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This repository contains source code of embARC Machine Learning Inference Library (embARC MLI Library),
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This repository contains source code of embARC Machine Learning Inference Library (embARC MLI Library),
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documentation and examples.
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## Release notes
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## Documentation
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----------------
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The pre-built documentation can be found on the [release page](https://github.com/foss-for-synopsys-dwc-arc-processors/embarc_mli/releases)
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The pre-built documentation can be found on the [release page](https://github.com/foss-for-synopsys-dwc-arc-processors/embarc_mli/releases/tag/Release_1.1.1)
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in the assets list of the required embARC MLI library version. To use it download
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*embARC_MLI_\<version\>_API_Doc.zip* file, unzip the archive and
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open `<unzipped_archive_root>/html/index.html` file in a browser.
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EM or HS configuration.
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Build requirements:
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1. The library has been tested with MetaWare Development tools 2019.12
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1. The library has been tested with MetaWare Development tools 2021.12
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Building of embARC MLI library
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1. Open command line and change working directory to './lib/make/'
Copy file name to clipboardExpand all lines: examples/example_cifar10_caffe/README.md
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### Build with ARC GNU toolchain
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Here we will consider building with ARC GNU toolchain. As a platform for the assembly, we use the [IoT Devkit](https://embarc.org/embarc_osp/doc/build/html/board/iotdk.html) from [the embARC Open Software Platform (OSP)](https://embarc.org/embarc_osp/doc/build/html/introduction/introduction.html#)
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Here we will consider building with ARC GNU toolchain. As a platform for the assembly, we use the [IoT Devkit](https://embarc.org/project/arc-iot-development-kit/) from [the embARC Open Software Platform (OSP)](https://embarc.org/project/embarc-open-software-platform-osp/)
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Build requirements:
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- ARC GNU toolchain version 2018.09 or higher
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### Run example without MetaWare Development tools
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See documentation on [IoT Devkit](https://embarc.org/embarc_osp/doc/build/html/board/iotdk.html) on how to run executable built with [ARC GNU](https://embarc.org/toolchain/index.html) and [ARC open source development tools](https://embarc.org/embarc_osp/doc/build/html/index.html) on IoT Devkit.
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See documentation on [IoT Devkit](https://embarc.org/project/arc-iot-development-kit/) on how to run executable built with [ARC GNU](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain) and [ARC open source development tools](https://embarc.org/project/embarc-open-software-platform-osp/) on IoT Devkit.
Copy file name to clipboardExpand all lines: examples/example_face_detect/README.md
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### Build with ARC GNU toolchain
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Here we will consider building with ARC GNU toolchain. As a platform for the assembly, we use the [IoT Devkit](https://embarc.org/embarc_osp/doc/build/html/board/iotdk.html) from [the embARC Open Software Platform (OSP)](https://embarc.org/embarc_osp/doc/build/html/introduction/introduction.html#)
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Here we will consider building with ARC GNU toolchain. As a platform for the assembly, we use the [IoT Devkit](https://embarc.org/project/arc-iot-development-kit/) from [the embARC Open Software Platform (OSP)](https://embarc.org/project/embarc-open-software-platform-osp/)
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Build requirements:
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- ARC GNU toolchain version 2018.09 or higher
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### Run example without MetaWare Development tools
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See documentation on [IoT Devkit](https://embarc.org/embarc_osp/doc/build/html/board/iotdk.html) on how to run executable built with [ARC GNU](https://embarc.org/toolchain/index.html) and [ARC open source development tools](https://embarc.org/embarc_osp/doc/build/html/index.html) on IoT Devkit.
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See documentation on [IoT Devkit](https://embarc.org/project/arc-iot-development-kit/) on how to run executable built with [ARC GNU](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain) and [ARC open source development tools](https://embarc.org/project/embarc-open-software-platform-osp/) on IoT Devkit.
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### Build with ARC GNU toolchain
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Here we will consider building with ARC GNU toolchain. As a platform for the assembly, we use the [IoT Devkit](https://embarc.org/embarc_osp/doc/build/html/board/iotdk.html) from [the embARC Open Software Platform (OSP)](https://embarc.org/embarc_osp/doc/build/html/introduction/introduction.html#)
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Here we will consider building with ARC GNU toolchain. As a platform for the assembly, we use the [IoT Devkit](https://embarc.org/project/arc-iot-development-kit/) from [the embARC Open Software Platform (OSP)](https://embarc.org/project/embarc-open-software-platform-osp/)
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Build requirements:
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- ARC GNU toolchain version 2018.09 or higher
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### Run example without MetaWare Development tools
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See documentation on [IoT Devkit](https://embarc.org/embarc_osp/doc/build/html/board/iotdk.html) on how to run executable built with [ARC GNU](https://embarc.org/toolchain/index.html) and [ARC open source development tools](https://embarc.org/embarc_osp/doc/build/html/index.html) on IoT Devkit.
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See documentation on [IoT Devkit](https://embarc.org/project/arc-iot-development-kit/) on how to run executable built with [ARC GNU](https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain) and [ARC open source development tools](https://embarc.org/project/embarc-open-software-platform-osp/) on IoT Devkit.
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Key Word Spotting Example
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==============================================
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Example shows implementation of small speech recognition use case for Key Word Spotting (KWS). [TensorFlow speech commands tutorial](https://www.tensorflow.org/tutorials/sequences/audio_recognition) was used as basis for neural network model training with the following most notable changes:
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Example shows implementation of small speech recognition use case for Key Word Spotting (KWS). [TensorFlow speech commands tutorial](https://www.tensorflow.org/tutorials/audio/simple_audio) was used as basis for neural network model training with the following most notable changes:
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1) Input features: FBANK features instead of MFCC
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2) Model architecture: Depthwise separable convolutions + LSTM Cell.
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KWS Modules are designed to process audio stream. The rest example code wraps modules to process single WAV file and output performance measurements.
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