diff options
Diffstat (limited to 'runtimes/tests/neural_networks_test/generated/models/local_response_norm_float_2.model.cpp')
-rw-r--r-- | runtimes/tests/neural_networks_test/generated/models/local_response_norm_float_2.model.cpp | 33 |
1 files changed, 33 insertions, 0 deletions
diff --git a/runtimes/tests/neural_networks_test/generated/models/local_response_norm_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/local_response_norm_float_2.model.cpp new file mode 100644 index 000000000..5aae9a67b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/local_response_norm_float_2.model.cpp @@ -0,0 +1,33 @@ +// Generated file (from: local_response_norm_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::FLOAT32, {}); + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 6}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto radius = model->addOperand(&type1); + auto bias = model->addOperand(&type2); + auto alpha = model->addOperand(&type2); + auto beta = model->addOperand(&type2); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t radius_init[] = {20}; + model->setOperandValue(radius, radius_init, sizeof(int32_t) * 1); + static float bias_init[] = {0.0f}; + model->setOperandValue(bias, bias_init, sizeof(float) * 1); + static float alpha_init[] = {1.0f}; + model->setOperandValue(alpha, alpha_init, sizeof(float) * 1); + static float beta_init[] = {0.5f}; + model->setOperandValue(beta, beta_init, sizeof(float) * 1); + model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} |