
Method signatures and docstrings:
- def league(self): Returns League for game id. First 2 in game id represent league - 00 for nba, 10 for wnba... | 38d5d75be50a478dbe718700c880e48020ffa123 | <|skeleton|>
class DataNbaLoaderBase:
"""Base Class for all data.nba.com data loaders This class should not be instantiated directly"""
def league(self):
"""Returns League for game id. First 2 in game id represent league - 00 for nba, 10 for wnba, 20 for g-league"""
<|body_0|>
def season(s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DataNbaLoaderBase:
"""Base Class for all data.nba.com data loaders This class should not be instantiated directly"""
def league(self):
"""Returns League for game id. First 2 in game id represent league - 00 for nba, 10 for wnba, 20 for g-league"""
if self.game_id[0:2] == NBA_GAME_ID_PREFI... | the_stack_v2_python_sparse | pbpstats/data_loader/data_nba/base.py | dblackrun/pbpstats | train | 73 |
74b1fa3e9a976311979e1c49b3659036856f89ab | [
"database.drop_tables([Customer])\ndatabase.create_tables([Customer])\nLOGGER.info('test setup complete')",
"pass\nadd_customer(self.customer_111[0], self.customer_111[1], self.customer_111[2], self.customer_111[3], self.customer_111[4], self.customer_111[5], self.customer_111[6], self.customer_111[7])\ncustomer ... | <|body_start_0|>
database.drop_tables([Customer])
database.create_tables([Customer])
LOGGER.info('test setup complete')
<|end_body_0|>
<|body_start_1|>
pass
add_customer(self.customer_111[0], self.customer_111[1], self.customer_111[2], self.customer_111[3], self.customer_111[4],... | testing basic operation | SuiteOfTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuiteOfTests:
"""testing basic operation"""
def setUp(self):
"""sets up the database"""
<|body_0|>
def test_add_customer(self):
"""test add customer"""
<|body_1|>
def test_search_customer(self):
"""test search customer"""
<|body_2|>
... | stack_v2_sparse_classes_10k_train_008318 | 5,744 | no_license | [
{
"docstring": "sets up the database",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "test add customer",
"name": "test_add_customer",
"signature": "def test_add_customer(self)"
},
{
"docstring": "test search customer",
"name": "test_search_customer",
... | 6 | null | Implement the Python class `SuiteOfTests` described below.
Class description:
testing basic operation
Method signatures and docstrings:
- def setUp(self): sets up the database
- def test_add_customer(self): test add customer
- def test_search_customer(self): test search customer
- def test_delete_customer(self): test... | Implement the Python class `SuiteOfTests` described below.
Class description:
testing basic operation
Method signatures and docstrings:
- def setUp(self): sets up the database
- def test_add_customer(self): test add customer
- def test_search_customer(self): test search customer
- def test_delete_customer(self): test... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class SuiteOfTests:
"""testing basic operation"""
def setUp(self):
"""sets up the database"""
<|body_0|>
def test_add_customer(self):
"""test add customer"""
<|body_1|>
def test_search_customer(self):
"""test search customer"""
<|body_2|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SuiteOfTests:
"""testing basic operation"""
def setUp(self):
"""sets up the database"""
database.drop_tables([Customer])
database.create_tables([Customer])
LOGGER.info('test setup complete')
def test_add_customer(self):
"""test add customer"""
pass
... | the_stack_v2_python_sparse | students/mmancini/lesson03/test_basic_operations.py | JavaRod/SP_Python220B_2019 | train | 1 |
6d0946232c0bbb3988daacfd5ddc13314dba2110 | [
"self.scipy = scipy\nself.data = data\nself.mu = mu\nself.sigma = sigma\nself.log = log\nself.info = info\nself.epsilon = epsilon",
"if self.data is None:\n output = gaussian(x, scipy=self.scipy, data=self.data, mu=self.mu[idx], sigma=self.sigma[idx], log=self.log, info=self.info, epsilon=self.epsilon)\nelse:\... | <|body_start_0|>
self.scipy = scipy
self.data = data
self.mu = mu
self.sigma = sigma
self.log = log
self.info = info
self.epsilon = epsilon
<|end_body_0|>
<|body_start_1|>
if self.data is None:
output = gaussian(x, scipy=self.scipy, data=self.... | GaussianDistribution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GaussianDistribution:
def __init__(self, scipy=False, data=None, mu=None, sigma=None, log=False, info=False, epsilon=1e-08):
"""Class for passing values through a Gaussian distribution, uses gaussian function. made this so I could use gaussian as a method For this class, training occurs ... | stack_v2_sparse_classes_10k_train_008319 | 47,457 | no_license | [
{
"docstring": "Class for passing values through a Gaussian distribution, uses gaussian function. made this so I could use gaussian as a method For this class, training occurs inside forward *Unimodal and univariate* Inputs: scipy (bool): if True use scipy's pdf functions, use custom is False see: https://docs.... | 2 | null | Implement the Python class `GaussianDistribution` described below.
Class description:
Implement the GaussianDistribution class.
Method signatures and docstrings:
- def __init__(self, scipy=False, data=None, mu=None, sigma=None, log=False, info=False, epsilon=1e-08): Class for passing values through a Gaussian distrib... | Implement the Python class `GaussianDistribution` described below.
Class description:
Implement the GaussianDistribution class.
Method signatures and docstrings:
- def __init__(self, scipy=False, data=None, mu=None, sigma=None, log=False, info=False, epsilon=1e-08): Class for passing values through a Gaussian distrib... | ad713e4eb15a2d9573622bace528fc86e19a6545 | <|skeleton|>
class GaussianDistribution:
def __init__(self, scipy=False, data=None, mu=None, sigma=None, log=False, info=False, epsilon=1e-08):
"""Class for passing values through a Gaussian distribution, uses gaussian function. made this so I could use gaussian as a method For this class, training occurs ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GaussianDistribution:
def __init__(self, scipy=False, data=None, mu=None, sigma=None, log=False, info=False, epsilon=1e-08):
"""Class for passing values through a Gaussian distribution, uses gaussian function. made this so I could use gaussian as a method For this class, training occurs inside forward... | the_stack_v2_python_sparse | manipulation/plating/GMM-Placing/gmm_placing/gaussian.py | HARPLab/gastronomy | train | 6 | |
a6a99ba75e9744fd4886bb06b052b77bea153e13 | [
"res = self.sumNumbers_(root)\nres = [int(i) for i in res]\nreturn sum(res)",
"if root is None:\n return []\nif root.left is None and root.right is None:\n return [str(root.val)]\nleft_sum: List[str] = self.sumNumbers_(root.left)\nres = []\nfor i in left_sum:\n res.append(str(root.val) + str(i))\nprint(r... | <|body_start_0|>
res = self.sumNumbers_(root)
res = [int(i) for i in res]
return sum(res)
<|end_body_0|>
<|body_start_1|>
if root is None:
return []
if root.left is None and root.right is None:
return [str(root.val)]
left_sum: List[str] = self.sum... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sumNumbers(self, root: TreeNode) -> int:
"""从根节点到叶子节点的数字之和"""
<|body_0|>
def sumNumbers_(self, root: TreeNode) -> List[str]:
"""创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个List [95,91], 然后再去加上根节点， 用List[str]的原因是中间有00的情况，转化为int会丢掉 :rtype... | stack_v2_sparse_classes_10k_train_008320 | 2,100 | no_license | [
{
"docstring": "从根节点到叶子节点的数字之和",
"name": "sumNumbers",
"signature": "def sumNumbers(self, root: TreeNode) -> int"
},
{
"docstring": "创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个List [95,91], 然后再去加上根节点， 用List[str]的原因是中间有00的情况，转化为int会丢掉 :rtype: object",
"name": "sumNumbers_",
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumNumbers(self, root: TreeNode) -> int: 从根节点到叶子节点的数字之和
- def sumNumbers_(self, root: TreeNode) -> List[str]: 创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumNumbers(self, root: TreeNode) -> int: 从根节点到叶子节点的数字之和
- def sumNumbers_(self, root: TreeNode) -> List[str]: 创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个Lis... | cd46cf08a580c418cc40a68bf9b32371fc69a803 | <|skeleton|>
class Solution:
def sumNumbers(self, root: TreeNode) -> int:
"""从根节点到叶子节点的数字之和"""
<|body_0|>
def sumNumbers_(self, root: TreeNode) -> List[str]:
"""创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个List [95,91], 然后再去加上根节点， 用List[str]的原因是中间有00的情况，转化为int会丢掉 :rtype... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def sumNumbers(self, root: TreeNode) -> int:
"""从根节点到叶子节点的数字之和"""
res = self.sumNumbers_(root)
res = [int(i) for i in res]
return sum(res)
def sumNumbers_(self, root: TreeNode) -> List[str]:
"""创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个... | the_stack_v2_python_sparse | tree/129 sumNumbers.py | pangyouzhen/data-structure | train | 0 | |
160446a2f3e1d695680252c4458d31cf4d6f8173 | [
"dp = [0] * (amount + 1)\ndp[0] = 1\nfor coin in coins:\n for i in range(coin, amount + 1):\n dp[i] += dp[i - coin]\nreturn dp[amount]",
"dp = [0] * (amount + 1)\ndp[0] = 1\ncoins.sort()\nfor i in range(1, amount + 1):\n for coin in coins:\n if i - coin > -1:\n dp[i] += dp[i - coin]... | <|body_start_0|>
dp = [0] * (amount + 1)
dp[0] = 1
for coin in coins:
for i in range(coin, amount + 1):
dp[i] += dp[i - coin]
return dp[amount]
<|end_body_0|>
<|body_start_1|>
dp = [0] * (amount + 1)
dp[0] = 1
coins.sort()
for ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def change(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int"""
<|body_0|>
def change_Wrong(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_008321 | 2,543 | no_license | [
{
"docstring": ":type amount: int :type coins: List[int] :rtype: int",
"name": "change",
"signature": "def change(self, amount, coins)"
},
{
"docstring": ":type amount: int :type coins: List[int] :rtype: int",
"name": "change_Wrong",
"signature": "def change_Wrong(self, amount, coins)"
... | 2 | stack_v2_sparse_classes_30k_train_006870 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def change(self, amount, coins): :type amount: int :type coins: List[int] :rtype: int
- def change_Wrong(self, amount, coins): :type amount: int :type coins: List[int] :rtype: in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def change(self, amount, coins): :type amount: int :type coins: List[int] :rtype: int
- def change_Wrong(self, amount, coins): :type amount: int :type coins: List[int] :rtype: in... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def change(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int"""
<|body_0|>
def change_Wrong(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def change(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int"""
dp = [0] * (amount + 1)
dp[0] = 1
for coin in coins:
for i in range(coin, amount + 1):
dp[i] += dp[i - coin]
return dp[amount]
def chan... | the_stack_v2_python_sparse | code518CoinChange2.py | cybelewang/leetcode-python | train | 0 | |
3024ef2c5cf655e8cdec3c7599e7fc864aa608fb | [
"self.set = set()\nself.table = collections.defaultdict(int)\nself.total = 0",
"self.set.add(timestamp)\nself.table[timestamp] += 1\nself.total += 1\ntmp = min(self.set)\nwhile timestamp - tmp >= 300:\n self.total -= self.table[tmp]\n self.table[tmp] = 0\n self.set.remove(tmp)\n tmp = min(self.set)",
... | <|body_start_0|>
self.set = set()
self.table = collections.defaultdict(int)
self.total = 0
<|end_body_0|>
<|body_start_1|>
self.set.add(timestamp)
self.table[timestamp] += 1
self.total += 1
tmp = min(self.set)
while timestamp - tmp >= 300:
sel... | HitCounter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def hit(self, timestamp: int) -> None:
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity)."""
<|body_1|>
def getHits(self, timestamp: in... | stack_v2_sparse_classes_10k_train_008322 | 1,412 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Record a hit. @param timestamp - The current timestamp (in seconds granularity).",
"name": "hit",
"signature": "def hit(self, timestamp: int) -> None"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_000579 | Implement the Python class `HitCounter` described below.
Class description:
Implement the HitCounter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def hit(self, timestamp: int) -> None: Record a hit. @param timestamp - The current timestamp (in seconds granulari... | Implement the Python class `HitCounter` described below.
Class description:
Implement the HitCounter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def hit(self, timestamp: int) -> None: Record a hit. @param timestamp - The current timestamp (in seconds granulari... | 54d0b3c237e0ffed8782915d6b75b7c6a0fe0de7 | <|skeleton|>
class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def hit(self, timestamp: int) -> None:
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity)."""
<|body_1|>
def getHits(self, timestamp: in... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
self.set = set()
self.table = collections.defaultdict(int)
self.total = 0
def hit(self, timestamp: int) -> None:
"""Record a hit. @param timestamp - The current timestamp (in seconds granula... | the_stack_v2_python_sparse | 0362_Design_Hit_Counter/try_2.py | novayo/LeetCode | train | 8 | |
f1b537b3865b0aa315b8685656e6862a20b14e85 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | The JobController provides methods to manage jobs. | JobControllerServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobControllerServicer:
"""The JobController provides methods to manage jobs."""
def SubmitJob(self, request, context):
"""Submits a job to a cluster."""
<|body_0|>
def GetJob(self, request, context):
"""Gets the resource representation for a job in a project."""
... | stack_v2_sparse_classes_10k_train_008323 | 6,938 | permissive | [
{
"docstring": "Submits a job to a cluster.",
"name": "SubmitJob",
"signature": "def SubmitJob(self, request, context)"
},
{
"docstring": "Gets the resource representation for a job in a project.",
"name": "GetJob",
"signature": "def GetJob(self, request, context)"
},
{
"docstrin... | 6 | stack_v2_sparse_classes_30k_train_002932 | Implement the Python class `JobControllerServicer` described below.
Class description:
The JobController provides methods to manage jobs.
Method signatures and docstrings:
- def SubmitJob(self, request, context): Submits a job to a cluster.
- def GetJob(self, request, context): Gets the resource representation for a ... | Implement the Python class `JobControllerServicer` described below.
Class description:
The JobController provides methods to manage jobs.
Method signatures and docstrings:
- def SubmitJob(self, request, context): Submits a job to a cluster.
- def GetJob(self, request, context): Gets the resource representation for a ... | d897d56bce03d1fda98b79afb08264e51d46c421 | <|skeleton|>
class JobControllerServicer:
"""The JobController provides methods to manage jobs."""
def SubmitJob(self, request, context):
"""Submits a job to a cluster."""
<|body_0|>
def GetJob(self, request, context):
"""Gets the resource representation for a job in a project."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class JobControllerServicer:
"""The JobController provides methods to manage jobs."""
def SubmitJob(self, request, context):
"""Submits a job to a cluster."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError... | the_stack_v2_python_sparse | dataproc/google/cloud/dataproc_v1/proto/jobs_pb2_grpc.py | tswast/google-cloud-python | train | 1 |
936171128a03de9b1c3fb1b3ceefea5cd224a70e | [
"super(FastGradientMethod, self).__init__(model, sess, dtypestr, **kwargs)\nself.feedable_kwargs = ('eps', 'y', 'y_target', 'clip_min', 'clip_max')\nself.structural_kwargs = ['ord', 'sanity_checks']",
"assert self.parse_params(**kwargs)\nlabels, _nb_classes = self.get_or_guess_labels(x, kwargs)\nreturn fgm(x, sel... | <|body_start_0|>
super(FastGradientMethod, self).__init__(model, sess, dtypestr, **kwargs)
self.feedable_kwargs = ('eps', 'y', 'y_target', 'clip_min', 'clip_max')
self.structural_kwargs = ['ord', 'sanity_checks']
<|end_body_0|>
<|body_start_1|>
assert self.parse_params(**kwargs)
... | This attack was originally implemented by Goodfellow et al. (2014) with the infinity norm (and is known as the "Fast Gradient Sign Method"). This implementation extends the attack to other norms, and is therefore called the Fast Gradient Method. Paper link: https://arxiv.org/abs/1412.6572 :param model: cleverhans.model... | FastGradientMethod | [
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FastGradientMethod:
"""This attack was originally implemented by Goodfellow et al. (2014) with the infinity norm (and is known as the "Fast Gradient Sign Method"). This implementation extends the attack to other norms, and is therefore called the Fast Gradient Method. Paper link: https://arxiv.or... | stack_v2_sparse_classes_10k_train_008324 | 8,992 | permissive | [
{
"docstring": "Create a FastGradientMethod instance. Note: the model parameter should be an instance of the cleverhans.model.Model abstraction provided by CleverHans.",
"name": "__init__",
"signature": "def __init__(self, model, sess=None, dtypestr='float32', **kwargs)"
},
{
"docstring": "Retur... | 3 | stack_v2_sparse_classes_30k_train_002458 | Implement the Python class `FastGradientMethod` described below.
Class description:
This attack was originally implemented by Goodfellow et al. (2014) with the infinity norm (and is known as the "Fast Gradient Sign Method"). This implementation extends the attack to other norms, and is therefore called the Fast Gradie... | Implement the Python class `FastGradientMethod` described below.
Class description:
This attack was originally implemented by Goodfellow et al. (2014) with the infinity norm (and is known as the "Fast Gradient Sign Method"). This implementation extends the attack to other norms, and is therefore called the Fast Gradie... | bbe96757fa7daded0090b1d9a26b9c90d7d87c61 | <|skeleton|>
class FastGradientMethod:
"""This attack was originally implemented by Goodfellow et al. (2014) with the infinity norm (and is known as the "Fast Gradient Sign Method"). This implementation extends the attack to other norms, and is therefore called the Fast Gradient Method. Paper link: https://arxiv.or... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FastGradientMethod:
"""This attack was originally implemented by Goodfellow et al. (2014) with the infinity norm (and is known as the "Fast Gradient Sign Method"). This implementation extends the attack to other norms, and is therefore called the Fast Gradient Method. Paper link: https://arxiv.org/abs/1412.65... | the_stack_v2_python_sparse | cleverhans/attacks/fast_gradient_method.py | yogeshbalaji/InvGAN | train | 17 |
0ca6fc1f8c555fdb1a279957f42bc8a9306011c9 | [
"for r in range(len(A)):\n for c in range(len(A[0])):\n A[r][c] ^= 1\nfor r in range(len(A)):\n A[r].reverse()\nreturn A",
"reverse = []\nfor i in A:\n temp = []\n for j in reversed(i):\n if j == 0:\n temp.append(1)\n else:\n temp.append(0)\n reverse.appen... | <|body_start_0|>
for r in range(len(A)):
for c in range(len(A[0])):
A[r][c] ^= 1
for r in range(len(A)):
A[r].reverse()
return A
<|end_body_0|>
<|body_start_1|>
reverse = []
for i in A:
temp = []
for j in reversed(i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def flipAndInvertImage(self, A):
""":type A: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def flipAndInvertImage(self, A):
""":type A: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for r i... | stack_v2_sparse_classes_10k_train_008325 | 875 | no_license | [
{
"docstring": ":type A: List[List[int]] :rtype: List[List[int]]",
"name": "flipAndInvertImage",
"signature": "def flipAndInvertImage(self, A)"
},
{
"docstring": ":type A: List[List[int]] :rtype: List[List[int]]",
"name": "flipAndInvertImage",
"signature": "def flipAndInvertImage(self, A... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def flipAndInvertImage(self, A): :type A: List[List[int]] :rtype: List[List[int]]
- def flipAndInvertImage(self, A): :type A: List[List[int]] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def flipAndInvertImage(self, A): :type A: List[List[int]] :rtype: List[List[int]]
- def flipAndInvertImage(self, A): :type A: List[List[int]] :rtype: List[List[int]]
<|skeleton|... | c92a5ddcc56e3f69be1e6fb25e9c8ed277e57ee0 | <|skeleton|>
class Solution:
def flipAndInvertImage(self, A):
""":type A: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def flipAndInvertImage(self, A):
""":type A: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def flipAndInvertImage(self, A):
""":type A: List[List[int]] :rtype: List[List[int]]"""
for r in range(len(A)):
for c in range(len(A[0])):
A[r][c] ^= 1
for r in range(len(A)):
A[r].reverse()
return A
def flipAndInvertImage(... | the_stack_v2_python_sparse | code/832#Flipping an Image.py | EachenKuang/LeetCode | train | 28 | |
4fc7a32c0888f1e407ae4a4706eaaf40051e0623 | [
"super(Transpose1dLayer, self).__init__()\nself.upsample = upsample\nreflection_pad = nn.ConstantPad1d(kernel_size // 2, value=0)\nconv1d = nn.Conv1d(in_channels, out_channels, kernel_size, stride)\nconv1d.weight.data.normal_(0.0, 0.02)\nConv1dTrans = nn.ConvTranspose1d(in_channels, out_channels, kernel_size, strid... | <|body_start_0|>
super(Transpose1dLayer, self).__init__()
self.upsample = upsample
reflection_pad = nn.ConstantPad1d(kernel_size // 2, value=0)
conv1d = nn.Conv1d(in_channels, out_channels, kernel_size, stride)
conv1d.weight.data.normal_(0.0, 0.02)
Conv1dTrans = nn.ConvTr... | Package of all 1d Convolution Transpose Layer | Transpose1dLayer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transpose1dLayer:
"""Package of all 1d Convolution Transpose Layer"""
def __init__(self, in_channels, out_channels, kernel_size, stride, padding=11, upsample=None, output_padding=1, use_batch_norm=False) -> NoReturn:
"""Initialize 1d Convolution Transpose Layer package -*-*-*Convolut... | stack_v2_sparse_classes_10k_train_008326 | 5,819 | permissive | [
{
"docstring": "Initialize 1d Convolution Transpose Layer package -*-*-*Convolution Transpose summary*-*-*- There isn't a direct back-process to convolution like deconvolution but there is a technique to retrieve most of the information back called \"Convolution Transpose\". Apply convolution with bigger kernel... | 2 | stack_v2_sparse_classes_30k_train_005963 | Implement the Python class `Transpose1dLayer` described below.
Class description:
Package of all 1d Convolution Transpose Layer
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, kernel_size, stride, padding=11, upsample=None, output_padding=1, use_batch_norm=False) -> NoReturn: Initial... | Implement the Python class `Transpose1dLayer` described below.
Class description:
Package of all 1d Convolution Transpose Layer
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, kernel_size, stride, padding=11, upsample=None, output_padding=1, use_batch_norm=False) -> NoReturn: Initial... | 4eea5339c8ad0aae2861b8f7cc8ea88bdd0852ed | <|skeleton|>
class Transpose1dLayer:
"""Package of all 1d Convolution Transpose Layer"""
def __init__(self, in_channels, out_channels, kernel_size, stride, padding=11, upsample=None, output_padding=1, use_batch_norm=False) -> NoReturn:
"""Initialize 1d Convolution Transpose Layer package -*-*-*Convolut... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Transpose1dLayer:
"""Package of all 1d Convolution Transpose Layer"""
def __init__(self, in_channels, out_channels, kernel_size, stride, padding=11, upsample=None, output_padding=1, use_batch_norm=False) -> NoReturn:
"""Initialize 1d Convolution Transpose Layer package -*-*-*Convolution Transpose... | the_stack_v2_python_sparse | not_functional/models/architectures/layers/BaseLayers.py | develooper1994/MasterThesis | train | 6 |
73dc5a7d0ef009b7289a3b07bea55fc9b7055afd | [
"super(Embedding, self).__init__()\nself.dropout = dropout\nwith self.init_scope():\n self.embed = L.EmbedID(num_classes, embedding_dim, ignore_label=ignore_index)\n if use_cuda:\n self.embed.to_gpu()",
"y = self.embed(y)\nif self.dropout > 0:\n y = F.dropout(y, ratio=self.dropout)\nreturn y"
] | <|body_start_0|>
super(Embedding, self).__init__()
self.dropout = dropout
with self.init_scope():
self.embed = L.EmbedID(num_classes, embedding_dim, ignore_label=ignore_index)
if use_cuda:
self.embed.to_gpu()
<|end_body_0|>
<|body_start_1|>
y = se... | Embedding | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Embedding:
def __init__(self, num_classes, embedding_dim, dropout=0, ignore_index=-1, use_cuda=False):
"""Embedding layer. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embedding in target space... | stack_v2_sparse_classes_10k_train_008327 | 5,435 | no_license | [
{
"docstring": "Embedding layer. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embedding in target spaces dropout (float, optional): the probability to drop nodes of the embedding ignore_index (int, optional): use_cuda... | 2 | stack_v2_sparse_classes_30k_val_000355 | Implement the Python class `Embedding` described below.
Class description:
Implement the Embedding class.
Method signatures and docstrings:
- def __init__(self, num_classes, embedding_dim, dropout=0, ignore_index=-1, use_cuda=False): Embedding layer. Args: num_classes (int): the number of nodes in softmax layer (incl... | Implement the Python class `Embedding` described below.
Class description:
Implement the Embedding class.
Method signatures and docstrings:
- def __init__(self, num_classes, embedding_dim, dropout=0, ignore_index=-1, use_cuda=False): Embedding layer. Args: num_classes (int): the number of nodes in softmax layer (incl... | b6b60a338d65bb369d0034f423feb09db10db8b7 | <|skeleton|>
class Embedding:
def __init__(self, num_classes, embedding_dim, dropout=0, ignore_index=-1, use_cuda=False):
"""Embedding layer. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embedding in target space... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Embedding:
def __init__(self, num_classes, embedding_dim, dropout=0, ignore_index=-1, use_cuda=False):
"""Embedding layer. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embedding in target spaces dropout (flo... | the_stack_v2_python_sparse | models/chainer/linear.py | carolinebear/pytorch_end2end_speech_recognition | train | 0 | |
e586d4fa8b815942078d576ab2fc68423d8082c3 | [
"if safe:\n endpoint = SAFE_BOORU_ENDPOINT\n provider = SAFE_BOORU_PROVIDER\n banned_tags = SAFE_TAGS_BANNED\nelse:\n endpoint = NSFW_BOORU_ENDPOINT\n provider = NSFW_BOORU_PROVIDER\n banned_tags = NSFW_TAGS_BANNED\nhandler = ImageHandlerBooru(provider, endpoint, None, banned_tags, requested_tags,... | <|body_start_0|>
if safe:
endpoint = SAFE_BOORU_ENDPOINT
provider = SAFE_BOORU_PROVIDER
banned_tags = SAFE_TAGS_BANNED
else:
endpoint = NSFW_BOORU_ENDPOINT
provider = NSFW_BOORU_PROVIDER
banned_tags = NSFW_TAGS_BANNED
handle... | Booru image cache. Attributes ---------- cache_id : `int` The identifier of the cache. handler : ``ImageHandlerBooru`` Handler used to request images. last : `None`, ``ImageDetail`` The last show image detail. last_call : `float` When was the handler last called. | ImageCache | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageCache:
"""Booru image cache. Attributes ---------- cache_id : `int` The identifier of the cache. handler : ``ImageHandlerBooru`` Handler used to request images. last : `None`, ``ImageDetail`` The last show image detail. last_call : `float` When was the handler last called."""
def __new_... | stack_v2_sparse_classes_10k_train_008328 | 9,784 | no_license | [
{
"docstring": "Creates a new image cache for booru commands. Parameters ---------- requested_tags : `set` of `str` The requested tags. safe : `bool` Whether we want safe images.",
"name": "__new__",
"signature": "def __new__(cls, requested_tags, safe)"
},
{
"docstring": "Invokes the booru cache... | 4 | null | Implement the Python class `ImageCache` described below.
