[mlir][tensor] Loosen restrictions on folding dynamic reshapes

mlir/lib/Dialect/Utils/ReshapeOpsUtils.cpp

@@ -31,64 +31,128 @@ mlir::getReassociationIndicesForReshape(ShapedType sourceType,
 std::optional<SmallVector<ReassociationIndices>>
 mlir::getReassociationIndicesForCollapse(ArrayRef<int64_t> sourceShape,
                                          ArrayRef<int64_t> targetShape) {
-  if (sourceShape.size() <= targetShape.size())
+  unsigned numSourceDims = sourceShape.size(),
+           numTargetDims = targetShape.size();
+  if (numSourceDims <= numTargetDims)
     return std::nullopt;
-  unsigned sourceDim = 0;
-  SmallVector<ReassociationIndices> reassociationMap;
-  reassociationMap.reserve(targetShape.size());
-
-  ReassociationIndices currIndices;
-  int64_t prodOfCollapsedDims = 1;
-  while (sourceDim < sourceShape.size()) {
-    unsigned targetDim = reassociationMap.size();
-    // If we have mapped all the target dimensions stop and handle the remaining
-    // tail of size-1 dimensions explicitly.
-    if (targetDim == targetShape.size())
-      break;
-
-    int64_t currTargetShape = targetShape[targetDim];
-    while (sourceDim < (sourceShape.size() - 1) &&
-           sourceShape[sourceDim] != ShapedType::kDynamic &&
-           prodOfCollapsedDims * sourceShape[sourceDim] < currTargetShape) {
-      prodOfCollapsedDims *= sourceShape[sourceDim];
-      currIndices.push_back(sourceDim++);
+  SmallVector<ReassociationIndices, 4> reassociationMap;
+  reassociationMap.reserve(numTargetDims);
+
+  unsigned sourceDimIdx = 0, targetDimIdx = 0;
+  // Source dimensions iteration logic for static target dimensions.
+  // FIXME: Instead of lambda-capturing this function's source shape index "in
+  // place", consider refactoring this into a separate function.
+  auto collectSourceIndicesForStaticTargetDim =
+      [&](int64_t targetShape,
+          bool mayHaveOffset = false) -> FailureOr<ReassociationIndices> {
+    ReassociationIndices resultIndices;
+    int64_t prodOfCollapsedDims = 1;
+    bool reachedTargetDimSize = false;
+    for (; sourceDimIdx < numSourceDims; ++sourceDimIdx) {
+      // Source shape cannot be dynamic if the target dim is static.
+      if (sourceShape[sourceDimIdx] == ShapedType::kDynamic)
+        return failure();
+      prodOfCollapsedDims *= sourceShape[sourceDimIdx];
+      resultIndices.push_back(sourceDimIdx);
+      if (prodOfCollapsedDims > targetShape && !mayHaveOffset)
+        return failure();
+      while (prodOfCollapsedDims > targetShape) {
+        assert(!resultIndices.empty());
+        auto frontOffsetIdx = resultIndices.begin();
+        prodOfCollapsedDims /= sourceShape[*frontOffsetIdx];
+        resultIndices.erase(frontOffsetIdx);
+      }
+      if (prodOfCollapsedDims == targetShape) {
+        reachedTargetDimSize = true;
+        ++sourceDimIdx;
+        break;
+      }
+    }
+    if (!reachedTargetDimSize)
+      return failure();
+    return resultIndices;
+  };
+  // Source dimensions iteration logic for dynamic target dimensions.
+  // FIXME: Instead of lambda-capturing this function's source shape index "in
+  // place", consider refactoring this into a separate function.
+  auto collectSourceIndicesForDynamicTargetDim =
+      [&](bool allowStaticNonOnes,
+          bool mapConsecutiveDynDims) -> FailureOr<ReassociationIndices> {
+    ReassociationIndices resultIndices;
+    bool foundFirstDynamic = false;
+    while (sourceDimIdx < numSourceDims) {
+      if (sourceShape[sourceDimIdx] == ShapedType::kDynamic) {
+        if (foundFirstDynamic && !mapConsecutiveDynDims)
+          break;
+        foundFirstDynamic |= true;
+      } else {
+        if (foundFirstDynamic)
+          break;
+        else if (sourceShape[sourceDimIdx] > 1 && !allowStaticNonOnes)
+          return failure();
+      }
+      resultIndices.push_back(sourceDimIdx++);
+    }
+    if (!foundFirstDynamic)
+      return failure();
+    return resultIndices;
+  };
+  // Iterate over target shape.
+  bool wasLastDimDynamic = false;
+  for (; targetDimIdx < numTargetDims; ++targetDimIdx) {
+    int64_t currTargetShape = targetShape[targetDimIdx];
+    if (currTargetShape != ShapedType::kDynamic) {
+      unsigned sourceDimAtStart = sourceDimIdx;
+      auto indices = collectSourceIndicesForStaticTargetDim(
+          currTargetShape, /*mayHaveOffset=*/wasLastDimDynamic);
+      if (failed(indices))
+        return std::nullopt;
+      if (wasLastDimDynamic) {
+        assert(!reassociationMap.empty());
+        auto &previousIndices = reassociationMap.back();
+        for (; sourceDimAtStart < indices->front(); ++sourceDimAtStart)
+          previousIndices.push_back(sourceDimAtStart);
+      }
+      reassociationMap.push_back(*indices);
+      wasLastDimDynamic = false;
+      continue;
     }
 
