Update for style check
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@@ -72,7 +72,8 @@ BOOST_AUTO_TEST_CASE(AdaBoostOutputDimensionTest)
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mlpackMain();
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// Check that number of predicted labels is equal to the input test points.
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BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::Row<size_t>>("output").n_cols, testSize);
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BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::Row<size_t>>("output").n_cols,
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testSize);
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BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::Row<size_t>>("output").n_rows, 1);
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}
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@@ -106,7 +107,8 @@ BOOST_AUTO_TEST_CASE(AdaBoostModelReuseTest)
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ResetSetting();
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SetInputParam("test", std::move(testData));
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SetInputParam("input_model", std::move(CLI::GetParam<AdaBoostModel>("output_model")));
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SetInputParam("input_model",
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std::move(CLI::GetParam<AdaBoostModel>("output_model")));
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mlpackMain();
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@@ -192,7 +194,8 @@ BOOST_AUTO_TEST_CASE(AdaBoostTrainingDataOrModelTest)
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mlpackMain();
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SetInputParam("input_model", std::move(CLI::GetParam<AdaBoostModel>("output_model")));
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SetInputParam("input_model",
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std::move(CLI::GetParam<AdaBoostModel>("output_model")));
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Log::Fatal.ignoreInput = true;
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BOOST_REQUIRE_THROW(mlpackMain(), std::runtime_error);
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@@ -248,7 +251,8 @@ BOOST_AUTO_TEST_CASE(AdaBoostWeakLearnerIgnoredTest)
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ResetSetting();
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// Default value is Decision Stump
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SetInputParam("input_model", std::move(CLI::GetParam<AdaBoostModel>("output_model")));
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SetInputParam("input_model",
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std::move(CLI::GetParam<AdaBoostModel>("output_model")));
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SetInputParam("weak_learner", std::string("perceptron"));
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const string weakLearner = CLI::GetParam<string>("weak_learner");
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