Fix some program example typos.
@@ -75,11 +75,11 @@ async def train_federated_model(
client data used during evaluation.
total_rounds: The number of training rounds to run.
number_of_clients: The number of clients per round of training.
- train_output_managers: An optional list of `tff.program.ReleaseManagers`s
+ train_output_managers: An optional list of `tff.program.ReleaseManager`s
used to release training output.
evaluation_output_managers: An optional list of
- `tff.program.ReleaseManagers`s used to release evaluation output.
- model_output_manager: An optional `tff.program.ReleaseManagers`s used to
+ `tff.program.ReleaseManager`s used to release evaluation output.
+ model_output_manager: An optional `tff.program.ReleaseManager` used to
release training output.
program_state_manager: An optional `tff.program.ProgramStateManager` used to
save program state for fault tolerance.
@@ -162,7 +162,7 @@ async def train_federated_model(
evaluation_metrics_type = evaluation.type_signature.result
tasks.add_all(*[
m.release(evaluation_metrics, evaluation_metrics_type, round_number)
- for m in train_output_managers
+ for m in evaluation_output_managers
])
# Release the model output.
