feat: add input artifact when creating a pipeline

google/cloud/aiplatform/pipeline_jobs.py

@@ -110,6 +110,7 @@ def __init__(
         job_id: Optional[str] = None,
         pipeline_root: Optional[str] = None,
         parameter_values: Optional[Dict[str, Any]] = None,
+        input_artifacts: Optional[Dict[str, str]] = None,
         enable_caching: Optional[bool] = None,
         encryption_spec_key_name: Optional[str] = None,
         labels: Optional[Dict[str, str]] = None,
@@ -139,6 +140,9 @@ def __init__(
             parameter_values (Dict[str, Any]):
                 Optional. The mapping from runtime parameter names to its values that
                 control the pipeline run.
+            input_artifacts (Dict[str, str]):
+                Optional. The mapping from the runtime parameter name for this artifact to its resource id.
+                For example: "vertex_model":"456". Note: full resource name ("projects/123/locations/us-central1/metadataStores/default/artifacts/456") cannot be used.
             enable_caching (bool):
                 Optional. Whether to turn on caching for the run.
 
@@ -235,6 +239,8 @@ def __init__(
         )
         builder.update_pipeline_root(pipeline_root)
         builder.update_runtime_parameters(parameter_values)
+        builder.update_input_artifacts(input_artifacts)
+
         builder.update_failure_policy(failure_policy)
         runtime_config_dict = builder.build()
 
@@ -662,6 +668,7 @@ def clone(
         job_id: Optional[str] = None,
         pipeline_root: Optional[str] = None,
         parameter_values: Optional[Dict[str, Any]] = None,
+        input_artifacts: Optional[Dict[str, str]] = None,
         enable_caching: Optional[bool] = None,
         encryption_spec_key_name: Optional[str] = None,
         labels: Optional[Dict[str, str]] = None,
@@ -685,6 +692,9 @@ def clone(
                 Optional. The mapping from runtime parameter names to its values that
                 control the pipeline run. Defaults to be the same values as original
                 PipelineJob.
+            input_artifacts (Dict[str, str]):
+                Optional. The mapping from the runtime parameter name for this artifact to its resource id. Defaults to be the same values as original
+                PipelineJob. For example: "vertex_model":"456". Note: full resource name ("projects/123/locations/us-central1/metadataStores/default/artifacts/456") cannot be used.
             enable_caching (bool):
                 Optional. Whether to turn on caching for the run.
                 If this is not set, defaults to be the same as original pipeline.
@@ -785,6 +795,7 @@ def clone(
         )
         builder.update_pipeline_root(pipeline_root)
         builder.update_runtime_parameters(parameter_values)
+        builder.update_input_artifacts(input_artifacts)
         runtime_config_dict = builder.build()
         runtime_config = gca_pipeline_job.PipelineJob.RuntimeConfig()._pb
         json_format.ParseDict(runtime_config_dict, runtime_config)
@@ -805,6 +816,7 @@ def from_pipeline_func(
         # Parameters for the PipelineJob constructor
         pipeline_func: Callable,
         parameter_values: Optional[Dict[str, Any]] = None,
+        input_artifacts: Optional[Dict[str, str]] = None,
         output_artifacts_gcs_dir: Optional[str] = None,
         enable_caching: Optional[bool] = None,
         context_name: Optional[str] = "pipeline",
@@ -827,6 +839,8 @@ def from_pipeline_func(
             parameter_values (Dict[str, Any]):
                 Optional. The mapping from runtime parameter names to its values that
                 control the pipeline run.
+            input_artifacts (Dict[str, str]):
+                Optional. The mapping from the runtime parameter name for this artifact to its resource id. For example: "vertex_model":"456". Note: full resource name ("projects/123/locations/us-central1/metadataStores/default/artifacts/456") cannot be used.
             output_artifacts_gcs_dir (str):
                 Optional. The GCS location of the pipeline outputs.
                 A GCS bucket for artifacts will be created if not specified.
@@ -907,6 +921,7 @@ def from_pipeline_func(
         pipeline_job = PipelineJob(
             template_path=pipeline_file,
             parameter_values=parameter_values,
+            input_artifacts=input_artifacts,
             pipeline_root=output_artifacts_gcs_dir,
             enable_caching=enable_caching,
             display_name=display_name,

google/cloud/aiplatform/utils/pipeline_utils.py

@@ -33,6 +33,7 @@ def __init__(
         schema_version: str,
         parameter_types: Mapping[str, str],
         parameter_values: Optional[Dict[str, Any]] = None,
+        input_artifacts: Optional[Dict[str, str]] = None,
         failure_policy: Optional[pipeline_failure_policy.PipelineFailurePolicy] = None,
     ):
         """Creates a PipelineRuntimeConfigBuilder object.
@@ -46,6 +47,8 @@ def __init__(
               Required. The mapping from pipeline parameter name to its type.
           parameter_values (Dict[str, Any]):
               Optional. The mapping from runtime parameter name to its value.
+          input_artifacts (Dict[str, str]):
+              Optional. The mapping from the runtime parameter name for this artifact to its resource id.
           failure_policy (pipeline_failure_policy.PipelineFailurePolicy):
               Optional. Represents the failure policy of a pipeline. Currently, the
               default of a pipeline is that the pipeline will continue to
@@ -59,6 +62,7 @@ def __init__(
         self._schema_version = schema_version
         self._parameter_types = parameter_types
         self._parameter_values = copy.deepcopy(parameter_values or {})
+        self._input_artifacts = copy.deepcopy(input_artifacts or {})
         self._failure_policy = failure_policy
 
