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Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict):
(v2, v3) = self.preprocess(v1)
v4 = self.run(v2, v3)
return v4
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, *v1) -> dict:
assert v1[3] == self.recent_response
return self.final_response
``` |
Imports:
```python
from matplotlib import pyplot as plt
import typing
```
Type definitions:
Input Types: str, int, dict, Path, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: int, v3: dict, v4: Path, v5: bool=False):
plt.figure(figsize=(3 * v2, 2), dpi=100)
for (v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, int, Any, Any, Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: int, v3=1, v4=10, v5=None) -> None:
self.__animation.scale_height(height=v2, offset=v3, milliseconds=v4)
self.__animation.start... |
Imports:
```python
from scipy import signal
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3) -> np.ndarray:
v4 = max(1, 3 * (max(v3.size, v2.size) - 1))
v5 = signal.filtfilt(b=v2, a=v3, x=v1, padtype='... |
Imports:
```python
import select
import os
import typing
```
Type definitions:
```python
v0 = Callable[[bytes], None]
```
Input Types: Popen, Optional[v0], Optional[v0], Optional[Callable[[int], None]]
Output Type: Any
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: Popen, v3: Optional[v0]=None, v... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: List[tuple], List[str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[tuple], v2: List[str]):
self.fieldnames = ['winner'] + self.fieldnames
v3 = []
v2 = [line.strip().split('\t') for ... |
Imports:
```python
import requests
import typing
```
Type definitions:
Input Types:
Output Type: Tuple[str, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Tuple[str, int]:
try:
v1 = requests.request(method='POST', url=self.token_refresh_endpoint, data=self.get_refresh_request_bo... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
v2 = {'dataset', 'dataset/imagenet', 'level1/level2/nested1', 'level1/level2/nested2', 'configs_with_defaults_list/global_package', 'configs_... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'BigInt', 'BigInt'
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'BigInt', v2: 'BigInt') -> None:
if not v1.sign or not v2.sign:
return
self._multiply_digits(v1.digits, v2.digits)
if v1.sig... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Optional[Tuple[str, str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Optional[Tuple[str, str]]:
if self._error_string:
return None
return (self._content['display_name'], self._content['licence'])... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float, Optional[int]
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float, v2: Optional[int]=2) -> float:
v1 = float(v1)
while not -180 <= v1 < 180:
v3 = 360 if v1 < -180 else -360
v1 += v3
... |
Imports:
```python
import os
import sys
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0() -> int:
v1 = os.getcwd()
v2 = v1.split('/')
if not v2:
print('cwd not found', file=sys.stderr)
return 1
if os.path.exi... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Vocabulary', List[str], List[List[str]]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Vocabulary', v2: List[str], v3: List[List[str]]) -> bool:
v4 = 0
for v5 in range(len(v2)):
if self.target... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Model):
v1: bool
v2: int
v3: List[Image]
v4: Dict[str, Localization]
v5: str
def v6(self, v7: bool) -> v0:
self.auto_enroll = v7
return self
def v8(self, v9: int) -> v0:
self.display_order = v... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str, v2: tuple):
self.key: str = v1
self.originalPosition: tuple = tuple([*v2])
self.removeFromBoard()
def v3(self):
self._setPieceInGame()
self.updateCurrentPosition(self.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: int
Dependencies:
```python
def v0(v1: list) -> int:
v2 = 0
v3 = []
v4 = 0
while v4 not in v3 and v4 != len(v1):
(v5, v6) = v1[v4].split()
v3.append(v4)
if v5 == 'acc':
v2 += int(v6... |
Imports:
```python
from copy import copy
import typing
```
Type definitions:
Input Types: list, int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: int=None, v3: int=None):
v4 = copy(v1)
if v2:
v4.insert(0, v2)
if v3:
v4.append(v3)
return ... |
Imports:
```python
import logging
from pathlib import Path
import pandas as pd
import typing
```
Type definitions:
Input Types: Dict[str, pd.DataFrame]
Output Type: Path
Dependencies:
```python
def v0() -> Path:
v1 = asksaveasfilename(initialdir='.', initialfile='entity-info.xlsx', filetypes=[('Excel', '.xlsx')])
