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Imports: ```python import typing ``` Type definitions: Input Types: Optional[dict] Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Optional[dict]): if v1: self._source_data['tool_shed_repository'] = {'name': v1['name'], 'owner': v1['owner'], 'tool_shed': v1['tool_shed...
Imports: ```python import typing ``` Type definitions: Input Types: pd.DataFrame Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: pd.DataFrame): v2 = [',', ';', ':', '{', '}', '(', ')', '=', '>', '<', '.', '!', '?'] v3 = {} for v4 in v1.columns: v5 = v4.lower() ...
Imports: ```python import typing ``` Type definitions: Input Types: Iterable[Any] Output Type: Dict[Any, int] Dependencies: Function Name: v0 Function: ```python def v0(v1: Iterable[Any]) -> Dict[Any, int]: v2: Dict[Any, int] = {} for v3 in v1: if v2.get(v3) is None: v2[v3] = 0 v2[...
Imports: ```python import os import typing ``` Type definitions: Input Types: Output Type: AsyncIterator[Tuple[str, Dict]] Dependencies: Function Name: v0 Function: ```python async def v0(self) -> AsyncIterator[Tuple[str, Dict]]: v1 = os.listdir(self.store) v2 = '.json' v3 = len(v2) for v4 in v1: ...
Imports: ```python import typing ``` Type definitions: Input Types: np.array, np.array, np.array, np.array, int Output Type: tuple Dependencies: Function Name: v0 Function: ```python def v0(self, v1: np.array, v2: np.array, v3: np.array=None, v4: np.array=None, v5: int=None) -> tuple: (v6, v7) = (v1.shape[0], v2....
Imports: ```python import subprocess import typing ``` Type definitions: Input Types: str, str, Any Output Type: subprocess.CompletedProcess Dependencies: Function Name: v0 Function: ```python def v0(v1: str, v2: str, v3) -> subprocess.CompletedProcess: v4 = subprocess.run(f'ffmpeg -y -fflags +discardcorrupt -i {...
Imports: ```python import logging import typing ``` Type definitions: Input Types: bool Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: bool=True) -> None: logging.info('SyncServer is started') self._server = self._loop.run_until_complete(self._server) logging.info(f...
Imports: ```python import typing ``` Type definitions: Input Types: str, list, Any Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: str, v2: list, v3='ID'): v4 = None for v5 in v2: if v1 == v5.get(v3, ''): v4 = v5 return v4 ```
Imports: ```python import datetime import typing ``` Type definitions: Input Types: str Output Type: datetime.time Dependencies: Function Name: v0 Function: ```python def v0(v1: str) -> datetime.time: (v2, v3) = [int(num) for v4 in v1.split(':')] return datetime.time(hour=v2, minute=v3) ```
Imports: ```python import typing ``` Type definitions: Input Types: int Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int): v2 = {'controller': 'Media', 'action': 'favMedia', 'media_id': str(v1)} return self.network.post(v2) ```
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str): if self.fix_hint is not None: self.fix_hint += '\n' + v1 else: self.fix_hint = v1 ```
Imports: ```python import typing ``` Type definitions: Input Types: Dict, Any Output Type: Dict Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Dict, v2=None) -> Dict: if v2: return {'objects': v1, 'coordinates': v2} else: return {'objects': [v1], 'coordinates': v1.get('co...
Imports: ```python import matplotlib from matplotlib import pyplot as plt import typing ``` Type definitions: Input Types: np.ndarray, Optional[str], Optional[str], Optional[str], str, str Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: np.ndarray, v2: Optional[str]=None, v3: Op...
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: np.array Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: np.array) -> None: self.D[-1] = self.D_outLayer(self.A[-1], v1.reshape(-1, self.layer_size[-1])) * self.derivative[self.lastLayerAc...
Imports: ```python import typing ``` Type definitions: Input Types: ast.Lambda Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: ast.Lambda): for v2 in v1.args.defaults + v1.args.kw_defaults: if v2 is None: continue self.visit(v2) v3 = self._get_...
Imports: ```python import typing ``` Type definitions: Input Types: CoolParser.BoolContext Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: CoolParser.BoolContext): v1.type = 'Bool' self.types[v1] = 'Bool' ```
Imports: ```python import typing ``` Type definitions: Input Types: Union[list, str], int, str Output Type: List[Dict] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Union[list, str]=None, v2: int=-1, v3: str='all', **v4) -> List[Dict]: v5 = False v6 = [] v7 = 0 v8 = 100 v9 =...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: Dict[str, int] Dependencies: Function Name: v0 Function: ```python def v0(self) -> Dict[str, int]: v1: List[Coin] = self.bundle.additions() v2: List[Coin] = self.bundle.removals() v3: List[Coin] = list(filter(lambda c: c not...
