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We recommend upgrading to the new Query API.
Attribute
Helper for specifying an attribute and picking a metric aggregation function.
When fetching experiments or runs, use the Attribute
constructor to filter and sort the returned entries.
Parameters
An attribute name to match exactly.
Aggregation function to apply when specifying a metric of type FloatSeries
.
Defaults to "last"
, that is, the last logged value.
Attribute type. Specify it to resolve ambiguity, in case some of the project's runs contain attributes that have the same name but are of a different type.
Examples
Select a metric and pick variance as the aggregation:
import neptune_fetcher.alpha as npt
from neptune_fetcher.alpha.filters import Attribute, Filter
val_loss_variance = Attribute(
name="val/loss",
aggregation="variance",
)
Construct a filter around the attribute with the Filter
class, then pass it to a fetching or listing method:
tiny_val_loss_variance = Filter.lt(val_loss_variance, 0.01)
npt.fetch_experiments_table(experiments=tiny_val_loss_variance)