问将两个tensorflow数据集连接到一个dataset元素中，如示例所示

EN

tf.Tensor([ 1.     72.      0.      5.6431 28.199 ], shape=(5,), dtype=float64)

tf.Tensor(
[6.6200e-03 3.3800e-05 4.0100e-03 3.1700e-03 1.2040e-02 2.5650e-02
 2.3000e-01 1.4380e-02 1.3090e-02 1.6620e-02 4.3140e-02 1.4290e-02
 2.1640e+01 4.1888e-01 5.4842e-01 1.6006e-01], shape=(16,), dtype=float64)
tf.Tensor(34.398, shape=(), dtype=float64)

tf.Tensor(
[1.     72.      0.      5.6431 28.199, 6.6200e-03 3.3800e-05 4.0100e-03 3.1700e-03 1.2040e-02 2.5650e-02
 2.3000e-01 1.4380e-02 1.3090e-02 1.6620e-02 4.3140e-02 1.4290e-02
 2.1640e+01 4.1888e-01 5.4842e-01 1.6006e-01], shape=(21,), dtype=float64)
tf.Tensor(34.398, shape=(), dtype=float64)

for featb, feate,label in packed_ds.take(1):
     print("featb: ", featb,'\n',"feate: " , feate,'\n')
     tf.concat([featb, feate], axis=1)

 featb:  tf.Tensor([ 1.     72.      0.      5.6431 28.199 ], shape=(5,), 
   dtype=float64) 
  feate:  tf.Tensor(
 [6.6200e-03 3.3800e-05 4.0100e-03 3.1700e-03 1.2040e-02 2.5650e-02
 2.3000e-01 1.4380e-02 1.3090e-02 1.6620e-02 4.3140e-02 1.4290e-02
 2.1640e+01 4.1888e-01 5.4842e-01 1.6006e-01], shape=(16,), dtype=float64) 

 ---------------------------------------------------------------------------
  InvalidArgumentError                      Traceback (most recent call 
  last)
  <ipython-input-16-3cb13cecc2c2> in <module>()
  1 for featb, feate,label in packed_ds.take(1):
  2   print("featb: ", featb,'\n',"feate: " , feate,'\n')
  ----> 3 tf.concat([featb, feate], axis=1)

  4 frames
  /usr/local/lib/python3.6/dist-packages/six.py in raise_from(value, 
   from_value)

   InvalidArgumentError: ConcatOp : Expected concatenating dimensions in 
   the range [-1, 1), but got 1 [Op:ConcatV2] name: concat

   As I could not add my error as comment, I have edited the question