code: def analyze(
      model_path=None,
      model_content=None,
      gpu_compatibility=False,
      **kwargs,
  ):
      """Analyzes the given tflite_model with dumping model structure.
  
      This tool provides a way to understand users' TFLite flatbuffer model by
      dumping internal graph structure. It also provides additional features
      like checking GPU delegate compatibility.
  
      WARNING: Experimental interface, subject to change.
               The output format is not guaranteed to stay stable, so don't
               write scripts to this.
  
      Args:
        model_path: TFLite flatbuffer model path.
        model_content: TFLite flatbuffer model object.
        gpu_compatibility: Whether to check GPU delegate compatibility.
        **kwargs: Experimental keyword arguments to analyze API.
  
      Returns:
        Print analyzed report via console output.
      """
      if not model_path and not model_content:
          raise ValueError(
              "neither `model_path` nor `model_content` is provided"
          )
      if model_path:
          print(f"=== {model_path} ===\n")
          tflite_model = model_path
          input_is_filepath = True
      else:
          print("=== TFLite ModelAnalyzer ===\n")
          tflite_model = model_content
          input_is_filepath = False
  
      if kwargs.get("experimental_use_mlir", False):
          print(
              wrap_toco.wrapped_flat_buffer_file_to_mlir(
                  tflite_model, input_is_filepath
              )
          )
      else:
          print(
              _analyzer_wrapper.ModelAnalyzer(
                  tflite_model, input_is_filepath, gpu_compatibility
              )
          )
  
label_desc: Use image node_id 1 for calling the ModelAnalyzer obj's underlying member method code with example usage: obj.analyze(model_path, model_content, gpu_compatibility) without return types