code: def __init__(self, model_channels, dropout, num_heads):
      super().__init__()
      self.resblk = ResBlock(
          model_channels,
          model_channels,
          dropout,
          model_channels,
          dims=1,
          use_scale_shift_norm=True,
      )
      self.attn = AttentionBlock(
          model_channels, num_heads, relative_pos_embeddings=True
      )
  
imports: import math
  import random
  from abc import abstractmethod
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import autocast
  from TTS.tts.layers.tortoise.arch_utils import AttentionBlock, normalization
label_desc: Use image node_id 1 to create a new DiffusionLayer object from inherited base classes: TimestepBlock with example: obj = DiffusionLayer(model_channels, dropout, num_heads)