(self,
in_channels=64,
block_channels=(64, 96, 128),
out_channels=128,
expand_ratio=6,
num_blocks=(3, 3, 3),
strides=(2, 2, 1),
pool_scales=(1, 2, 3, 6),
conv_cfg=None,
norm_cfg=dict(type='BN'),
act_cfg=dict(type='ReLU'),
align_corners=False)
| 114 | """ |
| 115 | |
| 116 | def __init__(self, |
| 117 | in_channels=64, |
| 118 | block_channels=(64, 96, 128), |
| 119 | out_channels=128, |
| 120 | expand_ratio=6, |
| 121 | num_blocks=(3, 3, 3), |
| 122 | strides=(2, 2, 1), |
| 123 | pool_scales=(1, 2, 3, 6), |
| 124 | conv_cfg=None, |
| 125 | norm_cfg=dict(type='BN'), |
| 126 | act_cfg=dict(type='ReLU'), |
| 127 | align_corners=False): |
| 128 | super(GlobalFeatureExtractor, self).__init__() |
| 129 | self.conv_cfg = conv_cfg |
| 130 | self.norm_cfg = norm_cfg |
| 131 | self.act_cfg = act_cfg |
| 132 | assert len(block_channels) == len(num_blocks) == 3 |
| 133 | self.bottleneck1 = self._make_layer(in_channels, block_channels[0], |
| 134 | num_blocks[0], strides[0], |
| 135 | expand_ratio) |
| 136 | self.bottleneck2 = self._make_layer(block_channels[0], |
| 137 | block_channels[1], num_blocks[1], |
| 138 | strides[1], expand_ratio) |
| 139 | self.bottleneck3 = self._make_layer(block_channels[1], |
| 140 | block_channels[2], num_blocks[2], |
| 141 | strides[2], expand_ratio) |
| 142 | self.ppm = PPM( |
| 143 | pool_scales, |
| 144 | block_channels[2], |
| 145 | block_channels[2] // 4, |
| 146 | conv_cfg=self.conv_cfg, |
| 147 | norm_cfg=self.norm_cfg, |
| 148 | act_cfg=self.act_cfg, |
| 149 | align_corners=align_corners) |
| 150 | |
| 151 | self.out = ConvModule( |
| 152 | block_channels[2] * 2, |
| 153 | out_channels, |
| 154 | 3, |
| 155 | padding=1, |
| 156 | conv_cfg=self.conv_cfg, |
| 157 | norm_cfg=self.norm_cfg, |
| 158 | act_cfg=self.act_cfg) |
| 159 | |
| 160 | def _make_layer(self, |
| 161 | in_channels, |
nothing calls this directly
no test coverage detected