reshape.https.any.js (96511B)
1 // META: title=test WebNN API reshape operation 2 // META: global=window 3 // META: variant=?cpu 4 // META: variant=?gpu 5 // META: variant=?npu 6 // META: script=../resources/utils.js 7 // META: timeout=long 8 9 'use strict'; 10 11 // https://www.w3.org/TR/webnn/#api-mlgraphbuilder-reshape-method 12 // Alter the shape of a tensor to a new shape. 13 // 14 // MLOperand reshape( 15 // MLOperand input, sequence<[EnforceRange] unsigned long> newShape); 16 17 const reshapeTests = [ 18 { 19 'name': 'reshape float32 tensor to a new shape (reorder all dimensions)', 20 'graph': { 21 'inputs': { 22 'reshapeInput': { 23 'data': [ 24 -30.0561466217041, 99.56941986083984, 88.04620361328125, 25 -91.87507629394531, -23.7972354888916, -91.28665161132812, 26 -63.15204620361328, 12.0669527053833, -96.1172866821289, 27 -44.77365493774414, -80.08650970458984, -64.43756866455078, 28 27.64195442199707, -96.86306762695312, 83.6834716796875, 29 50.599483489990234, -20.18765640258789, -1.3904608488082886, 30 -96.93603515625, 65.34143829345703, 34.835994720458984, 31 62.01485824584961, -2.8698415756225586, 27.903749465942383 32 ], 33 'descriptor': {shape: [2, 3, 4], dataType: 'float32'} 34 } 35 }, 36 'operators': [{ 37 'name': 'reshape', 38 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 2, 3]}], 39 'outputs': 'reshapeOutput' 40 }], 41 'expectedOutputs': { 42 'reshapeOutput': { 43 'data': [ 44 -30.0561466217041, 99.56941986083984, 88.04620361328125, 45 -91.87507629394531, -23.7972354888916, -91.28665161132812, 46 -63.15204620361328, 12.0669527053833, -96.1172866821289, 47 -44.77365493774414, -80.08650970458984, -64.43756866455078, 48 27.64195442199707, -96.86306762695312, 83.6834716796875, 49 50.599483489990234, -20.18765640258789, -1.3904608488082886, 50 -96.93603515625, 65.34143829345703, 34.835994720458984, 51 62.01485824584961, -2.8698415756225586, 27.903749465942383 52 ], 53 'descriptor': {shape: [4, 2, 3], dataType: 'float32'} 54 } 55 } 56 } 57 }, 58 { 59 'name': 60 'reshape float32 constant tensor to a new shape (reorder all dimensions)', 61 'graph': { 62 'inputs': { 63 'reshapeInput': { 64 'data': [ 65 -30.0561466217041, 99.56941986083984, 88.04620361328125, 66 -91.87507629394531, -23.7972354888916, -91.28665161132812, 67 -63.15204620361328, 12.0669527053833, -96.1172866821289, 68 -44.77365493774414, -80.08650970458984, -64.43756866455078, 69 27.64195442199707, -96.86306762695312, 83.6834716796875, 70 50.599483489990234, -20.18765640258789, -1.3904608488082886, 71 -96.93603515625, 65.34143829345703, 34.835994720458984, 72 62.01485824584961, -2.8698415756225586, 27.903749465942383 73 ], 74 'descriptor': {shape: [2, 3, 4], dataType: 'float32'}, 75 'constant': true 76 } 77 }, 78 'operators': [{ 79 'name': 'reshape', 80 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 2, 3]}], 81 'outputs': 'reshapeOutput' 82 }], 83 'expectedOutputs': { 84 'reshapeOutput': { 85 'data': [ 86 -30.0561466217041, 99.56941986083984, 88.04620361328125, 87 -91.87507629394531, -23.7972354888916, -91.28665161132812, 88 -63.15204620361328, 12.0669527053833, -96.1172866821289, 89 -44.77365493774414, -80.08650970458984, -64.43756866455078, 90 27.64195442199707, -96.86306762695312, 83.6834716796875, 91 50.599483489990234, -20.18765640258789, -1.3904608488082886, 92 -96.93603515625, 65.34143829345703, 34.835994720458984, 93 62.01485824584961, -2.8698415756225586, 27.903749465942383 94 ], 95 'descriptor': {shape: [4, 2, 3], dataType: 'float32'} 96 } 97 } 98 } 99 }, 100 { 101 'name': 'reshape float32 tensor to a new shape (reduce dimensions)', 102 'graph': { 103 'inputs': { 104 'reshapeInput': { 105 'data': [ 106 -30.0561466217041, 99.56941986083984, 88.04620361328125, 107 -91.87507629394531, -23.7972354888916, -91.28665161132812, 108 -63.15204620361328, 12.0669527053833, -96.1172866821289, 109 -44.77365493774414, -80.08650970458984, -64.43756866455078, 110 27.64195442199707, -96.86306762695312, 83.6834716796875, 111 50.599483489990234, -20.18765640258789, -1.3904608488082886, 112 -96.93603515625, 65.34143829345703, 34.835994720458984, 113 62.01485824584961, -2.8698415756225586, 27.903749465942383 114 ], 115 'descriptor': {shape: [4, 1, 1, 1, 6], dataType: 'float32'} 116 } 117 }, 118 'operators': [{ 119 'name': 'reshape', 120 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 1, 1, 6]}], 121 'outputs': 'reshapeOutput' 122 }], 123 'expectedOutputs': { 124 'reshapeOutput': { 125 'data': [ 126 -30.0561466217041, 99.56941986083984, 88.04620361328125, 127 -91.87507629394531, -23.7972354888916, -91.28665161132812, 128 -63.15204620361328, 12.0669527053833, -96.1172866821289, 129 -44.77365493774414, -80.08650970458984, -64.43756866455078, 130 27.64195442199707, -96.86306762695312, 83.6834716796875, 131 50.599483489990234, -20.18765640258789, -1.3904608488082886, 132 -96.93603515625, 65.34143829345703, 34.835994720458984, 133 62.01485824584961, -2.8698415756225586, 27.903749465942383 134 ], 135 'descriptor': {shape: [4, 1, 1, 6], dataType: 'float32'} 136 } 137 } 138 } 139 }, 140 { 141 'name': 'reshape float32 tensor to a new shape (extend dimensions)', 142 'graph': { 143 'inputs': { 144 'reshapeInput': { 145 'data': [ 146 -30.0561466217041, 99.56941986083984, 88.04620361328125, 147 -91.87507629394531, -23.7972354888916, -91.28665161132812, 148 -63.15204620361328, 12.0669527053833, -96.1172866821289, 149 -44.77365493774414, -80.08650970458984, -64.43756866455078, 150 27.64195442199707, -96.86306762695312, 83.6834716796875, 151 50.599483489990234, -20.18765640258789, -1.3904608488082886, 152 -96.93603515625, 65.34143829345703, 34.835994720458984, 153 62.01485824584961, -2.8698415756225586, 27.903749465942383 154 ], 155 'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'} 156 } 157 }, 158 'operators': [{ 159 'name': 'reshape', 160 'arguments': [{'input': 'reshapeInput'}, {'newShape': [2, 2, 2, 3, 1]}], 161 'outputs': 'reshapeOutput' 162 }], 163 'expectedOutputs': { 164 'reshapeOutput': { 165 'data': [ 166 -30.0561466217041, 99.56941986083984, 88.04620361328125, 167 -91.87507629394531, -23.7972354888916, -91.28665161132812, 168 -63.15204620361328, 12.0669527053833, -96.1172866821289, 169 -44.77365493774414, -80.08650970458984, -64.43756866455078, 170 27.64195442199707, -96.86306762695312, 83.6834716796875, 171 50.599483489990234, -20.18765640258789, -1.3904608488082886, 172 -96.93603515625, 65.34143829345703, 34.835994720458984, 173 62.01485824584961, -2.8698415756225586, 27.903749465942383 174 ], 175 'descriptor': {shape: [2, 2, 2, 3, 1], dataType: 'float32'} 176 } 177 } 178 } 179 }, 180 { 181 'name': 'reshape float32 tensor to a new shape (4D to 4D)', 182 'graph': { 183 'inputs': { 184 'reshapeInput': { 185 'data': [ 186 -30.0561466217041, 99.56941986083984, 88.04620361328125, 187 -91.87507629394531, -23.7972354888916, -91.28665161132812, 188 -63.15204620361328, 12.0669527053833, -96.1172866821289, 189 -44.77365493774414, -80.08650970458984, -64.43756866455078, 190 27.64195442199707, -96.86306762695312, 83.6834716796875, 191 50.599483489990234, -20.18765640258789, -1.3904608488082886, 192 -96.93603515625, 65.34143829345703, 34.835994720458984, 193 62.01485824584961, -2.8698415756225586, 27.903749465942383 194 ], 195 'descriptor': {shape: [3, 2, 2, 2], dataType: 'float32'} 196 } 197 }, 198 'operators': [{ 199 'name': 'reshape', 200 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 2, 3, 1]}], 201 'outputs': 'reshapeOutput' 202 }], 203 'expectedOutputs': { 204 'reshapeOutput': { 205 'data': [ 206 -30.0561466217041, 99.56941986083984, 88.04620361328125, 207 -91.87507629394531, -23.7972354888916, -91.28665161132812, 208 -63.15204620361328, 12.0669527053833, -96.1172866821289, 209 -44.77365493774414, -80.08650970458984, -64.43756866455078, 210 27.64195442199707, -96.86306762695312, 83.6834716796875, 211 50.599483489990234, -20.18765640258789, -1.3904608488082886, 212 -96.93603515625, 65.34143829345703, 34.835994720458984, 213 62.01485824584961, -2.8698415756225586, 27.903749465942383 214 ], 215 'descriptor': {shape: [4, 2, 3, 1], dataType: 'float32'} 216 } 217 } 218 } 219 }, 220 { 221 'name': 'reshape float32 tensor to 1D tensor', 222 'graph': { 223 'inputs': { 224 'reshapeInput': { 225 'data': [ 226 -30.0561466217041, 99.56941986083984, 88.04620361328125, 227 -91.87507629394531, -23.7972354888916, -91.28665161132812, 