feat(components): Use GetModel integration test to manually test writ…

…e_user_defined_error function

Signed-off-by: Googler <nobody@google.com>
PiperOrigin-RevId: 635979715

components/google-cloud/google_cloud_pipeline_components/container/utils/error_surfacing.py

@@ -20,10 +20,10 @@
 from google_cloud_pipeline_components.proto import task_error_pb2
 
 
-def write_user_defined_error(
+def write_customized_error(
     executor_input: str, error: task_error_pb2.TaskError
 ):
-  """Writes a TaskError to a JSON file ('executor_error.json') in the output directory specified in the executor input.
+  """Writes a TaskError customized by the author of the pipelines to a JSON file ('executor_error.json') in the output directory specified in the executor input.
 
   Args:
     executor_input: JSON string containing executor input data.

components/google-cloud/google_cloud_pipeline_components/container/v1/model/get_model/remote_runner.py

@@ -13,24 +13,51 @@
 # limitations under the License.
 """Remote runner for Get Model based on the Vertex AI SDK."""
 
+import contextlib
+from typing import Tuple, Type, Union
+
 from google.api_core.client_options import ClientOptions
 from google.cloud import aiplatform_v1 as aip_v1
 from google_cloud_pipeline_components.container.utils import artifact_utils
+from google_cloud_pipeline_components.container.utils import error_surfacing
+from google_cloud_pipeline_components.proto import task_error_pb2
 from google_cloud_pipeline_components.types import artifact_types
 
 
+@contextlib.contextmanager
+def catch_write_and_raise(
+    executor_input: str,
+    exception_types: Union[
+        Type[Exception], Tuple[Type[Exception], ...]
+    ] = Exception,
+) -> None:
+  """Context manager to catch specified exceptions, log them using error_surfacing, and then re-raise."""
+  try:
+    yield
+  except exception_types as e:
+    task_error = task_error_pb2.TaskError()
+    task_error.error_message = str(e)
+    error_surfacing.write_customized_error(executor_input, task_error)
+    raise
+
+
 def get_model(
     executor_input,
     model_name: str,
     project: str,
     location: str,
 ) -> None:
   """Get model."""
-  if not location or not project:
-    raise ValueError(
-        'Model resource name must be in the format'
-        ' projects/{project}/locations/{location}/models/{model_name}'
-    )
+  with catch_write_and_raise(
+      exception_types=ValueError,
+      executor_input=executor_input,
+  ):
+    if not location or not project:
+      model_name_error_message = (
+          'Model resource name must be in the format'
+          ' projects/{project}/locations/{location}/models/{model_name}'
+      )
+      raise ValueError(model_name_error_message)
   api_endpoint = location + '-aiplatform.googleapis.com'
   vertex_uri_prefix = f'https://{api_endpoint}/v1/'
   model_resource_name = (
@@ -40,7 +67,11 @@ def get_model(
   client_options = ClientOptions(api_endpoint=api_endpoint)
   client = aip_v1.ModelServiceClient(client_options=client_options)
   request = aip_v1.GetModelRequest(name=model_resource_name)
-  get_model_response = client.get_model(request)
+  with catch_write_and_raise(
+      exception_types=Exception,
+      executor_input=executor_input,
+  ):
+    get_model_response = client.get_model(request)
   resp_model_name_without_version = get_model_response.name.split('@', 1)[0]
   model_resource_name = (
       f'{resp_model_name_without_version}@{get_model_response.version_id}'