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吳裕雄 python深度學習與實踐(4)

shape math ret sof clas bsp pre 深度學習 sha

import numpy,math

def softmax(inMatrix):
    m,n = numpy.shape(inMatrix)
    outMatrix = numpy.mat(numpy.zeros((m,n)))
    soft_sum = 0
    for idx in range(0,n):
        outMatrix[0,idx] = math.exp(inMatrix[0,idx])
        soft_sum += outMatrix[0,idx]
    for idx in range(0,n):
        outMatrix[0,idx] 
= outMatrix[0,idx] / soft_sum return outMatrix aa = numpy.matrix([1,2,3,4,5,4,3,9,8]) outMatrix = softmax(aa) print(outMatrix)

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吳裕雄 python深度學習與實踐(4)