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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
e1b40f9335eccda2dde8abf4d688c50215f0aa31 | [
"self.cloud_domain_id = cloud_domain_id\nself.is_cad_mode = is_cad_mode\nself.migration_uid = migration_uid\nself.vault_id = vault_id\nself.view_box_id = view_box_id",
"if dictionary is None:\n return None\ncloud_domain_id = dictionary.get('cloudDomainId')\nis_cad_mode = dictionary.get('isCadMode')\nmigration_... | <|body_start_0|>
self.cloud_domain_id = cloud_domain_id
self.is_cad_mode = is_cad_mode
self.migration_uid = migration_uid
self.vault_id = vault_id
self.view_box_id = view_box_id
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
cloud_... | Implementation of the 'CreateCloudDomainMigrationParameters' model. CreateCloudDomainMigrationParameters represents the parameters needed to schedule the cloud domain migration. Attributes: cloud_domain_id (long|int): Specifies the Id of a specific cloud domain present inside the vault, that needs to be migrated. If no... | CreateCloudDomainMigrationParameters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateCloudDomainMigrationParameters:
"""Implementation of the 'CreateCloudDomainMigrationParameters' model. CreateCloudDomainMigrationParameters represents the parameters needed to schedule the cloud domain migration. Attributes: cloud_domain_id (long|int): Specifies the Id of a specific cloud d... | stack_v2_sparse_classes_10k_train_001500 | 2,951 | permissive | [
{
"docstring": "Constructor for the CreateCloudDomainMigrationParameters class",
"name": "__init__",
"signature": "def __init__(self, cloud_domain_id=None, is_cad_mode=None, migration_uid=None, vault_id=None, view_box_id=None)"
},
{
"docstring": "Creates an instance of this model from a dictiona... | 2 | null | Implement the Python class `CreateCloudDomainMigrationParameters` described below.
Class description:
Implementation of the 'CreateCloudDomainMigrationParameters' model. CreateCloudDomainMigrationParameters represents the parameters needed to schedule the cloud domain migration. Attributes: cloud_domain_id (long|int):... | Implement the Python class `CreateCloudDomainMigrationParameters` described below.
Class description:
Implementation of the 'CreateCloudDomainMigrationParameters' model. CreateCloudDomainMigrationParameters represents the parameters needed to schedule the cloud domain migration. Attributes: cloud_domain_id (long|int):... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class CreateCloudDomainMigrationParameters:
"""Implementation of the 'CreateCloudDomainMigrationParameters' model. CreateCloudDomainMigrationParameters represents the parameters needed to schedule the cloud domain migration. Attributes: cloud_domain_id (long|int): Specifies the Id of a specific cloud d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CreateCloudDomainMigrationParameters:
"""Implementation of the 'CreateCloudDomainMigrationParameters' model. CreateCloudDomainMigrationParameters represents the parameters needed to schedule the cloud domain migration. Attributes: cloud_domain_id (long|int): Specifies the Id of a specific cloud domain present... | the_stack_v2_python_sparse | cohesity_management_sdk/models/create_cloud_domain_migration_parameters.py | cohesity/management-sdk-python | train | 24 |
f79c1fc0d7b3ce46ff545255bcb10a80ce40d2a3 | [
"dict = json.loads(request.body.decode())\nreceiver = dict.get('receiver')\nprovince_id = dict.get('province_id')\ncity_id = dict.get('city_id')\ndistrict_id = dict.get('district_id')\nplace = dict.get('place')\nmobile = dict.get('mobile')\nphone = dict.get('tel')\nemail = dict.get('email')\nif not all([receiver, p... | <|body_start_0|>
dict = json.loads(request.body.decode())
receiver = dict.get('receiver')
province_id = dict.get('province_id')
city_id = dict.get('city_id')
district_id = dict.get('district_id')
place = dict.get('place')
mobile = dict.get('mobile')
phone ... | UpdateDestroyAddressView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateDestroyAddressView:
def put(self, request, address_id):
"""更新某一个指定的地址"""
<|body_0|>
def delete(self, request, address_id):
"""删除对应的地址"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dict = json.loads(request.body.decode())
receiver = d... | stack_v2_sparse_classes_10k_train_001501 | 22,210 | permissive | [
{
"docstring": "更新某一个指定的地址",
"name": "put",
"signature": "def put(self, request, address_id)"
},
{
"docstring": "删除对应的地址",
"name": "delete",
"signature": "def delete(self, request, address_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004003 | Implement the Python class `UpdateDestroyAddressView` described below.
Class description:
Implement the UpdateDestroyAddressView class.
Method signatures and docstrings:
- def put(self, request, address_id): 更新某一个指定的地址
- def delete(self, request, address_id): 删除对应的地址 | Implement the Python class `UpdateDestroyAddressView` described below.
Class description:
Implement the UpdateDestroyAddressView class.
Method signatures and docstrings:
- def put(self, request, address_id): 更新某一个指定的地址
- def delete(self, request, address_id): 删除对应的地址
<|skeleton|>
class UpdateDestroyAddressView:
... | e037bd86fd221e1a41a44059d148fe2f980ab0a5 | <|skeleton|>
class UpdateDestroyAddressView:
def put(self, request, address_id):
"""更新某一个指定的地址"""
<|body_0|>
def delete(self, request, address_id):
"""删除对应的地址"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UpdateDestroyAddressView:
def put(self, request, address_id):
"""更新某一个指定的地址"""
dict = json.loads(request.body.decode())
receiver = dict.get('receiver')
province_id = dict.get('province_id')
city_id = dict.get('city_id')
district_id = dict.get('district_id')
... | the_stack_v2_python_sparse | meiduo_mall/meiduo_mall/apps/users/views.py | wlyswh2010/meiduo_admin_project | train | 0 | |
a17927e3d2953aeb9956b37e9c1924ff3d06a7a1 | [
"median = raw_scores[test_key]\nscore = 0\nif 'hostconn' == test_key:\n if median > 2:\n score = 100\n elif median == 2:\n score = 50\n else:\n score = 0\nelif 'maxconn' == test_key:\n if median > 20:\n score = 100\n elif median >= 10:\n score = 50\n else:\n ... | <|body_start_0|>
median = raw_scores[test_key]
score = 0
if 'hostconn' == test_key:
if median > 2:
score = 100
elif median == 2:
score = 50
else:
score = 0
elif 'maxconn' == test_key:
if media... | CookiesTestSet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CookiesTestSet:
def GetTestScoreAndDisplayValue(self, test_key, raw_scores):
"""Get a normalized score (0 to 100) and a value to output to the display. Args: test_key: a key for a test_set test. raw_scores: a dict of raw_scores indexed by test keys. Returns: score, display_value # score ... | stack_v2_sparse_classes_10k_train_001502 | 7,631 | permissive | [
{
"docstring": "Get a normalized score (0 to 100) and a value to output to the display. Args: test_key: a key for a test_set test. raw_scores: a dict of raw_scores indexed by test keys. Returns: score, display_value # score is from 0 to 100. # display_value is the text for the cell.",
"name": "GetTestScoreA... | 2 | stack_v2_sparse_classes_30k_train_005708 | Implement the Python class `CookiesTestSet` described below.
Class description:
Implement the CookiesTestSet class.
Method signatures and docstrings:
- def GetTestScoreAndDisplayValue(self, test_key, raw_scores): Get a normalized score (0 to 100) and a value to output to the display. Args: test_key: a key for a test_... | Implement the Python class `CookiesTestSet` described below.
Class description:
Implement the CookiesTestSet class.
Method signatures and docstrings:
- def GetTestScoreAndDisplayValue(self, test_key, raw_scores): Get a normalized score (0 to 100) and a value to output to the display. Args: test_key: a key for a test_... | f0b3670d4692742d5f2e6cf605bce9b1a4b8ca1b | <|skeleton|>
class CookiesTestSet:
def GetTestScoreAndDisplayValue(self, test_key, raw_scores):
"""Get a normalized score (0 to 100) and a value to output to the display. Args: test_key: a key for a test_set test. raw_scores: a dict of raw_scores indexed by test keys. Returns: score, display_value # score ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CookiesTestSet:
def GetTestScoreAndDisplayValue(self, test_key, raw_scores):
"""Get a normalized score (0 to 100) and a value to output to the display. Args: test_key: a key for a test_set test. raw_scores: a dict of raw_scores indexed by test keys. Returns: score, display_value # score is from 0 to 1... | the_stack_v2_python_sparse | categories/cookies/test_set.py | IIKovalenko/browserscope | train | 1 | |
70a77c4b3080e362ed380a83dca79f6e3af65637 | [
"import bisect as bb\nri = [-1, -1]\ntmp_max = total = 0\ntmp_list = []\nbb.insort(tmp_list, (total, -1))\nfor i, v in enumerate(array):\n total += v\n tmp_total = total - tmp_list[0][0]\n if tmp_total > tmp_max:\n tmp_max = tmp_total\n ri[0] = tmp_list[0][1] + 1\n ri[1] = i\n bb.in... | <|body_start_0|>
import bisect as bb
ri = [-1, -1]
tmp_max = total = 0
tmp_list = []
bb.insort(tmp_list, (total, -1))
for i, v in enumerate(array):
total += v
tmp_total = total - tmp_list[0][0]
if tmp_total > tmp_max:
tm... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def kadane(self, array):
""":type array: List[int] :rtype: int"""
<|body_0|>
def kadane_2(self, array):
""":type array: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
import bisect as bb
ri = [-1, -1]
... | stack_v2_sparse_classes_10k_train_001503 | 1,498 | no_license | [
{
"docstring": ":type array: List[int] :rtype: int",
"name": "kadane",
"signature": "def kadane(self, array)"
},
{
"docstring": ":type array: List[int] :rtype: int",
"name": "kadane_2",
"signature": "def kadane_2(self, array)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kadane(self, array): :type array: List[int] :rtype: int
- def kadane_2(self, array): :type array: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kadane(self, array): :type array: List[int] :rtype: int
- def kadane_2(self, array): :type array: List[int] :rtype: int
<|skeleton|>
class Solution:
def kadane(self, ar... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def kadane(self, array):
""":type array: List[int] :rtype: int"""
<|body_0|>
def kadane_2(self, array):
""":type array: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def kadane(self, array):
""":type array: List[int] :rtype: int"""
import bisect as bb
ri = [-1, -1]
tmp_max = total = 0
tmp_list = []
bb.insort(tmp_list, (total, -1))
for i, v in enumerate(array):
total += v
tmp_total = ... | the_stack_v2_python_sparse | dp/kadane.py | vsdrun/lc_public | train | 6 | |
4161be37879990afbde90764f69d9ed3a2e2ee31 | [
"if cable not in ['straight', 'loopback']:\n raise ValueError(\"Cable can only be 'straight', or 'loopback'.\")\nsuper().__init__(mb_info, index, direction)\nself.cable = cable",
"if cable not in ['straight', 'loopback']:\n raise ValueError(\"Cable can only be 'straight', or 'loopback'.\")\nself.cable = cab... | <|body_start_0|>
if cable not in ['straight', 'loopback']:
raise ValueError("Cable can only be 'straight', or 'loopback'.")
super().__init__(mb_info, index, direction)
self.cable = cable
<|end_body_0|>
<|body_start_1|>
if cable not in ['straight', 'loopback']:
ra... | This class can be used for a cable connecting Pmod interfaces. This class inherits from the Pmod IO class. Note ---- When 2 Pmods are connected using a cable, the parameter 'cable' decides whether the cable is a 'loopback' or 'straight' cable. The default is a straight cable (no internal wire twisting). For pin mapping... | Pmod_Cable | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pmod_Cable:
"""This class can be used for a cable connecting Pmod interfaces. This class inherits from the Pmod IO class. Note ---- When 2 Pmods are connected using a cable, the parameter 'cable' decides whether the cable is a 'loopback' or 'straight' cable. The default is a straight cable (no in... | stack_v2_sparse_classes_10k_train_001504 | 3,844 | permissive | [
{
"docstring": "Return a new instance of a Cable object. Only the cable type is checked during initialization, since all the other parameters are checked by Pmod IO class. Parameters ---------- mb_info : dict A dictionary storing Microblaze information, such as the IP name and the reset name. index: int The ind... | 3 | stack_v2_sparse_classes_30k_train_000140 | Implement the Python class `Pmod_Cable` described below.
Class description:
This class can be used for a cable connecting Pmod interfaces. This class inherits from the Pmod IO class. Note ---- When 2 Pmods are connected using a cable, the parameter 'cable' decides whether the cable is a 'loopback' or 'straight' cable.... | Implement the Python class `Pmod_Cable` described below.
Class description:
This class can be used for a cable connecting Pmod interfaces. This class inherits from the Pmod IO class. Note ---- When 2 Pmods are connected using a cable, the parameter 'cable' decides whether the cable is a 'loopback' or 'straight' cable.... | de6b6fc3a803945d59f8f06523addfe0d9b60a1c | <|skeleton|>
class Pmod_Cable:
"""This class can be used for a cable connecting Pmod interfaces. This class inherits from the Pmod IO class. Note ---- When 2 Pmods are connected using a cable, the parameter 'cable' decides whether the cable is a 'loopback' or 'straight' cable. The default is a straight cable (no in... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Pmod_Cable:
"""This class can be used for a cable connecting Pmod interfaces. This class inherits from the Pmod IO class. Note ---- When 2 Pmods are connected using a cable, the parameter 'cable' decides whether the cable is a 'loopback' or 'straight' cable. The default is a straight cable (no internal wire t... | the_stack_v2_python_sparse | pynq/lib/pmod/pmod_cable.py | schelleg/PYNQ | train | 1 |
b3ea86eaca1c68187c9325ab5dd59af7ec26c478 | [
"if isinstance(key, int):\n return Packet(key)\nif key not in Packet._member_map_:\n extend_enum(Packet, key, default)\nreturn Packet[key]",
"if not (isinstance(value, int) and 0 <= value <= 127):\n raise ValueError('%r is not a valid %s' % (value, cls.__name__))\nif 5 <= value <= 15:\n extend_enum(cl... | <|body_start_0|>
if isinstance(key, int):
return Packet(key)
if key not in Packet._member_map_:
extend_enum(Packet, key, default)
return Packet[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) and 0 <= value <= 127):
raise ValueErro... | [Packet] HIP Packet Types | Packet | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Packet:
"""[Packet] HIP Packet Types"""
def get(key, default=-1):
"""Backport support for original codes."""
<|body_0|>
def _missing_(cls, value):
"""Lookup function used when value is not found."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i... | stack_v2_sparse_classes_10k_train_001505 | 2,001 | permissive | [
{
"docstring": "Backport support for original codes.",
"name": "get",
"signature": "def get(key, default=-1)"
},
{
"docstring": "Lookup function used when value is not found.",
"name": "_missing_",
"signature": "def _missing_(cls, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006961 | Implement the Python class `Packet` described below.
Class description:
[Packet] HIP Packet Types
Method signatures and docstrings:
- def get(key, default=-1): Backport support for original codes.
- def _missing_(cls, value): Lookup function used when value is not found. | Implement the Python class `Packet` described below.
Class description:
[Packet] HIP Packet Types
Method signatures and docstrings:
- def get(key, default=-1): Backport support for original codes.
- def _missing_(cls, value): Lookup function used when value is not found.
<|skeleton|>
class Packet:
"""[Packet] HI... | 71363d7948003fec88cedcf5bc80b6befa2ba244 | <|skeleton|>
class Packet:
"""[Packet] HIP Packet Types"""
def get(key, default=-1):
"""Backport support for original codes."""
<|body_0|>
def _missing_(cls, value):
"""Lookup function used when value is not found."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Packet:
"""[Packet] HIP Packet Types"""
def get(key, default=-1):
"""Backport support for original codes."""
if isinstance(key, int):
return Packet(key)
if key not in Packet._member_map_:
extend_enum(Packet, key, default)
return Packet[key]
def... | the_stack_v2_python_sparse | pcapkit/const/hip/packet.py | hiok2000/PyPCAPKit | train | 0 |
73882da4cba390e7a3e64a9e2c5552b5fc35e03b | [
"if 'user_id' not in in_data:\n in_data['user_id'] = 'us-' + str(uuid4())\nreturn in_data",
"if value:\n return pwd_context.encrypt(value)\nreturn None",
"if value:\n return int(value * 100)\nreturn None",
"if obj.budget:\n return obj.budget / 100.0\nreturn None"
] | <|body_start_0|>
if 'user_id' not in in_data:
in_data['user_id'] = 'us-' + str(uuid4())
return in_data
<|end_body_0|>
<|body_start_1|>
if value:
return pwd_context.encrypt(value)
return None
<|end_body_1|>
<|body_start_2|>
if value:
return in... | Schema to store details about a user. | UserSchema | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSchema:
"""Schema to store details about a user."""
def get_id(self, in_data: dict, **kwargs: Any) -> dict:
"""Add generated user_id."""
<|body_0|>
def get_password_hash(self, value: str) -> Optional[str]:
"""Convert password to password_hash."""
<|bo... | stack_v2_sparse_classes_10k_train_001506 | 4,600 | permissive | [
{
"docstring": "Add generated user_id.",
"name": "get_id",
"signature": "def get_id(self, in_data: dict, **kwargs: Any) -> dict"
},
{
"docstring": "Convert password to password_hash.",
"name": "get_password_hash",
"signature": "def get_password_hash(self, value: str) -> Optional[str]"
... | 4 | stack_v2_sparse_classes_30k_train_003669 | Implement the Python class `UserSchema` described below.
Class description:
Schema to store details about a user.
Method signatures and docstrings:
- def get_id(self, in_data: dict, **kwargs: Any) -> dict: Add generated user_id.
- def get_password_hash(self, value: str) -> Optional[str]: Convert password to password_... | Implement the Python class `UserSchema` described below.
Class description:
Schema to store details about a user.
Method signatures and docstrings:
- def get_id(self, in_data: dict, **kwargs: Any) -> dict: Add generated user_id.
- def get_password_hash(self, value: str) -> Optional[str]: Convert password to password_... | 822dbd3ccee25180cc48efd2f891504b6b5edc14 | <|skeleton|>
class UserSchema:
"""Schema to store details about a user."""
def get_id(self, in_data: dict, **kwargs: Any) -> dict:
"""Add generated user_id."""
<|body_0|>
def get_password_hash(self, value: str) -> Optional[str]:
"""Convert password to password_hash."""
<|bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserSchema:
"""Schema to store details about a user."""
def get_id(self, in_data: dict, **kwargs: Any) -> dict:
"""Add generated user_id."""
if 'user_id' not in in_data:
in_data['user_id'] = 'us-' + str(uuid4())
return in_data
def get_password_hash(self, value: st... | the_stack_v2_python_sparse | services/users/users/schema.py | Open-EO/openeo-eodc-driver | train | 3 |
dfda78681fe7f41c8f6aecdce8fffbffdbf9448f | [
"self.model = model\nself.feature_names = feature_names\nself.feature_types = feature_types",
"if name is None:\n name = gen_name_from_class(self)\ny = clean_dimensions(y, 'y')\nif y.ndim != 1:\n raise ValueError('y must be 1 dimensional')\nX, n_samples = preclean_X(X, self.feature_names, self.feature_types... | <|body_start_0|>
self.model = model
self.feature_names = feature_names
self.feature_types = feature_types
<|end_body_0|>
<|body_start_1|>
if name is None:
name = gen_name_from_class(self)
y = clean_dimensions(y, 'y')
if y.ndim != 1:
raise ValueErr... | Produces variety of regression metrics (including RMSE, R^2, etc). | RegressionPerf | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegressionPerf:
"""Produces variety of regression metrics (including RMSE, R^2, etc)."""
def __init__(self, model, feature_names=None, feature_types=None):
"""Initializes class. Args: model: model or prediction function of model (predict_proba for classification or predict for regres... | stack_v2_sparse_classes_10k_train_001507 | 5,223 | permissive | [
{
"docstring": "Initializes class. Args: model: model or prediction function of model (predict_proba for classification or predict for regression) feature_names: List of feature names. feature_types: List of feature types.",
"name": "__init__",
"signature": "def __init__(self, model, feature_names=None,... | 2 | stack_v2_sparse_classes_30k_train_007096 | Implement the Python class `RegressionPerf` described below.
Class description:
Produces variety of regression metrics (including RMSE, R^2, etc).
Method signatures and docstrings:
- def __init__(self, model, feature_names=None, feature_types=None): Initializes class. Args: model: model or prediction function of mode... | Implement the Python class `RegressionPerf` described below.
Class description:
Produces variety of regression metrics (including RMSE, R^2, etc).
Method signatures and docstrings:
- def __init__(self, model, feature_names=None, feature_types=None): Initializes class. Args: model: model or prediction function of mode... | e6f38ea195aecbbd9d28c7183a83c65ada16e1ae | <|skeleton|>
class RegressionPerf:
"""Produces variety of regression metrics (including RMSE, R^2, etc)."""
def __init__(self, model, feature_names=None, feature_types=None):
"""Initializes class. Args: model: model or prediction function of model (predict_proba for classification or predict for regres... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RegressionPerf:
"""Produces variety of regression metrics (including RMSE, R^2, etc)."""
def __init__(self, model, feature_names=None, feature_types=None):
"""Initializes class. Args: model: model or prediction function of model (predict_proba for classification or predict for regression) feature... | the_stack_v2_python_sparse | python/interpret-core/interpret/perf/_regression.py | interpretml/interpret | train | 3,731 |
cc11777e512aea4474ca2beb00a4b960d34830d0 | [
"self.interval = interval\nthread = threading.Thread(target=self.run, args=())\nthread.daemon = True\nthread.start()",
"while True:\n print('Doing something imporant in the background')\n time.sleep(self.interval)"
] | <|body_start_0|>
self.interval = interval
thread = threading.Thread(target=self.run, args=())
thread.daemon = True
thread.start()
<|end_body_0|>
<|body_start_1|>
while True:
print('Doing something imporant in the background')
time.sleep(self.interval)
<|e... | Threading example class The run() method will be started and it will run in the background until the application exits. | ThreadingExample | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThreadingExample:
"""Threading example class The run() method will be started and it will run in the background until the application exits."""
def __init__(self, interval=1):
"""Constructor :type interval: int :param interval: Check interval, in seconds"""
<|body_0|>
de... | stack_v2_sparse_classes_10k_train_001508 | 911 | permissive | [
{
"docstring": "Constructor :type interval: int :param interval: Check interval, in seconds",
"name": "__init__",
"signature": "def __init__(self, interval=1)"
},
{
"docstring": "Method that runs forever",
"name": "run",
"signature": "def run(self)"
}
] | 2 | null | Implement the Python class `ThreadingExample` described below.
Class description:
Threading example class The run() method will be started and it will run in the background until the application exits.
Method signatures and docstrings:
- def __init__(self, interval=1): Constructor :type interval: int :param interval:... | Implement the Python class `ThreadingExample` described below.
Class description:
Threading example class The run() method will be started and it will run in the background until the application exits.
Method signatures and docstrings:
- def __init__(self, interval=1): Constructor :type interval: int :param interval:... | 665d39a2bd82543d5196555f0801ef8fd4a3ee48 | <|skeleton|>
class ThreadingExample:
"""Threading example class The run() method will be started and it will run in the background until the application exits."""
def __init__(self, interval=1):
"""Constructor :type interval: int :param interval: Check interval, in seconds"""
<|body_0|>
de... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ThreadingExample:
"""Threading example class The run() method will be started and it will run in the background until the application exits."""
def __init__(self, interval=1):
"""Constructor :type interval: int :param interval: Check interval, in seconds"""
self.interval = interval
... | the_stack_v2_python_sparse | all-gists/832219525541e059aefa/snippet.py | gistable/gistable | train | 76 |
1f47d79c34b7204bef6f06bcdccec706ff4c6a8d | [
"blacklist = ['', None, '-']\nif value in blacklist:\n return\nelif type(value) == tuple and len(value) == 2 and (value[1] == True):\n self.__dict__[name] = value[0]\nelse:\n if type(value) == str:\n value = value.replace(\"'\", '')\n self.__dict__[name] = value",
"variableNames = [key for key ... | <|body_start_0|>
blacklist = ['', None, '-']
if value in blacklist:
return
elif type(value) == tuple and len(value) == 2 and (value[1] == True):
self.__dict__[name] = value[0]
else:
if type(value) == str:
value = value.replace("'", '')
... | Main | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Main:
def __setattr__(self, name, value):
"""Function doesnt set value if it is in blacklist"""
<|body_0|>
def insertQuery(self):
"""Function returns INSERT query with its class variables"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
blacklist = [... | stack_v2_sparse_classes_10k_train_001509 | 5,468 | permissive | [
{
"docstring": "Function doesnt set value if it is in blacklist",
"name": "__setattr__",
"signature": "def __setattr__(self, name, value)"
},
{
"docstring": "Function returns INSERT query with its class variables",
"name": "insertQuery",
"signature": "def insertQuery(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000704 | Implement the Python class `Main` described below.
Class description:
Implement the Main class.
Method signatures and docstrings:
- def __setattr__(self, name, value): Function doesnt set value if it is in blacklist
- def insertQuery(self): Function returns INSERT query with its class variables | Implement the Python class `Main` described below.
Class description:
Implement the Main class.
Method signatures and docstrings:
- def __setattr__(self, name, value): Function doesnt set value if it is in blacklist
- def insertQuery(self): Function returns INSERT query with its class variables
<|skeleton|>
class Ma... | c296af4934c9e70ce56ccdb23c5998e2d8418cab | <|skeleton|>
class Main:
def __setattr__(self, name, value):
"""Function doesnt set value if it is in blacklist"""
<|body_0|>
def insertQuery(self):
"""Function returns INSERT query with its class variables"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Main:
def __setattr__(self, name, value):
"""Function doesnt set value if it is in blacklist"""
blacklist = ['', None, '-']
if value in blacklist:
return
elif type(value) == tuple and len(value) == 2 and (value[1] == True):
self.__dict__[name] = value[0]... | the_stack_v2_python_sparse | web-app/generate_random_patients.py | sandbernar/corona-prod | train | 0 | |
c5ae46f540fcd83f656bdecc2373f998a1158310 | [
"self.epsilon = epsilon\nself.epsilon_decay = epsilon_decay\nself.epsilon_min = epsilon_min\nself.possible_actions = possible_actions\nself.continuous = continuous",
"if self.epsilon < self.epsilon_min:\n self.epsilon = self.epsilon_min\nif random.random() < self.epsilon:\n return True\nreturn False",
"se... | <|body_start_0|>
self.epsilon = epsilon
self.epsilon_decay = epsilon_decay
self.epsilon_min = epsilon_min
self.possible_actions = possible_actions
self.continuous = continuous
<|end_body_0|>
<|body_start_1|>
if self.epsilon < self.epsilon_min:
self.epsilon = ... | An implementation of epsilon greedy exploration. Epsilon greedy exploration selects an explorative action with probability epsilon at each step. The value of epsilon decays at a rate 'epsilon_decay', until it hits the minimum value of 'epsilon_min' | EpsilonGreedyExplorer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EpsilonGreedyExplorer:
"""An implementation of epsilon greedy exploration. Epsilon greedy exploration selects an explorative action with probability epsilon at each step. The value of epsilon decays at a rate 'epsilon_decay', until it hits the minimum value of 'epsilon_min'"""
def __init__(s... | stack_v2_sparse_classes_10k_train_001510 | 1,590 | no_license | [
{
"docstring": "Initialises the parameters for the explorer",
"name": "__init__",
"signature": "def __init__(self, possible_actions, continuous=False, epsilon=0.1, epsilon_decay=0, epsilon_min=0.1)"
},
{
"docstring": "Determines whether or not to explore in the current time step by comparing eps... | 3 | stack_v2_sparse_classes_30k_train_007099 | Implement the Python class `EpsilonGreedyExplorer` described below.
Class description:
An implementation of epsilon greedy exploration. Epsilon greedy exploration selects an explorative action with probability epsilon at each step. The value of epsilon decays at a rate 'epsilon_decay', until it hits the minimum value ... | Implement the Python class `EpsilonGreedyExplorer` described below.
Class description:
An implementation of epsilon greedy exploration. Epsilon greedy exploration selects an explorative action with probability epsilon at each step. The value of epsilon decays at a rate 'epsilon_decay', until it hits the minimum value ... | 6dfb342efda4c5ae0dff72bb132a6ce12fbfd8b8 | <|skeleton|>
class EpsilonGreedyExplorer:
"""An implementation of epsilon greedy exploration. Epsilon greedy exploration selects an explorative action with probability epsilon at each step. The value of epsilon decays at a rate 'epsilon_decay', until it hits the minimum value of 'epsilon_min'"""
def __init__(s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EpsilonGreedyExplorer:
"""An implementation of epsilon greedy exploration. Epsilon greedy exploration selects an explorative action with probability epsilon at each step. The value of epsilon decays at a rate 'epsilon_decay', until it hits the minimum value of 'epsilon_min'"""
def __init__(self, possible... | the_stack_v2_python_sparse | Software/Agents/Policies/Explorers/EpsilonGreedyExplorer.py | meelement/ArtificialIntelligence | train | 0 |
7518ec57cee1db9011db43c2edee61b1aaee2e03 | [
"if registration_enabled():\n return super().is_open_for_signup(request, *args, **kwargs)\nreturn False",
"mail_restriction = InvenTreeSetting.get_setting('LOGIN_SIGNUP_MAIL_RESTRICTION', None)\nif not mail_restriction:\n return super().clean_email(email)\nsplit_email = email.split('@')\nif len(split_email)... | <|body_start_0|>
if registration_enabled():
return super().is_open_for_signup(request, *args, **kwargs)
return False
<|end_body_0|>
<|body_start_1|>
mail_restriction = InvenTreeSetting.get_setting('LOGIN_SIGNUP_MAIL_RESTRICTION', None)
if not mail_restriction:
re... | Mixin to check if registration should be enabled. | RegistratonMixin | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegistratonMixin:
"""Mixin to check if registration should be enabled."""
def is_open_for_signup(self, request, *args, **kwargs):
"""Check if signup is enabled in settings. Configure the class variable `REGISTRATION_SETTING` to set which setting should be used, default: `LOGIN_ENABLE... | stack_v2_sparse_classes_10k_train_001511 | 12,546 | permissive | [
{
"docstring": "Check if signup is enabled in settings. Configure the class variable `REGISTRATION_SETTING` to set which setting should be used, default: `LOGIN_ENABLE_REG`.",
"name": "is_open_for_signup",
"signature": "def is_open_for_signup(self, request, *args, **kwargs)"
},
{
"docstring": "C... | 3 | null | Implement the Python class `RegistratonMixin` described below.
Class description:
Mixin to check if registration should be enabled.
Method signatures and docstrings:
- def is_open_for_signup(self, request, *args, **kwargs): Check if signup is enabled in settings. Configure the class variable `REGISTRATION_SETTING` to... | Implement the Python class `RegistratonMixin` described below.
Class description:
Mixin to check if registration should be enabled.
Method signatures and docstrings:
- def is_open_for_signup(self, request, *args, **kwargs): Check if signup is enabled in settings. Configure the class variable `REGISTRATION_SETTING` to... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class RegistratonMixin:
"""Mixin to check if registration should be enabled."""
def is_open_for_signup(self, request, *args, **kwargs):
"""Check if signup is enabled in settings. Configure the class variable `REGISTRATION_SETTING` to set which setting should be used, default: `LOGIN_ENABLE... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RegistratonMixin:
"""Mixin to check if registration should be enabled."""
def is_open_for_signup(self, request, *args, **kwargs):
"""Check if signup is enabled in settings. Configure the class variable `REGISTRATION_SETTING` to set which setting should be used, default: `LOGIN_ENABLE_REG`."""
