[mlir][Vector] Update patterns for flattening vector.xfer Ops

Updates "flatten vector" patterns to support more cases, namely Ops that
read/write vectors with leading unit dims. For example:

```mlir
%0 = vector.transfer_read %arg0[%c0, %c0, %c0, %c0] ... :
  memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>, vector<1x1x2x2xi8>
```

Currently, this `vector.transfer_read` would not be flattened. With this
change, it will be transformed as follows:
```mlir
%collapse_shape = memref.collapse_shape %arg0 [[0, 1, 2, 3]] :
  memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>
  into memref<120xi8, strided<[1], offset: ?>>
%0 = vector.transfer_read %collapse_shape[%c0] ... :
  memref<120xi8, strided<[1], offset: ?>>, vector<4xi8>
%1 = vector.shape_cast %0 : vector<4xi8> to vector<1x1x2x2xi8>
```

`hasMatchingInnerContigousShape` is generalised and renamed as
`isContiguousSlice` to better match the updated functionality. A few
test names are updated to better highlight what case is being exercised.

Author: banach-space

mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp

@@ -487,26 +487,75 @@ class TransferWriteDropUnitDimsPattern
 
 } // namespace
 
-/// Return true if the memref type has its inner dimension matching the given
-/// shape. Otherwise return false.
-static int64_t hasMatchingInnerContigousShape(MemRefType memrefType,
-                                              ArrayRef<int64_t> targetShape) {
-  auto shape = memrefType.getShape();
-  SmallVector<int64_t> strides;
+/// Return true if `vectorType` is a contiguous slice of `memrefType`.
+///
+/// Compares `vectorType` against the trailing dimensions (*) of `memrefType`
+/// to check whether `vectorType` is a contiguous slice of `memrefType`.
+///
+/// There are two cases:
+///
+/// 1. The trailing dimensions of `memrefType` match the dimensions of
+/// `vectorType` excluding the front dim (the leading dim of `vectorType` does
+/// not matter in this case):
+///
+///   vector<2x4x3x2xi32> vs memref<5x4x3x2xi32> (contiguous slice)
+///   vector<2x4x2x2xi32> vs memref<5x4x3x2xi32> (non-contiguous slice)
+///
+/// 2. The trailing dimension of `memrefType` match the trailing dimensions of
+/// `vectorType` (i.e. at least 2 leading dims of `vectorType` don't match). The
+/// first dim of `vectorType` that does not match can be arbitrary, but the
+/// remaining leading dims have to be 1:
+///
+///   vector<1x1x2x2xi32> vs memref<5x4x3x2xi32> (contiguous slice)
+///   vector<2x1x2x2xi32> vs memref<5x4x3x2xi32> (non-contiguous slice)
+///
+/// In both cases `memrefType` has to be contiguous (this is checked by looking
+/// at strides).
+///
+/// (*) Only relevant in cases when the rank(vectorType) < rank(memrefType)
+/// TODO: Update
+static bool isContiguousSlice(MemRefType memrefType, VectorType vectorType) {
+
+  ArrayRef<int64_t> targetShape = vectorType.getShape();
+  auto targetShapeTrailingDims = targetShape.drop_front(1);
+
+  // Not used
   int64_t offset;
+  SmallVector<int64_t> strides;
   if (!succeeded(getStridesAndOffset(memrefType, strides, offset)))
     return false;
+
+  // Non-unit stride in the trailing dimension means that this is memref is
+  // not contiguous.
   if (strides.back() != 1)
     return false;
-  strides.pop_back();
+
+  // Do all but the leading dim of `vectorType` and the trailing dims of
+  // `memrefType` match?
+  bool allTrailingDimsMatch = true;
+
+  // The trailing dimension of `memrefType` after collapsing/flattening the
+  // current dim. This will be a product of the leading dims, hence initialising
+  // to 1.
   int64_t flatDim = 1;
-  for (auto [targetDim, memrefDim, memrefStride] :
-       llvm::reverse(llvm::zip(targetShape, shape, strides))) {
+  strides.pop_back();
+  for (auto [targetDim, memrefDim, memrefStride] : llvm::reverse(llvm::zip(
+           targetShapeTrailingDims, memrefType.getShape(), strides))) {
     flatDim *= memrefDim;
-    if (flatDim != memrefStride || targetDim != memrefDim)
+    // If the memref stride does not match the flattened dim, then this is
+    // memref is not contiguous.
+    if (flatDim != memrefStride)
+      return false;
+
+    // If a non-matching dim was found, then the remaining dims of `VectorType`
+    // should be 1.
+    if (!allTrailingDimsMatch && (targetDim != 1))
       return false;
+
+    allTrailingDimsMatch = (targetDim == memrefDim);
   }
-  return true;
+
+  return allTrailingDimsMatch ? true : (targetShape[0] == 1);
 }
 
