1#!/usr/bin/env python3 2# 3# SPDX-FileCopyrightText: Copyright 2010-2024 Arm Limited and/or its affiliates <open-source-office@arm.com> 4# 5# SPDX-License-Identifier: Apache-2.0 6# 7# Licensed under the Apache License, Version 2.0 (the License); you may 8# not use this file except in compliance with the License. 9# You may obtain a copy of the License at 10# 11# www.apache.org/licenses/LICENSE-2.0 12# 13# Unless required by applicable law or agreed to in writing, software 14# distributed under the License is distributed on an AS IS BASIS, WITHOUT 15# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 16# See the License for the specific language governing permissions and 17# limitations under the License. 18# 19import os 20os.environ["TF_USE_LEGACY_KERAS"]="1" 21import sys 22import argparse 23 24from packaging import version 25 26from test_settings import TestSettings 27from conv_settings import ConvSettings 28from pooling_settings import PoolingSettings 29from softmax_settings import SoftmaxSettings 30from svdf_settings import SVDFSettings 31from add_mul_settings import AddMulSettings 32from lstm_settings import LSTMSettings 33from fully_connected_settings import FullyConnectedSettings 34 35import tensorflow as tf 36 37 38def parse_args() -> argparse.Namespace: 39 parser = argparse.ArgumentParser(description="Generate input and refererence output data for unittests." 40 " It can regenerate all data, load all stored data or a combination of it.") 41 parser.add_argument('--dataset', type=str, default=None, help="Name of generated test set.") 42 parser.add_argument('--regenerate-weights', action='store_true', help="Regenerate and store new weights.") 43 parser.add_argument('--regenerate-input', action='store_true', help="Regenerate and store new input.") 44 parser.add_argument('--regenerate-biases', action='store_true', help="Regenerate and store new biases.") 45 parser.add_argument('-a', '--regenerate-all', action='store_true', help="Regenerate and store all data.") 46 parser.add_argument('-t', 47 '--testtype', 48 type=str, 49 default=None, 50 choices=[ 51 'conv', 'depthwise_conv', 'avgpool', 'maxpool', 'fully_connected', 'softmax', 'svdf', 'add', 52 'mul', 'lstm', 'transpose_conv' 53 ], 54 help='Type of test. There are the operators that have unit tests.') 55 parser.add_argument('--run-all-testsets', 56 action='store_true', 57 help="Run the script for all existing test " 58 "sets. Regenerate all, partially all or no input data (output may still change, depending on" 59 " changes in script) depending on regenerate flags. If used together with the -t flag, only" 60 " tests of that type will be run.") 61 parser.add_argument('--schema-file', type=str, help="Path to schema file. This may be needed for some tests.") 62 parser.add_argument('--interpreter', type=str, default='tensorflow', choices=['tensorflow', 'tflite_runtime', 63 'tflite_micro'], 64 help="Use interpreter from tensorflow or tflite_runtime. See README for more info.") 65 66 return parser.parse_args() 67 68 69def load_testdata_sets(regenerate_input, regenerate_weights, regenerate_biases, schema_file, interpreter) -> dict: 70 """ 71 Add all new testdata sets here 72 """ 73 testdata_sets = {} 74 75 type_of_test = 'conv' 76 dataset = 'basic' 77 testdata_sets[dataset] = ConvSettings(dataset, 78 type_of_test, 79 regenerate_weights, 80 regenerate_input, 81 regenerate_biases, 82 schema_file, 83 in_ch=1, 84 out_ch=1, 85 x_in=5, 86 y_in=8, 87 w_x=2, 88 w_y=4, 89 stride_x=1, 90 stride_y=1, 91 pad=False, 92 interpreter=interpreter) 93 dataset = 'stride2pad1' 94 testdata_sets[dataset] = ConvSettings(dataset, 95 type_of_test, 96 regenerate_weights, 97 regenerate_input, 98 regenerate_biases, 99 schema_file, 100 in_ch=1, 101 out_ch=1, 102 x_in=7, 103 y_in=7, 104 w_x=3, 105 w_y=3, 106 stride_x=2, 107 stride_y=2, 108 pad=True, 109 interpreter=interpreter) 110 dataset = 'kernel1x1' 111 testdata_sets[dataset] = ConvSettings(dataset, 112 type_of_test, 113 regenerate_weights, 114 regenerate_input, 115 regenerate_biases, 116 schema_file, 117 in_ch=19, 118 out_ch=7, 119 x_in=7, 120 y_in=5, 121 w_x=1, 122 w_y=1, 123 stride_x=1, 124 stride_y=1, 125 pad=False, 126 bias_min=TestSettings.INT8_MIN, 127 bias_max=TestSettings.INT8_MAX, 128 out_activation_min=-126, 129 out_activation_max=127, 130 batches=2, 131 interpreter=interpreter) 132 dataset = 'kernel1x1_stride_x' 133 testdata_sets[dataset] = ConvSettings(dataset, 134 type_of_test, 135 regenerate_weights, 136 regenerate_input, 137 regenerate_biases, 138 schema_file, 139 in_ch=9, 140 out_ch=5, 141 x_in=7, 142 y_in=4, 143 w_x=1, 144 w_y=1, 145 stride_x=3, 146 stride_y=1, 147 pad=False, 148 out_activation_min=-126, 149 out_activation_max=127, 150 batches=2, 151 interpreter=interpreter) 152 dataset = 'kernel1x1_stride_x_y' 153 testdata_sets[dataset] = ConvSettings(dataset, 154 type_of_test, 155 regenerate_weights, 156 regenerate_input, 157 regenerate_biases, 158 schema_file, 159 in_ch=23, 160 out_ch=15, 161 randmin=0, 162 x_in=7, 163 y_in=6, 164 w_x=1, 165 w_y=1, 166 stride_x=2, 167 stride_y=2, 168 pad=False, 169 out_activation_min=-6, 170 out_activation_max=127, 171 batches=3, 172 interpreter=interpreter) 173 dataset = 'kernel1x1_stride_x_y_1' 174 testdata_sets[dataset] = ConvSettings(dataset, 175 type_of_test, 176 regenerate_weights, 177 regenerate_input, 178 regenerate_biases, 179 schema_file, 180 in_ch=5, 181 out_ch=5, 182 x_in=4, 183 y_in=4, 184 w_x=1, 185 w_y=1, 186 stride_x=2, 187 stride_y=2, 188 pad=False, 189 out_activation_min=-126, 190 out_activation_max=127, 191 batches=2, 192 interpreter=interpreter) 193 dataset = 'kernel1x1_stride_x_y_2' 194 testdata_sets[dataset] = ConvSettings(dataset, 195 type_of_test, 196 regenerate_weights, 197 regenerate_input, 198 regenerate_biases, 199 schema_file, 200 in_ch=5, 201 out_ch=5, 202 x_in=4, 203 y_in=4, 204 w_x=1, 205 w_y=1, 206 stride_x=3, 207 stride_y=3, 208 pad=False, 209 out_activation_min=-126, 210 out_activation_max=127, 211 batches=2, 212 interpreter=interpreter) 213 dataset = 'conv_3' 214 testdata_sets[dataset] = ConvSettings(dataset, 215 type_of_test, 216 regenerate_weights, 217 regenerate_input, 218 regenerate_biases, 219 schema_file, 220 in_ch=3, 221 out_ch=1, 222 x_in=10, 223 y_in=49, 224 w_x=4, 225 w_y=10, 226 stride_x=1, 227 stride_y=2, 228 pad=True, 229 out_activation_min=-127, 230 out_activation_max=127, 231 interpreter=interpreter) 232 dataset = 'conv_1_x_n_1' # left and right pad, no non-padded elements 233 testdata_sets[dataset] = ConvSettings(dataset, 234 type_of_test, 235 regenerate_weights, 236 regenerate_input, 237 regenerate_biases, 238 schema_file, 239 in_ch=4, 240 out_ch=3, 241 x_in=2, 242 y_in=1, 243 w_x=3, 244 w_y=1, 245 stride_x=1, 246 stride_y=1, 247 pad=True, 248 out_activation_min=-127, 249 out_activation_max=127, 250 batches=2, 251 interpreter=interpreter) 252 dataset = 'conv_1_x_n_2' # no pad 253 testdata_sets[dataset] = ConvSettings(dataset, 254 type_of_test, 255 regenerate_weights, 256 regenerate_input, 257 regenerate_biases, 258 schema_file, 259 in_ch=4, 260 out_ch=3, 261 x_in=296, 262 y_in=1, 263 w_x=48, 264 w_y=1, 265 stride_x=2, 266 stride_y=1, 267 pad=False, 268 out_activation_min=-111, 269 out_activation_max=127, 270 interpreter=interpreter) 271 dataset = 'conv_1_x_n_3' 272 testdata_sets[dataset] = ConvSettings(dataset, 273 type_of_test, 274 regenerate_weights, 275 regenerate_input, 276 regenerate_biases, 277 schema_file, 278 in_ch=4, 279 out_ch=1, 280 x_in=296, 281 y_in=1, 282 w_x=48, 283 w_y=1, 284 stride_x=2, 285 stride_y=1, 286 pad=True, 287 out_activation_min=-111, 288 out_activation_max=127, 289 interpreter=interpreter) 290 dataset = 'conv_1_x_n_4' # 0 left pad, 1 right pad 291 testdata_sets[dataset] = ConvSettings(dataset, 292 type_of_test, 293 regenerate_weights, 294 regenerate_input, 295 regenerate_biases, 296 schema_file, 297 in_ch=4, 298 out_ch=4, 299 x_in=16, 300 y_in=1, 301 w_x=3, 302 w_y=1, 303 stride_x=2, 304 stride_y=1, 305 pad=True, 306 out_activation_min=-88, 307 out_activation_max=127, 308 interpreter=interpreter) 309 dataset = 'conv_1_x_n_5' 310 testdata_sets[dataset] = ConvSettings(dataset, 311 type_of_test, 312 regenerate_weights, 313 regenerate_input, 314 regenerate_biases, 315 schema_file, 316 in_ch=4, 317 out_ch=1, 318 x_in=17, 319 y_in=1, 320 w_x=3, 321 w_y=1, 322 stride_x=3, 323 stride_y=1, 324 pad=True, 325 out_activation_min=-88, 326 out_activation_max=127, 327 interpreter=interpreter) 328 dataset = 'conv_1_x_n_6_generic' # right_pad_num + no_pad_num + left_pad_num != output_x 329 testdata_sets[dataset] = ConvSettings(dataset, 330 type_of_test, 331 regenerate_weights, 332 regenerate_input, 333 regenerate_biases, 334 schema_file, 335 in_ch=1, 336 out_ch=16, 337 x_in=4, 338 y_in=1, 339 w_x=8, 340 w_y=1, 341 stride_x=4, 342 stride_y=1, 343 pad=True, 344 out_activation_min=-125, 345 out_activation_max=126, 346 interpreter=interpreter) 347 dataset = 'conv_1_x_n_7' 348 testdata_sets[dataset] = ConvSettings(dataset, 349 type_of_test, 350 regenerate_weights, 351 regenerate_input, 352 regenerate_biases, 353 schema_file, 354 in_ch=20, 355 out_ch=15, 356 x_in=148, 357 y_in=1, 358 w_x=32, 359 w_y=1, 360 stride_x=1, 361 stride_y=1, 362 pad=True, 363 out_activation_min=-127, 364 out_activation_max=127, 365 batches=2, 366 interpreter=interpreter) 367 dataset = 'conv_1_x_n_8' 368 testdata_sets[dataset] = ConvSettings(dataset, 369 type_of_test, 370 regenerate_weights, 371 regenerate_input, 372 regenerate_biases, 373 schema_file, 374 in_ch=12, 375 out_ch=10, 376 x_in=148, 377 y_in=1, 378 w_x=48, 379 