Feature Request : Implement LogSoftmax, Softmax, ReduceMax

[jsilter]

Feature request

Request the implementation of the following ONNX operators:

• LogSoftmax
• Softmax
• ReduceMax

Motivation

These operators are common in neural networks of many types; softmax is common in classification, reducemax is common in CNNs.

[andrei-stoian-zama]

Thanks for the suggestion. We don't currently have plans to implement these ops. You can find a softmax implementation in the LLM use case. There is already a ReduceSum operator and a MaxPool operator, you could try to adapt them to obtain ReduceMax.

[jsilter]

Thanks for the pointers. Do you have additional guides on how one implements a custom op in this context? I really would need to convert my existing (torch) model, I can't re-write and retrain a quantized version.

It does seem like the reduce_sum could be adapted easily (np.sum -> np.amax) although I don't know if that's FHE compliant. Also I notice that there's already an implementation for Softmax, although the docstring says it's not FHE compliant it doesn't elaborate as to why.

[jfrery]

We have this documentation / guide on how to proceed to implement a new onnx node. Let us know if anything is unclear!

https://docs.zama.ai/concrete-ml/developers/support_new_onnx_node