mirror of https://github.com/llvm/torch-mlir
48 lines
2.1 KiB
C
48 lines
2.1 KiB
C
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//===------------------------------------------------------------*- 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 "mlir/Transforms/DialectConversion.h"
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namespace mlir {
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namespace torch {
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namespace torch_to_linalg {
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// Helper function to get the padding tensor given the padding int values.
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Value getPaddedTensor(Operation *op, OpBuilder &b, Value &input,
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SmallVectorImpl<int64_t> &lowPaddingInts,
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SmallVectorImpl<int64_t> &highPaddingInts, Value pad);
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// Helper function to get the padding tensor given the padding int values.
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// It's assumed that the padding on the low end and high end are the same,
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// and that zero padding is required.
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Value getPaddedTensor(Operation *op, OpBuilder &b, Value &input,
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SmallVectorImpl<int64_t> &paddingInts);
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// Helper function to caculate the output tensor dims for convolution-like ops.
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// Along each dim:
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// dim_out =
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// floor((dim_in + 2 * padding - dilation * (kernelSize - 1) - 1) / stride) + 1
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Value getOutputDimForConvOps(OpBuilder &b, Location loc, Value in,
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Value paddingInt, Value dilationInt,
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Value kernelSizeInt, Value strideInt);
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// Create a reduction of `tensorOperand`, reducing along the dimensions
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// in `dimSet`. If `keepDim` is true, the output tensor is the same
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// rank as the `tensorOperand` and reduced dimensions are set to size 1.
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// `initElem` is the element used to initialize the output tensor
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// where the reduction will be stored.
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Value createReductionLinalgGeneric(
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OpBuilder &b, Location loc, Value tensorOperand,
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const DenseSet<int64_t> &dimSet, bool keepDim, Value initElem,
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function_ref<void(OpBuilder &, Location, ValueRange)> bodyBuild);
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} // namespace torch_to_linalg
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} // namespace torch
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} // namespace mlir
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