arjundd/meddlr-data · Datasets at Hugging Face

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[01/08 07:41:21] mr.evaluation.evaluator INFO: Inference done 110/320. 0.0221 s / img. ETA=0:00:32
[01/08 07:41:27] mr.evaluation.evaluator INFO: Inference done 143/320. 0.0221 s / img. ETA=0:00:27
[01/08 07:41:32] mr.evaluation.evaluator INFO: Inference done 176/320. 0.0221 s / img. ETA=0:00:22
[01/08 07:41:37] mr.evaluation.evaluator INFO: Inference done 209/320. 0.0221 s / img. ETA=0:00:17
[01/08 07:41:42] mr.evaluation.evaluator INFO: Inference done 242/320. 0.0221 s / img. ETA=0:00:12
[01/08 07:41:47] mr.evaluation.evaluator INFO: Inference done 275/320. 0.0221 s / img. ETA=0:00:06
[01/08 07:41:52] mr.evaluation.evaluator INFO: Inference done 308/320. 0.0221 s / img. ETA=0:00:01
[01/08 07:41:54] mr.evaluation.evaluator INFO: Total inference time: 0:00:49.053359 (0.155725 s / batch on 1 devices)
[01/08 07:41:54] mr.evaluation.evaluator INFO: Total inference pure compute time: 0:00:06 (0.021976 s / batch on 1 devices)
[01/08 07:42:04] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:42:04] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:42:07] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Slice metrics summary:
channel_0
--------------- --------------
val_nrmse 0.176 (0.045)
val_nrmse_mag 0.122 (0.030)
val_psnr 33.094 (3.019)
val_psnr_mag 36.272 (3.018)
val_ssim (Wang) 0.860 (0.080)

[01/08 07:42:07] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Scan metrics summary:
channel_0
-------------------- --------------
val_nrmse_mag_scan 0.113 (0.005)
val_nrmse_scan 0.163 (0.006)
val_psnr_mag_scan 44.208 (0.394)
val_psnr_scan 41.032 (0.507)
val_ssim (Wang)_scan 0.963 (0.002)

