videoClassifier_lasagne.py 文件源码

def build_network(self, input_var = None, batch_size = None):


        print "build_network in VideoClassifier executed.."
        print "inputs are : " , self.sinputs

        if not input_var is None: self.sinputs = input_var
        if not batch_size is None:
            self.batch_size = batch_size


        # Merge or fuse or concatenate incoming layers
        self.network['ConcatLayer'] = lasagne.layers.ConcatLayer([self.right_network['FC_2'], self.left_network['FC_2']], axis=1, cropping=None)


        self.network['FC_3'] = batch_norm(lasagne.layers.DenseLayer(
                            lasagne.layers.dropout(self.network['ConcatLayer'], p=self.dropout_rates[0]),
                            num_units=84,
                            nonlinearity=lasagne.nonlinearities.tanh))


        self.network['prob'] = batch_norm(lasagne.layers.DenseLayer(
                            lasagne.layers.dropout(self.network['FC_3'], p=self.dropout_rates[2]),
                            num_units=self.fc_layers[2],
                            nonlinearity=lasagne.nonlinearities.softmax))



        return self.network