fix: possible confusion on when to wait for the email notification

.cloud-build/execute_notebook_helper.py

@@ -26,9 +26,6 @@ from utils import util
 
 # This script is used to execute a notebook and write out the output notebook.
 
-# This is used to force papermill to use this kernel to run the notebook instead of any defined inside the notebook itself
-DEFAULT_KERNEL_NAME = "python3"
-
 
 def execute_notebook(
     notebook_source: str,
@@ -53,11 +50,14 @@ def execute_notebook(
 
     execution_exception = None
 
+
     print("\n=== DOWNLOAD EXECUTED NOTEBOOK ===\n")
-    print(f"Please debug the executed notebook by downloading the executed notebook:")
+    print(
+                f"Please debug the executed notebook by downloading the executed notebook:"
+            )
 
     print("Option 1. Using gsutil. Run the following command in your terminal.")
-    print(f'\tgsutil cp "{output_file_or_uri}" .')
+    print(f"\tgsutil cp \"{output_file_or_uri}\" .")
 
     print("Option 2. Using this link.")
     print(f"\thttps://storage.googleapis.com/{output_file_or_uri[5:]}")
@@ -72,7 +72,6 @@ def execute_notebook(
             output_path=notebook_source,
             progress_bar=should_log_output,
             request_save_on_cell_execute=should_log_output,
-            kernel_name=DEFAULT_KERNEL_NAME,
             log_output=should_log_output,
             stdout_file=sys.stdout if should_log_output else None,
             stderr_file=sys.stderr if should_log_output else None,

notebooks/community/ml_ops/stage6/get_started_with_matching_engine_swivel.ipynb

@@ -1068,7 +1068,7 @@
         "model = aiplatform.Model.upload(\n",
         "    display_name=\"movies_\" + TIMESTAMP,\n",
         "    artifact_uri=SAVEDMODEL_DIR,\n",
-        "    serving_container_image_uri=DEPLOY_IMAGE,\n",
+        "    serving_container_image_uri=DELOY_IMAGE,\n",
         ")"
       ]
     },

notebooks/official/matching_engine/intro-swivel.ipynb

@@ -214,7 +214,7 @@
         "if not os.getenv(\"IS_TESTING\"):\n",
         "    # Automatically restart kernel after installs\n",
         "    import IPython\n",
-        "\n",
+        "    \n",
         "    app = IPython.Application.instance()\n",
         "    app.kernel.do_shutdown(True)"
       ]
@@ -675,18 +675,6 @@
         "!./swivel_template_configuration.sh -pipeline_suffix {YOUR_PIPELINE_SUFFIX} -project_number {PROJECT_NUMBER} -project_id {PROJECT_ID} -machine_type {MACHINE_TYPE} -accelerator_count {ACCELERATOR_COUNT} -accelerator_type {ACCELERATOR_TYPE} -pipeline_root {BUCKET}"
       ]
     },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "1cacea95d68c"
-      },
-      "outputs": [],
-      "source": [
-        "! sed \"s:\\t:    :g\" swivel_pipeline_basic.json >tmp.json\n",
-        "! mv tmp.json swivel_pipeline_basic.json"
-      ]
-    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -777,15 +765,19 @@
         "# Instantiate PipelineJob object\n",
         "pl = aiplatform.PipelineJob(\n",
         "    display_name=YOUR_PIPELINE_SUFFIX,\n",
+        "\n",
         "    # Whether or not to enable caching\n",
         "    # True = always cache pipeline step result\n",
         "    # False = never cache pipeline step result\n",
         "    # None = defer to cache option for each pipeline component in the pipeline definition\n",
         "    enable_caching=False,\n",
+        "\n",
         "    # Local or GCS path to a compiled pipeline definition\n",
         "    template_path=\"swivel_pipeline_basic.json\",\n",
+        "\n",
         "    # Dictionary containing input parameters for your pipeline\n",
         "    parameter_values=PARAMETER_VALUES,\n",
+        "\n",
         "    # GCS path to act as the pipeline root\n",
         "    pipeline_root=PIPELINE_ROOT,\n",
         ")\n",