Remove extra indent in the doc.
@@ -41,11 +41,11 @@ def build_personalization_eval(model_fn,
strategy name) to a no-argument function that returns a `tf.function`.
Each `tf.function` represents a personalization strategy: it accepts a
`tff.learning.Model` (with weights already initialized to the provided
- model weights when users invoke the returned TFF computation), a
- training `tf.dataset.Dataset`, a test `tf.dataset.Dataset`, and an
- arbitrary context object (which is used to hold any extra information
- that a personalization strategy may use), trains a personalized model,
- and returns the evaluation metrics. The evaluation metrics are usually
+ model weights when users invoke the returned TFF computation), a training
+ `tf.dataset.Dataset`, a test `tf.dataset.Dataset`, and an arbitrary
+ context object (which is used to hold any extra information that a
+ personalization strategy may use), trains a personalized model, and
+ returns the evaluation metrics. The evaluation metrics are usually
represented as an `OrderedDict` (or a nested `OrderedDict`) of `string`
metric names to scalar `tf.Tensor`s.
baseline_evaluate_fn: A `tf.function` that accepts a `tff.learning.Model`
