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Dear Clearml Community,
I Am Looking For A Way To Properly Resume A Training In A Way That Initial Scalars Get Reused And Expanded. Clearml Feature For Reusing The Same Task Works Fine (When Using
Hi @<1663354518726774784:profile|CrookedSeal85>
However, I systematically notice a jump of some number of "ghost iterations" when resuming my trainings...
Try the following:
task = Task.init(..., continue_last_task=0
from the Task.init docstring (Notice this value can be both boolean and integer)
:param bool continue_last_task: Continue the execution of a
...
- An integer - Specify initial iteration offset (override the auto automatic last_iteration_offset). Pass 0, to disable the automatic last_iteration_offset or specify a different initial offset. You can specify a Task ID to be used with `reuse_last_task_id='task_id_here'`
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9 months ago
9 months ago