fix diloco integration test (#218)

Summary:
- for diloco the model parameters, in the way they are saved by the test can be different across replicas
- only the global parameters can be the same
- fix the test to validate the global parameters are the same instead of the local model parameters

Test Plan:
```
$ pytest -v ./torchft/local_sgd_integ_test.py::LocalSGDIntegTest::test_diloco_recovery_0
```

Author: tushar00jain

torchft/local_sgd_integ_test.py

@@ -414,13 +414,26 @@ def test_diloco_recovery(self, use_cuda: bool) -> None:
         rep0, rep1 = state_dicts
 
         for step in rep0.keys():
-            # Inner optimizer will be different, outer optimizer and model should be the same
+            # Inner optimizer and local model parameters will be different e.g.
+            # with 2 replicas r1 and r2, we sync every 2 steps
+            #
+            # - Manager Step 1
+            #   - Step 1: r1 and r2 step
+            #   - Step 2: r1 and r2 step, sync the model, quorum succeeds
+            # - Manager Step 2
+            #   - Step 1: r1 steps but r2 fails
+            #   - Step 2:
+            #     - r1 steps, sync fails because r2 is down
+            #     - r1 recovers r2 from the model state at this step
+            #       that is different from the model for r1 at the beginning
+            #       of step Manager Step 2
+            #
+            # Outer optimizer and global model should be the same
+
             torch.testing.assert_close(
-                rep1[step]["model"],
-                rep0[step]["model"],
+                rep1[step]["original_params"],
+                rep0[step]["original_params"],
                 check_device=False,
-                rtol=1e-4,
-                atol=1e-4,
             )
             torch.testing.assert_close(
                 rep1[step]["outer_optim"],