def make_conv3d_layers()

in common/nets/layer.py [0:0]

• 15 lines of code
• 7 McCabe index (conditional complexity)

def make_conv3d_layers(feat_dims, kernel=3, stride=1, padding=1, bnrelu_final=True):
    layers = []
    for i in range(len(feat_dims)-1):
        layers.append(
            nn.Conv3d(
                in_channels=feat_dims[i],
                out_channels=feat_dims[i+1],
                kernel_size=kernel,
                stride=stride,
                padding=padding
                ))
        # Do not use BN and ReLU for final estimation
        if i < len(feat_dims)-2 or (i == len(feat_dims)-2 and bnrelu_final):
            layers.append(nn.BatchNorm3d(feat_dims[i+1]))
            layers.append(nn.ReLU(inplace=True))

    return nn.Sequential(*layers)