text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> None:
while True:
v1 = await self._receive()
assert self._in_queue is not None, 'Input queue not initialized.'
self._in_queue.put... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: Any
Output Type: Optional[Dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> Optional[Dict]:
v2 = re.match('^https://github.com/([^/]+)/([^/]+)/commit/([0-9a-f]+)$', v1)
if v2 is None:
return None
el... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Optional[dict]
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: int) -> Optional[dict]:
v2 = 'SELECT * FROM `dailies` WHERE userid = %(u)s;'
async with self.bot.db_query(v2, {'u': v1}) as v3:
... |
Imports:
```python
import torch
from torch import nn
from torch.nn.modules.loss import MSELoss, CrossEntropyLoss
import typing
```
Type definitions:
Input Types: torch.Tensor, List[str], torch.Tensor, bool
Output Type: Tuple[torch.Tensor, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: tor... |
Imports:
```python
from math import asin, sqrt, sin, cos, atan2
import numpy as np
from numpy import deg2rad, float64, savetxt
import math
import typing
```
Type definitions:
Input Types: Any, Any, Any, Any
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3, v4) -> float:
v5 ... |
Imports:
```python
import numpy as np
import torch
import typing
```
Type definitions:
Input Types: str, Union[torch.Tensor, np.ndarray]
Output Type: None
Dependencies:
```python
def v0(v1: Union[torch.Tensor, np.ndarray]) -> np.ndarray:
if isinstance(v1, torch.Tensor):
assert v1.dim() == 2, 'Input tensor ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
for v2 in self.players:
if v2['player'] == v1:
return v2['rank']
``` |
Imports:
```python
from pathlib import Path
import typing
```
Type definitions:
Input Types: Any, 'str', int, Any
Output Type: list
Dependencies:
```python
def v0(v1: 'Figure', v2: str) -> str:
v3 = Path(_temp_dir_path)
v4 = str(v3 / f'{v2}.png')
v3.mkdir(exist_ok=True)
v1.write_image(v4)
return v4... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
with self.mock_config_info({'api_key': 'TEST'}):
self.verify_reply('help', '`archive` Archive a conversation.\n`delete` Delete a conversation.\n`... |
Imports:
```python
import os
from os import sys
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> str:
v1 = os.environ.get('SCRYPTED_FFMPEG_PATH_ENV_VARIABLE', None)
if v1:
v2 = os.environ.get(v1, None)
... |
Imports:
```python
from datetime import datetime
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
```python
def v0() -> dict:
return {'created': f'{get_current_iso_timestamp()}', 'updated': f'{get_current_iso_timestamp()}', 'description': 'Asset description', 'copyrightHolder': 'As... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.item = self.next_item
self.next_item = next(self._it, self._default_item)
``` |
Imports:
```python
import re
from typing import Any, Awaitable, Callable, Dict, Iterable, List, Literal, Optional, Pattern, Set, Tuple, Type, Union
import typing
```
Type definitions:
Input Types: Optional[List[str]]
Output Type: Union[None, List[str], Pattern[str]]
Dependencies:
```python
def v0(v1: Optional[List[str... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
for v1 in range(self.first_leaf - 1, -1, -1):
self.fix_node(v1)
``` |
Imports:
```python
import math
import warnings
import torch
from torch import Tensor
import typing
```
Type definitions:
Input Types: float, float, int, int, float, str, Optional[float], torch.device, Optional[torch.dtype]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float, v2: floa... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: int or None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> int or None:
if v1 not in self.cache:
return None
v2 = self.cache[v1]
self._move_to_tail(v2)
return v2.val
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('A')
```
Input Types: Callable[[v0, v0], bool], Optional[v0], Optional[v0]
Output Type: bool
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: Callable[[v0, v0], bool], v3: Optional[v0], v4: Optional[v0]) -> bool:
if v3 and ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict):
v2 = self.trainer.cfg.test_data.data.type
if v2 in self.mulit_metircs_dataset_type:
v3 = [k for v4 in list(v1.keys()) if v4.find('metric... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tuple[int, int], Tuple[int, int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tuple[int, int], v2: Tuple[int, int]):
(v3, v4) = v1
(v5, v6) = v2
if v3 == v5:
