[FIX] Fix the error propagation in the case of tensor arguments

[tqchen]

This PR fixes error propagation in the case of tensor arguments. The bug was previously hidden and revealed after a fix landed in 0.1.8, so it does not impact previous versions. Added a regression test to cover this case.

[gemini-code-assist]

Summary of Changes

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This pull request resolves a critical error propagation issue that emerged with tensor arguments following a recent update (version 0.1.8). The core problem involved silent failures during the recovery of the DLPack managed tensor allocator. The fix ensures that such failures are now properly reported as Python RuntimeError exceptions, improving the robustness and debuggability of the system. A dedicated regression test has been added to prevent this specific bug from reappearing.

Highlights

• Error Propagation Fix: Addressed a bug in error propagation when tensor arguments are used, specifically when recovering the DLPack managed tensor allocator. Previously, errors in this path were hidden.
• Allocator Recovery Logic: Modified the TVMFFIEnvSetDLPackManagedTensorAllocator function to correctly set a Python RuntimeError and return an error code if the allocator recovery fails, preventing silent failures.
• DLPack Allocator Retrieval: Updated TVMFFIEnvSetDLPackManagedTensorAllocator to return the cached local dlpack_allocator_ instead of the global allocator when an original allocator is requested.
• Regression Test: Introduced a new regression test, test_tensor_auto_dlpack_with_error, to specifically cover the scenario where an error occurs when passing a PyTorch tensor argument, ensuring the corrected error propagation path is validated.

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[gemini-code-assist]

Code Review

This pull request addresses a bug concerning error propagation when tensor arguments are used, which was causing the original error to be overwritten during the cleanup phase. The fix ensures that the original error is correctly propagated. Additionally, the logic for saving and restoring thread-local allocators in env_context.cc has been refined for correctness. A regression test is included to verify the fix. The changes are well-implemented and effectively resolve the issue.