Supported deep learning frameworks
Supported deep learning frameworks included with IBM Watson® Machine Learning Accelerator.
The following frameworks are included with Watson Machine Learning Accelerator for use with IBM® Watson Machine Learning.
Framework, library or asset | Version available in WML Accelerator 4.3.0 | Version available in WML Accelerator 4.2.0 | Version available in WML Accelerator 4.1.0 | Version available in WML Accelerator 4.0.0 |
---|---|---|---|---|
TensorFlow | 2.12.0 | 2.12.0 | 2.12.0 | 2.12.0 |
PyTorch | 2.0.0 | 2.0.0 | 2.0.0 | 2.0.0 |
Tensorboard | 2.12.2 | 2.12.2 | 2.12.2 | 2.12.2 |
torchVision | 0.15.1 | 0.15.1 | 0.15.1 | 0.15.1 |
OpenCV | 4.7.0 | 4.7.0 | 4.7.0 | 4.7.0 |
scikit-learn | 1.1.1 | 1.1.1 | 1.1.1 | 1.1.1 |
XGBoost | 1.7.5 | 1.7.5 | 1.7.5 | 1.7.5 |
ONNX | 1.13.1 | 1.13.1 | 1.13.1 | 1.13.1 |
PyArrow | 11.0.0 | 11.0.0 | 11.0.0 | 11.0.0 |
Python | 3.10.10 | 3.10.10 | 3.10.10 | 3.10.10 |
- All frameworks support the supported versions of Python.
- PyTorch supports single node training, distributed training, and elastic distributed training.
- TensorFlow supports single node training, distributed training, and elastic distributed training (with TF.Keras).