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987 Bytes
| model_name: 'ddpm2d_seg2med_multimodal' | |
| GPU_ID: [0] | |
| ckpt_path: 'seg2med_app\model\cossim_model_100.pt' | |
| mode: 'train' | |
| dataset: | |
| train_csv: 'tutorial2_train_ablation.csv' | |
| test_csv: 'tutorial2_val_prior_1.csv' | |
| batch_size: 16 | |
| val_batch_size: 1 | |
| normalize: 'scale2000' | |
| zoom: (0.5,0.5,1.0) | |
| resized_size: (256,256,None) | |
| div_size: (None,None,None) | |
| num_workers: 1 | |
| train: | |
| val_epoch_interval: 1 | |
| save_ckpt_interval: 1 | |
| num_epochs: 100 | |
| learning_rate: 0.0002 | |
| writeTensorboard: True | |
| sample_range_lower: 10 | |
| sample_range_upper: 10 | |
| earlystopping_patience: 10 | |
| earlystopping_delta: 0.001 | |
| loss: 'cossim_contrastive' | |
| validation: | |
| evaluate_restore_transforms: True | |
| x_lower_limit: -1000 | |
| x_upper_limit: 3000 | |
| manual_aorta_diss: -1 | |
| ddpm: | |
| num_train_timesteps: 500 | |
| num_inference_steps: 500 | |
| num_channels: (64, 128, 256, 256) | |
| attention_levels: (False, False, False, True) | |
| num_res_units: 2 | |
| norm_num_groups: 32 | |
| num_head_channels: 32 | |
| noise_type: 'normal' | |