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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ba47fee67b69812a638d8e87212c98725aaa657e | [
"cnt = collections.Counter(arr)\nif cnt[0] % 2 != 0:\n return False\nfor num in sorted(set(arr)):\n if cnt[num] <= 0:\n continue\n if num == 0:\n del cnt[num]\n elif num < 0:\n if num % 2 != 0 or cnt[num // 2] < cnt[num]:\n return False\n cnt[num // 2] -= cnt[num]\... | <|body_start_0|>
cnt = collections.Counter(arr)
if cnt[0] % 2 != 0:
return False
for num in sorted(set(arr)):
if cnt[num] <= 0:
continue
if num == 0:
del cnt[num]
elif num < 0:
if num % 2 != 0 or cnt[... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canReorderDoubled2(self, arr: List[int]) -> bool:
"""Update: 20220401 Runtime: 596 ms, faster than 97.28% Memory Usage: 16.6 MB, less than 62.22% :param arr: 2 <= arr.length <= 3 * 10^4 arr.length is even. -10^5 <= arr[i] <= 10^5 :return:"""
<|body_0|>
def canR... | stack_v2_sparse_classes_10k_train_001400 | 3,036 | permissive | [
{
"docstring": "Update: 20220401 Runtime: 596 ms, faster than 97.28% Memory Usage: 16.6 MB, less than 62.22% :param arr: 2 <= arr.length <= 3 * 10^4 arr.length is even. -10^5 <= arr[i] <= 10^5 :return:",
"name": "canReorderDoubled2",
"signature": "def canReorderDoubled2(self, arr: List[int]) -> bool"
... | 2 | stack_v2_sparse_classes_30k_train_003601 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canReorderDoubled2(self, arr: List[int]) -> bool: Update: 20220401 Runtime: 596 ms, faster than 97.28% Memory Usage: 16.6 MB, less than 62.22% :param arr: 2 <= arr.length <= ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canReorderDoubled2(self, arr: List[int]) -> bool: Update: 20220401 Runtime: 596 ms, faster than 97.28% Memory Usage: 16.6 MB, less than 62.22% :param arr: 2 <= arr.length <= ... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def canReorderDoubled2(self, arr: List[int]) -> bool:
"""Update: 20220401 Runtime: 596 ms, faster than 97.28% Memory Usage: 16.6 MB, less than 62.22% :param arr: 2 <= arr.length <= 3 * 10^4 arr.length is even. -10^5 <= arr[i] <= 10^5 :return:"""
<|body_0|>
def canR... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def canReorderDoubled2(self, arr: List[int]) -> bool:
"""Update: 20220401 Runtime: 596 ms, faster than 97.28% Memory Usage: 16.6 MB, less than 62.22% :param arr: 2 <= arr.length <= 3 * 10^4 arr.length is even. -10^5 <= arr[i] <= 10^5 :return:"""
cnt = collections.Counter(arr)
... | the_stack_v2_python_sparse | src/954-ArrayofDoubledPairs.py | Jiezhi/myleetcode | train | 1 | |
d1bd666538526a5164051b8e37846b8b62aadc79 | [
"if 'modifier' in kwargs:\n self.modifier = kwargs['modifier']\nelif len(args) > 2:\n self.modifier = args[2]\n args = args[:2]\nelse:\n self.modifier = lambda x: x\nif not callable(self.modifier):\n raise TypeError('modify_iter(o, modifier): modifier must be callable')\nsuper().__init__(*args)",
"... | <|body_start_0|>
if 'modifier' in kwargs:
self.modifier = kwargs['modifier']
elif len(args) > 2:
self.modifier = args[2]
args = args[:2]
else:
self.modifier = lambda x: x
if not callable(self.modifier):
raise TypeError('modify_i... | An iterator object that supports modifying items as they are returned. Parameters ---------- o : iterable or callable `o` is interpreted very differently depending on the presence of `sentinel`. If `sentinel` is not given, then `o` must be a collection object which supports either the iteration protocol or the sequence... | modify_iter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class modify_iter:
"""An iterator object that supports modifying items as they are returned. Parameters ---------- o : iterable or callable `o` is interpreted very differently depending on the presence of `sentinel`. If `sentinel` is not given, then `o` must be a collection object which supports either... | stack_v2_sparse_classes_10k_train_001401 | 22,562 | permissive | [
{
"docstring": "__init__(o, sentinel=None, modifier=lambda x: x)",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Cache `n` modified items. If `n` is 0 or None, 1 item is cached. Each item returned by the iterator is passed through the `modify_iter.modi... | 2 | stack_v2_sparse_classes_30k_train_006758 | Implement the Python class `modify_iter` described below.
Class description:
An iterator object that supports modifying items as they are returned. Parameters ---------- o : iterable or callable `o` is interpreted very differently depending on the presence of `sentinel`. If `sentinel` is not given, then `o` must be a ... | Implement the Python class `modify_iter` described below.
Class description:
An iterator object that supports modifying items as they are returned. Parameters ---------- o : iterable or callable `o` is interpreted very differently depending on the presence of `sentinel`. If `sentinel` is not given, then `o` must be a ... | 59e1ca2f4b15ca3d1bc814330ab8ef0beb8d9af0 | <|skeleton|>
class modify_iter:
"""An iterator object that supports modifying items as they are returned. Parameters ---------- o : iterable or callable `o` is interpreted very differently depending on the presence of `sentinel`. If `sentinel` is not given, then `o` must be a collection object which supports either... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class modify_iter:
"""An iterator object that supports modifying items as they are returned. Parameters ---------- o : iterable or callable `o` is interpreted very differently depending on the presence of `sentinel`. If `sentinel` is not given, then `o` must be a collection object which supports either the iteratio... | the_stack_v2_python_sparse | moldesign/utils/docparsers/google.py | maxbates/molecular-design-toolkit | train | 1 |
530891ce0e430c68f51c74ca3a736cbc18339c37 | [
"self.save_new_valid_exploration('Exp1', 'user@example.com', end_state_name='End')\ncollection = collection_domain.Collection.from_yaml('cid', self.YAML_CONTENT_V1)\nself.assertEqual(collection.to_yaml(), self._LATEST_YAML_CONTENT)",
"self.save_new_valid_exploration('Exp1', 'user@example.com', end_state_name='End... | <|body_start_0|>
self.save_new_valid_exploration('Exp1', 'user@example.com', end_state_name='End')
collection = collection_domain.Collection.from_yaml('cid', self.YAML_CONTENT_V1)
self.assertEqual(collection.to_yaml(), self._LATEST_YAML_CONTENT)
<|end_body_0|>
<|body_start_1|>
self.save... | Test migration methods for yaml content. | SchemaMigrationUnitTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SchemaMigrationUnitTests:
"""Test migration methods for yaml content."""
def test_load_from_v1(self) -> None:
"""Test direct loading from a v1 yaml file."""
<|body_0|>
def test_load_from_v2(self) -> None:
"""Test direct loading from a v2 yaml file."""
<|b... | stack_v2_sparse_classes_10k_train_001402 | 48,157 | permissive | [
{
"docstring": "Test direct loading from a v1 yaml file.",
"name": "test_load_from_v1",
"signature": "def test_load_from_v1(self) -> None"
},
{
"docstring": "Test direct loading from a v2 yaml file.",
"name": "test_load_from_v2",
"signature": "def test_load_from_v2(self) -> None"
},
... | 6 | stack_v2_sparse_classes_30k_train_001896 | Implement the Python class `SchemaMigrationUnitTests` described below.
Class description:
Test migration methods for yaml content.
Method signatures and docstrings:
- def test_load_from_v1(self) -> None: Test direct loading from a v1 yaml file.
- def test_load_from_v2(self) -> None: Test direct loading from a v2 yaml... | Implement the Python class `SchemaMigrationUnitTests` described below.
Class description:
Test migration methods for yaml content.
Method signatures and docstrings:
- def test_load_from_v1(self) -> None: Test direct loading from a v1 yaml file.
- def test_load_from_v2(self) -> None: Test direct loading from a v2 yaml... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class SchemaMigrationUnitTests:
"""Test migration methods for yaml content."""
def test_load_from_v1(self) -> None:
"""Test direct loading from a v1 yaml file."""
<|body_0|>
def test_load_from_v2(self) -> None:
"""Test direct loading from a v2 yaml file."""
<|b... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SchemaMigrationUnitTests:
"""Test migration methods for yaml content."""
def test_load_from_v1(self) -> None:
"""Test direct loading from a v1 yaml file."""
self.save_new_valid_exploration('Exp1', 'user@example.com', end_state_name='End')
collection = collection_domain.Collection.... | the_stack_v2_python_sparse | core/domain/collection_domain_test.py | oppia/oppia | train | 6,172 |
bf066cbc17a32102c3bb2eea848caf82c68e5a8b | [
"ans = defaultdict(list)\nfor string in strs:\n count = [0] * 26\n for char in string:\n count[ord(char) - ord('a')] += 1\n ans[tuple(count)].append(string)\nreturn ans.values()",
"ans = defaultdict(list)\nfor string in strs:\n ans[tuple(sorted(string))].append(string)\nreturn ans.values()"
] | <|body_start_0|>
ans = defaultdict(list)
for string in strs:
count = [0] * 26
for char in string:
count[ord(char) - ord('a')] += 1
ans[tuple(count)].append(string)
return ans.values()
<|end_body_0|>
<|body_start_1|>
ans = defaultdict(l... | Anagrams | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Anagrams:
def group(self, strs: List[str]) -> List[str]:
"""Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:"""
<|body_0|>
def group_(self, strs: List[str]) -> List[str]:
"""Approach: Categorize by sorted string Time ... | stack_v2_sparse_classes_10k_train_001403 | 1,103 | no_license | [
{
"docstring": "Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:",
"name": "group",
"signature": "def group(self, strs: List[str]) -> List[str]"
},
{
"docstring": "Approach: Categorize by sorted string Time Complexity: O(N log K) Space Complexity... | 2 | stack_v2_sparse_classes_30k_train_002208 | Implement the Python class `Anagrams` described below.
Class description:
Implement the Anagrams class.
Method signatures and docstrings:
- def group(self, strs: List[str]) -> List[str]: Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:
- def group_(self, strs: List[st... | Implement the Python class `Anagrams` described below.
Class description:
Implement the Anagrams class.
Method signatures and docstrings:
- def group(self, strs: List[str]) -> List[str]: Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:
- def group_(self, strs: List[st... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Anagrams:
def group(self, strs: List[str]) -> List[str]:
"""Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:"""
<|body_0|>
def group_(self, strs: List[str]) -> List[str]:
"""Approach: Categorize by sorted string Time ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Anagrams:
def group(self, strs: List[str]) -> List[str]:
"""Approach: Categorize by count Time Complexity: O(NK) Space Complexity: O(NK) :param strs: :return:"""
ans = defaultdict(list)
for string in strs:
count = [0] * 26
for char in string:
cou... | the_stack_v2_python_sparse | revisited_2021/math_and_string/group_anagrams.py | Shiv2157k/leet_code | train | 1 | |
2190faf1dba8c9a34582b93824a41e8f7d5c099b | [
"self.nodes = nodes\nself.dist = dist\nself.size = size\nself.blacklist = blacklist",
"for node in self.nodes:\n if self.blacklist and node.is_in(self.blacklist):\n continue\n yield node",
"candidates = deque()\nprev = None\nnode_count = 0\nfor node in self.filter_nodes():\n node_count += 1\n ... | <|body_start_0|>
self.nodes = nodes
self.dist = dist
self.size = size
self.blacklist = blacklist
<|end_body_0|>
<|body_start_1|>
for node in self.nodes:
if self.blacklist and node.is_in(self.blacklist):
continue
yield node
<|end_body_1|>
... | GenomeSLINK | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenomeSLINK:
def __init__(self, nodes, dist, size=1, blacklist=None):
"""Graph-based single-linkage clustering of genomic coordinates. Parameters ---------- nodes : iterable of GSNode GSNodes sorted by chrA, posA dist : int Maximum clustering distance. size : int Minimum cluster size. Re... | stack_v2_sparse_classes_10k_train_001404 | 8,944 | no_license | [
{
"docstring": "Graph-based single-linkage clustering of genomic coordinates. Parameters ---------- nodes : iterable of GSNode GSNodes sorted by chrA, posA dist : int Maximum clustering distance. size : int Minimum cluster size. Recommended to use 1 for call/variant clustering, scale up for read pair clustering... | 5 | stack_v2_sparse_classes_30k_train_004990 | Implement the Python class `GenomeSLINK` described below.
Class description:
Implement the GenomeSLINK class.
Method signatures and docstrings:
- def __init__(self, nodes, dist, size=1, blacklist=None): Graph-based single-linkage clustering of genomic coordinates. Parameters ---------- nodes : iterable of GSNode GSNo... | Implement the Python class `GenomeSLINK` described below.
Class description:
Implement the GenomeSLINK class.
Method signatures and docstrings:
- def __init__(self, nodes, dist, size=1, blacklist=None): Graph-based single-linkage clustering of genomic coordinates. Parameters ---------- nodes : iterable of GSNode GSNo... | 3214cac465ee46e531c3cf5d78258b7aba4319a4 | <|skeleton|>
class GenomeSLINK:
def __init__(self, nodes, dist, size=1, blacklist=None):
"""Graph-based single-linkage clustering of genomic coordinates. Parameters ---------- nodes : iterable of GSNode GSNodes sorted by chrA, posA dist : int Maximum clustering distance. size : int Minimum cluster size. Re... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GenomeSLINK:
def __init__(self, nodes, dist, size=1, blacklist=None):
"""Graph-based single-linkage clustering of genomic coordinates. Parameters ---------- nodes : iterable of GSNode GSNodes sorted by chrA, posA dist : int Maximum clustering distance. size : int Minimum cluster size. Recommended to u... | the_stack_v2_python_sparse | svtk/genomeslink.py | xuefzhao/svtk | train | 2 | |
3344af935d4a3683b121094c5159c21cbc1d51bb | [
"super().__init__()\nif json is None:\n json = {}\nself._manager: 'SideBarManager' = side_bar_manager\nself.align = json.get('align', alignment)\nself.minimum_access_level = json.get('minimumAccessLevel', minimum_access_level)\nself.maximum_access_level = json.get('maximumAccessLevel', maximum_access_level)\nsel... | <|body_start_0|>
super().__init__()
if json is None:
json = {}
self._manager: 'SideBarManager' = side_bar_manager
self.align = json.get('align', alignment)
self.minimum_access_level = json.get('minimumAccessLevel', minimum_access_level)
self.maximum_access_lev... | Side-bar card class. Every side-bar can have one or more cards and is maintained as an object of this class. :cvar allowed_attributes: allowed additional attributed provided as options alongside the specifically allowed ones. :cvar item_type: the item type of this class. Defaults to a BUTTON. | SideBarCard | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SideBarCard:
"""Side-bar card class. Every side-bar can have one or more cards and is maintained as an object of this class. :cvar allowed_attributes: allowed additional attributed provided as options alongside the specifically allowed ones. :cvar item_type: the item type of this class. Defaults ... | stack_v2_sparse_classes_10k_train_001405 | 6,308 | permissive | [
{
"docstring": "Create a side-bar card. :param side_bar_manager: Manager object to which the button is linked. :param json: the json response to construct the :class:`SideBarButton` from :param title: visible label of the button :param icon: FontAwesome icon of the button :param uri: Uniform Resource Identifier... | 2 | stack_v2_sparse_classes_30k_train_004604 | Implement the Python class `SideBarCard` described below.
Class description:
Side-bar card class. Every side-bar can have one or more cards and is maintained as an object of this class. :cvar allowed_attributes: allowed additional attributed provided as options alongside the specifically allowed ones. :cvar item_type:... | Implement the Python class `SideBarCard` described below.
Class description:
Side-bar card class. Every side-bar can have one or more cards and is maintained as an object of this class. :cvar allowed_attributes: allowed additional attributed provided as options alongside the specifically allowed ones. :cvar item_type:... | e8352e4d434bd5d0a5d76f7351f100d0b63f6fa8 | <|skeleton|>
class SideBarCard:
"""Side-bar card class. Every side-bar can have one or more cards and is maintained as an object of this class. :cvar allowed_attributes: allowed additional attributed provided as options alongside the specifically allowed ones. :cvar item_type: the item type of this class. Defaults ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SideBarCard:
"""Side-bar card class. Every side-bar can have one or more cards and is maintained as an object of this class. :cvar allowed_attributes: allowed additional attributed provided as options alongside the specifically allowed ones. :cvar item_type: the item type of this class. Defaults to a BUTTON."... | the_stack_v2_python_sparse | pykechain/models/sidebar/sidebar_card.py | KE-works/pykechain | train | 7 |
401ae408ef9ecfbd03b7d9820b54d215e86c10cc | [
"tokens = SocialToken.objects.filter(app__provider=Provider.github.name).select_related('account__user')\nfor token in tokens:\n user = token.account.user\n try:\n GithubRepo.refresh_for_user(user, token)\n except Exception:\n logger.warning('Exception while refreshing GitHub repos for user',... | <|body_start_0|>
tokens = SocialToken.objects.filter(app__provider=Provider.github.name).select_related('account__user')
for token in tokens:
user = token.account.user
try:
GithubRepo.refresh_for_user(user, token)
except Exception:
logg... | A GitHub repository that a user has access to. A list of GitHub repos is maintained for each user that has a linked GitHub account. This makes it much faster for users to be able to search through a list when adding a GitHub source to a project. | GithubRepo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GithubRepo:
"""A GitHub repository that a user has access to. A list of GitHub repos is maintained for each user that has a linked GitHub account. This makes it much faster for users to be able to search through a list when adding a GitHub source to a project."""
def refresh_for_all_users():... | stack_v2_sparse_classes_10k_train_001406 | 4,620 | permissive | [
{
"docstring": "Refresh the list of repos for all users with a GitHub token.",
"name": "refresh_for_all_users",
"signature": "def refresh_for_all_users()"
},
{
"docstring": "Refresh the list of repos for the user.",
"name": "refresh_for_user",
"signature": "def refresh_for_user(user: Use... | 2 | null | Implement the Python class `GithubRepo` described below.
Class description:
A GitHub repository that a user has access to. A list of GitHub repos is maintained for each user that has a linked GitHub account. This makes it much faster for users to be able to search through a list when adding a GitHub source to a projec... | Implement the Python class `GithubRepo` described below.
Class description:
A GitHub repository that a user has access to. A list of GitHub repos is maintained for each user that has a linked GitHub account. This makes it much faster for users to be able to search through a list when adding a GitHub source to a projec... | b0edf060f4cc5494eef81fce62a563bd5b4e8e31 | <|skeleton|>
class GithubRepo:
"""A GitHub repository that a user has access to. A list of GitHub repos is maintained for each user that has a linked GitHub account. This makes it much faster for users to be able to search through a list when adding a GitHub source to a project."""
def refresh_for_all_users():... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GithubRepo:
"""A GitHub repository that a user has access to. A list of GitHub repos is maintained for each user that has a linked GitHub account. This makes it much faster for users to be able to search through a list when adding a GitHub source to a project."""
def refresh_for_all_users():
"""R... | the_stack_v2_python_sparse | manager/projects/models/providers.py | stencila/hub | train | 31 |
3a9492317c2cbd0cda515731be12781491f48c79 | [
"self.device = device\nself.alpha = alpha\nself.model = model.to(self.device)\nself.params = {n: p for n, p in self.model.named_parameters() if p.requires_grad}\nself._means = {}\nself._precision_matrices = {}\nfor n, p in deepcopy(self.params).items():\n p.data.zero_()\n self._precision_matrices[n] = p.data.... | <|body_start_0|>
self.device = device
self.alpha = alpha
self.model = model.to(self.device)
self.params = {n: p for n, p in self.model.named_parameters() if p.requires_grad}
self._means = {}
self._precision_matrices = {}
for n, p in deepcopy(self.params).items():
... | MAS | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MAS:
def __init__(self, model: nn.Module, device='cuda:0', alpha=0.5, n_slices=50):
"""MAS is the class for implementing the Memory-Aware-Synapses * Aljundi, R., Babiloni, F., Elhoseiny, M., Rohrbach, M. and Tuytelaars, T., 2018. Memory aware synapses: Learning what (not) to forget. In P... | stack_v2_sparse_classes_10k_train_001407 | 3,545 | no_license | [
{
"docstring": "MAS is the class for implementing the Memory-Aware-Synapses * Aljundi, R., Babiloni, F., Elhoseiny, M., Rohrbach, M. and Tuytelaars, T., 2018. Memory aware synapses: Learning what (not) to forget. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 139-154). Inputs: model : ... | 3 | stack_v2_sparse_classes_30k_train_006540 | Implement the Python class `MAS` described below.
Class description:
Implement the MAS class.
Method signatures and docstrings:
- def __init__(self, model: nn.Module, device='cuda:0', alpha=0.5, n_slices=50): MAS is the class for implementing the Memory-Aware-Synapses * Aljundi, R., Babiloni, F., Elhoseiny, M., Rohrb... | Implement the Python class `MAS` described below.
Class description:
Implement the MAS class.
Method signatures and docstrings:
- def __init__(self, model: nn.Module, device='cuda:0', alpha=0.5, n_slices=50): MAS is the class for implementing the Memory-Aware-Synapses * Aljundi, R., Babiloni, F., Elhoseiny, M., Rohrb... | f1f9e9f4f85c7eb076e3c15e2390c9d612adabdf | <|skeleton|>
class MAS:
def __init__(self, model: nn.Module, device='cuda:0', alpha=0.5, n_slices=50):
"""MAS is the class for implementing the Memory-Aware-Synapses * Aljundi, R., Babiloni, F., Elhoseiny, M., Rohrbach, M. and Tuytelaars, T., 2018. Memory aware synapses: Learning what (not) to forget. In P... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MAS:
def __init__(self, model: nn.Module, device='cuda:0', alpha=0.5, n_slices=50):
"""MAS is the class for implementing the Memory-Aware-Synapses * Aljundi, R., Babiloni, F., Elhoseiny, M., Rohrbach, M. and Tuytelaars, T., 2018. Memory aware synapses: Learning what (not) to forget. In Proceedings of ... | the_stack_v2_python_sparse | utils/mas_utils/mas.py | lihr04/corel2m | train | 0 | |
c5993e3b091914994612ba76aee13b6bd3a73d8b | [
"self.assertIsNotNone(model_utils.get_weight_parameter(MaskConv2d(32, 32, 3)))\nweight_groups = model_utils.get_weight_parameter(GroupConv2d(32, 64, 3, groups=2))\nself.assertIsNotNone(weight_groups)\nself.assertIsInstance(weight_groups, torch.Tensor)\nself.assertEqual(weight_groups.shape[0], 64)\nself.assertEqual(... | <|body_start_0|>
self.assertIsNotNone(model_utils.get_weight_parameter(MaskConv2d(32, 32, 3)))
weight_groups = model_utils.get_weight_parameter(GroupConv2d(32, 64, 3, groups=2))
self.assertIsNotNone(weight_groups)
self.assertIsInstance(weight_groups, torch.Tensor)
self.assertEqua... | TestModelUtils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestModelUtils:
def test_get_weight_parameter(self):
"""Check whether parameters can be get from Module."""
<|body_0|>
def test_get_group_allocation(self):
"""Test GSP based group allocation."""
<|body_1|>
def test_is_gsp_satisfied(self):
"""Test... | stack_v2_sparse_classes_10k_train_001408 | 3,864 | permissive | [
{
"docstring": "Check whether parameters can be get from Module.",
"name": "test_get_weight_parameter",
"signature": "def test_get_weight_parameter(self)"
},
{
"docstring": "Test GSP based group allocation.",
"name": "test_get_group_allocation",
"signature": "def test_get_group_allocatio... | 5 | stack_v2_sparse_classes_30k_train_007261 | Implement the Python class `TestModelUtils` described below.
Class description:
Implement the TestModelUtils class.
Method signatures and docstrings:
- def test_get_weight_parameter(self): Check whether parameters can be get from Module.
- def test_get_group_allocation(self): Test GSP based group allocation.
- def te... | Implement the Python class `TestModelUtils` described below.
Class description:
Implement the TestModelUtils class.
Method signatures and docstrings:
- def test_get_weight_parameter(self): Check whether parameters can be get from Module.
- def test_get_group_allocation(self): Test GSP based group allocation.
- def te... | f81c417d3754102c902bd153809130e12607bd7d | <|skeleton|>
class TestModelUtils:
def test_get_weight_parameter(self):
"""Check whether parameters can be get from Module."""
<|body_0|>
def test_get_group_allocation(self):
"""Test GSP based group allocation."""
<|body_1|>
def test_is_gsp_satisfied(self):
"""Test... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestModelUtils:
def test_get_weight_parameter(self):
"""Check whether parameters can be get from Module."""
self.assertIsNotNone(model_utils.get_weight_parameter(MaskConv2d(32, 32, 3)))
weight_groups = model_utils.get_weight_parameter(GroupConv2d(32, 64, 3, groups=2))
self.asse... | the_stack_v2_python_sparse | gumi/model_utils_test.py | kumasento/gconv-prune | train | 10 | |
36689514b90c50c01e5ba943d41560a44b93c2d6 | [
"self.current = 0\nself.accumToIndex = {}\nself.accum = []\nfor i, num in enumerate(w):\n self.current += num\n self.accum.append(self.current)\n self.accumToIndex[self.current] = i",
"randomNum = random.randint(1, self.current)\nl, r = (0, len(self.accum) - 1)\nwhile l < r:\n m = (l + r) / 2\n if ... | <|body_start_0|>
self.current = 0
self.accumToIndex = {}
self.accum = []
for i, num in enumerate(w):
self.current += num
self.accum.append(self.current)
self.accumToIndex[self.current] = i
<|end_body_0|>
<|body_start_1|>
randomNum = random.ran... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.current = 0
self.accumToIndex = {}
self.accum = []
for i, num in en... | stack_v2_sparse_classes_10k_train_001409 | 1,254 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | 76d767ec001649b2df07aac211ac4b43b415ebdd | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.current = 0
self.accumToIndex = {}
self.accum = []
for i, num in enumerate(w):
self.current += num
self.accum.append(self.current)
self.accumToIndex[self.current] = i
... | the_stack_v2_python_sparse | leetcode528 Random Pick with Weight.py | whglamrock/leetcode_series | train | 2 | |
50d98101dde7ef8c3e746f6611041c3134fcc7d8 | [
"if isinstance(tag, six.integer_types):\n try:\n tag = Tag.objects.get(pk=tag, owner=self.owner)\n except Tag.DoesNotExist:\n return\nif isinstance(tag, six.string_types):\n tname = tag\n try:\n tag = Tag(owner=self.owner, name=tag)\n tag.save()\n except IntegrityError:\n ... | <|body_start_0|>
if isinstance(tag, six.integer_types):
try:
tag = Tag.objects.get(pk=tag, owner=self.owner)
except Tag.DoesNotExist:
return
if isinstance(tag, six.string_types):
tname = tag
try:
tag = Tag(ow... | Base class for taggable models; anything taggable must extend this | Taggable | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Taggable:
"""Base class for taggable models; anything taggable must extend this"""
def tag(self, tag):
"""Tags this object with a tag specified by a tag name, primary key or Tag model instance"""
<|body_0|>
def untag(self, tag):
"""Untags this object from a tag s... | stack_v2_sparse_classes_10k_train_001410 | 10,108 | permissive | [
{
"docstring": "Tags this object with a tag specified by a tag name, primary key or Tag model instance",
"name": "tag",
"signature": "def tag(self, tag)"
},
{
"docstring": "Untags this object from a tag specified by a tag name, primary key or Tag model instance",
"name": "untag",
"signat... | 3 | stack_v2_sparse_classes_30k_train_004224 | Implement the Python class `Taggable` described below.
Class description:
Base class for taggable models; anything taggable must extend this
Method signatures and docstrings:
- def tag(self, tag): Tags this object with a tag specified by a tag name, primary key or Tag model instance
- def untag(self, tag): Untags thi... | Implement the Python class `Taggable` described below.
Class description:
Base class for taggable models; anything taggable must extend this
Method signatures and docstrings:
- def tag(self, tag): Tags this object with a tag specified by a tag name, primary key or Tag model instance
- def untag(self, tag): Untags thi... | 5e102935cc6166f4d8ea13051769787c47303153 | <|skeleton|>
class Taggable:
"""Base class for taggable models; anything taggable must extend this"""
def tag(self, tag):
"""Tags this object with a tag specified by a tag name, primary key or Tag model instance"""
<|body_0|>
def untag(self, tag):
"""Untags this object from a tag s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Taggable:
"""Base class for taggable models; anything taggable must extend this"""
def tag(self, tag):
"""Tags this object with a tag specified by a tag name, primary key or Tag model instance"""
if isinstance(tag, six.integer_types):
try:
tag = Tag.objects.get... | the_stack_v2_python_sparse | tags/models.py | RossBrunton/BMAT | train | 0 |
dc3bc04babbd05cc7879e90a99281c58e54fba3d | [
"if id is None:\n Base.__nb_objects += 1\n self.id = Base.__nb_objects\nelif id <= 0:\n raise ValueError('id must be positive integer')\nelse:\n self.id = id\n Base.__nb_objects += 1",
"if list_dictionaries is None or list_dictionaries is []:\n return '[]'\nreturn json.dumps(list_dictionaries)",... | <|body_start_0|>
if id is None:
Base.__nb_objects += 1
self.id = Base.__nb_objects
elif id <= 0:
raise ValueError('id must be positive integer')
else:
self.id = id
Base.__nb_objects += 1
<|end_body_0|>
<|body_start_1|>
if list_... | This class will be the base of all other classes in project | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""This class will be the base of all other classes in project"""
def __init__(self, id=None):
"""Assign obj id"""
<|body_0|>
def to_json_string(list_dictionaries):
"""json string rep of for instances of dicts"""
<|body_1|>
def save_to_file(cls... | stack_v2_sparse_classes_10k_train_001411 | 2,141 | no_license | [
{
"docstring": "Assign obj id",
"name": "__init__",
"signature": "def __init__(self, id=None)"
},
{
"docstring": "json string rep of for instances of dicts",
"name": "to_json_string",
"signature": "def to_json_string(list_dictionaries)"
},
{
"docstring": "writes the JSON string r... | 6 | stack_v2_sparse_classes_30k_train_000267 | Implement the Python class `Base` described below.
Class description:
This class will be the base of all other classes in project
Method signatures and docstrings:
- def __init__(self, id=None): Assign obj id
- def to_json_string(list_dictionaries): json string rep of for instances of dicts
- def save_to_file(cls, li... | Implement the Python class `Base` described below.
