text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
Input Types: mirpb.MirAnnotations
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: mirpb.MirAnnotations) -> None:
v2 = list(v1.task_annotations.keys())
if len(v2) == 1:
v1.head_task_id = v2[0]
elif len(v2) > 1:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float) -> float:
v2 = self.gas_model.env.get_oxygen_volume_of_air(v1)
v3 = self.gas_model.calc_volume_to_mol(v2)
v4 = self.isobutane_needed_for_... |
Imports:
```python
import numpy as np
from numpy import ndarray
import typing
```
Type definitions:
Input Types: Any, Any, Any, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3, v4: bool=False):
v5 = np.log(v2 / v1) / np.log(v3)
if v4:
v5 = v5 + 1
v6 = np... |
Imports:
```python
import typing
```
Type definitions:
Input Types: hammer_tech.Library
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: hammer_tech.Library):
if v1.provides is not None:
for v2 in v1.provides:
if v2.lib_type is not None and v2.lib_type == 'techno... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> int:
if len(v1) == 0:
return 0
v2 = 0
while v2 < len(v1) - 1 and v1[v2] <= v1[v2 + 1]:
if v1[v2] == v1[v2 + 1]:
for v... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Operation):
v1: str = '/iam/v3/admin/namespaces/{namespace}/users/{userId}/permissions/{resource}/{action}'
v2: str = 'DELETE'
v3: List[str] = []
v4: List[str] = ['application/json']
v5: Optional[str] = 'bearer'
v6: str = ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self._setup_device()
if self._plugin_debug_message is None:
self._display_setup_success_results()
else:
self._display_setup_failu... |
Imports:
```python
from PIL import Image
import typing
```
Type definitions:
Input Types: str, str, bool, int, int
Output Type: None
Dependencies:
```python
def v0(v1: Image, v2: int, v3: int) -> Image:
return v1.resize((v2, v3))
```
Function Name: v4
Function:
```python
def v4(v5: str, v6: str, v7: bool=False, v8... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: int
Output Type: tf.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> tf.Tensor:
v2 = tf.fill([v1, v1], float(v1))
for v3 in tf.range(v1):
v2 -= tf.linalg.band_part(tf.ones((v1, v1))... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Dict]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Dict]) -> None:
for v2 in v1:
if len(v1[v2]['internal_buffer']) == 0:
pass
elif len(self.inputs[v2]['inte... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: float
Output Type: float
Dependencies:
```python
def v0(v1: float) -> float:
return 12.39842 / v1
```
```python
def v2(v3: float, v4: float, v5: float, v6: float) -> float:
v7 = v3 - v4
return v5 * (1 / np.cos(v7) - 1) +... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types: str, Any
Output Type: str
Dependencies:
```python
def v0() -> Redis:
return get_redis_connection()
```
Function Name: v1
Function:
```python
def v1(v2: str, v3=100) -> str:
v4 = v0()
v2 = f'mysql:{v2}:id'
return str(v4.in... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[float, int]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[float, int]) -> str:
for v2 in ['bytes', 'KB', 'MB', 'GB', 'TB']:
if v1 < 1024.0:
return f'{v1:,.2f} {v2}'
v1 /= 1... |
Imports:
```python
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.axes import Axes
from matplotlib.gridspec import GridSpec
from matplotlib.offsetbox import AnchoredText
from numpy.typing import NDArray
import typing
```
Type definitions:
Input Types: Axes, int, int, Sequence[str | int | float], in... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any, Any
Output Type: Any
Dependencies:
```python
def v0(v1, v2):
v3 = {'file': 'isfile', 'dir': 'isdir', 'link': 'islink', 'mount': 'ismount', 'abspath': 'isabs', 'abs': 'isabs', 'exist': 'exists', 'f': 'isfile', 'd': 'isdir', 'e': 'exists'}... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor):
v2 = False
if self.check_finite and (not torch.isfinite(v1)):
v2 = True
v3 = f'Monitored metric {se... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: list
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list) -> None:
if self.sampling:
v2 = []
for v3 in v1:
v2.append(self.sample(v3['x'], v3['y']))
for (v4, (v5, v6... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: List, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List, v2: int):
for v3 in v1:
if abs(v3['value']) > v2:
v3['value'] = np.sign(v3['value']) * v2
``` |
Imports:
```python
import operator
import typing
```
Type definitions:
Input Types: dict, dict, str
