[Mlir-commits] [mlir] 9580468 - [mlir][affine] Enforce each result type to match Reduction ops in affine.parallel verifier
Mehdi Amini
llvmlistbot at llvm.org
Sun Oct 1 14:24:31 PDT 2023
Author: Zhenyan Zhu
Date: 2023-10-01T14:24:17-07:00
New Revision: 9580468302a1c8f6236a121163c9087ac4e02cfe
URL: https://github.com/llvm/llvm-project/commit/9580468302a1c8f6236a121163c9087ac4e02cfe
DIFF: https://github.com/llvm/llvm-project/commit/9580468302a1c8f6236a121163c9087ac4e02cfe.diff
LOG: [mlir][affine] Enforce each result type to match Reduction ops in affine.parallel verifier
This patch updates AffineParallelOp::verify() to check each result type matches
its corresponding reduction op (i.e, the result type must be a `FloatType` if
the reduction attribute is `addf`)
affine.parallel will crash on --lower-affine if the corresponding result type
cannot match the reduction attribute.
```
%128 = affine.parallel (%arg2, %arg3) = (0, 0) to (8, 7) reduce ("maxf") -> (memref<8x7xf32>) {
%alloc_33 = memref.alloc() : memref<8x7xf32>
affine.yield %alloc_33 : memref<8x7xf32>
}
```
This will crash and report a type conversion issue when we run `mlir-opt --lower-affine`
```
Assertion failed: (isa<To>(Val) && "cast<Ty>() argument of incompatible type!"), function cast, file Casting.h, line 572.
PLEASE submit a bug report to https://github.com/llvm/llvm-project/issues/ and include the crash backtrace.
Stack dump:
0. Program arguments: mlir-opt --lower-affine temp.mlir
#0 0x0000000102a18f18 llvm::sys::PrintStackTrace(llvm::raw_ostream&, int) (/workspacebin/mlir-opt+0x1002f8f18)
#1 0x0000000102a171b4 llvm::sys::RunSignalHandlers() (/workspacebin/mlir-opt+0x1002f71b4)
#2 0x0000000102a195c4 SignalHandler(int) (/workspacebin/mlir-opt+0x1002f95c4)
#3 0x00000001be7894c4 (/usr/lib/system/libsystem_platform.dylib+0x1803414c4)
#4 0x00000001be771ee0 (/usr/lib/system/libsystem_pthread.dylib+0x180329ee0)
#5 0x00000001be6ac340 (/usr/lib/system/libsystem_c.dylib+0x180264340)
#6 0x00000001be6ab754 (/usr/lib/system/libsystem_c.dylib+0x180263754)
#7 0x0000000106864790 mlir::arith::getIdentityValueAttr(mlir::arith::AtomicRMWKind, mlir::Type, mlir::OpBuilder&, mlir::Location) (.cold.4) (/workspacebin/mlir-opt+0x104144790)
#8 0x0000000102ba66ac mlir::arith::getIdentityValueAttr(mlir::arith::AtomicRMWKind, mlir::Type, mlir::OpBuilder&, mlir::Location) (/workspacebin/mlir-opt+0x1004866ac)
#9 0x0000000102ba6910 mlir::arith::getIdentityValue(mlir::arith::AtomicRMWKind, mlir::Type, mlir::OpBuilder&, mlir::Location) (/workspacebin/mlir-opt+0x100486910)
...
