[MLIR][Tensor,MemRef] Fold expand_shape and collapse_shape if identity (llvm#80658)

Before: op verifiers failed if the input and output ranks were the same
(i.e. no expansion or collapse). This behavior requires users of these
shape ops to verify manually that they are not creating identity
versions of these ops every time they build them -- problematic. This PR
removes this strict verification, and introduces folders for the the
identity cases.

The PR also removes the special case handling of rank-0 tensors for
expand_shape and collapse_shape, there doesn't seem to be any reason to
treat them differently.

Author: newling

mlir/include/mlir/Dialect/MemRef/IR/MemRefOps.td

@@ -641,7 +641,7 @@ def MemRef_DmaStartOp : MemRef_Op<"dma_start"> {
   let summary = "non-blocking DMA operation that starts a transfer";
   let description = [{
     Syntax:
-    
+
     ```
     operation ::= `memref.dma_start` ssa-use`[`ssa-use-list`]` `,`
                    ssa-use`[`ssa-use-list`]` `,` ssa-use `,`

mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td

@@ -1098,21 +1098,18 @@ class Tensor_ReassociativeReshapeOp<string mnemonic, list<Trait> traits = []> :
 def Tensor_ExpandShapeOp : Tensor_ReassociativeReshapeOp<"expand_shape"> {
   let summary = "operation to produce a tensor with a higher rank";
   let description = [{
-    The `tensor.expand_shape` op produces a new tensor with a higher
-    rank whose sizes are a reassociation of the original `src`.
+    The `tensor.expand_shape` op produces a tensor of higher (or equal)
+    rank than the operand `src` whose dimension sizes are a reassociation of
+    `src`.
 
-    A reassociation is defined as a continuous grouping of dimensions and is
-    represented with an array of DenseI64ArrayAttr attribute.
-
-    The verification rule is that the reassociation maps are applied to the
-    result tensor with the higher rank to obtain the operand tensor with the
-    smaller rank.
+    A reassociation is defined as a continuous grouping of dimensions. It is
+    represented with an array of DenseI64ArrayAttr attribute. Entries in the
+    array are referred to as reassociation maps.
 
-    The operand tensor type of a reshape can be zero-ranked if the result
-    tensor type is statically shaped with all dimensions being unit extent. In
-    such cases the reassociation map is empty.
+    The reassociation maps are applied to the result shape to obtain the operand
+    shape.
 
-    Examples:
+    Example:
 
     ```mlir
     // Dimension expansion i -> (i', j') and (k) -> (k')
@@ -1150,21 +1147,15 @@ def Tensor_ExpandShapeOp : Tensor_ReassociativeReshapeOp<"expand_shape"> {
 def Tensor_CollapseShapeOp : Tensor_ReassociativeReshapeOp<"collapse_shape"> {
   let summary = "operation to produce a tensor with a smaller rank";
   let description = [{
-    The `tensor.collapse_shape` op produces a new tensor with a smaller
-    rank whose sizes are a reassociation of the original `src`.
+    The `tensor.collapse_shape` op produces a new tensor of lower (or equal)
+    rank whose dimension sizes are a reassociation of the original `src` dimensions.
 
     A reassociation is defined as a continuous grouping of dimensions and is
-    represented with an array of DenseI64ArrayAttr attribute.
+    represented by an array of DenseI64ArrayAttr attribute. The reassociation
+    maps are applied to the operand shape to obtain the result shape.
 
-    The verification rule is that the reassociation maps are applied to the
-    operand tensor with the higher rank to obtain the result tensor with the
-    smaller rank.
 
-    The result tensor type of a reshape can be zero-ranked if the operand
-    tensor type is statically shaped with all dimensions being unit extent. In
-    such case the reassociation map is empty.
-
-    Examples:
+    Example:
 
     ```mlir
     // Dimension collapse (i, j) -> i' and k -> k'
@@ -1841,7 +1832,7 @@ def Tensor_PackOp : Tensor_RelayoutOp<"pack", [
     and optionally transposes the tiled source tensor dimensions.
 
     `inner_dims_pos` (mandatory) specifies `k` source tensor dimensions that are
-    being tiled, where `0 < k <= n`. The order of the dimensions matters: 
+    being tiled, where `0 < k <= n`. The order of the dimensions matters:
      - The tiled dimensions (of size `inner_tiles`) are added to the end of the result
     tensor in the order in which they appear in `inner_dims_pos`.
