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pip install atommic['all']1pretrained: true
2checkpoint: https://huggingface.co/wdika/SEG_DynUNet_BraTS2023AdultGlioma/blob/main/SEG_DynUNet_BraTS2023AdultGlioma.atommic
3mode: test1model:
2 model_name: SEGMENTATIONDYNUNET
3 segmentation_module: DYNUNet
4 segmentation_module_input_channels: 4
5 segmentation_module_output_channels: 4
6 segmentation_module_channels:
7 - 32
8 - 64
9 - 128
10 - 256
11 - 512
12 segmentation_module_kernel_size:
13 - 3
14 - 3
15 - 3
16 - 3
17 - 1
18 segmentation_module_strides:
19 - 1
20 - 1
21 - 1
22 - 1
23 - 1
24 segmentation_module_dropout: 0.0
25 segmentation_module_norm: instance
26 segmentation_module_activation: leakyrelu
27 segmentation_module_deep_supervision: true
28 segmentation_module_deep_supervision_levels: 2
29 segmentation_module_normalize: false
30 segmentation_module_norm_groups: 2
31 segmentation_loss:
32 dice: 1.0
33 dice_loss_include_background: true # always set to true if the background is removed
34 dice_loss_to_onehot_y: false
35 dice_loss_sigmoid: false
36 dice_loss_softmax: false
37 dice_loss_other_act: none
38 dice_loss_squared_pred: false
39 dice_loss_jaccard: false
40 dice_loss_flatten: false
41 dice_loss_reduction: mean_batch
42 dice_loss_smooth_nr: 1e-5
43 dice_loss_smooth_dr: 1e-5
44 dice_loss_batch: true
45 dice_metric_include_background: true # always set to true if the background is removed
46 dice_metric_to_onehot_y: false
47 dice_metric_sigmoid: false
48 dice_metric_softmax: false
49 dice_metric_other_act: none
50 dice_metric_squared_pred: false
51 dice_metric_jaccard: false
52 dice_metric_flatten: false
53 dice_metric_reduction: mean_batch
54 dice_metric_smooth_nr: 1e-5
55 dice_metric_smooth_dr: 1e-5
56 dice_metric_batch: true
57 segmentation_classes_thresholds: [ 0.5, 0.5, 0.5, 0.5 ]
58 segmentation_activation: sigmoid
59 magnitude_input: true
60 log_multiple_modalities: true # log all modalities in the same image, e.g. T1, T2, T1ce, FLAIR will be concatenated
61 normalization_type: minmax
62 normalize_segmentation_output: true
63 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