text stringlengths 190 325k |
|---|
Imports:
```python
import torch
from torch import Tensor, device
from torch.nn import Module
import typing
```
Type definitions:
Input Types: Tuple[Tensor, ...], List[bool]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tuple[Tensor, ...], v2: List[bool]) -> None:
assert isinstan... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: models.StocksEquitiesDailyOpenCloseApiResponse
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, **v3) -> models.StocksEquitiesDailyOpenCloseApiResponse:
v4 = f'{self.url}/v1/open-close/{v1}/{v2}'
... |
Imports:
```python
import io
from matplotlib import figure
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
from matplotlib.animation import FFMpegFileWriter
from matplotlib import collections as mc
import matplotlib.patches as patches
from matplotlib.patches import Circle, Wedge
import typing
`... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self._check_field_byte('WA0AA', 'WA0BBR', 2)
v2 = self._check_field_byte('WA0AA', '#WA0TTY', 1, input_len=0, input_base_reg='R0')
self._chec... |
Imports:
```python
from inspect import signature
import typing
```
Type definitions:
```python
v0 = Tuple[State, Optional[Union[bool, int, float, str]]]
```
Input Types: Callable[[str, Union[bool, int, float, str]], None], Callable[[str], v0]
Output Type: Any
Dependencies:
Function Name: v1
Function:
```python
def v1(... |
Imports:
```python
import cv2
import numpy as np
import typing
```
Type definitions:
Input Types: list, tuple
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: tuple=(640, 360)) -> np.ndarray:
v3 = []
for v4 in v1:
v3.append(np.hstack((cv2.cvtColor(cv2.re... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(ABC):
@abstractmethod
def v1(self) -> str:
pass
@abstractmethod
def v2(self) -> str:
pass
@abstractmethod
def v3(self) -> str:
pass
@abstractmethod
def v4(self) -> str:
pass
```
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v1 = v1.replace('/', '\\/')
if v1.endswith('+'):
v1 = v1.rstrip('+')
v1 = v1 + '[^\\/]*'
v1 = v1.replace('+', '.*')
v1 = v1.repl... |
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(v1: np.ndarray) -> np.ndarray:
v2 = np.tile(v1, (5, 5))
(v3, v4) = v1.shape
for v5 in range(5):
for v6 in range(5):
... |
Imports:
```python
import os
import tensorflow.compat.v1 as tf
import typing
```
Type definitions:
Input Types: Optional[tf.Graph]
Output Type: bool
Dependencies:
```python
def v0(v1: tf.Graph) -> Optional[object]:
v2 = v1._get_control_flow_context()
while v2:
if v2.IsXLAContext():
return v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> int:
v2 = 0
v3 = '0'
for v4 in v1:
if v4 == v3:
continue
else:
v3 = v4
v2 += 1
retur... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Iterable[str]
Output Type: int
Dependencies:
```python
def v0(v1: str) -> int:
v2 = []
for v3 in v1.strip():
match v3:
case '(' | '[' | '{' | '<':
v2.append(v3)
case ')':
if v2.po... |
Imports:
```python
import typing
```
Type definitions:
Input Types: types.Message, dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: types.Message, v2: dict):
v3 = await self._patcher.check_async(v1.text, self.pattern)
if v3 is None:
return
v4 = {}
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
```python
def v0(v1: list, v2: str, v3: list):
if v3 is None:
v3 = list()
for v4 in v1:
if v2 in v4 and set(v3).issubset(v4[v2]):
return v4
return None
```
```python
def v5(v6... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.acquire()
try:
for v1 in [self.err, self.out]:
if v1 and hasattr(v1, 'flush'):
v1.flush()
finally:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True):
for v2 in self.get_children_nodes():
v2.mark_invalid(v1)
v2.mark_children_invalid(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int=1, v2: str='ABC') -> bool:
str(v1) + v2
return
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(abc.MutableMapping):
v1: 'Dict[Any, ColumnBase]'
v2: bool
v3: Tuple[Any, ...]
