predict_generator: Generates predictions for the input samples from a data...

Description Usage Arguments Value Raises See Also

View source: R/model.R

Description

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

Usage

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predict_generator(object, generator, steps, max_queue_size = 10,
  workers = 1, verbose = 0, callbacks = NULL)

Arguments

object

Keras model object

generator

Generator yielding batches of input samples.

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.

verbose

verbosity mode, 0 or 1.

callbacks

List of callbacks to apply during prediction.

Value

Numpy array(s) of predictions.

Raises

ValueError: In case the generator yields data in an invalid format.

See Also

Other model functions: compile.keras.engine.training.Model, evaluate.keras.engine.training.Model, evaluate_generator, fit.keras.engine.training.Model, fit_generator, get_config, get_layer, keras_model_sequential, keras_model, multi_gpu_model, pop_layer, predict.keras.engine.training.Model, predict_on_batch, predict_proba, summary.keras.engine.training.Model, train_on_batch


keras documentation built on Oct. 9, 2019, 1:04 a.m.