Optimize: fuse quantize and pad op

src/framework/load_ops.h

@@ -233,3 +233,6 @@ LOAD_OP1(quantize, CPU);
 #ifdef DEQUANT_OP
 LOAD_OP1(dequantize, CPU);
 #endif
+#ifdef PAD_OP
+LOAD_OP1(pad, CPU);
+#endif

src/operators/dequantize_op.cpp

@@ -22,7 +22,7 @@ namespace operators {
 template <typename DeviceType, typename T>
 void DequantizeOp<DeviceType, T>::InferShape() const {
   const auto& input_dims = this->param_.input_->dims();
-  this->param_.out_->Resize(input_dims);
+  this->param_.output_->Resize(input_dims);
 }
 
 }  // namespace operators

src/operators/kernel/arm/conv_kernel.cpp

@@ -15,6 +15,7 @@ limitations under the License. */
 #ifdef CONV_OP
 
 #include "operators/kernel/conv_kernel.h"
+#include <iostream>
 #include "operators/kernel/central-arm-func/conv_arm_func.h"
 
 namespace paddle_mobile {
@@ -22,8 +23,15 @@ namespace operators {
 
 template <>
 bool ConvKernel<CPU, float>::Init(ConvParam<CPU> *param) {
-  if (param->Input()->type() == typeid(int8_t)) {
-    param->ExecMode() = ConvParam<CPU>::EXEC_GEMM_INT8;
+  if (param->Filter()->type() == typeid(int8_t)) {
+    if (param->Groups() == param->Input()->dims()[1] &&
+        param->Input()->dims()[1] == param->Output()->dims()[1] &&
+        param->Filter()->dims()[2] == param->Filter()->dims()[3] &&
+        param->Filter()->dims()[2] == 3) {
+      param->ExecMode() = ConvParam<CPU>::EXEC_DEPTHWISE3x3_INT8;
+    } else {
+      param->ExecMode() = ConvParam<CPU>::EXEC_GEMM_INT8;
+    }
   } else {
     if (param->Groups() == param->Input()->dims()[1] &&
         param->Input()->dims()[1] == param->Output()->dims()[1] &&
@@ -35,6 +43,7 @@ bool ConvKernel<CPU, float>::Init(ConvParam<CPU> *param) {
                param->Filter()->dims()[2] == param->Filter()->dims()[3] &&
                param->Filter()->dims()[2] == 3) {
       param->ExecMode() = ConvParam<CPU>::EXEC_DEPTHWISE3x3_FLOAT;
+#ifndef __aarch64__
     } else if (param->Filter()->dims()[2] == param->Filter()->dims()[3] &&
                param->Strides()[0] == param->Strides()[1] &&
                param->Dilations()[0] == param->Dilations()[1] &&
@@ -48,6 +57,7 @@ bool ConvKernel<CPU, float>::Init(ConvParam<CPU> *param) {
       operators::math::winograd_transform_weight<8, 3>(*param->Filter(),
                                                        transformed_weight);
       param->Filter() = transformed_weight;
+#endif
     } else {
       param->ExecMode() = ConvParam<CPU>::EXEC_GEMM_FLOAT;
     }
@@ -60,25 +70,36 @@ void ConvKernel<CPU, float>::Compute(const ConvParam<CPU> &param) {
   switch (param.ExecMode()) {
     case ConvParam<CPU>::EXEC_GEMM_INT8:
       GemmConv<int8_t, int32_t>(param);
+      std::cout << "EXEC_GEMM_INT8" << std::endl;
+      break;
+    case ConvParam<CPU>::EXEC_DEPTHWISE3x3_INT8:
+      DepthwiseConv3x3<int8_t, int32_t>(param);
+      std::cout << "EXEC_DEPTHWISE3x3_INT8" << std::endl;
       break;
     case ConvParam<CPU>::EXEC_DEPTHWISE3x3S1P1_FLOAT:
       math::DepthwiseConv3x3s1p1(param.Input(), param.Filter(), param.Output(),
                                  nullptr, false);
+      std::cout << "EXEC_DEPTHWISE3x3S1P1_FLOAT" << std::endl;
       break;
     case ConvParam<CPU>::EXEC_DEPTHWISE3x3_FLOAT:
       math::DepthwiseConv3x3(param.Input(), param.Strides(), param.Paddings(),
                              param.Filter(), nullptr, param.Output(), false);
+      std::cout << "EXEC_DEPTHWISE3x3_FLOAT=" << param.Strides()[0]
+                << std::endl;
       break;
     case ConvParam<CPU>::EXEC_WINOGRAD3X3_FLOAT:
       WinogradConv3x3<8, 3>(param);
+      std::cout << "EXEC_WINOGRAD3X3_FLOAT" << std::endl;
       break;
     case ConvParam<CPU>::EXEC_GEMM_FLOAT:
       GemmConv<float, float>(param);
+      std::cout << "EXEC_GEMM_FLOAT" << std::endl;
       break;
     default:
       PADDLE_MOBILE_THROW_EXCEPTION("Invalid convolution execute mode %d",
                                     param.ExecMode());
   }
+  std::cout << "exec here..." << std::endl;
 }
 
 template class ConvKernel<CPU, float>;

src/operators/kernel/arm/dequantize_kernel.cpp

@@ -15,6 +15,7 @@ limitations under the License. */
 #ifdef DEQUANT_OP
 
 #include "operators/kernel/dequantize_kernel.h"
+#include <iostream>
 
 #if defined(__ARM_NEON__) || defined(__ARM_NEON)
 #include <arm_neon.h>
@@ -31,7 +32,7 @@ bool DequantizeKernel<CPU, float>::Init(DequantizeParam<CPU> *param) {
 template <>
 void DequantizeKernel<CPU, float>::Compute(const DequantizeParam<CPU> &param) {
   const Tensor *input = param.input_;
-  Tensor *output = param.out_;
+  Tensor *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>();

src/operators/kernel/arm/elementwise_add_kernel.cpp

@@ -15,6 +15,7 @@ limitations under the License. */
 #ifdef ELEMENTWISEADD_OP
 
 #include "operators/kernel/elementwise_add_kernel.h"
+#include <iostream>
 #include "operators/kernel/central-arm-func/elementwise_add_arm_func.h"
 
 namespace paddle_mobile {

src/operators/kernel/arm/quantize_kernel.cpp

@@ -21,15 +21,15 @@ limitations under the License. */
 #include <arm_neon.h>
 
 #ifndef __aarch64__
-float32_t vmaxvq_f32(float32x4_t r) {
+inline float32_t vmaxvq_f32(float32x4_t r) {
   float32x2_t v = vmax_f32(vget_high_f32(r), vget_low_f32(r));
   return vget_lane_f32(vpmax_f32(v, v), 0);
 }
 #endif
 
-int32x4_t vrnd_towards_zero(float32x4_t r) { return vcvtq_s32_f32(r); }
+inline int32x4_t vrnd_towards_zero(float32x4_t r) { return vcvtq_s32_f32(r); }
 
-int32x4_t vrnd_away_zero(float32x4_t r) {
+inline int32x4_t vrnd_away_zero(float32x4_t r) {
   float32x4_t plus = vdupq_n_f32(0.5);
   float32x4_t minus = vdupq_n_f32(-0.5);
   float32x4_t zero = vdupq_n_f32(0);
@@ -40,7 +40,7 @@ int32x4_t vrnd_away_zero(float32x4_t r) {
   return ret;
 }
 
-int32x4_t vrnd_to_even(float32x4_t r) {
+inline int32x4_t vrnd_to_even(float32x4_t r) {
 #if 0
   int32x4_t ret;
   float value[4];
@@ -84,7 +84,6 @@ int32x4_t vrnd_to_even(float32x4_t r) {
   return rnd;
 #endif
 }
-#endif
 
 namespace paddle_mobile {
 namespace operators {
@@ -127,6 +126,7 @@ static float find_abs_max(const Tensor *input) {
   return max_abs;
 }
 
+#ifdef __aarch64__
 static void quantize_round_to_even(const Tensor *input, const float scale,
                                    Tensor *output) {
   const float *x = input->data<const float>();
@@ -188,7 +188,7 @@ static void quantize_round_to_zero(const Tensor *input, const float scale,
   const float *x = input->data<const float>();
   int8_t *y = output->mutable_data<int8_t>();
   size_t size = input->numel();
-#ifdef defined(__ARM_NEON__) || defined(__ARM_NEON)
+#if defined(__ARM_NEON__) || defined(__ARM_NEON)
   size_t loop = size >> 4;
   size_t remain = size & 0xF;
 
@@ -224,7 +224,7 @@ static void quantize_round_to_zero(const Tensor *input, const float scale,
   y += (loop << 4);
 #endif
   for (size_t i = 0; i < size; ++i) {
-    y[i] = trunc(x[i] * scale);
+    y[i] = static_cast<int8_t>(x[i] * scale);
   }
 }
 
