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|
//===- SparseTensorRuntime.cpp - SparseTensor runtime support lib ---------===//
//
// 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 implements a light-weight runtime support library for
// manipulating sparse tensors from MLIR. More specifically, it provides
// C-API wrappers so that MLIR-generated code can call into the C++ runtime
// support library. The functionality provided in this library is meant
// to simplify benchmarking, testing, and debugging of MLIR code operating
// on sparse tensors. However, the provided functionality is **not**
// part of core MLIR itself.
//
// The following memory-resident sparse storage schemes are supported:
//
// (a) A coordinate scheme for temporarily storing and lexicographically
// sorting a sparse tensor by coordinate (SparseTensorCOO).
//
// (b) A "one-size-fits-all" sparse tensor storage scheme defined by
// per-dimension sparse/dense annnotations together with a dimension
// ordering used by MLIR compiler-generated code (SparseTensorStorage).
//
// The following external formats are supported:
//
// (1) Matrix Market Exchange (MME): *.mtx
// https://math.nist.gov/MatrixMarket/formats.html
//
// (2) Formidable Repository of Open Sparse Tensors and Tools (FROSTT): *.tns
// http://frostt.io/tensors/file-formats.html
//
// Two public APIs are supported:
//
// (I) Methods operating on MLIR buffers (memrefs) to interact with sparse
// tensors. These methods should be used exclusively by MLIR
// compiler-generated code.
//
// (II) Methods that accept C-style data structures to interact with sparse
// tensors. These methods can be used by any external runtime that wants
// to interact with MLIR compiler-generated code.
//
// In both cases (I) and (II), the SparseTensorStorage format is externally
// only visible as an opaque pointer.
//
//===----------------------------------------------------------------------===//
#include "mlir/ExecutionEngine/SparseTensorRuntime.h"
#ifdef MLIR_CRUNNERUTILS_DEFINE_FUNCTIONS
#include "mlir/ExecutionEngine/SparseTensor/ArithmeticUtils.h"
#include "mlir/ExecutionEngine/SparseTensor/COO.h"
#include "mlir/ExecutionEngine/SparseTensor/ErrorHandling.h"
#include "mlir/ExecutionEngine/SparseTensor/File.h"
#include "mlir/ExecutionEngine/SparseTensor/Storage.h"
#include <cstring>
#include <numeric>
using namespace mlir::sparse_tensor;
//===----------------------------------------------------------------------===//
//
// Utilities for manipulating `StridedMemRefType`.
//
//===----------------------------------------------------------------------===//
namespace {
#define ASSERT_NO_STRIDE(MEMREF) \
do { \
assert((MEMREF) && "Memref is nullptr"); \
assert(((MEMREF)->strides[0] == 1) && "Memref has non-trivial stride"); \
} while (false)
#define MEMREF_GET_USIZE(MEMREF) \
detail::checkOverflowCast<uint64_t>((MEMREF)->sizes[0])
#define ASSERT_USIZE_EQ(MEMREF, SZ) \
assert(detail::safelyEQ(MEMREF_GET_USIZE(MEMREF), (SZ)) && \
"Memref size mismatch")
#define MEMREF_GET_PAYLOAD(MEMREF) ((MEMREF)->data + (MEMREF)->offset)
/// Initializes the memref with the provided size and data pointer. This
/// is designed for functions which want to "return" a memref that aliases
/// into memory owned by some other object (e.g., `SparseTensorStorage`),
/// without doing any actual copying. (The "return" is in scarequotes
/// because the `_mlir_ciface_` calling convention migrates any returned
/// memrefs into an out-parameter passed before all the other function
/// parameters.)
template <typename DataSizeT, typename T>
static inline void aliasIntoMemref(DataSizeT size, T *data,
StridedMemRefType<T, 1> &ref) {
ref.basePtr = ref.data = data;
ref.offset = 0;
using MemrefSizeT = std::remove_reference_t<decltype(ref.sizes[0])>;
ref.sizes[0] = detail::checkOverflowCast<MemrefSizeT>(size);
ref.strides[0] = 1;
}
} // anonymous namespace
extern "C" {
//===----------------------------------------------------------------------===//
//
// Public functions which operate on MLIR buffers (memrefs) to interact
// with sparse tensors (which are only visible as opaque pointers externally).
