Method
__init__
(self,
in_channels,
out_channel,
conv_cfg=None,
norm_cfg=dict(type='BN'),
act_cfg=dict(type='ReLU'),
init_cfg=None)
Source from the content-addressed store, hash-verified
| 92 | """ |
| 93 | |
| 94 | def __init__(self, |
| 95 | in_channels, |
| 96 | out_channel, |
| 97 | conv_cfg=None, |
| 98 | norm_cfg=dict(type='BN'), |
| 99 | act_cfg=dict(type='ReLU'), |
| 100 | init_cfg=None): |
| 101 | super(AttentionRefinementModule, self).__init__(init_cfg=init_cfg) |
| 102 | self.conv_layer = ConvModule( |
| 103 | in_channels=in_channels, |
| 104 | out_channels=out_channel, |
| 105 | kernel_size=3, |
| 106 | stride=1, |
| 107 | padding=1, |
| 108 | conv_cfg=conv_cfg, |
| 109 | norm_cfg=norm_cfg, |
| 110 | act_cfg=act_cfg) |
| 111 | self.atten_conv_layer = nn.Sequential( |
| 112 | nn.AdaptiveAvgPool2d((1, 1)), |
| 113 | ConvModule( |
| 114 | in_channels=out_channel, |
| 115 | out_channels=out_channel, |
| 116 | kernel_size=1, |
| 117 | bias=False, |
| 118 | conv_cfg=conv_cfg, |
| 119 | norm_cfg=norm_cfg, |
| 120 | act_cfg=None), nn.Sigmoid()) |
| 121 | |
| 122 | def forward(self, x): |
| 123 | x = self.conv_layer(x) |
Callers
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Tested by
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