R interface to TensorFlow Datasets API
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R Parse args for 'make_csv_dataset' according to TensorFlow version Oct 29, 2018
examples add until_out_of_range function (revert for_each_batch function) Jul 22, 2018
man update to roxygen 6.1.0 Oct 30, 2018
tests use text version of break Aug 25, 2018
vignettes install from cran Aug 25, 2018
DESCRIPTION update to roxygen 6.1.0 Oct 30, 2018
NAMESPACE add sample_from_datasets wrapper Jul 26, 2018


R interface to TensorFlow Dataset API

The TensorFlow Dataset API provides various facilities for creating scalable input pipelines for TensorFlow models, including:

  • Reading data from a variety of formats including CSV files and TFRecords files (the standard binary format for TensorFlow training data).

  • Transforming datasets in a variety of ways including mapping arbitrary functions against them.

  • Shuffling, batching, and repeating datasets over a number of epochs.

  • Streaming interface to data for reading arbitrarily large datasets.

  • Reading and transforming data are TensorFlow graph operations, so are executed in C++ and in parallel with model training.

The R interface to TensorFlow datasets provides access to the Dataset API, including high-level convenience functions for easy integration with the tfestimators package.

For documentation on using tfdatasets, see the package website at https://tensorflow.rstudio.com/tools/tfdatasets/.