// Generated from rank.mod.py // DO NOT EDIT // clang-format off #include "TestHarness.h" using namespace test_helper; // NOLINT(google-build-using-namespace) namespace generated_tests::rank { const TestModel& get_test_model_1d() { static TestModel model = { .main = { .operands = {{ // input0 .type = TestOperandType::TENSOR_FLOAT32, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({5.0f, 7.0f, 10.0f}) }, { // output0 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {0}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d = TestModelManager::get().add("rank_1d", get_test_model_1d()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_all_inputs_as_internal() { static TestModel model = { .main = { .operands = {{ // input0 .type = TestOperandType::TENSOR_FLOAT32, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({}) }, { // output0 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1}) }, { // input0_new .type = TestOperandType::TENSOR_FLOAT32, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({5.0f, 7.0f, 10.0f}) }, { // placeholder .type = TestOperandType::TENSOR_FLOAT32, .dimensions = {1}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0.0f}) }, { // param .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0}) }}, .operations = {{ .type = TestOperationType::ADD, .inputs = {2, 3, 4}, .outputs = {0} }, { .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {2}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_all_inputs_as_internal = TestModelManager::get().add("rank_1d_all_inputs_as_internal", get_test_model_1d_all_inputs_as_internal()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_int32() { static TestModel model = { .main = { .operands = {{ // input0 .type = TestOperandType::TENSOR_INT32, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({5, 7, 10}) }, { // output0 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {0}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_int32 = TestModelManager::get().add("rank_1d_int32", get_test_model_1d_int32()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_float16() { static TestModel model = { .main = { .operands = {{ // input0 .type = TestOperandType::TENSOR_FLOAT16, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector<_Float16>({5.0f, 7.0f, 10.0f}) }, { // output0 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {0}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_float16 = TestModelManager::get().add("rank_1d_float16", get_test_model_1d_float16()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_float16_all_inputs_as_internal() { static TestModel model = { .main = { .operands = {{ // input0 .type = TestOperandType::TENSOR_FLOAT16, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector<_Float16>({}) }, { // output0 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1}) }, { // input0_new .type = TestOperandType::TENSOR_FLOAT16, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector<_Float16>({5.0f, 7.0f, 10.0f}) }, { // placeholder1 .type = TestOperandType::TENSOR_FLOAT16, .dimensions = {1}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector<_Float16>({0.0f}) }, { // param1 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0}) }}, .operations = {{ .type = TestOperationType::ADD, .inputs = {2, 3, 4}, .outputs = {0} }, { .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {2}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_float16_all_inputs_as_internal = TestModelManager::get().add("rank_1d_float16_all_inputs_as_internal", get_test_model_1d_float16_all_inputs_as_internal()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_quant8() { static TestModel model = { .main = { .operands = {{ // input0 .type = TestOperandType::TENSOR_QUANT8_ASYMM, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 128, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({178, 198, 228}) }, { // output0 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {0}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_quant8 = TestModelManager::get().add("rank_1d_quant8", get_test_model_1d_quant8()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_quant8_all_inputs_as_internal() { static TestModel model = { .main = { .operands = {{ // input0 .type = TestOperandType::TENSOR_QUANT8_ASYMM, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 128, .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({}) }, { // output0 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1}) }, { // input0_new .type = TestOperandType::TENSOR_QUANT8_ASYMM, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 128, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({178, 198, 228}) }, { // placeholder2 .type = TestOperandType::TENSOR_QUANT8_ASYMM, .dimensions = {1}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 128, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({128}) }, { // param2 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0}) }}, .operations = {{ .type = TestOperationType::ADD, .inputs = {2, 3, 4}, .outputs = {0} }, { .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {2}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_quant8_all_inputs_as_internal = TestModelManager::get().add("rank_1d_quant8_all_inputs_as_internal", get_test_model_1d_quant8_all_inputs_as_internal()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_quant8_signed() { static TestModel model = { .main = { .operands = {{ // input0 .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({50, 70, 100}) }, { // output0 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {0}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_quant8_signed = TestModelManager::get().add("rank_1d_quant8_signed", get_test_model_1d_quant8_signed()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_quant8_signed_all_inputs_as_internal() { static TestModel model = { .main = { .operands = {{ // input0 .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({}) }, { // output0 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1}) }, { // input0_new .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({50, 70, 100}) }, { // placeholder3 .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED, .dimensions = {1}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0}) }, { // param3 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0}) }}, .operations = {{ .type = TestOperationType::ADD, .inputs = {2, 3, 4}, .outputs = {0} }, { .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {2}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_quant8_signed_all_inputs_as_internal = TestModelManager::get().add("rank_1d_quant8_signed_all_inputs_as_internal", get_test_model_1d_quant8_signed_all_inputs_as_internal()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_2() { static TestModel model = { .main = { .operands = {{ // input01 .type = TestOperandType::TENSOR_FLOAT32, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}) }, { // output01 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {0}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_2 = TestModelManager::get().add("rank_1d_2", get_test_model_1d_2()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_all_inputs_as_internal_2() { static TestModel model = { .main = { .operands = {{ // input01 .type = TestOperandType::TENSOR_FLOAT32, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({}) }, { // output01 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2}) }, { // input01_new .type = TestOperandType::TENSOR_FLOAT32, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}) }, { // placeholder4 .type = TestOperandType::TENSOR_FLOAT32, .dimensions = {1}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0.0f}) }, { // param4 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0}) }}, .operations = {{ .type = TestOperationType::ADD, .inputs = {2, 3, 4}, .outputs = {0} }, { .