| 231 | } |
| 232 | |
| 233 | void set_input_data(graph_t graph, int input_counts) |
| 234 | { |
| 235 | for(int ii = 0; ii < input_counts; ++ii) |
| 236 | { |
| 237 | tensor_t input_tensor = get_graph_input_tensor(graph, ii, 0); |
| 238 | |
| 239 | int data_type = get_tensor_data_type(input_tensor); |
| 240 | int buf_size = get_tensor_buffer_size(input_tensor); |
| 241 | void* i_buf = get_mem(buf_size); |
| 242 | |
| 243 | int dims[4]; |
| 244 | |
| 245 | int num = get_tensor_shape(input_tensor, dims, 4); |
| 246 | int elem_num = 1; |
| 247 | while(num != 0) |
| 248 | { |
| 249 | elem_num *= dims[num - 1]; |
| 250 | num--; |
| 251 | } |
| 252 | |
| 253 | // std::cout << "set input data counts : " << elem_num << "\n"; |
| 254 | |
| 255 | for(int i = 0; i < elem_num; i++) |
| 256 | { |
| 257 | int iVal = i + 1; |
| 258 | if(i == elem_num - 1) |
| 259 | { |
| 260 | iVal = 127; |
| 261 | } |
| 262 | |
| 263 | if(data_type == TENGINE_DT_FP32) |
| 264 | { |
| 265 | float* f = ( float* )i_buf; |
| 266 | f[i] = iVal; |
| 267 | // std::cout << f[i] << " "; |
| 268 | } |
| 269 | else if(data_type == TENGINE_DT_FP16) |
| 270 | { |
| 271 | __fp16* f16 = ( __fp16* )i_buf; |
| 272 | |
| 273 | #ifdef __ARM_ARCH |
| 274 | f16[i] = iVal; |
| 275 | #else |
| 276 | f16[i] = fp32_to_fp16(iVal); |
| 277 | #endif |
| 278 | // std::cout << iVal << " "; |
| 279 | } |
| 280 | else if(data_type == TENGINE_DT_UINT8) |
| 281 | { |
| 282 | uint8_t* i8 = ( uint8_t* )i_buf; |
| 283 | i8[i] = iVal; |
| 284 | // std::cout << (int)i8[i] << " "; |
| 285 | } |
| 286 | else |
| 287 | { |
| 288 | int8_t* i8 = ( int8_t* )i_buf; |
| 289 | i8[i] = iVal; |
| 290 | // std::cout << (int)i8[i] << " "; |
no test coverage detected