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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=false enable-buffer-initialization=true25// 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 enable-buffer-initialization=true 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#CCC = #sparse_tensor.encoding<{35 map = (d0, d1, d2) -> (d0 : compressed, d1 : compressed, d2 : compressed)36}>37 38#CDC = #sparse_tensor.encoding<{39 map = (d0, d1, d2) -> (d0 : compressed, d1 : dense, d2 : compressed)40}>41 42#DCC = #sparse_tensor.encoding<{43 map = (d0, d1, d2) -> (d0 : dense, d1 : compressed, d2 : compressed)44}>45 46#DDC = #sparse_tensor.encoding<{47 map = (d0, d1, d2) -> (d0 : dense, d1 : dense, d2 : compressed)48}>49 50// Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f51func.func @alloc_3d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %f : f32) -> tensor<?x?x?xf32> {52 %buf = tensor.empty(%s1, %s2, %s3) : tensor<?x?x?xf32>53 %ret = linalg.fill ins(%f : f32) outs(%buf : tensor<?x?x?xf32>) -> tensor<?x?x?xf32>54 return %ret : tensor<?x?x?xf32>55}56 57func.func @conv_3d(%arg0: tensor<?x?x?xf32>, %arg1: tensor<?x?x?xf32>, %arg2: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {58 %ret = linalg.conv_3d59 ins (%arg0, %arg1: tensor<?x?x?xf32>, tensor<?x?x?xf32>)60 outs (%arg2: tensor<?x?x?xf32>) -> tensor<?x?x?xf32>61 return %ret : tensor<?x?x?xf32>62}63 64func.func @conv_3d_CCC(%arg0: tensor<?x?x?xf32, #CCC>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32, #CCC> {65 %c6 = arith.constant 6 : index66 %s = tensor.empty(%c6, %c6, %c6) : tensor<?x?x?xf32, #CCC>67 %ret = linalg.conv_3d68 ins (%arg0, %arg1: tensor<?x?x?xf32, #CCC>, tensor<?x?x?xf32>)69 outs (%s: tensor<?x?x?xf32, #CCC>) -> tensor<?x?x?xf32, #CCC>70 return %ret : tensor<?x?x?xf32, #CCC>71}72 73func.func @conv_3d_CDC(%arg0: tensor<?x?x?xf32, #CDC>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32, #CDC> {74 %c6 = arith.constant 6 : index75 %s = tensor.empty(%c6, %c6, %c6) : tensor<?x?x?xf32, #CDC>76 %ret = linalg.conv_3d77 ins (%arg0, %arg1: tensor<?x?x?xf32, #CDC>, tensor<?x?x?xf32>)78 outs (%s: tensor<?x?x?xf32, #CDC>) -> tensor<?x?x?xf32, #CDC>79 return %ret : tensor<?x?x?xf32, #CDC>80}81 82func.func @conv_3d_DCC(%arg0: tensor<?x?x?xf32, #DCC>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32, #DCC> {83 %c6 = arith.constant 6 : index84 %s = tensor.empty(%c6, %c6, %c6) : tensor<?x?x?xf32, #DCC>85 %ret = linalg.conv_3d86 ins (%arg0, %arg1: tensor<?x?x?xf32, #DCC>, tensor<?x?x?xf32>)87 outs (%s: tensor<?x?x?xf32, #DCC>) -> tensor<?x?x?xf32, #DCC>88 return %ret : tensor<?x?x?xf32, #DCC>89}90 91func.func @conv_3d_DDC(%arg0: tensor<?x?x?xf32, #DDC>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32, #DDC> {92 %c6 = arith.constant 6 : index93 %s = tensor.empty(%c6, %c6, %c6) : tensor<?x?x?xf32, #DDC>94 %ret = linalg.conv_3d95 ins (%arg0, %arg1: tensor<?x?x?xf32, #DDC>, tensor<?x?x?xf32>)96 outs (%s: tensor<?x?x?xf32, #DDC>) -> tensor<?x?x?xf32, #DDC>97 return %ret : tensor<?x?x?xf32, #DDC>98}99 100func.func @main() {101 %c0 = arith.constant 0 : index102 %c1 = arith.constant 1 : index103 %c3 = arith.constant 3 : index104 %c6 = arith.constant 6 : index105 %c8 = arith.constant 8 : index106 %f10 = arith.constant 10.00000e+00 : f32107 %val = arith.constant 2.00000e+00 : f32108 %zero = arith.constant 0.00000e+00 : f32109 110 %filter3D = call @alloc_3d_filled_f32(%c3, %c3, %c3, %val) : (index, index, index, f32) -> (tensor<?x?x?xf32>)111 %in3D_tmp = call @alloc_3d_filled_f32(%c8, %c8, %c8, %val) : (index, index, index, f32) -> (tensor<?x?x?xf32>)112 %in3D = tensor.insert %f10 into %in3D_tmp[%c0, %c3, %c0] : tensor<?x?x?xf32>113 %out3D = call @alloc_3d_filled_f32(%c6, %c6, %c6, %zero) : (index, index, index, f32) -> (tensor<?x?x?xf32>)114 115 %in3D_CCC = sparse_tensor.convert %in3D116 : tensor<?x?x?xf32> to tensor<?x?x?xf32, #CCC>117 %in3D_CDC = sparse_tensor.convert %in3D118 : tensor<?x?x?xf32> to tensor<?x?x?xf32, #CDC>119 %in3D_DCC = sparse_tensor.convert %in3D120 : tensor<?x?x?xf32> to tensor<?x?x?xf32, #DCC>121 %in3D_DDC = sparse_tensor.convert %in3D122 : tensor<?x?x?xf32> to tensor<?x?x?xf32, #DDC>123 124 %dense_ret = call @conv_3d(%in3D, %filter3D, %out3D) : (tensor<?x?x?xf32>, tensor<?x?x?xf32>, tensor<?x?x?xf32>) -> (tensor<?x?x?xf32>)125 %CCC_ret = call @conv_3d_CCC(%in3D_CCC, %filter3D) : (tensor<?x?x?xf32, #CCC>, tensor<?x?x?xf32>) -> (tensor<?x?x?xf32, #CCC>)126 %CDC_ret = call @conv_3d_CDC(%in3D_CDC, %filter3D) : (tensor<?x?x?xf32, #CDC>, tensor<?x?x?xf32>) -> (tensor<?x?x?xf32, #CDC>)127 %DCC_ret = call @conv_3d_DCC(%in3D_DCC, %filter3D) : (tensor<?x?x?xf32, #DCC>, tensor<?x?x?xf32>) -> (tensor<?x?x?xf32, #DCC>)128 %DDC_ret = call @conv_3d_DDC(%in3D_DDC, %filter3D) : (tensor<?x?x?xf32, #DDC>, tensor<?x?x?xf32>) -> (tensor<?x?x?xf32, #DDC>)129 130 // CHECK:( ( ( 108, 108, 108, 108, 108, 108 ),131 // CHECK-SAME: ( 124, 108, 108, 108, 108, 108 ),132 // CHECK-SAME: ( 124, 108, 108, 108, 108, 108 ),133 // CHECK-SAME: ( 124, 108, 108, 108, 108, 108 ),134 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),135 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ),136 // CHECK-SAME: ( ( 108, 108, 108, 108, 108, 108 ),137 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),138 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),139 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),140 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),141 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ),142 // CHECK-SAME: ( ( 108, 108, 108, 108, 108, 108 ),143 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),144 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),145 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),146 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),147 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ),148 // CHECK-SAME: ( ( 108, 108, 108, 108, 108, 108 ),149 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),150 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),151 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),152 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),153 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ),154 // CHECK-SAME: ( ( 108, 108, 108, 108, 108, 108 ),155 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),156 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),157 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),158 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),159 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ),160 // CHECK-SAME: ( ( 108, 108, 108, 108, 108, 108 ),161 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),162 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),163 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),164 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ),165 // CHECK-SAME: ( 108, 108, 108, 108, 108, 108 ) ) )166 %dense_v = vector.transfer_read %dense_ret[%c0, %c0, %c0], %zero167 : tensor<?x?x?xf32>, vector<6x6x6xf32>168 vector.print %dense_v : vector<6x6x6xf32>169 170 //171 // CHECK: ---- Sparse Tensor ----172 // CHECK-NEXT: nse = 216173 // CHECK-NEXT: dim = ( 6, 6, 6 )174 // CHECK-NEXT: lvl = ( 6, 6, 6 )175 // CHECK-NEXT: pos[0] : ( 0, 6 )176 // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 4, 5 )177 // CHECK-NEXT: pos[1] : ( 0, 6, 12, 18, 24, 30, 36 )178 // CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,179 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5 )180 // CHECK-NEXT: pos[2] : ( 0, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78,181 // CHECK-SAME: 84, 90, 96, 102, 108, 114, 120, 126, 132, 138, 144, 150,182 // CHECK-SAME: 156, 162, 168, 174, 180, 186, 192, 198, 204, 210, 216 )183 // CHECK-NEXT: crd[2] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0,184 // CHECK-SAME: 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,185 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2,186 // CHECK-SAME: 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,187 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4,188 // CHECK-SAME: 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,189 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0,190 // CHECK-SAME: 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,191 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2,192 // CHECK-SAME: 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,193 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4,194 // CHECK-SAME: 5, 0, 1, 2, 3, 4, 5 )195 // CHECK-NEXT: values : ( 108, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,196 // CHECK-SAME: 124, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,197 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,198 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,199 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,200 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,201 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,202 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,203 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,204 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,205 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,206 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,207 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,208 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,209 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,210 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,211 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,212 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108 )213 // CHECK-NEXT: ----214 //215 sparse_tensor.print %CCC_ret : tensor<?x?x?xf32, #CCC>216 217 //218 // CHECK: ---- Sparse Tensor ----219 // CHECK-NEXT: nse = 216220 // CHECK-NEXT: dim = ( 6, 6, 6 )221 // CHECK-NEXT: lvl = ( 6, 6, 6 )222 // CHECK-NEXT: pos[0] : ( 0, 6 )223 // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 4, 5 )224 // CHECK-NEXT: pos[2] : ( 0, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78, 84,225 // CHECK-SAME: 90, 96, 102, 108, 114, 120, 126, 132, 138, 144, 150, 156,226 // CHECK-SAME: 162, 168, 174, 180, 186, 192, 198, 204, 210, 216 )227 // CHECK-NEXT: crd[2] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,228 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,229 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,230 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,231 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,232 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,233 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,234 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,235 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,236 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,237 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5 )238 // CHECK-NEXT: values : ( 108, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,239 // CHECK-SAME: 124, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,240 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,241 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,242 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,243 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,244 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,245 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,246 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,247 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,248 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,249 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,250 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,251 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,252 