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| import os | |
| import torch | |
| import hashlib | |
| import datetime | |
| from collections import OrderedDict | |
| def replace_keys_in_dict(d, old_key_part, new_key_part): | |
| # Use OrderedDict if the original is an OrderedDict | |
| if isinstance(d, OrderedDict): | |
| updated_dict = OrderedDict() | |
| else: | |
| updated_dict = {} | |
| for key, value in d.items(): | |
| # Replace the key part if found | |
| new_key = key.replace(old_key_part, new_key_part) | |
| # If the value is a dictionary, apply the function recursively | |
| if isinstance(value, dict): | |
| value = replace_keys_in_dict(value, old_key_part, new_key_part) | |
| updated_dict[new_key] = value | |
| return updated_dict | |
| def extract_small_model(path, name, sr, if_f0, version, epoch, step): | |
| try: | |
| ckpt = torch.load(path, map_location="cpu") | |
| pth_file = f"{name}.pth" | |
| pth_file_old_version_path = os.path.join("logs", f"{pth_file}_old_version.pth") | |
| opt = OrderedDict( | |
| weight={ | |
| key: value.half() for key, value in ckpt.items() if "enc_q" not in key | |
| } | |
| ) | |
| if "model" in ckpt: | |
| ckpt = ckpt["model"] | |
| opt = OrderedDict() | |
| opt["weight"] = {} | |
| for key in ckpt.keys(): | |
| if "enc_q" in key: | |
| continue | |
| opt["weight"][key] = ckpt[key].half() | |
| if sr == "40k": | |
| opt["config"] = [ | |
| 1025, | |
| 32, | |
| 192, | |
| 192, | |
| 768, | |
| 2, | |
| 6, | |
| 3, | |
| 0, | |
| "1", | |
| [3, 7, 11], | |
| [[1, 3, 5], [1, 3, 5], [1, 3, 5]], | |
| [10, 10, 2, 2], | |
| 512, | |
| [16, 16, 4, 4], | |
| 109, | |
| 256, | |
| 40000, | |
| ] | |
| elif sr == "48k": | |
| if version == "v1": | |
| opt["config"] = [ | |
| 1025, | |
| 32, | |
| 192, | |
| 192, | |
| 768, | |
| 2, | |
| 6, | |
| 3, | |
| 0, | |
| "1", | |
| [3, 7, 11], | |
| [[1, 3, 5], [1, 3, 5], [1, 3, 5]], | |
| [10, 6, 2, 2, 2], | |
| 512, | |
| [16, 16, 4, 4, 4], | |
| 109, | |
| 256, | |
| 48000, | |
| ] | |
| else: | |
| opt["config"] = [ | |
| 1025, | |
| 32, | |
| 192, | |
| 192, | |
| 768, | |
| 2, | |
| 6, | |
| 3, | |
| 0, | |
| "1", | |
| [3, 7, 11], | |
| [[1, 3, 5], [1, 3, 5], [1, 3, 5]], | |
| [12, 10, 2, 2], | |
| 512, | |
| [24, 20, 4, 4], | |
| 109, | |
| 256, | |
| 48000, | |
| ] | |
| elif sr == "32k": | |
| if version == "v1": | |
| opt["config"] = [ | |
| 513, | |
| 32, | |
| 192, | |
| 192, | |
| 768, | |
| 2, | |
| 6, | |
| 3, | |
| 0, | |
| "1", | |
| [3, 7, 11], | |
| [[1, 3, 5], [1, 3, 5], [1, 3, 5]], | |
| [10, 4, 2, 2, 2], | |
| 512, | |
| [16, 16, 4, 4, 4], | |
| 109, | |
| 256, | |
| 32000, | |
| ] | |
| else: | |
| opt["config"] = [ | |
| 513, | |
| 32, | |
| 192, | |
| 192, | |
| 768, | |
| 2, | |
| 6, | |
| 3, | |
| 0, | |
| "1", | |
| [3, 7, 11], | |
| [[1, 3, 5], [1, 3, 5], [1, 3, 5]], | |
| [10, 8, 2, 2], | |
| 512, | |
| [20, 16, 4, 4], | |
| 109, | |
| 256, | |
| 32000, | |
| ] | |
| opt["epoch"] = epoch | |
| opt["step"] = step | |
| opt["sr"] = sr | |
| opt["f0"] = int(if_f0) | |
| opt["version"] = version | |
| opt["creation_date"] = datetime.datetime.now().isoformat() | |
| hash_input = f"{str(ckpt)} {epoch} {step} {datetime.datetime.now().isoformat()}" | |
| model_hash = hashlib.sha256(hash_input.encode()).hexdigest() | |
| opt["model_hash"] = model_hash | |
| model = torch.load(pth_file_old_version_path, map_location=torch.device("cpu")) | |
| torch.save( | |
| replace_keys_in_dict( | |
| replace_keys_in_dict( | |
| model, ".parametrizations.weight.original1", ".weight_v" | |
| ), | |
| ".parametrizations.weight.original0", | |
| ".weight_g", | |
| ), | |
| pth_file_old_version_path, | |
| ) | |
| os.remove(pth_file_old_version_path) | |
| os.rename(pth_file_old_version_path, pth_file) | |
| except Exception as error: | |
| print(error) | |