unet/config.yaml

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: 24
    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: 2
  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:
  - skmtea_v1_test
  TRAIN:
  - skmtea_v1_train
  VAL:
  - skmtea_v1_val
DESCRIPTION:
  BRIEF: ''
  ENTITY_NAME: ''
  EXP_NAME: unet
  PROJECT_NAME: ''
  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: &id001
        - 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: *id001
      USE_FULLY_SAMPLED_TARGET: true
      USE_FULLY_SAMPLED_TARGET_EVAL: null
  DEVICE: cpu
  M2R:
    META_ARCHITECTURE: GeneralizedUnrolledCNN
    USE_SUPERVISED_CONSISTENCY: false
  META_ARCHITECTURE: UnetModel
  MONAI: {}
  N2R:
    META_ARCHITECTURE: GeneralizedUnrolledCNN
    USE_SUPERVISED_CONSISTENCY: false
  NM2R:
    META_ARCHITECTURE: GeneralizedUnrolledCNN
    USE_SUPERVISED_CONSISTENCY: false
  NORMALIZER:
    KEYWORDS: []
    NAME: TopMagnitudeNormalizer
  RECON_LOSS:
    NAME: mae
    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: 256
    NUM_RESBLOCKS: 2
    NUM_UNROLLED_STEPS: 5
    PADDING: ''
    SHARE_WEIGHTS: false
    STEP_SIZES:
    - -2.0
  WEIGHTS: ''
OUTPUT_DIR: /temp/my-experiment
SEED: 1000
SOLVER:
  BASE_LR: 0.0001
  BIAS_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: 50
  GAMMA: 0.1
  GRAD_ACCUM_ITERS: 1
  LR_SCHEDULER_NAME: ''
  MAX_ITER: 200
  MOMENTUM: 0.9
  OPTIMIZER: Adam
  STEPS:
  - 30000
  TEST_BATCH_SIZE: 16
  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: 50
  EXPECTED_RESULTS: []
  FLUSH_PERIOD: 0
  POSTPROCESSOR:
    NAME: ''
  VAL_AS_TEST: true
  VAL_METRICS:
    RECON: []
TIME_SCALE: iter
VERSION: 1
VIS_PERIOD: 0