fix masked_fill which will nan in trainning

paddlespeech/s2t/__init__.py

@@ -166,8 +166,19 @@ def broadcast_shape(shp1, shp2):
 def masked_fill(xs: paddle.Tensor,
                 mask: paddle.Tensor,
                 value: Union[float, int]):
-    mask = mask.astype(xs.dtype)
-    return xs * (1.0 - mask) + mask * value
+    # will be nan when value is `inf`.
+    # mask = mask.astype(xs.dtype)
+    # return xs * (1.0 - mask) + mask * value
+
+    bshape = broadcast_shape(xs.shape, mask.shape)
+    mask.stop_gradient = True
+    # tmp = paddle.ones(shape=[len(bshape)], dtype='int32')
+    # for index in range(len(bshape)):
+    #     tmp[index] = bshape[index]
+    mask = mask.broadcast_to(bshape)
+    trues = paddle.full_like(xs, fill_value=value)
+    xs = paddle.where(mask, trues, xs)
+    return xs
 
 
 if not hasattr(paddle.Tensor, 'masked_fill'):