margaretmz

adb shell /data/local/tmp/benchmark_model 
  --graph=/data/local/tmp/selfie2anime.tflite 
  --num_threads=4

margaretmz

adb install -r -d -g bazel-bin/tensorflow/lite/tools/benchmark/android/benchmark_model.apk
adb push selfie2anime.tflite /data/local/tmp

margaretmz

bazel build -c opt \
    --config=android_arm64 \         
    //tensorflow/lite/tools/benchmark:benchmark_model

margaretmz

metadata_writer_for_selfie2anime.py
|-- model_without_metadata
|   |--selfie2anime.tflite
|-- model_with_metadata
|   |--selfie2anime.tflite
|   |--selfie2anime.json

margaretmz

metadata_writer_for_selfie2anime.py
|-- model_without_metadata
|   |--selfie2anime.tflite
|-- model_with_metadata

margaretmz

python ./metadata_writer_for_selfie2anime.py \
--model_file=./model_without_metadata/selfie2anime.tflite \
--export_directory=model_with_metadata

margaretmz

converter = tf.lite.TFLiteConverter.from_concrete_functions([concrete_func])
converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_SIZE]
tflite_model = converter.convert()

margaretmz

concrete_func.inputs[0].set_shape([1, 256, 256, 3])
concrete_func.outputs[0].set_shape([1, 256, 256, 3])

margaretmz

model = tf.saved_model.load(saved_model_path)
concrete_func = model.signatures[ tf.saved_model.DEFAULT_SERVING_SIGNATURE_DEF_KEY]

margaretmz

tf.saved_model.simple_save(
       sess,
       saved_model_dir,
       inputs={gan.test_domain_A.name: gan.test_domain_A},
       outputs={gan.test_fake_B.name: gan.test_fake_B}
)