fix other file format

fluid/image_classification/caffe2fluid/kaffe/graph.py

@@ -122,8 +122,8 @@ class Graph(object):
     def compute_output_shapes(self):
         sorted_nodes = self.topologically_sorted()
         for node in sorted_nodes:
-            node.output_shape = make_tensor(*NodeKind.compute_output_shape(
-                node))
+            node.output_shape = make_tensor(
+                *NodeKind.compute_output_shape(node))
 
     def replaced(self, new_nodes):
         return Graph(nodes=new_nodes, name=self.name, trace=self.output_trace)

fluid/mnist/_ce.py

@@ -19,6 +19,7 @@ tracking_kpis = [
     train_duration_kpi,
 ]
 
+
 def parse_log(log):
     '''
     This method should be implemented by model developers.
@@ -37,7 +38,7 @@ def parse_log(log):
     '''
     for line in log.split('\n'):
         fs = line.strip().split('\t')
-        print (fs)
+        print(fs)
         if len(fs) == 3 and fs[0] == 'kpis':
             kpi_name = fs[1]
             kpi_value = float(fs[2])
@@ -50,12 +51,11 @@ def log_to_ce(log):
         kpi_tracker[kpi.name] = kpi
 
     for (kpi_name, kpi_value) in parse_log(log):
-        print (kpi_name, kpi_value)
+        print(kpi_name, kpi_value)
         kpi_tracker[kpi_name].add_record(kpi_value)
         kpi_tracker[kpi_name].persist()
 
 
 if __name__ == '__main__':
     log = sys.stdin.read()
-    log_to_ce(log) 
-    
+    log_to_ce(log)

fluid/mnist/model.py

@@ -183,10 +183,10 @@ def run_benchmark(model, args):
                (pass_end - pass_start)))
         #Note: The following logs are special for CE monitoring.
         #Other situations do not need to care about these logs.
-        print ("kpis	train_acc	%f" % train_avg_acc)
-        print ("kpis	train_cost	%f" % train_avg_loss)  
-        print ("kpis	test_acc	%f" % test_avg_acc)  
-        print ("kpis	train_duration	%f" % (pass_end - pass_start))  
+        print("kpis	train_acc	%f" % train_avg_acc)
+        print("kpis	train_cost	%f" % train_avg_loss)
+        print("kpis	test_acc	%f" % test_avg_acc)
+        print("kpis	train_duration	%f" % (pass_end - pass_start))
 
 
 if __name__ == '__main__':