Imports: ```python from argparse import ArgumentParser, RawTextHelpFormatter import typing ``` Type definitions: Input Types: Output Type: ArgumentParser Dependencies: Function Name: v0 Function: ```python def v0() -> ArgumentParser: v1 = ArgumentParser(description='CloudWatch Metrics Generator', formatter_class...
Imports: ```python import typing ``` Type definitions: Input Types: Any Output Type: bool Dependencies: Function Name: v0 Function: ```python def v0(self, v1) -> bool: if v1 in (0, 1, 2, 3): self.drive = v1 return True return False ```
Imports: ```python import shutil import subprocess import typing ``` Type definitions: Input Types: Output Type: bool Dependencies: Function Name: v0 Function: ```python def v0() -> bool: if shutil.which('ldc2'): return True elif shutil.which('ldc'): return True elif shutil.which('gdc'): ...
Imports: ```python import typing ``` Type definitions: Input Types: int, int Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int, v2: int) -> None: self.waiting = v2 self.total_cost_path = v2 self.path.append(self.position) self.prev_position = self.position ...
Imports: ```python import torch from torch import nn import typing ``` Type definitions: Input Types: torch.Tensor Output Type: torch.Tensor Dependencies: Function Name: v0 Function: ```python def v0(self, v1: torch.Tensor) -> torch.Tensor: v2 = torch.randn_like(v1) * self.sigma return self.base_classifier((v...
Imports: ```python import typing ``` Type definitions: Input Types: dict Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(v1: dict) -> None: for v2 in range(1, 25): v1['slot' + str(v2)] = 'empty.jpg' ```
Imports: ```python import typing ``` Type definitions: Input Types: Iterable[str], int, Container[str] Output Type: Iterator[str] Dependencies: ```python def v0(v1: str, v2: Container[str]) -> Iterator[str]: v3 = [] for v4 in v1: if v4 in v2: if v3: yield ''.join(v3) ...
Imports: ```python import typing ``` Type definitions: Input Types: str, int Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: int) -> int: v3 = [] for v4 in v1: v5 = ord(v4) - 96 if v5 < 10: v3.append(v5) else: v3.ex...
Imports: ```python import typing ``` Type definitions: ```python v0 = TypeVar('_ArgT') ``` ```python v1 = TypeVar('_OtherReturnT_co', covariant=True) ``` ```python v2 = TypeVar('_ReturnT') ``` ```python v3 = TypeVar('_ReturnT_co', covariant=True) ``` ```python v4 = TypeVar('_SendT') ``` ```python v5 = TypeVar('_SendT_c...
Imports: ```python from math import pi from qiskit.converters import circuit_to_dag from qiskit.transpiler.basepasses import TransformationPass from qiskit.dagcircuit.dagcircuit import DAGCircuit from qiskit.extensions.quantum_initializer import isometry from qiskit.quantum_info.synthesis import one_qubit_decompose fro...
Imports: ```python import typing ``` Type definitions: Input Types: int Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int) -> int: if v1 == -1: self.SetFocusedField(self.new_name) return 1 ```
Imports: ```python import typing ``` Type definitions: ```python class v0: def __init__(self) -> None: super().__init__() self.__container: typing.Optional[CanvasItemComposition] = None self.__canvas_size: typing.Optional[Geometry.IntSize] = None self.__canvas_origin: typing.Optiona...
Imports: ```python import os import typing ``` Type definitions: Input Types: Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self) -> int: v1 = os.environ.get('JSM_NAMESPACE_LOCAL_RANK') if v1 is None: raise ValueError('Cannot determine local rank. Environment variable `J...
Imports: ```python import cv2 import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: v1 = self.cap.get(cv2.CAP_PROP_FPS) self.audio = self.audio._spawn(self.audio.raw_data, overrides={'frame_rate': int(v1)}) self.audio....
Imports: ```python import typing ``` Type definitions: Input Types: List[str] Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self, v1: List[str]) -> int: (v2, v3) = (dict(), []) for v4 in set(v1): v5 = v2 for v6 in v4[::-1]: v5[v6] = v5.get(v6, dict()) ...
