Fix a bug in native::_do_all_gather related to group

ignite/distributed/comp_models/native.py

@@ -430,15 +430,20 @@
             return tensor
 
         def _do_all_gather(self, tensor: torch.Tensor, group: Optional[Any] = None) -> torch.Tensor:
-            if group is not None and not isinstance(group, dist.ProcessGroup):
+            if group == dist.GroupMember.NON_GROUP_MEMBER:
+                return tensor
+            elif group is None:
+                group_size = self.get_world_size()
+            elif isinstance(group, dist.ProcessGroup):
+                group_size = group.size()
+            elif isinstance(group, list):
+                group_size = len(group)
+            else:
                 raise ValueError("Argument group should be list of int or ProcessGroup")
             if tensor.ndimension() == 0:
                 tensor = tensor.unsqueeze(0)
-            output = [torch.zeros_like(tensor) for _ in range(self.get_world_size())]
-            if group is not None:
-                dist.all_gather(output, tensor, group=group)
-            else:
-                dist.all_gather(output, tensor)
+            output = [torch.zeros_like(tensor) for _ in range(group_size)]
+            dist.all_gather(output, tensor, group=group)
             return torch.cat(output, dim=0)
 
         def _do_new_group(self, ranks: List[int], **kwargs: Any) -> Any:

ignite/distributed/utils.py

@@ -356,13 +356,15 @@ def all_gather(
     """Helper method to perform all gather operation.
 
     Args:
-        tensor: tensor or number or str to collect across participating processes.
+        tensor: tensor or number or str to collect across participating processes. If tensor, it should have the
+            same shape across processes.
         group: list of integer or the process group for each backend. If None, the default process group will be used.
 
     Returns:
-        torch.Tensor of shape ``(world_size * tensor.shape[0], tensor.shape[1], ...)`` if input is a tensor or
-        torch.Tensor of shape ``(world_size, )`` if input is a number or
-        List of strings if input is a string
+        If input is a tensor, returns a torch.Tensor of shape ``(world_size * tensor.shape[0], tensor.shape[1], ...)``.
+        If input is a number, a torch.Tensor of shape ``(world_size, )`` is returned and finally a list of strings
+        is returned if input is a string. If current process does not belong to `group`, the very ``tensor`` is
+        returned.
 
     .. versionchanged:: 0.4.11
         added ``group``

tests/ignite/distributed/utils/__init__.py

@@ -155,32 +155,34 @@ def _test_distrib_all_reduce_group(device):
 
 
 def _test_distrib_all_gather(device):
+    rank = idist.get_rank()
+
     res = torch.tensor(idist.all_gather(10), device=device)
     true_res = torch.tensor([10] * idist.get_world_size(), device=device)
     assert (res == true_res).all()
 
-    t = torch.tensor(idist.get_rank(), device=device)
+    t = torch.tensor(rank, device=device)
     res = idist.all_gather(t)
     true_res = torch.tensor([i for i in range(idist.get_world_size())], device=device)
     assert (res == true_res).all()
 
     x = "test-test"
-    if idist.get_rank() == 0:
+    if rank == 0:
         x = "abc"
     res = idist.all_gather(x)
     true_res = ["abc"] + ["test-test"] * (idist.get_world_size() - 1)
     assert res == true_res
 
     base_x = "tests/ignite/distributed/utils/test_native.py" * 2000
     x = base_x
-    if idist.get_rank() == 0:
+    if rank == 0:
         x = "abc"
 
     res = idist.all_gather(x)
     true_res = ["abc"] + [base_x] * (idist.get_world_size() - 1)
     assert res == true_res
 
-    t = torch.arange(100, device=device).reshape(4, 25) * (idist.get_rank() + 1)
+    t = torch.arange(100, device=device).reshape(4, 25) * (rank + 1)
     in_dtype = t.dtype
     res = idist.all_gather(t)
     assert res.shape == (idist.get_world_size() * 4, 25)
@@ -208,17 +210,21 @@ def _test_distrib_all_gather_group(device):
                 res = idist.all_gather(t, group=group)
         else:
             res = idist.all_gather(t, group=group)
-            assert torch.equal(res, torch.tensor(ranks, device=device))
+            if rank in ranks:
+                assert torch.equal(res, torch.tensor(ranks, device=device))
+            else:
+                assert res == t
 
         t = torch.tensor([rank], device=device)
         if bnd in ("horovod"):
             with pytest.raises(NotImplementedError, match=r"all_gather with group for horovod is not implemented"):
                 res = idist.all_gather(t, group=ranks)
         else:
             res = idist.all_gather(t, group=ranks)
-            assert torch.equal(res, torch.tensor(ranks, device=device))
-
-        ranks = "abc"
+            if rank in ranks:
+                assert torch.equal(res, torch.tensor(ranks, device=device))
+            else:
+                assert res == t
 
         if bnd in ("nccl", "gloo", "mpi"):
             with pytest.raises(ValueError, match=r"Argument group should be list of int or ProcessGroup"):