feat: GenAI - Add cancel, delete, list methods in BatchPredictionJob

tests/unit/vertexai/test_batch_prediction.py

@@ -89,11 +89,36 @@ def complete_bq_uri_mock():
 
 
 @pytest.fixture
-def get_batch_prediction_job_mock():
+def get_batch_prediction_job_with_bq_output_mock():
     with mock.patch.object(
         job_service_client.JobServiceClient, "get_batch_prediction_job"
     ) as get_job_mock:
-        get_job_mock.return_value = _TEST_GAPIC_BATCH_PREDICTION_JOB
+        get_job_mock.return_value = gca_batch_prediction_job_compat.BatchPredictionJob(
+            name=_TEST_BATCH_PREDICTION_JOB_NAME,
+            display_name=_TEST_DISPLAY_NAME,
+            model=_TEST_GEMINI_MODEL_RESOURCE_NAME,
+            state=_TEST_JOB_STATE_SUCCESS,
+            output_info=gca_batch_prediction_job_compat.BatchPredictionJob.OutputInfo(
+                bigquery_output_table=_TEST_BQ_OUTPUT_PREFIX
+            ),
+        )
+        yield get_job_mock
+
+
+@pytest.fixture
+def get_batch_prediction_job_with_gcs_output_mock():
+    with mock.patch.object(
+        job_service_client.JobServiceClient, "get_batch_prediction_job"
+    ) as get_job_mock:
+        get_job_mock.return_value = gca_batch_prediction_job_compat.BatchPredictionJob(
+            name=_TEST_BATCH_PREDICTION_JOB_NAME,
+            display_name=_TEST_DISPLAY_NAME,
+            model=_TEST_GEMINI_MODEL_RESOURCE_NAME,
+            state=_TEST_JOB_STATE_SUCCESS,
+            output_info=gca_batch_prediction_job_compat.BatchPredictionJob.OutputInfo(
+                gcs_output_directory=_TEST_GCS_OUTPUT_PREFIX
+            ),
+        )
         yield get_job_mock
 
 
@@ -120,6 +145,39 @@ def create_batch_prediction_job_mock():
         yield create_job_mock
 
 
+@pytest.fixture
+def cancel_batch_prediction_job_mock():
+    with mock.patch.object(
+        job_service_client.JobServiceClient, "cancel_batch_prediction_job"
+    ) as cancel_job_mock:
+        yield cancel_job_mock
+
+
+@pytest.fixture
+def delete_batch_prediction_job_mock():
+    with mock.patch.object(
+        job_service_client.JobServiceClient, "delete_batch_prediction_job"
+    ) as delete_job_mock:
+        yield delete_job_mock
+
+
+@pytest.fixture
+def list_batch_prediction_jobs_mock():
+    with mock.patch.object(
+        job_service_client.JobServiceClient, "list_batch_prediction_jobs"
+    ) as list_jobs_mock:
+        list_jobs_mock.return_value = [
+            _TEST_GAPIC_BATCH_PREDICTION_JOB,
+            gca_batch_prediction_job_compat.BatchPredictionJob(
+                name=_TEST_BATCH_PREDICTION_JOB_NAME,
+                display_name=_TEST_DISPLAY_NAME,
+                model=_TEST_PALM_MODEL_RESOURCE_NAME,
+                state=_TEST_JOB_STATE_SUCCESS,
+            ),
+        ]
+        yield list_jobs_mock
+
+
 @pytest.mark.usefixtures(
     "google_auth_mock", "generate_display_name_mock", "complete_bq_uri_mock"
 )
@@ -138,10 +196,12 @@ def setup_method(self):
     def teardown_method(self):
         aiplatform_initializer.global_pool.shutdown(wait=True)
 
-    def test_init_batch_prediction_job(self, get_batch_prediction_job_mock):
+    def test_init_batch_prediction_job(
+        self, get_batch_prediction_job_with_gcs_output_mock
+    ):
         batch_prediction.BatchPredictionJob(_TEST_BATCH_PREDICTION_JOB_ID)
 
-        get_batch_prediction_job_mock.assert_called_once_with(
+        get_batch_prediction_job_with_gcs_output_mock.assert_called_once_with(
             name=_TEST_BATCH_PREDICTION_JOB_NAME, retry=aiplatform_base._DEFAULT_RETRY
         )
 
@@ -157,6 +217,7 @@ def test_init_batch_prediction_job_invalid_model(self):
         ):
             batch_prediction.BatchPredictionJob(_TEST_BATCH_PREDICTION_JOB_ID)
 
