1 files changed, 219 insertions, 0 deletions
diff --git a/tesseract/unittest/stridemap_test.cc b/tesseract/unittest/stridemap_test.cc
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+++ b/tesseract/unittest/stridemap_test.cc
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+// (C) Copyright 2017, Google Inc.
+// 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.
+
+#ifdef INCLUDE_TENSORFLOW
+#include <tensorflow/compiler/xla/array2d.h> // for xla::Array2D
+#else
+#include <array> // std::array
+#endif
+#include "include_gunit.h"
+#include "stridemap.h"
+
+namespace tesseract {
+
+#if !defined(INCLUDE_TENSORFLOW) && 0
+namespace xla {
+
+template <typename T>
+class Array2D : public std::vector<T> {
+ public:
+  Array2D() : std::vector<T>(std::vector<int64_t>{0, 0}) {}
+
+  Array2D(const int64_t n1, const int64_t n2)
+      : std::vector<T>(std::vector<int64_t>{n1, n2}) {}
+
+  Array2D(const int64_t n1, const int64_t n2, const T value)
+      : std::vector<T>({n1, n2}, value) {}
+};
+}
+#endif
+
+class StridemapTest : public ::testing::Test {
+ protected:
+  void SetUp() {
+    std::locale::global(std::locale(""));
+  }
+
+#ifdef INCLUDE_TENSORFLOW
+  // Sets up an Array2d object of the given size, initialized to increasing
+  // values starting with start.
+  std::unique_ptr<xla::Array2D<int>> SetupArray(int ysize, int xsize, int start) {
+    std::unique_ptr<xla::Array2D<int>> a(new xla::Array2D<int>(ysize, xsize));
+    int value = start;
+    for (int y = 0; y < ysize; ++y) {
+      for (int x = 0; x < xsize; ++x) {
+#ifdef INCLUDE_TENSORFLOW
+        (*a)(y, x) = value++;
+#else
+        a[y][x] = value++;
+#endif
+      }
+    }
+    return a;
+  }
+#endif
+};
+
+TEST_F(StridemapTest, Indexing) {
+  // This test verifies that with a batch of arrays of different sizes, the
+  // iteration index each of them in turn, without going out of bounds.
+#ifdef INCLUDE_TENSORFLOW
+  std::vector<std::unique_ptr<xla::Array2D<int>>> arrays;
+  arrays.push_back(SetupArray(3, 4, 0));
+  arrays.push_back(SetupArray(4, 5, 12));
+  arrays.push_back(SetupArray(4, 4, 32));
+  arrays.push_back(SetupArray(3, 5, 48));
+  std::vector<std::pair<int, int>> h_w_sizes;
+  for (size_t i = 0; i < arrays.size(); ++i) {
+    h_w_sizes.emplace_back(arrays[i].get()->height(), arrays[i].get()->width());
+  }
+  StrideMap stride_map;
+  stride_map.SetStride(h_w_sizes);
+  StrideMap::Index index(stride_map);
+  int pos = 0;
+  do {
+    EXPECT_GE(index.t(), pos);
+    EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT),
+                                                  index.index(FD_WIDTH)),
+              pos);
+    EXPECT_EQ(index.IsLast(FD_BATCH),
+              index.index(FD_BATCH) == arrays.size() - 1);
+    EXPECT_EQ(
+        index.IsLast(FD_HEIGHT),
+        index.index(FD_HEIGHT) == arrays[index.index(FD_BATCH)]->height() - 1);
+    EXPECT_EQ(
+        index.IsLast(FD_WIDTH),
+        index.index(FD_WIDTH) == arrays[index.index(FD_BATCH)]->width() - 1);
+    EXPECT_TRUE(index.IsValid());
+    ++pos;
+  } while (index.Increment());
+  LOG(INFO) << "pos=" << pos;
+  index.InitToLast();
+  do {
+    --pos;
+    EXPECT_GE(index.t(), pos);
+    EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT),
+                                                  index.index(FD_WIDTH)),
+              pos);
+    StrideMap::Index copy(index);
+    // Since a change in batch index changes the height and width, it isn't
+    // necessarily true that the position is still valid, even when changing
+    // to another valid batch index.
