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I Try To Update Scalars, But The Iteration I Pass Is Ignored, Instead The Last Iteration Is Incremented, Feels Wrong To Me.

I try to update scalars, but the iteration I pass is ignored, instead the last iteration is incremented, feels wrong to me.
prev_task = Task.init(continue_last_task=id)
prev_task.get_logger().report_scalar("model", "accuracy", 2, 0)

Posted 3 years ago
Votes Newest

Answers 5

Hi NastyOtter17 , I'm not sure I understand - can you explain what you see in the UI after running this as opposed to what you expect to see?

Posted 3 years ago

This seems to be in line with what you see

Posted 3 years ago

Indeed, does what stated in the docu, however I think its a bit odd, as .report_scalar() works quite different in this case compared to the normal case and iteration is not an optional param but will be ignored anyway

Posted 3 years ago

{'model': {'accuracy': {'name': 'accuracy', 'x': [0, 1], 'y': [0.5789473652839661, 1.0]}}
{'model': {'accuracy': {'name': 'accuracy', 'x': [0, 1, 2 ], 'y': [0.5789473652839661, 1.0, 2.0 ]}}
{'model': {'accuracy': {'name': 'accuracy', 'x': [ 0, 1], 'y': [ 2.0 , 1.0]}}

Posted 3 years ago

NastyOtter17 from Task.init() 's docstring regarding continue_last_task :
` continue_last_task (bool ) – Continue the execution of a previously executed Task (experiment)

When continuing the executing of a previously executed Task, all previous artifacts / models/ logs are intact. New logs will continue iteration/step based on the previous-execution maximum iteration value. For example: The last train/loss scalar reported was iteration 100, the next report will be iteration 101. `

Posted 3 years ago
5 Answers
3 years ago
one year ago