AssertionError: bad box: x1 larger than x2 #40
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[07/11 18:24:42 d2.engine.train_loop]: Starting training from iteration 0
[07/11 18:24:52 d2.utils.events]: eta: 7:53:07 iter: 19 total_loss: 1.522 loss_cls: 0.2083 loss_box_reg: 0.0001553 loss_mask: 0.6411 loss_rpn_cls: 0.6729 loss_rpn_loc: 0.02641 time: 0.4052 data_time: 0.0427 lr: 0.00019981 max_mem: 6824M
[07/11 18:25:00 d2.utils.events]: eta: 7:58:34 iter: 39 total_loss: 0.826 loss_cls: 0.02481 loss_box_reg: 0.001338 loss_mask: 0.3514 loss_rpn_cls: 0.3847 loss_rpn_loc: 0.0112 time: 0.4081 data_time: 0.0091 lr: 0.00039961 max_mem: 7054M
[07/11 18:25:09 d2.utils.events]: eta: 8:03:20 iter: 59 total_loss: 0.4657 loss_cls: 0.0525 loss_box_reg: 0.00528 loss_mask: 0.2328 loss_rpn_cls: 0.1254 loss_rpn_loc: 0.01294 time: 0.4081 data_time: 0.0062 lr: 0.00059941 max_mem: 7054M
[07/11 18:25:17 d2.utils.events]: eta: 8:10:51 iter: 79 total_loss: 0.5412 loss_cls: 0.1219 loss_box_reg: 0.01392 loss_mask: 0.1982 loss_rpn_cls: 0.1097 loss_rpn_loc: 0.04281 time: 0.4142 data_time: 0.0080 lr: 0.00079921 max_mem: 8390M
[07/11 18:25:26 d2.utils.events]: eta: 8:12:44 iter: 99 total_loss: 0.3733 loss_cls: 0.09589 loss_box_reg: 0.03402 loss_mask: 0.1765 loss_rpn_cls: 0.07032 loss_rpn_loc: 0.02893 time: 0.4211 data_time: 0.0077 lr: 0.00099901 max_mem: 10375M
[07/11 18:25:35 d2.utils.events]: eta: 8:17:41 iter: 119 total_loss: 0.3755 loss_cls: 0.08576 loss_box_reg: 0.03418 loss_mask: 0.1741 loss_rpn_cls: 0.0485 loss_rpn_loc: 0.02191 time: 0.4233 data_time: 0.0083 lr: 0.0011988 max_mem: 10375M
[07/11 18:25:44 d2.utils.events]: eta: 8:24:34 iter: 139 total_loss: 0.3946 loss_cls: 0.09633 loss_box_reg: 0.0391 loss_mask: 0.1771 loss_rpn_cls: 0.04919 loss_rpn_loc: 0.04056 time: 0.4265 data_time: 0.0084 lr: 0.0013986 max_mem: 10375M
[07/11 18:25:53 d2.utils.events]: eta: 8:28:27 iter: 159 total_loss: 0.4053 loss_cls: 0.08783 loss_box_reg: 0.03864 loss_mask: 0.1736 loss_rpn_cls: 0.04172 loss_rpn_loc: 0.04759 time: 0.4287 data_time: 0.0093 lr: 0.0015984 max_mem: 10375M
[07/11 18:26:02 d2.utils.events]: eta: 8:28:45 iter: 179 total_loss: 0.4056 loss_cls: 0.1044 loss_box_reg: 0.03753 loss_mask: 0.1796 loss_rpn_cls: 0.03264 loss_rpn_loc: 0.0305 time: 0.4302 data_time: 0.0074 lr: 0.0017982 max_mem: 10375M
[07/11 18:26:11 d2.utils.events]: eta: 8:28:40 iter: 199 total_loss: 0.3904 loss_cls: 0.08258 loss_box_reg: 0.02545 loss_mask: 0.1929 loss_rpn_cls: 0.03777 loss_rpn_loc: 0.02238 time: 0.4302 data_time: 0.0071 lr: 0.001998 max_mem: 10375M
[07/11 18:26:20 d2.utils.events]: eta: 8:30:04 iter: 219 total_loss: 0.3945 loss_cls: 0.09928 loss_box_reg: 0.02967 loss_mask: 0.1953 loss_rpn_cls: 0.0315 loss_rpn_loc: 0.03111 time: 0.4312 data_time: 0.0092 lr: 0.0021978 max_mem: 10375M
[07/11 18:26:28 d2.utils.events]: eta: 8:29:56 iter: 239 total_loss: 0.3698 loss_cls: 0.08268 loss_box_reg: 0.02776 loss_mask: 0.1708 loss_rpn_cls: 0.0224 loss_rpn_loc: 0.04258 time: 0.4310 data_time: 0.0067 lr: 0.0023976 max_mem: 10375M
[07/11 18:26:37 d2.utils.events]: eta: 8:30:41 iter: 259 total_loss: 0.3101 loss_cls: 0.05248 loss_box_reg: 0.01284 loss_mask: 0.1519 loss_rpn_cls: 0.01409 loss_rpn_loc: 0.02101 time: 0.4315 data_time: 0.0078 lr: 0.0025974 max_mem: 10375M
[07/11 18:26:46 d2.utils.events]: eta: 8:29:39 iter: 279 total_loss: 0.3361 loss_cls: 0.07323 loss_box_reg: 0.01987 loss_mask: 0.1451 loss_rpn_cls: 0.02021 loss_rpn_loc: 0.0349 time: 0.4326 data_time: 0.0072 lr: 0.0027972 max_mem: 10375M
