tensorflow 安裝: could no t load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
阿新 • • 發佈:2020-08-05
TensorFlow 是一個端到端開源機器學習平臺
安裝
pip3 install tensorflow
使用時報錯如下
2020-06-03 09:42:51.737502: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could no t load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found 2020-06-03 09:42:51.737502: 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. 2020-06-03 09:42:53.392597: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x167fbc50 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2020-06-03 09:42:53.392597: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor devic e (0): Host, Default Version 2020-06-03 09:42:53.395597: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successf ully opened dynamic library nvcuda.dll 2020-06-03 09:42:53.472601: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:01:00.0 name: GeForce GTX 670 computeCapability: 3.0
沒有cuDNN64_7.dll
檔案,TensorFlow 將無法載入
Windows上搭建TensorFlow的開發環境
需要至少需要安裝:
1.python
2.CUDA和CuDNN
CUDA是NVIDIA發明了一種平行計算平臺和程式設計模型。通過利用圖形處理單元(GPU)的功能,可以顯著提高計算效能
CUDA下載地址:https://developer.nvidia.com/cuda-90-download-archive
下載後安裝
配置環境變數
SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin;%PATH% SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\extras\CUPTI\libx64;%PATH% SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include;%PATH%
檢視是否安裝成功
nvcc -V
NVIDIA cuDNN是用於深度神經網路的GPU加速的原語庫
CuDNN下載地址:https://developer.nvidia.com/cudnn
下載後解壓
配置環境變數
SET PATH=C:\Program Files\cuda\bin;%PATH%
檢視自己的GPU,配置環境變數
SET PATH=C:\Program Files\NVIDIA Corporation\NVSMI;%PATH%
檢視命令
nvidia-smi
3.TensorFlow(GPU版)
安裝前一定要確認好每個軟體的版本是否相互支援
Bazel 是用於編譯 TensorFlow 的構建工具
將 Bazel 可執行檔案的位置新增到%PATH%
環境變數中
下載地址:https://github.com/bazelbuild/bazel/releases
先檢視tensorflow版本資訊,根據版本對應不同版本的軟體
eg:
tensorflow2.2.0
Python 3.7.7