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fix overspecializing constants in compilation #22816

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eellison
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When we specialize the tensor type of constants in compilation it causes all sorts of problems.

Fix for #22809

@eellison eellison requested review from suo and driazati July 12, 2019 19:51
@pytorchbot pytorchbot added the oncall: jit Add this issue/PR to JIT oncall triage queue label Jul 12, 2019
@eellison eellison changed the title fix overspecializing constants fix overspecializing constants in compilation Jul 12, 2019
@@ -96,6 +96,10 @@ struct ConstantTableValue : public SugaredValue {
<< constants_.size() << " entries).";
}
Value* value = m.graph()->insertConstant(constants_[offset], nullptr, loc);

// specializing tensor type on compilation messes up typing relations
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What typing relations does it mess up? Shouldn't we fix where those types are checked instead of throwing away the shape info?

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The shape info gets re-specialized again later anyway. It messes up things like in the example, where a list of complete tensor types does not subtype a list of tensor types, and you get error messages like:

  aten::cat(Tensor[] tensors, int dim=<default>) -> Tensor:
  Expected a value of type 'List[Tensor]' for argument 'tensors' but instead found type 'List[Tensor]'.

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This doesn't seem like the right place to fix this. Afterall, this same bug will exist anywhere insertConstant is used. insertConstant would be better, with shape propagation introducing a shape for a constant tensor.

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@eellison eellison Jul 19, 2019

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i don't think there's another pathway to create a specialized tensor type during typechecking. the shape analysis prim::Constant refinement already exists.

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@eellison has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

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@eellison merged this pull request in f2f3e8a.

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6 participants