| import sys |
| import types |
| import unittest |
| from pathlib import Path |
|
|
| import numpy as np |
|
|
| sys.path.insert(0, str(Path(__file__).resolve().parents[2] / "src")) |
|
|
| omegaconf_stub = types.ModuleType("omegaconf") |
| omegaconf_stub.OmegaConf = object |
| omegaconf_stub.DictConfig = object |
| sys.modules.setdefault("omegaconf", omegaconf_stub) |
|
|
| data_stub = types.ModuleType("data") |
| octflow_stub = types.ModuleType("data.octflow_dataset") |
| octflow_stub.OCTFlowDataset = object |
| sys.modules.setdefault("data", data_stub) |
| sys.modules.setdefault("data.octflow_dataset", octflow_stub) |
|
|
| from train_sd3_t2i import build_balanced_sampling_weights |
|
|
|
|
| class TaxonomySamplingTest(unittest.TestCase): |
| def test_temperature_sampling_gives_each_group_equal_total_weight_at_zero_temperature(self): |
| labels = np.array(["fundus"] * 8 + ["ubm"] * 2) |
|
|
| weights, counts, targets = build_balanced_sampling_weights( |
| labels, |
| temperature=0.0, |
| min_count=1, |
| ) |
|
|
| self.assertEqual(counts, {"fundus": 8, "ubm": 2}) |
| self.assertAlmostEqual(weights[:8].sum(), weights[8:].sum(), places=8) |
| self.assertEqual(set(targets), {"fundus", "ubm"}) |
|
|
| def test_min_count_excludes_tiny_groups(self): |
| labels = np.array(["fundus"] * 8 + ["ir_slo"] * 2) |
|
|
| weights, counts, targets = build_balanced_sampling_weights( |
| labels, |
| temperature=0.5, |
| min_count=3, |
| ) |
|
|
| self.assertEqual(counts, {"fundus": 8, "ir_slo": 2}) |
| self.assertGreater(weights[:8].sum(), 0.0) |
| self.assertEqual(weights[8:].sum(), 0.0) |
| self.assertEqual(targets, {"fundus": 1.0}) |
|
|
|
|
| if __name__ == "__main__": |
| unittest.main() |
|
|
