text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, str]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, str]) -> str:
v2 = '<?xml version="1.0" encoding="utf-8"?> <manifest> <type>ota</type> <ota> ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: x, *v4: x, v2: x, v3: x=3, **v5: x):
pass
```
Function Name: v6
Function:
```python
def v6() -> None:
v7 = int
def v8(v9: v7, *v12: v7, v10: v7, v11: v7=3, **v13: v7):
pass
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Iterable
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: Iterable) -> list:
v3 = set()
for v4 in v2:
if v1 == v4:
return [v1]
if v4.startswith(v1):
v3.add(... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float):
if v1.as_integer_ratio()[1] == 1:
self.selectedItem.minTime = int(v1)
else:
self.selectedItem.minTime = v1
self.canvas.update()
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
while True:
self.skip_ws()
(v1, v2) = (self.loc(), self.try_name())
if v2 is None:
break
self.colon()
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: 'np.ndarray', int, int, bool
Output Type: Iterator[Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: 'np.ndarray', v2: int=0, v3: int=None, v4: bool=False) -> Iterator[Any]:
if v4:
v1 = np.take(v1, np.... |
Imports:
```python
import numpy as np
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='total_gain'):
assert self.gbms_ is not None
v2 = self.gbms_[0].feature_names
for v3 in self.gbms_:
... |
Imports:
```python
from PIL import Image, ImageDraw, ImageFont, ImageColor
import typing
```
Type definitions:
```python
class v0:
def __init__(self):
self.colors: List[Tuple[float, Tuple[int, int, int]]] = []
def v1(self, v2, v3: Tuple[int, int, int]):
self.colors.append((v2, v3))
def v4... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[int]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[int]=None) -> bool:
if v1 is None:
v1 = self.get_last_epoch()
v2 = self[v1]
if not self.params.num_epochs:
v3 = ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> bool:
assert v1 >= 0
while v1 & 1 != 0:
v1 >>= 1
return v1 == 0
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=None) -> bool:
for v2 in self.components:
v2.save()
super().save(filename=v1)
return True
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: 'AsyncCursor'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> 'AsyncCursor':
self.dispatch = self.dispatch.max_await_time_ms(v1)
return self
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Model):
v1: str
v2: str
v3: str
v4: str
v5: str
v6: str
v7: str
def v8(self, v9: str) -> v0:
self.auth_type = v9
return self
def v10(self, v11: str) -> v0:
self.country = v11
r... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[None, str, List[str], Dict[str, str]]
Output Type: Any
Dependencies:
```python
def v0(v1):
if v1 in datasets:
used_dataset_names.add(v1)
return datasets[v1]
(v2, v3) = _transcode_split(v1)
if v2 in datasets:
u... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
self._check_step_timestamp(v1)
self._available_power = self.calculate_available_power(timestamp=v1)
self._current_power = min(self._available_... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tensor
Output Type: Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tensor) -> Tensor:
v2 = v1 @ v1.t()
v3 = v2.diagonal().view(v1.size(0), 1)
return -2 * v2 + v3 + v3.t()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=0) -> Dict:
v2 = ['NextBus', 'NextBus2', 'NextBus3']
return self.payload[v2[v1]]
``` |
Imports:
```python
import sys
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2) -> list:
v3 = len(v1)
v4 = len(v2)
v5 = len(v1[0])
v6 = len(v2[0])
if v5 != v4:
print('Inner matrix size do not match... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self) -> None:
self._padding_char = ' '
self._horizontal_outside_border_char = '-'
self._horizontal_inside_border_char = '-'
self._vertical_outside_border_char = '|'
self._vertical_inside... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list[str], int, int, str, str, str, int, str, bool, int
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list[str], v2: int, v3: int, v4: str, v5: str='all_traffic', v6: str='TCP_ACCELERATED', v7: int=None, v8: s... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: np.ndarray
Dependencies:
```python
def v0(v1: np.ndarray, v2):
return np.ma.array(v1, mask=v2.mask).filled(999999)
```
Function Name: v3
Function:
```python
def v3(self, v4: np.ndarray) -> np.ndarray:
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray) -> Dict[str, Any]:
(v2, v3) = self.axes_bounds
