text stringlengths 190 325k |
|---|
Imports:
```python
import numpy
import torch
from sklearn.neighbors import NearestNeighbors
import typing
```
Type definitions:
Input Types: torch.Tensor, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: bool):
v3 = v1.device
v4 = v1.shape[0]
v5 ... |
Imports:
```python
import numpy as np
from numpy.typing import ArrayLike
import typing
```
Type definitions:
Input Types: np.ndarray, str, str, Tuple[int, int]
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, *, v2: str='uint8', v3: str='minmax', v4: Tuple[int, int]=(... |
Imports:
```python
import torch
from torch import Tensor
import typing
```
Type definitions:
Input Types: Tensor
Output Type: Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tensor) -> Tensor:
assert len(v1.shape) == 3 and (v1.size(2) == 1 or v1.size(2) == 3), 'RGB image must have dimensiona... |
Imports:
```python
from cvxpy.atoms.affine.bmat import bmat
from cvxpy.atoms.affine.trace import trace
from cvxpy.constraints.constraint import Constraint
from cvxpy.expressions.variable import Variable
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: Tuple[float, List[Constraint]]
Dependencies:
... |
Imports:
```python
import numpy
import cv2
import typing
```
Type definitions:
Input Types: numpy.ndarray, List, List, float
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: numpy.ndarray, v2: List, v3: List, v4: float=2) -> None:
v5 = numpy.array(v2).astype(int)
cv2.rectangle(... |
Imports:
```python
import asyncio
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self._times_connected += 1
if self._times_connected > 1:
return
return asyncio.create_task(self._prepare_application_comma... |
Imports:
```python
import os
import pandas as pd
import shutil
import typing
```
Type definitions:
Input Types: str, str
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> dict:
self.logger.info(f'VPLoader - Start of viral proteome data processing.')
(v3, v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict) -> str:
v2 = ''
for (v3, v4) in v1.items():
v2 += f' -{v3}' if len(v3) == 1 else f' --{v3}'
if not isinstance(v4, bool):
v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, discord.Role
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1, v2: discord.Role):
await self.updateRoleList(v1)
v3 = await self.config.guild(v1.guild).roleList()
v3.remove(self.roledataItem(v... |
Imports:
```python
from math import pi
import typing
```
Type definitions:
Input Types: float, float, float, float, float, float, float
Output Type: Any
Dependencies:
```python
def v0(v1: float):
return cnst.k * v1
```
```python
def v2(v3, v4=cnst.c):
return v4 / v3
```
Function Name: v5
Function:
```python
de... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bool
Dependencies:
```python
async def v0(v1: int) -> Optional[models.Member]:
return await models.Member.get(v1)
```
Function Name: v2
Function:
```python
async def v2(v3: int) -> bool:
v4 = await v0(v3)
return v4.watched... |
Imports:
```python
import torch
from torch import nn
from torch.nn import functional as F
import typing
```
Type definitions:
Input Types: dict, dict, tuple, tuple, tuple, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict, v2: dict, v3: tuple, v4: tuple, v5: tuple, v6=False):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
self.ensure_current_steps()
for v2 in self.current_steps:
v2.add_event(v1)
``` |
Imports:
```python
import importlib
import typing
```
Type definitions:
Input Types: Union[Type[Any], str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[Type[Any], str]) -> Any:
if isinstance(v1, str):
v2 = v1.split('.')
v3 = '.'.join(v2[:-1])
v1 = v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: pd.DataFrame, v2: bool):
v3 = self._extractor(v1)
return v3.dot(self._components)
``` |
Imports:
```python
from urllib import parse
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
v1 = v2 = v3 = None
v4 = False
while True:
v5 = self.__network.Get()
for (v6, v7) in v5.items():
... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: int, bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: bool) -> None:
if not self._shutdown_signal or not self._terminate_signal:
return
if not v2:
os.system(f'shutd... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: str) -> bool:
v3 = "SELECT 1 FROM sqlite_master WHERE type='table' and name = ?"
return v1.execute(v3, (v2,)).fetchone() is not None
``` |
Imports:
```python
import os
import pathlib
import platform
import typing
```
Type definitions:
Input Types: str, bool
Output Type: str
Dependencies:
```python
def v0(v1: str, v2=False) -> str:
assert v1
v1 = os.path.abspath(os.path.expanduser(os.path.expandvars(v1)))
if v2:
os.makedirs(v1, exist_o... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[list, tuple], int
Output Type: list
Dependencies:
```python
def v0(v1: int, v2: int) -> (int, int):
v3 = v1 // v2
v4 = v1 - v2 * v3
return (v3, v4)
```
Function Name: v5
Function:
```python
def v5(v6: Union[list, tuple], v7: int) -> ... |
Imports:
```python
from pandas._config import get_option
from pandas._libs import algos as libalgos, lib, properties
from pandas._libs.lib import no_default
from pandas._typing import AggFuncType, AnyArrayLike, ArrayLike, Axes, Axis, ColspaceArgType, CompressionOptions, Dtype, FilePathOrBuffer, FloatFormatType, Formatt... |
Imports:
```python
from datetime import date, datetime, timedelta
from polars import internals as pli
from polars.datatypes import DataType, Date, Datetime, Float64, Object, UInt32, py_type_to_dtype
import typing
```
Type definitions:
```python
class v0:
def __init__(self) -> None:
self._pyexpr: PyExpr
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = {key: value for (v2, v3) in self.options.items() if v2 in self.cfg.settings and v3 is not None}
for (v2, v3) in v1.items():
self.cfg.set... |
Imports:
```python
import json
import subprocess
import typing
```
Type definitions:
```python
v0 = NewType('EnvVarName', str)
```
```python
v1 = NewType('FieldName', str)
```
```python
v2 = NewType('FieldValue', str)
```
```python
v3 = NewType('OpListItemsOutputOrderedByEnvVarName', List[OpListItemsEntry])
```
Input T... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
if 'lgpassword' not in self._uniquedescriptionstr():
super()._write_cache(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclasses.dataclass
class v0:
v1: Connection
v2: sqlalchemy.sql.Select
v3: Any
v4: Any
v5: bool = False
v6: Optional[_ResultProxyFake] = None
v7: Optional[Exception] = None
```
Input Types: greenlet.greenlet
Output Type: Dic... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: np.array
Dependencies:
```python
def v0(v1, v2):
if v1 >= v2:
return 1
return 0
```
Function Name: v3
Function:
```python
def v3(self, v4, v5) -> np.array:
v6 = v5[self._csp_enum.LOW]
d... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int | None
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int | None) -> int:
if v1 is None:
return 100000 // (len(self.cols) or 1) or 1
return int(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True) -> bool:
for v2 in range(0, self.n + 1):
for v3 in range(0, self.n + 1):
for v4 in range(0, self.n + 1):
if... |
Imports:
```python
import typing
```
Type definitions:
Input Types: tuple
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: tuple):
self.pos = v1
self.hitbox.topleft = (self.pos[0] + 10, self.pos[1] + 5)
``` |
Imports:
```python
from shapely.geometry import Polygon, LineString, LinearRing, Point
from shapely.geometry.base import BaseGeometry
from shapely.ops import nearest_points
import typing
```
Type definitions:
Input Types: BaseGeometry
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[str]) -> None:
if self.__endIndex > len(v1):
raise IndexError('CompoundOperation: cannot delete index range {}:{} (out of bounds)'.forma... |
Imports:
```python
import re
import typing
```
Type definitions:
```python
v0 = typing.Dict[str, typing.Any]
```
Input Types: v0, typing.Any
Output Type: bool
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: v0, v3: typing.Any) -> bool:
if 'syntax_names' in v2 and v3.disabled_syntaxes:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: couchbaseConstants.BATCH_MSG, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: couchbaseConstants.BATCH_MSG, v2: int):
self.msgs.append(v1)
self.bytes = self.bytes + v2
``` |
Imports:
```python
from itertools import product, count
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
```python
def v0(v1: List[List[str]]) -> List[List[str]]:
v2 = []
for (v3, v4) in enumerate(v1):
v5 = []
for (v6, v7) in enumerate(v4):
v8 = [v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, list, list, list, list
Output Type: Dict[str, dict]
Dependencies:
```python
def v0(v1: dict, v2: list) -> dict:
if not v1 or not v2:
return {}
v3 = {}
for v4 in v2:
if v4 in v1.keys():
v3[v4] = v1.get(v4)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Iterator[str], Any, Any, Any
Output Type: Iterator[Tuple[str, ...]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Iterator[str], v2=1, v3='#', v4='#') -> Iterator[Tuple[str, ...]]:
for v5 in v1:
v6 = []
v5 = f'{v3... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
v1 = False
if self.is_running:
self._process.terminate()
v1 = True
self._process = None
self._cmd = None
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Dict[str, str]
```
Input Types: v0
Output Type: str
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: v0) -> str:
v3 = ''
for (v4, v5) in v2.items():
v3 += f'{v4}() {{\n{v5}\n}}\n'
return v3
``` |
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.subcommands.pop(v1, None)
if v2 is None or v1 in v2.aliases:
return
for v3 in v2.aliases:
self.subcommands.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
if self.instance:
v2 = 'org/%s/project/%s' % (self.instance.id, v1)
v3 = self.client.get(v2)
v4 = v3.json()
v4['organi... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, dict
Output Type: tuple
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: dict) -> tuple:
if 'SAMPLE_BITS' in v2[v1]:
if v2[v1]['SAMPLE_BITS'] == 16:
v3 = 2
elif v2[v1]['SAMPLE_BITS'] == 8:
... |
Imports:
```python
import matplotlib
import matplotlib.pyplot as plt
import typing
```
Type definitions:
Input Types: list, list
Output Type: (tuple, tuple)
Dependencies:
```python
def v0(v1: str, v2: str):
plt.savefig('%s/%s.png' % (v2, v1))
```
Function Name: v3
Function:
```python
def v3(v4: list, v5: list) -> ... |
Imports:
```python
import pprint as pp
import typing
```
Type definitions:
Input Types: str, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> None:
pp.pprint('Attempting to make move %s' % v1)
if v1[0] in ['R', 'B', 'N', 'Q', 'K']:
self.make_n... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
if self._min is None:
return None
return round(self._min, 2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: 'typing.Tuple[str, str]'
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> 'typing.Tuple[str, str]':
if self.column is None:
return tuple(self._f_name.split('.'))[0:2]
return (self.foreign_column.table.... |
Imports:
```python
import random
import string
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0() -> str:
v1 = ''.join(random.choices(string.ascii_letters + string.digits, k=7))
return f'hyp3-testing-{v1}'
``` |
Imports:
```python
from pandas import DataFrame
from datetime import datetime
import typing
```
Type definitions:
Input Types: list, any, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: any, v3: str) -> None:
v4 = datetime.now().strftime('%H_%M_%S')
if v3 == 'csv... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: os.PathLike
Output Type: Union[str, bytes]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: os.PathLike) -> Union[str, bytes]:
(v2, v3) = os.path.split(v1)
(v4, v5) = os.path.splitext(v3)
v6 = v4 + '-dehinted' + v5... |
Imports:
```python
from qiskit import QuantumCircuit, Aer, execute, QuantumRegister
from qiskit.circuit import Qubit
from qiskit.transpiler import PassManager
from qiskit.transpiler.passes import Unroller
from qiskit import IBMQ
import typing
```
Type definitions:
Input Types: QuantumCircuit
Output Type: int
Dependenc... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: (pd.DataFrame, List)
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame) -> (pd.DataFrame, List):
v2 = ['tsne_x', 'tsne_y', 'lap_x', 'lap_y', 'umap_x', 'umap_y']
v3 = [x for v4 in v1.columns ... |
Imports:
```python
import torch
from torch import Tensor
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: Tuple[Tensor, Tensor, Tensor]
Dependencies:
```python
def v0(v1: Tuple, v2: torch.device) -> Tensor:
v3 = gumbel_map.get(v2)
if v3 is None:
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(AbstractArray, DataWithCoords, DataArrayArithmetic):
v1: dict[str, Any]
v2: dict[Any, Variable]
v3: Callable[[], None] | None
v4: dict[Hashable, Index] | None
v5: Hashable | None
v6: Variable
v7 = ('_cache', '_coords',... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Union[bool, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Union[bool, Any]:
(v2, v3) = self._get_endpoint(v1)
if v2:
(v4, v3) = self._deserialize_response(v2, self._response_classes... |
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:
v2 = 12
v3 = 24
v4 = 24
v5 = 1
v6 = 2
v7 = -0.3
v8 = np.array(((1, 0, 0)... |
Imports:
```python
import numpy as np
import h5py
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: str, v3: list):
v4 = h5py.File(v1, 'r')
v5 = v4['la_names'][:].astype(str)
v6 = np.isin(v5, v3)
v7 = v4['prediction'][:, :, :, v6]
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.tensor, int, float, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.tensor, v2: int, v3: float, v4: int) -> int:
self.base_classifier.eval()
v5 = self._sample_noise_predictions(v1, v2, v4)... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Union[int, str, None]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Union[int, str, None]:
v1 = self.amount_msat
if v1 in [None, '!']:
return v1
return int(v1 // 1000)
``` |
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: Dict[str, str] = {'layer1': 'res2', 'layer2': 'res3', 'layer3': 'res4', 'layer4': 'res5', 'bn1': 'conv1.norm', 'bn2': 'conv2.norm... |
Imports:
```python
import math
import pandas
import typing
```
Type definitions:
Input Types: Sequence[str], pandas.DataFrame, int
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Sequence[str], v2: pandas.DataFrame, v3: int) -> float:
v4 = pandas.DataFrame(data=dict(premise_id=v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Cursor'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: 'Cursor'=None):
await v1.execute(f'CREATE TABLE IF NOT EXISTS {self.TABLE} (GuildID BIGINT);')
await v1.execute(f'SELECT * FROM {self.TABLE};... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict, v2: dict):
if v2.pop('show_colorbar', True):
v1['legends'] = [{'fill': 'color', 'type': 'gradient'}]
``` |
Imports:
```python
from typing import Callable, Dict, Optional, Sequence, cast
import typing
```
Type definitions:
Input Types: Sequence[str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Sequence[str]) -> None:
assert isinstance(v1, Sequence), "'bands' must be a sequence"... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1, v2=None):
assert v1 is not None
self.key = v1
self.runspec = v2
self.dependencies = set()
self.dependents = set()
self.duration = None
self.priority = None
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: Any
Dependencies:
```python
def v0(v1):
for v2 in range(number):
v1.execute("INSERT INTO foobar VALUES (nextval('foobar_seq'), ?)", (instance_name,))
```
Function Name: v3
Function:
```python
def v3(self, v4: str, v5:... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2) -> None:
v3 = os.path.getsize(v1)
with open(v1, 'rb') as v4:
v5 = v4.tell()
while True:
v6 = v5
... |
Imports:
```python
from datetime import date, datetime, timedelta
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
v1 = False
if not self.convert and self.inserted:
if datetime.now() - self.created_at > timede... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: int, v3: int, v4: int):
v5 = []
try:
with open(v1, 'rb') as v6:
for v7 in range(v3):
v8 = []
... |
Imports:
```python
from collections import Counter
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
(self.table, self.rack, self.initial) = (Counter(), Counter(), True)
self.table_array = np.zeros(s... |
Imports:
```python
from nltk.translate.nist_score import sentence_nist as sent_nist
import typing
```
Type definitions:
Input Types: List[str], List[List[str]], Optional[Dict[str, str]]
Output Type: List[float]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[str], v2: List[List[str]], v3: Optional... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any, Any
Output Type: set
Dependencies:
```python
def v0(v1: int, v2: int, v3: int) -> list:
v4 = list()
if v1 >= v2:
v4.append(v1 - v2)
if v1 < v2 * v3 - v2:
v4.append(v1 + v2)
if v1 % v2 != 0:
v4.app... |
Imports:
```python
from datetime import datetime, timezone, timedelta
import re
import typing
```
Type definitions:
Input Types: datetime
Output Type: datetime
Dependencies:
```python
def v0(v1: str) -> False:
if type(v1) != str:
return False
return re.match('[0-9]{4}-[0-9]{2}-[0-9]{2}T[0-9]{2}:[0-9]{2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: typing.Dict[str, typing.Any]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: typing.Dict[str, typing.Any]):
if self._propagate_signals:
self._propagate_signals = False
self.cbColormap.setCurre... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2) -> list:
v3 = []
for v4 in v1:
v5 = self.__random_remove_by_percent(v4[4], v2)
v6 = len(v5)
v3.append((v4[0], v4[1], v... |
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):
for v2 in self.patterns:
v3 = v2.search(v1)
if v3:
v4 = self.canonicalize_path(os.path.join(self.root_path, v3.g... |
Imports:
```python
import typing
```
Type definitions:
Input Types: object, List[str]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: object, v2: List[str]) -> bool:
v3 = str(type(v1))
return v3 in v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.is_empty():
raise Exception('Stack is already')
self.top = self.top.next
self.size -= 1
``` |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: Namespace, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Namespace, v2: str='opts.json'):
