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[01/08 07:36:30] meddlr INFO: Running in debug mode
[01/08 07:36:30] meddlr INFO: Environment info:
------------------- ----------------------------------------------------------------------------------------------
sys.platform linux
Python 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0]
numpy 1.20.3
PyTorch 1.7.1 @/bmrNAS/people/arjun/miniconda3/envs/meddlr_env/lib/python3.7/site-packages/torch
PyTorch debug build False
CUDA available False
Pillow 8.4.0
torchvision 0.8.2 @/bmrNAS/people/arjun/miniconda3/envs/meddlr_env/lib/python3.7/site-packages/torchvision
SLURM_JOB_ID slurm not detected
------------------- ----------------------------------------------------------------------------------------------
PyTorch built with:
- GCC 7.3
- C++ Version: 201402
- Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v1.6.0 (Git Hash 5ef631a030a6f73131c77892041042805a06064f)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- NNPACK is enabled
- CPU capability usage: AVX
- Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,
[01/08 07:36:30] meddlr INFO: Command line arguments: Namespace(auto_version=False, config_file='../configs/tests/basic.yaml', debug=True, devices=None, eval_only=False, num_gpus=1, opts=['DATALOADER.NUM_WORKERS', '8', 'SOLVER.MAX_ITER', '1600', 'SOLVER.CHECKPOINT_PERIOD', '200', 'TEST.EVAL_PERIOD', '200'], reproducible=False, restart_iter=False, resume=False)
[01/08 07:36:30] meddlr INFO: Contents of args.config_file=../configs/tests/basic.yaml:
# Basic testing config
# Use this for any testing you may want to do in the future.
# The model will be trained for 60 iterations (not epochs)
# on the mridata.org 2019 knee dataset.
MODEL:
UNROLLED:
NUM_UNROLLED_STEPS: 8
NUM_RESBLOCKS: 2
NUM_FEATURES: 128
DROPOUT: 0.
DATASETS:
TRAIN: ("mridata_knee_2019_train",)
VAL: ("mridata_knee_2019_val",)
TEST: ("mridata_knee_2019_test",)
DATALOADER:
NUM_WORKERS: 0 # for debugging purposes
SOLVER:
TRAIN_BATCH_SIZE: 1
TEST_BATCH_SIZE: 2
CHECKPOINT_PERIOD: 20
MAX_ITER: 80
TEST:
EVAL_PERIOD: 40
VIS_PERIOD: 20
TIME_SCALE: "iter"
OUTPUT_DIR: "results://tests/basic"
VERSION: 1
[01/08 07:37:52] meddlr INFO: Running in debug mode
[01/08 07:37:54] meddlr INFO: Environment info:
---------------------- ----------------------------------------------------------------------------------------------
sys.platform linux
Python 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0]
numpy 1.20.3
PyTorch 1.7.1 @/bmrNAS/people/arjun/miniconda3/envs/meddlr_env/lib/python3.7/site-packages/torch
PyTorch debug build False
CUDA available True
GPU 0 GeForce RTX 2080 Ti
CUDA_HOME /usr/local/cuda
NVCC Cuda compilation tools, release 9.0, V9.0.176
Pillow 8.4.0
torchvision 0.8.2 @/bmrNAS/people/arjun/miniconda3/envs/meddlr_env/lib/python3.7/site-packages/torchvision
torchvision arch flags sm_35, sm_50, sm_60, sm_70, sm_75
SLURM_JOB_ID 29543
---------------------- ----------------------------------------------------------------------------------------------
PyTorch built with:
- GCC 7.3
- C++ Version: 201402
- Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v1.6.0 (Git Hash 5ef631a030a6f73131c77892041042805a06064f)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 10.2
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
- CuDNN 7.6.5
- Magma 2.5.2
- Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,
[01/08 07:37:54] meddlr INFO: Command line arguments: Namespace(auto_version=False, config_file='../configs/tests/basic.yaml', debug=True, devices=None, eval_only=False, num_gpus=1, opts=['DATALOADER.NUM_WORKERS', '8', 'SOLVER.MAX_ITER', '1600', 'SOLVER.CHECKPOINT_PERIOD', '200', 'TEST.EVAL_PERIOD', '200'], reproducible=False, restart_iter=False, resume=False)
[01/08 07:37:54] meddlr INFO: Contents of args.config_file=../configs/tests/basic.yaml:
# Basic testing config
# Use this for any testing you may want to do in the future.
# The model will be trained for 60 iterations (not epochs)
# on the mridata.org 2019 knee dataset.
MODEL:
UNROLLED:
NUM_UNROLLED_STEPS: 8
NUM_RESBLOCKS: 2
NUM_FEATURES: 128
DROPOUT: 0.
