This is a and fully integrated software stack that combines TensorFlow, an open-source machine learning library, with the Python programming language. It offers a reliable and thoroughly tested environment suitable for various machine learning tasks, including training, inference, and serving as an API service.
The stack is specifically designed to excel in both short and long-running high-performance tasks, making it versatile for a wide range of machine learning applications. Its seamless integration allows for easy inclusion in continuous integration and deployment (CI/CD) workflows, streamlining the development and deployment of machine learning models.
One of its notable features is its optimization for running on CPU, leveraging the Intel Math Kernel Library (MKL) and MKL-DNN libraries. These libraries enhance the performance and efficiency of mathematical and deep learning operations when executed on CPU-based systems.
Additionally, the stack includes a Development preset, providing essential program development and building tools such as a C compiler and make. These tools empower users to further customize and extend the capabilities of the stack to meet specific requirements.
In summary, this software stack offers a stable and tested environment for TensorFlow-based machine learning tasks, optimized for CPU performance with Intel MKL and MKL-DNN libraries. It is designed for flexibility and easy integration into CI/CD workflows, supported by development tools for customization.