text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> int:
v2 = str(v1)
v3: int = 0
while len(v2) > 1:
v4 = 1
for v5 in v2:
v4 *= int(v5)
v2 = str(v4)
v3 +=... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes) -> None:
self._broadcast_sub_connections(v1)
self.send(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: typing.Dict
Output Type: typing.Optional[bool]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: typing.Dict) -> typing.Optional[bool]:
v2 = v1['Type of Layoff'].lower() == 'temporary'
if v2:
return False
return... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> None:
v2 = ' '
v3 = 'Estado Atual:\n'
v3 += f'Quantum: {v1}\n'
print(v3)
return
``` |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
if os.path.isdir(v1):
return f"{v1.rstrip('/')}/*"
return v1
``` |
Imports:
```python
import numpy as np
import pandas as pd
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray):
if v1.dtype == object:
if any(np.isin(v1, self.parameters.index)):
v2 = self.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> bool:
if v1 == -1:
return True
for v2 in range(self._cost_dimension):
if self._available_costs[-1][v1][v2] + self._packed_costs... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tensor, int, Optional[Tensor]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tensor, v2: int, v3: Optional[Tensor]):
if v3 is None:
return v1
return v1.index_select(v2, v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Iterable
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Iterable:
with self._get_conn() as v2:
v3 = v2.cursor()
v4 = None
v5 = v3.execute('select currency_id from currencies w... |
Imports:
```python
from ctypes import CDLL, Array, Structure, c_char, c_char_p, c_int, c_int32, c_uint, c_uint8, c_uint16, c_uint32, c_ushort, cdll, pointer, sizeof
import typing
```
Type definitions:
Input Types: CDLL, c_int, int
Output Type: typing.Tuple[int, int, Optional[typing.List[bytes]]]
Dependencies:
Functio... |
Imports:
```python
import torch
from torch import nn
import typing
```
Type definitions:
Input Types: int, torch.Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: torch.Tensor):
assert v1 == 0 or self.last_get_n == v1 - 1, f'{v1}, {self.last_get_n}'
with tor... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: bytes, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes, v2: int) -> int:
v3 = np.frombuffer(v1[v2:], self.op2.idtype).copy()
if not v3[-1] == -1:
v3 = np.hstack([v3, -... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str) -> bool:
for v3 in v1:
if v3 in v2:
pass
else:
print('Word Error: Error with letter ' + v3)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
try:
try:
return v1.split('"song":{"type":"')[1].split('","image":')[0].split('"id":"')[-1]
except IndexError:
retur... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str], str, int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[str], v2: str, v3: int, v4: int):
if v3 == 0 and v4 == 0:
v1.append(v2)
else:
if v3 > 0:
self.gene... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Union[bytes, Callable[[str], Any], str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Union[bytes, Callable[[str], Any], str]) -> None:
self._group_data['fileName'] = v1
self._file_conten... |
Imports:
```python
import torch as t
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: t.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3) -> t.Tensor:
v4 = t.randn(size=(v1, v1), dtype=v2, device=v3)
(v4, v5) = t.qr(v4)
return v4
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: int, int, Optional[int]
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int, v3: Optional[int]=None) -> np.ndarray:
if v3 is None:
v3 = v2 + 1
if not v2 < v3:
... |
Imports:
```python
import matplotlib
import numpy as np
from matplotlib import patches
from matplotlib import pyplot as plt
from scipy.interpolate import CubicSpline
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: Tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]
Dependencies:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3=None) -> int:
v4 = self.exp.evaluacionCheck(v1, v2, v3)
if v4 != 1 and v4 != 2:
return 5
return v4
``` |
Imports:
```python
import asyncio
from asyncio import Task
import typing
```
Type definitions:
Input Types: int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: int) -> None:
del self.window_update_event[v1]
