Define and Set Up Metric Space
Similar to defining the hyperparameter space, you need to define the metric space to run a SigOpt Experiment.
The entire metric space is defined as a list of objects, where each object represents a metric.
Each metric is given a name
, an objective
and a strategy
. Metrics with a strategy of constraint
must have a threshold
. Metrics with a strategy of optimize
can optionally be assigned a threshold
.
name: str
name: str
The metric name is a string used to keep track of the different metrics in the experiment.
objective: maximize, minimize
objective: maximize, minimize
The objective is a flag that specifies if a metric is intended to be maximized (default) or minimized by either setting maximize
or minimize
.
strategy: optimize, constraint, store
strategy: optimize, constraint, store
SigOpt allows three different types of metrics: optimized (default), constrained and stored. They are invoked by calling optimize
, constraint,
and store
respectively.
Store
metrics are for tracking purposes. SigOpt can handle up to 50 stored metrics per training run or experiment.
Metric Failures
Cases we recommend marking as Failures:
Evaluating a metric is not possible because the SigOpt provided parameter assignments are infeasible/ not of interest
Certain parameter configurations lead to out-of-memory error or run-time errors
If model training abruptly stops because a machine randomly fails, we recommend deleting that Run or Observation instead of marking it as failed.
Core Module
AI Module
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