Class description:
Booru image cache. Attributes ---------- cache_id : `int` The identifier of the cache. handler : ``ImageHandlerBooru`` Handler used to request images. last : `None`, ``ImageDetail`` The last show image detail. last_call : `float` When was the ... | Implement the Python class `ImageCache` described below.
Class description:
Booru image cache. Attributes ---------- cache_id : `int` The identifier of the cache. handler : ``ImageHandlerBooru`` Handler used to request images. last : `None`, ``ImageDetail`` The last show image detail. last_call : `float` When was the ... | 74f92b598e86606ea3a269311316cddd84a5215f | <|skeleton|>
class ImageCache:
"""Booru image cache. Attributes ---------- cache_id : `int` The identifier of the cache. handler : ``ImageHandlerBooru`` Handler used to request images. last : `None`, ``ImageDetail`` The last show image detail. last_call : `float` When was the handler last called."""
def __new_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ImageCache:
"""Booru image cache. Attributes ---------- cache_id : `int` The identifier of the cache. handler : ``ImageHandlerBooru`` Handler used to request images. last : `None`, ``ImageDetail`` The last show image detail. last_call : `float` When was the handler last called."""
def __new__(cls, reques... | the_stack_v2_python_sparse | koishi/plugins/image_handling_commands/booru/booru.py | HuyaneMatsu/Koishi | train | 17 |
a97d04663c98faf08f6ac2c7cf5c7e7db5b5f4a0 | [
"smach.State.__init__(self, outcomes=['succeeded', 'failed'])\nself._robot = robot\nself._srv = rospy.ServiceProxy(robot.robot_name + '/ed/fit_entity_in_image', FitEntityInImage)\nself._entity_str = entity_str",
"self._robot.head.reset()\nself._robot.head.wait_for_motion_done(5.0)\nrospy.sleep(rospy.Duration(1.0)... | <|body_start_0|>
smach.State.__init__(self, outcomes=['succeeded', 'failed'])
self._robot = robot
self._srv = rospy.ServiceProxy(robot.robot_name + '/ed/fit_entity_in_image', FitEntityInImage)
self._entity_str = entity_str
<|end_body_0|>
<|body_start_1|>
self._robot.head.reset()... | Fits an entity | FitEntity | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FitEntity:
"""Fits an entity"""
def __init__(self, robot, entity_str):
"""Constructor :param robot: robot object :param entity_str: string with the entity type to fit"""
<|body_0|>
def execute(self, userdata=None):
"""Executes the state"""
<|body_1|>
<|e... | stack_v2_sparse_classes_10k_train_008329 | 1,370 | no_license | [
{
"docstring": "Constructor :param robot: robot object :param entity_str: string with the entity type to fit",
"name": "__init__",
"signature": "def __init__(self, robot, entity_str)"
},
{
"docstring": "Executes the state",
"name": "execute",
"signature": "def execute(self, userdata=None... | 2 | stack_v2_sparse_classes_30k_train_004006 | Implement the Python class `FitEntity` described below.
Class description:
Fits an entity
Method signatures and docstrings:
- def __init__(self, robot, entity_str): Constructor :param robot: robot object :param entity_str: string with the entity type to fit
- def execute(self, userdata=None): Executes the state | Implement the Python class `FitEntity` described below.
Class description:
Fits an entity
Method signatures and docstrings:
- def __init__(self, robot, entity_str): Constructor :param robot: robot object :param entity_str: string with the entity type to fit
- def execute(self, userdata=None): Executes the state
<|sk... | d4705c553f4711be792b37730658b481cc05eca1 | <|skeleton|>
class FitEntity:
"""Fits an entity"""
def __init__(self, robot, entity_str):
"""Constructor :param robot: robot object :param entity_str: string with the entity type to fit"""
<|body_0|>
def execute(self, userdata=None):
"""Executes the state"""
<|body_1|>
<|e... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FitEntity:
"""Fits an entity"""
def __init__(self, robot, entity_str):
"""Constructor :param robot: robot object :param entity_str: string with the entity type to fit"""
smach.State.__init__(self, outcomes=['succeeded', 'failed'])
self._robot = robot
self._srv = rospy.Serv... | the_stack_v2_python_sparse | challenge_storing_groceries/src/challenge_storing_groceries/fit_entity.py | SamAlexandrov/tue_robocup | train | 0 |
6f7b9a779abd8fe5f117f7610525cc19a0a63d52 | [
"super().__init__()\nself._initialize_arguments(args)\nself.temperature = args.temperature\nself.adj_type = args.adj_type\nif args.adj_type == 'fixed':\n self.adj_mx = adj_mx.to(device)\nelif args.adj_type == 'empty':\n self.adj_mx = torch.zeros(size=(args.num_nodes, args.num_nodes, args.num_relation_types), ... | <|body_start_0|>
super().__init__()
self._initialize_arguments(args)
self.temperature = args.temperature
self.adj_type = args.adj_type
if args.adj_type == 'fixed':
self.adj_mx = adj_mx.to(device)
elif args.adj_type == 'empty':
self.adj_mx = torch.z... | Implements the GATRNN model. | GATRNN | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GATRNN:
"""Implements the GATRNN model."""
def __init__(self, adj_mx, args):
"""Instantiates the GATRNN encoder model. Args: adj_mx: adjacency matrix, with shape (self.num_nodes, self.num_nodes). args: python argparse.ArgumentParser class, we only use model-related arguments here."""... | stack_v2_sparse_classes_10k_train_008330 | 13,550 | permissive | [
{
"docstring": "Instantiates the GATRNN encoder model. Args: adj_mx: adjacency matrix, with shape (self.num_nodes, self.num_nodes). args: python argparse.ArgumentParser class, we only use model-related arguments here.",
"name": "__init__",
"signature": "def __init__(self, adj_mx, args)"
},
{
"do... | 4 | stack_v2_sparse_classes_30k_train_000201 | Implement the Python class `GATRNN` described below.
Class description:
Implements the GATRNN model.
Method signatures and docstrings:
- def __init__(self, adj_mx, args): Instantiates the GATRNN encoder model. Args: adj_mx: adjacency matrix, with shape (self.num_nodes, self.num_nodes). args: python argparse.ArgumentP... | Implement the Python class `GATRNN` described below.
Class description:
Implements the GATRNN model.
Method signatures and docstrings:
- def __init__(self, adj_mx, args): Instantiates the GATRNN encoder model. Args: adj_mx: adjacency matrix, with shape (self.num_nodes, self.num_nodes). args: python argparse.ArgumentP... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class GATRNN:
"""Implements the GATRNN model."""
def __init__(self, adj_mx, args):
"""Instantiates the GATRNN encoder model. Args: adj_mx: adjacency matrix, with shape (self.num_nodes, self.num_nodes). args: python argparse.ArgumentParser class, we only use model-related arguments here."""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GATRNN:
"""Implements the GATRNN model."""
def __init__(self, adj_mx, args):
"""Instantiates the GATRNN encoder model. Args: adj_mx: adjacency matrix, with shape (self.num_nodes, self.num_nodes). args: python argparse.ArgumentParser class, we only use model-related arguments here."""
supe... | the_stack_v2_python_sparse | editable_graph_temporal/model/gat_model.py | Jimmy-INL/google-research | train | 1 |
feebcb9cfc57c504dbc296f2677cae605537abbc | [
"super().__init__()\nself.label = label\nself.tag_set = tag_set\nself.setText(str(label))\nfont = QFont('SansSerif', 9)\nfont.setBold(False)\nself.setFont(font)\nfont_metric = QFontMetrics(font)\nwidth = font_metric.width(str(label)) + 20\nif tooltip_lbl is not None:\n self.setToolTip(str(tooltip_lbl))\n self... | <|body_start_0|>
super().__init__()
self.label = label
self.tag_set = tag_set
self.setText(str(label))
font = QFont('SansSerif', 9)
font.setBold(False)
self.setFont(font)
font_metric = QFontMetrics(font)
width = font_metric.width(str(label)) + 20
... | QTagButton | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QTagButton:
def __init__(self, label: str, tag_set: set, tooltip_lbl: str=None):
"""Formats the tag button :param label: String of tag. :param tag_set: set of tag strings"""
<|body_0|>
def mousePressEvent(self, event):
"""Overides existing mousepressevent. If a right... | stack_v2_sparse_classes_10k_train_008331 | 1,526 | no_license | [
{
"docstring": "Formats the tag button :param label: String of tag. :param tag_set: set of tag strings",
"name": "__init__",
"signature": "def __init__(self, label: str, tag_set: set, tooltip_lbl: str=None)"
},
{
"docstring": "Overides existing mousepressevent. If a right click occurs the tag is... | 2 | stack_v2_sparse_classes_30k_train_000721 | Implement the Python class `QTagButton` described below.
Class description:
Implement the QTagButton class.
Method signatures and docstrings:
- def __init__(self, label: str, tag_set: set, tooltip_lbl: str=None): Formats the tag button :param label: String of tag. :param tag_set: set of tag strings
- def mousePressEv... | Implement the Python class `QTagButton` described below.
Class description:
Implement the QTagButton class.
Method signatures and docstrings:
- def __init__(self, label: str, tag_set: set, tooltip_lbl: str=None): Formats the tag button :param label: String of tag. :param tag_set: set of tag strings
- def mousePressEv... | ab04ca1c67839a8269f5275323907c5bc7f9af46 | <|skeleton|>
class QTagButton:
def __init__(self, label: str, tag_set: set, tooltip_lbl: str=None):
"""Formats the tag button :param label: String of tag. :param tag_set: set of tag strings"""
<|body_0|>
def mousePressEvent(self, event):
"""Overides existing mousepressevent. If a right... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QTagButton:
def __init__(self, label: str, tag_set: set, tooltip_lbl: str=None):
"""Formats the tag button :param label: String of tag. :param tag_set: set of tag strings"""
super().__init__()
self.label = label
self.tag_set = tag_set
self.setText(str(label))
fo... | the_stack_v2_python_sparse | custom_widgets/tag_button.py | tobias-gill/Figshare_desktop | train | 0 | |
e932213877e11870036b0aeda1d2e19c63bbfdf0 | [
"res = 0\n\ndef dfs(node, sumVal):\n nonlocal res\n if not node:\n return\n sumVal = sumVal * 10 + node.val\n if not node.left and (not node.right):\n res += sumVal\n dfs(node.left, sumVal)\n dfs(node.right, sumVal)\ndfs(root, 0)\nreturn res",
"if not root:\n return False\n\ndef... | <|body_start_0|>
res = 0
def dfs(node, sumVal):
nonlocal res
if not node:
return
sumVal = sumVal * 10 + node.val
if not node.left and (not node.right):
res += sumVal
dfs(node.left, sumVal)
dfs(node.r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sumNumbers(self, root):
"""https://leetcode-cn.com/problems/sum-root-to-leaf-numbers/ :type root: TreeNode :rtype: int"""
<|body_0|>
def hasPathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: bool"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k_train_008332 | 1,662 | no_license | [
{
"docstring": "https://leetcode-cn.com/problems/sum-root-to-leaf-numbers/ :type root: TreeNode :rtype: int",
"name": "sumNumbers",
"signature": "def sumNumbers(self, root)"
},
{
"docstring": ":type root: TreeNode :type sum: int :rtype: bool",
"name": "hasPathSum",
"signature": "def hasP... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumNumbers(self, root): https://leetcode-cn.com/problems/sum-root-to-leaf-numbers/ :type root: TreeNode :rtype: int
- def hasPathSum(self, root, sum): :type root: TreeNode :t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumNumbers(self, root): https://leetcode-cn.com/problems/sum-root-to-leaf-numbers/ :type root: TreeNode :rtype: int
- def hasPathSum(self, root, sum): :type root: TreeNode :t... | 63ac5a0921835b1e9d65f71e1346bbb7d66dad9b | <|skeleton|>
class Solution:
def sumNumbers(self, root):
"""https://leetcode-cn.com/problems/sum-root-to-leaf-numbers/ :type root: TreeNode :rtype: int"""
<|body_0|>
def hasPathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: bool"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def sumNumbers(self, root):
"""https://leetcode-cn.com/problems/sum-root-to-leaf-numbers/ :type root: TreeNode :rtype: int"""
res = 0
def dfs(node, sumVal):
nonlocal res
if not node:
return
sumVal = sumVal * 10 + node.val
... | the_stack_v2_python_sparse | LeetCode/中等/树/129. 求根到叶子节点数字之和.py | homezzm/leetcode | train | 1 | |
85b64b8c19b12e6c1aad5839e39e5e9348d634ea | [
"INT_MAX = 2 ** 31 - 1\nm = len(matrix)\nif m < 1:\n return matrix\nn = len(matrix[0])\nfor i in range(m):\n for j in range(n):\n if matrix[i][j] != 0:\n matrix[i][j] = INT_MAX - 1\nfor i in range(m):\n for j in range(n):\n if matrix[i][j] != 0:\n if i > 0:\n ... | <|body_start_0|>
INT_MAX = 2 ** 31 - 1
m = len(matrix)
if m < 1:
return matrix
n = len(matrix[0])
for i in range(m):
for j in range(n):
if matrix[i][j] != 0:
matrix[i][j] = INT_MAX - 1
for i in range(m):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def updateMatrix(self, matrix):
""":type matrix: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def updateMatrix2(self, matrix):
""":type matrix: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_008333 | 3,369 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: List[List[int]]",
"name": "updateMatrix",
"signature": "def updateMatrix(self, matrix)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: List[List[int]]",
"name": "updateMatrix2",
"signature": "def updateMatrix2(self, matrix)"... | 2 | stack_v2_sparse_classes_30k_train_003742 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def updateMatrix(self, matrix): :type matrix: List[List[int]] :rtype: List[List[int]]
- def updateMatrix2(self, matrix): :type matrix: List[List[int]] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def updateMatrix(self, matrix): :type matrix: List[List[int]] :rtype: List[List[int]]
- def updateMatrix2(self, matrix): :type matrix: List[List[int]] :rtype: List[List[int]]
<|... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def updateMatrix(self, matrix):
""":type matrix: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def updateMatrix2(self, matrix):
""":type matrix: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def updateMatrix(self, matrix):
""":type matrix: List[List[int]] :rtype: List[List[int]]"""
INT_MAX = 2 ** 31 - 1
m = len(matrix)
if m < 1:
return matrix
n = len(matrix[0])
for i in range(m):
for j in range(n):
i... | the_stack_v2_python_sparse | code542_01Matrix.py | cybelewang/leetcode-python | train | 0 | |
bca6a453a41ba655dafcabc99bc1a5d9f2101500 | [
"self.logger = logging.getLogger(__name__)\nself.enabled = enabled\nself.rank = rank\nself.profiler_output_tmp_dir = None\nself.profiler = None",
"if self.enabled:\n self.profiler_output_tmp_dir = tempfile.TemporaryDirectory()\n self.logger.info(f'Starting profiler (enabled=True) with tmp dir {self.profiler... | <|body_start_0|>
self.logger = logging.getLogger(__name__)
self.enabled = enabled
self.rank = rank
self.profiler_output_tmp_dir = None
self.profiler = None
<|end_body_0|>
<|body_start_1|>
if self.enabled:
self.profiler_output_tmp_dir = tempfile.TemporaryDirec... | This class handles the initialization and setup of PyTorch profiler | PyTorchProfilerHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyTorchProfilerHandler:
"""This class handles the initialization and setup of PyTorch profiler"""
def __init__(self, enabled=False, rank=None):
"""Constructor. Args: enabled (bool): is profiling enabled? export_format (str): generate 'markdown' or 'tensorboard' profile in mlflow arti... | stack_v2_sparse_classes_10k_train_008334 | 6,804 | permissive | [
{
"docstring": "Constructor. Args: enabled (bool): is profiling enabled? export_format (str): generate 'markdown' or 'tensorboard' profile in mlflow artifacts rank (int): rank of the current process/node",
"name": "__init__",
"signature": "def __init__(self, enabled=False, rank=None)"
},
{
"docs... | 3 | null | Implement the Python class `PyTorchProfilerHandler` described below.
Class description:
This class handles the initialization and setup of PyTorch profiler
Method signatures and docstrings:
- def __init__(self, enabled=False, rank=None): Constructor. Args: enabled (bool): is profiling enabled? export_format (str): ge... | Implement the Python class `PyTorchProfilerHandler` described below.
Class description:
This class handles the initialization and setup of PyTorch profiler
Method signatures and docstrings:
- def __init__(self, enabled=False, rank=None): Constructor. Args: enabled (bool): is profiling enabled? export_format (str): ge... | e5f7b247d4753f115a8f7da30cbe25294f71f9d7 | <|skeleton|>
class PyTorchProfilerHandler:
"""This class handles the initialization and setup of PyTorch profiler"""
def __init__(self, enabled=False, rank=None):
"""Constructor. Args: enabled (bool): is profiling enabled? export_format (str): generate 'markdown' or 'tensorboard' profile in mlflow arti... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PyTorchProfilerHandler:
"""This class handles the initialization and setup of PyTorch profiler"""
def __init__(self, enabled=False, rank=None):
"""Constructor. Args: enabled (bool): is profiling enabled? export_format (str): generate 'markdown' or 'tensorboard' profile in mlflow artifacts rank (i... | the_stack_v2_python_sparse | tutorials/e2e-distributed-pytorch-image/src/pytorch_dl_train/profiling.py | Azure/azureml-examples | train | 1,219 |
6cecbce301a792eb28d87a5e8ac57cac14f9b3ec | [
"if not root:\n return 0\nreturn 1 + max(self.maxDepth(root.left), self.maxDepth(root.right))",
"def top_down(root, depth):\n if not root:\n return depth\n return max(top_down(root.left, depth + 1), top_down(root.right, depth + 1))\nreturn top_down(root, 0)",
"if not root:\n return 0\nwhite, ... | <|body_start_0|>
if not root:
return 0
return 1 + max(self.maxDepth(root.left), self.maxDepth(root.right))
<|end_body_0|>
<|body_start_1|>
def top_down(root, depth):
if not root:
return depth
return max(top_down(root.left, depth + 1), top_down... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxDepth(self, root: TreeNode) -> int:
"""递归法（自底向上） 分别计算出左子树的深度，右子树的深度，再计算其最大值 最后+1，是加上根节点这一层"""
<|body_0|>
def maxDepth_1(self, root: TreeNode) -> int:
"""递归法（自顶向下）"""
<|body_1|>
def maxDepth_2(self, root: TreeNode) -> int:
"""层次遍历... | stack_v2_sparse_classes_10k_train_008335 | 1,701 | no_license | [
{
"docstring": "递归法（自底向上） 分别计算出左子树的深度，右子树的深度，再计算其最大值 最后+1，是加上根节点这一层",
"name": "maxDepth",
"signature": "def maxDepth(self, root: TreeNode) -> int"
},
{
"docstring": "递归法（自顶向下）",
"name": "maxDepth_1",
"signature": "def maxDepth_1(self, root: TreeNode) -> int"
},
{
"docstring": "层次... | 3 | stack_v2_sparse_classes_30k_train_001685 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root: TreeNode) -> int: 递归法（自底向上） 分别计算出左子树的深度，右子树的深度，再计算其最大值 最后+1，是加上根节点这一层
- def maxDepth_1(self, root: TreeNode) -> int: 递归法（自顶向下）
- def maxDepth_2(self, roo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root: TreeNode) -> int: 递归法（自底向上） 分别计算出左子树的深度，右子树的深度，再计算其最大值 最后+1，是加上根节点这一层
- def maxDepth_1(self, root: TreeNode) -> int: 递归法（自顶向下）
- def maxDepth_2(self, roo... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def maxDepth(self, root: TreeNode) -> int:
"""递归法（自底向上） 分别计算出左子树的深度，右子树的深度，再计算其最大值 最后+1，是加上根节点这一层"""
<|body_0|>
def maxDepth_1(self, root: TreeNode) -> int:
"""递归法（自顶向下）"""
<|body_1|>
def maxDepth_2(self, root: TreeNode) -> int:
"""层次遍历... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxDepth(self, root: TreeNode) -> int:
"""递归法（自底向上） 分别计算出左子树的深度，右子树的深度，再计算其最大值 最后+1，是加上根节点这一层"""
if not root:
return 0
return 1 + max(self.maxDepth(root.left), self.maxDepth(root.right))
def maxDepth_1(self, root: TreeNode) -> int:
"""递归法（自顶向下）"""... | the_stack_v2_python_sparse | algorithm/leetcode/tree/07-二叉树的最大深度.py | lxconfig/UbuntuCode_bak | train | 0 | |
1b6f047e9ae92ee4b46bf17206fa5402cbab9305 | [
"self.signup('healer')\nresponse = self.rest_client.get(reverse('provider_setup_intro'))\nself.assertEqual(response.status_code, 200)\nresponse = self.rest_client.get(reverse('notes'))\nself.assertEqual(response.status_code, 302)",
"self.signup()\nresponse = self.rest_client.get(reverse('provider_setup_intro'))\n... | <|body_start_0|>
self.signup('healer')
response = self.rest_client.get(reverse('provider_setup_intro'))
self.assertEqual(response.status_code, 200)
response = self.rest_client.get(reverse('notes'))
self.assertEqual(response.status_code, 302)
<|end_body_0|>
<|body_start_1|>
... | SignupAccessTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignupAccessTest:
def test_healer_not_confirmed(self):
"""Only setup should be available for healers without confirmed emails on signup."""
<|body_0|>
def test_client_not_confirmed(self):
"""Clients should not login on signup if email is not confirmed."""
<|b... | stack_v2_sparse_classes_10k_train_008336 | 38,593 | no_license | [
{
"docstring": "Only setup should be available for healers without confirmed emails on signup.",
"name": "test_healer_not_confirmed",
"signature": "def test_healer_not_confirmed(self)"
},
{
"docstring": "Clients should not login on signup if email is not confirmed.",
"name": "test_client_not... | 2 | stack_v2_sparse_classes_30k_train_004179 | Implement the Python class `SignupAccessTest` described below.
Class description:
Implement the SignupAccessTest class.
Method signatures and docstrings:
- def test_healer_not_confirmed(self): Only setup should be available for healers without confirmed emails on signup.
- def test_client_not_confirmed(self): Clients... | Implement the Python class `SignupAccessTest` described below.
Class description:
Implement the SignupAccessTest class.
Method signatures and docstrings:
- def test_healer_not_confirmed(self): Only setup should be available for healers without confirmed emails on signup.
- def test_client_not_confirmed(self): Clients... | 681ef09e4044879840f7f0c8bccc836c3cffec3c | <|skeleton|>
class SignupAccessTest:
def test_healer_not_confirmed(self):
"""Only setup should be available for healers without confirmed emails on signup."""
<|body_0|>
def test_client_not_confirmed(self):
"""Clients should not login on signup if email is not confirmed."""
<|b... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SignupAccessTest:
def test_healer_not_confirmed(self):
"""Only setup should be available for healers without confirmed emails on signup."""
self.signup('healer')
response = self.rest_client.get(reverse('provider_setup_intro'))
self.assertEqual(response.status_code, 200)
... | the_stack_v2_python_sparse | apps/account_hs/tests.py | RumorIO/healersource | train | 0 | |
295dfed522f472e30dac1cc6219bac27a9ad0ac8 | [
"b = torch.div(f, 1000.0)\nb = torch.pow(b, 2.0) * 1.4\nb = torch.pow(b + 1.0, 0.69)\nreturn b * 75.0 + 25.0",
"f = torch.div(x - 25.0, 75.0)\nf = torch.pow(f, 1.0 / 0.69)\nf = torch.div(f - 1.0, 1.4)\nf = torch.pow(f, 0.5)\nreturn f * 1000.0",
"assert check_argument_types()\nmin_center_frequency = torch.tensor... | <|body_start_0|>
b = torch.div(f, 1000.0)
b = torch.pow(b, 2.0) * 1.4
b = torch.pow(b + 1.0, 0.69)
return b * 75.0 + 25.0
<|end_body_0|>
<|body_start_1|>
f = torch.div(x - 25.0, 75.0)
f = torch.pow(f, 1.0 / 0.69)
f = torch.div(f - 1.0, 1.4)
f = torch.pow(... | Bark frequency scale. Has wider bandwidths at lower frequencies, see: Critical bandwidth: BARK Zwicker and Terhardt, 1980 | BarkScale | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BarkScale:
"""Bark frequency scale. Has wider bandwidths at lower frequencies, see: Critical bandwidth: BARK Zwicker and Terhardt, 1980"""
def convert(f):
"""Convert Hz to Bark."""
<|body_0|>
def invert(x):
"""Convert Bark to Hz."""
<|body_1|>
def ba... | stack_v2_sparse_classes_10k_train_008337 | 9,034 | permissive | [
{
"docstring": "Convert Hz to Bark.",
"name": "convert",
"signature": "def convert(f)"
},
{
"docstring": "Convert Bark to Hz.",
"name": "invert",
"signature": "def invert(x)"
},
{
"docstring": "Obtain initialization values for the Bark scale. Args: channels: Number of channels. f... | 3 | stack_v2_sparse_classes_30k_train_002577 | Implement the Python class `BarkScale` described below.
Class description:
Bark frequency scale. Has wider bandwidths at lower frequencies, see: Critical bandwidth: BARK Zwicker and Terhardt, 1980
Method signatures and docstrings:
- def convert(f): Convert Hz to Bark.
- def invert(x): Convert Bark to Hz.