Class description:
This class will be the base of all other classes in project
Method signatures and docstrings:
- def __init__(self, id=None): Assign obj id
- def to_json_string(list_dictionaries): json string rep of for instances of dicts
- def save_to_file(cls, li... | 75bedbbd249be2536da5a77f6337b14c8363f1b8 | <|skeleton|>
class Base:
"""This class will be the base of all other classes in project"""
def __init__(self, id=None):
"""Assign obj id"""
<|body_0|>
def to_json_string(list_dictionaries):
"""json string rep of for instances of dicts"""
<|body_1|>
def save_to_file(cls... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Base:
"""This class will be the base of all other classes in project"""
def __init__(self, id=None):
"""Assign obj id"""
if id is None:
Base.__nb_objects += 1
self.id = Base.__nb_objects
elif id <= 0:
raise ValueError('id must be positive intege... | the_stack_v2_python_sparse | 0x0C-python-almost_a_circle/models/base.py | Sainterman/holbertonschool-higher_level_programming | train | 0 |
5f3f187ddf31b186bbf5170a857490adf1d2370a | [
"bootstrap_exp_count = 1000\nresample_count = 1000\nbound_limits = list()\nfor N in xrange(2, self.N + 1):\n samples = self.sample_generator.generate_samples(N, self.T)\n for T in range(self.T):\n m_l, m_u = self.compute_boostrap_experiment(N, samples[:, T], resample_count, bootstrap_exp_count)\n ... | <|body_start_0|>
bootstrap_exp_count = 1000
resample_count = 1000
bound_limits = list()
for N in xrange(2, self.N + 1):
samples = self.sample_generator.generate_samples(N, self.T)
for T in range(self.T):
m_l, m_u = self.compute_boostrap_experiment(... | Class for Bootstrap Bounds The Confidence is set to 95* for this bound. Might mae it configurable in the future. | Bootstrap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bootstrap:
"""Class for Bootstrap Bounds The Confidence is set to 95* for this bound. Might mae it configurable in the future."""
def compute_mean(self):
"""Computes mean with the DELTA method of Bootstrapping. For Bootstrap T(Trails) is equivalent to number Bootstrap sampling experi... | stack_v2_sparse_classes_10k_train_001412 | 2,348 | no_license | [
{
"docstring": "Computes mean with the DELTA method of Bootstrapping. For Bootstrap T(Trails) is equivalent to number Bootstrap sampling experiment.",
"name": "compute_mean",
"signature": "def compute_mean(self)"
},
{
"docstring": "Performs one Bootstrap experiment. :param N: Number of samples, ... | 2 | stack_v2_sparse_classes_30k_train_006306 | Implement the Python class `Bootstrap` described below.
Class description:
Class for Bootstrap Bounds The Confidence is set to 95* for this bound. Might mae it configurable in the future.
Method signatures and docstrings:
- def compute_mean(self): Computes mean with the DELTA method of Bootstrapping. For Bootstrap T(... | Implement the Python class `Bootstrap` described below.
Class description:
Class for Bootstrap Bounds The Confidence is set to 95* for this bound. Might mae it configurable in the future.
Method signatures and docstrings:
- def compute_mean(self): Computes mean with the DELTA method of Bootstrapping. For Bootstrap T(... | 582db28c4f3251486f940f4054418cc7290f4d45 | <|skeleton|>
class Bootstrap:
"""Class for Bootstrap Bounds The Confidence is set to 95* for this bound. Might mae it configurable in the future."""
def compute_mean(self):
"""Computes mean with the DELTA method of Bootstrapping. For Bootstrap T(Trails) is equivalent to number Bootstrap sampling experi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Bootstrap:
"""Class for Bootstrap Bounds The Confidence is set to 95* for this bound. Might mae it configurable in the future."""
def compute_mean(self):
"""Computes mean with the DELTA method of Bootstrapping. For Bootstrap T(Trails) is equivalent to number Bootstrap sampling experiment."""
... | the_stack_v2_python_sparse | src/main/algorithm/bootstrap.py | abhinavshaw1993/SampleBounds | train | 4 |
6b39ff9c53a979931ce7bf0c667a608b44034da3 | [
"super(CnnFnn, self).__init__()\nself.num_var = num_var\nself.kernel_size = kernel_size\nself.stride = stride\nself.cnns = nn.ModuleList([nn.Sequential(nn.Conv3d(1, 1, (1, self.kernel_size, self.kernel_size), (1, self.stride, self.stride)), nn.ReLU(inplace=True)) for i in range(self.num_var)])\nself.input_dim = inp... | <|body_start_0|>
super(CnnFnn, self).__init__()
self.num_var = num_var
self.kernel_size = kernel_size
self.stride = stride
self.cnns = nn.ModuleList([nn.Sequential(nn.Conv3d(1, 1, (1, self.kernel_size, self.kernel_size), (1, self.stride, self.stride)), nn.ReLU(inplace=True)) for ... | Class for CNN model | CnnFnn | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CnnFnn:
"""Class for CNN model"""
def __init__(self, num_var, input_dim, output_dim, kernel_size=9, stride=5, hidden_dim=100, num_layers=2, num_epochs=100, learning_rate=0.001):
"""Initilize CNN model Args: num_var: int -- number of covariates as input, one CNN for each covariate inp... | stack_v2_sparse_classes_10k_train_001413 | 6,027 | no_license | [
{
"docstring": "Initilize CNN model Args: num_var: int -- number of covariates as input, one CNN for each covariate input_dim: int -- dimension of the input for fully connected layers after apply cnn output_dim: int -- dimension of the output feature kernel_size: int -- Size of the convolving kernel srtide: int... | 5 | stack_v2_sparse_classes_30k_train_003338 | Implement the Python class `CnnFnn` described below.
Class description:
Class for CNN model
Method signatures and docstrings:
- def __init__(self, num_var, input_dim, output_dim, kernel_size=9, stride=5, hidden_dim=100, num_layers=2, num_epochs=100, learning_rate=0.001): Initilize CNN model Args: num_var: int -- numb... | Implement the Python class `CnnFnn` described below.
Class description:
Class for CNN model
Method signatures and docstrings:
- def __init__(self, num_var, input_dim, output_dim, kernel_size=9, stride=5, hidden_dim=100, num_layers=2, num_epochs=100, learning_rate=0.001): Initilize CNN model Args: num_var: int -- numb... | d7e651024b07587b46497183d90934561a4839e2 | <|skeleton|>
class CnnFnn:
"""Class for CNN model"""
def __init__(self, num_var, input_dim, output_dim, kernel_size=9, stride=5, hidden_dim=100, num_layers=2, num_epochs=100, learning_rate=0.001):
"""Initilize CNN model Args: num_var: int -- number of covariates as input, one CNN for each covariate inp... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CnnFnn:
"""Class for CNN model"""
def __init__(self, num_var, input_dim, output_dim, kernel_size=9, stride=5, hidden_dim=100, num_layers=2, num_epochs=100, learning_rate=0.001):
"""Initilize CNN model Args: num_var: int -- number of covariates as input, one CNN for each covariate input_dim: int -... | the_stack_v2_python_sparse | model/cnn_fnn.py | SSF-climate/SSF | train | 7 |
d6dd6abb164353a62df9a490a4abc97dcd949888 | [
"pg = getToolByName(self, 'portal_groups')\ngroup = pg.getGroupById('Programacao')\nmembers = group.getGroupMembers()\nlist = DisplayList()\nfor member in members:\n memberId = member.getMemberId()\n fullname = member.getProperty('fullname', memberId)\n list.add(memberId, fullname)\nreturn list",
"list =... | <|body_start_0|>
pg = getToolByName(self, 'portal_groups')
group = pg.getGroupById('Programacao')
members = group.getGroupMembers()
list = DisplayList()
for member in members:
memberId = member.getMemberId()
fullname = member.getProperty('fullname', member... | '' | Chamada | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Chamada:
"""''"""
def getListaProgramacao(self):
"""Retorna a lista de usuários do grupo programacao"""
<|body_0|>
def getStatusOff(self):
"""Retorna a lista de status de Off"""
<|body_1|>
def getStatusCabeca(self):
"""Retorna a lista de stat... | stack_v2_sparse_classes_10k_train_001414 | 5,729 | permissive | [
{
"docstring": "Retorna a lista de usuários do grupo programacao",
"name": "getListaProgramacao",
"signature": "def getListaProgramacao(self)"
},
{
"docstring": "Retorna a lista de status de Off",
"name": "getStatusOff",
"signature": "def getStatusOff(self)"
},
{
"docstring": "Re... | 3 | stack_v2_sparse_classes_30k_train_001607 | Implement the Python class `Chamada` described below.
Class description:
''
Method signatures and docstrings:
- def getListaProgramacao(self): Retorna a lista de usuários do grupo programacao
- def getStatusOff(self): Retorna a lista de status de Off
- def getStatusCabeca(self): Retorna a lista de status de Cabecas | Implement the Python class `Chamada` described below.
Class description:
''
Method signatures and docstrings:
- def getListaProgramacao(self): Retorna a lista de usuários do grupo programacao
- def getStatusOff(self): Retorna a lista de status de Off
- def getStatusCabeca(self): Retorna a lista de status de Cabecas
... | 1a77e9f47e22b60af88cf23f492a8b47ddfd27b6 | <|skeleton|>
class Chamada:
"""''"""
def getListaProgramacao(self):
"""Retorna a lista de usuários do grupo programacao"""
<|body_0|>
def getStatusOff(self):
"""Retorna a lista de status de Off"""
<|body_1|>
def getStatusCabeca(self):
"""Retorna a lista de stat... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Chamada:
"""''"""
def getListaProgramacao(self):
"""Retorna a lista de usuários do grupo programacao"""
pg = getToolByName(self, 'portal_groups')
group = pg.getGroupById('Programacao')
members = group.getGroupMembers()
list = DisplayList()
for member in mem... | the_stack_v2_python_sparse | ebc/pauta/content/chamada.py | lflrocha/ebc.pauta | train | 0 |
cc7468515370e4a4845ed45bba1746e7a3b83941 | [
"super().__init__()\nsys.stdout.flush()\ntry:\n self.my_device = params['my_device']\nexcept:\n self.my_device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\nself.config = params\nif not self.config['include_metadata']:\n self.config['other_features_size'] = 0\nif params['activation'] ==... | <|body_start_0|>
super().__init__()
sys.stdout.flush()
try:
self.my_device = params['my_device']
except:
self.my_device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
self.config = params
if not self.config['include_metadata']:
... | myLSTMOutputHidden | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class myLSTMOutputHidden:
def __init__(self, params):
"""IGNORES THE INCLUDE METADATA PARAM TO FINETUNE Params are: dropout_layers: a list of dropout probabilities after each layer. Should be the same size as linear_layer_sizes. If zero or None, no dropout is applied. activation: "relu", "elu"... | stack_v2_sparse_classes_10k_train_001415 | 34,560 | no_license | [
{
"docstring": "IGNORES THE INCLUDE METADATA PARAM TO FINETUNE Params are: dropout_layers: a list of dropout probabilities after each layer. Should be the same size as linear_layer_sizes. If zero or None, no dropout is applied. activation: \"relu\", \"elu\", or \"selu\" to be applied to all dense activations vo... | 2 | stack_v2_sparse_classes_30k_train_003296 | Implement the Python class `myLSTMOutputHidden` described below.
Class description:
Implement the myLSTMOutputHidden class.
Method signatures and docstrings:
- def __init__(self, params): IGNORES THE INCLUDE METADATA PARAM TO FINETUNE Params are: dropout_layers: a list of dropout probabilities after each layer. Shoul... | Implement the Python class `myLSTMOutputHidden` described below.
Class description:
Implement the myLSTMOutputHidden class.
Method signatures and docstrings:
- def __init__(self, params): IGNORES THE INCLUDE METADATA PARAM TO FINETUNE Params are: dropout_layers: a list of dropout probabilities after each layer. Shoul... | b850f7c91e16e3dacca4d3b6377c77502960dd19 | <|skeleton|>
class myLSTMOutputHidden:
def __init__(self, params):
"""IGNORES THE INCLUDE METADATA PARAM TO FINETUNE Params are: dropout_layers: a list of dropout probabilities after each layer. Should be the same size as linear_layer_sizes. If zero or None, no dropout is applied. activation: "relu", "elu"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class myLSTMOutputHidden:
def __init__(self, params):
"""IGNORES THE INCLUDE METADATA PARAM TO FINETUNE Params are: dropout_layers: a list of dropout probabilities after each layer. Should be the same size as linear_layer_sizes. If zero or None, no dropout is applied. activation: "relu", "elu", or "selu" to... | the_stack_v2_python_sparse | common/mytorch.py | altLabs/attrib | train | 1 | |
2aee99df7590ac9a3497af616c93d882ecadc554 | [
"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!')"
] | <|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... | service | ImageServiceServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageServiceServicer:
"""service"""
def GetImageStream(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def GetShm(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|... | stack_v2_sparse_classes_10k_train_001416 | 10,385 | permissive | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "GetImageStream",
"signature": "def GetImageStream(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "GetShm",
"signature": "def GetShm(self, re... | 2 | stack_v2_sparse_classes_30k_train_006076 | Implement the Python class `ImageServiceServicer` described below.
Class description:
service
Method signatures and docstrings:
- def GetImageStream(self, request, context): Missing associated documentation comment in .proto file.
- def GetShm(self, request, context): Missing associated documentation comment in .prot... | Implement the Python class `ImageServiceServicer` described below.
Class description:
service
Method signatures and docstrings:
- def GetImageStream(self, request, context): Missing associated documentation comment in .proto file.
- def GetShm(self, request, context): Missing associated documentation comment in .prot... | a83a60c40eda7051a73363f67cb806ad73637e7a | <|skeleton|>
class ImageServiceServicer:
"""service"""
def GetImageStream(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def GetShm(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ImageServiceServicer:
"""service"""
def GetImageStream(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method n... | the_stack_v2_python_sparse | sap-toolkit/sap_toolkit/generated/eval_server_pb2_grpc.py | jelasus/sap-starterkit | train | 0 |
4d3c99df3922cb7b43e3519b589fbfc8b92bb5c7 | [
"if self.step_type not in _STEP_TYPES:\n raise TypeError(f'Invalid step type {self.step_type}')\nmp_func = _STEP_TYPES[self.step_type]\naccessor = mp_func\nparams = self.params\nfunc_text = f'.{mp_func}({self._get_param_string()})'\nif self.step_type == 'pivot':\n _, func = _get_entity_and_pivot(self.entity, ... | <|body_start_0|>
if self.step_type not in _STEP_TYPES:
raise TypeError(f'Invalid step type {self.step_type}')
mp_func = _STEP_TYPES[self.step_type]
accessor = mp_func
params = self.params
func_text = f'.{mp_func}({self._get_param_string()})'
if self.step_type ... | Pivot pipeline step class. | PipelineStep | [
"LicenseRef-scancode-generic-cla",
"LGPL-3.0-only",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown",
"ISC",
"LGPL-2.0-or-later",
"PSF-2.0",
"Apache-2.0",
"BSD-2-Clause",
"LGPL-2.1-only",
"Unlicense",
"Python-2.0",
"LicenseRef-scancode-python-cwi",
"MIT",
"LGPL-2.1-or-later",
"GPL-2.... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PipelineStep:
"""Pivot pipeline step class."""
def get_exec_step(self) -> PipelineExecStep:
"""Return the executable step details. Returns ------- PipelineExecStep Named tuple with the following fields accessor - the name of the pandas DataFrame accessor function params - parameters ... | stack_v2_sparse_classes_10k_train_001417 | 10,245 | permissive | [
{
"docstring": "Return the executable step details. Returns ------- PipelineExecStep Named tuple with the following fields accessor - the name of the pandas DataFrame accessor function params - parameters to be passed to the function text - the text representation of the accessor + params comment - optional com... | 2 | stack_v2_sparse_classes_30k_train_005308 | Implement the Python class `PipelineStep` described below.
Class description:
Pivot pipeline step class.
Method signatures and docstrings:
- def get_exec_step(self) -> PipelineExecStep: Return the executable step details. Returns ------- PipelineExecStep Named tuple with the following fields accessor - the name of th... | Implement the Python class `PipelineStep` described below.
Class description:
Pivot pipeline step class.
Method signatures and docstrings:
- def get_exec_step(self) -> PipelineExecStep: Return the executable step details. Returns ------- PipelineExecStep Named tuple with the following fields accessor - the name of th... | 44b1a390510f9be2772ec62cb95d0fc67dfc234b | <|skeleton|>
class PipelineStep:
"""Pivot pipeline step class."""
def get_exec_step(self) -> PipelineExecStep:
"""Return the executable step details. Returns ------- PipelineExecStep Named tuple with the following fields accessor - the name of the pandas DataFrame accessor function params - parameters ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PipelineStep:
"""Pivot pipeline step class."""
def get_exec_step(self) -> PipelineExecStep:
"""Return the executable step details. Returns ------- PipelineExecStep Named tuple with the following fields accessor - the name of the pandas DataFrame accessor function params - parameters to be passed ... | the_stack_v2_python_sparse | msticpy/datamodel/pivot_pipeline.py | RiskIQ/msticpy | train | 1 |
150526e2268e028666be9eed2338ff75ac2e6966 | [
"expected_obj = self.resize_prep_start_obj\nactual_json = json.dumps(self.base_resize_prep_dict)\nactual_obj = InstanceResizePrepStart.deserialize(actual_json, 'json')\nself.assertEqual(expected_obj, actual_obj)\nself.assertFalse(actual_obj.is_empty())",
"modified_dict = self.base_resize_prep_dict.copy()\nmodifie... | <|body_start_0|>
expected_obj = self.resize_prep_start_obj
actual_json = json.dumps(self.base_resize_prep_dict)
actual_obj = InstanceResizePrepStart.deserialize(actual_json, 'json')
self.assertEqual(expected_obj, actual_obj)
self.assertFalse(actual_obj.is_empty())
<|end_body_0|>
... | InstanceResizePrepStartTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanceResizePrepStartTest:
def test_instance_resize_prep_start_valid_json(self):
"""Verify that the valid event deserialized correctly"""
<|body_0|>
def test_instance_resize_prep_start_missing_attribute_json(self):
"""Verify event missing expected attribute does no... | stack_v2_sparse_classes_10k_train_001418 | 5,720 | permissive | [
{
"docstring": "Verify that the valid event deserialized correctly",
"name": "test_instance_resize_prep_start_valid_json",
"signature": "def test_instance_resize_prep_start_valid_json(self)"
},
{
"docstring": "Verify event missing expected attribute does not deserialize",
"name": "test_insta... | 3 | null | Implement the Python class `InstanceResizePrepStartTest` described below.
Class description:
Implement the InstanceResizePrepStartTest class.
Method signatures and docstrings:
- def test_instance_resize_prep_start_valid_json(self): Verify that the valid event deserialized correctly
- def test_instance_resize_prep_sta... | Implement the Python class `InstanceResizePrepStartTest` described below.
Class description:
Implement the InstanceResizePrepStartTest class.
Method signatures and docstrings:
- def test_instance_resize_prep_start_valid_json(self): Verify that the valid event deserialized correctly
- def test_instance_resize_prep_sta... | 7d49cf6bfd7e1a6e5b739e7de52f2e18e5ccf924 | <|skeleton|>
class InstanceResizePrepStartTest:
def test_instance_resize_prep_start_valid_json(self):
"""Verify that the valid event deserialized correctly"""
<|body_0|>
def test_instance_resize_prep_start_missing_attribute_json(self):
"""Verify event missing expected attribute does no... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InstanceResizePrepStartTest:
def test_instance_resize_prep_start_valid_json(self):
"""Verify that the valid event deserialized correctly"""
expected_obj = self.resize_prep_start_obj
actual_json = json.dumps(self.base_resize_prep_dict)
actual_obj = InstanceResizePrepStart.deseri... | the_stack_v2_python_sparse | metatests/events/models/compute/test_instance_resize_prep.py | kurhula/cloudcafe | train | 0 | |
a8f271199e7fcc4144c26d9aa4a616c2fb8803fe | [
"super(ValidateCommitForm, self).__init__(*args, **kwargs)\nself.repository = repository\nself.request = request",
"super(ValidateCommitForm, self).clean()\nvalidation_info = self.cleaned_data.get('validation_info')\nif validation_info:\n errors = []\n parent_id = self.cleaned_data.get('parent_id')\n com... | <|body_start_0|>
super(ValidateCommitForm, self).__init__(*args, **kwargs)
self.repository = repository
self.request = request
<|end_body_0|>
<|body_start_1|>
super(ValidateCommitForm, self).clean()
validation_info = self.cleaned_data.get('validation_info')
if validation... | A form for validating of DiffCommits. | ValidateCommitForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidateCommitForm:
"""A form for validating of DiffCommits."""
def __init__(self, repository, request=None, *args, **kwargs):
"""Initialize the form. Args: repository (reviewboard.scmtools.models.Repository): The repository against which the diff is being validated. request (django.... | stack_v2_sparse_classes_10k_train_001419 | 16,962 | permissive | [
{
"docstring": "Initialize the form. Args: repository (reviewboard.scmtools.models.Repository): The repository against which the diff is being validated. request (django.http.HttpRequest, optional): The HTTP request from the client. *args (tuple): Additional positional arguments to pass to the base class initia... | 3 | null | Implement the Python class `ValidateCommitForm` described below.
Class description:
A form for validating of DiffCommits.
Method signatures and docstrings:
- def __init__(self, repository, request=None, *args, **kwargs): Initialize the form. Args: repository (reviewboard.scmtools.models.Repository): The repository ag... | Implement the Python class `ValidateCommitForm` described below.
Class description:
A form for validating of DiffCommits.
Method signatures and docstrings:
- def __init__(self, repository, request=None, *args, **kwargs): Initialize the form. Args: repository (reviewboard.scmtools.models.Repository): The repository ag... | c3a991f1e9d7682239a1ab0e8661cee6da01d537 | <|skeleton|>
class ValidateCommitForm:
"""A form for validating of DiffCommits."""
def __init__(self, repository, request=None, *args, **kwargs):
"""Initialize the form. Args: repository (reviewboard.scmtools.models.Repository): The repository against which the diff is being validated. request (django.... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ValidateCommitForm:
"""A form for validating of DiffCommits."""
def __init__(self, repository, request=None, *args, **kwargs):
"""Initialize the form. Args: repository (reviewboard.scmtools.models.Repository): The repository against which the diff is being validated. request (django.http.HttpRequ... | the_stack_v2_python_sparse | reviewboard/diffviewer/forms.py | reviewboard/reviewboard | train | 1,141 |
03a92d81b28c99b16053ed2b71e9553298fb6e52 | [
"super().__init__(data, batch_size=batch_size, epochs=epochs, input_size=input_size, blacklist=blacklist)\nself.rnd_pool_ = []\nself.rnd = RandomState(seed=random_seed)",
"if not self.rnd_pool_:\n self.rnd_pool_ = self.rnd.randint(0, self.input_size - 1, self.batch_size * 10).tolist()\nreturn self.rnd_pool_.po... | <|body_start_0|>
super().__init__(data, batch_size=batch_size, epochs=epochs, input_size=input_size, blacklist=blacklist)
self.rnd_pool_ = []
self.rnd = RandomState(seed=random_seed)
<|end_body_0|>
<|body_start_1|>
if not self.rnd_pool_:
self.rnd_pool_ = self.rnd.randint(0, ... | Random sampling produces samples uniformly distributed from the input data. Individual samples are not guaranteed to be unique in the output, they can be repeated by the process of random sampling. The simplest usage of `RandomSampler` is no different than `OrderedSampler`: ```python sampler = RandomSampler(dataset) ba... | RandomSampler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomSampler:
"""Random sampling produces samples uniformly distributed from the input data. Individual samples are not guaranteed to be unique in the output, they can be repeated by the process of random sampling. The simplest usage of `RandomSampler` is no different than `OrderedSampler`: ```p... | stack_v2_sparse_classes_10k_train_001420 | 2,026 | permissive | [
{
"docstring": "Parameters ---------- data TODO batch_size : int TODO epochs : int TODO input_size : int TODO blacklist : set TODO random_seed : int TODO",
"name": "__init__",
"signature": "def __init__(self, data, batch_size: int=128, epochs: int=None, input_size: int=None, blacklist: set=None, random_... | 2 | stack_v2_sparse_classes_30k_train_006348 | Implement the Python class `RandomSampler` described below.
Class description:
Random sampling produces samples uniformly distributed from the input data. Individual samples are not guaranteed to be unique in the output, they can be repeated by the process of random sampling. The simplest usage of `RandomSampler` is n... | Implement the Python class `RandomSampler` described below.
Class description:
Random sampling produces samples uniformly distributed from the input data. Individual samples are not guaranteed to be unique in the output, they can be repeated by the process of random sampling. The simplest usage of `RandomSampler` is n... | 4d37af1713b7f166ead3459a7004748f954d336e | <|skeleton|>
class RandomSampler:
"""Random sampling produces samples uniformly distributed from the input data. Individual samples are not guaranteed to be unique in the output, they can be repeated by the process of random sampling. The simplest usage of `RandomSampler` is no different than `OrderedSampler`: ```p... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RandomSampler:
"""Random sampling produces samples uniformly distributed from the input data. Individual samples are not guaranteed to be unique in the output, they can be repeated by the process of random sampling. The simplest usage of `RandomSampler` is no different than `OrderedSampler`: ```python sampler... | the_stack_v2_python_sparse | bananas/sampling/random.py | owahltinez/bananas | train | 0 |
7b77dfe44cf236d66bcdfdb131c39d1d53c4a811 | [
"opens = '([{'\ncloses = ')]}'\nparstack = Stack()\nbalance = True\nfor each in s:\n if each in '([{':\n parstack.push(each)\n elif parstack.isEmpty():\n balance = False\n else:\n top = parstack.pop()\n if opens.index(top) != closes.index(each):\n balance = False\nif ... | <|body_start_0|>
opens = '([{'
closes = ')]}'
parstack = Stack()
balance = True
for each in s:
if each in '([{':
parstack.push(each)
elif parstack.isEmpty():
balance = False
else:
top = parstack.p... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValid_stack(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isValid(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
opens = '([{'
closes = ')]}'
parstack = Stack()
... | stack_v2_sparse_classes_10k_train_001421 | 1,433 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "isValid_stack",
"signature": "def isValid_stack(self, s)"
},
{
"docstring": ":type s: str :rtype: bool",
"name": "isValid",
"signature": "def isValid(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValid_stack(self, s): :type s: str :rtype: bool
- def isValid(self, s): :type s: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValid_stack(self, s): :type s: str :rtype: bool
- def isValid(self, s): :type s: str :rtype: bool
<|skeleton|>
class Solution:
def isValid_stack(self, s):
"""... | 85f71621c54f6b0029f3a2746f022f89dd7419d9 | <|skeleton|>
class Solution:
def isValid_stack(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isValid(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isValid_stack(self, s):
""":type s: str :rtype: bool"""
opens = '([{'
closes = ')]}'
parstack = Stack()
balance = True
for each in s:
if each in '([{':
parstack.push(each)
elif parstack.isEmpty():
... | the_stack_v2_python_sparse | LeetCode/String/20_Stack_valid_parentheses.py | XyK0907/for_work | train | 0 | |
cc19112ee95a9d2bf915268c7a0c35acca1869c1 | [
"roman = {'M': 1000, 'D': 500, 'C': 100, 'L': 50, 'X': 10, 'V': 5, 'I': 1}\nz = 0\nfor i in range(0, len(s) - 1):\n if roman[s[i]] < roman[s[i + 1]]:\n z -= roman[s[i]]\n else:\n z += roman[s[i]]\nreturn z + roman[s[-1]]",
"from __builtin__ import xrange\nroman = {'M': 1000, 'D': 500, 'C': 100... | <|body_start_0|>
roman = {'M': 1000, 'D': 500, 'C': 100, 'L': 50, 'X': 10, 'V': 5, 'I': 1}
z = 0
for i in range(0, len(s) - 1):
if roman[s[i]] < roman[s[i + 1]]:
z -= roman[s[i]]
else:
z += roman[s[i]]
return z + roman[s[-1]]
<|end_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def romanToInt(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def rewrite(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
roman = {'M': 1000, 'D': 500, 'C': 100, 'L': 50, 'X': 10, 'V': 5, 'I': 1}
... | stack_v2_sparse_classes_10k_train_001422 | 1,507 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "romanToInt",
"signature": "def romanToInt(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "rewrite",
"signature": "def rewrite(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005474 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def romanToInt(self, s): :type s: str :rtype: int
- def rewrite(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def romanToInt(self, s): :type s: str :rtype: int
- def rewrite(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def romanToInt(self, s):
""":type s:... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def romanToInt(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def rewrite(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def romanToInt(self, s):
""":type s: str :rtype: int"""
roman = {'M': 1000, 'D': 500, 'C': 100, 'L': 50, 'X': 10, 'V': 5, 'I': 1}
z = 0
for i in range(0, len(s) - 1):
if roman[s[i]] < roman[s[i + 1]]:
z -= roman[s[i]]
else:
... | the_stack_v2_python_sparse | co_ms/13_Roman_to_Integer.py | vsdrun/lc_public | train | 6 | |
03afe29e16b9302b0d6cc6f65ff195993467f874 | [
"n = len(nums)\ndp = [1] * n\nfor i in range(n):\n for j in range(i):\n if nums[i] > nums[j]:\n dp[i] = max(dp[i], dp[j] + 1)\n if dp[i] == 3:\n return True\nreturn False",
"smallest = second_smallest = float('inf')\nfor num in nums:\n if num < smallest:\n ... | <|body_start_0|>
n = len(nums)
dp = [1] * n
for i in range(n):
for j in range(i):
if nums[i] > nums[j]:
dp[i] = max(dp[i], dp[j] + 1)
if dp[i] == 3:
return True
return False
<|end_body_0|>
<|body... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def increasingTriplet(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def increasingTriplet(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
dp = [1] ... | stack_v2_sparse_classes_10k_train_001423 | 873 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "increasingTriplet",
"signature": "def increasingTriplet(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "increasingTriplet",
"signature": "def increasingTriplet(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def increasingTriplet(self, nums): :type nums: List[int] :rtype: bool
- def increasingTriplet(self, nums): :type nums: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def increasingTriplet(self, nums): :type nums: List[int] :rtype: bool
- def increasingTriplet(self, nums): :type nums: List[int] :rtype: bool
<|skeleton|>
class Solution:
d... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def increasingTriplet(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def increasingTriplet(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def increasingTriplet(self, nums):
""":type nums: List[int] :rtype: bool"""
n = len(nums)
dp = [1] * n
for i in range(n):
for j in range(i):
if nums[i] > nums[j]:
dp[i] = max(dp[i], dp[j] + 1)
if dp[i... | the_stack_v2_python_sparse | 0334_Increasing_Triplet_Subsequence.py | bingli8802/leetcode | train | 0 | |
84ca6ffd7994517b9735b1b6b3844aa37c67c2c6 | [
"l, r = (0, len(nums) - 1)\nwhile l <= r:\n m = (l + r) // 2\n if nums[m] < target:\n l = m + 1\n else:\n r = m - 1\nif l == len(nums) or nums[l] != target:\n return [-1, -1]\nretl = l\nl, r = (0, len(nums) - 1)\nwhile l <= r:\n m = (l + r) // 2\n if nums[m] <= target:\n l = m... | <|body_start_0|>
l, r = (0, len(nums) - 1)
while l <= r:
m = (l + r) // 2
if nums[m] < target:
l = m + 1
else:
r = m - 1
if l == len(nums) or nums[l] != target:
return [-1, -1]
retl = l
l, r = (0, len... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchRange_lowerandupperboundbinarysearch(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def searchRange_myself(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
... | stack_v2_sparse_classes_10k_train_001424 | 1,649 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "searchRange_lowerandupperboundbinarysearch",
"signature": "def searchRange_lowerandupperboundbinarysearch(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"... | 2 | stack_v2_sparse_classes_30k_train_004792 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchRange_lowerandupperboundbinarysearch(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def searchRange_myself(self, nums, target): :type ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchRange_lowerandupperboundbinarysearch(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def searchRange_myself(self, nums, target): :type ... | a7916e0818b0853ec75e24724bde94c49234c7dc | <|skeleton|>
class Solution:
def searchRange_lowerandupperboundbinarysearch(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def searchRange_myself(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def searchRange_lowerandupperboundbinarysearch(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
l, r = (0, len(nums) - 1)
while l <= r:
m = (l + r) // 2
if nums[m] < target:
l = m + 1
else... | the_stack_v2_python_sparse | 34.py | KevinWangTHU/LeetCode | train | 0 | |
600b474162e535fa590fe388601d73e476261085 | [
"super().__init__()\nself.n_patches = int(np.prod([i / patch_size for i in img_size]))\nself.pos_embed = nn.Parameter(torch.zeros(1, self.n_patches, embed_size))\nself.patch_embed = Conv(in_channels=in_feats, out_channels=embed_size, kernel_size=patch_size, stride=patch_size)",
"x = self.patch_embed(x)\nx = x.fla... | <|body_start_0|>
super().__init__()
self.n_patches = int(np.prod([i / patch_size for i in img_size]))
self.pos_embed = nn.Parameter(torch.zeros(1, self.n_patches, embed_size))
self.patch_embed = Conv(in_channels=in_feats, out_channels=embed_size, kernel_size=patch_size, stride=patch_size... | _Embedding | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Embedding:
def __init__(self, img_size, patch_size, in_feats, embed_size, Conv):
"""A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the input image tensor (H, W, C). patch_size (int): The size of each square patch that the image is divided... | stack_v2_sparse_classes_10k_train_001425 | 24,719 | permissive | [
{
"docstring": "A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the input image tensor (H, W, C). patch_size (int): The size of each square patch that the image is divided into. in_feats (int): The number of input channels in the image tensor. embed_size (int): Th... | 2 | stack_v2_sparse_classes_30k_train_003224 | Implement the Python class `_Embedding` described below.
