我们找到models文件夹中的common.py文件，添加CNeB模块，如下
########################convnext#############################
class Block(nn.Module):r""" ConvNeXt Block. There are two equivalent implementations:(1) DwConv -> LayerNorm (channels_first) -> 1x1 Conv -> GELU -> 1x1 Conv; all in (N, C, H, W)(2) DwConv -> Permute to (N, H, W, C); LayerNorm (channels_last) -> Linear -> GELU -> Linear; Permute backWe use (2) as we find it slightly faster in PyTorchArgs:dim (int): Number of input channels.drop_path (float): Stochastic depth rate. Default: 0.0layer_scale_init_value (float): Init value for Layer Scale. Default: 1e-6."""def __init__(self, dim, drop_path=0., layer_scale_init_value=1e-6):super().__init__()self.dwconv = nn.Conv2d(dim, dim, kernel_size=7, padding=3, groups=dim) # de
)
