As commented by the author of PyTorchTVM,
https://github.com/apache/tvm-rfcs/pull/25#issuecomment-908041324, many people
are interested in this feature. Also people are actively talking about deeper
integration of TVM into PyTorch workflow. So we should definitely land this.
As for me personal
> I wonder if we could work around it by providing a "dlpack-compat" header
Does this mean the same thing as
https://github.com/pytorch/pytorch/pull/65047#issuecomment-972734912? (which
sounds good to me). Anyway it seems we cannot count on the PyTorch-side to
change, so I'd say anything that c
@masahi So I had hoped to get the dlpack header version in PyTorch bumped (see
the linked bug) but Facebook has internal uses that let it insist on the old
one.
I wonder if we could work around it by providing a "dlpack-compat" header that
defines the names for the types / fields? Or I could try
@mbs-octoml Hi~ Many thanks for your reply! Here are several questions of me:
1. What does `call_lowered` mean? Does it mean we can put PrimFuncs and relay
functions into the same IRModule and make calls to each other now?
2. For the `VirtualDevice`, it would be the interface to keep all info
@t-vi Is this still WIP? I'm happy to merge whenever you think it is ready.
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This should be supported now.
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