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CUDA †$ sudo yum-config-manager --add-repo http://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo $ sudo yum clean all $ sudo yum -y install nvidia-driver-latest-dkms cuda $ sudo yum -y install cuda-drivers cuDNN †https://qiita.com/tatsuya11bbs/items/70205b070c7afd7dd651 に従う。NVIDIAへのユーザー登録が必要。 https://developer.nvidia.com/rdp/cudnn-download $ cp cudnn-10.2-linux-x64-v7.6.5.32.tgz /usr/local/ $ cd /usr/local/ $ tar zxvf cudnn-10.2-linux-x64-v7.6.5.32.tgz Pyenv †$ git clone https://github.com/yyuu/pyenv.git ~/.pyenv Add the following three lines to ~/.bashrc export PYENV_ROOT=$HOME/.pyenv export PATH=$PYENV_ROOT/bin:$PATH eval "$(pyenv init -)" Anaconda †$ pyenv install --list $ pyenv install anaconda3-2019.10 $ pyenv versions * system (set by /home/oda/.pyenv/version) anaconda3-2019.10 $ pyenv global anaconda3-2019.10 system * anaconda3-2019.10 (set by /home/oda/.pyenv/version) Keras †$ pip install --upgrade pip $ pip install keras TensorFlow †$ pip install --upgrade pip $ pip install tensorflow $ pip install tensorflow-gpu $ python Python 3.7.4 (default, Aug 13 2019, 20:35:49) [GCC 7.3.0] :: Anaconda, Inc. on linux Type "help", "copyright", "credits" or "license" for more information. >>> import tensorflow as tf 2020-01-30 12:32:29.462468: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer.so.6'; dlerror: libnvinfer.so.6: cannot open shared object file: No such file or directory 2020-01-30 12:32:29.462551: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvinfer_plugin.so.6: cannot open shared object file: No such file or directory 2020-01-30 12:32:29.462562: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly. >>> TensorRT †libnvinfer.so.6を用意するために、TensorRTを導入しようとしてみた。 https://developer.nvidia.com/tensorrt cp TensorRT-7.0.0.11.Ubuntu-18.04.x86_64-gnu.cuda-10.2.cudnn7.6.tar.gz /usr/local/ cd /usr/local/ tar zxvf TensorRT-7.0.0.11.Ubuntu-18.04.x86_64-gnu.cuda-10.2.cudnn7.6.tar.gz cd /usr/local/TensorRT-7.0.0.11/lib libnvinfer.so.7はあるが、libnvinfer.so.6はないので、 ln -s libnvinfer.so libnvinfer.so.6 ln -s libnvinfer_plugin.so libnvinfer_plugin.so.6 としてみた。 /.bashrc export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/TensorRT-7.0.0.11/lib:/usr/local/cuda/lib64 を追加して、glibcのバージョンを2.17から2.27に変更とかしようとしたけれど、つまづく。 TensorFlow2.0.1 †TensorFlow2.1.0でのlibnvinfer.so.6の問題は https://github.com/tensorflow/tensorflow/issues/35968 で10日前に報告されているので、対処は諦め、バージョンを下げた。 $ pip install tensorflow==2.0.1 $ pip install tensorflow-gpu==2.0.1 $ python Python 3.7.4 (default, Aug 13 2019, 20:35:49) [GCC 7.3.0] :: Anaconda, Inc. on linux Type "help", "copyright", "credits" or "license" for more information. >>> import tensorflow as tf >>> TensorFlowはインストールできた。しかし、 https://thr3a.hatenablog.com/entry/20180113/1515820265 に従って確認すると、 >>> from tensorflow.python.client import device_lib
>>> device_lib.list_local_devices()
2020-01-30 14:21:30.013092: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-01-30 14:21:30.022186: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3600000000 Hz
2020-01-30 14:21:30.022941: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55b1c0f6b170 executing computations on platform Host. Devices:
2020-01-30 14:21:30.022982: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): Host, Default Version
2020-01-30 14:21:30.024665: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2020-01-30 14:21:30.025440: E tensorflow/stream_executor/cuda/cuda_driver.cc:318] failed call to cuInit: CUDA_ERROR_SYSTEM_DRIVER_MISMATCH: system has unsupported display driver / cuda driver combination
2020-01-30 14:21:30.025468: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: localhost.localdomain
2020-01-30 14:21:30.025478: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: localhost.localdomain
2020-01-30 14:21:30.025514: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: 440.33.1
2020-01-30 14:21:30.025543: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 440.44.0
2020-01-30 14:21:30.025553: E tensorflow/stream_executor/cuda/cuda_diagnostics.cc:313] kernel version 440.44.0 does not match DSO version 440.33.1 -- cannot find working devices in this configuration
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 15191092083718892008
, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit: 17179869184
locality {
}
incarnation: 9175125806567128648
physical_device_desc: "device: XLA_CPU device"
]
となるので、GPUは認識されていない。。 ただ再起動したら、認識してくれた。 $ python
Python 3.7.4 (default, Aug 13 2019, 20:35:49)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from tensorflow.python.client import device_lib
>>> device_lib.list_local_devices()
2020-01-30 15:02:51.584089: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-01-30 15:02:51.594858: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3600000000 Hz
2020-01-30 15:02:51.595512: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x564f260a01a0 executing computations on platform Host. Devices:
2020-01-30 15:02:51.595559: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): Host, Default Version
