1. The source of the problem
- Environment: win10
- Anaconda 2020.07.20
- Virtual environment tf2nlp + python3.7
The source of the problem: Because I used the company's notebook, I needed to install the environment for that notebook, installed Anaconda, created the virtual environment tf2nlp, entered the virtual environment, installed:, pip install tensorflow==2.0when starting python, importing tensorflow, the following error occurred. Then I went to the official website of Microsoft to download VC_redist.x64.exeand install according to the error message , but the error message remained the same. Related articles on the Internet all say to reduce the version of tf, but downgrading is not my idea, I want to use tensorflow2.x , I am a person who is not going to work , and tf1.x is out of date and no longer has it. Maintenance, so I am more determined to use tf2, so I have been insisting on finding a solution, and finally... (tearful and happy)
[Note: Everything is normal on my own personal computer! 】The
error is as follows:
ImportError: DLL load failed: 动态链接库(DLL)初始化例程失败。
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow\__init__.py", line 98, in <module>
from tensorflow_core import *
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow_core\__init__.py", line 42, in <module>
from . _api.v2 import audio
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow_core\_api\v2\audio\__init__.py", line 10, in <module>
from tensorflow.python.ops.gen_audio_ops import decode_wav
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow_core\python\ops\gen_audio_ops.py", line 9, in <module>
from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow\__init__.py", line 50, in __getattr__
module = self._load()
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow\__init__.py", line 44, in _load
module = _importlib.import_module(self.__name__)
File "C:\Anaconda3\envs\tf2nlp\lib\importlib\__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow_core\python\__init__.py", line 49, in <module>
from tensorflow.python import pywrap_tensorflow
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py", line 74, in <module>
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py", line 58, in <module>
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py", line 28, in <module>
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Anaconda3\envs\tf2nlp\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "C:\Anaconda3\envs\tf2nlp\lib\imp.py", line 243, in load_module
return load_dynamic(name, filename, file)
File "C:\Anaconda3\envs\tf2nlp\lib\imp.py", line 343, in load_dynamic
return _load(spec)
ImportError: DLL load failed: 动态链接库(DLL)初始化例程失败。
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.
2. Problem solving process:
-
After that, I immediately guessed that some dll files were missing, so I used dll repair software to repair it, but it didn’t work! The first attempt failed.
-
After that, I checked the environment variables, CUDA, CUDNN, and the version correspondence, and then reinstalled the virtual environment and tensorflow! Obviously, there is no use for eggs! Failed for the second time.
-
Switch to conda installation, the same error is reported.
-
For the third time, start Baidu! There are many opinions on the Internet, some say that you want to reduce the tensorflow version, some call to install the vc64-bit runtime library, some say it is caused by AVX instructions, some say it is caused by 64-bit 32-bit, and some say it is caused by the python version! In fact, these are not the key to the problem! The key is to look at the fourth point!
-
After that, the following error was reported during an occasional import, and then I went to compare the h5py library version before and after the upgrade, to compare the similarities and differences between before and after the upgrade, and found the following:
>>> import tensorflow as tf
C:\Anaconda3\envs\tf2nlp\lib\site-packages\h5py\__init__.py:40: UserWarning: h5py is running against HDF5 1.10.5 when it was built against 1.10.4, this may cause problems
'{0}.{1}.{2}'.format(*version.hdf5_built_version_tuple)
Warning! ***HDF5 library version mismatched error***
The HDF5 header files used to compile this application do not match
the version used by the HDF5 library to which this application is linked.
Data corruption or segmentation faults may occur if the application continues.
This can happen when an application was compiled by one version of HDF5 but
linked with a different version of static or shared HDF5 library.
You should recompile the application or check your shared library related
settings such as 'LD_LIBRARY_PATH'.
You can, at your own risk, disable this warning by setting the environment
variable 'HDF5_DISABLE_VERSION_CHECK' to a value of '1'.
Setting it to 2 or higher will suppress the warning messages totally.