Class description:
Implement the _Embedding class.
Method signatures and docstrings:
- def __init__(self, img_size, patch_size, in_feats, embed_size, Conv): A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the inpu... | Implement the Python class `_Embedding` described below.
Class description:
Implement the _Embedding class.
Method signatures and docstrings:
- def __init__(self, img_size, patch_size, in_feats, embed_size, Conv): A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the inpu... | 72eb99f68205afd5f8d49a3bb6cfc08cfd467582 | <|skeleton|>
class _Embedding:
def __init__(self, img_size, patch_size, in_feats, embed_size, Conv):
"""A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the input image tensor (H, W, C). patch_size (int): The size of each square patch that the image is divided... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _Embedding:
def __init__(self, img_size, patch_size, in_feats, embed_size, Conv):
"""A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the input image tensor (H, W, C). patch_size (int): The size of each square patch that the image is divided into. in_feat... | the_stack_v2_python_sparse | GANDLF/models/unetr.py | mlcommons/GaNDLF | train | 45 | |
2c9ef78662ec0b05a092d3da18ec6ae627a784da | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn IPv6Range()",
"from .ip_range import IpRange\nfrom .ip_range import IpRange\nfields: Dict[str, Callable[[Any], None]] = {'lowerAddress': lambda n: setattr(self, 'lower_address', n.get_str_value()), 'upperAddress': lambda n: setattr(sel... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return IPv6Range()
<|end_body_0|>
<|body_start_1|>
from .ip_range import IpRange
from .ip_range import IpRange
fields: Dict[str, Callable[[Any], None]] = {'lowerAddress': lambda n: seta... | IPv6 Range definition. | IPv6Range | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IPv6Range:
"""IPv6 Range definition."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IPv6Range:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and ... | stack_v2_sparse_classes_10k_train_001426 | 2,237 | 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: IPv6Range",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(par... | 3 | null | Implement the Python class `IPv6Range` described below.
Class description:
IPv6 Range definition.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IPv6Range: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: T... | Implement the Python class `IPv6Range` described below.
Class description:
IPv6 Range definition.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IPv6Range: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: T... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class IPv6Range:
"""IPv6 Range definition."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IPv6Range:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IPv6Range:
"""IPv6 Range definition."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IPv6Range:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ob... | the_stack_v2_python_sparse | msgraph/generated/models/i_pv6_range.py | microsoftgraph/msgraph-sdk-python | train | 135 |
360344bffecce399a668c5a77d9d76a15d9dd637 | [
"super().__init__(syncthru, name)\nself._name = f'{name} Tray {number}'\nself._number = number\nself._id_suffix = f'_tray_{number}'",
"if self.syncthru.is_online():\n self._attributes = self.syncthru.input_tray_status().get(self._number, {})\n self._state = self._attributes.get('newError')\n if self._sta... | <|body_start_0|>
super().__init__(syncthru, name)
self._name = f'{name} Tray {number}'
self._number = number
self._id_suffix = f'_tray_{number}'
<|end_body_0|>
<|body_start_1|>
if self.syncthru.is_online():
self._attributes = self.syncthru.input_tray_status().get(sel... | Implementation of a Samsung Printer input tray sensor platform. | SyncThruInputTraySensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SyncThruInputTraySensor:
"""Implementation of a Samsung Printer input tray sensor platform."""
def __init__(self, syncthru, name, number):
"""Initialize the sensor."""
<|body_0|>
def update(self):
"""Get the latest data from SyncThru and update the state."""
... | stack_v2_sparse_classes_10k_train_001427 | 8,262 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, syncthru, name, number)"
},
{
"docstring": "Get the latest data from SyncThru and update the state.",
"name": "update",
"signature": "def update(self)"
}
] | 2 | null | Implement the Python class `SyncThruInputTraySensor` described below.
Class description:
Implementation of a Samsung Printer input tray sensor platform.
Method signatures and docstrings:
- def __init__(self, syncthru, name, number): Initialize the sensor.
- def update(self): Get the latest data from SyncThru and upda... | Implement the Python class `SyncThruInputTraySensor` described below.
Class description:
Implementation of a Samsung Printer input tray sensor platform.
Method signatures and docstrings:
- def __init__(self, syncthru, name, number): Initialize the sensor.
- def update(self): Get the latest data from SyncThru and upda... | ed4ab403deaed9e8c95e0db728477fcb012bf4fa | <|skeleton|>
class SyncThruInputTraySensor:
"""Implementation of a Samsung Printer input tray sensor platform."""
def __init__(self, syncthru, name, number):
"""Initialize the sensor."""
<|body_0|>
def update(self):
"""Get the latest data from SyncThru and update the state."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SyncThruInputTraySensor:
"""Implementation of a Samsung Printer input tray sensor platform."""
def __init__(self, syncthru, name, number):
"""Initialize the sensor."""
super().__init__(syncthru, name)
self._name = f'{name} Tray {number}'
self._number = number
self.... | the_stack_v2_python_sparse | homeassistant/components/syncthru/sensor.py | tchellomello/home-assistant | train | 8 |
32782efa9947842511be3bc886cf221e7372ca55 | [
"json_dict = json.loads(request.body.decode())\nsku_id = json_dict.get('sku_id')\ntry:\n SKU.objects.get(id=sku_id)\nexcept SKU.DoesNotExist:\n return http.HttpResponseForbidden('sku不存在')\nredis_conn = get_redis_connection('history')\npl = redis_conn.pipeline()\nuser_id = request.user.id\npl.lrem('history_{}'... | <|body_start_0|>
json_dict = json.loads(request.body.decode())
sku_id = json_dict.get('sku_id')
try:
SKU.objects.get(id=sku_id)
except SKU.DoesNotExist:
return http.HttpResponseForbidden('sku不存在')
redis_conn = get_redis_connection('history')
pl = r... | 用户浏览记录 | UserBrowseHistory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserBrowseHistory:
"""用户浏览记录"""
def post(self, request):
"""保存用户浏览记录"""
<|body_0|>
def get(self, request):
"""获取用户浏览记录"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
json_dict = json.loads(request.body.decode())
sku_id = json_dict.get('... | stack_v2_sparse_classes_10k_train_001428 | 26,474 | no_license | [
{
"docstring": "保存用户浏览记录",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "获取用户浏览记录",
"name": "get",
"signature": "def get(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002743 | Implement the Python class `UserBrowseHistory` described below.
Class description:
用户浏览记录
Method signatures and docstrings:
- def post(self, request): 保存用户浏览记录
- def get(self, request): 获取用户浏览记录 | Implement the Python class `UserBrowseHistory` described below.
Class description:
用户浏览记录
Method signatures and docstrings:
- def post(self, request): 保存用户浏览记录
- def get(self, request): 获取用户浏览记录
<|skeleton|>
class UserBrowseHistory:
"""用户浏览记录"""
def post(self, request):
"""保存用户浏览记录"""
<|body... | e3976cbb9e96a1558f4e00abed1c61d887f915b1 | <|skeleton|>
class UserBrowseHistory:
"""用户浏览记录"""
def post(self, request):
"""保存用户浏览记录"""
<|body_0|>
def get(self, request):
"""获取用户浏览记录"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserBrowseHistory:
"""用户浏览记录"""
def post(self, request):
"""保存用户浏览记录"""
json_dict = json.loads(request.body.decode())
sku_id = json_dict.get('sku_id')
try:
SKU.objects.get(id=sku_id)
except SKU.DoesNotExist:
return http.HttpResponseForbidden... | the_stack_v2_python_sparse | meiduo_mall/meiduo_mall/apps/users/views.py | yi0506/meiduo | train | 0 |
4df5eb94212597bef293f643dc197a4fe86c3856 | [
"if name == 'quiet':\n return self.level >= VERB_QUIET\nelif name == 'low':\n return self.level >= VERB_LOW\nelif name == 'medium':\n return self.level >= VERB_MEDIUM\nelif name == 'high':\n return self.level >= VERB_HIGH\nelif name == 'debug':\n return self.level >= VERB_DEBUG\nelif name == 'trace':... | <|body_start_0|>
if name == 'quiet':
return self.level >= VERB_QUIET
elif name == 'low':
return self.level >= VERB_LOW
elif name == 'medium':
return self.level >= VERB_MEDIUM
elif name == 'high':
return self.level >= VERB_HIGH
elif ... | Class used to determine what to print to standard output. Attributes: level: Determines what level of output to print. | Verbosity | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Verbosity:
"""Class used to determine what to print to standard output. Attributes: level: Determines what level of output to print."""
def __getattr__(self, name):
"""Determines whether a certain verbosity level is less than or greater than the stored value. Used to decide whether o... | stack_v2_sparse_classes_10k_train_001429 | 4,128 | no_license | [
{
"docstring": "Determines whether a certain verbosity level is less than or greater than the stored value. Used to decide whether or not a certain info or warning string should be output. Args: name: The verbosity level at which the info/warning string will be output.",
"name": "__getattr__",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_000776 | Implement the Python class `Verbosity` described below.
Class description:
Class used to determine what to print to standard output. Attributes: level: Determines what level of output to print.
Method signatures and docstrings:
- def __getattr__(self, name): Determines whether a certain verbosity level is less than o... | Implement the Python class `Verbosity` described below.
Class description:
Class used to determine what to print to standard output. Attributes: level: Determines what level of output to print.
Method signatures and docstrings:
- def __getattr__(self, name): Determines whether a certain verbosity level is less than o... | 57f255266d4668bafef0881d1e7cbf8a27270ddd | <|skeleton|>
class Verbosity:
"""Class used to determine what to print to standard output. Attributes: level: Determines what level of output to print."""
def __getattr__(self, name):
"""Determines whether a certain verbosity level is less than or greater than the stored value. Used to decide whether o... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Verbosity:
"""Class used to determine what to print to standard output. Attributes: level: Determines what level of output to print."""
def __getattr__(self, name):
"""Determines whether a certain verbosity level is less than or greater than the stored value. Used to decide whether or not a certa... | the_stack_v2_python_sparse | ipi/utils/messages.py | i-pi/i-pi | train | 170 |
d1e9dbd1e6b4fbba3f1b7dd198695b9e7c2537e0 | [
"number_validation_result = super().validate(value)\nif not number_validation_result.is_valid:\n return number_validation_result\nis_integer = float(value).is_integer()\nif not is_integer:\n return ValidationResult.failure([Integer.NotAnInteger(self, value)])\nreturn self.success()",
"if isinstance(failure,... | <|body_start_0|>
number_validation_result = super().validate(value)
if not number_validation_result.is_valid:
return number_validation_result
is_integer = float(value).is_integer()
if not is_integer:
return ValidationResult.failure([Integer.NotAnInteger(self, valu... | Validator which ensures the value is an integer which falls within a range. | Integer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Integer:
"""Validator which ensures the value is an integer which falls within a range."""
def validate(self, value: str) -> ValidationResult:
"""Ensure that `value` is an integer, optionally within a range. Args: value: The value to validate. Returns: The result of the validation.""... | stack_v2_sparse_classes_10k_train_001430 | 18,238 | permissive | [
{
"docstring": "Ensure that `value` is an integer, optionally within a range. Args: value: The value to validate. Returns: The result of the validation.",
"name": "validate",
"signature": "def validate(self, value: str) -> ValidationResult"
},
{
"docstring": "Describes why the validator failed. ... | 2 | stack_v2_sparse_classes_30k_test_000256 | Implement the Python class `Integer` described below.
Class description:
Validator which ensures the value is an integer which falls within a range.
Method signatures and docstrings:
- def validate(self, value: str) -> ValidationResult: Ensure that `value` is an integer, optionally within a range. Args: value: The va... | Implement the Python class `Integer` described below.
Class description:
Validator which ensures the value is an integer which falls within a range.
Method signatures and docstrings:
- def validate(self, value: str) -> ValidationResult: Ensure that `value` is an integer, optionally within a range. Args: value: The va... | b74ac1e47fdd16133ca567390c99ea19de278c5a | <|skeleton|>
class Integer:
"""Validator which ensures the value is an integer which falls within a range."""
def validate(self, value: str) -> ValidationResult:
"""Ensure that `value` is an integer, optionally within a range. Args: value: The value to validate. Returns: The result of the validation.""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Integer:
"""Validator which ensures the value is an integer which falls within a range."""
def validate(self, value: str) -> ValidationResult:
"""Ensure that `value` is an integer, optionally within a range. Args: value: The value to validate. Returns: The result of the validation."""
num... | the_stack_v2_python_sparse | src/textual/validation.py | Textualize/textual | train | 14,818 |
bf41c967b967706fb6036d15e571318c69bd34ae | [
"if 'QI' not in params:\n params['QI'] = 'IE'\nif 'QE' not in params:\n params['QE'] = 'EE'\nsuper(verlet, self).__init__(params)\n[self.QT, self.Qx, self.QQ] = self.__get_Qd()\nself.qQ = np.dot(self.coll.weights, self.coll.Qmat[1:, 1:])",
"QI = self.get_Qdelta_implicit(self.coll, self.params.QI)\nQE = self... | <|body_start_0|>
if 'QI' not in params:
params['QI'] = 'IE'
if 'QE' not in params:
params['QE'] = 'EE'
super(verlet, self).__init__(params)
[self.QT, self.Qx, self.QQ] = self.__get_Qd()
self.qQ = np.dot(self.coll.weights, self.coll.Qmat[1:, 1:])
<|end_body... | Custom sweeper class, implements Sweeper.py Second-order sweeper using velocity-Verlet as base integrator Attributes: QQ: 0-to-node collocation matrix (second order) QT: 0-to-node trapezoidal matrix Qx: 0-to-node Euler half-step for position update qQ: update rule for final value (if needed) | verlet | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class verlet:
"""Custom sweeper class, implements Sweeper.py Second-order sweeper using velocity-Verlet as base integrator Attributes: QQ: 0-to-node collocation matrix (second order) QT: 0-to-node trapezoidal matrix Qx: 0-to-node Euler half-step for position update qQ: update rule for final value (if n... | stack_v2_sparse_classes_10k_train_001431 | 7,247 | permissive | [
{
"docstring": "Initialization routine for the custom sweeper Args: params: parameters for the sweeper",
"name": "__init__",
"signature": "def __init__(self, params)"
},
{
"docstring": "Get integration matrices for 2nd-order SDC Returns: S: node-to-node collocation matrix (first order) SQ: node-... | 5 | null | Implement the Python class `verlet` described below.
Class description:
Custom sweeper class, implements Sweeper.py Second-order sweeper using velocity-Verlet as base integrator Attributes: QQ: 0-to-node collocation matrix (second order) QT: 0-to-node trapezoidal matrix Qx: 0-to-node Euler half-step for position updat... | Implement the Python class `verlet` described below.
Class description:
Custom sweeper class, implements Sweeper.py Second-order sweeper using velocity-Verlet as base integrator Attributes: QQ: 0-to-node collocation matrix (second order) QT: 0-to-node trapezoidal matrix Qx: 0-to-node Euler half-step for position updat... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class verlet:
"""Custom sweeper class, implements Sweeper.py Second-order sweeper using velocity-Verlet as base integrator Attributes: QQ: 0-to-node collocation matrix (second order) QT: 0-to-node trapezoidal matrix Qx: 0-to-node Euler half-step for position update qQ: update rule for final value (if n... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class verlet:
"""Custom sweeper class, implements Sweeper.py Second-order sweeper using velocity-Verlet as base integrator Attributes: QQ: 0-to-node collocation matrix (second order) QT: 0-to-node trapezoidal matrix Qx: 0-to-node Euler half-step for position update qQ: update rule for final value (if needed)"""
... | the_stack_v2_python_sparse | pySDC/implementations/sweeper_classes/verlet.py | Parallel-in-Time/pySDC | train | 30 |
20b41ef161ada47f25a02d82a5561b3fc3044a74 | [
"self.filepath = filepath\nxls_file = pd.ExcelFile(filepath)\nself.book = xls_file",
"sheet = self.book.parse('Final QC Results', skiprows=1, index_col=[0, 1])\nnew_column_names = ['VerifyBam_Omni_Free', 'VerifyBam_Affy_Free', 'VerifyBam_Omni_Chip', 'VerifyBam_Affy_Chip', 'Indel_Ratio', 'Passed_QC']\ndf = ''\nif ... | <|body_start_0|>
self.filepath = filepath
xls_file = pd.ExcelFile(filepath)
self.book = xls_file
<|end_body_0|>
<|body_start_1|>
sheet = self.book.parse('Final QC Results', skiprows=1, index_col=[0, 1])
new_column_names = ['VerifyBam_Omni_Free', 'VerifyBam_Affy_Free', 'VerifyBam... | Class representing a spreadsheet located at ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/working/20130606_sample_info/20130606_sample_info.xlsx containing information on the BAM QC done for the p3 | p3BAMQC | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class p3BAMQC:
"""Class representing a spreadsheet located at ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/working/20130606_sample_info/20130606_sample_info.xlsx containing information on the BAM QC done for the p3"""
def __init__(self, filepath):
"""Constructor Class variables -----... | stack_v2_sparse_classes_10k_train_001432 | 1,566 | permissive | [
{
"docstring": "Constructor Class variables --------------- filepath: str Path to the spreadsheet book: ExcelFile object",
"name": "__init__",
"signature": "def __init__(self, filepath)"
},
{
"docstring": "Method to get the sheet corresponding to 'Final QC Results' Parameters ---------- group: s... | 2 | stack_v2_sparse_classes_30k_train_002672 | Implement the Python class `p3BAMQC` described below.
Class description:
Class representing a spreadsheet located at ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/working/20130606_sample_info/20130606_sample_info.xlsx containing information on the BAM QC done for the p3
Method signatures and docstrings:
- def __... | Implement the Python class `p3BAMQC` described below.
Class description:
Class representing a spreadsheet located at ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/working/20130606_sample_info/20130606_sample_info.xlsx containing information on the BAM QC done for the p3
Method signatures and docstrings:
- def __... | 3926e2713fd5bce8fe7de71a30a1c067b6d7cb0b | <|skeleton|>
class p3BAMQC:
"""Class representing a spreadsheet located at ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/working/20130606_sample_info/20130606_sample_info.xlsx containing information on the BAM QC done for the p3"""
def __init__(self, filepath):
"""Constructor Class variables -----... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class p3BAMQC:
"""Class representing a spreadsheet located at ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/working/20130606_sample_info/20130606_sample_info.xlsx containing information on the BAM QC done for the p3"""
def __init__(self, filepath):
"""Constructor Class variables --------------- fi... | the_stack_v2_python_sparse | build/lib/p3/p3BAMQC.py | vj573/igsr_analysis | train | 0 |
70269cadb84db8f8ef8a2abeb63c03ad728f0d79 | [
"parser.add_argument('--variantset-id', type=str, required=True, help='The ID of the destination variant set.')\nparser.add_argument('--source-uris', type=arg_parsers.ArgList(min_length=1), required=True, help='A comma-delimited list of URI patterns referencing existing VCF or MasterVar files in Google Cloud Storag... | <|body_start_0|>
parser.add_argument('--variantset-id', type=str, required=True, help='The ID of the destination variant set.')
parser.add_argument('--source-uris', type=arg_parsers.ArgList(min_length=1), required=True, help='A comma-delimited list of URI patterns referencing existing VCF or MasterVar f... | Imports variants into Google Genomics. Import variants from VCF or MasterVar files that are in Google Cloud Storage. | Import | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Import:
"""Imports variants into Google Genomics. Import variants from VCF or MasterVar files that are in Google Cloud Storage."""
def Args(parser):
"""Register flags for this command."""
<|body_0|>
def Run(self, args):
"""This is what gets called when the user r... | stack_v2_sparse_classes_10k_train_001433 | 5,489 | permissive | [
{
"docstring": "Register flags for this command.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "This is what gets called when the user runs this command. Args: args: an argparse namespace, All the arguments that were provided to this command invocation. Returns: an ImportVa... | 2 | stack_v2_sparse_classes_30k_train_006933 | Implement the Python class `Import` described below.
Class description:
Imports variants into Google Genomics. Import variants from VCF or MasterVar files that are in Google Cloud Storage.
Method signatures and docstrings:
- def Args(parser): Register flags for this command.
- def Run(self, args): This is what gets c... | Implement the Python class `Import` described below.
Class description:
Imports variants into Google Genomics. Import variants from VCF or MasterVar files that are in Google Cloud Storage.
Method signatures and docstrings:
- def Args(parser): Register flags for this command.
- def Run(self, args): This is what gets c... | c98b58aeb0994e011df960163541e9379ae7ea06 | <|skeleton|>
class Import:
"""Imports variants into Google Genomics. Import variants from VCF or MasterVar files that are in Google Cloud Storage."""
def Args(parser):
"""Register flags for this command."""
<|body_0|>
def Run(self, args):
"""This is what gets called when the user r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Import:
"""Imports variants into Google Genomics. Import variants from VCF or MasterVar files that are in Google Cloud Storage."""
def Args(parser):
"""Register flags for this command."""
parser.add_argument('--variantset-id', type=str, required=True, help='The ID of the destination varia... | the_stack_v2_python_sparse | google-cloud-sdk/.install/.backup/lib/surface/genomics/variants/import.py | KaranToor/MA450 | train | 1 |
e186e7e45f3df5b77b37ab2b274296cc904ad2af | [
"if not arr1 or not arr2 or (not arr3):\n return []\narr1 = set(arr1)\narr2 = set(arr2)\narr3 = set(arr3)\narr1 = arr1.intersection(arr2)\narr1 = arr1.intersection(arr3)\nreturn sorted(list(arr1))",
"res = []\napperance = {}\nfor i in arr1:\n if i in apperance.keys():\n continue\n else:\n a... | <|body_start_0|>
if not arr1 or not arr2 or (not arr3):
return []
arr1 = set(arr1)
arr2 = set(arr2)
arr3 = set(arr3)
arr1 = arr1.intersection(arr2)
arr1 = arr1.intersection(arr3)
return sorted(list(arr1))
<|end_body_0|>
<|body_start_1|>
res = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def arraysIntersection(self, arr1, arr2, arr3):
"""思路一：利用集合的交操作 因为set无序，所以顺序会变，需要最后排个序 利用内置数据结构，时间空间都消耗极低，战胜100% :param arr1: :param arr2: :param arr3: :return:"""
<|body_0|>
def arraysIntersection1(self, arr1, arr2, arr3):
"""思路二：统计各个数字在三个列表中出现的次数，次数为3的为相交... | stack_v2_sparse_classes_10k_train_001434 | 1,888 | no_license | [
{
"docstring": "思路一：利用集合的交操作 因为set无序，所以顺序会变，需要最后排个序 利用内置数据结构，时间空间都消耗极低，战胜100% :param arr1: :param arr2: :param arr3: :return:",
"name": "arraysIntersection",
"signature": "def arraysIntersection(self, arr1, arr2, arr3)"
},
{
"docstring": "思路二：统计各个数字在三个列表中出现的次数，次数为3的为相交的数字",
"name": "arraysIn... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def arraysIntersection(self, arr1, arr2, arr3): 思路一：利用集合的交操作 因为set无序，所以顺序会变，需要最后排个序 利用内置数据结构，时间空间都消耗极低，战胜100% :param arr1: :param arr2: :param arr3: :return:
- def arraysIntersec... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def arraysIntersection(self, arr1, arr2, arr3): 思路一：利用集合的交操作 因为set无序，所以顺序会变，需要最后排个序 利用内置数据结构，时间空间都消耗极低，战胜100% :param arr1: :param arr2: :param arr3: :return:
- def arraysIntersec... | 95dddb78bccd169d9d219a473627361fe739ab5e | <|skeleton|>
class Solution:
def arraysIntersection(self, arr1, arr2, arr3):
"""思路一：利用集合的交操作 因为set无序，所以顺序会变，需要最后排个序 利用内置数据结构，时间空间都消耗极低，战胜100% :param arr1: :param arr2: :param arr3: :return:"""
<|body_0|>
def arraysIntersection1(self, arr1, arr2, arr3):
"""思路二：统计各个数字在三个列表中出现的次数，次数为3的为相交... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def arraysIntersection(self, arr1, arr2, arr3):
"""思路一：利用集合的交操作 因为set无序，所以顺序会变，需要最后排个序 利用内置数据结构，时间空间都消耗极低，战胜100% :param arr1: :param arr2: :param arr3: :return:"""
if not arr1 or not arr2 or (not arr3):
return []
arr1 = set(arr1)
arr2 = set(arr2)
a... | the_stack_v2_python_sparse | ArrayOperation/arraysIntersection.py | Philex5/codingPractice | train | 0 | |
d14182bd98980cea1160d087347ce243390bc388 | [
"response = self.client.get(reverse('cocktail_list'))\nself.assertEqual(response.status_code, 200)\nself.assertContains(response, 'There are no cocktails in the database.')\nself.assertQuerysetEqual(response.context['cocktail_list'], [])",
"add_cocktail('test', 1)\nadd_cocktail('temp', 1)\nadd_cocktail('tmp', 1)\... | <|body_start_0|>
response = self.client.get(reverse('cocktail_list'))
self.assertEqual(response.status_code, 200)
self.assertContains(response, 'There are no cocktails in the database.')
self.assertQuerysetEqual(response.context['cocktail_list'], [])
<|end_body_0|>
<|body_start_1|>
... | ListViewTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListViewTests:
def test_list_view_with_no_cocktails(self):
"""If no cocktails exist, an appropriate message should be displayed."""
<|body_0|>
def test_index_view_with_categories(self):
"""If some cocktails are created, they should be displayed"""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_001435 | 1,595 | no_license | [
{
"docstring": "If no cocktails exist, an appropriate message should be displayed.",
"name": "test_list_view_with_no_cocktails",
"signature": "def test_list_view_with_no_cocktails(self)"
},
{
"docstring": "If some cocktails are created, they should be displayed",
"name": "test_index_view_wit... | 2 | stack_v2_sparse_classes_30k_train_005754 | Implement the Python class `ListViewTests` described below.
Class description:
Implement the ListViewTests class.
Method signatures and docstrings:
- def test_list_view_with_no_cocktails(self): If no cocktails exist, an appropriate message should be displayed.
- def test_index_view_with_categories(self): If some cock... | Implement the Python class `ListViewTests` described below.
Class description:
Implement the ListViewTests class.
Method signatures and docstrings:
- def test_list_view_with_no_cocktails(self): If no cocktails exist, an appropriate message should be displayed.
- def test_index_view_with_categories(self): If some cock... | 18abb27ffd9824b9673be6aef0fa4d0a20c78fb4 | <|skeleton|>
class ListViewTests:
def test_list_view_with_no_cocktails(self):
"""If no cocktails exist, an appropriate message should be displayed."""
<|body_0|>
def test_index_view_with_categories(self):
"""If some cocktails are created, they should be displayed"""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ListViewTests:
def test_list_view_with_no_cocktails(self):
"""If no cocktails exist, an appropriate message should be displayed."""
response = self.client.get(reverse('cocktail_list'))
self.assertEqual(response.status_code, 200)
self.assertContains(response, 'There are no cockt... | the_stack_v2_python_sparse | apps/cocktails/tests.py | Carlosedo/mixees | train | 1 | |
34b946d9f4373fa25d7394b081ddaee87c81c99c | [
"expanded_groups = []\nfor group in match_object.groups():\n try:\n place_holder_number = int(group, 10) - 1\n expanded_group = '{{{0:d}:s}}'.format(place_holder_number)\n except ValueError:\n expanded_group = group\n expanded_groups.append(expanded_group)\nreturn ''.join(expanded_grou... | <|body_start_0|>
expanded_groups = []
for group in match_object.groups():
try:
place_holder_number = int(group, 10) - 1
expanded_group = '{{{0:d}:s}}'.format(place_holder_number)
except ValueError:
expanded_group = group
... | Windows PE/COFF resource file helper. | WindowsResourceFileHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WindowsResourceFileHelper:
"""Windows PE/COFF resource file helper."""
def _MessageStringPlaceHolderSpecifierReplacer(cls, match_object):
"""Replaces message string place holders into Python format() style. Args: match_object (re.Match): regular expression match object. Returns: str:... | stack_v2_sparse_classes_10k_train_001436 | 2,148 | permissive | [
{
"docstring": "Replaces message string place holders into Python format() style. Args: match_object (re.Match): regular expression match object. Returns: str: message string with Python format() style place holders.",
"name": "_MessageStringPlaceHolderSpecifierReplacer",
"signature": "def _MessageStrin... | 2 | null | Implement the Python class `WindowsResourceFileHelper` described below.
