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Fix and enable lstm related unittests (#2180)

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* Fix and build lstm related unittests
* Use ./tmp instead of ./ for files created by unittests
This commit is contained in:
Shreeshrii 2019-01-24 12:31:19 +05:30 committed by Stefan Weil
parent 12c1abcb6b
commit bbd23bbfd2
7 changed files with 129 additions and 53 deletions
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14
unittest/Makefile.am
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@ -133,9 +133,12 @@ check_PROGRAMS = \
if ENABLE_TRAINING
check_PROGRAMS += commandlineflags_test
check_PROGRAMS += lstm_recode_test
check_PROGRAMS += lstm_squashed_test
check_PROGRAMS += lstm_test
check_PROGRAMS += unichar_test
check_PROGRAMS += unicharset_test
check_PROGRAMS += unicharcompress_test
check_PROGRAMS += unicharset_test
check_PROGRAMS += validate_grapheme_test
check_PROGRAMS += validate_indic_test
check_PROGRAMS += validate_khmer_test
@ -215,6 +218,15 @@ linlsq_test_LDADD = $(GTEST_LIBS) $(TESS_LIBS)
loadlang_test_SOURCES = loadlang_test.cc
loadlang_test_LDADD = $(GTEST_LIBS) $(TESS_LIBS) $(LEPTONICA_LIBS)
lstm_recode_test_SOURCES = lstm_recode_test.cc
lstm_recode_test_LDADD = $(ABSEIL_LIBS) $(GTEST_LIBS) $(TESS_LIBS) $(TRAINING_LIBS)
lstm_squashed_test_SOURCES = lstm_squashed_test.cc
lstm_squashed_test_LDADD = $(ABSEIL_LIBS) $(GTEST_LIBS) $(TESS_LIBS) $(TRAINING_LIBS)
lstm_test_SOURCES = lstm_test.cc
lstm_test_LDADD = $(ABSEIL_LIBS) $(GTEST_LIBS) $(TESS_LIBS) $(TRAINING_LIBS)
mastertrainer_test_SOURCES = mastertrainer_test.cc
mastertrainer_test_LDADD = $(ABSEIL_LIBS) $(GTEST_LIBS) $(TRAINING_LIBS) $(TESS_LIBS)

2
unittest/include_gunit.h
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@ -17,7 +17,7 @@
#include "fileio.h" // for tesseract::File
#include "gtest/gtest.h"
const char* FLAGS_test_tmpdir = ".";
const char* FLAGS_test_tmpdir = "./tmp";
class file : public tesseract::File {
public:

33
unittest/lstm_recode_test.cc
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@ -1,25 +1,44 @@
// (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.
#include "tesseract/unittest/lstm_test.h"
#include "lstm_test.h"
namespace tesseract {
// Tests that training with unicharset recoding learns faster than without,
// for Korean. This test is split in two, so it can be run sharded.
TEST_F(LSTMTrainerTest, RecodeTestKorBase) {
// A basic single-layer, bi-di 1d LSTM on Korean.
SetupTrainer("[1,1,0,32 Lbx96 O1c1]", "kor-full", "kor.unicharset",
"arialuni.kor.lstmf", false, true, 5e-4, false);
double kor_full_err = TrainIterations(kTrainerIterations);
SetupTrainer("[1,1,0,32 Lbx96 O1c1]", "kor-full", "kor/kor.unicharset",
"kor.Arial_Unicode_MS.exp0.lstmf", false, true, 5e-4, false);
double kor_full_err = TrainIterations(kTrainerIterations * 2);
EXPECT_LT(kor_full_err, 88);
EXPECT_GT(kor_full_err, 85);
// EXPECT_GT(kor_full_err, 85);
}
TEST_F(LSTMTrainerTest, RecodeTestKor) {
// A basic single-layer, bi-di 1d LSTM on Korean.
SetupTrainer("[1,1,0,32 Lbx96 O1c1]", "kor-recode", "kor.unicharset",
"arialuni.kor.lstmf", true, true, 5e-4, false);
SetupTrainer("[1,1,0,32 Lbx96 O1c1]", "kor-recode", "kor/kor.unicharset",
"kor.Arial_Unicode_MS.exp0.lstmf", true, true, 5e-4, false);
double kor_recode_err = TrainIterations(kTrainerIterations);
EXPECT_LT(kor_recode_err, 60);
}
// Tests that the given string encodes and decodes back to the same
// with both recode on and off for Korean.
TEST_F(LSTMTrainerTest, EncodeDecodeBothTestKor) {
TestEncodeDecodeBoth("kor", "한국어 위키백과에 오신 것을 환영합니다!");
}
} // namespace tesseract.

