def __init__(self, inChannels, outChannels, filterSize):
        """
        Parameters
        ----------
            inChannels : int
                number of input channels for the first convolutional layer.
            outChannels : int
                number of output channels for the first convolutional layer.
                This is also used as input and output channels for the
                second convolutional layer.
            filterSize : int
                filter size for the convolution filter. input N would create
                a N x N filter.
        """


        super(down, self).__init__()
        # Initialize convolutional layers.
        self.conv1 = nn.Conv2d(inChannels,  outChannels, filterSize, stride=1, padding=int((filterSize - 1) / 2))
        self.conv2 = nn.Conv2d(outChannels, outChannels, filterSize, stride=1, padding=int((filterSize - 1) / 2))

        Parameters
        ----------
            inChannels : int
                number of input channels for the first convolutional layer.
            outChannels : int
                number of output channels for the first convolutional layer.
                This is also used as input and output channels for the
                second convolutional layer.
            filterSize : int
                filter size for the convolution filter. input N would create
                a N x N filter.
        
model.py