feat: support dataset update

google/cloud/aiplatform/datasets/dataset.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-# Copyright 2020 Google LLC
+# Copyright 2022 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -31,6 +31,7 @@
     io as gca_io,
 )
 from google.cloud.aiplatform.datasets import _datasources
+from google.protobuf import field_mask_pb2
 
 _LOGGER = base.Logger(__name__)
 
@@ -597,8 +598,69 @@ def export_data(self, output_dir: str) -> Sequence[str]:
 
         return export_data_response.exported_files
 
-    def update(self):
-        raise NotImplementedError("Update dataset has not been implemented yet")
+    def update(
+        self,
+        *,
+        display_name: Optional[str] = None,
+        labels: Optional[Dict[str, str]] = None,
+        description: Optional[str] = None,
+        update_request_timeout: Optional[float] = None,
+    ) -> "_Dataset":
+        """Update the dataset.
+            Updatable fields:
+                -  ``display_name``
+                -  ``description``
+                -  ``labels``
+
+        Args:
+            display_name (str):
+                Optional. The user-defined name of the Dataset.
+                The name can be up to 128 characters long and can be consist
+                of any UTF-8 characters.
+            labels (Dict[str, str]):
+                Optional. Labels with user-defined metadata to organize your Tensorboards.
+                Label keys and values can be no longer than 64 characters
+                (Unicode codepoints), can only contain lowercase letters, numeric
+                characters, underscores and dashes. International characters are allowed.
+                No more than 64 user labels can be associated with one Tensorboard
+                (System labels are excluded).
+                See https://goo.gl/xmQnxf for more information and examples of labels.
+                System reserved label keys are prefixed with "aiplatform.googleapis.com/"
+                and are immutable.
+            description (str):
+                Optional. The description of the Dataset.
+            update_request_timeout (float):
+                Optional. The timeout for the update request in seconds.
+
+        Returns:
+            dataset (Dataset):
+                Updated dataset.
+        """
+
+        update_mask = field_mask_pb2.FieldMask()
+        if display_name:
+            update_mask.paths.append("display_name")
+
+        if labels:
+            update_mask.paths.append("labels")
+
+        if description:
+            update_mask.paths.append("description")
+
+        update_dataset = gca_dataset.Dataset(
+            name=self.resource_name,
+            display_name=display_name,
+            description=description,
+            labels=labels,
+        )
+
+        self._gca_resource = self.api_client.update_dataset(
+            dataset=update_dataset,
+            update_mask=update_mask,
+            timeout=update_request_timeout,
+        )
+
+        return self
 
     @classmethod
     def list(

tests/system/aiplatform/test_dataset.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-# Copyright 2020 Google LLC
+# Copyright 2022 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -50,6 +50,8 @@
     "6203215905493614592"  # permanent_text_entity_extraction_dataset
 )
 _TEST_DATASET_DISPLAY_NAME = "permanent_50_flowers_dataset"
+_TEST_DATASET_LABELS = {"test": "labels"}
+_TEST_DATASET_DESCRIPTION = "test description"
 _TEST_TABULAR_CLASSIFICATION_GCS_SOURCE = "gs://ucaip-sample-resources/iris_1000.csv"
 _TEST_FORECASTING_BQ_SOURCE = (
     "bq://ucaip-sample-tests:ucaip_test_us_central1.2020_sales_train"
@@ -350,3 +352,26 @@ def test_export_data(self, storage_client, staging_bucket):
         blob = bucket.get_blob(prefix)
 
         assert blob  # Verify the returned GCS export path exists
+
+    def test_update_dataset(self):
+        """Create a new dataset and use update() method to change its display_name, labels, and description.
+        Then confirm these fields of the dataset was successfully modifed."""
+
+        try:
+            dataset = aiplatform.ImageDataset.create()
+            labels = dataset.labels
+
+            dataset = dataset.update(
+                display_name=_TEST_DATASET_DISPLAY_NAME,
+                labels=_TEST_DATASET_LABELS,
+                description=_TEST_DATASET_DESCRIPTION,
+                update_request_timeout=None,
+            )
+            labels.update(_TEST_DATASET_LABELS)
+
+            assert dataset.display_name == _TEST_DATASET_DISPLAY_NAME
+            assert dataset.labels == labels
+            assert dataset.gca_resource.description == _TEST_DATASET_DESCRIPTION
+
+        finally:
+            dataset.delete()

tests/unit/aiplatform/test_datasets.py

@@ -36,6 +36,7 @@
 from google.cloud.aiplatform import schema
 from google.cloud import bigquery
 from google.cloud import storage
+from google.protobuf import field_mask_pb2
 
 from google.cloud.aiplatform.compat.services import dataset_service_client
 
@@ -59,6 +60,7 @@
 _TEST_ID = "1028944691210842416"
 _TEST_DISPLAY_NAME = "my_dataset_1234"
 _TEST_DATA_LABEL_ITEMS = None
+_TEST_DESCRIPTION = "test description"
 
 _TEST_NAME = f"projects/{_TEST_PROJECT}/locations/{_TEST_LOCATION}/datasets/{_TEST_ID}"
 _TEST_ALT_NAME = (
@@ -425,6 +427,20 @@ def export_data_mock():
         yield export_data_mock
 
 
+@pytest.fixture
+def update_dataset_mock():
+    with patch.object(
+        dataset_service_client.DatasetServiceClient, "update_dataset"
+    ) as update_dataset_mock:
+        update_dataset_mock.return_value = gca_dataset.Dataset(
+            name=_TEST_NAME,
+            display_name=f"update_{_TEST_DISPLAY_NAME}",
+            labels=_TEST_LABELS,
+            description=_TEST_DESCRIPTION,
+        )
+        yield update_dataset_mock
+
+
 @pytest.fixture
 def list_datasets_mock():
     with patch.object(
@@ -996,6 +1012,36 @@ def test_delete_dataset(self, delete_dataset_mock, sync):
 
         delete_dataset_mock.assert_called_once_with(name=my_dataset.resource_name)
 
+    @pytest.mark.usefixtures("get_dataset_mock")
+    def test_update_dataset(self, update_dataset_mock):
+        aiplatform.init(project=_TEST_PROJECT)
+
+        my_dataset = datasets._Dataset(dataset_name=_TEST_NAME)
+
+        my_dataset = my_dataset.update(
+            display_name=f"update_{_TEST_DISPLAY_NAME}",
+            labels=_TEST_LABELS,
+            description=_TEST_DESCRIPTION,
+            update_request_timeout=None,
+        )
+
+        expected_dataset = gca_dataset.Dataset(
+            name=_TEST_NAME,
+            display_name=f"update_{_TEST_DISPLAY_NAME}",
+            labels=_TEST_LABELS,
+            description=_TEST_DESCRIPTION,
+        )
+
+        expected_mask = field_mask_pb2.FieldMask(
+            paths=["display_name", "labels", "description"]
+        )
+
+        update_dataset_mock.assert_called_once_with(
+            dataset=expected_dataset,
+            update_mask=expected_mask,
+            timeout=None,
+        )
+
 
 @pytest.mark.usefixtures("google_auth_mock")
 class TestImageDataset: