[mlir][sparse] Support pretty print to debug sparse iteration.

mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorPasses.cpp

@@ -95,13 +95,15 @@ struct SparsificationPass
   SparsificationPass(const SparsificationPass &pass) = default;
   SparsificationPass(const SparsificationOptions &options) {
     parallelization = options.parallelizationStrategy;
+    sparseEmitStrategy = options.sparseEmitStrategy;
     enableRuntimeLibrary = options.enableRuntimeLibrary;
   }
 
   void runOnOperation() override {
     auto *ctx = &getContext();
     // Translate strategy flags to strategy options.
-    SparsificationOptions options(parallelization, enableRuntimeLibrary);
+    SparsificationOptions options(parallelization, sparseEmitStrategy,
+                                  enableRuntimeLibrary);
     // Apply sparsification and cleanup rewriting.
     RewritePatternSet patterns(ctx);
     populateSparsificationPatterns(patterns, options);

mlir/lib/Dialect/SparseTensor/Transforms/Sparsification.cpp

@@ -1369,7 +1369,7 @@ struct GenericOpSparsifier : public OpRewritePattern<linalg::GenericOp> {
       return failure();
 
     // Recursively generates code if admissible.
-    env.startEmit();
+    env.startEmit(options.sparseEmitStrategy);
     genBuffers(env, rewriter);
     // TODO: Constant affine expression should be handled differently when using
     // slice-based codegen, it does not matter now because we already reject the

mlir/lib/Dialect/SparseTensor/Transforms/Utils/CodegenEnv.cpp

@@ -59,7 +59,7 @@ LogicalResult CodegenEnv::initTensorExp() {
   return success();
 }
 
-void CodegenEnv::startEmit() {
+void CodegenEnv::startEmit(SparseEmitStrategy emitStrategy) {
   assert(insChain == nullptr && "must only start emitting once");
   if (sparseOut) {
     insChain = sparseOut->get();
@@ -96,7 +96,8 @@ void CodegenEnv::startEmit() {
       /*dependentLvlGetter=*/
       [this](TensorId t, Level lvl) -> std::vector<LoopCoeffPair> {
         return merger().getDependentLoops(t, lvl);
-      });
+      },
+      emitStrategy);
 }
 
 std::optional<Operation *> CodegenEnv::genLoopBoundary(

mlir/lib/Dialect/SparseTensor/Transforms/Utils/CodegenEnv.h

@@ -52,7 +52,7 @@ class CodegenEnv {
   Merger &merger() { return latticeMerger; }
   LoopEmitter &emitter() { return loopEmitter; }
 
-  void startEmit();
+  void startEmit(SparseEmitStrategy emitStrategy);
 
   /// Generates loop boundary statements (entering/exiting loops). The function
   /// passes and updates the passed-in parameters.

mlir/lib/Dialect/SparseTensor/Transforms/Utils/LoopEmitter.cpp

@@ -81,17 +81,20 @@ static Value genSliceStride(OpBuilder &builder, Location loc, Value tensor,
 
 LoopEmitter::LoopEmitter(ValueRange tensors, StringAttr loopTag, bool hasOutput,
                          bool isSparseOut, unsigned numLoops,
-                         DependentLvlGetter dimGetter) {
+                         DependentLvlGetter dimGetter,
+                         SparseEmitStrategy emitStrategy) {
   initialize(tensors, loopTag, hasOutput, isSparseOut, numLoops, dimGetter);
 }
 
 void LoopEmitter::initialize(ValueRange ts, StringAttr loopTag, bool hasOutput,
                              bool isSparseOut, unsigned numLoops,
-                             DependentLvlGetter dimGetter) {
+                             DependentLvlGetter dimGetter,
+                             SparseEmitStrategy emitStrategy) {
   // First initialize the top-level type of the fields.
   this->loopTag = loopTag;
   this->hasOutput = hasOutput;
   this->isSparseOut = isSparseOut;
+  SparseIterator::setSparseEmitStrategy(emitStrategy);
 
   const unsigned numManifestTensors = ts.size();
   const unsigned synTensorId = numManifestTensors;
@@ -169,7 +172,7 @@ LoopEmitter::makeLevelIterator(OpBuilder &builder, Location loc, TensorId t,
     Value offset = genSliceOffset(builder, loc, tensors[t], l);
     Value stride = genSliceStride(builder, loc, tensors[t], l);
     auto slicedIt = makeSlicedLevelIterator(std::move(it), offset, stride,
-                                            lvls[t][l]->size());
+                                            lvls[t][l]->getSize());
     return slicedIt;
   }
   return it;
@@ -465,7 +468,7 @@ std::pair<Operation *, Value> LoopEmitter::emitWhileLoopOverTensorsAtLvls(
 
   // Construct the while-loop with a parameter for each coordinate.
   for (SparseIterator *it : spIters) {
-    ValueRange itVals = it->getItVals();
+    ValueRange itVals = it->getCursor();
     ivs.append(itVals.begin(), itVals.end());
   }
 
@@ -724,7 +727,7 @@ void LoopEmitter::exitWhileLoop(OpBuilder &builder, Location loc,
       // Forward the sparse iterator.
       Value cmp = CMPI(eq, it.getCrd(), iv);
       it.forwardIf(builder, loc, cmp);
-      operands.append(it.getItVals().begin(), it.getItVals().end());
+      operands.append(it.getCursor().begin(), it.getCursor().end());
       // const Value newPos = whileOp->getResult(o++);
       // Following loops continue iteration from the break point of the
       // current while loop.

mlir/lib/Dialect/SparseTensor/Transforms/Utils/LoopEmitter.h

@@ -15,6 +15,7 @@
 
 #include "mlir/Dialect/SparseTensor/IR/Enums.h"
 #include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"
+#include "mlir/Dialect/SparseTensor/Transforms/Passes.h"
 #include "mlir/Dialect/SparseTensor/Utils/Merger.h"
 #include "mlir/IR/PatternMatch.h"
 
@@ -84,14 +85,17 @@ class LoopEmitter {
   /// `isSparseOut` indicates that the sparse output tensor is empty,
   /// so the loop emitter will generate loops over it according to the
   /// level-sizes.
-  void initialize(ValueRange tensors, StringAttr loopTag = nullptr,
-                  bool hasOutput = false, bool isSparseOut = false,
-                  unsigned numLoops = 0, DependentLvlGetter getter = nullptr);
-
-  explicit LoopEmitter(ValueRange tensors, StringAttr loopTag = nullptr,
-                       bool hasOutput = false, bool isSparseOut = false,
-                       unsigned numLoops = 0,
-                       DependentLvlGetter getter = nullptr);
+  void
+  initialize(ValueRange tensors, StringAttr loopTag = nullptr,
+             bool hasOutput = false, bool isSparseOut = false,
+             unsigned numLoops = 0, DependentLvlGetter getter = nullptr,
+             SparseEmitStrategy emitStrategy = SparseEmitStrategy::kFunctional);
+
+  explicit LoopEmitter(
+      ValueRange tensors, StringAttr loopTag = nullptr, bool hasOutput = false,
+      bool isSparseOut = false, unsigned numLoops = 0,
+      DependentLvlGetter getter = nullptr,
+      SparseEmitStrategy emitStrategy = SparseEmitStrategy::kFunctional);
 
   /// Starts a loop emitting session by generating all the buffers needed
   /// for iterating over the tensors.