Re-land D66465376 (pytorch#2637)

Summary:

Re-land diff D66465376

NOTE: use jit.ignore on the forward function to get rid of jit script error with `TensorDict`
```
def test_td_scripting(self) -> None:
    class TestModule(torch.nn.Module):
        torch.jit.ignore # <----- test fails without this ignore
        def forward(self, x: Union[TensorDict, KeyedJaggedTensor]) -> torch.Tensor:
            if isinstance(x, TensorDict):
                keys = list(x.keys())
                return torch.cat([x[key]._values for key in keys], dim=0)
            else:
                return x._values

    m = TestModule()
    gm = torch.fx.symbolic_trace(m)
    jm = torch.jit.script(gm)
    values = torch.tensor([0, 1, 2, 3, 2, 3, 4])
    kjt = KeyedJaggedTensor.from_offsets_sync(
        keys=["f1", "f2", "f3"],
        values=values,
        offsets=torch.tensor([0, 2, 2, 3, 4, 5, 7]),
    )
    torch.testing.assert_allclose(jm(kjt), values)
```

Differential Revision: D66460392

torchrec/distributed/embedding.py

@@ -97,6 +97,14 @@
 except OSError:
     pass
 
+try:
+    from tensordict import TensorDict
+except ImportError:
+
+    class TensorDict:
+        pass
+
+
 logger: logging.Logger = logging.getLogger(__name__)
 
 

torchrec/distributed/embeddingbag.py

@@ -98,6 +98,13 @@
 except OSError:
     pass
 
+try:
+    from tensordict import TensorDict
+except ImportError:
+
+    class TensorDict:
+        pass
+
 
 def _pin_and_move(tensor: torch.Tensor, device: torch.device) -> torch.Tensor:
     return (

torchrec/modules/embedding_modules.py

@@ -21,6 +21,14 @@
 from torchrec.sparse.jagged_tensor import JaggedTensor, KeyedJaggedTensor, KeyedTensor
 
 
+try:
+    from tensordict import TensorDict
+except ImportError:
+
+    class TensorDict:
+        pass
+
+
 @torch.fx.wrap
 def reorder_inverse_indices(
     inverse_indices: Optional[Tuple[List[str], torch.Tensor]],

torchrec/sparse/jagged_tensor.py

@@ -49,9 +49,12 @@
 
 # OSS
 try:
-    pass
+    from tensordict import TensorDict
 except ImportError:
-    pass
+
+    class TensorDict:
+        pass
+
 
 logger: logging.Logger = logging.getLogger()