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Imports: ```python import numpy import typing ``` Type definitions: Input Types: Any, Any, bool, bool Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1, v2, v3: bool=False, v4: bool=False): v5 = 1.0 / v2 v6 = numpy.square(v5) v7 = v1 * 180.0 / numpy.pi v8 = 2.0 / numpy.pi ...
Imports: ```python import typing ``` Type definitions: ```python class v0(object): def __init__(self, v1, v2, v3): self.example_id = v1 self.choices_features = [{'input_ids': input_ids, 'input_mask': input_mask, 'segment_ids': segment_ids} for (v4, v5, v6, v7) in v2] self.label = v3 ``` ```...
Imports: ```python import typing ``` Type definitions: ```python class v0(DataPoint): def __init__(self, v1: List[Token]): super().__init__() self.tokens = v1 self.start_pos = None self.end_pos = None if v1: self.start_pos = v1[0].start_position self....
Imports: ```python import datetime import typing ``` Type definitions: Input Types: Output Type: Dict[str, Any] Dependencies: Function Name: v0 Function: ```python def v0(self) -> Dict[str, Any]: v1 = self.an_enum_value.value v2 = self.some_dict if isinstance(self.a_camel_date_time, datetime.datetime): ...
Imports: ```python import typing ``` Type definitions: Input Types: Any Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self, v1) -> int: self.stack = [] self.res = float('inf') self.prev = -float('inf') v2 = v1 while len(self.stack) != 0 or v2 != None: while v2...
Imports: ```python import os import shutil from datetime import datetime from logging import warning import pandas as pd import typing ``` Type definitions: Input Types: Any, Any, Any, str, str, Any Output Type: Any Dependencies: ```python def v0(v1, v2): v3 = '_TRAIN.tsv' v4 = {} for v5 in os.listdir(v1):...
Imports: ```python import typing ``` Type definitions: Input Types: Any, list Output Type: float Dependencies: Function Name: v0 Function: ```python def v0(self, v1, v2: list) -> float: v3 = 0.0 for (v4, v5) in zip(self.measurables, v2): v3 += v4.eval(v1, v5) return v3 ```
Imports: ```python import typing ``` Type definitions: Input Types: List[int] Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(v1: List[int]) -> int: try: v2 = [i for (v3, v4) in enumerate(v1) if (v3 + 1) % 1 == -1][0] except: return False return v1[v2 + 2] ```
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self) -> int: v1 = 0 if self.is_well_formed(): for v2 in self.faces.values(): if self.is_valid_face(v2): v1 += self.get_num_match...
Imports: ```python from collections import Counter import typing ``` Type definitions: Input Types: List[str], int, int Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self, v1: List[str], v2: int, v3: int) -> int: v4 = [[0] * (v3 + 1) for v5 in range(v2 + 1)] for (v6, v7) in [(c['...
Imports: ```python from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister from qiskit.quantum_info.random import random_unitary import typing ``` Type definitions: Input Types: Any Output Type: dict Dependencies: Function Name: v0 Function: ```python def v0(v1) -> dict: v2 = {'u1': [], 'u2': [], 'u...
Imports: ```python import re import typing ``` Type definitions: Input Types: bytes Output Type: bool Dependencies: Function Name: v0 Function: ```python def v0(self, v1: bytes) -> bool: v2 = self.last_chunk + v1 v3 = len(self.data) - len(self.last_chunk) self.data += v1 self.last_chunk = v1 for v...
Imports: ```python import logging import typing ``` Type definitions: Input Types: Output Type: logging.Logger Dependencies: Function Name: v0 Function: ```python def v0() -> logging.Logger: v1 = logging.getLogger() v1.setLevel(logging.INFO) v2 = logging.Formatter('%(asctime)s %(levelname)s [%(name)s]: %...
Imports: ```python import typing ``` Type definitions: Input Types: Dict[str, Union[str, List[str], Dict[str, Any], int, None]], Optional[str] Output Type: Any Dependencies: Function Name: v0 Function: ```python async def v0(self, v1: Dict[str, Union[str, List[str], Dict[str, Any], int, None]], v2: Optional[str]=None...
