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{
"imports": [
"$import functools",
"$import glob",
"$import scripts"
],
"bundle_root": ".",
"device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
"ckpt_dir": "$@bundle_root + '/models'",
"tf_dir": "$@bundle_root + '/eval'",
"dataset_dir": "/workspace/data/medical",
"pretrained": false,
"perceptual_loss_model_weights_path": null,
"train_batch_size": 2,
"lr": 1e-05,
"train_patch_size": [
112,
128,
80
],
"channel": 0,
"spacing": [
1.1,
1.1,
1.1
],
"spatial_dims": 3,
"image_channels": 1,
"latent_channels": 8,
"discriminator_def": {
"_target_": "generative.networks.nets.PatchDiscriminator",
"spatial_dims": "@spatial_dims",
"num_layers_d": 3,
"num_channels": 32,
"in_channels": 1,
"out_channels": 1,
"norm": "INSTANCE"
},
"autoencoder_def": {
"_target_": "generative.networks.nets.AutoencoderKL",
"spatial_dims": "@spatial_dims",
"in_channels": "@image_channels",
"out_channels": "@image_channels",
"latent_channels": "@latent_channels",
"num_channels": [
64,
128,
256
],
"num_res_blocks": 2,
"norm_num_groups": 32,
"norm_eps": 1e-06,
"attention_levels": [
false,
false,
false
],
"with_encoder_nonlocal_attn": false,
"with_decoder_nonlocal_attn": false
},
"perceptual_loss_def": {
"_target_": "generative.losses.PerceptualLoss",
"spatial_dims": "@spatial_dims",
"network_type": "resnet50",
"is_fake_3d": true,
"fake_3d_ratio": 0.2,
"pretrained": "@pretrained",
"pretrained_path": "@perceptual_loss_model_weights_path",
"pretrained_state_dict_key": "state_dict"
},
"dnetwork": "$@discriminator_def.to(@device)",
"gnetwork": "$@autoencoder_def.to(@device)",
"loss_perceptual": "$@perceptual_loss_def.to(@device)",
"doptimizer": {
"_target_": "torch.optim.Adam",
"params": "$@dnetwork.parameters()",
"lr": "@lr"
},
"goptimizer": {
"_target_": "torch.optim.Adam",
"params": "$@gnetwork.parameters()",
"lr": "@lr"
},
"preprocessing_transforms": [
{
"_target_": "LoadImaged",
"keys": "image"
},
{
"_target_": "EnsureChannelFirstd",
"keys": "image"
},
{
"_target_": "Lambdad",
"keys": "image",
"func": "$lambda x: x[@channel, :, :, :]"
},
{
"_target_": "AddChanneld",
"keys": "image"
},
{
"_target_": "EnsureTyped",
"keys": "image"
},
{
"_target_": "Orientationd",
"keys": "image",
"axcodes": "RAS"
},
{
"_target_": "Spacingd",
"keys": "image",
"pixdim": "@spacing",
"mode": "bilinear"
}
],
"final_transforms": [
{
"_target_": "ScaleIntensityRangePercentilesd",
"keys": "image",
"lower": 0,
"upper": 99.5,
"b_min": 0,
"b_max": 1
}
],
"train": {
"crop_transforms": [
{
"_target_": "RandSpatialCropd",
"keys": "image",
"roi_size": "@train_patch_size",
"random_size": false
}
],
"preprocessing": {
"_target_": "Compose",
"transforms": "$@preprocessing_transforms + @train#crop_transforms + @final_transforms"
},
"dataset": {
"_target_": "monai.apps.DecathlonDataset",
"root_dir": "@dataset_dir",
"task": "Task01_BrainTumour",
"section": "training",
"cache_rate": 1.0,
"num_workers": 8,
"download": false,
"transform": "@train#preprocessing"
},
"dataloader": {
"_target_": "DataLoader",
"dataset": "@train#dataset",
"batch_size": "@train_batch_size",
"shuffle": true,
"num_workers": 0
},
"handlers": [
{
"_target_": "CheckpointSaver",
"save_dir": "@ckpt_dir",
"save_dict": {
"model": "@gnetwork"
},
"save_interval": 0,
"save_final": true,
"epoch_level": true,
"final_filename": "model_autoencoder.pt"
},
{
"_target_": "StatsHandler",
"tag_name": "train_loss",
"output_transform": "$lambda x: monai.handlers.from_engine(['g_loss'], first=True)(x)[0]"
},
{
"_target_": "TensorBoardStatsHandler",
"log_dir": "@tf_dir",
"tag_name": "train_loss",
"output_transform": "$lambda x: monai.handlers.from_engine(['g_loss'], first=True)(x)[0]"
}
],
"trainer": {
"_target_": "scripts.ldm_trainer.VaeGanTrainer",
"device": "@device",
"max_epochs": 1500,
"train_data_loader": "@train#dataloader",
"g_network": "@gnetwork",
"g_optimizer": "@goptimizer",
"g_loss_function": "$functools.partial(scripts.losses.generator_loss, disc_net=@dnetwork, loss_perceptual=@loss_perceptual)",
"d_network": "@dnetwork",
"d_optimizer": "@doptimizer",
"d_loss_function": "$functools.partial(scripts.losses.discriminator_loss, disc_net=@dnetwork)",
"d_train_steps": 5,
"g_update_latents": true,
"latent_shape": "@latent_channels",
"key_train_metric": "$None",
"train_handlers": "@train#handlers"
}
},
"initialize": [
"$monai.utils.set_determinism(seed=0)"
],
"run": [
"$@train#trainer.run()"
]
}
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