tensorflow/core/kernels/non_max_suppression_op_gpu_test.cc

/* Copyright 2015 The TensorFlow 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 "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/fake_input.h"
#include "tensorflow/core/framework/node_def_builder.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_testutil.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/framework/types.pb.h"  // NOLINT
#include "tensorflow/core/kernels/ops_testutil.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/lib/strings/str_util.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {

#if GOOGLE_CUDA
// These tests are copied from non_max_suppression_op_test.cc file and modified
// to use GPU ops. See other file for test details.

class NonMaxSuppressionV2GPUOpTest : public OpsTestBase {
 protected:
  void MakeOp() {
    SetDevice(DEVICE_GPU,
              std::unique_ptr<tensorflow::Device>(DeviceFactory::NewDevice(
                  "GPU", {}, "/job:a/replica:0/task:0")));

    TF_EXPECT_OK(
        NodeDefBuilder("non_max_suppression_op_gpu", "NonMaxSuppressionV2")
            .Input(FakeInput(DT_FLOAT))
            .Input(FakeInput(DT_FLOAT))
            .Input(FakeInput(DT_INT32))
            .Input(FakeInput(DT_FLOAT))
            .Finalize(node_def()));
    TF_EXPECT_OK(InitOp());
  }
};

TEST_F(NonMaxSuppressionV2GPUOpTest, TestSelectFromThreeClusters) {
  MakeOp();
  AddInputFromArray<float>(
      TensorShape({6, 4}),
      {0, 0,  1, 1,  0, 0.1f,  1, 1.1f,  0, -0.1f, 1, 0.9f,
       0, 10, 1, 11, 0, 10.1f, 1, 11.1f, 0, 100,   1, 101});
  AddInputFromArray<float>(TensorShape({6}), {.9f, .75f, .6f, .95f, .5f, .3f});
  AddInputFromArray<int>(TensorShape({}), {3});
  AddInputFromArray<float>(TensorShape({}), {.5f});
  TF_ASSERT_OK(RunOpKernel());

  Tensor expected(allocator(), DT_INT32, TensorShape({3}));
  test::FillValues<int>(&expected, {3, 0, 5});
  test::ExpectTensorEqual<int>(expected, *GetOutput(0));
}

TEST_F(NonMaxSuppressionV2GPUOpTest,
       TestSelectFromThreeClustersFlippedCoordinates) {
  MakeOp();
  AddInputFromArray<float>(TensorShape({6, 4}),
                           {1, 1,     0, 0,      // score= 0.9
                            0, 0.1f,  1, 1.1f,   // score= 0.75
                            0, .9f,   1, -0.1f,  // score= 0.6
                            0, 10,    1, 11,     // score= 0.95
                            1, 10.1f, 0, 11.1f,  // score=  0.5
                            1, 101,   0, 100});  // score=0.3

  AddInputFromArray<float>(TensorShape({6}), {.9f, .75f, .6f, .95f, .5f, .3f});
  AddInputFromArray<int>(TensorShape({}), {3});
  AddInputFromArray<float>(TensorShape({}), {.5f});
  TF_ASSERT_OK(RunOpKernel());

  Tensor expected(allocator(), DT_INT32, TensorShape({3}));
  test::FillValues<int>(&expected, {3, 0, 5});
  test::ExpectTensorEqual<int>(expected, *GetOutput(0));
}

TEST_F(NonMaxSuppressionV2GPUOpTest,
       TestSelectAtMostTwoBoxesFromThreeClusters) {
  MakeOp();
  AddInputFromArray<float>(
      TensorShape({6, 4}),
      {0, 0,  1, 1,  0, 0.1f,  1, 1.1f,  0, -0.1f, 1, 0.9f,
       0, 10, 1, 11, 0, 10.1f, 1, 11.1f, 0, 100,   1, 101});
  AddInputFromArray<float>(TensorShape({6}), {.9f, .75f, .6f, .95f, .5f, .3f});
  AddInputFromArray<int>(TensorShape({}), {2});
  AddInputFromArray<float>(TensorShape({}), {.5f});
  TF_ASSERT_OK(RunOpKernel());

  Tensor expected(allocator(), DT_INT32, TensorShape({2}));
  test::FillValues<int>(&expected, {3, 0});
  test::ExpectTensorEqual<int>(expected, *GetOutput(0));
}

