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https://github.com/open-mmlab/mmselfsup.git
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7a7b048f23
* [Feature]: Add BEiT Support * [Fix]: fix bugs after update * [Fix]: fix bugs in backbone * [Refactor]: refactor config * [Feature]: Support BEiTv2 * [Fix]: Fix UT * [Fix]: rename some configs * [Fix]: fix beitv2neck * [Refactor]: refactor beitv2 * [Fix]: fix lint * refactor configs * refactor beitv2 * update configs * add dalle target generator * refactor for beitv1 * refactor rel_pos_bias of beit * update configs * update configs * update v1 configs * update v2 configs * refactoe layer decay * update unittest * fix lint * fix ut * add docstrings * rename * fix lint * add beit model and log links * fix lint * update according to review * update * update * update LearningRateDecayOptimWrapperConstructor related configs * update init and backbone * update neck and vqkd * refactor neck * fix lint * add some comments * fix typo Co-authored-by: 任琴 <PJLAB\renqin@shai14001114l.pjlab.org> Co-authored-by: fangyixiao18 <fangyx18@hotmail.com>
29 lines
679 B
Python
29 lines
679 B
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import platform
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import pytest
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import torch
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from mmselfsup.models.backbones import BEiTViT
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backbone = dict(
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arch='base',
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patch_size=16,
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drop_path_rate=0.1,
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final_norm=True,
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layer_scale_init_value=0.1,
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)
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@pytest.mark.skipif(platform.system() == 'Windows', reason='Windows mem limit')
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def test_beit_vit():
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beit_backbone = BEiTViT(**backbone)
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beit_backbone.init_weights()
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fake_inputs = torch.randn((2, 3, 224, 224))
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fake_mask = torch.zeros((2, 196))
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fake_mask[:, 75:150] = 1
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fake_outputs = beit_backbone(fake_inputs, fake_mask)
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assert list(fake_outputs[0].shape) == [2, 197, 768]
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