repair bug of dropout op

src/operators/kernel/arm/dropout_kernel.cpp

@@ -27,7 +27,11 @@ bool DropoutKernel<CPU, float>::Init(DropoutParam<CPU> *para) {
 
 template <typename T>
 struct DropoutFunctor {
-  inline T operator()(T in) const { return in; }
+  DropoutFunctor(T drop_pro) : dropout_pro_(drop_pro) {}
+  inline T operator()(T in) const { return (1 - dropout_pro_) * in; }
+
+ private:
+  T dropout_pro_;
 };
 
 template <>
@@ -36,8 +40,8 @@ void DropoutKernel<CPU, float>::Compute(const DropoutParam<CPU> &param) const {
   auto *input_x_ptr = input_x->data<float>();
   auto *out = param.Out();
   auto *out_ptr = out->mutable_data<float>();
-
-  DropoutFunctor<float> func_;
+  const float dropoutProb = param.DropoutProb();
+  DropoutFunctor<float> func_(dropoutProb);
   math::Transform trans;
   trans(input_x_ptr, input_x_ptr + input_x->numel(), out_ptr, func_);
 }

src/operators/op_param.h

@@ -2136,15 +2136,20 @@ class DropoutParam : public OpParam {
                const AttributeMap &attrs, const Scope &scope) {
     input_x_ = InputXFrom<GType>(inputs, scope);
     out_ = OutFrom<GType>(outputs, scope);
+
+    dropout_prob_ = GetAttr<float>("dropout_prob", attrs);
   }
 
   const RType *InputX() const { return input_x_; }
 
   RType *Out() const { return out_; }
 
+  float DropoutProb() const { return dropout_prob_; }
+
  private:
   RType *input_x_;
   RType *out_;
+  float dropout_prob_;
 };
 #endif
 

test/CMakeLists.txt

@@ -207,10 +207,20 @@ else ()
     ADD_EXECUTABLE(test-gru-op  operators/test_gru_op.cpp test_helper.h  test_include.h)
     target_link_libraries(test-gru-op paddle-mobile)
 
+    # gen test
+    ADD_EXECUTABLE(test-inceptionv4 net/test_inceptionv4.cpp test_helper.h  test_include.h executor_for_test.h)
+    target_link_libraries(test-inceptionv4 paddle-mobile)
+
+    # gen test
+    ADD_EXECUTABLE(test-alexnet net/test_alexnet.cpp test_helper.h  test_include.h executor_for_test.h)
+    target_link_libraries(test-alexnet paddle-mobile)
+
     #add_library(test-lib-size SHARED common/test_lib_size.h common/test_lib_size.cpp)
 
 
 
+
+
 endif()
 
 # if(FPGA)

test/net/test_alexnet.cpp

+/* 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. */
+
+#include <iostream>
+#include "../test_helper.h"
+#include "../test_include.h"
+
+int main() {
+  paddle_mobile::PaddleMobile<paddle_mobile::CPU> paddle_mobile;
+  paddle_mobile.SetThreadNum(4);
+  auto time1 = time();
+  //  auto isok = paddle_mobile.Load(std::string(g_mobilenet_detect) + "/model",
+  //                     std::string(g_mobilenet_detect) + "/params", true);
+
+  auto isok = paddle_mobile.Load(g_alexnet, true);
+  if (isok) {
+    auto time2 = time();
+    std::cout << "load cost :" << time_diff(time1, time1) << "ms" << std::endl;
+
+    std::vector<float> input;
+    std::vector<int64_t> dims{1, 3, 224, 224};
+    GetInput<float>(g_test_image_1x3x224x224_banana, &input, dims);
+
+    auto vec_result = paddle_mobile.Predict(input, dims);
+    std::vector<float>::iterator biggest =
+        std::max_element(std::begin(vec_result), std::end(vec_result));
+    std::cout << " Max element is " << *biggest << " at position "
+              << std::distance(std::begin(vec_result), biggest) << std::endl;
+
+    // 预热十次
+    for (int i = 0; i < 10; ++i) {
+      auto vec_result = paddle_mobile.Predict(input, dims);
+    }
+    auto time3 = time();
+    for (int i = 0; i < 10; ++i) {
+      auto vec_result = paddle_mobile.Predict(input, dims);
+    }
+    DLOG << vec_result;
+    auto time4 = time();
+    std::cout << "predict cost :" << time_diff(time3, time4) / 10 << "ms"
+              << std::endl;
+  }
+
+  std::cout << "如果结果Nan请查看: test/images/g_test_image_1x3x224x224_banana "
+               "是否存在?"
+            << std::endl;
+  return 0;
+}

test/net/test_inceptionv4.cpp

+/* 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. */
+
+#include <iostream>
+#include "../test_helper.h"
+#include "../test_include.h"
+
+int main() {
+  paddle_mobile::PaddleMobile<paddle_mobile::CPU> paddle_mobile;
+  paddle_mobile.SetThreadNum(4);
+  auto time1 = time();
+  //  auto isok = paddle_mobile.Load(std::string(g_mobilenet_detect) + "/model",
+  //                     std::string(g_mobilenet_detect) + "/params", true);
+
+  auto isok = paddle_mobile.Load(g_inceptionv4, true);
+  if (isok) {
+    auto time2 = time();
+    std::cout << "load cost :" << time_diff(time1, time1) << "ms" << std::endl;
+
+    std::vector<float> input;
+    std::vector<int64_t> dims{1, 3, 224, 224};
+    GetInput<float>(g_test_image_1x3x224x224_banana, &input, dims);
+
+    auto vec_result = paddle_mobile.Predict(input, dims);
+    std::vector<float>::iterator biggest =
+        std::max_element(std::begin(vec_result), std::end(vec_result));
+    std::cout << " Max element is " << *biggest << " at position "
+              << std::distance(std::begin(vec_result), biggest) << std::endl;
+
+    // 预热十次
+    for (int i = 0; i < 10; ++i) {
+      auto vec_result = paddle_mobile.Predict(input, dims);
+    }
+    auto time3 = time();
+    for (int i = 0; i < 10; ++i) {
+      auto vec_result = paddle_mobile.Predict(input, dims);
+    }
+    //        DLOG << vec_result;
+    auto time4 = time();
+    std::cout << "predict cost :" << time_diff(time3, time4) / 10 << "ms"
+              << std::endl;
+  }
+
+  std::cout << "如果结果Nan请查看: test/images/g_test_image_1x3x224x224_banana "
+               "是否存在?"
+            << std::endl;
+  return 0;
+}

test/test_helper.h

@@ -33,6 +33,8 @@ static const char *g_mobilenet_detect = "../models/mobilenet-detect";
 static const char *g_squeezenet = "../models/squeezenet";
 static const char *g_googlenet = "../models/googlenet";
 static const char *g_mobilenet = "../models/mobilenet";
+static const char *g_alexnet = "../models/alexnet";
+static const char *g_inceptionv4 = "../models/inceptionv4";
 static const char *g_nlp = "../models/nlp";
 static const char *g_resnet_50 = "../models/resnet_50";
 static const char *g_resnet = "../models/resnet";