if self.response_task is not None:
await self.resp... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: int) -> bool:
v4 = super().__call__(v1, v2, v3)
return v4
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: Iterable[Tuple[Any]]=None, v2: Iterable[Any]=None):
self._vertexes = dict()
if v2 is not None:
for v3 in v2:
self._vertexes[v3] = set()
if v1 is not None:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> Dict:
v2: List[Optional[Dict[str, str]]] = []
if not v1.is_success:
v2 = [{'code': error.code, 'message': error.message} for v3 in v1.errors.deep_... |
Imports:
```python
import typing
```
Type definitions:
Input Types: typing.Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: typing.Any) -> None:
v2 = self.__items.index(v1)
del self.__items[v2]
self.begin_changes_event.fire(self.__items_key)
self.notify_remove... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
v2 = datetime.datetime.strptime(v1, '%Y%m%d%H%M%S.%f')
return v2.isoformat()
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, Union[List[int], np.ndarray]
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: Union[List[int], np.ndarray]) -> np.ndarray:
v3 = np.zeros((len(v1), len(v2)), dtyp... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict, v2: bool=False) -> None:
for (v3, v4) in v1.items():
try:
self.fields[v3].set(v4)
except KeyError:
pas... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> bool:
if v1 == 1:
return True
return self.isPerfectSquareHelper(1, v1, v1)
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: Callable[..., v0]
Output Type: Callable[..., v0]
Dependencies:
```python
def v1(v2: types.CodeType, v3: bool, v4: bool=False) -> types.CodeType:
v5 = Instrumentor(v2)
for v6 in v5.consts:
if isinstance(v6... |
Imports:
```python
import typing
```
Type definitions:
Input Types: {}
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: {}) -> bool:
if v1['type'] == 'script':
return 'run' in v1
if v1['type'] == 'remote':
return 'url' in v1 or 'path' in v1
return False
``` |
Imports:
```python
import hashlib
import uuid
import typing
```
Type definitions:
Input Types: uuid.UUID, Union[str, bytes]
Output Type: uuid.UUID
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: uuid.UUID, v2: Union[str, bytes]) -> uuid.UUID:
if isinstance(v2, str):
return uuid.uuid5(v1, v2... |
Imports:
```python
from collections import Counter, deque
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 = len(v1)
v4 = len(v2)
v5 = max(v3, v4)
v6 = 0
v7 = deque()
for v8 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any, T.Sequence[T.Union[T.Sequence[str], str]], Any, str, bool
Output Type: T.Tuple[bool, bool]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2, *, v3: T.Sequence[T.Union[T.Sequence[str], str]]=None, v4=None, v5: str... |
Imports:
```python
import os
import platform
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Any) -> bool:
if str(v1).strip().lower() == 'auto':
v1 = platform.system() == 'Linux' and (not (os.environ.get('DISPLAY')... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[str]:
v1 = self.decode(self.personality)
print(f'PERSONA:{v1}')
return v1
``` |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: torch.Tensor, v3: torch.Tensor=None) -> torch.Tensor:
if v1.shape[0] == 0:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
v1 = self._get_cache_dir(self.current_cache_index)
return v1.exists()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict) -> dict:
v2 = v1['style']['text']
v3 = v1['content']
v4 = self.lhood_text(*self.decoder_text(v2, v3))
return {'text': v4}
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: tp.Callable[['FPVector', 'FPVector'], tp.Any]
Output Type: tp.Callable[['FPVector', tp.Any], tp.Any]
Dependencies:
```python
def v0(v1: tp.Type['FPVector'], v2: tp.Any) -> 'FPVector':
if not isinstance(v2, FPVector):
return v1(v2)
elif... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int):
assert isinstance(v1, int) and v1 > 0
v2 = 2 ** (v1 - 1).bit_length()
assert v1 <= v2 < 2 * v1, f'{v1}, {v2}'
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, str, str, str, str, str, str, str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str='', v2: int=443, v3: str='', v4: str='', v5: str='origin', v6: str='', v7: str='plain', v8: str='', v9: str=Non... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[str]) -> None:
for v2 in v1:
self.__states[v2] = True
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
if self._statistics is None:
v1 = len(self.list_data_assets_validated())
v2 = len(self.list_validation_results())
v3 = len([valid... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(ABC):
v1: str = ' \n\t\r'
v2: bool = False
v3: OptionalType[type] = None
@staticmethod
def v4(v5: str) -> None:
"""
Overrides the default whitespace chars
Example::
# default whitespace c... |
Imports:
```python
import numpy as np
import cv2
import typing
```
Type definitions:
```python
class v0(object):
def __init__(self, v1: Projection, v2, v3, v4, v5, v6: float=1.0):
self.lens = v1
v7 = np.eye(4)
v7[0:3, 3] = v2
v7[0:3, 0:3] = v3
self._pose = np.asarray(v7, dty... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any, np.ndarray
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1=0, v2: np.ndarray=None) -> np.ndarray:
if v1 >= self.input_size:
raise IndexError(f'Input index: {v1} >= max si... |
Imports:
```python
import copy
import typing
```
Type definitions:
Input Types: Any
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> str:
assert len(v1.sentence_level_entities) == 1
(v2, v3) = (v1.sentence_level_entities[0].start, v1.sentence_level_entities[0].end)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: int) -> str:
v3 = []
for v4 in range(len(v1)):
v5 = v1[v4]
if v5.isupper():
v3.append(chr((ord(v5) + v2 - 65) % 26 +... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1=[], v2=[]) -> None:
for v3 in range(0, len(v1)):
try:
print('-' * (v1[v3] - 1) + v2[v3] + '-' * (29 - v1[v3]) + 'Goal')
except:
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: np.ndarray) -> None:
for v3 in range(self.n_folds):
v4 = np.logical_not(self.outer_clusters =... |
Imports:
```python
from matplotlib import axes
import matplotlib.pyplot as plt
import typing
```
Type definitions:
Input Types: Tuple[float, float]
Output Type: axes.Subplot
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tuple[float, float]=(20, 20)) -> axes.Subplot:
(v2, v3) = plt.subplots(1, fig... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
v1 = self.__metadata.copy()
v1.pop('dictionary')
v1['dictionary_size'] = len(self.__dictionary)
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int], int
Output Type: Tuple[int, int, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int], v2: int) -> Tuple[int, int, int]:
for v3 in range(0, len(v1) - 1):
v4 = v1[v3]
v5: List[int] = v1[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 = str(v1).encode('utf-8')
return self._set_and_assert(b'set_full_charge_duration', v2)
``` |
Imports:
```python
import torch
import torch.nn as nn
from torch.ao.quantization.fake_quantize import FakeQuantize, FakeQuantizeBase, default_fake_quant, default_dynamic_fake_quant, default_per_channel_weight_fake_quant, default_weight_fake_quant, default_fused_act_fake_quant, default_fused_wt_fake_quant, FusedMovingAv... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'geo.RayDifferential'
Output Type: 'BSSRDF'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'geo.RayDifferential') -> 'BSSRDF':
self.dg.compute_differential(v1)
return self.primitive.get_bssrdf(self.dg, self.o2w)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: Callable
Dependencies:
```python
def v0(v1: 'Adversary', *v2, **v3):
v1.model.attack(True)
v4 = func(v1, *v2, **v3)
v1.model.attack(False)
return v4
```
Function Name: v5
Function:
```python
def v5(v6) -> Callable:
... |
Imports:
```python
from PIL import Image, ImageDraw, ImageFont, ImageFilter, ImageColor, ImageMath, ImageOps
import typing
```
Type definitions:
Input Types: Image, Image
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Image, v2: Image):
v3 = ImageMath.eval("convert(a,'RGB')", a=v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: assets.AssetManager
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: assets.AssetManager) -> None:
v2 = v1
v2.create_context('c1')
v2.create_context('c2')
assert set(v2.list_context_names()) == {'c1', '... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=30000, v2: bool=True) -> None:
v3 = f'netserver -p {v1} '
if not v2:
v3 += ' -D '
self.node.execute(v3, sudo=True, expected_exit_... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1, v2=None, v3=None):
"""
Constructor for a node, the sub-trees can be omitted if there is no value for these.
:param value: The node payload.
