From e550651ec10c58ce1823bcd4c32f43430eaf17ad Mon Sep 17 00:00:00 2001 From: Hyunsu Cho Date: Thu, 28 Sep 2023 17:31:41 -0700 Subject: [PATCH] Small fixes --- .../time-series-forecasting-with-hpo/notebook.ipynb | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/source/examples/time-series-forecasting-with-hpo/notebook.ipynb b/source/examples/time-series-forecasting-with-hpo/notebook.ipynb index 6afba35b..7d1b2307 100644 --- a/source/examples/time-series-forecasting-with-hpo/notebook.ipynb +++ b/source/examples/time-series-forecasting-with-hpo/notebook.ipynb @@ -37,16 +37,18 @@ "id": "fde94ab8-123c-4a72-95db-86a2098247bb", "metadata": {}, "source": [ - "To run the example, you will need a working Google Kubernetes Engine (GKE) cluster with access to NVIDIA GPUs. Use the following resources to set up a cluster:\n", + "To run the example, you will need a working Google Kubernetes Engine (GKE) cluster with access to NVIDIA GPUs.\n", "\n", "````{docref} /cloud/gcp/gke\n", "Set up a Google Kubernetes Engine (GKE) cluster with access to NVIDIA GPUs. Follow instructions in [Google Kubernetes Engine](../../cloud/gcp/gke).\n", "````\n", "\n", - "To ensure that the example runs smoothly, ensure that you have ample memory in your GPUs. This notebook has been tested with NVIDIA A100.\n", + "1. To ensure that the example runs smoothly, ensure that you have ample memory in your GPUs. This notebook has been tested with NVIDIA A100.\n", "\n", - "* [Install the Dask-Kubernetes operator](https://kubernetes.dask.org/en/latest/operator_installation.html)\n", - "* [Install Kubeflow](https://www.kubeflow.org/docs/started/installing-kubeflow/)\n", + "2. Set up Dask-Kubernetes integration by following instructions in the following guides:\n", + "\n", + " * [Install the Dask-Kubernetes operator](https://kubernetes.dask.org/en/latest/operator_installation.html)\n", + " * [Install Kubeflow](https://www.kubeflow.org/docs/started/installing-kubeflow/)\n", "\n", "Kubeflow is not strictly necessary, but we highly recommend it, as Kubeflow gives you a nice notebook environment to run this notebook within the k8s cluster. (You may choose any method; we tested this example after installing Kubeflow from manifests.) When creating the notebook environment, use the following configuration:\n", "\n", @@ -54,7 +56,7 @@ "* 1 NVIDIA GPU\n", "* 40 GiB disk volume\n", "\n", - "After uploading all the notebooks in the example, run this notebook (`time_series_forecasting.ipynb`) in the notebook environment.\n", + "After uploading all the notebooks in the example, run this notebook (`notebook.ipynb`) in the notebook environment.\n", "\n", "Note: We will use the worker pods to speed up the training stage. The preprocessing steps will run solely on the scheduler node." ]