Implement split_function_and_wrangler | test(torchlib)

onnxscript/tests/function_libs/torch_lib/ops_test.py

@@ -17,7 +17,7 @@
 
 import unittest
 import warnings
-from typing import Callable, Optional, Sequence
+from typing import Any, Callable, Optional, Sequence
 
 import numpy as np
 import onnx
@@ -55,14 +55,23 @@ def _should_skip_test_sample(op_name: str, sample) -> Optional[str]:
     return None
 
 
+def _split_function_and_wrangler(
+    onnx_function_and_wrangler: Callable[..., Any]
+    | tuple[Callable[..., Any], Callable[..., Any]]
+) -> tuple[Callable[..., Any], Callable[..., Any] | None]:
+    """Splits a function with an optional input wrangler into a function and an input wrangler."""
+    if isinstance(onnx_function_and_wrangler, tuple):
+        return onnx_function_and_wrangler
+
+    assert callable(onnx_function_and_wrangler)
+    return onnx_function_and_wrangler, None
+
+
 class TestFunctionValidity(unittest.TestCase):
     def test_all_script_functions_are_onnx_functions(self):
         functions = set()
         for func_with_wrangler in ops_test_data.OPINFO_FUNCTION_MAPPING_SCRIPTED.values():
-            if isinstance(func_with_wrangler, tuple):
-                func = func_with_wrangler[0]
-            else:
-                func = func_with_wrangler
+            func, _ = _split_function_and_wrangler(func_with_wrangler)
             functions.add(func)
 
         # TODO(justinchuby): Add from the registry
@@ -76,10 +85,7 @@ def test_all_script_functions_are_onnx_functions(self):
 
     def test_all_trace_only_functions_are_not_onnx_functions(self):
         for func_with_wrangler in ops_test_data.OPINFO_FUNCTION_MAPPING_TRACE_ONLY.values():
-            if isinstance(func_with_wrangler, tuple):
-                func = func_with_wrangler[0]
-            else:
-                func = func_with_wrangler
+            func, _ = _split_function_and_wrangler(func_with_wrangler)
             if isinstance(func, onnxscript.OnnxFunction):
                 raise AssertionError(
                     f"'{func.name}' is an OnnxFunction. "
@@ -95,10 +101,7 @@ def test_all_trace_only_functions_are_not_onnx_functions(self):
         "Function checker is not available before ONNX 1.14",
     )
     def test_script_function_passes_checker(self, _, func_with_wrangler):
-        if isinstance(func_with_wrangler, tuple):
-            func = func_with_wrangler[0]
-        else:
-            func = func_with_wrangler
+        func, _ = _split_function_and_wrangler(func_with_wrangler)
         function_proto = func.to_function_proto()
         onnx.checker.check_function(function_proto)  # type: ignore[attr-defined]
 
@@ -127,16 +130,11 @@ def run_test_output_match(
     )
 
     onnx_function_and_wrangler = ops_test_data.OPINFO_FUNCTION_MAPPING[op.name]
-    input_wrangler = None
-    if isinstance(onnx_function_and_wrangler, tuple):
-        # Obtain the input_wrangler that manipulates the OpInfo inputs
-        # to match the aten operator signature
-        # An example is nn.functional.upsample_nearest2d, which has a different signature
-        # than the aten operator upsample_nearest2d
-        onnx_function, input_wrangler = onnx_function_and_wrangler
-    else:
-        assert callable(onnx_function_and_wrangler)
-        onnx_function = onnx_function_and_wrangler
+    # Obtain the input_wrangler that manipulates the OpInfo inputs
+    # to match the aten operator signature
+    # An example is nn.functional.upsample_nearest2d, which has a different signature
+    # than the aten operator upsample_nearest2d
+    onnx_function, input_wrangler = _split_function_and_wrangler(onnx_function_and_wrangler)
 
     for i, cpu_sample in enumerate(samples):
         inputs = (cpu_sample.input, *cpu_sample.args)