conda 安装好tensorflow-gpu，import tensorflow报错

最新推荐文章于 2025-05-01 17:23:39 发布

magic_ll

最新推荐文章于 2025-05-01 17:23:39 发布

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本文介绍了一个关于在Anaconda环境中安装TensorFlow-GPU 1.8.0后，由于NumPy版本过高导致的警告错误。通过将NumPy版本回退到1.16.0，成功解决了该问题。

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问题：
在创建虚拟环境后，使用conda install tensorflow-gpu==1.8.0，成功安装好tensorflow，但是我们在运行import tensorflow时却报错：

C:\Users\USER\anaconda3\envs\BoNet\lib\site-packages\tensorflow\python\framework\dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
 _np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\USER\anaconda3\envs\BoNet\lib\site-packages\tensorflow\python\framework\dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
 _np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\USER\anaconda3\envs\BoNet\lib\site-packages\tensorflow\python\framework\dtypes.py:521: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
 _np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\USER\anaconda3\envs\BoNet\lib\site-packages\tensorflow\python\framework\dtypes.py:522: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
 _np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\USER\anaconda3\envs\BoNet\lib\site-packages\tensorflow\python\framework\dtypes.py:523: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
 _np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\USER\anaconda3\envs\BoNet\lib\site-packages\tensorflow\python\framework\dtypes.py:528: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
 np_resource = np.dtype([("resource", np.ubyte, 1)])