def __init__()

in models/modules/dynamic_layers.py [0:0]

• 34 lines of code
• 3 McCabe index (conditional complexity)

    def __init__(self, in_channel_list, out_channel_list,
                 kernel_size_list=3, expand_ratio_list=6, stride=1, act_func='relu6', use_se=False, channels_per_group=1):
        super(DynamicMBConvLayer, self).__init__()
        
        self.in_channel_list = int2list(in_channel_list)
        self.out_channel_list = int2list(out_channel_list)
        
        self.kernel_size_list = int2list(kernel_size_list, 1)
        self.expand_ratio_list = int2list(expand_ratio_list, 1)
        
        self.stride = stride
        self.act_func = act_func
        self.use_se = use_se
        self.channels_per_group = channels_per_group
        
        # build modules
        max_middle_channel = round(max(self.in_channel_list) * max(self.expand_ratio_list))
        if max(self.expand_ratio_list) == 1:
            self.inverted_bottleneck = None
        else:
            self.inverted_bottleneck = nn.Sequential(OrderedDict([
                ('conv', DynamicPointConv2d(max(self.in_channel_list), max_middle_channel)),
                ('bn', DynamicBatchNorm2d(max_middle_channel)),
                ('act', build_activation(self.act_func, inplace=True)),
            ]))
        
        self.depth_conv = nn.Sequential(OrderedDict([
            ('conv', DynamicSeparableConv2d(max_middle_channel, self.kernel_size_list, stride=self.stride, channels_per_group=self.channels_per_group)),
            ('bn', DynamicBatchNorm2d(max_middle_channel)),
            ('act', build_activation(self.act_func, inplace=True))
        ]))
        if self.use_se:
            self.depth_conv.add_module('se', DynamicSE(max_middle_channel))
        
        self.point_linear = nn.Sequential(OrderedDict([
            ('conv', DynamicPointConv2d(max_middle_channel, max(self.out_channel_list))),
            ('bn', DynamicBatchNorm2d(max(self.out_channel_list))),
        ]))
        
        self.active_kernel_size = max(self.kernel_size_list)
        self.active_expand_ratio = max(self.expand_ratio_list)
        self.active_out_channel = max(self.out_channel_list)