Fix tensorflow import in dataset wrapper to handle invalid tensorflow…

… installation due to unsupported protobuf

python/ml_wrappers/dataset/dataset_wrapper.py

@@ -30,6 +30,13 @@
     import tensorflow as tf
 except ImportError:
     module_logger.debug('Could not import tensorflow, required if using a Tensorflow model')
+except TypeError as te:
+    # handle issues with protobuf version mismatch on some environments
+    module_logger.debug(
+        "Could not import tensorflow in ml-wrappers due to"
+        "TypeError, required if using a Tensorflow model. "
+        "Inner exception: {0}".format(te))
+
 
 SAMPLED_STRING_ROWS = 10
 

python/ml_wrappers/model/tensorflow_wrapper.py

@@ -28,10 +28,14 @@ def is_sequential(model):
     :rtype: bool
     """
     model_type = str(type(model))
-    # the sequential namespace changed in tensorflow 2.13
     old_sequential_ns = "keras.engine.sequential.Sequential'>"
-    new_sequential_ns = "keras.src.engine.sequential.Sequential'>"
-    return (model_type.endswith(old_sequential_ns) or model_type.endswith(new_sequential_ns))
+    # the sequential namespace changed in tensorflow 2.13
+    new_sequential_ns1 = "keras.src.engine.sequential.Sequential'>"
+    # it changed again in tensorflow 2.17
+    new_sequential_ns2 = "keras.src.models.sequential.Sequential'>"
+    return any([model_type.endswith(old_sequential_ns),
+                model_type.endswith(new_sequential_ns1),
+                model_type.endswith(new_sequential_ns2)])
 
 
 class WrappedTensorflowModel(object):

python/ml_wrappers/version.py

@@ -1,5 +1,5 @@
 name = 'ml_wrappers'
 _major = '0'
 _minor = '5'
-_patch = '5'
+_patch = '6'
 version = '{}.{}.{}'.format(_major, _minor, _patch)

tests/main/test_model_wrapper.py

@@ -131,12 +131,10 @@ def test_wrap_lightgbm_regression_model(self, housing):
         train_regression_model_numpy(create_lightgbm_regressor, housing)
         train_regression_model_pandas(create_lightgbm_regressor, housing)
 
-    @pytest.mark.skip("Keras API failing in tests with latest tensorflow")
     def test_wrap_keras_regression_model(self, housing):
         train_regression_model_numpy(create_keras_regressor, housing)
         train_regression_model_pandas(create_keras_regressor, housing)
 
-    @pytest.mark.skip("Keras API failing in tests with latest tensorflow")
     def test_wrap_scikit_keras_regression_model(self, housing):
         train_regression_model_numpy(create_scikit_keras_regressor, housing)
         train_regression_model_pandas(create_scikit_keras_regressor, housing)

tests/main/test_tf_model_wrapper.py

@@ -38,7 +38,6 @@ def test_wrap_scikit_keras_regression_model(self, housing):
         train_regression_model_numpy(wrapped_init, housing)
         train_regression_model_pandas(wrapped_init, housing)
 
-    @pytest.mark.skip("Keras API failing in tests with latest tensorflow")
     def test_validate_is_sequential(self):
         sequential_layer = tf.keras.Sequential(layers=None, name=None)
         assert is_sequential(sequential_layer)