code: def forward(self, x: torch.Tensor):
      autocast_dtype = get_autocast_dtype(x)
      if x.device.type == "xpu":
          # force to use bf16 on gpu
          x = x.to(torch.bfloat16)
      elif autocast_dtype is not None:
          x = x.to(autocast_dtype)
      result = super().forward(x)
  
      if (
          self.disable_adapters
          or self.active_adapter not in self.lora_A.keys()
      ):
          return result
      elif self.r[self.active_adapter] > 0:
          result = result.clone()
          if autocast_dtype is None and x.device.type == "cpu":
              expected_dtype = result.dtype
              x = x.to(self.lora_A[self.active_adapter].weight.dtype)
              output = (
                  self.lora_B[self.active_adapter](
                      self.lora_A[self.active_adapter](
                          self.lora_dropout[self.active_adapter](x)
                      )
                  ).to(expected_dtype)
                  * self.scaling[self.active_adapter]
              )
          else:
              output = (
                  self.lora_B[self.active_adapter](
                      self.lora_A[self.active_adapter](
                          self.lora_dropout[self.active_adapter](x)
                      )
                  )
                  * self.scaling[self.active_adapter]
              )
          result += output
      return result
  
imports: import torch
  from torch.nn import Linear, Embedding
  from bigdl.llm.transformers.low_bit_linear import LowBitLinear, BF16Linear, get_qk_size
  from peft.tuners.lora import LoraLayer
  from bigdl.llm.utils.common import invalidInputError
  from bigdl.llm.transformers.utils import get_autocast_dtype
  from bigdl.llm.ggml.quantize import ggml_tensor_qtype
  import functools
  from bigdl.llm.transformers import training_patch
  from peft.tuners.lora import LoraModel
  from peft.tuners.lora import LoraConfig
  from dataclasses import dataclass, field
  from peft.mapping import PEFT_TYPE_TO_CONFIG_MAPPING
label_desc: Use image node_id 2 for calling the LoraBF16Linear obj's underlying member method code with example usage: obj.forward(x) and returns: result, result