- def bank(c... | Implement the Python class `BarkScale` described below.
Class description:
Bark frequency scale. Has wider bandwidths at lower frequencies, see: Critical bandwidth: BARK Zwicker and Terhardt, 1980
Method signatures and docstrings:
- def convert(f): Convert Hz to Bark.
- def invert(x): Convert Bark to Hz.
- def bank(c... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class BarkScale:
"""Bark frequency scale. Has wider bandwidths at lower frequencies, see: Critical bandwidth: BARK Zwicker and Terhardt, 1980"""
def convert(f):
"""Convert Hz to Bark."""
<|body_0|>
def invert(x):
"""Convert Bark to Hz."""
<|body_1|>
def ba... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BarkScale:
"""Bark frequency scale. Has wider bandwidths at lower frequencies, see: Critical bandwidth: BARK Zwicker and Terhardt, 1980"""
def convert(f):
"""Convert Hz to Bark."""
b = torch.div(f, 1000.0)
b = torch.pow(b, 2.0) * 1.4
b = torch.pow(b + 1.0, 0.69)
re... | the_stack_v2_python_sparse | espnet2/layers/sinc_conv.py | espnet/espnet | train | 7,242 |
a141ec628b5b6d9fcd3d9af3bf0f485ea2e7d2d6 | [
"if not nums:\n return nums\nred = 0\nwhite = 0\nblue = 0\nindex = 0\nfor item in nums:\n if item == 0:\n red += 1\n elif item == 1:\n white += 1\n else:\n blue += 1\nwhile red > 0:\n nums[index] = 0\n index += 1\n red -= 1\nwhile white > 0:\n nums[index] = 1\n index ... | <|body_start_0|>
if not nums:
return nums
red = 0
white = 0
blue = 0
index = 0
for item in nums:
if item == 0:
red += 1
elif item == 1:
white += 1
else:
blue += 1
while... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortColors(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def sortColors2(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""... | stack_v2_sparse_classes_10k_train_008338 | 2,355 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.",
"name": "sortColors",
"signature": "def sortColors(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.",
"name": "so... | 2 | stack_v2_sparse_classes_30k_train_006024 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortColors(self, nums): :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.
- def sortColors2(self, nums): :type nums: List[int] :rtype: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortColors(self, nums): :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.
- def sortColors2(self, nums): :type nums: List[int] :rtype: ... | 2866df7587ee867a958a2b4fc02345bc3ef56999 | <|skeleton|>
class Solution:
def sortColors(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def sortColors2(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def sortColors(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
if not nums:
return nums
red = 0
white = 0
blue = 0
index = 0
for item in nums:
if item == 0:
... | the_stack_v2_python_sparse | 中级算法/sortColors.py | OrangeJessie/Fighting_Leetcode | train | 1 | |
09222643100a3693261a4aa64611fff7bd981946 | [
"try:\n return Post.objects.get(id=id)\nexcept Post.DoesNotExist:\n raise Http404",
"postObject = self.get_object(id)\nresponse = self.serializer_class(postObject)\nreturn Response(response.data)",
"posts = self.get_object(id)\nposts.delete()\nreturn Response(status=status.HTTP_204_NO_CONTENT)"
] | <|body_start_0|>
try:
return Post.objects.get(id=id)
except Post.DoesNotExist:
raise Http404
<|end_body_0|>
<|body_start_1|>
postObject = self.get_object(id)
response = self.serializer_class(postObject)
return Response(response.data)
<|end_body_1|>
<|bod... | This class is an API for geting newsfeed posts information. | PostViewDetail | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostViewDetail:
"""This class is an API for geting newsfeed posts information."""
def get_object(self, id):
"""Get post by id. Args: id: id of post. Return: post object."""
<|body_0|>
def get(self, request, id=None, format=None):
"""Get single post object by id. ... | stack_v2_sparse_classes_10k_train_008339 | 17,464 | no_license | [
{
"docstring": "Get post by id. Args: id: id of post. Return: post object.",
"name": "get_object",
"signature": "def get_object(self, id)"
},
{
"docstring": "Get single post object by id. Args: request: Django Rest Framework request object. id: id of post. format: pattern for Web APIs. Return: S... | 3 | stack_v2_sparse_classes_30k_train_002734 | Implement the Python class `PostViewDetail` described below.
Class description:
This class is an API for geting newsfeed posts information.
Method signatures and docstrings:
- def get_object(self, id): Get post by id. Args: id: id of post. Return: post object.
- def get(self, request, id=None, format=None): Get singl... | Implement the Python class `PostViewDetail` described below.
Class description:
This class is an API for geting newsfeed posts information.
Method signatures and docstrings:
- def get_object(self, id): Get post by id. Args: id: id of post. Return: post object.
- def get(self, request, id=None, format=None): Get singl... | 1d01b8133669208cdd35d4aa61a41521ecd52720 | <|skeleton|>
class PostViewDetail:
"""This class is an API for geting newsfeed posts information."""
def get_object(self, id):
"""Get post by id. Args: id: id of post. Return: post object."""
<|body_0|>
def get(self, request, id=None, format=None):
"""Get single post object by id. ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PostViewDetail:
"""This class is an API for geting newsfeed posts information."""
def get_object(self, id):
"""Get post by id. Args: id: id of post. Return: post object."""
try:
return Post.objects.get(id=id)
except Post.DoesNotExist:
raise Http404
def... | the_stack_v2_python_sparse | newsfeed/views.py | whsatku/social | train | 10 |
3a170742570a1bdd95daf55499a98b63a475e575 | [
"if self._attrMap is not None:\n for key in self.__dict__.keys():\n if key[0] != '_':\n msg = 'Unexpected attribute %s found in %s' % (key, self)\n assert key in self._attrMap, msg\n for attr, metavalue in self._attrMap.items():\n msg = 'Missing attribute %s from %s' % (att... | <|body_start_0|>
if self._attrMap is not None:
for key in self.__dict__.keys():
if key[0] != '_':
msg = 'Unexpected attribute %s found in %s' % (key, self)
assert key in self._attrMap, msg
for attr, metavalue in self._attrMap.items(... | Base for property holders | PropHolder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PropHolder:
"""Base for property holders"""
def verify(self):
"""If the _attrMap attribute is not None, this checks all expected attributes are present; no unwanted attributes are present; and (if a checking function is found) checks each attribute has a valid value. Either succeeds ... | stack_v2_sparse_classes_10k_train_008340 | 18,700 | permissive | [
{
"docstring": "If the _attrMap attribute is not None, this checks all expected attributes are present; no unwanted attributes are present; and (if a checking function is found) checks each attribute has a valid value. Either succeeds or raises an informative exception.",
"name": "verify",
"signature": ... | 4 | null | Implement the Python class `PropHolder` described below.
Class description:
Base for property holders
Method signatures and docstrings:
- def verify(self): If the _attrMap attribute is not None, this checks all expected attributes are present; no unwanted attributes are present; and (if a checking function is found) ... | Implement the Python class `PropHolder` described below.
Class description:
Base for property holders
Method signatures and docstrings:
- def verify(self): If the _attrMap attribute is not None, this checks all expected attributes are present; no unwanted attributes are present; and (if a checking function is found) ... | cabf6e4f1970dc14302f87414f170de19944bac2 | <|skeleton|>
class PropHolder:
"""Base for property holders"""
def verify(self):
"""If the _attrMap attribute is not None, this checks all expected attributes are present; no unwanted attributes are present; and (if a checking function is found) checks each attribute has a valid value. Either succeeds ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PropHolder:
"""Base for property holders"""
def verify(self):
"""If the _attrMap attribute is not None, this checks all expected attributes are present; no unwanted attributes are present; and (if a checking function is found) checks each attribute has a valid value. Either succeeds or raises an ... | the_stack_v2_python_sparse | Pdf_docx_pptx_xlsx_epub_png/source/reportlab/graphics/widgetbase.py | ryfeus/lambda-packs | train | 1,283 |
861b7761560f515ea622702bf5094957313ced07 | [
"self.index = 0\nself.twitters = dict()\nself.followers = dict()",
"if userId in self.twitters:\n self.twitters[userId].append((tweetId, self.index))\nelse:\n self.twitters.setdefault(userId, [(tweetId, self.index)])\nself.index += 1",
"tweets = []\nif userId in self.twitters:\n tweets += self.twitters... | <|body_start_0|>
self.index = 0
self.twitters = dict()
self.followers = dict()
<|end_body_0|>
<|body_start_1|>
if userId in self.twitters:
self.twitters[userId].append((tweetId, self.index))
else:
self.twitters.setdefault(userId, [(tweetId, self.index)])
... | Twitter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
<|body_1|>
def getNewsFeed(self, userId: int) -> list:
"""Retrieve the 10 most r... | stack_v2_sparse_classes_10k_train_008341 | 2,372 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compose a new tweet.",
"name": "postTweet",
"signature": "def postTweet(self, userId: int, tweetId: int) -> None"
},
{
"docstring": "Retrieve the 10 mos... | 5 | stack_v2_sparse_classes_30k_train_000908 | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId: int, tweetId: int) -> None: Compose a new tweet.
- def getNewsFeed(self, userId: int) -> list... | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId: int, tweetId: int) -> None: Compose a new tweet.
- def getNewsFeed(self, userId: int) -> list... | 4416d0c711b8978f12de960c29d00a9d9792b9e0 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
<|body_1|>
def getNewsFeed(self, userId: int) -> list:
"""Retrieve the 10 most r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Twitter:
def __init__(self):
"""Initialize your data structure here."""
self.index = 0
self.twitters = dict()
self.followers = dict()
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
if userId in self.twitters:
... | the_stack_v2_python_sparse | 301-400/355. Design Twitter.py | Ys-Zhou/leetcode-medi-p3 | train | 0 | |
bac192a712995eb015617aa410cf905788ae7070 | [
"super().__init__()\nself.input_dim = input_dim\nself.hidden_size = hidden_size\nself.num_layers = num_layers\nself.num_classes = num_classes\nself.output_dim = output_dim\nself.lstm_layer = nn.LSTM(input_dim, hidden_size, num_layers, batch_first=True)\nself.linear = nn.Linear(self.hidden_size, output_dim)\nself.ou... | <|body_start_0|>
super().__init__()
self.input_dim = input_dim
self.hidden_size = hidden_size
self.num_layers = num_layers
self.num_classes = num_classes
self.output_dim = output_dim
self.lstm_layer = nn.LSTM(input_dim, hidden_size, num_layers, batch_first=True)
... | Simple LSTM decoder. | LSTM_attention_embedding_decoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSTM_attention_embedding_decoder:
"""Simple LSTM decoder."""
def __init__(self, input_dim, hidden_size, output_dim, num_classes, num_layers=1):
"""Initialize model with params."""
<|body_0|>
def forward(self, inp, hidden):
"""Forward pass through LSTM layer. shap... | stack_v2_sparse_classes_10k_train_008342 | 1,863 | permissive | [
{
"docstring": "Initialize model with params.",
"name": "__init__",
"signature": "def __init__(self, input_dim, hidden_size, output_dim, num_classes, num_layers=1)"
},
{
"docstring": "Forward pass through LSTM layer. shape of lstm_out: [input_size, batch_size, hidden_dim] shape of self.hidden: (... | 2 | stack_v2_sparse_classes_30k_train_005900 | Implement the Python class `LSTM_attention_embedding_decoder` described below.
Class description:
Simple LSTM decoder.
Method signatures and docstrings:
- def __init__(self, input_dim, hidden_size, output_dim, num_classes, num_layers=1): Initialize model with params.
- def forward(self, inp, hidden): Forward pass thr... | Implement the Python class `LSTM_attention_embedding_decoder` described below.
Class description:
Simple LSTM decoder.
Method signatures and docstrings:
- def __init__(self, input_dim, hidden_size, output_dim, num_classes, num_layers=1): Initialize model with params.
- def forward(self, inp, hidden): Forward pass thr... | 9cdbf270487751a0ad6862b2fea2ccc0e23a0b67 | <|skeleton|>
class LSTM_attention_embedding_decoder:
"""Simple LSTM decoder."""
def __init__(self, input_dim, hidden_size, output_dim, num_classes, num_layers=1):
"""Initialize model with params."""
<|body_0|>
def forward(self, inp, hidden):
"""Forward pass through LSTM layer. shap... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LSTM_attention_embedding_decoder:
"""Simple LSTM decoder."""
def __init__(self, input_dim, hidden_size, output_dim, num_classes, num_layers=1):
"""Initialize model with params."""
super().__init__()
self.input_dim = input_dim
self.hidden_size = hidden_size
self.num... | the_stack_v2_python_sparse | caspr/models/lstm_decoder.py | microsoft/CASPR | train | 29 |
9923f29d3cc88b68ee931e8f9406b423c8e0f587 | [
"try:\n article = Articles.objects.get(slug=self.kwargs['slug'])\nexcept Articles.DoesNotExist:\n return Response({'errors': COMMENTS_MSG['ARTICLE_DOES_NOT_EXIST']}, status=status.HTTP_404_NOT_FOUND)\ntry:\n comment = Comment.objects.get(pk=self.kwargs['id'])\n serializer = self.serializer_class(comment... | <|body_start_0|>
try:
article = Articles.objects.get(slug=self.kwargs['slug'])
except Articles.DoesNotExist:
return Response({'errors': COMMENTS_MSG['ARTICLE_DOES_NOT_EXIST']}, status=status.HTTP_404_NOT_FOUND)
try:
comment = Comment.objects.get(pk=self.kwargs... | Handles viewing of a specific comment if not authenticated and Handles replying to a comment on an article if authenticated Handles Deleting a comment from an article | RetrieveUpdateDeleteCommentAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RetrieveUpdateDeleteCommentAPIView:
"""Handles viewing of a specific comment if not authenticated and Handles replying to a comment on an article if authenticated Handles Deleting a comment from an article"""
def get(self, request, *args, **kwargs):
"""Handles retrieving a specific c... | stack_v2_sparse_classes_10k_train_008343 | 7,543 | permissive | [
{
"docstring": "Handles retrieving a specific comment and all their replies :param request: :param args: :param kwargs: :return:",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Handles updating a comment if author is same as the requester :param request... | 3 | stack_v2_sparse_classes_30k_val_000083 | Implement the Python class `RetrieveUpdateDeleteCommentAPIView` described below.
Class description:
Handles viewing of a specific comment if not authenticated and Handles replying to a comment on an article if authenticated Handles Deleting a comment from an article
Method signatures and docstrings:
- def get(self, r... | Implement the Python class `RetrieveUpdateDeleteCommentAPIView` described below.
Class description:
Handles viewing of a specific comment if not authenticated and Handles replying to a comment on an article if authenticated Handles Deleting a comment from an article
Method signatures and docstrings:
- def get(self, r... | 5a31840856de4b361fe2594dfa7a33d7774d3fe2 | <|skeleton|>
class RetrieveUpdateDeleteCommentAPIView:
"""Handles viewing of a specific comment if not authenticated and Handles replying to a comment on an article if authenticated Handles Deleting a comment from an article"""
def get(self, request, *args, **kwargs):
"""Handles retrieving a specific c... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RetrieveUpdateDeleteCommentAPIView:
"""Handles viewing of a specific comment if not authenticated and Handles replying to a comment on an article if authenticated Handles Deleting a comment from an article"""
def get(self, request, *args, **kwargs):
"""Handles retrieving a specific comment and al... | the_stack_v2_python_sparse | authors/apps/comments/views.py | bl4ck4ndbr0wn/ah-centauri-backend | train | 0 |
fbea40680de29349759c2331af73f633b42a45b0 | [
"try:\n self.UDPlist = UDPlist_p\n self.sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n self.sock.bind(('', UDP_PORT))\n hasUDP = True\nexcept socket.error:\n hasUDP = False\n print('AHF_UDPTrig failed to create a socket.')",
"try:\n for address in self.UDPlist:\n self.sock.s... | <|body_start_0|>
try:
self.UDPlist = UDPlist_p
self.sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
self.sock.bind(('', UDP_PORT))
hasUDP = True
except socket.error:
hasUDP = False
print('AHF_UDPTrig failed to create a socke... | Sends/receives UDP signals as to another pi to start/stop recording AHF_UDPTrig uses the socket module to do the UDP stuff, but it should be part of the default install | AHF_UDPTrig | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AHF_UDPTrig:
"""Sends/receives UDP signals as to another pi to start/stop recording AHF_UDPTrig uses the socket module to do the UDP stuff, but it should be part of the default install"""
def __init__(self, UDPlist_p):
"""Makes a new AHF_UDPtrig object using passed in list of ip addr... | stack_v2_sparse_classes_10k_train_008344 | 1,743 | no_license | [
{
"docstring": "Makes a new AHF_UDPtrig object using passed in list of ip addresses. stores UDPlist in the new object sets hasUDP to false if object creation fails because of network error, else True",
"name": "__init__",
"signature": "def __init__(self, UDPlist_p)"
},
{
"docstring": "Sends a UD... | 3 | stack_v2_sparse_classes_30k_test_000344 | Implement the Python class `AHF_UDPTrig` described below.
Class description:
Sends/receives UDP signals as to another pi to start/stop recording AHF_UDPTrig uses the socket module to do the UDP stuff, but it should be part of the default install
Method signatures and docstrings:
- def __init__(self, UDPlist_p): Makes... | Implement the Python class `AHF_UDPTrig` described below.
Class description:
Sends/receives UDP signals as to another pi to start/stop recording AHF_UDPTrig uses the socket module to do the UDP stuff, but it should be part of the default install
Method signatures and docstrings:
- def __init__(self, UDPlist_p): Makes... | a7fa58f47cfbb92de1f6c33d003bc290f1f37d86 | <|skeleton|>
class AHF_UDPTrig:
"""Sends/receives UDP signals as to another pi to start/stop recording AHF_UDPTrig uses the socket module to do the UDP stuff, but it should be part of the default install"""
def __init__(self, UDPlist_p):
"""Makes a new AHF_UDPtrig object using passed in list of ip addr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AHF_UDPTrig:
"""Sends/receives UDP signals as to another pi to start/stop recording AHF_UDPTrig uses the socket module to do the UDP stuff, but it should be part of the default install"""
def __init__(self, UDPlist_p):
"""Makes a new AHF_UDPtrig object using passed in list of ip addresses. stores... | the_stack_v2_python_sparse | moreModules/AutoHeadFix/AHF_UDPTrig.py | ilangold/AutoHeadFix | train | 0 |
b80e52d2f5ae92891d6486075e20d9a98e04a0e0 | [
"x, y, z = self.coords\nif self.orientation == '+x':\n yield (x - 1, y, z)\nelif self.orientation == '-x':\n yield (x + 1, y, z)\nelif self.orientation == '+z':\n yield (x, y, z - 1)\nelif self.orientation == '-z':\n yield (x, y, z + 1)\nelif self.orientation == '+y':\n yield (x, y - 1, z)",
"x, y,... | <|body_start_0|>
x, y, z = self.coords
if self.orientation == '+x':
yield (x - 1, y, z)
elif self.orientation == '-x':
yield (x + 1, y, z)
elif self.orientation == '+z':
yield (x, y, z - 1)
elif self.orientation == '-z':
yield (x, y... | A redstone torch. Torches do a NOT operation from their input. | Torch | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Torch:
"""A redstone torch. Torches do a NOT operation from their input."""
def iter_inputs(self):
"""Provide the input corresponding to the block upon which this torch is mounted."""
<|body_0|>
def iter_outputs(self):
"""Provide the outputs corresponding to the ... | stack_v2_sparse_classes_10k_train_008345 | 13,022 | permissive | [
{
"docstring": "Provide the input corresponding to the block upon which this torch is mounted.",
"name": "iter_inputs",
"signature": "def iter_inputs(self)"
},
{
"docstring": "Provide the outputs corresponding to the block upon which this torch is mounted.",
"name": "iter_outputs",
"sign... | 2 | stack_v2_sparse_classes_30k_train_001262 | Implement the Python class `Torch` described below.
Class description:
A redstone torch. Torches do a NOT operation from their input.
Method signatures and docstrings:
- def iter_inputs(self): Provide the input corresponding to the block upon which this torch is mounted.
- def iter_outputs(self): Provide the outputs ... | Implement the Python class `Torch` described below.
Class description:
A redstone torch. Torches do a NOT operation from their input.
Method signatures and docstrings:
- def iter_inputs(self): Provide the input corresponding to the block upon which this torch is mounted.
- def iter_outputs(self): Provide the outputs ... | 7be5d792871a8447499911fa1502c6a7c1437dc3 | <|skeleton|>
class Torch:
"""A redstone torch. Torches do a NOT operation from their input."""
def iter_inputs(self):
"""Provide the input corresponding to the block upon which this torch is mounted."""
<|body_0|>
def iter_outputs(self):
"""Provide the outputs corresponding to the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Torch:
"""A redstone torch. Torches do a NOT operation from their input."""
def iter_inputs(self):
"""Provide the input corresponding to the block upon which this torch is mounted."""
x, y, z = self.coords
if self.orientation == '+x':
yield (x - 1, y, z)
elif s... | the_stack_v2_python_sparse | bravo/utilities/redstone.py | CyberFlameGO/bravo | train | 0 |
a0c71bebfec8a4e9c5f85e6dda4a021f3bd32c9f | [
"if start_time is None:\n self.started = time.time()\nelse:\n self.started = start_time",
"ended = time.time()\nstarted_wait = datetime.datetime.fromtimestamp(self.started).strftime('%Y-%m-%d %H:%M:%S')\nraised_date = datetime.datetime.fromtimestamp(ended).strftime('%Y-%m-%d %H:%M:%S')\nduration = ended - s... | <|body_start_0|>
if start_time is None:
self.started = time.time()
else:
self.started = start_time
<|end_body_0|>
<|body_start_1|>
ended = time.time()
started_wait = datetime.datetime.fromtimestamp(self.started).strftime('%Y-%m-%d %H:%M:%S')
raised_date =... | Holds timeout exception information. | TimeoutExceptionInfo | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeoutExceptionInfo:
"""Holds timeout exception information."""
def __init__(self, start_time=None):
"""Mark the time for started waiting."""
<|body_0|>
def msg(self):
"""Return a message to be used by TimeoutException containing timing information."""
<... | stack_v2_sparse_classes_10k_train_008346 | 14,890 | permissive | [
{
"docstring": "Mark the time for started waiting.",
"name": "__init__",
"signature": "def __init__(self, start_time=None)"
},
{
"docstring": "Return a message to be used by TimeoutException containing timing information.",
"name": "msg",
"signature": "def msg(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004308 | Implement the Python class `TimeoutExceptionInfo` described below.
Class description:
Holds timeout exception information.
Method signatures and docstrings:
- def __init__(self, start_time=None): Mark the time for started waiting.
- def msg(self): Return a message to be used by TimeoutException containing timing info... | Implement the Python class `TimeoutExceptionInfo` described below.
Class description:
Holds timeout exception information.
Method signatures and docstrings:
- def __init__(self, start_time=None): Mark the time for started waiting.
- def msg(self): Return a message to be used by TimeoutException containing timing info... | 69c082d2bf9b9985db77d1d25a3f423ecf016e00 | <|skeleton|>
class TimeoutExceptionInfo:
"""Holds timeout exception information."""
def __init__(self, start_time=None):
"""Mark the time for started waiting."""
<|body_0|>
def msg(self):
"""Return a message to be used by TimeoutException containing timing information."""
<... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TimeoutExceptionInfo:
"""Holds timeout exception information."""
def __init__(self, start_time=None):
"""Mark the time for started waiting."""
if start_time is None:
self.started = time.time()
else:
self.started = start_time
def msg(self):
"""R... | the_stack_v2_python_sparse | testplan/common/utils/timing.py | morganstanley/testplan | train | 78 |
a966b5b6e49d1b8dd50721541fe866b7c4c5a03b | [
"self.day = day\nself.month = month\nself.year = year",
"if cls.is_valid_date(astring):\n day, month, year = map(int, astring.split('-'))\n return cls(day, month, year)\nelse:\n raise IOError(f'{astring!r} is not a valid date string.')",
"try:\n day, month, year = map(int, astring.split('-'))\nexcep... | <|body_start_0|>
self.day = day
self.month = month
self.year = year
<|end_body_0|>
<|body_start_1|>
if cls.is_valid_date(astring):
day, month, year = map(int, astring.split('-'))
return cls(day, month, year)
else:
raise IOError(f'{astring!r} i... | Source: https://stackoverflow.com/questions/12179271 | Date | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Date:
"""Source: https://stackoverflow.com/questions/12179271"""
def __init__(self, day=0, month=0, year=0):
"""Initialize from day, month and year values (no verification)."""
<|body_0|>
def from_string(cls, astring):
"""Initialize from (verified) 'day-month-yea... | stack_v2_sparse_classes_10k_train_008347 | 3,912 | no_license | [
{
"docstring": "Initialize from day, month and year values (no verification).",
"name": "__init__",
"signature": "def __init__(self, day=0, month=0, year=0)"
},
{
"docstring": "Initialize from (verified) 'day-month-year' string.",
"name": "from_string",
"signature": "def from_string(cls,... | 3 | stack_v2_sparse_classes_30k_train_001046 | Implement the Python class `Date` described below.
Class description:
Source: https://stackoverflow.com/questions/12179271
Method signatures and docstrings:
- def __init__(self, day=0, month=0, year=0): Initialize from day, month and year values (no verification).
- def from_string(cls, astring): Initialize from (ver... | Implement the Python class `Date` described below.
Class description:
Source: https://stackoverflow.com/questions/12179271
Method signatures and docstrings:
- def __init__(self, day=0, month=0, year=0): Initialize from day, month and year values (no verification).
- def from_string(cls, astring): Initialize from (ver... | dd931c09fe5229907a93f3c3992924650abb3315 | <|skeleton|>
class Date:
"""Source: https://stackoverflow.com/questions/12179271"""
def __init__(self, day=0, month=0, year=0):
"""Initialize from day, month and year values (no verification)."""
