gru_classifier.py 文件源码

def init_params(options,W):

    n_h = options['n_h']
    n_y = options['n_y']

    params = OrderedDict()
    # W is initialized by the pretrained word embedding
    params['Wemb'] = W.astype(config.floatX)
    # otherwise, W will be initialized randomly
    # n_words = options['n_words']
    # n_x = options['n_x'] 
    # params['Wemb'] = uniform_weight(n_words,n_x)

    # bidirectional LSTM
    params = param_init_encoder(options,params,prefix="gru_encoder")
    params = param_init_encoder(options,params,prefix="gru_encoder_rev")

    params['Wy'] = uniform_weight(2*n_h,n_y)
    params['by'] = zero_bias(n_y)                                     

    return params