The test was failing in CI with Debug stdlib due to a different
ordering of struct_extract operations. Changed to use CHECK-DAG
for the two independent struct_extract operations that can appear
in either order.
rdar://165265446
This adds initial support for differentiation of functions that may produce `Error` result.
Essentially we wrap the pullback into `Optional` and emit a diamond-shape control flow pattern depending on whether the pullback value is available or not. VJP emission was modified to accommodate for this. In addition to this, some additional tricks are required as `try_apply` result is not available in the instruction parent block, it is available in normal successor basic block.
As a result we can now:
- differentiate an active `try_apply` result (that would be produced from `do ... try .. catch` constructions)
- `try_apply` when error result is unreachable (usually `try!` and similar source code constructs)
- Support (some) throwing functions with builtin differentiation operators. stdlib change will follow. Though we cannot support typed throws here (yet)
- Correctly propagate error types during currying around differentiable functions as well as type-checking for `@derivative(of:)` attribute, so we can register custom derivatives for functions producing error result
- Added custom derivative for `Optional.??` operator (note that support here is not yet complete as we cannot differentiate through autoclosures, so `x ?? y` works only if `y` is not active, e.g. a constant value).
Some fixes here and there
1. When differentiable nested function (closure) is specialized by capture promotion pass ensure we generate a differentiability witness for the specialized function as well. Ensure the original witness is removed if the original function becomes dead.
2. Differentiability witnesses for a function could originate either from its `@differentiable` attribute or from explicit `@derivative(of:)` attribute on the derivative. In the latter case the derivative itself might not be emitted, while original function is (e.g. original function is `@inlineable`, but derivative is `@usableFromInline`). Previously both cases were handled only when function body was emitted. As a result we missed witness in the aforementioned case. Ensure the
differentiability witness originating from `@derivative(of:)` is emitted even if we're not going to emit body of the derivative.
Fixes#59135
In #84704, some tests were XFAIL'ed since they've become failing. The
root cause of failures is lack of ownership info on the 2nd run of
AutoDiff closure specialization pass. Ownership info is required for the
pass run after #84704, so at the moment only the 1st run of the pass is
effective.
Several test cases still remain passing because for some cases we are
lucky and all the inlining required for specialization is done before
the 1st pass run. This patch enables such test cases back so we have at
least some test coverage.
`Array.TangentVector` conformance to `AdditiveArithmetic` was incorrect as the returned values weren't negated if the lhs was an empty vector (considered to be a zero tangentvector)
Beside supporting OSSA, this change significantly simplifies the pass.
The main change is that instead of starting at a closure (e.g. `partial_apply`) and finding all call sites, we now start at a call site and look for closures for all arguments. This makes a lot of things much simpler, e.g. not so many intermediate data structures are required to track all the states.
I needed to remove the 3 unit tests because the things those tests were testing are not there anymore. However, the pass is tested with a lot of sil tests (and I added quite a few), which should give good test coverage.
The old ClosureSpecializer pass is still kept in place, because at that point in the pipeline we don't have OSSA, yet. Once we have that, we can replace the old pass withe the new one.
However, the autodiff closure specializer already runs in the OSSA pipeline and there the new changes take effect.
These are tests that fail in the next commit without this flag. This
does not add -verify-ignore-unrelated to all tests with -verify, only
the ones that would fail without it. This is NFC since this flag is
currently a no-op.
The intent for `@inline(always)` is to act as an optimization control.
The user can rely on inlining to happen or the compiler will emit an error
message.
Because function values can be dynamic (closures, protocol/class lookup)
this guarantee can only be upheld for direct function references.
In cases where the optimizer can resolve dynamic function values the
attribute shall be respected.
rdar://148608854
Previously, AutoDiff closure specialization pass was triggered only on
VJPs containing single basic block. However, the pass logic allows
running on arbitrary VJPs. This PR enables the pass for all VJPs
unconditionally. So, if the pullback corresponding to multiple-BB VJP
accepts some closures directly as arguments, these closures might become
specialized by the pass. Closures passed via payload of branch tracing
enum are not specialized - this is subject for future changes.
The PR contains several commits.
1. The thing named "call site" in the code is partial_apply of pullback
corresponding to the VJP. This might appear only once, so we drop
support for multiple "call sites".
2. Enhance existing SILOptimizer tests for the pass.
3. Add validation-tests for single basic block case.
4. The change itself - delete check against single basic block.
5. Add validation-tests for multiple basic block case.
6. Add SILOptimizer tests for multiple basic block case.
This pass replaces `alloc_box` with `alloc_stack` if the box is not escaping.
The original implementation had some limitations. It could not handle cases of local functions which are called multiple times or even recursively, e.g.
