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Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Any:
self._composition.kill(self._mz_service.name)
self._composition.up(self._mz_service.name)
return 0.0
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> bool:
v3 = self.get_enrolled_courses(v1)
return int(v2) in [p.id for v4 in v3]
``` |
Imports:
```python
import zipfile
from PIL import Image
import pandas as pd
from tqdm import tqdm
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if (self._processed_dir / 'ISIC-images').is_dir():
return
if n... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Any]
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Any]) -> Dict[str, Any]:
v1 = self.set_defaults(v1)
v1 = self.validate_fields(v1)
v1 = self.update_instance(v1)
... |
Imports:
```python
import json
import base64
import typing
```
Type definitions:
Input Types: object
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: object) -> str:
v2 = json.dumps(v1)
v3 = bytes(v2, 'utf-8')
v4 = base64.b64encode(v3)
v5 = v4.decode('utf-8')
return ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Union[None, str]
Dependencies:
```python
def v0(v1: str, v2: int) -> str:
return v1 + (str(v2) if v2 > 1 else '')
```
Function Name: v3
Function:
```python
def v3(v4: str) -> Union[None, str]:
if not v4 or v4 is None:
... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0() -> str:
if os.getenv('LOGZIO_REGION') == 'us':
return 'https://listener.logz.io:8053'
else:
return 'https://listener.logz.io:8053'.replac... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
v1: Dict[Tuple[Type[Object], sn.Name], sd.RenameObject[Object]]
v2: Dict[Tuple[Type[Object], sn.Name], sd.DeleteObject[Object]]
v3: Optional[DeltaGuidance]
v4: List[sd.ObjectCommand[Any]]
def __init__(self, *, v5: bool=False... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
assert self.module
if self.function:
return self.function.fullname()
if self.classes:
return self.classes[-1].fullname()
return... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, QtCore.QThread
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3: QtCore.QThread):
v3.function = v1
v3.arguments = v2
v3.start()
``` |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
if not self.resample_opts:
v1 = ''
else:
v1 = f'RESAMPLE {self.resample_opts}'
v2 = f'CREATE CONTINUOUS QUERY {self.name}... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
v1 = self.P_f.invert().permutate(v1)
for v2 in self.rounds[::-1]:
v1 = v2.decrypt(v1)
return self.P_i.invert().permutate(v1)
``... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: (Union[Tensor, None], (float, float, float))
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, *v2) -> (Union[Tensor, None], (float, float, float)):
(v3, v4, v5) = v1
(v6, v7, v8, v9, v10) = v2
(v11, v1... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, List[int], Any
Output Type: List[torch.Tensor]
Dependencies:
```python
def v0(v1: torch.Tensor, v2: torch.Tensor, v3='exp_rank') -> torch.Tensor:
v4 = process_recsys_components(v1, v2)
v5 = v4.device
... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: str, *, v2: Iterable[str]) -> str:
v3 = input(v1)
while v3 not in v2:
print('TRY AGAIN...')
v3 = input(v1)
return v3
```
```python
def v4(v5: float) -> boo... |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: List[str], Optional[str]
Output Type: Any
Dependencies:
```python
def v0(v1: List[str], v2=True) -> str:
v3 = '\x1b[34m'
v4 = '\x1b[0m'
v5 = ' '.join(v1)
return f'{v3}# {v5}{v4}' if v2 else f'# {v5}'
```
Function Name... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2) -> None:
self.losses.reset_accuracy_metric()
for (v3, v4, v5) in v1:
self._call_test(v3, v5, v2)
return self.losses.get_accuracy_r... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: Any
Dependencies:
```python
def v0(v1: str) -> int:
v2 = 0
for v3 in v1[0:68]:
if v3.isdigit():
v2 += int(v3)
elif v3 == '-':
v2 += 1
v2 = v2 % 10
return v2
```
```python
de... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int], Dict[str, str], List[str], bool, int
Output Type: str
Dependencies:
```python
def v0(v1: str, v2: int, v3: bool=False, v4: int=2) -> str:
v5 = v2 + v4
if v3:
return v1.center(v5, ' ')
v6 = v1.rjust(min(int(v4 / 2) + len(... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Generator[Any, Any, Any]
```
Input Types:
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self) -> v0:
while True:
if not self.ready:
self.iopoll(None)
else:
self.iopoll(0)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, int], Dict[str, int], bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[str, int], v2: Dict[str, int], v3: bool) -> None:
