code: def __init__(
      self,
      in_features: int,
      hidden_features: int,
      out_features: int,
      dropout_rate: float = 0.0,
  ) -> None:
      super().__init__(
          nn.Linear(in_features, hidden_features),
          nn.GELU(),
          nn.Dropout(dropout_rate),
          nn.Linear(hidden_features, out_features),
          nn.Dropout(dropout_rate),  # added one extra as in timm
      )
  
imports: from typing import Any, Callable, Dict, List, Optional, Tuple
  import torch
  from torch import nn
  from kornia.core import Module, Tensor
label_desc: Use image node_id 1 to create a new FeedForward object from inherited base classes: nn with example: obj = FeedForward(in_features, hidden_features, out_features, dropout_rate)