228 -63.15204620361328, 12.0669527053833, -96.1172866821289, 229 -44.77365493774414, -80.08650970458984, -64.43756866455078, 230 27.64195442199707, -96.86306762695312, 83.6834716796875, 231 50.599483489990234, -20.18765640258789, -1.3904608488082886, 232 -96.93603515625, 65.34143829345703, 34.835994720458984, 233 62.01485824584961, -2.8698415756225586, 27.903749465942383 234 ], 235 'descriptor': {shape: [3, 2, 2, 2], dataType: 'float32'} 236 } 237 }, 238 'operators': [{ 239 'name': 'reshape', 240 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 241 'outputs': 'reshapeOutput' 242 }], 243 'expectedOutputs': { 244 'reshapeOutput': { 245 'data': [ 246 -30.0561466217041, 99.56941986083984, 88.04620361328125, 247 -91.87507629394531, -23.7972354888916, -91.28665161132812, 248 -63.15204620361328, 12.0669527053833, -96.1172866821289, 249 -44.77365493774414, -80.08650970458984, -64.43756866455078, 250 27.64195442199707, -96.86306762695312, 83.6834716796875, 251 50.599483489990234, -20.18765640258789, -1.3904608488082886, 252 -96.93603515625, 65.34143829345703, 34.835994720458984, 253 62.01485824584961, -2.8698415756225586, 27.903749465942383 254 ], 255 'descriptor': {shape: [24], dataType: 'float32'} 256 } 257 } 258 } 259 }, 260 { 261 'name': 'reshape (squeeze) float32 2D tensor by eliminating one dimension', 262 'graph': { 263 'inputs': { 264 'reshapeInput': { 265 'data': [ 266 -30.0561466217041, 99.56941986083984, 88.04620361328125, 267 -91.87507629394531, -23.7972354888916, -91.28665161132812, 268 -63.15204620361328, 12.0669527053833, -96.1172866821289, 269 -44.77365493774414, -80.08650970458984, -64.43756866455078, 270 27.64195442199707, -96.86306762695312, 83.6834716796875, 271 50.599483489990234, -20.18765640258789, -1.3904608488082886, 272 -96.93603515625, 65.34143829345703, 34.835994720458984, 273 62.01485824584961, -2.8698415756225586, 27.903749465942383 274 ], 275 'descriptor': {shape: [1, 24], dataType: 'float32'} 276 } 277 }, 278 'operators': [{ 279 'name': 'reshape', 280 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 281 'outputs': 'reshapeOutput' 282 }], 283 'expectedOutputs': { 284 'reshapeOutput': { 285 'data': [ 286 -30.0561466217041, 99.56941986083984, 88.04620361328125, 287 -91.87507629394531, -23.7972354888916, -91.28665161132812, 288 -63.15204620361328, 12.0669527053833, -96.1172866821289, 289 -44.77365493774414, -80.08650970458984, -64.43756866455078, 290 27.64195442199707, -96.86306762695312, 83.6834716796875, 291 50.599483489990234, -20.18765640258789, -1.3904608488082886, 292 -96.93603515625, 65.34143829345703, 34.835994720458984, 293 62.01485824584961, -2.8698415756225586, 27.903749465942383 294 ], 295 'descriptor': {shape: [24], dataType: 'float32'} 296 } 297 } 298 } 299 }, 300 { 301 'name': 'reshape (squeeze) float32 3D tensor by eliminating one dimension', 302 'graph': { 303 'inputs': { 304 'reshapeInput': { 305 'data': [ 306 -30.0561466217041, 99.56941986083984, 88.04620361328125, 307 -91.87507629394531, -23.7972354888916, -91.28665161132812, 308 -63.15204620361328, 12.0669527053833, -96.1172866821289, 309 -44.77365493774414, -80.08650970458984, -64.43756866455078, 310 27.64195442199707, -96.86306762695312, 83.6834716796875, 311 50.599483489990234, -20.18765640258789, -1.3904608488082886, 312 -96.93603515625, 65.34143829345703, 34.835994720458984, 313 62.01485824584961, -2.8698415756225586, 27.903749465942383 314 ], 315 'descriptor': {shape: [4, 1, 6], dataType: 'float32'} 316 } 317 }, 318 'operators': [{ 319 'name': 'reshape', 320 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 6]}], 321 'outputs': 'reshapeOutput' 322 }], 323 'expectedOutputs': { 324 'reshapeOutput': { 325 'data': [ 326 -30.0561466217041, 99.56941986083984, 88.04620361328125, 327 -91.87507629394531, -23.7972354888916, -91.28665161132812, 328 -63.15204620361328, 12.0669527053833, -96.1172866821289, 329 -44.77365493774414, -80.08650970458984, -64.43756866455078, 330 27.64195442199707, -96.86306762695312, 83.6834716796875, 331 50.599483489990234, -20.18765640258789, -1.3904608488082886, 332 -96.93603515625, 65.34143829345703, 34.835994720458984, 333 62.01485824584961, -2.8698415756225586, 27.903749465942383 334 ], 335 'descriptor': {shape: [4, 6], dataType: 'float32'} 336 } 337 } 338 } 339 }, 340 { 341 'name': 'reshape (squeeze) float32 3D tensor by eliminating two dimensions', 342 'graph': { 343 'inputs': { 344 'reshapeInput': { 345 'data': [ 346 -30.0561466217041, 99.56941986083984, 88.04620361328125, 347 -91.87507629394531, -23.7972354888916, -91.28665161132812, 348 -63.15204620361328, 12.0669527053833, -96.1172866821289, 349 -44.77365493774414, -80.08650970458984, -64.43756866455078, 350 27.64195442199707, -96.86306762695312, 83.6834716796875, 351 50.599483489990234, -20.18765640258789, -1.3904608488082886, 352 -96.93603515625, 65.34143829345703, 34.835994720458984, 353 62.01485824584961, -2.8698415756225586, 27.903749465942383 354 ], 355 'descriptor': {shape: [1, 24, 1], dataType: 'float32'} 356 } 357 }, 358 'operators': [{ 359 'name': 'reshape', 360 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 361 'outputs': 'reshapeOutput' 362 }], 363 'expectedOutputs': { 364 'reshapeOutput': { 365 'data': [ 366 -30.0561466217041, 99.56941986083984, 88.04620361328125, 367 -91.87507629394531, -23.7972354888916, -91.28665161132812, 368 -63.15204620361328, 12.0669527053833, -96.1172866821289, 369 -44.77365493774414, -80.08650970458984, -64.43756866455078, 370 27.64195442199707, -96.86306762695312, 83.6834716796875, 371 50.599483489990234, -20.18765640258789, -1.3904608488082886, 372 -96.93603515625, 65.34143829345703, 34.835994720458984, 373 62.01485824584961, -2.8698415756225586, 27.903749465942383 374 ], 375 'descriptor': {shape: [24], dataType: 'float32'} 376 } 377 } 378 } 379 }, 380 { 381 'name': 'reshape (squeeze) float32 4D tensor by eliminating two dimensions', 382 'graph': { 383 'inputs': { 384 'reshapeInput': { 385 'data': [ 386 -30.0561466217041, 99.56941986083984, 88.04620361328125, 387 -91.87507629394531, -23.7972354888916, -91.28665161132812, 388 -63.15204620361328, 12.0669527053833, -96.1172866821289, 389 -44.77365493774414, -80.08650970458984, -64.43756866455078, 390 27.64195442199707, -96.86306762695312, 83.6834716796875, 391 50.599483489990234, -20.18765640258789, -1.3904608488082886, 392 -96.93603515625, 65.34143829345703, 34.835994720458984, 393 62.01485824584961, -2.8698415756225586, 27.903749465942383 394 ], 395 'descriptor': {shape: [1, 4, 1, 6], dataType: 'float32'} 396 } 397 }, 398 'operators': [{ 399 'name': 'reshape', 400 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 6]}], 401 'outputs': 'reshapeOutput' 402 }], 403 'expectedOutputs': { 404 'reshapeOutput': { 405 'data': [ 406 -30.0561466217041, 99.56941986083984, 88.04620361328125, 407 -91.87507629394531, -23.7972354888916, -91.28665161132812, 408 -63.15204620361328, 12.0669527053833, -96.1172866821289, 409 -44.77365493774414, -80.08650970458984, -64.43756866455078, 410 27.64195442199707, -96.86306762695312, 83.6834716796875, 411 50.599483489990234, -20.18765640258789, -1.3904608488082886, 412 -96.93603515625, 65.34143829345703, 34.835994720458984, 413 62.01485824584961, -2.8698415756225586, 27.903749465942383 414 ], 415 'descriptor': {shape: [4, 6], dataType: 'float32'} 416 } 417 } 418 } 419 }, 420 { 421 'name': 'reshape (squeeze) float32 4D tensor by eliminating all dimensions', 422 'graph': { 423 'inputs': { 424 'reshapeInput': { 425 'data': [-33.82555389404297], 426 'descriptor': {shape: [1, 1, 1, 1], dataType: 'float32'} 427 } 428 }, 429 'operators': [{ 430 'name': 'reshape', 431 'arguments': [{'input': 'reshapeInput'}, {'newShape': []}], 432 'outputs': 'reshapeOutput' 433 }], 434 'expectedOutputs': { 435 'reshapeOutput': { 436 'data': [-33.82555389404297], 437 'descriptor': {shape: [], dataType: 'float32'} 438 } 439 } 440 } 441 }, 442 { 443 'name': 444 'reshape (squeeze) float32 5D tensor by eliminating four dimensions', 445 'graph': { 446 'inputs': { 447 'reshapeInput': { 448 'data': [ 449 -30.0561466217041, 99.56941986083984, 88.04620361328125, 450 -91.87507629394531, -23.7972354888916, -91.28665161132812, 451 -63.15204620361328, 12.0669527053833, -96.1172866821289, 452 -44.77365493774414, -80.08650970458984, -64.43756866455078, 453 27.64195442199707, -96.86306762695312, 83.6834716796875, 454 