Imports: ```python import typing ``` Type definitions: Input Types: Any Output Type: {} Dependencies: Function Name: v0 Function: ```python def v0(self, v1) -> {}: for v2 in self.my_allplane_infos: if v2['ID'] == v1: return v2 return None ```
Imports: ```python import typing ``` Type definitions: Input Types: int Output Type: bytes Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int) -> bytes: v2 = (v1 - self.first_frame_idx) * self.bytes_per_frame return self.data[v2:v2 + self.bytes_per_frame] ```
Imports: ```python import logging import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: logging.debug('close grpc') self.client.close() ```
Imports: ```python import typing ``` Type definitions: ```python class v0(Visitable, Generic[_T]): v1 = True v2 = False v3 = False v4 = False v5 = False v6 = False v7 = False 'Render bind casts for :attr:`.BindTyping.RENDER_CASTS` mode.\n\n If True, this type (usually a dialect level ...
Imports: ```python import json import typing ``` Type definitions: Input Types: str Output Type: Any Dependencies: ```python def v0(v1: dict) -> Response: if v1['tag'] == 'ExecCaptureResponse': if v1['success']: return Response.from_value(v1['content']) else: return Response...
Imports: ```python import copy import numpy as np import torch import typing ``` Type definitions: Input Types: List[np.ndarray], np.ndarray, int Output Type: torch.Tensor Dependencies: ```python def v0(v1: List[np.ndarray], v2: int, v3: int) -> np.ndarray: assert len(v1) > 0, 'COCOAPI does not support empty polyg...
Imports: ```python import typing ``` Type definitions: Input Types: np.array, float Output Type: np.array Dependencies: Function Name: v0 Function: ```python def v0(v1: np.array, v2: float) -> np.array: v1[v1 > v2] = v2 return v1 ```
Imports: ```python from math import ceil import typing ``` Type definitions: Input Types: int, int Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1: int, v2: int) -> str: v3 = v1 if v1 < 0: v3 += 1 << v2 v4 = (1 << v2) - 1 v3 &= v4 v5 = '{{:0{}x}}'.format(ceil...
Imports: ```python import typing ``` Type definitions: Input Types: QtWidgets.QLayout Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: QtWidgets.QLayout) -> None: v1.addWidget(self.getCanvas().native) super().setLayout(v1) ```
Imports: ```python import typing ``` Type definitions: Input Types: str, str, str, date, str Output Type: tuple Dependencies: Function Name: v0 Function: ```python async def v0(self, v1: str, v2: str, v3: str, v4: date, v5: str='paypal') -> tuple: self._check_org_uid_plan_id(v1, v3, v2) return await self._cre...
Imports: ```python import typing ``` Type definitions: Input Types: Any, Any Output Type: [int, int, float] Dependencies: Function Name: v0 Function: ```python def v0(self, v1, v2='rowwise') -> [int, int, float]: if self.opt.data.internal_data_type == 'matrix': assert v2 in ['rowwise', 'colwise'], 'Unexpe...
Imports: ```python from io import StringIO import typing ``` Type definitions: Input Types: object Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self, v1: object) -> str: v2 = StringIO() self.write(v2, v1) return v2.getvalue() ```
Imports: ```python import functools import operator import typing import numpy import numpy.fft import numpy.typing import typing ``` Type definitions: ```python v0 = DataAndMetadata._DataAndMetadataLike ``` ```python v1 = Image._ImageDataType ``` Input Types: DataAndMetadata.DataAndMetadata, typing.Optional[str] Outpu...
Imports: ```python from typing import Any, AnyStr, Dict, List, Optional, cast import typing ``` Type definitions: Input Types: str, AnyStr, Optional[int] Output Type: List[Dict[AnyStr, Any]] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: AnyStr, v3: Optional[int]=1) -> List[Dict[AnyStr,...
Imports: ```python import sys import argparse import typing ``` Type definitions: Input Types: str, List[str] Output Type: argparse.Namespace Dependencies: Function Name: v0 Function: ```python def v0(v1: str, v2: List[str]) -> argparse.Namespace: v3 = argparse.ArgumentParser(prog=v1, description=' .\n ') ...
Imports: ```python import typing ``` Type definitions: ```python v0 = TypeVar('T') ``` Input Types: int Output Type: Optional[v0] Dependencies: Function Name: v1 Function: ```python def v1(self, v2: int) -> Optional[v0]: if v2 in self.reverse_mapper: return self.reverse_mapper[v2] else: return ...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: float Dependencies: Function Name: v0 Function: ```python def v0(self) -> float: v1 = self.health - self.max_health self.health = self.max_health return v1 ```
Imports: ```python import typing ``` Type definitions: ```python v0 = Mapping[str, int] ``` Input Types: v0, jnp.ndarray Output Type: Mapping[str, jnp.ndarray] Dependencies: Function Name: v1 Function: ```python def v1(v2: v0, v3: jnp.ndarray) -> Mapping[str, jnp.ndarray]: v4 = {} v5 = 0 for v6 in sorted(v...
