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https://github.com/open-mmlab/mmselfsup.git
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20488d01b4
* [Refactor]: Refactor data flow * [Fix]: Change data sample to data samples * [Fix]: Change batch_inputs to inputs * [Fix]: Fix lint and UT * [Fix]: Fix UT * [Fix]: Fix lint * [Fix]: Fix docstring * [Fix]: Fix UT * [Refactor]: Add assert in data preprocessor * [Fix]: Fix lint
109 lines
4.0 KiB
Python
109 lines
4.0 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from unittest import TestCase
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import numpy as np
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import torch
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# TODO: will use real PixelData once it is added in mmengine
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from mmengine.structures import InstanceData, LabelData
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from mmselfsup.structures import SelfSupDataSample
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def _equal(a, b):
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if isinstance(a, (torch.Tensor, np.ndarray)):
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return (a == b).all()
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else:
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return a == b
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class TestSelfSupDataSample(TestCase):
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def test_init(self):
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meta_info = dict(img_size=[256, 256])
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det_data_sample = SelfSupDataSample(metainfo=meta_info)
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assert 'img_size' in det_data_sample
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assert det_data_sample.img_size == [256, 256]
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def test_setter(self):
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selfsup_data_sample = SelfSupDataSample()
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# test gt_label
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gt_label_data = dict(value=[1])
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gt_label = LabelData(**gt_label_data)
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selfsup_data_sample.gt_label = gt_label
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assert 'gt_label' in selfsup_data_sample
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assert _equal(selfsup_data_sample.gt_label.value,
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gt_label_data['value'])
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# test idx
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idx_data = dict(value=[1])
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idx_instances = InstanceData(**idx_data)
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selfsup_data_sample.sample_idx = idx_instances
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assert 'sample_idx' in selfsup_data_sample
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assert _equal(selfsup_data_sample.sample_idx.value, idx_data['value'])
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# test mask
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mask_data = dict(value=torch.rand(4, 4))
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mask = InstanceData(**mask_data)
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selfsup_data_sample.mask = mask
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assert 'mask' in selfsup_data_sample
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assert _equal(selfsup_data_sample.mask.value, mask_data['value'])
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# test pred_label
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pred_label_data = dict(value=[1])
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pred_label_instances = LabelData(**pred_label_data)
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selfsup_data_sample.pred_label = pred_label_instances
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assert 'pred_label' in selfsup_data_sample
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assert _equal(selfsup_data_sample.pred_label.value,
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pred_label_data['value'])
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# test pseudo_label
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pseudo_label_data = dict(value=[1])
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pseudo_label_instances = InstanceData(**pseudo_label_data)
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selfsup_data_sample.pseudo_label = pseudo_label_instances
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assert 'pseudo_label' in selfsup_data_sample
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assert _equal(selfsup_data_sample.pseudo_label.value,
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pseudo_label_data['value'])
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def test_deleter(self):
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gt_label_data = dict(value=[1])
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selfsup_data_sample = SelfSupDataSample()
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gt_label = LabelData(value=gt_label_data)
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selfsup_data_sample.gt_label = gt_label
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assert 'gt_label' in selfsup_data_sample
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del selfsup_data_sample.gt_label
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assert 'gt_label' not in selfsup_data_sample
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idx_data = dict(value=[1])
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selfsup_data_sample = SelfSupDataSample()
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sample_idx = InstanceData(value=idx_data)
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selfsup_data_sample.sample_idx = sample_idx
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assert 'sample_idx' in selfsup_data_sample
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del selfsup_data_sample.sample_idx
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assert 'sample_idx' not in selfsup_data_sample
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mask_data = dict(value=torch.rand(4, 4))
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selfsup_data_sample = SelfSupDataSample()
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mask = InstanceData(**mask_data)
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selfsup_data_sample.mask = mask
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assert 'mask' in selfsup_data_sample
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del selfsup_data_sample.mask
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assert 'mask' not in selfsup_data_sample
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pred_label_data = dict(value=[1])
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selfsup_data_sample = SelfSupDataSample()
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pred_label = LabelData(value=pred_label_data)
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selfsup_data_sample.pred_label = pred_label
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assert 'pred_label' in selfsup_data_sample
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del selfsup_data_sample.pred_label
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assert 'pred_label' not in selfsup_data_sample
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pseudo_label_data = dict(value=[1])
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selfsup_data_sample = SelfSupDataSample()
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pseudo_label = InstanceData(value=pseudo_label_data)
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selfsup_data_sample.pseudo_label = pseudo_label
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assert 'pseudo_label' in selfsup_data_sample
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del selfsup_data_sample.pseudo_label
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assert 'pseudo_label' not in selfsup_data_sample
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