fix tanh problem

fluid/text_classification/clouds/scdb_parallel_executor.py

@@ -238,7 +238,7 @@ def lstm_net(data,
         size=[dict_dim, emb_dim],
         param_attr=fluid.ParamAttr(learning_rate=emb_lr))
 
-    fc0 = fluid.layers.fc(input=emb, size=hid_dim * 4, act='tanh')
+    fc0 = fluid.layers.fc(input=emb, size=hid_dim * 4)
 
     lstm_h, c = fluid.layers.dynamic_lstm(
         input=fc0, size=hid_dim * 4, is_reverse=False)
@@ -273,9 +273,9 @@ def bilstm_net(data,
         size=[dict_dim, emb_dim],
         param_attr=fluid.ParamAttr(learning_rate=emb_lr))
 
-    fc0 = fluid.layers.fc(input=emb, size=hid_dim * 4, act='tanh')
+    fc0 = fluid.layers.fc(input=emb, size=hid_dim * 4)
 
-    rfc0 = fluid.layers.fc(input=emb, size=hid_dim * 4, act='tanh')
+    rfc0 = fluid.layers.fc(input=emb, size=hid_dim * 4)
 
     lstm_h, c = fluid.layers.dynamic_lstm(
         input=fc0, size=hid_dim * 4, is_reverse=False)

fluid/text_classification/clouds/scdb_single_card.py

@@ -238,7 +238,7 @@ def lstm_net(data,
         size=[dict_dim, emb_dim],
         param_attr=fluid.ParamAttr(learning_rate=emb_lr))
 
-    fc0 = fluid.layers.fc(input=emb, size=hid_dim * 4, act='tanh')
+    fc0 = fluid.layers.fc(input=emb, size=hid_dim * 4)
 
     lstm_h, c = fluid.layers.dynamic_lstm(
         input=fc0, size=hid_dim * 4, is_reverse=False)
@@ -273,9 +273,9 @@ def bilstm_net(data,
         size=[dict_dim, emb_dim],
         param_attr=fluid.ParamAttr(learning_rate=emb_lr))
 
-    fc0 = fluid.layers.fc(input=emb, size=hid_dim * 4, act='tanh')
+    fc0 = fluid.layers.fc(input=emb, size=hid_dim * 4)
 
-    rfc0 = fluid.layers.fc(input=emb, size=hid_dim * 4, act='tanh')
+    rfc0 = fluid.layers.fc(input=emb, size=hid_dim * 4)
 
     lstm_h, c = fluid.layers.dynamic_lstm(
         input=fc0, size=hid_dim * 4, is_reverse=False)

fluid/text_classification/nets.py

@@ -75,7 +75,7 @@ def lstm_net(data,
         size=[dict_dim, emb_dim],
         param_attr=fluid.ParamAttr(learning_rate=emb_lr))
 
-    fc0 = fluid.layers.fc(input=emb, size=hid_dim * 4, act='tanh')
+    fc0 = fluid.layers.fc(input=emb, size=hid_dim * 4)
 
     lstm_h, c = fluid.layers.dynamic_lstm(
         input=fc0, size=hid_dim * 4, is_reverse=False)