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {2}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_all_inputs_as_internal_2 = TestModelManager::get().add("rank_1d_all_inputs_as_internal_2", get_test_model_1d_all_inputs_as_internal_2()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_int32_2() { static TestModel model = { .main = { .operands = {{ // input01 .type = TestOperandType::TENSOR_INT32, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1, 2, 3, 4, 5, 6}) }, { // output01 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {0}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_int32_2 = TestModelManager::get().add("rank_1d_int32_2", get_test_model_1d_int32_2()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_float16_2() { static TestModel model = { .main = { .operands = {{ // input01 .type = TestOperandType::TENSOR_FLOAT16, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}) }, { // output01 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {0}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_float16_2 = TestModelManager::get().add("rank_1d_float16_2", get_test_model_1d_float16_2()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_float16_all_inputs_as_internal_2() { static TestModel model = { .main = { .operands = {{ // input01 .type = TestOperandType::TENSOR_FLOAT16, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector<_Float16>({}) }, { // output01 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2}) }, { // input01_new .type = TestOperandType::TENSOR_FLOAT16, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}) }, { // placeholder5 .type = TestOperandType::TENSOR_FLOAT16, .dimensions = {1}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector<_Float16>({0.0f}) }, { // param5 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0}) }}, .operations = {{ .type = TestOperationType::ADD, .inputs = {2, 3, 4}, .outputs = {0} }, { .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {2}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_float16_all_inputs_as_internal_2 = TestModelManager::get().add("rank_1d_float16_all_inputs_as_internal_2", get_test_model_1d_float16_all_inputs_as_internal_2()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_quant8_2() { static TestModel model = { .main = { .operands = {{ // input01 .type = TestOperandType::TENSOR_QUANT8_ASYMM, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 128, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({138, 148, 158, 168, 178, 188}) }, { // output01 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {0}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_quant8_2 = TestModelManager::get().add("rank_1d_quant8_2", get_test_model_1d_quant8_2()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_quant8_all_inputs_as_internal_2() { static TestModel model = { .main = { .operands = {{ // input01 .type = TestOperandType::TENSOR_QUANT8_ASYMM, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 128, .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({}) }, { // output01 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2}) }, { // input01_new .type = TestOperandType::TENSOR_QUANT8_ASYMM, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 128, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({138, 148, 158, 168, 178, 188}) }, { // placeholder6 .type = TestOperandType::TENSOR_QUANT8_ASYMM, .dimensions = {1}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 128, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({128}) }, { // param6 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0}) }}, .operations = {{ .type = TestOperationType::ADD, .inputs = {2, 3, 4}, .outputs = {0} }, { .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {2}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_quant8_all_inputs_as_internal_2 = TestModelManager::get().add("rank_1d_quant8_all_inputs_as_internal_2", get_test_model_1d_quant8_all_inputs_as_internal_2()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_quant8_signed_2() { static TestModel model = { .main = { .operands = {{ // input01 .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({10, 20, 30, 40, 50, 60}) }, { // output01 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {0}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_quant8_signed_2 = TestModelManager::get().add("rank_1d_quant8_signed_2", get_test_model_1d_quant8_signed_2()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_1d_quant8_signed_all_inputs_as_internal_2() { static TestModel model = { .main = { .operands = {{ // input01 .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({}) }, { // output01 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2}) }, { // input01_new .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({10, 20, 30, 40, 50, 60}) }, { // placeholder7 .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED, .dimensions = {1}, .numberOfConsumers = 1, .scale = 0.1f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0}) }, { // param7 .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::CONSTANT_COPY, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({0}) }}, .operations = {{ .type = TestOperationType::ADD, .inputs = {2, 3, 4}, .outputs = {0} }, { .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }}, .inputIndexes = {2}, .outputIndexes = {1} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_1d_quant8_signed_all_inputs_as_internal_2 = TestModelManager::get().add("rank_1d_quant8_signed_all_inputs_as_internal_2", get_test_model_1d_quant8_signed_all_inputs_as_internal_2()); } // namespace generated_tests::rank namespace generated_tests::rank { const TestModel& get_test_model_internal_output() { static TestModel model = { .main = { .operands = {{ // input02 .type = TestOperandType::TENSOR_FLOAT32, .dimensions = {2, 3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}) }, { // rank_internal_result .type = TestOperandType::INT32, .dimensions = {}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({}) }, { // input03 .type = TestOperandType::TENSOR_INT32, .dimensions = {3}, .numberOfConsumers = 1, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2, 3, 4}) }, { // output .type = TestOperandType::TENSOR_INT32, .dimensions = {2, 3, 4}, .numberOfConsumers = 0, .scale = 0.0f, .zeroPoint = 0, .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, .channelQuant = {}, .isIgnored = false, .data = TestBuffer::createFromVector({2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2}) }}, .operations = {{ .type = TestOperationType::RANK, .inputs = {0}, .outputs = {1} }, { .type = TestOperationType::FILL, .inputs = {2, 1}, .outputs = {3} }}, .inputIndexes = {0, 2}, .outputIndexes = {3} }, .referenced = {}, .isRelaxed = false, .expectedMultinomialDistributionTolerance = 0, .expectFailure = false, .minSupportedVersion = TestHalVersion::V1_3 }; return model; } const auto dummy_test_model_internal_output = TestModelManager::get().add("rank_internal_output", get_test_model_internal_output()); } // namespace generated_tests::rank