This is the full print(cfg)
{'dataset': {'name': '<my-dataset-name>', 'path': '', 'target_shape': [128, 128]}, 'model': 'unet', 'models': {'unet': {'dim': 8, 'dim_mults': [1, 2, 4], 'num_blocks_per_stage': [2, 2, 2], 'num_self_attn_per_stage': [0, 0, 1], 'nested_unet_depths': [0, 0, 0], 'nested_unet_dim': 16, 'use_convnext': False, 'resnet_groups': 2, 'consolidate_upsample_fmaps': True, 'weight_standardize': False, 'attn_heads': 2, 'attn_dim_head': 16}}, 'train': {'accelerator': 'auto', 'gpus': 1, 'epochs': 100, 'batch_size': 8, 'lr': 0.001, 'seed': -1, 'log_every_n_steps': 1, 'checkpoints': False, 'enable_checkpoints': False, 'save': ''}, 'clearml': {'project': '<project-name>', 'task': '<task-name>', 'output_uri': 's3://<myhost>/<mybucket>', 'save': False, 'tags': None}, 'log': {'clearml': False, 'log_images_every_steps': 100}}