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Imports: ```python import typing ``` Type definitions: Input Types: list, list, list, list, list Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: list, v2: list, v3: list, v4: list, v5: list): if self.N - 1 >= 0: for v6 in range(self.N - 1 + 1): for v7 in r...
Imports: ```python import typing ``` Type definitions: Input Types: str, str, str Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: str, v3: str): v4 = self.bash(f"dig -6 @{v1} '{v2}' {v3}", encoding='raw_unicode_escape') v5 = None v6 = {'QUESTION': [], 'ANSWER...
Imports: ```python import json import os import typing ``` Type definitions: Input Types: str Output Type: Sequence[str] Dependencies: Function Name: v0 Function: ```python def v0(v1: str) -> Sequence[str]: with open(os.path.expanduser(v1), 'r') as v2: v3 = json.load(v2) v4 = [article['text'] for v5 i...
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1: str) -> str: v2 = [' ', ',', ';', '{', '}', '(', ')', '\t', '=', '/', '\\'] for v3 in v2: v1 = v1.replace(v3, '') return v1 ```
Imports: ```python import hashlib import os from pathlib import Path import typing ``` Type definitions: Input Types: Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self) -> str: if self.cloud == 'local': return os.path.join(str(Path.home()), '.opta', 'local', 'tfstate') ...
Imports: ```python import copy 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): v2 = copy.deepcopy(v1) v2[v2 < 0] = 0 self.cache = v1 if self.gradient is None or self.gradient.s...
Imports: ```python import typing ``` Type definitions: ```python class v0(Get): def __init__(self, v1: SimContext, v2: QueueFIFO, v3: Process): super().__init__(v1, v2, v3) self.item: Any = None self._func = lambda event: event.item ``` Input Types: v0 Output Type: bool Dependencies: Funct...
Imports: ```python import typing ``` Type definitions: Input Types: int Output Type: tuple[int, ...] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int) -> tuple[int, ...]: (v2, v3) = self._private_key v4 = [(v1 - random_message) ** v3 % v2 for v5 in self.random_messages] return tupl...
Imports: ```python import typing ``` Type definitions: Input Types: int Output Type: Any Dependencies: Function Name: v0 Function: ```python async def v0(self, v1: int, **v2: typing.Any): v3 = {k: v for (v4, v5) in v2.items()} await self.request('PATCH', f'/channels/{v1}', headers={'Content-Type': 'applicatio...
Imports: ```python import os import csv import subprocess from collections import Counter, defaultdict import typing ``` Type definitions: Input Types: Dict[str, Dict[str, str]], List[str], Any, Any, Any Output Type: Dict[str, Dict[str, str]] Dependencies: ```python def v0(v1, v2, v3) -> str: if v2 != '': ...
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 self._last_unlocked_level == self.last_level: return (v1 + 1) % (self.last_level + 1) v2 = self.levels_scores[v1 + 1:self.last_u...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self) -> int: if self.reversed: return self.reversed[-1] return self.top ```
Imports: ```python import collections import typing ``` Type definitions: Input Types: list[list[int]], int Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(v1: list[list[int]], v2: int) -> int: (v3, v4) = (len(v1), len(v1[0])) v5 = collections.deque() v6 = [[-1] * v4 for v7 in ...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: Optional[str] Dependencies: Function Name: v0 Function: ```python def v0(self) -> Optional[str]: v1 = self.config_dict.get('security') if not v1: return None return v1.get('outbound_firewall') ```
Imports: ```python import typing ``` Type definitions: Input Types: bool Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: bool=False): self.metadata = self._parse_metadata() self.chapters = self._parse_chapters(self.metadata['contents'], parse_chapter=v1) ```
Imports: ```python import typing ``` Type definitions: Input Types: Any Output Type: bytes Dependencies: ```python def v0(v1) -> Optional[Account]: v2 = v1.obj.account_manager v3 = v2.who() if v3: return v3 else: print('[italic red]No recent user, please adding or selecting one[/]') ...
