1.在进行

gdb pythonr XX.pywhere

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_initGpuArrayException: 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 mklconda 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 disabledTraceback (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_initGpuArrayException: cuDeviceGet: CUDA_ERROR_INVALID_DEVICE: invalid device ordinal
     

在我的.theanorc配置文件中，是这么写的：

[global]floatX = float32device =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 NoneMapped 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：

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 NoneMapped 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 secondsResult 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 -Vnvcc: NVIDIA (R) Cuda compiler driverCopyright (c) 2005-2017 NVIDIA CorporationBuilt on Fri_Sep__1_21:08:03_CDT_2017Cuda 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)

 

 

 

#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。