README.md

In rstudio/tfds: Interface to 'TensorFlow' Collection of Datasets

tfds

tfds is an R interface to TensorFlow Datasets and provides a collection of datasets ready to use with TensorFlow and Keras. It handles downloading and preparing the data and constructing a TensorFlow Dataset.

Installation

tfds is not currently on CRAN. The development version can be installed from GitHub with:

# install.packages("remotes")
remotes::install_github("rstudio/tfds")

After installing the R package, you need to install the tensorflow_datasets python module with:

tfds::install_tfds()

Example

tfds_load is a convenience method that’s the simplest way to build and load a tf_dataset.

Below, we load the MNIST training data. It downloads and prepares the data, unless you specify download=FALSE. Note that once data has been prepared, subsequent calls of load will reuse the prepared data. You can customize where the data is saved/loaded by specifying data_dir= (defaults to ~/tensorflow_datasets/).

library(tfds)
mnist <- tfds_load("mnist")
mnist
#> $test
#> <_OptionsDataset shapes: {image: (28, 28, 1), label: ()}, types: {image: tf.uint8, label: tf.int64}>
#> 
#> $train
#> <_OptionsDataset shapes: {image: (28, 28, 1), label: ()}, types: {image: tf.uint8, label: tf.int64}>

This will use the default version of the dataset. It’s however recommended to specify the dataset version when loading:

minst <- tfds_load("mnist:1.*.*")

We can build a simple model using mnist and Keras with:

library(keras)
library(tfdatasets)

model <- keras_model_sequential() %>% 
layer_flatten(input_shape = c(28,28,1)) %>% 
  layer_dense(512, activation = "relu") %>% 
  layer_dense(10, activation = "softmax")

model %>% 
  compile(
    loss = "sparse_categorical_crossentropy", 
    optimizer = "adam", 
    metric = "accuracy"
  )

train_dataset <- mnist$train %>% 
  dataset_shuffle(1024) %>% 
  dataset_batch(32) %>% 
  dataset_map(unname)

test_dataset <- mnist$test %>% 
  dataset_batch(32) %>% 
  dataset_map(unname)

model %>% 
  fit(train_dataset, validation_data = test_dataset, epochs = 5)

rstudio/tfds documentation built on Nov. 25, 2021, 6:20 p.m.