text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
Input Types: maze.Maze, vector.Vector
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: maze.Maze, v2: vector.Vector) -> None:
self.maze = v1
self.position = v2
self.reset()
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: list, str
Output Type: Any
Dependencies:
```python
def v0(v1: list, v2: int):
v1 = np.sort(v1)
v2 = v2 / 100
v3 = v2 * len(v1)
v4 = int(v3 // 1)
if v4 == len(v1):
return v1[-1]
return v1[v4]
```
```py... |
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:
v2 = self.tvwFieldMap.get_column(1).get_cells()[0]
v3 = v2.get_property('model')
v3.clear()
v3.append([''])
for (... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: int):
v3 = self._compute_loss(v1)
self.log('train_loss', v3, on_epoch=True, on_step=False, prog_bar=True)
return v3
``` |
Imports:
```python
import torch
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: torch.Tensor, str
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: str='mean') -> torch.Tensor:
v3 = F.relu(1 - v1)
if v2 == 'none':
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Union[None, bool]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool) -> Union[None, bool]:
if self.string is None:
return self.string
v2 = f'{self.string[0]}{self.string[-1]}'
if v1:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: int):
if not v1:
if v2 < 6:
return (None, *v0(v1, v2 + 1))
elif v2 < 5:
(v3, v4, v1) = v1.partition('/')
return (v3.strip(':/'), *v0(v1, v2 + ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str], float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[str], v2: float):
v3 = len(v1)
assert v3 % 2 == 1
v4 = v3 // 2
v5 = self._get_random_walk(v4, v3 // 2 + 1, 1 - v2)
v6 = se... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(abc.ABC):
@abc.abstractmethod
def v1(self, v2: str, v3: ExtensionContext) -> None:
...
```
```python
@dataclasses.dataclass(eq=False)
class v4(Type):
v5: t.Optional[str] = dataclasses.field(default=None, init=False)
v6: t... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> bool:
for v2 in v1:
try:
int(v2.text())
except ValueError:
return True
return False
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
for (v1, v2) in self.boards.items():
if not (v2 and v2.valid_board):
return False
self.turn = 1
return True
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int]
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int]) -> List[str]:
v2 = self._tokenizer.convert_ids_to_tokens(v1)
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
if not v1 in self._adjacency_sets:
v2 = f'Vertex with the name {v1} not found.'
raise ValueError(v2)
``` |
Imports:
```python
import argparse
import typing
```
Type definitions:
Input Types: argparse.Action
Output Type: Tuple[List[str], str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: argparse.Action) -> Tuple[List[str], str]:
v2 = (v1.help or '') % {'default': v1.default}
if not isinstance(v1, ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: callable
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> callable:
v2 = [_ for v3 in range(0, self.rowCount)]
for v4 in range(0, self.rowCount):
v2[v4] = self.getElement(v4, v1)
return... |
Imports:
```python
import torch
from torch.utils.data import Dataset
from torch import Tensor
import typing
```
Type definitions:
```python
v0 = TypeVar('T_idx')
```
Input Types: Sequence[v0], Sequence[v0], bool
Output Type: Tensor
Dependencies:
```python
def v1(v2):
if isinstance(v2, Tensor):
return v2.tol... |
Imports:
```python
import typing
```
Type definitions:
Input Types: typing.Optional[DatagramTransport]
Output Type: typing.Optional[socket.socket]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: typing.Optional[DatagramTransport]) -> typing.Optional[socket.socket]:
if v1 is None or not hasattr(v1, ... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = os.path.dirname(os.path.abspath(v1))
if not os.path.exists(v2):
raise NotADirectoryError(v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool, bool, bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True, v2: bool=False, v3: bool=False) -> None:
self.mission_watcher_thread.start()
self.robot_status_watcher_thread.start()
super... |
Imports:
```python
import numpy as np
import cv2
import typing
```
Type definitions:
Input Types: np.ndarray, Any
Output Type: np.ndarray
Dependencies:
```python
def v0(v1: np.ndarray, v2: Tuple[int, int, int]) -> np.ndarray:
if v2 == (0, 0, 0):
v1 = np.where(v1 == 0, 1, v1)
v2 = (1, 1, 1)
