The Vivante ACUITY Toolkit offers both command line tools and APIs, enabling seamless deployment of machine learning neural network models onto devices with a neural processing unit (NPU). This toolkit facilitates the translation of model formats, network optimization, model training, quantization, and inference, until
final integrations with devices.
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Linux NPU Driver | Vivante ACUITY Toolkit | Vivante IDE |
v6.4.13.8 | 6.18.1 | 5.7.2 |
v6.4.15.9 | 6.21.1 | 5.8.2 |
v6.4.18.5 | 6.30.07 | 5.10.1 |
3. Installing ACUITY Binary Version
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Extract the ACUITY package 'Verisilicon_Tool_Acuity_Toolkit_<version>.tgz' to your desired destination directory.
From this directory, locate and unpack the binary package 'Vivante_acuity-_toolkit-_binary-_<version>.tgz'. Once unpacking is complete, the installation process is finished.
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Extract the ACUITY package, ‘Verisilicon_Tool_Acuity_Toolkit_<version>.tgz’, to a destination directory.
From this directory, locate and unpack the ACUITY Wheel package ‘acuity-toolkit-whl-<version>’ ‘Vivante_acuity_toolkit_whl_<version>_python<version>’.
From the './acuity-toolkit-whl-<version>/bin' directory, select and install a Wheel package with the following commands:
Code Block pip3 install ./acuity-*.whl
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pip3 install tensorflow==2.12.0 pip3 install scipy pip3 install networkx>=1.11 pip3 install lmdb==0.93 pip3 install protobuf<=3.20.3 pip3 install onnxoptimizer==0.3.13 pip3 install onnx==1.14.0 pip3 install dill==0.2.8.2 pip3 install ruamel.yaml==0.15.81 pip3 install ply==3.11 pip3 install torch==1.5.1 |
4.2.3 ACUITY Toolkit 6.30.
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pip3 install tensorflow==2.15.0 pip3 install scipy pip3 install networkx>=1.11 pip3 install lmdb==0.93 pip3 install protobuf<=3.20.3 pip3 install onnxoptimizer==0.3.13 pip3 install onnx==1.14.0 pip3 install dill==0.2.8.2 pip3 install ruamel.yaml==0.15.81 pip3 install ply==3.11 pip3 install torch==1.5.1 |
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