@@ -272,6 +272,464 @@ static void quantize_round_to_nearest(const Tensor *input, const float scale,
     y[i] = round(x[i] * scale);
   }
 }
+#else   // __aarch64__
+
+static void quantize_round_to_even(const Tensor *input, const float scale,
+                                   const std::vector<int> &paddings,
+                                   const int8_t padding_val, Tensor *output) {}
+
+static void quantize_round_to_nearest(const Tensor *input, const float scale,
+                                      const std::vector<int> &paddings,
+                                      const int8_t padding_val,
+                                      Tensor *output) {}
+
+static void quantize_round_to_zero(const Tensor *input, const float scale,
+                                   const std::vector<int> &paddings,
+                                   const int8_t padding_val, Tensor *output) {
+  int channels = input->dims()[1];
+  int input_h = input->dims()[2];
+  int input_w = input->dims()[3];
+  int output_h = output->dims()[2];
+  int output_w = output->dims()[3];
+  int input_spatial_size = input_h * input_w;
+  int output_spatial_size = output_h * output_w;
+  const float *x = input->data<float>();
+  int8_t *y = output->mutable_data<int8_t>();
+  // valid area start
+  int start = paddings[0] * output_w + paddings[1];
+
+  for (int batch = 0; batch < input->dims()[0]; ++batch) {
+    for (int c = 0; c < channels - 3; c += 4) {
+      const float *x0 = x + c * input_spatial_size;
+      const float *x1 = x0 + input_spatial_size;
+      const float *x2 = x1 + input_spatial_size;
+      const float *x3 = x2 + input_spatial_size;
+      size_t offset = c * output_spatial_size;
+      for (int h = 0; h < 2; ++h) {
+        int8_t *y0 =
+            y + offset + h * ((input_h + paddings[0]) * output_w - paddings[1]);
+        int8_t *y1 = y0 + output_spatial_size;
+        int8_t *y2 = y1 + output_spatial_size;
+        int8_t *y3 = y2 + output_spatial_size;
+        int loop = start >> 4;
+        int remain = start & 0xFFF0;
+        asm volatile(
+            "vdup.s8    q0,     %[val]      \n"
+            "cmp        %[loop], #0         \n"
+            "ble        start_remain_%=     \n"
+
+            "store_16w_%=:                  \n"
+            "vst1.32    {q0}, [%[y0]]!      \n"
+            "vst1.32    {q0}, [%[y1]]!      \n"
+            "vst1.32    {q0}, [%[y2]]!      \n"
+            "vst1.32    {q0}, [%[y3]]!      \n"
+            "subs       %[loop], #1         \n"
+            "bne        store_16w_%=        \n"
+
+            "start_remain_%=:               \n"
+            "cmp        %[remain], #8       \n"
+            "blt        store_4w_%=         \n"
+            "vst1.32    {d0}, [%[y0]]!      \n"
+            "vst1.32    {d0}, [%[y1]]!      \n"
+            "vst1.32    {d0}, [%[y2]]!      \n"
+            "vst1.32    {d0}, [%[y3]]!      \n"
+            "sub        %[remain], #8       \n"
+
+            "store_4w_%=:                   \n"
+            "cmp        %[remain], #4       \n"
+            "blt        store_2w_%=         \n"
+            "vst1.32    {d0[0]}, [%[y0]]!   \n"
+            "vst1.32    {d0[0]}, [%[y1]]!   \n"
+            "vst1.32    {d0[0]}, [%[y2]]!   \n"
+            "vst1.32    {d0[0]}, [%[y3]]!   \n"
+            "sub        %[remain], #4       \n"
+
+            "store_2w_%=:                   \n"
+            "cmp        %[remain], #4       \n"
+            "blt        store_1w_%=         \n"
+            "vst1.16    {d0[0]}, [%[y0]]!   \n"
+            "vst1.16    {d0[0]}, [%[y1]]!   \n"
+            "vst1.16    {d0[0]}, [%[y2]]!   \n"
+            "vst1.16    {d0[0]}, [%[y3]]!   \n"
+            "sub        %[remain], #2       \n"
+
+            "store_1w_%=:                   \n"
+            "cmp        %[remain], #1       \n"
+            "blt        end_%=              \n"
+            "vst1.8     {d0[0]}, [%[y0]]!   \n"
+            "vst1.8     {d0[0]}, [%[y1]]!   \n"
+            "vst1.8     {d0[0]}, [%[y2]]!   \n"
+            "vst1.8     {d0[0]}, [%[y3]]!   \n"
+            "end_%=:                        \n"
+            : [y0] "+r"(y0), [y1] "+r"(y1), [y2] "+r"(y2), [y3] "+r"(y3),
+              [loop] "+r"(loop), [remain] "+r"(remain)
+            : [val] "r"(padding_val)
+            : "cc", "memory", "q0");
+      }
+      // quantize valid area
+      int8_t *y0 = y + offset + start;
+      int8_t *y1 = y0 + output_spatial_size;
+      int8_t *y2 = y1 + output_spatial_size;
+      int8_t *y3 = y2 + output_spatial_size;
+      for (int h = 0; h < input_h; ++h) {
+        int loop = input_w >> 4;
+        int remain = input_w & 0xFFF0;
+        int pad_loop = paddings[1] >> 1;
+        int pad_remain = paddings[1] & 0xFFFE;
+        asm volatile(
+            "vdup.f32   q0, %[scale]        \n"
+            "cmp        %[loop], #0         \n"
+            "ble        quantize_remain_%=  \n"
+
+            "loop_quantize_%=:              \n"
+            "vld1.32    {q1, q2}, [%[x0]]!  \n"
+            "vld1.32    {q3, q4}, [%[x1]]!  \n"
+            "vld1.32    {q5, q6}, [%[x2]]!  \n"
+            "vld1.32    {q7, q8}, [%[x3]]!  \n"
+            "vmul.f32  q1, q1, q0           \n"
+            "vmul.f32  q2, q2, q0           \n"
+            "vmul.f32  q3, q3, q0           \n"
+            "vmul.f32  q4, q4, q0           \n"
+            "vmul.f32  q5, q5, q0           \n"
+            "vmul.f32  q6, q6, q0           \n"
+            "vmul.f32  q7, q7, q0           \n"
+            "vmul.f32  q8, q8, q0           \n"
+            "vcvt.s32.f32  q1, q1           \n"
+            "vcvt.s32.f32  q2, q2           \n"
+            "vcvt.s32.f32  q3, q3           \n"
+            "vcvt.s32.f32  q4, q4           \n"
+            "vcvt.s32.f32  q5, q5           \n"
+            "vcvt.s32.f32  q6, q6           \n"
+            "vcvt.s32.f32  q7, q7           \n"
+            "vcvt.s32.f32  q8, q8           \n"
+            "vmovn.s32  d2, q1              \n"
+            "vmovn.s32  d3, q2              \n"
+            "vmovn.s32  d4, q3              \n"
+            "vmovn.s32  d5, q4              \n"
+            "vmovn.s32  d6, q5              \n"
+            "vmovn.s32  d7, q6              \n"
+            "vmovn.s32  d8, q7              \n"
+            "vmovn.s32  d9, q8              \n"
+            "vmovn.s16  d18, q1             \n"
+            "vmovn.s16  d20, q2             \n"
+            "vmovn.s16  d22, q3             \n"
+            "vmovn.s16  d24, q4             \n"
+            "vld1.32    {q1, q2}, [%[x0]]!  \n"
+            "vld1.32    {q3, q4}, [%[x1]]!  \n"
+            "vld1.32    {q5, q6}, [%[x2]]!  \n"
+            "vld1.32    {q7, q8}, [%[x3]]!  \n"
+            "vmul.f32  q1, q1, q0           \n"
+            "vmul.f32  q2, q2, q0           \n"
+            "vmul.f32  q3, q3, q0           \n"
+            "vmul.f32  q4, q4, q0           \n"
+            "vmul.f32  q5, q5, q0           \n"
+            "vmul.f32  q6, q6, q0           \n"
+            "vmul.f32  q7, q7, q0           \n"
+            "vmul.f32  q8, q8, q0           \n"
+            "vcvt.s32.f32  q1, q1           \n"
+            "vcvt.s32.f32  q2, q2           \n"
+            "vcvt.s32.f32  q3, q3           \n"
+            "vcvt.s32.f32  q4, q4           \n"
+            "vcvt.s32.f32  q5, q5           \n"
+            "vcvt.s32.f32  q6, q6           \n"
+            "vcvt.s32.f32  q7, q7           \n"
+            "vcvt.s32.f32  q8, q8           \n"
+            "vmovn.s32  d2, q1              \n"
+            "vmovn.s32  d3, q2              \n"
+            "vmovn.s32  d4, q3              \n"
+            "vmovn.s32  d5, q4              \n"
+            "vmovn.s32  d6, q5              \n"
+            "vmovn.s32  d7, q6              \n"
+            "vmovn.s32  d8, q7              \n"
+            "vmovn.s32  d9, q8              \n"
+            "vmovn.s16  d19, q1             \n"
+            "vmovn.s16  d21, q2             \n"
+            "vmovn.s16  d23, q3             \n"
+            "vmovn.s16  d25, q4             \n"
+            "vst1.32    {q9}, [%[y0]]       \n"
+            "vst1.32    {q10}, [%[y0]]      \n"
+            "vst1.32    {q11}, [%[y0]]      \n"
+            "vst1.32    {q12}, [%[y0]]      \n"
+
+            "subs       %[loop], #1         \n"
+            "bne        loop_quantize_%=    \n"
+
+            "quantize_remain_%=:            \n"
+            "cmp        %[remain], #0       \n"
+            "ble        end_%=              \n"
+
+            "vld1.32    {q1, q2}, [%[x0]]   \n"
+            "vld1.32    {q3, q4}, [%[x1]]   \n"
+            "vld1.32    {q5, q6}, [%[x2]]   \n"
+            "vld1.32    {q7, q8}, [%[x3]]   \n"
+            "vmul.f32  q1, q1, q0           \n"
+            "vmul.f32  q2, q2, q0           \n"
+            "vmul.f32  q3, q3, q0           \n"
+            "vmul.f32  q4, q4, q0           \n"
+            "vmul.f32  q5, q5, q0           \n"
+            "vmul.f32  q6, q6, q0           \n"
+            "vmul.f32  q7, q7, q0           \n"
+            "vmul.f32  q8, q8, q0           \n"
+            "vcvt.s32.f32  q1, q1           \n"
+            "vcvt.s32.f32  q2, q2           \n"
+            "vcvt.s32.f32  q3, q3           \n"
+            "vcvt.s32.f32  q4, q4           \n"
+            "vcvt.s32.f32  q5, q5           \n"
+            "vcvt.s32.f32  q6, q6           \n"
+            "vcvt.s32.f32  q7, q7           \n"
+            "vcvt.s32.f32  q8, q8           \n"
+            "vmovn.s32  d2, q1              \n"
+            "vmovn.s32  d3, q2              \n"
+            "vmovn.s32  d4, q3              \n"
+            "vmovn.s32  d5, q4              \n"
+            "vmovn.s32  d6, q5              \n"
+            "vmovn.s32  d7, q6              \n"
+            "vmovn.s32  d8, q7              \n"
+            "vmovn.s32  d9, q8              \n"
+            "vmovn.s16  d18, q1             \n"
+            "vmovn.s16  d20, q2             \n"
+            "vmovn.s16  d22, q3             \n"
+            "vmovn.s16  d24, q4             \n"
+            "vld1.32    {q1, q2}, [%[x0]]!  \n"
+            "vld1.32    {q3, q4}, [%[x1]]!  \n"
+            "vld1.32    {q5, q6}, [%[x2]]!  \n"
+            "vld1.32    {q7, q8}, [%[x3]]!  \n"
+            "vmul.f32  q1, q1, q0           \n"
+            "vmul.f32  q2, q2, q0           \n"
+            "vmul.f32  q3, q3, q0           \n"
+            "vmul.f32  q4, q4, q0           \n"
+            "vmul.f32  q5, q5, q0           \n"
+            "vmul.f32  q6, q6, q0           \n"
+            "vmul.f32  q7, q7, q0           \n"
+            "vmul.f32  q8, q8, q0           \n"
+            "vcvt.s32.f32  q1, q1           \n"
+            "vcvt.s32.f32  q2, q2           \n"
+            "vcvt.s32.f32  q3, q3           \n"
+            "vcvt.s32.f32  q4, q4           \n"
+            "vcvt.s32.f32  q5, q5           \n"
+            "vcvt.s32.f32  q6, q6           \n"
+            "vcvt.s32.f32  q7, q7           \n"
+            "vcvt.s32.f32  q8, q8           \n"
+            "vmovn.s32  d2, q1              \n"
+            "vmovn.s32  d3, q2              \n"
+            "vmovn.s32  d4, q3              \n"
+            "vmovn.s32  d5, q4              \n"
+            "vmovn.s32  d6, q5              \n"
+            "vmovn.s32  d7, q6              \n"
+            "vmovn.s32  d8, q7              \n"
+            "vmovn.s32  d9, q8              \n"
+            "vmovn.s16  d19, q1             \n"
+            "vmovn.s16  d21, q2             \n"
+            "vmovn.s16  d23, q3             \n"
+            "vmovn.s16  d25, q4             \n"
+
+            "cmp        %[remain], #8       \n"
+            "blt        store_4w_%=         \n"
+            "vst1.32    {d18}, [%[y0]]!     \n"
+            "vst1.32    {d20}, [%[y1]]!     \n"
+            "vst1.32    {d22}, [%[y2]]!     \n"
+            "vst1.32    {d24}, [%[y3]]!     \n"
+            "vmov.32    d18, d19            \n"
+            "vmov.32    d20, d21            \n"
+            "vmov.32    d22, d23            \n"
+            "vmov.32    d24, d25            \n"
+            "sub        %[remain], #8       \n"
+
+            "store_4w_%=:                   \n"
+            "cmp        %[remain], #4       \n"
+            "blt        store_2w_%=         \n"
+            "vst1.32    {d18[0]}, [%[y0]]!  \n"
+            "vst1.32    {d20[0]}, [%[y1]]!  \n"
+            "vst1.32    {d22[0]}, [%[y2]]!  \n"
+            "vst1.32    {d24[0]}, [%[y3]]!  \n"
+            "vext.32    d18, d18, d18, #1   \n"
+            "vext.32    d20, d20, d20, #1   \n"
+            "vext.32    d22, d22, d22, #1   \n"
+            "vext.32    d24, d24, d24, #1   \n"
+            "sub        %[remain], #4       \n"
+
+            "store_2w_%=:                   \n"
+            "cmp        %[remain], #2       \n"
+            "blt        store_1w_%=         \n"
+            "vst1.16    {d18[0]}, [%[y0]]!  \n"
+            "vst1.16    {d20[0]}, [%[y1]]!  \n"
+            "vst1.16    {d22[0]}, [%[y2]]!  \n"
+            "vst1.16    {d24[0]}, [%[y3]]!  \n"
+            "vext.16    d18, d18, d18, #1   \n"
+            "vext.16    d20, d20, d20, #1   \n"
+            "vext.16    d22, d22, d22, #1   \n"
+            "vext.16    d24, d24, d24, #1   \n"
+            "sub        %[remain], #2       \n"
+
+            "store_1w_%=:"
+            "cmp        %[remain], #1       \n"
+            "blt        end_%=              \n"
+            "vst1.8     {d18[0]}, [%[y0]]!  \n"
+            "vst1.8     {d20[0]}, [%[y1]]!  \n"
+            "vst1.8     {d22[0]}, [%[y2]]!  \n"
+            "vst1.8     {d24[0]}, [%[y3]]!  \n"
+
+            "end_%=:                        \n"
+            : [x0] "+r"(x0), [x1] "+r"(x1), [x2] "+r"(x2), [x3] "+r"(x3),
+              [y0] "+r"(y0), [y1] "+r"(y1), [y2] "+r"(y2), [y3] "+r"(y3),
+              [loop] "+r"(loop), [remain] "+r"(remain)
+            : [scale] "r"(scale)
+            : "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8",
+              "q9", "q10", "q11", "q12");
+        asm volatile(
+            "vdup.s8    d0, %[val]          \n"
+            "cmp        %[pad_loop], #0     \n"
+            "ble        store_pad_2w_%=     \n"
+            "loop_pad_4w_%=:                \n"
+            "vst1.32    {d0[0]}, [%[y0]]!   \n"
+            "vst1.32    {d0[0]}, [%[y1]]!   \n"
+            "vst1.32    {d0[0]}, [%[y2]]!   \n"
+            "vst1.32    {d0[0]}, [%[y3]]!   \n"
+            "subs       %[pad_loop], #1     \n"
+            "bne        loop_pad_4w_%=      \n"
+
+            "store_pad_2w_%=:               \n"
+            "cmp        %[pad_remain], #2   \n"
+            "ble        store_pad_1w_%=     \n"
+            "vst1.16    {d0[0]}, [%[y0]]!   \n"
+            "vst1.16    {d0[0]}, [%[y1]]!   \n"
+            "vst1.16    {d0[0]}, [%[y2]]!   \n"
+            "vst1.16    {d0[0]}, [%[y3]]!   \n"
+            "sub        %[pad_remain], #2   \n"
+
+            "store_pad_1w_%=:               \n"
+            "cmp        %[pad_remain], #1   \n"
+            "ble        end_%=              \n"
+            "vst1.8    {d0[0]}, [%[y0]]!    \n"
+            "vst1.8    {d0[0]}, [%[y1]]!    \n"
+            "vst1.8    {d0[0]}, [%[y2]]!    \n"
+            "vst1.8    {d0[0]}, [%[y3]]!    \n"
+            "end_%=:                        \n"
+            : [y0] "+r"(y0), [y1] "+r"(y1), [y2] "+r"(y2), [y3] "+r"(y3),
+              [pad_loop] "+r"(pad_loop), [pad_remain] "+r"(pad_remain)
+            : [val] "r"(padding_val)
+            : "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8",
+              "q9", "q10", "q11", "q12");
+
+        x0 += remain;
+        x1 += remain;
+        x2 += remain;
+        x3 += remain;
+      }
+    }
+    for (int c = (channels & 0xFFFC); c < channels; ++c) {
+      const float *x0 = x + c * input_spatial_size;
+      int8_t *y0 = y + c * output_spatial_size;
+      for (int h = 0; h < paddings[0]; ++h) {
+        int loop = input_w >> 4;
+        int remain = input_w & 0xFFF0;
+        int pad_loop = paddings[1] >> 1;
+        int pad_remain = paddings[1] & 0xFFFE;
+        asm volatile(
+            "vdup.f32   q0, %[scale]        \n"
+            "cmp        %[loop], #0         \n"
+            "ble        quantize_remain_%=  \n"
+
+            "loop_quantize_%=:              \n"
+            "vld1.32    {q1, q2}, [%[x0]]!  \n"
+            "vmul.f32  q1, q1, q0           \n"
+            "vmul.f32  q2, q2, q0           \n"
+            "vcvt.s32.f32  q1, q1           \n"
+            "vcvt.s32.f32  q2, q2           \n"
+            "vmovn.s32  d2, q1              \n"
+            "vmovn.s32  d3, q2              \n"
+            "vmovn.s16  d18, q1             \n"
+            "vld1.32    {q1, q2}, [%[x0]]!  \n"
+            "vmul.f32  q1, q1, q0           \n"
+            "vmul.f32  q2, q2, q0           \n"
+            "vcvt.s32.f32  q1, q1           \n"
+            "vcvt.s32.f32  q2, q2           \n"
+            "vmovn.s32  d2, q1              \n"
+            "vmovn.s32  d3, q2              \n"
+            "vmovn.s16  d19, q1             \n"
+            "vst1.32    {q9}, [%[y0]]       \n"
+
+            "subs       %[loop], #1         \n"
+            "bne        loop_quantize_%=    \n"
+
+            "quantize_remain_%=:            \n"
+            "cmp        %[remain], #0       \n"
+            "ble        start_pad_%=        \n"
+
+            "vld1.32    {q1, q2}, [%[x0]]   \n"
+            "vmul.f32  q1, q1, q0           \n"
+            "vmul.f32  q2, q2, q0           \n"
+            "vcvt.s32.f32  q1, q1           \n"
+            "vcvt.s32.f32  q2, q2           \n"
+            "vmovn.s32  d2, q1              \n"
+            "vmovn.s32  d3, q2              \n"
+            "vmovn.s16  d18, q1             \n"
+            "vld1.32    {q1, q2}, [%[x0]]!  \n"
+            "vmul.f32  q1, q1, q0           \n"
+            "vmul.f32  q2, q2, q0           \n"
+            "vcvt.s32.f32  q1, q1           \n"
+            "vcvt.s32.f32  q2, q2           \n"
+            "vmovn.s32  d2, q1              \n"
+            "vmovn.s32  d3, q2              \n"
+            "vmovn.s16  d19, q1             \n"
+
+            "cmp        %[remain], #8       \n"
+            "blt        store_4w_%=         \n"
+            "vst1.32    {d18}, [%[y0]]!     \n"
+            "vmov.32    d18, d19            \n"
+            "sub        %[remain], #8       \n"
+
+            "store_4w_%=:                   \n"
+            "cmp        %[remain], #4       \n"
+            "blt        store_2w_%=         \n"
+            "vst1.32    {d18[0]}, [%[y0]]!  \n"
+            "vext.32    d18, d18, d18, #1   \n"
+            "sub        %[remain], #4       \n"
+
+            "store_2w_%=:                   \n"
+            "cmp        %[remain], #2       \n"
+            "blt        store_1w_%=         \n"
+            "vst1.16    {d18[0]}, [%[y0]]!  \n"
+            "vext.16    d18, d18, d18, #1   \n"
+            "sub        %[remain], #2       \n"
+
+            "store_1w_%=:"
+            "cmp        %[remain], #1       \n"
+            "blt        start_pad_%=        \n"
+            "vst1.8     {d18[0]}, [%[y0]]!  \n"
+
+            "start_pad_%=:                  \n"
+            "vdup.s8    d0, %[val]          \n"
+            "cmp        %[pad_loop], #0     \n"
+            "ble        pad_remain_%=       \n"
+            "loop_pad_4w_%=:                \n"
+            "vst1.32    {d0[0]}, [%[y0]]!   \n"
+            "subs       %[pad_loop], #1     \n"
+            "bne        loop_pad_4w_%=      \n"
+
+            "pad_remain_%=:                 \n"
+            "cmp        %[pad_remain], #2   \n"
+            "ble        store_pad_1w_%=     \n"
+            "vst1.16    {d0[0]}, [%[y0]]!   \n"
+            "sub        %[pad_remain], #2   \n"
+
+            "store_pad_1w_%=:               \n"
+            "cmp        %[pad_remain], #1   \n"
+            "ble        end_%=              \n"
+            "vst1.8    {d0[0]}, [%[y0]]!    \n"
+            "end_%=:                        \n"
+            : [x0] "+r"(x0), [y0] "+r"(y0), [loop] "+r"(loop),
+              [remain] "+r"(remain), [pad_loop] "+r"(pad_loop),
+              [pad_remain] "+r"(pad_remain)
+            : [scale] "r"(scale), [val] "r"(padding_val)
+            : "memory", "q0", "q1", "q2", "q9");
+        x0 += remain;
+      }
+    }
+  }
+}
+#endif  // __aarch64__
+#endif  // ARM_NEON
 
 template <>
 bool QuantizeKernel<CPU, float>::Init(QuantizeParam<CPU> *param) {
@@ -280,10 +738,10 @@ bool QuantizeKernel<CPU, float>::Init(QuantizeParam<CPU> *param) {
 
 template <>
 void QuantizeKernel<CPU, float>::Compute(const QuantizeParam<CPU> &param) {
-  float max_abs = 0.f;
   const Tensor *input = param.input_;
-  Tensor *output = param.out_;
+  Tensor *output = param.output_;
   Tensor *output_scale = param.online_scale_;
+  float max_abs = 0.f;
   if (param.is_static_) {
     max_abs = param.static_scale_;
   } else {
@@ -293,15 +751,19 @@ void QuantizeKernel<CPU, float>::Compute(const QuantizeParam<CPU> &param) {
   // only support int8 currently
   float scale = 127 / max_abs;
   param.online_scale_->mutable_data<float>()[0] = max_abs;
+  //  const auto &paddings = param.paddings_;
+  std::vector<int> paddings = {0, 0};
+  //  const auto padding_val = param.padding_val_;
+  int8_t padding_val = 127;
   switch (param.round_type_) {
     case ROUND_NEAREST_TO_EVEN:
-      quantize_round_to_even(input, scale, output);
+      quantize_round_to_even(input, scale, paddings, padding_val, output);
       break;
     case ROUND_NEAREST_TOWARDS_ZERO:
-      quantize_round_to_zero(input, scale, output);
+      quantize_round_to_zero(input, scale, paddings, padding_val, output);
       break;
     case ROUND_NEAREST_AWAY_ZERO:
-      quantize_round_to_nearest(input, scale, output);
+      quantize_round_to_nearest(input, scale, paddings, padding_val, output);
       break;
     default:
       LOG(kLOG_ERROR) << "round type is not supported.";

src/operators/kernel/central-arm-func/conv_add_arm_func.h

@@ -17,7 +17,7 @@ limitations under the License. */
 
 #include <vector>
 #include "operators/math/conv_func.h"
-#include "operators/math/depthwise_conv_3x3.h"
+#include "operators/math/depthwise_conv3x3.h"
 #include "operators/math/im2col.h"
 #include "operators/math/math_function.h"
 #include "operators/math/vol2col.h"

src/operators/kernel/central-arm-func/conv_add_bn_relu_arm_func.h

@@ -17,7 +17,7 @@ limitations under the License. */
 #pragma once
 
 #include <vector>
-#include "operators/math/depthwise_conv_3x3.h"
+#include "operators/math/depthwise_conv3x3.h"
 #include "operators/math/im2col.h"
 #include "operators/math/math_function.h"
 #include "operators/math/vol2col.h"

src/operators/kernel/central-arm-func/conv_arm_func.h

@@ -17,7 +17,7 @@ limitations under the License. */
 #pragma once
 #include <vector>
 #include "operators/math/conv_func.h"
-#include "operators/math/depthwise_conv_3x3.h"
+#include "operators/math/depthwise_conv3x3.h"
 #include "operators/math/im2col.h"
 #include "operators/math/math_function.h"
 #include "operators/math/pad.h"
@@ -39,10 +39,7 @@ inline void GemmConv(const ConvParam<CPU> &param) {
   const std::vector<int> paddings = param.Paddings();
   const std::vector<int> dilations = param.Dilations();
 
