Is this u meant?

logger.report_scalar("loss-train", "train", iteration=0, value=100)
logger.report_scalar("loss=test", "test", iteration=0, value=200)
notice that the title of the graph is its uniue id, so if you send scalars to with the same "title" they will show on the same graph

logger.report_scalar("loss", "train", iteration=0, value=100)
logger.report_scalar("loss", "test", iteration=0, value=200)

I have 100 experiments and I have to log them and update those experiments every 5 minutes

I will share my script u can see it what I am doing

no i want all of them in the same experiment

but this gives the results in the same graph

What do you mean by "tag" / "sub-tags"?

and under that there will be three graphs with title as train test and loss

Just call the Task.init before you create the subprocess, that's it 🙂 they will all automatically log to the same Task. You can also call the Task.init again from within the subprocess task, it will not create a new experiment but use the main process experiment.

its like main title will be loss

Like here in the sidebar I am getting three different plots named as loss, train_loss and test_loss

So you want these two on two different graphs ?

but what is happening is it is creating new task under same project with same task name

I didn't got it.

so, if I call Task.init() before that line there is no need of calling Task.init() on line number 92

Hi @<1523701205467926528:profile|AgitatedDove14> , I wanted to ask you something. Is it possible that we can talk over voice somewhere so that I can explain my problem better?

In the side bar you get the title of the graphs, then when you click on them you can see the diff series on the graphs themselves

Oh I got it.

and it should log it into the same task and same project

This code will give you one graph titled "loss" with two series: (1) trains (2) loss

i mean all 100 experiments in one project

This code gives me the graph that I displayed above

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

like in the above picture

logger.report_scalar(title="loss", series="train", iteration=0, value=100)
logger.report_scalar(title="loss", series="test", iteration=0, value=200)

what changes should I make here?

Just so I understand,
scheduler executes main every 60sec
main spins X sub-processes
Each subprocess needs to report scalars ?

And you want all of them to log into the same experiment ? or do you want an experiment per 60sec (i.e. like the scheduler)