TensorX：用于神经网络模型设计和部署的可扩展API
TensorX: Extensible API for Neural Network Model Design and Deployment
摘要：
TensorX是一个Python库，用于在TensorFlow中对复杂的神经网络模型进行原型设计、设计和部署。特别强调的是易用性、性能和API一致性。它的目标是提供高级组件，如神经网络层，这些层实际上是有状态函数，易于组合和重用。它的架构允许表达在研究或工业环境中构建神经网络模型时常见的模式。它继承了其他几个深度学习库的思想，使其易于使用最先进模型中常见的组件。该库设计将函数式递归计算图与面向对象的神经网络构建块混合在一起。TensorX将Python的动态特性与TensorFlow的高性能GPU支持的操作相结合。该库具有最小的核心依赖（TensorFlow和NumPy），并在Apache License 2.0许可下分发，鼓励其在学术和商业环境中使用。完整的文档、源代码和二进制文件可以在https://tensorx.org/中找到。
英文摘要：
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/.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
