def forward()

in classy_vision/models/efficientnet.py [0:0]

• 17 lines of code
• 11 McCabe index (conditional complexity)

    def forward(self, inputs, drop_connect_rate=None):
        # Expansion and Depthwise Convolution
        if self.expand_ratio != 1:
            x = self.relu_fn(self.bn0(self.expand_conv(inputs)))
        else:
            x = inputs

        x = self.relu_fn(self.bn1(self.depthwise_conv(x)))

        # Squeeze and Excitation
        if self.has_se:
            # squeeze x in the spatial dimensions
            x_squeezed = self.se_avgpool(x)
            x_expanded = self.se_expand(self.relu_fn(self.se_reduce(x_squeezed)))
            x = torch.sigmoid(x_expanded) * x

        x = self.bn2(self.project_conv(x))

        # Skip connection and Drop Connect
        if self.id_skip:
            if self.stride == 1 and self.input_filters == self.output_filters:
                # only apply drop connect if a skip connection is present
                if drop_connect_rate:
                    x = drop_connect(x, self.training, drop_connect_rate)
                x = x + inputs
        return x