//
//===----------------------------------------------------------------------===//
#define CASE(p, c, v, P, C, V) \
if (posTp == (p) && crdTp == (c) && valTp == (v)) { \
switch (action) { \
case Action::kEmpty: { \
return SparseTensorStorage<P, C, V>::newEmpty( \
dimRank, dimSizes, lvlRank, lvlSizes, lvlTypes, dim2lvl, lvl2dim); \
} \
case Action::kFromReader: { \
assert(ptr && "Received nullptr for SparseTensorReader object"); \
SparseTensorReader &reader = *static_cast<SparseTensorReader *>(ptr); \
return static_cast<void *>(reader.readSparseTensor<P, C, V>( \
lvlRank, lvlSizes, lvlTypes, dim2lvl, lvl2dim)); \
} \
case Action::kPack: { \
assert(ptr && "Received nullptr for SparseTensorStorage object"); \
intptr_t *buffers = static_cast<intptr_t *>(ptr); \
return SparseTensorStorage<P, C, V>::packFromLvlBuffers( \
dimRank, dimSizes, lvlRank, lvlSizes, lvlTypes, dim2lvl, lvl2dim, \
dimRank, buffers); \
} \
case Action::kSortCOOInPlace: { \
assert(ptr && "Received nullptr for SparseTensorStorage object"); \
auto &tensor = *static_cast<SparseTensorStorage<P, C, V> *>(ptr); \
tensor.sortInPlace(); \
return ptr; \
} \
} \
MLIR_SPARSETENSOR_FATAL("unknown action: %d\n", \
static_cast<uint32_t>(action)); \
}
#define CASE_SECSAME(p, v, P, V) CASE(p, p, v, P, P, V)
// Assume index_type is in fact uint64_t, so that _mlir_ciface_newSparseTensor
// can safely rewrite kIndex to kU64. We make this assertion to guarantee
// that this file cannot get out of sync with its header.
static_assert(std::is_same<index_type, uint64_t>::value,
"Expected index_type == uint64_t");
// The Swiss-army-knife for sparse tensor creation.
void *_mlir_ciface_newSparseTensor( // NOLINT
StridedMemRefType<index_type, 1> *dimSizesRef,
StridedMemRefType<index_type, 1> *lvlSizesRef,
StridedMemRefType<LevelType, 1> *lvlTypesRef,
StridedMemRefType<index_type, 1> *dim2lvlRef,
StridedMemRefType<index_type, 1> *lvl2dimRef, OverheadType posTp,
OverheadType crdTp, PrimaryType valTp, Action action, void *ptr) {
ASSERT_NO_STRIDE(dimSizesRef);
ASSERT_NO_STRIDE(lvlSizesRef);
ASSERT_NO_STRIDE(lvlTypesRef);
ASSERT_NO_STRIDE(dim2lvlRef);
ASSERT_NO_STRIDE(lvl2dimRef);
const uint64_t dimRank = MEMREF_GET_USIZE(dimSizesRef);
const uint64_t lvlRank = MEMREF_GET_USIZE(lvlSizesRef);
ASSERT_USIZE_EQ(lvlTypesRef, lvlRank);
ASSERT_USIZE_EQ(dim2lvlRef, lvlRank);
ASSERT_USIZE_EQ(lvl2dimRef, dimRank);
const index_type *dimSizes = MEMREF_GET_PAYLOAD(dimSizesRef);
const index_type *lvlSizes = MEMREF_GET_PAYLOAD(lvlSizesRef);
const LevelType *lvlTypes = MEMREF_GET_PAYLOAD(lvlTypesRef);
const index_type *dim2lvl = MEMREF_GET_PAYLOAD(dim2lvlRef);
const index_type *lvl2dim = MEMREF_GET_PAYLOAD(lvl2dimRef);
// Rewrite kIndex to kU64, to avoid introducing a bunch of new cases.
// This is safe because of the static_assert above.
if (posTp == OverheadType::kIndex)
posTp = OverheadType::kU64;
if (crdTp == OverheadType::kIndex)
crdTp = OverheadType::kU64;
// Double matrices with all combinations of overhead storage.
