and under that there will be three graphs with title as train test and loss
Sure @<1523720500038078464:profile|MotionlessSeagull22> DM me 🙂
each subprocess logs one experiment as task
Can my request be made as new feature so that we can tag same type of graphs under one main tag
Sure, open a Git Issue :)
This code will give you one graph titled "loss" with two series: (1) trains (2) loss
main will initialize parent task and then my multiprocessing occurs which call combined function with parameters as project_name and exp_name
okay, Thanks @<1523701205467926528:profile|AgitatedDove14> for the help.
logger.report_scalar(title="loss", series="train", iteration=0, value=100)logger.report_scalar(title="loss", series="test", iteration=0, value=200)
So you want these two on two different graphs ?
I have to create a main task for example named as main
so I want loss should be my main title and I want two different graphs of train and test loss under that loss
yes But i want two graphs with title as train loss and test loss and they should be under main category "loss"
so what I have done is rather than reading sequentially I am reading those experiments through multiprocessing and for each experiment I am creating new task with specified project_name and task_name
I have 100 experiments and I have to log them and update those experiments every 5 minutes
i mean all 100 experiments in one project
Are you using tensorboard or do you want to log directly to trains ?
so, like if validation loss appears then there will be three sub-tags under one main tag loss
Like here in the sidebar I am getting three different plots named as loss, train_loss and test_loss
No. since you are using Pool. there is no need to call task init again. Just call it once before you create the Pool, then when you want to use it, just do task = Task.current_task()
and it should log it into the same task and same project