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This repository has been archived by the owner on Nov 17, 2023. It is now read-only.
I was trying to implement a Relational Network: https://arxiv.org/abs/1706.01427
It seems to be related to using for loops within the forward pass, which I assumed would be supported since the API is similar to pytorch
libc++abi.dylib: terminating with uncaught exception of type dmlc::Error: [16:57:57] src/engine/./threaded_engine.h:347: [16:57:57] src/operator/tensor/./matrix_op-inl.h:964: CropAssign only supports kWriteTo
Is there a different way to implement this that may avoid this issue?
I guess I essentially need to do the equivalent of the code below, but with the all_relations array being a memory view of the original array rather than a copy, does anyone know of a good tutorial or example of how to implement this with the NDArray API?
The model doesn't throw an exception on the latest mainline branch built from source, but I haven't gotten the network produce anything other than the same prediction for every sample.
And it throws an exception if I try to apply batch-normalization to stabilize training.
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I was trying to implement a Relational Network: https://arxiv.org/abs/1706.01427
It seems to be related to using for loops within the forward pass, which I assumed would be supported since the API is similar to pytorch
Implementation is below
The error I'm getting is
Is there a different way to implement this that may avoid this issue?
I guess I essentially need to do the equivalent of the code below, but with the all_relations array being a memory view of the original array rather than a copy, does anyone know of a good tutorial or example of how to implement this with the NDArray API?
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