Imports: ```python import typing ``` Type definitions: Input Types: MuParser.Return_exprContext Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: MuParser.Return_exprContext): v2 = self.visit(v1.expr()) self.result = v2 return v2 ```
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: np.ndarray Output Type: np.ndarray Dependencies: Function Name: v0 Function: ```python def v0(self, v1: np.ndarray) -> np.ndarray: v1 += self.offsets v2 = np.apply_along_axis(self.func, axis=1, arr=v1) v3 = np.random.ra...
Imports: ```python import json import typing ``` Type definitions: Input Types: Output Type: list Dependencies: ```python def v0(v1: list, v2): def v3(v4, v5, v6): """ This nested function set value of all instance attr :param instance: instance to set it attrs :param data: ...
Imports: ```python import multiprocessing as mp import multiprocessing.pool import os import os.path import torch import torch.multiprocessing from torch.optim import Optimizer import typing ``` Type definitions: Input Types: int, Optional[str], Optional[Callable[[], None]] Output Type: mp.Pool Dependencies: ```python...
Imports: ```python import typing ``` Type definitions: ```python class v0: def __init__(self, v1=0, v2=None, v3=None): self.val = v1 self.left = v2 self.right = v3 ``` Input Types: v0 Output Type: List[List[int]] Dependencies: Function Name: v4 Function: ```python def v4(self, v5: v0) -> L...
Imports: ```python import typing ``` Type definitions: Input Types: str, Callable[[Any], Any], Any Output Type: Tuple[Any, bool] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: Callable[[Any], Any]=None, v3=None) -> Tuple[Any, bool]: (v4, v5) = self._cache.get(v1) if not v5: ...
Imports: ```python import typing ``` Type definitions: ```python class v0: v1 = 0 def __init__(self) -> None: self.gameVersion = '21' self.binaryVersion = '35' self.secret = 'Wmfd2893gb7' self.level_secret = 'Wmfv2898gc9' self.login_secret = 'Wmfv3899gc9' self.mo...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: dict Dependencies: Function Name: v0 Function: ```python def v0() -> dict: v1 = {'block_versions': {'0.1a': 0}, 'hash_versions': {'genesis': 1, '0x2': 1, '0x3': 1}, 'load_cert': False, 'consensus_cert_use': False, 'tx_cert_use': Fal...
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: Doc Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str) -> Doc: v2 = None for v3 in self.pipeline['nlp'].pipe([v1]): v2 = v3 return v2 ```
Imports: ```python import typing ``` Type definitions: Input Types: bool Output Type: None Dependencies: Function Name: v0 Function: ```python async def v0(self, v1: bool) -> None: if v1: await self._device.mute_on() self._is_volume_muted = True else: await self._device.mute_off() ...
Imports: ```python import json import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: with self.metrics_file.open('w') as v1: v2 = {'num_training_examples': self.num_samples, 'max_seq_len': self.seq_len, 'vocab_len': se...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0() -> None: try: while True: print(input()) except KeyboardInterrupt: exit() except EOFError: exit() ```
Imports: ```python import matplotlib.pyplot as plt from matplotlib.backends.backend_agg import FigureCanvasAgg import numpy as np import typing ``` Type definitions: Input Types: np.ndarray, np.ndarray, Tuple or List, Any, Any, Any Output Type: np.ndarray Dependencies: Function Name: v0 Function: ```python def v0(v1:...
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: str Output Type: Tuple[np.ndarray, np.ndarray] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str) -> Tuple[np.ndarray, np.ndarray]: (v2, v3) = tuple(map(int, v1.split(':'))) return (np.array([v2]), np...
Imports: ```python import typing ``` Type definitions: Input Types: Path, int, int Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(v1: Path, v2: int, v3: int) -> int: v4 = 0 for (v5, v6) in enumerate(open(v1)): v6 = v6.strip() if v5 == 0: v7 = len(v6) ...
Imports: ```python import typing ``` Type definitions: Input Types: Any, Any, Any, Any Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1=str, v2='', v3='', v4=[]) -> str: if v1 == 'summary': v5 = 'https://api.covid19api.com/summary' elif v1 == 'slugs_codes': v5 = '...
Imports: ```python import typing ``` Type definitions: Input Types: int, int Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int, v2: int): for v3 in self.envs: v3.set_display_size(width=v1, height=v2) ```
Imports: ```python from itertools import chain import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, *v1: Any) -> None: for v2 in chain(*v1): self.add(v2) ```
Imports: ```python import typing ``` Type definitions: Input Types: dict, list Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: dict, v2: list): v3 = None if v1.get('media'): v3 = v1['media'][0]['url'] elif v1.get('images'): v3 = v1['images'][0]['url'] ...
Imports: ```python import matplotlib as mpl import numpy as npy import matplotlib.pyplot as plt from matplotlib import ticker, rcParams from matplotlib.patches import Circle from matplotlib.pyplot import quiver from matplotlib.dates import date2num import matplotlib.tri as tri import typing ``` Type definitions: Input...
Imports: ```python from pathlib import Path import typing ``` Type definitions: Input Types: bool Output Type: Path Dependencies: Function Name: v0 Function: ```python def v0(v1: bool=True) -> Path: v2 = (Path.home() / 'quantify-data').resolve() if v1: print(f'Data will be saved in:\n{v2}') return...
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: Union[str, int] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, *v2: str, **v3: Any) -> Union[str, int]: v1 = self._bin(v1) v4 = [v1] + list(v2) return self._run(v4, **v3) ```
Imports: ```python import typing ``` Type definitions: ```python class v0: def __init__(self, v1: str): self.addedNodes_: List[str] = [] self.removedNodes_: List[str] = [] self.ancestors_: List['Transformation'] = [] self.scopeName_: str = '' self.transID_: str = v1 ...
Imports: ```python import typing ``` Type definitions: Input Types: int, str Output Type: dict Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int=20, v2: str='score') -> dict: self.send_server({'command': 'lb_get_by_place_down', 'place': v1, 'type': v2}) return self._get_data('lb') ```
Imports: ```python from os.path import join import typing ``` Type definitions: Input Types: str, int, int, str Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1: str, v2: int, v3: int, v4: str) -> str: v5 = str(v2) + 'particle' + str(v3) + '.' + v4 return join(v1, v5) ```
Imports: ```python import typing ``` Type definitions: ```python v0 = Dict[str, Any] ``` Input Types: str, str, Optional[str], Optional[bool] Output Type: Generator[Optional[Callable], None, None] Dependencies: ```python @conversion def v1(v2: v0, v3: str) -> None: v2[v3] = ','.join(map(str, sum(force_dict(v2[v3] o...
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str): for v2 in self.projects_list(): if v2.path_with_namespace == v1: return v2 ```
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: v3 = self.warmup_steps * v1 v4 = self.lr_annealing_steps * v1 v5 = self.decay_steps * v1 self._calculate_lr_momentu...
Imports: ```python import tensorflow as tf import typing ``` Type definitions: Input Types: tf.data.Dataset, int Output Type: tf.keras.Model Dependencies: ```python def v0(v1: tf.Tensor, v2: tf.Tensor): return v1 ``` Function Name: v3 Function: ```python def v3(v4: tf.data.Dataset, v5: int) -> tf.keras.Model: ...
Imports: ```python import numpy as np import matplotlib.pyplot as plt import typing ``` Type definitions: Input Types: int, int, int Output Type: None Dependencies: ```python def v0(v1: float, v2: float, v3: int, v4: int) -> int: v5 = np.complex(v1, v2) v6 = v5 for v7 in range(v3): v6 = v6 ** 2 + v...