[01/08 07:42:07] mr.evaluation.evaluator INFO: Evaluation Time: 13.187915 s
[01/08 07:42:07] mr.engine.trainer INFO: Evaluation results for mridata_knee_2019_val in csv format:
[01/08 07:42:07] mr.evaluation.testing INFO: copypaste: val_nrmse,val_nrmse_mag,val_psnr,val_psnr_mag,val_ssim (Wang),val_nrmse_mag_scan,val_nrmse_scan,val_psnr_mag_scan,val_psnr_scan,val_ssim (Wang)_scan
[01/08 07:42:07] mr.evaluation.testing INFO: copypaste: 0.1758,0.1218,33.0937,36.2715,0.8602,0.1128,0.1626,44.2078,41.0316,0.9630
[01/08 07:42:07] mr.evaluation.testing INFO: Metrics (comma delimited):
val_nrmse,val_nrmse_mag,val_psnr,val_psnr_mag,val_ssim (Wang),val_nrmse_mag_scan,val_nrmse_scan,val_psnr_mag_scan,val_psnr_scan,val_ssim (Wang)_scan
0.1758,0.1218,33.0937,36.2715,0.8602,0.1128,0.1626,44.2078,41.0316,0.9630
[01/08 07:42:07] mr.utils.events INFO: eta: 0:11:15 iter: 399 loss: 14768.049 total_loss: 14768.049 time: 0.2410 data_time: 0.0001 lr: 0.000040 max_mem: 4235M
[01/08 07:42:13] mr.utils.events INFO: eta: 0:11:11 iter: 419 loss: 14830.163 total_loss: 14830.163 time: 0.2410 data_time: 0.0001 lr: 0.000042 max_mem: 4235M
[01/08 07:42:18] mr.utils.events INFO: eta: 0:11:06 iter: 439 loss: 16323.925 total_loss: 16323.925 time: 0.2410 data_time: 0.0001 lr: 0.000044 max_mem: 4235M
[01/08 07:42:23] mr.utils.events INFO: eta: 0:11:02 iter: 459 loss: 14716.628 total_loss: 14716.628 time: 0.2409 data_time: 0.0001 lr: 0.000046 max_mem: 4235M
[01/08 07:42:29] mr.utils.events INFO: eta: 0:10:57 iter: 479 loss: 15069.688 total_loss: 15069.688 time: 0.2409 data_time: 0.0001 lr: 0.000048 max_mem: 4235M
[01/08 07:42:34] mr.utils.events INFO: eta: 0:10:53 iter: 499 loss: 14391.693 total_loss: 14391.693 time: 0.2409 data_time: 0.0001 lr: 0.000050 max_mem: 4235M
[01/08 07:42:39] mr.utils.events INFO: eta: 0:10:48 iter: 519 loss: 14284.784 total_loss: 14284.784 time: 0.2409 data_time: 0.0001 lr: 0.000052 max_mem: 4235M
[01/08 07:42:45] mr.utils.events INFO: eta: 0:10:44 iter: 539 loss: 15812.837 total_loss: 15812.837 time: 0.2409 data_time: 0.0001 lr: 0.000054 max_mem: 4235M
[01/08 07:42:51] mr.utils.events INFO: eta: 0:10:39 iter: 559 loss: 15930.277 total_loss: 15930.277 time: 0.2409 data_time: 0.0001 lr: 0.000056 max_mem: 4235M
[01/08 07:43:02] mr.utils.events INFO: eta: 0:10:34 iter: 579 loss: 15495.331 total_loss: 15495.331 time: 0.2410 data_time: 0.0001 lr: 0.000058 max_mem: 4235M
[01/08 07:43:07] fvcore.common.checkpoint INFO: Saving checkpoint to /bmrNAS/people/arjun/results/meddlr/tests/basic/model_0000599.pth
[01/08 07:43:08] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/val.json takes 0.00 seconds
[01/08 07:43:08] mr.data.build INFO: Dropped 0 scans. 2 scans remaining
[01/08 07:43:08] mr.data.build INFO: Dropped references for 0/2 scans. 2 scans with reference remaining
[01/08 07:43:08] mr.evaluation.evaluator INFO: Start inference on 320 batches
[01/08 07:43:11] mr.evaluation.evaluator INFO: Inference done 11/320. 0.0221 s / img. ETA=0:00:48
[01/08 07:43:16] mr.evaluation.evaluator INFO: Inference done 44/320. 0.0221 s / img. ETA=0:00:42
[01/08 07:43:21] mr.evaluation.evaluator INFO: Inference done 77/320. 0.0222 s / img. ETA=0:00:37
[01/08 07:43:26] mr.evaluation.evaluator INFO: Inference done 109/320. 0.0222 s / img. ETA=0:00:32
[01/08 07:43:31] mr.evaluation.evaluator INFO: Inference done 141/320. 0.0222 s / img. ETA=0:00:27
[01/08 07:43:37] mr.evaluation.evaluator INFO: Inference done 173/320. 0.0222 s / img. ETA=0:00:22
[01/08 07:43:42] mr.evaluation.evaluator INFO: Inference done 205/320. 0.0222 s / img. ETA=0:00:17
[01/08 07:43:47] mr.evaluation.evaluator INFO: Inference done 237/320. 0.0222 s / img. ETA=0:00:12
[01/08 07:43:52] mr.evaluation.evaluator INFO: Inference done 269/320. 0.0222 s / img. ETA=0:00:07
[01/08 07:43:57] mr.evaluation.evaluator INFO: Inference done 301/320. 0.0222 s / img. ETA=0:00:02
[01/08 07:44:00] mr.evaluation.evaluator INFO: Total inference time: 0:00:49.342107 (0.156642 s / batch on 1 devices)
[01/08 07:44:00] mr.evaluation.evaluator INFO: Total inference pure compute time: 0:00:06 (0.022043 s / batch on 1 devices)
[01/08 07:44:09] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:44:09] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:44:13] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Slice metrics summary:
channel_0
--------------- --------------
val_nrmse 0.217 (0.036)
val_nrmse_mag 0.169 (0.023)
val_psnr 31.138 (2.830)
val_psnr_mag 33.292 (2.814)
val_ssim (Wang) 0.867 (0.077)