w_y=1, 380 stride_x=2, 381 stride_y=1, 382 pad=True, 383 out_activation_min=-127, 384 out_activation_max=127, 385 batches=2, 386 interpreter=interpreter) 387 dataset = 'conv_2' 388 testdata_sets[dataset] = ConvSettings(dataset, 389 type_of_test, 390 regenerate_weights, 391 regenerate_input, 392 regenerate_biases, 393 schema_file, 394 in_ch=2, 395 out_ch=4, 396 x_in=6, 397 y_in=3, 398 w_x=3, 399 w_y=3, 400 stride_x=1, 401 stride_y=1, 402 pad=True, 403 out_activation_min=-101, 404 out_activation_max=127, 405 interpreter=interpreter) 406 dataset = 'conv_4' # batches > 2 407 testdata_sets[dataset] = ConvSettings(dataset, 408 type_of_test, 409 regenerate_weights, 410 regenerate_input, 411 regenerate_biases, 412 schema_file, 413 in_ch=3, 414 out_ch=3, 415 x_in=5, 416 y_in=5, 417 w_x=2, 418 w_y=3, 419 stride_x=2, 420 stride_y=2, 421 pad=False, 422 out_activation_min=-109, 423 out_activation_max=127, 424 batches=3, 425 interpreter=interpreter) 426 dataset = 'conv_5' 427 testdata_sets[dataset] = ConvSettings(dataset, 428 type_of_test, 429 regenerate_weights, 430 regenerate_input, 431 regenerate_biases, 432 schema_file, 433 in_ch=128, 434 out_ch=1, 435 x_in=128, 436 y_in=1, 437 w_x=3, 438 w_y=3, 439 stride_x=4, 440 stride_y=4, 441 pad=True, 442 out_activation_min=-88, 443 out_activation_max=127, 444 interpreter=interpreter) 445 dataset = 'conv_out_activation' 446 testdata_sets[dataset] = ConvSettings(dataset, 447 type_of_test, 448 regenerate_weights, 449 regenerate_input, 450 regenerate_biases, 451 schema_file, 452 in_ch=4, 453 out_ch=2, 454 x_in=3, 455 y_in=3, 456 w_x=3, 457 w_y=3, 458 stride_x=1, 459 stride_y=1, 460 pad=True, 461 out_activation_min=-61, 462 out_activation_max=107, 463 interpreter=interpreter) 464 dataset = 'conv_dilation_golden' 465 testdata_sets[dataset] = ConvSettings(dataset, 466 type_of_test, 467 regenerate_weights, 468 regenerate_input, 469 regenerate_biases, 470 schema_file, 471 in_ch=1, 472 batches=2, 473 out_ch=3, 474 x_in=6, 475 y_in=4, 476 w_x=2, 477 w_y=2, 478 stride_x=1, 479 stride_y=1, 480 pad=True, 481 out_activation_min=-128, 482 out_activation_max=127, 483 dilation_x=3, 484 dilation_y=2, 485 interpreter=interpreter) 486 dataset = 'conv_2x2_dilation' 487 testdata_sets[dataset] = ConvSettings(dataset, 488 type_of_test, 489 regenerate_weights, 490 regenerate_input, 491 regenerate_biases, 492 schema_file, 493 in_ch=2, 494 out_ch=2, 495 x_in=10, 496 y_in=10, 497 w_x=3, 498 w_y=3, 499 stride_x=1, 500 stride_y=1, 501 pad=False, 502 out_activation_min=-61, 503 out_activation_max=107, 504 dilation_x=2, 505 dilation_y=2, 506 interpreter=interpreter) 507 dataset = 'conv_2x3_dilation' 508 testdata_sets[dataset] = ConvSettings(dataset, 509 type_of_test, 510 regenerate_weights, 511 regenerate_input, 512 regenerate_biases, 513 schema_file, 514 in_ch=2, 515 out_ch=2, 516 x_in=3, 517 y_in=3, 518 w_x=3, 519 w_y=3, 520 stride_x=1, 521 stride_y=1, 522 pad=True, 523 out_activation_min=-61, 524 out_activation_max=107, 525 dilation_x=2, 526 dilation_y=2, 527 interpreter=interpreter) 528 dataset = 'conv_3x2_dilation' 529 testdata_sets[dataset] = ConvSettings(dataset, 530 type_of_test, 531 regenerate_weights, 532 regenerate_input, 533 regenerate_biases, 534 schema_file, 535 in_ch=2, 536 out_ch=2, 537 x_in=3, 538 y_in=3, 539 w_x=3, 540 w_y=3, 541 stride_x=1, 542 stride_y=1, 543 pad=True, 544 out_activation_min=-61, 545 out_activation_max=107, 546 dilation_x=3, 547 dilation_y=2, 548 interpreter=interpreter) 549 dataset = 'conv_2x2_dilation_5x5_input' 550 testdata_sets[dataset] = ConvSettings(dataset, 551 type_of_test, 552 regenerate_weights, 553 regenerate_input, 554 regenerate_biases, 555 schema_file, 556 in_ch=2, 557 out_ch=2, 558 x_in=5, 559 y_in=5, 560 w_x=3, 561 w_y=3, 562 stride_x=1, 563 stride_y=1, 564 pad=True, 565 out_activation_min=-61, 566 out_activation_max=107, 567 dilation_x=2, 568 dilation_y=2, 569 interpreter=interpreter) 570 dataset = 'conv_3x3_dilation_5x5_input' 571 testdata_sets[dataset] = ConvSettings(dataset, 572 type_of_test, 573 regenerate_weights, 574 regenerate_input, 575 regenerate_biases, 576 schema_file, 577 in_ch=2, 578 out_ch=2, 579 x_in=9, 580 y_in=11, 581 w_x=3, 582 w_y=3, 583 stride_x=1, 584 stride_y=1, 585 pad=True, 586 out_activation_min=-61, 587 out_activation_max=107, 588 dilation_x=2, 589 dilation_y=2, 590 interpreter=interpreter) 591 dataset = 'int16xint8' 592 testdata_sets[dataset] = ConvSettings(dataset, 593 type_of_test, 594 regenerate_weights, 595 regenerate_input, 596 regenerate_biases, 597 schema_file, 598 in_ch=55, 599 out_ch=4, 600 x_in=10, 601 y_in=8, 602 w_x=9, 603 w_y=4, 604 stride_x=1, 605 stride_y=1, 606 pad=False, 607 generate_bias=False, 608 randmin=TestSettings.INT16_MIN, 609 randmax=TestSettings.INT16_MAX, 610 out_activation_min=TestSettings.INT16_MIN, 611 out_activation_max=TestSettings.INT16_MAX, 612 int16xint8=True, 613 interpreter=interpreter) 614 dataset = 'int16xint8_spill' 615 testdata_sets[dataset] = ConvSettings(dataset, 616 type_of_test, 617 regenerate_weights, 618 regenerate_input, 619 regenerate_biases, 620 schema_file, 621 in_ch=55, 622 out_ch=9, 623 x_in=10, 624 y_in=8, 625 w_x=9, 626 w_y=4, 627 stride_x=1, 628 stride_y=1, 629 pad=False, 630 generate_bias=False, 631 randmin=TestSettings.INT16_MAX - 100, 632 randmax=TestSettings.INT16_MAX, 633 out_activation_min=TestSettings.INT16_MAX - 100, 634 out_activation_max=TestSettings.INT16_MAX, 635 bias_min=TestSettings.INT64_MIN, 636 bias_max=TestSettings.INT64_MAX, 637 int16xint8=True, 638 interpreter=interpreter, 639 weights_min=100) 640 dataset = 'int16xint8_spill2' 641 testdata_sets[dataset] = ConvSettings(dataset, 642 type_of_test, 643 regenerate_weights, 644 regenerate_input, 645 regenerate_biases, 646 schema_file, 647 in_ch=12, 648 out_ch=9, 649 x_in=10, 650 y_in=8, 651 w_x=9, 652 w_y=4, 653 stride_x=1, 654 stride_y=1, 655 pad=False, 656 generate_bias=False, 657 randmin=TestSettings.INT16_MAX - 100, 658 randmax=TestSettings.INT16_MAX, 659 out_activation_min=TestSettings.INT16_MAX - 100, 660 out_activation_max=TestSettings.INT16_MAX, 661 bias_min=TestSettings.INT64_MIN, 662 bias_max=TestSettings.INT64_MAX, 663 int16xint8=True, 664 interpreter=interpreter, 665 weights_min=100) 666 dataset = 'requantize_s64' 667 testdata_sets[dataset] = ConvSettings(dataset, 668 type_of_test, 669 regenerate_weights, 670 regenerate_input, 671 regenerate_biases, 672 schema_file, 673 in_ch=8, 674 out_ch=8, 675 x_in=4, 676 y_in=4, 677 w_x=2, 678 w_y=2, 679 stride_x=1, 680 stride_y=1, 681 pad=False, 682 generate_bias=True, 683 out_activation_min=TestSettings.INT16_MIN, 684 out_activation_max=TestSettings.INT16_MAX, 685 int16xint8=True, 686 bias_min=-0x300, 687 bias_max=TestSettings.INT32_MAX + 1000, 688 interpreter=interpreter) 689 dataset = 'int16xint8_dilation_1' 690 testdata_sets[dataset] = ConvSettings(dataset, 691 type_of_test, 692 regenerate_weights, 693 regenerate_input, 694 regenerate_biases, 695 schema_file, 696 in_ch=2, 697 out_ch=2, 698 x_in=32, 699 y_in=32, 700 w_x=2, 701 w_y=2, 702 stride_x=1, 703 stride_y=1, 704 pad=False, 705 out_activation_min=TestSettings.INT16_MIN, 706 out_activation_max=TestSettings.INT16_MAX, 707 int16xint8=True, 708 bias_min=-0x300, 709 dilation_x=2, 710 dilation_y=2, 711 interpreter=interpreter) 712 dataset = 'int16xint8_dilation_2' 713 testdata_sets[dataset] = ConvSettings(dataset, 714 type_of_test, 715 regenerate_weights, 716 regenerate_input, 717 regenerate_biases, 718 schema_file, 719 in_ch=3, 720 out_ch=4, 721 x_in=7, 722 y_in=8, 723 w_x=2, 724 w_y=4, 725 stride_x=1, 726 stride_y=1, 727 pad=True, 728 randmin=TestSettings.INT16_MIN, 729 randmax=TestSettings.INT16_MAX, 730 out_activation_min=-13335, 731 out_activation_max=32767, 732 int16xint8=True, 733 dilation_x=2, 734 dilation_y=2, 735 interpreter=interpreter) 736 dataset = 'int16xint8_dilation_3' 737 testdata_sets[dataset] = ConvSettings(dataset, 738 type_of_test, 739 regenerate_weights, 740 regenerate_input, 741 regenerate_biases, 742 schema_file, 743 in_ch=3, 744 out_ch=4, 745 x_in=7, 746 y_in=8, 747 w_x=2, 748 w_y=4, 749 stride_x=1, 750 stride_y=1, 751 pad=True, 752 randmin=TestSettings.INT16_MIN, 753 randmax=TestSettings.INT16_MAX, 754 out_activation_min=-13335, 755 out_activation_max=32767, 756 int16xint8=True, 757 dilation_x=2, 758 interpreter=interpreter) 759 dataset = 'int16xint8xint32_1' 760 testdata_sets[dataset] = ConvSettings(dataset, 761 type_of_test, 762 regenerate_weights, 763 regenerate_input, 764 regenerate_biases, 765 schema_file, 766 in_ch=55, 767 out_ch=4, 768 x_in=10, 769 y_in=8, 770 w_x=9, 771 w_y=4, 772 stride_x=1, 773 stride_y=1, 774 pad=False, 775 generate_bias=False, 776 randmin=TestSettings.INT16_MIN, 777 randmax=TestSettings.INT16_MAX, 778 out_activation_min=TestSettings.INT16_MIN, 779 out_activation_max=TestSettings.INT16_MAX, 780 int16xint8=True, 781 int16xint8_int32=True, 782 interpreter=interpreter) 783 dataset = 'int16xint8xint32_2' 784 testdata_sets[dataset] = ConvSettings(dataset, 785 type_of_test, 786 regenerate_weights, 787 regenerate_input, 788 regenerate_biases, 789 schema_file, 790 in_ch=55, 791 out_ch=9, 792 x_in=10, 793 y_in=8, 794 w_x=9, 795 w_y=4, 796 stride_x=1, 797 stride_y=1, 798 pad=False, 799 generate_bias=False, 800 randmin=TestSettings.INT16_MAX - 100, 801 randmax=TestSettings.INT16_MAX, 802 out_activation_min=TestSettings.INT16_MAX - 100, 803 out_activation_max=TestSettings.INT16_MAX, 804 bias_min=TestSettings.INT64_MIN, 805 bias_max=TestSettings.INT64_MAX, 806 int16xint8=True, 807 int16xint8_int32=True, 808 interpreter=interpreter, 809 