deel.lip.losses module¶
This module contains losses used in wasserstein distance estimation.
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deel.lip.losses.
HKR_loss
(alpha, min_margin=1, true_values=1, - 1)¶ Wasserstein loss with a regularization param based on hinge loss.
- Parameters
alpha – regularization factor
min_margin – minimal margin ( see hinge_margin_loss )
true_values – tuple containing the two label for each predicted class
- Returns
a function that compute the regularized Wasserstein loss
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deel.lip.losses.
KR_loss
(true_values=0, 1)¶ Loss to estimate wasserstein-1 distance using Kantorovich-Rubinstein duality.
- Parameters
true_values – tuple containing the two label for each predicted class
- Returns
Callable, the function to compute Wasserstein loss
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deel.lip.losses.
hinge_margin_loss
(min_margin=1)¶ Compute the hinge margin loss.
- Parameters
min_margin – the minimal margin to enforce.
- Returns
a function that compute the hinge loss
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deel.lip.losses.
neg_KR_loss
(true_values=1, - 1)¶ Loss to compute the negative wasserstein-1 distance using Kantorovich-Rubinstein duality.
- Parameters
true_values – tuple containing the two label for each predicted class
- Returns
Callable, the function to compute negative Wasserstein loss