[07/11 18:26:55 d2.utils.events]: eta: 8:28:24 iter: 299 total_loss: 0.2654 loss_cls: 0.06387 loss_box_reg: 0.01594 loss_mask: 0.1451 loss_rpn_cls: 0.01477 loss_rpn_loc: 0.01315 time: 0.4324 data_time: 0.0065 lr: 0.002997 max_mem: 10375M
[07/11 18:27:04 d2.utils.events]: eta: 8:30:20 iter: 319 total_loss: 0.3898 loss_cls: 0.08069 loss_box_reg: 0.02259 loss_mask: 0.1694 loss_rpn_cls: 0.02082 loss_rpn_loc: 0.03517 time: 0.4336 data_time: 0.0093 lr: 0.0031968 max_mem: 10375M
[07/11 18:27:13 d2.utils.events]: eta: 8:30:33 iter: 339 total_loss: 0.3345 loss_cls: 0.08011 loss_box_reg: 0.02296 loss_mask: 0.161 loss_rpn_cls: 0.0221 loss_rpn_loc: 0.04661 time: 0.4344 data_time: 0.0076 lr: 0.0033966 max_mem: 10375M
[07/11 18:27:22 d2.utils.events]: eta: 8:30:21 iter: 359 total_loss: 0.2744 loss_cls: 0.0485 loss_box_reg: 0.01726 loss_mask: 0.1293 loss_rpn_cls: 0.01705 loss_rpn_loc: 0.03203 time: 0.4351 data_time: 0.0077 lr: 0.0035964 max_mem: 10375M
[07/11 18:27:31 d2.utils.events]: eta: 8:30:16 iter: 379 total_loss: 0.2558 loss_cls: 0.06494 loss_box_reg: 0.01695 loss_mask: 0.1368 loss_rpn_cls: 0.008527 loss_rpn_loc: 0.01464 time: 0.4352 data_time: 0.0068 lr: 0.0037962 max_mem: 10375M
[07/11 18:27:40 d2.utils.events]: eta: 8:30:04 iter: 399 total_loss: 0.246 loss_cls: 0.04827 loss_box_reg: 0.01576 loss_mask: 0.1197 loss_rpn_cls: 0.01373 loss_rpn_loc: 0.01939 time: 0.4349 data_time: 0.0070 lr: 0.003996 max_mem: 10375M
[07/11 18:27:48 d2.utils.events]: eta: 8:29:17 iter: 419 total_loss: 0.2877 loss_cls: 0.06765 loss_box_reg: 0.01713 loss_mask: 0.156 loss_rpn_cls: 0.01482 loss_rpn_loc: 0.0207 time: 0.4345 data_time: 0.0082 lr: 0.0041958 max_mem: 10375M
[07/11 18:27:57 d2.utils.events]: eta: 8:29:30 iter: 439 total_loss: 0.4209 loss_cls: 0.1212 loss_box_reg: 0.02121 loss_mask: 0.1896 loss_rpn_cls: 0.01865 loss_rpn_loc: 0.03847 time: 0.4343 data_time: 0.0088 lr: 0.0043956 max_mem: 10375M
[07/11 18:28:06 d2.utils.events]: eta: 8:29:38 iter: 459 total_loss: 0.4073 loss_cls: 0.1058 loss_box_reg: 0.02056 loss_mask: 0.163 loss_rpn_cls: 0.02908 loss_rpn_loc: 0.04771 time: 0.4348 data_time: 0.0089 lr: 0.0045954 max_mem: 10375M
[07/11 18:28:15 d2.utils.events]: eta: 8:30:15 iter: 479 total_loss: 0.3359 loss_cls: 0.08171 loss_box_reg: 0.0161 loss_mask: 0.1719 loss_rpn_cls: 0.02255 loss_rpn_loc: 0.03287 time: 0.4353 data_time: 0.0076 lr: 0.0047952 max_mem: 10375M
[07/11 18:28:24 d2.utils.events]: eta: 8:31:50 iter: 499 total_loss: 0.3511 loss_cls: 0.09287 loss_box_reg: 0.02037 loss_mask: 0.1579 loss_rpn_cls: 0.009786 loss_rpn_loc: 0.03596 time: 0.4361 data_time: 0.0082 lr: 0.004995 max_mem: 10375M
[07/11 18:28:33 d2.utils.events]: eta: 8:31:51 iter: 519 total_loss: 0.3224 loss_cls: 0.08946 loss_box_reg: 0.02361 loss_mask: 0.1484 loss_rpn_cls: 0.0141 loss_rpn_loc: 0.03703 time: 0.4363 data_time: 0.0084 lr: 0.0051948 max_mem: 10375M
[07/11 18:28:42 d2.utils.events]: eta: 8:33:04 iter: 539 total_loss: 0.3617 loss_cls: 0.06344 loss_box_reg: 0.01625 loss_mask: 0.2091 loss_rpn_cls: 0.01894 loss_rpn_loc: 0.02714 time: 0.4365 data_time: 0.0091 lr: 0.0053946 max_mem: 10375M
[07/11 18:28:51 d2.utils.events]: eta: 8:33:12 iter: 559 total_loss: 0.3383 loss_cls: 0.09253 loss_box_reg: 0.01976 loss_mask: 0.1941 loss_rpn_cls: 0.0146 loss_rpn_loc: 0.02182 time: 0.4367 data_time: 0.0078 lr: 0.0055944 max_mem: 10375M
