156 lines
7.8 KiB
Python
156 lines
7.8 KiB
Python
import os
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import torch
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from safetensors.torch import save_file, load_file
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reshapes = ["first_stage_model.decoder.mid.attn_1.to_k.weight",
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"first_stage_model.decoder.mid.attn_1.to_q.weight",
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"first_stage_model.decoder.mid.attn_1.to_v.weight",
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"first_stage_model.encoder.mid.attn_1.to_k.weight",
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"first_stage_model.encoder.mid.attn_1.to_q.weight",
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"first_stage_model.encoder.mid.attn_1.to_v.weight",
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"first_stage_model.decoder.mid.attn_1.to_out.0.weight",
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"first_stage_model.encoder.mid.attn_1.to_out.0.weight"
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]
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def _reshape(state_dict, key):
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if key in reshapes:
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if state_dict[key].dim() == 2:
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old_shape = state_dict[key].shape
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# add two dimensions after last dim
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state_dict[key] = state_dict[key].unsqueeze(-1).unsqueeze(-1)
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print(f" ** reshaped {key} from {old_shape} to {state_dict[key].shape}")
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else:
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print(f" ** skipping {key} because it is already correct shape {state_dict[key].shape}")
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def fix_vae_keys(state_dict, is_sd1=True):
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if not is_sd1:
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return state_dict
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new_state_dict = {}
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with open("backdate_vae_keys.log", "w") as f:
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f.write(f"keys:\n")
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changed_i = 0
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if 'cond_stage_model.transformer.text_model.embeddings.position_ids' not in state_dict:
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# openai clip-l for some reason has this defined as part of its state_dict, which is dumb, but whatever
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state_dict['cond_stage_model.transformer.text_model.embeddings.position_ids'] = torch.linspace(0, 76, 77, dtype=torch.int64).unsqueeze(0)
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for key in state_dict.keys():
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new_key = key
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_reshape(state_dict, key)
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if key.startswith("first_stage_model"):
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if ".to_q" in key:
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print(f" * backdating {key} {state_dict[key].shape}")
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new_key = new_key.replace('.to_q.', '.q.')
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print(f" ** new key -> {new_key}\n")
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elif ".to_k" in key:
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print(f" * backdating {key} {state_dict[key].shape}")
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new_key = new_key.replace('.to_k.', '.k.')
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print(f" ** new key -> {new_key}\n")
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elif ".to_v" in key:
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print(f" * backdating {key} {state_dict[key].shape}")
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new_key = new_key.replace('.to_v.', '.v.')
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print(f" ** new key -> {new_key}\n")
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elif ".to_out.0" in key:
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print(f" * backdating {key} {state_dict[key].shape}")
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new_key = new_key.replace('.to_out.0', '.proj_out')
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print(f" ** new key -> {new_key} {state_dict[key].shape}\n")
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new_state_dict[new_key] = state_dict[key]
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changed = 1 if key != new_key else 0
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f.write(f"{changed}: {key} -- {new_key} {new_state_dict[new_key].shape}\n")
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return new_state_dict
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def _backdate_keys(filepath, state_dict):
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new_state_dict = fix_vae_keys(state_dict)
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base_path_without_ext = os.path.splitext(filepath)[0]
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ext = os.path.splitext(filepath)[1]
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new_path = f"{base_path_without_ext}_fixed{ext}"
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print (f"Saving to {new_path}")
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save_file(new_state_dict, new_path)
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def _compare_keys(filea_state_dict, fileb_state_dict):
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#remove cond_stage_model.transformer.text_model.embeddings.position_ids key
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if 'cond_stage_model.transformer.text_model.embeddings.position_ids' in filea_state_dict:
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filea_state_dict.pop('cond_stage_model.transformer.text_model.embeddings.position_ids', None)
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if 'cond_stage_model.transformer.text_model.embeddings.position_ids' in fileb_state_dict:
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fileb_state_dict.pop('cond_stage_model.transformer.text_model.embeddings.position_ids', None)
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# sort the keys for comparison (best shot we have at a fair comparison without trying to count params and other nonsense)
