[AutoDiff upstream] Serialize derivative function configurations. #30672
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Serialize derivative function configurations per module.
@differentiableand@derivativeattributes register derivatives forAbstractFunctionDecls for a particular "derivative function configuration":parameter indices and dervative generic signature.
To find
@derivativefunctions registered in other Swift modules, derivativefunction configurations must be serialized per module. When configurations for
a
AbstractFunctionDeclare requested, all configurations from importedmodules are deserialized. This module serialization technique has precedent: it
is used for protocol conformances (e.g. extension declarations for a nominal
type) and Obj-C members for a class type.
Add
AbstractFunctionDecl::getDerivativeFunctionConfigurationsentry pointfor accessing derivative function configurations.
In the differentiation transform: use
AbstractFunctionDecl::getDerivativeFunctionConfigurationsto implementfindMinimalDerivativeConfigurationfor canonical derivative functionconfiguration lookup, replacing
getMinimalASTDifferentiableAttr.Resolves TF-1100.
Upstreams #28608 from
tensorflowbranch.Tests will be added when the differentiation transform is upstreamed: TF-1211.