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nohup.out
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loading annotations into memory...
Done (t=0.07s)
creating index...
index created!
loading annotations into memory...
Done (t=0.13s)
creating index...
index created!
Traceback (most recent call last):
File "pretrain.py", line 64, in <module>
train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq=10)
File "/home/AndreevPK/projects/irdec/engine.py", line 30, in train_one_epoch
loss_dict = model(images, targets)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torch/nn/modules/module.py", line 547, in __call__
result = self.forward(*input, **kwargs)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/models/detection/generalized_rcnn.py", line 51, in forward
proposals, proposal_losses = self.rpn(images, features, targets)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torch/nn/modules/module.py", line 547, in __call__
result = self.forward(*input, **kwargs)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/models/detection/rpn.py", line 411, in forward
boxes, scores = self.filter_proposals(proposals, objectness, images.image_sizes, num_anchors_per_level)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/models/detection/rpn.py", line 336, in filter_proposals
keep = box_ops.batched_nms(boxes, scores, lvl, self.nms_thresh)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/ops/boxes.py", line 72, in batched_nms
keep = nms(boxes_for_nms, scores, iou_threshold)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/ops/boxes.py", line 32, in nms
_C = _lazy_import()
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/extension.py", line 30, in _lazy_import
.format(t_major, t_minor, tv_major, tv_minor))
RuntimeError: Detected that PyTorch and torchvision were compiled with different CUDA versions. PyTorch has CUDA Version=9.2 and torchvision has CUDA Version=10.0. Please reinstall the torchvision that matches your PyTorch install.
loading annotations into memory...
Done (t=0.07s)
creating index...
index created!
loading annotations into memory...
Done (t=0.13s)
creating index...
index created!
Traceback (most recent call last):
File "pretrain.py", line 64, in <module>
train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq=10)
File "/home/AndreevPK/projects/irdec/engine.py", line 30, in train_one_epoch
loss_dict = model(images, targets)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torch/nn/modules/module.py", line 547, in __call__
result = self.forward(*input, **kwargs)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/models/detection/generalized_rcnn.py", line 51, in forward
proposals, proposal_losses = self.rpn(images, features, targets)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torch/nn/modules/module.py", line 547, in __call__
result = self.forward(*input, **kwargs)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/models/detection/rpn.py", line 411, in forward
boxes, scores = self.filter_proposals(proposals, objectness, images.image_sizes, num_anchors_per_level)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/models/detection/rpn.py", line 336, in filter_proposals
keep = box_ops.batched_nms(boxes, scores, lvl, self.nms_thresh)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/ops/boxes.py", line 72, in batched_nms
keep = nms(boxes_for_nms, scores, iou_threshold)
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/ops/boxes.py", line 32, in nms
_C = _lazy_import()
File "/home/AndreevPK/env/lib64/python3.6/site-packages/torchvision/extension.py", line 30, in _lazy_import
.format(t_major, t_minor, tv_major, tv_minor))
RuntimeError: Detected that PyTorch and torchvision were compiled with different CUDA versions. PyTorch has CUDA Version=9.2 and torchvision has CUDA Version=10.0. Please reinstall the torchvision that matches your PyTorch install.
loading annotations into memory...
Done (t=0.07s)
creating index...
index created!
loading annotations into memory...
Done (t=0.13s)
creating index...
index created!
