def __init__()

in source/sent_classif.py [0:0]

• 33 lines of code
• 9 McCabe index (conditional complexity)

    def __init__(self, idim=1024, odim=2, nhid=None,
                 dropout=0.0, gpu=0, activation='TANH'):
        super(Net, self).__init__()
        self.gpu = gpu
        modules = []

        modules = []
        print(' - mlp {:d}'.format(idim), end='')
        if len(nhid) > 0:
            if dropout > 0:
                modules.append(nn.Dropout(p=dropout))
            nprev = idim
            for nh in nhid:
                if nh > 0:
                    modules.append(nn.Linear(nprev, nh))
                    nprev = nh
                    if activation == 'TANH':
                        modules.append(nn.Tanh())
                        print('-{:d}t'.format(nh), end='')
                    elif activation == 'RELU':
                        modules.append(nn.ReLU())
                        print('-{:d}r'.format(nh), end='')
                    else:
                       raise Exception('Unrecognized activation {activation}')
                    if dropout > 0:
                        modules.append(nn.Dropout(p=dropout))
            modules.append(nn.Linear(nprev, odim))
            print('-{:d}, dropout={:.1f}'.format(odim, dropout))
        else:
            modules.append(nn.Linear(idim, odim))
            print(' - mlp %d-%d'.format(idim, odim))
        self.mlp = nn.Sequential(*modules)
        # Softmax is included CrossEntropyLoss !

        if self.gpu >= 0:
            self.mlp = self.mlp.cuda()