 /// Creates a memref.collapse_shape collapsing all inner dimensions of the
@@ -568,9 +617,7 @@ class FlattenContiguousRowMajorTransferReadPattern
     if (vectorType.getRank() <= 1)
       // Already 0D/1D, nothing to do.
       return failure();
-    if (!hasMatchingInnerContigousShape(
-            sourceType,
-            vectorType.getShape().take_back(vectorType.getRank() - 1)))
+    if (!isContiguousSlice(sourceType, vectorType))
       return failure();
     int64_t firstContiguousInnerDim =
         sourceType.getRank() - vectorType.getRank();
@@ -628,9 +675,7 @@ class FlattenContiguousRowMajorTransferWritePattern
     if (vectorType.getRank() <= 1)
       // Already 0D/1D, nothing to do.
       return failure();
-    if (!hasMatchingInnerContigousShape(
-            sourceType,
-            vectorType.getShape().take_back(vectorType.getRank() - 1)))
+    if (!isContiguousSlice(sourceType, vectorType))
       return failure();
     int64_t firstContiguousInnerDim =
         sourceType.getRank() - vectorType.getRank();

mlir/test/Dialect/Vector/vector-transfer-flatten.mlir

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s -test-vector-transfer-flatten-patterns -split-input-file | FileCheck %s
 
-func.func @transfer_read_flattenable_with_offset(
+func.func @transfer_read_dims_match_contiguous(
       %arg : memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>) -> vector<5x4x3x2xi8> {
     %c0 = arith.constant 0 : index
     %cst = arith.constant 0 : i8
@@ -9,7 +9,7 @@ func.func @transfer_read_flattenable_with_offset(
     return %v : vector<5x4x3x2xi8>
 }
 
-// CHECK-LABEL: func @transfer_read_flattenable_with_offset
+// CHECK-LABEL: func @transfer_read_dims_match_contiguous
 // CHECK-SAME:      %[[ARG:[0-9a-zA-Z]+]]: memref<5x4x3x2xi8
 // CHECK:         %[[COLLAPSED:.+]] = memref.collapse_shape %[[ARG]] {{.}}[0, 1, 2, 3]
 // CHECK:         %[[READ1D:.+]] = vector.transfer_read %[[COLLAPSED]]
@@ -18,15 +18,52 @@ func.func @transfer_read_flattenable_with_offset(
 
 // -----
 
-func.func @transfer_write_flattenable_with_offset(
+// The shape of the memref and the vector don't match, but the vector is a
+// contiguous subset of the memref, so "flattenable".
+
+func.func @transfer_read_dims_mismatch_contiguous(
+      %arg : memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>) -> vector<1x1x2x2xi8> {
+    %c0 = arith.constant 0 : index
+    %cst = arith.constant 0 : i8
+    %v = vector.transfer_read %arg[%c0, %c0, %c0, %c0], %cst :
+      memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>, vector<1x1x2x2xi8>
+    return %v : vector<1x1x2x2xi8>
+}
+
+// CHECK-LABEL:   func.func @transfer_read_dims_mismatch_contiguous(
+// CHECK-SAME:                                           %[[VAL_0:.*]]: memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>) -> vector<1x1x2x2xi8> {
+// CHECK:           %[[VAL_1:.*]] = arith.constant 0 : i8
+// CHECK:           %[[VAL_2:.*]] = arith.constant 0 : index
+// CHECK:           %[[VAL_3:.*]] = memref.collapse_shape %[[VAL_0]] {{\[\[}}0, 1, 2, 3]] : memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>> into memref<120xi8, strided<[1], offset: ?>>
+// CHECK:           %[[VAL_4:.*]] = vector.transfer_read %[[VAL_3]]{{\[}}%[[VAL_2]]], %[[VAL_1]] {in_bounds = [true]} : memref<120xi8, strided<[1], offset: ?>>, vector<4xi8>
+// CHECK:           %[[VAL_5:.*]] = vector.shape_cast %[[VAL_4]] : vector<4xi8> to vector<1x1x2x2xi8>
+// CHECK:           return %[[VAL_5]] : vector<1x1x2x2xi8>
+
+// -----
+
+func.func @transfer_read_dims_mismatch_contiguous(
+    %arg : memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>) -> vector<2x1x2x2xi8> {
+    %c0 = arith.constant 0 : index
+    %cst = arith.constant 0 : i8
+    %v = vector.transfer_read %arg[%c0, %c0, %c0, %c0], %cst :
+      memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>, vector<2x1x2x2xi8>
+    return %v : vector<2x1x2x2xi8>
+}
+
+// CHECK-NOT: memref.collapse_shape
+// CHECK-NOT: vector.shape_cast
+
+// -----
+
+func.func @transfer_write_dims_match_contiguous(
       %arg : memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>, %vec : vector<5x4x3x2xi8>) {
     %c0 = arith.constant 0 : index
     vector.transfer_write %vec, %arg [%c0, %c0, %c0, %c0] :
       vector<5x4x3x2xi8>, memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>
     return
 }
 