[07/11 18:28:59 d2.utils.events]: eta: 8:33:44 iter: 579 total_loss: 0.3444 loss_cls: 0.08604 loss_box_reg: 0.01819 loss_mask: 0.1638 loss_rpn_cls: 0.01426 loss_rpn_loc: 0.02466 time: 0.4369 data_time: 0.0084 lr: 0.0057942 max_mem: 10375M
[07/11 18:29:08 d2.utils.events]: eta: 8:32:55 iter: 599 total_loss: 0.3361 loss_cls: 0.07452 loss_box_reg: 0.01833 loss_mask: 0.148 loss_rpn_cls: 0.02424 loss_rpn_loc: 0.03891 time: 0.4367 data_time: 0.0082 lr: 0.005994 max_mem: 10375M
[07/11 18:29:17 d2.utils.events]: eta: 8:32:46 iter: 619 total_loss: 0.3567 loss_cls: 0.0879 loss_box_reg: 0.01742 loss_mask: 0.1598 loss_rpn_cls: 0.009541 loss_rpn_loc: 0.01607 time: 0.4367 data_time: 0.0081 lr: 0.0061938 max_mem: 10375M
[07/11 18:29:26 d2.utils.events]: eta: 8:32:22 iter: 639 total_loss: 0.2534 loss_cls: 0.07315 loss_box_reg: 0.01847 loss_mask: 0.1428 loss_rpn_cls: 0.006772 loss_rpn_loc: 0.01518 time: 0.4364 data_time: 0.0067 lr: 0.0063936 max_mem: 10375M
[07/11 18:29:34 d2.utils.events]: eta: 8:32:10 iter: 659 total_loss: 0.3182 loss_cls: 0.06682 loss_box_reg: 0.01769 loss_mask: 0.178 loss_rpn_cls: 0.007947 loss_rpn_loc: 0.02726 time: 0.4364 data_time: 0.0077 lr: 0.0065934 max_mem: 10375M
[07/11 18:29:43 d2.utils.events]: eta: 8:32:20 iter: 679 total_loss: 0.3215 loss_cls: 0.07152 loss_box_reg: 0.01705 loss_mask: 0.1694 loss_rpn_cls: 0.01041 loss_rpn_loc: 0.02417 time: 0.4365 data_time: 0.0086 lr: 0.0067932 max_mem: 10375M
[07/11 18:29:52 d2.utils.events]: eta: 8:32:46 iter: 699 total_loss: 0.2565 loss_cls: 0.06282 loss_box_reg: 0.02091 loss_mask: 0.1476 loss_rpn_cls: 0.006757 loss_rpn_loc: 0.01335 time: 0.4368 data_time: 0.0075 lr: 0.006993 max_mem: 10375M
[07/11 18:30:01 d2.utils.events]: eta: 8:32:03 iter: 719 total_loss: 0.2769 loss_cls: 0.07035 loss_box_reg: 0.01751 loss_mask: 0.1437 loss_rpn_cls: 0.009603 loss_rpn_loc: 0.02026 time: 0.4365 data_time: 0.0072 lr: 0.0071928 max_mem: 10375M
[07/11 18:30:10 d2.utils.events]: eta: 8:32:29 iter: 739 total_loss: 0.3333 loss_cls: 0.09517 loss_box_reg: 0.0208 loss_mask: 0.1501 loss_rpn_cls: 0.01084 loss_rpn_loc: 0.03651 time: 0.4370 data_time: 0.0096 lr: 0.0073926 max_mem: 10375M
[07/11 18:30:19 d2.utils.events]: eta: 8:32:32 iter: 759 total_loss: 0.3375 loss_cls: 0.08592 loss_box_reg: 0.02321 loss_mask: 0.1568 loss_rpn_cls: 0.008646 loss_rpn_loc: 0.0306 time: 0.4375 data_time: 0.0076 lr: 0.0075924 max_mem: 10375M
[07/11 18:30:28 d2.utils.events]: eta: 8:32:09 iter: 779 total_loss: 0.3126 loss_cls: 0.06175 loss_box_reg: 0.0145 loss_mask: 0.1849 loss_rpn_cls: 0.01163 loss_rpn_loc: 0.01285 time: 0.4372 data_time: 0.0082 lr: 0.0077922 max_mem: 10375M
[07/11 18:30:37 d2.utils.events]: eta: 8:32:03 iter: 799 total_loss: 0.261 loss_cls: 0.06443 loss_box_reg: 0.01786 loss_mask: 0.1488 loss_rpn_cls: 0.01037 loss_rpn_loc: 0.02081 time: 0.4375 data_time: 0.0085 lr: 0.007992 max_mem: 10375M
[07/11 18:30:45 d2.utils.events]: eta: 8:31:52 iter: 819 total_loss: 0.2574 loss_cls: 0.05869 loss_box_reg: 0.01517 loss_mask: 0.1326 loss_rpn_cls: 0.008631 loss_rpn_loc: 0.02182 time: 0.4372 data_time: 0.0073 lr: 0.0081918 max_mem: 10375M
[07/11 18:30:55 d2.utils.events]: eta: 8:31:43 iter: 839 total_loss: 0.333 loss_cls: 0.08468 loss_box_reg: 0.02047 loss_mask: 0.1637 loss_rpn_cls: 0.01798 loss_rpn_loc: 0.03197 time: 0.4375 data_time: 0.0077 lr: 0.0083916 max_mem: 10375M
[07/11 18:31:03 d2.utils.events]: eta: 8:31:13 iter: 859 total_loss: 0.277 loss_cls: 0.07466 loss_box_reg: 0.01636 loss_mask: 0.1659 loss_rpn_cls: 0.006309 loss_rpn_loc: 0.0188 time: 0.4370 data_time: 0.0075 lr: 0.0085914 max_mem: 10375M