[01/08 07:44:13] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Scan metrics summary:
channel_0
-------------------- --------------
val_nrmse_mag_scan 0.162 (0.003)
val_nrmse_scan 0.207 (0.002)
val_psnr_mag_scan 41.054 (0.641)
val_psnr_scan 38.946 (0.736)
val_ssim (Wang)_scan 0.962 (0.000)

[01/08 07:44:13] mr.evaluation.evaluator INFO: Evaluation Time: 13.194743 s
[01/08 07:44:13] mr.engine.trainer INFO: Evaluation results for mridata_knee_2019_val in csv format:
[01/08 07:44:13] mr.evaluation.testing INFO: copypaste: val_nrmse,val_nrmse_mag,val_psnr,val_psnr_mag,val_ssim (Wang),val_nrmse_mag_scan,val_nrmse_scan,val_psnr_mag_scan,val_psnr_scan,val_ssim (Wang)_scan
[01/08 07:44:13] mr.evaluation.testing INFO: copypaste: 0.2174,0.1691,31.1379,33.2924,0.8669,0.1621,0.2066,41.0542,38.9462,0.9623
[01/08 07:44:13] mr.evaluation.testing INFO: Metrics (comma delimited):
val_nrmse,val_nrmse_mag,val_psnr,val_psnr_mag,val_ssim (Wang),val_nrmse_mag_scan,val_nrmse_scan,val_psnr_mag_scan,val_psnr_scan,val_ssim (Wang)_scan
0.2174,0.1691,31.1379,33.2924,0.8669,0.1621,0.2066,41.0542,38.9462,0.9623
[01/08 07:44:13] mr.utils.events INFO: eta: 0:09:24 iter: 599 loss: 13945.590 total_loss: 13945.590 time: 0.2409 data_time: 0.0001 lr: 0.000060 max_mem: 4237M
[01/08 07:44:18] mr.utils.events INFO: eta: 0:09:19 iter: 619 loss: 16922.678 total_loss: 16922.678 time: 0.2410 data_time: 0.0001 lr: 0.000062 max_mem: 4237M
[01/08 07:44:23] mr.utils.events INFO: eta: 0:09:15 iter: 639 loss: 14901.438 total_loss: 14901.438 time: 0.2410 data_time: 0.0001 lr: 0.000064 max_mem: 4237M
[01/08 07:44:28] mr.utils.events INFO: eta: 0:09:10 iter: 659 loss: 14073.586 total_loss: 14073.586 time: 0.2410 data_time: 0.0001 lr: 0.000066 max_mem: 4237M
[01/08 07:44:34] mr.utils.events INFO: eta: 0:09:06 iter: 679 loss: 16618.619 total_loss: 16618.619 time: 0.2410 data_time: 0.0001 lr: 0.000068 max_mem: 4237M
[01/08 07:44:39] mr.utils.events INFO: eta: 0:09:01 iter: 699 loss: 17848.932 total_loss: 17848.932 time: 0.2410 data_time: 0.0001 lr: 0.000070 max_mem: 4237M
[01/08 07:44:44] mr.utils.events INFO: eta: 0:08:56 iter: 719 loss: 16070.655 total_loss: 16070.655 time: 0.2410 data_time: 0.0001 lr: 0.000072 max_mem: 4237M
[01/08 07:44:49] mr.utils.events INFO: eta: 0:08:52 iter: 739 loss: 16163.839 total_loss: 16163.839 time: 0.2411 data_time: 0.0001 lr: 0.000074 max_mem: 4237M
[01/08 07:44:54] mr.utils.events INFO: eta: 0:08:47 iter: 759 loss: 15517.578 total_loss: 15517.578 time: 0.2411 data_time: 0.0001 lr: 0.000076 max_mem: 4237M
[01/08 07:45:00] mr.utils.events INFO: eta: 0:08:42 iter: 779 loss: 15658.616 total_loss: 15658.616 time: 0.2411 data_time: 0.0001 lr: 0.000078 max_mem: 4237M

