Question

我安装了GPU NVIDIA GeForce GT 740M（计算能力3.0）以及以下版本的CUDA，cuDNN和tensorflow。

nvcc -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: opensource@google.com
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显示张量流

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: opensource@google.com
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

但是当我使用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？

p.s。 tensorflow-gpu是在tensorflow之前安装的，因此以“ 1）tensorflow-gpu 2）tensorflow”的顺序重新安装效率不高

Answer 1

张量流需要+3.2的计算能力。

您拥有一个具有3.0计算能力的GPU

Tensorflow 1.13.1无法识别GPU

1 个答案: