technical:recipes:tensorflow-in-virtualenv

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technical:recipes:tensorflow-in-virtualenv [2025-10-28 15:45] – [Create TensorFlow Virtualenv] thuachentechnical:recipes:tensorflow-in-virtualenv [2025-11-06 15:30] (current) – [Create TensorFlow Virtualenv] thuachen
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 </code> </code>
  
-The ''conda search tensorflow'' command can be used to locate the specific version you wish to install.  The example shows a search for TensorFlow release at least 2.17.0.+The ''conda search tensorflow'' command can be used to locate the specific version you wish to install.  The example shows a search for TensorFlow CPU release at least 2.17.0.
  
 <code bash> <code bash>
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 tensorflow                    2.17.0 cpu_py310h42475c5_1  conda-forge tensorflow                    2.17.0 cpu_py310h42475c5_1  conda-forge
 tensorflow                    2.17.0 cpu_py310h42475c5_2  conda-forge tensorflow                    2.17.0 cpu_py310h42475c5_2  conda-forge
-tensorflow                    2.17.0 cpu_py310h42475c5_3  conda-forge +
-tensorflow                    2.17.0 cpu_py311h6ac8430_0  conda-forge +
-tensorflow                    2.17.0 cpu_py311h6ac8430_1  conda-forge+
 ... ...
  
- +tensorflow                    2.19.0 cpu_py312h69ecde4_3  conda-forge 
-All versions of the TensorFlow virtual environment will be stored in the directory ''$WORKDIR/sw/tensorflow''; each virtual environment must have a unique name that will become the VALET version of TensorFlow. In this tutorial, we will install the Tensorflow version 2.19.0 with and without the CUDA support. An appropriate version for the former would be ''2.19.0:cpu'' and the latter ''2.19.0:cuda''.  Those versions can be translated to VALET-friendly directory names:+tensorflow                    2.19.0 cpu_py312h69ecde4_52  conda-forge 
 +tensorflow                    2.19.0 cpu_py312h69ecde4_53  conda-forge 
 +</code> 
 +All versions of the TensorFlow virtual environment will be stored in the directory ''$WORKDIR/sw/tensorflow''; each virtual environment must have a unique name that will become the VALET version of TensorFlow. In this tutorial, we will install the Tensorflow version 2.17.0 with the CPU support and with CUDA support. An appropriate version for the former would be ''2.17.0:cpu'' and the latter ''2.17.0:cuda''.  Those versions can be translated to VALET-friendly directory names:
  
 <code bash> <code bash>
-[(my_workgroup:user)@login01 ~]$ vpkg_id2path --version-id=2.19.0:cpu +[(my_workgroup:user)@login01 ~]$ vpkg_id2path --version-id=2.17.0:cpu 
-2.19.0-cpu +2.17.0-cpu 
-[(my_workgroup:user)@login01 ~]$ mkdir --mode=3750 ${WORKDIR}/sw/tensorflow/2.19.0-cpu+[(my_workgroup:user)@login01 ~]$ mkdir --mode=3750 ${WORKDIR}/sw/tensorflow/2.17.0-cpu
  
-[(my_workgroup:user)@login01 ~]$ vpkg_id2path --version-id=2.19.0:cuda +[(my_workgroup:user)@login01 ~]$ vpkg_id2path --version-id=2.17.0:cuda 
-2.19.0-cuda +2.17.0-cuda 
-[(my_workgroup:user)@login01 ~]$ mkdir --mode=3750 ${WORKDIR}/sw/tensorflow/2.19.0-cuda+[(my_workgroup:user)@login01 ~]$ mkdir --mode=3750 ${WORKDIR}/sw/tensorflow/2.17.0-cuda
 </code> </code>
  