Class description:
Windows PE/COFF resource file helper.
Method signatures and docstrings:
- def _MessageStringPlaceHolderSpecifierReplacer(cls, match_object): Replaces message string place holders into Python format() style. Args: match_object (... | Implement the Python class `WindowsResourceFileHelper` described below.
Class description:
Windows PE/COFF resource file helper.
Method signatures and docstrings:
- def _MessageStringPlaceHolderSpecifierReplacer(cls, match_object): Replaces message string place holders into Python format() style. Args: match_object (... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class WindowsResourceFileHelper:
"""Windows PE/COFF resource file helper."""
def _MessageStringPlaceHolderSpecifierReplacer(cls, match_object):
"""Replaces message string place holders into Python format() style. Args: match_object (re.Match): regular expression match object. Returns: str:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WindowsResourceFileHelper:
"""Windows PE/COFF resource file helper."""
def _MessageStringPlaceHolderSpecifierReplacer(cls, match_object):
"""Replaces message string place holders into Python format() style. Args: match_object (re.Match): regular expression match object. Returns: str: message stri... | the_stack_v2_python_sparse | plaso/helpers/windows/resource_files.py | log2timeline/plaso | train | 1,506 |
66c1032ec50d8353cc3b2814d70f4a22a4a40a28 | [
"super(Cd, self).__init__(connection=connection, prompt=prompt, newline_chars=newline_chars, runner=runner)\nself.path = path\nself.ret_required = False\nself._re_expected_prompt = None\nif expected_prompt:\n self._re_expected_prompt = CommandTextualGeneric._calculate_prompt(expected_prompt)",
"cmd = 'cd'\nif ... | <|body_start_0|>
super(Cd, self).__init__(connection=connection, prompt=prompt, newline_chars=newline_chars, runner=runner)
self.path = path
self.ret_required = False
self._re_expected_prompt = None
if expected_prompt:
self._re_expected_prompt = CommandTextualGeneric.... | Cd | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cd:
def __init__(self, connection, path=None, prompt=None, newline_chars=None, runner=None, expected_prompt=None):
""":param connection: moler connection to device :param prompt: start prompt (on system where command cd starts) :param path: path to directory :param expected_prompt: Promp... | stack_v2_sparse_classes_10k_train_001437 | 3,352 | permissive | [
{
"docstring": ":param connection: moler connection to device :param prompt: start prompt (on system where command cd starts) :param path: path to directory :param expected_prompt: Prompt after change directory :param newline_chars: Characters to split lines :param runner: Runner to run command",
"name": "_... | 4 | null | Implement the Python class `Cd` described below.
Class description:
Implement the Cd class.
Method signatures and docstrings:
- def __init__(self, connection, path=None, prompt=None, newline_chars=None, runner=None, expected_prompt=None): :param connection: moler connection to device :param prompt: start prompt (on s... | Implement the Python class `Cd` described below.
Class description:
Implement the Cd class.
Method signatures and docstrings:
- def __init__(self, connection, path=None, prompt=None, newline_chars=None, runner=None, expected_prompt=None): :param connection: moler connection to device :param prompt: start prompt (on s... | 5a7bb06807b6e0124c77040367d0c20f42849a4c | <|skeleton|>
class Cd:
def __init__(self, connection, path=None, prompt=None, newline_chars=None, runner=None, expected_prompt=None):
""":param connection: moler connection to device :param prompt: start prompt (on system where command cd starts) :param path: path to directory :param expected_prompt: Promp... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Cd:
def __init__(self, connection, path=None, prompt=None, newline_chars=None, runner=None, expected_prompt=None):
""":param connection: moler connection to device :param prompt: start prompt (on system where command cd starts) :param path: path to directory :param expected_prompt: Prompt after change... | the_stack_v2_python_sparse | moler/cmd/unix/cd.py | nokia/moler | train | 60 | |
7f2afa923309d8e0e28db397392ca0a3239cdf3b | [
"if p.val < root.val and q.val < root.val:\n return self.lowestCommonAncestor(root.left, p, q)\nif p.val > root.val and q.val > root.val:\n return self.lowestCommonAncestor(root.right, p, q)\nreturn root",
"if max(p.val, q.val) < root.val:\n return self.lowestCommonAncestor(root.left, p, q)\nif root.val ... | <|body_start_0|>
if p.val < root.val and q.val < root.val:
return self.lowestCommonAncestor(root.left, p, q)
if p.val > root.val and q.val > root.val:
return self.lowestCommonAncestor(root.right, p, q)
return root
<|end_body_0|>
<|body_start_1|>
if max(p.val, q.v... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""08/16/2021 00:06"""
<|body_0|>
def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""08/21/2022 15:00"""
<|bo... | stack_v2_sparse_classes_10k_train_001438 | 2,517 | no_license | [
{
"docstring": "08/16/2021 00:06",
"name": "lowestCommonAncestor",
"signature": "def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode'"
},
{
"docstring": "08/21/2022 15:00",
"name": "lowestCommonAncestor",
"signature": "def lowestCommonAncestor(self... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode': 08/16/2021 00:06
- def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode': 08/16/2021 00:06
- def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""08/16/2021 00:06"""
<|body_0|>
def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""08/21/2022 15:00"""
<|bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""08/16/2021 00:06"""
if p.val < root.val and q.val < root.val:
return self.lowestCommonAncestor(root.left, p, q)
if p.val > root.val and q.val > root.val:
r... | the_stack_v2_python_sparse | leetcode/solved/235_Lowest_Common_Ancestor_of_a_Binary_Search_Tree/solution.py | sungminoh/algorithms | train | 0 | |
184a439cb9211ffe1c6a0a9cbd78e290bb067ddb | [
"self.defaultElementWidth, self.defaultElementHeight = (50, 50)\nself.defaultLabelWidth, self.defaultLabelHeight = (30, 10)\nself.context = context\nself.context.new_path()",
"if alpha is None:\n context.set_source_rgb(float(r) / 255.0, float(g) / 255.0, float(b) / 255.0)\nelse:\n context.set_source_rgba(fl... | <|body_start_0|>
self.defaultElementWidth, self.defaultElementHeight = (50, 50)
self.defaultLabelWidth, self.defaultLabelHeight = (30, 10)
self.context = context
self.context.new_path()
<|end_body_0|>
<|body_start_1|>
if alpha is None:
context.set_source_rgb(float(r)... | Base class for drawing objects | CBaseDrawing | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CBaseDrawing:
"""Base class for drawing objects"""
def __init__(self, context):
"""Constructor @type context: CairoContext @param context: cairo context, will be painted on this context"""
<|body_0|>
def ChangeColor(self, context, r, g, b, alpha=None):
"""Change ... | stack_v2_sparse_classes_10k_train_001439 | 1,264 | no_license | [
{
"docstring": "Constructor @type context: CairoContext @param context: cairo context, will be painted on this context",
"name": "__init__",
"signature": "def __init__(self, context)"
},
{
"docstring": "Change color on given context @type context: CairoContext @param context: cairo context on wh... | 2 | stack_v2_sparse_classes_30k_train_002378 | Implement the Python class `CBaseDrawing` described below.
Class description:
Base class for drawing objects
Method signatures and docstrings:
- def __init__(self, context): Constructor @type context: CairoContext @param context: cairo context, will be painted on this context
- def ChangeColor(self, context, r, g, b,... | Implement the Python class `CBaseDrawing` described below.
Class description:
Base class for drawing objects
Method signatures and docstrings:
- def __init__(self, context): Constructor @type context: CairoContext @param context: cairo context, will be painted on this context
- def ChangeColor(self, context, r, g, b,... | eb050a93ef955b8fbc184a437cb0e6fae54264cd | <|skeleton|>
class CBaseDrawing:
"""Base class for drawing objects"""
def __init__(self, context):
"""Constructor @type context: CairoContext @param context: cairo context, will be painted on this context"""
<|body_0|>
def ChangeColor(self, context, r, g, b, alpha=None):
"""Change ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CBaseDrawing:
"""Base class for drawing objects"""
def __init__(self, context):
"""Constructor @type context: CairoContext @param context: cairo context, will be painted on this context"""
self.defaultElementWidth, self.defaultElementHeight = (50, 50)
self.defaultLabelWidth, self.... | the_stack_v2_python_sparse | plugin/gui/BaseDrawing.py | umlfri-old/addon_team | train | 0 |
6d50eec95ab9d007acff606ca3fb77acac5ec6bf | [
"if self._errors:\n return\nuser = authenticate(username=self.cleaned_data['username'].lower(), password=self.cleaned_data['password'])\nif user:\n if user.is_active:\n self.user = user\n else:\n raise forms.ValidationError('This account is currently inactive.')\nelse:\n raise forms.Valida... | <|body_start_0|>
if self._errors:
return
user = authenticate(username=self.cleaned_data['username'].lower(), password=self.cleaned_data['password'])
if user:
if user.is_active:
self.user = user
else:
raise forms.ValidationError(... | Django-backed login form for normal authentication. | LoginForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginForm:
"""Django-backed login form for normal authentication."""
def clean(self):
"""Validates the login form."""
<|body_0|>
def login(self, request):
"""Logs the user in."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if self._errors:
... | stack_v2_sparse_classes_10k_train_001440 | 1,209 | permissive | [
{
"docstring": "Validates the login form.",
"name": "clean",
"signature": "def clean(self)"
},
{
"docstring": "Logs the user in.",
"name": "login",
"signature": "def login(self, request)"
}
] | 2 | null | Implement the Python class `LoginForm` described below.
Class description:
Django-backed login form for normal authentication.
Method signatures and docstrings:
- def clean(self): Validates the login form.
- def login(self, request): Logs the user in. | Implement the Python class `LoginForm` described below.
Class description:
Django-backed login form for normal authentication.
Method signatures and docstrings:
- def clean(self): Validates the login form.
- def login(self, request): Logs the user in.
<|skeleton|>
class LoginForm:
"""Django-backed login form for... | 4b7dd685012ec64758affe0ecee3103596d16aa7 | <|skeleton|>
class LoginForm:
"""Django-backed login form for normal authentication."""
def clean(self):
"""Validates the login form."""
<|body_0|>
def login(self, request):
"""Logs the user in."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LoginForm:
"""Django-backed login form for normal authentication."""
def clean(self):
"""Validates the login form."""
if self._errors:
return
user = authenticate(username=self.cleaned_data['username'].lower(), password=self.cleaned_data['password'])
if user:
... | the_stack_v2_python_sparse | makahiki/apps/managers/auth_mgr/forms.py | justinslee/Wai-Not-Makahiki | train | 1 |
0d5c616df16683eb0cf1c6cdfd1569980a81ae8f | [
"try:\n return self._list(self._PROJECTS_URL, 'projects', obj_class=Project)\nexcept exceptions.EndpointNotFound:\n endpoint_filter = {'interface': plugin.AUTH_INTERFACE}\n return self._list(self._PROJECTS_URL, 'projects', obj_class=Project, endpoint_filter=endpoint_filter)",
"try:\n return self._list... | <|body_start_0|>
try:
return self._list(self._PROJECTS_URL, 'projects', obj_class=Project)
except exceptions.EndpointNotFound:
endpoint_filter = {'interface': plugin.AUTH_INTERFACE}
return self._list(self._PROJECTS_URL, 'projects', obj_class=Project, endpoint_filter=e... | Retrieve auth context specific information. The information returned by the auth routes is entirely dependent on the authentication information provided by the user. | AuthManager | [
"Apache-2.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthManager:
"""Retrieve auth context specific information. The information returned by the auth routes is entirely dependent on the authentication information provided by the user."""
def projects(self):
"""List projects that the specified token can be rescoped to. :returns: a list ... | stack_v2_sparse_classes_10k_train_001441 | 3,252 | permissive | [
{
"docstring": "List projects that the specified token can be rescoped to. :returns: a list of projects. :rtype: list of :class:`keystoneclient.v3.projects.Project`",
"name": "projects",
"signature": "def projects(self)"
},
{
"docstring": "List Domains that the specified token can be rescoped to... | 3 | stack_v2_sparse_classes_30k_train_006508 | Implement the Python class `AuthManager` described below.
Class description:
Retrieve auth context specific information. The information returned by the auth routes is entirely dependent on the authentication information provided by the user.
Method signatures and docstrings:
- def projects(self): List projects that ... | Implement the Python class `AuthManager` described below.
Class description:
Retrieve auth context specific information. The information returned by the auth routes is entirely dependent on the authentication information provided by the user.
Method signatures and docstrings:
- def projects(self): List projects that ... | 141787ae8b0db7ac4dffce915e033a78d145d54e | <|skeleton|>
class AuthManager:
"""Retrieve auth context specific information. The information returned by the auth routes is entirely dependent on the authentication information provided by the user."""
def projects(self):
"""List projects that the specified token can be rescoped to. :returns: a list ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AuthManager:
"""Retrieve auth context specific information. The information returned by the auth routes is entirely dependent on the authentication information provided by the user."""
def projects(self):
"""List projects that the specified token can be rescoped to. :returns: a list of projects. ... | the_stack_v2_python_sparse | keystoneclient/v3/auth.py | openstack/python-keystoneclient | train | 118 |
ca5c1fd0a53a01b92dd10826b1d38bc50fdfbd62 | [
"from stock.models import StockItem\nlogger.info(f'SampleLocatePlugin attempting to locate item ID {item_pk}')\ntry:\n item = StockItem.objects.get(pk=item_pk)\n logger.info(f'StockItem {item_pk} located!')\n item.set_metadata('located', True)\nexcept (ValueError, StockItem.DoesNotExist):\n logger.error... | <|body_start_0|>
from stock.models import StockItem
logger.info(f'SampleLocatePlugin attempting to locate item ID {item_pk}')
try:
item = StockItem.objects.get(pk=item_pk)
logger.info(f'StockItem {item_pk} located!')
item.set_metadata('located', True)
... | A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger. | SampleLocatePlugin | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SampleLocatePlugin:
"""A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger."""
def locate_stock_item(self, item_pk):
"""Locate a StockItem. Args: item_pk: primary key for item"""
<|body_0|>
def locate_stock_loc... | stack_v2_sparse_classes_10k_train_001442 | 1,854 | permissive | [
{
"docstring": "Locate a StockItem. Args: item_pk: primary key for item",
"name": "locate_stock_item",
"signature": "def locate_stock_item(self, item_pk)"
},
{
"docstring": "Locate a StockLocation. Args: location_pk: primary key for location",
"name": "locate_stock_location",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_002006 | Implement the Python class `SampleLocatePlugin` described below.
Class description:
A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger.
Method signatures and docstrings:
- def locate_stock_item(self, item_pk): Locate a StockItem. Args: item_pk: primary key... | Implement the Python class `SampleLocatePlugin` described below.
Class description:
A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger.
Method signatures and docstrings:
- def locate_stock_item(self, item_pk): Locate a StockItem. Args: item_pk: primary key... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class SampleLocatePlugin:
"""A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger."""
def locate_stock_item(self, item_pk):
"""Locate a StockItem. Args: item_pk: primary key for item"""
<|body_0|>
def locate_stock_loc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SampleLocatePlugin:
"""A very simple example of the 'locate' plugin. This plugin class simply prints location information to the logger."""
def locate_stock_item(self, item_pk):
"""Locate a StockItem. Args: item_pk: primary key for item"""
from stock.models import StockItem
logger... | the_stack_v2_python_sparse | InvenTree/plugin/samples/locate/locate_sample.py | inventree/InvenTree | train | 3,077 |
da2c6ea2117d2ec77f4a60748315d23c80dfafc8 | [
"def swap(i, j):\n tmp = nums[i]\n nums[i] = nums[j]\n nums[j] = tmp\npivot = self.findKthLargest(nums, len(nums) // 2)\nwiggleTable = [0 for _ in range(len(nums))]\nfor i in range(len(nums)):\n if i % 2 == 1:\n wiggleTable[i // 2] = i\n else:\n wiggleTable[-i // 2 - 1] = i\nleft = 0\nr... | <|body_start_0|>
def swap(i, j):
tmp = nums[i]
nums[i] = nums[j]
nums[j] = tmp
pivot = self.findKthLargest(nums, len(nums) // 2)
wiggleTable = [0 for _ in range(len(nums))]
for i in range(len(nums)):
if i % 2 == 1:
wiggleTab... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wiggleSort(self, nums):
"""O(n) time O(n) space :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def findKthLargest(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body... | stack_v2_sparse_classes_10k_train_001443 | 4,011 | no_license | [
{
"docstring": "O(n) time O(n) space :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.",
"name": "wiggleSort",
"signature": "def wiggleSort(self, nums)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "findKthLargest",
"s... | 5 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wiggleSort(self, nums): O(n) time O(n) space :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def findKthLargest(self, nums, k): :ty... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wiggleSort(self, nums): O(n) time O(n) space :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def findKthLargest(self, nums, k): :ty... | e16702d2b3ec4e5054baad56f4320bc3b31676ad | <|skeleton|>
class Solution:
def wiggleSort(self, nums):
"""O(n) time O(n) space :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def findKthLargest(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def wiggleSort(self, nums):
"""O(n) time O(n) space :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
def swap(i, j):
tmp = nums[i]
nums[i] = nums[j]
nums[j] = tmp
pivot = self.findKthLargest(nums, ... | the_stack_v2_python_sparse | leetcode/medium/wiggle_sort2.py | SuperMartinYang/learning_algorithm | train | 0 | |
7832d6c9eda8448515dcca08029e2f8e73b792dc | [
"end = len(numbers) - 1\nstart = 1\nfor index, num in enumerate(numbers):\n find_index = self.find_num(numbers, target - num, index + 1, end)\n if find_index != -1:\n return [index + 1, find_index + 1]",
"if end - start < 2:\n if numbers[start] == target:\n return start\n elif numbers[en... | <|body_start_0|>
end = len(numbers) - 1
start = 1
for index, num in enumerate(numbers):
find_index = self.find_num(numbers, target - num, index + 1, end)
if find_index != -1:
return [index + 1, find_index + 1]
<|end_body_0|>
<|body_start_1|>
if en... | Solution_1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_1:
def twoSum(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def find_num(self, numbers, target, start, end):
"""return index if target was find, else return -1"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_10k_train_001444 | 2,289 | no_license | [
{
"docstring": ":type numbers: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def twoSum(self, numbers, target)"
},
{
"docstring": "return index if target was find, else return -1",
"name": "find_num",
"signature": "def find_num(self, numbers, target, sta... | 2 | null | Implement the Python class `Solution_1` described below.
Class description:
Implement the Solution_1 class.
Method signatures and docstrings:
- def twoSum(self, numbers, target): :type numbers: List[int] :type target: int :rtype: List[int]
- def find_num(self, numbers, target, start, end): return index if target was ... | Implement the Python class `Solution_1` described below.
Class description:
Implement the Solution_1 class.
Method signatures and docstrings:
- def twoSum(self, numbers, target): :type numbers: List[int] :type target: int :rtype: List[int]
- def find_num(self, numbers, target, start, end): return index if target was ... | f96a2273c6831a8035e1adacfa452f73c599ae16 | <|skeleton|>
class Solution_1:
def twoSum(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def find_num(self, numbers, target, start, end):
"""return index if target was find, else return -1"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution_1:
def twoSum(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
end = len(numbers) - 1
start = 1
for index, num in enumerate(numbers):
find_index = self.find_num(numbers, target - num, index + 1, end)
if ... | the_stack_v2_python_sparse | Python/TwoSumIIInputarrayissorted.py | here0009/LeetCode | train | 1 | |
4b653de11fba1d6aa8bfc0f0e14ea998358939b0 | [
"super(NormalizeImage, self).__init__()\nself.mean = mean\nself.std = std\nself.is_scale = is_scale\nself.is_channel_first = is_channel_first\nif not (isinstance(self.mean, list) and isinstance(self.std, list) and isinstance(self.is_scale, bool)):\n raise TypeError('{}: input type is invalid.'.format(self))\nfro... | <|body_start_0|>
super(NormalizeImage, self).__init__()
self.mean = mean
self.std = std
self.is_scale = is_scale
self.is_channel_first = is_channel_first
if not (isinstance(self.mean, list) and isinstance(self.std, list) and isinstance(self.is_scale, bool)):
r... | NormalizeImage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NormalizeImage:
def __init__(self, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], is_scale=True, is_channel_first=False):
"""Args: mean (list): the pixel mean std (list): the pixel variance"""
<|body_0|>
def __call__(self, sample, context=None):
"""Normalize ... | stack_v2_sparse_classes_10k_train_001445 | 19,057 | permissive | [
{
"docstring": "Args: mean (list): the pixel mean std (list): the pixel variance",
"name": "__init__",
"signature": "def __init__(self, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], is_scale=True, is_channel_first=False)"
},
{
"docstring": "Normalize the image. Operators: 1.(optional) S... | 2 | stack_v2_sparse_classes_30k_train_005124 | Implement the Python class `NormalizeImage` described below.
Class description:
Implement the NormalizeImage class.
Method signatures and docstrings:
- def __init__(self, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], is_scale=True, is_channel_first=False): Args: mean (list): the pixel mean std (list): the pi... | Implement the Python class `NormalizeImage` described below.
Class description:
Implement the NormalizeImage class.
Method signatures and docstrings:
- def __init__(self, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], is_scale=True, is_channel_first=False): Args: mean (list): the pixel mean std (list): the pi... | b8ec015fa9e16c0a879c619ee1f2aab8a393c7bd | <|skeleton|>
class NormalizeImage:
def __init__(self, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], is_scale=True, is_channel_first=False):
"""Args: mean (list): the pixel mean std (list): the pixel variance"""
<|body_0|>
def __call__(self, sample, context=None):
"""Normalize ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NormalizeImage:
def __init__(self, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], is_scale=True, is_channel_first=False):
"""Args: mean (list): the pixel mean std (list): the pixel variance"""
super(NormalizeImage, self).__init__()
self.mean = mean
self.std = std
... | the_stack_v2_python_sparse | CV/PaddleReid/reid/data/transform/operators.py | sserdoubleh/Research | train | 10 | |
79f5ad33c3b213df679c819b41c060746b18252e | [
"if not root:\n return '[]'\nqueue = collections.deque()\nqueue.append(root)\nres = []\nwhile queue:\n node = queue.popleft()\n if node:\n res.append(str(node.val))\n queue.append(node.left)\n queue.append(node.right)\n else:\n res.append('null')\nreturn '[' + ','.join(res) +... | <|body_start_0|>
if not root:
return '[]'
queue = collections.deque()
queue.append(root)
res = []
while queue:
node = queue.popleft()
if node:
res.append(str(node.val))
queue.append(node.left)
que... | 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_001446 | 1,977 | 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_004577 | 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:... | 809424acee0e63b795a46fdc51c5aef6e669d547 | <|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 = collections.deque()
queue.append(root)
res = []
while queue:
node = queue.popleft()
i... | the_stack_v2_python_sparse | python_offer/37_序列化二叉树.py | Madanfeng/JianZhiOffer | train | 0 | |
51568a7b64c68d881b2f996f67197c8c127f8789 | [
"self.rank = rank\nself.ls_solve = ls_solve\nself.n_iter_max = n_iter_max\nself.tol = tol\nself.random_state = random_state\nself.verbose = verbose\nself.callback = callback",
"tr_decomp = tensor_ring_als(tensor, rank=self.rank, ls_solve=self.ls_solve, n_iter_max=self.n_iter_max, tol=self.tol, random_state=self.r... | <|body_start_0|>
self.rank = rank
self.ls_solve = ls_solve
self.n_iter_max = n_iter_max
self.tol = tol
self.random_state = random_state
self.verbose = verbose
self.callback = callback
<|end_body_0|>
<|body_start_1|>
tr_decomp = tensor_ring_als(tensor, ran... | A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th core will be of size rank[i]-by-shape[i]-by-rank[i+1], where shape[i] is the dim... | TensorRingALS | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TensorRingALS:
"""A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th core will be of size rank[i]-by-shape[i... | stack_v2_sparse_classes_10k_train_001447 | 16,136 | permissive | [
{
"docstring": "Parameters ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th core will be of size rank[i]-by-shape[i]-by-rank[i+1], where shape[i] is the dimension of the i-th mode o... | 2 | stack_v2_sparse_classes_30k_val_000253 | Implement the Python class `TensorRingALS` described below.
Class description:
A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th ... | Implement the Python class `TensorRingALS` described below.
Class description:
A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th ... | de05e178850eb2abe43ec1a40f80624ca606807d | <|skeleton|>
class TensorRingALS:
"""A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th core will be of size rank[i]-by-shape[i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TensorRingALS:
"""A class wrapper for the tensor_ring_als function Attributes ---------- rank : Union[int, List[int]] The rank of the decomposition. If `rank` is an int, then all ranks will be the same and equal to `rank`. If `rank` is a list, then the i-th core will be of size rank[i]-by-shape[i]-by-rank[i+1... | the_stack_v2_python_sparse | tensorly/decomposition/_tr.py | tensorly/tensorly | train | 1,533 |
a98e03c1f3cc30278fad3213d0176d2991df7f8a | [
"self.paths = module_paths\nself.module_append_string = '\\n'.join(('module.paths.push(\"%s\")\\n' % p for p in self.paths))\ncommand_string = 'var babel = require(\"babel-core\")'\nself.babel = execjs.compile(self.module_append_string + command_string)",
"if options is None:\n options = {'ast': False, 'preset... | <|body_start_0|>
self.paths = module_paths
self.module_append_string = '\n'.join(('module.paths.push("%s")\n' % p for p in self.paths))
command_string = 'var babel = require("babel-core")'
self.babel = execjs.compile(self.module_append_string + command_string)
<|end_body_0|>
<|body_star... | Babel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Babel:
def __init__(self, *module_paths):
"""Constructor :param module_paths: Paths to node_modules"""
<|body_0|>
def transpile(self, code, options=None):
"""Takes code and runs it through babel.js if ``options`` is not provided it'll default to: .. code-block:: pyth... | stack_v2_sparse_classes_10k_train_001448 | 2,713 | permissive | [
{
"docstring": "Constructor :param module_paths: Paths to node_modules",
"name": "__init__",
"signature": "def __init__(self, *module_paths)"
},
{
"docstring": "Takes code and runs it through babel.js if ``options`` is not provided it'll default to: .. code-block:: python {'ast': false, 'presets... | 2 | stack_v2_sparse_classes_30k_train_005106 | Implement the Python class `Babel` described below.
Class description:
Implement the Babel class.
Method signatures and docstrings:
- def __init__(self, *module_paths): Constructor :param module_paths: Paths to node_modules
- def transpile(self, code, options=None): Takes code and runs it through babel.js if ``option... | Implement the Python class `Babel` described below.
Class description:
Implement the Babel class.
Method signatures and docstrings:
- def __init__(self, *module_paths): Constructor :param module_paths: Paths to node_modules
- def transpile(self, code, options=None): Takes code and runs it through babel.js if ``option... | 408f3fa3d36542d8fc1236ba1cac804de6f14b0c | <|skeleton|>
class Babel:
def __init__(self, *module_paths):
"""Constructor :param module_paths: Paths to node_modules"""
<|body_0|>
def transpile(self, code, options=None):
"""Takes code and runs it through babel.js if ``options`` is not provided it'll default to: .. code-block:: pyth... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Babel:
def __init__(self, *module_paths):
"""Constructor :param module_paths: Paths to node_modules"""
self.paths = module_paths
self.module_append_string = '\n'.join(('module.paths.push("%s")\n' % p for p in self.paths))
command_string = 'var babel = require("babel-core")'
... | the_stack_v2_python_sparse | hard-gists/19a4b105d1dff9a591b8/snippet.py | dockerizeme/dockerizeme | train | 24 | |
abd5c1a29f7f6d7625c832f7e1b9434b41a5d1dd | [
"self.aliyunrequest.set_action_name('DescribeLoadBalancers')\nif not isinstance(config, list):\n return self.MResponse(code=20001, msg='config不是列表', status=False)\nself.Mconfig(config)\nresponse = self.aliyunapiclient.do_action_with_exception(self.aliyunrequest)\nreturn response",
"self.aliyunrequest.set_actio... | <|body_start_0|>
self.aliyunrequest.set_action_name('DescribeLoadBalancers')
if not isinstance(config, list):
return self.MResponse(code=20001, msg='config不是列表', status=False)
self.Mconfig(config)
response = self.aliyunapiclient.do_action_with_exception(self.aliyunrequest)
... | 实例API | ALiYunApiSLB | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ALiYunApiSLB:
"""实例API"""
def DescribeLoadBalancers(self, config):
"""查询已创建的负载均衡实例。 :param config: [{}]数据类型 :return: 根据自己配置输出格式"""
<|body_0|>
def DescribeLoadBalancerAttribute(self, config):
"""查询指定负载均衡实例的详细信息。 :param config: [{}]数据类型 :return: 根据自己配置输出格式"""
... | stack_v2_sparse_classes_10k_train_001449 | 7,651 | no_license | [
{
"docstring": "查询已创建的负载均衡实例。 :param config: [{}]数据类型 :return: 根据自己配置输出格式",
"name": "DescribeLoadBalancers",
"signature": "def DescribeLoadBalancers(self, config)"
},
{
"docstring": "查询指定负载均衡实例的详细信息。 :param config: [{}]数据类型 :return: 根据自己配置输出格式",
"name": "DescribeLoadBalancerAttribute",
"... | 5 | stack_v2_sparse_classes_30k_train_004463 | Implement the Python class `ALiYunApiSLB` described below.
Class description:
实例API
Method signatures and docstrings:
- def DescribeLoadBalancers(self, config): 查询已创建的负载均衡实例。 :param config: [{}]数据类型 :return: 根据自己配置输出格式
- def DescribeLoadBalancerAttribute(self, config): 查询指定负载均衡实例的详细信息。 :param config: [{}]数据类型 :return... | Implement the Python class `ALiYunApiSLB` described below.
