Add resolve in add decomp to enable view (#153945)

Fixes #148950.

During the construction of graph and running the node of add under [interpreter](/github.com/pytorch/pytorch/blob/d68d4d31f4824f1d1e0d1d6899e9879ad19b0754/torch/fx/interpreter.py#L301
), the functional argument of conj complex tensor gets cloned. This result in always having *.is_conj()* evaluted to false in decomposition function.

Propose a fix of calling resolve_conj() in the decomposition of complex tensor add.

Test as below
`python test/dynamo/test_repros.py ReproTests.test_add_complex_conj`

Pull Request resolved: https://github.com/pytorch/pytorch/pull/153945
Approved by: https://github.com/jansel

test/dynamo/test_repros.py

@@ -5742,6 +5742,17 @@ def forward(self, s77 : torch.SymInt, s27 : torch.SymInt, L_x_ : torch.Tensor):
         torch.view_as_real(out_test).sum().backward()
         self.assertEqual(x_ref.grad, x_test.grad)
 
+    def test_add_complex_conj(self):
+        def f(x):
+            return x + x.conj()
+
+        x = torch.randn(4, dtype=torch.complex64, requires_grad=True)
+        out = torch.compile(f)(x)
+        expected_complex = (2 * x.real).to(dtype=out.dtype)
+
+        self.assertTrue(out.dtype == torch.complex64)
+        self.assertEqual(out, expected_complex)
+
     # https://github.com/pytorch/pytorch/issues/132200
     def test_partitioner_cse_respects_mutation_boundaries(self):
         set_available = hasattr(torch.ops, "fsdp") and hasattr(torch.ops.fsdp, "set_")

torch/_inductor/decomposition.py

@@ -496,6 +496,10 @@ def add(
         reshaped_tensor = tensor.view(new_shape)
         return reshaped_tensor
 
+    # Manually resolve complex tensors, as .is_conj() is unreliable after cloning during compilation.
+    x = x + 0
+    z = z + 0
+
     x_reshaped = reshape_tensor_complex(x.view(x.real.dtype))
     z_reshaped = reshape_tensor_complex(z.view(y.real.dtype))
     result = torch.flatten(x_reshaped + z_reshaped, start_dim=-2).view(complex_type)
@@ -504,7 +508,8 @@ def add(
 
 @register_decomposition([aten.conj_physical])
 def conj_physical(self: torch.Tensor) -> torch.Tensor:
-    assert not self.is_complex(), "TODO: implement this"
+    if self.is_complex():
+        return NotImplemented
     return self