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. The original
dualing.core, dualing.datasets, dualing.models.base, and dualing.utils
APIs remain available.
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.
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