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// UNSUPPORTED: asan
// RUN: mlir-opt %s -test-transform-dialect-erase-schedule -linalg-bufferize -arith-bufferize \
// RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -buffer-deallocation -convert-linalg-to-loops -convert-scf-to-cf \
// RUN: -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils \
// RUN: | FileCheck %s
// RUN: mlir-opt %s -test-transform-dialect-interpreter -test-transform-dialect-erase-schedule -linalg-bufferize \
// RUN: -scf-bufferize -arith-bufferize -tensor-bufferize \
// RUN: -func-bufferize \
// RUN: -finalizing-bufferize -convert-linalg-to-loops -convert-scf-to-cf -convert-scf-to-cf \
// RUN: -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils \
// RUN: | FileCheck %s
func.func @main() {
%A = arith.constant dense<[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]> : tensor<2x3xf32>
%B = arith.constant dense<[[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0],
[9.0, 10.0, 11.0, 12.0]]> : tensor<3x4xf32>
%C = arith.constant dense<1000.0> : tensor<2x4xf32>
%D = linalg.matmul ins(%A, %B: tensor<2x3xf32>, tensor<3x4xf32>)
outs(%C: tensor<2x4xf32>) -> tensor<2x4xf32>
%unranked = tensor.cast %D : tensor<2x4xf32> to tensor<*xf32>
call @printMemrefF32(%unranked) : (tensor<*xf32>) -> ()
// CHECK: Unranked Memref base@ = {{0x[-9a-f]*}}
// CHECK-SAME: rank = 2 offset = 0 sizes = [2, 4] strides = [4, 1] data =
// CHECK-NEXT: [1038, 1044, 1050, 1056]
// CHECK-NEXT: [1083, 1098, 1113, 1128]
return
}
transform.sequence failures(propagate) {
^bb0(%arg1: !transform.any_op):
%0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
%1, %loops:3 = transform.structured.tile %0 [1, 2, 3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
}
func.func private @printMemrefF32(%ptr : tensor<*xf32>)
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