add elementwise_add kernel and unit test (#17825)

* add elementwise_add kernel
test=develop

* add elementwise_add unit test
test=develop

* enable arm neon
test=develop

* remove Repetitive funcs
test=develop

paddle/fluid/lite/arm/math/CMakeLists.txt

@@ -6,4 +6,4 @@ if(NOT (LITE_WITH_LIGHT_WEIGHT_FRAMEWORK AND LITE_WITH_ARM))
   return()
 endif()
 
-cc_library(math_arm SRCS funcs.cc packed_sgemm.cc softmax.cc scale.cc DEPS ${lite_kernel_deps} eigen3)
+cc_library(math_arm SRCS funcs.cc packed_sgemm.cc softmax.cc scale.cc elementwise.cc DEPS ${lite_kernel_deps} eigen3)

paddle/fluid/lite/arm/math/elementwise.cc

+// Copyright (c) 2019 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.
+
+#include "paddle/fluid/lite/arm/math/elementwise.h"
+#include "paddle/fluid/lite/arm/math/funcs.h"
+
+namespace paddle {
+namespace lite {
+namespace arm {
+namespace math {
+
+template <>
+void elementwise_add<float>(const float* dinx, const float* diny, float* dout,
+                            int num) {
+  int cnt = num >> 4;
+  int remain = num % 16;
+#pragma omp parallel for
+  for (int i = 0; i < cnt; i++) {
+    const float* dinx_ptr = dinx + (i << 4);
+    const float* diny_ptr = diny + (i << 4);
+    float* dout_ptr = dout + (i << 4);
+
+    float32x4_t dinx0 = vld1q_f32(dinx_ptr);
+    float32x4_t dinx1 = vld1q_f32(dinx_ptr + 4);
+    float32x4_t dinx2 = vld1q_f32(dinx_ptr + 8);
+    float32x4_t dinx3 = vld1q_f32(dinx_ptr + 12);
+
+    float32x4_t diny0 = vld1q_f32(diny_ptr);
+    float32x4_t diny1 = vld1q_f32(diny_ptr + 4);
+    float32x4_t diny2 = vld1q_f32(diny_ptr + 8);
+    float32x4_t diny3 = vld1q_f32(diny_ptr + 12);
+
+    float32x4_t vsum0 = vaddq_f32(dinx0, diny0);
+    float32x4_t vsum1 = vaddq_f32(dinx1, diny1);
+    float32x4_t vsum2 = vaddq_f32(dinx2, diny2);
+    float32x4_t vsum3 = vaddq_f32(dinx3, diny3);
+
+    vst1q_f32(dout_ptr, vsum0);
+    vst1q_f32(dout_ptr + 4, vsum1);
+    vst1q_f32(dout_ptr + 8, vsum2);
+    vst1q_f32(dout_ptr + 12, vsum3);
+  }
+  if (remain > 0) {
+    const float* dinx_ptr = dinx + (cnt << 4);
+    const float* diny_ptr = diny + (cnt << 4);
+    float* dout_ptr = dout + (cnt << 4);
+    for (int i = 0; i < remain; i++) {
+      *dout_ptr = *dinx_ptr + *diny_ptr;
+      dout_ptr++;
+      dinx_ptr++;
+      diny_ptr++;
+    }
+  }
+}
+
+}  // namespace math
+}  // namespace arm
+}  // namespace lite
+}  // namespace paddle

paddle/fluid/lite/arm/math/elementwise.h

+// Copyright (c) 2019 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
+
+namespace paddle {
+namespace lite {
+namespace arm {
+namespace math {
+
+template <typename T>
+void elementwise_add(const T* dinx, const T* diny, T* dout, int num);
+
+}  // namespace math
+}  // namespace arm
+}  // namespace lite
+}  // namespace paddle

paddle/fluid/lite/kernels/arm/CMakeLists.txt

@@ -9,16 +9,19 @@ cc_library(relu_compute_arm SRCS relu_compute.cc DEPS ${lite_kernel_deps})
 cc_library(mul_compute_arm SRCS mul_compute.cc DEPS ${lite_kernel_deps} eigen3)
 cc_library(scale_compute_arm SRCS scale_compute.cc DEPS ${lite_kernel_deps} math_arm)
 cc_library(softmax_compute_arm SRCS softmax_compute.cc DEPS ${lite_kernel_deps} math_arm)
+cc_library(elementwise_add_compute_arm SRCS elementwise_add_compute.cc DEPS ${lite_kernel_deps} math_arm)
 
 lite_cc_test(test_fc_compute_arm SRCS fc_compute_test.cc DEPS fc_compute_arm math_arm)
 lite_cc_test(test_scale_compute_arm SRCS scale_compute_test.cc DEPS scale_compute_arm)
 lite_cc_test(test_softmax_compute_arm SRCS softmax_compute_test.cc DEPS softmax_compute_arm)
+lite_cc_test(test_elementwise_add_compute_arm SRCS elementwise_add_compute_test.cc DEPS elementwise_add_compute_arm)
 
 set(arm_kernels
     fc_compute_arm
     relu_compute_arm
     mul_compute_arm
     scale_compute_arm
-    softmax_compute_arm)
+    softmax_compute_arm
+	elementwise_add_compute_arm)
 