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: Union[pyredner.EnvironmentMap, tf.Tensor, None], Union[pyrednertorch.EnvironmentMap, torch.Tensor, None], Callable, Any Output Type: bool Dependencies: ```python def v0(v1, v2): v3 = v1 is None and v2 is not None v4 = v1 is ...
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: float, float, int Output Type: tuple Dependencies: Function Name: v0 Function: ```python def v0(v1: float, v2: float, v3: int) -> tuple: if v3 % 2 == 0: v4 = list(np.logspace(np.log10(v1), np.log10(v2), v3 // 2)) ...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python async def v0(self, **v1: Any) -> None: await self._smartbridge.lower_cover(self.device_id) self.async_update() self.async_write_ha_state() ```
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: Generator[bytes, None, None] Dependencies: Function Name: v0 Function: ```python def v0(self) -> Generator[bytes, None, None]: self.stream.seek(0) v1 = self.stream.read(self.chunk_size) while v1: yield v1 v1 ...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: self.reset_gamedata() object.__setattr__(self, 'players', []) ```
Imports: ```python import typing ``` Type definitions: Input Types: Iterable[dask.distributed.client.Future], Any Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(v1: Iterable[dask.distributed.client.Future], v2=True) -> None: if v2: for v3 in v1: if v3.status == 'p...
Imports: ```python import torch import torch.nn as nn import torch.nn.functional as F from torch import Tensor import typing ``` Type definitions: Input Types: Any, Optional[Tuple[Tensor, Tensor, Tensor, Tensor]], Optional[Dict[str, Dict[str, Optional[Tensor]]]], Optional[Tensor], Any Output Type: Any Dependencies: F...
Imports: ```python from urllib.parse import urlparse import requests import typing ``` Type definitions: Input Types: str Output Type: str Dependencies: ```python def v0(v1: str) -> Optional[str]: v2 = format_ipfs_cid(v1) if v2 is None: return None try: with ipfshttpclient.connect(util.IPFS...
Imports: ```python from datetime import datetime import typing ``` Type definitions: Input Types: str Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: str): v2 = datetime.now() v3 = datetime.strptime(v1, '%Y-%m-%d') return v2.year - v3.year - ((v2.month, v2.day) < (v3.month,...
Imports: ```python import requests import typing ``` Type definitions: Input Types: str Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: str): v2 = requests.get(url='https://friendbot.stellar.org', params={'addr': v1}) v2.raise_for_status() ```
Imports: ```python import typing ``` Type definitions: ```python class v0(JsonObject): def __init__(self, v1: str, v2: 'CloudFoundryClient', **v3): super(v0, self).__init__(**v3) v4 = self._default_manager(v1, v2) self._create_navigable_links(v2.v3, v4) self._create_navigable_includ...
Imports: ```python import math import typing ``` Type definitions: Input Types: float Output Type: Tuple[int, int, float] Dependencies: Function Name: v0 Function: ```python def v0(v1: float) -> Tuple[int, int, float]: v2 = math.modf(v1) v3 = int(v2[1]) v4 = abs(int(math.modf(v2[0] * 60)[1])) v5 = abs...
Imports: ```python from random import randint import typing ``` Type definitions: Input Types: Output Type: tuple Dependencies: Function Name: v0 Function: ```python def v0() -> tuple: v1 = set() while len(v1) < 6: v1.add(randint(1, 33)) v2 = sorted(v1) v2.append(randint(1, 16)) return tu...
Imports: ```python import typing ``` Type definitions: Input Types: bytes, bytes Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: bytes, v2: bytes): if len(v2) != 256: raise ValueError('Input table must be 256 bytes long.') v3 = [] for v4 in v1: v3.append(v2[...
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: Any Output Type: np.ndarray Dependencies: Function Name: v0 Function: ```python def v0(self, v1) -> np.ndarray: v2 = self.size v3 = np.ones(v2).astype(bool) for v4 in v1: v5 = self.find_covered_by_literal_mask(v...
Imports: ```python import typing ``` Type definitions: Input Types: str, int, int, int Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: int, v3: int, v4: int) -> int: v5 = 0 v6 = {} for v7 in range(0, len(v1) - v3 + 1): v8 = v1[v7:v7 + v3] if l...
