This release has been yanked by its maintainers, and will be ignored by installers, except when explicitly specified.
Consider using release 2.0.1 instead.
Reason given by maintainers: AI-slop
Dualing
Dualing provides small TensorFlow building blocks for contrastive, cross-entropy, and triplet Siamese networks.
Install
uv add dualing
Dualing requires Python 3.11 or newer.
Quick start
import numpy as np
from dualing import MLP, ContrastiveSiamese, balanced_pair_dataset
samples = np.random.default_rng(0).normal(size=(100, 16))
labels = np.repeat([0, 1], 50)
dataset = balanced_pair_dataset(samples, labels, n_pairs=100, batch_size=16)
model = ContrastiveSiamese(MLP((32, 8)))
model.compile(optimizer="adam")
model.fit(dataset, epochs=5)
Dataset helpers return native tf.data.Dataset objects and all models use
standard Keras compile, fit, and evaluate behavior.
Development
uv sync
uv run pytest
uv run ruff check .
uv run ruff format --check .
uv run --group docs sphinx-build -W -b html docs docs/_build/html
uv build
API documentation is available at dualing.readthedocs.io.
1 maintainer
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