CASE(OverheadType::kU64, OverheadType::kU64, PrimaryType::kF64, uint64_t,
uint64_t, double);
CASE(OverheadType::kU64, OverheadType::kU32, PrimaryType::kF64, uint64_t,
uint32_t, double);
CASE(OverheadType::kU64, OverheadType::kU16, PrimaryType::kF64, uint64_t,
uint16_t, double);
CASE(OverheadType::kU64, OverheadType::kU8, PrimaryType::kF64, uint64_t,
uint8_t, double);
CASE(OverheadType::kU32, OverheadType::kU64, PrimaryType::kF64, uint32_t,
uint64_t, double);
CASE(OverheadType::kU32, OverheadType::kU32, PrimaryType::kF64, uint32_t,
uint32_t, double);
CASE(OverheadType::kU32, OverheadType::kU16, PrimaryType::kF64, uint32_t,
uint16_t, double);
CASE(OverheadType::kU32, OverheadType::kU8, PrimaryType::kF64, uint32_t,
uint8_t, double);
CASE(OverheadType::kU16, OverheadType::kU64, PrimaryType::kF64, uint16_t,
uint64_t, double);
CASE(OverheadType::kU16, OverheadType::kU32, PrimaryType::kF64, uint16_t,
uint32_t, double);
CASE(OverheadType::kU16, OverheadType::kU16, PrimaryType::kF64, uint16_t,
uint16_t, double);
CASE(OverheadType::kU16, OverheadType::kU8, PrimaryType::kF64, uint16_t,
uint8_t, double);
CASE(OverheadType::kU8, OverheadType::kU64, PrimaryType::kF64, uint8_t,
uint64_t, double);
CASE(OverheadType::kU8, OverheadType::kU32, PrimaryType::kF64, uint8_t,
uint32_t, double);
CASE(OverheadType::kU8, OverheadType::kU16, PrimaryType::kF64, uint8_t,
uint16_t, double);
CASE(OverheadType::kU8, OverheadType::kU8, PrimaryType::kF64, uint8_t,
uint8_t, double);
// Float matrices with all combinations of overhead storage.
CASE(OverheadType::kU64, OverheadType::kU64, PrimaryType::kF32, uint64_t,
uint64_t, float);
CASE(OverheadType::kU64, OverheadType::kU32, PrimaryType::kF32, uint64_t,
uint32_t, float);
CASE(OverheadType::kU64, OverheadType::kU16, PrimaryType::kF32, uint64_t,
uint16_t, float);
CASE(OverheadType::kU64, OverheadType::kU8, PrimaryType::kF32, uint64_t,
uint8_t, float);
CASE(OverheadType::kU32, OverheadType::kU64, PrimaryType::kF32, uint32_t,
uint64_t, float);
CASE(OverheadType::kU32, OverheadType::kU32, PrimaryType::kF32, uint32_t,
uint32_t, float);
CASE(OverheadType::kU32, OverheadType::kU16, PrimaryType::kF32, uint32_t,
uint16_t, float);
CASE(OverheadType::kU32, OverheadType::kU8, PrimaryType::kF32, uint32_t,
uint8_t, float);
CASE(OverheadType::kU16, OverheadType::kU64, PrimaryType::kF32, uint16_t,
uint64_t, float);
CASE(OverheadType::kU16, OverheadType::kU32, PrimaryType::kF32, uint16_t,
uint32_t, float);
CASE(OverheadType::kU16, OverheadType::kU16, PrimaryType::kF32, uint16_t,
uint16_t, float);
CASE(OverheadType::kU16, OverheadType::kU8, PrimaryType::kF32, uint16_t,
uint8_t, float);
CASE(OverheadType::kU8, OverheadType::kU64, PrimaryType::kF32, uint8_t,
uint64_t, float);
CASE(OverheadType::kU8, OverheadType::kU32, PrimaryType::kF32, uint8_t,
uint32_t, float);
CASE(OverheadType::kU8, OverheadType::kU16, PrimaryType::kF32, uint8_t,
uint16_t, float);
CASE(OverheadType::kU8, OverheadType::kU8, PrimaryType::kF32, uint8_t,
uint8_t, float);
// Two-byte floats with both overheads of the same type.
CASE_SECSAME(OverheadType::kU64, PrimaryType::kF16, uint64_t, f16);
CASE_SECSAME(OverheadType::kU64, PrimaryType::kBF16, uint64_t, bf16);
CASE_SECSAME(OverheadType::kU32, PrimaryType::kF16, uint32_t, f16);
CASE_SECSAME(OverheadType::kU32, PrimaryType::kBF16, uint32_t, bf16);
CASE_SECSAME(OverheadType::kU16, PrimaryType::kF16, uint16_t, f16);
CASE_SECSAME(OverheadType::kU16, PrimaryType::kBF16, uint16_t, bf16);
CASE_SECSAME(OverheadType::kU8, PrimaryType::kF16, uint8_t, f16);
CASE_SECSAME(OverheadType::kU8, PrimaryType::kBF16, uint8_t, bf16);
// Integral matrices with both overheads of the same type.