TEST_F(NonMaxSuppressionV2GPUOpTest,
       TestSelectAtMostThirtyBoxesFromThreeClusters) {
  MakeOp();
  AddInputFromArray<float>(
      TensorShape({6, 4}),
      {0, 0,  1, 1,  0, 0.1f,  1, 1.1f,  0, -0.1f, 1, 0.9f,
       0, 10, 1, 11, 0, 10.1f, 1, 11.1f, 0, 100,   1, 101});
  AddInputFromArray<float>(TensorShape({6}), {.9f, .75f, .6f, .95f, .5f, .3f});
  AddInputFromArray<int>(TensorShape({}), {30});
  AddInputFromArray<float>(TensorShape({}), {.5f});
  TF_ASSERT_OK(RunOpKernel());

  Tensor expected(allocator(), DT_INT32, TensorShape({3}));
  test::FillValues<int>(&expected, {3, 0, 5});
  test::ExpectTensorEqual<int>(expected, *GetOutput(0));
}

TEST_F(NonMaxSuppressionV2GPUOpTest, TestSelectSingleBox) {
  MakeOp();
  AddInputFromArray<float>(TensorShape({1, 4}), {0, 0, 1, 1});
  AddInputFromArray<float>(TensorShape({1}), {.9f});
  AddInputFromArray<int>(TensorShape({}), {3});
  AddInputFromArray<float>(TensorShape({}), {.5f});
  TF_ASSERT_OK(RunOpKernel());

  Tensor expected(allocator(), DT_INT32, TensorShape({1}));
  test::FillValues<int>(&expected, {0});
  test::ExpectTensorEqual<int>(expected, *GetOutput(0));
}

TEST_F(NonMaxSuppressionV2GPUOpTest, TestSelectFromTenIdenticalBoxes) {
  MakeOp();

  int num_boxes = 10;
  std::vector<float> corners(num_boxes * 4);
  std::vector<float> scores(num_boxes);
  for (int i = 0; i < num_boxes; ++i) {
    corners[i * 4 + 0] = 0;
    corners[i * 4 + 1] = 0;
    corners[i * 4 + 2] = 1;
    corners[i * 4 + 3] = 1;
    scores[i] = .9;
  }
  AddInputFromArray<float>(TensorShape({num_boxes, 4}), corners);
  AddInputFromArray<float>(TensorShape({num_boxes}), scores);
  AddInputFromArray<int>(TensorShape({}), {3});
  AddInputFromArray<float>(TensorShape({}), {.5f});
  TF_ASSERT_OK(RunOpKernel());

  Tensor expected(allocator(), DT_INT32, TensorShape({1}));
  test::FillValues<int>(&expected, {0});
  test::ExpectTensorEqual<int>(expected, *GetOutput(0));
}

TEST_F(NonMaxSuppressionV2GPUOpTest, TestInconsistentBoxAndScoreShapes) {
  MakeOp();
  AddInputFromArray<float>(
      TensorShape({6, 4}),
      {0, 0,  1, 1,  0, 0.1f,  1, 1.1f,  0, -0.1f, 1, 0.9f,
       0, 10, 1, 11, 0, 10.1f, 1, 11.1f, 0, 100,   1, 101});
  AddInputFromArray<float>(TensorShape({5}), {.9f, .75f, .6f, .95f, .5f});
  AddInputFromArray<int>(TensorShape({}), {30});
  AddInputFromArray<float>(TensorShape({}), {.5f});
  Status s = RunOpKernel();

  ASSERT_FALSE(s.ok());
  EXPECT_TRUE(
      str_util::StrContains(s.ToString(), "scores has incompatible shape"))
      << s;
}

TEST_F(NonMaxSuppressionV2GPUOpTest, TestInvalidIOUThreshold) {
  MakeOp();
  AddInputFromArray<float>(TensorShape({1, 4}), {0, 0, 1, 1});
  AddInputFromArray<float>(TensorShape({1}), {.9f});
  AddInputFromArray<int>(TensorShape({}), {3});
  AddInputFromArray<float>(TensorShape({}), {1.2f});
  Status s = RunOpKernel();

  ASSERT_FALSE(s.ok());
  EXPECT_TRUE(
      str_util::StrContains(s.ToString(), "iou_threshold must be in [0, 1]"))
      << s;
}

TEST_F(NonMaxSuppressionV2GPUOpTest, TestEmptyInput) {
  MakeOp();
  AddInputFromArray<float>(TensorShape({0, 4}), {});
  AddInputFromArray<float>(TensorShape({0}), {});
  AddInputFromArray<int>(TensorShape({}), {30});
  AddInputFromArray<float>(TensorShape({}), {.5f});
  TF_ASSERT_OK(RunOpKernel());

  Tensor expected(allocator(), DT_INT32, TensorShape({0}));
  test::FillValues<int>(&expected, {});
  test::ExpectTensorEqual<int>(expected, *GetOutput(0));
}

#endif

}  // namespace tensorflow