# Check the name of the conda environment for PyTorchcondaenvlist# Activate the environment for PyTorchcondaactivatepytorch# Display the PyTorch versionpython-c"import torch; print(torch.__version__)"# Make sure to use pip from the conda environment for PyTorch# This should be `/opt/conda/envs/pytorch/bin/pip`whichpip# Upgrade PyTorchpipinstall--upgradetorch
刪除 conda 核心
部分 conda 套件會在安裝套件時，將預設核心新增至環境。舉例來說，安裝 R 時，conda 可能也會新增 python3 核心。這可能會導致環境中的核心重複。為避免重複的核心，請先刪除預設核心，再建立名稱相同的新核心。
[[["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,["# Manage the conda environment in your Vertex AI Workbench instance\n\nManage your conda environment\n=============================\n\nThis page describes how to manage a conda environment in your\nVertex AI Workbench instance.\n\nOverview\n--------\n\nIf you've added a conda environment to your Vertex AI Workbench instance,\nit appears as a\n[kernel](https://jupyterlab.readthedocs.io/en/stable/user/documents_kernels.html)\nin your instance's JupyterLab interface.\n\nYou might have added a conda environment to your instance to use a kernel\nthat isn't available in a default Vertex AI Workbench instance.\nThis page describes how to modify and delete that kernel.\n\nOpen JupyterLab\n---------------\n\n1. In the Google Cloud console, go to the **Instances** page.\n\n [Go to Instances](https://console.cloud.google.com/vertex-ai/workbench/instances)\n2. Next to your Vertex AI Workbench instance's name,\n click **Open JupyterLab**.\n\n Your Vertex AI Workbench instance opens JupyterLab.\n\nModify a conda kernel\n---------------------\n\nVertex AI Workbench instances come with pre-installed frameworks such as PyTorch\nand TensorFlow. If you need a different version, you can modify the\nlibraries by using pip in the relevant conda environment.\n\nFor example, if you want to upgrade PyTorch: \n\n```python\n# Check the name of the conda environment for PyTorch\nconda env list\n\n# Activate the environment for PyTorch\nconda activate pytorch\n\n# Display the PyTorch version\npython -c \"import torch; print(torch.__version__)\"\n\n# Make sure to use pip from the conda environment for PyTorch\n# This should be `/opt/conda/envs/pytorch/bin/pip`\nwhich pip\n\n# Upgrade PyTorch\npip install --upgrade torch\n```\n\nDelete a conda kernel\n---------------------\n\nSome conda packages add default kernels to your environment when the packages\nare installed. For example, when you install R, conda might also add a\n`python3` kernel. This can cause a duplication of kernels in your\nenvironment. To avoid duplicated kernels, delete the default kernel\nbefore you create a new kernel with the same name. \n\n```scdoc\nrm -rf /opt/conda/envs/CONDA_ENVIRONMENT_NAME/share/jupyter/kernels/python3\n```\n\nTroubleshoot\n------------\n\nTo diagnose and resolve issues related to managing a conda environment in\nyour Vertex AI Workbench instance, see [Troubleshooting\nVertex AI Workbench](/vertex-ai/docs/general/troubleshooting-workbench#instances).\n\nWhat's next\n-----------\n\n- Learn more about [conda](https://docs.conda.io/en/latest/)."]]