v4 = '\n--------------------------\n Third-party packages\n------------... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Iterable[Hashable], Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Iterable[Hashable], v2: Any=None) -> None:
v1 = frozenset(v1)
self.add_vertices(v1)
for v3 in v1:
self._adjacency_lists... |
Imports:
```python
import io
import typing
```
Type definitions:
Input Types: Any, bool, bool
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Any, *, v2: bool=False, v3: bool=False) -> bool:
if v2 or v3:
return (not v2 or hasattr(v1, 'read')) and (not v3 or hasattr(v1, 'wr... |
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) -> None:
v4 = self.get_link_properties(v1, v2)
v5 = v4['position']
v6 = v4['orientation']
v7 = v4['mass']
... |
Imports:
```python
from collections import deque
import typing
```
Type definitions:
Input Types: int, int
Output Type: IO[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int) -> IO[str]:
if v1 == v2:
return
v3 = [False] * self._num_vertices
v3[v1] = True
v4 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: 'TexturesVertex'
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> 'TexturesVertex':
v1 = self.__class__(self.verts_features_padded().detach())
if self._verts_features_list is not None:
v1._verts_featur... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, str, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: str, v3: int=3) -> str:
for v4 in ['', 'K', 'M', 'B']:
if v1 < 1000:
break
v1 /= 1000
return f'{v1:.{v3}f} {v4}... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2):
v3 = self.params[v1]
setattr(self[v3], v1, v2)
if v3 == 'cosmo' and v1 == 'H0':
if self.cosmo.fix_Omega_b_h2:
sel... |
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 not in self.store:
return ''
v2 = self.store[v1]
if v2 == self.tail:
self.tail = v2.left
if v2.left:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, float]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[str, float]) -> str:
v2 = []
(v3, v4) = ([], None)
for v5 in sorted(v1.keys()):
v6 = v5.rsplit('_', maxsplit=1)[0]
if v6... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: str
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> float:
if isinstance(v1, float):
return v1 * 180.0 / np.pi
elif str(v1) == 'EAST':
return 0.0
elif str(v1) ==... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict, v2: str, v3: Any):
if v2 not in v1:
v1[v2] = v3
return v1[v2]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
if len(self.rows) < v1:
return self._cursor.fetchmany(size=len(self.rows))
else:
return self._cursor.fetchmany(size=v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Optional[int]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Optional[int]=None) -> None:
self.main.stackedWidget_modes.setCurrentWidget(getattr(self.main, f'page{v1}'))
for v3 in self.mai... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> int:
v2 = ['CM', 'CD', 'XC', 'XL', 'IX', 'IV']
v3 = 0
for v4 in v2:
if v4 in v1:
v1 = v1.replace(v4, '')
v3 ... |
Imports:
```python
import asyncio
import typing
```
Type definitions:
```python
v0 = TypeVar('R')
```
```python
v1 = TypeVar('T')
```
Input Types: Callable[[v1], Awaitable[v0]], Callable[[v1], Awaitable[v0]], Sequence[v1]
Output Type: Sequence[v0]
Dependencies:
```python
async def v2():
while pending:
for v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
v2 = self._create_redirect_uri('facebook')
return f'https://www.facebook.com/v8.0/dialog/oauth?client_id={self.facebook_id}&redirect_uri={v... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.store > 100:
self.environment[self.y][self.x] += self.store
self.store = 0
``` |
Imports:
```python
import requests
from requests import Response
import typing
```
Type definitions:
Input Types: str, dict
Output Type: Response
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: dict=None) -> Response:
v2 = v2 or {}
return requests.post(f"{self._server_address}/{v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[List[str]]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[List[str]]=None) -> None:
v1 = v1 or []
if len(v1) == 0:
if self.config.path.exists():
self.config.path.un... |
Imports:
```python
from operator import attrgetter
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: Iterable[v0]
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: Iterable[v0], **v3: Any) -> v0:
v4 = [(attrgetter(attr.replace('__', '.')), value) for (v5,... |
Imports:
```python
import numpy
import numpy as np
import typing
```
Type definitions:
Input Types: numpy.ndarray, numpy.ndarray, int
