blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3a005c5ad54df10eb57e4795d2ce367a16971efb | [
"self.mode = mode\nself.detection_timeout = detection_timeout\nself.silence_timeout = silence_timeout\nself.speech_threshold = speech_threshold\nself.speech_end_threshold = speech_end_threshold\nself.machine_speech_end_threshold = machine_speech_end_threshold\nself.delay_result = delay_result\nself.callback_url = c... | <|body_start_0|>
self.mode = mode
self.detection_timeout = detection_timeout
self.silence_timeout = silence_timeout
self.speech_threshold = speech_threshold
self.speech_end_threshold = speech_end_threshold
self.machine_speech_end_threshold = machine_speech_end_threshold
... | Implementation of the 'MachineDetectionRequest' model. TODO: type model description here. Attributes: mode (ModeEnum): The machine detection mode. If set to 'async', the detection result will be sent in a 'machineDetectionComplete' callback. If set to 'sync', the 'answer' callback will wait for the machine detection to... | MachineDetectionConfiguration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MachineDetectionConfiguration:
"""Implementation of the 'MachineDetectionRequest' model. TODO: type model description here. Attributes: mode (ModeEnum): The machine detection mode. If set to 'async', the detection result will be sent in a 'machineDetectionComplete' callback. If set to 'sync', the... | stack_v2_sparse_classes_36k_train_012100 | 6,854 | permissive | [
{
"docstring": "Constructor for the MachineDetectionRequest class",
"name": "__init__",
"signature": "def __init__(self, mode=None, detection_timeout=None, silence_timeout=None, speech_threshold=None, speech_end_threshold=None, machine_speech_end_threshold=None, delay_result=None, callback_url=None, cal... | 2 | null | Implement the Python class `MachineDetectionConfiguration` described below.
Class description:
Implementation of the 'MachineDetectionRequest' model. TODO: type model description here. Attributes: mode (ModeEnum): The machine detection mode. If set to 'async', the detection result will be sent in a 'machineDetectionCo... | Implement the Python class `MachineDetectionConfiguration` described below.
Class description:
Implementation of the 'MachineDetectionRequest' model. TODO: type model description here. Attributes: mode (ModeEnum): The machine detection mode. If set to 'async', the detection result will be sent in a 'machineDetectionCo... | 447df3cc8cb7acaf3361d842630c432a9c31ce6e | <|skeleton|>
class MachineDetectionConfiguration:
"""Implementation of the 'MachineDetectionRequest' model. TODO: type model description here. Attributes: mode (ModeEnum): The machine detection mode. If set to 'async', the detection result will be sent in a 'machineDetectionComplete' callback. If set to 'sync', the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MachineDetectionConfiguration:
"""Implementation of the 'MachineDetectionRequest' model. TODO: type model description here. Attributes: mode (ModeEnum): The machine detection mode. If set to 'async', the detection result will be sent in a 'machineDetectionComplete' callback. If set to 'sync', the 'answer' cal... | the_stack_v2_python_sparse | bandwidth/voice/models/machine_detection_configuration.py | Bandwidth/python-sdk | train | 10 |
0dfeae045626a29e4454ec233aa351bfded982de | [
"check_classification_targets(y)\nlab_enc = LabelEncoder()\nenc_y = lab_enc.fit_transform(y).astype(np.float64, copy=False)\nself.classes_ = lab_enc.classes_\nif self.classes_.shape[0] != self.num_classes:\n raise ValueError('Number of classes defined in configuration file and the classes derived from the data d... | <|body_start_0|>
check_classification_targets(y)
lab_enc = LabelEncoder()
enc_y = lab_enc.fit_transform(y).astype(np.float64, copy=False)
self.classes_ = lab_enc.classes_
if self.classes_.shape[0] != self.num_classes:
raise ValueError('Number of classes defined in con... | XGBClassifierFLModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XGBClassifierFLModel:
def encode_target(self, y):
"""Converts the input y to the expected dtype and performs a label encoding. Here, we assume that each party has at least one sample of the corresponding class label type for each different classes. :param y: The corresponding target data... | stack_v2_sparse_classes_36k_train_012101 | 17,389 | no_license | [
{
"docstring": "Converts the input y to the expected dtype and performs a label encoding. Here, we assume that each party has at least one sample of the corresponding class label type for each different classes. :param y: The corresponding target data from the dataset to encode. :type y: `np.array` :return y: R... | 5 | stack_v2_sparse_classes_30k_train_020126 | Implement the Python class `XGBClassifierFLModel` described below.
Class description:
Implement the XGBClassifierFLModel class.
Method signatures and docstrings:
- def encode_target(self, y): Converts the input y to the expected dtype and performs a label encoding. Here, we assume that each party has at least one sam... | Implement the Python class `XGBClassifierFLModel` described below.
Class description:
Implement the XGBClassifierFLModel class.
Method signatures and docstrings:
- def encode_target(self, y): Converts the input y to the expected dtype and performs a label encoding. Here, we assume that each party has at least one sam... | a4cd429484e857b849df08d93688d35e632b3e29 | <|skeleton|>
class XGBClassifierFLModel:
def encode_target(self, y):
"""Converts the input y to the expected dtype and performs a label encoding. Here, we assume that each party has at least one sample of the corresponding class label type for each different classes. :param y: The corresponding target data... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XGBClassifierFLModel:
def encode_target(self, y):
"""Converts the input y to the expected dtype and performs a label encoding. Here, we assume that each party has at least one sample of the corresponding class label type for each different classes. :param y: The corresponding target data from the data... | the_stack_v2_python_sparse | venv/Lib/site-packages/ibmfl/model/xgb_fl_model.py | yusufcet/healty-hearts | train | 0 | |
8d6a1029cf5e4f9797ad21c8afc18b99c3dc36a5 | [
"self.path = path\nself.name = os.path.basename(path)\nself.detector_path, self.description = self.get_data()",
"detector_path = None\ndescription = ''\nfor name in os.listdir(self.path):\n suffix = pathlib.Path(os.path.join(self.path, name)).suffix\n prefix = pathlib.Path(os.path.join(self.path, name)).ste... | <|body_start_0|>
self.path = path
self.name = os.path.basename(path)
self.detector_path, self.description = self.get_data()
<|end_body_0|>
<|body_start_1|>
detector_path = None
description = ''
for name in os.listdir(self.path):
suffix = pathlib.Path(os.path.... | This class holds the data and path of the event detector. | EventDetector | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventDetector:
"""This class holds the data and path of the event detector."""
def __init__(self, path):
""":param path: the inserted path of the event detector."""
<|body_0|>
def get_data(self):
""":return: the file path, a sample image and a description of the ... | stack_v2_sparse_classes_36k_train_012102 | 1,161 | permissive | [
{
"docstring": ":param path: the inserted path of the event detector.",
"name": "__init__",
"signature": "def __init__(self, path)"
},
{
"docstring": ":return: the file path, a sample image and a description of the event detector.",
"name": "get_data",
"signature": "def get_data(self)"
... | 2 | stack_v2_sparse_classes_30k_train_000192 | Implement the Python class `EventDetector` described below.
Class description:
This class holds the data and path of the event detector.
Method signatures and docstrings:
- def __init__(self, path): :param path: the inserted path of the event detector.
- def get_data(self): :return: the file path, a sample image and ... | Implement the Python class `EventDetector` described below.
Class description:
This class holds the data and path of the event detector.
Method signatures and docstrings:
- def __init__(self, path): :param path: the inserted path of the event detector.
- def get_data(self): :return: the file path, a sample image and ... | 8d03f5f7c85ccc113a0561c58b7e3bf76e888f03 | <|skeleton|>
class EventDetector:
"""This class holds the data and path of the event detector."""
def __init__(self, path):
""":param path: the inserted path of the event detector."""
<|body_0|>
def get_data(self):
""":return: the file path, a sample image and a description of the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EventDetector:
"""This class holds the data and path of the event detector."""
def __init__(self, path):
""":param path: the inserted path of the event detector."""
self.path = path
self.name = os.path.basename(path)
self.detector_path, self.description = self.get_data()
... | the_stack_v2_python_sparse | entities/event_detector.py | biktokle/Automated-Microscope | train | 0 |
30147ad08d1449da20967b35b58fb82ef743d49f | [
"_AgentBase.__init__(self, reactor, pool)\nendpoint_factory = ReplicationEndpointFactory(reactor, instance_map, contextFactory)\nself._endpointFactory = endpoint_factory",
"parsedURI = URI.fromBytes(uri)\ntry:\n endpoint = self._endpointFactory.endpointForURI(parsedURI)\nexcept SchemeNotSupported:\n return ... | <|body_start_0|>
_AgentBase.__init__(self, reactor, pool)
endpoint_factory = ReplicationEndpointFactory(reactor, instance_map, contextFactory)
self._endpointFactory = endpoint_factory
<|end_body_0|>
<|body_start_1|>
parsedURI = URI.fromBytes(uri)
try:
endpoint = self... | Client for connecting to replication endpoints via HTTP and HTTPS. Much of this code is copied from Twisted's twisted.web.client.Agent. | ReplicationAgent | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReplicationAgent:
"""Client for connecting to replication endpoints via HTTP and HTTPS. Much of this code is copied from Twisted's twisted.web.client.Agent."""
def __init__(self, reactor: ISynapseReactor, instance_map: Dict[str, InstanceLocationConfig], contextFactory: IPolicyForHTTPS, conne... | stack_v2_sparse_classes_36k_train_012103 | 6,722 | permissive | [
{
"docstring": "Create a ReplicationAgent. Args: reactor: A reactor for this Agent to place outgoing connections. contextFactory: A factory for TLS contexts, to control the verification parameters of OpenSSL. The default is to use a BrowserLikePolicyForHTTPS, so unless you have special requirements you can leav... | 2 | stack_v2_sparse_classes_30k_train_014205 | Implement the Python class `ReplicationAgent` described below.
Class description:
Client for connecting to replication endpoints via HTTP and HTTPS. Much of this code is copied from Twisted's twisted.web.client.Agent.
Method signatures and docstrings:
- def __init__(self, reactor: ISynapseReactor, instance_map: Dict[... | Implement the Python class `ReplicationAgent` described below.
Class description:
Client for connecting to replication endpoints via HTTP and HTTPS. Much of this code is copied from Twisted's twisted.web.client.Agent.
Method signatures and docstrings:
- def __init__(self, reactor: ISynapseReactor, instance_map: Dict[... | d35bed8369514fe727b4fe1afb68f48cc8b2655a | <|skeleton|>
class ReplicationAgent:
"""Client for connecting to replication endpoints via HTTP and HTTPS. Much of this code is copied from Twisted's twisted.web.client.Agent."""
def __init__(self, reactor: ISynapseReactor, instance_map: Dict[str, InstanceLocationConfig], contextFactory: IPolicyForHTTPS, conne... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReplicationAgent:
"""Client for connecting to replication endpoints via HTTP and HTTPS. Much of this code is copied from Twisted's twisted.web.client.Agent."""
def __init__(self, reactor: ISynapseReactor, instance_map: Dict[str, InstanceLocationConfig], contextFactory: IPolicyForHTTPS, connectTimeout: Op... | the_stack_v2_python_sparse | synapse/http/replicationagent.py | matrix-org/synapse | train | 12,215 |
1c33403e20decec3471fab228037b980e1532ad2 | [
"if InChannel != growRate:\n self.InConv = op.Conv2d(in_channels=InChannel, out_channels=growRate, kernel_size=1, stride=1, padding=0)\n self.make_conv(nConvLayers, growRate, OutChannel)\nelse:\n self.make_conv(nConvLayers, growRate, OutChannel)",
"convs = []\nfor c in range(nConvLayers):\n conv = Blo... | <|body_start_0|>
if InChannel != growRate:
self.InConv = op.Conv2d(in_channels=InChannel, out_channels=growRate, kernel_size=1, stride=1, padding=0)
self.make_conv(nConvLayers, growRate, OutChannel)
else:
self.make_conv(nConvLayers, growRate, OutChannel)
<|end_body_0|... | Create InConv_Group SearchSpace. | InConv_Group | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InConv_Group:
"""Create InConv_Group SearchSpace."""
def constructor(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3):
"""Create InConv_Group Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel... | stack_v2_sparse_classes_36k_train_012104 | 16,263 | permissive | [
{
"docstring": "Create InConv_Group Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel: int :param growRate: growth rate of block :type growRate: int :param nConvLayers: the number of convlution layer :type nConvLayers: int :param k... | 2 | null | Implement the Python class `InConv_Group` described below.
Class description:
Create InConv_Group SearchSpace.
Method signatures and docstrings:
- def constructor(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3): Create InConv_Group Block. :param InChannel: channel number of input :type InChannel: int :pa... | Implement the Python class `InConv_Group` described below.
Class description:
Create InConv_Group SearchSpace.
Method signatures and docstrings:
- def constructor(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3): Create InConv_Group Block. :param InChannel: channel number of input :type InChannel: int :pa... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class InConv_Group:
"""Create InConv_Group SearchSpace."""
def constructor(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3):
"""Create InConv_Group Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InConv_Group:
"""Create InConv_Group SearchSpace."""
def constructor(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3):
"""Create InConv_Group Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel: int :param ... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/cv/image_classification/Cars_for_TensorFlow/automl/vega/search_space/fine_grained_space/blocks/sr.py | Huawei-Ascend/modelzoo | train | 1 |
a853f6c0349144676faabd315be16355aeb06b4a | [
"i, count = (0, 1)\nl = len(nums)\nwhile i < l:\n num = nums[i]\n if 1 <= num < l and nums[num - 1] != nums[i]:\n nums[num - 1], nums[i] = (nums[i], nums[num - 1])\n else:\n i += 1\n while count - 1 < l and nums[count - 1] == count:\n count += 1\nreturn count",
"n = len(nu... | <|body_start_0|>
i, count = (0, 1)
l = len(nums)
while i < l:
num = nums[i]
if 1 <= num < l and nums[num - 1] != nums[i]:
nums[num - 1], nums[i] = (nums[i], nums[num - 1])
else:
i += 1
while count - 1 < l and num... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def firstMissingPositive_solution_1(self, nums: List[int]) -> int:
""":type nums: List[int] :rtype: int Basic idea: 1. for any array whose length is l, the first missing positive must be in range [1,...,l+1], so we only have to care about those elements in this range and remove... | stack_v2_sparse_classes_36k_train_012105 | 9,733 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int Basic idea: 1. for any array whose length is l, the first missing positive must be in range [1,...,l+1], so we only have to care about those elements in this range and remove the rest. 2. we can use the array index as the hash to restore the frequency of each nu... | 3 | stack_v2_sparse_classes_30k_train_017576 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstMissingPositive_solution_1(self, nums: List[int]) -> int: :type nums: List[int] :rtype: int Basic idea: 1. for any array whose length is l, the first missing positive mu... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstMissingPositive_solution_1(self, nums: List[int]) -> int: :type nums: List[int] :rtype: int Basic idea: 1. for any array whose length is l, the first missing positive mu... | f2621cd76822a922c49b60f32931f26cce1c571d | <|skeleton|>
class Solution:
def firstMissingPositive_solution_1(self, nums: List[int]) -> int:
""":type nums: List[int] :rtype: int Basic idea: 1. for any array whose length is l, the first missing positive must be in range [1,...,l+1], so we only have to care about those elements in this range and remove... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def firstMissingPositive_solution_1(self, nums: List[int]) -> int:
""":type nums: List[int] :rtype: int Basic idea: 1. for any array whose length is l, the first missing positive must be in range [1,...,l+1], so we only have to care about those elements in this range and remove the rest. 2. ... | the_stack_v2_python_sparse | Arrays/032_leetcode_P_041_FirstMissingPositive/Solution.py | Keshav1506/competitive_programming | train | 0 | |
94c4848ee9abfedf54b9bc281ac420e9cabe4e93 | [
"zero = 0\nfor i, n in enumerate(nums):\n if n == 0:\n continue\n nums[zero], nums[i] = (nums[i], nums[zero])\n zero += 1",
"snowball_size = 0\nfor i, n in enumerate(nums):\n if n == 0:\n snowball_size += 1\n else:\n nums[i], nums[i - snowball_size] = (0, n)"
] | <|body_start_0|>
zero = 0
for i, n in enumerate(nums):
if n == 0:
continue
nums[zero], nums[i] = (nums[i], nums[zero])
zero += 1
<|end_body_0|>
<|body_start_1|>
snowball_size = 0
for i, n in enumerate(nums):
if n == 0:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def move_zeroes(self, nums):
""":type nums: List[int] :rtyp"""
<|body_0|>
def move_zeroes_by_snowball(self, nums):
"""雪球计数 数值为 0 时，雪球数量加 1；数值不为 0 时，将当前位置的值赋值给第一个雪球位置, 当前位置赋值为 0"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
zero = 0
... | stack_v2_sparse_classes_36k_train_012106 | 1,055 | no_license | [
{
"docstring": ":type nums: List[int] :rtyp",
"name": "move_zeroes",
"signature": "def move_zeroes(self, nums)"
},
{
"docstring": "雪球计数 数值为 0 时，雪球数量加 1；数值不为 0 时，将当前位置的值赋值给第一个雪球位置, 当前位置赋值为 0",
"name": "move_zeroes_by_snowball",
"signature": "def move_zeroes_by_snowball(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def move_zeroes(self, nums): :type nums: List[int] :rtyp
- def move_zeroes_by_snowball(self, nums): 雪球计数 数值为 0 时，雪球数量加 1；数值不为 0 时，将当前位置的值赋值给第一个雪球位置, 当前位置赋值为 0 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def move_zeroes(self, nums): :type nums: List[int] :rtyp
- def move_zeroes_by_snowball(self, nums): 雪球计数 数值为 0 时，雪球数量加 1；数值不为 0 时，将当前位置的值赋值给第一个雪球位置, 当前位置赋值为 0
<|skeleton|>
class... | 2b7f4a9fefbfd358f8ff31362d60e2007641ca29 | <|skeleton|>
class Solution:
def move_zeroes(self, nums):
""":type nums: List[int] :rtyp"""
<|body_0|>
def move_zeroes_by_snowball(self, nums):
"""雪球计数 数值为 0 时，雪球数量加 1；数值不为 0 时，将当前位置的值赋值给第一个雪球位置, 当前位置赋值为 0"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def move_zeroes(self, nums):
""":type nums: List[int] :rtyp"""
zero = 0
for i, n in enumerate(nums):
if n == 0:
continue
nums[zero], nums[i] = (nums[i], nums[zero])
zero += 1
def move_zeroes_by_snowball(self, nums):
... | the_stack_v2_python_sparse | Week_01/G20190343020166/LeetCode_283_0166.py | algorithm005-class01/algorithm005-class01 | train | 27 | |
6a2daec0823f97ea5e6b50cf3e544791ff3d8998 | [
"if target in nums:\n return nums.index(target)\nelse:\n for i in range(len(nums)):\n if nums[i] > target:\n return i\nreturn len(nums)",
"left, right = (0, len(nums) - 1)\nif nums[right] < target:\n return len(nums)\nelse:\n while left <= right:\n mid = (left + right) // 2\n ... | <|body_start_0|>
if target in nums:
return nums.index(target)
else:
for i in range(len(nums)):
if nums[i] > target:
return i
return len(nums)
<|end_body_0|>
<|body_start_1|>
left, right = (0, len(nums) - 1)
if nums[righ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchInsert(self, nums, target):
"""常规版本"""
<|body_0|>
def searchInsert2(self, nums, target):
"""二分搜索版本"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if target in nums:
return nums.index(target)
else:
... | stack_v2_sparse_classes_36k_train_012107 | 899 | no_license | [
{
"docstring": "常规版本",
"name": "searchInsert",
"signature": "def searchInsert(self, nums, target)"
},
{
"docstring": "二分搜索版本",
"name": "searchInsert2",
"signature": "def searchInsert2(self, nums, target)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008177 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsert(self, nums, target): 常规版本
- def searchInsert2(self, nums, target): 二分搜索版本 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsert(self, nums, target): 常规版本
- def searchInsert2(self, nums, target): 二分搜索版本
<|skeleton|>
class Solution:
def searchInsert(self, nums, target):
"""常规版... | 04810f2603ef6e4e5627ab64a5d4cd8678d429ac | <|skeleton|>
class Solution:
def searchInsert(self, nums, target):
"""常规版本"""
<|body_0|>
def searchInsert2(self, nums, target):
"""二分搜索版本"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def searchInsert(self, nums, target):
"""常规版本"""
if target in nums:
return nums.index(target)
else:
for i in range(len(nums)):
if nums[i] > target:
return i
return len(nums)
def searchInsert2(self, nums,... | the_stack_v2_python_sparse | leetcode/35_ 搜索插入位置.py | Rsj-Python/project | train | 0 | |
12a34f6fcb6b0bd7d129ceff3f8d3d5c170484a8 | [
"super(VolumeStagingWorkflow, self).__init__(__name__, **opts)\nself.workflow = self._create_workflow()\n'\\n The staging workflow sequence described in\\n :class:`qipipe.pipeline.staging.StagingWorkflow`.\\n '",
"input_spec = self.workflow.get_node('input_spec')\ninput_spec.inputs.collection... | <|body_start_0|>
super(VolumeStagingWorkflow, self).__init__(__name__, **opts)
self.workflow = self._create_workflow()
'\n The staging workflow sequence described in\n :class:`qipipe.pipeline.staging.StagingWorkflow`.\n '
<|end_body_0|>
<|body_start_1|>
input_spec =... | The StagingWorkflow class builds and executes the staging Nipype workflow. The staging workflow includes the following steps: - Group the input DICOM images into volume. - Fix each input DICOM file header using the :class:`qipipe.interfaces.fix_dicom.FixDicom` interface. - Compress each corrected DICOM file. - Upload e... | VolumeStagingWorkflow | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VolumeStagingWorkflow:
"""The StagingWorkflow class builds and executes the staging Nipype workflow. The staging workflow includes the following steps: - Group the input DICOM images into volume. - Fix each input DICOM file header using the :class:`qipipe.interfaces.fix_dicom.FixDicom` interface.... | stack_v2_sparse_classes_36k_train_012108 | 26,347 | permissive | [
{
"docstring": "If the optional configuration file is specified, then the workflow settings in that file override the default settings. :param opts: the :class:`qipipe.pipeline.workflow_base.WorkflowBase` initializer keyword arguments",
"name": "__init__",
"signature": "def __init__(self, **opts)"
},
... | 3 | stack_v2_sparse_classes_30k_train_019387 | Implement the Python class `VolumeStagingWorkflow` described below.
Class description:
The StagingWorkflow class builds and executes the staging Nipype workflow. The staging workflow includes the following steps: - Group the input DICOM images into volume. - Fix each input DICOM file header using the :class:`qipipe.in... | Implement the Python class `VolumeStagingWorkflow` described below.
Class description:
The StagingWorkflow class builds and executes the staging Nipype workflow. The staging workflow includes the following steps: - Group the input DICOM images into volume. - Fix each input DICOM file header using the :class:`qipipe.in... | 5c468bb5e53f87bf280b0abcd4b5321068a27cc3 | <|skeleton|>
class VolumeStagingWorkflow:
"""The StagingWorkflow class builds and executes the staging Nipype workflow. The staging workflow includes the following steps: - Group the input DICOM images into volume. - Fix each input DICOM file header using the :class:`qipipe.interfaces.fix_dicom.FixDicom` interface.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VolumeStagingWorkflow:
"""The StagingWorkflow class builds and executes the staging Nipype workflow. The staging workflow includes the following steps: - Group the input DICOM images into volume. - Fix each input DICOM file header using the :class:`qipipe.interfaces.fix_dicom.FixDicom` interface. - Compress e... | the_stack_v2_python_sparse | qipipe/pipeline/staging.py | ohsu-qin/qipipe | train | 0 |
c051275ca47b9101d783269539d6b03c1b6b7a11 | [
"end = res = 0\nwhile end < T:\n tmp = max([r for l, r in clips if l <= end] or [0])\n if tmp == end:\n return -1\n end = tmp\n res += 1\nreturn res",
"T += 1\ndp = [-1] * T\ndp[0] = 0\nclips = sorted(clips, key=lambda a: a[0])\nfor c in clips:\n if c[0] >= T:\n break\n if dp[c[0]]... | <|body_start_0|>
end = res = 0
while end < T:
tmp = max([r for l, r in clips if l <= end] or [0])
if tmp == end:
return -1
end = tmp
res += 1
return res
<|end_body_0|>
<|body_start_1|>
T += 1
dp = [-1] * T
d... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def videoStitching(self, clips, T):
""":type clips: List[List[int]] :type T: int :rtype: int"""
<|body_0|>
def videoStitching2(self, clips, T):
""":type clips: List[List[int]] :type T: int :rtype: int"""
<|body_1|>
def videoStitching3(self, cli... | stack_v2_sparse_classes_36k_train_012109 | 3,920 | no_license | [
{
"docstring": ":type clips: List[List[int]] :type T: int :rtype: int",
"name": "videoStitching",
"signature": "def videoStitching(self, clips, T)"
},
{
"docstring": ":type clips: List[List[int]] :type T: int :rtype: int",
"name": "videoStitching2",
"signature": "def videoStitching2(self... | 4 | stack_v2_sparse_classes_30k_train_008228 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def videoStitching(self, clips, T): :type clips: List[List[int]] :type T: int :rtype: int
- def videoStitching2(self, clips, T): :type clips: List[List[int]] :type T: int :rtype:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def videoStitching(self, clips, T): :type clips: List[List[int]] :type T: int :rtype: int
- def videoStitching2(self, clips, T): :type clips: List[List[int]] :type T: int :rtype:... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def videoStitching(self, clips, T):
""":type clips: List[List[int]] :type T: int :rtype: int"""
<|body_0|>
def videoStitching2(self, clips, T):
""":type clips: List[List[int]] :type T: int :rtype: int"""
<|body_1|>
def videoStitching3(self, cli... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def videoStitching(self, clips, T):
""":type clips: List[List[int]] :type T: int :rtype: int"""
end = res = 0
while end < T:
tmp = max([r for l, r in clips if l <= end] or [0])
if tmp == end:
return -1
end = tmp
... | the_stack_v2_python_sparse | 1024_视频拼接.py | lovehhf/LeetCode | train | 0 | |
1552b956f077527d5298877a4e1597a5e9a78d57 | [
"self.char_map = string.ascii_lowercase\nif key == '':\n key = ''.join((random.choice(self.char_map) for _ in range(100)))\nself.key = key.lower()",
"key = self.key\nwhile len(key) < len(buf):\n key += self.key\nreturn key",
"try:\n ndx_plain = self.char_map.index(plain.lower())\n ndx_key = self.cha... | <|body_start_0|>
self.char_map = string.ascii_lowercase
if key == '':
key = ''.join((random.choice(self.char_map) for _ in range(100)))
self.key = key.lower()
<|end_body_0|>
<|body_start_1|>
key = self.key
while len(key) < len(buf):
key += self.key
... | implement a simple substitution cipher encode/decode mechanism | Cipher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cipher:
"""implement a simple substitution cipher encode/decode mechanism"""
def __init__(self, key=''):
"""init the key, make up a 100char random key if not specified"""
<|body_0|>
def lengthen_key(self, buf):
"""lengthen key to be as long as buffer"""
<... | stack_v2_sparse_classes_36k_train_012110 | 2,060 | no_license | [
{
"docstring": "init the key, make up a 100char random key if not specified",
"name": "__init__",
"signature": "def __init__(self, key='')"
},
{
"docstring": "lengthen key to be as long as buffer",
"name": "lengthen_key",
"signature": "def lengthen_key(self, buf)"
},
{
"docstring... | 6 | null | Implement the Python class `Cipher` described below.
Class description:
implement a simple substitution cipher encode/decode mechanism
Method signatures and docstrings:
- def __init__(self, key=''): init the key, make up a 100char random key if not specified
- def lengthen_key(self, buf): lengthen key to be as long a... | Implement the Python class `Cipher` described below.
Class description:
implement a simple substitution cipher encode/decode mechanism
Method signatures and docstrings:
- def __init__(self, key=''): init the key, make up a 100char random key if not specified
- def lengthen_key(self, buf): lengthen key to be as long a... | be0e2f635a7558f56c61bc0b36c6146b01d1e6e6 | <|skeleton|>
class Cipher:
"""implement a simple substitution cipher encode/decode mechanism"""
def __init__(self, key=''):
"""init the key, make up a 100char random key if not specified"""
<|body_0|>
def lengthen_key(self, buf):
"""lengthen key to be as long as buffer"""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cipher:
"""implement a simple substitution cipher encode/decode mechanism"""
def __init__(self, key=''):
"""init the key, make up a 100char random key if not specified"""
self.char_map = string.ascii_lowercase
if key == '':
key = ''.join((random.choice(self.char_map) f... | the_stack_v2_python_sparse | all_data/exercism_data/python/simple-cipher/7c01cf41b0f24cea85c35bdef068d4ef.py | itsolutionscorp/AutoStyle-Clustering | train | 4 |
bc8a35fbaec6f622cb69d1508c583f4d9349e342 | [
"self.temp_type = temp_type\nself.convert_to = convert_to\nself.temp = temp",
"if self.temp_type == 'C' and self.convert_to == 'F':\n new_temp = self.temp * 9 / 5 + 32\nelif self.temp_type == 'F' and self.convert_to == 'C':\n new_temp = (self.temp - 32) * 5 / 9\nreturn new_temp"
] | <|body_start_0|>
self.temp_type = temp_type
self.convert_to = convert_to
self.temp = temp
<|end_body_0|>
<|body_start_1|>
if self.temp_type == 'C' and self.convert_to == 'F':
new_temp = self.temp * 9 / 5 + 32
elif self.temp_type == 'F' and self.convert_to == 'C':
... | Represents a temperature conversion calculator Attributes: TEMP_SCALES: Constant. Defines the temperatures scales usable by the class CONVERT_SCALES: Constant. Map of value to convert to temp_type: The scale in which the user enters a temperature to convert convert_to: The scale the temperature should be converted to t... | TempConverter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TempConverter:
"""Represents a temperature conversion calculator Attributes: TEMP_SCALES: Constant. Defines the temperatures scales usable by the class CONVERT_SCALES: Constant. Map of value to convert to temp_type: The scale in which the user enters a temperature to convert convert_to: The scale... | stack_v2_sparse_classes_36k_train_012111 | 2,431 | no_license | [
{
"docstring": "Initializes the class",
"name": "__init__",
"signature": "def __init__(self, temp_type=None, convert_to=None, temp=None)"
},
{
"docstring": "Converts from one temperature scale to another The formulas to convert from Celsius (C) to Fahrenheit (F) and vice versa are shown below: C... | 2 | null | Implement the Python class `TempConverter` described below.
Class description:
Represents a temperature conversion calculator Attributes: TEMP_SCALES: Constant. Defines the temperatures scales usable by the class CONVERT_SCALES: Constant. Map of value to convert to temp_type: The scale in which the user enters a tempe... | Implement the Python class `TempConverter` described below.
Class description:
Represents a temperature conversion calculator Attributes: TEMP_SCALES: Constant. Defines the temperatures scales usable by the class CONVERT_SCALES: Constant. Map of value to convert to temp_type: The scale in which the user enters a tempe... | 218894fbad8ac3389003ce7321fd4c4020239fd6 | <|skeleton|>
class TempConverter:
"""Represents a temperature conversion calculator Attributes: TEMP_SCALES: Constant. Defines the temperatures scales usable by the class CONVERT_SCALES: Constant. Map of value to convert to temp_type: The scale in which the user enters a temperature to convert convert_to: The scale... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TempConverter:
"""Represents a temperature conversion calculator Attributes: TEMP_SCALES: Constant. Defines the temperatures scales usable by the class CONVERT_SCALES: Constant. Map of value to convert to temp_type: The scale in which the user enters a temperature to convert convert_to: The scale the temperat... | the_stack_v2_python_sparse | challenges/c18_TemperatureConverter/temp_convert/temp_convert.py | andrew-rietz/FiftySeven_Coding_Challenges | train | 0 |
a226ac26d353ffc140c0d5c0e6f4f124ba8fb790 | [
"self.ax_kw.update(kwargs)\nDynaPlotBackTest.__init__(self, fig=fig, ax=ax, size=size, **self.ax_kw)\nself.set_axes()\nself.ax2 = self.ax.twinx()",
"if clear:\n self.clear()\n self.ax2.clear()\nself.h_test = self.ax.plot(test, **self.test_plot_kw)\nself.h_eval = self.ax2.plot(eval, **self.eval_plot_kw)\nsel... | <|body_start_0|>
self.ax_kw.update(kwargs)
DynaPlotBackTest.__init__(self, fig=fig, ax=ax, size=size, **self.ax_kw)
self.set_axes()
self.ax2 = self.ax.twinx()
<|end_body_0|>
<|body_start_1|>
if clear:
self.clear()
self.ax2.clear()
self.h_test = se... | Plot dynamically the performance values. Attributes ---------- fig : matplotlib.figure.Figure Figure to display backtest. ax : matplotlib.axes Axe(s) to display a part of backtest. ax_kwargs : dict Parameters of matplotlib axes containing title, ylabel, xlabel, yscale, xscale and ticks_params. Methods ------- plot set_... | DynaPlotPerf | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DynaPlotPerf:
"""Plot dynamically the performance values. Attributes ---------- fig : matplotlib.figure.Figure Figure to display backtest. ax : matplotlib.axes Axe(s) to display a part of backtest. ax_kwargs : dict Parameters of matplotlib axes containing title, ylabel, xlabel, yscale, xscale and... | stack_v2_sparse_classes_36k_train_012112 | 21,693 | permissive | [
{
"docstring": "Initialize method. Parameters ---------- fig : matplotlib.figure.Figure, optional Figure to display backtest. ax : matplotlib.axes, optional Axe(s) to display a part of backtest. size : tuple, optional Size of figure, default is (9, 6) kwargs : dict, optional Axes configuration, cf matplotlib do... | 3 | stack_v2_sparse_classes_30k_train_015282 | Implement the Python class `DynaPlotPerf` described below.