-  const int batch_size = static_cast<int>(input->dims()[0]);
-
   std::vector<int64_t> filter_shape_vec(framework::vectorize(filter.dims()));
-
   std::vector<int64_t> output_shape_vec(framework::vectorize(output->dims()));
   size_t data_dim = filter_shape_vec.size() - 2;
   std::vector<int64_t> col_shape_vec(1 + 2 * data_dim);
@@ -83,6 +80,7 @@ inline void GemmConv(const ConvParam<CPU> &param) {
   math::Vol2ColFunctor<CPU, Itype> vol2col;
   math::Im2ColFunctor<math::ColFormat::kCFO, CPU, Itype> im2col;
 
+  const int batch_size = static_cast<int>(input->dims()[0]);
   for (int i = 0; i < batch_size; i++) {
     Tensor in_batch = input->Slice(i, i + 1).Resize(input_shape);
     Tensor out_batch = output->Slice(i, i + 1).Resize(output_matrix_shape);
@@ -126,7 +124,6 @@ inline void WinogradConv3x3(const ConvParam<CPU> &param) {
   int batch_size = input->dims()[0];
   int groups = param.Groups();
   const std::vector<int> &paddings = param.Paddings();
-  math::PadFunctor<CPU, float> pad;
 
   auto winograd_pad = [&](int width, int pad) {
     int output_tile = tile - kernel + 1;
@@ -136,6 +133,7 @@ inline void WinogradConv3x3(const ConvParam<CPU> &param) {
     return pad_width + tile - width;
   };
 
+  math::PadFunctor<CPU, float> pad;
   Tensor input_pad;
   framework::Tensor transformed_input;
   for (int i = 0; i < batch_size; ++i) {
@@ -155,15 +153,49 @@ inline void WinogradConv3x3(const ConvParam<CPU> &param) {
     } else {
       input_pad = in_batch;
     }
-#if __aarch64__
-      // TODO(hjchen2)
-#else
     // tile input and transform
     math::winograd_transform_input<tile, kernel>(input_pad, &transformed_input);
     // caculate output
     math::winograd_transform_output<tile, kernel>(transformed_input, *filter,
                                                   output);
-#endif
+  }
+}
+
+template <typename Itype, typename Otype>
+inline void DepthwiseConv3x3(const ConvParam<CPU> &param) {
+  const Tensor *input = param.Input();
+  const Tensor *filter = param.Filter();
+  Tensor *output = param.Output();
+  output->mutable_data<Otype>();
+
+  const std::vector<int> &paddings = param.Paddings();
+  const std::vector<int> &strides = param.Strides();
+  const int batch_size = static_cast<int>(input->dims()[0]);
+  Tensor input_pad;
+  math::PadFunctor<CPU, Itype> pad;
+  for (int i = 0; i < batch_size; i++) {
+    Tensor in_batch = input->Slice(i, i + 1);
+    Tensor out_batch = output->Slice(i, i + 1);
+    //    if (paddings[0] || paddings[1]) {
+    //      framework::DDim pad_shape = in_batch.dims();
+    //      pad_shape[2] += 2 * paddings[0];
+    //      pad_shape[3] += 2 * paddings[1];
+    //      input_pad.mutable_data<float>(pad_shape);
+    //      pad(in_batch, paddings[0], paddings[0], paddings[1], paddings[1],
+    //          &input_pad);
+    //    } else {
+    //      input_pad = in_batch;
+    //    }
+    //    math::DepthwiseConv3x3s1<Itype, Otype>(input_pad, *filter,
+    //    &out_batch);
+    if (strides[0] == 1) {
+      math::DepthwiseConv3x3s1<Itype, Otype>(in_batch, *filter, &out_batch);
+    } else if (strides[0] == 2) {
+      math::DepthwiseConv3x3s2<Itype, Otype>(in_batch, *filter, &out_batch);
+    } else {
+      //      math::DepthwiseConv3x3<Itype, Otype>(in_batch, *filter,
+      //      &out_batch);
+    }
   }
 }
 

src/operators/kernel/central-arm-func/conv_bn_add_relu_arm_func.h

@@ -17,7 +17,7 @@ limitations under the License. */
 #pragma once
 
 #include <vector>
-#include "operators/math/depthwise_conv_3x3.h"
+#include "operators/math/depthwise_conv3x3.h"
 #include "operators/math/im2col.h"
 #include "operators/math/math_function.h"
 #include "operators/math/vol2col.h"

src/operators/kernel/central-arm-func/conv_bn_relu_arm_func.h

@@ -16,13 +16,15 @@ limitations under the License. */
 
 #pragma once
 #include <vector>
-#include "operators/math/depthwise_conv_3x3.h"
+#include "operators/math/depthwise_conv3x3.h"
 #include "operators/math/im2col.h"
 #include "operators/math/math_function.h"
 #include "operators/math/vol2col.h"
 #include "operators/op_param.h"
+
 namespace paddle_mobile {
 namespace operators {
+
 void ConvBNReluBasic(const FusionConvBNReluParam<CPU> &param) {
   const Tensor *input = param.Input();
   Tensor filter = *param.Filter();

src/operators/kernel/central-arm-func/depthwise_conv_arm_func.h

@@ -15,10 +15,9 @@ limitations under the License. */
 #ifdef DEPTHWISECONV_OP
 
 #pragma once
-#include <operators/math/depthwise_conv_3x3.h>
 #include <vector>
 #include "operators/kernel/central-arm-func/conv_arm_func.h"
-
+#include "operators/math/depthwise_conv3x3.h"
 #include "operators/op_param.h"
 
 namespace paddle_mobile {

src/operators/kernel/central-arm-func/dwconv_bn_relu_arm_func.h

@@ -16,13 +16,15 @@ limitations under the License. */
 
 #pragma once
 #include <vector>
-#include "operators/math/depthwise_conv_3x3.h"
+#include "operators/math/depthwise_conv3x3.h"
 #include "operators/math/im2col.h"
 #include "operators/math/math_function.h"
 #include "operators/math/vol2col.h"
 #include "operators/op_param.h"
+
 namespace paddle_mobile {
 namespace operators {
+
 void DWConvBNReluBasic(const FusionDWConvBNReluParam<CPU> &param) {
   const Tensor *input = param.Input();
   Tensor filter = *param.Filter();

src/operators/kernel/conv_add_kernel.h

@@ -24,7 +24,7 @@ limitations under the License. */
 #include "framework/ddim.h"
 #include "framework/operator.h"
 #include "operators/math/conv_func.h"
-#include "operators/math/depthwise_conv_3x3.h"
+#include "operators/math/depthwise_conv3x3.h"
 #include "operators/math/im2col.h"
 #include "operators/math/math_function.h"
 #include "operators/math/vol2col.h"

src/operators/math/depthwise_conv_3x3.cpp → src/operators/math/depthwise_conv3x3.cpp

@@ -11,18 +11,22 @@ distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
-#include "operators/math/depthwise_conv_3x3.h"
+
+#include "operators/math/depthwise_conv3x3.h"
+#include <vector>
 #if __ARM_NEON
 #include <arm_neon.h>
 #endif
-#include <vector>
 
 namespace paddle_mobile {
 namespace operators {
 namespace math {
-void DepthwiseConv3x3(const Tensor *input, vector<int> strides,
-                      vector<int> paddings, const Tensor *filter, Tensor *bias,
-                      Tensor *output, bool if_bias) {
+
+void DepthwiseConv3x3(const framework::Tensor *input,
+                      const std::vector<int> &strides,
+                      const std::vector<int> &paddings,
+                      const framework::Tensor *filter, framework::Tensor *bias,
+                      framework::Tensor *output, bool if_bias) {
   const int batch_size = input->dims()[0];
 
   const int input_height = input->dims()[2];
@@ -67,12 +71,12 @@ void DepthwiseConv3x3(const Tensor *input, vector<int> strides,
         for (int pw = 0; pw < output_width; pw++) {
           hstart = ph * stride_height - padding_height;
           wstart = pw * stride_width - padding_width;
-          hend = min(hstart + _kernel_size, input_height + padding_height);
-          wend = min(wstart + _kernel_size, input_width + padding_width);
-          hstart = max(hstart, 0);
-          wstart = max(wstart, 0);
-          hend = min(hend, input_height);
-          wend = min(wend, input_width);
+          hend = std::min(hstart + _kernel_size, input_height + padding_height);
+          wend = std::min(wstart + _kernel_size, input_width + padding_width);
+          hstart = std::max(hstart, 0);
+          wstart = std::max(wstart, 0);
+          hend = std::min(hend, input_height);
+          wend = std::min(wend, input_width);
           pos1 = input_data + hstart * input_width + wstart;
           pos2 = input_data + (hstart + 1) * input_width + wstart;
           pos3 = input_data + (hstart + 2) * input_width + wstart;
@@ -244,8 +248,10 @@ void DepthwiseConv3x3(const Tensor *input, vector<int> strides,
   }
 }
 
-void DepthwiseConv3x3s1p1(const Tensor *input, const Tensor *filter,
-                          Tensor *output, Tensor *bias, bool if_bias) {
+void DepthwiseConv3x3s1p1(const framework::Tensor *input,
+                          const framework::Tensor *filter,
+                          framework::Tensor *output, framework::Tensor *bias,
+                          bool if_bias) {
 #if __ARM_NEON
   const float *input_data = input->data<float>();
   const float *filter_data = filter->data<float>();
@@ -517,9 +523,12 @@ void DepthwiseConv3x3s1p1(const Tensor *input, const Tensor *filter,
 #endif
 }
 
-void DepthwiseConvAddBNRelu3x3s1p1(const Tensor *input, const Tensor *filter,
-                                   Tensor *output, const Tensor *new_scale,
-                                   const Tensor *new_bias, bool if_relu) {
+void DepthwiseConvAddBNRelu3x3s1p1(const framework::Tensor *input,
+                                   const framework::Tensor *filter,
+                                   framework::Tensor *output,
+                                   const framework::Tensor *new_scale,
+                                   const framework::Tensor *new_bias,
+                                   bool if_relu) {
 #if __ARM_NEON
   const float *input_data = input->data<float>();
   const float *filter_data = filter->data<float>();
@@ -1059,9 +1068,12 @@ void DepthwiseConvAddBNRelu3x3s1p1(const Tensor *input, const Tensor *filter,
 }
 
 /// w!=h not fix
-void DepthwiseConvAddBNRelu3x3s2p1(const Tensor *input, const Tensor *filter,
-                                   Tensor *output, const Tensor *new_scale,
-                                   const Tensor *new_bias, bool if_relu) {
+void DepthwiseConvAddBNRelu3x3s2p1(const framework::Tensor *input,
+                                   const framework::Tensor *filter,
+                                   framework::Tensor *output,
+                                   const framework::Tensor *new_scale,
+                                   const framework::Tensor *new_bias,
+                                   bool if_relu) {
 #if __ARM_NEON
 
   const int batch_size = input->dims()[0];
@@ -1107,12 +1119,12 @@ void DepthwiseConvAddBNRelu3x3s2p1(const Tensor *input, const Tensor *filter,
         for (int pw = 0; pw < output_width; pw++) {
           hstart = ph * stride_height - padding_height;
           wstart = pw * stride_width - padding_width;
-          hend = min(hstart + _kernel_size, input_height + padding_height);
-          wend = min(wstart + _kernel_size, input_width + padding_width);
-          hstart = max(hstart, 0);
-          wstart = max(wstart, 0);
-          hend = min(hend, input_height);
-          wend = min(wend, input_width);
+          hend = std::min(hstart + _kernel_size, input_height + padding_height);
+          wend = std::min(wstart + _kernel_size, input_width + padding_width);
+          hstart = std::max(hstart, 0);
+          wstart = std::max(wstart, 0);
+          hend = std::min(hend, input_height);
+          wend = std::min(wend, input_width);
           pos1 = input_data + hstart * input_width + wstart;
           pos2 = input_data + (hstart + 1) * input_width + wstart;
           pos3 = input_data + (hstart + 2) * input_width + wstart;
@@ -1258,8 +1270,10 @@ void DepthwiseConvAddBNRelu3x3s2p1(const Tensor *input, const Tensor *filter,
 #endif
 }
 
-void DepthwiseConv3x3s2p1v2(const Tensor *input, const Tensor *filter,
-                            Tensor *output, Tensor bias, bool if_bias) {
+void DepthwiseConv3x3s2p1v2(const framework::Tensor *input,
+                            const framework::Tensor *filter,
+                            framework::Tensor *output, framework::Tensor bias,
+                            bool if_bias) {
 #if __ARM_NEON
   const float *input_data = input->data<float>();
   const float *filter_data = filter->data<float>();
@@ -1463,9 +1477,12 @@ void DepthwiseConv3x3s2p1v2(const Tensor *input, const Tensor *filter,
 #endif
 }
 
-void DepthwiseConvAddBNRelu3x3s2p1v2(const Tensor *input, const Tensor *filter,
-                                     Tensor *output, const Tensor *new_scale,
-                                     const Tensor *new_bias, bool if_relu) {
+void DepthwiseConvAddBNRelu3x3s2p1v2(const framework::Tensor *input,
+                                     const framework::Tensor *filter,
+                                     framework::Tensor *output,
+                                     const framework::Tensor *new_scale,
+                                     const framework::Tensor *new_bias,
+                                     bool if_relu) {
 #if __ARM_NEON
   // #ifdef _OPENMP
   //  const float *newscale_data = new_scale->data<float>();
@@ -1886,8 +1903,10 @@ void DepthwiseConvAddBNRelu3x3s2p1v2(const Tensor *input, const Tensor *filter,
 #endif
 }
 
