Handle meta tensors in FX quantization (pytorch#142262)

Summary:
X-link: pytorch/torchrec#2622


If module being quantized contains a some meta tensors and some tensors with actual device, we should not fail quantization.

Quantization should also not fail if new quantized module is created on a meta device.

Test Plan:
```
buck run fbcode//mode/dev-nosan fbcode//torchrec/fb/quant/tests:test_embedding_modules
```

Differential Revision: D66895899

torch/ao/quantization/quantize.py

@@ -781,10 +781,10 @@ def swap_module(
             # respect device affinity when swapping modules
             devices = _get_unique_devices_(mod)
             assert (
-                len(devices) <= 1
+                len(devices) <= 1 or (len(devices) == 2 and torch.device("meta") in devices)
             ), f"swap_module only works with cpu or single-device CUDA modules, but got devices {devices}"
             device = next(iter(devices)) if len(devices) > 0 else None
-            if device:
+            if device and torch.device("meta") not in devices:
                 new_mod.to(device)
     return new_mod