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 <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}(<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
test_collectives error
原文地址：https://www.cnblogs.com/BlueBlueSea/p/10780182.html
时间： 2024-10-10 10:21:38