... | the_stack_v2_python_sparse | InvenTree/InvenTree/forms.py | inventree/InvenTree | train | 3,077 |
816e186e6055271ac2835763078c42f718656f02 | [
"if filters is None:\n filters = {}\norm_filters = super(SpecialResource, self).build_filters(filters)\nquery = filters.get('q')\ncategory_pk = filters.get('catpk')\nif query is not None:\n sqs = SearchQuerySet().models(Special).load_all().auto_query(query)\n orm_filters['pk__in'] = [i.pk for i in sqs]\nif... | <|body_start_0|>
if filters is None:
filters = {}
orm_filters = super(SpecialResource, self).build_filters(filters)
query = filters.get('q')
category_pk = filters.get('catpk')
if query is not None:
sqs = SearchQuerySet().models(Special).load_all().auto_que... | SpecialResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpecialResource:
def build_filters(self, filters=None):
"""Custom filters used for category and searching."""
<|body_0|>
def dehydrate(self, bundle):
"""If idonly is specified as a flag, the bundle will be reduced to just the resource id."""
<|body_1|>
<|end... | stack_v2_sparse_classes_10k_train_001512 | 1,770 | no_license | [
{
"docstring": "Custom filters used for category and searching.",
"name": "build_filters",
"signature": "def build_filters(self, filters=None)"
},
{
"docstring": "If idonly is specified as a flag, the bundle will be reduced to just the resource id.",
"name": "dehydrate",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_train_003106 | Implement the Python class `SpecialResource` described below.
Class description:
Implement the SpecialResource class.
Method signatures and docstrings:
- def build_filters(self, filters=None): Custom filters used for category and searching.
- def dehydrate(self, bundle): If idonly is specified as a flag, the bundle w... | Implement the Python class `SpecialResource` described below.
Class description:
Implement the SpecialResource class.
Method signatures and docstrings:
- def build_filters(self, filters=None): Custom filters used for category and searching.
- def dehydrate(self, bundle): If idonly is specified as a flag, the bundle w... | 3ed85e856a026001a1d91d09d31d944c64704824 | <|skeleton|>
class SpecialResource:
def build_filters(self, filters=None):
"""Custom filters used for category and searching."""
<|body_0|>
def dehydrate(self, bundle):
"""If idonly is specified as a flag, the bundle will be reduced to just the resource id."""
<|body_1|>
<|end... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SpecialResource:
def build_filters(self, filters=None):
"""Custom filters used for category and searching."""
if filters is None:
filters = {}
orm_filters = super(SpecialResource, self).build_filters(filters)
query = filters.get('q')
category_pk = filters.ge... | the_stack_v2_python_sparse | scenable/specials/api.py | gregarious/betasite | train | 0 | |
dc5ede1c14d55a3946c904f5acf7db914fc1e712 | [
"if not head or not head.next or (not head.next.next):\n return\nhead2 = self.findMid(head)\nhead2 = self.reverseList(head2)\nself.zigZagMerge(head, head2)",
"slow, fast = (head, head.next)\nwhile fast:\n slow = slow.next\n fast = fast.next.next if fast.next else None\nhead2, slow.next = (slow.next, None... | <|body_start_0|>
if not head or not head.next or (not head.next.next):
return
head2 = self.findMid(head)
head2 = self.reverseList(head2)
self.zigZagMerge(head, head2)
<|end_body_0|>
<|body_start_1|>
slow, fast = (head, head.next)
while fast:
slow ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reorderList(self, head):
""":type head: ListNode :rtype: None Do not return anything, modify head in-place instead."""
<|body_0|>
def findMid(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
def reverseList(self, head):
... | stack_v2_sparse_classes_10k_train_001513 | 2,938 | no_license | [
{
"docstring": ":type head: ListNode :rtype: None Do not return anything, modify head in-place instead.",
"name": "reorderList",
"signature": "def reorderList(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "findMid",
"signature": "def findMid(self, head)"... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reorderList(self, head): :type head: ListNode :rtype: None Do not return anything, modify head in-place instead.
- def findMid(self, head): :type head: ListNode :rtype: ListN... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reorderList(self, head): :type head: ListNode :rtype: None Do not return anything, modify head in-place instead.
- def findMid(self, head): :type head: ListNode :rtype: ListN... | 3d9e0ad2f6ed92ec969556f75d97c51ea4854719 | <|skeleton|>
class Solution:
def reorderList(self, head):
""":type head: ListNode :rtype: None Do not return anything, modify head in-place instead."""
<|body_0|>
def findMid(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
def reverseList(self, head):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def reorderList(self, head):
""":type head: ListNode :rtype: None Do not return anything, modify head in-place instead."""
if not head or not head.next or (not head.next.next):
return
head2 = self.findMid(head)
head2 = self.reverseList(head2)
self.... | the_stack_v2_python_sparse | Solutions/0143_reorderList.py | YoupengLi/leetcode-sorting | train | 3 | |
73039ce8069918e0f2192da82ae9276e38581553 | [
"if dtype not in NUMERIC_TYPES:\n raise ValueError(\"invalid numeric type '{}'\".format(dtype))\nsuper(Numeric, self).__init__(dtype=dtype, name=name, index=index, label=label, help=help, default=default, required=required, group=group)\nself.constraint = constraint",
"if value in ['-inf', 'inf']:\n value =... | <|body_start_0|>
if dtype not in NUMERIC_TYPES:
raise ValueError("invalid numeric type '{}'".format(dtype))
super(Numeric, self).__init__(dtype=dtype, name=name, index=index, label=label, help=help, default=default, required=required, group=group)
self.constraint = constraint
<|end_b... | Base class for numeric parameter types. Extends the base class with an optional range constraint. | Numeric | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Numeric:
"""Base class for numeric parameter types. Extends the base class with an optional range constraint."""
def __init__(self, dtype: str, name: str, index: Optional[int]=0, label: Optional[str]=None, help: Optional[str]=None, default: Optional[Union[int, float]]=None, required: Optiona... | stack_v2_sparse_classes_10k_train_001514 | 16,105 | permissive | [
{
"docstring": "Initialize the base properties for a numeric parameter declaration. Parameters ---------- dtype: string Parameter type identifier. name: string Unique parameter identifier index: int Index position of the parameter (for display purposes). label: string Human-readable parameter name. help: string... | 4 | stack_v2_sparse_classes_30k_train_002965 | Implement the Python class `Numeric` described below.
Class description:
Base class for numeric parameter types. Extends the base class with an optional range constraint.
Method signatures and docstrings:
- def __init__(self, dtype: str, name: str, index: Optional[int]=0, label: Optional[str]=None, help: Optional[str... | Implement the Python class `Numeric` described below.
Class description:
Base class for numeric parameter types. Extends the base class with an optional range constraint.
Method signatures and docstrings:
- def __init__(self, dtype: str, name: str, index: Optional[int]=0, label: Optional[str]=None, help: Optional[str... | 7116b7060aa68ab36bf08e6393be166dc5db955f | <|skeleton|>
class Numeric:
"""Base class for numeric parameter types. Extends the base class with an optional range constraint."""
def __init__(self, dtype: str, name: str, index: Optional[int]=0, label: Optional[str]=None, help: Optional[str]=None, default: Optional[Union[int, float]]=None, required: Optiona... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Numeric:
"""Base class for numeric parameter types. Extends the base class with an optional range constraint."""
def __init__(self, dtype: str, name: str, index: Optional[int]=0, label: Optional[str]=None, help: Optional[str]=None, default: Optional[Union[int, float]]=None, required: Optional[bool]=False... | the_stack_v2_python_sparse | flowserv/model/parameter/numeric.py | anrunw/flowserv-core-1 | train | 0 |
3c83ab4713119336ab3daa4880399cc30acf5f05 | [
"fd_mock = mock.mock_open()\nargs = ['script_name', 'gtest', '--test-exe=out_eve/Release/base_unittests', '--board=eve', '--path-to-outdir=out_eve/Release', '--use-vm' if use_vm else '--device=localhost:2222']\nif stop_ui:\n args.append('--stop-ui')\nwith mock.patch.object(sys, 'argv', args), mock.patch.object(t... | <|body_start_0|>
fd_mock = mock.mock_open()
args = ['script_name', 'gtest', '--test-exe=out_eve/Release/base_unittests', '--board=eve', '--path-to-outdir=out_eve/Release', '--use-vm' if use_vm else '--device=localhost:2222']
if stop_ui:
args.append('--stop-ui')
with mock.patc... | GTestTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GTestTest:
def test_gtest(self, use_vm, stop_ui):
"""Tests running a gtest."""
<|body_0|>
def test_gtest_with_vpython(self):
"""Tests building a gtest with --vpython-dir."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
fd_mock = mock.mock_open()
... | stack_v2_sparse_classes_10k_train_001515 | 12,985 | permissive | [
{
"docstring": "Tests running a gtest.",
"name": "test_gtest",
"signature": "def test_gtest(self, use_vm, stop_ui)"
},
{
"docstring": "Tests building a gtest with --vpython-dir.",
"name": "test_gtest_with_vpython",
"signature": "def test_gtest_with_vpython(self)"
}
] | 2 | null | Implement the Python class `GTestTest` described below.
Class description:
Implement the GTestTest class.
Method signatures and docstrings:
- def test_gtest(self, use_vm, stop_ui): Tests running a gtest.
- def test_gtest_with_vpython(self): Tests building a gtest with --vpython-dir. | Implement the Python class `GTestTest` described below.
Class description:
Implement the GTestTest class.
Method signatures and docstrings:
- def test_gtest(self, use_vm, stop_ui): Tests running a gtest.
- def test_gtest_with_vpython(self): Tests building a gtest with --vpython-dir.
<|skeleton|>
class GTestTest:
... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class GTestTest:
def test_gtest(self, use_vm, stop_ui):
"""Tests running a gtest."""
<|body_0|>
def test_gtest_with_vpython(self):
"""Tests building a gtest with --vpython-dir."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GTestTest:
def test_gtest(self, use_vm, stop_ui):
"""Tests running a gtest."""
fd_mock = mock.mock_open()
args = ['script_name', 'gtest', '--test-exe=out_eve/Release/base_unittests', '--board=eve', '--path-to-outdir=out_eve/Release', '--use-vm' if use_vm else '--device=localhost:2222']... | the_stack_v2_python_sparse | build/chromeos/test_runner_test.py | chromium/chromium | train | 17,408 | |
2e9fd050211c7e0d9ffa6160a971028a8cf8baa1 | [
"self.xd = kwargs['xd']\nself.skip_days = 0\nself.factor_name = '{}:{}'.format(self.__class__.__name__, self.xd)\nself.hit_ml = kwargs['hit_ml']",
"ump = self.ump_manger\ndeg_hit_cnt = ump.ump_main_deg.predict_hit_kwargs(**ml_feature_dict)\njump_hit_cnt = ump.ump_main_jump.predict_hit_kwargs(**ml_feature_dict)\nw... | <|body_start_0|>
self.xd = kwargs['xd']
self.skip_days = 0
self.factor_name = '{}:{}'.format(self.__class__.__name__, self.xd)
self.hit_ml = kwargs['hit_ml']
<|end_body_0|>
<|body_start_1|>
ump = self.ump_manger
deg_hit_cnt = ump.ump_main_deg.predict_hit_kwargs(**ml_feat... | 继续继承AbuFactorBuyBreak复写make_ump_block_decision， 区别是使用AbuFactorBuyBreakReocrdHitDemo的学习成果hit_ml 对几个裁判这次交易命中的分类簇个数组成矢量特征进行predict， 拦截预测结果为-1的交易 | AbuFactorBuyBreakHitPredictDemo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbuFactorBuyBreakHitPredictDemo:
"""继续继承AbuFactorBuyBreak复写make_ump_block_decision， 区别是使用AbuFactorBuyBreakReocrdHitDemo的学习成果hit_ml 对几个裁判这次交易命中的分类簇个数组成矢量特征进行predict， 拦截预测结果为-1的交易"""
def _init_self(self, **kwargs):
"""与AbuFactorBuyBreak基本相同，唯一区别是关键子参数中添加了通过AbuFactorBuyBreakUmpDemo记录训练好... | stack_v2_sparse_classes_10k_train_001516 | 9,900 | no_license | [
{
"docstring": "与AbuFactorBuyBreak基本相同，唯一区别是关键子参数中添加了通过AbuFactorBuyBreakUmpDemo记录训练好的决策器 self.hit_ml = kwargs['hit_ml']",
"name": "_init_self",
"signature": "def _init_self(self, **kwargs)"
},
{
"docstring": "用回测的数据进行训练后再次反过来指导回测，结果是没有意义的， 这里的示例只是为了容易理解什么叫做：让裁判自己学习怎么配合， 自己做出最正确的判断，更详细完整的示例会在之后的章... | 2 | stack_v2_sparse_classes_30k_train_000296 | Implement the Python class `AbuFactorBuyBreakHitPredictDemo` described below.
Class description:
继续继承AbuFactorBuyBreak复写make_ump_block_decision， 区别是使用AbuFactorBuyBreakReocrdHitDemo的学习成果hit_ml 对几个裁判这次交易命中的分类簇个数组成矢量特征进行predict， 拦截预测结果为-1的交易
Method signatures and docstrings:
- def _init_self(self, **kwargs): 与AbuFactorB... | Implement the Python class `AbuFactorBuyBreakHitPredictDemo` described below.
Class description:
继续继承AbuFactorBuyBreak复写make_ump_block_decision， 区别是使用AbuFactorBuyBreakReocrdHitDemo的学习成果hit_ml 对几个裁判这次交易命中的分类簇个数组成矢量特征进行predict， 拦截预测结果为-1的交易
Method signatures and docstrings:
- def _init_self(self, **kwargs): 与AbuFactorB... | f00a070626407afe87763a50c99241696a38df46 | <|skeleton|>
class AbuFactorBuyBreakHitPredictDemo:
"""继续继承AbuFactorBuyBreak复写make_ump_block_decision， 区别是使用AbuFactorBuyBreakReocrdHitDemo的学习成果hit_ml 对几个裁判这次交易命中的分类簇个数组成矢量特征进行predict， 拦截预测结果为-1的交易"""
def _init_self(self, **kwargs):
"""与AbuFactorBuyBreak基本相同，唯一区别是关键子参数中添加了通过AbuFactorBuyBreakUmpDemo记录训练好... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AbuFactorBuyBreakHitPredictDemo:
"""继续继承AbuFactorBuyBreak复写make_ump_block_decision， 区别是使用AbuFactorBuyBreakReocrdHitDemo的学习成果hit_ml 对几个裁判这次交易命中的分类簇个数组成矢量特征进行predict， 拦截预测结果为-1的交易"""
def _init_self(self, **kwargs):
"""与AbuFactorBuyBreak基本相同，唯一区别是关键子参数中添加了通过AbuFactorBuyBreakUmpDemo记录训练好的决策器 self.hit... | the_stack_v2_python_sparse | abupy/FactorBuyBu/ABuFactorBuyDemo.py | zly111/abu | train | 1 |
2bca047ba68a6efe9e91ac2fcfce1f65f58b554f | [
"positive_mask = (input_img > 0).type_as(input_img)\noutput = torch.addcmul(torch.zeros(input_img.size()).type_as(input_img), input_img, positive_mask)\nself.save_for_backward(input_img, output)\nreturn output",
"input_img, output = self.saved_tensors\npositive_mask_1 = (input_img > 0).type_as(grad_output)\nposit... | <|body_start_0|>
positive_mask = (input_img > 0).type_as(input_img)
output = torch.addcmul(torch.zeros(input_img.size()).type_as(input_img), input_img, positive_mask)
self.save_for_backward(input_img, output)
return output
<|end_body_0|>
<|body_start_1|>
input_img, output = self... | GuidedBackPropReLU | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GuidedBackPropReLU:
def forward(self, input_img):
""":param self: :param input_img: :return:"""
<|body_0|>
def backward(self, grad_output):
""":param self: :param grad_output: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
positive_mask = ... | stack_v2_sparse_classes_10k_train_001517 | 2,971 | permissive | [
{
"docstring": ":param self: :param input_img: :return:",
"name": "forward",
"signature": "def forward(self, input_img)"
},
{
"docstring": ":param self: :param grad_output: :return:",
"name": "backward",
"signature": "def backward(self, grad_output)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004925 | Implement the Python class `GuidedBackPropReLU` described below.
Class description:
Implement the GuidedBackPropReLU class.
Method signatures and docstrings:
- def forward(self, input_img): :param self: :param input_img: :return:
- def backward(self, grad_output): :param self: :param grad_output: :return: | Implement the Python class `GuidedBackPropReLU` described below.
Class description:
Implement the GuidedBackPropReLU class.
Method signatures and docstrings:
- def forward(self, input_img): :param self: :param input_img: :return:
- def backward(self, grad_output): :param self: :param grad_output: :return:
<|skeleton... | 94a402cab47a2bd6241608308371490079af4d53 | <|skeleton|>
class GuidedBackPropReLU:
def forward(self, input_img):
""":param self: :param input_img: :return:"""
<|body_0|>
def backward(self, grad_output):
""":param self: :param grad_output: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GuidedBackPropReLU:
def forward(self, input_img):
""":param self: :param input_img: :return:"""
positive_mask = (input_img > 0).type_as(input_img)
output = torch.addcmul(torch.zeros(input_img.size()).type_as(input_img), input_img, positive_mask)
self.save_for_backward(input_img... | the_stack_v2_python_sparse | draugr/torch_utilities/optimisation/debugging/gradients/guided.py | cnheider/draugr | train | 4 | |
64c205c66879ce9b153b5476d91bacf986692feb | [
"super().__init__()\nself.register_buffer('support', torch.linspace(vmin, vmax, n_atoms))\nself.fc1 = nn.Linear(state_size, 256)\nself.fc2 = nn.Linear(256 + action_size, 256)\nself.fc3 = nn.Linear(256, 128)\nself.fc4 = nn.Linear(128, n_atoms)",
"x = F.leaky_relu(self.fc1(state))\nx = torch.cat([x, action], dim=1)... | <|body_start_0|>
super().__init__()
self.register_buffer('support', torch.linspace(vmin, vmax, n_atoms))
self.fc1 = nn.Linear(state_size, 256)
self.fc2 = nn.Linear(256 + action_size, 256)
self.fc3 = nn.Linear(256, 128)
self.fc4 = nn.Linear(128, n_atoms)
<|end_body_0|>
<|... | Distributional Value Model | Critic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Critic:
"""Distributional Value Model"""
def __init__(self, state_size, action_size, vmin, vmax, n_atoms=51):
"""Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size : int Dimension of each action vmin, vmax : float Upper &... | stack_v2_sparse_classes_10k_train_001518 | 2,383 | no_license | [
{
"docstring": "Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size : int Dimension of each action vmin, vmax : float Upper & Lower bounds of the support n_atoms : int Number of bins in the support",
"name": "__init__",
"signature": "def __in... | 2 | stack_v2_sparse_classes_30k_train_002994 | Implement the Python class `Critic` described below.
Class description:
Distributional Value Model
Method signatures and docstrings:
- def __init__(self, state_size, action_size, vmin, vmax, n_atoms=51): Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size ... | Implement the Python class `Critic` described below.
Class description:
Distributional Value Model
Method signatures and docstrings:
- def __init__(self, state_size, action_size, vmin, vmax, n_atoms=51): Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size ... | f6d450e0c68236bf493689bffef48a0f3723416d | <|skeleton|>
class Critic:
"""Distributional Value Model"""
def __init__(self, state_size, action_size, vmin, vmax, n_atoms=51):
"""Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size : int Dimension of each action vmin, vmax : float Upper &... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Critic:
"""Distributional Value Model"""
def __init__(self, state_size, action_size, vmin, vmax, n_atoms=51):
"""Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size : int Dimension of each action vmin, vmax : float Upper & Lower bounds... | the_stack_v2_python_sparse | drlnd/p2_continuous-control/control/model.py | jkorge/udacity | train | 0 |
4ece046735739e3557e9a59bdccd0629bd8648e8 | [
"Canvas.__init__(self)\nself.configure(width=larg, height=haut)\nself.boss = boss\nself.larg = larg\nself.haut = haut\npas = (larg - 25) / 8\nfor t in range(0, 9):\n stx = 10 + t * pas\n self.create_line(stx, haut - 12, stx, 15, fill='grey')\npas = (haut - 25) / 10\nfor t in range(-5, 6):\n sty = haut / 2 ... | <|body_start_0|>
Canvas.__init__(self)
self.configure(width=larg, height=haut)
self.boss = boss
self.larg = larg
self.haut = haut
pas = (larg - 25) / 8
for t in range(0, 9):
stx = 10 + t * pas
self.create_line(stx, haut - 12, stx, 15, fill=... | Canevas pour le dessin de courbes élongation/temps | OscilloGraphe | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OscilloGraphe:
"""Canevas pour le dessin de courbes élongation/temps"""
def __init__(self, boss=None, larg=400, haut=350):
"""Constructeur du graphique : axes et échelle horizontale"""
<|body_0|>
def axes(self):
"""Création des axes de références"""
<|bod... | stack_v2_sparse_classes_10k_train_001519 | 3,176 | no_license | [
{
"docstring": "Constructeur du graphique : axes et échelle horizontale",
"name": "__init__",
"signature": "def __init__(self, boss=None, larg=400, haut=350)"
},
{
"docstring": "Création des axes de références",
"name": "axes",
"signature": "def axes(self)"
},
{
"docstring": "Tra... | 3 | stack_v2_sparse_classes_30k_train_004409 | Implement the Python class `OscilloGraphe` described below.
Class description:
Canevas pour le dessin de courbes élongation/temps
Method signatures and docstrings:
- def __init__(self, boss=None, larg=400, haut=350): Constructeur du graphique : axes et échelle horizontale
- def axes(self): Création des axes de référe... | Implement the Python class `OscilloGraphe` described below.
Class description:
Canevas pour le dessin de courbes élongation/temps
Method signatures and docstrings:
- def __init__(self, boss=None, larg=400, haut=350): Constructeur du graphique : axes et échelle horizontale
- def axes(self): Création des axes de référe... | 14b306447e227ddc5cb04b8819f388ca9f91a1d6 | <|skeleton|>
class OscilloGraphe:
"""Canevas pour le dessin de courbes élongation/temps"""
def __init__(self, boss=None, larg=400, haut=350):
"""Constructeur du graphique : axes et échelle horizontale"""
<|body_0|>
def axes(self):
"""Création des axes de références"""
<|bod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OscilloGraphe:
"""Canevas pour le dessin de courbes élongation/temps"""
def __init__(self, boss=None, larg=400, haut=350):
"""Constructeur du graphique : axes et échelle horizontale"""
Canvas.__init__(self)
self.configure(width=larg, height=haut)
self.boss = boss
s... | the_stack_v2_python_sparse | Course/Book/Programmer_avec_Python3/13-ClasseEtInterfacesGraphiques/oscillo.py | BjaouiAya/Cours-Python | train | 0 |
15774ba744ea6456b49bca281a0da434323ca343 | [
"firebase_token = self.get_token(request)\nif firebase_token is None:\n return None\ntry:\n payload = auth.verify_id_token(firebase_token)\nexcept ValueError:\n msg = _('Signature has expired.')\n raise exceptions.AuthenticationFailed(msg)\nexcept auth.AuthError:\n msg = _('Could not log in.')\n r... | <|body_start_0|>
firebase_token = self.get_token(request)
if firebase_token is None:
return None
try:
payload = auth.verify_id_token(firebase_token)
except ValueError:
msg = _('Signature has expired.')
raise exceptions.AuthenticationFailed(... | Token based authentication using firebase. | BaseFirebaseuthentication | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseFirebaseuthentication:
"""Token based authentication using firebase."""
def authenticate(self, request):
"""Returns a two-tuple of `User` and token if a valid signature has been supplied using Firebase authentication. Otherwise returns `None`."""
<|body_0|>
def authe... | stack_v2_sparse_classes_10k_train_001520 | 5,651 | no_license | [
{
"docstring": "Returns a two-tuple of `User` and token if a valid signature has been supplied using Firebase authentication. Otherwise returns `None`.",
"name": "authenticate",
"signature": "def authenticate(self, request)"
},
{
"docstring": "Returns an active user that matches the payload's us... | 2 | stack_v2_sparse_classes_30k_train_007274 | Implement the Python class `BaseFirebaseuthentication` described below.
Class description:
Token based authentication using firebase.
Method signatures and docstrings:
- def authenticate(self, request): Returns a two-tuple of `User` and token if a valid signature has been supplied using Firebase authentication. Other... | Implement the Python class `BaseFirebaseuthentication` described below.
Class description:
Token based authentication using firebase.
Method signatures and docstrings:
- def authenticate(self, request): Returns a two-tuple of `User` and token if a valid signature has been supplied using Firebase authentication. Other... | 5714b02deb0acc8fa185eb02bd6b561e2f5f185e | <|skeleton|>
class BaseFirebaseuthentication:
"""Token based authentication using firebase."""
def authenticate(self, request):
"""Returns a two-tuple of `User` and token if a valid signature has been supplied using Firebase authentication. Otherwise returns `None`."""
<|body_0|>
def authe... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BaseFirebaseuthentication:
"""Token based authentication using firebase."""
def authenticate(self, request):
"""Returns a two-tuple of `User` and token if a valid signature has been supplied using Firebase authentication. Otherwise returns `None`."""
firebase_token = self.get_token(reques... | the_stack_v2_python_sparse | user_repo3/user_management/authentication.py | jyothinaidu/user_management | train | 1 |
e405d7988a62c1d40b8c40719db965e35556ad29 | [
"super(VGG16, self).__init__()\nself.vgg16_feature_extractor = VGG16FeatureExtraction(weights_update=True)\nself.max_pool = nn.MaxPool2d(kernel_size=2, stride=2)\nself.classifier = VGG16Classfier()\nself.fc3 = _fc(in_channels=4096, out_channels=num_classes)",
"feature_maps = self.vgg16_feature_extractor(x)\nx = s... | <|body_start_0|>
super(VGG16, self).__init__()
self.vgg16_feature_extractor = VGG16FeatureExtraction(weights_update=True)
self.max_pool = nn.MaxPool2d(kernel_size=2, stride=2)
self.classifier = VGG16Classfier()
self.fc3 = _fc(in_channels=4096, out_channels=num_classes)
<|end_body... | VGG16 | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VGG16:
def __init__(self, num_classes):
"""VGG16 construct for training backbone"""
<|body_0|>
def construct(self, x):
""":param x: shape=(B, 3, 224, 224) :return: logits, shape=(B, 1000)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(VGG16, ... | stack_v2_sparse_classes_10k_train_001521 | 5,998 | permissive | [
{
"docstring": "VGG16 construct for training backbone",
"name": "__init__",
"signature": "def __init__(self, num_classes)"
},
{
"docstring": ":param x: shape=(B, 3, 224, 224) :return: logits, shape=(B, 1000)",
"name": "construct",
"signature": "def construct(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006384 | Implement the Python class `VGG16` described below.
Class description:
Implement the VGG16 class.
Method signatures and docstrings:
- def __init__(self, num_classes): VGG16 construct for training backbone
- def construct(self, x): :param x: shape=(B, 3, 224, 224) :return: logits, shape=(B, 1000) | Implement the Python class `VGG16` described below.
Class description:
Implement the VGG16 class.
Method signatures and docstrings:
- def __init__(self, num_classes): VGG16 construct for training backbone
- def construct(self, x): :param x: shape=(B, 3, 224, 224) :return: logits, shape=(B, 1000)
<|skeleton|>
class V... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class VGG16:
def __init__(self, num_classes):
"""VGG16 construct for training backbone"""
<|body_0|>
def construct(self, x):
""":param x: shape=(B, 3, 224, 224) :return: logits, shape=(B, 1000)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VGG16:
def __init__(self, num_classes):
"""VGG16 construct for training backbone"""
super(VGG16, self).__init__()
self.vgg16_feature_extractor = VGG16FeatureExtraction(weights_update=True)
self.max_pool = nn.MaxPool2d(kernel_size=2, stride=2)
self.classifier = VGG16Clas... | the_stack_v2_python_sparse | official/cv/CTPN/src/CTPN/vgg16.py | mindspore-ai/models | train | 301 | |
cb4c021f77704289820f0c1dec6a99632d8424ad | [
"super().__init__()\nself.dim_head = int(dim / heads) if dim_head is None else dim_head\n_dim = self.dim_head * heads\nself.heads = heads\nself.to_qvk = nn.Linear(dim, _dim * 3, bias=False)\nself.W_0 = nn.Linear(_dim, dim, bias=False)\nself.scale_factor = self.dim_head ** (-0.5)\nself.space_att = space_att\nself.re... | <|body_start_0|>
super().__init__()
self.dim_head = int(dim / heads) if dim_head is None else dim_head
_dim = self.dim_head * heads
self.heads = heads
self.to_qvk = nn.Linear(dim, _dim * 3, bias=False)
self.W_0 = nn.Linear(_dim, dim, bias=False)
self.scale_factor ... | SpacetimeMHSA | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpacetimeMHSA:
def __init__(self, dim, tokens_to_attend, space_att, heads=8, dim_head=None, classification=True, linear_spatial_attention=False, k=None):
"""Attention through time and space to process videos choose mode (whether to operate in space and time with space_att (bool) ) CLS to... | stack_v2_sparse_classes_10k_train_001522 | 4,810 | permissive | [
{
"docstring": "Attention through time and space to process videos choose mode (whether to operate in space and time with space_att (bool) ) CLS token is used for video classification, which will attend all tokens in both space and time before attention only in time or space. Code is based on lucidrains repo: h... | 2 | stack_v2_sparse_classes_30k_train_006407 | Implement the Python class `SpacetimeMHSA` described below.
Class description:
Implement the SpacetimeMHSA class.
Method signatures and docstrings:
- def __init__(self, dim, tokens_to_attend, space_att, heads=8, dim_head=None, classification=True, linear_spatial_attention=False, k=None): Attention through time and sp... | Implement the Python class `SpacetimeMHSA` described below.
Class description:
Implement the SpacetimeMHSA class.
