[GNA] Added mode for Split and concat tests (#7773)
* added gna_mode to existing tests * removed from tests_deprecated * Commit for CI restart
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@ -15,8 +15,10 @@ namespace {
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InferenceEngine::Precision::FP32
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InferenceEngine::Precision::FP32
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};
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};
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std::map<std::string, std::string> config = {
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std::vector<std::map<std::string, std::string>> additionalConfig = {
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{"GNA_COMPACT_MODE", "NO"}
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{ {"GNA_COMPACT_MODE", "NO"} },
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{ {"GNA_COMPACT_MODE", "NO"},
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{"GNA_DEVICE_MODE", "GNA_SW_FP32"}}
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};
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};
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std::vector<size_t> inputSizes = {
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std::vector<size_t> inputSizes = {
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@ -37,6 +39,6 @@ namespace {
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::testing::Values(CommonTestUtils::DEVICE_GNA),
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::testing::Values(CommonTestUtils::DEVICE_GNA),
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::testing::ValuesIn(inputSizes),
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::testing::ValuesIn(inputSizes),
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::testing::ValuesIn(hiddenSizes),
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::testing::ValuesIn(hiddenSizes),
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::testing::Values(config)),
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::testing::ValuesIn(additionalConfig)),
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ConcatQuantDuringMemoryRequantTest::getTestCaseName);
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ConcatQuantDuringMemoryRequantTest::getTestCaseName);
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} // namespace
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} // namespace
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@ -22,9 +22,15 @@ const std::vector<InferenceEngine::Precision> netPrecisions = {
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InferenceEngine::Precision::FP16,
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InferenceEngine::Precision::FP16,
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};
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};
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std::map<std::string, std::string> additional_config = {
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std::vector<std::map<std::string, std::string>> additional_config = {
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{
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{"GNA_DEVICE_MODE", "GNA_SW_EXACT"},
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{"GNA_DEVICE_MODE", "GNA_SW_EXACT"},
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{"GNA_COMPACT_MODE", "NO"},
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{"GNA_COMPACT_MODE", "NO"}
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},
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{
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{"GNA_DEVICE_MODE", "GNA_SW_FP32"},
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{"GNA_COMPACT_MODE", "NO"}
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}
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};
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};
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INSTANTIATE_TEST_SUITE_P(smoke_concat_first_input, ConcatFirstInputTest,
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INSTANTIATE_TEST_SUITE_P(smoke_concat_first_input, ConcatFirstInputTest,
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@ -32,7 +38,7 @@ INSTANTIATE_TEST_SUITE_P(smoke_concat_first_input, ConcatFirstInputTest,
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::testing::ValuesIn(inShapes),
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::testing::ValuesIn(inShapes),
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::testing::ValuesIn(netPrecisions),
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::testing::ValuesIn(netPrecisions),
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::testing::Values(CommonTestUtils::DEVICE_GNA),
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::testing::Values(CommonTestUtils::DEVICE_GNA),
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::testing::Values(additional_config)),
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::testing::ValuesIn(additional_config)),
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ConcatFirstInputTest::getTestCaseName);
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ConcatFirstInputTest::getTestCaseName);
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} //namespace
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} //namespace
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@ -27,10 +27,17 @@ std::vector<size_t> constant_sizes_unaligned = {
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99
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99
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};
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};
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std::map<std::string, std::string> additional_config = {
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std::vector<std::map<std::string, std::string>> additional_config = {
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{
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{"GNA_COMPACT_MODE", "NO"},
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{"GNA_COMPACT_MODE", "NO"},
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{"GNA_DEVICE_MODE", "GNA_SW_EXACT"},
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{"GNA_DEVICE_MODE", "GNA_SW_EXACT"},
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{"GNA_SCALE_FACTOR_0", "3276.8"},
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{"GNA_SCALE_FACTOR_0", "3276.8"}
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},
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{
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{"GNA_COMPACT_MODE", "NO"},
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{"GNA_DEVICE_MODE", "GNA_SW_FP32"},
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{"GNA_SCALE_FACTOR_0", "3276.8"}