weights_min=100) 810 dataset = 'int16xint8xint32_3' 811 testdata_sets[dataset] = ConvSettings(dataset, 812 type_of_test, 813 regenerate_weights, 814 regenerate_input, 815 regenerate_biases, 816 schema_file, 817 in_ch=8, 818 out_ch=8, 819 x_in=4, 820 y_in=4, 821 w_x=2, 822 w_y=2, 823 stride_x=1, 824 stride_y=1, 825 pad=False, 826 generate_bias=True, 827 out_activation_min=TestSettings.INT16_MIN, 828 out_activation_max=TestSettings.INT16_MAX, 829 int16xint8=True, 830 int16xint8_int32=True, 831 bias_min=-0x300, 832 bias_max=TestSettings.INT32_MAX + 1000, 833 interpreter=interpreter) 834 dataset = 'int16xint8xint32_4' 835 testdata_sets[dataset] = ConvSettings(dataset, 836 type_of_test, 837 regenerate_weights, 838 regenerate_input, 839 regenerate_biases, 840 schema_file, 841 in_ch=2, 842 out_ch=2, 843 x_in=32, 844 y_in=32, 845 w_x=2, 846 w_y=2, 847 stride_x=1, 848 stride_y=1, 849 pad=False, 850 out_activation_min=TestSettings.INT16_MIN, 851 out_activation_max=TestSettings.INT16_MAX, 852 int16xint8=True, 853 int16xint8_int32=True, 854 bias_min=-0x300, 855 dilation_x=2, 856 dilation_y=2, 857 interpreter=interpreter) 858 dataset = 'int16xint8xint32_5' 859 testdata_sets[dataset] = ConvSettings(dataset, 860 type_of_test, 861 regenerate_weights, 862 regenerate_input, 863 regenerate_biases, 864 schema_file, 865 in_ch=3, 866 out_ch=4, 867 x_in=7, 868 y_in=8, 869 w_x=2, 870 w_y=4, 871 stride_x=1, 872 stride_y=1, 873 pad=True, 874 randmin=TestSettings.INT16_MIN, 875 randmax=TestSettings.INT16_MAX, 876 out_activation_min=-13335, 877 out_activation_max=32767, 878 int16xint8=True, 879 int16xint8_int32=True, 880 dilation_x=2, 881 dilation_y=2, 882 interpreter=interpreter) 883 dataset = 'int16xint8xint32_6' 884 testdata_sets[dataset] = ConvSettings(dataset, 885 type_of_test, 886 regenerate_weights, 887 regenerate_input, 888 regenerate_biases, 889 schema_file, 890 in_ch=3, 891 out_ch=4, 892 x_in=7, 893 y_in=8, 894 w_x=2, 895 w_y=4, 896 stride_x=1, 897 stride_y=1, 898 pad=True, 899 randmin=TestSettings.INT16_MIN, 900 randmax=TestSettings.INT16_MAX, 901 out_activation_min=-13335, 902 out_activation_max=32767, 903 int16xint8=True, 904 int16xint8_int32=True, 905 dilation_x=2, 906 interpreter=interpreter) 907 dataset = 'grouped_conv_1' 908 testdata_sets[dataset] = ConvSettings(dataset, 909 type_of_test, 910 regenerate_weights, 911 regenerate_input, 912 regenerate_biases, 913 schema_file, 914 in_ch=2, 915 out_ch=6, 916 groups=2, 917 x_in=5, 918 y_in=5, 919 w_x=2, 920 w_y=2, 921 generate_bias=False, 922 stride_x=1, 923 stride_y=1, 924 pad=False, 925 batches=2, 926 interpreter=interpreter) 927 dataset = 'grouped_conv_2' 928 testdata_sets[dataset] = ConvSettings(dataset, 929 type_of_test, 930 regenerate_weights, 931 regenerate_input, 932 regenerate_biases, 933 schema_file, 934 in_ch=4, 935 out_ch=2, 936 groups=2, 937 x_in=7, 938 y_in=3, 939 w_x=1, 940 w_y=2, 941 generate_bias=True, 942 stride_x=1, 943 stride_y=1, 944 pad=False, 945 interpreter=interpreter) 946 dataset = 'grouped_conv_3' 947 testdata_sets[dataset] = ConvSettings(dataset, 948 type_of_test, 949 regenerate_weights, 950 regenerate_input, 951 regenerate_biases, 952 schema_file, 953 in_ch=2, 954 out_ch=4, 955 groups=2, 956 x_in=3, 957 y_in=2, 958 w_x=3, 959 w_y=2, 960 generate_bias=True, 961 stride_x=2, 962 stride_y=2, 963 pad=True, 964 batches=2, 965 interpreter=interpreter) 966 dataset = 'grouped_conv_4' 967 testdata_sets[dataset] = ConvSettings(dataset, 968 type_of_test, 969 regenerate_weights, 970 regenerate_input, 971 regenerate_biases, 972 schema_file, 973 in_ch=3, 974 out_ch=6, 975 groups=3, 976 x_in=9, 977 y_in=9, 978 w_x=2, 979 w_y=2, 980 generate_bias=True, 981 stride_x=1, 982 stride_y=1, 983 dilation_x=3, 984 dilation_y=3, 985 pad=True, 986 interpreter=interpreter) 987 dataset = 'basic_int4' 988 testdata_sets[dataset] = ConvSettings(dataset, 989 type_of_test, 990 regenerate_weights, 991 regenerate_input, 992 regenerate_biases, 993 schema_file, 994 in_ch=1, 995 out_ch=1, 996 x_in=5, 997 y_in=8, 998 w_x=2, 999 w_y=4, 1000 stride_x=1, 1001 stride_y=1, 1002 pad=False, 1003 interpreter=interpreter, 1004 int4_weights=True) 1005 dataset = 'basic_2_int4' 1006 testdata_sets[dataset] = ConvSettings(dataset, 1007 type_of_test, 1008 regenerate_weights, 1009 regenerate_input, 1010 regenerate_biases, 1011 schema_file, 1012 in_ch=5, 1013 out_ch=15, 1014 x_in=15, 1015 y_in=15, 1016 w_x=5, 1017 w_y=5, 1018 stride_x=1, 1019 stride_y=1, 1020 pad=False, 1021 interpreter=interpreter, 1022 int4_weights=True) 1023 dataset = 'stride2pad1_int4' 1024 testdata_sets[dataset] = ConvSettings(dataset, 1025 type_of_test, 1026 regenerate_weights, 1027 regenerate_input, 1028 regenerate_biases, 1029 schema_file, 1030 in_ch=1, 1031 out_ch=1, 1032 x_in=7, 1033 y_in=7, 1034 w_x=3, 1035 w_y=3, 1036 stride_x=2, 1037 stride_y=2, 1038 pad=True, 1039 interpreter=interpreter, 1040 int4_weights=True) 1041 1042 dataset = 'kernel1x1_int4' 1043 testdata_sets[dataset] = ConvSettings(dataset, 1044 type_of_test, 1045 regenerate_weights, 1046 regenerate_input, 1047 regenerate_biases, 1048 schema_file, 1049 in_ch=19, 1050 out_ch=7, 1051 x_in=7, 1052 y_in=5, 1053 w_x=1, 1054 w_y=1, 1055 stride_x=1, 1056 stride_y=1, 1057 pad=False, 1058 bias_min=TestSettings.INT8_MIN, 1059 bias_max=TestSettings.INT8_MAX, 1060 out_activation_min=-126, 1061 out_activation_max=127, 1062 batches=2, 1063 interpreter=interpreter, 1064 int4_weights=True, 1065 generate_bias=False) 1066 1067 dataset = 'kernel1x1_int4_2' 1068 testdata_sets[dataset] = ConvSettings(dataset, 1069 type_of_test, 1070 regenerate_weights, 1071 regenerate_input, 1072 regenerate_biases, 1073 schema_file, 1074 in_ch=60, 1075 out_ch=60, 1076 x_in=60, 1077 y_in=1, 1078 w_x=1, 1079 w_y=1, 1080 stride_x=1, 1081 stride_y=1, 1082 pad=False, 1083 bias_min=TestSettings.INT8_MIN, 1084 bias_max=TestSettings.INT8_MAX, 1085 out_activation_min=-126, 1086 out_activation_max=127, 1087 batches=1, 1088 interpreter=interpreter, 1089 int4_weights=True) 1090 1091 dataset = 'kernel1x1_int4_3' 1092 testdata_sets[dataset] = ConvSettings(dataset, 1093 type_of_test, 1094 regenerate_weights, 1095 regenerate_input, 1096 regenerate_biases, 1097 schema_file, 1098 in_ch=18, 1099 out_ch=47, 1100 x_in=43, 1101 y_in=1, 1102 w_x=1, 1103 w_y=1, 1104 stride_x=1, 1105 stride_y=1, 1106 pad=False, 1107 bias_min=TestSettings.INT8_MIN, 1108 bias_max=TestSettings.INT8_MAX, 1109 out_activation_min=-126, 1110 out_activation_max=127, 1111 batches=1, 1112 interpreter=interpreter, 1113 int4_weights=True) 1114 1115 dataset = 'kernel1x1_stride_x_int4' 1116 testdata_sets[dataset] = ConvSettings(dataset, 1117 type_of_test, 1118 regenerate_weights, 1119 regenerate_input, 1120 regenerate_biases, 1121 schema_file, 1122 in_ch=9, 1123 out_ch=5, 1124 x_in=7, 1125 y_in=4, 1126 w_x=1, 1127 w_y=1, 1128 stride_x=3, 1129 stride_y=1, 1130 pad=False, 1131 out_activation_min=-126, 1132 out_activation_max=127, 1133 batches=2, 1134 interpreter=interpreter, 1135 int4_weights=True) 1136 dataset = 'kernel1x1_stride_x_y_int4' 1137 testdata_sets[dataset] = ConvSettings(dataset, 1138 type_of_test, 1139 regenerate_weights, 1140 regenerate_input, 1141 regenerate_biases, 1142 schema_file, 1143 in_ch=23, 1144 out_ch=15, 1145 randmin=0, 1146 x_in=7, 1147 y_in=6, 1148 w_x=1, 1149 w_y=1, 1150 stride_x=2, 1151 stride_y=2, 1152 pad=False, 1153 out_activation_min=-6, 1154 out_activation_max=127, 1155 batches=3, 1156 interpreter=interpreter, 1157 int4_weights=True) 1158 dataset = 'kernel1x1_stride_x_y_1_int4' 1159 testdata_sets[dataset] = ConvSettings(dataset, 1160 type_of_test, 1161 regenerate_weights, 1162 regenerate_input, 1163 regenerate_biases, 1164 schema_file, 1165 in_ch=5, 1166 out_ch=5, 1167 x_in=4, 1168 y_in=4, 1169 w_x=1, 1170 w_y=1, 1171 stride_x=2, 1172 stride_y=2, 1173 pad=False, 1174 out_activation_min=-126, 1175 out_activation_max=127, 1176 batches=2, 1177 interpreter=interpreter, 1178 int4_weights=True, 1179 generate_bias=False) 1180 dataset = 'kernel1x1_stride_x_y_2_int4' 1181 testdata_sets[dataset] = ConvSettings(dataset, 1182 type_of_test, 1183 regenerate_weights, 1184 regenerate_input, 1185 regenerate_biases, 1186 schema_file, 1187 in_ch=5, 1188 out_ch=5, 1189 x_in=4, 1190 y_in=4, 1191 w_x=1, 1192 w_y=1, 1193 stride_x=3, 1194 stride_y=3, 1195 pad=False, 1196 out_activation_min=-126, 1197 out_activation_max=127, 1198 batches=2, 1199 interpreter=interpreter, 1200 int4_weights=True) 1201 1202 dataset = 'conv_3_int4' 1203 testdata_sets[dataset] = ConvSettings(dataset, 1204 type_of_test, 1205 regenerate_weights, 1206 regenerate_input, 1207 regenerate_biases, 1208 schema_file, 1209 in_ch=3, 1210 out_ch=1, 1211 x_in=10, 1212 y_in=49, 1213 w_x=4, 1214 w_y=10, 1215 stride_x=1, 1216 stride_y=2, 1217 pad=True, 1218 out_activation_min=-127, 1219 out_activation_max=127, 1220 interpreter=interpreter, 1221 int4_weights=True, 1222 generate_bias=False) 1223 1224 dataset = 'conv_1_x_n_1_int4' # left and right pad, no non-padded elements 1225 testdata_sets[dataset] = ConvSettings(dataset, 1226 type_of_test, 1227 regenerate_weights, 1228 regenerate_input, 1229 regenerate_biases, 1230 schema_file, 1231 in_ch=4, 1232 out_ch=3, 1233 x_in=2, 1234 y_in=1, 1235 w_x=3, 1236 w_y=1, 1237 stride_x=1, 1238 stride_y=1, 1239 pad=True, 1240 out_activation_min=-127, 1241 out_activation_max=127, 1242 batches=2, 1243 interpreter=interpreter, 1244 int4_weights=True) 1245 dataset = 'conv_1_x_n_2_int4' # no pad 1246 testdata_sets[dataset] = ConvSettings(dataset, 1247 type_of_test, 1248 regenerate_weights, 1249 regenerate_input, 1250 regenerate_biases, 