CASE_SECSAME(OverheadType::kU64, PrimaryType::kI64, uint64_t, int64_t);
CASE_SECSAME(OverheadType::kU64, PrimaryType::kI32, uint64_t, int32_t);
CASE_SECSAME(OverheadType::kU64, PrimaryType::kI16, uint64_t, int16_t);
CASE_SECSAME(OverheadType::kU64, PrimaryType::kI8, uint64_t, int8_t);
CASE_SECSAME(OverheadType::kU32, PrimaryType::kI64, uint32_t, int64_t);
CASE_SECSAME(OverheadType::kU32, PrimaryType::kI32, uint32_t, int32_t);
CASE_SECSAME(OverheadType::kU32, PrimaryType::kI16, uint32_t, int16_t);
CASE_SECSAME(OverheadType::kU32, PrimaryType::kI8, uint32_t, int8_t);
CASE_SECSAME(OverheadType::kU16, PrimaryType::kI64, uint16_t, int64_t);
CASE_SECSAME(OverheadType::kU16, PrimaryType::kI32, uint16_t, int32_t);
CASE_SECSAME(OverheadType::kU16, PrimaryType::kI16, uint16_t, int16_t);
CASE_SECSAME(OverheadType::kU16, PrimaryType::kI8, uint16_t, int8_t);
CASE_SECSAME(OverheadType::kU8, PrimaryType::kI64, uint8_t, int64_t);
CASE_SECSAME(OverheadType::kU8, PrimaryType::kI32, uint8_t, int32_t);
CASE_SECSAME(OverheadType::kU8, PrimaryType::kI16, uint8_t, int16_t);
CASE_SECSAME(OverheadType::kU8, PrimaryType::kI8, uint8_t, int8_t);
// Complex matrices with wide overhead.
CASE_SECSAME(OverheadType::kU64, PrimaryType::kC64, uint64_t, complex64);
CASE_SECSAME(OverheadType::kU64, PrimaryType::kC32, uint64_t, complex32);
// Unsupported case (add above if needed).
MLIR_SPARSETENSOR_FATAL(
"unsupported combination of types: <P=%d, C=%d, V=%d>\n",
static_cast<int>(posTp), static_cast<int>(crdTp),
static_cast<int>(valTp));
}
#undef CASE
#undef CASE_SECSAME
#define IMPL_SPARSEVALUES(VNAME, V) \
void _mlir_ciface_sparseValues##VNAME(StridedMemRefType<V, 1> *ref, \
void *tensor) { \
assert(ref &&tensor); \
std::vector<V> *v; \
static_cast<SparseTensorStorageBase *>(tensor)->getValues(&v); \
assert(v); \
aliasIntoMemref(v->size(), v->data(), *ref); \
}
MLIR_SPARSETENSOR_FOREVERY_V(IMPL_SPARSEVALUES)
#undef IMPL_SPARSEVALUES
#define IMPL_GETOVERHEAD(NAME, TYPE, LIB) \
void _mlir_ciface_##NAME(StridedMemRefType<TYPE, 1> *ref, void *tensor, \
index_type lvl) { \
assert(ref &&tensor); \
std::vector<TYPE> *v; \
static_cast<SparseTensorStorageBase *>(tensor)->LIB(&v, lvl); \
assert(v); \
aliasIntoMemref(v->size(), v->data(), *ref); \
}
#define IMPL_SPARSEPOSITIONS(PNAME, P) \
IMPL_GETOVERHEAD(sparsePositions##PNAME, P, getPositions)
MLIR_SPARSETENSOR_FOREVERY_O(IMPL_SPARSEPOSITIONS)
#undef IMPL_SPARSEPOSITIONS
#define IMPL_SPARSECOORDINATES(CNAME, C) \
IMPL_GETOVERHEAD(sparseCoordinates##CNAME, C, getCoordinates)
MLIR_SPARSETENSOR_FOREVERY_O(IMPL_SPARSECOORDINATES)
#undef IMPL_SPARSECOORDINATES
#undef IMPL_GETOVERHEAD
#define IMPL_LEXINSERT(VNAME, V) \
void _mlir_ciface_lexInsert##VNAME( \
void *t, StridedMemRefType<index_type, 1> *lvlCoordsRef, \
StridedMemRefType<V, 0> *vref) { \
assert(t &&vref); \
auto &tensor = *static_cast<SparseTensorStorageBase *>(t); \
ASSERT_NO_STRIDE(lvlCoordsRef); \
