diff --git a/src/operators/kernel/arm/dequantize_kernel.cpp b/src/operators/kernel/arm/dequantize_kernel.cpp
index c9dfd6f93667cf283e83e21c0a1f3725bb847956..7c0d1cea18c90145c5dbc06de7cb97fa5ed289b6 100644
--- a/src/operators/kernel/arm/dequantize_kernel.cpp
+++ b/src/operators/kernel/arm/dequantize_kernel.cpp
@@ -34,7 +34,7 @@ void DequantizeKernel<CPU, float>::Compute(const DequantizeParam<CPU> &param) {
   LoDTensor *output = param.output_;
   float activation_scale = param.activation_scale_->data<float>()[0];
   float weight_scale = param.weight_scale_;
-  const int32_t *x = input->data<const int32_t>();
+  const int32_t *x = input->data<int32_t>();
   float *y = output->mutable_data<float>();
   size_t size = output->numel();
   // float scale = 1.f / (activation_scale * weight_scale);
diff --git a/src/operators/kernel/arm/quantize_kernel.cpp b/src/operators/kernel/arm/quantize_kernel.cpp
index 79186be79e5b4207e9f6b2b221bc1a4160e4e67e..515e9cf40dad4eedd307bc59309177910330a3bf 100644
--- a/src/operators/kernel/arm/quantize_kernel.cpp
+++ b/src/operators/kernel/arm/quantize_kernel.cpp
@@ -36,7 +36,7 @@ inline float32_t vmaxvq_f32(float32x4_t r) {
 template <RoundType R>
 inline void QuantizeOffline(const Tensor *input, const float scale,
                             const float max_abs, Tensor *output) {
-  const float *x = input->data<const float>();
+  const float *x = input->data<float>();
   int8_t *y = output->mutable_data<int8_t>();
   size_t remain = input->numel();
 #if defined(__ARM_NEON__) || defined(__ARM_NEON)
@@ -88,7 +88,7 @@ inline void QuantizeOffline(const Tensor *input, const float scale,
 template <RoundType R>
 inline void QuantizeOnline(const Tensor *input, const float scale,
                            Tensor *output) {
-  const float *x = input->data<const float>();
+  const float *x = input->data<float>();
   int8_t *y = output->mutable_data<int8_t>();
   size_t remain = input->numel();
 #if defined(__ARM_NEON__) || defined(__ARM_NEON)
@@ -143,7 +143,7 @@ static void Quantize(const Tensor *input, const float max_abs,
 
 float find_abs_max(const Tensor *input) {
   float max_abs = 0.f;
-  const float *x = input->data<const float>();
+  const float *x = input->data<float>();
   size_t remain = input->numel();
 #if defined(__ARM_NEON__) || defined(__ARM_NEON)
   size_t loop = remain >> 4;
diff --git a/test/operators/test_gru_op.cpp b/test/operators/test_gru_op.cpp
index 704a4df0294e46cd661d5b010398baa6fa40a740..b14c4642fd7638aed0473790ac9ca3bc18476160 100644
--- a/test/operators/test_gru_op.cpp
+++ b/test/operators/test_gru_op.cpp
@@ -20,8 +20,8 @@ namespace paddle_mobile {
 
 template <typename Itype, typename Otype>
 int TestGruOp(int in_channels, int out_channels, std::string opname) {
-  int input_c = in_channels;
-  int output_c = out_channels;
+  size_t input_c = in_channels;
+  size_t output_c = out_channels;
   paddle_mobile::framework::LoD lod{{0, input_c}};
   int batch_size = lod.size();
   framework::DDim input_shape = framework::make_ddim({input_c, output_c * 3});
diff --git a/test/operators/test_quantize_op.cpp b/test/operators/test_quantize_op.cpp
index 2f8e08806be426e3cb23804514a01b0ca44a0fe1..d8e72e9b1472d0de48143b37ee2a7fe48ad4e174 100644
--- a/test/operators/test_quantize_op.cpp
+++ b/test/operators/test_quantize_op.cpp
@@ -65,7 +65,7 @@ static void quantize(const Tensor *input, const float scale, Tensor *output) {
   int output_w = output->dims()[3];
   size_t input_spatial = input_h * input_w;
   size_t output_spatial = output_h * output_w;
-  const float *x = input->data<const float>();
+  const float *x = input->data<float>();
   int8_t *y = output->mutable_data<int8_t>();
 
   for (int nc = 0; nc < batch_size * channels; ++nc) {
@@ -81,7 +81,7 @@ static void quantize(const Tensor *input, const float scale, Tensor *output) {
 
 static float find_abs_max(const Tensor *input) {
   float max_abs = 0.f;
-  const float *x = input->data<const float>();
+  const float *x = input->data<float>();
   size_t size = input->numel();
   for (size_t i = 0; i < size; ++i) {
     float value = std::abs(x[i]);