Add the `@differentiable` function conversion pipeline:
- New expressions that convert between `@differentiable`,
`@differentiable(linear)`, and non-`@differentiable` functions:
- `DifferentiableFunction`
- `LinearFunction`
- `DifferentiableFunctionExtractOriginal`
- `LinearFunctionExtractOriginal`
- `LinearToDifferentiableFunction`
- All the AST handling (e.g. printing) necessary for those expressions.
- SILGen for those expressions.
- CSApply code that inserts these expressions to implicitly convert between
the various function types.
- Sema tests for the implicit conversions.
- SILGen tests for the SILGen of these expressions.
Resolves TF-833.
Use `TypeChecker::checkDeclarationAvailability` instead of `isDeclAvailable`,
that is a proper API endpoint which does flag checking before calling
`isDeclAvailable` internally.
Add type checking for `@differentiable` function types:
- Check that parameters and results conform to `Differentiable`.
- Implicitly conform parameters and results whose types are generic parameters
to `Differentiable`.
- Upstream most of the differentiable_func_type_type_checking.swift test from
`tensorflow` branch. A few function conversion tests have not been added
because they depend on the `@differentiable` function conversion pipeline.
Diagnose gracefully when the `Differentiable` protocol is unavailable because
`_Differentiation` has not been imported.
Resolves TF-823 and TF-1219.
A request is intended to be a pure function of its inputs. That function could, in theory, fail. In practice, there were basically no requests taking advantage of this ability - the few that were using it to explicitly detect cycles can just return reasonable defaults instead of forwarding the error on up the stack.
This is because cycles are checked by *the Evaluator*, and are unwound by the Evaluator.
Therefore, restore the idea that the evaluate functions are themselves pure, but keep the idea that *evaluation* of those requests may fail. This model enables the best of both worlds: we not only keep the evaluator flexible enough to handle future use cases like cancellation and diagnostic invalidation, but also request-based dependencies using the values computed at the evaluation points. These aforementioned use cases would use the llvm::Expected interface and the regular evaluation-point interface respectively.
Introduce evaluator::SideEffect, the type of a request that performs
some operation solely to execute its side effects. Thankfully, there are
precious few requests that need to use this type in practice, but it's
good to call them out explicitly so we can get around to making them
behave much more functionally in the future.
Checking for `-disable-availability-checking` in
`ConstraintSystem::isDeclUnavailable` caused a regression with
obsolete/introduced checking. Let's rely on
`DeclAttributes::isUnavailable` and `TypeChecker::isDeclAvailable`
to do the right thing instead.
Resolves: rdar://problem/60898369
This reverts commit f0cdd76f18, reversing
changes made to 703fe0f1a1.
Revert "IRGen: Refactor getObjCEncodingForMethod and getObjectEncodingFromClangNode into one"
This reverts commit 0082682b0d.
Revert "Merge pull request #30438 from aschwaighofer/irgen_prefer_clang_type_encoding"
This reverts commit eeb7fa52b2, reversing
changes made to 77af77fa8a.
Revert "Merge pull request #30433 from aschwaighofer/irgen_no_duplicate_objc_method_descriptor_entries"
This reverts commit 77af77fa8a, reversing
changes made to 841eeb05b0.
This reverts the changes for
rdar://60461850, rdar://60474785, rdar://60778637
There is still at least an issue that we address with PR#30654.
Revert until we have confidence that this is the right fix set.
Property wrappers are allowed to infer the type of a variable, but this
only worked when the property wrapper was provided with an explicit
initialization, e.g.,
@WrapsAnInt() var x // infers type Int from WrapsAnInt.wrappedValue
However, when default initialization is supported by the property wrapper,
dropping the parentheses would produce an error about the missing type
annotation
@WrapsAnInt var x
Make this second case behave like the first, so that default initialization
works consistently with the explicitly-specified version.
Fixes rdar://problem/59471019.
RedundantPhiElimination eliminates block phi-arguments which have the same value as other arguments of the same block.
This also works with cycles, like two equivalent loop induction variables. Such patterns are generated e.g. when using stdlib's enumerated() on Array.
preheader:
br bb1(%initval, %initval)
header(%phi1, %phi2):
%next1 = builtin "add" (%phi1, %one)
%next2 = builtin "add" (%phi2, %one)
cond_br %loopcond, header(%next1, %next2), exit
exit:
is replaced with
preheader:
br bb1(%initval)
header(%phi1):
%next1 = builtin "add" (%phi1, %one)
%next2 = builtin "add" (%phi1, %one) // dead: will be cleaned-up later
cond_br %loopcond, header(%next1), exit
exit:
Any remaining dead or "trivially" equivalent instructions will then be cleaned-up by DCE and CSE, respectively.
rdar://problem/33438123
Add a request to lookup all implied conformances for use while
typechecking the primary. This provides a cache-point for
evaluator-based dependency tracking.
Add `linear_function` and `linear_function_extract` instructions.
`linear_function` creates a `@differentiable(linear)` function-typed value from
an original function operand and a transpose function operand (optional).
`linear_function_extract` extracts either the original or transpose function
value from a `@differentiable(linear)` function.
Resolves TF-1142 and TF-1143.
For instance:
--
let globalVar = {
func something(arg: Int) -> Int {
#^HERE^#
}
return something(12)
}()
--
We want to consider this as a top-level completion, not a function body
completion.
rdar://problem/60838686
We could assume usr/include belongs to header search paths. If a header
is located in a deeper location inside this directory, we need to print
the additional path components.
rdar://60857172
Previously solution application only supported references to
key path dynamic member lookup as components but it should support both kinds.
Resolves: rdar://problem/60225883
Resolves: [SR-12313](https://bugs.swift.org/browse/SR-12313)
Several tests related to indexing system modules were taking a considerable
amount of time (100+ seconds in the worst case) indexing the standard library.
This adds a frontend option to skip it and updates those tests to pass it.
Generate `differentiable_function` and `differentiable_function_extract` in
derivative witness table/vtable thunks.
`differentiation_function` is later canonicalized by the differentiation
transform.
Add SIL FileCheck tests.
Add `AdditiveArithmetic` derived conformances for structs, gated by the
`-enable-experimential-additive-arithmetic-derivation` flag.
Structs whose stored properties all conform to `AdditiveArithmetic` can derive
`AdditiveArithmetic`:
- `static var zero: Self`
- `static func +(lhs: Self, rhs: Self) -> Self`
- `static func -(lhs: Self, rhs: Self) -> Self`
- An "effective memberwise initializer":
- Either a synthesized memberwise initializer or a user-defined initializer
with the same type.
Effective memberwise initializers are used only by derived conformances for
`Self`-returning protocol requirements like `AdditiveArithmetic.+`, which
require memberwise initialization.
Resolves TF-844.
Unblocks TF-845: upstream `Differentiable` derived conformances.
`SK_Fix` was used to indicate that solver has encountered a hole
along the current path but since there is `SK_Hole` now, increasing
`SK_Fix` no longer makes sense.
Problems related to incorrect use of `_` where previously diagnosed
by syntactic diagnostics which meant that it could only happen on
type-checked AST. This is no longer a case so we don't have to allow
incorrect uses of `_` to form solution without any fixes.
Previously, all witnesses of a `@differentiable` protocol requirement were
required to have the same attribute (or one with superset parameter indices).
However, this leads to many annotations on witnesses and is not ideal for
usability. `@differentiable` attributes are really only significant on
public witnesses, so that they are clearly `@differentiable` at a glance (in
source code, interface files, and API documentation), without looking through
protocol conformance hierarchies.
Now, only *public* witnesses of `@differentiable` protocol requirements are
required to have the same attribute (or one with superset parameter indices).
For less-visible witnesses, an implicit `@differentiable` attribute is created
with the same configuration as the requirement's.
Resolves TF-1117.
Upstreams #29771 from tensorflow branch.
Define type signatures and SILGen for the following builtins:
```
/// Applies the {jvp|vjp} of `f` to `arg1`, ..., `argN`.
func applyDerivative_arityN_{jvp|vjp}(f, arg1, ..., argN) -> jvp/vjp return type
/// Applies the transpose of `f` to `arg`.
func applyTranspose_arityN(f, arg) -> transpose return type
/// Makes a differentiable function from the given `original`, `jvp`, and
/// `vjp` functions.
func differentiableFunction_arityN(original, jvp, vjp)
/// Makes a linear function from the given `original` and `transpose` functions.
func linearFunction_arityN(original, transpose)
```
Add SILGen FileCheck tests for all builtins.