DATASETS:
TRAIN: ("mridata_knee_2019_train",)
VAL: ("mridata_knee_2019_val",)
TEST: ("mridata_knee_2019_test",)
DATALOADER:
NUM_WORKERS: 0 # for debugging purposes
SOLVER:
TRAIN_BATCH_SIZE: 1
TEST_BATCH_SIZE: 2
CHECKPOINT_PERIOD: 20
MAX_ITER: 80
TEST:
EVAL_PERIOD: 40
VIS_PERIOD: 20
TIME_SCALE: "iter"
OUTPUT_DIR: "results://tests/basic"
VERSION: 1
[01/08 07:37:54] meddlr INFO: Running with full config:
AUG_TEST:
UNDERSAMPLE:
ACCELERATIONS: (6,)
AUG_TRAIN:
MOTION_P: 0.2
MRI_RECON:
AUG_SENSITIVITY_MAPS: True
SCHEDULER_P:
IGNORE: False
TRANSFORMS: ()
NOISE_P: 0.2
UNDERSAMPLE:
ACCELERATIONS: (6,)
CALIBRATION_SIZE: 20
CENTER_FRACTIONS: ()
MAX_ATTEMPTS: 30
NAME: PoissonDiskMaskFunc
USE_MOTION: False
USE_NOISE: False
CUDNN_BENCHMARK: False
DATALOADER:
ALT_SAMPLER:
PERIOD_SUPERVISED: 1
PERIOD_UNSUPERVISED: 1
DATA_KEYS: ()
DROP_LAST: True
FILTER:
BY: ()
GROUP_SAMPLER:
AS_BATCH_SAMPLER: False
BATCH_BY: ()
NUM_WORKERS: 8
PREFETCH_FACTOR: 2
SAMPLER_TRAIN:
SUBSAMPLE_TRAIN:
NUM_TOTAL: -1
NUM_TOTAL_BY_GROUP: ()
NUM_UNDERSAMPLED: 0
NUM_VAL: -1
NUM_VAL_BY_GROUP: ()
SEED: 1000
DATASETS:
TEST: ('mridata_knee_2019_test',)
TRAIN: ('mridata_knee_2019_train',)
VAL: ('mridata_knee_2019_val',)
DESCRIPTION:
BRIEF:
ENTITY_NAME: ss_recon
EXP_NAME:
PROJECT_NAME: ss_recon
TAGS: ()
MODEL:
A2R:
META_ARCHITECTURE: GeneralizedUnrolledCNN
USE_SUPERVISED_CONSISTENCY: False
CONSISTENCY:
AUG:
MOTION:
RANGE: (0.2, 0.5)
SCHEDULER:
WARMUP_ITERS: 0
WARMUP_METHOD:
MRI_RECON:
AUG_SENSITIVITY_MAPS: True
SCHEDULER_P:
IGNORE: False
TRANSFORMS: ()
NOISE:
MASK:
RHO: 1.0
SCHEDULER:
WARMUP_ITERS: 0
WARMUP_METHOD:
STD_DEV: (1,)
LATENT_LOSS_NAME: mag_l1
LATENT_LOSS_WEIGHT: 0.1
LOSS_NAME: l1
LOSS_WEIGHT: 0.1
NUM_LATENT_LAYERS: 1
USE_CONSISTENCY: True
USE_LATENT: False
CS:
MAX_ITER: 200
REGULARIZATION: 0.005
DENOISING:
META_ARCHITECTURE: GeneralizedUnrolledCNN
NOISE:
STD_DEV: (1,)
USE_FULLY_SAMPLED_TARGET: True
USE_FULLY_SAMPLED_TARGET_EVAL: None
DEVICE: cuda
M2R:
META_ARCHITECTURE: GeneralizedUnrolledCNN
USE_SUPERVISED_CONSISTENCY: False
META_ARCHITECTURE: GeneralizedUnrolledCNN
N2R:
META_ARCHITECTURE: GeneralizedUnrolledCNN
USE_SUPERVISED_CONSISTENCY: False
NM2R:
META_ARCHITECTURE: GeneralizedUnrolledCNN
USE_SUPERVISED_CONSISTENCY: False
NORMALIZER:
KEYWORDS: ()
NAME: TopMagnitudeNormalizer
RECON_LOSS:
NAME: l1
RENORMALIZE_DATA: True
SEG:
ACTIVATION: sigmoid
CLASSES: ()
INCLUDE_BACKGROUND: False
SSDU:
MASKER:
PARAMS:
META_ARCHITECTURE: GeneralizedUnrolledCNN
UNET:
BLOCK_ORDER: ('conv', 'relu', 'conv', 'relu', 'batchnorm', 'dropout')
CHANNELS: 32
DROPOUT: 0.0
IN_CHANNELS: 2
NORMALIZE: False
NUM_POOL_LAYERS: 4
OUT_CHANNELS: 2
UNROLLED:
BLOCK_ARCHITECTURE: ResNet
CONV_BLOCK:
ACTIVATION: relu
NORM: none
NORM_AFFINE: False
ORDER: ('norm', 'act', 'drop', 'conv')
DROPOUT: 0.0
FIX_STEP_SIZE: False
KERNEL_SIZE: (3,)
NUM_EMAPS: 1
NUM_FEATURES: 128
NUM_RESBLOCKS: 2
NUM_UNROLLED_STEPS: 8
PADDING:
SHARE_WEIGHTS: False
WEIGHTS:
OUTPUT_DIR: /bmrNAS/people/arjun/results/meddlr/tests/basic
SEED: -1
SOLVER:
BASE_LR: 0.0001
BIAS_LR_FACTOR: 1.0
CHECKPOINT_PERIOD: 200
GAMMA: 0.1
GRAD_ACCUM_ITERS: 1
LR_SCHEDULER_NAME: WarmupMultiStepLR
MAX_ITER: 1600
MOMENTUM: 0.9
OPTIMIZER: Adam
STEPS: (30000,)
TEST_BATCH_SIZE: 2
TRAIN_BATCH_SIZE: 1
WARMUP_FACTOR: 0.001
WARMUP_ITERS: 1000
WARMUP_METHOD: linear
WEIGHT_DECAY: 0.0001
WEIGHT_DECAY_BIAS: 0.0001
WEIGHT_DECAY_NORM: 0.0
TEST:
EVAL_PERIOD: 200
EXPECTED_RESULTS: []
FLUSH_PERIOD: 0
VAL_AS_TEST: True
VAL_METRICS:
RECON: ()
TIME_SCALE: iter
VERSION: 1
VIS_PERIOD: 20
[01/08 07:37:54] meddlr INFO: Full config saved to /bmrNAS/people/arjun/results/meddlr/tests/basic/config.yaml
[01/08 07:37:54] mr.utils.env INFO: Using a generated random seed 55308770
[01/08 07:37:54] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/train.json takes 0.04 seconds
[01/08 07:37:54] mr.data.build INFO: Dropped 0 scans. 14 scans remaining
[01/08 07:37:54] mr.data.build INFO: Dropped references for 0/14 scans. 14 scans with reference remaining
[01/08 07:37:54] meddlr INFO: Calculated 4480 iterations per epoch
[01/08 07:37:54] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/train.json takes 0.00 seconds
[01/08 07:37:54] mr.data.build INFO: Dropped 0 scans. 14 scans remaining
[01/08 07:37:54] mr.data.build INFO: Dropped references for 0/14 scans. 14 scans with reference remaining
[01/08 07:38:01] fvcore.common.checkpoint INFO: No checkpoint found. Initializing model from scratch
[01/08 07:38:01] mr.engine.train_loop INFO: Starting training from iteration 0
[01/08 07:38:13] mr.utils.events INFO: eta: 0:05:59 iter: 19 loss: 100222.734 total_loss: 100222.734 time: 0.2279 data_time: 0.2790 lr: 0.000002 max_mem: 2468M
