Deep learning and AI frameworks for the Azure Data Science Virtual Machine

Deep learning frameworks on the DSVM are listed here:

CUDA, cuDNN, NVIDIA Driver

Category	Value
Supported versions	11
Supported DSVM editions	Windows Server 2019 Linux
How is it configured and installed on the DSVM?	nvidia-smi is available on the system path.
How to run it	Open a command prompt (on Windows) or a terminal (on Linux), and then run nvidia-smi.

Horovod

Category	Value
Supported versions	0.21.3
Supported DSVM editions	Linux
How is it configured and installed on the DSVM?	Horovod is installed in Python 3.5
How to run it	Activate the correct environment at the terminal, and then run Python.

NVidia System Management Interface (nvidia-smi)

Category	Value
Supported versions
Supported DSVM editions	Windows Server 2019 Linux
What is it used for?	As an NVIDIA tool to query GPU activity
How is it configured and installed on the DSVM?	nvidia-smi is on the system path.
How to run it	On a virtual machine with GPU's, open a command prompt (on Windows), or a terminal (on Linux), and then run nvidia-smi.

PyTorch

Category	Value
Supported versions	1.9.0 (Linux, Windows 2019)
Supported DSVM editions	Windows Server 2019 Linux
How is it configured and installed on the DSVM?	Installed in Python, conda environments 'py38_default', 'py38_pytorch'
How to run it	At the terminal, activate the appropriate environment, and then run Python. * JupyterHub: Connect, and then open the PyTorch directory for samples.

TensorFlow

Category	Value
Supported versions	2.5
Supported DSVM editions	Windows Server 2019 Linux
How is it configured and installed on the DSVM?	Installed in Python, conda environments 'py38_default', 'py38_tensorflow'
How to run it	At the terminal, activate the correct environment, and then run Python. * Jupyter: Connect to Jupyter or JupyterHub, and then open the TensorFlow directory for samples.