port: kfp2

notebooks/official/pipelines/google_cloud_pipeline_components_automl_tabular.ipynb

@@ -152,8 +152,8 @@
       "source": [
         "! pip3 install --upgrade --quiet google-cloud-aiplatform \\\n",
         "                                 google-cloud-storage \\\n",
-        "                                 'kfp<2' \\\n",
-        "                                 'google-cloud-pipeline-components<2'"
+        "                                 kfp \\\n",
+        "                                 google-cloud-pipeline-components"
       ]
     },
     {
@@ -379,7 +379,7 @@
       },
       "outputs": [],
       "source": [
-        "! gsutil mb -l $REGION -p $PROJECT_ID $BUCKET_URI"
+        "! gsutil mb -l {REGION} -p {PROJECT_ID} {BUCKET_URI}"
       ]
     },
     {
@@ -556,15 +556,18 @@
         "\n",
         "@kfp.dsl.pipeline(name=\"automl-tab-training-v2\")\n",
         "def pipeline(project: str = PROJECT_ID, region: str = REGION):\n",
-        "    from google_cloud_pipeline_components import aiplatform as gcc_aip\n",
+        "    from google_cloud_pipeline_components.v1.automl.training_job import \\\n",
+        "        AutoMLTabularTrainingJobRunOp\n",
+        "    from google_cloud_pipeline_components.v1.dataset import \\\n",
+        "        TabularDatasetCreateOp\n",
         "    from google_cloud_pipeline_components.v1.endpoint import (EndpointCreateOp,\n",
         "                                                              ModelDeployOp)\n",
         "\n",
-        "    dataset_create_op = gcc_aip.TabularDatasetCreateOp(\n",
+        "    dataset_create_op = TabularDatasetCreateOp(\n",
         "        project=project, display_name=\"housing\", gcs_source=gcs_csv_path\n",
         "    )\n",
         "\n",
-        "    training_op = gcc_aip.AutoMLTabularTrainingJobRunOp(\n",
+        "    training_op = AutoMLTabularTrainingJobRunOp(\n",
         "        project=project,\n",
         "        display_name=\"train-automl-cal_housing\",\n",
         "        optimization_prediction_type=\"regression\",\n",
@@ -622,7 +625,7 @@
         "\n",
         "compiler.Compiler().compile(\n",
         "    pipeline_func=pipeline,\n",
-        "    package_path=\"tabular_regression_pipeline.json\",\n",
+        "    package_path=\"tabular_regression_pipeline.yaml\",\n",
         ")"
       ]
     },
@@ -649,14 +652,14 @@
         "\n",
         "job = aip.PipelineJob(\n",
         "    display_name=DISPLAY_NAME,\n",
-        "    template_path=\"tabular_regression_pipeline.json\",\n",
+        "    template_path=\"tabular_regression_pipeline.yaml\",\n",
         "    pipeline_root=PIPELINE_ROOT,\n",
         "    enable_caching=False,\n",
         ")\n",
         "\n",
         "job.run()\n",
         "\n",
-        "! rm tabular_regression_pipeline.json"
+        "! rm tabular_regression_pipeline.yaml"
       ]
     },
     {