Open-sources a unit test.
PiperOrigin-RevId: 493184055
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@ -38,10 +38,7 @@ limitations under the License.
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#include "mediapipe/tasks/cc/text/text_classifier/text_classifier_test_utils.h"
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#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
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namespace mediapipe {
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namespace tasks {
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namespace text {
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namespace text_classifier {
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namespace mediapipe::tasks::text::text_classifier {
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namespace {
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using ::mediapipe::file::JoinPath;
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@ -88,6 +85,8 @@ void ExpectApproximatelyEqual(const TextClassifierResult& actual,
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}
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}
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} // namespace
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class TextClassifierTest : public tflite_shims::testing::Test {};
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TEST_F(TextClassifierTest, CreateSucceedsWithBertModel) {
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@ -217,8 +216,42 @@ TEST_F(TextClassifierTest, TextClassifierWithStringToBool) {
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MP_ASSERT_OK(classifier->Close());
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}
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} // namespace
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} // namespace text_classifier
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} // namespace text
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} // namespace tasks
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} // namespace mediapipe
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TEST_F(TextClassifierTest, BertLongPositive) {
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std::stringstream ss_for_positive_review;
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ss_for_positive_review
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<< "it's a charming and often affecting journey and this is a long";
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for (int i = 0; i < kMaxSeqLen; ++i) {
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ss_for_positive_review << " long";
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}
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ss_for_positive_review << " movie review";
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auto options = std::make_unique<TextClassifierOptions>();
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options->base_options.model_asset_path = GetFullPath(kTestBertModelPath);
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MP_ASSERT_OK_AND_ASSIGN(std::unique_ptr<TextClassifier> classifier,
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TextClassifier::Create(std::move(options)));
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MP_ASSERT_OK_AND_ASSIGN(TextClassifierResult result,
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classifier->Classify(ss_for_positive_review.str()));
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TextClassifierResult expected;
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std::vector<Category> categories;
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// Predicted scores are slightly different on Mac OS.
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#ifdef __APPLE__
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categories.push_back(
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{/*index=*/1, /*score=*/0.974181, /*category_name=*/"positive"});
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categories.push_back(
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{/*index=*/0, /*score=*/0.025819, /*category_name=*/"negative"});
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#else
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categories.push_back(
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{/*index=*/1, /*score=*/0.985889, /*category_name=*/"positive"});
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categories.push_back(
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{/*index=*/0, /*score=*/0.014112, /*category_name=*/"negative"});
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#endif // __APPLE__
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expected.classifications.emplace_back(
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Classifications{/*categories=*/categories,
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/*head_index=*/0,
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/*head_name=*/"probability"});
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ExpectApproximatelyEqual(result, expected);
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MP_ASSERT_OK(classifier->Close());
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}
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} // namespace mediapipe::tasks::text::text_classifier
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