Imports: ```python import difflib, itertools, sqlite3, threading, re, os, logging, random, time, functools, collections as pyCollections import typing ``` Type definitions: Input Types: str Output Type: bool Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str) -> bool: self.logger.debug('Chec...
Imports: ```python import json import datetime import urllib import urllib.request import typing ``` Type definitions: Input Types: str, str Output Type: Any Dependencies: ```python def v0(v1): try: v2 = urllib.request.Request(v1) v2.add_header('User-Agent', 'robots-bypass-2342') with urlli...
Imports: ```python import typing ``` Type definitions: Input Types: typing.Dict Output Type: typing.Dict Dependencies: Function Name: v0 Function: ```python def v0(self, v1: typing.Dict) -> typing.Dict: if self.strategy == 'obv': pass elif self.strategy == 'sup_res': pass elif self.strateg...
Imports: ```python import numpy import typing ``` Type definitions: Input Types: Any, Any, bool Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1, v2, v3: bool=False): v4 = 0.5 * (v2 + 1.0) - numpy.cos(v1) * (v2 - 1.0) * 0.5 v5 = {} if v3: v5['p_phi'] = 0.5 - 0.5 * num...
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: bool Dependencies: ```python def v0(v1: list) -> bool: v2 = '' for v3 in v1: v2 += v3 v4 = [] v5 = len(v1) for v6 in range(v5): v4.append(v2[v6::v5]) return check_horizontal_visibility(v4) ``` `...
Imports: ```python import typing ``` Type definitions: Input Types: str, str, list, Any Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: str, v3: list=None, v4=False): v5 = self.session.get(v1, auth=self.base_auth, verify=False, timeout=self.requests_timeout, allow_re...
Imports: ```python import typing ``` Type definitions: Input Types: int Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int): for v2 in self.modules(): if id(self) == id(v2): continue if hasattr(v2, 'freeze_block'): v2.freeze_block(v1) ...
Imports: ```python import os from tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau, ModelCheckpoint from tensorflow.keras.models import Model from tensorflow.keras.preprocessing.image import ImageDataGenerator from tensorflow.keras.metrics import categorical_crossentropy, categorical_accuracy, top_k_c...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: v1 = self.Transpose() self._data = v1._data ```
Imports: ```python from scipy.special import softmax from sklearn.metrics import log_loss from sklearn.preprocessing import MinMaxScaler import typing ``` Type definitions: Input Types: List[float], NDArray[np.float_], NDArray[np.int_] Output Type: float Dependencies: Function Name: v0 Function: ```python def v0(self...
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: ElectronicT Output Type: ArrayLike Dependencies: Function Name: v0 Function: ```python def v0(self, v1: ElectronicT=None) -> ArrayLike: if v1 is None: v1 = self.electronics return np.dot(np.real(np.diag(self.rho)), ...
Imports: ```python import typing ``` Type definitions: ```python class v0: v1 = ['role', 'rank', 'local_world_size'] def __init__(self, v2: str, v3: int, v4: int): """ Arguments: role (str): user-defined role for the workers with this spec rank (int): the rank of the ag...
Imports: ```python import typing ``` Type definitions: ```python v0 = Callable[[io.StringIO], io.StringIO] ``` Input Types: io.StringIO, List[v0] Output Type: io.StringIO Dependencies: Function Name: v1 Function: ```python def v1(v2: io.StringIO, v3: List[v0]) -> io.StringIO: v2.seek(0) if not v3: retu...
Imports: ```python import torch from torch.utils.data import DataLoader from torch.utils.data import Dataset import typing ``` Type definitions: Input Types: Dataset Output Type: DataLoader Dependencies: Function Name: v0 Function: ```python def v0(v1: Dataset, **v2) -> DataLoader: if not isinstance(v1, Dataset):...
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: Any Dependencies: ```python def v0(v1: str): v2 = v1.split('.') if len(v2) != 4: raise ValueError(f'{v1} not in correct IPv4 format') return _struct.pack('BBBB', *[int(bt) for v3 in v2]) ``` Function Name: v4 Funct...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: list Dependencies: Function Name: v0 Function: ```python def v0(self) -> list: v1 = self.meta_run_tree.view('traces') v2 = [] for v3 in v1.keys(): v4 = self.idx_to_ctx(v3).to_dict() for (v5, v6) in v1[v3].ite...
Imports: ```python import typing ``` Type definitions: Input Types: int | str Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int | str): if v1 not in self.sprites.keys(): raise ValueError(f'The sprite corresponding to {v1} does not exist in this scene') del self....
