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OPTIMIZING PERFORMANCE OF RECURRENT NEURAL NETWORKS

机译:递归神经网络的性能优化

摘要

An apparatus for optimizing a computational network is configure to receive an input at a first processing component. The first processing component may include at least a first programmable processing component and a second programmable processing component. The first programmable processing component is configured to compute a first nonlinear function and the second programmable processing component is configured to compute a second nonlinear function which is different than the second nonlinear function. The computational network which may be a recurrent neural network such as a long short-term memory may be operated to generate an inference based at least in part on outputs of the first programmable processing component and the second programmable processing component.
机译:用于优化计算网络的设备被配置为在第一处理组件处接收输入。第一处理组件可以至少包括第一可编程处理组件和第二可编程处理组件。第一可编程处理组件被配置为计算第一非线性函数,第二可编程处理组件被配置为计算与第二非线性函数不同的第二非线性函数。可以是诸如长期短期记忆之类的递归神经网络的计算网络可以被操作以至少部分地基于第一可编程处理组件和第二可编程处理组件的输出来生成推断。

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