[Mlir-commits] [mlir] [mlir][sparse] support sparse dilated convolution. (PR #80470)
Peiming Liu
llvmlistbot at llvm.org
Fri Feb 2 11:39:10 PST 2024
https://github.com/PeimingLiu updated https://github.com/llvm/llvm-project/pull/80470
>From 317d7ede02f4271dc0f24f7f4d3433c9f6abd6a5 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 9eea57825de6a1d7b1e492d8b371fa42e153a3a2 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 d69fae2286694b9546f1cfabfccf772f902dbac3 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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