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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
a2b1488c59bb862c21c0f5b7ac30a7f82aeddd48 | [
"self.random_state = random_state\nself.kernel_sizes = kernel_sizes\nself.filter_sizes = filter_sizes\nself.lstm_size = lstm_size\nself.dropout = dropout\nself.attention = attention\nsuper().__init__()",
"from tensorflow import keras\nfrom sktime.networks.lstmfcn_layers import make_attention_lstm\ninput_layer = k... | <|body_start_0|>
self.random_state = random_state
self.kernel_sizes = kernel_sizes
self.filter_sizes = filter_sizes
self.lstm_size = lstm_size
self.dropout = dropout
self.attention = attention
super().__init__()
<|end_body_0|>
<|body_start_1|>
from tensor... | Implementation of LSTMFCNClassifier from Karim et al (2019) [1]. Overview -------- Combines an LSTM arm with a CNN arm. Optionally uses an attention mechanism in the LSTM which the author indicates provides improved performance. Notes ----- Ported from sktime-dl source code https://github.com/sktime/sktime-dl/blob/mast... | LSTMFCNNetwork | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSTMFCNNetwork:
"""Implementation of LSTMFCNClassifier from Karim et al (2019) [1]. Overview -------- Combines an LSTM arm with a CNN arm. Optionally uses an attention mechanism in the LSTM which the author indicates provides improved performance. Notes ----- Ported from sktime-dl source code htt... | stack_v2_sparse_classes_36k_train_014300 | 3,786 | permissive | [
{
"docstring": "Initialize a new LSTMFCNNetwork object. Parameters ---------- kernel_sizes: List[int], default=[8, 5, 3] specifying the length of the 1D convolution windows filter_sizes: List[int], default=[128, 256, 128] size of filter for each conv layer random_state: int, default=0 seed to any needed random ... | 2 | null | Implement the Python class `LSTMFCNNetwork` described below.
Class description:
Implementation of LSTMFCNClassifier from Karim et al (2019) [1]. Overview -------- Combines an LSTM arm with a CNN arm. Optionally uses an attention mechanism in the LSTM which the author indicates provides improved performance. Notes ----... | Implement the Python class `LSTMFCNNetwork` described below.
Class description:
Implementation of LSTMFCNClassifier from Karim et al (2019) [1]. Overview -------- Combines an LSTM arm with a CNN arm. Optionally uses an attention mechanism in the LSTM which the author indicates provides improved performance. Notes ----... | 70b2bfaaa597eb31bc3a1032366dcc0e1f4c8a9f | <|skeleton|>
class LSTMFCNNetwork:
"""Implementation of LSTMFCNClassifier from Karim et al (2019) [1]. Overview -------- Combines an LSTM arm with a CNN arm. Optionally uses an attention mechanism in the LSTM which the author indicates provides improved performance. Notes ----- Ported from sktime-dl source code htt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LSTMFCNNetwork:
"""Implementation of LSTMFCNClassifier from Karim et al (2019) [1]. Overview -------- Combines an LSTM arm with a CNN arm. Optionally uses an attention mechanism in the LSTM which the author indicates provides improved performance. Notes ----- Ported from sktime-dl source code https://github.c... | the_stack_v2_python_sparse | sktime/networks/lstmfcn.py | sktime/sktime | train | 1,117 |
86956a53d61e51c32ffb3b3f2a2af5a664c7fe8a | [
"C = sum(nums)\nif C % 2 != 0:\n return False\nC = C // 2\ndp = [False] * (C + 1)\nfor c in range(C + 1):\n dp[c] = nums[0] == c\nfor i in range(1, len(nums)):\n for j in range(C, -1, -1):\n if j >= nums[i]:\n dp[j] = dp[j] or dp[j - nums[i]]\n else:\n continue\nreturn d... | <|body_start_0|>
C = sum(nums)
if C % 2 != 0:
return False
C = C // 2
dp = [False] * (C + 1)
for c in range(C + 1):
dp[c] = nums[0] == c
for i in range(1, len(nums)):
for j in range(C, -1, -1):
if j >= nums[i]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def canPartition2(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
C = sum(nums)
if C % 2 != 0:
... | stack_v2_sparse_classes_36k_train_014301 | 1,265 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartition",
"signature": "def canPartition(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartition2",
"signature": "def canPartition2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015711 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
- def canPartition2(self, nums): :type nums: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
- def canPartition2(self, nums): :type nums: List[int] :rtype: bool
<|skeleton|>
class Solution:
def canPar... | a32a1add8720de35e0ddc0c51efe781fb04c9d4a | <|skeleton|>
class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def canPartition2(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
C = sum(nums)
if C % 2 != 0:
return False
C = C // 2
dp = [False] * (C + 1)
for c in range(C + 1):
dp[c] = nums[0] == c
for i in range(1, len(nums)):... | the_stack_v2_python_sparse | 动态规划/leetcode_416_Partition_Equal_Subset_Sum.py | cleverer123/Algorithm | train | 0 | |
cfe392df5f9776933bad3774e37c1d2977d1b334 | [
"for line in stream:\n key, value = line.strip().split(' ', 1)\n key = key.strip('::')\n value = value.strip(';').strip('\"').strip()\n if not value:\n continue\n yield (key, value)",
"fields = {'Package': 0, 'Version': 1, 'File': 2}\nfield_names = fields.keys()\nfield_count = len(field_name... | <|body_start_0|>
for line in stream:
key, value = line.strip().split(' ', 1)
key = key.strip('::')
value = value.strip(';').strip('"').strip()
if not value:
continue
yield (key, value)
<|end_body_0|>
<|body_start_1|>
fields = {... | AptParser | [
"GPL-1.0-or-later",
"GPL-2.0-or-later",
"OFL-1.1",
"MS-PL",
"AFL-2.1",
"GPL-2.0-only",
"Python-2.0",
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AptParser:
def config_reader(stream):
"""apt-config dump command parser Function consumes io.TextIOBase compatible objects as input and return iterator with parsed items :type stream collections.Iterable :rtype collections.Iterable :return tuple(key, value) Usage: for key, value in __con... | stack_v2_sparse_classes_36k_train_014302 | 4,287 | permissive | [
{
"docstring": "apt-config dump command parser Function consumes io.TextIOBase compatible objects as input and return iterator with parsed items :type stream collections.Iterable :rtype collections.Iterable :return tuple(key, value) Usage: for key, value in __config_reader(text_stream): ... Parsing subject: PRO... | 3 | null | Implement the Python class `AptParser` described below.
Class description:
Implement the AptParser class.
Method signatures and docstrings:
- def config_reader(stream): apt-config dump command parser Function consumes io.TextIOBase compatible objects as input and return iterator with parsed items :type stream collect... | Implement the Python class `AptParser` described below.
Class description:
Implement the AptParser class.
Method signatures and docstrings:
- def config_reader(stream): apt-config dump command parser Function consumes io.TextIOBase compatible objects as input and return iterator with parsed items :type stream collect... | 23881f23577a65de396238998e8672d6c4c5a250 | <|skeleton|>
class AptParser:
def config_reader(stream):
"""apt-config dump command parser Function consumes io.TextIOBase compatible objects as input and return iterator with parsed items :type stream collections.Iterable :rtype collections.Iterable :return tuple(key, value) Usage: for key, value in __con... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AptParser:
def config_reader(stream):
"""apt-config dump command parser Function consumes io.TextIOBase compatible objects as input and return iterator with parsed items :type stream collections.Iterable :rtype collections.Iterable :return tuple(key, value) Usage: for key, value in __config_reader(tex... | the_stack_v2_python_sparse | ambari-common/src/main/python/ambari_commons/repo_manager/apt_parser.py | apache/ambari | train | 2,078 | |
cc2b11a5423c0a22227250d7864cb64f00955fb1 | [
"self.source_scene_name = bpy.context.scene.name\nself.target_asset_list = target_asset_list\nself.jsonoutput = None\n' Initialize logging variables '\nself.conout = False\nself.conoutmessage = None\nself.check = []\nself.error = []\nself.fail = []\nself.log = []\nself.success = []\nself.conoutmessage = '----------... | <|body_start_0|>
self.source_scene_name = bpy.context.scene.name
self.target_asset_list = target_asset_list
self.jsonoutput = None
' Initialize logging variables '
self.conout = False
self.conoutmessage = None
self.check = []
self.error = []
self.f... | Write presets selections for each item in corresponding asset folder | JSONExportPresets | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSONExportPresets:
"""Write presets selections for each item in corresponding asset folder"""
def __init__(self, target_asset_list):
"""Initialize general variables"""
<|body_0|>
def execute(self):
"""Process actions"""
<|body_1|>
def json_encoder(se... | stack_v2_sparse_classes_36k_train_014303 | 44,083 | no_license | [
{
"docstring": "Initialize general variables",
"name": "__init__",
"signature": "def __init__(self, target_asset_list)"
},
{
"docstring": "Process actions",
"name": "execute",
"signature": "def execute(self)"
},
{
"docstring": "Create JSON output from collection/sub-collection",
... | 5 | null | Implement the Python class `JSONExportPresets` described below.
Class description:
Write presets selections for each item in corresponding asset folder
Method signatures and docstrings:
- def __init__(self, target_asset_list): Initialize general variables
- def execute(self): Process actions
- def json_encoder(self):... | Implement the Python class `JSONExportPresets` described below.
Class description:
Write presets selections for each item in corresponding asset folder
Method signatures and docstrings:
- def __init__(self, target_asset_list): Initialize general variables
- def execute(self): Process actions
- def json_encoder(self):... | 0788f00283d7c8c083aa5d554eb1f32c201adbd6 | <|skeleton|>
class JSONExportPresets:
"""Write presets selections for each item in corresponding asset folder"""
def __init__(self, target_asset_list):
"""Initialize general variables"""
<|body_0|>
def execute(self):
"""Process actions"""
<|body_1|>
def json_encoder(se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JSONExportPresets:
"""Write presets selections for each item in corresponding asset folder"""
def __init__(self, target_asset_list):
"""Initialize general variables"""
self.source_scene_name = bpy.context.scene.name
self.target_asset_list = target_asset_list
self.jsonoutpu... | the_stack_v2_python_sparse | repos/blender_addons/internal/2.7.x/addon_customprops_preset.py | BlenderCN-Org/working_files | train | 0 |
362de0a7a2e1ac1a68f0152e50cdf6d41c3b7598 | [
"self.host = host\nself.username = username\nself.password = password\nself.to_emails = to_emails\nself.subject = subject\nself.content = content",
"msgRoot = MIMEMultipart('related')\nmsgRoot['Subject'] = self.subject\nmsgRoot['From'] = self.username\nmsgRoot['To'] = ','.join(self.to_emails)\nmsgRoot['Date'] = e... | <|body_start_0|>
self.host = host
self.username = username
self.password = password
self.to_emails = to_emails
self.subject = subject
self.content = content
<|end_body_0|>
<|body_start_1|>
msgRoot = MIMEMultipart('related')
msgRoot['Subject'] = self.subje... | MailSender | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MailSender:
def __init__(self, host, username, password, to_emails, subject, content):
"""初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param title 标题 @param content 内容"""
<|body_0|>
def send_mail(self):
"""发送邮件"""
... | stack_v2_sparse_classes_36k_train_014304 | 2,042 | permissive | [
{
"docstring": "初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param title 标题 @param content 内容",
"name": "__init__",
"signature": "def __init__(self, host, username, password, to_emails, subject, content)"
},
{
"docstring": "发送邮件",
"name": "send_m... | 2 | stack_v2_sparse_classes_30k_train_008465 | Implement the Python class `MailSender` described below.
Class description:
Implement the MailSender class.
Method signatures and docstrings:
- def __init__(self, host, username, password, to_emails, subject, content): 初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param ti... | Implement the Python class `MailSender` described below.
Class description:
Implement the MailSender class.
Method signatures and docstrings:
- def __init__(self, host, username, password, to_emails, subject, content): 初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param ti... | 931fca8fab9d7397c52cf9e76a76b1c60e190403 | <|skeleton|>
class MailSender:
def __init__(self, host, username, password, to_emails, subject, content):
"""初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param title 标题 @param content 内容"""
<|body_0|>
def send_mail(self):
"""发送邮件"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MailSender:
def __init__(self, host, username, password, to_emails, subject, content):
"""初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param title 标题 @param content 内容"""
self.host = host
self.username = username
self.password = pas... | the_stack_v2_python_sparse | src/utils/send_email.py | Karmenzind/fp-server | train | 180 | |
1f838f72e7a20b99f4652bdd49781111b3a00c9c | [
"output_file_name = 'linux_account_analysis.txt'\noutput_file_path = os.path.join(self.output_dir, output_file_name)\noutput_evidence = ReportText(source_path=output_file_path)\ntry:\n collected_artifacts = extract_artifacts(artifact_names=['LoginPolicyConfiguration'], disk_path=evidence.local_path, output_dir=s... | <|body_start_0|>
output_file_name = 'linux_account_analysis.txt'
output_file_path = os.path.join(self.output_dir, output_file_name)
output_evidence = ReportText(source_path=output_file_path)
try:
collected_artifacts = extract_artifacts(artifact_names=['LoginPolicyConfiguratio... | Task to analyze a Linux password file. | LinuxAccountAnalysisTask | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinuxAccountAnalysisTask:
"""Task to analyze a Linux password file."""
def run(self, evidence, result):
"""Run the Linux Account worker. Args: evidence (Evidence object): The evidence to process result (TurbiniaTaskResult): The object to place task results into. Returns: TurbiniaTask... | stack_v2_sparse_classes_36k_train_014305 | 5,092 | permissive | [
{
"docstring": "Run the Linux Account worker. Args: evidence (Evidence object): The evidence to process result (TurbiniaTaskResult): The object to place task results into. Returns: TurbiniaTaskResult object.",
"name": "run",
"signature": "def run(self, evidence, result)"
},
{
"docstring": "Extra... | 3 | stack_v2_sparse_classes_30k_train_013382 | Implement the Python class `LinuxAccountAnalysisTask` described below.
Class description:
Task to analyze a Linux password file.
Method signatures and docstrings:
- def run(self, evidence, result): Run the Linux Account worker. Args: evidence (Evidence object): The evidence to process result (TurbiniaTaskResult): The... | Implement the Python class `LinuxAccountAnalysisTask` described below.
Class description:
Task to analyze a Linux password file.
Method signatures and docstrings:
- def run(self, evidence, result): Run the Linux Account worker. Args: evidence (Evidence object): The evidence to process result (TurbiniaTaskResult): The... | a756f4c625cf3796fc82d160f3c794c7e2039437 | <|skeleton|>
class LinuxAccountAnalysisTask:
"""Task to analyze a Linux password file."""
def run(self, evidence, result):
"""Run the Linux Account worker. Args: evidence (Evidence object): The evidence to process result (TurbiniaTaskResult): The object to place task results into. Returns: TurbiniaTask... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinuxAccountAnalysisTask:
"""Task to analyze a Linux password file."""
def run(self, evidence, result):
"""Run the Linux Account worker. Args: evidence (Evidence object): The evidence to process result (TurbiniaTaskResult): The object to place task results into. Returns: TurbiniaTaskResult object... | the_stack_v2_python_sparse | turbinia/workers/analysis/linux_acct.py | joachimmetz/turbinia | train | 1 |
bf2f829c85d143ecb2efc1d2f3c5bf88e7f54b82 | [
"self.instr = Instructions(reg, mem, alu)\nself.mem = mem\nself.reg = reg\nself.op_codes = {}\nself.op_codes[1] = self.instr.halt\nself.op_codes[32] = self.instr.add\nself.op_codes[33] = self.instr.lda\nself.op_codes[34] = self.instr.sta\nself.op_codes[35] = self.instr.jmp\nself.op_codes[36] = self.instr.sza\nself.... | <|body_start_0|>
self.instr = Instructions(reg, mem, alu)
self.mem = mem
self.reg = reg
self.op_codes = {}
self.op_codes[1] = self.instr.halt
self.op_codes[32] = self.instr.add
self.op_codes[33] = self.instr.lda
self.op_codes[34] = self.instr.sta
s... | Decode op codes into instructions. | Decoder | [
"Artistic-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""Decode op codes into instructions."""
def __init__(self, reg, mem, alu):
"""Create the op code instruction map."""
<|body_0|>
def fetch_execute(self):
"""The fetch execute cycle. Fetch the next instruction and the value of the address following it. Th... | stack_v2_sparse_classes_36k_train_014306 | 5,867 | permissive | [
{
"docstring": "Create the op code instruction map.",
"name": "__init__",
"signature": "def __init__(self, reg, mem, alu)"
},
{
"docstring": "The fetch execute cycle. Fetch the next instruction and the value of the address following it. That value, typically an address itself, is passed to the i... | 2 | stack_v2_sparse_classes_30k_train_016553 | Implement the Python class `Decoder` described below.
Class description:
Decode op codes into instructions.
Method signatures and docstrings:
- def __init__(self, reg, mem, alu): Create the op code instruction map.
- def fetch_execute(self): The fetch execute cycle. Fetch the next instruction and the value of the add... | Implement the Python class `Decoder` described below.
Class description:
Decode op codes into instructions.
Method signatures and docstrings:
- def __init__(self, reg, mem, alu): Create the op code instruction map.
- def fetch_execute(self): The fetch execute cycle. Fetch the next instruction and the value of the add... | 75997d72ceefdc35fd3c76fe50676626cb2be887 | <|skeleton|>
class Decoder:
"""Decode op codes into instructions."""
def __init__(self, reg, mem, alu):
"""Create the op code instruction map."""
<|body_0|>
def fetch_execute(self):
"""The fetch execute cycle. Fetch the next instruction and the value of the address following it. Th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Decoder:
"""Decode op codes into instructions."""
def __init__(self, reg, mem, alu):
"""Create the op code instruction map."""
self.instr = Instructions(reg, mem, alu)
self.mem = mem
self.reg = reg
self.op_codes = {}
self.op_codes[1] = self.instr.halt
... | the_stack_v2_python_sparse | decoder.py | kmggh/python-simple-machine | train | 0 |
2d43ee9133a47b53caef7d151d3fb3622d3d8ba1 | [
"self.test_data_true = dictionary_class_helper_true()\nself.test_data_false = dictionary_class_helper_false()\nself.sock_conn_valid = socketconnection.SocketConnection(self.test_data_true.car_id)\nself.valid_dict = self.test_data_true.get_socket_dictionary()\nprint('Test suite: {}'.format(type(self).__name__))",
... | <|body_start_0|>
self.test_data_true = dictionary_class_helper_true()
self.test_data_false = dictionary_class_helper_false()
self.sock_conn_valid = socketconnection.SocketConnection(self.test_data_true.car_id)
self.valid_dict = self.test_data_true.get_socket_dictionary()
print('T... | This class tests edge cases resulting in an invalid action Basically send a random integer as the action that is not one of the accepted actions. | TestInvalidAction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestInvalidAction:
"""This class tests edge cases resulting in an invalid action Basically send a random integer as the action that is not one of the accepted actions."""
def setUp(self):
"""It is necessary to instantiate the data classes and extract the relevant dictionaries."""
... | stack_v2_sparse_classes_36k_train_014307 | 23,291 | no_license | [
{
"docstring": "It is necessary to instantiate the data classes and extract the relevant dictionaries.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Vary loops through this to vary the extensiveness of the test.",
"name": "test_invalid_action",
"signature": "def te... | 2 | null | Implement the Python class `TestInvalidAction` described below.
Class description:
This class tests edge cases resulting in an invalid action Basically send a random integer as the action that is not one of the accepted actions.
Method signatures and docstrings:
- def setUp(self): It is necessary to instantiate the d... | Implement the Python class `TestInvalidAction` described below.
Class description:
This class tests edge cases resulting in an invalid action Basically send a random integer as the action that is not one of the accepted actions.
Method signatures and docstrings:
- def setUp(self): It is necessary to instantiate the d... | 8f68cc2a6ca568e803a6bfea49a452a5b0c1a2cf | <|skeleton|>
class TestInvalidAction:
"""This class tests edge cases resulting in an invalid action Basically send a random integer as the action that is not one of the accepted actions."""
def setUp(self):
"""It is necessary to instantiate the data classes and extract the relevant dictionaries."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestInvalidAction:
"""This class tests edge cases resulting in an invalid action Basically send a random integer as the action that is not one of the accepted actions."""
def setUp(self):
"""It is necessary to instantiate the data classes and extract the relevant dictionaries."""
self.tes... | the_stack_v2_python_sparse | AgentPi/agenttesting.py | JiewenGuan/Iot-Carshare | train | 0 |
d4e2a0df87f091a6f573c49f5817d6cb699a8958 | [
"list = []\nif root is None:\n return []\nlist += self.inorderTraversal(root.left)\nlist.append(root.val)\nlist += self.inorderTraversal(root.right)\nreturn list",
"WHITE, GRAY = (0, 1)\nres = []\nstack = [(WHITE, root)]\nwhile stack:\n color, node = stack.pop()\n if node is None:\n continue\n ... | <|body_start_0|>
list = []
if root is None:
return []
list += self.inorderTraversal(root.left)
list.append(root.val)
list += self.inorderTraversal(root.right)
return list
<|end_body_0|>
<|body_start_1|>
WHITE, GRAY = (0, 1)
res = []
st... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def inorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def inorderTraversal_iter(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
list = []
if... | stack_v2_sparse_classes_36k_train_014308 | 1,450 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "inorderTraversal",
"signature": "def inorderTraversal(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "inorderTraversal_iter",
"signature": "def inorderTraversal_iter(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015176 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def inorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def inorderTraversal_iter(self, root): :type root: TreeNode :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def inorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def inorderTraversal_iter(self, root): :type root: TreeNode :rtype: List[int]
<|skeleton|>
class Solut... | 3f4284330f9771037ca59e2e6a94122e51e58540 | <|skeleton|>
class Solution:
def inorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def inorderTraversal_iter(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def inorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
list = []
if root is None:
return []
list += self.inorderTraversal(root.left)
list.append(root.val)
list += self.inorderTraversal(root.right)
return list... | the_stack_v2_python_sparse | Leetcode/94.二叉树的中序遍历.py | myf-algorithm/Leetcode | train | 1 | |
824a34fa39aca4984a49de66eaf92db46fc37cf3 | [
"url = reverse('reports')\nresponse = self.client.get(url)\nself.assertEqual(response.status_code, 302)",
"url = reverse('reports')\nfor user in ['admin', 'poweruser', 'normaluser']:\n self.client.login(username=user, password='pass')\n response = self.client.get(url)\n self.assertEqual(response.status_c... | <|body_start_0|>
url = reverse('reports')
response = self.client.get(url)
self.assertEqual(response.status_code, 302)
<|end_body_0|>
<|body_start_1|>
url = reverse('reports')
for user in ['admin', 'poweruser', 'normaluser']:
self.client.login(username=user, password=... | PublishViewTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublishViewTest:
def test_reportview_anon_unauth_redirect(self):
"""Test that the ReportView redirects anonymous users"""
<|body_0|>
def test_reportview_auth(self):
"""Test that authenticated users can open the ReportView"""
<|body_1|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_36k_train_014309 | 751 | permissive | [
{
"docstring": "Test that the ReportView redirects anonymous users",
"name": "test_reportview_anon_unauth_redirect",
"signature": "def test_reportview_anon_unauth_redirect(self)"
},
{
"docstring": "Test that authenticated users can open the ReportView",
"name": "test_reportview_auth",
"s... | 2 | stack_v2_sparse_classes_30k_train_001457 | Implement the Python class `PublishViewTest` described below.
Class description:
Implement the PublishViewTest class.
Method signatures and docstrings:
- def test_reportview_anon_unauth_redirect(self): Test that the ReportView redirects anonymous users
- def test_reportview_auth(self): Test that authenticated users c... | Implement the Python class `PublishViewTest` described below.
Class description:
Implement the PublishViewTest class.
Method signatures and docstrings:
- def test_reportview_anon_unauth_redirect(self): Test that the ReportView redirects anonymous users
- def test_reportview_auth(self): Test that authenticated users c... | 5db00d52574a62498036f526813878d11d873b54 | <|skeleton|>
class PublishViewTest:
def test_reportview_anon_unauth_redirect(self):
"""Test that the ReportView redirects anonymous users"""
<|body_0|>
def test_reportview_auth(self):
"""Test that authenticated users can open the ReportView"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PublishViewTest:
def test_reportview_anon_unauth_redirect(self):
"""Test that the ReportView redirects anonymous users"""
url = reverse('reports')
response = self.client.get(url)
self.assertEqual(response.status_code, 302)
def test_reportview_auth(self):
"""Test th... | the_stack_v2_python_sparse | prs2/reports/test_views.py | ScottEvansDBCA/prs | train | 0 | |
81c33081d7d7543742f48b8b034c3e4e9d75b05c | [
"self.dendogram = hierarchy.linkage(self.data.T, method)\nself.method = method\nreturn self.dendogram",
"if not 'labels' in kwargs:\n kwargs['labels'] = self.data.T.index\nif not 'leaf_rotation' in kwargs:\n kwargs['leaf_rotation'] = 0\nif not 'orientation' in kwargs:\n kwargs['orientation'] = 'right'\ni... | <|body_start_0|>
self.dendogram = hierarchy.linkage(self.data.T, method)
self.method = method
return self.dendogram
<|end_body_0|>
<|body_start_1|>
if not 'labels' in kwargs:
kwargs['labels'] = self.data.T.index
if not 'leaf_rotation' in kwargs:
kwargs['l... | Hierarchical clustering is a method of cluster analysis which seeks to build a hierarchy of clusters. | Linkage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Linkage:
"""Hierarchical clustering is a method of cluster analysis which seeks to build a hierarchy of clusters."""
def run(self, method: str='complete', metric: Union[str, Callable[[object], float]]='euclidean', optimal_ordering: bool=False) -> object:
"""Runs the hierarchical clus... | stack_v2_sparse_classes_36k_train_014310 | 3,306 | no_license | [
{
"docstring": "Runs the hierarchical clustering for the input vectors Args: method (str, optional, default=complete): Methods for calculating the distance between the newly formed cluster u and each v. <br/> See https://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.hierarchy.linkage.html . <br/> M... | 2 | null | Implement the Python class `Linkage` described below.
Class description:
Hierarchical clustering is a method of cluster analysis which seeks to build a hierarchy of clusters.
Method signatures and docstrings:
- def run(self, method: str='complete', metric: Union[str, Callable[[object], float]]='euclidean', optimal_or... | Implement the Python class `Linkage` described below.
Class description:
Hierarchical clustering is a method of cluster analysis which seeks to build a hierarchy of clusters.
Method signatures and docstrings:
- def run(self, method: str='complete', metric: Union[str, Callable[[object], float]]='euclidean', optimal_or... | adddd0b5cb67a50301ef5ae323c61bde57210cb8 | <|skeleton|>
class Linkage:
"""Hierarchical clustering is a method of cluster analysis which seeks to build a hierarchy of clusters."""
def run(self, method: str='complete', metric: Union[str, Callable[[object], float]]='euclidean', optimal_ordering: bool=False) -> object:
"""Runs the hierarchical clus... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Linkage:
"""Hierarchical clustering is a method of cluster analysis which seeks to build a hierarchy of clusters."""
def run(self, method: str='complete', metric: Union[str, Callable[[object], float]]='euclidean', optimal_ordering: bool=False) -> object:
"""Runs the hierarchical clustering for th... | the_stack_v2_python_sparse | venv/lib/python3.9/site-packages/compling/unsupervisedLearning/clustering/linkage.py | TheKing-coder68/Verselet | train | 1 |
6ab84c58144f1aeee01eed6b54daae899ebaef69 | [
"user, data = self.account.selectAccount()\njsonResponse = self.load(self.API_URL, get={'action': 'connectUser', 'login': user, 'password': data['password']})\nres = json_loads(jsonResponse)\nif res['response_code'] == 'ok':\n self.token = res['token']\n return True\nelse:\n return False",
"if not self.a... | <|body_start_0|>
user, data = self.account.selectAccount()
jsonResponse = self.load(self.API_URL, get={'action': 'connectUser', 'login': user, 'password': data['password']})
res = json_loads(jsonResponse)
if res['response_code'] == 'ok':
self.token = res['token']
... | MegaDebridEu | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MegaDebridEu:
def api_load(self):
"""Connexion to the mega-debrid API Return True if succeed"""
<|body_0|>
def handlePremium(self, pyfile):
"""Debrid a link Return The debrided link if succeed or original link if fail"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_014311 | 1,758 | no_license | [
{
"docstring": "Connexion to the mega-debrid API Return True if succeed",
"name": "api_load",
"signature": "def api_load(self)"
},
{
"docstring": "Debrid a link Return The debrided link if succeed or original link if fail",
"name": "handlePremium",
"signature": "def handlePremium(self, p... | 2 | stack_v2_sparse_classes_30k_train_000082 | Implement the Python class `MegaDebridEu` described below.
Class description:
Implement the MegaDebridEu class.
Method signatures and docstrings:
- def api_load(self): Connexion to the mega-debrid API Return True if succeed
- def handlePremium(self, pyfile): Debrid a link Return The debrided link if succeed or origin... | Implement the Python class `MegaDebridEu` described below.
Class description:
Implement the MegaDebridEu class.
Method signatures and docstrings:
- def api_load(self): Connexion to the mega-debrid API Return True if succeed
- def handlePremium(self, pyfile): Debrid a link Return The debrided link if succeed or origin... | ef6d859b92dbcace76abef04ef251ee0bf09cf8b | <|skeleton|>
class MegaDebridEu:
def api_load(self):
"""Connexion to the mega-debrid API Return True if succeed"""
<|body_0|>
def handlePremium(self, pyfile):
"""Debrid a link Return The debrided link if succeed or original link if fail"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MegaDebridEu:
def api_load(self):
"""Connexion to the mega-debrid API Return True if succeed"""
user, data = self.account.selectAccount()
jsonResponse = self.load(self.API_URL, get={'action': 'connectUser', 'login': user, 'password': data['password']})
res = json_loads(jsonResp... | the_stack_v2_python_sparse | data/root-.pyload-config/userplugins/hoster/MegaDebridEu.py | kurtiss/htpc | train | 0 | |
d9a498e7ec694766c61d66025b59413bb71e96df | [
"super().__init__(data=data, sampling_rate=sampling_rate, time_intervals=time_intervals, include_start=include_start)\nself.eeg_result: Dict[str, pd.DataFrame] = {}\n'Dictionary with EEG processing result dataframes, split into different phases.\\n\\n '",
"from mne.time_frequency import psd_array_welch\nee... | <|body_start_0|>
super().__init__(data=data, sampling_rate=sampling_rate, time_intervals=time_intervals, include_start=include_start)
self.eeg_result: Dict[str, pd.DataFrame] = {}
'Dictionary with EEG processing result dataframes, split into different phases.\n\n '
<|end_body_0|>
<|body_... | Class for processing EEG data. | EegProcessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EegProcessor:
"""Class for processing EEG data."""
def __init__(self, data: Union[pd.DataFrame, Dict[str, pd.DataFrame]], sampling_rate: Optional[float]=None, time_intervals: Optional[Union[pd.Series, Dict[str, Sequence[str]]]]=None, include_start: Optional[bool]=False):
"""Initializ... | stack_v2_sparse_classes_36k_train_014312 | 5,188 | permissive | [
{
"docstring": "Initialize an ``EegProcessor`` instance. You can either pass a data dictionary 'data_dict' containing EEG data or dataframe containing EEG data. For the latter, you can additionally supply time information via ``time_intervals`` parameter to automatically split the data into single phases. Param... | 2 | stack_v2_sparse_classes_30k_train_004587 | Implement the Python class `EegProcessor` described below.
Class description:
Class for processing EEG data.
Method signatures and docstrings:
- def __init__(self, data: Union[pd.DataFrame, Dict[str, pd.DataFrame]], sampling_rate: Optional[float]=None, time_intervals: Optional[Union[pd.Series, Dict[str, Sequence[str]... | Implement the Python class `EegProcessor` described below.
Class description:
Class for processing EEG data.
