code: def PytorchIPEXQuantizationModel(
      model,
      calib_data,
      q_config=None,
      input_sample=None,
      channels_last=None,
      thread_num=None,
      inplace=False,
      jit_strict=True,
      example_kwarg_inputs=None,
      enable_onednn=False,
  ):
      """
      :param model: the model(nn.module) to be transform.
      :param calib_data: calibration data is required for static quantization.
      :param q_config: describes how to quantize a layer or a part of the network
              by providing settings (observer classes) for activations and weights
              respectively.
      :param input_sample: torch tensor indicate the data sample to be used
              for tracing.
      :param channels_last: if set model and data to be channels-last mode.
      :param thread_num: the thread num allocated for this model.
      :param inplace: whether to perform inplace optimization. Default: ``False``.
      :param jit_strict: Whether recording your mutable container types.
      :param example_kwarg_inputs: keyword arguments of example inputs that will be passed
             to ``torch.jit.trace``. Default to None. Either this argument or input_sample
             should be specified when use_jit is ``True`` and torch > 2.0,
             otherwise will be ignored.
      :param enable_onednn: Whether to use PyTorch JIT graph fuser based on oneDNN Graph
             API, which provides a flexible API for aggressive fusion. Default to
             ``False``.
      """
      from .ipex_quantization_model import PytorchIPEXQuantizationModel
  
      return PytorchIPEXQuantizationModel(
          model,
          calib_data,
          q_config=q_config,
          input_sample=input_sample,
          channels_last=channels_last,
          thread_num=thread_num,
          inplace=inplace,
          jit_strict=jit_strict,
          example_kwarg_inputs=example_kwarg_inputs,
          enable_onednn=enable_onednn,
      )
  
file_path: BigDL/python/nano/src/bigdl/nano/deps/ipex/ipex_api.py
imports: from typing import Any
  from bigdl.nano.utils.common import invalidInputError
label_desc: Use image node_id 4 for calling a global function with example usage: PytorchIPEXQuantizationModel(model, calib_data, q_config, input_sample, channels_last, thread_num, inplace, jit_strict, example_kwarg_inputs, enable_onednn) and returns: PytorchIPEXQuantizationModel