Check for failed pipeline. (Azure#2013)

Co-authored-by: Nikolay Rovinskiy <[email protected]>

Author: nick863

sdk/python/jobs/pipelines/1h_automl_in_pipeline/automl-forecasting-in-pipeline/automl-forecasting-in-pipeline.ipynb

@@ -488,18 +488,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[2022-10-28 05:20:59Z] Completing processing run id 82ef9376-93e3-4678-bc8c-d3421870363c.\n",
-      "[2022-10-28 05:21:00Z] Submitting 1 runs, first five are: c1f85bd1:0bd3ed1c-ebb5-4f5f-a0bc-18500d18e26e\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# Wait until the job completes\n",
     "ml_client.jobs.stream(pipeline_job.name)"
@@ -617,6 +608,7 @@
    "outputs": [],
    "source": [
     "import re\n",
+    "from mlflow.entities import RunStatus\n",
     "\n",
     "parent_run_id = ml_model[\"run_id\"][: ml_model[\"run_id\"].index(\"_\")]\n",
     "child_run_regex = re.compile(r\"[^_]+_\\d+$\")\n",
@@ -625,10 +617,12 @@
     "    lambda x: child_run_regex.match(x.name),\n",
     "    ml_client.jobs.list(parent_job_name=parent_run_id),\n",
     "):\n",
-    "    print(\n",
-    "        f\"{child_run.name}: \"\n",
-    "        f'{mlflow_client.get_run(child_run.name).data.metrics[\"normalized_root_mean_squared_error\"]}'\n",
-    "    )"
+    "    mlflow_child_run = mlflow_client.get_run(child_run.name)\n",
+    "    if RunStatus.from_string(mlflow_child_run.info.status) == RunStatus.FINISHED:\n",
+    "        print(\n",
+    "            f\"{child_run.name}: \"\n",
+    "            f'{mlflow_child_run.data.metrics[\"normalized_root_mean_squared_error\"]}'\n",
+    "        )"
    ]
   },
   {