Class description:
Plot dynamically the performance values. Attributes ---------- fig : matplotlib.figure.Figure Figure to display backtest. ax : matplotlib.axes Axe(s) to display a part of backtest. ax_kwargs : dict Parameters of matplotlib axes containing ti... | Implement the Python class `DynaPlotPerf` described below.
Class description:
Plot dynamically the performance values. Attributes ---------- fig : matplotlib.figure.Figure Figure to display backtest. ax : matplotlib.axes Axe(s) to display a part of backtest. ax_kwargs : dict Parameters of matplotlib axes containing ti... | b7e9bfce52fc5d732f340348945bde3b514f5a3a | <|skeleton|>
class DynaPlotPerf:
"""Plot dynamically the performance values. Attributes ---------- fig : matplotlib.figure.Figure Figure to display backtest. ax : matplotlib.axes Axe(s) to display a part of backtest. ax_kwargs : dict Parameters of matplotlib axes containing title, ylabel, xlabel, yscale, xscale and... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DynaPlotPerf:
"""Plot dynamically the performance values. Attributes ---------- fig : matplotlib.figure.Figure Figure to display backtest. ax : matplotlib.axes Axe(s) to display a part of backtest. ax_kwargs : dict Parameters of matplotlib axes containing title, ylabel, xlabel, yscale, xscale and ticks_params... | the_stack_v2_python_sparse | fynance/backtest/dynamic_plot_backtest.py | ArthurBernard/Fynance | train | 22 |
6fb8102d093237d7fae68bf6523a4e94eb2c7044 | [
"self.k = k\nself.kheap = []\nheapq.heapify(self.kheap)\nfor i in nums:\n self.add(i)",
"heapq.heappush(self.kheap, val)\nif len(self.kheap) > self.k:\n heapq.heappop(self.kheap)\nreturn self.kheap[0]"
] | <|body_start_0|>
self.k = k
self.kheap = []
heapq.heapify(self.kheap)
for i in nums:
self.add(i)
<|end_body_0|>
<|body_start_1|>
heapq.heappush(self.kheap, val)
if len(self.kheap) > self.k:
heapq.heappop(self.kheap)
return self.kheap[0]
<|... | KthLargest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.k = k
self.kheap = []
heapq.heapify(s... | stack_v2_sparse_classes_36k_train_012113 | 650 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004948 | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | 70d8827f430b484fd3407001e02107b2545ef787 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.k = k
self.kheap = []
heapq.heapify(self.kheap)
for i in nums:
self.add(i)
def add(self, val):
""":type val: int :rtype: int"""
heapq.heappush(self.kh... | the_stack_v2_python_sparse | leetcode/algorithms/heap/kth-largest-element-in-a-stream.py | AnujPancholi/codingQuestionSolutions | train | 1 | |
2ec589c14498750098724158d44fc12a80ec5260 | [
"BasePoller.__init__(self, config, generator)\nself.couch = None\nself._query = '/_stats'\nself._setUp()",
"try:\n couchURL = getattr(self.config, 'couchURL', None)\n if not couchURL:\n raise Exception(\"Configuration value 'couchURL' missing, can't connect to CouchDB.\")\n self.couch = CouchServe... | <|body_start_0|>
BasePoller.__init__(self, config, generator)
self.couch = None
self._query = '/_stats'
self._setUp()
<|end_body_0|>
<|body_start_1|>
try:
couchURL = getattr(self.config, 'couchURL', None)
if not couchURL:
raise Exception("... | Polling CouchDb statistics values - number of status error codes (configurable). | CouchErrorsPoller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CouchErrorsPoller:
"""Polling CouchDb statistics values - number of status error codes (configurable)."""
def __init__(self, config, generator):
"""couch - instance of CouchServer class"""
<|body_0|>
def _setUp(self):
"""Instantiate CouchServer reference. Test co... | stack_v2_sparse_classes_36k_train_012114 | 9,060 | no_license | [
{
"docstring": "couch - instance of CouchServer class",
"name": "__init__",
"signature": "def __init__(self, config, generator)"
},
{
"docstring": "Instantiate CouchServer reference. Test connection with CouchDB (first connect and retrieve attempt).",
"name": "_setUp",
"signature": "def ... | 4 | stack_v2_sparse_classes_30k_train_004823 | Implement the Python class `CouchErrorsPoller` described below.
Class description:
Polling CouchDb statistics values - number of status error codes (configurable).
Method signatures and docstrings:
- def __init__(self, config, generator): couch - instance of CouchServer class
- def _setUp(self): Instantiate CouchServ... | Implement the Python class `CouchErrorsPoller` described below.
Class description:
Polling CouchDb statistics values - number of status error codes (configurable).
Method signatures and docstrings:
- def __init__(self, config, generator): couch - instance of CouchServer class
- def _setUp(self): Instantiate CouchServ... | f4cb398de940560e40491ba676b704e1489d4682 | <|skeleton|>
class CouchErrorsPoller:
"""Polling CouchDb statistics values - number of status error codes (configurable)."""
def __init__(self, config, generator):
"""couch - instance of CouchServer class"""
<|body_0|>
def _setUp(self):
"""Instantiate CouchServer reference. Test co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CouchErrorsPoller:
"""Polling CouchDb statistics values - number of status error codes (configurable)."""
def __init__(self, config, generator):
"""couch - instance of CouchServer class"""
BasePoller.__init__(self, config, generator)
self.couch = None
self._query = '/_stat... | the_stack_v2_python_sparse | src/python/WMComponent/AlertGenerator/Pollers/Couch.py | PerilousApricot/WMCore | train | 1 |
1a4ee4664525da3082e070eaa359ef95c3c63e50 | [
"super(FactorizedReduce, self).__init__()\nif desc.channel_out % 2 != 0:\n raise Exception('channel_out must be divided by 2.')\naffine = desc.get('affine', True)\nself.relu = nn.ReLU(inplace=False)\nself.conv1 = nn.Conv2d(desc.channel_in, desc.channel_out // 2, 1, stride=2, padding=0, bias=False)\nself.conv2 = ... | <|body_start_0|>
super(FactorizedReduce, self).__init__()
if desc.channel_out % 2 != 0:
raise Exception('channel_out must be divided by 2.')
affine = desc.get('affine', True)
self.relu = nn.ReLU(inplace=False)
self.conv1 = nn.Conv2d(desc.channel_in, desc.channel_out /... | Class of Factorized Reduce operation. :param desc: description of FactorizedReduce :type desc: Config | FactorizedReduce | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FactorizedReduce:
"""Class of Factorized Reduce operation. :param desc: description of FactorizedReduce :type desc: Config"""
def __init__(self, desc):
"""Init FactorizedReduce."""
<|body_0|>
def forward(self, x):
"""Forward function of FactorizedReduce."""
... | stack_v2_sparse_classes_36k_train_012115 | 5,395 | permissive | [
{
"docstring": "Init FactorizedReduce.",
"name": "__init__",
"signature": "def __init__(self, desc)"
},
{
"docstring": "Forward function of FactorizedReduce.",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | null | Implement the Python class `FactorizedReduce` described below.
Class description:
Class of Factorized Reduce operation. :param desc: description of FactorizedReduce :type desc: Config
Method signatures and docstrings:
- def __init__(self, desc): Init FactorizedReduce.
- def forward(self, x): Forward function of Facto... | Implement the Python class `FactorizedReduce` described below.
Class description:
Class of Factorized Reduce operation. :param desc: description of FactorizedReduce :type desc: Config
Method signatures and docstrings:
- def __init__(self, desc): Init FactorizedReduce.
- def forward(self, x): Forward function of Facto... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class FactorizedReduce:
"""Class of Factorized Reduce operation. :param desc: description of FactorizedReduce :type desc: Config"""
def __init__(self, desc):
"""Init FactorizedReduce."""
<|body_0|>
def forward(self, x):
"""Forward function of FactorizedReduce."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FactorizedReduce:
"""Class of Factorized Reduce operation. :param desc: description of FactorizedReduce :type desc: Config"""
def __init__(self, desc):
"""Init FactorizedReduce."""
super(FactorizedReduce, self).__init__()
if desc.channel_out % 2 != 0:
raise Exception('... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/cv/image_classification/Cars_for_TensorFlow/automl/vega/search_space/networks/pytorch/blocks/operations.py | Huawei-Ascend/modelzoo | train | 1 |
120dab200c3109aededeffda58951351287bed1e | [
"returned = super().__init__(*args, **kwargs)\nnew_fields = OrderedDict()\nfor symptom in SYMPTOM_CHOICES:\n if symptom[0] not in self.initial:\n self.initial[symptom[0]] = 0\n new_fields[symptom[0]] = forms.IntegerField(required=False, min_value=min([x[0] for x in SYMPTOM_INTENSITY_CHOICES]), max_valu... | <|body_start_0|>
returned = super().__init__(*args, **kwargs)
new_fields = OrderedDict()
for symptom in SYMPTOM_CHOICES:
if symptom[0] not in self.initial:
self.initial[symptom[0]] = 0
new_fields[symptom[0]] = forms.IntegerField(required=False, min_value=m... | SymptomReportForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SymptomReportForm:
def __init__(self, *args, **kwargs):
"""Add fields to the form for each potential symptom. This reorders to place the symptom list first, in the order of SYMPTOM_CHOICES. The value is initialized to 0 if none is provided."""
<|body_0|>
def save(self):
... | stack_v2_sparse_classes_36k_train_012116 | 2,503 | permissive | [
{
"docstring": "Add fields to the form for each potential symptom. This reorders to place the symptom list first, in the order of SYMPTOM_CHOICES. The value is initialized to 0 if none is provided.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Add sa... | 2 | null | Implement the Python class `SymptomReportForm` described below.
Class description:
Implement the SymptomReportForm class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Add fields to the form for each potential symptom. This reorders to place the symptom list first, in the order of SYMPTOM_C... | Implement the Python class `SymptomReportForm` described below.
Class description:
Implement the SymptomReportForm class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Add fields to the form for each potential symptom. This reorders to place the symptom list first, in the order of SYMPTOM_C... | 3ee9bdefbd567299b27bb22f0bf35d64f7764b3a | <|skeleton|>
class SymptomReportForm:
def __init__(self, *args, **kwargs):
"""Add fields to the form for each potential symptom. This reorders to place the symptom list first, in the order of SYMPTOM_CHOICES. The value is initialized to 0 if none is provided."""
<|body_0|>
def save(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SymptomReportForm:
def __init__(self, *args, **kwargs):
"""Add fields to the form for each potential symptom. This reorders to place the symptom list first, in the order of SYMPTOM_CHOICES. The value is initialized to 0 if none is provided."""
returned = super().__init__(*args, **kwargs)
... | the_stack_v2_python_sparse | reports/forms.py | OpenHumans/quantified-flu | train | 18 | |
6f446e2ef3f403c60ff5f7f25eb434eea7ca3343 | [
"if not root:\n return ''\nrt = []\nstk = [root]\nwhile stk:\n newstk = []\n while stk:\n p = stk.pop(0)\n if p == None:\n rt.append('#')\n else:\n rt.append(str(p.val))\n newstk.extend([p.left, p.right])\n stk = newstk\nreturn ':'.join(rt)",
"if n... | <|body_start_0|>
if not root:
return ''
rt = []
stk = [root]
while stk:
newstk = []
while stk:
p = stk.pop(0)
if p == None:
rt.append('#')
else:
rt.append(str(p.val... | Codec1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec1:
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_36k_train_012117 | 3,374 | 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_003203 | Implement the Python class `Codec1` described below.
Class description:
Implement the Codec1 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 :rtyp... | Implement the Python class `Codec1` described below.
Class description:
Implement the Codec1 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 :rtyp... | 0e99f9a5226507706b3ee66fd04bae813755ef40 | <|skeleton|>
class Codec1:
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_36k | data/stack_v2_sparse_classes_30k | class Codec1:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
rt = []
stk = [root]
while stk:
newstk = []
while stk:
p = stk.pop(0)
... | the_stack_v2_python_sparse | medium/tree/test_449_Serialize_and_Deserialize_BST.py | wuxu1019/leetcode_sophia | train | 1 | |
bd3b9ce934873ae57b6560d24fcd136ee542c0aa | [
"Functor.__init__(self, Rings(), Rings())\nfrom .graded_ring import canonical_parameters\nself._group, R, red_hom, n = canonical_parameters(group, ZZ, red_hom)\nself._red_hom = bool(red_hom)\nself._analytic_type = self.AT(analytic_type)",
"if isinstance(R, BaseFacade):\n R = _get_base_ring(R._ring)\n return... | <|body_start_0|>
Functor.__init__(self, Rings(), Rings())
from .graded_ring import canonical_parameters
self._group, R, red_hom, n = canonical_parameters(group, ZZ, red_hom)
self._red_hom = bool(red_hom)
self._analytic_type = self.AT(analytic_type)
<|end_body_0|>
<|body_start_1|... | Construction functor for forms rings. NOTE: When the base ring is not a ``BaseFacade`` the functor is first merged with the ConstantFormsSpaceFunctor. This case occurs in the pushout constructions. (when trying to find a common parent between a forms ring and a ring which is not a ``BaseFacade``). | FormsRingFunctor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FormsRingFunctor:
"""Construction functor for forms rings. NOTE: When the base ring is not a ``BaseFacade`` the functor is first merged with the ConstantFormsSpaceFunctor. This case occurs in the pushout constructions. (when trying to find a common parent between a forms ring and a ring which is ... | stack_v2_sparse_classes_36k_train_012118 | 31,146 | no_license | [
{
"docstring": "Construction functor for the forms ring with the given ``analytic_type``, ``group`` and variable ``red_hom`` See :meth:`__call__` for a description of the functor. INPUT: - ``analytic_type`` -- An element of ``AnalyticType()``. - ``group`` -- The index of a Hecke Triangle group. - ``red_hom`` --... | 5 | null | Implement the Python class `FormsRingFunctor` described below.
Class description:
Construction functor for forms rings. NOTE: When the base ring is not a ``BaseFacade`` the functor is first merged with the ConstantFormsSpaceFunctor. This case occurs in the pushout constructions. (when trying to find a common parent be... | Implement the Python class `FormsRingFunctor` described below.
Class description:
Construction functor for forms rings. NOTE: When the base ring is not a ``BaseFacade`` the functor is first merged with the ConstantFormsSpaceFunctor. This case occurs in the pushout constructions. (when trying to find a common parent be... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class FormsRingFunctor:
"""Construction functor for forms rings. NOTE: When the base ring is not a ``BaseFacade`` the functor is first merged with the ConstantFormsSpaceFunctor. This case occurs in the pushout constructions. (when trying to find a common parent between a forms ring and a ring which is ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FormsRingFunctor:
"""Construction functor for forms rings. NOTE: When the base ring is not a ``BaseFacade`` the functor is first merged with the ConstantFormsSpaceFunctor. This case occurs in the pushout constructions. (when trying to find a common parent between a forms ring and a ring which is not a ``BaseF... | the_stack_v2_python_sparse | sage/src/sage/modular/modform_hecketriangle/functors.py | bopopescu/geosci | train | 0 |
5dfc6676c56dfad32159938555132555f1c9e5e5 | [
"try:\n task = taskqueue.add(queue_name=queue_name, **kwargs)\n return task\nexcept (taskqueue.TombstonedTaskError, taskqueue.DuplicateTaskNameError, taskqueue.BadTransactionStateError, taskqueue.BadTaskStateError, taskqueue.TooManyTasksError, taskqueue.UnknownQueueError) as e:\n logger.error('Task for que... | <|body_start_0|>
try:
task = taskqueue.add(queue_name=queue_name, **kwargs)
return task
except (taskqueue.TombstonedTaskError, taskqueue.DuplicateTaskNameError, taskqueue.BadTransactionStateError, taskqueue.BadTaskStateError, taskqueue.TooManyTasksError, taskqueue.UnknownQueueErr... | TaskQueueMixin | TaskQueueMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskQueueMixin:
"""TaskQueueMixin"""
def add_task(queue_name='default', **kwargs):
"""Enqueue a task as part of a Datastore transaction https://cloud.google.com/appengine/docs/python/ndb/transactions https://cloud.google.com/appengine/docs/python/taskqueue/queues https://cloud.google... | stack_v2_sparse_classes_36k_train_012119 | 2,029 | permissive | [
{
"docstring": "Enqueue a task as part of a Datastore transaction https://cloud.google.com/appengine/docs/python/ndb/transactions https://cloud.google.com/appengine/docs/python/taskqueue/queues https://cloud.google.com/appengine/docs/python/taskqueue/push/ :param url: :param params: :return:",
"name": "add_... | 2 | stack_v2_sparse_classes_30k_train_011343 | Implement the Python class `TaskQueueMixin` described below.
Class description:
TaskQueueMixin
Method signatures and docstrings:
- def add_task(queue_name='default', **kwargs): Enqueue a task as part of a Datastore transaction https://cloud.google.com/appengine/docs/python/ndb/transactions https://cloud.google.com/ap... | Implement the Python class `TaskQueueMixin` described below.
Class description:
TaskQueueMixin
Method signatures and docstrings:
- def add_task(queue_name='default', **kwargs): Enqueue a task as part of a Datastore transaction https://cloud.google.com/appengine/docs/python/ndb/transactions https://cloud.google.com/ap... | 0afd1360f5a102335c55afaf138e0ecb96644128 | <|skeleton|>
class TaskQueueMixin:
"""TaskQueueMixin"""
def add_task(queue_name='default', **kwargs):
"""Enqueue a task as part of a Datastore transaction https://cloud.google.com/appengine/docs/python/ndb/transactions https://cloud.google.com/appengine/docs/python/taskqueue/queues https://cloud.google... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TaskQueueMixin:
"""TaskQueueMixin"""
def add_task(queue_name='default', **kwargs):
"""Enqueue a task as part of a Datastore transaction https://cloud.google.com/appengine/docs/python/ndb/transactions https://cloud.google.com/appengine/docs/python/taskqueue/queues https://cloud.google.com/appengin... | the_stack_v2_python_sparse | apollo/common/mixins/task_queue.py | aukbit/apollo | train | 0 |
6c430eafa9e0a5e6493c7a0c725e43cfb199fed9 | [
"if G.Env.save_transformed_metrics:\n self.evaluate('holdout', self.data_holdout.target.T.run, self.data_holdout.prediction.T.run)\nelse:\n self.evaluate('holdout', self.data_holdout.target.fold, self.data_holdout.prediction.run)\nsuper().on_run_end()",
"if G.Env.save_transformed_metrics:\n self.evaluate... | <|body_start_0|>
if G.Env.save_transformed_metrics:
self.evaluate('holdout', self.data_holdout.target.T.run, self.data_holdout.prediction.T.run)
else:
self.evaluate('holdout', self.data_holdout.target.fold, self.data_holdout.prediction.run)
super().on_run_end()
<|end_body... | EvaluatorHoldout | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EvaluatorHoldout:
def on_run_end(self):
"""Evaluate holdout predictions for the run"""
<|body_0|>
def on_fold_end(self):
"""Evaluate (run-averaged) holdout predictions for the fold"""
<|body_1|>
def on_rep_end(self):
"""Evaluate (run-averaged) ho... | stack_v2_sparse_classes_36k_train_012120 | 5,856 | permissive | [
{
"docstring": "Evaluate holdout predictions for the run",
"name": "on_run_end",
"signature": "def on_run_end(self)"
},
{
"docstring": "Evaluate (run-averaged) holdout predictions for the fold",
"name": "on_fold_end",
"signature": "def on_fold_end(self)"
},
{
"docstring": "Evalua... | 4 | stack_v2_sparse_classes_30k_train_000024 | Implement the Python class `EvaluatorHoldout` described below.
Class description:
Implement the EvaluatorHoldout class.
Method signatures and docstrings:
- def on_run_end(self): Evaluate holdout predictions for the run
- def on_fold_end(self): Evaluate (run-averaged) holdout predictions for the fold
- def on_rep_end(... | Implement the Python class `EvaluatorHoldout` described below.
Class description:
Implement the EvaluatorHoldout class.
Method signatures and docstrings:
- def on_run_end(self): Evaluate holdout predictions for the run
- def on_fold_end(self): Evaluate (run-averaged) holdout predictions for the fold
- def on_rep_end(... | 3709d5e97dd23efa0df1b79982ae029789e1af57 | <|skeleton|>
class EvaluatorHoldout:
def on_run_end(self):
"""Evaluate holdout predictions for the run"""
<|body_0|>
def on_fold_end(self):
"""Evaluate (run-averaged) holdout predictions for the fold"""
<|body_1|>
def on_rep_end(self):
"""Evaluate (run-averaged) ho... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EvaluatorHoldout:
def on_run_end(self):
"""Evaluate holdout predictions for the run"""
if G.Env.save_transformed_metrics:
self.evaluate('holdout', self.data_holdout.target.T.run, self.data_holdout.prediction.T.run)
else:
self.evaluate('holdout', self.data_holdou... | the_stack_v2_python_sparse | hyperparameter_hunter/callbacks/evaluators.py | shaoeric/hyperparameter_hunter | train | 0 | |
2347fde8cd85e21dc9f8ed72dd04e736f400ba85 | [
"Frame.__init__(self, master)\nself.pack()\nself.createArtistWidgets()",
"tag_name = Frame(self)\nartist_name = Frame(self)\nsong_name = Frame(self)\nalbum_name = Frame(self)\nself.labeltag = Label(tag_name, text='Update Song Artist')\nself.labelSong = Label(song_name, text='Song Name')\nself.labelAlbum = Label(a... | <|body_start_0|>
Frame.__init__(self, master)
self.pack()
self.createArtistWidgets()
<|end_body_0|>
<|body_start_1|>
tag_name = Frame(self)
artist_name = Frame(self)
song_name = Frame(self)
album_name = Frame(self)
self.labeltag = Label(tag_name, text='Up... | Application main window class. | Application | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
<|body_0|>
def createArtistWidgets(self):
"""Add all the widgets to the main frame."""
<|body_1|>
def handle(self):
... | stack_v2_sparse_classes_36k_train_012121 | 2,506 | no_license | [
{
"docstring": "Main frame initialization (mostly delegated)",
"name": "__init__",
"signature": "def __init__(self, master=None)"
},
{
"docstring": "Add all the widgets to the main frame.",
"name": "createArtistWidgets",
"signature": "def createArtistWidgets(self)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_val_000415 | Implement the Python class `Application` described below.
Class description:
Application main window class.
Method signatures and docstrings:
- def __init__(self, master=None): Main frame initialization (mostly delegated)
- def createArtistWidgets(self): Add all the widgets to the main frame.
- def handle(self): Hand... | Implement the Python class `Application` described below.
Class description:
Application main window class.
Method signatures and docstrings:
- def __init__(self, master=None): Main frame initialization (mostly delegated)
- def createArtistWidgets(self): Add all the widgets to the main frame.
- def handle(self): Hand... | 2dba11861f91e4bdc1ef28279132a6d8dd4ccf54 | <|skeleton|>
class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
<|body_0|>
def createArtistWidgets(self):
"""Add all the widgets to the main frame."""
<|body_1|>
def handle(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
Frame.__init__(self, master)
self.pack()
self.createArtistWidgets()
def createArtistWidgets(self):
"""Add all the widgets to t... | the_stack_v2_python_sparse | Mux_Gui/Update_Artist_Of_Song_Gui.py | rduvalwa5/Mux | train | 0 |
719d78b5fc72a0524b9c6c21fc50e2df08176e42 | [
"super().__init__(objective=objective)\nself.penalty_objective = penalty_objective\nself.regularization_parameter = regularization_parameter\nself.expand_dim = expand_dim",
"obj = super().forward(samples=samples, X=X)\npenalty_obj = self.penalty_objective(X)\nif self.expand_dim is not None:\n penalty_obj = pen... | <|body_start_0|>
super().__init__(objective=objective)
self.penalty_objective = penalty_objective
self.regularization_parameter = regularization_parameter
self.expand_dim = expand_dim
<|end_body_0|>
<|body_start_1|>
obj = super().forward(samples=samples, X=X)
penalty_obj... | Penalized MC objective. Allows to construct a penaltized MC-objective by adding a penalty term to the original objective. mc_acq(X) = objective(X) + penalty_objective(X) Note: PenalizedMCObjective allows adding penalty at the MCObjective level, different from the AcquisitionFunction level in PenalizedAcquisitionFunctio... | PenalizedMCObjective | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PenalizedMCObjective:
"""Penalized MC objective. Allows to construct a penaltized MC-objective by adding a penalty term to the original objective. mc_acq(X) = objective(X) + penalty_objective(X) Note: PenalizedMCObjective allows adding penalty at the MCObjective level, different from the Acquisit... | stack_v2_sparse_classes_36k_train_012122 | 14,396 | permissive | [
{
"docstring": "Penalized MC objective. Args: objective: A callable `f(samples, X)` mapping a `sample_shape x batch-shape x q x m`-dim Tensor `samples` and an optional `batch-shape x q x d`-dim Tensor `X` to a `sample_shape x batch-shape x q`-dim Tensor of objective values. penalty_objective: A torch.nn.Module ... | 2 | null | Implement the Python class `PenalizedMCObjective` described below.
Class description:
Penalized MC objective. Allows to construct a penaltized MC-objective by adding a penalty term to the original objective. mc_acq(X) = objective(X) + penalty_objective(X) Note: PenalizedMCObjective allows adding penalty at the MCObjec... | Implement the Python class `PenalizedMCObjective` described below.
Class description:
Penalized MC objective. Allows to construct a penaltized MC-objective by adding a penalty term to the original objective. mc_acq(X) = objective(X) + penalty_objective(X) Note: PenalizedMCObjective allows adding penalty at the MCObjec... | 4cc5ed59b2e8a9c780f786830c548e05cc74d53c | <|skeleton|>
class PenalizedMCObjective:
"""Penalized MC objective. Allows to construct a penaltized MC-objective by adding a penalty term to the original objective. mc_acq(X) = objective(X) + penalty_objective(X) Note: PenalizedMCObjective allows adding penalty at the MCObjective level, different from the Acquisit... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PenalizedMCObjective:
"""Penalized MC objective. Allows to construct a penaltized MC-objective by adding a penalty term to the original objective. mc_acq(X) = objective(X) + penalty_objective(X) Note: PenalizedMCObjective allows adding penalty at the MCObjective level, different from the AcquisitionFunction l... | the_stack_v2_python_sparse | botorch/acquisition/penalized.py | pytorch/botorch | train | 2,891 |
7d0ae7d93e5380e1380bc54c0889f08eacc8c1a0 | [
"super(DuelingHead, self).__init__()\nself.A = [fc_block(hidden_dim, hidden_dim, activation=activation, norm_type=norm_type) for _ in range(a_layer_num)]\nself.V = [fc_block(hidden_dim, hidden_dim, activation=activation, norm_type=norm_type) for _ in range(v_layer_num)]\nself.A += fc_block(hidden_dim, action_dim, a... | <|body_start_0|>
super(DuelingHead, self).__init__()
self.A = [fc_block(hidden_dim, hidden_dim, activation=activation, norm_type=norm_type) for _ in range(a_layer_num)]
self.V = [fc_block(hidden_dim, hidden_dim, activation=activation, norm_type=norm_type) for _ in range(v_layer_num)]
sel... | Overview: The Dueling head used in models. Notes: Dueling head is one of the three most major improvements in DQN algorithm. The paper introducing \\ this improvement `Dueling Network Architectures for Deep Reinforcement Learning` was published \\ by Google in 2016. You can view the original paper on <https://arxiv.org... | DuelingHead | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DuelingHead:
"""Overview: The Dueling head used in models. Notes: Dueling head is one of the three most major improvements in DQN algorithm. The paper introducing \\ this improvement `Dueling Network Architectures for Deep Reinforcement Learning` was published \\ by Google in 2016. You can view t... | stack_v2_sparse_classes_36k_train_012123 | 2,805 | permissive | [
{
"docstring": "Overview: Init the DuelingHead according to arguments. Arguments: - hidden_dim (:obj:`int`): the hidden_dim used before connected to DuelingHead - action_dim (:obj:`int`): the num of actions - a_layer_num (:obj:`int`): the num of fc_block used in the network to compute action output - v_layer_nu... | 2 | stack_v2_sparse_classes_30k_train_003151 | Implement the Python class `DuelingHead` described below.
Class description:
Overview: The Dueling head used in models. Notes: Dueling head is one of the three most major improvements in DQN algorithm. The paper introducing \\ this improvement `Dueling Network Architectures for Deep Reinforcement Learning` was publish... | Implement the Python class `DuelingHead` described below.
Class description:
Overview: The Dueling head used in models. Notes: Dueling head is one of the three most major improvements in DQN algorithm. The paper introducing \\ this improvement `Dueling Network Architectures for Deep Reinforcement Learning` was publish... | 09d507c412235a2f0cf9c0b3485ec9ed15fb6421 | <|skeleton|>
class DuelingHead:
"""Overview: The Dueling head used in models. Notes: Dueling head is one of the three most major improvements in DQN algorithm. The paper introducing \\ this improvement `Dueling Network Architectures for Deep Reinforcement Learning` was published \\ by Google in 2016. You can view t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DuelingHead:
"""Overview: The Dueling head used in models. Notes: Dueling head is one of the three most major improvements in DQN algorithm. The paper introducing \\ this improvement `Dueling Network Architectures for Deep Reinforcement Learning` was published \\ by Google in 2016. You can view the original p... | the_stack_v2_python_sparse | ctools/model/common_arch/dueling.py | LFhase/DI-star | train | 1 |
e265c15f3fc0929d1ddcb36f9d7abd77afe2e6a8 | [
"self.parallel_trap_list = parallel_trap_list\nself.parallel_ccd = parallel_ccd\nself.serial_trap_list = serial_trap_list\nself.serial_ccd = serial_ccd",
"parallel_traps = self.parallel_trap_list or []\nserial_traps = self.serial_trap_list or []\nreturn [trap for trap in parallel_traps] + [trap for trap in serial... | <|body_start_0|>
self.parallel_trap_list = parallel_trap_list
self.parallel_ccd = parallel_ccd
self.serial_trap_list = serial_trap_list
self.serial_ccd = serial_ccd
<|end_body_0|>
<|body_start_1|>
parallel_traps = self.parallel_trap_list or []
serial_traps = self.serial_... | CTI2D | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CTI2D:
def __init__(self, parallel_trap_list: Optional[List[TrapInstantCapture]]=None, parallel_ccd: Optional[CCDPhase]=None, serial_trap_list: Optional[List[TrapInstantCapture]]=None, serial_ccd: Optional[CCDPhase]=None):
"""An object which determines the behaviour of CTI during 2D para... | stack_v2_sparse_classes_36k_train_012124 | 3,711 | permissive | [
{
"docstring": "An object which determines the behaviour of CTI during 2D parallel and serial clocking. This includes the traps that capture and trail electrons and the CCD volume filling behaviour. Parameters ---------- parallel_trap_list The traps on the dataset that capture and release electrons during paral... | 2 | stack_v2_sparse_classes_30k_train_006266 | Implement the Python class `CTI2D` described below.
Class description:
Implement the CTI2D class.
Method signatures and docstrings:
- def __init__(self, parallel_trap_list: Optional[List[TrapInstantCapture]]=None, parallel_ccd: Optional[CCDPhase]=None, serial_trap_list: Optional[List[TrapInstantCapture]]=None, serial... | Implement the Python class `CTI2D` described below.
Class description:
Implement the CTI2D class.
Method signatures and docstrings:
- def __init__(self, parallel_trap_list: Optional[List[TrapInstantCapture]]=None, parallel_ccd: Optional[CCDPhase]=None, serial_trap_list: Optional[List[TrapInstantCapture]]=None, serial... | 32e9ec7194776e5f60329e674942bc19f8626b04 | <|skeleton|>
class CTI2D:
def __init__(self, parallel_trap_list: Optional[List[TrapInstantCapture]]=None, parallel_ccd: Optional[CCDPhase]=None, serial_trap_list: Optional[List[TrapInstantCapture]]=None, serial_ccd: Optional[CCDPhase]=None):
"""An object which determines the behaviour of CTI during 2D para... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CTI2D:
def __init__(self, parallel_trap_list: Optional[List[TrapInstantCapture]]=None, parallel_ccd: Optional[CCDPhase]=None, serial_trap_list: Optional[List[TrapInstantCapture]]=None, serial_ccd: Optional[CCDPhase]=None):
"""An object which determines the behaviour of CTI during 2D parallel and seria... | the_stack_v2_python_sparse | autocti/model/model_util.py | Jammy2211/PyAutoCTI | train | 6 | |
712b4ac36d64d1707b48f7d7bb9b81ed49c7cfe4 | [
"casts = super(DateTime, self)._input_casts\ncasts[datetime] = self._datetime_cast\nreturn casts",
"initial_date = datetime(year=2010, month=1, day=1, hour=0, minute=0, second=0)\nseconds = int((value - initial_date).total_seconds())\nself._value = int(seconds)",
"try:\n mat = re.match('(\\\\d{4})\\\\-(\\\\d... | <|body_start_0|>
casts = super(DateTime, self)._input_casts
casts[datetime] = self._datetime_cast
return casts
<|end_body_0|>
<|body_start_1|>
initial_date = datetime(year=2010, month=1, day=1, hour=0, minute=0, second=0)
seconds = int((value - initial_date).total_seconds())
... | Date-Time field which accepts datetime input and string time inputs | DateTime | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DateTime:
"""Date-Time field which accepts datetime input and string time inputs"""
def _input_casts(self):
"""Add datetime cast in input casts :return: (input format: cast function) dict"""
<|body_0|>
def _datetime_cast(self, value):
"""Cast datetime value :para... | stack_v2_sparse_classes_36k_train_012125 | 1,227 | no_license | [
{
"docstring": "Add datetime cast in input casts :return: (input format: cast function) dict",
"name": "_input_casts",
"signature": "def _input_casts(self)"
},
{
"docstring": "Cast datetime value :param value: datetime value",
"name": "_datetime_cast",
"signature": "def _datetime_cast(se... | 3 | stack_v2_sparse_classes_30k_train_016891 | Implement the Python class `DateTime` described below.
