text stringlengths 190 325k |
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Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: tuple[float, list, bool]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> tuple[float, list, bool]:
v1 = self.step_reward
v2 = list()
if 'camera' in self.observation:
v2.append(self.camera.capture_... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass
class v0(VerificationResult):
v1: exceptions.VerificationError
def __init__(self, v2: str, v3: List[VerificationResult], v4: llvm.Contract, v5: exceptions.VerificationError) -> None:
self.server_name = v2
self.assumptio... |
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.cursors = {}
self.widget_ids_this_run = set()
self.form_ids_this_run = set()
self.query_string = v1
self._set_page_co... |
Imports:
```python
import numpy as np
import pandas as pd
import typing
```
Type definitions:
Input Types: pd.DataFrame, pd.Series
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame, v2: pd.Series):
v3 = np.concatenate((v1.to_numpy(), v2.to_numpy().reshape(-1, 1)), axis=1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: dict[str, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float) -> dict[str, int]:
v2 = dict(seconds=0, minutes=0, hours=0, days=0)
v2['days'] = int(v1 / 86400)
v2['hours'] = int(v1 % 86400 / 3600)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Optional[bytes]
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: str, v2: Optional[bytes]=None) -> bytes:
if v2 is not None and (not isinstance(v2, bytes)):
raise ValueError(f'raw_body {ty... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
self.send_action(v1)
retu... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[Tensor, Any], Optional[Union[Tensor, Any]]
Output Type: Union[Tensor, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[Tensor, Any], v2: Optional[Union[Tensor, Any]]=None) -> Union[Tensor, Any]:
if v2 is None:... |
Imports:
```python
import typing
```
Type definitions:
Input Types: html.Element
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: html.Element) -> str:
if v1.tag == 'table':
return ''
if v1.tag == 'iframe':
return ''
if len(self.elem) == 0:
v2 =... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=None):
v2 = {}
if v1 is not None:
v2['symbol'] = v1
v3 = self.get('ticker/price', params=v2, api_version='v3')
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: pytest.TestReport
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: pytest.TestReport) -> None:
v2: Optional[RichTerminalReporter.Status] = None
if v1.when == 'setup':
v2 = 'running'
elif v1.wh... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self.dt.group_milestone_events(type='changed_milestone')
self.assertIsNot(v1, None)
``` |
Imports:
```python
import json
import os
from tqdm import tqdm
import typing
```
Type definitions:
Input Types:
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict:
for v1 in tqdm(self.sample_tokens, disable=not self.verbose):
v2 = self.nusc.get('sample', v1)
... |
Imports:
```python
import numpy as np
import random
import typing
```
Type definitions:
Input Types: Any, Union[str, List[str]], Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: Union[str, List[str]], v3=1):
v4 = v1.split()
for v5 in range(v3):
if isinstance(v2, ... |
Imports:
```python
import json
from pathlib import Path
import pandas as pd
import typing
```
Type definitions:
Input Types: str
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> pd.DataFrame:
v2 = Path(v1).read_text().split('\n')
v3 = [json.loads(o, encoding='ut... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Type['ParameterStore']
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=False) -> Type['ParameterStore']:
v2 = self.__class__()
for (v3, v4) in self._params:
v2.add(v4)
for (v3, v4) in se... |
Imports:
```python
import torch
from torch.fx.graph import Graph, Node
import torch.overrides
from torch._prims.utils import TensorMeta, torch_function_passthrough
import torch._refs as refs
import torch._refs
import torch._refs.nn
import torch._refs.nn.functional
import torch._refs.special
import torch._prims
import t... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types:
Output Type: Optional[Dict[str, Any]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Optional[Dict[str, Any]]:
v1 = f'{self.BASE_API_URL}/manga/{self.id_onpage}'
v2 = self.get_html(v1)
if v2:
pass... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Dict[Text, np.ndarray]
```
Input Types:
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self) -> v0:
if self._current_node > 0:
v2 = self._sorted_node_indices[self._current_node - 1]
v3 = self._macro_i... |
Imports:
```python
import gzip
import logging