-    // If the current expanded dimension is dynamic, then the collapsed
-    // dimensions should also be dynamic and product of all previous unprocessed
-    // dimensions of the expanded shape should be 1.
-    if (sourceShape[sourceDim] == ShapedType::kDynamic &&
-        (currTargetShape != ShapedType::kDynamic || prodOfCollapsedDims != 1))
-      return std::nullopt;
-
-    // If the collapsed dim is dynamic, the current expanded dim should also
-    // be dynamic.
-    if (currTargetShape == ShapedType::kDynamic &&
-        sourceShape[sourceDim] != ShapedType::kDynamic)
-      return std::nullopt;
-
-    // For static shapes, if the product of dimensions of the expanded shape
-    // should match the collapsed dimension shape.
-    if (prodOfCollapsedDims * sourceShape[sourceDim] != currTargetShape)
+    bool isNextDimDynamic =
+        targetDimIdx + 1 < numTargetDims &&
+        targetShape[targetDimIdx + 1] == ShapedType::kDynamic;
+    auto indices = collectSourceIndicesForDynamicTargetDim(
+        /*allowStaticNonOnes=*/!wasLastDimDynamic,
+        /*mapConsecutiveDynDims=*/!wasLastDimDynamic && !isNextDimDynamic);
+    if (failed(indices))
       return std::nullopt;
-
-    currIndices.push_back(sourceDim++);
-    reassociationMap.emplace_back(ReassociationIndices{});
-    std::swap(reassociationMap.back(), currIndices);
-    prodOfCollapsedDims = 1;
+    reassociationMap.push_back(*indices);
+    wasLastDimDynamic = true;
   }
-  // All the dimensions in the target must have been processed.
-  if (reassociationMap.size() != targetShape.size())
-    return std::nullopt;
-  // Process any remaining entries in the source shape. They all need to be
-  // 1 or dynamic.
-  for (; sourceDim < sourceShape.size(); sourceDim++) {
-    if (sourceShape[sourceDim] != ShapedType::kDynamic &&
-        sourceShape[sourceDim] != 1)
+  // Now that we've mapped all the target dimensions, process any remaining
+  // entries in the source shape explicitly.
+  for (; sourceDimIdx < numSourceDims; sourceDimIdx++) {
+    const bool isOne = sourceShape[sourceDimIdx] == 1,
+               isDynamic = sourceShape[sourceDimIdx] == ShapedType::kDynamic;
+    if (targetShape.empty()) {
+      if (!isOne && !isDynamic)
+        return std::nullopt;
+      continue;
+    }
+    // If the last 2 dimensions in the target were dynamic, the tail in the
+    // source shape cannot contain a dynamic value. E.g. ?x?->? is valid,
+    // however ?x?x10x?->?x? would be indeterminate.
+    if (wasLastDimDynamic && numTargetDims > 1 &&
+        targetShape[numTargetDims - 2] == ShapedType::kDynamic) {
+      if (isDynamic)
+        return std::nullopt;
+    }
+    // If the last target dimension is static, only source dimensions of 1 are
+    // acceptable.
+    if (!wasLastDimDynamic && !isOne)
       return std::nullopt;
-    // The map is empty when the target type is a scalar.
-    if (!reassociationMap.empty())
-      reassociationMap.back().push_back(sourceDim);
+    assert(!reassociationMap.empty());
+    reassociationMap.back().push_back(sourceDimIdx);
   }
   return reassociationMap;
 }