[01/08 07:38:18] mr.utils.events INFO: eta: 0:05:55 iter: 39 loss: 31516.157 total_loss: 31516.157 time: 0.2280 data_time: 0.0001 lr: 0.000004 max_mem: 2468M
[01/08 07:38:23] mr.utils.events INFO: eta: 0:05:51 iter: 59 loss: 27504.994 total_loss: 27504.994 time: 0.2283 data_time: 0.0001 lr: 0.000006 max_mem: 2468M
[01/08 07:38:28] mr.utils.events INFO: eta: 0:05:47 iter: 79 loss: 24592.978 total_loss: 24592.978 time: 0.2288 data_time: 0.0001 lr: 0.000008 max_mem: 2468M
[01/08 07:38:34] mr.utils.events INFO: eta: 0:05:43 iter: 99 loss: 24272.967 total_loss: 24272.967 time: 0.2399 data_time: 0.0528 lr: 0.000010 max_mem: 2468M
[01/08 07:38:39] mr.utils.events INFO: eta: 0:05:39 iter: 119 loss: 21447.893 total_loss: 21447.893 time: 0.2385 data_time: 0.0001 lr: 0.000012 max_mem: 2468M
[01/08 07:38:44] mr.utils.events INFO: eta: 0:05:35 iter: 139 loss: 21284.981 total_loss: 21284.981 time: 0.2376 data_time: 0.0001 lr: 0.000014 max_mem: 2468M
[01/08 07:38:49] mr.utils.events INFO: eta: 0:05:31 iter: 159 loss: 22184.024 total_loss: 22184.024 time: 0.2369 data_time: 0.0001 lr: 0.000016 max_mem: 2468M
[01/08 07:38:55] mr.utils.events INFO: eta: 0:05:27 iter: 179 loss: 20008.485 total_loss: 20008.485 time: 0.2365 data_time: 0.0001 lr: 0.000018 max_mem: 2468M
[01/08 07:39:00] fvcore.common.checkpoint INFO: Saving checkpoint to /bmrNAS/people/arjun/results/meddlr/tests/basic/model_0000199.pth
[01/08 07:39:01] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/val.json takes 0.07 seconds
[01/08 07:39:01] mr.data.build INFO: Dropped 0 scans. 2 scans remaining
[01/08 07:39:01] mr.data.build INFO: Dropped references for 0/2 scans. 2 scans with reference remaining
[01/08 07:39:01] mr.evaluation.evaluator INFO: Start inference on 320 batches
[01/08 07:39:05] mr.evaluation.evaluator INFO: Inference done 11/320. 0.0258 s / img. ETA=0:00:46
[01/08 07:39:10] mr.evaluation.evaluator INFO: Inference done 44/320. 0.0238 s / img. ETA=0:00:41
[01/08 07:39:15] mr.evaluation.evaluator INFO: Inference done 77/320. 0.0229 s / img. ETA=0:00:36
[01/08 07:39:20] mr.evaluation.evaluator INFO: Inference done 110/320. 0.0226 s / img. ETA=0:00:31
[01/08 07:39:25] mr.evaluation.evaluator INFO: Inference done 143/320. 0.0224 s / img. ETA=0:00:26
[01/08 07:39:30] mr.evaluation.evaluator INFO: Inference done 176/320. 0.0223 s / img. ETA=0:00:21
[01/08 07:39:35] mr.evaluation.evaluator INFO: Inference done 209/320. 0.0222 s / img. ETA=0:00:16
[01/08 07:39:40] mr.evaluation.evaluator INFO: Inference done 237/320. 0.0221 s / img. ETA=0:00:12
[01/08 07:39:45] mr.evaluation.evaluator INFO: Inference done 270/320. 0.0221 s / img. ETA=0:00:07
[01/08 07:39:50] mr.evaluation.evaluator INFO: Inference done 303/320. 0.0220 s / img. ETA=0:00:02
[01/08 07:39:53] mr.evaluation.evaluator INFO: Total inference time: 0:00:48.855011 (0.155095 s / batch on 1 devices)
[01/08 07:39:53] mr.evaluation.evaluator INFO: Total inference pure compute time: 0:00:06 (0.021862 s / batch on 1 devices)
[01/08 07:40:03] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:40:03] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:40:06] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Slice metrics summary:
channel_0
--------------- --------------
val_nrmse 0.211 (0.055)
val_nrmse_mag 0.140 (0.033)
val_psnr 31.509 (2.961)
val_psnr_mag 35.018 (2.864)
val_ssim (Wang) 0.831 (0.090)
[01/08 07:40:06] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Scan metrics summary:
channel_0
-------------------- --------------
val_nrmse_mag_scan 0.131 (0.007)
val_nrmse_scan 0.195 (0.012)
val_psnr_mag_scan 42.912 (0.363)
val_psnr_scan 39.450 (0.290)
val_ssim (Wang)_scan 0.957 (0.003)
[01/08 07:40:06] mr.evaluation.evaluator INFO: Evaluation Time: 13.612028 s
[01/08 07:40:06] mr.engine.trainer INFO: Evaluation results for mridata_knee_2019_val in csv format:
[01/08 07:40:06] 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 07:40:06] mr.evaluation.testing INFO: copypaste: 0.2112,0.1404,31.5090,35.0178,0.8314,0.1310,0.1952,42.9119,39.4501,0.9571
[01/08 07:40:06] 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
0.2112,0.1404,31.5090,35.0178,0.8314,0.1310,0.1952,42.9119,39.4501,0.9571
[01/08 07:40:06] mr.utils.events INFO: eta: 0:13:01 iter: 199 loss: 18439.461 total_loss: 18439.461 time: 0.2363 data_time: 0.0001 lr: 0.000020 max_mem: 4234M
[01/08 07:40:12] mr.utils.events INFO: eta: 0:12:57 iter: 219 loss: 17119.530 total_loss: 17119.530 time: 0.2367 data_time: 0.0001 lr: 0.000022 max_mem: 4234M
[01/08 07:40:17] mr.utils.events INFO: eta: 0:12:53 iter: 239 loss: 16810.184 total_loss: 16810.184 time: 0.2394 data_time: 0.0279 lr: 0.000024 max_mem: 4234M
