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Mangio621 / Mangio-RVC-Fork

*CREPE+HYBRID TRAINING* A very experimental fork of the Retrieval-based-Voice-Conversion-WebUI repo that incorporates a variety of other f0 methods, along with a hybrid f0 nanmedian method.
MIT License
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Trying to train results in this error #12

Closed Chris2918 closed 1 year ago

Chris2918 commented 1 year ago

start preprocess ['trainset_preprocess_pipeline_print.py', 'C:\Users\lccji\Documents\ConkerDataset', '40000', '16', 'C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker', 'False'] C:\Users\lccji\Documents\ConkerDataset/12.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/15.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/27.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/21.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/17.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/16.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/23.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/22.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/13.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/01.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/31.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/20.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/46.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/35.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/ahheck.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/40.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/48.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/hereyougo.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/32.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/54.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/25.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/illpressb.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/howmuch.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/ohcharming.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/29.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/greedyconker.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/afryingpan.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/hiveisgone.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/53.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/illgetitforya.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/beardyummbirdy.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/94673910fdddac2d06e7536fbd9768e4.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/yeahthanks.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/weaponscool.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/okaysuitsme.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/confidencepills.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/whatdoesthatmean.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/47.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/herewegoagain.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/luckyibroughtthisaswell.wav->Suc. end preprocess

Traceback (most recent call last): File "C:\Users\lccji\Downloads\Mangio-RVC-Fork-main\extract_f0_print.py", line 29, in extraction_crepe_hop_length = int(sys.argv[4]) IndexError: list index out of range

['extract_feature_print.py', 'cuda:0', '1', '0', '0', 'C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker', 'v2'] C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker load model(s) from hubert_base.pt 2023-06-13 23:52:30 | INFO | fairseq.tasks.hubert_pretraining | current directory is C:\Users\lccji\Downloads\Mangio-RVC-Fork-main 2023-06-13 23:52:30 | INFO | fairseq.tasks.hubert_pretraining | HubertPretrainingTask Config {'_name': 'hubert_pretraining', 'data': 'metadata', 'fine_tuning': False, 'labels': ['km'], 'label_dir': 'label', 'label_rate': 50.0, 'sample_rate': 16000, 'normalize': False, 'enable_padding': False, 'max_keep_size': None, 'max_sample_size': 250000, 'min_sample_size': 32000, 'single_target': False, 'random_crop': True, 'pad_audio': False} 2023-06-13 23:52:30 | INFO | fairseq.models.hubert.hubert | HubertModel Config: {'_name': 'hubert', 'label_rate': 50.0, 'extractor_mode': default, 'encoder_layers': 12, 'encoder_embed_dim': 768, 'encoder_ffn_embed_dim': 3072, 'encoder_attention_heads': 12, 'activation_fn': gelu, 'layer_type': transformer, 'dropout': 0.1, 'attention_dropout': 0.1, 'activation_dropout': 0.0, 'encoder_layerdrop': 0.05, 'dropout_input': 0.1, 'dropout_features': 0.1, 'final_dim': 256, 'untie_final_proj': True, 'layer_norm_first': False, 'conv_feature_layers': '[(512,10,5)] + [(512,3,2)] 4 + [(512,2,2)] 2', 'conv_bias': False, 'logit_temp': 0.1, 'target_glu': False, 'feature_grad_mult': 0.1, 'mask_length': 10, 'mask_prob': 0.8, 'mask_selection': static, 'mask_other': 0.0, 'no_mask_overlap': False, 'mask_min_space': 1, 'mask_channel_length': 10, 'mask_channel_prob': 0.0, 'mask_channel_selection': static, 'mask_channel_other': 0.0, 'no_mask_channel_overlap': False, 'mask_channel_min_space': 1, 'conv_pos': 128, 'conv_pos_groups': 16, 'latent_temp': [2.0, 0.5, 0.999995], 'skip_masked': False, 'skip_nomask': False, 'checkpoint_activations': False, 'required_seq_len_multiple': 2, 'depthwise_conv_kernel_size': 31, 'attn_type': '', 'pos_enc_type': 'abs', 'fp16': False} move model to cuda all-feature-158 all-feature-done ['extract_feature_print.py', 'cuda:0', '1', '0', '0', 'C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker', 'v2'] C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker load model(s) from hubert_base.pt move model to cuda all-feature-158 all-feature-done

