merge

pytorch · pianpwk · Apr 1, 2025 · Apr 1, 2025 · Apr 2, 2025 · Apr 2, 2025
commit 5a9460e86f07a03551d50a28249277ac6cebe48f
diff --git a/test/dynamo/test_recompiles.py b/test/dynamo/test_recompiles.py
@@ -1,5 +1,5 @@
 # Owner(s): ["module: dynamo"]
-import unittest
+from unittest import expectedFailure
 from unittest.mock import patch
 
 import torch
@@ -394,9 +394,7 @@ def f(x):
 
         self.assertEqual(counter.frame_count, 2)  # not three or four!
 
-    # TODO(laithsakka): guard_or_false fallback should occur before oblivious/unbacked hints
-    # maybe we can deprecate this option with backed_size_oblivious?
-    @unittest.expectedFailure
+    @expectedFailure  # TODO(laithsakka, pianpwk): handle guard_or_false before oblivious hint fallback
     @torch._dynamo.config.patch(automatic_dynamic_shapes_mark_as="oblivious")
     def test_automatic_dynamic_shapes_mark_as_oblivious(self):
         counter = torch._dynamo.testing.CompileCounter()

diff --git a/test/export/test_export.py b/test/export/test_export.py
@@ -4377,6 +4377,18 @@ def forward(self, x):
         ):
             _ = export(M(), (torch.tensor([2, 3, 5]),))
 
+    def test_unbacked_infer_size(self):
+        class Foo(torch.nn.Module):
+            def forward(self, x):
+                u0 = x.item()
+                torch._check_is_size(u0)
+                t = torch.empty(u0 - 1)
+                return t + t
+
+        ep = torch.export.export(Foo(), (torch.tensor([5]),))
+        ep.module()(torch.tensor([5]))
+        ep.module()(torch.tensor([1]))
+
     def test_unbacked_pad(self):
         class Foo(torch.nn.Module):
             def forward(self, xs, pad):
@@ -4455,9 +4467,6 @@ def forward(self, t):
         M = M_v1
         export(N(), (t,), strict=strict)
 
-    # decomp introduces contiguity data-dependent error for cf_changevar
-    @testing.expectedFailureTrainingIRToRunDecomp
-    @testing.expectedFailureTrainingIRToRunDecompNonStrict
     def test_suggested_fixes_for_data_dependent_errors_puzzlers(self):
         # suggested fixes for data-dependent errors only work in non-strict mode
         strict = False
@@ -4499,22 +4508,6 @@ def forward(self, x, y, fixes):
             ],
         )
 
-        class cf_changevar(torch.nn.Module):
-            def forward(self, x, fixes):
-                i = x.item()
-                eval(fixes)
-                r = torch.arange(i // 2)
-                return r + r
-
-        retry_export(
-            cf_changevar(),
-            (torch.tensor(20),),
-            fixes=[
-                # Could not guard on data-dependent expression Eq((u0//2), 1)
-                "torch._check((i // 2) != 1)",
-            ],
-        )
-
         class cf_stacklist(torch.nn.Module):
             def forward(self, xs, y, fixes):
                 i = y.item()