最近,tensorflow網站上給出了新的使用Anaconda配置和安裝Tensorflow的步驟,經過測試,在國內可以無障礙的訪問。Anaconda 是一個基于Python的科學計算包集合,目前支持Python 2.7和3.5。
注意:在安裝過程中如果出現很長的報錯,觀察錯誤信息的末尾,如果是網絡鏈接相關,就重新運行一遍語句即可(如出現進度條不動的情況,也可重新運行語句),Anaconda自身約500M,tensorflow所需軟件包約幾十M。
操作系統: Ubuntu 14.04
1. 安裝Anaconda
從anaconda官網(https://www.continuum.io/downloads)上下載Linux版本的安裝文件(推薦Python 2.7版本),運行sh完成安裝。
2. 建立一個tensorflow的運行環境
- # Python 2.7
- $ conda create -n tensorflow python=2.7
-
- # Python 3.4
- $ conda create -n tensorflow python=3.4
-
- # Python 3.5
- $ conda create -n tensorflow python=3.5
3.在conda環境中安裝tensorflow
在conda環境中安裝tensorflow的好處是可以便捷的管理tensorflow的依賴包。分為兩個步驟:激活上一步建立的名為tensorflow的conda環境;用conda或者pip工具安裝Tensorflow,作者選擇的是pip方式。
3.1 pip方式
pip方式需要首先激活conda環境
- $ source activate tensorflow
然后根據要安裝的不同tensorflow版本選擇對應的
一條環境變量設置export語句(操作系統,Python版本,CPU版本還是CPU+GPU版本)
- # Ubuntu/Linux 64-bit, CPU only, Python 2.7
- (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp27-none-linux_x86_64.whl
-
- # Ubuntu/Linux 64-bit, GPU enabled, Python 2.7
- # Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
- (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.10.0-cp27-none-linux_x86_64.whl
-
- # Mac OS X, CPU only, Python 2.7:
- (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.10.0-py2-none-any.whl
-
- # Mac OS X, GPU enabled, Python 2.7:
- (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow-0.10.0-py2-none-any.whl
-
- # Ubuntu/Linux 64-bit, CPU only, Python 3.4
- (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp34-cp34m-linux_x86_64.whl
-
- # Ubuntu/Linux 64-bit, GPU enabled, Python 3.4
- # Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
- (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.10.0-cp34-cp34m-linux_x86_64.whl
-
- # Ubuntu/Linux 64-bit, CPU only, Python 3.5
- (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp35-cp35m-linux_x86_64.whl
-
- # Ubuntu/Linux 64-bit, GPU enabled, Python 3.5
- # Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
- (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.10.0-cp35-cp35m-linux_x86_64.whl
-
- # Mac OS X, CPU only, Python 3.4 or 3.5:
- (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.10.0-py3-none-any.whl
-
- # Mac OS X, GPU enabled, Python 3.4 or 3.5:
- (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow-0.10.0-py3-none-any.whl
最后根據是python 2還是3版本選擇一句進行安裝。
- # Python 2
- (tensorflow)$ pip install --ignore-installed --upgrade $TF_BINARY_URL
-
- # Python 3
- (tensorflow)$ pip3 install --ignore-installed --upgrade $TF_BINARY_URL
3.2 conda方式
conda上面目前有人已經做好了tensorflow的pkg,但是版本不一定最新,且只有CPU版本,不支持GPU。
步驟也是首先激活conda環境,然后調用conda install 語句安裝.
- $ source activate tensorflow
- (tensorflow)$ # Your prompt should change
-
- # Linux/Mac OS X, Python 2.7/3.4/3.5, CPU only:
- (tensorflow)$ conda install -c conda-forge tensorflow
上面的步驟完成后,從conda環境中退出:
- (tensorflow)$ source deactivate
4. 測試安裝
- $ source activate tensorflow
- (tensorflow)$ # Your prompt should change.
- # Run Python programs that use TensorFlow.
- ...
- # When you are done using TensorFlow, deactivate the environment.
- (tensorflow)$ source deactivate
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