adding meddlr testing data

test-data/sample-gdrive-folder/hello-world-2.txt

@@ -0,0 +1 @@
+Hello world!

test-data/sample-gdrive-folder/hello-world.txt

@@ -0,0 +1 @@
+Hello world!

test-data/test-exps/basic-cpu-orig/config.yaml

@@ -0,0 +1,190 @@
+AUG_TEST:
+  UNDERSAMPLE:
+    ACCELERATIONS: &id001
+    - 6
+AUG_TRAIN:
+  MOTION_P: 0.2
+  MRI_RECON:
+    AUG_SENSITIVITY_MAPS: true
+    SCHEDULER_P:
+      IGNORE: false
+    TRANSFORMS: []
+  NOISE_P: 0.2
+  UNDERSAMPLE:
+    ACCELERATIONS: *id001
+    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: &id002
+        - 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: *id002
+      USE_FULLY_SAMPLED_TARGET: true
+      USE_FULLY_SAMPLED_TARGET_EVAL: null
+  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: "results://meddlr/tests/basic-cpu"
+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

test-data/test-exps/basic-cpu-orig/events.out.tfevents.1641656281.vigata.1085133.0

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9fcc5fac0439a0d47714148c49456ee98b16329b1339f8e8e6d4929b579c0b57
+size 62368621

test-data/test-exps/basic-cpu-orig/last_checkpoint

@@ -0,0 +1 @@
+model_final.pth

test-data/test-exps/basic-cpu-orig/log.txt

@@ -0,0 +1,731 @@
+[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)

test-data/test-exps/basic-cpu-orig/metrics.json

@@ -0,0 +1,80 @@
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test-data/test-exps/basic-cpu/config.yaml

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+AUG_TEST:
+  UNDERSAMPLE:
+    ACCELERATIONS: &id001
+    - 6
+AUG_TRAIN:
+  MOTION_P: 0.2
+  MRI_RECON:
+    AUG_SENSITIVITY_MAPS: true
+    SCHEDULER_P:
+      IGNORE: false
+    TRANSFORMS: []
+  NOISE_P: 0.2
+  UNDERSAMPLE:
+    ACCELERATIONS: *id001
+    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: &id002
+        - 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: *id002
+      USE_FULLY_SAMPLED_TARGET: true
+      USE_FULLY_SAMPLED_TARGET_EVAL: null
+  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: "results://meddlr/tests/basic-cpu"
+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

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test-data/test-model/config-with-deps.yaml

@@ -0,0 +1,188 @@
+# Test file for testing that dependencies get parsed
+# DEPENDENCY: numpy<=0.0.1
+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: 0
+  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
+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: null
+  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: "results://meddlr/tests/basic"
+SEED: -1
+SOLVER:
+  BASE_LR: 0.0001
+  BIAS_LR_FACTOR: 1.0
+  CHECKPOINT_PERIOD: 20
+  GAMMA: 0.1
+  GRAD_ACCUM_ITERS: 1
+  LR_SCHEDULER_NAME: WarmupMultiStepLR
+  MAX_ITER: 80
+  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: 40
+  EXPECTED_RESULTS: []
+  FLUSH_PERIOD: 0
+  VAL_AS_TEST: true
+  VAL_METRICS:
+    RECON: []
+TIME_SCALE: iter
+VERSION: 1
+VIS_PERIOD: 20

test-data/test-model/config.yaml

@@ -0,0 +1,186 @@
+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: 0
+  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
+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: null
+  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: "results://meddlr/tests/basic"
+SEED: -1
+SOLVER:
+  BASE_LR: 0.0001
+  BIAS_LR_FACTOR: 1.0
+  CHECKPOINT_PERIOD: 20
+  GAMMA: 0.1
+  GRAD_ACCUM_ITERS: 1
+  LR_SCHEDULER_NAME: WarmupMultiStepLR
+  MAX_ITER: 80
+  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: 40
+  EXPECTED_RESULTS: []
+  FLUSH_PERIOD: 0
+  VAL_AS_TEST: true
+  VAL_METRICS:
+    RECON: []
+TIME_SCALE: iter
+VERSION: 1
+VIS_PERIOD: 20

test-data/test-model/model-cpu.pt

@@ -0,0 +1,3 @@
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+size 14382615