[01/08 07:41:21] mr.evaluation.evaluator INFO: Inference done 110/320. 0.0221 s / img. ETA=0:00:32

[01/08 07:41:27] mr.evaluation.evaluator INFO: Inference done 143/320. 0.0221 s / img. ETA=0:00:27

[01/08 07:41:32] mr.evaluation.evaluator INFO: Inference done 176/320. 0.0221 s / img. ETA=0:00:22

[01/08 07:41:37] mr.evaluation.evaluator INFO: Inference done 209/320. 0.0221 s / img. ETA=0:00:17

[01/08 07:41:42] mr.evaluation.evaluator INFO: Inference done 242/320. 0.0221 s / img. ETA=0:00:12

[01/08 07:41:47] mr.evaluation.evaluator INFO: Inference done 275/320. 0.0221 s / img. ETA=0:00:06

[01/08 07:41:52] mr.evaluation.evaluator INFO: Inference done 308/320. 0.0221 s / img. ETA=0:00:01

[01/08 07:41:54] mr.evaluation.evaluator INFO: Total inference time: 0:00:49.053359 (0.155725 s / batch on 1 devices)

[01/08 07:41:54] mr.evaluation.evaluator INFO: Total inference pure compute time: 0:00:06 (0.021976 s / batch on 1 devices)

[01/08 07:42:04] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...

[01/08 07:42:07] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Slice metrics summary:

channel_0

--------------- --------------

val_nrmse 0.176 (0.045)

val_nrmse_mag 0.122 (0.030)

val_psnr 33.094 (3.019)

val_psnr_mag 36.272 (3.018)

val_ssim (Wang) 0.860 (0.080)

[01/08 07:42:07] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Scan metrics summary:

channel_0

-------------------- --------------

val_nrmse_mag_scan 0.113 (0.005)

val_nrmse_scan 0.163 (0.006)

val_psnr_mag_scan 44.208 (0.394)

val_psnr_scan 41.032 (0.507)

val_ssim (Wang)_scan 0.963 (0.002)

[01/08 07:42:07] mr.evaluation.evaluator INFO: Evaluation Time: 13.187915 s

[01/08 07:42:07] mr.engine.trainer INFO: Evaluation results for mridata_knee_2019_val in csv format:

[01/08 07:42:07] mr.evaluation.testing INFO: copypaste: val_nrmse,val_nrmse_mag,val_psnr,val_psnr_mag,val_ssim (Wang),val_nrmse_mag_scan,val_nrmse_scan,val_psnr_mag_scan,val_psnr_scan,val_ssim (Wang)_scan

[01/08 07:42:07] mr.evaluation.testing INFO: copypaste: 0.1758,0.1218,33.0937,36.2715,0.8602,0.1128,0.1626,44.2078,41.0316,0.9630

[01/08 07:42:07] mr.evaluation.testing INFO: Metrics (comma delimited):

val_nrmse,val_nrmse_mag,val_psnr,val_psnr_mag,val_ssim (Wang),val_nrmse_mag_scan,val_nrmse_scan,val_psnr_mag_scan,val_psnr_scan,val_ssim (Wang)_scan

0.1758,0.1218,33.0937,36.2715,0.8602,0.1128,0.1626,44.2078,41.0316,0.9630

[01/08 07:42:07] mr.utils.events INFO: eta: 0:11:15 iter: 399 loss: 14768.049 total_loss: 14768.049 time: 0.2410 data_time: 0.0001 lr: 0.000040 max_mem: 4235M

[01/08 07:42:13] mr.utils.events INFO: eta: 0:11:11 iter: 419 loss: 14830.163 total_loss: 14830.163 time: 0.2410 data_time: 0.0001 lr: 0.000042 max_mem: 4235M

[01/08 07:42:18] mr.utils.events INFO: eta: 0:11:06 iter: 439 loss: 16323.925 total_loss: 16323.925 time: 0.2410 data_time: 0.0001 lr: 0.000044 max_mem: 4235M

