目錄

• • • • 一、問題描述
      • 二、原因分析
      • 三、處理過程
      • 四、解決方法
      • 五、安裝2.1和2.0命令的不同點
      • • 1、TensorFlow2.0
        • 2、TensorFlow2.1
      • 六、使用TenforFlow2.0-GPU時，報錯:cudart64_100.dll not found
      • • 1、錯誤信息如下
        • 2、原因分析
        • 3、解決方法
      • 七、測試TensorFlow是否支持GPU
      • • 1、測試對cuda的支持
        • 2、測試對GPU的支持

一、問題描述

在win10上安裝TensorFlow2成功，但是在使用時（import tensorflow ）報錯。這個問題困擾了我兩天兩夜，熬了兩宿終于解決了，趕緊記錄下來。
錯誤信息如下：

 import tensorflow as tf
Traceback (most recent call last):File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py", line 58, in <module>from tensorflow.python.pywrap_tensorflow_internal import *File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py", line 28, in <module>_pywrap_tensorflow_internal = swig_import_helper()File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\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:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\imp.py", line 243, in load_modulereturn load_dynamic(name, filename, file)File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\imp.py", line 343, in load_dynamicreturn _load(spec)
ImportError: DLL load failed: 找不到指定的模塊。During handling of the above exception, another exception occurred:Traceback (most recent call last):File "<stdin>", line 1, in <module>File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\site-packages\tensorflow\__init__.py", line 101, in <module>from tensorflow_core import *File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\site-packages\tensorflow_core\__init__.py", line 40, in <module>from tensorflow.python.tools import module_util as _module_utilFile "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\site-packages\tensorflow\__init__.py", line 50, in __getattr__module = self._load()File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\site-packages\tensorflow\__init__.py", line 44, in _loadmodule = _importlib.import_module(self.__name__)File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\importlib\__init__.py", line 126, in import_modulereturn _bootstrap._gcd_import(name[level:], package, level)File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\site-packages\tensorflow_core\python\__init__.py", line 49, in <module>from tensorflow.python import pywrap_tensorflowFile "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py", line 74, in <module>raise ImportError(msg)
ImportError: Traceback (most recent call last):File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py", line 58, in <module>from tensorflow.python.pywrap_tensorflow_internal import *File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py", line 28, in <module>_pywrap_tensorflow_internal = swig_import_helper()File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\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:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\imp.py", line 243, in load_modulereturn load_dynamic(name, filename, file)File "C:\Users\gwlbl\Anaconda3\envs\tf2.1cpu\lib\imp.py", line 343, in load_dynamicreturn _load(spec)
ImportError: DLL load failed: 找不到指定的模塊。Failed to load the native TensorFlow runtime.See https://www.tensorflow.org/install/errorsfor some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

二、原因分析

導致錯誤的本質原因沒有找到，在嘗試安裝v2.0版本后，才沒有出現這個錯誤。

三、處理過程

截至今天（2020-2-12）TensorFlow的最新穩定版本是v2.1，在win10 + python3.6 + pip2.0環境下默認安裝的就是最新的版本v2.1。安裝過程沒有異常，但是在使用時就會報上述錯誤。導致錯誤的本質原因沒有找到，在嘗試安裝v2.0版本后，才沒有出現這個錯誤。
其它嘗試都會報錯，如：

將CUDA版本改為10.1、10.2；
嘗試安裝v2.1的cpu和gpu版本；
嘗試Python3.7和Python3.6；
嘗試刪除protobuf

四、解決方法

使用pip安裝時指定版本：

pip install tensorflow==2.0.0

或

pip install tensorflow-gpu==2.0.0

五、安裝2.1和2.0命令的不同點

在使用命令pip install tensorflow安裝TensorFlow2.1時，將會同時安裝cpu和gpu；
安裝TensorFlow2.1或2.0的命令略有不用，匯總如下

1、TensorFlow2.0

單獨安裝CPU：pip install tensorflow ==2.0.0
單獨安裝GPU：pip install tensorflow-gpu ==2.0.0

2、TensorFlow2.1

單獨安裝CPU：pip install tensorflow-cpu == 2.1.0
單獨安裝GPU：pip install tensorflow-gpu== 2.1.0
同時安裝CPU和GPU：pip install tensorflow==2.1.0

六、使用TenforFlow2.0-GPU時，報錯:cudart64_100.dll not found

1、錯誤信息如下

import tensorflow as tf
2020-02-12 01:12:14.047720: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_100.dll'; dlerror: cudart64_100.dll not found

2、原因分析

cudart64_100.dll是CUDA10.0版本中的庫，而我安裝是最新的（截至2020-2-12）CUDA10.2，這個版本中cudart64庫的名字是cudart64_102.dll，因此報錯沒有找到cudart64_100.dll。

3、解決方法

一種解決方法是重新安裝CUDA10.0的版本；
另外一種簡單方法是，直接找到cudart64_102.dll將它修改為cudart64_100.dll（這個方法不太嚴謹，不知道以后會不會報錯）
更改后的打印信息

>>> import tensorflow as tf
2020-02-12 01:15:35.685062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll

七、測試TensorFlow是否支持GPU

1、測試對cuda的支持

>>> tf.test.is_built_with_cuda()
True

2、測試對GPU的支持

>>> tf.test.is_gpu_available(cuda_only=False,min_cuda_compute_capability=None)
2020-02-12 01:17:21.667124: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2020-02-12 01:17:21.681120: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2020-02-12 01:17:22.159708: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce 940MX major: 5 minor: 0 memoryClockRate(GHz): 1.189
pciBusID: 0000:01:00.0
2020-02-12 01:17:22.208181: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2020-02-12 01:17:22.246881: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2020-02-12 01:17:22.579081: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-02-12 01:17:22.587504: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0
2020-02-12 01:17:22.593051: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N
2020-02-12 01:17:22.601454: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/device:GPU:0 with 1464 MB memory) -> physical GPU (device: 0, name: GeForce 940MX, pci bus id: 0000:01:00.0, compute capability: 5.0)
True