Transcendental-Programmer
Add unit tests for core modules: latent explorer, attribute directions, and custom loss
341b6b4
import unittest | |
import torch | |
from faceforge_core.custom_loss import attribute_preserving_loss | |
class TestAttributePreservingLoss(unittest.TestCase): | |
def setUp(self): | |
self.generated = torch.ones((2, 3, 4, 4)) | |
self.original = torch.zeros((2, 3, 4, 4)) | |
self.y_target = torch.ones((2, 1)) | |
self.attr_predictor = lambda x: torch.ones((2, 1)) | |
def test_loss_value(self): | |
loss = attribute_preserving_loss( | |
self.generated, self.original, self.attr_predictor, self.y_target, lambda_pred=2.0, lambda_recon=3.0 | |
) | |
# pred_loss = 0, recon_loss = mean((1-0)^2) = 1 | |
self.assertAlmostEqual(loss.item(), 3.0) | |
def test_loss_with_nonzero_pred(self): | |
attr_predictor = lambda x: torch.zeros((2, 1)) | |
loss = attribute_preserving_loss( | |
self.generated, self.original, attr_predictor, self.y_target, lambda_pred=2.0, lambda_recon=3.0 | |
) | |
# pred_loss = mean((0-1)^2) = 1, recon_loss = 1 | |
self.assertAlmostEqual(loss.item(), 5.0) | |
if __name__ == "__main__": | |
unittest.main() |