fix: Check that training checkpoint feature works as expected

Fixes the checkpoint feature in training and also completes unit tests for it

Resolves: MLIA-1111

Signed-off-by: Nathan Bailey <nathan.bailey@arm.com>
Change-Id: Ic2b84b4b045db5ba3cb299fcd137ae9d31df5298

1 files changed, 19 insertions, 2 deletions

diff --git a/tests/test_nn_rewrite_core_train.py b/tests/test_nn_rewrite_core_train.py
index 6d24133..624c5ed 100644
--- a/tests/test_nn_rewrite_core_train.py
+++ b/tests/test_nn_rewrite_core_train.py
@@ -63,8 +63,11 @@ def check_train(
             output_tensors=["StatefulPartitionedCall:0"],
             train_params=train_params,
         )
-        assert len(result) == 2
-        assert all(res >= 0.0 for res in result[0]), f"Results out of bound: {result}"
+
+        assert len(result[0][0]) == 2
+        assert all(
+            res >= 0.0 for res in result[0][0]
+        ), f"Results out of bound: {result}"
         assert output_file.is_file()
 
         if quantized:
@@ -229,3 +232,17 @@ def test_augment_fn_twins(augmentations: tuple, expected_error: Any) -> None:
     with expected_error:
         fn_twins = augment_fn_twins(dataset, augmentations)  # type: ignore
         assert len(fn_twins) == 2
+
+
+def test_train_checkpoint(
+    test_tflite_model: Path,
+    test_tfrecord: Path,
+) -> None:
+    """Test the train() function with valid checkpoint parameters."""
+    check_train(
+        tflite_model=test_tflite_model,
+        tfrecord=test_tfrecord,
+        train_params=MockTrainingParameters(steps=64, checkpoint_at=[24, 32]),
+        use_unmodified_model=False,
+        quantized=True,
+    )