Method signatures and docstrings:
- def __init__(self, data: Union[pd.DataFrame, Dict[str, pd.DataFrame]], sampling_rate: Optional[float]=None, time_intervals: Optional[Union[pd.Series, Dict[str, Sequence[str]... | 5b2eab0b0e4b52c1b3997f760ad0d1ae33d1a81d | <|skeleton|>
class EegProcessor:
"""Class for processing EEG data."""
def __init__(self, data: Union[pd.DataFrame, Dict[str, pd.DataFrame]], sampling_rate: Optional[float]=None, time_intervals: Optional[Union[pd.Series, Dict[str, Sequence[str]]]]=None, include_start: Optional[bool]=False):
"""Initializ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EegProcessor:
"""Class for processing EEG data."""
def __init__(self, data: Union[pd.DataFrame, Dict[str, pd.DataFrame]], sampling_rate: Optional[float]=None, time_intervals: Optional[Union[pd.Series, Dict[str, Sequence[str]]]]=None, include_start: Optional[bool]=False):
"""Initialize an ``EegPro... | the_stack_v2_python_sparse | src/biopsykit/signals/eeg/eeg.py | mad-lab-fau/BioPsyKit | train | 35 |
9259970583166bb4060bf9853c86cbaa340eb743 | [
"kwargs = super().get_form_kwargs()\nkwargs.update({'cart': Cart(self.request)})\nreturn kwargs",
"cart_items = {}\nfor offer_form in form.forms:\n offer_form.is_valid()\n cart_items[str(offer_form.offer.pk)] = {'quantity': offer_form.cleaned_data['quantity']}\nself.request.session[CART_KEY] = cart_items\ns... | <|body_start_0|>
kwargs = super().get_form_kwargs()
kwargs.update({'cart': Cart(self.request)})
return kwargs
<|end_body_0|>
<|body_start_1|>
cart_items = {}
for offer_form in form.forms:
offer_form.is_valid()
cart_items[str(offer_form.offer.pk)] = {'quan... | Страница корзины. | CartView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CartView:
"""Страница корзины."""
def get_form_kwargs(self):
"""Передаём корзину пользователя в форму."""
<|body_0|>
def form_valid(self, form):
"""Для уверенности мы пересохраняем данные из формы в сессию пользователя."""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_014313 | 7,131 | no_license | [
{
"docstring": "Передаём корзину пользователя в форму.",
"name": "get_form_kwargs",
"signature": "def get_form_kwargs(self)"
},
{
"docstring": "Для уверенности мы пересохраняем данные из формы в сессию пользователя.",
"name": "form_valid",
"signature": "def form_valid(self, form)"
}
] | 2 | null | Implement the Python class `CartView` described below.
Class description:
Страница корзины.
Method signatures and docstrings:
- def get_form_kwargs(self): Передаём корзину пользователя в форму.
- def form_valid(self, form): Для уверенности мы пересохраняем данные из формы в сессию пользователя. | Implement the Python class `CartView` described below.
Class description:
Страница корзины.
Method signatures and docstrings:
- def get_form_kwargs(self): Передаём корзину пользователя в форму.
- def form_valid(self, form): Для уверенности мы пересохраняем данные из формы в сессию пользователя.
<|skeleton|>
class Ca... | 97c29690929693b172ab88a52c3b426b17461011 | <|skeleton|>
class CartView:
"""Страница корзины."""
def get_form_kwargs(self):
"""Передаём корзину пользователя в форму."""
<|body_0|>
def form_valid(self, form):
"""Для уверенности мы пересохраняем данные из формы в сессию пользователя."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CartView:
"""Страница корзины."""
def get_form_kwargs(self):
"""Передаём корзину пользователя в форму."""
kwargs = super().get_form_kwargs()
kwargs.update({'cart': Cart(self.request)})
return kwargs
def form_valid(self, form):
"""Для уверенности мы пересохраня... | the_stack_v2_python_sparse | stationery/apps/cart/views.py | minidron/stationery | train | 0 |
49f2864cb44f4ef69e6fcd9d945904d5e219b72e | [
"super(StreamPowerThresholdModel, self).__init__(input_file=input_file, params=params)\nself.flow_router = FlowRouter(self.grid, **self.params)\nself.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)\nself.eroder = StreamPowerSmoothThresholdEroder(self.grid, K_sp=self.params['K_sp'], threshold_sp=se... | <|body_start_0|>
super(StreamPowerThresholdModel, self).__init__(input_file=input_file, params=params)
self.flow_router = FlowRouter(self.grid, **self.params)
self.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)
self.eroder = StreamPowerSmoothThresholdEroder(self.grid, ... | A StreamPowerThresholdModel computes erosion using a form of the unit stream power model that represents a threshold using an exponential term. | StreamPowerThresholdModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StreamPowerThresholdModel:
"""A StreamPowerThresholdModel computes erosion using a form of the unit stream power model that represents a threshold using an exponential term."""
def __init__(self, input_file=None, params=None):
"""Initialize the StreamPowerThresholdModel."""
<... | stack_v2_sparse_classes_36k_train_014314 | 2,839 | no_license | [
{
"docstring": "Initialize the StreamPowerThresholdModel.",
"name": "__init__",
"signature": "def __init__(self, input_file=None, params=None)"
},
{
"docstring": "Advance model for one time-step of duration dt.",
"name": "run_one_step",
"signature": "def run_one_step(self, dt)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011814 | Implement the Python class `StreamPowerThresholdModel` described below.
Class description:
A StreamPowerThresholdModel computes erosion using a form of the unit stream power model that represents a threshold using an exponential term.
Method signatures and docstrings:
- def __init__(self, input_file=None, params=None... | Implement the Python class `StreamPowerThresholdModel` described below.
Class description:
A StreamPowerThresholdModel computes erosion using a form of the unit stream power model that represents a threshold using an exponential term.
Method signatures and docstrings:
- def __init__(self, input_file=None, params=None... | 3506ec741a7c8a170ea654d40c6119fefe1b93ba | <|skeleton|>
class StreamPowerThresholdModel:
"""A StreamPowerThresholdModel computes erosion using a form of the unit stream power model that represents a threshold using an exponential term."""
def __init__(self, input_file=None, params=None):
"""Initialize the StreamPowerThresholdModel."""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StreamPowerThresholdModel:
"""A StreamPowerThresholdModel computes erosion using a form of the unit stream power model that represents a threshold using an exponential term."""
def __init__(self, input_file=None, params=None):
"""Initialize the StreamPowerThresholdModel."""
super(StreamPo... | the_stack_v2_python_sparse | erosion_modeling_suite/erosion_model/single_component/stream_power_threshold/stream_power_threshold_model.py | kbarnhart/inverting_topography_postglacial | train | 4 |
77932f13b4ac3231f02c16a782b358af9bea9d3b | [
"str_num = str(num)\nlength = len(str_num)\ndp = [0] * (length + 1)\ndp[-1] = 1\nfor i in range(length - 1, -1, -1):\n if 10 <= int(str_num[i:i + 2]) < 26:\n dp[i] += dp[i + 2]\n dp[i] += dp[i + 1]\nreturn dp[0]",
"dp1 = dp2 = dp3 = 1\nwhile num > 0:\n if 10 <= num % 100 < 26:\n dp3 += dp1\... | <|body_start_0|>
str_num = str(num)
length = len(str_num)
dp = [0] * (length + 1)
dp[-1] = 1
for i in range(length - 1, -1, -1):
if 10 <= int(str_num[i:i + 2]) < 26:
dp[i] += dp[i + 2]
dp[i] += dp[i + 1]
return dp[0]
<|end_body_0|>
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def translateNum(self, num):
""":type num: int :rtype: int"""
<|body_0|>
def translateNum2(self, num):
""":type num: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
str_num = str(num)
length = len(str_num)
d... | stack_v2_sparse_classes_36k_train_014315 | 700 | permissive | [
{
"docstring": ":type num: int :rtype: int",
"name": "translateNum",
"signature": "def translateNum(self, num)"
},
{
"docstring": ":type num: int :rtype: int",
"name": "translateNum2",
"signature": "def translateNum2(self, num)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def translateNum(self, num): :type num: int :rtype: int
- def translateNum2(self, num): :type num: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def translateNum(self, num): :type num: int :rtype: int
- def translateNum2(self, num): :type num: int :rtype: int
<|skeleton|>
class Solution:
def translateNum(self, num):... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|skeleton|>
class Solution:
def translateNum(self, num):
""":type num: int :rtype: int"""
<|body_0|>
def translateNum2(self, num):
""":type num: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def translateNum(self, num):
""":type num: int :rtype: int"""
str_num = str(num)
length = len(str_num)
dp = [0] * (length + 1)
dp[-1] = 1
for i in range(length - 1, -1, -1):
if 10 <= int(str_num[i:i + 2]) < 26:
dp[i] += dp[i... | the_stack_v2_python_sparse | LCOF/41-50/46/46.py | xuychen/Leetcode | train | 0 | |
eba6c7127755c10078ef984a16ea5129996caaee | [
"assert style in ColorSchemeColorHighlighter._region_style_flags\nself._view = view\nself._color_scheme_builder = color_scheme_builder\nself._text_coloring = style == 'text'\nself._flags = ColorSchemeColorHighlighter._region_style_flags[style]\nself._name = name\nself._debug = debug",
"if 'values' not in context:... | <|body_start_0|>
assert style in ColorSchemeColorHighlighter._region_style_flags
self._view = view
self._color_scheme_builder = color_scheme_builder
self._text_coloring = style == 'text'
self._flags = ColorSchemeColorHighlighter._region_style_flags[style]
self._name = nam... | A color highlighter that uses color scheme scopes to highlight colors. | ColorSchemeColorHighlighter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ColorSchemeColorHighlighter:
"""A color highlighter that uses color scheme scopes to highlight colors."""
def __init__(self, view, style, color_scheme_builder, name, debug):
"""Init a ColorSchemeColorHighlighter. Arguments: - view - a view to highlight colors in. - style - the style ... | stack_v2_sparse_classes_36k_train_014316 | 7,723 | no_license | [
{
"docstring": "Init a ColorSchemeColorHighlighter. Arguments: - view - a view to highlight colors in. - style - the style of color highlighting. - color_scheme_builder - the color scheme builder to build regions for colors. - name - the name of the color highlighter. - debug - whether to enable debug mode.",
... | 4 | stack_v2_sparse_classes_30k_train_010011 | Implement the Python class `ColorSchemeColorHighlighter` described below.
Class description:
A color highlighter that uses color scheme scopes to highlight colors.
Method signatures and docstrings:
- def __init__(self, view, style, color_scheme_builder, name, debug): Init a ColorSchemeColorHighlighter. Arguments: - v... | Implement the Python class `ColorSchemeColorHighlighter` described below.
Class description:
A color highlighter that uses color scheme scopes to highlight colors.
Method signatures and docstrings:
- def __init__(self, view, style, color_scheme_builder, name, debug): Init a ColorSchemeColorHighlighter. Arguments: - v... | 83d469af3fc11d1aedb5193976ef84c59b595d6c | <|skeleton|>
class ColorSchemeColorHighlighter:
"""A color highlighter that uses color scheme scopes to highlight colors."""
def __init__(self, view, style, color_scheme_builder, name, debug):
"""Init a ColorSchemeColorHighlighter. Arguments: - view - a view to highlight colors in. - style - the style ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ColorSchemeColorHighlighter:
"""A color highlighter that uses color scheme scopes to highlight colors."""
def __init__(self, view, style, color_scheme_builder, name, debug):
"""Init a ColorSchemeColorHighlighter. Arguments: - view - a view to highlight colors in. - style - the style of color high... | the_stack_v2_python_sparse | .config/sublime-text-2/Packages/Color Highlighter/color_scheme_color_highlighter.py | Wallkerock/X-setup | train | 10 |
4fb5a451ebf722022fd3f55c58b7a8f9f4de0cd4 | [
"points = [[1, 3], [-2, 2]]\nK = 1\nexpected_out = [[-2, 2]]\nself.assertEqual(k_closest_brute_force(points, K), expected_out)\nself.assertEqual(k_closest_divide_conquer(points, K), expected_out)",
"points = [[3, 3], [5, -1], [-2, 4]]\nK = 2\nexpected_out = [[3, 3], [-2, 4]]\nself.assertEqual(k_closest_brute_forc... | <|body_start_0|>
points = [[1, 3], [-2, 2]]
K = 1
expected_out = [[-2, 2]]
self.assertEqual(k_closest_brute_force(points, K), expected_out)
self.assertEqual(k_closest_divide_conquer(points, K), expected_out)
<|end_body_0|>
<|body_start_1|>
points = [[3, 3], [5, -1], [-2,... | Unit test for k_closest problem. | TestKClosest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestKClosest:
"""Unit test for k_closest problem."""
def test_1(self):
"""The distance between (1, 3) and the origin is sqrt(10). The distance between (-2, 2) and the origin is sqrt(8). Since sqrt(8) < sqrt(10), (-2, 2) is closer to the origin. We only want the closest K = 1 points f... | stack_v2_sparse_classes_36k_train_014317 | 2,643 | no_license | [
{
"docstring": "The distance between (1, 3) and the origin is sqrt(10). The distance between (-2, 2) and the origin is sqrt(8). Since sqrt(8) < sqrt(10), (-2, 2) is closer to the origin. We only want the closest K = 1 points from the origin, so the answer is just [[-2,2]].",
"name": "test_1",
"signature... | 2 | null | Implement the Python class `TestKClosest` described below.
Class description:
Unit test for k_closest problem.
Method signatures and docstrings:
- def test_1(self): The distance between (1, 3) and the origin is sqrt(10). The distance between (-2, 2) and the origin is sqrt(8). Since sqrt(8) < sqrt(10), (-2, 2) is clos... | Implement the Python class `TestKClosest` described below.
Class description:
Unit test for k_closest problem.
Method signatures and docstrings:
- def test_1(self): The distance between (1, 3) and the origin is sqrt(10). The distance between (-2, 2) and the origin is sqrt(8). Since sqrt(8) < sqrt(10), (-2, 2) is clos... | 8105e1b20bf450a03a9bb910f344fc140e5ba703 | <|skeleton|>
class TestKClosest:
"""Unit test for k_closest problem."""
def test_1(self):
"""The distance between (1, 3) and the origin is sqrt(10). The distance between (-2, 2) and the origin is sqrt(8). Since sqrt(8) < sqrt(10), (-2, 2) is closer to the origin. We only want the closest K = 1 points f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestKClosest:
"""Unit test for k_closest problem."""
def test_1(self):
"""The distance between (1, 3) and the origin is sqrt(10). The distance between (-2, 2) and the origin is sqrt(8). Since sqrt(8) < sqrt(10), (-2, 2) is closer to the origin. We only want the closest K = 1 points from the origi... | the_stack_v2_python_sparse | module_4/python/k_closest.py | vprusso/6-Weeks-to-Interview-Ready | train | 6 |
0fec10dbe543db399a8f78a81dcec6ce15dc74af | [
"allowed_fields = super().filter_allowed_fields\nallowed_fields.remove('assignment_id')\nreturn allowed_fields",
"assignment_id = self.request.matchdict.get('assignment_id')\nif assignment_id:\n query.filter(self.model.assignment_id == assignment_id)\nreturn query"
] | <|body_start_0|>
allowed_fields = super().filter_allowed_fields
allowed_fields.remove('assignment_id')
return allowed_fields
<|end_body_0|>
<|body_start_1|>
assignment_id = self.request.matchdict.get('assignment_id')
if assignment_id:
query.filter(self.model.assignme... | Assets service. | AssetService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssetService:
"""Assets service."""
def filter_allowed_fields(self):
"""List of fields allowed in filtering and sorting."""
<|body_0|>
def default_filters(self, query) -> object:
"""Default filters for this Service."""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_014318 | 2,803 | no_license | [
{
"docstring": "List of fields allowed in filtering and sorting.",
"name": "filter_allowed_fields",
"signature": "def filter_allowed_fields(self)"
},
{
"docstring": "Default filters for this Service.",
"name": "default_filters",
"signature": "def default_filters(self, query) -> object"
... | 2 | stack_v2_sparse_classes_30k_train_002669 | Implement the Python class `AssetService` described below.
Class description:
Assets service.
Method signatures and docstrings:
- def filter_allowed_fields(self): List of fields allowed in filtering and sorting.
- def default_filters(self, query) -> object: Default filters for this Service. | Implement the Python class `AssetService` described below.
Class description:
Assets service.
Method signatures and docstrings:
- def filter_allowed_fields(self): List of fields allowed in filtering and sorting.
- def default_filters(self, query) -> object: Default filters for this Service.
<|skeleton|>
class AssetS... | e85c0ba0992bccb80878e89ec791ee64754646b0 | <|skeleton|>
class AssetService:
"""Assets service."""
def filter_allowed_fields(self):
"""List of fields allowed in filtering and sorting."""
<|body_0|>
def default_filters(self, query) -> object:
"""Default filters for this Service."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AssetService:
"""Assets service."""
def filter_allowed_fields(self):
"""List of fields allowed in filtering and sorting."""
allowed_fields = super().filter_allowed_fields
allowed_fields.remove('assignment_id')
return allowed_fields
def default_filters(self, query) -> ... | the_stack_v2_python_sparse | src/briefy/leica/views/assets.py | BriefyHQ/briefy.leica | train | 0 |
9df7acce6cbe4b69599fafd287f95991fb96842b | [
"self.df_path = df_path\nself.sc = sc\nself.sql = sql\nself.df = sql.read.format('com.databricks.spark.csv').option('header', 'true').load(self.df_path)\nself.rulelist_filename = None\nself.rulelist = None\nself.id_field = id_field\nself.snippet_field = snippet_field",
"print(rulelist_filename)\nself.rulelist_fil... | <|body_start_0|>
self.df_path = df_path
self.sc = sc
self.sql = sql
self.df = sql.read.format('com.databricks.spark.csv').option('header', 'true').load(self.df_path)
self.rulelist_filename = None
self.rulelist = None
self.id_field = id_field
self.snippet_f... | The parent class for creating and viewing labeled categories on a dataframe of snippets and other metadata | Categorizer | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Categorizer:
"""The parent class for creating and viewing labeled categories on a dataframe of snippets and other metadata"""
def __init__(self, df_path, sc=sc, sql=sql, id_field='Url', snippet_field='Cleaned Snippet'):
""":param df_path: Pandas df containing cleaned snippets and ids... | stack_v2_sparse_classes_36k_train_014319 | 4,874 | permissive | [
{
"docstring": ":param df_path: Pandas df containing cleaned snippets and ids (as a maximum) :param sc: spark context :param sql: spark.sql context :param id_field: the id field in source df :param snippet_field: the field containing the text data to search in",
"name": "__init__",
"signature": "def __i... | 4 | stack_v2_sparse_classes_30k_train_008242 | Implement the Python class `Categorizer` described below.
Class description:
The parent class for creating and viewing labeled categories on a dataframe of snippets and other metadata
Method signatures and docstrings:
- def __init__(self, df_path, sc=sc, sql=sql, id_field='Url', snippet_field='Cleaned Snippet'): :par... | Implement the Python class `Categorizer` described below.
Class description:
The parent class for creating and viewing labeled categories on a dataframe of snippets and other metadata
Method signatures and docstrings:
- def __init__(self, df_path, sc=sc, sql=sql, id_field='Url', snippet_field='Cleaned Snippet'): :par... | b810c6e1a93a2ecaa9d6351449239d0a1833f971 | <|skeleton|>
class Categorizer:
"""The parent class for creating and viewing labeled categories on a dataframe of snippets and other metadata"""
def __init__(self, df_path, sc=sc, sql=sql, id_field='Url', snippet_field='Cleaned Snippet'):
""":param df_path: Pandas df containing cleaned snippets and ids... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Categorizer:
"""The parent class for creating and viewing labeled categories on a dataframe of snippets and other metadata"""
def __init__(self, df_path, sc=sc, sql=sql, id_field='Url', snippet_field='Cleaned Snippet'):
""":param df_path: Pandas df containing cleaned snippets and ids (as a maximu... | the_stack_v2_python_sparse | usherwood_ds/nlp/taxonomy/spark_regex_categorizer.py | Usherwood/usherwood_ds | train | 2 |
fb0160eee3cdaf072a390a80cbebc6c22b58847e | [
"cls.require_notfound(path)\nNEW_SCRIPT_TEMPLATE = '\"\"\"%s\"\"\"\\n# Keep __doc__ to a single line\\nfrom pyClanSphere.upgrades.versions import *\\n\\n# use this or define your own if you need\\nmetadata = db.MetaData()\\n\\n# Define tables here\\n\\n\\n# Define the objects here\\n\\n\\ndef map_tables(mapper):\\n... | <|body_start_0|>
cls.require_notfound(path)
NEW_SCRIPT_TEMPLATE = '"""%s"""\n# Keep __doc__ to a single line\nfrom pyClanSphere.upgrades.versions import *\n\n# use this or define your own if you need\nmetadata = db.MetaData()\n\n# Define tables here\n\n\n# Define the objects here\n\n\ndef map_tables(map... | PythonScript | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PythonScript:
def create(cls, path, **opts):
"""Create an empty migration script at specified path :returns: :class:`PythonScript instance <migrate.versioning.script.py.PythonScript>`"""
<|body_0|>
def run(self, engine, step):
"""Core method of Script file. Exectues ... | stack_v2_sparse_classes_36k_train_014320 | 8,942 | permissive | [
{
"docstring": "Create an empty migration script at specified path :returns: :class:`PythonScript instance <migrate.versioning.script.py.PythonScript>`",
"name": "create",
"signature": "def create(cls, path, **opts)"
},
{
"docstring": "Core method of Script file. Exectues :func:`update` or :func... | 2 | stack_v2_sparse_classes_30k_train_002910 | Implement the Python class `PythonScript` described below.
Class description:
Implement the PythonScript class.
Method signatures and docstrings:
- def create(cls, path, **opts): Create an empty migration script at specified path :returns: :class:`PythonScript instance <migrate.versioning.script.py.PythonScript>`
- d... | Implement the Python class `PythonScript` described below.
Class description:
Implement the PythonScript class.
Method signatures and docstrings:
- def create(cls, path, **opts): Create an empty migration script at specified path :returns: :class:`PythonScript instance <migrate.versioning.script.py.PythonScript>`
- d... | 03904b3de4ae2043c0ff2a68a50c5f916896b68d | <|skeleton|>
class PythonScript:
def create(cls, path, **opts):
"""Create an empty migration script at specified path :returns: :class:`PythonScript instance <migrate.versioning.script.py.PythonScript>`"""
<|body_0|>
def run(self, engine, step):
"""Core method of Script file. Exectues ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PythonScript:
def create(cls, path, **opts):
"""Create an empty migration script at specified path :returns: :class:`PythonScript instance <migrate.versioning.script.py.PythonScript>`"""
cls.require_notfound(path)
NEW_SCRIPT_TEMPLATE = '"""%s"""\n# Keep __doc__ to a single line\nfrom p... | the_stack_v2_python_sparse | pyClanSphere/upgrades/customisation.py | jokey2k/pyClanSphere | train | 1 | |
6b1749c324eba4829dfd834bfda3bf544da7f8b9 | [
"try:\n result = []\n for record in response:\n numOfIteration = 0\n original_map = target_map.copy()\n for key, value in target_map.items():\n if type(record[numOfIteration]) == datetime.datetime:\n target_map[key] = record[numOfIteration].strftime('%Y-%m-%d %H:... | <|body_start_0|>
try:
result = []
for record in response:
numOfIteration = 0
original_map = target_map.copy()
for key, value in target_map.items():
if type(record[numOfIteration]) == datetime.datetime:
... | DBreadHelper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DBreadHelper:
def map_response(self, response=[], target_map={}):
"""map_response() => Maps Database Query Response to Object. params => response (array)"""
<|body_0|>
def map_detail_response(self, response=[], target_map={}):
"""map_detail_response() => Maps Databas... | stack_v2_sparse_classes_36k_train_014321 | 3,601 | no_license | [
{
"docstring": "map_response() => Maps Database Query Response to Object. params => response (array)",
"name": "map_response",
"signature": "def map_response(self, response=[], target_map={})"
},
{
"docstring": "map_detail_response() => Maps Database Query Response to Object. params => response ... | 2 | null | Implement the Python class `DBreadHelper` described below.
Class description:
Implement the DBreadHelper class.
Method signatures and docstrings:
- def map_response(self, response=[], target_map={}): map_response() => Maps Database Query Response to Object. params => response (array)
- def map_detail_response(self, r... | Implement the Python class `DBreadHelper` described below.
Class description:
Implement the DBreadHelper class.
Method signatures and docstrings:
- def map_response(self, response=[], target_map={}): map_response() => Maps Database Query Response to Object. params => response (array)
- def map_detail_response(self, r... | bbe7c7e74313ed63d7765a16cf11fdf7f3ad706a | <|skeleton|>
class DBreadHelper:
def map_response(self, response=[], target_map={}):
"""map_response() => Maps Database Query Response to Object. params => response (array)"""
<|body_0|>
def map_detail_response(self, response=[], target_map={}):
"""map_detail_response() => Maps Databas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DBreadHelper:
def map_response(self, response=[], target_map={}):
"""map_response() => Maps Database Query Response to Object. params => response (array)"""
try:
result = []
for record in response:
numOfIteration = 0
original_map = target... | the_stack_v2_python_sparse | skytrip/db_read/helper.py | NumanIbnMazid/reservation | train | 1 | |
593463b05855cb3ebffac5c7ec4c9ca85eaba891 | [
"super().__init__()\nself._name = name\nself._cities = cities\nself._overhead_queue = queue",
"for i, city in enumerate(self._cities, start=1):\n overhead_time = city_processor.ISSDataRequest.get_overhead_pass(city)\n logging.info('Producer %d is adding to the queue', self._name)\n self._overhead_queue.p... | <|body_start_0|>
super().__init__()
self._name = name
self._cities = cities
self._overhead_queue = queue
<|end_body_0|>
<|body_start_1|>
for i, city in enumerate(self._cities, start=1):
overhead_time = city_processor.ISSDataRequest.get_overhead_pass(city)
... | ProducerThread | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProducerThread:
def __init__(self, cities: list, queue: CityOverheadTimeQueue, name: int):
"""This method initializes the class with a list of City Objects as well as a CityOverheadTimeQueue. :param cities: list(City) :param queue: CityOverheadTimeQueue :return: None"""
<|body_0|... | stack_v2_sparse_classes_36k_train_014322 | 5,647 | no_license | [
{
"docstring": "This method initializes the class with a list of City Objects as well as a CityOverheadTimeQueue. :param cities: list(City) :param queue: CityOverheadTimeQueue :return: None",
"name": "__init__",
"signature": "def __init__(self, cities: list, queue: CityOverheadTimeQueue, name: int)"
}... | 2 | stack_v2_sparse_classes_30k_val_000898 | Implement the Python class `ProducerThread` described below.
Class description:
Implement the ProducerThread class.
Method signatures and docstrings:
- def __init__(self, cities: list, queue: CityOverheadTimeQueue, name: int): This method initializes the class with a list of City Objects as well as a CityOverheadTime... | Implement the Python class `ProducerThread` described below.
Class description:
Implement the ProducerThread class.
Method signatures and docstrings:
- def __init__(self, cities: list, queue: CityOverheadTimeQueue, name: int): This method initializes the class with a list of City Objects as well as a CityOverheadTime... | 5fbc92a7ddd9103076a7095124b5ae108b002f03 | <|skeleton|>
class ProducerThread:
def __init__(self, cities: list, queue: CityOverheadTimeQueue, name: int):
"""This method initializes the class with a list of City Objects as well as a CityOverheadTimeQueue. :param cities: list(City) :param queue: CityOverheadTimeQueue :return: None"""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProducerThread:
def __init__(self, cities: list, queue: CityOverheadTimeQueue, name: int):
"""This method initializes the class with a list of City Objects as well as a CityOverheadTimeQueue. :param cities: list(City) :param queue: CityOverheadTimeQueue :return: None"""
super().__init__()
... | the_stack_v2_python_sparse | Labs/Lab10/producer_consumer.py | pyopoly/3522_A00699267 | train | 0 | |
883e4b40ce9d3ed4c00311e6c40aac692aad3cc2 | [
"if not head or not head.next:\n return head\ncount = 1\ncur = head\nwhile cur.next:\n cur = cur.next\n count += 1\nk = count - k % count\ncur.next = head\nwhile k > 0:\n cur = cur.next\n k -= 1\nhead = cur.next\ncur.next = None\nreturn head",
"nums = []\nguard = ListNode(next=head)\nwhile head:\n ... | <|body_start_0|>
if not head or not head.next:
return head
count = 1
cur = head
while cur.next:
cur = cur.next
count += 1
k = count - k % count
cur.next = head
while k > 0:
cur = cur.next
k -= 1
h... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotateRight(self, head: ListNode, k: int) -> ListNode:
"""执行用时： 60 ms , 在所有 Python3 提交中击败了 5.44% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 67.75% 的用户"""
<|body_0|>
def rotateRight1(self, head: ListNode, k: int) -> ListNode:
"""执行用时： 44 ms , 在所有 Python3 提交中... | stack_v2_sparse_classes_36k_train_014323 | 2,485 | no_license | [
{
"docstring": "执行用时： 60 ms , 在所有 Python3 提交中击败了 5.44% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 67.75% 的用户",
"name": "rotateRight",
"signature": "def rotateRight(self, head: ListNode, k: int) -> ListNode"
},
{
"docstring": "执行用时： 44 ms , 在所有 Python3 提交中击败了 63.50% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotateRight(self, head: ListNode, k: int) -> ListNode: 执行用时： 60 ms , 在所有 Python3 提交中击败了 5.44% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 67.75% 的用户
- def rotateRight1(self, head:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotateRight(self, head: ListNode, k: int) -> ListNode: 执行用时： 60 ms , 在所有 Python3 提交中击败了 5.44% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 67.75% 的用户
- def rotateRight1(self, head:... | d613ed8a5a2c15ace7d513965b372d128845d66a | <|skeleton|>
class Solution:
def rotateRight(self, head: ListNode, k: int) -> ListNode:
"""执行用时： 60 ms , 在所有 Python3 提交中击败了 5.44% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 67.75% 的用户"""
<|body_0|>
def rotateRight1(self, head: ListNode, k: int) -> ListNode:
"""执行用时： 44 ms , 在所有 Python3 提交中... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotateRight(self, head: ListNode, k: int) -> ListNode:
"""执行用时： 60 ms , 在所有 Python3 提交中击败了 5.44% 的用户 内存消耗： 14.9 MB , 在所有 Python3 提交中击败了 67.75% 的用户"""
if not head or not head.next:
return head
count = 1
cur = head
while cur.next:
cur... | the_stack_v2_python_sparse | 旋转链表.py | nomboy/leetcode | train | 0 | |
7492e29f36ea40248a2dac87529e0290e6668ea4 | [
"self.u1 = User.objects.create_user('user1', 'user@user.com', 'password')\nself.u2 = User.objects.create_user('user2', 'user@user.com', 'password')\ncreate_permission('permission1', description='Permission 1 description.')\ngive_permission_to('permission1', self.u1, self.u1, can_delegate=True)\ngive_permission_to('... | <|body_start_0|>
self.u1 = User.objects.create_user('user1', 'user@user.com', 'password')
self.u2 = User.objects.create_user('user2', 'user@user.com', 'password')
create_permission('permission1', description='Permission 1 description.')
give_permission_to('permission1', self.u1, self.u1,... | RequestsTests | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RequestsTests:
def setUp(self):
"""Create some permissions and users."""
<|body_0|>
def test_req_process(self):
"""Test that when a request is made for a user, it shows up in the dashboard."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.u1 = U... | stack_v2_sparse_classes_36k_train_014324 | 3,183 | permissive | [
{
"docstring": "Create some permissions and users.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test that when a request is made for a user, it shows up in the dashboard.",
"name": "test_req_process",
"signature": "def test_req_process(self)"
}
] | 2 | null | Implement the Python class `RequestsTests` described below.
Class description:
Implement the RequestsTests class.
Method signatures and docstrings:
- def setUp(self): Create some permissions and users.
- def test_req_process(self): Test that when a request is made for a user, it shows up in the dashboard. | Implement the Python class `RequestsTests` described below.
Class description:
Implement the RequestsTests class.
Method signatures and docstrings:
- def setUp(self): Create some permissions and users.
- def test_req_process(self): Test that when a request is made for a user, it shows up in the dashboard.
<|skeleton... | 059ed2b3308bda2af5e1942dc9967e6573dd6a53 | <|skeleton|>
class RequestsTests:
def setUp(self):
"""Create some permissions and users."""