Class description:
实例API
Method signatures and docstrings:
- def DescribeLoadBalancers(self, config): 查询已创建的负载均衡实例。 :param config: [{}]数据类型 :return: 根据自己配置输出格式
- def DescribeLoadBalancerAttribute(self, config): 查询指定负载均衡实例的详细信息。 :param config: [{}]数据类型 :return... | 401ad869298d55a6cb2f78442385f67f40b9db52 | <|skeleton|>
class ALiYunApiSLB:
"""实例API"""
def DescribeLoadBalancers(self, config):
"""查询已创建的负载均衡实例。 :param config: [{}]数据类型 :return: 根据自己配置输出格式"""
<|body_0|>
def DescribeLoadBalancerAttribute(self, config):
"""查询指定负载均衡实例的详细信息。 :param config: [{}]数据类型 :return: 根据自己配置输出格式"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ALiYunApiSLB:
"""实例API"""
def DescribeLoadBalancers(self, config):
"""查询已创建的负载均衡实例。 :param config: [{}]数据类型 :return: 根据自己配置输出格式"""
self.aliyunrequest.set_action_name('DescribeLoadBalancers')
if not isinstance(config, list):
return self.MResponse(code=20001, msg='config... | the_stack_v2_python_sparse | utils/maliyun/aliyunapi.py | Alotofwater/cookcmdb | train | 8 |
dbb50fd1ea93ee7b5d369d25c3eb98016d8c1d5b | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn CalendarSharingMessageAction()",
"from .calendar_sharing_action import CalendarSharingAction\nfrom .calendar_sharing_action_importance import CalendarSharingActionImportance\nfrom .calendar_sharing_action_type import CalendarSharingAct... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return CalendarSharingMessageAction()
<|end_body_0|>
<|body_start_1|>
from .calendar_sharing_action import CalendarSharingAction
from .calendar_sharing_action_importance import CalendarSharingA... | CalendarSharingMessageAction | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalendarSharingMessageAction:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessageAction:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value... | stack_v2_sparse_classes_10k_train_001450 | 3,763 | 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: CalendarSharingMessageAction",
"name": "create_from_discriminator_value",
"signature": "def create_from_disc... | 3 | null | Implement the Python class `CalendarSharingMessageAction` described below.
Class description:
Implement the CalendarSharingMessageAction class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessageAction: Creates a new instance of the a... | Implement the Python class `CalendarSharingMessageAction` described below.
Class description:
Implement the CalendarSharingMessageAction class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessageAction: Creates a new instance of the a... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class CalendarSharingMessageAction:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessageAction:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CalendarSharingMessageAction:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessageAction:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create th... | the_stack_v2_python_sparse | msgraph/generated/models/calendar_sharing_message_action.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
dc640536bba212964069ff5476d89dbbe1f6673e | [
"if data is None:\n if n <= 0:\n raise ValueError('n must be a positive value')\n if p >= 1 or p <= 0:\n raise ValueError('p must be greater than 0 and less than 1')\n else:\n self.n = int(n)\n self.p = float(p)\nelif not isinstance(data, list):\n raise TypeError('data must b... | <|body_start_0|>
if data is None:
if n <= 0:
raise ValueError('n must be a positive value')
if p >= 1 or p <= 0:
raise ValueError('p must be greater than 0 and less than 1')
else:
self.n = int(n)
self.p = float(p... | Class Binomial | Binomial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Binomial:
"""Class Binomial"""
def __init__(self, data=None, n=1, p=0.5):
"""Contructor of class binomial and definition"""
<|body_0|>
def pmf(self, k):
"""Definition of probability density function"""
<|body_1|>
def factor(number):
"""Factor... | stack_v2_sparse_classes_10k_train_001451 | 2,018 | no_license | [
{
"docstring": "Contructor of class binomial and definition",
"name": "__init__",
"signature": "def __init__(self, data=None, n=1, p=0.5)"
},
{
"docstring": "Definition of probability density function",
"name": "pmf",
"signature": "def pmf(self, k)"
},
{
"docstring": "Factorial o... | 4 | stack_v2_sparse_classes_30k_train_005216 | Implement the Python class `Binomial` described below.
Class description:
Class Binomial
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): Contructor of class binomial and definition
- def pmf(self, k): Definition of probability density function
- def factor(number): Factorial outside of ... | Implement the Python class `Binomial` described below.
Class description:
Class Binomial
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): Contructor of class binomial and definition
- def pmf(self, k): Definition of probability density function
- def factor(number): Factorial outside of ... | 74213384b0998f65e123adc146ea5e91c4d77b37 | <|skeleton|>
class Binomial:
"""Class Binomial"""
def __init__(self, data=None, n=1, p=0.5):
"""Contructor of class binomial and definition"""
<|body_0|>
def pmf(self, k):
"""Definition of probability density function"""
<|body_1|>
def factor(number):
"""Factor... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Binomial:
"""Class Binomial"""
def __init__(self, data=None, n=1, p=0.5):
"""Contructor of class binomial and definition"""
if data is None:
if n <= 0:
raise ValueError('n must be a positive value')
if p >= 1 or p <= 0:
raise ValueEr... | the_stack_v2_python_sparse | math/0x03-probability/binomial.py | PilarPinto/holbertonschool-machine_learning | train | 0 |
500f450bbf8526904ca0447b2b2ec1f819f9d6aa | [
"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... | Service for configuring sinks used to export log entries outside of Stackdriver Logging. | ConfigServiceV2Servicer | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigServiceV2Servicer:
"""Service for configuring sinks used to export log entries outside of Stackdriver Logging."""
def ListSinks(self, request, context):
"""Lists sinks."""
<|body_0|>
def GetSink(self, request, context):
"""Gets a sink."""
<|body_1|>... | stack_v2_sparse_classes_10k_train_001452 | 6,663 | permissive | [
{
"docstring": "Lists sinks.",
"name": "ListSinks",
"signature": "def ListSinks(self, request, context)"
},
{
"docstring": "Gets a sink.",
"name": "GetSink",
"signature": "def GetSink(self, request, context)"
},
{
"docstring": "Creates a sink that exports specified log entries to... | 5 | stack_v2_sparse_classes_30k_train_006740 | Implement the Python class `ConfigServiceV2Servicer` described below.
Class description:
Service for configuring sinks used to export log entries outside of Stackdriver Logging.
Method signatures and docstrings:
- def ListSinks(self, request, context): Lists sinks.
- def GetSink(self, request, context): Gets a sink.
... | Implement the Python class `ConfigServiceV2Servicer` described below.
Class description:
Service for configuring sinks used to export log entries outside of Stackdriver Logging.
Method signatures and docstrings:
- def ListSinks(self, request, context): Lists sinks.
- def GetSink(self, request, context): Gets a sink.
... | 86977c0e2e97011359b619c88db47168181908ea | <|skeleton|>
class ConfigServiceV2Servicer:
"""Service for configuring sinks used to export log entries outside of Stackdriver Logging."""
def ListSinks(self, request, context):
"""Lists sinks."""
<|body_0|>
def GetSink(self, request, context):
"""Gets a sink."""
<|body_1|>... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ConfigServiceV2Servicer:
"""Service for configuring sinks used to export log entries outside of Stackdriver Logging."""
def ListSinks(self, request, context):
"""Lists sinks."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
... | the_stack_v2_python_sparse | generated/python/proto-google-cloud-logging-v2/google/cloud/proto/logging/v2/logging_config_pb2_grpc.py | QPC-github/api-client-staging | train | 1 |
e89ef6f86e716dba631971f85e881459eb8d18a2 | [
"super().__init__('custom_unitary', children, None)\nself.id = children[0]\nself.name = self.id.name\nif len(children) == 3:\n self.arguments = children[1]\n self.bitlist = children[2]\nelse:\n self.arguments = None\n self.bitlist = children[1]",
"string = self.name\nif self.arguments is not None:\n ... | <|body_start_0|>
super().__init__('custom_unitary', children, None)
self.id = children[0]
self.name = self.id.name
if len(children) == 3:
self.arguments = children[1]
self.bitlist = children[2]
else:
self.arguments = None
self.bitli... | Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = None or exp_list node .bitlist = primary_list node | CustomUnitary | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomUnitary:
"""Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = None or exp_list node .bitlist = primary... | stack_v2_sparse_classes_10k_train_001453 | 1,663 | permissive | [
{
"docstring": "Create the custom gate node.",
"name": "__init__",
"signature": "def __init__(self, children)"
},
{
"docstring": "Return the corresponding OPENQASM string.",
"name": "qasm",
"signature": "def qasm(self, prec=15)"
}
] | 2 | null | Implement the Python class `CustomUnitary` described below.
Class description:
Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = N... | Implement the Python class `CustomUnitary` described below.
Class description:
Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = N... | abf6c23d4ab6c63f9c01c7434fb46321e6a69200 | <|skeleton|>
class CustomUnitary:
"""Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = None or exp_list node .bitlist = primary... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CustomUnitary:
"""Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = None or exp_list node .bitlist = primary_list node"""... | the_stack_v2_python_sparse | qiskit/qasm/node/customunitary.py | indian-institute-of-science-qc/qiskit-aakash | train | 37 |
89eada8540f136577f80e6c2e797c3d17d958a9c | [
"self.switch_profiles = switch_profiles\nself.switches = switches\nself.stacks = stacks\nself.stp_priority = stp_priority",
"if dictionary is None:\n return None\nstp_priority = dictionary.get('stpPriority')\nswitch_profiles = dictionary.get('switchProfiles')\nswitches = dictionary.get('switches')\nstacks = di... | <|body_start_0|>
self.switch_profiles = switch_profiles
self.switches = switches
self.stacks = stacks
self.stp_priority = stp_priority
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
stp_priority = dictionary.get('stpPriority')
swit... | Implementation of the 'StpBridgePriority' model. TODO: type model description here. Attributes: switch_profiles (list of string): List of switch profile IDs switches (list of string): List of switch serial numbers stacks (list of string): List of stack IDs stp_priority (int): STP priority for switch, stacks, or switch ... | StpBridgePriorityModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StpBridgePriorityModel:
"""Implementation of the 'StpBridgePriority' model. TODO: type model description here. Attributes: switch_profiles (list of string): List of switch profile IDs switches (list of string): List of switch serial numbers stacks (list of string): List of stack IDs stp_priority ... | stack_v2_sparse_classes_10k_train_001454 | 2,255 | permissive | [
{
"docstring": "Constructor for the StpBridgePriorityModel class",
"name": "__init__",
"signature": "def __init__(self, stp_priority=None, switch_profiles=None, switches=None, stacks=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A di... | 2 | stack_v2_sparse_classes_30k_val_000338 | Implement the Python class `StpBridgePriorityModel` described below.
Class description:
Implementation of the 'StpBridgePriority' model. TODO: type model description here. Attributes: switch_profiles (list of string): List of switch profile IDs switches (list of string): List of switch serial numbers stacks (list of s... | Implement the Python class `StpBridgePriorityModel` described below.
Class description:
Implementation of the 'StpBridgePriority' model. TODO: type model description here. Attributes: switch_profiles (list of string): List of switch profile IDs switches (list of string): List of switch serial numbers stacks (list of s... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class StpBridgePriorityModel:
"""Implementation of the 'StpBridgePriority' model. TODO: type model description here. Attributes: switch_profiles (list of string): List of switch profile IDs switches (list of string): List of switch serial numbers stacks (list of string): List of stack IDs stp_priority ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StpBridgePriorityModel:
"""Implementation of the 'StpBridgePriority' model. TODO: type model description here. Attributes: switch_profiles (list of string): List of switch profile IDs switches (list of string): List of switch serial numbers stacks (list of string): List of stack IDs stp_priority (int): STP pr... | the_stack_v2_python_sparse | meraki/models/stp_bridge_priority_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
6d5836acff36cf8f9e8590779c9a76a3134a8782 | [
"mock_class_node_1 = create_mock_java_class(pkg=self.TEST_PKG_1)\nmock_class_node_2 = create_mock_java_class(pkg=self.TEST_PKG_1)\nmock_class_node_3 = create_mock_java_class(pkg=self.TEST_PKG_2)\nmock_class_graph = unittest.mock.Mock()\nmock_class_graph.nodes = [mock_class_node_1, mock_class_node_2, mock_class_node... | <|body_start_0|>
mock_class_node_1 = create_mock_java_class(pkg=self.TEST_PKG_1)
mock_class_node_2 = create_mock_java_class(pkg=self.TEST_PKG_1)
mock_class_node_3 = create_mock_java_class(pkg=self.TEST_PKG_2)
mock_class_graph = unittest.mock.Mock()
mock_class_graph.nodes = [mock_... | Unit tests for JavaPackageDependencyGraph. Full name: dependency_analysis.class_dependency.JavaPackageDependencyGraph. | TestJavaPackageDependencyGraph | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestJavaPackageDependencyGraph:
"""Unit tests for JavaPackageDependencyGraph. Full name: dependency_analysis.class_dependency.JavaPackageDependencyGraph."""
def test_initialization(self):
"""Tests that initialization collapses a class dependency graph."""
<|body_0|>
def ... | stack_v2_sparse_classes_10k_train_001455 | 4,704 | permissive | [
{
"docstring": "Tests that initialization collapses a class dependency graph.",
"name": "test_initialization",
"signature": "def test_initialization(self)"
},
{
"docstring": "Tests that a package with no external dependencies is included.",
"name": "test_initialization_no_dependencies",
... | 4 | null | Implement the Python class `TestJavaPackageDependencyGraph` described below.
Class description:
Unit tests for JavaPackageDependencyGraph. Full name: dependency_analysis.class_dependency.JavaPackageDependencyGraph.
Method signatures and docstrings:
- def test_initialization(self): Tests that initialization collapses ... | Implement the Python class `TestJavaPackageDependencyGraph` described below.
Class description:
Unit tests for JavaPackageDependencyGraph. Full name: dependency_analysis.class_dependency.JavaPackageDependencyGraph.
Method signatures and docstrings:
- def test_initialization(self): Tests that initialization collapses ... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class TestJavaPackageDependencyGraph:
"""Unit tests for JavaPackageDependencyGraph. Full name: dependency_analysis.class_dependency.JavaPackageDependencyGraph."""
def test_initialization(self):
"""Tests that initialization collapses a class dependency graph."""
<|body_0|>
def ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestJavaPackageDependencyGraph:
"""Unit tests for JavaPackageDependencyGraph. Full name: dependency_analysis.class_dependency.JavaPackageDependencyGraph."""
def test_initialization(self):
"""Tests that initialization collapses a class dependency graph."""
mock_class_node_1 = create_mock_j... | the_stack_v2_python_sparse | tools/android/dependency_analysis/package_dependency_unittest.py | chromium/chromium | train | 17,408 |
04c9c86a051476ad7a66e8bf453a8a7abccce607 | [
"if not self.session.cookies:\n try:\n self.session.cookies = cookies.load()\n except MissingCookiesError:\n return False\n except Exception as exc:\n import traceback\n LOG.error('Failed to load stored cookies: {}', type(exc).__name__)\n LOG.error(traceback.format_exc())... | <|body_start_0|>
if not self.session.cookies:
try:
self.session.cookies = cookies.load()
except MissingCookiesError:
return False
except Exception as exc:
import traceback
LOG.error('Failed to load stored cookies... | Handle the cookies | SessionCookie | [
"LicenseRef-scancode-warranty-disclaimer",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionCookie:
"""Handle the cookies"""
def _load_cookies(self):
"""Load stored cookies from disk"""
<|body_0|>
def _verify_session_cookies(self):
"""Verify that the session cookies have not expired"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_001456 | 1,950 | permissive | [
{
"docstring": "Load stored cookies from disk",
"name": "_load_cookies",
"signature": "def _load_cookies(self)"
},
{
"docstring": "Verify that the session cookies have not expired",
"name": "_verify_session_cookies",
"signature": "def _verify_session_cookies(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003671 | Implement the Python class `SessionCookie` described below.
Class description:
Handle the cookies
Method signatures and docstrings:
- def _load_cookies(self): Load stored cookies from disk
- def _verify_session_cookies(self): Verify that the session cookies have not expired | Implement the Python class `SessionCookie` described below.
Class description:
Handle the cookies
Method signatures and docstrings:
- def _load_cookies(self): Load stored cookies from disk
- def _verify_session_cookies(self): Verify that the session cookies have not expired
<|skeleton|>
class SessionCookie:
"""H... | ece10d24449faaccd7d65a4093c6b5679ee0b383 | <|skeleton|>
class SessionCookie:
"""Handle the cookies"""
def _load_cookies(self):
"""Load stored cookies from disk"""
<|body_0|>
def _verify_session_cookies(self):
"""Verify that the session cookies have not expired"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SessionCookie:
"""Handle the cookies"""
def _load_cookies(self):
"""Load stored cookies from disk"""
if not self.session.cookies:
try:
self.session.cookies = cookies.load()
except MissingCookiesError:
return False
except ... | the_stack_v2_python_sparse | resources/lib/services/nfsession/session/cookie.py | CastagnaIT/plugin.video.netflix | train | 2,019 |
c9609a40c4a9a4913b961d70967237983afb7a9d | [
"if state.func_ir is None:\n pm.add_pass(TranslateByteCode, 'analyzing bytecode')\n pm.add_pass(FixupArgs, 'fix up args')\npm.add_pass(IRProcessing, 'processing IR')\npm.add_pass(WithLifting, 'Handle with contexts')\npm.add_pass(DPPYRewriteOverloadedNumPyFunctions, 'Rewrite name of Numpy functions to overload... | <|body_start_0|>
if state.func_ir is None:
pm.add_pass(TranslateByteCode, 'analyzing bytecode')
pm.add_pass(FixupArgs, 'fix up args')
pm.add_pass(IRProcessing, 'processing IR')
pm.add_pass(WithLifting, 'Handle with contexts')
pm.add_pass(DPPYRewriteOverloadedNumPy... | This is the DPPY pass builder to run Intel GPU/CPU specific code-generation and optimization passes. This pass builder does not offer objectmode and interpreted passes. | DPPYPassBuilder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DPPYPassBuilder:
"""This is the DPPY pass builder to run Intel GPU/CPU specific code-generation and optimization passes. This pass builder does not offer objectmode and interpreted passes."""
def default_numba_nopython_pipeline(state, pm):
"""Adds the default set of NUMBA passes to t... | stack_v2_sparse_classes_10k_train_001457 | 5,412 | permissive | [
{
"docstring": "Adds the default set of NUMBA passes to the pass manager",
"name": "default_numba_nopython_pipeline",
"signature": "def default_numba_nopython_pipeline(state, pm)"
},
{
"docstring": "Returns an nopython mode pipeline based PassManager",
"name": "define_nopython_pipeline",
... | 2 | stack_v2_sparse_classes_30k_train_003544 | Implement the Python class `DPPYPassBuilder` described below.
Class description:
This is the DPPY pass builder to run Intel GPU/CPU specific code-generation and optimization passes. This pass builder does not offer objectmode and interpreted passes.
Method signatures and docstrings:
- def default_numba_nopython_pipel... | Implement the Python class `DPPYPassBuilder` described below.
Class description:
This is the DPPY pass builder to run Intel GPU/CPU specific code-generation and optimization passes. This pass builder does not offer objectmode and interpreted passes.
Method signatures and docstrings:
- def default_numba_nopython_pipel... | f8b3cc81b65ba75d126c8b3cb603d752eb681c7e | <|skeleton|>
class DPPYPassBuilder:
"""This is the DPPY pass builder to run Intel GPU/CPU specific code-generation and optimization passes. This pass builder does not offer objectmode and interpreted passes."""
def default_numba_nopython_pipeline(state, pm):
"""Adds the default set of NUMBA passes to t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DPPYPassBuilder:
"""This is the DPPY pass builder to run Intel GPU/CPU specific code-generation and optimization passes. This pass builder does not offer objectmode and interpreted passes."""
def default_numba_nopython_pipeline(state, pm):
"""Adds the default set of NUMBA passes to the pass manag... | the_stack_v2_python_sparse | numba_dppy/dppy_passbuilder.py | FermiQ/numba-dppy | train | 0 |
f0913172965055a60aae137c7a7a38428a172554 | [
"self.pipe = pipe\nself.cache_file_path = cache_file_path\nself.lang_orig = lang_orig\nself.lang_dest = lang_dest\nif not cache_file_path.exists():\n self.cached_tran = {}\n return\nself.cached_tran = json.loads(cache_file_path.read_text())",
"if str_orig not in self.cached_tran:\n if self.pipe is None:\... | <|body_start_0|>
self.pipe = pipe
self.cache_file_path = cache_file_path
self.lang_orig = lang_orig
self.lang_dest = lang_dest
if not cache_file_path.exists():
self.cached_tran = {}
return
self.cached_tran = json.loads(cache_file_path.read_text())
... | A cached translation pipeline. | TranslationPipelineCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TranslationPipelineCache:
"""A cached translation pipeline."""
def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str):
"""Initialize a cached TranslationPipeline."""
<|body_0|>
def __call__(self, str_orig: str):
... | stack_v2_sparse_classes_10k_train_001458 | 1,437 | no_license | [
{
"docstring": "Initialize a cached TranslationPipeline.",
"name": "__init__",
"signature": "def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str)"
},
{
"docstring": "Call an instance of the class with a string to return the translation.",... | 2 | stack_v2_sparse_classes_30k_train_002790 | Implement the Python class `TranslationPipelineCache` described below.
Class description:
A cached translation pipeline.
Method signatures and docstrings:
- def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str): Initialize a cached TranslationPipeline.
- def __... | Implement the Python class `TranslationPipelineCache` described below.
Class description:
A cached translation pipeline.
Method signatures and docstrings:
- def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str): Initialize a cached TranslationPipeline.
- def __... | 1d7e5657014b00612cde87b78d5506a9e8b6adfc | <|skeleton|>
class TranslationPipelineCache:
"""A cached translation pipeline."""
def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str):
"""Initialize a cached TranslationPipeline."""
<|body_0|>
def __call__(self, str_orig: str):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TranslationPipelineCache:
"""A cached translation pipeline."""
def __init__(self, pipe: Optional[TranslationPipeline], cache_file_path: Path, lang_orig: str, lang_dest: str):
"""Initialize a cached TranslationPipeline."""
self.pipe = pipe
self.cache_file_path = cache_file_path
... | the_stack_v2_python_sparse | python/streamlit-sample/align-epub/cached_pipe.py | Pitrified/snippet | train | 2 |
5d6140fb5fe74bccb0c6bb45abe46be604b0c16e | [
"if filter_name is None or filter_name == '':\n self.include = []\n self.exclude = []\nelif filter_name == 'uncategorized':\n exclude = []\n for f in self.filters:\n exclude += self.filters[f].get('include', [])\n self.exclude = exclude\n self.include = []\nelse:\n self.include = self.fi... | <|body_start_0|>
if filter_name is None or filter_name == '':
self.include = []
self.exclude = []
elif filter_name == 'uncategorized':
exclude = []
for f in self.filters:
exclude += self.filters[f].get('include', [])
self.exclud... | Class to assist in filtering jobs which are in error, based on their last log message. | JSAProcErrorFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSAProcErrorFilter:
"""Class to assist in filtering jobs which are in error, based on their last log message."""
def __init__(self, filter_name, extrafilter=None, state_prev=None):
"""Create error filter object. Parameters: filter_name: the name of the filter. Must be one of the valu... | stack_v2_sparse_classes_10k_train_001459 | 4,160 | no_license | [
{
"docstring": "Create error filter object. Parameters: filter_name: the name of the filter. Must be one of the values of the JSAProcErrorFilter.filter_names list.",
"name": "__init__",
"signature": "def __init__(self, filter_name, extrafilter=None, state_prev=None)"
},
{
"docstring": "Apply fil... | 2 | stack_v2_sparse_classes_30k_train_005924 | Implement the Python class `JSAProcErrorFilter` described below.
Class description:
Class to assist in filtering jobs which are in error, based on their last log message.
Method signatures and docstrings:
- def __init__(self, filter_name, extrafilter=None, state_prev=None): Create error filter object. Parameters: fil... | Implement the Python class `JSAProcErrorFilter` described below.
Class description:
Class to assist in filtering jobs which are in error, based on their last log message.
Method signatures and docstrings:
- def __init__(self, filter_name, extrafilter=None, state_prev=None): Create error filter object. Parameters: fil... | 8b8ef99700108dec85c6a14613181eef2d8d311e | <|skeleton|>
class JSAProcErrorFilter:
"""Class to assist in filtering jobs which are in error, based on their last log message."""
def __init__(self, filter_name, extrafilter=None, state_prev=None):
"""Create error filter object. Parameters: filter_name: the name of the filter. Must be one of the valu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class JSAProcErrorFilter:
"""Class to assist in filtering jobs which are in error, based on their last log message."""
def __init__(self, filter_name, extrafilter=None, state_prev=None):
"""Create error filter object. Parameters: filter_name: the name of the filter. Must be one of the values of the JSA... | the_stack_v2_python_sparse | lib/jsa_proc/action/error_filter.py | eaobservatory/jsa_proc | train | 0 |
4570a96598f5e57f6d8d66e24b426fdb8382f5ce | [
"batch = batch.to(self.device)\nchars, char_lens = batch.grapheme_encoded\nphn_bos, phn_lens = batch.phn_encoded_bos\nemb_char = self.hparams.encoder_emb(chars)\nx, _ = self.modules.enc(emb_char)\ne_in = self.modules.emb(phn_bos)\nh, w = self.modules.dec(e_in, x, char_lens)\nlogits = self.modules.lin(h)\np_seq = se... | <|body_start_0|>
batch = batch.to(self.device)
chars, char_lens = batch.grapheme_encoded
phn_bos, phn_lens = batch.phn_encoded_bos
emb_char = self.hparams.encoder_emb(chars)
x, _ = self.modules.enc(emb_char)
e_in = self.modules.emb(phn_bos)
h, w = self.modules.dec... | ASR | [
"GPL-1.0-or-later",
"LicenseRef-scancode-other-permissive",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ASR:
def compute_forward(self, batch, stage):
"""Forward computations from the char batches to the output probabilities."""
<|body_0|>
def compute_objectives(self, predictions, batch, stage):
"""Computes the loss (CTC+NLL) given predictions and targets."""
<|... | stack_v2_sparse_classes_10k_train_001460 | 10,934 | permissive | [
{
"docstring": "Forward computations from the char batches to the output probabilities.",
"name": "compute_forward",
"signature": "def compute_forward(self, batch, stage)"
},
{
"docstring": "Computes the loss (CTC+NLL) given predictions and targets.",
"name": "compute_objectives",
"signa... | 6 | stack_v2_sparse_classes_30k_train_000061 | Implement the Python class `ASR` described below.
Class description:
Implement the ASR class.
Method signatures and docstrings:
- def compute_forward(self, batch, stage): Forward computations from the char batches to the output probabilities.
- def compute_objectives(self, predictions, batch, stage): Computes the los... | Implement the Python class `ASR` described below.
Class description:
Implement the ASR class.
Method signatures and docstrings:
- def compute_forward(self, batch, stage): Forward computations from the char batches to the output probabilities.
- def compute_objectives(self, predictions, batch, stage): Computes the los... | d4c9a53773f13d5a2843f25bc7f89482936e2f17 | <|skeleton|>
class ASR:
def compute_forward(self, batch, stage):
"""Forward computations from the char batches to the output probabilities."""
<|body_0|>
def compute_objectives(self, predictions, batch, stage):
"""Computes the loss (CTC+NLL) given predictions and targets."""
<|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ASR:
def compute_forward(self, batch, stage):
"""Forward computations from the char batches to the output probabilities."""
batch = batch.to(self.device)
chars, char_lens = batch.grapheme_encoded
phn_bos, phn_lens = batch.phn_encoded_bos
emb_char = self.hparams.encoder_... | the_stack_v2_python_sparse | recipes/LibriSpeech/G2P/train.py | zycv/speechbrain | train | 2 | |
89e28e49b5385f7d8edb59509235eeac2487684f | [
"super(InputManager_Radix, self).__init__(config, is_inference)\nc = self.config\nmax_word_len = len(ops.number_to_base(len(c.wtoi), c.radix_base))\nself.buckets = [b * max_word_len for b in self.buckets]\nself.radix_wtoi = {}\nassert c.wtoi['<PAD>'] == -1\nfor k in c.wtoi:\n if k == '<GO>':\n idx = [c.ra... | <|body_start_0|>
super(InputManager_Radix, self).__init__(config, is_inference)
c = self.config
max_word_len = len(ops.number_to_base(len(c.wtoi), c.radix_base))
self.buckets = [b * max_word_len for b in self.buckets]
self.radix_wtoi = {}
assert c.wtoi['<PAD>'] == -1
... | Input Manager object for Radix-token models. | InputManager_Radix | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputManager_Radix:
"""Input Manager object for Radix-token models."""
def __init__(self, config, is_inference=False):
"""Loads the h5 file containing caption data and corresponding image paths."""
<|body_0|>
def _gen(self, data, is_training=True):
"""Generator f... | stack_v2_sparse_classes_10k_train_001461 | 19,609 | permissive | [
{
"docstring": "Loads the h5 file containing caption data and corresponding image paths.",
"name": "__init__",
"signature": "def __init__(self, config, is_inference=False)"
},
{
"docstring": "Generator fn, yields the image filepath and word IDs. Handles dataset shuffling.",
"name": "_gen",
... | 2 | stack_v2_sparse_classes_30k_test_000126 | Implement the Python class `InputManager_Radix` described below.
Class description:
Input Manager object for Radix-token models.
Method signatures and docstrings:
- def __init__(self, config, is_inference=False): Loads the h5 file containing caption data and corresponding image paths.
- def _gen(self, data, is_traini... | Implement the Python class `InputManager_Radix` described below.
Class description:
Input Manager object for Radix-token models.
Method signatures and docstrings:
- def __init__(self, config, is_inference=False): Loads the h5 file containing caption data and corresponding image paths.
- def _gen(self, data, is_traini... | 73165e0aac2816e89732571814f978801958e1ac | <|skeleton|>
class InputManager_Radix:
"""Input Manager object for Radix-token models."""
def __init__(self, config, is_inference=False):
"""Loads the h5 file containing caption data and corresponding image paths."""
<|body_0|>
def _gen(self, data, is_training=True):
"""Generator f... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InputManager_Radix:
"""Input Manager object for Radix-token models."""
def __init__(self, config, is_inference=False):
"""Loads the h5 file containing caption data and corresponding image paths."""
super(InputManager_Radix, self).__init__(config, is_inference)
c = self.config
... | the_stack_v2_python_sparse | common/inputs/manager_image_caption.py | jiahuei/COMIC-Compact-Image-Captioning-with-Attention | train | 10 |
6632c6b6b8e14c40a7a79ca64b051a26d327a9a5 | [
"if request.user.is_authenticated and request.user.is_administrator_of_search_pages:\n return True\nreturn super().has_add_permission(request, obj)",
"if request.user.is_authenticated and request.user.is_administrator_of_search_pages:\n return True\nreturn super().has_delete_permission(request, obj)"
] | <|body_start_0|>
if request.user.is_authenticated and request.user.is_administrator_of_search_pages:
return True
return super().has_add_permission(request, obj)
<|end_body_0|>
<|body_start_1|>
if request.user.is_authenticated and request.user.is_administrator_of_search_pages:
... | WithFullPermission | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WithFullPermission:
def has_add_permission(self, request, obj=None):
"""Grant permission to authenticated users that are administrator of search pages."""
<|body_0|>
def has_delete_permission(self, request, obj=None):
"""Grant permission to authenticated users that a... | stack_v2_sparse_classes_10k_train_001462 | 1,718 | permissive | [
{
"docstring": "Grant permission to authenticated users that are administrator of search pages.",
"name": "has_add_permission",
"signature": "def has_add_permission(self, request, obj=None)"
},
{
"docstring": "Grant permission to authenticated users that are administrator of search pages.",
... | 2 | null | Implement the Python class `WithFullPermission` described below.
