1. In order to use the tensorboard package tool in the tensorflow package, create a virtual environment pytorch in python==3.12.8 environment, use the command line as follows.
1.1 Use Anaconda prompt to enter the BASE environment
1.2 Create a virtual environment conda create -n pytorch python=3.12.8
1.3 Entering the pytorch virtual environment activate pytorch
1.4 Execute the following command line in the pytorch virtual environment
pip3 install torch==2.5.1 torchvision==0.20.1 matplotlib==3.7.5 numpy==1.26.4 tensorflow==2.16.1
Successfully installed contourpy-1.3.1 cycler-0.12.1 filelock-3.18.0 fonttools-4.56.0 fsspec-2025.3.0 kiwisolver-1.4.8 matplotlib-3.7.5 mpmath-1.3.0 networkx-3.4.2 numpy-1.26.4 pillow-11.1.0 pyparsing-3.2.3 sympy-1.13.1 torch-2.5.1 torchvision-0.20.1 tensorflow-2.16.1 tensorboard-2.16.2
2. In order to use the second new version of torchtext==0.17.0, according to the installation prompts of the torchtext official website, create a virtual environment pytorch311 in the python==3.11 environment, and use the command line as follows.
2.1 Use Anaconda prompt to enter the BASE environment
2.2 Create a virtual environment conda create -n pytorch311 python=3.11
2.3 Enter the pytorch311 virtual environment activate pytorch311
2.4 Execute the following command line in the pytorch311 virtual environment
pip3 install torch==2.2.0 torchvision torchaudio torchtext==0.17.0 matplotlib==3.10.0 numpy==1.26.4 pandas==2.2.3 jieba==0.42.1
Successfully installed filelock-3.18.0 fsspec-2025.3.2 mpmath-1.3.0 networkx-3.4.2 numpy-1.26.4 pillow-11.1.0 sympy-1.13.3 torch-2.2.0 torchaudio-2.2.0 torchdata-0.7.1 torchtext-0.17.0 torchvision-0.17.0 tqdm-4.67.1 pandas-2.2.3 jieba-0.42.1 matplotlib-3.10.0
3. Conclusion
Today 2025-04-04 17:00, all the above installation processes have been repeatedly installed and tested during this summary, and can be installed stably, silky and smoothly and run all installed software packages stably, reliably and safely after installation.
3.1 You only need to install the Anaconda software installation package downloaded on the official website once, and you can enter the BASE environment in the Anaconda prompt tool to create various virtual environments with different python versions;
3.2 The installation of torchtext must be based on the requirements of the torchtext official website, that is, the torchtext version is installed together with the corresponding torch version, and then other software packages must also be found on this basis and then installed;
3.3 Tensorboard installation. The information of the python version and the corresponding version of tensorflow displayed on the tensorflow website is relatively old. At this time, log in to the Kaggle official website to create a jupyter notebook of a code project, and query the Kaggle platform that has been installed and configured python, pytorch, tensorflow, and tensorboard versions. Then, after modifying the above installation command line on the local computer, you only need to use one line of command line to successfully install all software packages.
1.1 Use Anaconda prompt to enter the BASE environment
1.2 Create a virtual environment conda create -n pytorch python=3.12.8
1.3 Entering the pytorch virtual environment activate pytorch
1.4 Execute the following command line in the pytorch virtual environment
pip3 install torch==2.5.1 torchvision==0.20.1 matplotlib==3.7.5 numpy==1.26.4 tensorflow==2.16.1
Successfully installed contourpy-1.3.1 cycler-0.12.1 filelock-3.18.0 fonttools-4.56.0 fsspec-2025.3.0 kiwisolver-1.4.8 matplotlib-3.7.5 mpmath-1.3.0 networkx-3.4.2 numpy-1.26.4 pillow-11.1.0 pyparsing-3.2.3 sympy-1.13.1 torch-2.5.1 torchvision-0.20.1 tensorflow-2.16.1 tensorboard-2.16.2
2. In order to use the second new version of torchtext==0.17.0, according to the installation prompts of the torchtext official website, create a virtual environment pytorch311 in the python==3.11 environment, and use the command line as follows.
2.1 Use Anaconda prompt to enter the BASE environment
2.2 Create a virtual environment conda create -n pytorch311 python=3.11
2.3 Enter the pytorch311 virtual environment activate pytorch311
2.4 Execute the following command line in the pytorch311 virtual environment
pip3 install torch==2.2.0 torchvision torchaudio torchtext==0.17.0 matplotlib==3.10.0 numpy==1.26.4 pandas==2.2.3 jieba==0.42.1
Successfully installed filelock-3.18.0 fsspec-2025.3.2 mpmath-1.3.0 networkx-3.4.2 numpy-1.26.4 pillow-11.1.0 sympy-1.13.3 torch-2.2.0 torchaudio-2.2.0 torchdata-0.7.1 torchtext-0.17.0 torchvision-0.17.0 tqdm-4.67.1 pandas-2.2.3 jieba-0.42.1 matplotlib-3.10.0
3. Conclusion
Today 2025-04-04 17:00, all the above installation processes have been repeatedly installed and tested during this summary, and can be installed stably, silky and smoothly and run all installed software packages stably, reliably and safely after installation.
3.1 You only need to install the Anaconda software installation package downloaded on the official website once, and you can enter the BASE environment in the Anaconda prompt tool to create various virtual environments with different python versions;
3.2 The installation of torchtext must be based on the requirements of the torchtext official website, that is, the torchtext version is installed together with the corresponding torch version, and then other software packages must also be found on this basis and then installed;
3.3 Tensorboard installation. The information of the python version and the corresponding version of tensorflow displayed on the tensorflow website is relatively old. At this time, log in to the Kaggle official website to create a jupyter notebook of a code project, and query the Kaggle platform that has been installed and configured python, pytorch, tensorflow, and tensorboard versions. Then, after modifying the above installation command line on the local computer, you only need to use one line of command line to successfully install all software packages.