50.599483489990234, -20.18765640258789, -1.3904608488082886, 455 -96.93603515625, 65.34143829345703, 34.835994720458984, 456 62.01485824584961, -2.8698415756225586, 27.903749465942383 457 ], 458 'descriptor': {shape: [1, 1, 1, 24, 1], dataType: 'float32'} 459 } 460 }, 461 'operators': [{ 462 'name': 'reshape', 463 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 464 'outputs': 'reshapeOutput' 465 }], 466 'expectedOutputs': { 467 'reshapeOutput': { 468 'data': [ 469 -30.0561466217041, 99.56941986083984, 88.04620361328125, 470 -91.87507629394531, -23.7972354888916, -91.28665161132812, 471 -63.15204620361328, 12.0669527053833, -96.1172866821289, 472 -44.77365493774414, -80.08650970458984, -64.43756866455078, 473 27.64195442199707, -96.86306762695312, 83.6834716796875, 474 50.599483489990234, -20.18765640258789, -1.3904608488082886, 475 -96.93603515625, 65.34143829345703, 34.835994720458984, 476 62.01485824584961, -2.8698415756225586, 27.903749465942383 477 ], 478 'descriptor': {shape: [24], dataType: 'float32'} 479 } 480 } 481 } 482 }, 483 { 484 'name': 'reshape (squeeze) float32 2D tensor by eliminating 1st dimension', 485 'graph': { 486 'inputs': { 487 'reshapeInput': { 488 'data': [ 489 -30.0561466217041, 99.56941986083984, 88.04620361328125, 490 -91.87507629394531, -23.7972354888916, -91.28665161132812, 491 -63.15204620361328, 12.0669527053833, -96.1172866821289, 492 -44.77365493774414, -80.08650970458984, -64.43756866455078, 493 27.64195442199707, -96.86306762695312, 83.6834716796875, 494 50.599483489990234, -20.18765640258789, -1.3904608488082886, 495 -96.93603515625, 65.34143829345703, 34.835994720458984, 496 62.01485824584961, -2.8698415756225586, 27.903749465942383 497 ], 498 'descriptor': {shape: [1, 24], dataType: 'float32'} 499 } 500 }, 501 'operators': [{ 502 'name': 'reshape', 503 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 504 'outputs': 'reshapeOutput' 505 }], 506 'expectedOutputs': { 507 'reshapeOutput': { 508 'data': [ 509 -30.0561466217041, 99.56941986083984, 88.04620361328125, 510 -91.87507629394531, -23.7972354888916, -91.28665161132812, 511 -63.15204620361328, 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'descriptor': {shape: [4, 6], dataType: 'float32'} 887 } 888 }, 889 'operators': [{ 890 'name': 'reshape', 891 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 1, 6]}], 892 'outputs': 'reshapeOutput' 893 }], 894 'expectedOutputs': { 895 'reshapeOutput': { 896 'data': [ 897 -30.0561466217041, 99.56941986083984, 88.04620361328125, 898 -91.87507629394531, -23.7972354888916, -91.28665161132812, 899 -63.15204620361328, 12.0669527053833, -96.1172866821289, 900 -44.77365493774414, -80.08650970458984, -64.43756866455078, 901 27.64195442199707, -96.86306762695312, 83.6834716796875, 902 50.599483489990234, -20.18765640258789, -1.3904608488082886, 903 -96.93603515625, 65.34143829345703, 34.835994720458984, 904 62.01485824584961, -2.8698415756225586, 27.903749465942383 905 ], 906 'descriptor': {shape: [4, 1, 6], dataType: 'float32'} 907 } 908 } 909 } 910 }, 911 { 912 'name': 'reshape (unsqueeze) float32 2D tensor by adding two dimensions', 913 'graph': { 914 'inputs': { 915 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-96.1172866821289, 940 -44.77365493774414, -80.08650970458984, -64.43756866455078, 941 27.64195442199707, -96.86306762695312, 83.6834716796875, 942 50.599483489990234, -20.18765640258789, -1.3904608488082886, 943 -96.93603515625, 65.34143829345703, 34.835994720458984, 944 62.01485824584961, -2.8698415756225586, 27.903749465942383 945 ], 946 'descriptor': {shape: [1, 4, 1, 6], dataType: 'float32'} 947 } 948 } 949 } 950 }, 951 { 952 'name': 'reshape (unsqueeze) float32 2D tensor by adding 1st dimension', 953 'graph': { 954 'inputs': { 955 'reshapeInput': { 956 'data': [ 957 -30.0561466217041, 99.56941986083984, 88.04620361328125, 958 -91.87507629394531, -23.7972354888916, -91.28665161132812, 959 -63.15204620361328, 12.0669527053833, -96.1172866821289, 960 -44.77365493774414, -80.08650970458984, -64.43756866455078, 961 27.64195442199707, -96.86306762695312, 83.6834716796875, 962 50.599483489990234, -20.18765640258789, -1.3904608488082886, 963 -96.93603515625, 65.34143829345703, 34.835994720458984, 964 62.01485824584961, -2.8698415756225586, 27.903749465942383 965 ], 966 'descriptor': {shape: [24], dataType: 'float32'} 967 } 968 }, 969 'operators': [{ 970 'name': 'reshape', 971 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 24]}], 972 'outputs': 'reshapeOutput' 973 }], 974 'expectedOutputs': { 975 'reshapeOutput': { 976 'data': [ 977 -30.0561466217041, 99.56941986083984, 88.04620361328125, 978 -91.87507629394531, -23.7972354888916, -91.28665161132812, 979 -63.15204620361328, 12.0669527053833, -96.1172866821289, 980 -44.77365493774414, -80.08650970458984, -64.43756866455078, 981 27.64195442199707, -96.86306762695312, 83.6834716796875, 982 50.599483489990234, -20.18765640258789, -1.3904608488082886, 983 -96.93603515625, 65.34143829345703, 34.835994720458984, 984 62.01485824584961, -2.8698415756225586, 27.903749465942383 985 ], 986 'descriptor': {shape: [1, 24], dataType: 'float32'} 987 } 988 } 989 } 990 }, 991 { 992 'name': 993 'reshape (unsqueeze) float32 2D tensor by adding 1st and 4th dimensions', 994 'graph': { 995 'inputs': { 996 'reshapeInput': { 997 'data': [ 998 -30.0561466217041, 99.56941986083984, 88.04620361328125, 999 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1000 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1001 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1002 27.64195442199707, -96.86306762695312, 83.6834716796875, 1003 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1004 -96.93603515625, 65.34143829345703, 34.835994720458984, 1005 62.01485824584961, -2.8698415756225586, 27.903749465942383 1006 ], 1007 'descriptor': {shape: [4, 6], dataType: 'float32'} 1008 } 1009 }, 1010 'operators': [{ 1011 'name': 'reshape', 1012 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 4, 6, 1]}], 1013 'outputs': 'reshapeOutput' 1014 }], 1015 'expectedOutputs': { 1016 'reshapeOutput': { 1017 'data': [ 1018 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1019 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1020 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1021 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1022 27.64195442199707, -96.86306762695312, 83.6834716796875, 1023 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1024 -96.93603515625, 65.34143829345703, 34.835994720458984, 1025 62.01485824584961, -2.8698415756225586, 27.903749465942383 1026 ], 1027 'descriptor': {shape: [1, 4, 6, 1], dataType: 'float32'} 1028 } 1029 } 1030 } 1031 }, 1032 { 1033 'name': 1034 'reshape (unsqueeze) float32 3D tensor by adding 2nd and 3rd dimensions', 1035 'graph': { 1036 'inputs': { 1037 'reshapeInput': { 1038 'data': [ 1039 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1040 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1041 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1042 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1043 27.64195442199707, -96.86306762695312, 83.6834716796875, 1044 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1045 -96.93603515625, 65.34143829345703, 34.835994720458984, 1046 62.01485824584961, -2.8698415756225586, 27.903749465942383 1047 ], 1048 'descriptor': {shape: [2, 12, 1], dataType: 'float32'} 1049 } 1050 }, 1051 'operators': [{ 1052 'name': 'reshape', 1053 'arguments': 1054 [{'input': 'reshapeInput'}, {'newShape': [2, 1, 1, 12, 1]}], 1055 'outputs': 'reshapeOutput' 1056 }], 1057 'expectedOutputs': { 1058 'reshapeOutput': { 1059 'data': [ 1060 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1061 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1062 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1063 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1064 27.64195442199707, -96.86306762695312, 83.6834716796875, 1065 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1066 -96.93603515625, 65.34143829345703, 34.835994720458984, 1067 62.01485824584961, -2.8698415756225586, 27.903749465942383 1068 ], 1069 'descriptor': {shape: [2, 1, 1, 12, 1], dataType: 'float32'} 1070 } 1071 } 1072 } 1073 }, 1074 { 1075 'name': 'reshape (unsqueeze) float32 4D tensor by adding 2nd dimension', 1076 'graph': { 1077 'inputs': { 1078 'reshapeInput': { 1079 