[mlir][vector][NFC] Make function name more meaningful in lit tests.

[hanhanW]

It also moves the test near other similar test cases.

[llvmbot]

@llvm/pr-subscribers-mlir

@llvm/pr-subscribers-mlir-vector

Author: Han-Chung Wang (hanhanW)

Changes

It also moves the test near other similar test cases.

---

Full diff: https://github.com/llvm/llvm-project/pull/94538.diff

1 Files Affected:

• (modified) mlir/test/Dialect/Vector/vector-transfer-flatten.mlir (+38-37)

diff --git a/mlir/test/Dialect/Vector/vector-transfer-flatten.mlir b/mlir/test/Dialect/Vector/vector-transfer-flatten.mlir
index 65bf0b9335d28..de45a530db9a6 100644
--- a/mlir/test/Dialect/Vector/vector-transfer-flatten.mlir
+++ b/mlir/test/Dialect/Vector/vector-transfer-flatten.mlir
@@ -102,6 +102,25 @@ func.func @transfer_read_dims_mismatch_non_zero_indices(
 
 // -----
 
+func.func @transfer_read_dims_mismatch_contiguous_non_zero_idx(
+    %subview : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>>,
+    %idx0 : index, %idx1 : index) -> vector<2x2xf32> {
+  %c0 = arith.constant 0 : index
+  %cst_1 = arith.constant 0.000000e+00 : f32
+  %8 = vector.transfer_read %subview[%c0, %idx0, %idx1, %c0], %cst_1 {in_bounds = [true, true]} : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>>, vector<2x2xf32>
+  return %8 : vector<2x2xf32>
+}
+
+//       CHECK:  #[[$MAP:.+]] = affine_map<()[s0] -> (s0 * 2)>
+// CHECK-LABEL:  func.func @transfer_read_dims_mismatch_contiguous_non_zero_idx(
+//       CHECK:    %[[COLLAPSE:.+]] = memref.collapse_shape %{{.*}} {{\[}}[0], [1], [2, 3]] : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>> into memref<1x3x6xf32, strided<[40, 10, 1], offset: ?>>
+//       CHECK:    %[[APPLY:.*]] = affine.apply #[[$MAP]]()
+
+// CHECK-128B-LABEL: func @transfer_read_dims_mismatch_contiguous_non_zero_idx(
+//       CHECK-128B:   memref.collapse_shape
+
+// -----
+
 // The input memref has a dynamic trailing shape and hence is not flattened.
 // TODO: This case could be supported via memref.dim
 
@@ -212,6 +231,25 @@ func.func @transfer_write_dims_mismatch_contiguous(
 
 // -----
 
+func.func @transfer_write_dims_mismatch_contiguous_non_zero_idx(
+    %value : vector<2x2xf32>,
+    %subview : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>>,
+    %idx0 : index, %idx1 : index) {
+  %c0 = arith.constant 0 : index
+  vector.transfer_write %value, %subview[%c0, %idx0, %idx1, %c0] {in_bounds = [true, true]} : vector<2x2xf32>, memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>>
+  return
+}
+
+//       CHECK:  #[[$MAP:.+]] = affine_map<()[s0] -> (s0 * 2)>
+// CHECK-LABEL:  func.func @transfer_write_dims_mismatch_contiguous_non_zero_idx(
+//       CHECK:    %[[APPLY:.*]] = affine.apply #[[$MAP]]()
+//       CHECK:    %[[COLLAPSE:.+]] = memref.collapse_shape %{{.*}} {{\[}}[0], [1], [2, 3]] : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>> into memref<1x3x6xf32, strided<[40, 10, 1], offset: ?>>
+
+// CHECK-128B-LABEL: func @transfer_write_dims_mismatch_contiguous_non_zero_idx(
+//       CHECK-128B:   memref.collapse_shape
+
+// -----
+
 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
@@ -459,43 +497,6 @@ func.func @fold_unit_dims_entirely(%arg0 : vector<8xi32>,
 // CHECK-128B-LABEL: func @fold_unit_dims_entirely(
 //   CHECK-128B-NOT:   memref.collapse_shape
 