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filea_state_dict_keys = sorted(filea_state_dict.keys())
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fileb_state_dict_keys = sorted(fileb_state_dict.keys())
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print("filea keys <-----> fileb keys")
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# compare the keys line by line
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for filea_key, fileb_key in zip(filea_state_dict_keys, fileb_state_dict_keys):
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if filea_key != fileb_key:
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print("Mismatched keys:")
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print (f" filea key: {filea_key} {filea_state_dict[filea_key].shape}")
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print (f" fileb key: {fileb_key} {fileb_state_dict[fileb_key].shape}")
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else:
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#print (f"{ckpt_key} == {st_key}")
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pass
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print("filea keys <-----> fileb keys")
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def _load(filepath):
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if filepath.endswith(".safetensors"):
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print(f" Loading {filepath} loading as safetensors file")
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state_dict = load_file(filepath)
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else: # LDM ckpt
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print(f" Loading {filepath} loading as LDM checkpoint")
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state_dict = torch.load(filepath, map_location='cpu')['state_dict']
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return state_dict
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def _dump_keys(filepath, state_dict):
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with open(filepath, "w") as f:
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state_dict_keys = sorted(state_dict.keys())
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for key in state_dict_keys:
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f.write(f"{key} - {state_dict[key].shape}\n")
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if __name__ == "__main__":
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print("BACKDATE AutoencoderKL/VAE KEYS TO OLD NAMES SCRIPT OF DOOM")
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print("================================")
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print(" --filea <path to ckpt or safetensors file> file to backdate the VAE keys (will make a copy as <filename>_fixed.safetensors)")
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print(" --fileb <path to ckpt or safetensors file> to compare keys to filea")
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print(" --compare to run keys comparison (requires both --filea and --fileb)")
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print(" --backdate to backdate keys (only for --filea)")
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print(" --dumpkeys to write key and shapes for either or both files keys for files to '<filename>.txt'")
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print(" You must specify one of --compare or --backdate or --dumpkeys to do anything.")
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print(" ex. python utils/backdate_vae_keys.py --filea my_finetune.safetensors --fileb original_sd15.ckpt --compare")
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print(" ex. python utils/backdate_vae_keys.py --filea my_finetune.safetensors --backdate")
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print(" ex. python utils/backdate_vae_keys.py --filea what_is_this_model_shape.safetensors --dumpkeys")
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import argparse
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parser = argparse.ArgumentParser()
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parser.add_argument("--filea", type=str, required=True, help="Path to the safetensors file to fix")
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parser.add_argument("--fileb", type=str, required=False, help="Path to the safetensors file to fix")
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parser.add_argument("--compare", action="store_true", help="Compare keys")
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parser.add_argument("--backdate", action="store_true", help="backdates the keys in filea only")
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parser.add_argument("--dumpkeys", action="store_true", help="dump keys to txt file")
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args = parser.parse_args()
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filea_state_dict = _load(args.filea) if args.filea else None
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fileb_state_dict = _load(args.fileb) if args.fileb else None
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if args.dumpkeys:
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print(f"Dumping keys to txt files")
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if args.filea:
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_dump_keys(f"{os.path.splitext(args.filea)[0]}.txt", filea_state_dict)
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if args.fileb:
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_dump_keys(f"{os.path.splitext(args.fileb)[0]}.txt", fileb_state_dict)
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if args.compare and not args.backdate:
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print(f"Comparing keys in {args.filea} to {args.fileb}")
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_compare_keys(filea_state_dict, fileb_state_dict)
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elif args.backdate:
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print(f"Backdating keys in {args.filea}")
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print(f" ** ignoring {args.fileb}") if args.fileb else None
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_backdate_keys(args.filea, filea_state_dict)
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else:
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print("Please specify only --compare with both --filea and --fileb to compare keys and print differences to console")
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print(" ... or --backdate with only --filea to backdate its keys to old LDM names and save to <filea>_fixed.safetensors")
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