段错误 核心已转储尝试解决

1.在进行

gdb python
r XX.py
where

调试时，报出以下错误：

1）每次运行都开38个线程，是否是线程超载[New Thread 0x7ffff2fd2700 (LWP 7415)]

[New Thread 0x7ffff27d1700 (LWP 7416)]
[New Thread 0x7fffeffd0700 (LWP 7417)]
[New Thread 0x7fffeb7cf700 (LWP 7418)]
[New Thread 0x7fffe8fce700 (LWP 7419)]
[New Thread 0x7fffe67cd700 (LWP 7420)]
[New Thread 0x7fffe3fcc700 (LWP 7421)]
[New Thread 0x7fffe17cb700 (LWP 7422)]
[New Thread 0x7fffdefca700 (LWP 7423)]
[New Thread 0x7fffdc7c9700 (LWP 7424)]
[New Thread 0x7fffd9fc8700 (LWP 7425)]
[New Thread 0x7fffd77c7700 (LWP 7426)]
[New Thread 0x7fffd4fc6700 (LWP 7427)]
[New Thread 0x7fffd27c5700 (LWP 7428)]
[New Thread 0x7fffcffc4700 (LWP 7429)]
[New Thread 0x7fffcd7c3700 (LWP 7430)]
[New Thread 0x7fffcafc2700 (LWP 7431)]
[New Thread 0x7fffc87c1700 (LWP 7432)]
[New Thread 0x7fffc5fc0700 (LWP 7433)]
[New Thread 0x7fffc37bf700 (LWP 7434)]
[New Thread 0x7fffc0fbe700 (LWP 7435)]
[New Thread 0x7fffbe7bd700 (LWP 7436)]
[New Thread 0x7fffbbfbc700 (LWP 7437)]
[New Thread 0x7fffb97bb700 (LWP 7438)]
[New Thread 0x7fffb6fba700 (LWP 7439)]
[New Thread 0x7fffb47b9700 (LWP 7440)]
[New Thread 0x7fffb1fb8700 (LWP 7441)]
[New Thread 0x7fffaf7b7700 (LWP 7442)]
[New Thread 0x7fffacfb6700 (LWP 7443)]
[New Thread 0x7fffaa7b5700 (LWP 7444)]
[New Thread 0x7fffa7fb4700 (LWP 7445)]
[New Thread 0x7fffa57b3700 (LWP 7446)]
[New Thread 0x7fffa2fb2700 (LWP 7447)]
[New Thread 0x7fffa07b1700 (LWP 7448)]
[New Thread 0x7fff9dfb0700 (LWP 7449)]

[New Thread 0x7fff9b7af700 (LWP 7450)]
[New Thread 0x7fff98fae700 (LWP 7451)]
[New Thread 0x7fff967ad700 (LWP 7452)]
[New Thread 0x7fff93fac700 (LWP 7453)]

 

2）现在报出：

ERROR (theano.gpuarray): Could not initialize pygpu, support disabled
。。。
  File "pygpu/gpuarray.pyx", line 658, in pygpu.gpuarray.init
  File "pygpu/gpuarray.pyx", line 587, in pygpu.gpuarray.pygpu_init
GpuArrayException: cuDeviceGet: CUDA_ERROR_INVALID_DEVICE: invalid device ordinal

先不解决这个，先尝试测试一下：

发现，在import keras，也会报上述同样的错误！

 conda install mkl
conda install mkl-service
#使用以上两句均显示：
# All requested packages already installed.

conda install blas

 依旧不可以导入keras包。

 3)将原有的conda环境删除，又新创建了环境，用conda安装了mkl之后，尝试import keras之后，仍然报错：

Using Theano backend.
~/lib/python2.7/site-packages/theano/gpuarray/dnn.py:184: UserWarning: Your cuDNN version is more recent than Theano. 
If you encounter problems, try updating Theano or downgrading cuDNN to a version >= v5 and <= v7.
  warnings.warn("Your cuDNN version is more recent than "
ERROR (theano.gpuarray): Could not initialize pygpu, support disabled
Traceback (most recent call last):
  File "~/lib/python2.7/site-packages/theano/gpuarray/__init__.py", line 227, in 
    use(config.device)
  File "~/lib/python2.7/site-packages/theano/gpuarray/__init__.py", line 214, in use
    init_dev(device, preallocate=preallocate)
  File "~/lib/python2.7/site-packages/theano/gpuarray/__init__.py", line 99, in init_dev
    **args)
  File "pygpu/gpuarray.pyx", line 658, in pygpu.gpuarray.init
  File "pygpu/gpuarray.pyx", line 587, in pygpu.gpuarray.pygpu_init
GpuArrayException: cuDeviceGet: CUDA_ERROR_INVALID_DEVICE: invalid device ordinal