<|body_0|>
def test_req_process(self):
"""Test that when a request is made for a user, it shows up in the dashboard."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RequestsTests:
def setUp(self):
"""Create some permissions and users."""
self.u1 = User.objects.create_user('user1', 'user@user.com', 'password')
self.u2 = User.objects.create_user('user2', 'user@user.com', 'password')
create_permission('permission1', description='Permission 1 ... | the_stack_v2_python_sparse | expedient/src/python/expedient/clearinghouse/permissionmgmt/tests.py | dana-i2cat/felix | train | 4 | |
29a1f81b6cf6f160d3e819a697662b4bf8503e08 | [
"with transaction.atomic(savepoint=True):\n self.task.started = now()\n self.task.save()\n signals.task_started.send(sender=self.flow_class, process=self.process, task=self.task)\n for task in self.process.active_tasks():\n if task != self.task:\n break\n else:\n self.process... | <|body_start_0|>
with transaction.atomic(savepoint=True):
self.task.started = now()
self.task.save()
signals.task_started.send(sender=self.flow_class, process=self.process, task=self.task)
for task in self.process.active_tasks():
if task != self.ta... | Activation that finishes the flow process. .. graphviz:: digraph status { UNRIPE; NEW -> CANCELED [label="cancel"]; DONE -> NEW [label="undo"]; NEW -> DONE [label="perform"]; {rank = min;NEW} } | EndActivation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EndActivation:
"""Activation that finishes the flow process. .. graphviz:: digraph status { UNRIPE; NEW -> CANCELED [label="cancel"]; DONE -> NEW [label="undo"]; NEW -> DONE [label="perform"]; {rank = min;NEW} }"""
def perform(self):
"""Finalize the flow. If there is no active task, ... | stack_v2_sparse_classes_36k_train_014325 | 24,697 | permissive | [
{
"docstring": "Finalize the flow. If there is no active task, process marked as finished. .. seealso:: :data:`viewflow.signals.task_started` .. seealso:: :data:`viewflow.signals.task_finished` .. seealso:: :data:`viewflow.signals.flow_finished`",
"name": "perform",
"signature": "def perform(self)"
},... | 3 | stack_v2_sparse_classes_30k_val_001196 | Implement the Python class `EndActivation` described below.
Class description:
Activation that finishes the flow process. .. graphviz:: digraph status { UNRIPE; NEW -> CANCELED [label="cancel"]; DONE -> NEW [label="undo"]; NEW -> DONE [label="perform"]; {rank = min;NEW} }
Method signatures and docstrings:
- def perfo... | Implement the Python class `EndActivation` described below.
Class description:
Activation that finishes the flow process. .. graphviz:: digraph status { UNRIPE; NEW -> CANCELED [label="cancel"]; DONE -> NEW [label="undo"]; NEW -> DONE [label="perform"]; {rank = min;NEW} }
Method signatures and docstrings:
- def perfo... | 0267168bb90e8e9c85aecdd715972b9622b82384 | <|skeleton|>
class EndActivation:
"""Activation that finishes the flow process. .. graphviz:: digraph status { UNRIPE; NEW -> CANCELED [label="cancel"]; DONE -> NEW [label="undo"]; NEW -> DONE [label="perform"]; {rank = min;NEW} }"""
def perform(self):
"""Finalize the flow. If there is no active task, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EndActivation:
"""Activation that finishes the flow process. .. graphviz:: digraph status { UNRIPE; NEW -> CANCELED [label="cancel"]; DONE -> NEW [label="undo"]; NEW -> DONE [label="perform"]; {rank = min;NEW} }"""
def perform(self):
"""Finalize the flow. If there is no active task, process marke... | the_stack_v2_python_sparse | Scripts/ict/viewflow/activation.py | mspgeek/Client_Portal | train | 6 |
1b27a07071ac669eed2ea6fd63abbb44245e8a56 | [
"if amount == 0:\n return 0\nqueue = collections.deque(coins)\nd = {x: 1 for x in coins}\nwhile queue:\n cur = queue.popleft()\n if cur == amount:\n return d[cur]\n for i in coins:\n k = cur + i\n if k <= amount and (not k in d):\n queue.append(k)\n d[k] = d[cu... | <|body_start_0|>
if amount == 0:
return 0
queue = collections.deque(coins)
d = {x: 1 for x in coins}
while queue:
cur = queue.popleft()
if cur == amount:
return d[cur]
for i in coins:
k = cur + i
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def coinChange(self, coins, amount):
"""bfs AC :param coins: :param amount: :return:"""
<|body_0|>
def coinChange3(self, coins, amount):
"""完全背包问题 :param coins: :param amount: :return:"""
<|body_1|>
def coinChange2(self, coins, amount):
... | stack_v2_sparse_classes_36k_train_014326 | 2,469 | no_license | [
{
"docstring": "bfs AC :param coins: :param amount: :return:",
"name": "coinChange",
"signature": "def coinChange(self, coins, amount)"
},
{
"docstring": "完全背包问题 :param coins: :param amount: :return:",
"name": "coinChange3",
"signature": "def coinChange3(self, coins, amount)"
},
{
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def coinChange(self, coins, amount): bfs AC :param coins: :param amount: :return:
- def coinChange3(self, coins, amount): 完全背包问题 :param coins: :param amount: :return:
- def coinC... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def coinChange(self, coins, amount): bfs AC :param coins: :param amount: :return:
- def coinChange3(self, coins, amount): 完全背包问题 :param coins: :param amount: :return:
- def coinC... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def coinChange(self, coins, amount):
"""bfs AC :param coins: :param amount: :return:"""
<|body_0|>
def coinChange3(self, coins, amount):
"""完全背包问题 :param coins: :param amount: :return:"""
<|body_1|>
def coinChange2(self, coins, amount):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def coinChange(self, coins, amount):
"""bfs AC :param coins: :param amount: :return:"""
if amount == 0:
return 0
queue = collections.deque(coins)
d = {x: 1 for x in coins}
while queue:
cur = queue.popleft()
if cur == amount:... | the_stack_v2_python_sparse | 322_零钱兑换.py | lovehhf/LeetCode | train | 0 | |
47b8d4587edf5e941c97bcf02cf828571cc749d7 | [
"self.host = host\nself.user = user\nself.private_key = private_key\nself.password = password\nself.stdout = stdout\nself.client = self._connect()",
"try:\n client = SSHClient()\n client.set_missing_host_key_policy(AutoAddPolicy())\n if self.private_key:\n client.connect(self.host, username=self.u... | <|body_start_0|>
self.host = host
self.user = user
self.private_key = private_key
self.password = password
self.stdout = stdout
self.client = self._connect()
<|end_body_0|>
<|body_start_1|>
try:
client = SSHClient()
client.set_missing_host... | A class that connects to remote server | Connection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Connection:
"""A class that connects to remote server"""
def __init__(self, host, user=None, private_key=None, password=None, stdout=False):
"""Initialize all required variables Args: host (str): Hostname or IP to connect user (str): User name to connect private_key (str): Private ke... | stack_v2_sparse_classes_36k_train_014327 | 2,862 | permissive | [
{
"docstring": "Initialize all required variables Args: host (str): Hostname or IP to connect user (str): User name to connect private_key (str): Private key to connect to load balancer password (password): Password for host stdout (bool): output stdout to console",
"name": "__init__",
"signature": "def... | 3 | null | Implement the Python class `Connection` described below.
Class description:
A class that connects to remote server
Method signatures and docstrings:
- def __init__(self, host, user=None, private_key=None, password=None, stdout=False): Initialize all required variables Args: host (str): Hostname or IP to connect user ... | Implement the Python class `Connection` described below.
Class description:
A class that connects to remote server
Method signatures and docstrings:
- def __init__(self, host, user=None, private_key=None, password=None, stdout=False): Initialize all required variables Args: host (str): Hostname or IP to connect user ... | 5e9e504957403148e413326f65c3769bf9d8eb39 | <|skeleton|>
class Connection:
"""A class that connects to remote server"""
def __init__(self, host, user=None, private_key=None, password=None, stdout=False):
"""Initialize all required variables Args: host (str): Hostname or IP to connect user (str): User name to connect private_key (str): Private ke... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Connection:
"""A class that connects to remote server"""
def __init__(self, host, user=None, private_key=None, password=None, stdout=False):
"""Initialize all required variables Args: host (str): Hostname or IP to connect user (str): User name to connect private_key (str): Private key to connect ... | the_stack_v2_python_sparse | ocs_ci/utility/connection.py | red-hat-storage/ocs-ci | train | 146 |
6895f11868462aa091d0e48854df6cdd16f4f47d | [
"skill_set = get_object_or_404(Instrument, slug=slug)\nself.check_object_permissions(request, skill_set)\nserializer = InstrumentRetrieveUpdateSerializer(skill_set, many=False)\nreturn Response(data=serializer.data, status=status.HTTP_200_OK)",
"skill_set = get_object_or_404(Instrument, slug=slug)\nself.check_obj... | <|body_start_0|>
skill_set = get_object_or_404(Instrument, slug=slug)
self.check_object_permissions(request, skill_set)
serializer = InstrumentRetrieveUpdateSerializer(skill_set, many=False)
return Response(data=serializer.data, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>... | InstrumentRetrieveUpdateAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstrumentRetrieveUpdateAPIView:
def get(self, request, slug=None):
"""Retrieve"""
<|body_0|>
def put(self, request, slug=None):
"""Update"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
skill_set = get_object_or_404(Instrument, slug=slug)
s... | stack_v2_sparse_classes_36k_train_014328 | 2,477 | permissive | [
{
"docstring": "Retrieve",
"name": "get",
"signature": "def get(self, request, slug=None)"
},
{
"docstring": "Update",
"name": "put",
"signature": "def put(self, request, slug=None)"
}
] | 2 | null | Implement the Python class `InstrumentRetrieveUpdateAPIView` described below.
Class description:
Implement the InstrumentRetrieveUpdateAPIView class.
Method signatures and docstrings:
- def get(self, request, slug=None): Retrieve
- def put(self, request, slug=None): Update | Implement the Python class `InstrumentRetrieveUpdateAPIView` described below.
Class description:
Implement the InstrumentRetrieveUpdateAPIView class.
Method signatures and docstrings:
- def get(self, request, slug=None): Retrieve
- def put(self, request, slug=None): Update
<|skeleton|>
class InstrumentRetrieveUpdate... | 98e1ff8bab7dda3492e5ff637bf5aafd111c840c | <|skeleton|>
class InstrumentRetrieveUpdateAPIView:
def get(self, request, slug=None):
"""Retrieve"""
<|body_0|>
def put(self, request, slug=None):
"""Update"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstrumentRetrieveUpdateAPIView:
def get(self, request, slug=None):
"""Retrieve"""
skill_set = get_object_or_404(Instrument, slug=slug)
self.check_object_permissions(request, skill_set)
serializer = InstrumentRetrieveUpdateSerializer(skill_set, many=False)
return Respon... | the_stack_v2_python_sparse | mikaponics/instrument/views/resource/instrument_crud_api_views.py | mikaponics/mikaponics-back | train | 4 | |
d7c3e5d1a4d4224173c286b11ef56dcc505953a6 | [
"n = len(s)\nst = [[0] * n for _ in range(n)]\nfor i in range(n - 1, -1, -1):\n for j in range(i, n):\n if j - i <= 1 and s[i] == s[j]:\n st[i][j] = 1\n elif st[i + 1][j - 1] and s[i] == s[j]:\n st[i][j] = 1\ndp = [0] * (n + 1)\nfor i in range(1, n + 1):\n dp[i] = min([dp[j... | <|body_start_0|>
n = len(s)
st = [[0] * n for _ in range(n)]
for i in range(n - 1, -1, -1):
for j in range(i, n):
if j - i <= 1 and s[i] == s[j]:
st[i][j] = 1
elif st[i + 1][j - 1] and s[i] == s[j]:
st[i][j] = 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minCut(self, s):
"""两次dp :param s: :return:"""
<|body_0|>
def minCut2(self, s):
"""dfs 妥妥的超时 res 存储所有可能的分割的次数 :type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(s)
st = [[0] * n for _ in range(n)]
... | stack_v2_sparse_classes_36k_train_014329 | 2,232 | no_license | [
{
"docstring": "两次dp :param s: :return:",
"name": "minCut",
"signature": "def minCut(self, s)"
},
{
"docstring": "dfs 妥妥的超时 res 存储所有可能的分割的次数 :type s: str :rtype: int",
"name": "minCut2",
"signature": "def minCut2(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minCut(self, s): 两次dp :param s: :return:
- def minCut2(self, s): dfs 妥妥的超时 res 存储所有可能的分割的次数 :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minCut(self, s): 两次dp :param s: :return:
- def minCut2(self, s): dfs 妥妥的超时 res 存储所有可能的分割的次数 :type s: str :rtype: int
<|skeleton|>
class Solution:
def minCut(self, s):
... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def minCut(self, s):
"""两次dp :param s: :return:"""
<|body_0|>
def minCut2(self, s):
"""dfs 妥妥的超时 res 存储所有可能的分割的次数 :type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minCut(self, s):
"""两次dp :param s: :return:"""
n = len(s)
st = [[0] * n for _ in range(n)]
for i in range(n - 1, -1, -1):
for j in range(i, n):
if j - i <= 1 and s[i] == s[j]:
st[i][j] = 1
elif st[i +... | the_stack_v2_python_sparse | 132_分割回文串 II.py | lovehhf/LeetCode | train | 0 | |
e6fbe557a1cec65b2bbe82599d29dd09e8cdc2f6 | [
"if data is None:\n if lambtha < 1:\n raise ValueError('lambtha must be a positive value')\n else:\n self.lambtha = lambtha\nelse:\n if not isinstance(data, list):\n raise TypeError('data must be a list')\n if len(data) < 2:\n raise ValueError('data must contain multiple valu... | <|body_start_0|>
if data is None:
if lambtha < 1:
raise ValueError('lambtha must be a positive value')
else:
self.lambtha = lambtha
else:
if not isinstance(data, list):
raise TypeError('data must be a list')
... | The Exponential Distribution class | Exponential | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exponential:
"""The Exponential Distribution class"""
def __init__(self, data=None, lambtha=1.0):
"""init lambtha of data"""
<|body_0|>
def pdf(self, x):
"""The pdf for exponential distribution"""
<|body_1|>
def cdf(self, x):
"""The cumulativ... | stack_v2_sparse_classes_36k_train_014330 | 1,084 | no_license | [
{
"docstring": "init lambtha of data",
"name": "__init__",
"signature": "def __init__(self, data=None, lambtha=1.0)"
},
{
"docstring": "The pdf for exponential distribution",
"name": "pdf",
"signature": "def pdf(self, x)"
},
{
"docstring": "The cumulative distribution function",
... | 3 | null | Implement the Python class `Exponential` described below.
Class description:
The Exponential Distribution class
Method signatures and docstrings:
- def __init__(self, data=None, lambtha=1.0): init lambtha of data
- def pdf(self, x): The pdf for exponential distribution
- def cdf(self, x): The cumulative distribution ... | Implement the Python class `Exponential` described below.
Class description:
The Exponential Distribution class
Method signatures and docstrings:
- def __init__(self, data=None, lambtha=1.0): init lambtha of data
- def pdf(self, x): The pdf for exponential distribution
- def cdf(self, x): The cumulative distribution ... | 4200798bdbbe828db94e5585b62a595e3a96c3e6 | <|skeleton|>
class Exponential:
"""The Exponential Distribution class"""
def __init__(self, data=None, lambtha=1.0):
"""init lambtha of data"""
<|body_0|>
def pdf(self, x):
"""The pdf for exponential distribution"""
<|body_1|>
def cdf(self, x):
"""The cumulativ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Exponential:
"""The Exponential Distribution class"""
def __init__(self, data=None, lambtha=1.0):
"""init lambtha of data"""
if data is None:
if lambtha < 1:
raise ValueError('lambtha must be a positive value')
else:
self.lambtha = l... | the_stack_v2_python_sparse | math/0x03-probability/exponential.py | JohnCook17/holbertonschool-machine_learning | train | 3 |
f54c70bccf53b3a61009efc4e4c59dec03e03fc0 | [
"kwds['channels'] = channels\nsuper().__init__(**kwds)\nfor channel in self.channels:\n channel[2].setMaximum(1.0)",
"active = []\nincrement = []\nfor i, channel in enumerate(self.channels):\n if self.which_checked[i] and frame_number % channel[3].value() == 0:\n active.append(True)\n incremen... | <|body_start_0|>
kwds['channels'] = channels
super().__init__(**kwds)
for channel in self.channels:
channel[2].setMaximum(1.0)
<|end_body_0|>
<|body_start_1|>
active = []
increment = []
for i, channel in enumerate(self.channels):
if self.which_che... | Channels class for linear progression. | LinearChannels | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearChannels:
"""Channels class for linear progression."""
def __init__(self, channels=None, **kwds):
"""This is basically the same as for MathChannels. It also specifies a maximum value for the increment spin box."""
<|body_0|>
def handleNewFrame(self, frame_number):
... | stack_v2_sparse_classes_36k_train_014331 | 25,535 | permissive | [
{
"docstring": "This is basically the same as for MathChannels. It also specifies a maximum value for the increment spin box.",
"name": "__init__",
"signature": "def __init__(self, channels=None, **kwds)"
},
{
"docstring": "Called when we get a new frame from the camera. Returns the which channe... | 2 | null | Implement the Python class `LinearChannels` described below.
Class description:
Channels class for linear progression.
Method signatures and docstrings:
- def __init__(self, channels=None, **kwds): This is basically the same as for MathChannels. It also specifies a maximum value for the increment spin box.
- def hand... | Implement the Python class `LinearChannels` described below.
Class description:
Channels class for linear progression.
Method signatures and docstrings:
- def __init__(self, channels=None, **kwds): This is basically the same as for MathChannels. It also specifies a maximum value for the increment spin box.
- def hand... | f185df3d23b231a26c46f33b0b91fffa86356dc4 | <|skeleton|>
class LinearChannels:
"""Channels class for linear progression."""
def __init__(self, channels=None, **kwds):
"""This is basically the same as for MathChannels. It also specifies a maximum value for the increment spin box."""
<|body_0|>
def handleNewFrame(self, frame_number):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinearChannels:
"""Channels class for linear progression."""
def __init__(self, channels=None, **kwds):
"""This is basically the same as for MathChannels. It also specifies a maximum value for the increment spin box."""
kwds['channels'] = channels
super().__init__(**kwds)
... | the_stack_v2_python_sparse | storm_control/hal4000/progressions/progressions.py | ZhuangLab/storm-control | train | 54 |
defeaceebf02603bd7b6a99f07f637d54018a87f | [
"assert isinstance(param_group, dict), 'param group must be a dict'\nparams = param_group['params']\nif isinstance(params, (torch.Tensor, crypten.CrypTensor)):\n param_group['params'] = [params]\nelif isinstance(params, set):\n raise TypeError('optimizer parameters need to be organized in ordered collections,... | <|body_start_0|>
assert isinstance(param_group, dict), 'param group must be a dict'
params = param_group['params']
if isinstance(params, (torch.Tensor, crypten.CrypTensor)):
param_group['params'] = [params]
elif isinstance(params, set):
raise TypeError('optimizer ... | Base class for all optimizers. .. warning:: Parameters need to be specified as collections that have a deterministic ordering that is consistent between runs. Examples of objects that don't satisfy those properties are sets and iterators over values of dictionaries. Arguments: params (iterable): an iterable of :class:`... | Optimizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Optimizer:
"""Base class for all optimizers. .. warning:: Parameters need to be specified as collections that have a deterministic ordering that is consistent between runs. Examples of objects that don't satisfy those properties are sets and iterators over values of dictionaries. Arguments: param... | stack_v2_sparse_classes_36k_train_014332 | 4,383 | permissive | [
{
"docstring": "Add a param group to the :class:`Optimizer` s `param_groups`. This can be useful when fine tuning a pre-trained network as frozen layers can be made trainable and added to the :class:`Optimizer` as training progresses. Arguments: param_group (dict): Specifies what Tensors should be optimized alo... | 2 | null | Implement the Python class `Optimizer` described below.
Class description:
Base class for all optimizers. .. warning:: Parameters need to be specified as collections that have a deterministic ordering that is consistent between runs. Examples of objects that don't satisfy those properties are sets and iterators over v... | Implement the Python class `Optimizer` described below.
Class description:
Base class for all optimizers. .. warning:: Parameters need to be specified as collections that have a deterministic ordering that is consistent between runs. Examples of objects that don't satisfy those properties are sets and iterators over v... | 99c3a046b705c9d69d7a10fcab59a444ffbee39a | <|skeleton|>
class Optimizer:
"""Base class for all optimizers. .. warning:: Parameters need to be specified as collections that have a deterministic ordering that is consistent between runs. Examples of objects that don't satisfy those properties are sets and iterators over values of dictionaries. Arguments: param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Optimizer:
"""Base class for all optimizers. .. warning:: Parameters need to be specified as collections that have a deterministic ordering that is consistent between runs. Examples of objects that don't satisfy those properties are sets and iterators over values of dictionaries. Arguments: params (iterable):... | the_stack_v2_python_sparse | crypten/optim/optimizer.py | facebookresearch/CrypTen | train | 1,388 |
8d41b5aa0b39dd65c417649d1765dcc1e5f62eb8 | [
"self.dic = {}\nself.queue = []\nself.remain = capacity",
"if key not in self.dic:\n return -1\nelse:\n self.queue.remove(key)\n self.queue.append(key)\n return self.dic[key]",
"if key in self.dic:\n self.queue.remove(key)\n self.queue.append(key)\nelse:\n if self.remain > 0:\n self.... | <|body_start_0|>
self.dic = {}
self.queue = []
self.remain = capacity
<|end_body_0|>
<|body_start_1|>
if key not in self.dic:
return -1
else:
self.queue.remove(key)
self.queue.append(key)
return self.dic[key]
<|end_body_1|>
<|body... | LRUCache2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache2:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_014333 | 3,363 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: nothing",
"name": "set",
"sig... | 3 | null | Implement the Python class `LRUCache2` described below.
Class description:
Implement the LRUCache2 class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing | Implement the Python class `LRUCache2` described below.
Class description:
Implement the LRUCache2 class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing
<|skeleton|>
c... | 1df8d93a8ecb8627899aadddb5dd5c5d0b144cdf | <|skeleton|>
class LRUCache2:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache2:
def __init__(self, capacity):
""":type capacity: int"""
self.dic = {}
self.queue = []
self.remain = capacity
def get(self, key):
""":rtype: int"""
if key not in self.dic:
return -1
else:
self.queue.remove(key)
... | the_stack_v2_python_sparse | LRU.py | zhuolikevin/Algorithm-Practices-Python | train | 0 | |
ae2442c4d6ad0fb664be80d134e8bc7feeee63a7 | [
"if decay_time <= datetime.timedelta(0):\n raise ValueError('decay_time must have positive duration')\nself.decay_time = decay_time\nself.decay_factor = decay_factor",
"timestamp, x = value\nif now is None:\n now = datetime.datetime.utcnow()\ndelta = now - timestamp\nif delta < datetime.timedelta(seconds=0)... | <|body_start_0|>
if decay_time <= datetime.timedelta(0):
raise ValueError('decay_time must have positive duration')
self.decay_time = decay_time
self.decay_factor = decay_factor
<|end_body_0|>
<|body_start_1|>
timestamp, x = value
if now is None:
now = da... | TimeDecay class. Helps to update counters that require a time decay | TimeDecay | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeDecay:
"""TimeDecay class. Helps to update counters that require a time decay"""
def __init__(self, decay_time, decay_factor=2.0):
"""decay_time is timedelta"""
<|body_0|>
def update_value(self, value, now=None):
"""Computes the updated value for the given ha... | stack_v2_sparse_classes_36k_train_014334 | 1,847 | permissive | [
{
"docstring": "decay_time is timedelta",
"name": "__init__",
"signature": "def __init__(self, decay_time, decay_factor=2.0)"
},
{
"docstring": "Computes the updated value for the given half-life. Args: value (tuple(datetime.datetime, numeric_type)): tuple with the numeric value we wish to updat... | 2 | stack_v2_sparse_classes_30k_train_011536 | Implement the Python class `TimeDecay` described below.
Class description:
TimeDecay class. Helps to update counters that require a time decay
Method signatures and docstrings:
- def __init__(self, decay_time, decay_factor=2.0): decay_time is timedelta
- def update_value(self, value, now=None): Computes the updated v... | Implement the Python class `TimeDecay` described below.
Class description:
TimeDecay class. Helps to update counters that require a time decay
Method signatures and docstrings:
- def __init__(self, decay_time, decay_factor=2.0): decay_time is timedelta
- def update_value(self, value, now=None): Computes the updated v... | 70280110ec342a6f6db1c102e96756fcc3c3c01b | <|skeleton|>
class TimeDecay:
"""TimeDecay class. Helps to update counters that require a time decay"""
def __init__(self, decay_time, decay_factor=2.0):
"""decay_time is timedelta"""
<|body_0|>
def update_value(self, value, now=None):
"""Computes the updated value for the given ha... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimeDecay:
"""TimeDecay class. Helps to update counters that require a time decay"""
def __init__(self, decay_time, decay_factor=2.0):
"""decay_time is timedelta"""
if decay_time <= datetime.timedelta(0):
raise ValueError('decay_time must have positive duration')
self.... | the_stack_v2_python_sparse | pylib/util/time_decay.py | room77/py77 | train | 0 |
e910ff849bd391adad910ddebabb5cad65964106 | [
"super().__init__()\nif shared_dim is None:\n shared_dim = num_filts * 2 ** n_sample\nshared_block_enc = block_cls(shared_dim)\nshared_block_gen = block_cls(shared_dim)\nself.encoder_a = encoder_cls(shared_block_enc, img_shape[0], num_filts, n_sample)\nself.encoder_b = encoder_cls(shared_block_enc, img_shape[0],... | <|body_start_0|>
super().__init__()
if shared_dim is None:
shared_dim = num_filts * 2 ** n_sample
shared_block_enc = block_cls(shared_dim)
shared_block_gen = block_cls(shared_dim)
self.encoder_a = encoder_cls(shared_block_enc, img_shape[0], num_filts, n_sample)
... | Class implementing Unsupervised Image-to-Image Translation Networks References ---------- `Paper <https://arxiv.org/abs/1703.00848>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained network, it might be best, to split this network into its parts (i. e. separa... | UNIT | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UNIT:
"""Class implementing Unsupervised Image-to-Image Translation Networks References ---------- `Paper <https://arxiv.org/abs/1703.00848>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained network, it might be best, to split this netw... | stack_v2_sparse_classes_36k_train_014335 | 8,177 | permissive | [
{
"docstring": "Parameters ---------- img_shape : tuple the shape of the images to translate from and to (including channels, excluding batch dimension) num_filts : int number of filters to use n_sample : int number of sampling layers per network shared_dim : int size of the shared dimension between generators ... | 2 | stack_v2_sparse_classes_30k_train_003597 | Implement the Python class `UNIT` described below.
Class description:
Class implementing Unsupervised Image-to-Image Translation Networks References ---------- `Paper <https://arxiv.org/abs/1703.00848>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained networ... | Implement the Python class `UNIT` described below.
Class description:
Class implementing Unsupervised Image-to-Image Translation Networks References ---------- `Paper <https://arxiv.org/abs/1703.00848>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained networ... | 1078f5030b8aac2bf022daf5fa14d66f74c3c893 | <|skeleton|>
class UNIT:
"""Class implementing Unsupervised Image-to-Image Translation Networks References ---------- `Paper <https://arxiv.org/abs/1703.00848>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained network, it might be best, to split this netw... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UNIT:
"""Class implementing Unsupervised Image-to-Image Translation Networks References ---------- `Paper <https://arxiv.org/abs/1703.00848>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained network, it might be best, to split this network into its ... | the_stack_v2_python_sparse | dlutils/models/gans/unit/unit.py | justusschock/dl-utils | train | 15 |
642a58bca1175a1a8d6fb1df852720568e4c8709 | [
"agent = Agent.query.filter_by(id=agent_id).first()\nif agent is None:\n return (jsonify(error='Agent %r not found' % agent_id), NOT_FOUND)\nout = []\nfor task in agent.tasks:\n task_dict = task.to_dict(unpack_relationships=False)\n task_dict['job'] = {'id': task.job.id, 'title': task.job.title, 'jobtype':... | <|body_start_0|>
agent = Agent.query.filter_by(id=agent_id).first()
if agent is None:
return (jsonify(error='Agent %r not found' % agent_id), NOT_FOUND)
out = []
for task in agent.tasks:
task_dict = task.to_dict(unpack_relationships=False)
task_dict['j... | TasksInAgentAPI | [
"BSD-3-Clause",
"Apache-2.0",
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TasksInAgentAPI:
def get(self, agent_id):
"""A ``GET`` to this endpoint will return a list of all tasks assigned to this agent. .. http:get:: /api/v1/agents/<str:agent_id>/tasks/ HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/agents/bbf55143-f2b1-4c15-9d41-139bd8057931/tasks/ HTTP... | stack_v2_sparse_classes_36k_train_014336 | 40,281 | permissive | [
{
"docstring": "A ``GET`` to this endpoint will return a list of all tasks assigned to this agent. .. http:get:: /api/v1/agents/<str:agent_id>/tasks/ HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/agents/bbf55143-f2b1-4c15-9d41-139bd8057931/tasks/ HTTP/1.1 Accept: application/json **Response** .. sourcec... | 2 | stack_v2_sparse_classes_30k_train_006542 | Implement the Python class `TasksInAgentAPI` described below.
Class description:
Implement the TasksInAgentAPI class.
Method signatures and docstrings:
- def get(self, agent_id): A ``GET`` to this endpoint will return a list of all tasks assigned to this agent. .. http:get:: /api/v1/agents/<str:agent_id>/tasks/ HTTP/... | Implement the Python class `TasksInAgentAPI` described below.
Class description:
Implement the TasksInAgentAPI class.
Method signatures and docstrings:
- def get(self, agent_id): A ``GET`` to this endpoint will return a list of all tasks assigned to this agent. .. http:get:: /api/v1/agents/<str:agent_id>/tasks/ HTTP/... | ea04bbcb807eb669415c569417b4b1b68e75d29d | <|skeleton|>
class TasksInAgentAPI:
def get(self, agent_id):
"""A ``GET`` to this endpoint will return a list of all tasks assigned to this agent. .. http:get:: /api/v1/agents/<str:agent_id>/tasks/ HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/agents/bbf55143-f2b1-4c15-9d41-139bd8057931/tasks/ HTTP... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TasksInAgentAPI:
def get(self, agent_id):
"""A ``GET`` to this endpoint will return a list of all tasks assigned to this agent. .. http:get:: /api/v1/agents/<str:agent_id>/tasks/ HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/agents/bbf55143-f2b1-4c15-9d41-139bd8057931/tasks/ HTTP/1.1 Accept: a... | the_stack_v2_python_sparse | pyfarm/master/api/agents.py | pyfarm/pyfarm-master | train | 2 | |
255af835c212721b7b9215d58b7305291fbb1c6b | [
"self.bars = bars\nself.symbol_list = self.bars.symbol_list\nself.events = events\nself.approvals_csv_dir = approvals_csv_dir\nself.approvals_data = pd.read_csv(approvals_csv_dir)\nself.approvals_data['catalyst_date'] = pd.to_datetime(self.approvals_data['catalyst_date'])\nself.bought = self._calculate_initial_boug... | <|body_start_0|>
self.bars = bars
self.symbol_list = self.bars.symbol_list
self.events = events
self.approvals_csv_dir = approvals_csv_dir
self.approvals_data = pd.read_csv(approvals_csv_dir)
self.approvals_data['catalyst_date'] = pd.to_datetime(self.approvals_data['catal... | Performs a biotech approval strategy where... PUT STUFF HERE | BiotechApprovalStrategy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BiotechApprovalStrategy:
"""Performs a biotech approval strategy where... PUT STUFF HERE"""
def __init__(self, bars, events, approvals_csv_dir):
"""Initializes the Biotech approval strategy Parameters: bars - The DataHandler object that provides bar information events - The Event Que... | stack_v2_sparse_classes_36k_train_014337 | 4,941 | no_license | [
{
"docstring": "Initializes the Biotech approval strategy Parameters: bars - The DataHandler object that provides bar information events - The Event Queue object approvals_csv_dir - The path to the csv file that has the tickers and the approval dates",
"name": "__init__",
"signature": "def __init__(self... | 3 | stack_v2_sparse_classes_30k_train_010356 | Implement the Python class `BiotechApprovalStrategy` described below.
Class description:
Performs a biotech approval strategy where... PUT STUFF HERE
Method signatures and docstrings:
- def __init__(self, bars, events, approvals_csv_dir): Initializes the Biotech approval strategy Parameters: bars - The DataHandler ob... | Implement the Python class `BiotechApprovalStrategy` described below.
