dataset_shuffle_and_repeat: Shuffles and repeats a dataset returning a new permutation...

In tfdatasets: Interface to 'TensorFlow' Datasets

Shuffles and repeats a dataset returning a new permutation for each epoch.

Description

Shuffles and repeats a dataset returning a new permutation for each epoch.

Usage

dataset_shuffle_and_repeat(dataset, buffer_size, count = NULL, seed = NULL)

Arguments

dataset	A dataset
buffer_size	An integer, representing the number of elements from this dataset from which the new dataset will sample.
count	(Optional.) An integer value representing the number of times the elements of this dataset should be repeated. The default behavior (if count is NULL or -1) is for the elements to be repeated indefinitely.
seed	(Optional) An integer, representing the random seed that will be used to create the distribution.

See Also

Other dataset methods: dataset_batch(), dataset_cache(), dataset_collect(), dataset_concatenate(), dataset_decode_delim(), dataset_filter(), dataset_interleave(), dataset_map(), dataset_map_and_batch(), dataset_padded_batch(), dataset_prefetch(), dataset_prefetch_to_device(), dataset_reduce(), dataset_repeat(), dataset_shuffle(), dataset_skip(), dataset_take(), dataset_take_while(), dataset_window()

tfdatasets documentation built on Sept. 11, 2024, 8:53 p.m.