install_misle: Install the TensorFlow backend (modified code from Keras)

In agnesdeng/misle: Multiple imputation through statistical learning

Install the TensorFlow backend (modified code from Keras)

Description

TensorFlow will be installed in to an "r-tensorflow" virtual or conda environment. Note: "virtualenv" is not avilable on Windows

Usage

install_misle(
  method = c("auto", "virtualenv", "conda"),
  conda = "auto",
  version = "default",
  tensorflow = "default",
  extra_packages = c("tensorflow-hub"),
  ...
)

Arguments

method	Installation method ("virtualenv" or "conda")
conda	The path to a conda executable. Use "auto" to allow reticulate to automatically find an appropriate conda binary. See Finding Conda for more details.
version	TensorFlow version to install. Up to and including TensorFlow 2.0, specify "default" to install the CPU version of the latest release; specify "gpu" to install the GPU version of the latest release. Starting from TensorFlow 2.1, by default a version is installed that works on both GPU- and CPU-only systems. Specify "cpu" to install a CPU-only version. You can also provide a full major.minor.patch specification (e.g. "1.1.0"), appending "-gpu" if you want the GPU version (e.g. "1.1.0-gpu"). Alternatively, you can provide the full URL to an installer binary (e.g. for a nightly binary).
tensorflow	TensorFlow version to install. Specify "default" to install the CPU version of the latest release. Specify "gpu" to install the GPU version of the latest release.
extra_packages	Additional PyPI packages to install along with Keras and TensorFlow.
...	Other arguments passed to [tensorflow::install_tensorflow()].
conda_python_version	the python version installed in the created conda environment. Python 3.6 is installed by default.

GPU Installation

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 misle.

- *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_misle()'. For example:

“' install_misle(tensorflow = "gpu") ““

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.

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_misle()', or alternatively install them into an existing environment using the [reticulate::py_install()] function.

Examples

## Not run: 

# default installation
library(misle)
install_misle()

# install using a conda environment (default is virtualenv)
install_misle(method = "conda")

# install with GPU version of TensorFlow
# (NOTE: only do this if you have an NVIDIA GPU + CUDA!)
install_misle(tensorflow = "gpu")

# install a specific version of TensorFlow
install_misle(tensorflow = "1.2.1")
install_misle(tensorflow = "1.2.1-gpu")


## End(Not run)

agnesdeng/misle documentation built on Sept. 22, 2023, 8:48 p.m.