BERT 模型复现报错: Cannot convert a symbolic Tensor (bert/encoder/strided

BERT 模型复现 报错
报错提示信息：NotImplementedError: Cannot convert a symbolic Tensor (bert/encoder/strided_slice:0) to a numpy array.

W0505 17:07:49.208633 140668126729024 error_handling.py:135] Reraising captured error
Traceback (most recent call last):
  File "run_classifier.py", line 984, in 
    tf.app.run()
  File "/home/thy/anaconda3/envs/tf115/lib/python3.7/site-packages/tensorflow_core/python/platform/app.py", line 40, in run
    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
  File "/home/thy/anaconda3/envs/tf115/lib/python3.7/site-packages/absl/app.py", line 312, in run
    _run_main(main, args)
    
  .............
  
  File "/home/thy/anaconda3/envs/tf115/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 736, in __array__
    " array.".format(self.name))
NotImplementedError: Cannot convert a symbolic Tensor (bert/encoder/strided_slice:0) to a numpy array.

降低numpy 版本，例如我的tensorflow是1.15的，numpy版本调整为 1.16.5
ps：选择numpy == 1.16.5 另一个原因是为了满足 scipy （==1.7.3）
另外，建议用pip安装，conda install 会提示调整其他包的版本

pip install numpy==1.16.5