[07/11 18:31:12 d2.utils.events]: eta: 8:31:40 iter: 879 total_loss: 0.3506 loss_cls: 0.09326 loss_box_reg: 0.02224 loss_mask: 0.1705 loss_rpn_cls: 0.01516 loss_rpn_loc: 0.03855 time: 0.4375 data_time: 0.0082 lr: 0.0087912 max_mem: 10375M
[07/11 18:31:21 d2.utils.events]: eta: 8:31:31 iter: 899 total_loss: 0.2598 loss_cls: 0.07439 loss_box_reg: 0.01754 loss_mask: 0.1518 loss_rpn_cls: 0.005731 loss_rpn_loc: 0.01866 time: 0.4375 data_time: 0.0079 lr: 0.008991 max_mem: 10375M
[07/11 18:31:30 d2.utils.events]: eta: 8:31:23 iter: 919 total_loss: 0.2764 loss_cls: 0.08773 loss_box_reg: 0.01714 loss_mask: 0.1435 loss_rpn_cls: 0.006121 loss_rpn_loc: 0.01353 time: 0.4374 data_time: 0.0077 lr: 0.0091908 max_mem: 10375M
[07/11 18:31:39 d2.utils.events]: eta: 8:31:23 iter: 939 total_loss: 0.264 loss_cls: 0.08377 loss_box_reg: 0.01873 loss_mask: 0.1317 loss_rpn_cls: 0.008426 loss_rpn_loc: 0.02521 time: 0.4376 data_time: 0.0067 lr: 0.0093906 max_mem: 10375M
[07/11 18:31:47 d2.utils.events]: eta: 8:31:05 iter: 959 total_loss: 0.249 loss_cls: 0.04743 loss_box_reg: 0.008316 loss_mask: 0.1123 loss_rpn_cls: 0.005139 loss_rpn_loc: 0.006432 time: 0.4374 data_time: 0.0071 lr: 0.0095904 max_mem: 10375M
[07/11 18:31:56 d2.utils.events]: eta: 8:31:19 iter: 979 total_loss: 0.3152 loss_cls: 0.1002 loss_box_reg: 0.01721 loss_mask: 0.1611 loss_rpn_cls: 0.01409 loss_rpn_loc: 0.02712 time: 0.4376 data_time: 0.0092 lr: 0.0097902 max_mem: 10375M
[07/11 18:32:05 d2.utils.events]: eta: 8:31:14 iter: 999 total_loss: 0.3033 loss_cls: 0.1042 loss_box_reg: 0.02027 loss_mask: 0.153 loss_rpn_cls: 0.01101 loss_rpn_loc: 0.02101 time: 0.4375 data_time: 0.0085 lr: 0.00999 max_mem: 10375M
[07/11 18:32:14 d2.utils.events]: eta: 8:31:48 iter: 1019 total_loss: 0.3161 loss_cls: 0.08504 loss_box_reg: 0.02013 loss_mask: 0.1508 loss_rpn_cls: 0.01067 loss_rpn_loc: 0.03305 time: 0.4376 data_time: 0.0087 lr: 0.01 max_mem: 10375M
[07/11 18:32:23 d2.utils.events]: eta: 8:33:14 iter: 1039 total_loss: 0.2638 loss_cls: 0.05909 loss_box_reg: 0.01622 loss_mask: 0.1384 loss_rpn_cls: 0.008573 loss_rpn_loc: 0.0123 time: 0.4377 data_time: 0.0087 lr: 0.01 max_mem: 10375M
[07/11 18:32:31 d2.utils.events]: eta: 8:33:05 iter: 1059 total_loss: 0.2521 loss_cls: 0.06265 loss_box_reg: 0.0175 loss_mask: 0.1267 loss_rpn_cls: 0.006054 loss_rpn_loc: 0.0113 time: 0.4373 data_time: 0.0076 lr: 0.01 max_mem: 10375M
[07/11 18:32:40 d2.utils.events]: eta: 8:34:00 iter: 1079 total_loss: 0.3011 loss_cls: 0.09204 loss_box_reg: 0.02271 loss_mask: 0.1404 loss_rpn_cls: 0.006699 loss_rpn_loc: 0.02894 time: 0.4375 data_time: 0.0080 lr: 0.01 max_mem: 10375M
[07/11 18:32:49 d2.utils.events]: eta: 8:33:59 iter: 1099 total_loss: 0.3083 loss_cls: 0.09003 loss_box_reg: 0.01742 loss_mask: 0.1526 loss_rpn_cls: 0.01039 loss_rpn_loc: 0.02548 time: 0.4377 data_time: 0.0084 lr: 0.01 max_mem: 10375M
[07/11 18:32:58 d2.utils.events]: eta: 8:33:51 iter: 1119 total_loss: 0.3485 loss_cls: 0.106 loss_box_reg: 0.02342 loss_mask: 0.1609 loss_rpn_cls: 0.008596 loss_rpn_loc: 0.02881 time: 0.4379 data_time: 0.0084 lr: 0.01 max_mem: 10375M
[07/11 18:33:07 d2.utils.events]: eta: 8:33:28 iter: 1139 total_loss: 0.2774 loss_cls: 0.07644 loss_box_reg: 0.02027 loss_mask: 0.1465 loss_rpn_cls: 0.01067 loss_rpn_loc: 0.03347 time: 0.4379 data_time: 0.0093 lr: 0.01 max_mem: 10375M
