def __init__(self, in_channels, n_filters):
    super().__init__()
    self.upsample = nn.Upsample(scale_factor=2, mode='bilinear')
    self.conv1 = nn.Conv2d(in_channels, n_filters, 3, padding=1)
    self.norm1 = nn.BatchNorm2d(n_filters)
    self.relu1 = nonlinearity(inplace=True)
def __init__(self, in_channels, n_filters):
    super().__init__()
    self.upsample = nn.Upsample(scale_factor=2, mode='bilinear')
    self.conv1 = nn.Conv2d(in_channels, n_filters, 3, padding=1)
    self.norm1 = nn.BatchNorm2d(n_filters)
    self.relu1 = nonlinearity(inplace=True)