Headers are 1.10.4, library is 1.10.5
SUMMARY OF THE HDF5 CONFIGURATION
=================================
General Information:
-------------------
HDF5 Version: 1.10.5
Configured on: 2019-03-04
Configured by: Visual Studio 15 2017 Win64
Host system: Windows-10.0.17763
Uname information: Windows
Byte sex: little-endian
Installation point: C:/Program Files/HDF5
Compiling Options:
------------------
Build Mode:
Debugging Symbols:
Asserts:
Profiling:
Optimization Level:
Linking Options:
----------------
Libraries:
Statically Linked Executables: OFF
LDFLAGS: /machine:x64
H5_LDFLAGS:
AM_LDFLAGS:
Extra libraries:
Archiver:
Ranlib:
Languages:
----------
C: yes
C Compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe 19.16.27027.1
CPPFLAGS:
H5_CPPFLAGS:
AM_CPPFLAGS:
CFLAGS: /DWIN32 /D_WINDOWS /W3
H5_CFLAGS:
AM_CFLAGS:
Shared C Library: YES
Static C Library: YES
Fortran: OFF
Fortran Compiler:
Fortran Flags:
H5 Fortran Flags:
AM Fortran Flags:
Shared Fortran Library: YES
Static Fortran Library: YES
C++: ON
C++ Compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe 19.16.27027.1
C++ Flags: /DWIN32 /D_WINDOWS /W3 /GR /EHsc
H5 C++ Flags:
AM C++ Flags:
Shared C++ Library: YES
Static C++ Library: YES
JAVA: OFF
JAVA Compiler:
Features:
---------
Parallel HDF5: OFF
Parallel Filtered Dataset Writes:
Large Parallel I/O:
High-level library: ON
Threadsafety: OFF
Default API mapping: v110
With deprecated public symbols: ON
I/O filters (external): DEFLATE DECODE ENCODE
MPE:
Direct VFD:
dmalloc:
Packages w/ extra debug output:
API Tracing: OFF
Using memory checker: OFF
Memory allocation sanity checks: OFF
Function Stack Tracing: OFF
Strict File Format Checks: OFF
Optimization Instrumentation:
Bye...
>>> import h5py
C:\Anaconda3\envs\tf2nlp\lib\site-packages\h5py\__init__.py:40: UserWarning: h5py is running against HDF5 1.10.5 when it was built against 1.10.4, this may cause problems
'{0}.{1}.{2}'.format(*version.hdf5_built_version_tuple)
Warning! ***HDF5 library version mismatched error***
The HDF5 header files used to compile this application do not match
the version used by the HDF5 library to which this application is linked.
Data corruption or segmentation faults may occur if the application continues.
This can happen when an application was compiled by one version of HDF5 but
linked with a different version of static or shared HDF5 library.
You should recompile the application or check your shared library related
settings such as 'LD_LIBRARY_PATH'.
You can, at your own risk, disable this warning by setting the environment
variable 'HDF5_DISABLE_VERSION_CHECK' to a value of '1'.
Setting it to 2 or higher will suppress the warning messages totally.
Headers are 1.10.4, library is 1.10.5
SUMMARY OF THE HDF5 CONFIGURATION
=================================
General Information:
-------------------
HDF5 Version: 1.10.5
Configured on: 2019-03-04
Configured by: Visual Studio 15 2017 Win64
Host system: Windows-10.0.17763
Uname information: Windows
Byte sex: little-endian
Installation point: C:/Program Files/HDF5
Compiling Options:
------------------
Build Mode:
Debugging Symbols:
Asserts:
Profiling:
Optimization Level:
Linking Options:
----------------
Libraries:
Statically Linked Executables: OFF
LDFLAGS: /machine:x64
H5_LDFLAGS:
AM_LDFLAGS:
Extra libraries:
Archiver:
Ranlib:
Languages:
----------
C: yes
C Compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe 19.16.27027.1
CPPFLAGS:
H5_CPPFLAGS:
AM_CPPFLAGS:
CFLAGS: /DWIN32 /D_WINDOWS /W3
H5_CFLAGS:
AM_CFLAGS:
Shared C Library: YES
Static C Library: YES
Fortran: OFF
Fortran Compiler:
Fortran Flags:
H5 Fortran Flags:
AM Fortran Flags:
Shared Fortran Library: YES
Static Fortran Library: YES
C++: ON
C++ Compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe 19.16.27027.1
C++ Flags: /DWIN32 /D_WINDOWS /W3 /GR /EHsc
H5 C++ Flags:
AM C++ Flags:
Shared C++ Library: YES
Static C++ Library: YES
JAVA: OFF
JAVA Compiler:
Features:
---------
Parallel HDF5: OFF
Parallel Filtered Dataset Writes:
Large Parallel I/O:
High-level library: ON
Threadsafety: OFF
Default API mapping: v110
With deprecated public symbols: ON
I/O filters (external): DEFLATE DECODE ENCODE
MPE:
Direct VFD:
dmalloc:
Packages w/ extra debug output:
API Tracing: OFF
Using memory checker: OFF
Memory allocation sanity checks: OFF
Function Stack Tracing: OFF
Strict File Format Checks: OFF
Optimization Instrumentation:
Bye...
After the upgrade is found, tensorflow can be imported normally:
Note that I upgraded h5py with pip, of course conda is also possible.
pip install -U h5py
>>> import tensorflow
>>>
I hope it will be helpful to you who are reading. Welcome to one-click triple connection, I will insist on sharing some of my mistake notes on the blog
