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, this 5// config could be moved to lit.local.cfg. However, there are downstream users that 6// do not use these LIT config files. Hence why this is kept inline. 7// 8// DEFINE: %{sparsifier_opts} = enable-runtime-library=true 9// 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_utils 13// DEFINE: %{run_libs_sve} = -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils 14// DEFINE: %{run_opts} = -e main -entry-point-result=void 15// 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 %s 22// 23// Do the same run, but now with direct IR generation. 24// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false enable-buffer-initialization=true 25// RUN: %{compile} | %{run} | FileCheck %s 26// 27// Do the same run, but now with direct IR generation and vectorization. 28// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false enable-buffer-initialization=true vl=2 reassociate-fp-reductions=true enable-index-optimizations=true 29// RUN: %{compile} | %{run} | FileCheck %s 30// 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#CSR = #sparse_tensor.encoding<{ 35 map = (d0, d1) -> (d0 : dense, d1 : compressed) 36}> 37 38#CSC = #sparse_tensor.encoding<{ 39 map = (d0, d1) -> (d1 : dense, d0 : compressed) 40}> 41 42#BSR = #sparse_tensor.encoding<{ 43 map = ( i, j ) -> 44 ( i floordiv 2 : dense, 45 j floordiv 2 : compressed, 46 i mod 2 : dense, 47 j mod 2 : dense 48 ) 49}> 50 51 52// 53// Integration test that tests conversions between sparse tensors. 54// 55module { 56 // 57 // Main driver. 58 // 59 func.func @main() { 60 %c0 = arith.constant 0 : index 61 %c1 = arith.constant 1 : index 62 %c2 = arith.constant 2 : index 63 64 // 65 // Initialize a 2-dim dense tensor. 66 // 67 %t = arith.constant sparse<[[0, 0], [0, 1], [0, 2], [0, 3], 68 [1, 0], [1, 1], [1, 2], [1, 3]], 69 [ 1.0, 2.0, 3.0, 4.0, 70 5.0, 6.0, 7.0, 8.0 ]> : tensor<2x4xf64> 71 72 %td = arith.constant dense<[[ 1.0, 2.0, 3.0, 4.0 ], 73 [ 5.0, 6.0, 7.0, 8.0 ]]> : tensor<2x4xf64> 74 75 // constant -> BSR (either from SparseElementAttibutes or DenseElementAttribute) 76 %1 = sparse_tensor.convert %t : tensor<2x4xf64> to tensor<2x4xf64, #BSR> 77 %2 = sparse_tensor.convert %td : tensor<2x4xf64> to tensor<2x4xf64, #BSR> 78 %3 = sparse_tensor.convert %1 : tensor<2x4xf64, #BSR> to tensor<2x4xf64, #CSR> 79 %4 = sparse_tensor.convert %1 : tensor<2x4xf64, #BSR> to tensor<2x4xf64, #CSC> 80 81 // 82 // CHECK: ---- Sparse Tensor ---- 83 // CHECK-NEXT: nse = 8 84 // CHECK-NEXT: dim = ( 2, 4 ) 85 // CHECK-NEXT: lvl = ( 1, 2, 2, 2 ) 86 // CHECK-NEXT: pos[1] : ( 0, 2 ) 87 // CHECK-NEXT: crd[1] : ( 0, 1 ) 88 // CHECK-NEXT: values : ( 1, 2, 5, 6, 3, 4, 7, 8 ) 89 // CHECK-NEXT: ---- 90 // 91 // CHECK: ---- Sparse Tensor ---- 92 // CHECK-NEXT: nse = 8 93 // CHECK-NEXT: dim = ( 2, 4 ) 94 // CHECK-NEXT: lvl = ( 1, 2, 2, 2 ) 95 // CHECK-NEXT: pos[1] : ( 0, 2 ) 96 // CHECK-NEXT: crd[1] : ( 0, 1 ) 97 // CHECK-NEXT: values : ( 1, 2, 5, 6, 3, 4, 7, 8 ) 98 // CHECK-NEXT: ---- 99 // 100 // CHECK: ---- Sparse Tensor ---- 101 // CHECK-NEXT: nse = 8 102 // CHECK-NEXT: dim = ( 2, 4 ) 103 // CHECK-NEXT: lvl = ( 2, 4 ) 104 // CHECK-NEXT: pos[1] : ( 0, 4, 8 ) 105 // CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 0, 1, 2, 3 ) 106 // CHECK-NEXT: values : ( 1, 2, 3, 4, 5, 6, 7, 8 ) 107 // CHECK-NEXT: ---- 108 // 109 // CHECK: ---- Sparse Tensor ---- 110 // CHECK-NEXT: nse = 8 111 // CHECK-NEXT: dim = ( 2, 4 ) 112 // CHECK-NEXT: lvl = ( 4, 2 ) 113 // CHECK-NEXT: pos[1] : ( 0, 2, 4, 6, 8 ) 114 // CHECK-NEXT: crd[1] : ( 0, 1, 0, 1, 0, 1, 0, 1 ) 115 // CHECK-NEXT: values : ( 1, 5, 2, 6, 3, 7, 4, 8 ) 116 // CHECK-NEXT: ---- 117 // 118 sparse_tensor.print %1 : tensor<2x4xf64, #BSR> 119 sparse_tensor.print %2 : tensor<2x4xf64, #BSR> 120 sparse_tensor.print %3 : tensor<2x4xf64, #CSR> 121 sparse_tensor.print %4 : tensor<2x4xf64, #CSC> 122 123 // TODO: Fix memory leaks. 124 bufferization.dealloc_tensor %1 : tensor<2x4xf64, #BSR> 125 bufferization.dealloc_tensor %2 : tensor<2x4xf64, #BSR> 126 bufferization.dealloc_tensor %3 : tensor<2x4xf64, #CSR> 127 bufferization.dealloc_tensor %4 : tensor<2x4xf64, #CSC> 128 129 return 130 } 131} 132