class_docstr: ## Feedforward Network
class_docstr_tok: ["#","#","Feedforward","Network"]
docstr: :param x: has shape `[batch_size, seq_len, n_hidden]`
code: def forward(self, x: torch.Tensor):
      """
      :param x: has shape `[batch_size, seq_len, n_hidden]`
      """
      x = self.dense_h_h4(x)
      x = self.activation(x)
      x = self.dense_h4_h(x)
  
      return x
  
imports: import copy
  import math
  from typing import Dict, Optional, Set, Callable, Any, Generator, Tuple
  import torch
  from torch import nn
  from torch.cuda.amp import autocast
  from labml import monit, logger
  from labml.logger import Text
  from labml_nn.neox import checkpoint
  from labml_nn.neox.utils.cache import get_cache
label_desc: Use image node_id 2 for calling the FFNLayer obj's underlying member method code with example usage: obj.forward(x) and returns: x