我无法让Tensorflow 2.0在我的GPU上运行

Question

我一直在我的电脑上用Tensorflow写程序，它使用Linux薄荷。无论出于什么原因，我都无法让Tensorflow在我的图形处理器上运行。

2021-04-26 15:46:11.462612： W tenstorflow/stream_executor/平台/默认/dso_loader.cc:60]无法加载动态库'libcudart.so.11.0'；libcudart.so.11.0：无法打开共享对象文件：没有这样的文件或目录<--plhd--5/如果您的机器上没有设置GPU，请忽略上面的cudart dlfalse。

我知道我已经安装了CUDA，因为对于PyTorch，GPU工作良好：

mydevice = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print(mydevice)

产量

库达

另外，我用tensorflow运行了一个程序，我得到：

START TIME:  Mon Apr 26 16:34:24 2021
2021-04-26 16:34:24.499178: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-26 16:34:24.499862: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2021-04-26 16:34:24.526372: 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
2021-04-26 16:34:24.526781: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: GeForce GTX 1650 computeCapability: 7.5
coreClock: 1.56GHz coreCount: 16 deviceMemorySize: 3.82GiB deviceMemoryBandwidth: 119.24GiB/s
2021-04-26 16:34:24.526900: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2021-04-26 16:34:24.526986: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcublas.so.11'; dlerror: libcublas.so.11: cannot open shared object file: No such file or directory
2021-04-26 16:34:24.527069: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcublasLt.so.11'; dlerror: libcublasLt.so.11: cannot open shared object file: No such file or directory
2021-04-26 16:34:24.528676: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-04-26 16:34:24.528994: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-04-26 16:34:24.530990: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-04-26 16:34:24.531125: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcusparse.so.11'; dlerror: libcusparse.so.11: cannot open shared object file: No such file or directory
2021-04-26 16:34:24.531230: 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
2021-04-26 16:34:24.531245: 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...
2021-04-26 16:34:24.531641: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-04-26 16:34:24.532140: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-26 16:34:24.532178: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-04-26 16:34:24.532192: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      
2021-04-26 16:34:24.592917: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-04-26 16:34:24.593369: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2400000000 Hz

我使用conda在anaconda上安装了tensorflow，尽管我相信它是从PyPi构建的。请告诉我你的建议。非常感谢。

Answer 1

你是从哪个频道安装的？如果使用默认通道，则必须指定tensorflow的GPU版本。

conda install tensorflow=2.4.*=gpu* -c anaconda 

Answer 2

从您的错误日志中可以看出，tensorflow正在拾取您的GPU（GTX 1650）。但是，问题是cudatoolkit和cudnn版本可能与tensorflow版本不兼容。TF对这些要求相当具体。您需要注意的错误行如下：

2021-04-26 16:34:24.526900: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library **'libcudart.so.11.0'**; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2021-04-26 16:34:24.526986: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library **'libcublas.so.11'**; dlerror: libcublas.so.11: cannot open shared object file: No such file or directory
2021-04-26 16:34:24.527069: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library **'libcublasLt.so.11'**; dlerror: libcublasLt.so.11: cannot open shared object file: No such file or directory
2021-04-26 16:34:24.528676: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10

2021-04-26 16:34:24.531125: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library **'libcusparse.so.11'**; dlerror: libcusparse.so.11: cannot open shared object file: No such file or directory
2021-04-26 16:34:24.531230: 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

最新的tensorflow发行版tensorflow-2.4。0（请参阅完整表格）只能与cuDNN 8.0和CUDA 11.0版本配合使用。（尽管这些新版本已经发布——您可能需要检查您的版本，我认为您可能正在使用CUDA 10）。

我建议大家看看这篇文章（虽然比较老，但命令和原则仍然适用）。

1. 制作yaml文件（tensorflow的yaml文件示例）
2. 使用上述yaml文件为Tensorflow创建一个新环境

conda env创建-f环境。yml

激活tensorflow_env_388

注意。全新的环境将避免任何冲突包。

conda列表cudnn

# packages in environment at /rds/general/user/home/anaconda3/envs/tensorflow_env_388:
#
# Name                    Version                   Build  Channel
cudnn                     7.0.5.39             ha5ca753_1    conda-forge

conda列表cudatoolkit

然后根据需要安装cudnn/cuda

conda安装cudatoolkit=11.0

conda安装cudnn=8.0