def __init__(self, in_channels, out_channels, act_cfg=dict(type='ReLU'), norm_cfg=dict(type='BN')):
    super().__init__()
    self.in_channels = in_channels
    self.out_channels = out_channels
    self.act_cfg = act_cfg
    self.norm_cfg = norm_cfg
    self.relu = build_activation_layer(self.act_cfg)
    self.conv1 = nn.Conv2d(self.in_channels, (self.out_channels // 2), 1, stride=2, padding=0, bias=False)
    self.conv2 = nn.Conv2d(self.in_channels, (self.out_channels // 2), 1, stride=2, padding=0, bias=False)
    self.bn = build_norm_layer(self.norm_cfg, self.out_channels)[1]
def __init__(self, in_channels, out_channels, act_cfg=dict(type='ReLU'), norm_cfg=dict(type='BN')):
    super().__init__()
    self.in_channels = in_channels
    self.out_channels = out_channels
    self.act_cfg = act_cfg
    self.norm_cfg = norm_cfg
    self.relu = build_activation_layer(self.act_cfg)
    self.conv1 = nn.Conv2d(self.in_channels, (self.out_channels // 2), 1, stride=2, padding=0, bias=False)
    self.conv2 = nn.Conv2d(self.in_channels, (self.out_channels // 2), 1, stride=2, padding=0, bias=False)
    self.bn = build_norm_layer(self.norm_cfg, self.out_channels)[1]