-
Notifications
You must be signed in to change notification settings - Fork 22
Install TensorFlow @ LN41
用户可以通过module 加载或 source xxxx/active . 因为这是GPU 分区，就只配置 GPU 版本的 Module 咯。
module load TensorFlow/1.0.1-gpu
Py 2.7.9 , CPU ONLY , tensorflow 1.0.1
- 解压python 安装包 ，配置并安装 ,配置环境变量
$ ./configure --prefix=/BIGDATA/app/Python/2.7.9 --with-ensurepip --with-threads --enable-shared --enable-unicode=ucs4
$ make -j 12
$ make install
$ export PATH=/BIGDATA/app/Python/2.7.9/bin:$PATH
$ export LD_LIBRARY_PATH=/BIGDATA/app/Python/2.7.9/lib:$LD_LIBRARY_PATH
- 安装 virtualenv , 并创建环境 并加装
$ pip install virtualenv
$ virtualenv --system-site-packages /BIGDATA/app/TensorFlow/python-venv/py2.9
$ source /BIGDATA/app/TensorFlow/python-venv/py2.9/bin/activate
- 安装 tensorflow 并测试
(py2.9) $ pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.1-cp27-none-linux_x86_64.whl
(py2.9) $ python /BIGDATA/app/TensorFlow/testtf.py
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
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.
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.
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.
Hello, TensorFlow!
可以看出 tensorflow 正常工作了，但 W 也指出了可以通过针对指令集编译 TensorFLow 的库 来提高运算性能 ，这方面需要之后再探究了 。
- 第一次安装时直接 ./configure 安装的Python , 导致 tensorflow 安装完出现 ： ``` undefined symbol: PyUnicodeUCS4_AsUTF8String
# GPU 版
Py 2.7.9 , GPU , tensorflow 1.0.1
安装
$ virtualenv --system-site-packages /BIGDATA/app/TensorFlow/python-venv/py2.9-gpu $ source /BIGDATA/app/TensorFlow/python-venv/py2.9-gpu/bin/activate (py2.9-gpu) $ pip install --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.0.1-cp27-none-linux_x86_64.whl
测试
(py2.9-gpu) $ yhrun -n 1 python /BIGDATA/app/TensorFlow/testtf.py I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:126] Couldn't open CUDA library libcudnn.so.5. LD_LIBRARY_PATH: /BIGDATA/app/CUDA/8.0/lib64/stubs:/BIGDATA/app/CUDA/8.0/libnvvp:/BIGDATA/app/CUDA/8.0/libnsight:/BIGDATA/app/CUDA/8.0/lib64:/BIGDATA/app/CUDA/8.0/lib:/BIGDATA/app/Python/2.7.9/lib: I tensorflow/stream_executor/cuda/cuda_dnn.cc:3517] Unable to load cuDNN DSO I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.8.0 locally W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations. 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. 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. 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. 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. 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. I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties: name: Tesla K80 major: 3 minor: 7 memoryClockRate (GHz) 0.8235 pciBusID 0000:04:00.0 Total memory: 11.17GiB Free memory: 11.11GiB W tensorflow/stream_executor/cuda/cuda_driver.cc:590] creating context when one is currently active; existing: 0x1f489d0 I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 1 with properties: name: Tesla K80 major: 3 minor: 7 memoryClockRate (GHz) 0.8235 pciBusID 0000:05:00.0 Total memory: 11.17GiB Free memory: 11.11GiB W tensorflow/stream_executor/cuda/cuda_driver.cc:590] creating context when one is currently active; existing: 0x1f4c350 I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 2 with properties: name: Tesla K80 major: 3 minor: 7 memoryClockRate (GHz) 0.8235 pciBusID 0000:84:00.0 Total memory: 11.17GiB Free memory: 11.11GiB W tensorflow/stream_executor/cuda/cuda_driver.cc:590] creating context when one is currently active; existing: 0x1f4fcd0 I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 3 with properties: name: Tesla K80 major: 3 minor: 7 memoryClockRate (GHz) 0.8235 pciBusID 0000:85:00.0 Total memory: 11.17GiB Free memory: 11.11GiB I tensorflow/core/common_runtime/gpu/gpu_device.cc:777] Peer access not supported between device ordinals 0 and 2 I tensorflow/core/common_runtime/gpu/gpu_device.cc:777] Peer access not supported between device ordinals 0 and 3 I tensorflow/core/common_runtime/gpu/gpu_device.cc:777] Peer access not supported between device ordinals 1 and 2 I tensorflow/core/common_runtime/gpu/gpu_device.cc:777] Peer access not supported between device ordinals 1 and 3 I tensorflow/core/common_runtime/gpu/gpu_device.cc:777] Peer access not supported between device ordinals 2 and 0 I tensorflow/core/common_runtime/gpu/gpu_device.cc:777] Peer access not supported between device ordinals 2 and 1 I tensorflow/core/common_runtime/gpu/gpu_device.cc:777] Peer access not supported between device ordinals 3 and 0 I tensorflow/core/common_runtime/gpu/gpu_device.cc:777] Peer access not supported between device ordinals 3 and 1 I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0 1 2 3 I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y Y N N I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 1: Y Y N N I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 2: N N Y Y I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 3: N N Y Y I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Tesla K80, pci bus id: 0000:04:00.0) I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:1) -> (device: 1, name: Tesla K80, pci bus id: 0000:05:00.0) I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:2) -> (device: 2, name: Tesla K80, pci bus id: 0000:84:00.0) I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:3) -> (device: 3, name: Tesla K80, pci bus id: 0000:85:00.0) ('Version of TensorFlow :', '1.0.1') Hello, TensorFlow!
从测试结果可以看出GPU 版本能正常工作 ，可以提高性能之处除了针对指令集的编译外还有 使用 cuDNN DSO .
# 其他说明
如果需要提前的PYTHON 包可以和我联系 ，
如果需要的PYTHON 包太多，特别是有很多非通用的包的话可以在自己的账号目录下创建 virtualenv 环境 。
自己的PYTHON 环境需要通过 PIP 安装包时可以联系我使用PROXY.