Examples: query, "exact match", wildcard*, wild?ard, wild*rd
Fuzzy search: cake~ (finds cakes, bake)
Term boost: "red velvet"^4, chocolate^2
Field grouping: tags:(+work -"fun-stuff")
Escaping: Escape characters +-&|!(){}[]^"~*?:\ with \, e.g. \+
Range search: properties.timestamp:[1587729413488 TO *] (inclusive), properties.title:{A TO Z}(excluding A and Z)
Combinations: chocolate AND vanilla, chocolate OR vanilla, (chocolate OR vanilla) NOT "vanilla pudding"
Field search: properties.title:"The Title" AND text
Answered
, This Is A Great Tool For Visualizing All Your Experiments. I Wanted To Know That When I Am Logging Scalar Plots With Title As Train Loss And Test Loss They Are Getting Diplayed As Train Loss And Test Loss In The Scalar Tab. I Wanted That The Title Shoul

@<1523701205467926528:profile|AgitatedDove14> , this is a great tool for visualizing all your experiments. I wanted to know that when I am logging scalar plots with title as train loss and test loss they are getting diplayed as train loss and test loss in the scalar tab.
I wanted that the title should be loss and under that I should get these two differnet graphs train loss and test loss. Is this possible?
image

  
  
Posted 4 years ago
Votes Newest

Answers 68


now after 1st iteration is completed then after 5 minutes my script runs automatically and then again it logs into trains server

  
  
Posted 4 years ago

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

  
  
Posted 4 years ago

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

  
  
Posted 4 years ago

You can do:
task = Task.get_task(task_id='uuid_of_experiment')
task.get_logger().report_scalar(...)

Now the only question is who will create the initial Task, so that the others can report to it. Do you have like a "master" process ?

  
  
Posted 4 years ago

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

  
  
Posted 4 years ago

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.

  
  
Posted 4 years ago

I didn't got it.

  
  
Posted 4 years ago

See on line 212 I am calling one function "combined" with some arguments

  
  
Posted 4 years ago

and that function creates Task and log them

  
  
Posted 4 years ago

Before this line, call Task.init

  
  
Posted 4 years ago

so , it will create a task when i will run it first time

  
  
Posted 4 years ago

then if there are 100 experiments how it will create 100 tasks?

  
  
Posted 4 years ago

It will not create another 100 tasks, they will all use the main Task. Think of it as they "inherit" it from the main process. If the main process never created a task (i.e. no call to Tasl.init) then they will create their own tasks (i.e. each one will create its own task and you will end up with 100 tasks)

  
  
Posted 4 years ago

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

  
  
Posted 4 years ago

Oh I got it.

  
  
Posted 4 years ago

I have to create a main task for example named as main

  
  
Posted 4 years ago

then if there are 10 experiments then I have to call Task.create() for those 10 experiments

  
  
Posted 4 years ago

Is this u meant?

  
  
Posted 4 years ago

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()

  
  
Posted 4 years ago

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()

  
  
Posted 4 years ago

what changes should I make here?

  
  
Posted 4 years ago

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

  
  
Posted 4 years ago

main will initialize parent task and then my multiprocessing occurs which call combined function with parameters as project_name and exp_name

  
  
Posted 4 years ago

then my combined function create a sub task using Task.create(task_name=exp_name)

  
  
Posted 4 years ago

and then log using logger

  
  
Posted 4 years ago

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

  
  
Posted 4 years ago

yes

  
  
Posted 4 years ago

each subprocess logs one experiment as task

  
  
Posted 4 years ago

image

  
  
Posted 4 years ago

like in the above picture

  
  
Posted 4 years ago
26K Views
68 Answers
4 years ago
7 months ago
Tags