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

Segmentation fault: Failed to select voice

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Description

Issue:

When I select an item in Inferencing voice it produces this output:

$python infer-web.py 
2025-01-23 22:29:34 | INFO | configs.config | Found GPU Radeon RX 570 Series
2025-01-23 22:29:34 | INFO | configs.config | Half-precision floating-point: True, device: cuda:0
/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/gradio_client/documentation.py:106: UserWarning: Could not get documentation group for <class 'gradio.mix.Parallel'>: No known documentation group for module 'gradio.mix'
  warnings.warn(f"Could not get documentation group for {cls}: {exc}")
/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/gradio_client/documentation.py:106: UserWarning: Could not get documentation group for <class 'gradio.mix.Series'>: No known documentation group for module 'gradio.mix'
  warnings.warn(f"Could not get documentation group for {cls}: {exc}")
2025-01-23 22:29:36 | INFO | __main__ | Use Language: en_US
Running on local URL:  http://0.0.0.0:7865
2025-01-23 22:29:48 | INFO | infer.modules.vc.modules | Get sid: mashima_himeko_580e_15660s.pth
2025-01-23 22:29:48 | INFO | infer.modules.vc.modules | Loading: assets/weights/mashima_himeko_580e_15660s.pth
Segmentation fault (core dumped)

Computer settings:

OS: Ubuntu 24.04.1 LTS
Processor: AMD Ryzen™ 5 3400G with Radeon™ Vega Graphics × 8
RAM: 32.0 GiB
GPU: Radeon™ RX 570 Series

ROCm Info:

ROCk module version 6.8.5 is loaded
=====================    
HSA System Attributes    
=====================    
Runtime Version:         1.14
Runtime Ext Version:     1.6
System Timestamp Freq.:  1000.000000MHz
Sig. Max Wait Duration:  18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model:           LARGE                              
System Endianness:       LITTLE                             
Mwaitx:                  DISABLED
DMAbuf Support:          YES

==========               
HSA Agents               
==========               
*******                  
Agent 1                  
*******                  
  Name:                    AMD Ryzen 5 3400G with Radeon Vega Graphics
  Uuid:                    CPU-XX                             
  Marketing Name:          AMD Ryzen 5 3400G with Radeon Vega Graphics
  Vendor Name:             CPU                                
  Feature:                 None specified                     
  Profile:                 FULL_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        0(0x0)                             
  Queue Min Size:          0(0x0)                             
  Queue Max Size:          0(0x0)                             
  Queue Type:              MULTI                              
  Node:                    0                                  
  Device Type:             CPU                                
  Cache Info:              
    L1:                      32768(0x8000) KB                   
  Chip ID:                 0(0x0)                             
  ASIC Revision:           0(0x0)                             
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   3700                               
  BDFID:                   0                                  
  Internal Node ID:        0                                  
  Compute Unit:            8                                  
  SIMDs per CU:            0                                  
  Shader Engines:          0                                  
  Shader Arrs. per Eng.:   0                                  
  WatchPts on Addr. Ranges:1                                  
  Memory Properties:       
  Features:                None
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: FINE GRAINED        
      Size:                    32787664(0x1f44cd0) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: KERNARG, FINE GRAINED
      Size:                    32787664(0x1f44cd0) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 3                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    32787664(0x1f44cd0) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
  ISA Info:                
*******                  
Agent 2                  
*******                  
  Name:                    gfx803                             
  Uuid:                    GPU-XX                             
  Marketing Name:          Radeon RX 570 Series               
  Vendor Name:             AMD                                
  Feature:                 KERNEL_DISPATCH                    
  Profile:                 BASE_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        128(0x80)                          
  Queue Min Size:          64(0x40)                           
  Queue Max Size:          131072(0x20000)                    
  Queue Type:              MULTI                              
  Node:                    1                                  
  Device Type:             GPU                                
  Cache Info:              
    L1:                      16(0x10) KB                        
  Chip ID:                 26591(0x67df)                      
  ASIC Revision:           1(0x1)                             
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   1250                               
  BDFID:                   256                                
  Internal Node ID:        1                                  
  Compute Unit:            32                                 
  SIMDs per CU:            4                                  
  Shader Engines:          4                                  
  Shader Arrs. per Eng.:   1                                  
  WatchPts on Addr. Ranges:4                                  
  Coherent Host Access:    FALSE                              
  Memory Properties:       
  Features:                KERNEL_DISPATCH 
  Fast F16 Operation:      TRUE                               
  Wavefront Size:          64(0x40)                           
  Workgroup Max Size:      1024(0x400)                        
  Workgroup Max Size per Dimension:
    x                        1024(0x400)                        
    y                        1024(0x400)                        
    z                        1024(0x400)                        
  Max Waves Per CU:        40(0x28)                           
  Max Work-item Per CU:    2560(0xa00)                        
  Grid Max Size:           4294967295(0xffffffff)             
  Grid Max Size per Dimension:
    x                        4294967295(0xffffffff)             
    y                        4294967295(0xffffffff)             
    z                        4294967295(0xffffffff)             
  Max fbarriers/Workgrp:   32                                 
  Packet Processor uCode:: 730                                
  SDMA engine uCode::      58                                 
  IOMMU Support::          None                               
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    4194304(0x400000) KB               
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    4194304(0x400000) KB               
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 3                   
      Segment:                 GROUP                              
      Size:                    64(0x40) KB                        
      Allocatable:             FALSE                              
      Alloc Granule:           0KB                                
      Alloc Recommended Granule:0KB                                
      Alloc Alignment:         0KB                                
      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx803          
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32    

