Adding ability to use dill to pass DataPipes in mutiprocessing (#77288)

Summary:
X-link: pytorch/pytorch#77288

Fixes part of #397 (only DataLoader v2 remaining)

Reviewed By: NivekT, ejguan

Differential Revision: D36347737

Pulled By: VitalyFedyunin

fbshipit-source-id: 144d149f1da98b7108f54e9dcecda0f5740d1eb9

test/test_graph.py

@@ -51,14 +51,26 @@ def finalize_iteration(self) -> None:
             dp.started = False
 
 
+def _x_and_x_plus_5(x):
+    return [x, x + 5]
+
+
+def _x_mod_2(x):
+    return x % 2
+
+
+def _x_mult_2(x):
+    return x * 2
+
+
 class TestGraph(expecttest.TestCase):
     def _get_datapipes(self) -> Tuple[IterDataPipe, IterDataPipe, IterDataPipe]:
         src_dp = IterableWrapper(range(20))
-        m1 = src_dp.map(lambda x: [x, x + 5])
+        m1 = src_dp.map(_x_and_x_plus_5)
         ub = m1.unbatch()
-        c1, c2 = ub.demux(2, lambda x: x % 2)
+        c1, c2 = ub.demux(2, _x_mod_2)
         dm = c1.main_datapipe
-        m2 = c1.map(lambda x: x * 2)
+        m2 = c1.map(_x_mult_2)
         dp = m2.zip(c2)
 
         return traverse(dp, only_datapipe=True), (src_dp, m1, ub, dm, c1, c2, m2, dp)