from collections import OrderedDict def swin_convert(ckpt): new_ckpt = OrderedDict() def correct_unfold_reduction_order(x): out_channel, in_channel = x.shape x = x.reshape(out_channel, 4, in_channel // 4) x = x[:, [0, 2, 1, 3], :].transpose(1, 2).reshape(out_channel, in_channel) return x def correct_unfold_norm_order(x): in_channel = x.shape[0] x = x.reshape(4, in_channel // 4) x = x[[0, 2, 1, 3], :].transpose(0, 1).reshape(in_channel) return x for k, v in ckpt.items(): if k.startswith('head'): continue elif k.startswith('layers'): new_v = v if 'attn.' in k: new_k = k.replace('attn.', 'attn.w_msa.') elif 'mlp.' in k: if 'mlp.fc1.' in k: new_k = k.replace('mlp.fc1.', 'ffn.layers.0.0.') elif 'mlp.fc2.' in k: new_k = k.replace('mlp.fc2.', 'ffn.layers.1.') else: new_k = k.replace('mlp.', 'ffn.') elif 'downsample' in k: new_k = k if 'reduction.' in k: new_v = correct_unfold_reduction_order(v) elif 'norm.' in k: new_v = correct_unfold_norm_order(v) else: new_k = k new_k = new_k.replace('layers', 'stages', 1) elif k.startswith('patch_embed'): new_v = v if 'proj' in k: new_k = k.replace('proj', 'projection') else: new_k = k else: new_v = v new_k = k new_ckpt[new_k] = new_v return new_ckpt def vit_convert(ckpt): new_ckpt = OrderedDict() for k, v in ckpt.items(): if k.startswith('head'): continue if k.startswith('norm'): new_k = k.replace('norm.', 'ln1.') elif k.startswith('patch_embed'): if 'proj' in k: new_k = k.replace('proj', 'projection') else: new_k = k elif k.startswith('blocks'): if 'norm' in k: new_k = k.replace('norm', 'ln') elif 'mlp.fc1' in k: new_k = k.replace('mlp.fc1', 'ffn.layers.0.0') elif 'mlp.fc2' in k: new_k = k.replace('mlp.fc2', 'ffn.layers.1') elif 'attn.qkv' in k: new_k = k.replace('attn.qkv.', 'attn.attn.in_proj_') elif 'attn.proj' in k: new_k = k.replace('attn.proj', 'attn.attn.out_proj') else: new_k = k new_k = new_k.replace('blocks.', 'layers.') else: new_k = k new_ckpt[new_k] = v return new_ckpt