text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: 'PagureIssue'
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> 'PagureIssue':
v1 = {'status': 'Closed'}
self.project._call_project_api('issue', str(self.id), 'status', data=v1, method='POST')
self.__dirty ... |
Imports:
```python
from typing import cast
import torch
import torch.nn.functional as F
from torch.nn.modules import Module
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: torch... |
Imports:
```python
import typing
```
Type definitions:
Input Types: [str, list]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: [str, list]) -> str:
if isinstance(v1, str) or isinstance(v1, list):
self.meta['@graph']['scidata']['dataset']['scope'] = v1
return self... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Receive
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: Receive):
while True:
v2 = await v1()
if v2['type'] == 'http.disconnect':
break
``` |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types:
Output Type: typing.Dict[typing.AnyStr, typing.List[typing.Dict]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> typing.Dict[typing.AnyStr, typing.List[typing.Dict]]:
v1 = self._get_all_hearbeat_info_partition_by... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(DialogueStateTracker):
def __init__(self, v1, v2, v3=None, v4=None, v5=False, v6=UserMessage.DEFAULT_REQUEST_ID, v7=UserMessage.DEFAULT_USER_ID):
super(v0, self).__init__(v1, v6, v7, v2, v3)
self._states = None
self.d... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Decimal'
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: 'Decimal') -> str:
v2 = max(0, -v1.as_tuple().exponent)
return format(v1, f'.{v2}f')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, int, int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str='arg{i}: {Ts}', v3: int=0, v4: int=LIMIT) -> None:
print()
for v5 in range(v3, v4):
v6 = ', '.join(('T{i}'.format(i=j + 1... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
for v2 in self.vars['ignore_command_regexp']:
if re.search(v2, v1):
return True
return False
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, list, list, int, bool
Output Type: tuple
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list, v2: list, v3: list, v4: int, v5: bool) -> tuple:
(v6, v7) = self.__get_graph_and_data_manager()
(v8, v9) = v7.split_data... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.set_models({'meeting/222': {'name': 'meeting_222', 'is_active_in_organization_id': 1}})
v1 = self.request('motion.create_forwarded', {'title': '... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[int]=None):
super().reset(v1)
self.sampler_init.reinit(self._env, self.init_expl_policy)
self.sampler.reinit(self._env, self._exp... |
Imports:
```python
import math
from math import copysign
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.horizontal:
self.bcb_body.angle = 0
v1 = self.bar_loc * self.bcb_range
self.bcb_bod... |
Imports:
```python
import itertools
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1: list, v2: int=1) -> list:
v3 = len(v1)
for v4 in range(0, v3, v2):
yield v1[v4:min(v4 + v2, v3)]
```
Function Name: v5
Function:
```python
def v5(self: object, v6... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List):
for v2 in v1:
v3 = False
(v4, v5) = v2[0]
for v6 in self.components.values():
if v6.check_device_type(v4):
... |
Imports:
```python
import math
import typing
```
Type definitions:
Input Types: float, float, float, float, float, float
Output Type: float
Dependencies:
```python
def v0(v1: float) -> float:
return v1 * (math.pi / 180)
```
Function Name: v2
Function:
```python
def v2(v3: float, v4: float, v5: float, v6: float, v7... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Any', str, int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Any', v2: str, v3: int, v4: int):
v5 = [(field, getattr(v1, field)) for v6 in dir(v1) if not (v6.startswith('_') or v6 in ['metadata', 're... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float) -> float:
v1 = self.__cast_to_float(v1)
self.__raise_value_error_if_albedo_is_unphysical(v1)
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
if not isinstance(v1, str):
return False
if len(v1) < 6 or len(v1) > 20:
return False
return True
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float):
(v2, v3, v4) = self.grid.rasterize(v1)
return self._raster(v2, v3, v4)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int) -> Any:
v3 = self.block_path(v1, v2)
return self.load_pickle(v3)
``` |
Imports:
```python
import os
from matplotlib import pyplot as plt
import typing
```
Type definitions:
Input Types: str, bool, str, list, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=None, v2: bool=True, v3: str='png', v4: list='auto', v5: bool=True):
if v1 is None... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional['EntryPoint'], Dict[str, Any]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Optional['EntryPoint'], v2: Dict[str, Any]) -> str:
if v1 is None:
return ''
return v1.compute_command(v2)
``` |
Imports:
```python
import gzip
import typing
```
Type definitions:
Input Types: str, bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, *, v2: bool=False) -> None:
if v2:
with gzip.open(v1, 'wb') as v3:
v3.write(self.data)
else:
with op... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Imports'
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Imports') -> None:
assert not self._package and (not v1._package)
for (v2, v3) in v1.items():
self.__setitem__(v2, v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict[str, Any]:
v1 = {'cluster_name': self.cluster_name, 'database_name': self.database_name, 'parsed_conn': self.obfuscate_parsed_conn()}
v2 = s... |
Imports:
```python
import re
import numpy as np
import typing
```
Type definitions:
Input Types: Union[str, bytes, Pattern, Any], int, bool
Output Type: Union[Pattern, Any]
Dependencies:
```python
def v0(*, v1: Callable, v2: Any, v3: Union[str, np.dtype, Type]=None, v4: Union[list, tuple]=((),), v5: Mapping[Any, int]=... |
Imports:
```python
from statistics import mean, stdev
import typing
```
Type definitions:
Input Types: List[float]
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[float]) -> float:
if len(v1) == 0:
return 0
elif len(v1) == 1:
return 0
return stdev(v1)... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int) -> str:
v3 = f'{v1} in ('
v4 = self.DEFAULT_PLACEHOLDER
for v5 in range(v2):
v3 += f'{v4}'
v4 = f', {self.DEFAULT... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: Tuple[float, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: np.ndarray) -> Tuple[float, float]:
v3 = 0.01 * np.eye(v1.shape[-1])
v4 = np.linalg.solv... |
Imports:
```python
import pathlib
from pathlib import Path
from PIL import Image
from PIL import ImageOps
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str, v2: Union[str, None], v3: str):
self.filename = v1
if v1[-4:-1] == '.tif':
self.filename += '.tif... |
Imports:
```python
import typing
```
Type definitions:
Input Types: JavaParserLabeled.ClassBodyDeclaration2Context
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: JavaParserLabeled.ClassBodyDeclaration2Context):
if self.is_source_class is True:
self.nested_level += 1
... |
Imports:
```python
import pandas as pd
from collections import defaultdict, Counter
import typing
```
Type definitions:
Input Types: list, list
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: list) -> pd.DataFrame:
v3 = defaultdict(dict)
for (v4, v5) in zip(v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict, v2: str):
v3 = self._get(f'workflows/{v2}')
self._assert_status_code_is(v3, 200)
v4 = v3.json()['steps']
return sorted((step for v5 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
v2 = self.private_cursor.edition_states_
if v2:
v3 = v2.find(v1)
if v3 and v3 == v2.current():
self.private_c... |
Imports:
```python
import typing
```
Type definitions:
Input Types: object
Output Type: object
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: object) -> object:
try:
v1 = ('%f' % v1).rstrip('0').rstrip('.')
return v1
except TypeError:
return v1
``` |
Imports:
```python
import numpy as np
from scipy.optimize import linear_sum_assignment
import typing
```
Type definitions:
Input Types: Any, Any, Optional[int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3: Optional[int]=None):
if v3 is None:
v3 = max(v2.max(), v1.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor) -> int:
if len(v1.shape) < 4:
return 1
else:
return v1.view(-1, *v1.shape[-3:]).shape[0]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, int, int, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: int, v3: int, v4: bool):
if v2 < 0 or v2 >= self.width or v3 < 0 or (v3 >= self.height):
raise ValueError('x %d, y %d out of ran... |
Imports:
```python
from scipy.sparse import csr_matrix, lil_matrix
import typing
```
Type definitions:
Input Types: Any, Any, Callable
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2=[], v3: Callable=None):
v4 = v1[:, v2].toarray()
if not v3:
v3: Callable = sel... |
Imports:
```python
import typing
```
Type definitions:
Input Types: arxiv.Result
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: arxiv.Result):
self.assert_nonempty(v1.entry_id)
self.assertIsNotNone(v1.updated)
