https://github.com/Capgemini-Invent-France/CarbonAI
Python package to monitor the power consumption of any algorithm
https://github.com/Capgemini-Invent-France/CarbonAI
Last synced: about 1 month ago
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Python package to monitor the power consumption of any algorithm
- Host: GitHub
- URL: https://github.com/Capgemini-Invent-France/CarbonAI
- Owner: Capgemini-Invent-France
- License: mit
- Created: 2021-09-30T17:12:13.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-10-17T13:51:06.000Z (over 2 years ago)
- Last Synced: 2025-03-14T14:39:02.026Z (2 months ago)
- Language: Python
- Homepage:
- Size: 1.96 MB
- Stars: 46
- Watchers: 4
- Forks: 12
- Open Issues: 22
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG
- Contributing: CONTRIBUTING.md
- License: LICENSE.txt
- Code of conduct: CODE_OF_CONDUCT.md
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README
# CarbonAI
This project aims at creating a python package that allows you to monitor the power consumption of any python function.
## Documentation
The complete documentation is available [here](https://capgemini-invent-france.github.io/CarbonAI/).
## Getting started
### Install
First of all you need to install the intel utility allowing you to monitor power consumption ([support](https://software.intel.com/en-us/articles/intel-power-gadget)):
* [Windows](https://software.intel.com/file/823776/download)
* [MacOS](https://software.intel.com/sites/default/files/managed/91/6b/Intel%20Power%20Gadget.dmg)
* Linux, no need to install any software
To install this package :
```sh
pip install carbonai
```
### Example
There are several ways to use this package depending on how you develop.
You just have to import the `PowerMeter` object, initialize it and call the function you want to monitor.
Please insert a description of the running function, the dataset, the model, any info would be useful.
#### Function decorator
To monitor the power consumption of a function, follow this example:
```python
from carbonai import PowerMeter
power_meter = PowerMeter(project_name="MNIST classifier")
@power_meter.measure_power(
package="sklearn",
algorithm="RandomForestClassifier",
data_type="tabular",
data_shape=.shape,
algorithm_params="n_estimators=300, max_depth=15",
comments="Classifier trained on the MNIST dataset, 3rd test"
)
def my_func(arg1, arg2, ...):
# Do something
```
#### Using the with statement
To monitor the power consumption of some specific inline code, you can use with statements
```python
from carbonai import PowerMeter
power_meter = PowerMeter(project_name="MNIST classifier")
with power_meter(
package="sklearn",
algorithm="RandomForestClassifier",
data_type="tabular",
data_shape=.shape,
algorithm_params="n_estimators=300, max_depth=15",
comments="Classifier trained on the MNIST dataset, 3rd test"
):
# Do something
```
## Contribute
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.
You can find details on how to contribute in [our guide](CONTRIBUTING.md)