```
public func foo() -> Int {
var i = 1
func localFunction() { i += 1 }
localFunction()
localFunction()
return i
}
```
The new implementation (done in Swift) fixes this problem with a new algorithm.
It's not only more powerful, but also simpler: the new pass has less than half lines of code than the old pass.
The pass is invoked in the mandatory pipeline and later in the optimizer pipeline.
The new implementation provides a module-pass for the mandatory pipeline (whereas the "regular" pass is a function pass).
This is required because the mandatory pass needs to remove originals of specialized closures, which cannot be done from a function-pass.
In the old implementation this was done with a hack by adding a semantic attribute and deleting the function later in the pipeline.
I still kept the sources of the old pass for being able to bootstrap the compiler without a host compiler.
rdar://142756547
Consider an `@_alwaysEmitIntoClient` function and a custom derivative
defined
for it. Previously, such a combination resulted different errors under
different
circumstances.
Sometimes, there were linker errors due to missing derivative function
symbol -
these occurred when we tried to find the derivative in a module, while
it
should have been emitted into client's code (and it did not happen).
Sometimes, there were SIL verification failures like this:
```
SIL verification failed: internal/private function cannot be serialized or serializable: !F->isAnySerialized() || embedded
```
Linkage and serialization options for the derivative were not handled
properly,
and, instead of PublicNonABI linkage, we had Private one which is
unsupported
for serialization - but we need to serialize `@_alwaysEmitIntoClient`
functions
so the client's code is able to see them.
This patch resolves the issue and adds proper handling of custom
derivatives
of `@_alwaysEmitIntoClient` functions. Note that either both the
function and
its custom derivative or none of them should have
`@_alwaysEmitIntoClient`
attribute, mismatch in this attribute is not supported.
The following cases are handled (assume that in each case client's code
uses
the derivative).
1. Both the function and its derivative are defined in a single file in
one module.
2. Both the function and its derivative are defined in different files
which
are compiled to a single module.
3. The function is defined in one module, its derivative is defined in
another
module.
4. The function and the derivative are defined as members of a protocol
extension in two separate modules - one for the function and one for the
derivative. A struct conforming the protocol is defined in the third
module.
5. The function and the derivative are defined as members of a struct
extension in two separate modules - one for the function and one for the
derivative.
The changes allow to define derivatives for methods of `SIMD`.
Fixes#54445
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Introduce a new pass MandatoryTempRValueElimination, which works as the original TempRValueElimination, except that it does not remove any alloc_stack instruction which are associated with source variables.
Running this pass at Onone helps to reduce copies of large structs, e.g. InlineArrays or structs containing InlineArrays.
Copying large structs can be a performance problem, even at Onone.
rdar://151629149
There are four attributes which serialize out a DeclNameRef, sometimes by dropping some of its components. Standardize them with a representation that can handle module selectors.
Both the syntax and relative order of the LLVM `nocapture` parameter
attribute changed upstream in 29441e4f5fa5f5c7709f7cf180815ba97f611297.
To reduce conflicts with rebranch, adjust FileCheck patterns to expect
both syntaxes and orders anywhere the presence of the attribute is not
critical to the test. These changes are temporary and will be cleaned
up once rebranch is merged into main.
This attribute was introduced in
7eca38ce76d5d1915f4ab7e665964062c0b37697 (llvm-project).
Match it using a wildcard regex, since it is not relevant to these
tests.
This is intended to reduce future conflicts with rebranch.
For example:
```
%0 = load %1
copy_addr %1 to %2
```
->
```
%0 = load %1
store %0 to %2
```
This is important for MandatoryRedundantLoadElimination to be able to create statically initialized globals in the mandatory pipeline.
For example:
```
public struct MyStruct {
public static let r: Range<Int> = 1 ..< 3
}
```
gets a statically initialized global, even at Onone, with this improvement.
rdar://149356742
* `sitofp` signed integer to floating point
* `rint` round floating point to integral
* `bitcast` between integer and floating point
Constant folding `bitcast`s also made it necessary to rewrite constant folding for Nan and inf values, because the old code explicitly checked for `bitcast` intrinsics.
Relying on constant folded `bitcast`s makes the new version much simpler.
It is important to constant fold these intrinsics already in SIL because it enables other optimizations.
If the default argument generator (and, consequently, the function taking this default argument) has public visibility, it's OK to have a closure (which always has private visibility) as the default value of the argument.
Inside fragile functions, we expect function derivatives to be public, which could be achieved by either explicitly marking the functions as differentiable or having a public explicit derivative defined for them. This is obviously not
possible for single and double curry thunks which are a special case of `AutoClosureExpr`.
Instead of looking at the thunk itself, we unwrap it and look at the function being wrapped. While the thunk itself and its differentiability witness will not have public visibility, it's not an issue for the case where the function being wrapped (and its witness) have public visibility.
Fixes#54819Fixes#75776
