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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
759ff7c3d203a7ee35183d86cd5b3115d714edc0 | [
"count, base, length = ([0] * 26, ord('a'), 0)\nfor i in range(len(p)):\n if i > 0 and ord(p[i]) - ord(p[i - 1]) in (1, -25):\n length += 1\n else:\n length = 1\n index = ord(p[i]) - base\n count[index] = max(count[index], length)\nprint(count)\nreturn sum(count)",
"i, j, res = (0, 1, 0)... | <|body_start_0|>
count, base, length = ([0] * 26, ord('a'), 0)
for i in range(len(p)):
if i > 0 and ord(p[i]) - ord(p[i - 1]) in (1, -25):
length += 1
else:
length = 1
index = ord(p[i]) - base
count[index] = max(count[index]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findSubstringInWraproundString(self, p):
""":type p: str :rtype: int"""
<|body_0|>
def findSubstringInWraproundString2(self, p):
""":type p: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
count, base, length = ([0] * 2... | stack_v2_sparse_classes_10k_train_002900 | 2,158 | no_license | [
{
"docstring": ":type p: str :rtype: int",
"name": "findSubstringInWraproundString",
"signature": "def findSubstringInWraproundString(self, p)"
},
{
"docstring": ":type p: str :rtype: int",
"name": "findSubstringInWraproundString2",
"signature": "def findSubstringInWraproundString2(self,... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findSubstringInWraproundString(self, p): :type p: str :rtype: int
- def findSubstringInWraproundString2(self, p): :type p: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findSubstringInWraproundString(self, p): :type p: str :rtype: int
- def findSubstringInWraproundString2(self, p): :type p: str :rtype: int
<|skeleton|>
class Solution:
... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def findSubstringInWraproundString(self, p):
""":type p: str :rtype: int"""
<|body_0|>
def findSubstringInWraproundString2(self, p):
""":type p: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findSubstringInWraproundString(self, p):
""":type p: str :rtype: int"""
count, base, length = ([0] * 26, ord('a'), 0)
for i in range(len(p)):
if i > 0 and ord(p[i]) - ord(p[i - 1]) in (1, -25):
length += 1
else:
leng... | the_stack_v2_python_sparse | code467UniqueSubstringsInWraparoundString.py | cybelewang/leetcode-python | train | 0 | |
4d04cfdfd48f34058e147cd16bf684b413ba4533 | [
"self.name = name\nself.center = center\nself.bottom_left_corner = bottom_left_corner\nself.bottom_right_corner = bottom_right_corner\nself.top_left_corner = top_left_corner\nself.top_right_corner = top_right_corner\nself.image_contents = image_contents",
"if dictionary is None:\n return None\nname = dictionar... | <|body_start_0|>
self.name = name
self.center = center
self.bottom_left_corner = bottom_left_corner
self.bottom_right_corner = bottom_right_corner
self.top_left_corner = top_left_corner
self.top_right_corner = top_right_corner
self.image_contents = image_contents
... | Implementation of the 'updateNetworkFloorPlan' model. TODO: type model description here. Attributes: name (string): The name of your floor plan. center (Center1Model): The longitude and latitude of the center of your floor plan. If you want to change the geolocation data of your floor plan, either the 'center' or two a... | UpdateNetworkFloorPlanModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNetworkFloorPlanModel:
"""Implementation of the 'updateNetworkFloorPlan' model. TODO: type model description here. Attributes: name (string): The name of your floor plan. center (Center1Model): The longitude and latitude of the center of your floor plan. If you want to change the geolocatio... | stack_v2_sparse_classes_10k_train_002901 | 5,591 | permissive | [
{
"docstring": "Constructor for the UpdateNetworkFloorPlanModel class",
"name": "__init__",
"signature": "def __init__(self, name=None, center=None, bottom_left_corner=None, bottom_right_corner=None, top_left_corner=None, top_right_corner=None, image_contents=None)"
},
{
"docstring": "Creates an... | 2 | null | Implement the Python class `UpdateNetworkFloorPlanModel` described below.
Class description:
Implementation of the 'updateNetworkFloorPlan' model. TODO: type model description here. Attributes: name (string): The name of your floor plan. center (Center1Model): The longitude and latitude of the center of your floor pla... | Implement the Python class `UpdateNetworkFloorPlanModel` described below.
Class description:
Implementation of the 'updateNetworkFloorPlan' model. TODO: type model description here. Attributes: name (string): The name of your floor plan. center (Center1Model): The longitude and latitude of the center of your floor pla... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class UpdateNetworkFloorPlanModel:
"""Implementation of the 'updateNetworkFloorPlan' model. TODO: type model description here. Attributes: name (string): The name of your floor plan. center (Center1Model): The longitude and latitude of the center of your floor plan. If you want to change the geolocatio... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UpdateNetworkFloorPlanModel:
"""Implementation of the 'updateNetworkFloorPlan' model. TODO: type model description here. Attributes: name (string): The name of your floor plan. center (Center1Model): The longitude and latitude of the center of your floor plan. If you want to change the geolocation data of you... | the_stack_v2_python_sparse | meraki_sdk/models/update_network_floor_plan_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
088ac256a3cf15785085c494bc69912280c63774 | [
"client = mock_client(mocker)\nargs = {'user-profile': {'email': 'testdemisto2@paloaltonetworks.com', 'givenname': 'mock_first_name'}}\nmocker.patch.object(client, 'get_user', return_value=None)\nmocker.patch.object(IAMUserProfile, 'map_object', return_value={})\nmocker.patch.object(client, 'create_user', return_va... | <|body_start_0|>
client = mock_client(mocker)
args = {'user-profile': {'email': 'testdemisto2@paloaltonetworks.com', 'givenname': 'mock_first_name'}}
mocker.patch.object(client, 'get_user', return_value=None)
mocker.patch.object(IAMUserProfile, 'map_object', return_value={})
mock... | Class to group the update user commands test | TestUpdateUserCommand | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestUpdateUserCommand:
"""Class to group the update user commands test"""
def test_update_user_command__non_existing_user(self, mocker):
"""Given: - An app client object - A user-profile argument that contains user data When: - The user does not exist in the application - create-if-n... | stack_v2_sparse_classes_10k_train_002902 | 13,964 | permissive | [
{
"docstring": "Given: - An app client object - A user-profile argument that contains user data When: - The user does not exist in the application - create-if-not-exists parameter is checked - Create User command is enabled - Calling function update_user_command Then: - Ensure the create action is executed - En... | 3 | null | Implement the Python class `TestUpdateUserCommand` described below.
Class description:
Class to group the update user commands test
Method signatures and docstrings:
- def test_update_user_command__non_existing_user(self, mocker): Given: - An app client object - A user-profile argument that contains user data When: -... | Implement the Python class `TestUpdateUserCommand` described below.
Class description:
Class to group the update user commands test
Method signatures and docstrings:
- def test_update_user_command__non_existing_user(self, mocker): Given: - An app client object - A user-profile argument that contains user data When: -... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class TestUpdateUserCommand:
"""Class to group the update user commands test"""
def test_update_user_command__non_existing_user(self, mocker):
"""Given: - An app client object - A user-profile argument that contains user data When: - The user does not exist in the application - create-if-n... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestUpdateUserCommand:
"""Class to group the update user commands test"""
def test_update_user_command__non_existing_user(self, mocker):
"""Given: - An app client object - A user-profile argument that contains user data When: - The user does not exist in the application - create-if-not-exists par... | the_stack_v2_python_sparse | Packs/PrismaCloud/Integrations/PrismaCloudIAM/PrismaCloudIAM_test.py | demisto/content | train | 1,023 |
d212b6c73ece8e4a11261fbf50c893dddbce2086 | [
"def canShip(m):\n t, days = (0, 0)\n for w in weights:\n if t + w > m:\n days += 1\n t = w\n else:\n t += w\n return days + 1 <= D\nl, r = (max(weights), sum(weights))\nwhile l < r:\n mid = l + (r - l) // 2\n if canShip(mid):\n r = mid\n else:... | <|body_start_0|>
def canShip(m):
t, days = (0, 0)
for w in weights:
if t + w > m:
days += 1
t = w
else:
t += w
return days + 1 <= D
l, r = (max(weights), sum(weights))
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shipWithinDaysAC(self, weights, D):
""":type weights: List[int] :type D: int :rtype: int"""
<|body_0|>
def shipWithinDays(self, weights, D):
""":type weights: List[int] :type D: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_002903 | 3,083 | no_license | [
{
"docstring": ":type weights: List[int] :type D: int :rtype: int",
"name": "shipWithinDaysAC",
"signature": "def shipWithinDaysAC(self, weights, D)"
},
{
"docstring": ":type weights: List[int] :type D: int :rtype: int",
"name": "shipWithinDays",
"signature": "def shipWithinDays(self, we... | 2 | stack_v2_sparse_classes_30k_train_003141 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shipWithinDaysAC(self, weights, D): :type weights: List[int] :type D: int :rtype: int
- def shipWithinDays(self, weights, D): :type weights: List[int] :type D: int :rtype: in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shipWithinDaysAC(self, weights, D): :type weights: List[int] :type D: int :rtype: int
- def shipWithinDays(self, weights, D): :type weights: List[int] :type D: int :rtype: in... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def shipWithinDaysAC(self, weights, D):
""":type weights: List[int] :type D: int :rtype: int"""
<|body_0|>
def shipWithinDays(self, weights, D):
""":type weights: List[int] :type D: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def shipWithinDaysAC(self, weights, D):
""":type weights: List[int] :type D: int :rtype: int"""
def canShip(m):
t, days = (0, 0)
for w in weights:
if t + w > m:
days += 1
t = w
else:
... | the_stack_v2_python_sparse | C/CapacityToShipPackagesWithinDDays.py | bssrdf/pyleet | train | 2 | |
9c92fbd9297794a203831d22c596a06ad3f1623d | [
"Presentation.__init__(self, pere, detail, attribut, False)\nif pere and detail:\n self.construire(detail)",
"detail = self.objet\nsalle = detail.parent\nnouveau_nom = supprimer_accents(arguments)\nif not nouveau_nom:\n self.pere << '|err|Vous devez indiquer un nouveau nom.|ff|'\n return\nif nouveau_nom ... | <|body_start_0|>
Presentation.__init__(self, pere, detail, attribut, False)
if pere and detail:
self.construire(detail)
<|end_body_0|>
<|body_start_1|>
detail = self.objet
salle = detail.parent
nouveau_nom = supprimer_accents(arguments)
if not nouveau_nom:
... | Ce contexte permet d'éditer un detail observable d'une salle. | EdtDetail | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EdtDetail:
"""Ce contexte permet d'éditer un detail observable d'une salle."""
def __init__(self, pere, detail=None, attribut=None):
"""Constructeur de l'éditeur"""
<|body_0|>
def opt_renommer_detail(self, arguments):
"""Renomme le détail courant. Syntaxe : /n <n... | stack_v2_sparse_classes_10k_train_002904 | 7,487 | permissive | [
{
"docstring": "Constructeur de l'éditeur",
"name": "__init__",
"signature": "def __init__(self, pere, detail=None, attribut=None)"
},
{
"docstring": "Renomme le détail courant. Syntaxe : /n <nouveau nom>",
"name": "opt_renommer_detail",
"signature": "def opt_renommer_detail(self, argume... | 4 | null | Implement the Python class `EdtDetail` described below.
Class description:
Ce contexte permet d'éditer un detail observable d'une salle.
Method signatures and docstrings:
- def __init__(self, pere, detail=None, attribut=None): Constructeur de l'éditeur
- def opt_renommer_detail(self, arguments): Renomme le détail cou... | Implement the Python class `EdtDetail` described below.
Class description:
Ce contexte permet d'éditer un detail observable d'une salle.
Method signatures and docstrings:
- def __init__(self, pere, detail=None, attribut=None): Constructeur de l'éditeur
- def opt_renommer_detail(self, arguments): Renomme le détail cou... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class EdtDetail:
"""Ce contexte permet d'éditer un detail observable d'une salle."""
def __init__(self, pere, detail=None, attribut=None):
"""Constructeur de l'éditeur"""
<|body_0|>
def opt_renommer_detail(self, arguments):
"""Renomme le détail courant. Syntaxe : /n <n... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EdtDetail:
"""Ce contexte permet d'éditer un detail observable d'une salle."""
def __init__(self, pere, detail=None, attribut=None):
"""Constructeur de l'éditeur"""
Presentation.__init__(self, pere, detail, attribut, False)
if pere and detail:
self.construire(detail)
... | the_stack_v2_python_sparse | src/primaires/salle/editeurs/redit/edt_detail.py | vincent-lg/tsunami | train | 5 |
f566e586deb45031b1ca6f316e5f706fa765db5c | [
"self = object.__new__(cls)\nself.name = value\nself.value = value\nself.metadata_type = RoleManagerMetadataBase\nreturn self",
"self.name = name\nself.value = value\nself.metadata_type = metadata_type\nself.INSTANCES[value] = self",
"if self.value:\n boolean = True\nelse:\n boolean = False\nreturn boolea... | <|body_start_0|>
self = object.__new__(cls)
self.name = value
self.value = value
self.metadata_type = RoleManagerMetadataBase
return self
<|end_body_0|>
<|body_start_1|>
self.name = name
self.value = value
self.metadata_type = metadata_type
self.I... | Represents a managed role's manager type. Attributes ---------- name : `str` The name of the role manager type. value : `int` The identifier value the role manager type. Class Attributes ---------------- INSTANCES : `dict` of (`int`, ``RoleManagerType``) items Stores the predefined ``RoleManagerType``-s. These can be a... | RoleManagerType | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoleManagerType:
"""Represents a managed role's manager type. Attributes ---------- name : `str` The name of the role manager type. value : `int` The identifier value the role manager type. Class Attributes ---------------- INSTANCES : `dict` of (`int`, ``RoleManagerType``) items Stores the prede... | stack_v2_sparse_classes_10k_train_002905 | 5,532 | permissive | [
{
"docstring": "Creates a new role manager type with the given value. Parameters ---------- value : `int` Value representing the role manager. Returns ------- self : `instance<cls>`",
"name": "_from_value",
"signature": "def _from_value(cls, value)"
},
{
"docstring": "Creates a new scheduled eve... | 3 | null | Implement the Python class `RoleManagerType` described below.
Class description:
Represents a managed role's manager type. Attributes ---------- name : `str` The name of the role manager type. value : `int` The identifier value the role manager type. Class Attributes ---------------- INSTANCES : `dict` of (`int`, ``Ro... | Implement the Python class `RoleManagerType` described below.
Class description:
Represents a managed role's manager type. Attributes ---------- name : `str` The name of the role manager type. value : `int` The identifier value the role manager type. Class Attributes ---------------- INSTANCES : `dict` of (`int`, ``Ro... | 53f24fdb38459dc5a4fd04f11bdbfee8295b76a4 | <|skeleton|>
class RoleManagerType:
"""Represents a managed role's manager type. Attributes ---------- name : `str` The name of the role manager type. value : `int` The identifier value the role manager type. Class Attributes ---------------- INSTANCES : `dict` of (`int`, ``RoleManagerType``) items Stores the prede... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RoleManagerType:
"""Represents a managed role's manager type. Attributes ---------- name : `str` The name of the role manager type. value : `int` The identifier value the role manager type. Class Attributes ---------------- INSTANCES : `dict` of (`int`, ``RoleManagerType``) items Stores the predefined ``RoleM... | the_stack_v2_python_sparse | hata/discord/role/role/preinstanced.py | HuyaneMatsu/hata | train | 3 |
35f62cef9101337ed9ba64411ad848447a7b3c3e | [
"self.field_config = field_config\nself.tokenizer = None\nself.token_embedding = None\nif field_config.vocab_path and field_config.need_convert:\n self.tokenizer = CustomTokenizer(vocab_file=self.field_config.vocab_path)",
"src_ids = []\nfor text in batch_text:\n src_id = text.split(' ')\n if self.tokeni... | <|body_start_0|>
self.field_config = field_config
self.tokenizer = None
self.token_embedding = None
if field_config.vocab_path and field_config.need_convert:
self.tokenizer = CustomTokenizer(vocab_file=self.field_config.vocab_path)
<|end_body_0|>
<|body_start_1|>
src... | return shape= [batch_size,1] | ScalarFieldReader | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScalarFieldReader:
"""return shape= [batch_size,1]"""
def __init__(self, field_config):
""":param field_config:"""
<|body_0|>
def convert_texts_to_ids(self, batch_text):
""":param batch_text: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_002906 | 2,055 | permissive | [
{
"docstring": ":param field_config:",
"name": "__init__",
"signature": "def __init__(self, field_config)"
},
{
"docstring": ":param batch_text: :return:",
"name": "convert_texts_to_ids",
"signature": "def convert_texts_to_ids(self, batch_text)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001728 | Implement the Python class `ScalarFieldReader` described below.
Class description:
return shape= [batch_size,1]
Method signatures and docstrings:
- def __init__(self, field_config): :param field_config:
- def convert_texts_to_ids(self, batch_text): :param batch_text: :return: | Implement the Python class `ScalarFieldReader` described below.
Class description:
return shape= [batch_size,1]
Method signatures and docstrings:
- def __init__(self, field_config): :param field_config:
- def convert_texts_to_ids(self, batch_text): :param batch_text: :return:
<|skeleton|>
class ScalarFieldReader:
... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class ScalarFieldReader:
"""return shape= [batch_size,1]"""
def __init__(self, field_config):
""":param field_config:"""
<|body_0|>
def convert_texts_to_ids(self, batch_text):
""":param batch_text: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ScalarFieldReader:
"""return shape= [batch_size,1]"""
def __init__(self, field_config):
""":param field_config:"""
self.field_config = field_config
self.tokenizer = None
self.token_embedding = None
if field_config.vocab_path and field_config.need_convert:
... | the_stack_v2_python_sparse | research/nlp/senta/src/data/field_reader/scalar_field_reader.py | mindspore-ai/models | train | 301 |
4a3d25c7358022048e0f534ec908b5337c91dbe5 | [
"self.config = config\nself.binary = libp2p_node_binary\nself._proc = None",
"config_file = '.acn_config'\nself.config.dump(config_file)\ncmd = [self.binary, config_file]\nif self.config.config[AcnNodeConfig.ACN_LOG_FILE] != '':\n self._proc = subprocess.Popen(cmd, shell=False, stdout=subprocess.PIPE, stderr=s... | <|body_start_0|>
self.config = config
self.binary = libp2p_node_binary
self._proc = None
<|end_body_0|>
<|body_start_1|>
config_file = '.acn_config'
self.config.dump(config_file)
cmd = [self.binary, config_file]
if self.config.config[AcnNodeConfig.ACN_LOG_FILE] !... | Deploy an acn node in standalone mode. | AcnNodeStandalone | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AcnNodeStandalone:
"""Deploy an acn node in standalone mode."""
def __init__(self, config: AcnNodeConfig, libp2p_node_binary: str):
"""Initialize a new AcnNodeStandalone object. :param config: node's configuration :param libp2p_node_binary: path to libp2p node binary"""
<|bod... | stack_v2_sparse_classes_10k_train_002907 | 12,337 | permissive | [
{
"docstring": "Initialize a new AcnNodeStandalone object. :param config: node's configuration :param libp2p_node_binary: path to libp2p node binary",
"name": "__init__",
"signature": "def __init__(self, config: AcnNodeConfig, libp2p_node_binary: str)"
},
{
"docstring": "Run the node.",
"nam... | 3 | null | Implement the Python class `AcnNodeStandalone` described below.
Class description:
Deploy an acn node in standalone mode.
Method signatures and docstrings:
- def __init__(self, config: AcnNodeConfig, libp2p_node_binary: str): Initialize a new AcnNodeStandalone object. :param config: node's configuration :param libp2p... | Implement the Python class `AcnNodeStandalone` described below.
Class description:
Deploy an acn node in standalone mode.
Method signatures and docstrings:
- def __init__(self, config: AcnNodeConfig, libp2p_node_binary: str): Initialize a new AcnNodeStandalone object. :param config: node's configuration :param libp2p... | bec49adaeba661d8d0f03ac9935dc89f39d95a0d | <|skeleton|>
class AcnNodeStandalone:
"""Deploy an acn node in standalone mode."""
def __init__(self, config: AcnNodeConfig, libp2p_node_binary: str):
"""Initialize a new AcnNodeStandalone object. :param config: node's configuration :param libp2p_node_binary: path to libp2p node binary"""
<|bod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AcnNodeStandalone:
"""Deploy an acn node in standalone mode."""
def __init__(self, config: AcnNodeConfig, libp2p_node_binary: str):
"""Initialize a new AcnNodeStandalone object. :param config: node's configuration :param libp2p_node_binary: path to libp2p node binary"""
self.config = conf... | the_stack_v2_python_sparse | scripts/acn/run_acn_node_standalone.py | fetchai/agents-aea | train | 192 |
5e45f898473d8664befd3d2f16c416a7138cd3f2 | [
"concept_parsers.ConceptParser([flags.GetReplicationPresentationSpec('The Replication to create.')]).AddToParser(parser)\nreplications_flags.AddReplicationVolumeArg(parser)\nreplications_flags.AddReplicationReplicationScheduleArg(parser)\nreplications_flags.AddReplicationDestinationVolumeParametersArg(parser)\nflag... | <|body_start_0|>
concept_parsers.ConceptParser([flags.GetReplicationPresentationSpec('The Replication to create.')]).AddToParser(parser)
replications_flags.AddReplicationVolumeArg(parser)
replications_flags.AddReplicationReplicationScheduleArg(parser)
replications_flags.AddReplicationDes... | Create a Cloud NetApp Volume Replication. | Create | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Create:
"""Create a Cloud NetApp Volume Replication."""
def Args(parser):
"""Add args for creating a Replication."""
<|body_0|>
def Run(self, args):
"""Create a Cloud NetApp Volume Replication in the current project."""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_10k_train_002908 | 4,060 | permissive | [
{
"docstring": "Add args for creating a Replication.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "Create a Cloud NetApp Volume Replication in the current project.",
"name": "Run",
"signature": "def Run(self, args)"
}
] | 2 | null | Implement the Python class `Create` described below.
Class description:
Create a Cloud NetApp Volume Replication.
Method signatures and docstrings:
- def Args(parser): Add args for creating a Replication.
- def Run(self, args): Create a Cloud NetApp Volume Replication in the current project. | Implement the Python class `Create` described below.
Class description:
Create a Cloud NetApp Volume Replication.
Method signatures and docstrings:
- def Args(parser): Add args for creating a Replication.
- def Run(self, args): Create a Cloud NetApp Volume Replication in the current project.
<|skeleton|>
class Creat... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class Create:
"""Create a Cloud NetApp Volume Replication."""
def Args(parser):
"""Add args for creating a Replication."""
<|body_0|>
def Run(self, args):
"""Create a Cloud NetApp Volume Replication in the current project."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Create:
"""Create a Cloud NetApp Volume Replication."""
def Args(parser):
"""Add args for creating a Replication."""
concept_parsers.ConceptParser([flags.GetReplicationPresentationSpec('The Replication to create.')]).AddToParser(parser)
replications_flags.AddReplicationVolumeArg(p... | the_stack_v2_python_sparse | lib/surface/netapp/volumes/replications/create.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
26537d9382d6f8363261e12c6a0c4e880ac9a552 | [
"self.force_delete = force_delete\nself.id = id\nself.include_marked_for_removal = include_marked_for_removal\nself.retry = retry",
"if dictionary is None:\n return None\nforce_delete = dictionary.get('forceDelete')\nid = dictionary.get('id')\ninclude_marked_for_removal = dictionary.get('includeMarkedForRemova... | <|body_start_0|>
self.force_delete = force_delete
self.id = id
self.include_marked_for_removal = include_marked_for_removal
self.retry = retry
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
force_delete = dictionary.get('forceDelete')
... | Implementation of the 'VaultDeleteParams' model. VaultDeleteParams represents the parameters needed to delete a specific vault. Attributes: force_delete (bool): Specifies whether to force delete the vault. If the flag is set to true, the RemovalState of the vault is changed to 'kMarkedForRemoval' and Eventually vault i... | VaultDeleteParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VaultDeleteParams:
"""Implementation of the 'VaultDeleteParams' model. VaultDeleteParams represents the parameters needed to delete a specific vault. Attributes: force_delete (bool): Specifies whether to force delete the vault. If the flag is set to true, the RemovalState of the vault is changed ... | stack_v2_sparse_classes_10k_train_002909 | 2,521 | permissive | [
{
"docstring": "Constructor for the VaultDeleteParams class",
"name": "__init__",
"signature": "def __init__(self, force_delete=None, id=None, include_marked_for_removal=None, retry=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dic... | 2 | stack_v2_sparse_classes_30k_train_007150 | Implement the Python class `VaultDeleteParams` described below.
Class description:
Implementation of the 'VaultDeleteParams' model. VaultDeleteParams represents the parameters needed to delete a specific vault. Attributes: force_delete (bool): Specifies whether to force delete the vault. If the flag is set to true, th... | Implement the Python class `VaultDeleteParams` described below.
Class description:
Implementation of the 'VaultDeleteParams' model. VaultDeleteParams represents the parameters needed to delete a specific vault. Attributes: force_delete (bool): Specifies whether to force delete the vault. If the flag is set to true, th... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class VaultDeleteParams:
"""Implementation of the 'VaultDeleteParams' model. VaultDeleteParams represents the parameters needed to delete a specific vault. Attributes: force_delete (bool): Specifies whether to force delete the vault. If the flag is set to true, the RemovalState of the vault is changed ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VaultDeleteParams:
"""Implementation of the 'VaultDeleteParams' model. VaultDeleteParams represents the parameters needed to delete a specific vault. Attributes: force_delete (bool): Specifies whether to force delete the vault. If the flag is set to true, the RemovalState of the vault is changed to 'kMarkedFo... | the_stack_v2_python_sparse | cohesity_management_sdk/models/vault_delete_params.py | cohesity/management-sdk-python | train | 24 |
34725e46b81bebc569953c20c9ab09eedc7576e0 | [
"self.name = name\nself.subnet = subnet\nself.appliance_ip = appliance_ip\nself.vpn_nat_subnet = vpn_nat_subnet\nself.dhcp_handling = dhcp_handling\nself.dhcp_relay_server_ips = dhcp_relay_server_ips\nself.dhcp_lease_time = dhcp_lease_time\nself.dhcp_boot_options_enabled = dhcp_boot_options_enabled\nself.dhcp_boot_... | <|body_start_0|>
self.name = name
self.subnet = subnet
self.appliance_ip = appliance_ip
self.vpn_nat_subnet = vpn_nat_subnet
self.dhcp_handling = dhcp_handling
self.dhcp_relay_server_ips = dhcp_relay_server_ips
self.dhcp_lease_time = dhcp_lease_time
self.d... | Implementation of the 'updateNetworkVlan' model. TODO: type model description here. Attributes: name (string): The name of the VLAN subnet (string): The subnet of the VLAN appliance_ip (string): The local IP of the appliance on the VLAN vpn_nat_subnet (string): The translated VPN subnet if VPN and VPN subnet translatio... | UpdateNetworkVlanModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNetworkVlanModel:
"""Implementation of the 'updateNetworkVlan' model. TODO: type model description here. Attributes: name (string): The name of the VLAN subnet (string): The subnet of the VLAN appliance_ip (string): The local IP of the appliance on the VLAN vpn_nat_subnet (string): The tran... | stack_v2_sparse_classes_10k_train_002910 | 7,095 | permissive | [
{
"docstring": "Constructor for the UpdateNetworkVlanModel class",
"name": "__init__",
"signature": "def __init__(self, name=None, subnet=None, appliance_ip=None, vpn_nat_subnet=None, dhcp_handling=None, dhcp_relay_server_ips=None, dhcp_lease_time=None, dhcp_boot_options_enabled=None, dhcp_boot_next_ser... | 2 | stack_v2_sparse_classes_30k_train_003907 | Implement the Python class `UpdateNetworkVlanModel` described below.
Class description:
Implementation of the 'updateNetworkVlan' model. TODO: type model description here. Attributes: name (string): The name of the VLAN subnet (string): The subnet of the VLAN appliance_ip (string): The local IP of the appliance on the... | Implement the Python class `UpdateNetworkVlanModel` described below.
Class description:
Implementation of the 'updateNetworkVlan' model. TODO: type model description here. Attributes: name (string): The name of the VLAN subnet (string): The subnet of the VLAN appliance_ip (string): The local IP of the appliance on the... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class UpdateNetworkVlanModel:
"""Implementation of the 'updateNetworkVlan' model. TODO: type model description here. Attributes: name (string): The name of the VLAN subnet (string): The subnet of the VLAN appliance_ip (string): The local IP of the appliance on the VLAN vpn_nat_subnet (string): The tran... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UpdateNetworkVlanModel:
"""Implementation of the 'updateNetworkVlan' model. TODO: type model description here. Attributes: name (string): The name of the VLAN subnet (string): The subnet of the VLAN appliance_ip (string): The local IP of the appliance on the VLAN vpn_nat_subnet (string): The translated VPN su... | the_stack_v2_python_sparse | meraki_sdk/models/update_network_vlan_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
795453f10a85f9fe6bbec59c84e15847f13d9090 | [
"self.id = id\nself.number = number\nself.name = name\nself.balance = balance\nself.mtype = mtype\nself.status = status\nself.customer_id = customer_id\nself.institution_id = institution_id\nself.balance_date = balance_date\nself.created_date = created_date\nself.currency = currency\nself.institution_login_id = ins... | <|body_start_0|>
self.id = id
self.number = number
self.name = name
self.balance = balance
self.mtype = mtype
self.status = status
self.customer_id = customer_id
self.institution_id = institution_id
self.balance_date = balance_date
self.cre... | Implementation of the 'Account1' model. TODO: type model description here. Attributes: id (string): TODO: type description here. number (string): TODO: type description here. name (string): TODO: type description here. balance (float): TODO: type description here. mtype (string): TODO: type description here. status (st... | Account1 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Account1:
"""Implementation of the 'Account1' model. TODO: type model description here. Attributes: id (string): TODO: type description here. number (string): TODO: type description here. name (string): TODO: type description here. balance (float): TODO: type description here. mtype (string): TOD... | stack_v2_sparse_classes_10k_train_002911 | 4,584 | permissive | [
{
"docstring": "Constructor for the Account1 class",
"name": "__init__",
"signature": "def __init__(self, id=None, number=None, name=None, balance=None, mtype=None, status=None, customer_id=None, institution_id=None, balance_date=None, created_date=None, currency=None, institution_login_id=None, display... | 2 | stack_v2_sparse_classes_30k_train_001271 | Implement the Python class `Account1` described below.
Class description:
Implementation of the 'Account1' model. TODO: type model description here. Attributes: id (string): TODO: type description here. number (string): TODO: type description here. name (string): TODO: type description here. balance (float): TODO: typ... | Implement the Python class `Account1` described below.