Class description:
Date-Time field which accepts datetime input and string time inputs
Method signatures and docstrings:
- def _input_casts(self): Add datetime cast in input casts :return: (input format: cast function) dict
- def _datetime_cast(self, value): Cast... | Implement the Python class `DateTime` described below.
Class description:
Date-Time field which accepts datetime input and string time inputs
Method signatures and docstrings:
- def _input_casts(self): Add datetime cast in input casts :return: (input format: cast function) dict
- def _datetime_cast(self, value): Cast... | d553dfb2e58a17366c13e57c4c1b16a387111df7 | <|skeleton|>
class DateTime:
"""Date-Time field which accepts datetime input and string time inputs"""
def _input_casts(self):
"""Add datetime cast in input casts :return: (input format: cast function) dict"""
<|body_0|>
def _datetime_cast(self, value):
"""Cast datetime value :para... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DateTime:
"""Date-Time field which accepts datetime input and string time inputs"""
def _input_casts(self):
"""Add datetime cast in input casts :return: (input format: cast function) dict"""
casts = super(DateTime, self)._input_casts
casts[datetime] = self._datetime_cast
r... | the_stack_v2_python_sparse | egts/egts_types/date_time_field.py | dkraminov/egts-python | train | 0 |
7f111884c18c209de8947fa0f594c7adaea431a9 | [
"self.timeout = timeout\nself.Url = 'http://epsg.io/'\nself.proxyUrl = ''\nif (isinstance(proxyHost, unicode) or isinstance(proxyHost, str)) & proxyHost.startswith('http://'):\n self.proxyUrl = 'http://'\n if proxyUser and proxyPass:\n self.proxyUrl += proxyUser + ':' + proxyPass + '@'\n self.proxyU... | <|body_start_0|>
self.timeout = timeout
self.Url = 'http://epsg.io/'
self.proxyUrl = ''
if (isinstance(proxyHost, unicode) or isinstance(proxyHost, str)) & proxyHost.startswith('http://'):
self.proxyUrl = 'http://'
if proxyUser and proxyPass:
self.... | srsLookUp | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class srsLookUp:
def __init__(self, timeout=5, proxyHost='', port='', proxyUser=None, proxyPass=None):
"""find SRS params using http://epsg.io/"""
<|body_0|>
def wkid2proj4(self, wkid, format='proj4'):
""":param wkid: the espg or other well known id, like 4326 for wgs84 :p... | stack_v2_sparse_classes_36k_train_012126 | 1,757 | permissive | [
{
"docstring": "find SRS params using http://epsg.io/",
"name": "__init__",
"signature": "def __init__(self, timeout=5, proxyHost='', port='', proxyUser=None, proxyPass=None)"
},
{
"docstring": ":param wkid: the espg or other well known id, like 4326 for wgs84 :param format: *format*: The crs fo... | 2 | stack_v2_sparse_classes_30k_train_020132 | Implement the Python class `srsLookUp` described below.
Class description:
Implement the srsLookUp class.
Method signatures and docstrings:
- def __init__(self, timeout=5, proxyHost='', port='', proxyUser=None, proxyPass=None): find SRS params using http://epsg.io/
- def wkid2proj4(self, wkid, format='proj4'): :param... | Implement the Python class `srsLookUp` described below.
Class description:
Implement the srsLookUp class.
Method signatures and docstrings:
- def __init__(self, timeout=5, proxyHost='', port='', proxyUser=None, proxyPass=None): find SRS params using http://epsg.io/
- def wkid2proj4(self, wkid, format='proj4'): :param... | d0d2e4da7cb9d6f08ef82b6c6f94d3340b96f9ba | <|skeleton|>
class srsLookUp:
def __init__(self, timeout=5, proxyHost='', port='', proxyUser=None, proxyPass=None):
"""find SRS params using http://epsg.io/"""
<|body_0|>
def wkid2proj4(self, wkid, format='proj4'):
""":param wkid: the espg or other well known id, like 4326 for wgs84 :p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class srsLookUp:
def __init__(self, timeout=5, proxyHost='', port='', proxyUser=None, proxyPass=None):
"""find SRS params using http://epsg.io/"""
self.timeout = timeout
self.Url = 'http://epsg.io/'
self.proxyUrl = ''
if (isinstance(proxyHost, unicode) or isinstance(proxyHost... | the_stack_v2_python_sparse | mxdParser/_srsLookUp.py | julor/arcgis2qgs | train | 0 | |
7f5ff152339ebf040aef35c46e7757df84eda353 | [
"service = self.context['compute'].images\nrequests = [(service, messages.ComputeImagesListRequest(filter=lister.ConstructNameFilterExpression(['^{0}-v[0-9]+.*'.format(alias.name_prefix)]), maxResults=constants.MAX_RESULTS_PER_PAGE, project=alias.project)), (service, messages.ComputeImagesListRequest(filter=lister.... | <|body_start_0|>
service = self.context['compute'].images
requests = [(service, messages.ComputeImagesListRequest(filter=lister.ConstructNameFilterExpression(['^{0}-v[0-9]+.*'.format(alias.name_prefix)]), maxResults=constants.MAX_RESULTS_PER_PAGE, project=alias.project)), (service, messages.ComputeImage... | Mixin class for expanding image aliases. | ImageExpander | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageExpander:
"""Mixin class for expanding image aliases."""
def GetMatchingImages(self, image, alias):
"""Yields images from a public image project and the user's project."""
<|body_0|>
def ExpandImageFlag(self, args):
"""Returns a full URI for the given value ... | stack_v2_sparse_classes_36k_train_012127 | 6,858 | permissive | [
{
"docstring": "Yields images from a public image project and the user's project.",
"name": "GetMatchingImages",
"signature": "def GetMatchingImages(self, image, alias)"
},
{
"docstring": "Returns a full URI for the given value of --image.",
"name": "ExpandImageFlag",
"signature": "def E... | 2 | stack_v2_sparse_classes_30k_train_004270 | Implement the Python class `ImageExpander` described below.
Class description:
Mixin class for expanding image aliases.
Method signatures and docstrings:
- def GetMatchingImages(self, image, alias): Yields images from a public image project and the user's project.
- def ExpandImageFlag(self, args): Returns a full URI... | Implement the Python class `ImageExpander` described below.
Class description:
Mixin class for expanding image aliases.
Method signatures and docstrings:
- def GetMatchingImages(self, image, alias): Yields images from a public image project and the user's project.
- def ExpandImageFlag(self, args): Returns a full URI... | 90d87b2adb1eab7f218b075886aa620d8d6eeedb | <|skeleton|>
class ImageExpander:
"""Mixin class for expanding image aliases."""
def GetMatchingImages(self, image, alias):
"""Yields images from a public image project and the user's project."""
<|body_0|>
def ExpandImageFlag(self, args):
"""Returns a full URI for the given value ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageExpander:
"""Mixin class for expanding image aliases."""
def GetMatchingImages(self, image, alias):
"""Yields images from a public image project and the user's project."""
service = self.context['compute'].images
requests = [(service, messages.ComputeImagesListRequest(filter=... | the_stack_v2_python_sparse | old/google-cloud-sdk/lib/googlecloudsdk/compute/lib/image_utils.py | altock/dev | train | 0 |
38ca684ab7d1ead8234b107f0511de0ee76ac58b | [
"self.name = name\nself.mva_number = mva_number\nself.company_phone = company_phone\nself.company_email = company_email\nself.company_url = company_url\nself.contact = contact\nself.address = address\nself.dealer = dealer\nself.settings = settings\nself.country = country\nself.additional_properties = additional_pro... | <|body_start_0|>
self.name = name
self.mva_number = mva_number
self.company_phone = company_phone
self.company_email = company_email
self.company_url = company_url
self.contact = contact
self.address = address
self.dealer = dealer
self.settings = s... | Implementation of the 'CreateAccountRequest' model. TODO: type model description here. Attributes: name (string): Name of the account owner (company) mva_number (string): Mva / Organization number company_phone (string): TODO: type description here. company_email (string): TODO: type description here. company_url (stri... | CreateAccountRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateAccountRequest:
"""Implementation of the 'CreateAccountRequest' model. TODO: type model description here. Attributes: name (string): Name of the account owner (company) mva_number (string): Mva / Organization number company_phone (string): TODO: type description here. company_email (string)... | stack_v2_sparse_classes_36k_train_012128 | 4,517 | permissive | [
{
"docstring": "Constructor for the CreateAccountRequest class",
"name": "__init__",
"signature": "def __init__(self, name=None, mva_number=None, company_phone=None, company_email=None, company_url=None, contact=None, address=None, dealer=None, settings=None, country=None, additional_properties={})"
}... | 2 | null | Implement the Python class `CreateAccountRequest` described below.
Class description:
Implementation of the 'CreateAccountRequest' model. TODO: type model description here. Attributes: name (string): Name of the account owner (company) mva_number (string): Mva / Organization number company_phone (string): TODO: type d... | Implement the Python class `CreateAccountRequest` described below.
Class description:
Implementation of the 'CreateAccountRequest' model. TODO: type model description here. Attributes: name (string): Name of the account owner (company) mva_number (string): Mva / Organization number company_phone (string): TODO: type d... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class CreateAccountRequest:
"""Implementation of the 'CreateAccountRequest' model. TODO: type model description here. Attributes: name (string): Name of the account owner (company) mva_number (string): Mva / Organization number company_phone (string): TODO: type description here. company_email (string)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateAccountRequest:
"""Implementation of the 'CreateAccountRequest' model. TODO: type model description here. Attributes: name (string): Name of the account owner (company) mva_number (string): Mva / Organization number company_phone (string): TODO: type description here. company_email (string): TODO: type ... | the_stack_v2_python_sparse | idfy_rest_client/models/create_account_request.py | dealflowteam/Idfy | train | 0 |
844039f1b19601baeb8cba086dfc36abf999429a | [
"if not page_url or not html_cont:\n return\nsoup = BeautifulSoup(html_cont, 'html.parser', from_encoding='utf-8')\nnew_urls = self._get_new_urls(page_url, soup)\nnew_data = self._get_new_data(page_url, soup)\nreturn (new_urls, new_data)",
"new_urls = set()\nlinks = soup.find_all('a', href=re.compile('/view/\\... | <|body_start_0|>
if not page_url or not html_cont:
return
soup = BeautifulSoup(html_cont, 'html.parser', from_encoding='utf-8')
new_urls = self._get_new_urls(page_url, soup)
new_data = self._get_new_data(page_url, soup)
return (new_urls, new_data)
<|end_body_0|>
<|bo... | html 解析器 | HtmlParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HtmlParser:
"""html 解析器"""
def parser(self, page_url, html_cont):
"""用于解析网页内容，抽取 URL 和数据 :param page_url: 下载页面的 URL :param html_cont: 下载的网页内容 :return:"""
<|body_0|>
def _get_new_urls(self, page_url, soup: BeautifulSoup):
"""抽取新的 url 集合 :param page_url: 下载页面的 URL ... | stack_v2_sparse_classes_36k_train_012129 | 1,975 | no_license | [
{
"docstring": "用于解析网页内容，抽取 URL 和数据 :param page_url: 下载页面的 URL :param html_cont: 下载的网页内容 :return:",
"name": "parser",
"signature": "def parser(self, page_url, html_cont)"
},
{
"docstring": "抽取新的 url 集合 :param page_url: 下载页面的 URL :param soup: soup :return: 返回新的 URL 集合",
"name": "_get_new_urls... | 3 | stack_v2_sparse_classes_30k_train_014769 | Implement the Python class `HtmlParser` described below.
Class description:
html 解析器
Method signatures and docstrings:
- def parser(self, page_url, html_cont): 用于解析网页内容，抽取 URL 和数据 :param page_url: 下载页面的 URL :param html_cont: 下载的网页内容 :return:
- def _get_new_urls(self, page_url, soup: BeautifulSoup): 抽取新的 url 集合 :param... | Implement the Python class `HtmlParser` described below.
Class description:
html 解析器
Method signatures and docstrings:
- def parser(self, page_url, html_cont): 用于解析网页内容，抽取 URL 和数据 :param page_url: 下载页面的 URL :param html_cont: 下载的网页内容 :return:
- def _get_new_urls(self, page_url, soup: BeautifulSoup): 抽取新的 url 集合 :param... | 21c3b190329e4f3571747c2feba8fad268592c0d | <|skeleton|>
class HtmlParser:
"""html 解析器"""
def parser(self, page_url, html_cont):
"""用于解析网页内容，抽取 URL 和数据 :param page_url: 下载页面的 URL :param html_cont: 下载的网页内容 :return:"""
<|body_0|>
def _get_new_urls(self, page_url, soup: BeautifulSoup):
"""抽取新的 url 集合 :param page_url: 下载页面的 URL ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HtmlParser:
"""html 解析器"""
def parser(self, page_url, html_cont):
"""用于解析网页内容，抽取 URL 和数据 :param page_url: 下载页面的 URL :param html_cont: 下载的网页内容 :return:"""
if not page_url or not html_cont:
return
soup = BeautifulSoup(html_cont, 'html.parser', from_encoding='utf-8')
... | the_stack_v2_python_sparse | day03_base_spider/HtmlParser.py | zhayangtao/python-reptile | train | 0 |
6c332649851f1ee551eedb5b8daac3639cb1395b | [
"super().__init__(coordinator, description)\nself._serial_number = serial_number\nself._attr_unique_id = f'{serial_number}_{description.key}'\nencharge_inventory = self.data.encharge_inventory\nassert encharge_inventory is not None\nself._attr_device_info = DeviceInfo(identifiers={(DOMAIN, serial_number)}, manufact... | <|body_start_0|>
super().__init__(coordinator, description)
self._serial_number = serial_number
self._attr_unique_id = f'{serial_number}_{description.key}'
encharge_inventory = self.data.encharge_inventory
assert encharge_inventory is not None
self._attr_device_info = Dev... | Defines an Encharge binary_sensor entity. | EnvoyEnchargeBinarySensorEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnvoyEnchargeBinarySensorEntity:
"""Defines an Encharge binary_sensor entity."""
def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnchargeBinarySensorEntityDescription, serial_number: str) -> None:
"""Init the Encharge base entity."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_012130 | 5,991 | permissive | [
{
"docstring": "Init the Encharge base entity.",
"name": "__init__",
"signature": "def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnchargeBinarySensorEntityDescription, serial_number: str) -> None"
},
{
"docstring": "Return the state of the Encharge binary_sensor.",
... | 2 | null | Implement the Python class `EnvoyEnchargeBinarySensorEntity` described below.
Class description:
Defines an Encharge binary_sensor entity.
Method signatures and docstrings:
- def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnchargeBinarySensorEntityDescription, serial_number: str) -> None:... | Implement the Python class `EnvoyEnchargeBinarySensorEntity` described below.
Class description:
Defines an Encharge binary_sensor entity.
Method signatures and docstrings:
- def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnchargeBinarySensorEntityDescription, serial_number: str) -> None:... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class EnvoyEnchargeBinarySensorEntity:
"""Defines an Encharge binary_sensor entity."""
def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnchargeBinarySensorEntityDescription, serial_number: str) -> None:
"""Init the Encharge base entity."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnvoyEnchargeBinarySensorEntity:
"""Defines an Encharge binary_sensor entity."""
def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnchargeBinarySensorEntityDescription, serial_number: str) -> None:
"""Init the Encharge base entity."""
super().__init__(coordinato... | the_stack_v2_python_sparse | homeassistant/components/enphase_envoy/binary_sensor.py | home-assistant/core | train | 35,501 |
1875a85d9c666a213aee953439fe52d961adcdf5 | [
"if root.left:\n self.helper(result, root.left)\nif root.right:\n self.helper(result, root.right)\nresult.append(root.val)",
"result = []\nif not root:\n return result\nself.helper(result, root)\nreturn result"
] | <|body_start_0|>
if root.left:
self.helper(result, root.left)
if root.right:
self.helper(result, root.right)
result.append(root.val)
<|end_body_0|>
<|body_start_1|>
result = []
if not root:
return result
self.helper(result, root)
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def helper(self, result: List[int], root: TreeNode):
"""帮助方法 Args: result: 结果集 root: 根节点"""
<|body_0|>
def post_order_traversal(self, root: TreeNode) -> List[int]:
"""后序遍历 Args: res: 链表 root: 根节点"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_012131 | 1,876 | permissive | [
{
"docstring": "帮助方法 Args: result: 结果集 root: 根节点",
"name": "helper",
"signature": "def helper(self, result: List[int], root: TreeNode)"
},
{
"docstring": "后序遍历 Args: res: 链表 root: 根节点",
"name": "post_order_traversal",
"signature": "def post_order_traversal(self, root: TreeNode) -> List[i... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def helper(self, result: List[int], root: TreeNode): 帮助方法 Args: result: 结果集 root: 根节点
- def post_order_traversal(self, root: TreeNode) -> List[int]: 后序遍历 Args: res: 链表 root: 根节点 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def helper(self, result: List[int], root: TreeNode): 帮助方法 Args: result: 结果集 root: 根节点
- def post_order_traversal(self, root: TreeNode) -> List[int]: 后序遍历 Args: res: 链表 root: 根节点
... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def helper(self, result: List[int], root: TreeNode):
"""帮助方法 Args: result: 结果集 root: 根节点"""
<|body_0|>
def post_order_traversal(self, root: TreeNode) -> List[int]:
"""后序遍历 Args: res: 链表 root: 根节点"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def helper(self, result: List[int], root: TreeNode):
"""帮助方法 Args: result: 结果集 root: 根节点"""
if root.left:
self.helper(result, root.left)
if root.right:
self.helper(result, root.right)
result.append(root.val)
def post_order_traversal(self, ... | the_stack_v2_python_sparse | src/leetcodepython/tree/postorder_traversal_145.py | zhangyu345293721/leetcode | train | 101 | |
1b209fe72f984ff382d8da3ac02bcd9d6173e0b1 | [
"if isinstance(value, list):\n return [item['id'] for item in value]\nelse:\n raise ValueError('Unable to deserialize list reference: %s' % value)",
"if isinstance(value, list):\n return [{'id': item} for item in value]\nelse:\n raise ValueError('Unable to serialize list reference: %s' % value)"
] | <|body_start_0|>
if isinstance(value, list):
return [item['id'] for item in value]
else:
raise ValueError('Unable to deserialize list reference: %s' % value)
<|end_body_0|>
<|body_start_1|>
if isinstance(value, list):
return [{'id': item} for item in value]
... | A formatter used to serialize/deserialize list reference [{"id": "any-id"}] <-> ["any-id"], for example. | ListRef | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListRef:
"""A formatter used to serialize/deserialize list reference [{"id": "any-id"}] <-> ["any-id"], for example."""
def deserialize(cls, value):
"""Convert a list primitive to list reference"""
<|body_0|>
def serialize(cls, value):
"""Convert list reference t... | stack_v2_sparse_classes_36k_train_012132 | 3,502 | permissive | [
{
"docstring": "Convert a list primitive to list reference",
"name": "deserialize",
"signature": "def deserialize(cls, value)"
},
{
"docstring": "Convert list reference to list primitive",
"name": "serialize",
"signature": "def serialize(cls, value)"
}
] | 2 | null | Implement the Python class `ListRef` described below.
Class description:
A formatter used to serialize/deserialize list reference [{"id": "any-id"}] <-> ["any-id"], for example.
Method signatures and docstrings:
- def deserialize(cls, value): Convert a list primitive to list reference
- def serialize(cls, value): Con... | Implement the Python class `ListRef` described below.
Class description:
A formatter used to serialize/deserialize list reference [{"id": "any-id"}] <-> ["any-id"], for example.
Method signatures and docstrings:
- def deserialize(cls, value): Convert a list primitive to list reference
- def serialize(cls, value): Con... | 60d75438d71ffb7998f5dc407ffa890cc98d3171 | <|skeleton|>
class ListRef:
"""A formatter used to serialize/deserialize list reference [{"id": "any-id"}] <-> ["any-id"], for example."""
def deserialize(cls, value):
"""Convert a list primitive to list reference"""
<|body_0|>
def serialize(cls, value):
"""Convert list reference t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListRef:
"""A formatter used to serialize/deserialize list reference [{"id": "any-id"}] <-> ["any-id"], for example."""
def deserialize(cls, value):
"""Convert a list primitive to list reference"""
if isinstance(value, list):
return [item['id'] for item in value]
else:... | the_stack_v2_python_sparse | openstack/format.py | huaweicloudsdk/sdk-python | train | 20 |
09449c57a820da4e7c8a60100819edd0528199c5 | [
"self.args.findspec.iterator.number = self.MAX_FILES_TO_CHECK\nif self.args.findspec.path_glob:\n self.args.findspec.path_regex = self.args.findspec.path_glob.AsRegEx()\nself.CallClient(server_stubs.Find, self.args.findspec, next_state=self.StoreResults.__name__)",
"if not responses.success:\n raise IOError... | <|body_start_0|>
self.args.findspec.iterator.number = self.MAX_FILES_TO_CHECK
if self.args.findspec.path_glob:
self.args.findspec.path_regex = self.args.findspec.path_glob.AsRegEx()
self.CallClient(server_stubs.Find, self.args.findspec, next_state=self.StoreResults.__name__)
<|end_bo... | Find files on the client. The logic is: - Find files under "Path" - Filter for files with os.path.basename matching "Path Regular Expression" - Filter for files with sizes between min and max limits - Filter for files that contain "Data Regular Expression" in the first 1MB of file data - Return a StatEntry rdfvalue for... | FindFiles | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FindFiles:
"""Find files on the client. The logic is: - Find files under "Path" - Filter for files with os.path.basename matching "Path Regular Expression" - Filter for files with sizes between min and max limits - Filter for files that contain "Data Regular Expression" in the first 1MB of file d... | stack_v2_sparse_classes_36k_train_012133 | 3,095 | permissive | [
{
"docstring": "Issue the find request to the client.",
"name": "Start",
"signature": "def Start(self)"
},
{
"docstring": "Stores the results returned from the client.",
"name": "StoreResults",
"signature": "def StoreResults(self, responses)"
}
] | 2 | null | Implement the Python class `FindFiles` described below.
Class description:
Find files on the client. The logic is: - Find files under "Path" - Filter for files with os.path.basename matching "Path Regular Expression" - Filter for files with sizes between min and max limits - Filter for files that contain "Data Regular... | Implement the Python class `FindFiles` described below.
Class description:
Find files on the client. The logic is: - Find files under "Path" - Filter for files with os.path.basename matching "Path Regular Expression" - Filter for files with sizes between min and max limits - Filter for files that contain "Data Regular... | 44c0eb8c938302098ef7efae8cfd6b90bcfbb2d6 | <|skeleton|>
class FindFiles:
"""Find files on the client. The logic is: - Find files under "Path" - Filter for files with os.path.basename matching "Path Regular Expression" - Filter for files with sizes between min and max limits - Filter for files that contain "Data Regular Expression" in the first 1MB of file d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FindFiles:
"""Find files on the client. The logic is: - Find files under "Path" - Filter for files with os.path.basename matching "Path Regular Expression" - Filter for files with sizes between min and max limits - Filter for files that contain "Data Regular Expression" in the first 1MB of file data - Return ... | the_stack_v2_python_sparse | grr/server/grr_response_server/flows/general/find.py | google/grr | train | 4,683 |
0e734b47810b86e5da76e1dab6298abe0c24b0ab | [
"curr = head\nwhile True:\n if curr.child:\n curr = self.flatten_util(curr, curr.child)\n if curr.next:\n curr = curr.next\n else:\n break\ncurr.next = parent.next\nif parent.next:\n parent.next.prev = curr\nparent.next = head\nhead.prev = parent\nparent.child = None\nreturn head",
... | <|body_start_0|>
curr = head
while True:
if curr.child:
curr = self.flatten_util(curr, curr.child)
if curr.next:
curr = curr.next
else:
break
curr.next = parent.next
if parent.next:
parent.nex... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def flatten_util(self, parent, head):
""":type parent: Node :type head: Node :rtype: Node"""
<|body_0|>
def flatten(self, head):
""":type head: Node :rtype: Node"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
curr = head
while Tru... | stack_v2_sparse_classes_36k_train_012134 | 1,054 | no_license | [
{
"docstring": ":type parent: Node :type head: Node :rtype: Node",
"name": "flatten_util",
"signature": "def flatten_util(self, parent, head)"
},
{
"docstring": ":type head: Node :rtype: Node",
"name": "flatten",
"signature": "def flatten(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019311 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def flatten_util(self, parent, head): :type parent: Node :type head: Node :rtype: Node
- def flatten(self, head): :type head: Node :rtype: Node | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def flatten_util(self, parent, head): :type parent: Node :type head: Node :rtype: Node
- def flatten(self, head): :type head: Node :rtype: Node
<|skeleton|>
class Solution:
... | 959abf6f95b75540d19c699ada0253e047f9ec6f | <|skeleton|>
class Solution:
def flatten_util(self, parent, head):
""":type parent: Node :type head: Node :rtype: Node"""
<|body_0|>
def flatten(self, head):
""":type head: Node :rtype: Node"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def flatten_util(self, parent, head):
""":type parent: Node :type head: Node :rtype: Node"""
curr = head
while True:
if curr.child:
curr = self.flatten_util(curr, curr.child)
if curr.next:
curr = curr.next
el... | the_stack_v2_python_sparse | leet-flatten-multilinked-doubly-list/main.py | zohairajmal/competitive-programming-problems | train | 0 | |
6061407931ff3a37c9a11e4ce1f5e1dca0bb1096 | [
"super(DessedDNNEncoder, self).__init__()\nself.in_channels: int = in_channels\nself.cnn_channels: int = cnn_channels\nself.dnn = DepthWiseSeparableDNN(cnn_channels=cnn_channels, cnn_dropout=0.2, inner_kernel_size=inner_kernel_size, inner_padding=inner_padding)\nself.fc_audioset = Linear(last_dim, last_dim, bias=Tr... | <|body_start_0|>
super(DessedDNNEncoder, self).__init__()
self.in_channels: int = in_channels
self.cnn_channels: int = cnn_channels
self.dnn = DepthWiseSeparableDNN(cnn_channels=cnn_channels, cnn_dropout=0.2, inner_kernel_size=inner_kernel_size, inner_padding=inner_padding)
self.... | DessedDNNEncoder | [
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DessedDNNEncoder:
def __init__(self, in_channels: int, cnn_channels: int, inner_kernel_size: int, inner_padding: int, last_dim: int) -> None:
"""DessedDNNEncoder module. :param in_channels: Input channels. :type in_channels: int :param cnn_channels: Amount of output CNN channels. :type c... | stack_v2_sparse_classes_36k_train_012135 | 2,163 | permissive | [
{
"docstring": "DessedDNNEncoder module. :param in_channels: Input channels. :type in_channels: int :param cnn_channels: Amount of output CNN channels. :type cnn_channels: int :param inner_kernel_size: Kernel shape/size of the second convolution for DWS-DNN. :type inner_kernel_size: int :param inner_padding: In... | 2 | stack_v2_sparse_classes_30k_train_002364 | Implement the Python class `DessedDNNEncoder` described below.
Class description:
Implement the DessedDNNEncoder class.
Method signatures and docstrings:
- def __init__(self, in_channels: int, cnn_channels: int, inner_kernel_size: int, inner_padding: int, last_dim: int) -> None: DessedDNNEncoder module. :param in_cha... | Implement the Python class `DessedDNNEncoder` described below.
Class description:
Implement the DessedDNNEncoder class.
Method signatures and docstrings:
- def __init__(self, in_channels: int, cnn_channels: int, inner_kernel_size: int, inner_padding: int, last_dim: int) -> None: DessedDNNEncoder module. :param in_cha... | c78458ac0887851a743b7f47101b0fff97724b4f | <|skeleton|>
class DessedDNNEncoder:
def __init__(self, in_channels: int, cnn_channels: int, inner_kernel_size: int, inner_padding: int, last_dim: int) -> None:
"""DessedDNNEncoder module. :param in_channels: Input channels. :type in_channels: int :param cnn_channels: Amount of output CNN channels. :type c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DessedDNNEncoder:
def __init__(self, in_channels: int, cnn_channels: int, inner_kernel_size: int, inner_padding: int, last_dim: int) -> None:
"""DessedDNNEncoder module. :param in_channels: Input channels. :type in_channels: int :param cnn_channels: Amount of output CNN channels. :type cnn_channels: i... | the_stack_v2_python_sparse | modules/dessed_dnn_encoder.py | audio-captioning/wavetransformer | train | 0 | |
155a160a413c20fa2e8e58094b2d5329899945fb | [
"self.rawdata = {}\nf = open(filename, 'r')\nheader = f.readline().strip().split(',')\nfor line in f:\n items = line.strip().split(',')\n date = re.match('(\\\\d\\\\d\\\\d\\\\d)(\\\\d\\\\d)(\\\\d\\\\d)', items[header.index('DATE')])\n year = int(date.group(1))\n month = int(date.group(2))\n day = int... | <|body_start_0|>
self.rawdata = {}
f = open(filename, 'r')
header = f.readline().strip().split(',')
for line in f:
items = line.strip().split(',')
date = re.match('(\\d\\d\\d\\d)(\\d\\d)(\\d\\d)', items[header.index('DATE')])
year = int(date.group(1))
... | The collection of temperature records loaded from given csv file | Temperature | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Temperature:
"""The collection of temperature records loaded from given csv file"""
def __init__(self, filename):
"""Initialize a Temperature instance, which stores the temperature records loaded from a given csv file specified by filename. Args: filename: name of the csv file (str)"... | stack_v2_sparse_classes_36k_train_012136 | 15,625 | no_license | [
{
"docstring": "Initialize a Temperature instance, which stores the temperature records loaded from a given csv file specified by filename. Args: filename: name of the csv file (str)",
"name": "__init__",
"signature": "def __init__(self, filename)"
},
{
"docstring": "Get the daily temperatures f... | 3 | stack_v2_sparse_classes_30k_train_016179 | Implement the Python class `Temperature` described below.
Class description:
The collection of temperature records loaded from given csv file
Method signatures and docstrings:
- def __init__(self, filename): Initialize a Temperature instance, which stores the temperature records loaded from a given csv file specified... | Implement the Python class `Temperature` described below.
Class description:
The collection of temperature records loaded from given csv file
Method signatures and docstrings:
- def __init__(self, filename): Initialize a Temperature instance, which stores the temperature records loaded from a given csv file specified... | c1e18b39ecc6635c96a9f99709697e06f36e9762 | <|skeleton|>
class Temperature:
"""The collection of temperature records loaded from given csv file"""
def __init__(self, filename):
"""Initialize a Temperature instance, which stores the temperature records loaded from a given csv file specified by filename. Args: filename: name of the csv file (str)"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Temperature:
"""The collection of temperature records loaded from given csv file"""
def __init__(self, filename):
"""Initialize a Temperature instance, which stores the temperature records loaded from a given csv file specified by filename. Args: filename: name of the csv file (str)"""
se... | the_stack_v2_python_sparse | 6.0002PSET/2_ps5/ps5.py | elahea2020/6.00 | train | 0 |
3d8dfa00c3baea651281aaf933d336355769cf1a | [
"n = len(heights)\nright = [1] * n\nleft = [1] * n\nfor i in range(n - 2, -1, -1):\n if heights[i] > heights[i + 1]:\n continue\n else:\n j = i + 1\n while j < n and heights[i] <= heights[j]:\n j += right[j]\n right[i] = j - i\nfor i in range(1, n):\n if heights[i] < ... | <|body_start_0|>
n = len(heights)
right = [1] * n
left = [1] * n
for i in range(n - 2, -1, -1):
if heights[i] > heights[i + 1]:
continue
else:
j = i + 1
while j < n and heights[i] <= heights[j]:
j... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
<|body_0|>
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(heights... | stack_v2_sparse_classes_36k_train_012137 | 1,278 | no_license | [
{
"docstring": ":type heights: List[int] :rtype: int",
"name": "largestRectangleArea",
"signature": "def largestRectangleArea(self, heights)"
},
{
"docstring": ":type heights: List[int] :rtype: int",
"name": "largestRectangleArea",
"signature": "def largestRectangleArea(self, heights)"
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestRectangleArea(self, heights): :type heights: List[int] :rtype: int
- def largestRectangleArea(self, heights): :type heights: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestRectangleArea(self, heights): :type heights: List[int] :rtype: int
- def largestRectangleArea(self, heights): :type heights: List[int] :rtype: int
<|skeleton|>
class ... | 6fd7b1bea597867889b7a4ababfb54fa649a717c | <|skeleton|>
class Solution:
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
<|body_0|>
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
n = len(heights)
right = [1] * n
left = [1] * n
for i in range(n - 2, -1, -1):
if heights[i] > heights[i + 1]:
continue
else:
... | the_stack_v2_python_sparse | python/51-100/84. Largest Rectangle in Histogram.py | CrazyCoder4Carrot/leetcode | train | 3 | |
19790ca512da97ff895ec9509e019ea3bc47844d | [
"comp = GPSPhonePage(self.driver)\nlp = ListViewPhonePage(self.driver)\nname = 'GPS定位类型'\ncompname = 'GPS定位_名称'\nlp.open_fisrt_doc()\ntarget_element = comp.getcomp(compname)\ncomp.scroll_to_target_element(target_element)\ntype = target_element.get_attribute('moduletype')\nself.assertEqual(type, 'weixingpsfield', ms... | <|body_start_0|>
comp = GPSPhonePage(self.driver)
lp = ListViewPhonePage(self.driver)
name = 'GPS定位类型'
compname = 'GPS定位_名称'
lp.open_fisrt_doc()
target_element = comp.getcomp(compname)
comp.scroll_to_target_element(target_element)
type = target_element.get... | GPS定位控件测试 | GPSPhoneTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GPSPhoneTest:
"""GPS定位控件测试"""
def test_type_case(self):
"""GPS定位类型"""
<|body_0|>
def test_desription_case(self):
"""描述"""
<|body_1|>
def test_show_when_hide_case(self):
"""隐藏时显示值"""
<|body_2|>
def init(self):
"""所有测试"""
... | stack_v2_sparse_classes_36k_train_012138 | 2,178 | no_license | [
{
"docstring": "GPS定位类型",
"name": "test_type_case",
"signature": "def test_type_case(self)"
},
{
"docstring": "描述",
"name": "test_desription_case",
"signature": "def test_desription_case(self)"
},
{
"docstring": "隐藏时显示值",
"name": "test_show_when_hide_case",
"signature": "... | 4 | null | Implement the Python class `GPSPhoneTest` described below.