Steps:

  • Using ROCm 5.4.2:
  1. Created a virtual environment using venv using Python 3.10.16
  2. Run: pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/rocm5.4.2
  3. Run: pip install -r requirements-amd.txt
  4. Run: python tools/download_models.py
  5. Run: export ROCM_PATH=/opt/rocm
  6. Moved both *.index and *.pth files into weights/ folder.
  7. Run: python infer-web.py -
  • Using ROCm 5.6:
  1. Created a virtual environment using venv using Python 3.10.16
  2. Run: pip install torch==2.2.0 torchvision==0.17.0 torchaudio==2.2.0 --index-url https://download.pytorch.org/whl/rocm5.6
  3. Run: pip install -r requirements-amd.txt
  4. Run: python tools/download_models.py
  5. export ROCM_PATH=/opt/rocm
  6. Moved both *.index and *.pth files into weights/ folder.
  7. Run: python infer-web.py
  • Using ROCm 5.7
  1. Created a virtual environment using venv using Python 3.10.16
  2. Run: pip install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/rocm5.7
  3. Run: pip install -r requirements-amd.txt
  4. Run: python tools/download_models.py
  5. export ROCM_PATH=/opt/rocm
  6. Moved both *.index and *.pth files into weights/ folder.
  7. Run: python infer-web.py

ROCm 5.7 Output

python infer-web.py 
2025-01-23 23:29:59 | INFO | configs.config | Found GPU Radeon RX 570 Series
2025-01-23 23:29:59 | INFO | configs.config | Half-precision floating-point: True, device: cuda:0
/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/gradio_client/documentation.py:106: UserWarning: Could not get documentation group for <class 'gradio.mix.Parallel'>: No known documentation group for module 'gradio.mix'
  warnings.warn(f"Could not get documentation group for {cls}: {exc}")
/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/gradio_client/documentation.py:106: UserWarning: Could not get documentation group for <class 'gradio.mix.Series'>: No known documentation group for module 'gradio.mix'
  warnings.warn(f"Could not get documentation group for {cls}: {exc}")
2025-01-23 23:30:01 | INFO | __main__ | Use Language: en_US
Running on local URL:  http://0.0.0.0:7865
2025-01-23 23:30:06 | INFO | infer.modules.vc.modules | Get sid: mashima_himeko_580e_15660s.pth
2025-01-23 23:30:06 | INFO | infer.modules.vc.modules | Loading: assets/weights/mashima_himeko_580e_15660s.pth
Traceback (most recent call last):
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/gradio/routes.py", line 437, in run_predict
    output = await app.get_blocks().process_api(
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/gradio/blocks.py", line 1346, in process_api
    result = await self.call_function(
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/gradio/blocks.py", line 1074, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/anyio/to_thread.py", line 56, in run_sync
    return await get_async_backend().run_sync_in_worker_thread(
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 2461, in run_sync_in_worker_thread
    return await future
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 962, in run
    result = context.run(func, *args)
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/infer/modules/vc/modules.py", line 125, in get_vc
    self.net_g = self.net_g.half()
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1007, in half
    return self._apply(lambda t: t.half() if t.is_floating_point() else t)
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 802, in _apply
    module._apply(fn)
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 802, in _apply
    module._apply(fn)
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 802, in _apply
    module._apply(fn)
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 825, in _apply
    param_applied = fn(param)
  File "/home/leejun/pessoais/programs/Retrieval-based-Voice-Conversion-WebUI/rvcenv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1007, in <lambda>
    return self._apply(lambda t: t.half() if t.is_floating_point() else t)
RuntimeError: HIP error: invalid device function
HIP kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing HIP_LAUNCH_BLOCKING=1.
Compile with `TORCH_USE_HIP_DSA` to enable device-side assertions.

Image

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  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 with infer-web.py and the voice-model loading path reached after selecting a voice; reproduce the crash using the supplied commands and compare the listed Python, PyTorch, and ROCm setups. Done means identifying a project-side failure or documenting that the segmentation fault is environment-specific with a reproducible result.

Written by the indexing model from the issue text.

Assessment

Tech stack
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
25/100

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