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1//--------------------------------------------------------------------------------------------------2// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS.3//4// Set-up that's shared across all tests in this directory. In principle, this5// config could be moved to lit.local.cfg. However, there are downstream users that6// do not use these LIT config files. Hence why this is kept inline.7//8// DEFINE: %{sparsifier_opts} = enable-runtime-library=true9// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts}10// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"11// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"12// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils13// DEFINE: %{run_libs_sve} = -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils14// DEFINE: %{run_opts} = -e main -entry-point-result=void15// DEFINE: %{run} = mlir-runner %{run_opts} %{run_libs}16// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs_sve}17//18// DEFINE: %{env} =19//--------------------------------------------------------------------------------------------------20 21// RUN: %{compile} | %{run} | FileCheck %s22//23// Do the same run, but now with direct IR generation.24// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false25// RUN: %{compile} | %{run} | FileCheck %s26//27// Do the same run, but now with direct IR generation and vectorization.28// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true29// RUN: %{compile} | %{run} | FileCheck %s30//31// Do the same run, but now with direct IR generation and VLA vectorization.32// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %}33 34#SparseVector = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed)}>35 36#trait_op = {37 indexing_maps = [38 affine_map<(i) -> (i)>, // a (in)39 affine_map<(i) -> (i)> // x (out)40 ],41 iterator_types = ["parallel"],42 doc = "x(i) = OP a(i)"43}44 45module {46 func.func @cre(%arga: tensor<?xcomplex<f32>, #SparseVector>)47 -> tensor<?xf32, #SparseVector> {48 %c = arith.constant 0 : index49 %d = tensor.dim %arga, %c : tensor<?xcomplex<f32>, #SparseVector>50 %xv = tensor.empty(%d) : tensor<?xf32, #SparseVector>51 %0 = linalg.generic #trait_op52 ins(%arga: tensor<?xcomplex<f32>, #SparseVector>)53 outs(%xv: tensor<?xf32, #SparseVector>) {54 ^bb(%a: complex<f32>, %x: f32):55 %1 = complex.re %a : complex<f32>56 linalg.yield %1 : f3257 } -> tensor<?xf32, #SparseVector>58 return %0 : tensor<?xf32, #SparseVector>59 }60 61 func.func @cim(%arga: tensor<?xcomplex<f32>, #SparseVector>)62 -> tensor<?xf32, #SparseVector> {63 %c = arith.constant 0 : index64 %d = tensor.dim %arga, %c : tensor<?xcomplex<f32>, #SparseVector>65 %xv = tensor.empty(%d) : tensor<?xf32, #SparseVector>66 %0 = linalg.generic #trait_op67 ins(%arga: tensor<?xcomplex<f32>, #SparseVector>)68 outs(%xv: tensor<?xf32, #SparseVector>) {69 ^bb(%a: complex<f32>, %x: f32):70 %1 = complex.im %a : complex<f32>71 linalg.yield %1 : f3272 } -> tensor<?xf32, #SparseVector>73 return %0 : tensor<?xf32, #SparseVector>74 }75 76 func.func @main() {77 // Setup sparse vectors.78 %v1 = arith.constant sparse<79 [ [0], [20], [31] ],80 [ (5.13, 2.0), (3.0, 4.0), (5.0, 6.0) ] > : tensor<32xcomplex<f32>>81 %sv1 = sparse_tensor.convert %v1 : tensor<32xcomplex<f32>> to tensor<?xcomplex<f32>, #SparseVector>82 83 // Call sparse vector kernels.84 %0 = call @cre(%sv1)85 : (tensor<?xcomplex<f32>, #SparseVector>) -> tensor<?xf32, #SparseVector>86 87 %1 = call @cim(%sv1)88 : (tensor<?xcomplex<f32>, #SparseVector>) -> tensor<?xf32, #SparseVector>89 90 //91 // Verify the results.92 //93 // CHECK: ---- Sparse Tensor ----94 // CHECK-NEXT: nse = 395 // CHECK-NEXT: dim = ( 32 )96 // CHECK-NEXT: lvl = ( 32 )97 // CHECK-NEXT: pos[0] : ( 0, 3 )98 // CHECK-NEXT: crd[0] : ( 0, 20, 31 )99 // CHECK-NEXT: values : ( 5.13, 3, 5 )100 // CHECK-NEXT: ----101 //102 // CHECK-NEXT: ---- Sparse Tensor ----103 // CHECK-NEXT: nse = 3104 // CHECK-NEXT: dim = ( 32 )105 // CHECK-NEXT: lvl = ( 32 )106 // CHECK-NEXT: pos[0] : ( 0, 3 )107 // CHECK-NEXT: crd[0] : ( 0, 20, 31 )108 // CHECK-NEXT: values : ( 2, 4, 6 )109 // CHECK-NEXT: ----110 //111 sparse_tensor.print %0 : tensor<?xf32, #SparseVector>112 sparse_tensor.print %1 : tensor<?xf32, #SparseVector>113 114 // Release the resources.115 bufferization.dealloc_tensor %sv1 : tensor<?xcomplex<f32>, #SparseVector>116 bufferization.dealloc_tensor %0 : tensor<?xf32, #SparseVector>117 bufferization.dealloc_tensor %1 : tensor<?xf32, #SparseVector>118 return119 }120}121