Imports: ```python import typing ``` Type definitions: Input Types: str, Any Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: str, v2): v3 = v2.tokenize(v1) v4 = [] for v5 in v3: if v5.startswith('##'): v4[-1] += v5[2:] else: v4.append...
Imports: ```python import typing ``` Type definitions: Input Types: int Output Type: List[Dict[str, Any]] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int=10485760) -> List[Dict[str, Any]]: v2 = [{'size': self._sizes[x[0]], 'key': x[0], 'paths': x[1]} for v3 in self._files.items() if self....
Imports: ```python from spacy.language import Language from spacy.pipeline import Pipe from spacy.tokens import Doc from spacy import util import typing ``` Type definitions: Input Types: Iterable[Doc], int Output Type: Iterator[Doc] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Iterable[Doc], ...
Imports: ```python import typing ``` Type definitions: ```python class v0: def __init__(self, v1, v2, v3, v4, v5=None): self.lefts = [] self.rights = [] self.id = int(v1) self.parent = int(v3) - 1 self.word = v2 self.deprel = v4 self.postag = v5 ``` Input Typ...
Imports: ```python import typing ``` Type definitions: Input Types: Dict[str, Dict[str, Dict[str, List[Dict[str, Any]]]]] Output Type: Tuple[str, str, Dict[str, List[Dict[str, Any]]]] Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Dict[str, Dict[str, Dict[str, List[Dict[str, Any]]]]]) -> Tuple[s...
Imports: ```python import math import typing ``` Type definitions: Input Types: np.array, float Output Type: [int] Dependencies: Function Name: v0 Function: ```python def v0(v1: np.array, v2: float) -> [int]: if v2 == 0.0: return [] v2 = 0.1 v3 = len(v1) v4 = [] for v5 in v1: if v5...
Imports: ```python import typing ``` Type definitions: Input Types: dict Output Type: Any Dependencies: ```python def v0(v1, *v2, **v3): with lock: default_logger.info(v1, *v2, **v3) ``` Function Name: v4 Function: ```python def v4(v5: dict, *v6, **v7): v8 = '\n\t{:<80} {:<15} {:<20} {:<15} {:<10}\n'.f...
Imports: ```python import typing ``` Type definitions: ```python class v0(BaseModel): @property def v1(self) -> str: """Pytest ID for console feedback during tests runs.""" return self.__repr__() def __repr__(self) -> str: """Valid __repr__ string to fully reproduce the object unde...
Imports: ```python import numpy as np import pandas as pd import typing ``` Type definitions: Input Types: Union[pd.DataFrame, pd.Series], Optional[str], Optional[int], Optional[str] Output Type: pd.DataFrame Dependencies: ```python def v0(v1: np.array) -> np.array: v2 = v1.shape[0] _LOG.debug('signal length=%...
Imports: ```python from collections import OrderedDict import numpy as np from sklearn.metrics import mean_absolute_error, r2_score, mean_squared_error, max_error from sklearn.metrics import f1_score, recall_score, precision_score, accuracy_score import typing ``` Type definitions: Input Types: Union[np.ndarray, pd.Da...
Imports: ```python import typing ``` Type definitions: Input Types: Tuple[int, int], Tuple[int, int, int, int] Output Type: List[Tuple[int, int]] Dependencies: ```python def v0(v1: Tuple[int, int], v2: Tuple[int, int, int, int]) -> bool: (v3, v4) = v1 (v5, v6, v5, v7) = v2 return v3 > v6 or v4 < v7 ``` ```...
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: bool Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str) -> bool: self.assert_can_edit() v2 = self.collection.document(v1).get() if not v2.exists: return False v2.reference.delete() r...
Imports: ```python import random import string import typing ``` Type definitions: Input Types: Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self) -> str: v1 = f'{self.listener.name}_' v2 = f"{v1}{''.join(random.choices(string.ascii_letters + string.digits, k=20))}" while v...