Output Type: list[float]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict, v2: dict, v3: str) -> list[float]:
v4 = 0
v5 = 0
if v2['date'] > v1['date']:
v4 = 1
if v2['date'] < ... |
Imports:
```python
import cv2
import typing
```
Type definitions:
Input Types: np.ndarray, List[Any]
Output Type: None
Dependencies:
```python
def v0(v1: np.ndarray, v2: List[Tuple[int]], v3: int) -> None:
v4 = len(v2)
for v5 in range(v4):
cv2.line(v1, v2[v5], v2[(v5 + 1) % v4], PRIMARY_PALETTE[(v3 + 1... |
Imports:
```python
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]):
if self.timescale == 'iter':
v2 = self._bs_schedule_fn(v1['iter_cnt'])
self._train_data.batch_size = v2
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Tensor], Dict[str, Union[Tensor, List[Tensor], Dict[str, Tensor]]]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[Tensor], v2: Dict[str, Union[Tensor, List[Tensor], Dict[str, Tensor]]]):
v3 = self.... |
Imports:
```python
import keras
from keras.models import load_model
from keras.callbacks import CSVLogger
from keras.callbacks import ModelCheckpoint
from keras import metrics
import typing
```
Type definitions:
Input Types: int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: bool):
v3 = self._checkGameRequest(v1)
if v3:
self.db.makeRequest('DELETE FROM gameRequests WHERE (discordID = ? OR discord2ID = ... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(ItemBase):
def __init__(self, v1: Tensor):
self._px = v1
self._logit_px = None
self._flow = None
self._affine_mat = None
self.sample_kwargs = {}
def v2(self, **v3) -> 'ImageBase':
"""Set p... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0() -> None:
print('Your input was not valid. Try again.\n')
```
Function Name: v1
Function:
```python
def v1(self) -> None:
while True:
try:
v2: str = input('Save path for th... |
Imports:
```python
import typing
```
Type definitions:
Input Types: nn.Variable
Output Type: nn.Variable
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: nn.Variable) -> nn.Variable:
v2 = self.all_quantiles(v1)
v3 = self._argmax_q_from_quantiles(v2)
return self._quantiles_of(v2, v3)
``... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> None:
if self._server is None:
await self.open()
assert self._server is not None
async with self._server:
await self._server.serv... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, map
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: map):
(v3, v4) = v1.split(' ')
v3 = float(v3)
if int(v3) == v3:
v3 = int(v3)
if v4 not in v2:
raise ValueError(f'unit {v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
self._training_results[v1] = []
self._validation_results[v1] = []
self._training_summaries[v1] = []
self._validation_summaries[v1] = []
``... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'TimeDeltaLike'
Output Type: 'LedgerMetadata'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'TimeDeltaLike') -> 'LedgerMetadata':
if self._cached_metadata is not None:
return self._cached_metadata
if self._pool ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame()
Output Type: pd.DataFrame()
Dependencies:
```python
def v0(v1: pd.Series, v2: str) -> str:
if v1['is_complex{}'.format(v2)]:
return 'complex:{}'.format(v1['name{}'.format(v2)])
return 'simple:{}'.format(v1['name{}'.forma... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
global latest_release
v1 = self.read_body()
self.send_response(200)
self.end_headers()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame) -> pd.DataFrame:
v1 = v1.dropna(subset=['Year'])
return v1
``` |
Imports:
```python
import torch
from torch.utils import tensorboard
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, Optional[torch.Tensor], Sequence[int]
Output Type: dict[int, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: torch.Tensor, v3: Option... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list[int], int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list[int], v2: int) -> int:
v3 = 0
v4 = 0
for v5 in v1:
v3 += v5
if v5 > v4:
v4 = v5
if v2 == 1:
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Union[int, list, np.ndarray, range]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[int, list, np.ndarray, range]) -> None:
if isinstance(v1, int) and v1 < 1:
raise Exception... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self.get_datasets()
v2 = self.client.project
if v1:
print('Datasets in project {}:'.format(v2))
for v3 in v1:
pr... |
Imports:
```python
import copy
import typing
```
Type definitions:
Input Types: Tuple[str, object]
Output Type: 'AbstractEnv'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tuple[str, object]) -> 'AbstractEnv':
(v2, v3) = v1
v4 = copy.deepcopy(self)
for v5 in v4.road.vehicles:
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray) -> np.ndarray:
v1 = np.append(v1, self.bodyinfo)
return v1
``` |
Imports:
```python
import dask
import dask.array as da
import dask.dataframe as dd
import numpy as np
import pandas as pd
from dask.utils import parse_bytes
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict):
v2 = self.... |
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()
if len(v2) == 1:
v3 = self.morph.parse(v1)[0].normalized.word
elif len(v2) == 2:
v4 = self.morph.parse(v2[1])[... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Residue], List[Residue]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Residue], v2: List[Residue]) -> None:
for v3 in v2:
v4 = v3.internal_coord
for v5 in v1:
v6 = v5.intern... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: Any, tf.keras.Model, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: tf.keras.Model, v3=None):
(v4, v5) = v1
v6 = self.inference_step(v4, v2)
v7 = self.build_losses(lab... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(object):
v1 = ['coordinates', 'is_extremity', 'is_outdated', 'coordinates_translated', 'angle_representation', 'distance_to_origin']
def __init__(self, v2):
self.coordinates = np.array(v2)
self.is_extremity: bool = False
... |
Imports:
```python
from queue import Queue
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1=0, v2=None, v3=None):
self.val = v1
self.left = v2
self.right = v3
```
Input Types: v0
Output Type: Any
Dependencies:
Function Name: v4
Function:
```python
def v4(self, ... |
Imports:
```python
from io import StringIO, BytesIO
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.output.close()
self.output = StringIO()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Node'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Node'):
if v1 == None:
return
self.result.append(v1.val)
for v2 in v1.children:
self.walk(v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: int) -> bool:
if v1 != '\\' and v2 == '"':
self._is_in_string = not self._is_in_string
if self._is_in_string and se... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict):
print('Saving')
if self.connected():
self.__store(v1)
else:
self.__enqueue(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int]) -> int:
v2 = [0] * 60
v3 = 0
for v4 in v1:
v3 += v2[-v4 % 60]
v2[v4 % 60] += 1
return v3
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
```python
v0 = Tuple[np.ndarray, float, bool, Dict]
```
Input Types: List[Any]
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: List[Any]) -> v0:
if self._flattener is not None:
v2 = self._flattene... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> bool:
v2 = ['train', 'test', 'cg/', 'loss']
return any([v1.startswith(prefix) for v3 in v2])
``` |
Imports:
```python
import numpy
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = numpy.loadtxt(v1, str, delimiter='\t')
for v3 in range(0, len(v2)):
v4 = v2[v3].split(',')[0].split(' ', 1)[1]
v2[v3] ... |
Imports:
```python
import itertools
import typing
```
Type definitions:
Input Types: dict, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict, v2: str):
v3 = []
v4 = [v1.get('id')]
if v2:
v4 += [v2]
try:
v5 = self.stix_parser.parse(v1.get('pa... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, float
Output Type: Union[float, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: float) -> Union[float, str]:
if v1 == -1:
v3 = 'ALL'
else:
v3 = v2
return v3
``` |
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.grant:
v2 = self.get_grant(v1)
for v3 in v2.tokens:
if v3.replaced or not v3.is_valid():
v2.de... |
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 = {'Key': v1, 'Value': v2}
self.tags.append(v3)
return self
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
v1 = v1.replace(':*', '')
v1 = v1.replace('%20', '-')
v1 = v1.replace(' ', '-')
v1 = v1.replace('/', '')
v1 = v1.replace('&in=', '_')... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, dict, int, bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict, v2: dict, v3: int, v4: bool) -> None:
self.gateway.write_log('结算信息确认成功')
self.reqid += 1
self.reqQryInstrument({}, self.req... |
Imports:
```python
from pathlib import Path
from functools import partial
from multiprocessing.pool import Pool
from tqdm import tqdm
import os
import typing
```
Type definitions:
Input Types: Path, Any
Output Type: Any
Dependencies:
```python
def v0(v1: dict):
v2 = v1.get('inpath')
