mirror of https://github.com/llvm/torch-mlir
55 lines
2.0 KiB
C++
55 lines
2.0 KiB
C++
//===------------------------------------------------------------*- C++ -*-===//
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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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// Also available under a BSD-style license. See LICENSE.
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//
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//===----------------------------------------------------------------------===//
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#include "torch-mlir-dialects/Dialect/TMTensor/IR/TMTensorInterfaces.h"
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using namespace mlir;
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using namespace mlir::torch;
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using namespace mlir::torch::TMTensor;
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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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LogicalResult
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mlir::torch::TMTensor::detail::verifyTMTensorOpInterface(Operation *op) {
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TMTensorOp mtTensorOp = cast<TMTensorOp>(op);
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if (op->getNumResults()) {
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if (!mtTensorOp.hasTensorSemantics()) {
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return mtTensorOp.emitOpError(
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"expected inputs and outputs to be RankedTensorType or scalar");
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}
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if (op->getNumResults() != mtTensorOp.getOutputs().size()) {
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return mtTensorOp.emitOpError(
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"expected number of outputs to be same as the number of results");
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}
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for (auto en : llvm::enumerate(op->getResultTypes())) {
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Type outputType = mtTensorOp.getOutputs()[en.index()].getType();
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if (en.value() != outputType) {
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return mtTensorOp.emitOpError("expected type of `outs` operand #")
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<< en.index() << " " << outputType
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<< " to be same as result type " << en.value();
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}
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}
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} else {
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if (!mtTensorOp.hasBufferSemantics()) {
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return mtTensorOp.emitOpError(
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"expected inputs and outputs to be MemRefType or scalar");
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}
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}
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return success();
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}
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#include "torch-mlir-dialects/Dialect/TMTensor/IR/TMTensorOpInterfaces.cpp.inc" // IWYU pragma: export
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