mlir/test/Dialect/Linalg/simplify-pack-unpack.mlir

@@ -158,8 +158,8 @@ func.func @unpack_to_partial_slice(%arg0: tensor<8x32xf32>) -> tensor<255xf32> {
 // -----
 
 // CHECK-LABEL: func.func @unpack_dynamic
-// CHECK-NOT:     tensor.collapse
-// CHECK:         linalg.unpack
+// CHECK:     tensor.collapse
+// CHECK-NOT:         linalg.unpack
 func.func @unpack_dynamic(%arg0: tensor<?x32xf32>) -> tensor<?xf32> {
   %c32 = arith.constant 32 : index
   %c0 = arith.constant 0 : index

mlir/test/Dialect/Tensor/canonicalize.mlir

@@ -1068,28 +1068,59 @@ func.func @fold_expand_of_collapse(%arg0 : tensor<3x4x4xf32>) -> tensor<3x4x4xf3
 
 // -----
 
-func.func @fold_expand_of_collapse_dynamic(%arg0 : tensor<?x4x?xf32>, %arg1: index, %arg2: index)
+func.func @fold_expand_of_collapse_mixed_subshape(%arg0 : tensor<?x4x?xf32>, %arg1: index, %arg2: index)
     -> tensor<?x4x?xf32> {
   %0 = tensor.collapse_shape %arg0 [[0, 1], [2]]
       : tensor<?x4x?xf32> into tensor<?x?xf32>
   %1 = tensor.expand_shape %0 [[0, 1], [2]] output_shape [%arg1, 4, %arg2]
       : tensor<?x?xf32> into tensor<?x4x?xf32>
   return %1 : tensor<?x4x?xf32>
 }
-// CHECK-LABEL: @fold_expand_of_collapse_dynamic
+// CHECK-LABEL: @fold_expand_of_collapse_mixed_subshape
 //   CHECK-NOT:   tensor.{{.*}}_shape
 
 // -----
 
-func.func @no_fold_expand_of_collapse_dynamic(%arg0 : tensor<?x?x?xf32>, %arg1: index, %arg2: index, %arg3: index)
+func.func @fold_expand_of_collapse_mixed_target_subshape(%arg0 : tensor<?x4x?x2xf32>, %arg1: index, %arg2: index)
+    -> tensor<?x4x?xf32> {
+  %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]]
+      : tensor<?x4x?x2xf32> into tensor<?x?xf32>
+  %1 = tensor.expand_shape %0 [[0, 1], [2]] output_shape [%arg1, 4, %arg2]
+      : tensor<?x?xf32> into tensor<?x4x?xf32>
+  return %1 : tensor<?x4x?xf32>
+}
+// CHECK-LABEL: @fold_expand_of_collapse_mixed_target_subshape
+//   CHECK-NOT:   tensor.expand_shape
+//       CHECK:   %[[COLLAPSE:.+]] = tensor.collapse_shape %arg0 {{\[}}[0], [1], [2, 3]]
+//  CHECK-SAME:     : tensor<?x4x?x2xf32> into tensor<?x4x?xf32>
+//  CHECK-NEXT:   return %[[COLLAPSE]]
+
+// -----
+
+func.func @no_fold_expand_of_collapse_fully_dynamic(%arg0 : tensor<?x?x?xf32>, %arg1: index, %arg2: index, %arg3: index)
     -> tensor<?x?x?xf32> {
   %0 = tensor.collapse_shape %arg0 [[0, 1], [2]]
       : tensor<?x?x?xf32> into tensor<?x?xf32>
   %1 = tensor.expand_shape %0 [[0, 1], [2]] output_shape [%arg1, %arg2, %arg3]
       : tensor<?x?xf32> into tensor<?x?x?xf32>
   return %1 : tensor<?x?x?xf32>
 }
-// CHECK-LABEL: @no_fold_expand_of_collapse_dynamic
+// CHECK-LABEL: @no_fold_expand_of_collapse_fully_dynamic
+//       CHECK:   tensor.collapse_shape
+//       CHECK:   %[[EXPAND:.+]] = tensor.expand_shape
+//       CHECK:   return %[[EXPAND]]
+
+// -----
+
+func.func @no_fold_expand_of_collapse_adjacent_dynamic(%arg0 : tensor<?x?x?xf32>, %arg1: index, %arg2: index)
+    -> tensor<?x?xf32> {
+  %0 = tensor.collapse_shape %arg0 [[0, 1, 2]]
+      : tensor<?x?x?xf32> into tensor<?xf32>
+  %1 = tensor.expand_shape %0 [[0, 1]] output_shape [%arg1, %arg2]
+      : tensor<?xf32> into tensor<?x?xf32>
+  return %1 : tensor<?x?xf32>
+}
+// CHECK-LABEL: @no_fold_expand_of_collapse_adjacent_dynamic
 //       CHECK:   tensor.collapse_shape
 //       CHECK:   %[[EXPAND:.+]] = tensor.expand_shape
 //       CHECK:   return %[[EXPAND]]

