背景:
需要用anaconda建一个python 3.5的虚拟环境,用Tensorflow做深度学习
开始的时候用默认镜像总是连接不成功,就加入了清华镜像
用清华的镜像可以新建环境并且安装tensorflow-gpu
但是导入tensorflow的时候会报错
错误表现
import tensorflow
Traceback (most recent call last):
File "D:\Users\lidon\Anaconda3\envs\tfgpu35_2\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "D:\Users\lidon\Anaconda3\envs\tfgpu35_2\lib\importlib\__init__.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 986, in _gcd_import
File "<frozen importlib._bootstrap>", line 969, in _find_and_load
File "<frozen importlib._bootstrap>", line 958, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 666, in _load_unlocked
File "<frozen importlib._bootstrap>", line 577, in module_from_spec
File "<frozen importlib._bootstrap_external>", line 919, in create_module
File "<frozen importlib._bootstrap>", line 222, in _call_with_frames_removed
ImportError: DLL load failed: 找不到指定的模块。
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "D:\Users\lidon\Anaconda3\envs\tfgpu35_2\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 41, in <module>
#以下省略
发生之后,我就百度各种搜,也有人有成功的解决方案,但是我试了不好使
我搜索了3个小时之后,基本把网上的方法试完了,还是没解决。
这让我不得不陷入了深深的思考,因为楼主以前用同样的方法建过3.6的环境,而且现在还可以用,为啥3.5的就不行了呢?而且楼主前两天还在另外一台机器上建3.5的成功了。
想到本次建环境和以前建的有一个明显区别就是这次用清华的镜像,以前用的是默认镜像,想到这里立马动手删掉清华镜像,重新新建环境,网路也是抽风,现在可以连接成功了,然后安装tensorflow-gpu,再次试import tenworflow导入成功;
Python 3.5.5 |Anaconda custom (64-bit)| (default, Apr 7 2018, 04:52:34) [MSC v.1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow
D:\Users\lidon\Anaconda3\envs\tfgpu35\lib\site-packages\h5py\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
>>>
希望能够对遇见同样问题的人有所帮助