13
unittest/lstm_squashed_test.cc
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@ -1,5 +1,15 @@
// (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.
#include "tesseract/unittest/lstm_test.h"
#include "lstm_test.h"
namespace tesseract {
@ -14,6 +24,7 @@ TEST_F(LSTMTrainerTest, TestSquashed) {
"SQU-2-layer-lstm", /*recode*/ true, /*adam*/ true);
double lstm_2d_err = TrainIterations(kTrainerIterations * 2);
EXPECT_LT(lstm_2d_err, 80);
LOG(INFO) << "********** < 80 ************" ;
TestIntMode(kTrainerIterations);
}

41
unittest/lstm_test.cc
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@ -1,15 +1,24 @@
// (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.
// Generating the training data:
// If the format of the lstmf (ImageData) file changes, the training data will
// have to be regenerated as follows:
// ./tesseract/text2image --xsize=800 --font=Arial \
// --text=tesseract/testdata/lstm_training.txt --leading=32 \
// --outputbase=tesseract/testdata/lstm_training.arial
// ./tesseract tesseract/testdata/lstm_training.arial.tif \
// tesseract/testdata/lstm_training.arial lstm.train \
// --pageseg_mode=6
// have to be regenerated as follows:
//
// Use --xsize 800 for text2image to be similar to original training data.
//
// src/training/tesstrain.sh --fonts_dir /usr/share/fonts --lang eng --linedata_only --noextract_font_properties --langdata_dir ../langdata_lstm --tessdata_dir ../tessdata --output_dir ~/tesseract/test/testdata --fontlist "Arial" --maxpages 10
//
#include "tesseract/unittest/lstm_test.h"
#include "lstm_test.h"
namespace tesseract {
@ -19,15 +28,17 @@ TEST_F(LSTMTrainerTest, BasicTest) {
SetupTrainer(
"[1,32,0,1 Ct5,5,16 Mp4,4 Ct1,1,16 Ct3,3,128 Mp4,1 Ct1,1,64 S2,1 "
"Ct1,1,64O1c1]",
"no-lstm", "eng.unicharset", "lstm_training.arial.lstmf", false, false,
"no-lstm", "eng/eng.unicharset", "eng.Arial.exp0.lstmf", false, false,
2e-4, false);
double non_lstm_err = TrainIterations(kTrainerIterations * 3 / 2);
double non_lstm_err = TrainIterations(kTrainerIterations * 3);
EXPECT_LT(non_lstm_err, 98);
LOG(INFO) << "********** Expected < 98 ************" ;
// A basic single-layer, single direction LSTM.
SetupTrainerEng("[1,1,0,32 Lfx100 O1c1]", "1D-lstm", false, false);
double lstm_uni_err = TrainIterations(kTrainerIterations * 2);
EXPECT_LT(lstm_uni_err, 86);
LOG(INFO) << "********** Expected < 86 ************" ;
// Beats the convolver. (Although it does have a lot more weights, it still
// iterates faster.)
EXPECT_LT(lstm_uni_err, non_lstm_err);
@ -41,6 +52,7 @@ TEST_F(LSTMTrainerTest, ColorTest) {
double lstm_uni_err = TrainIterations(kTrainerIterations);
EXPECT_LT(lstm_uni_err, 85);
EXPECT_GT(lstm_uni_err, 66);
LOG(INFO) << "********** Expected > 66 ** < 85 ************" ;
}