v3 = v1.get('outpath')
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if not self.batch:
print()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Iterable
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Iterable) -> int:
if hasattr(v1, '__len__'):
return len(v1)
else:
return len(list(v1))
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'WikipediaPage'
Output Type: 'WikipediaPage'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'WikipediaPage') -> 'WikipediaPage':
v2 = {'action': 'query', 'list': 'categorymembers', 'cmtitle': v1.title, 'cmtype': 'page', 'cml... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: Path) -> None:
self._path = v1
self._python = str(self._path.joinpath('Scripts/python.exe' if WINDOWS else 'bin/python'))
@property
def v2(self):
return self._path
@classmethod
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
async def v0(v1: connection.TextWriter, v2: Path, v3: Sequence[lsp.Diagnostic]) -> None:
LOG.debug(f'Publish diagnostics for {v2}: {v3}')
await lsp.write_json_rpc(v1, json_rpc.Request(method='textDocu... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any
Output Type: Tuple[np.datetime64, np.datetime64]
Dependencies:
```python
def v0(v1: Optional[Union[np.datetime64, str]]) -> np.datetime64:
if isinstance(v1, str):
return np.datetime64(v1)
return v1
```
Function N... |
Imports:
```python
import logging
import os
import typing
```
Type definitions:
Input Types: Any, Path, Path, Path, Any, Any
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: str, v3: str, v4, v5):
logging.info(f'saving condensed video to {v5}')
v6 = ffmpeg.probe(v1, cmd='ffprobe')
v7 = int(v6['... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1, v2, v3, v4, v5):
if v1 == len(v2):
v5.append(v4)
return
for v6 in range(v1, len(v2)):
if v3[v1][v6]:
v0(v6 + 1, v2, v3, v4 + [v2[v1:v6 + 1]], v5)
```
F... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: str):
if self.shift_exist(v1, v2):
v3 = v1.get_stream(v2)
v4 = v3['stream_properties']['sync']['frame_shift']
return v4
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(_SubParsersAction):
v1 = ()
def v2(self, v3: str, **v4) -> ArgumentParser:
v5 = super().add_parser(v3, **v4)
v5.cmd_prefix = (*self.cmd_prefix, v3)
return v5
def __call__(self, v6, v7, v8, v9, **v10):
... |
Imports:
```python
import os
import pandas as pd
from tqdm import tqdm
from datasets import ClassLabel, load_dataset, load_metric
import typing
```
Type definitions:
Input Types: Any
Output Type: pd.DataFrame
Dependencies:
```python
def v0(v1) -> pd.DataFrame:
v2 = []
for (v3, v4) in enumerate(tqdm(v1)):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float=0) -> np.ndarray:
v2 = self.transformation_matrix_2D(v1)
v3 = self.S_reduced
v4 = v2.T.dot(v3).dot(v2)
return v4
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, bytes
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: bytes):
v3 = self.http_request(f'/images/{v1}.mp4', 'PUT', v2, 'video/mp4')
if v3.status_code != 204:
print(f'Error updating vid... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
global contenidoSym
v2 += v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Callable, dict
Output Type: Future
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: Callable, *v3: Any, v2: dict=None, **v4: Any) -> Future:
if self.client is None:
raise ValueError('This executor has not been st... |
Imports:
```python
import torch
import torch.nn as nn
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor
Output Type: Tuple[torch.nn.utils.rnn.PackedSequence, torch.Tensor]
Dependencies:
Function Name: v0
Function:
```py... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass
class v0:
v1: int
v2: int
```
Input Types:
Output Type: v0
Dependencies:
Function Name: v3
Function:
```python
def v3(self) -> v0:
with self.targeting_this_textinfo():
return self.controlPipe._get_coordinates()
``` |
Imports:
```python
import torch
import torch.nn.functional as F
import torch.distributions as D
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, float, str
Output Type: torch.Tensor
Dependencies:
```python
def v0(v1: torch.Tensor, v2: float, v3: bool=False, v4: str='sum') -> torch.Tensor:
... |
Imports:
```python
from glob import glob
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
v2 = glob(v1)
for v3 in v2:
self.add_file(v3)
``` |
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 range(self.siteCount()):
v1.append(self.getSiteState(v2))
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Sequence[str]
Dependencies:
Function Name: v0
Function:
```python
def v0() -> Sequence[str]:
with open(u'requirements.txt') as v1:
return [x.strip() for v2 in v1 if not v2.startswith('#')]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> str:
v1.drop(columns=['TIME', 'CRS', 'heading_angle', 'steering_angle', 'velocity'], inplace=True)
return v1.to_json(orient='records')
``` |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray, np.ndarray, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: np.ndarray, v3: np.ndarray, v4: int):
logging.debug(f'assemble() element {v4}')
v5 = v3.sha... |
Imports:
```python
from collections import Counter
import collections
import typing
```
Type definitions:
Input Types: collections.Counter, float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: collections.Counter, v2: float):
v3 = Counter()
for ((v4, v5, v6), v7) in v1.most_co... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[sparse.csr_matrix, np.ndarray], Union[np.ndarray, dict], Optional[Union[np.ndarray, dict]]
Output Type: 'BiKNN'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[sparse.csr_matrix, np.ndarray], v2: Union[np.ndarray, dic... |
Imports:
```python
from PIL import ImageDraw, Image
import typing
```
Type definitions:
Input Types: List[Tuple[int, int, int, int]], Image.Image
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Tuple[int, int, int, int]], v2: Image.Image) -> None:
v3 = ImageDraw.Draw(v2)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: testing.FlaskClient, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: testing.FlaskClient, v2):
v3 = v1.post('tasks/', json=v2)
assert v3.status_code == 401
``` |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, Pattern, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Pattern, v3: str) -> str:
v4 = re.findall(v2, v1)
return self.replace_all(v1, v4, v3)
``` |
Imports:
```python
import argparse
import collections
import typing
```
Type definitions:
Input Types:
Output Type: Optional[int]
Dependencies:
```python
def v0(v1: str) -> int:
with open(v1, 'r', encoding='utf=8') as v2:
v3 = 0
for v4 in v2:
v3 += 1
return v3
```
```python
def v5(... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, 'VisitCallback', 'VisitCallback'
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: 'VisitCallback', v3: 'VisitCallback') -> bool:
v4 = ''
if self.ctx.corpus.block_declared_path_changes is Fal... |
Imports:
```python
import matplotlib.pyplot as plt
from matplotlib import colors as mcolors
from matplotlib.collections import LineCollection
import typing
```
Type definitions:
Input Types:
Output Type: (plt.Figure, plt.Axes)
Dependencies:
Function Name: v0
Function:
```python
def v0() -> (plt.Figure, plt.Axes):
... |
Imports:
```python
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]={}):
if not len(v1.items()) > 0:
print('[_apply_config] Config params was provided empty. No changes applied.')
re... |
Imports:
```python
import csv
import os
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if not self.overwrite and os.path.exists(self._filepath):
with open(self._filepath, 'r') as v1:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Iterable[Tuple[str, str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Iterable[Tuple[str, str]]:
yield ('-codec:v', 'prores_ks')
if self.spoof_vendor:
yield ('-vendor', 'apl0')
if self.qscale ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
if v1 not in self.layer_manager.shown_layer_names:
self.layer_manager.show_layer(v1)
self.canvas.setLayers(self.layer_manager.shown_layers... |
Imports:
```python
import traceback
import typing
```
Type definitions:
Input Types: str, str, Callable[[], object]
Output Type: Optional[object]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: Callable[[], object]) -> Optional[object]:
try:
return v3()
except Ex... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: tuple[np.ndarray, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=None) -> tuple[np.ndarray, int]:
if v1 is None:
v1 = self.scales[-1]
return (self[::v1, ::v1], v1)
``` |
Imports:
```python
import torch
from torch import Tensor
import typing
```
Type definitions:
Input Types: Tensor, Tensor, bool
Output Type: Tensor
Dependencies:
```python
def v0(v1: Tensor, v2: Tensor, v3: bool=False) -> Tensor:
with torch.no_grad():
if v3:
(v1, v4) = torch.sort(v1)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str], List[str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[str], v2: List[str]):
v3 = {}
for (v4, v5) in enumerate(v1):
v6 = 0
v7 = 5
while v7 < len(v2):
v8 = ... |
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