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 <code bash> <code bash>
-[(my_workgroup:user)@login01 ~]$ conda create --prefix=${WORKDIR}/sw/tensorflow/2.19.0-cpu 'tensorflow[version=2.19.0,build=cpu_py312h69ecde4_52]' +[(my_workgroup:user)@login01 ~]$ conda create --prefix=${WORKDIR}/sw/tensorflow/2.17.0-cpu 'tensorflow[version=2.17.0,build=cpu_py310h42475c5_0]' 
-WARNING: A directory already exists at the target location '/work/workgroup/sw/tensorflow/2.19.0-cpu'+WARNING: A directory already exists at the target location '/work/workgroup/sw/tensorflow/2.17.0-cpu'
 but it is not a conda environment. but it is not a conda environment.
 Continue creating environment (y/[n])? y Continue creating environment (y/[n])? y
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 # To activate this environment, use # To activate this environment, use
 # #
-#     $ conda activate /work/workgroup/sw/tensorflow/2.19.0-cpu+#     $ conda activate /work/workgroup/sw/tensorflow/2.17.0-cpu
 # #
 # To deactivate an active environment, use # To deactivate an active environment, use
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 <code bash> <code bash>
-[(my_workgroup:user)@login01 ~]$ conda create --prefix=${WORKDIR}/sw/tensorflow/2.19.0-cuda 'tensorflow[version=2.19.0,build=cuda128py312hae5ec6b_202,channel=conda-forge]' +[(my_workgroup:user)@login01 ~]$ conda create --prefix=${WORKDIR}/sw/tensorflow/2.17.0-cuda 'python==3.10' -c conda-forge 
-WARNING: A directory already exists at the target location '/work/workgroup/sw/tensorflow/2.19.0-cuda'+WARNING: A directory already exists at the target location '/work/workgroup/sw/tensorflow/2.17.0-cuda'
 but it is not a conda environment. but it is not a conda environment.
 Continue creating environment (y/[n])? y Continue creating environment (y/[n])? y
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 # To activate this environment, use # To activate this environment, use
 # #
-#     $ conda activate /work/workgroup/sw/tensorflow/2.3.0-intel-python3.8+#     $ conda activate /work/workgroup/sw/tensorflow/2.17.0-cuda
 # #
 # To deactivate an active environment, use # To deactivate an active environment, use
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 #     $ conda deactivate #     $ conda deactivate
 </code> </code>
- +We will need to run the ''conda activate'' command and then install the Tensorflow with cuda: 
-Ignore that ''conda activate'' command as well. Roll back the environment changes before proceeding:+<code bash> 
 +[(my_workgroup:user)@login01 ~]$ conda activate /work/workgroup/sw/tensorflow/2.17.0-cuda 
 +(/work/workgroup/sw/tensorflow/2.17.0-cuda)[(my_workgroup:user)@login01 ~]$ pip install "tensorflow[and-cuda]==2.17.0" 
 +</code> 
 +Use ''conda deactivate'' command to exit the virtual environment. Roll back the environment changes before proceeding:
  
 <code bash> <code bash>
-[(my_workgroup:user)@login01 ~]$ vpkg_rollback +(/work/workgroup/sw/tensorflow/2.17.0-cuda)[(my_workgroup:user)@login01 ~]$ conda deactivate 
-[(my_workgroup:user)@login01 ~]$ +[(my_workgroup:user)@login01 ~]$ vpkg_rollback all
 </code> </code>
  
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           success: 0           success: 0
     versions:     versions:
-        "2.19.0:cpu": +        "2.17.0:cpu": 
-            description: 2.19.0 with CPU support+            description: 2.17.0 with CPU support
             dependencies:             dependencies:
                 - miniconda/25.1.1.2                 - miniconda/25.1.1.2
-        "2.19.0:cuda": +        "2.17.0:cuda": 
-            description: 2.19.0 with CUDA support+            description: 2.17.0 with CUDA support
             dependencies:             dependencies:
                 - miniconda/25.1.1.2                 - miniconda/25.1.1.2
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           success: 0           success: 0
     versions:     versions:
-        "2.19.0:cpu": +        "2.17.0:cpu": 
-            description: 2.19.0 with CPU support+            description: 2.17.0 with CPU support
             dependencies:             dependencies:
                 - miniconda/25.1.1.2                 - miniconda/25.1.1.2
-        "2.19.0:cuda": +        "2.17.0:cuda": 
-            description: 2.19.0 with CUDA support+            description: 2.17.0 with CUDA support
             dependencies:             dependencies:
                 - miniconda/25.1.1.2                 - miniconda/25.1.1.2
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 [/work/my_workgroup/sw/valet/tensorflow.vpkg_yaml] [/work/my_workgroup/sw/valet/tensorflow.vpkg_yaml]
 tensorflow               TensorFlow Python environments tensorflow               TensorFlow Python environments
-* 2.19.0:cpu              2.19.0 with GPU support +* 2.17.0:cpu              2.17.0 with GPU support 
-  2.19.0:cuda             2.19.0 with CUDA support+  2.17.0:cuda             2.17.0 with CUDA support
      
      :      :
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 # Setup TensorFlow virtualenv: # Setup TensorFlow virtualenv:
 # #
-vpkg_require tensorflow/2.19.0:cpu+vpkg_require tensorflow/2.17.0:cpu
  
 # #
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  • Last modified: 2025-10-28 15:45
  • by thuachen