mirror of
https://github.com/tesseract-ocr/tesseract.git
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216 lines
6.8 KiB
C++
216 lines
6.8 KiB
C++
// (C) Copyright 2017, Google Inc.
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "networkio.h"
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#include "include_gunit.h"
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#include "stridemap.h"
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#ifdef INCLUDE_TENSORFLOW
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# include <tensorflow/compiler/xla/array2d.h> // for xla::Array2D
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#endif
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namespace tesseract {
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class NetworkioTest : public ::testing::Test {
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protected:
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void SetUp() override {
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std::locale::global(std::locale(""));
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}
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#ifdef INCLUDE_TENSORFLOW
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// Sets up an Array2d object of the given size, initialized to increasing
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// values starting with start.
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std::unique_ptr<xla::Array2D<int>> SetupArray(int ysize, int xsize, int start) {
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std::unique_ptr<xla::Array2D<int>> a(new xla::Array2D<int>(ysize, xsize));
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int value = start;
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for (int y = 0; y < ysize; ++y) {
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for (int x = 0; x < xsize; ++x) {
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(*a)(y, x) = value++;
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}
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}
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return a;
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}
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// Sets up a NetworkIO with a batch of 2 "images" of known values.
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void SetupNetworkIO(NetworkIO *nio) {
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std::vector<std::unique_ptr<xla::Array2D<int>>> arrays;
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arrays.push_back(SetupArray(3, 4, 0));
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arrays.push_back(SetupArray(4, 5, 12));
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std::vector<std::pair<int, int>> h_w_sizes;
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for (size_t i = 0; i < arrays.size(); ++i) {
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h_w_sizes.emplace_back(arrays[i].get()->height(), arrays[i].get()->width());
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}
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StrideMap stride_map;
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stride_map.SetStride(h_w_sizes);
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nio->ResizeToMap(true, stride_map, 2);
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// Iterate over the map, setting nio's contents from the arrays.
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StrideMap::Index index(stride_map);
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do {
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int value = (*arrays[index.index(FD_BATCH)])(index.index(FD_HEIGHT), index.index(FD_WIDTH));
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nio->SetPixel(index.t(), 0, 128 + value, 0.0f, 128.0f);
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nio->SetPixel(index.t(), 1, 128 - value, 0.0f, 128.0f);
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} while (index.Increment());
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}
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#endif
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};
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// Tests that the initialization via SetPixel works and the resize correctly
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// fills with zero where image sizes don't match.
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TEST_F(NetworkioTest, InitWithZeroFill) {
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#ifdef INCLUDE_TENSORFLOW
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NetworkIO nio;
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nio.Resize2d(true, 32, 2);
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int width = nio.Width();
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for (int t = 0; t < width; ++t) {
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nio.SetPixel(t, 0, 0, 0.0f, 128.0f);
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nio.SetPixel(t, 1, 0, 0.0f, 128.0f);
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}
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// The initialization will wipe out all previously set values.
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SetupNetworkIO(&nio);
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nio.ZeroInvalidElements();
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StrideMap::Index index(nio.stride_map());
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int next_t = 0;
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int pos = 0;
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do {
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int t = index.t();
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// The indexed values just increase monotonically.
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int value = nio.i(t)[0];
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EXPECT_EQ(value, pos);
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value = nio.i(t)[1];
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EXPECT_EQ(value, -pos);
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// When we skip t values, the data is always 0.
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while (next_t < t) {
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EXPECT_EQ(nio.i(next_t)[0], 0);
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EXPECT_EQ(nio.i(next_t)[1], 0);
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++next_t;
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}
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++pos;
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++next_t;
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} while (index.Increment());
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EXPECT_EQ(pos, 32);
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EXPECT_EQ(next_t, 40);
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#else
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LOG(INFO) << "Skip test because of missing xla::Array2D";
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GTEST_SKIP();
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#endif
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}
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// Tests that CopyWithYReversal works.