Class description:
Performs a biotech approval strategy where... PUT STUFF HERE
Method signatures and docstrings:
- def __init__(self, bars, events, approvals_csv_dir): Initializes the Biotech approval strategy Parameters: bars - The DataHandler ob... | 8fbaf833e03977fa8d0c6e073889ec75bee8f01b | <|skeleton|>
class BiotechApprovalStrategy:
"""Performs a biotech approval strategy where... PUT STUFF HERE"""
def __init__(self, bars, events, approvals_csv_dir):
"""Initializes the Biotech approval strategy Parameters: bars - The DataHandler object that provides bar information events - The Event Que... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BiotechApprovalStrategy:
"""Performs a biotech approval strategy where... PUT STUFF HERE"""
def __init__(self, bars, events, approvals_csv_dir):
"""Initializes the Biotech approval strategy Parameters: bars - The DataHandler object that provides bar information events - The Event Queue object app... | the_stack_v2_python_sparse | strategy_biotechapproval.py | jonathan-soll/quantstrat_backtester | train | 1 |
ceb4452c1d2962045cef531f5f74ea60a19c819d | [
"super(CustomBatchNormAutograd, self).__init__()\nself.n_neurons = n_neurons\nself.eps = eps\nself.params = nn.ParameterDict({'gamma': nn.Parameter(torch.ones(n_neurons)), 'beta': nn.Parameter(torch.zeros(n_neurons))})",
"_n_batch, n_neurons = input.shape\nassert n_neurons == self.n_neurons\nmean = input.mean(dim... | <|body_start_0|>
super(CustomBatchNormAutograd, self).__init__()
self.n_neurons = n_neurons
self.eps = eps
self.params = nn.ParameterDict({'gamma': nn.Parameter(torch.ones(n_neurons)), 'beta': nn.Parameter(torch.zeros(n_neurons))})
<|end_body_0|>
<|body_start_1|>
_n_batch, n_neu... | This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need to be implemented, it is dealt with by the automatic differentiation provided by PyTorch. | CustomBatchNormAutograd | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomBatchNormAutograd:
"""This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need to be implemented, it is dealt with by... | stack_v2_sparse_classes_36k_train_014338 | 7,737 | no_license | [
{
"docstring": "Initializes CustomBatchNormAutograd object. Args: n_neurons: int specifying the number of neurons eps: small float to be added to the variance for stability",
"name": "__init__",
"signature": "def __init__(self, n_neurons, eps=1e-05)"
},
{
"docstring": "Compute the batch normaliz... | 2 | stack_v2_sparse_classes_30k_train_020812 | Implement the Python class `CustomBatchNormAutograd` described below.
Class description:
This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need... | Implement the Python class `CustomBatchNormAutograd` described below.
Class description:
This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need... | b2cd0d67337b101f3e204e519625e1aaf3cea43b | <|skeleton|>
class CustomBatchNormAutograd:
"""This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need to be implemented, it is dealt with by... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomBatchNormAutograd:
"""This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need to be implemented, it is dealt with by the automati... | the_stack_v2_python_sparse | assignment_1/code/custom_batchnorm.py | Ivan-Yovchev/uvadlc_practicals_2019 | train | 0 |
4fef52fd4a8284eee32ba3cbbb312e12e1593df7 | [
"if not builder:\n raise ValueError('Instance builder is not specified')\nself._builder = builder",
"osh = self._builder.buildNoNameInstance(number, hostname, system)\nosh.setContainer(containerOsh)\nreturn osh",
"if not pdo:\n raise ValueError('Instance information is not specified')\nif not containerOsh... | <|body_start_0|>
if not builder:
raise ValueError('Instance builder is not specified')
self._builder = builder
<|end_body_0|>
<|body_start_1|>
osh = self._builder.buildNoNameInstance(number, hostname, system)
osh.setContainer(containerOsh)
return osh
<|end_body_1|>
... | InstanceReporter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanceReporter:
def __init__(self, builder):
"""@types: InstanceBuilder"""
<|body_0|>
def reportNoNameInst(self, number, hostname, system, containerOsh):
"""@types: str, str, System, osh -> osh"""
<|body_1|>
def reportInstance(self, pdo, containerOsh):... | stack_v2_sparse_classes_36k_train_014339 | 14,040 | no_license | [
{
"docstring": "@types: InstanceBuilder",
"name": "__init__",
"signature": "def __init__(self, builder)"
},
{
"docstring": "@types: str, str, System, osh -> osh",
"name": "reportNoNameInst",
"signature": "def reportNoNameInst(self, number, hostname, system, containerOsh)"
},
{
"d... | 3 | stack_v2_sparse_classes_30k_val_000638 | Implement the Python class `InstanceReporter` described below.
Class description:
Implement the InstanceReporter class.
Method signatures and docstrings:
- def __init__(self, builder): @types: InstanceBuilder
- def reportNoNameInst(self, number, hostname, system, containerOsh): @types: str, str, System, osh -> osh
- ... | Implement the Python class `InstanceReporter` described below.
Class description:
Implement the InstanceReporter class.
Method signatures and docstrings:
- def __init__(self, builder): @types: InstanceBuilder
- def reportNoNameInst(self, number, hostname, system, containerOsh): @types: str, str, System, osh -> osh
- ... | c431e809e8d0f82e1bca7e3429dd0245560b5680 | <|skeleton|>
class InstanceReporter:
def __init__(self, builder):
"""@types: InstanceBuilder"""
<|body_0|>
def reportNoNameInst(self, number, hostname, system, containerOsh):
"""@types: str, str, System, osh -> osh"""
<|body_1|>
def reportInstance(self, pdo, containerOsh):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstanceReporter:
def __init__(self, builder):
"""@types: InstanceBuilder"""
if not builder:
raise ValueError('Instance builder is not specified')
self._builder = builder
def reportNoNameInst(self, number, hostname, system, containerOsh):
"""@types: str, str, S... | the_stack_v2_python_sparse | reference/ucmdb/discovery/sap_abap.py | madmonkyang/cda-record | train | 0 | |
c9d23ccbbd241589058809c5c823b47d63d95db3 | [
"self.table_names = []\nself.accepted_tables = []\nself.basic_tables = []\nself.badge_tables = []\nself.type_tables = []\nself.custom_tables = []\nself.pokemonByNumber = {}\nself.pokemonByName = {}\nself.__build_pokemon_list__\nself.__verify_database__\nself.__delete_unused_tables__",
"for pokemon in BOT.schema['... | <|body_start_0|>
self.table_names = []
self.accepted_tables = []
self.basic_tables = []
self.badge_tables = []
self.type_tables = []
self.custom_tables = []
self.pokemonByNumber = {}
self.pokemonByName = {}
self.__build_pokemon_list__
self.... | Validates the database is created with the expected tables | Storage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Storage:
"""Validates the database is created with the expected tables"""
def __init__(self):
"""Initializes list to validate against"""
<|body_0|>
def __build_pokemon_list__(self):
"""Creates validation with the pokemon"""
<|body_1|>
def __verify_da... | stack_v2_sparse_classes_36k_train_014340 | 2,844 | permissive | [
{
"docstring": "Initializes list to validate against",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Creates validation with the pokemon",
"name": "__build_pokemon_list__",
"signature": "def __build_pokemon_list__(self)"
},
{
"docstring": "Creates any t... | 4 | stack_v2_sparse_classes_30k_train_012031 | Implement the Python class `Storage` described below.
Class description:
Validates the database is created with the expected tables
Method signatures and docstrings:
- def __init__(self): Initializes list to validate against
- def __build_pokemon_list__(self): Creates validation with the pokemon
- def __verify_databa... | Implement the Python class `Storage` described below.
Class description:
Validates the database is created with the expected tables
Method signatures and docstrings:
- def __init__(self): Initializes list to validate against
- def __build_pokemon_list__(self): Creates validation with the pokemon
- def __verify_databa... | b28775a348f400a98f54b6521ce57297ba538861 | <|skeleton|>
class Storage:
"""Validates the database is created with the expected tables"""
def __init__(self):
"""Initializes list to validate against"""
<|body_0|>
def __build_pokemon_list__(self):
"""Creates validation with the pokemon"""
<|body_1|>
def __verify_da... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Storage:
"""Validates the database is created with the expected tables"""
def __init__(self):
"""Initializes list to validate against"""
self.table_names = []
self.accepted_tables = []
self.basic_tables = []
self.badge_tables = []
self.type_tables = []
... | the_stack_v2_python_sparse | src/record_keeper/startup/storage.py | williamwissemann/record_keeper | train | 0 |
fb3af232f47e3a0c26bfb739b84c004280112591 | [
"self.start = start\nself.home = home\nrandom.seed(seed)\nself.left_limit = left_limit\nself.right_limit = right_limit",
"walker = BoundedWalker(self.start, self.home, self.left_limit, self.right_limit)\nwhile not walker.is_at_home():\n walker.move()\nreturn walker.steps"
] | <|body_start_0|>
self.start = start
self.home = home
random.seed(seed)
self.left_limit = left_limit
self.right_limit = right_limit
<|end_body_0|>
<|body_start_1|>
walker = BoundedWalker(self.start, self.home, self.left_limit, self.right_limit)
while not walker.is... | BoundedSimulation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BoundedSimulation:
def __init__(self, start, home, seed, left_limit, right_limit):
"""Initialise the simulation Arguments --------- start : int The walker's initial position home : int The walk ends when the walker reaches home seed : int Random generator seed left_limit : int The left b... | stack_v2_sparse_classes_36k_train_014341 | 2,633 | no_license | [
{
"docstring": "Initialise the simulation Arguments --------- start : int The walker's initial position home : int The walk ends when the walker reaches home seed : int Random generator seed left_limit : int The left boundary of walker movement right_limit : int The right boundary of walker movement",
"name... | 2 | stack_v2_sparse_classes_30k_train_000295 | Implement the Python class `BoundedSimulation` described below.
Class description:
Implement the BoundedSimulation class.
Method signatures and docstrings:
- def __init__(self, start, home, seed, left_limit, right_limit): Initialise the simulation Arguments --------- start : int The walker's initial position home : i... | Implement the Python class `BoundedSimulation` described below.
Class description:
Implement the BoundedSimulation class.
Method signatures and docstrings:
- def __init__(self, start, home, seed, left_limit, right_limit): Initialise the simulation Arguments --------- start : int The walker's initial position home : i... | 527f908422b559e6afc1ec025c04336d7a13828d | <|skeleton|>
class BoundedSimulation:
def __init__(self, start, home, seed, left_limit, right_limit):
"""Initialise the simulation Arguments --------- start : int The walker's initial position home : int The walk ends when the walker reaches home seed : int Random generator seed left_limit : int The left b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BoundedSimulation:
def __init__(self, start, home, seed, left_limit, right_limit):
"""Initialise the simulation Arguments --------- start : int The walker's initial position home : int The walk ends when the walker reaches home seed : int Random generator seed left_limit : int The left boundary of wal... | the_stack_v2_python_sparse | src/nicolai_munsterhjelm_ex/ex05/bounded_sim.py | Nicomunster/INF200-2019-Exercises | train | 0 | |
04cbe688ff1a5ebf5e8deb7e3e1e989715926f78 | [
"try:\n tinc = value.first()\nexcept AttributeError:\n tinc = value\nif tinc is None:\n return None\nreturn TincHostSerializer(tinc).to_native(tinc)",
"if data:\n tinc_host = TincHost(pubkey=data.get('pubkey'))\n tinc_host.full_clean(exclude=['content_type', 'object_id', 'name'])\n return [tinc_... | <|body_start_0|>
try:
tinc = value.first()
except AttributeError:
tinc = value
if tinc is None:
return None
return TincHostSerializer(tinc).to_native(tinc)
<|end_body_0|>
<|body_start_1|>
if data:
tinc_host = TincHost(pubkey=data.g... | TincHost writable serializer | TincHostRelatedField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TincHostRelatedField:
"""TincHost writable serializer"""
def to_native(self, value):
"""Convert to serialized fields"""
<|body_0|>
def from_native(self, data):
"""Return a list of tinc configuration objects"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_014342 | 2,992 | no_license | [
{
"docstring": "Convert to serialized fields",
"name": "to_native",
"signature": "def to_native(self, value)"
},
{
"docstring": "Return a list of tinc configuration objects",
"name": "from_native",
"signature": "def from_native(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009412 | Implement the Python class `TincHostRelatedField` described below.
Class description:
TincHost writable serializer
Method signatures and docstrings:
- def to_native(self, value): Convert to serialized fields
- def from_native(self, data): Return a list of tinc configuration objects | Implement the Python class `TincHostRelatedField` described below.
Class description:
TincHost writable serializer
Method signatures and docstrings:
- def to_native(self, value): Convert to serialized fields
- def from_native(self, data): Return a list of tinc configuration objects
<|skeleton|>
class TincHostRelated... | dd798dc9bd3321b17007ff131e7b1288a2cd3c36 | <|skeleton|>
class TincHostRelatedField:
"""TincHost writable serializer"""
def to_native(self, value):
"""Convert to serialized fields"""
<|body_0|>
def from_native(self, data):
"""Return a list of tinc configuration objects"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TincHostRelatedField:
"""TincHost writable serializer"""
def to_native(self, value):
"""Convert to serialized fields"""
try:
tinc = value.first()
except AttributeError:
tinc = value
if tinc is None:
return None
return TincHostSer... | the_stack_v2_python_sparse | controller/apps/tinc/serializers.py | m00dy/vct-controller | train | 2 |
9140d9f61f20b311ece85e8f4b5bb5cbf010c99c | [
"self.log_directory = log_directory\nself.ack_batch_size = ack_batch_size\nself._current_file_obj = None\nsuper(TopicLogger, self).__init__(*args, **kwargs)",
"for filename in filenames:\n filepath = os.path.join(self.log_directory, filename)\n with open(filepath, 'r') as file_obj:\n for line in file... | <|body_start_0|>
self.log_directory = log_directory
self.ack_batch_size = ack_batch_size
self._current_file_obj = None
super(TopicLogger, self).__init__(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
for filename in filenames:
filepath = os.path.join(self.log_direc... | writes pubsub request messages to disk | TopicLogger | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopicLogger:
"""writes pubsub request messages to disk"""
def __init__(self, log_directory, ack_batch_size=100, *args, **kwargs):
"""creates instance"""
<|body_0|>
def iter_pull_messages_from_log(self, filenames):
"""creates subscribe message objects from files i... | stack_v2_sparse_classes_36k_train_014343 | 10,989 | permissive | [
{
"docstring": "creates instance",
"name": "__init__",
"signature": "def __init__(self, log_directory, ack_batch_size=100, *args, **kwargs)"
},
{
"docstring": "creates subscribe message objects from files in log filenames is list of base filenames to read from",
"name": "iter_pull_messages_f... | 5 | stack_v2_sparse_classes_30k_train_020235 | Implement the Python class `TopicLogger` described below.
Class description:
writes pubsub request messages to disk
Method signatures and docstrings:
- def __init__(self, log_directory, ack_batch_size=100, *args, **kwargs): creates instance
- def iter_pull_messages_from_log(self, filenames): creates subscribe message... | Implement the Python class `TopicLogger` described below.
Class description:
writes pubsub request messages to disk
Method signatures and docstrings:
- def __init__(self, log_directory, ack_batch_size=100, *args, **kwargs): creates instance
- def iter_pull_messages_from_log(self, filenames): creates subscribe message... | d2deb42c25cf83816993015532194a5fc0c4146a | <|skeleton|>
class TopicLogger:
"""writes pubsub request messages to disk"""
def __init__(self, log_directory, ack_batch_size=100, *args, **kwargs):
"""creates instance"""
<|body_0|>
def iter_pull_messages_from_log(self, filenames):
"""creates subscribe message objects from files i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TopicLogger:
"""writes pubsub request messages to disk"""
def __init__(self, log_directory, ack_batch_size=100, *args, **kwargs):
"""creates instance"""
self.log_directory = log_directory
self.ack_batch_size = ack_batch_size
self._current_file_obj = None
super(Topi... | the_stack_v2_python_sparse | gcloud/datastores/pubsub.py | pantheon-systems/etl-framework | train | 2 |
b99068089f987ed177540500d348dd3fc61d08ed | [
"logging.info(f'Loading model {model_name} from master at {det_master}')\ncheckpoint = Determined(master=det_master).get_model(model_name).get_version()\nself.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\ntrial = checkpoint.load(map_location=self.device)\nself.model = trial.model\nlogging.i... | <|body_start_0|>
logging.info(f'Loading model {model_name} from master at {det_master}')
checkpoint = Determined(master=det_master).get_model(model_name).get_version()
self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
trial = checkpoint.load(map_location=self.dev... | Model template. You can load your model parameters in __init__ from a location accessible at runtime | MNISTModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MNISTModel:
"""Model template. You can load your model parameters in __init__ from a location accessible at runtime"""
def __init__(self, det_master=None, model_name=None):
"""Add any initialization parameters. These will be passed at runtime from the graph definition parameters defi... | stack_v2_sparse_classes_36k_train_014344 | 1,767 | permissive | [
{
"docstring": "Add any initialization parameters. These will be passed at runtime from the graph definition parameters defined in your seldondeployment kubernetes resource manifest.",
"name": "__init__",
"signature": "def __init__(self, det_master=None, model_name=None)"
},
{
"docstring": "Retu... | 2 | stack_v2_sparse_classes_30k_train_019201 | Implement the Python class `MNISTModel` described below.
Class description:
Model template. You can load your model parameters in __init__ from a location accessible at runtime
Method signatures and docstrings:
- def __init__(self, det_master=None, model_name=None): Add any initialization parameters. These will be pa... | Implement the Python class `MNISTModel` described below.
Class description:
Model template. You can load your model parameters in __init__ from a location accessible at runtime
Method signatures and docstrings:
- def __init__(self, det_master=None, model_name=None): Add any initialization parameters. These will be pa... | 735a0dbedbf5972aef48461359df22d66d6c6588 | <|skeleton|>
class MNISTModel:
"""Model template. You can load your model parameters in __init__ from a location accessible at runtime"""
def __init__(self, det_master=None, model_name=None):
"""Add any initialization parameters. These will be passed at runtime from the graph definition parameters defi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MNISTModel:
"""Model template. You can load your model parameters in __init__ from a location accessible at runtime"""
def __init__(self, det_master=None, model_name=None):
"""Add any initialization parameters. These will be passed at runtime from the graph definition parameters defined in your s... | the_stack_v2_python_sparse | kubeflow_pipelines/seldon/model/MNISTModel.py | LittlePrince2021/works-with-determined | train | 0 |
bccfe4ae034ae6553e56cf939a16ff87565aaf84 | [
"if 'Could not attack sample:' in sample:\n return AttackResult.FAILED\n_, dest = map_string.split(' --> ')\nif 'FAILED' in dest:\n return AttackResult.FAILED\nelif 'SKIPPED' in dest:\n return AttackResult.SKIPPED\nelse:\n return AttackResult.SUCCESS",
"if textattack_cls == 'ErrorAttackResult':\n r... | <|body_start_0|>
if 'Could not attack sample:' in sample:
return AttackResult.FAILED
_, dest = map_string.split(' --> ')
if 'FAILED' in dest:
return AttackResult.FAILED
elif 'SKIPPED' in dest:
return AttackResult.SKIPPED
else:
retur... | AttackResult | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttackResult:
def from_mapping_string(cls, map_string, sample):
"""Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [SKIPPED/FAILED]"""
<|body_0|>
def from_textattack_class(cls, textattack_cls):
"""... | stack_v2_sparse_classes_36k_train_014345 | 1,407 | no_license | [
{
"docstring": "Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [SKIPPED/FAILED]",
"name": "from_mapping_string",
"signature": "def from_mapping_string(cls, map_string, sample)"
},
{
"docstring": "Computes the attack result fr... | 2 | stack_v2_sparse_classes_30k_train_013606 | Implement the Python class `AttackResult` described below.
Class description:
Implement the AttackResult class.
Method signatures and docstrings:
- def from_mapping_string(cls, map_string, sample): Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [S... | Implement the Python class `AttackResult` described below.
Class description:
Implement the AttackResult class.
Method signatures and docstrings:
- def from_mapping_string(cls, map_string, sample): Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [S... | a0673613f489f355ddef37c89f0a635c89a500e9 | <|skeleton|>
class AttackResult:
def from_mapping_string(cls, map_string, sample):
"""Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [SKIPPED/FAILED]"""
<|body_0|>
def from_textattack_class(cls, textattack_cls):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttackResult:
def from_mapping_string(cls, map_string, sample):
"""Computes the attack result from a string in the formats LABEL, ..., LABEL --> LABEL, ..., LABEL LABEL, ..., LABEL --> [SKIPPED/FAILED]"""
if 'Could not attack sample:' in sample:
return AttackResult.FAILED
_... | the_stack_v2_python_sparse | experiments/attack_result.py | dumpmemory/SeqAttack | train | 0 | |
c1d61de8eae3b0b64386ce957dadc24817ca334c | [
"size = len(prices)\nif size <= 0:\n return 0\nminIdx = 0\nfor i in range(1, size):\n if prices[i] < prices[minIdx]:\n minIdx = i\nmaxPro = 0\nfor i in range(minIdx + 1, size):\n maxPro = max(maxPro, prices[i] - prices[minIdx])\nreturn maxPro",
"size = len(prices)\nif size <= 0:\n return 0\nmax... | <|body_start_0|>
size = len(prices)
if size <= 0:
return 0
minIdx = 0
for i in range(1, size):
if prices[i] < prices[minIdx]:
minIdx = i
maxPro = 0
for i in range(minIdx + 1, size):
maxPro = max(maxPro, prices[i] - price... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""直接解法：[2,4,1]不满足"""
<|body_0|>
def maxProfit1(self, prices: List[int]) -> int:
"""暴力解法：超时，遍历每一个数对，固定了买入时间 改变思路：上述前面2，4也符合但是没有计算，暴力，把每个数都当成最小值，然后计算和最大值的差别"""
<|body_1|>
def maxProfit2(self, prices... | stack_v2_sparse_classes_36k_train_014346 | 2,828 | permissive | [
{
"docstring": "直接解法：[2,4,1]不满足",
"name": "maxProfit",
"signature": "def maxProfit(self, prices: List[int]) -> int"
},
{
"docstring": "暴力解法：超时，遍历每一个数对，固定了买入时间 改变思路：上述前面2，4也符合但是没有计算，暴力，把每个数都当成最小值，然后计算和最大值的差别",
"name": "maxProfit1",
"signature": "def maxProfit1(self, prices: List[int]) -> ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 直接解法：[2,4,1]不满足
- def maxProfit1(self, prices: List[int]) -> int: 暴力解法：超时，遍历每一个数对，固定了买入时间 改变思路：上述前面2，4也符合但是没有计算，暴力，把每个数都当成最小值，然后计算和... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 直接解法：[2,4,1]不满足
- def maxProfit1(self, prices: List[int]) -> int: 暴力解法：超时，遍历每一个数对，固定了买入时间 改变思路：上述前面2，4也符合但是没有计算，暴力，把每个数都当成最小值，然后计算和... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""直接解法：[2,4,1]不满足"""
<|body_0|>
def maxProfit1(self, prices: List[int]) -> int:
"""暴力解法：超时，遍历每一个数对，固定了买入时间 改变思路：上述前面2，4也符合但是没有计算，暴力，把每个数都当成最小值，然后计算和最大值的差别"""
<|body_1|>
def maxProfit2(self, prices... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""直接解法：[2,4,1]不满足"""
size = len(prices)
if size <= 0:
return 0
minIdx = 0
for i in range(1, size):
if prices[i] < prices[minIdx]:
minIdx = i
maxPro = 0
for ... | the_stack_v2_python_sparse | lcof/63-gu-piao-de-zui-da-li-run-lcof.py | yuenliou/leetcode | train | 0 | |
30494a7b1a538396380a9897b4209b08a10edfaa | [
"try:\n ScfUser.objects.get(email=data)\nexcept:\n raise ParseError('User {} does not exist'.format(data))\nreturn data",
"newPassword = data.get('newPassword')\nif newPassword and newPassword != data.get('newPasswordConfirm'):\n raise ParseError('newPassword did not match newPasswordConfirm')\nreturn da... | <|body_start_0|>
try:
ScfUser.objects.get(email=data)
except:
raise ParseError('User {} does not exist'.format(data))
return data
<|end_body_0|>
<|body_start_1|>
newPassword = data.get('newPassword')
if newPassword and newPassword != data.get('newPassword... | User reset password serializer | UserPasswordResetSerializer | [
"Apache-2.0",
"GPL-3.0-only",
"BSD-3-Clause",
"AGPL-3.0-only",
"GPL-1.0-or-later",
"Python-2.0",
"BSD-2-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserPasswordResetSerializer:
"""User reset password serializer"""
def validate_email(self, data):
"""check email is exist or not"""
<|body_0|>
def validate(self, data):
"""validate password"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_36k_train_014347 | 4,134 | permissive | [
{
"docstring": "check email is exist or not",
"name": "validate_email",
"signature": "def validate_email(self, data)"
},
{
"docstring": "validate password",
"name": "validate",
"signature": "def validate(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006015 | Implement the Python class `UserPasswordResetSerializer` described below.
Class description:
User reset password serializer
Method signatures and docstrings:
- def validate_email(self, data): check email is exist or not
- def validate(self, data): validate password | Implement the Python class `UserPasswordResetSerializer` described below.
Class description:
User reset password serializer
Method signatures and docstrings:
- def validate_email(self, data): check email is exist or not
- def validate(self, data): validate password
<|skeleton|>
class UserPasswordResetSerializer:
... | 4df3f46e35eb8fcab796be27fc1cc7fa7ed561f3 | <|skeleton|>
class UserPasswordResetSerializer:
"""User reset password serializer"""
def validate_email(self, data):
"""check email is exist or not"""
<|body_0|>
def validate(self, data):
"""validate password"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserPasswordResetSerializer:
"""User reset password serializer"""
def validate_email(self, data):
"""check email is exist or not"""
try:
ScfUser.objects.get(email=data)
except:
raise ParseError('User {} does not exist'.format(data))
return data
... | the_stack_v2_python_sparse | SCRM/ums/serializers.py | aricent/secure-cloud-native-fabric | train | 2 |
06c0fcfbc7a04ef95670ddba3889f66c1b6c2c84 | [
"self.readservice = readservice\nif u_context:\n self.user_context = u_context\n self.username = u_context.user\n if u_context.context == u_context.ChoicesOfView.COMMON:\n self.use_user = None\n else:\n self.use_user = u_context.user",
"from bl.person import Person\nsource = self.readser... | <|body_start_0|>
self.readservice = readservice
if u_context:
self.user_context = u_context
self.username = u_context.user
if u_context.context == u_context.ChoicesOfView.COMMON:
self.use_user = None
else:
self.use_user = u_... | Public methods for accessing active database. Returns a PersonResult object | DbReader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DbReader:
"""Public methods for accessing active database. Returns a PersonResult object"""
def __init__(self, readservice, u_context=None):
"""Create a reader object with db driver and user context. - readservice Neo4jReadService or Neo4jWriteDriver"""
<|body_0|>
def ge... | stack_v2_sparse_classes_36k_train_014348 | 3,432 | no_license | [
{
"docstring": "Create a reader object with db driver and user context. - readservice Neo4jReadService or Neo4jWriteDriver",
"name": "__init__",
"signature": "def __init__(self, readservice, u_context=None)"
},
{
"docstring": "Read the source, repository and events etc referencing this source. R... | 2 | stack_v2_sparse_classes_30k_train_014248 | Implement the Python class `DbReader` described below.
Class description:
Public methods for accessing active database. Returns a PersonResult object
Method signatures and docstrings:
- def __init__(self, readservice, u_context=None): Create a reader object with db driver and user context. - readservice Neo4jReadServ... | Implement the Python class `DbReader` described below.
Class description:
Public methods for accessing active database. Returns a PersonResult object
Method signatures and docstrings:
- def __init__(self, readservice, u_context=None): Create a reader object with db driver and user context. - readservice Neo4jReadServ... | 0f8d6ba035e3cca8dc756531b7cc51029a549a4f | <|skeleton|>
class DbReader:
"""Public methods for accessing active database. Returns a PersonResult object"""
def __init__(self, readservice, u_context=None):
"""Create a reader object with db driver and user context. - readservice Neo4jReadService or Neo4jWriteDriver"""
<|body_0|>
def ge... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DbReader:
"""Public methods for accessing active database. Returns a PersonResult object"""
def __init__(self, readservice, u_context=None):
"""Create a reader object with db driver and user context. - readservice Neo4jReadService or Neo4jWriteDriver"""
self.readservice = readservice
... | the_stack_v2_python_sparse | pe/db_reader.py | kkujansuu/stk | train | 0 |
dd260005932a3e6e0390ea379d23d90165dd1aeb | [
"rs = ta.transforms.Resample()\nself.nsr = noise_lvl\nself.noises = []\nself.probs = []\nself.nsr_scalar = []\nself.reverber = ReverbEcho()\nnoise_dirs = os.listdir(noise_dir)\nnoise_dirs.sort()\nfor index, directory in enumerate(noise_dirs):\n directory = './noises/' + str(directory)\n print(directory)\n ... | <|body_start_0|>
rs = ta.transforms.Resample()
self.nsr = noise_lvl
self.noises = []
self.probs = []
self.nsr_scalar = []
self.reverber = ReverbEcho()
noise_dirs = os.listdir(noise_dir)
noise_dirs.sort()
for index, directory in enumerate(noise_dirs... | Noiser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Noiser:
def __init__(self, noise_dir, noise_lvl=0.4, probs=[], nsr_scalar=[]):
"""add noise to signal, where noise is randomly selected wav from noise_dir. noise_lvl = ratio of noise to signal (additive)"""
<|body_0|>
def add_noise(self, sig):
"""sig is expected to b... | stack_v2_sparse_classes_36k_train_014349 | 22,249 | no_license | [
{
"docstring": "add noise to signal, where noise is randomly selected wav from noise_dir. noise_lvl = ratio of noise to signal (additive)",
"name": "__init__",
"signature": "def __init__(self, noise_dir, noise_lvl=0.4, probs=[], nsr_scalar=[])"
},
{
"docstring": "sig is expected to be one-dimens... | 2 | stack_v2_sparse_classes_30k_train_013837 | Implement the Python class `Noiser` described below.
Class description:
Implement the Noiser class.
Method signatures and docstrings:
- def __init__(self, noise_dir, noise_lvl=0.4, probs=[], nsr_scalar=[]): add noise to signal, where noise is randomly selected wav from noise_dir. noise_lvl = ratio of noise to signal ... | Implement the Python class `Noiser` described below.
Class description:
Implement the Noiser class.
Method signatures and docstrings:
- def __init__(self, noise_dir, noise_lvl=0.4, probs=[], nsr_scalar=[]): add noise to signal, where noise is randomly selected wav from noise_dir. noise_lvl = ratio of noise to signal ... | 6b4567c0bc1325a36b0d08fdf0f4fdcf8d803909 | <|skeleton|>
class Noiser:
def __init__(self, noise_dir, noise_lvl=0.4, probs=[], nsr_scalar=[]):
"""add noise to signal, where noise is randomly selected wav from noise_dir. noise_lvl = ratio of noise to signal (additive)"""
<|body_0|>
def add_noise(self, sig):
"""sig is expected to b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Noiser:
def __init__(self, noise_dir, noise_lvl=0.4, probs=[], nsr_scalar=[]):
"""add noise to signal, where noise is randomly selected wav from noise_dir. noise_lvl = ratio of noise to signal (additive)"""
rs = ta.transforms.Resample()
self.nsr = noise_lvl
self.noises = []
... | the_stack_v2_python_sparse | real-time-python-app/app.py | ashwinahuja/chvoice | train | 1 | |
d7d635572e3004d7b7b925f8210a82fd016d9d15 | [
"super().__init__()\nself.setWindowTitle('Add brain regions')\nself.ui()\nself.main_window = main_window\nself.setStyleSheet(update_css(style, palette))\nself.timer = QtCore.QTimer(self)\nself.timer.setInterval(1500)\nself.timer.timeout.connect(self.close)\nself.timer.start()",
"self.setGeometry(self.left, self.t... | <|body_start_0|>
super().__init__()
self.setWindowTitle('Add brain regions')
self.ui()
self.main_window = main_window
self.setStyleSheet(update_css(style, palette))
self.timer = QtCore.QTimer(self)
self.timer.setInterval(1500)
self.timer.timeout.connect(se... | ScreenshotModal | [
"BSD-3-Clause",
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScreenshotModal:
def __init__(self, main_window, palette):
"""Creates a new window for user to input which regions to add to scene. Arguments: ---------- main_window: reference to the App's main window palette: main_window's palette, used to style widgets"""
<|body_0|>
def u... | stack_v2_sparse_classes_36k_train_014350 | 1,389 | permissive | [
{
"docstring": "Creates a new window for user to input which regions to add to scene. Arguments: ---------- main_window: reference to the App's main window palette: main_window's palette, used to style widgets",
"name": "__init__",
"signature": "def __init__(self, main_window, palette)"
},
{
"do... | 2 | null | Implement the Python class `ScreenshotModal` described below.