Method signatures and docstrings:
- def __init__(self, dim, tokens_to_attend, space_att, heads=8, dim_head=None, classification=True, linear_spatial_attention=False, k=None): Attention through time and sp... | 25622d56490ccca60a62a492fe48743e874a3e16 | <|skeleton|>
class SpacetimeMHSA:
def __init__(self, dim, tokens_to_attend, space_att, heads=8, dim_head=None, classification=True, linear_spatial_attention=False, k=None):
"""Attention through time and space to process videos choose mode (whether to operate in space and time with space_att (bool) ) CLS to... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SpacetimeMHSA:
def __init__(self, dim, tokens_to_attend, space_att, heads=8, dim_head=None, classification=True, linear_spatial_attention=False, k=None):
"""Attention through time and space to process videos choose mode (whether to operate in space and time with space_att (bool) ) CLS token is used fo... | the_stack_v2_python_sparse | self_attention_cv/timesformer/spacetime_attention.py | cumtChenLL/self-attention-cv | train | 1 | |
8993e36d53f21eb9675c8dac0716841f699ef201 | [
"if coco91_to_80 and include_mask:\n raise ValueError('If masks are included you cannot convert coco from the91 class format to the 80 class format.')\nself._coco91_to_80 = coco91_to_80\nsuper().__init__(include_mask=include_mask, regenerate_source_id=regenerate_source_id, mask_binarize_threshold=mask_binarize_t... | <|body_start_0|>
if coco91_to_80 and include_mask:
raise ValueError('If masks are included you cannot convert coco from the91 class format to the 80 class format.')
self._coco91_to_80 = coco91_to_80
super().__init__(include_mask=include_mask, regenerate_source_id=regenerate_source_id... | Tensorflow Example proto decoder. | TfExampleDecoder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TfExampleDecoder:
"""Tensorflow Example proto decoder."""
def __init__(self, coco91_to_80=None, include_mask=False, regenerate_source_id=False, mask_binarize_threshold=None):
"""Initialize the example decoder. Args: coco91_to_80: `bool` indicating whether to convert coco from its 91 ... | stack_v2_sparse_classes_10k_train_001523 | 4,810 | permissive | [
{
"docstring": "Initialize the example decoder. Args: coco91_to_80: `bool` indicating whether to convert coco from its 91 class format to the 80 class format. include_mask: `bool` indicating if the decoder should also decode instance masks for instance segmentation. regenerate_source_id: `bool` indicating if th... | 2 | null | Implement the Python class `TfExampleDecoder` described below.
Class description:
Tensorflow Example proto decoder.
Method signatures and docstrings:
- def __init__(self, coco91_to_80=None, include_mask=False, regenerate_source_id=False, mask_binarize_threshold=None): Initialize the example decoder. Args: coco91_to_8... | Implement the Python class `TfExampleDecoder` described below.
Class description:
Tensorflow Example proto decoder.
Method signatures and docstrings:
- def __init__(self, coco91_to_80=None, include_mask=False, regenerate_source_id=False, mask_binarize_threshold=None): Initialize the example decoder. Args: coco91_to_8... | d3507b550a3ade40cade60a79eb5b8978b56c7ae | <|skeleton|>
class TfExampleDecoder:
"""Tensorflow Example proto decoder."""
def __init__(self, coco91_to_80=None, include_mask=False, regenerate_source_id=False, mask_binarize_threshold=None):
"""Initialize the example decoder. Args: coco91_to_80: `bool` indicating whether to convert coco from its 91 ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TfExampleDecoder:
"""Tensorflow Example proto decoder."""
def __init__(self, coco91_to_80=None, include_mask=False, regenerate_source_id=False, mask_binarize_threshold=None):
"""Initialize the example decoder. Args: coco91_to_80: `bool` indicating whether to convert coco from its 91 class format ... | the_stack_v2_python_sparse | official/projects/yolo/dataloaders/tf_example_decoder.py | jianzhnie/models | train | 2 |
350652045fbaa57dfe7b38a93a11d750a3601951 | [
"if self.path == '/del_config' or self.path == '/del_config/':\n self.server.config = dict()\n self.log_message('Reset Server Configuration.')\n self.send_response(200)\nelse:\n self.send_response(404)",
"self.log_message(f'Youtube provider received GET request to path {self.path}')\nif 'get_config' i... | <|body_start_0|>
if self.path == '/del_config' or self.path == '/del_config/':
self.server.config = dict()
self.log_message('Reset Server Configuration.')
self.send_response(200)
else:
self.send_response(404)
<|end_body_0|>
<|body_start_1|>
self.l... | A handler for Youtube GET requests. | StubYouTubeHandler | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StubYouTubeHandler:
"""A handler for Youtube GET requests."""
def do_DELETE(self):
"""Allow callers to delete all the server configurations using the /del_config URL."""
<|body_0|>
def do_GET(self):
"""Handle a GET request from the client and sends response back.... | stack_v2_sparse_classes_10k_train_001524 | 6,207 | permissive | [
{
"docstring": "Allow callers to delete all the server configurations using the /del_config URL.",
"name": "do_DELETE",
"signature": "def do_DELETE(self)"
},
{
"docstring": "Handle a GET request from the client and sends response back.",
"name": "do_GET",
"signature": "def do_GET(self)"
... | 4 | null | Implement the Python class `StubYouTubeHandler` described below.
Class description:
A handler for Youtube GET requests.
Method signatures and docstrings:
- def do_DELETE(self): Allow callers to delete all the server configurations using the /del_config URL.
- def do_GET(self): Handle a GET request from the client and... | Implement the Python class `StubYouTubeHandler` described below.
Class description:
A handler for Youtube GET requests.
Method signatures and docstrings:
- def do_DELETE(self): Allow callers to delete all the server configurations using the /del_config URL.
- def do_GET(self): Handle a GET request from the client and... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class StubYouTubeHandler:
"""A handler for Youtube GET requests."""
def do_DELETE(self):
"""Allow callers to delete all the server configurations using the /del_config URL."""
<|body_0|>
def do_GET(self):
"""Handle a GET request from the client and sends response back.... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StubYouTubeHandler:
"""A handler for Youtube GET requests."""
def do_DELETE(self):
"""Allow callers to delete all the server configurations using the /del_config URL."""
if self.path == '/del_config' or self.path == '/del_config/':
self.server.config = dict()
self.... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/common/djangoapps/terrain/stubs/youtube.py | luque/better-ways-of-thinking-about-software | train | 3 |
435f48322403ca8e571f3bccfe8cc3a0a1677b7e | [
"super().__init__()\nself.frequency = frequency\nself.length = length\nself.type = type",
"mother_wavelet = self.type\nspread = np.arange(1, self.length + 1, 1)\nscales = central_frequency(mother_wavelet) * self.frequency / spread\ncoeffs, _ = cwt(signal, scales, mother_wavelet, 1.0 / self.frequency)\ncoeffs = np... | <|body_start_0|>
super().__init__()
self.frequency = frequency
self.length = length
self.type = type
<|end_body_0|>
<|body_start_1|>
mother_wavelet = self.type
spread = np.arange(1, self.length + 1, 1)
scales = central_frequency(mother_wavelet) * self.frequency /... | Generate continuous wavelet transform of a signal | SignalContinuousWavelet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignalContinuousWavelet:
"""Generate continuous wavelet transform of a signal"""
def __init__(self, type: str='mexh', length: float=125.0, frequency: float=500.0) -> None:
"""Args: type: mother wavelet type. Available options are: {``"mexh"``, ``"morl"``, ``"cmorB-C"``, , ``"gausP"``... | stack_v2_sparse_classes_10k_train_001525 | 16,322 | permissive | [
{
"docstring": "Args: type: mother wavelet type. Available options are: {``\"mexh\"``, ``\"morl\"``, ``\"cmorB-C\"``, , ``\"gausP\"``} see : https://pywavelets.readthedocs.io/en/latest/ref/cwt.html length: expected length, default ``125.0`` frequency: signal frequency, default ``500.0``",
"name": "__init__"... | 2 | stack_v2_sparse_classes_30k_train_005146 | Implement the Python class `SignalContinuousWavelet` described below.
Class description:
Generate continuous wavelet transform of a signal
Method signatures and docstrings:
- def __init__(self, type: str='mexh', length: float=125.0, frequency: float=500.0) -> None: Args: type: mother wavelet type. Available options a... | Implement the Python class `SignalContinuousWavelet` described below.
Class description:
Generate continuous wavelet transform of a signal
Method signatures and docstrings:
- def __init__(self, type: str='mexh', length: float=125.0, frequency: float=500.0) -> None: Args: type: mother wavelet type. Available options a... | e48c3e2c741fa3fc705c4425d17ac4a5afac6c47 | <|skeleton|>
class SignalContinuousWavelet:
"""Generate continuous wavelet transform of a signal"""
def __init__(self, type: str='mexh', length: float=125.0, frequency: float=500.0) -> None:
"""Args: type: mother wavelet type. Available options are: {``"mexh"``, ``"morl"``, ``"cmorB-C"``, , ``"gausP"``... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SignalContinuousWavelet:
"""Generate continuous wavelet transform of a signal"""
def __init__(self, type: str='mexh', length: float=125.0, frequency: float=500.0) -> None:
"""Args: type: mother wavelet type. Available options are: {``"mexh"``, ``"morl"``, ``"cmorB-C"``, , ``"gausP"``} see : https... | the_stack_v2_python_sparse | monai/transforms/signal/array.py | Project-MONAI/MONAI | train | 4,805 |
a3a777a18022111b81a565503bf9a2246dd90bbb | [
"super().__init__()\nif weights is not None and (not np.isclose(weights.sum(), 1)):\n raise ValueError('Weights must sum to 1.')\nself.weights = weights",
"if self.weights is None:\n m = scores.shape[-1]\n self.weights = torch.ones(m, device=scores.device) / m\nreturn scores @ self.weights"
] | <|body_start_0|>
super().__init__()
if weights is not None and (not np.isclose(weights.sum(), 1)):
raise ValueError('Weights must sum to 1.')
self.weights = weights
<|end_body_0|>
<|body_start_1|>
if self.weights is None:
m = scores.shape[-1]
self.wei... | AverageAggregator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AverageAggregator:
def __init__(self, weights: Optional[torch.Tensor]=None):
"""Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter to weight the scores. If `weights` is left ``None`` then will be set to a vector of ones. Raises ------ Va... | stack_v2_sparse_classes_10k_train_001526 | 9,337 | permissive | [
{
"docstring": "Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter to weight the scores. If `weights` is left ``None`` then will be set to a vector of ones. Raises ------ ValueError If `weights` does not sum to ``1``.",
"name": "__init__",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_006412 | Implement the Python class `AverageAggregator` described below.
Class description:
Implement the AverageAggregator class.
Method signatures and docstrings:
- def __init__(self, weights: Optional[torch.Tensor]=None): Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter ... | Implement the Python class `AverageAggregator` described below.
Class description:
Implement the AverageAggregator class.
Method signatures and docstrings:
- def __init__(self, weights: Optional[torch.Tensor]=None): Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter ... | 4a1b4f74a8590117965421e86c2295bff0f33e89 | <|skeleton|>
class AverageAggregator:
def __init__(self, weights: Optional[torch.Tensor]=None):
"""Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter to weight the scores. If `weights` is left ``None`` then will be set to a vector of ones. Raises ------ Va... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AverageAggregator:
def __init__(self, weights: Optional[torch.Tensor]=None):
"""Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter to weight the scores. If `weights` is left ``None`` then will be set to a vector of ones. Raises ------ ValueError If `w... | the_stack_v2_python_sparse | alibi_detect/od/pytorch/ensemble.py | SeldonIO/alibi-detect | train | 1,922 | |
4803cb51431bb469ea5de378fb41ed534113d883 | [
"super().__init__(args, functionToRun, **kwargs)\nself.subque = collections.deque()\nself.skipOnCopy.append('subque')\nself.thread = None",
"if not self.started:\n return False\nif self.thread is None:\n return True\nelse:\n return not self.thread.is_alive()",
"if not self.hasBeenAdded:\n self._coll... | <|body_start_0|>
super().__init__(args, functionToRun, **kwargs)
self.subque = collections.deque()
self.skipOnCopy.append('subque')
self.thread = None
<|end_body_0|>
<|body_start_1|>
if not self.started:
return False
if self.thread is None:
return... | Class for running internal objects in a threaded fashion using the built-in threading library | SharedMemoryRunner | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SharedMemoryRunner:
"""Class for running internal objects in a threaded fashion using the built-in threading library"""
def __init__(self, args, functionToRun, **kwargs):
"""Init method @ In, args, dict, this is a list of arguments that will be passed as function parameters into what... | stack_v2_sparse_classes_10k_train_001527 | 7,256 | permissive | [
{
"docstring": "Init method @ In, args, dict, this is a list of arguments that will be passed as function parameters into whatever method is stored in functionToRun. e.g., functionToRun(*args) @ In, functionToRun, method or function, function that needs to be run @ In, kwargs, dict, additional arguments to pass... | 6 | stack_v2_sparse_classes_30k_train_002305 | Implement the Python class `SharedMemoryRunner` described below.
Class description:
Class for running internal objects in a threaded fashion using the built-in threading library
Method signatures and docstrings:
- def __init__(self, args, functionToRun, **kwargs): Init method @ In, args, dict, this is a list of argum... | Implement the Python class `SharedMemoryRunner` described below.
Class description:
Class for running internal objects in a threaded fashion using the built-in threading library
Method signatures and docstrings:
- def __init__(self, args, functionToRun, **kwargs): Init method @ In, args, dict, this is a list of argum... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class SharedMemoryRunner:
"""Class for running internal objects in a threaded fashion using the built-in threading library"""
def __init__(self, args, functionToRun, **kwargs):
"""Init method @ In, args, dict, this is a list of arguments that will be passed as function parameters into what... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SharedMemoryRunner:
"""Class for running internal objects in a threaded fashion using the built-in threading library"""
def __init__(self, args, functionToRun, **kwargs):
"""Init method @ In, args, dict, this is a list of arguments that will be passed as function parameters into whatever method i... | the_stack_v2_python_sparse | ravenframework/Runners/SharedMemoryRunner.py | idaholab/raven | train | 201 |
923f9447f414f81193353def17042d5976d2b1bd | [
"text = simplicity.file_opener('sample.rst')\nself.assertNotEqual(text, 'sample.rst')\ntext = simplicity.file_opener('README.rst')\nself.assertNotEqual(text, 'README.rst')",
"with open('sample.rst') as f:\n text = f.read()\nself.assertEqual(text, simplicity.file_opener('sample.rst'))"
] | <|body_start_0|>
text = simplicity.file_opener('sample.rst')
self.assertNotEqual(text, 'sample.rst')
text = simplicity.file_opener('README.rst')
self.assertNotEqual(text, 'README.rst')
<|end_body_0|>
<|body_start_1|>
with open('sample.rst') as f:
text = f.read()
... | FileOpener | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileOpener:
def test_basics(self):
"""I test that file_opener returns more than just itself!"""
<|body_0|>
def test_open(self):
"""I test that file_opener gets things correctly!"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
text = simplicity.file_... | stack_v2_sparse_classes_10k_train_001528 | 6,339 | no_license | [
{
"docstring": "I test that file_opener returns more than just itself!",
"name": "test_basics",
"signature": "def test_basics(self)"
},
{
"docstring": "I test that file_opener gets things correctly!",
"name": "test_open",
"signature": "def test_open(self)"
}
] | 2 | null | Implement the Python class `FileOpener` described below.
Class description:
Implement the FileOpener class.
Method signatures and docstrings:
- def test_basics(self): I test that file_opener returns more than just itself!
- def test_open(self): I test that file_opener gets things correctly! | Implement the Python class `FileOpener` described below.
Class description:
Implement the FileOpener class.
Method signatures and docstrings:
- def test_basics(self): I test that file_opener returns more than just itself!
- def test_open(self): I test that file_opener gets things correctly!
<|skeleton|>
class FileOp... | 0ac6653219c2701c13c508c5c4fc9bc3437eea06 | <|skeleton|>
class FileOpener:
def test_basics(self):
"""I test that file_opener returns more than just itself!"""
<|body_0|>
def test_open(self):
"""I test that file_opener gets things correctly!"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FileOpener:
def test_basics(self):
"""I test that file_opener returns more than just itself!"""
text = simplicity.file_opener('sample.rst')
self.assertNotEqual(text, 'sample.rst')
text = simplicity.file_opener('README.rst')
self.assertNotEqual(text, 'README.rst')
d... | the_stack_v2_python_sparse | repoData/pydanny-simplicity/allPythonContent.py | aCoffeeYin/pyreco | train | 0 | |
60014608146cb20e89e8802abb2693fffeec27da | [
"res = 0\nfor i in range(len(s) + 1):\n temp = self.helper(s, i)\n res = max(res, temp)\nreturn res",
"res = len(s)\nfor i in range(len(s)):\n if s[i] == '0' and i < left_end:\n res += 1\n elif s[i] == '1' and i >= left_end:\n res += 1\nreturn res"
] | <|body_start_0|>
res = 0
for i in range(len(s) + 1):
temp = self.helper(s, i)
res = max(res, temp)
return res
<|end_body_0|>
<|body_start_1|>
res = len(s)
for i in range(len(s)):
if s[i] == '0' and i < left_end:
res += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def func(self, s):
"""Args: s: list[int] Return: int"""
<|body_0|>
def helper(self, s, left_end):
"""Args: s: str left_end: int Return: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = 0
for i in range(len(s) + 1):
... | stack_v2_sparse_classes_10k_train_001529 | 744 | no_license | [
{
"docstring": "Args: s: list[int] Return: int",
"name": "func",
"signature": "def func(self, s)"
},
{
"docstring": "Args: s: str left_end: int Return: int",
"name": "helper",
"signature": "def helper(self, s, left_end)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def func(self, s): Args: s: list[int] Return: int
- def helper(self, s, left_end): Args: s: str left_end: int Return: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def func(self, s): Args: s: list[int] Return: int
- def helper(self, s, left_end): Args: s: str left_end: int Return: int
<|skeleton|>
class Solution:
def func(self, s):
... | 101bce2fac8b188a4eb2f5e017293d21ad0ecb21 | <|skeleton|>
class Solution:
def func(self, s):
"""Args: s: list[int] Return: int"""
<|body_0|>
def helper(self, s, left_end):
"""Args: s: str left_end: int Return: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def func(self, s):
"""Args: s: list[int] Return: int"""
res = 0
for i in range(len(s) + 1):
temp = self.helper(s, i)
res = max(res, temp)
return res
def helper(self, s, left_end):
"""Args: s: str left_end: int Return: int"""
... | the_stack_v2_python_sparse | 秋招/网易/网易云音乐/1.py | AiZhanghan/Leetcode | train | 0 | |
ba93715786f1a6fed25ec3b8d8746d07ccbcefa9 | [
"super(DecoderLayer, self).__init__()\nwith self.init_scope():\n self.self_attn = MultiHeadAttention(n_units, h, dropout=dropout, initialW=initialW, initial_bias=initial_bias)\n self.src_attn = MultiHeadAttention(n_units, h, dropout=dropout, initialW=initialW, initial_bias=initial_bias)\n self.feed_forward... | <|body_start_0|>
super(DecoderLayer, self).__init__()
with self.init_scope():
self.self_attn = MultiHeadAttention(n_units, h, dropout=dropout, initialW=initialW, initial_bias=initial_bias)
self.src_attn = MultiHeadAttention(n_units, h, dropout=dropout, initialW=initialW, initial_... | Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate | DecoderLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderLayer:
"""Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate"""
def __init__(self, n_units, ... | stack_v2_sparse_classes_10k_train_001530 | 2,526 | permissive | [
{
"docstring": "Initialize DecoderLayer.",
"name": "__init__",
"signature": "def __init__(self, n_units, d_units=0, h=8, dropout=0.1, initialW=None, initial_bias=None)"
},
{
"docstring": "Compute Encoder layer. Args: e (chainer.Variable): Batch of padded features. (B, Lmax) s (chainer.Variable):... | 2 | null | Implement the Python class `DecoderLayer` described below.
Class description:
Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout ra... | Implement the Python class `DecoderLayer` described below.
Class description:
Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout ra... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class DecoderLayer:
"""Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate"""
def __init__(self, n_units, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DecoderLayer:
"""Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate"""
def __init__(self, n_units, d_units=0, h=... | the_stack_v2_python_sparse | espnet/nets/chainer_backend/transformer/decoder_layer.py | espnet/espnet | train | 7,242 |
e8e05023d5d3a4d7d689422fe3aae4b55299e097 | [
"ip_dict = {'Address': ['1.1.1.1', '1.2.3.4'], 'Range': ['1.1.1.3-1.1.2.1']}\ndicts = create_ip_list_dicts(ip_dict)\nassert len(dicts[0]) == 2\nassert len(dicts[1]) == 1",
"ip_dict = {'Address': '1.1.1.1'}\ndicts = create_ip_list_dicts(ip_dict)\nassert len(dicts) == 1\nassert len(dicts[0]) == 1",
"ip_dict = {'A... | <|body_start_0|>
ip_dict = {'Address': ['1.1.1.1', '1.2.3.4'], 'Range': ['1.1.1.3-1.1.2.1']}
dicts = create_ip_list_dicts(ip_dict)
assert len(dicts[0]) == 2
assert len(dicts[1]) == 1
<|end_body_0|>
<|body_start_1|>
ip_dict = {'Address': '1.1.1.1'}
dicts = create_ip_list_... | TestCreateIPListDicts | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCreateIPListDicts:
def test_create_ip_list_dicts_expected_format(self):
"""Given - dictionary of ip list command result When - the dictionary has the expected format Then - create a list of dictionaries"""
<|body_0|>
def test_create_ip_list_dicts_expected_format_single_v... | stack_v2_sparse_classes_10k_train_001531 | 44,285 | permissive | [
{
"docstring": "Given - dictionary of ip list command result When - the dictionary has the expected format Then - create a list of dictionaries",
"name": "test_create_ip_list_dicts_expected_format",
"signature": "def test_create_ip_list_dicts_expected_format(self)"
},
{
"docstring": "Given - dic... | 6 | null | Implement the Python class `TestCreateIPListDicts` described below.
Class description:
Implement the TestCreateIPListDicts class.
Method signatures and docstrings:
- def test_create_ip_list_dicts_expected_format(self): Given - dictionary of ip list command result When - the dictionary has the expected format Then - c... | Implement the Python class `TestCreateIPListDicts` described below.
Class description:
Implement the TestCreateIPListDicts class.
Method signatures and docstrings:
- def test_create_ip_list_dicts_expected_format(self): Given - dictionary of ip list command result When - the dictionary has the expected format Then - c... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class TestCreateIPListDicts:
def test_create_ip_list_dicts_expected_format(self):
"""Given - dictionary of ip list command result When - the dictionary has the expected format Then - create a list of dictionaries"""
<|body_0|>
def test_create_ip_list_dicts_expected_format_single_v... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestCreateIPListDicts:
def test_create_ip_list_dicts_expected_format(self):
"""Given - dictionary of ip list command result When - the dictionary has the expected format Then - create a list of dictionaries"""
ip_dict = {'Address': ['1.1.1.1', '1.2.3.4'], 'Range': ['1.1.1.3-1.1.2.1']}
... | the_stack_v2_python_sparse | Packs/qualys/Integrations/Qualysv2/Qualysv2_test.py | demisto/content | train | 1,023 | |
69e99b258182a9c78627a6973f04b5d62b13e744 | [
"n = len(prices)\ndp = [[None] * 5 for _ in range(n)]\ndp[0][0] = 0\ndp[0][1] = -prices[0]\ndp[0][2] = 0\ndp[0][3] = -prices[0]\ndp[0][4] = 0\nfor idx in range(1, n):\n dp[idx][0] = 0\n dp[idx][1] = max(dp[idx - 1][1], dp[idx - 1][0] - prices[idx])\n dp[idx][2] = max(dp[idx - 1][2], dp[idx - 1][1] + prices... | <|body_start_0|>
n = len(prices)
dp = [[None] * 5 for _ in range(n)]
dp[0][0] = 0
dp[0][1] = -prices[0]
dp[0][2] = 0
dp[0][3] = -prices[0]
dp[0][4] = 0
for idx in range(1, n):
dp[idx][0] = 0
dp[idx][1] = max(dp[idx - 1][1], dp[idx -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""动态规划-二维数组"""
<|body_0|>
def maxProfitDPOpt(self, prices: List[int]) -> int:
"""动态规划-空间优化"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(prices)
dp = [[None] * 5 for _ in ra... | stack_v2_sparse_classes_10k_train_001532 | 2,661 | no_license | [
{
"docstring": "动态规划-二维数组",
"name": "maxProfit",
"signature": "def maxProfit(self, prices: List[int]) -> int"
},
{
"docstring": "动态规划-空间优化",
"name": "maxProfitDPOpt",
"signature": "def maxProfitDPOpt(self, prices: List[int]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_006265 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 动态规划-二维数组
- def maxProfitDPOpt(self, prices: List[int]) -> int: 动态规划-空间优化 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 动态规划-二维数组
- def maxProfitDPOpt(self, prices: List[int]) -> int: 动态规划-空间优化
<|skeleton|>
class Solution:
def maxProfit(self, pr... | 52756b30e9d51794591aca030bc918e707f473f1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""动态规划-二维数组"""
<|body_0|>
def maxProfitDPOpt(self, prices: List[int]) -> int:
"""动态规划-空间优化"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""动态规划-二维数组"""
n = len(prices)
dp = [[None] * 5 for _ in range(n)]
dp[0][0] = 0
dp[0][1] = -prices[0]
dp[0][2] = 0
dp[0][3] = -prices[0]
dp[0][4] = 0
for idx in range(1, n):
... | the_stack_v2_python_sparse | 123.买卖股票的最佳时机III/solution.py | QtTao/daily_leetcode | train | 0 | |
c76bdeb34099414b91b0d717b82c3ec2f2ccfbbc | [
"Component.__init__(self)\nself.name = 'Compressor_default_name'\nself.bus_h2_in = None\nself.bus_h2_out = None\nself.bus_el = None\nself.m_flow_max = 33.6\nself.life_time = 20\nself.temp_in = 293.15\nself.efficiency = 0.88829\nself.set_parameters(params)\nself.spec_compression_energy = None\nself.R = 8.314\nself.M... | <|body_start_0|>
Component.__init__(self)
self.name = 'Compressor_default_name'
self.bus_h2_in = None
self.bus_h2_out = None
self.bus_el = None
self.m_flow_max = 33.6
self.life_time = 20
self.temp_in = 293.15
self.efficiency = 0.88829
self.... | :param name: unique name given to the compressor component :type name: str :param bus_h2_in: lower pressure hydrogen bus that is an input of the compressor :type bus_h2_in: str :param bus_el: electricity bus that is an input of the compressor :type bus_el: str :param bus_h2_out: higher pressure hydrogen bus that is the... | CompressorH2 | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompressorH2:
""":param name: unique name given to the compressor component :type name: str :param bus_h2_in: lower pressure hydrogen bus that is an input of the compressor :type bus_h2_in: str :param bus_el: electricity bus that is an input of the compressor :type bus_el: str :param bus_h2_out: ... | stack_v2_sparse_classes_10k_train_001533 | 10,964 | permissive | [
{
"docstring": "Constructor method",
"name": "__init__",
"signature": "def __init__(self, params)"
},
{
"docstring": "Creates an oemof Transformer component using the information given in the CompressorH2 class, to be used in the oemof model :param busses: virtual buses used in the energy system... | 4 | stack_v2_sparse_classes_30k_train_001757 | Implement the Python class `CompressorH2` described below.
Class description:
:param name: unique name given to the compressor component :type name: str :param bus_h2_in: lower pressure hydrogen bus that is an input of the compressor :type bus_h2_in: str :param bus_el: electricity bus that is an input of the compresso... | Implement the Python class `CompressorH2` described below.
Class description:
:param name: unique name given to the compressor component :type name: str :param bus_h2_in: lower pressure hydrogen bus that is an input of the compressor :type bus_h2_in: str :param bus_el: electricity bus that is an input of the compresso... | 0d4d55d587c18d9e05258f85c1bb41c0b5fdaee7 | <|skeleton|>
class CompressorH2:
""":param name: unique name given to the compressor component :type name: str :param bus_h2_in: lower pressure hydrogen bus that is an input of the compressor :type bus_h2_in: str :param bus_el: electricity bus that is an input of the compressor :type bus_el: str :param bus_h2_out: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CompressorH2:
""":param name: unique name given to the compressor component :type name: str :param bus_h2_in: lower pressure hydrogen bus that is an input of the compressor :type bus_h2_in: str :param bus_el: electricity bus that is an input of the compressor :type bus_el: str :param bus_h2_out: higher pressu... | the_stack_v2_python_sparse | smooth/components/component_compressor_h2.py | rl-institut/smooth | train | 7 |
4af76edc472e5a9d297e4282a38f5c5782d8d3d0 | [
"if self.state_model.op_state in [DevState.FAULT, DevState.UNKNOWN, DevState.DISABLE]:\n return False\nreturn True",
"device_data = self.target\ncommand_name = 'Abort'\ndevice_data.event_track_time.set()\ncmd_ended_cb = CommandCallBack(self.logger).cmd_ended_cb\ntry:\n this_server = TangoServerHelper.get_in... | <|body_start_0|>
if self.state_model.op_state in [DevState.FAULT, DevState.UNKNOWN, DevState.DISABLE]:
return False
return True
<|end_body_0|>
<|body_start_1|>
device_data = self.target
command_name = 'Abort'
device_data.event_track_time.set()
cmd_ended_cb = ... | A class for DishLeafNode's Abort command. | Abort | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Abort:
"""A class for DishLeafNode's Abort command."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device state :rtype: boolean"""
<|body_0|>
def do(sel... | stack_v2_sparse_classes_10k_train_001534 | 2,704 | permissive | [
{
"docstring": "Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device state :rtype: boolean",
"name": "check_allowed",
"signature": "def check_allowed(self)"
},
{
"docstring": "Invokes TrackStop command on th... | 2 | stack_v2_sparse_classes_30k_test_000243 | Implement the Python class `Abort` described below.
Class description:
A class for DishLeafNode's Abort command.
Method signatures and docstrings:
- def check_allowed(self): Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device st... | Implement the Python class `Abort` described below.
Class description:
A class for DishLeafNode's Abort command.
Method signatures and docstrings:
- def check_allowed(self): Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device st... | 7ee65a9c8dada9b28893144b372a398bd0646195 | <|skeleton|>
class Abort:
"""A class for DishLeafNode's Abort command."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device state :rtype: boolean"""
<|body_0|>
def do(sel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Abort:
"""A class for DishLeafNode's Abort command."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device state :rtype: boolean"""
if self.state_model.op_state in [DevSta... | the_stack_v2_python_sparse | temp_src/ska_tmc_dishleafnode_mid/abort_command.py | ska-telescope/tmc-prototype | train | 4 |
4f3b0318c630b43da88388ca43e9262bd47dd651 | [
"pmf = thinkbayes.MakePoissonPmf(r, high, step=step)\nthinkbayes.Suite.__init__(self, pmf, name=r)\nself.r = r\nself.f = f",
"k = data\nn = hypo\np = self.f\nreturn thinkbayes.EvalBinomialPmf(k, n, p)",
"total = 0\nfor hypo, prob in self.Items():\n like = self.Likelihood(data, hypo)\n total += prob * like... | <|body_start_0|>
pmf = thinkbayes.MakePoissonPmf(r, high, step=step)
thinkbayes.Suite.__init__(self, pmf, name=r)
self.r = r
self.f = f
<|end_body_0|>
<|body_start_1|>
k = data
n = hypo
p = self.f
return thinkbayes.EvalBinomialPmf(k, n, p)
<|end_body_1|>
... | Represents hypotheses about n. | Detector | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Detector:
"""Represents hypotheses about n."""
def __init__(self, r, f, high=500, step=5):
"""Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step size between hypothetical values of n"""
<|body_0... | stack_v2_sparse_classes_10k_train_001535 | 5,605 | permissive | [
{
"docstring": "Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step size between hypothetical values of n",
"name": "__init__",
"signature": "def __init__(self, r, f, high=500, step=5)"
},
{
"docstring": "Likelihood... | 3 | null | Implement the Python class `Detector` described below.
Class description:
Represents hypotheses about n.
Method signatures and docstrings:
- def __init__(self, r, f, high=500, step=5): Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step ... | Implement the Python class `Detector` described below.
