text stringlengths 190 325k |
|---|
Imports:
```python
import argparse
import typing
```
Type definitions:
Input Types:
Output Type: argparse.ArgumentParser
Dependencies:
Function Name: v0
Function:
```python
def v0() -> argparse.ArgumentParser:
v1 = argparse.ArgumentParser(prog='dbt-package-manager')
v1.add_argument('--repo-type', required=Tr... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str='', v3=None):
if not v2.startswith('.'):
v2 = '.' + v2
v4 = list()
for (v5, v6, v7) in os.walk(v1, followlinks=Tr... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass
class v0:
v1: bool
v2: Predicate
```
```python
v3 = Union[Variable, Function]
```
Input Types: v0
Output Type: str
Dependencies:
```python
def v4(v5: v3) -> str:
if isinstance(v5, Function):
v6 = [v4(argument) for v7 in v5.a... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[int]]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[List[int]]) -> bool:
v2 = len(v1)
v3 = len(v1[0])
for v4 in range(v2):
v5 = v1[v4][0]
for (v6, v7) in zip(range(v4, v2),... |
Imports:
```python
from matplotlib import rcParams
from matplotlib.pyplot import errorbar, fill_between, plot
from numpy import array, ndarray
from numpy.typing import ArrayLike
import typing
```
Type definitions:
```python
v0 = v1 = v2 = Any
```
```python
v0 = v1 = v2 = Any
```
Input Types: ArrayLike, ArrayLike, bool,... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int]
Output Type: List[List[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int]) -> List[List[int]]:
if len(v1) == 0:
return [[]]
else:
v2 = self.subsets(v1[:-1])
return v2 + [it +... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, float
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: float) -> np.ndarray:
v3 = np.zeros(v1.shape)
v3[1] = np.mod(v1[1] + v2 * np.sin(v1[0]), 2 * np.... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: str
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> torch.Tensor:
assert v1 in self.variables
v2 = getattr(self, v1)
v3 = getattr(self, f'{v1}_fixed')
v4 = getattr(se... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> List[int]:
if not v1:
return list()
return [int(x) for v2 in v1.rstrip(',').split(',')]
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
```python
v0 = Union[str, np.ndarray]
```
Input Types: v0, Any, Any, Any
Output Type: Any
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: v0, v3, v4, v5):
self.init_norms()
v6 = self._lookup_if_needed(v2)
v7 = v4... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict[str, Any]:
v1: Dict[str, Any] = {'transactions': [], 'elements': [], 'aggregate': self.aggregate.serialize().hex().upper()}
for v2 in self.p... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Callable, str, session.Session, int, Optional[int]
Output Type: List[Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Callable, v2: str, v3: session.Session, v4: int=200, v5: Optional[int]=None, **v6: Any) -> List[Any]:
v7: Lis... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.__dictionary.setup_corpus()
self.__dictionary.index()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int], List[float]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int], v2: List[float]):
v3 = [abs(float(p)) + self.epsilon for v4 in v2]
for (v5, v6) in zip(v1, v3):
self.memory[v5] = ... |
Imports:
```python
import copy
import typing
```
Type definitions:
Input Types: Any, Any, int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3: int) -> None:
self.agents.append(v2)
for v4 in range(v3 - 1):
v5 = copy.deepcopy(v2)
self.agents.append(v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
v1 = self.validate_username(v1)
v2 = self.connection.request('GET', self.admin_patterns(f'/users/{v1}/admin', 1))
return v2.json()['a... |
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=False):
v3 = '[LOG]'
self._process(v1, symbol=v3, nl=v2)
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any, Any, np.ndarray, np.ndarray, np.ndarray, Any, Any, Any, float, float
Output Type: Tuple[Tuple[float], Tuple[float], Tuple[float]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3: np.ndarray, v4: np.ndarra... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = v1.split(' ')
v1 = [word.strip().title() for v3 in v2 if v3 != '']
return ' '.join(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[str, List[str]]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[str, List[str]]=None):
if v1 is None:
v2 = list(self.by_name)
elif isinstance(v1, str):
v2 = [v1]
else:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> bool:
if v1 is None:
