Update Wall-X to 1.1.0 (#104)

wall_x/trainer/optimizer/dmuon/__init__.py

@@ -0,0 +1,16 @@
+import torch.nn as nn
+
+from .utils import get_dmuon_optimizer
+
+
+def is_dmuon_model(model: nn.Module) -> bool:
+    """True if ``dmuon.dedicate_params()`` has been applied to this model.
+
+    Checked via an attribute the external ``dmuon`` package attaches to
+    the root module, so this predicate works without importing ``dmuon``
+    and returns ``False`` for ordinary (non-DMuon) models.
+    """
+    return hasattr(model, "_dedicated_comm_ctx")
+
+
+__all__ = ["get_dmuon_optimizer", "is_dmuon_model"]