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
super()._connect()
self.flush_connection()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
(v2, v3) = (0, len(v1) - 1)
while v2 < v3:
while v2 < v3 and (not self.isAlphaNumeric(v1[v2])):
v2 += 1
while... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict):
self._raw_device_state = v1
for (v2, v3) in v1.items():
if v2 in self._data_points:
self._data_points[v2].set_attribute_data... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = '{foo}'
with self.assertRaises(UnicodeEncodeError):
v1.encode('b64')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: commands.Context, list, dict, discord.Message, int, float, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: commands.Context, v2: list, v3: dict, v4: discord.Message, v5: int, v6: float=None, v7: str=Non... |
Imports:
```python
from collections import defaultdict
from qiskit.circuit.quantumcircuit import QuantumCircuit
from qiskit.circuit.barrier import Barrier
from qiskit.pulse.schedule import Schedule
from qiskit.scheduler.config import ScheduleConfig
from qiskit.scheduler.lowering import lower_gates
import typing
```
Typ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: pandas.Series
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2) -> pandas.Series:
v3 = getattr(self, v1)
return v3[v2]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Chem.Mol
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Chem.Mol=None):
if v1 is None:
v1 = self.positioned_mol
return [atom.GetDoubleProp('_Stdev') if atom.HasProp('_Stdev') else 0 for v2 in v1.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, torch.Tensor]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, torch.Tensor]):
v2 = {k: v.detach().cpu().item() for (v3, v4) in v1.items()}
for (v3, v4) in v1.items():
self.visd... |
Imports:
```python
import glob
import os
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
for v2 in glob.glob(f'{v1}/*/'):
if os.path.isdir(v2) and (not os.listdir(v2)):
print('removing empty directory', ... |
Imports:
```python
import ast
import typing
```
Type definitions:
Input Types: ast.Subscript
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: ast.Subscript) -> Any:
if self._marking:
self._is_subscript = True
self.generic_visit(v1)
self._is_subscript = ... |
Imports:
```python
import gzip
import logging
import os
import shutil
import stat
import typing
```
Type definitions:
Input Types: str, str, bool, bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str, v3: bool, v4: bool) -> None:
logging.info(f'Unzipping files in {v1}... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v1 = 'ivor'
return 'hello' + v1
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Container):
v1: uint64
v2: Root
v3: Slot
v4: Fork
v5: BeaconBlockHeader
v6: Vector[Root, SLOTS_PER_HISTORICAL_ROOT]
v7: Vector[Root, SLOTS_PER_HISTORICAL_ROOT]
v8: List[Root, HISTORICAL_ROOTS_LIMIT]
v9: Eth1Dat... |
Imports:
```python
from typing import Any, cast, Dict, Iterator, Iterable, List, Optional, Sequence, Sized, Tuple, Set
import typing
```
Type definitions:
Input Types: Sequence[Iterable[Optional[Any]]], Sequence[Iterable[Optional[Any]]], bool, bool
Output Type: Any
Dependencies:
```python
def v0(v1: Sequence[Sized]) -... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: [str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> [str]:
if self._sys_path is None:
return None
return [path for v1 in self._sys_path if 'lib' in v1 and v1.startswith('/')]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
v2 = v1.split(' ')
v3 = v2[0].split('-')
if len(v3[0]) == 2:
v2[0] = v3[2] + '-' + v3[0] + '-' + v3[1]
v1 = ' '.join(v2)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: t.Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> t.Dict:
if self.name.startswith('ascad'):
if self.name.endswith('_mlp'):
v2 = 'mlp'
v3 = 100
v4 = 200... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
v2 = v1.split('/')
v3 = v2[len(v2) - 1]
return self.get_issue(v3)
``` |
Imports:
```python
from rdkit import Chem
from rdkit.Chem import Draw, AllChem
from rdkit.Chem.Draw import rdMolDraw2D
import typing
```
Type definitions:
Input Types: str
Output Type: Dict
Dependencies:
```python
def v0(v1: Chem.Mol) -> nx.Graph:
v2 = mol_coords(v1)
v3 = nx.Graph()
for v4 in v1.GetAtoms()... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types: nx.DiGraph, nx.DiGraph
Output Type: Sequence['PackageName']
Dependencies:
```python
def v0(v1):
with graph.nodes[v1]['payload'] as v2:
v3 = v2.get('new_version', '')
v4 = v2.get('new_version_attempts', {}).get(v3, 0)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Dict[str, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict[str, str]:
v1: Dict[str, str] = {}
for (v2, v3) in self._data.items():
if not isinstance(v3, str):
v3 = v3()
v1[... |
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 type(v2) == str:
v2 = f"'{v2}'"
return f'{v1} != {v2}'
``` |
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.positions[v1 + '_row_start'][self.index_of_meas], self.positions[v1 + '_row_end'][self.index_of_meas], self.positions[v1 + '_col_start'][se... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tensor, Optional[Tensor]
Output Type: Tuple[int, int, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tensor, v2: Optional[Tensor]) -> Tuple[int, int, int]:
if v2 is not None:
v3 = int(v2[0])
else:
v3... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any
Output Type: 'Storyboard'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Any) -> 'Storyboard':
self.story += f'{v1}: {v2}\n'
self.add_new_line = True
return self
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=False) -> dict:
v2: dict = {}
if hasattr(self, 'auto_enroll'):
v2['autoEnroll'] = bool(self.auto_enroll)
elif v1:
v2['autoEnr... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: 'np.ndarray'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'np.ndarray', *v2, **v3) -> Any:
self.logger.info(f'{self._greetings} {v1}')
return np.random.random([v1.shape[0], 3])
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
```python
def v0(v1: int, v2: str) -> str:
if len(v2) == 0:
return v2
if v2[0] not in vowel:
v2 = v2[1:] + v2[0]
return v2 + 'ma' + 'a' * (v1 + 1)
```
Function Name: v3
Function:
```python... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> bool:
if v1 < self.__latest_slot:
return False
if v1 > self.__latest_slot:
self.__latest_slot = v1
self._logger.debug(f... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
if v1.lower().startswith('this') or v1.lower().startswith('that'):
v2 = 'D' if v1[0].isupper() else 'd'
v1 = v2 + v1[2:]
else:
i... |
Imports:
```python
import tensorflow as tf
from tensorflow.python.framework import func_graph
from tensorflow.python.framework import ops
import typing
```
Type definitions:
Input Types: Optional[str]
Output Type: str
Dependencies:
```python
def v0(v1: str) -> str:
return v1.replace('/', '#')
```
Function Name: v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v1 = v1.rstrip('/') + '/'
v2 = v1 + 'rtx_kg2.'
return {'nodes': [v2 + 'node.tsv', v2 + 'nodeprop.tsv'], 'edges': [v2 + 'edge.tsv', v2 + 'edgeprop.ts... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list[str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list[str]):
if self.primary_constraint is None:
return False
return self.primary_constraint.column_names == v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: TextIO, dict, Any
Output Type: Any
Dependencies:
```python
def v0(v1: TextIO, v2: int):
v1.write(str(v2) + '\n')
v1.write('\\raisebox{-.5\\height}{' + '\\includegraphics[scale=0.2]{./molecule_diagrams/' + str(v2) + '.pdf}}\n')
```
Function Nam... |
Imports:
```python
import os
import tempfile
import tensorflow as tf
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
with tempfile.TemporaryDirectory() as v2:
v3 = self.__make_fname(v1)
v4 = os.path.jo... |
Imports:
```python
import torch
from torch import Tensor
import random
import typing
```
Type definitions:
Input Types: int, int, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int, v3=None):
v2 = min(v1, v2)
return torch.tensor(random.sample(range(v1), v2), devic... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = '\n import bar\n import baz\n\n def foo() -> None:\n pass\n '
v2 = '\n import ... |
Imports:
```python
import torch
from torch.utils.data import DataLoader, Dataset, Sampler, Subset
import typing
```
Type definitions:
Input Types: Dataset
Output Type: DataLoader
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dataset) -> DataLoader:
v2 = self.loader_batch_size if isinstance(... |
Imports:
```python
import numpy as np
import PIL
import PIL.ImageOps
import skimage.color as sk_color
import skimage.exposure as sk_exposure
import skimage.feature as sk_feature
import skimage.filters as sk_filters
import skimage.future as sk_future
import skimage.morphology as sk_morphology
import skimage.segmentation... |
Imports:
```python
import logging
import logging.handlers
import typing
```
Type definitions:
Input Types: str, Union[logging.Logger, str]
Output Type: Any
Dependencies:
```python
def v0() -> logging.Logger:
if _defaultLogger is None:
v1 = 'No default logger instance available.'
