azure - 在 Azure ML 中将本地计算与估算器结合使用

Question

是否可以对 TensorFlow 估计器使用本地计算？为训练运行配置虚拟机需要花费大量时间，我希望能够在本地尝试几次运行，直到我的配置稳定。

https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/machine-learning/service/how-to-train-tensorflow.md

可以通过创建一个空的 RunConfiguration 来使用 ScriptRunConfig 来执行此操作。该文档声称可以创建本地 ComputeTarget，但缺少有关如何执行此操作的文档:

https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/machine-learning/service/how-to-set-up-training-targets.md#local

Local computer

Create and attach: There's no need to create or attach a compute target to use your local computer as the training environment.

Configure: When you use your local computer as a compute target, the training code is run in your development environment. If that environment already has the Python packages you need, use the user-managed environment.

[!code-python]

Answer 1

我会使用Microsoft docs直接，而不是 GitHub 原始页面 - 我注意到后者有时不完整和/或过时。

正如您所怀疑的，docs确认您应该创建一个空的 RunConfiguration，类似于以下代码(取自上述链接):

from azureml.core.runconfig import RunConfiguration

# Edit a run configuration property on the fly.
run_local = RunConfiguration()

run_local.environment.python.user_managed_dependencies = True