| 199 | } |
| 200 | |
| 201 | static void dry_run(std::unique_ptr<executorch::extension::Module>& module) { |
| 202 | |
| 203 | // Dummy run for a module |
| 204 | // ------------------------- |
| 205 | auto module_forward_meta_res = module->method_meta("forward"); |
| 206 | AUDIOGEN_CHECK(module_forward_meta_res.ok()); |
| 207 | |
| 208 | auto module_forward_meta = module_forward_meta_res.get(); |
| 209 | size_t module_num_inputs = module_forward_meta.num_inputs(); |
| 210 | |
| 211 | // To keep the created tensors inside the loop alive |
| 212 | std::vector<std::shared_ptr<Tensor>> allocated_tensors; |
| 213 | |
| 214 | std::vector<executorch::runtime::EValue> module_inputs(module_num_inputs); |
| 215 | for (size_t i = 0; i < module_num_inputs; ++i) { |
| 216 | auto input_tensor_meta = module_forward_meta.input_tensor_meta(i).get(); |
| 217 | auto input_tensor_dims = get_tensor_dims(input_tensor_meta); |
| 218 | auto input_tensor_scalar_type = input_tensor_meta.scalar_type(); |
| 219 | auto input_tensor = input_tensor_scalar_type == ScalarType::Float ? randn(input_tensor_dims, input_tensor_scalar_type) : randint(1, 100, input_tensor_dims, input_tensor_scalar_type); |
| 220 | allocated_tensors.push_back(input_tensor); |
| 221 | module_inputs[i] = input_tensor; |
| 222 | } |
| 223 | |
| 224 | auto module_output = module->forward(module_inputs); |
| 225 | if(!module_output.ok()) { |
| 226 | ET_LOG(Error, "Failed to run module forward"); |
| 227 | exit(EXIT_FAILURE); |
| 228 | } |
| 229 | } |
| 230 | |
| 231 | int main(int32_t argc, char** argv) { |
| 232 |
no test coverage detected