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. |
Inheritance
builtins.object > proto.message.Message > IterationResultClasses
ArimaResult
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
ClusterInfo(mapping=None, *, ignore_unknown_fields=False, **kwargs)Information about a single cluster for clustering model.
Methods
__delattr__
__delattr__(key)Delete the value on the given field.
This is generally equivalent to setting a falsy value.
__eq__
__eq__(other)Return True if the messages are equal, False otherwise.
__ne__
__ne__(other)Return True if the messages are unequal, False otherwise.
__setattr__
__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.