text stringlengths 190 325k |
|---|
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = ['src/pyslang.py', 'run', f'tests/{v1}.slang']
v3 = subprocess.Popen(v2, stdout=subprocess.PIPE)
(v4, v5) = (v3.stdout.read()... |
Imports:
```python
import re
import datetime
import typing
```
Type definitions:
Input Types: Any
Output Type: datetime.datetime
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> datetime.datetime:
v2 = re.search('(\\d+-\\d+-\\d+ \\d+:\\d+:\\d+)', v1)
if v2.endpos >= 1:
try:
... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> bool:
if self.plugin_data != {}:
return await self.__save_data_to_json_file(self.plugin_data, f"{self.plugin_dataj_filename}.bak.... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, float
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: float=0.5) -> List[int]:
v3 = v1[:, 0]
v4 = v1[:, 1]
v5 = v1[:, 2]
v6 = v1[:, 3]
v7 = v1[:,... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(object):
v1 = 'http://dart.fss.or.kr/api/'
def __init__(self, v2: str, v3: bool=True, **v4):
""" ์ข
๋ชฉ ์ ๋ณด ์ด๊ธฐํ
Parameters
----------
crp_cd: str
์ข
๋ชฉ ์ฝ๋
lazy_loading: bool
True ์ผ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
self.gui.set_region(v1)
self.region_menu.setTitle(v1)
``` |
Imports:
```python
import torch
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
v2 = dict()
v2['loss_history'] = self.loss_history
v2['loss_iter'] = self.loss_iter
... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass
class v0:
v1: 'accera.Plan'
v2: Union[Array, Any]
v3: LoopIndex = None
v4: LoopIndex = None
v5: int = None
v6: int = None
v7: Union[Array.Layout, Tuple[int]] = None
v8: int = None
v9: bool = False
v10: bo... |
Imports:
```python
import torch.nn as nn
import torch
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:
v2 = torch.tensor(v1.astype('float32'))
return ((self.pgan_model.test(v2).cl... |
Imports:
```python
import typing
```
Type definitions:
Input Types: th.Tensor
Output Type: th.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: th.Tensor) -> th.Tensor:
self.check_args(v1)
v2 = self.conv(v1[:, None] if v1.dim() == 3 else v1)
v2 = v2.transpose(1, 2)
(v3, v4, v... |
Imports:
```python
import torch
from torch import Tensor
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, Optional[torch.Tensor]
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: torch.Tensor, *, v3: Optional[torch.Tensor]=None) -> t... |
Imports:
```python
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 = f'{v1}/scanset-{v2}'
self.create_directory(v3)
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes, v2):
v1 = v1.decode('utf-8')
if 'ready' in v1:
try:
v3 = v1.split('&')
v4 = v3[1]
v5 = v3[2]
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.FloatTensor, torch.FloatTensor, Any, Any
Output Type: torch.FloatTensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.FloatTensor, v2: torch.FloatTensor, v3=None, v4=None) -> torch.FloatTensor:
if self.negative_... |
Imports:
```python
from urllib.parse import urlparse, urlunparse
import typing
```
Type definitions:
Input Types: str, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str) -> str:
(v3, v4) = (urlparse(v1), urlparse(v2))
v5 = {**v4._asdict(), 'path': v3.path}
v6... |
Imports:
```python
import random
from functools import partial
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
random.seed(v1)
v2 = partial(random.randint, 180, 255)
return '#{:0>6X}'.format(v2() * v2() * v2(... |
Imports:
```python
import math
import typing
```
Type definitions:
Input Types: int, float
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: float) -> float:
v3 = -self.value / self.visits if self.visits else 0
v4 = self.policy_prior * math.sqrt(v1) / (1 + self.v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int], List[int]
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int], v2: List[int]) -> List[int]:
if not v1 or not v2:
return []
v3 = {}
v4 = []
v5 = []
for v6 in rang... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: float, int
Output Type: np.array
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float=0.0, v2: int=0) -> np.array:
if v2 < 0 or v2 >= self.number_of_frames:
return np.zeros(3)
if v1 < 0:
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray):
v1 = np.atleast_2d(v1)
v2 = np.roll(v1, 1, axis=1)
return np.sum(-10 * np.exp(-0.2 * np.sqrt(v1[:, :-1] ** 2 + v2[:... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(IsmnComponent):
def __init__(self, v1, v2=None):
"""
Initialise Network object.