Class description:
Implementation of the 'Account1' model. TODO: type model description here. Attributes: id (string): TODO: type description here. number (string): TODO: type description here. name (string): TODO: type description here. balance (float): TODO: typ... | b2ab1ded435db75c78d42261f5e4acd2a3061487 | <|skeleton|>
class Account1:
"""Implementation of the 'Account1' model. TODO: type model description here. Attributes: id (string): TODO: type description here. number (string): TODO: type description here. name (string): TODO: type description here. balance (float): TODO: type description here. mtype (string): TOD... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Account1:
"""Implementation of the 'Account1' model. TODO: type model description here. Attributes: id (string): TODO: type description here. number (string): TODO: type description here. name (string): TODO: type description here. balance (float): TODO: type description here. mtype (string): TODO: type descr... | the_stack_v2_python_sparse | finicityapi/models/account_1.py | monarchmoney/finicity-python | train | 0 |
948828e5464d4d07cb1299bb678291e4a74e6529 | [
"import Dice\nnumber = Dice.dice.Dicerolling(self)\nres = number\nexp = Dice.dice.rollGet(self)\nself.assertEqual(res, exp)",
"import Dice\nnumber = Dice.dice.Dicerolling(self)\nres = number\nexp = 1 <= res <= 6\nself.assertTrue(exp)"
] | <|body_start_0|>
import Dice
number = Dice.dice.Dicerolling(self)
res = number
exp = Dice.dice.rollGet(self)
self.assertEqual(res, exp)
<|end_body_0|>
<|body_start_1|>
import Dice
number = Dice.dice.Dicerolling(self)
res = number
exp = 1 <= res <=... | This is the unittest for the class Dice | dicetest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class dicetest:
"""This is the unittest for the class Dice"""
def testdice1(self):
"""Tests if rollGet returns the correct number"""
<|body_0|>
def testdice2(self):
"""Tests if the dice rolling works, giving a number between 1-6"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_10k_train_002912 | 637 | permissive | [
{
"docstring": "Tests if rollGet returns the correct number",
"name": "testdice1",
"signature": "def testdice1(self)"
},
{
"docstring": "Tests if the dice rolling works, giving a number between 1-6",
"name": "testdice2",
"signature": "def testdice2(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001005 | Implement the Python class `dicetest` described below.
Class description:
This is the unittest for the class Dice
Method signatures and docstrings:
- def testdice1(self): Tests if rollGet returns the correct number
- def testdice2(self): Tests if the dice rolling works, giving a number between 1-6 | Implement the Python class `dicetest` described below.
Class description:
This is the unittest for the class Dice
Method signatures and docstrings:
- def testdice1(self): Tests if rollGet returns the correct number
- def testdice2(self): Tests if the dice rolling works, giving a number between 1-6
<|skeleton|>
class... | 73a8962c762ff48da331c9212f10676f066ed940 | <|skeleton|>
class dicetest:
"""This is the unittest for the class Dice"""
def testdice1(self):
"""Tests if rollGet returns the correct number"""
<|body_0|>
def testdice2(self):
"""Tests if the dice rolling works, giving a number between 1-6"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class dicetest:
"""This is the unittest for the class Dice"""
def testdice1(self):
"""Tests if rollGet returns the correct number"""
import Dice
number = Dice.dice.Dicerolling(self)
res = number
exp = Dice.dice.rollGet(self)
self.assertEqual(res, exp)
def te... | the_stack_v2_python_sparse | methoddice/testdice.py | JohanK91/MethodDice | train | 0 |
8a62f6b885148ba8f39a86c9eaf934d56ee9c4e4 | [
"with tf.name_scope('MaskedLMTask/losses'):\n metrics = dict([(metric.name, metric) for metric in metrics])\n lm_prediction_losses = tf.keras.losses.sparse_categorical_crossentropy(labels['masked_lm_ids'], tf.cast(model_outputs['mlm_logits'], tf.float32), from_logits=True)\n lm_label_weights = labels['mask... | <|body_start_0|>
with tf.name_scope('MaskedLMTask/losses'):
metrics = dict([(metric.name, metric) for metric in metrics])
lm_prediction_losses = tf.keras.losses.sparse_categorical_crossentropy(labels['masked_lm_ids'], tf.cast(model_outputs['mlm_logits'], tf.float32), from_logits=True)
... | Task object for Mask language modeling. | TokenDropMaskedLMTask | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TokenDropMaskedLMTask:
"""Task object for Mask language modeling."""
def build_losses(self, labels, model_outputs, metrics, aux_losses=None) -> Tuple[tf.Tensor, tf.Tensor]:
"""Return the final loss, and the masked-lm loss."""
<|body_0|>
def train_step(self, inputs, model... | stack_v2_sparse_classes_10k_train_002913 | 4,551 | permissive | [
{
"docstring": "Return the final loss, and the masked-lm loss.",
"name": "build_losses",
"signature": "def build_losses(self, labels, model_outputs, metrics, aux_losses=None) -> Tuple[tf.Tensor, tf.Tensor]"
},
{
"docstring": "Does forward and backward. Args: inputs: a dictionary of input tensors... | 3 | stack_v2_sparse_classes_30k_train_000113 | Implement the Python class `TokenDropMaskedLMTask` described below.
Class description:
Task object for Mask language modeling.
Method signatures and docstrings:
- def build_losses(self, labels, model_outputs, metrics, aux_losses=None) -> Tuple[tf.Tensor, tf.Tensor]: Return the final loss, and the masked-lm loss.
- de... | Implement the Python class `TokenDropMaskedLMTask` described below.
Class description:
Task object for Mask language modeling.
Method signatures and docstrings:
- def build_losses(self, labels, model_outputs, metrics, aux_losses=None) -> Tuple[tf.Tensor, tf.Tensor]: Return the final loss, and the masked-lm loss.
- de... | d3507b550a3ade40cade60a79eb5b8978b56c7ae | <|skeleton|>
class TokenDropMaskedLMTask:
"""Task object for Mask language modeling."""
def build_losses(self, labels, model_outputs, metrics, aux_losses=None) -> Tuple[tf.Tensor, tf.Tensor]:
"""Return the final loss, and the masked-lm loss."""
<|body_0|>
def train_step(self, inputs, model... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TokenDropMaskedLMTask:
"""Task object for Mask language modeling."""
def build_losses(self, labels, model_outputs, metrics, aux_losses=None) -> Tuple[tf.Tensor, tf.Tensor]:
"""Return the final loss, and the masked-lm loss."""
with tf.name_scope('MaskedLMTask/losses'):
metrics ... | the_stack_v2_python_sparse | official/projects/token_dropping/masked_lm.py | jianzhnie/models | train | 2 |
51671e0eb5829e6c208b4dd7afd3867a921e3492 | [
"p = hyperparams.Params()\nif not m:\n return p\ndesc = 'See comments for {msg} for description'.format(msg=m.full_name)\nfor f in m.fields:\n if f.containing_oneof:\n continue\n if omit and f.full_name in omit:\n continue\n if f.label == descriptor.FieldDescriptor.LABEL_REPEATED:\n ... | <|body_start_0|>
p = hyperparams.Params()
if not m:
return p
desc = 'See comments for {msg} for description'.format(msg=m.full_name)
for f in m.fields:
if f.containing_oneof:
continue
if omit and f.full_name in omit:
con... | Generate default hyper params for dynamic config components. | Util | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Util:
"""Generate default hyper params for dynamic config components."""
def CreateParamsForMessage(cls, m, omit=None):
"""Proto to hyper params conversion. Method will define hyperparameters matching a protocol message. Each field added will match the proto field names. Nested messa... | stack_v2_sparse_classes_10k_train_002914 | 4,230 | permissive | [
{
"docstring": "Proto to hyper params conversion. Method will define hyperparameters matching a protocol message. Each field added will match the proto field names. Nested messages will be added recursively. Parameters will be initialized to None or the empty list. Note that one_of messages are skipped and no h... | 3 | null | Implement the Python class `Util` described below.
Class description:
Generate default hyper params for dynamic config components.
Method signatures and docstrings:
- def CreateParamsForMessage(cls, m, omit=None): Proto to hyper params conversion. Method will define hyperparameters matching a protocol message. Each f... | Implement the Python class `Util` described below.
Class description:
Generate default hyper params for dynamic config components.
Method signatures and docstrings:
- def CreateParamsForMessage(cls, m, omit=None): Proto to hyper params conversion. Method will define hyperparameters matching a protocol message. Each f... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class Util:
"""Generate default hyper params for dynamic config components."""
def CreateParamsForMessage(cls, m, omit=None):
"""Proto to hyper params conversion. Method will define hyperparameters matching a protocol message. Each field added will match the proto field names. Nested messa... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Util:
"""Generate default hyper params for dynamic config components."""
def CreateParamsForMessage(cls, m, omit=None):
"""Proto to hyper params conversion. Method will define hyperparameters matching a protocol message. Each field added will match the proto field names. Nested messages will be a... | the_stack_v2_python_sparse | cognate_inpaint_neighbors/neighbors/model/util.py | Jimmy-INL/google-research | train | 1 |
fa3038ae9ffe3c69d5ffed859cbfa10975664a3b | [
"self.problem = problem\nself.u = problem.T\nself.params = {'snes_type': 'newtonls', 'mat_type': 'matfree', 'ksp_type': 'gmres', 'pc_type': 'python', 'pc_python_type': 'firedrake.AssembledPC', 'assembled_pc_type': 'hypre', 'assembled_pc_factor_mat_solver_type': 'mumps', 'assembled_pc_hypre_type': 'boomeramg', 'asse... | <|body_start_0|>
self.problem = problem
self.u = problem.T
self.params = {'snes_type': 'newtonls', 'mat_type': 'matfree', 'ksp_type': 'gmres', 'pc_type': 'python', 'pc_python_type': 'firedrake.AssembledPC', 'assembled_pc_type': 'hypre', 'assembled_pc_factor_mat_solver_type': 'mumps', 'assembled_... | A class for the solver. Attributes: problem (TTiP.problem.Problem (or subclass)): The problem to solve. u (firedrake.Function): The variable to solve for in the problem. params (dict): The parameters passed to the solver. | Solver | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solver:
"""A class for the solver. Attributes: problem (TTiP.problem.Problem (or subclass)): The problem to solve. u (firedrake.Function): The variable to solve for in the problem. params (dict): The parameters passed to the solver."""
def __init__(self, problem):
"""Initialise the S... | stack_v2_sparse_classes_10k_train_002915 | 3,977 | permissive | [
{
"docstring": "Initialise the Solver. Args: problem (TTiP.problem.Problem): The problem to solve.",
"name": "__init__",
"signature": "def __init__(self, problem)"
},
{
"docstring": "Setup and solve the nonlinear problem. Save value to file given. Any additional keyword arguments are passed to t... | 3 | stack_v2_sparse_classes_30k_train_007107 | Implement the Python class `Solver` described below.
Class description:
A class for the solver. Attributes: problem (TTiP.problem.Problem (or subclass)): The problem to solve. u (firedrake.Function): The variable to solve for in the problem. params (dict): The parameters passed to the solver.
Method signatures and do... | Implement the Python class `Solver` described below.
Class description:
A class for the solver. Attributes: problem (TTiP.problem.Problem (or subclass)): The problem to solve. u (firedrake.Function): The variable to solve for in the problem. params (dict): The parameters passed to the solver.
Method signatures and do... | cc4e7f7b9abb498893aaa05e2b25416f513905b0 | <|skeleton|>
class Solver:
"""A class for the solver. Attributes: problem (TTiP.problem.Problem (or subclass)): The problem to solve. u (firedrake.Function): The variable to solve for in the problem. params (dict): The parameters passed to the solver."""
def __init__(self, problem):
"""Initialise the S... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solver:
"""A class for the solver. Attributes: problem (TTiP.problem.Problem (or subclass)): The problem to solve. u (firedrake.Function): The variable to solve for in the problem. params (dict): The parameters passed to the solver."""
def __init__(self, problem):
"""Initialise the Solver. Args: ... | the_stack_v2_python_sparse | TTiP/core/solver.py | AndrewLister-STFC/TTiP | train | 0 |
ac88a8dc489c850231c74a64c197c011485dfbf6 | [
"self.table = []\nfor i in range(len(w)):\n self.table += [i] * w[i]",
"total = len(self.table)\nrnd = random.randint(0, total - 1)\nreturn self.table[rnd]"
] | <|body_start_0|>
self.table = []
for i in range(len(w)):
self.table += [i] * w[i]
<|end_body_0|>
<|body_start_1|>
total = len(self.table)
rnd = random.randint(0, total - 1)
return self.table[rnd]
<|end_body_1|>
| Solution_MLE | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_MLE:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.table = []
for i in range(len(w)):
self.table += [i] * w[i]
<|end_b... | stack_v2_sparse_classes_10k_train_002916 | 1,874 | 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_MLE` described below.
Class description:
Implement the Solution_MLE class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution_MLE` described below.
Class description:
Implement the Solution_MLE class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution_MLE:
def __init__(self, w):
""":type w: List[int]""... | ce68f5af57f772185211f4e81952d0345a6d23cb | <|skeleton|>
class Solution_MLE:
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_MLE:
def __init__(self, w):
""":type w: List[int]"""
self.table = []
for i in range(len(w)):
self.table += [i] * w[i]
def pickIndex(self):
""":rtype: int"""
total = len(self.table)
rnd = random.randint(0, total - 1)
return self.... | the_stack_v2_python_sparse | Previous/528_Random_Pick_with_Weight.py | xizhang77/LeetCode | train | 0 | |
e50c8a57edf736b2ca0a59d501a8c27f9e50638c | [
"user_name = request.GET.get('user_name', None)\ntry:\n user = BigfishUser.objects.get(username=user_name)\nexcept:\n return Response(rsp_msg_400('该用户不存在'), status=status.HTTP_200_OK)\nversion = Version.objects.all().order_by('-version_code').first()\ntry:\n identity_version = IdentityVersion.objects.get(i... | <|body_start_0|>
user_name = request.GET.get('user_name', None)
try:
user = BigfishUser.objects.get(username=user_name)
except:
return Response(rsp_msg_400('该用户不存在'), status=status.HTTP_200_OK)
version = Version.objects.all().order_by('-version_code').first()
... | VersionViews | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VersionViews:
def update_version(self, request):
"""更新版本 :param request: { "user_name": "10720001" } :return: { "data": { "version_name": "1.2.7", "apk_size": 30140, "message": "1231qweqw", "apk_code": 20, "version_code": 1, "folder_name": "http://127.0.0.1:8000/media/version/1.2.7/Super... | stack_v2_sparse_classes_10k_train_002917 | 7,575 | no_license | [
{
"docstring": "更新版本 :param request: { \"user_name\": \"10720001\" } :return: { \"data\": { \"version_name\": \"1.2.7\", \"apk_size\": 30140, \"message\": \"1231qweqw\", \"apk_code\": 20, \"version_code\": 1, \"folder_name\": \"http://127.0.0.1:8000/media/version/1.2.7/SuperFishTeacher.apk\" }, \"message\": \"s... | 3 | stack_v2_sparse_classes_30k_train_000976 | Implement the Python class `VersionViews` described below.
Class description:
Implement the VersionViews class.
Method signatures and docstrings:
- def update_version(self, request): 更新版本 :param request: { "user_name": "10720001" } :return: { "data": { "version_name": "1.2.7", "apk_size": 30140, "message": "1231qweqw... | Implement the Python class `VersionViews` described below.
Class description:
Implement the VersionViews class.
Method signatures and docstrings:
- def update_version(self, request): 更新版本 :param request: { "user_name": "10720001" } :return: { "data": { "version_name": "1.2.7", "apk_size": 30140, "message": "1231qweqw... | 4189fdcacc20795a4778b53c9d47d6fdd3e71811 | <|skeleton|>
class VersionViews:
def update_version(self, request):
"""更新版本 :param request: { "user_name": "10720001" } :return: { "data": { "version_name": "1.2.7", "apk_size": 30140, "message": "1231qweqw", "apk_code": 20, "version_code": 1, "folder_name": "http://127.0.0.1:8000/media/version/1.2.7/Super... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VersionViews:
def update_version(self, request):
"""更新版本 :param request: { "user_name": "10720001" } :return: { "data": { "version_name": "1.2.7", "apk_size": 30140, "message": "1231qweqw", "apk_code": 20, "version_code": 1, "folder_name": "http://127.0.0.1:8000/media/version/1.2.7/SuperFishTeacher.ap... | the_stack_v2_python_sparse | bigfish/apps/versionupdate/views.py | hyu9999/bigfish | train | 0 | |
bdbb3e95204c2bd3f5ca28ae7fb38a2111782372 | [
"self.pers = persistence\nself.logger = logging.getLogger('app')\nself.cfg = cfg",
"try:\n self.logger.debug('Password Reset attempt %s', user_id)\n password_reset_token = ''\n nosqldb = self.pers.nosql_db\n db_user_record = nosqldb['users'].find_one({'$or': [{'username': user_id}, {'email': user_id}]... | <|body_start_0|>
self.pers = persistence
self.logger = logging.getLogger('app')
self.cfg = cfg
<|end_body_0|>
<|body_start_1|>
try:
self.logger.debug('Password Reset attempt %s', user_id)
password_reset_token = ''
nosqldb = self.pers.nosql_db
... | Web user authentication database helper | PasswordResetDBHelper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordResetDBHelper:
"""Web user authentication database helper"""
def __init__(self, persistence, cfg):
"""Class initialization"""
<|body_0|>
def create_password_reset_token(self, user_id):
"""Initiate a password reset with a complex token, multi step"""
... | stack_v2_sparse_classes_10k_train_002918 | 4,820 | no_license | [
{
"docstring": "Class initialization",
"name": "__init__",
"signature": "def __init__(self, persistence, cfg)"
},
{
"docstring": "Initiate a password reset with a complex token, multi step",
"name": "create_password_reset_token",
"signature": "def create_password_reset_token(self, user_i... | 4 | stack_v2_sparse_classes_30k_train_001662 | Implement the Python class `PasswordResetDBHelper` described below.
Class description:
Web user authentication database helper
Method signatures and docstrings:
- def __init__(self, persistence, cfg): Class initialization
- def create_password_reset_token(self, user_id): Initiate a password reset with a complex token... | Implement the Python class `PasswordResetDBHelper` described below.
Class description:
Web user authentication database helper
Method signatures and docstrings:
- def __init__(self, persistence, cfg): Class initialization
- def create_password_reset_token(self, user_id): Initiate a password reset with a complex token... | 3c774731b054c38a273371450a451c951d73b726 | <|skeleton|>
class PasswordResetDBHelper:
"""Web user authentication database helper"""
def __init__(self, persistence, cfg):
"""Class initialization"""
<|body_0|>
def create_password_reset_token(self, user_id):
"""Initiate a password reset with a complex token, multi step"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PasswordResetDBHelper:
"""Web user authentication database helper"""
def __init__(self, persistence, cfg):
"""Class initialization"""
self.pers = persistence
self.logger = logging.getLogger('app')
self.cfg = cfg
def create_password_reset_token(self, user_id):
... | the_stack_v2_python_sparse | genesis/passwordresetdbhelper.py | wbmartin/exodus-app | train | 0 |
6bb16b612543b0821297c8ed8df68020445d9dd4 | [
"super().__init__(screen)\nself.faction = faction\nif self.faction == Faction.Allied:\n self.base_speed = Settings.player_bullet_base_speed\nelse:\n self.base_speed = Settings.enemy_bullet_base_speed\nself.base_damage = Settings.bullet_base_damage\nself.set_position(starting_position)\nself.angle = starting_a... | <|body_start_0|>
super().__init__(screen)
self.faction = faction
if self.faction == Faction.Allied:
self.base_speed = Settings.player_bullet_base_speed
else:
self.base_speed = Settings.enemy_bullet_base_speed
self.base_damage = Settings.bullet_base_damage
... | A class to manage projectiles fired by anyone. | AbstractProjectile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbstractProjectile:
"""A class to manage projectiles fired by anyone."""
def __init__(self, screen, starting_position, starting_angle, damage_multiplier, speed_multiplier, faction):
"""Create a projectile at a given position moving through a given angle"""
<|body_0|>
def... | stack_v2_sparse_classes_10k_train_002919 | 1,184 | no_license | [
{
"docstring": "Create a projectile at a given position moving through a given angle",
"name": "__init__",
"signature": "def __init__(self, screen, starting_position, starting_angle, damage_multiplier, speed_multiplier, faction)"
},
{
"docstring": "Move the bullet through the screen.",
"name... | 2 | stack_v2_sparse_classes_30k_train_000967 | Implement the Python class `AbstractProjectile` described below.
Class description:
A class to manage projectiles fired by anyone.
Method signatures and docstrings:
- def __init__(self, screen, starting_position, starting_angle, damage_multiplier, speed_multiplier, faction): Create a projectile at a given position mo... | Implement the Python class `AbstractProjectile` described below.
Class description:
A class to manage projectiles fired by anyone.
Method signatures and docstrings:
- def __init__(self, screen, starting_position, starting_angle, damage_multiplier, speed_multiplier, faction): Create a projectile at a given position mo... | e06bbf5210f653554e22d558558e4bac8f739e4a | <|skeleton|>
class AbstractProjectile:
"""A class to manage projectiles fired by anyone."""
def __init__(self, screen, starting_position, starting_angle, damage_multiplier, speed_multiplier, faction):
"""Create a projectile at a given position moving through a given angle"""
<|body_0|>
def... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AbstractProjectile:
"""A class to manage projectiles fired by anyone."""
def __init__(self, screen, starting_position, starting_angle, damage_multiplier, speed_multiplier, faction):
"""Create a projectile at a given position moving through a given angle"""
super().__init__(screen)
... | the_stack_v2_python_sparse | game_sprites/projectiles/abstract_projectile.py | Mocardo/jogo-ces22 | train | 0 |
056944e23ef4a406a65a8d028260ad145efa2ddf | [
"d = {}\nfor t in tasks:\n if t in d:\n d[t] += 1\n else:\n d[t] = 1\npq = queue.PriorityQueue()\nfor k, v in d.items():\n pq.put(-v)\nans = 0\nwhile not pq.empty():\n time = 0\n tmp = []\n while time <= n and (not pq.empty()):\n v = pq.get()\n if -v > 1:\n t... | <|body_start_0|>
d = {}
for t in tasks:
if t in d:
d[t] += 1
else:
d[t] = 1
pq = queue.PriorityQueue()
for k, v in d.items():
pq.put(-v)
ans = 0
while not pq.empty():
time = 0
tmp ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def leastInterval2(self, tasks, n):
""":type tasks: List[str] :type n: int :rtype: int"""
<|body_0|>
def leastInterval1(self, tasks, n):
""":type tasks: List[str] :type n: int :rtype: int"""
<|body_1|>
def leastInterval3(self, tasks, n):
... | stack_v2_sparse_classes_10k_train_002920 | 2,596 | no_license | [
{
"docstring": ":type tasks: List[str] :type n: int :rtype: int",
"name": "leastInterval2",
"signature": "def leastInterval2(self, tasks, n)"
},
{
"docstring": ":type tasks: List[str] :type n: int :rtype: int",
"name": "leastInterval1",
"signature": "def leastInterval1(self, tasks, n)"
... | 4 | stack_v2_sparse_classes_30k_train_002462 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def leastInterval2(self, tasks, n): :type tasks: List[str] :type n: int :rtype: int
- def leastInterval1(self, tasks, n): :type tasks: List[str] :type n: int :rtype: int
- def le... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def leastInterval2(self, tasks, n): :type tasks: List[str] :type n: int :rtype: int
- def leastInterval1(self, tasks, n): :type tasks: List[str] :type n: int :rtype: int
- def le... | 763674fcbe271af3d21eed790c3968c4d33f7b09 | <|skeleton|>
class Solution:
def leastInterval2(self, tasks, n):
""":type tasks: List[str] :type n: int :rtype: int"""
<|body_0|>
def leastInterval1(self, tasks, n):
""":type tasks: List[str] :type n: int :rtype: int"""
<|body_1|>
def leastInterval3(self, tasks, n):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def leastInterval2(self, tasks, n):
""":type tasks: List[str] :type n: int :rtype: int"""
d = {}
for t in tasks:
if t in d:
d[t] += 1
else:
d[t] = 1
pq = queue.PriorityQueue()
for k, v in d.items():
... | the_stack_v2_python_sparse | 621_task_scheduler/621.py | guzhoudiaoke/leetcode_python3 | train | 0 | |
fec7700de7b07f68226f7ef00f1f1845d569f3d9 | [
"key_name = 'The Mark'\nthe_mark = db.get(datastore_types.Key.from_path(cls.kind(), key_name))\nif the_mark is None:\n next_start = now() - datetime.timedelta(seconds=60)\n the_mark = PollingMarker(key_name=key_name, next_start=next_start, current_key=None)\nreturn the_mark",
"now_time = now()\nif self.next... | <|body_start_0|>
key_name = 'The Mark'
the_mark = db.get(datastore_types.Key.from_path(cls.kind(), key_name))
if the_mark is None:
next_start = now() - datetime.timedelta(seconds=60)
the_mark = PollingMarker(key_name=key_name, next_start=next_start, current_key=None)
... | Keeps track of the current position in the bootstrap polling process. | PollingMarker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PollingMarker:
"""Keeps track of the current position in the bootstrap polling process."""
def get(cls, now=datetime.datetime.utcnow):
"""Returns the current PollingMarker, creating it if it doesn't exist. Args: now: Returns the current time as a UTC datetime."""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_002921 | 30,847 | no_license | [
{
"docstring": "Returns the current PollingMarker, creating it if it doesn't exist. Args: now: Returns the current time as a UTC datetime.",
"name": "get",
"signature": "def get(cls, now=datetime.datetime.utcnow)"
},
{
"docstring": "Returns True if the bootstrap polling should progress. May modi... | 2 | stack_v2_sparse_classes_30k_train_002813 | Implement the Python class `PollingMarker` described below.
Class description:
Keeps track of the current position in the bootstrap polling process.
Method signatures and docstrings:
- def get(cls, now=datetime.datetime.utcnow): Returns the current PollingMarker, creating it if it doesn't exist. Args: now: Returns th... | Implement the Python class `PollingMarker` described below.
Class description:
Keeps track of the current position in the bootstrap polling process.
Method signatures and docstrings:
- def get(cls, now=datetime.datetime.utcnow): Returns the current PollingMarker, creating it if it doesn't exist. Args: now: Returns th... | e28ffc2c685a7ee92b0686462e61bb06255a65ac | <|skeleton|>
class PollingMarker:
"""Keeps track of the current position in the bootstrap polling process."""
def get(cls, now=datetime.datetime.utcnow):
"""Returns the current PollingMarker, creating it if it doesn't exist. Args: now: Returns the current time as a UTC datetime."""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PollingMarker:
"""Keeps track of the current position in the bootstrap polling process."""
def get(cls, now=datetime.datetime.utcnow):
"""Returns the current PollingMarker, creating it if it doesn't exist. Args: now: Returns the current time as a UTC datetime."""
key_name = 'The Mark'
... | the_stack_v2_python_sparse | hub/hubmodel.py | PaulKinlan/Amplifriend | train | 3 |
537afaca93922f63ec238470e55622e3fe17f6cd | [
"self.threshold_method = threshold_method\nself.threshold = threshold\nself.cf = filters.CompoundUniformFilter(samples)\nself.mf = filters.MaximumFilter(2 * samples + 1)",
"cfilt = self.cf.filter_image(image)\nmfilt = self.mf.filter_image(cfilt)\nif 'std' in self.threshold_method:\n threshold = np.std(self.cf.... | <|body_start_0|>
self.threshold_method = threshold_method
self.threshold = threshold
self.cf = filters.CompoundUniformFilter(samples)
self.mf = filters.MaximumFilter(2 * samples + 1)
<|end_body_0|>
<|body_start_1|>
cfilt = self.cf.filter_image(image)
mfilt = self.mf.filt... | Estimate the position of bright spots in a fluorescence image using a compound uniform filter. Spots are retained if their grey level value is above the threshold. | Estimate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Estimate:
"""Estimate the position of bright spots in a fluorescence image using a compound uniform filter. Spots are retained if their grey level value is above the threshold."""
def __init__(self, samples, threshold_method, threshold):
"""Initialise the position estimator. Paramete... | stack_v2_sparse_classes_10k_train_002922 | 9,306 | no_license | [
{
"docstring": "Initialise the position estimator. Parameters ---------- samples : int Size of kernel used in filtering. threshold_method : str Threshold method (either `std` or `manual`). threshold : float, optional Intensity threshold for position estimation - to be used if threshold_method is `manual`.",
... | 2 | stack_v2_sparse_classes_30k_train_005861 | Implement the Python class `Estimate` described below.
Class description:
Estimate the position of bright spots in a fluorescence image using a compound uniform filter. Spots are retained if their grey level value is above the threshold.
Method signatures and docstrings:
- def __init__(self, samples, threshold_method... | Implement the Python class `Estimate` described below.
Class description:
Estimate the position of bright spots in a fluorescence image using a compound uniform filter. Spots are retained if their grey level value is above the threshold.
Method signatures and docstrings:
- def __init__(self, samples, threshold_method... | 8fdb4122788d0967536ac3f14759e1f32a0c616e | <|skeleton|>
class Estimate:
"""Estimate the position of bright spots in a fluorescence image using a compound uniform filter. Spots are retained if their grey level value is above the threshold."""
def __init__(self, samples, threshold_method, threshold):
"""Initialise the position estimator. Paramete... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Estimate:
"""Estimate the position of bright spots in a fluorescence image using a compound uniform filter. Spots are retained if their grey level value is above the threshold."""
def __init__(self, samples, threshold_method, threshold):
"""Initialise the position estimator. Parameters ----------... | the_stack_v2_python_sparse | smlm_analysis/localise/estimate.py | drmatthews/SMLM_analysis | train | 0 |
42fb7ce224ffc89425c8ebadd8f8e749612d64e2 | [
"XB = np.dot(self.exog, params)\nendog = self.endog\nreturn np.exp(XB) - endog * XB + np.log(factorial(endog))",
"if not hasattr(self, result):\n raise ValueError\nelse:\n mu = np.exp(np.dot(exog, params))\n return stats.poisson(mu, loc=0)"
] | <|body_start_0|>
XB = np.dot(self.exog, params)
endog = self.endog
return np.exp(XB) - endog * XB + np.log(factorial(endog))
<|end_body_0|>
<|body_start_1|>
if not hasattr(self, result):
raise ValueError
else:
mu = np.exp(np.dot(exog, params))
... | Maximum Likelihood Estimation of Poisson Model This is an example for generic MLE which has the same statistical model as discretemod.Poisson. Except for defining the negative log-likelihood method, all methods and results are generic. Gradients and Hessian and all resulting statistics are based on numerical differenti... | PoissonGMLE | [
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PoissonGMLE:
"""Maximum Likelihood Estimation of Poisson Model This is an example for generic MLE which has the same statistical model as discretemod.Poisson. Except for defining the negative log-likelihood method, all methods and results are generic. Gradients and Hessian and all resulting stati... | stack_v2_sparse_classes_10k_train_002923 | 10,838 | permissive | [
{
"docstring": "Loglikelihood of Poisson model Parameters ---------- params : array-like The parameters of the model. Returns ------- The log likelihood of the model evaluated at `params` Notes -------- .. math :: \\\\ln L=\\\\sum_{i=1}^{n}\\\\left[-\\\\lambda_{i}+y_{i}x_{i}^{\\\\prime}\\\\beta-\\\\ln y_{i}!\\\... | 2 | null | Implement the Python class `PoissonGMLE` described below.
Class description:
Maximum Likelihood Estimation of Poisson Model This is an example for generic MLE which has the same statistical model as discretemod.Poisson. Except for defining the negative log-likelihood method, all methods and results are generic. Gradie... | Implement the Python class `PoissonGMLE` described below.