1251 schema_file, 1252 in_ch=4, 1253 out_ch=3, 1254 x_in=296, 1255 y_in=1, 1256 w_x=48, 1257 w_y=1, 1258 stride_x=2, 1259 stride_y=1, 1260 pad=False, 1261 out_activation_min=-111, 1262 out_activation_max=127, 1263 interpreter=interpreter, 1264 int4_weights=True, 1265 generate_bias=False) 1266 dataset = 'conv_1_x_n_3_int4' 1267 testdata_sets[dataset] = ConvSettings(dataset, 1268 type_of_test, 1269 regenerate_weights, 1270 regenerate_input, 1271 regenerate_biases, 1272 schema_file, 1273 in_ch=4, 1274 out_ch=1, 1275 x_in=296, 1276 y_in=1, 1277 w_x=48, 1278 w_y=1, 1279 stride_x=2, 1280 stride_y=1, 1281 pad=True, 1282 out_activation_min=-111, 1283 out_activation_max=127, 1284 interpreter=interpreter, 1285 int4_weights=True) 1286 dataset = 'conv_1_x_n_4_int4' # 0 left pad, 1 right pad 1287 testdata_sets[dataset] = ConvSettings(dataset, 1288 type_of_test, 1289 regenerate_weights, 1290 regenerate_input, 1291 regenerate_biases, 1292 schema_file, 1293 in_ch=4, 1294 out_ch=4, 1295 x_in=16, 1296 y_in=1, 1297 w_x=3, 1298 w_y=1, 1299 stride_x=2, 1300 stride_y=1, 1301 pad=True, 1302 out_activation_min=-88, 1303 out_activation_max=127, 1304 interpreter=interpreter, 1305 int4_weights=True) 1306 dataset = 'conv_1_x_n_5_int4' 1307 testdata_sets[dataset] = ConvSettings(dataset, 1308 type_of_test, 1309 regenerate_weights, 1310 regenerate_input, 1311 regenerate_biases, 1312 schema_file, 1313 in_ch=4, 1314 out_ch=1, 1315 x_in=17, 1316 y_in=1, 1317 w_x=3, 1318 w_y=1, 1319 stride_x=3, 1320 stride_y=1, 1321 pad=True, 1322 out_activation_min=-88, 1323 out_activation_max=127, 1324 interpreter=interpreter, 1325 int4_weights=True) 1326 1327 dataset = 'conv_2_int4' 1328 testdata_sets[dataset] = ConvSettings(dataset, 1329 type_of_test, 1330 regenerate_weights, 1331 regenerate_input, 1332 regenerate_biases, 1333 schema_file, 1334 in_ch=2, 1335 out_ch=4, 1336 x_in=6, 1337 y_in=3, 1338 w_x=3, 1339 w_y=3, 1340 stride_x=1, 1341 stride_y=1, 1342 pad=True, 1343 out_activation_min=-101, 1344 out_activation_max=127, 1345 interpreter=interpreter, 1346 int4_weights=True) 1347 dataset = 'conv_4_int4' # batches > 2 1348 testdata_sets[dataset] = ConvSettings(dataset, 1349 type_of_test, 1350 regenerate_weights, 1351 regenerate_input, 1352 regenerate_biases, 1353 schema_file, 1354 in_ch=3, 1355 out_ch=3, 1356 x_in=5, 1357 y_in=5, 1358 w_x=2, 1359 w_y=3, 1360 stride_x=2, 1361 stride_y=2, 1362 pad=False, 1363 out_activation_min=-109, 1364 out_activation_max=127, 1365 batches=3, 1366 interpreter=interpreter, 1367 int4_weights=True) 1368 dataset = 'conv_5_int4' 1369 testdata_sets[dataset] = ConvSettings(dataset, 1370 type_of_test, 1371 regenerate_weights, 1372 regenerate_input, 1373 regenerate_biases, 1374 schema_file, 1375 in_ch=128, 1376 out_ch=1, 1377 x_in=128, 1378 y_in=1, 1379 w_x=3, 1380 w_y=3, 1381 stride_x=4, 1382 stride_y=4, 1383 pad=True, 1384 out_activation_min=-88, 1385 out_activation_max=127, 1386 interpreter=interpreter, 1387 int4_weights=True, 1388 generate_bias=False) 1389 dataset = 'conv_out_activation_int4' 1390 testdata_sets[dataset] = ConvSettings(dataset, 1391 type_of_test, 1392 regenerate_weights, 1393 regenerate_input, 1394 regenerate_biases, 1395 schema_file, 1396 in_ch=4, 1397 out_ch=2, 1398 x_in=3, 1399 y_in=3, 1400 w_x=3, 1401 w_y=3, 1402 stride_x=1, 1403 stride_y=1, 1404 pad=True, 1405 out_activation_min=-61, 1406 out_activation_max=107, 1407 interpreter=interpreter, 1408 int4_weights=True) 1409 dataset = 'conv_dilation_golden_int4' 1410 testdata_sets[dataset] = ConvSettings(dataset, 1411 type_of_test, 1412 regenerate_weights, 1413 regenerate_input, 1414 regenerate_biases, 1415 schema_file, 1416 in_ch=1, 1417 batches=2, 1418 out_ch=3, 1419 x_in=6, 1420 y_in=4, 1421 w_x=2, 1422 w_y=2, 1423 stride_x=1, 1424 stride_y=1, 1425 pad=True, 1426 out_activation_min=-128, 1427 out_activation_max=127, 1428 dilation_x=3, 1429 dilation_y=2, 1430 interpreter=interpreter, 1431 int4_weights=True) 1432 dataset = 'conv_2x2_dilation_int4' 1433 testdata_sets[dataset] = ConvSettings(dataset, 1434 type_of_test, 1435 regenerate_weights, 1436 regenerate_input, 1437 regenerate_biases, 1438 schema_file, 1439 in_ch=2, 1440 out_ch=2, 1441 x_in=10, 1442 y_in=10, 1443 w_x=3, 1444 w_y=3, 1445 stride_x=1, 1446 stride_y=1, 1447 pad=False, 1448 out_activation_min=-61, 1449 out_activation_max=107, 1450 dilation_x=2, 1451 dilation_y=2, 1452 interpreter=interpreter, 1453 int4_weights=True) 1454 dataset = 'conv_2x3_dilation_int4' 1455 testdata_sets[dataset] = ConvSettings(dataset, 1456 type_of_test, 1457 regenerate_weights, 1458 regenerate_input, 1459 regenerate_biases, 1460 schema_file, 1461 in_ch=2, 1462 out_ch=2, 1463 x_in=3, 1464 y_in=3, 1465 w_x=3, 1466 w_y=3, 1467 stride_x=1, 1468 stride_y=1, 1469 pad=True, 1470 out_activation_min=-61, 1471 out_activation_max=107, 1472 dilation_x=2, 1473 dilation_y=2, 1474 interpreter=interpreter, 1475 int4_weights=True) 1476 dataset = 'conv_3x2_dilation_int4' 1477 testdata_sets[dataset] = ConvSettings(dataset, 1478 type_of_test, 1479 regenerate_weights, 1480 regenerate_input, 1481 regenerate_biases, 1482 schema_file, 1483 in_ch=2, 1484 out_ch=2, 1485 x_in=3, 1486 y_in=3, 1487 w_x=3, 1488 w_y=3, 1489 stride_x=1, 1490 stride_y=1, 1491 pad=True, 1492 out_activation_min=-61, 1493 out_activation_max=107, 1494 dilation_x=3, 1495 dilation_y=2, 1496 interpreter=interpreter, 1497 int4_weights=True) 1498 dataset = 'conv_2x2_dilation_5x5_input_int4' 1499 testdata_sets[dataset] = ConvSettings(dataset, 1500 type_of_test, 1501 regenerate_weights, 1502 regenerate_input, 1503 regenerate_biases, 1504 schema_file, 1505 in_ch=2, 1506 out_ch=2, 1507 x_in=5, 1508 y_in=5, 1509 w_x=3, 1510 w_y=3, 1511 stride_x=1, 1512 stride_y=1, 1513 pad=True, 1514 out_activation_min=-61, 1515 out_activation_max=107, 1516 dilation_x=2, 1517 dilation_y=2, 1518 interpreter=interpreter, 1519 int4_weights=True) 1520 dataset = 'conv_3x3_dilation_5x5_input_int4' 1521 testdata_sets[dataset] = ConvSettings(dataset, 1522 type_of_test, 1523 regenerate_weights, 1524 regenerate_input, 1525 regenerate_biases, 1526 schema_file, 1527 in_ch=2, 1528 out_ch=2, 1529 x_in=9, 1530 y_in=11, 1531 w_x=3, 1532 w_y=3, 1533 stride_x=1, 1534 stride_y=1, 1535 pad=True, 1536 out_activation_min=-61, 1537 out_activation_max=107, 1538 dilation_x=2, 1539 dilation_y=2, 1540 interpreter=interpreter, 1541 int4_weights=True) 1542 1543 type_of_test = 'transpose_conv' 1544 dataset = 'transpose_conv_1' 1545 testdata_sets[dataset] = ConvSettings(dataset, 1546 type_of_test, 1547 regenerate_weights, 1548 regenerate_input, 1549 regenerate_biases, 1550 schema_file, 1551 in_ch=32, 1552 batches=2, 1553 out_ch=3, 1554 x_in=9, 1555 y_in=9, 1556 w_x=6, 1557 w_y=6, 1558 generate_bias=True, 1559 stride_x=2, 1560 stride_y=2, 1561 pad=True, 1562 interpreter=interpreter) 1563 dataset = 'transpose_conv_2' 1564 testdata_sets[dataset] = ConvSettings(dataset, 1565 type_of_test, 1566 regenerate_weights, 1567 regenerate_input, 1568 regenerate_biases, 1569 schema_file, 1570 in_ch=15, 1571 batches=1, 1572 out_ch=4, 1573 x_in=12, 1574 y_in=12, 1575 w_x=3, 1576 w_y=3, 1577 generate_bias=False, 1578 stride_x=3, 1579 stride_y=1, 1580 pad=False, 1581 interpreter=interpreter) 1582 dataset = 'transpose_conv_3' 1583 testdata_sets[dataset] = ConvSettings(dataset, 1584 type_of_test, 1585 regenerate_weights, 1586 regenerate_input, 1587 regenerate_biases, 1588 schema_file, 1589 in_ch=7, 1590 batches=3, 1591 out_ch=5, 1592 x_in=1, 1593 y_in=7, 1594 w_x=5, 1595 w_y=1, 1596 generate_bias=True, 1597 stride_x=2, 1598 stride_y=5, 1599 pad=True, 1600 interpreter=interpreter) 1601 dataset = 'transpose_conv_4' 1602 testdata_sets[dataset] = ConvSettings(dataset, 1603 type_of_test, 1604 regenerate_weights, 1605 regenerate_input, 1606 regenerate_biases, 1607 schema_file, 1608 in_ch=32, 1609 batches=3, 1610 out_ch=5, 1611 x_in=1, 1612 y_in=7, 1613 w_x=3, 1614 w_y=3, 1615 generate_bias=False, 1616 stride_x=3, 1617 stride_y=1, 1618 pad=False, 1619 interpreter=interpreter) 1620 1621 type_of_test = 'depthwise_conv' 1622 dataset = 'depthwise_2' 1623 testdata_sets[dataset] = ConvSettings(dataset, 1624 type_of_test, 1625 regenerate_weights, 1626 regenerate_input, 1627 regenerate_biases, 1628 schema_file, 1629 in_ch=3, 1630 out_ch=9, 1631 x_in=6, 1632 y_in=5, 1633 w_x=3, 1634 w_y=4, 1635 stride_x=2, 1636 stride_y=2, 1637 pad=True, 1638 out_activation_min=-73, 1639 out_activation_max=127, 1640 interpreter=interpreter) 1641 dataset = 'depthwise_kernel_3x3' 1642 testdata_sets[dataset] = ConvSettings(dataset, 1643 type_of_test, 1644 regenerate_weights, 1645 regenerate_input, 1646 regenerate_biases, 1647 schema_file, 1648 in_ch=5, 1649 out_ch=5, 1650 x_in=4, 1651 y_in=5, 1652 w_x=3, 1653 w_y=3, 1654 stride_x=2, 1655 stride_y=2, 1656 pad=True, 1657 bias_min=TestSettings.INT8_MIN, 1658 bias_max=TestSettings.INT8_MAX, 1659 out_activation_min=-104, 1660 out_activation_max=127, 1661 interpreter=interpreter) 1662 dataset = 'depthwise_kernel_3x3_null_bias' 1663 testdata_sets[dataset] = ConvSettings(dataset, 1664 type_of_test, 1665 regenerate_weights, 1666 regenerate_input, 1667 regenerate_biases, 1668 schema_file, 1669 in_ch=5, 1670 out_ch=5, 1671 x_in=4, 1672 y_in=5, 1673 w_x=3, 1674 w_y=3, 1675 stride_x=2, 1676 stride_y=2, 1677 pad=True, 1678 generate_bias=False, 1679 out_activation_min=-104, 1680 out_activation_max=127, 1681 interpreter=interpreter) 1682 dataset = 'depthwise_eq_in_out_ch' 1683 testdata_sets[dataset] = ConvSettings(dataset, 1684 type_of_test, 1685 regenerate_weights, 1686 regenerate_input, 1687 regenerate_biases, 1688 schema_file, 