return False
return v1.startswith('/')
``` |
Imports:
```python
import ast
import inspect
import typing
```
Type definitions:
Input Types: inspect.Signature
Output Type: ast.arguments
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: inspect.Signature) -> ast.arguments:
v2 = []
v3 = []
v4 = None
v5 = []
v6 = None
for v7 in v... |
Imports:
```python
import torch
from torch import nn
from torch.nn import functional as F
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, torch.Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: torch.Tensor, v3: torch.Tensor):
... |
Imports:
```python
import math
import typing
```
Type definitions:
Input Types: [], Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: [], v2):
v3 = 0
v4 = len(v1) - 1
while v3 <= v4:
v5 = math.ceil((v3 + v4) / 2)
if v1[v5] == v2:
return v5
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, int
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: int) -> np.ndarray:
if v1.ndim == 1:
(v3,) = v1.shape
v4 = 1
else:
(v3, v4) = v1... |
Imports:
```python
import typing, datetime, asyncio
import typing
```
Type definitions:
Input Types: str, typing.Callable
Output Type: typing.List[typing.Any]
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: str, v2: typing.Callable=None) -> typing.List[typing.Any]:
v3 = []
v4 = date... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, t.Type, t.Any
Output Type: t.Any
Dependencies:
```python
def v0(v1: str) -> bool:
return v1.lower() in ('yes', 'true', 't', '1')
```
Function Name: v2
Function:
```python
def v2(self, v3: str, v4: str, v5: t.Type, v6: t.Any) -> t.Any:
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(ABC):
def __init__(self, v1: Optional[Text]=None, v2: Optional[List[Text]]=None, v3: Optional[TensorNetwork]=None, v4: Optional[BaseBackend]=None, v5: Optional[Tuple[int]]=None) -> None:
"""Create a node for the TensorNetwork. Should... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict=None):
v2 = self._note_store_call('listNotebooks')
v2 = [{'guid': nb.guid, 'name': nb.name} for v3 in v2]
if not v1:
return v2
ret... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.epsilon *= self.epsilon_decay
if self.minimum_epsilon is not None:
self.epsilon = max(self.epsilon, self.minimum_epsilon)
``` |
Imports:
```python
from datetime import datetime
from os.path import abspath
from os.path import expanduser
from os.path import exists
import typing
```
Type definitions:
Input Types: Event
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Event) -> None:
v2 = abspath(expandus... |
Imports:
```python
import ast
import typing
```
Type definitions:
Input Types: ast.Name
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: ast.Name):
v2 = self.symtable
v3 = v1.id
if isinstance(v1.ctx, ast.Store):
v2.entered.add(v3)
elif isinstance(v1.ctx, as... |
Imports:
```python
import os
from pathlib import Path
import typing
```
Type definitions:
Input Types: pd.DataFrame, str, str, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame, v2: str, v3: str=None, v4: bool=True):
v5 = Path(v2)
if v3 is None:
v3 = ''
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, float, Any, Any, Any, Any
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: float, v3=1.0, v4=0.0, v5=1.0, v6=0.0) -> float:
v7 = (v2 - v4) / v3
v8 = 0.0
if v7 >= 0.5 and v7 <= 1:
v8 = v1(v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, float
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=0, v2: float=0.01) -> bool:
self.command_return_error = ''
self.command = 'F072#2#' + str(v1) + '#' + str(v2) + '#'
(v3, v4) = self.send... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Prensor'
Output Type: List[tf.Tensor]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Prensor') -> List[tf.Tensor]:
v2 = []
self._append_to_components(v1, v2)
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'BinaryIO', 'Instance'
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'BinaryIO', v2: 'Instance') -> None:
self.write_header(v1, 1, 1, 1, 0)
self.write_instance(v1, v2)
while len(self._object_cache)... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(BaseModel):
v1 = ForeignKeyField(Player)
v2 = ForeignKeyField(Chart)
v3 = DoubleField()
v4 = IntegerField()
v5 = CharField()
v6 = CharField()
```
Input Types: v0
Output Type: Any
Dependencies:
Function Name: v7
Function:
... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: Any, Any, Any, Optional[str]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1=1, v2=0, v3='stdout', v4: Optional[str]=None) -> str:
v4 = v4 if v4 else os.getcwd()
return f'{v4}/job-{v1}/{v2}.{v3}'