Class description:
Maximum Likelihood Estimation of Poisson Model This is an example for generic MLE which has the same statistical model as discretemod.Poisson. Except for defining the negative log-likelihood method, all methods and results are generic. Gradie... | 2c9002f16bb5c265e0d14f4a2314c86eeaa35cb6 | <|skeleton|>
class PoissonGMLE:
"""Maximum Likelihood Estimation of Poisson Model This is an example for generic MLE which has the same statistical model as discretemod.Poisson. Except for defining the negative log-likelihood method, all methods and results are generic. Gradients and Hessian and all resulting stati... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PoissonGMLE:
"""Maximum Likelihood Estimation of Poisson Model This is an example for generic MLE which has the same statistical model as discretemod.Poisson. Except for defining the negative log-likelihood method, all methods and results are generic. Gradients and Hessian and all resulting statistics are bas... | the_stack_v2_python_sparse | pkgs/statsmodels-0.6.1-np110py27_0/lib/python2.7/site-packages/statsmodels/miscmodels/count.py | wangyum/Anaconda | train | 11 |
177b716b76c9a75e8f64a7cac9e0a9ae545e4fe0 | [
"persistent_query_keyword = PersistentQueryKeyword(user_id=str(self.context['request'].user.id), content=validated_data['content'] if 'content' in validated_data else None, name=validated_data['name'] if 'name' in validated_data else None)\npersistent_query_keyword_api.upsert(persistent_query_keyword, self.context[... | <|body_start_0|>
persistent_query_keyword = PersistentQueryKeyword(user_id=str(self.context['request'].user.id), content=validated_data['content'] if 'content' in validated_data else None, name=validated_data['name'] if 'name' in validated_data else None)
persistent_query_keyword_api.upsert(persistent_q... | persistent query keyword serializer | PersistentQueryKeywordSerializer | [
"NIST-Software",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersistentQueryKeywordSerializer:
"""persistent query keyword serializer"""
def create(self, validated_data):
"""Create and return a new `PersistentQueryKeyword` instance, given the validated data."""
<|body_0|>
def update(self, persistent_query_keyword, validated_data):... | stack_v2_sparse_classes_10k_train_002924 | 3,197 | permissive | [
{
"docstring": "Create and return a new `PersistentQueryKeyword` instance, given the validated data.",
"name": "create",
"signature": "def create(self, validated_data)"
},
{
"docstring": "Update and return an existing `PersistentQueryKeyword` instance, given the validated data.",
"name": "up... | 2 | stack_v2_sparse_classes_30k_train_003747 | Implement the Python class `PersistentQueryKeywordSerializer` described below.
Class description:
persistent query keyword serializer
Method signatures and docstrings:
- def create(self, validated_data): Create and return a new `PersistentQueryKeyword` instance, given the validated data.
- def update(self, persistent... | Implement the Python class `PersistentQueryKeywordSerializer` described below.
Class description:
persistent query keyword serializer
Method signatures and docstrings:
- def create(self, validated_data): Create and return a new `PersistentQueryKeyword` instance, given the validated data.
- def update(self, persistent... | d85d18363c65be3cdffc2fdd79797a50ef65cb2a | <|skeleton|>
class PersistentQueryKeywordSerializer:
"""persistent query keyword serializer"""
def create(self, validated_data):
"""Create and return a new `PersistentQueryKeyword` instance, given the validated data."""
<|body_0|>
def update(self, persistent_query_keyword, validated_data):... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PersistentQueryKeywordSerializer:
"""persistent query keyword serializer"""
def create(self, validated_data):
"""Create and return a new `PersistentQueryKeyword` instance, given the validated data."""
persistent_query_keyword = PersistentQueryKeyword(user_id=str(self.context['request'].us... | the_stack_v2_python_sparse | core_explore_keyword_app/rest/persistent_query_keyword/serializers.py | usnistgov/core_explore_keyword_app | train | 0 |
2a9a821f01405c06ab68c56de156e868e99d147a | [
"parser = parent.add_parser('attach', help='attach to container')\nparser.add_argument('--image', help='image to instantiate and attach to')\nparser.add_argument('command', nargs='*', help='image to instantiate and attach to')\nparser.set_defaults(class_=cls, method='attach')",
"super().__init__(args)\nif not arg... | <|body_start_0|>
parser = parent.add_parser('attach', help='attach to container')
parser.add_argument('--image', help='image to instantiate and attach to')
parser.add_argument('command', nargs='*', help='image to instantiate and attach to')
parser.set_defaults(class_=cls, method='attach'... | Class for attaching to a running container. | Attach | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Attach:
"""Class for attaching to a running container."""
def subparser(cls, parent):
"""Add Attach command to parent parser."""
<|body_0|>
def __init__(self, args):
"""Construct Attach class."""
<|body_1|>
def attach(self):
"""Attach to inst... | stack_v2_sparse_classes_10k_train_002925 | 2,057 | permissive | [
{
"docstring": "Add Attach command to parent parser.",
"name": "subparser",
"signature": "def subparser(cls, parent)"
},
{
"docstring": "Construct Attach class.",
"name": "__init__",
"signature": "def __init__(self, args)"
},
{
"docstring": "Attach to instantiated image.",
"n... | 3 | stack_v2_sparse_classes_30k_train_001175 | Implement the Python class `Attach` described below.
Class description:
Class for attaching to a running container.
Method signatures and docstrings:
- def subparser(cls, parent): Add Attach command to parent parser.
- def __init__(self, args): Construct Attach class.
- def attach(self): Attach to instantiated image. | Implement the Python class `Attach` described below.
Class description:
Class for attaching to a running container.
Method signatures and docstrings:
- def subparser(cls, parent): Add Attach command to parent parser.
- def __init__(self, args): Construct Attach class.
- def attach(self): Attach to instantiated image.... | 94a46127cb0db2b6187186788a941ec72af476dd | <|skeleton|>
class Attach:
"""Class for attaching to a running container."""
def subparser(cls, parent):
"""Add Attach command to parent parser."""
<|body_0|>
def __init__(self, args):
"""Construct Attach class."""
<|body_1|>
def attach(self):
"""Attach to inst... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Attach:
"""Class for attaching to a running container."""
def subparser(cls, parent):
"""Add Attach command to parent parser."""
parser = parent.add_parser('attach', help='attach to container')
parser.add_argument('--image', help='image to instantiate and attach to')
parse... | the_stack_v2_python_sparse | pypodman/pypodman/lib/actions/attach_action.py | 4383/python-podman | train | 0 |
1f9ba8647301914a4961c0ba940186474cba209e | [
"fake_head = ListNode(0)\np, p1, p2 = (fake_head, l1, l2)\nwhile p1 and p2:\n if p1.val < p2.val:\n p.next = ListNode(p1.val)\n p1 = p1.next\n else:\n p.next = ListNode(p2.val)\n p2 = p2.next\n p = p.next\np.next = p1 or p2\nreturn fake_head.next",
"if not l1 or not l2:\n r... | <|body_start_0|>
fake_head = ListNode(0)
p, p1, p2 = (fake_head, l1, l2)
while p1 and p2:
if p1.val < p2.val:
p.next = ListNode(p1.val)
p1 = p1.next
else:
p.next = ListNode(p2.val)
p2 = p2.next
p ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeTwoLists_iterative(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_0|>
def mergeTwoLists_recursive(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_10k_train_002926 | 1,522 | no_license | [
{
"docstring": ":type l1: ListNode :type l2: ListNode :rtype: ListNode",
"name": "mergeTwoLists_iterative",
"signature": "def mergeTwoLists_iterative(self, l1, l2)"
},
{
"docstring": ":type l1: ListNode :type l2: ListNode :rtype: ListNode",
"name": "mergeTwoLists_recursive",
"signature":... | 2 | stack_v2_sparse_classes_30k_train_001093 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists_iterative(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
- def mergeTwoLists_recursive(self, l1, l2): :type l1: ListNode :type l2: ListNo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists_iterative(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
- def mergeTwoLists_recursive(self, l1, l2): :type l1: ListNode :type l2: ListNo... | 9ac54720f571a4bea09d0cceb0039381a78df9e8 | <|skeleton|>
class Solution:
def mergeTwoLists_iterative(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_0|>
def mergeTwoLists_recursive(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeTwoLists_iterative(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
fake_head = ListNode(0)
p, p1, p2 = (fake_head, l1, l2)
while p1 and p2:
if p1.val < p2.val:
p.next = ListNode(p1.val)
p... | the_stack_v2_python_sparse | code/021_merge-two-sorted-lists.py | linhdvu14/leetcode-solutions | train | 2 | |
fb966322b9d5f78d5e116d502db6e94c96fc455a | [
"try:\n params = request._serialize()\n headers = request.headers\n body = self.call('DescribeMaterialList', params, headers=headers)\n response = json.loads(body)\n model = models.DescribeMaterialListResponse()\n model._deserialize(response['Response'])\n return model\nexcept Exception as e:\n... | <|body_start_0|>
try:
params = request._serialize()
headers = request.headers
body = self.call('DescribeMaterialList', params, headers=headers)
response = json.loads(body)
model = models.DescribeMaterialListResponse()
model._deserialize(res... | FacefusionClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FacefusionClient:
def DescribeMaterialList(self, request):
"""通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for DescribeMaterialList. :type request: :class:`tencentcloud.facefusion.v20181201.models.DescribeMaterialListR... | stack_v2_sparse_classes_10k_train_002927 | 5,785 | permissive | [
{
"docstring": "通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for DescribeMaterialList. :type request: :class:`tencentcloud.facefusion.v20181201.models.DescribeMaterialListRequest` :rtype: :class:`tencentcloud.facefusion.v20181201.models.Descr... | 4 | stack_v2_sparse_classes_30k_train_006970 | Implement the Python class `FacefusionClient` described below.
Class description:
Implement the FacefusionClient class.
Method signatures and docstrings:
- def DescribeMaterialList(self, request): 通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for De... | Implement the Python class `FacefusionClient` described below.
Class description:
Implement the FacefusionClient class.
Method signatures and docstrings:
- def DescribeMaterialList(self, request): 通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for De... | 6baf00a5a56ba58b6a1123423e0a1422d17a0201 | <|skeleton|>
class FacefusionClient:
def DescribeMaterialList(self, request):
"""通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for DescribeMaterialList. :type request: :class:`tencentcloud.facefusion.v20181201.models.DescribeMaterialListR... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FacefusionClient:
def DescribeMaterialList(self, request):
"""通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for DescribeMaterialList. :type request: :class:`tencentcloud.facefusion.v20181201.models.DescribeMaterialListRequest` :rtype... | the_stack_v2_python_sparse | tencentcloud/facefusion/v20181201/facefusion_client.py | TencentCloud/tencentcloud-sdk-python | train | 594 | |
6ad1b647fb85a1c6260e9b8833bd72085dd1f4f7 | [
"securityPartitions = zoneManager.getDevicesByType(AlarmPartition)\nif len(securityPartitions) > 0:\n if AlarmPartition.STATE_ARM_AWAY == securityPartitions[0].getArmMode():\n return True\nreturn False",
"securityPartitions = zoneManager.getDevicesByType(AlarmPartition)\nif len(securityPartitions) > 0:\... | <|body_start_0|>
securityPartitions = zoneManager.getDevicesByType(AlarmPartition)
if len(securityPartitions) > 0:
if AlarmPartition.STATE_ARM_AWAY == securityPartitions[0].getArmMode():
return True
return False
<|end_body_0|>
<|body_start_1|>
securityPartiti... | Provide quick access to the alarm partition of the zones. | SecurityManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecurityManager:
"""Provide quick access to the alarm partition of the zones."""
def isArmedAway(zoneManager):
""":return: True if at least one zone is armed-away"""
<|body_0|>
def isArmedStay(zoneManager):
""":return: True if at least one zone is armed-stay"""
... | stack_v2_sparse_classes_10k_train_002928 | 2,333 | no_license | [
{
"docstring": ":return: True if at least one zone is armed-away",
"name": "isArmedAway",
"signature": "def isArmedAway(zoneManager)"
},
{
"docstring": ":return: True if at least one zone is armed-stay",
"name": "isArmedStay",
"signature": "def isArmedStay(zoneManager)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000833 | Implement the Python class `SecurityManager` described below.
Class description:
Provide quick access to the alarm partition of the zones.
Method signatures and docstrings:
- def isArmedAway(zoneManager): :return: True if at least one zone is armed-away
- def isArmedStay(zoneManager): :return: True if at least one zo... | Implement the Python class `SecurityManager` described below.
Class description:
Provide quick access to the alarm partition of the zones.
Method signatures and docstrings:
- def isArmedAway(zoneManager): :return: True if at least one zone is armed-away
- def isArmedStay(zoneManager): :return: True if at least one zo... | c64c9e109173277b6b4b2473adaac9d2da623cdb | <|skeleton|>
class SecurityManager:
"""Provide quick access to the alarm partition of the zones."""
def isArmedAway(zoneManager):
""":return: True if at least one zone is armed-away"""
<|body_0|>
def isArmedStay(zoneManager):
""":return: True if at least one zone is armed-stay"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SecurityManager:
"""Provide quick access to the alarm partition of the zones."""
def isArmedAway(zoneManager):
""":return: True if at least one zone is armed-away"""
securityPartitions = zoneManager.getDevicesByType(AlarmPartition)
if len(securityPartitions) > 0:
if Al... | the_stack_v2_python_sparse | legacy-jython-code/aaa_modules/security_manager.py | yfaway/openhab-rules | train | 10 |
2b5a9ccd91976fe2552abe89c222e3942f7b54e0 | [
"try:\n cart = Cart.objects.get(created_by=request.user)\n serializer = CartItemSerializer(CartItem.objects.filter(cart=cart, purchased=False), many=True)\n return JsonResponse({'message': 'list of item in the cart', 'data': serializer.data}, status=200)\nexcept Exception as e:\n logger.error(e, exc_inf... | <|body_start_0|>
try:
cart = Cart.objects.get(created_by=request.user)
serializer = CartItemSerializer(CartItem.objects.filter(cart=cart, purchased=False), many=True)
return JsonResponse({'message': 'list of item in the cart', 'data': serializer.data}, status=200)
exc... | AddToCartView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddToCartView:
def get(self, request):
"""Get cart items"""
<|body_0|>
def post(self, request):
"""Add items to cart"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
cart = Cart.objects.get(created_by=request.user)
serial... | stack_v2_sparse_classes_10k_train_002929 | 5,301 | no_license | [
{
"docstring": "Get cart items",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Add items to cart",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002596 | Implement the Python class `AddToCartView` described below.
Class description:
Implement the AddToCartView class.
Method signatures and docstrings:
- def get(self, request): Get cart items
- def post(self, request): Add items to cart | Implement the Python class `AddToCartView` described below.
Class description:
Implement the AddToCartView class.
Method signatures and docstrings:
- def get(self, request): Get cart items
- def post(self, request): Add items to cart
<|skeleton|>
class AddToCartView:
def get(self, request):
"""Get cart ... | 367cccca72f0eae6c3ccb70fabb371dc905f915e | <|skeleton|>
class AddToCartView:
def get(self, request):
"""Get cart items"""
<|body_0|>
def post(self, request):
"""Add items to cart"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AddToCartView:
def get(self, request):
"""Get cart items"""
try:
cart = Cart.objects.get(created_by=request.user)
serializer = CartItemSerializer(CartItem.objects.filter(cart=cart, purchased=False), many=True)
return JsonResponse({'message': 'list of item in... | the_stack_v2_python_sparse | course/views/cart_view.py | vshaladhav97/first_kick | train | 0 | |
2dcfb82d0599322fff085ffb434c6808b8cc2af3 | [
"self.feature_score = feature_score\nself.sampler_name = sampler_name\nself.regression_model = regression_model",
"device = select_device()\nsample = []\nsorted_score = sorted(self.feature_score, key=itemgetter('score'), reverse=True)\ncnt = 0\ni = 0\nwhile cnt < n_sample:\n if sorted_score[i] not in already_s... | <|body_start_0|>
self.feature_score = feature_score
self.sampler_name = sampler_name
self.regression_model = regression_model
<|end_body_0|>
<|body_start_1|>
device = select_device()
sample = []
sorted_score = sorted(self.feature_score, key=itemgetter('score'), reverse=T... | RegressionSampler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegressionSampler:
def __init__(self, sampler_name, regression_model, feature_score):
""":param sampler_name: :param regression_model: :param feature_score: :list[dict] {'image_id': int, 'score':tensor}"""
<|body_0|>
def select_batch(self, n_sample, already_selected):
... | stack_v2_sparse_classes_10k_train_002930 | 1,977 | permissive | [
{
"docstring": ":param sampler_name: :param regression_model: :param feature_score: :list[dict] {'image_id': int, 'score':tensor}",
"name": "__init__",
"signature": "def __init__(self, sampler_name, regression_model, feature_score)"
},
{
"docstring": ":param feature_path: :param self: :param reg... | 2 | stack_v2_sparse_classes_30k_train_000263 | Implement the Python class `RegressionSampler` described below.
Class description:
Implement the RegressionSampler class.
Method signatures and docstrings:
- def __init__(self, sampler_name, regression_model, feature_score): :param sampler_name: :param regression_model: :param feature_score: :list[dict] {'image_id': ... | Implement the Python class `RegressionSampler` described below.
Class description:
Implement the RegressionSampler class.
Method signatures and docstrings:
- def __init__(self, sampler_name, regression_model, feature_score): :param sampler_name: :param regression_model: :param feature_score: :list[dict] {'image_id': ... | bd75971b94f055fded6125c1d136b1ea188b75f0 | <|skeleton|>
class RegressionSampler:
def __init__(self, sampler_name, regression_model, feature_score):
""":param sampler_name: :param regression_model: :param feature_score: :list[dict] {'image_id': int, 'score':tensor}"""
<|body_0|>
def select_batch(self, n_sample, already_selected):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RegressionSampler:
def __init__(self, sampler_name, regression_model, feature_score):
""":param sampler_name: :param regression_model: :param feature_score: :list[dict] {'image_id': int, 'score':tensor}"""
self.feature_score = feature_score
self.sampler_name = sampler_name
self... | the_stack_v2_python_sparse | liuy/implementation/RegressorSampler.py | liuy-61/al_ins_seg | train | 3 | |
f1f2ab8a2dd361b8dd32ad5e25f9c3c0393a02d9 | [
"if controller is not None:\n if not is_string(controller):\n raise ValueError('Controller name must be a string')\n controller = controller.strip()\n if not controller:\n _logger.warning('Empty controller name given')\n controller = None\n elif ' ' in controller:\n raise Val... | <|body_start_0|>
if controller is not None:
if not is_string(controller):
raise ValueError('Controller name must be a string')
controller = controller.strip()
if not controller:
_logger.warning('Empty controller name given')
con... | @Provides decorator Defines an interface exported by a component. | Provides | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Provides:
"""@Provides decorator Defines an interface exported by a component."""
def __init__(self, specifications, controller=None):
"""Sets up a provided service. A service controller can be defined to enable or disable the service. :param specifications: A list of provided interf... | stack_v2_sparse_classes_10k_train_002931 | 41,418 | permissive | [
{
"docstring": "Sets up a provided service. A service controller can be defined to enable or disable the service. :param specifications: A list of provided interface(s) name(s) (can't be empty) :param controller: Name of the service controller class field (optional) :raise ValueError: If the specifications are ... | 2 | stack_v2_sparse_classes_30k_train_006627 | Implement the Python class `Provides` described below.
Class description:
@Provides decorator Defines an interface exported by a component.
Method signatures and docstrings:
- def __init__(self, specifications, controller=None): Sets up a provided service. A service controller can be defined to enable or disable the ... | Implement the Python class `Provides` described below.
Class description:
@Provides decorator Defines an interface exported by a component.
Method signatures and docstrings:
- def __init__(self, specifications, controller=None): Sets up a provided service. A service controller can be defined to enable or disable the ... | 686556cdde20beba77ae202de9969be46feed5e2 | <|skeleton|>
class Provides:
"""@Provides decorator Defines an interface exported by a component."""
def __init__(self, specifications, controller=None):
"""Sets up a provided service. A service controller can be defined to enable or disable the service. :param specifications: A list of provided interf... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Provides:
"""@Provides decorator Defines an interface exported by a component."""
def __init__(self, specifications, controller=None):
"""Sets up a provided service. A service controller can be defined to enable or disable the service. :param specifications: A list of provided interface(s) name(s... | the_stack_v2_python_sparse | python/src/lib/python/pelix/ipopo/decorators.py | cohorte/cohorte-runtime | train | 3 |
300807ca340381ed02b2f1ca77674a4080ebac22 | [
"if not head or not head.next:\n return head\nfast, slow = (head.next, head)\nwhile fast and fast.next:\n fast = fast.next.next\n slow = slow.next\nsecond = slow.next\nslow.next = None\nl = self.sortList(head)\nr = self.sortList(second)\nreturn self.merge(l, r)",
"if not l or not r:\n return l or r\ni... | <|body_start_0|>
if not head or not head.next:
return head
fast, slow = (head.next, head)
while fast and fast.next:
fast = fast.next.next
slow = slow.next
second = slow.next
slow.next = None
l = self.sortList(head)
r = self.sort... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def merge(self, l, r):
""":type l: ListNode :type r: ListNode :rtype: ListNode"""
<|body_1|>
def sortList_1(self, head):
""":type head: ListNode :rtype: Li... | stack_v2_sparse_classes_10k_train_002932 | 4,222 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "sortList",
"signature": "def sortList(self, head)"
},
{
"docstring": ":type l: ListNode :type r: ListNode :rtype: ListNode",
"name": "merge",
"signature": "def merge(self, l, r)"
},
{
"docstring": ":type head: ListN... | 5 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortList(self, head): :type head: ListNode :rtype: ListNode
- def merge(self, l, r): :type l: ListNode :type r: ListNode :rtype: ListNode
- def sortList_1(self, head): :type ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortList(self, head): :type head: ListNode :rtype: ListNode
- def merge(self, l, r): :type l: ListNode :type r: ListNode :rtype: ListNode
- def sortList_1(self, head): :type ... | 3d9e0ad2f6ed92ec969556f75d97c51ea4854719 | <|skeleton|>
class Solution:
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def merge(self, l, r):
""":type l: ListNode :type r: ListNode :rtype: ListNode"""
<|body_1|>
def sortList_1(self, head):
""":type head: ListNode :rtype: Li... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
if not head or not head.next:
return head
fast, slow = (head.next, head)
while fast and fast.next:
fast = fast.next.next
slow = slow.next
second = slow.ne... | the_stack_v2_python_sparse | Solutions/0148_sortList.py | YoupengLi/leetcode-sorting | train | 3 | |
54b7e8e44014323b74024b48a00592d00bffc4e8 | [
"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... | Copyright 2017 Google Inc. All Rights Reserved. Proto file for the Google Cloud Machine Learning Engine. Describes the 'job service' to manage training and prediction jobs. Service to create and manage training and batch prediction jobs. | JobServiceServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobServiceServicer:
"""Copyright 2017 Google Inc. All Rights Reserved. Proto file for the Google Cloud Machine Learning Engine. Describes the 'job service' to manage training and prediction jobs. Service to create and manage training and batch prediction jobs."""
def CreateJob(self, request,... | stack_v2_sparse_classes_10k_train_002933 | 4,689 | no_license | [
{
"docstring": "Creates a training or a batch prediction job.",
"name": "CreateJob",
"signature": "def CreateJob(self, request, context)"
},
{
"docstring": "Lists the jobs in the project.",
"name": "ListJobs",
"signature": "def ListJobs(self, request, context)"
},
{
"docstring": ... | 4 | stack_v2_sparse_classes_30k_train_001783 | Implement the Python class `JobServiceServicer` described below.
Class description:
Copyright 2017 Google Inc. All Rights Reserved. Proto file for the Google Cloud Machine Learning Engine. Describes the 'job service' to manage training and prediction jobs. Service to create and manage training and batch prediction job... | Implement the Python class `JobServiceServicer` described below.
Class description:
Copyright 2017 Google Inc. All Rights Reserved. Proto file for the Google Cloud Machine Learning Engine. Describes the 'job service' to manage training and prediction jobs. Service to create and manage training and batch prediction job... | d7424d21aa0dc121acc4d64b427ba365a3581a20 | <|skeleton|>
class JobServiceServicer:
"""Copyright 2017 Google Inc. All Rights Reserved. Proto file for the Google Cloud Machine Learning Engine. Describes the 'job service' to manage training and prediction jobs. Service to create and manage training and batch prediction jobs."""
def CreateJob(self, request,... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class JobServiceServicer:
"""Copyright 2017 Google Inc. All Rights Reserved. Proto file for the Google Cloud Machine Learning Engine. Describes the 'job service' to manage training and prediction jobs. Service to create and manage training and batch prediction jobs."""
def CreateJob(self, request, context):
... | the_stack_v2_python_sparse | google/cloud/ml/v1/job_service_pb2_grpc.py | msachtler/bazel-event-protocol-parser | train | 1 |
4505e5d322791156ea24b49dfa24d5e501d3c43a | [
"my_dict = defaultdict(list)\nfor index, num in enumerate(nums):\n if my_dict[num] and index - my_dict[num][-1] <= k:\n return True\n my_dict[num].append(index)\nreturn False",
"my_dict = {}\nfor index, num in enumerate(nums):\n if num in my_dict and index - my_dict[num] <= k:\n return True... | <|body_start_0|>
my_dict = defaultdict(list)
for index, num in enumerate(nums):
if my_dict[num] and index - my_dict[num][-1] <= k:
return True
my_dict[num].append(index)
return False
<|end_body_0|>
<|body_start_1|>
my_dict = {}
for index, ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def containsNearbyDuplicate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: bool"""
<|body_0|>
def containsNearbyDuplicate2(self, nums, k):
""":type nums: List[int] :type k: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_10k_train_002934 | 813 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: bool",
"name": "containsNearbyDuplicate",
"signature": "def containsNearbyDuplicate(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: bool",
"name": "containsNearbyDuplicate2",
"signature": "def contai... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def containsNearbyDuplicate(self, nums, k): :type nums: List[int] :type k: int :rtype: bool
- def containsNearbyDuplicate2(self, nums, k): :type nums: List[int] :type k: int :rty... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def containsNearbyDuplicate(self, nums, k): :type nums: List[int] :type k: int :rtype: bool
- def containsNearbyDuplicate2(self, nums, k): :type nums: List[int] :type k: int :rty... | cefa2f08667de4d2973274de3ff29a31a7d25eda | <|skeleton|>
class Solution:
def containsNearbyDuplicate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: bool"""
<|body_0|>
def containsNearbyDuplicate2(self, nums, k):
""":type nums: List[int] :type k: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def containsNearbyDuplicate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: bool"""
my_dict = defaultdict(list)
for index, num in enumerate(nums):
if my_dict[num] and index - my_dict[num][-1] <= k:
return True
my_dict[num]... | the_stack_v2_python_sparse | 219/Solution.py | zhangruochi/leetcode | train | 14 | |
008fd01e24115e77b6f93e255232261e66da16cf | [
"super().__init__()\nassert kernel_size % 2 == 1, 'Kernel size must be odd number.'\nassert len(upsample_scales) == len(upsample_kernel_sizes)\nassert len(resblock_dilations) == len(resblock_kernel_sizes)\nself.num_upsamples = len(upsample_kernel_sizes)\nself.num_blocks = len(resblock_kernel_sizes)\nself.input_conv... | <|body_start_0|>
super().__init__()
assert kernel_size % 2 == 1, 'Kernel size must be odd number.'
assert len(upsample_scales) == len(upsample_kernel_sizes)
assert len(resblock_dilations) == len(resblock_kernel_sizes)
self.num_upsamples = len(upsample_kernel_sizes)
self.n... | Avocodo generator module. | AvocodoGenerator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AvocodoGenerator:
"""Avocodo generator module."""
def __init__(self, in_channels: int=80, out_channels: int=1, channels: int=512, global_channels: int=-1, kernel_size: int=7, upsample_scales: List[int]=[8, 8, 2, 2], upsample_kernel_sizes: List[int]=[16, 16, 4, 4], resblock_kernel_sizes: List... | stack_v2_sparse_classes_10k_train_002935 | 29,046 | permissive | [
{
"docstring": "Initialize AvocodoGenerator module. Args: in_channels (int): Number of input channels. out_channels (int): Number of output channels. channels (int): Number of hidden representation channels. global_channels (int): Number of global conditioning channels. kernel_size (int): Kernel size of initial... | 5 | null | Implement the Python class `AvocodoGenerator` described below.
Class description:
Avocodo generator module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=80, out_channels: int=1, channels: int=512, global_channels: int=-1, kernel_size: int=7, upsample_scales: List[int]=[8, 8, 2, 2], upsample... | Implement the Python class `AvocodoGenerator` described below.
Class description:
Avocodo generator module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=80, out_channels: int=1, channels: int=512, global_channels: int=-1, kernel_size: int=7, upsample_scales: List[int]=[8, 8, 2, 2], upsample... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class AvocodoGenerator:
"""Avocodo generator module."""
def __init__(self, in_channels: int=80, out_channels: int=1, channels: int=512, global_channels: int=-1, kernel_size: int=7, upsample_scales: List[int]=[8, 8, 2, 2], upsample_kernel_sizes: List[int]=[16, 16, 4, 4], resblock_kernel_sizes: List... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AvocodoGenerator:
"""Avocodo generator module."""
def __init__(self, in_channels: int=80, out_channels: int=1, channels: int=512, global_channels: int=-1, kernel_size: int=7, upsample_scales: List[int]=[8, 8, 2, 2], upsample_kernel_sizes: List[int]=[16, 16, 4, 4], resblock_kernel_sizes: List[int]=[3, 7, ... | the_stack_v2_python_sparse | espnet2/gan_svs/avocodo/avocodo.py | espnet/espnet | train | 7,242 |
64afc0a3d40b5cfa056454125a537b828f83d3c2 | [
"if value == '':\n raise ValueError(\"value can't be an empty string\")\nreturn value",
"if not validate_isbn_digit(value):\n raise ValueError('value is not a valid ISBN')\nreturn value",
"if value < 1:\n raise ValueError(\"number of pages can't be 0 or less\")\nreturn value"
] | <|body_start_0|>
if value == '':
raise ValueError("value can't be an empty string")
return value
<|end_body_0|>
<|body_start_1|>
if not validate_isbn_digit(value):
raise ValueError('value is not a valid ISBN')
return value
<|end_body_1|>
<|body_start_2|>
... | Segunda versão da classe de livros contento todos os campos dos exemplos anteriores e mais alguns novos. | BookV2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BookV2:
"""Segunda versão da classe de livros contento todos os campos dos exemplos anteriores e mais alguns novos."""
def validate_not_empty(cls, value: str, **kwargs) -> str:
"""Verifica se os campos informados não estão vazios."""
<|body_0|>
def validate_isbn(cls, val... | stack_v2_sparse_classes_10k_train_002936 | 2,791 | no_license | [
{
"docstring": "Verifica se os campos informados não estão vazios.",
"name": "validate_not_empty",
"signature": "def validate_not_empty(cls, value: str, **kwargs) -> str"
},
{
"docstring": "Verifica se o ISBN informado é válido.",
"name": "validate_isbn",
"signature": "def validate_isbn(... | 3 | stack_v2_sparse_classes_30k_train_003780 | Implement the Python class `BookV2` described below.
Class description:
Segunda versão da classe de livros contento todos os campos dos exemplos anteriores e mais alguns novos.
Method signatures and docstrings:
- def validate_not_empty(cls, value: str, **kwargs) -> str: Verifica se os campos informados não estão vazi... | Implement the Python class `BookV2` described below.
