text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: 'DataSet'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> 'DataSet':
v2 = self.get_data_set(v1, include_deleted=True)
if v2 is None:
v2 = self.add_data_set(v1)
if v2.deleted:
r... |
Imports:
```python
import torch
import torch.nn as nn
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor) -> torch.Tensor:
v2 = self.encode1(v1)
v3 = self.encode2(self.max_pool(v2))
v4 = ... |
Imports:
```python
import warnings
import torch
from torch import nn
import typing
```
Type definitions:
Input Types: Union[numpy.ndarray, torch.Tensor], int
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[numpy.ndarray, torch.Tensor], v2: int=None) -> torch.Tensor... |
Imports:
```python
import numpy
import typing
```
Type definitions:
Input Types: numpy.ndarray, numpy.ndarray
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: numpy.ndarray, v2: numpy.ndarray) -> float:
v3 = v1 - v2
v4 = numpy.dot(v3, v3)
return numpy.sqrt(v4)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'TreeNode', 'TreeNode'
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'TreeNode', v2: 'TreeNode') -> None:
if v1 is None:
raise TypeError('old_subtree is not allowed to be None.')
if v2 == v1:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optimizer, Dict[str, Any]
Output Type: Dict[str, Dict[str, Any]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optimizer, v2: Dict[str, Any]) -> Dict[str, Dict[str, Any]]:
v3 = v2['lr']
v4 = {'step_size': 10 * self.stat... |
Imports:
```python
import geopandas as gpd
from geopandas.sindex import PyGEOSSTRTreeIndex
from shapely import prepared
from shapely.affinity import scale
from shapely.geometry import LineString, MultiLineString, MultiPoint, MultiPolygon, Point, Polygon, box
from shapely.geometry.base import BaseGeometry, BaseMultipart... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Tensor], Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Tensor], v2: Tensor):
v3 = v1['encoder_out']
v3 = v3.index_select(1, v2)
v4 = {'encoder_out': v3}
v4['src_tokens... |
Imports:
```python
import typing
```
Type definitions:
Input Types: object, str, str, str, Optional[bytes], datetime, datetime
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: object, v2: str='', v3: str='', v4: str='', v5: Optional[bytes]=b'', v6: datetime=datetime.fromtimestamp... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
v2 = []
v3 = v1.split(' ')
for v4 in v3:
v5 = v4.strip()
if v5:
v2.append(v5)
return ' '.join(v2[::-1])... |
Imports:
```python
import typing
```
Type definitions:
Input Types: ast.Attribute
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: ast.Attribute) -> None:
v2 = self._position_from_node(v1)
self.visit(v1.value)
v3 = self._names_from(v1.value)
with self.collector.na... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pathlib.Path
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pathlib.Path) -> str:
v2 = None
v3 = v1.name.split('_')
if v3[0].startswith('transformation'):
v2 = '_'.join(v3[3:6])
if v3[0:2] == [... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
```python
def v0(v1=6, v2=None) -> GuitarShape:
if v2 is None:
v2 = random.randrange(0, 12)
v3 = [FretPosition(string=v1, fret=v2), FretPosition(string=v1 - 1, fret=v2 + 2)]
return G... |
Imports:
```python
import asyncio
import inspect
import threading
import typing
```
Type definitions:
Input Types: Callable, bool
Output Type: Callable
Dependencies:
```python
@functools.wraps(function)
def v0(*v1: Any, **v2: Any) -> Any:
try:
v3 = asyncio.get_event_loop()
except RuntimeError:
... |
Imports:
```python
import os
import uuid
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str='mp4'):
os.makedirs('sandbox', exist_ok=True)
return f'sandbox/{uuid.uuid4()}.{v1}'
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Model):
v1: List[str]
v2: Dict[str, str]
v3: str
v4: List[str]
v5: str
v6: str
v7: List[str]
v8: List[str]
def v9(self, v10: List[str]) -> v0:
self.achievements = v10
return self
def v11(s... |
Imports:
```python
from uuid import UUID
import numpy as np
from scipy.interpolate import LinearNDInterpolator
from scipy.spatial import cKDTree
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray):
if v1 is N... |
Imports:
```python
import numpy as np
from skimage.feature import peak_local_max
from skimage.filters import gaussian, threshold_otsu
from skimage.measure import label, regionprops
from skimage.segmentation import watershed
from skimage.transform import hough_line, hough_line_peaks, resize
from sklearn.neighbors import... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
v2 = self.conn.cursor()
v3 = '\n SELECT inventory.id, inventory.name, \n inventory.desc, inventory.warehouse_id,\n wa... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, int, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int, v3: int, v4={}):
v5 = 1 << v2
v6 = self.bus.read_byte_data(self.addr, v1)
if v3 == 1:
self.bus.write_byte_data(... |
Imports:
```python
from requests.models import CaseInsensitiveDict
