This document describes the key features, software enhancements and improvements, and known issues regarding PyTorch on the Jetson platform. See Installing PyTorch for Jetson Platform for installation information.
Key Features and Enhancements
This release includes the following key features and enhancements.
-
The TF32 numerical format is enabled by default for cuBLAS and cuDNN operations on Ampere GPUs starting with the 22.06 release. If you encounter training issues especially for regression, generative or higher-order models, or by using TF32 operations in pre- or post-processing steps, try to disable TF32 by setting the following:
torch.set_float32_matmul_precision('highest')
Compatibility
| PyTorch Version | NVIDIA Framework Container | NVIDIA Framework Wheel | JetPack Version |
|---|---|---|---|
| 2.4.0a0+f70bd71a48 | 24.06 | 24.06 | 6.0 |
| 2.4.0a0+07cecf4168 | 24.05 | 24.05 | 6.0 |
| 2.3.0a0+6ddf5cf85e | 24.04 | 24.04 | 6.0 Developer Preview |
| 2.3.0a0+40ec155e58 | 24.03 | 24.03 | |
| 2.3.0a0+ebedce2 | 24.02 | 24.02 | |
| 2.2.0a0+81ea7a4 | 23.12, 24.01 | 23.12, 24.01 | |
| 2.2.0a0+6a974bec | 23.11 | 23.11 | |
| 2.1.0a | 23.06 | 5.1.x | |
| 2.0.0 | 23.05 | ||
| 2.0.0a0+fe05266f | 23.04 | ||
| 2.0.0a0+8aa34602 | 23.03 | ||
| 1.14.0a0+44dac51c | 23.02, 23.01 | ||
| 1.13.0a0+936e930 | 22.11 | 5.0.2 | |
| 1.13.0a0+d0d6b1f | 22.09, 22,10 | ||
| 1.13.0a0+08820cb | 22.07 | 22.07 | |
| 1.13.0a0+340c412 | 22.06 | 22.06 | 5.0.1 |
| 1.12.0a0+8a1a93a9 | 22.05 | 22.05 | 5.0 |
| 1.12.0a0+bd13bc66 | 22.04 | ||
| 1.12.0a0+2c916ef | 22.03 | ||
| 1.11.0a0+bfe5ad28 | 22.01 | 4.6.1 |
Using PyTorch with the Jetson Platform
- Storage
-
If you need more storage, we recommend connecting an external SSD via SATA on TX2 or Xavier devices, or USB on Jetson Nano.
Known Issues
- TensorRT Model Optimizer is a new module but is not yet supported on Jetson due to its dependency on pytorch distributed functionality, which was disabled for Jetson.