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1. Prerequisites

1.1. Host Requirements

The host meets the requirements as described in Section 1.4, System Requirements

Resource

Note

CPU

Intel ® CoreTM i5-6500 CPU@3.2GHz x4 with support of the Intel® Advanced Vector Extensions.

GPU

(Optional) NVIDIA® GPU cards with CUDA® architectures. A compatible version of CUDA and cuDNN is installed for TensorFlow

RAM

8 GB at least

Disk

160 GB

OS

Ubuntu 22.04 LTS 64-bit with Python 3.10,

Ubuntu 20.04 LTS 64-bit with Python 3.8 (recommended), or

Ubuntu 18.04 LTS 64-bit with Python 3.6

Note: Other Ubuntu versions are not recommended.

1.2. Python Requirements

Ubuntu 22.04 with Python 3.10, Ubuntu 20.04 with Python 3.8, or Ubuntu 18.04 with Python 3.6 is set up.

1.3. VivanteIDE

The VivanteIDE is installed correctly if you want to generate NBG cases from the ACUITY Toolkit. Please refer to this document: VivanteIDE Install

2. Version Information

The VIP9000 NPU driver Acuity Toolkit and ViviantelIDE need to match the version

VIP9000 NPU Kernel Driver

Acuity Toolkit

ViviantelIDE

v6.4.13.8

6.18.1

5.7.2

v6.4.15.9

6.21.1

5.8.2

3. Binary Toolkit

3.1. Install Procedure

  1. Extract the ACUITY package, Verisilicon_Tool_Acuity_Toolkit_<version>.tgz, to a destination directory. There are two versions of the toolkit, Please confirm the version that needs to be installed:

    • acuity-toolkit-binary-6.18.1, matches the VIP9000-NPU kernel driver v6.4.13.8

    • acuity-toolkit-binary-6.21.1, matches the VIP9000-NPU kernel driver v6.4.15.9

  2. From this directory, locate and unpack the binary package acuity-toolkit-binary-<version>.tgz. When the unpacking is completed, the installation finishes.

3.2. Toolkit Verification

  1. Switch to the ./acuity-toolkit-binary-<version>/bin directory.

  2. Set the environment variable ACUITY_PATH as follows, which will used to execute the ACUITY binary tools

  3. Execute binary file

user@linux:~/c3v/acuity-toolkit-binary-6.21.1/bin$ ./pegasus -h
yang.luo@ti-d630:~/c3v/acuity-toolkit-binary-6.21.1/bin$ ./pegasus 
usage: pegasus [-h] {import,export,generate,prune,inference,quantize,train,dump,measure,help} ...

Pegasus commands.

positional arguments:
  {import,export,generate,prune,inference,quantize,train,dump,measure,help}
    import              Import models.
    export              Export models.
    generate            Generate metas.
    prune               prune models.
    inference           Inference model and get result.
    quantize            Quantize model.
    train               Train model.
    dump                Dump model activations.
    measure             Get amount of calculation, parameter and activation.
    help                Print a synopsis and a list of commands.

optional arguments:
	-h, --help						show this help message and exit

4. Wheel Toolkit

4.1. Install Procedure

  1. Install requirement packages

    • acuity-toolkit-6.18.1. Matches the VIP9000-NPU kernel driver v6.4.13.8

tensorflow==2.10.0
scipy
networkx==1.11
lmdb==0.93
onnxoptimizer==0.3.1
onnx==1.12.0
dill==0.2.8.2
ruamel.yaml==0.15.81
ply==3.11
torch==1.5.1

  • acuity-toolkit-6.21.1. Matches the VIP9000-NPU kernel driver v6.4.15.9

tensorflow==2.12.0
scipy
networkx==1.11
lmdb==0.93
protobuf==3.20.3
onnxoptimizer==0.3.13
onnx==1.14.0
dill==0.2.8.2
ruamel.yaml==0.15.81
ply==3.11
torch==1.5.1

  1. Extract the ACUITY package, Verisilicon_Tool_Acuity_Toolkit_<version>.tgz, to a destination directory. There are two versions of the toolkit, Please confirm the toolkit version matches the Python version that needs to be installed：

    • acuity-toolkit- whl-6.18.1-python-xxx

    • acuity-toolkit- whl-6.21.1-python-xxx

  2. From this directory, locate and unpack the binary package acuity-toolkit-whl-<version>.tgz. select and install a Wheel package with the following commands: 

pip3 install ./acuity-*.whl

4.2. Toolkit Verification

  1. Switch to the ./acuity-toolkit-whl-<version>/bin directory.

  2. Execute python file

user@linux:~/c3v/acuity-toolkit-whl-6.21.1-python3.8.10/bin$ python pegasus.py -h
usage: pegasus [-h] {import,export,generate,prune,inference,quantize,train,dump,measure,help} ...

Pegasus commands.

positional arguments:
  {import,export,generate,prune,inference,quantize,train,dump,measure,help}
    import              Import models.
    export              Export models.
    generate            Generate metas.
    prune               prune models.
    inference           Inference model and get result.
    quantize            Quantize model.
    train               Train model.
    dump                Dump model activations.
    measure             Get amount of calculation, parameter and activation.
    help                Print a synopsis and a list of commands.

optional arguments:
  -h, --help            show this help message and exit

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