Pool1DLayer.py 文件源码

def inv(self, output):

        output = output.dimshuffle(0,1,2,'x').repeat(self.pool_shape[0], axis=3)

        if self.depooler == 'random':
            mask = self.theano_rng.uniform(size=output.shape, dtype=theano.config.floatX) 
            mask = T.floor(mask / mask.max(axis=3).dimshuffle(0,1,2,'x'))
            output = mask * output
        elif self.depooler == 'first':
            mask_np = np.zeros(self.pool_shape, dtype=theano.config.floatX)
            mask_np[0] = 1.0
            mask = theano.shared(mask_np, borrow=True).dimshuffle('x','x','x',0)
            output = mask * output
        else:
            output = self.depooler(output, axis=3)

        return output.reshape(self.input_shape)