from requests.models import Response as RequestsResponse
import typing
```
Type definitions:
Input Types: str, Optional[int], Optional[str], Optional[str], Optional[str]
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: Optional[int]=400, v3... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict) -> Any:
if v1['error'] and v1['error']['code'] == 'ECONNREFUSED':
return Exception('The server refused the connection')
if v1['total_retr... |
Imports:
```python
from qiskit.chemistry.algorithms.pes_samplers.potentials.potential_base import PotentialBase
from qiskit.chemistry.drivers import Molecule
import qiskit.chemistry.constants as const
import typing
```
Type definitions:
Input Types: int
Output Type: float
Dependencies:
Function Name: v0
Function:
```... |
Imports:
```python
import typing
```
Type definitions:
Input Types: nx.DiGraph
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: nx.DiGraph):
(v2, v3) = self._get_ns_id(graph=v1, node_name=self.query.source)
(v4, v5) = self._get_ns_id(graph=v1, node_name=self.query.target)
... |
Imports:
```python
from pathlib import Path
import typing
```
Type definitions:
Input Types:
Output Type: Path
Dependencies:
Function Name: v0
Function:
```python
def v0(self, *v1) -> Path:
v2 = Path(self._tempdir.name).absolute()
return self._makedirs_join(*v1, root_dir=v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'List[int]'
Output Type: 'int'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'List[int]') -> 'int':
v2 = len(v1)
if v2 == 0:
return 0
(v3, v4, v5) = (0, 0, v1[0])
for v6 in range(1, v2):
if v6 > ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Mapping[str, str]
Output Type: Optional[float]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Mapping[str, str]) -> Optional[float]:
v2 = v1.get('font-size')
if v2 is None:
return v2
return self._pt_to_float(... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
for (v2, v3) in self.patterns_.items():
if v2.match(v1):
return v3
return 'O'
``` |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
self.checkpoint_path.mkdir(exist_ok=True, parents=True)
if len(self.get_checkpoint_files()) > self.max_checkpoints:
self.remo... |
Imports:
```python
from qiskit.transpiler import CouplingMap, InstructionDurations, TranspilerError
from qiskit.providers.fake_provider import FakeMontrealV2
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1, v2, v3='dt'):
for v4 in range(self.num_qubits):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> bool:
v2 = len(self.d[v1]) == 0
self.d[v1].add(len(self.l))
self.l.append(v1)
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.array
Output Type: List[float]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.array) -> List[float]:
v2 = self._ptm_matrix_values(v1)
v3 = []
v4 = len(self.Gs)
v5 = 2 ** self.qubits
v6 = v5 ** 2
v7 ... |
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.get_button_text('disable_auto_rollbacks', is_active=False)
super().start_auto_rollback_countdown(extra_text=f'Click "{v2}" t... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, bool
Output Type: Dict[str, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: bool) -> Dict[str, str]:
v4 = {'dash': '-', 'underscore': '_'}
v5 = {}
v5.update({f'{sep_name}_{v1}': f'{sep... |
Imports:
```python
import cvxpy as cp
import cvxpy.settings as s
from cvxpy.transforms.partial_optimize import partial_optimize
from cvxpy.expressions.variable import Variable
from cvxpy.expressions.constants import Parameter, Constant
from cvxpy.reductions.solvers.defines import INSTALLED_MI_SOLVERS
import numpy as np... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1, v2, v3: str=None, **v4):
async with self.session.request(v1, v2, **v4) as v5:
if not v3:
return v5
v6 = getattr(... |
Imports:
```python
from datetime import datetime, timezone
import typing
```
Type definitions:
Input Types: dict
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict) -> dict:
v1['create_date'] = datetime.now(timezone.utc)
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 'USD' in v1 and 'JPY' in v1:
return 1 / 100
else:
return 1 / 10000
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
v1 = [self.get_transaction(h) for v2 in self.get_best_block_tips()]
v3 = 0
for v4 in v1:
v5 = v4.get_metadata().height
if v5 > v3:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
if '#' in v1:
return v1.split('#')[0].rstrip()
return v1.rstrip()
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: np.ndarray
Dependencies:
```python
def v0(v1: int, v2: [tuple], v3=-1, v4=False) -> np.ndarray:
v5 = np.identity(v1, dtype=np.float)
for v6 in v2:
(v7, v8, v9) = v6
v10 = np.cos(v9)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: bool) -> str:
if v1:
return '✓'
return ''
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self._unzip()
v1 = self.temp / 'ffmpeg'
self._cleanup(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: JavaParserLabeled.ClassDeclarationContext
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: JavaParserLabeled.ClassDeclarationContext):
print('Refactoring started, please wait...')
