simplify recognize digits example code (#10722)

python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py

@@ -71,24 +71,18 @@ def train(use_cuda, train_program, save_dirname):
         if isinstance(event, fluid.EndEpochEvent):
             test_reader = paddle.batch(
                 paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
-            test_metrics = trainer.test(
+            avg_cost, acc = trainer.test(
                 reader=test_reader, feed_order=['img', 'label'])
-            avg_cost_set = test_metrics[0]
-            acc_set = test_metrics[1]
-
-            # get test acc and loss
-            acc = numpy.array(acc_set).mean()
-            avg_cost = numpy.array(avg_cost_set).mean()
 
             print("avg_cost: %s" % avg_cost)
             print("acc     : %s" % acc)
 
-            if float(acc) > 0.2:  # Smaller value to increase CI speed
+            if acc > 0.2:  # Smaller value to increase CI speed
                 trainer.save_params(save_dirname)
             else:
                 print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
-                    event.epoch + 1, float(avg_cost), float(acc)))
-                if math.isnan(float(avg_cost)):
+                    event.epoch + 1, avg_cost, acc))
+                if math.isnan(avg_cost):
                     sys.exit("got NaN loss, training failed.")
         elif isinstance(event, fluid.EndStepEvent):
             print("Step {0}, Epoch {1} Metrics {2}".format(

python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py

@@ -55,24 +55,18 @@ def train(use_cuda, train_program, save_dirname):
         if isinstance(event, fluid.EndEpochEvent):
             test_reader = paddle.batch(
                 paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
-            test_metrics = trainer.test(
+            avg_cost, acc = trainer.test(
                 reader=test_reader, feed_order=['img', 'label'])
-            avg_cost_set = test_metrics[0]
-            acc_set = test_metrics[1]
-
-            # get test acc and loss
-            acc = numpy.array(acc_set).mean()
-            avg_cost = numpy.array(avg_cost_set).mean()
 
             print("avg_cost: %s" % avg_cost)
             print("acc     : %s" % acc)
 
-            if float(acc) > 0.2:  # Smaller value to increase CI speed
+            if acc > 0.2:  # Smaller value to increase CI speed
                 trainer.save_params(save_dirname)
             else:
                 print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
-                    event.epoch + 1, float(avg_cost), float(acc)))
-                if math.isnan(float(avg_cost)):
+                    event.epoch + 1, avg_cost, acc))
+                if math.isnan(avg_cost):
                     sys.exit("got NaN loss, training failed.")
 
     train_reader = paddle.batch(