fix the "masked_fill" bug

If you use masked_fill according to ex_mask (0 for pad), it will fill not padding position(which value in ex_mask is 1) with 0, this will lead a bad performance.

fastNLP/modules/encoder/star_transformer.py

@@ -57,6 +57,7 @@ class StarTransformer(nn.Module):
         nodes = embs
         relay = embs.mean(2, keepdim=True)
         ex_mask = mask[:, None, :, None].expand(B, H, L, 1)
+        ex_mask = ex_mask.ne(1) # reverse mask for next masked_fill.
         r_embs = embs.view(B, H, 1, L)
         for i in range(self.iters):
             ax = torch.cat([r_embs, relay.expand(B, H, 1, L)], 2)