首页> 外国专利> DERIVING A CONCORDANT SOFTWARE NEURAL NETWORK LAYER FROM A QUANTIZED FIRMWARE NEURAL NETWORK LAYER

DERIVING A CONCORDANT SOFTWARE NEURAL NETWORK LAYER FROM A QUANTIZED FIRMWARE NEURAL NETWORK LAYER

机译:从量化的固件神经网络层推导一致的软件神经网络层

摘要

Systems and methods for deriving a concordant software neural network layer are provided. A method includes receiving first instructions configured to, using a neural network processor (NNP), process a first set of data corresponding to a neural network layer, where the NNP is configured to quantize the first set of the data to generate a set of quantized data and then perform matrix-vector multiply operations on the set of quantized data using a matrix-vector-multiplier incorporated within hardware associated with the NNP to generate a first set of results. The method further includes processing the first instructions to automatically generate second instructions configured for use with at least one processor, different from the NNP, such that the second instructions, when executed by the at least one processor to perform matrix multiply operations, generate a second set of results that are concordant with the first set of results.
机译:提供了用于导出一致的软件神经网络层的系统和方法。一种方法,包括接收第一指令,该第一指令被配置为使用神经网络处理器(NNP)来处理与神经网络层相对应的第一组数据,其中,NNP被配置为对第一组数据进行量化以生成一组量化的数据。然后,使用结合在与NNP相关联的硬件中的矩阵向​​量乘法器对量化数据集执行矩阵向量乘法运算,以生成第一组结果。该方法还包括处理第一指令以自动生成配置为与至少一个不同于NNP的处理器一起使用的第二指令,以使得第二指令在由至少一个处理器执行以执行矩阵乘法运算时生成第二指令。与第一组结果一致的一组结果。

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