class_docstr: This class is a modification of the FeedForward class implemented in
  the LLaMA repo. The class has been modified for training, since the
  original one just supports inference.
code: def forward(self, x):
      return self.w2(F.silu(self.w1(x)) * self.w3(x))
  
imports: import json
  import math
  import os
  from dataclasses import dataclass
  from pathlib import Path
  from typing import Tuple, List, Union, Optional
  import deepspeed
  import torch
  import torch.distributed
  import torch.nn.functional
  import fairscale.nn.model_parallel.initialize
  from fairscale.nn.model_parallel.initialize import initialize_model_parallel
  from fairscale.nn.model_parallel.layers import ParallelEmbedding, RowParallelLinear, ColumnParallelLinear
  from torch import nn
  from transformers import AutoTokenizer
  from llama import Tokenizer
  from llama.generation import sample_top_p
label_desc: Use image node_id 2 for calling the FeedForward obj's underlying member method code with example usage: obj.forward(x) and returns: self