tensorflow_examples/lite/model_maker/core/task/question_answer.py [153:182]:
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  def _export_tflite(self,
                     tflite_filepath,
                     quantization_config='default',
                     with_metadata=True,
                     export_metadata_json_file=False):
    """Converts the retrained model to tflite format and saves it.

    Args:
      tflite_filepath: File path to save tflite model.
      quantization_config: Configuration for post-training quantization. If
        'default', sets the `quantization_config` by default according to
        `self.model_spec`. If None, exports the float tflite model without
        quantization.
      with_metadata: Whether the output tflite model contains metadata.
      export_metadata_json_file: Whether to export metadata in json file. If
        True, export the metadata in the same directory as tflite model.Used
        only if `with_metadata` is True.
    """
    if quantization_config == 'default':
      quantization_config = self.model_spec.get_default_quantization_config()

    # Sets batch size from None to 1 when converting to tflite.
    model_util.set_batch_size(self.model, batch_size=1)
    model_util.export_tflite(self.model, tflite_filepath, quantization_config,
                             self.model_spec.convert_from_saved_model_tf2)
    # Sets batch size back to None to support retraining later.
    model_util.set_batch_size(self.model, batch_size=None)

    if with_metadata:
      with tempfile.TemporaryDirectory() as temp_dir:
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tensorflow_examples/lite/model_maker/core/task/text_classifier.py [122:151]:
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  def _export_tflite(self,
                     tflite_filepath,
                     quantization_config='default',
                     with_metadata=True,
                     export_metadata_json_file=False):
    """Converts the retrained model to tflite format and saves it.

    Args:
      tflite_filepath: File path to save tflite model.
      quantization_config: Configuration for post-training quantization. If
        'default', sets the `quantization_config` by default according to
        `self.model_spec`. If None, exports the float tflite model without
        quantization.
      with_metadata: Whether the output tflite model contains metadata.
      export_metadata_json_file: Whether to export metadata in json file. If
        True, export the metadata in the same directory as tflite model.Used
        only if `with_metadata` is True.
    """
    if quantization_config == 'default':
      quantization_config = self.model_spec.get_default_quantization_config()

    # Sets batch size from None to 1 when converting to tflite.
    model_util.set_batch_size(self.model, batch_size=1)
    model_util.export_tflite(self.model, tflite_filepath, quantization_config,
                             self.model_spec.convert_from_saved_model_tf2)
    # Sets batch size back to None to support retraining later.
    model_util.set_batch_size(self.model, batch_size=None)

    if with_metadata:
      with tempfile.TemporaryDirectory() as temp_dir:
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