mlir/unittests/Dialect/Utils/CMakeLists.txt

@@ -1,5 +1,6 @@
 add_mlir_unittest(MLIRDialectUtilsTests
   StructuredOpsUtilsTest.cpp
+  ReshapeOpsUtilsTest.cpp
   IndexingUtilsTest.cpp
 )
 mlir_target_link_libraries(MLIRDialectUtilsTests

mlir/unittests/Dialect/Utils/ReshapeOpsUtilsTest.cpp

@@ -0,0 +1,134 @@
+//===- ReshapeOpsUtilsTest.cpp - ReshapeOpsUtils unit tests ---------------===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+
+#include "mlir/Dialect/Utils/ReshapeOpsUtils.h"
+#include "llvm/ADT/STLExtras.h"
+#include "gtest/gtest.h"
+#include <optional>
+
+using namespace mlir;
+
+/// Helper to make constructing
+/// `std::optional<SmallVector<ReassociationIndices>>` more readable.
+static std::optional<SmallVector<ReassociationIndices>>
+makeOptionalIndices(std::initializer_list<ReassociationIndices> list) {
+  return std::optional<SmallVector<ReassociationIndices>>(list);
+}
+
+TEST(ReassociationIndicesForCollapse, StaticTest) {
+  EXPECT_EQ(getReassociationIndicesForCollapse({10, 20}, {200}),
+            makeOptionalIndices({{0, 1}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse({10, 20, 30}, {10, 600}),
+            makeOptionalIndices({{0}, {1, 2}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse({10, 20, 30}, {200, 30}),
+            makeOptionalIndices({{0, 1}, {2}}));
+}
+
+TEST(ReassociationIndicesForCollapse, StaticTestFailure) {
+  EXPECT_EQ(getReassociationIndicesForCollapse({10, 20}, {10}), std::nullopt);
+  EXPECT_EQ(getReassociationIndicesForCollapse({10, 20}, {10, 20}),
+            std::nullopt);
+  EXPECT_EQ(getReassociationIndicesForCollapse({10, 20, 30}, {200, 300}),
+            std::nullopt);
+  EXPECT_EQ(getReassociationIndicesForCollapse({10, 20, 30}, {1, 10, 20, 30}),
+            std::nullopt);
+}
+
+TEST(ReassociationIndicesForCollapse, StaticTestUnitDims) {
+  EXPECT_EQ(getReassociationIndicesForCollapse({10, 1}, {10}),
+            makeOptionalIndices({{0, 1}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse({1, 20, 30}, {600}),
+            makeOptionalIndices({{0, 1, 2}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse({1, 1, 1}, {1}),
+            makeOptionalIndices({{0, 1, 2}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse({1, 1, 1}, {1, 1}),
+            makeOptionalIndices({{0}, {1, 2}}));
+}
+
+TEST(ReassociationIndicesForCollapse, DynamicTest) {
+  EXPECT_EQ(getReassociationIndicesForCollapse({ShapedType::kDynamic, 1},
+                                               {ShapedType::kDynamic}),
+            makeOptionalIndices({{0, 1}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse({ShapedType::kDynamic, 1, 1},
+                                               {ShapedType::kDynamic}),
+            makeOptionalIndices({{0, 1, 2}}));
+  EXPECT_EQ(
+      getReassociationIndicesForCollapse(
+          {ShapedType::kDynamic, ShapedType::kDynamic}, {ShapedType::kDynamic}),
+      makeOptionalIndices({{0, 1}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {1, ShapedType::kDynamic, ShapedType::kDynamic},
+                {1, ShapedType::kDynamic}),
+            makeOptionalIndices({{0}, {1, 2}}));
+
+  EXPECT_EQ(getReassociationIndicesForCollapse({ShapedType::kDynamic, 10},
+                                               {ShapedType::kDynamic}),
