keras (version 2.13.0)

predict_generator: (Deprecated) Generates predictions for the input samples from a data generator.

Description

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

Usage

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

Value

Numpy array(s) of predictions.

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.

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()