[Mlir-commits] [mlir] [mlir][sparse] support sparse dilated convolution. (PR #80470)

Peiming Liu llvmlistbot at llvm.org
Fri Feb 2 11:46:25 PST 2024


https://github.com/PeimingLiu updated https://github.com/llvm/llvm-project/pull/80470

>From ddc0130a31316851f8e7fac342953555241763f5 Mon Sep 17 00:00:00 2001
From: Peiming Liu <peiming at google.com>
Date: Fri, 2 Feb 2024 17:51:57 +0000
Subject: [PATCH 1/3] [mlir][sparse] support sparse dilated convolution.

---
 .../Transforms/Utils/LoopEmitter.cpp          |   4 +-
 .../Transforms/Utils/SparseTensorLevel.cpp    |  41 +++--
 .../Transforms/Utils/SparseTensorLevel.h      |   5 +-
 .../CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir | 148 ++++++++++++++++++
 4 files changed, 171 insertions(+), 27 deletions(-)
 create mode 100644 mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir

diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/LoopEmitter.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/LoopEmitter.cpp
index 70488c34e440c..a8aa8d8f01797 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/LoopEmitter.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/LoopEmitter.cpp
@@ -321,8 +321,8 @@ void LoopEmitter::initSubSectIterator(OpBuilder &builder, Location loc) {
       } else {
         Value size = loopHighs[loop];
         const SparseIterator &subSectIter = *iters[t][lvl].back();
-        it = makeTraverseSubSectIterator(subSectIter, *parent, std::move(lvlIt),
-                                         size, curDep.second);
+        it = makeTraverseSubSectIterator(builder, loc, subSectIter, *parent,
+                                         std::move(lvlIt), size, curDep.second);
       }
       lastIter[t] = it.get();
       iters[t][lvl].emplace_back(std::move(it));
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.cpp
index c1fc2a062fa10..47aa2fcaa6ae5 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.cpp
@@ -665,13 +665,11 @@ class SubSectIterator : public SparseIterator {
 public:
   SubSectIterator(const NonEmptySubSectIterator &subSect,
                   const SparseIterator &parent,
-                  std::unique_ptr<SparseIterator> &&wrap, Value size,
-                  unsigned stride)
+                  std::unique_ptr<SparseIterator> &&wrap, Value size)
       : SparseIterator(IterKind::kSubSect, *wrap,
                        /*extraCursorCnt=*/wrap->randomAccessible() ? 0 : 1),
         subSect(subSect), wrap(std::move(wrap)), parent(parent), size(size),
-        stride(stride), helper(*this) {
-    assert(stride == 1 && "Not implemented.");
+        helper(*this) {
     assert(subSect.tid == tid && subSect.lvl == lvl);
     assert(parent.kind != IterKind::kSubSect || parent.lvl + 1 == lvl);
   };
@@ -766,8 +764,6 @@ class SubSectIterator : public SparseIterator {
   const SparseIterator &parent;
 
   Value size;
-  unsigned stride;
-
   SubSectIterHelper helper;
 };
 
@@ -1330,29 +1326,19 @@ sparse_tensor::makeSlicedLevelIterator(std::unique_ptr<SparseIterator> &&sit,
   return std::make_unique<FilterIterator>(std::move(sit), offset, stride, size);
 }
 
-template <typename IterType>
 static const SparseIterator *tryUnwrapFilter(const SparseIterator *it) {
   auto *filter = llvm::dyn_cast_or_null<FilterIterator>(it);
-  if (filter && llvm::isa<IterType>(filter->wrap.get())) {
+  if (filter)
     return filter->wrap.get();
-  }
   return it;
 }
-template <typename IterType>
-static const IterType *unwrapFilter(const SparseIterator *it) {
-  auto *filter = llvm::dyn_cast_or_null<FilterIterator>(it);
-  if (filter) {
-    return llvm::cast<IterType>(filter->wrap.get());
-  }
-  return llvm::cast<IterType>(it);
-}
 
 std::unique_ptr<SparseIterator> sparse_tensor::makeNonEmptySubSectIterator(
     OpBuilder &b, Location l, const SparseIterator *parent, Value loopBound,
     std::unique_ptr<SparseIterator> &&delegate, Value size, unsigned stride) {
 
   // Try unwrap the NonEmptySubSectIterator from a filter parent.
-  parent = tryUnwrapFilter<NonEmptySubSectIterator>(parent);
+  parent = tryUnwrapFilter(parent);
   auto it = std::make_unique<NonEmptySubSectIterator>(
       b, l, parent, std::move(delegate), size);
 
@@ -1366,12 +1352,21 @@ std::unique_ptr<SparseIterator> sparse_tensor::makeNonEmptySubSectIterator(
 }
 
 std::unique_ptr<SparseIterator> sparse_tensor::makeTraverseSubSectIterator(
-    const SparseIterator &subSectIter, const SparseIterator &parent,
-    std::unique_ptr<SparseIterator> &&wrap, Value size, unsigned stride) {
+    OpBuilder &b, Location l, const SparseIterator &subSectIter,
+    const SparseIterator &parent, std::unique_ptr<SparseIterator> &&wrap,
+    Value size, unsigned stride) {
+
   // This must be a subsection iterator or a filtered subsection iterator.
-  auto &subSect = *unwrapFilter<NonEmptySubSectIterator>(&subSectIter);
-  return std::make_unique<SubSectIterator>(subSect, parent, std::move(wrap),
-                                           size, stride);
+  auto &subSect =
+      llvm::cast<NonEmptySubSectIterator>(*tryUnwrapFilter(&subSectIter));
+
+  auto it = std::make_unique<SubSectIterator>(
+      subSect, *tryUnwrapFilter(&parent), std::move(wrap), size);
+  if (stride != 1) {
+    return std::make_unique<FilterIterator>(std::move(it), /*offset=*/C_IDX(0),
+                                            C_IDX(stride), /*size=*/size);
+  }
+  return it;
 }
 
 #undef CMPI
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.h b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.h
index 318530cda7632..d8bb7f81ac1f4 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.h
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.h
@@ -300,8 +300,9 @@ std::unique_ptr<SparseIterator> makeNonEmptySubSectIterator(
 /// Helper function to create a SparseIterator object that iterate over a
 /// non-empty subsection created by NonEmptySubSectIterator.
 std::unique_ptr<SparseIterator> makeTraverseSubSectIterator(
-    const SparseIterator &subsectIter, const SparseIterator &parent,
-    std::unique_ptr<SparseIterator> &&delegate, Value size, unsigned stride);
+    OpBuilder &b, Location l, const SparseIterator &subsectIter,
+    const SparseIterator &parent, std::unique_ptr<SparseIterator> &&delegate,
+    Value size, unsigned stride);
 