[07/11 18:33:16 d2.utils.events]: eta: 8:32:37 iter: 1159 total_loss: 0.2716 loss_cls: 0.07568 loss_box_reg: 0.02224 loss_mask: 0.1451 loss_rpn_cls: 0.005922 loss_rpn_loc: 0.01752 time: 0.4379 data_time: 0.0085 lr: 0.01 max_mem: 10375M
[07/11 18:33:24 d2.utils.events]: eta: 8:32:29 iter: 1179 total_loss: 0.23 loss_cls: 0.07258 loss_box_reg: 0.01687 loss_mask: 0.125 loss_rpn_cls: 0.004398 loss_rpn_loc: 0.01229 time: 0.4378 data_time: 0.0071 lr: 0.01 max_mem: 10375M
[07/11 18:33:33 d2.utils.events]: eta: 8:32:32 iter: 1199 total_loss: 0.3609 loss_cls: 0.08158 loss_box_reg: 0.02385 loss_mask: 0.1824 loss_rpn_cls: 0.01222 loss_rpn_loc: 0.03337 time: 0.4380 data_time: 0.0081 lr: 0.01 max_mem: 10375M
[07/11 18:33:42 d2.utils.events]: eta: 8:32:01 iter: 1219 total_loss: 0.2507 loss_cls: 0.0415 loss_box_reg: 0.009657 loss_mask: 0.1466 loss_rpn_cls: 0.01578 loss_rpn_loc: 0.03665 time: 0.4378 data_time: 0.0085 lr: 0.01 max_mem: 10375M
[07/11 18:33:52 d2.utils.events]: eta: 8:32:51 iter: 1239 total_loss: 0.3217 loss_cls: 0.0634 loss_box_reg: 0.01922 loss_mask: 0.1806 loss_rpn_cls: 0.01585 loss_rpn_loc: 0.0405 time: 0.4382 data_time: 0.0086 lr: 0.01 max_mem: 10824M
[07/11 18:34:00 d2.utils.events]: eta: 8:32:42 iter: 1259 total_loss: 0.2819 loss_cls: 0.05084 loss_box_reg: 0.0185 loss_mask: 0.1524 loss_rpn_cls: 0.01591 loss_rpn_loc: 0.02505 time: 0.4381 data_time: 0.0075 lr: 0.01 max_mem: 10824M
[07/11 18:34:09 d2.utils.events]: eta: 8:32:48 iter: 1279 total_loss: 0.3119 loss_cls: 0.05793 loss_box_reg: 0.01852 loss_mask: 0.1548 loss_rpn_cls: 0.01206 loss_rpn_loc: 0.03262 time: 0.4382 data_time: 0.0074 lr: 0.01 max_mem: 10824M
[07/11 18:34:18 d2.utils.events]: eta: 8:32:56 iter: 1299 total_loss: 0.2717 loss_cls: 0.06279 loss_box_reg: 0.01653 loss_mask: 0.129 loss_rpn_cls: 0.01387 loss_rpn_loc: 0.02503 time: 0.4381 data_time: 0.0076 lr: 0.01 max_mem: 10824M
[07/11 18:34:27 d2.utils.events]: eta: 8:32:24 iter: 1319 total_loss: 0.3009 loss_cls: 0.08376 loss_box_reg: 0.01819 loss_mask: 0.1446 loss_rpn_cls: 0.00914 loss_rpn_loc: 0.01798 time: 0.4379 data_time: 0.0077 lr: 0.01 max_mem: 10824M
[07/11 18:34:36 d2.utils.events]: eta: 8:32:26 iter: 1339 total_loss: 0.2284 loss_cls: 0.06878 loss_box_reg: 0.01575 loss_mask: 0.1159 loss_rpn_cls: 0.01002 loss_rpn_loc: 0.02297 time: 0.4381 data_time: 0.0086 lr: 0.01 max_mem: 10824M
[07/11 18:34:45 d2.utils.events]: eta: 8:32:33 iter: 1359 total_loss: 0.2712 loss_cls: 0.06552 loss_box_reg: 0.01762 loss_mask: 0.1461 loss_rpn_cls: 0.008251 loss_rpn_loc: 0.02143 time: 0.4383 data_time: 0.0090 lr: 0.01 max_mem: 10824M
[07/11 18:34:53 d2.utils.events]: eta: 8:32:08 iter: 1379 total_loss: 0.242 loss_cls: 0.05389 loss_box_reg: 0.01578 loss_mask: 0.1311 loss_rpn_cls: 0.004269 loss_rpn_loc: 0.007739 time: 0.4381 data_time: 0.0070 lr: 0.01 max_mem: 10824M
[07/11 18:35:02 d2.utils.events]: eta: 8:32:54 iter: 1399 total_loss: 0.2266 loss_cls: 0.05687 loss_box_reg: 0.01922 loss_mask: 0.1227 loss_rpn_cls: 0.006927 loss_rpn_loc: 0.0143 time: 0.4382 data_time: 0.0069 lr: 0.01 max_mem: 10824M
[07/11 18:35:11 d2.utils.events]: eta: 8:32:58 iter: 1419 total_loss: 0.305 loss_cls: 0.08086 loss_box_reg: 0.02218 loss_mask: 0.1419 loss_rpn_cls: 0.006573 loss_rpn_loc: 0.01774 time: 0.4382 data_time: 0.0083 lr: 0.01 max_mem: 10824M
[07/11 18:35:20 d2.utils.events]: eta: 8:32:48 iter: 1439 total_loss: 0.3102 loss_cls: 0.08404 loss_box_reg: 0.02221 loss_mask: 0.149 loss_rpn_cls: 0.01271 loss_rpn_loc: 0.04032 time: 0.4383 data_time: 0.0093 lr: 0.01 max_mem: 10824M
