perception: remove common/test directory. RDFModelUltra code is not available.

modules/perception/common/test/BUILD.txt

-# DO NOT MODIFY
-# THIS FILE IS GENERATED AUTOMATICALLY TO HELP WRITE BUILD FILE
-# DELETE THIS FILE WHEN YOU HAVE CREATED THE COMPLETE BUILD FILE
-load("//tools:cpplint.bzl", "cpplint")
-
-package(default_visibility = ["//visibility:public"])
-
-cc_library(
-    name = "common_image_processing_hough_test",
-    srcs = [
-        "common_image_processing_hough_test.cc",
-    ],
-    deps = [
-    ],
-)
-
-cc_library(
-    name = "common_io_io_util_test",
-    srcs = [
-        "common_io_io_util_test.cc",
-    ],
-    deps = [
-    ],
-)
-
-cc_library(
-    name = "common_machine_learning_rdf_test",
-    srcs = [
-        "common_machine_learning_rdf_test.cc",
-    ],
-    deps = [
-    ],
-)
-
-cc_library(
-    name = "common_point_cloud_processing_common_test",
-    srcs = [
-        "common_point_cloud_processing_common_test.cc",
-    ],
-    deps = [
-    ],
-)
-
-cpplint()

modules/perception/common/test/common_machine_learning_rdf_test.cc

-/******************************************************************************
- * Copyright 2018 The Apollo 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 <gtest/gtest.h>
-#include "modules/perception/common/machine_learning/rdf_helper.h"
-#include "modules/perception/common/machine_learning/rdf_model_ultra.h"
-
-namespace apollo {
-namespace perception {
-namespace common {
-
-TEST(RDFModelUltraTest, bit_operation_test) {
-  uint32_t var_idx = 0x00000010;
-  uint32_t dest = 0x10011000;
-  uint32_t i_result = SetVarIdx(var_idx, dest);
-  EXPECT_EQ(0x01011000, i_result);
-
-  uint32_t childpos = 0x00000080;
-  i_result = SetChildPos(childpos, dest);
-  EXPECT_EQ(0x10000080, i_result);
-
-  i_result = GetVarIdx(dest);
-  EXPECT_EQ(0x00000100, i_result);
-
-  i_result = GetChildPos(dest);
-  EXPECT_EQ(0x00011000, i_result);
-
-  float f_result = SetLeftChildLeaf(Uint32ToFloatByBit(dest));
-  EXPECT_EQ(0x10011002, FloatToUint32ByBit(f_result));
-
-  f_result = SetLeftChildUnleaf(Uint32ToFloatByBit(dest));
-  EXPECT_EQ(0x10011000, FloatToUint32ByBit(f_result));
-
-  f_result = SetRightChildLeaf(Uint32ToFloatByBit(dest));
-  EXPECT_EQ(0x10011001, FloatToUint32ByBit(f_result));
-
-  f_result = SetRightChildUnleaf(Uint32ToFloatByBit(dest));
-  EXPECT_EQ(0x10011000, FloatToUint32ByBit(f_result));
-
-  bool b_result = IsLeftChildLeaf(Uint32ToFloatByBit(dest));
-  EXPECT_FALSE(b_result);
-
-  b_result = IsRightChildLeaf(Uint32ToFloatByBit(dest));
-  EXPECT_FALSE(b_result);
-
-  b_result = IsBothChildLeaf(Uint32ToFloatByBit(dest));
-  EXPECT_FALSE(b_result);
-
-  b_result = IsBothChildNotLeaf(Uint32ToFloatByBit(dest));
-  EXPECT_TRUE(b_result);
-
-  f_result = SetChildClassOnSplitVal(0x00000003, Uint32ToFloatByBit(dest));
-  EXPECT_EQ(0x1001100c, FloatToUint32ByBit(f_result));
-
-  i_result = GetChildClassOnSplitVal(Uint32ToFloatByBit(dest));
-  EXPECT_EQ(0, i_result);
-
-  i_result = SetChildClassOnPos(0x00000003, dest);
-  EXPECT_EQ(0x10011003, i_result);
-
-  i_result = GetChildClassOnPos(dest);
-  EXPECT_EQ(0x00000000, i_result);
-}
-
-TEST(RDFModelUltraTest, trans_old_model_to_ultra_model_test) {
-  RDFModelUltra ultra_model;
-  bool model_loaded = ultra_model.IsModelLoaded();
-  EXPECT_FALSE(model_loaded);
-  bool trans_res = ultra_model.TransOldModelToUltraModel(
-      "./common_test_data/machine_learning/data/not_exist_model");
-  EXPECT_FALSE(trans_res);
-  trans_res = ultra_model.TransOldModelToUltraModel(
-      "./common_test_data/machine_learning/data/normal_correct_model.bin");
-  EXPECT_TRUE(trans_res);
-  model_loaded = ultra_model.IsModelLoaded();
-  EXPECT_TRUE(model_loaded);
-  bool save_res = ultra_model.SaveBinModel(
-      "./common_test_data/machine_learning/data/ultra_correct_model.bin");
-  EXPECT_TRUE(save_res);
-
-  const RDFModelUltra::ForestHead* head = ultra_model.GetForestHeader();
-  EXPECT_EQ(2, head->tree_num);
-  EXPECT_EQ(4, head->tree_node_num);
-  EXPECT_EQ(0, head->tree_pos_list[0]);
-  EXPECT_EQ(2, head->tree_pos_list[1]);
