This function will install Tensorflow and all Keras dependencies. This is a thin wrapper around tensorflow::install_tensorflow(), with the only difference being that this includes by default additional extra packages that keras expects, and the default version of tensorflow installed by install_keras() may at times be different from the default installed install_tensorflow(). The default version of tensorflow installed by install_keras() is "2.8".

  method = c("auto", "virtualenv", "conda"),
  conda = "auto",
  version = "default",
  tensorflow = version,
  extra_packages = NULL,
  pip_ignore_installed = TRUE



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 and conda_binary() for more details.


TensorFlow version to install. Valid values include:

  • "default" installs 2.8

  • "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.


Synonym for version. Maintained for backwards.


Additional Python packages to install along with TensorFlow.


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 default additional packages are: tensorflow-hub, scipy, requests, pyyaml, Pillow, h5py, pandas, pydot, with their versions potentially constrained for compatibility with the requested tensorflow version.