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path: root/mlir/lib/ExecutionEngine/SparseTensor/Storage.cpp
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//===- StorageBase.cpp - TACO-flavored sparse tensor representation -------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// This file contains method definitions for `SparseTensorStorageBase`.
// In particular we want to ensure that the default implementations of
// the "partial method specialization" trick aren't inline (since there's
// no benefit).  Though this also helps ensure that we avoid weak-vtables:
// <https://llvm.org/docs/CodingStandards.html#provide-a-virtual-method-anchor-for-classes-in-headers>
//
// This file is part of the lightweight runtime support library for sparse
// tensor manipulations.  The functionality of the support library is meant
// to simplify benchmarking, testing, and debugging MLIR code operating on
// sparse tensors.  However, the provided functionality is **not** part of
// core MLIR itself.
//
//===----------------------------------------------------------------------===//

#include "mlir/ExecutionEngine/SparseTensor/Storage.h"

using namespace mlir::sparse_tensor;

SparseTensorStorageBase::SparseTensorStorageBase( // NOLINT
    uint64_t dimRank, const uint64_t *dimSizes, uint64_t lvlRank,
    const uint64_t *lvlSizes, const DimLevelType *lvlTypes,
    const uint64_t *lvl2dim)
    : dimSizes(dimSizes, dimSizes + dimRank),
      lvlSizes(lvlSizes, lvlSizes + lvlRank),
      lvlTypes(lvlTypes, lvlTypes + lvlRank),
      lvl2dim(lvl2dim, lvl2dim + lvlRank) {
  // TODO: If we do get any nullptrs, I'm pretty sure these assertions
  // will run too late (i.e., after copying things into vectors above).
  // But since those fields are const I'm not sure there's any clean way
  // to assert things before copying...
  assert(dimSizes && "Got nullptr for dimension sizes");
  assert(lvlSizes && "Got nullptr for level sizes");
  assert(lvlTypes && "Got nullptr for level types");
  assert(lvl2dim && "Got nullptr for level-to-dimension mapping");
  // Validate dim-indexed parameters.
  assert(dimRank > 0 && "Trivial shape is unsupported");
  for (uint64_t d = 0; d < dimRank; ++d)
    assert(dimSizes[d] > 0 && "Dimension size zero has trivial storage");
  // Validate level-indexed parameters.
  assert(lvlRank > 0 && "Trivial shape is unsupported");
  for (uint64_t l = 0; l < lvlRank; ++l) {
    assert(lvlSizes[l] > 0 && "Level size zero has trivial storage");
    const auto dlt = lvlTypes[l]; // Avoid redundant bounds checking.
    // We use `MLIR_SPARSETENSOR_FATAL` here instead of `assert` so that
    // when this ctor is successful then all the methods can rely on the
    // fact that each level-type satisfies one of these options (even
    // when `NDEBUG` is true), thereby reducing the need to re-assert things.
    if (!(isDenseDLT(dlt) || isCompressedDLT(dlt) || isSingletonDLT(dlt)))
      MLIR_SPARSETENSOR_FATAL("unsupported level type: %d\n",
                              static_cast<uint8_t>(dlt));
  }
}

// Helper macro for generating error messages when some
// `SparseTensorStorage<P,I,V>` is cast to `SparseTensorStorageBase`
// and then the wrong "partial method specialization" is called.
#define FATAL_PIV(NAME)                                                        \
  MLIR_SPARSETENSOR_FATAL("<P,I,V> type mismatch for: " #NAME);

#define IMPL_NEWENUMERATOR(VNAME, V)                                           \
  void SparseTensorStorageBase::newEnumerator(                                 \
      SparseTensorEnumeratorBase<V> **, uint64_t, const uint64_t *, uint64_t,  \
      const uint64_t *) const {                                                \
    FATAL_PIV("newEnumerator" #VNAME);                                         \
  }
MLIR_SPARSETENSOR_FOREVERY_V(IMPL_NEWENUMERATOR)
#undef IMPL_NEWENUMERATOR

#define IMPL_GETPOSITIONS(PNAME, P)                                            \
  void SparseTensorStorageBase::getPositions(std::vector<P> **, uint64_t) {    \
    FATAL_PIV("getPositions" #PNAME);                                          \
  }
MLIR_SPARSETENSOR_FOREVERY_FIXED_O(IMPL_GETPOSITIONS)
#undef IMPL_GETPOSITIONS

#define IMPL_GETCOORDINATES(CNAME, C)                                          \
  void SparseTensorStorageBase::getCoordinates(std::vector<C> **, uint64_t) {  \
    FATAL_PIV("getCoordinates" #CNAME);                                        \
  }
MLIR_SPARSETENSOR_FOREVERY_FIXED_O(IMPL_GETCOORDINATES)
#undef IMPL_GETCOORDINATES

#define IMPL_GETVALUES(VNAME, V)                                               \
  void SparseTensorStorageBase::getValues(std::vector<V> **) {                 \
    FATAL_PIV("getValues" #VNAME);                                             \
  }
MLIR_SPARSETENSOR_FOREVERY_V(IMPL_GETVALUES)
#undef IMPL_GETVALUES

#define IMPL_LEXINSERT(VNAME, V)                                               \
  void SparseTensorStorageBase::lexInsert(const uint64_t *, V) {               \
    FATAL_PIV("lexInsert" #VNAME);                                             \
  }
MLIR_SPARSETENSOR_FOREVERY_V(IMPL_LEXINSERT)
#undef IMPL_LEXINSERT

#define IMPL_EXPINSERT(VNAME, V)                                               \
  void SparseTensorStorageBase::expInsert(uint64_t *, V *, bool *, uint64_t *, \
                                          uint64_t) {                          \
    FATAL_PIV("expInsert" #VNAME);                                             \
  }
MLIR_SPARSETENSOR_FOREVERY_V(IMPL_EXPINSERT)
#undef IMPL_EXPINSERT

#undef FATAL_PIV