text stringlengths 190 325k |
|---|
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:
v2 = re.match('^[\\u30A0-\\u30FF]*$', v1)
return v2 is True
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, sqlalchemy.engine.Engine
Output Type: Optional[sqlalchemy.Table]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str='public', v3: sqlalchemy.engine.Engine=None) -> Optional[sqlalchemy.Table]:
self.log.info... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes):
self.bus.write_byte_data(self.sensor, self.ACCESS_CONFIG, v1)
self.wait_NVM()
return
``` |
Imports:
```python
import torch
from torch.testing._internal.jit_utils import JitTestCase, make_global
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: torch.Tensor) -> torch.Tensor:
... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: Type[v0], Any, Any
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: Type[v0], v3=None, v4=None) -> v0:
if v3 is not None:
v4 = self.element_factory.create(v3)
v5: v0 =... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str='', v3: bool=False) -> None:
v4 = {'datasetName': v1, 'alias': v2, 'isPublic': v3}
self._client.open_api_do('POST', f'searchRes... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: int
Output Type: tf.keras.Model
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int=7) -> tf.keras.Model:
v2 = getattr(tf.keras.applications.efficientnet, f'EfficientNetB{v1}')
v3 = v2(include_top=False,... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Tuple[str, Sequence[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Tuple[str, Sequence[int]]:
assert self._bip32_xpub is not None and self._derivation_path is not None
return (self._bip32_xpub, self._d... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: dict) -> None:
v2 = 'An unexpected error occurred'
v3 = 'You can report this issue together with the traceback below on GitHub. Please restart M... |
Imports:
```python
import os
import webbrowser
import typing
```
Type definitions:
Input Types: str, str, int, str, list
Output Type: None
Dependencies:
```python
def v0(v1: str='', v2: str='pyproject.toml', v3: list=None, v4: str='site') -> dict:
v5: Dict[str, Union[str, list]] = {}
if v3:
v5['modules... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: 'VideoReader'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float) -> 'VideoReader':
self._c.seek(v1)
return self
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.set_high_score()
self.__init__()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: pyramid.request.Request, pyramid.response.Response
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pyramid.request.Request, v2: pyramid.response.Response=None) -> None:
if v2 is None:
v2 = v1.response
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
v1 = self.tail.prev.key
self.tail.prev.prev.next = self.tail
self.tail.prev = self.tail.prev.prev
return v1
``` |
Imports:
```python
from nltk.corpus import stopwords
import nltk
import typing
```
Type definitions:
Input Types: pd.Series, str
Output Type: pd.Series
Dependencies:
```python
def v0(v1: str, v2: str):
v3 = set(' '.join(v2.split('\n')))
v1 = ' '.join([word for v4 in v1.split() if v4 not in v3])
return v1
`... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any, Any, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3: int=256):
v4 = 0
v5 = None
v6 = [0]
for v7 in v2:
if v5 is not None:
v4 = v4 + np.linalg.norm... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any, Any, Any, Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3, v4=0.5) -> bool:
(v5, v6) = (v3[:, 0], v3[:, 1])
v7 = v1.GetConformer(0).GetPositions()
v8 = v2.GetConformer(0)... |
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:
v1 = [channel.lstrip('#') for v2 in v1]
[self.channels.remove(v2) for v2 in v1]
self.send_raw('PART #' + '#'.join(v1))
``... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
v2 = 0
v3 = 0
v4 = np.array([])
for v5 in range(self.x_max - self.x_min + 1):
v3 += self.line_set[self.current_... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Tuple[str, Optional[str], Optional[str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> Tuple[str, Optional[str], Optional[str]]:
v2 = v1.find('@')
if v2 == -1:
v3 = v1
v4 = None
el... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: int
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> np.ndarray:
v2 = self.dataset.scenes
assert v1 < len(v2), f'scene_idx {v1} is over len {len(v2)}'
v3 = self.datase... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray, bool, float, float
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: bool=False, v3: float=1.0, v4: float=0.0) -> np.ndarray:
if not v2:
return v1 * 1000.0
else:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> int:
if len(v1) < 2:
return len(v1)
v2 = 0
v3 = []
v4 = 0
for (v5, v6) in enumerate(v1):
if v6 not in v3:
... |
Imports:
```python
import sqlite3
import typing
```
Type definitions:
```python
v0 = Dict[str, int]
```
Input Types: sqlite3.Cursor, str, str, v0
Output Type: Any
Dependencies:
```python
def v1(v2: v0) -> str:
v3 = []
for v4 in v2.items():
v3.append('%s(%s)' % v4)
return _format_keywords(v3)
```
```... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if not self._data_queue.empty():
v1 = self._data_queue.get_nowait()
if self._validator.validate(v1):
self._notify_primitive_e... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor
Output Type: Tuple[np.ndarray, np.ndarray]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: torch.Tensor) -> Tuple[np.ndarray, np.ndarray]:
v3 = np.zeros(len(v2))... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[int]]
Output Type: List[Tuple[int, ...]]