Class description:
Implement the WithFullPermission class.
Method signatures and docstrings:
- def has_add_permission(self, request, obj=None): Grant permission to authenticated users that are administrator of search pages.
- def has_delete_permission(s... | Implement the Python class `WithFullPermission` described below.
Class description:
Implement the WithFullPermission class.
Method signatures and docstrings:
- def has_add_permission(self, request, obj=None): Grant permission to authenticated users that are administrator of search pages.
- def has_delete_permission(s... | af9f6e6e8b1918363793fbf291f3518ef1454169 | <|skeleton|>
class WithFullPermission:
def has_add_permission(self, request, obj=None):
"""Grant permission to authenticated users that are administrator of search pages."""
<|body_0|>
def has_delete_permission(self, request, obj=None):
"""Grant permission to authenticated users that a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WithFullPermission:
def has_add_permission(self, request, obj=None):
"""Grant permission to authenticated users that are administrator of search pages."""
if request.user.is_authenticated and request.user.is_administrator_of_search_pages:
return True
return super().has_add_... | the_stack_v2_python_sparse | src/admin_lite/mixins.py | MTES-MCT/aides-territoires | train | 21 | |
bf0fcf389638ae57744b106e826e41758ad0b8a9 | [
"argument = lab04.eratosthenes(1)\nexpected = []\nself.assertEqual(expected, argument, 'There are no prime numbers in the list.')",
"argument = lab04.eratosthenes(2)\nexpected = [2]\nself.assertEqual(expected, argument, 'The list contains one prime number.')",
"argument = lab04.eratosthenes(31)\nexpected = [2, ... | <|body_start_0|>
argument = lab04.eratosthenes(1)
expected = []
self.assertEqual(expected, argument, 'There are no prime numbers in the list.')
<|end_body_0|>
<|body_start_1|>
argument = lab04.eratosthenes(2)
expected = [2]
self.assertEqual(expected, argument, 'The list ... | Test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test:
def test_smallest_bound(self):
"""Test the upper bound of one."""
<|body_0|>
def test_list_of_one(self):
"""Test the upper bound of two."""
<|body_1|>
def test_list_of_several(self):
"""Test an upper bound that returns a list of many intege... | stack_v2_sparse_classes_10k_train_001463 | 1,187 | no_license | [
{
"docstring": "Test the upper bound of one.",
"name": "test_smallest_bound",
"signature": "def test_smallest_bound(self)"
},
{
"docstring": "Test the upper bound of two.",
"name": "test_list_of_one",
"signature": "def test_list_of_one(self)"
},
{
"docstring": "Test an upper boun... | 4 | stack_v2_sparse_classes_30k_train_003967 | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def test_smallest_bound(self): Test the upper bound of one.
- def test_list_of_one(self): Test the upper bound of two.
- def test_list_of_several(self): Test an upper bound that returns ... | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def test_smallest_bound(self): Test the upper bound of one.
- def test_list_of_one(self): Test the upper bound of two.
- def test_list_of_several(self): Test an upper bound that returns ... | a7014be9881ec4a2d0b332fef353a29f5dbb05de | <|skeleton|>
class Test:
def test_smallest_bound(self):
"""Test the upper bound of one."""
<|body_0|>
def test_list_of_one(self):
"""Test the upper bound of two."""
<|body_1|>
def test_list_of_several(self):
"""Test an upper bound that returns a list of many intege... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test:
def test_smallest_bound(self):
"""Test the upper bound of one."""
argument = lab04.eratosthenes(1)
expected = []
self.assertEqual(expected, argument, 'There are no prime numbers in the list.')
def test_list_of_one(self):
"""Test the upper bound of two."""
... | the_stack_v2_python_sparse | Lab04/test_eratosthenes.py | ronliang6/A01199458_1510 | train | 0 | |
e39d095d412449dda0330fe53d079656088c9ea5 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn DetectedApp()",
"from .detected_app_platform_type import DetectedAppPlatformType\nfrom .entity import Entity\nfrom .managed_device import ManagedDevice\nfrom .detected_app_platform_type import DetectedAppPlatformType\nfrom .entity impo... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return DetectedApp()
<|end_body_0|>
<|body_start_1|>
from .detected_app_platform_type import DetectedAppPlatformType
from .entity import Entity
from .managed_device import ManagedDevice... | A managed or unmanaged app that is installed on a managed device. Unmanaged apps will only appear for devices marked as corporate owned. | DetectedApp | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DetectedApp:
"""A managed or unmanaged app that is installed on a managed device. Unmanaged apps will only appear for devices marked as corporate owned."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DetectedApp:
"""Creates a new instance of the appro... | stack_v2_sparse_classes_10k_train_001464 | 4,234 | 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: DetectedApp",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(p... | 3 | null | Implement the Python class `DetectedApp` described below.
Class description:
A managed or unmanaged app that is installed on a managed device. Unmanaged apps will only appear for devices marked as corporate owned.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=... | Implement the Python class `DetectedApp` described below.
Class description:
A managed or unmanaged app that is installed on a managed device. Unmanaged apps will only appear for devices marked as corporate owned.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class DetectedApp:
"""A managed or unmanaged app that is installed on a managed device. Unmanaged apps will only appear for devices marked as corporate owned."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DetectedApp:
"""Creates a new instance of the appro... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DetectedApp:
"""A managed or unmanaged app that is installed on a managed device. Unmanaged apps will only appear for devices marked as corporate owned."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DetectedApp:
"""Creates a new instance of the appropriate class ... | the_stack_v2_python_sparse | msgraph/generated/models/detected_app.py | microsoftgraph/msgraph-sdk-python | train | 135 |
eb38ee0b3754ba5cbda846192e86317722f13909 | [
"self.match_labels = match_labels\nself.name = name\nself.service_name = service_name",
"if dictionary is None:\n return None\nmatch_labels = None\nif dictionary.get('matchLabels') != None:\n match_labels = list()\n for structure in dictionary.get('matchLabels'):\n match_labels.append(cohesity_man... | <|body_start_0|>
self.match_labels = match_labels
self.name = name
self.service_name = service_name
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
match_labels = None
if dictionary.get('matchLabels') != None:
match_labels = lis... | Implementation of the 'LabelSelector' model. TODO: type description here. Attributes: match_labels (list of LabelSelector_MatchLabelsEntry): This field is an object which consists of key-value pairs of all labels that must be matched by the selector name (string): Select all objects which have a label with key : "name"... | LabelSelector | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LabelSelector:
"""Implementation of the 'LabelSelector' model. TODO: type description here. Attributes: match_labels (list of LabelSelector_MatchLabelsEntry): This field is an object which consists of key-value pairs of all labels that must be matched by the selector name (string): Select all obj... | stack_v2_sparse_classes_10k_train_001465 | 2,409 | permissive | [
{
"docstring": "Constructor for the LabelSelector class",
"name": "__init__",
"signature": "def __init__(self, match_labels=None, name=None, service_name=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of th... | 2 | stack_v2_sparse_classes_30k_train_000013 | Implement the Python class `LabelSelector` described below.
Class description:
Implementation of the 'LabelSelector' model. TODO: type description here. Attributes: match_labels (list of LabelSelector_MatchLabelsEntry): This field is an object which consists of key-value pairs of all labels that must be matched by the... | Implement the Python class `LabelSelector` described below.
Class description:
Implementation of the 'LabelSelector' model. TODO: type description here. Attributes: match_labels (list of LabelSelector_MatchLabelsEntry): This field is an object which consists of key-value pairs of all labels that must be matched by the... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class LabelSelector:
"""Implementation of the 'LabelSelector' model. TODO: type description here. Attributes: match_labels (list of LabelSelector_MatchLabelsEntry): This field is an object which consists of key-value pairs of all labels that must be matched by the selector name (string): Select all obj... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LabelSelector:
"""Implementation of the 'LabelSelector' model. TODO: type description here. Attributes: match_labels (list of LabelSelector_MatchLabelsEntry): This field is an object which consists of key-value pairs of all labels that must be matched by the selector name (string): Select all objects which ha... | the_stack_v2_python_sparse | cohesity_management_sdk/models/label_selector.py | cohesity/management-sdk-python | train | 24 |
e39bfbcf338391d9bfdc489a0db6ac063155827d | [
"super(ActionTypeHead, self).__init__()\nself.cfg = cfg\nself.act = build_activation(cfg.activation)\nself.project = fc_block(cfg.input_dim, cfg.res_dim)\nblocks = [ResFCBlock(cfg.res_dim, self.act, cfg.norm_type) for _ in range(cfg.res_num)]\nself.res = nn.Sequential(*blocks)\nself.weight_norm = cfg.get('weight_no... | <|body_start_0|>
super(ActionTypeHead, self).__init__()
self.cfg = cfg
self.act = build_activation(cfg.activation)
self.project = fc_block(cfg.input_dim, cfg.res_dim)
blocks = [ResFCBlock(cfg.res_dim, self.act, cfg.norm_type) for _ in range(cfg.res_num)]
self.res = nn.Seq... | Overview: The action type head uses lstm_output and scalar_context to get action_type_logits, action_type and its autoregressive_embedding. Interface: __init__, forward | ActionTypeHead | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActionTypeHead:
"""Overview: The action type head uses lstm_output and scalar_context to get action_type_logits, action_type and its autoregressive_embedding. Interface: __init__, forward"""
def __init__(self, cfg):
"""Overview: initialize architect. Arguments: - cfg (:obj:`dict`): h... | stack_v2_sparse_classes_10k_train_001466 | 5,506 | permissive | [
{
"docstring": "Overview: initialize architect. Arguments: - cfg (:obj:`dict`): head architecture definition",
"name": "__init__",
"signature": "def __init__(self, cfg)"
},
{
"docstring": "Overview: This head embeds lstm_output into a 1D tensor of size 256, passes it through 16 ResBlocks with la... | 2 | stack_v2_sparse_classes_30k_train_006344 | Implement the Python class `ActionTypeHead` described below.
Class description:
Overview: The action type head uses lstm_output and scalar_context to get action_type_logits, action_type and its autoregressive_embedding. Interface: __init__, forward
Method signatures and docstrings:
- def __init__(self, cfg): Overview... | Implement the Python class `ActionTypeHead` described below.
Class description:
Overview: The action type head uses lstm_output and scalar_context to get action_type_logits, action_type and its autoregressive_embedding. Interface: __init__, forward
Method signatures and docstrings:
- def __init__(self, cfg): Overview... | 09d507c412235a2f0cf9c0b3485ec9ed15fb6421 | <|skeleton|>
class ActionTypeHead:
"""Overview: The action type head uses lstm_output and scalar_context to get action_type_logits, action_type and its autoregressive_embedding. Interface: __init__, forward"""
def __init__(self, cfg):
"""Overview: initialize architect. Arguments: - cfg (:obj:`dict`): h... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ActionTypeHead:
"""Overview: The action type head uses lstm_output and scalar_context to get action_type_logits, action_type and its autoregressive_embedding. Interface: __init__, forward"""
def __init__(self, cfg):
"""Overview: initialize architect. Arguments: - cfg (:obj:`dict`): head architect... | the_stack_v2_python_sparse | distar/model/alphastar/head/action_type_head.py | LFhase/DI-star | train | 1 |
f8867f2d69751f84fa1d61451ca1d884430197ea | [
"self.fn = ''\nself.pt_id = 'X X X X' + ' ' * 73\nself.rec_info = 'Startdate X X X X' + ' ' * 63\nself.start_date = '01.01.01'\nself.start_time = '01.01.01'\nself.py_h = 2\nself.pyedf_header = {'technician': '002', 'recording_additional': '', 'patientname': '', 'patient_additional': '', 'patientcode': '', 'equipmen... | <|body_start_0|>
self.fn = ''
self.pt_id = 'X X X X' + ' ' * 73
self.rec_info = 'Startdate X X X X' + ' ' * 63
self.start_date = '01.01.01'
self.start_time = '01.01.01'
self.py_h = 2
self.pyedf_header = {'technician': '002', 'recording_additional': '', 'patientnam... | Data structure for holding information for saving to edf namely the anonymized header | SaveEdfInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaveEdfInfo:
"""Data structure for holding information for saving to edf namely the anonymized header"""
def __init__(self):
"""Header parameters set to default values"""
<|body_0|>
def convert_to_header(self):
"""Converts from native EDF format: self.data.pt_id ... | stack_v2_sparse_classes_10k_train_001467 | 3,114 | no_license | [
{
"docstring": "Header parameters set to default values",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Converts from native EDF format: self.data.pt_id = file[8:88].decode(\"utf-8\") self.data.rec_info = file[88:168].decode(\"utf-8\") self.data.start_date = file[168:1... | 2 | stack_v2_sparse_classes_30k_train_003348 | Implement the Python class `SaveEdfInfo` described below.
Class description:
Data structure for holding information for saving to edf namely the anonymized header
Method signatures and docstrings:
- def __init__(self): Header parameters set to default values
- def convert_to_header(self): Converts from native EDF for... | Implement the Python class `SaveEdfInfo` described below.
Class description:
Data structure for holding information for saving to edf namely the anonymized header
Method signatures and docstrings:
- def __init__(self): Header parameters set to default values
- def convert_to_header(self): Converts from native EDF for... | 099920716fdab891592ccc7f324445f088827298 | <|skeleton|>
class SaveEdfInfo:
"""Data structure for holding information for saving to edf namely the anonymized header"""
def __init__(self):
"""Header parameters set to default values"""
<|body_0|>
def convert_to_header(self):
"""Converts from native EDF format: self.data.pt_id ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SaveEdfInfo:
"""Data structure for holding information for saving to edf namely the anonymized header"""
def __init__(self):
"""Header parameters set to default values"""
self.fn = ''
self.pt_id = 'X X X X' + ' ' * 73
self.rec_info = 'Startdate X X X X' + ' ' * 63
... | the_stack_v2_python_sparse | visualization/edf_saving/saveEdf_info.py | jcraley/jhu-eeg | train | 2 |
a82b954550123140dc0dab113db482e303d3ecf6 | [
"self.maxEpochs = maxEpochs\nself.initAlpha = initAlpha\nself.power = power\npass",
"decay = (1 - epoch / float(self.maxEpochs)) ** self.power\nalpha = self.initAlpha * decay\nreturn float(alpha)"
] | <|body_start_0|>
self.maxEpochs = maxEpochs
self.initAlpha = initAlpha
self.power = power
pass
<|end_body_0|>
<|body_start_1|>
decay = (1 - epoch / float(self.maxEpochs)) ** self.power
alpha = self.initAlpha * decay
return float(alpha)
<|end_body_1|>
| PolynomialDecay | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PolynomialDecay:
def __init__(self, maxEpochs=100, initAlpha=0.01, power=1.0):
"""- initialize polynomial learning rate decay schedule with 3 args" - maxEpochs = # of training epochs; - initAlpha = initial learning rate; - power = power/exponent of the polynomial; linear if power=1.0, qu... | stack_v2_sparse_classes_10k_train_001468 | 2,358 | no_license | [
{
"docstring": "- initialize polynomial learning rate decay schedule with 3 args\" - maxEpochs = # of training epochs; - initAlpha = initial learning rate; - power = power/exponent of the polynomial; linear if power=1.0, quadratic if power=2.0, etc.",
"name": "__init__",
"signature": "def __init__(self,... | 2 | stack_v2_sparse_classes_30k_train_004356 | Implement the Python class `PolynomialDecay` described below.
Class description:
Implement the PolynomialDecay class.
Method signatures and docstrings:
- def __init__(self, maxEpochs=100, initAlpha=0.01, power=1.0): - initialize polynomial learning rate decay schedule with 3 args" - maxEpochs = # of training epochs; ... | Implement the Python class `PolynomialDecay` described below.
Class description:
Implement the PolynomialDecay class.
Method signatures and docstrings:
- def __init__(self, maxEpochs=100, initAlpha=0.01, power=1.0): - initialize polynomial learning rate decay schedule with 3 args" - maxEpochs = # of training epochs; ... | ebf5edb4d71f81dd9d8478c6251e97c097d189c3 | <|skeleton|>
class PolynomialDecay:
def __init__(self, maxEpochs=100, initAlpha=0.01, power=1.0):
"""- initialize polynomial learning rate decay schedule with 3 args" - maxEpochs = # of training epochs; - initAlpha = initial learning rate; - power = power/exponent of the polynomial; linear if power=1.0, qu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PolynomialDecay:
def __init__(self, maxEpochs=100, initAlpha=0.01, power=1.0):
"""- initialize polynomial learning rate decay schedule with 3 args" - maxEpochs = # of training epochs; - initAlpha = initial learning rate; - power = power/exponent of the polynomial; linear if power=1.0, quadratic if pow... | the_stack_v2_python_sparse | callbacks/learning_rate_scheduler.py | zlyin/Orca | train | 0 | |
43a91a5f9ccf7006d4cbbc4cf9333c00e92d4cac | [
"self.bands = []\nself.r95 = []\nfor bandlike in roi.selected:\n band = bandlike.band\n if band.emin < emin[band.event_type]:\n continue\n self.r95.append(np.radians(band.psf.inverse_integral(95, on_axis=False)))\n self.bands.append(band)",
"sd = skydir or SkyDir(Hep3Vector(v[0], v[1], v[2]))\n... | <|body_start_0|>
self.bands = []
self.r95 = []
for bandlike in roi.selected:
band = bandlike.band
if band.emin < emin[band.event_type]:
continue
self.r95.append(np.radians(band.psf.inverse_integral(95, on_axis=False)))
self.bands.ap... | Implement a SkyFunction that returns KDE data for a given ROI | KdeMap | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KdeMap:
"""Implement a SkyFunction that returns KDE data for a given ROI"""
def __init__(self, roi, emin=[500, 1000], **kwargs):
"""roi: an ROIstat object emin: list of two minimum energies"""
<|body_0|>
def __call__(self, v, skydir=None):
"""copied from roi_tsma... | stack_v2_sparse_classes_10k_train_001469 | 24,274 | permissive | [
{
"docstring": "roi: an ROIstat object emin: list of two minimum energies",
"name": "__init__",
"signature": "def __init__(self, roi, emin=[500, 1000], **kwargs)"
},
{
"docstring": "copied from roi_tsmap.HealpixKDEMap",
"name": "__call__",
"signature": "def __call__(self, v, skydir=None)... | 2 | stack_v2_sparse_classes_30k_train_002648 | Implement the Python class `KdeMap` described below.
Class description:
Implement a SkyFunction that returns KDE data for a given ROI
Method signatures and docstrings:
- def __init__(self, roi, emin=[500, 1000], **kwargs): roi: an ROIstat object emin: list of two minimum energies
- def __call__(self, v, skydir=None):... | Implement the Python class `KdeMap` described below.
Class description:
Implement a SkyFunction that returns KDE data for a given ROI
Method signatures and docstrings:
- def __init__(self, roi, emin=[500, 1000], **kwargs): roi: an ROIstat object emin: list of two minimum energies
- def __call__(self, v, skydir=None):... | edcdc696c3300e2f26ff3efa92a1bd9790074247 | <|skeleton|>
class KdeMap:
"""Implement a SkyFunction that returns KDE data for a given ROI"""
def __init__(self, roi, emin=[500, 1000], **kwargs):
"""roi: an ROIstat object emin: list of two minimum energies"""
<|body_0|>
def __call__(self, v, skydir=None):
"""copied from roi_tsma... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KdeMap:
"""Implement a SkyFunction that returns KDE data for a given ROI"""
def __init__(self, roi, emin=[500, 1000], **kwargs):
"""roi: an ROIstat object emin: list of two minimum energies"""
self.bands = []
self.r95 = []
for bandlike in roi.selected:
band = b... | the_stack_v2_python_sparse | python/uw/like2/maps.py | fermi-lat/pointlike | train | 1 |
968b1b0349ce74e58af2193d7743ea3b4aafa6a4 | [
"def reverse(nl: ListNode):\n if nl is None or nl.next is None:\n return (nl, nl)\n hnode, tnode = reverse(nl.next)\n nl.next = None\n tnode.next = nl\n return (hnode, nl)\nret, _ = reverse(head)\nreturn ret",
"pre = None\nwhile head:\n pre, head.next, head = (head, pre, head.next)\nretur... | <|body_start_0|>
def reverse(nl: ListNode):
if nl is None or nl.next is None:
return (nl, nl)
hnode, tnode = reverse(nl.next)
nl.next = None
tnode.next = nl
return (hnode, nl)
ret, _ = reverse(head)
return ret
<|end_body... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList2(self, head: Optional[ListNode]) -> Optional[ListNode]:
"""20210907 Updated with recursively 28 / 28 test cases passed. Status: Accepted Runtime: 40 ms Memory Usage: 20.3 MB :param head: :return:"""
<|body_0|>
def reverseList(self, head: ListNode) -... | stack_v2_sparse_classes_10k_train_001470 | 1,605 | permissive | [
{
"docstring": "20210907 Updated with recursively 28 / 28 test cases passed. Status: Accepted Runtime: 40 ms Memory Usage: 20.3 MB :param head: :return:",
"name": "reverseList2",
"signature": "def reverseList2(self, head: Optional[ListNode]) -> Optional[ListNode]"
},
{
"docstring": "2022-08-23 :... | 2 | stack_v2_sparse_classes_30k_train_005584 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList2(self, head: Optional[ListNode]) -> Optional[ListNode]: 20210907 Updated with recursively 28 / 28 test cases passed. Status: Accepted Runtime: 40 ms Memory Usage:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList2(self, head: Optional[ListNode]) -> Optional[ListNode]: 20210907 Updated with recursively 28 / 28 test cases passed. Status: Accepted Runtime: 40 ms Memory Usage:... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def reverseList2(self, head: Optional[ListNode]) -> Optional[ListNode]:
"""20210907 Updated with recursively 28 / 28 test cases passed. Status: Accepted Runtime: 40 ms Memory Usage: 20.3 MB :param head: :return:"""
<|body_0|>
def reverseList(self, head: ListNode) -... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList2(self, head: Optional[ListNode]) -> Optional[ListNode]:
"""20210907 Updated with recursively 28 / 28 test cases passed. Status: Accepted Runtime: 40 ms Memory Usage: 20.3 MB :param head: :return:"""
def reverse(nl: ListNode):
if nl is None or nl.next is No... | the_stack_v2_python_sparse | src/206-ReverseLinkedList.py | Jiezhi/myleetcode | train | 1 | |
8dcb13c4188770ec1f8a0cfb4ca8f75fba1a67cb | [
"next_index = next_object_key(self)\nnew_section = Section()\nnew_section.load_section_from_library(path, material_id)\nsetattr(self, str(next_index), new_section)\nreturn next_index",
"next_index = next_object_key(self)\nnew_section = Section()\nnew_section.load_custom_from_library(name, material_id)\nsetattr(se... | <|body_start_0|>
next_index = next_object_key(self)
new_section = Section()
new_section.load_section_from_library(path, material_id)
setattr(self, str(next_index), new_section)
return next_index
<|end_body_0|>
<|body_start_1|>
next_index = next_object_key(self)
n... | Creates an instance of the SkyCiv Sections class. | Sections | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sections:
"""Creates an instance of the SkyCiv Sections class."""
def add_library_section(self, path: list[str], material_id: int) -> int:
"""Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an array of 4 strings (see example below). It is the path o... | stack_v2_sparse_classes_10k_train_001471 | 2,588 | permissive | [
{
"docstring": "Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an array of 4 strings (see example below). It is the path of the section in the section library, obtained by inspection from within SkyCiv Section Builder or by attaining the library tree via S3D.SB.getLibraryTree... | 3 | stack_v2_sparse_classes_30k_train_007027 | Implement the Python class `Sections` described below.
Class description:
Creates an instance of the SkyCiv Sections class.
Method signatures and docstrings:
- def add_library_section(self, path: list[str], material_id: int) -> int: Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an... | Implement the Python class `Sections` described below.
Class description:
Creates an instance of the SkyCiv Sections class.
Method signatures and docstrings:
- def add_library_section(self, path: list[str], material_id: int) -> int: Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an... | 1cf3dad7f8d451760df02886df41684add72a4eb | <|skeleton|>
class Sections:
"""Creates an instance of the SkyCiv Sections class."""
def add_library_section(self, path: list[str], material_id: int) -> int:
"""Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an array of 4 strings (see example below). It is the path o... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Sections:
"""Creates an instance of the SkyCiv Sections class."""
def add_library_section(self, path: list[str], material_id: int) -> int:
"""Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an array of 4 strings (see example below). It is the path of the section... | the_stack_v2_python_sparse | src/skyciv/classes/model/components/sections/sections.py | osasanchezme/skyciv-pip | train | 0 |
4d733c4aefc460de5b36fbc0fb046509e030af71 | [
"alloy_type = alloy_model.AlloyType.objects.only('id', 'type').filter(is_delete=False, id=alloy_type_id)\nif alloy_type:\n data = {'alloy_type': alloy_type}\n return render(request, 'admin/alloy/alloy_type_edit.html', context=data)\nelse:\n logger.info('id为<{}>合金类型不存在'.format(alloy_type_id))\n return to... | <|body_start_0|>
alloy_type = alloy_model.AlloyType.objects.only('id', 'type').filter(is_delete=False, id=alloy_type_id)
if alloy_type:
data = {'alloy_type': alloy_type}
return render(request, 'admin/alloy/alloy_type_edit.html', context=data)
else:
logger.info... | 合金类型修改 | AlloyTypeEdit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlloyTypeEdit:
"""合金类型修改"""
def get(self, request, alloy_type_id):
"""指定合金类型查询展示 :param request: :param alloy_type_id: :return:"""
<|body_0|>
def put(self, request, alloy_type_id):
"""指定合金类型修改 :param request: :param alloy_type_id: :return:"""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_001472 | 11,849 | no_license | [
{
"docstring": "指定合金类型查询展示 :param request: :param alloy_type_id: :return:",
"name": "get",
"signature": "def get(self, request, alloy_type_id)"
},
{
"docstring": "指定合金类型修改 :param request: :param alloy_type_id: :return:",
"name": "put",
"signature": "def put(self, request, alloy_type_id)"... | 3 | stack_v2_sparse_classes_30k_train_003481 | Implement the Python class `AlloyTypeEdit` described below.
Class description:
合金类型修改
Method signatures and docstrings:
- def get(self, request, alloy_type_id): 指定合金类型查询展示 :param request: :param alloy_type_id: :return:
- def put(self, request, alloy_type_id): 指定合金类型修改 :param request: :param alloy_type_id: :return:
- ... | Implement the Python class `AlloyTypeEdit` described below.
Class description:
合金类型修改
Method signatures and docstrings:
- def get(self, request, alloy_type_id): 指定合金类型查询展示 :param request: :param alloy_type_id: :return:
- def put(self, request, alloy_type_id): 指定合金类型修改 :param request: :param alloy_type_id: :return:
- ... | 063332d2a5e2ddabf800817f02074b4f5c162ade | <|skeleton|>
class AlloyTypeEdit:
"""合金类型修改"""
def get(self, request, alloy_type_id):
"""指定合金类型查询展示 :param request: :param alloy_type_id: :return:"""
<|body_0|>
def put(self, request, alloy_type_id):
"""指定合金类型修改 :param request: :param alloy_type_id: :return:"""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AlloyTypeEdit:
"""合金类型修改"""
def get(self, request, alloy_type_id):
"""指定合金类型查询展示 :param request: :param alloy_type_id: :return:"""
alloy_type = alloy_model.AlloyType.objects.only('id', 'type').filter(is_delete=False, id=alloy_type_id)
if alloy_type:
data = {'alloy_type... | the_stack_v2_python_sparse | sfs/apps/alloy/views.py | Hx-someone/sfs-1 | train | 0 |
0949634a1477577fdaf6639bf57aa9672c1c9116 | [
"if not isinstance(config, KubeflowV2DagRunnerConfig):\n raise TypeError('config must be type of KubeflowV2DagRunnerConfig.')\nsuper().__init__()\nself._config = config\nself._output_dir = output_dir or os.getcwd()\nself._output_filename = output_filename or 'pipeline.json'\nself._exit_handler = None",
"if not... | <|body_start_0|>
if not isinstance(config, KubeflowV2DagRunnerConfig):
raise TypeError('config must be type of KubeflowV2DagRunnerConfig.')
super().__init__()
self._config = config
self._output_dir = output_dir or os.getcwd()
self._output_filename = output_filename or... | Kubeflow V2 pipeline runner (currently for managed pipelines). Builds a pipeline job spec in json format based on TFX pipeline DSL object. | KubeflowV2DagRunner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KubeflowV2DagRunner:
"""Kubeflow V2 pipeline runner (currently for managed pipelines). Builds a pipeline job spec in json format based on TFX pipeline DSL object."""
def __init__(self, config: KubeflowV2DagRunnerConfig, output_dir: Optional[str]=None, output_filename: Optional[str]=None):
... | stack_v2_sparse_classes_10k_train_001473 | 8,534 | permissive | [
{
"docstring": "Constructs an KubeflowV2DagRunner for compiling pipelines. Args: config: An KubeflowV2DagRunnerConfig object to specify runtime configuration when running the pipeline in Kubeflow. output_dir: An optional output directory into which to output the pipeline definition files. Defaults to the curren... | 3 | null | Implement the Python class `KubeflowV2DagRunner` described below.
Class description:
Kubeflow V2 pipeline runner (currently for managed pipelines). Builds a pipeline job spec in json format based on TFX pipeline DSL object.
Method signatures and docstrings:
- def __init__(self, config: KubeflowV2DagRunnerConfig, outp... | Implement the Python class `KubeflowV2DagRunner` described below.
Class description:
Kubeflow V2 pipeline runner (currently for managed pipelines). Builds a pipeline job spec in json format based on TFX pipeline DSL object.
