| |
| import os.path as osp |
| import tempfile |
| from unittest import TestCase |
|
|
| import torch |
| from torch import Tensor |
|
|
| from mmengine.evaluator import DumpResults |
| from mmengine.fileio import load |
|
|
|
|
| class TestDumpResults(TestCase): |
|
|
| def test_init(self): |
| with self.assertRaisesRegex(ValueError, |
| 'The output file must be a pkl file.'): |
| DumpResults(out_file_path='./results.json') |
|
|
| def test_process(self): |
| metric = DumpResults(out_file_path='./results.pkl') |
| data_samples = [dict(data=(Tensor([1, 2, 3]), Tensor([4, 5, 6])))] |
| metric.process(None, data_samples) |
| self.assertEqual(len(metric.results), 1) |
| self.assertEqual(metric.results[0]['data'][0].device, |
| torch.device('cpu')) |
|
|
| def test_compute_metrics(self): |
| temp_dir = tempfile.TemporaryDirectory() |
| path = osp.join(temp_dir.name, 'results.pkl') |
| metric = DumpResults(out_file_path=path) |
| data_samples = [dict(data=(Tensor([1, 2, 3]), Tensor([4, 5, 6])))] |
| metric.process(None, data_samples) |
| metric.compute_metrics(metric.results) |
| self.assertTrue(osp.isfile(path)) |
|
|
| results = load(path) |
| self.assertEqual(len(results), 1) |
| self.assertEqual(results[0]['data'][0].device, torch.device('cpu')) |
|
|
| temp_dir.cleanup() |
|
|