1689 in_ch=250, 1690 out_ch=250, 1691 x_in=7, 1692 y_in=5, 1693 w_x=2, 1694 w_y=2, 1695 stride_x=1, 1696 stride_y=1, 1697 pad=True, 1698 interpreter=interpreter) 1699 dataset = 'depthwise_sub_block' 1700 testdata_sets[dataset] = ConvSettings(dataset, 1701 type_of_test, 1702 regenerate_weights, 1703 regenerate_input, 1704 regenerate_biases, 1705 schema_file, 1706 in_ch=9, 1707 out_ch=9, 1708 x_in=7, 1709 y_in=5, 1710 w_x=2, 1711 w_y=2, 1712 stride_x=1, 1713 stride_y=1, 1714 pad=False, 1715 interpreter=interpreter) 1716 dataset = 'depthwise_x_stride' 1717 testdata_sets[dataset] = ConvSettings(dataset, 1718 type_of_test, 1719 regenerate_weights, 1720 regenerate_input, 1721 regenerate_biases, 1722 schema_file, 1723 in_ch=9, 1724 out_ch=9, 1725 x_in=7, 1726 y_in=5, 1727 w_x=2, 1728 w_y=2, 1729 stride_x=2, 1730 stride_y=1, 1731 pad=False, 1732 interpreter=interpreter) 1733 dataset = 'depthwise_out_activation' 1734 testdata_sets[dataset] = ConvSettings(dataset, 1735 type_of_test, 1736 regenerate_weights, 1737 regenerate_input, 1738 regenerate_biases, 1739 schema_file, 1740 in_ch=3, 1741 out_ch=3, 1742 x_in=6, 1743 y_in=5, 1744 w_x=3, 1745 w_y=4, 1746 pad=False, 1747 out_activation_min=-45, 1748 out_activation_max=103, 1749 interpreter=interpreter) 1750 dataset = 'depthwise_mult_batches' 1751 testdata_sets[dataset] = ConvSettings(dataset, 1752 type_of_test, 1753 regenerate_weights, 1754 regenerate_input, 1755 regenerate_biases, 1756 schema_file, 1757 in_ch=3, 1758 out_ch=3, 1759 x_in=3, 1760 y_in=5, 1761 w_x=2, 1762 w_y=4, 1763 stride_x=2, 1764 stride_y=2, 1765 pad=True, 1766 batches=2, 1767 interpreter=interpreter) 1768 dataset = 'depthwise_null_bias_0' 1769 testdata_sets[dataset] = ConvSettings(dataset, 1770 type_of_test, 1771 regenerate_weights, 1772 regenerate_input, 1773 regenerate_biases, 1774 schema_file, 1775 in_ch=2, 1776 out_ch=2, 1777 x_in=4, 1778 y_in=5, 1779 w_x=2, 1780 w_y=2, 1781 stride_x=1, 1782 stride_y=1, 1783 pad=True, 1784 generate_bias=False, 1785 batches=1, 1786 interpreter=interpreter) 1787 dataset = 'depthwise_null_bias_1' 1788 testdata_sets[dataset] = ConvSettings(dataset, 1789 type_of_test, 1790 regenerate_weights, 1791 regenerate_input, 1792 regenerate_biases, 1793 schema_file, 1794 in_ch=2, 1795 out_ch=16, 1796 x_in=4, 1797 y_in=5, 1798 w_x=2, 1799 w_y=2, 1800 stride_x=1, 1801 stride_y=1, 1802 pad=True, 1803 generate_bias=False, 1804 batches=1, 1805 interpreter=interpreter) 1806 dataset = 'depthwise_dilation' 1807 testdata_sets[dataset] = ConvSettings(dataset, 1808 type_of_test, 1809 regenerate_weights, 1810 regenerate_input, 1811 regenerate_biases, 1812 schema_file, 1813 in_ch=3, 1814 out_ch=9, 1815 x_in=6, 1816 y_in=5, 1817 w_x=3, 1818 w_y=4, 1819 stride_x=1, 1820 stride_y=1, 1821 pad=True, 1822 out_activation_min=-70, 1823 out_activation_max=127, 1824 dilation_x=2, 1825 dilation_y=3, 1826 interpreter=interpreter) 1827 dataset = 'dw_int16xint8' 1828 testdata_sets[dataset] = ConvSettings(dataset, 1829 type_of_test, 1830 regenerate_weights, 1831 regenerate_input, 1832 regenerate_biases, 1833 schema_file, 1834 in_ch=4, 1835 out_ch=8, 1836 x_in=9, 1837 y_in=5, 1838 w_x=3, 1839 w_y=4, 1840 stride_x=3, 1841 stride_y=2, 1842 pad=True, 1843 randmin=TestSettings.INT16_MIN, 1844 randmax=TestSettings.INT16_MAX, 1845 out_activation_min=-21111, 1846 out_activation_max=32767, 1847 int16xint8=True, 1848 interpreter=interpreter) 1849 dataset = 'dw_int16xint8_dilation' 1850 testdata_sets[dataset] = ConvSettings(dataset, 1851 type_of_test, 1852 regenerate_weights, 1853 regenerate_input, 1854 regenerate_biases, 1855 schema_file, 1856 in_ch=4, 1857 out_ch=8, 1858 x_in=9, 1859 y_in=5, 1860 w_x=4, 1861 w_y=4, 1862 stride_x=1, 1863 stride_y=1, 1864 pad=True, 1865 randmin=TestSettings.INT16_MIN, 1866 randmax=TestSettings.INT16_MAX, 1867 out_activation_min=-32700, 1868 dilation_x=3, 1869 dilation_y=2, 1870 out_activation_max=32767, 1871 int16xint8=True, 1872 interpreter=interpreter) 1873 dataset = 'dw_int16xint8_mult4' 1874 testdata_sets[dataset] = ConvSettings(dataset, 1875 type_of_test, 1876 regenerate_weights, 1877 regenerate_input, 1878 regenerate_biases, 1879 schema_file, 1880 in_ch=2, 1881 out_ch=8, 1882 x_in=4, 1883 y_in=5, 1884 w_x=3, 1885 w_y=4, 1886 stride_x=3, 1887 stride_y=2, 1888 pad=False, 1889 randmin=TestSettings.INT16_MIN, 1890 randmax=TestSettings.INT16_MAX, 1891 out_activation_min=-32767, 1892 out_activation_max=32767, 1893 int16xint8=True, 1894 interpreter=interpreter) 1895 dataset = 'dw_int16xint8_fast' 1896 testdata_sets[dataset] = ConvSettings(dataset, 1897 type_of_test, 1898 regenerate_weights, 1899 regenerate_input, 1900 regenerate_biases, 1901 schema_file, 1902 in_ch=8, 1903 out_ch=8, 1904 x_in=4, 1905 y_in=4, 1906 w_x=2, 1907 w_y=2, 1908 stride_x=1, 1909 stride_y=1, 1910 pad=False, 1911 randmin=TestSettings.INT16_MIN, 1912 randmax=TestSettings.INT16_MAX, 1913 out_activation_min=-17000, 1914 out_activation_max=32767, 1915 int16xint8=True, 1916 interpreter=interpreter) 1917 dataset = 'dw_int16xint8_fast_multiple_batches_uneven_buffers' 1918 testdata_sets[dataset] = ConvSettings(dataset, 1919 type_of_test, 1920 regenerate_weights, 1921 regenerate_input, 1922 regenerate_biases, 1923 schema_file, 1924 in_ch=8, 1925 out_ch=8, 1926 x_in=5, 1927 y_in=5, 1928 w_x=3, 1929 w_y=3, 1930 stride_x=1, 1931 stride_y=1, 1932 pad=False, 1933 randmin=TestSettings.INT16_MIN, 1934 randmax=TestSettings.INT16_MAX, 1935 out_activation_min=-17000, 1936 out_activation_max=32767, 1937 int16xint8=True, 1938 batches=3, 1939 interpreter=interpreter) 1940 dataset = 'dw_int16xint8_fast_multiple_batches_uneven_buffers_null_bias' 1941 testdata_sets[dataset] = ConvSettings(dataset, 1942 type_of_test, 1943 regenerate_weights, 1944 regenerate_input, 1945 regenerate_biases, 1946 schema_file, 1947 in_ch=8, 1948 out_ch=8, 1949 x_in=4, 1950 y_in=4, 1951 w_x=3, 1952 w_y=2, 1953 stride_x=1, 1954 stride_y=1, 1955 pad=False, 1956 randmin=TestSettings.INT16_MIN, 1957 randmax=TestSettings.INT16_MAX, 1958 out_activation_min=-17000, 1959 out_activation_max=32767, 1960 int16xint8=True, 1961 batches=3, 1962 generate_bias=False, 1963 interpreter=interpreter) 1964 1965 dataset = 'dw_int16xint8_fast_test_bias' 1966 nbr_of_out_channels = 8 1967 bias = [i for i in range(nbr_of_out_channels)] 1968 testdata_sets[dataset] = ConvSettings(dataset, 1969 type_of_test, 1970 regenerate_weights, 1971 regenerate_input, 1972 regenerate_biases, 1973 schema_file, 1974 in_ch=8, 1975 out_ch=nbr_of_out_channels, 1976 x_in=4, 1977 y_in=4, 1978 w_x=2, 1979 w_y=2, 1980 stride_x=1, 1981 stride_y=1, 1982 pad=False, 1983 randmin=TestSettings.INT16_MIN, 1984 randmax=TestSettings.INT16_MAX, 1985 out_activation_min=-17000, 1986 out_activation_max=32767, 1987 int16xint8=True, 1988 generate_bias=bias, 1989 interpreter=interpreter) 1990 1991 dataset = 'dw_int16xint8_fast_null_bias' 1992 testdata_sets[dataset] = ConvSettings(dataset, 1993 type_of_test, 1994 regenerate_weights, 1995 regenerate_input, 1996 regenerate_biases, 1997 schema_file, 1998 in_ch=8, 1999 out_ch=8, 2000 x_in=4, 2001 y_in=4, 2002 w_x=2, 2003 w_y=2, 2004 stride_x=1, 2005 stride_y=1, 2006 pad=False, 2007 randmin=TestSettings.INT16_MIN, 2008 randmax=TestSettings.INT16_MAX, 2009 out_activation_min=-17000, 2010 out_activation_max=32767, 2011 int16xint8=True, 2012 generate_bias=False, 2013 interpreter=interpreter) 2014 dataset = 'dw_int16xint8_fast_stride' 2015 testdata_sets[dataset] = ConvSettings(dataset, 2016 type_of_test, 2017 regenerate_weights, 2018 regenerate_input, 2019 regenerate_biases, 2020 schema_file, 2021 in_ch=8, 2022 out_ch=8, 2023 x_in=4, 2024 y_in=4, 2025 w_x=2, 2026 w_y=2, 2027 stride_x=2, 2028 stride_y=2, 2029 pad=True, 2030 randmin=TestSettings.INT16_MIN, 2031 randmax=TestSettings.INT16_MAX, 2032 batches=2, 2033 out_activation_min=TestSettings.INT16_MIN, 2034 out_activation_max=16000, 2035 int16xint8=True, 2036 interpreter=interpreter) 2037 dataset = 'dw_int16xint8_fast_stride_null_bias' 2038 testdata_sets[dataset] = ConvSettings(dataset, 2039 type_of_test, 2040 regenerate_weights, 2041 regenerate_input, 2042 regenerate_biases, 2043 schema_file, 2044 in_ch=8, 2045 out_ch=8, 2046 x_in=4, 2047 y_in=4, 2048 w_x=2, 2049 w_y=2, 2050 stride_x=2, 2051 stride_y=2, 2052 pad=True, 2053 randmin=TestSettings.INT16_MIN, 2054 randmax=TestSettings.INT16_MAX, 2055 batches=2, 2056 out_activation_min=TestSettings.INT16_MIN, 2057 out_activation_max=16000, 2058 int16xint8=True, 2059 generate_bias=False, 2060 interpreter=interpreter) 2061 dataset = 'dw_int16xint8_fast_spill' 2062 testdata_sets[dataset] = ConvSettings(dataset, 2063 type_of_test, 2064 regenerate_weights, 2065 regenerate_input, 2066 regenerate_biases, 2067 schema_file, 2068 in_ch=5, 2069 out_ch=5, 2070 x_in=4, 2071 y_in=4, 2072 w_x=3, 2073 w_y=3, 2074 stride_x=2, 2075 stride_y=1, 2076 pad=True, 2077 randmin=TestSettings.INT16_MIN, 2078 randmax=TestSettings.INT16_MAX, 2079 batches=3, 2080 out_activation_min=-30000, 2081 out_activation_max=32767, 2082 int16xint8=True, 2083 interpreter=interpreter) 2084 dataset = 'dw_int16xint8_fast_spill_null_bias' 2085 testdata_sets[dataset] = ConvSettings(dataset, 2086 type_of_test, 2087 regenerate_weights, 2088 regenerate_input, 2089 regenerate_biases, 2090 schema_file, 2091 in_ch=5, 2092 out_ch=5, 2093 x_in=4, 2094 y_in=4, 2095 w_x=3, 2096 w_y=3, 2097 stride_x=2, 2098 stride_y=1, 2099 pad=True, 2100 randmin=TestSettings.INT16_MIN, 2101 randmax=TestSettings.INT16_MAX, 2102 batches=3, 2103 out_activation_min=-30000, 2104 out_activation_max=32767, 2105 int16xint8=True, 2106 