check compatibility with Mooncake on CPU #640

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1. CarloLucibello

   added

   good first issueGood for newcomersGood for newcomers

   on Feb 21, 2026
2. Parvm1102 commented on Mar 2, 2026

   

   Parvm1102

   on Mar 2, 2026

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   Hi @CarloLucibello ,

   I have done some progress on this: I've set up the test suite for the spatial convolutional layers comparing Mooncake and Zygote.

   Results: 16 / 20 conv layers are compatible (935 passed tests).
   However, there are errors with these two layers:

   • DConv (3 errors): Fails during reverse-mode differentiation (might be related to Wrong implementation DConv #592).
   • ChebConv (1 error): Crashes during gradient cache preparation before the test executes.

   2 layers were excluded: CGConv and GMMConv, same as existing tests.

   How would you like me to proceed? Should I dig into finding workarounds for DConv and ChebConv, or should I move on to testing the other layer categories (pool.jl, heteroconv.jl, etc.)? I can also open a PR if you want to see the code.
3. CarloLucibello commented on Mar 3, 2026

   

   CarloLucibello

   on Mar 3, 2026

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   Hi @Parvm1102, thanks.
   I suggest you implement something similar to the test infrastructure of Flux (see the test_gradients function)
   https://github.com/FluxML/Flux.jl/blob/master/test/test_utils.jl#L82

   Then open a PR with just the conv layers tested and we will discuss there.
4. Parvm1102 commented on Mar 5, 2026

   

   Parvm1102

   on Mar 5, 2026

   Last edited by Parvm1102

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   Currently incompatible layers (found in #641 and #642 ):

   • ChebConv
   • DConv
   • GNNChain
   • GConvLSTMCell / GConvLSTM
   • GConvGRUCell / GConvGRU
   • DCGRUCell/ DCGRU
   • EvolveGCNOCell
5. muskan-101 commented on Mar 18, 2026

   

   muskan-101

   on Mar 18, 2026

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   @CarloLucibello Hey, Can I work on this issue I have theoretical knowledge of Neural Networks and a little hands on experience as well, we were taught Neural Networks and fuzzy logic as a separate course in our college. So should I work on this or is there any issue that will be more suitable for me. I would really appreciate your suggestions.
6. jeanphilippeadielou commented on Mar 27, 2026

   

   jeanphilippeadielou

   on Mar 27, 2026

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   Hi, I'm willing to have a look. I got a few basis in Julia and got a good understanding of Neural Networks, as well as Graphs/Networks more broadly on the theoretical side.
7. CarloLucibello commented on Jul 31, 2026

   

   CarloLucibello

   on Jul 31, 2026

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   @Parvm1102 this issue should be updated with the current status
8. CarloLucibello

   changed the title [-]check compatibility with Mooncake[/-] [+]check compatibility with Mooncake on CPU[/+] on Jul 31, 2026
9. CarloLucibello commented on Jul 31, 2026

   

   CarloLucibello

   on Jul 31, 2026

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   let's keep track of CUDA compatibility in #702 and leave this issue for CPU
10. jeanphilippeadielou commented on Aug 13, 2026

    

    jeanphilippeadielou

    on Aug 13, 2026 via email

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    I've taken good note of that.

    …

    On Fri, Jul 31, 2026 at 2:12 AM Carlo Lucibello ***@***.***> wrote: *CarloLucibello* left a comment (JuliaGraphs/GraphNeuralNetworks.jl#640) <#640 (comment)> let's keep track of CUDA compatibility in #702 <#702> and leave this issue for CPU — Reply to this email directly, view it on GitHub <#640?email_source=notifications&email_token=AIQFCPNCHHVKPVXX2GVKXM35HQ2GLA5CNFSNUABFM5UWIORPF5TWS5BNNB2WEL2JONZXKZKDN5WW2ZLOOQXTKMJTHE4TAMZVHE32M4TFMFZW63VHMNXW23LFNZ2KKZLWMVXHJLDGN5XXIZLSL5RWY2LDNM#issuecomment-5139903597>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AIQFCPMQK4UNKHRGJKGG74T5HQ2GLAVCNFSNUABFKJSXA33TNF2G64TZHM2DAMJSGI3TQOJYHNEXG43VMU5TGOJXGE3DGNBXGE2KC5QC> . You are receiving this because you commented.Message ID: ***@***.***>