diff --git a/python/paddle/fluid/memory_optimization_transpiler.py b/python/paddle/fluid/memory_optimization_transpiler.py
index 708ca08b17c85efbb25ecaf2580b7141421e25b9..e82456a99fc607f8a892b78c11450488c7b93a10 100644
--- a/python/paddle/fluid/memory_optimization_transpiler.py
+++ b/python/paddle/fluid/memory_optimization_transpiler.py
@@ -31,6 +31,8 @@ dtype_to_size = {
 
 sub_block_ops = ["while", "while_grad", "parallel_do", "parallel_do_grad"]
 
+PRINT_LOG = False
+
 
 class ControlFlowGraph(object):
     def __init__(self, Program, ops, forward_num, skip_opt):
@@ -170,7 +172,7 @@ class ControlFlowGraph(object):
                                     block_desc, cache_var, is_forward).dtype()
                                 # TODO(qijun): actually, we should compare dtype_to_size[x_dtype]
                                 # and dtype_to_size[cache_dtype]
-                                if x_dtype == cache_dtype:
+                                if x_dtype == cache_dtype and PRINT_LOG:
                                     print(("Hit Cache !!!! cache pool index "
                                            "is %d, var name is %s, "
                                            "cached var name is %s, "
@@ -277,7 +279,9 @@ def _get_cfgs(input_program):
     return cfgs
 
 
-def memory_optimize(input_program):
+def memory_optimize(input_program, print_log=False):
+    global PRINT_LOG
+    PRINT_LOG = print_log
     cfgs = _get_cfgs(input_program)
     for cfg in cfgs:
         cfg.memory_optimize()
diff --git a/python/paddle/fluid/tests/book_memory_optimization/test_memopt_fit_a_line.py b/python/paddle/fluid/tests/book_memory_optimization/test_memopt_fit_a_line.py
index 7648bb9fe1c8d2dae3590fa67f781743ba297c32..c9d2a5ecaab0669f308b5b9c5cf74d0212fa462a 100644
--- a/python/paddle/fluid/tests/book_memory_optimization/test_memopt_fit_a_line.py
+++ b/python/paddle/fluid/tests/book_memory_optimization/test_memopt_fit_a_line.py
@@ -49,7 +49,7 @@ avg_cost = fluid.layers.mean(x=cost)
 sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.01)
 sgd_optimizer.minimize(avg_cost)
 
-fluid.memory_optimize(fluid.default_main_program())
+fluid.memory_optimize(fluid.default_main_program(), print_log=True)
 
 BATCH_SIZE = 200