+            makeOptionalIndices({{0, 1}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {1, ShapedType::kDynamic, ShapedType::kDynamic},
+                {ShapedType::kDynamic}),
+            makeOptionalIndices({{0, 1, 2}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse({10, ShapedType::kDynamic},
+                                               {ShapedType::kDynamic}),
+            makeOptionalIndices({{0, 1}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse({ShapedType::kDynamic, 10, 20},
+                                               {ShapedType::kDynamic, 20}),
+            makeOptionalIndices({{0, 1}, {2}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse({10, ShapedType::kDynamic, 20},
+                                               {ShapedType::kDynamic, 20}),
+            makeOptionalIndices({{0, 1}, {2}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {ShapedType::kDynamic, 3, 2, 5, 2}, {ShapedType::kDynamic, 20}),
+            makeOptionalIndices({{0, 1}, {2, 3, 4}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {10, ShapedType::kDynamic, 20, ShapedType::kDynamic, 1},
+                {ShapedType::kDynamic, 20, ShapedType::kDynamic}),
+            makeOptionalIndices({{0, 1}, {2}, {3, 4}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse({1, ShapedType::kDynamic, 1},
+                                               {ShapedType::kDynamic}),
+            makeOptionalIndices({{0, 1, 2}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {ShapedType::kDynamic, ShapedType::kDynamic, 1},
+                {ShapedType::kDynamic, ShapedType::kDynamic}),
+            makeOptionalIndices({{0}, {1, 2}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {1, ShapedType::kDynamic, ShapedType::kDynamic},
+                {ShapedType::kDynamic, ShapedType::kDynamic}),
+            makeOptionalIndices({{0, 1}, {2}}));
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {ShapedType::kDynamic, 1, ShapedType::kDynamic},
+                {ShapedType::kDynamic, ShapedType::kDynamic}),
+            makeOptionalIndices({{0}, {1, 2}}));
+}
+
+TEST(ReassociationIndicesForCollapse, DynamicTestFailure) {
+  EXPECT_EQ(getReassociationIndicesForCollapse({ShapedType::kDynamic, 10, 20},
+                                               {ShapedType::kDynamic, 10}),
+            std::nullopt);
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {ShapedType::kDynamic, 10, ShapedType::kDynamic},
+                {ShapedType::kDynamic, ShapedType::kDynamic}),
+            std::nullopt);
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {20, ShapedType::kDynamic, 10, ShapedType::kDynamic},
+                {ShapedType::kDynamic, ShapedType::kDynamic}),
+            std::nullopt);
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {ShapedType::kDynamic, 5, 3, 2, 2}, {ShapedType::kDynamic, 20}),
+            std::nullopt);
+  EXPECT_EQ(
+      getReassociationIndicesForCollapse(
+          {ShapedType::kDynamic, ShapedType::kDynamic, ShapedType::kDynamic},
+          {ShapedType::kDynamic, ShapedType::kDynamic}),
+      std::nullopt);
+  EXPECT_EQ(getReassociationIndicesForCollapse(
+                {ShapedType::kDynamic, ShapedType::kDynamic, 10, 1,
+                 ShapedType::kDynamic},
+                {ShapedType::kDynamic, ShapedType::kDynamic}),
+            std::nullopt);
+}