Dependencies:
```python
def v0(v1: List[int], v2: List[int]) -> List[int]:
v1[1] = v2[1]
return v1
```
```python
def v3(v4: List[int], v5: List[int]) -> bool:
return v5[0] >= v4[1]
```
Fun... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, *v1: Any) -> None:
for v2 in v1:
del self._change_callbacks[v2]
``` |
Imports:
```python
import numpy as np
import pandas as pd
import typing
```
Type definitions:
Input Types: pd.DataFrame, int
Output Type: pd.Series
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: pd.DataFrame, v2: int) -> pd.Series:
if self._is_root():
v3 = pd.Series(np.zeros(v2, dtyp... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: list
Dependencies:
```python
def v0(v1: dict) -> str:
validate_task(v1)
return jinja2.Template(TEMPLATE_PATHS['task'].read_text()).render(**v1, namespaced_operator=AIRFLOW_IMPORTS[AIRFLOW_VERSION][v1['operator']]['class'])
``... |
Imports:
```python
import pandas as pd
from pandas import DataFrame
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str='country'):
if not self._baseline_built and self._experiment_defined:
raise ValueError('Model m... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = List[Dict[str, Any]]
```
Input Types: Dict[int, v0], bool
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: Dict[int, v0], v3: bool=True) -> v0:
v4 = []
if len(v2) == 1:
for v5 in v2[0]:
... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0() -> FrozenTrial:
return FrozenTrial(number=0, trial_id=0, state=TrialState.COMPLETE, value=0.2, datetime_start=datetime.datetime.now(), datetime_complete=datetime.datetime.now(), p... |
Imports:
```python
from selenium.common.exceptions import MoveTargetOutOfBoundsException, NoSuchElementException, TimeoutException
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.remote.w... |
Imports:
```python
from math import cos, radians, sin, exp
from warnings import warn
import typing
```
Type definitions:
Input Types:
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> float:
if self.d == 0:
warn('d has not been computed, I do it...')
self.comp... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Dict[Module, Dependencies]
```
```python
v1 = NewType('Module', str)
```
Input Types: v0
Output Type: Iterator[v1]
Dependencies:
Function Name: v2
Function:
```python
def v2(v3: v0) -> Iterator[v1]:
for (v4, v5) in v3.items():
yield v4
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, [str], Any, Any, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: [str], v3=False, v4=1, v5=True, v6='PNG_MASKS'):
v7 = {}
v7 = self.setEvalLabelMapPath2EvalDict(evalDict=v7, path=v1... |
Imports:
```python
from urllib.parse import quote_plus
import typing
```
Type definitions:
Input Types: str, str, bool
Output Type: Iterator[bytes]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str=None, v3: bool=None) -> Iterator[bytes]:
v4 = {'contentId': v2, 'includeDeleted': v3... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: io.FileIO
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: io.FileIO):
v2 = v1.read().lower()
v2 = re.sub('[^a-zA-Z0-9]', ' ', v2)
v2 = re.sub('\\t', ' ', v2)
v2 = re.sub('\\n', ' ', v2)
v2... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2=False, v3=False) -> dict:
v4 = {}
v4['img_path'] = os.path.join('image_2', '{}.png'.format(v1))
v4['img_prev_path'] = None
if ... |
Imports:
```python
from scipy.sparse import csr_matrix
from scipy.sparse.csgraph import maximum_flow
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0() -> None:
(v1, v2, v3) = map(int, input().split())
(v4, v5, v6) = ([], [], [])
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: 'DistrictsCollection'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[str]) -> 'DistrictsCollection':
if v1 is None:
return self
self.regions = {key: value for (v2, v3) in self.regions.... |
Imports:
```python
from collections import defaultdict
import typing
```
Type definitions:
Input Types: list[str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list[str]) -> None:
self.energy_levels: ENERGY_LEVEL_TYPE = defaultdict(int)
for (v2, v3) in enumerate(v1):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, str, str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str, v3: str, v4: str, v5: str):
v6 = []
if v1 == 'SIM':
v6.append('Fever')
if v2 == 'SIM':
v6.append('Cough'... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Callable
