Yes your observation is correct. We cannot support PT retinanet for two reasons:
* Our dynamic strided slice doesn't work great when input shape is partially static/dynamic. It makes output shape dynamic in all dimensions, even if slicing is only in a certain dimension (batch axis etc). Unfortunately this is a limitation of how runtime shapes are represented in Relay: Runtime shapes are fully dynamic in all dimensions. * Our `split` op doesn't support dynamic sections. This is the error you got. Even if the first point cannot be overcome, in principle we can support retinanet if our `split` op supports dynamic sections (although performance would be suboptimal than the ideal case). This would be an easier solution in the short term. --- [Visit Topic](https://discuss.tvm.apache.org/t/pytorch-dyn-strided-slice-loses-shape-information/10655/2) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/88ef04b9311ceac616fb64ea2ae653675eb5b021ea6fe090bbad4b5b99e143d3).
