| """GPU-host tests; local execution requires torch, not installed by this test.""" |
| import sys |
| from pathlib import Path |
| import unittest |
| sys.path.insert(0,str(Path(__file__).resolve().parents[1]/'src')) |
| import torch |
| from visual_preference import sequence_logps,anchored_loss |
|
|
| class Preference(unittest.TestCase): |
| def test_completion_mask_and_shift(self): |
| logits=torch.zeros(1,4,3,requires_grad=True) |
| labels=torch.tensor([[-100,-100,1,2]]) |
| lp=sequence_logps(logits,labels) |
| self.assertAlmostEqual(float(lp[0]),-1.098612288,places=6) |
| (-lp.mean()).backward() |
| self.assertEqual(float(logits.grad[0,0].abs().sum()),0.) |
| self.assertGreater(float(logits.grad[0,1].abs().sum()),0.) |
| self.assertGreater(float(logits.grad[0,2].abs().sum()),0.) |
| self.assertEqual(float(logits.grad[0,3].abs().sum()),0.) |
| def test_preference_gradient_direction(self): |
| good=torch.tensor([-.7],requires_grad=True);bad=torch.tensor([-1.],requires_grad=True) |
| loss,_,_=anchored_loss(good,bad,torch.ones(1));loss.backward() |
| self.assertLess(float(good.grad[0]),0.) |
| self.assertGreater(float(bad.grad[0]),0.) |
| def test_ineligible_pairs_have_only_sft_gradient(self): |
| good=torch.tensor([-1.],requires_grad=True);bad=torch.tensor([-1.],requires_grad=True) |
| loss,_,_=anchored_loss(good,bad,torch.zeros(1));loss.backward() |
| self.assertAlmostEqual(float(loss),1.) |
| self.assertEqual(float(bad.grad[0]),0.) |
| def test_length_normalization(self): |
| logits=torch.zeros(2,4,3) |
| labels=torch.tensor([[-100,1,2,-100],[-100,1,2,1]]) |
| self.assertTrue(torch.allclose(sequence_logps(logits,labels),torch.full((2,),-1.098612288))) |
|
|
| if __name__=='__main__':unittest.main() |
|
|