      - `inner_dims_pos[i]` specifies the source tensor dimension tiled by

mlir/include/mlir/Dialect/Utils/ReshapeOpsUtils.h

@@ -85,16 +85,21 @@ bool isReassociationValid(ArrayRef<AffineMap> reassociation,
 template <typename ReshapeOpTy, typename InverseReshapeOpTy>
 static OpFoldResult foldReshapeOp(ReshapeOpTy reshapeOp,
                                   ArrayRef<Attribute> operands) {
-  // Fold producer-consumer reshape ops that where the operand type of the
+
+  if (reshapeOp.getSrcType() == reshapeOp.getType())
+    return reshapeOp.getSrc();
+
+  // Fold producer-consumer reshape ops where the operand type of the
   // producer is same as the return type of the consumer.
   auto reshapeSrcOp =
       reshapeOp.getSrc().template getDefiningOp<InverseReshapeOpTy>();
   if (reshapeSrcOp && reshapeSrcOp.getSrcType() == reshapeOp.getResultType())
     return reshapeSrcOp.getSrc();
+
   // Reshape of a constant can be replaced with a new constant.
-  if (auto elements = dyn_cast_or_null<DenseElementsAttr>(operands.front())) {
+  if (auto elements = dyn_cast_or_null<DenseElementsAttr>(operands.front()))
     return elements.reshape(cast<ShapedType>(reshapeOp.getResult().getType()));
-  }
+
   return nullptr;
 }
 
@@ -103,41 +108,36 @@ static OpFoldResult foldReshapeOp(ReshapeOpTy reshapeOp,
 template <typename Op, typename T>
 static LogicalResult verifyReshapeLikeTypes(Op op, T expandedType,
                                             T collapsedType, bool isExpansion) {
+
   unsigned expandedRank = expandedType.getRank();
   unsigned collapsedRank = collapsedType.getRank();
   if (expandedRank < collapsedRank)
-    return op.emitOpError("expected the type ")
-           << expandedType
-           << " to have higher rank than the type = " << collapsedType;
-  if (expandedRank == 0)
-    return op.emitOpError("expected non-zero memref ranks");
-  if (expandedRank == collapsedRank)
-    return op.emitOpError("expected to collapse or expand dims");
-
-  if (collapsedRank == 0) {
-    // If collapsed rank is 0, then expanded type must be static shaped and of
-    // sizes 1.
-    if (llvm::any_of(expandedType.getShape(),
-                     [](int64_t dim) -> bool { return dim != 1; }))
-      return op.emitOpError("invalid to reshape tensor/memref with non-unit "
-                            "extent dimensions to zero-rank tensor/memref");
-    return success();
-  }
+    return op.emitOpError("expected the expanded type, ")
+           << expandedType << " to have a higher (or same) rank "
+           << "than the collapsed type, " << collapsedType << '.';
+
   if (collapsedRank != op.getReassociation().size())
-    return op.emitOpError("expected rank of the collapsed type(")
-           << collapsedRank << ") to be the number of reassociation maps("
-           << op.getReassociation().size() << ")";
+    return op.emitOpError("expected collapsed rank (")
+           << collapsedRank << ") to equal the number of reassociation maps ("
+           << op.getReassociation().size() << ").";
+
   auto maps = op.getReassociationMaps();
   for (auto it : llvm::enumerate(maps))
     if (it.value().getNumDims() != expandedRank)
       return op.emitOpError("expected reassociation map #")
-             << it.index() << " of same rank as expanded memref("
-             << expandedRank << "), but got " << it.value().getNumDims();
+             << it.index() << " to have size equal to the expanded rank ("
+             << expandedRank << "), but it is  " << it.value().getNumDims()
+             << '.';
+
   int invalidIdx = 0;
   if (!isReassociationValid(maps, &invalidIdx))
     return op.emitOpError("expected reassociation map #")
-           << invalidIdx << " to be valid and contiguous";
-  return verifyReshapeLikeShapes(op, collapsedType, expandedType, isExpansion);
+           << invalidIdx << " to be valid and contiguous.";
+
+  return reshapeLikeShapesAreCompatible(
+      [&](const Twine &msg) { return op->emitOpError(msg); },
+      collapsedType.getShape(), expandedType.getShape(),
+      op.getReassociationIndices(), isExpansion);
 }
 
 /// Verify that shapes of the reshaped types using following rules
@@ -153,16 +153,6 @@ LogicalResult reshapeLikeShapesAreCompatible(
     ArrayRef<int64_t> collapsedShape, ArrayRef<int64_t> expandedShape,
     ArrayRef<ReassociationIndices> reassociationMaps, bool isExpandingReshape);
 
-template <typename OpTy>
-static LogicalResult verifyReshapeLikeShapes(OpTy op, ShapedType collapsedType,
-                                             ShapedType expandedType,
-                                             bool isExpandingReshape) {
-  return reshapeLikeShapesAreCompatible(
-      [&](const Twine &msg) { return op->emitOpError(msg); },
-      collapsedType.getShape(), expandedType.getShape(),
-      op.getReassociationIndices(), isExpandingReshape);
-}
-
 /// Returns true iff the type is a MemRefType and has a non-identity layout.
