【win10和linux版】tensorflow-gpu配置踩坑心得（python3.6 + cuda10.0 + keras2.2.4 + tensorflow-gpu1.13.1）

迷南。 2022-11-04 12:29 18阅读 0赞

### 文章目录 ###

*  一、安装问题汇总
 *  二、keras在代码中实现tensorboard记录绘图
 *  三、cudnn环境变量配置
 *  四、tensorboard报错
 *  四、linux配置环境错误
 *  五、报错：AttributeError: 'str' object has no attribute 'decode'
 *  六、源
 *  七、多gpu运算报错
 *  八、pytorch==1.2.0安装
 *  九、opencv==3.4.3安装
 *  参考

注意：在linux是区分大小写的，但是在windows中，不区分，所以如果数据是.JPG，在linux中用.jpg是读不出来的

# 一、安装问题汇总 #

[【anaconda】conda创建、查看、删除虚拟环境（anaconda命令集）][anaconda_conda_anaconda]  
[cuda10.0下载地址][cuda10.0]  
[cuDNN v7.6.5 (November 5th, 2019), for CUDA 10.0][cuDNN v7.6.5 _November 5th_ 2019_ for CUDA 10.0]

**keras中调用tensorflow-gpu**

import keras.backend.tensorflow_backend as KTF
    import os
    
    #进行配置，每个GPU使用90%上限现存
    os.environ["CUDA_VISIBLE_DEVICES"]="0" # 使用编号为0，1号的GPU
    config = tf.ConfigProto()
    config.gpu_options.per_process_gpu_memory_fraction = 0.9 # 每个GPU上限控制在90%以内
    session = tf.Session(config=config)
    # 设置session
    KTF.set_session(session)

**配置完cuda10.0 + keras2.1.5 + tensorflow-gpu1.14后，再次报错：**

2021-03-03 09:40:02.989207: W tensorflow/core/common_runtime/bfc_allocator.cc:319] ****************************************************************************************************
    2021-03-03 09:40:02.989419: W tensorflow/core/framework/op_kernel.cc:1502] OP_REQUIRES failed at constant_op.cc:172 : Resource exhausted: OOM when allocating tensor with shape[8,304,104,104] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
    Traceback (most recent call last):
      File "D:\ananconda\lib\site-packages\tensorflow\python\client\session.py", line 1356, in _do_call
        return fn(*args)
      File "D:\ananconda\lib\site-packages\tensorflow\python\client\session.py", line 1341, in _run_fn
        options, feed_dict, fetch_list, target_list, run_metadata)
      File "D:\ananconda\lib\site-packages\tensorflow\python\client\session.py", line 1429, in _call_tf_sessionrun
        run_metadata)
    tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
      (0) Resource exhausted: OOM when allocating tensor with shape[8,304,104,104] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
    	 [[{ { node decoder_conv0_depthwise_BN/FusedBatchNorm}}]]
    Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
    
    	 [[loss/mul/_3631]]
    Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
    
      (1) Resource exhausted: OOM when allocating tensor with shape[8,304,104,104] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
    	 [[{ { node decoder_conv0_depthwise_BN/FusedBatchNorm}}]]
    Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
    
    0 successful operations.
    0 derived errors ignored.
    
    During handling of the above exception, another exception occurred:
    
    Traceback (most recent call last):
      File "D:/pycharm/Semantic-Segmentation-master/deeplab_Mobile/train.py", line 145, in <module>
        callbacks=[checkpoint_period, reduce_lr, early_stopping])
      File "D:\ananconda\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper
        return func(*args, **kwargs)
      File "D:\ananconda\lib\site-packages\keras\engine\training.py", line 2224, in fit_generator
        class_weight=class_weight)
      File "D:\ananconda\lib\site-packages\keras\engine\training.py", line 1883, in train_on_batch
        outputs = self.train_function(ins)
      File "D:\ananconda\lib\site-packages\keras\backend\tensorflow_backend.py", line 2478, in __call__
        **self.session_kwargs)
      File "D:\ananconda\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
        run_metadata_ptr)
      File "D:\ananconda\lib\site-packages\tensorflow\python\client\session.py", line 1173, in _run
        feed_dict_tensor, options, run_metadata)
      File "D:\ananconda\lib\site-packages\tensorflow\python\client\session.py", line 1350, in _do_run
        run_metadata)
      File "D:\ananconda\lib\site-packages\tensorflow\python\client\session.py", line 1370, in _do_call
        raise type(e)(node_def, op, message)
    tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
      (0) Resource exhausted: OOM when allocating tensor with shape[8,304,104,104] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
    	 [[node decoder_conv0_depthwise_BN/FusedBatchNorm (defined at \ananconda\lib\site-packages\keras\backend\tensorflow_backend.py:1802) ]]
    Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
    