Class description:
Segunda versão da classe de livros contento todos os campos dos exemplos anteriores e mais alguns novos.
Method signatures and docstrings:
- def validate_not_empty(cls, value: str, **kwargs) -> str: Verifica se os campos informados não estão vazi... | 11d8391f0db79331892884a391750810399a3c45 | <|skeleton|>
class BookV2:
"""Segunda versão da classe de livros contento todos os campos dos exemplos anteriores e mais alguns novos."""
def validate_not_empty(cls, value: str, **kwargs) -> str:
"""Verifica se os campos informados não estão vazios."""
<|body_0|>
def validate_isbn(cls, val... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BookV2:
"""Segunda versão da classe de livros contento todos os campos dos exemplos anteriores e mais alguns novos."""
def validate_not_empty(cls, value: str, **kwargs) -> str:
"""Verifica se os campos informados não estão vazios."""
if value == '':
raise ValueError("value can... | the_stack_v2_python_sparse | usando-o-pydantic/books/models.py | plainspooky/giovannireisnunes | train | 11 |
c506c4115e9a29e10e005c12702987e735f96f3d | [
"if digits[-1] < 9:\n digits[-1] += 1\n return digits\nelse:\n str_s = str()\n result = []\n for i in range(len(digits)):\n str_s += str(digits[i])\n for i in str(int(str_s) + 1):\n result.append(int(i))\n return result",
"index = len(digits)\nif index == 0:\n return digits\n... | <|body_start_0|>
if digits[-1] < 9:
digits[-1] += 1
return digits
else:
str_s = str()
result = []
for i in range(len(digits)):
str_s += str(digits[i])
for i in str(int(str_s) + 1):
result.append(int(i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def plusOne1(self, digits: List[int]) -> List[int]:
"""执行用时： 40 ms , 在所有 Python3 提交中击败了 57.89% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 21.62% 的用户 :param digits: :return:"""
<|body_0|>
def plusOne(self, digits: List[int]) -> List[int]:
"""执行用时： 24 ms , 在所有 Py... | stack_v2_sparse_classes_10k_train_002937 | 2,456 | no_license | [
{
"docstring": "执行用时： 40 ms , 在所有 Python3 提交中击败了 57.89% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 21.62% 的用户 :param digits: :return:",
"name": "plusOne1",
"signature": "def plusOne1(self, digits: List[int]) -> List[int]"
},
{
"docstring": "执行用时： 24 ms , 在所有 Python3 提交中击败了 99.67% 的用户 内存消耗： 14.7 MB ,... | 3 | stack_v2_sparse_classes_30k_train_000984 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plusOne1(self, digits: List[int]) -> List[int]: 执行用时： 40 ms , 在所有 Python3 提交中击败了 57.89% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 21.62% 的用户 :param digits: :return:
- def plusOn... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plusOne1(self, digits: List[int]) -> List[int]: 执行用时： 40 ms , 在所有 Python3 提交中击败了 57.89% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 21.62% 的用户 :param digits: :return:
- def plusOn... | d613ed8a5a2c15ace7d513965b372d128845d66a | <|skeleton|>
class Solution:
def plusOne1(self, digits: List[int]) -> List[int]:
"""执行用时： 40 ms , 在所有 Python3 提交中击败了 57.89% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 21.62% 的用户 :param digits: :return:"""
<|body_0|>
def plusOne(self, digits: List[int]) -> List[int]:
"""执行用时： 24 ms , 在所有 Py... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def plusOne1(self, digits: List[int]) -> List[int]:
"""执行用时： 40 ms , 在所有 Python3 提交中击败了 57.89% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 21.62% 的用户 :param digits: :return:"""
if digits[-1] < 9:
digits[-1] += 1
return digits
else:
str_s = str()... | the_stack_v2_python_sparse | plus_one.py | nomboy/leetcode | train | 0 | |
c1fb96d281ff340126642b38e421cb45381803dd | [
"config = current_app.cea_config\ndashboards = cea.plots.read_dashboards(config, current_app.plot_cache)\nreturn dashboard_to_dict(dashboards[dashboard_index])['plots'][plot_index]",
"form = api.payload\nconfig = current_app.cea_config\ntemp_config = cea.config.Configuration()\ndashboards = cea.plots.read_dashboa... | <|body_start_0|>
config = current_app.cea_config
dashboards = cea.plots.read_dashboards(config, current_app.plot_cache)
return dashboard_to_dict(dashboards[dashboard_index])['plots'][plot_index]
<|end_body_0|>
<|body_start_1|>
form = api.payload
config = current_app.cea_config
... | DashboardPlot | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DashboardPlot:
def get(self, dashboard_index, plot_index):
"""Get Dashboard Plot"""
<|body_0|>
def put(self, dashboard_index, plot_index):
"""Create/Replace a new Plot at specified index"""
<|body_1|>
def delete(self, dashboard_index, plot_index):
... | stack_v2_sparse_classes_10k_train_002938 | 9,106 | permissive | [
{
"docstring": "Get Dashboard Plot",
"name": "get",
"signature": "def get(self, dashboard_index, plot_index)"
},
{
"docstring": "Create/Replace a new Plot at specified index",
"name": "put",
"signature": "def put(self, dashboard_index, plot_index)"
},
{
"docstring": "Delete Plot ... | 3 | null | Implement the Python class `DashboardPlot` described below.
Class description:
Implement the DashboardPlot class.
Method signatures and docstrings:
- def get(self, dashboard_index, plot_index): Get Dashboard Plot
- def put(self, dashboard_index, plot_index): Create/Replace a new Plot at specified index
- def delete(s... | Implement the Python class `DashboardPlot` described below.
Class description:
Implement the DashboardPlot class.
Method signatures and docstrings:
- def get(self, dashboard_index, plot_index): Get Dashboard Plot
- def put(self, dashboard_index, plot_index): Create/Replace a new Plot at specified index
- def delete(s... | b84bcefdfdfc2bc0e009b5284b74391a957995ac | <|skeleton|>
class DashboardPlot:
def get(self, dashboard_index, plot_index):
"""Get Dashboard Plot"""
<|body_0|>
def put(self, dashboard_index, plot_index):
"""Create/Replace a new Plot at specified index"""
<|body_1|>
def delete(self, dashboard_index, plot_index):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DashboardPlot:
def get(self, dashboard_index, plot_index):
"""Get Dashboard Plot"""
config = current_app.cea_config
dashboards = cea.plots.read_dashboards(config, current_app.plot_cache)
return dashboard_to_dict(dashboards[dashboard_index])['plots'][plot_index]
def put(sel... | the_stack_v2_python_sparse | cea/interfaces/dashboard/api/dashboard.py | architecture-building-systems/CityEnergyAnalyst | train | 166 | |
8e73fe7b8dd0aceaaa4c0739085c488d2649a286 | [
"new_spec = Specification(key=validated_data.get('key'), value=validated_data.get('value'), category=validated_data.get('category'), car=validated_data.get('car'))\nnew_spec.save()\nreturn new_spec",
"instance.key = validated_data.get('key', instance.key)\ninstance.value = validated_data.get('value', instance.val... | <|body_start_0|>
new_spec = Specification(key=validated_data.get('key'), value=validated_data.get('value'), category=validated_data.get('category'), car=validated_data.get('car'))
new_spec.save()
return new_spec
<|end_body_0|>
<|body_start_1|>
instance.key = validated_data.get('key', in... | SpecificationSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpecificationSerializer:
def create(self, validated_data):
"""create and return new 'Specification' instance"""
<|body_0|>
def update(self, instance, validated_data):
"""Update and return an existing `Specification` instance"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_10k_train_002939 | 6,342 | no_license | [
{
"docstring": "create and return new 'Specification' instance",
"name": "create",
"signature": "def create(self, validated_data)"
},
{
"docstring": "Update and return an existing `Specification` instance",
"name": "update",
"signature": "def update(self, instance, validated_data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006555 | Implement the Python class `SpecificationSerializer` described below.
Class description:
Implement the SpecificationSerializer class.
Method signatures and docstrings:
- def create(self, validated_data): create and return new 'Specification' instance
- def update(self, instance, validated_data): Update and return an ... | Implement the Python class `SpecificationSerializer` described below.
Class description:
Implement the SpecificationSerializer class.
Method signatures and docstrings:
- def create(self, validated_data): create and return new 'Specification' instance
- def update(self, instance, validated_data): Update and return an ... | dba8d1fdb96889e41328e792816a4968cbeb1ed4 | <|skeleton|>
class SpecificationSerializer:
def create(self, validated_data):
"""create and return new 'Specification' instance"""
<|body_0|>
def update(self, instance, validated_data):
"""Update and return an existing `Specification` instance"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SpecificationSerializer:
def create(self, validated_data):
"""create and return new 'Specification' instance"""
new_spec = Specification(key=validated_data.get('key'), value=validated_data.get('value'), category=validated_data.get('category'), car=validated_data.get('car'))
new_spec.sa... | the_stack_v2_python_sparse | cars_web/cars_app/serializers.py | Ignisor/cars_scrapper | train | 0 | |
91442f6d224b496bd35061a83b4e0e9c7d1a677b | [
"self.nums = nums\nself.cacheId = None\nself.candidates = []",
"if self.cacheId != target:\n self.cacheId = target\n self.candidates[:] = []\n for index, i in enumerate(self.nums):\n if i == target:\n self.candidates.append(index)\nreturn self.candidates[random.randint(0, len(self.candi... | <|body_start_0|>
self.nums = nums
self.cacheId = None
self.candidates = []
<|end_body_0|>
<|body_start_1|>
if self.cacheId != target:
self.cacheId = target
self.candidates[:] = []
for index, i in enumerate(self.nums):
if i == target:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, nums):
""":type nums: List[int] :type numsSize: int"""
<|body_0|>
def pick(self, target):
""":type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.nums = nums
self.cacheId = None
... | stack_v2_sparse_classes_10k_train_002940 | 800 | no_license | [
{
"docstring": ":type nums: List[int] :type numsSize: int",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type target: int :rtype: int",
"name": "pick",
"signature": "def pick(self, target)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001492 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int] :type numsSize: int
- def pick(self, target): :type target: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int] :type numsSize: int
- def pick(self, target): :type target: int :rtype: int
<|skeleton|>
class Solution:
def __init__(self, ... | 01498cd07e552d8ddf7b7fb7f8b8c71f303a4a87 | <|skeleton|>
class Solution:
def __init__(self, nums):
""":type nums: List[int] :type numsSize: int"""
<|body_0|>
def pick(self, target):
""":type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, nums):
""":type nums: List[int] :type numsSize: int"""
self.nums = nums
self.cacheId = None
self.candidates = []
def pick(self, target):
""":type target: int :rtype: int"""
if self.cacheId != target:
self.cacheId = t... | the_stack_v2_python_sparse | leetcode/398. Random Pick Index/398._Random_Pick_Index_2.py | tyge318/tyge318.github.io | train | 1 | |
b38989d148a7bdbe085c2511acd1689c1b1fa96c | [
"if minfo is None:\n minfo = {}\nsuper(ResetPeerStatsMessage, self).__init__(minfo)\nself.IsSystemMessage = False\nself.IsForward = True\nself.IsReliable = True\nself.PeerIDList = minfo.get('PeerIDList', [])\nself.MetricList = minfo.get('MetricList', [])",
"result = super(ResetPeerStatsMessage, self).dump()\nr... | <|body_start_0|>
if minfo is None:
minfo = {}
super(ResetPeerStatsMessage, self).__init__(minfo)
self.IsSystemMessage = False
self.IsForward = True
self.IsReliable = True
self.PeerIDList = minfo.get('PeerIDList', [])
self.MetricList = minfo.get('Metric... | Reset peer stats messages are sent to a peer node to request it to reset statistics about specified peer connections. Attributes: ResetPeerStatsMessage.MessageType (str): The class name of the message. IsSystemMessage (bool): Whether or not this is a system message. System messages have special delivery priority rules.... | ResetPeerStatsMessage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResetPeerStatsMessage:
"""Reset peer stats messages are sent to a peer node to request it to reset statistics about specified peer connections. Attributes: ResetPeerStatsMessage.MessageType (str): The class name of the message. IsSystemMessage (bool): Whether or not this is a system message. Syst... | stack_v2_sparse_classes_10k_train_002941 | 13,482 | permissive | [
{
"docstring": "Constructor for the ResetPeerStatsMessage class. Args: minfo (dict): Dictionary of values for message fields.",
"name": "__init__",
"signature": "def __init__(self, minfo=None)"
},
{
"docstring": "Dumps a dict containing object attributes. Returns: dict: A mapping of object attri... | 2 | stack_v2_sparse_classes_30k_train_006053 | Implement the Python class `ResetPeerStatsMessage` described below.
Class description:
Reset peer stats messages are sent to a peer node to request it to reset statistics about specified peer connections. Attributes: ResetPeerStatsMessage.MessageType (str): The class name of the message. IsSystemMessage (bool): Whethe... | Implement the Python class `ResetPeerStatsMessage` described below.
Class description:
Reset peer stats messages are sent to a peer node to request it to reset statistics about specified peer connections. Attributes: ResetPeerStatsMessage.MessageType (str): The class name of the message. IsSystemMessage (bool): Whethe... | 8f4ca1aab54ef420a0db10c8ca822ec8686cd423 | <|skeleton|>
class ResetPeerStatsMessage:
"""Reset peer stats messages are sent to a peer node to request it to reset statistics about specified peer connections. Attributes: ResetPeerStatsMessage.MessageType (str): The class name of the message. IsSystemMessage (bool): Whether or not this is a system message. Syst... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ResetPeerStatsMessage:
"""Reset peer stats messages are sent to a peer node to request it to reset statistics about specified peer connections. Attributes: ResetPeerStatsMessage.MessageType (str): The class name of the message. IsSystemMessage (bool): Whether or not this is a system message. System messages h... | the_stack_v2_python_sparse | validator/gossip/messages/gossip_debug.py | aludvik/sawtooth-core | train | 0 |
114a26f379a54a0ca74551d5906e6c0040134bfb | [
"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\nself.reduction = reduction\nself.down_sample_layers = nn.ModuleList([ConvBlock(in_chans, chans, drop_prob, attention=False, attention_type=attention_type... | <|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
self.reduction = reduction
self.down_sample_layers = nn.ModuleList([ConvBlock(in_ch... | 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. | CSEUnetModelTakeLatentDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CSEUnetModelTakeLatentDecoder:
"""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 interventi... | stack_v2_sparse_classes_10k_train_002942 | 10,589 | 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_val_000049 | Implement the Python class `CSEUnetModelTakeLatentDecoder` 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 com... | Implement the Python class `CSEUnetModelTakeLatentDecoder` 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 com... | 219652c8a08c4f2f682acd9f95a4e1b3fd36b70b | <|skeleton|>
class CSEUnetModelTakeLatentDecoder:
"""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 interventi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CSEUnetModelTakeLatentDecoder:
"""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_relu/chattn.py | Bala93/Holistic-MRI-Reconstruction | train | 1 |
99090aa4fad4c9ba36cc4895c2779a3f4498a7c4 | [
"user = getattr(request._request, 'user', None)\nif not user or not user.is_active:\n return None\nself.enforce_csrf(request)\nreturn (user, None)",
"reason = CSRFCheck().process_view(request, None, (), {})\nif reason:\n raise exceptions.PermissionDenied('CSRF Failed: %s' % reason)"
] | <|body_start_0|>
user = getattr(request._request, 'user', None)
if not user or not user.is_active:
return None
self.enforce_csrf(request)
return (user, None)
<|end_body_0|>
<|body_start_1|>
reason = CSRFCheck().process_view(request, None, (), {})
if reason:
... | Use Django's session framework for authentication. | SessionAuthentication | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionAuthentication:
"""Use Django's session framework for authentication."""
def authenticate(self, request):
"""Returns a `User` if the request session currently has a logged in user. Otherwise returns `None`."""
<|body_0|>
def enforce_csrf(self, request):
""... | stack_v2_sparse_classes_10k_train_002943 | 8,216 | permissive | [
{
"docstring": "Returns a `User` if the request session currently has a logged in user. Otherwise returns `None`.",
"name": "authenticate",
"signature": "def authenticate(self, request)"
},
{
"docstring": "Enforce CSRF validation for session based authentication.",
"name": "enforce_csrf",
... | 2 | stack_v2_sparse_classes_30k_train_000245 | Implement the Python class `SessionAuthentication` described below.
Class description:
Use Django's session framework for authentication.
Method signatures and docstrings:
- def authenticate(self, request): Returns a `User` if the request session currently has a logged in user. Otherwise returns `None`.
- def enforce... | Implement the Python class `SessionAuthentication` described below.
Class description:
Use Django's session framework for authentication.
Method signatures and docstrings:
- def authenticate(self, request): Returns a `User` if the request session currently has a logged in user. Otherwise returns `None`.
- def enforce... | 7e3dedddbe821283d909393f333eed4acd452953 | <|skeleton|>
class SessionAuthentication:
"""Use Django's session framework for authentication."""
def authenticate(self, request):
"""Returns a `User` if the request session currently has a logged in user. Otherwise returns `None`."""
<|body_0|>
def enforce_csrf(self, request):
""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SessionAuthentication:
"""Use Django's session framework for authentication."""
def authenticate(self, request):
"""Returns a `User` if the request session currently has a logged in user. Otherwise returns `None`."""
user = getattr(request._request, 'user', None)
if not user or no... | the_stack_v2_python_sparse | api/authentication.py | erigones/esdc-ce | train | 123 |
5a33546340dfb068cef5289b43b5decb19e22a92 | [
"left = 0\nright = len(height) - 1\nleft_max = right_max = water = 0\nwhile left < right:\n if height[left] <= height[right]:\n if height[left] >= left_max:\n left_max = height[left]\n else:\n water += left_max - height[left]\n left += 1\n else:\n if height[ri... | <|body_start_0|>
left = 0
right = len(height) - 1
left_max = right_max = water = 0
while left < right:
if height[left] <= height[right]:
if height[left] >= left_max:
left_max = height[left]
else:
water +=... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int 用两个指针来做"""
<|body_0|>
def trap1(self, height):
"""动态规划, 维护数组dp 对于height中的每一个元素 第一次遍历 dp[i]的值是height[i]左边的最大元素, 第二次遍历, dp[i] 取height[i]中右边最大元素和左边做大元素中较小的 减去height[i]就是当前元素能存的水 对于height[i],最终水平面一定... | stack_v2_sparse_classes_10k_train_002944 | 1,983 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int 用两个指针来做",
"name": "trap",
"signature": "def trap(self, height)"
},
{
"docstring": "动态规划, 维护数组dp 对于height中的每一个元素 第一次遍历 dp[i]的值是height[i]左边的最大元素, 第二次遍历, dp[i] 取height[i]中右边最大元素和左边做大元素中较小的 减去height[i]就是当前元素能存的水 对于height[i],最终水平面一定是左边做大元素和右边最大元素较小的... | 2 | stack_v2_sparse_classes_30k_train_006714 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trap(self, height): :type height: List[int] :rtype: int 用两个指针来做
- def trap1(self, height): 动态规划, 维护数组dp 对于height中的每一个元素 第一次遍历 dp[i]的值是height[i]左边的最大元素, 第二次遍历, dp[i] 取height[i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trap(self, height): :type height: List[int] :rtype: int 用两个指针来做
- def trap1(self, height): 动态规划, 维护数组dp 对于height中的每一个元素 第一次遍历 dp[i]的值是height[i]左边的最大元素, 第二次遍历, dp[i] 取height[i... | 11ad9d3841de09c0b4dc3a667e7e63c3558656a5 | <|skeleton|>
class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int 用两个指针来做"""
<|body_0|>
def trap1(self, height):
"""动态规划, 维护数组dp 对于height中的每一个元素 第一次遍历 dp[i]的值是height[i]左边的最大元素, 第二次遍历, dp[i] 取height[i]中右边最大元素和左边做大元素中较小的 减去height[i]就是当前元素能存的水 对于height[i],最终水平面一定... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int 用两个指针来做"""
left = 0
right = len(height) - 1
left_max = right_max = water = 0
while left < right:
if height[left] <= height[right]:
if height[left] >= left_max:
... | the_stack_v2_python_sparse | trapping-rain-water.py | ganlanshu/leetcode | train | 0 | |
6085c3fc8b08f9cc24ecae36b7d32f8b26182e3c | [
"roman_symbols = ['M', 'D', 'C', 'L', 'X', 'V', 'I']\nnumbers = [1000, 500, 100, 50, 10, 5, 1]\nroman = []\nfor idx, n in enumerate(numbers):\n i, num = (num / n, num % n)\n if i > 3:\n last = roman.pop()\n if last == '':\n li = [roman_symbols[idx], roman_symbols[idx - 1]]\n el... | <|body_start_0|>
roman_symbols = ['M', 'D', 'C', 'L', 'X', 'V', 'I']
numbers = [1000, 500, 100, 50, 10, 5, 1]
roman = []
for idx, n in enumerate(numbers):
i, num = (num / n, num % n)
if i > 3:
last = roman.pop()
if last == '':
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def intToRoman(self, num):
"""http://en.wikipedia.org/wiki/Roman_numerals"""
<|body_0|>
def intToRoman2(self, num):
"""little bit improvement"""
<|body_1|>
def intToRoman3(self, num):
"""recursive version"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_10k_train_002945 | 2,501 | no_license | [
{
"docstring": "http://en.wikipedia.org/wiki/Roman_numerals",
"name": "intToRoman",
"signature": "def intToRoman(self, num)"
},
{
"docstring": "little bit improvement",
"name": "intToRoman2",
"signature": "def intToRoman2(self, num)"
},
{
"docstring": "recursive version",
"na... | 3 | stack_v2_sparse_classes_30k_train_002318 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intToRoman(self, num): http://en.wikipedia.org/wiki/Roman_numerals
- def intToRoman2(self, num): little bit improvement
- def intToRoman3(self, num): recursive version | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intToRoman(self, num): http://en.wikipedia.org/wiki/Roman_numerals
- def intToRoman2(self, num): little bit improvement
- def intToRoman3(self, num): recursive version
<|ske... | c10ed7710cfbb74fd068e5c5d05d45564ad22194 | <|skeleton|>
class Solution:
def intToRoman(self, num):
"""http://en.wikipedia.org/wiki/Roman_numerals"""
<|body_0|>
def intToRoman2(self, num):
"""little bit improvement"""
<|body_1|>
def intToRoman3(self, num):
"""recursive version"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def intToRoman(self, num):
"""http://en.wikipedia.org/wiki/Roman_numerals"""
roman_symbols = ['M', 'D', 'C', 'L', 'X', 'V', 'I']
numbers = [1000, 500, 100, 50, 10, 5, 1]
roman = []
for idx, n in enumerate(numbers):
i, num = (num / n, num % n)
... | the_stack_v2_python_sparse | leetcode/python/integer-to-roman.py | deepgully/codes | train | 1 | |
36ebfbd99598734f82e688a20403ec0c57c577b6 | [
"self.generic_visit(node)\nis_multiple = len(node.targets) > 1\nis_compound = any(map(is_sequence_node, node.targets))\nis_simple = not is_compound\nif is_simple and is_multiple:\n return self.visit_simple_assign(node)\nelif is_compound and (is_multiple or is_sequence_node(node.value)):\n return self.visit_co... | <|body_start_0|>
self.generic_visit(node)
is_multiple = len(node.targets) > 1
is_compound = any(map(is_sequence_node, node.targets))
is_simple = not is_compound
if is_simple and is_multiple:
return self.visit_simple_assign(node)
elif is_compound and (is_multip... | Eliminate statements with multiple targets. Converts any assignment or deletion statement with multiple targets to a sequences of statements which each have a single target. We are careful to preserve Python's evaluation order: https://docs.python.org/3/reference/expressions.html#evaluation-order This normalization is ... | EliminateMultipleTargets | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EliminateMultipleTargets:
"""Eliminate statements with multiple targets. Converts any assignment or deletion statement with multiple targets to a sequences of statements which each have a single target. We are careful to preserve Python's evaluation order: https://docs.python.org/3/reference/expr... | stack_v2_sparse_classes_10k_train_002946 | 15,969 | permissive | [
{
"docstring": "Replace multiple assignment with single assignments.",
"name": "visit_Assign",
"signature": "def visit_Assign(self, node)"
},
{
"docstring": "Visit assignment node whose targets are all simple.",
"name": "visit_simple_assign",
"signature": "def visit_simple_assign(self, n... | 4 | stack_v2_sparse_classes_30k_train_005125 | Implement the Python class `EliminateMultipleTargets` described below.
Class description:
Eliminate statements with multiple targets. Converts any assignment or deletion statement with multiple targets to a sequences of statements which each have a single target. We are careful to preserve Python's evaluation order: h... | Implement the Python class `EliminateMultipleTargets` described below.
Class description:
Eliminate statements with multiple targets. Converts any assignment or deletion statement with multiple targets to a sequences of statements which each have a single target. We are careful to preserve Python's evaluation order: h... | a6097d36c8863925c774f04155e2af6cc8cb3859 | <|skeleton|>
class EliminateMultipleTargets:
"""Eliminate statements with multiple targets. Converts any assignment or deletion statement with multiple targets to a sequences of statements which each have a single target. We are careful to preserve Python's evaluation order: https://docs.python.org/3/reference/expr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EliminateMultipleTargets:
"""Eliminate statements with multiple targets. Converts any assignment or deletion statement with multiple targets to a sequences of statements which each have a single target. We are careful to preserve Python's evaluation order: https://docs.python.org/3/reference/expressions.html#... | the_stack_v2_python_sparse | flowgraph/trace/ast_transform.py | epatters/pyflowgraph | train | 2 |
f79227895895befb9d6477caac884e53171e7c28 | [
"super().__init__(parent, Qt.FramelessWindowHint | Qt.WindowSystemMenuHint)\nself.question = str(question)\nself.style = style\nself.initUi()",
"self.questionLabel = QLabel(self.question)\nself.questionLabel.setWordWrap(True)\nstyleBtn = '\\n QPushButton {\\n font-family: Asap;\\n fon... | <|body_start_0|>
super().__init__(parent, Qt.FramelessWindowHint | Qt.WindowSystemMenuHint)
self.question = str(question)
self.style = style
self.initUi()
<|end_body_0|>
<|body_start_1|>
self.questionLabel = QLabel(self.question)
self.questionLabel.setWordWrap(True)
... | Dialog to ask a question. | QuestionDialog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionDialog:
"""Dialog to ask a question."""
def __init__(self, parent, question, style=None):
"""Init."""
<|body_0|>
def initUi(self):
"""Ui Setup."""
<|body_1|>
def paintEvent(self, event):
"""Set window background color."""
<|bo... | stack_v2_sparse_classes_10k_train_002947 | 27,111 | no_license | [
{
"docstring": "Init.",
"name": "__init__",
"signature": "def __init__(self, parent, question, style=None)"
},
{
"docstring": "Ui Setup.",
"name": "initUi",
"signature": "def initUi(self)"
},
{
"docstring": "Set window background color.",
"name": "paintEvent",
"signature"... | 3 | stack_v2_sparse_classes_30k_train_002516 | Implement the Python class `QuestionDialog` described below.
Class description:
Dialog to ask a question.
Method signatures and docstrings:
- def __init__(self, parent, question, style=None): Init.
- def initUi(self): Ui Setup.
- def paintEvent(self, event): Set window background color. | Implement the Python class `QuestionDialog` described below.
Class description:
Dialog to ask a question.
Method signatures and docstrings:
- def __init__(self, parent, question, style=None): Init.
- def initUi(self): Ui Setup.
- def paintEvent(self, event): Set window background color.
<|skeleton|>
class QuestionDi... | a5d18593e689123cac34af552628ed2818ca5d59 | <|skeleton|>
class QuestionDialog:
"""Dialog to ask a question."""
def __init__(self, parent, question, style=None):
"""Init."""
<|body_0|>
def initUi(self):
"""Ui Setup."""
<|body_1|>
def paintEvent(self, event):
"""Set window background color."""
<|bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QuestionDialog:
"""Dialog to ask a question."""
def __init__(self, parent, question, style=None):
"""Init."""
super().__init__(parent, Qt.FramelessWindowHint | Qt.WindowSystemMenuHint)
self.question = str(question)
self.style = style
self.initUi()
def initUi(s... | the_stack_v2_python_sparse | Dialogs.py | edgary777/lonchepos | train | 0 |
54f88c0e4b171c1d19d72011ea4e774ab71db650 | [
"if values['mode'] == 'master':\n values['puppet_server'] = ''\n values['puppet_port'] = ''\n values['puppet_log'] = ''\n values['puppet_extra_opts'] = ''\n if 'puppetmaster_ports' in values:\n values['puppetmaster_ports'] = re.split('[ ,]+', values['puppetmaster_ports'])\nelse:\n values['p... | <|body_start_0|>
if values['mode'] == 'master':
values['puppet_server'] = ''
values['puppet_port'] = ''
values['puppet_log'] = ''
values['puppet_extra_opts'] = ''
if 'puppetmaster_ports' in values:
values['puppetmaster_ports'] = re.spli... | Puppet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Puppet:
def renderContext(self, values):
"""Validate values"""
<|body_0|>
def renderContextVariable(self, variable, value):
"""Final transformations on the variables"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if values['mode'] == 'master':
... | stack_v2_sparse_classes_10k_train_002948 | 2,044 | no_license | [
{
"docstring": "Validate values",
"name": "renderContext",
"signature": "def renderContext(self, values)"
},
{
"docstring": "Final transformations on the variables",
"name": "renderContextVariable",
"signature": "def renderContextVariable(self, variable, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003810 | Implement the Python class `Puppet` described below.
Class description:
Implement the Puppet class.
Method signatures and docstrings:
- def renderContext(self, values): Validate values
- def renderContextVariable(self, variable, value): Final transformations on the variables | Implement the Python class `Puppet` described below.
Class description:
Implement the Puppet class.
Method signatures and docstrings:
- def renderContext(self, values): Validate values
- def renderContextVariable(self, variable, value): Final transformations on the variables
<|skeleton|>
class Puppet:
def rende... | aacb83e9656b73edd1cac71dfcad4890a9bcc669 | <|skeleton|>
class Puppet:
def renderContext(self, values):
"""Validate values"""
<|body_0|>
def renderContextVariable(self, variable, value):
"""Final transformations on the variables"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Puppet:
def renderContext(self, values):
"""Validate values"""
if values['mode'] == 'master':
values['puppet_server'] = ''
values['puppet_port'] = ''
values['puppet_log'] = ''
values['puppet_extra_opts'] = ''
if 'puppetmaster_ports' i... | the_stack_v2_python_sparse | src/cvmo/core/plugin/puppet.py | cernvm/cernvm-online | train | 1 | |
8f02b1a1282199fd012756dfbc111afa1a50d0cb | [
"number = self.validate_number(number)\nif number == 1:\n bottom = 0\n top = self.per_page - self.delta\nelse:\n bottom = (number - 1) * self.per_page - self.delta\n top = bottom + self.per_page\nif top + self.orphans >= self.count:\n top = self.count\nreturn Page(self.object_list[bottom:top], number... | <|body_start_0|>
number = self.validate_number(number)
if number == 1:
bottom = 0
top = self.per_page - self.delta
else:
bottom = (number - 1) * self.per_page - self.delta
top = bottom + self.per_page
if top + self.orphans >= self.count:
... | DeltaFirstPagePaginator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeltaFirstPagePaginator:
def page(self, number):
"""Returns first page with `per_page` - `delta` entries."""
