pytorch
diff --git a/‎test/dynamo/test_functions.py
Lines changed: 15 additions & 0 deletions b/‎test/dynamo/test_functions.py
Lines changed: 15 additions & 0 deletions
diff --git a/‎torch/_dynamo/polyfill.py
Lines changed: 5 additions & 0 deletions b/‎torch/_dynamo/polyfill.py
Lines changed: 5 additions & 0 deletions
diff --git a/‎torch/_dynamo/variables/torch.py
Lines changed: 8 additions & 1 deletion b/‎torch/_dynamo/variables/torch.py
Lines changed: 8 additions & 1 deletion
@@ -4,6 +4,7 @@
 import functools
 import inspect
 import itertools
+import math
 import operator
 import sys
 import unittest
@@ -1124,6 +1125,20 @@ def augment(x: torch.Tensor) -> torch.Tensor:
     #         case {"b": param}:
     #             return x / param
 
+    def test_math_radians(self):
+        def func(x, a):
+            return x + math.radians(a)
+
+        cnt = torch._dynamo.testing.CompileCounter()
+        cfunc = torch._dynamo.optimize_assert(cnt)(func)
+
+        assert cnt.frame_count == 0
+        x = torch.rand(10)
+        expected = func(x, 12)
+        output = cfunc(x, 12)
+        self.assertTrue(same(output, expected))
+        assert cnt.frame_count == 1
+
     @make_test
     def test_numpy_meshgrid(x, y):
         r1, r2 = np.meshgrid(x.numpy(), y.numpy())
 
@@ -1,6 +1,7 @@
 """
 Python polyfills for common builtins.
 """
+import math
 
 
 def all(iterator):
@@ -21,3 +22,7 @@ def index(iterator, item, start=0, end=-1):
 def repeat(item, count):
     for i in range(count):
         yield item
+
+def radians(x):
+    return math.pi / 180.0 * x
@@ -22,7 +22,7 @@
 import torch.onnx.operators
 from torch._dynamo.variables import UserFunctionVariable
 
-from .. import config, variables
+from .. import config, polyfill, variables
 from ..allowed_functions import torch_get_name
 from ..device_interface import get_registered_device_interfaces
 from ..exc import unimplemented
@@ -298,6 +298,13 @@ def call_function(
                     **{k: v.as_python_constant() for k, v in kwargs.items()},
                 ),
             )
+        elif self.value == math.radians and not (constant_args or unspec_python_args):
+            # Use polyfill to convert math.radians(x) into math.pi * x / 180.0
+            from .builder import SourcelessBuilder
+
+            return tx.inline_user_function_return(
+                SourcelessBuilder()(tx, polyfill.radians), args, kwargs
+            )
         elif self.value in (torch.is_tensor, torch.overrides.is_tensor_like):
             assert len(args) == 1
             if isinstance(args[0], TensorVariable) or (