import paddle.fluid as fluid
class ConvPool(fluid.dygraph.Layer):
    def __init__(self,
                 num_channels,
                 num_filters,
                 filter_size,
                 pool_size,
                 pool_stride,
                 groups,
                 pool_padding=0,
                 pool_type='max',
                 conv_stride=1,
                 conv_padding=1,
                 act=None):
        super(ConvPool,self).__init__()
        self._conv2d_list=[]
        for i in range (groups):
            conv2d = self.add_sublayer('bb_%d'%i,
                                       fluid.dygraph.Conv2D(
                                           num_channels=num_channels,
                                           num_filters=num_filters,
                                           filter_size=filter_size,
                                           stride=conv_stride,
                                           padding=conv_padding,
                                           act=act
                                       ))

            num_channels = num_filters
            self._conv2d_list.append(conv2d)

        self._pool2d=fluid.dygraph.Pool2D(
            pool_size=pool_size,
            pool_type=pool_type,
            pool_stride=pool_stride,
            pool_padding=pool_padding
        )

    def forward(self, inputs):
        x= inputs
        for conv in self._conv2d_list:
            x= conv(x)
        x = self._pool2d(x)
        return x