```
Fixes #64068
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D157985
Added:
Modified:
mlir/lib/Dialect/Affine/IR/AffineOps.cpp
mlir/test/Dialect/Affine/invalid.mlir
Removed:
################################################################################
diff --git a/mlir/lib/Dialect/Affine/IR/AffineOps.cpp b/mlir/lib/Dialect/Affine/IR/AffineOps.cpp
index c61bd566c7676f1..113f4cfc31c104b 100644
--- a/mlir/lib/Dialect/Affine/IR/AffineOps.cpp
+++ b/mlir/lib/Dialect/Affine/IR/AffineOps.cpp
@@ -3915,6 +3915,49 @@ void AffineParallelOp::setSteps(ArrayRef<int64_t> newSteps) {
setStepsAttr(getBodyBuilder().getI64ArrayAttr(newSteps));
}
+// check whether resultType match op or not in affine.parallel
+static bool isResultTypeMatchAtomicRMWKind(Type resultType,
+ arith::AtomicRMWKind op) {
+ switch (op) {
+ case arith::AtomicRMWKind::addf:
+ return isa<FloatType>(resultType);
+ case arith::AtomicRMWKind::addi:
+ return isa<IntegerType>(resultType);
+ case arith::AtomicRMWKind::assign:
+ return true;
+ case arith::AtomicRMWKind::mulf:
+ return isa<FloatType>(resultType);
+ case arith::AtomicRMWKind::muli:
+ return isa<IntegerType>(resultType);
+ case arith::AtomicRMWKind::maximumf:
+ return isa<FloatType>(resultType);
+ case arith::AtomicRMWKind::minimumf:
+ return isa<FloatType>(resultType);
+ case arith::AtomicRMWKind::maxs: {
+ auto intType = llvm::dyn_cast<IntegerType>(resultType);
+ return intType && intType.isSigned();
+ }
+ case arith::AtomicRMWKind::mins: {
+ auto intType = llvm::dyn_cast<IntegerType>(resultType);
+ return intType && intType.isSigned();
+ }
+ case arith::AtomicRMWKind::maxu: {
+ auto intType = llvm::dyn_cast<IntegerType>(resultType);
+ return intType && intType.isUnsigned();
+ }
+ case arith::AtomicRMWKind::minu: {
+ auto intType = llvm::dyn_cast<IntegerType>(resultType);
+ return intType && intType.isUnsigned();
+ }
+ case arith::AtomicRMWKind::ori:
+ return isa<IntegerType>(resultType);
+ case arith::AtomicRMWKind::andi:
+ return isa<IntegerType>(resultType);
+ default:
+ return false;
+ }
+}
+
LogicalResult AffineParallelOp::verify() {
auto numDims = getNumDims();
if (getLowerBoundsGroups().getNumElements() != numDims ||
@@ -3946,11 +3989,16 @@ LogicalResult AffineParallelOp::verify() {
if (getReductions().size() != getNumResults())
return emitOpError("a reduction must be specified for each output");
- // Verify reduction ops are all valid
- for (Attribute attr : getReductions()) {
+ // Verify reduction ops are all valid and each result type matches reduction
+ // ops
+ for (auto it : llvm::enumerate((getReductions()))) {
+ Attribute attr = it.value();
auto intAttr = llvm::dyn_cast<IntegerAttr>(attr);
if (!intAttr || !arith::symbolizeAtomicRMWKind(intAttr.getInt()))
return emitOpError("invalid reduction attribute");
+ auto kind = arith::symbolizeAtomicRMWKind(intAttr.getInt()).value();
+ if (!isResultTypeMatchAtomicRMWKind(getResult(it.index()).getType(), kind))
+ return emitOpError("result type cannot match reduction attribute");
}
// Verify that the bound operands are valid dimension/symbols.
diff --git a/mlir/test/Dialect/Affine/invalid.mlir b/mlir/test/Dialect/Affine/invalid.mlir
index 1dc3451ed7db87c..1bcb6fc4a365ddf 100644
--- a/mlir/test/Dialect/Affine/invalid.mlir
+++ b/mlir/test/Dialect/Affine/invalid.mlir
@@ -297,6 +297,18 @@ func.func @affine_parallel(%arg0 : index, %arg1 : index, %arg2 : index) {
// -----
+func.func @affine_parallel(%arg0 : index, %arg1 : index, %arg2 : index) {
+ %0 = memref.alloc() : memref<100x100xi32>
+ // expected-error at +1 {{result type cannot match reduction attribute}}
+ %1 = affine.parallel (%i, %j) = (0, 0) to (100, 100) step (10, 10) reduce ("minimumf") -> (i32) {
+ %2 = affine.load %0[%i, %j] : memref<100x100xi32>
+ affine.yield %2 : i32
+ }
+ return
+}
+
+// -----
+
func.func @vector_load_invalid_vector_type() {
%0 = memref.alloc() : memref<100xf32>
affine.for %i0 = 0 to 16 step 8 {
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