Method signatures and docstrings:
- def __init__(self, config: KubeflowV2DagRunnerConfig, outp... | 1b328504fa08a70388691e4072df76f143631325 | <|skeleton|>
class KubeflowV2DagRunner:
"""Kubeflow V2 pipeline runner (currently for managed pipelines). Builds a pipeline job spec in json format based on TFX pipeline DSL object."""
def __init__(self, config: KubeflowV2DagRunnerConfig, output_dir: Optional[str]=None, output_filename: Optional[str]=None):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KubeflowV2DagRunner:
"""Kubeflow V2 pipeline runner (currently for managed pipelines). Builds a pipeline job spec in json format based on TFX pipeline DSL object."""
def __init__(self, config: KubeflowV2DagRunnerConfig, output_dir: Optional[str]=None, output_filename: Optional[str]=None):
"""Cons... | the_stack_v2_python_sparse | tfx/orchestration/kubeflow/v2/kubeflow_v2_dag_runner.py | tensorflow/tfx | train | 2,116 |
ba055b1214ab013bece7d277b8c7ae461caac1e1 | [
"Node.__init__(self)\nself.dim = dim\nif init:\n self.value = np.mat(np.random.normal(0, 0.001, (self.dim, 1)))\nself.trainable = trainable",
"assert isinstance(value, np.matrix) and value.shape == (self.dim, 1)\nself.reset_value()\nself.value = value"
] | <|body_start_0|>
Node.__init__(self)
self.dim = dim
if init:
self.value = np.mat(np.random.normal(0, 0.001, (self.dim, 1)))
self.trainable = trainable
<|end_body_0|>
<|body_start_1|>
assert isinstance(value, np.matrix) and value.shape == (self.dim, 1)
self.re... | 变（向）量节点 | Variable | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Variable:
"""变（向）量节点"""
def __init__(self, dim, init=False, trainable=True):
"""变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识"""
<|body_0|>
def set_value(self, value):
"""为变量赋值"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Node.__init__(self)
se... | stack_v2_sparse_classes_10k_train_001474 | 6,904 | permissive | [
{
"docstring": "变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识",
"name": "__init__",
"signature": "def __init__(self, dim, init=False, trainable=True)"
},
{
"docstring": "为变量赋值",
"name": "set_value",
"signature": "def set_value(self, value)"
}
] | 2 | null | Implement the Python class `Variable` described below.
Class description:
变（向）量节点
Method signatures and docstrings:
- def __init__(self, dim, init=False, trainable=True): 变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识
- def set_value(self, value): 为变量赋值 | Implement the Python class `Variable` described below.
Class description:
变（向）量节点
Method signatures and docstrings:
- def __init__(self, dim, init=False, trainable=True): 变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识
- def set_value(self, value): 为变量赋值
<|skeleton|>
class Variable:
"""变（向）量节点"""
def __init__(self, dim... | b4a9ddcc2820fd0e3c9bbd81c26a8fa35f348c23 | <|skeleton|>
class Variable:
"""变（向）量节点"""
def __init__(self, dim, init=False, trainable=True):
"""变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识"""
<|body_0|>
def set_value(self, value):
"""为变量赋值"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Variable:
"""变（向）量节点"""
def __init__(self, dim, init=False, trainable=True):
"""变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识"""
Node.__init__(self)
self.dim = dim
if init:
self.value = np.mat(np.random.normal(0, 0.001, (self.dim, 1)))
self.trainable = trainable
... | the_stack_v2_python_sparse | lang/programming/python/深入理解神经网络：从逻辑回归到CNN/neural_network-neural_network_code-master/neural_network_code/第 8 章 计算图/node.py | dlxj/doc | train | 10 |
d954c4a82d03bb04604e78b48e43504363c6d5d6 | [
"slow = 0\nwhile slow < len(nums) and nums[slow] != 0:\n slow += 1\nfast = slow + 1\nwhile fast < len(nums):\n if nums[fast]:\n nums[slow], nums[fast] = (nums[fast], 0)\n slow += 1\n fast += 1\nreturn nums",
"tail = 0\nfor i in range(len(nums)):\n if nums[i] != 0:\n nums[tail], nu... | <|body_start_0|>
slow = 0
while slow < len(nums) and nums[slow] != 0:
slow += 1
fast = slow + 1
while fast < len(nums):
if nums[fast]:
nums[slow], nums[fast] = (nums[fast], 0)
slow += 1
fast += 1
return nums
<|en... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def moveZeroes(self, nums):
"""time O(n) space O(1) :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def moveZeroes_precisetomine(self, nums):
"""time O(n) space O(1) :type nums: List[int] :rtype: None D... | stack_v2_sparse_classes_10k_train_001475 | 1,563 | no_license | [
{
"docstring": "time O(n) space O(1) :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.",
"name": "moveZeroes",
"signature": "def moveZeroes(self, nums)"
},
{
"docstring": "time O(n) space O(1) :type nums: List[int] :rtype: None Do not return anything, modif... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveZeroes(self, nums): time O(n) space O(1) :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.
- def moveZeroes_precisetomine(self, num... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveZeroes(self, nums): time O(n) space O(1) :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.
- def moveZeroes_precisetomine(self, num... | 85f71621c54f6b0029f3a2746f022f89dd7419d9 | <|skeleton|>
class Solution:
def moveZeroes(self, nums):
"""time O(n) space O(1) :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def moveZeroes_precisetomine(self, nums):
"""time O(n) space O(1) :type nums: List[int] :rtype: None D... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def moveZeroes(self, nums):
"""time O(n) space O(1) :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
slow = 0
while slow < len(nums) and nums[slow] != 0:
slow += 1
fast = slow + 1
while fast < len(nums):
... | the_stack_v2_python_sparse | LeetCode/Array/283_move_zeros.py | XyK0907/for_work | train | 0 | |
5b3d31405bf7e32431b5a43d8a6822a0bc4d0007 | [
"request = self.context.get('request')\ndata['poster'] = request.user\nreturn validate_complete_address(data)",
"response = super().to_representation(instance)\nresponse['poster'] = {'id': instance.poster.id}\nreturn response"
] | <|body_start_0|>
request = self.context.get('request')
data['poster'] = request.user
return validate_complete_address(data)
<|end_body_0|>
<|body_start_1|>
response = super().to_representation(instance)
response['poster'] = {'id': instance.poster.id}
return response
<|en... | Serializer handles creation of a new listing | CreateListingSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateListingSerializer:
"""Serializer handles creation of a new listing"""
def validate(self, data):
"""Validate creation of new listing - Check complete address listing is valid"""
<|body_0|>
def to_representation(self, instance):
"""Return only id of poster wh... | stack_v2_sparse_classes_10k_train_001476 | 3,983 | no_license | [
{
"docstring": "Validate creation of new listing - Check complete address listing is valid",
"name": "validate",
"signature": "def validate(self, data)"
},
{
"docstring": "Return only id of poster when creating listing",
"name": "to_representation",
"signature": "def to_representation(se... | 2 | stack_v2_sparse_classes_30k_train_000471 | Implement the Python class `CreateListingSerializer` described below.
Class description:
Serializer handles creation of a new listing
Method signatures and docstrings:
- def validate(self, data): Validate creation of new listing - Check complete address listing is valid
- def to_representation(self, instance): Return... | Implement the Python class `CreateListingSerializer` described below.
Class description:
Serializer handles creation of a new listing
Method signatures and docstrings:
- def validate(self, data): Validate creation of new listing - Check complete address listing is valid
- def to_representation(self, instance): Return... | 1f2c8c232372de6a40089c8b867ce1798d2296c7 | <|skeleton|>
class CreateListingSerializer:
"""Serializer handles creation of a new listing"""
def validate(self, data):
"""Validate creation of new listing - Check complete address listing is valid"""
<|body_0|>
def to_representation(self, instance):
"""Return only id of poster wh... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CreateListingSerializer:
"""Serializer handles creation of a new listing"""
def validate(self, data):
"""Validate creation of new listing - Check complete address listing is valid"""
request = self.context.get('request')
data['poster'] = request.user
return validate_comple... | the_stack_v2_python_sparse | core/roommates_api/serializers/listing_serializers.py | harmanT23/yournextroommates | train | 1 |
a59b3e9bdad38206fb724febb069a86cf5cc96ae | [
"i, j, n = (0, len(A) - 1, len(A))\nwhile i + 1 < n and A[i] < A[i + 1]:\n i += 1\nwhile j > 0 and A[j - 1] > A[j]:\n j -= 1\nreturn 0 < i == j < n - 1",
"if len(A) < 3:\n return False\nif A[0] >= A[1]:\n return False\nclimb = True\nfor a, b in zip(A, A[1:]):\n if climb:\n if a < b:\n ... | <|body_start_0|>
i, j, n = (0, len(A) - 1, len(A))
while i + 1 < n and A[i] < A[i + 1]:
i += 1
while j > 0 and A[j - 1] > A[j]:
j -= 1
return 0 < i == j < n - 1
<|end_body_0|>
<|body_start_1|>
if len(A) < 3:
return False
if A[0] >= A[1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def validMountainArray(self, A):
""":type A: List[int] :rtype: bool"""
<|body_0|>
def validMountainArray(self, A):
""":type A: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i, j, n = (0, len(A) - 1, len(A))
... | stack_v2_sparse_classes_10k_train_001477 | 839 | no_license | [
{
"docstring": ":type A: List[int] :rtype: bool",
"name": "validMountainArray",
"signature": "def validMountainArray(self, A)"
},
{
"docstring": ":type A: List[int] :rtype: bool",
"name": "validMountainArray",
"signature": "def validMountainArray(self, A)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validMountainArray(self, A): :type A: List[int] :rtype: bool
- def validMountainArray(self, A): :type A: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validMountainArray(self, A): :type A: List[int] :rtype: bool
- def validMountainArray(self, A): :type A: List[int] :rtype: bool
<|skeleton|>
class Solution:
def validMo... | c92a5ddcc56e3f69be1e6fb25e9c8ed277e57ee0 | <|skeleton|>
class Solution:
def validMountainArray(self, A):
""":type A: List[int] :rtype: bool"""
<|body_0|>
def validMountainArray(self, A):
""":type A: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def validMountainArray(self, A):
""":type A: List[int] :rtype: bool"""
i, j, n = (0, len(A) - 1, len(A))
while i + 1 < n and A[i] < A[i + 1]:
i += 1
while j > 0 and A[j - 1] > A[j]:
j -= 1
return 0 < i == j < n - 1
def validMountai... | the_stack_v2_python_sparse | code/941#Valid Mountain Array.py | EachenKuang/LeetCode | train | 28 | |
8b58ce2f1b5a01d3200561af10721fad1b1b04cc | [
"super().__init__()\nself._pokemon = pokemon\nself._name = Text(pokemon.nickname)\nself._name.position = (-self._name.width, 0)\nself.add(self._name, z=1)\nself._level_txt = cocos.sprite.Sprite(pyglet.image.load(PATH + '/assets/img/battle/hud/level.png'))\nself._level_txt.position = (5, -2)\nself.add(self._level_tx... | <|body_start_0|>
super().__init__()
self._pokemon = pokemon
self._name = Text(pokemon.nickname)
self._name.position = (-self._name.width, 0)
self.add(self._name, z=1)
self._level_txt = cocos.sprite.Sprite(pyglet.image.load(PATH + '/assets/img/battle/hud/level.png'))
... | The information about the opponent pokemon: name, level, HP Attributes: - HP_BAR_SIZE: The size in pixels of the HP bar. - HP_UPDATE_DURATION: The time it takes for the HP bar to update. | OpponentHUDLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpponentHUDLayer:
"""The information about the opponent pokemon: name, level, HP Attributes: - HP_BAR_SIZE: The size in pixels of the HP bar. - HP_UPDATE_DURATION: The time it takes for the HP bar to update."""
def __init__(self, pokemon: PokemonModel) -> None:
"""Create a new HUD sh... | stack_v2_sparse_classes_10k_train_001478 | 4,187 | no_license | [
{
"docstring": "Create a new HUD showing the opponent pokemon's information. :param pokemon: The opponent pokemon.",
"name": "__init__",
"signature": "def __init__(self, pokemon: PokemonModel) -> None"
},
{
"docstring": "Update the size and the color of the HP bar.",
"name": "update_hp",
... | 3 | stack_v2_sparse_classes_30k_train_000456 | Implement the Python class `OpponentHUDLayer` described below.
Class description:
The information about the opponent pokemon: name, level, HP Attributes: - HP_BAR_SIZE: The size in pixels of the HP bar. - HP_UPDATE_DURATION: The time it takes for the HP bar to update.
Method signatures and docstrings:
- def __init__(... | Implement the Python class `OpponentHUDLayer` described below.
Class description:
The information about the opponent pokemon: name, level, HP Attributes: - HP_BAR_SIZE: The size in pixels of the HP bar. - HP_UPDATE_DURATION: The time it takes for the HP bar to update.
Method signatures and docstrings:
- def __init__(... | dfff995e3e50a8cfa56af73d93de82c427bfa2f5 | <|skeleton|>
class OpponentHUDLayer:
"""The information about the opponent pokemon: name, level, HP Attributes: - HP_BAR_SIZE: The size in pixels of the HP bar. - HP_UPDATE_DURATION: The time it takes for the HP bar to update."""
def __init__(self, pokemon: PokemonModel) -> None:
"""Create a new HUD sh... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OpponentHUDLayer:
"""The information about the opponent pokemon: name, level, HP Attributes: - HP_BAR_SIZE: The size in pixels of the HP bar. - HP_UPDATE_DURATION: The time it takes for the HP bar to update."""
def __init__(self, pokemon: PokemonModel) -> None:
"""Create a new HUD showing the opp... | the_stack_v2_python_sparse | src/views/battle/opponent_hud_layer.py | J-GG/Pymon | train | 0 |
16e509d461bbcd8e35e1a729109b639bad08f2db | [
"self.method = method\nself.url = url\nself.params = params[:]\nself.body = body\nself.headers = headers.copy()\nself.timeout = timeout\nself.stream = stream\nself.follow_redirects = follow_redirects\nself._cookies = None",
"if self._cookies is None:\n self._cookies = http.cookiejar.CookieJar()\nreturn self._c... | <|body_start_0|>
self.method = method
self.url = url
self.params = params[:]
self.body = body
self.headers = headers.copy()
self.timeout = timeout
self.stream = stream
self.follow_redirects = follow_redirects
self._cookies = None
<|end_body_0|>
<|... | Request to HttpService. | HttpRequest | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HttpRequest:
"""Request to HttpService."""
def __init__(self, method, url, params, body, headers, timeout, stream, follow_redirects):
"""Arguments: |method| - HTTP method to use |url| - relative URL to the resource, without query parameters |params| - list of (key, value) pairs to pu... | stack_v2_sparse_classes_10k_train_001479 | 31,532 | permissive | [
{
"docstring": "Arguments: |method| - HTTP method to use |url| - relative URL to the resource, without query parameters |params| - list of (key, value) pairs to put into GET parameters |body| - encoded body of the request (None or str) |headers| - dict with request headers |timeout| - socket read timeout (None ... | 3 | stack_v2_sparse_classes_30k_test_000312 | Implement the Python class `HttpRequest` described below.
Class description:
Request to HttpService.
Method signatures and docstrings:
- def __init__(self, method, url, params, body, headers, timeout, stream, follow_redirects): Arguments: |method| - HTTP method to use |url| - relative URL to the resource, without que... | Implement the Python class `HttpRequest` described below.
Class description:
Request to HttpService.
Method signatures and docstrings:
- def __init__(self, method, url, params, body, headers, timeout, stream, follow_redirects): Arguments: |method| - HTTP method to use |url| - relative URL to the resource, without que... | 10cc5fdcca53e2a1690867acbe6fce099273f092 | <|skeleton|>
class HttpRequest:
"""Request to HttpService."""
def __init__(self, method, url, params, body, headers, timeout, stream, follow_redirects):
"""Arguments: |method| - HTTP method to use |url| - relative URL to the resource, without query parameters |params| - list of (key, value) pairs to pu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HttpRequest:
"""Request to HttpService."""
def __init__(self, method, url, params, body, headers, timeout, stream, follow_redirects):
"""Arguments: |method| - HTTP method to use |url| - relative URL to the resource, without query parameters |params| - list of (key, value) pairs to put into GET pa... | the_stack_v2_python_sparse | client/utils/net.py | luci/luci-py | train | 84 |
7178540ea4ce038e1ecca25ea90e3846dc79ddd9 | [
"self.config = config\nself.regs = config['model']['regs']\nself.decay = self.regs[0]\nself.norm_adj = config['model']['norm_adj']\nself.model = LightGCN(config['model'], self.norm_adj)\nsuper(LightGCNEngine, self).__init__(config)\nself.model.to(self.device)",
"assert hasattr(self, 'model'), 'Please specify the ... | <|body_start_0|>
self.config = config
self.regs = config['model']['regs']
self.decay = self.regs[0]
self.norm_adj = config['model']['norm_adj']
self.model = LightGCN(config['model'], self.norm_adj)
super(LightGCNEngine, self).__init__(config)
self.model.to(self.de... | LightGCNEngine Class. | LightGCNEngine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LightGCNEngine:
"""LightGCNEngine Class."""
def __init__(self, config):
"""Initialize LightGCNEngine Class."""
<|body_0|>
def train_single_batch(self, batch_data):
"""Train the model in a single batch. Args: batch_data (list): batch users, positive items and nega... | stack_v2_sparse_classes_10k_train_001480 | 6,800 | permissive | [
{
"docstring": "Initialize LightGCNEngine Class.",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Train the model in a single batch. Args: batch_data (list): batch users, positive items and negative items. Return: loss (float): batch loss.",
"name": "train_s... | 4 | stack_v2_sparse_classes_30k_train_004263 | Implement the Python class `LightGCNEngine` described below.
Class description:
LightGCNEngine Class.
Method signatures and docstrings:
- def __init__(self, config): Initialize LightGCNEngine Class.
- def train_single_batch(self, batch_data): Train the model in a single batch. Args: batch_data (list): batch users, po... | Implement the Python class `LightGCNEngine` described below.
Class description:
LightGCNEngine Class.
Method signatures and docstrings:
- def __init__(self, config): Initialize LightGCNEngine Class.
- def train_single_batch(self, batch_data): Train the model in a single batch. Args: batch_data (list): batch users, po... | 625189d5e1002a3edc27c3e3ce075fddf7ae1c92 | <|skeleton|>
class LightGCNEngine:
"""LightGCNEngine Class."""
def __init__(self, config):
"""Initialize LightGCNEngine Class."""
<|body_0|>
def train_single_batch(self, batch_data):
"""Train the model in a single batch. Args: batch_data (list): batch users, positive items and nega... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LightGCNEngine:
"""LightGCNEngine Class."""
def __init__(self, config):
"""Initialize LightGCNEngine Class."""
self.config = config
self.regs = config['model']['regs']
self.decay = self.regs[0]
self.norm_adj = config['model']['norm_adj']
self.model = LightG... | the_stack_v2_python_sparse | beta_rec/models/lightgcn.py | beta-team/beta-recsys | train | 156 |
22a154805b4573d46b8ca66397ca40cd28d8ff32 | [
"if len(digits) == 0:\n digits = [1]\nelif digits[-1] == 9:\n print('aaa')\n print(digits[:-1])\n digits = self.plusOne(digits[:-1])\n print('xxxxx')\n print(digits)\n digits.append(0)\nelse:\n digits[-1] += 1\nreturn digits",
"n = len(digits)\nif digits[-1] != 9:\n digits[-1] += 1\nels... | <|body_start_0|>
if len(digits) == 0:
digits = [1]
elif digits[-1] == 9:
print('aaa')
print(digits[:-1])
digits = self.plusOne(digits[:-1])
print('xxxxx')
print(digits)
digits.append(0)
else:
digits[-... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def plusOne(self, digits):
""":type digits: List[int] :rtype: List[int]"""
<|body_0|>
def plusOne2(self, digits):
""":type digits: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(digits) == 0:
... | stack_v2_sparse_classes_10k_train_001481 | 2,031 | no_license | [
{
"docstring": ":type digits: List[int] :rtype: List[int]",
"name": "plusOne",
"signature": "def plusOne(self, digits)"
},
{
"docstring": ":type digits: List[int] :rtype: List[int]",
"name": "plusOne2",
"signature": "def plusOne2(self, digits)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000449 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plusOne(self, digits): :type digits: List[int] :rtype: List[int]
- def plusOne2(self, digits): :type digits: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plusOne(self, digits): :type digits: List[int] :rtype: List[int]
- def plusOne2(self, digits): :type digits: List[int] :rtype: List[int]
<|skeleton|>
class Solution:
de... | f022677c042db3598003df1a320a70f0edc4f870 | <|skeleton|>
class Solution:
def plusOne(self, digits):
""":type digits: List[int] :rtype: List[int]"""
<|body_0|>
def plusOne2(self, digits):
""":type digits: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def plusOne(self, digits):
""":type digits: List[int] :rtype: List[int]"""
if len(digits) == 0:
digits = [1]
elif digits[-1] == 9:
print('aaa')
print(digits[:-1])
digits = self.plusOne(digits[:-1])
print('xxxxx')
... | the_stack_v2_python_sparse | ArrayDeal/jiayi.py | daisyzl/program-exercise-python | train | 0 | |
0cd01d4da8a9e28c5896a1e2b072fcace47bc687 | [
"lst = []\nQ = [root] if root else []\nwhile len(Q) > 0:\n p = Q.pop()\n if not p:\n lst.append(None)\n continue\n Q.append(p.left)\n Q.append(p.right)\nwhile len(lst) > 0 and lst[-1] == None:\n lst.pop()\nreturn str(lst)",
"data = data[1:-1]\nif len(data) == 0:\n return None\nlst ... | <|body_start_0|>
lst = []
Q = [root] if root else []
while len(Q) > 0:
p = Q.pop()
if not p:
lst.append(None)
continue
Q.append(p.left)
Q.append(p.right)
while len(lst) > 0 and lst[-1] == None:
ls... | 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_001482 | 1,480 | 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` 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:... | a95b871578aae0103066962c33b8c0f4ec22d0f2 | <|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"""
lst = []
Q = [root] if root else []
while len(Q) > 0:
p = Q.pop()
if not p:
lst.append(None)
continue
... | the_stack_v2_python_sparse | Offer037.py | Jane11111/Leetcode2021 | train | 2 | |
a23199544234ac2152a5052c3010a5e60b590cf1 | [
"leaf_nodes1 = self.getLeafNodes(root1)\nleaf_nodes2 = self.getLeafNodes(root2)\nif leaf_nodes1 == leaf_nodes2:\n return True\nreturn False",
"if root.left == None and root.right == None:\n res.append(root)\nelif root.left != None:\n self.getLeafNodes(root.left, res)\nelif root.right != None:\n self.g... | <|body_start_0|>
leaf_nodes1 = self.getLeafNodes(root1)
leaf_nodes2 = self.getLeafNodes(root2)
if leaf_nodes1 == leaf_nodes2:
return True
return False
<|end_body_0|>
<|body_start_1|>
if root.left == None and root.right == None:
res.append(root)
el... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def leafSimilar(self, root1, root2):
""":type root1: TreeNode :type root2: TreeNode :rtype: bool"""
<|body_0|>
def getLeafNodes(self, root, res):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_001483 | 1,562 | no_license | [
{
"docstring": ":type root1: TreeNode :type root2: TreeNode :rtype: bool",
"name": "leafSimilar",
"signature": "def leafSimilar(self, root1, root2)"
},
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "getLeafNodes",
"signature": "def getLeafNodes(self, root, res)"
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def leafSimilar(self, root1, root2): :type root1: TreeNode :type root2: TreeNode :rtype: bool
- def getLeafNodes(self, root, res): :type root: TreeNode :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def leafSimilar(self, root1, root2): :type root1: TreeNode :type root2: TreeNode :rtype: bool
- def getLeafNodes(self, root, res): :type root: TreeNode :rtype: List[List[int]]
<... | 1211eac167f33084f536007468ea10c1a0ceab08 | <|skeleton|>
class Solution:
def leafSimilar(self, root1, root2):
""":type root1: TreeNode :type root2: TreeNode :rtype: bool"""
<|body_0|>
def getLeafNodes(self, root, res):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def leafSimilar(self, root1, root2):
""":type root1: TreeNode :type root2: TreeNode :rtype: bool"""
leaf_nodes1 = self.getLeafNodes(root1)
leaf_nodes2 = self.getLeafNodes(root2)
if leaf_nodes1 == leaf_nodes2:
return True
return False
def getLe... | the_stack_v2_python_sparse | 872_LeafSimilarTrees.py | renukadeshmukh/Leetcode_Solutions | train | 3 | |
ceeff7b250ac1858f1286342b799ac0c9968b8ec | [
"if not matrix:\n self.M, self.N = (0, -1)\n return\nself.M, self.N = (len(matrix), len(matrix[0]))\nfor i in xrange(1, self.M):\n matrix[i][0] += matrix[i - 1][0]\nfor j in xrange(1, self.N):\n matrix[0][j] += matrix[0][j - 1]\nfor i in xrange(1, self.M):\n for j in xrange(1, self.N):\n matri... | <|body_start_0|>
if not matrix:
self.M, self.N = (0, -1)
return
self.M, self.N = (len(matrix), len(matrix[0]))
for i in xrange(1, self.M):
matrix[i][0] += matrix[i - 1][0]
for j in xrange(1, self.N):
matrix[0][j] += matrix[0][j - 1]
... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_10k_train_001484 | 1,750 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int",
"name": "sumRegion",
"signature": "def sumRegion(self, row1, col1, row2, col2)"
... | 2 | stack_v2_sparse_classes_30k_train_000930 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | 00196f836d4bc226ddcb745b17e247c2ed4e9b4b | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
if not matrix:
self.M, self.N = (0, -1)
return
self.M, self.N = (len(matrix), len(matrix[0]))
for i in xrange(1, self.M):
matrix[i][0] += matrix[i - 1][0]
for ... | the_stack_v2_python_sparse | Facebook习题/面经/304. Range Sum Query 2D - Immutable.py | signalwolf/Leetcode_by_type | train | 0 | |
0d638be1356d8d56ed9720c241a5f8cc401c2b40 | [
"self._session = requests.Session()\nself._adapter = requests.adapters.HTTPAdapter(max_retries=2)\nself._session.mount('https://', self._adapter)\nif not endpoint[-1] == '/':\n endpoint += '/'\nself.endpoint = endpoint",
"if not document_id:\n raise ValueError('Invalid value for document_id')\ntry:\n res... | <|body_start_0|>
self._session = requests.Session()
self._adapter = requests.adapters.HTTPAdapter(max_retries=2)
self._session.mount('https://', self._adapter)
if not endpoint[-1] == '/':
endpoint += '/'
self.endpoint = endpoint
<|end_body_0|>
<|body_start_1|>
... | An HTTP session with the fulltext endpoint. | FulltextSession | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FulltextSession:
"""An HTTP session with the fulltext endpoint."""
def __init__(self, endpoint: str) -> None:
"""Initialize an HTTP session."""
<|body_0|>
def retrieve(self, document_id: str) -> Fulltext:
"""Retrieve fulltext content for an arXiv paper. Parameter... | stack_v2_sparse_classes_10k_train_001485 | 3,414 | permissive | [
{
"docstring": "Initialize an HTTP session.",
"name": "__init__",
"signature": "def __init__(self, endpoint: str) -> None"
},
{
"docstring": "Retrieve fulltext content for an arXiv paper. Parameters ---------- document_id : str arXiv identifier, including version tag. E.g. ``\"1234.56787v3\"``. ... | 2 | stack_v2_sparse_classes_30k_test_000261 | Implement the Python class `FulltextSession` described below.
Class description:
An HTTP session with the fulltext endpoint.
Method signatures and docstrings:
- def __init__(self, endpoint: str) -> None: Initialize an HTTP session.
- def retrieve(self, document_id: str) -> Fulltext: Retrieve fulltext content for an a... | Implement the Python class `FulltextSession` described below.
Class description:
An HTTP session with the fulltext endpoint.
Method signatures and docstrings:
- def __init__(self, endpoint: str) -> None: Initialize an HTTP session.
- def retrieve(self, document_id: str) -> Fulltext: Retrieve fulltext content for an a... | e48f74bb2a858ae7bcf19d68f80cb6dcaa1f4761 | <|skeleton|>
class FulltextSession:
"""An HTTP session with the fulltext endpoint."""
def __init__(self, endpoint: str) -> None:
"""Initialize an HTTP session."""
