chore: fix sample and integration tests (googleapis#1432)

Removes metadata integration tests which supported Preview experiment creation.

Author: sasha-gitg

.github/CODEOWNERS

@@ -3,29 +3,10 @@
 #
 # For syntax help see:
 # https://help.github.com/en/github/creating-cloning-and-archiving-repositories/about-code-owners#codeowners-syntax
+# Note: This file is autogenerated. To make changes to the codeowner team, please update .repo-metadata.json.
 
-# @googleapis/cdpe-cloudai and yoshi-python are the default owners
-*                                      @googleapis/cdpe-cloudai @googleapis/yoshi-python
+# @googleapis/yoshi-python is the default owner for changes in this repo
+*     @googleapis/yoshi-python
 
-# The AI Platform GAPIC libraries are owned by Cloud AI DPE
-/google/cloud/aiplatform_*/**          @googleapis/cdpe-cloudai
-
-# The Vertex SDK is owned by Vertex SDK Dev team
-/google/cloud/aiplatform/**            @googleapis/cloud-aiplatform-model-builder-sdk
-/tests/system/aiplatform/**            @googleapis/cloud-aiplatform-model-builder-sdk
-/tests/unit/aiplatform/**              @googleapis/cloud-aiplatform-model-builder-sdk
-
-# The Cloud AI DPE team is the default owner for samples
-/samples/**/*.py                       @googleapis/cdpe-cloudai @googleapis/python-samples-reviewers
-/.sample_configs/**                    @googleapis/cdpe-cloudai
-
-# The enhanced client library tests are owned by Cloud AI DPE
-/tests/unit/enhanced_library/*.py      @googleapis/cdpe-cloudai
-
-# Core library files owned by Cloud AI DPE and Vertex SDK Dev teams
-CHANGELOG.md                           @googleapis/cloud-aiplatform-model-builder-sdk @googleapis/cdpe-cloudai
-README.rst                             @googleapis/cloud-aiplatform-model-builder-sdk @googleapis/cdpe-cloudai
-setup.py                               @googleapis/cloud-aiplatform-model-builder-sdk @googleapis/cdpe-cloudai
-
-# Vertex AI product team-specific ownership
-/google/cloud/aiplatform/constants/prediction.py                        @googleapis/vertex-prediction-team
+# @googleapis/python-samples-reviewers is the default owner for samples changes
+/samples/   @googleapis/python-samples-reviewers

.kokoro/samples/python3.7/periodic.cfg

@@ -2,5 +2,5 @@
 
 env_vars: {
     key: "INSTALL_LIBRARY_FROM_SOURCE"
-    value: "False"
+    value: "True"
 }

.kokoro/samples/python3.8/periodic.cfg

@@ -2,5 +2,5 @@
 
 env_vars: {
     key: "INSTALL_LIBRARY_FROM_SOURCE"
-    value: "False"
+    value: "True"
 }

google/cloud/aiplatform/metadata/experiment_run_resource.py

@@ -118,7 +118,12 @@ def __init__(
                 credentials set in aiplatform.init.
         """
 
-        self._experiment = self._get_experiment(experiment=experiment)
+        self._experiment = self._get_experiment(
+            experiment=experiment,
+            project=project,
+            location=location,
+            credentials=credentials,
+        )
         self._run_name = run_name
 
         run_id = _format_experiment_run_resource_id(

google/cloud/aiplatform/metadata/resource.py

@@ -218,7 +218,7 @@ def _nested_update_metadata(
             if gca_resource.metadata:
                 for key, value in metadata.items():
                     # Note: This only support nested dictionaries one level deep
-                    if isinstance(value, collections.Mapping):
+                    if isinstance(value, collections.abc.Mapping):
                         gca_resource.metadata[key].update(value)
                     else:
                         gca_resource.metadata[key] = value

owlbot.py

@@ -98,6 +98,13 @@
         ".coveragerc",
         ".kokoro/continuous/common.cfg",
         ".kokoro/presubmit/presubmit.cfg",
+        # exclude sample configs so periodic samples are tested against main
+        # instead of pypi
+        ".kokoro/samples/python3.6/periodic.cfg",
+        ".kokoro/samples/python3.7/periodic.cfg",
+        ".kokoro/samples/python3.8/periodic.cfg",
+        ".kokoro/samples/python3.9/periodic.cfg",
+        ".kokoro/samples/python3.10/periodic.cfg",
         ".github/CODEOWNERS",
         ".github/workflows",  # exclude gh actions as credentials are needed for tests
     ],

samples/model-builder/experiment_tracking/assign_artifact_as_execution_input_sample.py

