File size: 2,100 Bytes
1e2bb2f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | import torch
from stimulus_synthesis.scoring.robust_transform import RobustTransformScorer, RobustTransformSpec, apply_robust_transform
class MeanScorer:
def score(self, videos, target, **kwargs):
return videos.mean(dim=(1, 2, 3, 4)).tolist()
def test_robust_transform_expands_draws_and_is_reproducible():
videos = torch.linspace(0, 1, steps=2 * 3 * 8 * 8).reshape(1, 2, 3, 8, 8)
spec = RobustTransformSpec(num_draws=4, crop_scale=0.8, gaussian_sigma=0.1)
first = apply_robust_transform(videos, spec)
second = apply_robust_transform(videos, spec)
assert first.shape == (4, 2, 3, 8, 8)
assert torch.equal(first, second)
def test_robust_transform_scorer_is_independent_of_batch_order():
a = torch.zeros(2, 3, 8, 8)
b = torch.ones(2, 3, 8, 8) * 0.5
videos = torch.stack([a, b], dim=0)
reversed_videos = torch.stack([b, a], dim=0)
scorer = RobustTransformScorer(MeanScorer(), RobustTransformSpec(num_draws=4, crop_scale=0.8, gaussian_sigma=0.1))
scores = scorer.score(videos, None)
reversed_scores = scorer.score(reversed_videos, None)
assert torch.allclose(torch.tensor(scores), torch.tensor(list(reversed(reversed_scores))))
def test_pipeline_default_score_transform_is_clean(monkeypatch):
"""Default scoring matches the canonical clean single pass (no robust augmentation)."""
from stimulus_synthesis.pipeline import NevoPipeline
from stimulus_synthesis.scoring.robust_transform import RobustTransformScorer
class DummyEncoderScorer:
def __init__(self, *args, **kwargs):
pass
def score(self, videos, target, **kwargs):
return [0.0] * videos.shape[0]
monkeypatch.setattr("stimulus_synthesis.pipeline.EncoderScorer", DummyEncoderScorer)
pipe = NevoPipeline(text_to_image=object(), image_to_video=object())
pipe._ensure_components(device="cpu")
# Robust augmentation is disabled by default -> the encoder scorer is used directly.
assert not isinstance(pipe.scorer, RobustTransformScorer)
assert isinstance(pipe.scorer, DummyEncoderScorer)
|