1 files changed, 36 insertions, 0 deletions
diff --git a/runtimes/tests/neural_networks_test/generated/models/svdf.model.cpp b/runtimes/tests/neural_networks_test/generated/models/svdf.model.cpp
new file mode 100644
index 000000000..30632a9b5
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/generated/models/svdf.model.cpp
@@ -0,0 +1,36 @@
+// Generated file (from: svdf.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type5(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type4(Type::TENSOR_FLOAT32, {2, 40});
+  OperandType type6(Type::TENSOR_FLOAT32, {2, 4});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 10});
+  OperandType type1(Type::TENSOR_FLOAT32, {4, 3});
+  OperandType type3(Type::TENSOR_FLOAT32, {4});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto weights_feature = model->addOperand(&type1);
+  auto weights_time = model->addOperand(&type2);
+  auto bias = model->addOperand(&type3);
+  auto state_in = model->addOperand(&type4);
+  auto rank_param = model->addOperand(&type5);
+  auto activation_param = model->addOperand(&type5);
+  auto state_out = model->addOperand(&type4);
+  auto output = model->addOperand(&type6);
+  // Phase 2, operations
+  static int32_t rank_param_init[] = {1};
+  model->setOperandValue(rank_param, rank_param_init, sizeof(int32_t) * 1);
+  static int32_t activation_param_init[] = {0};
+  model->setOperandValue(activation_param, activation_param_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_SVDF, {input, weights_feature, weights_time, bias, state_in, rank_param, activation_param}, {state_out, output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input, weights_feature, weights_time, bias, state_in},
+    {state_out, output});
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {0};
+  return ignore.find(i) != ignore.end();
+}