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TEST_F(NetworkioTest, CopyWithYReversal) {
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#ifdef INCLUDE_TENSORFLOW
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NetworkIO nio;
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SetupNetworkIO(&nio);
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NetworkIO copy;
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copy.CopyWithYReversal(nio);
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StrideMap::Index index(copy.stride_map());
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int next_t = 0;
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int pos = 0;
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std::vector<int> expected_values = {8, 9, 10, 11, 4, 5, 6, 7, 0, 1, 2,
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3, 27, 28, 29, 30, 31, 22, 23, 24, 25, 26,
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17, 18, 19, 20, 21, 12, 13, 14, 15, 16};
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do {
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int t = index.t();
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// The indexed values match the expected values.
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int value = copy.i(t)[0];
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EXPECT_EQ(value, expected_values[pos]);
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value = copy.i(t)[1];
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EXPECT_EQ(value, -expected_values[pos]);
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// When we skip t values, the data is always 0.
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while (next_t < t) {
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EXPECT_EQ(copy.i(next_t)[0], 0) << "Failure t = " << next_t;
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EXPECT_EQ(copy.i(next_t)[1], 0) << "Failure t = " << next_t;
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++next_t;
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}
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++pos;
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++next_t;
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} while (index.Increment());
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EXPECT_EQ(pos, 32);
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EXPECT_EQ(next_t, 40);
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#else
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LOG(INFO) << "Skip test because of missing xla::Array2D";
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GTEST_SKIP();
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#endif
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}
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// Tests that CopyWithXReversal works.
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TEST_F(NetworkioTest, CopyWithXReversal) {
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#ifdef INCLUDE_TENSORFLOW
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NetworkIO nio;
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SetupNetworkIO(&nio);
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NetworkIO copy;
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copy.CopyWithXReversal(nio);
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StrideMap::Index index(copy.stride_map());
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int next_t = 0;
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int pos = 0;
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std::vector<int> expected_values = {3, 2, 1, 0, 7, 6, 5, 4, 11, 10, 9,
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8, 16, 15, 14, 13, 12, 21, 20, 19, 18, 17,
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26, 25, 24, 23, 22, 31, 30, 29, 28, 27};
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do {
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int t = index.t();
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// The indexed values match the expected values.
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int value = copy.i(t)[0];
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EXPECT_EQ(value, expected_values[pos]);
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value = copy.i(t)[1];
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EXPECT_EQ(value, -expected_values[pos]);
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// When we skip t values, the data is always 0.
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while (next_t < t) {
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EXPECT_EQ(copy.i(next_t)[0], 0) << "Failure t = " << next_t;
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EXPECT_EQ(copy.i(next_t)[1], 0) << "Failure t = " << next_t;
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++next_t;
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}
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++pos;
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++next_t;
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} while (index.Increment());
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EXPECT_EQ(pos, 32);
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EXPECT_EQ(next_t, 40);
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#else
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LOG(INFO) << "Skip test because of missing xla::Array2D";
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GTEST_SKIP();
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#endif
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}
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// Tests that CopyWithXYTranspose works.
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TEST_F(NetworkioTest, CopyWithXYTranspose) {
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#ifdef INCLUDE_TENSORFLOW
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NetworkIO nio;
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SetupNetworkIO(&nio);
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NetworkIO copy;
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copy.CopyWithXYTranspose(nio);
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StrideMap::Index index(copy.stride_map());
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int next_t = 0;
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int pos = 0;
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std::vector<int> expected_values = {0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7,
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11, 12, 17, 22, 27, 13, 18, 23, 28, 14, 19,
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24, 29, 15, 20, 25, 30, 16, 21, 26, 31};
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do {
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int t = index.t();
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// The indexed values match the expected values.
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int value = copy.i(t)[0];
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EXPECT_EQ(value, expected_values[pos]);
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value = copy.i(t)[1];
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EXPECT_EQ(value, -expected_values[pos]);
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// When we skip t values, the data is always 0.
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while (next_t < t) {
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EXPECT_EQ(copy.i(next_t)[0], 0);
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EXPECT_EQ(copy.i(next_t)[1], 0);
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++next_t;
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}
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++pos;
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++next_t;
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} while (index.Increment());
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EXPECT_EQ(pos, 32);
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EXPECT_EQ(next_t, 40);
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#else
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LOG(INFO) << "Skip test because of missing xla::Array2D";
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GTEST_SKIP();
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#endif
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}
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} // namespace tesseract
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