Imports: ```python import requests import typing ``` Type definitions: Input Types: str Output Type: str Dependencies: ```python def v0(v1: str) -> str: v2 = '6LcCoP8SAAAAAKzsvbTXymxqNWcC-dAhDYik0V3C' v3 = f'http://2captcha.com/in.php?key={APIKEY_2CAPTCHA}&method=userrecaptcha&googlekey={v2}&pageurl={v1}' ...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: Tuple[str, str] Dependencies: Function Name: v0 Function: ```python def v0(self) -> Tuple[str, str]: v1 = self.soup.find('span', ['h3_titel']).contents (v2, v3) = (v1[0], v1[2]) return (v2, v3) ```
Imports: ```python import typing ``` Type definitions: Input Types: Any, float Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1, v2: float): v3: int = self._data_pointer + self.capacity - 1 self.update(v3, v2) self._data[self._data_pointer] = v1 self._data_pointer +...
Imports: ```python import typing ``` Type definitions: Input Types: int, int Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(v1: int, v2: int) -> int: if v1 <= v2: return v1 v3 = 1 for v4 in range(2, min(int(v1 ** 0.5), v2) + 1): v5 = v1 // v4 if v5 * v4...
Imports: ```python import typing ``` Type definitions: ```python v0 = Union[int, Literal[Any]] ``` ```python v1 = Union[type, Literal[Any], np.dtype] ``` Input Types: Tuple[Tuple[v0, ...], v1] Output Type: Tuple[Tuple[v0, ...], v1] Dependencies: Function Name: v2 Function: ```python def v2(cls, v3: Tuple[Tuple[v0, ......
Imports: ```python import typing ``` Type definitions: Input Types: int, bool Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(v1: int, v2: bool) -> int: if v2: return 10 * v1 else: return int(v1 / 10) ```
Imports: ```python import os import pandas as pd import typing ``` Type definitions: Input Types: Tuple Output Type: pd.DataFrame Dependencies: Function Name: v0 Function: ```python def v0(self, v1: Tuple) -> pd.DataFrame: v2 = self._data.copy() for (v3, v4) in enumerate(self._parameters): v2 = v2[v2[...
Imports: ```python import numpy as np import typing ``` Type definitions: Input Types: np.dtype Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1: np.dtype) -> str: if v1 == np.int8: return 'int8' if v1 == np.uint16: return 'uint16' if v1 == np.float32: ...
Imports: ```python import numpy as np import scipy import sklearn from scipy.sparse import isspmatrix_csr from scipy.stats import norm import typing ``` Type definitions: Input Types: Any, Any, Any, Any, Any, Optional[int] Output Type: Any Dependencies: ```python def v0(v1): v2 = len(v1) v3 = np.zeros(v2) ...
Imports: ```python import typing ``` Type definitions: ```python class v0: def __init__(self, v1=0, v2=None, v3=None): self.val = v1 self.left = v2 self.right = v3 ``` Input Types: v0, int Output Type: int Dependencies: Function Name: v4 Function: ```python def v4(self, v5: v0, v6: int) ->...
Imports: ```python import matplotlib.pyplot as plt import matplotlib.colors as colors import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: self.__cmap = plt.get_cmap('twilight_shifted') self.__norm = colors.Normalize(vmin...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: Sequence[str] Dependencies: Function Name: v0 Function: ```python def v0() -> Sequence[str]: v1: Dict[str, int] = {'one': 1, 'two': 2, 'three': 3} v2: Tuple[str] = v1.keys() return v2 ```
Imports: ```python import typing ``` Type definitions: Input Types: str Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, *v2) -> None: if v1 in self.events: for v3 in self.events[v1]: v3(*v2, self.server) ```
Imports: ```python from typing import Union, Iterable, SupportsInt import typing ``` Type definitions: Input Types: Union[Iterable, SupportsInt] Output Type: Iterable Dependencies: Function Name: v0 Function: ```python def v0(v1: Union[Iterable, SupportsInt]) -> Iterable: if isinstance(v1, Iterable): retu...
