Update get_start_model.rst

Author: zsdonghao

docs/user/get_start_model.rst

@@ -23,7 +23,7 @@ Static model
       nn = Dropout(keep=0.8)(nn)
       nn = Dense(n_units=800, act=tf.nn.relu)(nn)
       nn = Dropout(keep=0.8)(nn)
-      nn = Dense(n_units=10, act=tf.nn.relu)(nn)
+      nn = Dense(n_units=10, act=None)(nn)
       M = Model(inputs=ni, outputs=nn, name="mlp") # “name" is optional
       return M
 
@@ -49,7 +49,7 @@ In this case, you need to manually input the output shape of the previous layer
           self.dropout2 = Dropout(keep=0.8)
           self.dense2 = Dense(n_units=800, act=tf.nn.relu, in_channels=800)
           self.dropout3 = Dropout(keep=0.8)
-          self.dense3 = Dense(n_units=10, act=tf.nn.relu, in_channels=800)
+          self.dense3 = Dense(n_units=10, act=None, in_channels=800)
 
       def forward(self, x, foo=False):
           z = self.dropout1(x)
@@ -156,7 +156,7 @@ Print model information
   #   (dropout_1): Dropout(keep=0.8, name='dropout_1')
   #   (dense_1): Dense(n_units=800, relu, in_channels='800', name='dense_1')
   #   (dropout_2): Dropout(keep=0.8, name='dropout_2')
-  #   (dense_2): Dense(n_units=10, relu, in_channels='800', name='dense_2')
+  #   (dense_2): Dense(n_units=10, None, in_channels='800', name='dense_2')
   # )
   
   import pprint
@@ -195,7 +195,7 @@ Print model information
   #                                   'name': 'dropout_3'},
   #                          'class': 'Dropout',
   #                          'prev_layer': ['dense_2_node_0']},
-  #                         {'args': {'act': 'relu',
+  #                         {'args': {'act': None,
   #                                   'layer_type': 'normal',
   #                                   'n_units': 10,
   #                                   'name': 'dense_3'},