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75 × Eureka!no, I set the env variable CLEARML_TASK_ID myself
report_scalar works, report_text does not, this is very weird
I am not an expert on this, just started using torchmetrics.
which is probably why it does not work for me, right?
my code snippet
` from clearml import Task
import os
clearml_task_id = os.environ['CLEARML_TASK_ID']
Task.debug_simulate_remote_task(clearml_task_id)
clearml_task = Task.init(auto_connect_arg_parser=False, auto_resource_monitoring=False)
print(clearml_task.id)
clearml_task.logger.report_scalar(series='s', value='123', iteration=2, title='title')
clearml_task.logger.report_text("some text") `
I can't make anything appear in the console part of the ui
I created my own docker image with a newer python and the error disappeared
and in the future I do want to have an Agent on the k8s cluster, but then this should not be a problem I guess as the user is set during Task.init
, right?
just put ssh config with the proper key marked
they are universal, I thought there is some interface to them in clearml, but probably not
it is typically sued with pytorch
console output:ClearML results page:
01b77a220869442d80af42efce82c617 some text 2022-03-21 22:47:16,660 - clearml.Task - INFO - Waiting to finish uploads 2022-03-21 22:47:28,217 - clearml.Task - INFO - Finished uploading
I am only getting one user for some reason, even though 4 are in the system
but perhaps it is worth adding to the docs page a hint to avoid using the CLEARML_TASK_ID env variable, perhaps I am not the only one to ever try it
it is a configuration object (line of my code:config_path = task.connect_configuration(config_path)
I did something similar to what you suggests and it worked, the key insight was that connect and connect_configuration work differently in terms of overrides, thanks!
I could have been more inventive as well 😄