1 files changed, 33 insertions, 0 deletions
diff --git a/runtimes/tests/neural_networks_test/generated/models/avg_pool_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/avg_pool_float_3.model.cpp
new file mode 100644
index 000000000..c056c61c3
--- /dev/null
+++ b/runtimes/tests/neural_networks_test/generated/models/avg_pool_float_3.model.cpp
@@ -0,0 +1,33 @@
+// Generated file (from: avg_pool_float_3.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 200, 180, 1});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 96, 86, 1});
+  // Phase 1, operands
+  auto i0 = model->addOperand(&type0);
+  auto stride = model->addOperand(&type1);
+  auto filter = model->addOperand(&type1);
+  auto padding = model->addOperand(&type1);
+  auto activation = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t stride_init[] = {2};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t filter_init[] = {10};
+  model->setOperandValue(filter, filter_init, sizeof(int32_t) * 1);
+  static int32_t padding_init[] = {0};
+  model->setOperandValue(padding, padding_init, sizeof(int32_t) * 1);
+  static int32_t activation_init[] = {0};
+  model->setOperandValue(activation, activation_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {i0},
+    {output});
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}