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},
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};
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};
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} // namespace
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} // namespace
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@ -40,7 +47,7 @@ INSTANTIATE_TEST_SUITE_P(I_aligned_C_aligned, MultipleConcatTest,
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::testing::Values(InferenceEngine::Precision::FP32),
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::testing::Values(InferenceEngine::Precision::FP32),
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::testing::ValuesIn(input_sizes_aligned),
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::testing::ValuesIn(input_sizes_aligned),
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::testing::ValuesIn(constant_sizes_aligned),
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::testing::ValuesIn(constant_sizes_aligned),
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::testing::Values(additional_config)),
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::testing::ValuesIn(additional_config)),
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MultipleConcatTest::getTestCaseName);
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MultipleConcatTest::getTestCaseName);
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INSTANTIATE_TEST_SUITE_P(I_aligned_C_unaligned, MultipleConcatTest,
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INSTANTIATE_TEST_SUITE_P(I_aligned_C_unaligned, MultipleConcatTest,
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@ -49,7 +56,7 @@ INSTANTIATE_TEST_SUITE_P(I_aligned_C_unaligned, MultipleConcatTest,
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::testing::Values(InferenceEngine::Precision::FP32),
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::testing::Values(InferenceEngine::Precision::FP32),
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::testing::ValuesIn(input_sizes_aligned),
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::testing::ValuesIn(input_sizes_aligned),
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::testing::ValuesIn(constant_sizes_unaligned),
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::testing::ValuesIn(constant_sizes_unaligned),
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::testing::Values(additional_config)),
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::testing::ValuesIn(additional_config)),
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MultipleConcatTest::getTestCaseName);
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MultipleConcatTest::getTestCaseName);
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INSTANTIATE_TEST_SUITE_P(I_unaligned_C_aligned, MultipleConcatTest,
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INSTANTIATE_TEST_SUITE_P(I_unaligned_C_aligned, MultipleConcatTest,
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@ -58,7 +65,7 @@ INSTANTIATE_TEST_SUITE_P(I_unaligned_C_aligned, MultipleConcatTest,
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::testing::Values(InferenceEngine::Precision::FP32),
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::testing::Values(InferenceEngine::Precision::FP32),
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::testing::ValuesIn(input_sizes_unaligned),
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::testing::ValuesIn(input_sizes_unaligned),
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::testing::ValuesIn(constant_sizes_aligned),
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::testing::ValuesIn(constant_sizes_aligned),
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::testing::Values(additional_config)),
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::testing::ValuesIn(additional_config)),
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MultipleConcatTest::getTestCaseName);
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MultipleConcatTest::getTestCaseName);
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INSTANTIATE_TEST_SUITE_P(I_unaligned_C_unaligned, MultipleConcatTest,
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INSTANTIATE_TEST_SUITE_P(I_unaligned_C_unaligned, MultipleConcatTest,
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@ -67,6 +74,6 @@ INSTANTIATE_TEST_SUITE_P(I_unaligned_C_unaligned, MultipleConcatTest,
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::testing::Values(InferenceEngine::Precision::FP32),
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::testing::Values(InferenceEngine::Precision::FP32),
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::testing::ValuesIn(input_sizes_unaligned),
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::testing::ValuesIn(input_sizes_unaligned),
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::testing::ValuesIn(constant_sizes_unaligned),
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::testing::ValuesIn(constant_sizes_unaligned),
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::testing::Values(additional_config)),
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::testing::ValuesIn(additional_config)),
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MultipleConcatTest::getTestCaseName);
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MultipleConcatTest::getTestCaseName);
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} // namespace SubgraphTestsDefinitions
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} // namespace SubgraphTestsDefinitions
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@ -10,13 +10,17 @@ namespace SubgraphTestsDefinitions {
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std::string targetName;
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std::string targetName;
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size_t inputSize;
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size_t inputSize;
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size_t hiddenSize;
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size_t hiddenSize;
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std::tie(netPrecision, targetName, inputSize, hiddenSize, std::ignore) = obj.param;
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std::map<std::string, std::string> config;
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std::tie(netPrecision, targetName, inputSize, hiddenSize, config) = obj.param;
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std::ostringstream results;
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std::ostringstream results;
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results << "netPRC=" << netPrecision.name() << "_";
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results << "netPRC=" << netPrecision.name() << "_";
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results << "IS=" << inputSize << "_";