Imports: ```python import torch import torch.nn as nn import torch.nn.functional as F 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 = self.forward(v1) v3 = v2['categ...
Imports: ```python from torch import Tensor, nn from torch.nn.functional import interpolate import typing ``` Type definitions: Input Types: Tensor Output Type: Tensor Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Tensor) -> Tensor: v2 = v1.size(2) v3 = v1.size(3) v4 = (v2, v3) ...
Imports: ```python import pathlib import re import typing ``` Type definitions: Input Types: typing.Union[str, re.Pattern] Output Type: typing.List[pathlib.Path] Dependencies: ```python def v0(v1: str='solutions') -> pathlib.Path: return pathlib.Path(__file__).parent / v1 ``` Function Name: v2 Function: ```python ...
Imports: ```python import typing ``` Type definitions: Input Types: classfile.MemberInfo Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: classfile.MemberInfo): v2 = v1.CodeAttribute if v2 != None: self.maxStack = v2.MaxStack self.maxLocals = v2.MaxLocals ...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: v1 = self.__class__.__name__ if not isinstance(self.data, bool): raise TypeError(f'Data in {v1} must be a bool') ```
Imports: ```python import typing ``` Type definitions: Input Types: Union[float, int] Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1: Union[float, int]) -> str: if v1 != v1: return '' if isinstance(v1, int): return str(v1) if v1 >= 1000: v2 = f'{v1:....
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: assert not self.trainer.model.training assert not self.training ```
Imports: ```python import copy import torch import torch.nn as nn import torch.nn.functional as F import typing ``` Type definitions: Input Types: str Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str): self.actor.load_state_dict(torch.load(v1)) self.actor_target = copy...
Imports: ```python import io import os import typing ``` Type definitions: ```python v0 = Union[None, io.BytesIO, io.StringIO] ``` ```python v1 = Union[str, bytes, None, Sequence[Union[str, bytes]]] ``` Input Types: v1, v0 Output Type: Union[io.BytesIO, io.StringIO] Dependencies: Function Name: v2 Function: ```python ...
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: np.ndarray, int Output Type: np.ndarray Dependencies: Function Name: v0 Function: ```python def v0(v1: np.ndarray, v2: int) -> np.ndarray: assert v2 % 2 == 1, 'Only odd sizes supported' v3 = (v2 - 1) // 2 v4 = np.empty(...
Imports: ```python import typing ``` Type definitions: Input Types: Token, Any Output Type: bool Dependencies: Function Name: v0 Function: ```python def v0(v1: Token, v2=200) -> bool: if len(v1) < 2: return False elif v1.lemma_.istitle() and len(v1.lemma_) > 2: return True elif v1.lemma_.i...
Imports: ```python import typing ``` Type definitions: Input Types: list, Any Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: list, v2): v3 = len(v1) if v3 == 0: return if (v3 == self.nodeCount - 1 or self.nodeCount > v2) and v3 >= v2: for v4 in range(...
Imports: ```python import typing ``` Type definitions: Input Types: List[str], List[Tuple] Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(v1: List[str], v2: List[Tuple]) -> None: for v3 in range(len(v1)): for v4 in range(len(v1[0])): if (v3, v4) in v2 and v1[v3][v...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: super().setUp() self.inner_mock.tasks.find_by_project.return_value = [t.to_dict() for v1 in self.tasks] self.inner_mock.tasks.find_by_section.ret...
Imports: ```python import re from datetime import datetime import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: if self.googleDB == True: v1 = datetime.now().strftime('%m/%d/%Y %H:%M:%S') v2 = self.sheet.add_w...
Imports: ```python import typing ``` Type definitions: Input Types: stix2.Bundle Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: stix2.Bundle) -> None: v2 = v1.serialize() self.helper.send_stix2_bundle(v2, work_id=self.work_id) ```
Imports: ```python import matplotlib.dates as mdates import matplotlib.pyplot as plt from matplotlib.figure import Figure from matplotlib.ticker import MaxNLocator import typing ``` Type definitions: Input Types: pd.DataFrame, Dict Output Type: (str, Figure) Dependencies: ```python def v0(v1: pd.Series, v2: int, v3: s...
Imports: ```python import asyncio import signal from sys import stderr import typing ``` Type definitions: Input Types: str Output Type: asyncio.Event Dependencies: ```python def v0(v1: signal.Signals) -> None: print(f'\nStopping {name}', file=stderr) stop.set() ``` Function Name: v2 Function: ```python def v2...