'data': [ 1080 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1081 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1082 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1083 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1084 27.64195442199707, -96.86306762695312, 83.6834716796875, 1085 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1086 -96.93603515625, 65.34143829345703, 34.835994720458984, 1087 62.01485824584961, -2.8698415756225586, 27.903749465942383 1088 ], 1089 'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'} 1090 } 1091 }, 1092 'operators': [{ 1093 'name': 'reshape', 1094 'arguments': [{'input': 'reshapeInput'}, {'newShape': [2, 1, 2, 2, 3]}], 1095 'outputs': 'reshapeOutput' 1096 }], 1097 'expectedOutputs': { 1098 'reshapeOutput': { 1099 'data': [ 1100 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1101 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1102 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1103 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1104 27.64195442199707, -96.86306762695312, 83.6834716796875, 1105 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1106 -96.93603515625, 65.34143829345703, 34.835994720458984, 1107 62.01485824584961, -2.8698415756225586, 27.903749465942383 1108 ], 1109 'descriptor': {shape: [2, 1, 2, 2, 3], dataType: 'float32'} 1110 } 1111 } 1112 } 1113 }, 1114 { 1115 'name': 'reshape (unsqueeze) float32 5D tensor by adding 4th dimension', 1116 'graph': { 1117 'inputs': { 1118 'reshapeInput': { 1119 'data': [ 1120 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1121 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1122 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1123 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1124 27.64195442199707, -96.86306762695312, 83.6834716796875, 1125 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1126 -96.93603515625, 65.34143829345703, 34.835994720458984, 1127 62.01485824584961, -2.8698415756225586, 27.903749465942383 1128 ], 1129 'descriptor': {shape: [2, 1, 4, 3, 1], dataType: 'float32'} 1130 } 1131 }, 1132 'operators': [{ 1133 'name': 'reshape', 1134 'arguments': 1135 [{'input': 'reshapeInput'}, {'newShape': [2, 1, 4, 1, 3, 1]}], 1136 'outputs': 'reshapeOutput' 1137 }], 1138 'expectedOutputs': { 1139 'reshapeOutput': { 1140 'data': [ 1141 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1142 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1143 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1144 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1145 27.64195442199707, -96.86306762695312, 83.6834716796875, 1146 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1147 -96.93603515625, 65.34143829345703, 34.835994720458984, 1148 62.01485824584961, -2.8698415756225586, 27.903749465942383 1149 ], 1150 'descriptor': {shape: [2, 1, 4, 1, 3, 1], dataType: 'float32'} 1151 } 1152 } 1153 } 1154 }, 1155 { 1156 'name': 'reshape (flatten) float32 3D tensor to 2D', 1157 'graph': { 1158 'inputs': { 1159 'reshapeInput': { 1160 'data': [ 1161 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1162 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1163 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1164 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1165 27.64195442199707, -96.86306762695312, 83.6834716796875, 1166 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1167 -96.93603515625, 65.34143829345703, 34.835994720458984, 1168 62.01485824584961, -2.8698415756225586, 27.903749465942383 1169 ], 1170 'descriptor': {shape: [2, 3, 4], dataType: 'float32'} 1171 } 1172 }, 1173 'operators': [{ 1174 'name': 'reshape', 1175 'arguments': [{'input': 'reshapeInput'}, {'newShape': [2, 12]}], 1176 'outputs': 'reshapeOutput' 1177 }], 1178 'expectedOutputs': { 1179 'reshapeOutput': { 1180 'data': [ 1181 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1182 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1183 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1184 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1185 27.64195442199707, -96.86306762695312, 83.6834716796875, 1186 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1187 -96.93603515625, 65.34143829345703, 34.835994720458984, 1188 62.01485824584961, -2.8698415756225586, 27.903749465942383 1189 ], 1190 'descriptor': {shape: [2, 12], dataType: 'float32'} 1191 } 1192 } 1193 } 1194 }, 1195 { 1196 'name': 'reshape (flatten) float32 4D to 2D', 1197 'graph': { 1198 'inputs': { 1199 'reshapeInput': { 1200 'data': [ 1201 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1202 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1203 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1204 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1205 27.64195442199707, -96.86306762695312, 83.6834716796875, 1206 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1207 -96.93603515625, 65.34143829345703, 34.835994720458984, 1208 62.01485824584961, -2.8698415756225586, 27.903749465942383 1209 ], 1210 'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'} 1211 } 1212 }, 1213 'operators': [{ 1214 'name': 'reshape', 1215 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 6]}], 1216 'outputs': 'reshapeOutput' 1217 }], 1218 'expectedOutputs': { 1219 'reshapeOutput': { 1220 'data': [ 1221 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1222 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1223 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1224 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1225 27.64195442199707, -96.86306762695312, 83.6834716796875, 1226 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1227 -96.93603515625, 65.34143829345703, 34.835994720458984, 1228 62.01485824584961, -2.8698415756225586, 27.903749465942383 1229 ], 1230 'descriptor': {shape: [4, 6], dataType: 'float32'} 1231 } 1232 } 1233 } 1234 }, 1235 { 1236 'name': 'reshape (flatten) float32 4D to 2D exclusive 1st dimension', 1237 'graph': { 1238 'inputs': { 1239 'reshapeInput': { 1240 'data': [ 1241 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1242 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1243 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1244 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1245 27.64195442199707, -96.86306762695312, 83.6834716796875, 1246 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1247 -96.93603515625, 65.34143829345703, 34.835994720458984, 1248 62.01485824584961, -2.8698415756225586, 27.903749465942383 1249 ], 1250 'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'} 1251 } 1252 }, 1253 'operators': [{ 1254 'name': 'reshape', 1255 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 24]}], 1256 'outputs': 'reshapeOutput' 1257 }], 1258 'expectedOutputs': { 1259 'reshapeOutput': { 1260 'data': [ 1261 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1262 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1263 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1264 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1265 27.64195442199707, -96.86306762695312, 83.6834716796875, 1266 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1267 -96.93603515625, 65.34143829345703, 34.835994720458984, 1268 62.01485824584961, -2.8698415756225586, 27.903749465942383 1269 ], 1270 'descriptor': {shape: [1, 24], dataType: 'float32'} 1271 } 1272 } 1273 } 1274 }, 1275 { 1276 'name': 'reshape (flatten) float32 4D to 2D exclusive 4th dimension', 1277 'graph': { 1278 'inputs': { 1279 'reshapeInput': { 1280 'data': [ 1281 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1282 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1283 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1284 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1285 27.64195442199707, -96.86306762695312, 83.6834716796875, 1286 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1287 -96.93603515625, 65.34143829345703, 34.835994720458984, 1288 62.01485824584961, -2.8698415756225586, 27.903749465942383 1289 ], 1290 'descriptor': {shape: [2, 2, 2, 3], dataType: 'float32'} 1291 } 1292 }, 1293 'operators': [{ 1294 'name': 'reshape', 1295 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24, 1]}], 1296 'outputs': 'reshapeOutput' 1297 }], 1298 'expectedOutputs': { 1299 'reshapeOutput': { 1300 'data': [ 1301 -30.0561466217041, 99.56941986083984, 