Imports: ```python import random import typing ``` Type definitions: Input Types: Any, Dict[Text, Any] Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1, v2: Dict[Text, Any]): v3 = ['Your apartment viewing has been successfuly scheduled.', 'That time is unavailable. Please try another...
Imports: ```python import os import re import typing ``` Type definitions: Input Types: int Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: int): v2 = os.listdir('input/regi') for v3 in v2: try: v4 = int(re.split(' |-', v3)[0]) except ValueError: ...
Imports: ```python import typing ``` Type definitions: Input Types: List[str] Output Type: int Dependencies: ```python def v0(v1: str) -> int: v2 = v1.replace('F', '0').replace('B', '1').replace('L', '0').replace('R', '1') return int(v2, 2) ``` ```python def v3(v4: List[str]) -> List[int]: return [v0(x) fo...
Imports: ```python import numpy as np import pandas._libs.window as libwindow from pandas.compat._optional import import_optional_dependency from pandas.compat.numpy import function as nv from pandas.util._decorators import Appender, Substitution, cache_readonly from pandas.core.dtypes.common import ensure_float64, is_...
Imports: ```python import typing ``` Type definitions: ```python class v0(object): def __init__(self, v1: datetime.datetime, v2: int, v3: str): self.time = v1 self.duration = v2 self.url = v3 def v4(self): return f'{self.time}, {self.duration}, {self.url}' ``` Input Types: str,...
Imports: ```python import typing ``` Type definitions: Input Types: events.Event, Dict[str, Any] Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: events.Event, v2: Dict[str, Any]): for v3 in self.event_handlers[type(v1)]: v3(v1, self.uow, v2) ```
Imports: ```python import typing ``` Type definitions: ```python class v0: def __init__(self, v1: str='', v2: str='', v3: str='', v4: str='', v5: str=''): """ :param prov: :param city: :param area: :param area_code: """ self.prov = v1 self.city = v2 ...
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(v1: str) -> int: v2 = 131 v3 = 1 << 31 v4 = 0 for v5 in v1: v4 = (v4 * v2 + (ord(v5) - ord('a'))) % v3 return v4 ```
Imports: ```python from json import loads, dumps import binascii import typing ``` Type definitions: Input Types: str Output Type: Any Dependencies: ```python def v0(v1: str): v2 = binascii.unhexlify(v1[:32]) v3 = binascii.unhexlify(v1[32:]) v4 = AES.new(key[3:] + b'tmp', AES.MODE_ECB).decrypt(v2) v5 =...
Imports: ```python from typing import Generator, List, Union, cast import torch import typing ``` Type definitions: ```python v0 = Union[torch.cuda.Stream, CPUStreamType] ``` Input Types: v0, v0 Output Type: None Dependencies: ```python def v1(v2: v0) -> torch.cuda.Stream: return cast(torch.cuda.Stream, v2) ``` ```...
Imports: ```python import typing ``` Type definitions: Input Types: str, str Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1: str, v2: str) -> str: if '/' in v2: v3 = v2.split('/')[0] return f'{v1}.{v3}' else: return v1 ```
Imports: ```python import asyncio import typing ``` Type definitions: Input Types: Any, float Output Type: Any Dependencies: Function Name: v0 Function: ```python async def v0(v1, v2: float): v3 = await asyncio.gather(*v1) await asyncio.sleep(v2) return v3 ```
Imports: ```python import typing ``` Type definitions: Input Types: str, str Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: str='') -> None: if v2: self.run(f'{v1} -o {v2}') else: self.run(v1) ```
Imports: ```python import typing ``` Type definitions: Input Types: str, dict Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: dict): v3: dict = {} for v4 in v2: for (v5, v6) in v2[v4].get(v1, {}).items(): v3[f'{v5}{v4}'] = v6 v7 = '\n'.joi...
Imports: ```python import numpy as np import os import logging import typing ``` Type definitions: Input Types: str Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str) -> None: if self.poles is None: logging.error('Nothing to export; Poles have not been fitted.') ...
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: bool Dependencies: ```python def v0(v1: str) -> bool: for v2 in range(len(v1) - 1): if v1[v2] == v1[v2 + 1]: return True return False ``` ```python def v3(v4: str) -> bool: for v5 in invalid: if...
Imports: ```python import typing ``` Type definitions: Input Types: int Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int) -> int: if v1 in self.hash_map: v2 = self.hash_map[v1] self.delete_node(v2) self.insert_begin(v2) return v2.val ret...