 bool hasNonIdentityLayout(Type type);
 

mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp

@@ -2224,9 +2224,13 @@ LogicalResult ExpandShapeOp::verify() {
   MemRefType srcType = getSrcType();
   MemRefType resultType = getResultType();
 
-  if (srcType.getRank() >= resultType.getRank())
-    return emitOpError("expected rank expansion, but found source rank ")
-           << srcType.getRank() << " >= result rank " << resultType.getRank();
+  if (srcType.getRank() > resultType.getRank()) {
+    auto r0 = srcType.getRank();
+    auto r1 = resultType.getRank();
+    return emitOpError("has source rank ")
+           << r0 << " and result rank " << r1 << ". This is not an expansion ("
+           << r0 << " > " << r1 << ").";
+  }
 
   // Verify result shape.
   if (failed(verifyCollapsedShape(getOperation(), srcType.getShape(),
@@ -2378,9 +2382,13 @@ LogicalResult CollapseShapeOp::verify() {
   MemRefType srcType = getSrcType();
   MemRefType resultType = getResultType();
 
-  if (srcType.getRank() <= resultType.getRank())
-    return emitOpError("expected rank reduction, but found source rank ")
-           << srcType.getRank() << " <= result rank " << resultType.getRank();
+  if (srcType.getRank() < resultType.getRank()) {
+    auto r0 = srcType.getRank();
+    auto r1 = resultType.getRank();
+    return emitOpError("has source rank ")
+           << r0 << " and result rank " << r1 << ". This is not a collapse ("
+           << r0 << " < " << r1 << ").";
+  }
 
   // Verify result shape.
   if (failed(verifyCollapsedShape(getOperation(), resultType.getShape(),

mlir/lib/Dialect/Tensor/IR/TensorOps.cpp

@@ -1656,22 +1656,10 @@ static LogicalResult verifyTensorReshapeOp(TensorReshapeOp op,
 }
 
 LogicalResult ExpandShapeOp::verify() {
-  auto srcType = getSrcType();
-  auto resultType = getResultType();
-  if (srcType.getRank() >= resultType.getRank())
-    return emitOpError("expected rank expansion, but found source rank ")
-           << srcType.getRank() << " >= result rank " << resultType.getRank();
-
   return verifyTensorReshapeOp(*this, getResultType(), getSrcType());
 }
 
 LogicalResult CollapseShapeOp::verify() {
-  auto srcType = getSrcType();
-  auto resultType = getResultType();
-  if (srcType.getRank() <= resultType.getRank())
-    return emitOpError("expected rank reduction, but found source rank ")
-           << srcType.getRank() << " <= result rank " << resultType.getRank();
-
   return verifyTensorReshapeOp(*this, getSrcType(), getResultType());
 }
 

mlir/test/Dialect/MemRef/canonicalize.mlir

@@ -1,5 +1,34 @@
 // RUN: mlir-opt %s -canonicalize="test-convergence" --split-input-file -allow-unregistered-dialect | FileCheck %s
 
+
+// CHECK-LABEL: collapse_shape_identity_fold
