AttentionNet.py 文件源码

def build_emission_network(r2):
    if not isinstance(r2, lasagne.layers.Layer):
        l_in = lasagne.layers.InputLayer((None, glimpse_output_size, recurrent_output_size), r2)
    else:
        l_in = r2
    output = lasagne.layers.DenseLayer(l_in, 2, nonlinearity=nl.rectify, 
                                       W = emission_weights, b = emission_bias)
    return output

#input is r1 of length glimpse_output_size
#output is labels of length classification_units