Description Super class Methods
This rule helps to detect outlier in step durations. Rule returns True if duration is larger than stddev * standard deviation.
sagemaker.debugger::ProfilerRuleBase
-> StepOutlier
new()
Initialize StepOutlier class
StepOutlier$new( stddev = 3, mode = NULL, n_outliers = 10, scan_interval_us = 60 * 1000 * 1000 )
stddev
: factor by which to multiply the standard deviation. Default is 3
mode
: select mode under which steps have been saved and on which Rule should run on. Per default rule will run on steps from EVAL and TRAIN phase.
n_outliers
: How many outliers to ignore before rule returns True. Default 10.
scan_interval_us
: interval with which timeline files are scanned. Default is 60000000 us.
clone()
The objects of this class are cloneable with this method.
StepOutlier$clone(deep = FALSE)
deep
Whether to make a deep clone.
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