class_docstr: used in AsymmetricAutoencoderKL
code: def forward(
      self, x: torch.FloatTensor, mask=None
  ) -> torch.FloatTensor:
      out = {}
      for l in range(len(self.layers)):
          layer = self.layers[l]
          x = layer(x)
          out[str(tuple(x.shape))] = x
          x = torch.relu(x)
      return out
  
imports: from dataclasses import dataclass
  from typing import Optional
  import numpy
  import torch
  import torch.nn
  from ..utils import BaseOutput, is_torch_version
  from ..utils.torch_utils import randn_tensor
  from .activations import get_activation
  from .attention_processor import SpatialNorm
  from .unet_2d_blocks import AutoencoderTinyBlock, UNetMidBlock2D, get_down_block, get_up_block
label_desc: Use image node_id 2 for calling the MaskConditionEncoder obj's underlying member method code with example usage: obj.forward(x, mask) and returns: out