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__array_function__ internals #474

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helpmeoricry opened this issue Jun 7, 2023 · 7 comments
Closed

__array_function__ internals #474

helpmeoricry opened this issue Jun 7, 2023 · 7 comments

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@helpmeoricry
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File "<array_function internals>", line 180, in concatenate
ValueError: need at least one array to concatenate

concatewhat?????
@helpmeoricry
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this is showing up when i'm loading the One click training

@Slack-FX
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Slack-FX commented Jun 8, 2023 •
edited

Same, currently using 20 minutes of training data, assumed that would be enough.

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Loading personal and system profiles took 1337ms.

TroubleChute Retrieval-based Voice Conversion WebUI One-Line Launcher
https://tc.ht/ & YouTube.com/TroubleChute

Launching Retrieval-based Voice Conversion WebUI...
Use Language: en_US
Running on local URL: http://0.0.0.0:7865
start preprocess
['trainset_preprocess_pipeline_print.py', 'D:\Modding\JS\Raw', '40000', '24', 'D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI/logs/test20', 'False']
D:\Modding\JS\Raw/pt1.wav->Suc.
D:\Modding\JS\Raw/pt2.wav->Suc.
end preprocess
start preprocess
['trainset_preprocess_pipeline_print.py', 'D:\Modding\JS\Raw', '40000', '24', 'D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI/logs/test20', 'False']
D:\Modding\JS\Raw/pt1.wav->Suc.
D:\Modding\JS\Raw/pt2.wav->Suc.
end preprocess

['extract_f0_print.py', 'D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI/logs/test20', '24', 'harvest']
todo-f0-14
f0ing,now-0,all-14,-D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI/logs/test20/1_16k_wavs/0_0.wav
todo-f0-14
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['extract_f0_print.py', 'D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI/logs/test20', '24', 'harvest']
todo-f0-14
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['extract_feature_print.py', 'cuda:0', '1', '0', '0', 'D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI/logs/test20', 'v1']
D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI/logs/test20
load model(s) from hubert_base.pt
Traceback (most recent call last):
File "D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI\extract_feature_print.py", line 66, in
models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
File "C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\fairseq\checkpoint_utils.py", line 423, in load_model_ensemble_and_task
raise IOError("Model file not found: {}".format(filename))
OSError: Model file not found: hubert_base.pt
['extract_f0_print.py', 'D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI/logs/test20', '24', 'harvest']
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['extract_feature_print.py', 'cuda:0', '1', '0', '0', 'D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI/logs/test20', 'v1']
D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI/logs/test20
load model(s) from hubert_base.pt

INFO:test20:{'train': {'log_interval': 200, 'seed': 1234, 'epochs': 20000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 12, '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\test20/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\test20', 'experiment_dir': './logs\test20', 'save_every_epoch': 5, 'name': 'test20', 'total_epoch': 20, 'pretrainG': 'pretrained/f0G40k.pth', 'pretrainD': 'pretrained/f0D40k.pth', 'version': 'v1', '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
INFO:test20:loaded pretrained pretrained/f0G40k.pth pretrained/f0D40k.pth