Imports: ```python import typing ``` Type definitions: ```python class v0: v1: Union[None, Connection] = None v2: str def __init__(self: v0, v3: str) -> None: """Initialize database. Args: self (Database): Itself. database_path (str): Path to database file. ...
Imports: ```python import typing ``` Type definitions: Input Types: List[str] Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self, v1: List[str]) -> str: if not v1: return '' for (v2, v3) in enumerate(min(v1, key=len)): for v4 in v1: if v4[v2] != v3: ...
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: int Output Type: list Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int) -> list: v2 = {'0': 'good', '1': 'LITTLE_COVERAGE', '2': 'SMALL_DELTA_CHI2', '3': 'NEGATIVE_MODEL', '4': 'MANY_OUTLIERS', '5': 'Z_F...
Imports: ```python import typing ``` Type definitions: Input Types: str, tuple Output Type: Any Dependencies: Function Name: v0 Function: ```python async def v0(self, v1: str, v2: tuple=None): assert self.conn_pool is not None async with self.conn_pool.acquire() as v3: async with v3.cursor() as v4: ...
Imports: ```python import typing ``` Type definitions: Input Types: Optional[str] Output Type: dict Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Optional[str]='') -> dict: v1 = v1 if v1 != '' else self.rule_name v2 = self.cloudwatch_events.list_targets_by_rule(Rule=v1) v3 = [target...
Imports: ```python import requests import json import typing ``` Type definitions: Input Types: Any, Any Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self, v1, v2=None) -> str: try: v3 = requests.get(self.REST_BASE_URL.format(self._host, self._jsonport, v1), timeout=self.TIM...
Imports: ```python import typing ``` Type definitions: Input Types: str, int, Type[Exception] Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: int, v3: Type[Exception]): if v1.startswith('next_'): if not self._rollout.continuous: raise v3('Access t...
Imports: ```python import argparse import pathlib import torch import torch.nn as nn import typing ``` Type definitions: Input Types: Output Type: argparse.Namespace Dependencies: Function Name: v0 Function: ```python def v0() -> argparse.Namespace: v1 = argparse.ArgumentParser() v1.add_argument('--policy_va...
Imports: ```python import torch from torch import Tensor import typing ``` Type definitions: Input Types: Tensor, int, Tensor, int, int, int, Optional[float], bool Output Type: Tensor Dependencies: ```python def v0(v1: Tensor, v2: float=1.0) -> Tensor: return v1.pow(2.0).sum(-1).pow(0.5 * v2) ``` Function Name: v3...
Imports: ```python import os import csv from pathlib import Path import pickle import typing ``` Type definitions: Input Types: pd.DataFrame, str, str, str, str Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(v1: pd.DataFrame, v2: str='USERID', v3: str='ITEMID', v4: str='TIMESTAMP', v5: s...
Imports: ```python import typing ``` Type definitions: Input Types: 'list of Album', 'Function on Albums' Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(v1: 'list of Album', v2: 'Function on Albums') -> None: v1.sort(key=v2) return ```
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: Dict Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str) -> Dict: v2 = dict() for (v3, v4) in self.processors.items(): v2[v3] = v4.read_from_disk(v1) return v2 ```
Imports: ```python import typing ``` Type definitions: Input Types: Any Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(v1) -> None: with open('retiredcommenthashes.txt', 'a') as v2: v2.write(v1 + '\n') ```
Imports: ```python import typing ``` Type definitions: Input Types: int, List[str] Output Type: float Dependencies: Function Name: v0 Function: ```python def v0(v1: int, v2: List[str]) -> float: if v1 > 0: return 1.0 if v2: return 0.0 return -1.0 ```
Imports: ```python import numpy as np import pandas as pd import typing ``` Type definitions: Input Types: int, pd.DataFrame, List[float], int Output Type: pd.DataFrame Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int, v2: pd.DataFrame=None, v3: List[float]=None, v4: int=None) -> pd.DataFrame:...
Imports: ```python import typing ``` Type definitions: Input Types: str, str, bool Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: str, v3: bool=False) -> str: v4 = self.siunitx_num_to_plain_latex(v1, in_math=True) v5 = self.siunitx_si_to_plain_latex(v2, in_math=...
Imports: ```python import logging import numpy as np import typing ``` Type definitions: Input Types: Any, Any, Union[str, Callable], float, int, int Output Type: Any Dependencies: ```python def v0(v1: np.ndarray, v2: Union[str, Callable]='euclidean', v3: float=-1, v4: int=30, v5: int=-1) -> TSNEEmbedding: v6 = v1...
