Added a getter and a setter for __metadata

ote_sdk/ote_sdk/entities/dataset_item.py

@@ -118,9 +118,16 @@ def __init__(
             set() if ignored_labels is None else set(ignored_labels)
         )
 
-    @property
-    def metadata(self) -> Sequence[MetadataItemEntity]:
-        """Provides access to metadata."""
+    def set_metadata(self, metadata: List[MetadataItemEntity]):
+        """
+        Sets the metadata
+        """
+        self.__metadata = metadata
+
+    def get_metadata(self) -> List[MetadataItemEntity]:
+        """
+        Returns the metadata
+        """
         return self.__metadata
 
     @property
@@ -486,6 +493,6 @@ def get_metadata_by_name_and_model(
         """
         return [
             meta
-            for meta in self.metadata
+            for meta in self.get_metadata()
             if meta.data.name == name and meta.model == model
         ]

ote_sdk/ote_sdk/tests/configuration/elements/test_primitive_parameters.py

@@ -140,7 +140,7 @@ def check_configurable_integer(
             assert integer_instance._default == 100
             assert integer_instance.type == int
             assert len(integer_instance._validator._validators) == 2
-            assert integer_instance.metadata == expected_metadata
+            assert integer_instance.get_metadata() == expected_metadata
 
         # Checking _CountingAttr object returned by "configurable_integer" for default values of optional parameters
         default_value = 100
@@ -243,7 +243,7 @@ def check_configurable_float(
             assert isinstance(float_instance, _make._CountingAttr)
             assert float_instance._default == 100.1
             assert float_instance.type == float
-            assert float_instance.metadata == expected_metadata
+            assert float_instance.get_metadata() == expected_metadata
 
         # Checking _CountingAttr object returned by "configurable_float" for default values of optional parameters
         default_value = 100.1
@@ -343,7 +343,7 @@ def check_configurable_boolean(
                 boolean_instance._validator, validators._InstanceOfValidator  # type: ignore
             )
             assert boolean_instance._validator.type == bool
-            assert boolean_instance.metadata == expected_metadata
+            assert boolean_instance.get_metadata() == expected_metadata
 
         # Checking _CountingAttr object returned by "configurable_boolean" for default values of optional parameters
         default_value = True
@@ -435,7 +435,7 @@ def check_float_selectable(
             assert isinstance(float_selectable_instance, _make._CountingAttr)
             assert float_selectable_instance._default
             assert float_selectable_instance.type == float
-            assert float_selectable_instance.metadata == expected_metadata
+            assert float_selectable_instance.get_metadata() == expected_metadata
 
         # Checking _CountingAttr object returned by "float_selectable" for default values of optional parameters
         default_value = 0.1
@@ -534,7 +534,7 @@ def check_selectable(
             assert isinstance(selectable_instance, _make._CountingAttr)
             assert selectable_instance._default == SomeEnumSelectable.OPTION_C
             assert selectable_instance.type == ConfigurableEnum
-            assert selectable_instance.metadata == expected_metadata
+            assert selectable_instance.get_metadata() == expected_metadata
 
         # Checking _CountingAttr object returned by "selectable" for default values of optional parameters
         default_value = SomeEnumSelectable.OPTION_C

ote_sdk/ote_sdk/tests/configuration/helper/test_create.py

@@ -479,7 +479,7 @@ def test_gather_parameter_arguments_and_values_from_dict(self):
             )
             assert isinstance(argument, _make._CountingAttr)
             assert argument.type == int
-            metadata = argument.metadata
+            metadata = argument.get_metadata()
             assert metadata.get("default_value") == 70
             assert metadata.get("description") == "Default integer description"
             assert metadata.get("header") == "non selectable parameter header"
@@ -492,7 +492,7 @@ def test_gather_parameter_arguments_and_values_from_dict(self):
             argument = arguments_and_values_dict.get("make_arguments").get("selectable")
             assert isinstance(argument, _make._CountingAttr)
             assert argument.type == ConfigurableEnum
-            metadata = argument.metadata
+            metadata = argument.get_metadata()
             assert type(metadata.get("default_value")).__name__ == "test enum"
             assert metadata.get("default_value").name == "test_2"
             assert metadata.get("default_value").value == 2

