diff options
Diffstat (limited to 'nn')
20 files changed, 181 insertions, 939 deletions
diff --git a/nn/common/Utils.cpp b/nn/common/Utils.cpp index fedc8cb30..4e4d0e06a 100644 --- a/nn/common/Utils.cpp +++ b/nn/common/Utils.cpp @@ -26,7 +26,10 @@ #include <sys/system_properties.h> #include <algorithm> +#include <functional> +#include <iostream> #include <limits> +#include <numeric> #include <set> #include <string> #include <tuple> @@ -1509,8 +1512,10 @@ int validateOperation(ANeuralNetworksOperationType opType, uint32_t inputCount, logInvalidInOutNumber(1, 1); return ANEURALNETWORKS_BAD_DATA; } - auto inputType = operands[inputIndexes[0]].type; - auto outputType = operands[outputIndexes[0]].type; + auto inputOperand = operands[inputIndexes[0]]; + auto outputOperand = operands[outputIndexes[0]]; + auto inputType = inputOperand.type; + auto outputType = outputOperand.type; std::vector<OperandType> inExpectedTypes; std::vector<OperandType> outExpectedTypes; if ((inputType == OperandType::TENSOR_FLOAT16 || @@ -1536,6 +1541,19 @@ int validateOperation(ANeuralNetworksOperationType opType, uint32_t inputCount, LOG(ERROR) << "Unsupported data type for operation " << getOperationName(opType); return ANEURALNETWORKS_BAD_DATA; } + // Validate that output shape is equal to input shape if dimensions + // are already known. + auto getNumberOfElements = [](const hardware::hidl_vec<uint32_t>& dims) { + if (dims.size() == 0) { + return 0; + } + return std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<>()); + }; + if (inputOperand.dimensions.size() != 0 && outputOperand.dimensions.size() != 0 && + getNumberOfElements(outputOperand.dimensions) != 0 && + inputOperand.dimensions != outputOperand.dimensions) { + return ANEURALNETWORKS_BAD_DATA; + } return validateOperationOperandTypes(operands, inputCount, inputIndexes, inExpectedTypes, outputCount, outputIndexes, outExpectedTypes); diff --git a/nn/runtime/ExecutionBuilder.cpp b/nn/runtime/ExecutionBuilder.cpp index 61e320f9a..d65d96446 100644 --- a/nn/runtime/ExecutionBuilder.cpp +++ b/nn/runtime/ExecutionBuilder.cpp @@ -876,7 +876,11 @@ std::vector<OutputShape> ExecutionBuilder::getInitialOutputShapes() const { std::vector<OutputShape> outputShapes(mOutputs.size()); std::transform(mOutputs.begin(), mOutputs.end(), outputShapes.begin(), [](const auto& x) -> OutputShape { - return {.dimensions = x.dimensions(), .isSufficient = true}; + hidl_vec<uint32_t> dimensions; + if (x.state() != ModelArgumentInfo::HAS_NO_VALUE) { + dimensions = x.dimensions(); + } + return {.dimensions = std::move(dimensions), .isSufficient = true}; }); return outputShapes; } diff --git a/nn/runtime/test/fuzzing/TestRandomGraph.cpp b/nn/runtime/test/fuzzing/TestRandomGraph.cpp index 55c6542f1..2c8024a22 100644 --- a/nn/runtime/test/fuzzing/TestRandomGraph.cpp +++ b/nn/runtime/test/fuzzing/TestRandomGraph.cpp @@ -485,7 +485,7 @@ const AccuracyCriteria kStrictCriteria = { // broadcast or elementwise, e.g ADD, FLOOR. const AccuracyCriteria kMediumCriteria = { .float32 = {.bias = 1e-6f, .mse = 1e-8f, .atol = 1e-5f, .rtol = 1e-5f}, - .float16 = {.bias = 1e-3f, .mse = 1e-6f, .atol = 1e-2f, .rtol = 1e-2f}, + .float16 = {.bias = 1e-3f, .mse = 1e-5f, .atol = 1e-2f, .rtol = 1e-2f}, .int32 = {.atol = 1}, .quant8Asymm = {.bias = 1.2, .mse = 1.2, .atol = 2}, .quant8AsymmSigned = {.bias = 1.2, .mse = 1.2, .atol = 2}, diff --git a/nn/runtime/test/fuzzing/operation_signatures/Elementwise.cpp b/nn/runtime/test/fuzzing/operation_signatures/Elementwise.cpp index 567ff0581..d84727d95 100644 --- a/nn/runtime/test/fuzzing/operation_signatures/Elementwise.cpp +++ b/nn/runtime/test/fuzzing/operation_signatures/Elementwise.cpp @@ -131,41 +131,51 @@ DEFINE_ELEMENTWISE_WITH_QUANT_OUTPUT_SIGNATURE(LOGISTIC, V1_3, /*scale=*/1.f / 2 DEFINE_ELEMENTWISE_WITH_QUANT_OUTPUT_SIGNATURE(TANH, V1_3, /*scale=*/1.f / 128, /*zeroPoint=*/0, TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED); +static void castingOpConstructor(TestOperandType dataType, uint32_t rank, RandomOperation* op) { + sameDimensionOpConstructor(dataType, rank, op); + + // If it is casting to/from a FP16 data type, the source/destination should have a scale + // representable in FP16 to avoid precision loss. + if (op->inputs[0]->dataType == TestOperandType::TENSOR_FLOAT16) { + op->outputs[0]->scale = static_cast<_Float16>(op->outputs[0]->scale); + } else if (op->outputs[0]->dataType == TestOperandType::TENSOR_FLOAT16) { + op->inputs[0]->scale = static_cast<_Float16>(op->inputs[0]->scale); + } +} + // Operations with output data type different from input. -#define DEFINE_ELEMENTWISE_WITH_TYPED_OUTPUT_SIGNATURE(op, ver, outType, ...) \ - DEFINE_OPERATION_SIGNATURE(op##_##outType##_##ver){ \ - .opType = TestOperationType::op, \ - .supportedDataTypes = {__VA_ARGS__}, \ - .supportedRanks = {1, 2, 3, 4}, \ - .version = TestHalVersion::ver, \ - .inputs = {INPUT_DEFAULT}, \ - .outputs = {OUTPUT_TYPED(TestOperandType::outType)}, \ - .constructor = sameDimensionOpConstructor}; - -DEFINE_ELEMENTWISE_WITH_TYPED_OUTPUT_SIGNATURE(DEQUANTIZE, V1_0, /*outType=*/TENSOR_FLOAT32, - TestOperandType::TENSOR_QUANT8_ASYMM); +#define DEFINE_QUANTIZATION_OP_SIGNATURE(op, ver, outType, ...) \ + DEFINE_OPERATION_SIGNATURE(op##_##outType##_##ver){ \ + .opType = TestOperationType::op, \ + .supportedDataTypes = {__VA_ARGS__}, \ + .supportedRanks = {1, 2, 3, 4}, \ + .version = TestHalVersion::ver, \ + .inputs = {INPUT_DEFAULT}, \ + .outputs = {OUTPUT_TYPED(TestOperandType::outType)}, \ + .constructor = castingOpConstructor}; -DEFINE_ELEMENTWISE_WITH_TYPED_OUTPUT_SIGNATURE(DEQUANTIZE, V1_2, /*outType=*/TENSOR_FLOAT32, - TestOperandType::TENSOR_QUANT8_SYMM); +DEFINE_QUANTIZATION_OP_SIGNATURE(DEQUANTIZE, V1_0, /*outType=*/TENSOR_FLOAT32, + TestOperandType::TENSOR_QUANT8_ASYMM); -DEFINE_ELEMENTWISE_WITH_TYPED_OUTPUT_SIGNATURE(DEQUANTIZE, V1_2, /*outType=*/TENSOR_FLOAT16, - TestOperandType::TENSOR_QUANT8_ASYMM, - TestOperandType::TENSOR_QUANT8_SYMM); +DEFINE_QUANTIZATION_OP_SIGNATURE(DEQUANTIZE, V1_2, /*outType=*/TENSOR_FLOAT32, + TestOperandType::TENSOR_QUANT8_SYMM); -DEFINE_ELEMENTWISE_WITH_TYPED_OUTPUT_SIGNATURE(DEQUANTIZE, V1_3, /*outType=*/TENSOR_FLOAT32, - TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED); +DEFINE_QUANTIZATION_OP_SIGNATURE(DEQUANTIZE, V1_2, /*outType=*/TENSOR_FLOAT16, + TestOperandType::TENSOR_QUANT8_ASYMM, + TestOperandType::TENSOR_QUANT8_SYMM); -DEFINE_ELEMENTWISE_WITH_TYPED_OUTPUT_SIGNATURE(DEQUANTIZE, V1_3, /*outType=*/TENSOR_FLOAT16, - TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED); +DEFINE_QUANTIZATION_OP_SIGNATURE(DEQUANTIZE, V1_3, /*outType=*/TENSOR_FLOAT32, + TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED); -DEFINE_ELEMENTWISE_WITH_TYPED_OUTPUT_SIGNATURE(QUANTIZE, V1_2, /*outType=*/TENSOR_QUANT8_ASYMM, - TestOperandType::TENSOR_FLOAT32, - TestOperandType::TENSOR_FLOAT16); +DEFINE_QUANTIZATION_OP_SIGNATURE(DEQUANTIZE, V1_3, /*outType=*/TENSOR_FLOAT16, + TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED); -DEFINE_ELEMENTWISE_WITH_TYPED_OUTPUT_SIGNATURE(QUANTIZE, V1_3, - /*outType=*/TENSOR_QUANT8_ASYMM_SIGNED, - TestOperandType::TENSOR_FLOAT32, - TestOperandType::TENSOR_FLOAT16); +DEFINE_QUANTIZATION_OP_SIGNATURE(QUANTIZE, V1_2, /*outType=*/TENSOR_QUANT8_ASYMM, + TestOperandType::TENSOR_FLOAT32, TestOperandType::TENSOR_FLOAT16); + +DEFINE_QUANTIZATION_OP_SIGNATURE(QUANTIZE, V1_3, + /*outType=*/TENSOR_QUANT8_ASYMM_SIGNED, + TestOperandType::TENSOR_FLOAT32, TestOperandType::TENSOR_FLOAT16); #define DEFINE_CAST_SIGNATURE(ver, outType, ...) \ DEFINE_OPERATION_SIGNATURE(CAST_##outType##_##ver){ \ @@ -175,7 +185,7 @@ DEFINE_ELEMENTWISE_WITH_TYPED_OUTPUT_SIGNATURE(QUANTIZE, V1_3, .version = TestHalVersion::ver, \ .inputs = {INPUT_DEFAULT}, \ .outputs = {OUTPUT_TYPED(TestOperandType::outType)}, \ - .constructor = sameDimensionOpConstructor}; + .constructor = castingOpConstructor}; DEFINE_CAST_SIGNATURE(V1_2, /*outType=*/TENSOR_FLOAT32, TestOperandType::TENSOR_FLOAT32, TestOperandType::TENSOR_FLOAT16, TestOperandType::TENSOR_QUANT8_ASYMM, diff --git a/nn/runtime/test/generated/spec_V1_1/lsh_projection_2_relaxed.example.cpp b/nn/runtime/test/generated/spec_V1_1/lsh_projection_2_relaxed.example.cpp index 6fcbb81ec..23dbd2795 100644 --- a/nn/runtime/test/generated/spec_V1_1/lsh_projection_2_relaxed.example.cpp +++ b/nn/runtime/test/generated/spec_V1_1/lsh_projection_2_relaxed.example.cpp @@ -158,114 +158,3 @@ const auto dummy_test_model_all_tensors_as_inputs = TestModelManager::get().add( } // namespace generated_tests::lsh_projection_2_relaxed -namespace generated_tests::lsh_projection_2_relaxed { - -const TestModel& get_test_model_all_tensors_as_inputs_all_inputs_as_internal() { - static TestModel model = { - .expectFailure = false, - .expectedMultinomialDistributionTolerance = 0, - .isRelaxed = true, - .main = { - .inputIndexes = {1, 2, 5}, - .operands = {{ // hash - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // lookup - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({12345, 54321, 67890, 9876, -12345678, -87654321}), - .dimensions = {3, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // weight - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({}), - .dimensions = {3}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // type_param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }, { // output - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1, 2, 2, 0}), - .dimensions = {4}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, - .numberOfConsumers = 0, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // hash_new - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // dummy - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({0.0f}), - .dimensions = {1}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({0}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }}, - .operations = {{ - .inputs = {5, 6, 7}, - .outputs = {0}, - .type = TestOperationType::ADD - }, { - .inputs = {0, 1, 2, 3}, - .outputs = {4}, - .type = TestOperationType::LSH_PROJECTION - }}, - .outputIndexes = {4} - }, - .minSupportedVersion = TestHalVersion::UNKNOWN, - .referenced = {} - }; - return model; -} - -const auto dummy_test_model_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("lsh_projection_2_relaxed_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_all_tensors_as_inputs_all_inputs_as_internal()); - -} // namespace generated_tests::lsh_projection_2_relaxed - diff --git a/nn/runtime/test/generated/spec_V1_1/lsh_projection_relaxed.example.cpp b/nn/runtime/test/generated/spec_V1_1/lsh_projection_relaxed.example.cpp index 68782659b..aa7ccfb24 100644 --- a/nn/runtime/test/generated/spec_V1_1/lsh_projection_relaxed.example.cpp +++ b/nn/runtime/test/generated/spec_V1_1/lsh_projection_relaxed.example.cpp @@ -277,13 +277,13 @@ const TestModel& get_test_model_all_tensors_as_inputs_all_inputs_as_internal() { .expectedMultinomialDistributionTolerance = 0, .isRelaxed = true, .main = { - .inputIndexes = {1, 5, 8}, + .inputIndexes = {0, 1, 5}, .operands = {{ // hash .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({}), + .data = TestBuffer::createFromVector<float>({0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}), .dimensions = {4, 2}, .isIgnored = false, - .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, + .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, .numberOfConsumers = 1, .scale = 0.0f, .type = TestOperandType::TENSOR_FLOAT32, @@ -328,36 +328,6 @@ const TestModel& get_test_model_all_tensors_as_inputs_all_inputs_as_internal() { .scale = 0.0f, .type = TestOperandType::TENSOR_INT32, .zeroPoint = 0 - }, { // hash_new - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // dummy1 - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({0.0f}), - .dimensions = {1}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // param1 - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({0}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 }, { // weight_new .channelQuant = {}, .data = TestBuffer::createFromVector<float>({0.12f, 0.34f, 0.56f}), @@ -368,7 +338,7 @@ const TestModel& get_test_model_all_tensors_as_inputs_all_inputs_as_internal() { .scale = 0.0f, .type = TestOperandType::TENSOR_FLOAT32, .zeroPoint = 0 - }, { // dummy2 + }, { // dummy1 .channelQuant = {}, .data = TestBuffer::createFromVector<float>({0.0f}), .dimensions = {1}, @@ -378,7 +348,7 @@ const TestModel& get_test_model_all_tensors_as_inputs_all_inputs_as_internal() { .scale = 0.0f, .type = TestOperandType::TENSOR_FLOAT32, .zeroPoint = 0 - }, { // param2 + }, { // param1 .channelQuant = {}, .data = TestBuffer::createFromVector<int32_t>({0}), .dimensions = {}, @@ -391,10 +361,6 @@ const TestModel& get_test_model_all_tensors_as_inputs_all_inputs_as_internal() { }}, .operations = {{ .inputs = {5, 6, 7}, - .outputs = {0}, - .type = TestOperationType::ADD - }, { - .inputs = {8, 9, 10}, .outputs = {2}, .type = TestOperationType::ADD }, { diff --git a/nn/runtime/test/generated/spec_V1_2/lsh_projection_3_relaxed.example.cpp b/nn/runtime/test/generated/spec_V1_2/lsh_projection_3_relaxed.example.cpp index 0b964f97c..f44967963 100644 --- a/nn/runtime/test/generated/spec_V1_2/lsh_projection_3_relaxed.example.cpp +++ b/nn/runtime/test/generated/spec_V1_2/lsh_projection_3_relaxed.example.cpp @@ -158,114 +158,3 @@ const auto dummy_test_model_all_tensors_as_inputs = TestModelManager::get().add( } // namespace generated_tests::lsh_projection_3_relaxed -namespace generated_tests::lsh_projection_3_relaxed { - -const TestModel& get_test_model_all_tensors_as_inputs_all_inputs_as_internal() { - static TestModel model = { - .expectFailure = false, - .expectedMultinomialDistributionTolerance = 0, - .isRelaxed = true, - .main = { - .inputIndexes = {1, 2, 5}, - .operands = {{ // hash - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // lookup - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({12345, 54321, 67890, 9876, -12345678, -87654321}), - .dimensions = {3, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // weight - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({}), - .dimensions = {3}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // type_param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({3}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }, { // output - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1, 