I guess this is doable:
You can get the entire set of scalars like as pandas DF: https://www.tensorflow.org/tensorboard/dataframe_api
(another example: https://stackoverflow.com/a/45899735 )
Then iterate over the different runs and create + report scalars)
` from clearml import Task

for run in runs:
task = Task.create_task(...)
logger = task.get_logger()

not real code, just example:

w_times, step_nums, vals = zip(*event_acc.Scalars('Accuracy'))
for step, val in zip(step_nums, vals):
logger.report_scalar(title='Accuracy', series='Accuracy', iteraiton=step, value=val)

we are done

task.close() `Obviously this is missing the link to the code repository + python packages + console logs etc. But it will get you the scalars 🙂