:param left: the left sub-tree (defined as an... |
Imports:
```python
import subprocess
import zipfile
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=None):
print('Installing VSCode.\n')
self.vscode_path.mkdir(exist_ok=True, parents=True)
v2 = self.vscode_path ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list[int]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list[int]) -> int:
v2 = 0
v3 = v1[0]
v4 = v1[0]
v5 = []
for v6 in v1:
if v6 > v3:
v3 = v6
if v6 < v4:
... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
if not v1.endswith(os.sep):
v1 += os.sep
self.pickle_path = v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: jt.Var
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> jt.Var:
v1 = self.FAF
v2 = v1.reindex(shape=[self.N, self.F, 3, 3], indexes=['i0', '@e0(i0, i1, i2)', 'i3'], extras=[v1])
for v3 in range(2):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'List[int]'
Output Type: 'int'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'List[int]') -> 'int':
if not v1:
return 0
v2 = [[0] * len(v1) for v3 in range(len(v1))]
(v4, v5, v6) = (0, 0, 0)
for v6 in ra... |
Imports:
```python
import typing
```
Type definitions:
Input Types: SDF.math.Vector3, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: SDF.math.Vector3, v2):
v3 = self.to_parent_frame(v1)
return v2.to_local_frame(v3)
``` |
Imports:
```python
from typing import Any, Callable, Generator, TextIO, Union, cast
import typing
```
Type definitions:
Input Types: Callable
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Callable=f_id) -> dict:
v2: dict[Union[flowfilter.TFilter, str], Any] = {}
for (v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, types.Context, Any
Output Type: Any
Dependencies:
```python
def v0(v1, v2: types.Context):
v3 = FORMATTERS.get(type(v1))
if v3 is None:
import pdb
pdb.set_trace()
raise Exception('Need to write a formatter for {}'.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: v1, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: v1, v2: int):
v3 = ''
for v4 in range(v2):
v3 += v1[v4]
v3 += '..."\n'
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1=False) -> dict:
v2 = {}
v3 = []
v2['symbol'] = self.symbol
if self.order_id is not None or v1:
v2['orderID'] = self.order_id
if self... |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str):
v3 = logging.getLogger(v1)
v3.setLevel(logging.INFO)
v4 = logging.FileHandler(v2)
v4.setLevel(logging.INFO)
v5 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: Tuple[Optional[float], Optional[float]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: np.ndarray) -> Tuple[Optional[float], Optional[float]]:
v3: Optional[float] = None
... |
Imports:
```python
from .csv import csv_row
from .csv import csv_quote
from .csv import csv_split
from .csv import csv_unquote
from .csv import csv_splitlines
import typing
```
Type definitions:
```python
class v0(object):
@t.overload
def __init__(self, v1: t.Optional[t.Dict[str, int]]):
...
@t.ov... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: int):
v3 = sum([ord(c) * v2 ** idx for (v4, v5) in enumerate(v1)])
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: 'BaseTransformer'
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> 'BaseTransformer':
self.apply(method='_invalidate')
return self
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> str:
try:
if len(v1) == 0:
return 'empty string'
return v1.upper() + ', ' + v1.lower()
except Exception:
return 'not a ... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: dict, str, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict, v2: str, v3: str='index') -> None:
if v2.split('.')[-1].lower() == 'csv':
v4 = pd.DataFrame.from_dict(v1, orient=v3)... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: IO[str]
Dependencies:
```python
def v0(v1: int) -> None:
nonlocal found
if found:
return
visited[v1] = True
if v1 == t:
v2 = True
return
for v3 in self._adjacency[v1]:
if not vi... |
Imports:
```python
from shlex import split
from subprocess import Popen
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> int:
v2 = f'pip --no-cache-dir --disable-pip-version-check --retries 0 --timeout 5 --no-input {v1}'
... |
Imports:
```python
from math import exp, pi, sqrt
import typing
```
Type definitions:
Input Types: float, float, float
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float, v2: float, v3: float) -> float:
v4 = 1.0 / (v3 * sqrt(2.0 * pi))
return v4 * exp(-0.5 * ((v1 - v2) / v... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: Union[str, List[str]], str, int, Optional[List[str]]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[str, List[str]], v2: str='./', v3: int=6, v4: Optional[List[str]]=None) -> None:
try:
... |
Imports:
```python
import numpy as np
import torch
from sklearn.mixture import GaussianMixture
import typing
```
Type definitions:
Input Types: Type[torch.nn.Module], Union[torch.Tensor, np.ndarray], int
Output Type: Tuple[np.ndarray]
Dependencies:
```python
def v0(v1: Type[torch.nn.Module], v2: Union[torch.Tensor, np... |
Imports:
```python
import typing
```
Type definitions:
Input Types: aiohttp.web.Request
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(v1: aiohttp.web.Request):
v2 = v1.app['settings']['minimum_password_length']
if len(v1['data']['password']) < v2:
return f'Password ... |
Imports:
```python
import torch
import torch.distributed.rpc
from torch._C import Future as CFuture
from torch._sources import get_source_lines_and_file, parse_def, fake_range
from torch.futures import Future
import torch.package._mangling as package_mangling
import typing
```
Type definitions:
Input Types: Any
Output... |
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=None):
self.slack_client.api_call('chat.postMessage', channel=self.channel, text=v1, thread_ts=v2)
return
``` |
Imports:
```python
import inspect
from typing import Union, Any, Optional, Iterable, Pattern, Dict, Callable, cast, Set, List
import typing
```
Type definitions:
Input Types: str
Output Type: Set[str]
Dependencies:
```python
def v0(v1: Any) -> Optional[List[Any]]:
if v1 is None:
return None
if isinstan... |
Imports:
```python
import os
import logging
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: logging.Logger
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2) -> logging.Logger:
v3 = logging.getLogger(v1)
v3.setLevel(logging.DEBUG)
v4 = logging.Formatter(fmt='%(asctim... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float, float, float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float, v2: float, v3: float):
self.pnt.x = self.pnt.x + v1
self.pnt.y = self.pnt.y + v2
self.pnt.z = self.pnt.z + v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
if v1 == 'rgt':
self.rbtx.right.write_handcamimg_ftp()
elif v1 == 'lft':
self.rbtx.left.write_handcamimg_ftp()
else:
r... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: matplotlib.axes.Axes, np.ndarray, np.ndarray, np.ndarray, matplotlib.colors.ListedColormap, float
Output Type: matplotlib.axes.Axes.contour
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: matplotlib.axes.Axes, v2: np... |
Imports:
```python
import numpy as np
import pandas as pd
from tqdm.auto import tqdm
import typing
```
Type definitions:
Input Types: pd.Series, pd.Series, pd.Series, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any
Output Type: pd.Series
Dependencies:
```python
def v0(v1: pd.Series, v2: pd.Series, v3=100, v4=0.0... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, List[str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int, v3: List[str]) -> None:
v4 = []
for v5 in v3:
v4.extend([subline.strip() for v6 in v5.splitlines()])
self._as... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: dict
Dependencies:
```python
def v0(v1: Type) -> str:
if v1.__module__ == 'builtins':
return v1.__name__
if v1.__module__ == 'typing':
return str(v1).replace('typing.', '')
return f'{v1.__module__}.{v1.__n... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
v2: V1alpha1ApplicationList = self._application_service.list_mixin9(project=[v1])
return self._make_enforcements(v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: dict[int, list[int]]
Dependencies:
```python
def v0(v1):
return input(v1).strip().split(' ')
```
Function Name: v2
Function:
```python
def v2(v3: int, v4: int) -> dict[int, list[int]]:
v5: dict[int, list[int]] = {}
fo... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tuple[torch.Tensor, torch.Tensor], int
Output Type: Dict[str, torch.Tensor]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tuple[torch.Tensor, torch.Tensor], v2: int) -> Dict[str, torch.Tensor]:
(v3, v4) = v1
v4[v4 == 25... |
Imports:
```python
from contextlib import ExitStack
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: _TaskInfo, v2: _Operand, v3: _Operand):
self.info = v1
self.left = v2
self.right = v3
def v4(self):
return _Operand(self.info.task_id, self.info.fu... |
Imports:
```python
import argparse
import typing
```
Type definitions:
Input Types:
Output Type: argparse.ArgumentParser
Dependencies:
Function Name: v0
Function:
```python
def v0() -> argparse.ArgumentParser:
v1 = argparse.ArgumentParser()
v1.add_argument('--bbox-geojson', required=True, type=str)
v1.ad... |
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