Instalei recentemente Nvidia driver-375.39, Cuda-8.0 & amp; CUDNN-5.1 com muita dor de cabeça e dificuldades. Depois disso eu instalei o Tensorflow , já que é o que eu queria fazer desde o começo.
Eu tomei a ajuda de fontes como: link
link
Eu tinha instalado o tensorflow com virtualenv no Ubuntu 16.04 rodando a Nvidia Geforce 940MX.
Embora eu não tenha conseguido rodar as amostras de Cuda (que vieram com o arquivo cuda_8.0.61_375.26_linux.run ), dando-me poucos erros, como estes:
nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
/usr/bin/ld: cannot find -lglut
collect2: error: ld returned 1 exit status
Makefile:267: recipe for target 'simpleGL' failed
make[1]: *** [simpleGL] Error 1
make[1]: Leaving directory '/home/jayant/NVIDIA_CUDA-8.0_Samples/2_Graphics/simpleGL'
Makefile:52: recipe for target '2_Graphics/simpleGL/Makefile.ph_build' failed
make: *** [2_Graphics/simpleGL/Makefile.ph_build] Error 2
ainda instalei o tensorflow e agora estou em dúvida se ele está usando Cuda ou não.
Minha dúvida surge quando tento importar tensorflow, da seguinte forma:
>>>import tensorflow as tf
>>>hello = tf.constant('Hello, TensorFlow!')
>>>sess = tf.Session()
>>>print(sess.run(hello))
Eu não recebo essas mensagens (como mencionado em muitos blogs):
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcurand.so locally
em vez disso, eu entendo isso:
2017-05-01 00:08:12.079557: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2017-05-01 00:08:12.079584: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-05-01 00:08:12.079588: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-05-01 00:08:12.079591: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-05-01 00:08:12.079595: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
2017-05-01 00:08:12.322193: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2017-05-01 00:08:12.322566: I tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 with properties:
name: GeForce 940MX
major: 5 minor: 0 memoryClockRate (GHz) 1.189
pciBusID 0000:01:00.0
Total memory: 3.95GiB
Free memory: 3.93GiB
2017-05-01 00:08:12.322580: I tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0
2017-05-01 00:08:12.322584: I tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0: Y
2017-05-01 00:08:12.322593: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce 940MX, pci bus id: 0000:01:00.0)
Hello, TensorFlow!
Alguém por favor pode me dizer se meu Cuda foi instalado corretamente e tensorflow está sendo executado corretamente com Cuda ?
Ou quais alterações eu preciso fazer alterações para suprimir esses avisos, executar as amostras cuda com sucesso e obter essas mensagens tensorflow em relação às bibliotecas abertas cuda ?
PS: por favor, deixe-me saber se qualquer outra informação é necessária.