Output Type: numpy.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: numpy.ndarray, v2: numpy.ndarray=None, v3: int=0) -> numpy.ndarray:
(v4, v5, v6) = v1.shap... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: io, bool, Optional[int], Optional[bool]
Output Type: Any
Dependencies:
```python
def v0(v1: pd.DataFrame, v2: Optional[int], v3: bool, v4: bool) -> pd.DataFrame:
v1 = v1.T if v3 is True else v1
v1 = v1.dropna(how='all', axi... |
Imports:
```python
import torch
from torch import Tensor
from torch.nn import Module
from torch.utils.data import DataLoader, Dataset
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3=0) -> Tensor:
v1 = v1.view(... |
Imports:
```python
import pandas as pd
import requests
import typing
```
Type definitions:
Input Types: str, Any
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2='1h') -> pd.DataFrame:
if self.basic_auth:
v3 = requests.auth.HTTPBasicAuth(self.basic_aut... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.package_dir.mkdir()
v1 = self.package_dir / '__init__.py'
v2 = self.env.get_template('package_init.pyi')
v1.write_text(v2.render(descrip... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int=2, **v3: Dict[str, int]):
assert v1 == 1
assert v2 == 2
assert v3['c'] == 3
return ('success', vars())
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('M', bound=Union[NamedType, NicknamedType])
```
Input Types: str, Iterable[v0]
Output Type: Optional[v0]
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: str, v3: Iterable[v0]) -> Optional[v0]:
v4: Optional[int]
try:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[Union[str, Real]], Optional[Real]
Output Type: Any
Dependencies:
```python
def v0(v1: str) -> Real:
v2 = v1.lower().rsplit('u', 1)
v3 = len(v2)
if v3 == 2:
v1 = v2[1]
elif v3 != 0:
return 0
v4 = num_or_none... |
Imports:
```python
import itertools
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
```python
def v0(v1: str, v2=False) -> list:
v3 = set()
v4 = helper.find_vanity_number_format(v1)
if v4 == '':
print('Invalid Number')
return v4
(v5, v6) = v4
v7 =... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = self.keycloak_type()
return f'{v1}:{self.pk}'
``` |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
for v1 in self.tv.get_children():
self.tv.delete(v1)
self.path = os.path.abspath(self.directory)
self.node = self.tv.insert('',... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: tuple, int, float, frozenset, frozenset, frozenset, float, frozenset, bool
Output Type: Tuple[np.ndarray, np.ndarray]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: tuple, v2: int, v3: float=0.5, v4: frozenset... |
Imports:
```python
import string
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
for v2 in range(v1):
self.symboles.append(string.ascii_lowercase[v2])
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: argparse.ArgumentParser
Output Type: argparse.ArgumentParser
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: argparse.ArgumentParser) -> argparse.ArgumentParser:
v1.add_argument('--max-num-samples', dest='max_num_samples', type=int... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: types.Comparable[v0], types.Comparable[v0], types.Comparable[v0]
Output Type: types.Comparable[v0]
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: types.Comparable[v0], *, v3: types.Comparable[v0], v4: ty... |
Imports:
```python
import shutil
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: None
Dependencies:
```python
def v0(v1: str) -> None:
try:
shutil.rmtree(v1)
except FileNotFoundError:
pass
```
Function Name: v2
Function:
```python
def v2(v3, v4) -> None:
print('Writin... |
Imports:
```python
import pandas as pd
from pandas.io.parsers import TextFileReader
import typing
```
Type definitions:
Input Types: List[int], Union[List[int], None]
Output Type: Dict[str, datetime]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int], v2: Union[List[int], None]=None) -> Di... |
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:
if self._user_repository.user_exists(v1):
return 'Käyttäjätunnus on jo olemassa'
if len(v2) < 6:
return 'Sala... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
v1 = ['labbooks']
self.__stop_containers()
self.__delete_local_images()
for v2 in v1:
self.__delete_directory(v2)
return True
``` |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: str, Any, Any
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, *, v2=False, v3=False) -> Optional[str]:
v4 = {}
if v3:
v5 = f' > >(tee "{self.cmd_output_path}") 2>&... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = str
```
Input Types: str
