add is_cran_check()

Author: EmilHvitfeldt

R/aaa.R

@@ -12,4 +12,13 @@ utils::globalVariables(
   )
 )
 
+# adapted from ps:::is_cran_check()
+is_cran_check <- function() {
+  if (identical(Sys.getenv("NOT_CRAN"), "true")) {
+    FALSE
+  }
+  else {
+    Sys.getenv("_R_CHECK_PACKAGE_NAME_", "") != ""
+  }
+}
 # nocov end

R/embed.R

@@ -122,7 +122,7 @@
 #' "Concatenate Embeddings for Categorical Variables with Keras"
 #' \url{https://flovv.github.io/Embeddings_with_keras_part2/}
 #'
-#' @examplesIf embed:::is_tf_available() && rlang::is_installed("modeldata")
+#' @examplesIf !embed:::is_cran_check() && rlang::is_installed("modeldata")
 #' data(grants, package = "modeldata")
 #'
 #' set.seed(1)
@@ -150,7 +150,7 @@ step_embed <-
            skip = FALSE,
            id = rand_id("embed")) {
     # warm start for tf to avoid a bug in tensorflow
-    embed:::is_tf_available()
+    is_tf_available()
 
     if (is.null(outcome)) {
       rlang::abort("Please list a variable in `outcome`")
@@ -254,7 +254,7 @@ prep.step_embed <- function(x, training, info = NULL, ...) {
 }
 
 is_tf_2 <- function() {
-  if (!embed:::is_tf_available()) {
+  if (!is_tf_available()) {
     rlang::abort(
       c(
         "tensorflow could now be found.",

R/feature_hash.R

@@ -50,7 +50,7 @@
 #' Approach for Predictive Models_. CRC/Chapman Hall
 #' \url{https://bookdown.org/max/FES/encoding-predictors-with-many-categories.html}
 #' @seealso [recipes::step_dummy()], [recipes::step_zv()]
-#' @examplesIf embed:::is_tf_available() && rlang::is_installed("modeldata")
+#' @examplesIf !embed:::is_cran_check() && rlang::is_installed("modeldata")
 #' data(grants, package = "modeldata")
 #' rec <-
 #'   recipe(class ~ sponsor_code, data = grants_other) %>%
@@ -94,7 +94,7 @@ step_feature_hash <-
     }
 
     # warm start for tf to avoid a bug in tensorflow
-    embed:::is_tf_available()
+    is_tf_available()
 
     add_step(
       recipe,