def __init__()

in resmlp_models.py [0:0]

• 20 lines of code
• 4 McCabe index (conditional complexity)

    def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classes=1000, embed_dim=768, depth=12,drop_rate=0.,
                 Patch_layer=PatchEmbed,act_layer=nn.GELU,
                drop_path_rate=0.0,init_scale=1e-4):
        super().__init__()



        self.num_classes = num_classes
        self.num_features = self.embed_dim = embed_dim  

        self.patch_embed = Patch_layer(
                img_size=img_size, patch_size=patch_size, in_chans=int(in_chans), embed_dim=embed_dim)
        num_patches = self.patch_embed.num_patches
        dpr = [drop_path_rate for i in range(depth)]

        self.blocks = nn.ModuleList([
            layers_scale_mlp_blocks(
                dim=embed_dim,drop=drop_rate,drop_path=dpr[i],
                act_layer=act_layer,init_values=init_scale,
                num_patches=num_patches)
            for i in range(depth)])


        self.norm = Affine(embed_dim)



        self.feature_info = [dict(num_chs=embed_dim, reduction=0, module='head')]
        self.head = nn.Linear(embed_dim, num_classes) if num_classes > 0 else nn.Identity()
        self.apply(self._init_weights)