message: [2] add convert_tflite function for image classification task to convert saved model to tflite with metadata.
diff: @@ -22,12 +22,12 @@ from tensorflow_lite_support.metadata.python.metadata_writers import metadata_wr
  from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
  _MODEL_NAME = "ImageClassifier"
  -_MODEL_DESCRIPTION = ("Identify the most prominent object in the image from a "
  +MODEL_DESCRIPTION = ("Identify the most prominent object in the image from a "
  "known set of categories.")
  -_INPUT_NAME = "image"
  -_INPUT_DESCRIPTION = "Input image to be classified."
  -_OUTPUT_NAME = "probability"
  -_OUTPUT_DESCRIPTION = "Probabilities of the labels respectively."
  +INPUT_NAME = "image"
  +INPUT_DESCRIPTION = "Input image to be classified."
  +OUTPUT_NAME = "probability"
  +OUTPUT_DESCRIPTION = "Probabilities of the labels respectively."
  class MetadataWriter(metadata_writer.MetadataWriter):
  @@ -57,17 +57,17 @@ class MetadataWriter(metadata_writer.MetadataWriter):
  if general_md is None:
  general_md = metadata_info.GeneralMd(
  - name=_MODEL_NAME, description=_MODEL_DESCRIPTION)
  + name=_MODEL_NAME, description=MODEL_DESCRIPTION)
  if input_md is None:
  input_md = metadata_info.InputImageTensorMd(
  - name=_INPUT_NAME,
  - description=_INPUT_DESCRIPTION,
  + name=INPUT_NAME,
  + description=INPUT_DESCRIPTION,
  color_space_type=_metadata_fb.ColorSpaceType.RGB)
  if output_md is None:
  output_md = metadata_info.ClassificationTensorMd(
  - name=_OUTPUT_NAME, description=_OUTPUT_DESCRIPTION)
  + name=OUTPUT_NAME, description=OUTPUT_DESCRIPTION)
  if output_md.associated_files is None:
  output_md.associated_files = []
  @@ -117,16 +117,16 @@ class MetadataWriter(metadata_writer.MetadataWriter):
  A MetadataWriter object.
  """
  input_md = metadata_info.InputImageTensorMd(
  - name=_INPUT_NAME,
  - description=_INPUT_DESCRIPTION,
  + name=INPUT_NAME,
  + description=INPUT_DESCRIPTION,
  norm_mean=input_norm_mean,
  norm_std=input_norm_std,
  color_space_type=_metadata_fb.ColorSpaceType.RGB,
  tensor_type=writer_utils.get_input_tensor_types(model_buffer)[0])
  output_md = metadata_info.ClassificationTensorMd(
  - name=_OUTPUT_NAME,
  - description=_OUTPUT_DESCRIPTION,
  + name=OUTPUT_NAME,
  + description=OUTPUT_DESCRIPTION,
  label_files=[
  metadata_info.LabelFileMd(file_path=file_path)
  for file_path in label_file_paths
  