DestinationPassingStyle: allow additional non-tensor results

[Benoit]

Summary

Also some simplifications:

• outputBufferOperands was unused.
• The condition that the number of operands equals the number of inputs plus the number of inits seemed vacuously true (?).

[Benoit]

update error message string.

[nicolasvasilache]

positive and negative test updates please

[Benoit]

@nicolasvasilache please point to the tests that should be updated? I couldn't find them under test/Interfaces ?

[Benoit]

Actually I can see that CI reports failures in test/Dialect/Linalg/invalid.mlir . I dont know why this didn't happen when I ran check-mlir locally.

[Benoit]

Add a new DPS op test. Update Linalg invalid.mlir. Fix error message.

[Benoit]

@mravishankar @nicolasvasilache CI's green, PTAL.

[mravishankar]

Looks good to me. Thanks!

mlir/lib/Interfaces/DestinationStyleOpInterface.cpp

 OpOperandVector::operator SmallVector<Value>() {
   SmallVector<Value> result;
   result.reserve(this->size());
   llvm::transform(*this, std::back_inserter(result),
                   [](OpOperand *opOperand) { return opOperand->get(); });
   return result;
 }
 
+namespace {
+size_t getNumTensorResults(Operation *op) {
+  size_t numTensorResults = 0;
+  for (auto t : op->getResultTypes()) {
+    if (t.isa<TensorType>()) {
+      ++numTensorResults;
+    }
+  }
+  return numTensorResults;
+}
+} // namespace
+
 LogicalResult detail::verifyDestinationStyleOpInterface(Operation *op) {
   DestinationStyleOpInterface dstStyleOp =
       cast<DestinationStyleOpInterface>(op);
 
-  SmallVector<OpOperand *> outputBufferOperands, outputTensorOperands;
+  SmallVector<OpOperand *> outputTensorOperands;
   for (OpOperand *operand : dstStyleOp.getDpsInitOperands()) {
     Type type = operand->get().getType();
-    if (type.isa<MemRefType>()) {
-      outputBufferOperands.push_back(operand);
-    } else if (type.isa<RankedTensorType>()) {
+    if (type.isa<RankedTensorType>()) {
       outputTensorOperands.push_back(operand);
-    } else {
+    } else if (!type.isa<MemRefType>()) {
       return op->emitOpError("expected that operand #")
              << operand->getOperandNumber()
              << " is a ranked tensor or a ranked memref";
     }
   }
 
-  // Expect at least one output operand.
-  int64_t numInputs = dstStyleOp.getNumDpsInputs();
-  int64_t numInits = dstStyleOp.getNumDpsInits();
-  if (numInits == 0)
-    return op->emitOpError("expected at least one output operand");
-  if (failed(OpTrait::impl::verifyNOperands(op, numInputs + numInits)))
-    return failure();
-  // Verify the number of results matches the number of output tensors.
-  if (op->getNumResults() != outputTensorOperands.size())
+  // Verify the number of tensor results matches the number of output tensors.
+  if (getNumTensorResults(op) != outputTensorOperands.size())
     return op->emitOpError("expected the number of results (")
            << op->getNumResults()
            << ") to be equal to the number of output tensors ("
            << outputTensorOperands.size() << ")";
 
   for (OpOperand *opOperand : outputTensorOperands) {
     OpResult result = dstStyleOp.getTiedOpResult(opOperand);
     if (result.getType() != opOperand->get().getType())
       return op->emitOpError("expected type of operand #")
              << opOperand->getOperandNumber() << " ("
              << opOperand->get().getType() << ")"
              << " to match type of corresponding result (" << result.getType()
              << ")";
   }
   return success();
 }