Metadata-Version: 2.1
Name: ethos-u-vela
Version: 3.5.0
Summary: Neural network model compiler for Arm Ethos-U NPUs
Home-page: https://git.mlplatform.org/ml/ethos-u/ethos-u-vela.git/
Author: Arm Ltd.
Author-email: mlg-vela@arm.com
License: Apache License 2.0
Description: # Vela
        
        This tool is used to compile a
        [TensorFlow Lite for Microcontrollers](https://www.tensorflow.org/lite/microcontrollers)
        neural network model into an optimised version that can run on an embedded
        system containing an
        [Arm Ethos-U NPU](https://www.arm.com/products/silicon-ip-cpu).
        
        In order to be accelerated by the Ethos-U NPU the network operators must be
        quantised to either 8-bit (unsigned or signed) or 16-bit (signed).
        
        The optimised model will contain TensorFlow Lite Custom operators for those
        parts of the model that can be accelerated by the Ethos-U NPU.  Parts of the
        model that cannot be accelerated are left unchanged and will instead run on the
        Cortex-M series CPU using an appropriate kernel (such as the
        [Arm](https://www.arm.com) optimised
        [CMSIS-NN](https://github.com/ARM-software/CMSIS_5/tree/develop/CMSIS/NN)
        kernels).
        
        After compilation the optimised model can only be run on an Ethos-U NPU
        embedded system.
        
        The tool will also generate performance estimates (EXPERIMENTAL) for the
        compiled model.
        
        The tool has limited functionality for compiling a
        [TOSA](https://git.mlplatform.org/tosa/specification.git/) neural network
        (EXPERIMENTAL).
        
        ## TensorFlow Support
        
        * Vela 3.5.0 to current supports TensorFlow 2.9
        * Vela 3.4.0 supports TensorFlow 2.8
        * Vela 3.3.0 supports TensorFlow 2.7
        * Vela 3.1.0 to 3.2.0 supports TensorFlow 2.5
        * Vela 2.1.0 to 3.0.0 supports TensorFlow 2.4
        * Vela 2.0.0 to 2.0.1 supports TensorFlow 2.3
        * Vela 0.1.0 to 1.2.0 supports TensorFlow 2.1
        
        ## Environment
        
        Vela runs on Linux and Microsoft Windows 10 operating systems.
        
        ## Prerequisites
        
        The following should be installed prior to the installation of Vela:
        
        * Python 3.7 or compatible
           - Development version containing the Python/C API header files
           - e.g. `apt install python3.7-dev` or `yum install python37-devel`
        * Pip3
        * A C99 capable compiler and associated toolchain
            - For Linux operating systems, a GNU toolchain is recommended.
            - For Microsoft Windows 10, Microsoft Visual C++ 14.2 Build Tools is recommended.
              See <https://wiki.python.org/moin/WindowsCompilers>
        
        ## Installation
        
        Vela is available to install as a package from
        [PyPi](https://pypi.org/project/ethos-u-vela/), or as
        source code from
        [ML Platform](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela).
        Both methods will automatically install all the required dependencies.
        
        ### PyPi
        
        Install Vela from PyPi using the following command:
        
        ```bash
        pip3 install ethos-u-vela
        ```
        
        ### ML Platform
        
        First obtain the source code by either downloading the desired TGZ file from:  
        <https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela>
        
        Or by cloning the git repository:
        
        ```bash
        git clone https://review.mlplatform.org/ml/ethos-u/ethos-u-vela.git
        ```
        
        Once you have the source code, Vela can be installed using the following
        command from the root directory of the repository:
        
        ```bash
        pip3 install .
        ```
        
        A `Pipfile` is maintained for the project, so users of the virtual environment
        tool `pipenv` may prefer the following command instead:
        
        ```bash
        pipenv install .
        ```
        
        #### Advanced Installation for Developers
        
        If you plan to modify the Vela codebase then it is recommended to install Vela
        as an editable package to avoid the need to re-install after every modification.
        This is done by adding the `-e` option to the install command like so:
        
        ```bash
        pip3 install -e .
        ```
        
        If you plan to contribute to the Vela project (highly encouraged!) then it is
        recommended to install Vela along with the pre-commit tools (see
        [Vela Testing](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/TESTING.md) for more details).
        
        ## Running
        
        Vela is run with an input `.tflite` or `.tosa` (EXPERIMENTAL) file passed on the
        command line. This file contains the neural network to be compiled. The tool then
        outputs an optimised `.tflite` file with a `_vela` suffix in the file name, along
        with performance estimate (EXPERIMENTAL) CSV files, all to the output directory.
        It also prints a performance estimation summary back to the console, see
        [Vela Performance Estimation Summary](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/PERFORMANCE.md).
        
