models.py 文件源码

def times_diag(input, n_hidden, diag, swap_re_im):
    # input is a Ix2n_hidden matrix, where I is number
    # of training examples
    # diag is a n_hidden-dimensional real vector, which creates
    # the 2n_hidden x 2n_hidden complex diagonal matrix using 
    # e.^{j.*diag}=cos(diag)+j.*sin(diag)
    d = T.concatenate([diag, -diag]) #d is 2n_hidden

    Re = T.cos(d).dimshuffle('x',0)
    Im = T.sin(d).dimshuffle('x',0)

    input_times_Re = input * Re
    input_times_Im = input * Im

    output = input_times_Re + input_times_Im[:, swap_re_im]

    return output