[AutoDiff] Support forward mode differentiation of functions with inout parameters (swiftlang#33584)

Adds forward mode support for `apply` instruction with `inout` arguments.

Example of supported code:
```
func add(_ x: inout Float, _ y: inout Float) -> Float {
  var result = x
  result += y
  return result
}
print(differential(at: 1, 1, in: add)(1, 1)) // prints "2"
```

Author: efremale

lib/SILOptimizer/Differentiation/JVPCloner.cpp

@@ -455,18 +455,6 @@ class JVPCloner::Implementation final
       return;
     }
 
-    // Diagnose functions with active inout arguments.
-    // TODO(TF-129): Support `inout` argument differentiation.
-    for (auto inoutArg : ai->getInoutArguments()) {
-      if (activityInfo.isActive(inoutArg, getIndices())) {
-        context.emitNondifferentiabilityError(
-            ai, invoker,
-            diag::autodiff_cannot_differentiate_through_inout_arguments);
-        errorOccurred = true;
-        return;
-      }
-    }
-
     auto loc = ai->getLoc();
     auto &builder = getBuilder();
     auto origCallee = getOpValue(ai->getCallee());
@@ -1241,6 +1229,10 @@ class JVPCloner::Implementation final
     SmallVector<SILValue, 8> differentialAllResults;
     collectAllActualResultsInTypeOrder(
         differentialCall, differentialDirectResults, differentialAllResults);
+    for (auto inoutArg : ai->getInoutArguments())
+      origAllResults.push_back(inoutArg);
+    for (auto inoutArg : differentialCall->getInoutArguments())
+      differentialAllResults.push_back(inoutArg);
     assert(applyIndices.results->getNumIndices() ==
            differentialAllResults.size());
 
@@ -1484,11 +1476,14 @@ void JVPCloner::Implementation::prepareForDifferentialGeneration() {
   auto origIndResults = original->getIndirectResults();
   auto diffIndResults = differential.getIndirectResults();
 #ifndef NDEBUG
-  unsigned numInoutParameters = llvm::count_if(
-      original->getLoweredFunctionType()->getParameters(),
-      [](SILParameterInfo paramInfo) { return paramInfo.isIndirectInOut(); });
-  assert(origIndResults.size() + numInoutParameters == diffIndResults.size());
+  unsigned numNonWrtInoutParameters = llvm::count_if(
+    range(original->getLoweredFunctionType()->getNumParameters()),
+    [&] (unsigned i) {
+      auto &paramInfo = original->getLoweredFunctionType()->getParameters()[i];
+      return paramInfo.isIndirectInOut() && !getIndices().parameters->contains(i);
+    });
 #endif
+  assert(origIndResults.size() + numNonWrtInoutParameters == diffIndResults.size());
   for (auto &origBB : *original)
     for (auto i : indices(origIndResults))
       setTangentBuffer(&origBB, origIndResults[i], diffIndResults[i]);
@@ -1521,23 +1516,10 @@ void JVPCloner::Implementation::prepareForDifferentialGeneration() {
   auto origParams = origTy->getParameters();
   auto indices = witness->getSILAutoDiffIndices();
 
-  // Add differential results.
-  Optional<SILParameterInfo> inoutDiffParam = None;
-  for (auto origParam : origTy->getParameters()) {
-    if (!origParam.isIndirectInOut())
-      continue;
-    inoutDiffParam = origParam;
-  }
-
-  if (inoutDiffParam) {
-    dfResults.push_back(
-        SILResultInfo(inoutDiffParam->getInterfaceType()
-                          ->getAutoDiffTangentSpace(lookupConformance)
-                          ->getType()
-                          ->getCanonicalType(witnessCanGenSig),
-                      ResultConvention::Indirect));
-  } else {
-    for (auto resultIndex : indices.results->getIndices()) {
+
+  for (auto resultIndex : indices.results->getIndices()) {
+    if (resultIndex < origTy->getNumResults()) {
+      // Handle formal original result.
       auto origResult = origTy->getResults()[resultIndex];
       origResult = origResult.getWithInterfaceType(
           origResult.getInterfaceType()->getCanonicalType(witnessCanGenSig));
@@ -1548,6 +1530,25 @@ void JVPCloner::Implementation::prepareForDifferentialGeneration() {
                             ->getCanonicalType(witnessCanGenSig),
                         origResult.getConvention()));
     }
+    else {
+      // Handle original `inout` parameter.
+      auto inoutParamIndex = resultIndex - origTy->getNumResults();
+      auto inoutParamIt = std::next(
+          origTy->getIndirectMutatingParameters().begin(), inoutParamIndex);
+      auto paramIndex =
+          std::distance(origTy->getParameters().begin(), &*inoutParamIt);
+      // If the original `inout` parameter is a differentiability parameter, then
+      // it already has a corresponding differential parameter. Skip adding a
+      // corresponding differential result.
+      if (indices.parameters->contains(paramIndex))
+        continue;
+      auto inoutParam = origTy->getParameters()[paramIndex];
+      auto paramTan = inoutParam.getInterfaceType()->getAutoDiffTangentSpace(
+          lookupConformance);
+      assert(paramTan && "Parameter type does not have a tangent space?");
+      dfResults.push_back(
+          {paramTan->getCanonicalType(), ResultConvention::Indirect});
+    }
   }
 
