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AUGMENTING ATTENTION-BASED NEURAL NETWORKS TO SELECTIVELY ATTEND TO PAST INPUTS

机译:增强基于关注的神经网络以选择性地参加过去的投入

摘要

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing a machine learning task on a network input that is a sequence to generate a network output. In one aspect, one of the methods includes, for each particular sequence of layer inputs: for each attention layer in the neural network: maintaining episodic memory data; maintaining compressed memory data; receiving a layer input to be processed by the attention layer; and applying an attention mechanism over (i) the compressed representation in the compressed memory data for the layer, (ii) the hidden states in the episodic memory data for the layer, and (iii) the respective hidden state at each of the plurality of input positions in the particular network input to generate a respective activation for each input position in the layer input.
机译:方法,系统和设备,包括在计算机存储介质上编码的计算机程序,用于对网络输入执行机器学习任务,该方法是用于生成网络输出的序列。在一个方面,其中一种方法包括用于每个特定层输入的特定序列:对于神经网络中的每个注意层:维护ePiSodic存储器数据;维护压缩的内存数据;接收要由注意层处理的图层输入;并在(i)上的压缩存储器数据中应用于(i)的压缩机制,(ii)在层的影片内存储器数据中的隐藏状态,和(iii)多个中的每一个的相应隐藏状态特定网络输入中的输入位置以生成层输入中的每个输入位置的相应激活。

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