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: str) -> v0:
v3 = 1
v4 = 'message_id'
v5 = f'{v4} DESC LIMIT {v3}'
v6 = f'SELECT {v4} FROM {v2} ORDER BY {v5};'
return v6
``` |
Imports:
```python
import os
from pathlib import Path
from tempfile import TemporaryDirectory
import typing
```
Type definitions:
Input Types: str
Output Type: Union[Path, 'TemporaryDirectory[str]']
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> Union[Path, 'TemporaryDirectory[str]']:
v2 =... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str):
v3 = self._path_to_env(self.env.db_service, v2)
v4 = self._path_to_env(self.env.db_service, v1)
self.env.engine.path_copy(v4, v3... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Callable[[], None]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Callable[[], None]):
if self._triggered:
v1()
else:
self._callables.append(v1)
``` |
Imports:
```python
import multiprocessing
import tensorflow as tf
import typing
```
Type definitions:
Input Types: Union[List[str], str], int, Optional[int]
Output Type: Union[List[str], str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[List[str], str], v2: int=1, v3: Optional[int]=None)... |
Imports:
```python
from sklearn.metrics import f1_score
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, Any
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: torch.Tensor, v3=False) -> torch.Tensor:
v1 = v1.cpu().numpy().tolist(... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
v1: List['Var']
v2: List['Var']
v3: List['Atom']
v4: List['JaxprEqn']
def __init__(self, v5: Sequence['Var'], v6: Sequence['Var'], v7: Sequence['Atom'], v8: Sequence['JaxprEqn']):
"""
Args:
constvars: list ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1=True) -> dict:
v2 = {k: getattr(self, k) for v3 in ['name', 'label', 'description']}
v2['channels'] = [item.json() for v4 in self.channels]
v2['spec... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'CeedFuncRef'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'CeedFuncRef'):
if v1.func not in self._ref_funcs:
raise ValueError("Returned function that wasn't added")
self._ref_funcs[v1.func] -=... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'CdmEntityDefinition', 'CdmAttributeContext'
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'CdmEntityDefinition', v2: 'CdmAttributeContext') -> str:
self._bldr = ''
self._get_content_declared_path(v1.at... |
Imports:
```python
import torch
import torch.nn as nn
from torch import optim
from torch.utils.data import DataLoader, RandomSampler
import typing
```
Type definitions:
Input Types: list
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list) -> dict:
v2 = 0
v3 = 0
for... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types:
Output Type: Dict[str, tf.Tensor]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict[str, tf.Tensor]:
with tf.name_scope('scalars'):
self._build_metrics_op()
return {'accuracy': self.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: ir_database.Database, split.Splitter
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: ir_database.Database, v2: split.Splitter):
v3 = v2.Split(v1)
assert len(v3) == 3
``` |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str):
v3 = pd.date_range(v1, v2, freq='1W-MON')
print(v3[0], v3[-1])
v4 = v5 = None
if v3[0] != v1:
v4 = (pd... |
Imports:
```python
from os.path import join, exists
from os import makedirs
from numpy import ndarray, array, clip, ceil, matmul, diag, around, power, argwhere, diff, split, where, empty, append
import typing
```
Type definitions:
Input Types: str, list
Output Type: Any
Dependencies:
```python
def v0(v1: Nifti1Image) ... |
Imports:
```python
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, **v3) -> np.ndarray:
if v2 >= len(v1):
raise ValueError(f'step ({v2}) should be less than the length ({len(v1)})... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> None:
if not self.git:
return
await self.git.load()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool, Optional[int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool, v2: Optional[int]=None):
if not v1:
self.keep_alive_service_enabled = False
self.keep_alive_service = None
if v2:
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: npt.NDArray[np.bool_], Any, Any
Output Type: Any
Dependencies:
```python
def v0(v1: npt.NDArray[np.bool_], v2: int) -> npt.NDArray[np.bool_]:
v3 = v1.shape[:-1] + (v1.shape[-1] - v2 + 1, v2)
v4 = v1.strides + (v1.strides[-1]... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
self.filterText = (v1 or '').strip()
self._applyFilter()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> None:
global MAX_PARALLEL_PILES
