SAS Deep Learning Python (DLPy)

DLPy is a high-level Python library for the SAS Deep Learning features available in SAS® Viya®. DLPy provides a convenient way to apply deep learning functionalities to solve computer vision, NLP, forecasting and speech processing problems.

DLPy features include the following: 

  • Read in and build deep learning models for image, text, audio and time series data.
    • High-level APIs for:
    • Deep neural networks for tabular data.
    • Image classification and regression.
    • Object detection.
    • RNN-based tasks – text classification, text generation and sequence labeling.
    • RNN-based time series processing and modeling.
  • Processing audio files and training deep learning algorithms to create a language model for speech recognition applications.
  • Predefined network architectures such as LeNet, VGG, ResNet, DenseNet, Darknet, Inception and YoloV2 and Tiny_Yolo. And many are provided with pre-trained weights!
  • Enhanced data visualization such as heat maps and feature maps to aid in the interpretation of deep learning computer vision models.
  • Import and export deep learning models in ONNX format.

DLPy can be used from Jupyter Notebook, JupyterLab, or from any Python console/scripting environment.

DLPy is open source and available on GitHub and PyPI. User contributions are accepted.

Get Started

Find all DLPy pre-requisites, installation, and configuration on

DLPy can be installed using pip as follows: 
pip install sas-dlpy

If you use the Anaconda distribution of Python, you can also use:
conda install -c sas-institute sas-dlpy

You can also download from the GitHub repository and install locally. 

Deep Learning with Python (DLPy) Computer Vision Demo Series

DLPy and SAS® Viya® Demo Resources


Example Notebooks and use cases can be found at sassoftware/python-dlpy/examples

Sample Notebook Screenshots

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