raise Exception(v1)... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Tuple[np.ndarray, float, bool, dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray) -> Tuple[np.ndarray, float, bool, dict]:
if self.lanes and (not self.lane.on_lane(self.vehicle.position)... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, bool
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: bool=False) -> dict:
v3 = f'\n <item xsi:type="xsd:str">{v1}</item>\n <item xsi:type="xsd:bool">{v2}</item>\n ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
if v1.endswith('consist-of'):
return False
return v1.endswith('-of')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self.example_user('hamlet')
self.login(v1.email, realm=v1.realm)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tuple[Iterable[int], Iterable[Any]], np.ndarray
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tuple[Iterable[int], Iterable[Any]], v2: np.ndarray) -> None:
for ((v3, v4), v5) in zip(v1, v2):
if sel... |
Imports:
```python
import torch
from torch.autograd import Variable
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list):
v1 = torch.LongTensor(v1)
(v2, v3) = torch.sort(v1, descending=True)
return (v2, v3)
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T', bound='Union[_StorageBase, _TypedStorage]')
```
Input Types: Any, Any
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2=None, v3=False, **v4) -> v0:
v5 = self._storage.cuda(v2, v3, **v4)
return ... |
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.update({'server_name': 'example.com', 'tou_url': 'dummy-url', 'testing': True, 'dashboard_bundle... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Generator['music21.base.Music21Object', None, None]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Generator['music21.base.Music21Object', None, None]:
v1 = self.origin
while v1 is not None:
yield v1... |
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.copy()
v3[v1] = v2
return v3
``` |
Imports:
```python
import numpy as np
from pandas._libs import missing as libmissing
from pandas.compat import np_version_under1p17
from pandas.core.nanops import check_below_min_count
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray, bool
Output Type: Any
Dependencies:
```python
def v0(v1: Call... |
Imports:
```python
import copy
import typing
```
Type definitions:
Input Types: str, str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3):
v4 = copy.deepcopy(self.config_dict)
v4[v1][v2] = v3
if self._config_legal(v4, self.config_schema):
... |
Imports:
```python
import colorsys
from matplotlib.colors import ListedColormap
import typing
```
Type definitions:
Input Types: tk.Event
Output Type: None
Dependencies:
```python
def v0(v1: float) -> ListedColormap:
return ListedColormap([colorsys.hsv_to_rgb(v1, saturation / 255, 1) for v2 in range(255)])
```
```... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> int:
assert os.path.isdir(v1), 'The directory {filedir} is not accessible.'
if os.path.isfile(os.path.join(v1, 'features.tsv.gz')):
... |
Imports:
```python
import logging
import os
import re
import sklearn
import sys
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1):
return 'unk... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes
Output Type: Dict[str, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: bytes) -> Dict[str, float]:
v2 = {}
for v3 in v1.decode().splitlines():
v4 = v3.split()
if v4[0] != '#':
v2.update(... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[Tuple[tf.Tensor, ...], Tuple[np.ndarray, ...]]
