modeling.py 文件源码

def log_softmax_poisson(x, p_k, log_lambda, k_max = 10, eps = 0.0):

    F = x.shape[1]

    p_k = T.clip(p_k, eps, 1.0 - eps)
    x_k = T.clip(x, 0, k_max)

    p_k = T.reshape(p_k, (-1, k_max + 1))
    x_k = T.reshape(x_k, (-1, 1))

    y_cross_entropy = objectives.categorical_crossentropy(p_k, x_k)
    y_cross_entropy = T.reshape(y_cross_entropy, (-1, F))

    y_log_poisson = T.ge(x, k_max) * log_poisson(x - k_max, log_lambda, eps)

    y = - y_cross_entropy + y_log_poisson

    return y