class_docstr: Layer that follows attention layer in encoder layer.
class_docstr_tok: ["Layer","that","follows","attention","layer","in","encoder","layer","."]
code: def __init__(
      self,
      io_features: int,
      intermediate_features: int,
      intermediate_dropout: float,
      output_dropout: float,
  ):
      super().__init__()
      self.intermediate_dense = nn.Linear(
          io_features, intermediate_features
      )
      self.intermediate_dropout = nn.Dropout(intermediate_dropout)
      self.output_dense = nn.Linear(intermediate_features, io_features)
      self.output_dropout = nn.Dropout(output_dropout)
  
imports: import logging
  from typing import List, Optional, Tuple
  import torch
  from torch import nn, Tensor
  from torch.nn import Module, Parameter
  from .wavlm_attention import WavLMSelfAttention
label_desc: Use image node_id 1 to create a new FeedForward object from inherited base classes: Module with example: obj = FeedForward(io_features, intermediate_features, intermediate_dropout, output_dropout)