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self) -> None: self.entry_point.topic_id = 'valid_topic1' self.entry_point.story_id = 'valid_story1' self.entry_point.exploration_id = 123 self._assert_vali...
Imports: ```python import typing ``` Type definitions: Input Types: Optional[Union[int, str]] Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1: Optional[Union[int, str]]) -> str: if v1 is None: return '' v1: str = str(v1) return ' + '.join(v1) + f' = {sum(map(int, v1)...
Imports: ```python import typing ``` Type definitions: ```python class v0: def __init__(self, v1=0, v2=None, v3=None): self.val = v1 self.left = v2 self.right = v3 ``` Input Types: v0 Output Type: Any Dependencies: Function Name: v4 Function: ```python def v4(v5: v0): v6: v0 = v5 v...
Imports: ```python import typing ``` Type definitions: Input Types: int Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(v1: int) -> int: v2 = v1.bit_length() if v2 >= 1300: return 2 if v2 >= 850: return 3 if v2 >= 650: return 4 if v2 >= 300: ...
Imports: ```python import typing ``` Type definitions: ```python v0 = Dict[bytes, bytes] ``` Input Types: bytes, v0, int, bool Output Type: None Dependencies: Function Name: v1 Function: ```python async def v1(self, v2: bytes, v3: v0, v4: int=None, v5: bool=True) -> None: async with self.batch(timestamp=v4, wal=v5...
Imports: ```python import typing ``` Type definitions: Input Types: str, str Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2: str): v3 = type(self.service) for v3 in type(self.service).__mro__: if not hasattr(v3, v1): continue v4 = geta...
Imports: ```python import itertools import torch from torch.utils.data import Dataset import typing ``` Type definitions: Input Types: int Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int): v2 = torch.utils.data.DataLoader(self.buffer, batch_size=v1, drop_last=True, shuffl...
Imports: ```python import typing ``` Type definitions: Input Types: tkinter.BooleanVar, object Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self, v1: tkinter.BooleanVar, v2: object) -> str: v1.set(not v1.get()) return 'break' ```
Imports: ```python import typing ``` Type definitions: Input Types: Output Type: None Dependencies: Function Name: v0 Function: ```python async def v0(self) -> None: async for v1 in self.TAGDB.find({}): if isinstance(v1.get('guild_id'), int): await self.TAGDB.update_one({'_id': v1.get('_id')}...
Imports: ```python import typing ``` Type definitions: Input Types: v7 Output Type: str Dependencies: ```python def v0(v1: int, v2: str) -> str: return '(net (code {}) (name "{}")'.format(v1, v2) ``` ```python def v3(v4: str, v5: str) -> str: return '(node (ref {}) (pin {})))'.format(v4, v5) ``` Function Name:...
Imports: ```python import typing ``` Type definitions: Input Types: int Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int) -> None: if v1 in self.node_lookup_map: if len(self.node_lookup_map) == 1 or self.node_lookup_map[v1] == self.head: return ...
Imports: ```python import typing ``` Type definitions: Input Types: Dict[str, Any] Output Type: bool Dependencies: Function Name: v0 Function: ```python def v0(v1: Dict[str, Any]) -> bool: if 'deployments' not in v1 or not v1['deployments']: return False return True ```
Imports: ```python import typing ``` Type definitions: Input Types: List[service.VersionRange] Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(self, v1: List[service.VersionRange]) -> str: v2 = str() for v3 in v1: if v2: v2 += ', ' v4 = v3.introduced if ...
Imports: ```python import typing ``` Type definitions: ```python v0 = Enum('TokenKind', 'IF THEN ELSE IDENT INT OPERATOR PRINT STRING VAR ASSIGN UNKNOWN EOF ENDLN OPEN METHOD BLOCKEND EQ INPUT DIV MUL MINUS PLUS LPAREN RPAREN FUNC RUN COMMA') ``` Input Types: v0 Output Type: Any Dependencies: Function Name: v1 Functio...
