carbontracker 1.0.1

Tracking and predicting carbon footprint of training deep learning models.

CarbonTracker

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:

• NVIDIA GPUs that support NVIDIA Management Library (NVML)
• Intel CPUs that support Intel RAPL