2020-01-30 15:02:51.597305: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2020-01-30 15:02:51.664145: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-01-30 15:02:51.664450: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x564f260c30d0 executing computations on platform CUDA. Devices:
2020-01-30 15:02:51.664470: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): GeForce RTX 2060 SUPER, Compute Capability 7.5
2020-01-30 15:02:51.664603: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-01-30 15:02:51.664822: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce RTX 2060 SUPER major: 7 minor: 5 memoryClockRate(GHz): 1.83
pciBusID: 0000:01:00.0
2020-01-30 15:02:51.664906: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcudart.so.10.0'; dlerror: libcudart.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/TensorRT-7.0.0.11/lib:/usr/local/cuda/lib64
2020-01-30 15:02:51.664958: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcublas.so.10.0'; dlerror: libcublas.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/TensorRT-7.0.0.11/lib:/usr/local/cuda/lib64
2020-01-30 15:02:51.665010: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcufft.so.10.0'; dlerror: libcufft.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/TensorRT-7.0.0.11/lib:/usr/local/cuda/lib64
2020-01-30 15:02:51.665059: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcurand.so.10.0'; dlerror: libcurand.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/TensorRT-7.0.0.11/lib:/usr/local/cuda/lib64
2020-01-30 15:02:51.665108: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcusolver.so.10.0'; dlerror: libcusolver.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/TensorRT-7.0.0.11/lib:/usr/local/cuda/lib64
2020-01-30 15:02:51.665158: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcusparse.so.10.0'; dlerror: libcusparse.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/TensorRT-7.0.0.11/lib:/usr/local/cuda/lib64
2020-01-30 15:02:51.667833: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-01-30 15:02:51.667848: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1641] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed
properly if you would like to use GPU. Follow the guide at
https://www.tensorflow.org/install/gpu for how to download and setup the
required libraries for your platform.
Skipping registering GPU devices...
2020-01-30 15:02:51.667868: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect
StreamExecutor with strength 1 edge matrix:
2020-01-30 15:02:51.667878: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0
2020-01-30 15:02:51.667885: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 6508581553371486294
, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit: 17179869184
locality {
}
incarnation: 1987290959829944833
physical_device_desc: "device: XLA_CPU device"
, name: "/device:XLA_GPU:0"
device_type: "XLA_GPU"
memory_limit: 17179869184
locality {
}
incarnation: 7094331008891992157
physical_device_desc: "device: XLA_GPU device"
]
>>>
しかし、良く見るとWarningが出ていて、ライブラリが見つからないから、GPUはつかえないとのこと。 2020-01-30 16:06:10.616708: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcublas.so.10.0'; dlerror: libcublas.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/TensorRT-7.0.0.11/lib:/usr/local/cuda/lib64:/usr/local/TensorRT-7.0.0.11/lib:/usr/local/cuda/lib64 CUDA 10.2を入れているが、CUDA 10.0を要求しているようで、 yum --showduplicates search cuda で利用可能なバージョンを調べて、 yum install cuda-cublas-10-0-10.0.130-1.x86_64 yum install cuda-cufft-10-0-10.0.130-1.x86_64 yum install cuda-curand-10-0-10.0.130-1.x86_64 yum install cuda-cusolver-10-0-10.0.130-1.x86_64 yum install cuda-cusparse-10-0-10.0.130-1.x86_64 yum install cuda-cudart-10-0-10.0.130-1.x86_64 でインストールし、 /.bashrc で export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/TensorRT-7.0.0.11/lib:/usr/local/cuda/lib64:/usr/local/cuda-10.0/lib64/ とした。すると、Warningは消えて、 tensorflowのジョブを走らせている時、 $ nvidia-smi Thu Jan 30 17:53:44 2020 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 440.33.01 Driver Version: 440.33.01 CUDA Version: 10.2 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | |===============================+======================+======================| | 0 GeForce RTX 206... Off | 00000000:01:00.0 Off | N/A | | 0% 52C P2 44W / 215W | 7692MiB / 7982MiB | 4% Default | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: GPU Memory | | GPU PID Type Process name Usage | |=============================================================================| | 0 18243 C ...v/versions/anaconda3-2019.10/bin/python 7681MiB | +-----------------------------------------------------------------------------+ となり、使われているようだ。 TensorFlowのテストジョブ †https://www.amazon.co.jp/gp/product/4839969515/ に基づいた、テストジョブ。 https://github.com/yusugomori/deeplearning-keras-tf2-torch 問題点 †RNNを使おうとするとcuDNN周りでこけた。 やりたかったこと †Autoencoder †
制約ボルツマンマシン †KerasでModelとParameterをLoad/Saveする方法 †https://qiita.com/supersaiakujin/items/b9c9da9497c2163d5a74 Colaboratory †https://colab.research.google.com/notebooks/welcome.ipynb?hl=ja これを使う方がラクか。 |
