Revert "[dynamo] handle fullgraph toggle using nested torch.compile (#155166)"

This reverts commit 24dc33b37b.

Reverted https://github.com/pytorch/pytorch/pull/155166 on behalf of https://github.com/ezyang due to All of this is responsible for regression, see https://github.com/pytorch/pytorch/pull/156561 ([comment](https://github.com/pytorch/pytorch/pull/154283#issuecomment-2994242583))

test/dynamo/test_decorators.py

@@ -1040,11 +1040,11 @@ If the above doesn't work, please subtmit an issue to GitHub.
         self.assertEqual(cnts.frame_count, 2)
         self.assertEqual(cnts.op_count, 4)
 
-        cnts.clear()
-        torch._dynamo.reset()
-        fn3(torch.randn(4, 5))
-        self.assertEqual(cnts.frame_count, 2)
-        self.assertEqual(cnts.op_count, 4)
+        try:
+            fn3(torch.randn(4, 5))
+            self.assertFalse(True)
+        except torch._dynamo.exc.Unsupported as e:
+            self.assertIn("Skip calling `torch.compiler.disable()`d function", str(e))
 
     def test_disable_optimize(self):
         cnt = torch._dynamo.testing.CompileCounter()
@@ -1903,34 +1903,6 @@ If the above doesn't work, please subtmit an issue to GitHub.
         with self.assertRaises(Unsupported):
             f2(inp)
 
-    def test_nested_compile_fullgraph(self):
-        inp = torch.ones(3)
-
-        @torch.compile(backend="eager", fullgraph=True)
-        def inner_f1(x):
-            x = x + 1
-            torch._dynamo.graph_break()
-            return x + 2
-
-        @torch.compile(backend="eager", fullgraph=False)
-        def f1(x):
-            return inner_f1(x)
-
-        with self.assertRaises(Unsupported):
-            f1(inp)
-
-        @torch.compile(backend="eager", fullgraph=False)
-        def inner_f2(x):
-            x = x + 1
-            torch._dynamo.graph_break()
-            return x + 2
-
-        @torch.compile(backend="eager", fullgraph=True)
-        def f2(x):
-            return inner_f2(x)
-
-        self.assertEqual(f2(inp), inp + 3)
-
 
 if __name__ == "__main__":
     from torch._dynamo.test_case import run_tests

test/test_dynamic_shapes.py

@@ -3050,7 +3050,6 @@ def custom_pass(graph: torch.fx.Graph) -> torch.fx.Graph:
 
 
 class TestUnbacked(TestCase):
-    @skipIfTorchDynamo("https://github.com/pytorch/pytorch/issues/156135")
     @torch._dynamo.config.patch("capture_scalar_outputs", True)
     @parametrize("backend", ["inductor", "eager"])
     def test_deferred_neq_assert(self, backend):
@@ -3098,7 +3097,6 @@ class TestUnbacked(TestCase):
         with self.assertRaises(RuntimeError):
             func(torch.rand(2, 50), torch.tensor([51]))
 
-    @skipIfTorchDynamo("https://github.com/pytorch/pytorch/issues/156135")
     @torch._dynamo.config.patch("capture_scalar_outputs", True)
     @parametrize("backend", ["inductor", "eager"])
     def test_deferred_sym_or_assert(self, backend):
@@ -3120,7 +3118,6 @@ class TestUnbacked(TestCase):
         self.assertTrue(has_free_symbols(sympy.sympify("a*2")))
         self.assertTrue(has_free_symbols(sympy.sympify("a+b")))
 
-    @skipIfTorchDynamo("https://github.com/pytorch/pytorch/issues/156135")
     @torch._dynamo.config.patch("capture_scalar_outputs", True)
     @parametrize("backend", ["inductor", "eager"])
     def test_deferred_sym_eq_assert(self, backend):

torch/_dynamo/eval_frame.py

@@ -528,7 +528,7 @@ class _TorchDynamoContext:
         patch_fn=nothing,
         first_ctx=False,
         *,
-        error_on_graph_break=False,
+        error_on_graph_break=None,
         export=False,
         dynamic=None,
         compiler_config=None,
@@ -737,9 +737,7 @@ class _TorchDynamoContext:
                 _maybe_set_eval_frame(prior)
 
         # hooks to properly handle inlining
-        compile_wrapper._torchdynamo_inline = (  # type: ignore[attr-defined]
-            external_utils.wrap_inline_with_set_fullgraph(fn, self.error_on_graph_break)
-        )
+        compile_wrapper._torchdynamo_inline = fn  # type: ignore[attr-defined]
 
         # Save the function pointer to find the original callable while nesting
         # of decorators.
@@ -799,7 +797,7 @@ class OptimizeContext(_TorchDynamoContext):
         backend_ctx_ctor,
         first_ctx=False,
         *,
-        error_on_graph_break=False,
+        error_on_graph_break=None,
         export=False,
         dynamic=None,
         compiler_config=None,
@@ -937,7 +935,7 @@ def _optimize_catch_errors(
     compile_fn,
     hooks: Hooks,
     backend_ctx_ctor=null_context,
-    error_on_graph_break=False,
+    error_on_graph_break=None,
     export=False,
     dynamic=None,
     compiler_config=None,

torch/_dynamo/external_utils.py

@@ -227,25 +227,3 @@ def call_accumulate_grad(
         [grad], variable, variable.grad, has_post_hooks
     )
     variable.grad = updated_grad[0]
-
-
-def wrap_inline_with_set_fullgraph(
-    fn: Callable[_P, _R], fullgraph: bool
-) -> Callable[_P, _R]:
-    # NB: need multiple definitions in order to prevent `fullgraph` from
-    # being a freevar of wrapper
-    if fullgraph:
-
-        @functools.wraps(fn)
-        def wrapper(*args: _P.args, **kwargs: _P.kwargs) -> _R:
-            with torch._dynamo.set_fullgraph(True):
-                return fn(*args, **kwargs)
-
-    else:
-
-        @functools.wraps(fn)
-        def wrapper(*args: _P.args, **kwargs: _P.kwargs) -> _R:
-            with torch._dynamo.set_fullgraph(False):
-                return fn(*args, **kwargs)
-
-    return wrapper