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diff --git a/docs/quick_start.md b/docs/quick_start.md new file mode 100644 index 0000000..f557c72 --- /dev/null +++ b/docs/quick_start.md @@ -0,0 +1,95 @@ +# Quick start example ML application + +This is a quick start guide that will show you how to run the keyword spotting example application. The aim of this guide +is to illustrate the flow of running an application on the evaluation kit rather than showing the keyword spotting +functionality or performance. All use cases in the evaluation kit follow the steps. + +1. Verify you have installed [the required prerequisites](sections/building.md#Build-prerequisites). + +2. Clone the Ethos-U55 evaluation kit repository. + + ```commandline + git clone "https://review.mlplatform.org/ml/ethos-u/ml-embedded-evaluation-kit" + cd ml-embedded-evaluation-kit + ``` + +3. Pull all the external dependencies with the commands below: + + ```commandline + git submodule update --init + ``` + +4. Next, you would need to get a neural network model. For the purpose of this quick start guide, we'll use the + `ds_cnn_clustered_int8` keyword spotting model from the [Arm public model zoo](https://github.com/ARM-software/ML-zoo) + and the principle remains the same for all of the other use cases. Download the `ds_cnn_large_int8.tflite` model + file with the curl command below: + + ```commandline + curl -L https://github.com/ARM-software/ML-zoo/blob/master/models/keyword_spotting/ds_cnn_large/tflite_clustered_int8/ds_cnn_clustered_int8.tflite?raw=true --output ds_cnn_clustered_int8.tflite + ``` + +5. [Vela](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-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](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/HEAD/SUPPORTED_OPS.md). + In this step, you will compile the model with Vela. + + For this step, you need to ensure you have [correctly installed the Vela package](https://pypi.org/project/ethos-u-vela/): + + ```commandline + python3 -m venv env + source ./env/bin/activate + pip install --upgrade pip + pip install ethos-u-vela + ``` + + In the command below, we specify that we are using the Arm® Ethos™-U55 NPU with a 128 Multiply-Accumulate units + (MAC units) configured for a High End Embedded use case. The [building section](sections/building.md#Optimize-custom-model-with-Vela-compiler) + has more detailed explanation about Vela usage. + + ```commandline + vela ds_cnn_clustered_int8.tflite \ + --accelerator-config=ethos-u55-128 \ + --block-config-limit=0 \ + --config scripts/vela/vela.ini \ + --memory-mode Shared_Sram \ + --system-config Ethos_U55_High_End_Embedded + ``` + + An optimized model file for Ethos-U55 is generated in a folder named `output`. + +6. Create a `build` folder in the root level of the evaluation kit. + + ```commandline + mkdir build && cd build + ``` + +7. Build the makefiles with `CMake` as shown in the command below. The [build process section](sections/building.md#Build-process) + gives an in-depth explanation about the meaning of every parameter. For the time being, note that we point the Vela + optimized model from stage 5 in the `-Dkws_MODEL_TFLITE_PATH` parameter. + + ```commandline + cmake \ + -DTARGET_PLATFORM=mps3 \ + -DTARGET_SUBSYSTEM=sse-300 \ + -DCMAKE_TOOLCHAIN_FILE=scripts/cmake/bare-metal-toolchain.cmake \ + -DUSE_CASE_BUILD=kws \ + -Dkws_MODEL_TFLITE_PATH=output/ds_cnn_clustered_int8_vela.tflite \ + .. + ``` + +8. Compile the project with a `make`. Details about this stage can be found in the [building part of the documentation](sections/building.md#Building-the-configured-project). + + ```commandline + make -j4 + ``` + +9. Launch the project as explained [here](sections/deployment.md#Deployment). In this quick-start guide, we'll use the Fixed + Virtual Platform. Point the generated `bin/ethos-u-kws.axf` file in stage 8 to the FVP that you have downloaded when + installing the prerequisites. + + ```commandline + <path_to_FVP>/FVP_Corstone_SSE-300_Ethos-U55 -a ./bin/ethos-u-kws.axf + ``` + +10. A telnet window is launched through which you can interact with the application and obtain performance figures. |