docs: minor tweaks to remove steps migration guide
@@ -1140,6 +1140,10 @@ the training data loader runs out of records).
Migration from v0.12.13 to v0.13.0
----------------------------------
+In v0.13.0, many configuration settings were renamed and updated to be configured in terms of
+the :ref:`training units<experiment-configuration_training_units>` records, batches, and epochs
+instead of steps.
+
This migration guide describes the steps to migrate your experiment configurations from v0.12.13 to
v0.13.0 while maintaining nearly identical behavior.
@@ -1170,30 +1174,38 @@ The table below describes the field names that have changed.
- min_checkpoint_period
For each configuration setting in the table, if it exists in your configuration, it should be
-renamed as shown above and the value should be changed from an integer to a map, `{batches: value}`,
-where value is the old value multiplied by the old value for ``batches_per_step``. If
-``batches_per_step`` was not specified, use the default value of 100. For example, to migrate this
-single searcher:
+renamed as shown above and changed to use the new units. To migrate the value to the new units,
+it should be changed from an integer to a map, ``{batches: value}``, where value is the old value
+multiplied by the old value for ``batches_per_step``. If ``batches_per_step`` was not specified, use
+the default value of 100. For example, to migrate this single searcher:
.. code:: yaml
batches_per_step: 100
+ min_validation_period: 1
+ min_checkpoint_period: 2
searcher:
name: single
metric: accuracy
max_trials: 5
max_steps: 10
-We replace ``max_steps`` by ``max_length``, change the value to ``{batches: 100*10}``.
+We replace ``max_steps`` by ``max_length`` and change the value to ``{batches: 100*10}``, change the
+value for ``min_validation_period`` to ``{batches: 100*1}``, and change the value for
+``min_checkpoint_period`` to ``{batches: 100*2}``.
.. code:: yaml
scheduling_unit: 100
+ min_validation_period:
+ batches: 100
+ min_checkpoint_period:
+ batches: 200
searcher:
name: single
metric: accuracy
max_trials: 5
- max_steps:
+ max_length:
batches: 1000
Finally, we also rename ``batches_per_step`` to ``scheduling_unit``, leaving the value the same.
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