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 _init_weights(self):
      weight_attr = paddle.ParamAttr(
          initializer=nn.initializer.Constant(1.0)
      )
      bias_attr = paddle.ParamAttr(
          initializer=nn.initializer.Constant(0.0)
      )
      return weight_attr, bias_attr
  
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 2 for calling the EncoderLayer obj's underlying member method code with example usage: obj._init_weights() and returns: weight_attr,  bias_attr