+    @pytest.mark.usefixtures("get_batch_prediction_job_with_gcs_output_mock")
     def test_submit_batch_prediction_job_with_gcs_input(
         self, create_batch_prediction_job_mock
     ):
@@ -167,6 +228,15 @@ def test_submit_batch_prediction_job_with_gcs_input(
         )
 
         assert job.gca_resource == _TEST_GAPIC_BATCH_PREDICTION_JOB
+        assert job.state == _TEST_JOB_STATE_RUNNING
+        assert not job.has_ended
+        assert not job.has_succeeded
+
+        job.refresh()
+        assert job.state == _TEST_JOB_STATE_SUCCESS
+        assert job.has_ended
+        assert job.has_succeeded
+        assert job.output_location == _TEST_GCS_OUTPUT_PREFIX
 
         expected_gapic_batch_prediction_job = gca_batch_prediction_job_compat.BatchPredictionJob(
             display_name=_TEST_DISPLAY_NAME,
@@ -188,6 +258,7 @@ def test_submit_batch_prediction_job_with_gcs_input(
             timeout=None,
         )
 
+    @pytest.mark.usefixtures("get_batch_prediction_job_with_bq_output_mock")
     def test_submit_batch_prediction_job_with_bq_input(
         self, create_batch_prediction_job_mock
     ):
@@ -198,6 +269,15 @@ def test_submit_batch_prediction_job_with_bq_input(
         )
 
         assert job.gca_resource == _TEST_GAPIC_BATCH_PREDICTION_JOB
+        assert job.state == _TEST_JOB_STATE_RUNNING
+        assert not job.has_ended
+        assert not job.has_succeeded
+
+        job.refresh()
+        assert job.state == _TEST_JOB_STATE_SUCCESS
+        assert job.has_ended
+        assert job.has_succeeded
+        assert job.output_location == _TEST_BQ_OUTPUT_PREFIX
 
         expected_gapic_batch_prediction_job = gca_batch_prediction_job_compat.BatchPredictionJob(
             display_name=_TEST_DISPLAY_NAME,
@@ -349,3 +429,35 @@ def test_submit_batch_prediction_job_without_output_uri_prefix_and_bucket(self):
                 source_model=_TEST_GEMINI_MODEL_NAME,
                 input_dataset=_TEST_GCS_INPUT_URI,
             )
+
+    @pytest.mark.usefixtures("create_batch_prediction_job_mock")
+    def test_cancel_batch_prediction_job(self, cancel_batch_prediction_job_mock):
+        job = batch_prediction.BatchPredictionJob.submit(
+            source_model=_TEST_GEMINI_MODEL_NAME,
+            input_dataset=_TEST_GCS_INPUT_URI,
+            output_uri_prefix=_TEST_GCS_OUTPUT_PREFIX,
+        )
+        job.cancel()
+
+        cancel_batch_prediction_job_mock.assert_called_once_with(
+            name=_TEST_BATCH_PREDICTION_JOB_NAME,
+        )
+
+    @pytest.mark.usefixtures("get_batch_prediction_job_with_gcs_output_mock")
+    def test_delete_batch_prediction_job(self, delete_batch_prediction_job_mock):
+        job = batch_prediction.BatchPredictionJob(_TEST_BATCH_PREDICTION_JOB_ID)
+        job.delete()
+
+        delete_batch_prediction_job_mock.assert_called_once_with(
+            name=_TEST_BATCH_PREDICTION_JOB_NAME,
+        )
+
+    def tes_list_batch_prediction_jobs(self, list_batch_prediction_jobs_mock):
+        jobs = batch_prediction.BatchPredictionJob.list()
+
+        assert len(jobs) == 1
+        assert jobs[0].gca_resource == _TEST_GAPIC_BATCH_PREDICTION_JOB
+
+        list_batch_prediction_jobs_mock.assert_called_once_with(
+            request={"parent": _TEST_PARENT}
+        )

vertexai/batch_prediction/_batch_prediction.py

@@ -23,8 +23,11 @@
 from google.cloud.aiplatform import initializer as aiplatform_initializer
 from google.cloud.aiplatform import jobs
 from google.cloud.aiplatform import utils as aiplatform_utils
+from google.cloud.aiplatform_v1 import types as gca_types
 from vertexai import generative_models
 
+from google.rpc import status_pb2
+
 
 _LOGGER = aiplatform_base.Logger(__name__)
 
