Sometimes I have " connection refused" when I logged my task but I've never been able to understand why exactly.
I followed the tutorial to setup my server  except I didn't set up any  of the experted parameters ," clearml_agent key"  " CLEARML_host_IP" / " CLEARML_AGENT_GIT_PASS" ...
Eventually I just run this command
docker compose -f opt/clearml/docker-compose.yml
Have you looked into why this comes up?
clearml-fileserver  |     raise ValueError('Connection Error: it seems *api_server* is misconfigured. '
clearml-fileserver  | ValueError: Connection Error: it seems *api_server* is misconfigured. Is this the ClearML API server 
 ?
@<1638349756755349504:profile|MistakenTurtle88>  - Can you also share your  docker-compose.yml  file?  Thanks!!
Hello,
This is my train.pymodel = ModelParams(cfg.get("model", None))opt = OptimizationParams(cfg.get("optimization", None))cmlparams = ClearmlParams(cfg.get("clearml", None))pipeline: "PipelineParams" = PipelineParams(cfg=cfg.get("pipeline", None))test_iterations_default = (list(range(0, 100)) + list(range(100, 1000, 10)) + list(range(1000, 10000, 50)))GS_loger: "loggingGS" = cfg.get("gs_logger", None)test_iterations_default = (list(range(0, 100, 10)) + list(range(0, 100000, 100)) + [opt.iterations - 1])
test_iterations_default = sorted(list(set(test_iterations_default)))
if CLEARML_FOUND and not pipeline.debug:from utils.clearml_utils import safe_init_clearml, connect_whole
assert (cmlparams.task_name != ""), "Please provide a task name for ClearML,got {}".format(cmlparams.task_name)
task = Task.init(project_name=cmlparams.project_name,task_name=cmlparams.task_name,tags=cmlparams.tags,)connect_whole(cfg=cfg,task=task,name_hyperparams_summary="train config",name_connect_cfg="whole train cfg",)# task.connect(cfg,name="test_train")else:print(" We didn't find clearml or you are in debug mode, we don't log to Clearml")print("Optimizing " + cfg.model.model_path)
# Initialize system state (RNG)safe_state(cfg.quiet, seed=cfg.seed)
# Start GUI server, configure and run trainingtorch.autograd.set_detect_anomaly(cfg.detect_anomaly)
training(sceneparams=model,opt=opt,pipe=pipeline,GS_loger=GS_loger,testing_iterations=test_iterations_default,saving_iterations=cfg.save_iterations,checkpoint_iterations=cfg.checkpoint_iterations,start_checkpoint=cfg.start_checkpoint,debug_from=cfg.debug_from,)# All doneprint("\nTraining complete.")if CLEARML_FOUND and not pipeline.debug:print("Attempting to close clearml task")# print("task url",task.get_web_a)
task.close()print("ClearML task closed")
The code stop at  task.close()
my clearml.conf is
@<1638349756755349504:profile|MistakenTurtle88>  I'm not sure I understand what gets stuck - you're running python code with the ClearML ASK and call task.close()? Can you share the code you're running and how your  clearml.conf  file is configured?
 
				 
				 
				