 } // namespace sparse_tensor
 } // namespace mlir
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir
new file mode 100644
index 0000000000000..259250490732c
--- /dev/null
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir
@@ -0,0 +1,148 @@
+//--------------------------------------------------------------------------------------------------
+// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS.
+//
+// Set-up that's shared across all tests in this directory. In principle, this
+// config could be moved to lit.local.cfg. However, there are downstream users that
+//  do not use these LIT config files. Hence why this is kept inline.
+//
+// DEFINE: %{sparsifier_opts} = enable-runtime-library=true
+// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts}
+// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
+// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
+// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
+// DEFINE: %{run_opts} = -e entry -entry-point-result=void
+// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
+// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs}
+//
+// DEFINE: %{env} =
+//--------------------------------------------------------------------------------------------------
+
+// RUN: %{compile} | %{run} | FileCheck %s
+//
+// Do the same run, but now with direct IR generation.
+// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false enable-buffer-initialization=true
+// RUN: %{compile} | %{run} | FileCheck %s
+//
+// Do the same run, but now with direct IR generation and vectorization.
+// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false enable-buffer-initialization=true vl=2 reassociate-fp-reductions=true enable-index-optimizations=true
+// RUN: %{compile} | %{run} | FileCheck %s
+//
+// Do the same run, but now with direct IR generation and VLA vectorization.
+// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %}
+
+#CCCC = #sparse_tensor.encoding<{
+  map = (d0, d1, d2, d3) -> (d0 : compressed, d1 : compressed, d2 : compressed, d3 : compressed)
+}>
+
+#CDCC = #sparse_tensor.encoding<{
+  map = (d0, d1, d2, d3) -> (d0 : compressed, d1 : dense, d2 : compressed, d3 : compressed)
+}>
+
+// Creates and returns 4-D buffer of size (%s1, %s2, %s3, %s4) filled with the value %f
+func.func @alloc_4d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %s4 : index, %f : f32) -> tensor<?x?x?x?xf32> {
+  %buf = tensor.empty(%s1, %s2, %s3, %s4) : tensor<?x?x?x?xf32>
+  %ret = linalg.fill ins(%f : f32) outs(%buf : tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
+  return %ret : tensor<?x?x?x?xf32>
+}
+
+func.func @conv_2d_nhwc_hwcf(%arg0: tensor<?x?x?x?xf32>, %arg1: tensor<?x?x?x?xf32>, %arg2: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32> {
+  %ret = linalg.conv_2d_nhwc_hwcf {dilations = dense<2> : tensor<2xi64>,
+                                     strides = dense<1> : tensor<2xi64>}
+     ins (%arg0, %arg1: tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>)
+    outs (%arg2: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
+  return %ret : tensor<?x?x?x?xf32>
+}
+
+func.func @conv_2d_nhwc_hwcf_CCCC(%arg0: tensor<?x?x?x?xf32, #CCCC>, %arg1: tensor<?x?x?x?xf32>, %arg2: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32> {
+  %ret = linalg.conv_2d_nhwc_hwcf {dilations = dense<2> : tensor<2xi64>,
+                                     strides = dense<1> : tensor<2xi64>}
+     ins (%arg0, %arg1: tensor<?x?x?x?xf32, #CCCC>, tensor<?x?x?x?xf32>)
+    outs (%arg2: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
+  return %ret : tensor<?x?x?x?xf32>
+}
+
+func.func @conv_2d_nhwc_hwcf_CDCC(%arg0: tensor<?x?x?x?xf32, #CDCC>, %arg1: tensor<?x?x?x?xf32>, %arg2: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32> {
+  %ret = linalg.conv_2d_nhwc_hwcf {dilations = dense<2> : tensor<2xi64>,
+                                     strides = dense<1> : tensor<2xi64>}
+     ins (%arg0, %arg1: tensor<?x?x?x?xf32, #CDCC>, tensor<?x?x?x?xf32>)
+    outs (%arg2: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
+  return %ret : tensor<?x?x?x?xf32>
+}
+
+func.func @conv_2d_nhwc_hwcf_dual_CDCC(%arg0: tensor<?x?x?x?xf32, #CDCC>, %arg1: tensor<?x?x?x?xf32, #CDCC>, %arg2: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32> {
+  %ret = linalg.conv_2d_nhwc_hwcf {dilations = dense<2> : tensor<2xi64>,
