Interface to 'TensorFlow' Datasets

Interface to 'TensorFlow' Datasets, a high-level library for building complex input pipelines from simple, re-usable pieces. See < https://www.tensorflow.org/programmers_guide/datasets> for additional details.


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/.

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Reference manual

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install.packages("tfdatasets")

1.9 by JJ Allaire, 6 months ago


https://github.com/rstudio/tfdatasets


Report a bug at https://github.com/rstudio/tfdatasets/issues


Browse source code at https://github.com/cran/tfdatasets


Authors: JJ Allaire [aut, cre] , Yuan Tang [aut] , Kevin Ushey [aut] , RStudio [cph, fnd] , Google Inc. [cph]


Documentation:   PDF Manual  


Apache License 2.0 license


Imports reticulate, tensorflow, magrittr, rlang, tidyselect, stats

Suggests testthat, knitr, tfestimators, keras

System requirements: TensorFlow >= 1.4 (https://www.tensorflow.org/)


Imported by tfio.


See at CRAN