@@ -21,6 +21,4 @@ def assign_artifact_as_execution_input_sample(
     artifact: aiplatform.Artifact,
 ):
     execution.assign_input_artifacts([artifact])
-
-
 #  [END aiplatform_sdk_assign_artifact_as_execution_input_sample]

samples/model-builder/requirements.txt

@@ -1 +1 @@
-google-cloud-aiplatform
+google-cloud-aiplatform

setup.py

@@ -72,7 +72,7 @@
 testing_extra_require = (
     full_extra_require
     + profiler_extra_require
-    + ["grpcio-testing", "pytest-xdist", "ipython"]
+    + ["grpcio-testing", "pytest-xdist", "ipython", "kfp"]
 )
 
 

tests/system/aiplatform/test_experiments.py

@@ -46,8 +46,8 @@ class TestExperiments(e2e_base.TestEndToEnd):
     _temp_prefix = "tmpvrtxsdk-e2e"
 
     def setup_class(cls):
-        cls._experiment_name = cls._make_display_name("experiment")[:30]
-        cls._dataset_artifact_name = cls._make_display_name("ds-artifact")[:30]
+        cls._experiment_name = cls._make_display_name("")[:64]
+        cls._dataset_artifact_name = cls._make_display_name("")[:64]
         cls._dataset_artifact_uri = cls._make_display_name("ds-uri")
         cls._pipeline_job_id = cls._make_display_name("job-id")
 
@@ -74,29 +74,63 @@ def test_create_experiment(self, shared_state):
         )
 
     def test_get_experiment(self):
-        experiment = aiplatform.Experiment(experiment_name=self._experiment_name)
+        experiment = aiplatform.Experiment(
+            experiment_name=self._experiment_name,
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+        )
         assert experiment.name == self._experiment_name
 
     def test_start_run(self):
+        aiplatform.init(
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+            experiment=self._experiment_name,
+        )
         run = aiplatform.start_run(_RUN)
         assert run.name == _RUN
 
     def test_get_run(self):
-        run = aiplatform.ExperimentRun(run_name=_RUN, experiment=self._experiment_name)
+        run = aiplatform.ExperimentRun(
+            run_name=_RUN,
+            experiment=self._experiment_name,
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+        )
         assert run.name == _RUN
         assert run.state == aiplatform.gapic.Execution.State.RUNNING
 
     def test_log_params(self):
+        aiplatform.init(
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+            experiment=self._experiment_name,
+        )
+        aiplatform.start_run(_RUN, resume=True)
         aiplatform.log_params(_PARAMS)
         run = aiplatform.ExperimentRun(run_name=_RUN, experiment=self._experiment_name)
         assert run.get_params() == _PARAMS
 
     def test_log_metrics(self):
+        aiplatform.init(
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+            experiment=self._experiment_name,
+        )
+        aiplatform.start_run(_RUN, resume=True)
         aiplatform.log_metrics(_METRICS)
         run = aiplatform.ExperimentRun(run_name=_RUN, experiment=self._experiment_name)
         assert run.get_metrics() == _METRICS
 
     def test_log_time_series_metrics(self):
+        aiplatform.init(
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+            experiment=self._experiment_name,
+        )
+
+        aiplatform.start_run(_RUN, resume=True)
+
         for i in range(5):
             aiplatform.log_time_series_metrics({_TIME_SERIES_METRIC_KEY: i})
 
