code: def __init__(
      self, blocks, norm_layer, layer_norm_first, layerdrop, dropout
  ):
      super().__init__()
      self.blocks = blocks
      self.norm = norm_layer
      self.layer_norm_first = layer_norm_first
      self.layerdrop = layerdrop
      self.dropout = nn.Dropout(dropout, inplace=True)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import numpy
  from dataclasses import dataclass
  from fairseq.modules import LayerNorm, SamePad, SamePad2d, TransposeLast
label_desc: Use image node_id 1 to create a new BlockEncoder object from inherited base classes: nn with example: obj = BlockEncoder(blocks, norm_layer, layer_norm_first, layerdrop, dropout)