1// RUN: mlir-opt %s -split-input-file -verify-diagnostics 2 3func.func @invalid_new_dense(%arg0: !llvm.ptr<i8>) -> tensor<32xf32> { 4 // expected-error@+1 {{'sparse_tensor.new' op result #0 must be sparse tensor of any type values, but got 'tensor<32xf32>'}} 5 %0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<32xf32> 6 return %0 : tensor<32xf32> 7} 8 9// ----- 10 11func.func @invalid_release_dense(%arg0: tensor<4xi32>) { 12 // expected-error@+1 {{'sparse_tensor.release' op operand #0 must be sparse tensor of any type values, but got 'tensor<4xi32>'}} 13 sparse_tensor.release %arg0 : tensor<4xi32> 14 return 15} 16 17// ----- 18 19func.func @invalid_pointers_dense(%arg0: tensor<128xf64>) -> memref<?xindex> { 20 %c = arith.constant 0 : index 21 // expected-error@+1 {{'sparse_tensor.pointers' op operand #0 must be sparse tensor of any type values, but got 'tensor<128xf64>'}} 22 %0 = sparse_tensor.pointers %arg0, %c : tensor<128xf64> to memref<?xindex> 23 return %0 : memref<?xindex> 24} 25 26// ----- 27 28func.func @invalid_pointers_unranked(%arg0: tensor<*xf64>) -> memref<?xindex> { 29 %c = arith.constant 0 : index 30 // expected-error@+1 {{'sparse_tensor.pointers' op operand #0 must be sparse tensor of any type values, but got 'tensor<*xf64>'}} 31 %0 = sparse_tensor.pointers %arg0, %c : tensor<*xf64> to memref<?xindex> 32 return %0 : memref<?xindex> 33} 34 35// ----- 36 37#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"], pointerBitWidth=32}> 38 39func.func @mismatch_pointers_types(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xindex> { 40 %c = arith.constant 0 : index 41 // expected-error@+1 {{unexpected type for pointers}} 42 %0 = sparse_tensor.pointers %arg0, %c : tensor<128xf64, #SparseVector> to memref<?xindex> 43 return %0 : memref<?xindex> 44} 45 46// ----- 47 48#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> 49 50func.func @pointers_oob(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xindex> { 51 %c = arith.constant 1 : index 52 // expected-error@+1 {{requested pointers dimension out of bounds}} 53 %0 = sparse_tensor.pointers %arg0, %c : tensor<128xf64, #SparseVector> to memref<?xindex> 54 return %0 : memref<?xindex> 55} 56 57// ----- 58 59func.func @invalid_indices_dense(%arg0: tensor<10x10xi32>) -> memref<?xindex> { 60 %c = arith.constant 1 : index 61 // expected-error@+1 {{'sparse_tensor.indices' op operand #0 must be sparse tensor of any type values, but got 'tensor<10x10xi32>'}} 62 %0 = sparse_tensor.indices %arg0, %c : tensor<10x10xi32> to memref<?xindex> 63 return %0 : memref<?xindex> 64} 65 66// ----- 67 68func.func @invalid_indices_unranked(%arg0: tensor<*xf64>) -> memref<?xindex> { 69 %c = arith.constant 0 : index 70 // expected-error@+1 {{'sparse_tensor.indices' op operand #0 must be sparse tensor of any type values, but got 'tensor<*xf64>'}} 71 %0 = sparse_tensor.indices %arg0, %c : tensor<*xf64> to memref<?xindex> 72 return %0 : memref<?xindex> 73} 74 75// ----- 76 77#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> 78 79func.func @mismatch_indices_types(%arg0: tensor<?xf64, #SparseVector>) -> memref<?xi32> { 80 %c = arith.constant 0 : index 81 // expected-error@+1 {{unexpected type for indices}} 82 %0 = sparse_tensor.indices %arg0, %c : tensor<?xf64, #SparseVector> to memref<?xi32> 83 return %0 : memref<?xi32> 84} 85 86// ----- 87 88#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> 89 90func.func @indices_oob(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xindex> { 91 %c = arith.constant 1 : index 92 // expected-error@+1 {{requested indices dimension out of bounds}} 93 %0 = sparse_tensor.indices %arg0, %c : tensor<128xf64, #SparseVector> to memref<?xindex> 94 return %0 : memref<?xindex> 95} 96 97// ----- 98 99func.func @invalid_values_dense(%arg0: tensor<1024xf32>) -> memref<?xf32> { 100 // expected-error@+1 {{'sparse_tensor.values' op operand #0 must be sparse tensor of any type values, but got 'tensor<1024xf32>'}} 101 %0 = sparse_tensor.values %arg0 : tensor<1024xf32> to memref<?xf32> 102 return %0 : memref<?xf32> 103} 104 105// ----- 106 107#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> 108 109func.func @mismatch_values_types(%arg0: tensor<?xf64, #SparseVector>) -> memref<?xf32> { 110 // expected-error@+1 {{unexpected mismatch in element types}} 111 %0 = sparse_tensor.values %arg0 : tensor<?xf64, #SparseVector> to memref<?xf32> 112 return %0 : memref<?xf32> 113} 114 115// ----- 116 117func.func @sparse_unannotated_load(%arg0: tensor<16x32xf64>) -> tensor<16x32xf64> { 118 // expected-error@+1 {{'sparse_tensor.load' op operand #0 must be sparse tensor of any type values, but got 'tensor<16x32xf64>'}} 119 %0 = sparse_tensor.load %arg0 : tensor<16x32xf64> 120 return %0 : tensor<16x32xf64> 121} 122 123// ----- 124 125func.func @sparse_unannotated_insert(%arg0: tensor<128xf64>, %arg1: memref<?xindex>, %arg2: f64) { 126 // expected-error@+1 {{'sparse_tensor.lex_insert' op operand #0 must be sparse tensor of any type values, but got 'tensor<128xf64>'}} 127 sparse_tensor.lex_insert %arg0, %arg1, %arg2 : tensor<128xf64>, memref<?xindex>, f64 128 return 129} 130 131// ----- 132 133func.func @sparse_unannotated_expansion(%arg0: tensor<128xf64>) { 134 // expected-error@+1 {{'sparse_tensor.expand' op operand #0 must be sparse tensor of any type values, but got 'tensor<128xf64>'}} 135 %values, %filled, %added, %count = sparse_tensor.expand %arg0 136 : tensor<128xf64> to memref<?xf64>, memref<?xi1>, memref<?xindex>, index 137 return 138} 139 140// ----- 141 142func.func @sparse_unannotated_compression(%arg0: tensor<128xf64>, %arg1: memref<?xindex>, 143 %arg2: memref<?xf64>, %arg3: memref<?xi1>, 144 %arg4: memref<?xindex>, %arg5: index) { 145 // expected-error@+1 {{'sparse_tensor.compress' op operand #0 must be sparse tensor of any type values, but got 'tensor<128xf64>'}} 146 sparse_tensor.compress %arg0, %arg1, %arg2, %arg3, %arg4, %arg5 147 : tensor<128xf64>, memref<?xindex>, memref<?xf64>, memref<?xi1>, memref<?xindex>, index 148} 149 150// ----- 151 152func.func @sparse_convert_unranked(%arg0: tensor<*xf32>) -> tensor<10xf32> { 153 // expected-error@+1 {{unexpected type in convert}} 154 %0 = sparse_tensor.convert %arg0 : tensor<*xf32> to tensor<10xf32> 155 return %0 : tensor<10xf32> 156} 157 158// ----- 159 160#DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}> 161 162func.func @sparse_convert_rank_mismatch(%arg0: tensor<10x10xf64, #DCSR>) -> tensor<?xf64> { 163 // expected-error@+1 {{unexpected conversion mismatch in rank}} 164 %0 = sparse_tensor.convert %arg0 : tensor<10x10xf64, #DCSR> to tensor<?xf64> 165 return %0 : tensor<?xf64> 166} 167 168// ----- 169 170#CSR = #sparse_tensor.encoding<{dimLevelType = ["dense", "compressed"]}> 171 172func.func @sparse_convert_dim_mismatch(%arg0: tensor<10x?xf32>) -> tensor<10x10xf32, #CSR> { 173 // expected-error@+1 {{unexpected conversion mismatch in dimension 1}} 174 %0 = sparse_tensor.convert %arg0 : tensor<10x?xf32> to tensor<10x10xf32, #CSR> 175 return %0 : tensor<10x10xf32, #CSR> 176} 177 178// ----- 179 180func.func @invalid_out_dense(%arg0: tensor<10xf64>, %arg1: !llvm.ptr<i8>) { 181 // expected-error@+1 {{'sparse_tensor.out' op operand #0 must be sparse tensor of any type values, but got 'tensor<10xf64>'}} 182 sparse_tensor.out %arg0, %arg1 : tensor<10xf64>, !llvm.ptr<i8> 183 return 184} 185 186// ----- 187 188func.func @invalid_binary_num_args_mismatch_overlap(%arg0: f64, %arg1: f64) -> f64 { 189 // expected-error@+1 {{overlap region must have exactly 2 arguments}} 190 %r = sparse_tensor.binary %arg0, %arg1 : f64, f64 to f64 191 overlap={ 192 ^bb0(%x: f64): 193 sparse_tensor.yield %x : f64 194 } 195 left={} 196 right={} 197 return %r : f64 198} 199 200// ----- 201 202func.func @invalid_binary_num_args_mismatch_right(%arg0: f64, %arg1: f64) -> f64 { 203 // expected-error@+1 {{right region must have exactly 1 arguments}} 204 %r = sparse_tensor.binary %arg0, %arg1 : f64, f64 to f64 205 overlap={} 206 left={} 207 right={ 208 ^bb0(%x: f64, %y: f64): 209 sparse_tensor.yield %y : f64 210 } 211 return %r : f64 212} 213 214// ----- 215 216func.func @invalid_binary_argtype_mismatch(%arg0: f64, %arg1: f64) -> f64 { 217 // expected-error@+1 {{overlap region argument 2 type mismatch}} 218 %r = sparse_tensor.binary %arg0, %arg1 : f64, f64 to f64 219 overlap={ 220 ^bb0(%x: f64, %y: f32): 221 sparse_tensor.yield %x : f64 222 } 223 left=identity 224 right=identity 225 return %r : f64 226} 227 228// ----- 229 230func.func @invalid_binary_wrong_return_type(%arg0: f64, %arg1: f64) -> f64 { 231 // expected-error@+1 {{left region yield type mismatch}} 232 %0 = sparse_tensor.binary %arg0, %arg1 : f64, f64 to f64 233 overlap={} 234 left={ 235 ^bb0(%x: f64): 236 %1 = arith.constant 0.0 : f32 237 sparse_tensor.yield %1 : f32 238 } 239 right=identity 240 return %0 : f64 241} 242 243// ----- 244 245func.func @invalid_binary_wrong_identity_type(%arg0: i64, %arg1: f64) -> f64 { 246 // expected-error@+1 {{left=identity requires first argument to have the same type as the output}} 247 %0 = sparse_tensor.binary %arg0, %arg1 : i64, f64 to f64 248 overlap={} 249 left=identity 250 right=identity 251 return %0 : f64 252} 253 254// ----- 255 256func.func @invalid_binary_wrong_yield(%arg0: f64, %arg1: f64) -> f64 { 257 // expected-error@+1 {{left region must end with sparse_tensor.yield}} 258 %0 = sparse_tensor.binary %arg0, %arg1 : f64, f64 to f64 259 overlap={} 260 left={ 261 ^bb0(%x: f64): 262 tensor.yield %x : f64 263 } 264 right=identity 265 return %0 : f64 266} 267 268// ----- 269 270func.func @invalid_unary_argtype_mismatch(%arg0: f64) -> f64 { 271 // expected-error@+1 {{present region argument 1 type mismatch}} 272 %r = sparse_tensor.unary %arg0 : f64 to f64 273 present={ 274 ^bb0(%x: index): 275 sparse_tensor.yield %x : index 276 } 277 absent={} 278 return %r : f64 279} 280 281// ----- 282 283func.func @invalid_unary_num_args_mismatch(%arg0: f64) -> f64 { 284 // expected-error@+1 {{absent region must have exactly 0 arguments}} 285 %r = sparse_tensor.unary %arg0 : f64 to f64 286 present={} 287 absent={ 288 ^bb0(%x: f64): 289 sparse_tensor.yield %x : f64 290 } 291 return %r : f64 292} 293 294// ----- 295 296func.func @invalid_unary_wrong_return_type(%arg0: f64) -> f64 { 297 // expected-error@+1 {{present region yield type mismatch}} 298 %0 = sparse_tensor.unary %arg0 : f64 to f64 299 present={ 300 ^bb0(%x: f64): 301 %1 = arith.constant 0.0 : f32 302 sparse_tensor.yield %1 : f32 303 } 304 absent={} 305 return %0 : f64 306} 307 308// ----- 309 310func.func @invalid_unary_wrong_yield(%arg0: f64) -> f64 { 311 // expected-error@+1 {{present region must end with sparse_tensor.yield}} 312 %0 = sparse_tensor.unary %arg0 : f64 to f64 313 present={ 314 ^bb0(%x: f64): 315 tensor.yield %x : f64 316 } 317 absent={} 318 return %0 : f64 319} 320 321// ----- 322 323func.func @invalid_reduce_num_args_mismatch(%arg0: f64, %arg1: f64) -> f64 { 324 %cf1 = arith.constant 1.0 : f64 325 // expected-error@+1 {{reduce region must have exactly 2 arguments}} 326 %r = sparse_tensor.reduce %arg0, %arg1, %cf1 : f64 { 327 ^bb0(%x: f64): 328 sparse_tensor.yield %x : f64 329 } 330 return %r : f64 331} 332 333// ----- 334 335func.func @invalid_reduce_block_arg_type_mismatch(%arg0: i64, %arg1: i64) -> i64 { 336 %ci1 = arith.constant 1 : i64 337 // expected-error@+1 {{reduce region argument 1 type mismatch}} 338 %r = sparse_tensor.reduce %arg0, %arg1, %ci1 : i64 { 339 ^bb0(%x: f64, %y: f64): 340 %cst = arith.constant 2 : i64 341 sparse_tensor.yield %cst : i64 342 } 343 return %r : i64 344} 345 346// ----- 347 348func.func @invalid_reduce_return_type_mismatch(%arg0: f64, %arg1: f64) -> f64 { 349 %cf1 = arith.constant 1.0 : f64 350 // expected-error@+1 {{reduce region yield type mismatch}} 351 %r = sparse_tensor.reduce %arg0, %arg1, %cf1 : f64 { 352 ^bb0(%x: f64, %y: f64): 353 %cst = arith.constant 2 : i64 354 sparse_tensor.yield %cst : i64 355 } 356 return %r : f64 357} 358 359// ----- 360 361func.func @invalid_reduce_wrong_yield(%arg0: f64, %arg1: f64) -> f64 { 362 %cf1 = arith.constant 1.0 : f64 363 // expected-error@+1 {{reduce region must end with sparse_tensor.yield}} 364 %r = sparse_tensor.reduce %arg0, %arg1, %cf1 : f64 { 365 ^bb0(%x: f64, %y: f64): 366 %cst = arith.constant 2 : i64 367 tensor.yield %cst : i64 368 } 369 return %r : f64 370} 371