def createMLP()

in lib/net_util.py [0:0]

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

def createMLP(dims, norm='bn', activation='relu', last_op=nn.Tanh(), dropout=False):
    act = None
    if activation == 'relu':
        act = nn.ReLU()
    if activation == 'lrelu':
        act = nn.LeakyReLU()
    if activation == 'selu':
        act = nn.SELU()
    if activation == 'elu':
        act = nn.ELU()
    if activation == 'prelu':
        act = nn.PReLU()

    mlp = []
    for i in range(1,len(dims)):
        if norm == 'bn':
            mlp += [  nn.Linear(dims[i-1], dims[i]),
                    nn.BatchNorm1d(dims[i])]
        if norm == 'in':
            mlp += [  nn.Linear(dims[i-1], dims[i]),
                    nn.InstanceNorm1d(dims[i])]
        if norm == 'wn':
            mlp += [  nn.utils.weight_norm(nn.Linear(dims[i-1], dims[i]), name='weight')]
        if norm == 'none':
            mlp += [ nn.Linear(dims[i-1], dims[i])]
        
        if i != len(dims)-1:
            if act is not None:
                mlp += [act]
            if dropout:
                mlp += [nn.Dropout(0.2)]

    if last_op is not None:
        mlp += [last_op]

    return mlp