-void DepthwiseConv3x3s2p0(const Tensor *input, const Tensor *filter,
-                          Tensor *output, Tensor bias, bool if_bias) {
+void DepthwiseConv3x3s2p0(const framework::Tensor *input,
+                          const framework::Tensor *filter,
+                          framework::Tensor *output, framework::Tensor bias,
+                          bool if_bias) {
 #if __ARM_NEON
 
   const int batch_size = static_cast<int>(input->dims()[0]);

src/operators/math/depthwise_conv3x3.h

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#pragma once
+
+#include <algorithm>
+#include <vector>
+#include "framework/tensor.h"
+#include "operators/math/conv_func.h"
+
+namespace paddle_mobile {
+namespace operators {
+namespace math {
+
+void DepthwiseConv3x3(const framework::Tensor *input,
+                      const std::vector<int> &strides,
+                      const std::vector<int> &paddings,
+                      const framework::Tensor *filter, framework::Tensor *bias,
+                      framework::Tensor *output, bool if_bias);
+
+void DepthwiseConv3x3s1p1(const framework::Tensor *input,
+                          const framework::Tensor *filter,
+                          framework::Tensor *output, framework::Tensor *bias,
+                          bool if_bias);
+
+void DepthwiseConvAddBNRelu3x3s1p1(const framework::Tensor *input,
+                                   const framework::Tensor *filter,
+                                   framework::Tensor *output,
+                                   const framework::Tensor *new_scale,
+                                   const framework::Tensor *new_bias,
+                                   bool if_relu);
+
+void DepthwiseConvAddBNRelu3x3s2p1(const framework::Tensor *input,
+                                   const framework::Tensor *filter,
+                                   framework::Tensor *output,
+                                   const framework::Tensor *new_scale,
+                                   const framework::Tensor *new_bias,
+                                   bool if_relu);
+
+void DepthwiseConv3x3s2p1v2(const framework::Tensor *input,
+                            const framework::Tensor *filter,
+                            framework::Tensor *output, framework::Tensor bias,
+                            bool if_bias);
+
+void DepthwiseConvAddBNRelu3x3s2p1v2(const framework::Tensor *input,
+                                     const framework::Tensor *filter,
+                                     framework::Tensor *output,
+                                     const framework::Tensor *new_scale,
+                                     const framework::Tensor *new_bias,
+                                     bool if_relu);
+
+void DepthwiseConv3x3s2p0(const framework::Tensor *input,
+                          const framework::Tensor *filter,
+                          framework::Tensor *output, framework::Tensor bias,
+                          bool if_bias);
+
+// template<typename Itype, typename Otype>
+// void DepthwiseConv3x3(const framework::Tensor *input,
+//                      const framework::Tensor *filter,
+//                      const std::vector<int> &strides,
+//                      framework::Tensor *output);
+
+template <typename Itype, typename Otype>
+void DepthwiseConv3x3s1(const framework::Tensor &input,
+                        const framework::Tensor &filter,
+                        framework::Tensor *output);
+
+template <typename Itype, typename Otype>
+void DepthwiseConv3x3s2(const framework::Tensor &input,
+                        const framework::Tensor &filter,
+                        framework::Tensor *output);
+
+}  // namespace math
+}  // namespace operators
+}  // namespace paddle_mobile

src/operators/math/depthwise_conv3x3_int8.cpp

@@ -12,23 +12,24 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#include "operators/math/depthwise_conv3x3_int8.h"
+#include "operators/math/depthwise_conv3x3.h"
 
 namespace paddle_mobile {
 namespace operators {
 namespace math {
 
-void DepthwiseConv3x3_int8(const framework::Tensor *input,
-                           const framework::Tensor *filter,
-                           const std::vector<int> &strides,
-                           framework::Tensor *output) {
-  PADDLE_MOBILE_THROW_EXCEPTION(
-      "Depthwise conv with generic strides has not been implemented.");
-}
+// template<>
+// void DepthwiseConv3x3<int8_t, int32_t>(
+//     const framework::Tensor *input, const framework::Tensor *filter,
+//     const std::vector<int> &strides, framework::Tensor *output) {
+//   PADDLE_MOBILE_THROW_EXCEPTION(
+//       "Depthwise conv with generic strides has not been implemented.");
+// }
 
-void DepthwiseConv3x3s1_int8(const framework::Tensor &input,
-                             const framework::Tensor &filter,
-                             framework::Tensor *output) {
+template <>
+void DepthwiseConv3x3s1<int8_t, int32_t>(const framework::Tensor &input,
+                                         const framework::Tensor &filter,
+                                         framework::Tensor *output) {
   const int8_t *input_data = input.data<int8_t>();
   const int8_t *filter_data = filter.data<int8_t>();
   int32_t *out_data = output->mutable_data<int32_t>();
@@ -41,26 +42,27 @@ void DepthwiseConv3x3s1_int8(const framework::Tensor &input,
   int output_w = output->dims()[3];
   int image_size = input_h * input_w;
   int out_image_size = output_h * output_w;
-  memset(out_data, 0, output_c * out_image_size * sizeof(int32_t));
 #if __aarch64__
   // TODO(hjchen2)
 #else
   #pragma omp parallel for
   for (int g = 0; g < input_c; ++g) {
-    const int8_t* input_ptr0 = input_data + g * image_size;
-    const int8_t* input_ptr1 = input_ptr0 + input_w;
-    const int8_t* input_ptr2 = input_ptr1 + input_w;
-    const int8_t* input_ptr3 = input_ptr2 + input_w;
-    const int8_t* input_ptr4 = input_ptr3 + input_w;
-    const int8_t* input_ptr5 = input_ptr4 + input_w;
+    const int8_t* input_ptr = input_data + g * image_size;
     const int8_t* filter_ptr = filter_data + g * 9;
-    int32_t* output_ptr0 = out_data + g * out_image_size;
-    int32_t* output_ptr1 = output_ptr0 + output_w;
-    int32_t* output_ptr2 = output_ptr1 + output_w;
-    int32_t* output_ptr3 = output_ptr2 + output_w;
+    int32_t* output_ptr = out_data + g * out_image_size;
+    int loop = (input_w - 2) / 6;
+    int remain = input_w - 2 - loop * 6;
     for (int h = 0; h < input_h - 5 /*(input_h - 2) - 3*/; h += 4) {
-      int loop = (input_w - 2) / 6;
-      int remain = input_w - loop * 6;
+      const int8_t* input_ptr0 = input_ptr + h * input_w;
+      const int8_t* input_ptr1 = input_ptr0 + input_w;
+      const int8_t* input_ptr2 = input_ptr1 + input_w;
+      const int8_t* input_ptr3 = input_ptr2 + input_w;
+      const int8_t* input_ptr4 = input_ptr3 + input_w;
+      const int8_t* input_ptr5 = input_ptr4 + input_w;
+      int32_t* output_ptr0 = output_ptr + h * output_w;
+      int32_t* output_ptr1 = output_ptr0 + output_w;
+      int32_t* output_ptr2 = output_ptr1 + output_w;
+      int32_t* output_ptr3 = output_ptr2 + output_w;
       asm volatile(
           "vld1.32    {q0}, [%[filter_ptr]] \n"
           "vmovl.s8   q14, d0               \n"
@@ -81,14 +83,13 @@ void DepthwiseConv3x3s1_int8(const framework::Tensor &input,
           "mov        r0, #6                \n"
           "cmp        %[loop], #0           \n"
           "ble        start_remain_%=       \n"
-          // loop 8 widths
-          "loop_4h8w_%=:                          \n"
+          // loop 6 widths
+          "loop_4h6w_%=:                          \n"
           "vld1.32    {d9}, [%[input_ptr0]], r0   \n"
           "vld1.32    {d10}, [%[input_ptr1]], r0  \n"
           "vld1.32    {d11}, [%[input_ptr2]], r0  \n"
-
-          "vext.s8    d12, d9, #1           \n"
-          "vext.s8    d13, d9, #2           \n"
+          "vext.s8    d12, d9, d9, #1       \n"
+          "vext.s8    d13, d9, d9, #2       \n"
           "vmovl.s8   q7, d9                \n"
           "vmovl.s8   q8, d12               \n"
           "vmovl.s8   q9, d13               \n"
@@ -99,11 +100,18 @@ void DepthwiseConv3x3s1_int8(const framework::Tensor &input,
           "vmlal.s16  q11, d17, d1          \n"
           "vmlal.s16  q11, d19, d2          \n"
 
-          "vext.s8    d12, d10, #1          \n"
-          "vext.s8    d13, d10, #2          \n"
+          "vext.s8    d12, d10, d10, #1     \n"
+          "vext.s8    d13, d10, d10, #2     \n"
           "vmovl.s8   q7, d10               \n"
           "vmovl.s8   q8, d12               \n"
           "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d3          \n"
+          "vmlal.s16  q10, d16, d4          \n"
+          "vmlal.s16  q10, d18, d5          \n"
+          "vmlal.s16  q11, d15, d3          \n"
+          "vmlal.s16  q11, d17, d4          \n"
+          "vmlal.s16  q11, d19, d5          \n"
+
           "vmull.s16  q12, d14, d0          \n"
           "vmlal.s16  q12, d16, d1          \n"
           "vmlal.s16  q12, d18, d2          \n"
@@ -111,57 +119,42 @@ void DepthwiseConv3x3s1_int8(const framework::Tensor &input,
           "vmlal.s16  q13, d17, d1          \n"
           "vmlal.s16  q13, d19, d2          \n"
 
-          "vmlal.s16  q10, d14, d3          \n"
-          "vmlal.s16  q10, d16, d4          \n"
-          "vmlal.s16  q10, d18, d5          \n"
-          "vmull.s16  q11, d15, d3          \n"
-          "vmlal.s16  q11, d17, d4          \n"
-          "vmlal.s16  q11, d19, d5          \n"
-
-          "vext.s8    d12, d11, #1          \n"
-          "vext.s8    d13, d11, #2          \n"
-          "vmovl.s8   q7, d10               \n"
+          "vext.s8    d12, d11, d11, #1     \n"
+          "vext.s8    d13, d11, d11, #2     \n"
+          "vmovl.s8   q7, d11               \n"
           "vmovl.s8   q8, d12               \n"
           "vmovl.s8   q9, d13               \n"
-          "vmull.s16  q14, d14, d0          \n"
-          "vmlal.s16  q14, d16, d1          \n"
-          "vmlal.s16  q14, d18, d2          \n"
-          "vmull.s16  q15, d15, d0          \n"
-          "vmlal.s16  q15, d17, d1          \n"
-          "vmlal.s16  q15, d19, d2          \n"
-
-          "vmlal.s16  q12, d14, d3          \n"
-          "vmlal.s16  q12, d16, d4          \n"
-          "vmlal.s16  q12, d18, d5          \n"
-          "vmull.s16  q13, d15, d3          \n"
-          "vmlal.s16  q13, d17, d4          \n"
-          "vmlal.s16  q13, d19, d5          \n"
-
           "vmlal.s16  q10, d14, d6          \n"
           "vmlal.s16  q10, d16, d7          \n"
           "vmlal.s16  q10, d18, d8          \n"
-          "vmull.s16  q11, d15, d6          \n"
+          "vmlal.s16  q11, d15, d6          \n"
           "vmlal.s16  q11, d17, d7          \n"
           "vmlal.s16  q11, d19, d8          \n"
           // store row 0, reuse q10/q11
           "vst1.32    {d20-d22}, [%[output_ptr0]]! \n"
 
+          "vmlal.s16  q12, d14, d3          \n"
+          "vmlal.s16  q12, d16, d4          \n"
+          "vmlal.s16  q12, d18, d5          \n"
+          "vmlal.s16  q13, d15, d3          \n"
+          "vmlal.s16  q13, d17, d4          \n"
+          "vmlal.s16  q13, d19, d5          \n"
+
+          "vmull.s16  q14, d14, d0          \n"
+          "vmlal.s16  q14, d16, d1          \n"
+          "vmlal.s16  q14, d18, d2          \n"
+          "vmull.s16  q15, d15, d0          \n"
+          "vmlal.s16  q15, d17, d1          \n"
+          "vmlal.s16  q15, d19, d2          \n"
+
           "vld1.32    {d9}, [%[input_ptr3]], r0    \n"
           "vld1.32    {d10}, [%[input_ptr4]], r0   \n"
           "vld1.32    {d11}, [%[input_ptr5]], r0   \n"
-
-          "vext.s8    d12, d9, #1           \n"
-          "vext.s8    d13, d9, #2           \n"
+          "vext.s8    d12, d9, d9, #1       \n"
+          "vext.s8    d13, d9, d9, #2       \n"
           "vmovl.s8   q7, d9                \n"
           "vmovl.s8   q8, d12               \n"
           "vmovl.s8   q9, d13               \n"
-          "vmull.s16  q10, d14, d0          \n"
-          "vmlal.s16  q10, d16, d1          \n"
-          "vmlal.s16  q10, d18, d2          \n"
-          "vmull.s16  q11, d15, d0          \n"
-          "vmlal.s16  q11, d17, d1          \n"
-          "vmlal.s16  q11, d19, d2          \n"
-
           "vmlal.s16  q12, d14, d6          \n"
           "vmlal.s16  q12, d16, d7          \n"
           "vmlal.s16  q12, d18, d8          \n"
@@ -178,126 +171,121 @@ void DepthwiseConv3x3s1_int8(const framework::Tensor &input,
           "vmlal.s16  q15, d17, d4          \n"
           "vmlal.s16  q15, d19, d5          \n"
 
-          "vext.s8    d12, d10, #1          \n"
-          "vext.s8    d13, d10, #2          \n"
+          "vmull.s16  q10, d14, d0          \n"
+          "vmlal.s16  q10, d16, d1          \n"
+          "vmlal.s16  q10, d18, d2          \n"
+          "vmull.s16  q11, d15, d0          \n"
+          "vmlal.s16  q11, d17, d1          \n"
+          "vmlal.s16  q11, d19, d2          \n"
+
+          "vext.s8    d12, d10, d10, #1     \n"
+          "vext.s8    d13, d10, d10, #2     \n"
           "vmovl.s8   q7, d10               \n"
           "vmovl.s8   q8, d12               \n"
           "vmovl.s8   q9, d13               \n"
-          "vmlal.s16  q10, d14, d3          \n"
-          "vmlal.s16  q10, d16, d4          \n"
-          "vmlal.s16  q10, d18, d5          \n"
-          "vmull.s16  q11, d15, d3          \n"
-          "vmlal.s16  q11, d17, d4          \n"
-          "vmlal.s16  q11, d19, d5          \n"
-
-          "vmull.s16  q14, d14, d6          \n"
+          "vmlal.s16  q14, d14, d6          \n"
           "vmlal.s16  q14, d16, d7          \n"
           "vmlal.s16  q14, d18, d8          \n"
-          "vmull.s16  q15, d15, d6          \n"
+          "vmlal.s16  q15, d15, d6          \n"
           "vmlal.s16  q15, d17, d7          \n"
           "vmlal.s16  q15, d19, d8          \n"
           // store row 2
-          "vst1.32    {d24-d26}, [%[output_ptr2]]! \n"
+          "vst1.32    {d28-d30}, [%[output_ptr2]]! \n"
 
-          "vext.s8    d12, d11, #1          \n"
-          "vext.s8    d13, d11, #2          \n"
-          "vmovl.s8   q7, d10               \n"
+          "vmlal.s16  q10, d14, d3          \n"
+          "vmlal.s16  q10, d16, d4          \n"
+          "vmlal.s16  q10, d18, d5          \n"
+          "vmlal.s16  q11, d15, d3          \n"
+          "vmlal.s16  q11, d17, d4          \n"
+          "vmlal.s16  q11, d19, d5          \n"
+
+          "vext.s8    d12, d11, d11, #1     \n"
+          "vext.s8    d13, d11, d11, #2     \n"
+          "vmovl.s8   q7, d11               \n"
           "vmovl.s8   q8, d12               \n"
           "vmovl.s8   q9, d13               \n"
-          "vmull.s16  q10, d14, d6          \n"
+          "vmlal.s16  q10, d14, d6          \n"
           "vmlal.s16  q10, d16, d7          \n"
           "vmlal.s16  q10, d18, d8          \n"
-          "vmull.s16  q11, d15, d6          \n"
+          "vmlal.s16  q11, d15, d6          \n"
           "vmlal.s16  q11, d17, d7          \n"
           "vmlal.s16  q11, d19, d8          \n"
           // store row 3
           "vst1.32    {d20-d22}, [%[output_ptr3]]! \n"
 
-          "subs       %[loop], #1          \n"
-          "bne        loop_4h8w_%=          \n"
+          "subs       %[loop], #1           \n"
+          "bne        loop_4h6w_%=          \n"
 
           "start_remain_%=:                 \n"
           "cmp %[remain], #0                \n"
           "ble end_%=                       \n"
-          "mov        r0, %[remain]         \n"
-          "add        r0, #2                \n"
 
-          "vld1.32    {d9}, [%[input_ptr0]], r0   \n"
-          "vext.s8    d12, d9, #1           \n"
-          "vext.s8    d13, d9, #2           \n"
+          "vld1.32    {d9}, [%[input_ptr0]] \n"
           "vmovl.s8   q7, d9                \n"
-          "vmovl.s8   q8, d12               \n"
-          "vmovl.s8   q9, d13               \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
           "vmull.s16  q10, d14, d0          \n"
           "vmlal.s16  q10, d16, d1          \n"
           "vmlal.s16  q10, d18, d2          \n"
-
-          "vld1.32    {d9}, [%[input_ptr1]], r0   \n"
+          "vld1.32    {d9}, [%[input_ptr1]] \n"
           "vmull.s16  q11, d15, d0          \n"
           "vmlal.s16  q11, d17, d1          \n"
           "vmlal.s16  q11, d19, d2          \n"
 
