tutorials/generative/smrd/configs/demo/SMRD-brain_T2-noise005-R8.yaml at 1f598209ff29e95b870fb458af5fd32f0db78f4b · Project-MONAI/tutorials · GitHub

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user: csgm-mri-langevin
model_type: ncsnv2
seed: 42
device: cuda
batch_size: 1
repeat: 1

# The pre-trained NCSNV2 checkpoint
gen_ckpt: checkpoints/mri-unet-smrd.pth

## weights of different losses
mse: 5.

## start from different noise level of langevin
start_iter: 1155

# can be decreased for super-resolution
image_size:
  - 384
  - 384

## files
input_dir: ./datasets/brain_T2/
maps_dir: ./datasets/brain_T2_maps/
anatomy: brain

early_stop: stop

## Acceleration
R: 8
pattern: equispaced
exp_names: 0
orientation: vertical

## SMRD hyperparameters
num_cg_iter: 5
window_size: 160
lambda_lr: 0.2
init_lambda_update: 1154
last_lambda_update: 1655

## Lambda
lambda_init: 2.0
lambda_end: 2.0
lambda_func: learnable

exp_name: admm-learn-sure_brain_noise_005_R8
learning_loss: SURE

## Input noise
noise_std: 0.005


# logging
save_latent: false
save_images: true
save_dataloader_every: 1000000
save_iter: 100

debug: false
world_size: 1
multiprocessing: false
port: 12345

langevin_config:
    training:
      batch_size: 4
      n_epochs: 500000
      n_iters: 320001
      snapshot_freq: 10000
      snapshot_sampling: true
      anneal_power: 2
      log_all_sigmas: false

    sampling:
      batch_size: 4
      data_init: false
      step_lr: 5e-5
      n_steps_each: 4
      ckpt_id: 5000
      final_only: true
      fid: false
      denoise: true
      num_samples4fid: 10000
      inpainting: false
      interpolation: false
      n_interpolations: 8

    fast_fid:
      batch_size: 1000
      num_samples: 1000
      step_lr: 0.0000009
      n_steps_each: 3
      begin_ckpt: 100000
      end_ckpt: 80000
      verbose: false
      ensemble: false

    test:
      begin_ckpt: 5000
      end_ckpt: 80000
      batch_size: 100

    data:
      dataset: "mri-mvue"
      image_size: 384
      channels: 2
      logit_transform: false
      uniform_dequantization: false
      gaussian_dequantization: false
      random_flip: false
      rescaled: false
      num_workers: 8

    model:
      sigma_begin: 232
      num_classes: 2311
      ema: true
      ema_rate: 0.999
      spec_norm: false
      sigma_dist: geometric
      sigma_end: 0.0066
      normalization: InstanceNorm++
      nonlinearity: elu
      ngf: 128

    optim:
      weight_decay: 0.000
      optimizer: "Adam"
      lr: 0.0001
      beta1: 0.9
      amsgrad: false
      eps: 0.001