code: def execute(
      self,
      model: bytes,
      model_params: ModelParams,
      input_tfms: MultiStageTransformation,
      **kwargs,
  ):
      self.inference_learner = TFLiteBackendInferenceLearner(
          model,
          network_parameters=model_params,
          input_tfms=input_tfms,
          device=self.device,
      )
  
imports: from pathlib import Path
  from typing import Any, Union
  from nebullvm.core.models import ModelParams, DeepLearningFramework, QuantizationType, DeviceType
  from nebullvm.operations.inference_learners.base import BuildInferenceLearner
  from nebullvm.operations.inference_learners.deepsparse import PytorchDeepSparseInferenceLearner
  from nebullvm.operations.inference_learners.faster_transformer import FasterTransformerInferenceLearner
  from nebullvm.operations.inference_learners.neural_compressor import PytorchNeuralCompressorInferenceLearner
  from nebullvm.operations.inference_learners.onnx import ONNX_INFERENCE_LEARNERS
  from nebullvm.operations.inference_learners.openvino import OPENVINO_INFERENCE_LEARNERS
  from nebullvm.operations.inference_learners.tensor_rt import TENSOR_RT_INFERENCE_LEARNERS, PytorchTensorRTInferenceLearner
  from nebullvm.operations.inference_learners.tensorflow import TensorflowBackendInferenceLearner, TFLiteBackendInferenceLearner
  from nebullvm.operations.inference_learners.torch_dynamo import TorchDynamoInferenceLearner
  from nebullvm.operations.inference_learners.torch_neuron import TorchNeuronInferenceLearner
  from nebullvm.operations.inference_learners.torch_xla import TorchXLAInferenceLearner
  from nebullvm.operations.inference_learners.torchscript import TorchScriptInferenceLearner
  from nebullvm.operations.inference_learners.tvm import APACHE_TVM_INFERENCE_LEARNERS, PytorchApacheTVMInferenceLearner
  from nebullvm.optional_modules.tensor_rt import tensorrt
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.optional_modules.torch import ScriptModule, Module, GraphModule, torch
  from nebullvm.optional_modules.tvm import tvm, ExecutorFactoryModule
  from nebullvm.tools.onnx import get_input_names, get_output_names
  from nebullvm.tools.transformations import MultiStageTransformation, VerifyContiguity
label_desc: Use image node_id 1 for calling the TFLiteBuildInferenceLearner obj's underlying member method code with example usage: obj.execute(model, model_params, input_tfms) without return types