151 lines
7 KiB
Markdown
151 lines
7 KiB
Markdown
# Chronos Installation
|
|
|
|
---
|
|
|
|
#### OS and Python version requirement
|
|
|
|
|
|
```eval_rst
|
|
.. note::
|
|
|
|
**Supported OS**:
|
|
|
|
Chronos is thoroughly tested on Ubuntu (16.04/18.04/20.04), and should works fine on CentOS. If you are a Windows user, there are 2 ways to use Chronos:
|
|
|
|
1. You could use Chronos on a windows laptop with WSL2 (you may refer to `here <https://docs.microsoft.com/en-us/windows/wsl/setup/environment>`_) or just install a ubuntu virtual machine.
|
|
|
|
2. You could use Chronos on native Windows, but some features are unavailable in this case, the limitations will be shown below.
|
|
```
|
|
```eval_rst
|
|
.. note::
|
|
|
|
**Supported Python Version**:
|
|
|
|
Chronos supports all installation options on Python 3.7 ~ 3.9. For details about different installation options, refer to `here <#install-using-conda>`_.
|
|
```
|
|
|
|
|
|
|
|
#### Install using Conda
|
|
|
|
We recommend using conda to manage the Chronos python environment. For more information about Conda, refer to [here](https://docs.conda.io/en/latest/miniconda.html#).
|
|
Select your preferences in the panel below to find the proper install command. Then run the install command as the example shown below.
|
|
|
|
|
|
```eval_rst
|
|
.. raw:: html
|
|
|
|
<link rel="stylesheet" type="text/css" href="../../../_static/css/installation_panel.css" />
|
|
|
|
<div class="installation-panel-wrapper">
|
|
|
|
<table class="installation-panel-table">
|
|
<tbody>
|
|
<tr>
|
|
<td colspan="1">Functionality</td>
|
|
<td colspan="2"><button id="Forecasting">Forecasting</button></td>
|
|
<td colspan="2"><button id="Anomaly" class="fitting-cell">Anomaly Detection</button></td>
|
|
<td colspan="2"><button id="Simulation">Simulation</button></td>
|
|
</tr>
|
|
<tr id="model">
|
|
<td colspan="1">Model</td>
|
|
<td colspan="2"><button id="Deep_learning_models">Deep learning</button></td>
|
|
<td colspan="2"><button id="Prophet">Prophet</button></td>
|
|
<td colspan="2"><button id="ARIMA">ARIMA</button></td>
|
|
</tr>
|
|
<tr>
|
|
<td colspan="1">DL framework</td>
|
|
<td colspan="3"><button id="pytorch"
|
|
title="Use PyTorch as deep learning models' backend. Most of the model support and works better under PyTorch.">PyTorch (Recommended)</button>
|
|
</td>
|
|
<td colspan="3"><button id="tensorflow"
|
|
title="Use Tensorflow as deep learning models' backend.">TensorFlow</button></td>
|
|
</tr>
|
|
<tr>
|
|
<td colspan="1">OS</td>
|
|
<td colspan="3"><button id="linux" title="Ubuntu/CentOS is recommended">Linux</button></td>
|
|
<td colspan="3"><button id="win" title="WSL is needed for Windows users">Windows</button></td>
|
|
</tr>
|
|
|
|
<tr>
|
|
<td colspan="1">Auto Tuning</td>
|
|
<td colspan="3" title="I don't need any hyperparameter auto tuning feature."><button
|
|
id="automlno">No</button></td>
|
|
<td colspan="3" title="I need chronos to help me tune the hyperparameters."><button
|
|
id="automlyes">Yes</button></td>
|
|
</tr>
|
|
|
|
<tr>
|
|
<td colspan="1">Inference Opt</td>
|
|
<td colspan="3" title="No need for low-latency inference models"><button id="inferenceno">No</button></td>
|
|
<td colspan="3" title="Get low-latency inference models with onnx\openvino\inc"><button id="inferenceyes">Yes</button></td>
|
|
</tr>
|
|
|
|
<tr>
|
|
<td colspan="1">Hardware</td>
|
|
<td colspan="3"><button id="singlenode" title="For users use laptop/single node server.">Single
|
|
node</button></td>
|
|
<td colspan="3"><button id="cluster" title="For users use K8S/Yarn Cluster.">Cluster</button></td>
|
|
</tr>
|
|
|
|
<tr>
|
|
<td colspan="1">Package</td>
|
|
<td colspan="3"><button id="pypi" title="For users use pip to install chronos.">Pip</button></td>
|
|
<td colspan="3"><button id="docker" title="For users use docker image.">Docker</button></td>
|
|
</tr>
|
|
|
|
<tr>
|
|
<td colspan="1">Version</td>
|
|
<td colspan="3"><button id="nightly"
|
|
title="For users would like to try chronos's latest feature">Nightly</button></td>
|
|
<td colspan="3"><button id="stable"
|
|
title="For users would like to deploy chronos in their production">Stable</button></td>
|
|
</tr>
|
|
|
|
<tr>
|
|
<td colspan="1">Install CMD</td>
|
|
<td colspan="6" id="cmd">NA</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
</div>
|
|
|
|
<script src="../../../_static/js/chronos_installation_panel.js"></script>
|
|
```
|
|
|
|
</br>
|
|
|
|
|
|
```bash
|
|
# create a conda environment for chronos
|
|
conda create -n my_env python=3.8 setuptools=58.0.4
|
|
conda activate my_env
|
|
|
|
# select your preference in above panel to find the proper command to replace the below command, e.g.
|
|
pip install --pre --upgrade bigdl-chronos[pytorch]
|
|
|
|
# init bigdl-nano to enable local accelerations
|
|
source bigdl-nano-init # accelerate the conda env
|
|
```
|
|
|
|
##### Install Chronos on native Windows
|
|
|
|
Chronos can be simply installed using pip on native Windows, you could use the same command as Linux to install, but unfortunately, some features are unavailable now:
|
|
|
|
1. `bigdl-chronos[distributed]` is not supported.
|
|
|
|
2. `intel_extension_for_pytorch (ipex)` is unavailable for Windows now, so the related feature is not supported.
|
|
|
|
For some known issues when installing and using Chronos on native Windows, you could refer to [windows_guide](https://bigdl.readthedocs.io/en/latest/doc/Chronos/Howto/windows_guide.html).
|
|
|
|
##### Install Chronos along with specific Tensorflow
|
|
|
|
Currently, the default Tensorflow version of Chronos is 2.7. But Chronos is also validated on Tensorflow 2.8-2.12. If you want to use specific Tensorflow, please follow the table below to find the extra install command after installing Chronos.
|
|
|
|
| TF version | Install CMD |
|
|
| ---------------- | --------------------------------------------------------------------------- |
|
|
| **2.8** | pip install tensorflow==2.8.0 intel-tensorflow==2.8.0 |
|
|
| **2.9** | pip install tensorflow==2.9.0 intel-tensorflow==2.9.1 |
|
|
| **2.10** | pip install tensorflow==2.10.0 intel-tensorflow==2.10.0 |
|
|
| **2.11** | pip install tensorflow==2.11.0 intel-tensorflow==2.11.0 |
|
|
| **2.12** | pip install tensorflow==2.12.0 intel-tensorflow==2.12.0 protobuf==3.20.3 |
|