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Amith_lal
Associate III
June 12, 2024
Question

ML implementation in ISPU

  • June 12, 2024
  • 2 replies
  • 1429 views

Can anyone provide a documentation over integration custom ml algorithm in ISPU.

If I have a machine learning model like tflite or onnx how can I deploy it in ISPU

2 replies

Federica Bossi
Technical Moderator
June 12, 2024
In order to give better visibility on the answered topics, please click on 'Accept as Solution' on the reply which solved your issue or answered your question.
Amith_lal
Amith_lalAuthor
Associate III
June 12, 2024

I think in this article the are dealing with the example provided in the X-CUBE ISPU. What I need is to deploy the model that I developed (.tflite or .onnx) to the LSM6DSO16IS. What should be the next step? Is there any document related to that?

 

Federica Bossi
Technical Moderator
June 28, 2024

Hi @Amith_lal ,

Thanks for your patience. 

We now have tools to convert pretrained models to an implementation optimized for ISPU. You have to download ST Edge AI Core from here: https://www.st.com/en/development-tools/stedgeai-core.html (available for Linux and Windows, soon for macOS). If you want a graphical interface, you can also download MEMS-Studio from here: https://www.st.com/en/development-tools/mems-studio.html.

The ST Edge AI Core package includes some documentation. In addition, you can refer to the documentation and resources on the GitHub repository for ISPU: https://github.com/STMicroelectronics/st-mems-ispu. In particular, you can refer to the template specific for the integration of models converted with ST Edge AI, which includes a README file explaining the steps to perform: https://github.com/STMicroelectronics/ispu-examples/tree/master/ism330is_lsm6dso16is/template_stedgeai. At https://github.com/STMicroelectronics/ispu-examples/tree/master/ism330is_lsm6dso16is/template_stedgeai_validate you can instead find out how to validate your converted model.

You may be also interested in the ST Edge AI Developer Cloud (https://www.st.com/en/development-tools/stedgeai-dc.html), which allows you to benchmark your models and download the generated code with no installation or additional hardware required.

In order to give better visibility on the answered topics, please click on 'Accept as Solution' on the reply which solved your issue or answered your question.