Currently, I’m manually tracking multiple output models at the end of the training process
model_paths = list(Path(checkpoint_dir).absolute().glob('*')) for model_path in model_paths: output_model = OutputModel(task=task, name=f'{args.task_name}-{model_path.stem}', framework='PyTorch') output_model.update_weights(weights_filename=str(model_path), target_filename=model_path.stem) # task.update_output_model(model_path=str(model_path), # model_name=f'{args.task_name}-{model_path.stem}')The problem with this approach is when I publish my experiment, only one (the first or the last OutputModel, idk) of all logged models is published, the others remain Draft .
Is this a feature of ClearML? If not, how could I fix it? Thanks!