Class description:
Represents hypotheses about n.
Method signatures and docstrings:
- def __init__(self, r, f, high=500, step=5): Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step ... | 53c7ce7ca7da62c9fbb3d991ae9e4e34d07ece5f | <|skeleton|>
class Detector:
"""Represents hypotheses about n."""
def __init__(self, r, f, high=500, step=5):
"""Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step size between hypothetical values of n"""
<|body_0... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Detector:
"""Represents hypotheses about n."""
def __init__(self, r, f, high=500, step=5):
"""Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step size between hypothetical values of n"""
pmf = thinkbayes.Make... | the_stack_v2_python_sparse | python/learn/thinkbayes/jaynes.py | qrsforever/workspace | train | 2 |
94dfbea49d648d211a72dbae07fb1d7a9f7e437c | [
"UserSim.__init__(self, error_evaluator)\nself.user_type = 'real'\nself.bool_undo = bool_undo\nself.undo_semantic_units = []",
"self.questioned_pointers.append(pointer)\nif self.bool_undo:\n answer = input('Please enter yes(y)/no(n)/undo/exit: ').lower().strip()\n while answer not in {'yes', 'no', 'exit', '... | <|body_start_0|>
UserSim.__init__(self, error_evaluator)
self.user_type = 'real'
self.bool_undo = bool_undo
self.undo_semantic_units = []
<|end_body_0|>
<|body_start_1|>
self.questioned_pointers.append(pointer)
if self.bool_undo:
answer = input('Please enter ... | This is the class for real users (used in user study). | RealUser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RealUser:
"""This is the class for real users (used in user study)."""
def __init__(self, error_evaluator, bool_undo=True):
"""Constructor of RealUser. :param error_evaluator: An instance of ErrorEvaluator."""
<|body_0|>
def get_answer(self, pointer, *args):
"""R... | stack_v2_sparse_classes_10k_train_001536 | 9,856 | permissive | [
{
"docstring": "Constructor of RealUser. :param error_evaluator: An instance of ErrorEvaluator.",
"name": "__init__",
"signature": "def __init__(self, error_evaluator, bool_undo=True)"
},
{
"docstring": "Request for user answers. :param pointer: the pointer to the questioned semantic unit. :para... | 3 | stack_v2_sparse_classes_30k_train_003783 | Implement the Python class `RealUser` described below.
Class description:
This is the class for real users (used in user study).
Method signatures and docstrings:
- def __init__(self, error_evaluator, bool_undo=True): Constructor of RealUser. :param error_evaluator: An instance of ErrorEvaluator.
- def get_answer(sel... | Implement the Python class `RealUser` described below.
Class description:
This is the class for real users (used in user study).
Method signatures and docstrings:
- def __init__(self, error_evaluator, bool_undo=True): Constructor of RealUser. :param error_evaluator: An instance of ErrorEvaluator.
- def get_answer(sel... | 7870566ab6b9e121d648478968367bc79c12f7ef | <|skeleton|>
class RealUser:
"""This is the class for real users (used in user study)."""
def __init__(self, error_evaluator, bool_undo=True):
"""Constructor of RealUser. :param error_evaluator: An instance of ErrorEvaluator."""
<|body_0|>
def get_answer(self, pointer, *args):
"""R... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RealUser:
"""This is the class for real users (used in user study)."""
def __init__(self, error_evaluator, bool_undo=True):
"""Constructor of RealUser. :param error_evaluator: An instance of ErrorEvaluator."""
UserSim.__init__(self, error_evaluator)
self.user_type = 'real'
... | the_stack_v2_python_sparse | MISP_SQL/environment.py | sunlab-osu/MISP | train | 59 |
78684c89a06df79f0c2207c4a41c7b4ebdf4a036 | [
"y = 0\nfor x in range(len(nums)):\n if nums[x]:\n nums[x], nums[y] = (nums[y], nums[x])\n y += 1",
"l = len(nums)\nfor i in range(l):\n if nums[i] == 0:\n j = i + 1\n while j < l and nums[j] == 0:\n j += 1\n if j < l:\n nums[i], nums[j] = (nums[j], n... | <|body_start_0|>
y = 0
for x in range(len(nums)):
if nums[x]:
nums[x], nums[y] = (nums[y], nums[x])
y += 1
<|end_body_0|>
<|body_start_1|>
l = len(nums)
for i in range(l):
if nums[i] == 0:
j = i + 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def moveZeroes(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def moveZeroes(self, nums: List[int]) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1... | stack_v2_sparse_classes_10k_train_001537 | 1,129 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.",
"name": "moveZeroes",
"signature": "def moveZeroes(self, nums)"
},
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "moveZeroes",
"signature": "def mo... | 2 | stack_v2_sparse_classes_30k_train_005448 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveZeroes(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def moveZeroes(self, nums: List[int]) -> None: Do not retur... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def moveZeroes(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def moveZeroes(self, nums: List[int]) -> None: Do not retur... | 378cb9b53e7710c5cf546f5d75e572060e2a211a | <|skeleton|>
class Solution:
def moveZeroes(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def moveZeroes(self, nums: List[int]) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def moveZeroes(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
y = 0
for x in range(len(nums)):
if nums[x]:
nums[x], nums[y] = (nums[y], nums[x])
y += 1
def moveZeroes... | the_stack_v2_python_sparse | 283.MoveZeroes.py | RupertMa/LeetCode-Playground | train | 0 | |
f61d606639088dd477963fa8ce5e5effb4675a20 | [
"res = {}\nfor section in config.sections(issuer=request.environ.get('issuer'), vo=request.environ.get('vo')):\n res[section] = {}\n for item in config.items(section, issuer=request.environ.get('issuer'), vo=request.environ.get('vo')):\n res[section][item[0]] = item[1]\nreturn (jsonify(res), 200)",
"... | <|body_start_0|>
res = {}
for section in config.sections(issuer=request.environ.get('issuer'), vo=request.environ.get('vo')):
res[section] = {}
for item in config.items(section, issuer=request.environ.get('issuer'), vo=request.environ.get('vo')):
res[section][item... | REST API for full configuration. | Config | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Config:
"""REST API for full configuration."""
def get(self):
"""--- summary: List description: List the full configuration. tags: - Config responses: 200: description: OK content: application/json: schema: description: A dict with the sections as keys and a dict with the configurati... | stack_v2_sparse_classes_10k_train_001538 | 10,156 | permissive | [
{
"docstring": "--- summary: List description: List the full configuration. tags: - Config responses: 200: description: OK content: application/json: schema: description: A dict with the sections as keys and a dict with the configuration as value. type: object 401: description: Invalid Auth Token 406: descripti... | 2 | stack_v2_sparse_classes_30k_train_004556 | Implement the Python class `Config` described below.
Class description:
REST API for full configuration.
Method signatures and docstrings:
- def get(self): --- summary: List description: List the full configuration. tags: - Config responses: 200: description: OK content: application/json: schema: description: A dict ... | Implement the Python class `Config` described below.
Class description:
REST API for full configuration.
Method signatures and docstrings:
- def get(self): --- summary: List description: List the full configuration. tags: - Config responses: 200: description: OK content: application/json: schema: description: A dict ... | 7f0d229ac0b3bc7dec12c6e158bea2b82d414a3b | <|skeleton|>
class Config:
"""REST API for full configuration."""
def get(self):
"""--- summary: List description: List the full configuration. tags: - Config responses: 200: description: OK content: application/json: schema: description: A dict with the sections as keys and a dict with the configurati... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Config:
"""REST API for full configuration."""
def get(self):
"""--- summary: List description: List the full configuration. tags: - Config responses: 200: description: OK content: application/json: schema: description: A dict with the sections as keys and a dict with the configuration as value. ... | the_stack_v2_python_sparse | lib/rucio/web/rest/flaskapi/v1/config.py | rucio/rucio | train | 232 |
9c92976cc44735c8181fda6b49d999cfe9630247 | [
"if server_ip == '' and server_port != 0 or (server_ip != '' and server_port == 0):\n raise Exception('server_ip和server_port必须同时指定')\nself._server_ip = server_ip\nself._server_port = server_port\nself._service_name = service_name\nself._host = host",
"headers = {'org': org, 'user': user}\nroute_name = ''\nserv... | <|body_start_0|>
if server_ip == '' and server_port != 0 or (server_ip != '' and server_port == 0):
raise Exception('server_ip和server_port必须同时指定')
self._server_ip = server_ip
self._server_port = server_port
self._service_name = service_name
self._host = host
<|end_bod... | ExecuteClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExecuteClient:
def __init__(self, server_ip='', server_port=0, service_name='', host=''):
"""初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和servi... | stack_v2_sparse_classes_10k_train_001539 | 6,070 | permissive | [
{
"docstring": "初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和service_name同时设置，server_ip优先级更高 :param host: 指定sdk请求服务的host名称, 如cmdb.easyops-only.com",
"name": "__ini... | 4 | stack_v2_sparse_classes_30k_train_001605 | Implement the Python class `ExecuteClient` described below.
Class description:
Implement the ExecuteClient class.
Method signatures and docstrings:
- def __init__(self, server_ip='', server_port=0, service_name='', host=''): 初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_p... | Implement the Python class `ExecuteClient` described below.
Class description:
Implement the ExecuteClient class.
Method signatures and docstrings:
- def __init__(self, server_ip='', server_port=0, service_name='', host=''): 初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_p... | adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0 | <|skeleton|>
class ExecuteClient:
def __init__(self, server_ip='', server_port=0, service_name='', host=''):
"""初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和servi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExecuteClient:
def __init__(self, server_ip='', server_port=0, service_name='', host=''):
"""初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和service_name同时设置，se... | the_stack_v2_python_sparse | flow_sdk/api/execute/execute_client.py | easyopsapis/easyops-api-python | train | 5 | |
affb9f2df666928742fb99fae67a15df05a78f37 | [
"xml_ele = ET.fromstring(serialized_str)\ncls._remove_xml_etree_namespace(xml_ele, Constants.XML_API_NAMESPACE)\ngroups = []\nfor group in xml_ele.findall('security_group'):\n groups.append(SecurityGroup._xml_ele_to_obj(group))\nreturn groups",
"ret = []\njson_dict = json.loads(serialized_str)\ngroups = json_d... | <|body_start_0|>
xml_ele = ET.fromstring(serialized_str)
cls._remove_xml_etree_namespace(xml_ele, Constants.XML_API_NAMESPACE)
groups = []
for group in xml_ele.findall('security_group'):
groups.append(SecurityGroup._xml_ele_to_obj(group))
return groups
<|end_body_0|>
... | SecurityGroups | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecurityGroups:
def _xml_to_obj(cls, serialized_str):
"""@summary: Returns a list of a SecurityGroup based on the xml serialized_str passed in. @param serialized_str: xml serialized string. @type serialized_str: String. @return: List. @rtype: List."""
<|body_0|>
def _json_to... | stack_v2_sparse_classes_10k_train_001540 | 5,294 | permissive | [
{
"docstring": "@summary: Returns a list of a SecurityGroup based on the xml serialized_str passed in. @param serialized_str: xml serialized string. @type serialized_str: String. @return: List. @rtype: List.",
"name": "_xml_to_obj",
"signature": "def _xml_to_obj(cls, serialized_str)"
},
{
"docst... | 2 | null | Implement the Python class `SecurityGroups` described below.
Class description:
Implement the SecurityGroups class.
Method signatures and docstrings:
- def _xml_to_obj(cls, serialized_str): @summary: Returns a list of a SecurityGroup based on the xml serialized_str passed in. @param serialized_str: xml serialized str... | Implement the Python class `SecurityGroups` described below.
Class description:
Implement the SecurityGroups class.
Method signatures and docstrings:
- def _xml_to_obj(cls, serialized_str): @summary: Returns a list of a SecurityGroup based on the xml serialized_str passed in. @param serialized_str: xml serialized str... | 7d49cf6bfd7e1a6e5b739e7de52f2e18e5ccf924 | <|skeleton|>
class SecurityGroups:
def _xml_to_obj(cls, serialized_str):
"""@summary: Returns a list of a SecurityGroup based on the xml serialized_str passed in. @param serialized_str: xml serialized string. @type serialized_str: String. @return: List. @rtype: List."""
<|body_0|>
def _json_to... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SecurityGroups:
def _xml_to_obj(cls, serialized_str):
"""@summary: Returns a list of a SecurityGroup based on the xml serialized_str passed in. @param serialized_str: xml serialized string. @type serialized_str: String. @return: List. @rtype: List."""
xml_ele = ET.fromstring(serialized_str)
... | the_stack_v2_python_sparse | cloudcafe/compute/extensions/security_groups_api/models/security_group.py | kurhula/cloudcafe | train | 0 | |
d4c0e4196111b8af34ccf7cdc63f1a47a9a78e9f | [
"assert isinstance(block_string, str)\nops = block_string.split('_')\noptions = {}\nfor op in ops:\n splits = re.split('(\\\\d.*)', op)\n if len(splits) >= 2:\n key, value = splits[:2]\n options[key] = value\nassert 's' in options and len(options['s']) == 1 or (len(options['s']) == 2 and options... | <|body_start_0|>
assert isinstance(block_string, str)
ops = block_string.split('_')
options = {}
for op in ops:
splits = re.split('(\\d.*)', op)
if len(splits) >= 2:
key, value = splits[:2]
options[key] = value
assert 's' in... | Block Decoder for readability, straight from the official TensorFlow repository. | BlockDecoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BlockDecoder:
"""Block Decoder for readability, straight from the official TensorFlow repository."""
def _decode_block_string(block_string):
"""Get a block through a string notation of arguments. Args: block_string (str): A string notation of arguments. Examples: 'r1_k3_s11_e1_i32_o1... | stack_v2_sparse_classes_10k_train_001541 | 42,101 | permissive | [
{
"docstring": "Get a block through a string notation of arguments. Args: block_string (str): A string notation of arguments. Examples: 'r1_k3_s11_e1_i32_o16_se0.25_noskip'. Returns: BlockArgs: The namedtuple defined at the top of this file.",
"name": "_decode_block_string",
"signature": "def _decode_bl... | 4 | stack_v2_sparse_classes_30k_train_003759 | Implement the Python class `BlockDecoder` described below.
Class description:
Block Decoder for readability, straight from the official TensorFlow repository.
Method signatures and docstrings:
- def _decode_block_string(block_string): Get a block through a string notation of arguments. Args: block_string (str): A str... | Implement the Python class `BlockDecoder` described below.
Class description:
Block Decoder for readability, straight from the official TensorFlow repository.
Method signatures and docstrings:
- def _decode_block_string(block_string): Get a block through a string notation of arguments. Args: block_string (str): A str... | a835a21cc45d13bd1da4b7cf4c0a837d52c2844d | <|skeleton|>
class BlockDecoder:
"""Block Decoder for readability, straight from the official TensorFlow repository."""
def _decode_block_string(block_string):
"""Get a block through a string notation of arguments. Args: block_string (str): A string notation of arguments. Examples: 'r1_k3_s11_e1_i32_o1... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BlockDecoder:
"""Block Decoder for readability, straight from the official TensorFlow repository."""
def _decode_block_string(block_string):
"""Get a block through a string notation of arguments. Args: block_string (str): A string notation of arguments. Examples: 'r1_k3_s11_e1_i32_o16_se0.25_nosk... | the_stack_v2_python_sparse | ImitationLearning/backbone.py | Suryavf/SelfDrivingCar | train | 13 |
93798abde17ade54cb4e99b13ed949f519389d80 | [
"skill_set = get_object_or_404(InstrumentAnalysis, slug=slug)\nself.check_object_permissions(request, skill_set)\nserializer = InstrumentAnalysisRetrieveUpdateSerializer(skill_set, many=False)\nreturn Response(data=serializer.data, status=status.HTTP_200_OK)",
"instrument_analysis = get_object_or_404(InstrumentAn... | <|body_start_0|>
skill_set = get_object_or_404(InstrumentAnalysis, slug=slug)
self.check_object_permissions(request, skill_set)
serializer = InstrumentAnalysisRetrieveUpdateSerializer(skill_set, many=False)
return Response(data=serializer.data, status=status.HTTP_200_OK)
<|end_body_0|>
... | InstrumentAnalysisRetrieveUpdateDestroyAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstrumentAnalysisRetrieveUpdateDestroyAPIView:
def get(self, request, slug=None):
"""Retrieve"""
<|body_0|>
def put(self, request, slug=None):
"""Update"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
skill_set = get_object_or_404(InstrumentAnalysi... | stack_v2_sparse_classes_10k_train_001542 | 3,789 | permissive | [
{
"docstring": "Retrieve",
"name": "get",
"signature": "def get(self, request, slug=None)"
},
{
"docstring": "Update",
"name": "put",
"signature": "def put(self, request, slug=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000281 | Implement the Python class `InstrumentAnalysisRetrieveUpdateDestroyAPIView` described below.
Class description:
Implement the InstrumentAnalysisRetrieveUpdateDestroyAPIView class.
Method signatures and docstrings:
- def get(self, request, slug=None): Retrieve
- def put(self, request, slug=None): Update | Implement the Python class `InstrumentAnalysisRetrieveUpdateDestroyAPIView` described below.
Class description:
Implement the InstrumentAnalysisRetrieveUpdateDestroyAPIView class.
Method signatures and docstrings:
- def get(self, request, slug=None): Retrieve
- def put(self, request, slug=None): Update
<|skeleton|>
... | 98e1ff8bab7dda3492e5ff637bf5aafd111c840c | <|skeleton|>
class InstrumentAnalysisRetrieveUpdateDestroyAPIView:
def get(self, request, slug=None):
"""Retrieve"""
<|body_0|>
def put(self, request, slug=None):
"""Update"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InstrumentAnalysisRetrieveUpdateDestroyAPIView:
def get(self, request, slug=None):
"""Retrieve"""
skill_set = get_object_or_404(InstrumentAnalysis, slug=slug)
self.check_object_permissions(request, skill_set)
serializer = InstrumentAnalysisRetrieveUpdateSerializer(skill_set, ma... | the_stack_v2_python_sparse | mikaponics/instrument/views/resource/instrument_analysis_crud_views.py | mikaponics/mikaponics-back | train | 4 | |
09dc5b08544f1c579a47c0861aef266f7eb885f8 | [
"if n < 3:\n return 0\nelse:\n num_list = [1] * n\n num_list[0], num_list[1] = (0, 0)\n for i in range(2, int(n ** 0.5 + 1)):\n if num_list[i] == 1:\n num_list[i * i:n:i] = [0] * len(num_list[i * i:n:i])\n return sum(num_list)",
"pre = None\nwhile head:\n tmp = head.next\n h... | <|body_start_0|>
if n < 3:
return 0
else:
num_list = [1] * n
num_list[0], num_list[1] = (0, 0)
for i in range(2, int(n ** 0.5 + 1)):
if num_list[i] == 1:
num_list[i * i:n:i] = [0] * len(num_list[i * i:n:i])
r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countPrimes(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n < 3:
return 0
else:
... | stack_v2_sparse_classes_10k_train_001543 | 1,059 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "countPrimes",
"signature": "def countPrimes(self, n)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList",
"signature": "def reverseList(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005348 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimes(self, n): :type n: int :rtype: int
- def reverseList(self, head): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimes(self, n): :type n: int :rtype: int
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
def countPrimes(self, n... | 4251f7d8f4b5c30546424f823a0ec527a06dda5d | <|skeleton|>
class Solution:
def countPrimes(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def countPrimes(self, n):
""":type n: int :rtype: int"""
if n < 3:
return 0
else:
num_list = [1] * n
num_list[0], num_list[1] = (0, 0)
for i in range(2, int(n ** 0.5 + 1)):
if num_list[i] == 1:
... | the_stack_v2_python_sparse | leetcode/11-27-test.py | MaLei666/learngit | train | 0 | |
9280b8a652b605b6c18b40ac13aa790e819341b4 | [
"content_type = ContentType.objects.get_for_model(instance.__class__)\nobject_id = instance.id\nqueryset = super(UserTrackerManager, self).filter(content_type=content_type, object_id=object_id)\nreturn queryset",
"if request.user.is_authenticated:\n viewed_item = self.filter_by_model(instance=instance).filter(... | <|body_start_0|>
content_type = ContentType.objects.get_for_model(instance.__class__)
object_id = instance.id
queryset = super(UserTrackerManager, self).filter(content_type=content_type, object_id=object_id)
return queryset
<|end_body_0|>
<|body_start_1|>
if request.user.is_auth... | UserTrackerManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserTrackerManager:
def filter_by_model(self, instance):
"""bar assasse model filter mikone"""
<|body_0|>
def recommended_list(self, request, instance):
"""ye recommended list bar assasse category va session"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_001544 | 3,879 | permissive | [
{
"docstring": "bar assasse model filter mikone",
"name": "filter_by_model",
"signature": "def filter_by_model(self, instance)"
},
{
"docstring": "ye recommended list bar assasse category va session",
"name": "recommended_list",
"signature": "def recommended_list(self, request, instance)... | 2 | stack_v2_sparse_classes_30k_train_006793 | Implement the Python class `UserTrackerManager` described below.
Class description:
Implement the UserTrackerManager class.
Method signatures and docstrings:
- def filter_by_model(self, instance): bar assasse model filter mikone
- def recommended_list(self, request, instance): ye recommended list bar assasse category... | Implement the Python class `UserTrackerManager` described below.
Class description:
Implement the UserTrackerManager class.
Method signatures and docstrings:
- def filter_by_model(self, instance): bar assasse model filter mikone
- def recommended_list(self, request, instance): ye recommended list bar assasse category... | aef47922fdd6488550881ed9d42bf30a0d33a32a | <|skeleton|>
class UserTrackerManager:
def filter_by_model(self, instance):
"""bar assasse model filter mikone"""
<|body_0|>
def recommended_list(self, request, instance):
"""ye recommended list bar assasse category va session"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserTrackerManager:
def filter_by_model(self, instance):
"""bar assasse model filter mikone"""
content_type = ContentType.objects.get_for_model(instance.__class__)
object_id = instance.id
queryset = super(UserTrackerManager, self).filter(content_type=content_type, object_id=obj... | the_stack_v2_python_sparse | src/usertrackers/models.py | m3h-D/Myinfoblog | train | 0 | |
44f771ad2aa9d61407b6fb37a4e9a9cc35dbd7df | [
"if len(s) < k:\n return 0\ncount = collections.Counter(s)\nbefore = 0\nresult = 0\nfor i in range(len(s) + 1):\n if i == len(s) and before == 0:\n return len(s)\n if i == len(s) or count[s[i]] < k:\n current = s[before:i]\n if current:\n result = max(result, self.longestSub... | <|body_start_0|>
if len(s) < k:
return 0
count = collections.Counter(s)
before = 0
result = 0
for i in range(len(s) + 1):
if i == len(s) and before == 0:
return len(s)
if i == len(s) or count[s[i]] < k:
current =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_0|>
def longestSubstring_v2(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(s) < k:
... | stack_v2_sparse_classes_10k_train_001545 | 2,118 | no_license | [
{
"docstring": ":type s: str :type k: int :rtype: int",
"name": "longestSubstring",
"signature": "def longestSubstring(self, s, k)"
},
{
"docstring": ":type s: str :type k: int :rtype: int",
"name": "longestSubstring_v2",
"signature": "def longestSubstring_v2(self, s, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005874 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestSubstring(self, s, k): :type s: str :type k: int :rtype: int
- def longestSubstring_v2(self, s, k): :type s: str :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestSubstring(self, s, k): :type s: str :type k: int :rtype: int
- def longestSubstring_v2(self, s, k): :type s: str :type k: int :rtype: int
<|skeleton|>
class Solution:... | d6ddbef76dd8630234f669d272d1f8065c6be128 | <|skeleton|>
class Solution:
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_0|>
def longestSubstring_v2(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
if len(s) < k:
return 0
count = collections.Counter(s)
before = 0
result = 0
for i in range(len(s) + 1):
if i == len(s) and before == 0:
... | the_stack_v2_python_sparse | 395. Longest Substring with At Least K Repeating Characters.py | Mang0o/leetcode | train | 0 | |
1f11d1aa9246b51483f9f881a0aef16d0bbd2b22 | [
"super(VGG19, self).__init__()\nassert len(output_blocks) >= 1, 'Need at least one output block'\nself.output_blocks = sorted(output_blocks)\nlast_needed_block = self.output_blocks[-1]\nassert last_needed_block <= 5, 'VGG19 has at most 6 blocks'\nlayers = models.vgg19(pretrained=True).features\nself.blocks = nn.Mod... | <|body_start_0|>
super(VGG19, self).__init__()
assert len(output_blocks) >= 1, 'Need at least one output block'
self.output_blocks = sorted(output_blocks)
last_needed_block = self.output_blocks[-1]
assert last_needed_block <= 5, 'VGG19 has at most 6 blocks'
layers = model... | Pretrained VGG19 network, without fully connected layers | VGG19 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VGG19:
"""Pretrained VGG19 network, without fully connected layers"""
def __init__(self, output_blocks=[LAST_FEATURE_MAP], requires_grad=False):
"""Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indices of feature blocks to return. Each feature block ends be... | stack_v2_sparse_classes_10k_train_001546 | 2,538 | permissive | [
{
"docstring": "Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indices of feature blocks to return. Each feature block ends before a max-pooling layer, i.e. the output of a feature block is the output of the last convolutional layer and activation right before the feature map is downsc... | 2 | stack_v2_sparse_classes_30k_train_002674 | Implement the Python class `VGG19` described below.
Class description:
Pretrained VGG19 network, without fully connected layers
Method signatures and docstrings:
- def __init__(self, output_blocks=[LAST_FEATURE_MAP], requires_grad=False): Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indice... | Implement the Python class `VGG19` described below.
Class description:
Pretrained VGG19 network, without fully connected layers
Method signatures and docstrings:
- def __init__(self, output_blocks=[LAST_FEATURE_MAP], requires_grad=False): Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indice... | 1df1fd37e7adc812b7a5e3859801d8d4a5ff5905 | <|skeleton|>
class VGG19:
"""Pretrained VGG19 network, without fully connected layers"""
def __init__(self, output_blocks=[LAST_FEATURE_MAP], requires_grad=False):
"""Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indices of feature blocks to return. Each feature block ends be... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VGG19:
"""Pretrained VGG19 network, without fully connected layers"""
def __init__(self, output_blocks=[LAST_FEATURE_MAP], requires_grad=False):
"""Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indices of feature blocks to return. Each feature block ends before a max-po... | the_stack_v2_python_sparse | srgan/models/vgg.py | ZrbTz/HypernetworkSiren | train | 1 |
ce53712d4bb18831cbad74c8ec18ed70d25130df | [
"if root is None:\n return []\nif root.left is None and root.right is None:\n if sum == root.val:\n return [[root.val]]\n else:\n return []\nreturn [[root.val, *x] for x in self.pathSum(root.left, sum - root.val) + self.pathSum(root.right, sum - root.val)]",
"def dfs(node, backtrack, summat... | <|body_start_0|>
if root is None:
return []
if root.left is None and root.right is None:
if sum == root.val:
return [[root.val]]
else:
return []
return [[root.val, *x] for x in self.pathSum(root.left, sum - root.val) + self.path... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pathSum(self, root, sum):
"""05/06/2018 21:21"""
<|body_0|>
def pathSum(self, root: Optional[TreeNode], targetSum: int) -> List[List[int]]:
"""08/22/2021 22:30"""
<|body_1|>
def pathSum(self, root: Optional[TreeNode], targetSum: int) -> Lis... | stack_v2_sparse_classes_10k_train_001547 | 3,394 | no_license | [
{
"docstring": "05/06/2018 21:21",
"name": "pathSum",
"signature": "def pathSum(self, root, sum)"
},
{
"docstring": "08/22/2021 22:30",
"name": "pathSum",
"signature": "def pathSum(self, root: Optional[TreeNode], targetSum: int) -> List[List[int]]"
},
{
"docstring": "10/22/2022 0... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, sum): 05/06/2018 21:21
- def pathSum(self, root: Optional[TreeNode], targetSum: int) -> List[List[int]]: 08/22/2021 22:30
- def pathSum(self, root: Option... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, sum): 05/06/2018 21:21
- def pathSum(self, root: Optional[TreeNode], targetSum: int) -> List[List[int]]: 08/22/2021 22:30
- def pathSum(self, root: Option... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def pathSum(self, root, sum):
"""05/06/2018 21:21"""
<|body_0|>
def pathSum(self, root: Optional[TreeNode], targetSum: int) -> List[List[int]]:
"""08/22/2021 22:30"""
<|body_1|>
def pathSum(self, root: Optional[TreeNode], targetSum: int) -> Lis... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def pathSum(self, root, sum):
"""05/06/2018 21:21"""
if root is None:
return []
if root.left is None and root.right is None:
if sum == root.val:
return [[root.val]]
else:
return []
return [[root.val, ... | the_stack_v2_python_sparse | leetcode/solved/113_Path_Sum_II/solution.py | sungminoh/algorithms | train | 0 | |
f3dfca092894902a32bcede13550df83662b2c97 | [
"u = rolemanage(self.driver)\nu.open_rolemanage()\nself.assertEqual(u.verify(), True)\nu.modify_obj()\nself.assertEqual(u.sub_tagname(), '角色管理-修改')\nu.clear_name()\nu.add_role('Update', '')\nself.assertEqual(u.company_status(), False)\nu.add_save()\nself.assertEqual(u.success(), True)\nfunction.screenshot(self.driv... | <|body_start_0|>
u = rolemanage(self.driver)
u.open_rolemanage()
self.assertEqual(u.verify(), True)
u.modify_obj()
self.assertEqual(u.sub_tagname(), '角色管理-修改')
u.clear_name()
u.add_role('Update', '')
self.assertEqual(u.company_status(), False)
u.ad... | Test016_Role_Modify_P1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test016_Role_Modify_P1:
def test_modify_name(self):
"""修改角色名称"""
<|body_0|>
def test_modify_description(self):
"""修改角色备注"""
<|body_1|>
def test_modify_type(self):
"""修改角色类型"""
<|body_2|>
def test_modify_back(self):
"""修改角色并返回... | stack_v2_sparse_classes_10k_train_001548 | 2,067 | no_license | [
{
"docstring": "修改角色名称",
"name": "test_modify_name",
"signature": "def test_modify_name(self)"
},
{
"docstring": "修改角色备注",
"name": "test_modify_description",
"signature": "def test_modify_description(self)"
},
{
"docstring": "修改角色类型",
"name": "test_modify_type",
"signatur... | 4 | stack_v2_sparse_classes_30k_train_006988 | Implement the Python class `Test016_Role_Modify_P1` described below.
Class description:
Implement the Test016_Role_Modify_P1 class.
Method signatures and docstrings:
- def test_modify_name(self): 修改角色名称
- def test_modify_description(self): 修改角色备注
- def test_modify_type(self): 修改角色类型
- def test_modify_back(self): 修改角色... | Implement the Python class `Test016_Role_Modify_P1` described below.
Class description:
Implement the Test016_Role_Modify_P1 class.
