This is almost entirely mechanical. Differential Revision: https://reviews.llvm.org/D93357
20 lines
880 B
MLIR
20 lines
880 B
MLIR
// RUN: mlir-opt %s -convert-elementwise-to-linalg -std-bufferize -tensor-constant-bufferize -linalg-bufferize -tensor-bufferize -func-bufferize -convert-linalg-to-loops -convert-linalg-to-llvm -convert-std-to-llvm | \
|
|
// RUN: mlir-cpu-runner -e main -entry-point-result=void \
|
|
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
|
|
// RUN: | FileCheck %s
|
|
|
|
func @main() {
|
|
%a = constant dense<[1.0, 2.0, 3.0]> : tensor<3xf32>
|
|
%b = constant dense<[10.0, 20.0, 30.0]> : tensor<3xf32>
|
|
|
|
%addf = addf %a, %b : tensor<3xf32>
|
|
%addf_unranked = tensor.cast %addf : tensor<3xf32> to tensor<*xf32>
|
|
call @print_memref_f32(%addf_unranked) : (tensor<*xf32>) -> ()
|
|
// CHECK: Unranked Memref base@ = {{.*}} rank = 1 offset = 0 sizes = [3] strides = [1] data =
|
|
// CHECK-NEXT: [11, 22, 33]
|
|
|
|
return
|
|
}
|
|
|
|
func private @print_memref_f32(%ptr : tensor<*xf32>)
|