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2bd6077d7f
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 (?). Differential Revision: https://reviews.llvm.org/D150376
71 lines
2.4 KiB
C++
71 lines
2.4 KiB
C++
//===- DestinationStyleOpInterface.cpp -- Destination style ops -----------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Interfaces/DestinationStyleOpInterface.h"
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using namespace mlir;
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namespace mlir {
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#include "mlir/Interfaces/DestinationStyleOpInterface.cpp.inc"
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} // namespace mlir
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OpOperandVector::operator SmallVector<Value>() {
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SmallVector<Value> result;
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result.reserve(this->size());
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llvm::transform(*this, std::back_inserter(result),
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[](OpOperand *opOperand) { return opOperand->get(); });
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return result;
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}
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namespace {
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size_t getNumTensorResults(Operation *op) {
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size_t numTensorResults = 0;
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for (auto t : op->getResultTypes()) {
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if (isa<TensorType>(t)) {
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++numTensorResults;
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}
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}
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return numTensorResults;
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}
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} // namespace
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LogicalResult detail::verifyDestinationStyleOpInterface(Operation *op) {
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DestinationStyleOpInterface dstStyleOp =
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cast<DestinationStyleOpInterface>(op);
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SmallVector<OpOperand *> outputTensorOperands;
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for (OpOperand *operand : dstStyleOp.getDpsInitOperands()) {
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Type type = operand->get().getType();
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if (isa<RankedTensorType>(type)) {
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outputTensorOperands.push_back(operand);
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} else if (!isa<MemRefType>(type)) {
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return op->emitOpError("expected that operand #")
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<< operand->getOperandNumber()
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<< " is a ranked tensor or a ranked memref";
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}
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}
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// Verify the number of tensor results matches the number of output tensors.
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if (getNumTensorResults(op) != outputTensorOperands.size())
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return op->emitOpError("expected the number of tensor results (")
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<< getNumTensorResults(op)
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<< ") to be equal to the number of output tensors ("
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<< outputTensorOperands.size() << ")";
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for (OpOperand *opOperand : outputTensorOperands) {
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OpResult result = dstStyleOp.getTiedOpResult(opOperand);
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if (result.getType() != opOperand->get().getType())
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return op->emitOpError("expected type of operand #")
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<< opOperand->getOperandNumber() << " ("
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<< opOperand->get().getType() << ")"
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<< " to match type of corresponding result (" << result.getType()
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<< ")";
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}
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return success();
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}
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