Method signatures and docstrings:
- def test_modify_name(self): 修改角色名称
- def test_modify_description(self): 修改角色备注
- def test_modify_type(self): 修改角色类型
- def test_modify_back(self): 修改角色... | 6f42c25249fc642cecc270578a180820988d45b5 | <|skeleton|>
class Test016_Role_Modify_P1:
def test_modify_name(self):
"""修改角色名称"""
<|body_0|>
def test_modify_description(self):
"""修改角色备注"""
<|body_1|>
def test_modify_type(self):
"""修改角色类型"""
<|body_2|>
def test_modify_back(self):
"""修改角色并返回... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test016_Role_Modify_P1:
def test_modify_name(self):
"""修改角色名称"""
u = rolemanage(self.driver)
u.open_rolemanage()
self.assertEqual(u.verify(), True)
u.modify_obj()
self.assertEqual(u.sub_tagname(), '角色管理-修改')
u.clear_name()
u.add_role('Update', ''... | the_stack_v2_python_sparse | GlxssLive_web/TestCase/Manage_Role/Test016_role_modify_P1.py | rrmiracle/GlxssLive | train | 0 | |
946c0e46b7e3e6b2a39f7d7686a6a31e7051d7df | [
"super(LSTMime, self).__init__()\nself.hidden_size = d_model\nself.lstm = nn.LSTM(input_size=input_size, hidden_size=d_model, num_layers=layers, batch_first=True)\nself.fc1 = nn.Linear(d_model, d_model)\nself.fc2 = nn.Linear(d_model, num_experts)\nself.fc3 = nn.Linear(d_model, out_len)\nself.drop_out = nn.Dropout(d... | <|body_start_0|>
super(LSTMime, self).__init__()
self.hidden_size = d_model
self.lstm = nn.LSTM(input_size=input_size, hidden_size=d_model, num_layers=layers, batch_first=True)
self.fc1 = nn.Linear(d_model, d_model)
self.fc2 = nn.Linear(d_model, num_experts)
self.fc3 = nn... | An implementation of LSTM. This LSTM is used by interpretable mixture of expert as assigner module. | LSTMime | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSTMime:
"""An implementation of LSTM. This LSTM is used by interpretable mixture of expert as assigner module."""
def __init__(self, input_size, num_experts, out_len, d_model=512, layers=3, dropout=0.0, device=torch.device('cuda:0')):
"""Initializes a LSTMime instance. Args: input_s... | stack_v2_sparse_classes_10k_train_001549 | 4,262 | permissive | [
{
"docstring": "Initializes a LSTMime instance. Args: input_size: Input features dimension num_experts: Number of experts out_len: Forecasting horizon d_model: Hidden layer dimension layers: Number of LSTM layers. dropout: Fraction of neurons affected by Dropout (default=0.0). device: Device used by the model",... | 2 | null | Implement the Python class `LSTMime` described below.
Class description:
An implementation of LSTM. This LSTM is used by interpretable mixture of expert as assigner module.
Method signatures and docstrings:
- def __init__(self, input_size, num_experts, out_len, d_model=512, layers=3, dropout=0.0, device=torch.device(... | Implement the Python class `LSTMime` described below.
Class description:
An implementation of LSTM. This LSTM is used by interpretable mixture of expert as assigner module.
Method signatures and docstrings:
- def __init__(self, input_size, num_experts, out_len, d_model=512, layers=3, dropout=0.0, device=torch.device(... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class LSTMime:
"""An implementation of LSTM. This LSTM is used by interpretable mixture of expert as assigner module."""
def __init__(self, input_size, num_experts, out_len, d_model=512, layers=3, dropout=0.0, device=torch.device('cuda:0')):
"""Initializes a LSTMime instance. Args: input_s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LSTMime:
"""An implementation of LSTM. This LSTM is used by interpretable mixture of expert as assigner module."""
def __init__(self, input_size, num_experts, out_len, d_model=512, layers=3, dropout=0.0, device=torch.device('cuda:0')):
"""Initializes a LSTMime instance. Args: input_size: Input fe... | the_stack_v2_python_sparse | ime/models/lstm.py | Jimmy-INL/google-research | train | 1 |
5990ccb1b5f9112ef136e851311cd6ffc554c581 | [
"m, n = (len(grid), len(grid[0]))\ndp = [[0] * (n + 1) for _ in range(m + 1)]\nfor i in range(1, m + 1):\n for j in range(1, n + 1):\n dp[i][j] = max(dp[i - 1][j], dp[i][j - 1]) + grid[i - 1][j - 1]\nreturn dp[-1][-1]",
"m, n = (len(grid), len(grid[0]))\ndp = [0] * (n + 1)\nfor i in range(1, m + 1):\n ... | <|body_start_0|>
m, n = (len(grid), len(grid[0]))
dp = [[0] * (n + 1) for _ in range(m + 1)]
for i in range(1, m + 1):
for j in range(1, n + 1):
dp[i][j] = max(dp[i - 1][j], dp[i][j - 1]) + grid[i - 1][j - 1]
return dp[-1][-1]
<|end_body_0|>
<|body_start_1|>
... | Soluton | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Soluton:
def maxValue(self, grid):
"""dp[i][j] 从(0, 0)走到(i, j) 的最大价值 dp[i][j] = max(dp[i-1_最短回文串.py][j], dp[i][j-1_最短回文串.py]) + grid[i][j] 边界 dp[i][0] = 0 dp[0][i] res = dp[-1_最短回文串.py][-1_最短回文串.py] 时间复杂度 O(mn) 空间 O(mn)"""
<|body_0|>
def maxValue(self, grid):
"""dp[i... | stack_v2_sparse_classes_10k_train_001550 | 1,413 | no_license | [
{
"docstring": "dp[i][j] 从(0, 0)走到(i, j) 的最大价值 dp[i][j] = max(dp[i-1_最短回文串.py][j], dp[i][j-1_最短回文串.py]) + grid[i][j] 边界 dp[i][0] = 0 dp[0][i] res = dp[-1_最短回文串.py][-1_最短回文串.py] 时间复杂度 O(mn) 空间 O(mn)",
"name": "maxValue",
"signature": "def maxValue(self, grid)"
},
{
"docstring": "dp[i][j] 从(0, 0)走... | 2 | null | Implement the Python class `Soluton` described below.
Class description:
Implement the Soluton class.
Method signatures and docstrings:
- def maxValue(self, grid): dp[i][j] 从(0, 0)走到(i, j) 的最大价值 dp[i][j] = max(dp[i-1_最短回文串.py][j], dp[i][j-1_最短回文串.py]) + grid[i][j] 边界 dp[i][0] = 0 dp[0][i] res = dp[-1_最短回文串.py][-1_最短回... | Implement the Python class `Soluton` described below.
Class description:
Implement the Soluton class.
Method signatures and docstrings:
- def maxValue(self, grid): dp[i][j] 从(0, 0)走到(i, j) 的最大价值 dp[i][j] = max(dp[i-1_最短回文串.py][j], dp[i][j-1_最短回文串.py]) + grid[i][j] 边界 dp[i][0] = 0 dp[0][i] res = dp[-1_最短回文串.py][-1_最短回... | 57f303aa6e76f7c5292fa60bffdfddcb4ff9ddfb | <|skeleton|>
class Soluton:
def maxValue(self, grid):
"""dp[i][j] 从(0, 0)走到(i, j) 的最大价值 dp[i][j] = max(dp[i-1_最短回文串.py][j], dp[i][j-1_最短回文串.py]) + grid[i][j] 边界 dp[i][0] = 0 dp[0][i] res = dp[-1_最短回文串.py][-1_最短回文串.py] 时间复杂度 O(mn) 空间 O(mn)"""
<|body_0|>
def maxValue(self, grid):
"""dp[i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Soluton:
def maxValue(self, grid):
"""dp[i][j] 从(0, 0)走到(i, j) 的最大价值 dp[i][j] = max(dp[i-1_最短回文串.py][j], dp[i][j-1_最短回文串.py]) + grid[i][j] 边界 dp[i][0] = 0 dp[0][i] res = dp[-1_最短回文串.py][-1_最短回文串.py] 时间复杂度 O(mn) 空间 O(mn)"""
m, n = (len(grid), len(grid[0]))
dp = [[0] * (n + 1) for _ in r... | the_stack_v2_python_sparse | 3_Offer2nd-HandWriting/6_DP/7_礼物的最大价值.py | fzingithub/SwordRefers2Offer | train | 1 | |
91dacf26f4827d2e5dca7d9bf3ed15454aafedf7 | [
"self.n = n\nself.discount = discount\nself.prices = {k: v for k, v in zip(products, prices)}\nself.c = 1",
"s = 0\nfor p, c in zip(product, amount):\n s += self.prices[p] * c\nif self.c == self.n:\n s *= 1 - self.discount / 100.0\n self.c = 1\nelse:\n self.c += 1\nreturn s"
] | <|body_start_0|>
self.n = n
self.discount = discount
self.prices = {k: v for k, v in zip(products, prices)}
self.c = 1
<|end_body_0|>
<|body_start_1|>
s = 0
for p, c in zip(product, amount):
s += self.prices[p] * c
if self.c == self.n:
s *... | Cashier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
<|body_0|>
def getBill(self, product, amount):
""":type product: List[int] :type amount: List[int] :rtype: float"""
... | stack_v2_sparse_classes_10k_train_001551 | 3,686 | no_license | [
{
"docstring": ":type n: int :type discount: int :type products: List[int] :type prices: List[int]",
"name": "__init__",
"signature": "def __init__(self, n, discount, products, prices)"
},
{
"docstring": ":type product: List[int] :type amount: List[int] :rtype: float",
"name": "getBill",
... | 2 | stack_v2_sparse_classes_30k_train_006032 | Implement the Python class `Cashier` described below.
Class description:
Implement the Cashier class.
Method signatures and docstrings:
- def __init__(self, n, discount, products, prices): :type n: int :type discount: int :type products: List[int] :type prices: List[int]
- def getBill(self, product, amount): :type pr... | Implement the Python class `Cashier` described below.
Class description:
Implement the Cashier class.
Method signatures and docstrings:
- def __init__(self, n, discount, products, prices): :type n: int :type discount: int :type products: List[int] :type prices: List[int]
- def getBill(self, product, amount): :type pr... | f2bf9b13508cd01c8f383789569e55a438f77202 | <|skeleton|>
class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
<|body_0|>
def getBill(self, product, amount):
""":type product: List[int] :type amount: List[int] :rtype: float"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
self.n = n
self.discount = discount
self.prices = {k: v for k, v in zip(products, prices)}
self.c = 1
def getBill(se... | the_stack_v2_python_sparse | version1/1357_Apply_Discount_Every_n_Orders.py | moontree/leetcode | train | 1 | |
b788c401a0d172e09009ea433b224665ee1c62da | [
"super().__init__(device=device, env=env, tx_conn=tx_conn, topics_to_subs=topics_to_subs)\nself.done = False\nself.stop_queue = stop_queue\nself.received_event = False",
"ev = DummyServiceEvent(self.env, 'aa:aa:aa:aa:aa:aa', 'dummy_value')\nyield self.async_wait_for_event(ev)\nself.received_event = True\nself.sto... | <|body_start_0|>
super().__init__(device=device, env=env, tx_conn=tx_conn, topics_to_subs=topics_to_subs)
self.done = False
self.stop_queue = stop_queue
self.received_event = False
<|end_body_0|>
<|body_start_1|>
ev = DummyServiceEvent(self.env, 'aa:aa:aa:aa:aa:aa', 'dummy_value... | WaiterService | [
"Apache-2.0",
"GPL-1.0-or-later",
"GPL-2.0-or-later",
"GPL-2.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WaiterService:
def __init__(self, device, env, tx_conn, topics_to_subs, stop_queue):
"""Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice that owns the service env: simpy environment tx_conn: Connection (e.g. pipe end with 'send' method) us... | stack_v2_sparse_classes_10k_train_001552 | 4,078 | permissive | [
{
"docstring": "Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice that owns the service env: simpy environment tx_conn: Connection (e.g. pipe end with 'send' method) used to send packets.",
"name": "__init__",
"signature": "def __init__(self, device, env, ... | 2 | stack_v2_sparse_classes_30k_train_001042 | Implement the Python class `WaiterService` described below.
Class description:
Implement the WaiterService class.
Method signatures and docstrings:
- def __init__(self, device, env, tx_conn, topics_to_subs, stop_queue): Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice ... | Implement the Python class `WaiterService` described below.
Class description:
Implement the WaiterService class.
Method signatures and docstrings:
- def __init__(self, device, env, tx_conn, topics_to_subs, stop_queue): Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice ... | 3a6d63af1ff468f94887a091e3a408a8449cf832 | <|skeleton|>
class WaiterService:
def __init__(self, device, env, tx_conn, topics_to_subs, stop_queue):
"""Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice that owns the service env: simpy environment tx_conn: Connection (e.g. pipe end with 'send' method) us... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WaiterService:
def __init__(self, device, env, tx_conn, topics_to_subs, stop_queue):
"""Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice that owns the service env: simpy environment tx_conn: Connection (e.g. pipe end with 'send' method) used to send pac... | the_stack_v2_python_sparse | scripts/automation/trex_control_plane/interactive/trex/wireless/services/unit_tests/wireless_service_event_test.py | elados93/trex-core | train | 1 | |
2333602754edf3221787eeb0323fd210ba613ab9 | [
"self.battery_size = battery_size\nif self.battery_size == 70:\n self.range = 240\nelif self.battery_size == 85:\n self.range = 270",
"message = 'This car can go approximately ' + str(self.range)\nmessage += ' miles on a full charge.'\nprint(message)"
] | <|body_start_0|>
self.battery_size = battery_size
if self.battery_size == 70:
self.range = 240
elif self.battery_size == 85:
self.range = 270
<|end_body_0|>
<|body_start_1|>
message = 'This car can go approximately ' + str(self.range)
message += ' miles o... | A simple model of an electic car battery. | Battery | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Battery:
"""A simple model of an electic car battery."""
def __init__(self, battery_size):
"""Initialize the battery's attributes."""
<|body_0|>
def get_range(self):
"""Print the range of the battery."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_001553 | 2,340 | no_license | [
{
"docstring": "Initialize the battery's attributes.",
"name": "__init__",
"signature": "def __init__(self, battery_size)"
},
{
"docstring": "Print the range of the battery.",
"name": "get_range",
"signature": "def get_range(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003107 | Implement the Python class `Battery` described below.
Class description:
A simple model of an electic car battery.
Method signatures and docstrings:
- def __init__(self, battery_size): Initialize the battery's attributes.
- def get_range(self): Print the range of the battery. | Implement the Python class `Battery` described below.
Class description:
A simple model of an electic car battery.
Method signatures and docstrings:
- def __init__(self, battery_size): Initialize the battery's attributes.
- def get_range(self): Print the range of the battery.
<|skeleton|>
class Battery:
"""A sim... | 115f712e0c7e3d02270b8748fcff85f0e3df2c30 | <|skeleton|>
class Battery:
"""A simple model of an electic car battery."""
def __init__(self, battery_size):
"""Initialize the battery's attributes."""
<|body_0|>
def get_range(self):
"""Print the range of the battery."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Battery:
"""A simple model of an electic car battery."""
def __init__(self, battery_size):
"""Initialize the battery's attributes."""
self.battery_size = battery_size
if self.battery_size == 70:
self.range = 240
elif self.battery_size == 85:
self.ra... | the_stack_v2_python_sparse | python_crash_course/car_classes.py | keithkay/python | train | 0 |
c3fd0c2b8cda7614eb66345f4411756675d544bb | [
"if len(ransomNote) > len(magazine):\n return False\nif not ransomNote:\n return True\ndic = defaultdict(int)\nfor i in ransomNote:\n dic[i] += 1\nfor k in dic.keys():\n if magazine.count(k) < dic[k]:\n return False\nreturn True",
"a = dict(collections.Counter(ransomNote))\nfor k, v in a.items(... | <|body_start_0|>
if len(ransomNote) > len(magazine):
return False
if not ransomNote:
return True
dic = defaultdict(int)
for i in ransomNote:
dic[i] += 1
for k in dic.keys():
if magazine.count(k) < dic[k]:
return Fals... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canConstruct(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_0|>
def canConstruct(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k_train_001554 | 869 | no_license | [
{
"docstring": ":type ransomNote: str :type magazine: str :rtype: bool",
"name": "canConstruct",
"signature": "def canConstruct(self, ransomNote, magazine)"
},
{
"docstring": ":type ransomNote: str :type magazine: str :rtype: bool",
"name": "canConstruct",
"signature": "def canConstruct(... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canConstruct(self, ransomNote, magazine): :type ransomNote: str :type magazine: str :rtype: bool
- def canConstruct(self, ransomNote, magazine): :type ransomNote: str :type m... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canConstruct(self, ransomNote, magazine): :type ransomNote: str :type magazine: str :rtype: bool
- def canConstruct(self, ransomNote, magazine): :type ransomNote: str :type m... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def canConstruct(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_0|>
def canConstruct(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def canConstruct(self, ransomNote, magazine):
""":type ransomNote: str :type magazine: str :rtype: bool"""
if len(ransomNote) > len(magazine):
return False
if not ransomNote:
return True
dic = defaultdict(int)
for i in ransomNote:
... | the_stack_v2_python_sparse | 0383_Ransom_Note.py | bingli8802/leetcode | train | 0 | |
6731c1d7b9275bf8364ee4f2c2af3919903dc619 | [
"super().__init__(imageset, threshold_function, mask, region_of_interest, max_strong_pixel_fraction, compute_mean_background)\nself.min_spot_size = min_spot_size\nself.max_spot_size = max_spot_size\nself.filter_spots = filter_spots",
"num_panels = len(self.imageset.get_detector())\npixel_labeller = [PixelListLabe... | <|body_start_0|>
super().__init__(imageset, threshold_function, mask, region_of_interest, max_strong_pixel_fraction, compute_mean_background)
self.min_spot_size = min_spot_size
self.max_spot_size = max_spot_size
self.filter_spots = filter_spots
<|end_body_0|>
<|body_start_1|>
nu... | A class to extract pixels from a single image | ExtractPixelsFromImage2DNoShoeboxes | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtractPixelsFromImage2DNoShoeboxes:
"""A class to extract pixels from a single image"""
def __init__(self, imageset, threshold_function, mask, region_of_interest, max_strong_pixel_fraction, compute_mean_background, min_spot_size, max_spot_size, filter_spots):
"""Initialise the class... | stack_v2_sparse_classes_10k_train_001555 | 29,989 | permissive | [
{
"docstring": "Initialise the class :param imageset: The imageset to extract from :param threshold_function: The function to threshold with :param mask: The image mask :param region_of_interest: A region of interest to process :param max_strong_pixel_fraction: The maximum fraction of pixels allowed",
"name... | 2 | null | Implement the Python class `ExtractPixelsFromImage2DNoShoeboxes` described below.
Class description:
A class to extract pixels from a single image
Method signatures and docstrings:
- def __init__(self, imageset, threshold_function, mask, region_of_interest, max_strong_pixel_fraction, compute_mean_background, min_spot... | Implement the Python class `ExtractPixelsFromImage2DNoShoeboxes` described below.
Class description:
A class to extract pixels from a single image
Method signatures and docstrings:
- def __init__(self, imageset, threshold_function, mask, region_of_interest, max_strong_pixel_fraction, compute_mean_background, min_spot... | 88bf7f7c5ac44defc046ebf0719cde748092cfff | <|skeleton|>
class ExtractPixelsFromImage2DNoShoeboxes:
"""A class to extract pixels from a single image"""
def __init__(self, imageset, threshold_function, mask, region_of_interest, max_strong_pixel_fraction, compute_mean_background, min_spot_size, max_spot_size, filter_spots):
"""Initialise the class... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExtractPixelsFromImage2DNoShoeboxes:
"""A class to extract pixels from a single image"""
def __init__(self, imageset, threshold_function, mask, region_of_interest, max_strong_pixel_fraction, compute_mean_background, min_spot_size, max_spot_size, filter_spots):
"""Initialise the class :param image... | the_stack_v2_python_sparse | src/dials/algorithms/spot_finding/finder.py | dials/dials | train | 71 |
533090537ef05fc6faa3738b6a8c8bfa6c2ca461 | [
"pos = 0\nwhile pos < len(self.value):\n list_entry_header = self.value[pos:pos + 26]\n if len(list_entry_header) != 26:\n break\n attribute_type_code, record_length, attribute_name_length, attribute_name_offset, lowest_vcn, segment_reference, attribute_instance = struct.unpack('<LHBBQQH', list_entr... | <|body_start_0|>
pos = 0
while pos < len(self.value):
list_entry_header = self.value[pos:pos + 26]
if len(list_entry_header) != 26:
break
attribute_type_code, record_length, attribute_name_length, attribute_name_offset, lowest_vcn, segment_reference, a... | $ATTRIBUTE_LIST. | AttributeList | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttributeList:
"""$ATTRIBUTE_LIST."""
def entries(self):
"""This method yields each attribute list entry (AttributeListEntry)."""
<|body_0|>
def print_information(self):
"""Print all information in a human-readable form."""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_10k_train_001556 | 36,119 | permissive | [
{
"docstring": "This method yields each attribute list entry (AttributeListEntry).",
"name": "entries",
"signature": "def entries(self)"
},
{
"docstring": "Print all information in a human-readable form.",
"name": "print_information",
"signature": "def print_information(self)"
}
] | 2 | null | Implement the Python class `AttributeList` described below.
Class description:
$ATTRIBUTE_LIST.
Method signatures and docstrings:
- def entries(self): This method yields each attribute list entry (AttributeListEntry).
- def print_information(self): Print all information in a human-readable form. | Implement the Python class `AttributeList` described below.
Class description:
$ATTRIBUTE_LIST.
Method signatures and docstrings:
- def entries(self): This method yields each attribute list entry (AttributeListEntry).
- def print_information(self): Print all information in a human-readable form.
<|skeleton|>
class A... | f9299b8ad0cb2a6bbbd5e65f01d2ba06406c70ac | <|skeleton|>
class AttributeList:
"""$ATTRIBUTE_LIST."""
def entries(self):
"""This method yields each attribute list entry (AttributeListEntry)."""
<|body_0|>
def print_information(self):
"""Print all information in a human-readable form."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AttributeList:
"""$ATTRIBUTE_LIST."""
def entries(self):
"""This method yields each attribute list entry (AttributeListEntry)."""
pos = 0
while pos < len(self.value):
list_entry_header = self.value[pos:pos + 26]
if len(list_entry_header) != 26:
... | the_stack_v2_python_sparse | modules/NTFS/dfir_ntfs/Attributes.py | dfrc-korea/carpe | train | 75 |
17b08756a0fd45fe379484af9ec8d98b7a266698 | [
"self.lenses_list = lenses_list\nself.sources_list = sources_list\nself.global_dict = global_dict\nself.observation_dict = observation_dict\nself.set_up_global()\nself.set_up_observation()",
"self.z_s = self.global_dict['z_s']\nself.z_l = self.global_dict['z_l']\nself.D_s = Planck15.angular_diameter_distance(z=se... | <|body_start_0|>
self.lenses_list = lenses_list
self.sources_list = sources_list
self.global_dict = global_dict
self.observation_dict = observation_dict
self.set_up_global()
self.set_up_observation()
<|end_body_0|>
<|body_start_1|>
self.z_s = self.global_dict['z_... | LensingSim | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LensingSim:
def __init__(self, lenses_list=[{}], sources_list=[{}], global_dict={}, observation_dict={}):
"""Class for simulation of strong lensing images"""
<|body_0|>
def set_up_global(self):
"""Set some global variables so don't need to recompute each time"""
... | stack_v2_sparse_classes_10k_train_001557 | 5,119 | permissive | [
{
"docstring": "Class for simulation of strong lensing images",
"name": "__init__",
"signature": "def __init__(self, lenses_list=[{}], sources_list=[{}], global_dict={}, observation_dict={})"
},
{
"docstring": "Set some global variables so don't need to recompute each time",
"name": "set_up_... | 4 | stack_v2_sparse_classes_30k_train_003894 | Implement the Python class `LensingSim` described below.
Class description:
Implement the LensingSim class.
Method signatures and docstrings:
- def __init__(self, lenses_list=[{}], sources_list=[{}], global_dict={}, observation_dict={}): Class for simulation of strong lensing images
- def set_up_global(self): Set som... | Implement the Python class `LensingSim` described below.
Class description:
Implement the LensingSim class.
Method signatures and docstrings:
- def __init__(self, lenses_list=[{}], sources_list=[{}], global_dict={}, observation_dict={}): Class for simulation of strong lensing images
- def set_up_global(self): Set som... | 8f432b58cecdafd70054fa63f285f3f284fa0720 | <|skeleton|>
class LensingSim:
def __init__(self, lenses_list=[{}], sources_list=[{}], global_dict={}, observation_dict={}):
"""Class for simulation of strong lensing images"""
<|body_0|>
def set_up_global(self):
"""Set some global variables so don't need to recompute each time"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LensingSim:
def __init__(self, lenses_list=[{}], sources_list=[{}], global_dict={}, observation_dict={}):
"""Class for simulation of strong lensing images"""
self.lenses_list = lenses_list
self.sources_list = sources_list
self.global_dict = global_dict
self.observation_... | the_stack_v2_python_sparse | simulation/lensing_sim.py | smsharma/mining-for-substructure-lens | train | 25 | |
3c26419e5d29474b3dff3181b455a9518d5c97ad | [
"storage = get_storage()\nauth0_id = get_auth0_id_of_user(email)\nuser_id = storage.read_user_id(auth0_id)\nreturn super().post(user_id, role_id)",
"storage = get_storage()\nauth0_id = get_auth0_id_of_user(email)\ntry:\n user_id = storage.read_user_id(auth0_id)\nexcept StorageAuthError:\n return ('', 204)\n... | <|body_start_0|>
storage = get_storage()
auth0_id = get_auth0_id_of_user(email)
user_id = storage.read_user_id(auth0_id)
return super().post(user_id, role_id)
<|end_body_0|>
<|body_start_1|>
storage = get_storage()
auth0_id = get_auth0_id_of_user(email)
try:
... | UserRolesManagementByEmailView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRolesManagementByEmailView:
def post(self, email, role_id):
"""--- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Roles responses: 204: description: Role Added Successfully. 401: $ref: '#/components/responses/401-Unauthorized' 404: $ref... | stack_v2_sparse_classes_10k_train_001558 | 12,608 | permissive | [
{
"docstring": "--- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Roles responses: 204: description: Role Added Successfully. 401: $ref: '#/components/responses/401-Unauthorized' 404: $ref: '#/components/responses/404-NotFound'",
"name": "post",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_002794 | Implement the Python class `UserRolesManagementByEmailView` described below.
Class description:
Implement the UserRolesManagementByEmailView class.
Method signatures and docstrings:
- def post(self, email, role_id): --- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Rol... | Implement the Python class `UserRolesManagementByEmailView` described below.
Class description:
Implement the UserRolesManagementByEmailView class.
Method signatures and docstrings:
- def post(self, email, role_id): --- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Rol... | 280800c73eb7cfd49029462b352887e78f1ff91b | <|skeleton|>
class UserRolesManagementByEmailView:
def post(self, email, role_id):
"""--- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Roles responses: 204: description: Role Added Successfully. 401: $ref: '#/components/responses/401-Unauthorized' 404: $ref... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserRolesManagementByEmailView:
def post(self, email, role_id):
"""--- summary: Add a Role to a User by email. parameters: - email - role_id tags: - Users-By-Email - Roles responses: 204: description: Role Added Successfully. 401: $ref: '#/components/responses/401-Unauthorized' 404: $ref: '#/component... | the_stack_v2_python_sparse | sfa_api/users.py | SolarArbiter/solarforecastarbiter-api | train | 9 | |
9c4bb1ab64b3d3e0cbcc036288cbd4a5e986c27d | [
"try:\n response = Database.Table.get_item(Key={'DocumentID': document_id})\nexcept Exception as e:\n response = None\n Logger.info(f'Database GetDocument : document_id = {document_id} : exception = {e}')\nif response and response.get('Item') and (response['ResponseMetadata']['HTTPStatusCode'] == 200):\n ... | <|body_start_0|>
try:
response = Database.Table.get_item(Key={'DocumentID': document_id})
except Exception as e:
response = None
Logger.info(f'Database GetDocument : document_id = {document_id} : exception = {e}')
if response and response.get('Item') and (resp... | Database Abstraction Layer | Database | [
"Apache-2.0",
"MIT-0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Database:
"""Database Abstraction Layer"""
def GetDocument(document_id: str) -> Document:
"""Fetch a specific document"""
<|body_0|>
def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]:
"""Fetch a specific document set"""
<|body_1... | stack_v2_sparse_classes_10k_train_001559 | 3,107 | permissive | [
{
"docstring": "Fetch a specific document",
"name": "GetDocument",
"signature": "def GetDocument(document_id: str) -> Document"
},
{
"docstring": "Fetch a specific document set",
"name": "GetDocuments",
"signature": "def GetDocuments(stages: List[Stage], states: List[State]) -> List[Docu... | 4 | stack_v2_sparse_classes_30k_train_001957 | Implement the Python class `Database` described below.
Class description:
Database Abstraction Layer
Method signatures and docstrings:
- def GetDocument(document_id: str) -> Document: Fetch a specific document
- def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]: Fetch a specific document se... | Implement the Python class `Database` described below.
Class description:
Database Abstraction Layer
Method signatures and docstrings:
- def GetDocument(document_id: str) -> Document: Fetch a specific document
- def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]: Fetch a specific document se... | 633e6291eea95a3933d34cae53b68cf6570b9bbb | <|skeleton|>
class Database:
"""Database Abstraction Layer"""
def GetDocument(document_id: str) -> Document:
"""Fetch a specific document"""
<|body_0|>
def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]:
"""Fetch a specific document set"""
<|body_1... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Database:
"""Database Abstraction Layer"""
def GetDocument(document_id: str) -> Document:
"""Fetch a specific document"""
try:
response = Database.Table.get_item(Key={'DocumentID': document_id})
except Exception as e:
response = None
Logger.info... | the_stack_v2_python_sparse | source/lambdas/shared/database.py | jhasatis/TabularDocumentDigitization | train | 0 |
dc92843aa5e5d967194dd284517e082eb1df4776 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Onenote()",
"from .entity import Entity\nfrom .notebook import Notebook\nfrom .onenote_operation import OnenoteOperation\nfrom .onenote_page import OnenotePage\nfrom .onenote_resource import OnenoteResource\nfrom .onenote_section impor... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Onenote()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .notebook import Notebook
from .onenote_operation import OnenoteOperation
from .onenote_page imp... | Onenote | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Onenote:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Onenote:
"""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: Onenote"""... | stack_v2_sparse_classes_10k_train_001560 | 4,865 | 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: Onenote",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse... | 3 | stack_v2_sparse_classes_30k_train_002802 | Implement the Python class `Onenote` described below.
Class description:
Implement the Onenote class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Onenote: Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | Implement the Python class `Onenote` described below.
Class description:
Implement the Onenote class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Onenote: Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Onenote:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Onenote:
"""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: Onenote"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Onenote:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Onenote:
"""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: Onenote"""
if no... | the_stack_v2_python_sparse | msgraph/generated/models/onenote.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
099cb67cd295cd3c425fc8aaac0ce577b8b72c80 | [
"downsample_raito = H // SparseHelper._cur_active.shape[-1]\nactive_ex = SparseHelper._cur_active.repeat_interleave(downsample_raito, 2).repeat_interleave(downsample_raito, 3)\nreturn active_ex if returning_active_map else active_ex.squeeze(1).nonzero(as_tuple=True)",
"x = super(type(self), self).forward(x)\nx *=... | <|body_start_0|>
downsample_raito = H // SparseHelper._cur_active.shape[-1]
active_ex = SparseHelper._cur_active.repeat_interleave(downsample_raito, 2).repeat_interleave(downsample_raito, 3)
return active_ex if returning_active_map else active_ex.squeeze(1).nonzero(as_tuple=True)
<|end_body_0|>
... | The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc. | SparseHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SparseHelper:
"""The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc."""
def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor:
"""Get current active map with (B, 1, f, f) shape or index format."""
