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[AutoDiff] Directly SILGen @derivative
attributes to diff witnesses.
#28621
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[AutoDiff] Directly SILGen `@derivative` attributes to diff witnesses.
dan-zheng 8415cbc
Update checkout for tensorflow-swift-apis.
dan-zheng f709407
Clarify comment in `TBDGenVisitor::addDerivativeAttr`.
dan-zheng 0c531bb
Address review feedback.
dan-zheng a26b443
Improve test name.
dan-zheng 571e9d9
Fix `@differentiable` attribute requirement type-checking in non-prim…
dan-zheng 979914e
Implement `@derivative` attribut serialization.
dan-zheng f9ced25
Address review feedback.
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Would it be possible to use the derivative config list that you created in the previous serialization PR, so that we do not have to maintain another list?
Could the derivative config list actually also replace
DifferentiableAttrs
?Uh oh!
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I wondered the same. The derivative function configuration doesn't currently store whether the configuration came from (a
@differentiable
attribute or@derivative
attribute), and that information is important for users ofDifferentiableAttrs
andDerivativeAttrs
, which check duplicate attributes of a specific kind, not just configurations.I haven't thought deeply about this. I'll file an issue tracking this question if it isn't resolved by the time this PR is merged.
Edit: filed TF-1042 to track Investigate removing/moving
ASTContext::{Differentiable,Derivative}Attrs
.Using
AbstractFunctionDecl::getDerivativeFunctionConfigurations
to detect duplicate@differentiable
and@derivative
attributes may be significant for cross-file duplicate derivative registration (TF-1021).If you import a derivative for
func foo
, you shouldn't be able to register a new derivative forfunc foo
with the same configuration.This requires changing
AbstractFunctionDecl::getDerivativeFunctionConfigurations
to return more information thanArrayRef<AutoDiffConfig>
.OptionSet
perAutoDiffConfig
, specifying where theAutoDiffConfig
came from:@differentiable
attribute@derivative
JVP@derivative
VJP@differentiable
/@derivative
attributeSourceLoc
.