+                                     strides = dense<1> : tensor<2xi64>}
+     ins (%arg0, %arg1: tensor<?x?x?x?xf32, #CDCC>, tensor<?x?x?x?xf32, #CDCC>)
+    outs (%arg2: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
+  return %ret : tensor<?x?x?x?xf32>
+}
+
+
+func.func @entry() {
+  %c0 = arith.constant 0 : index
+  %c1 = arith.constant 1 : index
+  %c3 = arith.constant 3 : index
+  %c5 = arith.constant 5 : index
+  %c6 = arith.constant 6 : index
+  %c7 = arith.constant 7 : index
+  %f10 = arith.constant 10.00000e+00 : f32
+  %val = arith.constant 2.00000e+00 : f32
+  %zero = arith.constant 0.00000e+00 : f32
+
+  %filter2D_nhwc = call @alloc_4d_filled_f32(%c3, %c3, %c3, %c1, %val) :(index, index, index, index, f32) -> (tensor<?x?x?x?xf32>)
+  %in2D_tmp = call @alloc_4d_filled_f32(%c3, %c7, %c7, %c3, %zero) : (index, index, index, index, f32) -> (tensor<?x?x?x?xf32>)
+  %in2D_nhwc = tensor.insert %f10 into %in2D_tmp[%c0, %c1, %c1, %c0] : tensor<?x?x?x?xf32>
+  %out2D_nhwc = call @alloc_4d_filled_f32(%c3, %c3, %c3, %c1, %zero) : (index, index, index, index, f32) -> (tensor<?x?x?x?xf32>)
+
+  %in2D_nhwc_CCCC = sparse_tensor.convert %in2D_nhwc
+    : tensor<?x?x?x?xf32> to tensor<?x?x?x?xf32, #CCCC>
+  %filter2D_nhwc_CDCC = sparse_tensor.convert %filter2D_nhwc
+    : tensor<?x?x?x?xf32> to tensor<?x?x?x?xf32, #CDCC>
+  %in2D_nhwc_CDCC = sparse_tensor.convert %in2D_nhwc
+    : tensor<?x?x?x?xf32> to tensor<?x?x?x?xf32, #CDCC>
+
+  %dense_ret = call @conv_2d_nhwc_hwcf(%in2D_nhwc, %filter2D_nhwc, %out2D_nhwc) : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>) -> (tensor<?x?x?x?xf32>)
+  %CCCC_ret = call @conv_2d_nhwc_hwcf_CCCC(%in2D_nhwc_CCCC, %filter2D_nhwc, %out2D_nhwc) : (tensor<?x?x?x?xf32, #CCCC>, tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>) -> (tensor<?x?x?x?xf32>)
+  %CDCC_ret = call @conv_2d_nhwc_hwcf_CDCC(%in2D_nhwc_CDCC, %filter2D_nhwc, %out2D_nhwc) : (tensor<?x?x?x?xf32, #CDCC>, tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>) -> (tensor<?x?x?x?xf32>)
+
+  %dual_CDCC_ret = call @conv_2d_nhwc_hwcf_dual_CDCC(%in2D_nhwc_CDCC, %filter2D_nhwc_CDCC, %out2D_nhwc)
+    : (tensor<?x?x?x?xf32, #CDCC>, tensor<?x?x?x?xf32, #CDCC>, tensor<?x?x?x?xf32>) -> (tensor<?x?x?x?xf32>)
+
+  // CHECK:      ( ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 20 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
+  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
+  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ) )
+  %dense_v = vector.transfer_read %dense_ret[%c0, %c0, %c0, %c0], %zero
+      : tensor<?x?x?x?xf32>, vector<3x3x3x1xf32>
+  vector.print %dense_v : vector<3x3x3x1xf32>
+
+  // CHECK-NEXT: ( ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 20 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
+  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
+  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ) )
+  %v_dual = vector.transfer_read %dual_CDCC_ret[%c0, %c0, %c0, %c0], %zero
+      : tensor<?x?x?x?xf32>, vector<3x3x3x1xf32>
+  vector.print %v_dual : vector<3x3x3x1xf32>
+
+  // CHECK-NEXT: ( ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 20 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
+  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
+  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ) )
+  %v1 = vector.transfer_read %CCCC_ret[%c0, %c0, %c0, %c0], %zero
+      : tensor<?x?x?x?xf32>, vector<3x3x3x1xf32>
+  vector.print %v1 : vector<3x3x3x1xf32>
+
+  // CHECK-NEXT: ( ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 20 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
+  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
+  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ) )
+  %v2 = vector.transfer_read %CDCC_ret[%c0, %c0, %c0, %c0], %zero
+      : tensor<?x?x?x?xf32>, vector<3x3x3x1xf32>
+  vector.print %v1 : vector<3x3x3x1xf32>
+
+  // Free the resources
+  bufferization.dealloc_tensor %in2D_nhwc : tensor<?x?x?x?xf32>
+  bufferization.dealloc_tensor %filter2D_nhwc : tensor<?x?x?x?xf32>
+  bufferization.dealloc_tensor %out2D_nhwc : tensor<?x?x?x?xf32>
+
+  bufferization.dealloc_tensor %filter2D_nhwc_CDCC : tensor<?x?x?x?xf32, #CDCC>
+  bufferization.dealloc_tensor %in2D_nhwc_CCCC : tensor<?x?x?x?xf32, #CCCC>
+  bufferization.dealloc_tensor %in2D_nhwc_CDCC : tensor<?x?x?x?xf32, #CDCC>
+  return
+}