self._add_vertical_line(v3, v4,... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> int:
if v1 == 1:
return False
elif v1 % 2 == 0 and v1 > 2:
return False
else:
for v2 in range(3, int(v1 ** (1 / 2)) + 1, 2... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[int]:
v1 = []
for v2 in self._score_grouped_embedding_configs_per_rank:
v3 = 0
for v4 in v2:
v3 += v4.num_features()
... |
Imports:
```python
import threading
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
super().enable()
threading.Thread(target=self.remove_expired_tpas_thread).start()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool):
if v1:
self.switchFromLoginUI(True)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
v1 = self.request.path.split(b'/')
v2 = self.sAPI.test_for_namespace(v1)
if len(v2) > 0:
v3 = self.sAPI.get_microblog(v2)
v4 = 'pro... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.LongTensor, torch.LongTensor, torch.LongTensor, Optional[torch.LongTensor], Optional[torch.LongTensor], Any, Any
Output Type: Any
Dependencies:
```python
def v0(v1: torch.LongTensor, v2: torch.LongTensor):
v3 = v1.unsqueeze(-1) ... |
Imports:
```python
import base64
import hashlib
import os
import re
import typing
```
Type definitions:
Input Types: str, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str='S256', v2: int=64):
v3 = {'S256': hashlib.sha256}
v4 = base64.urlsafe_b64encode(os.urandom(40)).dec... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Any]
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Any]) -> Dict[str, Any]:
v1['remote_host'] = v1['remote_system_name']
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: bool):
v1 = max(v1, 0)
super().enablePWMOutput(v1, v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
if self.stream_name != '':
return True
if self.connection_type is not None:
return True
if self.premises is not None:
ret... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Sequence[dict], int
Output Type: Sequence[dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Sequence[dict], v2: int) -> Sequence[dict]:
v3 = []
for v4 in v1:
v4 = v4.copy()
v5 = v4.pop('stages', None)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, bool
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: bool=True) -> list:
if not isinstance(v1, list):
raise TypeError('array parameter should be a list')
if not isinstance(v2, bool):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, Optional[int]
Output Type: List[dict]
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: str, v2: int, v3: Optional[int]=None) -> List[dict]:
if v3 is not None:
if not self._receipts_stream_cache.has_enti... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, int, int, int, int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int, v3: int, v4: int, v5: int, v6: int, v7: int):
for v8 in range(max(v2, -50), min(v3, 50) + 1):
for v9 in ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Iterator['Entity']
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Iterator['Entity']:
for v1 in self.vmf.entities:
if self.id in v1.visgroup_ids:
yield v1
``` |
Imports:
```python
from pymatgen.core import Structure, Element, Species, Lattice
from pymatgen.core.operations import SymmOp
import typing
```
Type definitions:
Input Types: Union[str, Element, Species]
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[str, Element, Species]) ->... |
Imports:
```python
import random
import re
import typing
```
Type definitions:
```python
class v0(NamedTuple):
v1: str
v2: int
v3: int
```
Input Types: List[v0]
Output Type: str
Dependencies:
```python
def v4(v5: float) -> str:
return re.sub('\\.?0*$', '', '{:.3f}'.format(v5))
```
Function Name: v6
Func... |
Imports:
```python
import torch
from torch.autograd import Variable as V
from torch.nn import functional as F
import re
import numpy as np
import typing
```
Type definitions:
Input Types: Image
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Image) -> List[str]:
v2 = ['... |
Imports:
```python
import datetime as dt
import typing
```
Type definitions:
Input Types: Optional[dt.datetime], Any
Output Type: Optional[dt.datetime]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[dt.datetime], v2) -> Optional[dt.datetime]:
if self.auto_now:
v1 = dt.dateti... |
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 not in (v2 := self._cfg_types()):
raise ValueError("Unknown config type '{c}'. Known types: {k}".format(c=v1, k=', '.join(v2.keys())))
`... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Union[float, int]], List[str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(*, v1: List[Union[float, int]], v2: List[str]) -> None:
