message: Add `--quantize_to_float16` flag to tflite_convert
  Note that this must always be used in conjunction with
  `--post_training_quantize` to have any effect in conversion.
diff: @@ -178,12 +178,18 @@ def _convert_tf1_model(flags):
  converter.target_spec.supported_ops.add(lite.OpsSet(option))
  if flags.post_training_quantize:
  - converter.post_training_quantize = flags.post_training_quantize
  + converter.optimizations = [lite.Optimize.DEFAULT]
  if converter.inference_type == lite_constants.QUANTIZED_UINT8:
  print("--post_training_quantize quantizes a graph of inference_type "
  "FLOAT. Overriding inference type QUANTIZED_UINT8 to FLOAT.")
  converter.inference_type = lite_constants.FLOAT
  + if flags.quantize_to_float16:
  + converter.target_spec.supported_types = [lite.constants.FLOAT16]
  + if not flags.post_training_quantize:
  + print("--quantize_to_float16 will only take effect with the "
  + "--post_training_quantize flag enabled.")
  +
  if flags.dump_graphviz_dir:
  converter.dump_graphviz_dir = flags.dump_graphviz_dir
  if flags.dump_graphviz_video:
  @@ -390,7 +396,13 @@ def _get_tf1_parser():
  "Boolean indicating whether to quantize the weights of the "
  "converted float model. Model size will be reduced and there will "
  "be latency improvements (at the cost of accuracy). (default False)"))
  -
  + parser.add_argument(
  + "--quantize_to_float16",
  + dest="quantize_to_float16",
  + action="store_true",
  + help=("Boolean indicating whether to quantize weights to fp16 instead of "
  + "the default int8 when post-training quantization "
  + "(--post_training_quantize) is enabled. (default False)"))
  # Graph manipulation flags.
  parser.add_argument(
  "--drop_control_dependency",
  