TEST_F(LSTMTrainerTest, BidiTest) {
@ -48,7 +60,7 @@ TEST_F(LSTMTrainerTest, BidiTest) {
SetupTrainerEng("[1,1,0,32 Lbx100 O1c1]", "bidi-lstm", false, false);
double lstm_bi_err = TrainIterations(kTrainerIterations);
EXPECT_LT(lstm_bi_err, 75);
LOG(INFO) << "********** Expected < 75 ************" ;
// Int mode training is dead, so convert the trained network to int and check
// that its error rate is close to the float version.
TestIntMode(kTrainerIterations);
@ -63,6 +75,7 @@ TEST_F(LSTMTrainerTest, Test2D) {
double lstm_2d_err = TrainIterations(kTrainerIterations);
EXPECT_LT(lstm_2d_err, 98);
EXPECT_GT(lstm_2d_err, 90);
LOG(INFO) << "********** Expected > 90 ** < 98 ************" ;
// Int mode training is dead, so convert the trained network to int and check
// that its error rate is close to the float version.
TestIntMode(kTrainerIterations);
@ -76,6 +89,7 @@ TEST_F(LSTMTrainerTest, TestAdam) {
"2-D-2-layer-lstm", false, true);
double lstm_2d_err = TrainIterations(kTrainerIterations);
EXPECT_LT(lstm_2d_err, 70);
LOG(INFO) << "********** Expected < 70 ************" ;
TestIntMode(kTrainerIterations);
}
@ -86,6 +100,7 @@ TEST_F(LSTMTrainerTest, SpeedTest) {
"O1c1]",
"2-D-2-layer-lstm", false, true);
TrainIterations(kTrainerIterations);
LOG(INFO) << "********** *** ************" ;
}
// Tests that two identical networks trained the same get the same results.
@ -121,6 +136,7 @@ TEST_F(LSTMTrainerTest, DeterminismTest) {
EXPECT_FLOAT_EQ(lstm_2d_err_a, lstm_2d_err_b);
EXPECT_FLOAT_EQ(act_error_a, act_error_b);
EXPECT_FLOAT_EQ(char_error_a, char_error_b);
LOG(INFO) << "********** *** ************" ;
}
// The baseline network against which to test the built-in softmax.
@ -130,6 +146,7 @@ TEST_F(LSTMTrainerTest, SoftmaxBaselineTest) {
double lstm_uni_err = TrainIterations(kTrainerIterations * 2);
EXPECT_LT(lstm_uni_err, 60);
EXPECT_GT(lstm_uni_err, 48);
LOG(INFO) << "********** Expected > 48 ** < 60 ************" ;
// Check that it works in int mode too.
TestIntMode(kTrainerIterations);
// If we run TestIntMode again, it tests that int_mode networks can
@ -148,6 +165,7 @@ TEST_F(LSTMTrainerTest, SoftmaxTest) {
SetupTrainerEng("[1,1,0,32 LS96]", "Lstm-+-softmax", false, true);
double lstm_sm_err = TrainIterations(kTrainerIterations * 2);
EXPECT_LT(lstm_sm_err, 49.0);
LOG(INFO) << "********** Expected < 49 ************" ;
// Check that it works in int mode too.
TestIntMode(kTrainerIterations);
}
@ -159,6 +177,7 @@ TEST_F(LSTMTrainerTest, EncodedSoftmaxTest) {
SetupTrainerEng("[1,1,0,32 LE96]", "Lstm-+-softmax", false, true);
double lstm_sm_err = TrainIterations(kTrainerIterations * 2);
EXPECT_LT(lstm_sm_err, 62.0);
LOG(INFO) << "********** Expected < 62 ************" ;
// Check that it works in int mode too.
TestIntMode(kTrainerIterations);
}