Epoch: [0] [ 0/2910] eta: 0:50:02 lr: 0.000010 loss: 0.2511 (0.2511) loss_classifier: 0.1280 (0.1280) loss_box_reg: 0.0935 (0.0935) loss_objectness: 0.0152 (0.0152) loss_rpn_box_reg: 0.0145 (0.0145) time: 1.0317 data: 0.3222 max mem: 0
Epoch: [0] [ 10/2910] eta: 0:12:50 lr: 0.000060 loss: 0.3013 (0.4085) loss_classifier: 0.1538 (0.1982) loss_box_reg: 0.0929 (0.0961) loss_objectness: 0.0534 (0.0859) loss_rpn_box_reg: 0.0193 (0.0283) time: 0.2657 data: 0.0342 max mem: 0
Epoch: [0] [ 20/2910] eta: 0:11:01 lr: 0.000110 loss: 0.3013 (0.3836) loss_classifier: 0.1805 (0.1906) loss_box_reg: 0.0592 (0.0847) loss_objectness: 0.0381 (0.0834) loss_rpn_box_reg: 0.0193 (0.0249) time: 0.1887 data: 0.0056 max mem: 0
Epoch: [0] [ 30/2910] eta: 0:10:22 lr: 0.000160 loss: 0.3542 (0.3702) loss_classifier: 0.1377 (0.1830) loss_box_reg: 0.0592 (0.0825) loss_objectness: 0.0311 (0.0802) loss_rpn_box_reg: 0.0221 (0.0245) time: 0.1890 data: 0.0058 max mem: 0
Epoch: [0] [ 40/2910] eta: 0:10:01 lr: 0.000210 loss: 0.2659 (0.3538) loss_classifier: 0.1147 (0.1731) loss_box_reg: 0.0761 (0.0855) loss_objectness: 0.0162 (0.0704) loss_rpn_box_reg: 0.0174 (0.0248) time: 0.1891 data: 0.0059 max mem: 0
Epoch: [0] [ 50/2910] eta: 0:09:47 lr: 0.000260 loss: 0.2115 (0.3701) loss_classifier: 0.1053 (0.1684) loss_box_reg: 0.0888 (0.0882) loss_objectness: 0.0092 (0.0813) loss_rpn_box_reg: 0.0188 (0.0322) time: 0.1887 data: 0.0060 max mem: 0
Epoch: [0] [ 60/2910] eta: 0:09:38 lr: 0.000310 loss: 0.1589 (0.3339) loss_classifier: 0.0874 (0.1545) loss_box_reg: 0.0549 (0.0808) loss_objectness: 0.0080 (0.0699) loss_rpn_box_reg: 0.0163 (0.0286) time: 0.1892 data: 0.0061 max mem: 0
Epoch: [0] [ 70/2910] eta: 0:09:30 lr: 0.000360 loss: 0.1469 (0.3253) loss_classifier: 0.0848 (0.1541) loss_box_reg: 0.0450 (0.0812) loss_objectness: 0.0109 (0.0631) loss_rpn_box_reg: 0.0100 (0.0269) time: 0.1891 data: 0.0060 max mem: 0
Epoch: [0] [ 80/2910] eta: 0:09:24 lr: 0.000410 loss: 0.2719 (0.3297) loss_classifier: 0.1424 (0.1541) loss_box_reg: 0.0564 (0.0812) loss_objectness: 0.0200 (0.0624) loss_rpn_box_reg: 0.0132 (0.0320) time: 0.1889 data: 0.0059 max mem: 0
Epoch: [0] [ 90/2910] eta: 0:09:19 lr: 0.000460 loss: 0.2443 (0.3211) loss_classifier: 0.1351 (0.1502) loss_box_reg: 0.0641 (0.0803) loss_objectness: 0.0244 (0.0592) loss_rpn_box_reg: 0.0146 (0.0314) time: 0.1890 data: 0.0059 max mem: 0
Epoch: [0] [ 100/2910] eta: 0:09:15 lr: 0.000509 loss: 0.2443 (0.3127) loss_classifier: 0.1164 (0.1470) loss_box_reg: 0.0641 (0.0791) loss_objectness: 0.0232 (0.0567) loss_rpn_box_reg: 0.0137 (0.0299) time: 0.1902 data: 0.0064 max mem: 0
