PyTorch has 3 fusers (legacy, NNC/TensorExpr fuser, and cuda/nvFuser), the PYTORCH_FUSION_DEBUG only worked for the old (now legacy) fuser.
For the newer fusers, you probably could get some info from the logging facility described here:

  

      github.com
  

  
    pytorch/pytorch/blob/f9c0a39ad9320795fc8df77b570c317e0c2ab60e/torch/csrc/jit/jit_log.h#L7-L38 2



      
      
          // `TorchScript` offers a simple logging facility that can enabled by setting an
          // environment variable `PYTORCH_JIT_LOG_LEVEL`.
          
          
// Logging is enabled on a per file basis. To enable logging in
          // `dead_code_elimination.cpp`, `PYTORCH_JIT_LOG_LEVEL` should be
          // set to `dead_code_elimination.cpp` or, simply, to `dead_code_elimination`
          // (i.e. `PYTORCH_JIT_LOG_LEVEL=dead_code_elimination`).
          
          
// Multiple files can be logged by separating each file name with a colon `:` as
          // in the following example,
          // `PYTORCH_JIT_LOG_LEVEL=dead_code_elimination:guard_elimination`
          
          
// There are 3 logging levels available for your use ordered by the detail level
          // from lowest to highest.
          
          
// * `GRAPH_DUMP` should be used for printing entire graphs after optimization
          // passes
          // * `GRAPH_UPDATE` should be used for reporting graph transformations (i.e.
          // node deletion, constant folding, etc)
          // * `GRAPH_DEBUG` should be used for providing information useful for debugging
      
    
  

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Best regards
Thomas