mirror of https://github.com/llvm/torch-mlir
78 lines
3.4 KiB
C++
78 lines
3.4 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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#ifndef TORCHMLIR_CONVERSION_TORCHTOSTABLEHLO_STABLEHLOLEGALIZEUTILS_H
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#define TORCHMLIR_CONVERSION_TORCHTOSTABLEHLO_STABLEHLOLEGALIZEUTILS_H
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#include "mlir/IR/BuiltinAttributes.h"
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#include "mlir/IR/BuiltinTypes.h"
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#include "mlir/IR/PatternMatch.h"
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#include "mlir/Interfaces/InferTypeOpInterface.h"
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#include "mlir/Support/LLVM.h"
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#include "mlir/Transforms/DialectConversion.h"
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namespace mlir {
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namespace hlo {
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using mlir::ConversionPatternRewriter;
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// Create a 32-bit float constant operator from a float
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Value getStablehloConstTensorSingleF32(PatternRewriter &rewriter, Operation *op,
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float val);
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// Create a 64-bit float constant operator from a double
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Value getStablehloConstTensorSingleF64(PatternRewriter &rewriter, Operation *op,
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double val);
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// Templated function to create a constant op for given type and shape.
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// T: storage C type.
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// Default template creates a constant tensor in T.
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// To create INT48 StableHLO constant, need to pass in llvm::APInt instead.
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template <typename T>
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std::optional<Value> getConstTensor(PatternRewriter &rewriter, Operation *op,
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ArrayRef<T> vec, ArrayRef<int64_t> shape);
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template <typename T>
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Value getSplatConstTensor(ConversionPatternRewriter &rewriter, Operation *op,
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T val, Type dtype, llvm::ArrayRef<int64_t> dshape);
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Value scalarToStablehloTensor(ConversionPatternRewriter &rewriter,
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Operation *op, Value scalarValue, Type dtype);
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Value promoteType(PatternRewriter &rewriter, Value input, TensorType outType);
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Value promoteAndBroadcast(ConversionPatternRewriter &rewriter, Value input,
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TensorType outType);
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SmallVector<size_t> toPositiveDims(ArrayRef<int64_t> dims, int64_t rank);
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// Get the dimension sizes of the input tensor, given the dimension axes
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FailureOr<SmallVector<Value, 4>> getDimSizesOfTensor(PatternRewriter &rewriter,
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Operation *op, Value value,
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ArrayRef<int64_t> inpDims,
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size_t dimSizeIndexBits);
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// Get the dimension sizes of the input tensor
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FailureOr<SmallVector<Value, 4>> getDimSizesOfTensor(PatternRewriter &rewriter,
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Operation *op, Value value,
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size_t dimSizeIndexBits);
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// Get a tensor that unsqueezed the specified dimensions of the input tensor
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FailureOr<Value> unsqueezeTensor(PatternRewriter &rewriter, Operation *op,
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Value tensor, ArrayRef<int64_t> inputUnsqzDims,
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size_t dimSizeIndexBits);
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Value getConstantOfShape(PatternRewriter &rewriter, Location loc,
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const APFloat &constant, Value shape,
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TensorType outType);
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} // namespace hlo
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} // namespace mlir
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#endif // TORCHMLIR_CONVERSION_TORCHTOSTABLEHLO_STABLEHLOLEGALIZEUTILS_H
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