code: def __init__(
      self, in_feat, expansion_factor, kernel_size, conv_type, dropout
  ):
      super().__init__()
  
      self.time_mix = PreNormResidual(
          fn=Mix(
              first_mix_layer=create_time_mix_layer(
                  in_feat=in_feat,
                  out_feat=in_feat,
                  kernel_size=kernel_size,
                  conv_type=conv_type,
              ),
              second_mix_layer=create_time_mix_layer(
                  in_feat=in_feat,
                  out_feat=in_feat,
                  kernel_size=kernel_size,
                  conv_type=conv_type,
              ),
              dropout=dropout,
          ),
          feature_dim=in_feat,
      )
  
      self.channel_mix = PreNormResidual(
          fn=Mix(
              first_mix_layer=create_channel_mix_layer(
                  in_feat=in_feat,
                  out_feat=expansion_factor * in_feat,
              ),
              second_mix_layer=create_channel_mix_layer(
                  in_feat=expansion_factor * in_feat,
                  out_feat=in_feat,
              ),
              dropout=dropout,
          ),
          feature_dim=in_feat,
      )
  
imports: import math
  import torch
  from torch import nn
  from nemo.collections.tts.modules.submodules import ConvNorm
  from nemo.collections.tts.modules.transformer import PositionalEmbedding
label_desc: Use image node_id 1 to create a new MixerTTSBlock object from inherited base classes: nn with example: obj = MixerTTSBlock(in_feat, expansion_factor, kernel_size, conv_type, dropout)