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GPU-BASED ARTIFICIAL INTELLIGENCE SYSTEM USING CHANNEL-LEVEL ARCHITECTURE SEARCH FOR DEEP NEURAL NETWORK

机译:深度神经网络的通道级架构搜索的基于GPU的人工智能系统

摘要

An artificial intelligence system and a method for searching for an optimal model are provided. A method for searching for a learning mode of an artificial intelligence system includes receiving, by an operator included in a first node, first channels, deriving, by the operator included in the first node, first parameter weight indexes corresponding to weights of first parameters by calculating the first parameters corresponding to each of the received first channels with the received first channels, generating and outputting a second channel group by combining the first channel with the other channel, receiving, by an operator included in a second node, second channels included in the second channel group, and deriving, by the operator included in the second node, second parameter weight indexes corresponding to weights of second parameters by calculating the second parameters corresponding to the received second channels with the received second channels.
机译:提供了一种人工智能系统和一种用于搜索最优模型的方法。一种用于搜索人工智能系统的学习模式的方法,包括:由第一节点中包括的操作者接收第一信道,由第一节点中包括的操作者得出对应于第一参数权重的第一参数权重索引。计算与接收到的第一信道对应的每个接收到的第一信道的第一参数,通过将第一信道与另一信道组合,生成并输出第二信道组,第二节点中包括的操作员接收第二信道中包括的第二信道。所述第二信道组,并通过包括在所述第二节点中的运算符,通过利用所述接收到的第二信道计算与所述接收到的第二信道对应的第二参数,得出与所述第二参数的权重对应的第二参数权重索引。

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