torch-mlir/lib/Conversion/TorchToMhlo/MhloLegalizeUtils.h

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//===------------------------------------------------------------*- C++ -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
// Also available under a BSD-style license. See LICENSE.
//
//===----------------------------------------------------------------------===//
#ifndef TORCHMLIR_CONVERSION_TORCHTOMHLO_MHLOLEGALIZEUTILS_H
#define TORCHMLIR_CONVERSION_TORCHTOMHLO_MHLOLEGALIZEUTILS_H
#include "mlir/IR/BuiltinAttributes.h"
#include "mlir/IR/BuiltinTypes.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/Interfaces/InferTypeOpInterface.h"
#include "mlir/Support/LLVM.h"
#include "mlir/Transforms/DialectConversion.h"
namespace mlir {
namespace mhlo {
using mlir::ConversionPatternRewriter;
// Create a 32-bit float constant operator from a float
Value getMhloConstTensorSingleF32(PatternRewriter &rewriter, Operation *op,
float val);
// Create a 64-bit float constant operator from a double
Value getMhloConstTensorSingleF64(PatternRewriter &rewriter, Operation *op,
double val);
// Templated function to create a constant op for given type and shape.
// T: storage C type.
// Default template creates a constant tensor in T.
// To create INT48 MHLO constant, need to pass in llvm::APInt instead.
template <typename T>
llvm::Optional<Value> getConstTensor(PatternRewriter &rewriter, Operation *op,
ArrayRef<T> vec, ArrayRef<int64_t> shape);
template <typename T>
Value getSplatConstTensor(ConversionPatternRewriter &rewriter, Operation *op,
T val, Type dtype, llvm::ArrayRef<int64_t> dshape);
Value scalarToMhloTensor(ConversionPatternRewriter &rewriter, Operation *op,
Value scalarValue, Type dtype);
Value promoteType(PatternRewriter &rewriter, Value input, TensorType outType);
Value promoteAndBroadcast(ConversionPatternRewriter &rewriter, Value input,
TensorType outType);
SmallVector<size_t> toPositiveDims(ArrayRef<int64_t> dims, int64_t rank);
// Get the dimension sizes of the input tensor, given the dimension axes
FailureOr<SmallVector<Value, 4>> getDimSizesOfTensor(PatternRewriter &rewriter,
Operation *op, Value value,
ArrayRef<int64_t> inpDims,
size_t dimSizeIndexBits);
// Get the dimension sizes of the input tensor
FailureOr<SmallVector<Value, 4>> getDimSizesOfTensor(PatternRewriter &rewriter,
Operation *op, Value value,
size_t dimSizeIndexBits);
// Get a tensor that unsqueezed the specified dimensions of the input tensor
FailureOr<Value> unsqueezeTensor(PatternRewriter &rewriter, Operation *op,
Value tensor, ArrayRef<int64_t> inputUnsqzDims,
size_t dimSizeIndexBits);
Value getConstantOfShape(PatternRewriter &rewriter, Location loc,
const APFloat &constant, Value shape,
TensorType outType);
} // namespace mhlo
} // namespace mlir
#endif // TORCHMLIR_CONVERSION_TORCHTOMHLO_MHLOLEGALIZEUTILS_H