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69 × Eureka!Maybe I should pass something in extra_docker_arguments?
CostlyOstrich36
I just added -p port_num:port_num to extra_docker_arguments
I know, but I run a scheduler on the script that downloads a dataset, and if there is no new dataset to download, I try to figure out what it will do
Hey,
Thanks!
The pipline demo is running but the first step stack on 'Pending'
CostlyOstrich36 tensorflow reporting it, ClearML capture it, and I get it with that function.
CostlyOstrich36 I have my own function that gives an estimate of performance, and I want to display it in the graph of each iteration.
And I am using tensorflow
CostlyOstrich36 thanks.
Maybe I should pass something in extra_docker_arguments in the config file?
Hi SweetBadger76
It worked great yesterday and also a week ago ..
I'm trying to figure out what happened because I did not make any change to the code
CostlyOstrich36 More precisely, My function only calculates the accuracy as I defined it.
I passing the accuracy to logger.report_scalar by
logger.report_scalar(title='evaluate', series='score', value=my_acc, iteration=task.get_last_iteration())
Hi CostlyOstrich36 CrookedWalrus33 AgitatedDove14
When I init an agent and run a task it works, but when I run the same task again it does not map the keys..
I found the problem I think, thanks!
CostlyOstrich36 Not sure I understood, the current iterations come from the function
task.get_last_iteration() ...
MelancholyElk85 How do I change the SCRIPT PATH/SCRIPT PATH
I have nowhere else to bring iteration number ..
And again only in docker mode CostlyOstrich36
ExasperatedCrab78
logger = task.get_logger()
train(model_dir=trained_model_dst, pipeline_config_path=pipeline_config_path, save_checkpoints_steps=args.checkpoints)
logger.report_scalar(title='evaluate', series='score', value=5, iteration=task.get_last_iteration())