self.assertIsNotNone(v1.published)
self.assert_nonemp... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> bool:
(v3, v4, *v5) = v2.split(' ')
v4: str
v3: str = v3.lower()
v5 = ' '.join(v5)
if not v5:
return False
... |
Imports:
```python
import numpy as np
import scipy as sp
import pandas as pd
import typing
```
Type definitions:
Input Types: List[np.ndarray], int
Output Type: pd.DataFrame
Dependencies:
```python
def v0(v1: np.ndarray, v2: float=0.0001) -> Tuple:
if v1.shape[0] != v1.shape[1]:
raise ValueError('Transitio... |
Imports:
```python
import torch
import typing
```
Type definitions:
```python
class v0:
v1 = {'has_video': bool, 'video_timebase': Timebase, 'video_duration': float, 'video_fps': float, 'has_audio': bool, 'audio_timebase': Timebase, 'audio_duration': float, 'audio_sample_rate': float}
v2 = ['has_video', 'video_... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1: str=''):
global charm_of_hummingbirds
if v1 == '':
global current_hummingbird_slot
v1 = current_hummingbird_slot
return charm_of_hummingbirds[v1]
```
Function Name: v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: int
Dependencies:
```python
def v0(v1: str) -> Tuple[int, int]:
return (int(v1[:4]), int(v1[4:]))
```
Function Name: v2
Function:
```python
def v2(v3: str, v4: str) -> int:
assert v4 >= v3
(v5, v6) = v0(v3)
(v7, v... |
Imports:
```python
from datetime import date, datetime, timedelta
from polars.utils import _timedelta_to_pl_duration
from polars import internals as pli
from polars.datatypes import DataType, Date, Datetime, Float64, Int32, Object, UInt32, py_type_to_dtype
import typing
```
Type definitions:
```python
class v0:
de... |
Imports:
```python
import operator
import numpy as np
from skimage.transform import resize
import typing
```
Type definitions:
Input Types: np.ndarray, Optional[Tuple[int]]
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: Optional[Tuple[int]]) -> np.ndarray:... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
with self.lock:
return v1 in self.v_tx
``` |
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:
if self.big_endian == 1:
v3 = self.flip_bit_order(v1, v2)
self.m_bits |= v3 << self.count
else:
sel... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types:
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Optional[str]:
if self.get('wallet_path'):
return os.path.join(self.get('cwd'), self.get('wallet_path'))
return None
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: int, List[float], List[float], List[float]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: List[float], v3: List[float], v4: List[float]) -> Any:
(v5, v6, v7) = self.space.get_acti... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray) -> int:
v2 = [str(n) for v3 in v1]
v2 = int(''.join(v2))
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
v2 = self.moodle.post('mod_workshop_get_submission_assessments', submissionid=v1)
return v2
``` |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: str, int, Any, bool, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int, v3=True, v4: bool=False, v5: str=None):
with tf.variable_scope(v1):
v6 = self.__network.g... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: dict) -> None:
v2 = self._mx_handlers.get(str(v1.type), [self._on_mx_unhandled_event])
for v3 in v2:
await v3(v1)
``` |
Imports:
```python
import dataclasses
import typing
```
Type definitions:
Input Types: Optional[str]
Output Type: dataclasses.Field
Dependencies:
Function Name: v0
Function:
```python
def v0(*v2: Any, v1: Optional[str]=None) -> dataclasses.Field:
v2 = list(v2)
v3 = {'choices': v2, 'default': v2[0]}
if v1 ... |
Imports:
```python
from numpy import array, ndarray
from numpy.linalg import norm
import typing
```
Type definitions:
Input Types: int, int
Output Type: tuple[int, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int) -> tuple[int, int]:
v3: ndarray = array(self.tile_size) * self... |
Imports:
```python
from math import 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:
if v1 < 0 or v2 < 0 or v3 < 0:
raise ValueError('area_triangle_three_si... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types: str, str, float
Output Type: Tuple[str, str, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: float) -> Tuple[str, str, float]:
v4 = self.dag
v5 = self.hypernyms(v2) - self.hypernyms(... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, float
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: float) -> None:
v3 = v1.n
v4 = v2 - v3
v1.update(v4)
``` |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: Any
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> list:
