Make pytorch/backend/refjit.py a bit tidier

- Print out initial PyTorch IR.
- Rename ambiguous "frontend IR" to "TCF IR".
- Add newlines to prints
- Rename FRONTEND_PASSES to TORCH_TO_TCF_PASSES

python/npcomp/compiler/pytorch/backend/refjit.py

@@ -14,8 +14,12 @@ __all__ = [
     "CompilerBackend",
 ]
 
-FRONTEND_PASSES = ("func(aten-recognize-kernels)", "func(convert-aten-to-tcf)",
-                   "numpy-public-functions-to-tensor", "canonicalize")
+TORCH_TO_TCF_PASSES = (
+    "func(aten-recognize-kernels)",
+    "func(convert-aten-to-tcf)",
+    "numpy-public-functions-to-tensor",
+    "canonicalize",
+)
 
 # Re-export.
 is_enabled = refjit_backend.is_enabled
@@ -43,11 +47,14 @@ class CompilerBackend:
     """
     # TODO: Once transitioned to new Python API, don't reparse the module.
     with Context() as context:
+      if self._debug:
+        logging.debug("Initial PyTorch IR:\n{}", imported_module)
+
       # Frontend.
-      pm = PassManager.parse(",".join(FRONTEND_PASSES))
+      pm = PassManager.parse(",".join(TORCH_TO_TCF_PASSES))
       pm.run(imported_module)
       if self._debug:
-        logging.debug("Frontend IR:{}", imported_module)
+        logging.debug("TCF IR:\n{}", imported_module)
 
       # Backend.
       # Note that this is a separate pass manager purely to aid in debugging.
@@ -55,7 +62,7 @@ class CompilerBackend:
       self._refjit.build_backend_compilation_pipeline(pm)
       pm.run(imported_module)
       if self._debug:
-        logging.debug("Backend IR:{}", imported_module)
+        logging.debug("Backend IR:\n{}", imported_module)
 
     jit_module = self._refjit.JITModule.from_compiled_module(
         imported_module, refjit_backend.get_runtime_libs())