v3 =... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: typing.NoReturn
Dependencies:
```python
def v0(v1: int) -> int:
v1 -= v1 >> 1 & 6148914691236517205
v1 = (v1 & 3689348814741910323) + (v1 >> 2 & 3689348814741910323)
v1 = v1 + (v1 >> 4) & 1085102592571150095
v1 = v1 + (v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, int, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1=None, v2=None, v3: int=None, v4=False):
if v1 is None:
v1 = self.x_test
v2 = self.y_test
print('\n*** Evaluation')
ret... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.create_model('meeting/222', {'name': 'name_xQyvfmsS'})
self.create_model('motion_comment_section/111', {'name': 'name_srtgb123', 'meeting_id': 2... |
Imports:
```python
from sklearn.utils.class_weight import compute_class_weight
from sklearn import metrics as skmetrics
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray):
v2 = np.unique(v1)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True):
self._set_attrs(v1)
if self._args:
self._set_attrs_from_args()
self._set_override_attrs()
``` |
Imports:
```python
from datetime import datetime
import typing
```
Type definitions:
Input Types: str
Output Type: datetime
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> datetime:
v2 = len('2020-10-09T12:28:14.7710')
if len(v1) > v2:
v1 = v1[:v2]
return datetime.strptime(v... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(params.Params):
v1: str
v2: pd.Series
v3: pd.DataFrame
v4: pd.DataFrame
```
Input Types: v0
Output Type: None
Dependencies:
Function Name: v5
Function:
```python
def v5(self, *, v6: v0) -> None:
self.base_dir = v6['base_dir']... |
Imports:
```python
import copy
import typing
```
Type definitions:
Input Types: Dict[Text, Any]
Output Type: Dict[Text, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[Text, Any]) -> Dict[Text, float]:
v2 = {}
v1 = copy.deepcopy(v1)
v1.pop('file_name', None)
v3 = v1.pop('tas... |
Imports:
```python
import re
import collections.abc
from collections import defaultdict
import typing
```
Type definitions:
Input Types: List[str]
Output Type: Mapping[str, List[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[str]) -> Mapping[str, List[int]]:
if v1 is None:
retur... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True) -> None:
if v1 != self._classification:
self._classification = v1
self._update_activation()
``` |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
for v2 in self.filepath_stack:
if os.path.samefile(v1, v2):
return True
return False
``` |
Imports:
```python
import sys
import typing
```
Type definitions:
Input Types: List[List[int]]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[List[int]]) -> None:
v2 = len(v1)
v3 = len(v1[0])
v4 = sys.maxsize
for v5 in range(v2):
for v6 in range(v3)... |
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.layer[v1].append(v2)
self.index[self.layer[v1]] = v1
self.node_to_layer[v2] = v1
``` |
Imports:
```python
import matplotlib.pyplot as plt
import numpy as np
import typing
```
Type definitions:
Input Types: pd.DataFrame, str, Tuple[float, float], int
Output Type: plt.Axes
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame, v2: str, v3: Tuple[float, float]=None, v4: int=0) -> plt... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Parser'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Parser'):
self.skill = self.raw['skill']
self.id = self.raw['Id']
self.char = self.raw['charclass']
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
self.__maxes.append(max(v1, self.__maxes[len(self.__maxes) - 1]) if self.__maxes else v1)
self.__stack.append(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = typing.TypeVar('_ValueT')
```
Input Types: collections.Callable[[str], v0]
Output Type: collections.Callable[[str], v0]
Dependencies:
```python
def v1(v2: str, /) -> v0:
if v2.startswith('<') and v2.endswith('>'):
v2 = v2[1:-1]
return... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int, v3: int) -> None:
v4 = {'name': v1, 'stars': v2, 'contributors': v3}
self.stars_contributors_table.insert(v4)
``` |
Imports:
```python
import hashlib
import os
import typing
```
Type definitions:
Input Types: str, str
Output Type: typing.Tuple[str, str]
Dependencies:
```python
def v0(v1: str) -> str:
v2 = 64 * 1024
v3 = hashlib.md5()
with open(v1, 'rb') as v4:
while True:
v5 = v4.read(v2)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2=False) -> bool:
if v1 == '_' or v1.isalpha():
return True
return v1 in [':', '.'] or v1.isnumeric() if not v2 else False
``` |
Imports:
```python
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import scale
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.neighbors import KNeighborsClassifier
from sklearn.tree import DecisionTreeClassifier
from sklea... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, Namespace
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict, v2: Namespace):
self.assertEquals(v1['url'], v2.url)
self.assertEquals(v1['interval'], v2.interval)
self.assertEquals(v1['delimite... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int]) -> None:
self.resMap.clear()
v2 = v1[0]
v3 = v1[1]
v4 = self.set_pos_name(v2, v3)
if not self.cMap.get(v4):
self.c... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
try:
self.grid = self.initial_grid.copy()
except:
self.__create_initial_grid()
self.grid = self.initial_grid.copy()
self.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes
Output Type: Tuple[Optional[bytes], bool]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: bytes) -> Tuple[Optional[bytes], bool]:
if v1[0:1] == b'$':
(v2, v3) = v1[1:].rsplit(b'#', 1)
if len(v3) != 2:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Iterator[Dict[str, str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Iterator[Dict[str, str]]:
v1 = self._process_string(v1)
for (v2, v3) in self._phenos.items():
if v1 in v3['--spaced... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'RequestContext'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'RequestContext'=None):
v2 = self.obj_get_changes()
v3 = self.dbapi.update_availability_window(self.uuid, v2)
self._from_db_object(self... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, list, str
Output Type: Union[None, Tuple[str]]
Dependencies:
```python
def v0(v1: list) -> VARIANT:
return VARIANT(pythoncom.VT_VARIANT | pythoncom.VT_ARRAY, v1)
```
Function Name: v2
Function:
```python
def v2(self, v3: str, v4: list, v5: st... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Command'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Command'=None):
if v1 is None:
if self.parent is not None and self.name in self.parent.sub_cmds:
del self.parent.sub_cmds[self.na... |
Imports:
```python
import hmac
import json
from hashlib import sha256
import typing
```
Type definitions:
Input Types: str, dict, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str=None, v2: dict=None, v3: int=0) -> str:
v4 = v1.encode()
v5 = ''.join([json.dumps(v2), '1.0.... |
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, v3, v4) = (v1[0], v1[0], 0)
for v5 in v1:
if v5 < v3:
v4 += v3 - v2
v2 = v5
v3... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
v1 = max(0, min(v1, 10))
self.current_volume = v1
os.system(f'amixer sset "Master" {v1}0%')
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(object):
def __init__(self, v1=False, v2: int=0, v3: int=0, v4: int=0, v5: int=0) -> None:
self.invalidate = v1
self.num_in_vocab_tokens = v2
self.total_num_tokens = v3
self.sum_in_vocab_token_lengths = v4
... |
Imports:
```python
import os
from os import listdir
from os.path import join
import typing
```
Type definitions:
Input Types: str, str
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> list:
v3 = join(self.path, v1, v2)
if not os.path.exists(v3):
r... |
Imports:
```python
import os
import hashlib
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
for (v1, v2, v2) in os.walk(self.config_dict['general']['image_temp_dir']):
if v1.lower().endswith(eval(self.config_dict... |
Imports:
```python
import re
from sys import stderr
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
for [v1, v2] in self.api.items():
v1 = re.sub('Chromium(.*)', '\\1', v1)
v1 = re.sub('WebKit(.*)', '\\1'... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Tuple[np.ndarray, List[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray) -> Tuple[np.ndarray, List[int]]:
v2 = v1.shape[0]
v3 = np.eye(v2)
v4 = []
for (v5, v6) ... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(SQL):
def __init__(self: v0, v1: str, v2: str) -> None:
try:
super(SQL, self).__init__(database=v1, mode=v2)
except DatabaseDoesNotExistException as e:
raise e
def v3(self: v0, v4: str, **v5):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float, Tuple[Union[float, int]], Tuple[Union[float, int]]
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float, v2: Tuple[Union[float, int]], v3: Tuple[Union[float, int]]) -> float:
if v3[1] == v3[0]:
re... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
v1 = str(v1)
if v1 not in self._configs['roles']:
return None