6, 10, 12}), - .dimensions = {4}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, - .numberOfConsumers = 0, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // hash_new - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // dummy - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({0.0f}), - .dimensions = {1}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({0}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }}, - .operations = {{ - .inputs = {5, 6, 7}, - .outputs = {0}, - .type = TestOperationType::ADD - }, { - .inputs = {0, 1, 2, 3}, - .outputs = {4}, - .type = TestOperationType::LSH_PROJECTION - }}, - .outputIndexes = {4} - }, - .minSupportedVersion = TestHalVersion::UNKNOWN, - .referenced = {} - }; - return model; -} - -const auto dummy_test_model_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("lsh_projection_3_relaxed_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_all_tensors_as_inputs_all_inputs_as_internal()); - -} // namespace generated_tests::lsh_projection_3_relaxed - diff --git a/nn/runtime/test/generated/spec_V1_2/lsh_projection_4_relaxed.example.cpp b/nn/runtime/test/generated/spec_V1_2/lsh_projection_4_relaxed.example.cpp index 2329565ae..09e165d52 100644 --- a/nn/runtime/test/generated/spec_V1_2/lsh_projection_4_relaxed.example.cpp +++ b/nn/runtime/test/generated/spec_V1_2/lsh_projection_4_relaxed.example.cpp @@ -158,114 +158,3 @@ const auto dummy_test_model_all_tensors_as_inputs = TestModelManager::get().add( } // namespace generated_tests::lsh_projection_4_relaxed -namespace generated_tests::lsh_projection_4_relaxed { - -const TestModel& get_test_model_all_tensors_as_inputs_all_inputs_as_internal() { - static TestModel model = { - .expectFailure = false, - .expectedMultinomialDistributionTolerance = 0, - .isRelaxed = true, - .main = { - .inputIndexes = {1, 2, 5}, - .operands = {{ // hash - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // lookup - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({12345, 54321, 67890, 9876, -12345678, -87654321}), - .dimensions = {3, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // weight - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({}), - .dimensions = {3}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // type_param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }, { // output - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1, 2, 2, 0}), - .dimensions = {4}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, - .numberOfConsumers = 0, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // hash_new - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // dummy - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({0.0f}), - .dimensions = {1}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({0}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }}, - .operations = {{ - .inputs = {5, 6, 7}, - .outputs = {0}, - .type = TestOperationType::ADD - }, { - .inputs = {0, 1, 2, 3}, - .outputs = {4}, - .type = TestOperationType::LSH_PROJECTION - }}, - .outputIndexes = {4} - }, - .minSupportedVersion = TestHalVersion::UNKNOWN, - .referenced = {} - }; - return model; -} - -const auto dummy_test_model_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("lsh_projection_4_relaxed_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_all_tensors_as_inputs_all_inputs_as_internal()); - -} // namespace generated_tests::lsh_projection_4_relaxed - diff --git a/nn/runtime/test/generated/spec_V1_2/lsh_projection_deprecated.example.cpp b/nn/runtime/test/generated/spec_V1_2/lsh_projection_deprecated.example.cpp index e225e5500..e87591ee9 100644 --- a/nn/runtime/test/generated/spec_V1_2/lsh_projection_deprecated.example.cpp +++ b/nn/runtime/test/generated/spec_V1_2/lsh_projection_deprecated.example.cpp @@ -158,114 +158,3 @@ const auto dummy_test_model_all_tensors_as_inputs = TestModelManager::get().add( } // namespace generated_tests::lsh_projection_deprecated -namespace generated_tests::lsh_projection_deprecated { - -const TestModel& get_test_model_all_tensors_as_inputs_all_inputs_as_internal() { - static TestModel model = { - .expectFailure = false, - .expectedMultinomialDistributionTolerance = 0, - .isRelaxed = true, - .main = { - .inputIndexes = {1, 2, 5}, - .operands = {{ // hash - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // lookup - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({12345, 54321, 67890, 9876, -12345678, -87654321}), - .dimensions = {3, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // weight - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({}), - .dimensions = {3}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // type_param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }, { // output - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1, 