Class description:
GPS定位控件测试
Method signatures and docstrings:
- def test_type_case(self): GPS定位类型
- def test_desription_case(self): 描述
- def test_show_when_hide_case(self): 隐藏时显示值
- def init(self): 所有测试 | Implement the Python class `GPSPhoneTest` described below.
Class description:
GPS定位控件测试
Method signatures and docstrings:
- def test_type_case(self): GPS定位类型
- def test_desription_case(self): 描述
- def test_show_when_hide_case(self): 隐藏时显示值
- def init(self): 所有测试
<|skeleton|>
class GPSPhoneTest:
"""GPS定位控件测试"""
... | 78768989a79a14013b983024cf6e4838d51ed595 | <|skeleton|>
class GPSPhoneTest:
"""GPS定位控件测试"""
def test_type_case(self):
"""GPS定位类型"""
<|body_0|>
def test_desription_case(self):
"""描述"""
<|body_1|>
def test_show_when_hide_case(self):
"""隐藏时显示值"""
<|body_2|>
def init(self):
"""所有测试"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GPSPhoneTest:
"""GPS定位控件测试"""
def test_type_case(self):
"""GPS定位类型"""
comp = GPSPhonePage(self.driver)
lp = ListViewPhonePage(self.driver)
name = 'GPS定位类型'
compname = 'GPS定位_名称'
lp.open_fisrt_doc()
target_element = comp.getcomp(compname)
com... | the_stack_v2_python_sparse | test_case/running/phone/form/test_gps.py | pylk/pythonSelenium | train | 0 |
596bc8597536b9a9f1e62cedb9af4b39ee6b70e8 | [
"dp = [amount + 1] * (amount + 1)\ndp[0] = 0\nfor i in range(amount):\n for j in range(len(coins)):\n if i + coins[j] > amount:\n continue\n dp[i + coins[j]] = min(dp[i] + 1, dp[i + coins[j]])\nreturn dp[-1] if dp[-1] <= amount else -1",
"level = 0\nqueue = [amount]\ncoins = sorted(coi... | <|body_start_0|>
dp = [amount + 1] * (amount + 1)
dp[0] = 0
for i in range(amount):
for j in range(len(coins)):
if i + coins[j] > amount:
continue
dp[i + coins[j]] = min(dp[i] + 1, dp[i + coins[j]])
return dp[-1] if dp[-1] <... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def coinChange(self, coins, amount):
""":type coins: List[int] :type amount: int :rtype: int"""
<|body_0|>
def coinChange2(self, coins, amount):
""":type coins: List[int] :type amount: int :rtype: int :BFS solution"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_012139 | 2,496 | permissive | [
{
"docstring": ":type coins: List[int] :type amount: int :rtype: int",
"name": "coinChange",
"signature": "def coinChange(self, coins, amount)"
},
{
"docstring": ":type coins: List[int] :type amount: int :rtype: int :BFS solution",
"name": "coinChange2",
"signature": "def coinChange2(sel... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def coinChange(self, coins, amount): :type coins: List[int] :type amount: int :rtype: int
- def coinChange2(self, coins, amount): :type coins: List[int] :type amount: int :rtype:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def coinChange(self, coins, amount): :type coins: List[int] :type amount: int :rtype: int
- def coinChange2(self, coins, amount): :type coins: List[int] :type amount: int :rtype:... | aec1ddd0c51b619c1bae1e05f940d9ed587aa82f | <|skeleton|>
class Solution:
def coinChange(self, coins, amount):
""":type coins: List[int] :type amount: int :rtype: int"""
<|body_0|>
def coinChange2(self, coins, amount):
""":type coins: List[int] :type amount: int :rtype: int :BFS solution"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def coinChange(self, coins, amount):
""":type coins: List[int] :type amount: int :rtype: int"""
dp = [amount + 1] * (amount + 1)
dp[0] = 0
for i in range(amount):
for j in range(len(coins)):
if i + coins[j] > amount:
con... | the_stack_v2_python_sparse | Python/leetcode/coinChange.py | darrencheng0817/AlgorithmLearning | train | 2 | |
466171e0da9874e9635228007ce5ab28b604010e | [
"self.np_shape = params['shape'][::-1]\nself.np_dtype = params['dtype']\nself.seed = params['seed']\nself.rng = np.random.default_rng(self.seed)",
"probabilities = [1.0 - settings.FLIP_PROBABILITY, settings.FLIP_PROBABILITY]\na = self.rng.choice([0, 1], p=probabilities, size=self.np_shape)\na = np.array(a, dtype=... | <|body_start_0|>
self.np_shape = params['shape'][::-1]
self.np_dtype = params['dtype']
self.seed = params['seed']
self.rng = np.random.default_rng(self.seed)
<|end_body_0|>
<|body_start_1|>
probabilities = [1.0 - settings.FLIP_PROBABILITY, settings.FLIP_PROBABILITY]
a = ... | Class defining the random flip implementation. | RandomFlipFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomFlipFunction:
"""Class defining the random flip implementation."""
def __init__(self, params):
""":params params: dictionary of params conatining shape: output shape of this class. dtype: output dtype of this class. seed: seed to be used for randomization."""
<|body_0|>... | stack_v2_sparse_classes_36k_train_012140 | 7,328 | no_license | [
{
"docstring": ":params params: dictionary of params conatining shape: output shape of this class. dtype: output dtype of this class. seed: seed to be used for randomization.",
"name": "__init__",
"signature": "def __init__(self, params)"
},
{
"docstring": ":returns : random flip values calculat... | 2 | null | Implement the Python class `RandomFlipFunction` described below.
Class description:
Class defining the random flip implementation.
Method signatures and docstrings:
- def __init__(self, params): :params params: dictionary of params conatining shape: output shape of this class. dtype: output dtype of this class. seed:... | Implement the Python class `RandomFlipFunction` described below.
Class description:
Class defining the random flip implementation.
Method signatures and docstrings:
- def __init__(self, params): :params params: dictionary of params conatining shape: output shape of this class. dtype: output dtype of this class. seed:... | 3ca77c4a5fb62c60372e8a2839b1fccc3c4e4212 | <|skeleton|>
class RandomFlipFunction:
"""Class defining the random flip implementation."""
def __init__(self, params):
""":params params: dictionary of params conatining shape: output shape of this class. dtype: output dtype of this class. seed: seed to be used for randomization."""
<|body_0|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomFlipFunction:
"""Class defining the random flip implementation."""
def __init__(self, params):
""":params params: dictionary of params conatining shape: output shape of this class. dtype: output dtype of this class. seed: seed to be used for randomization."""
self.np_shape = params[... | the_stack_v2_python_sparse | TensorFlow/computer_vision/common/resnet_media_pipe.py | HabanaAI/Model-References | train | 108 |
e492a409b226a8754f0fd898e3ec2bcea3d174a1 | [
"userp = request.user\nserializer = EditProfile(instance=userp, data=request.data)\nif serializer.is_valid():\n print('serializer.data:', serializer.validated_data)\n serializer.save()\n return Response({'message': 'edit profile successfully!'}, status=status.HTTP_200_OK)\nelse:\n return Response(serial... | <|body_start_0|>
userp = request.user
serializer = EditProfile(instance=userp, data=request.data)
if serializer.is_valid():
print('serializer.data:', serializer.validated_data)
serializer.save()
return Response({'message': 'edit profile successfully!'}, status... | EditProfileItem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EditProfileItem:
def put(self, request):
"""edit profile"""
<|body_0|>
def get(self, request):
"""get users list:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
userp = request.user
serializer = EditProfile(instance=userp, data=request.data... | stack_v2_sparse_classes_36k_train_012141 | 10,046 | no_license | [
{
"docstring": "edit profile",
"name": "put",
"signature": "def put(self, request)"
},
{
"docstring": "get users list:",
"name": "get",
"signature": "def get(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002978 | Implement the Python class `EditProfileItem` described below.
Class description:
Implement the EditProfileItem class.
Method signatures and docstrings:
- def put(self, request): edit profile
- def get(self, request): get users list: | Implement the Python class `EditProfileItem` described below.
Class description:
Implement the EditProfileItem class.
Method signatures and docstrings:
- def put(self, request): edit profile
- def get(self, request): get users list:
<|skeleton|>
class EditProfileItem:
def put(self, request):
"""edit pro... | ee8b9d7d754849e2b2b9d86750099563fbdfc806 | <|skeleton|>
class EditProfileItem:
def put(self, request):
"""edit profile"""
<|body_0|>
def get(self, request):
"""get users list:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EditProfileItem:
def put(self, request):
"""edit profile"""
userp = request.user
serializer = EditProfile(instance=userp, data=request.data)
if serializer.is_valid():
print('serializer.data:', serializer.validated_data)
serializer.save()
retu... | the_stack_v2_python_sparse | HW2/chat_project/users1/views.py | rezvan-hb/django | train | 0 | |
56e60fca5935ad62b797c8de1cf0bf50e3dff4b8 | [
"super(TransformerEncoder, self).__init__()\nself.layers = nn.ModuleList([self.SubLayer(**kargs) for _ in range(num_layers)])\nself.norm = nn.LayerNorm(kargs['model_size'], eps=1e-06)",
"output = x\nif seq_mask is None:\n atte_mask_out = None\nelse:\n atte_mask_out = (seq_mask == 0)[:, None, :]\n seq_mas... | <|body_start_0|>
super(TransformerEncoder, self).__init__()
self.layers = nn.ModuleList([self.SubLayer(**kargs) for _ in range(num_layers)])
self.norm = nn.LayerNorm(kargs['model_size'], eps=1e-06)
<|end_body_0|>
<|body_start_1|>
output = x
if seq_mask is None:
atte_... | transformer的encoder模块，不包含embedding层 | TransformerEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerEncoder:
"""transformer的encoder模块，不包含embedding层"""
def __init__(self, num_layers, **kargs):
""":param int num_layers: transformer的层数 :param int model_size: 输入维度的大小。同时也是输出维度的大小。 :param int inner_size: FFN层的hidden大小 :param int key_size: 每个head的维度大小。 :param int value_size: 每个... | stack_v2_sparse_classes_36k_train_012142 | 3,009 | permissive | [
{
"docstring": ":param int num_layers: transformer的层数 :param int model_size: 输入维度的大小。同时也是输出维度的大小。 :param int inner_size: FFN层的hidden大小 :param int key_size: 每个head的维度大小。 :param int value_size: 每个head中value的维度。 :param int num_head: head的数量。 :param float dropout: dropout概率. Default: 0.1",
"name": "__init__",
... | 2 | stack_v2_sparse_classes_30k_train_007444 | Implement the Python class `TransformerEncoder` described below.
Class description:
transformer的encoder模块，不包含embedding层
Method signatures and docstrings:
- def __init__(self, num_layers, **kargs): :param int num_layers: transformer的层数 :param int model_size: 输入维度的大小。同时也是输出维度的大小。 :param int inner_size: FFN层的hidden大小 :p... | Implement the Python class `TransformerEncoder` described below.
Class description:
transformer的encoder模块，不包含embedding层
Method signatures and docstrings:
- def __init__(self, num_layers, **kargs): :param int num_layers: transformer的层数 :param int model_size: 输入维度的大小。同时也是输出维度的大小。 :param int inner_size: FFN层的hidden大小 :p... | dffc7a06cdbff2671a3ca73d2398159d91a4a7db | <|skeleton|>
class TransformerEncoder:
"""transformer的encoder模块，不包含embedding层"""
def __init__(self, num_layers, **kargs):
""":param int num_layers: transformer的层数 :param int model_size: 输入维度的大小。同时也是输出维度的大小。 :param int inner_size: FFN层的hidden大小 :param int key_size: 每个head的维度大小。 :param int value_size: 每个... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransformerEncoder:
"""transformer的encoder模块，不包含embedding层"""
def __init__(self, num_layers, **kargs):
""":param int num_layers: transformer的层数 :param int model_size: 输入维度的大小。同时也是输出维度的大小。 :param int inner_size: FFN层的hidden大小 :param int key_size: 每个head的维度大小。 :param int value_size: 每个head中value的维度... | the_stack_v2_python_sparse | phenobert/utils/fastNLP/modules/encoder/transformer.py | TianlabTech/PhenoBERT | train | 2 |
4d9839bde36fff5c4027e394a82c5f4b1e52fdba | [
"def backTrack(res, nums, tmp, start):\n if len(tmp) > 0:\n t = tmp.copy()\n res.append(t)\n for i in range(start, len(nums)):\n tmp.append(nums[i])\n backTrack(res, nums, tmp, i + 1)\n tmp.pop()\nt = [[]]\nres = [[]]\ntmp = []\ndic = {}\nnums.sort()\nbackTrack(t, nums, tmp,... | <|body_start_0|>
def backTrack(res, nums, tmp, start):
if len(tmp) > 0:
t = tmp.copy()
res.append(t)
for i in range(start, len(nums)):
tmp.append(nums[i])
backTrack(res, nums, tmp, i + 1)
tmp.pop()
t ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subsetsWithDup(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def subsetsWithDup0(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def backTrack(... | stack_v2_sparse_classes_36k_train_012143 | 1,933 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "subsetsWithDup",
"signature": "def subsetsWithDup(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "subsetsWithDup0",
"signature": "def subsetsWithDup0(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009135 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsetsWithDup(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def subsetsWithDup0(self, nums): :type nums: List[int] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsetsWithDup(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def subsetsWithDup0(self, nums): :type nums: List[int] :rtype: List[List[int]]
<|skeleton|>
class... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def subsetsWithDup(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def subsetsWithDup0(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def subsetsWithDup(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
def backTrack(res, nums, tmp, start):
if len(tmp) > 0:
t = tmp.copy()
res.append(t)
for i in range(start, len(nums)):
tmp.append... | the_stack_v2_python_sparse | PythonCode/src/0090_Subsets_II.py | oneyuan/CodeforFun | train | 0 | |
15df0facc0acfb61e4cda22bcff81496bf47557b | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ApplicationTemplate()",
"from .entity import Entity\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {'categories': lambda n: setattr(self, 'categories', n.get_collection_of_primitive_values(str)), 'description':... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ApplicationTemplate()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .entity import Entity
fields: Dict[str, Callable[[Any], None]] = {'categories': lambda n: se... | ApplicationTemplate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApplicationTemplate:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ApplicationTemplate:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ob... | stack_v2_sparse_classes_36k_train_012144 | 4,422 | 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: ApplicationTemplate",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator... | 3 | null | Implement the Python class `ApplicationTemplate` described below.
Class description:
Implement the ApplicationTemplate class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ApplicationTemplate: Creates a new instance of the appropriate class based on d... | Implement the Python class `ApplicationTemplate` described below.
Class description:
Implement the ApplicationTemplate class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ApplicationTemplate: Creates a new instance of the appropriate class based on d... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ApplicationTemplate:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ApplicationTemplate:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ob... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ApplicationTemplate:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ApplicationTemplate:
"""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: ... | the_stack_v2_python_sparse | msgraph/generated/models/application_template.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
ccfbaee071c177ed75f739e748ea65bcc7d53700 | [
"if len(word) == k:\n return True\nif row < 0 or row >= row_max or col < 0 or (col >= col_max):\n return False\nif board[row][col] != word[k]:\n return False\nletter = board[row][col]\nboard[row][col] = None\nfor i, j in [[0, 1], [1, 0], [0, -1], [-1, 0]]:\n if self.recur(board, word, row_max, col_max, ... | <|body_start_0|>
if len(word) == k:
return True
if row < 0 or row >= row_max or col < 0 or (col >= col_max):
return False
if board[row][col] != word[k]:
return False
letter = board[row][col]
board[row][col] = None
for i, j in [[0, 1], [... | solution | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""solution"""
def recur(self, board: List[List[str]], word: str, row_max: int, col_max: int, row: int, col: int, k: int) -> bool:
"""recur Parameters ---------- board : List[List[str]] characters board word : str word row_max : int number of rows col_max : int number of co... | stack_v2_sparse_classes_36k_train_012145 | 2,889 | no_license | [
{
"docstring": "recur Parameters ---------- board : List[List[str]] characters board word : str word row_max : int number of rows col_max : int number of columns row : int current row col : int current column k : int index of letter in word Returns ------- bool result",
"name": "recur",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_train_004092 | Implement the Python class `Solution` described below.
Class description:
solution
Method signatures and docstrings:
- def recur(self, board: List[List[str]], word: str, row_max: int, col_max: int, row: int, col: int, k: int) -> bool: recur Parameters ---------- board : List[List[str]] characters board word : str wor... | Implement the Python class `Solution` described below.
Class description:
solution
Method signatures and docstrings:
- def recur(self, board: List[List[str]], word: str, row_max: int, col_max: int, row: int, col: int, k: int) -> bool: recur Parameters ---------- board : List[List[str]] characters board word : str wor... | 86766a73a617086784ad777906a2782e39fe262e | <|skeleton|>
class Solution:
"""solution"""
def recur(self, board: List[List[str]], word: str, row_max: int, col_max: int, row: int, col: int, k: int) -> bool:
"""recur Parameters ---------- board : List[List[str]] characters board word : str word row_max : int number of rows col_max : int number of co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""solution"""
def recur(self, board: List[List[str]], word: str, row_max: int, col_max: int, row: int, col: int, k: int) -> bool:
"""recur Parameters ---------- board : List[List[str]] characters board word : str word row_max : int number of rows col_max : int number of columns row : i... | the_stack_v2_python_sparse | src/medium/word_search.py | albul-k/leetcode | train | 0 |
e1618cadfd51887f36816ee4dfeabc54fffd3178 | [
"dummy, self.fset = _readFunction(filename, func_name, 0)\nself.x = self.fset.x\nself.y = self.fset.y\nself.length = len(self.x)",
"if x <= 0:\n return self.y[0]\nif x >= 1:\n return self.y[self.length - 1]\nindex = 0\nfor i, this in enumerate(self.x):\n if x > this:\n index = i\n else:\n ... | <|body_start_0|>
dummy, self.fset = _readFunction(filename, func_name, 0)
self.x = self.fset.x
self.y = self.fset.y
self.length = len(self.x)
<|end_body_0|>
<|body_start_1|>
if x <= 0:
return self.y[0]
if x >= 1:
return self.y[self.length - 1]
... | Read a L-studio functions.fset file, extract a func_name and returns interpolated values. :Example: Starting from a file like:: funcgalleryver 1 1 items: 2 fver 1 1 name: _fruit_mass samples: 100 flip: off points: 4 0.000000 0.000000 0.586364 0.000000 0.586364 0.250000 1.000000 0.250000 fver 1 1 name: _leaf_area sample... | ReadFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReadFunction:
"""Read a L-studio functions.fset file, extract a func_name and returns interpolated values. :Example: Starting from a file like:: funcgalleryver 1 1 items: 2 fver 1 1 name: _fruit_mass samples: 100 flip: off points: 4 0.000000 0.000000 0.586364 0.000000 0.586364 0.250000 1.000000 0... | stack_v2_sparse_classes_36k_train_012146 | 5,835 | no_license | [
{
"docstring": ":param filename: the filename with the extension :param func_name: the function name to extract",
"name": "__init__",
"signature": "def __init__(self, filename, func_name)"
},
{
"docstring": "returns the y values corresponding to x Use scipy and its simplest 1D interpolation meth... | 2 | stack_v2_sparse_classes_30k_val_000577 | Implement the Python class `ReadFunction` described below.
Class description:
Read a L-studio functions.fset file, extract a func_name and returns interpolated values. :Example: Starting from a file like:: funcgalleryver 1 1 items: 2 fver 1 1 name: _fruit_mass samples: 100 flip: off points: 4 0.000000 0.000000 0.58636... | Implement the Python class `ReadFunction` described below.
Class description:
Read a L-studio functions.fset file, extract a func_name and returns interpolated values. :Example: Starting from a file like:: funcgalleryver 1 1 items: 2 fver 1 1 name: _fruit_mass samples: 100 flip: off points: 4 0.000000 0.000000 0.58636... | 090370f08271455f6c1b89592a0b7eb18212a6c9 | <|skeleton|>
class ReadFunction:
"""Read a L-studio functions.fset file, extract a func_name and returns interpolated values. :Example: Starting from a file like:: funcgalleryver 1 1 items: 2 fver 1 1 name: _fruit_mass samples: 100 flip: off points: 4 0.000000 0.000000 0.586364 0.000000 0.586364 0.250000 1.000000 0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReadFunction:
"""Read a L-studio functions.fset file, extract a func_name and returns interpolated values. :Example: Starting from a file like:: funcgalleryver 1 1 items: 2 fver 1 1 name: _fruit_mass samples: 100 flip: off points: 4 0.000000 0.000000 0.586364 0.000000 0.586364 0.250000 1.000000 0.250000 fver ... | the_stack_v2_python_sparse | src/stocatree/tools/read_function.py | junqi108/MAppleT | train | 0 |
70a7f1a0602d48a5278caf03dbcb2a215bd1d01b | [
"self.morpho = Morpho.load(dictMorpho)\nif self.morpho is None:\n raise LemmatizerException('Chybný DICT.')\nself.tokenizer = self.morpho.newTokenizer()\nif self.tokenizer is None:\n raise LemmatizerException('Není definovaný tokenizer pro dodaný model.')\nself.forms = Forms()\nself.tokens = TokenRanges()\nse... | <|body_start_0|>
self.morpho = Morpho.load(dictMorpho)
if self.morpho is None:
raise LemmatizerException('Chybný DICT.')
self.tokenizer = self.morpho.newTokenizer()
if self.tokenizer is None:
raise LemmatizerException('Není definovaný tokenizer pro dodaný model.')... | Třída pro lemmatizaci slov a extrakci vybraných slovních druhů. Používá nástroj morphodita. Značky slovních druhů: N - 1 A - 2 P - 3 C - 4 V - 5 D - 6 R - 7 J - 8 T - 9 I - 10 Z - Symboly X - Neznámé | Lemmatizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Lemmatizer:
"""Třída pro lemmatizaci slov a extrakci vybraných slovních druhů. Používá nástroj morphodita. Značky slovních druhů: N - 1 A - 2 P - 3 C - 4 V - 5 D - 6 R - 7 J - 8 T - 9 I - 10 Z - Symboly X - Neznámé"""
def __init__(self, dictMorpho):
"""Konstrukce objektu. :param dict... | stack_v2_sparse_classes_36k_train_012147 | 35,729 | no_license | [
{
"docstring": "Konstrukce objektu. :param dictMorpho: Cesta k souboru pro dictMorpho morphodity. :raises LemmatizerException: Když není definovaný tokenizer pro dodaný model. Nebo nevalidní slovník.",
"name": "__init__",
"signature": "def __init__(self, dictMorpho)"
},
{
"docstring": "Vrací lem... | 5 | stack_v2_sparse_classes_30k_train_006353 | Implement the Python class `Lemmatizer` described below.
Class description:
Třída pro lemmatizaci slov a extrakci vybraných slovních druhů. Používá nástroj morphodita. Značky slovních druhů: N - 1 A - 2 P - 3 C - 4 V - 5 D - 6 R - 7 J - 8 T - 9 I - 10 Z - Symboly X - Neznámé
Method signatures and docstrings:
- def __... | Implement the Python class `Lemmatizer` described below.
Class description:
Třída pro lemmatizaci slov a extrakci vybraných slovních druhů. Používá nástroj morphodita. Značky slovních druhů: N - 1 A - 2 P - 3 C - 4 V - 5 D - 6 R - 7 J - 8 T - 9 I - 10 Z - Symboly X - Neznámé
Method signatures and docstrings:
- def __... | 4e5395875d60ed3b138922d1100f6a4e05ac60e7 | <|skeleton|>
class Lemmatizer:
"""Třída pro lemmatizaci slov a extrakci vybraných slovních druhů. Používá nástroj morphodita. Značky slovních druhů: N - 1 A - 2 P - 3 C - 4 V - 5 D - 6 R - 7 J - 8 T - 9 I - 10 Z - Symboly X - Neznámé"""
def __init__(self, dictMorpho):
"""Konstrukce objektu. :param dict... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Lemmatizer:
"""Třída pro lemmatizaci slov a extrakci vybraných slovních druhů. Používá nástroj morphodita. Značky slovních druhů: N - 1 A - 2 P - 3 C - 4 V - 5 D - 6 R - 7 J - 8 T - 9 I - 10 Z - Symboly X - Neznámé"""
def __init__(self, dictMorpho):
"""Konstrukce objektu. :param dictMorpho: Cesta... | the_stack_v2_python_sparse | CPKclassifierPack/preprocessing/Preprocessing.py | KNOT-FIT-BUT/CPKclassifier | train | 1 |
4dc032b772ae863399a6b8ff20a932cdbf18783a | [
"args = self.parser.parse_args()\ndata = self.build_data(args=args, collection='asset_site')\nreturn data",
"args = self.parse_args(add_site_fields)\nsite = args.pop('site')\nscope_id = args.pop('scope_id')\nurl = utils.normal_url(site).strip('/')\nif not url:\n return utils.build_ret(ErrorMsg.DomainInvalid, {... | <|body_start_0|>
args = self.parser.parse_args()
data = self.build_data(args=args, collection='asset_site')
return data
<|end_body_0|>
<|body_start_1|>
args = self.parse_args(add_site_fields)
site = args.pop('site')
scope_id = args.pop('scope_id')
url = utils.nor... | ARLAssetSite | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ARLAssetSite:
def get(self):
"""资产站点信息查询"""
<|body_0|>
def post(self):
"""添加站点到资产组中"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args = self.parser.parse_args()
data = self.build_data(args=args, collection='asset_site')
return dat... | stack_v2_sparse_classes_36k_train_012148 | 8,529 | no_license | [
{
"docstring": "资产站点信息查询",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "添加站点到资产组中",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019469 | Implement the Python class `ARLAssetSite` described below.
Class description:
Implement the ARLAssetSite class.
Method signatures and docstrings:
- def get(self): 资产站点信息查询
- def post(self): 添加站点到资产组中 | Implement the Python class `ARLAssetSite` described below.
Class description:
Implement the ARLAssetSite class.
Method signatures and docstrings:
- def get(self): 资产站点信息查询
- def post(self): 添加站点到资产组中
<|skeleton|>
class ARLAssetSite:
def get(self):
"""资产站点信息查询"""
<|body_0|>
def post(self):
... | 5ca64806252b9e7e6d2b31a6bfaeecbfdc4baf06 | <|skeleton|>
class ARLAssetSite:
def get(self):
"""资产站点信息查询"""
<|body_0|>
def post(self):
"""添加站点到资产组中"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ARLAssetSite:
def get(self):
"""资产站点信息查询"""
args = self.parser.parse_args()
data = self.build_data(args=args, collection='asset_site')
return data
def post(self):
"""添加站点到资产组中"""
args = self.parse_args(add_site_fields)
site = args.pop('site')
... | the_stack_v2_python_sparse | app/routes/assetSite.py | QmF0c3UK/ARL | train | 0 | |
0ff5024261af037006235a72cc02bc4e6e1c8a84 | [
"result_set = np.array([])\ndistinct_documents = list(set([(x['year'], x['document_name']) for x in dataset]))\nfor year, document in distinct_documents:\n items = [x['data'] for x in dataset if x['year'] == year and x['document_name'] == document]\n topic_ids = [x['topic_id'] for x in items[0]]\n weights ... | <|body_start_0|>
result_set = np.array([])
distinct_documents = list(set([(x['year'], x['document_name']) for x in dataset]))
for year, document in distinct_documents:
items = [x['data'] for x in dataset if x['year'] == year and x['document_name'] == document]
topic_ids =... | Reduces a composition file by adding all items, i.e. splitted documents or rows in the file, that belongs to the same document into a single items. | CompositionDocumentReducer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompositionDocumentReducer:
"""Reduces a composition file by adding all items, i.e. splitted documents or rows in the file, that belongs to the same document into a single items."""
def compute(self, dataset, threshold=0.0):
"""Compute a new composition data set by an addative reduce... | stack_v2_sparse_classes_36k_train_012149 | 13,916 | no_license | [
{
"docstring": "Compute a new composition data set by an addative reduce of all items that belongs to the same document",
"name": "compute",
"signature": "def compute(self, dataset, threshold=0.0)"
},
{
"docstring": "Writes dataset into a semicolon separated UTF-8 encoded text file using regiona... | 2 | stack_v2_sparse_classes_30k_train_002328 | Implement the Python class `CompositionDocumentReducer` described below.
Class description:
Reduces a composition file by adding all items, i.e. splitted documents or rows in the file, that belongs to the same document into a single items.
Method signatures and docstrings:
- def compute(self, dataset, threshold=0.0):... | Implement the Python class `CompositionDocumentReducer` described below.
Class description:
Reduces a composition file by adding all items, i.e. splitted documents or rows in the file, that belongs to the same document into a single items.
Method signatures and docstrings:
- def compute(self, dataset, threshold=0.0):... | 32fc444ed11649a948a7bf59653ec792396f06e3 | <|skeleton|>
class CompositionDocumentReducer:
"""Reduces a composition file by adding all items, i.e. splitted documents or rows in the file, that belongs to the same document into a single items."""
def compute(self, dataset, threshold=0.0):
"""Compute a new composition data set by an addative reduce... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompositionDocumentReducer:
"""Reduces a composition file by adding all items, i.e. splitted documents or rows in the file, that belongs to the same document into a single items."""
def compute(self, dataset, threshold=0.0):
"""Compute a new composition data set by an addative reduce of all items... | the_stack_v2_python_sparse | pending_deletes/topic_modelling/topic_co_occurrence.py | humlab/text_analytic_tools | train | 2 |
9b17a340886e5d9b2c7586617e54a61bbf434be3 | [
"request_new = clone_request(request, 'GET')\ndata = QueryDict('', mutable=True)\nparams = dict(request.GET.items())\nif 'u_id' in params:\n data['user_id'] = params['u_id']\nif 'p_id' in params:\n data['booking_ref'] = params.get('p_id')\nif 'pagination' in params:\n data['page_size'] = params['pagination... | <|body_start_0|>
request_new = clone_request(request, 'GET')
data = QueryDict('', mutable=True)
params = dict(request.GET.items())
if 'u_id' in params:
data['user_id'] = params['u_id']
if 'p_id' in params:
data['booking_ref'] = params.get('p_id')
i... | My Bookings Backward compatibility viewset. * Requires token for verification of the user. | MyBookingsBackwardViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyBookingsBackwardViewSet:
"""My Bookings Backward compatibility viewset. * Requires token for verification of the user."""
def clone_search_booking_request(self, request):
"""Clone request searchbookingv4."""
<|body_0|>
def list(self, request, *args, **kwargs):
... | stack_v2_sparse_classes_36k_train_012150 | 19,225 | no_license | [
{
"docstring": "Clone request searchbookingv4.",
"name": "clone_search_booking_request",
"signature": "def clone_search_booking_request(self, request)"
},
{
"docstring": "Search booking v4. Args: request: version: *args: **kwargs: Returns:",
"name": "list",
"signature": "def list(self, r... | 2 | stack_v2_sparse_classes_30k_train_002875 | Implement the Python class `MyBookingsBackwardViewSet` described below.
Class description:
My Bookings Backward compatibility viewset. * Requires token for verification of the user.
Method signatures and docstrings:
- def clone_search_booking_request(self, request): Clone request searchbookingv4.
- def list(self, req... | Implement the Python class `MyBookingsBackwardViewSet` described below.
Class description:
My Bookings Backward compatibility viewset. * Requires token for verification of the user.
Method signatures and docstrings:
- def clone_search_booking_request(self, request): Clone request searchbookingv4.
- def list(self, req... | 26ca47c726f2c38211247a41d294e38a67cecb7f | <|skeleton|>
class MyBookingsBackwardViewSet:
"""My Bookings Backward compatibility viewset. * Requires token for verification of the user."""
def clone_search_booking_request(self, request):
"""Clone request searchbookingv4."""
