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}}

Hi TrickyFox41 , does you script contains hydra integration? do you import hydra? using some configuration file?

When enqueued the configuration tab still shows the correct arguments

But not argument is passed to the scripts. Here i am printing sys.argv

Yes it uses hydra and everything works fine without clearml. The script is similar to this one https://github.com/galatolofederico/lightning-template/blob/main/train.py