Epoch: [0] [ 110/2910] eta: 0:09:11 lr: 0.000559 loss: 0.1731 (0.3027) loss_classifier: 0.0877 (0.1430) loss_box_reg: 0.0400 (0.0773) loss_objectness: 0.0168 (0.0531) loss_rpn_box_reg: 0.0147 (0.0294) time: 0.1909 data: 0.0065 max mem: 0
Epoch: [0] [ 120/2910] eta: 0:09:07 lr: 0.000609 loss: 0.1731 (0.2975) loss_classifier: 0.0783 (0.1415) loss_box_reg: 0.0478 (0.0764) loss_objectness: 0.0154 (0.0505) loss_rpn_box_reg: 0.0163 (0.0292) time: 0.1893 data: 0.0061 max mem: 0
Epoch: [0] [ 130/2910] eta: 0:09:05 lr: 0.000659 loss: 0.2332 (0.2913) loss_classifier: 0.1072 (0.1384) loss_box_reg: 0.0602 (0.0758) loss_objectness: 0.0155 (0.0483) loss_rpn_box_reg: 0.0185 (0.0288) time: 0.1917 data: 0.0067 max mem: 0
Epoch: [0] [ 140/2910] eta: 0:09:02 lr: 0.000709 loss: 0.2218 (0.2884) loss_classifier: 0.1001 (0.1370) loss_box_reg: 0.0655 (0.0770) loss_objectness: 0.0141 (0.0463) loss_rpn_box_reg: 0.0185 (0.0280) time: 0.1938 data: 0.0069 max mem: 0
Epoch: [0] [ 150/2910] eta: 0:08:59 lr: 0.000759 loss: 0.1829 (0.2852) loss_classifier: 0.0987 (0.1361) loss_box_reg: 0.0602 (0.0770) loss_objectness: 0.0106 (0.0444) loss_rpn_box_reg: 0.0152 (0.0276) time: 0.1920 data: 0.0061 max mem: 0
Epoch: [0] [ 160/2910] eta: 0:08:57 lr: 0.000809 loss: 0.1838 (0.2817) loss_classifier: 0.0987 (0.1346) loss_box_reg: 0.0594 (0.0776) loss_objectness: 0.0092 (0.0426) loss_rpn_box_reg: 0.0129 (0.0270) time: 0.1911 data: 0.0060 max mem: 0
Epoch: [0] [ 170/2910] eta: 0:08:54 lr: 0.000859 loss: 0.1838 (0.2770) loss_classifier: 0.0997 (0.1325) loss_box_reg: 0.0594 (0.0768) loss_objectness: 0.0102 (0.0413) loss_rpn_box_reg: 0.0135 (0.0263) time: 0.1909 data: 0.0060 max mem: 0
Epoch: [0] [ 180/2910] eta: 0:08:52 lr: 0.000909 loss: 0.2532 (0.2767) loss_classifier: 0.1345 (0.1327) loss_box_reg: 0.0972 (0.0778) loss_objectness: 0.0100 (0.0401) loss_rpn_box_reg: 0.0146 (0.0261) time: 0.1916 data: 0.0062 max mem: 0
Epoch: [0] [ 190/2910] eta: 0:08:49 lr: 0.000959 loss: 0.1964 (0.2758) loss_classifier: 0.1016 (0.1316) loss_box_reg: 0.0762 (0.0772) loss_objectness: 0.0077 (0.0414) loss_rpn_box_reg: 0.0143 (0.0256) time: 0.1929 data: 0.0065 max mem: 0
Epoch: [0] [ 200/2910] eta: 0:08:47 lr: 0.001009 loss: 0.1641 (0.2719) loss_classifier: 0.0884 (0.1299) loss_box_reg: 0.0586 (0.0769) loss_objectness: 0.0106 (0.0400) loss_rpn_box_reg: 0.0141 (0.0252) time: 0.1938 data: 0.0065 max mem: 0
Epoch: [0] [ 210/2910] eta: 0:08:45 lr: 0.001059 loss: 0.1862 (0.2694) loss_classifier: 0.0885 (0.1294) loss_box_reg: 0.0525 (0.0762) loss_objectness: 0.0128 (0.0391) loss_rpn_box_reg: 0.0130 (0.0247) time: 0.1932 data: 0.0063 max mem: 0
