feat: enabling AutoML Forecasting training response to include BigQue…

…ry location of exported evaluated examples (#657)

* Added BigQuery location of exported evaluated examples from AutoML Forecasting Training Job in training output

* Testing BQ uri output feature for AutoML Forecasting

* Testing BQ uri output feature for AutoML Forecasting

* Testing BQ uri output feature for AutoML Forecasting

* Testing BQ uri output feature for AutoML Forecasting

* Testing BQ uri output feature for AutoML Forecasting

* Testing BQ uri output feature for AutoML Forecasting

* Testing BQ uri output feature for AutoML Forecasting

* Adding changes from dev to master branch

* Removed extra try/except block 

Removed the unnecessary try/except block from the evaluated bigquery uri property method in Automl Forecasting

* Fix lint errors

* Address comments

* Add metadata existence check

Co-authored-by: Mansi Achuthan <mansiachuthan@google.com>
Co-authored-by: Vinny Senthil <vinnysenthil@gmail.com>
Co-authored-by: Hardik Vala <hardikv@google.com>
Co-authored-by: sasha-gitg <44654632+sasha-gitg@users.noreply.github.com>
Co-authored-by: thehardikv <78449654+thehardikv@users.noreply.github.com>

google/cloud/aiplatform/training_jobs.py

@@ -4418,7 +4418,7 @@ def _run(
             encryption_spec=self._model_encryption_spec,
         )
 
-        return self._run_job(
+        new_model = self._run_job(
             training_task_definition=training_task_definition,
             training_task_inputs=training_task_inputs_dict,
             dataset=dataset,
@@ -4430,6 +4430,14 @@ def _run(
             model=model,
         )
 
+        if export_evaluated_data_items:
+            _LOGGER.info(
+                "Exported examples available at:\n%s"
+                % self.evaluated_data_items_bigquery_uri
+            )
+
+        return new_model
+
     @property
     def _model_upload_fail_string(self) -> str:
         """Helper property for model upload failure."""
@@ -4438,6 +4446,23 @@ def _model_upload_fail_string(self) -> str:
             "Model."
         )
 
+    @property
+    def evaluated_data_items_bigquery_uri(self) -> Optional[str]:
+        """BigQuery location of exported evaluated examples from the Training Job
+        Returns:
+            str: BigQuery uri for the exported evaluated examples if the export
+                feature is enabled for training.
+            None: If the export feature was not enabled for training.
+        """
+
+        self._assert_gca_resource_is_available()
+
+        metadata = self._gca_resource.training_task_metadata
+        if metadata and "evaluatedDataItemsBigqueryUri" in metadata:
+            return metadata["evaluatedDataItemsBigqueryUri"]
+
+        return None
+
     def _add_additional_experiments(self, additional_experiments: List[str]):
         """Add experiment flags to the training job.
         Args:

tests/unit/aiplatform/test_automl_forecasting_training_jobs.py

@@ -151,6 +151,9 @@ def mock_pipeline_service_get():
             name=_TEST_PIPELINE_RESOURCE_NAME,
             state=gca_pipeline_state.PipelineState.PIPELINE_STATE_SUCCEEDED,
             model_to_upload=gca_model.Model(name=_TEST_MODEL_NAME),
+            training_task_metadata={
+                "evaluatedDataItemsBigqueryUri": _TEST_TRAINING_EXPORT_EVALUATED_DATA_ITEMS_BIGQUERY_DESTINATION_URI
+            },
         )
         yield mock_get_training_pipeline