class_docstr: Video Augmentation for batched video input: input_signal shape (B, C, T, H, W) 
class_docstr_tok: ["Video","Augmentation","for","batched","video","input",":","input_signal","shape","(","B",",","C",",","T",",","H",",","W",")"]
code: def forward(self, input_signal, length):
      if self.training:
          augments = self.training_augments
      else:
          augments = self.inference_augments
  
      output_signal = input_signal
  
      for augment in augments:
          if isinstance(augment, VideoFrameMasking) or isinstance(
              augment, SpatialVideoMasking
          ):
              output_signal = augment(output_signal, length)
          else:
              output_signal = augment(output_signal)
  
      return output_signal
  
file_path: NeMo/nemo/collections/multimodal/speech_cv/modules/video_augment.py
imports: import random
  from collections import OrderedDict
  import torch
  from torch import nn
  from nemo.core.classes.module import NeuralModule
  from nemo.core.neural_types import NeuralType, VideoSignal
label_desc: Use image node_id 4 for calling the VideoAugmentation obj's underlying member method code with example usage: obj.forward(input_signal, length) and returns: output_signal