no i want all of them in the same experiment

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.

i mean all 100 experiments in one project

so I want loss should be my main title and I want two different graphs of train and test loss under that loss

and then log using logger

its like main title will be loss

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

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

Can my request be made as new feature so that we can tag same type of graphs under one main tag

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

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

Sure

If you one each "main" process as a single experiment, just don't call Task.init in the scheduler

@<1523720500038078464:profile|MotionlessSeagull22> you cannot have two graphs with the same title, the left side panel presents graph titles. That means that you cannot have a title=loss series=train & title=loss series=test on two diff graphs, they will always be displayed on the same graph.
That said, when comparing experiments, all graph pairs (i.e. title+series) will be displayed as a single graph, where the diff series are the experiments.

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?

make sense ?

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

but this gives the results in the same graph

like in the sidebar there should be a title called "loss" and under that two different plots should be there named as "train_loss" and "test_loss"

I have one more question?

and that function creates Task and log them

Before this line, call Task.init

like in the above picture

Create one experiment (I guess in the scheduler)
task = Task.init('test', 'one big experiment')
Then make sure the the scheduler creates the "main" process as subprocess, basically the default behavior)
Then the sub process can call Task.init and it will get the scheduler Task (i.e. it will not create a new task). Just make sure they all call Task init with the same task name and the same project name.

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

my scheduler will be running every 60 seconds and calling main function

okay, Thanks @<1523701205467926528:profile|AgitatedDove14> for the help.

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

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