2, 2, 0}), - .dimensions = {4}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, - .numberOfConsumers = 0, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // hash_new - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // dummy - .channelQuant = {}, - .data = TestBuffer::createFromVector<float>({0.0f}), - .dimensions = {1}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT32, - .zeroPoint = 0 - }, { // param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({0}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }}, - .operations = {{ - .inputs = {5, 6, 7}, - .outputs = {0}, - .type = TestOperationType::ADD - }, { - .inputs = {0, 1, 2, 3}, - .outputs = {4}, - .type = TestOperationType::LSH_PROJECTION - }}, - .outputIndexes = {4} - }, - .minSupportedVersion = TestHalVersion::UNKNOWN, - .referenced = {} - }; - return model; -} - -const auto dummy_test_model_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("lsh_projection_deprecated_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_all_tensors_as_inputs_all_inputs_as_internal()); - -} // namespace generated_tests::lsh_projection_deprecated - diff --git a/nn/runtime/test/generated/spec_V1_2/lsh_projection_float16.example.cpp b/nn/runtime/test/generated/spec_V1_2/lsh_projection_float16.example.cpp index c69b0c1e3..4a57101db 100644 --- a/nn/runtime/test/generated/spec_V1_2/lsh_projection_float16.example.cpp +++ b/nn/runtime/test/generated/spec_V1_2/lsh_projection_float16.example.cpp @@ -414,413 +414,3 @@ const auto dummy_test_model_all_tensors_as_inputs_all_inputs_as_internal = TestM } // namespace generated_tests::lsh_projection_float16 -namespace generated_tests::lsh_projection_float16 { - -const TestModel& get_test_model_float16() { - static TestModel model = { - .expectFailure = false, - .expectedMultinomialDistributionTolerance = 0, - .isRelaxed = false, - .main = { - .inputIndexes = {1, 2}, - .operands = {{ // hash - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // lookup - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({12345, 54321, 67890, 9876, -12345678, -87654321}), - .dimensions = {3, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // weight - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.12f, 0.34f, 0.56f}), - .dimensions = {3}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // type_param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({2}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }, { // output - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1, 1, 1, 1, 1, 0, 0, 0}), - .dimensions = {8}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, - .numberOfConsumers = 0, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }}, - .operations = {{ - .inputs = {0, 1, 2, 3}, - .outputs = {4}, - .type = TestOperationType::LSH_PROJECTION - }}, - .outputIndexes = {4} - }, - .minSupportedVersion = TestHalVersion::V1_2, - .referenced = {} - }; - return model; -} - -const auto dummy_test_model_float16 = TestModelManager::get().add("lsh_projection_float16_float16", get_test_model_float16()); - -} // namespace generated_tests::lsh_projection_float16 - -namespace generated_tests::lsh_projection_float16 { - -const TestModel& get_test_model_float16_all_inputs_as_internal() { - static TestModel model = { - .expectFailure = false, - .expectedMultinomialDistributionTolerance = 0, - .isRelaxed = false, - .main = { - .inputIndexes = {1, 5}, - .operands = {{ // hash - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // lookup - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({12345, 54321, 67890, 9876, -12345678, -87654321}), - .dimensions = {3, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // weight - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({}), - .dimensions = {3}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // type_param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({2}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }, { // output - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1, 1, 1, 1, 1, 0, 0, 0}), - .dimensions = {8}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, - .numberOfConsumers = 0, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // weight_new - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.12f, 0.34f, 0.56f}), - .dimensions = {3}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // dummy3 - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.0f}), - .dimensions = {1}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // param3 - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({0}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }}, - .operations = {{ - .inputs = {5, 6, 7}, - .outputs = {2}, - .type = TestOperationType::ADD - }, { - .inputs = {0, 1, 2, 3}, - .outputs = {4}, - .type = TestOperationType::LSH_PROJECTION - }}, - .outputIndexes = {4} - }, - .minSupportedVersion = TestHalVersion::V1_2, - .referenced = {} - }; - return model; -} - -const auto dummy_test_model_float16_all_inputs_as_internal = TestModelManager::get().add("lsh_projection_float16_float16_all_inputs_as_internal", get_test_model_float16_all_inputs_as_internal()); - -} // namespace generated_tests::lsh_projection_float16 - -namespace generated_tests::lsh_projection_float16 { - -const TestModel& get_test_model_float16_all_tensors_as_inputs() { - static TestModel model = { - .expectFailure = false, - .expectedMultinomialDistributionTolerance = 0, - .isRelaxed = false, - .main = { - .inputIndexes = {0, 1, 2}, - .operands = {{ // hash - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // lookup - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({12345, 54321, 67890, 9876, -12345678, -87654321}), - .dimensions = {3, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // weight - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.12f, 0.34f, 0.56f}), - .dimensions = {3}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // type_param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({2}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }, { // output - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1, 1, 1, 1, 1, 0, 0, 0}), - .dimensions = {8}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, - .numberOfConsumers = 0, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }}, - .operations = {{ - .inputs = {0, 1, 2, 3}, - .outputs = {4}, - .type = TestOperationType::LSH_PROJECTION - }}, - .outputIndexes = {4} - }, - .minSupportedVersion = TestHalVersion::V1_2, - .referenced = {} - }; - return model; -} - -const auto dummy_test_model_float16_all_tensors_as_inputs = TestModelManager::get().add("lsh_projection_float16_float16_all_tensors_as_inputs", get_test_model_float16_all_tensors_as_inputs()); - -} // namespace generated_tests::lsh_projection_float16 - -namespace generated_tests::lsh_projection_float16 { - -const TestModel& get_test_model_float16_all_tensors_as_inputs_all_inputs_as_internal() { - static TestModel model = { - .expectFailure = false, - .expectedMultinomialDistributionTolerance = 0, - .isRelaxed = false, - .main = { - .inputIndexes = {1, 5, 8}, - .operands = {{ // hash - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // lookup - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({12345, 54321, 67890, 9876, -12345678, -87654321}), - .dimensions = {3, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // weight - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({}), - .dimensions = {3}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // type_param - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({2}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }, { // output - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({1, 1, 1, 1, 1, 0, 0, 0}), - .dimensions = {8}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, - .numberOfConsumers = 0, - .scale = 0.0f, - .type = TestOperandType::TENSOR_INT32, - .zeroPoint = 0 - }, { // hash_new - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.123f, 0.456f, -0.321f, -0.654f, 1.234f, 5.678f, -4.321f, -8.765f}), - .dimensions = {4, 2}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // dummy4 - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.0f}), - .dimensions = {1}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // param4 - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({0}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }, { // weight_new - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.12f, 0.34f, 0.56f}), - .dimensions = {3}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // dummy5 - .channelQuant = {}, - .data = TestBuffer::createFromVector<_Float16>({0.0f}), - .dimensions = {1}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::TENSOR_FLOAT16, - .zeroPoint = 0 - }, { // param5 - .channelQuant = {}, - .data = TestBuffer::createFromVector<int32_t>({0}), - .dimensions = {}, - .isIgnored = false, - .lifetime = TestOperandLifeTime::CONSTANT_COPY, - .numberOfConsumers = 1, - .scale = 0.0f, - .type = TestOperandType::INT32, - .zeroPoint = 0 - }}, - .operations = {{ - .inputs = {5, 6, 7}, - .outputs = {0}, - .type = TestOperationType::ADD - }, { - .inputs = {8, 9, 10}, - .outputs = {2}, - .type = TestOperationType::ADD - }, { - .inputs = {0, 1, 2, 3}, - .outputs = {4}, - .type = TestOperationType::LSH_PROJECTION - }}, - .outputIndexes = {4} - }, - .minSupportedVersion = TestHalVersion::V1_2, - .referenced = {} - }; - return model; -} - -const auto dummy_test_model_float16_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("lsh_projection_float16_float16_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_float16_all_tensors_as_inputs_all_inputs_as_internal()); - -} // namespace