[07/11 18:35:29 d2.utils.events]: eta: 8:32:28 iter: 1459 total_loss: 0.2952 loss_cls: 0.06519 loss_box_reg: 0.01814 loss_mask: 0.1636 loss_rpn_cls: 0.00677 loss_rpn_loc: 0.02062 time: 0.4381 data_time: 0.0078 lr: 0.01 max_mem: 10824M
[07/11 18:35:38 d2.utils.events]: eta: 8:32:31 iter: 1479 total_loss: 0.2856 loss_cls: 0.06728 loss_box_reg: 0.01703 loss_mask: 0.1394 loss_rpn_cls: 0.006174 loss_rpn_loc: 0.02054 time: 0.4385 data_time: 0.0086 lr: 0.01 max_mem: 10824M
[07/11 18:35:47 d2.utils.events]: eta: 8:31:51 iter: 1499 total_loss: 0.2848 loss_cls: 0.07849 loss_box_reg: 0.02293 loss_mask: 0.15 loss_rpn_cls: 0.009778 loss_rpn_loc: 0.0196 time: 0.4387 data_time: 0.0076 lr: 0.01 max_mem: 10824M
[07/11 18:35:56 d2.utils.events]: eta: 8:31:17 iter: 1519 total_loss: 0.3311 loss_cls: 0.07853 loss_box_reg: 0.01755 loss_mask: 0.1597 loss_rpn_cls: 0.01422 loss_rpn_loc: 0.02734 time: 0.4387 data_time: 0.0080 lr: 0.01 max_mem: 10824M
[07/11 18:36:05 d2.utils.events]: eta: 8:32:08 iter: 1539 total_loss: 0.314 loss_cls: 0.09528 loss_box_reg: 0.02204 loss_mask: 0.1555 loss_rpn_cls: 0.008758 loss_rpn_loc: 0.02828 time: 0.4390 data_time: 0.0095 lr: 0.01 max_mem: 10824M
[07/11 18:36:14 d2.utils.events]: eta: 8:32:09 iter: 1559 total_loss: 0.2458 loss_cls: 0.05934 loss_box_reg: 0.01621 loss_mask: 0.1345 loss_rpn_cls: 0.005067 loss_rpn_loc: 0.018 time: 0.4390 data_time: 0.0076 lr: 0.01 max_mem: 10824M
[07/11 18:36:24 d2.utils.events]: eta: 8:32:26 iter: 1579 total_loss: 0.356 loss_cls: 0.1014 loss_box_reg: 0.02792 loss_mask: 0.1477 loss_rpn_cls: 0.007858 loss_rpn_loc: 0.03938 time: 0.4394 data_time: 0.0095 lr: 0.01 max_mem: 10824M
[07/11 18:36:33 d2.utils.events]: eta: 8:33:11 iter: 1599 total_loss: 0.2719 loss_cls: 0.08995 loss_box_reg: 0.02081 loss_mask: 0.1336 loss_rpn_cls: 0.007486 loss_rpn_loc: 0.04157 time: 0.4397 data_time: 0.0088 lr: 0.01 max_mem: 10824M
[07/11 18:36:42 d2.utils.events]: eta: 8:33:36 iter: 1619 total_loss: 0.2727 loss_cls: 0.06473 loss_box_reg: 0.01508 loss_mask: 0.1268 loss_rpn_cls: 0.00439 loss_rpn_loc: 0.01114 time: 0.4399 data_time: 0.0076 lr: 0.01 max_mem: 10824M
[07/11 18:36:51 d2.utils.events]: eta: 8:33:56 iter: 1639 total_loss: 0.3048 loss_cls: 0.07076 loss_box_reg: 0.01792 loss_mask: 0.1598 loss_rpn_cls: 0.01129 loss_rpn_loc: 0.0204 time: 0.4399 data_time: 0.0076 lr: 0.01 max_mem: 10824M
[07/11 18:37:00 d2.utils.events]: eta: 8:34:01 iter: 1659 total_loss: 0.2019 loss_cls: 0.05851 loss_box_reg: 0.0147 loss_mask: 0.1105 loss_rpn_cls: 0.006341 loss_rpn_loc: 0.01156 time: 0.4400 data_time: 0.0094 lr: 0.01 max_mem: 10824M
[07/11 18:37:09 d2.utils.events]: eta: 8:33:38 iter: 1679 total_loss: 0.2913 loss_cls: 0.07293 loss_box_reg: 0.01963 loss_mask: 0.1563 loss_rpn_cls: 0.01009 loss_rpn_loc: 0.01724 time: 0.4401 data_time: 0.0089 lr: 0.01 max_mem: 10824M
[07/11 18:37:18 d2.utils.events]: eta: 8:33:19 iter: 1699 total_loss: 0.242 loss_cls: 0.0543 loss_box_reg: 0.01551 loss_mask: 0.1358 loss_rpn_cls: 0.006947 loss_rpn_loc: 0.0167 time: 0.4403 data_time: 0.0076 lr: 0.01 max_mem: 10824M
[07/11 18:37:27 d2.utils.events]: eta: 8:33:28 iter: 1719 total_loss: 0.2673 loss_cls: 0.06433 loss_box_reg: 0.01698 loss_mask: 0.1393 loss_rpn_cls: 0.01027 loss_rpn_loc: 0.026 time: 0.4402 data_time: 0.0089 lr: 0.01 max_mem: 10824M
[07/11 18:37:36 d2.utils.events]: eta: 8:33:12 iter: 1739 total_loss: 0.2919 loss_cls: 0.07103 loss_box_reg: 0.02 loss_mask: 0.1496 loss_rpn_cls: 0.006164 loss_rpn_loc: 0.01211 time: 0.4403 data_time: 0.0083 lr: 0.01 max_mem: 10824M