... | stack_v2_sparse_classes_10k_train_001561 | 5,428 | permissive | [
{
"docstring": "Get current active map with (B, 1, f, f) shape or index format.",
"name": "_get_active_map_or_index",
"signature": "def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor"
},
{
"docstring": "Sparse convolution forward function.",
"name": "sp_con... | 3 | null | Implement the Python class `SparseHelper` described below.
Class description:
The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc.
Method signatures and docstrings:
- def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor: Get current... | Implement the Python class `SparseHelper` described below.
Class description:
The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc.
Method signatures and docstrings:
- def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor: Get current... | d2ccc44a2c8e5d49bb26187aff42f2abc90aee28 | <|skeleton|>
class SparseHelper:
"""The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc."""
def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor:
"""Get current active map with (B, 1, f, f) shape or index format."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SparseHelper:
"""The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc."""
def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor:
"""Get current active map with (B, 1, f, f) shape or index format."""
downsa... | the_stack_v2_python_sparse | mmpretrain/models/utils/sparse_modules.py | open-mmlab/mmpretrain | train | 652 |
02c4f92b4dd013cc5388f23e9fe2a1ca3c54767b | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn HostComponent()",
"from .artifact import Artifact\nfrom .host import Host\nfrom .artifact import Artifact\nfrom .host import Host\nfields: Dict[str, Callable[[Any], None]] = {'category': lambda n: setattr(self, 'category', n.get_str_va... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return HostComponent()
<|end_body_0|>
<|body_start_1|>
from .artifact import Artifact
from .host import Host
from .artifact import Artifact
from .host import Host
fields... | HostComponent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HostComponent:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> HostComponent:
"""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... | stack_v2_sparse_classes_10k_train_001562 | 3,935 | 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: HostComponent",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value... | 3 | null | Implement the Python class `HostComponent` described below.
Class description:
Implement the HostComponent class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> HostComponent: Creates a new instance of the appropriate class based on discriminator value... | Implement the Python class `HostComponent` described below.
Class description:
Implement the HostComponent class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> HostComponent: Creates a new instance of the appropriate class based on discriminator value... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class HostComponent:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> HostComponent:
"""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... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HostComponent:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> HostComponent:
"""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: HostComponen... | the_stack_v2_python_sparse | msgraph/generated/models/security/host_component.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
6074432aef43e3d3ee1a60fb6a37bcf3f7e1ef42 | [
"self._pairs = [(re.compile(x, re.IGNORECASE), y, z) for x, y, z in pairs]\nself._reflections = reflections\nself._regex = self._compile_reflections()",
"for pattern, response, callback in self._pairs:\n match = pattern.match(str)\n if match:\n resp = random.choice(response)\n resp = self._wil... | <|body_start_0|>
self._pairs = [(re.compile(x, re.IGNORECASE), y, z) for x, y, z in pairs]
self._reflections = reflections
self._regex = self._compile_reflections()
<|end_body_0|>
<|body_start_1|>
for pattern, response, callback in self._pairs:
match = pattern.match(str)
... | MyChat | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyChat:
def __init__(self, pairs, reflections={}):
"""Initialize the chatbot. Pairs is a list of patterns and responses. Each pattern is a regular expression matching the user's statement or question, e.g. r'I like (.*)'. For each such pattern a list of possible responses is given, e.g. ... | stack_v2_sparse_classes_10k_train_001563 | 3,184 | permissive | [
{
"docstring": "Initialize the chatbot. Pairs is a list of patterns and responses. Each pattern is a regular expression matching the user's statement or question, e.g. r'I like (.*)'. For each such pattern a list of possible responses is given, e.g. ['Why do you like %1', 'Did you ever dislike %1']. Material wh... | 2 | stack_v2_sparse_classes_30k_train_000221 | Implement the Python class `MyChat` described below.
Class description:
Implement the MyChat class.
Method signatures and docstrings:
- def __init__(self, pairs, reflections={}): Initialize the chatbot. Pairs is a list of patterns and responses. Each pattern is a regular expression matching the user's statement or qu... | Implement the Python class `MyChat` described below.
Class description:
Implement the MyChat class.
Method signatures and docstrings:
- def __init__(self, pairs, reflections={}): Initialize the chatbot. Pairs is a list of patterns and responses. Each pattern is a regular expression matching the user's statement or qu... | 95cb53b664f312e0830f010c0c96be94d4a4db90 | <|skeleton|>
class MyChat:
def __init__(self, pairs, reflections={}):
"""Initialize the chatbot. Pairs is a list of patterns and responses. Each pattern is a regular expression matching the user's statement or question, e.g. r'I like (.*)'. For each such pattern a list of possible responses is given, e.g. ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MyChat:
def __init__(self, pairs, reflections={}):
"""Initialize the chatbot. Pairs is a list of patterns and responses. Each pattern is a regular expression matching the user's statement or question, e.g. r'I like (.*)'. For each such pattern a list of possible responses is given, e.g. ['Why do you l... | the_stack_v2_python_sparse | __NLTK__/chat-run-function/main.py | furas/python-examples | train | 176 | |
27701991639a3d2aeeb7689fba6321c07836db99 | [
"pygame.font.init()\nbasicfont = pygame.font.Font(None, fontsize)\nself.linewidths = []\nfor x in text:\n self.texttemp = basicfont.render(x, 0, (1, 1, 1))\n self.linewidths.append(self.texttemp.get_width())\nself.imagewidth = basicfont.render(text[self.linewidths.index(max(self.linewidths))], 0, (1, 1, 1)).g... | <|body_start_0|>
pygame.font.init()
basicfont = pygame.font.Font(None, fontsize)
self.linewidths = []
for x in text:
self.texttemp = basicfont.render(x, 0, (1, 1, 1))
self.linewidths.append(self.texttemp.get_width())
self.imagewidth = basicfont.render(text... | Linesoftext | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Linesoftext:
def __init__(self, text, position, xmid=False, fontsize=36, backgroundcolor=(200, 200, 200), surface=None):
"""This object will create an image of text that is passed in as a list of strings. It will put a new line for each element in the list. Use its image attribute to put... | stack_v2_sparse_classes_10k_train_001564 | 5,935 | no_license | [
{
"docstring": "This object will create an image of text that is passed in as a list of strings. It will put a new line for each element in the list. Use its image attribute to put this text on your screen",
"name": "__init__",
"signature": "def __init__(self, text, position, xmid=False, fontsize=36, ba... | 2 | stack_v2_sparse_classes_30k_train_003016 | Implement the Python class `Linesoftext` described below.
Class description:
Implement the Linesoftext class.
Method signatures and docstrings:
- def __init__(self, text, position, xmid=False, fontsize=36, backgroundcolor=(200, 200, 200), surface=None): This object will create an image of text that is passed in as a ... | Implement the Python class `Linesoftext` described below.
Class description:
Implement the Linesoftext class.
Method signatures and docstrings:
- def __init__(self, text, position, xmid=False, fontsize=36, backgroundcolor=(200, 200, 200), surface=None): This object will create an image of text that is passed in as a ... | 3eae1428fdd30fddc66669d40b8bb0a715d5595a | <|skeleton|>
class Linesoftext:
def __init__(self, text, position, xmid=False, fontsize=36, backgroundcolor=(200, 200, 200), surface=None):
"""This object will create an image of text that is passed in as a list of strings. It will put a new line for each element in the list. Use its image attribute to put... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Linesoftext:
def __init__(self, text, position, xmid=False, fontsize=36, backgroundcolor=(200, 200, 200), surface=None):
"""This object will create an image of text that is passed in as a list of strings. It will put a new line for each element in the list. Use its image attribute to put this text on ... | the_stack_v2_python_sparse | General Python/Guessing_game_with_gui/pygametools.py | jbm950/personal_projects | train | 0 | |
5f938d7858cd85b5b4c68d2639ff06f084747f35 | [
"self.rows = []\nself.variables_places = {}\ni = 0\nfor var in variables:\n self.variables_places[var] = i\n i += 1",
"if len(values) != len(self.variables_places.keys()):\n raise ValueError('Invalid number of values. Should be equal to a number of variables')\nself.rows.append(self.Row(probability, valu... | <|body_start_0|>
self.rows = []
self.variables_places = {}
i = 0
for var in variables:
self.variables_places[var] = i
i += 1
<|end_body_0|>
<|body_start_1|>
if len(values) != len(self.variables_places.keys()):
raise ValueError('Invalid number ... | ProbabilityDistribution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProbabilityDistribution:
def __init__(self, variables):
""":param variables iterable(str): names of all variables in this probability distribution"""
<|body_0|>
def set(self, probability, values):
"""Add probability of variables in probability distribution to have sp... | stack_v2_sparse_classes_10k_train_001565 | 20,140 | no_license | [
{
"docstring": ":param variables iterable(str): names of all variables in this probability distribution",
"name": "__init__",
"signature": "def __init__(self, variables)"
},
{
"docstring": "Add probability of variables in probability distribution to have specified values. :param probability: pro... | 3 | stack_v2_sparse_classes_30k_train_006208 | Implement the Python class `ProbabilityDistribution` described below.
Class description:
Implement the ProbabilityDistribution class.
Method signatures and docstrings:
- def __init__(self, variables): :param variables iterable(str): names of all variables in this probability distribution
- def set(self, probability, ... | Implement the Python class `ProbabilityDistribution` described below.
Class description:
Implement the ProbabilityDistribution class.
Method signatures and docstrings:
- def __init__(self, variables): :param variables iterable(str): names of all variables in this probability distribution
- def set(self, probability, ... | 32a9b9158d73dc80b355993a5a5f8fc49ae25334 | <|skeleton|>
class ProbabilityDistribution:
def __init__(self, variables):
""":param variables iterable(str): names of all variables in this probability distribution"""
<|body_0|>
def set(self, probability, values):
"""Add probability of variables in probability distribution to have sp... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProbabilityDistribution:
def __init__(self, variables):
""":param variables iterable(str): names of all variables in this probability distribution"""
self.rows = []
self.variables_places = {}
i = 0
for var in variables:
self.variables_places[var] = i
... | the_stack_v2_python_sparse | aima/core/probability/algorithms.py | afcarl/aima-python-mushketyk | train | 1 | |
e04042c5ffbf72824e9a68fd2514ae41abfdc212 | [
"RenderableResource.__init__(self, parent)\nself.localeNames = []\nfor locale, translation in self.config.locales.items():\n localeName = locale + ': '\n langName = translation.info().get('x-exe-language', None)\n if langName == None:\n langName = translation.info().get('x-poedit-language', 'English... | <|body_start_0|>
RenderableResource.__init__(self, parent)
self.localeNames = []
for locale, translation in self.config.locales.items():
localeName = locale + ': '
langName = translation.info().get('x-exe-language', None)
if langName == None:
l... | The PreferencesPage is responsible for managing eXe preferences | PreferencesPage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreferencesPage:
"""The PreferencesPage is responsible for managing eXe preferences"""
def __init__(self, parent):
"""Initialize"""
<|body_0|>
def getChild(self, name, request):
"""Try and find the child for the name given"""
<|body_1|>
def render_GE... | stack_v2_sparse_classes_10k_train_001566 | 3,657 | no_license | [
{
"docstring": "Initialize",
"name": "__init__",
"signature": "def __init__(self, parent)"
},
{
"docstring": "Try and find the child for the name given",
"name": "getChild",
"signature": "def getChild(self, name, request)"
},
{
"docstring": "Render the preferences",
"name": "... | 4 | stack_v2_sparse_classes_30k_train_002769 | Implement the Python class `PreferencesPage` described below.
Class description:
The PreferencesPage is responsible for managing eXe preferences
Method signatures and docstrings:
- def __init__(self, parent): Initialize
- def getChild(self, name, request): Try and find the child for the name given
- def render_GET(se... | Implement the Python class `PreferencesPage` described below.
Class description:
The PreferencesPage is responsible for managing eXe preferences
Method signatures and docstrings:
- def __init__(self, parent): Initialize
- def getChild(self, name, request): Try and find the child for the name given
- def render_GET(se... | 1a99c1788f0eb9f1e5d8c2ced3892d00cd9449ad | <|skeleton|>
class PreferencesPage:
"""The PreferencesPage is responsible for managing eXe preferences"""
def __init__(self, parent):
"""Initialize"""
<|body_0|>
def getChild(self, name, request):
"""Try and find the child for the name given"""
<|body_1|>
def render_GE... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PreferencesPage:
"""The PreferencesPage is responsible for managing eXe preferences"""
def __init__(self, parent):
"""Initialize"""
RenderableResource.__init__(self, parent)
self.localeNames = []
for locale, translation in self.config.locales.items():
localeNam... | the_stack_v2_python_sparse | eXe/rev3426-3513/right-branch-3513/exe/webui/preferencespage.py | joliebig/featurehouse_fstmerge_examples | train | 3 |
fdfb16032d63dccfe736757871f28ac55b96b3da | [
"self._filename = filename\nself._filelayout = filelayout\nself._data = self._parse()",
"output = pd.read_csv(self._filename, comment='#', delim_whitespace=True, names=self._filelayout)\noutput_dict = output.to_dict()\nreturn output_dict",
"try:\n selected_data = np.array(list(self._data[name].values()))\nex... | <|body_start_0|>
self._filename = filename
self._filelayout = filelayout
self._data = self._parse()
<|end_body_0|>
<|body_start_1|>
output = pd.read_csv(self._filename, comment='#', delim_whitespace=True, names=self._filelayout)
output_dict = output.to_dict()
return outp... | Parses information for known data files in txt format. | RawData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RawData:
"""Parses information for known data files in txt format."""
def __init__(self, filename, filelayout):
"""Parses information for known data files in txt format. :filename: name of the file to parse :filelayout: list of column names in file"""
<|body_0|>
def _par... | stack_v2_sparse_classes_10k_train_001567 | 15,467 | no_license | [
{
"docstring": "Parses information for known data files in txt format. :filename: name of the file to parse :filelayout: list of column names in file",
"name": "__init__",
"signature": "def __init__(self, filename, filelayout)"
},
{
"docstring": "Parse the data form the object's file. :return: a... | 3 | stack_v2_sparse_classes_30k_train_007318 | Implement the Python class `RawData` described below.
Class description:
Parses information for known data files in txt format.
Method signatures and docstrings:
- def __init__(self, filename, filelayout): Parses information for known data files in txt format. :filename: name of the file to parse :filelayout: list of... | Implement the Python class `RawData` described below.
Class description:
Parses information for known data files in txt format.
Method signatures and docstrings:
- def __init__(self, filename, filelayout): Parses information for known data files in txt format. :filename: name of the file to parse :filelayout: list of... | 0c1894ce8d9f5daed539240d3ac86e645d6de44c | <|skeleton|>
class RawData:
"""Parses information for known data files in txt format."""
def __init__(self, filename, filelayout):
"""Parses information for known data files in txt format. :filename: name of the file to parse :filelayout: list of column names in file"""
<|body_0|>
def _par... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RawData:
"""Parses information for known data files in txt format."""
def __init__(self, filename, filelayout):
"""Parses information for known data files in txt format. :filename: name of the file to parse :filelayout: list of column names in file"""
self._filename = filename
sel... | the_stack_v2_python_sparse | stan_implementation/analysis_interface/interfaces/data.py | cescalara/soiaporn_model | train | 1 |
e60b9b10d7443ed4c5cbb372a600ff99ee5fc767 | [
"session = async_get_clientsession(self.hass)\nweb_account = WebAccount(session, email, password)\nweb_account_info = await web_account.login()\nmobile_account = MobileAccount(session, email, password)\nawait mobile_account.login()\nreturn {CONF_ACCESS_TOKEN: mobile_account.access_token, CONF_EMAIL: web_account_inf... | <|body_start_0|>
session = async_get_clientsession(self.hass)
web_account = WebAccount(session, email, password)
web_account_info = await web_account.login()
mobile_account = MobileAccount(session, email, password)
await mobile_account.login()
return {CONF_ACCESS_TOKEN: m... | Handle a config flow for Aseko Pool Live. | ConfigFlow | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for Aseko Pool Live."""
async def get_account_info(self, email: str, password: str) -> dict:
"""Get account info from the mobile API and the web API."""
<|body_0|>
async def async_step_user(self, user_input: dict[str, Any] | None=None)... | stack_v2_sparse_classes_10k_train_001568 | 2,634 | permissive | [
{
"docstring": "Get account info from the mobile API and the web API.",
"name": "get_account_info",
"signature": "async def get_account_info(self, email: str, password: str) -> dict"
},
{
"docstring": "Handle the initial step.",
"name": "async_step_user",
"signature": "async def async_st... | 2 | null | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for Aseko Pool Live.
Method signatures and docstrings:
- async def get_account_info(self, email: str, password: str) -> dict: Get account info from the mobile API and the web API.
- async def async_step_user(self, user_in... | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for Aseko Pool Live.
Method signatures and docstrings:
- async def get_account_info(self, email: str, password: str) -> dict: Get account info from the mobile API and the web API.
- async def async_step_user(self, user_in... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for Aseko Pool Live."""
async def get_account_info(self, email: str, password: str) -> dict:
"""Get account info from the mobile API and the web API."""
<|body_0|>
async def async_step_user(self, user_input: dict[str, Any] | None=None)... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ConfigFlow:
"""Handle a config flow for Aseko Pool Live."""
async def get_account_info(self, email: str, password: str) -> dict:
"""Get account info from the mobile API and the web API."""
session = async_get_clientsession(self.hass)
web_account = WebAccount(session, email, passwo... | the_stack_v2_python_sparse | homeassistant/components/aseko_pool_live/config_flow.py | home-assistant/core | train | 35,501 |
ea7b5e46017a612f3f18889cbd7ab408db080af2 | [
"include_2D_map = self.get_query_argument('include2DMap', False)\nlocalization = Localization.query_records_accessible_by(self.current_user).filter(Localization.dateobs == dateobs, Localization.localization_name == localization_name).first()\nif localization is None:\n return self.error('Localization not found',... | <|body_start_0|>
include_2D_map = self.get_query_argument('include2DMap', False)
localization = Localization.query_records_accessible_by(self.current_user).filter(Localization.dateobs == dateobs, Localization.localization_name == localization_name).first()
if localization is None:
re... | LocalizationHandler | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocalizationHandler:
def get(self, dateobs, localization_name):
"""--- description: Retrieve a GCN localization tags: - localizations parameters: - in: path name: dateobs required: true schema: type: dateobs - in: path name: localization_name required: true schema: type: localization_nam... | stack_v2_sparse_classes_10k_train_001569 | 12,885 | permissive | [
{
"docstring": "--- description: Retrieve a GCN localization tags: - localizations parameters: - in: path name: dateobs required: true schema: type: dateobs - in: path name: localization_name required: true schema: type: localization_name - in: query name: include2DMap nullable: true schema: type: boolean descr... | 2 | stack_v2_sparse_classes_30k_train_004966 | Implement the Python class `LocalizationHandler` described below.
Class description:
Implement the LocalizationHandler class.
Method signatures and docstrings:
- def get(self, dateobs, localization_name): --- description: Retrieve a GCN localization tags: - localizations parameters: - in: path name: dateobs required:... | Implement the Python class `LocalizationHandler` described below.
Class description:
Implement the LocalizationHandler class.
Method signatures and docstrings:
- def get(self, dateobs, localization_name): --- description: Retrieve a GCN localization tags: - localizations parameters: - in: path name: dateobs required:... | 2433d5ae0b2f41faac3c76ed4ae8d9a4da5522fb | <|skeleton|>
class LocalizationHandler:
def get(self, dateobs, localization_name):
"""--- description: Retrieve a GCN localization tags: - localizations parameters: - in: path name: dateobs required: true schema: type: dateobs - in: path name: localization_name required: true schema: type: localization_nam... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LocalizationHandler:
def get(self, dateobs, localization_name):
"""--- description: Retrieve a GCN localization tags: - localizations parameters: - in: path name: dateobs required: true schema: type: dateobs - in: path name: localization_name required: true schema: type: localization_name - in: query ... | the_stack_v2_python_sparse | skyportal/handlers/api/gcn.py | dmitryduev/skyportal | train | 1 | |
8b5de17457890678b2bf473802ae0182a5d7a447 | [
"self.graph = graph\nself.distances = graph.distance\nself.links = graph.links\nself.weighted_edge_list = graph.weighted_edge_list\nself.G = graph.G\nself.sort = sorted(self.weighted_edge_list, key=lambda x: x[2])\nself.ordered_distance = [i[2] for i in self.sort]\nself.ordered_links = [i[0:2] for i in self.sort]\n... | <|body_start_0|>
self.graph = graph
self.distances = graph.distance
self.links = graph.links
self.weighted_edge_list = graph.weighted_edge_list
self.G = graph.G
self.sort = sorted(self.weighted_edge_list, key=lambda x: x[2])
self.ordered_distance = [i[2] for i in ... | Kruskal and prims algorithm. | MST | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MST:
"""Kruskal and prims algorithm."""
def __init__(self, graph):
"""Take Graph object from read.py."""
<|body_0|>
def kruskal(self):
"""Find minimum spanning tree using kruskals algorithm."""
<|body_1|>
def prims(self, start_node, matrix=None):
... | stack_v2_sparse_classes_10k_train_001570 | 2,939 | no_license | [
{
"docstring": "Take Graph object from read.py.",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Find minimum spanning tree using kruskals algorithm.",
"name": "kruskal",
"signature": "def kruskal(self)"
},
{
"docstring": "Prims algorithm.",
"... | 3 | stack_v2_sparse_classes_30k_val_000160 | Implement the Python class `MST` described below.
Class description:
Kruskal and prims algorithm.
Method signatures and docstrings:
- def __init__(self, graph): Take Graph object from read.py.
- def kruskal(self): Find minimum spanning tree using kruskals algorithm.
- def prims(self, start_node, matrix=None): Prims a... | Implement the Python class `MST` described below.
Class description:
Kruskal and prims algorithm.
Method signatures and docstrings:
- def __init__(self, graph): Take Graph object from read.py.
- def kruskal(self): Find minimum spanning tree using kruskals algorithm.
- def prims(self, start_node, matrix=None): Prims a... | 1ab79611816cabe8d658d8893e06cab62b2b6af6 | <|skeleton|>
class MST:
"""Kruskal and prims algorithm."""
def __init__(self, graph):
"""Take Graph object from read.py."""
<|body_0|>
def kruskal(self):
"""Find minimum spanning tree using kruskals algorithm."""
<|body_1|>
def prims(self, start_node, matrix=None):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MST:
"""Kruskal and prims algorithm."""
def __init__(self, graph):
"""Take Graph object from read.py."""
self.graph = graph
self.distances = graph.distance
self.links = graph.links
self.weighted_edge_list = graph.weighted_edge_list
self.G = graph.G
... | the_stack_v2_python_sparse | GraphTheory/mst.py | Pullabhatla/M2R | train | 0 |
34c202f078fefacd38f73b7acdf67c9e98897565 | [
"super().__init__()\nself.resize_input = resize_input\nself.normalize_input = normalize_input\nself.output_blocks = sorted(output_blocks)\nself.last_needed_block = max(output_blocks)\nassert self.last_needed_block <= 3, 'Last possible output block index is 3'\nself.blocks = nn.ModuleList()\nif use_fid_inception:\n ... | <|body_start_0|>
super().__init__()
self.resize_input = resize_input
self.normalize_input = normalize_input
self.output_blocks = sorted(output_blocks)
self.last_needed_block = max(output_blocks)
assert self.last_needed_block <= 3, 'Last possible output block index is 3'
... | Pretrained InceptionV3 network returning feature maps. | InceptionV3 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InceptionV3:
"""Pretrained InceptionV3 network returning feature maps."""
def __init__(self, output_blocks=[DEFAULT_BLOCK_INDEX], resize_input=True, normalize_input=True, requires_grad=False, use_fid_inception=True, load_fid_inception=True):
"""Build pretrained InceptionV3. Args: out... | stack_v2_sparse_classes_10k_train_001571 | 12,348 | permissive | [
{
"docstring": "Build pretrained InceptionV3. Args: output_blocks (list[int]): Indices of blocks to return features of. Possible values are: - 0: corresponds to output of first max pooling - 1: corresponds to output of second max pooling - 2: corresponds to output which is fed to aux classifier - 3: corresponds... | 2 | null | Implement the Python class `InceptionV3` described below.
Class description:
Pretrained InceptionV3 network returning feature maps.
Method signatures and docstrings:
- def __init__(self, output_blocks=[DEFAULT_BLOCK_INDEX], resize_input=True, normalize_input=True, requires_grad=False, use_fid_inception=True, load_fid... | Implement the Python class `InceptionV3` described below.
Class description:
Pretrained InceptionV3 network returning feature maps.
Method signatures and docstrings:
- def __init__(self, output_blocks=[DEFAULT_BLOCK_INDEX], resize_input=True, normalize_input=True, requires_grad=False, use_fid_inception=True, load_fid... | a382f143c0fd20d227e1e5524831ba26a568190d | <|skeleton|>
class InceptionV3:
"""Pretrained InceptionV3 network returning feature maps."""
def __init__(self, output_blocks=[DEFAULT_BLOCK_INDEX], resize_input=True, normalize_input=True, requires_grad=False, use_fid_inception=True, load_fid_inception=True):
"""Build pretrained InceptionV3. Args: out... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InceptionV3:
"""Pretrained InceptionV3 network returning feature maps."""
def __init__(self, output_blocks=[DEFAULT_BLOCK_INDEX], resize_input=True, normalize_input=True, requires_grad=False, use_fid_inception=True, load_fid_inception=True):
"""Build pretrained InceptionV3. Args: output_blocks (l... | the_stack_v2_python_sparse | mmagic/evaluation/functional/fid_inception.py | open-mmlab/mmagic | train | 1,370 |
667884fe1789f0822e5d0e5f57f7ed660fa8383a | [
"for row in matrix:\n for col in range(1, len(row)):\n row[col] += row[col - 1]\nself.matrix = matrix",
"original = self.matrix[row][col]\nif col != 0:\n original -= self.matrix[row][col - 1]\ndiff = original - val\nfor y in range(col, len(self.matrix[0])):\n self.matrix[row][y] -= diff",
"regio... | <|body_start_0|>
for row in matrix:
for col in range(1, len(row)):
row[col] += row[col - 1]
self.matrix = matrix
<|end_body_0|>
<|body_start_1|>
original = self.matrix[row][col]
if col != 0:
original -= self.matrix[row][col - 1]
diff = ori... | Your NumMatrix object will be instantiated and called as such: obj = NumMatrix(matrix) obj.update(row,col,val) param_2 = obj.sumRegion(row1,col1,row2,col2) https://leetcode.com/problems/range-sum-query-2d-mutable/discuss/75872/Python-94.5-Simple-sum-array-on-one-dimension-O(n)-for-both-update-and-sum beats 83.86% | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
"""Your NumMatrix object will be instantiated and called as such: obj = NumMatrix(matrix) obj.update(row,col,val) param_2 = obj.sumRegion(row1,col1,row2,col2) https://leetcode.com/problems/range-sum-query-2d-mutable/discuss/75872/Python-94.5-Simple-sum-array-on-one-dimension-O(n)-for-b... | stack_v2_sparse_classes_10k_train_001572 | 8,379 | no_license | [
{
"docstring": ":type matrix: List[List[int]] element m[i][j] in self.matrix means sum of previous elements in this row, namely sum(m[i][0] + m[i][1] + ... + m[i][j])",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": "original means the single element value in ori... | 3 | null | Implement the Python class `NumMatrix` described below.
Class description:
Your NumMatrix object will be instantiated and called as such: obj = NumMatrix(matrix) obj.update(row,col,val) param_2 = obj.sumRegion(row1,col1,row2,col2) https://leetcode.com/problems/range-sum-query-2d-mutable/discuss/75872/Python-94.5-Simpl... | Implement the Python class `NumMatrix` described below.
Class description:
Your NumMatrix object will be instantiated and called as such: obj = NumMatrix(matrix) obj.update(row,col,val) param_2 = obj.sumRegion(row1,col1,row2,col2) https://leetcode.com/problems/range-sum-query-2d-mutable/discuss/75872/Python-94.5-Simpl... | 035ef08434fa1ca781a6fb2f9eed3538b7d20c02 | <|skeleton|>
class NumMatrix:
"""Your NumMatrix object will be instantiated and called as such: obj = NumMatrix(matrix) obj.update(row,col,val) param_2 = obj.sumRegion(row1,col1,row2,col2) https://leetcode.com/problems/range-sum-query-2d-mutable/discuss/75872/Python-94.5-Simple-sum-array-on-one-dimension-O(n)-for-b... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NumMatrix:
"""Your NumMatrix object will be instantiated and called as such: obj = NumMatrix(matrix) obj.update(row,col,val) param_2 = obj.sumRegion(row1,col1,row2,col2) https://leetcode.com/problems/range-sum-query-2d-mutable/discuss/75872/Python-94.5-Simple-sum-array-on-one-dimension-O(n)-for-both-update-an... | the_stack_v2_python_sparse | leetcode_python/Array/range-sum-query-2d-mutable.py | yennanliu/CS_basics | train | 64 |
d8d4a26c2a05cf21b87e9bc6384a43e3d4f01973 | [
"manifest = []\nfor line in manifest_xml_content:\n if 'Scripts' not in line:\n manifest.append(line)\nreturn manifest",
"manifest = []\nfor line in manifest_xml_content:\n if '</manifest:manifest>' in line:\n for path in python_file_paths:\n document_path = Manifest.file_path_to_do... | <|body_start_0|>
manifest = []
for line in manifest_xml_content:
if 'Scripts' not in line:
manifest.append(line)
return manifest
<|end_body_0|>
<|body_start_1|>
manifest = []
for line in manifest_xml_content:
if '</manifest:manifest>' in l... | Manifest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Manifest:
def remove_source_paths(cls, manifest_xml_content):
"""Remove all Python source paths from the given manifest.xml content and return the modified content array."""
<|body_0|>
def add_file_paths(cls, manifest_xml_content, python_file_paths):
"""Add given Pyt... | stack_v2_sparse_classes_10k_train_001573 | 6,797 | permissive | [
{
"docstring": "Remove all Python source paths from the given manifest.xml content and return the modified content array.",
"name": "remove_source_paths",
"signature": "def remove_source_paths(cls, manifest_xml_content)"
},
{
"docstring": "Add given Python source file paths to manifest.xml so Li... | 4 | stack_v2_sparse_classes_30k_train_001909 | Implement the Python class `Manifest` described below.
Class description:
Implement the Manifest class.
Method signatures and docstrings:
- def remove_source_paths(cls, manifest_xml_content): Remove all Python source paths from the given manifest.xml content and return the modified content array.
- def add_file_paths... | Implement the Python class `Manifest` described below.
Class description:
Implement the Manifest class.
Method signatures and docstrings:
- def remove_source_paths(cls, manifest_xml_content): Remove all Python source paths from the given manifest.xml content and return the modified content array.
- def add_file_paths... | d4defdfd6714cfc78667643694999e9e3f4bd5c2 | <|skeleton|>
class Manifest:
def remove_source_paths(cls, manifest_xml_content):
"""Remove all Python source paths from the given manifest.xml content and return the modified content array."""
