RVC-Project / RVC-Project/Retrieval-based-Voice-Conversion-WebUI

RuntimeError+ 'NoneType' object has no attribute 'dtype'

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Description

I need help....

2025-05-15 20:11:03 | WARNING | infer.modules.vc.modules | Traceback (most recent call last):
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\infer\modules\vc\modules.py", line 186, in vc_single
audio_opt = self.pipeline.pipeline(
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\infer\modules\vc\pipeline.py", line 375, in pipeline
self.vc(
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\infer\modules\vc\pipeline.py", line 271, in vc
audio1 = (net_g.infer(*arg)[0][0, 0]).data.cpu().float().numpy()
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\infer\lib\infer_pack\models.py", line 953, in infer
m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\runtime\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\infer\lib\infer_pack\models.py", line 119, in forward
x = self.encoder(x * x_mask, x_mask)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\runtime\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\infer\lib\infer_pack\attentions.py", line 69, in forward
y = attn_layers(x, x, attn_mask)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\runtime\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\infer\lib\infer_pack\attentions.py", line 227, in forward
x, _ = self.attention(q, k, v, mask=attn_mask)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\infer\lib\infer_pack\attentions.py", line 278, in attention
relative_weights = self._absolute_position_to_relative_position(p_attn)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\infer\lib\infer_pack\attentions.py", line 373, in _absolute_position_to_relative_position
x_final = x_flat.view([batch, heads, length, 2 * length])[:, :, :, 1:]
RuntimeError: Could not allocate tensor with 257795132 bytes. There is not enough GPU video memory available!

Traceback (most recent call last):
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\runtime\lib\site-packages\gradio\routes.py", line 321, in run_predict
output = await app.blocks.process_api(
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\runtime\lib\site-packages\gradio\blocks.py", line 1007, in process_api
data = self.postprocess_data(fn_index, result["prediction"], state)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\runtime\lib\site-packages\gradio\blocks.py", line 953, in postprocess_data
prediction_value = block.postprocess(prediction_value)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\runtime\lib\site-packages\gradio\components.py", line 2076, in postprocess
processing_utils.audio_to_file(sample_rate, data, file.name)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\runtime\lib\site-packages\gradio\processing_utils.py", line 206, in audio_to_file
data = convert_to_16_bit_wav(data)
File "C:\RVC\RVC1006AMD_Intel\RVC1006AMD_Intel\runtime\lib\site-packages\gradio\processing_utils.py", line 219, in convert_to_16_bit_wav
if data.dtype in [np.float64, np.float32, np.float16]:
AttributeError: 'NoneType' object has no attribute 'dtype'

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First steps

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  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reading infer/modules/vc/pipeline.py, infer/lib/infer_pack/models.py, and infer/lib/infer_pack/attentions.py, then reproduce the reported conversion failure with the same input and GPU constraints. Trace the allocation failure through the inference pipeline and confirm that a failed conversion does not pass None into Gradio's audio postprocessing.

Written by the indexing model from the issue text.

Assessment

Tech stack
numpy, python, pytorch
Domain
audio-video-rtc, machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
15/100

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