ssl_thymus_quantification/get_features.yaml at public_release · AIM-Harvard/ssl_thymus_quantification · GitHub

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trainer:
    _target_: pytorch_lightning.Trainer
    benchmark: True
    max_epochs: 100
    check_val_every_n_epoch: 4
    accelerator: gpu
    precision: 16-mixed
    devices: 1
    log_every_n_steps: 50
    logger:
        _target_: pytorch_lightning.loggers.CSVLogger
        save_dir: "./logs"
        name: "get_features"

    callbacks:
        - _target_: project.callbacks.prediction_saver.SavePredictions
          path: /home/suraj/Repositories/ssl-thymus-lighter/swav_features.csv

network:
    _target_: project.utils.adjust_prefix_and_load_state_dict
    ckpt_path: /mnt/data16_r2d6/SSLThymus/training/checkpoints/ssl_thymus_idc_pretrain_swav/last.ckpt
    ckpt_to_model_prefix: {"model.network.backbone.": ""}
    model:
      _target_: monai.networks.nets.resnet.resnet50
      pretrained: False
      n_input_channels: 1
      widen_factor: 2
      conv1_t_stride: 2
      feed_forward: False

model:
    _target_: project.system.LighterSystem
    network: "@network"
    criterion: null
    optimizer: null
    scheduler: null
    train_metrics: null
    val_metrics: null
    test_metrics: null

data:
    _target_: lighter.LighterDataModule
    predict_dataloader:
      _target_: torch.utils.data.DataLoader
      batch_size: 64
      pin_memory: True
      num_workers: 8
      dataset:
        _target_: monai.data.CSVDataset
        src: /mnt/data16_r2d6/SSLThymus/annotated_processed_patches_train.csv
        colnames: ["positive", "label"]
        transform:
            _target_: monai.transforms.Compose
            transforms:
              - _target_: monai.transforms.LoadImaged
                keys: ["positive"]
                image_only: True
                reader: "NumpyReader"

              - _target_: monai.transforms.EnsureChannelFirstd
                keys: ["positive"]

              - _target_: monai.transforms.SelectItemsd
                keys: ["positive"]

              - _target_: monai.transforms.CenterSpatialCropd
                keys: ["positive"]
                roi_size: [48, 48, 48]

              - _target_: monai.transforms.SpatialPadd
                keys: ["positive"]
                spatial_size: [48, 48, 48]

              - _target_: torchvision.transforms.Lambda
                lambd: '$lambda x: x["positive"].as_tensor()'

              - _target_: project.transforms.utils.AddDummyTarget