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results << "IS=" << inputSize << "_";
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results << "HS=" << hiddenSize << "_";
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results << "HS=" << hiddenSize << "_";
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results << "targetDevice=" << targetName;
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results << "targetDevice=" << targetName;
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for (auto const& configItem : config) {
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results << "_configItem=" << configItem.second;
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}
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return results.str();
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return results.str();
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}
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}
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@ -18,7 +18,9 @@ std::string ConcatFirstInputTest::getTestCaseName(const testing::TestParamInfo<c
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result << "IS=" << CommonTestUtils::vec2str(inputShapes) << "_";
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result << "IS=" << CommonTestUtils::vec2str(inputShapes) << "_";
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result << "netPRC=" << netPrecision.name() << "_";
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result << "netPRC=" << netPrecision.name() << "_";
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result << "targetDevice=" << targetDevice;
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result << "targetDevice=" << targetDevice;
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for (auto const& configItem : additional_config) {
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result << "_configItem=" << configItem.first << "_" << configItem.second;
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}
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return result.str();
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return result.str();
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}
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}
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@ -20,6 +20,9 @@ std::string MultipleConcatTest::getTestCaseName(const testing::TestParamInfo<mul
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result << "IS=" << inputSize << "_";
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result << "IS=" << inputSize << "_";
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result << "CS=" << constantSize << "_";
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result << "CS=" << constantSize << "_";
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result << "targetDevice=" << targetDevice;
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result << "targetDevice=" << targetDevice;
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for (auto const& configItem : config) {
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result << "_configItem=" << configItem.second;
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}
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return result.str();
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return result.str();
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}
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}
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@ -41,22 +41,6 @@ static std::string getTestName(testing::TestParamInfo<FP32TestParams> obj) {
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return "channels_" + std::to_string(obj.param.nChannels) + "_" + (obj.param.eltwise_type == FP32TestParams::eSumm ? "summ" : "mull");
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return "channels_" + std::to_string(obj.param.nChannels) + "_" + (obj.param.eltwise_type == FP32TestParams::eSumm ? "summ" : "mull");
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}
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}
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TEST_P(GNAFP32ParametricTest, SplitFollowedByEltwiseMulOnAllignedCPU) {
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auto c = GetParam().nChannels;
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auto isMull = GetParam().eltwise_type == FP32TestParams::eMul;
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std::vector<float> input_data1(c, 3.0);
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std::vector<float> input_data2(c, 2.0);
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std::vector<float> input_data;
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input_data.insert(input_data.end(), input_data1.begin(), input_data1.end());
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input_data.insert(input_data.end(), input_data2.begin(), input_data2.end());
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std::vector<float> expected_result(c, isMull ? 6.0 : 5.0);
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assert_that().onInferModel(EltwiseAfterSplitModel(c, isMull))
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.inNotCompactMode().gna().propagate_forward().onCPU()
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.called_with().input("input_1", input_data).equals_to(expected_result);
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}
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FP32TestParams gna_fp32_test_params[] = {
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FP32TestParams gna_fp32_test_params[] = {
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{7, FP32TestParams::eMul},
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{7, FP32TestParams::eMul},
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{7, FP32TestParams::eSumm},
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{7, FP32TestParams::eSumm},
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@ -106,49 +90,6 @@ TEST_F(FP32NonQuantizedTest, SliceFollowedBy2FCsAnd2EltwisesOnCPU) {
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.called_with_input_and_expected_output(input_data, expected_result);
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.called_with_input_and_expected_output(input_data, expected_result);
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}
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}
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TEST_F(FP32NonQuantizedTest, SplitAfterFCFollowedByFCAndEltwiseOnCPU) {
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std::vector<float> input_data = {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
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1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0};
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std::vector<float> expected_result = {232.0, 232.0, 232.0, 232.0, 232.0,
