Evaluates the model on a data generator.

The generator should return the same kind of data as accepted by test_on_batch().

evaluate_generator(object, generator, steps, max_queue_size = 10,
  workers = 1)

Arguments

object	Model object to evaluate
generator	Generator yielding lists (inputs, targets) or (inputs, targets, sample_weights)
steps	Total number of steps (batches of samples) to yield from `generator` before stopping.
max_queue_size	Maximum size for the generator queue. If unspecified, `max_queue_size` will default to 10.
workers	Maximum number of threads to use for parallel processing. Note that parallel processing will only be performed for native Keras generators (e.g. `flow_images_from_directory()`) as R based generators must run on the main thread.

Named list of model test loss (or losses for models with multiple outputs) and model metrics.