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)