code: def __init__(
      self, row_block_size=1, col_block_size=4, dtype=torch.qint8
  ):
      super().__init__()
  
      if dtype != torch.qint8:
          raise NotImplementedError(
              "Linear prepacking only supports QINT8"
          )
      self.dtype = dtype
      wq = torch._empty_affine_quantized(
          [1, 1], scale=1.0, zero_point=0, dtype=torch.qint8
      )
      self.set_weight_bias(wq, None, row_block_size, col_block_size)
  
imports: from typing import Optional
  import torch
  from torch.ao.nn.quantized.modules.utils import _quantize_weight, _hide_packed_params_repr
label_desc: Use image node_id 1 to create a new LinearPackedParams object from inherited base classes: torch.nn with example: obj = LinearPackedParams(row_block_size, col_block_size, dtype)