88.04620361328125, 1302 -91.87507629394531, -23.7972354888916, -91.28665161132812, 1303 -63.15204620361328, 12.0669527053833, -96.1172866821289, 1304 -44.77365493774414, -80.08650970458984, -64.43756866455078, 1305 27.64195442199707, -96.86306762695312, 83.6834716796875, 1306 50.599483489990234, -20.18765640258789, -1.3904608488082886, 1307 -96.93603515625, 65.34143829345703, 34.835994720458984, 1308 62.01485824584961, -2.8698415756225586, 27.903749465942383 1309 ], 1310 'descriptor': {shape: [24, 1], dataType: 'float32'} 1311 } 1312 } 1313 } 1314 }, 1315 1316 // float16 tests 1317 { 1318 'name': 'reshape float16 tensor to a new shape (reorder all dimensions)', 1319 'graph': { 1320 'inputs': { 1321 'reshapeInput': { 1322 'data': [ 1323 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1324 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1325 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1326 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1327 ], 1328 'descriptor': {shape: [2, 3, 4], dataType: 'float16'} 1329 } 1330 }, 1331 'operators': [{ 1332 'name': 'reshape', 1333 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 2, 3]}], 1334 'outputs': 'reshapeOutput' 1335 }], 1336 'expectedOutputs': { 1337 'reshapeOutput': { 1338 'data': [ 1339 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1340 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1341 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1342 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1343 ], 1344 'descriptor': {shape: [4, 2, 3], dataType: 'float16'} 1345 } 1346 } 1347 } 1348 }, 1349 { 1350 'name': 1351 'reshape float16 constant tensor to a new shape (reorder all dimensions)', 1352 'graph': { 1353 'inputs': { 1354 'reshapeInput': { 1355 'data': [ 1356 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1357 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1358 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1359 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1360 ], 1361 'descriptor': {shape: [2, 3, 4], dataType: 'float16'}, 1362 'constant': true 1363 } 1364 }, 1365 'operators': [{ 1366 'name': 'reshape', 1367 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 2, 3]}], 1368 'outputs': 'reshapeOutput' 1369 }], 1370 'expectedOutputs': { 1371 'reshapeOutput': { 1372 'data': [ 1373 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1374 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1375 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1376 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1377 ], 1378 'descriptor': {shape: [4, 2, 3], dataType: 'float16'} 1379 } 1380 } 1381 } 1382 }, 1383 { 1384 'name': 'reshape float16 tensor to a new shape (reduce dimensions)', 1385 'graph': { 1386 'inputs': { 1387 'reshapeInput': { 1388 'data': [ 1389 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1390 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1391 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1392 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1393 ], 1394 'descriptor': {shape: [4, 1, 1, 1, 6], dataType: 'float16'} 1395 } 1396 }, 1397 'operators': [{ 1398 'name': 'reshape', 1399 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 1, 1, 6]}], 1400 'outputs': 'reshapeOutput' 1401 }], 1402 'expectedOutputs': { 1403 'reshapeOutput': { 1404 'data': [ 1405 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1406 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1407 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1408 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1409 ], 1410 'descriptor': {shape: [4, 1, 1, 6], dataType: 'float16'} 1411 } 1412 } 1413 } 1414 }, 1415 { 1416 'name': 'reshape float16 tensor to a new shape (extend dimensions)', 1417 'graph': { 1418 'inputs': { 1419 'reshapeInput': { 1420 'data': [ 1421 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1422 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1423 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1424 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1425 ], 1426 'descriptor': {shape: [2, 2, 2, 3], dataType: 'float16'} 1427 } 1428 }, 1429 'operators': [{ 1430 'name': 'reshape', 1431 'arguments': [{'input': 'reshapeInput'}, {'newShape': [2, 2, 2, 3, 1]}], 1432 'outputs': 'reshapeOutput' 1433 }], 1434 'expectedOutputs': { 1435 'reshapeOutput': { 1436 'data': [ 1437 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1438 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1439 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1440 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1441 ], 1442 'descriptor': {shape: [2, 2, 2, 3, 1], dataType: 'float16'} 1443 } 1444 } 1445 } 1446 }, 1447 { 1448 'name': 'reshape float16 tensor to a new shape (4D to 4D)', 1449 'graph': { 1450 'inputs': { 1451 'reshapeInput': { 1452 'data': [ 1453 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1454 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1455 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1456 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1457 ], 1458 'descriptor': {shape: [3, 2, 2, 2], dataType: 'float16'} 1459 } 1460 }, 1461 'operators': [{ 1462 'name': 'reshape', 1463 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 2, 3, 1]}], 1464 'outputs': 'reshapeOutput' 1465 }], 1466 'expectedOutputs': { 1467 'reshapeOutput': { 1468 'data': [ 1469 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1470 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1471 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1472 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1473 ], 1474 'descriptor': {shape: [4, 2, 3, 1], dataType: 'float16'} 1475 } 1476 } 1477 } 1478 }, 1479 { 1480 'name': 'reshape float16 tensor to 1D tensor', 1481 'graph': { 1482 'inputs': { 1483 'reshapeInput': { 1484 'data': [ 1485 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1486 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1487 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1488 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1489 ], 1490 'descriptor': {shape: [3, 2, 2, 2], dataType: 'float16'} 1491 } 1492 }, 1493 'operators': [{ 1494 'name': 'reshape', 1495 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 1496 'outputs': 'reshapeOutput' 1497 }], 1498 'expectedOutputs': { 1499 'reshapeOutput': { 1500 'data': [ 1501 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1502 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1503 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1504 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1505 ], 1506 'descriptor': {shape: [24], dataType: 'float16'} 1507 } 1508 } 1509 } 1510 }, 1511 { 1512 'name': 'reshape (squeeze) float16 2D tensor by eliminating one dimension', 1513 'graph': { 1514 'inputs': { 1515 'reshapeInput': { 1516 'data': [ 1517 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1518 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1519 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1520 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1521 ], 1522 'descriptor': {shape: [1, 24], dataType: 'float16'} 1523 } 1524 }, 1525 'operators': [{ 1526 'name': 'reshape', 1527 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 1528 'outputs': 'reshapeOutput' 1529 }], 1530 'expectedOutputs': { 1531 'reshapeOutput': { 1532 'data': [ 1533 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1534 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1535 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1536 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1537 ], 1538 'descriptor': {shape: [24], dataType: 'float16'} 1539 } 1540 } 1541 } 1542 }, 1543 { 1544 'name': 'reshape (squeeze) float16 3D tensor by eliminating one dimension', 1545 'graph': { 1546 'inputs': { 1547 'reshapeInput': { 1548 'data': [ 1549 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1550 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1551 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1552 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1553 ], 1554 'descriptor': {shape: [4, 1, 6], dataType: 'float16'} 1555 } 1556 }, 1557 'operators': [{ 1558 'name': 'reshape', 1559 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 6]}], 1560 'outputs': 'reshapeOutput' 1561 }], 1562 'expectedOutputs': { 