>From 5b15e44600b56e01ef3b967b3d68ffbd9400b7b7 Mon Sep 17 00:00:00 2001
From: Peiming Liu <peiming at google.com>
Date: Fri, 2 Feb 2024 19:31:26 +0000
Subject: [PATCH 2/3] address comment + fix bug

---
 .../Transforms/Utils/LoopEmitter.cpp          |  8 ++---
 .../Transforms/Utils/SparseTensorLevel.cpp    | 19 ++++++------
 .../Transforms/Utils/SparseTensorLevel.h      |  4 +--
 .../CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir | 30 +++++++++----------
 4 files changed, 31 insertions(+), 30 deletions(-)

diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/LoopEmitter.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/LoopEmitter.cpp
index a8aa8d8f01797..1c2857d868a60 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/LoopEmitter.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/LoopEmitter.cpp
@@ -313,16 +313,16 @@ void LoopEmitter::initSubSectIterator(OpBuilder &builder, Location loc) {
         // Compute the subsection size.
         Value size = c0;
         for (auto [loop, stride] : remDepStack[t][lvl]) {
-          Value loopHi = loopHighs[loop];
-          size = ADDI(size, MULI(loopHi, C_IDX(stride)));
+          Value idxMax = SUBI(loopHighs[loop], C_IDX(1));
+          size = ADDI(size, ADDI(MULI(idxMax, C_IDX(stride)), C_IDX(1)));
         }
         it = makeNonEmptySubSectIterator(builder, loc, parent, loopHighs[loop],
                                          std::move(lvlIt), size, curDep.second);
       } else {
-        Value size = loopHighs[loop];
         const SparseIterator &subSectIter = *iters[t][lvl].back();
         it = makeTraverseSubSectIterator(builder, loc, subSectIter, *parent,
-                                         std::move(lvlIt), size, curDep.second);
+                                         std::move(lvlIt), loopHighs[loop],
+                                         curDep.second);
       }
       lastIter[t] = it.get();
       iters[t][lvl].emplace_back(std::move(it));
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.cpp
index 47aa2fcaa6ae5..04b49c320f07a 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.cpp
@@ -665,11 +665,10 @@ class SubSectIterator : public SparseIterator {
 public:
   SubSectIterator(const NonEmptySubSectIterator &subSect,
                   const SparseIterator &parent,
-                  std::unique_ptr<SparseIterator> &&wrap, Value size)
+                  std::unique_ptr<SparseIterator> &&wrap)
       : SparseIterator(IterKind::kSubSect, *wrap,
                        /*extraCursorCnt=*/wrap->randomAccessible() ? 0 : 1),
-        subSect(subSect), wrap(std::move(wrap)), parent(parent), size(size),
-        helper(*this) {
+        subSect(subSect), wrap(std::move(wrap)), parent(parent), helper(*this) {
     assert(subSect.tid == tid && subSect.lvl == lvl);
     assert(parent.kind != IterKind::kSubSect || parent.lvl + 1 == lvl);
   };
@@ -691,7 +690,9 @@ class SubSectIterator : public SparseIterator {
 
   bool randomAccessible() const override { return wrap->randomAccessible(); };
   bool iteratableByFor() const override { return randomAccessible(); };
-  Value upperBound(OpBuilder &b, Location l) const override { return size; }
+  Value upperBound(OpBuilder &b, Location l) const override {
+    return subSect.subSectSz;
+  }
   std::pair<Value, Value> getCurPosition() const override {
     return wrap->getCurPosition();
   };
@@ -709,7 +710,7 @@ class SubSectIterator : public SparseIterator {
         assert(p->lvl + 1 == lvl);
         wrap->genInit(b, l, p);
         // Linearize the dense subsection index.
-        nxLvlTupleStart = MULI(size, p->getNxLvlTupleId(b, l));
+        nxLvlTupleStart = MULI(subSect.subSectSz, p->getNxLvlTupleId(b, l));
       } else {
         assert(subSect.lvl == lvl && subSect.isSubSectRoot());
         wrap->deserialize(subSect.delegate->serialize());
@@ -763,7 +764,6 @@ class SubSectIterator : public SparseIterator {
   std::unique_ptr<SparseIterator> wrap;
   const SparseIterator &parent;
 