<|body_0|>
def add_file_paths(cls, manifest_xml_content, python_file_paths):
"""Add given Pyt... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Manifest:
def remove_source_paths(cls, manifest_xml_content):
"""Remove all Python source paths from the given manifest.xml content and return the modified content array."""
manifest = []
for line in manifest_xml_content:
if 'Scripts' not in line:
manifest.a... | the_stack_v2_python_sparse | scripts/utils.py | Kazhuu/movelister | train | 3 | |
a400a771e9b3dbe12e955e2578d8fe5b7e0628da | [
"super().__init__()\nself.wide = WideLayer(inputs_size=num_fields, output_size=1, dropout_p=wide_dropout_p)\nself.deep = MultilayerPerceptionLayer(inputs_size=embed_size, output_size=1, layer_sizes=deep_layer_sizes, dropout_p=deep_dropout_p, activation=deep_activation)\nself.output = WideLayer(inputs_size=num_field... | <|body_start_0|>
super().__init__()
self.wide = WideLayer(inputs_size=num_fields, output_size=1, dropout_p=wide_dropout_p)
self.deep = MultilayerPerceptionLayer(inputs_size=embed_size, output_size=1, layer_sizes=deep_layer_sizes, dropout_p=deep_dropout_p, activation=deep_activation)
self... | Model class of Wide and Deep Model Wide and Deep Model is one of the most famous click-through-rate prediction model which is designed by Google in 2016. :Reference: #. `Heng-Tze Cheng, 2016. Wide & Deep Learning for Recommender Systems <https://arxiv.org/pdf/1606.07792.pdf>`_. | WideAndDeepModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WideAndDeepModel:
"""Model class of Wide and Deep Model Wide and Deep Model is one of the most famous click-through-rate prediction model which is designed by Google in 2016. :Reference: #. `Heng-Tze Cheng, 2016. Wide & Deep Learning for Recommender Systems <https://arxiv.org/pdf/1606.07792.pdf>`... | stack_v2_sparse_classes_10k_train_001574 | 3,948 | permissive | [
{
"docstring": "Initialize WideAndDeepModel Args: embed_size (int): size of embedding tensor num_fields (int): number of inputs' fields deep_layer_sizes (List[int]): layer sizes of dense network out_dropout_p (float, optional): probability of Dropout in output layer. Defaults to None wide_dropout_p (float, opti... | 2 | stack_v2_sparse_classes_30k_train_001621 | Implement the Python class `WideAndDeepModel` described below.
Class description:
Model class of Wide and Deep Model Wide and Deep Model is one of the most famous click-through-rate prediction model which is designed by Google in 2016. :Reference: #. `Heng-Tze Cheng, 2016. Wide & Deep Learning for Recommender Systems ... | Implement the Python class `WideAndDeepModel` described below.
Class description:
Model class of Wide and Deep Model Wide and Deep Model is one of the most famous click-through-rate prediction model which is designed by Google in 2016. :Reference: #. `Heng-Tze Cheng, 2016. Wide & Deep Learning for Recommender Systems ... | 751a43b9cd35e951d81c0d9cf46507b1777bb7ff | <|skeleton|>
class WideAndDeepModel:
"""Model class of Wide and Deep Model Wide and Deep Model is one of the most famous click-through-rate prediction model which is designed by Google in 2016. :Reference: #. `Heng-Tze Cheng, 2016. Wide & Deep Learning for Recommender Systems <https://arxiv.org/pdf/1606.07792.pdf>`... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WideAndDeepModel:
"""Model class of Wide and Deep Model Wide and Deep Model is one of the most famous click-through-rate prediction model which is designed by Google in 2016. :Reference: #. `Heng-Tze Cheng, 2016. Wide & Deep Learning for Recommender Systems <https://arxiv.org/pdf/1606.07792.pdf>`_."""
de... | the_stack_v2_python_sparse | torecsys/models/ctr/wide_and_deep.py | p768lwy3/torecsys | train | 98 |
f2313a5e2139f55fdfd67a66f6eb53b0e706db5d | [
"parser.add_argument('usernames', metavar='USERNAME', nargs='*', help=_('The usernames of users whose tokens will be invalidated.'))\nparser.add_argument('-r', '--reason', default='', help=_('A message indicating why the tokens are no longer valid.'))\nparser.add_argument('-a', '--all', action='store_true', default... | <|body_start_0|>
parser.add_argument('usernames', metavar='USERNAME', nargs='*', help=_('The usernames of users whose tokens will be invalidated.'))
parser.add_argument('-r', '--reason', default='', help=_('A message indicating why the tokens are no longer valid.'))
parser.add_argument('-a', '--... | Management command to invalidate API tokens. Version Added: 5.0 | Command | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Command:
"""Management command to invalidate API tokens. Version Added: 5.0"""
def add_arguments(self, parser):
"""Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command."""
<|body_0|>
def handle(self, *args, **options):... | stack_v2_sparse_classes_10k_train_001575 | 3,834 | permissive | [
{
"docstring": "Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command.",
"name": "add_arguments",
"signature": "def add_arguments(self, parser)"
},
{
"docstring": "Handle the command. Args: *args (tuple, unused): Arguments parsed on the command... | 2 | null | Implement the Python class `Command` described below.
Class description:
Management command to invalidate API tokens. Version Added: 5.0
Method signatures and docstrings:
- def add_arguments(self, parser): Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command.
- def... | Implement the Python class `Command` described below.
Class description:
Management command to invalidate API tokens. Version Added: 5.0
Method signatures and docstrings:
- def add_arguments(self, parser): Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command.
- def... | c3a991f1e9d7682239a1ab0e8661cee6da01d537 | <|skeleton|>
class Command:
"""Management command to invalidate API tokens. Version Added: 5.0"""
def add_arguments(self, parser):
"""Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command."""
<|body_0|>
def handle(self, *args, **options):... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Command:
"""Management command to invalidate API tokens. Version Added: 5.0"""
def add_arguments(self, parser):
"""Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command."""
parser.add_argument('usernames', metavar='USERNAME', nargs='*', ... | the_stack_v2_python_sparse | reviewboard/webapi/management/commands/invalidate-api-tokens.py | reviewboard/reviewboard | train | 1,141 |
2408c8e28b4bb315cac68c09a501602e50981abc | [
"if not nums:\n return 1\ni = 0\nwhile i < len(nums):\n if nums[i] <= 0 or nums[i] > len(nums) or nums[nums[i] - 1] == nums[i]:\n i += 1\n else:\n nums[nums[i] - 1], nums[i] = (nums[i], nums[nums[i] - 1])\nfor i in range(len(nums)):\n if nums[i] != i + 1:\n return i + 1\nreturn nums... | <|body_start_0|>
if not nums:
return 1
i = 0
while i < len(nums):
if nums[i] <= 0 or nums[i] > len(nums) or nums[nums[i] - 1] == nums[i]:
i += 1
else:
nums[nums[i] - 1], nums[i] = (nums[i], nums[nums[i] - 1])
for i in ra... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def firstMissingPositive_failed(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums:
... | stack_v2_sparse_classes_10k_train_001576 | 2,233 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "firstMissingPositive",
"signature": "def firstMissingPositive(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "firstMissingPositive_failed",
"signature": "def firstMissingPositive_failed(self, nums)"... | 2 | stack_v2_sparse_classes_30k_train_005971 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstMissingPositive(self, nums): :type nums: List[int] :rtype: int
- def firstMissingPositive_failed(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstMissingPositive(self, nums): :type nums: List[int] :rtype: int
- def firstMissingPositive_failed(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solut... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def firstMissingPositive_failed(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return 1
i = 0
while i < len(nums):
if nums[i] <= 0 or nums[i] > len(nums) or nums[nums[i] - 1] == nums[i]:
i += 1
else:
... | the_stack_v2_python_sparse | src/lt_41.py | oxhead/CodingYourWay | train | 0 | |
b120b63a4fcac2126041d970782f94c654c95d95 | [
"for rasterlayer in queryset:\n rasterlayer.parsestatus.reset()\n rasterlayer.refresh_from_db()\n rasterlayer.save()\nmsg = 'Parsing Rasters, check parse logs for progress'\nself.message_user(request, msg)",
"form = None\nlayer = queryset[0]\nif layer.rasterfile:\n self.message_user(request, 'This lay... | <|body_start_0|>
for rasterlayer in queryset:
rasterlayer.parsestatus.reset()
rasterlayer.refresh_from_db()
rasterlayer.save()
msg = 'Parsing Rasters, check parse logs for progress'
self.message_user(request, msg)
<|end_body_0|>
<|body_start_1|>
form ... | Admin action to update filepaths only. Files can be uploadded to the filesystems through any channel and then files can be assigned to the raster objects through this action. This might be useful for large raster files. | RasterLayerModelAdmin | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RasterLayerModelAdmin:
"""Admin action to update filepaths only. Files can be uploadded to the filesystems through any channel and then files can be assigned to the raster objects through this action. This might be useful for large raster files."""
def reparse_rasters(self, request, queryset... | stack_v2_sparse_classes_10k_train_001577 | 5,409 | permissive | [
{
"docstring": "Admin action to re-parse a set of rasterlayers.",
"name": "reparse_rasters",
"signature": "def reparse_rasters(self, request, queryset)"
},
{
"docstring": "Admin action to change filepath without uploading new file.",
"name": "manually_update_filepath",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_003103 | Implement the Python class `RasterLayerModelAdmin` described below.
Class description:
Admin action to update filepaths only. Files can be uploadded to the filesystems through any channel and then files can be assigned to the raster objects through this action. This might be useful for large raster files.
Method sign... | Implement the Python class `RasterLayerModelAdmin` described below.
Class description:
Admin action to update filepaths only. Files can be uploadded to the filesystems through any channel and then files can be assigned to the raster objects through this action. This might be useful for large raster files.
Method sign... | 34fffe3d1f921b2850d3cad598a3c9b382e1fec7 | <|skeleton|>
class RasterLayerModelAdmin:
"""Admin action to update filepaths only. Files can be uploadded to the filesystems through any channel and then files can be assigned to the raster objects through this action. This might be useful for large raster files."""
def reparse_rasters(self, request, queryset... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RasterLayerModelAdmin:
"""Admin action to update filepaths only. Files can be uploadded to the filesystems through any channel and then files can be assigned to the raster objects through this action. This might be useful for large raster files."""
def reparse_rasters(self, request, queryset):
""... | the_stack_v2_python_sparse | raster/admin.py | henhuy/django-raster | train | 0 |
6b5e7be9613c16b13e9f1e6e1feaa9b528316d81 | [
"super().__init__(*args, **kwargs)\ntry:\n self.idp_hint_param_names = config['allowed_params']\nexcept KeyError:\n raise SATOSAConfigurationError(f\"{self.__class__.__name__} can't find allowed_params\")",
"target_entity_id = context.get_decoration(context.KEY_TARGET_ENTITYID)\nqs_params = context.qs_param... | <|body_start_0|>
super().__init__(*args, **kwargs)
try:
self.idp_hint_param_names = config['allowed_params']
except KeyError:
raise SATOSAConfigurationError(f"{self.__class__.__name__} can't find allowed_params")
<|end_body_0|>
<|body_start_1|>
target_entity_id =... | Detect if an idp hinting feature have been requested | IdpHinting | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IdpHinting:
"""Detect if an idp hinting feature have been requested"""
def __init__(self, config, *args, **kwargs):
"""Constructor. :param config: microservice configuration :type config: Dict[str, Dict[str, str]]"""
<|body_0|>
def process(self, context, data):
"... | stack_v2_sparse_classes_10k_train_001578 | 1,773 | permissive | [
{
"docstring": "Constructor. :param config: microservice configuration :type config: Dict[str, Dict[str, str]]",
"name": "__init__",
"signature": "def __init__(self, config, *args, **kwargs)"
},
{
"docstring": "This intercepts if idp_hint paramenter is in use :param context: request context :par... | 2 | stack_v2_sparse_classes_30k_train_002914 | Implement the Python class `IdpHinting` described below.
Class description:
Detect if an idp hinting feature have been requested
Method signatures and docstrings:
- def __init__(self, config, *args, **kwargs): Constructor. :param config: microservice configuration :type config: Dict[str, Dict[str, str]]
- def process... | Implement the Python class `IdpHinting` described below.
Class description:
Detect if an idp hinting feature have been requested
Method signatures and docstrings:
- def __init__(self, config, *args, **kwargs): Constructor. :param config: microservice configuration :type config: Dict[str, Dict[str, str]]
- def process... | d5cac7fc150807f3a42b4ec5942679dd9622cc97 | <|skeleton|>
class IdpHinting:
"""Detect if an idp hinting feature have been requested"""
def __init__(self, config, *args, **kwargs):
"""Constructor. :param config: microservice configuration :type config: Dict[str, Dict[str, str]]"""
<|body_0|>
def process(self, context, data):
"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IdpHinting:
"""Detect if an idp hinting feature have been requested"""
def __init__(self, config, *args, **kwargs):
"""Constructor. :param config: microservice configuration :type config: Dict[str, Dict[str, str]]"""
super().__init__(*args, **kwargs)
try:
self.idp_hint... | the_stack_v2_python_sparse | src/satosa/micro_services/idp_hinting.py | IdentityPython/SATOSA | train | 139 |
e84be0586edee80e04b2403c807a77b2ec25fede | [
"if request.user.is_staff or request.method in permissions.SAFE_METHODS:\n return True\ntry:\n org = Organization.objects.get(pk=request.data['organization'])\n is_in_org = org.is_admin(request.user) or org.is_member(request.user)\n return is_in_org and super().has_permission(request, view)\nexcept KeyE... | <|body_start_0|>
if request.user.is_staff or request.method in permissions.SAFE_METHODS:
return True
try:
org = Organization.objects.get(pk=request.data['organization'])
is_in_org = org.is_admin(request.user) or org.is_member(request.user)
return is_in_org... | Custom to check if user belongs to org | IsOrgAdminOrMember | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsOrgAdminOrMember:
"""Custom to check if user belongs to org"""
def has_permission(self, request, view):
"""if user is staff or if SAFE request, we're done otherwise check model object perms try for user object if request.user is member or admin of org check perms except: this is or... | stack_v2_sparse_classes_10k_train_001579 | 5,524 | permissive | [
{
"docstring": "if user is staff or if SAFE request, we're done otherwise check model object perms try for user object if request.user is member or admin of org check perms except: this is org object, check permissions",
"name": "has_permission",
"signature": "def has_permission(self, request, view)"
... | 2 | stack_v2_sparse_classes_30k_train_004447 | Implement the Python class `IsOrgAdminOrMember` described below.
Class description:
Custom to check if user belongs to org
Method signatures and docstrings:
- def has_permission(self, request, view): if user is staff or if SAFE request, we're done otherwise check model object perms try for user object if request.user... | Implement the Python class `IsOrgAdminOrMember` described below.
Class description:
Custom to check if user belongs to org
Method signatures and docstrings:
- def has_permission(self, request, view): if user is staff or if SAFE request, we're done otherwise check model object perms try for user object if request.user... | 40d9608295daefc5e1cd83afd84ecb5b0518cc3d | <|skeleton|>
class IsOrgAdminOrMember:
"""Custom to check if user belongs to org"""
def has_permission(self, request, view):
"""if user is staff or if SAFE request, we're done otherwise check model object perms try for user object if request.user is member or admin of org check perms except: this is or... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IsOrgAdminOrMember:
"""Custom to check if user belongs to org"""
def has_permission(self, request, view):
"""if user is staff or if SAFE request, we're done otherwise check model object perms try for user object if request.user is member or admin of org check perms except: this is org object, che... | the_stack_v2_python_sparse | app/squac/permissions.py | pnsn/squacapi | train | 7 |
8b44b3e1f7a451cf4076ccc875df59795ae48bc3 | [
"time = self.flowsheet().config.time\nt = self.flowsheet().config.time.first()\nself.lift_height = Var(time, initialize=400, domain=NonNegativeReals, units=pyunits.ft, doc='Lift height for pump [ft]')\nself.flow_in = pyunits.convert(self.flow_vol_in[t], to_units=pyunits.m ** 3 / pyunits.hr)\ntry:\n self.lift_hei... | <|body_start_0|>
time = self.flowsheet().config.time
t = self.flowsheet().config.time.first()
self.lift_height = Var(time, initialize=400, domain=NonNegativeReals, units=pyunits.ft, doc='Lift height for pump [ft]')
self.flow_in = pyunits.convert(self.flow_vol_in[t], to_units=pyunits.m **... | UnitProcess | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnitProcess:
def fixed_cap(self, unit_params):
"""Fixed capital cost for deep well injection. :param unit_params: Input parameter dictionary from input sheet. :type unit_params: dict :param lift_height: Lift height for pump [ft] :type lift_height: float :param pipe_distance: Piping dista... | stack_v2_sparse_classes_10k_train_001580 | 3,523 | permissive | [
{
"docstring": "Fixed capital cost for deep well injection. :param unit_params: Input parameter dictionary from input sheet. :type unit_params: dict :param lift_height: Lift height for pump [ft] :type lift_height: float :param pipe_distance: Piping distance to deep well injection site :type pipe_distance: float... | 3 | stack_v2_sparse_classes_30k_train_004418 | Implement the Python class `UnitProcess` described below.
Class description:
Implement the UnitProcess class.
Method signatures and docstrings:
- def fixed_cap(self, unit_params): Fixed capital cost for deep well injection. :param unit_params: Input parameter dictionary from input sheet. :type unit_params: dict :para... | Implement the Python class `UnitProcess` described below.
Class description:
Implement the UnitProcess class.
Method signatures and docstrings:
- def fixed_cap(self, unit_params): Fixed capital cost for deep well injection. :param unit_params: Input parameter dictionary from input sheet. :type unit_params: dict :para... | 0e9713a195b50824c4d38ff6ea5db244a6f1ad57 | <|skeleton|>
class UnitProcess:
def fixed_cap(self, unit_params):
"""Fixed capital cost for deep well injection. :param unit_params: Input parameter dictionary from input sheet. :type unit_params: dict :param lift_height: Lift height for pump [ft] :type lift_height: float :param pipe_distance: Piping dista... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UnitProcess:
def fixed_cap(self, unit_params):
"""Fixed capital cost for deep well injection. :param unit_params: Input parameter dictionary from input sheet. :type unit_params: dict :param lift_height: Lift height for pump [ft] :type lift_height: float :param pipe_distance: Piping distance to deep we... | the_stack_v2_python_sparse | watertap3/watertap3/wt_units/deep_well_injection.py | JamariMurke/WaterTAP3 | train | 0 | |
bc403fcdd9722d84dd2b72e1f64e8c21370e268f | [
"self.graph = graph\nself.point_dict = dict()\nself.radius = 1",
"if root is None:\n algorithm = TreeCenter(self.graph)\n algorithm.run()\n root = algorithm.tree_center[0]\nself.plot(root, 0, 6, level=0)",
"assert isinstance(left, (int, Fraction))\nassert isinstance(right, (int, Fraction))\nangle = Fra... | <|body_start_0|>
self.graph = graph
self.point_dict = dict()
self.radius = 1
<|end_body_0|>
<|body_start_1|>
if root is None:
algorithm = TreeCenter(self.graph)
algorithm.run()
root = algorithm.tree_center[0]
self.plot(root, 0, 6, level=0)
<|e... | Finding the positions of tree nodes in the plane (radius, angle). | TreePlotRadiusAngle | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TreePlotRadiusAngle:
"""Finding the positions of tree nodes in the plane (radius, angle)."""
def __init__(self, graph):
"""The algorithm initialization."""
<|body_0|>
def run(self, root=None):
"""Executable pseudocode."""
<|body_1|>
def plot(self, so... | stack_v2_sparse_classes_10k_train_001581 | 3,663 | permissive | [
{
"docstring": "The algorithm initialization.",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Executable pseudocode.",
"name": "run",
"signature": "def run(self, root=None)"
},
{
"docstring": "Find node positions (radius, angle). Parameters -----... | 3 | stack_v2_sparse_classes_30k_train_006559 | Implement the Python class `TreePlotRadiusAngle` described below.
Class description:
Finding the positions of tree nodes in the plane (radius, angle).
Method signatures and docstrings:
- def __init__(self, graph): The algorithm initialization.
- def run(self, root=None): Executable pseudocode.
- def plot(self, source... | Implement the Python class `TreePlotRadiusAngle` described below.
Class description:
Finding the positions of tree nodes in the plane (radius, angle).
Method signatures and docstrings:
- def __init__(self, graph): The algorithm initialization.
- def run(self, root=None): Executable pseudocode.
- def plot(self, source... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class TreePlotRadiusAngle:
"""Finding the positions of tree nodes in the plane (radius, angle)."""
def __init__(self, graph):
"""The algorithm initialization."""
<|body_0|>
def run(self, root=None):
"""Executable pseudocode."""
<|body_1|>
def plot(self, so... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TreePlotRadiusAngle:
"""Finding the positions of tree nodes in the plane (radius, angle)."""
def __init__(self, graph):
"""The algorithm initialization."""
self.graph = graph
self.point_dict = dict()
self.radius = 1
def run(self, root=None):
"""Executable pseu... | the_stack_v2_python_sparse | graphtheory/forests/treeplot.py | kgashok/graphs-dict | train | 0 |
0ef7971de8b5e7700e3bf304c91ead69a8ac9971 | [
"if ws is None:\n self.tmp_folder = tempfile.TemporaryDirectory()\n ws = self.tmp_folder.name\nself.ws = ws",
"folder = path.join(self.ws, name)\nmakedirs(folder, exist_ok=True)\nmapping_path = path.join(folder, 'mapping.json')\nif path.exists(mapping_path):\n with open(mapping_path, 'r', encoding='utf-8... | <|body_start_0|>
if ws is None:
self.tmp_folder = tempfile.TemporaryDirectory()
ws = self.tmp_folder.name
self.ws = ws
<|end_body_0|>
<|body_start_1|>
folder = path.join(self.ws, name)
makedirs(folder, exist_ok=True)
mapping_path = path.join(folder, 'mapp... | Generate a folder name for caching intermediate variables | CachedWorkspace | [
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CachedWorkspace:
"""Generate a folder name for caching intermediate variables"""
def __init__(self, ws=None):
"""Initialization Args: ws (str, optional): Workspace folder If not given, will use a temporary folder."""
<|body_0|>
def get_path_for_name_and_kwargs(self, name... | stack_v2_sparse_classes_10k_train_001582 | 22,314 | permissive | [
{
"docstring": "Initialization Args: ws (str, optional): Workspace folder If not given, will use a temporary folder.",
"name": "__init__",
"signature": "def __init__(self, ws=None)"
},
{
"docstring": "Generate a hashed path in the workspace (self.ws) Args: name (str): a basename (e.g., the inter... | 2 | stack_v2_sparse_classes_30k_train_006774 | Implement the Python class `CachedWorkspace` described below.
Class description:
Generate a folder name for caching intermediate variables
Method signatures and docstrings:
- def __init__(self, ws=None): Initialization Args: ws (str, optional): Workspace folder If not given, will use a temporary folder.
- def get_pat... | Implement the Python class `CachedWorkspace` described below.
Class description:
Generate a folder name for caching intermediate variables
Method signatures and docstrings:
- def __init__(self, ws=None): Initialization Args: ws (str, optional): Workspace folder If not given, will use a temporary folder.
- def get_pat... | 9aefa13e1cc873cb68801cba49d4e9a48572eeb7 | <|skeleton|>
class CachedWorkspace:
"""Generate a folder name for caching intermediate variables"""
def __init__(self, ws=None):
"""Initialization Args: ws (str, optional): Workspace folder If not given, will use a temporary folder."""
<|body_0|>
def get_path_for_name_and_kwargs(self, name... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CachedWorkspace:
"""Generate a folder name for caching intermediate variables"""
def __init__(self, ws=None):
"""Initialization Args: ws (str, optional): Workspace folder If not given, will use a temporary folder."""
if ws is None:
self.tmp_folder = tempfile.TemporaryDirectory... | the_stack_v2_python_sparse | pecos/apps/text2text/model.py | zusmani/pecos | train | 1 |
0a63623e867dcd0367f8ab7ea08ba1e903061791 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Process()",
"from .file_hash import FileHash\nfrom .process_integrity_level import ProcessIntegrityLevel\nfrom .file_hash import FileHash\nfrom .process_integrity_level import ProcessIntegrityLevel\nfields: Dict[str, Callable[[Any], No... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Process()
<|end_body_0|>
<|body_start_1|>
from .file_hash import FileHash
from .process_integrity_level import ProcessIntegrityLevel
from .file_hash import FileHash
from ... | Process | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Process:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Process:
"""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: Process"""... | stack_v2_sparse_classes_10k_train_001583 | 6,144 | 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: Process",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse... | 3 | stack_v2_sparse_classes_30k_train_003172 | Implement the Python class `Process` described below.
Class description:
Implement the Process class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Process: Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | Implement the Python class `Process` described below.
Class description:
Implement the Process class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Process: Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Process:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Process:
"""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: Process"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Process:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Process:
"""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: Process"""
if no... | the_stack_v2_python_sparse | msgraph/generated/models/process.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
c01d79cb05b4f8c46a7f0024c397a22edf3aa765 | [
"lock = threading.Lock()\nthreads = []\nfor url in league_urls:\n t = threading.Thread(target=self.crawl_teams_per_league, args=(url, lock))\n t.start()\n threads.append(t)\nfor t in threads:\n t.join()\nreturn self.statistics['teams']",
"lock = threading.Lock()\nthreads = []\nfor url in league_result... | <|body_start_0|>
lock = threading.Lock()
threads = []
for url in league_urls:
t = threading.Thread(target=self.crawl_teams_per_league, args=(url, lock))
t.start()
threads.append(t)
for t in threads:
t.join()
return self.statistics['... | TODO: not using proper functions anymore TODO: document, fix bugs. TODO: Can be further improved by not blocking results / fixtures by eachother. | SRSCrawlerConcurrent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SRSCrawlerConcurrent:
"""TODO: not using proper functions anymore TODO: document, fix bugs. TODO: Can be further improved by not blocking results / fixtures by eachother."""
def crawl_teams(self, league_urls: List[str]):
"""TODO: write doc."""
<|body_0|>
def crawl_result... | stack_v2_sparse_classes_10k_train_001584 | 2,070 | no_license | [
{
"docstring": "TODO: write doc.",
"name": "crawl_teams",
"signature": "def crawl_teams(self, league_urls: List[str])"
},
{
"docstring": ":param league_results_urls: list of tuples [(league_shortcode, league_url), ..] :param deep_crawl: defaults to False. Set True to follow pagination :return: -... | 3 | stack_v2_sparse_classes_30k_val_000003 | Implement the Python class `SRSCrawlerConcurrent` described below.
Class description:
TODO: not using proper functions anymore TODO: document, fix bugs. TODO: Can be further improved by not blocking results / fixtures by eachother.
Method signatures and docstrings:
- def crawl_teams(self, league_urls: List[str]): TOD... | Implement the Python class `SRSCrawlerConcurrent` described below.
Class description:
TODO: not using proper functions anymore TODO: document, fix bugs. TODO: Can be further improved by not blocking results / fixtures by eachother.
Method signatures and docstrings:
- def crawl_teams(self, league_urls: List[str]): TOD... | 1aeb0ee82ba6052de9a0dee488393bcd79e7d98e | <|skeleton|>
class SRSCrawlerConcurrent:
"""TODO: not using proper functions anymore TODO: document, fix bugs. TODO: Can be further improved by not blocking results / fixtures by eachother."""
def crawl_teams(self, league_urls: List[str]):
"""TODO: write doc."""
<|body_0|>
def crawl_result... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SRSCrawlerConcurrent:
"""TODO: not using proper functions anymore TODO: document, fix bugs. TODO: Can be further improved by not blocking results / fixtures by eachother."""
def crawl_teams(self, league_urls: List[str]):
"""TODO: write doc."""
lock = threading.Lock()
threads = []
... | the_stack_v2_python_sparse | swissrugbystats/crawler/crawler/SRSCrawlerConcurrent.py | SwissRugbyStats/swissrugbystats_server | train | 0 |
048562c223f206e16cb9dc4a6975e2ecc5cb2012 | [
"tree = []\nqueue = collections.deque([root])\nwhile queue:\n val = queue.popleft()\n if not val:\n tree.append(None)\n else:\n tree.append(str(val.val))\n queue.append(val.left)\n queue.append(val.right)\nreturn ' '.join(tree)",
"data = collections.deque(data.split(' '))\nnod... | <|body_start_0|>
tree = []
queue = collections.deque([root])
while queue:
val = queue.popleft()
if not val:
tree.append(None)
else:
tree.append(str(val.val))
queue.append(val.left)
queue.append(va... | 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_001585 | 2,037 | 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_005969 | 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:... | c7a42753b2b16c7b9c66b8d7c2e67b683a15e27d | <|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"""
tree = []
queue = collections.deque([root])
while queue:
val = queue.popleft()
if not val:
tree.append(None)
else:
... | the_stack_v2_python_sparse | hard/297.py | brandoneng000/LeetCode | train | 0 | |
a2d6aa03aa41ae5fa842219ae37a6dabdfddf0c9 | [
"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... | Missing associated documentation comment in .proto file. | UserFavServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserFavServicer:
"""Missing associated documentation comment in .proto file."""
def GetFavList(self, request, context):
"""过滤收藏信息"""
<|body_0|>
def AddUserFav(self, request, context):
"""添加留言"""
<|body_1|>
def DeleteUserFav(self, request, context):
... | stack_v2_sparse_classes_10k_train_001586 | 6,939 | no_license | [
{
"docstring": "过滤收藏信息",
"name": "GetFavList",
"signature": "def GetFavList(self, request, context)"
},
{
"docstring": "添加留言",
"name": "AddUserFav",
"signature": "def AddUserFav(self, request, context)"
},
{
"docstring": "删除留言",
"name": "DeleteUserFav",
"signature": "def ... | 4 | stack_v2_sparse_classes_30k_train_001932 | Implement the Python class `UserFavServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def GetFavList(self, request, context): 过滤收藏信息
- def AddUserFav(self, request, context): 添加留言
- def DeleteUserFav(self, request, context): 删除留言
... | Implement the Python class `UserFavServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def GetFavList(self, request, context): 过滤收藏信息
- def AddUserFav(self, request, context): 添加留言
- def DeleteUserFav(self, request, context): 删除留言
... | e01c8fc9d9e734578733816669c122dede02489e | <|skeleton|>
class UserFavServicer:
"""Missing associated documentation comment in .proto file."""
def GetFavList(self, request, context):
"""过滤收藏信息"""
<|body_0|>
def AddUserFav(self, request, context):
"""添加留言"""
<|body_1|>
def DeleteUserFav(self, request, context):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserFavServicer:
"""Missing associated documentation comment in .proto file."""
def GetFavList(self, request, context):
"""过滤收藏信息"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not impleme... | the_stack_v2_python_sparse | other/mxshop_srvs/userop_srv/proto/userfav_pb2_grpc.py | xqmmy/go-fresh | train | 1 |
c00ecc88838314256947875c026edee9048581e6 | [
"self.value_stack = []\nwhile root:\n self.value_stack.append(root)\n root = root.left",
"temp_root = self.value_stack.pop()\ntemp_value = temp_root.val\ntemp_root = temp_root.right\nwhile temp_root:\n self.value_stack.append(temp_root)\n temp_root = temp_root.left\nreturn temp_value",
"if self.valu... | <|body_start_0|>
self.value_stack = []
while root:
self.value_stack.append(root)
root = root.left
<|end_body_0|>
<|body_start_1|>
temp_root = self.value_stack.pop()
temp_value = temp_root.val
temp_root = temp_root.right
while temp_root:
... | BSTIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
self.value_stack = []
... | stack_v2_sparse_classes_10k_train_001587 | 1,145 | no_license | [
{
"docstring": ":type root: TreeNode",
"name": "__init__",
"signature": "def __init__(self, root)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",
"signature": "def hasNext(self)"
}
] | 3 | null | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool
<|skeleton|>
class BSTIterator:
def __init__(self, root... | dc45210cb2cc50bfefd8c21c865e6ee2163a022a | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
self.value_stack = []
while root:
self.value_stack.append(root)
root = root.left
def next(self):
""":rtype: int"""
temp_root = self.value_stack.pop()
temp_value = temp... | the_stack_v2_python_sparse | practice/solution/0173_binary_search_tree_iterator.py | kesarb/leetcode-summary-python | train | 0 | |
06c9deea268d960d8d0ee98a1bfd9a07619be465 | [
"self.n = int(n)\nself.p = float(p)\nif data is None:\n if self.n < 1:\n raise ValueError('n must be a positive value')\n elif self.p <= 0 or self.p >= 1:\n raise ValueError('p must be greater than 0 and less than 1')\nelif isinstance(data, list):\n if len(data) > 1:\n self.data = data... | <|body_start_0|>
self.n = int(n)
self.p = float(p)
if data is None:
if self.n < 1:
raise ValueError('n must be a positive value')
elif self.p <= 0 or self.p >= 1:
raise ValueError('p must be greater than 0 and less than 1')
elif isi... | Class Binomial | Binomial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Binomial:
"""Class Binomial"""
def __init__(self, data=None, n=1, p=0.5):
"""Initializes the distribution. Args: data (list): distribution data n (int): Bernoulli number. p (float): success probability."""
