text stringlengths 190 325k |
|---|
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: base.ClockSignal
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: base.ClockSignal):
v2 = np.nonzero(self.triggers(v1))[0]
v3 = [self.shape_maker(v1.clock.get_clock_signal_with_start(i))... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: int
Dependencies:
```python
def v0(v1: int, v2: int, v3: list) -> int:
if v1 == 0 or v2 == 0:
print(v3)
return 0
elif v1 == 1 or v2 == 1:
if v2 > 1:
v4 = v2
while v4 > 1:
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(BaseModel):
v1: int
v2: t.List[ParkItem]
```
Input Types: Any, Any
Output Type: v0
Dependencies:
Function Name: v3
Function:
```python
def v3(self, v4=0, v5=100) -> v0:
v6 = self._client.get_last_parks(v4, v5)
return self._parse_... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.LongTensor, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.LongTensor, v2: int):
v3 = v1[:, 0]
v4 = v1[:, 1]
v5 = v1[:, 2]
v6 = v3 * v2 + v4
v7 = v4 * v2 + v3
v8 = ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.match_reserved('package')
v1 = self.match_identifier(package=True)
self.match_reserved(';')
if v1[0] == '.' or v1[-1] == '.':
ra... |
Imports:
```python
import sys
import typing
```
Type definitions:
Input Types: Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> int:
v2 = [-1] * 256
v3 = sys.maxsize
for v4 in range(len(v1)):
if v2[ord(v1[v4])] == -1:
v2[ord(v1[v4])] = v4
e... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[str], Optional[List[str]]
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: Union[int, float, str, bool, List[int], List[float], List[str]]) -> List[str]:
v3 = [format_key(v1)]
if isinstance(v2, list):
for v4 in v2:... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(typing.NamedTuple):
v1: str
v2: str
v3: str
v4: typing.Optional[str]
```
Input Types: v0, bytes, str
Output Type: bool
Dependencies:
Function Name: v5
Function:
```python
def v5(v6: v0, v7: bytes, v8: str) -> bool:
v9 = blob.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any, Any
Output Type: List
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3=None, v4=None) -> List:
v5 = self.select(select=v1, table_name=v2, where=v3, extra=v4)
if v5 is None:
return []
retur... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int=0, v3: bool=True) -> None:
v4 = self._calc_abs_indent(v2, v3)
for v5 in v1.splitlines():
self.logger.info(' ' * v4 + v5... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list) -> list:
if len(v1) <= 1:
return v1
else:
v2 = 1
v3 = len(v1)
while v2 < v3:
if v1[v2] == v1[v2 - 1]:
... |
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.get_class(v1)
for (v4, v5) in v2.items():
if v5 is None:
if v4 in v3:
del v3[v4]
else:... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Path
Output Type: Iterator[Tuple[str, str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Path) -> Iterator[Tuple[str, str]]:
for v2 in v1.read_text().splitlines(keepends=False):
(v3, v4, v5) = v2.partition('==')
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str) -> bool:
v3 = True
for v4 in range(min(len(v1), len(v2))):
v3 &= v1[v4] == v2[v4]
return v3
``` |
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.sumo_connection.api.save_top_level_json(json=v1)
v3 = v2.json().get('objectid')
return v3
``` |
Imports:
```python
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors
import matplotlib.animation as animation
from matplotlib.patches import Rectangle
import xarray as xr
from cartopy.crs import PlateCarree
import typing
```
Type definitions:
Input Types: xr.DataArray, Any, float, float,... |
Imports:
```python
import os
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 = {'nt': f'{v2}.exe', 'posix': v2}
v4 = v3[os.name]
v5 = os.path.join(v1, v4)
if not os.path.isfile(v5):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[int]]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[List[int]]) -> int:
v2 = len(v1)
if v2 == 1:
return v1[0][0]
v3 = float('inf')
for v4 in range(1, v2):
for v5 i... |
Imports:
```python
import typing
```
Type definitions:
Input Types: T_VECTOR, T_VECTOR
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: T_VECTOR, v2: T_VECTOR) -> None:
if v1 not in self._verts:
raise KeyError(v1)
if v2 not in self._verts:
raise KeyError(v... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass
class v0(object):
v1 = ('node', 'input', 'next')
v2: 'BaseCDAGNode'
v3: str
v4: Optional['Subscriber']
```
Input Types:
Output Type: Iterable[v0]
Dependencies:
Function Name: v5
Function:
```python
def v5(self) -> Iterable[v0]... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: tf.Tensor, int, int, float, Text, bool, Optional[int]
Output Type: tf.Tensor
Dependencies:
```python
def v0(v1: int, v2: int, v3: float, v4: float):
v5 = tf.cast(v2, tf.float32)
v6 = tf.cast(v1, tf.float32)
def v7(... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass
class v0:
v1: Any
v2: Optional[str] = None
def v3(self, v4: str) -> Any:
"""Delegates to the underlying model."""