-          "vext.s8    d12, d9, #1           \n"
-          "vext.s8    d13, d9, #2           \n"
           "vmovl.s8   q7, d9                \n"
-          "vmovl.s8   q8, d12               \n"
-          "vmovl.s8   q9, d13               \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
+          "vmlal.s16  q10, d14, d3          \n"
+          "vmlal.s16  q10, d16, d4          \n"
+          "vmlal.s16  q10, d18, d5          \n"
+          "vmlal.s16  q11, d15, d3          \n"
+          "vmlal.s16  q11, d17, d4          \n"
+          "vmlal.s16  q11, d19, d5          \n"
+
           "vmull.s16  q12, d14, d0          \n"
           "vmlal.s16  q12, d16, d1          \n"
           "vmlal.s16  q12, d18, d2          \n"
+          "vld1.32    {d9}, [%[input_ptr2]] \n"
           "vmull.s16  q13, d15, d0          \n"
           "vmlal.s16  q13, d17, d1          \n"
           "vmlal.s16  q13, d19, d2          \n"
 
-          "vmlal.s16  q10, d14, d3          \n"
-          "vmlal.s16  q10, d16, d4          \n"
-          "vmlal.s16  q10, d18, d5          \n"
-
-          "vld1.32    {d9}, [%[input_ptr2]], r0   \n"
-          "vmull.s16  q11, d15, d3          \n"
-          "vmlal.s16  q11, d17, d4          \n"
-          "vmlal.s16  q11, d19, d5          \n"
-
-          "vext.s8    d12, d9, #1           \n"
-          "vext.s8    d13, d9, #2           \n"
           "vmovl.s8   q7, d9                \n"
-          "vmovl.s8   q8, d12               \n"
-          "vmovl.s8   q9, d13               \n"
-          "vmull.s16  q14, d14, d0          \n"
-          "vmlal.s16  q14, d16, d1          \n"
-          "vmlal.s16  q14, d18, d2          \n"
-          "vmull.s16  q15, d15, d0          \n"
-          "vmlal.s16  q15, d17, d1          \n"
-          "vmlal.s16  q15, d19, d2          \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
+          "vmlal.s16  q10, d14, d6          \n"
+          "vmlal.s16  q10, d16, d7          \n"
+          "vmlal.s16  q10, d18, d8          \n"
+          "vmlal.s16  q11, d15, d6          \n"
+          "vmlal.s16  q11, d17, d7          \n"
+          "vmlal.s16  q11, d19, d8          \n"
 
           "vmlal.s16  q12, d14, d3          \n"
           "vmlal.s16  q12, d16, d4          \n"
           "vmlal.s16  q12, d18, d5          \n"
-          "vmull.s16  q13, d15, d3          \n"
+          "vmlal.s16  q13, d15, d3          \n"
           "vmlal.s16  q13, d17, d4          \n"
           "vmlal.s16  q13, d19, d5          \n"
 
-          "vmlal.s16  q10, d14, d6          \n"
-          "vmlal.s16  q10, d16, d7          \n"
-          "vmlal.s16  q10, d18, d8          \n"
-
-          "vld1.32    {d9}, [%[input_ptr3]], r0   \n"
-          "vmull.s16  q11, d15, d6          \n"
-          "vmlal.s16  q11, d17, d7          \n"
-          "vmlal.s16  q11, d19, d8          \n"
+          "vmull.s16  q14, d14, d0          \n"
+          "vmlal.s16  q14, d16, d1          \n"
+          "vmlal.s16  q14, d18, d2          \n"
+          "vld1.32    {d9}, [%[input_ptr3]] \n"
+          "vmull.s16  q15, d15, d0          \n"
+          "vmlal.s16  q15, d17, d1          \n"
+          "vmlal.s16  q15, d19, d2          \n"
 
-          "vext.s8    d12, d9, #1           \n"
-          "vext.s8    d13, d9, #2           \n"
           "vmovl.s8   q7, d9                \n"
-          "vmovl.s8   q8, d12               \n"
-          "vmovl.s8   q9, d13               \n"
-          "vmull.s16  q5, d14, d0           \n"
-          "vmlal.s16  q5, d16, d1           \n"
-          "vmlal.s16  q5, d18, d2           \n"
-          "vmull.s16  q6, d15, d0           \n"
-          "vmlal.s16  q6, d17, d1           \n"
-          "vmlal.s16  q6, d19, d2           \n"
-
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
           "vmlal.s16  q12, d14, d6          \n"
           "vmlal.s16  q12, d16, d7          \n"
           "vmlal.s16  q12, d18, d8          \n"
@@ -308,42 +296,47 @@ void DepthwiseConv3x3s1_int8(const framework::Tensor &input,
           "vmlal.s16  q14, d14, d3          \n"
           "vmlal.s16  q14, d16, d4          \n"
           "vmlal.s16  q14, d18, d5          \n"
-
-          "vld1.32    {d9}, [%[input_ptr4]], r0   \n"
           "vmlal.s16  q15, d15, d3          \n"
           "vmlal.s16  q15, d17, d4          \n"
           "vmlal.s16  q15, d19, d5          \n"
 
-          "vext.s8    d12, d9, #1           \n"
-          "vext.s8    d13, d9, #2           \n"
+          "vmull.s16  q5, d14, d0           \n"
+          "vmlal.s16  q5, d16, d1           \n"
+          "vmlal.s16  q5, d18, d2           \n"
+          "vld1.32    {d9}, [%[input_ptr4]] \n"
+          "vmull.s16  q6, d15, d0           \n"
+          "vmlal.s16  q6, d17, d1           \n"
+          "vmlal.s16  q6, d19, d2           \n"
+
           "vmovl.s8   q7, d9                \n"
-          "vmovl.s8   q8, d12               \n"
-          "vmovl.s8   q9, d13               \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
+          "vmlal.s16  q14, d14, d6          \n"
+          "vmlal.s16  q14, d16, d7          \n"
+          "vmlal.s16  q14, d18, d8          \n"
+          "vmlal.s16  q15, d15, d6          \n"
+          "vmlal.s16  q15, d17, d7          \n"
+          "vmlal.s16  q15, d19, d8          \n"
+
           "vmlal.s16  q5, d14, d3           \n"
           "vmlal.s16  q5, d16, d4           \n"
           "vmlal.s16  q5, d18, d5           \n"
-          "vmull.s16  q6, d15, d3           \n"
+          "vld1.32    {d9}, [%[input_ptr5]] \n"
+          "vmlal.s16  q6, d15, d3           \n"
           "vmlal.s16  q6, d17, d4           \n"
           "vmlal.s16  q6, d19, d5           \n"
 
-          "vmull.s16  q14, d14, d6          \n"
-          "vmlal.s16  q14, d16, d7          \n"
-          "vmlal.s16  q14, d18, d8          \n"
-
-          "vld1.32    {d9}, [%[input_ptr5]], r0   \n"
-          "vmull.s16  q15, d15, d6          \n"
-          "vmlal.s16  q15, d17, d7          \n"
-          "vmlal.s16  q15, d19, d8          \n"
-
-          "vext.s8    d12, d9, #1           \n"
-          "vext.s8    d13, d9, #2           \n"
           "vmovl.s8   q7, d9                \n"
-          "vmovl.s8   q8, d12               \n"
-          "vmovl.s8   q9, d13               \n"
-          "vmull.s16  q5, d14, d6           \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
+          "vmlal.s16  q5, d14, d6           \n"
           "vmlal.s16  q5, d16, d7           \n"
           "vmlal.s16  q5, d18, d8           \n"
-          "vmull.s16  q6, d15, d6           \n"
+          "vmlal.s16  q6, d15, d6           \n"
           "vmlal.s16  q6, d17, d7           \n"
           "vmlal.s16  q6, d19, d8           \n"
 
@@ -372,7 +365,7 @@ void DepthwiseConv3x3s1_int8(const framework::Tensor &input,
           "blt        end_%=                      \n"
           "vst1.32    {d21[0]}, [%[output_ptr0]]! \n"
           "vst1.32    {d25[0]}, [%[output_ptr1]]! \n"
-          "vst1.32    {d27[0]}, [%[output_ptr2]]! \n"
+          "vst1.32    {d29[0]}, [%[output_ptr2]]! \n"
           "vst1.32    {d11[0]}, [%[output_ptr3]]! \n"
           "b          end_%=                      \n"
 
