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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// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false22 23// RUN: %{compile} | %{run} | FileCheck %s24//25// Do the same run, but now with vectorization.26// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true27// RUN: %{compile} | %{run} | FileCheck %s28//29// Do the same run, but now with VLA vectorization.30// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %}31 32#Tensor1 = #sparse_tensor.encoding<{33 map = (d0, d1, d2) -> (d0 : compressed(nonunique), d1 : singleton(nonunique), d2 : singleton)34}>35 36#Tensor2 = #sparse_tensor.encoding<{37 map = (d0, d1, d2) -> (d0 : dense, d1 : compressed, d2 : dense)38}>39 40#Tensor3 = #sparse_tensor.encoding<{41 map = (d0, d1, d2) -> (d0 : dense, d2 : dense, d1 : compressed)42}>43 44module {45 //46 // Utility for output.47 //48 func.func @dump(%arg0: tensor<2x3x4xf32>) {49 %c0 = arith.constant 0 : index50 %d0 = arith.constant -1.0 : f3251 %0 = vector.transfer_read %arg0[%c0, %c0, %c0], %d0: tensor<2x3x4xf32>, vector<2x3x4xf32>52 vector.print %0 : vector<2x3x4xf32>53 return54 }55 56 //57 // The first test suite (for non-singleton LevelTypes).58 //59 func.func @main() {60 //61 // Initialize a 3-dim dense tensor.62 //63 %src = arith.constant dense<[64 [ [ 1.0, 2.0, 3.0, 4.0 ],65 [ 5.0, 6.0, 7.0, 8.0 ],66 [ 9.0, 10.0, 11.0, 12.0 ] ],67 [ [ 13.0, 14.0, 15.0, 16.0 ],68 [ 17.0, 18.0, 19.0, 20.0 ],69 [ 21.0, 22.0, 23.0, 24.0 ] ]70 ]> : tensor<2x3x4xf64>71 72 //73 // Convert dense tensor directly to various sparse tensors.74 //75 %s1 = sparse_tensor.convert %src : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor1>76 %s2 = sparse_tensor.convert %src : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor2>77 %s3 = sparse_tensor.convert %src : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor3>78 79 //80 // Convert sparse tensor directly to another sparse format.81 //82 %t1 = sparse_tensor.convert %s1 : tensor<2x3x4xf64, #Tensor1> to tensor<2x3x4xf32, #Tensor1>83 %t2 = sparse_tensor.convert %s2 : tensor<2x3x4xf64, #Tensor2> to tensor<2x3x4xf32, #Tensor2>84 %t3 = sparse_tensor.convert %s3 : tensor<2x3x4xf64, #Tensor3> to tensor<2x3x4xf32, #Tensor3>85 86 //87 // Convert sparse tensor back to dense.88 //89 %d1 = sparse_tensor.convert %t1 : tensor<2x3x4xf32, #Tensor1> to tensor<2x3x4xf32>90 %d2 = sparse_tensor.convert %t2 : tensor<2x3x4xf32, #Tensor2> to tensor<2x3x4xf32>91 %d3 = sparse_tensor.convert %t3 : tensor<2x3x4xf32, #Tensor3> to tensor<2x3x4xf32>92 93 //94 // Check round-trip equality. And release dense tensors.95 //96 // CHECK-COUNT-3: ( ( ( 1, 2, 3, 4 ), ( 5, 6, 7, 8 ), ( 9, 10, 11, 12 ) ), ( ( 13, 14, 15, 16 ), ( 17, 18, 19, 20 ), ( 21, 22, 23, 24 ) ) )97 call @dump(%d1) : (tensor<2x3x4xf32>) -> ()98 call @dump(%d2) : (tensor<2x3x4xf32>) -> ()99 call @dump(%d3) : (tensor<2x3x4xf32>) -> ()100 101 //102 // Release sparse tensors.103 //104 bufferization.dealloc_tensor %t1 : tensor<2x3x4xf32, #Tensor1>105 bufferization.dealloc_tensor %t2 : tensor<2x3x4xf32, #Tensor2>106 bufferization.dealloc_tensor %t3 : tensor<2x3x4xf32, #Tensor3>107 bufferization.dealloc_tensor %s1 : tensor<2x3x4xf64, #Tensor1>108 bufferization.dealloc_tensor %s2 : tensor<2x3x4xf64, #Tensor2>109 bufferization.dealloc_tensor %s3 : tensor<2x3x4xf64, #Tensor3>110 bufferization.dealloc_tensor %d1 : tensor<2x3x4xf32>111 bufferization.dealloc_tensor %d2 : tensor<2x3x4xf32>112 bufferization.dealloc_tensor %d3 : tensor<2x3x4xf32>113 114 return115 }116}117