return {'data': np.vstack((v1[::-1, :], v1)), 'x': self.... |
Imports:
```python
import pandas as pd
from pandas import DataFrame, Series
import typing
```
Type definitions:
Input Types: str
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> list:
v2 = pd.read_csv(self.raw_data_dir + v1, encoding='utf-8')
print(v2.columns)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[Tuple[int, int, int, int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[Tuple[int, int, int, int]]:
v1 = [(s.x, s.y, s.width, s.height) for v2 in self.conn.pseudoscreens]
if not v1:
v1.ap... |
Imports:
```python
import torch
from torch import Tensor
import torch.nn as nn
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: Tensor, Tensor, Tensor, Tensor, Tensor, Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tensor, v2: Tensor, v3: T... |
Imports:
```python
from qiskit import QuantumCircuit
from qiskit.circuit.library.standard_gates import RXGate, RYGate, RZGate
import typing
```
Type definitions:
Input Types: Any
Output Type: QuantumCircuit
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> QuantumCircuit:
self._check_feature... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes, Callable
Output Type: Tuple[str, Optional[str], str]
Dependencies:
```python
def v0(v1: bytes) -> Tuple[dict, dict, bool]:
try:
v2 = JweEnvelope.from_json(v1)
except ValidationError:
raise ValueError('Invalid packed mess... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
v1 = -1
v2: RType = void_rtype
v3 = False
@property
def v4(self) -> bool:
return isinstance(self.type, RVoid)
```
Input Types:
Output Type: List[v0]
Dependencies:
Function Name: v5
Function:
```python
def v5(self) ... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: pd.DataFrame, pd.DataFrame
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame, v2: pd.DataFrame) -> pd.DataFrame:
v3 = pd.merge(v2, v1, on='order_id', how='left')
return v... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
v1 = {}
for v2 in self.default_options_list:
v1[v2] = getattr(self, v2)
return v1
``` |
Imports:
```python
import torch
from torch import Tensor
import typing
```
Type definitions:
Input Types: Tensor, Tensor
Output Type: Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tensor, v2: Tensor) -> Tensor:
v3 = len(v2)
v2 = v2 / v2.sum()
v1 = torch.nn.functional.pad(v1, [v3 //... |
Imports:
```python
import typing
```
Type definitions:
Input Types: object, Callable
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: object, v2: Callable):
if not hasattr(v2, self.DECORATORS_ATTR):
setattr(v2, self.DECORATORS_ATTR, [])
self._get_decorators(v2).app... |
Imports:
```python
import typing
```
Type definitions:
Input Types: model.ValueList, model.ValueList
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: model.ValueList, v2: model.ValueList):
for v3 in v2:
v4 = self._find_element_by_attribute(v3, v1, 'value', 'value_id', ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int):
v2 = {20: 'success', 30: 'mismatch word', 40: 'expired', 50: 'invalid token'}
return v2[v1]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> str:
(v3, v4, v5) = (len(v1) - 1, len(v2) - 1, 0)
v6 = []
while v3 >= 0 and v4 >= 0:
v7 = v5 + int(v1[v3]) + int(v2[v4... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self.waiting_deque.popleft()
v2 = self.pending_transactions[v1]
v3 = v2.get_connection()
if v3 is None:
self._remove_pending_tx(... |
Imports:
```python
from pandas.core.construction import extract_array
from pandas.core.reshape.merge import _MergeOperation
from pandas.api.types import is_datetime64_dtype, is_integer_dtype, is_float_dtype, is_string_dtype, is_extension_array_dtype, is_categorical_dtype
import pandas as pd
import numpy as np
import ty... |
Imports:
```python
from sqlite3 import Cursor
import sqlite3
import typing
```
Type definitions:
Input Types:
Output Type: Cursor
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Cursor:
v1 = sqlite3.connect(str(self.db_file), isolation_level=None)
return v1.cursor()
``` |
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, v3) in v1.iteritems():
print('{name}: "{value}"'.format(name=v2, value=v3[0]))
print('=+=============================... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict):
v1['x'].clear()
v1['y'].clear()
v1['width'].clear()
v1['height'].clear()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[str, Path], Union[str, Path], Union[str, Path], int, int, int, int, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[str, Path], v2: Union[str, Path], v3: Union[str, Path], *, v4: int=0, v5: int=0, v6: i... |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: nn.Module, torch.Tensor, torch.Tensor, torch.Tensor
