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69 × Eureka!then my combined function create a sub task using Task.create(task_name=exp_name)
so, if I call Task.init() before that line there is no need of calling Task.init() on line number 92
See on line 212 I am calling one function "combined" with some arguments
@<1523701205467926528:profile|AgitatedDove14> I want to log directly to trains using logger.report_scalar
like if u see in above image my project name is abcd18 and under that there are experiments Experiment1, Experiment2 etc.
and that function creates Task and log them
but this gives the results in the same graph
what changes should I make here?
i mean all 100 experiments in one project
so, like if validation loss appears then there will be three sub-tags under one main tag loss
I have to create a main task for example named as main
def combined(path,exp_name,project_name):
temp = Task.create(task_name="exp_name")
logger = temp.current_logger()
logger.report_scalar()
def main():
task=Task.init(project_name="test")
[pool.apply_async(combined, args = (row['Path'], row['exp_name'], row['project_name'])) for index,row in temp_df.iterrows()]
scheduler = BlockingScheduler()
scheduler.add_job(main, 'interval', seconds=60, max_instances=3)
scheduler.start()
this is ok but in the path if they have changed the model then
each subprocess logs one experiment as task
Like here in the sidebar I am getting three different plots named as loss, train_loss and test_loss
okay, Thanks @<1523701205467926528:profile|AgitatedDove14> for the help.
yes But i want two graphs with title as train loss and test loss and they should be under main category "loss"
its like main title will be loss
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?
main will initialize parent task and then my multiprocessing occurs which call combined function with parameters as project_name and exp_name