INFO:Conker:{'train': {'log_interval': 200, 'seed': 1234, 'epochs': 20000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 4, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 12800, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'max_wav_value': 32768.0, 'sampling_rate': 40000, 'filter_length': 2048, 'hop_length': 400, 'win_length': 2048, 'n_mel_channels': 125, 'mel_fmin': 0.0, 'mel_fmax': None, 'training_files': './logs\Conker/filelist.txt'}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 10, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'use_spectral_norm': False, 'gin_channels': 256, 'spk_embed_dim': 109}, 'model_dir': './logs\Conker', 'experiment_dir': './logs\Conker', 'save_every_epoch': 5, 'name': 'Conker', 'total_epoch': 250, 'pretrainG': 'pretrained_v2/f0G40k.pth', 'pretrainD': 'pretrained_v2/f0D40k.pth', 'version': 'v2', 'gpus': '0', 'sample_rate': '40k', 'if_f0': 1, 'if_latest': 1, 'save_every_weights': '1', 'if_cache_data_in_gpu': 1} INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 0 INFO:torch.distributed.distributed_c10d:Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 1 nodes. gin_channels: 256 self.spk_embed_dim: 109 ./logs\Conker\D_1800.pth INFO:Conker:loaded pretrained pretrained_v2/f0G40k.pth pretrained_v2/f0D40k.pth

C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error. Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ..\aten\src\ATen\native\SpectralOps.cpp:867.) return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined] INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration. C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\autograd\__init__.py:200: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance. grad.sizes() = [64, 1, 4], strides() = [4, 1, 1] bucket_view.sizes() = [64, 1, 4], strides() = [4, 4, 1] (Triggered internally at ..\torch\csrc\distributed\c10d\reducer.cpp:337.) Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass INFO:Conker:Train Epoch: 1 [0%] INFO:Conker:[0, 0.0001] INFO:Conker:loss_disc=4.443, loss_gen=1.567, loss_fm=1.197,loss_mel=25.497, loss_kl=9.000 DEBUG:matplotlib:matplotlib data path: C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\mpl-data DEBUG:matplotlib:CONFIGDIR=C:\Users\lccji\.matplotlib DEBUG:matplotlib:interactive is False DEBUG:matplotlib:platform is win32 INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration. INFO:Conker:====> Epoch: 1 [2023-06-13 23:52:47] | (0:00:03.732546) Process Process-1: Traceback (most recent call last): File "C:\Users\lccji\AppData\Local\Programs\Python\Python310\Lib\multiprocessing\process.py", line 314, in _bootstrap self.run() File "C:\Users\lccji\AppData\Local\Programs\Python\Python310\Lib\multiprocessing\process.py", line 108, in run self._target(*self._args, **self._kwargs) File "C:\Users\lccji\Downloads\Mangio-RVC-Fork-main\train_nsf_sim_cache_sid_load_pretrain.py", line 219, in run train_and_evaluate( File "C:\Users\lccji\Downloads\Mangio-RVC-Fork-main\train_nsf_sim_cache_sid_load_pretrain.py", line 421, in train_and_evaluate wave = commons.slice_segments( File "C:\Users\lccji\Downloads\Mangio-RVC-Fork-main\infer_pack\commons.py", line 49, in slice_segments ret[i] = x[i, :, idx_str:idx_end] RuntimeError: The expanded size of the tensor (12800) must match the existing size (0) at non-singleton dimension 1. Target sizes: [1, 12800]. Tensor sizes: [0] I am using the GUI and the latest version of the fork.
Chris2918 commented 1 year ago

