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e4080f8870
* add ppyoloe backbone, neck * add ppyoloe test * add docstring * add ppyoloe m/l/x configfile * add ppyoloe_coco.py * rename config * add typehint * format repvgg * format code; add ut * add doc; use mmdet.DropBlock * add doc, format code, add non-plus config * format code * format code * format code * format code * format code * format code
35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from unittest import TestCase
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import torch
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from mmyolo.models.layers import SPPFBottleneck
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from mmyolo.utils import register_all_modules
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register_all_modules()
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class TestSPPFBottleneck(TestCase):
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def test_forward(self):
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input_tensor = torch.randn((1, 3, 20, 20))
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bottleneck = SPPFBottleneck(3, 16)
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out_tensor = bottleneck(input_tensor)
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self.assertEqual(out_tensor.shape, (1, 16, 20, 20))
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bottleneck = SPPFBottleneck(3, 16, kernel_sizes=[3, 5, 7])
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out_tensor = bottleneck(input_tensor)
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self.assertEqual(out_tensor.shape, (1, 16, 20, 20))
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# set len(kernel_sizes)=4
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bottleneck = SPPFBottleneck(3, 16, kernel_sizes=[3, 5, 7, 9])
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out_tensor = bottleneck(input_tensor)
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self.assertEqual(out_tensor.shape, (1, 16, 20, 20))
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# set use_conv_first=False
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bottleneck = SPPFBottleneck(
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3, 16, use_conv_first=False, kernel_sizes=[3, 5, 7, 9])
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out_tensor = bottleneck(input_tensor)
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self.assertEqual(out_tensor.shape, (1, 16, 20, 20))
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