Adding tests for new functions

Author: davidrsch

tests/testthat/test_compile_keras_grid.R

@@ -0,0 +1,155 @@
+# --- Test Data ---
+x_train <- as.matrix(iris[, 1:4])
+y_train <- iris$Species
+# --- Tests ---
+
+test_that("compile_keras_grid works for sequential models", {
+  skip_on_cran()
+
+  model_name <- "test_seq_spec_compile"
+  on.exit(suppressMessages(remove_keras_spec(model_name)), add = TRUE)
+
+  create_keras_sequential_spec(
+    model_name = model_name,
+    mode = "classification",
+    layer_blocks = list(
+      dense = function(model, units = 32, activation = "relu") {
+        if (is.null(model)) {
+          keras3::keras_model_sequential(input_shape = 4) |>
+            keras3::layer_dense(units = units, activation = activation)
+        } else {
+          model |> keras3::layer_dense(units = units, activation = activation)
+        }
+      },
+      output = function(model, num_classes) {
+        model |>
+          keras3::layer_dense(units = num_classes, activation = "softmax")
+      }
+    )
+  )
+
+  spec <- test_seq_spec_compile() |>
+    set_engine("keras")
+
+  grid <- tibble::tibble(
+    dense_units = c(16, 32),
+    learn_rate = c(0.01, 0.001)
+  )
+
+  results <- compile_keras_grid(spec, grid, x_train, y_train)
+
+  expect_s3_class(results, "tbl_df")
+  expect_equal(nrow(results), 2)
+  expect_true(all(
+    c(
+      "dense_units",
+      "learn_rate",
+      "compiled_model",
+      "model_summary",
+      "error"
+    ) %in%
+      names(results)
+  ))
+  expect_true(all(is.na(results$error)))
+  expect_true(all(sapply(
+    results$compiled_model,
+    inherits,
+    "keras.src.models.model.Model"
+  )))
+})
+
+test_that("compile_keras_grid works for functional models", {
+  skip_on_cran()
+
+  model_name <- "test_func_spec_compile"
+  on.exit(suppressMessages(remove_keras_spec(model_name)), add = TRUE)
+
+  create_keras_functional_spec(
+    model_name = model_name,
+    mode = "classification",
+    layer_blocks = list(
+      input = function(input_shape) {
+        keras3::layer_input(shape = input_shape)
+      },
+      dense = function(input, units = 32) {
+        input |> keras3::layer_dense(units = units, activation = "relu")
+      },
+      output = function(dense, num_classes) {
+        dense |>
+          keras3::layer_dense(units = num_classes, activation = "softmax")
+      }
+    )
+  )
+
+  spec <- test_func_spec_compile() |>
+    set_engine("keras")
+
+  grid <- tibble::tibble(
+    dense_units = c(16, 32),
+    learn_rate = c(0.01, 0.001)
+  )
+
+  results <- compile_keras_grid(spec, grid, x_train, y_train)
+
+  expect_s3_class(results, "tbl_df")
+  expect_equal(nrow(results), 2)
+  expect_true(all(
+    c(
+      "dense_units",
+      "learn_rate",
+      "compiled_model",
+      "model_summary",
+      "error"
+    ) %in%
+      names(results)
+  ))
+  expect_true(all(is.na(results$error)))
+  expect_true(all(sapply(
+    results$compiled_model,
+    inherits,
+    "keras.src.models.model.Model"
+  )))
+})
+
+test_that("compile_keras_grid handles errors gracefully", {
+  skip_on_cran()
+
+  model_name <- "test_bad_func_spec_compile"
+  on.exit(suppressMessages(remove_keras_spec(model_name)), add = TRUE)
+
+  create_keras_functional_spec(
+    model_name = model_name,
+    mode = "classification",
+    layer_blocks = list(
+      input = function(input_shape) {
+        keras3::layer_input(shape = input_shape)
+      },
+      dense1 = function(input, units = 32) {
+        input |> keras3::layer_dense(units = units, activation = "relu")
+      },
+      dense2 = function(units = 16) {
+        # Missing input tensor
+        keras3::layer_dense(units = units, activation = "relu")
+      },
+      output = function(dense2, num_classes) {
+        dense2 |>
+          keras3::layer_dense(units = num_classes, activation = "softmax")
+      }
+    )
+  )
+
+  spec <- test_bad_func_spec_compile() |>
+    set_engine("keras")
+
+  grid <- tibble::tibble(dense1_units = 16)
+
+  expect_warning(
+    results <- compile_keras_grid(spec, grid, x_train, y_train),
+    "Block 'dense2' has no inputs from other blocks."
+  )
+
+  expect_s3_class(results, "tbl_df")
+  expect_equal(nrow(results), 1)
+  expect_false(is.na(results$error[1]))
+  expect_true(is.null(results$compiled_model[[1]]))
+})