def __init__(self, v4: Union[abc.MutableMapping, v0]=None, v5: bool=False, v6=None):
if v4 is None:
v4 = {}
if isinstance(v... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(_Pack):
def __init__(self, v1: Path, v2: Optional[Project]=None) -> None:
super().__init__(v1, project=v2)
self._entities: Optional[BpEntities] = None
self._animation_controllers: Optional[BpAnimationControllers] = No... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: float
Output Type: Any
Dependencies:
```python
def v0(v1):
v1 = torch.fmod(v1, 2 * phase_range)
v1[v1 > phase_range] = 2 * phase_range - v1[v1 > phase_range]
return v1
```
Function Name: v2
Function:
```python
def v... |
Imports:
```python
from typing import List, Optional, Tuple
import typing
```
Type definitions:
Input Types: Tuple
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tuple) -> str:
(v2, v3) = v1
if isinstance(v3, List):
v4 = 'Any' in v3
if not v4:
... |
Imports:
```python
import numpy as np
from numpy import ndarray
import typing
```
Type definitions:
Input Types: ndarray
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: ndarray) -> bool:
if v1.ndim == 0 and np.all(np.isnan(v1)):
return True
else:
return False
`... |
Imports:
```python
from datetime import datetime
from pathlib import Path
import numpy as np
import h5py
import typing
```
Type definitions:
Input Types: Path, Any
Output Type: Any
Dependencies:
```python
def v0(v1: Path) -> Path:
v2 = datetime.now().strftime('_%Y_%m_%d_%H_%M_%S')
v3 = v1.parent / 'backup'
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float, float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float, v2: float):
assert 0 < v1 < 1
assert 0 < v2 < 1
self._position = (v1, v2)
return self
``` |
Imports:
```python
from sklearn.preprocessing import LabelEncoder
import pandas as pd
from sklearn.utils import compute_class_weight
import typing
```
Type definitions:
Input Types: pd.Series, pd.Series
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: pd.Series, v2: pd.Series):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: List[int]
Dependencies:
```python
def v0(v1: int, v2: int) -> List[int]:
if v2:
return [0] * v1 + [0] + [0] + [1] * v2 + [1]
else:
return [0] * v1 + [0] + [0]
```
```python
def v3(v4: int, v5: int) -> List[int]... |
Imports:
```python
from math import acos, asin, atan2, cos, degrees, floor, radians, sin, sqrt
import typing
```
Type definitions:
Input Types: Tuple[float, float], Tuple[float, float], float
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tuple[float, float], v2: Tuple[float, float]... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
v1 = 'NIFTY 50'
v2 = 'NIFTY NEXT 50'
```
```python
class v3:
v4 = 'historical_pepb'
v5 = 'historicalindices'
```
Input Types: v3, v0, date, date
Output Type: Any
Dependencies:
Function Name: v6
Function:
```python
def v6(self, v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict):
if not v1:
return []
return ','.join(['{}={}'.format(k, v) for (v2, v3) in v1.items()])
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: requests.Response
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: requests.Response) -> Any:
if v1.status_code == 204:
return None
else:
v2 = v1.headers['Content-Type'].split(';')[0]
ass... |
Imports:
```python
import os, sys
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
```python
def v0(v1):
return os.path.join(get_files_dir(), v1)
```
```python
def v2():
v3 = os.getcwd()
return os.path.join(v3, 'assets\\files')
```
Function Name: v4
Function:
```python
de... |
Imports:
```python
import typing
```
Type definitions:
Input Types: sqlite3.Cursor, bool, bool, bool, str, int, bool
Output Type: Any
Dependencies:
```python
def v0(v1: str):
if v1[0] == '+':
return "date('now', '" + v1 + "')"
if v1 == 'today':
return "date('now')"
if v1 == 'tomorrow':
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: object
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: object):
if not self._initialized:
raise RuntimeError('Must call initialize before checking gates/configs/experiments or logging events')
v1.... |
Imports:
```python
import requests
from requests import ConnectTimeout, PreparedRequest, RequestException, Response
from requests.auth import HTTPBasicAuth
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
try:
sel... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
v2 = self.get_node(v1)
if v2 is None:
raise KeyError('No object named {key} in the file'.format(key=v1))
return self._read_group(v2)
`... |
Imports:
```python
import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.axes import Axes
from matplotlib.figure import Figure
from matplotlib.patches import Rectangle, Arrow
import typing
```
Type definitions:
Input Types: Tuple[float, float, float, float], List[str... |