Output Type: Dict[Text, tf.Tensor]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[Tuple[tf.Tensor, ...], Tuple[np.ndarray, ...]]) -> Dict[Text, tf.Tensor]:
self._tra... |
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 callable(self._Response):
return self._Response(v1)
return self._Response
``` |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types:
Output Type: tuple
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> tuple:
v1 = [self.buffers[i].sample_all() for v2 in range(self.rollout_num)]
return (torch.cat([item[0] for v3 in v1], dim=0), torch.cat([v3[... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, psycopg.Cursor
Output Type: Any
Dependencies:
```python
def v0(v1: dict, v2: psycopg.Cursor):
v3 = v1.get('players')
if v3 == None:
return None
for v4 in v3:
v2.execute('\n INSERT INTO involved_player (even... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
try:
v2: int = int(v1)
if v2 % 1000 == 0:
return f'{int(v2 / 1000)} kV'
return f'{v1} V'
except ValueError:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
if isinstance(v1, str):
v2 = True if v1 in self.task_list else False
else:
v2 = False
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Tuple[str, bool]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Tuple[str, bool]:
while True:
v1 = self.__FH.readline()
self.__pos = self.__FH.tell()
if v1 == '':
return ('', ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=None):
print()
if v1 is None:
self._help_all()
else:
self._help_single(v1)
print()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.in_channel is not None and self.ip_consuming_tag is not None:
self.stop_consuming(self.in_channel, self.ip_consuming_tag)
return
``` |
Imports:
```python
import sys
from ast import literal_eval
import typing
```
Type definitions:
Input Types: dict, tuple
Output Type: Tuple[dict, list]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict, v2: tuple=('gpu', 'save')) -> Tuple[dict, list]:
v3 = []
v4 = v1.copy()
(v5, v6) = (No... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Mapping[str, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, **v1: str) -> Mapping[str, str]:
v2 = dict(self.params, **v1)
if self.password is not None:
v2['password'] = self.password
return v2
... |
Imports:
```python
import math
import typing
```
Type definitions:
Input Types: np.datetime64
Output Type: float
Dependencies:
```python
def v0(v1: SortedDict, v2: Any) -> int:
v3 = len(v1)
if not v3:
return -1
v4 = v1.bisect_left(v2)
if v4 == v3:
return v3 - 1
if v1.keys()[v4] != v... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> bytes:
if '\r' in v1:
raise ValueError('Snapshot testing strings containing "\\r" is not supported.\nTo snapshot test non-standard new... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
return self.command
pass
``` |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: list
Dependencies:
```python
def v0(v1: list, v2: list, v3: list, v4: int) -> int:
if random.randrange(0, 2) == 1:
(v1, v2) = (v2, v1)
v5 = 0
v6 = 0
v7 = 0
for v8 in range(4):
... |
Imports:
```python
import numpy as np
import pandas as pd
import typing
```
Type definitions:
Input Types: Union[List, np.ndarray, pd.Series], dt.DataType, Optional[pd.Index]
Output Type: pd.Series
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[List, np.ndarray, pd.Series], v2: dt.DataType, v3: ... |
Imports:
```python
import argparse
import re
import sys
import typing
```
Type definitions:
Input Types: str, int, Sequence[Sequence[int]], Sequence[str], Sequence[Sequence[str]], Sequence[str]
Output Type: argparse.Namespace
Dependencies:
```python
def v0(v1: str) -> Sequence[str]:
if v1 == '[]':
return [... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = re.findall('{{pipelineparam:op=([\\w\\s_-]*);name=([\\w\\s_-]+);value=(.*?);type=(.*?);}}', v1)
if len(v2) == 0:
v2 = re.findall(... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Field, List[str]
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Field, v2: List[str]) -> List[str]:
v3 = []
v4 = v1.name + '.'
v5 = len(v4)
for v6 in v2:
if v6.startswith(v4):
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: object
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> object:
v1 = np.array(range(self.npop), dtype=np.float)
v2 = 1 / (np.sqrt(2 * np.pi) * self.q * float(self.npop)) * np.square(np.exp(-... |
Imports:
```python
import typing
```
Type definitions:
Input Types: zarr.Group, int
Output Type: Tuple[Tuple[slice, slice], npt.NDArray]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: zarr.Group, v2: int) -> Tuple[Tuple[slice, slice], npt.NDArray]:
v3 = v1['/0'][v2, 0, ...]
(v4, v5) = v3.nonze... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> list:
v1 = []
for v2 in self.dict:
v1.append((v2, self.dict[v2]))
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict):
if v1.get('possibly_sensitive'):
return v1.get('possibly_sensitive')
return False
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> float:
v1 = self.bandwidth_scale
v2 = self._x @ self._x_weights
v3 = v2.shape[0]
v4 = int(np.ceil(4 * (v3 / 100) ** self.rate))... |
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