fix broadcast_shape

deepspeech/utils/tensor_utils.py

@@ -25,6 +25,7 @@ __all__ = ["masked_fill", "pad_sequence", "add_sos_eos", "th_accuracy"]
 logger = Log(__name__).getlog()
 
 
+@paddle.jit.not_to_static
 def is_broadcastable(shp1, shp2):
     for a, b in zip(shp1[::-1], shp2[::-1]):
         if a == 1 or b == 1 or a == b:
@@ -39,10 +40,8 @@ def masked_fill(xs: paddle.Tensor,
                 value: Union[float, int]):
     if paddle.in_dynamic_mode():
         assert is_broadcastable(xs.shape, mask.shape) is True
-        bshape = paddle.broadcast_shape(xs.shape, mask.shape)
-    else:
-        # TODO(Hui Zhang): support broadcast_shape in static graph
-        bshape = xs.shape
+    # broadcast_shape input should be `list`
+    bshape = paddle.broadcast_shape(list(xs.shape), list(mask.shape))
     mask = mask.broadcast_to(bshape)
     trues = paddle.ones_like(xs) * value
     xs = paddle.where(mask, trues, xs)