print.md
In parsnip: A Common API to Modeling and Analysis Functions

model spec print methods work (whole game)

Code
  svm_poly()
Output
  Polynomial Support Vector Machine Model Specification (unknown mode)

  Computational engine: kernlab

Code
  boost_tree(mtry = 5)
Output
  Boosted Tree Model Specification (unknown mode)

  Main Arguments:
    mtry = 5

  Computational engine: xgboost

Code
  set_mode(rand_forest(), "regression")
Output
  Random Forest Model Specification (regression)

  Computational engine: ranger

Code
  set_engine(logistic_reg(), "glmnet", penalty = 0.5)
Output
  Logistic Regression Model Specification (classification)

  Engine-Specific Arguments:
    penalty = 0.5

  Computational engine: glmnet

Code
  translate(set_mode(mlp(), "classification"))
Output
  Single Layer Neural Network Model Specification (classification)

  Main Arguments:
    hidden_units = 5

  Computational engine: nnet

  Model fit template:
  nnet::nnet(formula = missing_arg(), data = missing_arg(), size = 5, 
      trace = FALSE, linout = FALSE)

`print_model_spec()` handles args correctly

Code
  print_model_spec(linear_reg())
Output
  Linear Regression Model Specification (regression)

  Computational engine: lm

Code
  print_model_spec(lr)
Message
  ! parsnip could not locate an implementation for `beep` model specifications.
Output
  beep Model Specification (regression)

  Computational engine: lm

Code
  print_model_spec(lr, cls = "boop")
Message
  ! parsnip could not locate an implementation for `boop` model specifications.
Output
  boop Model Specification (regression)

  Computational engine: lm

Code
  print_model_spec(lr, cls = "boop", desc = "Boop")
Message
  ! parsnip could not locate an implementation for `boop` model specifications.
Output
  Boop Model Specification (regression)

  Computational engine: lm