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Removing torch from Adila's pipeline #64

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Hamedloghmani opened this issue Apr 10, 2023 · 5 comments
Open

Removing torch from Adila's pipeline #64

Hamedloghmani opened this issue Apr 10, 2023 · 5 comments
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enhancement New feature or request

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@Hamedloghmani
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In Adila, we are using torch library just to load our .pred files. Using just a small function from a big toolkit is not desirable since being lightweight is one of our goals in Adila's development. We are looking for an alternate tool to remove torch from pipeline and use that library or toolkit instead for loading .pred files. Note that .pred files are PyTorch model predictions (e.g outputs of OpeNTF).

@Hamedloghmani
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Hi @edwinpaul121 , hope you are doing well.

I assigned this new side-task to you for the moment. Let me know if you have any questions. I'll send you another one soon.

@edwinpaul121
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Hi @Hamedloghmani, just to clarify, we're trying to load .pred files created using PyTorch in OpeNTF, using another library that we may already be using in our pipeline or can it be any other library that is a bit more lightweight than PyTorch?

@Hamedloghmani
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Hi @edwinpaul121 ,
Exactly, we are looking for something lighter. Although it should somehow be significantly lighter to be worthy of switching from PyTorch to that second library. In Adila, we don't use PyTorch except for loading .pred files.

@edwinpaul121
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Hi @Hamedloghmani hope you're doing well,
I was looking into a few ways to do this and came by ONNX and ONNX runtime, I still have to research it a little bit but from what I've understood they are tools that acts as an intermediary between different libraries, but I think we might be able to use it for this purpose.
Two concerns though:

  1. The output/export prediction file needs to be converted into the ONNX format beforehand, meaning ONNX might need to be incorporated into OpeNTF just for this purpose.
  2. I'm not entirely sure how much lighter it will be compared to PyTorch.

@Hamedloghmani
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Hi @edwinpaul121
Thank you for your update.
As you kindly mentioned, ONNX requires changes in saving procedure of the model as well which is a bit unpleasant for us. I'll take a deeper look and send you an update here.

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