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from typing import List, Callable
from torch import Tensor
import random
from hw_asr.augmentations.base import AugmentationBase
class SequentialRandomApply(AugmentationBase):
def __init__(self, augmentation_list: List[Callable], p: float = 0.5):
self.augmentation_list = augmentation_list
self.p = p
def __call__(self, data: Tensor) -> Tensor:
x = data
for augmentation in self.augmentation_list:
if random.random() < self.p:
x = augmentation(x)
return x