During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\run.py", line 15, in
run_task()
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\run.py", line 11, in run_task
task_cls.start()
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\training\task\base_task.py", line 236, in start
trainer.fit(task)
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 500, in fit
self.run_pretrain_routine(model)
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 545, in run_pretrain_routine
self.get_dataloaders(ref_model)
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 1110, in get_dataloaders
self.init_train_dataloader(model)
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 1126, in init_train_dataloader
if isinstance(self.get_train_dataloader(), torch.utils.data.DataLoader):
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 63, in _get_data_loader
value = fn(self) # Lazy evaluation, done only once.
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\training\task\fs2.py", line 50, in train_dataloader
train_dataset = self.dataset_cls(hparams['train_set_name'], shuffle=True)
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\training\dataset\fs2_utils.py", line 29, in init
self.sizes = np.load(f'{self.data_dir}/{self.prefix}_lengths.npy')
File "C:\Users\computer\anaconda3\envs\diff-svc\lib\site-packages\numpy\lib\npyio.py", line 427, in load
fid = stack.enter_context(open(os_fspath(file), "rb"))
FileNotFoundError: [Errno 2] No such file or directory: 'data/test/train_lengths.npy'
121217vv
commented
1 year ago
(diff-svc) C:\Users\computer\Downloads\diff-svc-main\diff-svc-main>python run.py --config training/config_nsf.yaml --exp_name test --reset | Hparams chains: ['training/config_nsf.yaml'] | Hparams: K_step: 1000, accumulate_grad_batches: 1, audio_num_mel_bins: 128, audio_sample_rate: 44100, binarization_args: {'shuffle': False, 'with_align': True, 'with_f0': True, 'with_hubert': True, 'with_spk_embed': False, 'with_wav': False}, binarizer_cls: preprocessing.SVCpre.SVCBinarizer, binary_data_dir: data/test, check_val_every_n_epoch: 10, choose_test_manually: False, clip_grad_norm: 1, config_path: training/config_nsf.yaml, content_cond_steps: [], cwt_add_f0_loss: False, cwt_hidden_size: 128, cwt_layers: 2, cwt_loss: l1, cwt_std_scale: 0.8, datasets: ['opencpop'], debug: False, dec_ffn_kernel_size: 9, dec_layers: 4, decay_steps: 40000, decoder_type: fft, dict_dir: , diff_decoder_type: wavenet, diff_loss_type: l2, dilation_cycle_length: 4, dropout: 0.1, ds_workers: 4, dur_enc_hidden_stride_kernel: ['0,2,3', '0,2,3', '0,1,3'], dur_loss: mse, dur_predictor_kernel: 3, dur_predictor_layers: 5, enc_ffn_kernel_size: 9, enc_layers: 4, encoder_K: 8, encoder_type: fft, endless_ds: False, f0_bin: 256, f0_max: 1100.0, f0_min: 40.0, ffn_act: gelu, ffn_padding: SAME, fft_size: 2048, fmax: 16000, fmin: 40, fs2_ckpt: , gaussian_start: True, gen_dir_name: , gen_tgt_spk_id: -1, hidden_size: 256, hop_size: 512, hubert_gpu: True, hubert_path: checkpoints/hubert/hubert_soft.pt, infer: False, keep_bins: 128, lambda_commit: 0.25, lambda_energy: 0.0, lambda_f0: 1.0, lambda_ph_dur: 0.3, lambda_sent_dur: 1.0, lambda_uv: 1.0, lambda_word_dur: 1.0, load_ckpt: , log_interval: 100, loud_norm: False, lr: 0.0008, max_beta: 0.02, max_epochs: 3000, max_eval_sentences: 1, max_eval_tokens: 60000, max_frames: 42000, max_input_tokens: 60000, max_sentences: 10, max_tokens: 128000, max_updates: 1000000, mel_loss: ssim:0.5|l1:0.5, mel_vmax: 1.5, mel_vmin: -6.0, min_level_db: -120, no_fs2: True, norm_type: gn, num_ckpt_keep: 10, num_heads: 2, num_sanity_val_steps: 1, num_spk: 1, num_test_samples: 0, num_valid_plots: 10, optimizer_adam_beta1: 0.9, optimizer_adam_beta2: 0.98, out_wav_norm: False, pe_ckpt: checkpoints/0102_xiaoma_pe/model_ckpt_steps_60000.ckpt, pe_enable: False, perform_enhance: True, pitch_ar: False, pitch_enc_hidden_stride_kernel: ['0,2,5', '0,2,5', '0,2,5'], pitch_extractor: parselmouth, pitch_loss: l2, pitch_norm: log, pitch_type: frame, pndm_speedup: 10, pre_align_args: {'allow_no_txt': False, 'denoise': False, 'forced_align': 'mfa', 'txt_processor': 'zh_g2pM', 'use_sox': True, 'use_tone': False}, pre_align_cls: data_gen.singing.pre_align.SingingPreAlign, predictor_dropout: 0.5, predictor_grad: 0.1, predictor_hidden: -1, predictor_kernel: 5, predictor_layers: 5, prenet_dropout: 0.5, prenet_hidden_size: 256, pretrain_fs_ckpt: , processed_data_dir: xxx, profile_infer: False, raw_data_dir: data/test, ref_norm_layer: bn, rel_pos: True, reset_phone_dict: True, residual_channels: 384, residual_layers: 20, save_best: False, save_ckpt: True, save_codes: ['configs', 'modules', 'src', 'utils'], save_f0: True, save_gt: False, schedule_type: linear, seed: 1234, sort_by_len: True, speaker_id: test, spec_max: [0.0], spec_min: [-5.0], spk_cond_steps: [], stop_token_weight: 5.0, task_cls: training.task.SVC_task.SVCTask, test_ids: [], test_input_dir: , test_num: 0, test_prefixes: ['test'], test_set_name: test, timesteps: 1000, train_set_name: train, use_amp: True, use_crepe: True, use_denoise: False, use_energy_embed: False, use_gt_dur: False, use_gt_f0: False, use_midi: False, use_nsf: True, use_pitch_embed: True, use_pos_embed: True, use_spk_embed: False, use_spk_id: False, use_split_spk_id: False, use_uv: False, use_var_enc: False, use_vec: False, val_check_interval: 2000, valid_num: 0, valid_set_name: valid, validate: False, vocoder: network.vocoders.nsf_hifigan.NsfHifiGAN, vocoder_ckpt: checkpoints/nsf_hifigan/model, warmup_updates: 2000, wav2spec_eps: 1e-6, weight_decay: 0, win_size: 2048, work_dir: checkpoints/test, | Mel losses: {'ssim': 0.5, 'l1': 0.5} Error: HifiGAN model file is not found! | model Trainable Parameters: 33.709M Traceback (most recent call last): File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 60, in _get_data_loader value = getattr(self, attr_name) File "C:\Users\computer\anaconda3\envs\diff-svc\lib\site-packages\torch\nn\modules\module.py", line 1269, in getattr raise AttributeError("'{}' object has no attribute '{}'".format( AttributeError: 'SVCTask' object has no attribute '_lazy_train_dataloader'
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\run.py", line 15, in
run_task()
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\run.py", line 11, in run_task
task_cls.start()
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\training\task\base_task.py", line 236, in start
trainer.fit(task)
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 500, in fit
self.run_pretrain_routine(model)
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 545, in run_pretrain_routine
self.get_dataloaders(ref_model)
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 1110, in get_dataloaders
self.init_train_dataloader(model)
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 1126, in init_train_dataloader
if isinstance(self.get_train_dataloader(), torch.utils.data.DataLoader):
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\utils\pl_utils.py", line 63, in _get_data_loader
value = fn(self) # Lazy evaluation, done only once.
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\training\task\fs2.py", line 50, in train_dataloader
train_dataset = self.dataset_cls(hparams['train_set_name'], shuffle=True)
File "C:\Users\computer\Downloads\diff-svc-main\diff-svc-main\training\dataset\fs2_utils.py", line 29, in init
self.sizes = np.load(f'{self.data_dir}/{self.prefix}_lengths.npy')
File "C:\Users\computer\anaconda3\envs\diff-svc\lib\site-packages\numpy\lib\npyio.py", line 427, in load
fid = stack.enter_context(open(os_fspath(file), "rb"))
FileNotFoundError: [Errno 2] No such file or directory: 'data/test/train_lengths.npy'
뭘 어떻게 고쳐야하나요
참고로 GPU메모리가 6GB인경우로 했습니다.