Epoch: [0] [ 220/2910] eta: 0:08:43 lr: 0.001109 loss: 0.1998 (0.2676) loss_classifier: 0.1079 (0.1287) loss_box_reg: 0.0479 (0.0764) loss_objectness: 0.0089 (0.0380) loss_rpn_box_reg: 0.0190 (0.0247) time: 0.1918 data: 0.0062 max mem: 0
Epoch: [0] [ 230/2910] eta: 0:08:40 lr: 0.001159 loss: 0.2835 (0.2729) loss_classifier: 0.1347 (0.1305) loss_box_reg: 0.1000 (0.0787) loss_objectness: 0.0151 (0.0384) loss_rpn_box_reg: 0.0229 (0.0253) time: 0.1912 data: 0.0061 max mem: 0
Epoch: [0] [ 240/2910] eta: 0:08:38 lr: 0.001209 loss: 0.2399 (0.2706) loss_classifier: 0.1202 (0.1294) loss_box_reg: 0.0800 (0.0783) loss_objectness: 0.0167 (0.0380) loss_rpn_box_reg: 0.0183 (0.0250) time: 0.1913 data: 0.0061 max mem: 0
Epoch: [0] [ 250/2910] eta: 0:08:36 lr: 0.001259 loss: 0.2275 (0.2692) loss_classifier: 0.1034 (0.1287) loss_box_reg: 0.0667 (0.0782) loss_objectness: 0.0157 (0.0372) loss_rpn_box_reg: 0.0161 (0.0251) time: 0.1912 data: 0.0061 max mem: 0
Epoch: [0] [ 260/2910] eta: 0:08:34 lr: 0.001309 loss: 0.2126 (0.2675) loss_classifier: 0.0995 (0.1277) loss_box_reg: 0.0559 (0.0778) loss_objectness: 0.0152 (0.0369) loss_rpn_box_reg: 0.0161 (0.0252) time: 0.1910 data: 0.0060 max mem: 0
Epoch: [0] [ 270/2910] eta: 0:08:31 lr: 0.001359 loss: 0.1834 (0.2648) loss_classifier: 0.0828 (0.1264) loss_box_reg: 0.0540 (0.0778) loss_objectness: 0.0108 (0.0358) loss_rpn_box_reg: 0.0130 (0.0249) time: 0.1907 data: 0.0060 max mem: 0
Epoch: [0] [ 280/2910] eta: 0:08:29 lr: 0.001409 loss: 0.1978 (0.2640) loss_classifier: 0.0934 (0.1263) loss_box_reg: 0.0732 (0.0778) loss_objectness: 0.0104 (0.0352) loss_rpn_box_reg: 0.0140 (0.0247) time: 0.1917 data: 0.0063 max mem: 0
Epoch: [0] [ 290/2910] eta: 0:08:27 lr: 0.001459 loss: 0.1978 (0.2623) loss_classifier: 0.0935 (0.1254) loss_box_reg: 0.0730 (0.0779) loss_objectness: 0.0128 (0.0346) loss_rpn_box_reg: 0.0140 (0.0245) time: 0.1921 data: 0.0063 max mem: 0
Epoch: [0] [ 300/2910] eta: 0:08:25 lr: 0.001508 loss: 0.2301 (0.2631) loss_classifier: 0.1153 (0.1256) loss_box_reg: 0.0593 (0.0778) loss_objectness: 0.0128 (0.0346) loss_rpn_box_reg: 0.0128 (0.0250) time: 0.1918 data: 0.0062 max mem: 0
Epoch: [0] [ 310/2910] eta: 0:08:23 lr: 0.001558 loss: 0.2634 (0.2636) loss_classifier: 0.1253 (0.1257) loss_box_reg: 0.0609 (0.0780) loss_objectness: 0.0182 (0.0342) loss_rpn_box_reg: 0.0178 (0.0257) time: 0.1920 data: 0.0063 max mem: 0
Epoch: [0] [ 320/2910] eta: 0:08:21 lr: 0.001608 loss: 0.2613 (0.2623) loss_classifier: 0.1282 (0.1252) loss_box_reg: 0.0728 (0.0780) loss_objectness: 0.0140 (0.0336) loss_rpn_box_reg: 0.0215 (0.0255) time: 0.1913 data: 0.0060 max mem: 0
