1 files changed, 0 insertions, 32 deletions
diff --git a/runtimes/tests/neural_networks_test/generated/models/rnn_state.model.cpp b/runtimes/tests/neural_networks_test/generated/models/rnn_state.model.cpp
deleted file mode 100644
index 72fcb6703..000000000
--- a/runtimes/tests/neural_networks_test/generated/models/rnn_state.model.cpp
+++ /dev/null
@@ -1,32 +0,0 @@
-// Generated file (from: rnn_state.mod.py). Do not edit
-void CreateModel(Model *model) {
-  OperandType type5(Type::INT32, {});
-  OperandType type2(Type::TENSOR_FLOAT32, {16, 16});
-  OperandType type1(Type::TENSOR_FLOAT32, {16, 8});
-  OperandType type3(Type::TENSOR_FLOAT32, {16});
-  OperandType type4(Type::TENSOR_FLOAT32, {2, 16});
-  OperandType type0(Type::TENSOR_FLOAT32, {2, 8});
-  // Phase 1, operands
-  auto input = model->addOperand(&type0);
-  auto weights = model->addOperand(&type1);
-  auto recurrent_weights = model->addOperand(&type2);
-  auto bias = model->addOperand(&type3);
-  auto hidden_state_in = model->addOperand(&type4);
-  auto activation_param = model->addOperand(&type5);
-  auto hidden_state_out = model->addOperand(&type4);
-  auto output = model->addOperand(&type4);
-  // Phase 2, operations
-  static int32_t activation_param_init[] = {1};
-  model->setOperandValue(activation_param, activation_param_init, sizeof(int32_t) * 1);
-  model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
-  // Phase 3, inputs and outputs
-  model->identifyInputsAndOutputs(
-    {input, weights, recurrent_weights, bias, hidden_state_in},
-    {hidden_state_out, output});
-  assert(model->isValid());
-}
-
-bool is_ignored(int i) {
-  static std::set<int> ignore = {0};
-  return ignore.find(i) != ignore.end();
-}