Update docs/about/features_index/workflowinterface.rst

Review comments incorporated.

Co-authored-by: Patrick Foley <[email protected]>
Signed-off-by: Parth Mandaliya <[email protected]>

docs/about/features_index/workflowinterface.rst

@@ -169,7 +169,7 @@ A :code:`Runtime` defines where the flow will be executed, who the participants
 
 Let's break this down, starting with the :code:`Aggregator` and :code:`Collaborator` components. These components represent the *Participants* in a Federated Learning experiment. Each participant has its own set of *private attributes*. As the name suggests, these *private attributes* represent private information they do not want to share with others, and will be filtered out when there is a transition from the aggregator to the collaborator or vice versa. In the example above each collaborator has it's own `train_dataloader` and `test_dataloader` that are only available when that collaborator is performing it's tasks via `self.train_loader` and `self.test_loader`. Once those collaborators transition to a task at the aggregator, this private information is filtered out and the remaining collaborator state can safely be sent back to the aggregator. 
 
-In the above :code:`FederatedFlow`, each collaborator accesses train and test datasets via *private attributes* :code:`train_loader` and :code:`test_loader`. These *private attributes* need to be set in form of a dictionary(user defined), where the key is the name of the attribute and the value is the object. In this example :code:`collaborator.private_attributes` sets the collaborator *private attributes* :code:`train_loader` and :code:`test_loader` that are accessed by collaborator steps (:code:`aggregated_model_validation`, :code:`train` and :code:`local_model_validation`). 
+These *private attributes* need to be set in form of a dictionary(user defined), where the key is the name of the attribute and the value is the object. In this example :code:`collaborator.private_attributes` sets the collaborator *private attributes* :code:`train_loader` and :code:`test_loader` that are accessed by collaborator steps (:code:`aggregated_model_validation`, :code:`train` and :code:`local_model_validation`). 
 
 While setting *private attributes* directly through a dictionary is the preferred method, this requires an object to be initialized before the flow begins execution. 
 In rare cases this can be a problem because certain python objects cannot be serialized. To compensate for these cases, users can delay the *private attributes* object initialization via the use of a callback: