chore(components): Temporary fix for artifact types (cf. kubeflow#8191)

PiperOrigin-RevId: 483477877

components/google-cloud/google_cloud_pipeline_components/aiplatform/utils.py

@@ -507,7 +507,8 @@ def convert_method_to_component(cls: aiplatform.base.VertexAiResourceNoun,
           output_name=output_metadata_name)
     except TypeError:
       from kfp.components import placeholders
-      output_spec = structures.OutputSpec(type=output_metadata_type)
+      output_spec = structures.OutputSpec(
+          type=(output_metadata_type + '@0.0.1'))
       output_uri_placeholder = placeholders.OutputUriPlaceholder(
           output_name=output_metadata_name)
 

components/google-cloud/google_cloud_pipeline_components/types/artifact_types.py

@@ -20,9 +20,21 @@
 # The artifact property key for the resource name
 ARTIFACT_PROPERTY_KEY_RESOURCE_NAME = 'resourceName'
 
+
+def google_artifact(type_name):
+  "Decorator for Google Artifact types for handling KFP v1/v2 artifact types"
+  def add_type_name(cls):
+    if hasattr(dsl.Artifact, 'schema_title'):
+      cls.schema_title = type_name
+      cls.schema_version = '0.0.1'
+    else:
+      cls.TYPE_NAME = type_name
+    return cls
+  return add_type_name
+
+@google_artifact('google.VertexModel')
 class VertexModel(dsl.Artifact):
   """An artifact representing a Vertex Model."""
-  TYPE_NAME = 'google.VertexModel'
 
   def __init__(self, name: str, uri: str, model_resource_name: str):
     """Args:
@@ -44,9 +56,9 @@ def __init__(self, name: str, uri: str, model_resource_name: str):
         metadata={ARTIFACT_PROPERTY_KEY_RESOURCE_NAME: model_resource_name})
 
 
+@google_artifact('google.VertexEndpoint')
 class VertexEndpoint(dsl.Artifact):
   """An artifact representing a Vertex Endpoint."""
-  TYPE_NAME = 'google.VertexEndpoint'
 
   def __init__(self, name: str, uri: str, endpoint_resource_name: str):
     """Args:
@@ -68,9 +80,9 @@ def __init__(self, name: str, uri: str, endpoint_resource_name: str):
         metadata={ARTIFACT_PROPERTY_KEY_RESOURCE_NAME: endpoint_resource_name})
 
 
+@google_artifact('google.VertexBatchPredictionJob')
 class VertexBatchPredictionJob(dsl.Artifact):
   """An artifact representing a Vertex BatchPredictionJob."""
-  TYPE_NAME = 'google.VertexBatchPredictionJob'
 
   def __init__(self,
                name: str,
@@ -115,9 +127,9 @@ def __init__(self,
         })
 
 
+@google_artifact('google.VertexDataset')
 class VertexDataset(dsl.Artifact):
   """An artifact representing a Vertex Dataset."""
-  TYPE_NAME = 'google.VertexDataset'
 
   def __init__(self, name: str, uri: str, dataset_resource_name: str):
     """Args:
@@ -139,9 +151,9 @@ def __init__(self, name: str, uri: str, dataset_resource_name: str):
         metadata={ARTIFACT_PROPERTY_KEY_RESOURCE_NAME: dataset_resource_name})
 
 
+@google_artifact('google.BQMLModel')
 class BQMLModel(dsl.Artifact):
   """An artifact representing a BQML Model."""
-  TYPE_NAME = 'google.BQMLModel'
 
   def __init__(self, name: str, project_id: str, dataset_id: str,
                model_id: str):
@@ -165,9 +177,9 @@ def __init__(self, name: str, project_id: str, dataset_id: str,
         })
 
 
+@google_artifact('google.BQTable')
 class BQTable(dsl.Artifact):
   """An artifact representing a BQ Table."""
-  TYPE_NAME = 'google.BQTable'
 
   def __init__(self, name: str, project_id: str, dataset_id: str,
                table_id: str):
@@ -191,9 +203,9 @@ def __init__(self, name: str, project_id: str, dataset_id: str,
         })
 
 
+@google_artifact('google.UnmanagedContainerModel')
 class UnmanagedContainerModel(dsl.Artifact):
   """An artifact representing an unmanaged container model."""
-  TYPE_NAME = 'google.UnmanagedContainerModel'
 
   def __init__(self, predict_schemata: Dict, container_spec: Dict):
     """Args: