[英]Importing TensorFlow 1.9.0 on Jupyter Notebook Causes an Error
[英]Error importing TensorFlow GPU in Jupyter Notebook
我試圖導入TensorFlow但最終出現此錯誤。
ImportError Traceback (most recent call last)
/Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/__init__.py in <module>()
60 sys.setdlopenflags(_default_dlopen_flags | ctypes.RTLD_GLOBAL)
---> 61 from tensorflow.python import pywrap_tensorflow
62 sys.setdlopenflags(_default_dlopen_flags)
/Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/pywrap_tensorflow.py in <module>()
27 return _mod
---> 28 _pywrap_tensorflow = swig_import_helper()
29 del swig_import_helper
/Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/pywrap_tensorflow.py in swig_import_helper()
23 try:
---> 24 _mod = imp.load_module('_pywrap_tensorflow', fp, pathname, description)
25 finally:
/Users/Aakaash/miniconda3/lib/python3.5/imp.py in load_module(name, file, filename, details)
241 else:
--> 242 return load_dynamic(name, filename, file)
243 elif type_ == PKG_DIRECTORY:
/Users/Aakaash/miniconda3/lib/python3.5/imp.py in load_dynamic(name, path, file)
341 name=name, loader=loader, origin=path)
--> 342 return _load(spec)
343
ImportError: dlopen(/Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/_pywrap_tensorflow.so, 10): Library not loaded: @rpath/libcudart.8.0.dylib
Referenced from: /Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/_pywrap_tensorflow.so
Reason: image not found
During handling of the above exception, another exception occurred:
ImportError Traceback (most recent call last)
<ipython-input-7-a649b509054f> in <module>()
----> 1 import tensorflow
/Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/__init__.py in <module>()
22
23 # pylint: disable=wildcard-import
---> 24 from tensorflow.python import *
25 # pylint: enable=wildcard-import
26
/Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/__init__.py in <module>()
70 for some common reasons and solutions. Include the entire stack trace
71 above this error message when asking for help.""" % traceback.format_exc()
---> 72 raise ImportError(msg)
73
74 # Protocol buffers
ImportError: Traceback (most recent call last):
File "/Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/__init__.py", line 61, in <module>
from tensorflow.python import pywrap_tensorflow
File "/Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/pywrap_tensorflow.py", line 28, in <module>
_pywrap_tensorflow = swig_import_helper()
File "/Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/pywrap_tensorflow.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow', fp, pathname, description)
File "/Users/Aakaash/miniconda3/lib/python3.5/imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "/Users/Aakaash/miniconda3/lib/python3.5/imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: dlopen(/Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/_pywrap_tensorflow.so, 10): Library not loaded: @rpath/libcudart.8.0.dylib
Referenced from: /Users/Aakaash/miniconda3/lib/python3.5/site-packages/tensorflow/python/_pywrap_tensorflow.so
Reason: image not found
Failed to load the native TensorFlow runtime.
See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md#import_error
for some common reasons and solutions. Include the entire stack trace
above this error message when asking for help.
我能夠毫無問題地導入TensorFlow的CPU版本。 我也可以在從終端發起的Python控制台中導入TensorFlow。 在Console和Jupyter Notebook中,python可執行文件的路徑是相同的( sys.executable
在Console和Jupyter Notebook中給出了相同的輸出)。
TensorFlow版本 - 1.0.0
Python版本 - 3.5.2
Cuda版本 - 8.0
看起來錯誤是我設置CUDA和CuDNN時的錯誤。 按照Nvidia提供的指南,它告訴我為Mac OS X設置DYLD_LIBRARY_PATH
的路徑。不幸的是,這在使用Jupyter Notebook時不起作用。 我們需要遵循Nvidia指南對Linux的步驟並設置LD_LIBRARY_PATH
。 這解決了這個問題。
在我的情況下,當啟動Jupyter筆記本時, LD_LIBRARY_PATH
被清除,即使將它導出到Ubuntu上的.bashrc
和.profile
中。 只有啟動帶有env VARIABLE=$VARIABLE jupyter notebook
的筆記本電腦服務器解決了它。
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