mirror of
https://github.com/fumiama/Retrieval-based-Voice-Conversion-WebUI.git
synced 2026-06-05 01:10:22 +08:00
70b43e8924
* chore(i18n): use english as the base language for i18n rewrite all of the locale files to use english as base for translation * fix(i18n): update rest of the scripts that rely on the chinese-base i18n translation * chore(i18n): change some of the base strings to be more correct * chore(i18n): sync locale on dev * chore(format): run black on dev --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
85 lines
2.2 KiB
Python
85 lines
2.2 KiB
Python
import traceback
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from i18n.i18n import I18nAuto
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from datetime import datetime
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import torch
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from .hash import model_hash_ckpt, hash_id, hash_similarity
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i18n = I18nAuto()
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def show_model_info(cpt, show_long_id=False):
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try:
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h = model_hash_ckpt(cpt)
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id = hash_id(h)
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idread = cpt.get("id", "None")
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hread = cpt.get("hash", "None")
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if id != idread:
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id += (
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"("
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+ i18n("Actually calculated")
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+ "), "
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+ idread
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+ "("
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+ i18n("Read from model")
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+ ")"
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)
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sim = hash_similarity(h, hread)
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if not isinstance(sim, str):
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sim = "%.2f%%" % (sim * 100)
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if not show_long_id:
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h = i18n("Hidden")
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if h != hread:
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h = i18n("Similarity") + " " + sim + " -> " + h
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elif h != hread:
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h = (
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i18n("Similarity")
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+ " "
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+ sim
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+ " -> "
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+ h
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+ "("
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+ i18n("Actually calculated")
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+ "), "
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+ hread
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+ "("
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+ i18n("Read from model")
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+ ")"
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)
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txt = f"""{i18n("Model name")}: %s
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{i18n("Sealing date")}: %s
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{i18n("模型作者")}: %s
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{i18n("Information")}: %s
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{i18n("Sampling rate")}: %s
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{i18n("Pitch guidance (f0)")}: %s
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{i18n("Version")}: %s
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{i18n("ID(short)")}: %s
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{i18n("ID(long)")}: %s""" % (
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cpt.get("name", i18n("Unknown")),
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datetime.fromtimestamp(float(cpt.get("timestamp", 0))),
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cpt.get("author", i18n("Unknown")),
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cpt.get("info", i18n("None")),
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cpt.get("sr", i18n("Unknown")),
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i18n("Exist") if cpt.get("f0", 0) == 1 else i18n("Not exist"),
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cpt.get("version", i18n("None")),
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id,
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h,
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)
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except:
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txt = traceback.format_exc()
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return txt
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def show_info(path):
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try:
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if hasattr(path, "name"):
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path = path.name
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a = torch.load(path, map_location="cpu")
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txt = show_model_info(a, show_long_id=True)
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del a
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except:
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txt = traceback.format_exc()
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return txt
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