mirror of https://github.com/llvm/torch-mlir
60 lines
1.8 KiB
C++
60 lines
1.8 KiB
C++
//===----------------------------------------------------------------------===//
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//
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// This file is licensed 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/Dialect/Torch/Utils/Utils.h"
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#include "torch-mlir/Dialect/Torch/IR/TorchOps.h"
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using namespace mlir::torch::torch_upstream;
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namespace mlir {
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namespace torch {
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namespace Torch {
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int64_t toPositiveDim(int64_t dim, int64_t inputRank) {
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return dim >= 0 ? dim : dim + inputRank;
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}
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bool isValidDim(int64_t dim, int64_t inputRank) {
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return dim >= 0 && dim < inputRank;
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}
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bool getListConstructElements(Value v, SmallVectorImpl<Value> &elems) {
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auto listConstruct = v.getDefiningOp<PrimListConstructOp>();
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if (!listConstruct)
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return false;
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elems = llvm::to_vector<4>(listConstruct.elements());
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return true;
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}
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ScalarType getScalarTypeForType(Type type) {
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if (type.isa<Float32Type>())
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return ScalarType::Float;
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if (type.isa<Float64Type>())
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return ScalarType::Double;
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if (type.isSignedInteger(64))
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return ScalarType::Long;
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if (type.isSignedInteger(32))
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return ScalarType::Int;
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if (type.isUnsignedInteger(1))
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return ScalarType::Bool;
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llvm::report_fatal_error("unhandled type for getScalarTypeForType");
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}
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LogicalResult checkNotNone(PatternRewriter &rewriter, Operation *op, Value v) {
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Type type = v.getType();
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if (type.isa<OptionalType>() || type.isa<Torch::NoneType>() ||
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type.isa<mlir::NoneType>())
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return rewriter.notifyMatchFailure(op, "unimplemented None type arg");
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return success();
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}
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} // namespace Torch
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} // namespace torch
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} // namespace mlir
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