commit | 611fcdf8f0e33dabba4486eb78ce482c189248e5 | [log] [tgz] |
---|---|---|
author | Jacob Bohlin <jacob.bohlin@arm.com> | Thu Jun 11 15:09:57 2020 +0200 |
committer | Tim Hall <tim.hall@arm.com> | Thu Jun 18 17:53:52 2020 +0100 |
tree | f2265bb694b901d6ff6a57bd616fd0ead0ddc950 | |
parent | 749d92115e8ac7d0cc755ce93ea8a8c53fd6e474 [diff] |
MLBEDSW-2435: Fix for cascading upscaling operators Fixed a coordinate issue which caused the compiler to crash when cascading upscaling operators such as ResizeBilinear. Signed-off-by: Jacob Bohlin <jacob.bohlin@arm.com> Change-Id: I982863573b0e5829e6d0c255dbbc308cb332a37a
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 Ethos-U55 NPU.
The optimised model will contain TensorFlow Lite Custom operators for those parts of the model that can be accelerated by the Ethos-U55. 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-U55 NPU embedded system.
The tool will also generate performance estimates (EXPERIMENTAL) for the compiled model.
Vela supports TensorFlow 2.1.0.
Vela runs on the Linux operating system.
The following should be installed prior to the installation of Vela:
And optionally:
Before running, the Vela package must be installed along with all its dependencies. To do this, first change to the directory that contains this README.md file. Then use the command:
pip3 install -U setuptools>=40.1.0 pip3 install .
Or, if you use pipenv
:
pipenv install .
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:
my_model.tflite
. The optimised version will be output to ./output/my_network_vela.tflite
.vela my_model.tflite
/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
MySysConfig
settings that are described in the sys_cfg_vela.ini
system configuration file. More details can be found in the next section.vela --config sys_cfg_vela.ini --system-config MySysConfig my_model.tflite
vela --help
Information about all of Vela's CLI options as well as the system configuration file format can be found in Vela Options
Please see Vela Testing
Please see Vela Contributions.
Please see Vela Security.
Please see Vela Releases.
Additional useful information:
Vela is licensed under Apache License 2.0