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ChenDarYen / Key-Locked-Rank-One-Editing-for-Text-to-Image-Personalization

An Pytorch implementation of the paper Key-Locked Rank One Editing for Text-to-Image Personalization
MIT License
76 stars 7 forks source link

missing 38 keys and having 2 unexpected keys #18

Open huitang0404 opened 7 months ago

huitang0404 commented 7 months ago

Restored from ./ckpt/v2-1_512-ema-pruned.ckpt with 38 missing and 2 unexpected keys Missing Keys: ['logvar', 'C_inv', 'target_input', 'model.diffusion_model.input_blocks.1.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.input_blocks.1.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.input_blocks.4.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.input_blocks.4.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.input_blocks.5.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.input_blocks.5.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.input_blocks.7.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.input_blocks.7.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.input_blocks.8.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.input_blocks.8.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.output_blocks.6.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.output_blocks.6.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.output_blocks.7.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.output_blocks.7.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.output_blocks.8.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.output_blocks.8.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.output_blocks.9.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.output_blocks.9.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.output_blocks.10.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.output_blocks.10.1.transformer_blocks.0.attn2.to_v.target_output', 'model.diffusion_model.output_blocks.11.1.transformer_blocks.0.attn2.to_k.target_output', 'model.diffusion_model.output_blocks.11.1.transformer_blocks.0.attn2.to_v.target_output', 'embedding_manager.string_to_param_dict.', 'embedding_manager.initial_embeddings.', 'embedding_manager.get_embedding_for_tkn.weight']

Unexpected Keys: ['model_ema.decay', 'model_ema.num_updates']

DO I have to worry about it?