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Runtime error
| import os | |
| import argparse | |
| from tqdm import tqdm | |
| from random import shuffle | |
| import json | |
| config_template = { | |
| "train": { | |
| "log_interval": 200, | |
| "eval_interval": 1000, | |
| "seed": 1234, | |
| "epochs": 10000, | |
| "learning_rate": 2e-4, | |
| "betas": [0.8, 0.99], | |
| "eps": 1e-9, | |
| "batch_size": 12, | |
| "fp16_run": False, | |
| "lr_decay": 0.999875, | |
| "segment_size": 17920, | |
| "init_lr_ratio": 1, | |
| "warmup_epochs": 0, | |
| "c_mel": 45, | |
| "c_kl": 1.0, | |
| "use_sr": True, | |
| "max_speclen": 384, | |
| "port": "8001" | |
| }, | |
| "data": { | |
| "training_files":"filelists/train.txt", | |
| "validation_files":"filelists/val.txt", | |
| "max_wav_value": 32768.0, | |
| "sampling_rate": 48000, | |
| "filter_length": 1280, | |
| "hop_length": 320, | |
| "win_length": 1280, | |
| "n_mel_channels": 80, | |
| "mel_fmin": 0.0, | |
| "mel_fmax": None | |
| }, | |
| "model": { | |
| "inter_channels": 192, | |
| "hidden_channels": 192, | |
| "filter_channels": 768, | |
| "n_heads": 2, | |
| "n_layers": 6, | |
| "kernel_size": 3, | |
| "p_dropout": 0.1, | |
| "resblock": "1", | |
| "resblock_kernel_sizes": [3,7,11], | |
| "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]], | |
| "upsample_rates": [10,8,2,2], | |
| "upsample_initial_channel": 512, | |
| "upsample_kernel_sizes": [16,16,4,4], | |
| "n_layers_q": 3, | |
| "use_spectral_norm": False, | |
| "gin_channels": 256, | |
| "ssl_dim": 256, | |
| "n_speakers": 0, | |
| }, | |
| "spk":{ | |
| "nen": 0, | |
| "paimon": 1, | |
| "yunhao": 2 | |
| } | |
| } | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--train_list", type=str, default="./filelists/train.txt", help="path to train list") | |
| parser.add_argument("--val_list", type=str, default="./filelists/val.txt", help="path to val list") | |
| parser.add_argument("--test_list", type=str, default="./filelists/test.txt", help="path to test list") | |
| parser.add_argument("--source_dir", type=str, default="./dataset/48k", help="path to source dir") | |
| args = parser.parse_args() | |
| train = [] | |
| val = [] | |
| test = [] | |
| idx = 0 | |
| spk_dict = {} | |
| spk_id = 0 | |
| for speaker in tqdm(os.listdir(args.source_dir)): | |
| spk_dict[speaker] = spk_id | |
| spk_id += 1 | |
| wavs = [os.path.join(args.source_dir, speaker, i)for i in os.listdir(os.path.join(args.source_dir, speaker))] | |
| wavs = [i for i in wavs if i.endswith("wav")] | |
| shuffle(wavs) | |
| train += wavs[2:-10] | |
| val += wavs[:2] | |
| test += wavs[-10:] | |
| n_speakers = len(spk_dict.keys())*2 | |
| shuffle(train) | |
| shuffle(val) | |
| shuffle(test) | |
| print("Writing", args.train_list) | |
| with open(args.train_list, "w") as f: | |
| for fname in tqdm(train): | |
| wavpath = fname | |
| f.write(wavpath + "\n") | |
| print("Writing", args.val_list) | |
| with open(args.val_list, "w") as f: | |
| for fname in tqdm(val): | |
| wavpath = fname | |
| f.write(wavpath + "\n") | |
| print("Writing", args.test_list) | |
| with open(args.test_list, "w") as f: | |
| for fname in tqdm(test): | |
| wavpath = fname | |
| f.write(wavpath + "\n") | |
| config_template["model"]["n_speakers"] = n_speakers | |
| config_template["spk"] = spk_dict | |
| print("Writing configs/config.json") | |
| with open("configs/config.json", "w") as f: | |
| json.dump(config_template, f, indent=2) | |