Class description:
Implement the ScreenshotModal class.
Method signatures and docstrings:
- def __init__(self, main_window, palette): Creates a new window for user to input which regions to add to scene. Arguments: ---------- main_window: reference to the ... | Implement the Python class `ScreenshotModal` described below.
Class description:
Implement the ScreenshotModal class.
Method signatures and docstrings:
- def __init__(self, main_window, palette): Creates a new window for user to input which regions to add to scene. Arguments: ---------- main_window: reference to the ... | a14ead80c1dbc75f20a145a49394dc467c4f7bf1 | <|skeleton|>
class ScreenshotModal:
def __init__(self, main_window, palette):
"""Creates a new window for user to input which regions to add to scene. Arguments: ---------- main_window: reference to the App's main window palette: main_window's palette, used to style widgets"""
<|body_0|>
def u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScreenshotModal:
def __init__(self, main_window, palette):
"""Creates a new window for user to input which regions to add to scene. Arguments: ---------- main_window: reference to the App's main window palette: main_window's palette, used to style widgets"""
super().__init__()
self.set... | the_stack_v2_python_sparse | brainrender/gui/widgets/screenshot_modal.py | brainglobe/brainrender | train | 345 | |
1b50cfca45dbede218987bf76d7966f12b05a7d3 | [
"self._fwdm.clear()\nself._invm.clear()\nself._sntl.nxt = self._sntl.prv = self._sntl",
"if not self:\n raise KeyError('mapping is empty')\nkey = next((reversed if last else iter)(self))\nval = self._pop(key)\nreturn (key, val)",
"node = self._fwdm[key]\nnode.prv.nxt = node.nxt\nnode.nxt.prv = node.prv\nsntl... | <|body_start_0|>
self._fwdm.clear()
self._invm.clear()
self._sntl.nxt = self._sntl.prv = self._sntl
<|end_body_0|>
<|body_start_1|>
if not self:
raise KeyError('mapping is empty')
key = next((reversed if last else iter)(self))
val = self._pop(key)
ret... | Mutable bidict type that maintains items in insertion order. | OrderedBidict | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderedBidict:
"""Mutable bidict type that maintains items in insertion order."""
def clear(self) -> None:
"""Remove all items."""
<|body_0|>
def popitem(self, last: bool=True) -> _t.Tuple[KT, VT]:
"""*x.popitem() → (k, v)* Remove and return the most recently add... | stack_v2_sparse_classes_36k_train_014351 | 3,409 | permissive | [
{
"docstring": "Remove all items.",
"name": "clear",
"signature": "def clear(self) -> None"
},
{
"docstring": "*x.popitem() → (k, v)* Remove and return the most recently added item as a (key, value) pair if *last* is True, else the least recently added item. :raises KeyError: if *x* is empty.",
... | 3 | null | Implement the Python class `OrderedBidict` described below.
Class description:
Mutable bidict type that maintains items in insertion order.
Method signatures and docstrings:
- def clear(self) -> None: Remove all items.
- def popitem(self, last: bool=True) -> _t.Tuple[KT, VT]: *x.popitem() → (k, v)* Remove and return ... | Implement the Python class `OrderedBidict` described below.
Class description:
Mutable bidict type that maintains items in insertion order.
Method signatures and docstrings:
- def clear(self) -> None: Remove all items.
- def popitem(self, last: bool=True) -> _t.Tuple[KT, VT]: *x.popitem() → (k, v)* Remove and return ... | 95b7a061eabd6f2b607fba79e007186030f02720 | <|skeleton|>
class OrderedBidict:
"""Mutable bidict type that maintains items in insertion order."""
def clear(self) -> None:
"""Remove all items."""
<|body_0|>
def popitem(self, last: bool=True) -> _t.Tuple[KT, VT]:
"""*x.popitem() → (k, v)* Remove and return the most recently add... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderedBidict:
"""Mutable bidict type that maintains items in insertion order."""
def clear(self) -> None:
"""Remove all items."""
self._fwdm.clear()
self._invm.clear()
self._sntl.nxt = self._sntl.prv = self._sntl
def popitem(self, last: bool=True) -> _t.Tuple[KT, VT]... | the_stack_v2_python_sparse | Ricardo_OS/Python_backend/venv/lib/python3.8/site-packages/bidict/_orderedbidict.py | icl-rocketry/Avionics | train | 9 |
da310b3991feb15ed362c955412aefb1f5b50f75 | [
"for treasury in self:\n if treasury.date_from:\n self.env['payment.treasury'].compute_payments(treasury.id, treasury.date_from)\nreturn True",
"for treasury in self:\n if treasury.date_from:\n self.env['sale.purchase.treasury'].compute_sale_purchase(treasury.id, treasury.date_from)\nreturn Tr... | <|body_start_0|>
for treasury in self:
if treasury.date_from:
self.env['payment.treasury'].compute_payments(treasury.id, treasury.date_from)
return True
<|end_body_0|>
<|body_start_1|>
for treasury in self:
if treasury.date_from:
self.env[... | Object for the treasury | treasury | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class treasury:
"""Object for the treasury"""
def compute_payment_list(self):
"""Fonction qui calcule les payments fait sur l'année sélectionnée"""
<|body_0|>
def compute_sale_purchase_list(self):
"""Fonction qui calcule le montant des ventes et achats en cours"""
... | stack_v2_sparse_classes_36k_train_014352 | 43,695 | no_license | [
{
"docstring": "Fonction qui calcule les payments fait sur l'année sélectionnée",
"name": "compute_payment_list",
"signature": "def compute_payment_list(self)"
},
{
"docstring": "Fonction qui calcule le montant des ventes et achats en cours",
"name": "compute_sale_purchase_list",
"signat... | 4 | null | Implement the Python class `treasury` described below.
Class description:
Object for the treasury
Method signatures and docstrings:
- def compute_payment_list(self): Fonction qui calcule les payments fait sur l'année sélectionnée
- def compute_sale_purchase_list(self): Fonction qui calcule le montant des ventes et ac... | Implement the Python class `treasury` described below.
Class description:
Object for the treasury
Method signatures and docstrings:
- def compute_payment_list(self): Fonction qui calcule les payments fait sur l'année sélectionnée
- def compute_sale_purchase_list(self): Fonction qui calcule le montant des ventes et ac... | eb394e1f79ba1995da2dcd81adfdd511c22caff9 | <|skeleton|>
class treasury:
"""Object for the treasury"""
def compute_payment_list(self):
"""Fonction qui calcule les payments fait sur l'année sélectionnée"""
<|body_0|>
def compute_sale_purchase_list(self):
"""Fonction qui calcule le montant des ventes et achats en cours"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class treasury:
"""Object for the treasury"""
def compute_payment_list(self):
"""Fonction qui calcule les payments fait sur l'année sélectionnée"""
for treasury in self:
if treasury.date_from:
self.env['payment.treasury'].compute_payments(treasury.id, treasury.date_f... | the_stack_v2_python_sparse | OpenPROD/openprod-addons/control_management/treasury.py | kazacube-mziouadi/ceci | train | 0 |
7b7924948f0443af3feaeb9bfc275d5664c8d0b5 | [
"def bfs(depth, start, value_list):\n res.append(value_list)\n if depth == len(nums):\n return\n for i in range(start, len(nums)):\n bfs(depth + 1, i + 1, value_list + [nums[i]])\nres = []\nbfs(0, 0, [])\nreturn res",
"print('nums', nums)\nif len(nums) <= 1:\n return [nums]\nans = []\nfo... | <|body_start_0|>
def bfs(depth, start, value_list):
res.append(value_list)
if depth == len(nums):
return
for i in range(start, len(nums)):
bfs(depth + 1, i + 1, value_list + [nums[i]])
res = []
bfs(0, 0, [])
return res
<... | 所有的子集和排列 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""所有的子集和排列"""
def subsets(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def permute(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def bfs(de... | stack_v2_sparse_classes_36k_train_014353 | 1,108 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "subsets",
"signature": "def subsets(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "permute",
"signature": "def permute(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
所有的子集和排列
Method signatures and docstrings:
- def subsets(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def permute(self, nums): :type nums: List[int] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
所有的子集和排列
Method signatures and docstrings:
- def subsets(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def permute(self, nums): :type nums: List[int] :rtype: List[List[int]]
<|skeleton|>
class Solution:
"""所有的子集和排列"""
d... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
"""所有的子集和排列"""
def subsets(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def permute(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:
"""所有的子集和排列"""
def subsets(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
def bfs(depth, start, value_list):
res.append(value_list)
if depth == len(nums):
return
for i in range(start, len(nums)):
... | the_stack_v2_python_sparse | subsets.py | NeilWangziyu/Leetcode_py | train | 2 |
468bae5ec28104a9163c2753881fc5d728ffdfc2 | [
"featuregroups, training_datasets, features_to_featuregroups, featurestore, settings, storage_connectors, online_featurestore_connector = self._parse_featurestore_metadata(metadata_json)\nself.featuregroups = featuregroups\nself.training_datasets = training_datasets\nself.features_to_featuregroups = features_to_fea... | <|body_start_0|>
featuregroups, training_datasets, features_to_featuregroups, featurestore, settings, storage_connectors, online_featurestore_connector = self._parse_featurestore_metadata(metadata_json)
self.featuregroups = featuregroups
self.training_datasets = training_datasets
self.fe... | Represents feature store metadata. This metadata is used by the feature store client to determine how to fetch and push features from/to the feature store | FeaturestoreMetadata | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeaturestoreMetadata:
"""Represents feature store metadata. This metadata is used by the feature store client to determine how to fetch and push features from/to the feature store"""
def __init__(self, metadata_json):
"""Initialize the featurestore metadata from JSON payload Args: :m... | stack_v2_sparse_classes_36k_train_014354 | 5,002 | permissive | [
{
"docstring": "Initialize the featurestore metadata from JSON payload Args: :metadata_json: JSON metadata about the featurestore returned from Hopsworks REST API",
"name": "__init__",
"signature": "def __init__(self, metadata_json)"
},
{
"docstring": "Parses the featurestore metadata from the R... | 2 | stack_v2_sparse_classes_30k_train_017684 | Implement the Python class `FeaturestoreMetadata` described below.
Class description:
Represents feature store metadata. This metadata is used by the feature store client to determine how to fetch and push features from/to the feature store
Method signatures and docstrings:
- def __init__(self, metadata_json): Initia... | Implement the Python class `FeaturestoreMetadata` described below.
Class description:
Represents feature store metadata. This metadata is used by the feature store client to determine how to fetch and push features from/to the feature store
Method signatures and docstrings:
- def __init__(self, metadata_json): Initia... | cf0f85a774663cb9324fa6ff561070bbfc8f126d | <|skeleton|>
class FeaturestoreMetadata:
"""Represents feature store metadata. This metadata is used by the feature store client to determine how to fetch and push features from/to the feature store"""
def __init__(self, metadata_json):
"""Initialize the featurestore metadata from JSON payload Args: :m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeaturestoreMetadata:
"""Represents feature store metadata. This metadata is used by the feature store client to determine how to fetch and push features from/to the feature store"""
def __init__(self, metadata_json):
"""Initialize the featurestore metadata from JSON payload Args: :metadata_json:... | the_stack_v2_python_sparse | hops/featurestore_impl/dao/common/featurestore_metadata.py | logicalclocks/hopsworks-cloud-sdk | train | 1 |
83453fed0c0ce8f86fc7bef9d46dca2095f24657 | [
"application_id = self.application.id\nassert _assert__application_id(application_id)\ndatas = await self.http.application_role_connection_metadata_get_all(application_id)\nreturn [ApplicationRoleConnectionMetadata.from_data(data) for data in datas]",
"application_id = self.application.id\nassert _assert__applica... | <|body_start_0|>
application_id = self.application.id
assert _assert__application_id(application_id)
datas = await self.http.application_role_connection_metadata_get_all(application_id)
return [ApplicationRoleConnectionMetadata.from_data(data) for data in datas]
<|end_body_0|>
<|body_st... | ClientCompoundApplicationRoleConnectionEndpoints | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClientCompoundApplicationRoleConnectionEndpoints:
async def application_role_connection_metadata_get_all(self):
"""Requests all the role connection metadatas of the client's application. Returns ------- application_role_connection_metadatas : `list` of `ApplicationRoleConnectionMetadata`... | stack_v2_sparse_classes_36k_train_014355 | 2,417 | permissive | [
{
"docstring": "Requests all the role connection metadatas of the client's application. Returns ------- application_role_connection_metadatas : `list` of `ApplicationRoleConnectionMetadata` Raises ------ ConnectionError No internet connection. DiscordException If any exception was received from the Discord API.... | 2 | null | Implement the Python class `ClientCompoundApplicationRoleConnectionEndpoints` described below.
Class description:
Implement the ClientCompoundApplicationRoleConnectionEndpoints class.
Method signatures and docstrings:
- async def application_role_connection_metadata_get_all(self): Requests all the role connection met... | Implement the Python class `ClientCompoundApplicationRoleConnectionEndpoints` described below.
Class description:
Implement the ClientCompoundApplicationRoleConnectionEndpoints class.
Method signatures and docstrings:
- async def application_role_connection_metadata_get_all(self): Requests all the role connection met... | 53f24fdb38459dc5a4fd04f11bdbfee8295b76a4 | <|skeleton|>
class ClientCompoundApplicationRoleConnectionEndpoints:
async def application_role_connection_metadata_get_all(self):
"""Requests all the role connection metadatas of the client's application. Returns ------- application_role_connection_metadatas : `list` of `ApplicationRoleConnectionMetadata`... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClientCompoundApplicationRoleConnectionEndpoints:
async def application_role_connection_metadata_get_all(self):
"""Requests all the role connection metadatas of the client's application. Returns ------- application_role_connection_metadatas : `list` of `ApplicationRoleConnectionMetadata` Raises ------... | the_stack_v2_python_sparse | hata/discord/client/compounds/application_role_connection.py | HuyaneMatsu/hata | train | 3 | |
8c6ae71451ac45506c7377355a4c0fffa888944f | [
"self.head = LinkNode(0)\nself.tail = self.head\nself.length = 0",
"if index < 0 or index >= self.length:\n return -1\nnode = self.head.next\nfor i in range(index):\n node = node.next\nreturn node.val",
"node = LinkNode(val)\nnode.next = self.head.next\nself.head.next = node\nself.length = self.length + 1... | <|body_start_0|>
self.head = LinkNode(0)
self.tail = self.head
self.length = 0
<|end_body_0|>
<|body_start_1|>
if index < 0 or index >= self.length:
return -1
node = self.head.next
for i in range(index):
node = node.next
return node.val
<|... | MyLinkedList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -1."""
<|body_1|>
def addAtHead(self, val:... | stack_v2_sparse_classes_36k_train_014356 | 2,897 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Get the value of the index-th node in the linked list. If the index is invalid, return -1.",
"name": "get",
"signature": "def get(self, index: int) -> int"
},... | 6 | null | Implement the Python class `MyLinkedList` described below.
Class description:
Implement the MyLinkedList class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def get(self, index: int) -> int: Get the value of the index-th node in the linked list. If the index is invali... | Implement the Python class `MyLinkedList` described below.
Class description:
Implement the MyLinkedList class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def get(self, index: int) -> int: Get the value of the index-th node in the linked list. If the index is invali... | 3b13a02f9c8273f9794a57b948d2655792707f37 | <|skeleton|>
class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -1."""
<|body_1|>
def addAtHead(self, val:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
self.head = LinkNode(0)
self.tail = self.head
self.length = 0
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -1... | the_stack_v2_python_sparse | linklist/myLinkedList.py | gsy/leetcode | train | 1 | |
9c82e85aef149e48556d92afbf473b7c33b72592 | [
"errors: dict[str, str] = {}\nhost: str = data[CONF_HOST]\nport: int = data[CONF_PORT]\nusername: str = data[CONF_USERNAME]\npassword: str = data[CONF_PASSWORD]\nverify_ssl: bool = data[CONF_VERIFY_SSL]\nuptime_robot_api = UptimeKuma(async_get_clientsession(self.hass), f'{host}:{port}', username, password, verify_s... | <|body_start_0|>
errors: dict[str, str] = {}
host: str = data[CONF_HOST]
port: int = data[CONF_PORT]
username: str = data[CONF_USERNAME]
password: str = data[CONF_PASSWORD]
verify_ssl: bool = data[CONF_VERIFY_SSL]
uptime_robot_api = UptimeKuma(async_get_clientsess... | Handle a config flow for Uptime Kuma. | ConfigFlow | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for Uptime Kuma."""
async def _validate_input(self, data: dict[str, Any]) -> tuple[dict[str, str], None]:
"""Validate the user input allows us to connect."""
<|body_0|>
async def async_step_user(self, user_input: dict[str, Any] | None=... | stack_v2_sparse_classes_36k_train_014357 | 2,760 | permissive | [
{
"docstring": "Validate the user input allows us to connect.",
"name": "_validate_input",
"signature": "async def _validate_input(self, data: dict[str, Any]) -> tuple[dict[str, str], None]"
},
{
"docstring": "Handle the initial step.",
"name": "async_step_user",
"signature": "async def ... | 2 | stack_v2_sparse_classes_30k_train_012771 | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for Uptime Kuma.
Method signatures and docstrings:
- async def _validate_input(self, data: dict[str, Any]) -> tuple[dict[str, str], None]: Validate the user input allows us to connect.
- async def async_step_user(self, us... | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for Uptime Kuma.
Method signatures and docstrings:
- async def _validate_input(self, data: dict[str, Any]) -> tuple[dict[str, str], None]: Validate the user input allows us to connect.
- async def async_step_user(self, us... | 8548d9999ddd54f13d6a307e013abcb8c897a74e | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for Uptime Kuma."""
async def _validate_input(self, data: dict[str, Any]) -> tuple[dict[str, str], None]:
"""Validate the user input allows us to connect."""
<|body_0|>
async def async_step_user(self, user_input: dict[str, Any] | None=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfigFlow:
"""Handle a config flow for Uptime Kuma."""
async def _validate_input(self, data: dict[str, Any]) -> tuple[dict[str, str], None]:
"""Validate the user input allows us to connect."""
errors: dict[str, str] = {}
host: str = data[CONF_HOST]
port: int = data[CONF_P... | the_stack_v2_python_sparse | custom_components/uptime_kuma/config_flow.py | bacco007/HomeAssistantConfig | train | 98 |
81ea3d1d961f8c3e9afd973b5778055e3b73dc77 | [
"util.validate_columns(df, self.marker_column)\nutil.validate_columns(df, self.orderby_columns)\nutil.validate_columns(df, self.groupby_columns)\nutil.validate_empty_df(df)",
"self._validate_input(df)\ndf_ordered = util.sort_values(df, self.orderby_columns, self.ascending)\ndf_grouped = util.groupby(df_ordered, s... | <|body_start_0|>
util.validate_columns(df, self.marker_column)
util.validate_columns(df, self.orderby_columns)
util.validate_columns(df, self.groupby_columns)
util.validate_empty_df(df)
<|end_body_0|>
<|body_start_1|>
self._validate_input(df)
df_ordered = util.sort_value... | Provides `transform` and `validate_input` methods common to more than one implementation of the pandas interval identification wrangler. The `transform` has several shared responsibilities. It sorts and groups the data before applying the `_transform` method which needs to be implemented by every wrangler subclassing t... | _BaseIntervalIdentifier | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _BaseIntervalIdentifier:
"""Provides `transform` and `validate_input` methods common to more than one implementation of the pandas interval identification wrangler. The `transform` has several shared responsibilities. It sorts and groups the data before applying the `_transform` method which need... | stack_v2_sparse_classes_36k_train_014358 | 13,674 | permissive | [
{
"docstring": "Checks input data frame in regard to column names and empty data. Parameters ---------- df: pd.DataFrame Dataframe to be validated.",
"name": "_validate_input",
"signature": "def _validate_input(self, df: pd.DataFrame)"
},
{
"docstring": "Extract interval ids from given dataframe... | 2 | stack_v2_sparse_classes_30k_val_000707 | Implement the Python class `_BaseIntervalIdentifier` described below.
Class description:
Provides `transform` and `validate_input` methods common to more than one implementation of the pandas interval identification wrangler. The `transform` has several shared responsibilities. It sorts and groups the data before appl... | Implement the Python class `_BaseIntervalIdentifier` described below.
Class description:
Provides `transform` and `validate_input` methods common to more than one implementation of the pandas interval identification wrangler. The `transform` has several shared responsibilities. It sorts and groups the data before appl... | 8561f5f267303e664487ae67095085fcea4308c9 | <|skeleton|>
class _BaseIntervalIdentifier:
"""Provides `transform` and `validate_input` methods common to more than one implementation of the pandas interval identification wrangler. The `transform` has several shared responsibilities. It sorts and groups the data before applying the `_transform` method which need... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _BaseIntervalIdentifier:
"""Provides `transform` and `validate_input` methods common to more than one implementation of the pandas interval identification wrangler. The `transform` has several shared responsibilities. It sorts and groups the data before applying the `_transform` method which needs to be imple... | the_stack_v2_python_sparse | src/pywrangler/pandas/wranglers/interval_identifier.py | mansenfranzen/pywrangler | train | 15 |
0a49a12b7aeef8bb51ffca1c6ad60c8a35ed2151 | [
"self.id: uuid.UUID = uuid.uuid4()\nself.state: 'State' = state\nself.name: str = name\nself._cities: Set['City'] = set()",
"self._cities.add(city)\nif reflexive:\n city.associate(self, reflexive=False)"
] | <|body_start_0|>
self.id: uuid.UUID = uuid.uuid4()
self.state: 'State' = state
self.name: str = name
self._cities: Set['City'] = set()
<|end_body_0|>
<|body_start_1|>
self._cities.add(city)
if reflexive:
city.associate(self, reflexive=False)
<|end_body_1|>
| A country. | County | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class County:
"""A country."""
def __init__(self, name: str, state: 'State'):
""":param name: the name of the state :param state: the state in which the county resides"""
<|body_0|>
def associate(self, city: 'City', reflexive: bool=True):
"""Associate this county with ... | stack_v2_sparse_classes_36k_train_014359 | 8,831 | permissive | [
{
"docstring": ":param name: the name of the state :param state: the state in which the county resides",
"name": "__init__",
"signature": "def __init__(self, name: str, state: 'State')"
},
{
"docstring": "Associate this county with a city. :param city: the city which which the county is associat... | 2 | stack_v2_sparse_classes_30k_train_015116 | Implement the Python class `County` described below.
Class description:
A country.
Method signatures and docstrings:
- def __init__(self, name: str, state: 'State'): :param name: the name of the state :param state: the state in which the county resides
- def associate(self, city: 'City', reflexive: bool=True): Associ... | Implement the Python class `County` described below.
Class description:
A country.
Method signatures and docstrings:
- def __init__(self, name: str, state: 'State'): :param name: the name of the state :param state: the state in which the county resides
- def associate(self, city: 'City', reflexive: bool=True): Associ... | f0750799eade79405e3f52e1a2a61dfd4e88dd4f | <|skeleton|>
class County:
"""A country."""
def __init__(self, name: str, state: 'State'):
""":param name: the name of the state :param state: the state in which the county resides"""
<|body_0|>
def associate(self, city: 'City', reflexive: bool=True):
"""Associate this county with ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class County:
"""A country."""
def __init__(self, name: str, state: 'State'):
""":param name: the name of the state :param state: the state in which the county resides"""
self.id: uuid.UUID = uuid.uuid4()
self.state: 'State' = state
self.name: str = name
self._cities: Se... | the_stack_v2_python_sparse | Python_lib/cliff/model.py | mndarren/Code-Lib | train | 8 |
28851718890d5678e2cccebb8a9d30ecdead9791 | [
"accts = []\nfor account in accounts:\n accts.append(str(account.user_id))\nreturn accts",
"locs = []\nfor location in locations:\n polygon = location.bbox\n extent = list(polygon.extent)\n locs.extend(extent)\nreturn locs",
"terms = []\nfor searchterm in searchterms:\n if searchterm.is_phrase():... | <|body_start_0|>
accts = []
for account in accounts:
accts.append(str(account.user_id))
return accts
<|end_body_0|>
<|body_start_1|>
locs = []
for location in locations:
polygon = location.bbox
extent = list(polygon.extent)
locs.ex... | Class for accessing the Twitter Streaming API. | PublicStreamsAPI | [
"MIT",
"LicenseRef-scancode-proprietary-license",
"GPL-3.0-only",
"LicenseRef-scancode-unknown-license-reference",
"GPL-1.0-or-later",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-other-copyleft"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublicStreamsAPI:
"""Class for accessing the Twitter Streaming API."""
def _format_followees_param(accounts):
"""Takes a list of Account objects and returns a list of user IDs, indicating the users whose Tweets should be delivered on the stream."""
<|body_0|>
def _format... | stack_v2_sparse_classes_36k_train_014360 | 10,023 | permissive | [
{
"docstring": "Takes a list of Account objects and returns a list of user IDs, indicating the users whose Tweets should be delivered on the stream.",
"name": "_format_followees_param",
"signature": "def _format_followees_param(accounts)"
},
{
"docstring": "Takes a list of Location objects and r... | 5 | null | Implement the Python class `PublicStreamsAPI` described below.
Class description:
Class for accessing the Twitter Streaming API.
Method signatures and docstrings:
- def _format_followees_param(accounts): Takes a list of Account objects and returns a list of user IDs, indicating the users whose Tweets should be delive... | Implement the Python class `PublicStreamsAPI` described below.
Class description:
Class for accessing the Twitter Streaming API.
Method signatures and docstrings:
- def _format_followees_param(accounts): Takes a list of Account objects and returns a list of user IDs, indicating the users whose Tweets should be delive... | a379a134c0c5af14df4ed2afa066c1626506b754 | <|skeleton|>
class PublicStreamsAPI:
"""Class for accessing the Twitter Streaming API."""
def _format_followees_param(accounts):
"""Takes a list of Account objects and returns a list of user IDs, indicating the users whose Tweets should be delivered on the stream."""
<|body_0|>
def _format... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PublicStreamsAPI:
"""Class for accessing the Twitter Streaming API."""
def _format_followees_param(accounts):
"""Takes a list of Account objects and returns a list of user IDs, indicating the users whose Tweets should be delivered on the stream."""
accts = []
for account in accoun... | the_stack_v2_python_sparse | Incident-Response/Tools/cyphon/cyphon/platforms/twitter/handlers.py | foss2cyber/Incident-Playbook | train | 1 |
3e05973f6ac5ea06f6720404166b62a28046930a | [
"left = []\nself.rt = 0\n\ndef dfs(root, pos, level):\n if not root:\n return\n if len(left) < level + 1:\n left.append(pos)\n self.rt = max(self.rt, pos - left[level] + 1)\n dfs(root.left, pos * 2 + 1, level + 1)\n dfs(root.right, pos * 2 + 2, level + 1)\ndfs(root, 0, 0)\nreturn self.r... | <|body_start_0|>
left = []
self.rt = 0
def dfs(root, pos, level):
if not root:
return
if len(left) < level + 1:
left.append(pos)
self.rt = max(self.rt, pos - left[level] + 1)
dfs(root.left, pos * 2 + 1, level + 1)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def widthOfBinaryTree_dfs(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def widthOfBinaryTree_bfs(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
left = []
self.rt =... | stack_v2_sparse_classes_36k_train_014361 | 1,553 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "widthOfBinaryTree_dfs",
"signature": "def widthOfBinaryTree_dfs(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "widthOfBinaryTree_bfs",
"signature": "def widthOfBinaryTree_bfs(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019186 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def widthOfBinaryTree_dfs(self, root): :type root: TreeNode :rtype: int
- def widthOfBinaryTree_bfs(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def widthOfBinaryTree_dfs(self, root): :type root: TreeNode :rtype: int
- def widthOfBinaryTree_bfs(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
... | 0e99f9a5226507706b3ee66fd04bae813755ef40 | <|skeleton|>
class Solution:
def widthOfBinaryTree_dfs(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def widthOfBinaryTree_bfs(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def widthOfBinaryTree_dfs(self, root):
""":type root: TreeNode :rtype: int"""
left = []
self.rt = 0
def dfs(root, pos, level):
if not root:
return
if len(left) < level + 1:
left.append(pos)
self.rt =... | the_stack_v2_python_sparse | medium/tree/test_662_Maximum_Width_of_Binary_Tree.py | wuxu1019/leetcode_sophia | train | 1 | |
2c0b573bef54e07444b9d2a19ef33f6860c54143 | [
"n_row = len(board)\nif n_row <= 2:\n return\nn_col = len(board[0])\nif n_col <= 2:\n return\nqueue = deque()\nfor i in [0, n_row - 1]:\n for j in range(n_col):\n if board[i][j] == 'O':\n queue.append((i, j))\nfor i in range(1, n_row - 1):\n for j in [0, n_col - 1]:\n if board[i... | <|body_start_0|>
n_row = len(board)
if n_row <= 2:
return
n_col = len(board[0])
if n_col <= 2:
return
queue = deque()
for i in [0, n_row - 1]:
for j in range(n_col):
if board[i][j] == 'O':
queue.appen... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def solve(self, board: List[List[str]]) -> None:
"""Do not return anything, modify board in-place instead."""
<|body_0|>
def solve2(self, board: List[List[str]]) -> None:
"""Do not return anything, modify board in-place instead."""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k_train_014362 | 3,118 | no_license | [
{
"docstring": "Do not return anything, modify board in-place instead.",
"name": "solve",
"signature": "def solve(self, board: List[List[str]]) -> None"
},
{
"docstring": "Do not return anything, modify board in-place instead.",
"name": "solve2",
"signature": "def solve2(self, board: Lis... | 2 | stack_v2_sparse_classes_30k_train_013655 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solve(self, board: List[List[str]]) -> None: Do not return anything, modify board in-place instead.
- def solve2(self, board: List[List[str]]) -> None: Do not return anything... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solve(self, board: List[List[str]]) -> None: Do not return anything, modify board in-place instead.
- def solve2(self, board: List[List[str]]) -> None: Do not return anything... | e52d24990122e07a976612dd9cea42fa1d778f60 | <|skeleton|>
class Solution:
def solve(self, board: List[List[str]]) -> None:
"""Do not return anything, modify board in-place instead."""
<|body_0|>
def solve2(self, board: List[List[str]]) -> None:
"""Do not return anything, modify board in-place instead."""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def solve(self, board: List[List[str]]) -> None:
"""Do not return anything, modify board in-place instead."""
n_row = len(board)
if n_row <= 2:
return
n_col = len(board[0])
if n_col <= 2:
return
queue = deque()
for i in ... | the_stack_v2_python_sparse | python/0130_surrounded_regions.py | forest-sky-sea/Leetcode-Problems | train | 1 | |
02cb5e2a47f634fb905fc7d9c62d4fee83368cfa | [
"super(Classifier, self).__init__()\nself.fc1 = blk.LinearReLU(in_dim=num_channels, out_dim=128)\nself.fc2 = blk.LinearReLU(in_dim=128, out_dim=64)\nself.fc3 = nn.Linear(in_features=64, out_features=2)",
"y = F.relu(self.fc1(x))\ny = F.relu(self.fc2(y))\ny = self.fc3(y)\nreturn y"
] | <|body_start_0|>
super(Classifier, self).__init__()
self.fc1 = blk.LinearReLU(in_dim=num_channels, out_dim=128)
self.fc2 = blk.LinearReLU(in_dim=128, out_dim=64)
self.fc3 = nn.Linear(in_features=64, out_features=2)
<|end_body_0|>
<|body_start_1|>
y = F.relu(self.fc1(x))
... | Classifier | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Classifier:
def __init__(self, num_channels: int):
"""represents the correlation and concatenation classifying heads. :param num_channels: feature dimension of the merged vector."""
<|body_0|>
def forward(self, x: torch.Tensor) -> torch.Tensor:
"""forward pass implem... | stack_v2_sparse_classes_36k_train_014363 | 965 | permissive | [
{
"docstring": "represents the correlation and concatenation classifying heads. :param num_channels: feature dimension of the merged vector.",
"name": "__init__",
"signature": "def __init__(self, num_channels: int)"
},
{
"docstring": "forward pass implementation. :param x: input tensor. :return:... | 2 | stack_v2_sparse_classes_30k_train_021347 | Implement the Python class `Classifier` described below.
