Ignore meta ops in inductor (pytorch#150137)

Fix for pytorch#144607

Pull Request resolved: pytorch#150137
Approved by: https://github.com/BoyuanFeng

Author: eellison

test/inductor/test_torchinductor_dynamic_shapes.py

@@ -608,6 +608,16 @@ def f(x):
 
         f(torch.tensor([3], device=device))
 
+    def test_meta_dynamic_shapes(self):
+        def foobar(x, y):
+            return x * 2, y * 3
+
+        foo_c = torch.compile(dynamic=True)(foobar)
+        t = torch.empty((1, 16, 128, 128), device="meta")
+        y = torch.rand([64])
+
+        self.assertEqual(foo_c(t, y), foobar(t, y))
+
     def test_floor(self):
         def fn(x):
             n = x.size(-1)

torch/_inductor/lowering.py

@@ -1927,6 +1927,9 @@ def unsupported_input_tensor(t: torch.Tensor, parent=None, node=None):
         _warn_complex_not_supported()
         return True
 
+    if t.is_meta:
+        return True
+
     if t.dtype == torch.float8_e8m0fnu:
         if not node:
             return True

torch/_inductor/scheduler.py

@@ -4394,7 +4394,11 @@ def _codegen(self, nodes: list[BaseSchedulerNode]) -> None:
 
             if not isinstance(node, NopKernelSchedulerNode):
                 device = node.get_device()
-                if device is not None and self.get_backend(device).ready_to_flush():
+                if (
+                    device is not None
+                    and device.type != "meta"
+                    and self.get_backend(device).ready_to_flush()
+                ):
                     self.flush()
 
         if self.current_device and device_need_guard(self.current_device.type):