I also tried it in the CLI and that didn't work as well. Mangio-RVC-Fork Train-CLI: Training... write filelist done use gpus: 0 python train_nsf_sim_cache_sid_load_pretrain.py -e Conker -sr 40k -f0 1 -bs 8 -g 0 -te 250 -se 50 -pg pretrained_v2/f0G40k.pth -pd pretrained_v2/f0D40k.pth -l 1 -c 1 -sw 1 -v v2 INFO:Conker:{'train': {'log_interval': 200, 'seed': 1234, 'epochs': 20000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 8, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 12800, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'max_wav_value': 32768.0, 'sampling_rate': 40000, 'filter_length': 2048, 'hop_length': 400, 'win_length': 2048, 'n_mel_channels': 125, 'mel_fmin': 0.0, 'mel_fmax': None, 'training_files': './logs\Conker/filelist.txt'}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 10, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'use_spectral_norm': False, 'gin_channels': 256, 'spk_embed_dim': 109}, 'model_dir': './logs\Conker', 'experiment_dir': './logs\Conker', 'save_every_epoch': 50, 'name': 'Conker', 'total_epoch': 250, 'pretrainG': 'pretrained_v2/f0G40k.pth', 'pretrainD': 'pretrained_v2/f0D40k.pth', 'version': 'v2', 'gpus': '0', 'sample_rate': '40k', 'if_f0': 1, 'if_latest': 1, 'save_every_weights': '1', 'if_cache_data_in_gpu': 1} INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 0 INFO:torch.distributed.distributed_c10d:Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 1 nodes. gin_channels: 256 self.spk_embed_dim: 109 ./logs\Conker\D_1800.pth INFO:Conker:loaded pretrained pretrained_v2/f0G40k.pth pretrained_v2/f0D40k.pth

C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error. Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ..\aten\src\ATen\native\SpectralOps.cpp:867.) return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined] INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration. C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\autograd\__init__.py:200: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance. grad.sizes() = [64, 1, 4], strides() = [4, 1, 1] bucket_view.sizes() = [64, 1, 4], strides() = [4, 4, 1] (Triggered internally at ..\torch\csrc\distributed\c10d\reducer.cpp:337.) Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass INFO:Conker:Train Epoch: 1 [0%] INFO:Conker:[0, 0.0001] INFO:Conker:loss_disc=4.444, loss_gen=1.568, loss_fm=1.276,loss_mel=26.549, loss_kl=9.000 DEBUG:matplotlib:matplotlib data path: C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\mpl-data DEBUG:matplotlib:CONFIGDIR=C:\Users\lccji\.matplotlib DEBUG:matplotlib:interactive is False DEBUG:matplotlib:platform is win32 INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration. Process Process-1: Traceback (most recent call last): File "C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\multiprocessing\process.py", line 314, in _bootstrap self.run() File "C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\multiprocessing\process.py", line 108, in run self._target(*self._args, **self._kwargs) File "C:\Users\lccji\Downloads\Mangio-RVC-Fork-main\train_nsf_sim_cache_sid_load_pretrain.py", line 219, in run train_and_evaluate( File "C:\Users\lccji\Downloads\Mangio-RVC-Fork-main\train_nsf_sim_cache_sid_load_pretrain.py", line 421, in train_and_evaluate wave = commons.slice_segments( File "C:\Users\lccji\Downloads\Mangio-RVC-Fork-main\infer_pack\commons.py", line 49, in slice_segments ret[i] = x[i, :, idx_str:idx_end] RuntimeError: The expanded size of the tensor (12800) must match the existing size (0) at non-singleton dimension 1. Target sizes: [1, 12800]. Tensor sizes: [0]
Mangio621 commented 1 year ago

Pushed a few changes. Let me know what happens now.

Chris2918 commented 1 year ago

Sorry for not responding sooner! Anyways, training appears to work now! I've just started training my model. Here is the output so far: start preprocess ['trainset_preprocess_pipeline_print.py', 'C:\Users\lccji\Documents\ConkerDataset', '40000', '16', 'C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker', 'False'] C:\Users\lccji\Documents\ConkerDataset/15.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/01.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/27.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/12.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/23.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/16.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/17.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/22.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/32.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/20.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/21.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/35.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/29.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/13.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/25.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/31.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/46.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/40.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/ahheck.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/hereyougo.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/54.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/confidencepills.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/howmuch.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/48.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/illgetitforya.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/hiveisgone.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/illpressb.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/greedyconker.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/53.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/ohcharming.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/94673910fdddac2d06e7536fbd9768e4.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/afryingpan.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/beardyummbirdy.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/okaysuitsme.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/herewegoagain.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/47.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/weaponscool.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/yeahthanks.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/whatdoesthatmean.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/luckyibroughtthisaswell.wav->Suc. end preprocess start preprocess ['trainset_preprocess_pipeline_print.py', 'C:\Users\lccji\Documents\ConkerDataset', '40000', '16', 'C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker', 'False'] C:\Users\lccji\Documents\ConkerDataset/15.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/01.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/27.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/12.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/23.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/16.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/17.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/22.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/32.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/20.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/21.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/35.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/29.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/13.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/25.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/31.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/46.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/40.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/ahheck.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/hereyougo.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/54.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/confidencepills.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/howmuch.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/48.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/illgetitforya.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/hiveisgone.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/illpressb.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/greedyconker.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/53.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/ohcharming.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/94673910fdddac2d06e7536fbd9768e4.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/afryingpan.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/beardyummbirdy.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/okaysuitsme.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/herewegoagain.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/47.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/weaponscool.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/yeahthanks.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/whatdoesthatmean.wav->Suc. C:\Users\lccji\Documents\ConkerDataset/luckyibroughtthisaswell.wav->Suc. end preprocess

EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> ['extract_f0_print.py', 'C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker', '16', 'harvest', '64'] EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/10_1.wav EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/0_1.wav EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/10_2.wav EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/10_3.wav EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP 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f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/10_8.wav EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/11_2.wav EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> todo-f0-10 f0ing,now-0,all-10,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/12_1.wav EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> todo-f0-10 f0ing,now-0,all-10,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/12_2.wav EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> todo-f0-10 f0ing,now-0,all-10,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/12_4.wav EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> todo-f0-10 f0ing,now-0,all-10,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/12_6.wav EXTRACTION CREPE HOP LENGTH: 64 EXTRACTION CREPE HOP LENGTH TYPE: <class 'int'> todo-f0-10 f0ing,now-0,all-10,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/12_3.wav f0ing,now-2,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/18_16.wav f0ing,now-2,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/18_19.wav f0ing,now-2,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/18_13.wav f0ing,now-2,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/18_12.wav f0ing,now-2,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/18_2.wav f0ing,now-2,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/18_3.wav f0ing,now-2,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/18_4.wav 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f0ing,now-10,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/7_1.wav f0ing,now-10,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/9_3.wav

['extract_feature_print.py', 'cuda:0', '1', '0', '0', 'C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker', 'v2'] C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker load model(s) from hubert_base.pt 2023-06-15 17:36:35 | INFO | fairseq.tasks.hubert_pretraining | current directory is C:\Users\lccji\Downloads\Mangio-RVC-Fork-main 2023-06-15 17:36:35 | INFO | fairseq.tasks.hubert_pretraining | HubertPretrainingTask Config {'_name': 'hubert_pretraining', 'data': 'metadata', 'fine_tuning': False, 'labels': ['km'], 'label_dir': 'label', 'label_rate': 50.0, 'sample_rate': 16000, 'normalize': False, 'enable_padding': False, 'max_keep_size': None, 'max_sample_size': 250000, 'min_sample_size': 32000, 'single_target': False, 'random_crop': True, 'pad_audio': False} 2023-06-15 17:36:35 | INFO | fairseq.models.hubert.hubert | HubertModel Config: {'_name': 'hubert', 'label_rate': 50.0, 'extractor_mode': default, 'encoder_layers': 12, 'encoder_embed_dim': 768, 'encoder_ffn_embed_dim': 3072, 'encoder_attention_heads': 12, 'activation_fn': gelu, 'layer_type': transformer, 'dropout': 0.1, 'attention_dropout': 0.1, 'activation_dropout': 0.0, 'encoder_layerdrop': 0.05, 'dropout_input': 0.1, 'dropout_features': 0.1, 'final_dim': 256, 'untie_final_proj': True, 'layer_norm_first': False, 'conv_feature_layers': '[(512,10,5)] + [(512,3,2)] 4 + [(512,2,2)] 2', 'conv_bias': False, 'logit_temp': 0.1, 'target_glu': False, 'feature_grad_mult': 0.1, 'mask_length': 10, 'mask_prob': 0.8, 'mask_selection': static, 'mask_other': 0.0, 'no_mask_overlap': False, 'mask_min_space': 1, 'mask_channel_length': 10, 'mask_channel_prob': 0.0, 'mask_channel_selection': static, 'mask_channel_other': 0.0, 'no_mask_channel_overlap': False, 'mask_channel_min_space': 1, 'conv_pos': 128, 'conv_pos_groups': 16, 'latent_temp': [2.0, 0.5, 0.999995], 'skip_masked': False, 'skip_nomask': False, 'checkpoint_activations': False, 'required_seq_len_multiple': 2, 'depthwise_conv_kernel_size': 31, 'attn_type': '', 'pos_enc_type': 'abs', 'fp16': False} move model to cuda all-feature-171 all-feature-done ['extract_f0_print.py', 'C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker', '16', 'harvest', '64'] todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/10_1.wav todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/0_1.wav todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/10_2.wav todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/10_3.wav todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/10_4.wav todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/10_7.wav todo-f0-11 todo-f0-11 todo-f0-11 todo-f0-11 f0ing,now-0,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/10_6.wav 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f0ing,now-8,all-10,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/37_2.wav f0ing,now-10,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/8_4.wav f0ing,now-10,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/8_2.wav f0ing,now-10,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/7_1.wav f0ing,now-10,all-11,-C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker/1_16k_wavs/9_3.wav ['extract_feature_print.py', 'cuda:0', '1', '0', '0', 'C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker', 'v2'] C:\Users\lccji\Downloads\Mangio-RVC-Fork-main/logs/Conker load model(s) from hubert_base.pt move model to cuda all-feature-171 all-feature-done