-
-  const std::vector<RDFModelUltra::TreeNodeUltra>* ultra_tree_nodes =
-      ultra_model.GetTreeNodeUltraList();
-  EXPECT_EQ(4, ultra_tree_nodes->size());
-}
-
-TEST(RDFModelUltraTest, load_predict_test) {
-  std::vector<float> test_feature1 = {0.5, 2.5, 2.6, 4.5, 4.6,
-                                      6.5, 6.6, 8.5, 8.6, 10.5};
-  std::vector<float> test_feature2 = {1.5, 1.5, 3.6, 3.5, 5.6,
-                                      5.5, 7.6, 7.5, 9.6, 9.5};
-  std::vector<float> test_features = {0.5, 2.5, 2.6,  4.5, 4.6, 6.5, 6.6,
-                                      8.5, 8.6, 10.5, 1.5, 1.5, 3.6, 3.5,
-                                      5.6, 5.5, 7.6,  7.5, 9.6, 9.5};
-  RDFModelUltra ultra_model;
-  bool load_res = ultra_model.LoadBinModel(
-      "./common_test_data/machine_learning/data/ultra_correct_model.bin");
-  EXPECT_TRUE(load_res);
-  int ultra_tree_node_idx = ultra_model.GetTreeNodeUltraIdx(nullptr);
-  EXPECT_EQ(-1, ultra_tree_node_idx);
-  ultra_tree_node_idx =
-      ultra_model.GetTreeNodeUltraIdx(ultra_model.tree_node_ultra_list_.data());
-  EXPECT_EQ(0, ultra_tree_node_idx);
-  std::vector<float> probs;
-  float predict_res = ultra_model.ForestPredict(test_feature1, &probs);
-  EXPECT_EQ(1, static_cast<int>(predict_res));
-  predict_res = ultra_model.ForestPredict(test_feature2, &probs);
-  EXPECT_EQ(0, static_cast<int>(predict_res));
-  ultra_model.BatchForestPredict(test_features.data(), probs.data(), 10, 2, 2);
-  EXPECT_FLOAT_EQ(0.0, probs[0]);
-  EXPECT_FLOAT_EQ(1.0, probs[1]);
-  EXPECT_FLOAT_EQ(0.5, probs[2]);
-  EXPECT_FLOAT_EQ(0.5, probs[3]);
-
-  ultra_model.ClearModel();
-  bool model_loaded = ultra_model.IsModelLoaded();
-  EXPECT_FALSE(model_loaded);
-  load_res = ultra_model.LoadBinModel(
-      "./common_test_data/machine_learning/data/normal_correct_model.bin");
-  EXPECT_FALSE(load_res);
-
-  load_res = ultra_model.LoadBinModel("not_exist_model");
-  EXPECT_FALSE(load_res);
-
-  bool save_res = ultra_model.SaveBinModel(
-      "./common_test_data/machine_learning/data/not_exist_model");
-  EXPECT_FALSE(save_res);
-}
-
-TEST(RDFModelTest, load_predict_test) {
-  std::vector<float> test_feature1 = {0.5, 2.5, 2.6, 4.5, 4.6,
-                                      6.5, 6.6, 8.5, 8.6, 10.5};
-  std::vector<float> test_feature2 = {1.5, 1.5, 3.6, 3.5, 5.6,
-                                      5.5, 7.6, 7.5, 9.6, 9.5};
-  std::vector<float> test_features = {0.5, 2.5, 2.6,  4.5, 4.6, 6.5, 6.6,
-                                      8.5, 8.6, 10.5, 1.5, 1.5, 3.6, 3.5,
-                                      5.6, 5.5, 7.6,  7.5, 9.6, 9.5};
-  RDFModel model;
-  bool load_res = model.LoadBinModel(
-      "./common_test_data/machine_learning/data/normal_correct_model.bin");
-  EXPECT_TRUE(load_res);
-  const std::vector<RDFModel::TreeNode>* node_list = model.GetTreeNodeList();
-  EXPECT_EQ(10, node_list->size());
-  int tree_node_idx = model.GetTreeNodeIdx(nullptr);
-  EXPECT_EQ(-1, tree_node_idx);
-  std::vector<float> probs;
-  float predict_res = model.ForestPredict(test_feature1, &probs);
-  EXPECT_EQ(1, static_cast<int>(predict_res));
-  predict_res = model.ForestPredict(test_feature2, &probs);
-  EXPECT_EQ(0, static_cast<int>(predict_res));
-  predict_res = model.ForestPredict(test_feature2, nullptr);
-  EXPECT_EQ(0, static_cast<int>(predict_res));
-  model.BatchForestPredict(test_features.data(), probs.data(), 10, 2, 2);
-  EXPECT_FLOAT_EQ(0.0, probs[0]);
-  EXPECT_FLOAT_EQ(1.0, probs[1]);
-  EXPECT_FLOAT_EQ(0.5, probs[2]);
-  EXPECT_FLOAT_EQ(0.5, probs[3]);
-
-  model.ClearModel();
-  bool model_loaded = model.IsModelLoaded();
-  EXPECT_FALSE(model_loaded);
-  load_res = model.LoadBinModel(
-      "./common_test_data/machine_learning/data/ultra_correct_model.bin");
-  EXPECT_FALSE(load_res);
-
-  load_res = model.LoadBinModel("not_exist_model");
-  EXPECT_FALSE(load_res);
-
-  bool save_res = model.SaveBinModel(
-      "./common_test_data/machine_learning/data/not_exist_model");
-  EXPECT_FALSE(save_res);
-}
-
-}  // namespace common
-}  // namespace perception
-}  // namespace apollo