[07/11 18:37:45 d2.utils.events]: eta: 8:33:05 iter: 1759 total_loss: 0.2686 loss_cls: 0.04505 loss_box_reg: 0.01351 loss_mask: 0.1634 loss_rpn_cls: 0.009903 loss_rpn_loc: 0.01445 time: 0.4404 data_time: 0.0077 lr: 0.01 max_mem: 10824M
[07/11 18:37:54 d2.utils.events]: eta: 8:33:57 iter: 1779 total_loss: 0.2619 loss_cls: 0.06645 loss_box_reg: 0.01745 loss_mask: 0.1382 loss_rpn_cls: 0.006083 loss_rpn_loc: 0.01326 time: 0.4404 data_time: 0.0076 lr: 0.01 max_mem: 10824M
[07/11 18:38:03 d2.utils.events]: eta: 8:33:51 iter: 1799 total_loss: 0.3124 loss_cls: 0.09307 loss_box_reg: 0.02187 loss_mask: 0.1663 loss_rpn_cls: 0.005512 loss_rpn_loc: 0.024 time: 0.4406 data_time: 0.0076 lr: 0.01 max_mem: 10824M
[07/11 18:38:12 d2.utils.events]: eta: 8:33:42 iter: 1819 total_loss: 0.2443 loss_cls: 0.05758 loss_box_reg: 0.01611 loss_mask: 0.1355 loss_rpn_cls: 0.004745 loss_rpn_loc: 0.01235 time: 0.4404 data_time: 0.0072 lr: 0.01 max_mem: 10824M
[07/11 18:38:21 d2.utils.events]: eta: 8:33:20 iter: 1839 total_loss: 0.2389 loss_cls: 0.05698 loss_box_reg: 0.01671 loss_mask: 0.1417 loss_rpn_cls: 0.008342 loss_rpn_loc: 0.01314 time: 0.4404 data_time: 0.0079 lr: 0.01 max_mem: 10824M
[07/11 18:38:30 d2.utils.events]: eta: 8:33:53 iter: 1859 total_loss: 0.2556 loss_cls: 0.07939 loss_box_reg: 0.01739 loss_mask: 0.1392 loss_rpn_cls: 0.009146 loss_rpn_loc: 0.02361 time: 0.4407 data_time: 0.0086 lr: 0.01 max_mem: 10824M
[07/11 18:38:39 d2.utils.events]: eta: 8:33:16 iter: 1879 total_loss: 0.268 loss_cls: 0.06665 loss_box_reg: 0.0187 loss_mask: 0.1206 loss_rpn_cls: 0.003925 loss_rpn_loc: 0.01439 time: 0.4408 data_time: 0.0082 lr: 0.01 max_mem: 10824M
[07/11 18:38:48 d2.utils.events]: eta: 8:33:08 iter: 1899 total_loss: 0.2089 loss_cls: 0.05096 loss_box_reg: 0.01195 loss_mask: 0.1319 loss_rpn_cls: 0.00131 loss_rpn_loc: 0.005368 time: 0.4407 data_time: 0.0075 lr: 0.01 max_mem: 10824M
[07/11 18:38:57 d2.utils.events]: eta: 8:33:05 iter: 1919 total_loss: 0.2939 loss_cls: 0.08017 loss_box_reg: 0.02089 loss_mask: 0.1447 loss_rpn_cls: 0.01021 loss_rpn_loc: 0.02003 time: 0.4408 data_time: 0.0080 lr: 0.01 max_mem: 10824M
[07/11 18:39:06 d2.utils.events]: eta: 8:33:25 iter: 1939 total_loss: 0.2455 loss_cls: 0.06749 loss_box_reg: 0.01648 loss_mask: 0.1294 loss_rpn_cls: 0.004726 loss_rpn_loc: 0.02557 time: 0.4409 data_time: 0.0082 lr: 0.01 max_mem: 10824M
*** WARNING: skipped 801942 bytes of output ***
[07/12 01:31:55 d2.data.dataset_mapper]: [DatasetMapper] Augmentations used in inference: [RandomRotation(angle=[0.0, 360.0], interp=2)]
[07/12 01:31:57 d2.data.common]: Serializing 234 elements to byte tensors and concatenating them all ...
[07/12 01:31:57 d2.data.common]: Serialized dataset takes 1.69 MiB
WARNING [07/12 01:31:57 d2.evaluation.coco_evaluation]: COCO Evaluator instantiated using config, this is deprecated behavior. Please pass in explicit arguments instead.
[07/12 01:31:57 d2.evaluation.coco_evaluation]: Trying to convert 'dataset_test' to COCO format ...
[07/12 01:31:57 d2.data.datasets.coco]: Converting annotations of dataset 'dataset_test' to COCO format ...)
[07/12 01:31:58 d2.data.datasets.coco]: Converting dataset dicts into COCO format
[07/12 01:31:58 d2.data.datasets.coco]: Conversion finished, #images: 234, #annotations: 2780
[07/12 01:31:58 d2.data.datasets.coco]: Caching COCO format annotations at 'Shared/cfu/models/c20495e1-6249-468f-a90a-985e980ac774/inference/dataset_test_coco_format.json' ...