<|body_0|>
def num_pages(self):
"""Return the total number of pages. Add delta elements to the count to get all pages."""
<|body_1|>
<|end_skeleton|>... | stack_v2_sparse_classes_10k_train_002949 | 1,054 | no_license | [
{
"docstring": "Returns first page with `per_page` - `delta` entries.",
"name": "page",
"signature": "def page(self, number)"
},
{
"docstring": "Return the total number of pages. Add delta elements to the count to get all pages.",
"name": "num_pages",
"signature": "def num_pages(self)"
... | 2 | stack_v2_sparse_classes_30k_test_000318 | Implement the Python class `DeltaFirstPagePaginator` described below.
Class description:
Implement the DeltaFirstPagePaginator class.
Method signatures and docstrings:
- def page(self, number): Returns first page with `per_page` - `delta` entries.
- def num_pages(self): Return the total number of pages. Add delta ele... | Implement the Python class `DeltaFirstPagePaginator` described below.
Class description:
Implement the DeltaFirstPagePaginator class.
Method signatures and docstrings:
- def page(self, number): Returns first page with `per_page` - `delta` entries.
- def num_pages(self): Return the total number of pages. Add delta ele... | e1a019c8fdf5c9ff6a384a45b56bffef128b78c1 | <|skeleton|>
class DeltaFirstPagePaginator:
def page(self, number):
"""Returns first page with `per_page` - `delta` entries."""
<|body_0|>
def num_pages(self):
"""Return the total number of pages. Add delta elements to the count to get all pages."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DeltaFirstPagePaginator:
def page(self, number):
"""Returns first page with `per_page` - `delta` entries."""
number = self.validate_number(number)
if number == 1:
bottom = 0
top = self.per_page - self.delta
else:
bottom = (number - 1) * self.... | the_stack_v2_python_sparse | apps/ideas/paginators.py | liqd/a4-advocate-europe | train | 8 | |
00dae8042704e80640a7e55b555150b0f19433fc | [
"pt_r = np.array([[-1, -3], [0, -2]])\npt_r -= pt_r.min()\npt_c = pt_r.T\npt = np.stack((pt_r, pt_c), axis=0).astype(float)\npt /= pt.max()\ngame = MatrixGame(pt, seed=0)\nsolver = qre_anneal_sym.Solver(temperature=100, proj_grad=False, euclidean=True, lrs=(0.0001, 0.0001), exp_thresh=0.01, rnd_init=True, seed=0)\n... | <|body_start_0|>
pt_r = np.array([[-1, -3], [0, -2]])
pt_r -= pt_r.min()
pt_c = pt_r.T
pt = np.stack((pt_r, pt_c), axis=0).astype(float)
pt /= pt.max()
game = MatrixGame(pt, seed=0)
solver = qre_anneal_sym.Solver(temperature=100, proj_grad=False, euclidean=True, l... | AdidasTest | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdidasTest:
def test_adidas_on_prisoners_dilemma(self):
"""Tests ADIDAS on a 2-player prisoner's dilemma game."""
<|body_0|>
def test_adidas_on_elfarol(self):
"""Test ADIDAS on a 10-player, symmetric El Farol bar game."""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_002950 | 3,284 | permissive | [
{
"docstring": "Tests ADIDAS on a 2-player prisoner's dilemma game.",
"name": "test_adidas_on_prisoners_dilemma",
"signature": "def test_adidas_on_prisoners_dilemma(self)"
},
{
"docstring": "Test ADIDAS on a 10-player, symmetric El Farol bar game.",
"name": "test_adidas_on_elfarol",
"sig... | 2 | stack_v2_sparse_classes_30k_train_001097 | Implement the Python class `AdidasTest` described below.
Class description:
Implement the AdidasTest class.
Method signatures and docstrings:
- def test_adidas_on_prisoners_dilemma(self): Tests ADIDAS on a 2-player prisoner's dilemma game.
- def test_adidas_on_elfarol(self): Test ADIDAS on a 10-player, symmetric El F... | Implement the Python class `AdidasTest` described below.
Class description:
Implement the AdidasTest class.
Method signatures and docstrings:
- def test_adidas_on_prisoners_dilemma(self): Tests ADIDAS on a 2-player prisoner's dilemma game.
- def test_adidas_on_elfarol(self): Test ADIDAS on a 10-player, symmetric El F... | ee149736f7d85e16c119a463eee338c6d4c2ceb0 | <|skeleton|>
class AdidasTest:
def test_adidas_on_prisoners_dilemma(self):
"""Tests ADIDAS on a 2-player prisoner's dilemma game."""
<|body_0|>
def test_adidas_on_elfarol(self):
"""Test ADIDAS on a 10-player, symmetric El Farol bar game."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AdidasTest:
def test_adidas_on_prisoners_dilemma(self):
"""Tests ADIDAS on a 2-player prisoner's dilemma game."""
pt_r = np.array([[-1, -3], [0, -2]])
pt_r -= pt_r.min()
pt_c = pt_r.T
pt = np.stack((pt_r, pt_c), axis=0).astype(float)
pt /= pt.max()
game ... | the_stack_v2_python_sparse | open_spiel/python/algorithms/adidas_test.py | lanctot/open_spiel | train | 1 | |
bfad6bfbc02b9bcd2423361806c38537356f56d4 | [
"def merge_sort(nums, nums_copy, start, end):\n if start >= end:\n return\n start1 = start\n end1 = (start + end) // 2\n start2 = end1 + 1\n end2 = end\n merge_sort(nums, nums_copy, start1, end1)\n merge_sort(nums, nums_copy, start2, end2)\n k = start\n while start1 <= end1 and sta... | <|body_start_0|>
def merge_sort(nums, nums_copy, start, end):
if start >= end:
return
start1 = start
end1 = (start + end) // 2
start2 = end1 + 1
end2 = end
merge_sort(nums, nums_copy, start1, end1)
merge_sort(num... | 执行结果：通过 执行用时：48 ms, 在所有 Python3 提交中击败了15.36%的用户 内存消耗：15 MB, 在所有 Python3 提交中击败了8.49%的用户 自己写的归并排序，有点慢！！！ 归并排序的缺点，需要使用O(N)的额外数组空间 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""执行结果：通过 执行用时：48 ms, 在所有 Python3 提交中击败了15.36%的用户 内存消耗：15 MB, 在所有 Python3 提交中击败了8.49%的用户 自己写的归并排序，有点慢！！！ 归并排序的缺点，需要使用O(N)的额外数组空间"""
def sortColors(self, nums):
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def sortColors2(self, nums):
... | stack_v2_sparse_classes_10k_train_002951 | 3,257 | no_license | [
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "sortColors",
"signature": "def sortColors(self, nums)"
},
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "sortColors2",
"signature": "def sortColors2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004365 | Implement the Python class `Solution` described below.
Class description:
执行结果：通过 执行用时：48 ms, 在所有 Python3 提交中击败了15.36%的用户 内存消耗：15 MB, 在所有 Python3 提交中击败了8.49%的用户 自己写的归并排序，有点慢！！！ 归并排序的缺点，需要使用O(N)的额外数组空间
Method signatures and docstrings:
- def sortColors(self, nums): Do not return anything, modify nums in-place instead.... | Implement the Python class `Solution` described below.
Class description:
执行结果：通过 执行用时：48 ms, 在所有 Python3 提交中击败了15.36%的用户 内存消耗：15 MB, 在所有 Python3 提交中击败了8.49%的用户 自己写的归并排序，有点慢！！！ 归并排序的缺点，需要使用O(N)的额外数组空间
Method signatures and docstrings:
- def sortColors(self, nums): Do not return anything, modify nums in-place instead.... | af4b922484879365921fa4252edf57fe19e53e6a | <|skeleton|>
class Solution:
"""执行结果：通过 执行用时：48 ms, 在所有 Python3 提交中击败了15.36%的用户 内存消耗：15 MB, 在所有 Python3 提交中击败了8.49%的用户 自己写的归并排序，有点慢！！！ 归并排序的缺点，需要使用O(N)的额外数组空间"""
def sortColors(self, nums):
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def sortColors2(self, nums):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
"""执行结果：通过 执行用时：48 ms, 在所有 Python3 提交中击败了15.36%的用户 内存消耗：15 MB, 在所有 Python3 提交中击败了8.49%的用户 自己写的归并排序，有点慢！！！ 归并排序的缺点，需要使用O(N)的额外数组空间"""
def sortColors(self, nums):
"""Do not return anything, modify nums in-place instead."""
def merge_sort(nums, nums_copy, start, end):
i... | the_stack_v2_python_sparse | LeetCode/leetcode#075.py | wsldwo/Python | train | 0 |
dfb6dffb0f177d15b329a7ec41cdbdf6521be772 | [
"try:\n serializer = RadiologistReportFilesSerializers(RadiologistReportFiles.objects.all(), many=True)\n return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)\nexcept Exception as e:\n info_message = 'Internal Server Error'\n logger.error(info_message, e)\n return JsonR... | <|body_start_0|>
try:
serializer = RadiologistReportFilesSerializers(RadiologistReportFiles.objects.all(), many=True)
return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)
except Exception as e:
info_message = 'Internal Server Error'
... | RadiologistReportFilesView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RadiologistReportFilesView:
def get(self, request):
"""Get all sellers"""
<|body_0|>
def post(self, request):
"""Save seller data"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
serializer = RadiologistReportFilesSerializers(Radiolo... | stack_v2_sparse_classes_10k_train_002952 | 31,833 | no_license | [
{
"docstring": "Get all sellers",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Save seller data",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006608 | Implement the Python class `RadiologistReportFilesView` described below.
Class description:
Implement the RadiologistReportFilesView class.
Method signatures and docstrings:
- def get(self, request): Get all sellers
- def post(self, request): Save seller data | Implement the Python class `RadiologistReportFilesView` described below.
Class description:
Implement the RadiologistReportFilesView class.
Method signatures and docstrings:
- def get(self, request): Get all sellers
- def post(self, request): Save seller data
<|skeleton|>
class RadiologistReportFilesView:
def g... | b63849983a592fd6a1f654191020fd86aa0787ae | <|skeleton|>
class RadiologistReportFilesView:
def get(self, request):
"""Get all sellers"""
<|body_0|>
def post(self, request):
"""Save seller data"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RadiologistReportFilesView:
def get(self, request):
"""Get all sellers"""
try:
serializer = RadiologistReportFilesSerializers(RadiologistReportFiles.objects.all(), many=True)
return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)
exc... | the_stack_v2_python_sparse | radiologist/views.py | RupeshKurlekar/biocare | train | 1 | |
e87a8683d4300f34018575e8d42abaf0fb780b5c | [
"self._model = model\nself.path = path\nself.external_data_path = external_data_path\nself.size_threshold = size_threshold\nself.all_tensors_to_one_file = all_tensors_to_one_file",
"model, _ = util.invoke_if_callable(self._model)\nG_LOGGER.info(f'Saving ONNX model to: {self.path}')\nif self.external_data_path is ... | <|body_start_0|>
self._model = model
self.path = path
self.external_data_path = external_data_path
self.size_threshold = size_threshold
self.all_tensors_to_one_file = all_tensors_to_one_file
<|end_body_0|>
<|body_start_1|>
model, _ = util.invoke_if_callable(self._model)
... | Functor that saves an ONNX model to the specified path. | SaveOnnx | [
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"ISC",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaveOnnx:
"""Functor that saves an ONNX model to the specified path."""
def __init__(self, model, path, external_data_path=None, size_threshold=None, all_tensors_to_one_file=None):
"""Saves an ONNX model to the specified path. Args: model (Union[onnx.ModelProto, Callable() -> onnx.Mo... | stack_v2_sparse_classes_10k_train_002953 | 37,448 | permissive | [
{
"docstring": "Saves an ONNX model to the specified path. Args: model (Union[onnx.ModelProto, Callable() -> onnx.ModelProto]): An ONNX model or a callable that returns one. path (str): Path at which to write the ONNX model. external_data_path (str): Path to save external data. This is always a relative path; e... | 2 | null | Implement the Python class `SaveOnnx` described below.
Class description:
Functor that saves an ONNX model to the specified path.
Method signatures and docstrings:
- def __init__(self, model, path, external_data_path=None, size_threshold=None, all_tensors_to_one_file=None): Saves an ONNX model to the specified path. ... | Implement the Python class `SaveOnnx` described below.
Class description:
Functor that saves an ONNX model to the specified path.
Method signatures and docstrings:
- def __init__(self, model, path, external_data_path=None, size_threshold=None, all_tensors_to_one_file=None): Saves an ONNX model to the specified path. ... | a167852705d74bcc619d8fad0af4b9e4d84472fc | <|skeleton|>
class SaveOnnx:
"""Functor that saves an ONNX model to the specified path."""
def __init__(self, model, path, external_data_path=None, size_threshold=None, all_tensors_to_one_file=None):
"""Saves an ONNX model to the specified path. Args: model (Union[onnx.ModelProto, Callable() -> onnx.Mo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SaveOnnx:
"""Functor that saves an ONNX model to the specified path."""
def __init__(self, model, path, external_data_path=None, size_threshold=None, all_tensors_to_one_file=None):
"""Saves an ONNX model to the specified path. Args: model (Union[onnx.ModelProto, Callable() -> onnx.ModelProto]): A... | the_stack_v2_python_sparse | tools/Polygraphy/polygraphy/backend/onnx/loader.py | NVIDIA/TensorRT | train | 8,026 |
40a15310b790c7932bcda06941d80f6183e8507f | [
"if not nums:\n return 0\nif len(nums) == 1:\n return nums[0]\nreturn max(self.rob1(nums[:-1]), self.rob1(nums[1:]))",
"size = len(num)\nif size == 0:\n return 0\nif size == 1:\n return num[0]\ndp = [0] * (size + 1)\ndp[0] = 0\ndp[1] = num[0]\nfor i in range(2, size + 1):\n dp[i] = max(dp[i - 1], d... | <|body_start_0|>
if not nums:
return 0
if len(nums) == 1:
return nums[0]
return max(self.rob1(nums[:-1]), self.rob1(nums[1:]))
<|end_body_0|>
<|body_start_1|>
size = len(num)
if size == 0:
return 0
if size == 1:
return num[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob1(self, num):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums:
return 0
if len(nums) == 1:
... | stack_v2_sparse_classes_10k_train_002954 | 2,121 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob",
"signature": "def rob(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob1",
"signature": "def rob1(self, num)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003197 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): :type nums: List[int] :rtype: int
- def rob1(self, num): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): :type nums: List[int] :rtype: int
- def rob1(self, num): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def rob(self, nums):
""... | fa638c7fda3802e9f4e0751a2c4c084edf09a441 | <|skeleton|>
class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob1(self, num):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return 0
if len(nums) == 1:
return nums[0]
return max(self.rob1(nums[:-1]), self.rob1(nums[1:]))
def rob1(self, num):
""":type nums: List[int] :rtype: int"""... | the_stack_v2_python_sparse | python/Dynamic Programming/213.House Robber II.py | EvanJamesMG/Leetcode | train | 5 | |
037b81d5fc2915be31411588c120f790c9a0b5c2 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\ntry:\n mapping_value = parse_node.get_child_node('@odata.type').get_str_value()\nexcept AttributeError:\n mapping_value = None\nif mapping_value and mapping_value.casefold() == '#microsoft.graph.printUsageByPrinter'.casefold():\n from ... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
try:
mapping_value = parse_node.get_child_node('@odata.type').get_str_value()
except AttributeError:
mapping_value = None
if mapping_value and mapping_value.casefold() ==... | PrintUsage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrintUsage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrintUsage:
"""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: Prin... | stack_v2_sparse_classes_10k_train_002955 | 5,663 | 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: PrintUsage",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(pa... | 3 | null | Implement the Python class `PrintUsage` described below.
Class description:
Implement the PrintUsage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrintUsage: Creates a new instance of the appropriate class based on discriminator value Args: pa... | Implement the Python class `PrintUsage` described below.
Class description:
Implement the PrintUsage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrintUsage: Creates a new instance of the appropriate class based on discriminator value Args: pa... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class PrintUsage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrintUsage:
"""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: Prin... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PrintUsage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrintUsage:
"""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: PrintUsage"""
... | the_stack_v2_python_sparse | msgraph/generated/models/print_usage.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
40606cd2eaf7ff4d64ad74d4605912873ac3b6f5 | [
"if vocab is None:\n vocab = default_vocab(default_vocab_size)\nwith tf.device('cpu'):\n self._table = tf.lookup.StaticVocabularyTable(tf.lookup.KeyValueTensorInitializer(vocab, tf.range(len(vocab), dtype=tf.int64)), num_oov_buckets=num_oov_buckets)",
"@tf.function(input_signature=[tf.TensorSpec(shape=[None... | <|body_start_0|>
if vocab is None:
vocab = default_vocab(default_vocab_size)
with tf.device('cpu'):
self._table = tf.lookup.StaticVocabularyTable(tf.lookup.KeyValueTensorInitializer(vocab, tf.range(len(vocab), dtype=tf.int64)), num_oov_buckets=num_oov_buckets)
<|end_body_0|>
<|b... | Tokenizer for the `tokens` feature in stackoverflow. See :meth:`load_data` for examples. | StackoverflowTokenizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StackoverflowTokenizer:
"""Tokenizer for the `tokens` feature in stackoverflow. See :meth:`load_data` for examples."""
def __init__(self, vocab: Optional[List[str]]=None, default_vocab_size: Optional[int]=10000, num_oov_buckets: int=1):
"""Initializes a tokenizer. Args: vocab: Option... | stack_v2_sparse_classes_10k_train_002956 | 8,376 | permissive | [
{
"docstring": "Initializes a tokenizer. Args: vocab: Optional vocabulary. If specified, `default_vocab_size` is ignored. If None, `default_vocab_size` is used to load the standard vocabulary. This vocabulary should NOT have special tokens PAD, EOS, BOS, and OOV. The special tokens are added and handled automat... | 2 | stack_v2_sparse_classes_30k_train_000764 | Implement the Python class `StackoverflowTokenizer` described below.
Class description:
Tokenizer for the `tokens` feature in stackoverflow. See :meth:`load_data` for examples.
Method signatures and docstrings:
- def __init__(self, vocab: Optional[List[str]]=None, default_vocab_size: Optional[int]=10000, num_oov_buck... | Implement the Python class `StackoverflowTokenizer` described below.
Class description:
Tokenizer for the `tokens` feature in stackoverflow. See :meth:`load_data` for examples.
Method signatures and docstrings:
- def __init__(self, vocab: Optional[List[str]]=None, default_vocab_size: Optional[int]=10000, num_oov_buck... | b78a052a0445a32270c446e778e0c0b73df854ed | <|skeleton|>
class StackoverflowTokenizer:
"""Tokenizer for the `tokens` feature in stackoverflow. See :meth:`load_data` for examples."""
def __init__(self, vocab: Optional[List[str]]=None, default_vocab_size: Optional[int]=10000, num_oov_buckets: int=1):
"""Initializes a tokenizer. Args: vocab: Option... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StackoverflowTokenizer:
"""Tokenizer for the `tokens` feature in stackoverflow. See :meth:`load_data` for examples."""
def __init__(self, vocab: Optional[List[str]]=None, default_vocab_size: Optional[int]=10000, num_oov_buckets: int=1):
"""Initializes a tokenizer. Args: vocab: Optional vocabulary... | the_stack_v2_python_sparse | fedjax/datasets/stackoverflow.py | jaehunro/fedjax | train | 0 |
09ceeff88db61da4ecf6a84878bedc5302bdf39a | [
"if self.request.version == 'v6':\n return ScanSerializerV6\nelif self.request.version == 'v7':\n return ScanSerializerV6",
"if request.version == 'v6':\n return self._list_v6(request)\nelif request.version == 'v7':\n return self._list_v6(request)\nraise Http404()",
"started = rest_util.parse_timest... | <|body_start_0|>
if self.request.version == 'v6':
return ScanSerializerV6
elif self.request.version == 'v7':
return ScanSerializerV6
<|end_body_0|>
<|body_start_1|>
if request.version == 'v6':
return self._list_v6(request)
elif request.version == 'v7'... | This view is the endpoint for retrieving the list of all Scan process. | ScansView | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScansView:
"""This view is the endpoint for retrieving the list of all Scan process."""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
<|body_0|>
def list(self, request):
"""Retrieves the l... | stack_v2_sparse_classes_10k_train_002957 | 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": "Retrieves the list of all Scan process and returns it in JSON form :param request: the HTTP GET re... | 5 | null | Implement the Python class `ScansView` described below.
Class description:
This view is the endpoint for retrieving the list of all Scan process.
Method signatures and docstrings:
- def get_serializer_class(self): Returns the appropriate serializer based off the requests version of the REST API.
- def list(self, requ... | Implement the Python class `ScansView` described below.
Class description:
This view is the endpoint for retrieving the list of all Scan process.
Method signatures and docstrings:
- def get_serializer_class(self): Returns the appropriate serializer based off the requests version of the REST API.
- def list(self, requ... | 28618aee07ceed9e4a6eb7b8d0e6f05b31d8fd6b | <|skeleton|>
class ScansView:
"""This view is the endpoint for retrieving the list of all Scan process."""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
<|body_0|>
def list(self, request):
"""Retrieves the l... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ScansView:
"""This view is the endpoint for retrieving the list of all Scan process."""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
if self.request.version == 'v6':
return ScanSerializerV6
eli... | the_stack_v2_python_sparse | scale/ingest/views.py | kfconsultant/scale | train | 0 |
a0d465e69f3bc97209e2bc3e56f12378e27eacf9 | [
"self.model_type = model_type\nself.batch_size = batch_size\nself.save_dir = save_dir\nif model_type == 'resnet':\n m = models.resnet152(pretrained=True)\n self.features = nn.Sequential(*[mod for n, mod in m._modules.items() if n not in ['avgpool', 'fc']])\nelif model_type == 'densenet':\n m = models.dense... | <|body_start_0|>
self.model_type = model_type
self.batch_size = batch_size
self.save_dir = save_dir
if model_type == 'resnet':
m = models.resnet152(pretrained=True)
self.features = nn.Sequential(*[mod for n, mod in m._modules.items() if n not in ['avgpool', 'fc']]... | Image Featurizer. | ImgFeaturizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImgFeaturizer:
"""Image Featurizer."""
def __init__(self, model_type, batch_size, save_dir):
"""Initialize ImgFeatureizer. Args ---- batch_size : int, batch size for data loader. save_dir : string, path to directory for saving img features."""
<|body_0|>
def transform(se... | stack_v2_sparse_classes_10k_train_002958 | 2,563 | no_license | [
{
"docstring": "Initialize ImgFeatureizer. Args ---- batch_size : int, batch size for data loader. save_dir : string, path to directory for saving img features.",
"name": "__init__",
"signature": "def __init__(self, model_type, batch_size, save_dir)"
},
{
"docstring": "Transform imgs to features... | 2 | stack_v2_sparse_classes_30k_train_003914 | Implement the Python class `ImgFeaturizer` described below.
Class description:
Image Featurizer.
Method signatures and docstrings:
- def __init__(self, model_type, batch_size, save_dir): Initialize ImgFeatureizer. Args ---- batch_size : int, batch size for data loader. save_dir : string, path to directory for saving ... | Implement the Python class `ImgFeaturizer` described below.
Class description:
Image Featurizer.
Method signatures and docstrings:
- def __init__(self, model_type, batch_size, save_dir): Initialize ImgFeatureizer. Args ---- batch_size : int, batch size for data loader. save_dir : string, path to directory for saving ... | fbfa1766dbc52cbf39036abe1a44f9315fad4a5c | <|skeleton|>
class ImgFeaturizer:
"""Image Featurizer."""
def __init__(self, model_type, batch_size, save_dir):
"""Initialize ImgFeatureizer. Args ---- batch_size : int, batch size for data loader. save_dir : string, path to directory for saving img features."""
<|body_0|>
def transform(se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ImgFeaturizer:
"""Image Featurizer."""
def __init__(self, model_type, batch_size, save_dir):
"""Initialize ImgFeatureizer. Args ---- batch_size : int, batch size for data loader. save_dir : string, path to directory for saving img features."""
self.model_type = model_type
self.bat... | the_stack_v2_python_sparse | preprocessing/img_featurizer.py | estebandito22/MC-BERT | train | 0 |
5e53b81f0e2794d3d95e17b1762dd2492bf41c25 | [
"self.pwdScheme = PasswordScheme() if pwdScheme is None else pwdScheme\nself.loginController = LoginController(toJson, pwdScheme=pwdScheme)\nCreateController.__init__(self, User, None, recordValueProvider=recordValueProvider)",
"try:\n createKwargs = dict(json)\n createKwargs['password'] = self.pwdScheme.ma... | <|body_start_0|>
self.pwdScheme = PasswordScheme() if pwdScheme is None else pwdScheme
self.loginController = LoginController(toJson, pwdScheme=pwdScheme)
CreateController.__init__(self, User, None, recordValueProvider=recordValueProvider)
<|end_body_0|>
<|body_start_1|>
try:
... | Controller to register a user | RegisterController | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegisterController:
"""Controller to register a user"""
def __init__(self, toJson, pwdScheme=None, recordValueProvider=None):
"""Initialize the Register Controller"""
<|body_0|>
def performWithJSON(self, json=None):
"""Create a User record with the given credenti... | stack_v2_sparse_classes_10k_train_002959 | 1,277 | permissive | [
{
"docstring": "Initialize the Register Controller",
"name": "__init__",
"signature": "def __init__(self, toJson, pwdScheme=None, recordValueProvider=None)"
},
{
"docstring": "Create a User record with the given credentials",
"name": "performWithJSON",
"signature": "def performWithJSON(s... | 2 | null | Implement the Python class `RegisterController` described below.
Class description:
Controller to register a user
Method signatures and docstrings:
- def __init__(self, toJson, pwdScheme=None, recordValueProvider=None): Initialize the Register Controller
- def performWithJSON(self, json=None): Create a User record wi... | Implement the Python class `RegisterController` described below.
Class description:
Controller to register a user
Method signatures and docstrings:
- def __init__(self, toJson, pwdScheme=None, recordValueProvider=None): Initialize the Register Controller
- def performWithJSON(self, json=None): Create a User record wi... | 2a54293181c1c2b1a2b840ddee4d4d80177efb33 | <|skeleton|>
class RegisterController:
"""Controller to register a user"""
def __init__(self, toJson, pwdScheme=None, recordValueProvider=None):
"""Initialize the Register Controller"""
<|body_0|>
def performWithJSON(self, json=None):
"""Create a User record with the given credenti... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RegisterController:
"""Controller to register a user"""
def __init__(self, toJson, pwdScheme=None, recordValueProvider=None):
"""Initialize the Register Controller"""
self.pwdScheme = PasswordScheme() if pwdScheme is None else pwdScheme
self.loginController = LoginController(toJso... | the_stack_v2_python_sparse | data/train/python/99f7f822e985fbf40ac8620e7a822e58c4b138e0register_controller.py | harshp8l/deep-learning-lang-detection | train | 0 |
283c28bc1bef0f0d4a6851ce8feed887180c31a8 | [
"mimetype = self.context.resource_mimetype()\nif mimetype:\n mime_parts = mimetype.split('/')\n for view_name in ['%s_%s' % tuple(mime_parts), mime_parts[0], 'default']:\n view = queryMultiAdapter((self.context, self.request), name='resource_%s' % view_name)\n if view:\n return view._... | <|body_start_0|>
mimetype = self.context.resource_mimetype()
if mimetype:
mime_parts = mimetype.split('/')
for view_name in ['%s_%s' % tuple(mime_parts), mime_parts[0], 'default']:
view = queryMultiAdapter((self.context, self.request), name='resource_%s' % view_na... | A view to display a resource. | ATResourceView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ATResourceView:
"""A view to display a resource."""
def resource_view(self):
"""Returns the view for the resource based on its mimetype."""
<|body_0|>
def resource(self):
"""Renders the resource."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
m... | stack_v2_sparse_classes_10k_train_002960 | 1,247 | no_license | [
{
"docstring": "Returns the view for the resource based on its mimetype.",
"name": "resource_view",
"signature": "def resource_view(self)"
},
{
"docstring": "Renders the resource.",
"name": "resource",
"signature": "def resource(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007165 | Implement the Python class `ATResourceView` described below.
Class description:
A view to display a resource.
Method signatures and docstrings:
- def resource_view(self): Returns the view for the resource based on its mimetype.
- def resource(self): Renders the resource. | Implement the Python class `ATResourceView` described below.
Class description:
A view to display a resource.
Method signatures and docstrings:
- def resource_view(self): Returns the view for the resource based on its mimetype.
- def resource(self): Renders the resource.
<|skeleton|>
class ATResourceView:
"""A v... | bd7ca0793d35bbdbc83200d27650fe024d1f432e | <|skeleton|>
class ATResourceView:
"""A view to display a resource."""
def resource_view(self):
"""Returns the view for the resource based on its mimetype."""
<|body_0|>
def resource(self):
"""Renders the resource."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ATResourceView:
"""A view to display a resource."""
def resource_view(self):
"""Returns the view for the resource based on its mimetype."""
mimetype = self.context.resource_mimetype()
if mimetype:
mime_parts = mimetype.split('/')
for view_name in ['%s_%s' %... | the_stack_v2_python_sparse | groundwire/atresources/browser/atresource.py | collective/groundwire.atresources | train | 0 |
7f7363430380b5165615220db708e3c1596e3861 | [
"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... | UserProvider API. The UserProvider API is responsible for creating a key-value map according to user userprovider. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC 2119. The followi... | UserAPIServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserAPIServicer:
"""UserProvider API. The UserProvider API is responsible for creating a key-value map according to user userprovider. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interp... | stack_v2_sparse_classes_10k_train_002961 | 5,753 | no_license | [
{
"docstring": "Gets the information about an user by its user id.",
"name": "GetUser",
"signature": "def GetUser(self, request, context)"
},
{
"docstring": "Gets the groups of a user.",
"name": "GetUserGroups",
"signature": "def GetUserGroups(self, request, context)"
},
{
"docst... | 4 | stack_v2_sparse_classes_30k_test_000245 | Implement the Python class `UserAPIServicer` described below.
Class description:
UserProvider API. The UserProvider API is responsible for creating a key-value map according to user userprovider. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTI... | Implement the Python class `UserAPIServicer` described below.
Class description:
UserProvider API. The UserProvider API is responsible for creating a key-value map according to user userprovider. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTI... | dad1a042b38db5f8bedcac3b6af25066f4d6eef9 | <|skeleton|>
class UserAPIServicer:
"""UserProvider API. The UserProvider API is responsible for creating a key-value map according to user userprovider. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interp... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserAPIServicer:
"""UserProvider API. The UserProvider API is responsible for creating a key-value map according to user userprovider. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as desc... | the_stack_v2_python_sparse | cs3/identity/user/v1beta1/user_api_pb2_grpc.py | SamuAlfageme/python-cs3apis | train | 0 |
aa4c6f10795ae00117ff3fdeb1c77f2b2f3964e7 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn IosStoreAppAssignmentSettings()",
"from .mobile_app_assignment_settings import MobileAppAssignmentSettings\nfrom .mobile_app_assignment_settings import MobileAppAssignmentSettings\nfields: Dict[str, Callable[[Any], None]] = {'isRemovab... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return IosStoreAppAssignmentSettings()
<|end_body_0|>
<|body_start_1|>
from .mobile_app_assignment_settings import MobileAppAssignmentSettings
from .mobile_app_assignment_settings import Mobile... | Contains properties used to assign an iOS Store mobile app to a group. | IosStoreAppAssignmentSettings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IosStoreAppAssignmentSettings:
"""Contains properties used to assign an iOS Store mobile app to a group."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosStoreAppAssignmentSettings:
"""Creates a new instance of the appropriate class based on discrimi... | stack_v2_sparse_classes_10k_train_002962 | 3,409 | 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: IosStoreAppAssignmentSettings",
"name": "create_from_discriminator_value",
"signature": "def create_from_dis... | 3 | stack_v2_sparse_classes_30k_train_006978 | Implement the Python class `IosStoreAppAssignmentSettings` described below.
