Rename fuse_pt2 to apply_pre_edge_transform_passes

Differential Revision: D86710591

Pull Request resolved: #15724

Author: ethansfng

backends/cadence/aot/compiler.py

@@ -144,7 +144,7 @@ def convert_pt2(
 # It is however useful for unit tests to separate the converted model from the
 # fused model, to be able to get reference numerics.
 # If this does not apply, please use quantize_pt2 instead.
-def fuse_pt2(
+def apply_pre_edge_transform_passes(
     converted_program: ExportedProgram,
     quantizer: CadenceQuantizer,
 ) -> ExportedProgram:
@@ -229,7 +229,7 @@ def quantize_pt2(
 
     # Apply quant fusion to the exported program
     program = torch.export.export(converted_gm, inputs, strict=True)
-    fused_program = fuse_pt2(program, quantizer)
+    fused_program = apply_pre_edge_transform_passes(program, quantizer)
 
     if dump_graphs:
         logging.info("Graph after quantization and fusion:")

backends/cadence/aot/export_example.py

@@ -18,8 +18,8 @@
 
 from executorch.backends.cadence.aot.compiler import (
     _lower_ep_to_cadence_gen_etrecord,
+    apply_pre_edge_transform_passes,
     convert_pt2,
-    fuse_pt2,
     prepare_pt2,
 )
 
@@ -66,7 +66,7 @@ def export_model(
     ep = torch.export.export(converted_model, example_inputs, strict=True)
 
     # Fuse the quantized patterns on the exported program (note: quantizer needs to be the same as the one used in prepare_and_convert_pt2)
-    ep = fuse_pt2(ep, quantizer)
+    ep = apply_pre_edge_transform_passes(ep, quantizer)
 
     # Get edge program after Cadence specific passes
     exec_prog: ExecutorchProgramManager = _lower_ep_to_cadence_gen_etrecord(