+// CHECK-NEXT: return
+func.func @collapse_shape_identity_fold(%arg0 : memref<5xi8>) -> memref<5xi8> {
+  %0 = memref.collapse_shape %arg0 [[0]] : memref<5xi8> into memref<5xi8>
+  return %0 : memref<5xi8>
+}
+
+// -----
+
+// CHECK-LABEL: expand_shape_identity_fold
+// CHECK-NEXT: return
+func.func @expand_shape_identity_fold(%arg0 : memref<5x4xi8>) -> memref<5x4xi8> {
+  %0 = memref.expand_shape %arg0 [[0], [1]] : memref<5x4xi8> into memref<5x4xi8>
+  return %0 : memref<5x4xi8>
+}
+
+// -----
+
+// CHECK-LABEL: collapse_expand_rank0_cancel
+// CHECK-NEXT: return
+func.func @collapse_expand_rank0_cancel(%arg0 : memref<1x1xi8>) -> memref<1x1xi8> {
+  %0 = memref.collapse_shape %arg0 [] : memref<1x1xi8> into memref<i8>
+  %1 = memref.expand_shape %0 [] : memref<i8> into memref<1x1xi8>
+  return %1 : memref<1x1xi8>
+}
+
+// -----
+
 // CHECK-LABEL: func @subview_of_size_memcast
 //  CHECK-SAME:   %[[ARG0:.[a-z0-9A-Z_]+]]: memref<4x6x16x32xi8>
 //       CHECK:   %[[S:.+]] = memref.subview %[[ARG0]][0, 1, 0, 0] [1, 1, 16, 32] [1, 1, 1, 1] : memref<4x6x16x32xi8> to memref<16x32xi8, strided{{.*}}>

mlir/test/Dialect/MemRef/invalid.mlir

@@ -415,20 +415,6 @@ func.func @collapse_shape_out_of_bounds(%arg0: memref<?x?xf32>) {
 
 // -----
 
-func.func @expand_shape_invalid_ranks(%arg0: memref<?x?xf32>) {
-  // expected-error @+1 {{op expected rank expansion, but found source rank 2 >= result rank 2}}
-  %0 = memref.expand_shape %arg0 [[0], [1]] : memref<?x?xf32> into memref<?x?xf32>
-}
-
-// -----
-
-func.func @collapse_shape_invalid_ranks(%arg0: memref<?x?xf32>) {
-  // expected-error @+1 {{op expected rank reduction, but found source rank 2 <= result rank 2}}
-  %0 = memref.collapse_shape %arg0 [[0], [1]] : memref<?x?xf32> into memref<?x?xf32>
-}
-
-// -----
-
 func.func @expand_shape_out_of_bounds(%arg0: memref<?xf32>) {
   // expected-error @+1 {{op reassociation index 2 is out of bounds}}
   %0 = memref.expand_shape %arg0 [[0, 1, 2]] : memref<?xf32> into memref<4x?xf32>
@@ -462,6 +448,34 @@ func.func @collapse_shape_invalid_reassociation(%arg0: memref<?x?x?xf32>) {
 
 // -----
 
+// An (invalid) attempt at using collapse_shape to increase the rank might look
+// like this. Verify that a sensible error is emitted in this case.
+func.func @collapse_shape_invalid_reassociation_expansion(%arg0: memref<?xf32>) {
+  // expected-error @+1 {{'memref.collapse_shape' op has source rank 1 and result rank 2. This is not a collapse (1 < 2)}}
+  %0 = memref.collapse_shape %arg0 [[0], [0]] :
+    memref<?xf32> into memref<?x?xf32>
+}
+
+// -----
+
+// An (invalid) attempt at using expand_shape to reduce the rank might look
+// like this. Verify that a sensible error is emitted in this case.