Class description:
Contains properties used to assign an iOS Store mobile app to a group.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosStoreAppAssignmentSettings: Creates ... | Implement the Python class `IosStoreAppAssignmentSettings` described below.
Class description:
Contains properties used to assign an iOS Store mobile app to a group.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosStoreAppAssignmentSettings: Creates ... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class IosStoreAppAssignmentSettings:
"""Contains properties used to assign an iOS Store mobile app to a group."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosStoreAppAssignmentSettings:
"""Creates a new instance of the appropriate class based on discrimi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IosStoreAppAssignmentSettings:
"""Contains properties used to assign an iOS Store mobile app to a group."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosStoreAppAssignmentSettings:
"""Creates a new instance of the appropriate class based on discriminator value A... | the_stack_v2_python_sparse | msgraph/generated/models/ios_store_app_assignment_settings.py | microsoftgraph/msgraph-sdk-python | train | 135 |
c7e8906553914cb951cb023b1af42c20752c8be1 | [
"assert_pycocotools_installed('PyCOCOWrapper')\nCOCO.__init__(self, annotation_file=None)\nself._eval_type = 'box'\nif gt_dataset:\n self.dataset = gt_dataset\n self.createIndex()",
"res = COCO()\nres.dataset['images'] = copy.deepcopy(self.dataset['images'])\nres.dataset['categories'] = copy.deepcopy(self.d... | <|body_start_0|>
assert_pycocotools_installed('PyCOCOWrapper')
COCO.__init__(self, annotation_file=None)
self._eval_type = 'box'
if gt_dataset:
self.dataset = gt_dataset
self.createIndex()
<|end_body_0|>
<|body_start_1|>
res = COCO()
res.dataset['... | COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support loading the prediction results using the external annotation dictionary. | PyCOCOWrapper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyCOCOWrapper:
"""COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support loading the prediction results using th... | stack_v2_sparse_classes_10k_train_002963 | 8,149 | permissive | [
{
"docstring": "Instantiates a COCO-style API object. Args: eval_type: either 'box' or 'mask'. annotation_file: a JSON file that stores annotations of the eval dataset. This is required if `gt_dataset` is not provided. gt_dataset: the groundtruth eval dataset in COCO API format.",
"name": "__init__",
"s... | 2 | null | Implement the Python class `PyCOCOWrapper` described below.
Class description:
COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support ... | Implement the Python class `PyCOCOWrapper` described below.
Class description:
COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support ... | e83f229f1b7b847cd712d5cd4810097d3e06d14e | <|skeleton|>
class PyCOCOWrapper:
"""COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support loading the prediction results using th... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PyCOCOWrapper:
"""COCO wrapper class. This class wraps COCO API object, which provides the following additional functionalities: 1. Support string type image id. 2. Support loading the groundtruth dataset using the external annotation dictionary. 3. Support loading the prediction results using the external an... | the_stack_v2_python_sparse | keras_cv/metrics/coco/pycoco_wrapper.py | keras-team/keras-cv | train | 818 |
442b6cfa1a9cf18acc2f172b4e8b762538b00071 | [
"assert len(ids) == 1, 'This option should only be used for a single id at a time.'\nir_model_data = self.pool.get('ir.model.data')\nres = {}\npicking = self.browse(cr, uid, ids[0])\ntry:\n template_id = ir_model_data.get_object_reference(cr, uid, 'openforce_sale', 'openforce_ddt_email_template')[1]\nexcept Valu... | <|body_start_0|>
assert len(ids) == 1, 'This option should only be used for a single id at a time.'
ir_model_data = self.pool.get('ir.model.data')
res = {}
picking = self.browse(cr, uid, ids[0])
try:
template_id = ir_model_data.get_object_reference(cr, uid, 'openforce... | stock_picking_out | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stock_picking_out:
def action_ddt_sent(self, cr, uid, ids, context=None):
"""This function opens a window to compose an email, with the edi invoice template message loaded by default"""
<|body_0|>
def _total_amount(self, cr, uid, ids, name, args, context=None):
"""Co... | stack_v2_sparse_classes_10k_train_002964 | 10,203 | no_license | [
{
"docstring": "This function opens a window to compose an email, with the edi invoice template message loaded by default",
"name": "action_ddt_sent",
"signature": "def action_ddt_sent(self, cr, uid, ids, context=None)"
},
{
"docstring": "Compute the attendances, analytic lines timesheets and di... | 2 | stack_v2_sparse_classes_30k_train_001856 | Implement the Python class `stock_picking_out` described below.
Class description:
Implement the stock_picking_out class.
Method signatures and docstrings:
- def action_ddt_sent(self, cr, uid, ids, context=None): This function opens a window to compose an email, with the edi invoice template message loaded by default... | Implement the Python class `stock_picking_out` described below.
Class description:
Implement the stock_picking_out class.
Method signatures and docstrings:
- def action_ddt_sent(self, cr, uid, ids, context=None): This function opens a window to compose an email, with the edi invoice template message loaded by default... | 78fc164679b690bcf84866987266838de134bc2f | <|skeleton|>
class stock_picking_out:
def action_ddt_sent(self, cr, uid, ids, context=None):
"""This function opens a window to compose an email, with the edi invoice template message loaded by default"""
<|body_0|>
def _total_amount(self, cr, uid, ids, name, args, context=None):
"""Co... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class stock_picking_out:
def action_ddt_sent(self, cr, uid, ids, context=None):
"""This function opens a window to compose an email, with the edi invoice template message loaded by default"""
assert len(ids) == 1, 'This option should only be used for a single id at a time.'
ir_model_data = s... | the_stack_v2_python_sparse | openforce_sale/stock/picking.py | alessandrocamilli/7-openforce-addons | train | 1 | |
85f82fd233c92a6959977eda259030bfddc12bc5 | [
"if isinstance(levels, int):\n levels = np.arange(levels)\nself.est = estimator\nself.levels = levels\nself.tmpshape = None",
"levels = self.levels\nexpanded_levels = levels[None, :]\nsamples = self.est.forward(x)\ntmp = samples * expanded_levels\nself.tmpshape = tmp.shape\nreturn tmp.sum(axis=-1)",
"levels ... | <|body_start_0|>
if isinstance(levels, int):
levels = np.arange(levels)
self.est = estimator
self.levels = levels
self.tmpshape = None
<|end_body_0|>
<|body_start_1|>
levels = self.levels
expanded_levels = levels[None, :]
samples = self.est.forward(x)... | An encoder that embds a continuous encoder, which encourages values to cluster at discrete states. | DiscreteEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiscreteEncoder:
"""An encoder that embds a continuous encoder, which encourages values to cluster at discrete states."""
def __init__(self, estimator, levels):
"""Create a new DiscreteEncoder. Parameters ---------- estimator : an initialized estimator for example GumbelSoftmax() lev... | stack_v2_sparse_classes_10k_train_002965 | 7,697 | permissive | [
{
"docstring": "Create a new DiscreteEncoder. Parameters ---------- estimator : an initialized estimator for example GumbelSoftmax() levels : int or numpy.ndarray if int, self-generates arange(levels) else, expected to be K discrete, non-overlapping integer states",
"name": "__init__",
"signature": "def... | 4 | stack_v2_sparse_classes_30k_train_005073 | Implement the Python class `DiscreteEncoder` described below.
Class description:
An encoder that embds a continuous encoder, which encourages values to cluster at discrete states.
Method signatures and docstrings:
- def __init__(self, estimator, levels): Create a new DiscreteEncoder. Parameters ---------- estimator :... | Implement the Python class `DiscreteEncoder` described below.
Class description:
An encoder that embds a continuous encoder, which encourages values to cluster at discrete states.
Method signatures and docstrings:
- def __init__(self, estimator, levels): Create a new DiscreteEncoder. Parameters ---------- estimator :... | af89c94d500a274eda664188ddb97fcae30c6ac5 | <|skeleton|>
class DiscreteEncoder:
"""An encoder that embds a continuous encoder, which encourages values to cluster at discrete states."""
def __init__(self, estimator, levels):
"""Create a new DiscreteEncoder. Parameters ---------- estimator : an initialized estimator for example GumbelSoftmax() lev... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DiscreteEncoder:
"""An encoder that embds a continuous encoder, which encourages values to cluster at discrete states."""
def __init__(self, estimator, levels):
"""Create a new DiscreteEncoder. Parameters ---------- estimator : an initialized estimator for example GumbelSoftmax() levels : int or ... | the_stack_v2_python_sparse | prysm/x/optym/activation.py | brandondube/prysm | train | 192 |
47e7b338024ef97cdc18c802c2a78541bc48b14e | [
"super().__init__()\nself.reduction = reduction\nself.axis = axis",
"if not isinstance(y_true, Tensor):\n y_true = y_true.class_id\nif not isinstance(y_pred, Tensor):\n y_pred = y_pred.class_id\npred_class = y_pred.argmax(dim=self.axis)\ntrue_class = y_true.long()\ncorrect_predictions = pred_class == true_c... | <|body_start_0|>
super().__init__()
self.reduction = reduction
self.axis = axis
<|end_body_0|>
<|body_start_1|>
if not isinstance(y_true, Tensor):
y_true = y_true.class_id
if not isinstance(y_pred, Tensor):
y_pred = y_pred.class_id
pred_class = y_... | SparseCategoricalAccuracy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SparseCategoricalAccuracy:
def __init__(self, model=None, reduction: str='mean', axis=-1):
"""Compute the sparse mean squared error. Sparse means that the targets are not one hot encoded. :param reduction: Specifies the reduction to apply to the output: `'none'` | `'mean'` | `'sum'`. `'n... | stack_v2_sparse_classes_10k_train_002966 | 4,640 | permissive | [
{
"docstring": "Compute the sparse mean squared error. Sparse means that the targets are not one hot encoded. :param reduction: Specifies the reduction to apply to the output: `'none'` | `'mean'` | `'sum'`. `'none'`: no reduction will be applied, `'mean'`: the sum of the output will be divided by the number of ... | 2 | stack_v2_sparse_classes_30k_train_004437 | Implement the Python class `SparseCategoricalAccuracy` described below.
Class description:
Implement the SparseCategoricalAccuracy class.
Method signatures and docstrings:
- def __init__(self, model=None, reduction: str='mean', axis=-1): Compute the sparse mean squared error. Sparse means that the targets are not one... | Implement the Python class `SparseCategoricalAccuracy` described below.
Class description:
Implement the SparseCategoricalAccuracy class.
Method signatures and docstrings:
- def __init__(self, model=None, reduction: str='mean', axis=-1): Compute the sparse mean squared error. Sparse means that the targets are not one... | 0c7fb170d62f193dbbb2018f7b8d42f713178bb8 | <|skeleton|>
class SparseCategoricalAccuracy:
def __init__(self, model=None, reduction: str='mean', axis=-1):
"""Compute the sparse mean squared error. Sparse means that the targets are not one hot encoded. :param reduction: Specifies the reduction to apply to the output: `'none'` | `'mean'` | `'sum'`. `'n... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SparseCategoricalAccuracy:
def __init__(self, model=None, reduction: str='mean', axis=-1):
"""Compute the sparse mean squared error. Sparse means that the targets are not one hot encoded. :param reduction: Specifies the reduction to apply to the output: `'none'` | `'mean'` | `'sum'`. `'none'`: no redu... | the_stack_v2_python_sparse | deeptech/training/losses/classification.py | penguinmenac3/deeptech | train | 1 | |
c858f3e2a1977317f395dfe0f1e4948d519aaa6b | [
"if x == 0:\n return x\nupper = x / 2 + 1\nlower = 1\nwhile upper - lower > 1:\n middle = int((upper + lower) / 2)\n if x > middle ** 2:\n lower = middle\n elif x < middle ** 2:\n upper = middle\n elif x == middle ** 2:\n return middle\nreturn lower",
"if x <= 1:\n return x\... | <|body_start_0|>
if x == 0:
return x
upper = x / 2 + 1
lower = 1
while upper - lower > 1:
middle = int((upper + lower) / 2)
if x > middle ** 2:
lower = middle
elif x < middle ** 2:
upper = middle
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mySqrt(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def mySqrt_float(self, x):
"""this method is useful for if we need to retun a more accurate float number type x: int rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_002967 | 1,038 | no_license | [
{
"docstring": ":type x: int :rtype: int",
"name": "mySqrt",
"signature": "def mySqrt(self, x)"
},
{
"docstring": "this method is useful for if we need to retun a more accurate float number type x: int rtype: float",
"name": "mySqrt_float",
"signature": "def mySqrt_float(self, x)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mySqrt(self, x): :type x: int :rtype: int
- def mySqrt_float(self, x): this method is useful for if we need to retun a more accurate float number type x: int rtype: float | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mySqrt(self, x): :type x: int :rtype: int
- def mySqrt_float(self, x): this method is useful for if we need to retun a more accurate float number type x: int rtype: float
<|... | 54d777e11b91c5debe49c1aef723234c66a5d2cc | <|skeleton|>
class Solution:
def mySqrt(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def mySqrt_float(self, x):
"""this method is useful for if we need to retun a more accurate float number type x: int rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def mySqrt(self, x):
""":type x: int :rtype: int"""
if x == 0:
return x
upper = x / 2 + 1
lower = 1
while upper - lower > 1:
middle = int((upper + lower) / 2)
if x > middle ** 2:
lower = middle
el... | the_stack_v2_python_sparse | leetcode_solution/math/#69.Sqrt.py | HsiangHung/Code-Challenges | train | 0 | |
0ec5394fe250feccaceb3daed9c66bfd6c188bde | [
"super(VDSMImportLog, self).parse_content(content)\nsplited_file_name = self.file_name.split('-')\nself.vm_uuid = '-'.join(splited_file_name[1:-1])\n_datetime = splited_file_name[-1].replace('.log', '')\ntry:\n self.file_datetime = datetime.strptime(_datetime, '%Y%m%dT%H%M%S')\nexcept:\n self.file_datetime = ... | <|body_start_0|>
super(VDSMImportLog, self).parse_content(content)
splited_file_name = self.file_name.split('-')
self.vm_uuid = '-'.join(splited_file_name[1:-1])
_datetime = splited_file_name[-1].replace('.log', '')
try:
self.file_datetime = datetime.strptime(_datetim... | Parser for the log file detailing virtual machine imports. Sample log file:: [ 0.2] preparing for copy [ 0.2] Copying disk 1/1 to /rhev/data-center/958ca292-9126/f524d2ba-155a/images/502f5598-335d-/d4b140c8-9cd5 [ 0.0] >>> source, dest, and storage-type have different lengths Example: >>> log = vdsm_import_logs.get('pr... | VDSMImportLog | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VDSMImportLog:
"""Parser for the log file detailing virtual machine imports. Sample log file:: [ 0.2] preparing for copy [ 0.2] Copying disk 1/1 to /rhev/data-center/958ca292-9126/f524d2ba-155a/images/502f5598-335d-/d4b140c8-9cd5 [ 0.0] >>> source, dest, and storage-type have different lengths Ex... | stack_v2_sparse_classes_10k_train_002968 | 11,713 | permissive | [
{
"docstring": "Parse ``import-@UUID-@datetime.log`` log file.",
"name": "parse_content",
"signature": "def parse_content(self, content)"
},
{
"docstring": "Find all the (available) logs that are after the given time stamp. If `s` is not supplied, then all lines are used. Otherwise, only the lin... | 2 | null | Implement the Python class `VDSMImportLog` described below.
Class description:
Parser for the log file detailing virtual machine imports. Sample log file:: [ 0.2] preparing for copy [ 0.2] Copying disk 1/1 to /rhev/data-center/958ca292-9126/f524d2ba-155a/images/502f5598-335d-/d4b140c8-9cd5 [ 0.0] >>> source, dest, and... | Implement the Python class `VDSMImportLog` described below.
Class description:
Parser for the log file detailing virtual machine imports. Sample log file:: [ 0.2] preparing for copy [ 0.2] Copying disk 1/1 to /rhev/data-center/958ca292-9126/f524d2ba-155a/images/502f5598-335d-/d4b140c8-9cd5 [ 0.0] >>> source, dest, and... | b0ea07fc3f4dd8801b505fe70e9b36e628152c4a | <|skeleton|>
class VDSMImportLog:
"""Parser for the log file detailing virtual machine imports. Sample log file:: [ 0.2] preparing for copy [ 0.2] Copying disk 1/1 to /rhev/data-center/958ca292-9126/f524d2ba-155a/images/502f5598-335d-/d4b140c8-9cd5 [ 0.0] >>> source, dest, and storage-type have different lengths Ex... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VDSMImportLog:
"""Parser for the log file detailing virtual machine imports. Sample log file:: [ 0.2] preparing for copy [ 0.2] Copying disk 1/1 to /rhev/data-center/958ca292-9126/f524d2ba-155a/images/502f5598-335d-/d4b140c8-9cd5 [ 0.0] >>> source, dest, and storage-type have different lengths Example: >>> lo... | the_stack_v2_python_sparse | insights/parsers/vdsm_log.py | RedHatInsights/insights-core | train | 144 |
5e6fd7af273e4b69cdadb9c3324341d542123d57 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Authentication()",
"from .authentication_method import AuthenticationMethod\nfrom .email_authentication_method import EmailAuthenticationMethod\nfrom .entity import Entity\nfrom .fido2_authentication_method import Fido2AuthenticationMe... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Authentication()
<|end_body_0|>
<|body_start_1|>
from .authentication_method import AuthenticationMethod
from .email_authentication_method import EmailAuthenticationMethod
from .... | Authentication | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Authentication:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Authentication:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Retur... | stack_v2_sparse_classes_10k_train_002969 | 8,427 | 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: Authentication",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_valu... | 3 | null | Implement the Python class `Authentication` described below.
Class description:
Implement the Authentication class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Authentication: Creates a new instance of the appropriate class based on discriminator va... | Implement the Python class `Authentication` described below.
Class description:
Implement the Authentication class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Authentication: Creates a new instance of the appropriate class based on discriminator va... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Authentication:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Authentication:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Retur... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Authentication:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Authentication:
"""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: Authentica... | the_stack_v2_python_sparse | msgraph/generated/models/authentication.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
3f3e1afad41a4469c7e251f93567751df01defd2 | [
"self.carange = carange\nself.crrange = crrange\nself.seed = seed\nself.ma = len(carange[0]) + 1 if carange is not None else None\nself.mr = len(crrange[0]) + 1 if crrange is not None else None\nif seed is not None:\n ts.setseed(seed)",
"if seed is not None:\n ts.setseed(seed)\nif self.ma is not None:\n ... | <|body_start_0|>
self.carange = carange
self.crrange = crrange
self.seed = seed
self.ma = len(carange[0]) + 1 if carange is not None else None
self.mr = len(crrange[0]) + 1 if crrange is not None else None
if seed is not None:
ts.setseed(seed)
<|end_body_0|>
... | PolyPhaseErrorGenerator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PolyPhaseErrorGenerator:
def __init__(self, carange=None, crrange=None, seed=None):
"""Polynominal phase error generator. Args: carange (None or tuple or list, optional): List of coefficients range of phase error in azimuth direction. crrange (None or tuple or list, optional): List of co... | stack_v2_sparse_classes_10k_train_002970 | 8,808 | permissive | [
{
"docstring": "Polynominal phase error generator. Args: carange (None or tuple or list, optional): List of coefficients range of phase error in azimuth direction. crrange (None or tuple or list, optional): List of coefficients range of phase error in range direction. seed (None or int, optional): The random se... | 2 | stack_v2_sparse_classes_30k_train_003322 | Implement the Python class `PolyPhaseErrorGenerator` described below.
Class description:
Implement the PolyPhaseErrorGenerator class.
Method signatures and docstrings:
- def __init__(self, carange=None, crrange=None, seed=None): Polynominal phase error generator. Args: carange (None or tuple or list, optional): List ... | Implement the Python class `PolyPhaseErrorGenerator` described below.
Class description:
Implement the PolyPhaseErrorGenerator class.
Method signatures and docstrings:
- def __init__(self, carange=None, crrange=None, seed=None): Polynominal phase error generator. Args: carange (None or tuple or list, optional): List ... | 05a46610d68bc884743a483565279f361ade5384 | <|skeleton|>
class PolyPhaseErrorGenerator:
def __init__(self, carange=None, crrange=None, seed=None):
"""Polynominal phase error generator. Args: carange (None or tuple or list, optional): List of coefficients range of phase error in azimuth direction. crrange (None or tuple or list, optional): List of co... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PolyPhaseErrorGenerator:
def __init__(self, carange=None, crrange=None, seed=None):
"""Polynominal phase error generator. Args: carange (None or tuple or list, optional): List of coefficients range of phase error in azimuth direction. crrange (None or tuple or list, optional): List of coefficients ran... | the_stack_v2_python_sparse | torchsar/autofocus/phase_error_model.py | wrccrwx/torchsar | train | 0 | |
e125e655a8febcb816ca069eaaa3bbd2076ae4e7 | [
"super(Encoder, self).__init__()\nK = sampling_rate // 8000\nself.spectrogram = Spectrogram(n_fft=1024 * K, hop=256 * K, mels=num_mels, sr=sampling_rate)\nself.filters = nn.ModuleList([])\nfilter_width = num_mels\nfor l in range(layers):\n n = N // 4\n k = kernel_size * 2 ** l\n self.filters.append(nn.Conv... | <|body_start_0|>
super(Encoder, self).__init__()
K = sampling_rate // 8000
self.spectrogram = Spectrogram(n_fft=1024 * K, hop=256 * K, mels=num_mels, sr=sampling_rate)
self.filters = nn.ModuleList([])
filter_width = num_mels
for l in range(layers):
n = N // 4
... | Encodes the waveforms into the latent representation | Encoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
"""Encodes the waveforms into the latent representation"""
def __init__(self, N, kernel_size, stride, layers, num_mels, sampling_rate):
"""Arguments: N {int} -- Dimension of the output latent representation kernel_size {int} -- Base convolutional kernel size stride {int} -- ... | stack_v2_sparse_classes_10k_train_002971 | 37,269 | no_license | [
{
"docstring": "Arguments: N {int} -- Dimension of the output latent representation kernel_size {int} -- Base convolutional kernel size stride {int} -- Stride of the convolutions layers {int} -- Number of parallel convolutions with different kernel sizes num_mels {int} -- Number of mel filters in the mel spectr... | 2 | stack_v2_sparse_classes_30k_train_001283 | Implement the Python class `Encoder` described below.
Class description:
Encodes the waveforms into the latent representation
Method signatures and docstrings:
- def __init__(self, N, kernel_size, stride, layers, num_mels, sampling_rate): Arguments: N {int} -- Dimension of the output latent representation kernel_size... | Implement the Python class `Encoder` described below.
Class description:
Encodes the waveforms into the latent representation
Method signatures and docstrings:
- def __init__(self, N, kernel_size, stride, layers, num_mels, sampling_rate): Arguments: N {int} -- Dimension of the output latent representation kernel_size... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class Encoder:
"""Encodes the waveforms into the latent representation"""
def __init__(self, N, kernel_size, stride, layers, num_mels, sampling_rate):
"""Arguments: N {int} -- Dimension of the output latent representation kernel_size {int} -- Base convolutional kernel size stride {int} -- ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Encoder:
"""Encodes the waveforms into the latent representation"""
def __init__(self, N, kernel_size, stride, layers, num_mels, sampling_rate):
"""Arguments: N {int} -- Dimension of the output latent representation kernel_size {int} -- Base convolutional kernel size stride {int} -- Stride of the... | the_stack_v2_python_sparse | generated/test_pfnet_research_meta_tasnet.py | jansel/pytorch-jit-paritybench | train | 35 |
04295c02a91de6178cb7dbea7dd23c3ae98b3991 | [
"if not root:\n return []\nqueue = [root]\nres = []\nwhile queue:\n child = []\n node = []\n for q in queue:\n if q:\n child.append(q.val)\n if q.left:\n node.append(q.left)\n if q.right:\n node.append(q.right)\n queue = node\n ... | <|body_start_0|>
if not root:
return []
queue = [root]
res = []
while queue:
child = []
node = []
for q in queue:
if q:
child.append(q.val)
if q.left:
node.appe... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrderBfs(self, root: TreeNode) -> List[List[int]]:
"""bfs"""
<|body_0|>
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""dfs :param root: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
... | stack_v2_sparse_classes_10k_train_002972 | 1,746 | no_license | [
{
"docstring": "bfs",
"name": "levelOrderBfs",
"signature": "def levelOrderBfs(self, root: TreeNode) -> List[List[int]]"
},
{
"docstring": "dfs :param root: :return:",
"name": "levelOrder",
"signature": "def levelOrder(self, root: TreeNode) -> List[List[int]]"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrderBfs(self, root: TreeNode) -> List[List[int]]: bfs
- def levelOrder(self, root: TreeNode) -> List[List[int]]: dfs :param root: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrderBfs(self, root: TreeNode) -> List[List[int]]: bfs
- def levelOrder(self, root: TreeNode) -> List[List[int]]: dfs :param root: :return:
<|skeleton|>
class Solution:... | 1a1abf5aabdd23755769efaa6c33579bc5b0917b | <|skeleton|>
class Solution:
def levelOrderBfs(self, root: TreeNode) -> List[List[int]]:
"""bfs"""
<|body_0|>
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""dfs :param root: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrderBfs(self, root: TreeNode) -> List[List[int]]:
"""bfs"""
if not root:
return []
queue = [root]
res = []
while queue:
child = []
node = []
for q in queue:
if q:
chi... | the_stack_v2_python_sparse | Week_03/G20190343020041/LeetCode_102_0041.py | algorithm005-class02/algorithm005-class02 | train | 45 | |
6926353fdae3345fd9c58cba4e88b821d6076eee | [
"def dfs(root):\n if not root:\n res.append('None')\n return\n res.append(str(root.val))\n dfs(root.left)\n dfs(root.right)\nres = []\ndfs(root)\nreturn ','.join(res)",
"def recursiveDeserialize(stringList):\n if stringList[0] == 'None':\n stringList.pop(0)\n return None... | <|body_start_0|>
def dfs(root):
if not root:
res.append('None')
return
res.append(str(root.val))
dfs(root.left)
dfs(root.right)
res = []
dfs(root)
return ','.join(res)
<|end_body_0|>
<|body_start_1|>
... | 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_002973 | 2,513 | 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_004850 | 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:... | d4d138716db9bfa236c87c25ae582a76a14faa28 | <|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"""
def dfs(root):
if not root:
res.append('None')
return
res.append(str(root.val))
dfs(root.left)
dfs(root.ri... | the_stack_v2_python_sparse | SerializeAndDeserializeBinaryTree.py | aaronfox/LeetCode-Work | train | 0 | |
6b9f314578c330d2d5bb937481033b46cec20ff6 | [
"ret = []\nif not root:\n return None\nQ = Queue()\nQ.put(root)\nwhile not Q.empty():\n count = Q.qsize()\n tmp = []\n for i in range(count):\n nd = Q.get()\n tmp.append(nd.val)\n if nd.left:\n Q.put(nd.left)\n if nd.right:\n Q.put(nd.right)\n ret.app... | <|body_start_0|>
ret = []
if not root:
return None
Q = Queue()
Q.put(root)
while not Q.empty():
count = Q.qsize()
tmp = []
for i in range(count):
nd = Q.get()
tmp.append(nd.val)
if nd.... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def averageOfLevels1(self, root):
""":type root: TreeNode :rtype: List[float]"""
<|body_0|>
def averageOfLevels2(self, root):
""":type root: TreeNode :rtype: List[float]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = []
if n... | stack_v2_sparse_classes_10k_train_002974 | 1,720 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[float]",
"name": "averageOfLevels1",
"signature": "def averageOfLevels1(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[float]",
"name": "averageOfLevels2",
"signature": "def averageOfLevels2(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def averageOfLevels1(self, root): :type root: TreeNode :rtype: List[float]
- def averageOfLevels2(self, root): :type root: TreeNode :rtype: List[float] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def averageOfLevels1(self, root): :type root: TreeNode :rtype: List[float]
- def averageOfLevels2(self, root): :type root: TreeNode :rtype: List[float]
<|skeleton|>
class Soluti... | d3e8669f932fc2e22711e8b7590d3365d020e189 | <|skeleton|>
class Solution:
def averageOfLevels1(self, root):
""":type root: TreeNode :rtype: List[float]"""
<|body_0|>
def averageOfLevels2(self, root):
""":type root: TreeNode :rtype: List[float]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def averageOfLevels1(self, root):
""":type root: TreeNode :rtype: List[float]"""
ret = []
if not root:
return None
Q = Queue()
Q.put(root)
while not Q.empty():
count = Q.qsize()
tmp = []
for i in range(co... | the_stack_v2_python_sparse | leetcode/637.py | liuweilin17/algorithm | train | 3 | |
43bc742e88650eb5c8cbe3c29336985cf2a8c8c7 | [
"super(KNNDist, self).__init__()\nself.k = k\nself.alpha = alpha",
"B, K = pc.shape[:2]\npc = pc.transpose(2, 1)\ninner = -2.0 * torch.matmul(pc.transpose(2, 1), pc)\nxx = torch.sum(pc ** 2, dim=1, keepdim=True)\ndist = xx + inner + xx.transpose(2, 1)\nassert dist.min().item() >= -1e-06\nneg_value, _ = (-dist).to... | <|body_start_0|>
super(KNNDist, self).__init__()
self.k = k
self.alpha = alpha
<|end_body_0|>
<|body_start_1|>
B, K = pc.shape[:2]
pc = pc.transpose(2, 1)
inner = -2.0 * torch.matmul(pc.transpose(2, 1), pc)
xx = torch.sum(pc ** 2, dim=1, keepdim=True)
dis... | KNNDist | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KNNDist:
def __init__(self, k=5, alpha=1.05):
"""Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): threshold = mean + alpha * std. Defaults to 1.05."""
<|body_0|>
def forward(self, pc, wei... | stack_v2_sparse_classes_10k_train_002975 | 11,583 | permissive | [
{
"docstring": "Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): threshold = mean + alpha * std. Defaults to 1.05.",
"name": "__init__",
"signature": "def __init__(self, k=5, alpha=1.05)"
},
{
"docstring": "K... | 2 | stack_v2_sparse_classes_30k_val_000042 | Implement the Python class `KNNDist` described below.
Class description:
Implement the KNNDist class.
Method signatures and docstrings:
- def __init__(self, k=5, alpha=1.05): Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): thresh... | Implement the Python class `KNNDist` described below.
Class description:
Implement the KNNDist class.
Method signatures and docstrings:
- def __init__(self, k=5, alpha=1.05): Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): thresh... | 4e2462b66fa1eac90cfbf61fa0dc635d223fdf2f | <|skeleton|>
class KNNDist:
def __init__(self, k=5, alpha=1.05):
"""Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): threshold = mean + alpha * std. Defaults to 1.05."""