-  Value size;
   SubSectIterHelper helper;
 };
 
@@ -1354,17 +1354,18 @@ std::unique_ptr<SparseIterator> sparse_tensor::makeNonEmptySubSectIterator(
 std::unique_ptr<SparseIterator> sparse_tensor::makeTraverseSubSectIterator(
     OpBuilder &b, Location l, const SparseIterator &subSectIter,
     const SparseIterator &parent, std::unique_ptr<SparseIterator> &&wrap,
-    Value size, unsigned stride) {
+    Value loopBound, unsigned stride) {
 
   // This must be a subsection iterator or a filtered subsection iterator.
   auto &subSect =
       llvm::cast<NonEmptySubSectIterator>(*tryUnwrapFilter(&subSectIter));
 
   auto it = std::make_unique<SubSectIterator>(
-      subSect, *tryUnwrapFilter(&parent), std::move(wrap), size);
+      subSect, *tryUnwrapFilter(&parent), std::move(wrap));
+
   if (stride != 1) {
     return std::make_unique<FilterIterator>(std::move(it), /*offset=*/C_IDX(0),
-                                            C_IDX(stride), /*size=*/size);
+                                            C_IDX(stride), /*size=*/loopBound);
   }
   return it;
 }
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.h b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.h
index d8bb7f81ac1f4..fc2d9de66cfe7 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.h
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/SparseTensorLevel.h
@@ -301,8 +301,8 @@ std::unique_ptr<SparseIterator> makeNonEmptySubSectIterator(
 /// non-empty subsection created by NonEmptySubSectIterator.
 std::unique_ptr<SparseIterator> makeTraverseSubSectIterator(
     OpBuilder &b, Location l, const SparseIterator &subsectIter,
-    const SparseIterator &parent, std::unique_ptr<SparseIterator> &&delegate,
-    Value size, unsigned stride);
+    const SparseIterator &parent, std::unique_ptr<SparseIterator> &&wrap,
+    Value loopBound, unsigned stride);
 
 } // namespace sparse_tensor
 } // namespace mlir
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir
index 259250490732c..4b5d4b9e68186 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir
@@ -90,8 +90,8 @@ func.func @entry() {
   %zero = arith.constant 0.00000e+00 : f32
 
   %filter2D_nhwc = call @alloc_4d_filled_f32(%c3, %c3, %c3, %c1, %val) :(index, index, index, index, f32) -> (tensor<?x?x?x?xf32>)
-  %in2D_tmp = call @alloc_4d_filled_f32(%c3, %c7, %c7, %c3, %zero) : (index, index, index, index, f32) -> (tensor<?x?x?x?xf32>)
-  %in2D_nhwc = tensor.insert %f10 into %in2D_tmp[%c0, %c1, %c1, %c0] : tensor<?x?x?x?xf32>
+  %in2D_tmp = call @alloc_4d_filled_f32(%c3, %c7, %c7, %c3, %f10) : (index, index, index, index, f32) -> (tensor<?x?x?x?xf32>)
+  %in2D_nhwc = tensor.insert %zero into %in2D_tmp[%c0, %c1, %c1, %c0] : tensor<?x?x?x?xf32>
   %out2D_nhwc = call @alloc_4d_filled_f32(%c3, %c3, %c3, %c1, %zero) : (index, index, index, index, f32) -> (tensor<?x?x?x?xf32>)
 
