code: def __init__(
      self, dim: int, hidden_dim: int, dropout: float = 0.0
  ) -> None:
      super().__init__()
      self.net = nn.Sequential(
          nn.Linear(dim, hidden_dim),
          nn.SiLU(),
          nn.Dropout(dropout),
          nn.Linear(hidden_dim, dim),
          nn.Dropout(dropout),
      )
  
imports: from typing import Any, Dict, 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: Module with example: obj = FeedForward(dim, hidden_dim, dropout)