Class description:
Implement the Classifier class.
Method signatures and docstrings:
- def __init__(self, num_channels: int): represents the correlation and concatenation classifying heads. :param num_channels: feature dimension of the merged vector.
- def forw... | Implement the Python class `Classifier` described below.
Class description:
Implement the Classifier class.
Method signatures and docstrings:
- def __init__(self, num_channels: int): represents the correlation and concatenation classifying heads. :param num_channels: feature dimension of the merged vector.
- def forw... | 583e6868864582f081f18689124e74e9ca169f28 | <|skeleton|>
class Classifier:
def __init__(self, num_channels: int):
"""represents the correlation and concatenation classifying heads. :param num_channels: feature dimension of the merged vector."""
<|body_0|>
def forward(self, x: torch.Tensor) -> torch.Tensor:
"""forward pass implem... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Classifier:
def __init__(self, num_channels: int):
"""represents the correlation and concatenation classifying heads. :param num_channels: feature dimension of the merged vector."""
super(Classifier, self).__init__()
self.fc1 = blk.LinearReLU(in_dim=num_channels, out_dim=128)
s... | the_stack_v2_python_sparse | models/classifier.py | beaupreda/domain-networks | train | 1 | |
888f8d30eafb54a3a3b15c30e988ee44c2ead35b | [
"self.config = {'inline_class': ['math', \"Inline math is SVG wrapped in a <span> tag, this option adds a class name to it - Default: 'math'\"], 'display_class': ['math', \"Display math is SVG wrapped in a <div> tag, this option adds a class name to it - Default: 'math'\"], 'smart_dollar': [True, \"Use mdx_math_svg... | <|body_start_0|>
self.config = {'inline_class': ['math', "Inline math is SVG wrapped in a <span> tag, this option adds a class name to it - Default: 'math'"], 'display_class': ['math', "Display math is SVG wrapped in a <div> tag, this option adds a class name to it - Default: 'math'"], 'smart_dollar': [True, "U... | Adds MathSvg extension to Markdown class. | MathSvgExtension | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MathSvgExtension:
"""Adds MathSvg extension to Markdown class."""
def __init__(self, *args, **kwargs):
"""Initialize."""
<|body_0|>
def extendMarkdown(self, md):
"""Extend the inline and block processor objects."""
<|body_1|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_36k_train_014364 | 22,334 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Extend the inline and block processor objects.",
"name": "extendMarkdown",
"signature": "def extendMarkdown(self, md)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000209 | Implement the Python class `MathSvgExtension` described below.
Class description:
Adds MathSvg extension to Markdown class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize.
- def extendMarkdown(self, md): Extend the inline and block processor objects. | Implement the Python class `MathSvgExtension` described below.
Class description:
Adds MathSvg extension to Markdown class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize.
- def extendMarkdown(self, md): Extend the inline and block processor objects.
<|skeleton|>
class MathSvgExt... | 45c862669d8d4e72c95f6b278819379a1c1e68d4 | <|skeleton|>
class MathSvgExtension:
"""Adds MathSvg extension to Markdown class."""
def __init__(self, *args, **kwargs):
"""Initialize."""
<|body_0|>
def extendMarkdown(self, md):
"""Extend the inline and block processor objects."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MathSvgExtension:
"""Adds MathSvg extension to Markdown class."""
def __init__(self, *args, **kwargs):
"""Initialize."""
self.config = {'inline_class': ['math', "Inline math is SVG wrapped in a <span> tag, this option adds a class name to it - Default: 'math'"], 'display_class': ['math', ... | the_stack_v2_python_sparse | pylbm_ui/widgets/mdx_math_svg.py | gouarin/pylbm_ui | train | 0 |
b4dc1fcdd1aad4db485cb445eabea1fd477eedfb | [
"input_spec = TensorSpec((10,), torch.float32)\nembedding = input_spec.ones(outer_dims=(1,))\nnet = OnehotCategoricalProjectionNetwork(input_size=input_spec.shape[0], mode=mode, action_spec=BoundedTensorSpec((1,), minimum=0, maximum=4), logits_init_output_factor=0)\ndist, _ = net(embedding)\nself.assertTrue(isinsta... | <|body_start_0|>
input_spec = TensorSpec((10,), torch.float32)
embedding = input_spec.ones(outer_dims=(1,))
net = OnehotCategoricalProjectionNetwork(input_size=input_spec.shape[0], mode=mode, action_spec=BoundedTensorSpec((1,), minimum=0, maximum=4), logits_init_output_factor=0)
dist, _ ... | TestOnehotCategoricalProjectionNetwork | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestOnehotCategoricalProjectionNetwork:
def test_onehot_categorical_uniform_projection_net(self, mode):
"""A zero-weight net generates uniform actions."""
<|body_0|>
def test_onehot_samples(self, mode):
"""Samples from the projection net are onehot vectors."""
... | stack_v2_sparse_classes_36k_train_014365 | 19,986 | permissive | [
{
"docstring": "A zero-weight net generates uniform actions.",
"name": "test_onehot_categorical_uniform_projection_net",
"signature": "def test_onehot_categorical_uniform_projection_net(self, mode)"
},
{
"docstring": "Samples from the projection net are onehot vectors.",
"name": "test_onehot... | 4 | stack_v2_sparse_classes_30k_train_004811 | Implement the Python class `TestOnehotCategoricalProjectionNetwork` described below.
Class description:
Implement the TestOnehotCategoricalProjectionNetwork class.
Method signatures and docstrings:
- def test_onehot_categorical_uniform_projection_net(self, mode): A zero-weight net generates uniform actions.
- def tes... | Implement the Python class `TestOnehotCategoricalProjectionNetwork` described below.
Class description:
Implement the TestOnehotCategoricalProjectionNetwork class.
Method signatures and docstrings:
- def test_onehot_categorical_uniform_projection_net(self, mode): A zero-weight net generates uniform actions.
- def tes... | b00ff2fa5e660de31020338ba340263183fbeaa4 | <|skeleton|>
class TestOnehotCategoricalProjectionNetwork:
def test_onehot_categorical_uniform_projection_net(self, mode):
"""A zero-weight net generates uniform actions."""
<|body_0|>
def test_onehot_samples(self, mode):
"""Samples from the projection net are onehot vectors."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestOnehotCategoricalProjectionNetwork:
def test_onehot_categorical_uniform_projection_net(self, mode):
"""A zero-weight net generates uniform actions."""
input_spec = TensorSpec((10,), torch.float32)
embedding = input_spec.ones(outer_dims=(1,))
net = OnehotCategoricalProjectio... | the_stack_v2_python_sparse | alf/networks/projection_networks_test.py | HorizonRobotics/alf | train | 288 | |
0231692cc20d662f02f1c475ae7d6f398306d9ae | [
"super().__init__()\nself.N = N\nself.h = h\nself.dm = dm\nself.embedding = tf.keras.layers.Embedding(input_dim=input_vocab, output_dim=dm)\nself.positional_encoding = positional_encoding(max_seq_len, self.dm)\nblocks = []\nfor i in range(N):\n blocks.append(EncoderBlock(dm, h, hidden, drop_rate))\nself.blocks =... | <|body_start_0|>
super().__init__()
self.N = N
self.h = h
self.dm = dm
self.embedding = tf.keras.layers.Embedding(input_dim=input_vocab, output_dim=dm)
self.positional_encoding = positional_encoding(max_seq_len, self.dm)
blocks = []
for i in range(N):
... | DecoderBlock class | Encoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
"""DecoderBlock class"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""Initializer. Args: dm: (int) the dimensionality of the model. h: (int) the number of heads. hidden: (int) the number of hidden units in the fully connected layer. drop_... | stack_v2_sparse_classes_36k_train_014366 | 13,062 | no_license | [
{
"docstring": "Initializer. Args: dm: (int) the dimensionality of the model. h: (int) the number of heads. hidden: (int) the number of hidden units in the fully connected layer. drop_rate: (float) the dropout rate.",
"name": "__init__",
"signature": "def __init__(self, N, dm, h, hidden, input_vocab, ma... | 2 | null | Implement the Python class `Encoder` described below.
Class description:
DecoderBlock class
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1): Initializer. Args: dm: (int) the dimensionality of the model. h: (int) the number of heads. hidden: (int) the n... | Implement the Python class `Encoder` described below.
Class description:
DecoderBlock class
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1): Initializer. Args: dm: (int) the dimensionality of the model. h: (int) the number of heads. hidden: (int) the n... | 75274394adb52d740f6cd4000cc00bbde44b9b72 | <|skeleton|>
class Encoder:
"""DecoderBlock class"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""Initializer. Args: dm: (int) the dimensionality of the model. h: (int) the number of heads. hidden: (int) the number of hidden units in the fully connected layer. drop_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Encoder:
"""DecoderBlock class"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""Initializer. Args: dm: (int) the dimensionality of the model. h: (int) the number of heads. hidden: (int) the number of hidden units in the fully connected layer. drop_rate: (float)... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/5-transformer.py | jdarangop/holbertonschool-machine_learning | train | 2 |
2dc192f442495bcb6f32d9f428ebcdeb503f565c | [
"super(YetiYaraCollector, self).__init__(state, name=name, critical=critical)\nself.rule_name_filter = ''\nself.api_key = ''\nself.api_root = ''",
"self.logger.info(f'Name filter: {rule_name_filter}')\nself.rule_name_filter = rule_name_filter or ''\nself.api_key = api_key\nself.api_root = api_root",
"self.logge... | <|body_start_0|>
super(YetiYaraCollector, self).__init__(state, name=name, critical=critical)
self.rule_name_filter = ''
self.api_key = ''
self.api_root = ''
<|end_body_0|>
<|body_start_1|>
self.logger.info(f'Name filter: {rule_name_filter}')
self.rule_name_filter = rule... | Collector of Yara rules from Yeti TBB instances. Yeti TBB is Apache 2.0 licensed. Stores them in container.YaraRule containers. Attributes: rule_name_filter: A string by which to filter Yara rule names api_key: The Yeti API key to use. api_root: The Yeti HTTP API root, e.g. http://localhost:8080/api/ | YetiYaraCollector | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class YetiYaraCollector:
"""Collector of Yara rules from Yeti TBB instances. Yeti TBB is Apache 2.0 licensed. Stores them in container.YaraRule containers. Attributes: rule_name_filter: A string by which to filter Yara rule names api_key: The Yeti API key to use. api_root: The Yeti HTTP API root, e.g. ... | stack_v2_sparse_classes_36k_train_014367 | 2,688 | permissive | [
{
"docstring": "Initializes a YaraCollector module.",
"name": "__init__",
"signature": "def __init__(self, state: DFTimewolfState, name: Optional[str]=None, critical: bool=False) -> None"
},
{
"docstring": "Sets up the YaraCollector module. Args: rule_name_filter: A string by which to filter Yar... | 3 | null | Implement the Python class `YetiYaraCollector` described below.
Class description:
Collector of Yara rules from Yeti TBB instances. Yeti TBB is Apache 2.0 licensed. Stores them in container.YaraRule containers. Attributes: rule_name_filter: A string by which to filter Yara rule names api_key: The Yeti API key to use. ... | Implement the Python class `YetiYaraCollector` described below.
Class description:
Collector of Yara rules from Yeti TBB instances. Yeti TBB is Apache 2.0 licensed. Stores them in container.YaraRule containers. Attributes: rule_name_filter: A string by which to filter Yara rule names api_key: The Yeti API key to use. ... | bcea85b1ce7a0feb2aa28b5be4fc6ae124e8ca3c | <|skeleton|>
class YetiYaraCollector:
"""Collector of Yara rules from Yeti TBB instances. Yeti TBB is Apache 2.0 licensed. Stores them in container.YaraRule containers. Attributes: rule_name_filter: A string by which to filter Yara rule names api_key: The Yeti API key to use. api_root: The Yeti HTTP API root, e.g. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class YetiYaraCollector:
"""Collector of Yara rules from Yeti TBB instances. Yeti TBB is Apache 2.0 licensed. Stores them in container.YaraRule containers. Attributes: rule_name_filter: A string by which to filter Yara rule names api_key: The Yeti API key to use. api_root: The Yeti HTTP API root, e.g. http://localh... | the_stack_v2_python_sparse | dftimewolf/lib/collectors/yara.py | log2timeline/dftimewolf | train | 248 |
3e02d2f87eefcadc2cf07da85cc4ebcb7c5c312c | [
"super().__init__(properties=properties, data=data, bounds=bounds, geometry=geometry, interior_ring=interior_ring, source=source, copy=copy, _use_data=_use_data)\nself._initialise_netcdf(source)\nself._initialise_original_filenames(source)",
"if _title is None:\n _title = 'Auxiliary coordinate: ' + self.identi... | <|body_start_0|>
super().__init__(properties=properties, data=data, bounds=bounds, geometry=geometry, interior_ring=interior_ring, source=source, copy=copy, _use_data=_use_data)
self._initialise_netcdf(source)
self._initialise_original_filenames(source)
<|end_body_0|>
<|body_start_1|>
i... | An auxiliary coordinate construct of the CF data model. An auxiliary coordinate construct provides information which locate the cells of the domain and which depend on a subset of the domain axis constructs. Auxiliary coordinate constructs have to be used, instead of dimension coordinate constructs, when a single domai... | AuxiliaryCoordinate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuxiliaryCoordinate:
"""An auxiliary coordinate construct of the CF data model. An auxiliary coordinate construct provides information which locate the cells of the domain and which depend on a subset of the domain axis constructs. Auxiliary coordinate constructs have to be used, instead of dimen... | stack_v2_sparse_classes_36k_train_014368 | 3,896 | permissive | [
{
"docstring": "**Initialisation** :Parameters: {{init properties: `dict`, optional}} *Parameter example:* ``properties={'standard_name': 'latitude'}`` {{init data: data_like, optional}} {{init bounds: `Bounds`, optional}} {{init geometry: `str`, optional}} {{init interior_ring: `InteriorRing`, optional}} {{ini... | 2 | null | Implement the Python class `AuxiliaryCoordinate` described below.
Class description:
An auxiliary coordinate construct of the CF data model. An auxiliary coordinate construct provides information which locate the cells of the domain and which depend on a subset of the domain axis constructs. Auxiliary coordinate const... | Implement the Python class `AuxiliaryCoordinate` described below.
Class description:
An auxiliary coordinate construct of the CF data model. An auxiliary coordinate construct provides information which locate the cells of the domain and which depend on a subset of the domain axis constructs. Auxiliary coordinate const... | 142accf27fbbc052473b4eee47daf0e81c88df3a | <|skeleton|>
class AuxiliaryCoordinate:
"""An auxiliary coordinate construct of the CF data model. An auxiliary coordinate construct provides information which locate the cells of the domain and which depend on a subset of the domain axis constructs. Auxiliary coordinate constructs have to be used, instead of dimen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuxiliaryCoordinate:
"""An auxiliary coordinate construct of the CF data model. An auxiliary coordinate construct provides information which locate the cells of the domain and which depend on a subset of the domain axis constructs. Auxiliary coordinate constructs have to be used, instead of dimension coordina... | the_stack_v2_python_sparse | cfdm/auxiliarycoordinate.py | NCAS-CMS/cfdm | train | 29 |
8e09b3c90ae813ea92a0fea935d9497c4608d498 | [
"super(MultiHeadedAttention, self).__init__()\nassert d_model % h == 0\nself.d_k = d_model // h\nself.h = h\nself.linears = clones(nn.Linear(d_model, d_model), 4)\nself.attn = None\nself.dropout = nn.Dropout(p=dropout)",
"if mask is not None:\n mask = mask.unsqueeze(1)\nn_batches = query.size(0)\nquery, key, v... | <|body_start_0|>
super(MultiHeadedAttention, self).__init__()
assert d_model % h == 0
self.d_k = d_model // h
self.h = h
self.linears = clones(nn.Linear(d_model, d_model), 4)
self.attn = None
self.dropout = nn.Dropout(p=dropout)
<|end_body_0|>
<|body_start_1|>
... | MultiHeadedAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""param h: number of heads param d_model: model dimension param dropout: dropout rate"""
<|body_0|>
def forward(self, query, key, value, mask=None):
"""Calculates multiheaded attention and then appli... | stack_v2_sparse_classes_36k_train_014369 | 11,359 | no_license | [
{
"docstring": "param h: number of heads param d_model: model dimension param dropout: dropout rate",
"name": "__init__",
"signature": "def __init__(self, h, d_model, dropout=0.1)"
},
{
"docstring": "Calculates multiheaded attention and then applies a linear transformation param query: query ten... | 2 | stack_v2_sparse_classes_30k_train_013489 | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Implement the MultiHeadedAttention class.
Method signatures and docstrings:
- def __init__(self, h, d_model, dropout=0.1): param h: number of heads param d_model: model dimension param dropout: dropout rate
- def forward(self, query... | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Implement the MultiHeadedAttention class.
Method signatures and docstrings:
- def __init__(self, h, d_model, dropout=0.1): param h: number of heads param d_model: model dimension param dropout: dropout rate
- def forward(self, query... | c0b2f83a7d4c0d5fa5effb7584e0e0acc6f877a0 | <|skeleton|>
class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""param h: number of heads param d_model: model dimension param dropout: dropout rate"""
<|body_0|>
def forward(self, query, key, value, mask=None):
"""Calculates multiheaded attention and then appli... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""param h: number of heads param d_model: model dimension param dropout: dropout rate"""
super(MultiHeadedAttention, self).__init__()
assert d_model % h == 0
self.d_k = d_model // h
self.h = h
s... | the_stack_v2_python_sparse | src/main/base_models/architectures/Transformer.py | iesl/institution_hierarchies | train | 3 | |
f1f2ab8a2dd361b8dd32ad5e25f9c3c0393a02d9 | [
"if not is_string(name):\n raise TypeError('Instance name must be a string')\nif properties is not None and (not isinstance(properties, dict)):\n raise TypeError('Instance properties must be a dictionary or None')\nname = name.strip()\nif not name:\n raise ValueError(\"Invalid instance name '{0}'\".format(... | <|body_start_0|>
if not is_string(name):
raise TypeError('Instance name must be a string')
if properties is not None and (not isinstance(properties, dict)):
raise TypeError('Instance properties must be a dictionary or None')
name = name.strip()
if not name:
... | Decorator that sets up a future instance of a component | Instantiate | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Instantiate:
"""Decorator that sets up a future instance of a component"""
def __init__(self, name, properties=None):
"""Sets up the decorator :param name: Instance name :param properties: Instance properties"""
<|body_0|>
def __call__(self, factory_class):
"""Se... | stack_v2_sparse_classes_36k_train_014370 | 41,418 | permissive | [
{
"docstring": "Sets up the decorator :param name: Instance name :param properties: Instance properties",
"name": "__init__",
"signature": "def __init__(self, name, properties=None)"
},
{
"docstring": "Sets up and registers the instances descriptions :param factory_class: The factory class to in... | 2 | stack_v2_sparse_classes_30k_train_001724 | Implement the Python class `Instantiate` described below.
Class description:
Decorator that sets up a future instance of a component
Method signatures and docstrings:
- def __init__(self, name, properties=None): Sets up the decorator :param name: Instance name :param properties: Instance properties
- def __call__(sel... | Implement the Python class `Instantiate` described below.
Class description:
Decorator that sets up a future instance of a component
Method signatures and docstrings:
- def __init__(self, name, properties=None): Sets up the decorator :param name: Instance name :param properties: Instance properties
- def __call__(sel... | 686556cdde20beba77ae202de9969be46feed5e2 | <|skeleton|>
class Instantiate:
"""Decorator that sets up a future instance of a component"""
def __init__(self, name, properties=None):
"""Sets up the decorator :param name: Instance name :param properties: Instance properties"""
<|body_0|>
def __call__(self, factory_class):
"""Se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Instantiate:
"""Decorator that sets up a future instance of a component"""
def __init__(self, name, properties=None):
"""Sets up the decorator :param name: Instance name :param properties: Instance properties"""
if not is_string(name):
raise TypeError('Instance name must be a ... | the_stack_v2_python_sparse | python/src/lib/python/pelix/ipopo/decorators.py | cohorte/cohorte-runtime | train | 3 |
5da4494b1b1818424d71ccbb1b66db0bb9dc17b7 | [
"for project_id, instances in resource_from_api.iteritems():\n for instance in instances:\n yield {'project_id': project_id, 'id': instance.get('id'), 'creation_timestamp': parser.format_timestamp(instance.get('creationTimestamp'), self.MYSQL_DATETIME_FORMAT), 'name': instance.get('name'), 'description': ... | <|body_start_0|>
for project_id, instances in resource_from_api.iteritems():
for instance in instances:
yield {'project_id': project_id, 'id': instance.get('id'), 'creation_timestamp': parser.format_timestamp(instance.get('creationTimestamp'), self.MYSQL_DATETIME_FORMAT), 'name': ins... | Load compute instances for all projects. | LoadInstancesPipeline | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoadInstancesPipeline:
"""Load compute instances for all projects."""
def _transform(self, resource_from_api):
"""Create an iterator of instances to load into database. Args: resource_from_api (dict): A dict of instances, keyed by project id, from GCP API. Yields: dict: Instance prop... | stack_v2_sparse_classes_36k_train_014371 | 4,162 | permissive | [
{
"docstring": "Create an iterator of instances to load into database. Args: resource_from_api (dict): A dict of instances, keyed by project id, from GCP API. Yields: dict: Instance properties.",
"name": "_transform",
"signature": "def _transform(self, resource_from_api)"
},
{
"docstring": "Retr... | 3 | stack_v2_sparse_classes_30k_train_002160 | Implement the Python class `LoadInstancesPipeline` described below.
Class description:
Load compute instances for all projects.
Method signatures and docstrings:
- def _transform(self, resource_from_api): Create an iterator of instances to load into database. Args: resource_from_api (dict): A dict of instances, keyed... | Implement the Python class `LoadInstancesPipeline` described below.
Class description:
Load compute instances for all projects.
Method signatures and docstrings:
- def _transform(self, resource_from_api): Create an iterator of instances to load into database. Args: resource_from_api (dict): A dict of instances, keyed... | a6a1aa7464cda2ad5948e3e8876eb8dded5e2514 | <|skeleton|>
class LoadInstancesPipeline:
"""Load compute instances for all projects."""
def _transform(self, resource_from_api):
"""Create an iterator of instances to load into database. Args: resource_from_api (dict): A dict of instances, keyed by project id, from GCP API. Yields: dict: Instance prop... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoadInstancesPipeline:
"""Load compute instances for all projects."""
def _transform(self, resource_from_api):
"""Create an iterator of instances to load into database. Args: resource_from_api (dict): A dict of instances, keyed by project id, from GCP API. Yields: dict: Instance properties."""
... | the_stack_v2_python_sparse | google/cloud/security/inventory/pipelines/load_instances_pipeline.py | shimizu19691210/forseti-security | train | 1 |
6ce8a912bf1d9ff03e395e3bba7cc8379c7a9491 | [
"self.__questions = Questions(data_file_path)\nself.__players = players\nself.__answers = list()",
"n_questions = len(self.__questions.get_questions())\nfor player in range(self.__players):\n print('\\nQuestions for player {}'.format(player + 1))\n print('----------------------\\n\\n')\n n_answered = lis... | <|body_start_0|>
self.__questions = Questions(data_file_path)
self.__players = players
self.__answers = list()
<|end_body_0|>
<|body_start_1|>
n_questions = len(self.__questions.get_questions())
for player in range(self.__players):
print('\nQuestions for player {}'.f... | Quiz class. | Quiz | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Quiz:
"""Quiz class."""
def __init__(self, players, data_file_path):
"""Constructor. :param players: Number of players. :param data_file_path: Text file to read the questions and answers from."""
<|body_0|>
def run(self):
"""Run a the quiz."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_014372 | 4,115 | no_license | [
{
"docstring": "Constructor. :param players: Number of players. :param data_file_path: Text file to read the questions and answers from.",
"name": "__init__",
"signature": "def __init__(self, players, data_file_path)"
},
{
"docstring": "Run a the quiz.",
"name": "run",
"signature": "def ... | 3 | null | Implement the Python class `Quiz` described below.
Class description:
Quiz class.
Method signatures and docstrings:
- def __init__(self, players, data_file_path): Constructor. :param players: Number of players. :param data_file_path: Text file to read the questions and answers from.
- def run(self): Run a the quiz.
-... | Implement the Python class `Quiz` described below.
Class description:
Quiz class.
Method signatures and docstrings:
- def __init__(self, players, data_file_path): Constructor. :param players: Number of players. :param data_file_path: Text file to read the questions and answers from.
- def run(self): Run a the quiz.
-... | 33bf532b397f21290d6f85631466d90964aab4ad | <|skeleton|>
class Quiz:
"""Quiz class."""
def __init__(self, players, data_file_path):
"""Constructor. :param players: Number of players. :param data_file_path: Text file to read the questions and answers from."""
<|body_0|>
def run(self):
"""Run a the quiz."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Quiz:
"""Quiz class."""
def __init__(self, players, data_file_path):
"""Constructor. :param players: Number of players. :param data_file_path: Text file to read the questions and answers from."""
self.__questions = Questions(data_file_path)
self.__players = players
self.__... | the_stack_v2_python_sparse | ass12/quiz.py | deadbok/eal_programming | train | 1 |
0fcbae6be239682fbbc1516b9c78a8536a6e68d5 | [
"self.W = np.random.randn(H, V)\nself.W /= np.sqrt(H)\nself.b = np.zeros(V)\nself.x = None",
"if W is not None and b is not None:\n self.W = W\n self.b = b\nN, T, H = x.shape\nV = self.b.shape[0]\nself.x = x\nreturn np.dot(x.reshape(N * T, H), self.W).reshape(N, T, V) + self.b",
"N, T, H = self.x.shape\nV... | <|body_start_0|>
self.W = np.random.randn(H, V)
self.W /= np.sqrt(H)
self.b = np.zeros(V)
self.x = None
<|end_body_0|>
<|body_start_1|>
if W is not None and b is not None:
self.W = W
self.b = b
N, T, H = x.shape
V = self.b.shape[0]
... | TemporalAffineLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemporalAffineLayer:
def __init__(self, H, V):
"""Args: H (int): Dimension of hidden state from LSTM cell. V (int): Number of words in the vocabulary."""
<|body_0|>
def forward(self, x, W=None, b=None):
"""Forward pass for temporarl affine layer. The input is a set o... | stack_v2_sparse_classes_36k_train_014373 | 2,707 | no_license | [
{
"docstring": "Args: H (int): Dimension of hidden state from LSTM cell. V (int): Number of words in the vocabulary.",
"name": "__init__",
"signature": "def __init__(self, H, V)"
},
{
"docstring": "Forward pass for temporarl affine layer. The input is a set of H-dimensional vectors arranged into... | 4 | stack_v2_sparse_classes_30k_train_006003 | Implement the Python class `TemporalAffineLayer` described below.
Class description:
Implement the TemporalAffineLayer class.
Method signatures and docstrings:
- def __init__(self, H, V): Args: H (int): Dimension of hidden state from LSTM cell. V (int): Number of words in the vocabulary.
- def forward(self, x, W=None... | Implement the Python class `TemporalAffineLayer` described below.
Class description:
Implement the TemporalAffineLayer class.
Method signatures and docstrings:
- def __init__(self, H, V): Args: H (int): Dimension of hidden state from LSTM cell. V (int): Number of words in the vocabulary.
- def forward(self, x, W=None... | 7da789ef34d5e5bcf9033cfbe0ff5df607b2437a | <|skeleton|>
class TemporalAffineLayer:
def __init__(self, H, V):
"""Args: H (int): Dimension of hidden state from LSTM cell. V (int): Number of words in the vocabulary."""
<|body_0|>
def forward(self, x, W=None, b=None):
"""Forward pass for temporarl affine layer. The input is a set o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TemporalAffineLayer:
def __init__(self, H, V):
"""Args: H (int): Dimension of hidden state from LSTM cell. V (int): Number of words in the vocabulary."""
self.W = np.random.randn(H, V)
self.W /= np.sqrt(H)
self.b = np.zeros(V)
self.x = None
def forward(self, x, W=N... | the_stack_v2_python_sparse | recurrent_neural_networks/rnn/temporal_affine_layer.py | calvinfeng/machine-learning-notebook | train | 38 | |
744d9780587aec75e5eec500a1dfc4f54ac8362e | [
"if isinstance(values, list):\n for value in values:\n self.append(value)\nelse:\n raise TypeError('Please package your item into a list!')",
"new_node = Node(value, None, None)\nif self.head is None:\n self.head = self.tail = new_node\nelse:\n new_node.prev = self.tail\n new_node.next = Non... | <|body_start_0|>
if isinstance(values, list):
for value in values:
self.append(value)
else:
raise TypeError('Please package your item into a list!')
<|end_body_0|>
<|body_start_1|>
new_node = Node(value, None, None)
if self.head is None:
... | Define a double pointered list. | DoublyLinkedList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoublyLinkedList:
"""Define a double pointered list."""
def __init__(self, values):
"""Accept a list of values and generate a chain of Nodes using those values."""
<|body_0|>
def append(self, value):
"""Append a value to the tail of the linked list."""
<|... | stack_v2_sparse_classes_36k_train_014374 | 3,676 | permissive | [
{
"docstring": "Accept a list of values and generate a chain of Nodes using those values.",
"name": "__init__",
"signature": "def __init__(self, values)"
},
{
"docstring": "Append a value to the tail of the linked list.",
"name": "append",
"signature": "def append(self, value)"
},
{
... | 6 | stack_v2_sparse_classes_30k_train_019535 | Implement the Python class `DoublyLinkedList` described below.
Class description:
Define a double pointered list.
Method signatures and docstrings:
- def __init__(self, values): Accept a list of values and generate a chain of Nodes using those values.
- def append(self, value): Append a value to the tail of the linke... | Implement the Python class `DoublyLinkedList` described below.
Class description:
Define a double pointered list.
Method signatures and docstrings:
- def __init__(self, values): Accept a list of values and generate a chain of Nodes using those values.
- def append(self, value): Append a value to the tail of the linke... | 35d7b3af8c6e745838d25e42be88c49382461c8a | <|skeleton|>
class DoublyLinkedList:
"""Define a double pointered list."""
def __init__(self, values):
"""Accept a list of values and generate a chain of Nodes using those values."""
<|body_0|>
def append(self, value):
"""Append a value to the tail of the linked list."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DoublyLinkedList:
"""Define a double pointered list."""
def __init__(self, values):
"""Accept a list of values and generate a chain of Nodes using those values."""
if isinstance(values, list):
for value in values:
self.append(value)
else:
ra... | the_stack_v2_python_sparse | src/dll.py | nadiabahrami/data-structures | train | 0 |
6d813bb102040147e9879520800106159d9225b8 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UserTrainingStatusInfo()",
"from .training_status import TrainingStatus\nfrom .training_status import TrainingStatus\nfields: Dict[str, Callable[[Any], None]] = {'assignedDateTime': lambda n: setattr(self, 'assigned_date_time', n.get_d... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UserTrainingStatusInfo()
<|end_body_0|>
<|body_start_1|>
from .training_status import TrainingStatus
from .training_status import TrainingStatus
fields: Dict[str, Callable[[Any],... | UserTrainingStatusInfo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserTrainingStatusInfo:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserTrainingStatusInfo:
"""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 ... | stack_v2_sparse_classes_36k_train_014375 | 3,696 | 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: UserTrainingStatusInfo",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrimina... | 3 | null | Implement the Python class `UserTrainingStatusInfo` described below.
Class description:
Implement the UserTrainingStatusInfo class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserTrainingStatusInfo: Creates a new instance of the appropriate class b... | Implement the Python class `UserTrainingStatusInfo` described below.
