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the deep learning reference stack
Translation of "the deep learning reference stack" in Chinese
深度学习参考堆栈
Performance test results for the Deep Learning Reference Stack and for this guide were obtained using runc as the runtime.
深度学习参考堆栈和本教程的性能测试结果是使用 runc 作为运行时获得的。
To uninstall the Deep Learning Reference Stack, you can choose to stop the container so that it is not using system resources, or you can stop the container and delete it to free storage space.
要卸载深度学习参考堆栈，您可以选择停止容器以使其不使用系统资源，或者可以停止容器并将其删除以释放存储空间。
You must add launcher.py to the Docker image to include the Deep Learning Reference Stack and put the benchmarks repo in the correct that this guide uses Kubeflow v0.4.0, and cannot guarantee results if you use a different version.
您必须将 launcher.py 添加到 Docker 映像中，以包含深度学习参考堆栈，并将基准测试存储库放在正确的位置。请注意，本教程使用 Kubeflow v0.4.0。如果使用不同的版本，则不能保证结果。
To take advantage of the Intel AVX-512 and VNNI functionality with the Deep Learning Reference Stack, you must use the following hardware
要利用英特尔 AVX-512 和 VNI 功能以及深度学习参考堆栈，您必须使用以下硬件：
You can continue working in this notebook, or you can download existing notebooks to take advantage of the Deep Learning Reference Stack's optimized deep learning frameworks. Refer to Jupyter Notebook for details.
您可以继续在此笔记本中工作，也可以下载现有笔记本来利用深度学习参考堆栈的优化深度学习框架。详情请参阅 Jupyter Notebook。
The Deep Learning Reference Stack is a collective work, and each piece of software within the work has its own license. Please see the DLRS Terms of Use for more details about licensing and usage of the Deep Learning Reference Stack.
深度学习参考堆栈是一项集体成果，成果中的每一个软件都有自己的许可证。有关深度学习参考堆栈的许可和使用的更多详细信息，请参阅 DLRS Terms of Use。
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