[FIX] Separate pykeops_enabled flag from use_pykeops for better control

[Leguark]

[BUG/CLN] Refactor tensor handling and cleanup lazy weight logic

Updated tensor operations in symbolic_evaluator.py to use lazy_weights consistently, replacing redundant LazyTensor calls. Adjusted dtype handling in backend_tensor.py for better compatibility with PyTorch.

[CLN] Rename pykeops_enabled to use_pykeops across codebase

Standardized the naming of the pykeops_enabled flag to use_pykeops for consistency and clarity in backend configuration. Updated relevant test cases, API calls, and internal logic accordingly.

[Leguark]

• [FIX] Reuse weights calculation instead of raising error on hash mismatch #27
• [ENH] Refactor dual contouring with parallel and sequential triangulation modules #26
• [ENH] Refactor dual contouring code with improved documentation and modular functions #25
• [REFACTOR] Use center grid for dual contouring instead of corners grid #24
• [FIX] Use timestamp for cache key instead of input parameters #23
• [FIX] Fix PyKeops tensor operations and ensure contiguous arrays #22
• [ENH] Add PyTorch backend support for dual contouring and octree operations #21
• [!!BUG] Chunking with faults were creating rogue voxels | GEN-13299 #20
• [ENH] Add transform support to meshes_to_subsurface method #19
• [FIX] Separate pykeops_enabled flag from use_pykeops for better control #18 👈 (View in Graphite)
• [ENH] Improve CG solver and add weights caching for better performance #17
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[Leguark]

Merge activity

• Sep 24, 12:13 PM UTC: A user started a stack merge that includes this pull request via Graphite.
• Sep 24, 12:15 PM UTC: Graphite rebased this pull request as part of a merge.
• Sep 24, 12:20 PM UTC: @Leguark merged this pull request with Graphite.