[Cleanup] Delete tiling tensor.pad test from LinalgExt. (#15902)
This is covered by upstream tests. Although they are tiling with
different tile sizes, but the test coverage is the same. We do not add
such file to LinalgExt/.
The upstream test can be found at
https://github.com/llvm/llvm-project/blob/215c5656449c8e817a3759d989f27ba39d711cbd/mlir/test/Dialect/Tensor/tiling.mlir#L25-L40
diff --git a/llvm-external-projects/iree-dialects/test/Dialect/iree_linalg_ext/pad_tiling.mlir b/llvm-external-projects/iree-dialects/test/Dialect/iree_linalg_ext/pad_tiling.mlir
deleted file mode 100644
index 21f7af3..0000000
--- a/llvm-external-projects/iree-dialects/test/Dialect/iree_linalg_ext/pad_tiling.mlir
+++ /dev/null
@@ -1,41 +0,0 @@
-// RUN: iree-dialects-opt --iree-linalg-ext-tile --split-input-file %s | FileCheck %s
-// XFAIL: *
-// TODO: Re-enable when upstream tensor.pad op properly implements the tiling
-// interface.
-
-func.func @pad_tensor(%arg0 : tensor<?x?xf32>, %arg1 : index, %arg2 : index,
- %arg3 : index, %arg4 : index, %arg5 : f32) -> tensor<?x?xf32> {
- %0 = tensor.pad %arg0 low[%arg1, %arg2] high[%arg3, %arg4] {
- ^bb0(%arg6 : index, %arg7 : index):
- tensor.yield %arg5 : f32
- } {__internal_iree_linalg_transform__ = "tiling_input"}
- : tensor<?x?xf32> to tensor<?x?xf32>
- return %0 : tensor<?x?xf32>
-}
-// CHECK-DAG: #[[MAP0:.+]] = affine_map<()[s0, s1, s2] -> (s2 + s0 + s1)>
-// CHECK: func.func @pad_tensor
-// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor<?x?xf32>
-// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: index
-// CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: index
-// CHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]]: index
-// CHECK-SAME: %[[ARG4:[a-zA-Z0-9]+]]: index
-// CHECK-SAME: %[[ARG5:[a-zA-Z0-9]+]]: f32
-// CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index
-// CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index
-// CHECK-DAG: %[[C10:.+]] = arith.constant 10 : index
-// CHECK-DAG: %[[C20:.+]] = arith.constant 20 : index
-// CHECK-DAG: %[[INIT:.+]] = tensor.empty()
-// CHECK: %[[D0:.+]] = tensor.dim %[[ARG0]], %[[C0]]
-// CHECK: %[[UBY:.+]] = affine.apply #[[MAP0]]()[%[[ARG1]], %[[ARG3]], %[[D0]]]
-// CHECK: %[[D1:.+]] = tensor.dim %[[ARG0]], %[[C1]]
-// CHECK: %[[UBX:.+]] = affine.apply #[[MAP0]]()[%[[ARG2]], %[[ARG4]], %[[D1]]]
-// CHECK: %[[RESULT:.+]] = scf.for %[[IV0:[a-zA-Z0-9]+]] = %[[C0]] to %[[UBY]] step %[[C10]]
-// CHECK-SAME: iter_args(%[[ARG7:.+]] = %[[INIT]])
-// CHECK: %[[YIELD:.+]] = scf.for %[[IV1:[a-zA-Z0-9]+]] = %[[C0]] to %[[UBX]] step %[[C20]]
-// CHECK-SAME: iter_args(%[[ARG9:.+]] = %[[ARG7]])
-// CHECK: %[[PAD_TILE:.+]] = scf.if
-// CHECK: %[[INSERT:.+]] = tensor.insert_slice %[[PAD_TILE]] into %[[ARG9]]
-// CHECK-SAME: [%[[IV0]], %[[IV1]]]
-// CHECK: scf.yield %[[INSERT]]
-// CHECK: scf.yield %[[YIELD]]
-// CHECK: return %[[RESULT]]