for v3 in range(len(v1) - 1):
if v1[v3] > v1[v3 + 1]:
rais... |
Imports:
```python
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 = v1[:, 0]
return self.lr_.predict(self.__transform(v2))
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
for v1 in self.stamina['priority']:
(v2, v3) = (v1.split(':') + ['1'])[:2]
if self.objects[f'stamina_{v2}'].found(False) and int(v3) > 0:... |
Imports:
```python
from copy import deepcopy
import typing
```
Type definitions:
Input Types: int, Any
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2=None) -> Dict:
if v2 is None:
v3 = self.ase_db.get(v1)
else:
v3 = self.ase_db.get(v1, default=v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: ast.AST
Output Type: ast.AST
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: ast.AST) -> ast.AST:
v1 = self._handle_assignments(v1)
v1 = self._handle_expressions(v1)
return self.generic_visit(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, pd.DataFrame, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: pd.DataFrame, v3: str=None):
v3 = v3 or self.schema_name
self.schema[v3].experiments[v1.lower()] = v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Optional[str]:
try:
v2 = v1[2:].replace('-', '_')
return self.args[v2]
except KeyError:
return self.args[v1]
`... |
Imports:
```python
from numpy import abs, linalg, log2, ndarray, sqrt, pi, exp, asarray, tile, power, diag, dot
from numpy.random import randn
import typing
```
Type definitions:
Input Types: int
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> List[int]:
v2 = []
w... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1):
return (analyze_function(v1), [])
```
```python
def v2(v3: List[object], v4: List[int]) -> List[object]:
...
```
Function Name: v5
Function:
```python
def v5(self) -> None:
def v6(v7:... |
Imports:
```python
import typing
```
Type definitions:
```python
@attr.s(slots=True, eq=False, order=False, repr=False)
class v0:
v1: str = attr.ib()
v2: 'Type' = attr.ib()
v3: 'Type' = attr.ib()
v4: str = attr.ib(default=None)
v5: 'Type' = attr.ib(default=None)
v6: bool = attr.ib(default=None)
... |
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):
if self.DEBUG:
print('TX %d=%d' % (v1, v2))
self.i2c.send(self.addr, [v1, v2])
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[str]], str
Output Type: List[Iterator[str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[List[str]], v2: str) -> List[Iterator[str]]:
v3 = [iter(house) for v4 in v1]
for v5 in range(int(v2)):
for (v6, ... |
Imports:
```python
import sys
import requests
import typing
```
Type definitions:
Input Types: list[str]
Output Type: None
Dependencies:
```python
def v0(v1: str) -> None:
print(f'Downloading binary content: {v1}')
v2 = fetch(v1)
v3 = lib.make_filename(v1, '.pdf', ADD_DATETIME_DEFAULT)
v4 = PNG_DIR / v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> bool:
v2 = (1 + (24 * v1 + 1) ** 0.5) / 6
return v2 == int(v2)
``` |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import typing
```
Type definitions:
Input Types: List[torch.Tensor], int
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[torch.Tensor], v2: int)... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: axes.Axes, Tuple[float, float], float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: axes.Axes=None, v2: Tuple[float, float]=(0, 0), v3: float=1.0, **v4):
v5 = np.linspace(0, 2 * np.pi, 15... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: pd.DataFrame) -> pd.DataFrame:
if self.columns is None:
self.columns = list(v1.columns)
raise NotImplementedError
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str):
self._source = v1
self._initial_state = []
self._state = []
self._pc = 0
self._hlt = True
self._wait = False
self._mode_pipeline = []
self._opcodes... |
Imports:
```python
import asyncio
from asyncio.streams import StreamReader, StreamReaderProtocol, StreamWriter
from asyncio import events
import typing
```
Type definitions:
Input Types: asyncio.transports.BaseTransport
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: asyncio.tra... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
self.UpdateButtons()
return self.OnButtonIsPress()
``` |
Imports:
```python
import importlib
from importlib import import_module
import typing
```
Type definitions:
Input Types: Optional[str]
Output Type: Optional[Callable]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Optional[str]) -> Optional[Callable]:
if v1 is None:
