Help protect the Great Barrier Reef with TensorFlow on Kaggle Join Challenge


Builds the TFF computation for federated evaluation of the given model.

Used in the notebooks

Used in the tutorials

model_fn A no-arg function that returns a tff.learning.Model. This method must not capture TensorFlow tensors or variables and use them. The model must be constructed entirely from scratch on each invocation, returning the same pre-constructed model each call will result in an error.
broadcast_process a tff.templates.MeasuredProcess that broadcasts the model weights on the server to the clients. It must support the signature (input_values@SERVER -> output_values@CLIENT) and have empty state. If set to default None, the server model is broadcast to the clients using the default tff.federated_broadcast.
use_experimental_simulation_loop Controls the reduce loop function for input dataset. An experimental reduce loop is used for simulation.

A federated computation (an instance of tff.Computation) that accepts model parameters and federated data, and returns the evaluation metrics as aggregated by tff.learning.Model.federated_output_computation.