R/load.R

In tfhub: Interface to 'TensorFlow' Hub

#' Hub Load
#'
#' Loads a module from a handle.
#'
#' Currently this method is fully supported only with Tensorflow 2.x and with
#' modules created by calling `export_savedmodel`. The method works in
#' both eager and graph modes.
#'
#' Depending on the type of handle used, the call may involve downloading a
#' TensorFlow Hub module to a local cache location specified by the
#' `TFHUB_CACHE_DIR` environment variable. If a copy of the module is already
#' present in the TFHUB_CACHE_DIR, the download step is skipped.
#'
#' Currently, three types of module handles are supported: 1) Smart URL resolvers
#' such as tfhub.dev, e.g.: https://tfhub.dev/google/nnlm-en-dim128/1. 2) A directory
#' on a file system supported by Tensorflow containing module files. This may include
#' a local directory (e.g. /usr/local/mymodule) or a Google Cloud Storage bucket
#' (gs://mymodule). 3) A URL pointing to a TGZ archive of a module, e.g.
#' https://example.com/mymodule.tar.gz.
#'
#' @param handle (string) the Module handle to resolve.
#' @param tags A set of strings specifying the graph variant to use, if loading
#'   from a v1 module.
#'
#' @examples
#'
#' \dontrun{
#'
#' model <- hub_load('https://tfhub.dev/google/tf2-preview/mobilenet_v2/feature_vector/4')
#'
#' }
#'
#' @export
hub_load <- function(handle, tags = NULL) {
  tfhub$load(handle, tags)
}