def __init__(self,
in_channels,
out_channels,
kernel_size,
stride,
upsample=None):
super(UpsampleConvLayer, self).__init__()
self.upsample = upsample
if upsample:
self.upsample_layer = nn.Upsample(mode='nearest',
scale_factor=upsample)
reflection_padding = kernel_size // 2
self.reflection_pad = nn.ReflectionPad2d(reflection_padding)
self.conv2d = nn.Conv2d(in_channels, out_channels, kernel_size,
stride)
def __init__(self):
super().__init__()
self.m = nn.ReflectionPad2d((2, 3, 0, 1))
def __init__(self, in_channels, out_channels, kernel_size, stride):
super(ConvLayer, self).__init__()
reflection_padding = kernel_size // 2
self.reflection_pad = nn.ReflectionPad2d(reflection_padding)
self.conv2d = nn.Conv2d(in_channels, out_channels, kernel_size,
stride)
