Sign in to your Google Cloud account. If you're new to
Google Cloud,
create an account to evaluate how our products perform in
real-world scenarios. New customers also get $300 in free credits to
run, test, and deploy workloads.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間：2025-09-04 (世界標準時間)。"],[],[],null,["# Run notebook executions with parameters\n=======================================\n\n\n| Vertex AI Workbench managed notebooks is\n| [deprecated](/vertex-ai/docs/deprecations). On\n| April 14, 2025, support for\n| managed notebooks will end and the ability to create managed notebooks instances\n| will be removed. Existing instances will continue to function\n| but patches, updates, and upgrades won't be available. To continue using\n| Vertex AI Workbench, we recommend that you\n| [migrate\n| your managed notebooks instances to Vertex AI Workbench instances](/vertex-ai/docs/workbench/managed/migrate-to-instances).\n\n\u003cbr /\u003e\n\nVertex AI Workbench managed notebooks instances\nlet you use parameter values in your notebook executions\nto specify differences in how your notebook file's code runs.\nThis page describes how to set up your notebook file to use parameters\nand how to run executions that specify different values\nfor your notebook parameters.\n\nUse parameters to run different iterations of your notebook file\n----------------------------------------------------------------\n\nYou can use notebook parameter values in your executions\nto run the same notebook code while specifying differences like the following:\n\n- Specify a different dataset to use, or a different sample size\n of the dataset.\n\n- Specify different model configurations such as learning rate or\n optimizer type.\n\n- Run different models, or run different versions of the same model.\n\nHow to use parameters in a notebook execution\n---------------------------------------------\n\nThe process for executing a notebook with parameters has two main steps:\n\n1. [Add the `parameters` tag to one of your notebook file's cells](#add-tag).\n While this isn't a technical requirement, this cell\n typically contains code that assigns values to your parameter\n variables, though this is not a technical requirement.\n If you don't assign different parameter values in your execution,\n the execution uses the parameter values in your notebook file\n as default values.\n\n2. [Create an execution for your notebook file that includes\n new values for your parameters](#provide-values). Use the\n following pattern to format your parameters and their values:\n `parameter1=value1,parameter2=value2`. The format requires commas\n between parameter-value pairs, no spaces, and no quotation marks.\n When your execution runs,\n the executor adds a cell to the notebook that updates the\n values of your parameters directly following the cell that\n is tagged `parameters`.\n\nBefore you begin\n----------------\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Notebooks and Vertex AI APIs.\n\n\n [Enable the APIs](https://console.cloud.google.com/flows/enableapi?apiid=notebooks.googleapis.com,aiplatform.googleapis.com)\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Notebooks and Vertex AI APIs.\n\n\n [Enable the APIs](https://console.cloud.google.com/flows/enableapi?apiid=notebooks.googleapis.com,aiplatform.googleapis.com)\n\n1. If you haven't already, [create\n a managed notebooks instance](/vertex-ai/docs/workbench/managed/create-instance#create).\n\n### Required roles\n\n\nTo ensure that your instance's service account has the necessary\npermissions to interact with the Vertex AI Workbench executor,\n\nask your administrator to grant your instance's service account the\nfollowing IAM roles on the project:\n\n| **Important:** You must grant these roles to your instance's service account, *not* to your user account. Failure to grant the roles to the correct principal might result in permission errors.\n\n- Notebooks Viewer ([`roles/notebooks.viewer`](/vertex-ai/docs/workbench/instances/iam#notebooks.viewer))\n- Vertex AI User ([`roles/aiplatform.user`](/vertex-ai/docs/general/access-control#aiplatform.user))\n- Storage Admin ([`roles/storage.admin`](/storage/docs/access-control/iam-roles#standard-roles))\n\n\nFor more information about granting roles, see [Manage access to projects, folders, and organizations](/iam/docs/granting-changing-revoking-access).\n\n\nYour administrator might also be able to give your instance's service account\nthe required permissions through [custom\nroles](/iam/docs/creating-custom-roles) or other [predefined\nroles](/iam/docs/roles-overview#predefined).\n\nOpen JupyterLab\n---------------\n\nTo open JupyterLab and prepare a notebook file to run,\ncomplete the following steps.\n\n1. [Open JupyterLab](/vertex-ai/docs/workbench/managed/create-managed-notebooks-instance-console-quickstart#open-jupyterlab).\n\n2. Upload a notebook (ipynb) file, open an existing file,\n or [open a new notebook\n file](/vertex-ai/docs/workbench/managed/create-managed-notebooks-instance-console-quickstart#open-a-new-notebook-file)\n and add the code that you want to run to the new notebook.\n\n3. Make sure your notebook file's code meets the [requirements\n for using the executor](/vertex-ai/docs/workbench/managed/executor#requirements).\n\nAdd the `parameters` tag to a notebook cell\n-------------------------------------------\n\n1. In your managed notebooks instance's\n JupyterLab user interface, open the notebook file that you want to run.\n\n2. Write code in one cell that assigns values to\n your parameter variables.\n These are the values your notebook file uses if\n you don't assign different parameter values in your execution.\n\n3. Make sure your parameters cell is still selected, and then\n in the right sidebar, click the\n **Property inspector**.\n\n4. In the property inspector, in the **Cell Tags** section,\n click **Add Tag** , enter `parameters`, and then press `Enter`.\n\n | **Note:** If you tag more than one cell with `parameters`, the executor adds only one parameters cell directly following the first cell with the `parameters` tag.\n\nProvide parameter values for your execution\n-------------------------------------------\n\n1. In your managed notebooks instance's\n JupyterLab user interface, click the\n **Executor** button.\n\n2. In the **Submit notebooks to Executor** dialog,\n enter a name for your execution in the **Execution name** field.\n\n3. Select a **Machine type** and **Accelerator type**.\n\n4. Select an **Environment**.\n\n5. In the **Type** field,\n select **One-time execution** , or\n select **Schedule-based recurring executions**, and complete\n the dialog for scheduling executions.\n\n6. In **Advanced options** ,\n select the **Region** where you want to run your notebook.\n\n7. In the **Cloud Storage bucket** field,\n select an available Cloud Storage bucket or\n enter a name for a new bucket and click **Create and select**.\n The executor stores your notebook output\n in this Cloud Storage bucket.\n\n8. In the **Notebook parameterization** section\n and the **Input parameters** text box,\n add notebook parameters separated by commas, for example\n `optimizer=SGD,learning_rate=0.01`. The format requires\n that there are no spaces and no quotation marks.\n\n9. Configure the rest of your execution, and then click **Submit**.\n\nWhat's next\n-----------\n\n- Learn more about [how to run notebook code in\n the executor](/vertex-ai/docs/workbench/managed/executor)."]]
。
按鈕。