<|body_0|>
def list(self, request, *args, **kwargs):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyBookingsBackwardViewSet:
"""My Bookings Backward compatibility viewset. * Requires token for verification of the user."""
def clone_search_booking_request(self, request):
"""Clone request searchbookingv4."""
request_new = clone_request(request, 'GET')
data = QueryDict('', mutabl... | the_stack_v2_python_sparse | depot/apps/apis/my_bookings/views.py | rsenwar/depot | train | 0 |
e28d554447a8898c872e589129b2ca698eae1bf8 | [
"n = len(nums)\nif n <= 0:\n return 0\nnCurSum, nGreatestSum = (0, float('-inf'))\nfor i in range(n):\n if nCurSum <= 0:\n nCurSum = nums[i]\n else:\n nCurSum += nums[i]\n if nCurSum > nGreatestSum:\n nGreatestSum = nCurSum\nreturn nGreatestSum",
"n = len(nums)\nif n <= 0:\n re... | <|body_start_0|>
n = len(nums)
if n <= 0:
return 0
nCurSum, nGreatestSum = (0, float('-inf'))
for i in range(n):
if nCurSum <= 0:
nCurSum = nums[i]
else:
nCurSum += nums[i]
if nCurSum > nGreatestSum:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray(self, nums: List[int]) -> int:
"""分析规律：贪心"""
<|body_0|>
def maxSubArray1(self, nums: List[int]) -> int:
"""状态转移方程：dp[i] 的值代表 nums 前 i 个数字的最大子数组和 if nums[i] > nums[i-1], dp[i] = max(dp[i], dp[j] + 1)"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_012151 | 2,099 | permissive | [
{
"docstring": "分析规律：贪心",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums: List[int]) -> int"
},
{
"docstring": "状态转移方程：dp[i] 的值代表 nums 前 i 个数字的最大子数组和 if nums[i] > nums[i-1], dp[i] = max(dp[i], dp[j] + 1)",
"name": "maxSubArray1",
"signature": "def maxSubArray1(self, nums... | 2 | stack_v2_sparse_classes_30k_train_002828 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums: List[int]) -> int: 分析规律：贪心
- def maxSubArray1(self, nums: List[int]) -> int: 状态转移方程：dp[i] 的值代表 nums 前 i 个数字的最大子数组和 if nums[i] > nums[i-1], dp[i] = max... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums: List[int]) -> int: 分析规律：贪心
- def maxSubArray1(self, nums: List[int]) -> int: 状态转移方程：dp[i] 的值代表 nums 前 i 个数字的最大子数组和 if nums[i] > nums[i-1], dp[i] = max... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def maxSubArray(self, nums: List[int]) -> int:
"""分析规律：贪心"""
<|body_0|>
def maxSubArray1(self, nums: List[int]) -> int:
"""状态转移方程：dp[i] 的值代表 nums 前 i 个数字的最大子数组和 if nums[i] > nums[i-1], dp[i] = max(dp[i], dp[j] + 1)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray(self, nums: List[int]) -> int:
"""分析规律：贪心"""
n = len(nums)
if n <= 0:
return 0
nCurSum, nGreatestSum = (0, float('-inf'))
for i in range(n):
if nCurSum <= 0:
nCurSum = nums[i]
else:
... | the_stack_v2_python_sparse | lcof/42-lian-xu-zi-shu-zu-de-zui-da-he-lcof.py | yuenliou/leetcode | train | 0 | |
608e07310af9aa3571de4855f3142bdc8424630a | [
"tm = TransactionManager()\ntm.retry_attempt_count = 1\nself.request.update(request=self.make_faux_request(tm=tm))\nwith tm:\n return self.run(*args, **kwargs)",
"if self.request.is_eager:\n return self.exec_eager(*args, **kwargs)\nrequest = self.get_request()\ntask = self\ntry:\n\n @retryable(tm=request... | <|body_start_0|>
tm = TransactionManager()
tm.retry_attempt_count = 1
self.request.update(request=self.make_faux_request(tm=tm))
with tm:
return self.run(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
if self.request.is_eager:
return self.exec_eager(*ar... | Celery task that commits all the work at the end of the task using transaction manager commit. A base class to be used with :py:meth:`celery.Celery.task` function decorator. Automatically commits all the work at the end of the task. In the case of transaction conflict, the task will rerun based on :func:`pyramid_tm.tm_... | RetryableTransactionTask | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RetryableTransactionTask:
"""Celery task that commits all the work at the end of the task using transaction manager commit. A base class to be used with :py:meth:`celery.Celery.task` function decorator. Automatically commits all the work at the end of the task. In the case of transaction conflict... | stack_v2_sparse_classes_36k_train_012152 | 11,925 | permissive | [
{
"docstring": "Run transaction aware task in eager mode.",
"name": "exec_eager",
"signature": "def exec_eager(self, *args, **kwargs)"
},
{
"docstring": "Call Celery task and insert request argument.",
"name": "__call__",
"signature": "def __call__(self, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001671 | Implement the Python class `RetryableTransactionTask` described below.
Class description:
Celery task that commits all the work at the end of the task using transaction manager commit. A base class to be used with :py:meth:`celery.Celery.task` function decorator. Automatically commits all the work at the end of the ta... | Implement the Python class `RetryableTransactionTask` described below.
Class description:
Celery task that commits all the work at the end of the task using transaction manager commit. A base class to be used with :py:meth:`celery.Celery.task` function decorator. Automatically commits all the work at the end of the ta... | a57de54fb8a3fae859f24f373f0292e1e4b3c344 | <|skeleton|>
class RetryableTransactionTask:
"""Celery task that commits all the work at the end of the task using transaction manager commit. A base class to be used with :py:meth:`celery.Celery.task` function decorator. Automatically commits all the work at the end of the task. In the case of transaction conflict... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RetryableTransactionTask:
"""Celery task that commits all the work at the end of the task using transaction manager commit. A base class to be used with :py:meth:`celery.Celery.task` function decorator. Automatically commits all the work at the end of the task. In the case of transaction conflict, the task wi... | the_stack_v2_python_sparse | websauna/system/task/tasks.py | websauna/websauna | train | 294 |
bb2df406d51564812edf99357cb4881afb6069a8 | [
"if request.user.is_authenticated():\n return True\nreturn False",
"if request.user.is_authenticated():\n if request.user.is_staff:\n return True\n return account.username == request.user.username\nreturn False"
] | <|body_start_0|>
if request.user.is_authenticated():
return True
return False
<|end_body_0|>
<|body_start_1|>
if request.user.is_authenticated():
if request.user.is_staff:
return True
return account.username == request.user.username
re... | Returns true if the request.user is owner of the account or Admin | IsAdminOrAccountOwner | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsAdminOrAccountOwner:
"""Returns true if the request.user is owner of the account or Admin"""
def has_permission(self, request, view):
"""Returns true or false if the user has the permission :param view: View set :return: Boolean with the user permission"""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_012153 | 1,273 | no_license | [
{
"docstring": "Returns true or false if the user has the permission :param view: View set :return: Boolean with the user permission",
"name": "has_permission",
"signature": "def has_permission(self, request, view)"
},
{
"docstring": "Returns `True` if permission is granted, `False` otherwise.",... | 2 | stack_v2_sparse_classes_30k_train_008093 | Implement the Python class `IsAdminOrAccountOwner` described below.
Class description:
Returns true if the request.user is owner of the account or Admin
Method signatures and docstrings:
- def has_permission(self, request, view): Returns true or false if the user has the permission :param view: View set :return: Bool... | Implement the Python class `IsAdminOrAccountOwner` described below.
Class description:
Returns true if the request.user is owner of the account or Admin
Method signatures and docstrings:
- def has_permission(self, request, view): Returns true or false if the user has the permission :param view: View set :return: Bool... | 9635d7ac37da6b705f6c95803d98956cfbd30ec4 | <|skeleton|>
class IsAdminOrAccountOwner:
"""Returns true if the request.user is owner of the account or Admin"""
def has_permission(self, request, view):
"""Returns true or false if the user has the permission :param view: View set :return: Boolean with the user permission"""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IsAdminOrAccountOwner:
"""Returns true if the request.user is owner of the account or Admin"""
def has_permission(self, request, view):
"""Returns true or false if the user has the permission :param view: View set :return: Boolean with the user permission"""
if request.user.is_authenticat... | the_stack_v2_python_sparse | trashradar-api/accounts/permissions.py | kahihia/trashradar-api | train | 0 |
700c101752261ad9721382912025c6a0f2508678 | [
"time_elements_structure = self._GetValueFromStructure(structure, 'date_time')\nevent_data = SnortFastAlertEventData()\nevent_data.classification = self._GetValueFromStructure(structure, 'classification')\nevent_data.destination_ip = self._GetValueFromStructure(structure, 'destination_ip_address')\nevent_data.desti... | <|body_start_0|>
time_elements_structure = self._GetValueFromStructure(structure, 'date_time')
event_data = SnortFastAlertEventData()
event_data.classification = self._GetValueFromStructure(structure, 'classification')
event_data.destination_ip = self._GetValueFromStructure(structure, 'd... | Text parser plugin for Snort3/Suricata fast-log alert log files. | SnortFastLogTextPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnortFastLogTextPlugin:
"""Text parser plugin for Snort3/Suricata fast-log alert log files."""
def _ParseRecord(self, parser_mediator, key, structure):
"""Parses a pyparsing structure. Args: parser_mediator (ParserMediator): mediates interactions between parsers and other components,... | stack_v2_sparse_classes_36k_train_012154 | 9,211 | permissive | [
{
"docstring": "Parses a pyparsing structure. Args: parser_mediator (ParserMediator): mediates interactions between parsers and other components, such as storage and dfVFS. key (str): name of the parsed structure. structure (pyparsing.ParseResults): tokens from a parsed log line. Raises: ParseError: if the stru... | 3 | null | Implement the Python class `SnortFastLogTextPlugin` described below.
Class description:
Text parser plugin for Snort3/Suricata fast-log alert log files.
Method signatures and docstrings:
- def _ParseRecord(self, parser_mediator, key, structure): Parses a pyparsing structure. Args: parser_mediator (ParserMediator): me... | Implement the Python class `SnortFastLogTextPlugin` described below.
Class description:
Text parser plugin for Snort3/Suricata fast-log alert log files.
Method signatures and docstrings:
- def _ParseRecord(self, parser_mediator, key, structure): Parses a pyparsing structure. Args: parser_mediator (ParserMediator): me... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class SnortFastLogTextPlugin:
"""Text parser plugin for Snort3/Suricata fast-log alert log files."""
def _ParseRecord(self, parser_mediator, key, structure):
"""Parses a pyparsing structure. Args: parser_mediator (ParserMediator): mediates interactions between parsers and other components,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnortFastLogTextPlugin:
"""Text parser plugin for Snort3/Suricata fast-log alert log files."""
def _ParseRecord(self, parser_mediator, key, structure):
"""Parses a pyparsing structure. Args: parser_mediator (ParserMediator): mediates interactions between parsers and other components, such as stor... | the_stack_v2_python_sparse | plaso/parsers/text_plugins/snort_fastlog.py | log2timeline/plaso | train | 1,506 |
d1334990644b30156a64546b7518735edc7f1f4d | [
"tree = copy(obj.__dict__)\nif tree['coordinates'].ndim <= 2:\n tree['coordinates'] = tree['coordinates'].data\nreturn tree",
"from weldx.constants import Q_\nif tag == 'asdf://weldx.bam.de/weldx/tags/core/geometry/spatial_data-0.1.0':\n node['coordinates'] = Q_(node['coordinates'], 'mm')\nreturn SpatialDat... | <|body_start_0|>
tree = copy(obj.__dict__)
if tree['coordinates'].ndim <= 2:
tree['coordinates'] = tree['coordinates'].data
return tree
<|end_body_0|>
<|body_start_1|>
from weldx.constants import Q_
if tag == 'asdf://weldx.bam.de/weldx/tags/core/geometry/spatial_data... | Converter for SpatialData. | SpatialDataConverter | [
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpatialDataConverter:
"""Converter for SpatialData."""
def to_yaml_tree(self, obj: SpatialData, tag: str, ctx) -> dict:
"""Serialize into tree."""
<|body_0|>
def from_yaml_tree(self, node: dict, tag: str, ctx) -> SpatialData:
"""Reconstruct from yaml node."""
... | stack_v2_sparse_classes_36k_train_012155 | 990 | permissive | [
{
"docstring": "Serialize into tree.",
"name": "to_yaml_tree",
"signature": "def to_yaml_tree(self, obj: SpatialData, tag: str, ctx) -> dict"
},
{
"docstring": "Reconstruct from yaml node.",
"name": "from_yaml_tree",
"signature": "def from_yaml_tree(self, node: dict, tag: str, ctx) -> Sp... | 2 | null | Implement the Python class `SpatialDataConverter` described below.
Class description:
Converter for SpatialData.
Method signatures and docstrings:
- def to_yaml_tree(self, obj: SpatialData, tag: str, ctx) -> dict: Serialize into tree.
- def from_yaml_tree(self, node: dict, tag: str, ctx) -> SpatialData: Reconstruct f... | Implement the Python class `SpatialDataConverter` described below.
Class description:
Converter for SpatialData.
Method signatures and docstrings:
- def to_yaml_tree(self, obj: SpatialData, tag: str, ctx) -> dict: Serialize into tree.
- def from_yaml_tree(self, node: dict, tag: str, ctx) -> SpatialData: Reconstruct f... | 7bc16a196ee669822f3663f3c7a08f6bbd0c76d5 | <|skeleton|>
class SpatialDataConverter:
"""Converter for SpatialData."""
def to_yaml_tree(self, obj: SpatialData, tag: str, ctx) -> dict:
"""Serialize into tree."""
<|body_0|>
def from_yaml_tree(self, node: dict, tag: str, ctx) -> SpatialData:
"""Reconstruct from yaml node."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpatialDataConverter:
"""Converter for SpatialData."""
def to_yaml_tree(self, obj: SpatialData, tag: str, ctx) -> dict:
"""Serialize into tree."""
tree = copy(obj.__dict__)
if tree['coordinates'].ndim <= 2:
tree['coordinates'] = tree['coordinates'].data
return ... | the_stack_v2_python_sparse | weldx/tags/core/geometry/spatial_data.py | BAMWelDX/weldx | train | 20 |
cd380f18c7d47aab90558f7754cf8554445a534b | [
"super(RND, self).__init__(state_size, action_size, eta)\nself.hidden_dim = hidden_dim\nself.state_rep_size = state_rep_size\nself.learning_rate = learning_rate\nself.predictor_dev = 'cpu'\nself.target_dev = 'cpu'\nself.predictor_model = RNDNetwork(state_size, action_size, hidden_dim, state_rep_size)\nself.target_m... | <|body_start_0|>
super(RND, self).__init__(state_size, action_size, eta)
self.hidden_dim = hidden_dim
self.state_rep_size = state_rep_size
self.learning_rate = learning_rate
self.predictor_dev = 'cpu'
self.target_dev = 'cpu'
self.predictor_model = RNDNetwork(state... | Random Network Distillation (RND) class Paper: Burda, Y., Edwards, H., Storkey, A., & Klimov, O. (2018). Exploration by random network distillation. arXiv preprint arXiv:1810.12894. Link: https://arxiv.org/abs/1810.12894 | RND | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RND:
"""Random Network Distillation (RND) class Paper: Burda, Y., Edwards, H., Storkey, A., & Klimov, O. (2018). Exploration by random network distillation. arXiv preprint arXiv:1810.12894. Link: https://arxiv.org/abs/1810.12894"""
def __init__(self, state_size, action_size, hidden_dim=128, ... | stack_v2_sparse_classes_36k_train_012156 | 3,425 | no_license | [
{
"docstring": "Initialise parameters for MARL training :param state_size: dimension of state input :param action_size: dimension of action input :param hidden_dim: hidden dimension of networks :param state_rep_size: dimension of state representation in network :param learning_rate: learning rate for ICM parame... | 3 | stack_v2_sparse_classes_30k_train_013191 | Implement the Python class `RND` described below.
Class description:
Random Network Distillation (RND) class Paper: Burda, Y., Edwards, H., Storkey, A., & Klimov, O. (2018). Exploration by random network distillation. arXiv preprint arXiv:1810.12894. Link: https://arxiv.org/abs/1810.12894
Method signatures and docstr... | Implement the Python class `RND` described below.
Class description:
Random Network Distillation (RND) class Paper: Burda, Y., Edwards, H., Storkey, A., & Klimov, O. (2018). Exploration by random network distillation. arXiv preprint arXiv:1810.12894. Link: https://arxiv.org/abs/1810.12894
Method signatures and docstr... | 2afa0a9d83bd66a151c1a19242c5ef22cf4eb1f6 | <|skeleton|>
class RND:
"""Random Network Distillation (RND) class Paper: Burda, Y., Edwards, H., Storkey, A., & Klimov, O. (2018). Exploration by random network distillation. arXiv preprint arXiv:1810.12894. Link: https://arxiv.org/abs/1810.12894"""
def __init__(self, state_size, action_size, hidden_dim=128, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RND:
"""Random Network Distillation (RND) class Paper: Burda, Y., Edwards, H., Storkey, A., & Klimov, O. (2018). Exploration by random network distillation. arXiv preprint arXiv:1810.12894. Link: https://arxiv.org/abs/1810.12894"""
def __init__(self, state_size, action_size, hidden_dim=128, state_rep_siz... | the_stack_v2_python_sparse | intrinsic_rewards/rnd/rnd.py | Jarvis-K/MSc_Curiosity_MARL | train | 0 |
510a03632a8c6eafebd6b14c8786f73655d6f77f | [
"super(MaskedMSELoss, self).__init__()\nif reduction != 'mean':\n NotImplementedError\nself.reduction = reduction",
"assert x.shape == target.shape == mask.shape\nsquared_error = (torch.flatten(x) - torch.flatten(target)) ** 2.0 * torch.flatten(mask)\nif self.reduction == 'mean':\n result = torch.sum(square... | <|body_start_0|>
super(MaskedMSELoss, self).__init__()
if reduction != 'mean':
NotImplementedError
self.reduction = reduction
<|end_body_0|>
<|body_start_1|>
assert x.shape == target.shape == mask.shape
squared_error = (torch.flatten(x) - torch.flatten(target)) ** 2.... | Masked MSE Loss module Arguments: torch {torch.nn.modules.loss._Loss} -- inherits from _Loss | MaskedMSELoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaskedMSELoss:
"""Masked MSE Loss module Arguments: torch {torch.nn.modules.loss._Loss} -- inherits from _Loss"""
def __init__(self, reduction: str='mean'):
"""Constructor Arguments: reduction (string, optional) -- how MSE should be reduced. Defaults to 'mean'."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_012157 | 2,211 | permissive | [
{
"docstring": "Constructor Arguments: reduction (string, optional) -- how MSE should be reduced. Defaults to 'mean'.",
"name": "__init__",
"signature": "def __init__(self, reduction: str='mean')"
},
{
"docstring": "Foreward pass Args: x (torch.Tensor): input tensor (output from neural network) ... | 2 | stack_v2_sparse_classes_30k_train_018271 | Implement the Python class `MaskedMSELoss` described below.
Class description:
Masked MSE Loss module Arguments: torch {torch.nn.modules.loss._Loss} -- inherits from _Loss
Method signatures and docstrings:
- def __init__(self, reduction: str='mean'): Constructor Arguments: reduction (string, optional) -- how MSE shou... | Implement the Python class `MaskedMSELoss` described below.
Class description:
Masked MSE Loss module Arguments: torch {torch.nn.modules.loss._Loss} -- inherits from _Loss
Method signatures and docstrings:
- def __init__(self, reduction: str='mean'): Constructor Arguments: reduction (string, optional) -- how MSE shou... | 5b4a61b5dd0bc259ffe68223877949ef4ebfa5e3 | <|skeleton|>
class MaskedMSELoss:
"""Masked MSE Loss module Arguments: torch {torch.nn.modules.loss._Loss} -- inherits from _Loss"""
def __init__(self, reduction: str='mean'):
"""Constructor Arguments: reduction (string, optional) -- how MSE should be reduced. Defaults to 'mean'."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MaskedMSELoss:
"""Masked MSE Loss module Arguments: torch {torch.nn.modules.loss._Loss} -- inherits from _Loss"""
def __init__(self, reduction: str='mean'):
"""Constructor Arguments: reduction (string, optional) -- how MSE should be reduced. Defaults to 'mean'."""
super(MaskedMSELoss, sel... | the_stack_v2_python_sparse | src/models/anomalia/losses.py | maurony/ts-vrae | train | 1 |
13c2070910709952904bde6c9c10bcc81d0ec81d | [
"self._mass_slice_list = []\nfor i in range(len(mass_map_list)):\n self._mass_slice_list.append(MassSlice(mass_map_list[i], grid_spacing_list[i], redshift_list[i]))\nself._mass_map_list = mass_map_list\nself._grid_spacing_list = grid_spacing_list\nself._redshift_list = redshift_list",
"lens_model = LensModel(l... | <|body_start_0|>
self._mass_slice_list = []
for i in range(len(mass_map_list)):
self._mass_slice_list.append(MassSlice(mass_map_list[i], grid_spacing_list[i], redshift_list[i]))
self._mass_map_list = mass_map_list
self._grid_spacing_list = grid_spacing_list
self._reds... | class to perform multi-plane ray-tracing from convergence maps at different redshifts From the convergence maps the deflection angles and lensing potential are computed (from different settings) and then an interpolated grid of all those quantities generate an instance of the lenstronomy LensModel multi-plane instance.... | LightCone | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LightCone:
"""class to perform multi-plane ray-tracing from convergence maps at different redshifts From the convergence maps the deflection angles and lensing potential are computed (from different settings) and then an interpolated grid of all those quantities generate an instance of the lenstr... | stack_v2_sparse_classes_36k_train_012158 | 5,293 | permissive | [
{
"docstring": ":param mass_map_list: 2d numpy array of mass map (in units physical Solar masses enclosed in each pixel/gird point of the map) :param grid_spacing_list: list of grid spacing of the individual mass maps in units of physical Mpc :param redshift_list: list of redshifts of the mass maps",
"name"... | 2 | stack_v2_sparse_classes_30k_train_020837 | Implement the Python class `LightCone` described below.
Class description:
class to perform multi-plane ray-tracing from convergence maps at different redshifts From the convergence maps the deflection angles and lensing potential are computed (from different settings) and then an interpolated grid of all those quanti... | Implement the Python class `LightCone` described below.
Class description:
class to perform multi-plane ray-tracing from convergence maps at different redshifts From the convergence maps the deflection angles and lensing potential are computed (from different settings) and then an interpolated grid of all those quanti... | 73c9645f26f6983fe7961104075ebe8bf7a4b54c | <|skeleton|>
class LightCone:
"""class to perform multi-plane ray-tracing from convergence maps at different redshifts From the convergence maps the deflection angles and lensing potential are computed (from different settings) and then an interpolated grid of all those quantities generate an instance of the lenstr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LightCone:
"""class to perform multi-plane ray-tracing from convergence maps at different redshifts From the convergence maps the deflection angles and lensing potential are computed (from different settings) and then an interpolated grid of all those quantities generate an instance of the lenstronomy LensMod... | the_stack_v2_python_sparse | lenstronomy/LensModel/LightConeSim/light_cone.py | lenstronomy/lenstronomy | train | 41 |
483140f5d0b3338d66a8d055fbab662f812b53d1 | [
"self.confirmed = confirmed\nself.synchronous = synchronous\nself.actions = actions",
"if dictionary is None:\n return None\nactions = None\nif dictionary.get('actions') != None:\n actions = list()\n for structure in dictionary.get('actions'):\n actions.append(meraki_sdk.models.action_model.Action... | <|body_start_0|>
self.confirmed = confirmed
self.synchronous = synchronous
self.actions = actions
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
actions = None
if dictionary.get('actions') != None:
actions = list()
... | Implementation of the 'createOrganizationActionBatch' model. TODO: type model description here. Attributes: confirmed (bool): Set to true for immediate execution. Set to false if the action should be previewed before executing. This property cannot be unset once it is true. Defaults to false. synchronous (bool): Set to... | CreateOrganizationActionBatchModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateOrganizationActionBatchModel:
"""Implementation of the 'createOrganizationActionBatch' model. TODO: type model description here. Attributes: confirmed (bool): Set to true for immediate execution. Set to false if the action should be previewed before executing. This property cannot be unset ... | stack_v2_sparse_classes_36k_train_012159 | 2,674 | permissive | [
{
"docstring": "Constructor for the CreateOrganizationActionBatchModel class",
"name": "__init__",
"signature": "def __init__(self, actions=None, confirmed=None, synchronous=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary ... | 2 | stack_v2_sparse_classes_30k_train_005815 | Implement the Python class `CreateOrganizationActionBatchModel` described below.
Class description:
Implementation of the 'createOrganizationActionBatch' model. TODO: type model description here. Attributes: confirmed (bool): Set to true for immediate execution. Set to false if the action should be previewed before ex... | Implement the Python class `CreateOrganizationActionBatchModel` described below.
Class description:
Implementation of the 'createOrganizationActionBatch' model. TODO: type model description here. Attributes: confirmed (bool): Set to true for immediate execution. Set to false if the action should be previewed before ex... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class CreateOrganizationActionBatchModel:
"""Implementation of the 'createOrganizationActionBatch' model. TODO: type model description here. Attributes: confirmed (bool): Set to true for immediate execution. Set to false if the action should be previewed before executing. This property cannot be unset ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateOrganizationActionBatchModel:
"""Implementation of the 'createOrganizationActionBatch' model. TODO: type model description here. Attributes: confirmed (bool): Set to true for immediate execution. Set to false if the action should be previewed before executing. This property cannot be unset once it is tr... | the_stack_v2_python_sparse | meraki_sdk/models/create_organization_action_batch_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
ebdb42da6564b6d827b1d617299e402fc85111c1 | [
"log_object_input_state(self, locals())\nself.image_pointer = image_name\nself.mask_name = mask_name\nself.label_name = label_name\nself.metadata_pointers = metadata_names\nself.pred_name = pred_name\nself.matching_function = FuseUtilsImageProcessing.match_img_to_input",
"image = FuseUtilsHierarchicalDict.get(sam... | <|body_start_0|>
log_object_input_state(self, locals())
self.image_pointer = image_name
self.mask_name = mask_name
self.label_name = label_name
self.metadata_pointers = metadata_names
self.pred_name = pred_name
self.matching_function = FuseUtilsImageProcessing.mat... | Visualizer for data including single 2D image with optional mask | FuseVisualizerDefault | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FuseVisualizerDefault:
"""Visualizer for data including single 2D image with optional mask"""
def __init__(self, image_name: str, mask_name: Optional[str]=None, label_name: Optional[str]=None, metadata_names: Iterable[str]=tuple(), pred_name: Optional[str]=None):
""":param image_name... | stack_v2_sparse_classes_36k_train_012160 | 7,546 | permissive | [
{
"docstring": ":param image_name: hierarchical key name of the image in batch_dict :param mask_name: hierarchical key name of the mask (gt map) in batch_dict. Optional, won't be displayed if not specified. :param label_name: hierarchical key name of the to a global label in batch_dict. Optional, won't be displ... | 4 | stack_v2_sparse_classes_30k_train_011377 | Implement the Python class `FuseVisualizerDefault` described below.
Class description:
Visualizer for data including single 2D image with optional mask
Method signatures and docstrings:
- def __init__(self, image_name: str, mask_name: Optional[str]=None, label_name: Optional[str]=None, metadata_names: Iterable[str]=t... | Implement the Python class `FuseVisualizerDefault` described below.
Class description:
Visualizer for data including single 2D image with optional mask
Method signatures and docstrings:
- def __init__(self, image_name: str, mask_name: Optional[str]=None, label_name: Optional[str]=None, metadata_names: Iterable[str]=t... | acbfd4975f18cd4361d31697faf2f82036399865 | <|skeleton|>
class FuseVisualizerDefault:
"""Visualizer for data including single 2D image with optional mask"""
def __init__(self, image_name: str, mask_name: Optional[str]=None, label_name: Optional[str]=None, metadata_names: Iterable[str]=tuple(), pred_name: Optional[str]=None):
""":param image_name... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FuseVisualizerDefault:
"""Visualizer for data including single 2D image with optional mask"""
def __init__(self, image_name: str, mask_name: Optional[str]=None, label_name: Optional[str]=None, metadata_names: Iterable[str]=tuple(), pred_name: Optional[str]=None):
""":param image_name: hierarchica... | the_stack_v2_python_sparse | fuse/data/visualizer/visualizer_default.py | rosenzvi/fuse-med-ml | train | 0 |
07d568d5e587a2dd2964e0f5136993d1f8d8aa8d | [
"if xml_path == None:\n script_path = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))\n xml_path = script_path + '/../robot_description/' + self.default_xml_file\nMjRobot.__init__(self, xml_path, object_names=object_names, render=render, g_comp=g_comp, tool_mass=tool_mass, tool_mass_... | <|body_start_0|>
if xml_path == None:
script_path = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
xml_path = script_path + '/../robot_description/' + self.default_xml_file
MjRobot.__init__(self, xml_path, object_names=object_names, render=render, g_com... | The 4 DoF, 80V Barret WAM robot | MjWam4 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MjWam4:
"""The 4 DoF, 80V Barret WAM robot"""
def __init__(self, xml_path=None, object_names=[], render=True, g_comp=False, tool_mass=0, tool_mass_site=None):
"""The 4 DoF, 80V Barret WAM robot xml_path: to change the robots environment or end effector, provide a modified version of ... | stack_v2_sparse_classes_36k_train_012161 | 22,293 | no_license | [
{
"docstring": "The 4 DoF, 80V Barret WAM robot xml_path: to change the robots environment or end effector, provide a modified version of the default xml description file object_names: states of the listed objects are included in recordings render: whether or not to render the simulation g_comp: whether or not ... | 2 | stack_v2_sparse_classes_30k_train_004125 | Implement the Python class `MjWam4` described below.
Class description:
The 4 DoF, 80V Barret WAM robot
Method signatures and docstrings:
- def __init__(self, xml_path=None, object_names=[], render=True, g_comp=False, tool_mass=0, tool_mass_site=None): The 4 DoF, 80V Barret WAM robot xml_path: to change the robots en... | Implement the Python class `MjWam4` described below.
Class description:
The 4 DoF, 80V Barret WAM robot
Method signatures and docstrings:
- def __init__(self, xml_path=None, object_names=[], render=True, g_comp=False, tool_mass=0, tool_mass_site=None): The 4 DoF, 80V Barret WAM robot xml_path: to change the robots en... | dd7c19b347e8167f9f5e1cd4ae32fbec194dc046 | <|skeleton|>
class MjWam4:
"""The 4 DoF, 80V Barret WAM robot"""
def __init__(self, xml_path=None, object_names=[], render=True, g_comp=False, tool_mass=0, tool_mass_site=None):
"""The 4 DoF, 80V Barret WAM robot xml_path: to change the robots environment or end effector, provide a modified version of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MjWam4:
"""The 4 DoF, 80V Barret WAM robot"""
def __init__(self, xml_path=None, object_names=[], render=True, g_comp=False, tool_mass=0, tool_mass_site=None):
"""The 4 DoF, 80V Barret WAM robot xml_path: to change the robots environment or end effector, provide a modified version of the default x... | the_stack_v2_python_sparse | mujoco_robots/robots.py | kploeger/mujoco_robots | train | 0 |
3c84ca4fa420335d54a90e4f610938c8eb382f5a | [
"self.filename = filename\nself.step = depend_value(name='step', value=step)\nself.stride = stride\nself.overwrite = overwrite\nself._storing = False\nself._continued = False",
"self.simul = simul\nimport ipi.inputs.simulation as isimulation\nself.status = isimulation.InputSimulation()\nself.status.store(simul)",... | <|body_start_0|>
self.filename = filename
self.step = depend_value(name='step', value=step)
self.stride = stride
self.overwrite = overwrite
self._storing = False
self._continued = False
<|end_body_0|>
<|body_start_1|>
self.simul = simul
import ipi.inputs.... | Class dealing with outputting checkpoints. Saves the complete status of the simulation at regular intervals. Attributes: filename: The (base) name of the file to output to. step: the number of times a checkpoint has been written out. stride: The number of steps that should be taken between outputting the data to file. ... | CheckpointOutput | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckpointOutput:
"""Class dealing with outputting checkpoints. Saves the complete status of the simulation at regular intervals. Attributes: filename: The (base) name of the file to output to. step: the number of times a checkpoint has been written out. stride: The number of steps that should be... | stack_v2_sparse_classes_36k_train_012162 | 22,634 | no_license | [
{
"docstring": "Initializes a checkpoint output proxy. Args: filename: A string giving the name of the file to be output to. stride: An integer giving how many steps should be taken between outputting the data to file. overwrite: If True, the checkpoint file is overwritten at each output. If False, will output ... | 4 | stack_v2_sparse_classes_30k_train_010113 | Implement the Python class `CheckpointOutput` described below.
Class description:
Class dealing with outputting checkpoints. Saves the complete status of the simulation at regular intervals. Attributes: filename: The (base) name of the file to output to. step: the number of times a checkpoint has been written out. str... | Implement the Python class `CheckpointOutput` described below.
Class description:
Class dealing with outputting checkpoints. Saves the complete status of the simulation at regular intervals. Attributes: filename: The (base) name of the file to output to. step: the number of times a checkpoint has been written out. str... | 57f255266d4668bafef0881d1e7cbf8a27270ddd | <|skeleton|>
class CheckpointOutput:
"""Class dealing with outputting checkpoints. Saves the complete status of the simulation at regular intervals. Attributes: filename: The (base) name of the file to output to. step: the number of times a checkpoint has been written out. stride: The number of steps that should be... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckpointOutput:
"""Class dealing with outputting checkpoints. Saves the complete status of the simulation at regular intervals. Attributes: filename: The (base) name of the file to output to. step: the number of times a checkpoint has been written out. stride: The number of steps that should be taken betwee... | the_stack_v2_python_sparse | ipi/engine/outputs.py | i-pi/i-pi | train | 170 |
90f428307e171c6d8fd2dd07b7e3f5e62735fd0c | [
"super(TeardownSession, self).__init__(*args, **kwargs)\nself.tools = tools\nreturn",
"for tool in self.tools:\n tool.run()\nreturn"
] | <|body_start_0|>
super(TeardownSession, self).__init__(*args, **kwargs)
self.tools = tools
return
<|end_body_0|>
<|body_start_1|>
for tool in self.tools:
tool.run()
return
<|end_body_1|>
| The TearDown does whatever needs to be done after the test is completed. It iterates over the `tools` passed in to the constructor. Each tool's `run` method is called. Choosing tools and ordering them defines the TeardownSession algorithm. | TeardownSession | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TeardownSession:
"""The TearDown does whatever needs to be done after the test is completed. It iterates over the `tools` passed in to the constructor. Each tool's `run` method is called. Choosing tools and ordering them defines the TeardownSession algorithm."""
def __init__(self, tools, *ar... | stack_v2_sparse_classes_36k_train_012163 | 780 | permissive | [
{
"docstring": ":param: - `tools`: a list of tools to run",
"name": "__init__",
"signature": "def __init__(self, tools, *args, **kwargs)"
},
{
"docstring": "Calls the run() method for each tool in `tools`",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016065 | Implement the Python class `TeardownSession` described below.
Class description:
The TearDown does whatever needs to be done after the test is completed. It iterates over the `tools` passed in to the constructor. Each tool's `run` method is called. Choosing tools and ordering them defines the TeardownSession algorithm... | Implement the Python class `TeardownSession` described below.
Class description:
The TearDown does whatever needs to be done after the test is completed. It iterates over the `tools` passed in to the constructor. Each tool's `run` method is called. Choosing tools and ordering them defines the TeardownSession algorithm... | b4d1c77e1d611fe2b30768b42bdc7493afb0ea95 | <|skeleton|>
class TeardownSession:
"""The TearDown does whatever needs to be done after the test is completed. It iterates over the `tools` passed in to the constructor. Each tool's `run` method is called. Choosing tools and ordering them defines the TeardownSession algorithm."""
def __init__(self, tools, *ar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TeardownSession:
"""The TearDown does whatever needs to be done after the test is completed. It iterates over the `tools` passed in to the constructor. Each tool's `run` method is called. Choosing tools and ordering them defines the TeardownSession algorithm."""
def __init__(self, tools, *args, **kwargs)... | the_stack_v2_python_sparse | apetools/proletarians/teardown.py | russell-n/oldape | train | 0 |
5c82cb99e568a7365b0748d3930c8d7e30083d7d | [
"if not A:\n return []\nresult = list(A[0])\nfor colum in A[1:]:\n current = []\n for c in colum:\n if c in result:\n current.append(c)\n result.remove(c)\n result = current\nreturn result",
"if not A:\n return []\ndata = {}\nfor d in A[0]:\n data[d] = data.get(d, 0)... | <|body_start_0|>
if not A:
return []
result = list(A[0])
for colum in A[1:]:
current = []
for c in colum:
if c in result:
current.append(c)
result.remove(c)
result = current
return res... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _commonChars(self, A):
""":type A: List[str] :rtype: List[str]"""
<|body_0|>
def commonChars(self, A):
""":type A: List[str] :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not A:
return []
resu... | stack_v2_sparse_classes_36k_train_012164 | 1,982 | permissive | [
{
"docstring": ":type A: List[str] :rtype: List[str]",
"name": "_commonChars",
"signature": "def _commonChars(self, A)"
},
{
"docstring": ":type A: List[str] :rtype: List[str]",
"name": "commonChars",
"signature": "def commonChars(self, A)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _commonChars(self, A): :type A: List[str] :rtype: List[str]
- def commonChars(self, A): :type A: List[str] :rtype: List[str] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _commonChars(self, A): :type A: List[str] :rtype: List[str]
- def commonChars(self, A): :type A: List[str] :rtype: List[str]
<|skeleton|>
class Solution:
def _commonCha... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _commonChars(self, A):
""":type A: List[str] :rtype: List[str]"""
<|body_0|>
def commonChars(self, A):
""":type A: List[str] :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _commonChars(self, A):
""":type A: List[str] :rtype: List[str]"""
if not A:
return []
result = list(A[0])
for colum in A[1:]:
current = []
for c in colum:
if c in result:
current.append(c)
... | the_stack_v2_python_sparse | 1002.find-common-characters.py | windard/leeeeee | train | 0 | |
e3e896be8568f3821d24c9de516942636c08ed72 | [
"self.tokenizer = spm.SentencePieceProcessor()\nself.tokenizer.Load(model)\nself.specials = specials\nself.lower = lower\nself.vocab_size = self.tokenizer.get_piece_size()\nself.pre_id = []\nself.post_id = []\nif prepend_bos:\n self.pre_id.append(self.tokenizer.piece_to_id(self.specials.BOS.value))\nif append_eo... | <|body_start_0|>
self.tokenizer = spm.SentencePieceProcessor()
self.tokenizer.Load(model)
self.specials = specials
self.lower = lower
self.vocab_size = self.tokenizer.get_piece_size()
self.pre_id = []
self.post_id = []
if prepend_bos:
self.pre_... | SentencepieceTokenizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentencepieceTokenizer:
def __init__(self, lower: bool=True, model: Optional[Any]=None, prepend_bos: bool=False, append_eos: bool=False, specials: Optional[SPECIAL_TOKENS]=SPECIAL_TOKENS):
"""Tokenize sentence using pretrained sentencepiece model Args: lower (bool): Lowercase string. Def... | stack_v2_sparse_classes_36k_train_012165 | 8,041 | permissive | [
{
"docstring": "Tokenize sentence using pretrained sentencepiece model Args: lower (bool): Lowercase string. Defaults to True. model (Optional[Any]): Sentencepiece model. Defaults to None. prepend_bos (bool): Prepend BOS for seq2seq. Defaults to False. append_eos (bool): Append EOS for seq2seq. Defaults to Fals... | 2 | stack_v2_sparse_classes_30k_train_001696 | Implement the Python class `SentencepieceTokenizer` described below.
Class description:
Implement the SentencepieceTokenizer class.
Method signatures and docstrings:
- def __init__(self, lower: bool=True, model: Optional[Any]=None, prepend_bos: bool=False, append_eos: bool=False, specials: Optional[SPECIAL_TOKENS]=SP... | Implement the Python class `SentencepieceTokenizer` described below.
Class description:
Implement the SentencepieceTokenizer class.
Method signatures and docstrings:
- def __init__(self, lower: bool=True, model: Optional[Any]=None, prepend_bos: bool=False, append_eos: bool=False, specials: Optional[SPECIAL_TOKENS]=SP... | e4987310ed277abdec19462bdd749e2e7a000bec | <|skeleton|>
class SentencepieceTokenizer:
def __init__(self, lower: bool=True, model: Optional[Any]=None, prepend_bos: bool=False, append_eos: bool=False, specials: Optional[SPECIAL_TOKENS]=SPECIAL_TOKENS):
"""Tokenize sentence using pretrained sentencepiece model Args: lower (bool): Lowercase string. Def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SentencepieceTokenizer:
def __init__(self, lower: bool=True, model: Optional[Any]=None, prepend_bos: bool=False, append_eos: bool=False, specials: Optional[SPECIAL_TOKENS]=SPECIAL_TOKENS):
"""Tokenize sentence using pretrained sentencepiece model Args: lower (bool): Lowercase string. Defaults to True.... | the_stack_v2_python_sparse | slp/data/transforms.py | georgepar/slp | train | 26 | |
2db669b00646c72ca4c963caeed9bcb3d7e9453b | [
"super(DiscordIO, self).__init__()\nconfig = ClientConfig()\nconfig.token = token\nclient = Client(config)\nself.text = self.__class__.__name__\ntry:\n self.message = client.api.channels_messages_create(channel_id, self.text)\nexcept Exception as e:\n tqdm_auto.write(str(e))",
"if not s:\n s = '...'\ns =... | <|body_start_0|>
super(DiscordIO, self).__init__()
config = ClientConfig()
config.token = token
client = Client(config)
self.text = self.__class__.__name__
try:
self.message = client.api.channels_messages_create(channel_id, self.text)
except Exception ... | Non-blocking file-like IO using a Discord Bot. | DiscordIO | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiscordIO:
"""Non-blocking file-like IO using a Discord Bot."""
def __init__(self, token, channel_id):
"""Creates a new message in the given `channel_id`."""
<|body_0|>
def write(self, s):
"""Replaces internal `message`'s text with `s`."""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k_train_012166 | 3,930 | permissive | [
{
"docstring": "Creates a new message in the given `channel_id`.",
"name": "__init__",
"signature": "def __init__(self, token, channel_id)"
},
{
"docstring": "Replaces internal `message`'s text with `s`.",
"name": "write",
"signature": "def write(self, s)"
}
] | 2 | null | Implement the Python class `DiscordIO` described below.
Class description:
Non-blocking file-like IO using a Discord Bot.
Method signatures and docstrings:
- def __init__(self, token, channel_id): Creates a new message in the given `channel_id`.
- def write(self, s): Replaces internal `message`'s text with `s`. | Implement the Python class `DiscordIO` described below.
Class description:
Non-blocking file-like IO using a Discord Bot.
Method signatures and docstrings:
- def __init__(self, token, channel_id): Creates a new message in the given `channel_id`.
- def write(self, s): Replaces internal `message`'s text with `s`.
<|sk... | 39efe4007fba2b12b75c72f7795827a1f74d640b | <|skeleton|>
class DiscordIO:
"""Non-blocking file-like IO using a Discord Bot."""
def __init__(self, token, channel_id):
"""Creates a new message in the given `channel_id`."""
<|body_0|>
def write(self, s):
"""Replaces internal `message`'s text with `s`."""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DiscordIO:
"""Non-blocking file-like IO using a Discord Bot."""
def __init__(self, token, channel_id):
"""Creates a new message in the given `channel_id`."""
super(DiscordIO, self).__init__()
config = ClientConfig()
config.token = token
client = Client(config)
... | the_stack_v2_python_sparse | venv/Lib/site-packages/tqdm/contrib/discord.py | tpike3/SugarScape | train | 11 |
d180b69ceeaf6dab9f0709052c4d95ecabaee491 | [
"out, stack = ([], [])\nnode = root\nwhile True:\n while node:\n out.append(node.val)\n stack.append(node)\n node = node.left\n if not stack:\n break\n node = stack.pop()\n node = node.right\nreturn out",
"out = []\nif root:\n out.append(root.val)\n out += self.traver... | <|body_start_0|>
out, stack = ([], [])
node = root
while True:
while node:
out.append(node.val)
stack.append(node)
node = node.left
if not stack:
break
node = stack.pop()
node = node.r... | TreeTraversalPreOrder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TreeTraversalPreOrder:
def traverse_iterative(root: TreeNode) -> []:
"""Iterative tree traversal pre order"""
<|body_0|>
def traverse_recursive(self, root: TreeNode) -> []:
"""Recursive tree traversal in order"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_012167 | 1,013 | no_license | [
{
"docstring": "Iterative tree traversal pre order",
"name": "traverse_iterative",
"signature": "def traverse_iterative(root: TreeNode) -> []"
},
{
"docstring": "Recursive tree traversal in order",
"name": "traverse_recursive",
"signature": "def traverse_recursive(self, root: TreeNode) -... | 2 | null | Implement the Python class `TreeTraversalPreOrder` described below.
Class description:
Implement the TreeTraversalPreOrder class.
Method signatures and docstrings:
- def traverse_iterative(root: TreeNode) -> []: Iterative tree traversal pre order
- def traverse_recursive(self, root: TreeNode) -> []: Recursive tree tr... | Implement the Python class `TreeTraversalPreOrder` described below.
Class description:
Implement the TreeTraversalPreOrder class.
Method signatures and docstrings:
- def traverse_iterative(root: TreeNode) -> []: Iterative tree traversal pre order
- def traverse_recursive(self, root: TreeNode) -> []: Recursive tree tr... | 8ae84f276cd07ffdb9b742569a5e32809ecc6b29 | <|skeleton|>
class TreeTraversalPreOrder:
def traverse_iterative(root: TreeNode) -> []:
"""Iterative tree traversal pre order"""
<|body_0|>
def traverse_recursive(self, root: TreeNode) -> []:
"""Recursive tree traversal in order"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TreeTraversalPreOrder:
def traverse_iterative(root: TreeNode) -> []:
"""Iterative tree traversal pre order"""
out, stack = ([], [])
node = root
while True:
while node:
out.append(node.val)
stack.append(node)
node = nod... | the_stack_v2_python_sparse | pyquiz/leetcode/TreeTraversalPreOrder.py | DmitryPukhov/pyquiz | train | 0 | |
8581c655dd3288aa0856a774e6a1d8fa676580eb | [
"levels = []\nif not root:\n return levels\n\ndef helper(node, level):\n if len(levels) == level:\n '\\n level层从0开始计数，而levels存储每一层的结点值，因此这里很巧妙的处理是依据当前\\n levels中元素的个数判断是否需要添加新的一层；比如个数为0，表示正处理第0层，个数为3\\n 表示正处理第3层。\\n '\n leve... | <|body_start_0|>
levels = []
if not root:
return levels
def helper(node, level):
if len(levels) == level:
'\n level层从0开始计数，而levels存储每一层的结点值，因此这里很巧妙的处理是依据当前\n levels中元素的个数判断是否需要添加新的一层；比如个数为0，表示正处理第0层，个数为3\n ... | 给定一个二叉树，返回其按层次遍历的节点值。 （即逐层地，从左到右访问所有节点）。 例如: 给定二叉树: [3,9,20,null,null,15,7], 3 / 9 20 / 15 7 返回其层次遍历结果： [ [3], [9,20], [15,7] ] | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""给定一个二叉树，返回其按层次遍历的节点值。 （即逐层地，从左到右访问所有节点）。 例如: 给定二叉树: [3,9,20,null,null,15,7], 3 / 9 20 / 15 7 返回其层次遍历结果： [ [3], [9,20], [15,7] ]"""
def level_order(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def level_order2(self, root):
... | stack_v2_sparse_classes_36k_train_012168 | 2,621 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "level_order",
"signature": "def level_order(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "level_order2",
"signature": "def level_order2(self, root)"
},
{
"docstring":... | 3 | null | Implement the Python class `Solution` described below.
Class description:
给定一个二叉树，返回其按层次遍历的节点值。 （即逐层地，从左到右访问所有节点）。 例如: 给定二叉树: [3,9,20,null,null,15,7], 3 / 9 20 / 15 7 返回其层次遍历结果： [ [3], [9,20], [15,7] ]
Method signatures and docstrings:
- def level_order(self, root): :type root: TreeNode :rtype: List[List[int]]
- def ... | Implement the Python class `Solution` described below.
Class description:
给定一个二叉树，返回其按层次遍历的节点值。 （即逐层地，从左到右访问所有节点）。 例如: 给定二叉树: [3,9,20,null,null,15,7], 3 / 9 20 / 15 7 返回其层次遍历结果： [ [3], [9,20], [15,7] ]
Method signatures and docstrings:
- def level_order(self, root): :type root: TreeNode :rtype: List[List[int]]
- def ... | 2c534185854c1a6f5ffdb2698f9db9989f30a25b | <|skeleton|>
class Solution:
"""给定一个二叉树，返回其按层次遍历的节点值。 （即逐层地，从左到右访问所有节点）。 例如: 给定二叉树: [3,9,20,null,null,15,7], 3 / 9 20 / 15 7 返回其层次遍历结果： [ [3], [9,20], [15,7] ]"""
def level_order(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def level_order2(self, root):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""给定一个二叉树，返回其按层次遍历的节点值。 （即逐层地，从左到右访问所有节点）。 例如: 给定二叉树: [3,9,20,null,null,15,7], 3 / 9 20 / 15 7 返回其层次遍历结果： [ [3], [9,20], [15,7] ]"""
def level_order(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
levels = []
if not root:
return levels
... | the_stack_v2_python_sparse | Week 03/id_668/leetcode_102_668.py | Carryours/algorithm004-03 | train | 2 |
4b612ccddcca123d374e51540159ac2215f18f3c | [
"users = User.query.all()\nusers_list = []\nfor user in users:\n users_list.append(user.__jsonapi__())\nreturn {'data': users_list}",
"current_identity = import_user()\ndata = request.get_json()['data']\nif User.query.filter_by(username=data['attributes']['username']).first():\n api.abort(code=409, message=... | <|body_start_0|>
users = User.query.all()
users_list = []
for user in users:
users_list.append(user.__jsonapi__())
return {'data': users_list}
<|end_body_0|>
<|body_start_1|>
current_identity = import_user()
data = request.get_json()['data']
if User.q... | UsersList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UsersList:
def get(self):
"""Get users list"""
<|body_0|>
def post(self):
"""Create user"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
users = User.query.all()
users_list = []
for user in users:
users_list.append(user._... | stack_v2_sparse_classes_36k_train_012169 | 46,738 | permissive | [
{
"docstring": "Get users list",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Create user",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003695 | Implement the Python class `UsersList` described below.
Class description:
Implement the UsersList class.
Method signatures and docstrings:
- def get(self): Get users list
- def post(self): Create user | Implement the Python class `UsersList` described below.
Class description:
Implement the UsersList class.
Method signatures and docstrings:
- def get(self): Get users list
- def post(self): Create user
<|skeleton|>
class UsersList:
def get(self):
"""Get users list"""
<|body_0|>
def post(sel... | 3439a2dd0bd527c5d604801fec3a5aac904a72e2 | <|skeleton|>
class UsersList:
def get(self):
"""Get users list"""
<|body_0|>
def post(self):
"""Create user"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UsersList:
def get(self):
"""Get users list"""
users = User.query.all()
users_list = []
for user in users:
users_list.append(user.__jsonapi__())
return {'data': users_list}
def post(self):
"""Create user"""
current_identity = import_user... | the_stack_v2_python_sparse | app/views.py | taidos/lxc-rest | train | 0 | |
20b554cca70f0aef733c2ca504c28fcb2d2d4894 | [
"for b in self.badAlignmentBlockStarts:\n mafFile = testFile(b)\n self.assertRaises(mafval.MissingAlignmentBlockLineError, mafval.validateMaf, mafFile, options)\n removeTempDir()",
"for b in self.badAlignmentBlockKeyValuePairs:\n mafFile = testFile(b)\n self.assertRaises(mafval.AlignmentBlockLineKe... | <|body_start_0|>
for b in self.badAlignmentBlockStarts:
mafFile = testFile(b)
self.assertRaises(mafval.MissingAlignmentBlockLineError, mafval.validateMaf, mafFile, options)
removeTempDir()
<|end_body_0|>
<|body_start_1|>
for b in self.badAlignmentBlockKeyValuePairs:
... | AlignmentBlockLinesChecks | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlignmentBlockLinesChecks:
def testAlignmentBlockLineExistence(self):
"""mafValidator should fail when a sequence block starts without an '^a' line"""
<|body_0|>
def testAlignmentBlockLineKeyValuePairs(self):
"""mafValidator should fail when an alignment block has ma... | stack_v2_sparse_classes_36k_train_012170 | 41,963 | permissive | [
{
"docstring": "mafValidator should fail when a sequence block starts without an '^a' line",
"name": "testAlignmentBlockLineExistence",
"signature": "def testAlignmentBlockLineExistence(self)"
},
{
"docstring": "mafValidator should fail when an alignment block has mal-formed key-value pairs",
... | 2 | stack_v2_sparse_classes_30k_train_013136 | Implement the Python class `AlignmentBlockLinesChecks` described below.
Class description:
Implement the AlignmentBlockLinesChecks class.
Method signatures and docstrings:
- def testAlignmentBlockLineExistence(self): mafValidator should fail when a sequence block starts without an '^a' line
- def testAlignmentBlockLi... | Implement the Python class `AlignmentBlockLinesChecks` described below.
Class description:
Implement the AlignmentBlockLinesChecks class.
Method signatures and docstrings:
- def testAlignmentBlockLineExistence(self): mafValidator should fail when a sequence block starts without an '^a' line
- def testAlignmentBlockLi... | 601832a780f328d48893474f0f4934dcbf9df73c | <|skeleton|>
class AlignmentBlockLinesChecks:
def testAlignmentBlockLineExistence(self):
"""mafValidator should fail when a sequence block starts without an '^a' line"""
<|body_0|>
def testAlignmentBlockLineKeyValuePairs(self):
"""mafValidator should fail when an alignment block has ma... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlignmentBlockLinesChecks:
def testAlignmentBlockLineExistence(self):
"""mafValidator should fail when a sequence block starts without an '^a' line"""
for b in self.badAlignmentBlockStarts:
mafFile = testFile(b)
self.assertRaises(mafval.MissingAlignmentBlockLineError, m... | the_stack_v2_python_sparse | mafValidator/src/test.mafValidator.py | sorrywm/mafTools | train | 0 | |
f6afe33cb8f3ccd53ae3834e85182ab42c25fa6e | [
"gr = Group.objects.get_or_404(id=id)\ns = Student.objects.get_or_404(id=sid)\nif gr.project.campus.id != s.campus.id:\n abort(400, error='Not authorized')\nif s in gr.students:\n abort(400, error='Student already exist')\ngr.students.append(s)\ngr.save()\nreturn ('Student successfully added', 204)",
"gr = ... | <|body_start_0|>
gr = Group.objects.get_or_404(id=id)
s = Student.objects.get_or_404(id=sid)
if gr.project.campus.id != s.campus.id:
abort(400, error='Not authorized')
if s in gr.students:
abort(400, error='Student already exist')
gr.students.append(s)
... | GroupItemStudent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupItemStudent:
def post(self, id, sid):
"""Add student"""
<|body_0|>
def delete(self, id, sid):
"""Remove student"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
gr = Group.objects.get_or_404(id=id)
s = Student.objects.get_or_404(id=sid)
... | stack_v2_sparse_classes_36k_train_012171 | 4,822 | no_license | [
{
"docstring": "Add student",
"name": "post",
"signature": "def post(self, id, sid)"
},
{
"docstring": "Remove student",
"name": "delete",
"signature": "def delete(self, id, sid)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000590 | Implement the Python class `GroupItemStudent` described below.
Class description:
Implement the GroupItemStudent class.
Method signatures and docstrings:
- def post(self, id, sid): Add student
- def delete(self, id, sid): Remove student | Implement the Python class `GroupItemStudent` described below.
Class description:
Implement the GroupItemStudent class.
Method signatures and docstrings:
- def post(self, id, sid): Add student
- def delete(self, id, sid): Remove student
<|skeleton|>
class GroupItemStudent:
def post(self, id, sid):
"""Ad... | f053f0f357b29a6649df41e4ff06a688090ed043 | <|skeleton|>
class GroupItemStudent:
def post(self, id, sid):
"""Add student"""
<|body_0|>
def delete(self, id, sid):
"""Remove student"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupItemStudent:
def post(self, id, sid):
"""Add student"""
gr = Group.objects.get_or_404(id=id)
s = Student.objects.get_or_404(id=sid)
if gr.project.campus.id != s.campus.id:
abort(400, error='Not authorized')
if s in gr.students:
abort(400, er... | the_stack_v2_python_sparse | app/admin/endpoints/groups.py | averdier/epsi_my_learning_chain_admin | train | 0 | |
c94a2880a63fbaf3791d26f5efd26b8bc47132d7 | [
"self.kvallist = []\nsuper(ConfListKey, self).__init__(keyword, keyvalue, comment)\nvlist = self.keyvalue.split()\nfor value in vlist:\n self.kvallist.append(float(value))",
"if index > len(self.kvallist) - 1:\n err_msg = 'Index: ' + str(index) + ' does not exist!'\n raise aXeError(err_msg)\nreturn self.... | <|body_start_0|>
self.kvallist = []
super(ConfListKey, self).__init__(keyword, keyvalue, comment)
vlist = self.keyvalue.split()
for value in vlist:
self.kvallist.append(float(value))
<|end_body_0|>
<|body_start_1|>
if index > len(self.kvallist) - 1:
err_m... | Class for a keyword list The keyword list class is a subclass derived from the keyword class. In the keyword list class has as an additional attribute the keyvalues transformed to a list of floats. | ConfListKey | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfListKey:
"""Class for a keyword list The keyword list class is a subclass derived from the keyword class. In the keyword list class has as an additional attribute the keyvalues transformed to a list of floats."""
def __init__(self, keyword, keyvalue, comment=None):
"""Constructor... | stack_v2_sparse_classes_36k_train_012172 | 48,172 | permissive | [
{
"docstring": "Constructor for the keyword list class Initializer for the keyword list class. The keyword instance is created using all input values. @param keyword: the keword name @type keyword: string @param keyvalue: the keyword values @type keyvalue: string @param comment: the keyword comment @type commen... | 4 | null | Implement the Python class `ConfListKey` described below.
Class description:
Class for a keyword list The keyword list class is a subclass derived from the keyword class. In the keyword list class has as an additional attribute the keyvalues transformed to a list of floats.
Method signatures and docstrings:
- def __i... | Implement the Python class `ConfListKey` described below.
Class description:
Class for a keyword list The keyword list class is a subclass derived from the keyword class. In the keyword list class has as an additional attribute the keyvalues transformed to a list of floats.
Method signatures and docstrings:
- def __i... | 043c173fd5497c18c2b1bfe8bcff65180bca3996 | <|skeleton|>
class ConfListKey:
"""Class for a keyword list The keyword list class is a subclass derived from the keyword class. In the keyword list class has as an additional attribute the keyvalues transformed to a list of floats."""
def __init__(self, keyword, keyvalue, comment=None):
"""Constructor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfListKey:
"""Class for a keyword list The keyword list class is a subclass derived from the keyword class. In the keyword list class has as an additional attribute the keyvalues transformed to a list of floats."""
def __init__(self, keyword, keyvalue, comment=None):
"""Constructor for the keyw... | the_stack_v2_python_sparse | stsdas/pkg/analysis/slitless/axe/axesrc/configfile.py | spacetelescope/stsdas_stripped | train | 1 |
a3473ba61beccbfb158e8b2d1a69589222fdcb20 | [
"res = set()\nB = set()\nfor a in A:\n B = {b | a for b in B} | {a}\n res |= B\nreturn len(res)",
"max_a = max(A)\nmask = 1\nwhile mask <= max_a:\n mask <<= 1\nmask -= 1\nres = set()\nfor i, a in enumerate(A):\n res.add(a)\n j = i - 1\n cur = a\n while j >= 0 and cur < mask:\n cur |= A... | <|body_start_0|>
res = set()
B = set()
for a in A:
B = {b | a for b in B} | {a}
res |= B
return len(res)
<|end_body_0|>
<|body_start_1|>
max_a = max(A)
mask = 1
while mask <= max_a:
mask <<= 1
mask -= 1
res = se... | [898. 子数组按位或操作](https://leetcode-cn.com/problems/bitwise-ors-of-subarrays/) | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""[898. 子数组按位或操作](https://leetcode-cn.com/problems/bitwise-ors-of-subarrays/)"""
def subarrayBitwiseORs(self, A: List[int]) -> int:
"""思路: 2个set存"""
<|body_0|>
def subarrayBitwiseORs2(self, A: List[int]) -> int:
"""思路: 位运算剪枝来代替两个set轮流io"""
<|bo... | stack_v2_sparse_classes_36k_train_012173 | 1,297 | no_license | [
{
"docstring": "思路: 2个set存",
"name": "subarrayBitwiseORs",
"signature": "def subarrayBitwiseORs(self, A: List[int]) -> int"
},
{
"docstring": "思路: 位运算剪枝来代替两个set轮流io",
"name": "subarrayBitwiseORs2",
"signature": "def subarrayBitwiseORs2(self, A: List[int]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_004773 | Implement the Python class `Solution` described below.
Class description:
[898. 子数组按位或操作](https://leetcode-cn.com/problems/bitwise-ors-of-subarrays/)
Method signatures and docstrings:
- def subarrayBitwiseORs(self, A: List[int]) -> int: 思路: 2个set存
- def subarrayBitwiseORs2(self, A: List[int]) -> int: 思路: 位运算剪枝来代替两个se... | Implement the Python class `Solution` described below.
Class description:
[898. 子数组按位或操作](https://leetcode-cn.com/problems/bitwise-ors-of-subarrays/)
Method signatures and docstrings:
- def subarrayBitwiseORs(self, A: List[int]) -> int: 思路: 2个set存
- def subarrayBitwiseORs2(self, A: List[int]) -> int: 思路: 位运算剪枝来代替两个se... | dbe8eb449e5b112a71bc1cd4eabfd138304de4a3 | <|skeleton|>
class Solution:
"""[898. 子数组按位或操作](https://leetcode-cn.com/problems/bitwise-ors-of-subarrays/)"""
def subarrayBitwiseORs(self, A: List[int]) -> int:
"""思路: 2个set存"""
<|body_0|>
def subarrayBitwiseORs2(self, A: List[int]) -> int:
"""思路: 位运算剪枝来代替两个set轮流io"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""[898. 子数组按位或操作](https://leetcode-cn.com/problems/bitwise-ors-of-subarrays/)"""
def subarrayBitwiseORs(self, A: List[int]) -> int:
"""思路: 2个set存"""
res = set()
B = set()
for a in A:
B = {b | a for b in B} | {a}
res |= B
return le... | the_stack_v2_python_sparse | leetcode/601-900/898.py | Rivarrl/leetcode_python | train | 3 |
9f6bd885b1f72e95c0c6abaf23878d839c9f0516 | [
"if component_type is None or not isinstance(component_container, ComponentContainer) or (not hasattr(component_container, 'has_component')):\n return False\nreturn component_container.has_component(component_type)",
"if component_type is None or not isinstance(component_container, ComponentContainer) or (not ... | <|body_start_0|>
if component_type is None or not isinstance(component_container, ComponentContainer) or (not hasattr(component_container, 'has_component')):
return False
return component_container.has_component(component_type)
<|end_body_0|>
<|body_start_1|>
if component_type is No... | Utilities for handling components of component containers. | CommonComponentUtils | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommonComponentUtils:
"""Utilities for handling components of component containers."""
def has_component(component_container: ComponentContainer, component_type: CommonComponentType) -> bool:
"""has_component(component_container, component_type) Determine if a ComponentContainer has ... | stack_v2_sparse_classes_36k_train_012174 | 3,633 | permissive | [
{
"docstring": "has_component(component_container, component_type) Determine if a ComponentContainer has a component of the specified type. :param component_container: The ComponentContainer to check. :type component_container: ComponentContainer :param component_type: The type of component to locate. :type com... | 3 | null | Implement the Python class `CommonComponentUtils` described below.
Class description:
Utilities for handling components of component containers.
Method signatures and docstrings:
- def has_component(component_container: ComponentContainer, component_type: CommonComponentType) -> bool: has_component(component_containe... | Implement the Python class `CommonComponentUtils` described below.
Class description:
Utilities for handling components of component containers.
Method signatures and docstrings:
- def has_component(component_container: ComponentContainer, component_type: CommonComponentType) -> bool: has_component(component_containe... | b59ea7e5f4bd01d3b3bd7603843d525a9c179867 | <|skeleton|>
class CommonComponentUtils:
"""Utilities for handling components of component containers."""
def has_component(component_container: ComponentContainer, component_type: CommonComponentType) -> bool:
"""has_component(component_container, component_type) Determine if a ComponentContainer has ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommonComponentUtils:
"""Utilities for handling components of component containers."""
def has_component(component_container: ComponentContainer, component_type: CommonComponentType) -> bool:
"""has_component(component_container, component_type) Determine if a ComponentContainer has a component o... | the_stack_v2_python_sparse | src/sims4communitylib/utils/common_component_utils.py | velocist/TS4CheatsInfo | train | 1 |
c76ce85112c52bafde6e529ee6819b36ee420489 | [
"self.text_predicate = text_predicate\nself.content = content\nself.skipping = bool(start)\nself.start: Optional[str] = None\nif start is not None and self.skipping:\n self.start = start.replace('_', ' ')\nself.site = site or pywikibot.Site()\nif not namespaces:\n self.namespaces = self.site.namespaces\nelse:... | <|body_start_0|>
self.text_predicate = text_predicate
self.content = content
self.skipping = bool(start)
self.start: Optional[str] = None
if start is not None and self.skipping:
self.start = start.replace('_', ' ')
self.site = site or pywikibot.Site()
... | Xml iterator that yields Page objects. .. versionadded:: 7.2 the `content` parameter :param filename: filename of XML dump :param start: skip entries below that value :param namespaces: namespace filter :param site: current site for the generator :param text_predicate: a callable with entry.text as parameter and boolea... | XMLDumpPageGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XMLDumpPageGenerator:
"""Xml iterator that yields Page objects. .. versionadded:: 7.2 the `content` parameter :param filename: filename of XML dump :param start: skip entries below that value :param namespaces: namespace filter :param site: current site for the generator :param text_predicate: a ... | stack_v2_sparse_classes_36k_train_012175 | 43,909 | permissive | [
{
"docstring": "Initializer.",
"name": "__init__",
"signature": "def __init__(self, filename: str, start: Optional[str]=None, namespaces: Union[None, NAMESPACE_OR_STR_TYPE, Sequence[NAMESPACE_OR_STR_TYPE]]=None, site: OPT_SITE_TYPE=None, text_predicate: Optional[Callable[[str], bool]]=None, content=Fals... | 2 | null | Implement the Python class `XMLDumpPageGenerator` described below.
