  TensorX is a Python library for prototyping, design, and deployment of
complex neural network models in TensorFlow. A special emphasis is put on ease
of use, performance, and API consistency. It aims to make available high-level
components like neural network layers that are, in effect, stateful functions,
easy to compose and reuse. Its architecture allows for the expression of
patterns commonly found when building neural network models either on research
or industrial settings. Incorporating ideas from several other deep learning
libraries, it makes it easy to use components commonly found in
state-of-the-art models. The library design mixes functional dataflow
computation graphs with object-oriented neural network building blocks. TensorX
combines the dynamic nature of Python with the high-performance GPU-enabled
operations of TensorFlow.
  This library has minimal core dependencies (TensorFlow and NumPy) and is
distributed under Apache License 2.0 licence, encouraging its use in both an
academic and commercial settings. Full documentation, source code, and binaries
can be found in https://tensorx.org/.