index_type *lvlCoords = MEMREF_GET_PAYLOAD(lvlCoordsRef); \
assert(lvlCoords); \
V *value = MEMREF_GET_PAYLOAD(vref); \
tensor.lexInsert(lvlCoords, *value); \
}
MLIR_SPARSETENSOR_FOREVERY_V(IMPL_LEXINSERT)
#undef IMPL_LEXINSERT
#define IMPL_EXPINSERT(VNAME, V) \
void _mlir_ciface_expInsert##VNAME( \
void *t, StridedMemRefType<index_type, 1> *lvlCoordsRef, \
StridedMemRefType<V, 1> *vref, StridedMemRefType<bool, 1> *fref, \
StridedMemRefType<index_type, 1> *aref, index_type count) { \
assert(t); \
auto &tensor = *static_cast<SparseTensorStorageBase *>(t); \
ASSERT_NO_STRIDE(lvlCoordsRef); \
ASSERT_NO_STRIDE(vref); \
ASSERT_NO_STRIDE(fref); \
ASSERT_NO_STRIDE(aref); \
ASSERT_USIZE_EQ(vref, MEMREF_GET_USIZE(fref)); \
index_type *lvlCoords = MEMREF_GET_PAYLOAD(lvlCoordsRef); \
V *values = MEMREF_GET_PAYLOAD(vref); \
bool *filled = MEMREF_GET_PAYLOAD(fref); \
index_type *added = MEMREF_GET_PAYLOAD(aref); \
uint64_t expsz = vref->sizes[0]; \
tensor.expInsert(lvlCoords, values, filled, added, count, expsz); \
}
MLIR_SPARSETENSOR_FOREVERY_V(IMPL_EXPINSERT)
#undef IMPL_EXPINSERT
void *_mlir_ciface_createCheckedSparseTensorReader(
char *filename, StridedMemRefType<index_type, 1> *dimShapeRef,
PrimaryType valTp) {
ASSERT_NO_STRIDE(dimShapeRef);
const uint64_t dimRank = MEMREF_GET_USIZE(dimShapeRef);
const index_type *dimShape = MEMREF_GET_PAYLOAD(dimShapeRef);
auto *reader = SparseTensorReader::create(filename, dimRank, dimShape, valTp);
return static_cast<void *>(reader);
}
void _mlir_ciface_getSparseTensorReaderDimSizes(
StridedMemRefType<index_type, 1> *out, void *p) {
assert(out && p);
SparseTensorReader &reader = *static_cast<SparseTensorReader *>(p);
auto *dimSizes = const_cast<uint64_t *>(reader.getDimSizes());
aliasIntoMemref(reader.getRank(), dimSizes, *out);
}
#define IMPL_GETNEXT(VNAME, V, CNAME, C) \
bool _mlir_ciface_getSparseTensorReaderReadToBuffers##CNAME##VNAME( \
void *p, StridedMemRefType<index_type, 1> *dim2lvlRef, \
StridedMemRefType<index_type, 1> *lvl2dimRef, \
StridedMemRefType<C, 1> *cref, StridedMemRefType<V, 1> *vref) { \
assert(p); \
auto &reader = *static_cast<SparseTensorReader *>(p); \
ASSERT_NO_STRIDE(dim2lvlRef); \
ASSERT_NO_STRIDE(lvl2dimRef); \
ASSERT_NO_STRIDE(cref); \
ASSERT_NO_STRIDE(vref); \
const uint64_t dimRank = reader.getRank(); \
const uint64_t lvlRank = MEMREF_GET_USIZE(dim2lvlRef); \
const uint64_t cSize = MEMREF_GET_USIZE(cref); \
const uint64_t vSize = MEMREF_GET_USIZE(vref); \
ASSERT_USIZE_EQ(lvl2dimRef, dimRank); \
assert(cSize >= lvlRank * reader.getNSE()); \
assert(vSize >= reader.getNSE()); \
(void)dimRank; \
(void)cSize; \
(void)vSize; \
index_type *dim2lvl = MEMREF_GET_PAYLOAD(dim2lvlRef); \
index_type *lvl2dim = MEMREF_GET_PAYLOAD(lvl2dimRef); \
C *lvlCoordinates = MEMREF_GET_PAYLOAD(cref); \
V *values = MEMREF_GET_PAYLOAD(vref); \
return reader.readToBuffers<C, V>(lvlRank, dim2lvl, lvl2dim, \
lvlCoordinates, values); \
}