    	 [[loss/mul/_3631]]
    Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
    
      (1) Resource exhausted: OOM when allocating tensor with shape[8,304,104,104] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
    	 [[node decoder_conv0_depthwise_BN/FusedBatchNorm (defined at \ananconda\lib\site-packages\keras\backend\tensorflow_backend.py:1802) ]]
    Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
    
    0 successful operations.
    0 derived errors ignored.
    
    Errors may have originated from an input operation.
    Input Source operations connected to node decoder_conv0_depthwise_BN/FusedBatchNorm:
     decoder_conv0_depthwise/depthwise (defined at \ananconda\lib\site-packages\keras\backend\tensorflow_backend.py:3522)	
     decoder_conv0_depthwise_BN/beta/read (defined at \ananconda\lib\site-packages\keras\backend\tensorflow_backend.py:395)
    
    Input Source operations connected to node decoder_conv0_depthwise_BN/FusedBatchNorm:
     decoder_conv0_depthwise/depthwise (defined at \ananconda\lib\site-packages\keras\backend\tensorflow_backend.py:3522)	
     decoder_conv0_depthwise_BN/beta/read (defined at \ananconda\lib\site-packages\keras\backend\tensorflow_backend.py:395)
    
    Original stack trace for 'decoder_conv0_depthwise_BN/FusedBatchNorm':
      File "/pycharm/Semantic-Segmentation-master/deeplab_Mobile/train.py", line 87, in <module>
        model = Deeplabv3(classes=NCLASSES,input_shape=(HEIGHT,WIDTH,3))
      File "\pycharm\Semantic-Segmentation-master\deeplab_Mobile\nets\deeplab.py", line 124, in Deeplabv3
        depth_activation=True, epsilon=1e-5)
      File "\pycharm\Semantic-Segmentation-master\deeplab_Mobile\nets\deeplab.py", line 47, in SepConv_BN
        x = BatchNormalization(name=prefix + '_depthwise_BN', epsilon=epsilon)(x)
      File "\ananconda\lib\site-packages\keras\engine\topology.py", line 619, in __call__
        output = self.call(inputs, **kwargs)
      File "\ananconda\lib\site-packages\keras\layers\normalization.py", line 181, in call
        epsilon=self.epsilon)
      File "\ananconda\lib\site-packages\keras\backend\tensorflow_backend.py", line 1827, in normalize_batch_in_training
        epsilon=epsilon)
      File "\ananconda\lib\site-packages\keras\backend\tensorflow_backend.py", line 1802, in _fused_normalize_batch_in_training
        data_format=tf_data_format)
      File "\ananconda\lib\site-packages\tensorflow\python\ops\nn_impl.py", line 1329, in fused_batch_norm
        name=name)
      File "\ananconda\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 4301, in _fused_batch_norm
        name=name)
      File "\ananconda\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
        op_def=op_def)
      File "\ananconda\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
        return func(*args, **kwargs)
      File "\ananconda\lib\site-packages\tensorflow\python\framework\ops.py", line 3616, in create_op
        op_def=op_def)
      File "\ananconda\lib\site-packages\tensorflow\python\framework\ops.py", line 2005, in __init__
        self._traceback = tf_stack.extract_stack()

