我有GPU NVIDIA GeForce GT 740M(计算能力3.0)和以下版本的CUDA,cuDNN和tensorflow安装。
nvsk -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Fri_Feb__8_19:08:17_PST_2019
Cuda compilation tools, release 10.1, V10.1.105
cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2
#define CUDNN_MAJOR 7
#define CUDNN_MINOR 5
#define CUDNN_PATCHLEVEL 0
--
#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)
#include "driver_types.h"
pip3显示tensorflow-gpu
Name: tensorflow-gpu
Version: 1.13.1
Summary: TensorFlow is an open source machine learning framework for everyone.
Home-page: https://www.tensorflow.org/
Author: Google Inc.
Author-email: [email protected]
License: Apache 2.0
Location: /home/lightning/.local/lib/python3.6/site-packages
Requires: grpcio, tensorboard, absl-py, termcolor, protobuf, astor, gast, numpy, tensorflow-estimator, wheel, keras-preprocessing, keras-applications, six
pip3显示tensorflow
Name: tensorflow
Version: 1.13.1
Summary: TensorFlow is an open source machine learning framework for everyone.
Home-page: https://www.tensorflow.org/
Author: Google Inc.
Author-email: [email protected]
License: Apache 2.0
Location: /home/lightning/.local/lib/python3.6/site-packages
Requires: wheel, keras-preprocessing, numpy, astor, six, protobuf, tensorflow-estimator, termcolor, grpcio, keras-applications, absl-py, tensorboard, gast
但是当我通过print(device_lib.list_local_devices())检查tensorflow检测到的设备时,输出如下......
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 13567978771733496471
, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit: 17179869184
locality {
}
incarnation: 12191851301991039336
physical_device_desc: "device: XLA_CPU device"
]
如何让tensorflow看到GPU?
附: tensorflow-gpu是在tensorflow之前安装的,所以按顺序重新安装“1)tensorflow-gpu 2)tensorflow”效率低下
tensorflow需要计算能力+3.2。
你有一个具有计算能力3.0的GPU