<|body_0|>
def forward(self, pc, wei... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KNNDist:
def __init__(self, k=5, alpha=1.05):
"""Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): threshold = mean + alpha * std. Defaults to 1.05."""
super(KNNDist, self).__init__()
self.k = k
... | the_stack_v2_python_sparse | baselines/attack/util/dist_utils.py | code-roamer/IF-Defense | train | 0 | |
4b612ccddcca123d374e51540159ac2215f18f3c | [
"current_identity = import_user()\ncontainers = []\nfor c in lxc.list_containers():\n container = Container.query.filter_by(name=c).first()\n if container.id in current_identity.containers or current_identity.admin:\n infos = lwp.ct_infos(c)\n container_json = container.__jsonapi__()\n co... | <|body_start_0|>
current_identity = import_user()
containers = []
for c in lxc.list_containers():
container = Container.query.filter_by(name=c).first()
if container.id in current_identity.containers or current_identity.admin:
infos = lwp.ct_infos(c)
... | ContainersList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContainersList:
def get(self):
"""Get containers list"""
<|body_0|>
def post(self):
"""Create container"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
current_identity = import_user()
containers = []
for c in lxc.list_containers():
... | stack_v2_sparse_classes_10k_train_002976 | 46,738 | permissive | [
{
"docstring": "Get containers list",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Create container",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003136 | Implement the Python class `ContainersList` described below.
Class description:
Implement the ContainersList class.
Method signatures and docstrings:
- def get(self): Get containers list
- def post(self): Create container | Implement the Python class `ContainersList` described below.
Class description:
Implement the ContainersList class.
Method signatures and docstrings:
- def get(self): Get containers list
- def post(self): Create container
<|skeleton|>
class ContainersList:
def get(self):
"""Get containers list"""
... | 3439a2dd0bd527c5d604801fec3a5aac904a72e2 | <|skeleton|>
class ContainersList:
def get(self):
"""Get containers list"""
<|body_0|>
def post(self):
"""Create container"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ContainersList:
def get(self):
"""Get containers list"""
current_identity = import_user()
containers = []
for c in lxc.list_containers():
container = Container.query.filter_by(name=c).first()
if container.id in current_identity.containers or current_iden... | the_stack_v2_python_sparse | app/views.py | taidos/lxc-rest | train | 0 | |
5b9ce0393b608fe830a7ac00f32ded5d74f34480 | [
"node = XMLHelper.build_node_from_string(ResourceInfoBuilder.RESOURCE_TEMPLATE)\nnode.set('Name', resource_info.name)\nnode.set('ResourceFamilyName', resource_info.family_name)\nnode.set('ResourceModelName', resource_info.model_name)\nnode.set('SerialNumber', resource_info.serial_number)\nnode.set('Address', resour... | <|body_start_0|>
node = XMLHelper.build_node_from_string(ResourceInfoBuilder.RESOURCE_TEMPLATE)
node.set('Name', resource_info.name)
node.set('ResourceFamilyName', resource_info.family_name)
node.set('ResourceModelName', resource_info.model_name)
node.set('SerialNumber', resource... | Build resource info node. | ResourceInfoBuilder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResourceInfoBuilder:
"""Build resource info node."""
def _build_resource_node(resource_info: ResourceInfo) -> Element:
"""Build resource xml node."""
<|body_0|>
def _build_attribute_node(attribute: Attribute) -> Element:
"""Build attribute node. :type attribute: ... | stack_v2_sparse_classes_10k_train_002977 | 3,487 | no_license | [
{
"docstring": "Build resource xml node.",
"name": "_build_resource_node",
"signature": "def _build_resource_node(resource_info: ResourceInfo) -> Element"
},
{
"docstring": "Build attribute node. :type attribute: cloudshell.layer_one.core.response.resource_info.entities.base.Attribute # noqa: E5... | 5 | stack_v2_sparse_classes_30k_train_003529 | Implement the Python class `ResourceInfoBuilder` described below.
Class description:
Build resource info node.
Method signatures and docstrings:
- def _build_resource_node(resource_info: ResourceInfo) -> Element: Build resource xml node.
- def _build_attribute_node(attribute: Attribute) -> Element: Build attribute no... | Implement the Python class `ResourceInfoBuilder` described below.
Class description:
Build resource info node.
Method signatures and docstrings:
- def _build_resource_node(resource_info: ResourceInfo) -> Element: Build resource xml node.
- def _build_attribute_node(attribute: Attribute) -> Element: Build attribute no... | 82562665834908294136bbe8e7bc46da1a21b8e2 | <|skeleton|>
class ResourceInfoBuilder:
"""Build resource info node."""
def _build_resource_node(resource_info: ResourceInfo) -> Element:
"""Build resource xml node."""
<|body_0|>
def _build_attribute_node(attribute: Attribute) -> Element:
"""Build attribute node. :type attribute: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ResourceInfoBuilder:
"""Build resource info node."""
def _build_resource_node(resource_info: ResourceInfo) -> Element:
"""Build resource xml node."""
node = XMLHelper.build_node_from_string(ResourceInfoBuilder.RESOURCE_TEMPLATE)
node.set('Name', resource_info.name)
node.se... | the_stack_v2_python_sparse | cloudshell/layer_one/core/response/resource_info/resource_info_builder.py | QualiSystems/cloudshell-L1-networking-core | train | 1 |
fb8950ec16af1f232f6be7b3262e0b8da5413090 | [
"super(Application, self).__init__(master)\nself.grid()\nself.create_widgets()",
"Label(self, text='Укажите ваш любимый жанр кино.').grid(row=0, column=0, sticky=W)\nLabel(self, text='Выберите ровно 1:').grid(row=1, column=0, sticky=W)\nself.favorite = StringVar()\nself.favorite.set(None)\nRadiobutton(self, text=... | <|body_start_0|>
super(Application, self).__init__(master)
self.grid()
self.create_widgets()
<|end_body_0|>
<|body_start_1|>
Label(self, text='Укажите ваш любимый жанр кино.').grid(row=0, column=0, sticky=W)
Label(self, text='Выберите ровно 1:').grid(row=1, column=0, sticky=W)
... | GUI-Приложение, позволяющее выбрать только один жанр | Application | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Application:
"""GUI-Приложение, позволяющее выбрать только один жанр"""
def __init__(self, master):
"""Инициализируем рамку"""
<|body_0|>
def create_widgets(self):
"""Создает элементы, с помощью которых пользователь будет выбирать"""
<|body_1|>
def u... | stack_v2_sparse_classes_10k_train_002978 | 2,726 | no_license | [
{
"docstring": "Инициализируем рамку",
"name": "__init__",
"signature": "def __init__(self, master)"
},
{
"docstring": "Создает элементы, с помощью которых пользователь будет выбирать",
"name": "create_widgets",
"signature": "def create_widgets(self)"
},
{
"docstring": "Обновляет... | 3 | stack_v2_sparse_classes_30k_train_002668 | Implement the Python class `Application` described below.
Class description:
GUI-Приложение, позволяющее выбрать только один жанр
Method signatures and docstrings:
- def __init__(self, master): Инициализируем рамку
- def create_widgets(self): Создает элементы, с помощью которых пользователь будет выбирать
- def updat... | Implement the Python class `Application` described below.
Class description:
GUI-Приложение, позволяющее выбрать только один жанр
Method signatures and docstrings:
- def __init__(self, master): Инициализируем рамку
- def create_widgets(self): Создает элементы, с помощью которых пользователь будет выбирать
- def updat... | 5c3342fca0ad705a7719770894ee2480b62bf593 | <|skeleton|>
class Application:
"""GUI-Приложение, позволяющее выбрать только один жанр"""
def __init__(self, master):
"""Инициализируем рамку"""
<|body_0|>
def create_widgets(self):
"""Создает элементы, с помощью которых пользователь будет выбирать"""
<|body_1|>
def u... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Application:
"""GUI-Приложение, позволяющее выбрать только один жанр"""
def __init__(self, master):
"""Инициализируем рамку"""
super(Application, self).__init__(master)
self.grid()
self.create_widgets()
def create_widgets(self):
"""Создает элементы, с помощью ... | the_stack_v2_python_sparse | Chapter_10/movie_chooser2.py | BlackJin1/FirstProgramm | train | 0 |
8d9be2ff8b8ac9e088adef79f4e58bfeccb68d13 | [
"context = {'measurements_form': forms.DatasetTypeMeasurementsForm(), 'flags_definition_form': forms.DatasetTypeFlagsDefinitionForm(), 'dataset_type_id': dataset_type_id}\ndataset_type = models.DatasetType.objects.using('agdc').get(id=dataset_type_id)\ncontext.update(utils.forms_from_definition(dataset_type.definit... | <|body_start_0|>
context = {'measurements_form': forms.DatasetTypeMeasurementsForm(), 'flags_definition_form': forms.DatasetTypeFlagsDefinitionForm(), 'dataset_type_id': dataset_type_id}
dataset_type = models.DatasetType.objects.using('agdc').get(id=dataset_type_id)
context.update(utils.forms_fr... | Main end piont for viewing or adding a dataset type | DatasetTypeView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatasetTypeView:
"""Main end piont for viewing or adding a dataset type"""
def get(self, request, dataset_type_id=None):
"""View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, DatasetTypeFlagsDefinitionForm dataset_type_id: id/pk of the d... | stack_v2_sparse_classes_10k_train_002979 | 10,227 | permissive | [
{
"docstring": "View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, DatasetTypeFlagsDefinitionForm dataset_type_id: id/pk of the dataset type",
"name": "get",
"signature": "def get(self, request, dataset_type_id=None)"
},
{
"docstring": "Add a datase... | 2 | stack_v2_sparse_classes_30k_train_003452 | Implement the Python class `DatasetTypeView` described below.
Class description:
Main end piont for viewing or adding a dataset type
Method signatures and docstrings:
- def get(self, request, dataset_type_id=None): View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, Datas... | Implement the Python class `DatasetTypeView` described below.
Class description:
Main end piont for viewing or adding a dataset type
Method signatures and docstrings:
- def get(self, request, dataset_type_id=None): View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, Datas... | ef50e918df89313f130d735e7cb7c0a069da410e | <|skeleton|>
class DatasetTypeView:
"""Main end piont for viewing or adding a dataset type"""
def get(self, request, dataset_type_id=None):
"""View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, DatasetTypeFlagsDefinitionForm dataset_type_id: id/pk of the d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DatasetTypeView:
"""Main end piont for viewing or adding a dataset type"""
def get(self, request, dataset_type_id=None):
"""View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, DatasetTypeFlagsDefinitionForm dataset_type_id: id/pk of the dataset type""... | the_stack_v2_python_sparse | apps/data_cube_manager/views/dataset_type.py | ceos-seo/data_cube_ui | train | 47 |
7007de2fcf60e7f6c4ce3ba3aa18aa104a4dd5ed | [
"from numpy import array, dot, arccos, pi\nx = self.positionRelativeToSample(element)\nx = array(x)\nfrom . import units\nm = units.length.meter\ntry:\n x + m\n x /= m\nexcept:\n pass\nlx = vlen(x)\nbeam = self.request_coordinate_system().neutronBeamDirection\nlbeam = vlen(array(beam))\ncost = dot(x, beam)... | <|body_start_0|>
from numpy import array, dot, arccos, pi
x = self.positionRelativeToSample(element)
x = array(x)
from . import units
m = units.length.meter
try:
x + m
x /= m
except:
pass
lx = vlen(x)
beam = self... | A geometer that is most useful for inelastic direct-geometry chopper spectrometer. | ARCSGeometer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ARCSGeometer:
"""A geometer that is most useful for inelastic direct-geometry chopper spectrometer."""
def scatteringAngle(self, element):
"""scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle of the specified element in degrees. Inputs: element: Th... | stack_v2_sparse_classes_10k_train_002980 | 4,790 | no_license | [
{
"docstring": "scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle of the specified element in degrees. Inputs: element: The element or the element signature Output: scattering angle, in radian Exceptions: KeyError Notes: scattering angle means angle from moderator to sample t... | 2 | stack_v2_sparse_classes_30k_train_006830 | Implement the Python class `ARCSGeometer` described below.
Class description:
A geometer that is most useful for inelastic direct-geometry chopper spectrometer.
Method signatures and docstrings:
- def scatteringAngle(self, element): scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle... | Implement the Python class `ARCSGeometer` described below.
Class description:
A geometer that is most useful for inelastic direct-geometry chopper spectrometer.
Method signatures and docstrings:
- def scatteringAngle(self, element): scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle... | 7d6fb88e7ec8245c488ab7988a8518de57dd73df | <|skeleton|>
class ARCSGeometer:
"""A geometer that is most useful for inelastic direct-geometry chopper spectrometer."""
def scatteringAngle(self, element):
"""scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle of the specified element in degrees. Inputs: element: Th... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ARCSGeometer:
"""A geometer that is most useful for inelastic direct-geometry chopper spectrometer."""
def scatteringAngle(self, element):
"""scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle of the specified element in degrees. Inputs: element: The element or ... | the_stack_v2_python_sparse | instrument/geometers/ARCSGeometer.py | danse-inelastic/instrument | train | 0 |
8a811a0ece610f3c3f50cf6a572fa198a6b2a4be | [
"if sk:\n self.n = sk.n\n self.h = sk.h\nelif n and h:\n self.n = n\n self.h = h\nelse:\n raise Exception('Public Key construction failed: insufficient/wrong arguments')\nself.signature_bound = Params[self.n]['sig_bound']\nself.sig_bytelen = Params[self.n]['sig_bytelen']",
"rep = 'Public for n = {n... | <|body_start_0|>
if sk:
self.n = sk.n
self.h = sk.h
elif n and h:
self.n = n
self.h = h
else:
raise Exception('Public Key construction failed: insufficient/wrong arguments')
self.signature_bound = Params[self.n]['sig_bound']
... | This class contains methods for performing public key operations in Falcon. | PublicKey | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublicKey:
"""This class contains methods for performing public key operations in Falcon."""
def __init__(self, sk=None, n=None, h=None):
"""Initialize a public key."""
<|body_0|>
def __repr__(self):
"""Print the object in readable form."""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_002981 | 15,043 | permissive | [
{
"docstring": "Initialize a public key.",
"name": "__init__",
"signature": "def __init__(self, sk=None, n=None, h=None)"
},
{
"docstring": "Print the object in readable form.",
"name": "__repr__",
"signature": "def __repr__(self)"
},
{
"docstring": "Hash a message to a point in ... | 4 | stack_v2_sparse_classes_30k_train_003360 | Implement the Python class `PublicKey` described below.
Class description:
This class contains methods for performing public key operations in Falcon.
Method signatures and docstrings:
- def __init__(self, sk=None, n=None, h=None): Initialize a public key.
- def __repr__(self): Print the object in readable form.
- de... | Implement the Python class `PublicKey` described below.
Class description:
This class contains methods for performing public key operations in Falcon.
Method signatures and docstrings:
- def __init__(self, sk=None, n=None, h=None): Initialize a public key.
- def __repr__(self): Print the object in readable form.
- de... | 1480c1e71b624a147dc0a18aa043f1101435ba85 | <|skeleton|>
class PublicKey:
"""This class contains methods for performing public key operations in Falcon."""
def __init__(self, sk=None, n=None, h=None):
"""Initialize a public key."""
<|body_0|>
def __repr__(self):
"""Print the object in readable form."""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PublicKey:
"""This class contains methods for performing public key operations in Falcon."""
def __init__(self, sk=None, n=None, h=None):
"""Initialize a public key."""
if sk:
self.n = sk.n
self.h = sk.h
elif n and h:
self.n = n
self... | the_stack_v2_python_sparse | falcon/falcon.py | samuelgoh1525/falcon-blockchain | train | 4 |
a6969c4bb9254320d5b80320ce10af94b3d87767 | [
"self.choice_enum = choice_enum\nkwargs.update({'required': kwargs.get('required', False), 'allow_null': kwargs.get('allow_null', True), 'help_text': f'String value of the enum.'})\nsuper().__init__(*args, **kwargs)",
"if isinstance(data, int):\n try:\n self.choice_enum(data)\n except ValueError:\n ... | <|body_start_0|>
self.choice_enum = choice_enum
kwargs.update({'required': kwargs.get('required', False), 'allow_null': kwargs.get('allow_null', True), 'help_text': f'String value of the enum.'})
super().__init__(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
if isinstance(data, int):... | DictField to deal with ChoiceEnums with structure below: { "name": "FOO_BAR" # variable name "value": "foo and bar" # human readable value } | ChoiceEnumField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChoiceEnumField:
"""DictField to deal with ChoiceEnums with structure below: { "name": "FOO_BAR" # variable name "value": "foo and bar" # human readable value }"""
def __init__(self, choice_enum: Type[_Enum], *args, **kwargs) -> None:
"""Regular initializing :param choice_enum: Choic... | stack_v2_sparse_classes_10k_train_002982 | 1,985 | no_license | [
{
"docstring": "Regular initializing :param choice_enum: ChoiceEnum to work with. :param only_value: used for representing value only.",
"name": "__init__",
"signature": "def __init__(self, choice_enum: Type[_Enum], *args, **kwargs) -> None"
},
{
"docstring": "Convert raw value into enum.",
... | 3 | stack_v2_sparse_classes_30k_train_001749 | Implement the Python class `ChoiceEnumField` described below.
Class description:
DictField to deal with ChoiceEnums with structure below: { "name": "FOO_BAR" # variable name "value": "foo and bar" # human readable value }
Method signatures and docstrings:
- def __init__(self, choice_enum: Type[_Enum], *args, **kwargs... | Implement the Python class `ChoiceEnumField` described below.
Class description:
DictField to deal with ChoiceEnums with structure below: { "name": "FOO_BAR" # variable name "value": "foo and bar" # human readable value }
Method signatures and docstrings:
- def __init__(self, choice_enum: Type[_Enum], *args, **kwargs... | fa794d08a3892f45e9e69fd226b53fb0bfa75145 | <|skeleton|>
class ChoiceEnumField:
"""DictField to deal with ChoiceEnums with structure below: { "name": "FOO_BAR" # variable name "value": "foo and bar" # human readable value }"""
def __init__(self, choice_enum: Type[_Enum], *args, **kwargs) -> None:
"""Regular initializing :param choice_enum: Choic... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ChoiceEnumField:
"""DictField to deal with ChoiceEnums with structure below: { "name": "FOO_BAR" # variable name "value": "foo and bar" # human readable value }"""
def __init__(self, choice_enum: Type[_Enum], *args, **kwargs) -> None:
"""Regular initializing :param choice_enum: ChoiceEnum to work... | the_stack_v2_python_sparse | api/v1/serializer_fields.py | NitinSatpal/mybill-server | train | 0 |
d5efbeedc0121decab2eca5964be7d7b33df4197 | [
"super().__init__()\nself.autoscaleX = utils.AutoscaleState.OFF\nself.minimumX = 0\nself.maximumX = 100\nself.pixelRangeAdditionX = 25\nself.autoscaleY = utils.AutoscaleState.OFF\nself.minimumY = 0\nself.maximumY = 100\nself.pixelRangeAdditionY = 25\nself.numHistogramBins = 40",
"self.autoscaleX = getattr(utils.A... | <|body_start_0|>
super().__init__()
self.autoscaleX = utils.AutoscaleState.OFF
self.minimumX = 0
self.maximumX = 100
self.pixelRangeAdditionX = 25
self.autoscaleY = utils.AutoscaleState.OFF
self.minimumY = 0
self.maximumY = 100
self.pixelRangeAddit... | Class for handling the configuration of the centroid plots (1D line, scatter and 1D histogram) Attributes ---------- autoscaleX : `utils.AutoscaleState` Set autoscaling on the x component 1D centroid line plot. autoscaleY : `utils.AutoscaleState` Set autoscaling on the y component 1D centroid line plot. maximumX : int ... | CentroidPlotConfig | [
"Python-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CentroidPlotConfig:
"""Class for handling the configuration of the centroid plots (1D line, scatter and 1D histogram) Attributes ---------- autoscaleX : `utils.AutoscaleState` Set autoscaling on the x component 1D centroid line plot. autoscaleY : `utils.AutoscaleState` Set autoscaling on the y co... | stack_v2_sparse_classes_10k_train_002983 | 4,267 | permissive | [
{
"docstring": "Initialize the class.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Translate config to class attributes. Parameters ---------- config : dict The configuration to translate.",
"name": "fromDict",
"signature": "def fromDict(self, config)"
},
... | 3 | stack_v2_sparse_classes_30k_train_004714 | Implement the Python class `CentroidPlotConfig` described below.
Class description:
Class for handling the configuration of the centroid plots (1D line, scatter and 1D histogram) Attributes ---------- autoscaleX : `utils.AutoscaleState` Set autoscaling on the x component 1D centroid line plot. autoscaleY : `utils.Auto... | Implement the Python class `CentroidPlotConfig` described below.
Class description:
Class for handling the configuration of the centroid plots (1D line, scatter and 1D histogram) Attributes ---------- autoscaleX : `utils.AutoscaleState` Set autoscaling on the x component 1D centroid line plot. autoscaleY : `utils.Auto... | 3d0242276198126240667ba13e95b7bdf901d053 | <|skeleton|>
class CentroidPlotConfig:
"""Class for handling the configuration of the centroid plots (1D line, scatter and 1D histogram) Attributes ---------- autoscaleX : `utils.AutoscaleState` Set autoscaling on the x component 1D centroid line plot. autoscaleY : `utils.AutoscaleState` Set autoscaling on the y co... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CentroidPlotConfig:
"""Class for handling the configuration of the centroid plots (1D line, scatter and 1D histogram) Attributes ---------- autoscaleX : `utils.AutoscaleState` Set autoscaling on the x component 1D centroid line plot. autoscaleY : `utils.AutoscaleState` Set autoscaling on the y component 1D ce... | the_stack_v2_python_sparse | spot_motion_monitor/config/centroid_plot_config.py | lsst-sitcom/spot_motion_monitor | train | 0 |
85d99c349eaed6abb904cab48233eb3b76b78124 | [
"if not fields:\n fields = ('id',)\ndb_sess = db_session.create_session()\narticle = db_sess.query(Article).get(article_id)\nif not article:\n raise ArticleNotFoundError\nreturn article.to_dict(only=fields)",
"if not fields:\n fields = ('id',)\ndb_sess = db_session.create_session()\narticles = db_sess.qu... | <|body_start_0|>
if not fields:
fields = ('id',)
db_sess = db_session.create_session()
article = db_sess.query(Article).get(article_id)
if not article:
raise ArticleNotFoundError
return article.to_dict(only=fields)
<|end_body_0|>
<|body_start_1|>
... | Класс для работы с моделью Article | ArticleModelWorker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArticleModelWorker:
"""Класс для работы с моделью Article"""
def get_article(article_id, fields=('id', 'title')):
"""Статья в JSON формате. Применяется в основном в API"""
<|body_0|>
def get_all_articles(fields=('id', 'title'), author=None, sorted_by='create_date', limit... | stack_v2_sparse_classes_10k_train_002984 | 5,022 | no_license | [
{
"docstring": "Статья в JSON формате. Применяется в основном в API",
"name": "get_article",
"signature": "def get_article(article_id, fields=('id', 'title'))"
},
{
"docstring": "Список статей в JSON формате. Применяется в основном в API",
"name": "get_all_articles",
"signature": "def ge... | 6 | stack_v2_sparse_classes_30k_train_007020 | Implement the Python class `ArticleModelWorker` described below.
Class description:
Класс для работы с моделью Article
Method signatures and docstrings:
- def get_article(article_id, fields=('id', 'title')): Статья в JSON формате. Применяется в основном в API
- def get_all_articles(fields=('id', 'title'), author=None... | Implement the Python class `ArticleModelWorker` described below.
Class description:
Класс для работы с моделью Article
Method signatures and docstrings:
- def get_article(article_id, fields=('id', 'title')): Статья в JSON формате. Применяется в основном в API
- def get_all_articles(fields=('id', 'title'), author=None... | 1bc59640f13ae4fe6582bb10c9093ff3d671aeb1 | <|skeleton|>
class ArticleModelWorker:
"""Класс для работы с моделью Article"""
def get_article(article_id, fields=('id', 'title')):
"""Статья в JSON формате. Применяется в основном в API"""
<|body_0|>
def get_all_articles(fields=('id', 'title'), author=None, sorted_by='create_date', limit... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ArticleModelWorker:
"""Класс для работы с моделью Article"""
def get_article(article_id, fields=('id', 'title')):
"""Статья в JSON формате. Применяется в основном в API"""
if not fields:
fields = ('id',)
db_sess = db_session.create_session()
article = db_sess.q... | the_stack_v2_python_sparse | model_workers/article.py | KosenokIvan/articles_website | train | 1 |
b85aaa0672f5f3600d8a08215e59bebde4f9c3f4 | [
"pools = [_GkeNodePoolTargetParser.Parse(dataproc, gke_cluster, arg_pool, support_shuffle_service) for arg_pool in arg_pools]\nGkeNodePoolTargetsParser._ValidateUniqueNames(pools)\nGkeNodePoolTargetsParser._ValidateRoles(dataproc, pools)\nGkeNodePoolTargetsParser._ValidatePoolsHaveSameLocation(pools)\nGkeNodePoolTa... | <|body_start_0|>
pools = [_GkeNodePoolTargetParser.Parse(dataproc, gke_cluster, arg_pool, support_shuffle_service) for arg_pool in arg_pools]
GkeNodePoolTargetsParser._ValidateUniqueNames(pools)
GkeNodePoolTargetsParser._ValidateRoles(dataproc, pools)
GkeNodePoolTargetsParser._ValidatePo... | Parses all the --pools flags into a list of GkeNodePoolTarget messages. | GkeNodePoolTargetsParser | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GkeNodePoolTargetsParser:
"""Parses all the --pools flags into a list of GkeNodePoolTarget messages."""
def Parse(dataproc, gke_cluster, arg_pools, support_shuffle_service=False):
"""Parses all the --pools flags into a list of GkeNodePoolTarget messages. Args: dataproc: The Dataproc ... | stack_v2_sparse_classes_10k_train_002985 | 19,343 | permissive | [
{
"docstring": "Parses all the --pools flags into a list of GkeNodePoolTarget messages. Args: dataproc: The Dataproc API version to use for GkeNodePoolTarget messages. gke_cluster: The GKE cluster's relative name, for example, 'projects/p1/locations/l1/clusters/c1'. arg_pools: The list of dict[str, any] generat... | 5 | stack_v2_sparse_classes_30k_train_004322 | Implement the Python class `GkeNodePoolTargetsParser` described below.
Class description:
Parses all the --pools flags into a list of GkeNodePoolTarget messages.
Method signatures and docstrings:
- def Parse(dataproc, gke_cluster, arg_pools, support_shuffle_service=False): Parses all the --pools flags into a list of ... | Implement the Python class `GkeNodePoolTargetsParser` described below.
Class description:
Parses all the --pools flags into a list of GkeNodePoolTarget messages.
Method signatures and docstrings:
- def Parse(dataproc, gke_cluster, arg_pools, support_shuffle_service=False): Parses all the --pools flags into a list of ... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class GkeNodePoolTargetsParser:
"""Parses all the --pools flags into a list of GkeNodePoolTarget messages."""
def Parse(dataproc, gke_cluster, arg_pools, support_shuffle_service=False):
"""Parses all the --pools flags into a list of GkeNodePoolTarget messages. Args: dataproc: The Dataproc ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GkeNodePoolTargetsParser:
"""Parses all the --pools flags into a list of GkeNodePoolTarget messages."""
def Parse(dataproc, gke_cluster, arg_pools, support_shuffle_service=False):
"""Parses all the --pools flags into a list of GkeNodePoolTarget messages. Args: dataproc: The Dataproc API version t... | the_stack_v2_python_sparse | lib/googlecloudsdk/command_lib/dataproc/gke_clusters.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
adfd234506b58be05a053865476d654fe3d3f82d | [
"conn = pymysql.connect(host='localhost', port=3306, user='root', passwd='zhangroot', db='hlrfw_test', unix_socket='/var/run/mysqld/mysqld.sock', cursorclass=pymysql.cursors.DictCursor)\ncur = conn.cursor()\ntry:\n cur.execute(sql)\n conn.commit()\nexcept Exception as e:\n conn.rollback()\nfinally:\n co... | <|body_start_0|>
conn = pymysql.connect(host='localhost', port=3306, user='root', passwd='zhangroot', db='hlrfw_test', unix_socket='/var/run/mysqld/mysqld.sock', cursorclass=pymysql.cursors.DictCursor)
cur = conn.cursor()
try:
cur.execute(sql)
conn.commit()
except... | MyDatabase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyDatabase:
def modify_data(self, sql):
"""- 执行sql语句"""
<|body_0|>
def select_last_data(self, sql):
"""- 返回sql的最后一条数据"""
<|body_1|>
def select_all_data(slef, sql):
"""- 返回所有符合sql语句的数据"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_002986 | 2,241 | no_license | [
{
"docstring": "- 执行sql语句",
"name": "modify_data",
"signature": "def modify_data(self, sql)"
},
{
"docstring": "- 返回sql的最后一条数据",
"name": "select_last_data",
"signature": "def select_last_data(self, sql)"
},
{
"docstring": "- 返回所有符合sql语句的数据",
"name": "select_all_data",
"si... | 3 | stack_v2_sparse_classes_30k_train_007067 | Implement the Python class `MyDatabase` described below.
Class description:
Implement the MyDatabase class.
Method signatures and docstrings:
- def modify_data(self, sql): - 执行sql语句
- def select_last_data(self, sql): - 返回sql的最后一条数据
- def select_all_data(slef, sql): - 返回所有符合sql语句的数据 | Implement the Python class `MyDatabase` described below.
Class description:
Implement the MyDatabase class.