MLIR_SPARSETENSOR_FOREVERY_V_O(IMPL_GETNEXT)
#undef IMPL_GETNEXT
void _mlir_ciface_outSparseTensorWriterMetaData(
void *p, index_type dimRank, index_type nse,
StridedMemRefType<index_type, 1> *dimSizesRef) {
assert(p);
ASSERT_NO_STRIDE(dimSizesRef);
assert(dimRank != 0);
index_type *dimSizes = MEMREF_GET_PAYLOAD(dimSizesRef);
std::ostream &file = *static_cast<std::ostream *>(p);
file << dimRank << " " << nse << '\n';
for (index_type d = 0; d < dimRank - 1; d++)
file << dimSizes[d] << " ";
file << dimSizes[dimRank - 1] << '\n';
}
#define IMPL_OUTNEXT(VNAME, V) \
void _mlir_ciface_outSparseTensorWriterNext##VNAME( \
void *p, index_type dimRank, \
StridedMemRefType<index_type, 1> *dimCoordsRef, \
StridedMemRefType<V, 0> *vref) { \
assert(p &&vref); \
ASSERT_NO_STRIDE(dimCoordsRef); \
const index_type *dimCoords = MEMREF_GET_PAYLOAD(dimCoordsRef); \
std::ostream &file = *static_cast<std::ostream *>(p); \
for (index_type d = 0; d < dimRank; d++) \
file << (dimCoords[d] + 1) << " "; \
V *value = MEMREF_GET_PAYLOAD(vref); \
file << *value << '\n'; \
}
MLIR_SPARSETENSOR_FOREVERY_V(IMPL_OUTNEXT)
#undef IMPL_OUTNEXT
//===----------------------------------------------------------------------===//
//
// Public functions which accept only C-style data structures to interact
// with sparse tensors (which are only visible as opaque pointers externally).
//
//===----------------------------------------------------------------------===//
index_type sparseLvlSize(void *tensor, index_type l) {
return static_cast<SparseTensorStorageBase *>(tensor)->getLvlSize(l);
}
index_type sparseDimSize(void *tensor, index_type d) {
return static_cast<SparseTensorStorageBase *>(tensor)->getDimSize(d);
}
void endLexInsert(void *tensor) {
return static_cast<SparseTensorStorageBase *>(tensor)->endLexInsert();
}
void delSparseTensor(void *tensor) {
delete static_cast<SparseTensorStorageBase *>(tensor);
}
char *getTensorFilename(index_type id) {
constexpr size_t bufSize = 80;
char var[bufSize];
snprintf(var, bufSize, "TENSOR%" PRIu64, id);
char *env = getenv(var);
if (!env)
MLIR_SPARSETENSOR_FATAL("Environment variable %s is not set\n", var);
return env;
}
index_type getSparseTensorReaderNSE(void *p) {
return static_cast<SparseTensorReader *>(p)->getNSE();
}
void delSparseTensorReader(void *p) {
delete static_cast<SparseTensorReader *>(p);
}
void *createSparseTensorWriter(char *filename) {
std::ostream *file =
(filename[0] == 0) ? &std::cout : new std::ofstream(filename);
*file << "# extended FROSTT format\n";
return static_cast<void *>(file);
}
void delSparseTensorWriter(void *p) {
std::ostream *file = static_cast<std::ostream *>(p);
file->flush();
assert(file->good());
if (file != &std::cout)
delete file;
}
} // extern "C"
#undef MEMREF_GET_PAYLOAD
#undef ASSERT_USIZE_EQ
#undef MEMREF_GET_USIZE
#undef ASSERT_NO_STRIDE
#endif // MLIR_CRUNNERUTILS_DEFINE_FUNCTIONS
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