Prevent notebook execution failure by avoiding mlclient private field… (#3327)

* Prevent notebook execution failure by avoiding mlclient private field access warning

* Take changes from Kevin's PR for blocking workflows

* update notebooks

* update flakes

* revert failing notebooks

* Revert "revert failing notebooks"

This reverts commit 14f3163.

* restore failing notebook to main commit

* Update

Author: novaturient95

.github/workflows/sdk-jobs-automl-standalone-jobs-automl-forecasting-distributed-tcn-automl-forecasting-distributed-tcn.yml

@@ -69,6 +69,14 @@ jobs:
           source "${{ github.workspace }}/infra/bootstrapping/init_environment.sh";
           bash setup.sh
       working-directory: cli
+    - name: Eagerly cache access tokens for required scopes
+      run: |
+          # Workaround for azure-cli's lack of support for ID token refresh
+          # Taken from: https://github.com/Azure/login/issues/372#issuecomment-2056289617
+          # Management
+          az account get-access-token --scope https://management.azure.com/.default --output none
+          # ML
+          az account get-access-token --scope https://ml.azure.com/.default --output none
       continue-on-error: true
     - name: Eagerly cache access tokens for required scopes
       run: |

sdk/python/jobs/automl-standalone-jobs/automl-classification-task-bankmarketing/automl-classification-task-bankmarketing-serverless.ipynb

@@ -9,7 +9,7 @@
     "**Requirements** - In order to benefit from this tutorial, you will need:\n",
     "- A basic understanding of Machine Learning\n",
     "- An Azure account with an active subscription. [Create an account for free](https://azure.microsoft.com/free/?WT.mc_id=A261C142F)\n",
-    "- An Azure ML workspace. [Check this notebook for creating a workspace](../../../resources/workspace/workspace.ipynb) \n",    
+    "- An Azure ML workspace. [Check this notebook for creating a workspace](../../../resources/workspace/workspace.ipynb) \n",
     "- A python environment\n",
     "- Installed Azure Machine Learning Python SDK v2 - [install instructions](../../../README.md) - check the getting started section\n",
     "\n",
@@ -120,7 +120,7 @@
    "source": [
     "workspace = ml_client.workspaces.get(name=ml_client.workspace_name)\n",
     "\n",
-    "subscription_id = ml_client.connections._subscription_id\n",
+    "subscription_id = ml_client.subscription_id\n",
     "resource_group = workspace.resource_group\n",
     "workspace_name = ml_client.workspace_name\n",
     "\n",
@@ -230,7 +230,7 @@
     "# Create the AutoML classification job with the related factory-function.\n",
     "from azure.ai.ml.entities import ResourceConfiguration \n",
     "\n",
-    "classification_job = automl.classification(\n",    
+    "classification_job = automl.classification(\n",
     "    experiment_name=exp_name,\n",
     "    training_data=my_training_data_input,\n",
     "    target_column_name=\"y\",\n",

sdk/python/jobs/automl-standalone-jobs/automl-classification-task-bankmarketing/automl-classification-task-bankmarketing.ipynb

@@ -122,7 +122,7 @@
    "source": [
     "workspace = ml_client.workspaces.get(name=ml_client.workspace_name)\n",
     "\n",
-    "subscription_id = ml_client.connections._subscription_id\n",
+    "subscription_id = ml_client.subscription_id\n",
     "resource_group = workspace.resource_group\n",
     "workspace_name = ml_client.workspace_name\n",
     "\n",

sdk/python/jobs/automl-standalone-jobs/automl-forecasting-distributed-tcn/automl-forecasting-distributed-tcn.ipynb

@@ -53,6 +53,16 @@
     "Make sure you have executed the [configuration](https://github.com/Azure/MachineLearningNotebooks/blob/master/configuration.ipynb) before running this notebook."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install azure-ai-ml==1.8.0\n",
+    "%pip install azure-identity==1.13.0"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -162,7 +172,7 @@
     "\n",
     "output = {}\n",
     "output[\"Workspace\"] = ml_client.workspace_name\n",
-    "output[\"Subscription ID\"] = ml_client.connections._subscription_id\n",
+    "output[\"Subscription ID\"] = ml_client.subscription_id\n",
     "output[\"Resource Group\"] = ws.resource_group\n",
     "output[\"Location\"] = ws.location\n",
     "pd.DataFrame(data=output, index=[\"\"]).T"
@@ -673,7 +683,7 @@
    "outputs": [],
    "source": [
     "inference_component = ml_client_registry.components.get(\n",
-    "    name=\"automl_forecasting_inference\", label=\"latest\"\n",
+    "    name=\"automl_forecasting_inference\"\n",
     ")\n",
     "print(f\"Inference component version: {inference_component.version}\\n---\")"
    ]
@@ -684,10 +694,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "compute_metrics_component = ml_client_registry.components.get(\n",
-    "    name=\"compute_metrics\",\n",
-    "    version=\"0.0.26\",  # label=\"latest\"\n",
-    ")\n",
+    "compute_metrics_component = ml_client_registry.components.get(name=\"compute_metrics\")\n",
     "print(f\"Compute metrics component version: {compute_metrics_component.version}\\n---\")"
    ]
   },

sdk/python/jobs/automl-standalone-jobs/automl-forecasting-github-dau/auto-ml-forecasting-github-dau.ipynb

@@ -138,7 +138,7 @@
     "\n",
     "output = {}\n",
     "output[\"Workspace\"] = ml_client.workspace_name\n",
-    "output[\"Subscription ID\"] = ml_client.connections._subscription_id\n",
+    "output[\"Subscription ID\"] = ml_client.subscription_id\n",
     "output[\"Resource Group\"] = workspace.resource_group\n",
     "output[\"Location\"] = workspace.location\n",
     "output"

sdk/python/jobs/automl-standalone-jobs/automl-forecasting-orange-juice-sales/automl-forecasting-orange-juice-sales-mlflow.ipynb

