[英]how do I correctly import tensorflow?
import tensorflow as tf
我在 Anaconda 解釋器中收到此消息...有人可以幫忙嗎?
謝謝!
ImportError Traceback (most recent call last)
~\anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py in <module>
57
---> 58 from tensorflow.python.pywrap_tensorflow_internal import *
59 from tensorflow.python.pywrap_tensorflow_internal import __version__
~\anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py in <module>
27 return _mod
---> 28 _pywrap_tensorflow_internal = swig_import_helper()
29 del swig_import_helper
~\anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py in swig_import_helper()
23 try:
---> 24 _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
25 finally:
~\anaconda3\lib\imp.py in load_module(name, file, filename, details)
241 else:
--> 242 return load_dynamic(name, filename, file)
243 elif type_ == PKG_DIRECTORY:
~\anaconda3\lib\imp.py in load_dynamic(name, path, file)
341 name=name, loader=loader, origin=path)
--> 342 return _load(spec)
343
ImportError: DLL load failed: Eine DLL-Initialisierungsroutine ist fehlgeschlagen.
During handling of the above exception, another exception occurred:
ImportError Traceback (most recent call last)
<ipython-input-1-64156d691fe5> in <module>
----> 1 import tensorflow as tf
~\anaconda3\lib\site-packages\tensorflow\__init__.py in <module>
22
23 # pylint: disable=g-bad-import-order
---> 24 from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
25
26 from tensorflow._api.v1 import app
~\anaconda3\lib\site-packages\tensorflow\python\__init__.py in <module>
47 import numpy as np
48
---> 49 from tensorflow.python import pywrap_tensorflow
50
51 # Protocol buffers
~\anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py in <module>
72 for some common reasons and solutions. Include the entire stack trace
73 above this error message when asking for help.""" % traceback.format_exc()
---> 74 raise ImportError(msg)
75
76 # pylint: enable=wildcard-import,g-import-not-at-top,unused-import,line-too-long
ImportError: Traceback (most recent call last):
File "C:\Users\MIGUEL\anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 58, in <module>
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\MIGUEL\anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 28, in <module>
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\MIGUEL\anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "C:\Users\MIGUEL\anaconda3\lib\imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "C:\Users\MIGUEL\anaconda3\lib\imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: DLL load failed: Eine DLL-Initialisierungsroutine ist fehlgeschlagen.
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions. Include the entire stack trace
above this error message when asking for help.
在這個(答案)部分指定答案,即使它出現在評論部分是為了社區的利益。
通過在New Virtual Environment
安裝Tensorflow
解決了問題。
使用虛擬環境具有以下優點
Virtual Environments
維護多個版本的Tensorflow
,每個Virtual Environment
包含每個版本,如Tensorflow
1.14, 1.15, 2.0, 2.1, 2.2,etc..
Virtual Environment
使用不同的Python Versions
( 2.x, 3.6, 3.7
)Tensorflow API
的source code
,我們可以在我們的Virtual Environment
,而不會影響其在其他Virtual Environments
功能。 在Anaconda
創建新的Virtual Environment
和安裝Tensorflow
步驟,對於不同的操作系統,如下所示:
# Create a New Virtual Environment
conda create --name TF_2_VE
# When conda asks you to proceed, type y:
proceed ([y]/n)?
# Activate the Virtual Environment. Conda Version > 4.6
conda activate TF_2_VE
# Activating Virtual Environment, Conda Version < 4.6 and Windows OS
activate TF_2_VE
# Activating Virtual Environment, Conda Version < 4.6 and Linux and Mac OS
source activate TF_2_VE
# Install the TF Version you need
conda install tensorflow
希望這些信息有幫助。 快樂學習!
要安裝當前版本的 CPU-only TensorFlow,推薦給初學者:
conda create -n tf tensorflow
conda activate tf
如果你已經有 cuda 軟件
conda create -n tf-gpu tensorflow-gpu
conda activate tf-gpu
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