<|body_0|>
def pmf(self, k):
"""Calculates the pmf at a g... | stack_v2_sparse_classes_10k_train_001588 | 2,389 | no_license | [
{
"docstring": "Initializes the distribution. Args: data (list): distribution data n (int): Bernoulli number. p (float): success probability.",
"name": "__init__",
"signature": "def __init__(self, data=None, n=1, p=0.5)"
},
{
"docstring": "Calculates the pmf at a given k Args: k (int): point to ... | 3 | stack_v2_sparse_classes_30k_val_000073 | Implement the Python class `Binomial` described below.
Class description:
Class Binomial
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): Initializes the distribution. Args: data (list): distribution data n (int): Bernoulli number. p (float): success probability.
- def pmf(self, k): Calc... | Implement the Python class `Binomial` described below.
Class description:
Class Binomial
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): Initializes the distribution. Args: data (list): distribution data n (int): Bernoulli number. p (float): success probability.
- def pmf(self, k): Calc... | 5aff923277cfe9f2b5324a773e4e5c3cac810a0c | <|skeleton|>
class Binomial:
"""Class Binomial"""
def __init__(self, data=None, n=1, p=0.5):
"""Initializes the distribution. Args: data (list): distribution data n (int): Bernoulli number. p (float): success probability."""
<|body_0|>
def pmf(self, k):
"""Calculates the pmf at a g... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Binomial:
"""Class Binomial"""
def __init__(self, data=None, n=1, p=0.5):
"""Initializes the distribution. Args: data (list): distribution data n (int): Bernoulli number. p (float): success probability."""
self.n = int(n)
self.p = float(p)
if data is None:
if s... | the_stack_v2_python_sparse | math/0x03-probability/binomial.py | cmmolanos1/holbertonschool-machine_learning | train | 1 |
43bbf56f80407f5494ca83052d1386aaf2432760 | [
"acl.enforce('dynamic_actions:create', context.ctx())\nLOG.debug('Creating dynamic action [action=%s]', dyn_action)\nif not dyn_action.code_source_id and (not dyn_action.code_source_name):\n raise exc.InputException(\"Either 'code_source_id' or 'code_source_name' must be provided.\")\ncode_source = db_api.get_co... | <|body_start_0|>
acl.enforce('dynamic_actions:create', context.ctx())
LOG.debug('Creating dynamic action [action=%s]', dyn_action)
if not dyn_action.code_source_id and (not dyn_action.code_source_name):
raise exc.InputException("Either 'code_source_id' or 'code_source_name' must be p... | DynamicActionsController | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DynamicActionsController:
def post(self, dyn_action):
"""Creates new dynamic action. :param dyn_action: Dynamic action to create."""
<|body_0|>
def put(self, dyn_action):
"""Update dynamic action. :param dyn_action: Dynamic action to create."""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_001589 | 9,796 | permissive | [
{
"docstring": "Creates new dynamic action. :param dyn_action: Dynamic action to create.",
"name": "post",
"signature": "def post(self, dyn_action)"
},
{
"docstring": "Update dynamic action. :param dyn_action: Dynamic action to create.",
"name": "put",
"signature": "def put(self, dyn_act... | 5 | stack_v2_sparse_classes_30k_train_002760 | Implement the Python class `DynamicActionsController` described below.
Class description:
Implement the DynamicActionsController class.
Method signatures and docstrings:
- def post(self, dyn_action): Creates new dynamic action. :param dyn_action: Dynamic action to create.
- def put(self, dyn_action): Update dynamic a... | Implement the Python class `DynamicActionsController` described below.
Class description:
Implement the DynamicActionsController class.
Method signatures and docstrings:
- def post(self, dyn_action): Creates new dynamic action. :param dyn_action: Dynamic action to create.
- def put(self, dyn_action): Update dynamic a... | 7baff017d0cf01d19c44055ad201ca59131b9f94 | <|skeleton|>
class DynamicActionsController:
def post(self, dyn_action):
"""Creates new dynamic action. :param dyn_action: Dynamic action to create."""
<|body_0|>
def put(self, dyn_action):
"""Update dynamic action. :param dyn_action: Dynamic action to create."""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DynamicActionsController:
def post(self, dyn_action):
"""Creates new dynamic action. :param dyn_action: Dynamic action to create."""
acl.enforce('dynamic_actions:create', context.ctx())
LOG.debug('Creating dynamic action [action=%s]', dyn_action)
if not dyn_action.code_source_i... | the_stack_v2_python_sparse | mistral/api/controllers/v2/dynamic_action.py | openstack/mistral | train | 214 | |
0df4bde1b6f4554f89f6ec69b315fe2a45f0786a | [
"self.intent_type = intent_type\nself.domain = domain\nself.service = service\nself.speech = speech",
"hass = intent_obj.hass\nslots = self.async_validate_slots(intent_obj.slots)\nstate = async_match_state(hass, slots['name']['value'])\nawait hass.services.async_call(self.domain, self.service, {ATTR_ENTITY_ID: st... | <|body_start_0|>
self.intent_type = intent_type
self.domain = domain
self.service = service
self.speech = speech
<|end_body_0|>
<|body_start_1|>
hass = intent_obj.hass
slots = self.async_validate_slots(intent_obj.slots)
state = async_match_state(hass, slots['name... | Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id. | ServiceIntentHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceIntentHandler:
"""Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id."""
def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None:
"""Create Service Intent Handler."""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_001590 | 8,241 | permissive | [
{
"docstring": "Create Service Intent Handler.",
"name": "__init__",
"signature": "def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None"
},
{
"docstring": "Handle the hass intent.",
"name": "async_handle",
"signature": "async def async_handle(self, intent_... | 2 | null | Implement the Python class `ServiceIntentHandler` described below.
Class description:
Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id.
Method signatures and docstrings:
- def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None: C... | Implement the Python class `ServiceIntentHandler` described below.
Class description:
Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id.
Method signatures and docstrings:
- def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None: C... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class ServiceIntentHandler:
"""Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id."""
def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None:
"""Create Service Intent Handler."""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ServiceIntentHandler:
"""Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id."""
def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None:
"""Create Service Intent Handler."""
self.intent_type = intent_typ... | the_stack_v2_python_sparse | homeassistant/helpers/intent.py | BenWoodford/home-assistant | train | 11 |
67b8c381ab3e85c8c39229f626375b11d4acdfe2 | [
"super(MultiboxLoss, self).__init__()\nself.iou_threshold = iou_threshold\nself.neg_pos_ratio = neg_pos_ratio\nself.center_variance = center_variance\nself.size_variance = size_variance\nself.priors = priors\nself.priors",
"num_classes = confidence.size(2)\nwith torch.no_grad():\n loss = -F.log_softmax(confide... | <|body_start_0|>
super(MultiboxLoss, self).__init__()
self.iou_threshold = iou_threshold
self.neg_pos_ratio = neg_pos_ratio
self.center_variance = center_variance
self.size_variance = size_variance
self.priors = priors
self.priors
<|end_body_0|>
<|body_start_1|>
... | MultiboxLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiboxLoss:
def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device):
"""Implement SSD Multibox Loss. Basically, Multibox loss combines classification loss and Smooth L1 regression loss."""
<|body_0|>
def forward(self, confidence, pr... | stack_v2_sparse_classes_10k_train_001591 | 33,668 | no_license | [
{
"docstring": "Implement SSD Multibox Loss. Basically, Multibox loss combines classification loss and Smooth L1 regression loss.",
"name": "__init__",
"signature": "def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device)"
},
{
"docstring": "Compute class... | 2 | null | Implement the Python class `MultiboxLoss` described below.
Class description:
Implement the MultiboxLoss class.
Method signatures and docstrings:
- def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device): Implement SSD Multibox Loss. Basically, Multibox loss combines classific... | Implement the Python class `MultiboxLoss` described below.
Class description:
Implement the MultiboxLoss class.
Method signatures and docstrings:
- def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device): Implement SSD Multibox Loss. Basically, Multibox loss combines classific... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class MultiboxLoss:
def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device):
"""Implement SSD Multibox Loss. Basically, Multibox loss combines classification loss and Smooth L1 regression loss."""
<|body_0|>
def forward(self, confidence, pr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MultiboxLoss:
def __init__(self, priors, iou_threshold, neg_pos_ratio, center_variance, size_variance, device):
"""Implement SSD Multibox Loss. Basically, Multibox loss combines classification loss and Smooth L1 regression loss."""
super(MultiboxLoss, self).__init__()
self.iou_threshol... | the_stack_v2_python_sparse | generated/test_qfgaohao_pytorch_ssd.py | jansel/pytorch-jit-paritybench | train | 35 | |
dbe740162d6866df73251f24ee41fbe2a4d30987 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('ckarjadi_johnnyg7', 'ckarjadi_johnnyg7')\nh_Locs = get_Col('h_Locs', repo)\nc_Inc = get_Col('c_Inc', repo)\nw_Jams = get_Col('w_Jams', repo)\nchange = change_hospitals(h_Locs)\ncrimes_close = closest_cri... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('ckarjadi_johnnyg7', 'ckarjadi_johnnyg7')
h_Locs = get_Col('h_Locs', repo)
c_Inc = get_Col('c_Inc', repo)
w_Jams = get_Col('w_Jams', repo)
... | hospitals | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class hospitals:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything hap... | stack_v2_sparse_classes_10k_train_001592 | 3,711 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_train_002136 | Implement the Python class `hospitals` described below.
Class description:
Implement the hospitals class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=N... | Implement the Python class `hospitals` described below.
Class description:
Implement the hospitals class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=N... | 9cb0ad789b6ff265222cbd3ea3561ff553b4cdff | <|skeleton|>
class hospitals:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything hap... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class hospitals:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('ckarjadi_johnnyg7', 'ckarjadi_johnnyg7')
... | the_stack_v2_python_sparse | ckarjadi_johnnyg7/project2/hospitals_execute.py | yinghang/course-2016-fal-proj | train | 1 | |
4fef52fd4a8284eee32ba3cbbb312e12e1593df7 | [
"if not builder:\n raise ValueError('Instance builder is not specified')\nself._builder = builder",
"osh = self._builder.buildNoNameInstance(number, hostname, system)\nosh.setContainer(containerOsh)\nreturn osh",
"if not pdo:\n raise ValueError('Instance information is not specified')\nif not containerOsh... | <|body_start_0|>
if not builder:
raise ValueError('Instance builder is not specified')
self._builder = builder
<|end_body_0|>
<|body_start_1|>
osh = self._builder.buildNoNameInstance(number, hostname, system)
osh.setContainer(containerOsh)
return osh
<|end_body_1|>
... | InstanceReporter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanceReporter:
def __init__(self, builder):
"""@types: InstanceBuilder"""
<|body_0|>
def reportNoNameInst(self, number, hostname, system, containerOsh):
"""@types: str, str, System, osh -> osh"""
<|body_1|>
def reportInstance(self, pdo, containerOsh):... | stack_v2_sparse_classes_10k_train_001593 | 14,040 | no_license | [
{
"docstring": "@types: InstanceBuilder",
"name": "__init__",
"signature": "def __init__(self, builder)"
},
{
"docstring": "@types: str, str, System, osh -> osh",
"name": "reportNoNameInst",
"signature": "def reportNoNameInst(self, number, hostname, system, containerOsh)"
},
{
"d... | 3 | null | Implement the Python class `InstanceReporter` described below.
Class description:
Implement the InstanceReporter class.
Method signatures and docstrings:
- def __init__(self, builder): @types: InstanceBuilder
- def reportNoNameInst(self, number, hostname, system, containerOsh): @types: str, str, System, osh -> osh
- ... | Implement the Python class `InstanceReporter` described below.
Class description:
Implement the InstanceReporter class.
Method signatures and docstrings:
- def __init__(self, builder): @types: InstanceBuilder
- def reportNoNameInst(self, number, hostname, system, containerOsh): @types: str, str, System, osh -> osh
- ... | c431e809e8d0f82e1bca7e3429dd0245560b5680 | <|skeleton|>
class InstanceReporter:
def __init__(self, builder):
"""@types: InstanceBuilder"""
<|body_0|>
def reportNoNameInst(self, number, hostname, system, containerOsh):
"""@types: str, str, System, osh -> osh"""
<|body_1|>
def reportInstance(self, pdo, containerOsh):... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InstanceReporter:
def __init__(self, builder):
"""@types: InstanceBuilder"""
if not builder:
raise ValueError('Instance builder is not specified')
self._builder = builder
def reportNoNameInst(self, number, hostname, system, containerOsh):
"""@types: str, str, S... | the_stack_v2_python_sparse | reference/ucmdb/discovery/sap_abap.py | madmonkyang/cda-record | train | 0 | |
8af38bc258b027642cf1db7d75621e7c25c195eb | [
"self.model = RandomForestClassifier(bootstrap=True, criterion='gini', min_samples_split=2, max_features='auto', min_samples_leaf=1, n_estimators=1000)\nself.X = X\nself.Y = Y",
"if params is None:\n params = [{'n_estimators': [100, 200, 500, 1000], 'criterion': ['entropy'], 'max_features': ['sqrt', 'auto'], '... | <|body_start_0|>
self.model = RandomForestClassifier(bootstrap=True, criterion='gini', min_samples_split=2, max_features='auto', min_samples_leaf=1, n_estimators=1000)
self.X = X
self.Y = Y
<|end_body_0|>
<|body_start_1|>
if params is None:
params = [{'n_estimators': [100, 2... | Random forest classifier | RFClassifier | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RFClassifier:
"""Random forest classifier"""
def __init__(self, X, Y):
""":param X: :param Y:"""
<|body_0|>
def tune_and_eval(self, results_file, params=None, feature_names=None, njobs=50, kfold=10):
""":param results_file: :param params: :param feature_names: :p... | stack_v2_sparse_classes_10k_train_001594 | 10,404 | permissive | [
{
"docstring": ":param X: :param Y:",
"name": "__init__",
"signature": "def __init__(self, X, Y)"
},
{
"docstring": ":param results_file: :param params: :param feature_names: :param njobs: :param kfold: :return:",
"name": "tune_and_eval",
"signature": "def tune_and_eval(self, results_fil... | 4 | stack_v2_sparse_classes_30k_train_002087 | Implement the Python class `RFClassifier` described below.
Class description:
Random forest classifier
Method signatures and docstrings:
- def __init__(self, X, Y): :param X: :param Y:
- def tune_and_eval(self, results_file, params=None, feature_names=None, njobs=50, kfold=10): :param results_file: :param params: :pa... | Implement the Python class `RFClassifier` described below.
Class description:
Random forest classifier
Method signatures and docstrings:
- def __init__(self, X, Y): :param X: :param Y:
- def tune_and_eval(self, results_file, params=None, feature_names=None, njobs=50, kfold=10): :param results_file: :param params: :pa... | 127177deb630ad66520a2fdae1793417cd77ee99 | <|skeleton|>
class RFClassifier:
"""Random forest classifier"""
def __init__(self, X, Y):
""":param X: :param Y:"""
<|body_0|>
def tune_and_eval(self, results_file, params=None, feature_names=None, njobs=50, kfold=10):
""":param results_file: :param params: :param feature_names: :p... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RFClassifier:
"""Random forest classifier"""
def __init__(self, X, Y):
""":param X: :param Y:"""
self.model = RandomForestClassifier(bootstrap=True, criterion='gini', min_samples_split=2, max_features='auto', min_samples_leaf=1, n_estimators=1000)
self.X = X
self.Y = Y
... | the_stack_v2_python_sparse | classifier/classical_classifiers.py | seedpcseed/DiTaxa | train | 0 |
3f57a3105668df5a1e4d8dc2a23ba80f3223ebb7 | [
"self.size = size\nself.que_list = [None] * self.size\nself.count = 0",
"i = self.count\nself.que_list[i] = enqueue_data\nself.count += 1",
"dequeued_value = self.que_list[0]\nfor i in range(0, len(self.que_list) - 1):\n self.que_list[i] = self.que_list[i + 1]\nself.que_list[len(self.que_list) - 1] = None\ns... | <|body_start_0|>
self.size = size
self.que_list = [None] * self.size
self.count = 0
<|end_body_0|>
<|body_start_1|>
i = self.count
self.que_list[i] = enqueue_data
self.count += 1
<|end_body_1|>
<|body_start_2|>
dequeued_value = self.que_list[0]
for i in ... | queクラス 引数：リストのサイズ | que | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class que:
"""queクラス 引数：リストのサイズ"""
def __init__(self, size):
"""引数：リストのサイズ"""
<|body_0|>
def enqueue(self, enqueue_data):
"""引数：エンキューしたい数値"""
<|body_1|>
def dequeue(self):
"""デキューした値を返す"""
<|body_2|>
def is_empty(self):
"""空ならT... | stack_v2_sparse_classes_10k_train_001595 | 2,175 | no_license | [
{
"docstring": "引数：リストのサイズ",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": "引数：エンキューしたい数値",
"name": "enqueue",
"signature": "def enqueue(self, enqueue_data)"
},
{
"docstring": "デキューした値を返す",
"name": "dequeue",
"signature": "def dequeue(self)... | 4 | stack_v2_sparse_classes_30k_test_000283 | Implement the Python class `que` described below.
Class description:
queクラス 引数：リストのサイズ
Method signatures and docstrings:
- def __init__(self, size): 引数：リストのサイズ
- def enqueue(self, enqueue_data): 引数：エンキューしたい数値
- def dequeue(self): デキューした値を返す
- def is_empty(self): 空ならTrue, 空でないならFalseを返す | Implement the Python class `que` described below.
Class description:
queクラス 引数：リストのサイズ
Method signatures and docstrings:
- def __init__(self, size): 引数：リストのサイズ
- def enqueue(self, enqueue_data): 引数：エンキューしたい数値
- def dequeue(self): デキューした値を返す
- def is_empty(self): 空ならTrue, 空でないならFalseを返す
<|skeleton|>
class que:
""... | c594461944316b6655ddaf7e877dd6b293649f53 | <|skeleton|>
class que:
"""queクラス 引数：リストのサイズ"""
def __init__(self, size):
"""引数：リストのサイズ"""
<|body_0|>
def enqueue(self, enqueue_data):
"""引数：エンキューしたい数値"""
<|body_1|>
def dequeue(self):
"""デキューした値を返す"""
<|body_2|>
def is_empty(self):
"""空ならT... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class que:
"""queクラス 引数：リストのサイズ"""
def __init__(self, size):
"""引数：リストのサイズ"""
self.size = size
self.que_list = [None] * self.size
self.count = 0
def enqueue(self, enqueue_data):
"""引数：エンキューしたい数値"""
i = self.count
self.que_list[i] = enqueue_data
... | the_stack_v2_python_sparse | a0303_stack_que.py | j-d-0630/python | train | 0 |
74769ddb370198b69f3b0b9aa950255f0798fd88 | [
"self._num_participants = num_participants\nself._counter = 0\nself._flag = False\nself._local_sense = threading.local()\nself._lock = threading.Lock()\nself._condition = threading.Condition()",
"self._local_sense.value = not self._flag\nwith self._lock:\n self._counter += 1\n if self._counter == self._num_... | <|body_start_0|>
self._num_participants = num_participants
self._counter = 0
self._flag = False
self._local_sense = threading.local()
self._lock = threading.Lock()
self._condition = threading.Condition()
<|end_body_0|>
<|body_start_1|>
self._local_sense.value = n... | A reusable barrier class for worker synchronization. | _Barrier | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Barrier:
"""A reusable barrier class for worker synchronization."""
def __init__(self, num_participants):
"""Initializes the barrier object. Args: num_participants: an integer which is the expected number of calls of `wait` pass to through this barrier."""
<|body_0|>
de... | stack_v2_sparse_classes_10k_train_001596 | 34,550 | permissive | [
{
"docstring": "Initializes the barrier object. Args: num_participants: an integer which is the expected number of calls of `wait` pass to through this barrier.",
"name": "__init__",
"signature": "def __init__(self, num_participants)"
},
{
"docstring": "Waits until all other callers reach the sa... | 2 | stack_v2_sparse_classes_30k_train_002991 | Implement the Python class `_Barrier` described below.
Class description:
A reusable barrier class for worker synchronization.
Method signatures and docstrings:
- def __init__(self, num_participants): Initializes the barrier object. Args: num_participants: an integer which is the expected number of calls of `wait` pa... | Implement the Python class `_Barrier` described below.
Class description:
A reusable barrier class for worker synchronization.
Method signatures and docstrings:
- def __init__(self, num_participants): Initializes the barrier object. Args: num_participants: an integer which is the expected number of calls of `wait` pa... | a7f3934a67900720af3d3b15389551483bee50b8 | <|skeleton|>
class _Barrier:
"""A reusable barrier class for worker synchronization."""
def __init__(self, num_participants):
"""Initializes the barrier object. Args: num_participants: an integer which is the expected number of calls of `wait` pass to through this barrier."""
<|body_0|>
de... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _Barrier:
"""A reusable barrier class for worker synchronization."""
def __init__(self, num_participants):
"""Initializes the barrier object. Args: num_participants: an integer which is the expected number of calls of `wait` pass to through this barrier."""
self._num_participants = num_pa... | the_stack_v2_python_sparse | tensorflow/python/distribute/distribute_coordinator.py | tensorflow/tensorflow | train | 208,740 |
db21eaabc1a1319d1e994172a07e5587c1c0cb48 | [
"yield mlist.posting_address\nfor destination in sorted(SUBDESTINATIONS):\n yield '{}-{}@{}'.format(mlist.list_name, destination, mlist.mail_host)",
"yield mlist.list_name\nfor destination in sorted(SUBDESTINATIONS):\n yield '{}-{}'.format(mlist.list_name, destination)"
] | <|body_start_0|>
yield mlist.posting_address
for destination in sorted(SUBDESTINATIONS):
yield '{}-{}@{}'.format(mlist.list_name, destination, mlist.mail_host)
<|end_body_0|>
<|body_start_1|>
yield mlist.list_name
for destination in sorted(SUBDESTINATIONS):
yield... | Utility for generating all the aliases of a mailing list. | MailTransportAgentAliases | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MailTransportAgentAliases:
"""Utility for generating all the aliases of a mailing list."""
def aliases(self, mlist):
"""See `IMailTransportAgentAliases`."""
<|body_0|>
def destinations(self, mlist):
"""See `IMailTransportAgentAliases`."""
<|body_1|>
<|en... | stack_v2_sparse_classes_10k_train_001597 | 1,771 | no_license | [
{
"docstring": "See `IMailTransportAgentAliases`.",
"name": "aliases",
"signature": "def aliases(self, mlist)"
},
{
"docstring": "See `IMailTransportAgentAliases`.",
"name": "destinations",
"signature": "def destinations(self, mlist)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002333 | Implement the Python class `MailTransportAgentAliases` described below.
Class description:
Utility for generating all the aliases of a mailing list.
Method signatures and docstrings:
- def aliases(self, mlist): See `IMailTransportAgentAliases`.
- def destinations(self, mlist): See `IMailTransportAgentAliases`. | Implement the Python class `MailTransportAgentAliases` described below.
Class description:
Utility for generating all the aliases of a mailing list.
Method signatures and docstrings:
- def aliases(self, mlist): See `IMailTransportAgentAliases`.
- def destinations(self, mlist): See `IMailTransportAgentAliases`.
<|ske... | 7edf8148e34b9f73ca6433ceb43a1770f4fa32c1 | <|skeleton|>
class MailTransportAgentAliases:
"""Utility for generating all the aliases of a mailing list."""
def aliases(self, mlist):
"""See `IMailTransportAgentAliases`."""
<|body_0|>
def destinations(self, mlist):
"""See `IMailTransportAgentAliases`."""
<|body_1|>
<|en... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MailTransportAgentAliases:
"""Utility for generating all the aliases of a mailing list."""
def aliases(self, mlist):
"""See `IMailTransportAgentAliases`."""
yield mlist.posting_address
for destination in sorted(SUBDESTINATIONS):
yield '{}-{}@{}'.format(mlist.list_name,... | the_stack_v2_python_sparse | libs/Mailman/mailman/mta/aliases.py | masomel/py-import-analysis | train | 1 |
f7b5d7eaa64b76249b580d82a7e821f923b2a2a2 | [
"lesson = Lessons.query.filter_by(id=self.lesson.data).first()\nacademy = Academy.query.filter_by(name=self.academy.data).first()\nstudent = Student.query.filter_by(academy_id=academy.id).filter_by(name=self.name.data).first()\nif student is not None:\n raise ValidationError('Student name is already in the syste... | <|body_start_0|>
lesson = Lessons.query.filter_by(id=self.lesson.data).first()
academy = Academy.query.filter_by(name=self.academy.data).first()
student = Student.query.filter_by(academy_id=academy.id).filter_by(name=self.name.data).first()
if student is not None:
raise Valid... | Form for getting initial student data | CreateStudentForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateStudentForm:
"""Form for getting initial student data"""
def validate_name(self, name):
"""Validate name has yet to be used within the academy"""
<|body_0|>
def validate_phone2(self, phone):
"""Validate phone is unique"""
<|body_1|>
def validat... | stack_v2_sparse_classes_10k_train_001598 | 19,666 | no_license | [
{
"docstring": "Validate name has yet to be used within the academy",
"name": "validate_name",
"signature": "def validate_name(self, name)"
},
{
"docstring": "Validate phone is unique",
"name": "validate_phone2",
"signature": "def validate_phone2(self, phone)"
},
{
"docstring": "... | 4 | stack_v2_sparse_classes_30k_train_006710 | Implement the Python class `CreateStudentForm` described below.
Class description:
Form for getting initial student data
Method signatures and docstrings:
- def validate_name(self, name): Validate name has yet to be used within the academy
- def validate_phone2(self, phone): Validate phone is unique
- def validate_ph... | Implement the Python class `CreateStudentForm` described below.
Class description:
Form for getting initial student data
Method signatures and docstrings:
- def validate_name(self, name): Validate name has yet to be used within the academy
- def validate_phone2(self, phone): Validate phone is unique
- def validate_ph... | e2404fef23258448764aaf9fabb36b6575ddf163 | <|skeleton|>
class CreateStudentForm:
"""Form for getting initial student data"""
def validate_name(self, name):
"""Validate name has yet to be used within the academy"""
<|body_0|>
def validate_phone2(self, phone):
"""Validate phone is unique"""
<|body_1|>
def validat... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CreateStudentForm:
"""Form for getting initial student data"""
def validate_name(self, name):
"""Validate name has yet to be used within the academy"""
lesson = Lessons.query.filter_by(id=self.lesson.data).first()
academy = Academy.query.filter_by(name=self.academy.data).first()
... | the_stack_v2_python_sparse | app/students/forms.py | Kwsswart/Academy | train | 0 |
dae1b4088ca26ece70dbd91d20a5d5f63fec1c5a | [
"Platform.__init__(self, pos=route[0][:], size=size)\nself._route = route\nself._flying_type = flying_type\nif flying_type == MovingPlatform.LINE:\n self._forward = True\nself._next_point = 1\nself._vector = (Vector2(route[1]) - Vector2(route[0])).normal()",
"vector = self._vector * MovingPlatform.SPEED\nself.... | <|body_start_0|>
Platform.__init__(self, pos=route[0][:], size=size)
self._route = route
self._flying_type = flying_type
if flying_type == MovingPlatform.LINE:
self._forward = True
self._next_point = 1
self._vector = (Vector2(route[1]) - Vector2(route[0])).nor... | The moving platform class. An instance of this class represents a moving platform of a level. Attributes: _route: The rout of this moving platform. _flying_type: The flying type of the moving platform. _forward: This optional flag, used for the LINE type, determines if the moving platform moves forward or backward in t... | MovingPlatform | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingPlatform:
"""The moving platform class. An instance of this class represents a moving platform of a level. Attributes: _route: The rout of this moving platform. _flying_type: The flying type of the moving platform. _forward: This optional flag, used for the LINE type, determines if the movi... | stack_v2_sparse_classes_10k_train_001599 | 4,212 | no_license | [
{
"docstring": "Generates a new instance of this class. Generates a new instance of this class and sets the field information. Args: size: The size of the moving platform. route: The route the moving platform. flying_type: The flying type of the moving platform.",
"name": "__init__",
"signature": "def _... | 2 | stack_v2_sparse_classes_30k_train_002357 | Implement the Python class `MovingPlatform` described below.
Class description:
The moving platform class. An instance of this class represents a moving platform of a level. Attributes: _route: The rout of this moving platform. _flying_type: The flying type of the moving platform. _forward: This optional flag, used fo... | Implement the Python class `MovingPlatform` described below.
Class description:
The moving platform class. An instance of this class represents a moving platform of a level. Attributes: _route: The rout of this moving platform. _flying_type: The flying type of the moving platform. _forward: This optional flag, used fo... | 0308785a51bf61d9a4fec2d8370540df502b8178 | <|skeleton|>
class MovingPlatform:
"""The moving platform class. An instance of this class represents a moving platform of a level. Attributes: _route: The rout of this moving platform. _flying_type: The flying type of the moving platform. _forward: This optional flag, used for the LINE type, determines if the movi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MovingPlatform:
"""The moving platform class. An instance of this class represents a moving platform of a level. Attributes: _route: The rout of this moving platform. _flying_type: The flying type of the moving platform. _forward: This optional flag, used for the LINE type, determines if the moving platform m... | the_stack_v2_python_sparse | game_objects/platform.py | donhilion/JumpAndRun | train | 0 |
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