Class IterationResult (2.4.0)

IterationResult(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Information about a single iteration of the training run.

Attributes

Name	Description
index	`.wrappers.Int32Value` Index of the iteration, 0 based.
duration_ms	`.wrappers.Int64Value` Time taken to run the iteration in milliseconds.
training_loss	`.wrappers.DoubleValue` Loss computed on the training data at the end of iteration.
eval_loss	`.wrappers.DoubleValue` Loss computed on the eval data at the end of iteration.
learn_rate	`float` Learn rate used for this iteration.
cluster_infos	Sequence[`.gcb_model.Model.TrainingRun.IterationResult.ClusterInfo`] Information about top clusters for clustering models.

builtins.object > proto.message.Message > IterationResult

ArimaResult(mapping=None, *, ignore_unknown_fields=False, **kwargs)

(Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results.

ClusterInfo(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Information about a single cluster for clustering model.

__delattr__(key)

Delete the value on the given field.

This is generally equivalent to setting a falsy value.

__eq__(other)

Return True if the messages are equal, False otherwise.

__ne__(other)

Return True if the messages are unequal, False otherwise.

__setattr__(key, value)

Set the value on the given field.

For well-known protocol buffer types which are marshalled, either the protocol buffer object or the Python equivalent is accepted.