[AutoDiff] Add @differentiable
fixit for protocols/classes.
#29332
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Outdated suggestions cannot be applied.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.
For protocol requirements and class members with
@differentiable
attribute,conforming types and subclasses must have the same
@differentiable
attribute(or one with a superset of differentiability parameters) on implementing/
overriding declarations.
For implementing/overriding declarations that are missing a
@differentiable
attribute, emit a fixit that adds the missing attribute.
Resolves TF-1118.
This
@differentiable
attribute usability improvement was discussed at the1/17/2020 Swift for TensorFlow open design meeting.
Example:
Before:
After:
The second note
protocol requires function 'callAsFunction' with type '(Float) -> Float'; do you want to add a stub?
is a bit confusing. Disabling it would be ideal.