Install Chronos on Windows#

There are 2 ways to install Chronos on Windows: install using WSL2 and install on native Windows. With WSL2, all the features of Chronos are available, while on native Windows, there are some limitations now.

Install using WSL2#

Step 1: Install WSL2#

Follow BigDL Windows User guide to install WSL2.

Step 2: Install Chronos#

Follow the Chronos Installation guide to install Chronos.

Install on native Windows#

Step1: Install conda#

We recommend using conda to manage the Chronos python environment, for more information on install conda on Windows, you can refer to here.

When conda is successfully installed, open the Anaconda Powershell Prompt, then you can create a conda environment using the following command:

# create a conda environment for chronos
conda create -n my_env python=3.7 setuptools=58.0.4  # you could change my_env to any name you want

Step2: Install Chronos from PyPI#

You can simply install Chronos from PyPI using the following command:

# activate your conda environment
conda activate my_env

# install Chronos nightly build version (2.1.0 stable release is not supported on native Windows)
pip install --pre --upgrade bigdl-chronos[pytorch]

You can use the install panel to select the proper install options based on your need, but there are some limitations now:

bigdl-chronos[distributed] is not supported.
intel_extension_for_pytorch (ipex) is unavailable for Windows now, so the related feature is not supported.

Known Issues on Native Windows#

Fail to Install Neural-compressor via pip#

Problem description

Installing neural-compressor via pip may stuck when installing pycocotools.

Solution

Install pycocotools using conda:

conda install pycocotools -c esri

Then neural-compressor can be successfully installed using pip, we recommend installing neural-compressor 1.13.1 or higher:

pip install neural-compressor==1.13.1

RuntimeError during Quantization#

Problem description

Calling forecaster.quantize() without specifying the metric parameter (e.g. forecaster.quantize(train_data)) will raise runtime error, it may happen when neural-compressor version is lower than 1.13.1

[ERROR] Unexpected exception AssertionError(’please use start() before end()’) happened during tuning.

RuntimeError: Found no quantized model satisfying accuracy criterion.

Solution

Upgrade neural-compressor to 1.13.1 or higher.

pip install neural-compressor==1.13.1

RuntimeError during forecaster.fit#

Problem description

ProphetForecaster.fit and ProphetModel.fit_eval may raise runtime error on native Windows.

RuntimeError: Error during optimization!

[ERROR] Chain [1] error: terminated by signal 3221225657

According to our test, this issue only arises on some test machines or environments, you could check it by running ProphetForecaster.fit and ProphetModel.fit_eval on your own machines or environments.

There is a similar issue in prophet repo, we will stay tuned for its progress.