fix add dense table (#23681)

* fix add dense table
test=develop

* fix
test=develop

* fix
test=develop

python/paddle/fluid/incubate/fleet/parameter_server/pslib/optimizer_factory.py

@@ -470,10 +470,10 @@ class DistributedAdam(DistributedOptimizerImplBase):
                                     strategy.get("scale_datanorm", -1)
                                 })
 
-                    program_configs[program_id]["pull_dense"].extend(
-                        [dense_table_index])
-                    program_configs[program_id]["push_dense"].extend(
-                        [dense_table_index])
+                        program_configs[program_id]["pull_dense"].extend(
+                            [dense_table_index])
+                        program_configs[program_id]["push_dense"].extend(
+                            [dense_table_index])
                     dense_table_index += 1
 
             # Todo(guru4elephant): figure out how to support more sparse parameters

python/paddle/fluid/tests/unittests/test_fleet.py

@@ -62,7 +62,9 @@ class TestFleet1(unittest.TestCase):
             emb = fluid.layers.embedding(input=show, size=[1, 1], \
                 is_sparse=True, is_distributed=True, \
                 param_attr=fluid.ParamAttr(name="embedding"))
-            fc = fluid.layers.fc(input=emb, size=1, act=None)
+            bow = fluid.layers.sequence_pool(input=emb, pool_type='sum')
+            bow = fluid.layers.data_norm(input=bow, epsilon=1e-4, name="norm")
+            fc = fluid.layers.fc(input=bow, size=1, act=None)
             label = fluid.layers.data(name="click", shape=[-1, 1], \
                 dtype="int64", lod_level=1, append_batch_size=False)
             label_cast = fluid.layers.cast(label, dtype='float32')