class_docstr: Model optimized on CPU using IntelNeuralCompressor.
  
  Attributes:
      network_parameters (ModelParams): The model parameters as batch
              size, input and output sizes.
      model (torch.fx.GraphModule): Torch fx graph model.
code: def free_gpu_memory(self):
      raise NotImplementedError(
          "NeuralCompressor does not support GPU inference."
      )
  
imports: from abc import ABC
  from pathlib import Path
  from typing import Union, Tuple, Dict, Type
  from loguru import logger
  from nebullvm.core.models import Device, ModelParams, DeepLearningFramework
  from nebullvm.operations.inference_learners.base import BaseInferenceLearner, LearnerMetadata, PytorchBaseInferenceLearner
  from nebullvm.optional_modules.neural_compressor import cfgs_to_fx_cfgs, cfg_to_qconfig
  from nebullvm.optional_modules.torch import torch, prepare_fx, convert_fx, Module, GraphModule
  from nebullvm.tools.pytorch import save_with_torch_fx, load_with_torch_fx, create_model_inputs_torch, get_torch_model_size
  from nebullvm.tools.transformations import MultiStageTransformation
  from nebullvm.tools.utils import check_module_version
label_desc: Use image node_id 1 for calling the PytorchNeuralCompressorInferenceLearner obj's underlying member method code with example usage: obj.free_gpu_memory() without return types