6d174f8012
* Fix to nano installation panel styles to avoid swing behaviour * Generalize the installation panel css for chronos and nano, and make some improvements
105 lines
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4.5 KiB
Markdown
105 lines
No EOL
4.5 KiB
Markdown
# Nano Installation
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You can select bigdl-nano along with some dependencies specific to PyTorch or Tensorflow using the following panel.
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```eval_rst
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.. raw:: html
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<link rel="stylesheet" type="text/css" href="../../../_static/css/installation_panel.css" />
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<div class="installation-panel-wrapper">
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<table class="installation-panel-table">
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<tbody>
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<tr>
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<td colspan="1">FrameWork</td>
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<td colspan="2"><button id="pytorch" class="install_option_button">PyTorch</button></td>
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<td colspan="2"><button id="tensorflow" class="install_option_button">TensorFlow</button></td>
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</tr>
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<tr id="version">
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<td colspan="1">Version</td>
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<td colspan="1"><button id="pytorch_113" class="install_option_button">1.13</button></td>
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<td colspan="1"><button id="pytorch_112" class="install_option_button">1.12</button></td>
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<td colspan="1"><button id="pytorch_111" class="install_option_button">1.11</button></td>
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<td colspan="1"><button id="pytorch_110" class="install_option_button">1.10</button></td>
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</tr>
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<tr>
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<td colspan="1">Inference Opt</td>
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<td colspan="2"><button id="inference_yes" class="install_option_button">Yes</button></td>
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<td colspan="2"><button id="inference_no" class="install_option_button">No</button></td>
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</tr>
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<tr>
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<td colspan="1">Release</td>
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<td colspan="2"><button id="nightly" class="install_option_button">Nightly</button></td>
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<td colspan="2"><button id="stable" class="install_option_button">Stable</button></td>
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</tr>
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<tr>
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<td colspan="1">Install CMD</td>
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<td colspan="4" id="cmd">NA</td>
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</tr>
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</tbody>
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</table>
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</div>
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<script src="../../../_static/js/nano_installation_panel.js"></script>
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```
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```eval_rst
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.. note::
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Since bigdl-nano is still in the process of rapid iteration, we highly recommend that you install nightly build version through the above command to facilitate your use of the latest features.
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For stable version, please refer to the document and installation guide `here <https://bigdl.readthedocs.io/en/v2.2.0/doc/Nano/Overview/install.html>`_ .
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```
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## Environment Management
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### Install in conda environment (Recommended)
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```bash
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conda create -n env
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conda activate env
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# select your preference in above panel to find the proper command to replace the below command, e.g.
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pip install --pre --upgrade bigdl-nano[pytorch]
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# after installing bigdl-nano, you can run the following command to setup a few environment variables.
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source bigdl-nano-init
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```
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The `bigdl-nano-init` scripts will export a few environment variable according to your hardware to maximize performance.
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In a conda environment, when you run `source bigdl-nano-init` manually, this command will also be added to `$CONDA_PREFIX/etc/conda/activate.d/`, which will automaticly run when you activate your current environment.
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### Install in pure pip environment
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In a pure pip environment, you need to run `source bigdl-nano-init` every time you open a new shell to get optimal performance and run `source bigdl-nano-unset-env` if you want to unset these environment variables.
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## Other PyTorch/Tensorflow Version Support
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We support a wide range of PyTorch and Tensorflow. We only care the MAJOR.MINOR in [Semantic Versioning](https://semver.org/). If you have a specific PyTorch/Tensorflow version want to use, e.g. PyTorch 1.11.0+cpu, you may select corresponding MAJOR.MINOR (i.e., PyTorch 1.11 in this case) and install PyTorch again after installing nano.
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## Python Version
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`bigdl-nano` is validated on Python 3.7-3.9.
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## Operating System
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Some specific note should be awared of when installing `bigdl-nano`.`
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### Install on Linux
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For Linux, Ubuntu (22.04/20.04) is recommended.
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### Install on Windows (experimental support)
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For Windows OS, users could only run `bigdl-nano-init` every time they open a new cmd terminal.
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We recommend using Windows Subsystem for Linux 2 (WSL2) to run BigDL-Nano. Please refer to [Nano Windows install guide](../Howto/Install/windows_guide.md) for instructions.
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### Install on MacOS (experimental support)
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#### MacOS with Intel Chip
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Same usage as Linux, while some of the funcions now rely on lower version dependencies.
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#### MacOS with M-series chip
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Currently, only tensorflow is supported for M-series chip Mac.
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```bash
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# any way to install tensorflow on macos
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pip install --pre --upgrade bigdl-nano[tensorflow]
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``` |