 set(arm_kernels "${arm_kernels}" CACHE INTERNAL "arm kernels")

paddle/fluid/lite/kernels/arm/elementwise_add_compute.cc

+// Copyright (c) 2019 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.
+
+#include "paddle/fluid/lite/kernels/arm/elementwise_add_compute.h"
+#include "paddle/fluid/lite/arm/math/funcs.h"
+
+namespace paddle {
+namespace lite {
+namespace kernels {
+namespace arm {
+
+void ElementwiseAddCompute::Run() {
+  auto& param = Param<operators::ElementwiseParam>();
+  const float* x_data = param.X->data<float>();
+  const float* y_data = param.Y->data<float>();
+  float* out_data = param.Out->mutable_data<float>();
+  int n = param.X->dims().production();
+  lite::arm::math::elementwise_add(x_data, y_data, out_data, n);
+}
+
+}  // namespace arm
+}  // namespace kernels
+}  // namespace lite
+}  // namespace paddle
+
+REGISTER_LITE_KERNEL(elementwise_add, kARM, kFloat, kNCHW,
+                     paddle::lite::kernels::arm::ElementwiseAddCompute, def)
+    .BindInput("X", {LiteType::GetTensorTy(TARGET(kARM))})
+    .BindInput("Y", {LiteType::GetTensorTy(TARGET(kARM))})
+    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kARM))})
+    .Finalize();

paddle/fluid/lite/kernels/arm/elementwise_add_compute.h

+// Copyright (c) 2019 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 "paddle/fluid/lite/core/kernel.h"
+#include "paddle/fluid/lite/core/op_registry.h"
+
+namespace paddle {
+namespace lite {
+namespace kernels {
+namespace arm {
+
+class ElementwiseAddCompute
+    : public KernelLite<TARGET(kARM), PRECISION(kFloat)> {
+ public:
+  void Run() override;
+
+  virtual ~ElementwiseAddCompute() = default;
+};
+
+}  // namespace arm
+}  // namespace kernels
+}  // namespace lite
+}  // namespace paddle

paddle/fluid/lite/kernels/arm/elementwise_add_compute_test.cc

+// Copyright (c) 2019 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.
+
+#include "paddle/fluid/lite/kernels/arm/elementwise_add_compute.h"
+#include <gtest/gtest.h>
+#include <vector>
+#include "paddle/fluid/lite/core/op_registry.h"
+
+namespace paddle {
+namespace lite {
+namespace kernels {
+namespace arm {
+
+TEST(elementwise_add_arm, retrive_op) {
+  auto elementwise_add =
+      KernelRegistry::Global().Create<TARGET(kARM), PRECISION(kFloat)>(
+          "elementwise_add");
+  ASSERT_FALSE(elementwise_add.empty());
+  ASSERT_TRUE(elementwise_add.front());
+}
+
+TEST(elementwise_add_arm, init) {
+  ElementwiseAddCompute elementwise_add;
+  ASSERT_EQ(elementwise_add.precision(), PRECISION(kFloat));
+  ASSERT_EQ(elementwise_add.target(), TARGET(kARM));
+}
+
+template <typename dtype>
+void elementwise_add_compute_ref(const operators::ElementwiseParam& param) {
+  const dtype* x_data = param.X->data<const dtype>();
+  const dtype* y_data = param.Y->data<const dtype>();
+  dtype* out_data = param.Out->mutable_data<dtype>();
+  DDim dim = param.X->dims();
+  ASSERT_EQ(dim.data(), param.Out->dims().data());
+  for (int i = 0; i < dim.production(); i++) {
+    out_data[i] = x_data[i] + y_data[i];
+  }
+}
+
+TEST(elementwise_add, compute) {
+  ElementwiseAddCompute elementwise_add;
+  operators::ElementwiseParam param;
+
+  lite::Tensor x, y, out, out_ref;
+  x.Resize(DDim(std::vector<int64_t>({2, 3, 4, 5})));
+  y.Resize(DDim(std::vector<int64_t>({2, 3, 4, 5})));
+  out.Resize(DDim(std::vector<int64_t>({2, 3, 4, 5})));
+  out_ref.Resize(DDim(std::vector<int64_t>({2, 3, 4, 5})));
+  auto* x_data = x.mutable_data<float>();
+  auto* y_data = y.mutable_data<float>();
+  auto* out_data = out.mutable_data<float>();
+  auto* out_ref_data = out_ref.mutable_data<float>();
+  for (int i = 0; i < x.dims().production(); i++) {
+    x_data[i] = y_data[i] = i;
+  }
+
+  param.X = &x;
+  param.Y = &y;
+  param.Out = &out;
+  elementwise_add.SetParam(param);
+  elementwise_add.Run();
+
+  param.Out = &out_ref;
+  elementwise_add_compute_ref<float>(param);
+  for (int i = 0; i < out.dims().production(); i++) {
+    EXPECT_NEAR(out_data[i], out_ref_data[i], 1e-5);
+  }
+}
+
+}  // namespace arm
+}  // namespace kernels
+}  // namespace lite
+}  // namespace paddle
+
+USE_LITE_KERNEL(elementwise_add, kARM, kFloat, kNCHW, def);