generate_bias=False, 2107 interpreter=interpreter) 2108 dataset = 'depthwise_int4_1' 2109 testdata_sets[dataset] = ConvSettings(dataset, 2110 type_of_test, 2111 regenerate_weights, 2112 regenerate_input, 2113 regenerate_biases, 2114 schema_file, 2115 in_ch=22, 2116 out_ch=22, 2117 x_in=1, 2118 y_in=23, 2119 w_x=1, 2120 w_y=3, 2121 stride_x=1, 2122 stride_y=1, 2123 pad=False, 2124 out_activation_min=-127, 2125 out_activation_max=127, 2126 generate_bias=False, 2127 interpreter=interpreter, 2128 int4_weights=True) 2129 dataset = 'depthwise_int4_2' 2130 testdata_sets[dataset] = ConvSettings(dataset, 2131 type_of_test, 2132 regenerate_weights, 2133 regenerate_input, 2134 regenerate_biases, 2135 schema_file, 2136 in_ch=19, 2137 out_ch=19, 2138 x_in=6, 2139 y_in=6, 2140 w_x=5, 2141 w_y=5, 2142 stride_x=1, 2143 stride_y=1, 2144 pad=False, 2145 out_activation_min=-127, 2146 out_activation_max=127, 2147 generate_bias=False, 2148 interpreter=interpreter, 2149 int4_weights=True) 2150 dataset = 'depthwise_int4_3' 2151 testdata_sets[dataset] = ConvSettings(dataset, 2152 type_of_test, 2153 regenerate_weights, 2154 regenerate_input, 2155 regenerate_biases, 2156 schema_file, 2157 in_ch=1, 2158 out_ch=1, 2159 x_in=2, 2160 y_in=2, 2161 w_x=2, 2162 w_y=2, 2163 stride_x=1, 2164 stride_y=1, 2165 pad=False, 2166 out_activation_min=-127, 2167 out_activation_max=127, 2168 generate_bias=False, 2169 interpreter=interpreter, 2170 int4_weights=True) 2171 dataset = 'depthwise_int4_4' 2172 testdata_sets[dataset] = ConvSettings(dataset, 2173 type_of_test, 2174 regenerate_weights, 2175 regenerate_input, 2176 regenerate_biases, 2177 schema_file, 2178 in_ch=3, 2179 out_ch=3, 2180 x_in=4, 2181 y_in=4, 2182 w_x=2, 2183 w_y=2, 2184 stride_x=2, 2185 stride_y=2, 2186 pad=False, 2187 out_activation_min=-127, 2188 out_activation_max=127, 2189 generate_bias=False, 2190 interpreter=interpreter, 2191 int4_weights=True) 2192 dataset = 'depthwise_int4_generic' 2193 testdata_sets[dataset] = ConvSettings(dataset, 2194 type_of_test, 2195 regenerate_weights, 2196 regenerate_input, 2197 regenerate_biases, 2198 schema_file, 2199 in_ch=2, 2200 out_ch=8, 2201 x_in=16, 2202 y_in=16, 2203 w_x=8, 2204 w_y=8, 2205 stride_x=2, 2206 stride_y=2, 2207 pad=False, 2208 out_activation_min=-127, 2209 out_activation_max=127, 2210 generate_bias=False, 2211 interpreter=interpreter, 2212 int4_weights=True) 2213 dataset = 'depthwise_int4_generic_2' 2214 testdata_sets[dataset] = ConvSettings(dataset, 2215 type_of_test, 2216 regenerate_weights, 2217 regenerate_input, 2218 regenerate_biases, 2219 schema_file, 2220 in_ch=3, 2221 out_ch=9, 2222 x_in=9, 2223 y_in=9, 2224 w_x=6, 2225 w_y=5, 2226 stride_x=2, 2227 stride_y=1, 2228 pad=True, 2229 out_activation_min=-127, 2230 out_activation_max=127, 2231 generate_bias=True, 2232 interpreter=interpreter, 2233 int4_weights=True) 2234 dataset = 'depthwise_int4_generic_3' 2235 testdata_sets[dataset] = ConvSettings(dataset, 2236 type_of_test, 2237 regenerate_weights, 2238 regenerate_input, 2239 regenerate_biases, 2240 schema_file, 2241 in_ch=4, 2242 out_ch=8, 2243 x_in=9, 2244 y_in=9, 2245 w_x=5, 2246 w_y=5, 2247 stride_x=1, 2248 stride_y=1, 2249 pad=False, 2250 out_activation_min=-127, 2251 out_activation_max=125, 2252 dilation_x=2, 2253 dilation_y=2, 2254 generate_bias=True, 2255 interpreter=interpreter, 2256 int4_weights=True) 2257 dataset = 'depthwise_int4_generic_4' 2258 testdata_sets[dataset] = ConvSettings(dataset, 2259 type_of_test, 2260 regenerate_weights, 2261 regenerate_input, 2262 regenerate_biases, 2263 schema_file, 2264 in_ch=1, 2265 out_ch=3, 2266 x_in=12, 2267 y_in=10, 2268 w_x=5, 2269 w_y=5, 2270 stride_x=1, 2271 stride_y=2, 2272 pad=True, 2273 out_activation_min=-127, 2274 out_activation_max=127, 2275 generate_bias=True, 2276 interpreter=interpreter, 2277 int4_weights=True) 2278 dataset = 'depthwise_int4_generic_5' 2279 testdata_sets[dataset] = ConvSettings(dataset, 2280 type_of_test, 2281 regenerate_weights, 2282 regenerate_input, 2283 regenerate_biases, 2284 schema_file, 2285 in_ch=20, 2286 out_ch=20, 2287 x_in=21, 2288 y_in=21, 2289 w_x=5, 2290 w_y=5, 2291 stride_x=1, 2292 stride_y=2, 2293 pad=False, 2294 out_activation_min=-127, 2295 out_activation_max=125, 2296 dilation_x=2, 2297 dilation_y=2, 2298 generate_bias=True, 2299 interpreter=interpreter, 2300 int4_weights=True) 2301 dataset = 'depthwise_int4_generic_6' 2302 testdata_sets[dataset] = ConvSettings(dataset, 2303 type_of_test, 2304 regenerate_weights, 2305 regenerate_input, 2306 regenerate_biases, 2307 schema_file, 2308 in_ch=4, 2309 out_ch=12, 2310 x_in=21, 2311 y_in=21, 2312 w_x=3, 2313 w_y=3, 2314 stride_x=1, 2315 stride_y=1, 2316 pad=False, 2317 out_activation_min=-127, 2318 out_activation_max=125, 2319 dilation_x=1, 2320 dilation_y=2, 2321 generate_bias=True, 2322 interpreter=interpreter, 2323 int4_weights=True) 2324 2325 type_of_test = 'fully_connected' 2326 dataset = 'fully_connected' 2327 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2328 type_of_test, 2329 regenerate_weights, 2330 regenerate_input, 2331 regenerate_biases, 2332 schema_file, 2333 in_ch=10, 2334 out_ch=6, 2335 x_in=2, 2336 y_in=1, 2337 batches=3, 2338 interpreter=interpreter) 2339 dataset = 'fully_connected_w_zp' 2340 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2341 type_of_test, 2342 regenerate_weights, 2343 regenerate_input, 2344 regenerate_biases, 2345 schema_file, 2346 in_ch=10, 2347 out_ch=6, 2348 x_in=2, 2349 y_in=1, 2350 batches=3, 2351 input_scale=0.034, 2352 w_scale=0.054, 2353 bias_scale=0.00000001, 2354 output_scale=0.356, 2355 input_zp=2, 2356 output_zp=35, 2357 w_zp=15, 2358 generate_bias=False, 2359 interpreter=interpreter) 2360 dataset = 'fully_connected_mve_0' 2361 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2362 type_of_test, 2363 regenerate_weights, 2364 regenerate_input, 2365 regenerate_biases, 2366 schema_file, 2367 in_ch=16, 2368 out_ch=9, 2369 x_in=1, 2370 y_in=1, 2371 batches=1, 2372 interpreter=interpreter) 2373 dataset = 'fully_connected_mve_1' 2374 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2375 type_of_test, 2376 regenerate_weights, 2377 regenerate_input, 2378 regenerate_biases, 2379 schema_file, 2380 in_ch=20, 2381 out_ch=4, 2382 x_in=1, 2383 y_in=1, 2384 batches=1, 2385 interpreter=interpreter) 2386 dataset = 'fully_connected_null_bias_0' 2387 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2388 type_of_test, 2389 regenerate_weights, 2390 regenerate_input, 2391 regenerate_biases, 2392 schema_file, 2393 in_ch=33, 2394 out_ch=5, 2395 batches=2, 2396 generate_bias=False, 2397 interpreter=interpreter) 2398 dataset = 'fully_connected_out_activation' 2399 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2400 type_of_test, 2401 regenerate_weights, 2402 regenerate_input, 2403 regenerate_biases, 2404 schema_file, 2405 in_ch=10, 2406 out_ch=4, 2407 out_activation_min=-70, 2408 out_activation_max=100, 2409 interpreter=interpreter) 2410 dataset = 'fully_connected_int16' 2411 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2412 type_of_test, 2413 regenerate_weights, 2414 regenerate_input, 2415 regenerate_biases, 2416 schema_file, 2417 in_ch=7, 2418 out_ch=11, 2419 x_in=3, 2420 y_in=3, 2421 batches=2, 2422 randmin=TestSettings.INT16_MIN, 2423 randmax=TestSettings.INT16_MAX, 2424 out_activation_min=-9999, 2425 out_activation_max=32767, 2426 int16xint8=True, 2427 interpreter=interpreter) 2428 dataset = 'fully_connected_int4' 2429 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2430 type_of_test, 2431 regenerate_weights, 2432 regenerate_input, 2433 regenerate_biases, 2434 schema_file, 2435 int4_weights=True, 2436 in_ch=82, 2437 out_ch=21, 2438 x_in=1, 2439 y_in=1, 2440 batches=1, 2441 bias_min=TestSettings.INT8_MIN, 2442 bias_max=TestSettings.INT8_MAX, 2443 int16xint8=False, 2444 input_zp=3, 2445 output_zp=-3, 2446 interpreter=interpreter) 2447 dataset = 'fully_connected_int4_2' 2448 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2449 type_of_test, 2450 regenerate_weights, 2451 regenerate_input, 2452 regenerate_biases, 2453 schema_file, 2454 int4_weights=True, 2455 in_ch=84, 2456 out_ch=23, 2457 x_in=1, 2458 y_in=1, 2459 batches=1, 2460 bias_min=TestSettings.INT8_MIN, 2461 bias_max=TestSettings.INT8_MAX, 2462 generate_bias=True, 2463 int16xint8=False, 2464 input_zp=-4, 2465 output_zp=16, 2466 interpreter=interpreter) 2467 dataset = 'fully_connected_int4_3' 2468 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2469 type_of_test, 2470 regenerate_weights, 2471 regenerate_input, 2472 regenerate_biases, 2473 schema_file, 2474 int4_weights=True, 2475 in_ch=86, 2476 out_ch=25, 2477 x_in=1, 2478 y_in=1, 2479 batches=1, 2480 bias_min=TestSettings.INT8_MIN, 2481 bias_max=TestSettings.INT8_MAX, 2482 out_activation_min=-64, 2483 out_activation_max=64, 2484 int16xint8=False, 2485 input_zp=1, 2486 output_zp=0, 2487 interpreter=interpreter) 2488 dataset = 'fully_connected_int4_4' 2489 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2490 type_of_test, 2491 regenerate_weights, 2492 regenerate_input, 2493 regenerate_biases, 2494 schema_file, 2495 int4_weights=True, 2496 in_ch=85, 2497 out_ch=19, 2498 x_in=1, 2499 y_in=1, 2500 batches=1, 2501 bias_min=TestSettings.INT8_MIN, 2502 bias_max=TestSettings.INT8_MAX, 2503 generate_bias=False, 2504 int16xint8=False, 2505 input_zp=-2, 2506 output_zp=0, 2507 interpreter=interpreter) 2508 dataset = 'fully_connected_int4_5' 2509 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2510 type_of_test, 2511 regenerate_weights, 2512 regenerate_input, 2513 regenerate_biases, 2514 