Skip to main content

Tracking and predicting the carbon footprint of training deep learning models.

Project description

CarbonTracker

License: MIT

About

CarbonTracker is a tool for tracking and predicting the carbon footprint of training deep learning models.

Installation

PyPi install

pip install carbontracker

Basic usage

Required arguments

  • epochs: Total epochs of your training loop.

Optional arguments

  • epochs_before_pred (default=1): Epochs to monitor before outputting prediction. Set to -1 for all epochs.
  • monitor_epochs (default=1): Total number of epochs to monitor. Set to -1 for all epochs. Cannot be less than epochs_before_pred.
  • update_interval (default=10): Interval in seconds between power usage measurements are taken.
  • interpretable (default=True): If set to True then the CO2eq are also converted to interpretable numbers such as the equivalent distance travelled in a car, etc. Otherwise, no conversions are done.
  • stop_and_confirm (default=False): If set to True then the main thread (with your training loop) is paused after epochs_before_pred epochs to output the prediction and the user will need to confirm to continue training. Otherwise, prediction is output and training is continued instantly.
  • ignore_errors (default=False): If set to True then all errors will cause energy monitoring to be stopped and training will continue. Otherwise, training will be interrupted as with regular errors.
  • components (default="all"): Comma-separated string of which components to monitor. Options are: "all", "gpu", "cpu", or "gpu,cpu".
  • log_dir (default=None): Path to the desired directory to write log files. If None, then no logging will be done.
  • verbose (default=0): Sets the level of verbosity.

Example:

from carbontracker.tracker import CarbonTracker

tracker = CarbonTracker(epochs=max_epochs)

# Training loop.
for epoch in range(max_epochs):
    tracker.epoch_start()

    # Your model training

    tracker.epoch_end()

Compatability

CarbonTracker is compatible with:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

carbontracker-1.0.5.tar.gz (11.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

carbontracker-1.0.5-py3-none-any.whl (18.4 kB view details)

Uploaded Python 3

File details

Details for the file carbontracker-1.0.5.tar.gz.

File metadata

  • Download URL: carbontracker-1.0.5.tar.gz
  • Upload date:
  • Size: 11.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.4.2 requests/2.23.0 setuptools/39.1.0 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.6.5

File hashes

Hashes for carbontracker-1.0.5.tar.gz
Algorithm Hash digest
SHA256 e9e130e4d8262a2f489db29d1e32bbd867b37f21209b85067b1b57d2ef41bdc6
MD5 2596252abe4695fdd172f5ecd8959fea
BLAKE2b-256 9c108898e941a147cd95e3bef982a94d76e8e7e7954f4a44ee6ca96555236024

See more details on using hashes here.

File details

Details for the file carbontracker-1.0.5-py3-none-any.whl.

File metadata

  • Download URL: carbontracker-1.0.5-py3-none-any.whl
  • Upload date:
  • Size: 18.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.4.2 requests/2.23.0 setuptools/39.1.0 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.6.5

File hashes

Hashes for carbontracker-1.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 66b72d7b28849ce52224739fa236e4761c32541127d17402ced85ac189b2cc6d
MD5 74af98228a4be496164d198eb268fc28
BLAKE2b-256 0372cc9addaebe2eea43656365a60114ed2501808abd35431ff3e61d83496a1f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page