<|body_0|>
def from_string(cls, astring):
"""Initialize from (verified) 'day-month-yea... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Date:
"""Source: https://stackoverflow.com/questions/12179271"""
def __init__(self, day=0, month=0, year=0):
"""Initialize from day, month and year values (no verification)."""
self.day = day
self.month = month
self.year = year
def from_string(cls, astring):
"... | the_stack_v2_python_sparse | Cours/avance.py | ycopin/Informatique-Python | train | 3 |
b15fc00fca98dc8e6cd574dd22bd024021e6d4f6 | [
"data = base_importData()\ndata.read_csv(filename)\ndata.format_data()\nself.add_data_stage02_isotopomer_measuredFluxes(data.data)\ndata.clear_data()",
"data = base_importData()\ndata.read_csv(filename)\ndata.format_data()\nself.add_data_stage02_isotopomer_measuredFragments(data.data)\ndata.clear_data()",
"data... | <|body_start_0|>
data = base_importData()
data.read_csv(filename)
data.format_data()
self.add_data_stage02_isotopomer_measuredFluxes(data.data)
data.clear_data()
<|end_body_0|>
<|body_start_1|>
data = base_importData()
data.read_csv(filename)
data.format_... | stage02_isotopomer_measuredData_io | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stage02_isotopomer_measuredData_io:
def import_data_stage02_isotopomer_measuredFluxes_add(self, filename):
"""table adds"""
<|body_0|>
def import_data_stage02_isotopomer_measuredFragments_add(self, filename):
"""table adds"""
<|body_1|>
def export_data_s... | stack_v2_sparse_classes_10k_train_008348 | 3,229 | permissive | [
{
"docstring": "table adds",
"name": "import_data_stage02_isotopomer_measuredFluxes_add",
"signature": "def import_data_stage02_isotopomer_measuredFluxes_add(self, filename)"
},
{
"docstring": "table adds",
"name": "import_data_stage02_isotopomer_measuredFragments_add",
"signature": "def... | 4 | stack_v2_sparse_classes_30k_train_004456 | Implement the Python class `stage02_isotopomer_measuredData_io` described below.
Class description:
Implement the stage02_isotopomer_measuredData_io class.
Method signatures and docstrings:
- def import_data_stage02_isotopomer_measuredFluxes_add(self, filename): table adds
- def import_data_stage02_isotopomer_measure... | Implement the Python class `stage02_isotopomer_measuredData_io` described below.
Class description:
Implement the stage02_isotopomer_measuredData_io class.
Method signatures and docstrings:
- def import_data_stage02_isotopomer_measuredFluxes_add(self, filename): table adds
- def import_data_stage02_isotopomer_measure... | 005e1d34c2ace7e28c53dffcab3e9cb8c7e7ce18 | <|skeleton|>
class stage02_isotopomer_measuredData_io:
def import_data_stage02_isotopomer_measuredFluxes_add(self, filename):
"""table adds"""
<|body_0|>
def import_data_stage02_isotopomer_measuredFragments_add(self, filename):
"""table adds"""
<|body_1|>
def export_data_s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class stage02_isotopomer_measuredData_io:
def import_data_stage02_isotopomer_measuredFluxes_add(self, filename):
"""table adds"""
data = base_importData()
data.read_csv(filename)
data.format_data()
self.add_data_stage02_isotopomer_measuredFluxes(data.data)
data.clear_... | the_stack_v2_python_sparse | SBaaS_MFA/stage02_isotopomer_measuredData_io.py | dmccloskey/SBaaS_MFA | train | 0 | |
4abd4942fd2439d6baf79daba82575febd901a5e | [
"super(EncodingLayer, self).__init__(**kwargs)\nself._initial_keep_rate = initial_keep_rate\nself._decay_interval = decay_interval\nself._decay_rate = decay_rate\nself._w_itr_att = None\nself._w1 = None\nself._w2 = None\nself._w3 = None\nself._b1 = None\nself._b2 = None\nself._b3 = None",
"d = input_shape[-1]\nse... | <|body_start_0|>
super(EncodingLayer, self).__init__(**kwargs)
self._initial_keep_rate = initial_keep_rate
self._decay_interval = decay_interval
self._decay_rate = decay_rate
self._w_itr_att = None
self._w1 = None
self._w2 = None
self._w3 = None
se... | Apply a self-attention layer and a semantic composite fuse gate to compute the encoding result of one tensor. :param initial_keep_rate: the initial_keep_rate parameter of DecayingDropoutLayer. :param decay_interval: the decay_interval parameter of DecayingDropoutLayer. :param decay_rate: the decay_rate parameter of Dec... | EncodingLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncodingLayer:
"""Apply a self-attention layer and a semantic composite fuse gate to compute the encoding result of one tensor. :param initial_keep_rate: the initial_keep_rate parameter of DecayingDropoutLayer. :param decay_interval: the decay_interval parameter of DecayingDropoutLayer. :param de... | stack_v2_sparse_classes_10k_train_008349 | 4,198 | permissive | [
{
"docstring": ":class: 'EncodingLayer' constructor.",
"name": "__init__",
"signature": "def __init__(self, initial_keep_rate: float, decay_interval: int, decay_rate: float, **kwargs)"
},
{
"docstring": "Build the layer. :param input_shape: the shape of the input tensor, for EncodingLayer we nee... | 3 | stack_v2_sparse_classes_30k_train_007034 | Implement the Python class `EncodingLayer` described below.
Class description:
Apply a self-attention layer and a semantic composite fuse gate to compute the encoding result of one tensor. :param initial_keep_rate: the initial_keep_rate parameter of DecayingDropoutLayer. :param decay_interval: the decay_interval param... | Implement the Python class `EncodingLayer` described below.
Class description:
Apply a self-attention layer and a semantic composite fuse gate to compute the encoding result of one tensor. :param initial_keep_rate: the initial_keep_rate parameter of DecayingDropoutLayer. :param decay_interval: the decay_interval param... | 1f763062c6cc861e93ccdba23d0f1f0171f74145 | <|skeleton|>
class EncodingLayer:
"""Apply a self-attention layer and a semantic composite fuse gate to compute the encoding result of one tensor. :param initial_keep_rate: the initial_keep_rate parameter of DecayingDropoutLayer. :param decay_interval: the decay_interval parameter of DecayingDropoutLayer. :param de... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EncodingLayer:
"""Apply a self-attention layer and a semantic composite fuse gate to compute the encoding result of one tensor. :param initial_keep_rate: the initial_keep_rate parameter of DecayingDropoutLayer. :param decay_interval: the decay_interval parameter of DecayingDropoutLayer. :param decay_rate: the... | the_stack_v2_python_sparse | matchzoo/contrib/layers/semantic_composite_layer.py | JRetza/MatchZoo | train | 1 |
fe562d7ac4da2a2da9688a3d2e4a78a790565a36 | [
"if not isinstance(other, Tag):\n return -1\nif other.name != self.name:\n return cmp(self.name, other.name)\nif other.attributes != self.attributes:\n return cmp(self.attributes, other.attributes)\nif other.content != self.content:\n return cmp(self.content, other.content)\nreturn 0",
"fragments = []... | <|body_start_0|>
if not isinstance(other, Tag):
return -1
if other.name != self.name:
return cmp(self.name, other.name)
if other.attributes != self.attributes:
return cmp(self.attributes, other.attributes)
if other.content != self.content:
... | Represents a particular tag within a document | Tag | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tag:
"""Represents a particular tag within a document"""
def __cmp__(self, other):
"""Compare this tag to another"""
<|body_0|>
def __repr__(self):
"""Create a decent representation of this tag"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if ... | stack_v2_sparse_classes_10k_train_008350 | 2,813 | no_license | [
{
"docstring": "Compare this tag to another",
"name": "__cmp__",
"signature": "def __cmp__(self, other)"
},
{
"docstring": "Create a decent representation of this tag",
"name": "__repr__",
"signature": "def __repr__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005488 | Implement the Python class `Tag` described below.
Class description:
Represents a particular tag within a document
Method signatures and docstrings:
- def __cmp__(self, other): Compare this tag to another
- def __repr__(self): Create a decent representation of this tag | Implement the Python class `Tag` described below.
Class description:
Represents a particular tag within a document
Method signatures and docstrings:
- def __cmp__(self, other): Compare this tag to another
- def __repr__(self): Create a decent representation of this tag
<|skeleton|>
class Tag:
"""Represents a par... | 496fc33954072147c379b8a9a1957bb04fd93670 | <|skeleton|>
class Tag:
"""Represents a particular tag within a document"""
def __cmp__(self, other):
"""Compare this tag to another"""
<|body_0|>
def __repr__(self):
"""Create a decent representation of this tag"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Tag:
"""Represents a particular tag within a document"""
def __cmp__(self, other):
"""Compare this tag to another"""
if not isinstance(other, Tag):
return -1
if other.name != self.name:
return cmp(self.name, other.name)
if other.attributes != self.a... | the_stack_v2_python_sparse | basicproperty/xmlencoder.py | eshikvtumane/basicproperty | train | 0 |
e804863764cd51b6008c332a5771ab1b96329ca7 | [
"dataset = m.device\nif not dataset_exists(dataset, 'filesystem'):\n raise ex.syncNotSnapable\nsnapdev = dataset + '@osvc_sync'\nmount_point = m.mount_point\nsnap_mount_point = mount_point + '/.zfs/snapshot/osvc_sync/'\nif dataset_exists(snapdev, 'snapshot'):\n ret, buff, err = self.vcall([rcEnv.syspaths.zfs,... | <|body_start_0|>
dataset = m.device
if not dataset_exists(dataset, 'filesystem'):
raise ex.syncNotSnapable
snapdev = dataset + '@osvc_sync'
mount_point = m.mount_point
snap_mount_point = mount_point + '/.zfs/snapshot/osvc_sync/'
if dataset_exists(snapdev, 'sna... | Defines a snap object with ZFS | Snap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Snap:
"""Defines a snap object with ZFS"""
def snapcreate(self, m):
"""create a snapshot for m add self.snaps[m] with dict(snapinfo key val)"""
<|body_0|>
def snapdestroykey(self, snap_key):
"""destroy a snapshot for a mount_point"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_10k_train_008351 | 1,445 | no_license | [
{
"docstring": "create a snapshot for m add self.snaps[m] with dict(snapinfo key val)",
"name": "snapcreate",
"signature": "def snapcreate(self, m)"
},
{
"docstring": "destroy a snapshot for a mount_point",
"name": "snapdestroykey",
"signature": "def snapdestroykey(self, snap_key)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000480 | Implement the Python class `Snap` described below.
Class description:
Defines a snap object with ZFS
Method signatures and docstrings:
- def snapcreate(self, m): create a snapshot for m add self.snaps[m] with dict(snapinfo key val)
- def snapdestroykey(self, snap_key): destroy a snapshot for a mount_point | Implement the Python class `Snap` described below.
Class description:
Defines a snap object with ZFS
Method signatures and docstrings:
- def snapcreate(self, m): create a snapshot for m add self.snaps[m] with dict(snapinfo key val)
- def snapdestroykey(self, snap_key): destroy a snapshot for a mount_point
<|skeleton... | 75baeb19e0d26d5e150e770aef4d615c2327f32e | <|skeleton|>
class Snap:
"""Defines a snap object with ZFS"""
def snapcreate(self, m):
"""create a snapshot for m add self.snaps[m] with dict(snapinfo key val)"""
<|body_0|>
def snapdestroykey(self, snap_key):
"""destroy a snapshot for a mount_point"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Snap:
"""Defines a snap object with ZFS"""
def snapcreate(self, m):
"""create a snapshot for m add self.snaps[m] with dict(snapinfo key val)"""
dataset = m.device
if not dataset_exists(dataset, 'filesystem'):
raise ex.syncNotSnapable
snapdev = dataset + '@osvc_... | the_stack_v2_python_sparse | lib/snapZfsSunOS.py | SLB-DeN/opensvc | train | 1 |
e04f857ccfad76cbf06f8c74727bc55653faa71a | [
"self.cardinality = cardinality\nif norm_factory is None:\n norm_factory = nn.BatchNorm2d\nself.norm_factory = norm_factory\nself.resnext_class = copy(models.resnet.Bottleneck)\nself.resnext_class.expansion = 2",
"stride = 1\nprojection = None\nif downsample > 1:\n stride = downsample\nif downsample > 1 or ... | <|body_start_0|>
self.cardinality = cardinality
if norm_factory is None:
norm_factory = nn.BatchNorm2d
self.norm_factory = norm_factory
self.resnext_class = copy(models.resnet.Bottleneck)
self.resnext_class.expansion = 2
<|end_body_0|>
<|body_start_1|>
stride... | Factory wrapper for ``torchvision`` ResNeXt blocks. | ResNeXtBlockFactory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResNeXtBlockFactory:
"""Factory wrapper for ``torchvision`` ResNeXt blocks."""
def __init__(self, cardinality=32, norm_factory: Optional[Callable[[int], nn.Module]]=None):
"""Args: cardinality: The cardinality of the block as defined in the ResNeXt paper. norm_factory: A factory obje... | stack_v2_sparse_classes_10k_train_008352 | 6,999 | permissive | [
{
"docstring": "Args: cardinality: The cardinality of the block as defined in the ResNeXt paper. norm_factory: A factory object to produce the normalization layers used in the ResNet blocks. Defaults to batch norm.",
"name": "__init__",
"signature": "def __init__(self, cardinality=32, norm_factory: Opti... | 2 | stack_v2_sparse_classes_30k_train_001934 | Implement the Python class `ResNeXtBlockFactory` described below.
Class description:
Factory wrapper for ``torchvision`` ResNeXt blocks.
Method signatures and docstrings:
- def __init__(self, cardinality=32, norm_factory: Optional[Callable[[int], nn.Module]]=None): Args: cardinality: The cardinality of the block as d... | Implement the Python class `ResNeXtBlockFactory` described below.
Class description:
Factory wrapper for ``torchvision`` ResNeXt blocks.
Method signatures and docstrings:
- def __init__(self, cardinality=32, norm_factory: Optional[Callable[[int], nn.Module]]=None): Args: cardinality: The cardinality of the block as d... | a27e329cd30337995c359160a0d878bf331c13fb | <|skeleton|>
class ResNeXtBlockFactory:
"""Factory wrapper for ``torchvision`` ResNeXt blocks."""
def __init__(self, cardinality=32, norm_factory: Optional[Callable[[int], nn.Module]]=None):
"""Args: cardinality: The cardinality of the block as defined in the ResNeXt paper. norm_factory: A factory obje... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ResNeXtBlockFactory:
"""Factory wrapper for ``torchvision`` ResNeXt blocks."""
def __init__(self, cardinality=32, norm_factory: Optional[Callable[[int], nn.Module]]=None):
"""Args: cardinality: The cardinality of the block as defined in the ResNeXt paper. norm_factory: A factory object to produce... | the_stack_v2_python_sparse | quantnn/models/pytorch/torchvision.py | simonpf/quantnn | train | 7 |
a4e2e7ef5c28a9d9fed11a70909fa91c9dfed64a | [
"super(ObservationGroupEncoder, self).__init__()\nassert isinstance(observation_group_shapes, OrderedDict)\nassert np.all([isinstance(observation_group_shapes[k], OrderedDict) for k in observation_group_shapes])\nself.observation_group_shapes = observation_group_shapes\nself.nets = nn.ModuleDict()\nfor obs_group in... | <|body_start_0|>
super(ObservationGroupEncoder, self).__init__()
assert isinstance(observation_group_shapes, OrderedDict)
assert np.all([isinstance(observation_group_shapes[k], OrderedDict) for k in observation_group_shapes])
self.observation_group_shapes = observation_group_shapes
... | This class allows networks to encode multiple observation dictionaries into a single flat, concatenated vector representation. It does this by assigning each observation dictionary (observation group) an @ObservationEncoder object. The class takes a dictionary of dictionaries, @observation_group_shapes. Each key corres... | ObservationGroupEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObservationGroupEncoder:
"""This class allows networks to encode multiple observation dictionaries into a single flat, concatenated vector representation. It does this by assigning each observation dictionary (observation group) an @ObservationEncoder object. The class takes a dictionary of dicti... | stack_v2_sparse_classes_10k_train_008353 | 37,945 | permissive | [
{
"docstring": "Args: observation_group_shapes (OrderedDict): a dictionary of dictionaries. Each key in this dictionary should specify an observation group, and the value should be an OrderedDict that maps modalities to expected shapes. visual_feature_dimension (int): feature dimension to encode images into vis... | 4 | stack_v2_sparse_classes_30k_train_004403 | Implement the Python class `ObservationGroupEncoder` described below.
Class description:
This class allows networks to encode multiple observation dictionaries into a single flat, concatenated vector representation. It does this by assigning each observation dictionary (observation group) an @ObservationEncoder object... | Implement the Python class `ObservationGroupEncoder` described below.
Class description:
This class allows networks to encode multiple observation dictionaries into a single flat, concatenated vector representation. It does this by assigning each observation dictionary (observation group) an @ObservationEncoder object... | 2804dd97dd1625ec861298a35cb677129d3bfacc | <|skeleton|>
class ObservationGroupEncoder:
"""This class allows networks to encode multiple observation dictionaries into a single flat, concatenated vector representation. It does this by assigning each observation dictionary (observation group) an @ObservationEncoder object. The class takes a dictionary of dicti... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ObservationGroupEncoder:
"""This class allows networks to encode multiple observation dictionaries into a single flat, concatenated vector representation. It does this by assigning each observation dictionary (observation group) an @ObservationEncoder object. The class takes a dictionary of dictionaries, @obs... | the_stack_v2_python_sparse | robomimic/models/obs_nets.py | sohams-MASS/robomimic | train | 0 |
668fc6b8d41dc44d72aea56c92eb0e6c3e297b4c | [
"self.data_frame: Optional[pd.DataFrame] = None\nself.frame_info = None\nself.workflow = kwargs.pop(str('workflow'), None)\nsuper().__init__(*args, **kwargs)",
"try:\n pandas.verify_data_frame(self.data_frame)\nexcept OnTaskDataFrameNoKey as exc:\n self.add_error(None, str(exc))\n return\ntry:\n self.... | <|body_start_0|>
self.data_frame: Optional[pd.DataFrame] = None
self.frame_info = None
self.workflow = kwargs.pop(str('workflow'), None)
super().__init__(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
try:
pandas.verify_data_frame(self.data_frame)
except On... | Basic class to use for inheritance. | UploadBasic | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"LGPL-2.1-only",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadBasic:
"""Basic class to use for inheritance."""
def __init__(self, *args, **kwargs):
"""Store the workflow for further processing."""
<|body_0|>
def validate_data_frame(self):
"""Check that the dataframe can be properly stored. :return: The cleaned data"""... | stack_v2_sparse_classes_10k_train_008354 | 10,714 | permissive | [
{
"docstring": "Store the workflow for further processing.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Check that the dataframe can be properly stored. :return: The cleaned data",
"name": "validate_data_frame",
"signature": "def validate_da... | 2 | stack_v2_sparse_classes_30k_train_002079 | Implement the Python class `UploadBasic` described below.
Class description:
Basic class to use for inheritance.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Store the workflow for further processing.
- def validate_data_frame(self): Check that the dataframe can be properly stored. :return... | Implement the Python class `UploadBasic` described below.
Class description:
Basic class to use for inheritance.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Store the workflow for further processing.
- def validate_data_frame(self): Check that the dataframe can be properly stored. :return... | c432745dfff932cbe7397100422d49df78f0a882 | <|skeleton|>
class UploadBasic:
"""Basic class to use for inheritance."""
def __init__(self, *args, **kwargs):
"""Store the workflow for further processing."""
<|body_0|>
def validate_data_frame(self):
"""Check that the dataframe can be properly stored. :return: The cleaned data"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UploadBasic:
"""Basic class to use for inheritance."""
def __init__(self, *args, **kwargs):
"""Store the workflow for further processing."""
self.data_frame: Optional[pd.DataFrame] = None
self.frame_info = None
self.workflow = kwargs.pop(str('workflow'), None)
supe... | the_stack_v2_python_sparse | ontask/dataops/forms/upload.py | abelardopardo/ontask_b | train | 43 |
c678bf6e311c441d9545e094dd1cb14e85c4091c | [
"self.problem = problem\nself.pp = post.PostProcessor(dict(casedir='Results', clean_casedir=True))\nself.pp.add_field(post.SolutionField('Solution', dict(save=True, save_as=['hdf5', 'xdmf'], plot=True, plot_args=dict(range_min=float(u_min), range_max=float(u_max)))))\nself.pp.add_field(post.SolutionField('Flux', di... | <|body_start_0|>
self.problem = problem
self.pp = post.PostProcessor(dict(casedir='Results', clean_casedir=True))
self.pp.add_field(post.SolutionField('Solution', dict(save=True, save_as=['hdf5', 'xdmf'], plot=True, plot_args=dict(range_min=float(u_min), range_max=float(u_max)))))
self.p... | user_action function for storing the solution and flux. | ProcessSolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessSolution:
"""user_action function for storing the solution and flux."""
def __init__(self, problem, u_min=0, u_max=1):
"""Define fields to be stored/plotted."""
<|body_0|>
def __call__(self, t, u, timestep):
"""Store u and its flux to file."""
<|bo... | stack_v2_sparse_classes_10k_train_008355 | 19,607 | no_license | [
{
"docstring": "Define fields to be stored/plotted.",
"name": "__init__",
"signature": "def __init__(self, problem, u_min=0, u_max=1)"
},
{
"docstring": "Store u and its flux to file.",
"name": "__call__",
"signature": "def __call__(self, t, u, timestep)"
}
] | 2 | null | Implement the Python class `ProcessSolution` described below.
Class description:
user_action function for storing the solution and flux.
Method signatures and docstrings:
- def __init__(self, problem, u_min=0, u_max=1): Define fields to be stored/plotted.
- def __call__(self, t, u, timestep): Store u and its flux to ... | Implement the Python class `ProcessSolution` described below.
Class description:
user_action function for storing the solution and flux.
Method signatures and docstrings:
- def __init__(self, problem, u_min=0, u_max=1): Define fields to be stored/plotted.
- def __call__(self, t, u, timestep): Store u and its flux to ... | 5e9a0e03aa7ddf5e5ddf89943ccc68d94b539e95 | <|skeleton|>
class ProcessSolution:
"""user_action function for storing the solution and flux."""
def __init__(self, problem, u_min=0, u_max=1):
"""Define fields to be stored/plotted."""
<|body_0|>
def __call__(self, t, u, timestep):
"""Store u and its flux to file."""
<|bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProcessSolution:
"""user_action function for storing the solution and flux."""
def __init__(self, problem, u_min=0, u_max=1):
"""Define fields to be stored/plotted."""
self.problem = problem
self.pp = post.PostProcessor(dict(casedir='Results', clean_casedir=True))
self.pp.... | the_stack_v2_python_sparse | Solving_PDEs_in_Python_Langtangen/src/src/heat_class.py | burakbayramli/books | train | 223 |
30f5da1e8c105f688997e87cb4a598a63ef4cf17 | [
"self.countTable = ChainingHashMap(1000)\nself.totalTable = ChainingHashMap(1000)\nself.totalWords = 0",
"textList = text.split()\nfor i in range(len(textList) - 1):\n self.totalWords += 1\n if self.totalTable[textList[i]] == None:\n self.totalTable[textList[i]] = 1\n else:\n self.totalTabl... | <|body_start_0|>
self.countTable = ChainingHashMap(1000)
self.totalTable = ChainingHashMap(1000)
self.totalWords = 0
<|end_body_0|>
<|body_start_1|>
textList = text.split()
for i in range(len(textList) - 1):
self.totalWords += 1
if self.totalTable[textLis... | A class that allows one to generate random text in the style of some provided source text | TextGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextGenerator:
"""A class that allows one to generate random text in the style of some provided source text"""
def __init__(self):
"""Initializes the text generator"""
<|body_0|>
def train(self, text):
"""Takes a body of text (as a string) and increases the appro... | stack_v2_sparse_classes_10k_train_008356 | 6,228 | no_license | [
{
"docstring": "Initializes the text generator",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Takes a body of text (as a string) and increases the appropriate frequency counts",
"name": "train",
"signature": "def train(self, text)"
},
{
"docstring": "C... | 4 | stack_v2_sparse_classes_30k_train_002735 | Implement the Python class `TextGenerator` described below.
Class description:
A class that allows one to generate random text in the style of some provided source text
Method signatures and docstrings:
- def __init__(self): Initializes the text generator
- def train(self, text): Takes a body of text (as a string) an... | Implement the Python class `TextGenerator` described below.
Class description:
A class that allows one to generate random text in the style of some provided source text
Method signatures and docstrings:
- def __init__(self): Initializes the text generator
- def train(self, text): Takes a body of text (as a string) an... | 0290deb3e1f008305fb2da353eda86210a7ba1e6 | <|skeleton|>
class TextGenerator:
"""A class that allows one to generate random text in the style of some provided source text"""
def __init__(self):
"""Initializes the text generator"""
<|body_0|>
def train(self, text):
"""Takes a body of text (as a string) and increases the appro... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TextGenerator:
"""A class that allows one to generate random text in the style of some provided source text"""
def __init__(self):
"""Initializes the text generator"""
self.countTable = ChainingHashMap(1000)
self.totalTable = ChainingHashMap(1000)
self.totalWords = 0
... | the_stack_v2_python_sparse | Random Text Generation/textgenerator.py | mbastola/Algorithms-Data-Structures-in-Python | train | 0 |
828b995dff7e6938a3411aa97e8d64c8de3907e4 | [
"self.mapper = {}\nself.names = []\nfor param in space:\n if param['name'] in self.names:\n raise ValueError('Duplicated name {}'.format(param['name']))\n self.names.append(param['name'])\n if param['type'] == TYPE.CATEGORICAL or param['type'] is TYPE.DISCRETE:\n self.mapper[param['name']] = ... | <|body_start_0|>
self.mapper = {}
self.names = []
for param in space:
if param['name'] in self.names:
raise ValueError('Duplicated name {}'.format(param['name']))
self.names.append(param['name'])
if param['type'] == TYPE.CATEGORICAL or param['t... | Converter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Converter:
def __init__(self, space):
"""Initialize the converter. Save the sequence of labels for keeping the same output and input order within the dict. Save the table used to convert the categorical and discrete parameters. Args: :param space: input space"""
<|body_0|>
d... | stack_v2_sparse_classes_10k_train_008357 | 10,066 | no_license | [
{
"docstring": "Initialize the converter. Save the sequence of labels for keeping the same output and input order within the dict. Save the table used to convert the categorical and discrete parameters. Args: :param space: input space",
"name": "__init__",
"signature": "def __init__(self, space)"
},
... | 3 | stack_v2_sparse_classes_30k_train_004247 | Implement the Python class `Converter` described below.
Class description:
Implement the Converter class.
