docstr: Forward of Simplified ParallelMLP.
  
  Args:
      x: :obj:`None` if pipeline rank != pippeline first rank. When :obj:`None`,
          `self.input_tensor` is taken care of by `forward_step` defined in
          apex/transformer/pipeline_parallel/schedules/common.py
docstr_tok: ["Forward","of","Simplified","ParallelMLP",".","Args",":","x",":",":","obj",":","`","None","`","if","pipeline","rank","!","=","pippeline","first","rank",".","When",":","obj",":","`","None","`",",","`","self.input_tensor","`","is","taken","care","of","by","`","forward_step","`","defined","in","apex\/transformer\/pipeline_parallel\/schedules\/common.py"]
code: def forward(
      self,
      x: Optional[torch.Tensor],
  ) -> torch.Tensor:
      """Forward of Simplified ParallelMLP.
  
      Args:
          x: :obj:`None` if pipeline rank != pippeline first rank. When :obj:`None`,
              `self.input_tensor` is taken care of by `forward_step` defined in
              apex/transformer/pipeline_parallel/schedules/common.py
      """
      # [s, b, h]
      if self.input_tensor is None:
          input = x
      else:
          input = self.input_tensor
      intermediate_parallel, bias_parallel = self.dense_h_to_4h(input)
  
      if bias_parallel is not None:
          intermediate_parallel += bias_parallel
      intermediate_parallel = self.activation_func(
          intermediate_parallel
      )
      # [s, b, h]
      output, output_bias = self.dense_4h_to_h(intermediate_parallel)
      return output
  
imports: from dataclasses import dataclass
  import datetime
  import os
  import random
  from typing import Optional, Union, List, Tuple, Callable, Dict
  import numpy
  import torch
  import torch.nn
  from apex import transformer
  from apex.transformer.tensor_parallel import ColumnParallelLinear, RowParallelLinear, scatter_to_sequence_parallel_region
  from apex.transformer.pipeline_parallel.utils import average_losses_across_data_parallel_group
  from apex.transformer.pipeline_parallel.schedules.common import Batch
  from apex.transformer.testing import global_vars
  from apex.transformer._ucc_util import HAS_UCC
label_desc: Use image node_id 3 for calling the ToyParallelMLP obj's underlying member method code with example usage: obj.forward(x) and returns: output