Python gpu上的Tensorflow:tf找不到gpu

我尝试了一切，但tensorflow看不到我的gpu。ı将向我展示所有版本，有人知道吗？ 1-我的nvidia

2 Cuda：版本

CuDNN版本：CuDNN（7.6.5）

我的tf版本

我从那里开始遵循所有这些步骤：

经过这些步骤，我控制了tf

>>> tf.config.list_physical_devices('GPU')
2020-12-30 10:41:50.035846: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-12-30 10:41:50.047043: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2020-12-30 10:41:50.080921: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-12-30 10:41:50.081141: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: GeForce RTX 2060 SUPER computeCapability: 7.5
coreClock: 1.665GHz coreCount: 34 deviceMemorySize: 7.79GiB deviceMemoryBandwidth: 417.29GiB/s
2020-12-30 10:41:50.081155: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-12-30 10:41:50.107337: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2020-12-30 10:41:50.107387: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2020-12-30 10:41:50.126300: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2020-12-30 10:41:50.132954: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2020-12-30 10:41:50.204340: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2020-12-30 10:41:50.212418: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2020-12-30 10:41:50.212534: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudnn.so.8'; dlerror: libcudnn.so.8: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib/cuda/include:/usr/lib/cuda/lib64:
2020-12-30 10:41:50.212543: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
[]
>>> tf.config.list_physical_devices('GPU')
`[]`

>>> tf.test.is_built_with_cuda()
true
>>> tf.test.is_gpu_available(cuda_only=False, 

min_cuda_compute_capability=None)
WARNING:tensorflow:From <stdin>:1: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.config.list_physical_devices('GPU')` instead.
2020-12-30 10:42:47.612041: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-12-30 10:42:47.612151: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-12-30 10:42:47.612381: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: GeForce RTX 2060 SUPER computeCapability: 7.5
coreClock: 1.665GHz coreCount: 34 deviceMemorySize: 7.79GiB deviceMemoryBandwidth: 417.29GiB/s
2020-12-30 10:42:47.612400: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-12-30 10:42:47.612421: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2020-12-30 10:42:47.612431: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2020-12-30 10:42:47.612441: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2020-12-30 10:42:47.612450: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2020-12-30 10:42:47.612459: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2020-12-30 10:42:47.612467: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2020-12-30 10:42:47.615079: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudnn.so.8'; dlerror: libcudnn.so.8: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib/cuda/include:/usr/lib/cuda/lib64:
2020-12-30 10:42:47.615090: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2020-12-30 10:42:47.725208: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-12-30 10:42:47.725230: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 
2020-12-30 10:42:47.725235: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N 
False

>>tf.config.list\u物理设备（'GPU'））
2020-123030:41: 50.035846：I TysFrase/Cyp/JIT/XLAYCPUION.CC：41不创建XLA设备，TFXXLANEABLE LXLAX设备未设置
2020-12-30 10:41:50.047043:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]已成功打开动态库libcuda.so.1
2020-12-30 10:41:50.080921:I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941]从SysFS读取的成功NUMA节点的值为负值（-1），但必须至少有一个NUMA节点，因此返回NUMA节点零
2020-12-30 10:41:50.081141:I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720]找到了具有以下属性的设备0：
pciBusID:0000:01:00.0名称：GeForce RTX 2060超级计算能力：7.5
核心时钟：1.665GHz核心计数：34设备内存大小：7.79GiB设备内存带宽：417.29GiB/s
2020-12-30 10:41:50.081155:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]成功打开动态库libcudart.so.11.0
2020-12-30 10:41:50.107337:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]成功打开动态库libcublas.so.11
2020-12-30 10:41:50.107387:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]已成功打开动态库libcublasLt.so.11
2020-12-30 10:41:50.126300:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]成功打开动态库libcuft.so.10
2020-12-30 10:41:50.132954:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]成功打开动态库libcurand.so.10
2020-12-30 10:41:50.204340:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]成功打开动态库libcusolver.so.10
2020-12-30 10:41:50.212418:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]已成功打开动态库libcusparse.so.11
2020-12-30 10:41:50.212534:W tensorflow/stream_executor/platform/default/dso_loader.cc:60]无法加载动态库“libcudnn.so.8”；dlerror:libcudnn.so.8:无法打开共享对象文件：没有此类文件或目录；LD_LIBRARY_路径：/usr/lib/cuda/include:/usr/lib/cuda/lib64:
2020-12-30 10:41:50.212543:W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757]无法打开某些gpu库。如果您想使用GPU，请确保正确安装了上述缺失的库。请按照以下指南操作：https://www.tensorflow.org/install/gpu 了解如何下载和设置平台所需的库。
正在跳过注册GPU设备。。。
[]
>>>tf.config.list_物理_设备（'GPU'）
`[]`
>>>tf.test.u是用cuda（）构建的吗
真的
>>>tf.test.是否有gpu可用（仅cuda\U=False，
最小计算能力=无）
警告：tensorflow:From:1:U gpu是否可用（来自tensorflow.python.framework.test\u util）已被弃用，并将在将来的版本中删除。
更新说明：
改用'tf.config.list_物理_设备（'GPU'）`。
2020-123030:42: 47.612041：I TysFult/Cys/JIT/XLAAGPUIONE.CAR:C:99）不创建XLA设备，TFXXLANEABLE LXLAX设备未设置
2020-12-30 10:42:47.612151:I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941]从SysFS读取的成功NUMA节点的值为负值（-1），但必须至少有一个NUMA节点，因此返回NUMA节点零
2020-12-30 10:42:47.612381:I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720]找到了具有以下属性的设备0：
pciBusID:0000:01:00.0名称：GeForce RTX 2060超级计算能力：7.5
核心时钟：1.665GHz核心计数：34设备内存大小：7.79GiB设备内存带宽：417.29GiB/s
2020-12-30 10:42:47.612400:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]已成功打开动态库libcudart.so.11.0
2020-12-30 10:42:47.612421:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]成功打开动态库libcublas.so.11
2020-12-30 10:42:47.612431:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]成功打开动态库libcublasLt.so.11
2020-12-30 10:42:47.612441:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]成功打开动态库libcuft.so.10
2020-12-30 10:42:47.612450:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]成功打开了动态库libcurand.so.10
2020-12-30 10:42:47.612459:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]成功打开了动态库libcusolver.so.10
2020-12-30 10:42:47.612467:I tensorflow/stream_executor/platform/default/dso_loader.cc:49]已成功打开动态库libcusparse.so.11
2020-12-30 10:42:47.615079:W tensorflow/stream_executor/platform/default/dso_loader.cc:60]无法加载动态库“libcudnn.so.8”；dlerror:libcudnn.so.8:无法打开共享对象文件：没有此类文件或目录；LD_LIBRARY_路径：/usr/lib/cuda/include:/usr/lib/cuda/lib64:
2020-12-30 10:42:47.615090:W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757]无法打开某些gpu库。如果您想使用GPU，请确保正确安装了上述缺失的库。请按照以下指南操作：https://www.tensorflow.org/install/gpu 了解如何下载和设置平台所需的库。
正在跳过注册GPU设备。。。
2020-12-30 10:42:47.725208:I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261]设备互连拖缆执行器与强度1边缘矩阵：
2020-12-30 10:42:47.725230:I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]0
2020-12-30 10:42:47.725235:I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280]0:N
假的

将表格复制到此处，以便