self._configs['roles'][v1]['enabled'] = not self._configs['roles'][v1]['... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0() -> None:
v1 = 'This is a string'
v2 = 'This Is A String'
v3 = v2.title()
assert v3 == v2
``` |
Imports:
```python
import json as json_import
from os import getenv, environ, getcwd
from os.path import isfile, join, expanduser
import typing
```
Type definitions:
Input Types: str
Output Type: dict
Dependencies:
```python
def v0(v1: str, v2: str='=') -> dict:
v3 = 'ibm-credentials.env'
v4 = getenv('IBM_CRED... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
v2 = len(self.inputs_register.values())
v3 = 'x'
if not v1 in self.inputs_register:
self.inputs_register[v1] = ''.join([v3, str(v2 - 1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: tuple
Dependencies:
```python
def v0(v1: str, v2: tuple, v3: list) -> tuple:
v4 = []
while v3[v2[0]][v2[1]] != 0:
v4.append(v1[v2[0] - 1])
v2 = (v2[0] - 1, v2[1] - 1)
v4.reverse()
return (v4, v2)
`... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'str', Any, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'str', v2, v3=True, v4=None):
v5 = v1.split(',')
v6 = self.websocket_request_impl.request_24h_trade_statistics_event(v5, v2, v3, v4)
... |
Imports:
```python
import glob
import os
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
if not os.path.exists(v1):
os.makedirs(v1)
else:
v2 = v1 + '/*'
v3 = glob.glob(v2)
for v4 in v3:
... |
Imports:
```python
from os import makedirs, path
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
makedirs(v1, exist_ok=True)
self.bus_lines.to_csv(path.join(v1, 'bus_lines.csv.xz'), index=False)
self.bus_line_... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> np.ndarray:
(v2, v2, v3) = v1.shape
v4 = self._classification_point_dictionary.get(v3, -1)
if v4 == -1:
raise ValueError(f'Input s... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Tuple[str, str, int]
```
Input Types: Sequence[v0], str
Output Type: str
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: Sequence[v0], v3: str) -> str:
for v4 in v2:
v5 = v4[0]
if v3 == v5:
return v4[1]... |
Imports:
```python
import os
import re
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
for v2 in open(v1):
v2 = v2.strip()
v2 = re.sub('(\\A|\\s+)#.*', '', v2)
if not v2:
c... |
Imports:
```python
import typing
```
Type definitions:
Input Types: requests.Response, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: requests.Response, v2: str) -> bool:
self._validate_response(v1)
v3 = [header.lower() for v4 in v1.headers.keys()]
return v2.low... |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types: subprocess.CompletedProcess, dashboard_api.DashboardAPI, str, str
Output Type: None
Dependencies:
```python
def v0(v1: str, v2: subprocess.CompletedProcess) -> str:
v3 = v2.args
if isinstance(v3, list):
v3 = utils.list_t... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(events.ParseEvent):
pass
```
Input Types: v0
Output Type: Iterator[dict]
Dependencies:
```python
def v1(v2):
if v2 is None:
v2 = []
if not isinstance(v2, list):
v2 = [v2]
return v2
```
```python
def v3(v4, v5, v6=N... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: typing.NoReturn
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> typing.NoReturn:
v1 = self.__a
(v2, v3) = (self.__n, self.__h)
v4 = [-1] * v2
for v5 in range(v2):
v6 = 0
for v7 in rang... |
Imports:
```python
import hmac
import hashlib
import typing
```
Type definitions:
Input Types: List[bytes], str
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[bytes], v2: str) -> bytes:
v3 = hmac.new(v2.encode('ascii'), digestmod=hashlib.sha256)
v4 = v3.copy()
for v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list) -> str:
v2 = ''
for v3 in v1:
v4 = ''
for v5 in v3['tasks']:
v4 += '🟢' if v5['ball']['is_new_bigger'] else '🔴'
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int, v3=None, v4=False):
try:
v5 = v1.to_bytes(1, 'big') + v2.to_bytes(1, 'big')
if v3:
v5 += v3
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
```python
def v0(v1, v2: list):
v3 = ['source', 'resolution']
return v2 if v1 in v3 else v2.pop()
```
Function Name: v4
Function:
```python
def v4(v5: dict):
v6 = v5.to_dict(flat=False)
return {k: v0... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[List[str], str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[List[str], str]) -> None:
if isinstance(v1, str):
self.remove_word(v1)
elif isinstance(v1, list):
for v2 in v1:... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> None:
await self.create_connection(with_db=False)