Output Type: Tuple[torch.Tensor, torch.Tensor]
Dependencies:
```python
def v0(v1: torch.Tensor):
(v2, v3, v4, v5) = v1.shape
... |
Imports:
```python
import functools
import gc
import warnings
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0() -> None:
with warnings.catch_warnings(record=True):
gc.collect()
v1 = [a for v2 in gc.get_objects() if isin... |
Imports:
```python
import os
from pathlib import Path
import typing
```
Type definitions:
Input Types:
Output Type: set()
Dependencies:
Function Name: v0
Function:
```python
def v0() -> set():
v1 = list(Path('./scowl-2019.10.06/').rglob('*'))
v2 = [_ for v3 in v1 if os.path.isfile(v3)]
v4 = 0
v5 = se... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: psycopg.Cursor[v0], str, Sequence[Sequence[Any]], int, str, Any, bool
Output Type: list[v0] | None
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: psycopg.Cursor[v0], v3: str, v4: Sequence[Sequence[Any]],... |
Imports:
```python
import typing
```
Type definitions:
Input Types: et._Element, str
Output Type: Any
Dependencies:
```python
def v0(v1: et._Element):
if not v1.text and v1.getchildren():
if v1.getchildren()[0].text:
return v1.getchildren()[0].text
elif v1.text and (not v1.getchildren()):
... |
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: Any) -> Dict[str, Any]:
v3 = self.get_url('circuit')
v4 = {'name': v1, 'params': v2}
return self.session.post(v3, json=v4).jso... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: pathlib.Path
Output Type: None
Dependencies:
```python
def v0(v1: Path):
raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), str(v1))
```
Function Name: v2
Function:
```python
def v2(v3: pathlib.Path) -> None:
if not v3.... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> list:
v1 = self[:]
v2 = len(v1)
v3 = [0] * v2
for v4 in range(1, v2):
for v5 in range(v4):
if v1[v5] > v1[v4]:
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: List[Dict[str, np.ndarray]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray) -> List[Dict[str, np.ndarray]]:
v2 = self.hp_ranges_for_prediction()
v3 = [v2.from_ndarray... |
Imports:
```python
import itertools
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
for v1 in itertools.product(range(self.n_rows * 2 - 1), range(self.n_columns * 2 - 1)):
if not v1[0] % 2 and (not v1[1] % 2):
... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
```python
def v0() -> str:
return os.path.abspath(os.path.join(HOME_PATH, 'stnm.conf'))
```
Function Name: v1
Function:
```python
def v1() -> str:
with open(v0(), 'r') as v2:
v3 = v2.read()
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Iterator[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> Iterator[int]:
for v2 in v1.split(':'):
yield int(v2, 16)
``` |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: Optional[str], list, Optional[bytes], Optional[dict]
Output Type: Tuple[int, bytes, bytes]
Dependencies:
```python
def v0(v1: list, v2: bytes=None, v3: Optional[dict]=None) -> Tuple[int, bytes, bytes]:
v4 = subprocess.Popen(v1, s... |
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 = list(v1)
if v3[v2] == '0':
v3[v2] = '9'
else:
v3[v2] = str(int(v3[v2]) - 1)
v4 = ''.join(v3)
... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: Any, str, str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Any, v2: str, v3: str, v4: str):
with open(f'{v3}/{v4}/{v2}.json', 'w') as v5:
json.dump(v1, v5, ensure_ascii=False, indent=' ... |
Imports:
```python
import sys
import typing
```
Type definitions:
Input Types: Optional[Tuple[str]]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Optional[Tuple[str]]=None) -> str:
if v1 is None:
v1 = sys.version_info
return f'{v1[0]}.{v1[1]}'
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.exc:
raise self.exc[0].with_traceback(self.exc[1])
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool, float, bool
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool, v2: float, v3: bool) -> bool:
if v1 and v3:
return True
elif v1 != v3:
return 0 < v2 < self.config.getfloat('RA.Sub... |
Imports:
```python
import cv2
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:
if np.count_nonzero(v1) != 0:
v1 = self._norm_min... |
Imports:
```python
import math
import typing
```
Type definitions:
Input Types: float, float, float
Output Type: 'Spherical'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float, v2: float, v3: float) -> 'Spherical':
self.radius = math.sqrt(v1 ** 2 + v2 ** 2 + v3 ** 2)
if self.radius == ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self._hide_button.label == '+':