INFO:Conker:{'train': {'log_interval': 200, 'seed': 1234, 'epochs': 20000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 4, 'fp16_run': True, 'lr_decay': 0.999875, 'segment_size': 12800, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'max_wav_value': 32768.0, 'sampling_rate': 40000, 'filter_length': 2048, 'hop_length': 400, 'win_length': 2048, 'n_mel_channels': 125, 'mel_fmin': 0.0, 'mel_fmax': None, 'training_files': './logs\Conker/filelist.txt'}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 10, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'use_spectral_norm': False, 'gin_channels': 256, 'spk_embed_dim': 109}, 'model_dir': './logs\Conker', 'experiment_dir': './logs\Conker', 'save_every_epoch': 50, 'name': 'Conker', 'total_epoch': 800, 'pretrainG': 'pretrained_v2/f0G40k.pth', 'pretrainD': 'pretrained_v2/f0D40k.pth', 'version': 'v2', 'gpus': '0', 'sample_rate': '40k', 'if_f0': 1, 'if_latest': 1, 'save_every_weights': '1', 'if_cache_data_in_gpu': 0} INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 0 INFO:torch.distributed.distributed_c10d:Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 1 nodes. gin_channels: 256 self.spk_embed_dim: 109 ./logs\Conker\D_1800.pth INFO:Conker:loaded pretrained pretrained_v2/f0G40k.pth

INFO:Conker:loaded pretrained pretrained_v2/f0D40k.pth C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error. Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ..\aten\src\ATen\native\SpectralOps.cpp:867.) return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined] C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error. Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ..\aten\src\ATen\native\SpectralOps.cpp:867.) return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined] C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error. Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ..\aten\src\ATen\native\SpectralOps.cpp:867.) return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined] C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error. Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ..\aten\src\ATen\native\SpectralOps.cpp:867.) return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined] C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error. Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ..\aten\src\ATen\native\SpectralOps.cpp:867.) return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined] INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration. C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\torch\autograd\__init__.py:200: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance. grad.sizes() = [64, 1, 4], strides() = [4, 1, 1] bucket_view.sizes() = [64, 1, 4], strides() = [4, 4, 1] (Triggered internally at ..\torch\csrc\distributed\c10d\reducer.cpp:337.) Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass INFO:Conker:Train Epoch: 1 [0%] INFO:Conker:[0, 0.0001] INFO:Conker:loss_disc=4.168, loss_gen=2.556, loss_fm=14.733,loss_mel=25.850, loss_kl=9.000 DEBUG:matplotlib:matplotlib data path: C:\Users\lccji\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\mpl-data DEBUG:matplotlib:CONFIGDIR=C:\Users\lccji\.matplotlib DEBUG:matplotlib:interactive is False DEBUG:matplotlib:platform is win32 INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration. INFO:Conker:====> Epoch: 1 [2023-06-15 17:37:28] | (0:00:27.910967) INFO:Conker:====> Epoch: 2 [2023-06-15 17:37:49] | (0:00:20.556559) INFO:Conker:====> Epoch: 3 [2023-06-15 17:38:08] | (0:00:18.946464) INFO:Conker:====> Epoch: 4 [2023-06-15 17:38:27] | (0:00:18.796072) INFO:Conker:Train Epoch: 5 [55%] INFO:Conker:[200, 9.995000937421877e-05] INFO:Conker:loss_disc=3.761, loss_gen=3.288, loss_fm=8.147,loss_mel=21.058, loss_kl=1.650
Chris2918 commented 1 year ago

Training has fully completed and the model is working!