class_docstr: FFN module optimized for Apple Neural Engine
      
class_docstr_tok: ["FFN","module","optimized","for","Apple","Neural","Engine"]
code: def __init__(self, config):
      super().__init__(config)
      self.seq_len_dim = 3
  
      setattr(
          self,
          "lin1",
          nn.Conv2d(
              in_channels=config.dim,
              out_channels=config.hidden_dim,
              kernel_size=1,
          ),
      )
  
      setattr(
          self,
          "lin2",
          nn.Conv2d(
              in_channels=config.hidden_dim,
              out_channels=config.dim,
              kernel_size=1,
          ),
      )
  
imports: from ane_transformers.reference.layer_norm import LayerNormANE
  import torch
  import torch.nn
  from transformers.models.distilbert import modeling_distilbert
label_desc: Use image node_id 1 to create a new FFN object from inherited base classes: modeling_distilbert with example: obj = FFN(config)