Revert "[mlir][sparse] implement lowering rules for IterateOp." (#95826)

Reverts llvm/llvm-project#95286

4 files changed, 17 insertions, 224 deletions

diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseIterationToScf.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseIterationToScf.cpp
index f57be49..62887c7 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseIterationToScf.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseIterationToScf.cpp
@@ -34,20 +34,6 @@ convertIterSpaceType(IterSpaceType itSp, SmallVectorImpl<Type> &fields) {
   return success();
 }
 
-static std::optional<LogicalResult>
-convertIteratorType(IteratorType itTp, SmallVectorImpl<Type> &fields) {
-  // The actually Iterator Values (that are updated every iteration).
-  auto idxTp = IndexType::get(itTp.getContext());
-  // TODO: handle batch dimension.
-  assert(itTp.getEncoding().getBatchLvlRank() == 0);
-  if (!itTp.isUnique()) {
-    // Segment high for non-unique iterator.
-    fields.push_back(idxTp);
-  }
-  fields.push_back(idxTp);
-  return success();
-}
-
 namespace {
 
 /// Sparse codegen rule for number of entries operator.
@@ -71,114 +57,10 @@ public:
   }
 };
 
-class SparseIterateOpConverter : public OneToNOpConversionPattern<IterateOp> {
-public:
-  using OneToNOpConversionPattern::OneToNOpConversionPattern;
-  LogicalResult
-  matchAndRewrite(IterateOp op, OpAdaptor adaptor,
-                  OneToNPatternRewriter &rewriter) const override {
-    if (!op.getCrdUsedLvls().empty())
-      return rewriter.notifyMatchFailure(
-          op, "non-empty coordinates list not implemented.");
-
-    Location loc = op.getLoc();
-
-    auto iterSpace = SparseIterationSpace::fromValues(
-        op.getIterSpace().getType(), adaptor.getIterSpace(), 0);
-
-    std::unique_ptr<SparseIterator> it =
-        iterSpace.extractIterator(rewriter, loc);
-
-    if (it->iteratableByFor()) {
-      auto [lo, hi] = it->genForCond(rewriter, loc);
-      Value step = constantIndex(rewriter, loc, 1);
-      SmallVector<Value> ivs;
-      for (ValueRange inits : adaptor.getInitArgs())
-        llvm::append_range(ivs, inits);
-      scf::ForOp forOp = rewriter.create<scf::ForOp>(loc, lo, hi, step, ivs);
-
-      Block *loopBody = op.getBody();
-      OneToNTypeMapping bodyTypeMapping(loopBody->getArgumentTypes());
-      if (failed(typeConverter->convertSignatureArgs(
-              loopBody->getArgumentTypes(), bodyTypeMapping)))
-        return failure();
-      rewriter.applySignatureConversion(loopBody, bodyTypeMapping);
-
-      forOp.getBody()->erase();
-      Region &dstRegion = forOp.getRegion();
-      rewriter.inlineRegionBefore(op.getRegion(), dstRegion, dstRegion.end());
-
-      auto yieldOp =
-          llvm::cast<sparse_tensor::YieldOp>(forOp.getBody()->getTerminator());
-
-      rewriter.setInsertionPointToEnd(forOp.getBody());
-      // replace sparse_tensor.yield with scf.yield.
-      rewriter.create<scf::YieldOp>(loc, yieldOp.getResults());
-      yieldOp.erase();
-
-      const OneToNTypeMapping &resultMapping = adaptor.getResultMapping();
-      rewriter.replaceOp(op, forOp.getResults(), resultMapping);
-    } else {
-      SmallVector<Value> ivs;
-      llvm::append_range(ivs, it->getCursor());
-      for (ValueRange inits : adaptor.getInitArgs())
-        llvm::append_range(ivs, inits);
-
-      assert(llvm::all_of(ivs, [](Value v) { return v != nullptr; }));
-
-      TypeRange types = ValueRange(ivs).getTypes();
-      auto whileOp = rewriter.create<scf::WhileOp>(loc, types, ivs);
-      SmallVector<Location> l(types.size(), op.getIterator().getLoc());
-
-      // Generates loop conditions.
-      Block *before = rewriter.createBlock(&whileOp.getBefore(), {}, types, l);
-      rewriter.setInsertionPointToStart(before);
-      ValueRange bArgs = before->getArguments();
-      auto [whileCond, remArgs] = it->genWhileCond(rewriter, loc, bArgs);
-      assert(remArgs.size() == adaptor.getInitArgs().size());
-      rewriter.create<scf::ConditionOp>(loc, whileCond, before->getArguments());
-
-      // Generates loop body.
-      Block *loopBody = op.getBody();
-      OneToNTypeMapping bodyTypeMapping(loopBody->getArgumentTypes());
-      if (failed(typeConverter->convertSignatureArgs(
-              loopBody->getArgumentTypes(), bodyTypeMapping)))
-        return failure();
-      rewriter.applySignatureConversion(loopBody, bodyTypeMapping);
-
-      Region &dstRegion = whileOp.getAfter();
-      // TODO: handle uses of coordinate!
-      rewriter.inlineRegionBefore(op.getRegion(), dstRegion, dstRegion.end());
-      ValueRange aArgs = whileOp.getAfterArguments();
-      auto yieldOp = llvm::cast<sparse_tensor::YieldOp>(
-          whileOp.getAfterBody()->getTerminator());
-
-      rewriter.setInsertionPointToEnd(whileOp.getAfterBody());
-
-      aArgs = it->linkNewScope(aArgs);
-      ValueRange nx = it->forward(rewriter, loc);
-      SmallVector<Value> yields;
-      llvm::append_range(yields, nx);
-      llvm::append_range(yields, yieldOp.getResults());
-
-      // replace sparse_tensor.yield with scf.yield.
-      yieldOp->erase();
-      rewriter.create<scf::YieldOp>(loc, yields);
-
-      const OneToNTypeMapping &resultMapping = adaptor.getResultMapping();
-      rewriter.replaceOp(
-          op, whileOp.getResults().drop_front(it->getCursor().size()),
-          resultMapping);
-    }
-    return success();
-  }
-};
-
 } // namespace
 