[01/08 07:40:22] mr.utils.events INFO: eta: 0:12:49 iter: 259 loss: 15697.525 total_loss: 15697.525 time: 0.2395 data_time: 0.0001 lr: 0.000026 max_mem: 4234M
[01/08 07:40:28] mr.utils.events INFO: eta: 0:12:45 iter: 279 loss: 16743.501 total_loss: 16743.501 time: 0.2393 data_time: 0.0001 lr: 0.000028 max_mem: 4234M
[01/08 07:40:33] mr.utils.events INFO: eta: 0:12:40 iter: 299 loss: 18045.708 total_loss: 18045.708 time: 0.2392 data_time: 0.0013 lr: 0.000030 max_mem: 4234M
[01/08 07:40:39] mr.utils.events INFO: eta: 0:12:36 iter: 319 loss: 16170.239 total_loss: 16170.239 time: 0.2392 data_time: 0.0001 lr: 0.000032 max_mem: 4234M
[01/08 07:40:45] mr.utils.events INFO: eta: 0:12:32 iter: 339 loss: 16581.456 total_loss: 16581.456 time: 0.2412 data_time: 0.0363 lr: 0.000034 max_mem: 4234M
[01/08 07:40:50] mr.utils.events INFO: eta: 0:12:28 iter: 359 loss: 17071.639 total_loss: 17071.639 time: 0.2411 data_time: 0.0001 lr: 0.000036 max_mem: 4234M
[01/08 07:40:56] mr.utils.events INFO: eta: 0:12:25 iter: 379 loss: 16226.621 total_loss: 16226.621 time: 0.2411 data_time: 0.0001 lr: 0.000038 max_mem: 4234M
[01/08 07:41:01] fvcore.common.checkpoint INFO: Saving checkpoint to /bmrNAS/people/arjun/results/meddlr/tests/basic/model_0000399.pth
[01/08 07:41:02] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/val.json takes 0.00 seconds
[01/08 07:41:02] mr.data.build INFO: Dropped 0 scans. 2 scans remaining
[01/08 07:41:02] mr.data.build INFO: Dropped references for 0/2 scans. 2 scans with reference remaining
[01/08 07:41:02] mr.evaluation.evaluator INFO: Start inference on 320 batches
[01/08 07:41:06] mr.evaluation.evaluator INFO: Inference done 11/320. 0.0223 s / img. ETA=0:00:47
[01/08 07:41:11] mr.evaluation.evaluator INFO: Inference done 44/320. 0.0222 s / img. ETA=0:00:42
[01/08 07:41:16] mr.evaluation.evaluator INFO: Inference done 77/320. 0.0221 s / img. ETA=0:00:37
[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 07:45:05] fvcore.common.checkpoint INFO: Saving checkpoint to /bmrNAS/people/arjun/results/meddlr/tests/basic/model_0000799.pth
[01/08 07:45:05] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/val.json takes 0.00 seconds
[01/08 07:45:05] mr.data.build INFO: Dropped 0 scans. 2 scans remaining
[01/08 07:45:05] mr.data.build INFO: Dropped references for 0/2 scans. 2 scans with reference remaining
[01/08 07:45:05] mr.evaluation.evaluator INFO: Start inference on 320 batches
[01/08 07:45:09] mr.evaluation.evaluator INFO: Inference done 11/320. 0.0251 s / img. ETA=0:00:48
[01/08 07:45:14] mr.evaluation.evaluator INFO: Inference done 43/320. 0.0227 s / img. ETA=0:00:43
[01/08 07:45:19] mr.evaluation.evaluator INFO: Inference done 75/320. 0.0224 s / img. ETA=0:00:38
[01/08 07:45:24] mr.evaluation.evaluator INFO: Inference done 107/320. 0.0224 s / img. ETA=0:00:33
[01/08 07:45:29] mr.evaluation.evaluator INFO: Inference done 139/320. 0.0223 s / img. ETA=0:00:28
[01/08 07:45:34] mr.evaluation.evaluator INFO: Inference done 171/320. 0.0223 s / img. ETA=0:00:23
[01/08 07:45:39] mr.evaluation.evaluator INFO: Inference done 203/320. 0.0223 s / img. ETA=0:00:18
[01/08 07:45:44] mr.evaluation.evaluator INFO: Inference done 235/320. 0.0223 s / img. ETA=0:00:13
[01/08 07:45:49] mr.evaluation.evaluator INFO: Inference done 267/320. 0.0223 s / img. ETA=0:00:08
[01/08 07:45:54] mr.evaluation.evaluator INFO: Inference done 299/320. 0.0222 s / img. ETA=0:00:03
[01/08 07:45:57] mr.evaluation.evaluator INFO: Total inference time: 0:00:49.500946 (0.157146 s / batch on 1 devices)
[01/08 07:45:57] mr.evaluation.evaluator INFO: Total inference pure compute time: 0:00:06 (0.022107 s / batch on 1 devices)
[01/08 07:46:07] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:46:07] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:46:10] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Slice metrics summary:
channel_0
--------------- --------------
val_nrmse 0.175 (0.043)
val_nrmse_mag 0.120 (0.032)
val_psnr 33.099 (2.996)
val_psnr_mag 36.426 (3.111)
val_ssim (Wang) 0.866 (0.082)
[01/08 07:46:10] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Scan metrics summary:
channel_0
-------------------- --------------
val_nrmse_mag_scan 0.111 (0.006)
val_nrmse_scan 0.163 (0.006)
val_psnr_mag_scan 44.388 (0.314)
val_psnr_scan 41.028 (0.479)
val_ssim (Wang)_scan 0.964 (0.002)
[01/08 07:46:10] mr.evaluation.evaluator INFO: Evaluation Time: 13.062179 s
[01/08 07:46:10] mr.engine.trainer INFO: Evaluation results for mridata_knee_2019_val in csv format:
[01/08 07:46:10] 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 07:46:10] mr.evaluation.testing INFO: copypaste: 0.1754,0.1200,33.0992,36.4262,0.8660,0.1105,0.1627,44.3880,41.0275,0.9637
[01/08 07:46:10] 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
