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PyTorch on Azure ML: problem accessing GPU with ACPT environment image

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In Azure Machine Learning, I am trying to set up a **PyTorch 2.0.1 run** on a curated **ACPT image**: `mcr.microsoft.com/azureml/curated/acpt-pytorch-2.0-cuda11.7:latest` (based on [this](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-azure-container-for-pytorch-environment?view=azureml-api-2) and [this](https://github.com/Azure/AzureML-Containers/tree/master/base/gpu) documentation) I use the image...

I have a training job that persists some files in an URI_FOLDER output. _How can I access those through the v2 SDK API after the job has finished?_ ### 1....

## What I'm trying to do For an **AutoML Forecasting** experiment, I'd like to compare the performance of the **best model** with the performance of **another model** from the same...