1 .正在进行
gdb python
r XX.py
where
调试期间报告了以下错误：
1 )每次运行38个线程，并且线程是否过载[ new thread0x7ffff2FD 2700 (lwp 7415 ) ]
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2 )现报告：
error(theAno.GPUArray ) : Could notinitialize pygpu，支持禁用。
File'pygpu/gpuarray.pyx '，line 658，inpygpu.gpuarray.init
File'pygpu/gpuarray.pyx '，line 587，inpygpu.gpuarray.pygpu_init
guarrayexception : cudeviceget : cuda _ error _ invalid _ device 3360 invaliddeviceordinal
请先不解决这个，先测试一下：
import keras也发现报告了与上述相同的错误！
康达安装mkl
康达安装mkl-service #使用这两个
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): Couldnotinitialize 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, inuse
init_dev(device, preallocate=preallocate)
File"~/lib/python2.7/site-packages/theano/gpuarray/__init__.py", line 99, ininit_dev**args)
File"pygpu/gpuarray.pyx", line 658, inpygpu.gpuarray.init
File"pygpu/gpuarray.pyx", line 587, inpygpu.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 version7201on context None
Mapped name None to device cuda: GeForce GTX1080 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()"
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 version7201on context None
Mapped name None to device cuda: GeForce GTX1080 Ti (0000:03:00.0)
[GpuElemwise{exp,no_inplace}((float32, vector)>), HostFromGpu(gpuarray)(GpuElemwise{exp,no_inplace}.0)]
Looping1000 times took 0.192847seconds
Resultis [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)2005-2017NVIDIA Corporation
Built on Fri_Sep__1_21:08:03_CDT_2017
Cuda compilation tools, release9.0, 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...
cjdjd (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cjdjd。
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cjdjd，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。