install tensorflow with specific version on Anaconda

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后悔当初
后悔当初 2021-02-02 02:33

Tensorflow has multiple versions, if I want to install a specific version in Anaconda, which command should I use.

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  • 2021-02-02 03:00

    I am assuming that you are using Windows, python3.5, and CPU version of tensorflow.

    let's first create conda environment.

    C:> conda create -n tensorflow python=3.5 
    C:> activate tensorflow
     (tensorflow)C:>  # Your prompt should change 
    

    After creating the conda environment successfully, issue the correct command to install the specific version. I will guide you through installing three different versions.

    To install version r1.0

    (tensorflow)C:> pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.0.1-cp35-cp35m-win_amd64.whl 
    

    To install version r1.3

    (tensorflow)C:> pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.3.0rc1-cp35-cp35m-win_amd64.whl 
    

    To install master version

    (tensorflow)C:> pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.2.0-cp35-cp35m-win_amd64.whl 
    

    let me know if this is what you are looking for

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  • 2021-02-02 03:07

    This is probably the simplest way to do it:

    pip install --ignore-installed --upgrade tensorflow==1.4
    

    If you want to see all available versions, you can check out https://pypi.python.org/pypi/tensorflow/json

    I would highly recommend you use virtualenv or conda to isolate your tensorflow installation, especially if you want to play-test different versions and the CPU/GPU versions.

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  • 2021-02-02 03:16

    I find the existing answers unsatisfying, as the OP asked specifically about Anaconda but the answers are just pip installs.

    You can list the available versions for install doing

    conda search tensorflow-gpu
    

    which should give you some output that looks like

    Loading channels: done
    # Name                       Version           Build  Channel             
    tensorflow-gpu                 1.4.1               0  pkgs/main           
    tensorflow-gpu                 1.5.0               0  pkgs/main           
    tensorflow-gpu                 1.6.0               0  pkgs/main           
    tensorflow-gpu                 1.7.0               0  pkgs/main           
    tensorflow-gpu                 1.8.0      h7b35bdc_0  pkgs/main           
    tensorflow-gpu                 1.9.0      hf154084_0  pkgs/main           
    tensorflow-gpu                1.10.0      hf154084_0  pkgs/main           
    tensorflow-gpu                1.11.0      h0d30ee6_0  pkgs/main           
    tensorflow-gpu                1.12.0      h0d30ee6_0  pkgs/main           
    tensorflow-gpu                1.13.1      h0d30ee6_0  pkgs/main           
    tensorflow-gpu                1.14.0      h0d30ee6_0  pkgs/main           
    tensorflow-gpu                1.15.0      h0d30ee6_0  pkgs/main           
    tensorflow-gpu                 2.0.0      h0d30ee6_0  pkgs/main           
    tensorflow-gpu                 2.1.0      h0d30ee6_0  pkgs/main           
    tensorflow-gpu                 2.2.0      h0d30ee6_0  pkgs/main
    

    Then you can select your version by passing it to the install command, for example:

    conda install tensorflow-gpu==2.0.0
    

    Note this will work the same for tensorflow (i.e. not the GPU version), just change the package name accordingly.

    If you use YAML environment configuration files, you can do the same thing:

    # environment.yml
    name: my_conda_env
    channels:
      - conda-forge
    dependencies:
      - tensorflow-gpu=2.0.0
    

    Create your environment with command:

    conda env create -f environment.yml
    

    or if you change the version of an already created environment:

    conda env update -f environment.yml
    
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