@@ -395,8 +388,1071 @@ void DepthwiseConv3x3s1_int8(const framework::Tensor &input,
     }
     // remain height
     int start_h = (input_h - 2) & 0xFFFC;
-    for (int h = start_h; h < input_h; ++h) {
-      // TODO(hjchen2)
+    for (int h = start_h; h < input_h - 3 /*(input_h - 2) - 1*/; h += 2) {
+      const int8_t* input_ptr0 = input_ptr + h * input_w;
+      const int8_t* input_ptr1 = input_ptr0 + input_w;
+      const int8_t* input_ptr2 = input_ptr1 + input_w;
+      const int8_t* input_ptr3 = input_ptr2 + input_w;
+      int32_t* output_ptr0 = output_ptr + h * output_w;
+      int32_t* output_ptr1 = output_ptr0 + output_w;
+      asm volatile(
+          "vld1.32    {q0}, [%[filter_ptr]] \n"
+          "vmovl.s8   q14, d0               \n"
+          "vmovl.s8   q15, d1               \n"
+          "vdup.s16   d0, d28[0]            \n"
+          "vdup.s16   d1, d28[1]            \n"
+          "vdup.s16   d2, d28[2]            \n"
+          "vdup.s16   d3, d28[3]            \n"
+          "vdup.s16   d4, d29[0]            \n"
+          "vdup.s16   d5, d29[1]            \n"
+          "vdup.s16   d6, d29[2]            \n"
+          "vdup.s16   d7, d29[3]            \n"
+          "vdup.s16   d8, d30[0]            \n"
+          :
+          : [filter_ptr] "r"(filter_ptr)
+          : "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q14", "q15");
+      asm volatile(
+          "mov        r0, #6                \n"
+          "cmp        %[loop], #0           \n"
+          "ble        start_remain_%=       \n"
+          // loop 6 widths
+          "loop_2h6w_%=:                          \n"
+          "vld1.32    {d9}, [%[input_ptr0]], r0   \n"
+          "vld1.32    {d10}, [%[input_ptr1]], r0  \n"
+          "vld1.32    {d11}, [%[input_ptr2]], r0  \n"
+          "vext.s8    d12, d9, d9, #1       \n"
+          "vext.s8    d13, d9, d9, #2       \n"
+          "vmovl.s8   q7, d9                \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmull.s16  q10, d14, d0          \n"
+          "vmlal.s16  q10, d16, d1          \n"
+          "vmlal.s16  q10, d18, d2          \n"
+          "vmull.s16  q11, d15, d0          \n"
+          "vmlal.s16  q11, d17, d1          \n"
+          "vmlal.s16  q11, d19, d2          \n"
+
+          "vext.s8    d12, d10, d10, #1     \n"
+          "vext.s8    d13, d10, d10, #2     \n"
+          "vmovl.s8   q7, d10               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d3          \n"
+          "vmlal.s16  q10, d16, d4          \n"
+          "vmlal.s16  q10, d18, d5          \n"
+          "vmlal.s16  q11, d15, d3          \n"
+          "vmlal.s16  q11, d17, d4          \n"
+          "vmlal.s16  q11, d19, d5          \n"
+
+          "vmull.s16  q12, d14, d0          \n"
+          "vmlal.s16  q12, d16, d1          \n"
+          "vmlal.s16  q12, d18, d2          \n"
+          "vmull.s16  q13, d15, d0          \n"
+          "vmlal.s16  q13, d17, d1          \n"
+          "vmlal.s16  q13, d19, d2          \n"
+
+          "vext.s8    d12, d11, d11, #1     \n"
+          "vext.s8    d13, d11, d11, #2     \n"
+          "vmovl.s8   q7, d11               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d6          \n"
+          "vmlal.s16  q10, d16, d7          \n"
+          "vmlal.s16  q10, d18, d8          \n"
+          "vmlal.s16  q11, d15, d6          \n"
+          "vmlal.s16  q11, d17, d7          \n"
+          "vmlal.s16  q11, d19, d8          \n"
+          // store row 0, reuse q10/q11
+          "vst1.32    {d20-d22}, [%[output_ptr0]]! \n"
+
+          "vmlal.s16  q12, d14, d3          \n"
+          "vmlal.s16  q12, d16, d4          \n"
+          "vmlal.s16  q12, d18, d5          \n"
+          "vmlal.s16  q13, d15, d3          \n"
+          "vmlal.s16  q13, d17, d4          \n"
+          "vmlal.s16  q13, d19, d5          \n"
+
+          "vld1.32    {d9}, [%[input_ptr3]], r0    \n"
+          "vext.s8    d12, d9, d9, #1       \n"
+          "vext.s8    d13, d9, d9, #2       \n"
+          "vmovl.s8   q7, d9                \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q12, d14, d6          \n"
+          "vmlal.s16  q12, d16, d7          \n"
+          "vmlal.s16  q12, d18, d8          \n"
+          "vmlal.s16  q13, d15, d6          \n"
+          "vmlal.s16  q13, d17, d7          \n"
+          "vmlal.s16  q13, d19, d8          \n"
+          // store row 1
+          "vst1.32    {d24-d26}, [%[output_ptr1]]! \n"
+
+          "subs       %[loop], #1            \n"
+          "bne        loop_2h6w_%=           \n"
+
+          "start_remain_%=:                  \n"
+          "cmp %[remain], #0                 \n"
+          "ble end_%=                        \n"
+
+          "vld1.32    {d9}, [%[input_ptr0]]  \n"
+          "vld1.32    {d10}, [%[input_ptr1]] \n"
+          "vld1.32    {d11}, [%[input_ptr2]] \n"
+          "vext.s8    d12, d9, d9, #1        \n"
+          "vext.s8    d13, d9, d9, #2        \n"
+          "vmovl.s8   q7, d9                 \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmull.s16  q10, d14, d0           \n"
+          "vmlal.s16  q10, d16, d1           \n"
+          "vmlal.s16  q10, d18, d2           \n"
+          "vmull.s16  q11, d15, d0           \n"
+          "vmlal.s16  q11, d17, d1           \n"
+          "vmlal.s16  q11, d19, d2           \n"
+
+          "vext.s8    d12, d10, d10, #1      \n"
+          "vext.s8    d13, d10, d10, #2      \n"
+          "vmovl.s8   q7, d10                \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmlal.s16  q10, d14, d3           \n"
+          "vmlal.s16  q10, d16, d4           \n"
+          "vmlal.s16  q10, d18, d5           \n"
+          "vmlal.s16  q11, d15, d3           \n"
+          "vmlal.s16  q11, d17, d4           \n"
+          "vmlal.s16  q11, d19, d5           \n"
+
+          "vmull.s16  q12, d14, d0           \n"
+          "vmlal.s16  q12, d16, d1           \n"
+          "vmlal.s16  q12, d18, d2           \n"
+          "vmull.s16  q13, d15, d0           \n"
+          "vmlal.s16  q13, d17, d1           \n"
+          "vmlal.s16  q13, d19, d2           \n"
+
+          "vext.s8    d12, d11, d11, #1      \n"
+          "vext.s8    d13, d11, d11, #2      \n"
+          "vmovl.s8   q7, d11                \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmlal.s16  q10, d14, d6           \n"
+          "vmlal.s16  q10, d16, d7           \n"
+          "vmlal.s16  q10, d18, d8           \n"
+          "vmlal.s16  q11, d15, d6           \n"
+          "vmlal.s16  q11, d17, d7           \n"
+          "vmlal.s16  q11, d19, d8           \n"
+
+          "vmlal.s16  q12, d14, d3           \n"
+          "vmlal.s16  q12, d16, d4           \n"
+          "vmlal.s16  q12, d18, d5           \n"
+          "vmlal.s16  q13, d15, d3           \n"
+          "vmlal.s16  q13, d17, d4           \n"
+          "vmlal.s16  q13, d19, d5           \n"
+
+          "vld1.32    {d9}, [%[input_ptr3]]  \n"
+          "vext.s8    d12, d9, d9, #1        \n"
+          "vext.s8    d13, d9, d9, #2        \n"
+          "vmovl.s8   q7, d9                 \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmlal.s16  q12, d14, d6           \n"
+          "vmlal.s16  q12, d16, d7           \n"
+          "vmlal.s16  q12, d18, d8           \n"
+          "vmlal.s16  q13, d15, d6           \n"
+          "vmlal.s16  q13, d17, d7           \n"
+          "vmlal.s16  q13, d19, d8           \n"
+
+          "cmp        %[remain], #4               \n"
+          "blt        store_2h2w_%=               \n"
+          "vst1.32    {q10}, [%[output_ptr0]]!    \n"
+          "vst1.32    {q12}, [%[output_ptr1]]!    \n"
+          "cmp        %[remain], #5               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d22[0]}, [%[output_ptr0]]! \n"
+          "vst1.32    {d26[0]}, [%[output_ptr1]]! \n"
+          "b          end_%=                      \n"
+
+          "store_2h2w_%=:                         \n"
+          "cmp        %[remain], #2               \n"
+          "blt        store_2h1w_%=               \n"
+          "vst1.32    {d20}, [%[output_ptr0]]!    \n"
+          "vst1.32    {d24}, [%[output_ptr1]]!    \n"
+          "cmp        %[remain], #3               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d21[0]}, [%[output_ptr0]]! \n"
+          "vst1.32    {d25[0]}, [%[output_ptr1]]! \n"
+          "b          end_%=                      \n"
+
+          "store_2h1w_%=:                         \n"
+          "cmp        %[remain], #1               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d20[0]}, [%[output_ptr0]]! \n"
+          "vst1.32    {d24[0]}, [%[output_ptr1]]! \n"
+          "end_%=:                                \n"
+          : [output_ptr0] "+r"(output_ptr0), [output_ptr1] "+r"(output_ptr1),
+            [input_ptr0] "+r"(input_ptr0), [input_ptr1] "+r"(input_ptr1),
+            [input_ptr2] "+r"(input_ptr2), [input_ptr3] "+r"(input_ptr3)
+          : [loop] "r"(loop), [remain] "r"(remain)
+          : "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8",
+            "q9", "q10", "q11", "q12", "q13", "r0");
+    }
+
+    start_h = (input_h - 2) & 0xFFFE;
+    if (start_h < input_h - 2) {
+      const int8_t* input_ptr0 = input_ptr + start_h * input_w;
+      const int8_t* input_ptr1 = input_ptr0 + input_w;
+      const int8_t* input_ptr2 = input_ptr1 + input_w;
+      int32_t* output_ptr0 = output_ptr + start_h * output_w;
+      asm volatile(
+          "vld1.32    {q0}, [%[filter_ptr]] \n"
+          "vmovl.s8   q14, d0               \n"
+          "vmovl.s8   q15, d1               \n"
+          "vdup.s16   d0, d28[0]            \n"
+          "vdup.s16   d1, d28[1]            \n"
+          "vdup.s16   d2, d28[2]            \n"
+          "vdup.s16   d3, d28[3]            \n"
+          "vdup.s16   d4, d29[0]            \n"
+          "vdup.s16   d5, d29[1]            \n"
+          "vdup.s16   d6, d29[2]            \n"
+          "vdup.s16   d7, d29[3]            \n"
+          "vdup.s16   d8, d30[0]            \n"
+          :
+          : [filter_ptr] "r"(filter_ptr)
+          : "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q14", "q15");
+      asm volatile(
+          "mov        r0, #6                \n"
+          "cmp        %[loop], #0           \n"
+          "ble        start_remain_%=       \n"
+          // loop 6 widths
+          "loop_1h6w_%=:                          \n"
+          "vld1.32    {d9}, [%[input_ptr0]], r0   \n"
+          "vld1.32    {d10}, [%[input_ptr1]], r0  \n"
+          "vld1.32    {d11}, [%[input_ptr2]], r0  \n"
+          "vext.s8    d12, d9, d9, #1       \n"
+          "vext.s8    d13, d9, d9, #2       \n"
+          "vmovl.s8   q7, d9                \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmull.s16  q10, d14, d0          \n"
+          "vmlal.s16  q10, d16, d1          \n"
+          "vmlal.s16  q10, d18, d2          \n"
+          "vmull.s16  q11, d15, d0          \n"
+          "vmlal.s16  q11, d17, d1          \n"
+          "vmlal.s16  q11, d19, d2          \n"
+
+          "vext.s8    d12, d10, d10, #1     \n"
+          "vext.s8    d13, d10, d10, #2     \n"
+          "vmovl.s8   q7, d10               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d3          \n"
+          "vmlal.s16  q10, d16, d4          \n"
+          "vmlal.s16  q10, d18, d5          \n"
+          "vmlal.s16  q11, d15, d3          \n"
+          "vmlal.s16  q11, d17, d4          \n"
+          "vmlal.s16  q11, d19, d5          \n"
+
+          "vext.s8    d12, d11, d11, #1     \n"
+          "vext.s8    d13, d11, d11, #2     \n"
+          "vmovl.s8   q7, d11               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d6          \n"
+          "vmlal.s16  q10, d16, d7          \n"
+          "vmlal.s16  q10, d18, d8          \n"
+          "vmlal.s16  q11, d15, d6          \n"
+          "vmlal.s16  q11, d17, d7          \n"
+          "vmlal.s16  q11, d19, d8          \n"
+          // store row 0, reuse q10/q11
+          "vst1.32    {d20-d22}, [%[output_ptr0]]! \n"
+
+          "subs       %[loop], #1            \n"
+          "bne        loop_1h6w_%=           \n"
+
+          "start_remain_%=:                  \n"
+          "cmp %[remain], #0                 \n"
+          "ble end_%=                        \n"
+
+          "vld1.32    {d9}, [%[input_ptr0]]  \n"
+          "vld1.32    {d10}, [%[input_ptr1]] \n"
+          "vld1.32    {d11}, [%[input_ptr2]] \n"
+          "vext.s8    d12, d9, d9, #1        \n"
+          "vext.s8    d13, d9, d9, #2        \n"
+          "vmovl.s8   q7, d9                 \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmull.s16  q10, d14, d0           \n"
+          "vmlal.s16  q10, d16, d1           \n"
+          "vmlal.s16  q10, d18, d2           \n"
+          "vmull.s16  q11, d15, d0           \n"
+          "vmlal.s16  q11, d17, d1           \n"
+          "vmlal.s16  q11, d19, d2           \n"
+
+          "vext.s8    d12, d10, d10, #1      \n"
+          "vext.s8    d13, d10, d10, #2      \n"
+          "vmovl.s8   q7, d10                \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmlal.s16  q10, d14, d3           \n"
+          "vmlal.s16  q10, d16, d4           \n"
+          "vmlal.s16  q10, d18, d5           \n"
+          "vmlal.s16  q11, d15, d3           \n"
+          "vmlal.s16  q11, d17, d4           \n"
+          "vmlal.s16  q11, d19, d5           \n"
+
+          "vext.s8    d12, d11, d11, #1      \n"
+          "vext.s8    d13, d11, d11, #2      \n"
+          "vmovl.s8   q7, d11                \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmlal.s16  q10, d14, d6           \n"
+          "vmlal.s16  q10, d16, d7           \n"
+          "vmlal.s16  q10, d18, d8           \n"
+          "vmlal.s16  q11, d15, d6           \n"
+          "vmlal.s16  q11, d17, d7           \n"
+          "vmlal.s16  q11, d19, d8           \n"
+
+          "cmp        %[remain], #4               \n"
+          "blt        store_1h2w_%=               \n"
+          "vst1.32    {q10}, [%[output_ptr0]]!    \n"
+          "cmp        %[remain], #5               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d22[0]}, [%[output_ptr0]]! \n"
+          "b          end_%=                      \n"
+
+          "store_1h2w_%=:                         \n"
+          "cmp        %[remain], #2               \n"
+          "blt        store_1h1w_%=               \n"
+          "vst1.32    {d20}, [%[output_ptr0]]!    \n"
+          "cmp        %[remain], #3               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d21[0]}, [%[output_ptr0]]! \n"
+          "b          end_%=                      \n"
+
+          "store_1h1w_%=:                         \n"
+          "cmp        %[remain], #1               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d20[0]}, [%[output_ptr0]]! \n"
+          "end_%=:                                \n"
+          : [output_ptr0] "+r"(output_ptr0), [input_ptr0] "+r"(input_ptr0),
+            [input_ptr1] "+r"(input_ptr1), [input_ptr2] "+r"(input_ptr2)
+          : [loop] "r"(loop), [remain] "r"(remain)
+          : "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8",
+            "q9", "q10", "q11", "r0");
+    }
+  }
+#endif  // __aarch64__
+}
+
+template <>
+void DepthwiseConv3x3s2<int8_t, int32_t>(const framework::Tensor &input,
+                                         const framework::Tensor &filter,
+                                         framework::Tensor *output) {
+  const int8_t *input_data = input.data<int8_t>();
+  const int8_t *filter_data = filter.data<int8_t>();
+  int32_t *out_data = output->mutable_data<int32_t>();
+  // make sure that batch size is 1
+  int input_c = input.dims()[1];
+  int input_h = input.dims()[2];
+  int input_w = input.dims()[3];
+  int output_c = output->dims()[1];
+  int output_h = output->dims()[2];
+  int output_w = output->dims()[3];
+  int image_size = input_h * input_w;
+  int out_image_size = output_h * output_w;
+#if __aarch64__
+  // TODO(hjchen2)
+#else
+  #pragma omp parallel for
+  for (int g = 0; g < input_c; ++g) {
+    const int8_t* input_ptr = input_data + g * image_size;
+    const int8_t* filter_ptr = filter_data + g * 9;
+    int32_t* output_ptr = out_data + g * out_image_size;
+    int loop = (input_w - 2) / 6;
+    int remain = input_w - 2 - loop * 6;
+    for (int h = 0; h < input_h - 5 /*(input_h - 2) - 3*/; h += 4) {
+      const int8_t* input_ptr0 = input_ptr + h * input_w;
+      const int8_t* input_ptr1 = input_ptr0 + input_w;
+      const int8_t* input_ptr2 = input_ptr1 + input_w;
+      const int8_t* input_ptr3 = input_ptr2 + input_w;
+      const int8_t* input_ptr4 = input_ptr3 + input_w;
+      const int8_t* input_ptr5 = input_ptr4 + input_w;
+      int32_t* output_ptr0 = output_ptr + h * output_w;
+      int32_t* output_ptr1 = output_ptr0 + output_w;
+      int32_t* output_ptr2 = output_ptr1 + output_w;
+      int32_t* output_ptr3 = output_ptr2 + output_w;
+      asm volatile(
+          "vld1.32    {q0}, [%[filter_ptr]] \n"
+          "vmovl.s8   q14, d0               \n"
+          "vmovl.s8   q15, d1               \n"
+          "vdup.s16   d0, d28[0]            \n"
+          "vdup.s16   d1, d28[1]            \n"
+          "vdup.s16   d2, d28[2]            \n"
+          "vdup.s16   d3, d28[3]            \n"
+          "vdup.s16   d4, d29[0]            \n"
+          "vdup.s16   d5, d29[1]            \n"
+          "vdup.s16   d6, d29[2]            \n"
+          "vdup.s16   d7, d29[3]            \n"
+          "vdup.s16   d8, d30[0]            \n"
+          :
+          : [filter_ptr] "r"(filter_ptr)
+          : "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q14", "q15");
+      asm volatile(
+          "mov        r0, #6                \n"
+          "cmp        %[loop], #0           \n"
+          "ble        start_remain_%=       \n"
+          // loop 6 widths
+          "loop_4h6w_%=:                          \n"
+          "vld1.32    {d9}, [%[input_ptr0]], r0   \n"
+          "vld1.32    {d10}, [%[input_ptr1]], r0  \n"
+          "vld1.32    {d11}, [%[input_ptr2]], r0  \n"
+          "vext.s8    d12, d9, d9, #1       \n"
+          "vext.s8    d13, d9, d9, #2       \n"
+          "vmovl.s8   q7, d9                \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmull.s16  q10, d14, d0          \n"
+          "vmlal.s16  q10, d16, d1          \n"
+          "vmlal.s16  q10, d18, d2          \n"
+          "vmull.s16  q11, d15, d0          \n"
+          "vmlal.s16  q11, d17, d1          \n"
+          "vmlal.s16  q11, d19, d2          \n"
+
+          "vext.s8    d12, d10, d10, #1     \n"
+          "vext.s8    d13, d10, d10, #2     \n"
+          "vmovl.s8   q7, d10               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d3          \n"
+          "vmlal.s16  q10, d16, d4          \n"
+          "vmlal.s16  q10, d18, d5          \n"
+          "vmlal.s16  q11, d15, d3          \n"
+          "vmlal.s16  q11, d17, d4          \n"
+          "vmlal.s16  q11, d19, d5          \n"
+
+          "vmull.s16  q12, d14, d0          \n"
+          "vmlal.s16  q12, d16, d1          \n"
+          "vmlal.s16  q12, d18, d2          \n"
+          "vmull.s16  q13, d15, d0          \n"
+          "vmlal.s16  q13, d17, d1          \n"
+          "vmlal.s16  q13, d19, d2          \n"
+
+          "vext.s8    d12, d11, d11, #1     \n"
+          "vext.s8    d13, d11, d11, #2     \n"
+          "vmovl.s8   q7, d11               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d6          \n"
+          "vmlal.s16  q10, d16, d7          \n"
+          "vmlal.s16  q10, d18, d8          \n"
+          "vmlal.s16  q11, d15, d6          \n"
+          "vmlal.s16  q11, d17, d7          \n"
+          "vmlal.s16  q11, d19, d8          \n"
+          // store row 0, reuse q10/q11
+          "vst1.32    {d20-d22}, [%[output_ptr0]]! \n"
+
+          "vmlal.s16  q12, d14, d3          \n"
+          "vmlal.s16  q12, d16, d4          \n"
+          "vmlal.s16  q12, d18, d5          \n"
+          "vmlal.s16  q13, d15, d3          \n"
+          "vmlal.s16  q13, d17, d4          \n"
+          "vmlal.s16  q13, d19, d5          \n"
+
+          "vmull.s16  q14, d14, d0          \n"
+          "vmlal.s16  q14, d16, d1          \n"
+          "vmlal.s16  q14, d18, d2          \n"
+          "vmull.s16  q15, d15, d0          \n"
+          "vmlal.s16  q15, d17, d1          \n"
+          "vmlal.s16  q15, d19, d2          \n"
+
+          "vld1.32    {d9}, [%[input_ptr3]], r0    \n"
+          "vld1.32    {d10}, [%[input_ptr4]], r0   \n"
+          "vld1.32    {d11}, [%[input_ptr5]], r0   \n"
+          "vext.s8    d12, d9, d9, #1       \n"
+          "vext.s8    d13, d9, d9, #2       \n"
+          "vmovl.s8   q7, d9                \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q12, d14, d6          \n"
+          "vmlal.s16  q12, d16, d7          \n"
+          "vmlal.s16  q12, d18, d8          \n"
+          "vmlal.s16  q13, d15, d6          \n"
+          "vmlal.s16  q13, d17, d7          \n"
+          "vmlal.s16  q13, d19, d8          \n"
+          // store row 1
+          "vst1.32    {d24-d26}, [%[output_ptr1]]! \n"
+
+          "vmlal.s16  q14, d14, d3          \n"
+          "vmlal.s16  q14, d16, d4          \n"
+          "vmlal.s16  q14, d18, d5          \n"
+          "vmlal.s16  q15, d15, d3          \n"
+          "vmlal.s16  q15, d17, d4          \n"
+          "vmlal.s16  q15, d19, d5          \n"
+
+          "vmull.s16  q10, d14, d0          \n"
+          "vmlal.s16  q10, d16, d1          \n"
+          "vmlal.s16  q10, d18, d2          \n"
+          "vmull.s16  q11, d15, d0          \n"
+          "vmlal.s16  q11, d17, d1          \n"
+          "vmlal.s16  q11, d19, d2          \n"
+
+          "vext.s8    d12, d10, d10, #1     \n"
+          "vext.s8    d13, d10, d10, #2     \n"
+          "vmovl.s8   q7, d10               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q14, d14, d6          \n"
+          "vmlal.s16  q14, d16, d7          \n"
+          "vmlal.s16  q14, d18, d8          \n"
+          "vmlal.s16  q15, d15, d6          \n"
+          "vmlal.s16  q15, d17, d7          \n"
+          "vmlal.s16  q15, d19, d8          \n"
+          // store row 2
+          "vst1.32    {d28-d30}, [%[output_ptr2]]! \n"
+
+          "vmlal.s16  q10, d14, d3          \n"
+          "vmlal.s16  q10, d16, d4          \n"
+          "vmlal.s16  q10, d18, d5          \n"
+          "vmlal.s16  q11, d15, d3          \n"
+          "vmlal.s16  q11, d17, d4          \n"
+          "vmlal.s16  q11, d19, d5          \n"
+
+          "vext.s8    d12, d11, d11, #1     \n"
+          "vext.s8    d13, d11, d11, #2     \n"
