code: def forward_step(self, *inputs):
      if self.channels_last:
          inputs = tuple(
              map(
                  lambda x: x.to(memory_format=torch.channels_last),
                  inputs,
              )
          )
      return self.model(*inputs)
  
file_path: BigDL/python/nano/src/bigdl/nano/pytorch/low_precision/jit_int8_model.py
imports: from bigdl.nano.pytorch.context_manager import generate_context_manager
  from bigdl.nano.pytorch.model import AcceleratedLightningModule
  from bigdl.nano.utils.pytorch import jit_convert
  from bigdl.nano.utils.common import compare_version
  import torch
  from torch.ao.quantization import QConfig, get_default_qconfig_mapping
  from torch.quantization.quantize_fx import prepare_fx, convert_fx
  import operator
  from collections.abc import Sequence
label_desc: Use image node_id 3 for calling the PytorchJITINT8Model obj's underlying member method code with example usage: obj.forward_step() and returns: self