chore: import upstream snapshot with attribution

python/dgl/multiprocessing/__init__.py

@@ -0,0 +1,17 @@
+"""Wrapper of the multiprocessing module for multi-GPU training."""
+
+# To avoid duplicating the graph structure for node classification or link prediction
+# training we recommend using fork() rather than spawn() for multiple GPU training.
+# However, we need to work around https://github.com/pytorch/pytorch/issues/17199 to
+# make fork() and openmp work together.
+from .. import backend as F
+
+if F.get_preferred_backend() == "pytorch":
+    # Wrap around torch.multiprocessing...
+    from torch.multiprocessing import *
+
+    # ... and override the Process initializer.
+    from .pytorch import *
+else:
+    # Just import multiprocessing module.
+    from multiprocessing import *  # pylint: disable=redefined-builtin