--- imports: - "$import glob" - "$import os" input_channels: 1 output_classes: 3 arch_ckpt_path: "$@bundle_root + '/models/search_code_18590.pt'" arch_ckpt: "$torch.load(@arch_ckpt_path, map_location=torch.device('cuda'))" bundle_root: "." output_dir: "$@bundle_root + '/eval'" dataset_dir: "/workspace/data/msd/Task07_Pancreas" data_list_file_path: "$@bundle_root + '/configs/dataset_0.json'" datalist: "$monai.data.load_decathlon_datalist(@data_list_file_path, data_list_key='testing', base_dir=@dataset_dir)" device: "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')" dints_space: _target_: monai.networks.nets.TopologyInstance channel_mul: 1 num_blocks: 12 num_depths: 4 use_downsample: true arch_code: - "$@arch_ckpt['arch_code_a']" - "$@arch_ckpt['arch_code_c']" device: "$torch.device('cuda')" network_def: _target_: monai.networks.nets.DiNTS dints_space: "@dints_space" in_channels: "@input_channels" num_classes: "@output_classes" use_downsample: true node_a: "$torch.from_numpy(@arch_ckpt['node_a'])" network: "$@network_def.to(@device)" preprocessing: _target_: Compose transforms: - _target_: LoadImaged keys: image - _target_: EnsureChannelFirstd keys: image - _target_: Orientationd keys: image axcodes: RAS - _target_: Spacingd keys: image pixdim: - 1 - 1 - 1 mode: bilinear - _target_: ScaleIntensityRanged keys: image a_min: -87 a_max: 199 b_min: 0 b_max: 1 clip: true - _target_: EnsureTyped keys: image dataset: _target_: Dataset data: "@datalist" transform: "@preprocessing" dataloader: _target_: DataLoader dataset: "@dataset" batch_size: 1 shuffle: false num_workers: 4 inferer: _target_: SlidingWindowInferer roi_size: - 96 - 96 - 96 sw_batch_size: 4 overlap: 0.625 postprocessing: _target_: Compose transforms: - _target_: Activationsd keys: pred softmax: true - _target_: Invertd keys: pred transform: "@preprocessing" orig_keys: image meta_key_postfix: meta_dict nearest_interp: false to_tensor: true - _target_: AsDiscreted keys: pred argmax: true - _target_: SaveImaged keys: pred meta_keys: pred_meta_dict output_dir: "@output_dir" handlers: - _target_: CheckpointLoader load_path: "$@bundle_root + '/models/model.pt'" load_dict: model: "@network" - _target_: StatsHandler iteration_log: false evaluator: _target_: SupervisedEvaluator device: "@device" val_data_loader: "@dataloader" network: "@network" inferer: "@inferer" postprocessing: "@postprocessing" val_handlers: "@handlers" amp: true initialize: - "$setattr(torch.backends.cudnn, 'benchmark', True)" run: - "$@evaluator.run()"