self._hide_button.label = 'β'
self.widget.children[1] = self._expanded_widget
else:
self._... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame, float
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame, v2: float) -> pd.DataFrame:
v3 = v1.corr()
v4 = v3[((v3 >= v2) | (v3 <= -v2)) & (v3 != 1.0)]
return v4
``` |
Imports:
```python
from collections import OrderedDict
import collections
import typing
```
Type definitions:
Input Types: NamedTuple, torch.Tensor, torch.Tensor, List[int]
Output Type: NamedTuple
Dependencies:
```python
def v0(v1: torch.Tensor) -> List[float]:
return v1.detach().cpu().tolist()
```
Function Name: ... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v1 = re.sub('<\\s*[/]*\\s*\\s*for[ei][ei]g[nh]\\s*\\w*>', '', v1)
v2 = re.findall('<lname>\\([^<]*\\)<\\/lname>', v1)
if len(v2) > 0:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[str]:
v1 = []
if self.name == 'Vilros':
for v2 in self.models:
v1.append(self.urls[0].replace('REPLACE_ME', str(v2)))
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
if '&' not in v1 and '<' not in v1:
return v1
return v1.replace('&', '&').replace('<', '<')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: Tuple[str, List[Any]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2) -> Tuple[str, List[Any]]:
(v3, v4) = super().as_sql(v1, v2)
v5 = v1.quote_name_unless_alias
v6 = ' AND '.join(['{}.{} = %... |
Imports:
```python
import sys
from pathlib import Path
import json
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
```python
def v0() -> Path:
v1 = Path.home() / '.amptoolstools'
if v1.exists():
with open(v1, 'r') as v2:
v3 = json.load(v2)
v4 = v3['... |
Imports:
```python
import json
import os
import shutil
import typing
```
Type definitions:
Input Types: dict, str
Output Type: None
Dependencies:
```python
def v0(v1: dict, v2: str) -> None:
with open(v2, 'w') as v3:
v4 = {'data': {}, 'major_revisions': []}
for v5 in v1:
v6 = v1[v5]
... |
Imports:
```python
import os
import csv
import typing
```
Type definitions:
Input Types: str
Output Type: List[Dict]
Dependencies:
```python
def v0(v1):
for v2 in v1:
for (v3, v4) in v2.items():
if v4 == 'False':
v2[v3] = False
if v4 == 'True':
v2[v3]... |
Imports:
```python
from datetime import datetime, timedelta, date, time
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> int:
v2 = datetime.strptime(v1, '%M:%S')
return v2.second + v2.minute * 60 + v2.hour * 3600... |
Imports:
```python
import sys
import typing
```
Type definitions:
Input Types: str, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int) -> int:
v3 = (v1, v2)
v4 = hash(v3) + sys.maxsize + 1
self._hash_map[v4] = v3
return v4
``` |
Imports:
```python
import copy
import typing
```
Type definitions:
Input Types: List[ast.AST], str, int, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[ast.AST], v2: str, v3: int, v4=True, v5=None):
v6 = self.last_state
self.last_state = None
v7 = self.... |
Imports:
```python
from pandas._config import get_option
from pandas._libs import lib, properties, reshape, tslibs
from pandas._libs.lib import no_default
from pandas._typing import AggFuncType, ArrayLike, Axis, Dtype, DtypeObj, FrameOrSeriesUnion, IndexKeyFunc, NpDtype, SingleManager, StorageOptions, ValueKeyFunc
from... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
v2 = os.path.join(self.build_dir.tools, '{}-{}'.format(self.key, self.target))
v3 = os.path.join(v2, v1)
if os.path.exists(v3... |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.utils
import torch.nn.functional as F
from torch.nn.utils.rnn import pad_packed_sequence, pack_padded_sequence
import typing
```
Type definitions:
Input Types: List[List[str]], List[List[str]]
Output Type: torch.Tensor
Dependencies:
Function Name: ... |
Imports:
```python
from requests import Response, codes
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list):
self._require_auth()
self.http_patch(self._url_for('/v1/api/namespaces'), json=v1, expected_status_codes=(c... |
Imports:
```python
from os import path
import json
import typing
```
Type definitions:
Input Types: str
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> dict:
v2 = open(v1, encoding='utf-8')
return json.load(v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Dict[str, float]'
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: 'Dict[str, float]') -> float:
if v1:
v2 = sum(v1.values()) / len(v1)
else:
v2 = 1
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if type(self.parameter_expressions) == list:
self.__unpack_parameter_expression_list()
else:
self.__request_api_and_emit(self.paramet... |