0.1754,0.1200,33.0992,36.4262,0.8660,0.1105,0.1627,44.3880,41.0275,0.9637
[01/08 07:46:10] mr.utils.events INFO: eta: 0:07:32 iter: 799 loss: 15171.014 total_loss: 15171.014 time: 0.2411 data_time: 0.0001 lr: 0.000080 max_mem: 4238M
[01/08 07:46:16] mr.utils.events INFO: eta: 0:07:27 iter: 819 loss: 14583.270 total_loss: 14583.270 time: 0.2411 data_time: 0.0001 lr: 0.000082 max_mem: 4238M
[01/08 07:46:21] mr.utils.events INFO: eta: 0:07:23 iter: 839 loss: 14240.295 total_loss: 14240.295 time: 0.2411 data_time: 0.0001 lr: 0.000084 max_mem: 4238M
[01/08 07:46:26] mr.utils.events INFO: eta: 0:07:18 iter: 859 loss: 15098.030 total_loss: 15098.030 time: 0.2411 data_time: 0.0001 lr: 0.000086 max_mem: 4238M
[01/08 07:46:31] mr.utils.events INFO: eta: 0:07:13 iter: 879 loss: 15402.230 total_loss: 15402.230 time: 0.2412 data_time: 0.0001 lr: 0.000088 max_mem: 4238M
[01/08 07:46:36] mr.utils.events INFO: eta: 0:07:08 iter: 899 loss: 14225.305 total_loss: 14225.305 time: 0.2412 data_time: 0.0001 lr: 0.000090 max_mem: 4238M
[01/08 07:46:43] mr.utils.events INFO: eta: 0:07:04 iter: 919 loss: 13569.448 total_loss: 13569.448 time: 0.2412 data_time: 0.0001 lr: 0.000092 max_mem: 4238M
[01/08 07:46:48] mr.utils.events INFO: eta: 0:06:59 iter: 939 loss: 14107.779 total_loss: 14107.779 time: 0.2412 data_time: 0.0001 lr: 0.000094 max_mem: 4238M
[01/08 07:46:53] mr.utils.events INFO: eta: 0:06:54 iter: 959 loss: 14675.758 total_loss: 14675.758 time: 0.2413 data_time: 0.0001 lr: 0.000096 max_mem: 4238M
[01/08 07:46:58] mr.utils.events INFO: eta: 0:06:50 iter: 979 loss: 14544.494 total_loss: 14544.494 time: 0.2413 data_time: 0.0001 lr: 0.000098 max_mem: 4238M
[01/08 07:47:03] fvcore.common.checkpoint INFO: Saving checkpoint to /bmrNAS/people/arjun/results/meddlr/tests/basic/model_0000999.pth
[01/08 07:47:04] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/val.json takes 0.00 seconds
[01/08 07:47:04] mr.data.build INFO: Dropped 0 scans. 2 scans remaining
[01/08 07:47:04] mr.data.build INFO: Dropped references for 0/2 scans. 2 scans with reference remaining
[01/08 07:47:04] mr.evaluation.evaluator INFO: Start inference on 320 batches
[01/08 07:47:08] mr.evaluation.evaluator INFO: Inference done 11/320. 0.0250 s / img. ETA=0:00:48
[01/08 07:47:13] mr.evaluation.evaluator INFO: Inference done 43/320. 0.0227 s / img. ETA=0:00:43
[01/08 07:47:18] mr.evaluation.evaluator INFO: Inference done 75/320. 0.0225 s / img. ETA=0:00:38
[01/08 07:47:23] mr.evaluation.evaluator INFO: Inference done 107/320. 0.0225 s / img. ETA=0:00:33
[01/08 07:47:28] mr.evaluation.evaluator INFO: Inference done 139/320. 0.0224 s / img. ETA=0:00:28
[01/08 07:47:33] mr.evaluation.evaluator INFO: Inference done 171/320. 0.0224 s / img. ETA=0:00:23
[01/08 07:47:38] mr.evaluation.evaluator INFO: Inference done 203/320. 0.0223 s / img. ETA=0:00:18
[01/08 07:47:43] mr.evaluation.evaluator INFO: Inference done 235/320. 0.0223 s / img. ETA=0:00:13
[01/08 07:47:48] mr.evaluation.evaluator INFO: Inference done 267/320. 0.0223 s / img. ETA=0:00:08
[01/08 07:47:53] mr.evaluation.evaluator INFO: Inference done 299/320. 0.0223 s / img. ETA=0:00:03
[01/08 07:47:56] mr.evaluation.evaluator INFO: Total inference time: 0:00:49.544317 (0.157284 s / batch on 1 devices)
[01/08 07:47:56] mr.evaluation.evaluator INFO: Total inference pure compute time: 0:00:06 (0.022172 s / batch on 1 devices)
[01/08 07:48:06] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:48:06] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:48:09] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Slice metrics summary:
channel_0
--------------- --------------
val_nrmse 0.175 (0.042)
val_nrmse_mag 0.138 (0.030)
val_psnr 33.089 (3.029)
val_psnr_mag 35.133 (2.998)
val_ssim (Wang) 0.810 (0.075)
[01/08 07:48:09] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Scan metrics summary:
channel_0
-------------------- --------------
val_nrmse_mag_scan 0.129 (0.006)
val_nrmse_scan 0.163 (0.005)
val_psnr_mag_scan 43.045 (0.422)
val_psnr_scan 41.020 (0.545)
val_ssim (Wang)_scan 0.932 (0.011)
[01/08 07:48:09] mr.evaluation.evaluator INFO: Evaluation Time: 13.296574 s
[01/08 07:48:09] mr.engine.trainer INFO: Evaluation results for mridata_knee_2019_val in csv format:
[01/08 07:48:09] 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 07:48:09] mr.evaluation.testing INFO: copypaste: 0.1755,0.1383,33.0890,35.1330,0.8102,0.1290,0.1628,43.0453,41.0200,0.9319
[01/08 07:48:09] 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
0.1755,0.1383,33.0890,35.1330,0.8102,0.1290,0.1628,43.0453,41.0200,0.9319
[01/08 07:48:09] mr.utils.events INFO: eta: 0:05:40 iter: 999 loss: 14674.882 total_loss: 14674.882 time: 0.2413 data_time: 0.0001 lr: 0.000100 max_mem: 4240M
