R/model.R

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 
) 

Arguments

Arguments Description
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.

Section

Raises

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

Value

Numpy array(s) of predictions.

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()