def __init__(self, in_channel, channels=64):
        """Initializes the DenseEncoder with specified input channels and feature size."""
        super(DenseEncoder, self).__init__()
        self.conv_1 = nn.Sequential(
            nn.Conv2d(in_channel, channels, (1, 1), (1, 1)),  # Initial convolution layer
            nn.InstanceNorm2d(channels, affine=True),  # Normalization layer
            nn.PReLU(channels)  # Activation function
        )
        self.dilated_dense = DilatedDenseNet(depth=4, in_channels=channels)  # Dilated Dense Network
        self.conv_2 = nn.Sequential(
            nn.Conv2d(channels, channels, (1, 3), (1, 2), padding=(0, 1)),  # Second convolution layer
            nn.InstanceNorm2d(channels, affine=True),  # Normalization layer
            nn.PReLU(channels)  # Activation function
        )
Initializes the DenseEncoder with specified input channels and feature size.
clearvoice/clearvoice/models/mossformer_gan_se/generator.py