Epoch: [0] [ 330/2910] eta: 0:08:19 lr: 0.001658 loss: 0.2606 (0.2630) loss_classifier: 0.1290 (0.1256) loss_box_reg: 0.0857 (0.0786) loss_objectness: 0.0127 (0.0333) loss_rpn_box_reg: 0.0206 (0.0255) time: 0.1912 data: 0.0061 max mem: 0
Epoch: [0] [ 340/2910] eta: 0:08:17 lr: 0.001708 loss: 0.2520 (0.2631) loss_classifier: 0.1324 (0.1259) loss_box_reg: 0.0892 (0.0788) loss_objectness: 0.0127 (0.0327) loss_rpn_box_reg: 0.0172 (0.0256) time: 0.1915 data: 0.0061 max mem: 0
Epoch: [0] [ 350/2910] eta: 0:08:14 lr: 0.001758 loss: 0.2267 (0.2614) loss_classifier: 0.1085 (0.1253) loss_box_reg: 0.0809 (0.0787) loss_objectness: 0.0099 (0.0321) loss_rpn_box_reg: 0.0141 (0.0253) time: 0.1913 data: 0.0059 max mem: 0
Epoch: [0] [ 360/2910] eta: 0:08:12 lr: 0.001808 loss: 0.1597 (0.2594) loss_classifier: 0.0888 (0.1245) loss_box_reg: 0.0554 (0.0784) loss_objectness: 0.0073 (0.0315) loss_rpn_box_reg: 0.0129 (0.0250) time: 0.1915 data: 0.0060 max mem: 0
Epoch: [0] [ 370/2910] eta: 0:08:11 lr: 0.001858 loss: 0.1527 (0.2576) loss_classifier: 0.0819 (0.1240) loss_box_reg: 0.0554 (0.0779) loss_objectness: 0.0060 (0.0310) loss_rpn_box_reg: 0.0104 (0.0246) time: 0.1934 data: 0.0067 max mem: 0
Epoch: [0] [ 380/2910] eta: 0:08:09 lr: 0.001908 loss: 0.1693 (0.2561) loss_classifier: 0.0835 (0.1233) loss_box_reg: 0.0620 (0.0775) loss_objectness: 0.0070 (0.0309) loss_rpn_box_reg: 0.0094 (0.0244) time: 0.1936 data: 0.0067 max mem: 0
Epoch: [0] [ 390/2910] eta: 0:08:07 lr: 0.001958 loss: 0.1887 (0.2568) loss_classifier: 0.0993 (0.1233) loss_box_reg: 0.0724 (0.0779) loss_objectness: 0.0108 (0.0310) loss_rpn_box_reg: 0.0118 (0.0247) time: 0.1916 data: 0.0061 max mem: 0
Epoch: [0] [ 400/2910] eta: 0:08:05 lr: 0.002008 loss: 0.2279 (0.2558) loss_classifier: 0.1087 (0.1228) loss_box_reg: 0.0670 (0.0779) loss_objectness: 0.0136 (0.0306) loss_rpn_box_reg: 0.0165 (0.0245) time: 0.1917 data: 0.0061 max mem: 0
Epoch: [0] [ 410/2910] eta: 0:08:03 lr: 0.002058 loss: 0.1864 (0.2546) loss_classifier: 0.0989 (0.1225) loss_box_reg: 0.0604 (0.0775) loss_objectness: 0.0156 (0.0304) loss_rpn_box_reg: 0.0127 (0.0243) time: 0.1922 data: 0.0062 max mem: 0
Epoch: [0] [ 420/2910] eta: 0:08:01 lr: 0.002108 loss: 0.2119 (0.2544) loss_classifier: 0.0989 (0.1223) loss_box_reg: 0.0628 (0.0775) loss_objectness: 0.0166 (0.0304) loss_rpn_box_reg: 0.0126 (0.0242) time: 0.1931 data: 0.0069 max mem: 0
Epoch: [0] [ 430/2910] eta: 0:07:59 lr: 0.002158 loss: 0.2410 (0.2548) loss_classifier: 0.0991 (0.1223) loss_box_reg: 0.0790 (0.0780) loss_objectness: 0.0162 (0.0301) loss_rpn_box_reg: 0.0152 (0.0243) time: 0.1932 data: 0.0068 max mem: 0