1563 'reshapeOutput': { 1564 'data': [ 1565 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1566 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1567 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1568 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1569 ], 1570 'descriptor': {shape: [4, 6], dataType: 'float16'} 1571 } 1572 } 1573 } 1574 }, 1575 { 1576 'name': 'reshape (squeeze) float16 3D tensor by eliminating two dimensions', 1577 'graph': { 1578 'inputs': { 1579 'reshapeInput': { 1580 'data': [ 1581 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1582 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1583 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1584 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1585 ], 1586 'descriptor': {shape: [1, 24, 1], dataType: 'float16'} 1587 } 1588 }, 1589 'operators': [{ 1590 'name': 'reshape', 1591 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 1592 'outputs': 'reshapeOutput' 1593 }], 1594 'expectedOutputs': { 1595 'reshapeOutput': { 1596 'data': [ 1597 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1598 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1599 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1600 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1601 ], 1602 'descriptor': {shape: [24], dataType: 'float16'} 1603 } 1604 } 1605 } 1606 }, 1607 { 1608 'name': 'reshape (squeeze) float16 4D tensor by eliminating two dimensions', 1609 'graph': { 1610 'inputs': { 1611 'reshapeInput': { 1612 'data': [ 1613 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1614 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1615 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1616 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1617 ], 1618 'descriptor': {shape: [1, 4, 1, 6], dataType: 'float16'} 1619 } 1620 }, 1621 'operators': [{ 1622 'name': 'reshape', 1623 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 6]}], 1624 'outputs': 'reshapeOutput' 1625 }], 1626 'expectedOutputs': { 1627 'reshapeOutput': { 1628 'data': [ 1629 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1630 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1631 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1632 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1633 ], 1634 'descriptor': {shape: [4, 6], dataType: 'float16'} 1635 } 1636 } 1637 } 1638 }, 1639 { 1640 'name': 'reshape (squeeze) float16 4D tensor by eliminating all dimensions', 1641 'graph': { 1642 'inputs': { 1643 'reshapeInput': { 1644 'data': [-33.8125], 1645 'descriptor': {shape: [1, 1, 1, 1], dataType: 'float16'} 1646 } 1647 }, 1648 'operators': [{ 1649 'name': 'reshape', 1650 'arguments': [{'input': 'reshapeInput'}, {'newShape': []}], 1651 'outputs': 'reshapeOutput' 1652 }], 1653 'expectedOutputs': { 1654 'reshapeOutput': 1655 {'data': [-33.8125], 'descriptor': {shape: [], dataType: 'float16'}} 1656 } 1657 } 1658 }, 1659 { 1660 'name': 1661 'reshape (squeeze) float16 5D tensor by eliminating four dimensions', 1662 'graph': { 1663 'inputs': { 1664 'reshapeInput': { 1665 'data': [ 1666 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1667 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1668 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1669 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1670 ], 1671 'descriptor': {shape: [1, 1, 1, 24, 1], dataType: 'float16'} 1672 } 1673 }, 1674 'operators': [{ 1675 'name': 'reshape', 1676 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 1677 'outputs': 'reshapeOutput' 1678 }], 1679 'expectedOutputs': { 1680 'reshapeOutput': { 1681 'data': [ 1682 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1683 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1684 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1685 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1686 ], 1687 'descriptor': {shape: [24], dataType: 'float16'} 1688 } 1689 } 1690 } 1691 }, 1692 { 1693 'name': 'reshape (squeeze) float16 2D tensor by eliminating 1st dimension', 1694 'graph': { 1695 'inputs': { 1696 'reshapeInput': { 1697 'data': [ 1698 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1699 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1700 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1701 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1702 ], 1703 'descriptor': {shape: [1, 24], dataType: 'float16'} 1704 } 1705 }, 1706 'operators': [{ 1707 'name': 'reshape', 1708 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 1709 'outputs': 'reshapeOutput' 1710 }], 1711 'expectedOutputs': { 1712 'reshapeOutput': { 1713 'data': [ 1714 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1715 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1716 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1717 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1718 ], 1719 'descriptor': {shape: [24], dataType: 'float16'} 1720 } 1721 } 1722 } 1723 }, 1724 { 1725 'name': 1726 'reshape (squeeze) float16 3D tensor by eliminating 2nd and 3rd dimensions', 1727 'graph': { 1728 'inputs': { 1729 'reshapeInput': { 1730 'data': [ 1731 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1732 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1733 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1734 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1735 ], 1736 'descriptor': {shape: [24, 1, 1], dataType: 'float16'} 1737 } 1738 }, 1739 'operators': [{ 1740 'name': 'reshape', 1741 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24]}], 1742 'outputs': 'reshapeOutput' 1743 }], 1744 'expectedOutputs': { 1745 'reshapeOutput': { 1746 'data': [ 1747 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1748 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1749 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1750 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1751 ], 1752 'descriptor': {shape: [24], dataType: 'float16'} 1753 } 1754 } 1755 } 1756 }, 1757 { 1758 'name': 1759 'reshape (squeeze) float16 4D tensor by eliminating 1st and 4th dimensions', 1760 'graph': { 1761 'inputs': { 1762 'reshapeInput': { 1763 'data': [ 1764 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1765 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1766 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1767 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1768 ], 1769 'descriptor': {shape: [1, 4, 6, 1], dataType: 'float16'} 1770 } 1771 }, 1772 'operators': [{ 1773 'name': 'reshape', 1774 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 6]}], 1775 'outputs': 'reshapeOutput' 1776 }], 1777 'expectedOutputs': { 1778 'reshapeOutput': { 1779 'data': [ 1780 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1781 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1782 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1783 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1784 ], 1785 'descriptor': {shape: [4, 6], dataType: 'float16'} 1786 } 1787 } 1788 } 1789 }, 1790 { 1791 'name': 1792 'reshape (squeeze) float16 5D tensor by eliminating 2nd and 3rd dimensions', 1793 'graph': { 1794 'inputs': { 1795 'reshapeInput': { 1796 'data': [ 1797 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1798 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1799 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1800 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1801 ], 1802 'descriptor': {shape: [2, 1, 1, 12, 1], dataType: 'float16'} 1803 } 1804 }, 1805 'operators': [{ 1806 'name': 'reshape', 1807 'arguments': [{'input': 'reshapeInput'}, {'newShape': [2, 12, 1]}], 1808 'outputs': 'reshapeOutput' 1809 }], 1810 'expectedOutputs': { 1811 'reshapeOutput': { 1812 'data': [ 1813 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1814 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1815 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1816 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1817 ], 1818 'descriptor': {shape: [2, 12, 1], dataType: 'float16'} 1819 } 1820 } 1821 } 1822 }, 1823 { 1824 'name': 1825 'reshape (squeeze) float16 5D tensor by eliminating 1st, 2nd and 5th dimensions', 1826 'graph': { 1827 'inputs': { 1828 'reshapeInput': { 1829 'data': [ 1830 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1831 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1832 