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: Any Dependencies: ```python def v0(v1: str) -> int: while True: try: v2 = int(input(v1)) return v2 except Exception as e: print(e) ``` ```python def v3(v4: List, v5: bool=False, ...
Imports: ```python import typing ``` Type definitions: ```python @pai_dataclass @dataclass class v0(AIPTrainerParams[CalamariScenarioParams, CalamariDefaultTrainerPipelineParams]): v1: int = SavedCalamariModel.VERSION v2: bool = field(default=True, metadata=pai_meta(help='When training with augmentations usuall...
Imports: ```python import typing ``` Type definitions: Input Types: th.Tensor, th.Tensor, th.Tensor, th.Tensor, th.Tensor Output Type: th.Tensor Dependencies: Function Name: v0 Function: ```python def v0(self, v1: th.Tensor, v2: th.Tensor, v3: th.Tensor, v4: th.Tensor, v5: th.Tensor) -> th.Tensor: if v5 is None: ...
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: np.ndarray, int, Union[float, Tuple[float, float, float]] Output Type: np.ndarray Dependencies: Function Name: v0 Function: ```python def v0(v1: np.ndarray, v2: int=10, v3: Union[float, Tuple[float, float, float]]=200) -> np.ndarra...
Imports: ```python import os import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: self.datapath = os.path.join(os.getcwd(), 'data') self.results = os.path.join(os.getcwd(), 'src', 'results') self.mockimg = [os.path.jo...
Imports: ```python import typing ``` Type definitions: Input Types: dict Output Type: dict Dependencies: Function Name: v0 Function: ```python def v0(v1: dict=None) -> dict: if v1 is None: v1 = {} if 'headers' not in v1: v1['headers'] = {} v2 = {'Content-type': 'application/json', 'Accept'...
Imports: ```python import typing ``` Type definitions: ```python class v0: def __init__(self) -> None: self.__preferred_width: typing.Optional[typing.Union[int, float]] = None self.__preferred_height: typing.Optional[typing.Union[int, float]] = None self.__preferred_aspect_ratio: typing.Opt...
Imports: ```python import typing ``` Type definitions: Input Types: List[int] Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: List[int]) -> None: self.enhance_list = v1 self.enhancer_priority = [[] for v2 in v1] ```
Imports: ```python import typing ``` Type definitions: Input Types: np.array, bool Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(v1: np.array, v2: bool) -> None: v1[:, 1] -= 10.2 v1[:, 1] *= -1 if v2: v1[:, 1] *= 1 / 1.02 ```
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: Dict Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str) -> Dict: v2 = self.list_nodes(v1) v3 = [] for (v4, v5) in v2['data'].items(): v6 = self.start_node(v1, v4) v3.append(v6) r...
Imports: ```python import typing ``` Type definitions: Input Types: str, str Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: str='') -> str: v3 = ', '.join((str(a) for v4 in self.argument_types)) return f'{self.return_type} (*{v2}{v1}) ({v3})' ```
Imports: ```python import math import typing ``` Type definitions: Input Types: int Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: int): v2 = [] while v1 % 2 == 0: v2.append(2) v1 = v1 // 2 for v3 in range(3, int(math.sqrt(v1)) + 1, 2): while v1 % v...
Imports: ```python import re import typing ``` Type definitions: Input Types: str Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1: str) -> str: v2 = re.sub('([a-z])([A-Z])', '\\g<1> \\g<2>', v1) v2 = v2.lower() v2 = re.sub('%', '_percent', v2) v2 = re.sub('[=-\\\\.,]', '...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: for v1 in range(len(self.polymer_template) - 1): v2 = self.polymer_template[v1:v1 + 2] self.d[v2] = 1 if v1 == len(self.polymer_t...
Imports: ```python import typing ``` Type definitions: Input Types: int, fractions.Fraction, fractions.Fraction Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(v1: int, v2: fractions.Fraction, v3: fractions.Fraction) -> int: if v2 != v3: v1 = int(v1 * v2 / v3) return v1 ```
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: Tuple[str, int, int, str] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str) -> Tuple[str, int, int, str]: v2 = v1.splitlines()[0] (v3, v4) = v2.split(';frame=') v4 = int(v4) v5 = self.__get_con...
