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[mlir][sparse] update doc of sparse tensor storage-layout/descriptor #71249

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Nov 3, 2023
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[mlir][sparse] update doc of sparse tensor storage-layout/descriptor #71249

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[mlir][sparse] update doc of sparse tensor storage-layout/descriptor
aartbik Nov 3, 2023
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aartbik Nov 3, 2023
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54 changes: 26 additions & 28 deletions mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorStorageLayout.h
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Original file line number Diff line number Diff line change
Expand Up @@ -21,19 +21,22 @@ namespace sparse_tensor {

///===----------------------------------------------------------------------===//
/// The sparse tensor storage scheme for a tensor is organized as a single
/// compound type with the following fields. Note that every memref with ? size
/// actually behaves as a "vector", i.e. the stored size is the capacity and the
/// used size resides in the storage_specifier struct.
/// compound type with the following fields. Note that every memref with `?`
/// size actually behaves as a "vector", i.e. the stored size is the capacity
/// and the used size resides in the storage_specifier struct.
///
/// struct {
/// ; per-level l:
/// ; if dense:
/// <nothing>
/// ; if compresed:
/// memref<? x pos> positions-l ; positions for sparse level l
/// memref<? x crd> coordinates-l ; coordinates for sparse level l
/// ; if singleton:
/// memref<? x crd> coordinates-l ; coordinates for singleton level l
/// ; if compressed:
/// memref<? x pos> positions ; positions for level l
/// memref<? x crd> coordinates ; coordinates for level l
/// ; if loose-compressed:
/// memref<? x pos> positions ; lo/hi position pairs for level l
/// memref<? x crd> coordinates ; coordinates for level l
/// ; if singleton/2-out-of-4:
/// memref<? x crd> coordinates ; coordinates for level l
///
/// memref<? x eltType> values ; values
///
Expand All @@ -59,25 +62,25 @@ namespace sparse_tensor {
/// Examples.
///
/// #CSR storage of 2-dim matrix yields
/// memref<?xindex> ; positions-1
/// memref<?xindex> ; coordinates-1
/// memref<?xf64> ; values
/// struct<(array<2 x i64>, array<3 x i64>)>) ; lvl0, lvl1, 3xsizes
/// memref<?xindex> ; positions-1
/// memref<?xindex> ; coordinates-1
/// memref<?xf64> ; values
/// struct<(array<2 x i64>, array<3 x i64>)>) ; lvl0, lvl1, 3xsizes
///
/// #COO storage of 2-dim matrix yields
/// memref<?xindex>, ; positions-0, essentially
/// [0,sz] memref<?xindex> ; AOS coordinates storage
/// memref<?xf64> ; values
/// struct<(array<2 x i64>, array<3 x i64>)>) ; lvl0, lvl1, 3xsizes
/// memref<?xindex>, ; positions-0, essentially [0,sz]
/// memref<?xindex> ; AOS coordinates storage
/// memref<?xf64> ; values
/// struct<(array<2 x i64>, array<3 x i64>)>) ; lvl0, lvl1, 3xsizes
///
/// Slice on #COO storage of 2-dim matrix yields
/// ;; Inherited from the original sparse tensors
/// memref<?xindex>, ; positions-0, essentially
/// [0,sz] memref<?xindex> ; AOS coordinates storage
/// memref<?xf64> ; values
/// struct<(array<2 x i64>, array<3 x i64>, ; lvl0, lvl1, 3xsizes
/// ;; Extra slicing-metadata
/// array<2 x i64>, array<2 x i64>)>) ; dim offset, dim stride.
/// ;; Inherited from the original sparse tensors
/// memref<?xindex>, ; positions-0, essentially [0,sz]
/// memref<?xindex> ; AOS coordinates storage
/// memref<?xf64> ; values
/// struct<(array<2 x i64>, array<3 x i64>, ; lvl0, lvl1, 3xsizes
/// ;; Extra slicing-metadata
/// array<2 x i64>, array<2 x i64>)>) ; dim offset, dim stride.
///
///===----------------------------------------------------------------------===//

