0c0f2d8895ad5b268d4c2c721980048286b12b34,paysage/models/tap_machine.py,TAP_rbm,gradient,#TAP_rbm#Any#Any#,339

Before Change

        db_EMF /= (num_p + num_r)

        // compute average grad_F_marginal over the minibatch
        intermediate = be.expit(be.add(be.unsqueeze(b,0), be.dot(data_state.units[0], w)))

        da = be.mean(data_state.units[0], axis=0)
        db = be.mean(intermediate, axis=0)
        batch_size = be.shape(data_state.units[0])[0]
        dw = be.dot(be.transpose(data_state.units[0]), intermediate) / batch_size

        grad = gu.Gradient(

After Change

        grad.weights[0] = layers.ParamsWeights(dw_EMF - grad_MFE.weights[0][0])
        grad.layers[0] = layers.ParamsBernoulli(da_EMF - grad_MFE.layers[0][0])
        grad.layers[1] = layers.ParamsBernoulli(db_EMF - grad_MFE.layers[][0])

        return grad

Instances