[01/08 07:48:15] mr.utils.events INFO: eta: 0:05:35 iter: 1019 loss: 14348.898 total_loss: 14348.898 time: 0.2413 data_time: 0.0001 lr: 0.000100 max_mem: 4240M
[01/08 07:48:20] mr.utils.events INFO: eta: 0:05:31 iter: 1039 loss: 14988.102 total_loss: 14988.102 time: 0.2413 data_time: 0.0001 lr: 0.000100 max_mem: 4240M
[01/08 07:48:25] mr.utils.events INFO: eta: 0:05:26 iter: 1059 loss: 17364.371 total_loss: 17364.371 time: 0.2413 data_time: 0.0001 lr: 0.000100 max_mem: 4240M
[01/08 07:48:30] mr.utils.events INFO: eta: 0:05:21 iter: 1079 loss: 14381.812 total_loss: 14381.812 time: 0.2413 data_time: 0.0001 lr: 0.000100 max_mem: 4240M
[01/08 07:48:35] mr.utils.events INFO: eta: 0:05:16 iter: 1099 loss: 14260.652 total_loss: 14260.652 time: 0.2413 data_time: 0.0001 lr: 0.000100 max_mem: 4240M
[01/08 07:48:41] mr.utils.events INFO: eta: 0:05:12 iter: 1119 loss: 14124.476 total_loss: 14124.476 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4240M
[01/08 07:48:46] mr.utils.events INFO: eta: 0:05:07 iter: 1139 loss: 13414.080 total_loss: 13414.080 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4240M
[01/08 07:48:51] mr.utils.events INFO: eta: 0:05:02 iter: 1159 loss: 14458.338 total_loss: 14458.338 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4240M
[01/08 07:48:56] mr.utils.events INFO: eta: 0:04:57 iter: 1179 loss: 13799.362 total_loss: 13799.362 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4240M
[01/08 07:49:01] fvcore.common.checkpoint INFO: Saving checkpoint to /bmrNAS/people/arjun/results/meddlr/tests/basic/model_0001199.pth
[01/08 07:49:02] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/val.json takes 0.00 seconds
[01/08 07:49:02] mr.data.build INFO: Dropped 0 scans. 2 scans remaining
[01/08 07:49:02] mr.data.build INFO: Dropped references for 0/2 scans. 2 scans with reference remaining
[01/08 07:49:02] mr.evaluation.evaluator INFO: Start inference on 320 batches
[01/08 07:49:06] mr.evaluation.evaluator INFO: Inference done 11/320. 0.0246 s / img. ETA=0:00:48
[01/08 07:49:11] mr.evaluation.evaluator INFO: Inference done 43/320. 0.0227 s / img. ETA=0:00:43
[01/08 07:49:16] mr.evaluation.evaluator INFO: Inference done 75/320. 0.0224 s / img. ETA=0:00:38
[01/08 07:49:21] mr.evaluation.evaluator INFO: Inference done 107/320. 0.0224 s / img. ETA=0:00:33
[01/08 07:49:26] mr.evaluation.evaluator INFO: Inference done 139/320. 0.0224 s / img. ETA=0:00:28
[01/08 07:49:31] mr.evaluation.evaluator INFO: Inference done 171/320. 0.0223 s / img. ETA=0:00:23
[01/08 07:49:36] mr.evaluation.evaluator INFO: Inference done 203/320. 0.0223 s / img. ETA=0:00:18
[01/08 07:49:41] mr.evaluation.evaluator INFO: Inference done 235/320. 0.0223 s / img. ETA=0:00:13
[01/08 07:49:46] mr.evaluation.evaluator INFO: Inference done 267/320. 0.0223 s / img. ETA=0:00:08
[01/08 07:49:51] mr.evaluation.evaluator INFO: Inference done 299/320. 0.0223 s / img. ETA=0:00:03
[01/08 07:49:54] mr.evaluation.evaluator INFO: Total inference time: 0:00:49.547863 (0.157295 s / batch on 1 devices)
[01/08 07:49:54] mr.evaluation.evaluator INFO: Total inference pure compute time: 0:00:06 (0.022115 s / batch on 1 devices)
[01/08 07:50:04] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:50:04] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:50:08] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Slice metrics summary:
channel_0
--------------- --------------
val_nrmse 0.182 (0.041)
val_nrmse_mag 0.135 (0.029)
val_psnr 32.762 (2.957)
val_psnr_mag 35.311 (2.952)
val_ssim (Wang) 0.863 (0.078)
[01/08 07:50:08] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Scan metrics summary:
channel_0
-------------------- --------------
val_nrmse_mag_scan 0.127 (0.005)
val_nrmse_scan 0.170 (0.005)
val_psnr_mag_scan 43.202 (0.427)
val_psnr_scan 40.667 (0.561)
val_ssim (Wang)_scan 0.961 (0.005)
[01/08 07:50:08] mr.evaluation.evaluator INFO: Evaluation Time: 13.242378 s
[01/08 07:50:08] mr.engine.trainer INFO: Evaluation results for mridata_knee_2019_val in csv format:
[01/08 07:50:08] 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 07:50:08] mr.evaluation.testing INFO: copypaste: 0.1817,0.1353,32.7618,35.3113,0.8626,0.1267,0.1695,43.2024,40.6668,0.9606
[01/08 07:50:08] 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
0.1817,0.1353,32.7618,35.3113,0.8626,0.1267,0.1695,43.2024,40.6668,0.9606
[01/08 07:50:08] mr.utils.events INFO: eta: 0:03:48 iter: 1199 loss: 14033.812 total_loss: 14033.812 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4241M
[01/08 07:50:13] mr.utils.events INFO: eta: 0:03:43 iter: 1219 loss: 15478.925 total_loss: 15478.925 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4241M
