Fix Customize Optimization tutorial import error #18584

[AshwiniBokka]

Fixes #18584

Problem

The tutorial docs/how_to/tutorials/customize_opt.py fails with "No module named 'tvm_ffi'" when TVM is not built. This happens because the tutorial imports tvm.relax.backend.cuda.cublas which requires TVM to be built with CUDA support.

Solution

1. Add clear prerequisite note about building TVM with CUDA
2. Add helpful error handling with guidance when import fails

Changes

• Added note after imports explaining build requirements
• Wrapped problematic import with try/except
• Provides clear error message pointing to build instructions
• Follows Python best practices (stderr, proper indentation)

Testing

• File compiles without syntax errors
• Error message clearly guides users to solution

Before

import tvm.relax.backend.cuda.cublas as _cublas
# Users get: No module named 'tvm_ffi'

[gemini-code-assist]

Summary of Changes

Hello @AshwiniBokka, I'm Gemini Code Assist¹! 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 addresses a common ImportError encountered by users of the customize_opt.py tutorial when TVM is not built with CUDA. The changes improve the user experience by adding clear documentation about the CUDA build requirement and implementing a try-except block to gracefully handle the missing module, providing actionable guidance. Additionally, it updates license-related URLs to use HTTPS.

Highlights

• Enhanced Tutorial Robustness: The customize_opt.py tutorial now includes explicit prerequisites and robust error handling for the tvm.relax.backend.cuda.cublas import, guiding users if TVM is not built with CUDA support.
• Improved Error Messaging: A try-except block has been added to catch ImportError related to tvm_ffi, providing a clear error message to stderr with instructions on how to build TVM with CUDA.
• URL Protocol Update: Several http links to Apache licenses in LICENSE and README.md files have been updated to https for improved security and consistency.

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[gemini-code-assist]

Code Review

This pull request addresses an import error in the 'Customize Optimization' tutorial that occurs when TVM is not built with CUDA support. The changes include adding a note about the CUDA dependency and implementing a try-except block to catch the ImportError and provide a user-friendly error message. The changes are well-aligned with the problem description. My review includes a critical fix for a Byte Order Mark (BOM) character that was introduced, and a suggestion to make the error handling more robust by checking for CUDA feature availability directly instead of parsing the exception message.

[AshwiniBokka]

@yongwww Thanks for the insights! Updated to:

1. Suggest pip install tvm-ffi first
2. Only fall back to full TVM build
3. Clearer error message with options

[AshwiniBokka]

Thank you @yongwww @tqchen for the guidance. This PR is now ready for merge:

1. All CI checks passed
2. Better user experience for missing CUDA
3. Clean error handling without breaking tutorial flow
4. Fixed existing bugs in tutorial

The tutorial now:

1. Helpfully guides users to install tvm-ffi first
2. Falls back to full TVM build if needed
3. Exits early with clear instructions if CUDA missing
4. Maintains all original functionality when CUDA available

Ready for final review/merge! 🙏