Parameters
----------
name : str
Network name.
stations : list[Station], optional (default: None)
... |
Imports:
```python
import warnings
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(**v1) -> None:
v2 = list(v1.keys())
v3 = list(v1.values())
if any(v3):
v4 = ', '.join(v2)
warnings.warn(f'Specifying any of: {v4... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float, v2: str):
v2 = v2.upper()
v3 = ['NS', 'US', 'MS', 'S']
if v2 in v3:
self.instr.write('TRIG_DELAY %.1f%s' % (v1, v2))
else:... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, dict, bool
Output Type: Any
Dependencies:
```python
def v0(v1: list, v2: dict, v3: str, v4: str, v5: bool):
for v6 in v2:
AddSignature(v1, v6, v3, v4, v5)
```
```python
def v7(v8, v9, v10: str, v11: str, v12: bool):
v13 = core_fu... |
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=None):
v3 = self.moodle.post('mod_data_get_entry', entryid=v1, returncontents=v2 or '')
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: Dict[v0, int], v0
Output Type: None
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: Dict[v0, int], v3: v0) -> None:
v4 = v2.get(v3)
if v4 is None:
v2[v3] = 1
else:
v2[v3] = v4 ... |
Imports:
```python
import json
import requests
from requests import Response
import typing
```
Type definitions:
Input Types: str, Any, Any, Optional[Dict[str, str]]
Output Type: Optional[Response]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Any=None, v3: Any=None, v4: Optional[Dict[... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
```python
class v0(NamedTuple):
v1: List[float]
v2: int
v3: int
```
Input Types: Sequence[v0], Sequence[str], Dict[str, float]
Output Type: float
Dependencies:
```python
def v4(v5: np.ndarray, v6: np.ndarray, v7: Sequence[float]) -> D... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list=None):
v2 = {'tw_bias': self.tw_bias}
v2.update(self.opt_args)
if self.target_tw:
v2['target_tw'] = self.target_tw
v3 = self.optim... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=-1) -> bytes:
if self._nbr == self._size:
return b''
v2 = self._size - self._nbr
if v1 > -1:
v1 = min(v2, v1)
else:
... |
Imports:
```python
from urllib.parse import quote_plus
import typing
```
Type definitions:
Input Types: str, Any, str, str
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Any, v3: str=None, v4: str=None) -> dict:
v5 = self._endpoint + '/' + quote_plus(v1) + '/conten... |
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):
if self.bmap_steamid is None and self.bmap_map is None:
return
if self.bmap_map == v1:
return
self.bmap_steamid ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = v1.find('่็ดๅท') + len('่็ดๅท')
v3 = v1[v2:v2 + 100]
v4 = v3.find('["')
v5 = v3.find('"]')
v6 = v3[v4 + 2:v5]
v1 = v1[v1.find('ๅ็งฐ') + l... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Any]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[Any]) -> None:
super().training_epoch_end(v1)
self.log('train_metrics', self.train_metrics.compute())
self.train_metrics.reset()
``` |
Imports:
```python
from copy import copy
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.query = copy(self.model._meta.basequery)
for (v1, v2) in self.fields_for_select.items():
self.add_field_to_select_... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: str, v3: str=None):
(v4, v5) = self.consul.catalog.service(v2, tag=v3)
v6 = []
for v7 in v5:
v8 = self.ctx.socket(v1)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Path
Output Type: None
Dependencies:
```python
def v0(*, v1: dict[str, str] | None=None, v2: str | None='grpc://fake.url:10', v3: str | None=None, v4: str | None=None) -> DynamicRemoteOptions:
if v1 is None:
v1 = {}
v5 = ['--remote-cac... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(PageVisitor, NodeVisitor, TimeoutBehaviour):
v1: str
v2: UserConfiguration
def __init__(self, v3: str, v4: EdgeNode, v5: UserConfiguration):
self.current_timeout = 0
self.current_node = v4
self.current_page = ... |
Imports:
```python
import numpy as np
import pandas as pd
import plotly.graph_objects as go
import plotly.express as px
import plotly.io as pio
import typing
```
Type definitions:
Input Types: pd.DataFrame, pd.Series, str
Output Type: NoReturn
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFram... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: requests.exceptions.HTTPError
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: requests.exceptions.HTTPError) -> bool:
v2 = json.loads(v1.response.text)
if v2.get('error').get('details') and v2['err... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: torch.Tensor) -> torch.Tensor:
assert len(v2.shape) == 2
v3 = torch.isfinite(v2).all(-1) * (v2[... |
Imports:
```python
import os
import cv2
import typing
```
Type definitions:
Input Types: str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2):
v3 = os.path.join(v1, 'Images')
v4 = os.path.join(v3, '%s.png' % v2)
return cv2.imread(v4, cv2.IMREAD_COLOR)
``` |
Imports:
```python
import tensorflow as tf
from tensorflow.python.ops import numpy_ops as np
import typing
```
Type definitions:
Input Types: Tuple[int, ...]