     @classmethod
@@ -129,6 +133,18 @@ def update_runtime_parameters(
                         parameters[k] = json.dumps(v)
             self._parameter_values.update(parameters)
 
+    def update_input_artifacts(
+        self, input_artifacts: Optional[Mapping[str, str]]
+    ) -> None:
+        """Merges runtime input artifacts.
+
+        Args:
+          input_artifacts (Mapping[str, str]):
+              Optional. The mapping from the runtime parameter name for this artifact to its resource id.
+        """
+        if input_artifacts:
+            self._input_artifacts.update(input_artifacts)
+
     def update_failure_policy(self, failure_policy: Optional[str] = None) -> None:
         """Merges runtime failure policy.
 
@@ -172,6 +188,9 @@ def build(self) -> Dict[str, Any]:
                 for k, v in self._parameter_values.items()
                 if v is not None
             },
+            "inputArtifacts": {
+                k: {"artifactId": v} for k, v in self._input_artifacts.items()
+            },
         }
 
         if self._failure_policy:

tests/unit/aiplatform/test_pipeline_jobs.py

@@ -74,6 +74,10 @@
     "struct_param": {"key1": 12345, "key2": 67890},
 }
 
+_TEST_PIPELINE_INPUT_ARTIFACTS = {
+    "vertex_model": "456",
+}
+
 _TEST_PIPELINE_SPEC_LEGACY_JSON = json.dumps(
     {
         "pipelineInfo": {"name": "my-pipeline"},
@@ -469,6 +473,7 @@ def test_run_call_pipeline_service_create(
             template_path=_TEST_TEMPLATE_PATH,
             job_id=_TEST_PIPELINE_JOB_ID,
             parameter_values=_TEST_PIPELINE_PARAMETER_VALUES,
+            input_artifacts=_TEST_PIPELINE_INPUT_ARTIFACTS,
             enable_caching=True,
         )
 
@@ -485,6 +490,7 @@ def test_run_call_pipeline_service_create(
         expected_runtime_config_dict = {
             "gcsOutputDirectory": _TEST_GCS_BUCKET_NAME,
             "parameterValues": _TEST_PIPELINE_PARAMETER_VALUES,
+            "inputArtifacts": {"vertex_model": {"artifactId": "456"}},
         }
         runtime_config = gca_pipeline_job.PipelineJob.RuntimeConfig()._pb
         json_format.ParseDict(expected_runtime_config_dict, runtime_config)
@@ -1475,6 +1481,7 @@ def test_clone_pipeline_job_with_all_args(
             job_id=f"cloned-{_TEST_PIPELINE_JOB_ID}",
             pipeline_root=f"cloned-{_TEST_GCS_BUCKET_NAME}",
             parameter_values=_TEST_PIPELINE_PARAMETER_VALUES,
+            input_artifacts=_TEST_PIPELINE_INPUT_ARTIFACTS,
             enable_caching=True,
             credentials=_TEST_CREDENTIALS,
             project=_TEST_PROJECT,
@@ -1490,6 +1497,7 @@ def test_clone_pipeline_job_with_all_args(
         expected_runtime_config_dict = {
             "gcsOutputDirectory": f"cloned-{_TEST_GCS_BUCKET_NAME}",
             "parameterValues": _TEST_PIPELINE_PARAMETER_VALUES,
+            "inputArtifacts": {"vertex_model": {"artifactId": "456"}},
         }
         runtime_config = gca_pipeline_job.PipelineJob.RuntimeConfig()._pb
         json_format.ParseDict(expected_runtime_config_dict, runtime_config)

tests/unit/aiplatform/test_utils.py

@@ -452,6 +452,7 @@ class TestPipelineUtils:
                 "int_param": {"intValue": 42},
                 "float_param": {"doubleValue": 3.14},
             },
+            "inputArtifacts": {},
         },
     }
 
@@ -539,6 +540,7 @@ def test_pipeline_utils_runtime_config_builder_with_merge_updates(
                 "list_param": {"stringValue": "[1, 2, 3]"},
                 "bool_param": {"stringValue": "true"},
             },
+            "inputArtifacts": {},
             "failurePolicy": failure_policy[1],
         }
         assert expected_runtime_config == actual_runtime_config