schema_file, 2515 int4_weights=True, 2516 in_ch=16, 2517 out_ch=20, 2518 bias_min=TestSettings.INT8_MIN, 2519 bias_max=TestSettings.INT8_MAX, 2520 input_zp=120, 2521 output_zp=100, 2522 interpreter=interpreter) 2523 dataset = 'fully_connected_int4_6' 2524 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2525 type_of_test, 2526 regenerate_weights, 2527 regenerate_input, 2528 regenerate_biases, 2529 schema_file, 2530 int4_weights=True, 2531 in_ch=89, 2532 out_ch=22, 2533 x_in=1, 2534 bias_min=TestSettings.INT32_MIN, 2535 bias_max=TestSettings.INT32_MAX, 2536 y_in=1, 2537 batches=1, 2538 generate_bias=False, 2539 int16xint8=False, 2540 input_zp=-127, 2541 output_zp=128, 2542 interpreter=interpreter) 2543 dataset = 'fully_connected_int16_big' 2544 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2545 type_of_test, 2546 regenerate_weights, 2547 regenerate_input, 2548 regenerate_biases, 2549 schema_file, 2550 in_ch=7, 2551 out_ch=11, 2552 x_in=10, 2553 y_in=10, 2554 batches=3, 2555 out_activation_min=-1444, 2556 out_activation_max=32767, 2557 int16xint8=True, 2558 interpreter=interpreter) 2559 dataset = 'fc_int16_slow' 2560 testdata_sets[dataset] = FullyConnectedSettings(dataset, 2561 type_of_test, 2562 regenerate_weights, 2563 regenerate_input, 2564 regenerate_biases, 2565 schema_file, 2566 in_ch=7, 2567 out_ch=11, 2568 x_in=10, 2569 y_in=8, 2570 batches=3, 2571 randmin=(TestSettings.INT16_MAX - 100), 2572 randmax=TestSettings.INT16_MAX, 2573 int16xint8=True, 2574 interpreter=interpreter) 2575 2576 type_of_test = 'avgpool' 2577 dataset = 'avgpooling' 2578 testdata_sets[dataset] = PoolingSettings(dataset, 2579 type_of_test, 2580 regenerate_weights, 2581 regenerate_input, 2582 regenerate_biases, 2583 schema_file, 2584 channels=20, 2585 x_in=22, 2586 y_in=12, 2587 stride_x=9, 2588 stride_y=5, 2589 w_x=6, 2590 w_y=5, 2591 pad=True, 2592 interpreter=interpreter) 2593 dataset = 'avgpooling_1' 2594 testdata_sets[dataset] = PoolingSettings(dataset, 2595 type_of_test, 2596 regenerate_weights, 2597 regenerate_input, 2598 regenerate_biases, 2599 schema_file, 2600 channels=3, 2601 x_in=9, 2602 y_in=5, 2603 stride_x=1, 2604 stride_y=2, 2605 w_x=9, 2606 w_y=5, 2607 pad=False, 2608 interpreter=interpreter) 2609 dataset = 'avgpooling_2' 2610 testdata_sets[dataset] = PoolingSettings(dataset, 2611 type_of_test, 2612 regenerate_weights, 2613 regenerate_input, 2614 regenerate_biases, 2615 schema_file, 2616 channels=5, 2617 x_in=12, 2618 y_in=1, 2619 stride_x=1, 2620 stride_y=2, 2621 w_x=3, 2622 w_y=1, 2623 pad=True, 2624 interpreter=interpreter) 2625 dataset = 'avgpooling_3' 2626 testdata_sets[dataset] = PoolingSettings(dataset, 2627 type_of_test, 2628 regenerate_weights, 2629 regenerate_input, 2630 regenerate_biases, 2631 schema_file, 2632 channels=2, 2633 x_in=9, 2634 y_in=1, 2635 stride_x=2, 2636 stride_y=1, 2637 w_x=1, 2638 w_y=1, 2639 batches=2, 2640 pad=False, 2641 interpreter=interpreter) 2642 dataset = 'avgpooling_4' 2643 testdata_sets[dataset] = PoolingSettings(dataset, 2644 type_of_test, 2645 regenerate_weights, 2646 regenerate_input, 2647 regenerate_biases, 2648 schema_file, 2649 channels=2, 2650 x_in=1, 2651 y_in=20, 2652 stride_x=1, 2653 stride_y=3, 2654 w_x=1, 2655 w_y=3, 2656 batches=3, 2657 pad=True, 2658 interpreter=interpreter) 2659 dataset = 'avgpooling_5' 2660 testdata_sets[dataset] = PoolingSettings(dataset, 2661 type_of_test, 2662 regenerate_weights, 2663 regenerate_input, 2664 regenerate_biases, 2665 schema_file, 2666 channels=1, 2667 x_in=3, 2668 y_in=3, 2669 stride_x=1, 2670 stride_y=1, 2671 w_x=1, 2672 w_y=3, 2673 pad=True, 2674 relu6=True, 2675 interpreter=interpreter) 2676 dataset = 'avgpooling_int16' 2677 testdata_sets[dataset] = PoolingSettings(dataset, 2678 type_of_test, 2679 regenerate_weights, 2680 regenerate_input, 2681 regenerate_biases, 2682 schema_file, 2683 channels=17, 2684 x_in=6, 2685 y_in=4, 2686 stride_x=2, 2687 stride_y=1, 2688 w_x=2, 2689 w_y=3, 2690 pad=True, 2691 randmin=TestSettings.INT16_MIN, 2692 randmax=TestSettings.INT16_MAX, 2693 int16xint8=True, 2694 interpreter=interpreter) 2695 dataset = 'avgpooling_int16_1' 2696 testdata_sets[dataset] = PoolingSettings(dataset, 2697 type_of_test, 2698 regenerate_weights, 2699 regenerate_input, 2700 regenerate_biases, 2701 schema_file, 2702 channels=2, 2703 x_in=9, 2704 y_in=1, 2705 stride_x=2, 2706 stride_y=1, 2707 w_x=1, 2708 w_y=1, 2709 batches=3, 2710 pad=False, 2711 randmin=TestSettings.INT16_MIN, 2712 randmax=TestSettings.INT16_MAX, 2713 int16xint8=True, 2714 interpreter=interpreter) 2715 dataset = 'avgpooling_int16_2' 2716 testdata_sets[dataset] = PoolingSettings(dataset, 2717 type_of_test, 2718 regenerate_weights, 2719 regenerate_input, 2720 regenerate_biases, 2721 schema_file, 2722 channels=20, 2723 x_in=9, 2724 y_in=1, 2725 stride_x=2, 2726 stride_y=1, 2727 w_x=1, 2728 w_y=1, 2729 pad=False, 2730 randmin=TestSettings.INT16_MIN, 2731 randmax=TestSettings.INT16_MAX, 2732 int16xint8=True, 2733 interpreter=interpreter) 2734 dataset = 'avgpooling_int16_3' 2735 testdata_sets[dataset] = PoolingSettings(dataset, 2736 type_of_test, 2737 regenerate_weights, 2738 regenerate_input, 2739 regenerate_biases, 2740 schema_file, 2741 channels=21, 2742 x_in=1, 2743 y_in=20, 2744 stride_x=1, 2745 stride_y=3, 2746 w_x=1, 2747 w_y=3, 2748 pad=True, 2749 randmin=TestSettings.INT16_MIN, 2750 randmax=TestSettings.INT16_MAX, 2751 int16xint8=True, 2752 interpreter=interpreter) 2753 2754 type_of_test = 'maxpool' 2755 dataset = 'maxpooling' 2756 testdata_sets[dataset] = PoolingSettings(dataset, 2757 type_of_test, 2758 regenerate_weights, 2759 regenerate_input, 2760 regenerate_biases, 2761 schema_file, 2762 channels=8, 2763 x_in=22, 2764 y_in=12, 2765 stride_x=9, 2766 stride_y=5, 2767 w_x=6, 2768 w_y=5, 2769 batches=2, 2770 pad=True, 2771 interpreter=interpreter) 2772 dataset = 'maxpooling_1' 2773 testdata_sets[dataset] = PoolingSettings(dataset, 2774 type_of_test, 2775 regenerate_weights, 2776 regenerate_input, 2777 regenerate_biases, 2778 schema_file, 2779 channels=3, 2780 x_in=9, 2781 y_in=5, 2782 stride_x=1, 2783 stride_y=2, 2784 w_x=9, 2785 w_y=5, 2786 pad=False, 2787 interpreter=interpreter) 2788 dataset = 'maxpooling_2' 2789 testdata_sets[dataset] = PoolingSettings(dataset, 2790 type_of_test, 2791 regenerate_weights, 2792 regenerate_input, 2793 regenerate_biases, 2794 schema_file, 2795 channels=5, 2796 x_in=12, 2797 y_in=1, 2798 stride_x=1, 2799 stride_y=2, 2800 w_x=3, 2801 w_y=1, 2802 pad=True, 2803 interpreter=interpreter) 2804 dataset = 'maxpooling_3' 2805 testdata_sets[dataset] = PoolingSettings(dataset, 2806 type_of_test, 2807 regenerate_weights, 2808 regenerate_input, 2809 regenerate_biases, 2810 schema_file, 2811 channels=2, 2812 x_in=9, 2813 y_in=1, 2814 stride_x=2, 2815 stride_y=1, 2816 w_x=1, 2817 w_y=1, 2818 batches=3, 2819 pad=False, 2820 interpreter=interpreter) 2821 dataset = 'maxpooling_4' 2822 testdata_sets[dataset] = PoolingSettings(dataset, 2823 type_of_test, 2824 regenerate_weights, 2825 regenerate_input, 2826 regenerate_biases, 2827 schema_file, 2828 channels=2, 2829 x_in=1, 2830 y_in=20, 2831 stride_x=1, 2832 stride_y=3, 2833 w_x=1, 2834 w_y=3, 2835 pad=True, 2836 interpreter=interpreter) 2837 dataset = 'maxpooling_5' 2838 testdata_sets[dataset] = PoolingSettings(dataset, 2839 type_of_test, 2840 regenerate_weights, 2841 regenerate_input, 2842 regenerate_biases, 2843 schema_file, 2844 channels=20, 2845 x_in=1, 2846 y_in=1, 2847 stride_x=1, 2848 stride_y=1, 2849 w_x=1, 2850 w_y=1, 2851 pad=True, 2852 interpreter=interpreter) 2853 dataset = 'maxpooling_6' 2854 testdata_sets[dataset] = PoolingSettings(dataset, 2855 type_of_test, 2856 regenerate_weights, 2857 regenerate_input, 2858 regenerate_biases, 2859 schema_file, 2860 channels=17, 2861 x_in=1, 2862 y_in=5, 2863 stride_x=1, 2864 stride_y=3, 2865 w_x=3, 2866 w_y=4, 2867 pad=True, 2868 interpreter=interpreter) 2869 dataset = 'maxpooling_7' 2870 testdata_sets[dataset] = PoolingSettings(dataset, 2871 type_of_test, 2872 regenerate_weights, 2873 regenerate_input, 2874 regenerate_biases, 2875 schema_file, 2876 channels=1, 2877 x_in=4, 2878 y_in=2, 2879 stride_x=2, 2880 stride_y=2, 2881 w_x=2, 2882 w_y=2, 2883 pad=False, 2884 relu6=True, 2885 interpreter=interpreter) 2886 dataset = 'maxpool_int16' 2887 testdata_sets[dataset] = PoolingSettings(dataset, 2888 type_of_test, 2889 regenerate_weights, 2890 regenerate_input, 2891 regenerate_biases, 2892 schema_file, 2893 channels=2, 2894 x_in=4, 2895 y_in=3, 2896 stride_x=2, 2897 stride_y=2, 2898 w_x=2, 2899 w_y=2, 2900 batches=3, 2901 pad=False, 2902 randmin=TestSettings.INT16_MIN, 2903 randmax=TestSettings.INT16_MAX, 2904 int16xint8=True, 2905 interpreter=interpreter) 2906 dataset = 'maxpool_int16_1' 2907 testdata_sets[dataset] = PoolingSettings(dataset, 2908 type_of_test, 2909 regenerate_weights, 2910 regenerate_input, 2911 regenerate_biases, 2912 schema_file, 2913 channels=2, 2914 x_in=4, 2915 y_in=5, 2916 stride_x=2, 2917 stride_y=1, 2918 w_x=3, 2919 w_y=3, 2920 batches=2, 2921 pad=True, 2922 randmin=TestSettings.INT16_MIN, 2923 randmax=TestSettings.INT16_MAX, 2924 out_activation_min=-30000, 2925 out_activation_max=30000, 2926 int16xint8=True, 2927 interpreter=interpreter) 2928 dataset = 'maxpool_int16_2' 2929 testdata_sets[dataset] = PoolingSettings(dataset, 2930 type_of_test, 2931 regenerate_weights, 2932 regenerate_input, 2933 regenerate_biases, 2934 schema_file, 2935 channels=3, 2936 x_in=7, 2937 y_in=7, 2938 stride_x=1, 2939 stride_y=1, 2940 w_x=3, 2941 w_y=3, 2942 pad=False, 2943 randmin=TestSettings.INT16_MIN, 