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1833 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1834 ], 1835 'descriptor': {shape: [1, 1, 1, 24, 1], dataType: 'float16'} 1836 } 1837 }, 1838 'operators': [{ 1839 'name': 'reshape', 1840 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 24]}], 1841 'outputs': 'reshapeOutput' 1842 }], 1843 'expectedOutputs': { 1844 'reshapeOutput': { 1845 'data': [ 1846 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1847 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1848 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1849 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1850 ], 1851 'descriptor': {shape: [1, 24], dataType: 'float16'} 1852 } 1853 } 1854 } 1855 }, 1856 { 1857 'name': 'reshape (unsqueeze) float16 0D tensor to 4D', 1858 'graph': { 1859 'inputs': { 1860 'reshapeInput': 1861 {'data': [-33.8125], 'descriptor': {shape: [], dataType: 'float16'}} 1862 }, 1863 'operators': [{ 1864 'name': 'reshape', 1865 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 1, 1, 1]}], 1866 'outputs': 'reshapeOutput' 1867 }], 1868 'expectedOutputs': { 1869 'reshapeOutput': { 1870 'data': [-33.8125], 1871 'descriptor': {shape: [1, 1, 1, 1], dataType: 'float16'} 1872 } 1873 } 1874 } 1875 }, 1876 { 1877 'name': 'reshape (unsqueeze) float16 1D tensor by adding one dimension', 1878 'graph': { 1879 'inputs': { 1880 'reshapeInput': { 1881 'data': [ 1882 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1883 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1884 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1885 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1886 ], 1887 'descriptor': {shape: [24], dataType: 'float16'} 1888 } 1889 }, 1890 'operators': [{ 1891 'name': 'reshape', 1892 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 24]}], 1893 'outputs': 'reshapeOutput' 1894 }], 1895 'expectedOutputs': { 1896 'reshapeOutput': { 1897 'data': [ 1898 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1899 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1900 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1901 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1902 ], 1903 'descriptor': {shape: [1, 24], dataType: 'float16'} 1904 } 1905 } 1906 } 1907 }, 1908 { 1909 'name': 'reshape (unsqueeze) float16 1D tensor by adding two dimensions', 1910 'graph': { 1911 'inputs': { 1912 'reshapeInput': { 1913 'data': [ 1914 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1915 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1916 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1917 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1918 ], 1919 'descriptor': {shape: [24], dataType: 'float16'} 1920 } 1921 }, 1922 'operators': [{ 1923 'name': 'reshape', 1924 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 24, 1]}], 1925 'outputs': 'reshapeOutput' 1926 }], 1927 'expectedOutputs': { 1928 'reshapeOutput': { 1929 'data': [ 1930 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1931 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1932 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1933 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1934 ], 1935 'descriptor': {shape: [1, 24, 1], dataType: 'float16'} 1936 } 1937 } 1938 } 1939 }, 1940 { 1941 'name': 'reshape (unsqueeze) float16 1D tensor to 5D', 1942 'graph': { 1943 'inputs': { 1944 'reshapeInput': { 1945 'data': [ 1946 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1947 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1948 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1949 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1950 ], 1951 'descriptor': {shape: [24], dataType: 'float16'} 1952 } 1953 }, 1954 'operators': [{ 1955 'name': 'reshape', 1956 'arguments': 1957 [{'input': 'reshapeInput'}, {'newShape': [1, 1, 1, 24, 1]}], 1958 'outputs': 'reshapeOutput' 1959 }], 1960 'expectedOutputs': { 1961 'reshapeOutput': { 1962 'data': [ 1963 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1964 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1965 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1966 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1967 ], 1968 'descriptor': {shape: [1, 1, 1, 24, 1], dataType: 'float16'} 1969 } 1970 } 1971 } 1972 }, 1973 { 1974 'name': 1975 'reshape (unsqueeze) float16 1D tensor by adding 2nd and 3rd dimensions', 1976 'graph': { 1977 'inputs': { 1978 'reshapeInput': { 1979 'data': [ 1980 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1981 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1982 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1983 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 1984 ], 1985 'descriptor': {shape: [24], dataType: 'float16'} 1986 } 1987 }, 1988 'operators': [{ 1989 'name': 'reshape', 1990 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24, 1, 1]}], 1991 'outputs': 'reshapeOutput' 1992 }], 1993 'expectedOutputs': { 1994 'reshapeOutput': { 1995 'data': [ 1996 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 1997 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 1998 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 1999 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2000 ], 2001 'descriptor': {shape: [24, 1, 1], dataType: 'float16'} 2002 } 2003 } 2004 } 2005 }, 2006 { 2007 'name': 'reshape (unsqueeze) float16 2D tensor by adding one dimension', 2008 'graph': { 2009 'inputs': { 2010 'reshapeInput': { 2011 'data': [ 2012 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2013 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2014 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2015 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2016 ], 2017 'descriptor': {shape: [4, 6], dataType: 'float16'} 2018 } 2019 }, 2020 'operators': [{ 2021 'name': 'reshape', 2022 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 1, 6]}], 2023 'outputs': 'reshapeOutput' 2024 }], 2025 'expectedOutputs': { 2026 'reshapeOutput': { 2027 'data': [ 2028 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2029 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2030 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2031 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2032 ], 2033 'descriptor': {shape: [4, 1, 6], dataType: 'float16'} 2034 } 2035 } 2036 } 2037 }, 2038 { 2039 'name': 'reshape (unsqueeze) float16 2D tensor by adding two dimensions', 2040 'graph': { 2041 'inputs': { 2042 'reshapeInput': { 2043 'data': [ 2044 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2045 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2046 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2047 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2048 ], 2049 'descriptor': {shape: [4, 6], dataType: 'float16'} 2050 } 2051 }, 2052 'operators': [{ 2053 'name': 'reshape', 2054 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 4, 1, 6]}], 2055 'outputs': 'reshapeOutput' 2056 }], 2057 'expectedOutputs': { 2058 'reshapeOutput': { 2059 'data': [ 2060 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2061 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2062 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2063 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2064 ], 2065 'descriptor': {shape: [1, 4, 1, 6], dataType: 'float16'} 2066 } 2067 } 2068 } 2069 }, 2070 { 2071 'name': 'reshape (unsqueeze) float16 2D tensor by adding 1st dimension', 2072 'graph': { 2073 'inputs': { 2074 'reshapeInput': { 2075 'data': [ 2076 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2077 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2078 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2079 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2080 ], 2081 'descriptor': {shape: [24], dataType: 'float16'} 2082 } 2083 }, 2084 'operators': [{ 2085 'name': 'reshape', 2086 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 24]}], 2087 'outputs': 'reshapeOutput' 2088 }], 2089 'expectedOutputs': { 2090 'reshapeOutput': { 2091 'data': [ 2092 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2093 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2094 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2095 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2096 ], 2097 'descriptor': {shape: [1, 24], dataType: 'float16'} 2098 } 2099 } 2100 } 2101 }, 2102 { 2103 'name': 2104 'reshape (unsqueeze) float16 2D tensor by adding 1st and 4th dimensions', 2105 'graph': { 2106 'inputs': { 2107 'reshapeInput': { 2108 'data': [ 2109 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2110 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2111 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2112 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2113 ], 2114 'descriptor': {shape: [4, 6], dataType: 'float16'} 2115 } 2116 }, 2117 'operators': [{ 2118 'name': 'reshape', 2119 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 4, 6, 1]}], 2120 'outputs': 'reshapeOutput' 2121 }], 2122 'expectedOutputs': { 2123 'reshapeOutput': { 2124 'data': [ 2125 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2126 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2127 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2128 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2129 ], 2130 'descriptor': {shape: [1, 4, 6, 1], dataType: 'float16'} 2131 } 2132 } 2133 } 2134 }, 2135 { 2136 'name': 2137 'reshape (unsqueeze) float16 3D tensor by adding 2nd and 3rd dimensions', 2138 'graph': { 2139 'inputs': { 2140 'reshapeInput': { 2141 'data': [ 2142 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2143 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2144 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2145 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2146 ], 2147 'descriptor': {shape: [2, 12, 1], dataType: 'float16'} 2148 } 2149 }, 2150 'operators': [{ 2151 'name': 'reshape', 2152 'arguments': 2153 [{'input': 'reshapeInput'}, {'newShape': [2, 1, 1, 12, 1]}], 2154 'outputs': 'reshapeOutput' 2155 }], 2156 'expectedOutputs': { 2157 'reshapeOutput': { 2158 'data': [ 2159 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2160 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2161 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2162 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2163 ], 2164 'descriptor': {shape: [2, 1, 1, 12, 1], dataType: 'float16'} 2165 } 2166 } 2167 } 2168 }, 2169 { 2170 'name': 'reshape (unsqueeze) float16 4D tensor by adding 2nd dimension', 2171 'graph': { 2172 'inputs': { 2173 'reshapeInput': { 2174 'data': [ 2175 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2176 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2177 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2178 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2179 ], 2180 'descriptor': {shape: [2, 2, 2, 3], dataType: 'float16'} 2181 } 2182 }, 2183 'operators': [{ 2184 'name': 'reshape', 2185 'arguments': [{'input': 'reshapeInput'}, {'newShape': [2, 1, 2, 2, 3]}], 2186 'outputs': 'reshapeOutput' 2187 }], 2188 'expectedOutputs': { 2189 'reshapeOutput': { 2190 'data': [ 2191 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2192 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2193 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2194 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2195 ], 2196 'descriptor': {shape: [2, 1, 2, 2, 3], dataType: 'float16'} 2197 } 2198 } 2199 } 2200 }, 2201 { 2202 'name': 'reshape (unsqueeze) float16 5D tensor by adding 4th dimension', 2203 'graph': { 2204 'inputs': { 2205 'reshapeInput': { 2206 'data': [ 2207 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2208 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2209 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2210 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2211 ], 2212 'descriptor': {shape: [2, 1, 4, 3, 1], dataType: 'float16'} 2213 } 2214 }, 2215 'operators': [{ 2216 'name': 'reshape', 2217 'arguments': 2218 [{'input': 'reshapeInput'}, {'newShape': [2, 1, 4, 1, 3, 1]}], 2219 'outputs': 'reshapeOutput' 2220 }], 2221 'expectedOutputs': { 2222 'reshapeOutput': { 2223 'data': [ 2224 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2225 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2226 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2227 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2228 ], 2229 'descriptor': {shape: [2, 1, 4, 1, 3, 1], dataType: 'float16'} 2230 } 2231 } 2232 } 2233 }, 2234 { 2235 'name': 'reshape (flatten) float16 3D tensor to 2D', 2236 'graph': { 2237 'inputs': { 2238 'reshapeInput': { 2239 'data': [ 2240 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2241 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2242 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2243 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2244 ], 2245 'descriptor': {shape: [2, 3, 4], dataType: 'float16'} 2246 } 2247 }, 2248 'operators': [{ 2249 'name': 'reshape', 2250 'arguments': [{'input': 'reshapeInput'}, {'newShape': [2, 12]}], 2251 'outputs': 'reshapeOutput' 2252 }], 2253 'expectedOutputs': { 2254 'reshapeOutput': { 2255 'data': [ 2256 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2257 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2258 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2259 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2260 ], 2261 'descriptor': {shape: [2, 12], dataType: 'float16'} 2262 } 2263 } 2264 } 2265 }, 2266 { 2267 'name': 'reshape (flatten) float16 4D to 2D', 2268 'graph': { 2269 'inputs': { 2270 'reshapeInput': { 2271 'data': [ 2272 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2273 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2274 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2275 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2276 ], 2277 'descriptor': {shape: [2, 2, 2, 3], dataType: 'float16'} 2278 } 2279 }, 2280 'operators': [{ 2281 'name': 'reshape', 2282 'arguments': [{'input': 'reshapeInput'}, {'newShape': [4, 6]}], 2283 'outputs': 'reshapeOutput' 2284 }], 2285 'expectedOutputs': { 2286 'reshapeOutput': { 2287 'data': [ 2288 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2289 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2290 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2291 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2292 ], 2293 'descriptor': {shape: [4, 6], dataType: 'float16'} 2294 } 2295 } 2296 } 2297 }, 2298 { 2299 'name': 'reshape (flatten) float16 4D to 2D exclusive 1st dimension', 2300 'graph': { 2301 'inputs': { 2302 'reshapeInput': { 2303 'data': [ 2304 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2305 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2306 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2307 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2308 ], 2309 'descriptor': {shape: [2, 2, 2, 3], dataType: 'float16'} 2310 } 2311 }, 2312 'operators': [{ 2313 'name': 'reshape', 2314 'arguments': [{'input': 'reshapeInput'}, {'newShape': [1, 24]}], 2315 'outputs': 'reshapeOutput' 2316 }], 2317 'expectedOutputs': { 2318 'reshapeOutput': { 2319 'data': [ 2320 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2321 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2322 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2323 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2324 ], 2325 'descriptor': {shape: [1, 24], dataType: 'float16'} 2326 } 2327 } 2328 } 2329 }, 2330 { 2331 'name': 'reshape (flatten) float16 4D to 2D exclusive 4th dimension', 2332 'graph': { 2333 'inputs': { 2334 'reshapeInput': { 2335 'data': [ 2336 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2337 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2338 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2339 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2340 ], 2341 'descriptor': {shape: [2, 2, 2, 3], dataType: 'float16'} 2342 } 2343 }, 2344 'operators': [{ 2345 'name': 'reshape', 2346 'arguments': [{'input': 'reshapeInput'}, {'newShape': [24, 1]}], 2347 'outputs': 'reshapeOutput' 2348 }], 2349 'expectedOutputs': { 2350 'reshapeOutput': { 2351 'data': [ 2352 -30.0625, 99.5625, 88.0625, -91.875, -23.796875, -91.3125, 2353 -63.15625, 12.0703125, -96.125, -44.78125, -80.0625, -64.4375, 2354 27.640625, -96.875, 83.6875, 50.59375, -20.1875, -1.390625, 2355 -96.9375, 65.3125, 34.84375, 62, -2.869140625, 27.90625 2356 ], 2357 'descriptor': {shape: [24, 1], dataType: 'float16'} 2358 } 2359 } 2360 } 2361 } 2362 ]; 2363 2364 webnn_conformance_test(reshapeTests, buildAndExecuteGraph, getZeroULPTolerance);