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1// RUN: mlir-opt %s -transform-interpreter -test-transform-dialect-erase-schedule \2// RUN: -one-shot-bufferize="bufferize-function-boundaries" \3// RUN: -buffer-deallocation-pipeline -convert-bufferization-to-memref \4// RUN: -convert-linalg-to-loops -convert-scf-to-cf -expand-strided-metadata \5// RUN: -lower-affine -convert-arith-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -convert-cf-to-llvm -reconcile-unrealized-casts | \6// RUN: mlir-runner -e main -entry-point-result=void \7// RUN: -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils \8// RUN: | FileCheck %s9 10// TODO: Use TD for vectorization and remove `test-linalg-to-vector-patterns`11// that's otherwise not required.12 13 14func.func @main() {15 %const = arith.constant dense<[[[1.0, 2.0, 3.0], [2.0, 3.0, 4.0]]]> : tensor<1x2x3xf32>16 %dynamic = tensor.cast %const: tensor<1x2x3xf32> to tensor<1x?x3xf32>17 %offset = arith.constant 2 : index18 %cst = arith.constant 2.3 : f3219 %c0 = arith.constant 0 : index20 %out = tensor.pad %dynamic low[%c0, %offset, %c0] high[%c0, %c0, %offset] {21 ^bb0(%gen_arg1: index, %gen_arg2: index, %gen_arg3: index):22 tensor.yield %cst : f3223 } : tensor<1x?x3xf32> to tensor<1x?x?xf32>24 %unranked = tensor.cast %out: tensor<1x?x?xf32> to tensor<*xf32>25 call @printMemrefF32(%unranked) : (tensor<*xf32>) -> ()26 27 // CHECK: Unranked Memref base@ = {{0x[-9a-f]*}}28 // CHECK-SAME: rank = 3 offset = 0 sizes = [1, 4, 5] strides = [20, 5, 1] data =29 // CHECK-NEXT{LITERAL}: [[[2.3, 2.3, 2.3, 2.3, 2.3],30 // CHECK-NEXT: [2.3, 2.3, 2.3, 2.3, 2.3],31 // CHECK-NEXT: [1, 2, 3, 2.3, 2.3],32 // CHECK-NEXT: [2, 3, 4, 2.3, 2.3]]]33 34 return35}36 37module attributes {transform.with_named_sequence} {38 transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {39 %func_op = transform.structured.match ops{["func.func"]} in %arg1 : (!transform.any_op) -> !transform.op<"func.func">40 41 transform.apply_patterns to %func_op {42 transform.apply_patterns.linalg.pad_vectorization43 } : !transform.op<"func.func">44 transform.yield45 }46}47 48func.func private @printMemrefF32(%ptr : tensor<*xf32>)49