rbm_sample.py 文件源码

def long_report(s):
        lgE = np.log2(np.e)
        # Long report
        # print('\nFound dataset %s T=%s Nh=%s Nv=%s'%(DIR,T,Nh,Nv))
        # print('DKL                   %0.2f'%DKL)
        print('\nRBM dataset Ns=%s Nh=%s Nv=%s'%(s.Ns,s.Nh,s.Nv))
        # Hidden layer entropy
        print('==Hidden layer entropy==')
        print('Hid capacity, maximum %0.2f'%(np.sum(rb.bitent(0.5*np.ones(s.Nh)))))
        print('Hid entropy , sampled %0.2f'%(s.Hhs))
        print('Entropy hid sample is %0.2f'%(entropy(s.Qh,base=2)))
        print('<<Eh>h|v>v sampled is %0.2f'%(s.barEhhv*lgE))
        print('<<Eh>h|v>v ufield  is %0.2f'%(s.barEhhv_meanfield*lgE))
        print('Mean hidde complexity %0.2f'%(rb.bitent(np.mean(s.Ph))*s.Nh))
        print('Mean hidden rate      %0.2f'%(np.mean(s.Ph)))
        # Conditional entropy
        print('==Conditional entropy==')
        print('Entropy difference    %0.2f'%(s.Hhs-s.Hvs))
        print('<H_h|v>v           is %0.2f'%(s.barHhv*lgE))
        # Likelihoods
        print('==Negative log-likelihood==')
        print('<<Ev|h>h|v>v sampl is %0.2f'%(s.barEvhhv *lgE))
        print('<<Ev|h>h|v>v ufild is %0.2f'%(s.barEvhhv_meanfield*lgE))
        # KL divergences
        print('==KL divergences==')
        print('<Dkl(h|v||h)>v sam is %0.2f'%(s.barDKLhv*lgE))
        print('<Dkl(h|v||h)>v uf1 is %0.2f'%(s.barDKLhv_meanfield*lgE))
        # Visible entropy; These should be close in value
        print('==Visible layer entropy==')
        print('Vis capacity, maximum %0.2f'%(np.sum(rb.bitent(0.5*np.ones(s.Nv)))))
        print('Vis entropy , sampled %0.2f'%(s.Hvs))
        print('Entropy vis sample is %0.2f'%(entropy(s.Qv,base=2)))
        print('<D(.)+<Ev|h>h|v>v sam %0.2f'%(s.barDKLhv*lgE+s.barEvhhv *lgE))
        print('<D(.)+<Ev|h>h|v>v uf1 %0.2f'%(s.barDKLhv_meanfield*lgE+s.barEvhhv_meanfield*lgE))