 mlir::SparseIterationTypeConverter::SparseIterationTypeConverter() {
   addConversion([](Type type) { return type; });
-  addConversion(convertIteratorType);
   addConversion(convertIterSpaceType);
 
   addSourceMaterialization([](OpBuilder &builder, IterSpaceType spTp,
@@ -192,6 +74,5 @@ mlir::SparseIterationTypeConverter::SparseIterationTypeConverter() {
 
 void mlir::populateLowerSparseIterationToSCFPatterns(
     TypeConverter &converter, RewritePatternSet &patterns) {
-  patterns.add<ExtractIterSpaceConverter, SparseIterateOpConverter>(
-      converter, patterns.getContext());
+  patterns.add<ExtractIterSpaceConverter>(converter, patterns.getContext());
 }
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorIterator.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorIterator.cpp
index ef95fcc..be8e15d 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorIterator.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorIterator.cpp
@@ -331,13 +331,6 @@ public:
   TrivialIterator(const SparseTensorLevel &stl)
       : ConcreteIterator(stl, IterKind::kTrivial, /*itValCnt=*/1) {}
 
-  TrivialIterator(OpBuilder &b, Location l, const SparseTensorLevel &stl,
-                  Value posLo, Value posHi)
-      : ConcreteIterator(stl, IterKind::kTrivial, /*itValCnt=*/1), posLo(posLo),
-        posHi(posHi) {
-    seek(posLo);
-  }
-
   std::string getDebugInterfacePrefix() const override {
     return std::string("trivial<") + stl.toString() + ">";
   }
@@ -427,14 +420,6 @@ public:
       : ConcreteIterator(stl, IterKind::kDedup, /*itValCnt=*/2) {
     assert(!stl.isUnique());
   }
-
-  DedupIterator(OpBuilder &b, Location l, const SparseTensorLevel &stl,
-                Value posLo, Value posHi)
-      : ConcreteIterator(stl, IterKind::kDedup, /*itValCnt=*/2), posHi(posHi) {
-    assert(!stl.isUnique());
-    seek({posLo, genSegmentHigh(b, l, posLo)});
-  }
-
   // For LLVM-style RTTI.
   static bool classof(const SparseIterator *from) {
     return from->kind == IterKind::kDedup;
@@ -1547,11 +1532,6 @@ SparseIterationSpace mlir::sparse_tensor::SparseIterationSpace::fromValues(
   return space;
 }
 