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Callable):
if v1 == 'opcode':
if not self.injected_functions['opcode']:
self.orig_trace_opcodes = self.frame.f_trace_... |
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=-1) -> 'np.ndarray':
v3 = np.max(v1, axis=v2, keepdims=True)
v4 = np.exp(v1 - v3)
v5 = np.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float):
self.time += v1
self.cs['time'] = self.time * 10
``` |
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 v1 not in self._server_mods:
self._server_mods.append(v1)
``` |
Imports:
```python
import torch
import torch.nn as nn
from torch.nn import functional as F
import typing
```
Type definitions:
```python
v0 = TypeVar('State')
```
Input Types: torch.Tensor, Optional[torch.LongTensor], Optional[v0], bool
Output Type: Tuple[torch.Tensor, torch.LongTensor]
Dependencies:
Function Name: v1... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(namedtuple('_Coach', ['id', 'name', 'bio', 'available', 'birth_year', 'gender', 'languages', 'need', 'rights', 'housing'])):
def v1(cls, *, v2: Optional[int]=None, v3: str, v4: str, v5: bool=True, v6: int, v7: str, v8: Dict[str, int], v9: Co... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, ailment.Block, int, ailment.Stmt.Return
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3: ailment.Block, v4: int, v5: ailment.Stmt.Return):
if v5.ret_exprs:
for v6 in v5.ret_exprs:
... |
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._output_style == 'panel':
self._write_text_to_panel(v1)
return
elif self._output_style == 'inline':
retur... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(object):
def __init__(self, v1):
self.val = v1
self.left = None
self.right = None
def __repr__(self):
return f'<{self.val}, {self.left}, {self.right}>'
```
Input Types: v0, v0, v0
Output Type: Any
Depende... |
Imports:
```python
import numpy as onp
import typing
```
Type definitions:
Input Types: Dict[str, Any], int, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[str, Any], v2: int, v3: bool=False):
if v3:
return {dim: onp.array(v2) for (v4, v5) in v1.items()}
else... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: list
Dependencies:
```python
def v0(v1: dict) -> list:
if 'ec-code' in v1['miriam'] and len(v1['miriam']['ec-code']):
return v1['miriam']['ec-code']
else:
return []
```
Function Name: v2
Function:
```python
de... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Callable, float, np.array
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Callable, v2: float, v3: np.array):
v4 = v1(v3) * v2
v5 = v1(v3 + 0.5 * v4) * v2
v6 = v1(v3 + 0.5 * v5) * v2
v7 = v1(v3 + v6) * ... |
Imports:
```python
from collections import deque
import typing
```
Type definitions:
Input Types: List[int], int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int], v2: int) -> None:
v2 %= len(v1)
if v2 == 0:
return v1
v3 = deque([])
v4 = [v3.appen... |
Imports:
```python
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import typing
```
Type definitions:
```python
class v0(NamedTuple):
v1: str
v2: datetime.datetime
v3: datetime.datetime
v4: List[Job]
@classmethod
def v5(cls, v6: dict) -> 'Metrics':
v7 = FieldValida... |
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 v1[-1:] == '?':
return v1 + 'dl=1'
if not v1[-5:] in ['?dl=1', '?dl=0']:
return v1 + '?dl=1'
if v1[-5:] == '?dl=0':
... |
Imports:
```python
import argparse
import multiprocessing
import os
import typing
```
Type definitions:
```python
class v0:
v1 = 0
v2: T.Dict[TestProtocol, T.Type['TestRun']] = {}
def v3(cls, v4: TestSerialisation, *v5: T.Any, **v6: T.Any) -> T.Any:
return super().__new__(v0.PROTOCOL_TO_CLASS[v4.pr... |
Imports:
```python
from tensorflow.core.framework import attr_value_pb2
from tensorflow.core.protobuf.tpu import tpu_embedding_configuration_pb2
from tensorflow.python.distribute import device_util
from tensorflow.python.distribute import distribute_utils
from tensorflow.python.distribute import distribution_strategy_c... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List['Git2Type']
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List['Git2Type']) -> str:
v2 = [p.c_wrapper_param for v3 in v1]
return ', '.join([x for v4 in v2 if v4])
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict):
v2 = 3
if v1['entry']:
v3 = v1['entry']['accession']
if v3 in self.ancestors:
v2 = 0
