model.py 文件源码

def build_decoder(self,input_shape):
        "this function did not converge well. sigh"
        data_dim = np.prod(input_shape)
        last_convolution = 1 + np.array(input_shape) // 4
        first_convolution = last_convolution * 4
        diff = tuple(first_convolution - input_shape)
        crop = [[0,0],[0,0]]
        for i in range(2):
            if diff[i] % 2 == 0:
                for j in range(2):
                    crop[i][j] = diff[i] // 2
            else:
                crop[i][0] = diff[i] // 2
                crop[i][1] = diff[i] // 2 + 1
        crop = ((crop[0][0],crop[0][1]),(crop[1][0],crop[1][1]))
        print(last_convolution,first_convolution,diff,crop)

        return [*([Dropout(self.parameters['dropout'])] if self.parameters['dropout_z'] else []),
                *[Dense(self.parameters['layer'], activation='relu', use_bias=False),
                  BN(),
                  Dropout(self.parameters['dropout']),],
                *[Dense(np.prod(last_convolution) * self.parameters['clayer'], activation='relu', use_bias=False),
                  BN(),
                  Dropout(self.parameters['dropout']),],
                Reshape((*last_convolution, self.parameters['clayer'])),
                *[UpSampling2D((2,2)),
                  Deconvolution2D(self.parameters['clayer'],(3,3), activation='relu',padding='same', use_bias=False),
                  BN(),
                  Dropout(self.parameters['dropout']),],
                *[UpSampling2D((2,2)),
                  Deconvolution2D(1,(3,3), activation='sigmoid',padding='same'),],
                Cropping2D(crop),
                Reshape(input_shape),]