-std::unique_ptr<SparseIterator>
-SparseIterationSpace::extractIterator(OpBuilder &b, Location l) const {
-  return makeSimpleIterator(b, l, *this);
-}
-
 //===----------------------------------------------------------------------===//
 // SparseIterator factory functions.
 //===----------------------------------------------------------------------===//
@@ -1611,26 +1591,6 @@ sparse_tensor::makeSynLevelAndIterator(Value sz, unsigned tid, unsigned lvl,
 }
 
 std::unique_ptr<SparseIterator>
-sparse_tensor::makeSimpleIterator(OpBuilder &b, Location l,
-                                  const SparseIterationSpace &iterSpace) {
-  // assert(iterSpace.getSpaceDim() == 1);
-  std::unique_ptr<SparseIterator> ret;
-  if (!iterSpace.isUnique()) {
-    // We always dedupliate the non-unique level, but we should optimize it away
-    // if possible.
-    ret = std::make_unique<DedupIterator>(b, l, iterSpace.getLastLvl(),
-                                          iterSpace.getBoundLo(),
-                                          iterSpace.getBoundHi());
-  } else {
-    ret = std::make_unique<TrivialIterator>(b, l, iterSpace.getLastLvl(),
-                                            iterSpace.getBoundLo(),
-                                            iterSpace.getBoundHi());
-  }
-  ret->setSparseEmitStrategy(SparseEmitStrategy::kFunctional);
-  return ret;
-}
-
-std::unique_ptr<SparseIterator>
 sparse_tensor::makeSimpleIterator(const SparseTensorLevel &stl,
                                   SparseEmitStrategy strategy) {
   std::unique_ptr<SparseIterator> ret;
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorIterator.h b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorIterator.h
index 91f363d..17636af 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorIterator.h
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorIterator.h
@@ -132,10 +132,6 @@ public:
   Value getBoundLo() const { return bound.first; }
   Value getBoundHi() const { return bound.second; }
 
-  // Extract an iterator to iterate over the sparse iteration space.
-  std::unique_ptr<SparseIterator> extractIterator(OpBuilder &b,
-                                                  Location l) const;
-
 private:
   SmallVector<std::unique_ptr<SparseTensorLevel>> lvls;
   std::pair<Value, Value> bound;
@@ -196,13 +192,6 @@ public:
     crd = nullptr;
   }
 
-  // Reconstructs a iteration space directly from the provided ValueRange.
-  static std::unique_ptr<SparseIterator>
-  fromValues(IteratorType dstTp, ValueRange values, unsigned tid);
-
-  // The inverse operation of `fromValues`.
-  SmallVector<Value> toValues() const { llvm_unreachable("Not implemented"); }
-
   //
   // Iterator properties.
   //
@@ -356,21 +345,12 @@ std::unique_ptr<SparseTensorLevel> makeSparseTensorLevel(OpBuilder &b,
                                                          unsigned tid,
                                                          Level lvl);
 
-/// Helper function to create a TensorLevel object from given ValueRange.
+/// Helper function to create a TensorLevel object from given `tensor`.
 std::unique_ptr<SparseTensorLevel> makeSparseTensorLevel(LevelType lt, Value sz,
                                                          ValueRange buffers,
                                                          unsigned tid, Level l);
-
-/// Helper function to create a simple SparseIterator object that iterate
-/// over the entire iteration space.
-std::unique_ptr<SparseIterator>
-makeSimpleIterator(OpBuilder &b, Location l,
-                   const SparseIterationSpace &iterSpace);
-
-/// Helper function to create a simple SparseIterator object that iterate
-/// over the sparse tensor level.
-/// TODO: switch to `SparseIterationSpace` (which support N-D iterator) when
-/// feature complete.
+/// Helper function to create a simple SparseIterator object that iterates
+/// over the SparseTensorLevel.
 std::unique_ptr<SparseIterator> makeSimpleIterator(
     const SparseTensorLevel &stl,
     SparseEmitStrategy strategy = SparseEmitStrategy::kFunctional);
diff --git a/mlir/test/Dialect/SparseTensor/sparse_iteration_to_scf.mlir b/mlir/test/Dialect/SparseTensor/sparse_iteration_to_scf.mlir
index 77a0e89..5fcd661 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_iteration_to_scf.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_iteration_to_scf.mlir
@@ -1,5 +1,4 @@
 // RUN: mlir-opt %s --lower-sparse-iteration-to-scf | FileCheck %s
-// RUN: mlir-opt %s --sparse-space-collapse --lower-sparse-iteration-to-scf | FileCheck %s --check-prefix COLLAPSED
 