-
-// -----
-
-func.func @regression_non_contiguous_dim_read(%subview : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>>,
-                                              %idx0 : index, %idx1 : index) -> vector<2x2xf32> {
-  %c0 = arith.constant 0 : index
-  %cst_1 = arith.constant 0.000000e+00 : f32
-  %8 = vector.transfer_read %subview[%c0, %idx0, %idx1, %c0], %cst_1 {in_bounds = [true, true]} : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>>, vector<2x2xf32>
-  return %8 : vector<2x2xf32>
-}
-
-//       CHECK:  #[[$MAP:.+]] = affine_map<()[s0] -> (s0 * 2)>
-// CHECK-LABEL:  func.func @regression_non_contiguous_dim_read(
-//       CHECK:    %[[COLLAPSE:.+]] = memref.collapse_shape %{{.*}} {{\[}}[0], [1], [2, 3]] : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>> into memref<1x3x6xf32, strided<[40, 10, 1], offset: ?>>
-//       CHECK:    %[[APPLY:.*]] = affine.apply #[[$MAP]]()
-
-// CHECK-128B-LABEL: func @regression_non_contiguous_dim_read(
-//       CHECK-128B:   memref.collapse_shape
-
-// -----
-
-func.func @regression_non_contiguous_dim_write(%value : vector<2x2xf32>,
-                                                %subview : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>>,
-                                                %idx0 : index, %idx1 : index) {
-  %c0 = arith.constant 0 : index
-  vector.transfer_write %value, %subview[%c0, %idx0, %idx1, %c0] {in_bounds = [true, true]} : vector<2x2xf32>, memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>>
-  return
-}
-
-//       CHECK:  #[[$MAP:.+]] = affine_map<()[s0] -> (s0 * 2)>
-// CHECK-LABEL:  func.func @regression_non_contiguous_dim_write(
-//       CHECK:    %[[APPLY:.*]] = affine.apply #[[$MAP]]()
-//       CHECK:    %[[COLLAPSE:.+]] = memref.collapse_shape %{{.*}} {{\[}}[0], [1], [2, 3]] : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>> into memref<1x3x6xf32, strided<[40, 10, 1], offset: ?>>
-
-// CHECK-128B-LABEL: func @regression_non_contiguous_dim_write(
-//       CHECK-128B:   memref.collapse_shape
-
 // -----
 
 func.func @negative_out_of_bound_transfer_read(

[banach-space]

This is greatly appreciated, thank you for following-up 🙏🏻

LGTM modulo one small comment :)

[banach-space]

Suggested change

	func.func @transfer_read_dims_mismatch_contiguous_non_zero_idx(
	func.func @transfer_read_dims_mismatch_non_contiguous_non_zero_indices(

• contiguous -> non_contiguous (probably a typo?)
• idx -> indices (for consistency with transfer_read_dims_mismatch_non_zero_indices)

Similar comment for transfer_write_dims_mismatch_contiguous_non_zero_idx

[hanhanW]

Sorry, I don't follow why it is non_contiguous? I think it is writing vector<2x2xf32> to a contiguous memory?

[banach-space]

%subview : memref<1x3x3x2xf32, strided<[40, 10, 2, 1], offset: ?>>

Note the strides - the memref is not contiguous when considering all dims. However, your point is correct:

I think it is writing vector<2x2xf32> to a contiguous memory?

When only considering the trailing 2 dims, memref is indeed contiguous. IIRC, the point of this test was to verify that the pattern works even if:

• overall, memref is non-contiguous, however
• the inner dims are contiguous and that's sufficient.

Does it make sense? If yes, then we probably need a better name or a comment to explain 😅 If not, bare with me :)

[hanhanW]

I see, it makes sense to me now! Thanks for the explanation. I found that you're improving the comments in #94490. Given that it will follow the naming convention, I'll leave the "comment improvement" to the PR that you're working on. And I will update the function name in this PR.