*  发现是由于显存不足而报的错，将batch\_size由8改为4，问题解决，正常运行。

# 二、keras在代码中实现tensorboard记录绘图 #

*  方法是在`model.fit_generator()`中加入 `TensorBoard(log_dir="./logs", histogram_freq=0, batch_size=4, write_grads=True)`，然后再控制台中输入`tensorboard --logdir=./logs --host=127.0.0.1 --port=6006`，得到可视化界面。

import tensorflow as tf
    from nets.deeplab import Deeplabv3
    from keras.utils.data_utils import get_file
    from keras.optimizers import Adam
    from keras.callbacks import TensorBoard, ModelCheckpoint, ReduceLROnPlateau, EarlyStopping
    from PIL import Image
    import time
    import keras
    from keras import backend as K
    import numpy as np
    import keras.backend.tensorflow_backend as KTF
    import os
    
        # 开始训练
        model.fit_generator(generate_arrays_from_file(lines[:num_train], batch_size),
                steps_per_epoch=max(1, num_train//batch_size),
                validation_data=generate_arrays_from_file(lines[num_train:], batch_size),
                validation_steps=max(1, num_val//batch_size),
                epochs=100,
                initial_epoch=0,
                # 早停版本
                # callbacks=[checkpoint_period, reduce_lr, early_stopping,
                # TensorBoard(log_dir="./logs", histogram_freq=0, batch_size=4, write_grads=True)])
                callbacks = [checkpoint_period, reduce_lr,
                     TensorBoard(log_dir="./logs", histogram_freq=0, batch_size=4, write_grads=True)])
    
        model.save_weights(log_dir+'last1.h5')

# 三、cudnn环境变量配置 #

ImportError: Could not find 'cudart64_100.dll'. TensorFlow requires that this DLL be installed in a directory that is named in your %PATH% environment variable. Download and install CUDA 10.0 from this URL: https://developer.nvidia.com/cuda-90-download-archive

*  在配置好cudnn环境后，建议重启pycharm或者powershell跟新配置，以解决此问题

# 四、tensorboard报错 #

d:\anaconda\anaconda\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      _np_qint8 = np.dtype([("qint8", np.int8, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      _np_quint8 = np.dtype([("quint8", np.uint8, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      _np_qint16 = np.dtype([("qint16", np.int16, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      _np_quint16 = np.dtype([("quint16", np.uint16, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      _np_qint32 = np.dtype([("qint32", np.int32, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      np_resource = np.dtype([("resource", np.ubyte, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorflow\python\framework\dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      _np_qint8 = np.dtype([("qint8", np.int8, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorflow\python\framework\dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      _np_quint8 = np.dtype([("quint8", np.uint8, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorflow\python\framework\dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      _np_qint16 = np.dtype([("qint16", np.int16, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorflow\python\framework\dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      _np_quint16 = np.dtype([("quint16", np.uint16, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorflow\python\framework\dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      _np_qint32 = np.dtype([("qint32", np.int32, 1)])
    d:\anaconda\anaconda\lib\site-packages\tensorflow\python\framework\dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
      np_resource = np.dtype([("resource", np.ubyte, 1)])
    Traceback (most recent call last):
      File "d:\anaconda\anaconda\lib\runpy.py", line 193, in _run_module_as_main
        "__main__", mod_spec)
      File "d:\anaconda\anaconda\lib\runpy.py", line 85, in _run_code
        exec(code, run_globals)
      File "D:\Anaconda\anaconda\Scripts\tensorboard.exe\__main__.py", line 4, in <module>
      File "d:\anaconda\anaconda\lib\site-packages\tensorboard\main.py", line 40, in <module>
        from tensorboard import default
      File "d:\anaconda\anaconda\lib\site-packages\tensorboard\default.py", line 39, in <module>
        from tensorboard.plugins.beholder import beholder_plugin_loader
      File "d:\anaconda\anaconda\lib\site-packages\tensorboard\plugins\beholder\__init__.py", line 22, in <module>
        from tensorboard.plugins.beholder.beholder import Beholder
      File "d:\anaconda\anaconda\lib\site-packages\tensorboard\plugins\beholder\beholder.py", line 199, in <module>
        class BeholderHook(tf.estimator.SessionRunHook):
      File "d:\anaconda\anaconda\lib\site-packages\tensorflow\python\util\deprecation_wrapper.py", line 106, in __getattr__
        attr = getattr(self._dw_wrapped_module, name)
    AttributeError: module 'tensorflow' has no attribute 'estimator'