v2 = v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[dict]:
v1 = 'process_payment'
return [{'name': plugin.PLUGIN_NAME, 'config': self.__get_payment_config(plugin.PLUGIN_NAME)} for v2 in self.plugi... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
```python
v0 = Callable[[np.ndarray, np.ndarray, np.ndarray, float], np.ndarray]
```
```python
v1 = Union[int, float]
```
Input Types: np.ndarray, np.ndarray, np.ndarray, v1, v0
Output Type: Any
Dependencies:
Function Name: v2
Function:
```pytho... |
Imports:
```python
from collections import namedtuple
from collections import Counter
import typing
```
Type definitions:
```python
class v0(NamedTuple):
v1: Access
v2: datetime.datetime
v3: str
v4: urllib.parse.ParseResult
v5: str
v6: urllib.parse.ParseResult
v7: Optional[AgentDetails]
```
... |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: torch.Tensor, int, int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: int, v3: int, v4: int):
v5 = next(self.paramete... |
Imports:
```python
import typing
```
Type definitions:
Input Types: tir.BufferStore, None
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: tir.BufferStore, v2: None) -> int:
v3 = 1 + self(v1.value, None)
for v4 in v1.indices:
v3 += self(v4, None)
return v3
``` |
Imports:
```python
import numpy
import typing
```
Type definitions:
```python
v0 = typing.Dict[str, typing.List[typing.Union[int, float]]]
```
Input Types: float, float, v0, float, v0, float, float, int, bool
Output Type: float
Dependencies:
```python
def v1(v2: float, v3: v0, v4: int, v5: bool=False) -> float:
if ... |
Imports:
```python
import math
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray) -> int:
v2 = 2 * math.pi
v3 = 16
v4 = v1[3]
v5 = np.clip(np.floor(v4 / v2 * v3), 0, v3 - 1)
retu... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Dict, List[float]
Output Type: List[float]
Dependencies:
```python
def v0(v1: List[float], v2: List[float]) -> float:
if len(v1) == 0:
return 0
return np.sum(np.interp(np.arange(0, 1.1, 0.1), v1, v2)) / 11
```
```pyt... |
Imports:
```python
from typing import BinaryIO, Dict, Generic, List, Optional, Sequence, TextIO, Tuple, TypeVar, Union, cast
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
if self.codec:
cast(BinaryI... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame, str, bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame, v2: str, *, v3: bool=False, **v4: Any) -> None:
with open(v2, 'a') as v5:
v1.to_csv(v5, header=False, index=v3, **v4)
`... |
Imports:
```python
import torch
import torch.nn as nn
import typing
```
Type definitions:
Input Types: Dict[str, torch.Tensor]
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, torch.Tensor]) -> torch.Tensor:
v2 = []
for v3 in self.inputs:
v4 = []... |
Imports:
```python
import shlex
import typing
```
Type definitions:
Input Types: str
Output Type: list[str]
Dependencies:
```python
def v0():
nonlocal buff, cmd_split
cmd_split.append(' '.join(buff))
v1 = []
```
Function Name: v2
Function:
```python
def v2(v3: str) -> list[str]:
def v4():
nonl... |
Imports:
```python
from PIL import Image, ImageDraw, ImageFont, ImageOps
import typing
```
Type definitions:
Input Types: Image.Image, str, str
Output Type: ImageFont
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: Image.Image, v2: str, v3: str=None) -> ImageFont:
v4 = 1
if not v3:
... |
Imports:
```python
import gc
import inspect
from itertools import islice
import typing
```
Type definitions:
Input Types: int, int | None
Output Type: str
Dependencies:
```python
def v0(v1: FrameType) -> str:
v2 = v1.f_code.co_name
v2 = next((f.__qualname__ for v3 in gc.get_referrers(v1.f_code) if inspect.isfu... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict):
if self.csvheader:
v2 = []
for v3 in self.csvheader:
v2.append(str(v1[v3]))
self.writer.log(100, ','.join(v2))
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.roll_key = np.copy(self.kra_key)
self.collector = np.zeros([5, 5], dtype=np.uint64)
self.digest = bytearray(b'')
self... |
Imports:
```python
from math import pi, acos, sqrt
from numbers import Number
import typing
```
Type definitions:
Input Types: tuple, tuple, bool
Output Type: float
Dependencies:
```python
def v0(v1: float) -> float:
v2 = v1 / abs(v1)
if abs(v1) > 1:
return 1 * v2
else:
return v1
```
```pyt... |
Imports:
```python
import datetime as dt
import typing
```
Type definitions:
Input Types: int
Output Type: dt.date
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> dt.date:
v2 = dt.date(v1, 8, 1).isocalendar()[2]
v3 = 7 - v2
return dt.date(v1, 8, 1 + v3)
``` |
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