elif v3 == self.entry:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, Any, int, int, Any, Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2, v3: int, v4: int, v5, v6) -> None:
for v7 in range(v3):
v8 = 0
for v8 in range(v1):
v2[v8] +=... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, 'variable.Variable'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: 'variable.Variable'):
if v1 in self.inputs:
raise KeyError(f'{v1} is already used as key of input variable f{self.inpu... |
Imports:
```python
import warnings
import numpy as np
from scipy.linalg import eigh
from scipy.spatial.distance import pdist
from scipy.cluster.hierarchy import linkage, cut_tree
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray, np.ndarray, np.ndarray, int, float, float, float, Any
Output Type: ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: str):
if v1 in self.source_list:
await self._speaker.set_source(v1)
else:
raise ValueError(f'Unknown input source: {v1}.')
``` |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types: str, Optional[str]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Optional[str]=None) -> str:
v3 = ''
if v2:
v3 = f" (CWD='{v2}')"
logging.info('Running command%s:\n ... |
Imports:
```python
import ast
import typing
```
Type definitions:
```python
v0 = Dict[str, Union[List[str], Dict[str, Union[int, List[str]]]]]
```
Input Types: ast.ClassDef, str
Output Type: v0
Dependencies:
```python
def v1(v2: ast.FunctionDef, v3: str, v4: bool=False) -> List[str]:
v5 = []
if not v4:
... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: int, List[str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: List[str]=None):
with self.format(v2):
return pd.DataFrame(self[:v1])
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.g_loss.reset_states()
self.d_loss.reset_states()
self.w_loss.reset_states()
``` |
Imports:
```python
import inspect
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> bool:
try:
if isinstance(self.gen, list):
self.item_cache.append(self.gen.pop(0))
elif inspect.isasyncgen(self... |
Imports:
```python
import difflib
import itertools
import typing
```
Type definitions:
Input Types: Iterable[Any], Iterable[Any]
Output Type: Iterator[Any]
Dependencies:
```python
def v0(v1: Iterable[Any], v2: Iterable[Any]) -> Iterator[Any]:
v3 = list(v1)
v4 = list(v2)
v5 = (v3[block.a:block.a + block.siz... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: bool=False, **v2):
yield ('Rebuilding Database...', True)
with self.minecraft.db() as v3:
if v1:
await self.minecraft.rebuild... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: dict
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict) -> dict:
v2 = {}
for (v3, v4) in v1.items():
if v3 in self.space.real_names:
v2[v3] = np.random.choice(se... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[np.ndarray], Optional[np.ndarray], Optional[np.ndarray], Optional[np.ndarray], Optional[np.ndarray]
Output Type: Dict[str, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[np.ndarray]=None, v2: Optional[np... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1=False) -> int:
v2 = next(iter(self.data.rv_dict.values())).shape[-1]
if v1:
return v2
return v2 - self.num_adaptive_samples
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[int]
Output Type: Awaitable
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[int]=None) -> Awaitable:
v2: List[EncodableT] = ['SLOWLOG GET']
if v1 is not None:
v2.append(v1)
v3 = self.connecti... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self._write_centered_text((self.kBoard_size_px, 0), 'Black Pieces to Play', (self.unplayed_area_surface_rect.width, 50))
self._write_centered_text((s... |
Imports:
```python
import math
import typing
```
Type definitions:
Input Types: int, int, int
Output Type: Tuple[List[List[int]], List[List[int]]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int, v3: int) -> Tuple[List[List[int]], List[List[int]]]:
v4: int = math.ceil(v1 / v2)
v5: ... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('V', bound=Comparable)
```
Input Types: v0
Output Type: None
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: v0) -> None:
if v2 in self._graph:
raise KeyError(f'Node already exists: {v2}')
self._graph[v2]... |
Imports:
```python
from typing import Any, Dict, Generic, Iterator, List, Optional, Type, cast
import typing
```
Type definitions:
Input Types: Dict[str, Any]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Any]) -> Any:
if set(v1.keys()) == {'_type_', '_data_'}:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int, v3: int) -> None:
self.red.set(v1)
self.green.set(v2)
self.blue.set(v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3=2 * days(2)) -> str:
v4 = self.getSett(v1)
return self.queue_upgrade(v4.address, v2.address)
``` |
Imports:
```python
import io
import logging
import os
import numpy as np
import pickle
import typing
```
Type definitions:
Input Types: str, str, str, int, int, str, str
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: str):
v3 = os.path.join(v2, f'params_{v1}.npz')
with open(v3, 'rb') as v4:
... |
Imports:
```python
import logging
from pathlib import Path
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
Path('logs/').mkdir(parents=True, exist_ok=True)
v2 = logging.getLogger(v1)
v2.setLevel(logging.DEBUG)
v... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: bytes, str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes, v2: str, v3: str):
self.validate_id(v2)
self.validate_owner(v2, v3)
v4 = self.make_meta(v1, v2, v3)
v5 = json.dum... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: torch.Tensor
Dependencies:
```python
def v0():
v1 = torch.cuda.device_count()
v2 = 'cuda' if v1 > 0 else 'cpu'
return torch.device(v2)
```
Function Name: v3
Function:
```python
def v3(v4: np.ndarray) ->... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, DefaultDict, List, DefaultDict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int, v3: DefaultDict, v4: List, v5: DefaultDict):
v6 = ['0' for v7 in range(v2)]
v8 = v1 + 1
while v4:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'LWPolyline'
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'LWPolyline') -> None:
self.add_source_code_lines(self.generic_api_call('LWPOLYLINE', v1.dxfattribs()))
self.add_list_source_code(v1.get_point... |
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 = super().get_config()
v1['seq_length'] = self.seq_length
v1['start_of_sequence_id'] = self.start_of_sequence_id
v1['e... |
Imports:
```python
import typing
```
Type definitions:
Input Types: typing.List[str], Any
Output Type: typing.List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: typing.List[str], v2=0) -> typing.List[str]:
v3 = v2
v4 = []
for v5 in v1:
if v5.endswith('{'):
v4.appe... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: str) -> Body:
if v1 not in BODIES:
BODIES[v1] = Body(v1)
return BODIES[v1]
```
```python
def v2(v3: List[str]) -> None:
for v4 in v3:
(v5, v6) = v4.split(')')
v5... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame, List[Text]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame, v2: List[Text]) -> None:
v3 = list(set(v2) - set(v1.columns))
if v3:
raise ValueError('Missing required columns: {... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes, v2: int) -> int:
v3 = self.op2
if v3.table_code == 2:
v4 = {b'BOPG1': '', b'OPG1': '', b'OPG2': '', b'OPGV1': '', b'OCRPG': '', b'... |
Imports:
```python
import math
import torch
from torch import Tensor
import typing
```
Type definitions:
Input Types: Tensor, Tensor, int, int, int, float, int, float, Optional[int], bool
Output Type: Tensor
Dependencies:
```python
def v0(v1: Tensor, v2: float=1.0) -> Tensor:
return v1.pow(2.0).sum(-1).pow(0.5 * v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: typing.Dict[str, float]
Output Type: typing.Union[str, float, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: typing.Dict[str, float]) -> typing.Union[str, float, int]:
if self.transformer is None:
return self.va... |
Imports:
```python
import cv2
import numpy as np
import typing
```
Type definitions:
```python
class v0(BoundBox):
v1: int
v2: int
v3: int
v4: int
v5: int
v6: int
v7: str
v8: int
v9: int
v10 = None
v11: [int, int]
v12 = 4
v13 = 0
def __init__(self, v14: BoundBox,... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: 'BasePlugin'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> 'BasePlugin':
self.config.set_key('use_' + v1, True, True)
v2 = self.get(v1)
if v2:
return v2
return self.load_plugin(v... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, Optional[int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Optional[int]=None):
v3 = ['uninstall', v1]
v4 = self.execute(v3, timeout=v2)
v5 = re.search('Failure \\[.+?\\]', ... |
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