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
先尝试测试一下，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 <module> 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.theanorc配置文件中，是这么写的：
[global] floatX = float32 device =cuda1
尝试去掉cuda编号？ok
Using Theano backend. ~/.conda/envs/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/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}(<GpuArrayType<None>(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ok
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。