1 files changed, 33 insertions, 0 deletions
diff --git a/runtimes/tests/neural_networks_test/generated/models/local_response_norm_float_4.model.cpp b/runtimes/tests/neural_networks_test/generated/models/local_response_norm_float_4.model.cpp
new file mode 100644
index 000000000..8311f8f80
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/generated/models/local_response_norm_float_4.model.cpp
@@ -0,0 +1,33 @@
+// Generated file (from: local_response_norm_float_4.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[] = {2};
+  model->setOperandValue(radius, radius_init, sizeof(int32_t) * 1);
+  static float bias_init[] = {9.0f};
+  model->setOperandValue(bias, bias_init, sizeof(float) * 1);
+  static float alpha_init[] = {4.0f};
+  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();
+}