This is a quick start guide that will show you how to run the keyword spotting example application. The aim of this quick start guide is to enable you to run an application quickly on the Fixed Virtual Platform. The assumption we are making is that your Arm® Ethos™-U55 NPU is configured to use 128 Multiply-Accumulate units, is using a shared SRAM with the Arm® Cortex®-M55.
Verify you have installed the required prerequisites.
Clone the Ethos-U55 evaluation kit repository.
git clone "https://review.mlplatform.org/ml/ethos-u/ml-embedded-evaluation-kit" cd ml-embedded-evaluation-kit
Pull all the external dependencies with the commands below:
git submodule update --init
Next, you can use the build_default python script to get the default neural network models, compile them with Vela and build the project. Vela is an open-source python tool converting TensorFlow Lite for Microcontrollers neural network model into an optimized model that can run on an embedded system containing an Ethos-U55 NPU. It is worth noting that in order to take full advantage of the capabilities of the NPU, the neural network operators should be supported by Vela.
python3 build_default.py
Launch the project as explained here. For the purpose of this quick start guide, we'll use the keyword spotting application and the Fixed Virtual Platform. Point the generated bin/ethos-u-kws.axf file in stage 4 to the FVP that you have downloaded when installing the prerequisites.
<path_to_FVP>/FVP_Corstone_SSE-300_Ethos-U55 -a ./bin/ethos-u-kws.axf
A telnet window is launched through which you can interact with the application and obtain performance figures.
Note:: Execution of the build_default.py script is equivalent to running the following commands:
mkdir resources_downloaded && cd resources_downloaded python3 -m venv env env/bin/python3 -m pip install --upgrade pip env/bin/python3 -m pip install --upgrade setuptools env/bin/python3 -m pip install ethos-u-vela==2.1.1 cd .. curl -L https://github.com/ARM-software/ML-zoo/raw/7c32b097f7d94aae2cd0b98a8ed5a3ba81e66b18/models/anomaly_detection/micronet_medium/tflite_int8/ad_medium_int8.tflite \ --output resources_downloaded/ad/ad_medium_int8.tflite curl -L https://github.com/ARM-software/ML-zoo/raw/7c32b097f7d94aae2cd0b98a8ed5a3ba81e66b18/models/anomaly_detection/micronet_medium/tflite_int8/testing_input/input/0.npy \ --output ./resources_downloaded/ad/ifm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/7c32b097f7d94aae2cd0b98a8ed5a3ba81e66b18/models/anomaly_detection/micronet_medium/tflite_int8/testing_output/Identity/0.npy \ --output ./resources_downloaded/ad/ofm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/wav2letter_int8.tflite \ --output ./resources_downloaded/asr/wav2letter_int8.tflite curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/testing_input/input_2_int8/0.npy \ --output ./resources_downloaded/asr/ifm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/testing_output/Identity_int8/0.npy \ --output ./resources_downloaded/asr/ofm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/image_classification/mobilenet_v2_1.0_224/tflite_uint8/mobilenet_v2_1.0_224_quantized_1_default_1.tflite \ --output ./resources_downloaded/img_class/mobilenet_v2_1.0_224_quantized_1_default_1.tflite curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/image_classification/mobilenet_v2_1.0_224/tflite_uint8/testing_input/input/0.npy \ --output ./resources_downloaded/img_class/ifm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/image_classification/mobilenet_v2_1.0_224/tflite_uint8/testing_output/output/0.npy \ --output ./resources_downloaded/img_class/ofm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/keyword_spotting/ds_cnn_large/tflite_clustered_int8/ds_cnn_clustered_int8.tflite \ --output ./resources_downloaded/kws/ds_cnn_clustered_int8.tflite curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/keyword_spotting/ds_cnn_large/tflite_clustered_int8/testing_input/input_2/0.npy \ --output ./resources_downloaded/kws/ifm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/keyword_spotting/ds_cnn_large/tflite_clustered_int8/testing_output/Identity/0.npy \ --output ./resources_downloaded/kws/ofm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/wav2letter_int8.tflite \ --output ./resources_downloaded/kws_asr/wav2letter_int8.tflite curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/testing_input/input_2_int8/0.npy \ --output ./resources_downloaded/kws_asr/asr/ifm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/testing_input/input_2_int8/0.npy --output ./resources_downloaded/kws_asr/asr/ifm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/speech_recognition/wav2letter/tflite_int8/testing_output/Identity_int8/0.npy \ --output ./resources_downloaded/kws_asr/asr/ofm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/keyword_spotting/ds_cnn_large/tflite_clustered_int8/ds_cnn_clustered_int8.tflite \ --output ./resources_downloaded/kws_asr/ds_cnn_clustered_int8.tflite curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/keyword_spotting/ds_cnn_large/tflite_clustered_int8/testing_input/input_2/0.npy \ --output ./resources_downloaded/kws_asr/kws/ifm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/keyword_spotting/ds_cnn_large/tflite_clustered_int8/testing_output/Identity/0.npy \ --output ./resources_downloaded/kws_asr/kws/ofm0.npy curl -L https://github.com/ARM-software/ML-zoo/raw/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b/models/keyword_spotting/dnn_small/tflite_int8/dnn_s_quantized.tflite \ --output ./resources_downloaded/inference_runner/dnn_s_quantized.tflite . resources_downloaded/env/bin/activate && vela resources_downloaded/kws/ds_cnn_clustered_int8.tflite \ --accelerator-config=ethos-u55-128 \ --block-config-limit=0 --config scripts/vela/default_vela.ini \ --memory-mode=Shared_Sram \ --system-config=Ethos_U55_High_End_Embedded \ --output-dir=resources_downloaded/kws mv resources_downloaded/kws/ds_cnn_clustered_int8_vela.tflite resources_downloaded/kws/ds_cnn_clustered_int8_vela_H128.tflite . resources_downloaded/env/bin/activate && vela resources_downloaded/kws_asr/wav2letter_int8.tflite \ --accelerator-config=ethos-u55-128 \ --block-config-limit=0 --config scripts/vela/default_vela.ini \ --memory-mode=Shared_Sram \ --system-config=Ethos_U55_High_End_Embedded \ --output-dir=resources_downloaded/kws_asr mv resources_downloaded/kws_asr/wav2letter_int8_vela.tflite resources_downloaded/kws_asr/wav2letter_int8_vela_H128.tflite . resources_downloaded/env/bin/activate && vela resources_downloaded/kws_asr/ds_cnn_clustered_int8.tflite -\ --accelerator-config=ethos-u55-128 \ --block-config-limit=0 --config scripts/vela/default_vela.ini \ --memory-mode=Shared_Sram \ --system-config=Ethos_U55_High_End_Embedded \ --output-dir=resources_downloaded/kws_asr mv resources_downloaded/kws_asr/ds_cnn_clustered_int8_vela.tflite resources_downloaded/kws_asr/ds_cnn_clustered_int8_vela_H128.tflite . resources_downloaded/env/bin/activate && vela resources_downloaded/inference_runner/dnn_s_quantized.tflite -\ --accelerator-config=ethos-u55-128 \ --block-config-limit=0 --config scripts/vela/default_vela.ini \ --memory-mode=Shared_Sram \ --system-config=Ethos_U55_High_End_Embedded \ --output-dir=resources_downloaded/inference_runner mv resources_downloaded/inference_runner/dnn_s_quantized_vela.tflite resources_downloaded/inference_runner/dnn_s_quantized_vela_H128.tflite . resources_downloaded/env/bin/activate && vela resources_downloaded/img_class/mobilenet_v2_1.0_224_quantized_1_default_1.tflite \ --accelerator-config=ethos-u55-128 \ --block-config-limit=0 --config scripts/vela/default_vela.ini \ --memory-mode=Shared_Sram \ --system-config=Ethos_U55_High_End_Embedded \ --output-dir=resources_downloaded/img_class mv resources_downloaded/img_class/mobilenet_v2_1.0_224_quantized_1_default_1_vela.tflite resources_downloaded/img_class/mobilenet_v2_1.0_224_quantized_1_default_1_vela_H128.tflite . resources_downloaded/env/bin/activate && vela resources_downloaded/asr/wav2letter_int8.tflite \ --accelerator-config=ethos-u55-128 \ --block-config-limit=0 --config scripts/vela/default_vela.ini \ --memory-mode=Shared_Sram \ --system-config=Ethos_U55_High_End_Embedded \ --output-dir=resources_downloaded/asr mv resources_downloaded/asr/wav2letter_int8_vela.tflite resources_downloaded/asr/wav2letter_int8_vela_H128.tflite . resources_downloaded/env/bin/activate && vela resources_downloaded/ad/ad_medium_int8.tflite \ --accelerator-config=ethos-u55-128 \ --block-config-limit=0 --config scripts/vela/default_vela.ini \ --memory-mode=Shared_Sram \ --system-config=Ethos_U55_High_End_Embedded \ --output-dir=resources_downloaded/ad mv resources_downloaded/ad/ad_medium_int8_vela.tflite resources_downloaded/ad/ad_medium_int8_vela_H128.tflite mkdir cmake-build-mps3-sse-300-gnu-release and cd cmake-build-mps3-sse-300-gnu-release cmake .. \ -DTARGET_PLATFORM=mps3 \ -DTARGET_SUBSYSTEM=sse-300 \ -DCMAKE_TOOLCHAIN_FILE=scripts/cmake/toolchains/bare-metal-gcc.cmake
Note: If you want to make changes to the application (for example modifying the number of MAC units of the Ethos-U or running a custom neural network), you should follow the approach defined in documentation.md instead of using the
build_defaultpython script.