code: def __init__(
      self,
      dim1,
      dim2,
      has_fp16_weights=True,
      memory_efficient_backward=False,
      threshold=0.0,
  ):
      super().__init__()
      self.fc1 = bnb.nn.Linear8bitLt(
          dim1,
          dim2,
          has_fp16_weights=has_fp16_weights,
          memory_efficient_backward=memory_efficient_backward,
          threshold=threshold,
      )
      self.fc2 = bnb.nn.Linear8bitLt(
          dim2,
          dim1,
          has_fp16_weights=has_fp16_weights,
          memory_efficient_backward=memory_efficient_backward,
          threshold=threshold,
      )
  
imports: from itertools import product
  import pytest
  import torch
  from torch import nn
  import bitsandbytes
label_desc: Use image node_id 1 to create a new MLP8bit object from inherited base classes: torch.nn with example: obj = MLP8bit(dim1, dim2, has_fp16_weights, memory_efficient_backward, threshold)