        Example usage:
        
        1) Compile the network `my_model.tflite`.  The optimised version will be output
        to `./output/my_network_vela.tflite`.
        
        ```bash
        vela my_model.tflite
        ```
        
        2) Compile the network `/path/to/my_model.tflite` and specify the output to go
        in the directory `./results_dir/`.
        
        ```bash
        vela --output-dir ./results_dir /path/to/my_model.tflite
        ```
        
        3) Compile a network targeting a particular Ethos-U NPU.  The following command
        selects an Ethos-U65 NPU accelerator configured with 512 MAC units.
        
        ```bash
        vela --accelerator-config ethos-u65-512 my_model.tflite
        ```
        4) Compile a network while minimizing peak SRAM usage, prioritising lower SRAM
        usage over runtime performance.
        
        ```bash
        vela --optimise Size my_model.tflite
        ```
        
        5) Compile a network to have maximum performance, i.e. the fastest inference time.
        This prioritises a higher runtime performance over a lower peak SRAM usage.
        
        ```bash
        vela --optimise Performance my_model.tflite
        ```
        
        6) Compile a network while optimising for the fastest inference time possible,
        with an upper bound for the SRAM usage. The memory limit is set in bytes, i.e.
        run the following example if one requires a limit of 300KB.
        
        ```bash
        vela --optimise Performance --arena-cache-size 300000 my_model.tflite
        ```
        
        7) Compile a network using a particular embedded system configuration defined in
        Vela's configuration file.  The following command selects the `My_Sys_Config`
        system configuration along with the `My_Mem_Mode` memory mode from the `vela.ini`
        configuration file located in the config_files directory.
        
        ```bash
        vela --config Arm/vela.ini --system-config My_Sys_Config --memory-mode My_Mem_Mode my_model.tflite
        ```
        
        8) To get a list of all available configuration files in the config_files directory:
        
        ```bash
        vela --list-config-files
        ```
        
        9) To get a list of all available options (see CLI Options section below):
        
        ```bash
        vela --help
        ```
        
        ## Warnings
        
        When running the Vela compiler it may report a number of warning messages to the
        console. These should all be thoroughly reviewed as they will indicate decisions
        that the compiler has made in order to create the optimised network.
        
        ## Example Networks
        
        Some example networks that contain quantised operators which can be compiled by
        Vela to run on the Ethos-U NPU can be found at:
        <https://tfhub.dev/s?deployment-format=lite&q=quantized>
        
        ## APIs
        
        Please see [Vela External APIs](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/API.md).
        
        ## Contributions
        
        Please see [Vela Contributions](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/CONTRIBUTIONS.md).
        
        ## Debug Database
        
        Please see [Vela Debug Database](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/DEBUG_DB.md).
        
        ## Options
        
        Please see [Vela CLI Options](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/OPTIONS.md).  This includes a description of the
        system configuration file format.
        
        ## Performance
        
        Please see [Vela Performance Estimation Summary](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/PERFORMANCE.md).
        
        ## Releases
        
        Please see [Vela Releases](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/RELEASES.md).
        
        ## Security
        
        Please see [Vela Security](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/SECURITY.md).
        
        ## Supported Operators
        
        Please see [Vela Supported Operators](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/SUPPORTED_OPS.md) for the list of
        operators supported in this release.
        
        ## Testing
        
        Please see [Vela Testing](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/TESTING.md).
        
        ## Bug Reporting
        
        Please see [Vela Community Bug Reporting](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/BUGS.md) for a description of how to
        report bugs.
        
        ## Resources
        
        Additional useful information:
        
        * [Arm Products: Ethos-U55 NPU](https://www.arm.com/products/silicon-ip-cpu/ethos/ethos-u55)
        * [Arm Products: Ethos-U65 NPU](https://www.arm.com/products/silicon-ip-cpu/ethos/ethos-u65)
        * [Arm Developer: Ethos-U55 NPU](https://developer.arm.com/ip-products/processors/machine-learning/arm-ethos-u/ethos-u55)
        * [Arm Developer: Ethos-U65 NPU](https://developer.arm.com/ip-products/processors/machine-learning/arm-ethos-u/ethos-u65)
        
        ## License
        
        Vela is licensed under [Apache License 2.0](https://review.mlplatform.org/plugins/gitiles/ml/ethos-u/ethos-u-vela/+/refs/tags/3.5.0/LICENSE.txt).
        
Keywords: ethos-u,vela compiler,tflite,npu
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: Programming Language :: C
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Compilers
Requires-Python: ~=3.7
Description-Content-Type: text/markdown