Class description:
Implement the UserTrainingStatusInfo class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserTrainingStatusInfo: Creates a new instance of the appropriate class b... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UserTrainingStatusInfo:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserTrainingStatusInfo:
"""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 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserTrainingStatusInfo:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserTrainingStatusInfo:
"""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 Ret... | the_stack_v2_python_sparse | msgraph/generated/models/user_training_status_info.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
72edcdf99f2acf4130917b530d7be7a117ffe091 | [
"self.inputFile = inputFile\nself.logLevel = logLevel\nlogging.basicConfig(level=self.logLevel)\nself.dConditions = {}\ntry:\n self.filehandle = open(self.inputFile, 'r')\nexcept Exception as e:\n logging.error(e)\n sys.exit(1)",
"for idx, line in enumerate(self.filehandle):\n currentLine = line.strip... | <|body_start_0|>
self.inputFile = inputFile
self.logLevel = logLevel
logging.basicConfig(level=self.logLevel)
self.dConditions = {}
try:
self.filehandle = open(self.inputFile, 'r')
except Exception as e:
logging.error(e)
sys.exit(1)
<|e... | ExpNucFileParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExpNucFileParser:
def __init__(self, inputFile='', logLevel='ERROR'):
"""Constructor"""
<|body_0|>
def parse(self):
"""parse file"""
<|body_1|>
def getlLabels(self):
"""return list of labels"""
<|body_2|>
def getlConditions(self):
... | stack_v2_sparse_classes_36k_train_014376 | 2,378 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, inputFile='', logLevel='ERROR')"
},
{
"docstring": "parse file",
"name": "parse",
"signature": "def parse(self)"
},
{
"docstring": "return list of labels",
"name": "getlLabels",
"signature"... | 6 | stack_v2_sparse_classes_30k_train_004330 | Implement the Python class `ExpNucFileParser` described below.
Class description:
Implement the ExpNucFileParser class.
Method signatures and docstrings:
- def __init__(self, inputFile='', logLevel='ERROR'): Constructor
- def parse(self): parse file
- def getlLabels(self): return list of labels
- def getlConditions(s... | Implement the Python class `ExpNucFileParser` described below.
Class description:
Implement the ExpNucFileParser class.
Method signatures and docstrings:
- def __init__(self, inputFile='', logLevel='ERROR'): Constructor
- def parse(self): parse file
- def getlLabels(self): return list of labels
- def getlConditions(s... | ee0be5513d6a429b07b057d0ddd3fd617a1073d7 | <|skeleton|>
class ExpNucFileParser:
def __init__(self, inputFile='', logLevel='ERROR'):
"""Constructor"""
<|body_0|>
def parse(self):
"""parse file"""
<|body_1|>
def getlLabels(self):
"""return list of labels"""
<|body_2|>
def getlConditions(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExpNucFileParser:
def __init__(self, inputFile='', logLevel='ERROR'):
"""Constructor"""
self.inputFile = inputFile
self.logLevel = logLevel
logging.basicConfig(level=self.logLevel)
self.dConditions = {}
try:
self.filehandle = open(self.inputFile, 'r'... | the_stack_v2_python_sparse | MSTS/Parser/ExpNucFileParser.py | nlapalu/MSTS | train | 0 | |
6eeb2d6be78771a9465d6d2e7b9be50ccaa4674f | [
"self.num_locations = num_locations\nself.coverages_per_location = coverages_per_location\nself.num_areaperils = num_areaperils\nself.num_vulnerabilities = num_vulnerabilities\nself.dtypes = OrderedDict([('item_id', 'i'), ('coverage_id', 'i'), ('areaperil_id', 'i'), ('vulnerability_id', 'i'), ('group_id', 'i')])\ns... | <|body_start_0|>
self.num_locations = num_locations
self.coverages_per_location = coverages_per_location
self.num_areaperils = num_areaperils
self.num_vulnerabilities = num_vulnerabilities
self.dtypes = OrderedDict([('item_id', 'i'), ('coverage_id', 'i'), ('areaperil_id', 'i'), (... | Generate data for Items dummy model Oasis file. This file lists the exposure items for which ground up loss will be sampled. Attributes: generate_data: Generate Items dummy model Oasis file data. | ItemsFile | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItemsFile:
"""Generate data for Items dummy model Oasis file. This file lists the exposure items for which ground up loss will be sampled. Attributes: generate_data: Generate Items dummy model Oasis file data."""
def __init__(self, num_locations, coverages_per_location, num_areaperils, num_v... | stack_v2_sparse_classes_36k_train_014377 | 39,722 | permissive | [
{
"docstring": "Initialise Items file class. Args: num_locations (int): number of locations. coverages_per_location (int): number of coverage types per location. num_areaperils (int): number of areaperils. num_vulnerabilities (int): number of vulnerabilities. random_seed (float): random seed for random number g... | 2 | null | Implement the Python class `ItemsFile` described below.
Class description:
Generate data for Items dummy model Oasis file. This file lists the exposure items for which ground up loss will be sampled. Attributes: generate_data: Generate Items dummy model Oasis file data.
Method signatures and docstrings:
- def __init_... | Implement the Python class `ItemsFile` described below.
Class description:
Generate data for Items dummy model Oasis file. This file lists the exposure items for which ground up loss will be sampled. Attributes: generate_data: Generate Items dummy model Oasis file data.
Method signatures and docstrings:
- def __init_... | 23e704c335629ccd010969b1090446cfa3f384d5 | <|skeleton|>
class ItemsFile:
"""Generate data for Items dummy model Oasis file. This file lists the exposure items for which ground up loss will be sampled. Attributes: generate_data: Generate Items dummy model Oasis file data."""
def __init__(self, num_locations, coverages_per_location, num_areaperils, num_v... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ItemsFile:
"""Generate data for Items dummy model Oasis file. This file lists the exposure items for which ground up loss will be sampled. Attributes: generate_data: Generate Items dummy model Oasis file data."""
def __init__(self, num_locations, coverages_per_location, num_areaperils, num_vulnerabilitie... | the_stack_v2_python_sparse | oasislmf/computation/data/dummy_model/generate.py | OasisLMF/OasisLMF | train | 122 |
8404f2fa5e730c2f4fabfb99f1919574d48586fb | [
"super(NumpyDeserializer, self).__init__(accept=accept)\nself.dtype = dtype\nself.allow_pickle = allow_pickle",
"try:\n if content_type == 'text/csv':\n return np.genfromtxt(codecs.getreader('utf-8')(stream), delimiter=',', dtype=self.dtype)\n if content_type == 'application/json':\n return np... | <|body_start_0|>
super(NumpyDeserializer, self).__init__(accept=accept)
self.dtype = dtype
self.allow_pickle = allow_pickle
<|end_body_0|>
<|body_start_1|>
try:
if content_type == 'text/csv':
return np.genfromtxt(codecs.getreader('utf-8')(stream), delimiter='... | Deserialize a stream of data in .npy, .npz or UTF-8 CSV/JSON format to a numpy array. Note that when using application/x-npz archive format, the result will usually be a dictionary-like object containing multiple arrays (as per ``numpy.load()``) - instead of a single array. | NumpyDeserializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumpyDeserializer:
"""Deserialize a stream of data in .npy, .npz or UTF-8 CSV/JSON format to a numpy array. Note that when using application/x-npz archive format, the result will usually be a dictionary-like object containing multiple arrays (as per ``numpy.load()``) - instead of a single array."... | stack_v2_sparse_classes_36k_train_014378 | 12,360 | permissive | [
{
"docstring": "Initialize a ``NumpyDeserializer`` instance. Args: dtype (str): The dtype of the data (default: None). accept (union[str, tuple[str]]): The MIME type (or tuple of allowable MIME types) that is expected from the inference endpoint (default: \"application/x-npy\"). allow_pickle (bool): Allow loadi... | 2 | stack_v2_sparse_classes_30k_train_013290 | Implement the Python class `NumpyDeserializer` described below.
Class description:
Deserialize a stream of data in .npy, .npz or UTF-8 CSV/JSON format to a numpy array. Note that when using application/x-npz archive format, the result will usually be a dictionary-like object containing multiple arrays (as per ``numpy.... | Implement the Python class `NumpyDeserializer` described below.
Class description:
Deserialize a stream of data in .npy, .npz or UTF-8 CSV/JSON format to a numpy array. Note that when using application/x-npz archive format, the result will usually be a dictionary-like object containing multiple arrays (as per ``numpy.... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class NumpyDeserializer:
"""Deserialize a stream of data in .npy, .npz or UTF-8 CSV/JSON format to a numpy array. Note that when using application/x-npz archive format, the result will usually be a dictionary-like object containing multiple arrays (as per ``numpy.load()``) - instead of a single array."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumpyDeserializer:
"""Deserialize a stream of data in .npy, .npz or UTF-8 CSV/JSON format to a numpy array. Note that when using application/x-npz archive format, the result will usually be a dictionary-like object containing multiple arrays (as per ``numpy.load()``) - instead of a single array."""
def _... | the_stack_v2_python_sparse | src/sagemaker/base_deserializers.py | aws/sagemaker-python-sdk | train | 2,050 |
9253f01e88adce33444245fcf2b4fbd744be6a7d | [
"errors = []\nif not file_path or file_path.isspace():\n errors.append(VerifierError(subject=self, local_error='Gromacs file name is white space.', global_error='Gromacs file not specified.'))\nif ext is not None:\n if not file_path.endswith('.{}'.format(ext)):\n errors.append(VerifierError(subject=sel... | <|body_start_0|>
errors = []
if not file_path or file_path.isspace():
errors.append(VerifierError(subject=self, local_error='Gromacs file name is white space.', global_error='Gromacs file not specified.'))
if ext is not None:
if not file_path.endswith('.{}'.format(ext)):
... | Class containing all input parameters for a single molecular fragment in a Gromacs simulation | FragmentDataSourceModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FragmentDataSourceModel:
"""Class containing all input parameters for a single molecular fragment in a Gromacs simulation"""
def _file_check(self, file_path, ext=None):
"""Performs a series of checks on selected Gromacs file located at file_path Parameters ---------- file_path: str F... | stack_v2_sparse_classes_36k_train_014379 | 2,768 | permissive | [
{
"docstring": "Performs a series of checks on selected Gromacs file located at file_path Parameters ---------- file_path: str File path for Gromacs input file ext: str, optional Expected extension of Gromacs input file",
"name": "_file_check",
"signature": "def _file_check(self, file_path, ext=None)"
... | 2 | stack_v2_sparse_classes_30k_train_000874 | Implement the Python class `FragmentDataSourceModel` described below.
Class description:
Class containing all input parameters for a single molecular fragment in a Gromacs simulation
Method signatures and docstrings:
- def _file_check(self, file_path, ext=None): Performs a series of checks on selected Gromacs file lo... | Implement the Python class `FragmentDataSourceModel` described below.
Class description:
Class containing all input parameters for a single molecular fragment in a Gromacs simulation
Method signatures and docstrings:
- def _file_check(self, file_path, ext=None): Performs a series of checks on selected Gromacs file lo... | 1518185e4cdab824d57570bc5df6c719f1f11bea | <|skeleton|>
class FragmentDataSourceModel:
"""Class containing all input parameters for a single molecular fragment in a Gromacs simulation"""
def _file_check(self, file_path, ext=None):
"""Performs a series of checks on selected Gromacs file located at file_path Parameters ---------- file_path: str F... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FragmentDataSourceModel:
"""Class containing all input parameters for a single molecular fragment in a Gromacs simulation"""
def _file_check(self, file_path, ext=None):
"""Performs a series of checks on selected Gromacs file located at file_path Parameters ---------- file_path: str File path for ... | the_stack_v2_python_sparse | force_gromacs/data_sources/fragment/fragment_model.py | force-h2020/force-bdss-plugin-gromacs | train | 0 |
46b0455592dded788b789dc9ba1a14f76d5a3ae3 | [
"self.type_mapping_dict = copy.deepcopy(type_dict)\nself.params_mapping_dict = copy.deepcopy(params_dict)\nself.backend_type = None\nif vega.is_torch_backend():\n self.backend_type = 'torch'\nelif vega.is_tf_backend():\n self.backend_type = 'tf'\nelif vega.is_ms_backend():\n self.backend_type = 'ms'\nelse:... | <|body_start_0|>
self.type_mapping_dict = copy.deepcopy(type_dict)
self.params_mapping_dict = copy.deepcopy(params_dict)
self.backend_type = None
if vega.is_torch_backend():
self.backend_type = 'torch'
elif vega.is_tf_backend():
self.backend_type = 'tf'
... | Config mapping according to backend. :param module_type: module type in trainer, 'optim', 'loss' or 'lr_scheduler' :type module_type: str | ConfigBackendMapping | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigBackendMapping:
"""Config mapping according to backend. :param module_type: module type in trainer, 'optim', 'loss' or 'lr_scheduler' :type module_type: str"""
def __init__(self, type_dict, params_dict):
"""Init config backend mapping."""
<|body_0|>
def backend_map... | stack_v2_sparse_classes_36k_train_014380 | 2,721 | permissive | [
{
"docstring": "Init config backend mapping.",
"name": "__init__",
"signature": "def __init__(self, type_dict, params_dict)"
},
{
"docstring": "Map config to specific backend. :param config: original config from config file :type config: Config or dict :return: config after mapping to backend :r... | 2 | stack_v2_sparse_classes_30k_train_020532 | Implement the Python class `ConfigBackendMapping` described below.
Class description:
Config mapping according to backend. :param module_type: module type in trainer, 'optim', 'loss' or 'lr_scheduler' :type module_type: str
Method signatures and docstrings:
- def __init__(self, type_dict, params_dict): Init config ba... | Implement the Python class `ConfigBackendMapping` described below.
Class description:
Config mapping according to backend. :param module_type: module type in trainer, 'optim', 'loss' or 'lr_scheduler' :type module_type: str
Method signatures and docstrings:
- def __init__(self, type_dict, params_dict): Init config ba... | 12e37a1991eb6771a2999fe0a46ddda920c47948 | <|skeleton|>
class ConfigBackendMapping:
"""Config mapping according to backend. :param module_type: module type in trainer, 'optim', 'loss' or 'lr_scheduler' :type module_type: str"""
def __init__(self, type_dict, params_dict):
"""Init config backend mapping."""
<|body_0|>
def backend_map... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfigBackendMapping:
"""Config mapping according to backend. :param module_type: module type in trainer, 'optim', 'loss' or 'lr_scheduler' :type module_type: str"""
def __init__(self, type_dict, params_dict):
"""Init config backend mapping."""
self.type_mapping_dict = copy.deepcopy(type_... | the_stack_v2_python_sparse | vega/trainer/modules/config_bakcend_map.py | huawei-noah/vega | train | 850 |
c5a7613b0bb497ee9afaf672fd1ded36f1afebfb | [
"if isinstance(value, bytes):\n value = value.decode('utf-8')\nreturn value",
"if isinstance(value, bytes):\n value = value.decode('utf-8')\nresult = repr(value)\nif six.PY2 and result.startswith('u'):\n result = result[1:].decode('unicode-escape')\nreturn result"
] | <|body_start_0|>
if isinstance(value, bytes):
value = value.decode('utf-8')
return value
<|end_body_0|>
<|body_start_1|>
if isinstance(value, bytes):
value = value.decode('utf-8')
result = repr(value)
if six.PY2 and result.startswith('u'):
res... | Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2 | StringSerialization | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringSerialization:
"""Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2"""
def serialize_to_signature(cls, value):
"""Serialize a string to JSON-compatible string. Args: value (byt... | stack_v2_sparse_classes_36k_train_014381 | 30,104 | permissive | [
{
"docstring": "Serialize a string to JSON-compatible string. Args: value (bytes or unicode): The string to serialize. If a byte string, it's expected to contain UTF-8 data. Returns: unicode: The resulting string.",
"name": "serialize_to_signature",
"signature": "def serialize_to_signature(cls, value)"
... | 2 | stack_v2_sparse_classes_30k_train_001219 | Implement the Python class `StringSerialization` described below.
Class description:
Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2
Method signatures and docstrings:
- def serialize_to_signature(cls, value): Seria... | Implement the Python class `StringSerialization` described below.
Class description:
Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2
Method signatures and docstrings:
- def serialize_to_signature(cls, value): Seria... | 756eedeacc41f77111a557fc13dee559cb94f433 | <|skeleton|>
class StringSerialization:
"""Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2"""
def serialize_to_signature(cls, value):
"""Serialize a string to JSON-compatible string. Args: value (byt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StringSerialization:
"""Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2"""
def serialize_to_signature(cls, value):
"""Serialize a string to JSON-compatible string. Args: value (bytes or unicode... | the_stack_v2_python_sparse | django_evolution/serialization.py | beanbaginc/django-evolution | train | 22 |
e87a8683d4300f34018575e8d42abaf0fb780b5c | [
"self._graph = graph\nself.opset = util.default(opset, 11)\nself.optimize = util.default(optimize, True)",
"(graph, output_names), _ = util.invoke_if_callable(self._graph)\ninput_names = list(tf_util.get_input_metadata(graph).keys())\ngraphdef = graph.as_graph_def()\nif self.optimize:\n graphdef = tf2onnx.tfon... | <|body_start_0|>
self._graph = graph
self.opset = util.default(opset, 11)
self.optimize = util.default(optimize, True)
<|end_body_0|>
<|body_start_1|>
(graph, output_names), _ = util.invoke_if_callable(self._graph)
input_names = list(tf_util.get_input_metadata(graph).keys())
... | Functor that loads a TensorFlow graph and converts it to ONNX using the tf2onnx converter. | OnnxFromTfGraph | [
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"ISC",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OnnxFromTfGraph:
"""Functor that loads a TensorFlow graph and converts it to ONNX using the tf2onnx converter."""
def __init__(self, graph, opset=None, optimize=None):
"""Converts a TensorFlow model into ONNX. Args: graph (Union[Tuple[tf.Graph, Sequence[str]], Callable() -> Tuple[tf.... | stack_v2_sparse_classes_36k_train_014382 | 37,448 | permissive | [
{
"docstring": "Converts a TensorFlow model into ONNX. Args: graph (Union[Tuple[tf.Graph, Sequence[str]], Callable() -> Tuple[tf.Graph, Sequence[str]]]): A tuple containing a TensorFlow graph and output names or a callable that returns one. opset (int): The ONNX opset to use during conversion. optimize (bool): ... | 2 | stack_v2_sparse_classes_30k_test_000728 | Implement the Python class `OnnxFromTfGraph` described below.
Class description:
Functor that loads a TensorFlow graph and converts it to ONNX using the tf2onnx converter.
Method signatures and docstrings:
- def __init__(self, graph, opset=None, optimize=None): Converts a TensorFlow model into ONNX. Args: graph (Unio... | Implement the Python class `OnnxFromTfGraph` described below.
Class description:
Functor that loads a TensorFlow graph and converts it to ONNX using the tf2onnx converter.
Method signatures and docstrings:
- def __init__(self, graph, opset=None, optimize=None): Converts a TensorFlow model into ONNX. Args: graph (Unio... | a167852705d74bcc619d8fad0af4b9e4d84472fc | <|skeleton|>
class OnnxFromTfGraph:
"""Functor that loads a TensorFlow graph and converts it to ONNX using the tf2onnx converter."""
def __init__(self, graph, opset=None, optimize=None):
"""Converts a TensorFlow model into ONNX. Args: graph (Union[Tuple[tf.Graph, Sequence[str]], Callable() -> Tuple[tf.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OnnxFromTfGraph:
"""Functor that loads a TensorFlow graph and converts it to ONNX using the tf2onnx converter."""
def __init__(self, graph, opset=None, optimize=None):
"""Converts a TensorFlow model into ONNX. Args: graph (Union[Tuple[tf.Graph, Sequence[str]], Callable() -> Tuple[tf.Graph, Sequen... | the_stack_v2_python_sparse | tools/Polygraphy/polygraphy/backend/onnx/loader.py | NVIDIA/TensorRT | train | 8,026 |
5b393a001338ee30598d34b5fa07ad5a691e7e9b | [
"with SIMPLE_FILE_PATH.open() as auth_file:\n for line in auth_file.readlines():\n match = re.match('(^STEAM_[0,1]{1}:[0,1]{1}:[0-9]+)', line)\n if match:\n self.add(match.group(0))",
"if uniqueid in self:\n return True\nreturn False"
] | <|body_start_0|>
with SIMPLE_FILE_PATH.open() as auth_file:
for line in auth_file.readlines():
match = re.match('(^STEAM_[0,1]{1}:[0,1]{1}:[0-9]+)', line)
if match:
self.add(match.group(0))
<|end_body_0|>
<|body_start_1|>
if uniqueid in se... | Class used to determine if a player is authorized | _SimpleAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _SimpleAuth:
"""Class used to determine if a player is authorized"""
def _parse_admins(self):
"""Method used to get all uniqueids that are authorized on the server"""
<|body_0|>
def is_player_authorized(self, uniqueid, level, permission, flag):
"""Method used to ... | stack_v2_sparse_classes_36k_train_014383 | 2,351 | no_license | [
{
"docstring": "Method used to get all uniqueids that are authorized on the server",
"name": "_parse_admins",
"signature": "def _parse_admins(self)"
},
{
"docstring": "Method used to check if a player is authorized",
"name": "is_player_authorized",
"signature": "def is_player_authorized(... | 2 | stack_v2_sparse_classes_30k_train_008392 | Implement the Python class `_SimpleAuth` described below.
Class description:
Class used to determine if a player is authorized
Method signatures and docstrings:
- def _parse_admins(self): Method used to get all uniqueids that are authorized on the server
- def is_player_authorized(self, uniqueid, level, permission, f... | Implement the Python class `_SimpleAuth` described below.
Class description:
Class used to determine if a player is authorized
Method signatures and docstrings:
- def _parse_admins(self): Method used to get all uniqueids that are authorized on the server
- def is_player_authorized(self, uniqueid, level, permission, f... | b84df87f67ecb0fb2487e68e8b4b6bee3944f506 | <|skeleton|>
class _SimpleAuth:
"""Class used to determine if a player is authorized"""
def _parse_admins(self):
"""Method used to get all uniqueids that are authorized on the server"""
<|body_0|>
def is_player_authorized(self, uniqueid, level, permission, flag):
"""Method used to ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _SimpleAuth:
"""Class used to determine if a player is authorized"""
def _parse_admins(self):
"""Method used to get all uniqueids that are authorized on the server"""
with SIMPLE_FILE_PATH.open() as auth_file:
for line in auth_file.readlines():
match = re.match... | the_stack_v2_python_sparse | addons/source-python/packages/source-python/auth/providers/simple.py | aurorapar/Source.Python | train | 0 |
345e3f8062c01205fe5dabe7f95fd75b69aaec68 | [
"mission_id = self.search(cr, uid, [('parent_id', 'in', ids)], context=context)\nif mission_id:\n raise osv.except_osv(_('Warning!'), _('You cannot delete this mission category because it is parent to another mission category'))\nreturn super(mission_category, self).unlink(cr, uid, ids, context)",
"default = {... | <|body_start_0|>
mission_id = self.search(cr, uid, [('parent_id', 'in', ids)], context=context)
if mission_id:
raise osv.except_osv(_('Warning!'), _('You cannot delete this mission category because it is parent to another mission category'))
return super(mission_category, self).unlin... | mission_category | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class mission_category:
def unlink(self, cr, uid, ids, context=None):
"""This method prevent to delete record if it has parent return super & raise exception"""
<|body_0|>
def copy(self, cr, uid, id, default=None, context=None):
"""This method prevent to duplicate record i... | stack_v2_sparse_classes_36k_train_014384 | 17,962 | no_license | [
{
"docstring": "This method prevent to delete record if it has parent return super & raise exception",
"name": "unlink",
"signature": "def unlink(self, cr, uid, ids, context=None)"
},
{
"docstring": "This method prevent to duplicate record if it has parent return super & raise exception",
"n... | 2 | null | Implement the Python class `mission_category` described below.
Class description:
Implement the mission_category class.
Method signatures and docstrings:
- def unlink(self, cr, uid, ids, context=None): This method prevent to delete record if it has parent return super & raise exception
- def copy(self, cr, uid, id, d... | Implement the Python class `mission_category` described below.
Class description:
Implement the mission_category class.
Method signatures and docstrings:
- def unlink(self, cr, uid, ids, context=None): This method prevent to delete record if it has parent return super & raise exception
- def copy(self, cr, uid, id, d... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class mission_category:
def unlink(self, cr, uid, ids, context=None):
"""This method prevent to delete record if it has parent return super & raise exception"""
<|body_0|>
def copy(self, cr, uid, id, default=None, context=None):
"""This method prevent to duplicate record i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class mission_category:
def unlink(self, cr, uid, ids, context=None):
"""This method prevent to delete record if it has parent return super & raise exception"""
mission_id = self.search(cr, uid, [('parent_id', 'in', ids)], context=context)
if mission_id:
raise osv.except_osv(_('W... | the_stack_v2_python_sparse | v_7/Dongola/common/hr_mission/hr_mission.py | musabahmed/baba | train | 0 | |
30fbd48d36f28a7a5ab0a7f1f029417b24e7957e | [
"if metadata is None:\n metadata = {}\nsecret = self.create(value=value, contributor=contributor, metadata=metadata, expires=expires)\nreturn str(secret.handle)",
"queryset = self.all()\nif contributor is not None:\n queryset = queryset.filter(contributor=contributor)\nsecret = queryset.get(handle=handle)\n... | <|body_start_0|>
if metadata is None:
metadata = {}
secret = self.create(value=value, contributor=contributor, metadata=metadata, expires=expires)
return str(secret.handle)
<|end_body_0|>
<|body_start_1|>
queryset = self.all()
if contributor is not None:
... | Manager for Secret objects. | SecretManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecretManager:
"""Manager for Secret objects."""
def create_secret(self, value, contributor, metadata=None, expires=None):
"""Create a new secret, returning its handle. :param value: Secret value to store :param contributor: User owning the secret :param metadata: Optional metadata d... | stack_v2_sparse_classes_36k_train_014385 | 2,264 | permissive | [
{
"docstring": "Create a new secret, returning its handle. :param value: Secret value to store :param contributor: User owning the secret :param metadata: Optional metadata dictionary (must be JSON serializable) :param expires: Optional date/time of expiry (defaults to None, which means that the secret never ex... | 2 | null | Implement the Python class `SecretManager` described below.
Class description:
Manager for Secret objects.
Method signatures and docstrings:
- def create_secret(self, value, contributor, metadata=None, expires=None): Create a new secret, returning its handle. :param value: Secret value to store :param contributor: Us... | Implement the Python class `SecretManager` described below.
Class description:
Manager for Secret objects.
Method signatures and docstrings:
- def create_secret(self, value, contributor, metadata=None, expires=None): Create a new secret, returning its handle. :param value: Secret value to store :param contributor: Us... | 25c0c45235ef37beb45c1af4c917fbbae6282016 | <|skeleton|>
class SecretManager:
"""Manager for Secret objects."""
def create_secret(self, value, contributor, metadata=None, expires=None):
"""Create a new secret, returning its handle. :param value: Secret value to store :param contributor: User owning the secret :param metadata: Optional metadata d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SecretManager:
"""Manager for Secret objects."""
def create_secret(self, value, contributor, metadata=None, expires=None):
"""Create a new secret, returning its handle. :param value: Secret value to store :param contributor: User owning the secret :param metadata: Optional metadata dictionary (mu... | the_stack_v2_python_sparse | resolwe/flow/models/secret.py | genialis/resolwe | train | 35 |
46692a96e0f31433821ea622d366179306bb7cbc | [
"torch.nn.Module.__init__(self)\nif hidden_size % num_heads:\n raise ValueError('hidden size must be a multiple of the number of attention heads')\nself.attention = Attention(hidden_size, hidden_size, num_heads, hidden_size // num_heads, dropout=dropout, initializer_range=initializer_range)\nself.encoder_attenti... | <|body_start_0|>
torch.nn.Module.__init__(self)
if hidden_size % num_heads:
raise ValueError('hidden size must be a multiple of the number of attention heads')
self.attention = Attention(hidden_size, hidden_size, num_heads, hidden_size // num_heads, dropout=dropout, initializer_range... | TransformerDecoder | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerDecoder:
def __init__(self, hidden_size=768, num_heads=12, intermediate_size=3072, dropout=0.1, initializer_range=0.02):
"""hidden_size - hidden size, must be multiple of num_heads num_heads - number of attention heads. intermediate_size - size of the intermediate dense layer ... | stack_v2_sparse_classes_36k_train_014386 | 6,126 | permissive | [
{
"docstring": "hidden_size - hidden size, must be multiple of num_heads num_heads - number of attention heads. intermediate_size - size of the intermediate dense layer dropout - dropout probability (0. means \"no dropout\")",
"name": "__init__",
"signature": "def __init__(self, hidden_size=768, num_hea... | 2 | stack_v2_sparse_classes_30k_train_009882 | Implement the Python class `TransformerDecoder` described below.
Class description:
Implement the TransformerDecoder class.
Method signatures and docstrings:
- def __init__(self, hidden_size=768, num_heads=12, intermediate_size=3072, dropout=0.1, initializer_range=0.02): hidden_size - hidden size, must be multiple of... | Implement the Python class `TransformerDecoder` described below.
Class description:
Implement the TransformerDecoder class.
Method signatures and docstrings:
- def __init__(self, hidden_size=768, num_heads=12, intermediate_size=3072, dropout=0.1, initializer_range=0.02): hidden_size - hidden size, must be multiple of... | 84c1c9507b3b1bffd2a08a86efaf9bc9955271e0 | <|skeleton|>
class TransformerDecoder:
def __init__(self, hidden_size=768, num_heads=12, intermediate_size=3072, dropout=0.1, initializer_range=0.02):
"""hidden_size - hidden size, must be multiple of num_heads num_heads - number of attention heads. intermediate_size - size of the intermediate dense layer ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransformerDecoder:
def __init__(self, hidden_size=768, num_heads=12, intermediate_size=3072, dropout=0.1, initializer_range=0.02):
"""hidden_size - hidden size, must be multiple of num_heads num_heads - number of attention heads. intermediate_size - size of the intermediate dense layer dropout - drop... | the_stack_v2_python_sparse | tbert/transformer.py | qianrenjian/tbert | train | 0 | |
0d98ccd859c6f267cb0472b419c3f42886f8608e | [
"try:\n session_duration = int(getenv('SESSION_DURATION'))\nexcept Exception:\n session_duration = 0\nself.session_duration = session_duration",
"session_id = super().create_session(user_id)\nif session_id is None:\n return None\nsession_dictionary = {'user_id': user_id, 'created_at': datetime.now()}\nSe... | <|body_start_0|>
try:
session_duration = int(getenv('SESSION_DURATION'))
except Exception:
session_duration = 0
self.session_duration = session_duration
<|end_body_0|>
<|body_start_1|>
session_id = super().create_session(user_id)
if session_id is None:
... | Session expiration authentification methods | SessionExpAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionExpAuth:
"""Session expiration authentification methods"""
def __init__(self):
"""Initialize class"""
<|body_0|>
def create_session(self, user_id=None):
"""Creates a session ID"""
<|body_1|>
def user_id_for_session_id(self, session_id=None):
... | stack_v2_sparse_classes_36k_train_014387 | 1,681 | no_license | [
{
"docstring": "Initialize class",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Creates a session ID",
"name": "create_session",
"signature": "def create_session(self, user_id=None)"
},
{
"docstring": "Returns a user ID for a given session ID",
"na... | 3 | stack_v2_sparse_classes_30k_train_002308 | Implement the Python class `SessionExpAuth` described below.
Class description:
Session expiration authentification methods
Method signatures and docstrings:
- def __init__(self): Initialize class
- def create_session(self, user_id=None): Creates a session ID
- def user_id_for_session_id(self, session_id=None): Retur... | Implement the Python class `SessionExpAuth` described below.
Class description:
Session expiration authentification methods
Method signatures and docstrings:
- def __init__(self): Initialize class
- def create_session(self, user_id=None): Creates a session ID
- def user_id_for_session_id(self, session_id=None): Retur... | 151c5c063b15c8474c1fa4ab5ce27f94f36c42b5 | <|skeleton|>
class SessionExpAuth:
"""Session expiration authentification methods"""
def __init__(self):
"""Initialize class"""
<|body_0|>
def create_session(self, user_id=None):
"""Creates a session ID"""
<|body_1|>
def user_id_for_session_id(self, session_id=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SessionExpAuth:
"""Session expiration authentification methods"""
def __init__(self):
"""Initialize class"""
try:
session_duration = int(getenv('SESSION_DURATION'))
except Exception:
session_duration = 0
self.session_duration = session_duration
... | the_stack_v2_python_sparse | 0x07-Session_authentication/api/v1/auth/session_exp_auth.py | Gzoref/holbertonschool-web_back_end | train | 0 |
9086f73c862baf94f5f88a771a3da38584ce2846 | [
"self.interval = interval\nthread = threading.Thread(target=self.run, args=())\nthread.start()",
"while True:\n global uri\n daemon = Pyro4.Daemon()\n uri = daemon.register(Client)\n daemon.requestLoop()"
] | <|body_start_0|>
self.interval = interval
thread = threading.Thread(target=self.run, args=())
thread.start()
<|end_body_0|>
<|body_start_1|>
while True:
global uri
daemon = Pyro4.Daemon()
uri = daemon.register(Client)
daemon.requestLoop()
... | Threading example class The run() method will be started and it will run in the background until the application exits. | ThreadingExample | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThreadingExample:
"""Threading example class The run() method will be started and it will run in the background until the application exits."""
def __init__(self, interval=1):
"""Constructor :type interval: int :param interval: Check interval, in seconds"""
<|body_0|>
de... | stack_v2_sparse_classes_36k_train_014388 | 3,896 | permissive | [
{
"docstring": "Constructor :type interval: int :param interval: Check interval, in seconds",
"name": "__init__",
"signature": "def __init__(self, interval=1)"
},
{
"docstring": "Method that runs forever",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002665 | Implement the Python class `ThreadingExample` described below.