76
unittest/lstm_test.h
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@ -1,3 +1,14 @@
// (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.
#ifndef TESSERACT_UNITTEST_LSTM_TEST_H_
#define TESSERACT_UNITTEST_LSTM_TEST_H_
@ -5,18 +16,17 @@
#include <string>
#include <utility>
#include "base/logging.h"
#include "base/stringprintf.h"
#include "file/base/file.h"
#include "file/base/helpers.h"
#include "file/base/path.h"
#include "testing/base/public/googletest.h"
#include "testing/base/public/gunit.h"
#include "include_gunit.h"
#include "absl/strings/str_cat.h"
#include "tesseract/ccutil/unicharset.h"
#include "tesseract/lstm/functions.h"
#include "tesseract/lstm/lstmtrainer.h"
#include "tesseract/training/lang_model_helpers.h"
#include "tprintf.h"
#include "helpers.h"
#include "functions.h"
#include "lang_model_helpers.h"
#include "log.h" // for LOG
#include "lstmtrainer.h"
#include "unicharset.h"
namespace tesseract {
@ -36,32 +46,32 @@ const int kBatchIterations = 1;
class LSTMTrainerTest : public testing::Test {
protected:
LSTMTrainerTest() {}
string TestDataNameToPath(const string& name) {
return file::JoinPath(FLAGS_test_srcdir,
"tesseract/testdata/" + name);
std::string TestDataNameToPath(const std::string& name) {
return file::JoinPath(TESTDATA_DIR,
"" + name);
}
void SetupTrainerEng(const string& network_spec, const string& model_name,
void SetupTrainerEng(const std::string& network_spec, const std::string& model_name,
bool recode, bool adam) {
SetupTrainer(network_spec, model_name, "eng.unicharset",
"lstm_training.arial.lstmf", recode, adam, 5e-4, false);
SetupTrainer(network_spec, model_name, "eng/eng.unicharset",
"eng.Arial.exp0.lstmf", recode, adam, 5e-4, false);
}
void SetupTrainer(const string& network_spec, const string& model_name,
const string& unicharset_file, const string& lstmf_file,
void SetupTrainer(const std::string& network_spec, const std::string& model_name,
const std::string& unicharset_file, const std::string& lstmf_file,
bool recode, bool adam, double learning_rate,
bool layer_specific) {
constexpr char kLang[] = "eng"; // Exact value doesn't matter.
string unicharset_name = TestDataNameToPath(unicharset_file);
std::string unicharset_name = TestDataNameToPath(unicharset_file);
UNICHARSET unicharset;
ASSERT_TRUE(unicharset.load_from_file(unicharset_name.c_str(), false));
string script_dir = file::JoinPath(
FLAGS_test_srcdir, "tesseract/training/langdata");
std::string script_dir = file::JoinPath(
LANGDATA_DIR, "");
GenericVector<STRING> words;
EXPECT_EQ(0, CombineLangModel(unicharset, script_dir, "", FLAGS_test_tmpdir,
kLang, !recode, words, words, words, false,
nullptr, nullptr));
string model_path = file::JoinPath(FLAGS_test_tmpdir, model_name);
string checkpoint_path = model_path + "_checkpoint";
std::string model_path = file::JoinPath(FLAGS_test_tmpdir, model_name);
std::string checkpoint_path = model_path + "_checkpoint";
trainer_.reset(new LSTMTrainer(nullptr, nullptr, nullptr, nullptr,
model_path.c_str(), checkpoint_path.c_str(),
0, 0));
@ -98,10 +108,11 @@ class LSTMTrainerTest : public testing::Test {
iteration = trainer_->training_iteration();
mean_error *= 100.0 / kBatchIterations;
LOG(INFO) << log_str.string();
LOG(INFO) << "Batch error = " << mean_error;
LOG(INFO) << "Best error = " << best_error;
LOG(INFO) << "Mean error = " << mean_error;
if (mean_error < best_error) best_error = mean_error;
} while (iteration < iteration_limit);
LOG(INFO) << "Trainer error rate = " << best_error;
LOG(INFO) << "Trainer error rate = " << best_error << "\n";
return best_error;
}
// Tests for a given number of iterations and returns the char error rate.
@ -122,7 +133,7 @@ class LSTMTrainerTest : public testing::Test {
trainer_->SetIteration(++iteration);
}
mean_error *= 100.0 / max_iterations;
LOG(INFO) << "Tester error rate = " << mean_error;
LOG(INFO) << "Tester error rate = " << mean_error << "\n" ;
return mean_error;
}
// Tests that the current trainer_ can be converted to int mode and still gets
@ -144,18 +155,19 @@ class LSTMTrainerTest : public testing::Test {
// Sets up a trainer with the given language and given recode+ctc condition.
// It then verifies that the given str encodes and decodes back to the same
// string.
void TestEncodeDecode(const string& lang, const string& str, bool recode) {
string unicharset_name = lang + ".unicharset";
void TestEncodeDecode(const std::string& lang, const std::string& str, bool recode) {
std::string unicharset_name = lang + "/" + lang + ".unicharset";
std::string lstmf_name = lang + ".Arial_Unicode_MS.exp0.lstmf";
SetupTrainer("[1,1,0,32 Lbx100 O1c1]", "bidi-lstm", unicharset_name,
"arialuni.kor.lstmf", recode, true, 5e-4, true);
lstmf_name, recode, true, 5e-4, true);
GenericVector<int> labels;
EXPECT_TRUE(trainer_->EncodeString(str.c_str(), &labels));
STRING decoded = trainer_->DecodeLabels(labels);
string decoded_str(&decoded[0], decoded.length());
std::string decoded_str(&decoded[0], decoded.length());
EXPECT_EQ(str, decoded_str);
}
// Calls TestEncodeDeode with both recode on and off.
void TestEncodeDecodeBoth(const string& lang, const string& str) {
void TestEncodeDecodeBoth(const std::string& lang, const std::string& str) {
TestEncodeDecode(lang, str, false);
TestEncodeDecode(lang, str, true);
}

3
unittest/tmp/README.md Normal file
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@ -0,0 +1,3 @@
Directory for holding temporary files created during unittests
Clear it before running `make check`.