code: def load_inc_model(path, model, framework, input_sample=None):
      if framework == "pytorch":
          from .pytorch.quantized_model import PytorchQuantizedModel
  
          # only ipex quantization needs example_inputs
          return PytorchQuantizedModel._load(
              path, model, example_inputs=input_sample
          )
      elif framework == "tensorflow":
          from .tensorflow.model import KerasQuantizedModel
  
          return KerasQuantizedModel._load(path, model)
      else:
          invalidInputError(
              False,
              "The value {} for framework is not supported."
              " Please choose from 'pytorch'/'tensorflow'.",
          )
  
imports: import operator
  from bigdl.nano.utils.common import invalidInputError
  from bigdl.nano.utils.common import compare_version
label_desc: Use image node_id 1 for calling a global function with example usage: load_inc_model(path, model, framework, input_sample) and returns: PytorchQuantizedModel, KerasQuantizedModel