Merge branch 'main' into sara-pipelines-update

notebooks/official/pipelines/automl_tabular_classification_beans.ipynb

@@ -256,7 +256,7 @@
         "id": "check_versions"
       },
       "source": [
-        "Check the versions of the packages you installed.  The KFP SDK version should be >=1.6."
+        "Check the versions of the packages you installed.  The KFP SDK version should be >=1.8."
       ]
     },
     {
@@ -745,7 +745,7 @@
       "outputs": [],
       "source": [
         "@component(\n",
-        "    base_image=\"gcr.io/deeplearning-platform-release/tf2-cpu.2-3:latest\",\n",
+        "    base_image=\"gcr.io/deeplearning-platform-release/tf2-cpu.2-6:latest\",\n",
         "    output_component_file=\"tabular_eval_component.yaml\",\n",
         "    packages_to_install=[\"google-cloud-aiplatform\"],\n",
         ")\n",
@@ -902,25 +902,25 @@
         "        optimization_prediction_type=\"classification\",\n",
         "        optimization_objective=\"minimize-log-loss\",\n",
         "        budget_milli_node_hours=1000,\n",
-        "        column_transformations=[\n",
-        "            {\"numeric\": {\"column_name\": \"Area\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"Perimeter\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"MajorAxisLength\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"MinorAxisLength\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"AspectRation\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"Eccentricity\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"ConvexArea\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"EquivDiameter\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"Extent\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"Solidity\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"roundness\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"Compactness\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"ShapeFactor1\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"ShapeFactor2\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"ShapeFactor3\"}},\n",
-        "            {\"numeric\": {\"column_name\": \"ShapeFactor4\"}},\n",
-        "            {\"categorical\": {\"column_name\": \"Class\"}},\n",
-        "        ],\n",
+        "        column_specs={\n",
+        "            \"Area\": \"numeric\",\n",
+        "            \"Perimeter\": \"numeric\",\n",
+        "            \"MajorAxisLength\": \"numeric\",\n",
+        "            \"MinorAxisLength\": \"numeric\",\n",
+        "            \"AspectRation\": \"numeric\",\n",
+        "            \"Eccentricity\": \"numeric\",\n",
+        "            \"ConvexArea\": \"numeric\",\n",
+        "            \"EquivDiameter\": \"numeric\",\n",
+        "            \"Extent\": \"numeric\",\n",
+        "            \"Solidity\": \"numeric\",\n",
+        "            \"roundness\": \"numeric\",\n",
+        "            \"Compactness\": \"numeric\",\n",
+        "            \"ShapeFactor1\": \"numeric\",\n",
+        "            \"ShapeFactor2\": \"numeric\",\n",
+        "            \"ShapeFactor3\": \"numeric\",\n",
+        "            \"ShapeFactor4\": \"numeric\",\n",
+        "            \"Class\": \"categorical\",\n",
+        "        },\n",
         "        dataset=dataset_create_op.outputs[\"dataset\"],\n",
         "        target_column=\"Class\",\n",
         "    )\n",
@@ -1007,7 +1007,7 @@
         "    parameter_values={\"project\": PROJECT_ID, \"display_name\": DISPLAY_NAME},\n",
         ")\n",
         "\n",
-        "job.run()\n",
+        "job.submit()\n",
         "\n",
         "! rm tabular_classification_pipeline.json"
       ]