class_docstr: Encoder Layer
  Encoder layer contains attention, norm, mlp and residual
  Attributes:
      hidden_size: transformer feature dim
      attn_norm: nn.LayerNorm before attention
      mlp_norm: nn.LayerNorm before mlp
      mlp: mlp modual
      attn: attention modual
code: def forward(self, x):
      h = x
      x = self.attn_norm(x)
      x = self.attn(x)
      x = self.drop_path(x)
      x = x + h
  
      h = x
      x = self.mlp_norm(x)
      x = self.mlp(x)
      x = self.drop_path(x)
      x = x + h
  
      return x
  
imports: import copy
  import paddle
  import paddle.nn
  from disco_diffusion_ernievil_base.vit_b_16x.ernievil2.transformers.droppath import DropPath
label_desc: Use image node_id 3 for calling the EncoderLayer obj's underlying member method code with example usage: obj.forward(x) and returns: x