2 d motion corruption main

configs/mri-recon/mridata-3dfse-knee/motion_eval_unet_ssdu_vortex.sh

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+#!/bin/bash
+export MEDDLR_DATASETS_DIR=/mnt/dense/ozt/dl-ss-recon/data 
+export MEDDLR_CACHE_DIR=/mnt/dense/deepro/cache
+export MEDDLR_RESULTS_DIR=/mnt/dense/deepro/results/Summer_2022_2023/motion_eval/unet_official/ssdu/wandb
+
+gpu=$(python get_available_gpu.py)
+echo "The first available gpu is $gpu"
+
+# Run normal unet yaml
+# took off --debug to allow wb to work. 
+WANDB__SERVICE_WAIT=300 CUDA_VISIBLE_DEVICES=$gpu$ python tools/eval_net.py --config-file configs/mri-recon/mridata-3dfse-knee/unet/ssdu/SSDU_UNET_13_Scan.yaml --auto-version --save-scans --angle 30 --translation 0.1 --nshots 5 --trajectory interleaved --mri_dim 2 --motion standard MODEL.WEIGHTS 3Dmridata/SSDU/model.cpkt
+
+# gpu=$(python get_available_gpu.py)
+# echo "The first available gpu for VORTEX is $gpu"
+
+# # Run vortex unet yaml
+# # took off --debug to allow wb to work. 
+# WANDB__SERVICE_WAIT=300 CUDA_VISIBLE_DEVICES=$gpu$ python tools/train_net.py --config-file configs/mri-recon/mridata-3dfse-knee/unet/ssdu/SSDU_Aug_UNET_13_Scan.yaml --auto-version

configs/mri-recon/mridata-3dfse-knee/old/SSDU_Aug_UNET_13_Scan.yaml

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+AUG_TEST:
+  UNDERSAMPLE:
+    ACCELERATIONS:
+    - 16
+AUG_TRAIN:
+  MOTION_P: 0.2
+  MRI_RECON:
+    AUG_SENSITIVITY_MAPS: true
+    SCHEDULER_P:
+      IGNORE: false
+    TRANSFORMS: []
+  NOISE_P: 0.2
+  UNDERSAMPLE:
+    ACCELERATIONS:
+    - 16
+    CALIBRATION_SIZE: 20
+    CENTER_FRACTIONS: []
+    MAX_ATTEMPTS: 30
+    NAME: PoissonDiskMaskFunc
+  USE_MOTION: false
+  USE_NOISE: false
+CUDNN_BENCHMARK: false
+# DATALOADER has 1 supervised and 13 unsupervised
+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: 14
+    NUM_TOTAL_BY_GROUP: []
+    NUM_UNDERSAMPLED: 13
+    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: SSDU 16x mridata - loss=k_l1, uniform/loss=k_l1/version_001
+  ENTITY_NAME: ''
+  EXP_NAME: vortex/mridata_knee_3dfse/SSDU
+  PROJECT_NAME: 'vortex_rm'
+  TAGS:
+  - baseline
+  - ssdu
+  - 16x
+  - mridata_knee_3dfse
+# For motion aug, A2R and Consistency were kept with std_dev range of 0.2 to 0.5.
+# For UNET, the META_ARCHITECTURE of SSDUModel is UnetModel
+MODEL:
+  A2R:
+    META_ARCHITECTURE: GeneralizedUnrolledCNN 
+    USE_SUPERVISED_CONSISTENCY: false  # TUNE 
+  CONSISTENCY:
+    AUG:
+      MRI_RECON:
+        AUG_SENSITIVITY_MAPS: true
+        SCHEDULER_P:
+          IGNORE: false
+        TRANSFORMS:
+        - name: RandomMRIMotion 
+          p: 0.2
+          std_devs:
+          - 0.2
+          - 0.5
+          use_mask: true
+    LOSS_NAME: l1
+    LOSS_WEIGHT: 0.1
+    USE_CONSISTENCY: true 
+  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: cpu
+  M2R:
+    META_ARCHITECTURE: GeneralizedUnrolledCNN
+    USE_SUPERVISED_CONSISTENCY: false
+  META_ARCHITECTURE: SSDUModel
+  N2R:
+    META_ARCHITECTURE: GeneralizedUnrolledCNN
+    USE_SUPERVISED_CONSISTENCY: false
+  NM2R:
+    META_ARCHITECTURE: GeneralizedUnrolledCNN
+    USE_SUPERVISED_CONSISTENCY: false
+  NORMALIZER:
+    KEYWORDS: []
+    NAME: TopMagnitudeNormalizer
+  RECON_LOSS:
+    NAME: k_l1
+    RENORMALIZE_DATA: false
+  SEG:
+    ACTIVATION: sigmoid
+    CLASSES: []
+    INCLUDE_BACKGROUND: false
+  SSDU:
+    MASKER:
+      PARAMS:
+        kind: uniform
+        p: 1.0
+        per_example: true
+        rhos: 0.4
+        std_scale: 4
+    META_ARCHITECTURE: UnetModel
+  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: 256
+    NUM_RESBLOCKS: 2
+    NUM_UNROLLED_STEPS: 5
+    PADDING: ''
+    SHARE_WEIGHTS: false
+  WEIGHTS: ''
+OUTPUT_DIR: results://vortex/mridata_knee_3dfse/SSDU
+SEED: 1000
+SOLVER:
+  BASE_LR: 0.001
+  BIAS_LR_FACTOR: 1.0
+  CHECKPOINT_PERIOD: -10
+  GAMMA: 0.1
+  GRAD_ACCUM_ITERS: 1
+  LR_SCHEDULER_NAME: ''
+  MAX_ITER: -200
+  MOMENTUM: 0.9
+  OPTIMIZER: Adam
+  STEPS: []
+  TEST_BATCH_SIZE: 24
+  TRAIN_BATCH_SIZE: 24
+  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: -10
+  EXPECTED_RESULTS: []
+  FLUSH_PERIOD: 0
+  VAL_AS_TEST: true
+  VAL_METRICS:
+    RECON:
+    - psnr
+    - psnr_scan
+    - psnr_mag
+    - psnr_mag_scan
+    - nrmse
+    - nrmse_scan
+    - nrmse_mag
+    - nrmse_mag_scan
+    - ssim (Wang)
+TIME_SCALE: iter
+VERSION: 1
+VIS_PERIOD: 100