在我的.theanorc配置文件中，是这么写的：

[global]
floatX = float32
device =cuda1

 

尝试去掉cuda编号？居然成功了！

Using Theano backend.
~/.conda/envs/xhs/lib/python2.7/site-packages/theano/gpuarray/dnn.py:184: UserWarning: Your cuDNN version is more recent than Theano.
 If you encounter problems, try updating Theano or downgrading cuDNN to a version >= v5 and <= v7.
  warnings.warn("Your cuDNN version is more recent than "
Using cuDNN version 7201 on context None
Mapped name None to device cuda: GeForce GTX 1080 Ti (0000:03:00.0)

 

接下来尝试解决 上述的用户警告。

由于theano已经是1.0.4最新版本，无法再进行更新，只能尝试将cuDNN版本降级。

但是使用conda list查看所有安装的包：

cudnn                     6.0.21                cuda8.0_0    https://mirrors.tuna.tsinghua.edu.cn/a

#尝试此命令查看pygpu是否可用
DEVICE="cuda" python -c "import pygpu; pygpu.test()"

 

出现以下问题：https://github.com/Theano/Theano/issues/6420

此帮助里说，如果不是使用多个GPU可以忽略test_collectives error。

#尝试以下，
python test_gpu.py
~/.conda/envs/xhs/lib/python2.7/site-packages/theano/gpuarray/dnn.py:184: UserWarning: Your cuDNN version is more recent than Theano. If you encounter problems, try updating Theano or downgrading cuDNN to a version >= v5 and <= v7.
  warnings.warn("Your cuDNN version is more recent than "
Using cuDNN version 7201 on context None
Mapped name None to device cuda: GeForce GTX 1080 Ti (0000:03:00.0)
[GpuElemwise{exp,no_inplace}((float32, vector)>), HostFromGpu(gpuarray)(GpuElemwise{exp,no_inplace}.0)]
Looping 1000 times took 0.192847 seconds
Result is [1.2317803 1.6187935 1.5227807 ... 2.2077181 2.2996776 1.623233 ]
Used the gpu

 

发现其使用的cudnn版本是7.2，明明是6.0但是却调用了7.2？

查看cuda的版本信息发现：

nvcc -V

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Sep__1_21:08:03_CDT_2017
Cuda compilation tools, release 9.0, V9.0.176

 //发现安装cuda简直十分麻烦，所以下尝试一下运行程序。

 

Starting epoch 0...
段错误 (核心已转储)

 

 

 http://imatlab.lofter.com/post/286ffc_a6ead7

#查看分配占空间的大小
ulimit -a

#显示
stack size              (kbytes, -s) 8192

 

 

 

也就仅仅8M大小，实在是太小了。

改为ulimit -s 102400，仍旧段错误。

试图将其调整为更大或者unlimit时，报错：

 

-bash: ulimit: stack size: 无法修改 limit 值: 不允许的操作

 

#使用sudo提示如下：
sudo: ulimit：找不到命令

在limit.conf下加了

 

#*               soft    stack           unlimited

 再使用ulimit -s unlimited就可以用了，但是运行程序发现仍是段错误，继续修改

#max locked memory       (kbytes, -l) 64
#尝试修改maxloc但是同样的方法不起作用

——————

终于解决了，在github上keras项目下发布的issue中找到了：

由于本机上的CUDA版本为9，所以又根据教程安装了CUDA8版本，以及cuDNN6.0版本，之后就可以了！！！ 

就是由于CUDA9不适合theano1.0!!!所以必须将版本，降版本之后就没有上述的warning了，就可以成功跑theano后端的keras代码了。

转载于:https://www.cnblogs.com/BlueBlueSea/p/10780182.html