Method signatures and docstrings:
- def modify_data(self, sql): - 执行sql语句
- def select_last_data(self, sql): - 返回sql的最后一条数据
- def select_all_data(slef, sql): - 返回所有符合sql语句的数据
<|skeleton|>
class MyDatabase:
... | 61f81163583582c1f5816909f1e3829686c572d7 | <|skeleton|>
class MyDatabase:
def modify_data(self, sql):
"""- 执行sql语句"""
<|body_0|>
def select_last_data(self, sql):
"""- 返回sql的最后一条数据"""
<|body_1|>
def select_all_data(slef, sql):
"""- 返回所有符合sql语句的数据"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MyDatabase:
def modify_data(self, sql):
"""- 执行sql语句"""
conn = pymysql.connect(host='localhost', port=3306, user='root', passwd='zhangroot', db='hlrfw_test', unix_socket='/var/run/mysqld/mysqld.sock', cursorclass=pymysql.cursors.DictCursor)
cur = conn.cursor()
try:
... | the_stack_v2_python_sparse | hlrfw/database/MyDatabase.py | 253765620/xuzhibo_work | train | 0 | |
7466c1601403866ca6b6be942ac5e4939b4f2188 | [
"if not grid:\n return 0\nm, n = (len(grid), len(grid[0]))\ndp = [[0 for i in range(n)] for j in range(m)]\ndp[0][0] = grid[0][0]\nfor i in range(1, m):\n dp[i][0] = dp[i - 1][0] + grid[i][0]\nfor j in range(1, n):\n dp[0][j] = dp[0][j - 1] + grid[0][j]\nfor i in range(1, m):\n for j in range(1, n):\n ... | <|body_start_0|>
if not grid:
return 0
m, n = (len(grid), len(grid[0]))
dp = [[0 for i in range(n)] for j in range(m)]
dp[0][0] = grid[0][0]
for i in range(1, m):
dp[i][0] = dp[i - 1][0] + grid[i][0]
for j in range(1, n):
dp[0][j] = dp[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def minPathSum2(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_1|>
def minPathSum3(self, grid):
""":type grid: List[List[int]] :rtyp... | stack_v2_sparse_classes_10k_train_002987 | 3,941 | no_license | [
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "minPathSum",
"signature": "def minPathSum(self, grid)"
},
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "minPathSum2",
"signature": "def minPathSum2(self, grid)"
},
{
"docstring": ":type grid: ... | 4 | stack_v2_sparse_classes_30k_test_000406 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minPathSum(self, grid): :type grid: List[List[int]] :rtype: int
- def minPathSum2(self, grid): :type grid: List[List[int]] :rtype: int
- def minPathSum3(self, grid): :type gr... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minPathSum(self, grid): :type grid: List[List[int]] :rtype: int
- def minPathSum2(self, grid): :type grid: List[List[int]] :rtype: int
- def minPathSum3(self, grid): :type gr... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def minPathSum2(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_1|>
def minPathSum3(self, grid):
""":type grid: List[List[int]] :rtyp... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
if not grid:
return 0
m, n = (len(grid), len(grid[0]))
dp = [[0 for i in range(n)] for j in range(m)]
dp[0][0] = grid[0][0]
for i in range(1, m):
dp[i][0]... | the_stack_v2_python_sparse | 64. Minimum Path Sum/minimum_path.py | Macielyoung/LeetCode | train | 1 | |
0fec9cb4b8d86dfaea25aec8c1361f09dd7e1b5d | [
"super(Embedding, self).__init__()\nself.N_freqs = N_freqs\nself.in_channels = in_channels\nself.funcs = [torch.sin, torch.cos]\nself.out_channels = in_channels * (len(self.funcs) * N_freqs + 1)\nif logscale:\n self.freq_bands = 2 ** torch.linspace(0, N_freqs - 1, N_freqs)\nelse:\n self.freq_bands = torch.lin... | <|body_start_0|>
super(Embedding, self).__init__()
self.N_freqs = N_freqs
self.in_channels = in_channels
self.funcs = [torch.sin, torch.cos]
self.out_channels = in_channels * (len(self.funcs) * N_freqs + 1)
if logscale:
self.freq_bands = 2 ** torch.linspace(0,... | Embedding | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Embedding:
def __init__(self, in_channels, N_freqs, logscale=True):
"""Defines a function that embeds x to (x, sin(2^k x), cos(2^k x), ...) in_channels: number of input channels (3 for both xyz and direction)"""
<|body_0|>
def forward(self, x):
"""Embeds x to (x, sin... | stack_v2_sparse_classes_10k_train_002988 | 18,983 | no_license | [
{
"docstring": "Defines a function that embeds x to (x, sin(2^k x), cos(2^k x), ...) in_channels: number of input channels (3 for both xyz and direction)",
"name": "__init__",
"signature": "def __init__(self, in_channels, N_freqs, logscale=True)"
},
{
"docstring": "Embeds x to (x, sin(2^k x), co... | 2 | stack_v2_sparse_classes_30k_train_001379 | Implement the Python class `Embedding` described below.
Class description:
Implement the Embedding class.
Method signatures and docstrings:
- def __init__(self, in_channels, N_freqs, logscale=True): Defines a function that embeds x to (x, sin(2^k x), cos(2^k x), ...) in_channels: number of input channels (3 for both ... | Implement the Python class `Embedding` described below.
Class description:
Implement the Embedding class.
Method signatures and docstrings:
- def __init__(self, in_channels, N_freqs, logscale=True): Defines a function that embeds x to (x, sin(2^k x), cos(2^k x), ...) in_channels: number of input channels (3 for both ... | 3b6e9d85e77077d1ad3b669fe88799d6a19e6d99 | <|skeleton|>
class Embedding:
def __init__(self, in_channels, N_freqs, logscale=True):
"""Defines a function that embeds x to (x, sin(2^k x), cos(2^k x), ...) in_channels: number of input channels (3 for both xyz and direction)"""
<|body_0|>
def forward(self, x):
"""Embeds x to (x, sin... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Embedding:
def __init__(self, in_channels, N_freqs, logscale=True):
"""Defines a function that embeds x to (x, sin(2^k x), cos(2^k x), ...) in_channels: number of input channels (3 for both xyz and direction)"""
super(Embedding, self).__init__()
self.N_freqs = N_freqs
self.in_c... | the_stack_v2_python_sparse | models/nert.py | jcn16/nert | train | 0 | |
7f91ea3c98907597d5448f682966786f1d91b46c | [
"self._value = cookie\nself._quoted = False\nif len(self._value) > 1 and self._value.startswith('\"') and self._value.endswith('\"'):\n self._value = self._value[1:-1]\n self._quoted = True",
"if self._quoted:\n yield ('\"' + payload + '\"')\nelse:\n yield payload"
] | <|body_start_0|>
self._value = cookie
self._quoted = False
if len(self._value) > 1 and self._value.startswith('"') and self._value.endswith('"'):
self._value = self._value[1:-1]
self._quoted = True
<|end_body_0|>
<|body_start_1|>
if self._quoted:
yiel... | This is for simple cookies. They are normally single values. The entire value can be replaced with a payload. | SimpleCookie | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleCookie:
"""This is for simple cookies. They are normally single values. The entire value can be replaced with a payload."""
def __init__(self, cookie):
"""Sets the string and removes quotes."""
<|body_0|>
def replace(self, payload):
"""Replace entire cookie... | stack_v2_sparse_classes_10k_train_002989 | 3,236 | permissive | [
{
"docstring": "Sets the string and removes quotes.",
"name": "__init__",
"signature": "def __init__(self, cookie)"
},
{
"docstring": "Replace entire cookie value and add back quotes. List will have a single item. :param payload: payload string :return: list of replacements",
"name": "replac... | 2 | stack_v2_sparse_classes_30k_train_002424 | Implement the Python class `SimpleCookie` described below.
Class description:
This is for simple cookies. They are normally single values. The entire value can be replaced with a payload.
Method signatures and docstrings:
- def __init__(self, cookie): Sets the string and removes quotes.
- def replace(self, payload): ... | Implement the Python class `SimpleCookie` described below.
Class description:
This is for simple cookies. They are normally single values. The entire value can be replaced with a payload.
Method signatures and docstrings:
- def __init__(self, cookie): Sets the string and removes quotes.
- def replace(self, payload): ... | 4483b301034a096b716646a470a6642b3df8ce61 | <|skeleton|>
class SimpleCookie:
"""This is for simple cookies. They are normally single values. The entire value can be replaced with a payload."""
def __init__(self, cookie):
"""Sets the string and removes quotes."""
<|body_0|>
def replace(self, payload):
"""Replace entire cookie... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SimpleCookie:
"""This is for simple cookies. They are normally single values. The entire value can be replaced with a payload."""
def __init__(self, cookie):
"""Sets the string and removes quotes."""
self._value = cookie
self._quoted = False
if len(self._value) > 1 and sel... | the_stack_v2_python_sparse | ava/parsers/cookie.py | indeedsecurity/ava-ce | train | 3 |
222a401d10fb35279cd9603571d067ea60195720 | [
"resource_args.AddDatabaseResourceArg(parser, 'to update')\ngroup_parser = parser.add_argument_group(mutex=True)\nflags.EnableDropProtection().AddToParser(group_parser)\nbase.ASYNC_FLAG.AddToParser(parser)",
"op = databases.Update(args.CONCEPTS.database.Parse(), args.enable_drop_protection)\nif args.async_:\n ... | <|body_start_0|>
resource_args.AddDatabaseResourceArg(parser, 'to update')
group_parser = parser.add_argument_group(mutex=True)
flags.EnableDropProtection().AddToParser(group_parser)
base.ASYNC_FLAG.AddToParser(parser)
<|end_body_0|>
<|body_start_1|>
op = databases.Update(args.C... | Update a Cloud Spanner database. | Update | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Update:
"""Update a Cloud Spanner database."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are allowed."""... | stack_v2_sparse_classes_10k_train_002990 | 2,534 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are allowed.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring"... | 2 | stack_v2_sparse_classes_30k_train_000388 | Implement the Python class `Update` described below.
Class description:
Update a Cloud Spanner database.
Method signatures and docstrings:
- def Args(parser): Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line... | Implement the Python class `Update` described below.
Class description:
Update a Cloud Spanner database.
Method signatures and docstrings:
- def Args(parser): Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class Update:
"""Update a Cloud Spanner database."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are allowed."""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Update:
"""Update a Cloud Spanner database."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are allowed."""
reso... | the_stack_v2_python_sparse | lib/surface/spanner/databases/update.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
20a5f6a70f8cfff97b42bfca47adc83319c0195a | [
"Thread.__init__(self)\nself.tasks = tasks\nself.daemon = True\nself.start()",
"while 1:\n func, args, kargs = self.tasks.get()\n try:\n func(*args, **kargs)\n except Exception as e:\n print(e)\n finally:\n self.tasks.task_done()"
] | <|body_start_0|>
Thread.__init__(self)
self.tasks = tasks
self.daemon = True
self.start()
<|end_body_0|>
<|body_start_1|>
while 1:
func, args, kargs = self.tasks.get()
try:
func(*args, **kargs)
except Exception as e:
... | Thread executing tasks from a given tasks queue | Worker | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Worker:
"""Thread executing tasks from a given tasks queue"""
def __init__(self, tasks):
"""Constructor :param tasks: queue containing tasks to execute"""
<|body_0|>
def run(self):
"""Run the worker thread"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_10k_train_002991 | 2,523 | permissive | [
{
"docstring": "Constructor :param tasks: queue containing tasks to execute",
"name": "__init__",
"signature": "def __init__(self, tasks)"
},
{
"docstring": "Run the worker thread",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003573 | Implement the Python class `Worker` described below.
Class description:
Thread executing tasks from a given tasks queue
Method signatures and docstrings:
- def __init__(self, tasks): Constructor :param tasks: queue containing tasks to execute
- def run(self): Run the worker thread | Implement the Python class `Worker` described below.
Class description:
Thread executing tasks from a given tasks queue
Method signatures and docstrings:
- def __init__(self, tasks): Constructor :param tasks: queue containing tasks to execute
- def run(self): Run the worker thread
<|skeleton|>
class Worker:
"""T... | 09692f8d2300172c41ce25331361875c56d0ba4a | <|skeleton|>
class Worker:
"""Thread executing tasks from a given tasks queue"""
def __init__(self, tasks):
"""Constructor :param tasks: queue containing tasks to execute"""
<|body_0|>
def run(self):
"""Run the worker thread"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Worker:
"""Thread executing tasks from a given tasks queue"""
def __init__(self, tasks):
"""Constructor :param tasks: queue containing tasks to execute"""
Thread.__init__(self)
self.tasks = tasks
self.daemon = True
self.start()
def run(self):
"""Run th... | the_stack_v2_python_sparse | DEVS Modelling and Simulation/pythonpdevs/src/pypdevs/threadpool.py | baturayo/Modeling-of-Software-Intensive-Systems | train | 2 |
5eae4fc521669e25024b4e7526a1b103c984d9a4 | [
"srcdir = tf_cfg.cfg.get('Tempesta', 'srcdir')\nworkdir = tf_cfg.cfg.get('Tempesta', 'workdir')\ntemplate = '%s/etc/js_challenge.tpl' % srcdir\njs_code = '%s/etc/js_challenge.js.tpl' % srcdir\nremote.tempesta.run_cmd('cp %s %s' % (js_code, workdir))\nremote.tempesta.run_cmd('cp %s %s/js1.tpl' % (template, workdir))... | <|body_start_0|>
srcdir = tf_cfg.cfg.get('Tempesta', 'srcdir')
workdir = tf_cfg.cfg.get('Tempesta', 'workdir')
template = '%s/etc/js_challenge.tpl' % srcdir
js_code = '%s/etc/js_challenge.js.tpl' % srcdir
remote.tempesta.run_cmd('cp %s %s' % (js_code, workdir))
remote.tem... | JSChallengeAfterReload | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSChallengeAfterReload:
def prepare_js_templates(self):
"""Templates for JS challenge are modified by start script, create a copy of default template for each vhost."""
<|body_0|>
def test(self):
"""Clients sends the validating request after reload just in time and p... | stack_v2_sparse_classes_10k_train_002992 | 24,777 | no_license | [
{
"docstring": "Templates for JS challenge are modified by start script, create a copy of default template for each vhost.",
"name": "prepare_js_templates",
"signature": "def prepare_js_templates(self)"
},
{
"docstring": "Clients sends the validating request after reload just in time and passes ... | 2 | null | Implement the Python class `JSChallengeAfterReload` described below.
Class description:
Implement the JSChallengeAfterReload class.
Method signatures and docstrings:
- def prepare_js_templates(self): Templates for JS challenge are modified by start script, create a copy of default template for each vhost.
- def test(... | Implement the Python class `JSChallengeAfterReload` described below.
Class description:
Implement the JSChallengeAfterReload class.
Method signatures and docstrings:
- def prepare_js_templates(self): Templates for JS challenge are modified by start script, create a copy of default template for each vhost.
- def test(... | d56358ea653dbb367624937197ce5e489abf0b00 | <|skeleton|>
class JSChallengeAfterReload:
def prepare_js_templates(self):
"""Templates for JS challenge are modified by start script, create a copy of default template for each vhost."""
<|body_0|>
def test(self):
"""Clients sends the validating request after reload just in time and p... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class JSChallengeAfterReload:
def prepare_js_templates(self):
"""Templates for JS challenge are modified by start script, create a copy of default template for each vhost."""
srcdir = tf_cfg.cfg.get('Tempesta', 'srcdir')
workdir = tf_cfg.cfg.get('Tempesta', 'workdir')
template = '%s/... | the_stack_v2_python_sparse | sessions/test_js_challenge.py | tempesta-tech/tempesta-test | train | 13 | |
67766d909c914465132ff891909fd2f7b2d68b3d | [
"if n <= 0 or k < 0:\n return ''\nres = []\n\ndef helper(i, temp):\n if len(temp) == n:\n res.append(temp)\n return\n for j in range(1, n + 1):\n if str(j) in temp:\n continue\n helper(j, temp + str(j))\nhelper(0, '')\nprint(res)\nreturn res[k - 1]",
"if n == 0:\n ... | <|body_start_0|>
if n <= 0 or k < 0:
return ''
res = []
def helper(i, temp):
if len(temp) == n:
res.append(temp)
return
for j in range(1, n + 1):
if str(j) in temp:
continue
h... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getPermutation(self, n: int, k: int) -> str:
"""可以使用回溯法来做，套用模板 需要求出所有解，超出时间限制"""
<|body_0|>
def getPermutation1(self, n: int, k: int) -> str:
"""123, 1为首字母，有23,32 ,2！ 第n个位置的数字，由 k // (n-1)! 决定"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_002993 | 1,879 | no_license | [
{
"docstring": "可以使用回溯法来做，套用模板 需要求出所有解，超出时间限制",
"name": "getPermutation",
"signature": "def getPermutation(self, n: int, k: int) -> str"
},
{
"docstring": "123, 1为首字母，有23,32 ,2！ 第n个位置的数字，由 k // (n-1)! 决定",
"name": "getPermutation1",
"signature": "def getPermutation1(self, n: int, k: int)... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getPermutation(self, n: int, k: int) -> str: 可以使用回溯法来做，套用模板 需要求出所有解，超出时间限制
- def getPermutation1(self, n: int, k: int) -> str: 123, 1为首字母，有23,32 ,2！ 第n个位置的数字，由 k // (n-1)! 决定 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getPermutation(self, n: int, k: int) -> str: 可以使用回溯法来做，套用模板 需要求出所有解，超出时间限制
- def getPermutation1(self, n: int, k: int) -> str: 123, 1为首字母，有23,32 ,2！ 第n个位置的数字，由 k // (n-1)! 决定... | 95dddb78bccd169d9d219a473627361fe739ab5e | <|skeleton|>
class Solution:
def getPermutation(self, n: int, k: int) -> str:
"""可以使用回溯法来做，套用模板 需要求出所有解，超出时间限制"""
<|body_0|>
def getPermutation1(self, n: int, k: int) -> str:
"""123, 1为首字母，有23,32 ,2！ 第n个位置的数字，由 k // (n-1)! 决定"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def getPermutation(self, n: int, k: int) -> str:
"""可以使用回溯法来做，套用模板 需要求出所有解，超出时间限制"""
if n <= 0 or k < 0:
return ''
res = []
def helper(i, temp):
if len(temp) == n:
res.append(temp)
return
for j in ra... | the_stack_v2_python_sparse | StringOperation/getPermutation.py | Philex5/codingPractice | train | 0 | |
51ba188f797c263aebb91c02b922df7478b794bd | [
"QMimeData.__init__(self)\nself._local_instance = p_data\nif p_data is not None:\n try:\n p_data = dumps(p_data)\n except Exception:\n return\n self.setData(self.MIME_TYPE, dumps(p_data.__class__) + p_data)",
"if self._local_instance is not None:\n return self._local_instance\nio = Strin... | <|body_start_0|>
QMimeData.__init__(self)
self._local_instance = p_data
if p_data is not None:
try:
p_data = dumps(p_data)
except Exception:
return
self.setData(self.MIME_TYPE, dumps(p_data.__class__) + p_data)
<|end_body_0|>
<... | The OrcMimeData wraps a Python instance as MIME data. | OrcMimeData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrcMimeData:
"""The OrcMimeData wraps a Python instance as MIME data."""
def __init__(self, p_data=None):
"""Initialise the instance."""
<|body_0|>
def instance(self):
"""Return the instance."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
QMime... | stack_v2_sparse_classes_10k_train_002994 | 13,946 | no_license | [
{
"docstring": "Initialise the instance.",
"name": "__init__",
"signature": "def __init__(self, p_data=None)"
},
{
"docstring": "Return the instance.",
"name": "instance",
"signature": "def instance(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002558 | Implement the Python class `OrcMimeData` described below.
Class description:
The OrcMimeData wraps a Python instance as MIME data.
Method signatures and docstrings:
- def __init__(self, p_data=None): Initialise the instance.
- def instance(self): Return the instance. | Implement the Python class `OrcMimeData` described below.
Class description:
The OrcMimeData wraps a Python instance as MIME data.
Method signatures and docstrings:
- def __init__(self, p_data=None): Initialise the instance.
- def instance(self): Return the instance.
<|skeleton|>
class OrcMimeData:
"""The OrcMim... | f3ccbbceaed4f4996f6907a2f4880c2fd3f82bbb | <|skeleton|>
class OrcMimeData:
"""The OrcMimeData wraps a Python instance as MIME data."""
def __init__(self, p_data=None):
"""Initialise the instance."""
<|body_0|>
def instance(self):
"""Return the instance."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OrcMimeData:
"""The OrcMimeData wraps a Python instance as MIME data."""
def __init__(self, p_data=None):
"""Initialise the instance."""
QMimeData.__init__(self)
self._local_instance = p_data
if p_data is not None:
try:
p_data = dumps(p_data)
... | the_stack_v2_python_sparse | OrcView/Lib/LibTree.py | pubselenium/OrcTestToolsKit | train | 0 |
9be1e23c6c24af6fd14e2478b3c7cb9c6b07b552 | [
"self.max_depth = max_depth\nself.save_images = save_images\nself.clock = time.time()\nself.t_buffer = t_buffer\nself.output_dir = output_dir\nself.data_dir = path.join(self.output_dir, '{}'.format(time.strftime('%d_%b_%Y_%H:%M', time.localtime())))\nif self.save_images:\n ensureDir(self.data_dir)\npass\nnp.warn... | <|body_start_0|>
self.max_depth = max_depth
self.save_images = save_images
self.clock = time.time()
self.t_buffer = t_buffer
self.output_dir = output_dir
self.data_dir = path.join(self.output_dir, '{}'.format(time.strftime('%d_%b_%Y_%H:%M', time.localtime())))
if ... | Object to get data from R200 | Camera | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Camera:
"""Object to get data from R200"""
def __init__(self, max_depth=4.0, save_images=False, t_buffer=5, output_dir='./Trials/'):
"""Intitalizes Camera object"""
<|body_0|>
def connect(self):
"""Establishes connection to R200 camera"""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_002995 | 6,258 | permissive | [
{
"docstring": "Intitalizes Camera object",
"name": "__init__",
"signature": "def __init__(self, max_depth=4.0, save_images=False, t_buffer=5, output_dir='./Trials/')"
},
{
"docstring": "Establishes connection to R200 camera",
"name": "connect",
"signature": "def connect(self)"
},
{
... | 5 | stack_v2_sparse_classes_30k_test_000270 | Implement the Python class `Camera` described below.
Class description:
Object to get data from R200
Method signatures and docstrings:
- def __init__(self, max_depth=4.0, save_images=False, t_buffer=5, output_dir='./Trials/'): Intitalizes Camera object
- def connect(self): Establishes connection to R200 camera
- def ... | Implement the Python class `Camera` described below.
Class description:
Object to get data from R200
Method signatures and docstrings:
- def __init__(self, max_depth=4.0, save_images=False, t_buffer=5, output_dir='./Trials/'): Intitalizes Camera object
- def connect(self): Establishes connection to R200 camera
- def ... | 08fe54fe37df89ffc7e6378125bb14ad5bead421 | <|skeleton|>
class Camera:
"""Object to get data from R200"""
def __init__(self, max_depth=4.0, save_images=False, t_buffer=5, output_dir='./Trials/'):
"""Intitalizes Camera object"""
<|body_0|>
def connect(self):
"""Establishes connection to R200 camera"""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Camera:
"""Object to get data from R200"""
def __init__(self, max_depth=4.0, save_images=False, t_buffer=5, output_dir='./Trials/'):
"""Intitalizes Camera object"""
self.max_depth = max_depth
self.save_images = save_images
self.clock = time.time()
self.t_buffer = t... | the_stack_v2_python_sparse | Camera/camera.py | marioliu/AutonomousQuadblade | train | 0 |
ec07f6fa25e8536bc98f276fcf3f6582056efbc2 | [
"flags.AddParentFlagsToParser(parser)\nparser.add_argument('RECOMMENDATION', type=str, help='Recommendation id which will be marked as active')\nparser.add_argument('--location', metavar='LOCATION', required=True, help='Location')\nparser.add_argument('--recommender', metavar='RECOMMENDER', required=True, help='Rec... | <|body_start_0|>
flags.AddParentFlagsToParser(parser)
parser.add_argument('RECOMMENDATION', type=str, help='Recommendation id which will be marked as active')
parser.add_argument('--location', metavar='LOCATION', required=True, help='Location')
parser.add_argument('--recommender', metava... | Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organization. ## EXAMPLES To mark a recommenation as ACTIVE: $ {command} RECOMMENDATION... | MarkActive | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MarkActive:
"""Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organization. ## EXAMPLES To mark a recommenation... | stack_v2_sparse_classes_10k_train_002996 | 2,733 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "Run 'gcloud recommender recomme... | 2 | null | Implement the Python class `MarkActive` described below.
Class description:
Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organizati... | Implement the Python class `MarkActive` described below.
Class description:
Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organizati... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class MarkActive:
"""Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organization. ## EXAMPLES To mark a recommenation... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MarkActive:
"""Mark Active operations for a recommendation. Mark a recommendation's state as ACTIVE. Can be applied to recommendations in DISMISSED state. This currently supports the following parent entities: project, billing account, folder, and organization. ## EXAMPLES To mark a recommenation as ACTIVE: $... | the_stack_v2_python_sparse | lib/surface/recommender/recommendations/mark_active.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
ebcb97e058c714c3c336aa38be84fa4228d4f6f6 | [
"if not root:\n return []\nres = []\nqueue = [root]\nwhile queue:\n level_node = []\n temp = []\n for i in queue:\n level_node.append(i.val)\n if i.left:\n temp.append(i.left)\n if i.right:\n temp.append(i.right)\n res.append(level_node)\n queue = temp\nr... | <|body_start_0|>
if not root:
return []
res = []
queue = [root]
while queue:
level_node = []
temp = []
for i in queue:
level_node.append(i.val)
if i.left:
temp.append(i.left)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""bfs 迭代：相对来说用队列就能实现"""
<|body_0|>
def levelOrder1(self, root: TreeNode) -> List[List[int]]:
"""递归"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return []... | stack_v2_sparse_classes_10k_train_002997 | 1,795 | no_license | [
{
"docstring": "bfs 迭代：相对来说用队列就能实现",
"name": "levelOrder",
"signature": "def levelOrder(self, root: TreeNode) -> List[List[int]]"
},
{
"docstring": "递归",
"name": "levelOrder1",
"signature": "def levelOrder1(self, root: TreeNode) -> List[List[int]]"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: TreeNode) -> List[List[int]]: bfs 迭代：相对来说用队列就能实现
- def levelOrder1(self, root: TreeNode) -> List[List[int]]: 递归 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: TreeNode) -> List[List[int]]: bfs 迭代：相对来说用队列就能实现
- def levelOrder1(self, root: TreeNode) -> List[List[int]]: 递归
<|skeleton|>
class Solution:
def ... | 069bb0b751ef7f469036b9897436eb5d138ffa24 | <|skeleton|>
class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""bfs 迭代：相对来说用队列就能实现"""
<|body_0|>
def levelOrder1(self, root: TreeNode) -> List[List[int]]:
"""递归"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""bfs 迭代：相对来说用队列就能实现"""
if not root:
return []
res = []
queue = [root]
while queue:
level_node = []
temp = []
for i in queue:
level_node.a... | the_stack_v2_python_sparse | 算法/Week_02/102. 二叉树的层序遍历.py | RichieSong/algorithm | train | 0 | |
0c19baaed8b431a649a08a96819e1047e32afe55 | [
"try:\n getattr(logging, value.upper())\nexcept AttributeError as err:\n raise ValueError(f'{value.upper()} is not a valid level') from err\nreturn value.upper()",
"assert issubclass(self.__class__, MixinLoggingSettings)\nassert hasattr(self, 'LOG_LEVEL')\nreturn getattr(logging, self.LOG_LEVEL.upper())"
] | <|body_start_0|>
try:
getattr(logging, value.upper())
except AttributeError as err:
raise ValueError(f'{value.upper()} is not a valid level') from err
return value.upper()
<|end_body_0|>
<|body_start_1|>
assert issubclass(self.__class__, MixinLoggingSettings)
... | USAGE example in packages/settings-library/tests/test_utils_logging.py::test_mixin_logging | MixinLoggingSettings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MixinLoggingSettings:
"""USAGE example in packages/settings-library/tests/test_utils_logging.py::test_mixin_logging"""
def validate_log_level(cls, value: str) -> str:
"""Standard implementation for @validator("LOG_LEVEL")"""
<|body_0|>
def log_level(self) -> int:
... | stack_v2_sparse_classes_10k_train_002998 | 862 | permissive | [
{
"docstring": "Standard implementation for @validator(\"LOG_LEVEL\")",
"name": "validate_log_level",
"signature": "def validate_log_level(cls, value: str) -> str"
},
{
"docstring": "Can be used in logging.setLogLevel()",
"name": "log_level",
"signature": "def log_level(self) -> int"
}... | 2 | stack_v2_sparse_classes_30k_train_006339 | Implement the Python class `MixinLoggingSettings` described below.
Class description:
USAGE example in packages/settings-library/tests/test_utils_logging.py::test_mixin_logging
Method signatures and docstrings:
- def validate_log_level(cls, value: str) -> str: Standard implementation for @validator("LOG_LEVEL")
- def... | Implement the Python class `MixinLoggingSettings` described below.
Class description:
USAGE example in packages/settings-library/tests/test_utils_logging.py::test_mixin_logging
Method signatures and docstrings:
- def validate_log_level(cls, value: str) -> str: Standard implementation for @validator("LOG_LEVEL")
- def... | f4c57ffc7b494ac06a2692cb5539d3acfd3d1d63 | <|skeleton|>
class MixinLoggingSettings:
"""USAGE example in packages/settings-library/tests/test_utils_logging.py::test_mixin_logging"""
def validate_log_level(cls, value: str) -> str:
"""Standard implementation for @validator("LOG_LEVEL")"""
<|body_0|>
def log_level(self) -> int:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MixinLoggingSettings:
"""USAGE example in packages/settings-library/tests/test_utils_logging.py::test_mixin_logging"""
def validate_log_level(cls, value: str) -> str:
"""Standard implementation for @validator("LOG_LEVEL")"""
try:
getattr(logging, value.upper())
except ... | the_stack_v2_python_sparse | packages/settings-library/src/settings_library/utils_logging.py | ITISFoundation/osparc-simcore | train | 39 |
081caee2d7425799f53590fdd7fc6c64c37aff29 | [
"self.problem = problem\nself.agents = agents\nself.max_value = max_value\nself.path_set = PathSet(self.agents, self.problem.heuristic)\nself.cats = []\nif cat is not None:\n self.cats.append(cat)\nself.cats.append(self.path_set.cat)\nself.stat_tracker = stat_tracker",
"agents = copy(self.agents)\ngroups = []\... | <|body_start_0|>
self.problem = problem
self.agents = agents
self.max_value = max_value
self.path_set = PathSet(self.agents, self.problem.heuristic)
self.cats = []
if cat is not None:
self.cats.append(cat)
self.cats.append(self.path_set.cat)
se... | Solver that uses Independence Detection: First solve for all agents individually. If paths are conflicting, merge the agents and solve for the new group | IDSolver | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IDSolver:
"""Solver that uses Independence Detection: First solve for all agents individually. If paths are conflicting, merge the agents and solve for the new group"""
def __init__(self, problem: MAPFProblem, agents: List[Agent], cat: Optional[CAT], stat_tracker, max_value=float('inf')):
... | stack_v2_sparse_classes_10k_train_002999 | 4,961 | permissive | [
{
"docstring": "Constructs an IDSolver instance :param problem: MAPF problem instance that needs to be solved :param agents: Agents that belong to the problem :param cat: Additional Collision Avoidance Table that should be used in calculating the result :param stat_tracker Statistic tracker :param max_value: Ma... | 3 | stack_v2_sparse_classes_30k_train_004318 | Implement the Python class `IDSolver` described below.
Class description:
Solver that uses Independence Detection: First solve for all agents individually. If paths are conflicting, merge the agents and solve for the new group
Method signatures and docstrings:
- def __init__(self, problem: MAPFProblem, agents: List[A... | Implement the Python class `IDSolver` described below.
Class description:
Solver that uses Independence Detection: First solve for all agents individually. If paths are conflicting, merge the agents and solve for the new group
Method signatures and docstrings:
- def __init__(self, problem: MAPFProblem, agents: List[A... | 13d8716f932bb98398fe8e190e668ee65bcf0f34 | <|skeleton|>
class IDSolver:
"""Solver that uses Independence Detection: First solve for all agents individually. If paths are conflicting, merge the agents and solve for the new group"""
def __init__(self, problem: MAPFProblem, agents: List[Agent], cat: Optional[CAT], stat_tracker, max_value=float('inf')):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IDSolver:
"""Solver that uses Independence Detection: First solve for all agents individually. If paths are conflicting, merge the agents and solve for the new group"""
def __init__(self, problem: MAPFProblem, agents: List[Agent], cat: Optional[CAT], stat_tracker, max_value=float('inf')):
"""Cons... | the_stack_v2_python_sparse | src/solver/epeastar/independence_detection.py | tbvanderwoude/matching-epea-star | train | 0 |
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