v2 = '[γοΌ!οΌ?οΌ;ο½β¦ββ
]+'
v3 = re.split(v2, v1)
v4 = re.findall(v2, v1)
v4.append('')
v5 = [''.join(x) for v6 in zip(v3, v4)]
... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1: int = random.randint(3, 10)
v2: str = ''
for v3 in range(v1):
v2 += self.gen_random_sentence() + ' '
return v2
``` |
Imports:
```python
import numpy
import typing
```
Type definitions:
Input Types:
Output Type: numpy.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> numpy.ndarray:
if self.it == 0 or self.jacobian is None:
self.reset_jacobian()
v1 = numpy.reshape(self.dx, (self.dim, 1))
... |
Imports:
```python
import matplotlib as mpl
import matplotlib.cm as cmx
import matplotlib.colors as colors
import matplotlib.patches as mpatches
import matplotlib.path as mpath
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
from matplotlib import patheffects
import typing
```
Type definitions:... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> float:
v1 = {0: 1, 1: -1}
v2: List[str] = ['GPS GPSAltitude', 'EXIF GPS GPSAltitude']
v3: List[str] = ['GPS GPSAltitudeRef', 'EXIF GPS GPSAltitudeRef'... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Dict[Union[str, Tuple[None, str]], str]
```
Input Types: v0, str
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: v0, v3: str) -> v0:
if (None, 'class') not in v2:
v2[None, 'class'] = ''
v2[None, 'class'... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Callable[[object], Any], object
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Callable[[object], Any], v2: object) -> Any:
if v2 is None:
return None
return v1(v2)
``` |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: int, int, str, list, list
Output Type: Any
Dependencies:
```python
def v0(v1: str, *v3, v2=False):
v4 = subprocess.check_output(['which', v1]).decode('utf-8')[:-1]
v5 = [v4]
v5.extend(v3)
if v2:
return subproc... |
Imports:
```python
import copy
import typing
```
Type definitions:
```python
v0 = Union[None, bool, int, float, Text, List[Any], Dict[Text, Any]]
```
Input Types: Text
Output Type: v0
Dependencies:
```python
def v1(v2: Text) -> None:
if v2 in _REGISTERED_NAMES:
raise JwtInvalidError('registered name %s cann... |
Imports:
```python
import pandas as pd
from pandas.tseries.frequencies import to_offset
import typing
```
Type definitions:
Input Types: xr.DataArray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: xr.DataArray):
if isinstance(v1.get_index(self._time_dim), pd.DatetimeIndex):
... |
Imports:
```python
import asyncio
from asyncio.queues import Queue
from asyncio.tasks import Task
import logging
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
async def v0(v1: models.Queue) -> Task:
v2 = await get_first_incomplete_job(v1)
if v2:
v3 = proces... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: int
Dependencies:
```python
def v0(v1, v2):
res.append(v2)
for v3 in range(v1, len(nums)):
if v3 > v1 and nums[v3] == nums[v3 - 1]:
continue
v0(v3 + 1, v2 + [nums[v3]])
```
Function Name: v4
Fu... |
Imports:
```python
import pickle
from sklearn import preprocessing
from sklearn.model_selection import train_test_split
import typing
```
Type definitions:
Input Types: str, float, int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: float=None, v3: int=None) -> None:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: Any
Dependencies:
```python
def v0(v1: List[str]) -> str:
v2 = []
for v3 in v1:
if v3.find(' ') == -1:
v2.append(v3)
else:
v2.append('"' + v3 + '"')
return ' '.join(v2)
```
Fun... |
Imports:
```python
import numpy as np
import pandas as pd
import typing
```
Type definitions:
Input Types: Union[pd.DataFrame, ks.DataFrame]
Output Type: Union[pd.DataFrame, ks.DataFrame]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[pd.DataFrame, ks.DataFrame]) -> Union[pd.DataFrame, ks.... |
Imports:
```python
import logging
import typing
```
Type definitions:
```python
@total_ordering
class v0(collections.abc.Sequence):
def __init__(self, *v1):
self._data: list = v1
@classmethod
def v2(cls, v3):
"""Optimized shortcut to generate a path from an existing tuple"""
if isi... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[str]]
Output Type: BatchEncoding
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[List[str]]) -> BatchEncoding:
v2: BatchEncoding = self.tokzer(v1, is_split_into_words=True, return_tensors='pt', padding=True, ad... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Any], int
Output Type: Dict[int, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Any], v2: int=0) -> Dict[int, Any]:
v3 = {}
v4: Callable[[Any, int], Any]
if v2 < 2:
v4 = self._convert... |
Imports:
```python
import sys
