rm nn.Graph.train (#5424)

* rm nn.Graph.train

* Update graph.py

GraphCofig default predict

* Update test_graph.py

oneflow/python/nn/graph.py

@@ -39,7 +39,6 @@ class Graph(object):
         self._optimizers = OrderedDict()
         self._is_compiled = False
         self._state_tensortuple = None
-        self.train(True)
 
     @property
     def name(self):
@@ -64,12 +63,6 @@ class Graph(object):
             optimizer, lr_scheduler, grad_clipping_conf, weight_decay_conf
         )
 
-    def train(self, mode: bool = True):
-        self.config._train(mode)
-        for name, block in self._blocks.items():
-            assert block.type == BlockType.MODULE
-            block.origin.train(mode)
-
     def _named_state(self):
         for _, b in self._blocks.items():
             prefix = b.name + "."
@@ -329,6 +322,7 @@ class Block(object):
 class GraphConfig(FunctionConfig):
     def __init__(self):
         super().__init__()
+        self._train(False)
 
     @property
     def proto(self):

oneflow/python/test/graph/test_graph.py

@@ -114,23 +114,11 @@ class TestGraph(flow.unittest.TestCase):
 
         g = CustomGraph()
 
-        # check set train to True
-        g.train(True)
-        test_case.assertEqual(g.training, True)
-        test_case.assertEqual(g.m.training, True)
-        test_case.assertEqual(g.m.layer.conv1.training, True)
+        # check default training is True
+        test_case.assertEqual(g.config.training, False)
 
         # set graph config
         g.config.enable_fuse_add_to_output(True)
-
-        # check set train to False
-        g.train(False)
-        test_case.assertEqual(g.training, False)
-        test_case.assertEqual(g.training, False)
-        test_case.assertEqual(g.m.training, False)
-        test_case.assertEqual(g.m.layer.conv1.training, False)
-
-        # set graph config
         g.config.enable_fuse_add_to_output(False)
 
         # check _named_state get the right tensor