code: def __init__(self, embed_dim, ffn_dim, dropout=0.1, **kwargs):
      super().__init__()
      self.layers = nn.ModuleList(
          [
              nn.Conv2d(embed_dim, ffn_dim, 1),
              nn.ReLU(),
              nn.Dropout(dropout) if dropout > 0.0 else nn.Identity(),
              nn.Conv2d(ffn_dim, embed_dim, 1),
          ]
      )
  
file_path: ml-ane-transformers/ane_transformers/reference/ffn.py
imports: import torch
  import torch.nn
  from .layer_norm import LayerNormANE
label_desc: Use image node_id 1 to create a new FFN object from inherited base classes: nn with example: obj = FFN(embed_dim, ffn_dim, dropout)