[01/08 07:50:18] mr.utils.events INFO: eta: 0:03:38 iter: 1239 loss: 14415.258 total_loss: 14415.258 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4241M
[01/08 07:50:23] mr.utils.events INFO: eta: 0:03:33 iter: 1259 loss: 14165.776 total_loss: 14165.776 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4241M
[01/08 07:50:28] mr.utils.events INFO: eta: 0:03:28 iter: 1279 loss: 14173.212 total_loss: 14173.212 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4241M
[01/08 07:50:34] mr.utils.events INFO: eta: 0:03:24 iter: 1299 loss: 13085.434 total_loss: 13085.434 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4241M
[01/08 07:50:39] mr.utils.events INFO: eta: 0:03:19 iter: 1319 loss: 12723.986 total_loss: 12723.986 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4241M
[01/08 07:50:45] mr.utils.events INFO: eta: 0:03:14 iter: 1339 loss: 15378.066 total_loss: 15378.066 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4241M
[01/08 07:50:50] mr.utils.events INFO: eta: 0:03:09 iter: 1359 loss: 14171.920 total_loss: 14171.920 time: 0.2414 data_time: 0.0001 lr: 0.000100 max_mem: 4241M
[01/08 07:50:55] mr.utils.events INFO: eta: 0:03:04 iter: 1379 loss: 14608.114 total_loss: 14608.114 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4241M
[01/08 07:51:00] fvcore.common.checkpoint INFO: Saving checkpoint to /bmrNAS/people/arjun/results/meddlr/tests/basic/model_0001399.pth
[01/08 07:51:01] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/val.json takes 0.00 seconds
[01/08 07:51:01] mr.data.build INFO: Dropped 0 scans. 2 scans remaining
[01/08 07:51:01] mr.data.build INFO: Dropped references for 0/2 scans. 2 scans with reference remaining
[01/08 07:51:01] mr.evaluation.evaluator INFO: Start inference on 320 batches
[01/08 07:51:05] mr.evaluation.evaluator INFO: Inference done 11/320. 0.0218 s / img. ETA=0:00:48
[01/08 07:51:10] mr.evaluation.evaluator INFO: Inference done 43/320. 0.0218 s / img. ETA=0:00:43
[01/08 07:51:15] mr.evaluation.evaluator INFO: Inference done 75/320. 0.0218 s / img. ETA=0:00:38
[01/08 07:51:20] mr.evaluation.evaluator INFO: Inference done 107/320. 0.0219 s / img. ETA=0:00:33
[01/08 07:51:25] mr.evaluation.evaluator INFO: Inference done 139/320. 0.0219 s / img. ETA=0:00:28
[01/08 07:51:30] mr.evaluation.evaluator INFO: Inference done 171/320. 0.0218 s / img. ETA=0:00:23
[01/08 07:51:35] mr.evaluation.evaluator INFO: Inference done 203/320. 0.0218 s / img. ETA=0:00:18
[01/08 07:51:40] mr.evaluation.evaluator INFO: Inference done 235/320. 0.0218 s / img. ETA=0:00:13
[01/08 07:51:45] mr.evaluation.evaluator INFO: Inference done 267/320. 0.0218 s / img. ETA=0:00:08
[01/08 07:51:50] mr.evaluation.evaluator INFO: Inference done 299/320. 0.0218 s / img. ETA=0:00:03
[01/08 07:51:53] mr.evaluation.evaluator INFO: Total inference time: 0:00:49.483551 (0.157091 s / batch on 1 devices)
[01/08 07:51:53] mr.evaluation.evaluator INFO: Total inference pure compute time: 0:00:06 (0.021677 s / batch on 1 devices)
[01/08 07:52:03] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:52:03] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:52:06] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Slice metrics summary:
channel_0
--------------- --------------
val_nrmse 0.164 (0.045)
val_nrmse_mag 0.120 (0.034)
val_psnr 33.694 (3.086)
val_psnr_mag 36.480 (3.132)
val_ssim (Wang) 0.833 (0.078)
[01/08 07:52:06] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Scan metrics summary:
channel_0
-------------------- --------------
val_nrmse_mag_scan 0.110 (0.008)
val_nrmse_scan 0.151 (0.006)
val_psnr_mag_scan 44.465 (0.208)
val_psnr_scan 41.657 (0.464)
val_ssim (Wang)_scan 0.944 (0.010)
[01/08 07:52:06] mr.evaluation.evaluator INFO: Evaluation Time: 13.212838 s
[01/08 07:52:06] mr.engine.trainer INFO: Evaluation results for mridata_knee_2019_val in csv format:
[01/08 07:52:06] 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 07:52:06] mr.evaluation.testing INFO: copypaste: 0.1645,0.1196,33.6935,36.4799,0.8328,0.1096,0.1513,44.4653,41.6570,0.9443
[01/08 07:52:06] 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
0.1645,0.1196,33.6935,36.4799,0.8328,0.1096,0.1513,44.4653,41.6570,0.9443
[01/08 07:52:06] mr.utils.events INFO: eta: 0:01:54 iter: 1399 loss: 14015.138 total_loss: 14015.138 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4243M
[01/08 07:52:12] mr.utils.events INFO: eta: 0:01:49 iter: 1419 loss: 14504.874 total_loss: 14504.874 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4243M
[01/08 07:52:17] mr.utils.events INFO: eta: 0:01:44 iter: 1439 loss: 14570.553 total_loss: 14570.553 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4243M
