import os import sys import traceback from collections import OrderedDict import torch def savee(ckpt, sr, if_f0, name, epoch, version, hps, relative_to="."): try: opt = OrderedDict() opt["weight"] = {} for key in ckpt.keys(): if "enc_q" in key: continue opt["weight"][key] = ckpt[key].half() opt["config"] = [ hps.data.filter_length // 2 + 1, 32, hps.model.inter_channels, hps.model.hidden_channels, hps.model.filter_channels, hps.model.n_heads, hps.model.n_layers, hps.model.kernel_size, hps.model.p_dropout, hps.model.resblock, hps.model.resblock_kernel_sizes, hps.model.resblock_dilation_sizes, hps.model.upsample_rates, hps.model.upsample_initial_channel, hps.model.upsample_kernel_sizes, hps.model.spk_embed_dim, hps.model.gin_channels, hps.data.sampling_rate, ] opt["info"] = "%sepoch" % epoch opt["sr"] = sr opt["f0"] = if_f0 opt["version"] = version torch.save(opt, os.path.join(relative_to, "assets/weights/%s.pth" % name)) return "Success." except: return traceback.format_exc() def show_info(path): try: a = torch.load(path, map_location="cpu") return "模型信息:%s\n采样率:%s\n模型是否输入音高引导:%s\n版本:%s" % ( a.get("info", "None"), a.get("sr", "None"), a.get("f0", "None"), a.get("version", "None"), ) except: return traceback.format_exc() def extract_small_model(path, name, sr, if_f0, info, version): try: ckpt = torch.load(path, map_location="cpu") 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, ] if info == "": info = "Extracted model." opt["info"] = info opt["version"] = version opt["sr"] = sr opt["f0"] = int(if_f0) torch.save(opt, "assets/weights/%s.pth" % name) return "Success." except: return traceback.format_exc() def change_info(path, info, name): try: ckpt = torch.load(path, map_location="cpu") ckpt["info"] = info if name == "": name = os.path.basename(path) torch.save(ckpt, "assets/weights/%s" % name) return "Success." except: return traceback.format_exc()