R/package.R

In tfestimators: Interface to 'TensorFlow' Estimators

#' High-level Estimator API in TensorFlow for R
#'
#' This library provides an R interface to the
#' \href{https://github.com/tensorflow/tensorflow/tree/r1.15/tensorflow/python/estimator}{Estimator}
#' API inside TensorFlow that's designed to streamline the process of creating,
#' evaluating, and deploying general machine learning and deep learning models.
#'
#' \href{https://www.tensorflow.org}{TensorFlow} is an open source software library
#' for numerical computation using data flow graphs. Nodes in the graph
#' represent mathematical operations, while the graph edges represent the
#' multidimensional data arrays (tensors) communicated between them. The
#' flexible architecture allows you to deploy computation to one or more CPUs or
#' GPUs in a desktop, server, or mobile device with a single API.
#'
#' The \href{https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/all_symbols}{TensorFlow
#' API} is composed of a set of Python modules that enable constructing and
#' executing TensorFlow graphs. The tensorflow package provides access to the
#' complete TensorFlow API from within R.
#'
#' For additional documentation on the tensorflow package see
#' \href{https://tensorflow.rstudio.com}{https://tensorflow.rstudio.com}
#'
#' @name tfestimators
"_PACKAGE"

estimator_lib <- NULL
feature_column_lib <- NULL
canned_estimator_lib <- NULL

np <- NULL

.globals <- new.env(parent = emptyenv())
.globals$active_column_names <- NULL
.globals$history <- NULL

.onLoad <- function(libname, pkgname) {

  # delay load handler
  displayed_warning <- FALSE
  delay_load <- list(

    priority = 5,

    environment = "r-tensorflow",

    on_load = function() {
      check_tensorflow_version(displayed_warning)
    },

    on_error = function(e) {
      emit <- base::message
      emit(
'To use legacy tfestimators, create a virtual environment with legacy TensorFlow:
  reticulate::install_python("3.7")
  tensorflow::install_tensorflow(
     version = "<2", python_version = "<3.8",
     extra_packages = "protobuf<3.21")'
      )
      stop(tf_config()$error_message, call. = FALSE)
    }
  )


  # core modules
  if (package_version(Sys.getenv("TENSORFLOW_VERSION", "1.15")) <= "1.12") {
    estimator_lib <<- import("tensorflow.python.estimator.estimator", delay_load = delay_load)
    feature_column_lib <<- import("tensorflow.python.feature_column.feature_column", delay_load = delay_load)
    canned_estimator_lib <<- import("tensorflow.python.estimator.canned", delay_load = delay_load)
  } else {
    estimator_lib <<- import("tensorflow_estimator.python.estimator.estimator", delay_load = delay_load)
    feature_column_lib <<- import("tensorflow.python.feature_column.feature_column_v2", delay_load = delay_load)
    canned_estimator_lib <<- import("tensorflow_estimator.python.estimator.canned", delay_load = delay_load)
  }

  # other modules
  np <<- import("numpy", convert = FALSE, delay_load = TRUE)
}

check_tensorflow_version <- function(displayed_warning) {
  current_tf_ver <- tf_version()
  required_least_ver <- "1.3"
  if (current_tf_ver < required_least_ver) {
    if (!displayed_warning) {
      message("tfestimators requires TensorFlow version >= ", required_least_ver, " ",
              "(you are currently running version ", current_tf_ver, ").\n")
      displayed_warning <<- TRUE
    }
  }
}

.onUnload <- function(libpath) {

}

.onAttach <- function(libname, pkgname) {
  msg <- "tfestimators is not recomended for new code. It is only compatible with Tensorflow version 1, and is not compatable with Tensorflow version 2."
  packageStartupMessage(msg)
}

.onDetach <- function(libpath) {

}