def __init__(self, inChannels, outChannels):
        """
        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 for setting input and output channels for
                the second convolutional layer.
        """

        
        super(up, self).__init__()
        # Initialize convolutional layers.
        self.conv1 = nn.Conv2d(inChannels,  outChannels, 3, stride=1, padding=1)
        # (2 * outChannels) is used for accommodating skip connection.
        self.conv2 = nn.Conv2d(2 * outChannels, outChannels, 3, stride=1, padding=1)

        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 for setting input and output channels for
                the second convolutional layer.
        
model.py