Method signatures and docstrings:
- def __init__(self, space): Initialize the converter. Save the sequence of labels for keeping the same output and input order within the dict. Save the table used to convert the... | Implement the Python class `Converter` described below.
Class description:
Implement the Converter class.
Method signatures and docstrings:
- def __init__(self, space): Initialize the converter. Save the sequence of labels for keeping the same output and input order within the dict. Save the table used to convert the... | 27f861c09615aedfd96cffdebf7d9653f72b4d7b | <|skeleton|>
class Converter:
def __init__(self, space):
"""Initialize the converter. Save the sequence of labels for keeping the same output and input order within the dict. Save the table used to convert the categorical and discrete parameters. Args: :param space: input space"""
<|body_0|>
d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Converter:
def __init__(self, space):
"""Initialize the converter. Save the sequence of labels for keeping the same output and input order within the dict. Save the table used to convert the categorical and discrete parameters. Args: :param space: input space"""
self.mapper = {}
self.n... | the_stack_v2_python_sparse | API/Algorithms/BayesianOptimization.py | AndreaCorsini1/Ahmet | train | 1 | |
6f3979926a7fcc962601e2867f7d6c01bc51fe5f | [
"i = 0\nfor user, msg in self._queue:\n if user == nick:\n return i\n i += 1\nreturn -1",
"outfile = self.registryValue('dumpFile')\nwith open(outfile, 'w') as h:\n i = 1\n for nick, msg in self._queue:\n if msg is None:\n msg = '[no message]'\n h.write('% 2d\\t%s\\t%s\... | <|body_start_0|>
i = 0
for user, msg in self._queue:
if user == nick:
return i
i += 1
return -1
<|end_body_0|>
<|body_start_1|>
outfile = self.registryValue('dumpFile')
with open(outfile, 'w') as h:
i = 1
for nick, ... | A simple queue manager for meetings. You can add yourself to the queue by using the queue command, giving an optional notice that the bot can display when it's your turn. If you call the queue command again, you can change the saved notice. Doing so won't make you lose your queue position. In case you changed your mind... | Queue | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Queue:
"""A simple queue manager for meetings. You can add yourself to the queue by using the queue command, giving an optional notice that the bot can display when it's your turn. If you call the queue command again, you can change the saved notice. Doing so won't make you lose your queue positi... | stack_v2_sparse_classes_10k_train_008358 | 5,983 | permissive | [
{
"docstring": "Check if a given user is in the queue",
"name": "_find_in_queue",
"signature": "def _find_in_queue(self, nick)"
},
{
"docstring": "Dump the queue to a file",
"name": "_dump_queue",
"signature": "def _dump_queue(self)"
},
{
"docstring": "[<notice>] Queue up for say... | 6 | stack_v2_sparse_classes_30k_train_005680 | Implement the Python class `Queue` described below.
Class description:
A simple queue manager for meetings. You can add yourself to the queue by using the queue command, giving an optional notice that the bot can display when it's your turn. If you call the queue command again, you can change the saved notice. Doing s... | Implement the Python class `Queue` described below.
Class description:
A simple queue manager for meetings. You can add yourself to the queue by using the queue command, giving an optional notice that the bot can display when it's your turn. If you call the queue command again, you can change the saved notice. Doing s... | 656f42f8d6b3fe4544a5270e0dab816fd3603118 | <|skeleton|>
class Queue:
"""A simple queue manager for meetings. You can add yourself to the queue by using the queue command, giving an optional notice that the bot can display when it's your turn. If you call the queue command again, you can change the saved notice. Doing so won't make you lose your queue positi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Queue:
"""A simple queue manager for meetings. You can add yourself to the queue by using the queue command, giving an optional notice that the bot can display when it's your turn. If you call the queue command again, you can change the saved notice. Doing so won't make you lose your queue position. In case y... | the_stack_v2_python_sparse | plugins/Queue/plugin.py | kblin/supybot-gsoc | train | 2 |
ef7dca91aee565f74bda816faac028eb4f4feab4 | [
"if head == None:\n return None\ndic = {}\ndummy = head\nwhile dummy != None:\n dic[dummy] = RandomListNode(dummy.label)\n dummy = dummy.next\ndummy = head\nwhile dummy != None:\n dic[dummy].next = dic.get(dummy.next)\n dic[dummy].random = dic.get(dummy.random)\n dummy = dummy.next\nreturn dic.get... | <|body_start_0|>
if head == None:
return None
dic = {}
dummy = head
while dummy != None:
dic[dummy] = RandomListNode(dummy.label)
dummy = dummy.next
dummy = head
while dummy != None:
dic[dummy].next = dic.get(dummy.next)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def copyRandomList(self, head):
""":type head: RandomListNode :rtype: RandomListNode"""
<|body_0|>
def copyRandomList(self, head):
""":type head: RandomListNode :rtype: RandomListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if head... | stack_v2_sparse_classes_10k_train_008359 | 1,676 | no_license | [
{
"docstring": ":type head: RandomListNode :rtype: RandomListNode",
"name": "copyRandomList",
"signature": "def copyRandomList(self, head)"
},
{
"docstring": ":type head: RandomListNode :rtype: RandomListNode",
"name": "copyRandomList",
"signature": "def copyRandomList(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000349 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def copyRandomList(self, head): :type head: RandomListNode :rtype: RandomListNode
- def copyRandomList(self, head): :type head: RandomListNode :rtype: RandomListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def copyRandomList(self, head): :type head: RandomListNode :rtype: RandomListNode
- def copyRandomList(self, head): :type head: RandomListNode :rtype: RandomListNode
<|skeleton|... | 10798e5b9c33c3f177594ea17cf0398fc117f0a1 | <|skeleton|>
class Solution:
def copyRandomList(self, head):
""":type head: RandomListNode :rtype: RandomListNode"""
<|body_0|>
def copyRandomList(self, head):
""":type head: RandomListNode :rtype: RandomListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def copyRandomList(self, head):
""":type head: RandomListNode :rtype: RandomListNode"""
if head == None:
return None
dic = {}
dummy = head
while dummy != None:
dic[dummy] = RandomListNode(dummy.label)
dummy = dummy.next
... | the_stack_v2_python_sparse | copy-list-with-random-node/copyListWithRandomNode.py | NanXiangPU/leetcode | train | 0 | |
93fcea611e99e3137b1b6047c362ac72cb988275 | [
"row = g.db.query(Machine).get(machine_id)\nif not row:\n log.warning('Requested a non-existant machine: %s', machine_id)\n abort(http_client.NOT_FOUND, description='Machine not found')\nrecord = row.as_dict()\nrecord['url'] = url_for('machines.entry', machine_id=machine_id, _external=True)\nrecord['servers_u... | <|body_start_0|>
row = g.db.query(Machine).get(machine_id)
if not row:
log.warning('Requested a non-existant machine: %s', machine_id)
abort(http_client.NOT_FOUND, description='Machine not found')
record = row.as_dict()
record['url'] = url_for('machines.entry', ma... | Information about specific machines | MachineAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MachineAPI:
"""Information about specific machines"""
def get(self, machine_id):
"""Find machine by ID Get information about a single battle server machine. Just dumps out the DB row as json"""
<|body_0|>
def put(self, machine_id):
"""Update machine Heartbeat and... | stack_v2_sparse_classes_10k_train_008360 | 8,672 | permissive | [
{
"docstring": "Find machine by ID Get information about a single battle server machine. Just dumps out the DB row as json",
"name": "get",
"signature": "def get(self, machine_id)"
},
{
"docstring": "Update machine Heartbeat and update the machine reference",
"name": "put",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_002684 | Implement the Python class `MachineAPI` described below.
Class description:
Information about specific machines
Method signatures and docstrings:
- def get(self, machine_id): Find machine by ID Get information about a single battle server machine. Just dumps out the DB row as json
- def put(self, machine_id): Update ... | Implement the Python class `MachineAPI` described below.
Class description:
Information about specific machines
Method signatures and docstrings:
- def get(self, machine_id): Find machine by ID Get information about a single battle server machine. Just dumps out the DB row as json
- def put(self, machine_id): Update ... | 9825cb22b26b577b715f2ce95453363bf90ecc7e | <|skeleton|>
class MachineAPI:
"""Information about specific machines"""
def get(self, machine_id):
"""Find machine by ID Get information about a single battle server machine. Just dumps out the DB row as json"""
<|body_0|>
def put(self, machine_id):
"""Update machine Heartbeat and... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MachineAPI:
"""Information about specific machines"""
def get(self, machine_id):
"""Find machine by ID Get information about a single battle server machine. Just dumps out the DB row as json"""
row = g.db.query(Machine).get(machine_id)
if not row:
log.warning('Requeste... | the_stack_v2_python_sparse | driftbase/api/machines.py | dgnorth/drift-base | train | 1 |
88000392ff7ed945a764d5d379e590379727bad8 | [
"super().__init__()\nself.enc = enc\nself.mlp = mlp",
"_, (hn, _) = self.enc(*args)\ny_pred = self.mlp(hn)\nreturn y_pred",
"data = (seq_cont_data, seq_cat_data, non_seq_cont_data, non_seq_cat_data)\nnonempty_tensors, nonempty_idx = get_nonempty_tensors(data)\ny_pred = self(*nonempty_tensors, nonempty_idx)\nlos... | <|body_start_0|>
super().__init__()
self.enc = enc
self.mlp = mlp
<|end_body_0|>
<|body_start_1|>
_, (hn, _) = self.enc(*args)
y_pred = self.mlp(hn)
return y_pred
<|end_body_1|>
<|body_start_2|>
data = (seq_cont_data, seq_cat_data, non_seq_cont_data, non_seq_cat... | ChurnModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChurnModel:
def __init__(self, enc, mlp):
"""Initialize model with params."""
<|body_0|>
def forward(self, *args):
"""Run a forward pass of model over the data."""
<|body_1|>
def run(self, y, seq_cont_data, seq_cat_data, non_seq_cont_data, non_seq_cat_da... | stack_v2_sparse_classes_10k_train_008361 | 15,906 | permissive | [
{
"docstring": "Initialize model with params.",
"name": "__init__",
"signature": "def __init__(self, enc, mlp)"
},
{
"docstring": "Run a forward pass of model over the data.",
"name": "forward",
"signature": "def forward(self, *args)"
},
{
"docstring": "Run model on data and prop... | 3 | stack_v2_sparse_classes_30k_train_000185 | Implement the Python class `ChurnModel` described below.
Class description:
Implement the ChurnModel class.
Method signatures and docstrings:
- def __init__(self, enc, mlp): Initialize model with params.
- def forward(self, *args): Run a forward pass of model over the data.
- def run(self, y, seq_cont_data, seq_cat_d... | Implement the Python class `ChurnModel` described below.
Class description:
Implement the ChurnModel class.
Method signatures and docstrings:
- def __init__(self, enc, mlp): Initialize model with params.
- def forward(self, *args): Run a forward pass of model over the data.
- def run(self, y, seq_cont_data, seq_cat_d... | 9cdbf270487751a0ad6862b2fea2ccc0e23a0b67 | <|skeleton|>
class ChurnModel:
def __init__(self, enc, mlp):
"""Initialize model with params."""
<|body_0|>
def forward(self, *args):
"""Run a forward pass of model over the data."""
<|body_1|>
def run(self, y, seq_cont_data, seq_cat_data, non_seq_cont_data, non_seq_cat_da... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ChurnModel:
def __init__(self, enc, mlp):
"""Initialize model with params."""
super().__init__()
self.enc = enc
self.mlp = mlp
def forward(self, *args):
"""Run a forward pass of model over the data."""
_, (hn, _) = self.enc(*args)
y_pred = self.mlp(... | the_stack_v2_python_sparse | caspr/models/model_wrapper.py | microsoft/CASPR | train | 29 | |
bc05bd0b36dbe5416c7371340719c386255a58ac | [
"if root is None:\n return\nself.stack.append(root)\nl = root.left\nwhile l:\n self.stack.append(l)\n l = l.left",
"if len(self.stack) > 0:\n return True\nreturn False",
"smallest = self.stack.pop()\nr = smallest.right\nif r is not None:\n self.stack.append(r)\n l = r.left\n while l:\n ... | <|body_start_0|>
if root is None:
return
self.stack.append(root)
l = root.left
while l:
self.stack.append(l)
l = l.left
<|end_body_0|>
<|body_start_1|>
if len(self.stack) > 0:
return True
return False
<|end_body_1|>
<|body... | BSTIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def hasNext(self):
""":rtype: bool"""
<|body_1|>
def next(self):
""":rtype: int"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
if root is None:
... | stack_v2_sparse_classes_10k_train_008362 | 1,487 | no_license | [
{
"docstring": ":type root: TreeNode",
"name": "__init__",
"signature": "def __init__(self, root)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",
"signature": "def hasNext(self)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
}
] | 3 | null | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def hasNext(self): :rtype: bool
- def next(self): :rtype: int | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def hasNext(self): :rtype: bool
- def next(self): :rtype: int
<|skeleton|>
class BSTIterator:
def __init__(self, root... | dd268af242d18bc2fd9527661c71d2e51af1039d | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def hasNext(self):
""":rtype: bool"""
<|body_1|>
def next(self):
""":rtype: int"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
if root is None:
return
self.stack.append(root)
l = root.left
while l:
self.stack.append(l)
l = l.left
def hasNext(self):
""":rtype: bool"""
if len... | the_stack_v2_python_sparse | DS/Tree/Medium/R__173.Binary_Search_Tree_Iterator.py | HotsauceLee/Leetcode | train | 2 | |
01d38d164a9b8314bf8d1090e64174179ddac863 | [
"if not strs:\n return None\nif strs == ['']:\n return ''\nx = chr(258).join(strs)\nreturn x",
"if s is None:\n return None\nif s == '':\n return ['']\nres = s.split(chr(258))\nreturn res"
] | <|body_start_0|>
if not strs:
return None
if strs == ['']:
return ''
x = chr(258).join(strs)
return x
<|end_body_0|>
<|body_start_1|>
if s is None:
return None
if s == '':
return ['']
res = s.split(chr(258))
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not st... | stack_v2_sparse_classes_10k_train_008363 | 515 | no_license | [
{
"docstring": "Encodes a list of strings to a single string.",
"name": "encode",
"signature": "def encode(self, strs: [str]) -> str"
},
{
"docstring": "Decodes a single string to a list of strings.",
"name": "decode",
"signature": "def decode(self, s: str) -> [str]"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings.
<|skeleton|>
cla... | fb5a930b5ad27e7ed405e5787346327d9b3bf957 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
if not strs:
return None
if strs == ['']:
return ''
x = chr(258).join(strs)
return x
def decode(self, s: str) -> [str]:
"""Decodes a sin... | the_stack_v2_python_sparse | Jiuzhang_practice/encode_decode_str.py | armstrong019/coding_n_project | train | 0 | |
b19f22e532f77f77ab5cf5d38a4012e3cc854230 | [
"pos, angle = controller.odometry(10, 10, Vector2(0, 0), 0)\nassert pos == Vector2(0, 0)\nassert angle == 0",
"pos, angle = controller.odometry(20, 20, Vector2(0, 0), 0)\nassert pos == Vector2(2 * math.pi * WHEEL_RADIUS * 10 / TICK_PER_REVOLUTION, 0)\nassert angle == 0\npos, angle = controller.odometry(10, 10, Ve... | <|body_start_0|>
pos, angle = controller.odometry(10, 10, Vector2(0, 0), 0)
assert pos == Vector2(0, 0)
assert angle == 0
<|end_body_0|>
<|body_start_1|>
pos, angle = controller.odometry(20, 20, Vector2(0, 0), 0)
assert pos == Vector2(2 * math.pi * WHEEL_RADIUS * 10 / TICK_PER_R... | Test the odometry function. | TestOdometry | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestOdometry:
"""Test the odometry function."""
def test_did_not_move(controller):
"""Robot did not move."""
<|body_0|>
def test_move_straight(controller):
"""Robot moved in a straight line."""
<|body_1|>
def test_rotate_without_moving(controller):
... | stack_v2_sparse_classes_10k_train_008364 | 3,622 | permissive | [
{
"docstring": "Robot did not move.",
"name": "test_did_not_move",
"signature": "def test_did_not_move(controller)"
},
{
"docstring": "Robot moved in a straight line.",
"name": "test_move_straight",
"signature": "def test_move_straight(controller)"
},
{
"docstring": "Robot rotate... | 5 | stack_v2_sparse_classes_30k_train_001956 | Implement the Python class `TestOdometry` described below.
Class description:
Test the odometry function.
Method signatures and docstrings:
- def test_did_not_move(controller): Robot did not move.
- def test_move_straight(controller): Robot moved in a straight line.
- def test_rotate_without_moving(controller): Robot... | Implement the Python class `TestOdometry` described below.
Class description:
Test the odometry function.
Method signatures and docstrings:
- def test_did_not_move(controller): Robot did not move.
- def test_move_straight(controller): Robot moved in a straight line.
- def test_rotate_without_moving(controller): Robot... | b55d1ce6143ee7ef248fa7a9d6675c693b727d91 | <|skeleton|>
class TestOdometry:
"""Test the odometry function."""
def test_did_not_move(controller):
"""Robot did not move."""
<|body_0|>
def test_move_straight(controller):
"""Robot moved in a straight line."""
<|body_1|>
def test_rotate_without_moving(controller):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestOdometry:
"""Test the odometry function."""
def test_did_not_move(controller):
"""Robot did not move."""
pos, angle = controller.odometry(10, 10, Vector2(0, 0), 0)
assert pos == Vector2(0, 0)
assert angle == 0
def test_move_straight(controller):
"""Robot m... | the_stack_v2_python_sparse | highlevel/robot/controller/motion/odometry_test.py | outech-robotic/hl-flowing-clean-arch | train | 2 |
c5299f241f5cb8708a1411d24e2d406780bd89d1 | [
"self.head = Node(0)\nself.tail = Node(0)\nself.head.insert(self.tail)\nself.dic = {}",
"if key in self.dic:\n node = self.dic[key]\n if node.next.value == node.value + 1:\n node.next.keys.add(key)\n self.dic[key] = node.next\n node.keys.remove(key)\n if len(node.keys) == 0:\n ... | <|body_start_0|>
self.head = Node(0)
self.tail = Node(0)
self.head.insert(self.tail)
self.dic = {}
<|end_body_0|>
<|body_start_1|>
if key in self.dic:
node = self.dic[key]
if node.next.value == node.value + 1:
node.next.keys.add(key)
... | AllOne | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllOne:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def inc(self, key: str) -> None:
"""Inserts a new key <Key> with value 1. Or increments an existing key by 1."""
<|body_1|>
def dec(self, key: str) -> None:
"""Decr... | stack_v2_sparse_classes_10k_train_008365 | 3,186 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Inserts a new key <Key> with value 1. Or increments an existing key by 1.",
"name": "inc",
"signature": "def inc(self, key: str) -> None"
},
{
"docstrin... | 5 | null | Implement the Python class `AllOne` described below.
Class description:
Implement the AllOne class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def inc(self, key: str) -> None: Inserts a new key <Key> with value 1. Or increments an existing key by 1.
- def dec(self, ... | Implement the Python class `AllOne` described below.
Class description:
Implement the AllOne class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def inc(self, key: str) -> None: Inserts a new key <Key> with value 1. Or increments an existing key by 1.
- def dec(self, ... | 920b65db80031fad45d495431eda8d3fb4ef06e5 | <|skeleton|>
class AllOne:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def inc(self, key: str) -> None:
"""Inserts a new key <Key> with value 1. Or increments an existing key by 1."""
<|body_1|>
def dec(self, key: str) -> None:
"""Decr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AllOne:
def __init__(self):
"""Initialize your data structure here."""
self.head = Node(0)
self.tail = Node(0)
self.head.insert(self.tail)
self.dic = {}
def inc(self, key: str) -> None:
"""Inserts a new key <Key> with value 1. Or increments an existing key ... | the_stack_v2_python_sparse | hard/ex432.py | ziyuan-shen/leetcode_algorithm_python_solution | train | 2 | |
da34c3f5ebfb7c342b52fd829cbd21838c150cf6 | [
"super(Filterer, self).__init__()\nself.expression = expression\nself.target = target\nself._event = event\nself._regex = None\nreturn",
"if self._event is None:\n self._event = DummyEvent()\nreturn self._event",
"if self._regex is None:\n self._regex = re.compile(self.expression)\nreturn self._regex",
... | <|body_start_0|>
super(Filterer, self).__init__()
self.expression = expression
self.target = target
self._event = event
self._regex = None
return
<|end_body_0|>
<|body_start_1|>
if self._event is None:
self._event = DummyEvent()
return self._e... | A Filterer filters out strings that don't match an expression. | Filterer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Filterer:
"""A Filterer filters out strings that don't match an expression."""
def __init__(self, expression, target, event=None):
""":param: - `expression`: A regular expression. - `target`: a target to send matching strings to - `event`: an Event to activate flow through the filter... | stack_v2_sparse_classes_10k_train_008366 | 1,774 | permissive | [
{
"docstring": ":param: - `expression`: A regular expression. - `target`: a target to send matching strings to - `event`: an Event to activate flow through the filter",
"name": "__init__",
"signature": "def __init__(self, expression, target, event=None)"
},
{
"docstring": ":return: threading eve... | 4 | null | Implement the Python class `Filterer` described below.
Class description:
A Filterer filters out strings that don't match an expression.
Method signatures and docstrings:
- def __init__(self, expression, target, event=None): :param: - `expression`: A regular expression. - `target`: a target to send matching strings t... | Implement the Python class `Filterer` described below.
Class description:
A Filterer filters out strings that don't match an expression.
Method signatures and docstrings:
- def __init__(self, expression, target, event=None): :param: - `expression`: A regular expression. - `target`: a target to send matching strings t... | b4d1c77e1d611fe2b30768b42bdc7493afb0ea95 | <|skeleton|>
class Filterer:
"""A Filterer filters out strings that don't match an expression."""
def __init__(self, expression, target, event=None):
""":param: - `expression`: A regular expression. - `target`: a target to send matching strings to - `event`: an Event to activate flow through the filter... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Filterer:
"""A Filterer filters out strings that don't match an expression."""
def __init__(self, expression, target, event=None):
""":param: - `expression`: A regular expression. - `target`: a target to send matching strings to - `event`: an Event to activate flow through the filter"""
s... | the_stack_v2_python_sparse | apetools/commons/filterer.py | russell-n/oldape | train | 0 |
5a866f7ed3243b014c36d9fffeec10b9cd2b94f3 | [
"if db_field.name == 'author':\n kwargs['initial'] = request.user.id\nreturn super().formfield_for_foreignkey(db_field, request, **kwargs)",
"try:\n profile = Profile.objects.get(user=request.user)\nexcept Profile.DoesNotExist:\n if request.user.is_superuser:\n return Mark.objects.all()\nif profil... | <|body_start_0|>
if db_field.name == 'author':
kwargs['initial'] = request.user.id
return super().formfield_for_foreignkey(db_field, request, **kwargs)
<|end_body_0|>
<|body_start_1|>
try:
profile = Profile.objects.get(user=request.user)
except Profile.DoesNotExi... | MarksAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MarksAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""Set default teacher"""
<|body_0|>
def get_queryset(self, request):
"""Get all marks for current profile"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if db_field.name ... | stack_v2_sparse_classes_10k_train_008367 | 2,628 | no_license | [
{
"docstring": "Set default teacher",
"name": "formfield_for_foreignkey",
"signature": "def formfield_for_foreignkey(self, db_field, request, **kwargs)"
},
{
"docstring": "Get all marks for current profile",
"name": "get_queryset",
"signature": "def get_queryset(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000901 | Implement the Python class `MarksAdmin` described below.
Class description:
Implement the MarksAdmin class.
Method signatures and docstrings:
- def formfield_for_foreignkey(self, db_field, request, **kwargs): Set default teacher
- def get_queryset(self, request): Get all marks for current profile | Implement the Python class `MarksAdmin` described below.
Class description:
Implement the MarksAdmin class.
Method signatures and docstrings:
- def formfield_for_foreignkey(self, db_field, request, **kwargs): Set default teacher
- def get_queryset(self, request): Get all marks for current profile
<|skeleton|>
class ... | 76c0df6f07f41f4baf7346acdbbf316b4dd13ee5 | <|skeleton|>
class MarksAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""Set default teacher"""
<|body_0|>
def get_queryset(self, request):
"""Get all marks for current profile"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MarksAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""Set default teacher"""
if db_field.name == 'author':
kwargs['initial'] = request.user.id
return super().formfield_for_foreignkey(db_field, request, **kwargs)
def get_queryset(self, request)... | the_stack_v2_python_sparse | journal/admin.py | HallrizonX/api_chpk | train | 3 | |
d2ae0f4ebdae9ea9bd656d6280854923752afeb8 | [
"def dfs(node):\n if not node:\n return\n eq = node.val == p.val or node.val == q.val\n l = dfs(node.left)\n if eq and l:\n return node\n r = dfs(node.right)\n if eq and r:\n return node\n if l and r:\n return node\n return eq and node or l or r\nreturn dfs(root)"... | <|body_start_0|>
def dfs(node):
if not node:
return
eq = node.val == p.val or node.val == q.val
l = dfs(node.left)
if eq and l:
return node
r = dfs(node.right)
if eq and r:
return node
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lowestCommonAncestor(self, root, p, q):
""":type root: TreeNode :type p: TreeNode :type q: TreeNode :rtype: TreeNode"""
<|body_0|>
def test(self, root, p, q):
""":type root: TreeNode :type p: TreeNode :type q: TreeNode :rtype: TreeNode"""
<|body... | stack_v2_sparse_classes_10k_train_008368 | 1,406 | no_license | [
{
"docstring": ":type root: TreeNode :type p: TreeNode :type q: TreeNode :rtype: TreeNode",
"name": "lowestCommonAncestor",
"signature": "def lowestCommonAncestor(self, root, p, q)"
},
{
"docstring": ":type root: TreeNode :type p: TreeNode :type q: TreeNode :rtype: TreeNode",
"name": "test",... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lowestCommonAncestor(self, root, p, q): :type root: TreeNode :type p: TreeNode :type q: TreeNode :rtype: TreeNode
- def test(self, root, p, q): :type root: TreeNode :type p: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lowestCommonAncestor(self, root, p, q): :type root: TreeNode :type p: TreeNode :type q: TreeNode :rtype: TreeNode
- def test(self, root, p, q): :type root: TreeNode :type p: ... | 4599634f31d78a0372cf0ff6fb7935d054d5ecb5 | <|skeleton|>
class Solution:
def lowestCommonAncestor(self, root, p, q):
""":type root: TreeNode :type p: TreeNode :type q: TreeNode :rtype: TreeNode"""
<|body_0|>
def test(self, root, p, q):
""":type root: TreeNode :type p: TreeNode :type q: TreeNode :rtype: TreeNode"""
<|body... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def lowestCommonAncestor(self, root, p, q):
""":type root: TreeNode :type p: TreeNode :type q: TreeNode :rtype: TreeNode"""
def dfs(node):
if not node:
return
eq = node.val == p.val or node.val == q.val
l = dfs(node.left)
... | the_stack_v2_python_sparse | leetcode_python/201-300/236.py | jhgdike/leetCode | train | 3 | |
765e942119ad5c735ba49c67ca98f3ce40a55ace | [
"node_list = response.xpath(\"//tr[@class='even'] | //tr[@class='odd']\")\nfor node in node_list:\n item = TencentItem()\n item['position_name'] = node.xpath('./td[1]/a/text()').extract_first()\n item['position_link'] = 'https://hr.tencent.com/' + node.xpath('./td[1]/a/@href').extract_first()\n item['po... | <|body_start_0|>
node_list = response.xpath("//tr[@class='even'] | //tr[@class='odd']")
for node in node_list:
item = TencentItem()
item['position_name'] = node.xpath('./td[1]/a/text()').extract_first()
item['position_link'] = 'https://hr.tencent.com/' + node.xpath('.... | TencentSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TencentSpider:
def parse(self, response):
"""默认列表页的解析方法"""
<|body_0|>
def parse_detail(self, response):
"""解析详情页的响应内容"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
node_list = response.xpath("//tr[@class='even'] | //tr[@class='odd']")
for ... | stack_v2_sparse_classes_10k_train_008369 | 2,985 | no_license | [
{
"docstring": "默认列表页的解析方法",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "解析详情页的响应内容",
"name": "parse_detail",
"signature": "def parse_detail(self, response)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001900 | Implement the Python class `TencentSpider` described below.