<|body_0|>
def retrieve(self, document_id: str) -> Fulltext:
"""Retrieve fulltext content for an arXiv paper. Parameter... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FulltextSession:
"""An HTTP session with the fulltext endpoint."""
def __init__(self, endpoint: str) -> None:
"""Initialize an HTTP session."""
self._session = requests.Session()
self._adapter = requests.adapters.HTTPAdapter(max_retries=2)
self._session.mount('https://', s... | the_stack_v2_python_sparse | search/services/fulltext.py | arXiv/arxiv-search | train | 54 |
081699249fde3244c0fdfff328bba4b73cd4a53f | [
"if n == 1:\n return True\ndic = {}\nkey = n\nwhile True:\n key = list(map(int, str(key)))\n tmp = [i ** 2 for i in key]\n key = sum(tmp)\n if key == 1:\n return True\n elif key not in dic:\n dic[key] = 1\n else:\n return False",
"dic = {}\nwhile n:\n if n == 1:\n ... | <|body_start_0|>
if n == 1:
return True
dic = {}
key = n
while True:
key = list(map(int, str(key)))
tmp = [i ** 2 for i in key]
key = sum(tmp)
if key == 1:
return True
elif key not in dic:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isHappy(self, n):
""":type n: int :rtype: bool"""
<|body_0|>
def isHappy_1(self, n):
""":type n: int :rtype: bool"""
<|body_1|>
def isHappy_2(self, n):
""":type n: int :rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_10k_train_001486 | 2,193 | no_license | [
{
"docstring": ":type n: int :rtype: bool",
"name": "isHappy",
"signature": "def isHappy(self, n)"
},
{
"docstring": ":type n: int :rtype: bool",
"name": "isHappy_1",
"signature": "def isHappy_1(self, n)"
},
{
"docstring": ":type n: int :rtype: bool",
"name": "isHappy_2",
... | 3 | stack_v2_sparse_classes_30k_train_004472 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isHappy(self, n): :type n: int :rtype: bool
- def isHappy_1(self, n): :type n: int :rtype: bool
- def isHappy_2(self, n): :type n: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isHappy(self, n): :type n: int :rtype: bool
- def isHappy_1(self, n): :type n: int :rtype: bool
- def isHappy_2(self, n): :type n: int :rtype: bool
<|skeleton|>
class Soluti... | 3d9e0ad2f6ed92ec969556f75d97c51ea4854719 | <|skeleton|>
class Solution:
def isHappy(self, n):
""":type n: int :rtype: bool"""
<|body_0|>
def isHappy_1(self, n):
""":type n: int :rtype: bool"""
<|body_1|>
def isHappy_2(self, n):
""":type n: int :rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isHappy(self, n):
""":type n: int :rtype: bool"""
if n == 1:
return True
dic = {}
key = n
while True:
key = list(map(int, str(key)))
tmp = [i ** 2 for i in key]
key = sum(tmp)
if key == 1:
... | the_stack_v2_python_sparse | Solutions/0202_isHappy.py | YoupengLi/leetcode-sorting | train | 3 | |
24b8fedff852ed30439b772a21d8802eaa222d89 | [
"dp = [[[0] * n for _ in range(m)] for _ in range(N + 1)]\nfor s in range(1, N + 1):\n for x in range(m):\n for y in range(n):\n v1 = 1 if x == 0 else dp[s - 1][x - 1][y]\n v2 = 1 if x == m - 1 else dp[s - 1][x + 1][y]\n v3 = 1 if y == 0 else dp[s - 1][x][y - 1]\n ... | <|body_start_0|>
dp = [[[0] * n for _ in range(m)] for _ in range(N + 1)]
for s in range(1, N + 1):
for x in range(m):
for y in range(n):
v1 = 1 if x == 0 else dp[s - 1][x - 1][y]
v2 = 1 if x == m - 1 else dp[s - 1][x + 1][y]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findPaths(self, m, n, N, i, j):
""":type m: int :type n: int :type N: int :type i: int :type j: int :rtype: int"""
<|body_0|>
def findPaths(self, m, n, N, i, j):
""":type m: int :type n: int :type N: int :type i: int :type j: int :rtype: int"""
... | stack_v2_sparse_classes_10k_train_001487 | 4,620 | no_license | [
{
"docstring": ":type m: int :type n: int :type N: int :type i: int :type j: int :rtype: int",
"name": "findPaths",
"signature": "def findPaths(self, m, n, N, i, j)"
},
{
"docstring": ":type m: int :type n: int :type N: int :type i: int :type j: int :rtype: int",
"name": "findPaths",
"si... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPaths(self, m, n, N, i, j): :type m: int :type n: int :type N: int :type i: int :type j: int :rtype: int
- def findPaths(self, m, n, N, i, j): :type m: int :type n: int :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPaths(self, m, n, N, i, j): :type m: int :type n: int :type N: int :type i: int :type j: int :rtype: int
- def findPaths(self, m, n, N, i, j): :type m: int :type n: int :... | 035ef08434fa1ca781a6fb2f9eed3538b7d20c02 | <|skeleton|>
class Solution:
def findPaths(self, m, n, N, i, j):
""":type m: int :type n: int :type N: int :type i: int :type j: int :rtype: int"""
<|body_0|>
def findPaths(self, m, n, N, i, j):
""":type m: int :type n: int :type N: int :type i: int :type j: int :rtype: int"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findPaths(self, m, n, N, i, j):
""":type m: int :type n: int :type N: int :type i: int :type j: int :rtype: int"""
dp = [[[0] * n for _ in range(m)] for _ in range(N + 1)]
for s in range(1, N + 1):
for x in range(m):
for y in range(n):
... | the_stack_v2_python_sparse | leetcode_python/Dynamic_Programming/out-of-boundary-paths.py | yennanliu/CS_basics | train | 64 | |
7888c2b1eb20ff56234bb05f494a8abc41294b8a | [
"search = ['أ', 'إ', 'آ', 'ة', '_', '-', '/', '.', '،', ' و ', ' يا ', '\"', 'ـ', \"'\", 'ى', '\\\\', '\\n', '\\t', '"', '?', '؟', '!', ':', '(', ')', '\\x02']\nreplace = ['ا', 'ا', 'ا', 'ه', ' ', ' ', '', '', '', ' و', ' يا', '', '', '', 'ي', '', ' ', ' ', ' ', ' ? ', ' ؟ ', ' ! ', '', '', '', '']\np_tashkeel... | <|body_start_0|>
search = ['أ', 'إ', 'آ', 'ة', '_', '-', '/', '.', '،', ' و ', ' يا ', '"', 'ـ', "'", 'ى', '\\', '\n', '\t', '"', '?', '؟', '!', ':', '(', ')', '\x02']
replace = ['ا', 'ا', 'ا', 'ه', ' ', ' ', '', '', '', ' و', ' يا', '', '', '', 'ي', '', ' ', ' ', ' ', ' ? ', ' ؟ ', ' ! ', '', '', ... | Procces the data and embed them using AraVec OR ELMo | Embedding | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Embedding:
"""Procces the data and embed them using AraVec OR ELMo"""
def clean_str(text: str) -> str:
"""Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns str as a preprocessed book"""
<|body_0|>
def ... | stack_v2_sparse_classes_10k_train_001488 | 5,959 | no_license | [
{
"docstring": "Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns str as a preprocessed book",
"name": "clean_str",
"signature": "def clean_str(text: str) -> str"
},
{
"docstring": "Embed each word in the book into a Vector in... | 3 | stack_v2_sparse_classes_30k_train_002304 | Implement the Python class `Embedding` described below.
Class description:
Procces the data and embed them using AraVec OR ELMo
Method signatures and docstrings:
- def clean_str(text: str) -> str: Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns s... | Implement the Python class `Embedding` described below.
Class description:
Procces the data and embed them using AraVec OR ELMo
Method signatures and docstrings:
- def clean_str(text: str) -> str: Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns s... | c7349dd0501e9a0d47a8f1024762ee15b225c6e0 | <|skeleton|>
class Embedding:
"""Procces the data and embed them using AraVec OR ELMo"""
def clean_str(text: str) -> str:
"""Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns str as a preprocessed book"""
<|body_0|>
def ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Embedding:
"""Procces the data and embed them using AraVec OR ELMo"""
def clean_str(text: str) -> str:
"""Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns str as a preprocessed book"""
search = ['أ', 'إ', 'آ', 'ة', '_'... | the_stack_v2_python_sparse | Algs/Embedding.py | saleems11/Final_Project_B | train | 0 |
0386f5ec419b6208473417122e44d6727a148020 | [
"repository = self.object\ngh = self.gh\nif not gh:\n return\nrepository.check_hook(gh)\nreturn repository.hook_set",
"if not result:\n CheckRepositoryEvents.add_job(self.identifier.hget())\nelse:\n for j in CheckRepositoryEvents.collection(queued=1, identifier=self.identifier.hget()).instances():\n ... | <|body_start_0|>
repository = self.object
gh = self.gh
if not gh:
return
repository.check_hook(gh)
return repository.hook_set
<|end_body_0|>
<|body_start_1|>
if not result:
CheckRepositoryEvents.add_job(self.identifier.hget())
else:
... | Every 15 minutes (+-2mn), check if the hook is set and if None and if there is no job to fetch events every minute, create one. | CheckRepositoryHook | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckRepositoryHook:
"""Every 15 minutes (+-2mn), check if the hook is set and if None and if there is no job to fetch events every minute, create one."""
def run(self, queue):
"""Check if the hook exist for this modele. If not, try to add a job to start checking events every minute ... | stack_v2_sparse_classes_10k_train_001489 | 3,018 | no_license | [
{
"docstring": "Check if the hook exist for this modele. If not, try to add a job to start checking events every minute (if one already exists, no new one will be added)",
"name": "run",
"signature": "def run(self, queue)"
},
{
"docstring": "If the repository hook is not set, add a job to fetch ... | 2 | stack_v2_sparse_classes_30k_train_007053 | Implement the Python class `CheckRepositoryHook` described below.
Class description:
Every 15 minutes (+-2mn), check if the hook is set and if None and if there is no job to fetch events every minute, create one.
Method signatures and docstrings:
- def run(self, queue): Check if the hook exist for this modele. If not... | Implement the Python class `CheckRepositoryHook` described below.
Class description:
Every 15 minutes (+-2mn), check if the hook is set and if None and if there is no job to fetch events every minute, create one.
Method signatures and docstrings:
- def run(self, queue): Check if the hook exist for this modele. If not... | 63a405b993e77f10b9c2b6d9790aae7576d9d84f | <|skeleton|>
class CheckRepositoryHook:
"""Every 15 minutes (+-2mn), check if the hook is set and if None and if there is no job to fetch events every minute, create one."""
def run(self, queue):
"""Check if the hook exist for this modele. If not, try to add a job to start checking events every minute ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CheckRepositoryHook:
"""Every 15 minutes (+-2mn), check if the hook is set and if None and if there is no job to fetch events every minute, create one."""
def run(self, queue):
"""Check if the hook exist for this modele. If not, try to add a job to start checking events every minute (if one alrea... | the_stack_v2_python_sparse | gim/hooks/tasks.py | derekey/github-issues-manager | train | 1 |
a2f7482fb19af0064e301bf6263ce26267abdd38 | [
"pairs = []\nfor i, num1 in enumerate(nums1):\n for j, num2 in enumerate(nums2):\n if i + j >= k:\n break\n pairs.append((num1 + num2, num1, num2))\nreturn map(lambda x: [x[1], x[2]], heapq.nsmallest(k, pairs))",
"if not nums1 or not nums2:\n return []\nlength1, length2 = (len(nums1... | <|body_start_0|>
pairs = []
for i, num1 in enumerate(nums1):
for j, num2 in enumerate(nums2):
if i + j >= k:
break
pairs.append((num1 + num2, num1, num2))
return map(lambda x: [x[1], x[2]], heapq.nsmallest(k, pairs))
<|end_body_0|>
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def kSmallestPairs(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]"""
<|body_0|>
def kSmallestPairs2(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: ... | stack_v2_sparse_classes_10k_train_001490 | 1,286 | permissive | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]",
"name": "kSmallestPairs",
"signature": "def kSmallestPairs(self, nums1, nums2, k)"
},
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]",
"nam... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kSmallestPairs(self, nums1, nums2, k): :type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]
- def kSmallestPairs2(self, nums1, nums2, k): :type ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kSmallestPairs(self, nums1, nums2, k): :type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]
- def kSmallestPairs2(self, nums1, nums2, k): :type ... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|skeleton|>
class Solution:
def kSmallestPairs(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]"""
<|body_0|>
def kSmallestPairs2(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def kSmallestPairs(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]"""
pairs = []
for i, num1 in enumerate(nums1):
for j, num2 in enumerate(nums2):
if i + j >= k:
brea... | the_stack_v2_python_sparse | 301-400/371-380/373-findKPairsWithSmallestSums/findKPairsWithSmallestSums.py | xuychen/Leetcode | train | 0 | |
4c55b67c7884e1406e3bc9158c8e6848de2b910a | [
"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!')"
] | <|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... | Proto file describing the Geo target constant service. Service to fetch geo target constants. | GeoTargetConstantServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeoTargetConstantServiceServicer:
"""Proto file describing the Geo target constant service. Service to fetch geo target constants."""
def GetGeoTargetConstant(self, request, context):
"""Returns the requested geo target constant in full detail."""
<|body_0|>
def SuggestG... | stack_v2_sparse_classes_10k_train_001491 | 3,645 | permissive | [
{
"docstring": "Returns the requested geo target constant in full detail.",
"name": "GetGeoTargetConstant",
"signature": "def GetGeoTargetConstant(self, request, context)"
},
{
"docstring": "Returns GeoTargetConstant suggestions by location name or by resource name.",
"name": "SuggestGeoTarg... | 2 | stack_v2_sparse_classes_30k_train_000687 | Implement the Python class `GeoTargetConstantServiceServicer` described below.
Class description:
Proto file describing the Geo target constant service. Service to fetch geo target constants.
Method signatures and docstrings:
- def GetGeoTargetConstant(self, request, context): Returns the requested geo target constan... | Implement the Python class `GeoTargetConstantServiceServicer` described below.
Class description:
Proto file describing the Geo target constant service. Service to fetch geo target constants.
Method signatures and docstrings:
- def GetGeoTargetConstant(self, request, context): Returns the requested geo target constan... | a5b6cede64f4d9912ae6ad26927a54e40448c9fe | <|skeleton|>
class GeoTargetConstantServiceServicer:
"""Proto file describing the Geo target constant service. Service to fetch geo target constants."""
def GetGeoTargetConstant(self, request, context):
"""Returns the requested geo target constant in full detail."""
<|body_0|>
def SuggestG... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GeoTargetConstantServiceServicer:
"""Proto file describing the Geo target constant service. Service to fetch geo target constants."""
def GetGeoTargetConstant(self, request, context):
"""Returns the requested geo target constant in full detail."""
context.set_code(grpc.StatusCode.UNIMPLEM... | the_stack_v2_python_sparse | google/ads/google_ads/v3/proto/services/geo_target_constant_service_pb2_grpc.py | fiboknacky/google-ads-python | train | 0 |
45495d78dc570079e39a7f66c7581619565bd988 | [
"self.var_dict = self.get_raw_dict()\npuller_params = default_config.DEFAULT_PULLER_CONF.copy()\ndb_params = default_config.DEFAULT_DB_CONF.copy()\ntry:\n puller_params.update(self.get_dict('puller'))\n db_params.update(self.get_dict('database'))\nexcept ValueError as error_info:\n sys.stderr.write(error_i... | <|body_start_0|>
self.var_dict = self.get_raw_dict()
puller_params = default_config.DEFAULT_PULLER_CONF.copy()
db_params = default_config.DEFAULT_DB_CONF.copy()
try:
puller_params.update(self.get_dict('puller'))
db_params.update(self.get_dict('database'))
... | StorageConfigParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StorageConfigParser:
def config_parse(self):
"""parse configuration from config file and default config"""
<|body_0|>
def get_db_from_config(self):
"""get database connection instance from config"""
<|body_1|>
def get_puller_from_config(self):
""... | stack_v2_sparse_classes_10k_train_001492 | 1,624 | no_license | [
{
"docstring": "parse configuration from config file and default config",
"name": "config_parse",
"signature": "def config_parse(self)"
},
{
"docstring": "get database connection instance from config",
"name": "get_db_from_config",
"signature": "def get_db_from_config(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_002690 | Implement the Python class `StorageConfigParser` described below.
Class description:
Implement the StorageConfigParser class.
Method signatures and docstrings:
- def config_parse(self): parse configuration from config file and default config
- def get_db_from_config(self): get database connection instance from config... | Implement the Python class `StorageConfigParser` described below.
Class description:
Implement the StorageConfigParser class.
Method signatures and docstrings:
- def config_parse(self): parse configuration from config file and default config
- def get_db_from_config(self): get database connection instance from config... | 8819fc30456b4bb8576a4c78798ec91cdc8ac062 | <|skeleton|>
class StorageConfigParser:
def config_parse(self):
"""parse configuration from config file and default config"""
<|body_0|>
def get_db_from_config(self):
"""get database connection instance from config"""
<|body_1|>
def get_puller_from_config(self):
""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StorageConfigParser:
def config_parse(self):
"""parse configuration from config file and default config"""
self.var_dict = self.get_raw_dict()
puller_params = default_config.DEFAULT_PULLER_CONF.copy()
db_params = default_config.DEFAULT_DB_CONF.copy()
try:
pu... | the_stack_v2_python_sparse | storage/config/config_parser.py | zhxfei/monitor | train | 1 | |
a184c10bc5a33f14401a45ca96bc88c0ee033b86 | [
"try:\n resp = Node().get_data_by_id(uid)\n return masked_json_template(resp, 200)\nexcept:\n abort(400, 'Input unrecognizable.')",
"try:\n json_data = api.payload\n resp = Node().update_data_by_id(uid, json_data)\n return masked_json_template(resp, 200)\nexcept:\n abort(400, 'Input unrecogni... | <|body_start_0|>
try:
resp = Node().get_data_by_id(uid)
return masked_json_template(resp, 200)
except:
abort(400, 'Input unrecognizable.')
<|end_body_0|>
<|body_start_1|>
try:
json_data = api.payload
resp = Node().update_data_by_id(uid... | DroneIDFindRoute | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DroneIDFindRoute:
def get(self, uid):
"""Get data by ID"""
<|body_0|>
def put(self, uid):
"""Update data by ID"""
<|body_1|>
def delete(self, uid):
"""Delete data by ID"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_10k_train_001493 | 4,218 | permissive | [
{
"docstring": "Get data by ID",
"name": "get",
"signature": "def get(self, uid)"
},
{
"docstring": "Update data by ID",
"name": "put",
"signature": "def put(self, uid)"
},
{
"docstring": "Delete data by ID",
"name": "delete",
"signature": "def delete(self, uid)"
}
] | 3 | stack_v2_sparse_classes_30k_train_004893 | Implement the Python class `DroneIDFindRoute` described below.
Class description:
Implement the DroneIDFindRoute class.
Method signatures and docstrings:
- def get(self, uid): Get data by ID
- def put(self, uid): Update data by ID
- def delete(self, uid): Delete data by ID | Implement the Python class `DroneIDFindRoute` described below.
Class description:
Implement the DroneIDFindRoute class.
Method signatures and docstrings:
- def get(self, uid): Get data by ID
- def put(self, uid): Update data by ID
- def delete(self, uid): Delete data by ID
<|skeleton|>
class DroneIDFindRoute:
d... | 100fca0d2dd9b0b2ab2fa5974d8126af35ddcfd1 | <|skeleton|>
class DroneIDFindRoute:
def get(self, uid):
"""Get data by ID"""
<|body_0|>
def put(self, uid):
"""Update data by ID"""
<|body_1|>
def delete(self, uid):
"""Delete data by ID"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DroneIDFindRoute:
def get(self, uid):
"""Get data by ID"""
try:
resp = Node().get_data_by_id(uid)
return masked_json_template(resp, 200)
except:
abort(400, 'Input unrecognizable.')
def put(self, uid):
"""Update data by ID"""
try:... | the_stack_v2_python_sparse | app/controllers/api/node/node.py | ardihikaru/api-dashboard-5g-dive | train | 0 | |
33503f923c891efbc5642917745ee32465f3430d | [
"vocab_size = 100\nsequence_length = 512\nd_model = 64\nd_latents = 48\nnum_layers = 2\nencoder_cfg = cfg.EncoderConfig(v_last_dim=d_latents, num_self_attends_per_block=num_layers)\nsequence_encoder_cfg = cfg.SequenceEncoderConfig(d_model=d_model, d_latents=d_latents, vocab_size=vocab_size, encoder=encoder_cfg)\nte... | <|body_start_0|>
vocab_size = 100
sequence_length = 512
d_model = 64
d_latents = 48
num_layers = 2
encoder_cfg = cfg.EncoderConfig(v_last_dim=d_latents, num_self_attends_per_block=num_layers)
sequence_encoder_cfg = cfg.SequenceEncoderConfig(d_model=d_model, d_late... | ClassifierTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassifierTest:
def test_perceiver_trainer(self, num_classes):
"""Validate that the Keras object can be created."""
<|body_0|>
def test_perceiver_trainer_tensor_call(self, num_classes, use_custom_head):
"""Validate that the Keras object can be invoked."""
<|b... | stack_v2_sparse_classes_10k_train_001494 | 8,478 | permissive | [
{
"docstring": "Validate that the Keras object can be created.",
"name": "test_perceiver_trainer",
"signature": "def test_perceiver_trainer(self, num_classes)"
},
{
"docstring": "Validate that the Keras object can be invoked.",
"name": "test_perceiver_trainer_tensor_call",
"signature": "... | 3 | null | Implement the Python class `ClassifierTest` described below.
Class description:
Implement the ClassifierTest class.
Method signatures and docstrings:
- def test_perceiver_trainer(self, num_classes): Validate that the Keras object can be created.
- def test_perceiver_trainer_tensor_call(self, num_classes, use_custom_h... | Implement the Python class `ClassifierTest` described below.
Class description:
Implement the ClassifierTest class.
Method signatures and docstrings:
- def test_perceiver_trainer(self, num_classes): Validate that the Keras object can be created.
- def test_perceiver_trainer_tensor_call(self, num_classes, use_custom_h... | d3507b550a3ade40cade60a79eb5b8978b56c7ae | <|skeleton|>
class ClassifierTest:
def test_perceiver_trainer(self, num_classes):
"""Validate that the Keras object can be created."""
<|body_0|>
def test_perceiver_trainer_tensor_call(self, num_classes, use_custom_head):
"""Validate that the Keras object can be invoked."""
<|b... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ClassifierTest:
def test_perceiver_trainer(self, num_classes):
"""Validate that the Keras object can be created."""
vocab_size = 100
sequence_length = 512
d_model = 64
d_latents = 48
num_layers = 2
encoder_cfg = cfg.EncoderConfig(v_last_dim=d_latents, nu... | the_stack_v2_python_sparse | official/projects/perceiver/modeling/models/classifier_test.py | jianzhnie/models | train | 2 | |
e378688782bc4d1f01ce5456f1b8ee24cb8c919f | [
"if not isinstance(actionspace, Dict):\n raise ValueError('actionspace must be Dict but found ' + str(actionspace))\nif len(agentComponentList) == 0:\n raise ValueError('There must be at least 1 agent in the list')\nfor agent in agentComponentList:\n if not isinstance(agent, QAgentComponent):\n rais... | <|body_start_0|>
if not isinstance(actionspace, Dict):
raise ValueError('actionspace must be Dict but found ' + str(actionspace))
if len(agentComponentList) == 0:
raise ValueError('There must be at least 1 agent in the list')
for agent in agentComponentList:
i... | A QCoordinator is an agent that can coordinate a set of sub-agents in such a way that the sum of their actions is optimal. See #step for more details. The QCoordinator should work with environments that have a dictionary action space of the form: A={ "entityId1": Discrete(n1) "entitityId2": Discrete(n2) "entityId3": Di... | QCoordinator | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QCoordinator:
"""A QCoordinator is an agent that can coordinate a set of sub-agents in such a way that the sum of their actions is optimal. See #step for more details. The QCoordinator should work with environments that have a dictionary action space of the form: A={ "entityId1": Discrete(n1) "en... | stack_v2_sparse_classes_10k_train_001495 | 4,795 | no_license | [
{
"docstring": "@param AgentComponentList: a list of QAgentComponent. Size must be >=1. The agent environments should be equal to our environment, or to a Packed version of it. We can't check this because environments do not implement equals at this moment. @param environment the openAI Gym Env. Must have actio... | 2 | stack_v2_sparse_classes_30k_val_000101 | Implement the Python class `QCoordinator` described below.
Class description:
A QCoordinator is an agent that can coordinate a set of sub-agents in such a way that the sum of their actions is optimal. See #step for more details. The QCoordinator should work with environments that have a dictionary action space of the ... | Implement the Python class `QCoordinator` described below.
Class description:
A QCoordinator is an agent that can coordinate a set of sub-agents in such a way that the sum of their actions is optimal. See #step for more details. The QCoordinator should work with environments that have a dictionary action space of the ... | e7d052c6a01e0470bfd011d9dc5ba95247466494 | <|skeleton|>
class QCoordinator:
"""A QCoordinator is an agent that can coordinate a set of sub-agents in such a way that the sum of their actions is optimal. See #step for more details. The QCoordinator should work with environments that have a dictionary action space of the form: A={ "entityId1": Discrete(n1) "en... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QCoordinator:
"""A QCoordinator is an agent that can coordinate a set of sub-agents in such a way that the sum of their actions is optimal. See #step for more details. The QCoordinator should work with environments that have a dictionary action space of the form: A={ "entityId1": Discrete(n1) "entitityId2": D... | the_stack_v2_python_sparse | aiagents/multi/QCoordinator.py | INFLUENCEorg/aiagents | train | 0 |
3a78e1890bf78f99afbf3bf71165c55257b51ded | [
"if not nums:\n return 0\nfirst = self.find_first(nums, target, 0, len(nums) - 1)\nif first == -1:\n return 0\nlast = self.find_last(nums, target, 0, len(nums) - 1)\nreturn last - first + 1",
"if begin > end:\n return -1\nmid = begin + (end - begin) // 2\nif nums[mid] == target:\n if mid > 0 and nums[... | <|body_start_0|>
if not nums:
return 0
first = self.find_first(nums, target, 0, len(nums) - 1)
if first == -1:
return 0
last = self.find_last(nums, target, 0, len(nums) - 1)
return last - first + 1
<|end_body_0|>
<|body_start_1|>
if begin > end:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def search(self, nums: List[int], target: int) -> int:
"""binary search, find first and last target in list. O(logn) time complexity."""
<|body_0|>
def find_first(self, nums, target, begin, end):
"""binary search, find first target"""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_001496 | 1,589 | no_license | [
{
"docstring": "binary search, find first and last target in list. O(logn) time complexity.",
"name": "search",
"signature": "def search(self, nums: List[int], target: int) -> int"
},
{
"docstring": "binary search, find first target",
"name": "find_first",
"signature": "def find_first(se... | 3 | stack_v2_sparse_classes_30k_train_005193 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def search(self, nums: List[int], target: int) -> int: binary search, find first and last target in list. O(logn) time complexity.
- def find_first(self, nums, target, begin, end... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def search(self, nums: List[int], target: int) -> int: binary search, find first and last target in list. O(logn) time complexity.
- def find_first(self, nums, target, begin, end... | 0f16635de49dc63a207d34f7e612546977a5753e | <|skeleton|>
class Solution:
def search(self, nums: List[int], target: int) -> int:
"""binary search, find first and last target in list. O(logn) time complexity."""
<|body_0|>
def find_first(self, nums, target, begin, end):
"""binary search, find first target"""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def search(self, nums: List[int], target: int) -> int:
"""binary search, find first and last target in list. O(logn) time complexity."""
if not nums:
return 0
first = self.find_first(nums, target, 0, len(nums) - 1)
if first == -1:
return 0
... | the_stack_v2_python_sparse | jianzhioffer/53-1findElementInOrderedList.py | bycxw/coder | train | 0 | |
66a652ff07569da696c0478841487379c5943f8c | [
"super().__init__()\nself.in_chans = in_chans\nself.out_chans = out_chans\nself.chans = chans\nself.num_pool_layers = num_pool_layers\nself.drop_prob = drop_prob\nnew_downsample_block = nn.ModuleDict({'conv1': ConvBlock(in_chans, chans, drop_prob)})\nself.down_sample_layers = nn.ModuleList([new_downsample_block])\n... | <|body_start_0|>
super().__init__()
self.in_chans = in_chans
self.out_chans = out_chans
self.chans = chans
self.num_pool_layers = num_pool_layers
self.drop_prob = drop_prob
new_downsample_block = nn.ModuleDict({'conv1': ConvBlock(in_chans, chans, drop_prob)})
... | PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention, pages 234–241. Springer, 2015. | UnetModelAssistLatentDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnetModelAssistLatentDecoder:
"""PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted interventio... | stack_v2_sparse_classes_10k_train_001497 | 15,577 | no_license | [
{
"docstring": "Args: in_chans (int): Number of channels in the input to the U-Net model. out_chans (int): Number of channels in the output to the U-Net model. chans (int): Number of output channels of the first convolution layer. num_pool_layers (int): Number of down-sampling and up-sampling layers. drop_prob ... | 2 | stack_v2_sparse_classes_30k_train_003672 | Implement the Python class `UnetModelAssistLatentDecoder` described below.
Class description:
PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image comp... | Implement the Python class `UnetModelAssistLatentDecoder` described below.
Class description:
PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image comp... | 219652c8a08c4f2f682acd9f95a4e1b3fd36b70b | <|skeleton|>
class UnetModelAssistLatentDecoder:
"""PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted interventio... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UnetModelAssistLatentDecoder:
"""PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention, pages 234–... | the_stack_v2_python_sparse | lemawarersn_unet_conv_redundancy_removed/unetmodels.py | Bala93/Holistic-MRI-Reconstruction | train | 1 |
24332902d67fda29df625c5dc9db93a6c3971397 | [
"s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\ntry:\n s.connect((host, int(port)))\n s.shutdown(2)\n print('port %s is uesd !' % port)\n return False\nexcept:\n print('port %s is available!' % port)\n return True",
"erromessage = ''\nappium_server_url = ''\nbootstrap_port = str(port + 1... | <|body_start_0|>
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
s.connect((host, int(port)))
s.shutdown(2)
print('port %s is uesd !' % port)
return False
except:
print('port %s is available!' % port)
return True
... | AppiumServer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AppiumServer:
def check_port(self, host, port):
"""检测端口是否被占用"""
<|body_0|>
def start_appium(self, host, port):
"""启动appium 服务"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
... | stack_v2_sparse_classes_10k_train_001498 | 2,400 | no_license | [
{
"docstring": "检测端口是否被占用",
"name": "check_port",
"signature": "def check_port(self, host, port)"
},
{
"docstring": "启动appium 服务",
"name": "start_appium",
"signature": "def start_appium(self, host, port)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001915 | Implement the Python class `AppiumServer` described below.
Class description:
Implement the AppiumServer class.
Method signatures and docstrings:
- def check_port(self, host, port): 检测端口是否被占用
- def start_appium(self, host, port): 启动appium 服务 | Implement the Python class `AppiumServer` described below.
Class description:
Implement the AppiumServer class.
Method signatures and docstrings:
- def check_port(self, host, port): 检测端口是否被占用
- def start_appium(self, host, port): 启动appium 服务
<|skeleton|>
class AppiumServer:
def check_port(self, host, port):
... | 4df8ce960721407a20d89de47faad0df0de063a1 | <|skeleton|>
class AppiumServer:
def check_port(self, host, port):
"""检测端口是否被占用"""
<|body_0|>
def start_appium(self, host, port):
"""启动appium 服务"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AppiumServer:
def check_port(self, host, port):
"""检测端口是否被占用"""
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
s.connect((host, int(port)))
s.shutdown(2)
print('port %s is uesd !' % port)
return False
except:
... | the_stack_v2_python_sparse | DispatcherMobile/appiumServer.py | namexiaohuihui/operating | train | 0 | |
09ceeff88db61da4ecf6a84878bedc5302bdf39a | [
"if self.request.version == 'v6':\n return ScanDetailsSerializerV6\nelif self.request.version == 'v7':\n return ScanDetailsSerializerV6",
"if request.version == 'v6':\n return self._post_v6(request, scan_id)\nelif request.version == 'v7':\n return self._post_v6(request, scan_id)\nraise Http404()",
"... | <|body_start_0|>
if self.request.version == 'v6':
return ScanDetailsSerializerV6
elif self.request.version == 'v7':
return ScanDetailsSerializerV6
<|end_body_0|>
<|body_start_1|>
if request.version == 'v6':
return self._post_v6(request, scan_id)
elif ... | This view is the endpoint for launching a scan execution to ingest | ScansProcessView | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScansProcessView:
"""This view is the endpoint for launching a scan execution to ingest"""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
<|body_0|>
def post(self, request, scan_id=None):
"... | stack_v2_sparse_classes_10k_train_001499 | 30,689 | permissive | [
{
"docstring": "Returns the appropriate serializer based off the requests version of the REST API.",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self)"
},
{
"docstring": "Launches a scan to ingest from an existing scan model instance :param request: the HTTP POST reque... | 3 | null | Implement the Python class `ScansProcessView` described below.
Class description:
This view is the endpoint for launching a scan execution to ingest
Method signatures and docstrings:
- def get_serializer_class(self): Returns the appropriate serializer based off the requests version of the REST API.
- def post(self, r... | Implement the Python class `ScansProcessView` described below.
Class description:
This view is the endpoint for launching a scan execution to ingest
Method signatures and docstrings:
- def get_serializer_class(self): Returns the appropriate serializer based off the requests version of the REST API.
- def post(self, r... | 28618aee07ceed9e4a6eb7b8d0e6f05b31d8fd6b | <|skeleton|>
class ScansProcessView:
"""This view is the endpoint for launching a scan execution to ingest"""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
<|body_0|>
def post(self, request, scan_id=None):
"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ScansProcessView:
"""This view is the endpoint for launching a scan execution to ingest"""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
if self.request.version == 'v6':
return ScanDetailsSerializerV6
... | the_stack_v2_python_sparse | scale/ingest/views.py | kfconsultant/scale | train | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.