| title | sidebar_label |
|---|---|
Getting Started |
Getting Started |
:::note This is a sample with databricks 10.4.x-gpu-ml-scala2.12 runtime :::
We build on top of torchvision, horovod and pytorch_lightning, so we need to reinstall horovod by building on specific versions of those packages. Download our horovod installation script and upload it to databricks dbfs.
Add the path of this script to Init Scripts section when configuring the spark cluster.
Restarting the cluster automatically installs horovod v0.25.0 with pytorch_lightning v1.5.0 and torchvision v0.12.0.
You could install the single synapseml-deep-learning wheel package to get the full functionality of deep vision classification. Run the following command:
pip install synapseml==1.0.2An alternative is installing the SynapseML jar package in library management section, by adding:
Coordinate: com.microsoft.azure:synapseml_2.12:1.0.2
Repository: https://mmlspark.azureedge.net/maven
:::note If you install the jar package, follow the first two cells of this sample to ensure horovod recognizes SynapseML. :::
You could follow the rest of this [sample](../Quickstart%20-%20Fine-Tune a Vision Classifier) and have a try on your own dataset.
Supported models (backbone parameter for DeepVisionClassifer) should be string format of Torchvision-supported models;
You could also check by running backbone in torchvision.models.__dict__.