from traceback import format_exception
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: BaseException=None, v2: TracebackType=None) -> Generator[Any, None, None]:
if not v1 or v2:
(v3, v4, v5) = sys.exc_info()
v1 = ... |
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=None, v2: str=None, v3: str=None, **v4):
v5 = self.process_message(v1, v2)
self.data = {'msg': v5, 'qq': v3}
return self.data
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True) -> None:
self.select_all = v1
for v2 in range(self.__listwidget.count()):
v3 = self.__listwidget.item(v2)
v4 = self.__listw... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: 'Grammar', *v2: Symbol):
self.grammar: Grammar = v1
self.sequence: Tuple[Symbol, ...] = v0.combine_terminals(v2)
self.has_terminals: bool = any((isinstance(t, Terminal) for v3 in self.sequence)... |
Imports:
```python
import numpy as np
import shapely.geometry as geom
from shapely.ops import nearest_points, unary_union, clip_by_rect
from skimage import draw, filters
from skimage.graph import MCP_Connect
from skimage.filters import apply_hysteresis_threshold, sobel
from skimage.measure import approximate_polygon, s... |
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 self._logger is not None:
self._logger.debug(f'Loading neighbors of {v1}')
``` |
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:
v2 = {'.csv': 'text/plain', '.gif': 'image/gif', '.jpeg': 'image/jpeg', '.jpg': 'image/jpeg', '.json': 'application/json', '.log': 'text/pl... |
Imports:
```python
from scipy.ndimage import label, measurements
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray):
(v1, v2) = label(v1)
if len(self.imageObjects) == 0:
for v3 in range(v2):
... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = FrozenSet[Tuple[str, Tuple[int, int]]]
```
Input Types: str
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: str) -> v0:
v3 = []
with open(v2) as v4:
v5 = v4.readlines()
for v6 in v5:
... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = typing.Union[_R, typing.Awaitable[_R]]
```
Input Types: Any, Any, Any, typing.List[dict]
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2, v3, v4, v5: typing.List[dict]) -> v0:
v6 = {'permissions': v5}
retu... |
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=False):
v3 = self.coco.getCatIds(catNms=v1)
v4 = self.coco.getImgIds(catIds=v3)
if not v2:
print(len(v4), 'Pictures with c... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: pd.Series
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.Series) -> str:
if isinstance(v1.dtype, pd.DatetimeTZDtype):
return 'datetime'
elif isinstance(v1.dtype, pd.StringDtype) ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[Tuple[str]]]
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[List[Tuple[str]]]) -> dict:
v2 = []
for v3 in v1:
v4 = dict(v3)
v2.append({'form': list(v4.keys()), 'upos': list(v4.v... |
Imports:
```python
import pandas as pd
from torch import long, tensor
from torch.utils.data.dataset import Dataset
import torch
import torch.nn.init as init
from sklearn.metrics import accuracy_score, f1_score, roc_auc_score
from sklearn.model_selection import train_test_split
from torch import Tensor
from torch.nn imp... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Set[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True) -> Set[str]:
v2 = self.client.pin.ls(type='recursive' if v1 else 'all')
return set(v2['Keys'])
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(int):
@staticmethod
def v1(v2: str) -> v0:
return v0('ABCD'.find(v2))
def v3(self) -> str:
return 'ABCD'[self]
@property
def v4(self) -> int:
return 10 ** self
@staticmethod
def v5() -> Iter... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Tuple[int, int, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Tuple[int, int, int]:
if self._column_left:
v1: int = self.place - self.start[1]
else:
v1 = self.place - self.start[2]
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
v2 = super().ask_raw(v1)
if v2 == v1:
v2 = self.visa_handle.read()
if v2.startswith('OK'):
return
if v2.startswit... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str):
v3: list = [str('zone "' + v2 + '.in-addr.arpa" IN {'), ' type master;', str(' file "/var/named/reverse.' + v1 + '.hosts";'), '}... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
v1 = {self.args[i].replace('-', ''): self.args[i + 1] for v2 in range(0, len(self.args) - 1, 2)}
v1 = self.validate_args(v1)
v1['cmd'] = self.cmd... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list) -> str:
v2 = ''
for v3 in v1:
v2 += f'{v3} '
return v2[:-1]
``` |
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