#include #include #include "../common/common.h" #define CONFIG_BIN "./trainer_config.bin" int main() { // Initalize Paddle char* argv[] = {"--use_gpu=False"}; CHECK(paddle_init(1, (char**)argv)); // Reading config binary file. It is generated by `convert_protobin.sh` long size; void* buf = read_config(CONFIG_BIN, &size); // Create a gradient machine for inference. paddle_gradient_machine machine; CHECK(paddle_gradient_machine_create_for_inference(&machine, buf, (int)size)); CHECK(paddle_gradient_machine_randomize_param(machine)); // Loading parameter. Uncomment the following line and change the directory. // CHECK(paddle_gradient_machine_load_parameter_from_disk(machine, // "./some_where_to_params")); paddle_arguments in_args = paddle_arguments_create_none(); // There is only one input of this network. CHECK(paddle_arguments_resize(in_args, 1)); // Create input matrix. paddle_matrix mat = paddle_matrix_create_sparse(1, 784, 3, true, false); srand(time(0)); paddle_real* array; int colBuf[] = {9, 93, 109}; int rowBuf[] = {0, sizeof(colBuf) / sizeof(int)}; CHECK(paddle_matrix_sparse_copy_from(mat, rowBuf, sizeof(rowBuf) / sizeof(int), colBuf, sizeof(colBuf) / sizeof(int), NULL, 0)); CHECK(paddle_arguments_set_value(in_args, 0, mat)); paddle_arguments out_args = paddle_arguments_create_none(); CHECK(paddle_gradient_machine_forward(machine, in_args, out_args, /* isTrain */ false)); paddle_matrix prob = paddle_matrix_create_none(); CHECK(paddle_arguments_value(out_args, 0, prob)); CHECK(paddle_matrix_get_row(prob, 0, &array)); printf("Prob: "); for (int i = 0; i < 10; ++i) { printf("%.2f ", array[i]); } printf("\n"); return 0; }