| // RUN: mlir-opt %s -linalg-bufferize -std-bufferize \ |
| // RUN: -tensor-constant-bufferize -tensor-bufferize -func-bufferize \ |
| // RUN: -finalizing-bufferize -buffer-deallocation \ |
| // RUN: -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm -convert-memref-to-llvm -convert-std-to-llvm -reconcile-unrealized-casts | \ |
| // 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() { |
| %const = arith.constant dense<[[[1.0, 2.0, 3.0], [2.0, 3.0, 4.0]]]> : tensor<1x2x3xf32> |
| %dynamic = tensor.cast %const: tensor<1x2x3xf32> to tensor<1x?x3xf32> |
| %offset = arith.constant 2 : index |
| %cst = arith.constant 2.3 : f32 |
| %c0 = arith.constant 0 : index |
| %out = linalg.pad_tensor %dynamic low[%c0, %offset, %c0] high[%c0, %c0, %offset] { |
| ^bb0(%gen_arg1: index, %gen_arg2: index, %gen_arg3: index): // no predecessors |
| linalg.yield %cst : f32 |
| } : tensor<1x?x3xf32> to tensor<1x?x?xf32> |
| %unranked = tensor.cast %out: tensor<1x?x?xf32> to tensor<*xf32> |
| call @print_memref_f32(%unranked) : (tensor<*xf32>) -> () |
| |
| // CHECK: Unranked Memref base@ = {{0x[-9a-f]*}} |
| // CHECK-SAME: rank = 3 offset = 0 sizes = [1, 4, 5] strides = [20, 5, 1] data = |
| // CHECK-NEXT{LITERAL}: [[[2.3, 2.3, 2.3, 2.3, 2.3], |
| // CHECK-NEXT: [2.3, 2.3, 2.3, 2.3, 2.3], |
| // CHECK-NEXT: [1, 2, 3, 2.3, 2.3], |
| // CHECK-NEXT: [2, 3, 4, 2.3, 2.3]]] |
| |
| return |
| } |
| |
| func private @print_memref_f32(%ptr : tensor<*xf32>) |