Imports:
```python
import datetime
import logging
import typing
```
Type definitions:
Input Types: int
Output Type: Tuple[Optional[datetime.datetime], Optional[datetime.datetime]]
Dependencies:
```python
def v0(v1: int, v2: Text) -> Optional[datetime.datetime]:
v3 = None
try:
v4 = registry.get_value(v2... |
Imports:
```python
import numpy as np
from numpy import ndarray
from scipy import sparse
from scipy.sparse.csc import csc_matrix
from scipy.sparse.dia import dia_matrix
import typing
```
Type definitions:
Input Types:
Output Type: csc_matrix
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> csc_mat... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict, v2: bool=True):
v3 = {}
if self.ohots is not None:
v3['ohots'] = {f: c.exemplify(v1['tokens']) for (v4, v5) in self.ohots.items()}
... |
Imports:
```python
import math
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
if self.__number < 0:
raise ValueError('Number cannot be less than zero')
return math.factorial(self.__number)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
if v1 not in self.Triggered:
return
self.Triggered[v1] = set()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list):
v2 = {k: v for (v3, v4) in v1}
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
for v1 in self.inputs():
v1.finalize()
``` |
Imports:
```python
import numpy as np
import cv2
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: np.ndarray, v3='b'):
if v3 == 'b':
v2 = np.concatenate([np.zeros((v2.shape[0], v2.sh... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(BaseModel):
v1: int = Field(description='Page index, must not be negative.', ge=0)
v2: int = Field(description='The size of the page to be returned, must be greater than 0.', gt=0)
@staticmethod
def v3(v4: int) -> 'PageRequest':
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> int:
v2 = v1.cursor()
v3 = 'SELECT COUNT(*) AS count from dbo.classified_widgets where is_good = 1'
v4 = v2.execute(v3).fetchone()
return v4.count
... |
Imports:
```python
import numpy as np
from scipy.stats import multivariate_normal, lognorm, norm, chi
import typing
```
Type definitions:
Input Types: np.ndarray, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2='univar_gaussian'):
v3 = {'distr': v2}
v4 = 1e-0... |
Imports:
```python
import csv
import typing
```
Type definitions:
Input Types: str, List[dict]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: List[dict]):
with open(v1, mode='w') as v3:
v4 = v2[0].keys()
v5 = csv.DictWriter(v3, v4)
v5.writeheader()... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Iterable[Tuple[float, float]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Iterable[Tuple[float, float]]:
for v1 in self:
yield (v1[0], v1[1])
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
v1: ArgumentParser
@classmethod
def v2(cls):
pass
```
Input Types:
Output Type: Any
Dependencies:
Function Name: v3
Function:
```python
def v3(cls: v0):
cls.parser.set_defaults(target=cls.run)
return cls
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: argparse.ArgumentParser
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: argparse.ArgumentParser):
v2 = v1.add_subparsers(dest='doc', help='DO NOT USE DOC SLUG AS IDENTIFIER WHICH MAY CAUSE ERROR')
v2.required =... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int], List[int]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int], v2: List[int]) -> int:
v3: List[int] = sorted([-(s // -d) for (v4, v5) in zip(v1, v2)])
for v6 in range(len(v3)):
if... |
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:
if self.norm_obs:
if self.dim_off is None:
v1 = np.clip((v1 - self.obs_rms.m... |
Imports:
```python
from collections import OrderedDict
import typing
```
Type definitions:
Input Types: Dict, str, Union[List, None], Any
Output Type: Union[Union[Dict, OrderedDict], List[Union[Dict, OrderedDict]]]
Dependencies:
```python
def v0(v1):
if len(v1) == 1:
return v1[0]
return v1
```
Function... |
Imports:
```python
import traceback
import sys
import typing
```
Type definitions:
Input Types:
Output Type: Callable
Dependencies:
```python
async def v0(v1: Request) -> Response:
v2 = v1.url._url
v3 = v1.cookies
print(f'Received request: url={v2!r} cookies={v3!r}')
try:
v4 = await original_r... |
Imports:
```python
from io import StringIO
import typing
```
Type definitions:
Input Types: str, Optional[str], Optional[str], bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, *v5: object, v2: Optional[str]=..., v3: Optional[str]=..., v4: bool=...):
v6 = self.console... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
self.distance[v1] = 0
for v2 in range(len(self.vertices)):
for v3 in self.edges:
v4: str = v3[0]
v5: str = v3[1]
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, float