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,253 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,254 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,255 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108 )256 // CHECK-NEXT: ----257 //258 sparse_tensor.print %CDC_ret : tensor<?x?x?xf32, #CDC>259 260 //261 // CHECK: ---- Sparse Tensor ----262 // CHECK-NEXT: nse = 216263 // CHECK-NEXT: dim = ( 6, 6, 6 )264 // CHECK-NEXT: lvl = ( 6, 6, 6 )265 // CHECK-NEXT: pos[2] : ( 0, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78, 84, 90,266 // CHECK-SAME: 96, 102, 108, 114, 120, 126, 132, 138, 144, 150, 156, 162,267 // CHECK-SAME: 168, 174, 180, 186, 192, 198, 204, 210, 216 )268 // CHECK-NEXT: crd[2] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,269 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,270 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,271 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,272 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,273 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,274 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,275 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,276 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,277 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,278 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5 )279 // CHECK-NEXT: values : ( 108, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,280 // CHECK-SAME: 124, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,281 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,282 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,283 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,284 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,285 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,286 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,287 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,288 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,289 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,290 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,291 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,292 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,293 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,294 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,295 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,296 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108 )297 // CHECK-NEXT: ----298 //299 sparse_tensor.print %DDC_ret : tensor<?x?x?xf32, #DDC>300 301 //302 // CHECK: ---- Sparse Tensor ----303 // CHECK-NEXT: nse = 216304 // CHECK-NEXT: dim = ( 6, 6, 6 )305 // CHECK-NEXT: lvl = ( 6, 6, 6 )306 // CHECK-NEXT: pos[1] : ( 0, 6, 12, 18, 24, 30, 36 )307 // CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,308 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5 )309 // CHECK-NEXT: pos[2] : ( 0, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78, 84, 90,310 // CHECK-SAME: 96, 102, 108, 114, 120, 126, 132, 138, 144, 150, 156, 162,311 // CHECK-SAME: 168, 174, 180, 186, 192, 198, 204, 210, 216 )312 // CHECK-NEXT: crd[2] : ( 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,313 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,314 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,315 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,316 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,317 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,318 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,319 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3,320 // CHECK-SAME: 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,321 // CHECK-SAME: 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1,322 // CHECK-SAME: 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5 )323 // CHECK-NEXT: values : ( 108, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,324 // CHECK-SAME: 124, 108, 108, 108, 108, 108, 124, 108, 108, 108, 108, 108,325 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,326 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,327 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,328 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,329 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,330 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,331 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,332 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,333 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,334 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,335 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,336 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,337 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,338 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,339 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108,340 // CHECK-SAME: 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108, 108 )341 // CHECK-NEXT: ----342 //343 sparse_tensor.print %DCC_ret : tensor<?x?x?xf32, #DCC>344 345 // Free the resources346 bufferization.dealloc_tensor %in3D : tensor<?x?x?xf32>347 bufferization.dealloc_tensor %filter3D : tensor<?x?x?xf32>348 bufferization.dealloc_tensor %out3D : tensor<?x?x?xf32>349 350 bufferization.dealloc_tensor %in3D_CDC : tensor<?x?x?xf32, #CDC>351 bufferization.dealloc_tensor %in3D_CCC : tensor<?x?x?xf32, #CCC>352 bufferization.dealloc_tensor %in3D_DDC : tensor<?x?x?xf32, #DDC>353 bufferization.dealloc_tensor %in3D_DCC : tensor<?x?x?xf32, #DCC>354 355 bufferization.dealloc_tensor %CCC_ret : tensor<?x?x?xf32, #CCC>356 bufferization.dealloc_tensor %CDC_ret : tensor<?x?x?xf32, #CDC>357 bufferization.dealloc_tensor %DDC_ret : tensor<?x?x?xf32, #DDC>358 bufferization.dealloc_tensor %DCC_ret : tensor<?x?x?xf32, #DCC>359 360 return361}362