code: def wrapped_experimental_mlir_quantize(
      input_data_str,
      disable_per_channel,
      fully_quantize,
      inference_type,
      input_data_type,
      output_data_type,
      enable_numeric_verify,
      enable_whole_model_verify,
      denylisted_ops,
      denylisted_nodes,
      enable_variable_quantization,
  ):
      """Wraps experimental mlir quantize model."""
      return _pywrap_toco_api.ExperimentalMlirQuantizeModel(
          input_data_str,
          disable_per_channel,
          fully_quantize,
          inference_type,
          input_data_type,
          output_data_type,
          enable_numeric_verify,
          enable_whole_model_verify,
          denylisted_ops,
          denylisted_nodes,
          enable_variable_quantization,
      )
  
file_path: tensorflow-upstream/tensorflow/lite/python/wrap_toco.py
imports: from tensorflow.python import pywrap_tensorflow
  from tensorflow.python import _pywrap_toco_api
label_desc: Use image node_id 2 for calling a global function with example usage: wrapped_experimental_mlir_quantize(input_data_str, disable_per_channel, fully_quantize, inference_type, input_data_type, output_data_type, enable_numeric_verify, enable_whole_model_verify, denylisted_ops, denylisted_nodes, enable_variable_quantization) and returns: _pywrap_toco_api