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pip install atommic['all']1pretrained: true
2checkpoint: https://huggingface.co/wdika/SEG_UNet3D_BraTS2023AdultGlioma/blob/main/SEG_UNet3D_BraTS2023AdultGlioma.atommic
3mode: test1model:
2 model_name: SEGMENTATION3DUNET
3 segmentation_module: UNet
4 segmentation_module_input_channels: 4
5 segmentation_module_output_channels: 4
6 segmentation_module_channels: 32
7 segmentation_module_pooling_layers: 5
8 segmentation_module_dropout: 0.0
9 segmentation_module_normalize: false
10 segmentation_loss:
11 dice: 1.0
12 dice_loss_include_background: true # always set to true if the background is removed
13 dice_loss_to_onehot_y: false
14 dice_loss_sigmoid: false
15 dice_loss_softmax: false
16 dice_loss_other_act: none
17 dice_loss_squared_pred: false
18 dice_loss_jaccard: false
19 dice_loss_flatten: false
20 dice_loss_reduction: mean_batch
21 dice_loss_smooth_nr: 1e-5
22 dice_loss_smooth_dr: 1e-5
23 dice_loss_batch: true
24 dice_metric_include_background: true # always set to true if the background is removed
25 dice_metric_to_onehot_y: false
26 dice_metric_sigmoid: false
27 dice_metric_softmax: false
28 dice_metric_other_act: none
29 dice_metric_squared_pred: false
30 dice_metric_jaccard: false
31 dice_metric_flatten: false
32 dice_metric_reduction: mean_batch
33 dice_metric_smooth_nr: 1e-5
34 dice_metric_smooth_dr: 1e-5
35 dice_metric_batch: true
36 segmentation_classes_thresholds: [ 0.5, 0.5, 0.5, 0.5 ]
37 segmentation_activation: sigmoid
38 magnitude_input: true
39 log_multiple_modalities: true # log all modalities in the same image, e.g. T1, T2, T1ce, FLAIR will be concatenated
40 normalization_type: minmax
41 normalize_segmentation_output: true
42 complex_data: false1 optim:
2 name: adam
3 lr: 1e-4
4 betas:
5 - 0.9
6 - 0.98
7 weight_decay: 0.0
8 sched:
9 name: InverseSquareRootAnnealing
10 min_lr: 0.0
11 last_epoch: -1
12 warmup_ratio: 0.1
13
14trainer:
15 strategy: ddp
16 accelerator: gpu
17 devices: 1
18 num_nodes: 1
19 max_epochs: 10
20 precision: 16-mixed
21 enable_checkpointing: false
22 logger: false
23 log_every_n_steps: 50
24 check_val_every_n_epoch: -1
25 max_steps: -1