``` |
Imports:
```python
import requests, bs4, datetime
import typing
```
Type definitions:
Input Types: datetime.time
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: datetime.time) -> bool:
v2 = datetime.datetime.now().time()
if v2 < v1:
print(f"RuntimeError: can't run unti... |
Imports:
```python
import shutil
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
try:
shutil.rmtree(path='{}'.format(self.old_repo), ignore_errors=False)
shutil.rmtree(path='{}'.format(self.new_repo), ign... |
Imports:
```python
import re
from pathlib import Path
import typing
```
Type definitions:
Input Types: Any, Any, Any, Any, Any, Any
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2='', v3='', v4=True, v5=False, v6=DATE_FMT) -> List[str]:
v7 = Path(v1)
if not v7.is_dir()... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: str, v2: str):
await self.configure_user()
await self.configure_profile(v1)
await self.configure_code(v1, v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict) -> Dict:
v2 = {'cls1': None, 'cls2': None, 'ent1': None, 'ent2': None}
if v1['n1'] == 'class' and v1['n2'] == 'class':
v2['cls1'] = v1['uri'][... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[str]], str
Output Type: bool
Dependencies:
```python
def v0(v1, v2, v3):
if v1 == len(word):
return True
if v2 < 0 or v2 >= rows or v3 < 0 or (v3 >= cols):
return False
if board[v2][v3] != word[v1]:
return... |
Imports:
```python
import typing
```
Type definitions:
Input Types: QtGui.QResizeEvent
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: QtGui.QResizeEvent) -> None:
self.detailsTab.setColumnWidth(0, int(self.detailsTab.width() / 9))
self.detailsTab.setColumnWidth(1, self.... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
v1 = {'title': '', 'description': '', 'termsOfService': '', 'contact': {}, 'license': {}, 'version': ''}
if self.contact:
v1['contact'] = sel... |
Imports:
```python
import torch
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2) -> torch.Tensor:
assert v1.shape[0] == v2.shape[0] and v1.shape[1] == v2.shape[1], (v1.shape,... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> np.ndarray:
v2 = self._transformer.transform(v1).to_numpy()
v3 = getattr(self._estimator, 'predict_proba', None)
if cal... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> None:
v2 = v1 - self._window_size + 1
while self._origin_ms < v2:
v3 = self._buckets[self._origin_index]
self._total.count -= v... |
Imports:
```python
import cffi
import typing
```
Type definitions:
```python
@unique
class v0(IntEnum):
v1 = -404
v2 = -203
v3 = -101
v4 = -18
v5 = -14
v6 = -10
v7 = -9
v8 = -8
v9 = -6
v10 = -5
v11 = -4
v12 = -3
v13 = -2
v14 = -1
v15 = 0
```
```python
class v1... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, float
Output Type: np.ndarray
Dependencies:
```python
def v0(v1: np.ndarray) -> np.ndarray:
v2 = np.arange(0.0, 255.0, 1.0)
v3 = np.zeros_like(v2)
v4 = np.transpose(np.where(v1 > 0))
v5 = [(abs(i - j), (i... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Callable[[], AsyncContextManager[AsyncSession]]
```
```python
class v1(BaseSettings):
v2: str
v3: str
v4: str
v5: int
v6: str
v7: int = 5
v8: int = 10
v9: int = 30
v10: int = -1
v11: bool = False
v12: str
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Any], 'Optional[Lintable]'
Output Type: Union[bool, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Any], v2: 'Optional[Lintable]'=None) -> Union[bool, str]:
if 'common' not in str(v2):
if 'ac... |
Imports:
```python
from random import randint
import typing
```
Type definitions:
Input Types: list['Ship']
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list['Ship']):
for v2 in range(self.aoe):
v1[randint(0, len(v1) - 1)].damages_ship(self)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[Text, Any], Union[Text, List[Text]]
Output Type: Text
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[Text, Any], v2: Union[Text, List[Text]]) -> Text:
if isinstance(v2, str):
v2 = [v2]
print(v2)
print(v1)... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
json.dump(self.list, self.path.open('w', encoding='utf-8'), indent=4, separators=(',', ': '), ensure_ascii=False)
return True
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, str
Output Type: Callable
Dependencies:
```python
def v0(v1):
if self.uselist:
self._registry.setdefault((target, qualifier), []).append(v1)
else:
assert (target, qualifier) not in self._registry
self._registry[tar... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Node'
Output Type: 'Node'
Dependencies:
```python
def v0(v1):
