[Project] Support callback function for train

diff --git a/contrib/kann/kann.c b/contrib/kann/kann.c
index 0af15fb2a7b6715251137b7e689169914a7b3af0..3fbf139cce17871f3e238ca38804e20938bd1a71 100644 (file)
--- a/contrib/kann/kann.c
+++ b/contrib/kann/kann.c
@@ -846,7 +846,10 @@ float kann_grad_clip(float thres, int n, float *g)
  *** @@XY: simpler API for network with a single input/output ***
  ****************************************************************/
 
-int kann_train_fnn1(kann_t *ann, float lr, int mini_size, int max_epoch, int max_drop_streak, float frac_val, int n, float **_x, float **_y)
+int kann_train_fnn1(kann_t *ann, float lr, int mini_size, int max_epoch,
+                                       int max_drop_streak, float frac_val, int n,
+                                       float **_x, float **_y,
+                                       kann_train_cb cb, void *ud)
 {
        int i, j, *shuf, n_train, n_val, n_in, n_out, n_var, n_const, drop_streak = 0, min_set = 0;
        float **x, **y, *x1, *y1, *r, min_val_cost = FLT_MAX, *min_x, *min_c;
@@ -907,7 +910,9 @@ int kann_train_fnn1(kann_t *ann, float lr, int mini_size, int max_epoch, int max
                        n_proc += ms;
                }
                if (n_val > 0) val_cost /= n_val;
-               if (kann_verbose >= 3) {
+               if (cb) {
+                       cb(i + 1, train_cost, val_cost, ud);
+#if 0
                        fprintf(stderr, "epoch: %d; training cost: %g", i+1, train_cost);
                        if (n_train_base) fprintf(stderr, " (class error: %.2f%%)", 100.0f * n_train_err / n_train);
                        if (n_val > 0) {
@@ -915,6 +920,7 @@ int kann_train_fnn1(kann_t *ann, float lr, int mini_size, int max_epoch, int max
                                if (n_val_base) fprintf(stderr, " (class error: %.2f%%)", 100.0f * n_val_err / n_val);
                        }
                        fputc('\n', stderr);
+#endif
                }
                if (i >= max_drop_streak && n_val > 0) {
                        if (val_cost < min_val_cost) {