Output Type: 'Kernel'
Dependencies:
```python
def v0(v1: Optional[np.ndarray], v2: int) -> Optional[np.ndarray]:
if v1 is not None:
v3 = tuple((v2 + ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
```python
def v0(v1, v2, v3):
if not v3:
return True
(v4, board[v1][v2]) = (board[v1][v2], None)
for (v5, v6) in yield_valid_directions(v1, v2, v3[0]):
if v0(v5, v6, v3[1:]):
b... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str='authentication required') -> None:
dict.clear(self)
dict.update(self, {'__auth_type__': 'basic', 'realm': v1})
if self.on_update:
self... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list):
v2 = len(v1)
v3 = 0
v4 = 0
for v5 in range(v2 - 1):
v6 = v5
v7 = v1[v5]
for v8 in range(v5 + 1, v2):
if v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, str
Output Type: Tuple[str, str]
Dependencies:
```python
def v0(v1: str, v2: int=-1) -> str:
if v2 == -1:
return v1
return f'{v1}#{v2}'
```
```python
def v3(v4: str, v5: str='') -> Dict[str, str]:
v6 = {MLFLOW_RUN_NAME: v... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: [()]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> [()]:
v1 = [('HKLM\\SAM', 'HKEY_LOCAL_MACHINE\\SAM'), ('HKLM\\SECURITY', 'HKEY_LOCAL_MACHINE\\SECURITY'), ('HKLM\\SOFTWARE', 'HKEY_LOCAL_MACHINE\\SOFTWARE'), (... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(NamedTuple):
v1: Path
v2: Path
v3: bool
v4: Optional[bool] = False
def v5(self):
v6 = f'\n{str(self.input.absolute())}\n{str(self.output.absolute())}\n{str(self.create_dimer)}\n{str(self.retain_water)}'
return... |
Imports:
```python
import webbrowser
import random
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1: str) -> str:
if any((x in v1 for v2 in ['google', 'bing', 'aol'])):
return 'search?q='
elif 'duckduckgo' in v1:
return '?q='
elif 'yaho... |
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
for v3 in v1.rstrip().splitlines():
v4 = self.level_cb(v3)
v5 = v3.strip()
self.logger.log(v4, v5)
v... |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types: bytes
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes) -> None:
logging.debug(f'sending command: {v1!r}')
self.serial_.write(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
```python
def v0(v1: Callable):
@functools.wraps(v1)
def v2(*v3: tuple or Any):
v4 = v3[0]
for v5 in cases:
v6 = v3 + (v5 if isinstance(v5, tuple) else (v5,))
with v4... |
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 == 'spherical':
return f'REGular xpinp={self.grid.min_x} ypinp={self.grid.min_y} & \n alpinp=0. mxinp={self.grid.x_cells... |
Imports:
```python
import copy
import torch
from torch import optim as optim
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, float
Output Type: Optional[Dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: torch.Tensor, v3: float=0.01) -> Optional[D... |
Imports:
```python
import torch
import torch.utils.data
import typing
```
Type definitions:
Input Types: str, List[torch.FloatTensor]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: List[torch.FloatTensor]):
assert self.n_bins is not None, 'Set n_bins manually'
v... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
```python
v0 = NamedTuple('Limitation', [('primitive_name', str), ('error_type', str), ('error_string', str), ('devices', Tuple[str, ...])])