Output Type: List[float]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: float=None) -> List[float]:
v3 = v1.shape[2]
v4 = v1.shape[1]
v5 = []
for v6 in range(len(v1)... |
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:
if v1 == -2 ** 31:
if v2 == -1:
return 2 ** 31 - 1
if v2 == 1:
return v1
if v1 == 2 *... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int) -> bool:
if self.middle:
return False
self.middle = True
self.x = v1
self.y = v2
return False
``` |
Imports:
```python
from tensorflow import keras
import typing
```
Type definitions:
Input Types: tuple, int, Any
Output Type: keras.Model
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: tuple, v2: int, v3=1024) -> keras.Model:
v4 = keras.layers.Input(shape=v1)
v5 = v4
v5 = keras.layers.Flat... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int]
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int]) -> List[int]:
v2 = range(1, len(v1) + 1)
v3 = [0] * (len(v1) + 1)
for v4 in v1:
v3[v4] += 1
for v5 in v2:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.lists = self.list = self.list_media
self.protect = self.protect_media
self.unprotect = self.unprotect_media
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[list], Optional[list], Optional[list], str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[list]=None, v2: Optional[list]=None, v3: Optional[list]=None, v4: str='In') -> None:
v5 = bool(not... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Optional[str]
Output Type: Iterable[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Optional[str]=None) -> Iterable[str]:
v3 = v2 or self.bucket
for v4 in self.ch.s3_resource.Bucket(v3).objects.filter(P... |
Imports:
```python
import os
import gzip
from binascii import unhexlify
import typing
```
Type definitions:
Input Types: str, Union[str, bytes]
Output Type: bytes
Dependencies:
```python
def v0(v1: Union[str, bytes], v2: bytes) -> bytes:
if not isinstance(v1, bytes):
v1 = int(v1.replace(' ', ''), 0).to_byt... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: (int, list[int])
Dependencies:
Function Name: v0
Function:
```python
def v0() -> (int, list[int]):
with open('input.txt') as v1:
v2 = int(v1.readline().rstrip())
v3 = v1.readline().rstrip().split(',')
return (v2,... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[Iterable[int]]
Output Type: Optional[Set[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[Iterable[int]]=None) -> Optional[Set[int]]:
if v1 is not None:
self._proc.cpu_setaffinity(v1)
re... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: int
Output Type: Generator[float, None, None]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=10) -> Generator[float, None, None]:
(v2, v3) = self.u_domain
return np.linspace(v2, v3, v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any
Output Type: Any
Dependencies:
```python
def v0(v1: Iterable, v2: Tuple[str], v3, v4: int):
from towhee.utils.milvus_utils import Collection, MutationResult
if isinstance(v3, str):
v3 = Collection(v3)
v5 = []
v6 = 0
... |
Imports:
```python
import matplotlib.pyplot as plt
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame):
v2 = {}
v3 = list(v1.columns)
v3.remove('NODECODE')
v3.remove('PICKINGLIST')
v3.remove('IN... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> int:
v2 = 0
v3 = 1
for v4 in range(1, len(v1)):
if v1[v4 - 1] == v1[v4]:
v3 += 1
else:
v2 = max(v2, ... |
Imports:
```python
import logging
from datetime import datetime, timezone
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=14):
for v2 in self.certificate_client.list_properties_of_certificates():
if not v2.enabl... |
Imports:
```python
from operator import itemgetter
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.ident:
self.attr_sheet.colnames = self.title_list
for v1 in filter(itemgetter(self.ident), self.a... |
Imports:
```python
import os
import requests
import zipfile
import io
from pathlib import Path
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str='https://ndownloader.figshare.com/files/25791104', v2: str='grid'):
v3 = Path... |
Imports:
```python
import itertools
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, list[tuple[int, int]], Any
Output Type: Any
Dependencies:
```python
def v0(v1: np.ndarray, v2, v3, v4: int, v5: int):
v6 = np.full(shape=(v2, v3), dtype=bool, fill_value=False)
if v4 == 0:
... |
Imports:
```python
from PIL import Image, ImageFile
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2) -> List[str]:
v3 = []
for v4 in v2:
with Image.open(v4) as v5:
if v5.size == v1:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> int:
v2 = {int(c) for v3 in v1 if v3.isdigit()}
if len(v2) < 2:
return -1
(*v4, v5, v4) = sorted(list(v2))
return v5
