如何配置我的 jupyter 笔记本，以便它在使用 keras 时使用可用的 GPU？
How do I configure my jupyter notebook so that it uses the available GPU while working with keras?
我搜索了解决办法，用pip安装了tensorflow-gpu
tf.config.list_physical_devices('GPU')
此代码returns 一个空列表。 []
You can see I have 2 GPUs but none of them are being used when I am doing image processing(CNN) with keras.
我是新手，所以不明白到底哪里出了问题。请帮助我配置，以便我可以使用我的 GPU 进行处理。我正在使用 Windows 10 64 位，Python-3.8.7。
按照建议，我尝试在 python 终端上导入 tensorflow，但出现以下错误：
import tensorflow as tf
2021-02-13 22:52:17.253841: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2021-02-13 22:52:17.266384: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
当我尝试列出 GPU 时紧随其后：
tf.config.list_physical_devices('GPU')
2021-02-13 22:57:17.390319: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-02-13 22:57:17.749790: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-02-13 22:57:18.937838: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce MX150 computeCapability: 6.1
coreClock: 1.5315GHz coreCount: 3 deviceMemorySize: 2.00GiB deviceMemoryBandwidth: 44.76GiB/s
2021-02-13 22:57:18.966071: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2021-02-13 22:57:18.974209: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found
2021-02-13 22:57:18.981154: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cublasLt64_11.dll'; dlerror: cublasLt64_11.dll not found
2021-02-13 22:57:18.988826: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found
2021-02-13 22:57:18.996411: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found
2021-02-13 22:57:19.002563: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
2021-02-13 22:57:19.009636: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusparse64_11.dll'; dlerror: cusparse64_11.dll not found
2021-02-13 22:57:19.018025: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found
2021-02-13 22:57:19.025064: 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...
[]
Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found 此错误消息说 Tensorflow-gpu 需要 CUDA 11
Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found 此错误消息表明 运行 Tensorflow-gpu 版本需要 cuDNN 8。
安装正确的版本 CUDA 和 cuDNN 并按照 here 中提到的说明在 Windows OS.
上设置 GPU 支持
我搜索了解决办法，用pip安装了tensorflow-gpu
tf.config.list_physical_devices('GPU')
此代码returns 一个空列表。 []
You can see I have 2 GPUs but none of them are being used when I am doing image processing(CNN) with keras.
我是新手，所以不明白到底哪里出了问题。请帮助我配置，以便我可以使用我的 GPU 进行处理。我正在使用 Windows 10 64 位，Python-3.8.7。 按照建议，我尝试在 python 终端上导入 tensorflow，但出现以下错误：
import tensorflow as tf
2021-02-13 22:52:17.253841: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found 2021-02-13 22:52:17.266384: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
当我尝试列出 GPU 时紧随其后：
tf.config.list_physical_devices('GPU')
2021-02-13 22:57:17.390319: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set 2021-02-13 22:57:17.749790: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll 2021-02-13 22:57:18.937838: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: pciBusID: 0000:01:00.0 name: GeForce MX150 computeCapability: 6.1 coreClock: 1.5315GHz coreCount: 3 deviceMemorySize: 2.00GiB deviceMemoryBandwidth: 44.76GiB/s 2021-02-13 22:57:18.966071: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found 2021-02-13 22:57:18.974209: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found 2021-02-13 22:57:18.981154: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cublasLt64_11.dll'; dlerror: cublasLt64_11.dll not found 2021-02-13 22:57:18.988826: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found 2021-02-13 22:57:18.996411: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found 2021-02-13 22:57:19.002563: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found 2021-02-13 22:57:19.009636: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusparse64_11.dll'; dlerror: cusparse64_11.dll not found 2021-02-13 22:57:19.018025: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found 2021-02-13 22:57:19.025064: 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... []
Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found 此错误消息说 Tensorflow-gpu 需要 CUDA 11
Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found 此错误消息表明 运行 Tensorflow-gpu 版本需要 cuDNN 8。
安装正确的版本 CUDA 和 cuDNN 并按照 here 中提到的说明在 Windows OS.