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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71186
So far we've only supported scalar inputs, but couldn't handle scalar outputs
or intermediates. This PR adds it.
Scalar outputs are returned as 0-dim tensors. If the kernel is invoked on a
stack of IValues, we correctly convert the results to scalar IValues when
needed. If the kernel is invoked with a vector of void* pointers, everything
works out of the box without any conversions.
Lowerings for scalar operators are a bit tricky. Usual lowerings return a pair
<Buf, Stmt> (aka Tensor), but for scalar operators we also want to have the
corresponding Var that the lowering function supposedly creates (in theory we
could just use Loads and Stores, but I'm worried it can affect performance as
there is no guarantee this will be optimized by LLVM). So, what we do here to
work around this is we return a fake buf + stmt that sets the corresponding
var. Then outside of the lowering we create a real buffer and generate a Store
to it with the value from the variable we passed as the base handle of the fake
buf. This real buffer is then treated as usual by the rest of the system and we
can use it if we need to return this scalar value as a kernel output. If we do
not need to return it, then the Store will be deleted by the DCE pass.
Differential Revision:
D33539324
D33539324
Test Plan: Imported from OSS
Reviewed By: navahgar
Pulled By: ZolotukhinM
fbshipit-source-id: ab4524b9820ce204f106effcf6232ed33d4ee223
(cherry picked from commit
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| api | ||
| c10d | ||
| common | ||
| dist_autograd | ||
| jit | ||
| lazy | ||
| lite_interpreter_runtime | ||
| monitor | ||
| rpc | ||
| tensorexpr | ||
| __init__.py | ||