Here is some code that shows exactly what goes wrong. I do local execution only. It seems not to be related to remote execution as I thought, but more related to clearml.Task:

` args = parser.parse_args()
print(args) # FIRST OUTPUT

command = args.command
enqueue = args.enqueue
track_remote = args.track_remote
preset_name = args.preset
type_name = args.type
environment_name = args.environment
nvidia_docker = args.nvidia_docker

# Initialize ClearML Task
task = (
    Task.init(
        project_name="reinforcement-learning/" + type_name,
        task_name=args.name or preset_name,
        tags=[environment_name],
        output_uri=True,
    )
    if track_remote or enqueue
    else None
)

print(task.get_parameters()) # SECOND OUTPUT `

First print(args) :
Namespace(checkpoint=None, checkpoint_every=1000, checkpoint_test_every=1000, command='train', device='cuda', enqueue=None, environment='walker_stand', jit=False, mixed_precision=False, name=None, nvidia_docker=False, preset='rlad.modules.dreamer.presets.dmc.original', render=False, steps=5000000, symbolic_obs=False, test_every=2000, test_steps=1000, track_remote=True, type='dmc')Second print print(task.get_parameters()) :
{'Args/command': "['train', 'rlad.modules.dreamer.presets.dmc.original', 'dmc', 'walker_stand', '5000000', '--test-steps', '1000', '--test-every', '2000', '--checkpoint-test-every', '1000', '--checkpoint-every', '1000', '--track-remote']", 'Args/preset': 'rlad.modules.dreamer.presets.dmc.original', 'Args/type': 'dmc', 'Args/environment': 'walker_stand', 'Args/nvidia_docker': 'False', 'Args/enqueue': '', 'Args/track_remote': 'True', 'Args/device': 'cuda', 'Args/name': '', 'Args/render': 'False', 'Args/checkpoint': '', 'Args/symbolic_obs': 'False', 'Args/mixed_precision': 'False', 'Args/jit': 'False', 'Args/steps': '5000000', 'Args/checkpoint_every': '1000', 'Args/checkpoint_test_every': '1000', 'Args/test_every': '2000', 'Args/test_steps': '1000'}