[07/12 01:31:59 d2.evaluation.evaluator]: Start inference on 234 batches
[07/12 01:32:01 d2.evaluation.evaluator]: Inference done 11/234. Dataloading: 0.0035 s/iter. Inference: 0.1297 s/iter. Eval: 0.0531 s/iter. Total: 0.1863 s/iter. ETA=0:00:41
[07/12 01:32:06 d2.evaluation.evaluator]: Inference done 34/234. Dataloading: 0.0051 s/iter. Inference: 0.1273 s/iter. Eval: 0.0807 s/iter. Total: 0.2131 s/iter. ETA=0:00:42
[07/12 01:32:11 d2.evaluation.evaluator]: Inference done 65/234. Dataloading: 0.0047 s/iter. Inference: 0.1202 s/iter. Eval: 0.0617 s/iter. Total: 0.1866 s/iter. ETA=0:00:31
[07/12 01:32:17 d2.evaluation.evaluator]: Inference done 102/234. Dataloading: 0.0045 s/iter. Inference: 0.1142 s/iter. Eval: 0.0496 s/iter. Total: 0.1684 s/iter. ETA=0:00:22
[07/12 01:32:22 d2.evaluation.evaluator]: Inference done 137/234. Dataloading: 0.0044 s/iter. Inference: 0.1145 s/iter. Eval: 0.0437 s/iter. Total: 0.1627 s/iter. ETA=0:00:15
[07/12 01:32:27 d2.evaluation.evaluator]: Inference done 172/234. Dataloading: 0.0042 s/iter. Inference: 0.1158 s/iter. Eval: 0.0388 s/iter. Total: 0.1589 s/iter. ETA=0:00:09
[07/12 01:32:32 d2.evaluation.evaluator]: Inference done 225/234. Dataloading: 0.0037 s/iter. Inference: 0.1080 s/iter. Eval: 0.0318 s/iter. Total: 0.1437 s/iter. ETA=0:00:01
[07/12 01:32:33 d2.evaluation.evaluator]: Total inference time: 0:00:32.351187 (0.141272 s / iter per device, on 1 devices)
[07/12 01:32:33 d2.evaluation.evaluator]: Total inference pure compute time: 0:00:24 (0.106709 s / iter per device, on 1 devices)
[07/12 01:32:33 d2.evaluation.coco_evaluation]: Preparing results for COCO format ...
[07/12 01:32:33 d2.evaluation.coco_evaluation]: Saving results to Shared/cfu/models/c20495e1-6249-468f-a90a-985e980ac774/inference/coco_instances_results.json
[07/12 01:32:33 d2.evaluation.coco_evaluation]: Evaluating predictions with unofficial COCO API...
Loading and preparing results...
DONE (t=0.00s)
creating index...
index created!
[07/12 01:32:33 d2.evaluation.fast_eval_api]: Evaluate annotation type bbox
[07/12 01:32:33 d2.evaluation.fast_eval_api]: COCOeval_opt.evaluate() finished in 0.06 seconds.
[07/12 01:32:33 d2.evaluation.fast_eval_api]: Accumulating evaluation results...
[07/12 01:32:33 d2.evaluation.fast_eval_api]: COCOeval_opt.accumulate() finished in 0.01 seconds.
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.001
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.002
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.001
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.001
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.004
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.002
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.009
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.008
[07/12 01:32:33 d2.evaluation.coco_evaluation]: Evaluation results for bbox:
File "/databricks/python/lib/python3.8/site-packages/detectron2/engine/defaults.py", line 494, in run_step
self._trainer.run_step()
File "/databricks/python/lib/python3.8/site-packages/detectron2/engine/train_loop.py", line 273, in run_step
loss_dict = self.model(data)
File "/databricks/python/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/databricks/python/lib/python3.8/site-packages/detectron2/modeling/meta_arch/rcnn.py", line 163, in forward
_, detector_losses = self.roi_heads(images, features, proposals, gt_instances)
File "/databricks/python/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/databricks/python/lib/python3.8/site-packages/detectron2/modeling/roi_heads/roi_heads.py", line 739, in forward
losses = self._forward_box(features, proposals)
File "/databricks/python/lib/python3.8/site-packages/detectron2/modeling/roi_heads/roi_heads.py", line 804, in _forward_box
losses = self.box_predictor.losses(predictions, proposals)
File "/databricks/python/lib/python3.8/site-packages/detectron2/modeling/roi_heads/fast_rcnn.py", line 323, in losses
"loss_box_reg": self.box_reg_loss(
File "/databricks/python/lib/python3.8/site-packages/detectron2/modeling/roi_heads/fast_rcnn.py", line 358, in box_reg_loss
loss_box_reg = giou_loss(fg_pred_boxes, gt_boxes[fg_inds], reduction="sum")
File "/databricks/python/lib/python3.8/site-packages/fvcore/nn/giou_loss.py", line 32, in giou_loss
assert (x2 >= x1).all(), "bad box: x1 larger than x2"
AssertionError: bad box: x1 larger than x2
[07/12 01:40:51 d2.engine.hooks]: Overall training speed: 57109 iterations in 7:04:29 (0.4460 s / it)
[07/12 01:40:51 d2.engine.hooks]: Total training time: 7:16:06 (0:11:36 on hooks)
[07/12 01:40:51 d2.utils.events]: eta: 1:49:42 iter: 57111 total_loss: 0.8432 loss_cls: 0.07376 loss_box_reg: 0.00708 loss_mask: 0.2679 loss_rpn_cls: 0.3349 loss_rpn_loc: 0.04453 time: 0.4460 data_time: 0.0079 lr: 0.01 max_mem: 11345M
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