+          "vmovl.s8   q7, d11               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d6          \n"
+          "vmlal.s16  q10, d16, d7          \n"
+          "vmlal.s16  q10, d18, d8          \n"
+          "vmlal.s16  q11, d15, d6          \n"
+          "vmlal.s16  q11, d17, d7          \n"
+          "vmlal.s16  q11, d19, d8          \n"
+          // store row 3
+          "vst1.32    {d20-d22}, [%[output_ptr3]]! \n"
+
+          "subs       %[loop], #1           \n"
+          "bne        loop_4h6w_%=          \n"
+
+          "start_remain_%=:                 \n"
+          "cmp %[remain], #0                \n"
+          "ble end_%=                       \n"
+
+          "vld1.32    {d9}, [%[input_ptr0]] \n"
+          "vmovl.s8   q7, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
+          "vmull.s16  q10, d14, d0          \n"
+          "vmlal.s16  q10, d16, d1          \n"
+          "vmlal.s16  q10, d18, d2          \n"
+          "vld1.32    {d9}, [%[input_ptr1]] \n"
+          "vmull.s16  q11, d15, d0          \n"
+          "vmlal.s16  q11, d17, d1          \n"
+          "vmlal.s16  q11, d19, d2          \n"
+
+          "vmovl.s8   q7, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
+          "vmlal.s16  q10, d14, d3          \n"
+          "vmlal.s16  q10, d16, d4          \n"
+          "vmlal.s16  q10, d18, d5          \n"
+          "vmlal.s16  q11, d15, d3          \n"
+          "vmlal.s16  q11, d17, d4          \n"
+          "vmlal.s16  q11, d19, d5          \n"
+
+          "vmull.s16  q12, d14, d0          \n"
+          "vmlal.s16  q12, d16, d1          \n"
+          "vmlal.s16  q12, d18, d2          \n"
+          "vld1.32    {d9}, [%[input_ptr2]] \n"
+          "vmull.s16  q13, d15, d0          \n"
+          "vmlal.s16  q13, d17, d1          \n"
+          "vmlal.s16  q13, d19, d2          \n"
+
+          "vmovl.s8   q7, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
+          "vmlal.s16  q10, d14, d6          \n"
+          "vmlal.s16  q10, d16, d7          \n"
+          "vmlal.s16  q10, d18, d8          \n"
+          "vmlal.s16  q11, d15, d6          \n"
+          "vmlal.s16  q11, d17, d7          \n"
+          "vmlal.s16  q11, d19, d8          \n"
+
+          "vmlal.s16  q12, d14, d3          \n"
+          "vmlal.s16  q12, d16, d4          \n"
+          "vmlal.s16  q12, d18, d5          \n"
+          "vmlal.s16  q13, d15, d3          \n"
+          "vmlal.s16  q13, d17, d4          \n"
+          "vmlal.s16  q13, d19, d5          \n"
+
+          "vmull.s16  q14, d14, d0          \n"
+          "vmlal.s16  q14, d16, d1          \n"
+          "vmlal.s16  q14, d18, d2          \n"
+          "vld1.32    {d9}, [%[input_ptr3]] \n"
+          "vmull.s16  q15, d15, d0          \n"
+          "vmlal.s16  q15, d17, d1          \n"
+          "vmlal.s16  q15, d19, d2          \n"
+
+          "vmovl.s8   q7, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
+          "vmlal.s16  q12, d14, d6          \n"
+          "vmlal.s16  q12, d16, d7          \n"
+          "vmlal.s16  q12, d18, d8          \n"
+          "vmlal.s16  q13, d15, d6          \n"
+          "vmlal.s16  q13, d17, d7          \n"
+          "vmlal.s16  q13, d19, d8          \n"
+
+          "vmlal.s16  q14, d14, d3          \n"
+          "vmlal.s16  q14, d16, d4          \n"
+          "vmlal.s16  q14, d18, d5          \n"
+          "vmlal.s16  q15, d15, d3          \n"
+          "vmlal.s16  q15, d17, d4          \n"
+          "vmlal.s16  q15, d19, d5          \n"
+
+          "vmull.s16  q5, d14, d0           \n"
+          "vmlal.s16  q5, d16, d1           \n"
+          "vmlal.s16  q5, d18, d2           \n"
+          "vld1.32    {d9}, [%[input_ptr4]] \n"
+          "vmull.s16  q6, d15, d0           \n"
+          "vmlal.s16  q6, d17, d1           \n"
+          "vmlal.s16  q6, d19, d2           \n"
+
+          "vmovl.s8   q7, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
+          "vmlal.s16  q14, d14, d6          \n"
+          "vmlal.s16  q14, d16, d7          \n"
+          "vmlal.s16  q14, d18, d8          \n"
+          "vmlal.s16  q15, d15, d6          \n"
+          "vmlal.s16  q15, d17, d7          \n"
+          "vmlal.s16  q15, d19, d8          \n"
+
+          "vmlal.s16  q5, d14, d3           \n"
+          "vmlal.s16  q5, d16, d4           \n"
+          "vmlal.s16  q5, d18, d5           \n"
+          "vld1.32    {d9}, [%[input_ptr5]] \n"
+          "vmlal.s16  q6, d15, d3           \n"
+          "vmlal.s16  q6, d17, d4           \n"
+          "vmlal.s16  q6, d19, d5           \n"
+
+          "vmovl.s8   q7, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q8, d9                \n"
+          "vext.s8    d9, d9, d9, #1        \n"
+          "vmovl.s8   q9, d9                \n"
+          "vmlal.s16  q5, d14, d6           \n"
+          "vmlal.s16  q5, d16, d7           \n"
+          "vmlal.s16  q5, d18, d8           \n"
+          "vmlal.s16  q6, d15, d6           \n"
+          "vmlal.s16  q6, d17, d7           \n"
+          "vmlal.s16  q6, d19, d8           \n"
+
+          "cmp        %[remain], #4               \n"
+          "blt        store_4h2w_%=               \n"
+          "vst1.32    {q10}, [%[output_ptr0]]!    \n"
+          "vst1.32    {q12}, [%[output_ptr1]]!    \n"
+          "vst1.32    {q14}, [%[output_ptr2]]!    \n"
+          "vst1.32    {q5}, [%[output_ptr3]]!     \n"
+          "cmp        %[remain], #5               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d22[0]}, [%[output_ptr0]]! \n"
+          "vst1.32    {d26[0]}, [%[output_ptr1]]! \n"
+          "vst1.32    {d30[0]}, [%[output_ptr2]]! \n"
+          "vst1.32    {d12[0]}, [%[output_ptr3]]! \n"
+          "b          end_%=                      \n"
+
+          "store_4h2w_%=:                         \n"
+          "cmp        %[remain], #2               \n"
+          "blt        store_4h1w_%=               \n"
+          "vst1.32    {d20}, [%[output_ptr0]]!    \n"
+          "vst1.32    {d24}, [%[output_ptr1]]!    \n"
+          "vst1.32    {d28}, [%[output_ptr2]]!    \n"
+          "vst1.32    {d10}, [%[output_ptr3]]!    \n"
+          "cmp        %[remain], #3               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d21[0]}, [%[output_ptr0]]! \n"
+          "vst1.32    {d25[0]}, [%[output_ptr1]]! \n"
+          "vst1.32    {d29[0]}, [%[output_ptr2]]! \n"
+          "vst1.32    {d11[0]}, [%[output_ptr3]]! \n"
+          "b          end_%=                      \n"
+
+          "store_4h1w_%=:                         \n"
+          "cmp        %[remain], #1               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d20[0]}, [%[output_ptr0]]! \n"
+          "vst1.32    {d24[0]}, [%[output_ptr1]]! \n"
+          "vst1.32    {d28[0]}, [%[output_ptr2]]! \n"
+          "vst1.32    {d10[0]}, [%[output_ptr3]]! \n"
+          "end_%=:                                \n"
+          : [output_ptr0] "+r"(output_ptr0), [output_ptr1] "+r"(output_ptr1),
+            [output_ptr2] "+r"(output_ptr2), [output_ptr3] "+r"(output_ptr3),
+            [input_ptr0] "+r"(input_ptr0), [input_ptr1] "+r"(input_ptr1),
+            [input_ptr2] "+r"(input_ptr2), [input_ptr3] "+r"(input_ptr3),
+            [input_ptr4] "+r"(input_ptr4), [input_ptr5] "+r"(input_ptr5)
+          : [loop] "r"(loop), [remain] "r"(remain)
+          : "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8",
+            "q9", "q10", "q11", "q12", "q13", "q14", "q15", "r0");
+    }
+    // remain height
+    int start_h = (input_h - 2) & 0xFFFC;
+    for (int h = start_h; h < input_h - 3 /*(input_h - 2) - 1*/; h += 2) {
+      const int8_t* input_ptr0 = input_ptr + h * input_w;
+      const int8_t* input_ptr1 = input_ptr0 + input_w;
+      const int8_t* input_ptr2 = input_ptr1 + input_w;
+      const int8_t* input_ptr3 = input_ptr2 + input_w;
+      int32_t* output_ptr0 = output_ptr + h * output_w;
+      int32_t* output_ptr1 = output_ptr0 + output_w;
+      asm volatile(
+          "vld1.32    {q0}, [%[filter_ptr]] \n"
+          "vmovl.s8   q14, d0               \n"
+          "vmovl.s8   q15, d1               \n"
+          "vdup.s16   d0, d28[0]            \n"
+          "vdup.s16   d1, d28[1]            \n"
+          "vdup.s16   d2, d28[2]            \n"
+          "vdup.s16   d3, d28[3]            \n"
+          "vdup.s16   d4, d29[0]            \n"
+          "vdup.s16   d5, d29[1]            \n"
+          "vdup.s16   d6, d29[2]            \n"
+          "vdup.s16   d7, d29[3]            \n"
+          "vdup.s16   d8, d30[0]            \n"
+          :
+          : [filter_ptr] "r"(filter_ptr)
+          : "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q14", "q15");
+      asm volatile(
+          "mov        r0, #6                \n"
+          "cmp        %[loop], #0           \n"
+          "ble        start_remain_%=       \n"
+          // loop 6 widths
+          "loop_2h6w_%=:                          \n"
+          "vld1.32    {d9}, [%[input_ptr0]], r0   \n"
+          "vld1.32    {d10}, [%[input_ptr1]], r0  \n"
+          "vld1.32    {d11}, [%[input_ptr2]], r0  \n"
+          "vext.s8    d12, d9, d9, #1       \n"
+          "vext.s8    d13, d9, d9, #2       \n"
+          "vmovl.s8   q7, d9                \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmull.s16  q10, d14, d0          \n"
+          "vmlal.s16  q10, d16, d1          \n"
+          "vmlal.s16  q10, d18, d2          \n"
+          "vmull.s16  q11, d15, d0          \n"
+          "vmlal.s16  q11, d17, d1          \n"
+          "vmlal.s16  q11, d19, d2          \n"
+
+          "vext.s8    d12, d10, d10, #1     \n"
+          "vext.s8    d13, d10, d10, #2     \n"
+          "vmovl.s8   q7, d10               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d3          \n"
+          "vmlal.s16  q10, d16, d4          \n"
+          "vmlal.s16  q10, d18, d5          \n"
+          "vmlal.s16  q11, d15, d3          \n"
+          "vmlal.s16  q11, d17, d4          \n"
+          "vmlal.s16  q11, d19, d5          \n"
+
+          "vmull.s16  q12, d14, d0          \n"
+          "vmlal.s16  q12, d16, d1          \n"
+          "vmlal.s16  q12, d18, d2          \n"
+          "vmull.s16  q13, d15, d0          \n"
+          "vmlal.s16  q13, d17, d1          \n"
+          "vmlal.s16  q13, d19, d2          \n"
+
+          "vext.s8    d12, d11, d11, #1     \n"
+          "vext.s8    d13, d11, d11, #2     \n"
+          "vmovl.s8   q7, d11               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d6          \n"
+          "vmlal.s16  q10, d16, d7          \n"
+          "vmlal.s16  q10, d18, d8          \n"
+          "vmlal.s16  q11, d15, d6          \n"
+          "vmlal.s16  q11, d17, d7          \n"
+          "vmlal.s16  q11, d19, d8          \n"
+          // store row 0, reuse q10/q11
+          "vst1.32    {d20-d22}, [%[output_ptr0]]! \n"
+
+          "vmlal.s16  q12, d14, d3          \n"
+          "vmlal.s16  q12, d16, d4          \n"
+          "vmlal.s16  q12, d18, d5          \n"
+          "vmlal.s16  q13, d15, d3          \n"
+          "vmlal.s16  q13, d17, d4          \n"
+          "vmlal.s16  q13, d19, d5          \n"
+
+          "vld1.32    {d9}, [%[input_ptr3]], r0    \n"
+          "vext.s8    d12, d9, d9, #1       \n"
+          "vext.s8    d13, d9, d9, #2       \n"
+          "vmovl.s8   q7, d9                \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q12, d14, d6          \n"
+          "vmlal.s16  q12, d16, d7          \n"
+          "vmlal.s16  q12, d18, d8          \n"
+          "vmlal.s16  q13, d15, d6          \n"
+          "vmlal.s16  q13, d17, d7          \n"
+          "vmlal.s16  q13, d19, d8          \n"
+          // store row 1
+          "vst1.32    {d24-d26}, [%[output_ptr1]]! \n"
+
+          "subs       %[loop], #1            \n"
+          "bne        loop_2h6w_%=           \n"
+
+          "start_remain_%=:                  \n"
+          "cmp %[remain], #0                 \n"
+          "ble end_%=                        \n"
+
+          "vld1.32    {d9}, [%[input_ptr0]]  \n"
+          "vld1.32    {d10}, [%[input_ptr1]] \n"
+          "vld1.32    {d11}, [%[input_ptr2]] \n"
+          "vext.s8    d12, d9, d9, #1        \n"
+          "vext.s8    d13, d9, d9, #2        \n"
+          "vmovl.s8   q7, d9                 \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmull.s16  q10, d14, d0           \n"
+          "vmlal.s16  q10, d16, d1           \n"
+          "vmlal.s16  q10, d18, d2           \n"
+          "vmull.s16  q11, d15, d0           \n"
+          "vmlal.s16  q11, d17, d1           \n"
+          "vmlal.s16  q11, d19, d2           \n"
+
+          "vext.s8    d12, d10, d10, #1      \n"
+          "vext.s8    d13, d10, d10, #2      \n"
+          "vmovl.s8   q7, d10                \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmlal.s16  q10, d14, d3           \n"
+          "vmlal.s16  q10, d16, d4           \n"
+          "vmlal.s16  q10, d18, d5           \n"
+          "vmlal.s16  q11, d15, d3           \n"
+          "vmlal.s16  q11, d17, d4           \n"
+          "vmlal.s16  q11, d19, d5           \n"
+
+          "vmull.s16  q12, d14, d0           \n"
+          "vmlal.s16  q12, d16, d1           \n"
+          "vmlal.s16  q12, d18, d2           \n"
+          "vmull.s16  q13, d15, d0           \n"
+          "vmlal.s16  q13, d17, d1           \n"
+          "vmlal.s16  q13, d19, d2           \n"
+
+          "vext.s8    d12, d11, d11, #1      \n"
+          "vext.s8    d13, d11, d11, #2      \n"
+          "vmovl.s8   q7, d11                \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmlal.s16  q10, d14, d6           \n"
+          "vmlal.s16  q10, d16, d7           \n"
+          "vmlal.s16  q10, d18, d8           \n"
+          "vmlal.s16  q11, d15, d6           \n"
+          "vmlal.s16  q11, d17, d7           \n"
+          "vmlal.s16  q11, d19, d8           \n"
+
+          "vmlal.s16  q12, d14, d3           \n"
+          "vmlal.s16  q12, d16, d4           \n"
+          "vmlal.s16  q12, d18, d5           \n"
+          "vmlal.s16  q13, d15, d3           \n"
+          "vmlal.s16  q13, d17, d4           \n"
+          "vmlal.s16  q13, d19, d5           \n"
+
+          "vld1.32    {d9}, [%[input_ptr3]]  \n"
+          "vext.s8    d12, d9, d9, #1        \n"
+          "vext.s8    d13, d9, d9, #2        \n"
+          "vmovl.s8   q7, d9                 \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmlal.s16  q12, d14, d6           \n"
+          "vmlal.s16  q12, d16, d7           \n"
+          "vmlal.s16  q12, d18, d8           \n"
+          "vmlal.s16  q13, d15, d6           \n"
+          "vmlal.s16  q13, d17, d7           \n"
+          "vmlal.s16  q13, d19, d8           \n"
+
+          "cmp        %[remain], #4               \n"
+          "blt        store_2h2w_%=               \n"
+          "vst1.32    {q10}, [%[output_ptr0]]!    \n"
+          "vst1.32    {q12}, [%[output_ptr1]]!    \n"
+          "cmp        %[remain], #5               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d22[0]}, [%[output_ptr0]]! \n"
+          "vst1.32    {d26[0]}, [%[output_ptr1]]! \n"
+          "b          end_%=                      \n"
+
+          "store_2h2w_%=:                         \n"
+          "cmp        %[remain], #2               \n"
+          "blt        store_2h1w_%=               \n"
+          "vst1.32    {d20}, [%[output_ptr0]]!    \n"
+          "vst1.32    {d24}, [%[output_ptr1]]!    \n"
+          "cmp        %[remain], #3               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d21[0]}, [%[output_ptr0]]! \n"
+          "vst1.32    {d25[0]}, [%[output_ptr1]]! \n"
+          "b          end_%=                      \n"
+
+          "store_2h1w_%=:                         \n"
+          "cmp        %[remain], #1               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d20[0]}, [%[output_ptr0]]! \n"
+          "vst1.32    {d24[0]}, [%[output_ptr1]]! \n"
+          "end_%=:                                \n"
+          : [output_ptr0] "+r"(output_ptr0), [output_ptr1] "+r"(output_ptr1),
+            [input_ptr0] "+r"(input_ptr0), [input_ptr1] "+r"(input_ptr1),
+            [input_ptr2] "+r"(input_ptr2), [input_ptr3] "+r"(input_ptr3)
+          : [loop] "r"(loop), [remain] "r"(remain)
+          : "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8",
+            "q9", "q10", "q11", "q12", "q13", "r0");
+    }
+
+    start_h = (input_h - 2) & 0xFFFE;
+    if (start_h < input_h - 2) {
+      const int8_t* input_ptr0 = input_ptr + start_h * input_w;
+      const int8_t* input_ptr1 = input_ptr0 + input_w;
+      const int8_t* input_ptr2 = input_ptr1 + input_w;
+      int32_t* output_ptr0 = output_ptr + start_h * output_w;
+      asm volatile(
+          "vld1.32    {q0}, [%[filter_ptr]] \n"
+          "vmovl.s8   q14, d0               \n"
+          "vmovl.s8   q15, d1               \n"
+          "vdup.s16   d0, d28[0]            \n"
+          "vdup.s16   d1, d28[1]            \n"
+          "vdup.s16   d2, d28[2]            \n"
+          "vdup.s16   d3, d28[3]            \n"
+          "vdup.s16   d4, d29[0]            \n"
+          "vdup.s16   d5, d29[1]            \n"
+          "vdup.s16   d6, d29[2]            \n"
+          "vdup.s16   d7, d29[3]            \n"
+          "vdup.s16   d8, d30[0]            \n"
+          :
+          : [filter_ptr] "r"(filter_ptr)
+          : "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q14", "q15");
+      asm volatile(
+          "mov        r0, #6                \n"
+          "cmp        %[loop], #0           \n"
+          "ble        start_remain_%=       \n"
+          // loop 6 widths
+          "loop_1h6w_%=:                          \n"
+          "vld1.32    {d9}, [%[input_ptr0]], r0   \n"
+          "vld1.32    {d10}, [%[input_ptr1]], r0  \n"
+          "vld1.32    {d11}, [%[input_ptr2]], r0  \n"
+          "vext.s8    d12, d9, d9, #1       \n"
+          "vext.s8    d13, d9, d9, #2       \n"
+          "vmovl.s8   q7, d9                \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmull.s16  q10, d14, d0          \n"
+          "vmlal.s16  q10, d16, d1          \n"
+          "vmlal.s16  q10, d18, d2          \n"
+          "vmull.s16  q11, d15, d0          \n"
+          "vmlal.s16  q11, d17, d1          \n"
+          "vmlal.s16  q11, d19, d2          \n"
+
+          "vext.s8    d12, d10, d10, #1     \n"
+          "vext.s8    d13, d10, d10, #2     \n"
+          "vmovl.s8   q7, d10               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d3          \n"
+          "vmlal.s16  q10, d16, d4          \n"
+          "vmlal.s16  q10, d18, d5          \n"
+          "vmlal.s16  q11, d15, d3          \n"
+          "vmlal.s16  q11, d17, d4          \n"
+          "vmlal.s16  q11, d19, d5          \n"
+
+          "vext.s8    d12, d11, d11, #1     \n"
+          "vext.s8    d13, d11, d11, #2     \n"
+          "vmovl.s8   q7, d11               \n"
+          "vmovl.s8   q8, d12               \n"
+          "vmovl.s8   q9, d13               \n"
+          "vmlal.s16  q10, d14, d6          \n"
+          "vmlal.s16  q10, d16, d7          \n"
+          "vmlal.s16  q10, d18, d8          \n"
+          "vmlal.s16  q11, d15, d6          \n"
+          "vmlal.s16  q11, d17, d7          \n"
+          "vmlal.s16  q11, d19, d8          \n"
+          // store row 0, reuse q10/q11
+          "vst1.32    {d20-d22}, [%[output_ptr0]]! \n"
+
+          "subs       %[loop], #1            \n"
+          "bne        loop_1h6w_%=           \n"
+
+          "start_remain_%=:                  \n"
+          "cmp %[remain], #0                 \n"
+          "ble end_%=                        \n"
+
+          "vld1.32    {d9}, [%[input_ptr0]]  \n"
+          "vld1.32    {d10}, [%[input_ptr1]] \n"
+          "vld1.32    {d11}, [%[input_ptr2]] \n"
+          "vext.s8    d12, d9, d9, #1        \n"
+          "vext.s8    d13, d9, d9, #2        \n"
+          "vmovl.s8   q7, d9                 \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmull.s16  q10, d14, d0           \n"
+          "vmlal.s16  q10, d16, d1           \n"
+          "vmlal.s16  q10, d18, d2           \n"
+          "vmull.s16  q11, d15, d0           \n"
+          "vmlal.s16  q11, d17, d1           \n"
+          "vmlal.s16  q11, d19, d2           \n"
+
+          "vext.s8    d12, d10, d10, #1      \n"
+          "vext.s8    d13, d10, d10, #2      \n"
+          "vmovl.s8   q7, d10                \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmlal.s16  q10, d14, d3           \n"
+          "vmlal.s16  q10, d16, d4           \n"
+          "vmlal.s16  q10, d18, d5           \n"
+          "vmlal.s16  q11, d15, d3           \n"
+          "vmlal.s16  q11, d17, d4           \n"
+          "vmlal.s16  q11, d19, d5           \n"
+
+          "vext.s8    d12, d11, d11, #1      \n"
+          "vext.s8    d13, d11, d11, #2      \n"
+          "vmovl.s8   q7, d11                \n"
+          "vmovl.s8   q8, d12                \n"
+          "vmovl.s8   q9, d13                \n"
+          "vmlal.s16  q10, d14, d6           \n"
+          "vmlal.s16  q10, d16, d7           \n"
+          "vmlal.s16  q10, d18, d8           \n"
+          "vmlal.s16  q11, d15, d6           \n"
+          "vmlal.s16  q11, d17, d7           \n"
+          "vmlal.s16  q11, d19, d8           \n"
+
+          "cmp        %[remain], #4               \n"
+          "blt        store_1h2w_%=               \n"
+          "vst1.32    {q10}, [%[output_ptr0]]!    \n"
+          "cmp        %[remain], #5               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d22[0]}, [%[output_ptr0]]! \n"
+          "b          end_%=                      \n"
+
+          "store_1h2w_%=:                         \n"
+          "cmp        %[remain], #2               \n"
+          "blt        store_1h1w_%=               \n"
+          "vst1.32    {d20}, [%[output_ptr0]]!    \n"
+          "cmp        %[remain], #3               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d21[0]}, [%[output_ptr0]]! \n"
+          "b          end_%=                      \n"
+
+          "store_1h1w_%=:                         \n"
+          "cmp        %[remain], #1               \n"
+          "blt        end_%=                      \n"
+          "vst1.32    {d20[0]}, [%[output_ptr0]]! \n"
+          "end_%=:                                \n"
+          : [output_ptr0] "+r"(output_ptr0), [input_ptr0] "+r"(input_ptr0),
+            [input_ptr1] "+r"(input_ptr1), [input_ptr2] "+r"(input_ptr2)
+          : [loop] "r"(loop), [remain] "r"(remain)
+          : "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8",
+            "q9", "q10", "q11", "r0");
     }
   }
 #endif  // __aarch64__