2944 randmax=TestSettings.INT16_MAX, 2945 out_activation_min=-30000, 2946 out_activation_max=30000, 2947 int16xint8=True, 2948 interpreter=interpreter) 2949 2950 type_of_test = 'softmax' 2951 dataset = 'softmax' 2952 testdata_sets[dataset] = SoftmaxSettings(dataset, 2953 type_of_test, 2954 regenerate_weights, 2955 regenerate_input, 2956 regenerate_biases, 2957 schema_file, 2958 x_in=5, 2959 y_in=2, 2960 interpreter=interpreter) 2961 dataset = 'softmax_s16' 2962 testdata_sets[dataset] = SoftmaxSettings(dataset, 2963 type_of_test, 2964 regenerate_weights, 2965 regenerate_input, 2966 regenerate_biases, 2967 schema_file, 2968 x_in=10, 2969 y_in=3, 2970 int16xint8=True, 2971 randmin=TestSettings.INT16_MIN, 2972 randmax=TestSettings.INT16_MAX, 2973 interpreter=interpreter) 2974 dataset = 'softmax_s8_s16' 2975 testdata_sets[dataset] = SoftmaxSettings(dataset, 2976 type_of_test, 2977 regenerate_weights, 2978 regenerate_input, 2979 regenerate_biases, 2980 schema_file, 2981 x_in=12, 2982 y_in=2, 2983 inInt8outInt16=True, 2984 interpreter=interpreter) 2985 2986 type_of_test = 'svdf' 2987 dataset = 'svdf' 2988 testdata_sets[dataset] = SVDFSettings(dataset, 2989 type_of_test, 2990 regenerate_weights, 2991 regenerate_input, 2992 regenerate_biases, 2993 schema_file, 2994 batches=2, 2995 number_inputs=2, 2996 rank=8, 2997 memory_size=8, 2998 input_size=3, 2999 number_units=3, 3000 interpreter=interpreter) 3001 dataset = 'svdf_1' 3002 testdata_sets[dataset] = SVDFSettings(dataset, 3003 type_of_test, 3004 regenerate_weights, 3005 regenerate_input, 3006 regenerate_biases, 3007 schema_file, 3008 batches=3, 3009 number_inputs=2, 3010 rank=1, 3011 memory_size=2, 3012 input_size=7, 3013 number_units=5, 3014 interpreter=interpreter) 3015 dataset = 'svdf_2' 3016 testdata_sets[dataset] = SVDFSettings(dataset, 3017 type_of_test, 3018 regenerate_weights, 3019 regenerate_input, 3020 regenerate_biases, 3021 schema_file, 3022 batches=3, 3023 number_inputs=2, 3024 rank=2, 3025 memory_size=2, 3026 input_size=7, 3027 number_units=5, 3028 generate_bias=False, 3029 interpreter=interpreter) 3030 dataset = 'svdf_3' 3031 testdata_sets[dataset] = SVDFSettings(dataset, 3032 type_of_test, 3033 regenerate_weights, 3034 regenerate_input, 3035 regenerate_biases, 3036 schema_file, 3037 batches=1, 3038 number_inputs=2, 3039 rank=1, 3040 memory_size=2, 3041 input_size=20, 3042 number_units=12, 3043 generate_bias=False, 3044 interpreter=interpreter) 3045 dataset = 'svdf_int8' 3046 testdata_sets[dataset] = SVDFSettings(dataset, 3047 type_of_test, 3048 regenerate_weights, 3049 regenerate_input, 3050 regenerate_biases, 3051 schema_file, 3052 batches=1, 3053 number_inputs=2, 3054 rank=1, 3055 memory_size=2, 3056 input_size=20, 3057 number_units=12, 3058 generate_bias=False, 3059 int8_time_weights=True, 3060 interpreter=interpreter) 3061 dataset = 'svdf_int8_2' 3062 testdata_sets[dataset] = SVDFSettings(dataset, 3063 type_of_test, 3064 regenerate_weights, 3065 regenerate_input, 3066 regenerate_biases, 3067 schema_file, 3068 batches=2, 3069 number_inputs=3, 3070 rank=2, 3071 memory_size=3, 3072 input_size=40, 3073 number_units=13, 3074 input_zp=-12, 3075 int8_time_weights=True, 3076 interpreter=interpreter) 3077 3078 type_of_test = 'add' 3079 dataset = 'add' 3080 testdata_sets[dataset] = AddMulSettings(dataset, 3081 type_of_test, 3082 regenerate_weights, 3083 regenerate_input, 3084 regenerate_biases, 3085 schema_file, 3086 channels=8, 3087 x_in=4, 3088 y_in=4, 3089 randmin=TestSettings.INT8_MIN, 3090 randmax=TestSettings.INT8_MAX, 3091 interpreter=interpreter) 3092 dataset = 'add_s16' 3093 testdata_sets[dataset] = AddMulSettings(dataset, 3094 type_of_test, 3095 regenerate_weights, 3096 regenerate_input, 3097 regenerate_biases, 3098 schema_file, 3099 channels=8, 3100 x_in=4, 3101 y_in=4, 3102 randmin=TestSettings.INT16_MIN, 3103 randmax=TestSettings.INT16_MAX, 3104 out_activation_min=TestSettings.INT16_MIN, 3105 out_activation_max=TestSettings.INT16_MAX, 3106 int16xint8=True, 3107 interpreter=interpreter) 3108 dataset = 'add_s16_spill' 3109 testdata_sets[dataset] = AddMulSettings(dataset, 3110 type_of_test, 3111 regenerate_weights, 3112 regenerate_input, 3113 regenerate_biases, 3114 schema_file, 3115 channels=7, 3116 x_in=5, 3117 y_in=3, 3118 randmin=TestSettings.INT16_MIN, 3119 randmax=TestSettings.INT16_MAX, 3120 out_activation_min=-2000, 3121 out_activation_max=TestSettings.INT16_MAX, 3122 int16xint8=True, 3123 interpreter=interpreter) 3124 3125 type_of_test = 'mul' 3126 dataset = 'mul' 3127 testdata_sets[dataset] = AddMulSettings(dataset, 3128 type_of_test, 3129 regenerate_weights, 3130 regenerate_input, 3131 regenerate_biases, 3132 schema_file, 3133 channels=8, 3134 x_in=4, 3135 y_in=5, 3136 randmin=TestSettings.INT8_MIN, 3137 randmax=TestSettings.INT8_MAX, 3138 interpreter=interpreter) 3139 dataset = 'mul_s16' 3140 testdata_sets[dataset] = AddMulSettings(dataset, 3141 type_of_test, 3142 regenerate_weights, 3143 regenerate_input, 3144 regenerate_biases, 3145 schema_file, 3146 channels=8, 3147 x_in=5, 3148 y_in=4, 3149 randmin=TestSettings.INT16_MIN, 3150 randmax=TestSettings.INT16_MAX, 3151 out_activation_min=TestSettings.INT16_MIN, 3152 out_activation_max=TestSettings.INT16_MAX, 3153 int16xint8=True, 3154 interpreter=interpreter) 3155 dataset = 'mul_s16_spill' 3156 testdata_sets[dataset] = AddMulSettings(dataset, 3157 type_of_test, 3158 regenerate_weights, 3159 regenerate_input, 3160 regenerate_biases, 3161 schema_file, 3162 channels=7, 3163 x_in=5, 3164 y_in=7, 3165 randmin=TestSettings.INT16_MIN, 3166 randmax=TestSettings.INT16_MAX, 3167 out_activation_min=TestSettings.INT16_MIN, 3168 out_activation_max=1000, 3169 int16xint8=True, 3170 interpreter=interpreter) 3171 3172 type_of_test = 'lstm' 3173 dataset = 'lstm_1' 3174 testdata_sets[dataset] = LSTMSettings(dataset, 3175 type_of_test, 3176 regenerate_weights, 3177 regenerate_input, 3178 regenerate_biases, 3179 schema_file, 3180 batches=1, 3181 time_steps=10, 3182 number_inputs=22, 3183 number_units=11, 3184 time_major=True, 3185 interpreter=interpreter) 3186 dataset = 'lstm_2' 3187 testdata_sets[dataset] = LSTMSettings(dataset, 3188 type_of_test, 3189 regenerate_weights, 3190 regenerate_input, 3191 regenerate_biases, 3192 schema_file, 3193 batches=1, 3194 time_steps=9, 3195 number_inputs=6, 3196 number_units=7, 3197 time_major=False, 3198 interpreter=interpreter) 3199 dataset = 'lstm_one_time_step' 3200 testdata_sets[dataset] = LSTMSettings(dataset, 3201 type_of_test, 3202 regenerate_weights, 3203 regenerate_input, 3204 regenerate_biases, 3205 schema_file, 3206 batches=3, 3207 time_steps=1, 3208 number_inputs=22, 3209 number_units=3, 3210 time_major=False, 3211 interpreter=interpreter) 3212 3213 return testdata_sets 3214 3215 3216def main(): 3217 if version.parse(tf.__version__) < TestSettings.REQUIRED_MINIMUM_TENSORFLOW_VERSION: 3218 print("Unsupported tensorflow version, ", version.parse(tf.__version__)) 3219 return 1 3220 3221 args = parse_args() 3222 3223 testdataset = args.dataset 3224 test_type = args.testtype 3225 schema_file = args.schema_file 3226 3227 regenerate_input = args.regenerate_input 3228 regenerate_weights = args.regenerate_weights 3229 regenerate_biases = args.regenerate_biases 3230 3231 if args.regenerate_all: 3232 regenerate_biases = True 3233 regenerate_weights = True 3234 regenerate_input = True 3235 3236 testdata_sets = load_testdata_sets(regenerate_input, 3237 regenerate_weights, 3238 regenerate_biases, 3239 schema_file, 3240 args.interpreter) 3241 3242 if args.run_all_testsets: 3243 for testset_name, testset_generator in testdata_sets.items(): 3244 if test_type and testset_generator.test_type != test_type: 3245 continue 3246 print("Generating testset {}..".format(testset_name)) 3247 testset_generator.generate_data() 3248 print() 3249 3250 # Check that all testsets have been loaded. 3251 found_test_data_sets = [] 3252 directory = 'TestCases/TestData' 3253 for dir in next(os.walk(directory))[1]: 3254 found_test_data_sets.append(dir) 3255 for testset_name in found_test_data_sets: 3256 if testset_name not in testdata_sets: 3257 print("WARNING: Testset {} in {} was not loaded".format(testset_name, directory)) 3258 elif testdataset: 3259 try: 3260 generator = testdata_sets[testdataset] 3261 except KeyError: 3262 print("WARNING: testset {} not in testset list".format(testdataset)) 3263 if test_type == 'conv' or test_type == 'depthwise_conv': 3264 generator = ConvSettings(testdataset, test_type, True, True, True, schema_file) 3265 elif test_type == 'fully_connected': 3266 generator = FullyConnectedSettings(testdataset, test_type, True, True, True, schema_file) 3267 elif test_type == 'avgpool' or test_type == 'maxpool': 3268 generator = PoolingSettings(testdataset, test_type, True, True, True, schema_file) 3269 elif test_type == 'softmax': 3270 generator = SoftmaxSettings(testdataset, test_type, True, True, True, schema_file) 3271 elif test_type == 'svdf': 3272 generator = SVDFSettings(testdataset, test_type, True, True, True, schema_file) 3273 elif test_type == 'add' or test_type == 'mul': 3274 generator = AddMulSettings(testdataset, test_type, True, True, True, schema_file) 3275 elif test_type == 'lstm': 3276 generator = LSTMSettings(testdataset, test_type, True, True, True, schema_file) 3277 else: 3278 raise RuntimeError("Please specify type of test with -t") 3279 generator.generate_data() 3280 else: 3281 raise RuntimeError("Please select testdataset or use --run-all-testsets") 3282 return 0 3283 3284if __name__ == '__main__': 3285 sys.exit(main()) 3286
