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