src/operators/math/depthwise_conv3x3_int8.h

-/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#pragma once
-
-#include <vector>
-#include "framework/tensor.h"
-
-namespace paddle_mobile {
-namespace operators {
-namespace math {
-
-void DepthwiseConv3x3_int8(const framework::Tensor *input,
-                           const framework::Tensor *filter,
-                           const std::vector<int> &strides,
-                           framework::Tensor *output);
-
-void DepthwiseConv3x3s1_int8(const framework::Tensor *input,
-                             const framework::Tensor *filter,
-                             framework::Tensor *output);
-
-void DepthwiseConv3x3s2_int8(const framework::Tensor *input,
-                             const framework::Tensor *filter,
-                             framework::Tensor *output);
-
-}  // namespace math
-}  // namespace operators
-}  // namespace paddle_mobile

src/operators/math/depthwise_conv_3x3.h

-/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#pragma once
-
-#include <algorithm>
-#include <vector>
-#include "framework/tensor.h"
-#include "operators/math/conv_func.h"
-
-namespace paddle_mobile {
-namespace operators {
-namespace math {
-using framework::Tensor;
-using std::max;
-using std::min;
-using std::vector;
-
-void DepthwiseConv3x3(const Tensor *input, vector<int> strides,
-                      vector<int> paddings, const Tensor *filter, Tensor *bias,
-                      Tensor *output, bool if_bias);
-void DepthwiseConv3x3s1p1(const Tensor *input, const Tensor *filter,
-                          Tensor *output, Tensor *bias, bool if_bias);
-void DepthwiseConvAddBNRelu3x3s1p1(const Tensor *input, const Tensor *filter,
-                                   Tensor *output, const Tensor *new_scale,
-                                   const Tensor *new_bias, bool if_relu);
-void DepthwiseConvAddBNRelu3x3s2p1(const Tensor *input, const Tensor *filter,
-                                   Tensor *output, const Tensor *new_scale,
-                                   const Tensor *new_bias, bool if_relu);
-void DepthwiseConv3x3s2p1v2(const Tensor *input, const Tensor *filter,
-                            Tensor *output, Tensor bias, bool if_bias);
-void DepthwiseConvAddBNRelu3x3s2p1v2(const Tensor *input, const Tensor *filter,
-                                     Tensor *output, const Tensor *new_scale,
-                                     const Tensor *new_bias, bool if_relu);
-
-void DepthwiseConv3x3s2p0(const Tensor *input, const Tensor *filter,
-                          Tensor *output, Tensor bias, bool if_bias);
-}  // namespace math
-}  // namespace operators
-}  // namespace paddle_mobile

src/operators/math/gemm.cpp

@@ -26,79 +26,6 @@ limitations under the License. */
 namespace paddle_mobile {
 namespace operators {
 namespace math {
-/*int MC = 0;
-int KC = 0;
-int NC = 0;
-
-float *packedA;
-float *packedB;
-float *packedC;
-float *zero;
-
-typedef void (*FnPack)(int, int, int, const float *, int, float *);
-typedef void (*FnAddDot)(int, const float *, const float *, float *, int);
-
-FnPack procPackA;
-FnPack procPackB;
-FnAddDot procAddDot;*/
-
-/*
-// 将A矩阵分块复制到连续内存(ColMajor)
-void PackMatrixA(int m, int k, int m_tail, const float *A, int lda,
-                 float *buffer) {
-  int i, j;
-  const float *Aij;
-  for (i = 0; i < m - m_tail; i += MR) {
-    for (j = 0; j < k; ++j) {
-      Aij = &A(i, j);
-      *buffer++ = *Aij;
-      *buffer++ = *(Aij + 1);
-      *buffer++ = *(Aij + 2);
-      *buffer++ = *(Aij + 3);
-    }
-  }
-  if (m_tail != 0) {
-    for (j = 0; j < k; ++j) {
-      Aij = &A(m - m_tail, j);
-      for (i = 0; i < m_tail; ++i) {
-        *buffer++ = *(Aij + i);
-      }
-      for (i = m_tail; i < MR; ++i) {
-        *buffer++ = 0;
-      }
-    }
-  }
-}
-
-// 将B矩阵分块复制到连续内存(ColMajor)
-void PackMatrixB(int k, int n, int n_tail, const float *B, int ldb,
-                 float *buffer) {
-  int i, j;
-  const float *Bj, *Bj1, *Bj2, *Bj3;
-  for (j = 0; j < n - n_tail; j += NR) {
-    Bj = &B(0, j);
-    Bj1 = &B(0, j + 1);
-    Bj2 = &B(0, j + 2);
-    Bj3 = &B(0, j + 3);
-    for (i = 0; i < k; ++i) {
-      *buffer++ = *Bj++;
-      *buffer++ = *Bj1++;
-      *buffer++ = *Bj2++;
-      *buffer++ = *Bj3++;
-    }
-  }
-  if (n_tail != 0) {
-    for (i = 0; i < k; ++i) {
-      for (int j = n - n_tail; j < n; ++j) {
-        *buffer++ = B(i, j);
-      }
-      for (int j = n; j < n + (NR - n_tail); ++j) {
-        *buffer++ = 0;
-      }
-    }
-  }
-}
-*/
 
 // 将A矩阵分块复制到连续内存(RowMajor)
 void Gemm::PackMatrixA_4r(int m, int k, int m_tail, const float *A, int lda,

src/operators/op_param.h

@@ -423,6 +423,7 @@ class ConvParam : public OpParam {
     EXEC_WINOGRAD3X3_FLOAT,
     EXEC_WINOGRAD5X5_FLOAT,
     EXEC_GEMM_INT8,
+    EXEC_DEPTHWISE3x3_INT8,
   };
 
   ExecMode &ExecMode() const { return exec_mode_; }
@@ -2498,7 +2499,7 @@ class QuantizeParam : public OpParam {
   QuantizeParam(const VariableNameMap &inputs, const VariableNameMap &outputs,
                 const AttributeMap &attrs, const Scope &scope) {
     input_ = InputXFrom<GType>(inputs, scope);
-    out_ = OutFrom<GType>(outputs, scope);
+    output_ = OutFrom<GType>(outputs, scope);
     // online
     // scale = max(abs(x))
     online_scale_ = GetVarValue<GType>("OutScale", outputs, scope);
@@ -2517,8 +2518,7 @@ class QuantizeParam : public OpParam {
   // op input
   RType *input_;
   // op output
-  RType *out_;
-  //
+  RType *output_;
   RType *online_scale_;
   // if static scale or not
   bool is_static_ = false;
@@ -2526,7 +2526,11 @@ class QuantizeParam : public OpParam {
   float static_scale_ = 1.0f;
   // round method type
   // nearest_zero and nearest_even is valid currently
-  RoundType round_type_ = ROUND_NEAREST_AWAY_ZERO;
+  // RoundType round_type_ = ROUND_NEAREST_AWAY_ZERO;
+  RoundType round_type_ = ROUND_NEAREST_TOWARDS_ZERO;
+  // optional paddings
+  std::vector<int> paddings_;
+  int8_t padding_val_;
 };
 #endif
 
@@ -2540,7 +2544,7 @@ class DequantizeParam : public OpParam {
   DequantizeParam(const VariableNameMap &inputs, const VariableNameMap &outputs,
                   const AttributeMap &attrs, const Scope &scope) {
     input_ = InputXFrom<GType>(inputs, scope);
-    out_ = OutFrom<GType>(outputs, scope);
+    output_ = OutFrom<GType>(outputs, scope);
     activation_scale_ = GetVarValue<GType>("Scale", inputs, scope);
     // dequantization is performed as x = x / static_scale / online_scale
     if (HasAttr("weight_scale", attrs)) {
@@ -2554,11 +2558,32 @@ class DequantizeParam : public OpParam {
   // op input
   RType *input_;
   // op output
-  RType *out_;
+  RType *output_;
   RType *activation_scale_;
   float weight_scale_;
 };
 #endif
 
+#ifdef PAD_OP
+template <typename Dtype>
+class PadParam : public OpParam {
+  typedef typename DtypeTensorTrait<Dtype>::gtype GType;
+  typedef typename DtypeTensorTrait<Dtype>::rtype RType;
+
+ public:
+  input_ = InputXFrom<GType>(inputs, scope);
+  output_ = OutFrom<GType>(outputs, scope);
+  paddings_ = GetVarValue<std::vector<int>>("Paddings", inputs, scope);
+
+ public:
+  // op input
+  RType *input_;
+  // op output
+  RType *output_;
+  // paddings
+  std::vector<int> paddings_;
+};
+#endif
+
 }  // namespace operators
 }  // namespace paddle_mobile

src/operators/quantize_op.cpp

@@ -22,8 +22,12 @@ namespace operators {
 
 template <typename DeviceType, typename T>
 void QuantizeOp<DeviceType, T>::InferShape() const {
-  const auto& input_dims = this->param_.input_->dims();
-  this->param_.out_->Resize(input_dims);
+  auto input_dims = this->param_.input_->dims();
+  //  const auto &paddings = this->param_.paddings_;
+  std::vector<int> paddings = {0, 0};
+  input_dims[2] += 2 * paddings[0];
+  input_dims[3] += 2 * paddings[1];
+  this->param_.output_->Resize(input_dims);
   auto scale_dims = framework::make_ddim(std::vector<int>{1});
   this->param_.online_scale_->Resize(scale_dims);
 }