keras: evaluate_generator – R documentation

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evaluate_generator

Evaluates the model on a data generator.

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,
  callbacks = NULL
)

`object`	Model object to evaluate
`generator`	Generator yielding lists (inputs, targets) or (inputs, targets, sample_weights)
`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.
`callbacks`	List of callbacks to apply during evaluation.

Named list of model test loss (or losses for models with multiple outputs) and model metrics.