*  **解决方法是在d:\\anaconda\\anaconda\\lib\\site-packages\\tensorboard\\plugins\\beholder\\beholder.py中，将beholder.py中类class BeholderHook(tf.estimator.SessionRunHook):的括号中内容删除，就没有报错了。  
    TF2 取消了SESSION，可以不用**
 *  **一定要是python3.6，不然tensorboard会报错！！！！！！！！！！**

# 四、linux配置环境错误 #

2021-03-13 17:53:43.280913: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcudart.so.10.0'; dlerror: libcudart.so.10.0: cannot open shared object file: No such file or directory
    2021-03-13 17:53:43.281034: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcublas.so.10.0'; dlerror: libcublas.so.10.0: cannot open shared object file: No such file or directory
    2021-03-13 17:53:43.281145: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcufft.so.10.0'; dlerror: libcufft.so.10.0: cannot open shared object file: No such file or directory
    2021-03-13 17:53:43.281253: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcurand.so.10.0'; dlerror: libcurand.so.10.0: cannot open shared object file: No such file or directory
    2021-03-13 17:53:43.281359: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcusolver.so.10.0'; dlerror: libcusolver.so.10.0: cannot open shared object file: No such file or directory
    2021-03-13 17:53:43.281463: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcusparse.so.10.0'; dlerror: libcusparse.so.10.0: cannot open shared object file: No such file or directory
    2021-03-13 17:53:43.281569: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcudnn.so.7'; dlerror: libcudnn.so.7: cannot open shared object file: No such file or directory
    2021-03-13 17:53:43.281592: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1663] Cannot dlopen some GPU libraries. Skipping registering GPU devices...
    2021-03-13 17:53:43.281658: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
    2021-03-13 17:53:43.281681: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187]      0 1 
    2021-03-13 17:53:43.281695: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0:   N N 
    2021-03-13 17:53:43.281706: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 1:   N N

*  上述文件都在`/usr/local/cuda-10.0/lib64/`目录下，该目录下的文件下图列出。本来文件都好好的在原来的目录，但是tensorflow死活找不到他们。  
    ![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21pcmFjbGVvYQ_size_16_color_FFFFFF_t_70]
 *  报这个错之后，程序能跑，但是特别慢，龟速，只用到了cpu。我在修复之前的操作是将`tensorflow-gpu==1.14.0`卸载了，然后安装了一下`tensorflow-gpu==1.13.1`。很有可能是这一步改变了tensorflow的某个配置文件，导致它又能够读取到`/usr/local/cuda-10.0/lib64/`目录下的配置文件了。
 *  接下来我列举一下我认为可能有效的所有的操作：首先我卸载了miniconda3，安装了anaconda，重新安装了`tensorflow-gpu==1.14.0`，`keras==2.1.5`，运行程序发现没用。
 *  然后我重新打开了`~/.bashrc`文件，将lib64的路径重新复制了一遍：`export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-10.0/lib64/`。`~/.bashrc`的配置具体如下：

export PATH="/home/sunqilin/anaconda3/bin:$PATH"
    
    export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-10.0/lib64/
    export PATH=$PATH:/usr/local/cuda-10.0/bin
    export CUDA_HOME=$CUDA_HOME:/usr/local/cuda-10.0

*  参考：[Tensorflow 缺少 libcusolver.so.10 和 libcudnn.so.8 两个库的解决办法][Tensorflow _ libcusolver.so.10 _ libcudnn.so.8]

--------------------

# 五、报错：AttributeError: ‘str’ object has no attribute ‘decode’ #

https://github.com/fchollet/deep-learning-models/releases/download/v0.6/mobilenet_1_0_224_tf_no_top.h5
    Traceback (most recent call last):
      File "/home/user-zhm/sql/Unet_attention/train.py", line 80, in <module>
        model.load_weights(weights_path, by_name=True, skip_mismatch=True)
      File "/home/user-zhm/anaconda3/envs/tensorflow-gpu/lib/python3.6/site-packages/keras/engine/topology.py", line 2653, in load_weights
        reshape=reshape)
      File "/home/user-zhm/anaconda3/envs/tensorflow-gpu/lib/python3.6/site-packages/keras/engine/topology.py", line 3407, in load_weights_from_hdf5_group_by_name
        original_keras_version = f.attrs['keras_version'].decode('utf8')
    AttributeError: 'str' object has no attribute 'decode'

