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Deployment requirements based on libtorch or ONNX #358
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Hi @wangrui9720! It’s great to see your interest in the SDV ecosystem. This comment is a reminder to consult your legal before adopting the SDV into your project, as SDV (and most of the related libraries such as CTGAN) has source-available, BSL license. For more information, you can read through our license FAQs (not legal advice) or our blog. For any other questions, please refer to our Support Page. You can also inquire about a commercial license to allow additional use. |
Hi there @wangrui9720 do you mind sharing a bit more about your use case? A few suggestions to consider:
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This is the code that I call the trained ctgan model. from ctgan import CTGAN def load_ctgan_model(): def get_welding_parameters(ctgan, NG_piece, desired_rows=500, batch_size=100):
When I want to deploy the trained ctgan code for real-time output, I can only call this python code with c++. The Gaussiancoupulaasynthesizer you mentioned is also the python code that needs me to call Gaussiancoupulaasynthesizer with c++ to train, right? Looking forward to your reply! |
Ah now I understand @wangrui9720 you're correct that CTGAN and SDV don't actually currently support portability of just the machine learning model. The pkl file also contain a lot of Python library context because all that context is usually needed to run the Synthesizer capabilities to generate synthetic data. We have a feature request issue in SDV to enable the exporting of just the model weights: sdv-dev/SDV#1970 I'll close this issue off and will add your use case over there so we can collect more examples for the team to prioritize! Thanks! |
After training ctgan, we hope to use C++ to call this model to work in real time. After trying, ctgan can't be deployed in torchscript and other formats, because the input and output data of ctgan are based on python's pandas library, while the input and output of libtorch are required to be in tensor format. We really need to provide a deployment method based on C++, which can improve the efficiency of software operation. We look forward to your proposal!
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