Expand Down Expand Up @@ -107,9 +110,6 @@ using FieldIndex = unsigned;
/// encoding.
class StorageLayout {
public:
// TODO: Functions/methods marked with [NUMFIELDS] should use
// `FieldIndex` for their return type, via the same reasoning for why
// `Dimension`/`Level` are used both for identifiers and ranks.
explicit StorageLayout(const SparseTensorType &stt)
: StorageLayout(stt.getEncoding()) {}
explicit StorageLayout(SparseTensorEncodingAttr enc) : enc(enc) {
Expand Down Expand Up @@ -154,12 +154,10 @@ class StorageLayout {
// Wrapper functions to invoke StorageLayout-related method.
//

// See note [NUMFIELDS].
inline unsigned getNumFieldsFromEncoding(SparseTensorEncodingAttr enc) {
return StorageLayout(enc).getNumFields();
}

// See note [NUMFIELDS].
inline unsigned getNumDataFieldsFromEncoding(SparseTensorEncodingAttr enc) {
return StorageLayout(enc).getNumDataFields();
}
Expand Down
2 changes: 1 addition & 1 deletion mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorDescriptor.cpp
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@@ -1,4 +1,4 @@
//===- SparseTensorStorageLayout.cpp --------------------------------------===//
//===- SparseTensorDescriptor.cpp -----------------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
Expand Down
17 changes: 2 additions & 15 deletions mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorDescriptor.h
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@@ -1,4 +1,4 @@
//===- SparseTensorDescriptor.h ------------------------------*- C++ -*-===//
//===- SparseTensorDescriptor.h ---------------------------------*- C++ -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
Expand All @@ -21,13 +21,6 @@
namespace mlir {
namespace sparse_tensor {

//===----------------------------------------------------------------------===//
// SparseTensorDescriptor and helpers that manage the sparse tensor memory
// layout scheme during "direct code generation" (i.e. when sparsification
// generates the buffers as part of actual IR, in constrast with the library
// approach where data structures are hidden behind opaque pointers).
//===----------------------------------------------------------------------===//

class SparseTensorSpecifier {
public:
explicit SparseTensorSpecifier(Value specifier)
Expand Down Expand Up @@ -57,9 +50,6 @@ class SparseTensorSpecifier {
template <typename ValueArrayRef>
class SparseTensorDescriptorImpl {
protected:
// TODO: Functions/methods marked with [NUMFIELDS] might should use
// `FieldIndex` for their return type, via the same reasoning for why
// `Dimension`/`Level` are used both for identifiers and ranks.
SparseTensorDescriptorImpl(SparseTensorType stt, ValueArrayRef fields)
: rType(stt), fields(fields), layout(stt) {
assert(layout.getNumFields() == getNumFields());
Expand All @@ -76,7 +66,6 @@ class SparseTensorDescriptorImpl {
return layout.getMemRefFieldIndex(kind, lvl);
}

// TODO: See note [NUMFIELDS].
unsigned getNumFields() const { return fields.size(); }

///
Expand Down Expand Up @@ -140,8 +129,7 @@ class SparseTensorDescriptorImpl {
}

ValueRange getMemRefFields() const {
// Drop the last metadata fields.
return fields.drop_back();
return fields.drop_back(); // drop the last metadata fields
}

std::pair<FieldIndex, unsigned> getCrdMemRefIndexAndStride(Level lvl) const {
Expand Down Expand Up @@ -173,7 +161,6 @@ class SparseTensorDescriptor : public SparseTensorDescriptorImpl<ValueRange> {
Value getCrdMemRefOrView(OpBuilder &builder, Location loc, Level lvl) const;
};

/// Uses SmallVectorImpl<Value> & for mutable descriptors.
/// Using SmallVector for mutable descriptor allows users to reuse it as a
/// tmp buffers to append value for some special cases, though users should
/// be responsible to restore the buffer to legal states after their use. It
Expand Down