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Package with losses for distribution learning

Project description

PyPI version Build Status PyPI license

Histogram Based Losses

This library contains implementations of some histogram-based loss functions:

  • Earth Mover Distrance Loss
  • Histgramm Loss (paper, original code)
  • Inverse Histogram Loss (our impovements)
  • Bidirectinal Histogramm Loss (our impovements)
  • Continuous Histogram Loss (paper)

Also there are implementations of another losses to compare:

  • Negative Log-Likelihood
  • Binomial Deviance loss (paper)

Installation

Installation from source

The instalation directly from this repository:

https://github.com/stat-ml/hist-loss.git
cd histloss
python setup.py install

Pip Installation

pip install hist-loss

Example of usage

criterion = HistogramLoss()
positive = torch.sigmoid(torch.randn(10, requires_grad=True))
negative = torch.sigmoid(torch.randn(10, requires_grad=True))
loss = criterion(positive, negative)
loss.backward()

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