Tracking and predicting the carbon footprint of training deep learning models.
Project description
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 thanepochs_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 afterepochs_before_predepochs 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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
carbontracker-1.0.4.tar.gz
(11.7 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file carbontracker-1.0.4.tar.gz.
File metadata
- Download URL: carbontracker-1.0.4.tar.gz
- Upload date:
- Size: 11.7 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
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
882c4d6807319b3f25cd57943a742c1569c11428a00e7c66014c82e6c279c1a7
|
|
| MD5 |
16c42a384bcce0bb7e0bb7075fb04671
|
|
| BLAKE2b-256 |
507d1df0e3dc0f4158852b8009ad5465e4f23f11d87ec4a4588dcbfefd2cf187
|
File details
Details for the file carbontracker-1.0.4-py3-none-any.whl.
File metadata
- Download URL: carbontracker-1.0.4-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
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
fab90ab8cfff8d4bd09ef7b1b52711ea816d6602d0d3b61dda4a84a950870a02
|
|
| MD5 |
6bbc48bf662de9dc632bd2ebed5a5df0
|
|
| BLAKE2b-256 |
d779475b87a2fac8bd7cc8e54921f6ed1d01ac6da4a51f8bec7e14ef153bad24
|