@@ -37,7 +40,6 @@ class BatchPredictionJob(aiplatform_base._VertexAiResourceNounPlus):
     _resource_noun = "batchPredictionJobs"
     _getter_method = "get_batch_prediction_job"
     _list_method = "list_batch_prediction_jobs"
-    _cancel_method = "cancel_batch_prediction_job"
     _delete_method = "delete_batch_prediction_job"
     _job_type = "batch-predictions"
     _parse_resource_name_method = "parse_batch_prediction_job_path"
@@ -63,13 +65,46 @@ def __init__(self, batch_prediction_job_name: str):
             resource_name=batch_prediction_job_name
         )
         # TODO(b/338452508) Support tuned GenAI models.
-        if not re.search(_GEMINI_MODEL_PATTERN, self._gca_resource.model):
+        if not re.search(_GEMINI_MODEL_PATTERN, self.model_name):
             raise ValueError(
                 f"BatchPredictionJob '{batch_prediction_job_name}' "
-                f"runs with the model '{self._gca_resource.model}', "
+                f"runs with the model '{self.model_name}', "
                 "which is not a GenAI model."
             )
 
+    @property
+    def model_name(self) -> str:
+        """Returns the model name used for this batch prediction job."""
+        return self._gca_resource.model
+
+    @property
+    def state(self) -> gca_types.JobState:
+        """Returns the state of this batch prediction job."""
+        return self._gca_resource.state
+
+    @property
+    def has_ended(self) -> bool:
+        """Returns true if this batch prediction job has ended."""
+        return self.state in jobs._JOB_COMPLETE_STATES
+
+    @property
+    def has_succeeded(self) -> bool:
+        """Returns true if this batch prediction job has succeeded."""
+        return self.state == gca_types.JobState.JOB_STATE_SUCCEEDED
+
+    @property
+    def error(self) -> Optional[status_pb2.Status]:
+        """Returns detailed error info for this Job resource."""
+        return self._gca_resource.error
+
+    @property
+    def output_location(self) -> str:
+        """Returns the output location of this batch prediction job."""
+        return (
+            self._gca_resource.output_info.gcs_output_directory
+            or self._gca_resource.output_info.bigquery_output_table
+        )
+
     @classmethod
     def submit(
         cls,
@@ -178,14 +213,54 @@ def submit(
             _LOGGER.log_create_complete(
                 cls, job._gca_resource, "job", module_name="batch_prediction"
             )
-            _LOGGER.info(
-                "View Batch Prediction Job:\n%s" % aiplatform_job._dashboard_uri()
-            )
+            _LOGGER.info("View Batch Prediction Job:\n%s" % job._dashboard_uri())
 
             return job
         finally:
             logging.getLogger("google.cloud.aiplatform.jobs").disabled = False
 
+    def refresh(self) -> "BatchPredictionJob":
+        """Refreshes the batch prediction job from the service."""
+        self._sync_gca_resource()
+        return self
+
+    def cancel(self):
+        """Cancels this BatchPredictionJob.
+
+        Success of cancellation is not guaranteed. Use `job.refresh()` and
+        `job.state` to verify if cancellation was successful.
+        """
+        _LOGGER.log_action_start_against_resource("Cancelling", "run", self)
+        self.api_client.cancel_batch_prediction_job(name=self.resource_name)
+
+    def delete(self):
+        """Deletes this BatchPredictionJob resource.
+
+        WARNING: This deletion is permanent.
+        """
+        self._delete()
+
+    @classmethod
+    def list(cls, filter=None) -> List["BatchPredictionJob"]:
+        """Lists all BatchPredictionJob instances that run with GenAI models."""
+        return cls._list(
+            cls_filter=lambda gca_resource: re.search(
+                _GEMINI_MODEL_PATTERN, gca_resource.model
+            ),
+            filter=filter,
+        )
+
+    def _dashboard_uri(self) -> Optional[str]:
+        """Returns the Google Cloud console URL where job can be viewed."""
+        fields = self._parse_resource_name(self.resource_name)
+        location = fields.pop("location")
+        project = fields.pop("project")
+        job = list(fields.values())[0]
+        return (
+            "https://console.cloud.google.com/ai/platform/locations/"
+            f"{location}/{self._job_type}/{job}?project={project}"
+        )
+
     @classmethod
     def _reconcile_model_name(cls, model_name: str) -> str:
         """Reconciles model name to a publisher model resource name."""