from tqdm import tqdm
import typing
```
Type definitions:
Input Types: str
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> dict:
v2 = dict()
logging.info('Making uniprot name to id map')
with gzip.open(v1, mode='rb') as... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[str, Path]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[str, Path]):
v2 = self.get_from_cache(v1)
if v2:
return v2
v3 = self.vpk_archive.find_file(full_path=v1)
if v3:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.Series, Any, Any, Any, Any, Any
Output Type: pd.Series
Dependencies:
```python
def v0(v1: pd.Series, v2: pd.Series, v3=100, v4=0.005) -> pd.Series:
v1 = v1.loc[v2.index]
v5 = v1[v2].iloc[::2]
v6 = v1[v2].iloc[1::2]
v5 = v5.iloc[:v6.... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('Element')
```
Input Types: [v0]
Output Type: Any
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: [v0]):
for v3 in v2:
print(v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List, List, int
Output Type: Iterable[List]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List=ANALYTICS_FIELDS_V2, v2: List=BASE_ANALLYTICS_FIELDS, v3: int=FIELDS_CHUNK_SIZE) -> Iterable[List]:
v4 = list((v1[f:f + v3] for v5 in ... |
Imports:
```python
from scipy.stats import norm
from scipy.spatial.distance import cdist
from numpy import array as np_array
from numpy import ndarray as np_ndarray
from numpy import empty as np_empty
from numpy import zeros as np_zeros
from numpy import uint32 as np_uint32
from numpy import float64 as np_float64
from ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self: QtWidgets.QMainWindow) -> None:
self.cam1.emgain = self.emgain1.value()
self.cam2.emgain = self.emgain2.value()
self.update_plot()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
```python
def v0(v1: str) -> t.Optional[t.Tuple[str, str]]:
v2 = v1.split('_')
return tuple(v2) if len(v2) == 2 else None
```
Function Name: v3
Function:
```python
def v3(v4: str, v5: str) -> bool:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Any]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[str, Any]) -> str:
if v1.get('teamMain'):
return f"[TEAM] {v1['name']}"
elif v1.get('t') == 'l':
return v1['fname']
else:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, list, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: list, v3: str):
try:
v1[v3].insert_many(v2)
except:
print('Error!')
``` |
Imports:
```python
import threading
import logging
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = '%(asctime)s: %(message)s'
logging.basicConfig(format=v1, level=logging.INFO, datefmt='%H:%M:%S')
v2 = threa... |
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.__engine is None:
raise AttributeError('Engine is not initialized')
self.__connection = self.__engine.connect()
v2 = [row[1] f... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, dict, dict
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list, v2: dict, v3: dict) -> list:
v4 = ['Diff', 'DiffRelative', 'L1', 'L2', 'MAPE', 'SMAPE', 'SSIM']
v5 = []
for v6 in v4:
v7... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.array
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.array) -> float:
if not np.any(v1):
return 1.0
v2 = np.mean(v1)
if v2 >= 0:
v3 = sum(v1 < 0)
else:
... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: sqlite3.Cursor
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: sqlite3.Cursor) -> pd.DataFrame:
v1.execute("SELECT name FROM actor\n JOIN casting ON actor.id = casting.ac... |
Imports:
```python
import matplotlib.pyplot as plt
import typing
```
Type definitions:
```python
v0 = Tuple[float, float]
```
Input Types: v0, v0, v0, v0, v0, v0, v0, v0, v0, v0, v0, v0, bool, float
Output Type: None
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: v0, v3: v0, v4: v0, v5: v0, v6: v0, v7:... |
Imports:
```python
import collections
import re
import typing
```
Type definitions:
Input Types: Union[str, dict, Iterable], str
Output Type: Any
Dependencies:
```python
@cache
def v0():
from airflow.configuration import conf
v1 = DEFAULT_SENSITIVE_FIELDS.copy()
v2 = conf.get('core', 'sensitive_var_conn_na... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, *v2: typing.Any, **v3: typing.Any) -> None:
v4 = getattr(self, v1, None)
if v4:
v4(*v2, **v3)
``` |
Imports:
```python
import argparse
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: str=None, v2: str=None, v3: str=None, v4: str=None, v5: str=None) -> None:
v6 = ['--runner=DirectRunner']
if v1 is not None and (v3 is not None or v4 is not None):
v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, str
Output Type: Dict[str, Any]
Dependencies:
```python
async def v0(v1: str, v2: bool=False) -> Dict[str, Any]:
v3 = {}
if v2:
v3 = get_auth_header()
try:
v4 = State.get_session()
async with v4.get(v1, headers... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
for v2 in self.entity_map.accessories:
for v3 in v1:
if (v2.aid, None, None) in self.entities:
continue
... |
Imports:
```python
import collections
import pathlib
import typing
```
Type definitions:
Input Types: list[pathlib.Path]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list[pathlib.Path]) -> None:
v2 = self.get_image_root(relative_to='fsroot')
v3: dict[str, set[pathlib.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list) -> None:
v2 = []
for v3 in v1:
for v4 in v3.tags.analytic_story:
if v4 == self.story.name:
v2.append(str('ES... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Tensor]
Output Type: Dict[str, Tensor]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Tensor]) -> Dict[str, Tensor]:
v2 = self.preprocess_sample(v1)
v3 = []
for v4 in self.modality_keys:
v... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Model):
v1: str
v2: int
v3: str
v4: int
v5: int
v6: Dict[str, Any]
v7: str
v8: str
v9: str
def v10(self, v11: str) -> v0:
self.currency_code = v11
return self
def v12(self, v13: int) -... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
v1 = 0
for v2 in self.tests:
if not v2['selected']:
continue
v1 += self.num_cases_for_test(v2)
return v1
``` |
Imports:
```python
import logging
from pathlib import Path
import typing
```
Type definitions:
Input Types: str, str, Any
Output Type: Any
Dependencies:
```python
def v0(v1: str):
v2 = boto3.resource('s3', region_name=Config.AWS_REGION_NAME, aws_access_key_id=Config.AWS_ACCESS_KEY_ID, aws_secret_access_key=Config.... |
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):
self._optimizer.zero_grad()
v3 = self._classifier(v1)
v4 = self._criterion(v3, v2)
v4.ba... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> int:
(v2, v3) = (0, 1)
while v1 >= v3:
v4 = v1 // (v3 * 10) * v3
v5 = max(v1 % (v3 * 10) - v3 + 1, 0)
v5 = min(v5, v3)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, np.ndarray
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: np.ndarray) -> None:
if v1 not in self.parameters_dict:
raise KeyError(v1)
else:
self.parameters_dict[v1] = v2.tol... |
Imports:
```python
import os
import os.path
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.prompt()
self.run_sanity_checks()
print('Temporary target directory: {}'.format(self.target_dir))
self.git_clon... |
Imports:
```python
from urllib.parse import urljoin
from qiskit import QuantumCircuit, execute
from qiskit.providers import JobStatus
from qiskit.providers.ibmq.job import IBMQJob
from qiskit.providers.ibmq.runtime import RuntimeJob
from qiskit.qobj import PulseQobj, QasmQobj
from qiskit.opflow import PauliSumOp
from q... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: float):
v2 = max(v2, 0)
v2 = min(v2, 1)
v1 = max(v1, 0)
v3 = int(1023 * v2)
super().setPWMOutput(v1, v3)
``` |
Imports:
```python
import torch
import torch.nn as nn
import torch.sparse as sparse
import torch.nn.init as init
from torch.nn.parameter import Parameter
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: Iterator[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> Iterator[str]:
yield from self.write_key(v1)
yield from self.write_value(v1, v2)
``` |
Imports:
```python
from datetime import datetime, timedelta
import typing
```
Type definitions:
Input Types:
Output Type: datetime
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> datetime:
v1 = self.current_curve_generator.get_next_schedule()
if v1 is None:
print("I don't have mor... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: NoReturn
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> NoReturn:
if self._io is not None:
raise ValueError('IO is already opened')
self._io: IO = v0(self._file, 'rb')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
self.lexer.input(v1)
while True:
v2 = self.lexer.token()
if not v2:
break
yield v2
``` |
Imports:
```python
import subprocess
import os
import os.path
import typing
```
Type definitions:
Input Types: str, str, str, int
Output Type: Any
Dependencies:
```python
def v0(v1: str, *v2):
v3 = os.getenv('INSTALLNAMETOOL', 'install_name_tool')
subprocess.check_call([v3, '-' + v1] + list(v2))
```
Function N... |
Imports:
```python
import os
import os.path as path
import typing
```
Type definitions:
Input Types: Path
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Path):
v1 = v1.resolve()
if not any((p in {'hydra_utils', 'hydra-zen', 'hydra_zen'} for v2 in v1.parts)):
raise Valu... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('R')
```
```python
v1 = TypeVar('T')
```
```python
v2 = TypeVar('U')
```
```python
v3 = TypeVar('V')
```
```python
v4 = TypeVar('W')
```
Input Types: Callable[[v1], v2], Callable[[v2], v3], Callable[[v3], v4], Callable[[v4], v0]
Output Type: ... |
Imports:
```python
import json
import logging
from requests import get
from datetime import datetime, timedelta
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
logging.debug('getting channels data')
v1 = self.__load_... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: Optional[bytes]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3) -> Optional[bytes]:
v4 = self.prefix_db.claim_to_channel.get(v1, v2, v3)
if v4:
return v4.signing_hash
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str):
v3 = sorted(v2.split(','))
v4 = ','.join(v3)
if v4 != v1:
return False
return True
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(BaseModel):
v1: Union[List['JsonSchemaObject'], 'JsonSchemaObject', None]
v2: Optional[bool]
v3: Union[str, List[str], None]
v4: Optional[str]
v5: Optional[str]
v6: Optional[int]
v7: Optional[int]
v8: Optional[floa... |
Imports:
```python
import hashlib
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
v2 = hashlib.sha256()
v2.update((self._prefix + v1).encode())
v3 = ''.join((bin(i)[2:].zfill(8) for v4 in v2.digest())... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: List['Step'], v2: float):
self.steps = v1
self.cost = v2
def v3(self: 'Path') -> int:
return len(self.steps)
def v4(self: 'Path') -> 'Step':
return self.steps[-1]
def v5(... |
Imports:
```python
import astropy.coordinates as coord
from astropy.table import QTable
from astropy.utils.data import get_pkg_data_filename
import typing
```
Type definitions:
Input Types: slice
Output Type: np.ndarray
Dependencies:
```python
def v0() -> TableType:
v1: str = get_pkg_data_filename(os.path.join('da... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: int=1) -> int:
v3 = False
while not v3:
if v2 in v1:
v2 += 1
else:
return v2
return v2 + 1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[dict, list]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[dict, list]) -> None:
v2 = {'delete': v1}
self.make_request('post', self.url, data=v2, params=self.params, headers=self.headers)
``... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
for v1 in self.collected_data.keys():
self.collected_data.update({v1: []})
``` |
Imports:
```python
from torch import autograd, Tensor
from torch.cuda.amp import autocast
from torch.cuda.amp.grad_scaler import GradScaler
from torch.nn import Flatten, GELU, Linear, Module, Sequential, Sigmoid, Unflatten
from torch.optim import Optimizer
from torch.utils.data import DataLoader
import torch
import typ... |
Imports:
```python
import uuid
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> None:
if self.session.has_root_transaction is False:
self.session.has_root_transaction = True
self.is_root = True
self.co... |
Imports:
```python
import torch
from torch import nn
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: torch.Tensor, Dict[str, torch.Tensor], int
Output Type: Tuple[torch.Tensor, Dict[str, torch.Tensor]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[types.LocalizedObjectAnnotation]
Output Type: Any
Dependencies:
```python
def v0(v1: Union[str, float]) -> float:
return round(float(v1) * 100, 1)
```
```python
def v2(v3: List[types.LocalizedObjectAnnotation], v4: str):
v5 = [v0(obj.scor... |
Imports:
```python
import cv2
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray, str, str, str, int, int, bool
Output Type: tuple
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: np.ndarray, v3: str='', v4: str='', v5: str='', v6: int=0, v7:... |
Imports:
```python
import typing
```
Type definitions:
Input Types: typing.Optional[str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: typing.Optional[str]=None):
v2 = {}
v3 = self._enabled_features if v1 is None else v1
for v4 in v3:
v2[v4] = {}
for... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: Optional[Tuple[None, str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str) -> Optional[Tuple[None, str]]:
if v1.startswith(v2):
return (None, v1[len(v2):])
return 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:
v2 = self._elb.describe_target_groups(LoadBalancerArn=v1)
assert 'TargetGroups' in v2
for v3 in v2['TargetGroups']:
if v3['Port... |
Imports:
```python
import typing
```
Type definitions:
Input Types: apsw.Connection
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: apsw.Connection) -> None:
v1.cursor().execute('create table if not exists torrent_meta (infohash text primary key collate nocase, generation int not ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: (str, str)
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> (str, str):
v2 = ['', 'encoder', 'decoder']
(v3, v4) = super().resolve_adapter_module_name_(v1)
