How to predict values using random forest model and multidplyr packages in parallel processing mode?

Question

multidplyr package not parallelizing prediction process for random forest model

It runs when not processed parallely. here [["finalModel"]] is output from caret package using randomForest R package.

pred_dat <- dat_met_morph  %>% 
  predict(rf_model[["finalModel"]],.) %>%
  data.frame()

but not running when ran with multidplyr package

cluster <- new_cluster(15)
dat_met_morph <- dat_met_morph_df %>% partition(cluster)
cluster_library(cluster, "randomForest")
cluster_library(cluster, "caret")
cluster_copy(cluster, "rf_model")

pred_dat <- dat_met_morph  %>% 
  predict(rf_model[["finalModel"]],.) %>%
  data.frame()

Showing error Error in predict.randomForest(rf_model[["finalModel"]], .) : 'list' object cannot be coerced to type 'double'