return None
(v2, v3... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
```python
def v0(v1: list, v2: int, v3: int):
if v2 >= v3:
return
v4 = v1[v2]
v5 = v2 + 1
for (v6, v7) in enumerate(v1[v2 + 1:v3], v2 + 1):
if v7 > v4:
v5 = v6
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'User'
Output Type: t.List[t.Optional[str]]
Dependencies:
```python
def v0(v1):
return v1.tf_totp_secret and v1.tf_primary_method
```
Function Name: v2
Function:
```python
def v2(self, v3: 'User') -> t.List[t.Optional[str]]:
if v0(v3):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame):
for v2 in ['left', 'right']:
v1[v2 + '_strip_tokenized_len'] = v1[v2 + '_strip_tokenized'].apply(len)
``` |
Imports:
```python
import asyncio
import random
import typing
```
Type definitions:
Input Types: float, float
Output Type: Any
Dependencies:
```python
async def v0(v1):
nonlocal disconnect_called_num
v2 += 1
```
Function Name: v3
Function:
```python
def v3(self, v4: float=0.01, v5: float=0.005):
async def... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: chr, v2: chr) -> bool:
return v1 != v2 and (v1 == v2.lower() or v1 == v2.upper())
```
```python
def v3(v4: str) -> str:
v5 = ''
for v6 in range(0, len(v4)):
if v6 == len(v4) - 1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool):
self.__filter_sync_err = v1
self.__filter_sync_event.set()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, str
Output Type: Any
Dependencies:
```python
def v0(v1: Any) -> str:
v2 = str(type(v1))
if isinstance(v1, Circuit):
return 'quantumflow'
if 'cirq' in v2 and 'Circuit' in v2:
return 'cirq'
if 'braket' in v2 and 'Cir... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = 0
v3 = []
while v2 < len(v1):
v4 = v1.find(' ', v2)
if v4 == -1:
v3.append(v1[v2:])
break
v3.ap... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> int:
v1 = v1 - (v1 >> 1 & 1431655765)
v1 = (v1 & 858993459) + (v1 >> 2 & 858993459)
v1 = v1 + (v1 >> 4) & 252645135
v1 = v1 + (v1 >> 8)
... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = tp.TypeVar('EnumTy', bound=Enum)
```
Input Types: tp.Union[str, v0], tp.Optional[click.Parameter], tp.Optional[click.Context]
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: tp.Union[str, v0], v3: tp.Optional[cli... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Tuple[int, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Tuple[int, str]:
v1 = self.option_name
if v1 == '--help':
return (2, '--help')
elif v1 == '--version':
return (1, '--version... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = os.path.join(self._tmpdir, 'async.txt')
v2 = 'Async Text'
try:
for v3 in range(1):
with self._pathmgr.opena(v1... |
Imports:
```python
import sqlite3
import typing
```
Type definitions:
Input Types: Any, tuple, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: tuple, v3, v4):
(v5, v6) = self._make_args_and_hash(v2, v3)
v7 = [(v1, v6, v5, v4)]
try:
self.connection... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, bool
Output Type: Tuple
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: bool=False) -> Tuple:
v3 = np.diff(v1, axis=0)
v4 = np.diff(v1, axis=1)
if v2:
v3 = np.pad... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str, v2, v3, v4=50, v5=False):
self._server = v1[:-1] if v1.endswith('/') else v1
self._proxies = v2
self._auth_headers = {'Content-Type': 'application/json'}
self._use_ssl = not v5
... |
Imports:
```python
from numpy import isscalar
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> bool:
if isscalar(v1):
return self.lower <= v1 <= self.upper
return self.lower <= v1.lower and v1.upper <= self.u... |
Imports:
```python
from urllib.parse import urlparse
import typing
```
Type definitions:
Input Types: str
Output Type: Optional[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> Optional[int]:
try:
v2 = urlparse(v1).path
return int(v2.split('/')[-1].split('-')[0])
exc... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: dict or list
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=0) -> dict or list:
if v1 == 0:
return self.orderbook['obu']
return self.orderbook['obu'][v1]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Optional[str], Optional[str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Optional[str]=None, v3: Optional[str]=None):
self.workbook = self.auth.create(v1, folder=v2, template=v3)
self.sh... |
Imports:
```python
from typing import List, Type, ClassVar, cast
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self._get_init_task_runner()
v2 = self.get_test_assignment()