ote_sdk/ote_sdk/tests/entities/test_dataset_item.py

@@ -254,12 +254,12 @@ def test_dataset_item_initialization(self):
         default_values_dataset_item = DatasetItemEntity(media, annotations_scene)
         assert default_values_dataset_item.media == media
         assert default_values_dataset_item.annotation_scene == annotations_scene
-        assert not default_values_dataset_item.metadata
+        assert not default_values_dataset_item.get_metadata()
         assert default_values_dataset_item.subset == Subset.NONE
         assert default_values_dataset_item.ignored_labels == set()
         # Checking attributes of DatasetItemEntity object initialized with specified optional parameters
         roi = DatasetItemParameters().roi()
-        metadata = DatasetItemParameters.metadata()
+        metadata = DatasetItemParameters.get_metadata()
         subset = Subset.TESTING
         ignored_labels = set(DatasetItemParameters().labels())
         specified_values_dataset_item = DatasetItemEntity(
@@ -268,7 +268,7 @@ def test_dataset_item_initialization(self):
         assert specified_values_dataset_item.media == media
         assert specified_values_dataset_item.annotation_scene == annotations_scene
         assert specified_values_dataset_item.roi == roi
-        assert specified_values_dataset_item.metadata == metadata
+        assert specified_values_dataset_item.get_metadata() == metadata
         assert specified_values_dataset_item.subset == subset
         assert specified_values_dataset_item.ignored_labels == ignored_labels
 
@@ -923,7 +923,7 @@ def test_dataset_item_deepcopy(self):
             dataset_item.annotation_scene.shapes == copy_dataset.annotation_scene.shapes
         )
         assert dataset_item.roi == copy_dataset.roi
-        assert dataset_item.metadata == copy_dataset.metadata
+        assert dataset_item.get_metadata() == copy_dataset.get_metadata()
         assert dataset_item.subset == copy_dataset.subset
 
     @pytest.mark.priority_medium
@@ -946,15 +946,15 @@ def test_dataset_item_append_metadata_item(self):
         2. Check "metadata" attribute after "append_metadata_item" method with specified "model" parameter
         """
         dataset_item = DatasetItemParameters().dataset_item()
-        expected_metadata = list(dataset_item.metadata)
+        expected_metadata = list(dataset_item.get_metadata())
         # Checking metadata attribute returned after "append_metadata_item" method with non-specified "model" parameter
         data_to_append = TensorEntity(
             name="appended_metadata",
             numpy=np.random.uniform(low=0.0, high=255.0, size=(10, 15, 3)),
         )
         expected_metadata.append(MetadataItemEntity(data=data_to_append))
         dataset_item.append_metadata_item(data=data_to_append)
-        assert list(dataset_item.metadata) == expected_metadata
+        assert list(dataset_item.get_metadata()) == expected_metadata
         # Checking metadata attribute returned after "append_metadata_item" method with specified "model" parameter
         metadata_item_with_model = self.metadata_item_with_model()
         data_to_append = metadata_item_with_model.data
@@ -964,7 +964,7 @@ def test_dataset_item_append_metadata_item(self):
         )
         expected_metadata.append(new_metadata_item_with_model)
         dataset_item.append_metadata_item(data_to_append, model_to_append)
-        assert list(dataset_item.metadata) == expected_metadata
+        assert list(dataset_item.get_metadata()) == expected_metadata
 
