[KED-2140] Fix issue with saving versioned HDF5 models. (#519)

RELEASE.md

@@ -18,11 +18,12 @@
 * Fixed `kedro install` for an Anaconda environment defined in `environment.yml`.
 * Fixed backwards compatibility with templates generated with older Kedro versions <0.16.5. No longer need to update `.kedro.yml` to use `kedro lint` and `kedro jupyter notebook convert`.
 * Improved documentation.
+* Fixed issue with saving a `TensorFlowModelDataset` in the HDF5 format with versioning enabled.
 
 ## Breaking changes to the API
 
 ## Thanks for supporting contributions
-[Deepyaman Datta](https://github.com/deepyaman), [Bhavya Merchant](https://github.com/bnmerchant), [Lovkush Agarwal](https://github.com/Lovkush-A), [Varun Krishna S](https://github.com/vhawk19), [Sebastian Bertoli](https://github.com/sebastianbertoli)
+[Deepyaman Datta](https://github.com/deepyaman), [Bhavya Merchant](https://github.com/bnmerchant), [Lovkush Agarwal](https://github.com/Lovkush-A), [Varun Krishna S](https://github.com/vhawk19), [Sebastian Bertoli](https://github.com/sebastianbertoli), [Daniel Petti](https://github.com/djpetti)
 
 # Release 0.16.5
 

kedro/extras/datasets/tensorflow/tensorflow_model_dataset.py

@@ -31,7 +31,7 @@
 """
 import copy
 import tempfile
-from pathlib import PurePath, PurePosixPath
+from pathlib import Path, PurePath, PurePosixPath
 from typing import Any, Dict
 
 import fsspec
@@ -151,6 +151,10 @@ def _load(self) -> tf.keras.Model:
     def _save(self, data: tf.keras.Model) -> None:
         save_path = get_filepath_str(self._get_save_path(), self._protocol)
 
+        # Make sure all intermediate directories are created.
+        save_dir = Path(save_path).parent
+        save_dir.mkdir(parents=True, exist_ok=True)
+
         with tempfile.TemporaryDirectory(prefix=self._tmp_prefix) as path:
             if self._is_h5:
                 path = str(PurePath(path) / TEMPORARY_H5_FILE)

tests/extras/datasets/tensorflow/test_tensorflow_model_dataset.py

@@ -317,6 +317,30 @@ def test_save_and_load(
         new_predictions = reloaded.predict(dummy_x_test)
         np.testing.assert_allclose(predictions, new_predictions, rtol=1e-6, atol=1e-6)
 
+    def test_hdf5_save_format(
+        self,
+        dummy_tf_base_model,
+        dummy_x_test,
+        filepath,
+        tensorflow_model_dataset,
+        load_version,
+        save_version,
+    ):
+        """Test versioned TensorflowModelDataset can save TF graph models in
+        HDF5 format"""
+        hdf5_dataset = tensorflow_model_dataset(
+            filepath=filepath,
+            save_args={"save_format": "h5"},
+            version=Version(load_version, save_version),
+        )
+
+        predictions = dummy_tf_base_model.predict(dummy_x_test)
+        hdf5_dataset.save(dummy_tf_base_model)
+
+        reloaded = hdf5_dataset.load()
+        new_predictions = reloaded.predict(dummy_x_test)
+        np.testing.assert_allclose(predictions, new_predictions, rtol=1e-6, atol=1e-6)
+
     def test_prevent_overwrite(self, dummy_tf_base_model, versioned_tf_model_dataset):
         """Check the error when attempting to override the data set if the
         corresponding file for a given save version already exists."""