deal with CRAN incoming notes

AshesITR · Oct 18, 2023 · aa6243c · aa6243c
1 parent 6d349f4
commit aa6243c
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Showing 15 changed files with 16 additions and 20 deletions.
diff --git a/R/callback_adaptive_lr.R b/R/callback_adaptive_lr.R
@@ -34,7 +34,7 @@
 #' x <- dist$sample(100, with_params = list(rate = group + 1))
 #' global_fit <- fit(dist, x)
 #'
-#' if (keras::is_keras_available()) {
+#' if (interactive() && keras::is_keras_available()) {
 #'   library(keras)
 #'   l_in <- layer_input(shape = 1L)
 #'   mod <- tf_compile_model(

diff --git a/R/callback_debug_dist_gradients.R b/R/callback_debug_dist_gradients.R
@@ -21,7 +21,7 @@
 #' x <- dist$sample(100, with_params = list(rate = group + 1))
 #' global_fit <- fit(dist, x)
 #'
-#' if (keras::is_keras_available()) {
+#' if (interactive() && keras::is_keras_available()) {
 #'   library(keras)
 #'   l_in <- layer_input(shape = 1L)
 #'   mod <- tf_compile_model(

diff --git a/R/integrate.R b/R/integrate.R
@@ -53,9 +53,7 @@ GK_QUAD <- list(
 #' `15 * .max_iter`.
 #'
 #' @return A vector of integrals with the i-th entry containing an approximation
-#' of
-#'
-#' int_{lower\[i\]}^{upper\[i\]} fun(t, pick_params_at(params, i)) dt
+#' of the integral of fun(t, pick_params_at(params, i)) dt over the interval lower\[i\] to upper\[i\]
 #'
 #' @examples
 #' # Argument recycling and parallel integration of two intervals

diff --git a/R/tf_compile.R b/R/tf_compile.R
@@ -23,7 +23,7 @@
 #' rand_input <- runif(N)
 #' x <- dist$sample(N, with_params = params)
 #'
-#' if (keras::is_keras_available()) {
+#' if (interactive() && keras::is_keras_available()) {
 #'   tf_in <- keras::layer_input(1L)
 #'   mod <- tf_compile_model(
 #'     inputs = list(tf_in),

diff --git a/R/tf_fit.R b/R/tf_fit.R
@@ -9,7 +9,7 @@
 #' Contains one set of parameters per row in `data`.
 #'
 #' @examples
-#' if (keras::is_keras_available()) {
+#' if (interactive() && keras::is_keras_available()) {
 #'   dist <- dist_exponential()
 #'   params <- list(rate = 1.0)
 #'   N <- 100L
@@ -88,7 +88,7 @@ generics::fit
 #' rand_input <- runif(N)
 #' x <- dist$sample(N, with_params = params)
 #'
-#' if (keras::is_keras_available()) {
+#' if (interactive() && keras::is_keras_available()) {
 #'   tf_in <- keras::layer_input(1L)
 #'   mod <- tf_compile_model(
 #'     inputs = list(tf_in),

diff --git a/R/tf_initialise.R b/R/tf_initialise.R
@@ -22,7 +22,7 @@
 #' x <- dist$sample(100, with_params = list(rate = group + 1))
 #' global_fit <- fit(dist, x)
 #'
-#' if (keras::is_keras_available()) {
+#' if (interactive() && keras::is_keras_available()) {
 #'   library(keras)
 #'   l_in <- layer_input(shape = 1L)
 #'   mod <- tf_compile_model(

diff --git a/R/tf_util.R b/R/tf_util.R
@@ -54,7 +54,7 @@ as_params <- function(x) {
 #' The shape will be `(nrow(x), ncol(x))` where `x` is first converted to an R matrix via [as.matrix()].
 #'
 #' @examples
-#' if (keras::is_keras_available()) {
+#' if (interactive() && keras::is_keras_available()) {
 #'   k_matrix(diag(1:3))
 #'   k_matrix(diag(1:3), dtype = "int32")
 #'   # Vectors are converted to columns:

diff --git a/man/callback_adaptive_lr.Rd b/man/callback_adaptive_lr.Rd
diff --git a/man/callback_debug_dist_gradients.Rd b/man/callback_debug_dist_gradients.Rd
diff --git a/man/fit.reservr_keras_model.Rd b/man/fit.reservr_keras_model.Rd
diff --git a/man/integrate_gk.Rd b/man/integrate_gk.Rd
diff --git a/man/k_matrix.Rd b/man/k_matrix.Rd
diff --git a/man/predict.reservr_keras_model.Rd b/man/predict.reservr_keras_model.Rd
diff --git a/man/tf_compile_model.Rd b/man/tf_compile_model.Rd
diff --git a/man/tf_initialise_model.Rd b/man/tf_initialise_model.Rd