Class description:
Implement the TencentSpider class.
Method signatures and docstrings:
- def parse(self, response): 默认列表页的解析方法
- def parse_detail(self, response): 解析详情页的响应内容 | Implement the Python class `TencentSpider` described below.
Class description:
Implement the TencentSpider class.
Method signatures and docstrings:
- def parse(self, response): 默认列表页的解析方法
- def parse_detail(self, response): 解析详情页的响应内容
<|skeleton|>
class TencentSpider:
def parse(self, response):
"""默认列表页... | a51e31acff41292e568ac22b0e213e6cb48218fa | <|skeleton|>
class TencentSpider:
def parse(self, response):
"""默认列表页的解析方法"""
<|body_0|>
def parse_detail(self, response):
"""解析详情页的响应内容"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TencentSpider:
def parse(self, response):
"""默认列表页的解析方法"""
node_list = response.xpath("//tr[@class='even'] | //tr[@class='odd']")
for node in node_list:
item = TencentItem()
item['position_name'] = node.xpath('./td[1]/a/text()').extract_first()
item[... | the_stack_v2_python_sparse | 爬虫项目/code10/2.Spider类多级页面数据采集/Tencent2/Tencent2/spiders/tencent2.py | byst4nder/his_spider | train | 1 | |
87c34a5ceb0c54dde76385d13c44a47e4f08876a | [
"username = 'test@test.com'\npassword = 'toto'\nself.client.post(reverse(register), {'username': username, 'password': password})\nresponse = self.client.post(reverse(obtain_auth_token), {'username': username, 'password': password}, format='json')\nself.token = json.loads(response.content)['token']\nself.client.get... | <|body_start_0|>
username = 'test@test.com'
password = 'toto'
self.client.post(reverse(register), {'username': username, 'password': password})
response = self.client.post(reverse(obtain_auth_token), {'username': username, 'password': password}, format='json')
self.token = json.l... | Test the Django/Vue interface. | TestDjangoVueInterface | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDjangoVueInterface:
"""Test the Django/Vue interface."""
def setUp(self):
"""Register and log user in."""
<|body_0|>
def test_default_monthly_requests_amount(self):
"""Test that default amount of monthly requests is correct."""
<|body_1|>
def tes... | stack_v2_sparse_classes_10k_train_008370 | 8,751 | no_license | [
{
"docstring": "Register and log user in.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test that default amount of monthly requests is correct.",
"name": "test_default_monthly_requests_amount",
"signature": "def test_default_monthly_requests_amount(self)"
},
{... | 4 | stack_v2_sparse_classes_30k_train_007118 | Implement the Python class `TestDjangoVueInterface` described below.
Class description:
Test the Django/Vue interface.
Method signatures and docstrings:
- def setUp(self): Register and log user in.
- def test_default_monthly_requests_amount(self): Test that default amount of monthly requests is correct.
- def test_de... | Implement the Python class `TestDjangoVueInterface` described below.
Class description:
Test the Django/Vue interface.
Method signatures and docstrings:
- def setUp(self): Register and log user in.
- def test_default_monthly_requests_amount(self): Test that default amount of monthly requests is correct.
- def test_de... | 9c0027b84d8dee6044ff28362e2b2b90c1759b90 | <|skeleton|>
class TestDjangoVueInterface:
"""Test the Django/Vue interface."""
def setUp(self):
"""Register and log user in."""
<|body_0|>
def test_default_monthly_requests_amount(self):
"""Test that default amount of monthly requests is correct."""
<|body_1|>
def tes... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestDjangoVueInterface:
"""Test the Django/Vue interface."""
def setUp(self):
"""Register and log user in."""
username = 'test@test.com'
password = 'toto'
self.client.post(reverse(register), {'username': username, 'password': password})
response = self.client.post(... | the_stack_v2_python_sparse | django_project/api_core/tests.py | juliensalinas/python-django-api-reactjs-frontend-slate-documentation-various-client-libs | train | 3 |
56ba4a33a842cfedb21b752c31b4dfaeeca1e292 | [
"super(OperatorLookupError, self).__init__(operator)\nself.operator = operator\nself.filename = filename\nself.lineno = lineno\nself.block = block",
"op = self.operator\ntext = '%s\\n\\n' % op\ntext += _format_source_error(self.filename, self.lineno, self.block)\noptext = \"'%s'\" % op\nif op in self.op_map:\n ... | <|body_start_0|>
super(OperatorLookupError, self).__init__(operator)
self.operator = operator
self.filename = filename
self.lineno = lineno
self.block = block
<|end_body_0|>
<|body_start_1|>
op = self.operator
text = '%s\n\n' % op
text += _format_source_e... | A LookupError subclass which nicely formats the exception. This class is intended for used by Declarative and its subclasses to report errors for failed operator lookups when building the object tree. | OperatorLookupError | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OperatorLookupError:
"""A LookupError subclass which nicely formats the exception. This class is intended for used by Declarative and its subclasses to report errors for failed operator lookups when building the object tree."""
def __init__(self, operator, filename, lineno, block):
"... | stack_v2_sparse_classes_10k_train_008371 | 4,784 | permissive | [
{
"docstring": "Initialize an OperatorLookupError. Parameters ---------- operator : str The name of the operator which was not found. filename : str The filename where the lookup failed. lineno : int The line number of the error. block : str The name of the lexical block in which the lookup failed.",
"name"... | 2 | null | Implement the Python class `OperatorLookupError` described below.
Class description:
A LookupError subclass which nicely formats the exception. This class is intended for used by Declarative and its subclasses to report errors for failed operator lookups when building the object tree.
Method signatures and docstrings... | Implement the Python class `OperatorLookupError` described below.
Class description:
A LookupError subclass which nicely formats the exception. This class is intended for used by Declarative and its subclasses to report errors for failed operator lookups when building the object tree.
Method signatures and docstrings... | 424bba29219de58fe9e47196de6763de8b2009f2 | <|skeleton|>
class OperatorLookupError:
"""A LookupError subclass which nicely formats the exception. This class is intended for used by Declarative and its subclasses to report errors for failed operator lookups when building the object tree."""
def __init__(self, operator, filename, lineno, block):
"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OperatorLookupError:
"""A LookupError subclass which nicely formats the exception. This class is intended for used by Declarative and its subclasses to report errors for failed operator lookups when building the object tree."""
def __init__(self, operator, filename, lineno, block):
"""Initialize ... | the_stack_v2_python_sparse | enaml/core/exceptions.py | enthought/enaml | train | 17 |
bba4634fb9d35cce790010d4d057a4be4ea00b86 | [
"qs = self.queryset.filter(expiry_date__gt=timezone.now())\nif not self.request.user.groups.filter(name=REGISTRIES_VIEWER_ROLE).exists():\n qs = qs.filter(Q(applications__current_status__code='A'), Q(applications__removal_date__isnull=True))\nreturn qs",
"instance = self.get_object()\ninstance.expiry_date = ti... | <|body_start_0|>
qs = self.queryset.filter(expiry_date__gt=timezone.now())
if not self.request.user.groups.filter(name=REGISTRIES_VIEWER_ROLE).exists():
qs = qs.filter(Q(applications__current_status__code='A'), Q(applications__removal_date__isnull=True))
return qs
<|end_body_0|>
<|b... | get: Returns the specified person put: Replaces the specified person record with a new one patch: Updates a person with the fields/values provided in the request body delete: Removes the specified person record | PersonDetailView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersonDetailView:
"""get: Returns the specified person put: Replaces the specified person record with a new one patch: Updates a person with the fields/values provided in the request body delete: Removes the specified person record"""
def get_queryset(self):
"""Returns only registere... | stack_v2_sparse_classes_10k_train_008372 | 35,975 | permissive | [
{
"docstring": "Returns only registered people (i.e. drillers with active registration) to anonymous users",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Set expiry_date to current date",
"name": "destroy",
"signature": "def destroy(self, request, *arg... | 2 | stack_v2_sparse_classes_30k_train_004005 | Implement the Python class `PersonDetailView` described below.
Class description:
get: Returns the specified person put: Replaces the specified person record with a new one patch: Updates a person with the fields/values provided in the request body delete: Removes the specified person record
Method signatures and doc... | Implement the Python class `PersonDetailView` described below.
Class description:
get: Returns the specified person put: Replaces the specified person record with a new one patch: Updates a person with the fields/values provided in the request body delete: Removes the specified person record
Method signatures and doc... | 6be3701a8e0085d0c6fa199b2672b7f9f1266a03 | <|skeleton|>
class PersonDetailView:
"""get: Returns the specified person put: Replaces the specified person record with a new one patch: Updates a person with the fields/values provided in the request body delete: Removes the specified person record"""
def get_queryset(self):
"""Returns only registere... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PersonDetailView:
"""get: Returns the specified person put: Replaces the specified person record with a new one patch: Updates a person with the fields/values provided in the request body delete: Removes the specified person record"""
def get_queryset(self):
"""Returns only registered people (i.e... | the_stack_v2_python_sparse | app/backend/registries/views.py | bcgov/gwells | train | 39 |
435f48322403ca8e571f3bccfe8cc3a0a1677b7e | [
"super().__init__()\ncheck_boundaries(boundaries)\nself.boundaries = boundaries",
"self.randomize(None)\nself.magnitude = self.R.uniform(low=self.boundaries[0], high=self.boundaries[1])\nsignal = convert_to_tensor(self.magnitude * signal)\nreturn signal"
] | <|body_start_0|>
super().__init__()
check_boundaries(boundaries)
self.boundaries = boundaries
<|end_body_0|>
<|body_start_1|>
self.randomize(None)
self.magnitude = self.R.uniform(low=self.boundaries[0], high=self.boundaries[1])
signal = convert_to_tensor(self.magnitude *... | Apply a random rescaling on a signal | SignalRandScale | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignalRandScale:
"""Apply a random rescaling on a signal"""
def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None:
"""Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``[-1.0, 1.0]``"""
<|body_0|>
def __call__(sel... | stack_v2_sparse_classes_10k_train_008373 | 16,322 | permissive | [
{
"docstring": "Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``[-1.0, 1.0]``",
"name": "__init__",
"signature": "def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None"
},
{
"docstring": "Args: signal: input 1 dimension signal to be sc... | 2 | stack_v2_sparse_classes_30k_train_000948 | Implement the Python class `SignalRandScale` described below.
Class description:
Apply a random rescaling on a signal
Method signatures and docstrings:
- def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None: Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``... | Implement the Python class `SignalRandScale` described below.
Class description:
Apply a random rescaling on a signal
Method signatures and docstrings:
- def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None: Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``... | e48c3e2c741fa3fc705c4425d17ac4a5afac6c47 | <|skeleton|>
class SignalRandScale:
"""Apply a random rescaling on a signal"""
def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None:
"""Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``[-1.0, 1.0]``"""
<|body_0|>
def __call__(sel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SignalRandScale:
"""Apply a random rescaling on a signal"""
def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None:
"""Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``[-1.0, 1.0]``"""
super().__init__()
check_boundaries(b... | the_stack_v2_python_sparse | monai/transforms/signal/array.py | Project-MONAI/MONAI | train | 4,805 |
471343fb66f19a525015d924c3895bfb6579e480 | [
"self.client = Client()\nself.test_user = User.objects.create_user('testuser', 'blah@blah.com', 'testpassword')\nself.test_user.is_superuser = True\nself.test_user.is_active = True\nself.test_user.save()\nself.assertEqual(self.test_user.is_superuser, True)\nlogin = self.client.login(username='testuser', password='t... | <|body_start_0|>
self.client = Client()
self.test_user = User.objects.create_user('testuser', 'blah@blah.com', 'testpassword')
self.test_user.is_superuser = True
self.test_user.is_active = True
self.test_user.save()
self.assertEqual(self.test_user.is_superuser, True)
... | This class covers the setup and tear down for all unit tests | BasicTests | [
"CC0-1.0",
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicTests:
"""This class covers the setup and tear down for all unit tests"""
def setUp(self):
"""Instantiate the test client. Creates a test user."""
<|body_0|>
def tearDown(self):
"""Depopulate created model instances from test database."""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_008374 | 2,724 | permissive | [
{
"docstring": "Instantiate the test client. Creates a test user.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Depopulate created model instances from test database.",
"name": "tearDown",
"signature": "def tearDown(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003909 | Implement the Python class `BasicTests` described below.
Class description:
This class covers the setup and tear down for all unit tests
Method signatures and docstrings:
- def setUp(self): Instantiate the test client. Creates a test user.
- def tearDown(self): Depopulate created model instances from test database. | Implement the Python class `BasicTests` described below.
Class description:
This class covers the setup and tear down for all unit tests
Method signatures and docstrings:
- def setUp(self): Instantiate the test client. Creates a test user.
- def tearDown(self): Depopulate created model instances from test database.
... | d6f6c9c068bbf668c253e5943d9514947023e66d | <|skeleton|>
class BasicTests:
"""This class covers the setup and tear down for all unit tests"""
def setUp(self):
"""Instantiate the test client. Creates a test user."""
<|body_0|>
def tearDown(self):
"""Depopulate created model instances from test database."""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BasicTests:
"""This class covers the setup and tear down for all unit tests"""
def setUp(self):
"""Instantiate the test client. Creates a test user."""
self.client = Client()
self.test_user = User.objects.create_user('testuser', 'blah@blah.com', 'testpassword')
self.test_u... | the_stack_v2_python_sparse | lab_website/tests.py | BridgesLab/Lab-Website | train | 0 |
641fc5ccae14d39fcb46af24add83e19271d92d7 | [
"self.abbr_dict = dict()\nfor word in dictionary:\n if len(word) < 3:\n abbr = word\n else:\n abbr = word[0] + str(len(word) - 2) + word[-1]\n if abbr not in self.abbr_dict.keys():\n self.abbr_dict[abbr] = set()\n self.abbr_dict[abbr].add(word)",
"if len(word) < 3:\n abbr = wor... | <|body_start_0|>
self.abbr_dict = dict()
for word in dictionary:
if len(word) < 3:
abbr = word
else:
abbr = word[0] + str(len(word) - 2) + word[-1]
if abbr not in self.abbr_dict.keys():
self.abbr_dict[abbr] = set()
... | ValidWordAbbr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool A word's abbreviation is unique if no other word from the dictionary has the same abbreviation. 1) empty abbr_dict, r... | stack_v2_sparse_classes_10k_train_008375 | 1,314 | no_license | [
{
"docstring": ":type dictionary: List[str]",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": ":type word: str :rtype: bool A word's abbreviation is unique if no other word from the dictionary has the same abbreviation. 1) empty abbr_dict, return True for all ... | 2 | null | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool A word's abbreviation is unique if no other word fr... | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool A word's abbreviation is unique if no other word fr... | 08c6d27498e35f636045fed05a6f94b760ab69ca | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool A word's abbreviation is unique if no other word from the dictionary has the same abbreviation. 1) empty abbr_dict, r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
self.abbr_dict = dict()
for word in dictionary:
if len(word) < 3:
abbr = word
else:
abbr = word[0] + str(len(word) - 2) + word[-1]
if abb... | the_stack_v2_python_sparse | solutions/design/288.Unique.Word.Abbreviation.py | ljia2/leetcode.py | train | 0 | |
4763bebac4d86b4e61cbce3d297de04ebbcc7d01 | [
"self.domain_obj = domains.DiscreteNumericDomain([4, 5, 207.2, -2.3])\nself.points = [207.2, 5, -2.3]\nself.non_points = [5.4, -1.1, 'kky', None]",
"self.report('Testing if exception is raised for non numeric elements in a ' + 'discrete domain.')\nexception_raised = False\ntry:\n domains.DiscreteNumericDomain(... | <|body_start_0|>
self.domain_obj = domains.DiscreteNumericDomain([4, 5, 207.2, -2.3])
self.points = [207.2, 5, -2.3]
self.non_points = [5.4, -1.1, 'kky', None]
<|end_body_0|>
<|body_start_1|>
self.report('Testing if exception is raised for non numeric elements in a ' + 'discrete domain.... | Discrete Numeric Domain. | DiscreteNumericDomainTestCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiscreteNumericDomainTestCase:
"""Discrete Numeric Domain."""
def _child_set_up(self):
"""Child set up."""
<|body_0|>
def test_non_numeric_discrete_domain(self):
"""Constructor."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.domain_obj = d... | stack_v2_sparse_classes_10k_train_008376 | 5,755 | permissive | [
{
"docstring": "Child set up.",
"name": "_child_set_up",
"signature": "def _child_set_up(self)"
},
{
"docstring": "Constructor.",
"name": "test_non_numeric_discrete_domain",
"signature": "def test_non_numeric_discrete_domain(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005081 | Implement the Python class `DiscreteNumericDomainTestCase` described below.
Class description:
Discrete Numeric Domain.
Method signatures and docstrings:
- def _child_set_up(self): Child set up.
- def test_non_numeric_discrete_domain(self): Constructor. | Implement the Python class `DiscreteNumericDomainTestCase` described below.
Class description:
Discrete Numeric Domain.
Method signatures and docstrings:
- def _child_set_up(self): Child set up.
- def test_non_numeric_discrete_domain(self): Constructor.
<|skeleton|>
class DiscreteNumericDomainTestCase:
"""Discre... | 3eef7d30bcc2e56f2221a624bd8ec7f933f81e40 | <|skeleton|>
class DiscreteNumericDomainTestCase:
"""Discrete Numeric Domain."""
def _child_set_up(self):
"""Child set up."""
<|body_0|>
def test_non_numeric_discrete_domain(self):
"""Constructor."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DiscreteNumericDomainTestCase:
"""Discrete Numeric Domain."""
def _child_set_up(self):
"""Child set up."""
self.domain_obj = domains.DiscreteNumericDomain([4, 5, 207.2, -2.3])
self.points = [207.2, 5, -2.3]
self.non_points = [5.4, -1.1, 'kky', None]
def test_non_numer... | the_stack_v2_python_sparse | dragonfly/exd/unittest_domains.py | dragonfly/dragonfly | train | 868 |
b8398bf58bd93cd1a684f97de3d308f3e884b86e | [
"p = PizzaList()\np.create(Pizza('alegg1', 'alegg2'))\nself.assertEqual(1, len(p.pizza_list))",
"p = PizzaList()\np.create(Pizza('alegg1', 'alegg2', 'alegg3'))\np.create(Pizza('alegg1', 'alegg2', 'alegg3'))\np.create(Pizza('alegg1', 'alegg2', 'alegg3'))\np.serve(2)\nself.assertEqual(p.getPizza(2).servedStatus, 's... | <|body_start_0|>
p = PizzaList()
p.create(Pizza('alegg1', 'alegg2'))
self.assertEqual(1, len(p.pizza_list))
<|end_body_0|>
<|body_start_1|>
p = PizzaList()
p.create(Pizza('alegg1', 'alegg2', 'alegg3'))
p.create(Pizza('alegg1', 'alegg2', 'alegg3'))
p.create(Pizza(... | MyTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyTest:
def createTest(self):
"""Tests the create function"""
<|body_0|>
def serveTest(self):
"""Tests the serve function"""
<|body_1|>
def removeTest(self):
"""Tests the remove function"""
<|body_2|>
def testPrint(self):
"""... | stack_v2_sparse_classes_10k_train_008377 | 3,166 | no_license | [
{
"docstring": "Tests the create function",
"name": "createTest",
"signature": "def createTest(self)"
},
{
"docstring": "Tests the serve function",
"name": "serveTest",
"signature": "def serveTest(self)"
},
{
"docstring": "Tests the remove function",
"name": "removeTest",
... | 4 | stack_v2_sparse_classes_30k_train_001083 | Implement the Python class `MyTest` described below.
Class description:
Implement the MyTest class.
Method signatures and docstrings:
- def createTest(self): Tests the create function
- def serveTest(self): Tests the serve function
- def removeTest(self): Tests the remove function
- def testPrint(self): Tests the pri... | Implement the Python class `MyTest` described below.
Class description:
Implement the MyTest class.
Method signatures and docstrings:
- def createTest(self): Tests the create function
- def serveTest(self): Tests the serve function
- def removeTest(self): Tests the remove function
- def testPrint(self): Tests the pri... | 567b129db4ede8d45dec599fc844274bf0953301 | <|skeleton|>
class MyTest:
def createTest(self):
"""Tests the create function"""
<|body_0|>
def serveTest(self):
"""Tests the serve function"""
<|body_1|>
def removeTest(self):
"""Tests the remove function"""
<|body_2|>
def testPrint(self):
"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MyTest:
def createTest(self):
"""Tests the create function"""
p = PizzaList()
p.create(Pizza('alegg1', 'alegg2'))
self.assertEqual(1, len(p.pizza_list))
def serveTest(self):
"""Tests the serve function"""
p = PizzaList()
p.create(Pizza('alegg1', 'al... | the_stack_v2_python_sparse | Tímadæmi/Tímadæmi 3/pizzaz.py | helenaj18/Gagnaskipan | train | 0 | |
495ab6017d9190fdc4e604d4ee1cfa16f7bf5d67 | [
"if not username:\n raise ValueError('Users must have an username.')\nuser = self.model(username=username)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(username=username, password=password)\nuser.is_admin = True\nuser.save(using=self._db)\nreturn user"
] | <|body_start_0|>
if not username:
raise ValueError('Users must have an username.')
user = self.model(username=username)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = self.create_user(username=username... | MyUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
def create_user(self, username, password=None):
"""Creates and saves a User with the given username and password."""
<|body_0|>
def create_superuser(self, username, password):
"""Creates and saves a superuser with the given username and password."""
... | stack_v2_sparse_classes_10k_train_008378 | 5,720 | no_license | [
{
"docstring": "Creates and saves a User with the given username and password.",
"name": "create_user",
"signature": "def create_user(self, username, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given username and password.",
"name": "create_superuser",
"sign... | 2 | stack_v2_sparse_classes_30k_train_006401 | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, username, password=None): Creates and saves a User with the given username and password.
- def create_superuser(self, username, password): Creates... | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, username, password=None): Creates and saves a User with the given username and password.
- def create_superuser(self, username, password): Creates... | a92f30a77ad3ba9f97e916d2c0a355641c9397ba | <|skeleton|>
class MyUserManager:
def create_user(self, username, password=None):
"""Creates and saves a User with the given username and password."""
<|body_0|>
def create_superuser(self, username, password):
"""Creates and saves a superuser with the given username and password."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MyUserManager:
def create_user(self, username, password=None):
"""Creates and saves a User with the given username and password."""
if not username:
raise ValueError('Users must have an username.')
user = self.model(username=username)
user.set_password(password)
... | the_stack_v2_python_sparse | app/models.py | nlattessi/inspt_tp_final_cpe | train | 0 | |
cf58fcdc9b8992c75065587a53a9f5a42e6610bf | [
"well = WellService.get_by_well_id(well_id)\nif well is None:\n return self.format_failure(404, 'Well Not Found')\nreturn self.format_success(200, {'well': well})",
"well = WellService.get_by_well_id(well_id)\nif well is None:\n self.format_failure(404, 'Well Not Found')\nreturn self.format_success(200, {'w... | <|body_start_0|>
well = WellService.get_by_well_id(well_id)
if well is None:
return self.format_failure(404, 'Well Not Found')
return self.format_success(200, {'well': well})
<|end_body_0|>
<|body_start_1|>
well = WellService.get_by_well_id(well_id)
if well is None:
... | API Resource for /wells/<well_id>/hygiene | WellHygiene | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WellHygiene:
"""API Resource for /wells/<well_id>/hygiene"""
def get(self, well_id, **_):
"""GET /wells/<well_id>/hygiene"""
<|body_0|>
def post(self, well_id: str):
"""POST /wells/<well_id>/hygiene"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_008379 | 1,884 | no_license | [
{
"docstring": "GET /wells/<well_id>/hygiene",
"name": "get",
"signature": "def get(self, well_id, **_)"
},
{
"docstring": "POST /wells/<well_id>/hygiene",
"name": "post",
"signature": "def post(self, well_id: str)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005353 | Implement the Python class `WellHygiene` described below.
Class description:
API Resource for /wells/<well_id>/hygiene
Method signatures and docstrings:
- def get(self, well_id, **_): GET /wells/<well_id>/hygiene
- def post(self, well_id: str): POST /wells/<well_id>/hygiene | Implement the Python class `WellHygiene` described below.