Class description:
Xml iterator that yields Page objects. .. versionadded:: 7.2 the `content` parameter :param filename: filename of XML dump :param start: skip entries below that value :param namespaces: namespace filter :param site: current site for ... | Implement the Python class `XMLDumpPageGenerator` described below.
Class description:
Xml iterator that yields Page objects. .. versionadded:: 7.2 the `content` parameter :param filename: filename of XML dump :param start: skip entries below that value :param namespaces: namespace filter :param site: current site for ... | 5c01e6bfcd328bc6eae643e661f1a0ae57612808 | <|skeleton|>
class XMLDumpPageGenerator:
"""Xml iterator that yields Page objects. .. versionadded:: 7.2 the `content` parameter :param filename: filename of XML dump :param start: skip entries below that value :param namespaces: namespace filter :param site: current site for the generator :param text_predicate: a ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XMLDumpPageGenerator:
"""Xml iterator that yields Page objects. .. versionadded:: 7.2 the `content` parameter :param filename: filename of XML dump :param start: skip entries below that value :param namespaces: namespace filter :param site: current site for the generator :param text_predicate: a callable with... | the_stack_v2_python_sparse | pywikibot/pagegenerators/_generators.py | wikimedia/pywikibot | train | 432 |
95d1af9bb9a34775ea089799b14cf80864985e86 | [
"super(TypeShareCoder, self).__init__(structure, conf)\nself.taskindices = {t: i for i, t in enumerate(structure.tasks.keys())}\nself.typeindices = dict()\nindex = len(structure.tasks)\nfor argtype in structure.types:\n self.typeindices[argtype] = {t: i + index for i, t in enumerate(structure.types[argtype].opti... | <|body_start_0|>
super(TypeShareCoder, self).__init__(structure, conf)
self.taskindices = {t: i for i, t in enumerate(structure.tasks.keys())}
self.typeindices = dict()
index = len(structure.tasks)
for argtype in structure.types:
self.typeindices[argtype] = {t: i + in... | a Coder that shares the places for args with the same type | TypeShareCoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TypeShareCoder:
"""a Coder that shares the places for args with the same type"""
def __init__(self, structure, conf):
"""Coder constructor Args: structure: a Structure object"""
<|body_0|>
def encode(self, task):
"""encode the task representation into a vector Ar... | stack_v2_sparse_classes_36k_train_012176 | 3,430 | no_license | [
{
"docstring": "Coder constructor Args: structure: a Structure object",
"name": "__init__",
"signature": "def __init__(self, structure, conf)"
},
{
"docstring": "encode the task representation into a vector Args: task: the task reresentation as a Task object Returns: the encoded task representat... | 3 | stack_v2_sparse_classes_30k_train_007445 | Implement the Python class `TypeShareCoder` described below.
Class description:
a Coder that shares the places for args with the same type
Method signatures and docstrings:
- def __init__(self, structure, conf): Coder constructor Args: structure: a Structure object
- def encode(self, task): encode the task representa... | Implement the Python class `TypeShareCoder` described below.
Class description:
a Coder that shares the places for args with the same type
Method signatures and docstrings:
- def __init__(self, structure, conf): Coder constructor Args: structure: a Structure object
- def encode(self, task): encode the task representa... | fcbe609505f86f142cc6e78686e5c25b0e58e178 | <|skeleton|>
class TypeShareCoder:
"""a Coder that shares the places for args with the same type"""
def __init__(self, structure, conf):
"""Coder constructor Args: structure: a Structure object"""
<|body_0|>
def encode(self, task):
"""encode the task representation into a vector Ar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TypeShareCoder:
"""a Coder that shares the places for args with the same type"""
def __init__(self, structure, conf):
"""Coder constructor Args: structure: a Structure object"""
super(TypeShareCoder, self).__init__(structure, conf)
self.taskindices = {t: i for i, t in enumerate(st... | the_stack_v2_python_sparse | assist/tasks/typeshare_coder.py | GillesDepypere/assist | train | 1 |
d60f2023b2cac48bf29ceb23acb8fd621716fba2 | [
"self.logfile_dir = logfile_dir\nself.logfile_name = logfile_name\nself.logfile_path = os.path.join(self.logfile_dir, self.logfile_name)\nself.screen_msg = screen_msg\nself.write_msg(msg='--NEW LOG STARTING FROM THIS LINE--', mode='w')",
"indent_tabs = ''.join(['\\t'] * msg_level)\ndecorated_msg = '{} {} {}-MSG {... | <|body_start_0|>
self.logfile_dir = logfile_dir
self.logfile_name = logfile_name
self.logfile_path = os.path.join(self.logfile_dir, self.logfile_name)
self.screen_msg = screen_msg
self.write_msg(msg='--NEW LOG STARTING FROM THIS LINE--', mode='w')
<|end_body_0|>
<|body_start_1|>... | Logfile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Logfile:
def __init__(self, logfile_dir='./', logfile_name='plom.log', screen_msg=True):
"""Initializing the logfile - logfile_dir: default is the same path of the PLoM package - logfile_name: default is the "plom.log" - screen_msg: default is to show message on screen"""
<|body_... | stack_v2_sparse_classes_36k_train_012177 | 11,187 | no_license | [
{
"docstring": "Initializing the logfile - logfile_dir: default is the same path of the PLoM package - logfile_name: default is the \"plom.log\" - screen_msg: default is to show message on screen",
"name": "__init__",
"signature": "def __init__(self, logfile_dir='./', logfile_name='plom.log', screen_msg... | 3 | null | Implement the Python class `Logfile` described below.
Class description:
Implement the Logfile class.
Method signatures and docstrings:
- def __init__(self, logfile_dir='./', logfile_name='plom.log', screen_msg=True): Initializing the logfile - logfile_dir: default is the same path of the PLoM package - logfile_name:... | Implement the Python class `Logfile` described below.
Class description:
Implement the Logfile class.
Method signatures and docstrings:
- def __init__(self, logfile_dir='./', logfile_name='plom.log', screen_msg=True): Initializing the logfile - logfile_dir: default is the same path of the PLoM package - logfile_name:... | 9c051b36e3c62b63795ae0ce072f80a02e342c34 | <|skeleton|>
class Logfile:
def __init__(self, logfile_dir='./', logfile_name='plom.log', screen_msg=True):
"""Initializing the logfile - logfile_dir: default is the same path of the PLoM package - logfile_name: default is the "plom.log" - screen_msg: default is to show message on screen"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Logfile:
def __init__(self, logfile_dir='./', logfile_name='plom.log', screen_msg=True):
"""Initializing the logfile - logfile_dir: default is the same path of the PLoM package - logfile_name: default is the "plom.log" - screen_msg: default is to show message on screen"""
self.logfile_dir = lo... | the_stack_v2_python_sparse | modules/performUQ/SimCenterUQ/PLoM/general.py | NHERI-SimCenter/SimCenterBackendApplications | train | 5 | |
c0b809a7c247a1f39c762fc62e0d4f045f528300 | [
"super(GroupEmbedding, self).__init__()\nself.user_embedding = nn.Embedding(user_num + 1, embedding_size)\nself.item_embedding = nn.Embedding(item_num + 1, embedding_size)\nself.user_attention = nn.Sequential(nn.Linear(embedding_size, embedding_size), nn.ReLU(), nn.Linear(embedding_size, 1))\nself.user_softmax = nn... | <|body_start_0|>
super(GroupEmbedding, self).__init__()
self.user_embedding = nn.Embedding(user_num + 1, embedding_size)
self.item_embedding = nn.Embedding(item_num + 1, embedding_size)
self.user_attention = nn.Sequential(nn.Linear(embedding_size, embedding_size), nn.ReLU(), nn.Linear(em... | Embedding Network | GroupEmbedding | [
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupEmbedding:
"""Embedding Network"""
def __init__(self, embedding_size: int, user_num: int, item_num: int):
"""Initialize Embedding :param embedding_size: embedding size :param user_num: number of users :param item_num: number of items"""
<|body_0|>
def forward(self, ... | stack_v2_sparse_classes_36k_train_012178 | 4,654 | permissive | [
{
"docstring": "Initialize Embedding :param embedding_size: embedding size :param user_num: number of users :param item_num: number of items",
"name": "__init__",
"signature": "def __init__(self, embedding_size: int, user_num: int, item_num: int)"
},
{
"docstring": "Forward :param group_members:... | 2 | null | Implement the Python class `GroupEmbedding` described below.
Class description:
Embedding Network
Method signatures and docstrings:
- def __init__(self, embedding_size: int, user_num: int, item_num: int): Initialize Embedding :param embedding_size: embedding size :param user_num: number of users :param item_num: numb... | Implement the Python class `GroupEmbedding` described below.
Class description:
Embedding Network
Method signatures and docstrings:
- def __init__(self, embedding_size: int, user_num: int, item_num: int): Initialize Embedding :param embedding_size: embedding size :param user_num: number of users :param item_num: numb... | 3bf673bb7980a2ba972241b0ba4bae7ca3af1870 | <|skeleton|>
class GroupEmbedding:
"""Embedding Network"""
def __init__(self, embedding_size: int, user_num: int, item_num: int):
"""Initialize Embedding :param embedding_size: embedding size :param user_num: number of users :param item_num: number of items"""
<|body_0|>
def forward(self, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupEmbedding:
"""Embedding Network"""
def __init__(self, embedding_size: int, user_num: int, item_num: int):
"""Initialize Embedding :param embedding_size: embedding size :param user_num: number of users :param item_num: number of items"""
super(GroupEmbedding, self).__init__()
... | the_stack_v2_python_sparse | recohut/models/embedding.py | recohut/recohut | train | 2 |
90b61c67022ddea582804ac8952d825dac68f539 | [
"need_params = ['device_id', 'device_owner', 'tenant_id', 'network_id']\nfilters, kwargs = rest_utils.parse_filters_kwargs(request, need_params)\nif not kwargs.get('tenant_id'):\n kwargs.update({'tenant_id': request.user.tenant_id})\nnetwork_list = api.neutron.network_list_for_tenant(request, kwargs.get('tenant_... | <|body_start_0|>
need_params = ['device_id', 'device_owner', 'tenant_id', 'network_id']
filters, kwargs = rest_utils.parse_filters_kwargs(request, need_params)
if not kwargs.get('tenant_id'):
kwargs.update({'tenant_id': request.user.tenant_id})
network_list = api.neutron.netw... | API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports | Ports | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ports:
"""API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports"""
def get(self, request):
"""Get a list of unused free ports The listing result is an object with property "items". Each item is a port."""
<|body_0|>
def post(self, request)... | stack_v2_sparse_classes_36k_train_012179 | 30,067 | permissive | [
{
"docstring": "Get a list of unused free ports The listing result is an object with property \"items\". Each item is a port.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Create a port on a specified network. :param network_id: network id a subnet is created on :para... | 2 | null | Implement the Python class `Ports` described below.
Class description:
API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports
Method signatures and docstrings:
- def get(self, request): Get a list of unused free ports The listing result is an object with property "items". Each item is a... | Implement the Python class `Ports` described below.
Class description:
API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports
Method signatures and docstrings:
- def get(self, request): Get a list of unused free ports The listing result is an object with property "items". Each item is a... | 9524f1952461c83db485d5d1702c350b158d7ce0 | <|skeleton|>
class Ports:
"""API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports"""
def get(self, request):
"""Get a list of unused free ports The listing result is an object with property "items". Each item is a port."""
<|body_0|>
def post(self, request)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ports:
"""API for Neutron Ports http://developer.openstack.org/api-ref-networking-v2.html#ports"""
def get(self, request):
"""Get a list of unused free ports The listing result is an object with property "items". Each item is a port."""
need_params = ['device_id', 'device_owner', 'tenant_... | the_stack_v2_python_sparse | easystack_dashboard/api/rest/neutron.py | oksbsb/horizon-acc | train | 0 |
69117973a07607d24177ed33d7a8ba403a976538 | [
"control_palette = control_instance.path.palette()\ncontrol_value = control_instance.path.value()\ncolor = QtCore.Qt.white\nred = QtGui.QColor(255, 220, 220)\nyellow = QtGui.QColor(255, 255, 200)\nis_valid = False\nif control_value is traits.Undefined:\n is_valid = True\n if not control_instance.optional:\n ... | <|body_start_0|>
control_palette = control_instance.path.palette()
control_value = control_instance.path.value()
color = QtCore.Qt.white
red = QtGui.QColor(255, 220, 220)
yellow = QtGui.QColor(255, 255, 200)
is_valid = False
if control_value is traits.Undefined:
... | Control to enter a directory. | DirectoryControlWidget | [
"CECILL-B"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DirectoryControlWidget:
"""Control to enter a directory."""
def is_valid(control_instance, *args, **kwargs):
"""Method to check if the new control value is correct. If the new entered value is not correct, the backroung control color will be red. Parameters ---------- control_instanc... | stack_v2_sparse_classes_36k_train_012180 | 3,756 | permissive | [
{
"docstring": "Method to check if the new control value is correct. If the new entered value is not correct, the backroung control color will be red. Parameters ---------- control_instance: QWidget (mandatory) the control widget we want to validate Returns ------- out: bool True if the control value is a file,... | 2 | null | Implement the Python class `DirectoryControlWidget` described below.
Class description:
Control to enter a directory.
Method signatures and docstrings:
- def is_valid(control_instance, *args, **kwargs): Method to check if the new control value is correct. If the new entered value is not correct, the backroung control... | Implement the Python class `DirectoryControlWidget` described below.
Class description:
Control to enter a directory.
Method signatures and docstrings:
- def is_valid(control_instance, *args, **kwargs): Method to check if the new control value is correct. If the new entered value is not correct, the backroung control... | 779e254098b183eb312eb589268c474dd65c5679 | <|skeleton|>
class DirectoryControlWidget:
"""Control to enter a directory."""
def is_valid(control_instance, *args, **kwargs):
"""Method to check if the new control value is correct. If the new entered value is not correct, the backroung control color will be red. Parameters ---------- control_instanc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DirectoryControlWidget:
"""Control to enter a directory."""
def is_valid(control_instance, *args, **kwargs):
"""Method to check if the new control value is correct. If the new entered value is not correct, the backroung control color will be red. Parameters ---------- control_instance: QWidget (m... | the_stack_v2_python_sparse | python/soma/qt_gui/controls/Directory.py | populse/soma-base | train | 0 |
6b1140cf106a575116f8049bf87304e977d93aa1 | [
"super(Ps, self).__init__(connection=connection, prompt=prompt, newline_chars=newline_chars, runner=runner)\nself.current_ret = list()\nself.options = options\nself._headers = None\nself._header_pos = None\nself.ret_required = False\nself._converter_helper = ConverterHelper.get_converter_helper()",
"if is_full_li... | <|body_start_0|>
super(Ps, self).__init__(connection=connection, prompt=prompt, newline_chars=newline_chars, runner=runner)
self.current_ret = list()
self.options = options
self._headers = None
self._header_pos = None
self.ret_required = False
self._converter_help... | Unix command ps. | Ps | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ps:
"""Unix command ps."""
def __init__(self, connection=None, options='', prompt=None, newline_chars=None, runner=None):
"""Represents Unix command ps. :param connection: moler connection to device, terminal where command is executed :param options: ps command options as string :par... | stack_v2_sparse_classes_36k_train_012181 | 15,745 | permissive | [
{
"docstring": "Represents Unix command ps. :param connection: moler connection to device, terminal where command is executed :param options: ps command options as string :param prompt: prompt (on system where command runs). :param newline_chars: characters to split lines :param runner: Runner to run command",
... | 5 | null | Implement the Python class `Ps` described below.
Class description:
Unix command ps.
Method signatures and docstrings:
- def __init__(self, connection=None, options='', prompt=None, newline_chars=None, runner=None): Represents Unix command ps. :param connection: moler connection to device, terminal where command is e... | Implement the Python class `Ps` described below.
Class description:
Unix command ps.
Method signatures and docstrings:
- def __init__(self, connection=None, options='', prompt=None, newline_chars=None, runner=None): Represents Unix command ps. :param connection: moler connection to device, terminal where command is e... | 5a7bb06807b6e0124c77040367d0c20f42849a4c | <|skeleton|>
class Ps:
"""Unix command ps."""
def __init__(self, connection=None, options='', prompt=None, newline_chars=None, runner=None):
"""Represents Unix command ps. :param connection: moler connection to device, terminal where command is executed :param options: ps command options as string :par... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ps:
"""Unix command ps."""
def __init__(self, connection=None, options='', prompt=None, newline_chars=None, runner=None):
"""Represents Unix command ps. :param connection: moler connection to device, terminal where command is executed :param options: ps command options as string :param prompt: pr... | the_stack_v2_python_sparse | moler/cmd/unix/ps.py | nokia/moler | train | 60 |
ed54f595f72848358d573f25fc017e83ead55810 | [
"super(Reader, self).__init__(auto_prefix=False)\nself.encoder = Albert(batch_size)\nparam_dict = load_checkpoint(encoder_ck_file)\nnot_load_params, _ = load_param_into_net(self.encoder, param_dict)\nprint(f'reader albert not loaded params: {not_load_params}')\nself.downstream = Reader_Downstream()\nparam_dict = lo... | <|body_start_0|>
super(Reader, self).__init__(auto_prefix=False)
self.encoder = Albert(batch_size)
param_dict = load_checkpoint(encoder_ck_file)
not_load_params, _ = load_param_into_net(self.encoder, param_dict)
print(f'reader albert not loaded params: {not_load_params}')
... | Reader model | Reader | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reader:
"""Reader model"""
def __init__(self, batch_size, encoder_ck_file, downstream_ck_file):
"""init function"""
<|body_0|>
def construct(self, input_ids, attn_mask, token_type_ids, context_mask, square_mask, packing_mask, cache_mask, para_start_mapping, sent_end_mapp... | stack_v2_sparse_classes_36k_train_012182 | 3,103 | permissive | [
{
"docstring": "init function",
"name": "__init__",
"signature": "def __init__(self, batch_size, encoder_ck_file, downstream_ck_file)"
},
{
"docstring": "construct function",
"name": "construct",
"signature": "def construct(self, input_ids, attn_mask, token_type_ids, context_mask, square... | 2 | null | Implement the Python class `Reader` described below.
Class description:
Reader model
Method signatures and docstrings:
- def __init__(self, batch_size, encoder_ck_file, downstream_ck_file): init function
- def construct(self, input_ids, attn_mask, token_type_ids, context_mask, square_mask, packing_mask, cache_mask, p... | Implement the Python class `Reader` described below.
Class description:
Reader model
Method signatures and docstrings:
- def __init__(self, batch_size, encoder_ck_file, downstream_ck_file): init function
- def construct(self, input_ids, attn_mask, token_type_ids, context_mask, square_mask, packing_mask, cache_mask, p... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class Reader:
"""Reader model"""
def __init__(self, batch_size, encoder_ck_file, downstream_ck_file):
"""init function"""
<|body_0|>
def construct(self, input_ids, attn_mask, token_type_ids, context_mask, square_mask, packing_mask, cache_mask, para_start_mapping, sent_end_mapp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Reader:
"""Reader model"""
def __init__(self, batch_size, encoder_ck_file, downstream_ck_file):
"""init function"""
super(Reader, self).__init__(auto_prefix=False)
self.encoder = Albert(batch_size)
param_dict = load_checkpoint(encoder_ck_file)
not_load_params, _ = ... | the_stack_v2_python_sparse | research/nlp/tprr/src/reader.py | mindspore-ai/models | train | 301 |
6da4fd9d59bed10ad4639d3c464deb47a3e7d103 | [
"torch_and_transformers_import.check()\nsuper().__init__()\nself.top_p = top_p\nself.score_field = score_field\nself.strict = strict\nself.devices, _ = initialize_device_settings(devices=devices, use_cuda=use_gpu, multi_gpu=True)\nself.cross_encoder = CrossEncoder(model_name_or_path, device=str(self.devices[0]))",
... | <|body_start_0|>
torch_and_transformers_import.check()
super().__init__()
self.top_p = top_p
self.score_field = score_field
self.strict = strict
self.devices, _ = initialize_device_settings(devices=devices, use_cuda=use_gpu, multi_gpu=True)
self.cross_encoder = Cr... | Filters documents based on the cumulative probability of the similarity scores between the query and the documents using top p sampling. Top p sampling selects a subset of the most relevant data points from a larger set of data. The technique involves calculating the cumulative probability of the scores of each data po... | TopPSampler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopPSampler:
"""Filters documents based on the cumulative probability of the similarity scores between the query and the documents using top p sampling. Top p sampling selects a subset of the most relevant data points from a larger set of data. The technique involves calculating the cumulative pr... | stack_v2_sparse_classes_36k_train_012183 | 7,453 | permissive | [
{
"docstring": "Initialize a TopPSampler. :param model_name_or_path: Path to a pretrained sentence-transformers model. :param top_p: Cumulative probability threshold for filtering the documents (usually between 0.9 and 0.99). :param strict: If `top_p` is set to a low value and sampler returned no documents, the... | 3 | null | Implement the Python class `TopPSampler` described below.
Class description:
Filters documents based on the cumulative probability of the similarity scores between the query and the documents using top p sampling. Top p sampling selects a subset of the most relevant data points from a larger set of data. The technique... | Implement the Python class `TopPSampler` described below.
Class description:
Filters documents based on the cumulative probability of the similarity scores between the query and the documents using top p sampling. Top p sampling selects a subset of the most relevant data points from a larger set of data. The technique... | 5f1256ac7e5734c2ea481e72cb7e02c34baf8c43 | <|skeleton|>
class TopPSampler:
"""Filters documents based on the cumulative probability of the similarity scores between the query and the documents using top p sampling. Top p sampling selects a subset of the most relevant data points from a larger set of data. The technique involves calculating the cumulative pr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TopPSampler:
"""Filters documents based on the cumulative probability of the similarity scores between the query and the documents using top p sampling. Top p sampling selects a subset of the most relevant data points from a larger set of data. The technique involves calculating the cumulative probability of ... | the_stack_v2_python_sparse | haystack/nodes/sampler/top_p_sampler.py | deepset-ai/haystack | train | 10,599 |
1a4fcfbc2af81d0722cb695cfefe25bddde9d8ad | [
"super(HistoryChangesetMiddleware, self).process_request(request)\nif request.META.get('REQUEST_METHOD') in ('GET', 'HEAD'):\n return\nrequest.changeset = None\nrequest.close_changeset = False\nrequest.delay_cache = False\nchangeset_id = request.GET.get('use_changeset')\nif changeset_id:\n changeset = Changes... | <|body_start_0|>
super(HistoryChangesetMiddleware, self).process_request(request)
if request.META.get('REQUEST_METHOD') in ('GET', 'HEAD'):
return
request.changeset = None
request.close_changeset = False
request.delay_cache = False
changeset_id = request.GET.g... | Add a changeset to the HistoricalRecords request. | HistoryChangesetMiddleware | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HistoryChangesetMiddleware:
"""Add a changeset to the HistoricalRecords request."""
def process_request(self, request):
"""Load requested changeset or prepare auto-changeset."""
<|body_0|>
def bad_request(self, request, message):
"""Reject invalid request changes... | stack_v2_sparse_classes_36k_train_012184 | 7,986 | no_license | [
{
"docstring": "Load requested changeset or prepare auto-changeset.",
"name": "process_request",
"signature": "def process_request(self, request)"
},
{
"docstring": "Reject invalid request changeset.",
"name": "bad_request",
"signature": "def bad_request(self, request, message)"
},
{... | 3 | stack_v2_sparse_classes_30k_train_011278 | Implement the Python class `HistoryChangesetMiddleware` described below.
Class description:
Add a changeset to the HistoricalRecords request.
Method signatures and docstrings:
- def process_request(self, request): Load requested changeset or prepare auto-changeset.
- def bad_request(self, request, message): Reject in... | Implement the Python class `HistoryChangesetMiddleware` described below.
Class description:
Add a changeset to the HistoricalRecords request.
Method signatures and docstrings:
- def process_request(self, request): Load requested changeset or prepare auto-changeset.
- def bad_request(self, request, message): Reject in... | bc092964153b03381aaff74a4d80f43a2b2dec19 | <|skeleton|>
class HistoryChangesetMiddleware:
"""Add a changeset to the HistoricalRecords request."""
def process_request(self, request):
"""Load requested changeset or prepare auto-changeset."""
<|body_0|>
def bad_request(self, request, message):
"""Reject invalid request changes... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HistoryChangesetMiddleware:
"""Add a changeset to the HistoricalRecords request."""
def process_request(self, request):
"""Load requested changeset or prepare auto-changeset."""
super(HistoryChangesetMiddleware, self).process_request(request)
if request.META.get('REQUEST_METHOD') ... | the_stack_v2_python_sparse | browsercompat/webplatformcompat/history.py | WeilerWebServices/MDN-Web-Docs | train | 1 |
55e1abb258743c4cc50fdf4aa1c4549d94582153 | [
"self.model = GMF(config['model'])\nself.loss = torch.nn.BCELoss()\nsuper(GMFEngine, self).__init__(config)",
"assert hasattr(self, 'model'), 'Please specify the exact model !'\nusers, items, ratings = (users.to(self.device), items.to(self.device), ratings.to(self.device))\nself.optimizer.zero_grad()\nratings_pre... | <|body_start_0|>
self.model = GMF(config['model'])
self.loss = torch.nn.BCELoss()
super(GMFEngine, self).__init__(config)
<|end_body_0|>
<|body_start_1|>
assert hasattr(self, 'model'), 'Please specify the exact model !'
users, items, ratings = (users.to(self.device), items.to(se... | Engine for training & evaluating GMF model. | GMFEngine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GMFEngine:
"""Engine for training & evaluating GMF model."""
def __init__(self, config):
"""Initialize GMFEngine Class."""
<|body_0|>
def train_single_batch(self, users, items, ratings):
"""Train the model in a single batch. Args: batch_data (list): batch users, ... | stack_v2_sparse_classes_36k_train_012185 | 3,601 | permissive | [
{
"docstring": "Initialize GMFEngine Class.",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Train the model in a single batch. Args: batch_data (list): batch users, positive items and negative items. Return: loss (float): batch loss.",
"name": "train_single... | 3 | null | Implement the Python class `GMFEngine` described below.
Class description:
Engine for training & evaluating GMF model.
Method signatures and docstrings:
- def __init__(self, config): Initialize GMFEngine Class.
- def train_single_batch(self, users, items, ratings): Train the model in a single batch. Args: batch_data ... | Implement the Python class `GMFEngine` described below.
Class description:
Engine for training & evaluating GMF model.
Method signatures and docstrings:
- def __init__(self, config): Initialize GMFEngine Class.
- def train_single_batch(self, users, items, ratings): Train the model in a single batch. Args: batch_data ... | 625189d5e1002a3edc27c3e3ce075fddf7ae1c92 | <|skeleton|>
class GMFEngine:
"""Engine for training & evaluating GMF model."""
def __init__(self, config):
"""Initialize GMFEngine Class."""
<|body_0|>
def train_single_batch(self, users, items, ratings):
"""Train the model in a single batch. Args: batch_data (list): batch users, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GMFEngine:
"""Engine for training & evaluating GMF model."""
def __init__(self, config):
"""Initialize GMFEngine Class."""
self.model = GMF(config['model'])
self.loss = torch.nn.BCELoss()
super(GMFEngine, self).__init__(config)
def train_single_batch(self, users, item... | the_stack_v2_python_sparse | beta_rec/models/gmf.py | beta-team/beta-recsys | train | 156 |
096b5e42b97daf89bae0e208beb0761f65d9d88f | [
"if not nums:\n return 0\nans = 0\nfor idx, i in enumerate(nums):\n if i == k:\n ans = max(ans, 1)\n for idy, j in enumerate(nums[idx + 1:]):\n i += j\n if i == k:\n ans = max(ans, idy + 2)\nreturn ans",
"prefix = 0\nindex = dict()\nans = 0\nfor idx, i in enumerate(nums):\... | <|body_start_0|>
if not nums:
return 0
ans = 0
for idx, i in enumerate(nums):
if i == k:
ans = max(ans, 1)
for idy, j in enumerate(nums[idx + 1:]):
i += j
if i == k:
ans = max(ans, idy + 2)
... | @param nums: an array @param k: a target value @return: the maximum length of a subarray that sums to k | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""@param nums: an array @param k: a target value @return: the maximum length of a subarray that sums to k"""
def maxSubArrayLen1(self, nums, k):
"""时间复杂度: O(n ^ 2) 超时"""
<|body_0|>
def maxSubArrayLen2(self, nums, target):
"""前缀和: sum[i], sum[j] j > i i... | stack_v2_sparse_classes_36k_train_012186 | 2,212 | no_license | [
{
"docstring": "时间复杂度: O(n ^ 2) 超时",
"name": "maxSubArrayLen1",
"signature": "def maxSubArrayLen1(self, nums, k)"
},
{
"docstring": "前缀和: sum[i], sum[j] j > i if: sum[i] + k = sum[j] then: k = sum[j] - sum[i] 因此每次计算完前缀和后, 只需要判断: 前缀和 - target 是否在dict中, 如果在, 则nums[i + 1: j]即为所求",
"name": "maxS... | 2 | stack_v2_sparse_classes_30k_train_011417 | Implement the Python class `Solution` described below.
Class description:
@param nums: an array @param k: a target value @return: the maximum length of a subarray that sums to k
Method signatures and docstrings:
- def maxSubArrayLen1(self, nums, k): 时间复杂度: O(n ^ 2) 超时
- def maxSubArrayLen2(self, nums, target): 前缀和: s... | Implement the Python class `Solution` described below.
Class description:
@param nums: an array @param k: a target value @return: the maximum length of a subarray that sums to k
Method signatures and docstrings:
- def maxSubArrayLen1(self, nums, k): 时间复杂度: O(n ^ 2) 超时
- def maxSubArrayLen2(self, nums, target): 前缀和: s... | c34757e66163e3be7b18d23c150c463e39c98442 | <|skeleton|>
class Solution:
"""@param nums: an array @param k: a target value @return: the maximum length of a subarray that sums to k"""
def maxSubArrayLen1(self, nums, k):
"""时间复杂度: O(n ^ 2) 超时"""
<|body_0|>
def maxSubArrayLen2(self, nums, target):
"""前缀和: sum[i], sum[j] j > i i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""@param nums: an array @param k: a target value @return: the maximum length of a subarray that sums to k"""
def maxSubArrayLen1(self, nums, k):
"""时间复杂度: O(n ^ 2) 超时"""
if not nums:
return 0
ans = 0
for idx, i in enumerate(nums):
if i ==... | the_stack_v2_python_sparse | lintcode/maximum-size-subarray-sum-equals-k.py | liujunsheng0/notes | train | 6 |
7d41496af057639223b02066655f2eabbec5c8e5 | [
"post_key = ndb.Key(urlsafe=post_id)\npost = post_key.get()\nself.render('blog/post_delete.html', post=post)",
"post_key = ndb.Key(urlsafe=post_id)\npost = post_key.get()\npost.key.delete()\nself.redirect('/blog/delete/post/success')"
] | <|body_start_0|>
post_key = ndb.Key(urlsafe=post_id)
post = post_key.get()
self.render('blog/post_delete.html', post=post)
<|end_body_0|>
<|body_start_1|>
post_key = ndb.Key(urlsafe=post_id)
post = post_key.get()
post.key.delete()
self.redirect('/blog/delete/post... | PostDeleteHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostDeleteHandler:
def get(self, post_id, *args, **kwargs):
"""Show user confirmation on post to delete"""
<|body_0|>
def post(self, post_id):
"""Delete post if post exist and user own post"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
post_key = ... | stack_v2_sparse_classes_36k_train_012187 | 829 | no_license | [
{
"docstring": "Show user confirmation on post to delete",
"name": "get",
"signature": "def get(self, post_id, *args, **kwargs)"
},
{
"docstring": "Delete post if post exist and user own post",
"name": "post",
"signature": "def post(self, post_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003861 | Implement the Python class `PostDeleteHandler` described below.
Class description:
Implement the PostDeleteHandler class.
Method signatures and docstrings:
- def get(self, post_id, *args, **kwargs): Show user confirmation on post to delete
- def post(self, post_id): Delete post if post exist and user own post | Implement the Python class `PostDeleteHandler` described below.
Class description:
Implement the PostDeleteHandler class.
Method signatures and docstrings:
- def get(self, post_id, *args, **kwargs): Show user confirmation on post to delete
- def post(self, post_id): Delete post if post exist and user own post
<|skel... | 53f3094549bac448fd8f6088142b03e6e374cc02 | <|skeleton|>
class PostDeleteHandler:
def get(self, post_id, *args, **kwargs):
"""Show user confirmation on post to delete"""
<|body_0|>
def post(self, post_id):
"""Delete post if post exist and user own post"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PostDeleteHandler:
def get(self, post_id, *args, **kwargs):
"""Show user confirmation on post to delete"""
post_key = ndb.Key(urlsafe=post_id)
post = post_key.get()
self.render('blog/post_delete.html', post=post)
def post(self, post_id):
"""Delete post if post exis... | the_stack_v2_python_sparse | app/post_delete_handler.py | thangthin/project-blog | train | 0 | |
ff890c55a8e0f80916b893ac39c98080cf131e61 | [
"super().__init__()\nextra_keys = kwargs.keys()\nfor extra_key in extra_keys:\n if extra_key not in ['sensitivity_map_model', 'model_name']:\n raise ValueError(f'{type(self).__name__} got key `{extra_key}` which is not supported.')\nself.unet: nn.Module\nif normalized:\n self.unet = NormUnetModel2d(in_... | <|body_start_0|>
super().__init__()
extra_keys = kwargs.keys()
for extra_key in extra_keys:
if extra_key not in ['sensitivity_map_model', 'model_name']:
raise ValueError(f'{type(self).__name__} got key `{extra_key}` which is not supported.')
self.unet: nn.Modu... | PyTorch implementation of a U-Net model for MRI Reconstruction. | Unet2d | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Unet2d:
"""PyTorch implementation of a U-Net model for MRI Reconstruction."""
def __init__(self, forward_operator: Callable, backward_operator: Callable, num_filters: int, num_pool_layers: int, dropout_probability: float, skip_connection: bool=False, normalized: bool=False, image_initializat... | stack_v2_sparse_classes_36k_train_012188 | 15,262 | permissive | [
{
"docstring": "Inits :class:`Unet2d`. Parameters ---------- forward_operator: Callable Forward Operator. backward_operator: Callable Backward Operator. num_filters: int Number of first layer filters. num_pool_layers: int Number of pooling layers. dropout_probability: float Dropout probability. skip_connection:... | 3 | stack_v2_sparse_classes_30k_train_014525 | Implement the Python class `Unet2d` described below.