   %in2D_nhwc_CCCC = sparse_tensor.convert %in2D_nhwc
@@ -108,35 +108,35 @@ func.func @entry() {
   %dual_CDCC_ret = call @conv_2d_nhwc_hwcf_dual_CDCC(%in2D_nhwc_CDCC, %filter2D_nhwc_CDCC, %out2D_nhwc)
     : (tensor<?x?x?x?xf32, #CDCC>, tensor<?x?x?x?xf32, #CDCC>, tensor<?x?x?x?xf32>) -> (tensor<?x?x?x?xf32>)
 
-  // CHECK:      ( ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 20 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
-  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
-  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ) )
+  // CHECK-NEXT: ( ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 520 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
+  // CHECK-SAME:   ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
+  // CHECK-SAME:   ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ) )
   %dense_v = vector.transfer_read %dense_ret[%c0, %c0, %c0, %c0], %zero
       : tensor<?x?x?x?xf32>, vector<3x3x3x1xf32>
   vector.print %dense_v : vector<3x3x3x1xf32>
 
-  // CHECK-NEXT: ( ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 20 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
-  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
-  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ) )
+  // CHECK-NEXT: ( ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 520 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
+  // CHECK-SAME:   ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
+  // CHECK-SAME:   ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ) )
   %v_dual = vector.transfer_read %dual_CDCC_ret[%c0, %c0, %c0, %c0], %zero
       : tensor<?x?x?x?xf32>, vector<3x3x3x1xf32>
   vector.print %v_dual : vector<3x3x3x1xf32>
 
-  // CHECK-NEXT: ( ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 20 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
-  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
-  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ) )
+  // CHECK-NEXT: ( ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 520 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
+  // CHECK-SAME:   ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
+  // CHECK-SAME:   ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ) )
   %v1 = vector.transfer_read %CCCC_ret[%c0, %c0, %c0, %c0], %zero
       : tensor<?x?x?x?xf32>, vector<3x3x3x1xf32>
   vector.print %v1 : vector<3x3x3x1xf32>
 
-  // CHECK-NEXT: ( ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 20 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
-  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ),
-  // CHECK-SAME:   ( ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ), ( ( 0 ), ( 0 ), ( 0 ) ) ) )
+  // CHECK-NEXT: ( ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 520 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
+  // CHECK-SAME:   ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
+  // CHECK-SAME:   ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ) )
   %v2 = vector.transfer_read %CDCC_ret[%c0, %c0, %c0, %c0], %zero
       : tensor<?x?x?x?xf32>, vector<3x3x3x1xf32>
   vector.print %v1 : vector<3x3x3x1xf32>
 
-  // Free the resources
+  // Free the resources.
   bufferization.dealloc_tensor %in2D_nhwc : tensor<?x?x?x?xf32>
   bufferization.dealloc_tensor %filter2D_nhwc : tensor<?x?x?x?xf32>
   bufferization.dealloc_tensor %out2D_nhwc : tensor<?x?x?x?xf32>

>From d91198dafc65b80643b8af5a1b51e920ebaf93ef Mon Sep 17 00:00:00 2001
From: Peiming Liu <peiming at google.com>
Date: Fri, 2 Feb 2024 19:38:56 +0000
Subject: [PATCH 3/3] fix

---
 .../SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir      | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir
index 4b5d4b9e68186..af7ee43647581 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dilated_conv_2d_nhwc_hwcf.mlir
@@ -108,7 +108,7 @@ func.func @entry() {
   %dual_CDCC_ret = call @conv_2d_nhwc_hwcf_dual_CDCC(%in2D_nhwc_CDCC, %filter2D_nhwc_CDCC, %out2D_nhwc)
     : (tensor<?x?x?x?xf32, #CDCC>, tensor<?x?x?x?xf32, #CDCC>, tensor<?x?x?x?xf32>) -> (tensor<?x?x?x?xf32>)
 
-  // CHECK-NEXT: ( ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 520 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
+  // CHECK:      ( ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 520 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
   // CHECK-SAME:   ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ),
   // CHECK-SAME:   ( ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ), ( ( 540 ), ( 540 ), ( 540 ) ) ) )
   %dense_v = vector.transfer_read %dense_ret[%c0, %c0, %c0, %c0], %zero



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