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@ -618,6 +618,44 @@ TEST(Layer_LSTM_Test_Accuracy_with_, HiddenParams) |
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normAssert(h_t_reference, outputs[0]); |
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normAssert(h_t_reference, outputs[0]); |
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} |
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} |
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typedef testing::TestWithParam<tuple<int>> Layer_Scale_1d_Test; |
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TEST_P(Layer_Scale_1d_Test, Accuracy) |
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{ |
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int batch_size = get<0>(GetParam()); |
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LayerParams lp; |
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lp.type = "Scale"; |
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lp.name = "scaleLayer"; |
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lp.set("axis", 0); |
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lp.set("mode", "scale"); |
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lp.set("bias_term", false); |
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Ptr<ScaleLayer> layer = ScaleLayer::create(lp); |
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std::vector<int> input_shape = {batch_size, 3}; |
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std::vector<int> output_shape = {batch_size, 3}; |
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if (batch_size == 0){ |
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input_shape.erase(input_shape.begin()); |
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output_shape.erase(output_shape.begin()); |
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} |
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cv::Mat input = cv::Mat(input_shape, CV_32F, 1.0); |
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cv::randn(input, 0.0, 1.0); |
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cv::Mat weight = cv::Mat(output_shape, CV_32F, 2.0); |
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std::vector<Mat> inputs{input, weight}; |
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std::vector<Mat> outputs; |
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cv::Mat output_ref = input.mul(weight); |
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runLayer(layer, inputs, outputs); |
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ASSERT_EQ(shape(output_ref), shape(outputs[0])); |
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normAssert(output_ref, outputs[0]); |
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} |
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INSTANTIATE_TEST_CASE_P(/*nothing*/, Layer_Scale_1d_Test, |
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/*operation*/ Values(0, 1)); |
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typedef testing::TestWithParam<tuple<int, int>> Layer_Gather_1d_Test; |
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typedef testing::TestWithParam<tuple<int, int>> Layer_Gather_1d_Test; |
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TEST_P(Layer_Gather_1d_Test, Accuracy) { |
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TEST_P(Layer_Gather_1d_Test, Accuracy) { |
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