code: def _convert_model_from_bytearray_to_object(model_bytearray):
      """Converts a tflite model from a bytearray into a parsable object."""
      model_object = tflite_schema.Model.GetRootAsModel(
          model_bytearray, 0
      )
      model_object = tflite_schema.ModelT.InitFromObj(model_object)
      model_object = copy.deepcopy(model_object)
      model_object.subgraphs[0].inputs[0] = model_object.subgraphs[
          0
      ].inputs[0]
      return model_object
  
file_path: compute-engine/larq_compute_engine/mlir/python/util.py
imports: import copy
  import flatbuffers
  import tensorflow
  from larq_compute_engine.mlir.python import tflite_schema
label_desc: Use image node_id 2 for calling a global function with example usage: _convert_model_from_bytearray_to_object(model_bytearray) and returns: model_object