Anaconda环境Jupyter Notebook导入Tensorflow库报错问题求助

以下是运行的LSTM模型相关代码：

# lstm model
import tensorflow as tf
from numpy import mean
from numpy import std
from numpy import dstack
from pandas import read_csv
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import Flatten
from tensorflow.keras.layers import Dropout
from tensorflow.keras.layers import LSTM
from tensorflow.keras.utils import to_categorical
from matplotlib import pyplot

在Anaconda环境中使用Jupyter Notebook运行上述代码，导入依赖库时出现TensorFlow相关报错，使用的Python版本为3.9，已安装所有Python相关依赖包，触发的TypeError错误日志如下：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_10616/748904884.py in <module>
       1 # lstm model
 ----> 2 import tensorflow as tf
       3 from numpy import mean
       4 from numpy import std
       5 from numpy import dstack

~\AppData\Roaming\Python\Python39\site-packages\tensorflow\__init__.py in <module>
      39 import sys as _sys
      40 
 ---> 41 from tensorflow.python.tools import module_util as _module_util
      42 from tensorflow.python.util.lazy_loader import LazyLoader as _LazyLoader
      43 

~\AppData\Roaming\Python\Python39\site-packages\tensorflow\python\__init__.py in <module>
     44 
     45 # Bring in subpackages.
---> 46 from tensorflow.python import data
     47 from tensorflow.python import distribute
     48 # from tensorflow.python import keras

~\AppData\Roaming\Python\Python39\site-packages\tensorflow\python\data\__init__.py in <module>
     23 
     24 # pylint: disable=unused-import
---> 25 from tensorflow.python.data import experimental
     26 from tensorflow.python.data.ops.dataset_ops import AUTOTUNE
     27 from tensorflow.python.data.ops.dataset_ops import Dataset

~\AppData\Roaming\Python\Python39\sitepackages\tensorflow\python\data\experimental\__init__.py 
   in <module>
     96 
     97 # pylint: disable=unused-import
--- > 98 from tensorflow.python.data.experimental import service
     99 from tensorflow.python.data.experimental.ops.batching import dense_to_ragged_batch
    100 from tensorflow.python.data.experimental.ops.batching import dense_to_sparse_batch

  ~\AppData\Roaming\Python\Python39\site- 
  packages\tensorflow\python\data\experimental\service\__init__.py in <module>
    372 from __future__ import print_function
    373 
---> 374 from tensorflow.python.data.experimental.ops.data_service_ops import distribute
    375 from tensorflow.python.data.experimental.ops.data_service_ops import from_dataset_id
    376 from tensorflow.python.data.experimental.ops.data_service_ops import register_dataset

~\anaconda3\envs\mygpu\lib\site- 
 packages\tensorflow\python\data\experimental\ops\data_service_ops.py in <module>
     23 
     24 from tensorflow.python import tf2
---> 25 from tensorflow.python.data.experimental.ops import compression_ops
     26 from tensorflow.python.data.experimental.ops.distribute_options import AutoShardPolicy
     27 from tensorflow.python.data.experimental.ops.distribute_options import 
        ExternalStatePolicy

~\anaconda3\envs\mygpu\lib\site- 
    packages\tensorflow\python\data\experimental\ops\compression_ops.py in <module>
     18 from __future__ import print_function
     19 
--- > 20 from tensorflow.python.data.util import structure
     21 from tensorflow.python.ops import gen_experimental_dataset_ops as ged_ops
     22 

~\anaconda3\envs\mygpu\lib\site-packages\tensorflow\python\data\util\structure.py in <module>
     24 import wrapt
     25 
---> 26 from tensorflow.python.data.util import nest
     27 from tensorflow.python.framework import composite_tensor
     28 from tensorflow.python.framework import ops

~\anaconda3\envs\mygpu\lib\site-packages\tensorflow\python\data\util\nest.py in <module>
     38 import six as _six
     39 
---> 40 from tensorflow.python.framework import sparse_tensor as _sparse_tensor
     41 from tensorflow.python.util import _pywrap_utils
     42 from tensorflow.python.util import nest

~\anaconda3\envs\mygpu\lib\site-packages\tensorflow\python\framework\sparse_tensor.py in 
 <module>
     26 from tensorflow.python import tf2
     27 from tensorflow.python.framework import composite_tensor
--- > 28 from tensorflow.python.framework import constant_op
     29 from tensorflow.python.framework import dtypes
     30 from tensorflow.python.framework import ops

~\anaconda3\envs\mygpu\lib\site-packages\tensorflow\python\framework\constant_op.py in 
  <module>
     27 from tensorflow.core.framework import types_pb2
     28 from tensorflow.python.eager import context
--- > 29 from tensorflow.python.eager import execute
     30 from tensorflow.python.framework import dtypes
     31 from tensorflow.python.framework import op_callbacks

~\anaconda3\envs\mygpu\lib\site-packages\tensorflow\python\eager\execute.py in <module>
     25 from tensorflow.python import pywrap_tfe
     26 from tensorflow.python.eager import core
--- > 27 from tensorflow.python.framework import dtypes
     28 from tensorflow.python.framework import ops
     29 from tensorflow.python.framework import tensor_shape

~\anaconda3\envs\mygpu\lib\site-packages\tensorflow\python\framework\dtypes.py in <module>
     30 from tensorflow.python.util.tf_export import tf_export
     31 
--- > 32 _np_bfloat16 = _pywrap_bfloat16.TF_bfloat16_type()
     33 
     34 

TypeError: Unable to convert function return value to a Python type! The signature was
    () -> handle

• 修复NumPy和TensorFlow版本不兼容问题：该报错核心原因是NumPy版本过高，与当前安装的TensorFlow版本不匹配。你可以先在当前激活的conda环境中执行pip show numpy tensorflow查看二者版本，若使用TensorFlow 2.10及以下版本，将NumPy降级到1.23.x分支即可解决，执行命令：pip install numpy==1.23.5
• 清除多路径TensorFlow安装冲突：从报错日志可见，你在系统全局Python路径和当前conda虚拟环境路径都安装了TensorFlow，会导致导入时模块搜索混乱。多次执行pip uninstall tensorflow直到提示无相关安装包，再在激活的conda环境中重新安装对应版本的TensorFlow，保证仅在当前虚拟环境存在TensorFlow安装包即可。
• 重启Jupyter内核：完成上述操作后，在Jupyter界面选择「Kernel」-「Restart & Clear Output」，重新运行代码即可正常导入依赖。

内容的提问来源于stack exchange，提问作者Gun