Why does custom passes before joint graph (joint_custom_pre_pass) executed twice?

QZero_Chen · October 16, 2025, 8:34am

torch/_inductor/fx_passes/joint_graph.py

d73c283c3


      
              torch.fx.passes.graph_transform_observer.GraphTransformObserver,
              subsystem="joint_graph_passes",
          )
          
          lazy_init()
          count = 0
          
          # must occur before other passes
          canonicalize_aten_ir_passes(graph)
          
          if config.joint_custom_pre_pass is not None:
              GraphTransformObserver(graph, "joint_custom_pre_pass").apply_graph_pass(
                  config.joint_custom_pre_pass
              )
              count += 1
          
          from .post_grad import remove_noop_ops
          
          GraphTransformObserver(graph, "remove_noop_ops").apply_graph_pass(remove_noop_ops)
          
          if config.joint_graph_constant_folding:

And

github.com/pytorch/pytorch

torch/_inductor/fx_passes/joint_graph.py

d73c283c3


      
          
          from .post_grad import remove_noop_ops
          
          GraphTransformObserver(graph, "remove_noop_ops").apply_graph_pass(remove_noop_ops)
          
          if config.joint_graph_constant_folding:
              GraphTransformObserver(graph, "constant_fold_uniform_value").apply_gm_pass(
                  constant_fold_uniform_value
              )
          
          if config.joint_custom_pre_pass is not None:
              GraphTransformObserver(graph, "joint_custom_pre_pass").apply_graph_pass(
                  config.joint_custom_pre_pass
              )
              count += 1
          
          if config.pattern_matcher:
              for i, patterns in enumerate(pass_patterns):
                  maybe_count = GraphTransformObserver(
                      graph, f"pass_pattern_{i}"
                  ).apply_graph_pass(patterns.apply)

Why does joint_custom_pre_pass executed twice, is this a mistake or a design by purpose?