if not v1:
return None
v0(v1.left)
print(v1.val)
if not self.lastNode:
self.firstNode = v1
else:
self.lastNode.right = v1
v1.left = self... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
v2 = re.compile('^(.*)\\/\\/.*$|^(.*)$', re.MULTILINE)
v3 = [m.span(m.lastindex) for v4 in v2.finditer(v1)]
for (v5, v6) in v3:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, List[str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: List[str]) -> None:
with open(v1, encoding='utf8') as v3:
v2.extend(v3.read().splitlines())
``` |
Imports:
```python
from collections import defaultdict
import typing
```
Type definitions:
```python
class v0(wrapt.ObjectProxy):
v1: bool = False
def __init__(self, v2: sqlite3.Connection):
super(v0, self).__init__(v2)
if isinstance(v2, v0):
raise ValueError('Attempted to create `C... |
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 = {'id': f'{v1}', 'warns': v2}
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Dict[str, Any]]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Dict[str, Any]]):
global npcs
v2 = []
for v3 in v1:
v4 = npc_types[v3['classname']](0, 0, 0)
del v3['classname']
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.set_models(self.permission_test_model)
v1 = self.request('mediafile.update', {'id': 111, 'token': 'test'})
self.assert_status_code(v1, 400)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
v1 = {}
v1.update(self.x())
v1.update({'diff': self.y()})
return v1
``` |
Imports:
```python
from collections import deque
import typing
```
Type definitions:
Input Types: List[List[str]]
Output Type: int
Dependencies:
```python
def v0(v1, v2):
v3 = False
v4 = deque([(v1, v2)])
while v4:
(v5, v6) = v4.popleft()
v7 = 0 <= v5 < rows and 0 <= v6 < cols
v8 = ... |
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._client.measures.get_component_with_specified_measures(component=v1, metricKeys='ncloc')
v3 = v2['component']['measures']
return v3[... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2) -> dict:
v3 = None
for (v4, v5) in enumerate(v1):
if v4 == 0:
v3 = v2[v5]
else:
v3 = v3[v5]
v6 = {}
... |
Imports:
```python
import asyncio
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> None:
if self._pending is None:
return
v1 = []
for (v2, v3) in self._pending.items():
if not v3.done():
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: tanjun.context.AutocompleteContext, mock.Mock
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: tanjun.context.AutocompleteContext, v2: mock.Mock):
v3 = v1.get_channel()
assert v3 is v2.get_channel.return_v... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, Any, Any
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2, v3) -> np.ndarray:
(v4, v5) = v1.shape
(v6, v7) = v2
v8 = []
for v9 in range(0, v4 - v6 + 1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[Dataset], Optional[List[str]], str
Output Type: Dict[str, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[Dataset]=None, v2: Optional[List[str]]=None, v3: str='eval', **v4) -> Dict[str, float]:
v4 = v... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Optional[Dict[str, np.ndarray]]
Output Type: Tuple[np.ndarray, np.ndarray, np.ndarray]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[Dict[str, np.ndarray]]=None) -> Tuple[np.ndarray, np.ndarray, np.n... |
Imports:
```python
import typing
```
Type definitions:
Input Types: maxes.Axes, List[int], List[int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: maxes.Axes, v2: List[int], v3: List[int]):
for v4 in v3:
v1.axhspan(v4 - 0.5, v4 + 0.5, fill=None, hatch='\\\\\\', alpha=0.3)... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Generator[str, None, None]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str=string.ascii_lowercase) -> Generator[str, None, None]:
(v2, v3, v4) = (0, 0, '')
while True:
if v2 < len(v1):
y... |
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.mirrored_channels().get(v1, {})
return (v2.get('last_spoke', None), v2.get('last_spoke_timestamp', None))
``` |
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 self._unmask:
return v1
if v1 not in self._name_map:
self._name_map[v1] = '%d' % len(self._name_map)
return self._na... |
Imports:
```python
import requests
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = requests.get(v1)
v2.encoding = 'utf-8'
return v2.text
``` |
Imports:
```python
import torch
from torch import Tensor
from torch.nn.functional import grid_sample, conv2d, interpolate, pad as torch_pad
import typing
```
Type definitions:
Input Types: Tensor, List[float], List[float], bool
Output Type: Tensor