Epoch: [0] [ 440/2910] eta: 0:07:57 lr: 0.002208 loss: 0.1916 (0.2525) loss_classifier: 0.0954 (0.1214) loss_box_reg: 0.0572 (0.0774) loss_objectness: 0.0087 (0.0296) loss_rpn_box_reg: 0.0129 (0.0241) time: 0.1925 data: 0.0061 max mem: 0
Epoch: [0] [ 450/2910] eta: 0:07:55 lr: 0.002258 loss: 0.1895 (0.2513) loss_classifier: 0.0851 (0.1208) loss_box_reg: 0.0654 (0.0774) loss_objectness: 0.0080 (0.0292) loss_rpn_box_reg: 0.0151 (0.0240) time: 0.1937 data: 0.0066 max mem: 0
Epoch: [0] [ 460/2910] eta: 0:07:53 lr: 0.002308 loss: 0.2022 (0.2523) loss_classifier: 0.0851 (0.1210) loss_box_reg: 0.0819 (0.0779) loss_objectness: 0.0097 (0.0293) loss_rpn_box_reg: 0.0162 (0.0241) time: 0.1945 data: 0.0066 max mem: 0
Epoch: [0] [ 470/2910] eta: 0:07:51 lr: 0.002358 loss: 0.1692 (0.2509) loss_classifier: 0.0811 (0.1203) loss_box_reg: 0.0625 (0.0772) loss_objectness: 0.0110 (0.0294) loss_rpn_box_reg: 0.0153 (0.0239) time: 0.1945 data: 0.0064 max mem: 0
Epoch: [0] [ 480/2910] eta: 0:07:49 lr: 0.002408 loss: 0.1633 (0.2503) loss_classifier: 0.0834 (0.1199) loss_box_reg: 0.0448 (0.0772) loss_objectness: 0.0153 (0.0293) loss_rpn_box_reg: 0.0118 (0.0240) time: 0.1950 data: 0.0065 max mem: 0
Epoch: [0] [ 490/2910] eta: 0:07:47 lr: 0.002458 loss: 0.1633 (0.2492) loss_classifier: 0.0831 (0.1193) loss_box_reg: 0.0631 (0.0772) loss_objectness: 0.0101 (0.0288) loss_rpn_box_reg: 0.0127 (0.0238) time: 0.1952 data: 0.0063 max mem: 0
Epoch: [0] [ 500/2910] eta: 0:07:46 lr: 0.002507 loss: 0.1828 (0.2481) loss_classifier: 0.0920 (0.1188) loss_box_reg: 0.0631 (0.0770) loss_objectness: 0.0073 (0.0285) loss_rpn_box_reg: 0.0107 (0.0237) time: 0.1945 data: 0.0062 max mem: 0
Epoch: [0] [ 510/2910] eta: 0:07:44 lr: 0.002557 loss: 0.1828 (0.2468) loss_classifier: 0.0971 (0.1183) loss_box_reg: 0.0550 (0.0767) loss_objectness: 0.0078 (0.0283) loss_rpn_box_reg: 0.0100 (0.0235) time: 0.1947 data: 0.0062 max mem: 0
Epoch: [0] [ 520/2910] eta: 0:07:42 lr: 0.002607 loss: 0.1427 (0.2461) loss_classifier: 0.0814 (0.1179) loss_box_reg: 0.0509 (0.0763) loss_objectness: 0.0085 (0.0285) loss_rpn_box_reg: 0.0069 (0.0235) time: 0.1950 data: 0.0063 max mem: 0
Epoch: [0] [ 530/2910] eta: 0:07:40 lr: 0.002657 loss: 0.1454 (0.2469) loss_classifier: 0.0679 (0.1178) loss_box_reg: 0.0510 (0.0762) loss_objectness: 0.0165 (0.0289) loss_rpn_box_reg: 0.0102 (0.0240) time: 0.1952 data: 0.0063 max mem: 0
Epoch: [0] [ 540/2910] eta: 0:07:38 lr: 0.002707 loss: 0.2464 (0.2486) loss_classifier: 0.1195 (0.1181) loss_box_reg: 0.0634 (0.0762) loss_objectness: 0.0262 (0.0298) loss_rpn_box_reg: 0.0207 (0.0246) time: 0.1952 data: 0.0063 max mem: 0