[01/08 07:42:23] mr.utils.events INFO: eta: 0:11:02 iter: 459 loss: 14716.628 total_loss: 14716.628 time: 0.2409 data_time: 0.0001 lr: 0.000046 max_mem: 4235M

[01/08 07:42:29] mr.utils.events INFO: eta: 0:10:57 iter: 479 loss: 15069.688 total_loss: 15069.688 time: 0.2409 data_time: 0.0001 lr: 0.000048 max_mem: 4235M

[01/08 07:42:34] mr.utils.events INFO: eta: 0:10:53 iter: 499 loss: 14391.693 total_loss: 14391.693 time: 0.2409 data_time: 0.0001 lr: 0.000050 max_mem: 4235M

[01/08 07:42:39] mr.utils.events INFO: eta: 0:10:48 iter: 519 loss: 14284.784 total_loss: 14284.784 time: 0.2409 data_time: 0.0001 lr: 0.000052 max_mem: 4235M

[01/08 07:42:45] mr.utils.events INFO: eta: 0:10:44 iter: 539 loss: 15812.837 total_loss: 15812.837 time: 0.2409 data_time: 0.0001 lr: 0.000054 max_mem: 4235M

[01/08 07:42:51] mr.utils.events INFO: eta: 0:10:39 iter: 559 loss: 15930.277 total_loss: 15930.277 time: 0.2409 data_time: 0.0001 lr: 0.000056 max_mem: 4235M

[01/08 07:43:02] mr.utils.events INFO: eta: 0:10:34 iter: 579 loss: 15495.331 total_loss: 15495.331 time: 0.2410 data_time: 0.0001 lr: 0.000058 max_mem: 4235M

[01/08 07:43:07] fvcore.common.checkpoint INFO: Saving checkpoint to /bmrNAS/people/arjun/results/meddlr/tests/basic/model_0000599.pth

[01/08 07:43:08] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/val.json takes 0.00 seconds

[01/08 07:43:08] mr.data.build INFO: Dropped 0 scans. 2 scans remaining

[01/08 07:43:08] mr.data.build INFO: Dropped references for 0/2 scans. 2 scans with reference remaining

[01/08 07:43:08] mr.evaluation.evaluator INFO: Start inference on 320 batches

[01/08 07:43:11] mr.evaluation.evaluator INFO: Inference done 11/320. 0.0221 s / img. ETA=0:00:48

[01/08 07:43:16] mr.evaluation.evaluator INFO: Inference done 44/320. 0.0221 s / img. ETA=0:00:42

[01/08 07:43:21] mr.evaluation.evaluator INFO: Inference done 77/320. 0.0222 s / img. ETA=0:00:37

[01/08 07:43:26] mr.evaluation.evaluator INFO: Inference done 109/320. 0.0222 s / img. ETA=0:00:32

[01/08 07:43:31] mr.evaluation.evaluator INFO: Inference done 141/320. 0.0222 s / img. ETA=0:00:27

[01/08 07:43:37] mr.evaluation.evaluator INFO: Inference done 173/320. 0.0222 s / img. ETA=0:00:22

[01/08 07:43:42] mr.evaluation.evaluator INFO: Inference done 205/320. 0.0222 s / img. ETA=0:00:17

[01/08 07:43:47] mr.evaluation.evaluator INFO: Inference done 237/320. 0.0222 s / img. ETA=0:00:12

[01/08 07:43:52] mr.evaluation.evaluator INFO: Inference done 269/320. 0.0222 s / img. ETA=0:00:07

[01/08 07:43:57] mr.evaluation.evaluator INFO: Inference done 301/320. 0.0222 s / img. ETA=0:00:02

[01/08 07:44:00] mr.evaluation.evaluator INFO: Total inference time: 0:00:49.342107 (0.156642 s / batch on 1 devices)

[01/08 07:44:00] mr.evaluation.evaluator INFO: Total inference pure compute time: 0:00:06 (0.022043 s / batch on 1 devices)

[01/08 07:44:09] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...