*  **解决办法：卸载原来的h5py模块，安装2.10版本**

pip install h5py==2.10 -i https://pypi.tuna.tsinghua.edu.cn/simple/

[参考][Link 1]

--------------------

# 六、源 #

*  推荐豆瓣源

阿里云 http://mirrors.aliyun.com/pypi/simple/
    
    中国科技大学 https://pypi.mirrors.ustc.edu.cn/simple/
    
    豆瓣(douban) http://pypi.douban.com/simple/
    
    清华大学 https://pypi.tuna.tsinghua.edu.cn/simple/
    
    中国科学技术大学 http://pypi.mirrors.ustc.edu.cn/simple/

--------------------

# 七、多gpu运算报错 #

AttributeError: '_TfDeviceCaptureOp' object has no attribute '_set_device_from_string'

*  tensorflow版本可能有问题，所以将tensorflow从1.14.0版本降到1.13.1版本，keras改到2.2.4版本，此问题得到解决。

# 八、pytorch==1.2.0安装 #

# CUDA 10.0
    pip install torch==1.2.0 torchvision==0.4.0

# 九、opencv==3.4.3安装 #

*  [3.4.3下载地址][3.4.3]
 *  [安装教程][Link 2]

# 参考 #

*  [ModuleNotFoundError: No module named ‘\_pywrap\_tensorflow\_internal’–解决方法][ModuleNotFoundError_ No module named _pywrap_tensorflow_internal]
 *  [Win10安装CUDA10和cuDNN][Win10_CUDA10_cuDNN]
 *  [linux版本cuda安装配置][linux_cuda]
 *  [AttributeError: ‘str’ object has no attribute ‘decode’][Link 1]
 *  [Tensorflow 缺少 libcusolver.so.10 和 libcudnn.so.8 两个库的解决办法][Tensorflow _ libcusolver.so.10 _ libcudnn.so.8]
 *  [AttributeError: ‘str’ object has no attribute ‘decode’][Link 1]
 *  [TensorFlow1.2~2.1各个GPU版本CUDA和cuDNN对应版本整理][TensorFlow1.2_2.1_GPU_CUDA_cuDNN]
 *  [tensorflow-gpu与cuda、keras之间的对应关系][tensorflow-gpu_cuda_keras]

[anaconda_conda_anaconda]: https://blog.csdn.net/miracleoa/article/details/106115730
[cuda10.0]: https://developer.nvidia.com/cuda-10.0-download-archive?target_os=Windows&target_arch=x86_64
[cuDNN v7.6.5 _November 5th_ 2019_ for CUDA 10.0]: https://developer.nvidia.com/compute/machine-learning/cudnn/secure/7.6.5.32/Production/10.0_20191031/cudnn-10.0-windows10-x64-v7.6.5.32.zip
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[Tensorflow _ libcusolver.so.10 _ libcudnn.so.8]: https://blog.csdn.net/weixin_44415928/article/details/114553413
[Link 1]: https://blog.csdn.net/qq_41251963/article/details/110132101
[3.4.3]: https://opencv.org/releases/page/4/
[Link 2]: https://www.jianshu.com/p/f646448da265
[ModuleNotFoundError_ No module named _pywrap_tensorflow_internal]: https://blog.csdn.net/qq_36556893/article/details/86406455
[Win10_CUDA10_cuDNN]: https://blog.csdn.net/u011473714/article/details/95042856
[linux_cuda]: https://blog.csdn.net/weixin_42887343/article/details/108112273
[TensorFlow1.2_2.1_GPU_CUDA_cuDNN]: https://www.cnblogs.com/yymn/articles/13151150.html
[tensorflow-gpu_cuda_keras]: https://blog.csdn.net/mr_muli/article/details/109116791