Imports: ```python import os, sys import typing ``` Type definitions: Input Types: Callable Output Type: Any Dependencies: ```python def v0(v1: List[str], v2=''): v3 = parse_cue_sheet(v1) v4 = next((x for v5 in v3.tracks if v5.mode.lower() != 'audio'), None) if v4: v6 = os.path.join(v2, v3.bin_file...
Imports: ```python import os import typing ``` Type definitions: Input Types: int Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int) -> str: v2 = os.path.abspath(os.path.join(self._dbdir, '%s%d' % (self._dbname, self._last_flag))) while os.path.exists(v2): self....
Imports: ```python from textwrap import dedent import typing ``` Type definitions: Input Types: Any Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1: Any) -> str: if isinstance(v1, str): v2 = dedent(v1) elif not isinstance(v1, (list, tuple)): v2 = '\n'.join(v1) ...
Imports: ```python import typing ``` Type definitions: ```python class v0(ctypes.Structure): pass ``` Input Types: ctypes.POINTER(v0) Output Type: Any Dependencies: Function Name: v1 Function: ```python def v1(self, v2: ctypes.POINTER(v0)): assert self._handle >= 0 self._lib.khaiii_free_results(self._handl...
Imports: ```python import math import numpy as np import typing ``` Type definitions: Input Types: np.array Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: np.array=None): v2 = sum([math.pow(abs(v1[i]), 2) for v3 in range(len(v1))]) v2 = v2 / len(v1) v4 = v2 / math.po...
Imports: ```python import math import numpy as np import typing ``` Type definitions: Input Types: int, int Output Type: list Dependencies: Function Name: v0 Function: ```python def v0(v1: int=None, v2: int=None) -> list: v3 = 1.0 / math.factorial(v2) v4 = [list() for v5 in range(v1)] v6 = 1.0 for v7 ...
Imports: ```python import typing ``` Type definitions: ```python v0 = Iterable[Accent] ``` Input Types: discord.Member, v0 Output Type: None Dependencies: Function Name: v1 Function: ```python def v1(self, v2: discord.Member, v3: v0) -> None: if v2.guild.id not in self._accents: self._accents[v2.guild.id] ...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self) -> str: v1 = [f'{key}: {value}' for (v2, v3) in self.headers.items()] return '\n'.join(v1) ```
Imports: ```python import typing ``` Type definitions: Input Types: logging.LogRecord Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: logging.LogRecord) -> None: try: self.acquire() try: if self.console.file.closed: return ...
Imports: ```python import typing ``` Type definitions: Input Types: ndarray, Any Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: ndarray, v2=0.5): v3 = self.predict_proba(v1) return (v3 >= v2).astype(int) ```
Imports: ```python import typing ``` Type definitions: Input Types: Dict[str, Any] Output Type: Dict[str, Any] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Dict[str, Any]) -> Dict[str, Any]: v1 = super()._modify_params(v1) v1[self._query_type('datasets').param] = self._datasets ret...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: v0(f"======= Executable '{self.name}' =======\n") for v1 in self.coreclrs_run.values(): v1.print() ```
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str) -> str: v2 = {x: format(i, '02d') for (v3, v4) in enumerate(['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'], 1)} ...
Imports: ```python import re import typing ``` Type definitions: Input Types: str Output Type: Optional[str] Dependencies: ```python def v0(v1: int, v2: int) -> str: v3 = v1 % v2 v4 = chr(97 + v3) return v4 ``` Function Name: v5 Function: ```python def v5(v6: str) -> Optional[str]: v7 = 'b' v8 = 3 ...
Imports: ```python import typing ``` Type definitions: Input Types: Tuple[int, int], int Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Tuple[int, int], v2: int): (v3, v4) = v1 return (0, abs(v2 - v4)) ```
Imports: ```python import math import numpy as np import typing ``` Type definitions: Input Types: Iterable[Tuple[float, any]] Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Iterable[Tuple[float, any]]) -> None: v1 = sorted(v1, key=lambda evaluation: evaluation[0], reverse=...
Imports: ```python import typing ``` Type definitions: Input Types: T.List[str] Output Type: T.Dict[str, str] Dependencies: Function Name: v0 Function: ```python def v0(v1: T.List[str]) -> T.Dict[str, str]: v2 = {} v3 = iter(v1) try: for v4 in v3: v2[v4] = next(v3) except StopItera...