- 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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