R/install_autokeras.R

In autokeras: R Interface to 'AutoKeras'

#' Install Autokeras, Keras, and the Tensorflow Backend
#'
#' AutoKeras, Keras, and TensorFlow will be installed into an "r-tensorflow"
#' virtual or conda environment. Note that "virtualenv" is not available on
#' Windows (as this isn't supported by TensorFlow).
#'
#' @inheritParams keras::install_keras
#'
#' @param version Version of AutoKeras to install. Specify "default" to install
#'   the latest release. Otherwise specify an alternate version (e.g. "0.3.5").
#'   The default value is "1.0.12" as it is the latest tested version.
#'
#' @param keras Keras version to install. Specify "default" to install
#'   the latest release. Otherwise specify an alternate version (e.g. "2.2.2").
#'
#' @return None
#'
#' @section GPU Installation:
#'
#' Keras and TensorFlow can be configured to run on either CPUs or GPUs. The CPU
#' version is much easier to install and configure so is the best starting place
#' especially when you are first learning how to use Keras. Here's the guidance
#' on CPU vs. GPU versions from the TensorFlow website:
#'
#' - *TensorFlow with CPU support only*. If your system does not have a NVIDIA®
#' GPU, you must install this version. Note that this version of TensorFlow is
#' typically much easier to install, so even if you have an NVIDIA GPU, we
#' recommend installing this version first.
#'
#' - *TensorFlow with GPU support*. TensorFlow programs typically run
#' significantly faster on a GPU than on a CPU. Therefore, if your system has a
#' NVIDIA® GPU meeting all prerequisites and you need to run
#' performance-critical applications, you should ultimately install this
#' version.
#'
#' To install the GPU version:
#'
#' 1) Ensure that you have met all installation prerequisites including
#'    installation of the CUDA and cuDNN libraries as described in
#'    [TensorFlow GPU Prerequistes](https://tensorflow.rstudio.com/installation_gpu.html#prerequisites).
#'
#' 2) Pass `tensorflow = "gpu"` to `install_autokeras()`. For example:
#'
#'     ```
#'       install_autokeras(tensorflow="gpu")
#'     ````
#'
#' @section Windows Installation:
#'
#' The only supported installation method on Windows is "conda". This means that
#' you should install Anaconda 3.x for Windows prior to installing Keras.
#'
#' @section Custom Installation:
#'
#' Installing Keras and TensorFlow using `install_autokeras()` isn't required
#' to use the Keras R package. You can do a custom installation of Keras (and
#' desired backend) as described on the
#' [Keras website](https://keras.io/#installation) and the Keras R package will
#' find and use that version.
#'
#' See the documentation on [custom installations](https://tensorflow.rstudio.com/installation.html#custom-installation)
#' for additional information on how version of Keras and TensorFlow are located
#' by the Keras package.
#'
#' @section Additional Packages:
#'
#' 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_autokeras()`,  or alternatively install them into an
#' existing environment using the [reticulate::py_install()] function.
#'
#' @examples
#' \dontrun{
#'
#' # default installation
#' library("autokeras")
#' install_autokeras()
#'
#' # install using a conda environment (default is virtualenv)
#' install_autokeras(method = "conda")
#'
#' # install with GPU version of TensorFlow
#' # (NOTE: only do this if you have an NVIDIA GPU + CUDA!)
#' install_autokeras(tensorflow = "gpu")
#'
#' # install a specific version of TensorFlow
#' install_autokeras(tensorflow = "1.2.1")
#' install_autokeras(tensorflow = "1.2.1-gpu")
#'
#' # install a specific version of Keras and TensorFlow
#' install_autokeras(keras = "2.2.2", tensorflow = "1.2.1")
#' }
#'
#' @importFrom keras install_keras
# @importFrom reticulate py_discover_config
#'
#' @export
install_autokeras <- function(
                              method = c("auto", "virtualenv", "conda"),
                              conda = "auto",
                              version = "1.0.12",
                              keras = "default",
                              tensorflow = "2.3.0",
                              extra_packages = NULL,
                              ...) {

  # resolve version
  autokeras_pkg <- version
  # if it is a git version then continue
  if (!startsWith(version, "git+")) {
    if (identical(version, "default")) {
      version <- ""
    } else {
      version <- paste0("==", version)
    }
    autokeras_pkg <- paste0("autokeras", version)
  }

  # perform the install
  install_keras(
    method = method,
    conda = conda,
    version = keras,
    tensorflow = tensorflow,
    extra_packages = c(autokeras_pkg, extra_packages),
    ...
  )
}