install_tensorflow() installs just the tensorflow python package and it's
direct dependencies. For a more complete installation that includes
additional optional dependencies, use keras::install_keras().
install_tensorflow(
method = c("auto", "virtualenv", "conda"),
conda = "auto",
version = "default",
envname = NULL,
extra_packages = NULL,
restart_session = TRUE,
conda_python_version = "3.7",
...,
pip_ignore_installed = TRUE,
python_version = conda_python_version
)Installation method. By default, "auto" automatically finds a method that will work in the local environment. Change the default to force a specific installation method. Note that the "virtualenv" method is not available on Windows.
The path to a conda executable. Use "auto" to allow
reticulate to automatically find an appropriate conda binary. See
Finding Conda for more details.
TensorFlow version to install. Valid values include:
"default" installs 2.7
"release" installs the latest release version of tensorflow (which may
be incompatible with the current version of the R package)
A version specification like "2.4" or "2.4.0". Note that if the patch
version is not supplied, the latest patch release is installed (e.g.,
"2.4" today installs version "2.4.2")
nightly for the latest available nightly build.
To any specification, you can append "-cpu" to install the cpu version
only of the package (e.g., "2.4-cpu")
The full URL or path to a installer binary or python *.whl file.
The name, or full path, of the environment in which Python
packages are to be installed. When NULL (the default), the active
environment as set by the RETICULATE_PYTHON_ENV variable will be used;
if that is unset, then the r-reticulate environment will be used.
Additional Python packages to install along with TensorFlow.
Restart R session after installing (note this will only occur within RStudio).
other arguments passed to reticulate::conda_install() or
reticulate::virtualenv_install(), depending on the method used.
Whether pip should ignore installed python
packages and reinstall all already installed python packages. This defaults
to TRUE, to ensure that TensorFlow dependencies like NumPy are compatible
with the prebuilt TensorFlow binaries.
the python version installed in the created conda environment. Ignored when attempting to install with a Python virtual environment.
install_tensorflow() or
keras::install_keras() isn't required to use tensorflow with the package.
If you manually configure a python environment with the required
dependencies, you can tell R to use it by pointing reticulate at it,
commonly by setting an environment variable:
Sys.setenv("RETICULATE_PYTHON" = "~/path/to/python-env/bin/python")
Tensorflow on Apple Silicon is not officially
supported by the tensorflow maintainers. It is known that there can be
issues running the official Tensorflow package under Rosetta as well.
Fortunately, for the time being Apple has published a custom version of
Tensorflow compatible with M1 macs. Installation instructions can be found
at: https://developer.apple.com/metal/tensorflow-plugin/. Please note
that this is an experimental build of both python and tensorflow. After
following the instructions provided by Apple, you can advise reticulate to
use that python installation by placing the following in your .Renviron
file:
RETICULATE_PYTHON = "~/miniforge3/bin/python"
If you wish to add additional PyPI packages to your Keras / TensorFlow
environment you can either specify the packages in the extra_packages
argument of install_tensorflow() or install_keras(), or alternatively
install them into an existing environment using the
reticulate::py_install() function. Note that install_keras() includes a
set of additional python packages by default, see ?keras::install_keras
for details.
You may be prompted you if you want it to download and install miniconda if reticulate did not find a non-system installation of python. Miniconda is the recommended installation method for most users, as it ensures that the R python installation is isolated from other python installations. All python packages will by default be installed into a self-contained conda or venv environment named "r-reticulate". Note that "conda" is the only supported method on Windows.
If you initially declined the miniconda installation prompt, you can later
manually install miniconda by running reticulate::install_miniconda().