code: def __init__(self, tflite_file: bytes, device: Device, **kwargs):
      super(TFLiteBackendInferenceLearner, self).__init__(**kwargs)
      self.tflite_file = tflite_file
      self.interpreter = tf.lite.Interpreter(model_content=tflite_file)
      self.device = device
  
imports: import pickle
  from pathlib import Path
  from typing import Tuple, Union, Dict, Type
  from nebullvm.config import TENSORFLOW_BACKEND_FILENAMES
  from nebullvm.core.models import DeviceType, Device, ModelParams
  from nebullvm.operations.inference_learners.base import TensorflowBaseInferenceLearner, LearnerMetadata
  from nebullvm.optional_modules.tensorflow import tensorflow
label_desc: Use image node_id 1 to create a new TFLiteBackendInferenceLearner object from inherited base classes: TensorflowBaseInferenceLearner with example: obj = TFLiteBackendInferenceLearner(tflite_file, device)