Skip to main content

Data augmentation methods for deep learning (CutMix, MixUp, PuzzleMix)

Project description

mlxops-aug

Data augmentation methods for deep learning, including CutMix, MixUp, and PuzzleMix.

Installation

pip install mlxops-aug

For PuzzleMix support (requires pygco):

pip install "mlxops-aug[puzzlemix]"

Note: pygco requires a C compiler. See pyGCO for installation instructions.

Usage

CutMix / MixUp

from mlxops_aug import CutMixUp

aug = CutMixUp(
    num_classes=10,
    config={
        "use_cutmix": True,
        "use_mixup": True,
        "alpha": 1.0,
        "prob": 0.5,
    },
)

x_aug, y_aug = aug(x, y)

PuzzleMix

from mlxops_aug import PuzzleMix

aug = PuzzleMix(
    num_classes=10,
    config={
        "block_num": 2,
        "transport": True,
        "prob": 1.0,
    },
)

Requirements

  • Python >= 3.10
  • PyTorch >= 2.0
  • torchvision >= 0.15

License

MIT

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

mlxops_aug-0.1.5.tar.gz (2.0 MB view details)

Uploaded Source

Built Distribution

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

mlxops_aug-0.1.5-py3-none-any.whl (22.3 kB view details)

Uploaded Python 3

File details

Details for the file mlxops_aug-0.1.5.tar.gz.

File metadata

  • Download URL: mlxops_aug-0.1.5.tar.gz
  • Upload date:
  • Size: 2.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.14

File hashes

Hashes for mlxops_aug-0.1.5.tar.gz
Algorithm Hash digest
SHA256 00dc45db9dd667e3f54c0c86d684681f890bc9e0d46e40206d11873322aa2877
MD5 141f19c416a167918c8f212136791719
BLAKE2b-256 c60cbf1b7a617beab4ba7b7bb9c6ea70eee763690d4ef4984018554a4a320d4a

See more details on using hashes here.

File details

Details for the file mlxops_aug-0.1.5-py3-none-any.whl.

File metadata

  • Download URL: mlxops_aug-0.1.5-py3-none-any.whl
  • Upload date:
  • Size: 22.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.14

File hashes

Hashes for mlxops_aug-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 ed85bb61fafe93e6532ad80bd27699f93c7338c74c9ec1c3590c20a71cf2b956
MD5 19c6a59c37db459095b1a644759cff45
BLAKE2b-256 82ee7b149b3c5b73986af1600fddeb19eafb7a3b21d5e2e23970f5aa474dc262

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