     @pytest.mark.priority_medium
     @pytest.mark.unit
@@ -992,7 +992,7 @@ def test_dataset_item_get_metadata_by_name_and_model(self):
         metadata_item_with_model = self.metadata_item_with_model()
         dataset_model = metadata_item_with_model.model
         dataset_item.append_metadata_item(metadata_item_with_model.data, dataset_model)
-        dataset_metadata = list(dataset_item.metadata)
+        dataset_metadata = list(dataset_item.get_metadata())
         # Checking "get_metadata_by_name_and_model" method for "model" parameter is "None"
         assert dataset_item.get_metadata_by_name_and_model("test_metadata", None) == [
             dataset_metadata[0]

ote_sdk/ote_sdk/tests/entities/test_task_environment.py

@@ -165,7 +165,7 @@ def test_compare_learning_parameters_num_workers(self):
             env.get_hyper_parameters().learning_parameters.num_workers
         )  # "default_value"
         config_example_learning_parameters_num_workers = (
-            config_example.learning_parameters._default.factory.num_workers.metadata[
+            config_example.learning_parameters._default.factory.num_workers.get_metadata()[
                 "default_value"
             ]
         )
@@ -199,7 +199,7 @@ def test_compare_learning_parameters_batch_size(self):
             env.get_hyper_parameters().learning_parameters.batch_size
         )  # "default_value"
         config_example_learning_parameters_batch_size = (
-            config_example.learning_parameters._default.factory.batch_size.metadata[
+            config_example.learning_parameters._default.factory.batch_size.get_metadata()[
                 "default_value"
             ]
         )
@@ -234,7 +234,7 @@ def test_compare_learning_parameters_num_iters(self):
             env.get_hyper_parameters().learning_parameters.num_iters
         )  # "default_value"
         config_example_learning_parameters_num_iters = (
-            config_example.learning_parameters._default.factory.num_iters.metadata[
+            config_example.learning_parameters._default.factory.num_iters.get_metadata()[
                 "default_value"
             ]
         )
@@ -269,7 +269,7 @@ def test_compare_learning_parameters_learning_rate(self):
             env.get_hyper_parameters().learning_parameters.learning_rate
         )  # "default_value"
         config_example_learning_parameters_learning_rate = (
-            config_example.learning_parameters._default.factory.learning_rate.metadata[
+            config_example.learning_parameters._default.factory.learning_rate.get_metadata()[
                 "default_value"
             ]
         )
@@ -313,7 +313,7 @@ def test_compare_learning_parameters_num_checkpoints(self):
         # Attempt to access the missing parameter in ConfigExample
         with pytest.raises(AttributeError):
             # AttributeError: type object '__LearningParameters' has no attribute 'num_checkpoints'
-            config_example.learning_parameters._default.factory.num_checkpoints.metadata[
+            config_example.learning_parameters._default.factory.num_checkpoints.get_metadata()[
                 "default_value"
             ]
 
@@ -368,7 +368,7 @@ def test_compare_postprocessing_confidence_threshold(self):
         )
         cep = config_example.postprocessing
         config_example_postprocessing_confidence_threshold = (
-            cep._default.factory.confidence_threshold.metadata["default_value"]
+            cep._default.factory.confidence_threshold.get_metadata()["default_value"]
         )
 
         # From dummy_config.yaml because it is missing in dummy_template.yaml "parameter_overrides"
@@ -404,7 +404,7 @@ def test_compare_postprocessing_result_based_confidence_threshold(self):
         cep = config_example.postprocessing
         def_factory = cep._default.factory
         rbct = def_factory.result_based_confidence_threshold
-        config_example_postprocessing_result_based_confidence_threshold = rbct.metadata[
+        config_example_postprocessing_result_based_confidence_threshold = rbct.get_metadata()[
             "default_value"
         ]
 

ote_sdk/ote_sdk/utils/dataset_utils.py

@@ -91,7 +91,7 @@ def get_local_subset(
                     local_annotations,
                     kind=item.annotation_scene.kind,
                 ),
-                metadata=item.metadata,
+                metadata=item.get_metadata(),
                 subset=item.subset,
                 roi=item.roi,
                 ignored_labels=item.ignored_labels,
@@ -120,7 +120,7 @@ def get_global_subset(dataset: DatasetEntity) -> DatasetEntity:
                 annotation_scene=AnnotationSceneEntity(
                     global_annotations, kind=item.annotation_scene.kind
                 ),
-                metadata=item.metadata,
+                metadata=item.get_metadata(),
                 subset=item.subset,
                 roi=item.roi,
                 ignored_labels=item.ignored_labels,