Dependencies:
```python
def v0(v1: Tensor) -> None:
if not _is_tens... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=False) -> int:
if v1:
return self.epoch
else:
return self.global_step
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Any:
if not self.isOpen():
raise Exception('cursor: Database not open')
if self.cursor_ is None:
if self.conn_ is None:
raise Ex... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float) -> None:
if v1 not in self.percentiles_requested:
self.percentiles_requested.append(v1)
self.percentiles_regenerated = False
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: float
Output Type: Union[int, None]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float) -> Union[int, None]:
if self.is_calibrated:
v2 = np.arange(self.n_channels)[np.logical_and(self.lower_bin_l... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: tuple[str, int, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> tuple[str, int, int]:
v2 = int(v1[:3], base=2)
v3 = int(v1[3:6], base=2)
return (v1[6:], v2, v3)
``` |
Imports:
```python
from inspect import Parameter, isclass, signature
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: Type[v0]
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: Type[v0]) -> v0:
if not isclass(v2):
self.fail(f'{v2} is not a ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
try:
self.throwsKeyboardInterrupt()
except KeyboardInterrupt:
self.fail('Unexpected KeyboardInterrupt')
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: Optional[Dict[str, Wikicode]]=None):
if v1 is None:
self._articles = {}
else:
self._articles = {_normalize_title(name): article for (v2, v3) in v1.items()}
def v4(self, v5:... |
Imports:
```python
import copy
import typing
```
Type definitions:
Input Types: set, set
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: set, v2: set):
v3 = copy.copy(v1)
v4 = set()
v5 = set()
v6 = set()
v7 = set()
v8 = False
while v3:
v9 = set()
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
while self._srl_count > 0:
self.srl_get()
``` |
Imports:
```python
from datetime import datetime
import typing
```
Type definitions:
Input Types: int, bool
Output Type: typing.NoReturn
Dependencies:
```python
def v0() -> float:
return datetime.now().timestamp()
```
Function Name: v1
Function:
```python
def v1(self, v2: int, v3: bool=False) -> typing.NoReturn:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> float:
if not self.stations:
return 0
v1 = self.stations[-1].get('counter')
if v1 is not None:
return v1
return self.lineLength()
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, float
Output Type: Dict[str, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=5, v2: float=0.5) -> Dict[str, str]:
v3 = '{}/jobs/{}/status/v/1'.format(self._websocket_url, self._job_id)
return self.stream(url... |
Imports:
```python
import curses
from curses import panel, ascii
from curses.textpad import Textbox
import typing
```
Type definitions:
Input Types: str, int, int, int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int=20, v3: int=0, v4: int=curses.COLOR_WHITE) -> None... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, str, list, str
Output Type: requests.models.Response
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: str, v3: list=[], v4: str=None) -> requests.models.Response:
v5 = 'v1/projects/{}/docs'.format(v1)
v6 = {'... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List, str
Output Type: List
Dependencies:
```python
def v0(v1: Dict) -> bool:
return is_dataset_file(v1['name']) or is_directory_entry(v1)
```
```python
def v2(v3: Dict) -> bool:
return 'directory' == v3['type']
```
```python
def v4(v5: Dict) ... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any, bool
Output Type: bool
Dependencies:
```python
def v0(v1: Any) -> Optional[bool]:
v2 = getattr(v1, '_apply_unitary_', None)
if v2 is None:
return None
v3 = qid_shape_protocol.qid_shape(v1, None)
if v3 is... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: Optional[str]
Dependencies:
```python
def v0(v1: str) -> str:
v2 = 'git@([^:]+):([^/]+)/(.+)'
v3 = re.search(v2, v1, re.IGNORECASE)
if v3:
return f'https://{v3.group(1)}/{v3.group(2)}/{v3.group(3)}'
r... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(NamedTuple):
v1: Optional['ANode']
v2: RC
v3: int = 0
v4: int = 0
@property
def v5(self) -> float:
return self.g + self.h
@classmethod
def v6(cls, v7: 'ANode', v8, *v9: RC):
v10 = cls.calc_g(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:
self.ERROR = True
self.errors.append(v1)
``` |
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