 #COO = #sparse_tensor.encoding<{
   map = (i, j) -> (
@@ -8,44 +7,17 @@
   )
 }>
 
-// CHECK-LABEL:   @sparse_iteration_to_scf
-//                  // deduplication
-// CHECK:           scf.while {{.*}} {
-// CHECK:           } do {
-// CHECK:           }
-// CHECK:           scf.while {{.*}} {
-// CHECK:           } do {
-//                    // actual computation
-// CHECK:             scf.for {{.*}} {
-// CHECK:               arith.addi
-// CHECK:             }
-//                    // deduplication
-// CHECK:             scf.while {{.*}} {
-// CHECK:             } do {
-// CHECK:             }
-// CHECK:             scf.yield
-// CHECK:           }
-// CHECK:           return
-
-// COLLAPSED-LABEL:   @sparse_iteration_to_scf
-// COLLAPSED:           %[[RET:.*]] = scf.for {{.*}} {
-// COLLAPSED:             %[[VAL:.*]] = arith.addi
-// COLLAPSED:             scf.yield %[[VAL]] : index
-// COLLAPSED:           }
-// COLLAPSED:           return %[[RET]] : index
-func.func @sparse_iteration_to_scf(%sp : tensor<4x8xf32, #COO>) -> index {
-  %i = arith.constant 0 : index
-  %c1 = arith.constant 1 : index
-  %l1 = sparse_tensor.extract_iteration_space %sp lvls = 0
-      : tensor<4x8xf32, #COO> -> !sparse_tensor.iter_space<#COO, lvls = 0>
-  %r1 = sparse_tensor.iterate %it1 in %l1 iter_args(%outer = %i): !sparse_tensor.iter_space<#COO, lvls = 0 to 1> -> index {
-    %l2 = sparse_tensor.extract_iteration_space %sp at %it1 lvls = 1
-        : tensor<4x8xf32, #COO>, !sparse_tensor.iterator<#COO, lvls = 0 to 1> -> !sparse_tensor.iter_space<#COO, lvls = 1>
-    %r2 = sparse_tensor.iterate %it2 in %l2 iter_args(%inner = %outer): !sparse_tensor.iter_space<#COO, lvls = 1 to 2> -> index {
-      %k = arith.addi %inner, %c1 : index
-      sparse_tensor.yield %k : index
-    }
-    sparse_tensor.yield %r2 : index
-  }
-  return %r1 : index
+// CHECK-LABEL:   func.func @sparse_1D_space(
+// CHECK-SAME:      %[[VAL_0:.*]]: tensor<?x?xf32, #sparse{{[0-9]*}}>) -> !sparse_tensor.iter_space<#sparse{{[0-9]*}}, lvls = 0> {
+// CHECK-DAG:       %[[C0:.*]] = arith.constant 0 : index
+// CHECK-DAG:       %[[C1:.*]] = arith.constant 1 : index
+// CHECK-DAG:       %[[LVL_SIZE:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[C0]] : tensor<?x?xf32, #sparse{{[0-9]*}}>
+// CHECK:           %[[POS_MEM:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK:           %[[CRD_MEM:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK:           %[[POS_LO:.*]] = memref.load %[[POS_MEM]]{{\[}}%[[C0]]] : memref<?xindex>
+// CHECK:           %[[POS_HI:.*]] = memref.load %[[POS_MEM]]{{\[}}%[[C1]]] : memref<?xindex>
+// CHECK:           %[[ITER_SPACE:.*]] = builtin.unrealized_conversion_cast %[[POS_MEM]], %[[CRD_MEM]], %[[LVL_SIZE]], %[[POS_LO]], %[[POS_HI]]
+func.func @sparse_1D_space(%sp : tensor<?x?xf32, #COO>) -> !sparse_tensor.iter_space<#COO, lvls = 0> {
+  %l1 = sparse_tensor.extract_iteration_space %sp lvls = 0 : tensor<?x?xf32, #COO> -> !sparse_tensor.iter_space<#COO, lvls = 0>
+  return %l1 : !sparse_tensor.iter_space<#COO, lvls = 0>
 }