predict_generator | R Documentation |
The generator should return the same kind of data as accepted by
predict_on_batch()
.
predict_generator(
object,
generator,
steps,
max_queue_size = 10,
workers = 1,
verbose = 0,
callbacks = NULL
)
object |
Keras model object |
generator |
Generator yielding batches of input samples. |
steps |
Total number of steps (batches of samples) to yield from
|
max_queue_size |
Maximum size for the generator queue. If unspecified,
|
workers |
Maximum number of threads to use for parallel processing. Note that
parallel processing will only be performed for native Keras generators (e.g.
|
verbose |
verbosity mode, 0 or 1. |
callbacks |
List of callbacks to apply during prediction. |
Numpy array(s) of predictions.
ValueError: In case the generator yields data in an invalid format.
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()
,
keras_model_sequential()
,
multi_gpu_model()
,
pop_layer()
,
predict.keras.engine.training.Model()
,
predict_on_batch()
,
predict_proba()
,
summary.keras.engine.training.Model()
,
train_on_batch()
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