with open(v1.log_root / v2, 'w') as v3:
v4 = {key: str(value) for (v5, v6) in v1.__dict__.items()}... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> dict:
v2 = self.endpoint + f'/vprr/{v1}/index.json'
v3 = self.edgar_session.make_request(method='get', endpoint=v2)
v4 = self.edgar_utiliti... |
Imports:
```python
import os
import pickle
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = os.path.join(self.config.saved_path, self.config.ds_name + '_' + self.config.net_name + '_train_' + str(self.train_size) + '... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
while v1 > 127:
self.write(bytes([v1 & 127 | 128]))
v1 >>= 7
self.write(bytes([v1]))
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> list:
if not isinstance(v1, list):
v1 = [v1]
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
self.__logger.debug(f"Retrieve order with order_id '{v1}'' from database")
return self.__dynamodb_service.find(id_name='order_id', item_id=v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Callable, str, str, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Callable, v2: str, v3: str, v4: str=None) -> None:
if not callable(v1):
raise ValueError('Invalid callback given to add_action(... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Job):
def __init__(self, v1: Job, v2: Union[str, int]):
self.job = v1
self.name = v2
@property
def v3(self) -> str:
return self.job.id
@property
def v4(self) -> int:
return self.job.retry_cou... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
if self._started:
self._num_insert += len(v1)
``` |
Imports:
```python
from collections import OrderedDict
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, Callable, OrderedDict, OrderedDict
Output Type: OrderedDict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: Callable, v3: OrderedDict, v4: OrderedDict) ... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: Tuple[int, int]
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: int):
v3 = tf.io.read_file(v1)
v4 = tf.image.decode_jpeg(v3, channels=1)
v4 = tf.image.convert_image_dtype(v4, tf.float32)
v4 = tf.ima... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.__io_base:
self.__io_base.close()
``` |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
v2 = pd.read_csv(filepath_or_buffer=v1)
v3 = v2.values.tolist()
v4 = v2.to_dict(orient='records')
self.dataframe = v2
... |
Imports:
```python
import math
from tqdm import tqdm
import typing
```
Type definitions:
Input Types: Iterable
Output Type: Any
Dependencies:
```python
def v0(v1):
""" Some test cases (use with print and doctest)
>>> _analyze('Ady7774))')
L3D4S2
['Ady', '7774', '))']
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = 'backend:\ncpp_namespace: torch_xla\nsupported:\n- abs'
v2 = self.get_errors_from_gen_backend_stubs(v1)
self.assertExpectedInline(v2, 'You m... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('_DeferredSemaphoreT', bound='DeferredSemaphore')
```
Input Types:
Output Type: None
Dependencies:
Function Name: v1
Function:
```python
def v1(self: v0) -> None:
assert self.tokens < self.limit, 'Someone released me too many times: too... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: Any
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> pd.DataFrame:
if isinstance(v1, dict):
return pd.DataFrame.from_dict({0: v1}, orient='index')
else:
return v1
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = self.extract_special_chars_then_lower_case()
v1 = '#' + v1.strip().replace(' ', '-')
return '(' + v1 + ')'
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Tuple
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Tuple:
self.stats['cpu'].append(self.cpu_usage)
self.stats['gpu'].append(self.gpu_usage)
return (self.cpu_usage, self.gpu_usage)
``` |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0() -> str:
v1 = 'abcdefghijklmnopqrstuvwxyz'
v2 = random.choice(v1)
v3 = random.randint(0, 2)
if v3 == 0:
v2 = f'%{v2}'
if v3 == 1:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> None:
v1.what.order()
v1.by.order()
v1.fro.order()
v1.too.order()
``` |
Imports:
```python
import collections
import socket
import requests
import typing
```
Type definitions:
```python
class v0(TypedDict, total=False):
v1: str
v2: int
v3: str
v4: str
v5: int
v6: bool
```
Input Types: str, str, int, str
Output Type: Dict[str, List[Tuple[v0, bool]]]
Dependencies:
```... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Any], int
Output Type: Iterator[List[Any]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Any], v2: int) -> Iterator[List[Any]]:
v3 = (v1[i:i + v2] for v4 in range(0, len(v1), v2))
return v3
``` |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.