gemini-code-assist[bot] commented on PR #54:
URL: https://github.com/apache/tvm-ffi/pull/54#issuecomment-3332907556

   ## Summary of Changes
   
   Hello @yzh119, I'm Gemini Code Assist[^1]! I'm currently reviewing this pull 
request and will post my feedback shortly. In the meantime, here's a summary to 
help you and other reviewers quickly get up to speed!
   
   This pull request improves compatibility with various PyTorch versions by 
introducing conditional logic for features introduced in PyTorch 2.8, such as 
`Float8_e8m0fnu` and `Float4_e2m1fn_x2`. The changes involve guarding C++ code 
blocks with version checks and dynamically adding Python mappings based on the 
presence of specific dtypes, thereby preventing runtime errors and ensuring 
broader compatibility across different PyTorch environments.
   
   ### Highlights
   
   * **Conditional Handling for Float8_e8m0fnu**: The `Float8_e8m0fnu` data 
type is now conditionally recognized and converted in the C++ extension, 
specifically guarded for PyTorch versions 2.8 and above, ensuring compatibility 
with older versions.
   * **Dynamic DLDataType Mapping**: The Python-side mapping for 
`torch.float8_e8m0fnu` and `torch.float4_e2m1fn_x2` to `DLDataType` is now 
dynamically added only if these data types are present in the `torch` module, 
preventing errors when running with older PyTorch installations.
   * **Guarded TORCH_CHECK for DType Lanes**: A `TORCH_CHECK` that verifies 
`dtype.lanes == 1` for most `DLDataTypeCode`s (excluding `kDLFloat4_e2m1fn`) 
has been moved inside the Torch 2.8 version guard, ensuring this check is only 
applied when relevant PyTorch features are available.
   
   
   
   
   
   
   
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