if self.objective_class =... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Union[int, float, str]
```
Input Types: str, Dict[str, v0], bool
Output Type: Any
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: str, v3: Dict[str, v0], v4: bool=False):
if v4:
if self.admin_loop is None:
... |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.conv import Conv2d
import typing
```
Type definitions:
Input Types: nn.Module, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: nn.Module, v2):
if torch.cuda.is_available(... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(BaseClient):
def __init__(self, v1: str, v2: str, v3: bool, v4: bool):
v5 = {'X-Auth-Token': v2, 'Accept': 'application/json', 'Content-Type': 'application/json'}
super().__init__(v1, headers=v5, verify=v3, proxy=v4)
def... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> int:
v2 = int(v1[:-1])
v3 = v1[-1]
v4 = {'m': 60, 'h': 60 * 60, 'd': 60 * 60 * 24, 'w': 60 * 60 * 24 * 7}
return v2 * v4[v3] * 1000
``` |
Imports:
```python
import numpy
import numpy as np
from numpy import linalg as LA
import cvxpy as cp
import cvxpy.interface as intf
import cvxpy.settings as s
from cvxpy.constraints import PSD, ExpCone, NonPos, Zero
from cvxpy.error import DCPError, ParameterError, SolverError
from cvxpy.expressions.constants import Co... |
Imports:
```python
import typing
```
Type definitions:
Input Types: object
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: object=None) -> None:
assert self._validate()
if self._nick_entry is None:
v2 = self._initial_config['nick']
else:
v2 = self._ni... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor) -> torch.Tensor:
v2 = v1.shape[0]
v3 = v1.view(-1, *self.in_shape.tolist())
v4 = [0]
v4.extend([self.in_num - i ... |
Imports:
```python
import torch
import copy
import random
import tqdm
import json
from pathlib import Path
import multiprocessing
import numpy as np
from functools import partial
from collections import defaultdict
import typing
```
Type definitions:
Input Types: str, str, str, int, int, int, bool, bool
Output Type: N... |
Imports:
```python
import urllib
import requests
import typing
```
Type definitions:
Input Types: str
Output Type: List[Mapping[str, Any]]
Dependencies:
```python
def v0(v1: Mapping[str, Any]) -> bool:
v2 = source_str in v1['label'][0]
v2 = v2 or any((source_str in alias for v3 in v1['alias']))
v4 = v1['de... |
Imports:
```python
import math
import typing
```
Type definitions:
Input Types: float, Optional[float], Optional[float]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float, v2: Optional[float], v3: Optional[float]=None) -> str:
if v2 is None:
return str(v1)
if v3 is N... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: str
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> pd.DataFrame:
v2 = self.get_nav(isin=v1)
return pd.DataFrame(data=v2['navPerUnit'], index=pd.DatetimeIndex(v2['date... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: (np.ndarray, np.ndarray, np.ndarray, np.ndarray)
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str=None) -> (np.ndarray, np.ndarray, np.ndarray, np.ndarray):
if v2 is None:
v3 = self._... |
Imports:
```python
import numpy
import typing
```
Type definitions:
Input Types: numpy.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: numpy.ndarray):
v2 = numpy.reshape(v1, (1, -1))
v3 = self.pca.transform(X=v2)
v4 = self.regressor.predict(X=v3)[0]
return... |
Imports:
```python
import gzip
from pathlib import Path
import typing
```
Type definitions:
Input Types: typing.Union[Path, str], str, bool
Output Type: typing.IO[typing.Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: typing.Union[Path, str], v2: str='r', v3: bool=True) -> typing.IO[typing.Any]:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: tuple, np.matrix, list[tuple]
Output Type: Sequence[tuple]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: tuple, v2: np.matrix, v3: list[tuple]) -> Sequence[tuple]:
(v4, v5) = v2.shape
v6 = [(v1[0], v1[1] + 1), (v1[0], v1[1] -... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1: bool):
self.title += '.'
