more input validations using hardhat (#166)

Signed-off-by: Yitao Li <[email protected]>
mlverse · Oct 25, 2021 · 5e93751 · 5e93751
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commit 5e93751
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diff --git a/R/knn.R b/R/knn.R
@@ -277,6 +277,7 @@ cuda_ml_knn.recipe <- function(x, data,
 }
 
 cuda_ml_knn_bridge <- function(processed, algo, metric, p, neighbors) {
+  hardhat::validate_predictors_are_numeric(processed$predictors)
   hardhat::validate_outcomes_are_univariate(processed$outcomes)
   x <- as.matrix(processed$predictors)
   y <- processed$outcomes[[1]]

diff --git a/R/rand_forest.R b/R/rand_forest.R
@@ -209,6 +209,7 @@ cuda_ml_rand_forest_bridge <- function(processed, mtry, trees, min_n, bootstrap,
                                        min_samples_leaf, split_criterion,
                                        min_impurity_decrease, max_batch_size,
                                        n_streams, cuML_log_level) {
+  hardhat::validate_predictors_are_numeric(processed$predictors)
   hardhat::validate_outcomes_are_univariate(processed$outcomes)
   x <- as.matrix(processed$predictors)
   y <- processed$outcomes[[1]]

diff --git a/R/svm.R b/R/svm.R
@@ -217,6 +217,7 @@ cuda_ml_svm.recipe <- function(x, data, cost = 1,
 cuda_ml_svm_bridge <- function(processed, cost, kernel, gamma, coef0, degree, tol,
                                max_iter, nochange_steps, cache_size, epsilon,
                                sample_weights, cuML_log_level) {
+  hardhat::validate_predictors_are_numeric(processed$predictors)
   hardhat::validate_outcomes_are_univariate(processed$outcomes)
   x <- as.matrix(processed$predictors)
   y <- processed$outcomes[[1]]