+func.func @expand_shape_invalid_reassociation(%arg0: memref<2x3x1xf32>) {
+  // expected-error @+1 {{'memref.expand_shape' op has source rank 3 and result rank 2. This is not an expansion (3 > 2)}}
+  %0 = memref.expand_shape %arg0 [[0], [1], [1]] :
+    memref<2x3x1xf32> into memref<2x3xf32>
+}
+
+// -----
+
+func.func @collapse_shape_invalid_reassociation_expansion(%arg0: memref<?x?xf32>) {
+  // expected-error @+1 {{reassociation indices must be contiguous}}
+  %0 = memref.collapse_shape %arg0 [[1], [0]] :
+    memref<?x?xf32> into memref<?x?xf32>
+}
+
+// -----
+
 func.func @collapse_shape_reshaping_non_contiguous(
     %arg0: memref<3x4x5xf32, strided<[270, 50, 10], offset: 0>>) {
   // expected-error @+1 {{invalid source layout map or collapsing non-contiguous dims}}

mlir/test/Dialect/Tensor/canonicalize.mlir

@@ -1,5 +1,42 @@
 // RUN: mlir-opt %s -split-input-file -canonicalize="test-convergence" | FileCheck %s
 
+
+// CHECK-LABEL: expand_shape_identity_fold
+// CHECK-NEXT: return
+func.func @expand_shape_identity_fold(%arg0 : tensor<5xf32>) -> tensor<5xf32> {
+  %0 = tensor.expand_shape %arg0 [[0]] : tensor<5xf32> into tensor<5xf32>
+  return %0 : tensor<5xf32>
+}
+
+// -----
+
+// CHECK-LABEL: expand_shape_rank0_identity_fold
+// CHECK-NEXT: return
+func.func @expand_shape_rank0_identity_fold(%arg0 : tensor<f32>) -> tensor<f32> {
+  %0 = tensor.expand_shape %arg0 [] : tensor<f32> into tensor<f32>
+  return %0 : tensor<f32>
+}
+
+// -----
+
+// CHECK-LABEL: collapse_shape_identity_fold
+// CHECK-NEXT: return
+func.func @collapse_shape_identity_fold(%arg0 : tensor<5x4xf32>) -> tensor<5x4xf32> {
+  %0 = tensor.collapse_shape %arg0 [[0], [1]] : tensor<5x4xf32> into tensor<5x4xf32>
+  return %0 : tensor<5x4xf32>
+}
+
+// -----
+
+// CHECK-LABEL: collapse_shape_rank0_identity_fold
+// CHECK-NEXT: return
+func.func @collapse_shape_rank0_identity_fold(%arg0 : tensor<f32>) -> tensor<f32> {
+  %0 = tensor.collapse_shape %arg0 [] : tensor<f32> into tensor<f32>
+  return %0 : tensor<f32>
+}
+
+// -----
+
 // CHECK-LABEL: @tensor_bitcast_chain_ok
 // CHECK-SAME: %[[IN:.*]]: tensor<2xi32>
 func.func @tensor_bitcast_chain_ok(%input: tensor<2xi32>) -> tensor<2xf32> {
@@ -2092,7 +2129,7 @@ func.func @unpack_pack(%t: tensor<128x128xf32>) -> tensor<128x128xf32> {
 
 // Chain: NC -> NCnc -> NCnc -> NC
 // CHECK: func.func @unpack_pack(
-// CHECK-SAME: %[[T:.+]]: tensor<128x128xf32>, 
+// CHECK-SAME: %[[T:.+]]: tensor<128x128xf32>,
 // CHECK: return %[[T]] : tensor<128x128xf32>
 func.func @unpack_pack(%t: tensor<128x128xf32>, %tile1: index, %tile2: index) -> tensor<128x128xf32> {
   %tensor_empty = tensor.empty(%tile1, %tile2) : tensor<16x16x?x?xf32>

mlir/test/Dialect/Tensor/invalid.mlir

@@ -343,20 +343,6 @@ func.func @illegal_collapsing_reshape_mixed_tensor_2(%arg0 : tensor<?x4x5xf32>)
 
 // -----
 
-func.func @expand_shape_invalid_ranks(%arg0: tensor<?x?xf32>) {
-  // expected-error @+1 {{op expected rank expansion, but found source rank 2 >= result rank 2}}
-  %0 = tensor.expand_shape %arg0 [[0], [1]] : tensor<?x?xf32> into tensor<?x?xf32>
-}
-
-// -----
-
-func.func @collapse_shape_invalid_ranks(%arg0: tensor<?x?xf32>) {
-  // expected-error @+1 {{op expected rank reduction, but found source rank 2 <= result rank 2}}
-  %0 = tensor.collapse_shape %arg0 [[0], [1]] : tensor<?x?xf32> into tensor<?x?xf32>
-}
-
-// -----
-
 func.func @rank(%0: f32) {
   // expected-error@+1 {{'tensor.rank' op operand #0 must be tensor of any type values}}
   "tensor.rank"(%0): (f32)->index