v3: List['Agent'] = [cast('Agent'... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=None, v2: str=None):
if v2:
v1 = self.performance_measure.index(v2)
if v1:
self.performance_data = self.performance_data_all[v1... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Dict[Gender, Counter]
```
```python
v1 = Dict[Gender, WordFrequency]
```
```python
v2 = Union[Counter, WordFrequency]
```
Input Types: str, str, str
Output Type: Dict[Union[str, int, float], v2]
Dependencies:
```python
def v3(v4: v0, v5: str, v6: str... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Dict[Node, Set[Node]]
```
```python
v1 = TypeVar('Node')
```
Input Types:
Output Type: None
Dependencies:
```python
def v2(v3: str, v4: Callable[[str], v1]) -> v0[v1]:
v5: v0[v1] = {}
for v6 in v3.splitlines():
(v7, *v8) = map(v4, v6... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray) -> bytes:
if v1.ndim == 2:
v1 = v1[..., None]
return tf.image.encode_png(v1).numpy()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> dict:
v2 = self.s.request('GET', url=f'{self.endpoint}/accounts/{v1}/transactions?bookingStatus=both&dateFrom=2000-01-01', data={})
return v2.j... |
Imports:
```python
import typing
```
Type definitions:
Input Types: decafAlejandroV2Parser.VardeclrContext
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: decafAlejandroV2Parser.VardeclrContext):
v2 = v1.var_type().getText()
if v1.field_var().var_id() is not None:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[bool]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[bool]=None) -> bool:
if v1 is None:
return self._get('fastreadout')
self._put('fastreadout', FastReadout=v1)
``` |
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 self.base_dir is not None:
v1 = os.path.join(self.base_dir, v1)
v2 = self.loader(v1)
if self.transform is not None:
... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('Symbol')
```
Input Types: Union[int, v0]
Output Type: Union[v0, int]
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: Union[int, v0]) -> Union[v0, int]:
if isinstance(v2, int):
return self._id2sym[v2]
els... |
Imports:
```python
import logging
import typing
```
Type definitions:
```python
class v0(NamedTuple):
v1: str
v2: int
```
Input Types: int
Output Type: None
Dependencies:
```python
def v3(v4: int) -> v0:
if v4 == 0:
return v0(LOG_FORMAT_DEFAULT, logging.WARNING)
elif v4 == 1:
return v0(L... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: np.ndarray) -> np.ndarray:
assert np.all(v2 > 0), f'Orders {v2} must be positive'
assert v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Tuple['_Substring', '_Substring', '_Substring']
Dependencies:
Function Name: v0
Function:
```python
def v0(self, *v1: Callable[[str], int]) -> Tuple['_Substring', '_Substring', '_Substring']:
(v2, v3, v4) = self._find(*v1)
retur... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: _typing.Dict[str, _typing.Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, *v2) -> _typing.Dict[str, _typing.Any]:
v3 = self._help_config.modes
if v1 not in v3:
self._log('Warning', self.... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: Any, str, Any
Output Type: Any
Dependencies:
```python
def v0(v1):
v2 = {}
for (v3, v4) in v1.items():
if 'num_batches_tracked' in v3:
continue
if v3.startswith('module.'):
if True:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> bool:
v2 = '.' not in v1
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Union[Sequence[Real], type(EMPTY_SET)]
```
Input Types: v0
Output Type: Real
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: v0) -> Real:
v2.sort()
v3 = v2[-1] - v2[0] if len(v2) > 0 else 0
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Path
Output Type: Iterator[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Path) -> Iterator[int]:
with v1.open('r') as v2:
for v3 in v2:
yield int(v3.strip())
``` |
Imports:
```python
import os
import typing
```
Type definitions:
```python
v0 = Union[BaseStore, MutableMapping, str, None]
```
Input Types: v0
Output Type: Any
Dependencies:
```python
def v1(v2):
return isinstance(v2, (str, os.PathLike))
```
```python
def v3(v4: v0, v5, **v6):
v7 = v1(v4)
v8: BaseStore = n... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list=[]):
v2 = {}
for v3 in v1:
if v3 in self.sensor_dict.keys():
v2[v3] = self.sensor_dict[v3]
return v2
``` |
Imports:
```python
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, **v3: bool) -> None:
if v1:
v4 = v1.rsplit('\n', 1)[-1]
if '\n' in v1:
self._current_line = v4
... |
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