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Enhance test_autoquant_compile to support ROCm #2100
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         petrex
  
      
      
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            petrex
  
      
      
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        Apr 22, 2025 
      
    
  
- Added checks for ROCm availability alongside CUDA.
- Improved device capability checks for CUDA to ensure compatibility with bfloat16 and specific tensor shapes.
- Updated skip conditions for unsupported devices and older PyTorch versions.
| 🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2100
 Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 60c847f with merge base 720a177 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. | 
| 
 | 
| refer to #2113 | 
| @pytorchbot rebase -b main | 
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    - Added checks for ROCm availability alongside CUDA. - Improved device capability checks for CUDA to ensure compatibility with bfloat16 and specific tensor shapes. - Updated skip conditions for unsupported devices and older PyTorch versions.
              
                    jerryzh168
  
              
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                    May 14, 2025 
                  
              
              
            
            
              
                    jerryzh168
  
              
              reviewed
              
                  
                    May 14, 2025 
                  
              
              
            
            
- Simplified the logic for checking supported devices by consolidating CUDA and ROCm checks. - Enhanced readability of the device capability validation for CUDA. - Updated skip conditions for unsupported devices to ensure accurate test execution.
…ed readability - Adjusted the formatting of the device check condition to enhance clarity. - Consolidated the logic for checking supported devices while maintaining functionality.
    
  liangel-02 
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      Aug 25, 2025 
    
    
      
  
    
      
    
  
* Enhance test_autoquant_compile to support ROCm and improve device checks - Added checks for ROCm availability alongside CUDA. - Improved device capability checks for CUDA to ensure compatibility with bfloat16 and specific tensor shapes. - Updated skip conditions for unsupported devices and older PyTorch versions. * lint * Refactor device checks in test_autoquant_compile for improved clarity - Simplified the logic for checking supported devices by consolidating CUDA and ROCm checks. - Enhanced readability of the device capability validation for CUDA. - Updated skip conditions for unsupported devices to ensure accurate test execution. * Fix formatting in device check condition for consistency in test_autoquant_compile * Refactor device check formatting in test_autoquant_compile for improved readability - Adjusted the formatting of the device check condition to enhance clarity. - Consolidated the logic for checking supported devices while maintaining functionality.
  
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