Class description:
API Resource for /wells/<well_id>/hygiene
Method signatures and docstrings:
- def get(self, well_id, **_): GET /wells/<well_id>/hygiene
- def post(self, well_id: str): POST /wells/<well_id>/hygiene
<|skeleton|>
class WellHygiene:
"""API... | 8ab4034413262ff2271740d73df72b3d83ce5918 | <|skeleton|>
class WellHygiene:
"""API Resource for /wells/<well_id>/hygiene"""
def get(self, well_id, **_):
"""GET /wells/<well_id>/hygiene"""
<|body_0|>
def post(self, well_id: str):
"""POST /wells/<well_id>/hygiene"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WellHygiene:
"""API Resource for /wells/<well_id>/hygiene"""
def get(self, well_id, **_):
"""GET /wells/<well_id>/hygiene"""
well = WellService.get_by_well_id(well_id)
if well is None:
return self.format_failure(404, 'Well Not Found')
return self.format_success... | the_stack_v2_python_sparse | app/main/controllers/wells/well_hygiene_controller.py | Malawi-Water-Wells-project/malawi-auth-api | train | 1 |
9eeb378858e67d613479fa41aed968acb7d98a55 | [
"student = g.user\napply = StayApplyModel.objects(student=student).first()\nreturn self.unicode_safe_json_response({'value': apply.value}, 200)",
"student = g.user\nnow = datetime.now()\nif current_app.testing or (now.weekday() == 6 and now.time() > time(20, 30)) or 0 <= now.weekday() < 3 or (now.weekday() == 3 a... | <|body_start_0|>
student = g.user
apply = StayApplyModel.objects(student=student).first()
return self.unicode_safe_json_response({'value': apply.value}, 200)
<|end_body_0|>
<|body_start_1|>
student = g.user
now = datetime.now()
if current_app.testing or (now.weekday() ==... | Stay | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Stay:
def get(self):
"""잔류신청 정보 조회"""
<|body_0|>
def post(self):
"""잔류신청"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
student = g.user
apply = StayApplyModel.objects(student=student).first()
return self.unicode_safe_json_response(... | stack_v2_sparse_classes_10k_train_008380 | 1,418 | permissive | [
{
"docstring": "잔류신청 정보 조회",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "잔류신청",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002545 | Implement the Python class `Stay` described below.
Class description:
Implement the Stay class.
Method signatures and docstrings:
- def get(self): 잔류신청 정보 조회
- def post(self): 잔류신청 | Implement the Python class `Stay` described below.
Class description:
Implement the Stay class.
Method signatures and docstrings:
- def get(self): 잔류신청 정보 조회
- def post(self): 잔류신청
<|skeleton|>
class Stay:
def get(self):
"""잔류신청 정보 조회"""
<|body_0|>
def post(self):
"""잔류신청"""
... | de585fe904a2bf15f9fc74219eae176151a0f8ca | <|skeleton|>
class Stay:
def get(self):
"""잔류신청 정보 조회"""
<|body_0|>
def post(self):
"""잔류신청"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Stay:
def get(self):
"""잔류신청 정보 조회"""
student = g.user
apply = StayApplyModel.objects(student=student).first()
return self.unicode_safe_json_response({'value': apply.value}, 200)
def post(self):
"""잔류신청"""
student = g.user
now = datetime.now()
... | the_stack_v2_python_sparse | Server/app/views/v1/student/apply/stay.py | miraedbswo/DMS-Backend | train | 2 | |
8def3f581639a798530279009a9154d96ef2f8dd | [
"prec_edges = main_model.external_precursor_nodes_names\ngraph_inputs = GlobalContext().onnx_graph_info.get('graph_inputs')\ninputs = dict()\nfor edge in graph_inputs:\n if not edge in inputs and edge in prec_edges:\n regular_edge = MatcherHelper.regular_edge_name(edge)\n inputs[edge] = regular_edg... | <|body_start_0|>
prec_edges = main_model.external_precursor_nodes_names
graph_inputs = GlobalContext().onnx_graph_info.get('graph_inputs')
inputs = dict()
for edge in graph_inputs:
if not edge in inputs and edge in prec_edges:
regular_edge = MatcherHelper.regu... | Helper function for matching processing. | MatcherHelper | [
"Apache-2.0",
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MatcherHelper:
"""Helper function for matching processing."""
def main_model_special_process_inputs(main_model: ModuleStruct):
"""Call in preprocess"""
<|body_0|>
def regular_edge_name(name: str) -> str:
"""Regular the edge name to adapt the python grammar."""
... | stack_v2_sparse_classes_10k_train_008381 | 8,903 | permissive | [
{
"docstring": "Call in preprocess",
"name": "main_model_special_process_inputs",
"signature": "def main_model_special_process_inputs(main_model: ModuleStruct)"
},
{
"docstring": "Regular the edge name to adapt the python grammar.",
"name": "regular_edge_name",
"signature": "def regular_... | 6 | stack_v2_sparse_classes_30k_train_003329 | Implement the Python class `MatcherHelper` described below.
Class description:
Helper function for matching processing.
Method signatures and docstrings:
- def main_model_special_process_inputs(main_model: ModuleStruct): Call in preprocess
- def regular_edge_name(name: str) -> str: Regular the edge name to adapt the ... | Implement the Python class `MatcherHelper` described below.
Class description:
Helper function for matching processing.
Method signatures and docstrings:
- def main_model_special_process_inputs(main_model: ModuleStruct): Call in preprocess
- def regular_edge_name(name: str) -> str: Regular the edge name to adapt the ... | 9073ef36d7f750c72262c87779e77e7c3602dd83 | <|skeleton|>
class MatcherHelper:
"""Helper function for matching processing."""
def main_model_special_process_inputs(main_model: ModuleStruct):
"""Call in preprocess"""
<|body_0|>
def regular_edge_name(name: str) -> str:
"""Regular the edge name to adapt the python grammar."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MatcherHelper:
"""Helper function for matching processing."""
def main_model_special_process_inputs(main_model: ModuleStruct):
"""Call in preprocess"""
prec_edges = main_model.external_precursor_nodes_names
graph_inputs = GlobalContext().onnx_graph_info.get('graph_inputs')
... | the_stack_v2_python_sparse | mindinsight/mindconverter/graph_based_converter/generator/matcher.py | nimengliusha/mindinsight | train | 0 |
62b33bf62ce4d87ded30504248ac66f7871778a0 | [
"if namespace is None:\n self.use_main_ns = 1\nelse:\n self.use_main_ns = 0\n self.namespace = namespace\nif global_namespace is None:\n self.global_namespace = {}\nelse:\n self.global_namespace = global_namespace",
"if self.use_main_ns:\n raise RuntimeError('Namespace must be provided!')\nif '.... | <|body_start_0|>
if namespace is None:
self.use_main_ns = 1
else:
self.use_main_ns = 0
self.namespace = namespace
if global_namespace is None:
self.global_namespace = {}
else:
self.global_namespace = global_namespace
<|end_body_... | Completer | [
"EPL-1.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Completer:
def __init__(self, namespace=None, global_namespace=None):
"""Create a new completer for the command line. Completer([namespace,global_namespace]) -> completer instance. If unspecified, the default namespace where completions are performed is __main__ (technically, __main__.__... | stack_v2_sparse_classes_10k_train_008382 | 6,762 | permissive | [
{
"docstring": "Create a new completer for the command line. Completer([namespace,global_namespace]) -> completer instance. If unspecified, the default namespace where completions are performed is __main__ (technically, __main__.__dict__). Namespaces should be given as dictionaries. An optional second namespace... | 4 | null | Implement the Python class `Completer` described below.
Class description:
Implement the Completer class.
Method signatures and docstrings:
- def __init__(self, namespace=None, global_namespace=None): Create a new completer for the command line. Completer([namespace,global_namespace]) -> completer instance. If unspec... | Implement the Python class `Completer` described below.
Class description:
Implement the Completer class.
Method signatures and docstrings:
- def __init__(self, namespace=None, global_namespace=None): Create a new completer for the command line. Completer([namespace,global_namespace]) -> completer instance. If unspec... | 05dbd4575d01a213f3f4d69aa4968473f2536142 | <|skeleton|>
class Completer:
def __init__(self, namespace=None, global_namespace=None):
"""Create a new completer for the command line. Completer([namespace,global_namespace]) -> completer instance. If unspecified, the default namespace where completions are performed is __main__ (technically, __main__.__... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Completer:
def __init__(self, namespace=None, global_namespace=None):
"""Create a new completer for the command line. Completer([namespace,global_namespace]) -> completer instance. If unspecified, the default namespace where completions are performed is __main__ (technically, __main__.__dict__). Names... | the_stack_v2_python_sparse | python/helpers/pydev/_pydev_bundle/_pydev_completer.py | JetBrains/intellij-community | train | 16,288 | |
04ce70de1e5ebc55ae65200088df561b8c34761a | [
"self.alive: bool = False\nself.console: Console = console\nsession = requests.session()\nretry = Retry(total=OtRobot.RETRIES, read=OtRobot.RETRIES, connect=OtRobot.RETRIES, backoff_factor=OtRobot.BACK_OFF_FACTOR, status_forcelist=OtRobot.ERROR_CODES)\nadapter = HTTPAdapter(max_retries=retry)\nsession.mount('http:/... | <|body_start_0|>
self.alive: bool = False
self.console: Console = console
session = requests.session()
retry = Retry(total=OtRobot.RETRIES, read=OtRobot.RETRIES, connect=OtRobot.RETRIES, backoff_factor=OtRobot.BACK_OFF_FACTOR, status_forcelist=OtRobot.ERROR_CODES)
adapter = HTTPA... | Opentrons Robot. | OtRobot | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OtRobot:
"""Opentrons Robot."""
def __init__(self, console: Console, robot_data: RobotDataType) -> None:
"""Initialize the robot."""
<|body_0|>
def is_alive(self) -> bool:
"""Is a robot available by http - request the openapi.json."""
<|body_1|>
def ... | stack_v2_sparse_classes_10k_train_008383 | 5,029 | permissive | [
{
"docstring": "Initialize the robot.",
"name": "__init__",
"signature": "def __init__(self, console: Console, robot_data: RobotDataType) -> None"
},
{
"docstring": "Is a robot available by http - request the openapi.json.",
"name": "is_alive",
"signature": "def is_alive(self) -> bool"
... | 6 | null | Implement the Python class `OtRobot` described below.
Class description:
Opentrons Robot.
Method signatures and docstrings:
- def __init__(self, console: Console, robot_data: RobotDataType) -> None: Initialize the robot.
- def is_alive(self) -> bool: Is a robot available by http - request the openapi.json.
- def get_... | Implement the Python class `OtRobot` described below.
Class description:
Opentrons Robot.
Method signatures and docstrings:
- def __init__(self, console: Console, robot_data: RobotDataType) -> None: Initialize the robot.
- def is_alive(self) -> bool: Is a robot available by http - request the openapi.json.
- def get_... | 026b523c8c9e5d45910c490efb89194d72595be9 | <|skeleton|>
class OtRobot:
"""Opentrons Robot."""
def __init__(self, console: Console, robot_data: RobotDataType) -> None:
"""Initialize the robot."""
<|body_0|>
def is_alive(self) -> bool:
"""Is a robot available by http - request the openapi.json."""
<|body_1|>
def ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OtRobot:
"""Opentrons Robot."""
def __init__(self, console: Console, robot_data: RobotDataType) -> None:
"""Initialize the robot."""
self.alive: bool = False
self.console: Console = console
session = requests.session()
retry = Retry(total=OtRobot.RETRIES, read=OtRo... | the_stack_v2_python_sparse | app-testing/automation/resources/ot_robot.py | Opentrons/opentrons | train | 326 |
7eae07e3f21efe42555adc9f7c3cc9b06fc4e13c | [
"assert 0 < eta, 'Efficiency of boiler should be greater 0.' + ' Check your input for eta.'\nassert eta <= 1, 'Efficiency of boiler should smaller or equal to 1.' + ' Check your input for eta.'\nsuper(BoilerExtended, self).__init__(environment=environment, qNominal=q_nominal, tMax=t_max, lowerActivationLimit=lower_... | <|body_start_0|>
assert 0 < eta, 'Efficiency of boiler should be greater 0.' + ' Check your input for eta.'
assert eta <= 1, 'Efficiency of boiler should smaller or equal to 1.' + ' Check your input for eta.'
super(BoilerExtended, self).__init__(environment=environment, qNominal=q_nominal, tMax=... | BoilerExtended class (inheritance from pycity Boiler class) Derives from boiler (HeatingDevice) of pycity. self.totalQOutput self.array_fuel_power | BoilerExtended | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BoilerExtended:
"""BoilerExtended class (inheritance from pycity Boiler class) Derives from boiler (HeatingDevice) of pycity. self.totalQOutput self.array_fuel_power"""
def __init__(self, environment, q_nominal, eta, t_max=85, lower_activation_limit=0.2):
"""Parameters ---------- env... | stack_v2_sparse_classes_10k_train_008384 | 6,053 | permissive | [
{
"docstring": "Parameters ---------- environment : Extended environment object Common to all other objects. Includes time and weather instances q_nominal : float nominal heat output in W eta : float efficiency (without unit) t_max : Integer, optional maximum provided temperature in °C (default : 85 °C) lower_a... | 5 | stack_v2_sparse_classes_30k_train_005077 | Implement the Python class `BoilerExtended` described below.
Class description:
BoilerExtended class (inheritance from pycity Boiler class) Derives from boiler (HeatingDevice) of pycity. self.totalQOutput self.array_fuel_power
Method signatures and docstrings:
- def __init__(self, environment, q_nominal, eta, t_max=8... | Implement the Python class `BoilerExtended` described below.
Class description:
BoilerExtended class (inheritance from pycity Boiler class) Derives from boiler (HeatingDevice) of pycity. self.totalQOutput self.array_fuel_power
Method signatures and docstrings:
- def __init__(self, environment, q_nominal, eta, t_max=8... | 99fd0dab7f9a9030fd84ba4715753364662927ec | <|skeleton|>
class BoilerExtended:
"""BoilerExtended class (inheritance from pycity Boiler class) Derives from boiler (HeatingDevice) of pycity. self.totalQOutput self.array_fuel_power"""
def __init__(self, environment, q_nominal, eta, t_max=85, lower_activation_limit=0.2):
"""Parameters ---------- env... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BoilerExtended:
"""BoilerExtended class (inheritance from pycity Boiler class) Derives from boiler (HeatingDevice) of pycity. self.totalQOutput self.array_fuel_power"""
def __init__(self, environment, q_nominal, eta, t_max=85, lower_activation_limit=0.2):
"""Parameters ---------- environment : Ex... | the_stack_v2_python_sparse | pycity_calc/energysystems/boiler.py | RWTH-EBC/pyCity_calc | train | 4 |
490b8cb3534d501c235da6e93a5d649dbb153400 | [
"resp = req.get_response(self.app, method='HEAD')\nacl = resp.object_acl if req.is_object_request else resp.bucket_acl\nresp = HTTPOk()\nresp.body = tostring(acl.elem())\nreturn resp",
"if req.is_object_request:\n headers = {}\n src_path = '/%s/%s' % (req.container_name, req.object_name)\n headers['X-Cop... | <|body_start_0|>
resp = req.get_response(self.app, method='HEAD')
acl = resp.object_acl if req.is_object_request else resp.bucket_acl
resp = HTTPOk()
resp.body = tostring(acl.elem())
return resp
<|end_body_0|>
<|body_start_1|>
if req.is_object_request:
header... | Handles the following APIs: * GET Bucket acl * PUT Bucket acl * GET Object acl * PUT Object acl Those APIs are logged as ACL operations in the S3 server log. | S3AclController | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class S3AclController:
"""Handles the following APIs: * GET Bucket acl * PUT Bucket acl * GET Object acl * PUT Object acl Those APIs are logged as ACL operations in the S3 server log."""
def GET(self, req):
"""Handles GET Bucket acl and GET Object acl."""
<|body_0|>
def PUT(se... | stack_v2_sparse_classes_10k_train_008385 | 2,097 | permissive | [
{
"docstring": "Handles GET Bucket acl and GET Object acl.",
"name": "GET",
"signature": "def GET(self, req)"
},
{
"docstring": "Handles PUT Bucket acl and PUT Object acl.",
"name": "PUT",
"signature": "def PUT(self, req)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001369 | Implement the Python class `S3AclController` described below.
Class description:
Handles the following APIs: * GET Bucket acl * PUT Bucket acl * GET Object acl * PUT Object acl Those APIs are logged as ACL operations in the S3 server log.
Method signatures and docstrings:
- def GET(self, req): Handles GET Bucket acl ... | Implement the Python class `S3AclController` described below.
Class description:
Handles the following APIs: * GET Bucket acl * PUT Bucket acl * GET Object acl * PUT Object acl Those APIs are logged as ACL operations in the S3 server log.
Method signatures and docstrings:
- def GET(self, req): Handles GET Bucket acl ... | f06e5369579599648cc78e4b556887bc6d978c2b | <|skeleton|>
class S3AclController:
"""Handles the following APIs: * GET Bucket acl * PUT Bucket acl * GET Object acl * PUT Object acl Those APIs are logged as ACL operations in the S3 server log."""
def GET(self, req):
"""Handles GET Bucket acl and GET Object acl."""
<|body_0|>
def PUT(se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class S3AclController:
"""Handles the following APIs: * GET Bucket acl * PUT Bucket acl * GET Object acl * PUT Object acl Those APIs are logged as ACL operations in the S3 server log."""
def GET(self, req):
"""Handles GET Bucket acl and GET Object acl."""
resp = req.get_response(self.app, metho... | the_stack_v2_python_sparse | swift/common/middleware/s3api/controllers/s3_acl.py | openstack/swift | train | 2,370 |
897a5b25f1ee712c2048b3ec66837a56cdfc0bf5 | [
"pip_manager = PipManager.get_singleton()\npip_manager.install_pip(lazy=True, op=op)\nadd_command_line_sys_path()\ndependency_install_command = [_get_python_exe_path(), '-m', 'pip', 'install', '--no-cache-dir', self.package_name]\nlog_report('INFO', f'Installing dependency with {dependency_install_command}', op)\ns... | <|body_start_0|>
pip_manager = PipManager.get_singleton()
pip_manager.install_pip(lazy=True, op=op)
add_command_line_sys_path()
dependency_install_command = [_get_python_exe_path(), '-m', 'pip', 'install', '--no-cache-dir', self.package_name]
log_report('INFO', f'Installing depen... | Class that describes an optional Python dependency of the addon. | OptionalDependency | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptionalDependency:
"""Class that describes an optional Python dependency of the addon."""
def install(self, op=None):
"""Install this dependency."""
<|body_0|>
def uninstall(self, remove_sys_path=True, op=None):
"""Uninstall this dependency."""
<|body_1|... | stack_v2_sparse_classes_10k_train_008386 | 14,831 | permissive | [
{
"docstring": "Install this dependency.",
"name": "install",
"signature": "def install(self, op=None)"
},
{
"docstring": "Uninstall this dependency.",
"name": "uninstall",
"signature": "def uninstall(self, remove_sys_path=True, op=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004546 | Implement the Python class `OptionalDependency` described below.
Class description:
Class that describes an optional Python dependency of the addon.
Method signatures and docstrings:
- def install(self, op=None): Install this dependency.
- def uninstall(self, remove_sys_path=True, op=None): Uninstall this dependency. | Implement the Python class `OptionalDependency` described below.
Class description:
Class that describes an optional Python dependency of the addon.
Method signatures and docstrings:
- def install(self, op=None): Install this dependency.
- def uninstall(self, remove_sys_path=True, op=None): Uninstall this dependency.... | da404ebf8d4412196c2740f0b569cbf9e542952d | <|skeleton|>
class OptionalDependency:
"""Class that describes an optional Python dependency of the addon."""
def install(self, op=None):
"""Install this dependency."""
<|body_0|>
def uninstall(self, remove_sys_path=True, op=None):
"""Uninstall this dependency."""
<|body_1|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OptionalDependency:
"""Class that describes an optional Python dependency of the addon."""
def install(self, op=None):
"""Install this dependency."""
pip_manager = PipManager.get_singleton()
pip_manager.install_pip(lazy=True, op=op)
add_command_line_sys_path()
depe... | the_stack_v2_python_sparse | photogrammetry_importer/preferences/dependency.py | SBCV/Blender-Addon-Photogrammetry-Importer | train | 718 |
435f48322403ca8e571f3bccfe8cc3a0a1677b7e | [
"super().__init__()\ncheck_boundaries(boundaries)\nself.boundaries = boundaries",
"self.randomize(None)\nself.magnitude = self.R.uniform(low=self.boundaries[0], high=self.boundaries[1])\nlength = signal.shape[1]\ngaussiannoise = self.magnitude * torch.randn(length)\nsignal = convert_to_tensor(signal) + gaussianno... | <|body_start_0|>
super().__init__()
check_boundaries(boundaries)
self.boundaries = boundaries
<|end_body_0|>
<|body_start_1|>
self.randomize(None)
self.magnitude = self.R.uniform(low=self.boundaries[0], high=self.boundaries[1])
length = signal.shape[1]
gaussianno... | Add a random gaussian noise to the input signal | SignalRandAddGaussianNoise | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignalRandAddGaussianNoise:
"""Add a random gaussian noise to the input signal"""
def __init__(self, boundaries: Sequence[float]=(0.001, 0.02)) -> None:
"""Args: boundaries: list defining lower and upper boundaries for the signal magnitude, default : ``[0.001,0.02]``"""
<|bod... | stack_v2_sparse_classes_10k_train_008387 | 16,322 | permissive | [
{
"docstring": "Args: boundaries: list defining lower and upper boundaries for the signal magnitude, default : ``[0.001,0.02]``",
"name": "__init__",
"signature": "def __init__(self, boundaries: Sequence[float]=(0.001, 0.02)) -> None"
},
{
"docstring": "Args: signal: input 1 dimension signal to ... | 2 | stack_v2_sparse_classes_30k_train_002501 | Implement the Python class `SignalRandAddGaussianNoise` described below.
Class description:
Add a random gaussian noise to the input signal
Method signatures and docstrings:
- def __init__(self, boundaries: Sequence[float]=(0.001, 0.02)) -> None: Args: boundaries: list defining lower and upper boundaries for the sign... | Implement the Python class `SignalRandAddGaussianNoise` described below.
Class description:
Add a random gaussian noise to the input signal
Method signatures and docstrings:
- def __init__(self, boundaries: Sequence[float]=(0.001, 0.02)) -> None: Args: boundaries: list defining lower and upper boundaries for the sign... | e48c3e2c741fa3fc705c4425d17ac4a5afac6c47 | <|skeleton|>
class SignalRandAddGaussianNoise:
"""Add a random gaussian noise to the input signal"""
def __init__(self, boundaries: Sequence[float]=(0.001, 0.02)) -> None:
"""Args: boundaries: list defining lower and upper boundaries for the signal magnitude, default : ``[0.001,0.02]``"""
<|bod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SignalRandAddGaussianNoise:
"""Add a random gaussian noise to the input signal"""
def __init__(self, boundaries: Sequence[float]=(0.001, 0.02)) -> None:
"""Args: boundaries: list defining lower and upper boundaries for the signal magnitude, default : ``[0.001,0.02]``"""
super().__init__()... | the_stack_v2_python_sparse | monai/transforms/signal/array.py | Project-MONAI/MONAI | train | 4,805 |
555e4586db963ddad37b0f87e242791794d8ecf9 | [
"self.encode_res = ''\nfor i in strs:\n self.encode_res += str(len(i)) + ','\n self.encode_res += i + ','\nreturn self.encode_res[:-1]",
"self.decode_res = []\ni = 0\nwhile i < len(s):\n len_word = ''\n while s[i] != ',':\n len_word += s[i]\n i += 1\n start = i + 1\n end = start + ... | <|body_start_0|>
self.encode_res = ''
for i in strs:
self.encode_res += str(len(i)) + ','
self.encode_res += i + ','
return self.encode_res[:-1]
<|end_body_0|>
<|body_start_1|>
self.decode_res = []
i = 0
while i < len(s):
len_word = ''... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.enco... | stack_v2_sparse_classes_10k_train_008388 | 2,072 | permissive | [
{
"docstring": "Encodes a list of strings to a single string.",
"name": "encode",
"signature": "def encode(self, strs: [str]) -> str"
},
{
"docstring": "Decodes a single string to a list of strings.",
"name": "decode",
"signature": "def decode(self, s: str) -> [str]"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings.
<|skeleton|>
cla... | 1dbd18114ed688ddeaa3ee83181d373dcc1429e5 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
self.encode_res = ''
for i in strs:
self.encode_res += str(len(i)) + ','
self.encode_res += i + ','
return self.encode_res[:-1]
def decode(self, s: str)... | the_stack_v2_python_sparse | source/Clarification/Array/271.字符串的编码与解码.py | zhangwang0537/LeetCode-Notebook | train | 0 | |
1451ccf5ff0951b9c8a222db4384a22ec0166fec | [
"super(ConvolutionModule, self).__init__()\nassert (depthwise_kernel_size - 1) % 2 == 0, \"kernel_size should be a odd number for 'SAME' padding\"\nself.layer_norm = LayerNorm(embed_dim, export=export)\nself.pointwise_conv1 = torch.nn.Conv1d(embed_dim, 2 * channels, kernel_size=1, stride=1, padding=0, bias=bias)\ns... | <|body_start_0|>
super(ConvolutionModule, self).__init__()
assert (depthwise_kernel_size - 1) % 2 == 0, "kernel_size should be a odd number for 'SAME' padding"
self.layer_norm = LayerNorm(embed_dim, export=export)
self.pointwise_conv1 = torch.nn.Conv1d(embed_dim, 2 * channels, kernel_siz... | Convolution block used in the conformer block | ConvolutionModule | [
"LicenseRef-scancode-unknown-license-reference",
"MIT",
"LGPL-2.1-or-later",
"LicenseRef-scancode-free-unknown",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvolutionModule:
"""Convolution block used in the conformer block"""
def __init__(self, embed_dim, channels, depthwise_kernel_size, dropout, activation_fn='swish', bias=False, export=False):
"""Args: embed_dim: Embedding dimension channels: Number of channels in depthwise conv laye... | stack_v2_sparse_classes_10k_train_008389 | 9,087 | permissive | [
{
"docstring": "Args: embed_dim: Embedding dimension channels: Number of channels in depthwise conv layers depthwise_kernel_size: Depthwise conv layer kernel size dropout: dropout value activation_fn: Activation function to use after depthwise convolution kernel bias: If bias should be added to conv layers expo... | 2 | null | Implement the Python class `ConvolutionModule` described below.