[01/08 07:44:13] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Slice metrics summary:

channel_0

--------------- --------------

val_nrmse 0.217 (0.036)

val_nrmse_mag 0.169 (0.023)

val_psnr 31.138 (2.830)

val_psnr_mag 33.292 (2.814)

val_ssim (Wang) 0.867 (0.077)

[01/08 07:44:13] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Scan metrics summary:

channel_0

-------------------- --------------

val_nrmse_mag_scan 0.162 (0.003)

val_nrmse_scan 0.207 (0.002)

val_psnr_mag_scan 41.054 (0.641)

val_psnr_scan 38.946 (0.736)

val_ssim (Wang)_scan 0.962 (0.000)

[01/08 07:44:13] mr.evaluation.evaluator INFO: Evaluation Time: 13.194743 s

[01/08 07:44:13] mr.engine.trainer INFO: Evaluation results for mridata_knee_2019_val in csv format:

[01/08 07:44:13] mr.evaluation.testing INFO: copypaste: val_nrmse,val_nrmse_mag,val_psnr,val_psnr_mag,val_ssim (Wang),val_nrmse_mag_scan,val_nrmse_scan,val_psnr_mag_scan,val_psnr_scan,val_ssim (Wang)_scan

[01/08 07:44:13] mr.evaluation.testing INFO: copypaste: 0.2174,0.1691,31.1379,33.2924,0.8669,0.1621,0.2066,41.0542,38.9462,0.9623

[01/08 07:44:13] mr.evaluation.testing INFO: Metrics (comma delimited):

val_nrmse,val_nrmse_mag,val_psnr,val_psnr_mag,val_ssim (Wang),val_nrmse_mag_scan,val_nrmse_scan,val_psnr_mag_scan,val_psnr_scan,val_ssim (Wang)_scan

0.2174,0.1691,31.1379,33.2924,0.8669,0.1621,0.2066,41.0542,38.9462,0.9623

[01/08 07:44:13] mr.utils.events INFO: eta: 0:09:24 iter: 599 loss: 13945.590 total_loss: 13945.590 time: 0.2409 data_time: 0.0001 lr: 0.000060 max_mem: 4237M

[01/08 07:44:18] mr.utils.events INFO: eta: 0:09:19 iter: 619 loss: 16922.678 total_loss: 16922.678 time: 0.2410 data_time: 0.0001 lr: 0.000062 max_mem: 4237M

[01/08 07:44:23] mr.utils.events INFO: eta: 0:09:15 iter: 639 loss: 14901.438 total_loss: 14901.438 time: 0.2410 data_time: 0.0001 lr: 0.000064 max_mem: 4237M

[01/08 07:44:28] mr.utils.events INFO: eta: 0:09:10 iter: 659 loss: 14073.586 total_loss: 14073.586 time: 0.2410 data_time: 0.0001 lr: 0.000066 max_mem: 4237M

[01/08 07:44:34] mr.utils.events INFO: eta: 0:09:06 iter: 679 loss: 16618.619 total_loss: 16618.619 time: 0.2410 data_time: 0.0001 lr: 0.000068 max_mem: 4237M

[01/08 07:44:39] mr.utils.events INFO: eta: 0:09:01 iter: 699 loss: 17848.932 total_loss: 17848.932 time: 0.2410 data_time: 0.0001 lr: 0.000070 max_mem: 4237M

[01/08 07:44:44] mr.utils.events INFO: eta: 0:08:56 iter: 719 loss: 16070.655 total_loss: 16070.655 time: 0.2410 data_time: 0.0001 lr: 0.000072 max_mem: 4237M

[01/08 07:44:49] mr.utils.events INFO: eta: 0:08:52 iter: 739 loss: 16163.839 total_loss: 16163.839 time: 0.2411 data_time: 0.0001 lr: 0.000074 max_mem: 4237M

[01/08 07:44:54] mr.utils.events INFO: eta: 0:08:47 iter: 759 loss: 15517.578 total_loss: 15517.578 time: 0.2411 data_time: 0.0001 lr: 0.000076 max_mem: 4237M

[01/08 07:45:00] mr.utils.events INFO: eta: 0:08:42 iter: 779 loss: 15658.616 total_loss: 15658.616 time: 0.2411 data_time: 0.0001 lr: 0.000078 max_mem: 4237M