| 209 | } |
| 210 | |
| 211 | void dump_output_data(node_t test_node) |
| 212 | { |
| 213 | tensor_t output_tensor = get_node_output_tensor(test_node, 0); |
| 214 | int dims[4]; |
| 215 | |
| 216 | get_tensor_shape(output_tensor, dims, 4); |
| 217 | |
| 218 | void* o_buf = get_tensor_buffer(output_tensor); |
| 219 | int data_type = get_tensor_data_type(output_tensor); |
| 220 | |
| 221 | for(int i = 0; i < dims[0] * dims[1]; i++) |
| 222 | { |
| 223 | if(data_type == TENGINE_DT_FP32) |
| 224 | { |
| 225 | float* p = ( float* )o_buf; |
| 226 | std::cout << i << " " << p[i] << "\n"; |
| 227 | } |
| 228 | else if(data_type == TENGINE_DT_FP16) |
| 229 | { |
| 230 | __fp16* p = ( __fp16* )o_buf; |
| 231 | |
| 232 | #ifdef __ARM_ARCH |
| 233 | std::cout << i << " " << ( float )p[i] << "\n"; |
| 234 | #else |
| 235 | std::cout << i << " " << fp16_to_fp32(p[i]) << "\n"; |
| 236 | #endif |
| 237 | } |
| 238 | else if(data_type == TENGINE_DT_INT8) |
| 239 | { |
| 240 | int8_t* p = ( int8_t* )o_buf; |
| 241 | std::cout << i << " " << ( int )p[i] << "\n"; |
| 242 | } |
| 243 | else |
| 244 | { |
| 245 | uint8_t* p = ( uint8_t* )o_buf; |
| 246 | |
| 247 | std::cout << i << " " << ( int )p[i] << "\n"; |
| 248 | } |
| 249 | } |
| 250 | |
| 251 | release_graph_tensor(output_tensor); |
| 252 | } |
| 253 | |
| 254 | int main(int argc, char* argv[]) |
| 255 | { |
no test coverage detected