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232.0, 232.0, 232.0, 232.0, 232.0};
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assert_that().onInferModel(FCBeforeSplitModel())
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.inNotCompactMode().gna().propagate_forward().onCPU()
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.called_with_input_and_expected_output(input_data, expected_result);
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}
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TEST_F(FP32NonQuantizedTest, ConcatPropagateForwardWithSuccessOnCPU) {
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std::vector<float> input_data = {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
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1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0};
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std::vector<float> expected_result = {121.0, 121.0, 121.0, 121.0, 121.0,
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121.0, 121.0, 121.0, 121.0, 121.0,
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121.0, 121.0, 121.0, 121.0, 121.0,
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121.0, 121.0, 121.0, 121.0, 121.0};
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assert_that().onInferModel(concatModel())
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.inNotCompactMode().gna().propagate_forward().onCPU()
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.called_with_input_and_expected_output(input_data, expected_result);
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}
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TEST_F(FP32NonQuantizedTest, DoubleConcatPropagateForwardWithSuccessOnCPU) {
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std::vector<float> input_data = {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
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1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
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1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
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1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0};
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std::vector<float> expected_result = {141.0, 141.0, 141.0, 141.0, 141.0,
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141.0, 141.0, 141.0, 141.0, 141.0,
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141.0, 141.0, 141.0, 141.0, 141.0,
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141.0, 141.0, 141.0, 141.0, 141.0,
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141.0, 141.0, 141.0, 141.0, 141.0,
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141.0, 141.0, 141.0, 141.0, 141.0,
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141.0, 141.0, 141.0, 141.0, 141.0,
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141.0, 141.0, 141.0, 141.0, 141.0};
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assert_that().onInferModel(doubleConcatModel())
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.inNotCompactMode().gna().propagate_forward().onCPU()
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.called_with_input_and_expected_output(input_data, expected_result);
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}
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TEST_F(FP32NonQuantizedTest, multiple_inputs_correct_results) {
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TEST_F(FP32NonQuantizedTest, multiple_inputs_correct_results) {
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std::vector<float> input_data = {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0};
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std::vector<float> input_data = {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0};
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std::vector<float> input2_data = {2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0};
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std::vector<float> input2_data = {2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0};
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@ -301,19 +242,6 @@ TEST_F(FP32NonQuantizedTest, ScaleShiftWithBroadcastSupported) {
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.called_with_input_and_expected_output(input_data, expected_result);
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.called_with_input_and_expected_output(input_data, expected_result);
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}
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}
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TEST_F(FP32NonQuantizedTest, ConcatWithConstInputPropagatedForward) {
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std::vector<float> input_data = {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0};
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std::vector<float> expected_result = {121.0, 121.0, 121.0, 121.0, 121.0,
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121.0, 121.0, 121.0, 121.0, 121.0,
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121.0, 121.0, 121.0, 121.0, 121.0,
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121.0, 121.0, 121.0, 121.0, 121.0};
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assert_that().onInferModel(concatModelWithConstLayer())
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.inNotCompactMode().gna().propagate_forward().onCPU()
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.called_with_input(input_data).equals_to(expected_result);
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}
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TEST_F(FP32NonQuantizedTest, InputSplitConcatPropagateForward) {
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TEST_F(FP32NonQuantizedTest, InputSplitConcatPropagateForward) {
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std::vector<float> input_data(64, 1.0f);
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std::vector<float> input_data(64, 1.0f);
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std::vector<float> expected_result(10, 64.f);
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std::vector<float> expected_result(10, 64.f);
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@ -696,4 +624,3 @@ TEST_F(FP32NonQuantizedTest, ReshapeConvolutionLessThan48Filters) {
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.called_with_input(input_data)
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.called_with_input(input_data)
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.equals_to(expected_result);
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.equals_to(expected_result);
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}
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}
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