This is a convenience utility to be used when overriding
$train_step, $test_step, or $predict_step.
This utility makes it easy to support data of the form (x,),
(x, y), or (x, y, sample_weight).
Example:
features_batch <- op_ones(c(10, 5))
labels_batch <- op_zeros(c(10, 5))
data <- list(features_batch, labels_batch)
# `y` and `sample_weight` will default to `NULL` if not provided.
c(x, y, sample_weight) %<-% unpack_x_y_sample_weight(data)You can also do the equivalent by providing default values to %<-%
See also
Other data utils: pack_x_y_sample_weight() zip_lists()
Other utils: audio_dataset_from_directory() clear_session() config_disable_interactive_logging() config_disable_traceback_filtering() config_enable_interactive_logging() config_enable_traceback_filtering() config_is_interactive_logging_enabled() config_is_traceback_filtering_enabled() get_file() get_source_inputs() image_array_save() image_dataset_from_directory() image_from_array() image_load() image_smart_resize() image_to_array() layer_feature_space() normalize() pack_x_y_sample_weight() pad_sequences() set_random_seed() split_dataset() text_dataset_from_directory() timeseries_dataset_from_array() to_categorical() zip_lists()