+    if (index.IsLast(FD_BATCH)) {
+      EXPECT_FALSE(copy.AddOffset(1, FD_BATCH));
+    }
+    copy = index;
+    EXPECT_EQ(index.IsLast(FD_HEIGHT), !copy.AddOffset(1, FD_HEIGHT));
+    copy = index;
+    EXPECT_EQ(index.IsLast(FD_WIDTH), !copy.AddOffset(1, FD_WIDTH));
+    copy = index;
+    if (index.index(FD_BATCH) == 0) {
+      EXPECT_FALSE(copy.AddOffset(-1, FD_BATCH));
+    }
+    copy = index;
+    EXPECT_EQ(index.index(FD_HEIGHT) == 0, !copy.AddOffset(-1, FD_HEIGHT));
+    copy = index;
+    EXPECT_EQ(index.index(FD_WIDTH) == 0, !copy.AddOffset(-1, FD_WIDTH));
+    copy = index;
+    EXPECT_FALSE(copy.AddOffset(10, FD_WIDTH));
+    copy = index;
+    EXPECT_FALSE(copy.AddOffset(-10, FD_HEIGHT));
+    EXPECT_TRUE(index.IsValid());
+  } while (index.Decrement());
+#else
+  LOG(INFO) << "Skip test because of missing xla::Array2D";
+  GTEST_SKIP();
+#endif
+}
+
+TEST_F(StridemapTest, Scaling) {
+  // This test verifies that with a batch of arrays of different sizes, the
+  // scaling/reduction functions work as expected.
+#ifdef INCLUDE_TENSORFLOW
+  std::vector<std::unique_ptr<xla::Array2D<int>>> arrays;
+  arrays.push_back(SetupArray(3, 4, 0));   // 0-11
+  arrays.push_back(SetupArray(4, 5, 12));  // 12-31
+  arrays.push_back(SetupArray(4, 4, 32));  // 32-47
+  arrays.push_back(SetupArray(3, 5, 48));  // 48-62
+  std::vector<std::pair<int, int>> h_w_sizes;
+  for (size_t i = 0; i < arrays.size(); ++i) {
+    h_w_sizes.emplace_back(arrays[i].get()->height(), arrays[i].get()->width());
+  }
+  StrideMap stride_map;
+  stride_map.SetStride(h_w_sizes);
+
+  // Scale x by 2, keeping y the same.
+  std::vector<int> values_x2 = {0,  1,  4,  5,  8,  9,  12, 13, 17, 18,
+                                22, 23, 27, 28, 32, 33, 36, 37, 40, 41,
+                                44, 45, 48, 49, 53, 54, 58, 59};
+  StrideMap test_map(stride_map);
+  test_map.ScaleXY(2, 1);
+  StrideMap::Index index(test_map);
+  int pos = 0;
+  do {
+    int expected_value = values_x2[pos++];
+    EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT),
+                                                  index.index(FD_WIDTH)),
+              expected_value);
+  } while (index.Increment());
+  EXPECT_EQ(pos, values_x2.size());
+
+  test_map = stride_map;
+  // Scale y by 2, keeping x the same.
+  std::vector<int> values_y2 = {0,  1,  2,  3,  12, 13, 14, 15, 16,
+                                17, 18, 19, 20, 21, 32, 33, 34, 35,
+                                36, 37, 38, 39, 48, 49, 50, 51, 52};
+  test_map.ScaleXY(1, 2);
+  index.InitToFirst();
+  pos = 0;
+  do {
+    int expected_value = values_y2[pos++];
+    EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT),
+                                                  index.index(FD_WIDTH)),
+              expected_value);
+  } while (index.Increment());
+  EXPECT_EQ(pos, values_y2.size());
+
+  test_map = stride_map;
+  // Scale x and y by 2.
+  std::vector<int> values_xy2 = {0, 1, 12, 13, 17, 18, 32, 33, 36, 37, 48, 49};
+  test_map.ScaleXY(2, 2);
+  index.InitToFirst();
+  pos = 0;
+  do {
+    int expected_value = values_xy2[pos++];
+    EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT),
+                                                  index.index(FD_WIDTH)),
+              expected_value);
+  } while (index.Increment());
+  EXPECT_EQ(pos, values_xy2.size());
+
+  test_map = stride_map;
+  // Reduce Width to 1.
+  std::vector<int> values_x_to_1 = {0,  4,  8,  12, 17, 22, 27,
+                                    32, 36, 40, 44, 48, 53, 58};
+  test_map.ReduceWidthTo1();
+  index.InitToFirst();
+  pos = 0;
+  do {
+    int expected_value = values_x_to_1[pos++];
+    EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT),
+                                                  index.index(FD_WIDTH)),
+              expected_value);
+  } while (index.Increment());
+  EXPECT_EQ(pos, values_x_to_1.size());
+#else
+  LOG(INFO) << "Skip test because of missing xla::Array2D";
+  GTEST_SKIP();
+#endif
+}
+
+}  // namespace