if isinstance((v5 := getattr(self.model, v4)), Column):
return Column(self, v5.field, v5.... |
Imports:
```python
import inspect
import typing
```
Type definitions:
Input Types: object, dict, dict
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: object, v2: dict, v3: dict=None) -> dict:
v3 = v3 or {}
v4 = {}
v5 = inspect.getfullargspec(v1)[0]
for (v6, v7) in v2.i... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, *, v2=_HOOK_MAP):
try:
v3 = v2[v1]
v3()
except KeyError:
pass
``` |
Imports:
```python
import os
import subprocess
import typing
```
Type definitions:
Input Types: Union[str, Path]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[str, Path]) -> bool:
v2 = os.path.exists(os.path.join(v1, '.git'))
v3 = subprocess.run('git branch'.split(), c... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types: Any, List[str]
Output Type: Any
Dependencies:
```python
def v0(v1):
from numpy import nan
v2 = {}
for (v3, v4) in v1.items():
v5 = {}
for v6 in v4.keys():
if str(v6) != 'nan' and str(v6) != '' an... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: np.ndarray):
self.experimental_design_input = v1
self.experimental_design_output = v2
self.design_matrix = self.p... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Any
```
```python
v1 = Any
```
```python
v2 = jnp.ndarray
```
```python
v3 = Any
```
Input Types: v3, v1, v2, v0
Output Type: Tuple[jnp.ndarray, v1]
Dependencies:
Function Name: v4
Function:
```python
def v4(self, v5: v3, v6: v1, v7: v2, v8: v0) -> ... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: v0
Output Type: None
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: v0) -> None:
if self.filter(v2):
return super().put_nowait(v2)
``` |
Imports:
```python
import torch
import torch.nn as nn
import typing
```
Type definitions:
Input Types: torch.Tensor, Optional[torch.ByteTensor], Any
Output Type: List[List[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: Optional[torch.ByteTensor]=None, v3=1) -> List[List[i... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[Dict[str, List[str]]], Optional[str]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[Dict[str, List[str]]]=None, v2: Optional[str]=None) -> int:
v3 = self.get_all_documents(index=v2, filters... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: 'User'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> 'User':
v3 = self.create_user(email=v1, password=v2)
v3.is_staff = True
v3.is_superuser = True
v3.save(using=self._db)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: csr_matrix
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> csr_matrix:
(v2, v3) = self.match_and_extend(v1)
if v2:
v4 = self.pipeline_.predict_proba(v2)[:, 1]
else:
v4 = []
retu... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> bool:
v2 = v1[:v1.rfind(':')]
return os.path.exists(v2)
``` |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: list
Output Type: List[pd.DataFrame]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list) -> List[pd.DataFrame]:
v2 = []
for v3 in v1:
v4 = pd.read_html(v3.prettify(), flavor='bs4')[0]
v2.ap... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tuple[List[int], List[int]]
Output Type: Tuple[float, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tuple[List[int], List[int]]) -> Tuple[float, int]:
v2 = 0
v3 = 0
v4 = 0
v5 = 0
for v6 in range(len(v1[1])):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int) -> str:
v3 = []
for v4 in v1:
while v3 and v3[-1] > v4 and (v2 > 0):
v3.pop()
v2 -= 1
if not ... |
Imports:
```python
import zipfile
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
with zipfile.ZipFile(v1, 'r') as v2:
return sum((f.file_size for v3 in v2.infolist()))
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(BoundedEntity, ABC):
v1 = Point3D.create(0, 0, 0)
v2 = Vector3D.create(0, 0, 0)
v3 = Vector3D.create(1, 0, 0)
v4 = Vector3D.create(0, 1, 0)
v5 = Vector3D.create(0, 0, 1)
'The name of the Component.\n \n When this Com... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types:
Output Type: Iterator[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Iterator[str]:
v1 = os.path.join(self.configs.data_path, 'multi.idx')
if not os.path.exists(v1):
raise FileNotFoundError(f'Canno... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: bool, **v3):
v4 = '\nimport network\nwlan = network.WLAN({})\nwlan.active({})\n'.format(v1, str(v2))
self.execute(v4, **v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: commands.Command