Class description:
Threading example class The run() method will be started and it will run in the background until the application exits.
Method signatures and docstrings:
- def __init__(self, interval=1): Constructor :type interval: int :param interval:... | Implement the Python class `ThreadingExample` described below.
Class description:
Threading example class The run() method will be started and it will run in the background until the application exits.
Method signatures and docstrings:
- def __init__(self, interval=1): Constructor :type interval: int :param interval:... | 0039e0eb5ad9b4e03e703c7c51295907fec6708d | <|skeleton|>
class ThreadingExample:
"""Threading example class The run() method will be started and it will run in the background until the application exits."""
def __init__(self, interval=1):
"""Constructor :type interval: int :param interval: Check interval, in seconds"""
<|body_0|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThreadingExample:
"""Threading example class The run() method will be started and it will run in the background until the application exits."""
def __init__(self, interval=1):
"""Constructor :type interval: int :param interval: Check interval, in seconds"""
self.interval = interval
... | the_stack_v2_python_sparse | src/example_applications/client_constraint.py | mazerius/khronos | train | 1 |
519127431cccfbb2ff502a3520b9ee554721da20 | [
"super(HiveNamedPartitionSensor, self).__init__(host, port, **kwargs)\nself._table_name = table_name\nself._partition_names = partition_names",
"with self._hive_metastore_client as client:\n try:\n for partition_name in self._partition_names:\n client.get_partition_by_name(self._schema, self.... | <|body_start_0|>
super(HiveNamedPartitionSensor, self).__init__(host, port, **kwargs)
self._table_name = table_name
self._partition_names = partition_names
<|end_body_0|>
<|body_start_1|>
with self._hive_metastore_client as client:
try:
for partition_name in ... | HiveNamedPartitionSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HiveNamedPartitionSensor:
def __init__(self, table_name, partition_names, host, port, **kwargs):
"""This class allows sensing for a specific named Hive Partition. This is the preferred partition sensing operator because it is more efficient than evaluating a filter expression. :param Tex... | stack_v2_sparse_classes_36k_train_014389 | 4,900 | permissive | [
{
"docstring": "This class allows sensing for a specific named Hive Partition. This is the preferred partition sensing operator because it is more efficient than evaluating a filter expression. :param Text table_name: The name of the table :param Text partition_name: The name of the partition to listen for (exa... | 2 | null | Implement the Python class `HiveNamedPartitionSensor` described below.
Class description:
Implement the HiveNamedPartitionSensor class.
Method signatures and docstrings:
- def __init__(self, table_name, partition_names, host, port, **kwargs): This class allows sensing for a specific named Hive Partition. This is the ... | Implement the Python class `HiveNamedPartitionSensor` described below.
Class description:
Implement the HiveNamedPartitionSensor class.
Method signatures and docstrings:
- def __init__(self, table_name, partition_names, host, port, **kwargs): This class allows sensing for a specific named Hive Partition. This is the ... | 2eb9ce7aacaab6e49c1fc901c14c7b0d6b479523 | <|skeleton|>
class HiveNamedPartitionSensor:
def __init__(self, table_name, partition_names, host, port, **kwargs):
"""This class allows sensing for a specific named Hive Partition. This is the preferred partition sensing operator because it is more efficient than evaluating a filter expression. :param Tex... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HiveNamedPartitionSensor:
def __init__(self, table_name, partition_names, host, port, **kwargs):
"""This class allows sensing for a specific named Hive Partition. This is the preferred partition sensing operator because it is more efficient than evaluating a filter expression. :param Text table_name: ... | the_stack_v2_python_sparse | flytekit/contrib/sensors/impl.py | jbrambleDC/flytekit | train | 1 | |
1b7af39a5c162e424b89882d5a61d07c970bd236 | [
"ap.fit.Beam.__init__(self, freqs)\nself.width = width\nself.length = length",
"vec_n = np.array(xyz)\nvec_z = np.array([0.0, 0.0, 1.0])\nnz = np.dot(vec_n, vec_z)\nif nz <= 0:\n return 0.0\nelse:\n vec_u = np.array([1.0, 0.0, 0.0])\n vec_v = np.array([0.0, 1.0, 0.0])\n nu = np.dot(vec_n, vec_u)\n ... | <|body_start_0|>
ap.fit.Beam.__init__(self, freqs)
self.width = width
self.length = length
<|end_body_0|>
<|body_start_1|>
vec_n = np.array(xyz)
vec_z = np.array([0.0, 0.0, 1.0])
nz = np.dot(vec_n, vec_z)
if nz <= 0:
return 0.0
else:
... | Represent the cylinder parabolic antenna beam. | BeamCylinder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BeamCylinder:
"""Represent the cylinder parabolic antenna beam."""
def __init__(self, freqs, width, length=0.0):
"""Arguments: - `freqs`: frequencies (in GHz) at bin centers across spectrum.; - `width`: the cylinder width (EW direction), in unit m; - `length`: the spacing between too... | stack_v2_sparse_classes_36k_train_014390 | 12,022 | no_license | [
{
"docstring": "Arguments: - `freqs`: frequencies (in GHz) at bin centers across spectrum.; - `width`: the cylinder width (EW direction), in unit m; - `length`: the spacing between too feeds (NS direction), in unit m.",
"name": "__init__",
"signature": "def __init__(self, freqs, width, length=0.0)"
},... | 2 | stack_v2_sparse_classes_30k_train_004362 | Implement the Python class `BeamCylinder` described below.
Class description:
Represent the cylinder parabolic antenna beam.
Method signatures and docstrings:
- def __init__(self, freqs, width, length=0.0): Arguments: - `freqs`: frequencies (in GHz) at bin centers across spectrum.; - `width`: the cylinder width (EW d... | Implement the Python class `BeamCylinder` described below.
Class description:
Represent the cylinder parabolic antenna beam.
Method signatures and docstrings:
- def __init__(self, freqs, width, length=0.0): Arguments: - `freqs`: frequencies (in GHz) at bin centers across spectrum.; - `width`: the cylinder width (EW d... | 7d2fe26a80abd165cc8fe13ccd2115cfa9b32232 | <|skeleton|>
class BeamCylinder:
"""Represent the cylinder parabolic antenna beam."""
def __init__(self, freqs, width, length=0.0):
"""Arguments: - `freqs`: frequencies (in GHz) at bin centers across spectrum.; - `width`: the cylinder width (EW direction), in unit m; - `length`: the spacing between too... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BeamCylinder:
"""Represent the cylinder parabolic antenna beam."""
def __init__(self, freqs, width, length=0.0):
"""Arguments: - `freqs`: frequencies (in GHz) at bin centers across spectrum.; - `width`: the cylinder width (EW direction), in unit m; - `length`: the spacing between too feeds (NS di... | the_stack_v2_python_sparse | src/cylinder.py | zuoshifan/TianlaiSim | train | 0 |
5abe3ea4b8896ca7082c89be224152eec67140fb | [
"self.attempt_number = attempt_number\nself.delta_size_bytes = delta_size_bytes\nself.indexing_status = indexing_status\nself.is_app_consistent = is_app_consistent\nself.is_full_backup = is_full_backup\nself.job_run_id = job_run_id\nself.local_mount_path = local_mount_path\nself.logical_size_bytes = logical_size_by... | <|body_start_0|>
self.attempt_number = attempt_number
self.delta_size_bytes = delta_size_bytes
self.indexing_status = indexing_status
self.is_app_consistent = is_app_consistent
self.is_full_backup = is_full_backup
self.job_run_id = job_run_id
self.local_mount_path... | Implementation of the 'SnapshotVersion' model. Specifies information about snapshots of a backup object. Attributes: attempt_number (long|int): Specifies the number of the attempts made by the Job Run to capture a snapshot of the object. For example, if an snapshot is successfully captured after three attempts, this fi... | SnapshotVersion | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnapshotVersion:
"""Implementation of the 'SnapshotVersion' model. Specifies information about snapshots of a backup object. Attributes: attempt_number (long|int): Specifies the number of the attempts made by the Job Run to capture a snapshot of the object. For example, if an snapshot is successf... | stack_v2_sparse_classes_36k_train_014391 | 7,459 | permissive | [
{
"docstring": "Constructor for the SnapshotVersion class",
"name": "__init__",
"signature": "def __init__(self, attempt_number=None, delta_size_bytes=None, indexing_status=None, is_app_consistent=None, is_full_backup=None, job_run_id=None, local_mount_path=None, logical_size_bytes=None, physical_size_b... | 2 | null | Implement the Python class `SnapshotVersion` described below.
Class description:
Implementation of the 'SnapshotVersion' model. Specifies information about snapshots of a backup object. Attributes: attempt_number (long|int): Specifies the number of the attempts made by the Job Run to capture a snapshot of the object. ... | Implement the Python class `SnapshotVersion` described below.
Class description:
Implementation of the 'SnapshotVersion' model. Specifies information about snapshots of a backup object. Attributes: attempt_number (long|int): Specifies the number of the attempts made by the Job Run to capture a snapshot of the object. ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class SnapshotVersion:
"""Implementation of the 'SnapshotVersion' model. Specifies information about snapshots of a backup object. Attributes: attempt_number (long|int): Specifies the number of the attempts made by the Job Run to capture a snapshot of the object. For example, if an snapshot is successf... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnapshotVersion:
"""Implementation of the 'SnapshotVersion' model. Specifies information about snapshots of a backup object. Attributes: attempt_number (long|int): Specifies the number of the attempts made by the Job Run to capture a snapshot of the object. For example, if an snapshot is successfully captured... | the_stack_v2_python_sparse | cohesity_management_sdk/models/snapshot_version.py | cohesity/management-sdk-python | train | 24 |
91a8c173d38077969ad7e6248ed289583bc40360 | [
"command = config.editor\nif jumpIndex:\n line = text[:jumpIndex].count('\\n')\n column = jumpIndex - (text[:jumpIndex].rfind('\\n') + 1)\nelse:\n line = column = 0\nif config.editor.startswith('kate'):\n command += ' -l %i -c %i' % (line + 1, column + 1)\nelif config.editor.startswith('gedit'):\n co... | <|body_start_0|>
command = config.editor
if jumpIndex:
line = text[:jumpIndex].count('\n')
column = jumpIndex - (text[:jumpIndex].rfind('\n') + 1)
else:
line = column = 0
if config.editor.startswith('kate'):
command += ' -l %i -c %i' % (lin... | Text editor. | TextEditor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextEditor:
"""Text editor."""
def command(self, tempFilename, text, jumpIndex=None):
"""Return editor selected in user-config.py."""
<|body_0|>
def convertLinebreaks(self, text):
"""Convert line-breaks."""
<|body_1|>
def restoreLinebreaks(self, text... | stack_v2_sparse_classes_36k_train_014392 | 4,743 | permissive | [
{
"docstring": "Return editor selected in user-config.py.",
"name": "command",
"signature": "def command(self, tempFilename, text, jumpIndex=None)"
},
{
"docstring": "Convert line-breaks.",
"name": "convertLinebreaks",
"signature": "def convertLinebreaks(self, text)"
},
{
"docstr... | 4 | stack_v2_sparse_classes_30k_train_019743 | Implement the Python class `TextEditor` described below.
Class description:
Text editor.
Method signatures and docstrings:
- def command(self, tempFilename, text, jumpIndex=None): Return editor selected in user-config.py.
- def convertLinebreaks(self, text): Convert line-breaks.
- def restoreLinebreaks(self, text): R... | Implement the Python class `TextEditor` described below.
Class description:
Text editor.
Method signatures and docstrings:
- def command(self, tempFilename, text, jumpIndex=None): Return editor selected in user-config.py.
- def convertLinebreaks(self, text): Convert line-breaks.
- def restoreLinebreaks(self, text): R... | 2461ccc6d24153790a1b1c0378348f99997c4eca | <|skeleton|>
class TextEditor:
"""Text editor."""
def command(self, tempFilename, text, jumpIndex=None):
"""Return editor selected in user-config.py."""
<|body_0|>
def convertLinebreaks(self, text):
"""Convert line-breaks."""
<|body_1|>
def restoreLinebreaks(self, text... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TextEditor:
"""Text editor."""
def command(self, tempFilename, text, jumpIndex=None):
"""Return editor selected in user-config.py."""
command = config.editor
if jumpIndex:
line = text[:jumpIndex].count('\n')
column = jumpIndex - (text[:jumpIndex].rfind('\n'... | the_stack_v2_python_sparse | pywikibot/editor.py | speedydeletion/pywikibot | train | 1 |
032133a028228459d6333aa26c0fa1b825308a76 | [
"generations = []\ntask_index = 0\nprevious_generations = None\nfor _ in range(NUMBER_OF_GENERATIONS):\n test_ranges = range(task_index, task_index + NUMBER_OF_TASKS)\n tasks = [IdentifierMockTask(STEERING_TEST_STAGE, t) for t in test_ranges]\n steering_tasks = set(tasks)\n current_generation = MockGene... | <|body_start_0|>
generations = []
task_index = 0
previous_generations = None
for _ in range(NUMBER_OF_GENERATIONS):
test_ranges = range(task_index, task_index + NUMBER_OF_TASKS)
tasks = [IdentifierMockTask(STEERING_TEST_STAGE, t) for t in test_ranges]
... | This class test the steering method. The steering algorithm should return if there is no new task in the initial generation. The steering algorithm should send all the tasks to the next stage and should terminate once there is no pending generation. A generation is pending if it contains pending task. A task is pending... | SteeringTest | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SteeringTest:
"""This class test the steering method. The steering algorithm should return if there is no new task in the initial generation. The steering algorithm should send all the tasks to the next stage and should terminate once there is no pending generation. A generation is pending if it ... | stack_v2_sparse_classes_36k_train_014393 | 5,497 | permissive | [
{
"docstring": "Test that the steering algorithm processes all the tasks properly. Test that the steering algorithm sends all the tasks to the next stage. Test that the steering algorithm terminates once all the tasks have been processed, i.e., the results for the tasks are all ready.",
"name": "testSteerin... | 2 | null | Implement the Python class `SteeringTest` described below.
Class description:
This class test the steering method. The steering algorithm should return if there is no new task in the initial generation. The steering algorithm should send all the tasks to the next stage and should terminate once there is no pending gen... | Implement the Python class `SteeringTest` described below.
Class description:
This class test the steering method. The steering algorithm should return if there is no new task in the initial generation. The steering algorithm should send all the tasks to the next stage and should terminate once there is no pending gen... | e2745b756317aac3c7a27a4c10bdfe0921a82a1c | <|skeleton|>
class SteeringTest:
"""This class test the steering method. The steering algorithm should return if there is no new task in the initial generation. The steering algorithm should send all the tasks to the next stage and should terminate once there is no pending generation. A generation is pending if it ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SteeringTest:
"""This class test the steering method. The steering algorithm should return if there is no new task in the initial generation. The steering algorithm should send all the tasks to the next stage and should terminate once there is no pending generation. A generation is pending if it contains pend... | the_stack_v2_python_sparse | app/src/main/java/com/syd/source/aosp/external/toolchain-utils/bestflags/steering_test.py | lz-purple/Source | train | 4 |
3b3124f2bcf27e33bedb4e9360e4a4fa1eb5dc21 | [
"self.internal_dict = {}\nfor i in dictionary.items():\n self.internal_dict[i[0]] = i[1]",
"result = 0\nfor i in self.internal_dict.items():\n result += hash(i[0]) + hash(i[1])\nreturn result",
"for i in self.internal_dict.items():\n if d.internal_dict[i[0]] != i[1]:\n return False\nreturn True"... | <|body_start_0|>
self.internal_dict = {}
for i in dictionary.items():
self.internal_dict[i[0]] = i[1]
<|end_body_0|>
<|body_start_1|>
result = 0
for i in self.internal_dict.items():
result += hash(i[0]) + hash(i[1])
return result
<|end_body_1|>
<|body_st... | Odpowiednik frozenset dla zbiorów, czyli słownik, który nie jest modyfikowalny, a dzięki temu może być np. elementem zbiorów, albo kluczem w innym słowniku. | FrozenDictionary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FrozenDictionary:
"""Odpowiednik frozenset dla zbiorów, czyli słownik, który nie jest modyfikowalny, a dzięki temu może być np. elementem zbiorów, albo kluczem w innym słowniku."""
def __init__(self, dictionary):
"""Tworzy nowy zamrożony słownik z podanego słownika"""
<|body_... | stack_v2_sparse_classes_36k_train_014394 | 4,370 | no_license | [
{
"docstring": "Tworzy nowy zamrożony słownik z podanego słownika",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": "Zwraca hasz słownika (int)",
"name": "__hash__",
"signature": "def __hash__(self)"
},
{
"docstring": "Porównuje nasz słownik z ... | 4 | stack_v2_sparse_classes_30k_train_019396 | Implement the Python class `FrozenDictionary` described below.
Class description:
Odpowiednik frozenset dla zbiorów, czyli słownik, który nie jest modyfikowalny, a dzięki temu może być np. elementem zbiorów, albo kluczem w innym słowniku.
Method signatures and docstrings:
- def __init__(self, dictionary): Tworzy nowy... | Implement the Python class `FrozenDictionary` described below.
Class description:
Odpowiednik frozenset dla zbiorów, czyli słownik, który nie jest modyfikowalny, a dzięki temu może być np. elementem zbiorów, albo kluczem w innym słowniku.
Method signatures and docstrings:
- def __init__(self, dictionary): Tworzy nowy... | cb0ff06a6b94ef5aa23adcfd2672365ceecaab56 | <|skeleton|>
class FrozenDictionary:
"""Odpowiednik frozenset dla zbiorów, czyli słownik, który nie jest modyfikowalny, a dzięki temu może być np. elementem zbiorów, albo kluczem w innym słowniku."""
def __init__(self, dictionary):
"""Tworzy nowy zamrożony słownik z podanego słownika"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FrozenDictionary:
"""Odpowiednik frozenset dla zbiorów, czyli słownik, który nie jest modyfikowalny, a dzięki temu może być np. elementem zbiorów, albo kluczem w innym słowniku."""
def __init__(self, dictionary):
"""Tworzy nowy zamrożony słownik z podanego słownika"""
self.internal_dict =... | the_stack_v2_python_sparse | labs/lab_5.py | MichalSzewczyk/python-learning | train | 0 |
d482198d2918ff18e254e2be319fa6ce6e5e1274 | [
"if not value:\n return []\nif isinstance(value, basestring):\n values = value.split(',')\n return [x.strip() for x in values if x.strip()]\nelse:\n return value",
"super(MultiEmailField, self).validate(value)\nfor email in value:\n validate_email(email)"
] | <|body_start_0|>
if not value:
return []
if isinstance(value, basestring):
values = value.split(',')
return [x.strip() for x in values if x.strip()]
else:
return value
<|end_body_0|>
<|body_start_1|>
super(MultiEmailField, self).validate(v... | MultiEmailField | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiEmailField:
def to_python(self, value):
"""Normalize data to a list of strings."""
<|body_0|>
def validate(self, value):
"""Check if value consists only of valid emails."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not value:
... | stack_v2_sparse_classes_36k_train_014395 | 3,815 | permissive | [
{
"docstring": "Normalize data to a list of strings.",
"name": "to_python",
"signature": "def to_python(self, value)"
},
{
"docstring": "Check if value consists only of valid emails.",
"name": "validate",
"signature": "def validate(self, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011678 | Implement the Python class `MultiEmailField` described below.
Class description:
Implement the MultiEmailField class.
Method signatures and docstrings:
- def to_python(self, value): Normalize data to a list of strings.
- def validate(self, value): Check if value consists only of valid emails. | Implement the Python class `MultiEmailField` described below.
Class description:
Implement the MultiEmailField class.
Method signatures and docstrings:
- def to_python(self, value): Normalize data to a list of strings.
- def validate(self, value): Check if value consists only of valid emails.
<|skeleton|>
class Mult... | aeaae292fbd55aca1b6043227ec105e67d73367f | <|skeleton|>
class MultiEmailField:
def to_python(self, value):
"""Normalize data to a list of strings."""
<|body_0|>
def validate(self, value):
"""Check if value consists only of valid emails."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiEmailField:
def to_python(self, value):
"""Normalize data to a list of strings."""
if not value:
return []
if isinstance(value, basestring):
values = value.split(',')
return [x.strip() for x in values if x.strip()]
else:
retu... | the_stack_v2_python_sparse | ietf/utils/fields.py | omunroe-com/ietfdb2 | train | 2 | |
53b4a1cbbf1dd4744a57e15fb25741cbbf2c088d | [
"response = self.client.get(reverse('polls:index'))\nself.assertEqual(response.status_code, 200)\nself.assertContains(response, 'No polls available.')\nself.assertQuerysetEqual(response.context['questions'], [])",
"time = timezone.now()\ncreate_question('Question_1', -5)\ncreate_question('Question_2', -1)\nrespon... | <|body_start_0|>
response = self.client.get(reverse('polls:index'))
self.assertEqual(response.status_code, 200)
self.assertContains(response, 'No polls available.')
self.assertQuerysetEqual(response.context['questions'], [])
<|end_body_0|>
<|body_start_1|>
time = timezone.now()
... | QuestionIndexViewTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionIndexViewTests:
def test_index_view_with_no_questions(self):
"""If no questions exist, an appropriate message should be displayed."""
<|body_0|>
def test_index_view_with_past_questions(self):
"""If questions exist with pub_date in the past, they should be vis... | stack_v2_sparse_classes_36k_train_014396 | 4,246 | no_license | [
{
"docstring": "If no questions exist, an appropriate message should be displayed.",
"name": "test_index_view_with_no_questions",
"signature": "def test_index_view_with_no_questions(self)"
},
{
"docstring": "If questions exist with pub_date in the past, they should be visible in the view.",
... | 3 | null | Implement the Python class `QuestionIndexViewTests` described below.
Class description:
Implement the QuestionIndexViewTests class.
Method signatures and docstrings:
- def test_index_view_with_no_questions(self): If no questions exist, an appropriate message should be displayed.
- def test_index_view_with_past_questi... | Implement the Python class `QuestionIndexViewTests` described below.
Class description:
Implement the QuestionIndexViewTests class.
Method signatures and docstrings:
- def test_index_view_with_no_questions(self): If no questions exist, an appropriate message should be displayed.
- def test_index_view_with_past_questi... | acbb6d21a8182feabcb3329e17c76ac3af375255 | <|skeleton|>
class QuestionIndexViewTests:
def test_index_view_with_no_questions(self):
"""If no questions exist, an appropriate message should be displayed."""
<|body_0|>
def test_index_view_with_past_questions(self):
"""If questions exist with pub_date in the past, they should be vis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuestionIndexViewTests:
def test_index_view_with_no_questions(self):
"""If no questions exist, an appropriate message should be displayed."""
response = self.client.get(reverse('polls:index'))
self.assertEqual(response.status_code, 200)
self.assertContains(response, 'No polls a... | the_stack_v2_python_sparse | pythonTutorial/django/mysite/polls/tests.py | rajatgirotra/study | train | 6 | |
0f645ee91782f286c68d418dd060752e7354a76d | [
"for entry in self._async_current_entries():\n if entry.data.get(CONF_HOST) == host and entry.data[CONF_PORT] == port:\n if updates is not None:\n changed = self.hass.config_entries.async_update_entry(entry, data={**entry.data, **updates})\n if changed and reload_on_update and (entry... | <|body_start_0|>
for entry in self._async_current_entries():
if entry.data.get(CONF_HOST) == host and entry.data[CONF_PORT] == port:
if updates is not None:
changed = self.hass.config_entries.async_update_entry(entry, data={**entry.data, **updates})
... | Handle a config flow for DSMR. | DSMRFlowHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DSMRFlowHandler:
"""Handle a config flow for DSMR."""
def _abort_if_host_port_configured(self, port: str, host: str=None, updates: Optional[Dict[Any, Any]]=None, reload_on_update: bool=True):
"""Test if host and port are already configured."""
<|body_0|>
async def async_... | stack_v2_sparse_classes_36k_train_014397 | 6,055 | permissive | [
{
"docstring": "Test if host and port are already configured.",
"name": "_abort_if_host_port_configured",
"signature": "def _abort_if_host_port_configured(self, port: str, host: str=None, updates: Optional[Dict[Any, Any]]=None, reload_on_update: bool=True)"
},
{
"docstring": "Handle the initial ... | 2 | stack_v2_sparse_classes_30k_train_001505 | Implement the Python class `DSMRFlowHandler` described below.
Class description:
Handle a config flow for DSMR.
Method signatures and docstrings:
- def _abort_if_host_port_configured(self, port: str, host: str=None, updates: Optional[Dict[Any, Any]]=None, reload_on_update: bool=True): Test if host and port are alread... | Implement the Python class `DSMRFlowHandler` described below.
Class description:
Handle a config flow for DSMR.
Method signatures and docstrings:
- def _abort_if_host_port_configured(self, port: str, host: str=None, updates: Optional[Dict[Any, Any]]=None, reload_on_update: bool=True): Test if host and port are alread... | ed4ab403deaed9e8c95e0db728477fcb012bf4fa | <|skeleton|>
class DSMRFlowHandler:
"""Handle a config flow for DSMR."""
def _abort_if_host_port_configured(self, port: str, host: str=None, updates: Optional[Dict[Any, Any]]=None, reload_on_update: bool=True):
"""Test if host and port are already configured."""
<|body_0|>
async def async_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DSMRFlowHandler:
"""Handle a config flow for DSMR."""
def _abort_if_host_port_configured(self, port: str, host: str=None, updates: Optional[Dict[Any, Any]]=None, reload_on_update: bool=True):
"""Test if host and port are already configured."""
for entry in self._async_current_entries():
... | the_stack_v2_python_sparse | homeassistant/components/dsmr/config_flow.py | tchellomello/home-assistant | train | 8 |
eb329a3c3167ea5b7392eeeda6985c37d3a3b532 | [
"classes = {b'\\xff': Header, b'[': Package}\nif not packetPrefix in classes:\n return None\nreturn classes[packetPrefix]",
"if data is None:\n return\npacketPrefix = data[:1]\nCLASS = self.getClass(packetPrefix)\nif not CLASS:\n raise Exception('Packet %s is not found' % binascii.hexlify(packetPrefix).d... | <|body_start_0|>
classes = {b'\xff': Header, b'[': Package}
if not packetPrefix in classes:
return None
return classes[packetPrefix]
<|end_body_0|>
<|body_start_1|>
if data is None:
return
packetPrefix = data[:1]
CLASS = self.getClass(packetPrefix... | Packet factory | PacketFactory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PacketFactory:
"""Packet factory"""
def getClass(cls, packetPrefix):
"""Returns a tag class by number @param packetPrefix: one byte buffer"""
<|body_0|>
def getInstance(self, data=None):
"""Returns a tag instance by its number"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_014398 | 15,657 | no_license | [
{
"docstring": "Returns a tag class by number @param packetPrefix: one byte buffer",
"name": "getClass",
"signature": "def getClass(cls, packetPrefix)"
},
{
"docstring": "Returns a tag instance by its number",
"name": "getInstance",
"signature": "def getInstance(self, data=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004592 | Implement the Python class `PacketFactory` described below.
Class description:
Packet factory
Method signatures and docstrings:
- def getClass(cls, packetPrefix): Returns a tag class by number @param packetPrefix: one byte buffer
- def getInstance(self, data=None): Returns a tag instance by its number | Implement the Python class `PacketFactory` described below.
Class description:
Packet factory
Method signatures and docstrings:
- def getClass(cls, packetPrefix): Returns a tag class by number @param packetPrefix: one byte buffer
- def getInstance(self, data=None): Returns a tag instance by its number
<|skeleton|>
c... | 4a4bc730252ece695b2773388812e2d59d4947ce | <|skeleton|>
class PacketFactory:
"""Packet factory"""
def getClass(cls, packetPrefix):
"""Returns a tag class by number @param packetPrefix: one byte buffer"""
<|body_0|>
def getInstance(self, data=None):
"""Returns a tag instance by its number"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PacketFactory:
"""Packet factory"""
def getClass(cls, packetPrefix):
"""Returns a tag class by number @param packetPrefix: one byte buffer"""
classes = {b'\xff': Header, b'[': Package}
if not packetPrefix in classes:
return None
return classes[packetPrefix]
... | the_stack_v2_python_sparse | lib/handlers/autolink/packets.py | maprox/pipe | train | 4 |
3fbb41778a5cb4febca5f851543837f52ddf960c | [
"if not isinstance(vref_vs_tau, list):\n vref_vs_tau = [vref_vs_tau]\nif len(vref_vs_tau) == 1:\n plt.plot(vref_vs_tau[0][:, 0], vref_vs_tau[0][:, 1], 'k')\nelse:\n for vref in vref_vs_tau:\n plt.plot(vref[:, 0], vref[:, 1])\nplt.xlabel('Time (a.u.)')\nplt.ylabel('$\\\\mathrm{E_{ref}}$ ($\\\\mathrm{... | <|body_start_0|>
if not isinstance(vref_vs_tau, list):
vref_vs_tau = [vref_vs_tau]
if len(vref_vs_tau) == 1:
plt.plot(vref_vs_tau[0][:, 0], vref_vs_tau[0][:, 1], 'k')
else:
for vref in vref_vs_tau:
plt.plot(vref[:, 0], vref[:, 1])
plt.x... | A very basic plotting class that will use matplotlib to generate various plots using results from PyVibDMC/AnalyzeWfn/SimInfo. | Plotter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Plotter:
"""A very basic plotting class that will use matplotlib to generate various plots using results from PyVibDMC/AnalyzeWfn/SimInfo."""
def plt_vref_vs_tau(vref_vs_tau, save_name='vref_vs_tau.png'):
"""Takes in the vref vs tau array from a DMC sim and plots it. Can also take in... | stack_v2_sparse_classes_36k_train_014399 | 4,642 | permissive | [
{
"docstring": "Takes in the vref vs tau array from a DMC sim and plots it. Can also take in many vref_vs_tau arrays and plot them successively :param vref_vs_tau: The vref_vs_tau array from the *sim_info.hdf5 file. Can be a list of these as well. :type vref_vs_tau: str or list :param save_name: The name of the... | 4 | stack_v2_sparse_classes_30k_train_002370 | Implement the Python class `Plotter` described below.
Class description:
A very basic plotting class that will use matplotlib to generate various plots using results from PyVibDMC/AnalyzeWfn/SimInfo.
Method signatures and docstrings:
- def plt_vref_vs_tau(vref_vs_tau, save_name='vref_vs_tau.png'): Takes in the vref v... | Implement the Python class `Plotter` described below.
Class description:
A very basic plotting class that will use matplotlib to generate various plots using results from PyVibDMC/AnalyzeWfn/SimInfo.
Method signatures and docstrings:
- def plt_vref_vs_tau(vref_vs_tau, save_name='vref_vs_tau.png'): Takes in the vref v... | c8ef4970d91d32f08fd938de4d2bcbc1fa7f81b4 | <|skeleton|>
class Plotter:
"""A very basic plotting class that will use matplotlib to generate various plots using results from PyVibDMC/AnalyzeWfn/SimInfo."""
def plt_vref_vs_tau(vref_vs_tau, save_name='vref_vs_tau.png'):
"""Takes in the vref vs tau array from a DMC sim and plots it. Can also take in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Plotter:
"""A very basic plotting class that will use matplotlib to generate various plots using results from PyVibDMC/AnalyzeWfn/SimInfo."""
def plt_vref_vs_tau(vref_vs_tau, save_name='vref_vs_tau.png'):
"""Takes in the vref vs tau array from a DMC sim and plots it. Can also take in many vref_vs... | the_stack_v2_python_sparse | pyvibdmc/analysis/plotter.py | rjdirisio/pyvibdmc | train | 10 |
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