Class description:
Convolution block used in the conformer block
Method signatures and docstrings:
- def __init__(self, embed_dim, channels, depthwise_kernel_size, dropout, activation_fn='swish', bias=False, export=False): Args: embed_dim: Embedding dime... | Implement the Python class `ConvolutionModule` described below.
Class description:
Convolution block used in the conformer block
Method signatures and docstrings:
- def __init__(self, embed_dim, channels, depthwise_kernel_size, dropout, activation_fn='swish', bias=False, export=False): Args: embed_dim: Embedding dime... | b60c741f746877293bb85eed6806736fc8fa0ffd | <|skeleton|>
class ConvolutionModule:
"""Convolution block used in the conformer block"""
def __init__(self, embed_dim, channels, depthwise_kernel_size, dropout, activation_fn='swish', bias=False, export=False):
"""Args: embed_dim: Embedding dimension channels: Number of channels in depthwise conv laye... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ConvolutionModule:
"""Convolution block used in the conformer block"""
def __init__(self, embed_dim, channels, depthwise_kernel_size, dropout, activation_fn='swish', bias=False, export=False):
"""Args: embed_dim: Embedding dimension channels: Number of channels in depthwise conv layers depthwise_... | the_stack_v2_python_sparse | kosmos-2/fairseq/fairseq/modules/conformer_layer.py | microsoft/unilm | train | 15,313 |
0a763de92b0b0258170c07b8b039d823b632ce69 | [
"self.logger.debug('Start unzipping the file: %s.' % zip_file)\ndir_name = os.path.basename(zip_file).rsplit('.', 1)[0]\nif not unzip_path:\n if add_dir:\n unzip_path = zip_file.rsplit('.', 1)[0]\n else:\n unzip_path = os.path.dirname(zip_file)\nwith zipfile.ZipFile(zip_file, 'r') as f:\n for... | <|body_start_0|>
self.logger.debug('Start unzipping the file: %s.' % zip_file)
dir_name = os.path.basename(zip_file).rsplit('.', 1)[0]
if not unzip_path:
if add_dir:
unzip_path = zip_file.rsplit('.', 1)[0]
else:
unzip_path = os.path.dirname... | cleanup class. Args: Example: Return: Author: cai, yong IsInterface: False ChangeInfo: cai, yong 2019-09-17 | MyZip | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyZip:
"""cleanup class. Args: Example: Return: Author: cai, yong IsInterface: False ChangeInfo: cai, yong 2019-09-17"""
def unzip_file(self, zip_file, unzip_path='', add_dir=False):
"""unzip the file. Args: zip_file type(str) the abspath of the file to be unzipped. unzip_path type(s... | stack_v2_sparse_classes_10k_train_008390 | 2,756 | no_license | [
{
"docstring": "unzip the file. Args: zip_file type(str) the abspath of the file to be unzipped. unzip_path type(str) unzipped path add_dir type(bool) whether to add a layer of directory when unzip the file Example: Return: Author: cai, yong IsInterface: False ChangeInfo: cai, yong 2019-09-23",
"name": "unz... | 2 | null | Implement the Python class `MyZip` described below.
Class description:
cleanup class. Args: Example: Return: Author: cai, yong IsInterface: False ChangeInfo: cai, yong 2019-09-17
Method signatures and docstrings:
- def unzip_file(self, zip_file, unzip_path='', add_dir=False): unzip the file. Args: zip_file type(str) ... | Implement the Python class `MyZip` described below.
Class description:
cleanup class. Args: Example: Return: Author: cai, yong IsInterface: False ChangeInfo: cai, yong 2019-09-17
Method signatures and docstrings:
- def unzip_file(self, zip_file, unzip_path='', add_dir=False): unzip the file. Args: zip_file type(str) ... | 2d3490393737b3e5f086cb6623369b988ffce67f | <|skeleton|>
class MyZip:
"""cleanup class. Args: Example: Return: Author: cai, yong IsInterface: False ChangeInfo: cai, yong 2019-09-17"""
def unzip_file(self, zip_file, unzip_path='', add_dir=False):
"""unzip the file. Args: zip_file type(str) the abspath of the file to be unzipped. unzip_path type(s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MyZip:
"""cleanup class. Args: Example: Return: Author: cai, yong IsInterface: False ChangeInfo: cai, yong 2019-09-17"""
def unzip_file(self, zip_file, unzip_path='', add_dir=False):
"""unzip the file. Args: zip_file type(str) the abspath of the file to be unzipped. unzip_path type(str) unzipped ... | the_stack_v2_python_sparse | lib/tools/public/my_zip.py | Lewescaiyong/auto_test_framework | train | 1 |
312588e7ffe7dd1fc6b11cd866583e8563f9c34f | [
"if m >= n:\n return head\nparent = None\np = head\nfor _ in range(m - 1):\n parent = p\n p = p.next\nt = p\ntmp = p.next\nchild = tmp\nfor _ in range(n - m):\n child = tmp\n if child:\n tmp = child.next\n child.next = p\n p = child\n else:\n break\nt.next = tmp\nif par... | <|body_start_0|>
if m >= n:
return head
parent = None
p = head
for _ in range(m - 1):
parent = p
p = p.next
t = p
tmp = p.next
child = tmp
for _ in range(n - m):
child = tmp
if child:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseBetween(self, head, m, n):
"""05/06/2018 01:00"""
<|body_0|>
def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]:
"""08/08/2021 17:38"""
<|body_1|>
def reverseBetween(self, head: Optional[L... | stack_v2_sparse_classes_10k_train_008391 | 3,687 | no_license | [
{
"docstring": "05/06/2018 01:00",
"name": "reverseBetween",
"signature": "def reverseBetween(self, head, m, n)"
},
{
"docstring": "08/08/2021 17:38",
"name": "reverseBetween",
"signature": "def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]"
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseBetween(self, head, m, n): 05/06/2018 01:00
- def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]: 08/08/2021 17:38
- def r... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseBetween(self, head, m, n): 05/06/2018 01:00
- def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]: 08/08/2021 17:38
- def r... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def reverseBetween(self, head, m, n):
"""05/06/2018 01:00"""
<|body_0|>
def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]:
"""08/08/2021 17:38"""
<|body_1|>
def reverseBetween(self, head: Optional[L... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseBetween(self, head, m, n):
"""05/06/2018 01:00"""
if m >= n:
return head
parent = None
p = head
for _ in range(m - 1):
parent = p
p = p.next
t = p
tmp = p.next
child = tmp
for _ in ... | the_stack_v2_python_sparse | leetcode/solved/92_Reverse_Linked_List_II/solution.py | sungminoh/algorithms | train | 0 | |
d59f52e8b4a45e98cb06fdfd00dfee331091988e | [
"pic_np = pic_tensor.asnumpy()[0]\nif pic_np.shape[0] == 1:\n pic_np = (pic_np[0] + 1) / 2.0 * 255.0\nelif pic_np.shape[0] == 3:\n pic_np = (np.transpose(pic_np, (1, 2, 0)) + 1) / 2.0 * 255.0\npic = Image.fromarray(pic_np)\npic = pic.convert('RGB')\npic.save(pic_path)\nprint(pic_path + ' is saved.')",
"real... | <|body_start_0|>
pic_np = pic_tensor.asnumpy()[0]
if pic_np.shape[0] == 1:
pic_np = (pic_np[0] + 1) / 2.0 * 255.0
elif pic_np.shape[0] == 3:
pic_np = (np.transpose(pic_np, (1, 2, 0)) + 1) / 2.0 * 255.0
pic = Image.fromarray(pic_np)
pic = pic.convert('RGB')... | Eval | Eval | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Eval:
"""Eval"""
def save_image(pic_tensor, pic_path='test.png'):
"""save image"""
<|body_0|>
def infer_one_image(net, all_data):
"""infer one image"""
<|body_1|>
def expand_tensor_data(data_tensor):
"""expand_tensor_data"""
<|body_2|... | stack_v2_sparse_classes_10k_train_008392 | 4,422 | permissive | [
{
"docstring": "save image",
"name": "save_image",
"signature": "def save_image(pic_tensor, pic_path='test.png')"
},
{
"docstring": "infer one image",
"name": "infer_one_image",
"signature": "def infer_one_image(net, all_data)"
},
{
"docstring": "expand_tensor_data",
"name": ... | 4 | null | Implement the Python class `Eval` described below.
Class description:
Eval
Method signatures and docstrings:
- def save_image(pic_tensor, pic_path='test.png'): save image
- def infer_one_image(net, all_data): infer one image
- def expand_tensor_data(data_tensor): expand_tensor_data
- def process_input(all_data, resul... | Implement the Python class `Eval` described below.
Class description:
Eval
Method signatures and docstrings:
- def save_image(pic_tensor, pic_path='test.png'): save image
- def infer_one_image(net, all_data): infer one image
- def expand_tensor_data(data_tensor): expand_tensor_data
- def process_input(all_data, resul... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class Eval:
"""Eval"""
def save_image(pic_tensor, pic_path='test.png'):
"""save image"""
<|body_0|>
def infer_one_image(net, all_data):
"""infer one image"""
<|body_1|>
def expand_tensor_data(data_tensor):
"""expand_tensor_data"""
<|body_2|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Eval:
"""Eval"""
def save_image(pic_tensor, pic_path='test.png'):
"""save image"""
pic_np = pic_tensor.asnumpy()[0]
if pic_np.shape[0] == 1:
pic_np = (pic_np[0] + 1) / 2.0 * 255.0
elif pic_np.shape[0] == 3:
pic_np = (np.transpose(pic_np, (1, 2, 0)) ... | the_stack_v2_python_sparse | research/cv/APDrawingGAN/eval.py | mindspore-ai/models | train | 301 |
e6164e470ea8b3e7fb60a21db9dd465ee5738e07 | [
"miner = Miner(name='Miner', version='1.0.b')\nminer.slug = get_unique_slug(miner, 'slug', 'name', 'version')\nminer.save()\nother_miner = Miner(name='MineR', version='1.0.b')\nother_miner.slug = get_unique_slug(other_miner, 'slug', 'name', 'version')\nself.assertNotEqual(miner.slug, other_miner.slug)",
"miner = ... | <|body_start_0|>
miner = Miner(name='Miner', version='1.0.b')
miner.slug = get_unique_slug(miner, 'slug', 'name', 'version')
miner.save()
other_miner = Miner(name='MineR', version='1.0.b')
other_miner.slug = get_unique_slug(other_miner, 'slug', 'name', 'version')
self.ass... | Тестирование гнерератора slug | GetSlugTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetSlugTest:
"""Тестирование гнерератора slug"""
def test_get_unique_slug(self):
"""Генерация уникального slug"""
<|body_0|>
def test_get_unique_slug_conflict(self):
"""Генерация уникального slug недопустимого значения"""
<|body_1|>
def test_get_slug... | stack_v2_sparse_classes_10k_train_008393 | 13,105 | permissive | [
{
"docstring": "Генерация уникального slug",
"name": "test_get_unique_slug",
"signature": "def test_get_unique_slug(self)"
},
{
"docstring": "Генерация уникального slug недопустимого значения",
"name": "test_get_unique_slug_conflict",
"signature": "def test_get_unique_slug_conflict(self)... | 5 | stack_v2_sparse_classes_30k_train_004693 | Implement the Python class `GetSlugTest` described below.
Class description:
Тестирование гнерератора slug
Method signatures and docstrings:
- def test_get_unique_slug(self): Генерация уникального slug
- def test_get_unique_slug_conflict(self): Генерация уникального slug недопустимого значения
- def test_get_slug(sel... | Implement the Python class `GetSlugTest` described below.
Class description:
Тестирование гнерератора slug
Method signatures and docstrings:
- def test_get_unique_slug(self): Генерация уникального slug
- def test_get_unique_slug_conflict(self): Генерация уникального slug недопустимого значения
- def test_get_slug(sel... | d173f1bee44d0752eefb53b1a0da847a3882a352 | <|skeleton|>
class GetSlugTest:
"""Тестирование гнерератора slug"""
def test_get_unique_slug(self):
"""Генерация уникального slug"""
<|body_0|>
def test_get_unique_slug_conflict(self):
"""Генерация уникального slug недопустимого значения"""
<|body_1|>
def test_get_slug... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GetSlugTest:
"""Тестирование гнерератора slug"""
def test_get_unique_slug(self):
"""Генерация уникального slug"""
miner = Miner(name='Miner', version='1.0.b')
miner.slug = get_unique_slug(miner, 'slug', 'name', 'version')
miner.save()
other_miner = Miner(name='Mine... | the_stack_v2_python_sparse | miningstatistic/core/tests.py | crowmurk/miners | train | 0 |
ee7b959f12a81d2d981a9ebf5c2fdb4cef154f76 | [
"super(ImprovedGAN_Discriminator, self).__init__()\nself.use_gpu = use_gpu\nself.n_B = n_B\nself.n_C = n_C\nself.featmap_dim = featmap_dim\nself.conv1 = nn.Conv2d(n_channel, featmap_dim / 4, 5, stride=2, padding=2)\nself.conv2 = nn.Conv2d(featmap_dim / 4, featmap_dim / 2, 5, stride=2, padding=2)\nself.BN2 = nn.Batc... | <|body_start_0|>
super(ImprovedGAN_Discriminator, self).__init__()
self.use_gpu = use_gpu
self.n_B = n_B
self.n_C = n_C
self.featmap_dim = featmap_dim
self.conv1 = nn.Conv2d(n_channel, featmap_dim / 4, 5, stride=2, padding=2)
self.conv2 = nn.Conv2d(featmap_dim / 4... | ImprovedGAN_Discriminator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImprovedGAN_Discriminator:
def __init__(self, featmap_dim=512, n_channel=1, use_gpu=False, n_B=128, n_C=16):
"""Minibatch discrimination: learn a tensor to encode side information from other examples in the same minibatch."""
<|body_0|>
def forward(self, x):
"""Archi... | stack_v2_sparse_classes_10k_train_008394 | 19,546 | no_license | [
{
"docstring": "Minibatch discrimination: learn a tensor to encode side information from other examples in the same minibatch.",
"name": "__init__",
"signature": "def __init__(self, featmap_dim=512, n_channel=1, use_gpu=False, n_B=128, n_C=16)"
},
{
"docstring": "Architecture is similar to DCGAN... | 2 | null | Implement the Python class `ImprovedGAN_Discriminator` described below.
Class description:
Implement the ImprovedGAN_Discriminator class.
Method signatures and docstrings:
- def __init__(self, featmap_dim=512, n_channel=1, use_gpu=False, n_B=128, n_C=16): Minibatch discrimination: learn a tensor to encode side inform... | Implement the Python class `ImprovedGAN_Discriminator` described below.
Class description:
Implement the ImprovedGAN_Discriminator class.
Method signatures and docstrings:
- def __init__(self, featmap_dim=512, n_channel=1, use_gpu=False, n_B=128, n_C=16): Minibatch discrimination: learn a tensor to encode side inform... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class ImprovedGAN_Discriminator:
def __init__(self, featmap_dim=512, n_channel=1, use_gpu=False, n_B=128, n_C=16):
"""Minibatch discrimination: learn a tensor to encode side information from other examples in the same minibatch."""
<|body_0|>
def forward(self, x):
"""Archi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ImprovedGAN_Discriminator:
def __init__(self, featmap_dim=512, n_channel=1, use_gpu=False, n_B=128, n_C=16):
"""Minibatch discrimination: learn a tensor to encode side information from other examples in the same minibatch."""
super(ImprovedGAN_Discriminator, self).__init__()
self.use_g... | the_stack_v2_python_sparse | generated/test_AaronYALai_Generative_Adversarial_Networks_PyTorch.py | jansel/pytorch-jit-paritybench | train | 35 | |
0cec5c6ceb1df809854e5dd36576a5b0c1e6acc7 | [
"super(COMACriticNetwork, self).__init__()\nself.action_shape = action_shape\nself.act = nn.ReLU()\nself.mlp = nn.Sequential(MLP(input_size, hidden_size, hidden_size, 2, activation=self.act), nn.Linear(hidden_size, action_shape))",
"x = self._preprocess_data(data)\nq = self.mlp(x)\nreturn {'q_value': q}",
"t_si... | <|body_start_0|>
super(COMACriticNetwork, self).__init__()
self.action_shape = action_shape
self.act = nn.ReLU()
self.mlp = nn.Sequential(MLP(input_size, hidden_size, hidden_size, 2, activation=self.act), nn.Linear(hidden_size, action_shape))
<|end_body_0|>
<|body_start_1|>
x = ... | Overview: Centralized critic network in COMA Interface: __init__, forward | COMACriticNetwork | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class COMACriticNetwork:
"""Overview: Centralized critic network in COMA Interface: __init__, forward"""
def __init__(self, input_size: int, action_shape: int, hidden_size: int=128):
"""Overview: initialize COMA critic network Arguments: - input_size (:obj:`int`): the size of input global ... | stack_v2_sparse_classes_10k_train_008395 | 7,790 | permissive | [
{
"docstring": "Overview: initialize COMA critic network Arguments: - input_size (:obj:`int`): the size of input global observation - action_shape (:obj:`int`): the dimension of action shape - hidden_size_list (:obj:`list`): the list of hidden size, default to 128",
"name": "__init__",
"signature": "def... | 3 | stack_v2_sparse_classes_30k_train_006520 | Implement the Python class `COMACriticNetwork` described below.
Class description:
Overview: Centralized critic network in COMA Interface: __init__, forward
Method signatures and docstrings:
- def __init__(self, input_size: int, action_shape: int, hidden_size: int=128): Overview: initialize COMA critic network Argume... | Implement the Python class `COMACriticNetwork` described below.
Class description:
Overview: Centralized critic network in COMA Interface: __init__, forward
Method signatures and docstrings:
- def __init__(self, input_size: int, action_shape: int, hidden_size: int=128): Overview: initialize COMA critic network Argume... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class COMACriticNetwork:
"""Overview: Centralized critic network in COMA Interface: __init__, forward"""
def __init__(self, input_size: int, action_shape: int, hidden_size: int=128):
"""Overview: initialize COMA critic network Arguments: - input_size (:obj:`int`): the size of input global ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class COMACriticNetwork:
"""Overview: Centralized critic network in COMA Interface: __init__, forward"""
def __init__(self, input_size: int, action_shape: int, hidden_size: int=128):
"""Overview: initialize COMA critic network Arguments: - input_size (:obj:`int`): the size of input global observation -... | the_stack_v2_python_sparse | ding/model/template/coma.py | shengxuesun/DI-engine | train | 1 |
f0576a541c8b0f7223af88b7c2a251597800cec0 | [
"signed_up = self.calc_signup(events)\nconsented, cohort = self.calc_consent(events)\nehr_consented = self.calc_ehr_consent(events)\ngror_received = self.calc_gror_received(events)\nbiobank_samples = self.calc_biobank_samples(events)\nphysical_measurements = self.calc_physical_measurements(events)\nthebasics_module... | <|body_start_0|>
signed_up = self.calc_signup(events)
consented, cohort = self.calc_consent(events)
ehr_consented = self.calc_ehr_consent(events)
gror_received = self.calc_gror_received(events)
biobank_samples = self.calc_biobank_samples(events)
physical_measurements = se... | Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sharing stays "Yes" even if there is a negative EHR consent later. | EnrollmentStatusCalculator_v3_0 | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnrollmentStatusCalculator_v3_0:
"""Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sharing stays "Yes" even if there is a neg... | stack_v2_sparse_classes_10k_train_008396 | 6,672 | permissive | [
{
"docstring": "Use the events list to calculate the participant enrolment status and status timestamps. :param events: List of events to use in calculations",
"name": "calculate_from_events",
"signature": "def calculate_from_events(self, events)"
},
{
"docstring": "Save the status timestamp whe... | 4 | null | Implement the Python class `EnrollmentStatusCalculator_v3_0` described below.
Class description:
Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sha... | Implement the Python class `EnrollmentStatusCalculator_v3_0` described below.
Class description:
Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sha... | 461ae46aeda21d54de8a91aa5ef677676d5db541 | <|skeleton|>
class EnrollmentStatusCalculator_v3_0:
"""Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sharing stays "Yes" even if there is a neg... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EnrollmentStatusCalculator_v3_0:
"""Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sharing stays "Yes" even if there is a negative EHR con... | the_stack_v2_python_sparse | rdr_service/resource/calculators/participant_enrollment_status_v30.py | all-of-us/raw-data-repository | train | 46 |
74f152c6f1c0b1b497fec4f5b1185c1a4c3a4356 | [
"user = request.user\nif user:\n ser = self.serializer_class(user)\n return Response({'data': ser.data}, status=status.HTTP_200_OK)\nelse:\n return Response({'status': status.HTTP_404_NOT_FOUND, 'error': 'User not found'})",
"ser_params = self.serializer_class(data=request.data)\nser_params.is_valid(rais... | <|body_start_0|>
user = request.user
if user:
ser = self.serializer_class(user)
return Response({'data': ser.data}, status=status.HTTP_200_OK)
else:
return Response({'status': status.HTTP_404_NOT_FOUND, 'error': 'User not found'})
<|end_body_0|>
<|body_start_... | AuthViewSet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthViewSet:
def user(self, request):
"""User profile information"""
<|body_0|>
def register(self, request):
"""User registration"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = request.user
if user:
ser = self.serializer_... | stack_v2_sparse_classes_10k_train_008397 | 3,325 | permissive | [
{
"docstring": "User profile information",
"name": "user",
"signature": "def user(self, request)"
},
{
"docstring": "User registration",
"name": "register",
"signature": "def register(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000652 | Implement the Python class `AuthViewSet` described below.
Class description:
Implement the AuthViewSet class.
Method signatures and docstrings:
- def user(self, request): User profile information
- def register(self, request): User registration | Implement the Python class `AuthViewSet` described below.
Class description:
Implement the AuthViewSet class.
Method signatures and docstrings:
- def user(self, request): User profile information
- def register(self, request): User registration
<|skeleton|>
class AuthViewSet:
def user(self, request):
""... | 05daac6bc1504658909dc396e48cc8100ec1747c | <|skeleton|>
class AuthViewSet:
def user(self, request):
"""User profile information"""
<|body_0|>
def register(self, request):
"""User registration"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AuthViewSet:
def user(self, request):
"""User profile information"""
user = request.user
if user:
ser = self.serializer_class(user)
return Response({'data': ser.data}, status=status.HTTP_200_OK)
else:
return Response({'status': status.HTTP_40... | the_stack_v2_python_sparse | backend/authentication/views.py | vindem22/work-hour-registration | train | 0 | |
4d0c70af6593109ec214ddf4a46e2b3a38aae4fd | [
"n = len(nums)\nnums.sort()\nsubset = []\nfor i in range(2 ** n, 2 ** (n + 1)):\n bitmask = bin(i)[3:]\n sub = []\n for j in range(n):\n if bitmask[j] == '1':\n sub.append(nums[j])\n if sub not in subset:\n subset.append(sub)\nreturn subset",
"def back_track(nums, index, path,... | <|body_start_0|>
n = len(nums)
nums.sort()
subset = []
for i in range(2 ** n, 2 ** (n + 1)):
bitmask = bin(i)[3:]
sub = []
for j in range(n):
if bitmask[j] == '1':
sub.append(nums[j])
if sub not in subset... | Subset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Subset:
def get_all_via_bit_manipulation(self, nums: List[int]) -> List[List[int]]:
"""Approach: Lexicographic (Binary Sorted) subsets Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :param nums: :return:"""
<|body_0|>
def get_all(self, nums: List[int]) -> List[List... | stack_v2_sparse_classes_10k_train_008398 | 1,439 | no_license | [
{
"docstring": "Approach: Lexicographic (Binary Sorted) subsets Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :param nums: :return:",
"name": "get_all_via_bit_manipulation",
"signature": "def get_all_via_bit_manipulation(self, nums: List[int]) -> List[List[int]]"
},
{
"docstring": "Ap... | 2 | stack_v2_sparse_classes_30k_train_003534 | Implement the Python class `Subset` described below.
Class description:
Implement the Subset class.
Method signatures and docstrings:
- def get_all_via_bit_manipulation(self, nums: List[int]) -> List[List[int]]: Approach: Lexicographic (Binary Sorted) subsets Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :... | Implement the Python class `Subset` described below.
Class description:
Implement the Subset class.
Method signatures and docstrings:
- def get_all_via_bit_manipulation(self, nums: List[int]) -> List[List[int]]: Approach: Lexicographic (Binary Sorted) subsets Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Subset:
def get_all_via_bit_manipulation(self, nums: List[int]) -> List[List[int]]:
"""Approach: Lexicographic (Binary Sorted) subsets Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :param nums: :return:"""
<|body_0|>
def get_all(self, nums: List[int]) -> List[List... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Subset:
def get_all_via_bit_manipulation(self, nums: List[int]) -> List[List[int]]:
"""Approach: Lexicographic (Binary Sorted) subsets Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :param nums: :return:"""
n = len(nums)
nums.sort()
subset = []
for i in range(... | the_stack_v2_python_sparse | revisited/math_and_strings/recursion_memoization_dp/subset_ii.py | Shiv2157k/leet_code | train | 1 | |
90e8c7804115a43dcecf8095d145941766d59127 | [
"self.record_value = dict()\nself.max_length = capacity\nself.queue = collections.deque()",
"if key not in self.record_value:\n return -1\nif key in self.queue:\n self.queue.remove(key)\nself.queue.append(key)\nreturn self.record_value.get(key)",
"if key in self.record_value:\n self.record_value[key] =... | <|body_start_0|>
self.record_value = dict()
self.max_length = capacity
self.queue = collections.deque()
<|end_body_0|>
<|body_start_1|>
if key not in self.record_value:
return -1
if key in self.queue:
self.queue.remove(key)
self.queue.append(key)
... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
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_10k_train_008399 | 1,517 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | f43d70cac56bdf6377b22b865174af822902ff78 | <|skeleton|>
class LRUCache:
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_10k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.record_value = dict()
self.max_length = capacity
self.queue = collections.deque()
def get(self, key):
""":type key: int :rtype: int"""
if key not in self.record_value:
return... | the_stack_v2_python_sparse | 队列/LeetCode146_LRU缓存机制.py | ltzp/LeetCode | train | 0 |
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