UPDATE 0.0.6

R/utils.R

@@ -88,59 +88,28 @@ show_flair_cache <- function() {
   }
 }
 
-#'
-#' #' @title Create or Use Python environment for Flair
-#' #'
-#' #' @description
-#' #' This function checks whether the Flair Python library is installed in the
-#' #' current Python environment. If it is not, it attempts to install it either
-#' #' in the current conda environment or creates a new one.
-#' #'
-#' #' @param env The name of the conda environment to be used or
-#' #' created (default is "r-reticulate").
-#' #'
-#' #' @return Nothing is returned. The function primarily ensures that the Python
-#' #' library Flair is installed and available.
-#' #' @export
-#' #' @importFrom reticulate import py_config use_condaenv
-#' #' @importFrom rstudioapi restartSession
-#' create_flair_env <- function(env = "r-reticulate") {
-#'   # check if flair is already installed in the current Python environment
-#'   if (reticulate::py_module_available("flair")) {
-#'     message("Environment creation stopped.", "\n", "Flair is already installed in ", reticulate::py_config()$python)
-#'     message(sprintf("Using Flair:  %-48s", reticulate::import("flair")$`__version__`))
-#'     return(invisible(NULL))
-#'   }
-#'   paths <- reticulate::conda_list()
-#'   env_path <- paths[grep("envs/", paths$python), "python"][1]
-#'   if (grepl("envs/", env_path)) {
-#'     message("you already created:", length(paths[grep("envs/", paths$python), "python"]))
-#'     message("you can run use_condaenv(",as.character(env_path),") to activate the enviroment in your R." )
-#'     reticulate::use_condaenv(env)
-#'   } else {
-#'     # No conda environment found or active, so create one
-#'     reticulate::conda_create(env)
-#'     message("No conda environment found. Creating a new environment named '", env, "'. ", "After restarting the R session, please run create_flair_env() again.")
-#'     rstudioapi::restartSession()
-#'   }
-#' }
-#'
-
 #' @title Check the Device for Accelerating PyTorch
 #'
 #' @description This function verifies if the specified device is available for PyTorch.
 #' If CUDA is not available, a message is shown. Additionally, if the system
-#' is running on a Mac M1, MPS will be used instead of CUDA.
+#' is running on a Mac M1, MPS will be used instead of CUDA. Checks if the specified device is compatible with the current system's
+#' hardware and operating system configuration, particularly for Mac systems
+#' with Apple M1/M2 silicon using Metal Performance Shaders (MPS).
+#'
+#' @details
+#' If MPS is available and the system meets the requirements, a device of type
+#' MPS will be returned. Otherwise, a CPU device will be used. The requirements
+#' for using MPS are as follows:\\cr
+#' - Mac computers with Apple silicon or AMD GPUs\\cr
+#' - macOS 12.3 or later\\cr
+#' - Python 3.7 or later\\cr
+#' - Xcode command-line tools installed (`xcode-select --install`)\\cr
+#' More information at: \url{https://developer.apple.com/metal/pytorch/}.
+#'
+#' @param device A character string specifying the device type.
 #'
-#' @note Flair NLP operates under the [PyTorch](https://pytorch.org) framework.
-#' As such, we can use the `$to` method to set the device for the Flair Python
-#' library. `flair_device("cpu")`  allows you to select whether to use the CPU,
-#' CUDA devices (like cuda:0, cuda:1, cuda:2), or specific MPS devices on Mac
-#' (such as mps:0, mps:1, mps:2). For information on Accelerated PyTorch
-#' training on Mac, please refer to https://developer.apple.com/metal/pytorch/.
-#' For more about CUDA, please visit: https://developer.nvidia.com/cuda-zone.
+#' @return A PyTorch device object.
 #'
-#' @param device Character. The device to be set for PyTorch.
 #' @importFrom reticulate import
 #' @keywords internal
 check_device <- function(device) {

_pkgdown.yml

@@ -91,7 +91,6 @@ reference:
   - map_entities
   - embeddings_to_matrix
   - clear_flair_cache
-  - create_flair_env
   - show_flair_cache