Ошибка в использовании tf.vectorized_map и tf.linalg.adjoint вместе

Question

import tensorflow as tf
import numpy as np

tf.vectorized_map(tf.linalg.adjoint,[[[0.92638035,0.86781654,0.07082932,0.05847008,0.8511125,0.36508426,0.93262938,0.50314175,0.42709555,0.70771005],
                                     [0.0939332,0.76758856,0.96512942,0.24077245,0.07860126,0.1635265,0.44031962,0.01234664,0.96572218,0.98906447],
                                     [0.11077884,0.88584282,0.65943618,0.12987475,0.15949519,0.33414308,0.87960809,0.83713104,0.60840816,0.9730074],
                                     [0.23029835,0.6888875,0.80855333,0.31993754,0.45145076,0.63365455,0.87677701,0.72228281,0.91911635,0.95122776],
                                     [0.21333733,0.45232663,0.35471942,0.44432004,0.43770469,0.37246978,0.54925199,0.80986723,0.85000438,0.73820948],
                                     [0.40354433,0.25843004,0.00363146,0.12305595,0.24252965,0.18175492,0.30010179,0.70433849,0.77924173,0.93688071],
                                     [0.78564701,0.53859908,0.14963083,0.95899188,0.92512729,0.29278922,0.54071035,0.71274694,0.34156953,0.80580388],
                                     [0.29272944,0.2288734,0.10608193,0.59221746,0.35921315,0.07014356,0.74207835,0.08194746,0.14855829,0.47673278],
                                     [0.68213703,0.96553305,0.4389587,0.26549066,0.25486691,0.66450013,0.24072084,0.31332454,0.61697049,0.83484757],
                                     [0.86981862,0.96334372,0.86572482,0.91249171,0.25454074,0.32785591,0.97890406,0.97341173,0.08787907,0.09747803]]])

Версия TensorFlow: 2.1.0

Когда я запускаю код, возникает ошибка:

IndexError: индекс списка вне диапазона

Разве я не могу использовать два API вместе?

---

Когда я изменил код таким образом, код будет работать нормально.

import tensorflow as tf
import numpy as np
x = np.arange(27).astype(np.float32).reshape(3,3,3)
print(tf.vectorized_map(tf.linalg.adjoint,x))

Но я нашел новый датчик, код выглядит следующим образом.

import tensorflow as tf
import numpy as np
x = np.arange(18).astype(np.float32).reshape(2,3,3)
print(tf.vectorized_map(tf.linalg.det,x))

Часть сообщения об ошибке приведена ниже.

ValueError: No converter defined for MatrixDeterminant
    name: "loop_body/MatrixDeterminant"
    op: "MatrixDeterminant"
    input: "loop_body/GatherV2"
    attr {
      key: "T"
      value {
        type: DT_FLOAT
      }
    }

    inputs: [WrappedTensor(t=<tf.Tensor 'loop_body/GatherV2/params:0' shape=(2, 3, 3) dtype=float32>, is_stacked=True, is_sparse_stacked=False)]. 
    Either add a converter or set --op_conversion_fallback_to_while_loop=True, which may run slower

Что-то не так с моим пониманием функции?