gemini-code-assist[bot] commented on PR #390:
URL: https://github.com/apache/tvm-ffi/pull/390#issuecomment-3723139433

   ## Summary of Changes
   
   Hello @junrushao, 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 significantly enhances the `Tensor Usage` documentation by 
restructuring the content and introducing a detailed 'Common Usage' section. 
This new section provides practical, day-to-day guidance for kernel developers 
on essential tensor operations, including metadata validation, seamless 
integration with PyTorch via DLPack, C++ memory allocation best practices, and 
effective stream management. The changes aim to improve clarity and provide 
more actionable examples for users interacting with tensors in the TVM-FFI 
framework.
   
   ### Highlights
   
   * **Documentation Reorganization**: The tutorial structure for tensor 
concepts has been updated, moving the 'Tensor APIs' section to an earlier 
position for better flow and emphasis.
   * **New 'Common Usage' Section**: A significant new section has been added, 
providing practical examples and explanations for key tensor operations in both 
C++ and Python.
   * **Kernel Signature Guidance**: Detailed C++ examples are now included to 
demonstrate how to validate tensor metadata (dtype, shape, device) and access 
data pointers within kernel implementations.
   * **PyTorch Interoperability**: The documentation now clearly explains how 
`tvm_ffi.Tensor` facilitates seamless import and export of tensors with 
external frameworks like PyTorch using the DLPack protocol.
   * **C++ Allocation Strategies**: New content covers both 
environment-specific (`Tensor::FromEnvAlloc`) and custom 
(`Tensor::FromNDAlloc`) C++ tensor allocation methods, along with a strong 
recommendation to avoid in-kernel allocations.
   * **C++ Stream Handling**: Comprehensive guidance on obtaining, 
automatically updating, and manually setting stream contexts in C++ for GPU 
kernel execution is now provided.
   * **Removed Redundant Section**: The previous 'Tensor APIs' section has been 
removed, as its content has been absorbed and expanded upon in the new 'Common 
Usage' section.
   
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