if v3 not in v2:
raise ValueE... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Set[str]]
Output Type: List[Set[str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Set[str]]) -> List[Set[str]]:
v2 = [set('') for v3 in range(10)]
for v4 in v1:
if len(v4) == 2:
v2[1] = v4
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: np.ndarray) -> float:
if v1.sum() == 0 or v2.sum() == 0:
return 0
return v1.dot(v2) / np.linal... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.set_models({'meeting/1': {'is_active_in_organization_id': 1}, 'motion_workflow/110': {'name': 'name_Ycefgee', 'state_ids': [111, 112, 113], 'meeting... |
Imports:
```python
import os
import shutil
from pathlib import Path
import typing
```
Type definitions:
Input Types: Optional[Path], Path
Output Type: Any
Dependencies:
```python
def v0(v1: Path) -> None:
v2: Keychain = Keychain()
v3 = v2.get_all_private_keys()
if len(v3) == 0:
print("No keys are p... |
Imports:
```python
import typing
```
Type definitions:
Input Types: sublime.View, int, list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: sublime.View, v2: int, v3: list):
for v4 in v3:
if v1.match_selector(v2, v4):
return True
return False
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: QtGui.QWheelEvent
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: QtGui.QWheelEvent):
self.camera.zoom(v1.delta())
self.update()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, int]):
v1 = v1 or {}
v1 = {position.upper(): num_of_players for (v2, v3) in v1.items()}
for (v4, v5) in v1.items():
sel... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
v1 = []
v2 = random.randint(1, 100) % 2 == 0
v1.append(self.get_timeline_feed([v2 and 'is_pull_to_refresh']))
v1.append(self.ge... |
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.openDatabase():
self.execute("DELETE FROM TMSwitchModel WHERE uid = '%s';" % v1, None)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: list[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> list[str]:
v2 = list()
for v3 in v1:
v4 = self.generate_name(v3)
while v4 in v2:
v4 = self.generate_name(v3.removes... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> str:
if v1.endswith('.scala') or v1.endswith('.tribble'):
return 'parse'
else:
return 'unmarshal'
``` |
Imports:
```python
import numpy as np
from collections import defaultdict
import typing
```
Type definitions:
Input Types: Any, bool
Output Type: Any
Dependencies:
```python
def v0(v1, v2) -> np.ndarray:
(v1, v2) = np.floor(np.divide((v1, v2), 3)).astype(int)
return sudoku[v1 * 3:(v1 + 1) * 3, v2 * 3:(v2 + 1) ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: DataFrame, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: DataFrame, v2: str) -> bool:
if v1['volume'].dtype != v1[v2].dtype:
return False
if 'volume' in v2:
return True
return F... |
Imports:
```python
import plotly.express as px
import plotly.graph_objs as go
from plotly.io import templates as pio_templates
from plotly.offline import plot
import typing
```
Type definitions:
Input Types: DataFrame, Dict, str, str, str, Dict, str, Dict, Tuple, Path, bool
Output Type: Any
Dependencies:
Function Nam... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, *, v1: str='0.1', v2: str, v3: str) -> str:
v4 = self.base_url(version=v1) + f'/apps/{v2}/{v3}'
self.log.debug(f'Generated URL: {v4}')
return ... |
Imports:
```python
from pathlib import Path
import sys
import typing
```
Type definitions:
```python
v0 = ply.lex.LexToken
```
Input Types: Optional[v0], str
Output Type: NoReturn
Dependencies:
```python
def v1(v2: str) -> str:
if args.error_filename_basename:
return Path(v2).name
else:
return v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict) -> bool:
for v2 in range(len(self.and_expression)):
if not self.and_expression[v2].evaluate(v1):
return False
return True
``... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: plt.Axes, str, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any
Output Type: Any
Dependencies:
```python
def v0(v1: np.ndarray, v2: str, v3=True):
if v2 == 'xy':
v4 = 0 if v3 else 2
elif v2 == 'xz':
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[Decimal], Optional[Decimal]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Optional[Decimal], v2: Optional[Decimal]) -> bool:
if v1 is None and v2 is None:
return True
if v1 is None and v2 is... |
Imports:
```python
from collections import defaultdict
import typing
```
Type definitions:
Input Types: str
Output Type: Tuple[Set[str], Dict[str, List[str]]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> Tuple[Set[str], Dict[str, List[str]]]:
v2: Dict[str, List[str]] = defaultdict(list)
... |
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