  A recent trend observed in traditionally challenging fields such as computer
vision and natural language processing has been the significant performance
gains shown by deep learning (DL). In many different research fields, DL models
have been evolving rapidly and become ubiquitous. Despite researchers'
excitement, unfortunately, most software developers are not DL experts and
oftentimes have a difficult time following the booming DL research outputs. As
a result, it usually takes a significant amount of time for the latest superior
DL models to prevail in industry. This issue is further exacerbated by the
common use of sundry incompatible DL programming frameworks, such as
Tensorflow, PyTorch, Theano, etc. To address this issue, we propose a system,
called Model Asset Exchange (MAX), that avails developers of easy access to
state-of-the-art DL models. Regardless of the underlying DL programming
frameworks, it provides an open source Python library (called the MAX
framework) that wraps DL models and unifies programming interfaces with our
standardized RESTful APIs. These RESTful APIs enable developers to exploit the
wrapped DL models for inference tasks without the need to fully understand
different DL programming frameworks. Using MAX, we have wrapped and
open-sourced more than 30 state-of-the-art DL models from various research
fields, including computer vision, natural language processing and signal
processing, etc. In the end, we selectively demonstrate two web applications
that are built on top of MAX, as well as the process of adding a DL model to
MAX.
