1 files changed, 0 insertions, 36 deletions
diff --git a/runtimes/tests/neural_networks_test/generated/models/svdf2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/svdf2.model.cpp
deleted file mode 100644
index 2b1ae214d..000000000
--- a/runtimes/tests/neural_networks_test/generated/models/svdf2.model.cpp
+++ /dev/null
@@ -1,36 +0,0 @@
-// Generated file (from: svdf2.mod.py). Do not edit
-void CreateModel(Model *model) {
-  OperandType type5(Type::INT32, {});
-  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
-  OperandType type6(Type::TENSOR_FLOAT32, {2, 4});
-  OperandType type4(Type::TENSOR_FLOAT32, {2, 80});
-  OperandType type3(Type::TENSOR_FLOAT32, {4});
-  OperandType type2(Type::TENSOR_FLOAT32, {8, 10});
-  OperandType type1(Type::TENSOR_FLOAT32, {8, 3});
-  // 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[] = {2};
-  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();
-}