STT-tensorflow/tensorflow/lite/tools/benchmark/ios

TFLite iOS benchmark app.

Description

An iOS app to benchmark TFLite models.

The app reads benchmark parameters from a JSON file named benchmark_params.json in its benchmark_data directory. Any downloaded models for benchmarking should also be placed in benchmark_data directory.

The JSON file specifies the name of the model file and other benchmarking parameters like inputs to the model, type of inputs, number of iterations, number of threads. The default values in the JSON file are for the Mobilenet_1.0_224 model (paper, tflite&pb)

To build/install/run

• Follow instructions at iOS build for TFLite to build TFLite.

Running

tensorflow/lite/tools/make/build_ios_universal_lib.sh

will also build tensorflow/lite/tools/make/gen/lib/benchmark-lib.a .

• Now copy the downloaded model file to benchmark_data directory.

• Modify benchmark_params.json change the input_layer, input_layer_shape and other benchmark parameters.

• Change Build Phases -> Copy Bundle Resources and add the model file to the resources that need to be copied.

• Ensure that Build Phases -> Link Binary With Library contains the Accelerate framework and tensorflow/lite/tools/make/gen/lib/benchmark-lib.a.

• Now try running the app. The app has a single button that runs the benchmark on the model and displays results in a text view below.

Profiling

If you want detailed profiling, use the following command:

tensorflow/lite/tools/make/build_ios_universal_lib.sh -p

Then following the same steps above and run the benchmark app. You will see the detailed profiling results in the outputs.