convnet.py 文件源码

def softmax_cost(out,y, theta3, filt1, filt2):
    eout = np.exp(out, dtype=np.float128)
    probs = eout/sum(eout)

    p = sum(y*probs)
    cost = -np.log(p)   ## (Only data loss. No regularised loss)
    return cost,probs   

## Returns gradient for all the paramaters in each iteration