moved to trainfprop

Author: hycis

tensorgraph/sequential.py

@@ -15,15 +15,15 @@ def train_fprop(self, input_state, layers=None):
         if layers is None:
             layers = range(len(self.layers))
         for i in layers:
-            layer_output = self.layers[i]._train_fprop(input_state)
+            layer_output = self.layers[i].train_fprop(input_state)
             input_state = layer_output
         return input_state
 
     def test_fprop(self, input_state, layers=None):
         if layers is None:
             layers = range(len(self.layers))
         for i in layers:
-            layer_output = self.layers[i]._test_fprop(input_state)
+            layer_output = self.layers[i].test_fprop(input_state)
             input_state = layer_output
         return input_state
 

test/tensorgraph_test.py

@@ -31,6 +31,7 @@ def __init__(self, h, w, c):
 
 class TGModel(BaseModel):
 
+    @BaseModel.init_name_scope
     def __init__(self, h, w, c, nclass):
         layers = []
         layers.append(CBR(h,w,c))
@@ -107,7 +108,7 @@ def train(n_exp, h, w, c, nclass, batch_size=100, tgmodel=True):
             # tensorgraph model
             print('..using graph model')
             seq = TGModel(h, w, c, nclass)
-            y_train_sb = seq._train_fprop(X_ph)
+            y_train_sb = seq.train_fprop(X_ph)
 
         else:
             # tensorflow model