Imports:
```python
import numpy as np
import torch
import torch.nn as nn
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2) -> float:
if type(v1) is np.ndarray:
v1 = torch.from_numpy(v1).to(self.device)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Simplygon.spObject, float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Simplygon.spObject, v2: float):
print('Progress: %f' % v2)
return True
``` |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, int
Output Type: Tuple[List[Dict], bool, bool]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int) -> Tuple[List[Dict], bool, bool]:
v3 = True
v4 = self.buildURL(v1, v2)
v5 = self.session.get(... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = 0
while not self.inbox.empty() and v1 < self.max_reactions:
v1 += 1
v2 = self.inbox.get_nowait()
if v2 is not None:
... |
Imports:
```python
import pandas as pd
import numpy as np
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: np.array
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2=None) -> np.array:
v3 = pd.read_csv(v1, nrows=v2)
v4 = np.array(v3, dtype=np.float32)
return (v4[:, 0]... |
Imports:
```python
import csv
import typing
```
Type definitions:
Input Types: TextIO
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: TextIO):
v2 = list(csv.reader(v1))
v3 = next((i for (v4, v5) in enumerate(v2) if v5[0] == '[Data]'))
v6 = list(map(str.lower, v2[v3 + 1]))
... |
Imports:
```python
import sys
from pathlib import Path
import typing
```
Type definitions:
Input Types: pytest.CaptureFixture[str], str
Output Type: None
Dependencies:
```python
def v0(v1: str, v2: ColumnSettings) -> None:
v3 = v1.replace('=', '').split('\n\n')
v4 = v3[0].strip()
v5 = v4.find(HEADER_TITLES... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Iterable
Output Type: Tuple[Any, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Iterable) -> Tuple[Any, Any]:
if not isinstance(v1, (str, list, tuple)):
v1 = list(v1)
if len(v1) == 0:
return (None, None)
... |
Imports:
```python
import os, json
from scipy.io import loadmat
import typing
```
Type definitions:
Input Types: Union[int, str], str, bool
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[int, str], v2: str='mV', v3: bool=True) -> np.ndarray:
v4 = os.path.join(se... |
Imports:
```python
import asyncio
import typing
```
Type definitions:
Input Types: bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True) -> None:
self.print_to_console = v1
self.loop.run_until_complete(self._connect(pipeline_start=False))
asyncio.ensure_fut... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[str]]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[List[str]]) -> int:
v2 = 0
v3 = [[0 for v4 in range(len(v1[0]))] for v4 in range(len(v1))]
for (v5, v6) in enumerate(v1):
for (v7... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: list, Any
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list, v2=False) -> np.ndarray:
if type(v1) is str or type(v1) is np.str_:
v1 = [c for v3 in v1]
if v2:
r... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Tuple[dict, dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict) -> Tuple[dict, dict]:
v1 = v1 or {}
v2 = {}
v3 = {}
for (v4, v5) in v1.items():
if v5 is None:
raise Va... |
Imports:
```python
import numpy
from PIL import Image, ImageChops, ImageDraw, ImageOps
import typing
```
Type definitions:
Input Types: Any, list, list, int
Output Type: Any
Dependencies:
```python
def v0(v1, v2):
v3 = []
for (v4, v5) in zip(v1, v2):
v3.append([v5[0], v5[1], 1, 0, 0, 0, -v4[0] * v5[0],... |
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.video_player.max > self.video_player.value:
self.video_player.value += 1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: tf.Tensor, int, str
Output Type: tf.Tensor
Dependencies:
```python
def v0(v1: tf.Tensor, v2: int, v3: str) -> tf.Tensor:
v4 = conv_block(v1, filters=64, name=f'{v3}_1')
v4 = conv_block(v4, filters=128, name=f'{v3}_2')
v4 = conv_block(v4, f... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Optional[str]:
if not self._generated_csv:
return None
self._scp_filename('results_summary.csv')
return 'results_summary.csv'
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: List[List[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> List[List[int]]:
v2 = [[1] * (i + 1) for v3 in range(v1)]
for v4 in range(v1 - 1):
for v5 in range(v4):
v2[v4 + ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bytes:
v1 = f'"NAK"0000L0R0A0[]{self._get_timestamp()}'
return self._frame_response(v1, self.is_binary_crc)
``` |
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