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: commands.Command):
v2 = await self.filter_commands([v1])
if v2:
self.paginator.add_command(self.clean_prefix, v1, self.get_co... |
Imports:
```python
import numpy as np
import cv2
import matplotlib.pyplot as plt
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
```python
def v0(v1: 'npt.NDArray', v2: int=50, v3: Any=255):
v4 = np.repeat(v3, v1.shape[1])
v4 = np.array(v4, dtype=np.uint8)
return np.conc... |
Imports:
```python
from qiskit.utils import algorithm_globals
from qiskit.utils.deprecation import deprecate_arguments
import typing
```
Type definitions:
Input Types: int, Callable[[np.ndarray], float], Optional[Callable[[np.ndarray], float]], Optional[List[Tuple[float, float]]], Optional[np.ndarray]
Output Type: Tup... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if not self.on_focus:
return
self.add_child(self.credits)
self.current_focus = self.credits
self.credits.popup()
self.on_focus = ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, dict
Output Type: Tuple[bool, dict, dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: dict) -> Tuple[bool, dict, dict]:
v3 = False
(v4, v5) = (dict(), dict())
for v6 in v1:
for (v7, v8) in v2.ite... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: typing.Set[float]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> typing.Set[float]:
v1 = super().transition_times()
v1.update(self.inside_temp.transition_times)
v1.update(self.outside_temp.transition_tim... |
Imports:
```python
import typing
```
Type definitions:
Input Types: MutableMapping[str, Any]
Output Type: Mapping[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: MutableMapping[str, Any]) -> Mapping[str, Any]:
for (v2, v3) in list(v1.items()):
if v2.startswith('_'):
v4... |
Imports:
```python
import typing
```
Type definitions:
Input Types: nx.Graph
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: nx.Graph) -> bool:
v2 = v1.edges
v3 = v1.order()
return len(v2) == v3 * (v3 - 1) / 2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: cairo.Context, symbols.Polyline
Output Type: None
Dependencies:
```python
def v0(v1: cairo.Context, v2: Tuple) -> None:
if len(v2) == 4:
(v3, v4, v5, v6) = v2
v1.set_source_rgba(v3 / 255.0, v4 / 255.0, v5 / 255.0, v6 / 255.0)
e... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tuple[torch.Tensor, torch.Tensor]
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tuple[torch.Tensor, torch.Tensor]) -> torch.Tensor:
self.optim.zero_grad()
v2 = self.backprop(v1)
self.optim.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
v2 = v1.split('or')
if len(v2) == 1:
return v1
v2 = [pt.strip() for v3 in v2]
if len(v2) == 2:
if v2[0] == 'None':
... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> bool:
if not str(v1).startswith('http') and (not str(v1).startswith('s3')) and (not str(v1).startswith('ftp')):
return False
v2 = r... |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1, *v2, **v3):
logger.info(f"Executing command: {' '.join(v1)}")
subprocess.run(v1, *v2, **v3)
```
Function Name: v4
Function:
```python
def v4(self, v5: str=None):
if ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list):
nonlocal header
if not v1:
return False
if len(v1) == 3 and (not header):
v2 = True
elif len(v1) == 3:
return (0, 0, f... |
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.getGeneratedRandomEffects()
assert v1 in v2, 'Group {} not found in generated random effects: {}'.format(v1, v2)
if not self.hasComp... |
Imports:
```python
import typing
```
Type definitions:
Input Types: datetime
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: datetime=None):
if v1 is None:
v1 = self.client.now
return {v1: self.client.hourlykWhPrice(v1, self.mpid)}
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
assert type(v1) is str
return v1 in self.classlist
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: typing.Dict
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: typing.Dict) -> int:
try:
return v1['pull_request']['number']
except Exception:
raise RuntimeError('pull_request.number not found in G... |
Imports:
```python
from pathlib import Path
import typing
```
Type definitions:
Input Types: Any, Union[str, Path], bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: Union[str, Path], v3: bool=False) -> None:
v2 = Path(v2)
if v2.exists() and (not v3):
raise File... |
Imports:
```python
import sqlite3
from datetime import datetime
from pathlib import Path
