2024-09-29 22:32:26 发布
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我想安装和使用TensorFlow 2.0。我有一台装有windows10的电脑,一台geforcegtx1080tigpu和一台旧的Intel Xeon X5660 CPU,它不支持AVX。在
现在,我的问题是,每当我试图在这台机器上运行任何TensorFlow代码时,都会出现DLL导入错误。我知道this repository为遗留CPU提供解决方案,但不幸的是,我在那里找不到任何TensorFlow 2.0包。在
任何帮助都将不胜感激。谢谢您。在
存储库中有一个全新的wheel文件:
{a1}
以下文件运行良好:
https://github.com/fo40225/tensorflow-windows-wheel/blob/master/2.0.0/py37/GPU/cuda101cudnn76sse2/tensorflow_gpu-2.0.0-cp37-cp37m-win_amd64.whl
如自述文件.md公司名称:
“第一次执行TensorFlow时,编译需要时间。”
看看这个测试:
>>>import tensorflow as tf tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll >>>print(tf.__version__) 2.0.0 >>>from tensorflow.python.client import device_lib >>>print(device_lib.list_local_devices()) tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: GeForce GTX 1050 major: 6 minor: 1 memoryClockRate(GHz): 1.531 GPU libraries are statically linked, skip dlopen check. Adding visible gpu devices: 0 Device interconnect StreamExecutor with strength 1 edge matrix: 0 0: N Created TensorFlow device (/device:GPU:0 with 1340 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1) [name: "/device:CPU:0" device_type: "CPU" memory_limit: 268435456 locality { } incarnation: 4456898788177247918 , name: "/device:GPU:0" device_type: "GPU" memory_limit: 1406107238 locality { bus_id: 1 links { } } incarnation: 3224787151756357043 physical_device_desc: "device: 0, name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1" ]
存储库中有一个全新的wheel文件:
{a1}
以下文件运行良好:
https://github.com/fo40225/tensorflow-windows-wheel/blob/master/2.0.0/py37/GPU/cuda101cudnn76sse2/tensorflow_gpu-2.0.0-cp37-cp37m-win_amd64.whl
如自述文件.md公司名称:
“第一次执行TensorFlow时,编译需要时间。”
看看这个测试:
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