329f2f103a
Previously, the SparseTensorUtils.cpp library contained a C++ core implementation, but hid it in an anonymous namespace and only exposed a C-API for accessing it. Now we are factoring out that C++ core into a standalone C++ library so that it can be used directly by downstream clients (per request of one such client). This refactoring has been decomposed into a stack of differentials in order to simplify the code review process, however the full stack of changes should be considered together. * D133462: Part 1: split one file into several * D133830: Part 2: Reorder chunks within files * (this): Part 3: General code cleanup * D133833: Part 4: Update documentation This part performs some general code cleanup including: * making more things `const`, especially for the targets of pointers * using preincrement wherever possible ([[ https://llvm.org/docs/CodingStandards.html#prefer-preincrement | per LLVM style guide ]]) * adding messages to most `assert` statments. * moving argument casting from the core function/method definitions to the CPP wrappers Depends On D133830 Reviewed By: aartbik Differential Revision: https://reviews.llvm.org/D133831
118 lines
5.3 KiB
C++
118 lines
5.3 KiB
C++
//===- StorageBase.cpp - TACO-flavored sparse tensor representation -------===//
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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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//
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//===----------------------------------------------------------------------===//
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//
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// This file contains method definitions for `SparseTensorStorageBase`.
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// In particular we want to ensure that the default implementations of
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// the "partial method specialization" trick aren't inline (since there's
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// no benefit). Though this also helps ensure that we avoid weak-vtables:
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// <https://llvm.org/docs/CodingStandards.html#provide-a-virtual-method-anchor-for-classes-in-headers>
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//
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// (This file also contains the definition of `assertPermutedSizesMatchShape`
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// which is used by `SparseTensorStorage` factories.)
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//
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// This file is part of the lightweight runtime support library for sparse
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// tensor manipulations. The functionality of the support library is meant
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// to simplify benchmarking, testing, and debugging MLIR code operating on
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// sparse tensors. However, the provided functionality is **not** part of
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// core MLIR itself.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/ExecutionEngine/SparseTensor/Storage.h"
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using namespace mlir::sparse_tensor;
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SparseTensorStorageBase::SparseTensorStorageBase(
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const std::vector<uint64_t> &dimSizes, const uint64_t *perm,
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const DimLevelType *sparsity)
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: dimSizes(dimSizes), rev(getRank()),
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dimTypes(sparsity, sparsity + getRank()) {
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assert(perm && "Got nullptr for permutation");
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assert(sparsity && "Got nullptr for sparsity");
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const uint64_t rank = getRank();
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// Validate parameters.
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assert(rank > 0 && "Trivial shape is unsupported");
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for (uint64_t r = 0; r < rank; ++r) {
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assert(dimSizes[r] > 0 && "Dimension size zero has trivial storage");
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assert((isDenseDim(r) || isCompressedDim(r) || isSingletonDim(r)) &&
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"Unsupported DimLevelType");
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}
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// Construct the "reverse" (i.e., inverse) permutation.
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// TODO: should move this computation off to the codegen
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for (uint64_t r = 0; r < rank; ++r)
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rev[perm[r]] = r;
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}
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// Helper macro for generating error messages when some
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// `SparseTensorStorage<P,I,V>` is cast to `SparseTensorStorageBase`
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// and then the wrong "partial method specialization" is called.
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#define FATAL_PIV(NAME) \
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MLIR_SPARSETENSOR_FATAL("<P,I,V> type mismatch for: " #NAME);
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#define IMPL_NEWENUMERATOR(VNAME, V) \
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void SparseTensorStorageBase::newEnumerator( \
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SparseTensorEnumeratorBase<V> **, uint64_t, const uint64_t *) const { \
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FATAL_PIV("newEnumerator" #VNAME); \
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}
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FOREVERY_V(IMPL_NEWENUMERATOR)
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#undef IMPL_NEWENUMERATOR
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#define IMPL_GETPOINTERS(PNAME, P) \
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void SparseTensorStorageBase::getPointers(std::vector<P> **, uint64_t) { \
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FATAL_PIV("getPointers" #PNAME); \
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}
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FOREVERY_FIXED_O(IMPL_GETPOINTERS)
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#undef IMPL_GETPOINTERS
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#define IMPL_GETINDICES(INAME, I) \
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void SparseTensorStorageBase::getIndices(std::vector<I> **, uint64_t) { \
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FATAL_PIV("getIndices" #INAME); \
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}
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FOREVERY_FIXED_O(IMPL_GETINDICES)
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#undef IMPL_GETINDICES
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#define IMPL_GETVALUES(VNAME, V) \
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void SparseTensorStorageBase::getValues(std::vector<V> **) { \
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FATAL_PIV("getValues" #VNAME); \
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}
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FOREVERY_V(IMPL_GETVALUES)
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#undef IMPL_GETVALUES
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#define IMPL_LEXINSERT(VNAME, V) \
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void SparseTensorStorageBase::lexInsert(const uint64_t *, V) { \
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FATAL_PIV("lexInsert" #VNAME); \
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}
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FOREVERY_V(IMPL_LEXINSERT)
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#undef IMPL_LEXINSERT
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#define IMPL_EXPINSERT(VNAME, V) \
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void SparseTensorStorageBase::expInsert(uint64_t *, V *, bool *, uint64_t *, \
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uint64_t) { \
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FATAL_PIV("expInsert" #VNAME); \
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}
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FOREVERY_V(IMPL_EXPINSERT)
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#undef IMPL_EXPINSERT
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#undef FATAL_PIV
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// TODO: try to unify this with `SparseTensorFile::assertMatchesShape`
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// (which is used by `openSparseTensorCOO`). It's easy enough to resolve
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// the `std::vector` vs pointer mismatch for `dimSizes`; but it's trickier
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// to resolve the presence/absence of `perm` (without introducing extra
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// overhead), so perhaps the code duplication is unavoidable?
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void mlir::sparse_tensor::detail::assertPermutedSizesMatchShape(
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const std::vector<uint64_t> &dimSizes, uint64_t rank, const uint64_t *perm,
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const uint64_t *shape) {
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assert(perm && "Got nullptr for permutation");
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assert(shape && "Got nullptr for shape");
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assert(rank == dimSizes.size() && "Rank mismatch");
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for (uint64_t d = 0; d < rank; ++d)
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assert((shape[d] == 0 || shape[d] == dimSizes[perm[d]]) &&
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"Dimension size mismatch");
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}
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