@@ -119,7 +119,7 @@
     "\n",
     "output = {}\n",
     "output[\"Workspace\"] = ml_client.workspace_name\n",
-    "output[\"Subscription ID\"] = ml_client.connections._subscription_id\n",
+    "output[\"Subscription ID\"] = ml_client.subscription_id\n",
     "output[\"Resource Group\"] = workspace.resource_group\n",
     "output[\"Location\"] = workspace.location\n",
     "pd.set_option(\"display.max_colwidth\", None)\n",

sdk/python/jobs/automl-standalone-jobs/automl-forecasting-recipes-univariate/automl-forecasting-recipe-univariate-run.ipynb

@@ -162,7 +162,7 @@
     "\n",
     "output = {}\n",
     "output[\"Workspace\"] = ml_client.workspace_name\n",
-    "output[\"Subscription ID\"] = ml_client.connections._subscription_id\n",
+    "output[\"Subscription ID\"] = ml_client.subscription_id\n",
     "output[\"Resource Group\"] = workspace.resource_group\n",
     "output[\"Location\"] = workspace.location\n",
     "output"

sdk/python/jobs/automl-standalone-jobs/automl-forecasting-task-bike-share/auto-ml-forecasting-bike-share.ipynb

@@ -120,7 +120,7 @@
     "\n",
     "output = {}\n",
     "output[\"Workspace\"] = ml_client.workspace_name\n",
-    "output[\"Subscription ID\"] = ml_client.connections._subscription_id\n",
+    "output[\"Subscription ID\"] = ml_client.subscription_id\n",
     "output[\"Resource Group\"] = workspace.resource_group\n",
     "output[\"Location\"] = workspace.location\n",
     "pd.set_option(\"display.max_colwidth\", None)\n",

sdk/python/jobs/automl-standalone-jobs/automl-forecasting-task-energy-demand/automl-forecasting-task-energy-demand-advanced-mlflow.ipynb

@@ -120,7 +120,7 @@
     "\n",
     "output = {}\n",
     "output[\"Workspace\"] = ml_client.workspace_name\n",
-    "output[\"Subscription ID\"] = ml_client.connections._subscription_id\n",
+    "output[\"Subscription ID\"] = ml_client.subscription_id\n",
     "output[\"Resource Group\"] = workspace.resource_group\n",
     "output[\"Location\"] = workspace.location\n",
     "pd.set_option(\"display.max_colwidth\", None)\n",

sdk/python/jobs/automl-standalone-jobs/automl-forecasting-task-energy-demand/automl-forecasting-task-energy-demand-advanced.ipynb

@@ -116,7 +116,7 @@
     "\n",
     "output = {}\n",
     "output[\"Workspace\"] = ml_client.workspace_name\n",
-    "output[\"Subscription ID\"] = ml_client.connections._subscription_id\n",
+    "output[\"Subscription ID\"] = ml_client.subscription_id\n",
     "output[\"Resource Group\"] = workspace.resource_group\n",
     "output[\"Location\"] = workspace.location\n",
     "output"

sdk/python/jobs/automl-standalone-jobs/automl-regression-task-hardware-performance/automl-regression-task-hardware-performance.ipynb

@@ -110,7 +110,7 @@
    "source": [
     "workspace = ml_client.workspaces.get(name=ml_client.workspace_name)\n",
     "\n",
-    "subscription_id = ml_client.connections._subscription_id\n",
+    "subscription_id = ml_client.subscription_id\n",
     "resource_group = workspace.resource_group\n",
     "workspace_name = ml_client.workspace_name\n",
     "\n",

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

@@ -136,7 +136,7 @@
     "\n",
     "output = {}\n",
     "output[\"Workspace\"] = ml_client.workspace_name\n",
-    "output[\"Subscription ID\"] = ml_client.connections._subscription_id\n",
+    "output[\"Subscription ID\"] = ml_client.subscription_id\n",
     "output[\"Resource Group\"] = workspace.resource_group\n",
     "output[\"Location\"] = workspace.location\n",
     "pd.set_option(\"display.max_colwidth\", None)\n",

sdk/python/jobs/pipelines/1k_demand_forecast_pipeline/aml-demand-forecast-hts-pipeline/aml-demand-forecast-hts.ipynb

@@ -151,7 +151,7 @@
     "\n",
     "output = {}\n",
     "output[\"Workspace\"] = ml_client.workspace_name\n",
-    "output[\"Subscription ID\"] = ml_client.connections._subscription_id\n",
+    "output[\"Subscription ID\"] = ml_client.subscription_id\n",
     "output[\"Resource Group\"] = ws.resource_group\n",
     "output[\"Location\"] = ws.location\n",
     "pd.DataFrame(data=output, index=[\"\"]).T"

sdk/python/jobs/pipelines/1k_demand_forecast_pipeline/aml-demand-forecast-mm-pipeline/aml-demand-forecast-mm-pipeline.ipynb

@@ -150,7 +150,7 @@
     "\n",
     "output = {}\n",
     "output[\"Workspace\"] = ml_client.workspace_name\n",
-    "output[\"Subscription ID\"] = ml_client.connections._subscription_id\n",
+    "output[\"Subscription ID\"] = ml_client.subscription_id\n",
     "output[\"Resource Group\"] = ws.resource_group\n",
     "output[\"Location\"] = ws.location\n",
     "pd.DataFrame(data=output, index=[\"\"]).T"