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.
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
This code will give you one graph titled "loss" with two series: (1) trains (2) loss
so, like if validation loss appears then there will be three sub-tags under one main tag loss
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 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 will share my script u can see it what I am doing
If you one each "main" process as a single experiment, just don't call Task.init in the scheduler
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
See on line 212 I am calling one function "combined" with some arguments
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.
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?
like if u see in above image my project name is abcd18 and under that there are experiments Experiment1, Experiment2 etc.
but this gives the results in the same graph
so I want loss should be my main title and I want two different graphs of train and test loss under that loss
i mean all 100 experiments in one project
Can my request be made as new feature so that we can tag same type of graphs under one main tag
Like here in the sidebar I am getting three different plots named as loss, train_loss and test_loss
@<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.
yes But i want two graphs with title as train loss and test loss and they should be under main category "loss"
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"
then my combined function create a sub task using Task.create(task_name=exp_name)
logger.report_scalar("loss", "train", iteration=0, value=100)
logger.report_scalar("loss", "test", iteration=0, value=200)
@<1523701205467926528:profile|AgitatedDove14> I want to log directly to trains using logger.report_scalar