code: def __init__(
      self,
      in_features: int,
      out_features: int,
      bias: bool = True,
      device=None,
      dtype=None,
  ) -> None:
      factory_kwargs = {"device": device, "dtype": dtype}
      super().__init__()
      self.in_features = in_features
      self.out_features = out_features
      self.register_buffer(
          "weight",
          torch.empty((out_features, in_features), dtype=torch.int8),
      )
      self.register_buffer(
          "scales", torch.ones(out_features, dtype=torch.bfloat16)
      )
  
imports: import time
  from pathlib import Path
  import torch
  import torch.nn
  import torch.nn.functional
  from sentencepiece import SentencePieceProcessor
  from model import Transformer
label_desc: Use image node_id 1 to create a new WeightOnlyInt8Linear object from inherited base classes: torch.nn with example: obj = WeightOnlyInt8Linear(in_features, out_features, bias, device, dtype)