digitalDLSorteR is based on Deep Neural Network
(DNN) models. To use them, keras package
(available on CRAN), a high-level neural networks API implemented in
Python, is used. keras R package
works as an interface between these two languages by using the reticulate
package. Therefore, keras requires a
Python interpreter to work. We recommend using conda environments to
provide a Python interpreter with all its dependencies covered. If you
already have a conda environment compatible with keras requirements,
the package is supposed to find it automatically during the
installation. Otherwise, keras will create a
new environment called r-reticulate with all these
dependencies covered. There are other ways to install a functionally
back-end and customized installations are possible, see https://keras3.posit.co/articles/getting_started.html
and https://tensorflow.rstudio.com/installation/ for more
details.
In addition, digitalDLSorteR provides the
installTFpython function, a helper function to install
miniconda (if needed) and create a conda environment called
digitaldlsorter-env with all dependencies covered (a Python
interpreter with tensorflow = v2.6). We recommend using
installTFpython to install TensorFlow Python library.
installTFpython(install.conda = TRUE)If you experiment errors related to its installation and/or keras is not able to find a functional Python environment, you can manually install the conda environment by following these steps:
First, in case you don’t have miniconda installed, use the following R code using reticulate:
reticulate::install_miniconda()
reticulate::conda_create(
envname = "digitaldlsorter-env",
packages = "python==3.7.11"
)Or type in a Terminal:
Then, instead of using keras::install_keras() function,
run the following code chunk using the tensorflow R
package. This code will create a Python interpreter with tensorflow with
all its dependencies covered.
tensorflow::install_tensorflow(
method = "conda",
conda = reticulate::conda_binary("auto"),
envname = "digitaldlsorter-env",
version = "2.6.0-cpu"
)Finally, although it is automatically done by digitalDLSorteR, if keras still does not recognize the functional environment, set this new environment as the selected Python environment:
tensorflow::use_condaenv("digitaldlsorter-env")If the Python-interpreter problems do not disappear, it is possible to set manually the interpreter that will be used with reticulate. See the following guide: https://rstudio.github.io/reticulate/articles/versions.html.