Imports: ```python import torch import typing ``` Type definitions: Input Types: Any Output Type: torch.nn.Module Dependencies: Function Name: v0 Function: ```python def v0(v1) -> torch.nn.Module: v2 = torch.nn.Sequential(torch.nn.Conv2d(in_channels=3, out_channels=32, kernel_size=(3, 3)), torch.nn.ReLU(), torch....
Imports: ```python import typing ``` Type definitions: Input Types: Dict[str, Any] Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: Dict[str, Any]): if 'optimizer' in v1: raise ValueError('The DeepSpeed configuration specifies an optimizer, but the Mosaic trainer will overri...
Imports: ```python import numpy as np import pandas as pd from sklearn.feature_extraction.text import TfidfVectorizer from tqdm import tqdm import typing ``` Type definitions: Input Types: nx.Graph, List[Tuple[str, str]], str, int Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: nx.Grap...
Imports: ```python import typing ``` Type definitions: ```python v0 = v1 = v2 = Dict[str, Any] ``` Input Types: str, str Output Type: Generator[v2, None, None] Dependencies: Function Name: v3 Function: ```python async def v3(self, v4: str, v5: str=None) -> Generator[v2, None, None]: v6 = dict(instance=v4, project=...
Imports: ```python import typing ``` Type definitions: Input Types: Any Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1) -> str: v2 = v1[:-1] v3 = '' for v4 in v2: if v4.endswith('r'): v4 = v4[:-1] v3 = v3 + v4 + ' ' return v3.strip() ```
Imports: ```python from shutil import copy from pathlib import Path import typing ``` Type definitions: Input Types: argparse.Namespace Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(v1: argparse.Namespace) -> None: v2 = Path(v1.data_dir) v3: str = v1.package v4: str = v1.cel...
Imports: ```python import re import typing ``` Type definitions: Input Types: Text Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: Text): v2 = '[a-z0-9]{8}-[a-z0-9]{4}-[a-z0-9]{4}-[a-z0-9]{4}-[a-z0-9]{12}' v3 = re.findall(v2, v1) if not v3: v4 = None else: ...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: v1 = self.parser.parse('token_with_multiple_values') assert v1 in {'value 1', 'value 2', 'value 3'} ```
Imports: ```python from datetime import date, datetime from urllib import parse import typing ``` Type definitions: Input Types: Any, int Output Type: None Dependencies: ```python def v0(v1: Optional[int], v2: Optional[str], v3: FormData) -> Tuple[int, Optional[str]]: v4 = v3.get('datasource', '') if '__' in v...
Imports: ```python import typing ``` Type definitions: ```python class v0: def __init__(self, v1: List[Card]): if len(v1) < 10 or len(v1) > 10: raise Exception('Invalid number of cards') self.cards = v1 def v2(self): for (v3, v4) in enumerate(self.cards): v2('Ca...
Imports: ```python import typing ``` Type definitions: Input Types: metadata_store_pb2.Artifact, Set[Text] Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: metadata_store_pb2.Artifact, v2: Set[Text]) -> None: if not v1.id: raise ValueError('Artifact id missing for %s'...
Imports: ```python import hashlib import typing ``` Type definitions: Input Types: str, bytes Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: bytes) -> str: v3 = int(hashlib.blake2b(v1.encode(), digest_size=2, salt=v2).hexdigest(), base=16) return hex(v3).lstrip(...
Imports: ```python import typing ``` Type definitions: Input Types: torch.Tensor Output Type: torch.Tensor Dependencies: ```python def v0(v1, v2, v3): try: act_out[name] = v2[0].detach() except (IndexError, AttributeError): act_out[name] = None handles[name].remove() ``` ```python def v4(v5...
Imports: ```python from urllib.parse import urljoin import typing ``` Type definitions: Input Types: Output Type: list Dependencies: ```python def v0(v1, v2=None): v3 = http.requests_retry_session() v3.auth = (settings.SONARQUBE_TOKEN, '') v4 = urljoin(settings.SONARQUBE_URL, v1) v5 = v3.get(v4, param...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python async def v0(self) -> None: if not self._client: raise AttributeError('HTTPClient not found!') await self._client.delete_channel(channel_id=int(self.id)) ```
Imports: ```python import typing ``` Type definitions: Input Types: Tensor, int Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Tensor, v2: int): if v1 is None: raise ValueError('param data cannot be set to None') if v1.shape != self._params[v2].data.shape: ...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: if self._data: return v1 = self._check_configuration() self._data = [] if self.num_qubits == 0: return if self._initial_s...