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84 lines
2.7 KiB
Python
84 lines
2.7 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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import torch
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from easycv.models.builder import build_head
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class UperHeadTest(unittest.TestCase):
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def setUp(self):
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print(('Testing %s.%s' % (type(self).__name__, self._testMethodName)))
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def test_forward_train(self):
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norm_cfg = dict(type='BN', requires_grad=True)
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uper_head_config = dict(
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type='UPerHead',
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in_channels=[256, 512, 1024, 2048],
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in_index=[0, 1, 2, 3],
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pool_scales=(1, 2, 3, 6),
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channels=512,
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dropout_ratio=0.1,
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num_classes=19,
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norm_cfg=norm_cfg,
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align_corners=False,
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loss_decode=dict(
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type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0))
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head = build_head(uper_head_config)
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head = head.to('cuda')
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batch_size = 2
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dummy_inputs = [
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torch.rand(batch_size, 256, 128, 128).to('cuda'),
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torch.rand(batch_size, 512, 64, 64).to('cuda'),
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torch.rand(batch_size, 1024, 32, 32).to('cuda'),
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torch.rand(batch_size, 2048, 16, 16).to('cuda'),
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]
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gt_semantic_seg = torch.randint(
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low=0, high=19, size=(batch_size, 1, 512, 512)).to('cuda')
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train_output = head.forward_train(
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dummy_inputs,
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img_metas=None,
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gt_semantic_seg=gt_semantic_seg,
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train_cfg=None)
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self.assertIn('loss_ce', train_output)
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self.assertIn('acc_seg', train_output)
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self.assertEqual(train_output['acc_seg'].shape, torch.Size([1]))
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def test_forward_test(self):
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norm_cfg = dict(type='BN', requires_grad=True)
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uper_head_config = dict(
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type='UPerHead',
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in_channels=[256, 512, 1024, 2048],
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in_index=[0, 1, 2, 3],
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pool_scales=(1, 2, 3, 6),
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channels=512,
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dropout_ratio=0.1,
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num_classes=19,
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norm_cfg=norm_cfg,
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align_corners=False,
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loss_decode=dict(
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type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0))
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head = build_head(uper_head_config)
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head = head.to('cuda')
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batch_size = 2
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dummy_inputs = [
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torch.rand(batch_size, 256, 128, 128).to('cuda'),
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torch.rand(batch_size, 512, 64, 64).to('cuda'),
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torch.rand(batch_size, 1024, 32, 32).to('cuda'),
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torch.rand(batch_size, 2048, 16, 16).to('cuda'),
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]
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with torch.no_grad():
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test_output = head.forward_test(
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dummy_inputs, img_metas=None, test_cfg=None)
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self.assertEqual(test_output.shape, torch.Size([2, 19, 128, 128]))
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if __name__ == '__main__':
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unittest.main()
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