Epoch: [0] [ 550/2910] eta: 0:07:36 lr: 0.002757 loss: 0.2477 (0.2482) loss_classifier: 0.1127 (0.1180) loss_box_reg: 0.0554 (0.0758) loss_objectness: 0.0293 (0.0299) loss_rpn_box_reg: 0.0192 (0.0245) time: 0.1953 data: 0.0062 max mem: 0
Epoch: [0] [ 560/2910] eta: 0:07:34 lr: 0.002807 loss: 0.2342 (0.2491) loss_classifier: 0.1127 (0.1185) loss_box_reg: 0.0626 (0.0761) loss_objectness: 0.0268 (0.0300) loss_rpn_box_reg: 0.0179 (0.0244) time: 0.1956 data: 0.0066 max mem: 0
Epoch: [0] [ 570/2910] eta: 0:07:33 lr: 0.002857 loss: 0.2137 (0.2493) loss_classifier: 0.1092 (0.1188) loss_box_reg: 0.0748 (0.0763) loss_objectness: 0.0211 (0.0298) loss_rpn_box_reg: 0.0175 (0.0244) time: 0.1954 data: 0.0066 max mem: 0
Epoch: [0] [ 580/2910] eta: 0:07:31 lr: 0.002907 loss: 0.1691 (0.2478) loss_classifier: 0.0807 (0.1181) loss_box_reg: 0.0530 (0.0760) loss_objectness: 0.0134 (0.0295) loss_rpn_box_reg: 0.0114 (0.0242) time: 0.1950 data: 0.0062 max mem: 0
Epoch: [0] [ 590/2910] eta: 0:07:29 lr: 0.002957 loss: 0.1869 (0.2489) loss_classifier: 0.0979 (0.1186) loss_box_reg: 0.0589 (0.0764) loss_objectness: 0.0113 (0.0294) loss_rpn_box_reg: 0.0142 (0.0245) time: 0.1951 data: 0.0062 max mem: 0
Epoch: [0] [ 600/2910] eta: 0:07:27 lr: 0.003007 loss: 0.2425 (0.2484) loss_classifier: 0.1281 (0.1186) loss_box_reg: 0.0767 (0.0762) loss_objectness: 0.0124 (0.0292) loss_rpn_box_reg: 0.0150 (0.0243) time: 0.1964 data: 0.0069 max mem: 0
Epoch: [0] [ 610/2910] eta: 0:07:25 lr: 0.003057 loss: 0.2202 (0.2477) loss_classifier: 0.1044 (0.1183) loss_box_reg: 0.0679 (0.0760) loss_objectness: 0.0123 (0.0291) loss_rpn_box_reg: 0.0145 (0.0244) time: 0.1963 data: 0.0068 max mem: 0
Epoch: [0] [ 620/2910] eta: 0:07:23 lr: 0.003107 loss: 0.2142 (0.2473) loss_classifier: 0.0996 (0.1179) loss_box_reg: 0.0596 (0.0760) loss_objectness: 0.0157 (0.0290) loss_rpn_box_reg: 0.0178 (0.0243) time: 0.1949 data: 0.0062 max mem: 0
Epoch: [0] [ 630/2910] eta: 0:07:21 lr: 0.003157 loss: 0.1617 (0.2464) loss_classifier: 0.0892 (0.1176) loss_box_reg: 0.0568 (0.0759) loss_objectness: 0.0146 (0.0287) loss_rpn_box_reg: 0.0137 (0.0242) time: 0.1950 data: 0.0062 max mem: 0
Epoch: [0] [ 640/2910] eta: 0:07:19 lr: 0.003207 loss: 0.2144 (0.2464) loss_classifier: 0.1029 (0.1176) loss_box_reg: 0.0774 (0.0761) loss_objectness: 0.0088 (0.0285) loss_rpn_box_reg: 0.0158 (0.0241) time: 0.1950 data: 0.0062 max mem: 0
Epoch: [0] [ 650/2910] eta: 0:07:18 lr: 0.003257 loss: 0.2356 (0.2456) loss_classifier: 0.1110 (0.1173) loss_box_reg: 0.0774 (0.0760) loss_objectness: 0.0089 (0.0283) loss_rpn_box_reg: 0.0151 (0.0240) time: 0.1950 data: 0.0062 max mem: 0