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 = v1.rfind('\n', 0, self.pos) + 1 v3 = v1.find('\n', self.pos) return v1[v2:v3] + '\n' + ' ' * (self.pos - v2) + '^\n' ```
Imports: ```python import typing ``` Type definitions: Input Types: List[int], int Output Type: None Dependencies: ```python def v0(v1: int, v2: int) -> int: return v1 // 10 ** v2 % 10 ``` Function Name: v3 Function: ```python def v3(v4: List[int], v5: int) -> None: v6 = [0 for v7 in range(max(v4) + 1)] fo...
Imports: ```python import typing ``` Type definitions: ```python @dataclasses.dataclass class v0: v1: dict v2: Set[str] v3: int v4: Set[str] v5: bool ``` Input Types: Any Output Type: List[v0] Dependencies: Function Name: v6 Function: ```python def v6(self, v7) -> List[v0]: v8 = [] for v9 i...
Imports: ```python import tensorflow as tf import random from glob import glob from tqdm import trange, tqdm import numpy as np import h5py from keras import models, layers, regularizers, constraints, backend as K from tensorflow.python import debug as tf_debug import os from tensorflow.python.client import timeline im...
Imports: ```python import typing ``` Type definitions: Input Types: int, int Output Type: int Dependencies: Function Name: v0 Function: ```python def v0(self, v1: int, v2: int) -> int: v3 = None for v4 in range(v1, v2): if v3 is None and v4 == v2 - 1 or self.check_for_poison([v4]): self.ma...
Imports: ```python import numpy as np from shapely.geometry import Polygon, MultiPolygon from shapely.geometry.point import Point from shapely.ops import unary_union from shapely.affinity import rotate, scale, translate import typing ``` Type definitions: Input Types: int, Any, Any, Any, Any, Any, Any Output Type: Any...
Imports: ```python import typing ``` Type definitions: Input Types: Dict[str, Any], Any Output Type: None Dependencies: Function Name: v0 Function: ```python def v0(v1: Dict[str, Any], v2: Any) -> None: if v1['result'] == 'error' and hasattr(v2, 'view'): v2.report_error([v1['msg']]) ```
Imports: ```python from itertools import chain import typing ``` Type definitions: ```python @dataclass class v0: v1: str v2: Optional[str] v3: Optional[str] v4: Optional[str] v5: set[str] = field(default_factory=set) v6: set[str] = field(default_factory=set) v7: ClassVar[dict[str, 'ClassDef...
Imports: ```python import typing ``` Type definitions: Input Types: tuple[int, int], str, int, int Output Type: bool Dependencies: Function Name: v0 Function: ```python def v0(self, v1: tuple[int, int], v2: str, v3: int, v4: int) -> bool: (v5, v6) = v1 v7 = 0 while v7 < self.get_ship_size(v2): if ...
Imports: ```python import logging import os import typing ``` Type definitions: Input Types: Path Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(v1: Path): if os.path.isfile(v1): v2 = input(f"File '{v1.resolve()}' exists. Delete? (Y/n) ") if v2 == 'Y': os.r...
Imports: ```python import torch import torch.nn as nn from torch.nn import 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: with torch.no_grad(): retur...
Imports: ```python import subprocess import typing ``` Type definitions: Input Types: str, bool Output Type: str Dependencies: Function Name: v0 Function: ```python def v0(v1: str, v2: bool=False) -> str: v3 = subprocess.run(v1.split(), stderr=subprocess.PIPE, stdout=subprocess.PIPE) v4 = v3.stdout.decode('ut...
Imports: ```python import requests import typing ``` Type definitions: Input Types: str, Any Output Type: Any Dependencies: Function Name: v0 Function: ```python def v0(self, v1: str, v2=True): v3 = {} if v2: v3 = self.header v4 = requests.get(v1, headers=v3) if v4.status_code == 401: ...