knitr::opts_chunk$set(eval = FALSE)
This is the R interface to datasets and filesystem extensions maintained by SIG-IO. Some example data sources that TensorFlow I/O supports are:
We provide a reference Dockerfile here for you so that you can use the R package directly for testing. You can build it via:
docker build -t tfio-r-dev -f R-package/scripts/Dockerfile .
Inside the container, you can start your R session, instantiate a SequenceFileDataset
from an example Hadoop SequenceFile
string.seq, and then use any transformation functions provided by tfdatasets package on the dataset like the following:
library(tfio) dataset <- sequence_file_dataset("R-package/tests/testthat/testdata/string.seq") %>% dataset_repeat(2) sess <- tf$Session() iterator <- make_iterator_one_shot(dataset) next_batch <- iterator_get_next(iterator) until_out_of_range({ batch <- sess$run(next_batch) print(batch) })
You'll see the key-value pairs from string.seq
file are printed as follows:
[1] "001" "VALUE001" [1] "002" "VALUE002" [1] "003" "VALUE003" [1] "004" "VALUE004" [1] "005" "VALUE005" [1] "006" "VALUE006" [1] "007" "VALUE007" [1] "008" "VALUE008" ... [1] "020" "VALUE020" [1] "021" "VALUE021" [1] "022" "VALUE022" [1] "023" "VALUE023" [1] "024" "VALUE024" [1] "025" "VALUE025"
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