C:\Users\whnan\anaconda3\envs\rvc\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\whnan\anaconda3\envs\rvc\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:test20:Train Epoch: 1 [0%]
INFO:test20:[0, 0.0001]
INFO:test20:loss_disc=3.366, loss_gen=2.107, loss_fm=0.548,loss_mel=18.856, loss_kl=9.000
DEBUG:matplotlib:matplotlib data path: C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\matplotlib\mpl-data
DEBUG:matplotlib:CONFIGDIR=C:\Users\whnan.matplotlib
DEBUG:matplotlib:interactive is False
DEBUG:matplotlib:platform is win32
INFO:test20:====> Epoch: 1 [2023-06-08 11:56:47] | (0:00:05.194512)
C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\torch\optim\lr_scheduler.py:139: UserWarning: Detected call of lr_scheduler.step() before optimizer.step(). In PyTorch 1.1.0 and later, you should call them in the opposite order: optimizer.step() before lr_scheduler.step(). Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
warnings.warn("Detected call of lr_scheduler.step() before optimizer.step(). "
INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration.
INFO:test20:====> Epoch: 2 [2023-06-08 11:56:47] | (0:00:00.360240)
INFO:test20:====> Epoch: 3 [2023-06-08 11:56:48] | (0:00:00.355426)
INFO:test20:====> Epoch: 4 [2023-06-08 11:56:48] | (0:00:00.361554)
INFO:test20:Saving model and optimizer state at epoch 5 to ./logs\test20\G_2333333.pth
INFO:test20:Saving model and optimizer state at epoch 5 to ./logs\test20\D_2333333.pth
INFO:test20:saving ckpt test20_e5:Success.
INFO:test20:====> Epoch: 5 [2023-06-08 11:56:49] | (0:00:00.747121)
INFO:test20:====> Epoch: 6 [2023-06-08 11:56:49] | (0:00:00.353977)
INFO:test20:====> Epoch: 7 [2023-06-08 11:56:49] | (0:00:00.345908)
INFO:test20:====> Epoch: 8 [2023-06-08 11:56:50] | (0:00:00.348669)
INFO:test20:====> Epoch: 9 [2023-06-08 11:56:50] | (0:00:00.375114)
INFO:test20:Saving model and optimizer state at epoch 10 to ./logs\test20\G_2333333.pth
INFO:test20:Saving model and optimizer state at epoch 10 to ./logs\test20\D_2333333.pth
INFO:test20:saving ckpt test20_e10:Success.
INFO:test20:====> Epoch: 10 [2023-06-08 11:56:51] | (0:00:01.162426)
INFO:test20:====> Epoch: 11 [2023-06-08 11:56:52] | (0:00:00.394429)
INFO:test20:====> Epoch: 12 [2023-06-08 11:56:52] | (0:00:00.375979)
INFO:test20:====> Epoch: 13 [2023-06-08 11:56:52] | (0:00:00.360657)
INFO:test20:====> Epoch: 14 [2023-06-08 11:56:53] | (0:00:00.374382)
INFO:test20:Saving model and optimizer state at epoch 15 to ./logs\test20\G_2333333.pth
INFO:test20:Saving model and optimizer state at epoch 15 to ./logs\test20\D_2333333.pth
INFO:test20:saving ckpt test20_e15:Success.
INFO:test20:====> Epoch: 15 [2023-06-08 11:56:54] | (0:00:01.404216)
INFO:test20:====> Epoch: 16 [2023-06-08 11:56:55] | (0:00:00.384436)
INFO:test20:====> Epoch: 17 [2023-06-08 11:56:55] | (0:00:00.377325)
INFO:test20:====> Epoch: 18 [2023-06-08 11:56:55] | (0:00:00.373106)
INFO:test20:====> Epoch: 19 [2023-06-08 11:56:56] | (0:00:00.376031)
INFO:test20:Saving model and optimizer state at epoch 20 to ./logs\test20\G_2333333.pth
INFO:test20:Saving model and optimizer state at epoch 20 to ./logs\test20\D_2333333.pth
INFO:test20:saving ckpt test20_e20:Success.
INFO:test20:====> Epoch: 20 [2023-06-08 11:56:57] | (0:00:01.433098)
INFO:test20:Training is done. The program is closed.
INFO:test20:saving final ckpt:Success.
Traceback (most recent call last):
File "C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\gradio\routes.py", line 427, in run_predict
output = await app.get_blocks().process_api(
File "C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\gradio\blocks.py", line 1323, in process_api
result = await self.call_function(
File "C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\gradio\blocks.py", line 1067, in call_function
prediction = await utils.async_iteration(iterator)
File "C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\gradio\utils.py", line 336, in async_iteration
return await iterator.anext()
File "C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\gradio\utils.py", line 329, in anext
return await anyio.to_thread.run_sync(
File "C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\anyio_backends_asyncio.py", line 877, in run_sync_in_worker_thread
return await future
File "C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\anyio_backends_asyncio.py", line 807, in run
result = context.run(func, *args)
File "C:\Users\whnan\anaconda3\envs\rvc\lib\site-packages\gradio\utils.py", line 312, in run_sync_iterator_async
return next(iterator)
File "D:\VoiceAIGithubInstall\Retrieval-based-Voice-Conversion-WebUI\infer-web.py", line 1049, in train1key
big_npy = np.concatenate(npys, 0)
File "<array_function internals>", line 180, in concatenate
ValueError: need at least one array to concatenate

@RVC-Boss
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RVC-Boss commented Jun 8, 2023

OSError: Model file not found: hubert_base.pt
Maybe you need rename it to hubert_base.pth

@Slack-FX
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Slack-FX commented Jun 8, 2023

OSError: Model file not found: hubert_base.pt Maybe you need rename it to hubert_base.pth

Yep got it working I think, thx (still training, but seems to be actually running now)

@Duonic
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Duonic commented Jun 8, 2023

OSError: Model file not found: hubert_base.pt Maybe you need rename it to hubert_base.pth

I'm having the same issue, renaming didn't work. Any other possible solutions?

@Duonic
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Duonic commented Jun 8, 2023

OSError: Model file not found: hubert_base.pt Maybe you need rename it to hubert_base.pth

Yep got it working I think, thx (still training, but seems to be actually running now)

Hey, can you please explain how you ended up making it work? Just by renaming the file from pt to pth?

@Slack-FX
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Slack-FX commented Jun 8, 2023 •
edited

OSError: Model file not found: hubert_base.pt Maybe you need rename it to hubert_base.pth

Yep got it working I think, thx (still training, but seems to be actually running now)

Hey, can you please explain how you ended up making it work? Just by renaming the file from pt to pth?

For me, hubert_base.pt had disappeared entirely from my dir (unsure how), so just simply replacing it fixed the issue. Idk that it matters whether its name .pt or .pth

Not sure what to tell you sorry

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@Duonic @Slack-FX @RVC-Boss @helpmeoricry