await self.execute_script('CREATE DATABASE "{}" OWNER "{}"'.format(self.database, self.user))
a... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Tuple[str, int]]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[Tuple[str, int]]):
for v2 in v1:
self._generate_dummy_text_files_in_container_dir(v2[0], v2[1])
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: list[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> list[str]:
v1 = []
while self._at_flag():
v2 = self._unconsumed_args.pop()
v1.append(v2)
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Any) -> bool:
v2 = v1
try:
v3 = iter(v1)
except TypeError:
return False
else:
return v2 is v3
``` |
Imports:
```python
from functools import reduce
from sklearn.svm import SVC, SVR
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.tree import DecisionTreeClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.ensemble import BaggingClassifier, ... |
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._percent == 100:
return self.data.model_scores[v1][self._metric]
else:
v2 = 0
v3 = self.data.scored_predictions[v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Optional[str]:
if self.conn_id:
v1 = self.get_connection(self.conn_id)
v2 = v1.extra_dejson
v3 = v2.get('extra__kubernetes__na... |
Imports:
```python
import logging as log
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = self._dict.get('donations_fiat_currency', 'usd').strip().casefold()
if v1 not in self.supported_fiats():
log.error(f... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: Tuple[np.ndarray, np.ndarray]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Tuple[np.ndarray, np.ndarray]:
import numpy as np
v1 = np.arange(self.num_examples())
np.random.shuffle(v1)... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, tp.Optional[tp.Iterable[tp.Hashable]], bool, dict
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, *v5, v1: int=None, v2: tp.Optional[tp.Iterable[tp.Hashable]]=None, v3: bool=False, v4: dict=None, **v6) -> None:... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str, *v2, **v3):
super(v0, self).__init__(*v2, **v3)
self._name = v1
@property
def v4(self):
"""Node name - must not be changed once node is in graph"""
return self._name
... |
Imports:
```python
from itertools import chain
import pandas as pd
import typing
```
Type definitions:
Input Types: str, bool
Output Type: pd.DataFrame
Dependencies:
```python
def v0(v1: Union[pd.Series, pd.DataFrame]) -> pd.DataFrame:
if isinstance(v1, pd.Series):
return v1.to_frame()
else:
re... |
Imports:
```python
import pickle
import typing
```
Type definitions:
Input Types: pd.DataFrame, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame, v2: str):
with open(v2, 'rb') as v3:
v4 = pickle.load(v3)
v1 = v1.values
v1 = v1[:, 6:]
v5 = v4.pred... |
Imports:
```python
import tempfile
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
with tempfile.NamedTemporaryFile(suffix='.dot', delete=False) as v2:
v2.write(v1.encode())
v3 = v2.name
retur... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.cuda.FloatTensor, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.cuda.FloatTensor, v2=None):
if not v2:
v2 = {}
(v3, v4) = self._break_up_pc(v1)
(v5, v6, v7) = self.sa1(v3, v4... |
Imports:
```python
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
import numpy as np
import typing
```
Type definitions:
Input Types: Any, dict
Output Type: Any
Dependencies:
```python
def v0(v1: Sequential, v2: int, v3: str, v4: float... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
if self._buildplate != v1:
self._buildplate = v1
self._active_printer_configuration.buildplateConfiguration = self._buildplat... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
v2 = self.choice_task()
print('Agent#{} next task:{}'.format(v1, v2['s']))
for v3 in range(len(v2['s'])):
v4 = self.agent_last_point[v... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: pd.DataFrame, dict, Any
Output Type: Any
Dependencies:
```python
def v0(v1, v2=None):
if v2:
if not isinstance(v2, dict):
v2 = v2._asdict()
if isinstance(v1, str):
if v1.isnumeric():
return int... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str):
v3 = '[АаБбВвГгДдЕеЁёЖжЗзИиЙйКкЛлМмНнОоПпРрСсТтУуФфХхЦцЧчШшЩщЪъЫыЬьЭэЮюЯя-]+'
v4 = '(\\.|^|<|"|\\\'|\\(|\\[|\\{)\\s*' + v3
w... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: torch.Tensor):
for v3 in range(len(self.metrics)):
if self._device != v1.device:
self.__to(v1.d... |
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