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Union[TASK_TRACKER_COLUMN, ACTIVITY_TRACKER_COLUMN]
```
Input Types: pd.DataFrame, v0, Any, Any
Output Type: pd.DataFrame
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: pd.DataFrame, v3: v0, v4: Any, v5: Any=None) -> pd.DataFrame:
... |
Imports:
```python
from typing import Any, Dict, List, Optional, cast
import tensorflow as tf
from tensorflow.python.training.tracking.tracking import AutoTrackable
import typing
```
Type definitions:
Input Types: pathlib.Path, Dict[str, Any], Optional[List[str]]
Output Type: AutoTrackable
Dependencies:
```python
def ... |
Imports:
```python
import numpy as np
from numpy import ndarray
import typing
```
Type definitions:
Input Types: ndarray
Output Type: ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: ndarray) -> ndarray:
v2 = v1.shape[0]
return np.kron(v1, np.identity(v2)) - np.kron(np.identity(v2), v1.T... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: str
Dependencies:
```python
def v0(v1: int, v2: int=1) -> str:
assert isinstance(v1, int)
v3 = pow(256, v2)
if v1 < -v3 / 2 or v1 >= v3:
raise OverflowError('cannot convert int {} to hex ({} bytes)'.format(v1, v2))... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> str:
v1 = await self._state.create_team_invite(self.id)
return v1.get('invite', v1).get('id')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.has_bag_server:
self._eval_skill('close_all_cellviews()')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> float:
if 1 < v1:
v2 = self.__get_previous_horizon_index(v1)
if v2 is not None:
v3 = self.points[v1][self.VERTICAL_ANG... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, int, Dict, Dict[str, float], Dict[str, float], float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: int, v3: Dict, v4: Dict[str, float], v5: Dict[str, float], v6: float=500):
for v7 in v3.values():
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self._simulation.panda_robot.reset()
self._simulation.y = 0.015
if self._object_id is not None:
self._simulation.remove_object(self._obje... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: typing.NoReturn
Dependencies:
Function Name: v0
Function:
```python
def v0() -> typing.NoReturn:
(v1, v2) = map(int, input().split())
v3 = np.array(input().split(), dtype=np.int64)
v4 = np.array(input().sp... |
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:
for v2 in v1:
v3 = self.root.insertValue(v2)
if v3 is not None:
self.root = v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: tuple
Output Type: str
Dependencies:
```python
def v0(v1: dict) -> dict:
v2 = dict()
while v1:
v3 = str()
v4 = str()
for (v5, v6) in v1.items():
if len(v6) == 1:
v3 = v6.pop()
... |
Imports:
```python
import torch
import torch.utils.data
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor):
v2 = torch.cat((self.model.get_s_embedder()._embeddings.weight.data[:len(v1)].cpu(), self.model... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: int):
if 1 <= v1 <= self.ctx.cog.latest_number:
await self.show_page(v1)
``` |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = re.split('/([0-9]{5,7})', v1)
v3 = None
for v4 in v2:
try:
v3 = int(v4)
except ValueError:
pa... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: [[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> [[int]]:
v2 = []
for v3 in range(v1):
v4 = [0 for v5 in range(v1)]
v2.append(v4)
(v5, v6) = (0, 0)
v7 = 0
(v8, v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: str):
for (v3, v4) in enumerate(v1):
if v4 != '' and v2.startswith(v4):
return v3
raise Exception(f'Did not find {v2} in {v1}')
`... |
Imports:
```python
import torch
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, builtins.float, builtins.bool
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: torch.Tensor, *, v3: builtins.float=0.00... |
Imports:
```python
from sklearn.model_selection import GridSearchCV, RepeatedStratifiedKFold, cross_val_score, cross_validate
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.neighbors import KNeighborsClassifier
import typing
```
Type definitions:
Input Types: dict, Any, An... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[docspec.Module]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[docspec.Module]):
assert v1[0].name == 'docspec_python'
assert any((x.name == 'docspec_python.parser' for v2 in v1))
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tuple[int, int]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tuple[int, int]) -> bool:
(v2, v3) = v1
return not 0 <= v2 < self.size or not 0 <= v3 < self.size
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> int:
v1 = v1.strip()
if len(v1) == 0:
return 0
if v1[0] == '-':
v2 = -1
v1 = v1[1:]
elif v1[0] == '+':
v... |
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