from torch.utils.tensorboard import SummaryWriter
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict={}):
v2 = datetime.now()
s... |
Imports:
```python
import torch
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: torch.Tensor) -> torch.Tensor:
v3 = self.sample_action(v1).ar... |
Imports:
```python
import requests
import typing
```
Type definitions:
Input Types: str, Optional[dict]
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Optional[dict]=None) -> dict:
v3 = self.__get_header()
v4 = v2
v5 = requests.delete(url=v1, headers=v3, pa... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any, Any, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3, v4, v5: str=''):
v1.subheader('[Discrete-time SIR modeling](https://mathworld.wolfram.com/SIRModel.html) of infections/recovery')
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, list, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: list, v3: int):
v4 = np.empty((v3, v1.shape[1]))
for v5 in range(v3):
v6 = np.where(v2 == np.max(... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[str]:
v1 = [str(self.validation_information)]
for v2 in self.validated_constraints:
v1 += v2.report()
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict) -> list:
v2 = []
for v3 in self.s_space.dim_keys:
v2.append(v1[v3])
return v2
``` |
Imports:
```python
import inspect
from inspect import signature
import typing
```
Type definitions:
Input Types: Any
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Any) -> str:
v2 = inspect.getdoc(v1)
return v2 if v2 else ''
``` |
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]:
v1 = ''
v2 = ''
for v3 in self.__records:
v1 += v3.groupName + ':x:' + str(v3.groupID) + ':' + ','.jo... |
Imports:
```python
import torch
from torch import nn
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, torch.Tensor, bool
Output Type: Tuple[torch.Tensor, Optional[torch.Tensor]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: torch.Tensor, v3: torch.T... |
Imports:
```python
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Circle
from matplotlib.projections import register_projection
from matplotlib.projections.polar import PolarAxes
import typing
```
Type definitions:
Input Types: np.ndarray, matplotlib.axes.Axes, List... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int) -> list:
v3 = []
v4 = v1 + v2
for v5 in range(v1, v4):
v3.append(self.hex_array[v5])
return v3
``` |
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 = [wire.split(',') for v3 in v1.splitlines()]
(v4, v5) = [self._build_path(path) for v6 in v2]
v7 = set(v4).intersection(set(v5))
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame) -> dict:
v2 = v1.loc[:, 'Value labels (vls)']
v3 = []
for v4 in v2:
if v4 is np.nan:
v3.app... |
Imports:
```python
import json, logging, os
from datetime import timedelta
import typing
```
Type definitions:
Input Types: df.DurableOrchestrationContext
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: df.DurableOrchestrationContext):
v2 = os.getenv('OnCallPhoneNumber')
v3 = {... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[Tuple[Tensor, Tensor]]
Output Type: Optional[List[Tuple[Tensor, Tensor, float]]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Optional[Tuple[Tensor, Tensor]]=None) -> Optional[List[Tuple[Tensor, Tensor, float]]]:
if v1 ... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.body.reset_pose(position=[0.0, 0.0, 0.0])
v1 = np.random.uniform(-1.0, 1.0, size=3)
v2 = np.random.uniform(-1.0, 1.0, siz... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int]
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int]) -> List[int]:
v2 = []
for v3 in range(len(v1))[::-1]:
if not v2 or v1[v3] > v1[v2[-1]]:
v2.append(v3)
ret... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, bool
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int, v3: bool) -> bytes:
if not isinstance(v1, int):
v1 = int(v1)
return bytes([i for v4 in v1.to_bytes(v2, 'little', signed=v3)... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, str, str, str, str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: str, v4: str, v5: str, v6: str, v7: str):
self._load_movie_data(v1)
self._load_link_data(v2)
self._l... |
Imports:
```python
import typing
```
Type definitions:
Input Types: types.ModuleType, str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: types.ModuleType, v2: str, v3: Any) -> Any:
if v2 == '':
return v1
v4 = v1
v5 = v2.replace('/', '.').split('.')
