| import os |
| import torch |
| import hashlib |
| import datetime |
| from collections import OrderedDict |
|
|
|
|
| def replace_keys_in_dict(d, old_key_part, new_key_part): |
| |
| if isinstance(d, OrderedDict): |
| updated_dict = OrderedDict() |
| else: |
| updated_dict = {} |
| for key, value in d.items(): |
| |
| new_key = key.replace(old_key_part, new_key_part) |
| |
| 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) |
|
|