```
```python
v1 = Any
```
Input Types: core.Primitive, Callable
Output Type: Callable
Dependencies:
```p... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, List[int]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: List[int]) -> int:
v3 = [1] * v1
for (v4, (v5, v6)) in enumerate(zip(v2, v2[1:])):
if v6 > v5:
v3[v4 + 1] = v3[v4] + 1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[str, int]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[str, int]) -> None:
if not self._at == None:
raise ValueError(f'Node already has an @ {self._at} !')
else:
self._at =... |
Imports:
```python
import math
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: np.ndarray
Dependencies:
```python
def v0(v1: np.ndarray) -> None:
if v1.shape != (3, 3):
raise ValueError(f'Matrix must have shape (3, 3) but has {v1.shape}.')
if abs(np.linalg.de... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool, int, int, bool, bool, str, str, str
Output Type: Response
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=None, v2: int=None, v3: int=None, v4: bool=None, v5: bool=None, v6: str=None, v7: str=None, v8: str=None) -> Res... |
Imports:
```python
import typing
```
Type definitions:
Input Types: adsk.core.Command, adsk.core.CommandInputs
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: adsk.core.Command, v2: adsk.core.CommandInputs):
v3 = v2.addSelectionInput('selection_input_id', 'Component', 'Select... |
Imports:
```python
import os
import platform
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0() -> str:
v1 = {'Windows': 'notepad'}
v2 = platform.system()
v3 = v1.get(v2, 'nvim')
return os.environ.get('EDITOR', v3)
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('DictUpperBound', bound='dict')
```
Input Types: v0, v0, bool
Output Type: Dict
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: v0, v3: v0, v4: bool=True) -> Dict:
v5 = dict()
for v6 in v2:
if v6 in v3:
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: float, float, int, int
Output Type: Tuple[List, List]
Dependencies:
```python
def v0(v1):
return self.mass_to_light_ratio * self.intensity * np.exp(-self.sersic_constant * ((v1 / scaled_effective_radius) ** (1.0 / self.sersic_in... |
Imports:
```python
import datetime
import pandas as pd
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: tuple
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame) -> tuple:
v2 = v1.columns.get_level_values('gvkey').drop_duplicates().to_list()
v3 = v1.index.sor... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Optional[Callable]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: Optional[Callable]=None) -> str:
v2 = v2 or open
with v2(v1, mode='r', encoding='utf-8') as v3:
v4 = v3.read()
return... |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
from torch.nn import Mish
import typing
```
Type definitions:
Input Types: Tensor, int
Output Type: Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tensor, v2: int=1) -> Tensor:
v3 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[str]:
v1 = ''
if len(self.bounds) > 0:
if len(self.bounds) == 1:
v1 = f', bound={self.bounds[0]}'
else:
v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, str
Output Type: list
Dependencies:
```python
def v0(v1: str, v2: str=None) -> str:
v3 = textblob.translate.Translator()
if v2:
return v3.translate(v1, from_lang=v2, to_lang='en')
return v3.translate(v1, to_lang='en')
```
Fun... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes):
self._signature = self._cose_key.sign(v1)
return
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2=None):
for v3 in self.task_list:
v3.perform(v1, seed=v2)
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any, Union[int, Sequence[int]], bool
Output Type: Any
Dependencies:
```python
def v0(*v1):
v2 = all((isinstance(x, _NP_LIKES) or _is_poly_dim(x) for v3 in v1))
return np if v2 else jnp
```
```python
def v4(v5):
return ja... |
Imports:
```python
import itertools
import random
import matplotlib.pyplot as plt
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, Any, Any
Output Type: np.ndarray
Dependencies:
```python
def v0(v1: float, v2: float, v3: float) -> bool:
return random.random() < np.exp((v1 - v2) / v3)... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.app.add_url_rule('/delete', 'delete', self.example_route, methods=['DELETE'])
v1 = self._get_status_code_for_method('/delete', 'DELETE')
sel... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Set[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> Set[int]:
v2 = set()
v3 = 1
while v1:
if v1 & 1:
v2.add(v3)
v1 >>= 1
v3 += 1
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: int, v3=','):
v4 = []
v5 = v1.split(v3)
while len(v5) > 0:
v4 += [v3.join(v5[:v2])]
v5 = v5[v2:]
return (v3 + '<br>... |
Imports:
```python
from textwrap import dedent, indent
import typing
```
Type definitions:
Input Types: re.Match[str]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: re.Match[str]) -> str:
v2 = v1['type']
v3 = v1['body']
if v1['name']:
v4 = f"**{v1['name'].strip()}*... |
Imports:
```python
import logging
import os
from pathlib import Path
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: Path, Callable[[Path], bool]
Output Type: List[Path]
Dependencies:
```python
def v1(v2: Path) -> Iterator[Path]:
for (v3, v4, v5) in os.walk(v2):
for v6 in v5... |
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 = {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1000}
v3 = 0
for v4 in range(0, len(v1)):
v5 = v1[v4:v4 + 2]
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
if self.index == -1:
raise ValueError('No current match.')
