Open gkrivor opened 11 months ago
.take
Thank you for looking into this issue! Please let us know if you have any questions or require any help.
Hello @sydarb! Thank you for taking a look, please let us know if you have any questions. Just yesterday our CONTRIBUTING.md has been updated with a technical guide - I highly recommend checking it out. :)
Hello @sydarb, are you still working on this issue?
I am happy to announce that we have created a channel dedicated to Good First Issues support on our Intel DevHub Discord server! Join it to receive support, engage in discussions, ask questions and talk to OpenVINO developers.
.take
Thank you for looking into this issue! Please let us know if you have any questions or require any help.
Hello @tanishka321, can we help you with anything?
Hello @tanishka321, thank you for your contribution! I've reviewed the PR #22650, unfortunately the proposed solution is not working yet. Please take a look at the latest review comments.
@gkrivor As ONNX SoftmaxCrossEntropyLoss is training related operator, I would suggest to verify it's applicability for custom decomposition in OpenVINO ONNX FE.
hey @tanishka321 will you work on this ticket? Or maybe you don't have time and we should move it back for other person?
Hi @mlukasze if the current assignee isn't working on the issue, can I take it up?
moving to you @kshitij01042002, have fun :)
Hi @mlukasze I am working on this issue, sorry I was caught up with my academics and was not able to do it. Also there was a request can you please look into the mail sent by @PRATHAM-SPS. It was needed on an urgent basis.
cc: @p-wysocki
Context
Neural networks are graphs consisting of nodes called operators. Each operator corresponds to a mathematical function, usually described in framework's documentation or an AI standard, such as ONNX. OpenVINO ONNX Frontend is a component responsible for working with ONNX graphs and requires implementation of different ONNX operators in order to use ONNX models. This task requires extending OpenVINO ONNX Frontend with Function SoftmaxCrossEntropyLoss.
Necessary help will be provided by ONNX Fronted team.
What needs to be done?
Operator details can be found in ONNX Operators More details can be found in ONNX Changelog
.hpp
and.cpp
files for *Windows hereExample Pull Requests
Resources
Contact points
@gkrivor
Ticket
No response