v6 = v5... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, int, bool, str, str
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1, v2: int, v3: bool, v4: str, v5: str=None) -> dict:
v6: dict = {'days': v2, 'compute_prune_count': v3, 'include_roles': v4, 'reas... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Union[List[Union[int, None, str]], None]]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Union[List[Union[int, None, str]], None]]):
if not v1:
return
for v2 in v1:
if not v2:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict):
v2 = []
for (v3, v4) in v1.items():
v2 += list(v4.columns)
v5 = set(v2)
return v5
``` |
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:
Input Types: 'Player', int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Player', v2: int):
self.subs.append((v1, v2))
self.combine_scores(v1)
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: 'wavelength np.array'
Output Type: np.array
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: 'wavelength np.array', *v2: 'amplitude, peak position, peak width, constant') -> np.array:
v3 = len(v2) // 3
v4 = v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'SyncConfig'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: 'SyncConfig'):
if v1.sync_to_driver is None:
v1.sync_to_driver = not bool(v1.upload_dir)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: object
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> object:
if self.strategy is None:
raise AttributeError('TreeNode has no Strategy')
else:
return self.strategy.can_classify()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, **v2) -> Dict[str, Any]:
self._check_keys(v1, v2)
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[str]) -> str:
if v1 is not None and len(v1) > 0:
return ';'.join(v1).replace('/', '\\') + ';'
return ''
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0() -> None:
_renderables.extend(_renderables_add)
_renderables_add.clear()
for v1 in _renderables_remove:
_renderables.remove(v1)
_renderables_remove.clear()
if False:
... |
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._task_def.label_vocab
if v2 is not None:
return v2[v1]
else:
return int(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor):
v2 = v1[..., 0, 0] * (v1[..., 1, 1] * v1[..., 2, 2] - v1[..., 1, 2] * v1[..., 2, 1]) - v1[..., 0, 1] * (v1[..., 1, 0] * v1[..., 2, 2] - v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
print('\t' + str(self))
print(f'\tdelta: {self.delta}')
if self.solutions:
print(f'\tSolutions: {self.solutions}')
else:
prin... |
Imports:
```python
import logging
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1, v2, v3, v4):
self.id = v1
self.event_name = v2
self.body = v4
self.receipt_handle = v3
```
Input Types: v0
Output Type: Any
Dependencies:
Function Name: v5
Function:
```... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> bool:
if len(v1) != len(v2):
return False
if v1 == v2:
return True
v3 = len(v1)
v4 = [[[False] * (v3 + 1)... |
Imports:
```python
import torch
from torch import nn
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray) -> List[str]:
v2 = self.preprocess_input(v1)
v3 = torch.softmax(self.backbone(v2), axis=-1)
... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass
class v0:
v1: ChpSimulator
v2: float = 0.0
v3: Dict[Loc, int] = field(default_factory=dict)
v4: Dict[int, Loc] = field(default_factory=dict)
v5: Dict[SpaceTimeLocation, MeasureResult] = field(default_factory=dict)
def v... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: argparse.Namespace
Output Type: None
Dependencies:
```python
def v0(v1: str) -> Optional[BugoutResource]:
v2 = get_subscription_type(v1)
if v2 is None:
return None
v2 = bc.delete_resource(token=MOONSTREAM_ADMIN_ACCESS_T... |
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