@@ -116,26 +150,41 @@ def test_create_artifact(self, shared_state):
             schema_title="system.Dataset",
             resource_id=self._dataset_artifact_name,
             uri=self._dataset_artifact_uri,
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
         )
 
         shared_state["resources"].append(ds)
         assert ds.uri == self._dataset_artifact_uri
 
     def test_get_artifact_by_uri(self):
-        ds = aiplatform.Artifact.get_with_uri(uri=self._dataset_artifact_uri)
+        ds = aiplatform.Artifact.get_with_uri(
+            uri=self._dataset_artifact_uri,
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+        )
 
         assert ds.uri == self._dataset_artifact_uri
         assert ds.name == self._dataset_artifact_name
 
     def test_log_execution_and_artifact(self, shared_state):
+        aiplatform.init(
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+            experiment=self._experiment_name,
+        )
+        aiplatform.start_run(_RUN, resume=True)
+
         with aiplatform.start_execution(
             schema_title="system.ContainerExecution",
             resource_id=self._make_display_name("execution"),
         ) as execution:
 
             shared_state["resources"].append(execution)
 
-            ds = aiplatform.Artifact(artifact_name=self._dataset_artifact_name)
+            ds = aiplatform.Artifact(
+                artifact_name=self._dataset_artifact_name,
+            )
             execution.assign_input_artifacts([ds])
 
             model = aiplatform.Artifact.create(schema_title="system.Model")
@@ -188,11 +237,22 @@ def test_log_execution_and_artifact(self, shared_state):
         )
 
     def test_end_run(self):
+        aiplatform.init(
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+            experiment=self._experiment_name,
+        )
+        aiplatform.start_run(_RUN, resume=True)
         aiplatform.end_run()
         run = aiplatform.ExperimentRun(run_name=_RUN, experiment=self._experiment_name)
         assert run.state == aiplatform.gapic.Execution.State.COMPLETE
 
     def test_run_context_manager(self):
+        aiplatform.init(
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+            experiment=self._experiment_name,
+        )
         with aiplatform.start_run(_RUN_2) as run:
             run.log_params(_PARAMS_2)
             run.log_metrics(_METRICS_2)
@@ -226,15 +286,25 @@ def pipeline(learning_rate: float, dropout_rate: float):
             job_id=self._pipeline_job_id,
             pipeline_root=f'gs://{shared_state["staging_bucket_name"]}',
             parameter_values={"learning_rate": 0.1, "dropout_rate": 0.2},
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
         )
 
-        job.submit(experiment=self._experiment_name)
+        job.submit(
+            experiment=self._experiment_name,
+        )
 
         shared_state["resources"].append(job)
 
         job.wait()
 
     def test_get_experiments_df(self):
+        aiplatform.init(
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+            experiment=self._experiment_name,
+        )
+
         df = aiplatform.get_experiment_df()
 
         pipelines_param_and_metrics = {
@@ -264,8 +334,6 @@ def test_get_experiments_df(self):
         true_df_dict_2["run_type"] = aiplatform.metadata.constants.SYSTEM_EXPERIMENT_RUN
         true_df_dict_2[f"time_series_metric.{_TIME_SERIES_METRIC_KEY}"] = 0.0
 
-        # TODO(remove when running CI)
-
         true_df_dict_3 = {
             "experiment_name": self._experiment_name,
             "run_name": self._pipeline_job_id,
@@ -292,14 +360,23 @@ def test_get_experiments_df(self):
         ) == sorted(df.fillna(0.0).to_dict("records"), key=lambda d: d["run_name"])
 
     def test_delete_run(self):
-        run = aiplatform.ExperimentRun(run_name=_RUN, experiment=self._experiment_name)
+        run = aiplatform.ExperimentRun(
+            run_name=_RUN,
+            experiment=self._experiment_name,
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+        )
         run.delete(delete_backing_tensorboard_run=True)
 
         with pytest.raises(exceptions.NotFound):
             aiplatform.ExperimentRun(run_name=_RUN, experiment=self._experiment_name)
 
     def test_delete_experiment(self):
-        experiment = aiplatform.Experiment(experiment_name=self._experiment_name)
+        experiment = aiplatform.Experiment(
+            experiment_name=self._experiment_name,
+            project=e2e_base._PROJECT,
+            location=e2e_base._LOCATION,
+        )
         experiment.delete(delete_backing_tensorboard_runs=True)
 
         with pytest.raises(exceptions.NotFound):