PyTorch
TWSC provides 10 ready-to-use working environments of NGC optimized PyTorch. PyTorch is a GPU accelerated tensor computational framework with a Python front end. Functionality can be easily extended with common Python libraries such as NumPy, SciPy and Cython. Automatic differentiation is done with a tape-based system at both a functional and neural network layer level. This functionality brings a high level of flexibility and speed for deep learning frameworks and offers NumPy-like acceleration. PyTorch also includes standard defined neural network layers, deep learning optimizers, data loading utilities, and multi-gpu and multi-node support. Functions are executed immediately instead of enqueued in a static graph, improving ease of use and providing a great debugging experience.
Image versions
| Container Version | Ubuntu | CUDA Toolkit | PyTorch Version | TensorRT | cuDNN | TWCC Release Date |
|---|---|---|---|---|---|---|
| pytorch-25.05-py3 | 24.04 | NVIDIA CUDA 12.9.0 | 2.8.0a0+5228986c39 | TensorRT 10.10.0.31 | - | 16JUN25 |
| pytorch-25.02-py3 | 24.04 | NVIDIA CUDA 12.8.0.38 | 2.7.0a0+6c5496875 | TensorRT 10.8.0.43 | 9.7.1.26 | 28MAR25 |
| pytorch-24.11-py3 | 24.04 | NVIDIA CUDA 12.6.3 | 2.6.0a0+df5bbc0911 | TensorRT 10.6.0.26 | 9.5.1.17 | 27DEC24 |
| pytorch-24.08-py3 | 24.04 | NVIDIA CUDA 12.6 | 2.5.0a0+872d972e41 | TensorRT 10.3.0.26 | 9.3.0.75 | 27MAY24 |
| pytorch-24.05-py3 | 24.04 | NVIDIA CUDA 12.4.1 | 2.4.0a0+07cecf4168 | TensorRT 10.0.1.6 | 9.1.0.70 | 27JUN24 |
| pytorch-24.02-py3 | 22.04 | NVIDIA CUDA 12.3.2 | 2.3.0a0+ebedce2 | TensorRT 8.6.3 | 9.0.0.306 | 29MAR24 |
| pytorch-23.11-py3 | 22.04 | NVIDIA CUDA 12.3.0 | 2.2.0a0+6a974bee | TensorRT 8.6.1.6 | 8.9.6 | 29DEC23 |
| pytorch-23.08-py3 | 22.04 | NVIDIA CUDA 12.2.1 | 2.1.0a0+29c30b1 | TensorRT 8.6.1.6 | 8.9.4 | 28SEP23 |
| pytorch-23.05-py3 | 22.04 | NVIDIA CUDA 12.1.1 | 2.0.0 | TensorRT 8.6.1.2 | 8.9.1.23 | 30JUN23 |
| pytorch-23.02-py3 | 22.04 | NVIDIA CUDA 12.0.1 | 1.14.0a0+44da651 | TensorRT 8.5.3 | 8.7.0.84 | 24MAR23 |
| pytorch-22.08-py3 | 20.04 | NVIDIA CUDA 11.7.1 | 1.13.0a0+4321be6 | TensorRT 8.4.2.4 | 8.5.0.96 | 30SEP22 |
| pytorch-22.05-py3 | 20.04 | NVIDIA CUDA 11.7.0 | 1.12.0a0+8a1a938 | TensorRT 8.2.5.1 | 8.4.0.27 | 21JUN22 |
| pytorch-22.02-py3 | 20.04 | NVIDIA CUDA 11.6.0 | 1.11.0a0+17540c5c | TensorRT 8.2.3 | 8.3.2.44 | 18MAY22 |
| pytorch-21.11-py3 | 20.04 | NVIDIA CUDA 11.5.0 | 1.11.0a0+b6df043 | TensorRT 8.0.3.4 | 8.3.0.96 | 18JAN22 |
| pytorch-21.08-py3 | 20.04 | NVIDIA CUDA 11.4.1 | 1.10.0a0+3fd9dcf | TensorRT 8.0.1.6 | 8.2.2.26 | 16SEP21 |
| pytorch-21.06-py3 | 20.04 | NVIDIA CUDA 11.3.1 | 1.9.0a0+c3d40fd | TensorRT 7.2.3.4 | 8.2.1 | 29JUN21 |
| pytorch-21.02-py3 | 20.04 | NVIDIA CUDA 11.2.0 | 1.8.0a0+52ea372 | TensorRT 7.2.2.3 | 8.1.0 | 27APR21 |
py3 and py2 are different Python versions.
Detailed package versions
- pytorch-25.05-py3
- pytorch-25.02-py3
- pytorch-24.11-py3
- pytorch-24.08-py3
- pytorch-24.05-py3
- pytorch-24.02-py3
- pytorch-23.11-py3
- pytorch-23.08-py3
- pytorch-23.05-py3
- pytorch-23.02-py3
- pytorch-22.02-py3
- pytorch-21.11-py3
- pytorch-21.08-py3
- pytorch-21.06-py3
- pytorch-21.02-py3
- pytorch-20.11-py3
- pytorch-20.08-py3
- pytorch-20.06-py3
- pytorch-20.02-py3
- pytorch-19.11-py3
- pytorch-19.08-py3
- pytorch-19.02-py3-v1
- pytorch-18.12-py3-v1
- pytorch-18.10-py3-v1
- pytorch-18.08-py3-v1