-// CHECK-LABEL: func @transfer_write_flattenable_with_offset
+// CHECK-LABEL: func @transfer_write_dims_match_contiguous
 // CHECK-SAME:      %[[ARG:[0-9a-zA-Z]+]]: memref<5x4x3x2xi8
 // CHECK-SAME:      %[[VEC:[0-9a-zA-Z]+]]: vector<5x4x3x2xi8>
 // CHECK-DAG:     %[[COLLAPSED:.+]] = memref.collapse_shape %[[ARG]] {{.}}[0, 1, 2, 3]{{.}} : memref<5x4x3x2xi8, {{.+}}> into memref<120xi8, {{.+}}>
@@ -35,16 +72,46 @@ func.func @transfer_write_flattenable_with_offset(
 
 // -----
 
+func.func @transfer_write_dims_mismatch_contiguous(
+      %arg : memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>, %vec : vector<1x1x2x2xi8>) {
+    %c0 = arith.constant 0 : index
+    vector.transfer_write %vec, %arg [%c0, %c0, %c0, %c0] :
+      vector<1x1x2x2xi8>, memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>
+    return
+}
+
+// CHECK-LABEL:   func.func @transfer_write_dims_mismatch_contiguous
+// CHECK-SAME:                                            %[[VAL_0:.*]]: memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>,
+// CHECK-SAME:                                            %[[VAL_1:.*]]: vector<1x1x2x2xi8>) {
+// CHECK:           %[[VAL_2:.*]] = arith.constant 0 : index
+// CHECK:           %[[VAL_3:.*]] = memref.collapse_shape %[[VAL_0]] {{\[\[}}0, 1, 2, 3]] : memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>> into memref<120xi8, strided<[1], offset: ?>>
+// CHECK:           %[[VAL_4:.*]] = vector.shape_cast %[[VAL_1]] : vector<1x1x2x2xi8> to vector<4xi8>
+// CHECK:           vector.transfer_write %[[VAL_4]], %[[VAL_3]]{{\[}}%[[VAL_2]]] {in_bounds = [true]} : vector<4xi8>, memref<120xi8, strided<[1], offset: ?>>
+// CHECK:           return
+// CHECK:         }
+
+// -----
+
+func.func @transfer_write_dims_mismatch_non_contiguous(
+      %arg : memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>, %vec : vector<2x1x2x2xi8>) {
+    %c0 = arith.constant 0 : index
+    vector.transfer_write %vec, %arg [%c0, %c0, %c0, %c0] :
+      vector<2x1x2x2xi8>, memref<5x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>
+    return
+}
+
+// CHECK-NOT: memref.collapse_shape
+// CHECK-NOT: vector.shape_cast
+
+// -----
+
 func.func @transfer_write_0d(%arg : memref<i8>, %vec : vector<i8>) {
       vector.transfer_write %vec, %arg[] : vector<i8>, memref<i8>
       return
 }
 
-// CHECK-LABEL: func @transfer_write_0d
-// CHECK-SAME:       %[[ARG:.+]]: memref<i8>
-// CHECK-SAME:       %[[VEC:.+]]: vector<i8>
-// CHECK:          vector.transfer_write %[[VEC]], %[[ARG]][] : vector<i8>, memref<i8>
-// CHECK:          return
+// CHECK-NOT: memref.collapse_shape
+// CHECK-NOT: vector.shape_cast
 
 // -----
 
@@ -54,11 +121,8 @@ func.func @transfer_read_0d(%arg : memref<i8>) -> vector<i8> {
       return %0 : vector<i8>
 }
 
-// CHECK-LABEL: func @transfer_read_0d
-// CHECK-SAME:       %[[ARG:.+]]: memref<i8>
-// CHECK:            %[[CST:.+]] = arith.constant 0 : i8
-// CHECK:            %[[READ:.+]] = vector.transfer_read %[[ARG]][], %[[CST]] : memref<i8>
-// CHECK:            return %[[READ]]
+// CHECK-NOT: memref.collapse_shape
+// CHECK-NOT: vector.shape_cast
 
 // -----