Neural network model compiler for Arm Ethos-U NPUs
Project description
Vela
This tool is used to compile a TensorFlow Lite for Microcontrollers neural network model into an optimised version that can run on an embedded system containing an Arm Ethos-U NPU.
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 optimised 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.
TensorFlow Support
- Vela 2.1.0 to current 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 the Linux and Microsoft Windows 10 operating systems, see note in Installation section below.
Prerequisites
The following should be installed prior to the installation of Vela:
- Python >= 3.6
- Pip3
- GNU toolchain (GCC, Binutils and libraries)
And optionally:
- Pipenv virtual environment tool
Installation
Vela is available to install as a package from PyPi, or as source code from ML Platform. Both methods will automatically install all the required dependencies.
Note: For installing on Microsoft Windows 10 you need to have a C99 capable toolchain installed. The recommended and tested toolchain is Microsoft Visual C++ 14.2 Build Tools, see https://wiki.python.org/moin/WindowsCompilers
PyPi
Install Vela from PyPi using the following command:
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:
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:
pip3 install -U setuptools>=40.1.0
pip3 install .
Or, if you use pipenv
:
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 above install commands like so:
pip3 install -e .
Or, if you use pipenv
:
pipenv 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 for more details).
Running
Vela is run with an input .tflite
file passed on the command line. This file
contains the neural network to be compiled. The tool then outputs an optimised
version with a _vela.tflite
file prefix, along with the performance estimate
(EXPERIMENTAL) CSV files, all to the output directory.
If you use the pipenv
virtual environment tool then first start by spawning a
shell in the virtual environment:
pipenv shell
After which running Vela is the same regardless of whether you are in a virtual environment or not.
Example usage:
- Compile the network
my_model.tflite
. The optimised version will be output to./output/my_network_vela.tflite
.
vela my_model.tflite
- Compile the network
/path/to/my_model.tflite
and specify the output to go in the directory./results_dir/
.
vela --output-dir ./results_dir /path/to/my_model.tflite
- Compile a network using a particular Ethos-U NPU. The following command selects an Ethos-U65 NPU accelerator configured with 512 MAC units.
vela --accelerator-config ethos-u65-512 my_model.tflite
- 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 theMy_Mem_Mode
memory mode from thevela_cfg.ini
configuration file.
vela --config vela_cfg.ini --system-config My_Sys_Config --memory-mode My_Mem_Mode my_model.tflite
- To get a list of all available options (see CLI Options section below):
vela --help
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.
Contributions
Please see Vela Contributions.
Debug Database
Please see Vela Debug Database.
Options
Please see Vela CLI Options. This includes a description of the system configuration file format.
Releases
Please see Vela Releases.
Security
Please see Vela Security.
Supported Operators
Please see Vela Supported Operators for the list of operators supported in this release.
Testing
Please see Vela Testing.
Resources
Additional useful information:
- Arm Products: Ethos-U55 NPU
- Arm Products: Ethos-U65 NPU
- Arm Developer: Ethos-U55 NPU
- Arm Developer: Ethos-U65 NPU
License
Vela is licensed under Apache License 2.0.
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