[01/08 07:52:22] mr.utils.events INFO: eta: 0:01:39 iter: 1459 loss: 14148.630 total_loss: 14148.630 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4243M
[01/08 07:52:27] mr.utils.events INFO: eta: 0:01:34 iter: 1479 loss: 14428.591 total_loss: 14428.591 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4243M
[01/08 07:52:32] mr.utils.events INFO: eta: 0:01:30 iter: 1499 loss: 13502.969 total_loss: 13502.969 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4243M
[01/08 07:52:38] mr.utils.events INFO: eta: 0:01:25 iter: 1519 loss: 16368.226 total_loss: 16368.226 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4243M
[01/08 07:52:43] mr.utils.events INFO: eta: 0:01:20 iter: 1539 loss: 14534.019 total_loss: 14534.019 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4243M
[01/08 07:52:48] mr.utils.events INFO: eta: 0:01:15 iter: 1559 loss: 14640.928 total_loss: 14640.928 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4243M
[01/08 07:52:53] mr.utils.events INFO: eta: 0:01:10 iter: 1579 loss: 13991.085 total_loss: 13991.085 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4243M
[01/08 07:52:58] fvcore.common.checkpoint INFO: Saving checkpoint to /bmrNAS/people/arjun/results/meddlr/tests/basic/model_0001599.pth
[01/08 07:52:59] fvcore.common.checkpoint INFO: Saving checkpoint to /bmrNAS/people/arjun/results/meddlr/tests/basic/model_final.pth
[01/08 07:52:59] mr.data.datasets.register_mrco INFO: Loading /bmrNAS/people/arjun/code/meddlr/annotations/mridata_knee_2019/val.json takes 0.00 seconds
[01/08 07:52:59] mr.data.build INFO: Dropped 0 scans. 2 scans remaining
[01/08 07:52:59] mr.data.build INFO: Dropped references for 0/2 scans. 2 scans with reference remaining
[01/08 07:52:59] mr.evaluation.evaluator INFO: Start inference on 320 batches
[01/08 07:53:03] mr.evaluation.evaluator INFO: Inference done 11/320. 0.0260 s / img. ETA=0:00:48
[01/08 07:53:08] mr.evaluation.evaluator INFO: Inference done 43/320. 0.0230 s / img. ETA=0:00:43
[01/08 07:53:13] mr.evaluation.evaluator INFO: Inference done 75/320. 0.0228 s / img. ETA=0:00:38
[01/08 07:53:18] mr.evaluation.evaluator INFO: Inference done 107/320. 0.0227 s / img. ETA=0:00:33
[01/08 07:53:23] mr.evaluation.evaluator INFO: Inference done 139/320. 0.0227 s / img. ETA=0:00:28
[01/08 07:53:28] mr.evaluation.evaluator INFO: Inference done 171/320. 0.0226 s / img. ETA=0:00:23
[01/08 07:53:33] mr.evaluation.evaluator INFO: Inference done 203/320. 0.0226 s / img. ETA=0:00:18
[01/08 07:53:38] mr.evaluation.evaluator INFO: Inference done 235/320. 0.0226 s / img. ETA=0:00:13
[01/08 07:53:43] mr.evaluation.evaluator INFO: Inference done 267/320. 0.0225 s / img. ETA=0:00:08
[01/08 07:53:48] mr.evaluation.evaluator INFO: Inference done 299/320. 0.0225 s / img. ETA=0:00:03
[01/08 07:53:52] mr.evaluation.evaluator INFO: Total inference time: 0:00:49.495082 (0.157127 s / batch on 1 devices)
[01/08 07:53:52] mr.evaluation.evaluator INFO: Total inference pure compute time: 0:00:07 (0.022384 s / batch on 1 devices)
[01/08 07:54:01] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:54:01] mr.evaluation.scan_evaluator INFO: Structuring slices into volumes...
[01/08 07:54:05] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Slice metrics summary:
channel_0
--------------- --------------
val_nrmse 0.189 (0.041)
val_nrmse_mag 0.117 (0.032)
val_psnr 32.410 (2.903)
val_psnr_mag 36.686 (3.132)
val_ssim (Wang) 0.858 (0.081)
[01/08 07:54:05] mr.evaluation.recon_evaluation INFO: [ReconEvaluator] Scan metrics summary:
channel_0
-------------------- --------------
val_nrmse_mag_scan 0.107 (0.005)
val_nrmse_scan 0.177 (0.004)
val_psnr_mag_scan 44.659 (0.393)
val_psnr_scan 40.292 (0.600)
val_ssim (Wang)_scan 0.959 (0.005)
[01/08 07:54:05] mr.evaluation.evaluator INFO: Evaluation Time: 13.055382 s
[01/08 07:54:05] mr.engine.trainer INFO: Evaluation results for mridata_knee_2019_val in csv format:
[01/08 07:54:05] 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 07:54:05] mr.evaluation.testing INFO: copypaste: 0.1889,0.1167,32.4100,36.6860,0.8582,0.1071,0.1770,44.6590,40.2923,0.9595
[01/08 07:54:05] 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
0.1889,0.1167,32.4100,36.6860,0.8582,0.1071,0.1770,44.6590,40.2923,0.9595
[01/08 07:54:05] mr.utils.events INFO: eta: 0:00:00 iter: 1599 loss: 13840.166 total_loss: 13840.166 time: 0.2415 data_time: 0.0001 lr: 0.000100 max_mem: 4245M
[01/08 07:54:05] mr.engine.hooks INFO: Overall training speed: 1597 iterations in 0:06:25 (0.2417 s / it)
[01/08 07:54:05] mr.engine.hooks INFO: Total training time: 0:15:56 (0:09:30 on hooks)
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