code: def _apply(self, fn):
      # prevent the bias from being converted to half
      super()._apply(fn)
      self.bias = self.bias.to(torch.float32)
      return self
  
imports: import torch
  from torch_int._CUDA import linear_a8_w8_b8_o8, linear_a8_w8_bfp32_ofp32
  from torch_int.functional.quantization import quantize_per_tensor_absmax
label_desc: Use image node_id 2 for calling the W8A8BFP32OFP32Linear obj's underlying member method code with example usage: obj._apply(fn) and returns: self