```
Function Name: v2
Function:
```python
def v2(self, v3: str):
def v4(v5: bool):
self.title += '.'
return v4
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tensor, Tensor, Optional[Tensor]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tensor, v2: Tensor, v3: Optional[Tensor]=None):
self.train_X = v1
self.train_Y = v2
self.train_Yvar = v3
``` |
Imports:
```python
import os
import numpy as np
import typing
```
Type definitions:
Input Types: Union[PosixPath, str], Sequence[float], Any
Output Type: Tuple[List[Union[PosixPath, str]], List[Union[PosixPath, str]], List[Union[PosixPath, str]]]
Dependencies:
```python
def v0(v1: List[str]):
return [os.path.join(... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Callable, Any
Output Type: Any
Dependencies:
```python
def v0(v1, v2):
return v2[v1:]
```
Function Name: v3
Function:
```python
def v3(v4: Callable, v5):
v6 = None
for (v7, v8) in enumerate(v5):
if not v4(v8):
v6 = v7
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Any) -> bool:
if isinstance(v1, list) and isinstance(self.op, list):
return all((x in self.op for v2 in v1))
else:
return v1 in self.op... |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: Any, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: str) -> None:
v3 = v1['summary'][:len("'s birthday") + 1]
v4 = v1['start'].get('dateTime', v1['start'].get('date'))
print(f'Se... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('IntervalArrayT', bound='IntervalArray')
```
Input Types: Any, Any, Any
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self: v0, v2=None, v3=None, v4=None) -> v0:
if v3 is not None:
raise TypeError('Fi... |
Imports:
```python
import typing
```
Type definitions:
Input Types: payload.Payload
Output Type: 'Tracker'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: payload.Payload) -> 'Tracker':
for v2 in self.emitters:
v2.input(v1.nv_pairs)
return self
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: str=''):
self._score += v1
v3 = '' if v1 < 0 else '+'
self._log.append(f'{v3}{v1} :: {v2}')
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
v2 = np.sum([o['pre'] for v3 in v1], axis=0)
v4 = np.sum([v3['cor'] for v3 in v1], axis=0)
v5 = np.sum([v3['true'] for ... |
Imports:
```python
import json
import os
import tarfile
import tensorflow.compat.v2 as tf
import typing
```
Type definitions:
Input Types: tfds.download.DownloadManager
Output Type: Any
Dependencies:
```python
def v0(v1: tfds.download.DownloadManager):
with tf.io.gfile.GFile(v1.download(_MULTI_LABELS_URL), 'r') as... |
Imports:
```python
import torch
from torch import multiprocessing as mp
from torch import nn
from torch.nn import functional as F
import typing
```
Type definitions:
```python
v0 = typing.Dict[str, typing.List[torch.Tensor]]
```
Input Types: Any, mp.SimpleQueue, mp.SimpleQueue, v0, Any, Any
Output Type: Any
Dependencie... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
v1 = self.current_file.get('script', {}).get('script', '') not in ['-', '']
if v1:
return True
v2 = [self.check_separators_in_folder(), s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
v2 = {'ip-src': 'ip', 'ip-dst': 'ip', 'pattern-in-file': 'filepath', 'target-email': 'email', 'email-src': 'email', 'email-dst': 'email', 'vuln... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, **v2: Any) -> None:
v3 = self.get_monitor_value()
if v3 is None:
return
if self.operator(v3 - self.min_delta, self.best):
(self.bes... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: 'DataArray'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, **v1) -> 'DataArray':
v2 = self.copy(deep=False)
return v2.load(**v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = 'example.docx'
v2 = self._send_request(v1, data={'structure_type': 'linear'})
v3 = v2['content']['structure']['subparagraphs']
self.asse... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2=None):
if '.' in v1:
return self.contents[v1]
v3 = []
for (v4, v5) in self.contents.items():
if v4.startswith(v1):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: typing.NoReturn
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> typing.NoReturn:
self.__solve_max()
self.__solve_min()
``` |
Imports:
```python
from copy import deepcopy
from functools import partial, reduce
import typing
```
Type definitions:
Input Types: List[Any], List[Any]
Output Type: List[Any]
Dependencies:
```python
def v0(v1: dict, v2: dict) -> dict:
return cut_(d1=v1, d2=v2, list_strategy=_cut_list_strategy)
```
Function Name: ... |
Imports:
```python
import cv2
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray) -> np.ndarray:
v1 = -1 * np.log(v1)
v1 = (v1 / np.max(v1) * 255).astype(np.uint8)
v2 = cv2.applyCo... |
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(self, v1) -> pd.DataFrame:
for v2 in v1.columns.values.tolist():
self.column = str(v2)
self.frame = pd.DataFrame(v1[self.... |
Imports:
```python
import torch
from torch import nn
import typing
```
Type definitions:
Input Types: experience.EpochTrajectories
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: experience.EpochTrajectories):
v2 = torch.optim.Adam(self.policy.net.parameters(), lr=0.01)
v... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
v1 = jinja2.PackageLoader('pandas', 'io/formats/templates')
v2 = jinja2.Environment(loader=v1, trim_blocks=True)
v3 = v2.get_template('html.tpl')
def __init__(self, v4: FrameOrSeriesUnion, v5: Optional[int]=None, v6: Optional[CS... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[Iterable[str], str]
Output Type: List[str]
Dependencies:
```python
def v0(v1: str) -> str:
if not v1.startswith(('http://', 'https://')):
return 'http://' + v1
return v1
```
Function Name: v2
Function:
```python
def v2(v3: Union[... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, str, str
Output Type: str
Dependencies:
```python
def v0(v1: str) -> str:
v2 = SpecifierSet(v1)
(v3, v4) = sorted(v2, key=str)
v5 = list()
v5.append(f'{v3} *, *{v4}')
v5.append(f'{v4} *, *{v3}')
return '|'.join(v... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
if not self._copy_paste_enabled:
return False
self._copy()
if self._selection_surface:
self._remove_selection()
return Tr... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: (int, int)
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> (int, int):
for v1 in range(len(self.alphabet)):
for v2 in range(len(self.alphabet)):
yield (v1, v2)
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(disnake.ui.View):
async def v1(self, v2: disnake.MessageInteraction) -> bool:
return v2.author == self.ctx.author and v2.channel == self.ctx.channel
def __init__(self, v3, v4: 'File', v5=None, v6=None, v7: list[str]=None):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, str, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: str, v4: str) -> None:
if self.__mp:
self.__mp.people_set(v1, {'$first_name': v2, '$last_name': v3, '$email': v4})... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = self.get_batch_template_path()
with open(v1, 'r') as v2:
return v2.read()
``` |
Imports:
```python
import os
import subprocess
import typing
```
Type definitions:
Input Types: os.path, os.path
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: os.path, v2: os.path):
os.mkdir(v2)
v3 = [pcd_file for v4 in os.listdir(v1) if os.path.isfile(os.path.join(v1, v4))]
... |
Imports:
```python
import calendar
import datetime
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
```python
def v0(v1: str):
try:
v2 = COURSES[v1]
except KeyError as e:
v2 = []
return v2
```
```python
def v3(v4: str=None) -> list:
v5 = []
if not... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
(v2, v3) = self.full_name.split('/')
return self.get_release_by_tag(v2, v3, v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
if self.widget:
if self.widget.winfo_class() in ('Button', 'TButton', 'Label', 'TLabel', 'Radiobutton'):
if self.widget['text'... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, float, float
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: float, v3: float) -> None:
v4 = v1 * v2
v5 = v4 * v3
v6 = v4 - v5
print('Regular price:', '%.2f' % v4)
print('Discount:', ... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: tf.Tensor, tf.Tensor
Output Type: List[tf.Tensor]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: tf.Tensor, v2: tf.Tensor) -> List[tf.Tensor]:
with tf.GradientTape() as v3:
v3.watch(self.netwo... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: str):
v3 = v1.objects.filter(connection_id=v2).order_by('-created').first()
if not v3:
raise RuntimeError(f'Not found: {v1} with connection_i... |
Imports:
```python
import weakref
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: weakref.WeakMethod) -> typing.Callable[[event_manager_.EventT], typing.Coroutine[typing.Any, typing.Any, None]]:
async def v2(v3: event_manager_.EventT) -> None:
v4 = v1... |
Imports:
```python
from pandas._config import get_option
from pandas._libs import algos as libalgos, lib, properties
from pandas._libs.hashtable import duplicated
from pandas._libs.lib import no_default
from pandas._typing import AggFuncType, AnyArrayLike, ArrayLike, Axes, Axis, ColspaceArgType, CompressionOptions, Dty... |
Imports:
```python
import typing
```
Type definitions:
Input Types: any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: any) -> None:
if v1.x < 0 or v1.x >= 288 or v1.y < 0 or (v1.y >= 416):
return
v2 = v1.x >> 5
v3 = v1.y >> 5
v4 = v2 + v3 * 9
if v4 ... |
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