Class description:
PyTorch implementation of a U-Net model for MRI Reconstruction.
Method signatures and docstrings:
- def __init__(self, forward_operator: Callable, backward_operator: Callable, num_filters: int, num_pool_layers: int, dropout_probability: float, sk... | Implement the Python class `Unet2d` described below.
Class description:
PyTorch implementation of a U-Net model for MRI Reconstruction.
Method signatures and docstrings:
- def __init__(self, forward_operator: Callable, backward_operator: Callable, num_filters: int, num_pool_layers: int, dropout_probability: float, sk... | 2a4c29342bc52a404aae097bc2654fb4323e1ac8 | <|skeleton|>
class Unet2d:
"""PyTorch implementation of a U-Net model for MRI Reconstruction."""
def __init__(self, forward_operator: Callable, backward_operator: Callable, num_filters: int, num_pool_layers: int, dropout_probability: float, skip_connection: bool=False, normalized: bool=False, image_initializat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Unet2d:
"""PyTorch implementation of a U-Net model for MRI Reconstruction."""
def __init__(self, forward_operator: Callable, backward_operator: Callable, num_filters: int, num_pool_layers: int, dropout_probability: float, skip_connection: bool=False, normalized: bool=False, image_initialization: str='zer... | the_stack_v2_python_sparse | direct/nn/unet/unet_2d.py | NKI-AI/direct | train | 151 |
8a1b9a85e32578f46b349476c1bd8d93f734abfc | [
"self.trialSet = trialSet\nself.easyOris = []\nself.hardOris = []\nself.numEasy = 30\nself.numHard = 20\nself.trialBuffer = []\nself.trialBufferPos = 0\nself.trialsByOrientation = {}\nfor t in trialSet:\n ori = t.sMinusOrientation\n if not ori in self.trialsByOrientation.keys():\n self.trialsByOrientat... | <|body_start_0|>
self.trialSet = trialSet
self.easyOris = []
self.hardOris = []
self.numEasy = 30
self.numHard = 20
self.trialBuffer = []
self.trialBufferPos = 0
self.trialsByOrientation = {}
for t in trialSet:
ori = t.sMinusOrientation... | SequencerInterval | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SequencerInterval:
def __init__(self, trialSet):
"""Sets up initial block and resets sequence. Creates a dictionary of trials arranged by their orientation. Args: trialSet: [list] Initial set of trials"""
<|body_0|>
def makeTrialBuffer(self):
"""Returns: [list] upcom... | stack_v2_sparse_classes_36k_train_012189 | 2,387 | no_license | [
{
"docstring": "Sets up initial block and resets sequence. Creates a dictionary of trials arranged by their orientation. Args: trialSet: [list] Initial set of trials",
"name": "__init__",
"signature": "def __init__(self, trialSet)"
},
{
"docstring": "Returns: [list] upcoming trials arranged by e... | 3 | null | Implement the Python class `SequencerInterval` described below.
Class description:
Implement the SequencerInterval class.
Method signatures and docstrings:
- def __init__(self, trialSet): Sets up initial block and resets sequence. Creates a dictionary of trials arranged by their orientation. Args: trialSet: [list] In... | Implement the Python class `SequencerInterval` described below.
Class description:
Implement the SequencerInterval class.
Method signatures and docstrings:
- def __init__(self, trialSet): Sets up initial block and resets sequence. Creates a dictionary of trials arranged by their orientation. Args: trialSet: [list] In... | 30b10c2d3f17909b437cd57b0325d8b4ba6929b8 | <|skeleton|>
class SequencerInterval:
def __init__(self, trialSet):
"""Sets up initial block and resets sequence. Creates a dictionary of trials arranged by their orientation. Args: trialSet: [list] Initial set of trials"""
<|body_0|>
def makeTrialBuffer(self):
"""Returns: [list] upcom... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SequencerInterval:
def __init__(self, trialSet):
"""Sets up initial block and resets sequence. Creates a dictionary of trials arranged by their orientation. Args: trialSet: [list] Initial set of trials"""
self.trialSet = trialSet
self.easyOris = []
self.hardOris = []
se... | the_stack_v2_python_sparse | ShrewDriver/sequencer/interval.py | msarvestani/shrewdriver | train | 2 | |
5b0d7616769a182b6ec79855e3584b130c5c06c8 | [
"self.conn = conn\nself._tables = {}\nself._rows = []\nself._global_errors = []\nself._global_warnings = []\nself._load_tables(self.conn)",
"for table, create_table in conn.tables().items():\n try:\n reader = Reader()\n reader.parse(create_table)\n except ValueError as e:\n print('Error... | <|body_start_0|>
self.conn = conn
self._tables = {}
self._rows = []
self._global_errors = []
self._global_warnings = []
self._load_tables(self.conn)
<|end_body_0|>
<|body_start_1|>
for table, create_table in conn.tables().items():
try:
... | Database | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Database:
def __init__(self, conn):
"""Constructor. Accepts a mygrations db wrapper :param conn: mygrations db wrapper :type conn: mygrations.drivers.mysqldb.mysqldb"""
<|body_0|>
def _load_tables(self, conn):
"""Reads a database from the MySQL connection. Accepts a ... | stack_v2_sparse_classes_36k_train_012190 | 3,339 | permissive | [
{
"docstring": "Constructor. Accepts a mygrations db wrapper :param conn: mygrations db wrapper :type conn: mygrations.drivers.mysqldb.mysqldb",
"name": "__init__",
"signature": "def __init__(self, conn)"
},
{
"docstring": "Reads a database from the MySQL connection. Accepts a mygrations db wrap... | 3 | null | Implement the Python class `Database` described below.
Class description:
Implement the Database class.
Method signatures and docstrings:
- def __init__(self, conn): Constructor. Accepts a mygrations db wrapper :param conn: mygrations db wrapper :type conn: mygrations.drivers.mysqldb.mysqldb
- def _load_tables(self, ... | Implement the Python class `Database` described below.
Class description:
Implement the Database class.
Method signatures and docstrings:
- def __init__(self, conn): Constructor. Accepts a mygrations db wrapper :param conn: mygrations db wrapper :type conn: mygrations.drivers.mysqldb.mysqldb
- def _load_tables(self, ... | 07dd733f3ee9e6e5b37afce7e16de3dcd93be6e1 | <|skeleton|>
class Database:
def __init__(self, conn):
"""Constructor. Accepts a mygrations db wrapper :param conn: mygrations db wrapper :type conn: mygrations.drivers.mysqldb.mysqldb"""
<|body_0|>
def _load_tables(self, conn):
"""Reads a database from the MySQL connection. Accepts a ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Database:
def __init__(self, conn):
"""Constructor. Accepts a mygrations db wrapper :param conn: mygrations db wrapper :type conn: mygrations.drivers.mysqldb.mysqldb"""
self.conn = conn
self._tables = {}
self._rows = []
self._global_errors = []
self._global_warn... | the_stack_v2_python_sparse | mygrations/formats/mysql/db_reader/database.py | cmancone/mygrations | train | 12 | |
6942a8c54638f3694df7675f120ba6496a69563e | [
"self.context_factor = context_factor\nself.test_factor = test_factor\nself._start_time = start_time\nself._end_time = end_time\nself._reb_type = reb_type\nself._context_num = context_num\nself._factor_groupnum = factor_groupnum\nself.show_progress = show_progress\nself._ind_cls = ind_cls",
"contextualfactor_test... | <|body_start_0|>
self.context_factor = context_factor
self.test_factor = test_factor
self._start_time = start_time
self._end_time = end_time
self._reb_type = reb_type
self._context_num = context_num
self._factor_groupnum = factor_groupnum
self.show_progres... | 使用条件因子对横截面股票划分分组，然后在每个分组内部进行对测试因子进行分组测试，从而查看测试因子 的表现是否受条件因子影响 | ConditionalTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConditionalTest:
"""使用条件因子对横截面股票划分分组，然后在每个分组内部进行对测试因子进行分组测试，从而查看测试因子 的表现是否受条件因子影响"""
def __init__(self, context_factor, test_factor, start_time, end_time, reb_type=MONTHLY, context_num=5, factor_groupnum=5, ind_cls='ZX_IND', show_progress=True):
"""Parameter --------- contex_factor: ... | stack_v2_sparse_classes_36k_train_012191 | 8,630 | no_license | [
{
"docstring": "Parameter --------- contex_factor: str 条件因子，要求能在fmaneger.get_factor_dict()返回的结果中找到 test_factor: str 测试因子，要求能在fmaneger.get_factor_dict()返回的结果中找到 start_time: datetime like 测试的开始时间 end_time: datetime like 测试的结束时间 reb_type: str, default MONTHLY 换仓频率，目前只支持月度（MONTHLY）和周度（WEEKLY） context_num: int, defa... | 6 | stack_v2_sparse_classes_30k_train_013503 | Implement the Python class `ConditionalTest` described below.
Class description:
使用条件因子对横截面股票划分分组，然后在每个分组内部进行对测试因子进行分组测试，从而查看测试因子 的表现是否受条件因子影响
Method signatures and docstrings:
- def __init__(self, context_factor, test_factor, start_time, end_time, reb_type=MONTHLY, context_num=5, factor_groupnum=5, ind_cls='ZX_IND',... | Implement the Python class `ConditionalTest` described below.
Class description:
使用条件因子对横截面股票划分分组，然后在每个分组内部进行对测试因子进行分组测试，从而查看测试因子 的表现是否受条件因子影响
Method signatures and docstrings:
- def __init__(self, context_factor, test_factor, start_time, end_time, reb_type=MONTHLY, context_num=5, factor_groupnum=5, ind_cls='ZX_IND',... | 4080154dbf05781f3b48f551ee830d9f66687f87 | <|skeleton|>
class ConditionalTest:
"""使用条件因子对横截面股票划分分组，然后在每个分组内部进行对测试因子进行分组测试，从而查看测试因子 的表现是否受条件因子影响"""
def __init__(self, context_factor, test_factor, start_time, end_time, reb_type=MONTHLY, context_num=5, factor_groupnum=5, ind_cls='ZX_IND', show_progress=True):
"""Parameter --------- contex_factor: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConditionalTest:
"""使用条件因子对横截面股票划分分组，然后在每个分组内部进行对测试因子进行分组测试，从而查看测试因子 的表现是否受条件因子影响"""
def __init__(self, context_factor, test_factor, start_time, end_time, reb_type=MONTHLY, context_num=5, factor_groupnum=5, ind_cls='ZX_IND', show_progress=True):
"""Parameter --------- contex_factor: str 条件因子，要求能在... | the_stack_v2_python_sparse | factortest/grouptest/conditionaltest.py | rlcjj/GeneralLib | train | 0 |
82b7a1472da221a53d8a2485753057f9610a160d | [
"self.name = _id\nself.host_type = 'rack'\nself.status = 'enabled'\nself.memberships = {}\nself.vCPUs = 0\nself.original_vCPUs = 0\nself.avail_vCPUs = 0\nself.mem_cap = 0\nself.original_mem_cap = 0\nself.avail_mem_cap = 0\nself.local_disk_cap = 0\nself.original_local_disk_cap = 0\nself.avail_local_disk_cap = 0\nsel... | <|body_start_0|>
self.name = _id
self.host_type = 'rack'
self.status = 'enabled'
self.memberships = {}
self.vCPUs = 0
self.original_vCPUs = 0
self.avail_vCPUs = 0
self.mem_cap = 0
self.original_mem_cap = 0
self.avail_mem_cap = 0
sel... | Class for Host Group Object. This Class represents a group of hosts. If a single host is a single server then host group is a rack or cluster of servers. This class contains all memberships and resources for the group of hosts. | HostGroup | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HostGroup:
"""Class for Host Group Object. This Class represents a group of hosts. If a single host is a single server then host group is a rack or cluster of servers. This class contains all memberships and resources for the group of hosts."""
def __init__(self, _id):
"""Init for Ho... | stack_v2_sparse_classes_36k_train_012192 | 21,975 | permissive | [
{
"docstring": "Init for Host Group Class.",
"name": "__init__",
"signature": "def __init__(self, _id)"
},
{
"docstring": "Init all host group resources to 0.",
"name": "init_resources",
"signature": "def init_resources(self)"
},
{
"docstring": "Init Host Group memberships.",
... | 6 | stack_v2_sparse_classes_30k_train_001953 | Implement the Python class `HostGroup` described below.
Class description:
Class for Host Group Object. This Class represents a group of hosts. If a single host is a single server then host group is a rack or cluster of servers. This class contains all memberships and resources for the group of hosts.
Method signatur... | Implement the Python class `HostGroup` described below.
Class description:
Class for Host Group Object. This Class represents a group of hosts. If a single host is a single server then host group is a rack or cluster of servers. This class contains all memberships and resources for the group of hosts.
Method signatur... | ea89fbfbbb488938ac322e2a9bb7f8f448a7cd76 | <|skeleton|>
class HostGroup:
"""Class for Host Group Object. This Class represents a group of hosts. If a single host is a single server then host group is a rack or cluster of servers. This class contains all memberships and resources for the group of hosts."""
def __init__(self, _id):
"""Init for Ho... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HostGroup:
"""Class for Host Group Object. This Class represents a group of hosts. If a single host is a single server then host group is a rack or cluster of servers. This class contains all memberships and resources for the group of hosts."""
def __init__(self, _id):
"""Init for Host Group Clas... | the_stack_v2_python_sparse | valet/engine/resource_manager/resource_base.py | att-comdev/valet | train | 5 |
d0189637af948eb9b79f3259caf5bcc55a3bde60 | [
"super().__init__(image=Chef.image, x=games.screen.width / 2, y=y, dx=speed)\nself.odds_change = odds_change\nself.time_til_drop = 0",
"if self.left < 0 or self.right > games.screen.width:\n self.dx = -self.dx\nelif random.randrange(self.odds_change) == 0:\n self.dx = -self.dx\nself.check_drop()",
"if sel... | <|body_start_0|>
super().__init__(image=Chef.image, x=games.screen.width / 2, y=y, dx=speed)
self.odds_change = odds_change
self.time_til_drop = 0
<|end_body_0|>
<|body_start_1|>
if self.left < 0 or self.right > games.screen.width:
self.dx = -self.dx
elif random.rand... | Chef whom throw pizza move left - right | Chef | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Chef:
"""Chef whom throw pizza move left - right"""
def __init__(self, y=55, speed=2, odds_change=200):
"""init object Chef"""
<|body_0|>
def update(self):
"""Defined got change course"""
<|body_1|>
def check_drop(self):
"""Reduce interval ex... | stack_v2_sparse_classes_36k_train_012193 | 6,619 | no_license | [
{
"docstring": "init object Chef",
"name": "__init__",
"signature": "def __init__(self, y=55, speed=2, odds_change=200)"
},
{
"docstring": "Defined got change course",
"name": "update",
"signature": "def update(self)"
},
{
"docstring": "Reduce interval expectation on one or drop ... | 3 | null | Implement the Python class `Chef` described below.
Class description:
Chef whom throw pizza move left - right
Method signatures and docstrings:
- def __init__(self, y=55, speed=2, odds_change=200): init object Chef
- def update(self): Defined got change course
- def check_drop(self): Reduce interval expectation on on... | Implement the Python class `Chef` described below.
Class description:
Chef whom throw pizza move left - right
Method signatures and docstrings:
- def __init__(self, y=55, speed=2, odds_change=200): init object Chef
- def update(self): Defined got change course
- def check_drop(self): Reduce interval expectation on on... | 501aed406bc88e0baebd402e18851f1f2f8ac9da | <|skeleton|>
class Chef:
"""Chef whom throw pizza move left - right"""
def __init__(self, y=55, speed=2, odds_change=200):
"""init object Chef"""
<|body_0|>
def update(self):
"""Defined got change course"""
<|body_1|>
def check_drop(self):
"""Reduce interval ex... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Chef:
"""Chef whom throw pizza move left - right"""
def __init__(self, y=55, speed=2, odds_change=200):
"""init object Chef"""
super().__init__(image=Chef.image, x=games.screen.width / 2, y=y, dx=speed)
self.odds_change = odds_change
self.time_til_drop = 0
def update(... | the_stack_v2_python_sparse | _Chapter_11_PYGAME_LIVEWIRES/panic_in_pizzeria.py | MrVeshij/Michael-Dawson | train | 1 |
5c464826b023af7d5d6f3ce7f6a2ffc6e913b977 | [
"self.login('Edith')\nself.browser.get(self.live_server_url + reverse('polls:home'))\ncreate_poll_link = wait_for(lambda: self.browser.find_element_by_link_text('Create a poll'))\ncreate_poll_link.click()\nquestion_box = wait_for(lambda: self.browser.find_element_by_name('question_text'))\nchoice_1_box = wait_for(l... | <|body_start_0|>
self.login('Edith')
self.browser.get(self.live_server_url + reverse('polls:home'))
create_poll_link = wait_for(lambda: self.browser.find_element_by_link_text('Create a poll'))
create_poll_link.click()
question_box = wait_for(lambda: self.browser.find_element_by_n... | Tests for polls. | PollTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PollTest:
"""Tests for polls."""
def test_can_create_poll(self):
"""Tests that user can create polls."""
<|body_0|>
def test_can_vote_on_poll(self):
"""Tests that user can vote on the poll."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.lo... | stack_v2_sparse_classes_36k_train_012194 | 3,674 | no_license | [
{
"docstring": "Tests that user can create polls.",
"name": "test_can_create_poll",
"signature": "def test_can_create_poll(self)"
},
{
"docstring": "Tests that user can vote on the poll.",
"name": "test_can_vote_on_poll",
"signature": "def test_can_vote_on_poll(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001408 | Implement the Python class `PollTest` described below.
Class description:
Tests for polls.
Method signatures and docstrings:
- def test_can_create_poll(self): Tests that user can create polls.
- def test_can_vote_on_poll(self): Tests that user can vote on the poll. | Implement the Python class `PollTest` described below.
Class description:
Tests for polls.
Method signatures and docstrings:
- def test_can_create_poll(self): Tests that user can create polls.
- def test_can_vote_on_poll(self): Tests that user can vote on the poll.
<|skeleton|>
class PollTest:
"""Tests for polls... | 5370e31e1b6a39604b1cae8ce3bafec3f4ec8842 | <|skeleton|>
class PollTest:
"""Tests for polls."""
def test_can_create_poll(self):
"""Tests that user can create polls."""
<|body_0|>
def test_can_vote_on_poll(self):
"""Tests that user can vote on the poll."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PollTest:
"""Tests for polls."""
def test_can_create_poll(self):
"""Tests that user can create polls."""
self.login('Edith')
self.browser.get(self.live_server_url + reverse('polls:home'))
create_poll_link = wait_for(lambda: self.browser.find_element_by_link_text('Create a ... | the_stack_v2_python_sparse | functional_tests/test_polls.py | shivams906/bootcamp-clone | train | 0 |
546da4336aab8bb0e83a3be2303b77c6baa21bcd | [
"try:\n self.init_rotation = init_rotation\n super().__init__(task_list, qubits=qubits, sweep_points=sweep_points, nr_seqs=nr_seqs, cycles=cycles, init_rotation=init_rotation, **kw)\nexcept Exception as x:\n self.exception = x\n traceback.print_exc()",
"pulse_op_codes_list = []\ntl = [self.preprocesse... | <|body_start_0|>
try:
self.init_rotation = init_rotation
super().__init__(task_list, qubits=qubits, sweep_points=sweep_points, nr_seqs=nr_seqs, cycles=cycles, init_rotation=init_rotation, **kw)
except Exception as x:
self.exception = x
traceback.print_exc(... | Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel. | SingleQubitXEB | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SingleQubitXEB:
"""Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel."""
def __init__(self, task_list, sweep_points=None, qubits=None, nr_seqs=None, cycles=None, init_rotation=None, **kw):
"""Init of the SingleQubitXEB class. The e... | stack_v2_sparse_classes_36k_train_012195 | 38,263 | permissive | [
{
"docstring": "Init of the SingleQubitXEB class. The experiment consists of applying [[Ry - Rz(theta)] * nr_cycles for nr_cycles in cycles] nr_seqs times, with random values of theta each time. Args: nr_seqs (int): the number of times to apply a random iteration of a sequence consisting of nr_cycles cycles. If... | 2 | stack_v2_sparse_classes_30k_val_000202 | Implement the Python class `SingleQubitXEB` described below.
Class description:
Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel.
Method signatures and docstrings:
- def __init__(self, task_list, sweep_points=None, qubits=None, nr_seqs=None, cycles=None, init_rota... | Implement the Python class `SingleQubitXEB` described below.
Class description:
Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel.
Method signatures and docstrings:
- def __init__(self, task_list, sweep_points=None, qubits=None, nr_seqs=None, cycles=None, init_rota... | bc6733d774fe31a23f4c7e73e5eb0beed8d30e7d | <|skeleton|>
class SingleQubitXEB:
"""Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel."""
def __init__(self, task_list, sweep_points=None, qubits=None, nr_seqs=None, cycles=None, init_rotation=None, **kw):
"""Init of the SingleQubitXEB class. The e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SingleQubitXEB:
"""Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel."""
def __init__(self, task_list, sweep_points=None, qubits=None, nr_seqs=None, cycles=None, init_rotation=None, **kw):
"""Init of the SingleQubitXEB class. The experiment con... | the_stack_v2_python_sparse | pycqed/measurement/benchmarking/randomized_benchmarking.py | QudevETH/PycQED_py3 | train | 8 |
8bf71c8b933406fbd71b0667c2a22f60091e7b49 | [
"if self.action in ['create']:\n permission_classes = [PortToPlaylistExists]\nelif self.action in ['destroy']:\n permission_classes = [UserIsAuthenticated & IsPortabilityRequestOwner]\nelif self.action in ['retrieve']:\n permission_classes = [UserIsAuthenticated & (IsPortabilityRequestOwner | IsPlaylistOwn... | <|body_start_0|>
if self.action in ['create']:
permission_classes = [PortToPlaylistExists]
elif self.action in ['destroy']:
permission_classes = [UserIsAuthenticated & IsPortabilityRequestOwner]
elif self.action in ['retrieve']:
permission_classes = [UserIsAut... | Viewset for the API of the portability request object. | PortabilityResourceViewSet | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PortabilityResourceViewSet:
"""Viewset for the API of the portability request object."""
def get_permissions(self):
"""Manage permissions for built-in DRF methods. Default to the ViewSet's default permissions. Only the `create` view is available from LTI."""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_012196 | 6,199 | permissive | [
{
"docstring": "Manage permissions for built-in DRF methods. Default to the ViewSet's default permissions. Only the `create` view is available from LTI.",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "Return the queryset according to the action.",
"na... | 5 | stack_v2_sparse_classes_30k_train_016051 | Implement the Python class `PortabilityResourceViewSet` described below.
Class description:
Viewset for the API of the portability request object.
Method signatures and docstrings:
- def get_permissions(self): Manage permissions for built-in DRF methods. Default to the ViewSet's default permissions. Only the `create`... | Implement the Python class `PortabilityResourceViewSet` described below.
Class description:
Viewset for the API of the portability request object.
Method signatures and docstrings:
- def get_permissions(self): Manage permissions for built-in DRF methods. Default to the ViewSet's default permissions. Only the `create`... | f767f1bdc12c9712f26ea17cb8b19f536389f0ed | <|skeleton|>
class PortabilityResourceViewSet:
"""Viewset for the API of the portability request object."""
def get_permissions(self):
"""Manage permissions for built-in DRF methods. Default to the ViewSet's default permissions. Only the `create` view is available from LTI."""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PortabilityResourceViewSet:
"""Viewset for the API of the portability request object."""
def get_permissions(self):
"""Manage permissions for built-in DRF methods. Default to the ViewSet's default permissions. Only the `create` view is available from LTI."""
if self.action in ['create']:
... | the_stack_v2_python_sparse | src/backend/marsha/core/api/portability_request.py | openfun/marsha | train | 92 |
80f5566eda0af69ba59e0b760e7ea436917dfb7b | [
"self.client_id = client_id\nself.enabled = enabled\nself.client_name = client_name\nself.account_id = account_id\nself.created = APIHelper.RFC3339DateTime(created) if created else None\nself.last_changed = APIHelper.RFC3339DateTime(last_changed) if last_changed else None\nself.additional_properties = additional_pr... | <|body_start_0|>
self.client_id = client_id
self.enabled = enabled
self.client_name = client_name
self.account_id = account_id
self.created = APIHelper.RFC3339DateTime(created) if created else None
self.last_changed = APIHelper.RFC3339DateTime(last_changed) if last_change... | Implementation of the 'OauthClientListItemResponse' model. TODO: type model description here. Attributes: client_id (string): TODO: type description here. enabled (bool): TODO: type description here. client_name (string): TODO: type description here. account_id (uuid|string): TODO: type description here. created (datet... | OauthClientListItemResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OauthClientListItemResponse:
"""Implementation of the 'OauthClientListItemResponse' model. TODO: type model description here. Attributes: client_id (string): TODO: type description here. enabled (bool): TODO: type description here. client_name (string): TODO: type description here. account_id (uu... | stack_v2_sparse_classes_36k_train_012197 | 3,433 | permissive | [
{
"docstring": "Constructor for the OauthClientListItemResponse class",
"name": "__init__",
"signature": "def __init__(self, client_id=None, enabled=None, client_name=None, account_id=None, created=None, last_changed=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this... | 2 | stack_v2_sparse_classes_30k_train_014063 | Implement the Python class `OauthClientListItemResponse` described below.
Class description:
Implementation of the 'OauthClientListItemResponse' model. TODO: type model description here. Attributes: client_id (string): TODO: type description here. enabled (bool): TODO: type description here. client_name (string): TODO... | Implement the Python class `OauthClientListItemResponse` described below.
Class description:
Implementation of the 'OauthClientListItemResponse' model. TODO: type model description here. Attributes: client_id (string): TODO: type description here. enabled (bool): TODO: type description here. client_name (string): TODO... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class OauthClientListItemResponse:
"""Implementation of the 'OauthClientListItemResponse' model. TODO: type model description here. Attributes: client_id (string): TODO: type description here. enabled (bool): TODO: type description here. client_name (string): TODO: type description here. account_id (uu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OauthClientListItemResponse:
"""Implementation of the 'OauthClientListItemResponse' model. TODO: type model description here. Attributes: client_id (string): TODO: type description here. enabled (bool): TODO: type description here. client_name (string): TODO: type description here. account_id (uuid|string): T... | the_stack_v2_python_sparse | idfy_rest_client/models/oauth_client_list_item_response.py | dealflowteam/Idfy | train | 0 |
8a2bad26db356a136f93881bd8ccbe7413d7b4f2 | [
"self._session = session_obj\nself._ctx_ks = KeyStore(self._session)\nself._ctx_key = KeyObject(self._ctx_ks)\nself.key_obj_mode = apis.kKeyObject_Mode_Persistent",
"if file_name[-4:] != '.pem' and file_name[-4:] != '.der':\n log.error('Unsupported file type. File type should be in pem or der format')\n ret... | <|body_start_0|>
self._session = session_obj
self._ctx_ks = KeyStore(self._session)
self._ctx_key = KeyObject(self._ctx_ks)
self.key_obj_mode = apis.kKeyObject_Mode_Persistent
<|end_body_0|>
<|body_start_1|>
if file_name[-4:] != '.pem' and file_name[-4:] != '.der':
l... | Generate key pair/public key of ecc/rsa | Generate | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Generate:
"""Generate key pair/public key of ecc/rsa"""
def __init__(self, session_obj):
"""Constructor :param session_obj: Instance of session"""
<|body_0|>
def gen_ecc_public(self, key_id, curve_type, file_name, policy, encode_format=''):
"""Generate ecc public... | stack_v2_sparse_classes_36k_train_012198 | 4,479 | permissive | [
{
"docstring": "Constructor :param session_obj: Instance of session",
"name": "__init__",
"signature": "def __init__(self, session_obj)"
},
{
"docstring": "Generate ecc public key :param key_id: Key index :param curve_type: ECC curve type :param file_name: File name to store public key :param po... | 6 | null | Implement the Python class `Generate` described below.
Class description:
Generate key pair/public key of ecc/rsa
Method signatures and docstrings:
- def __init__(self, session_obj): Constructor :param session_obj: Instance of session
- def gen_ecc_public(self, key_id, curve_type, file_name, policy, encode_format='')... | Implement the Python class `Generate` described below.
Class description:
Generate key pair/public key of ecc/rsa
Method signatures and docstrings:
- def __init__(self, session_obj): Constructor :param session_obj: Instance of session
- def gen_ecc_public(self, key_id, curve_type, file_name, policy, encode_format='')... | ab42459602787e9a557c3a00df40b20a52879fc7 | <|skeleton|>
class Generate:
"""Generate key pair/public key of ecc/rsa"""
def __init__(self, session_obj):
"""Constructor :param session_obj: Instance of session"""
<|body_0|>
def gen_ecc_public(self, key_id, curve_type, file_name, policy, encode_format=''):
"""Generate ecc public... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Generate:
"""Generate key pair/public key of ecc/rsa"""
def __init__(self, session_obj):
"""Constructor :param session_obj: Instance of session"""
self._session = session_obj
self._ctx_ks = KeyStore(self._session)
self._ctx_key = KeyObject(self._ctx_ks)
self.key_ob... | the_stack_v2_python_sparse | src/salt/base/state/secure_element/se05x_sss/sss/genkey.py | autopi-io/autopi-core | train | 141 |
0f9c22d0619771241895bda5077b516105d52d89 | [
"self.X = X\nself.M = np.shape(X)[0]\nself.N = np.shape(X)[1]",
"x = np.zeros([self.M, self.N], dtype=np.complex)\nfor m in range(self.M):\n for n in range(self.N):\n for i in range(self.M):\n for j in range(self.N):\n x[m, n] = x[m, n] + self.X[i, j] / np.sqrt(self.M * self.N)... | <|body_start_0|>
self.X = X
self.M = np.shape(X)[0]
self.N = np.shape(X)[1]
<|end_body_0|>
<|body_start_1|>
x = np.zeros([self.M, self.N], dtype=np.complex)
for m in range(self.M):
for n in range(self.N):
for i in range(self.M):
fo... | 2-D iDFT | iDFT_2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class iDFT_2D:
"""2-D iDFT"""
def __init__(self, X):
"""Input DFT X"""
<|body_0|>
def solve1(self):
"""\\\\\\ METHOD: Compute the iDFT of X with N^2 coefficients"""
<|body_1|>
def solve2(self):
"""\\\\\\ METHOD: Compute the iDFT of X with N^2/2 coe... | stack_v2_sparse_classes_36k_train_012199 | 4,947 | no_license | [
{
"docstring": "Input DFT X",
"name": "__init__",
"signature": "def __init__(self, X)"
},
{
"docstring": "\\\\\\\\\\\\ METHOD: Compute the iDFT of X with N^2 coefficients",
"name": "solve1",
"signature": "def solve1(self)"
},
{
"docstring": "\\\\\\\\\\\\ METHOD: Compute the iDFT ... | 3 | stack_v2_sparse_classes_30k_train_001250 | Implement the Python class `iDFT_2D` described below.
Class description:
2-D iDFT
Method signatures and docstrings:
- def __init__(self, X): Input DFT X
- def solve1(self): \\\\\\ METHOD: Compute the iDFT of X with N^2 coefficients
- def solve2(self): \\\\\\ METHOD: Compute the iDFT of X with N^2/2 coefficients | Implement the Python class `iDFT_2D` described below.
Class description:
2-D iDFT
Method signatures and docstrings:
- def __init__(self, X): Input DFT X
- def solve1(self): \\\\\\ METHOD: Compute the iDFT of X with N^2 coefficients
- def solve2(self): \\\\\\ METHOD: Compute the iDFT of X with N^2/2 coefficients
<|sk... | b72322cfc6d81c996117cea2160ee312da62d3ed | <|skeleton|>
class iDFT_2D:
"""2-D iDFT"""
def __init__(self, X):
"""Input DFT X"""
<|body_0|>
def solve1(self):
"""\\\\\\ METHOD: Compute the iDFT of X with N^2 coefficients"""
<|body_1|>
def solve2(self):
"""\\\\\\ METHOD: Compute the iDFT of X with N^2/2 coe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class iDFT_2D:
"""2-D iDFT"""
def __init__(self, X):
"""Input DFT X"""
self.X = X
self.M = np.shape(X)[0]
self.N = np.shape(X)[1]
def solve1(self):
"""\\\\\\ METHOD: Compute the iDFT of X with N^2 coefficients"""
x = np.zeros([self.M, self.N], dtype=np.compl... | the_stack_v2_python_sparse | 2D Signal Processing and Image De-noising/discrete_signal.py | FG-14/Signals-and-Information-Processing-DSP- | train | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.