diff --git a/paddle/fluid/operators/reshape_op.cc b/paddle/fluid/operators/reshape_op.cc
index a9fd1869c9df5464db6fc87ac633cdba2d6dbe7f..a1dfe39c3a4f84f5e4aaa2306813a7decf0e49ea 100644
--- a/paddle/fluid/operators/reshape_op.cc
+++ b/paddle/fluid/operators/reshape_op.cc
@@ -127,12 +127,6 @@ class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
     AddOutput("Out", "(Tensor). The output tensor of reshape operator.");
     AddAttr<std::vector<int>>(
         "shape", "(std::vector<int>) Target shape of reshape operator.");
-    AddAttr<bool>("inplace",
-                  "(default: false) Change the source tensor's shape without "
-                  "memory copy. When Attr(inplace) is set true, the output "
-                  "tensor shares memory with Input(X), otherwise, a new output "
-                  "tensor is created, and its data are copied from Input(x).")
-        .SetDefault(false);
     AddComment(R"DOC(
 Reshape Operator.
 
@@ -233,16 +227,9 @@ class ReshapeKernel {
           "sequence_reshape op.");
     }
 
-    bool inplace = ctx.Attr<bool>("inplace");
+    out->mutable_data(ctx.GetPlace(), in->type());
+    framework::TensorCopySync(*in, ctx.GetPlace(), out);
     out->Resize(out_dims);
-    if (!inplace) {
-      out->mutable_data(ctx.GetPlace(), in->type());
-      framework::TensorCopySync(*in, ctx.GetPlace(), out);
-      out->Resize(out_dims);
-    } else {
-      out->ShareDataWith(*in);
-      out->Resize(out_dims);
-    }
   }
 };
 
@@ -251,19 +238,11 @@ class ReshapeGradKernel {
   void operator()(const framework::ExecutionContext &ctx) const {
     auto *d_out = ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
     auto *d_x = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
+    auto in_dims = d_x->dims();
 
     d_x->mutable_data(ctx.GetPlace(), d_out->type());
-    bool inplace = ctx.Attr<bool>("inplace");
-
-    auto in_dims = d_x->dims();
-    if (!inplace) {
-      framework::TensorCopy(*d_out, ctx.GetPlace(), ctx.device_context(), d_x);
-      ctx.device_context().Wait();
-      d_x->Resize(in_dims);
-    } else {
-      d_x->ShareDataWith(*d_out);
-      d_x->Resize(in_dims);
-    }
+    framework::TensorCopySync(*d_out, ctx.GetPlace(), d_x);
+    d_x->Resize(in_dims);
   }
 };
 
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 5d7f1eadd93a82dc2bdb88c5f5c80e437df4e29f..058acd4a50ef54cea724a742d40eaca8f569a21c 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -4473,15 +4473,14 @@ def reshape(x, shape, actual_shape=None, act=None, inplace=True, name=None):
                 "except one unknown dimension.")
 
     helper = LayerHelper("reshape", **locals())
-    reshaped = helper.create_tmp_variable(dtype=x.dtype)
+    out = helper.create_tmp_variable(dtype=x.dtype)
     helper.append_op(
         type="reshape",
         inputs=inputs,
-        attrs={"shape": shape,
-               "inplace": inplace},
-        outputs={"Out": reshaped})
+        attrs={"shape": shape},
+        outputs={"Out": out})
 
-    return helper.append_activation(reshaped)
+    return helper.append_activation(out)
 
 
 def lod_reset(x, y=None, target_lod=None):
diff --git a/python/paddle/fluid/tests/unittests/test_memory_optimization_transpiler.py b/python/paddle/fluid/tests/unittests/test_memory_optimization_transpiler.py
index cfd6e63e12258a92447e68b4afbc7ead91b68cc1..67733807f8f8582f68dcfa3f361e13a631a29597 100644
--- a/python/paddle/fluid/tests/unittests/test_memory_optimization_transpiler.py
+++ b/python/paddle/fluid/tests/unittests/test_memory_optimization_transpiler.py
@@ -43,5 +43,29 @@ class TestControlFlowGraph(unittest.TestCase):
         print(str(result_program))
 
 
+class TestMemoryTranspiler2(unittest.TestCase):
+    def setUp(self):
+        program = Program()
+        with program_guard(program, startup_program=Program()):
+            x = layers.data(name='x', shape=[13], dtype='float32')
+            fc = layers.fc(input=x, size=10, act=None)
+            reshape = layers.reshape(x=fc, shape=[-1, 2, 5])
+            fc = layers.reshape(x=reshape, shape=[-1, 5, 2])
+            y_predict = layers.fc(input=fc, size=1, act=None)
+            y = layers.data(name='y', shape=[1], dtype='float32')
+            cost = layers.square_error_cost(input=y_predict, label=y)
+            avg_cost = layers.mean(cost)
+            opt = optimizer.SGD(learning_rate=0.001)
+            opt.minimize(avg_cost)
+        self.program = program
+
+    def test_inplace_ops(self):
+        print("before optimization")
+        print(str(self.program))
+        result_program = memory_optimize(self.program)
+        print("after optimization")
+        print(str(result_program))
+
+
 if __name__ == "__main__":
     unittest.main()
diff --git a/python/paddle/fluid/tests/unittests/test_reshape_op.py b/python/paddle/fluid/tests/unittests/test_reshape_op.py
index f51b5a7e9907294a5b91c920a363830d8b9a7137..2f5558578ac2a002a83c2a7e027ec5a96d8b4414 100644
--- a/python/paddle/fluid/tests/unittests/test_reshape_op.py
+++ b/python/paddle/fluid/tests/unittests/test_reshape_op.py
@@ -25,7 +25,7 @@ class TestReshapeOp(OpTest):
 
         self.op_type = "reshape"
         self.inputs = {"X": np.random.random(ori_shape).astype("float32")}
-        self.attrs = {"shape": new_shape, "inplace": False}
+        self.attrs = {"shape": new_shape}
         self.outputs = {"Out": self.inputs["X"].reshape(new_shape)}
 
     def test_check_output(self):
@@ -42,7 +42,7 @@ class TestReshapeOpDimInfer1(OpTest):
 
         self.op_type = "reshape"
         self.inputs = {"X": np.random.random(ori_shape).astype("float32")}
-        self.attrs = {"shape": new_shape, "inplace": False}
+        self.attrs = {"shape": new_shape}
         self.outputs = {"Out": self.inputs["X"].reshape(self.attrs["shape"])}
 
     def test_check_output(self):
@@ -60,7 +60,7 @@ class TestReshapeOpDimInfer2(OpTest):
 
         self.op_type = "reshape"
         self.inputs = {"X": np.random.random(ori_shape).astype("float32")}
-        self.attrs = {"shape": new_shape, "inplace": False}
+        self.attrs = {"shape": new_shape}
         self.outputs = {"Out": self.inputs["X"].reshape(infered_shape)}
 
     def test_check_output(self):