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)Model object to evaluate
Generator yielding lists (inputs, targets) or (inputs, targets, sample_weights)
Total number of steps (batches of samples) to yield from
generator before stopping.
Maximum size for the generator queue. If unspecified,
max_queue_size will default to 10.
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.
Other model functions: compile,
evaluate.keras.engine.training.Model,
fit_generator, fit,
get_config, get_layer,
keras_model_sequential,
keras_model, multi_gpu_model,
pop_layer,
predict.keras.engine.training.Model,
predict_generator,
predict_on_batch,
predict_proba,
summary.keras.engine.training.Model,
train_on_batch