   // Add differential parameters for the requested wrt parameters.

stdlib/public/Differentiation/FloatingPointDifferentiation.swift.gyb

@@ -205,8 +205,9 @@ extension ${Self} {
   static func _jvpMultiplyAssign(_ lhs: inout ${Self}, _ rhs: ${Self}) -> (
     value: Void, differential: (inout ${Self}, ${Self}) -> Void
   ) {
+    let oldLhs = lhs
     lhs *= rhs
-    return ((), { $0 *= $1 })
+    return ((), { $0 = $0 * rhs + oldLhs * $1 })
   }
 
   ${Availability(bits)}
@@ -251,8 +252,9 @@ extension ${Self} {
   static func _jvpDivideAssign(_ lhs: inout ${Self}, _ rhs: ${Self}) -> (
     value: Void, differential: (inout ${Self}, ${Self}) -> Void
   ) {
+    let oldLhs = lhs
     lhs /= rhs
-    return ((), { $0 /= $1 })
+    return ((), { $0 = ($0 * rhs - oldLhs * $1) / (rhs * rhs)  })
   }
 }
 

test/AutoDiff/SILOptimizer/forward_mode_diagnostics.swift

@@ -1,4 +1,4 @@
-// RUN: %target-swift-frontend -enable-experimental-forward-mode-differentiation -emit-sil -verify %s
+// RUN: %target-swift-frontend -emit-sil -enable-experimental-forward-mode-differentiation -verify %s
 
 // Test forward-mode differentiation transform diagnostics.
 
@@ -46,8 +46,6 @@ func nonVariedResult(_ x: Float) -> Float {
 // Multiple results
 //===----------------------------------------------------------------------===//
 
-// TODO(TF-983): Support differentiation of multiple results.
-/*
 func multipleResults(_ x: Float) -> (Float, Float) {
   return (x, x)
 }
@@ -56,28 +54,21 @@ func usesMultipleResults(_ x: Float) -> Float {
   let tuple = multipleResults(x)
   return tuple.0 + tuple.1
 }
-*/
 
 //===----------------------------------------------------------------------===//
 // `inout` parameter differentiation
 //===----------------------------------------------------------------------===//
 
-// expected-error @+1 {{function is not differentiable}}
 @differentiable
-// expected-note @+1 {{when differentiating this function definition}}
 func activeInoutParamNonactiveInitialResult(_ x: Float) -> Float {
   var result: Float = 1
-  // expected-note @+1 {{cannot differentiate through 'inout' arguments}}
   result += x
   return result
 }
 
-// expected-error @+1 {{function is not differentiable}}
 @differentiable
-// expected-note @+1 {{when differentiating this function definition}}
 func activeInoutParamTuple(_ x: Float) -> Float {
   var tuple = (x, x)
-  // expected-note @+1 {{cannot differentiate through 'inout' arguments}}
   tuple.0 *= x
   return x * tuple.0
 }
@@ -94,49 +85,37 @@ func activeInoutParamControlFlow(_ array: [Float]) -> Float {
   return result
 }
 
-struct Mut: Differentiable {}
-extension Mut {
-  @differentiable(wrt: x)
-  mutating func mutatingMethod(_ x: Mut) {}
-}
-
 // FIXME(TF-984): Forward-mode crash due to unset tangent buffer.
 /*
-@differentiable(wrt: x)
-func nonActiveInoutParam(_ nonactive: inout Mut, _ x: Mut) -> Mut {
-  return nonactive.mutatingMethod(x)
+struct X: Differentiable {
+  var x : Float
+
+  @differentiable(wrt: y)
+  mutating func mutate(_ y: X) { self.x = y.x }
 }
-*/
 
-// FIXME(TF-984): Forward-mode crash due to unset tangent buffer.
-/*
-@differentiable(wrt: x)
-func activeInoutParamMutatingMethod(_ x: Mut) -> Mut {
-  var result = x
-  result = result.mutatingMethod(result)
-  return result
+@differentiable
+func activeMutatingMethod(_ x: Float) -> Float {
+  let x1 = X.init(x: x)
+  var x2 = X.init(x: 0)
+  x2.mutate(x1)
+  return x1.x
 }
 */
 
-// FIXME(TF-984): Forward-mode crash due to unset tangent buffer.
-/*
-@differentiable(wrt: x)
-func activeInoutParamMutatingMethodVar(_ nonactive: inout Mut, _ x: Mut) -> Mut {
-  var result = nonactive
-  result = result.mutatingMethod(x)
-  return result
+
+struct Mut: Differentiable {}
+extension Mut {
+  @differentiable(wrt: x)
+  mutating func mutatingMethod(_ x: Mut) {}
 }
-*/
 
-// FIXME(TF-984): Forward-mode crash due to unset tangent buffer.
-/*
 @differentiable(wrt: x)
-func activeInoutParamMutatingMethodTuple(_ nonactive: inout Mut, _ x: Mut) -> Mut {
-  var result = (nonactive, x)
-  let result2 = result.0.mutatingMethod(result.0)
-  return result2
+func activeInoutParamMutatingMethod(_ x: Mut) -> Mut {
+  var result = x
+  result.mutatingMethod(result)
+  return result
 }
-*/
 
 //===----------------------------------------------------------------------===//
 // Subset parameter differentiation thunks