python 2.7 - "sequences"参数在theano.scan中接受哪些参数以及如何解释它们

Question

我从 http://deeplearning.net/software/theano/library/scan.html 中获取了以下代码

    import numpy
    coefficients = theano.tensor.vector("coefficients")
    x = T.scalar("x")
    max_coefficients_supported = 10000
    # Generate the components of the polynomial
    components, updates = theano.scan(fn=lambda coefficient, power, free_variable: coefficient * (free_variable ** power),
                              outputs_info=None,
                              sequences=[coefficients, theano.tensor.arange(max_coefficients_supported)],
                              non_sequences=x)

这里的代码旨在解释"序列"参数。这是我的问题：

1. 序列是如何喂养的？第一项"系数"是一个张量变量。第二个术语"theano.tensor.arange（max_coefficients）"是一个张量变量，在使用eval（）时给出一个带有[0......999]的列表。教程说——

   "The tensor(s) to be looped over should be provided to scan using the sequence keyword argument."
   

   根据此处在"序列"中提供的参数，循环如何发生？

Answer 1

参数的顺序是：sequence[t]，outputs_infor，non_sequence

 coefficients[t]
 theano.tensor.arange(max_coefficients_supported)[t]
 x

outputs_infor保存上一次迭代的结果