return self.matches[self.index]
``` |
Imports:
```python
import sys
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1, v2, v3=sys.stdout):
if not v1:
return
if not v3.isatty():
v3.write(v1 + '\n')
else:
v3.write(termcolor.colored(v1, v2) + '\n')
v3.flush()
```
Fu... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, bool
Output Type: Any
Dependencies:
```python
def v0(v1: Tag) -> str:
v2 = VERBALIZERS[v1.kind]
v3 = [f(v1.data) for v4 in v2]
v3 = [x for v5 in v3 if v5]
if not v3:
return v1.text
else:
return v3[0]
```
```pyt... |
Imports:
```python
import requests
import typing
```
Type definitions:
Input Types: str, Dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Dict):
v2['StagerName'] = v1
v3 = requests.post(url=f'{self.host}:{self.port}/api/stagers', json=v2, verify=False, params... |
Imports:
```python
import typing
```
Type definitions:
Input Types: T.FloatingPoint
Output Type: bool
Dependencies:
```python
def v0(v1: T.TorchTensor) -> T.Tuple[int]:
return tuple(v1.size())
```
Function Name: v2
Function:
```python
def v2(v3: T.FloatingPoint) -> bool:
try:
v0(v3)
return True... |
Imports:
```python
import base64
import cv2
import typing
```
Type definitions:
Input Types: int
Output Type: Dict
Dependencies:
```python
def v0(v1: NDArray[(Any, Any, 3), int]) -> str:
(v2, v1) = cv2.imencode('.jpg', v1)
if not v2:
return None
v1 = v1.tostring()
v1 = base64.encodebytes(v1)
... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = List[Task]
```
Input Types: v0
Output Type: Any
Dependencies:
```python
def v1(v2: List[Task]):
v3: List[Task] = list()
while len(v2) != 0:
v4 = v2.pop(0)
v5 = set(v3)
if v4 in v5:
continue
if len(v... |
Imports:
```python
import os, sys
import traceback
from datetime import datetime
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
```python
def v0(v1, v2, v3, v4, v5=False):
v6 = '/%s/%s/%s' % (v2, v3.replace(os.path.sep, '/'), v4)
while '//' in v6:
v6 = v6.replace('... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: {object, None}
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, **v2: Dict[str, any]) -> {object, None}:
try:
v3 = v1.objects.get(**v2)
except v1.DoesNotExist:
v3 = None
return v3
``` |
Imports:
```python
import os
import re
import random
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.remote.webelement import WebElement
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
De... |
Imports:
```python
import base64
import typing
```
Type definitions:
Input Types: str, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str='') -> str:
v3 = 'smart/filters:no_upscale()%s/%s/source_type/local_file'
v4 = ''
if v2:
v3 = '/%s/%s' % (v2, v3)
... |
Imports:
```python
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 = []
for (v4, v5) in enumerate(reversed(v1)):
for (v6, v7) in enumerate(reversed(v2)):
v8 = (ord(v5) -... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pg.TextItem
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: pg.TextItem):
self._text_items.append(v1)
self.plot_item.addItem(v1)
``` |
Imports:
```python
from datetime import datetime, timedelta
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
if not self.loop or not self.loop_length:
return
with self.midiout:
for v2 in range(v1):
... |
Imports:
```python
import warnings
import torch
from torch.ao.quantization.quant_type import QuantType, quant_type_to_str
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: torch.Tensor) -> bool... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: bool
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=False) -> pd.DataFrame:
v2 = pd.DataFrame({'text': [sample.text for v3 in self._dataset], 'label': [v3.label for v3 in se... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray):
v2 = len(v1)
v3 = np.zeros((v2, v2))
v4 = np.linalg.norm(v1)
for v5 in range(v2):
v3[v5] = -v1[v5] * v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Mapping[str, str], Mapping[str, Any]
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Mapping[str, str], v2: Mapping[str, Any]) -> Dict[str, Any]:
v3 = {}
for v4 in v2:
v5 = self._lookup... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Image
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Image):
v2 = self.__preprocess_img(v1)
v3 = self.__clusterize(v2)
v4 = self.__group_clusters(v3)
v5 = self.__estimate_centroids(v4)
v6 = s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> bytes:
assert isinstance(v1, str), str(type(v1))
return v1.encode()
``` |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.