generated_tests::lsh_projection_float16 - diff --git a/nn/runtime/test/generated/spec_V1_3_cts_only/cast_mismatching_shapes.example.cpp b/nn/runtime/test/generated/spec_V1_3_cts_only/cast_mismatching_shapes.example.cpp new file mode 100644 index 000000000..24ba83438 --- /dev/null +++ b/nn/runtime/test/generated/spec_V1_3_cts_only/cast_mismatching_shapes.example.cpp @@ -0,0 +1,53 @@ +// Generated from cast_mismatching_shapes.mod.py +// DO NOT EDIT +// clang-format off +#include "TestHarness.h" +using namespace test_helper; + +namespace generated_tests::cast_mismatching_shapes { + +const TestModel& get_test_model() { + static TestModel model = { + .expectFailure = true, + .expectedMultinomialDistributionTolerance = 0, + .isRelaxed = false, + .main = { + .inputIndexes = {0}, + .operands = {{ // input0 + .channelQuant = {}, + .data = TestBuffer::createFromVector<int32_t>({1, 2, 3, 4, 5, 6}), + .dimensions = {2, 3}, + .isIgnored = false, + .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT, + .numberOfConsumers = 1, + .scale = 0.0f, + .type = TestOperandType::TENSOR_INT32, + .zeroPoint = 0 + }, { // output0 + .channelQuant = {}, + .data = TestBuffer::createFromVector<int32_t>({1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}), + .dimensions = {100}, + .isIgnored = false, + .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT, + .numberOfConsumers = 0, + .scale = 0.0f, + .type = TestOperandType::TENSOR_INT32, + .zeroPoint = 0 + }}, + .operations = {{ + .inputs = {0}, + .outputs = {1}, + .type = TestOperationType::CAST + }}, + .outputIndexes = {1} + }, + .minSupportedVersion = TestHalVersion::UNKNOWN, + .referenced = {} + }; + return model; +} + +const auto dummy_test_model = TestModelManager::get().add("cast_mismatching_shapes", get_test_model()); + +} // namespace generated_tests::cast_mismatching_shapes + diff --git a/nn/runtime/test/specs/V1_1/lsh_projection_2_relaxed.mod.py b/nn/runtime/test/specs/V1_1/lsh_projection_2_relaxed.mod.py index 6608b0666..1904f0490 100644 --- a/nn/runtime/test/specs/V1_1/lsh_projection_2_relaxed.mod.py +++ b/nn/runtime/test/specs/V1_1/lsh_projection_2_relaxed.mod.py @@ -20,8 +20,9 @@ num_bits = 2 model = Model() -hhash = Parameter("hash", "TENSOR_FLOAT32", "{%d, %d}" % (num_hash, num_bits), - [0.123, 0.456, -0.321, -0.654, 1.234, 5.678, -4.321, -8.765]) +hhash = Parameter( + "hash", "TENSOR_FLOAT32", "{%d, %d}" % (num_hash, num_bits), + [0.123, 0.456, -0.321, -0.654, 1.234, 5.678, -4.321, -8.765]).ShouldNeverBeInternal() lookup = Input("lookup", "TENSOR_INT32", "{%d, %d}" % (num_input, num_bits)) weight = Input("weight", "TENSOR_FLOAT32", "{%d}" % (num_input)) type_param = Int32Scalar("type_param", 1) # SPARSE diff --git a/nn/runtime/test/specs/V1_1/lsh_projection_relaxed.mod.py b/nn/runtime/test/specs/V1_1/lsh_projection_relaxed.mod.py index 9a1bfaca2..c8ac42bdc 100644 --- a/nn/runtime/test/specs/V1_1/lsh_projection_relaxed.mod.py +++ b/nn/runtime/test/specs/V1_1/lsh_projection_relaxed.mod.py @@ -20,8 +20,9 @@ num_bits = 2 model = Model() -hhash = Parameter("hash", "TENSOR_FLOAT32", "{%d, %d}" % (num_hash, num_bits), - [0.123, 0.456, -0.321, -0.654, 1.234, 5.678, -4.321, -8.765]) +hhash = Parameter( + "hash", "TENSOR_FLOAT32", "{%d, %d}" % (num_hash, num_bits), + [0.123, 0.456, -0.321, -0.654, 1.234, 5.678, -4.321, -8.765]).ShouldNeverBeInternal() lookup = Input("lookup", "TENSOR_INT32", "{%d, %d}" % (num_input, num_bits)) weight = Input("weight", "TENSOR_FLOAT32", "{%d}" % (num_input)) type_param = Int32Scalar("type_param", 2) # DENSE @@ -38,4 +39,3 @@ input0 = { output0 = {output: [1, 1, 1, 0, 1, 1, 1, 0]} Example((input0, output0)) - diff --git a/nn/runtime/test/specs/V1_2/lsh_projection_3_relaxed.mod.py b/nn/runtime/test/specs/V1_2/lsh_projection_3_relaxed.mod.py index de7cec111..443fe6956 100644 --- a/nn/runtime/test/specs/V1_2/lsh_projection_3_relaxed.mod.py +++ b/nn/runtime/test/specs/V1_2/lsh_projection_3_relaxed.mod.py @@ -20,8 +20,9 @@ num_bits = 2 model = Model() -hhash = Parameter("hash", "TENSOR_FLOAT32", "{%d, %d}" % (num_hash, num_bits), - [0.123, 0.456, -0.321, -0.654, 1.234, 5.678, -4.321, -8.765]) +hhash = Parameter( + "hash", "TENSOR_FLOAT32", "{%d, %d}" % (num_hash, num_bits), + [0.123, 0.456, -0.321, -0.654, 1.234, 5.678, -4.321, -8.765]).ShouldNeverBeInternal() lookup = Input("lookup", "TENSOR_INT32", "{%d, %d}" % (num_input, num_bits)) weight = Input("weight", "TENSOR_FLOAT32", "{%d}" % (num_input)) type_param = Int32Scalar("type_param", 3) # SPARSE diff --git a/nn/runtime/test/specs/V1_2/lsh_projection_4_relaxed.mod.py b/nn/runtime/test/specs/V1_2/lsh_projection_4_relaxed.mod.py index 2b3b33a1e..a8af8940d 100644 --- a/nn/runtime/test/specs/V1_2/lsh_projection_4_relaxed.mod.py +++ b/nn/runtime/test/specs/V1_2/lsh_projection_4_relaxed.mod.py @@ -20,8 +20,9 @@ num_bits = 2 model = Model() -hhash = Parameter("hash", "TENSOR_FLOAT32", "{%d, %d}" % (num_hash, num_bits), - [0.123, 0.456, -0.321, -0.654, 1.234, 5.678, -4.321, -8.765]) +hhash = Parameter( + "hash", "TENSOR_FLOAT32", "{%d, %d}" % (num_hash, num_bits), + [0.123, 0.456, -0.321, -0.654, 1.234, 5.678, -4.321, -8.765]).ShouldNeverBeInternal() lookup = Input("lookup", "TENSOR_INT32", "{%d, %d}" % (num_input, num_bits)) weight = Input("weight", "TENSOR_FLOAT32", "{%d}" % (num_input)) type_param = Int32Scalar("type_param", 1) # SPARSE DEPRECATED diff --git a/nn/runtime/test/specs/V1_2/lsh_projection_deprecated.mod.py b/nn/runtime/test/specs/V1_2/lsh_projection_deprecated.mod.py index 2b3b33a1e..a8af8940d 100644 --- a/nn/runtime/test/specs/V1_2/lsh_projection_deprecated.mod.py +++ b/nn/runtime/test/specs/V1_2/lsh_projection_deprecated.mod.py @@ -20,8 +20,9 @@ num_bits = 2 model = Model() -hhash = Parameter("hash", "TENSOR_FLOAT32", "{%d, %d}" % (num_hash, num_bits), - [0.123, 0.456, -0.321, -0.654, 1.234, 5.678, -4.321, -8.765]) +hhash = Parameter( + "hash", "TENSOR_FLOAT32", "{%d, %d}" % (num_hash, num_bits), + [0.123, 0.456, -0.321, -0.654, 1.234, 5.678, -4.321, -8.765]).ShouldNeverBeInternal() lookup = Input("lookup", "TENSOR_INT32", "{%d, %d}" % (num_input, num_bits)) weight = Input("weight", "TENSOR_FLOAT32", "{%d}" % (num_input)) type_param = Int32Scalar("type_param", 1) # SPARSE DEPRECATED diff --git a/nn/runtime/test/specs/V1_2/lsh_projection_float16.mod.py b/nn/runtime/test/specs/V1_2/lsh_projection_float16.mod.py index ed19b17f7..4b22ad190 100644 --- a/nn/runtime/test/specs/V1_2/lsh_projection_float16.mod.py +++ b/nn/runtime/test/specs/V1_2/lsh_projection_float16.mod.py @@ -36,4 +36,4 @@ input0 = { } output0 = {output: [1, 1, 1, 1, 1, 0, 0, 0]} -Example((input0, output0)).AddVariations("float16"); +Example((input0, output0)) diff --git a/nn/runtime/test/specs/V1_3_cts_only/cast_mismatching_shapes.mod.py b/nn/runtime/test/specs/V1_3_cts_only/cast_mismatching_shapes.mod.py new file mode 100644 index 000000000..c718e5cc2 --- /dev/null +++ b/nn/runtime/test/specs/V1_3_cts_only/cast_mismatching_shapes.mod.py @@ -0,0 +1,25 @@ +# +# Copyright (C) 2020 The Android Open Source Project +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +input0 = Input("input0", "TENSOR_INT32", "{2, 3}") +output0 = Output("output0", "TENSOR_INT32", "{100}") + +model = Model().Operation("CAST", input0).To(output0) + +example = Example({ + input0: [1, 2, 3, 4, 5, 6], + output0: [1, 2, 3, 4, 5, 6] + [0] * 94, +}, model=model).ExpectFailure() diff --git a/nn/tools/test_generator/README.md b/nn/tools/test_generator/README.md index 29c1155d2..e781771ce 100644 --- a/nn/tools/test_generator/README.md +++ b/nn/tools/test_generator/README.md @@ -244,6 +244,14 @@ example.DisableLifeTimeVariation() example.DisableDynamicOutputShapeVariation() ``` +You may also specify a certain operand to be input/const-only that `AllInputsAsInternalCoverter` will skip converting this operand. + +```Python +# "hash" will be converted to a model input when applying AllTensorsAsInputsConverter, +# but will be skipped when further applying AllInputsAsInternalCoverter. +hash = Parameter("hash", "TENSOR_FLOAT32", "{1, 1}", [0.123]).ShouldNeverBeInternal() +``` + #### Some helper functions The test generator provides several helper functions or shorthands to add commonly used group of variations. diff --git a/nn/tools/test_generator/test_generator.py b/nn/tools/test_generator/test_generator.py index e1b10a7ad..92dfad756 100755 --- a/nn/tools/test_generator/test_generator.py +++ b/nn/tools/test_generator/test_generator.py @@ -295,6 +295,7 @@ class Operand(NamedVariable): self.model_index = None self.ins = [] self.outs = [] + self.mayBeInternal = True def SetValue(self, value): self.value = value if type(value) is list or type(value) is tuple or value is None \ @@ -330,8 +331,15 @@ class Operand(NamedVariable): extraParams=self.type.extraParams) if not issubclass(DerivedClass, Internal): newop.SetValue(self.value) + if not self.mayBeInternal: + assert not issubclass(DerivedClass, Internal) + newop.ShouldNeverBeInternal() return newop + def ShouldNeverBeInternal(self): + self.mayBeInternal = False + return self + # Base class of user-defined input/output operand class InOut(Operand): @@ -1031,7 +1039,7 @@ class AllInputsAsInternalCoverter(ModelVariation): raise SkipVariation # Find all input tensors that can be an output of the ADD operation. - modelInputs = [i for i in model.GetInputs() if CompatibleWithADD(i)] + modelInputs = [i for i in model.GetInputs() if CompatibleWithADD(i) and i.mayBeInternal] if not modelInputs: raise SkipVariation |