feat: add nn convenience function

DESCRIPTION

@@ -128,6 +128,7 @@ Collate:
     'learner_torch_methods.R'
     'materialize.R'
     'merge_graphs.R'
+    'nn.R'
     'nn_graph.R'
     'paramset_torchlearner.R'
     'preprocess.R'

NAMESPACE

@@ -162,6 +162,7 @@ export(mlr3torch_optimizers)
 export(model_descriptor_to_learner)
 export(model_descriptor_to_module)
 export(model_descriptor_union)
+export(nn)
 export(nn_graph)
 export(nn_merge_cat)
 export(nn_merge_prod)

R/nn.R

@@ -0,0 +1,13 @@
+#' @title Create a Neural Network Layer
+#' @description
+#' Retrieve a neural network layer from the
+#' [`mlr_pipeops`][mlr3pipelines::mlr_pipeops] dictionary.
+#' @param .key (`character(1)`)\cr
+#' @export
+#' @examples
+#' po1 = po("nn_linear", id = "linear")
+#' # is the same as:
+#' po2 = nn("linear")
+nn = function(.key, ...) {
+  invoke(po, .obj = paste0("nn_", .key), .args = insert_named(list(id = .key), list(...)))
+}

tests/testthat/test_nn.R

@@ -1,3 +1,6 @@
 test_that("nn works", {
-
+  x = nn("linear", out_features = 3)
+  expect_equal(x$id, "linear")
+  expect_class(x, "PipeOpTorchLinear")
+  expect_equal(x$param_set$values$out_features, 3)
 })