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* [Enhance] Support configuring synchronize directory for BaseMetric * Raise error if tmpdir is not an shared dirctory for ann ranks * Raise error if tmpdir is not an shared dirctory for ann ranks * Update mmengine/evaluator/metric.py Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com> * refine * Update mmengine/evaluator/metric.py --------- Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import os.path as osp
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import tempfile
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from unittest import TestCase
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import torch
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from torch import Tensor
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from mmengine.evaluator import DumpResults
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from mmengine.fileio import load
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class TestDumpResults(TestCase):
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def test_init(self):
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with self.assertRaisesRegex(ValueError,
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'The output file must be a pkl file.'):
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DumpResults(out_file_path='./results.json')
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# collect_dir could only be configured when collect_device='cpu'
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with self.assertRaises(ValueError):
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DumpResults(
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out_file_path='./results.json',
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collect_device='gpu',
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collect_dir='./tmp')
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def test_process(self):
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metric = DumpResults(out_file_path='./results.pkl')
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data_samples = [dict(data=(Tensor([1, 2, 3]), Tensor([4, 5, 6])))]
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metric.process(None, data_samples)
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self.assertEqual(len(metric.results), 1)
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self.assertEqual(metric.results[0]['data'][0].device,
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torch.device('cpu'))
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def test_compute_metrics(self):
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temp_dir = tempfile.TemporaryDirectory()
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path = osp.join(temp_dir.name, 'results.pkl')
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metric = DumpResults(out_file_path=path)
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data_samples = [dict(data=(Tensor([1, 2, 3]), Tensor([4, 5, 6])))]
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metric.process(None, data_samples)
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metric.compute_metrics(metric.results)
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self.assertTrue(osp.isfile(path))
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results = load(path)
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self.assertEqual(len(results), 1)
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self.assertEqual(results[0]['data'][0].device, torch.device('cpu'))
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temp_dir.cleanup()
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