code: def _compile_model(
      self,
      model: tf.Module,
  ):
      converter = tf.lite.TFLiteConverter.from_keras_model(model)
      tflite_model = converter.convert()
      return tflite_model
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/optimizations/compilers/tensorflow.py
imports: from typing import List, Tuple
  from nebullvm.config import QUANTIZATION_DATA_NUM
  from nebullvm.core.models import QuantizationType
  from nebullvm.operations.optimizations.compilers.base import Compiler
  from nebullvm.operations.optimizations.compilers.quantizations.tensorflow import quantize_tensorflow
  from nebullvm.operations.optimizations.compilers.quantizations.utils import check_quantization
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.transformations import MultiStageTransformation
label_desc: Use image node_id 2 for calling the TFLiteBackendCompiler obj's underlying member method code with example usage: obj._compile_model(model) and returns: tflite_model