def mult_test(self, xhat_re, xhat_im, shat_re, shat_im):
# log layer of xhat: Xhat
Xhat_re, Xhat_im = clog(xhat_re, xhat_im)
# log layer of shat: Shat
Shat_re, Shat_im = clog(shat_re, shat_im)
# multiplication of Xhat and Shat in log space: Yhat
Yhat1_re, Yhat1_im = cdot(self.Xhat_to_Yhat_re, self.Xhat_to_Yhat_im,
Xhat_re, Xhat_im)
Yhat2_re, Yhat2_im = cdot(self.Shat_to_Yhat_re, self.Shat_to_Yhat_im,
Shat_re, Shat_im)
Yhat_re = Yhat1_re + Yhat2_re
Yhat_im = Yhat1_im + Yhat2_im
# exp layer of Yhat: yhat
yhat_re, yhat_im = cexp(Yhat_re, Yhat_im)
return yhat_re, yhat_im
def output(self, x, output_y_im=False):
# DFT layer of x: xhat
xhat_re, xhat_im = cdot(self.x_to_xhat_re, self.x_to_xhat_im, x, T.zeros_like(x))
# log layer of xhat: Xhat
Xhat_re, Xhat_im = clog(xhat_re, xhat_im)
# multiplication of Xhat and Shat in log space: Yhat
Yhat_re, Yhat_im = cdot(self.Xhat_to_Yhat_re, self.Xhat_to_Yhat_im, Xhat_re, Xhat_im)
# exp layer of Yhat: yhat
yhat_re, yhat_im = cexp(Yhat_re, Yhat_im)
# inverse DFT layer of yhat: y
y_re, y_im = cdot(self.yhat_to_y_re, self.yhat_to_y_im, yhat_re, yhat_im)
if not output_y_im:
# output is real part of y
return y_re
else:
return y_re, y_im
def output(self, x, s, s_weight):
# DFT layer of x: xhat
xhat_re, xhat_im = cdot(self.x_to_xhat_re, self.x_to_xhat_im,
x, T.zeros_like(x))
# DFT layer of s / shift calculation: shat
shat_re, shat_im = cdot(self.s_to_shat_re, self.s_to_shat_im,
s, T.zeros_like(s))
# log layer of xhat: Xhat
Xhat_re, Xhat_im = clog(xhat_re, xhat_im)
if self.arch == 'conv':
# log layer of shat: Shat
Shat_re, Shat_im = clog(shat_re, shat_im)
elif self.arch == 'comp':
# linear transfer function for shat
Shat_re, Shat_im = shat_re, shat_im
else:
assert False
# multiplication of Xhat and Shat in log space: Yhat
Yhat1_re, Yhat1_im = cdot(self.Xhat_to_Yhat_re, self.Xhat_to_Yhat_im,
Xhat_re, Xhat_im)
Yhat2_re, Yhat2_im = cdot(self.Shat_to_Yhat_re, self.Shat_to_Yhat_im,
Shat_re, Shat_im)
Yhat_re = Yhat1_re + s_weight * Yhat2_re
Yhat_im = Yhat1_im + s_weight * Yhat2_im
# exp layer of Yhat: yhat
yhat_re, yhat_im = cexp(Yhat_re, Yhat_im)
# inverse DFT layer of yhat: y
y_re, y_im = cdot(self.yhat_to_y_re, self.yhat_to_y_im,
yhat_re, yhat_im)
return y_re, y_im
def output(self, x, s, output_y_im=False):
# DFT layer of x: xhat
xhat_re, xhat_im = cdot(self.x_to_xhat_re, self.x_to_xhat_im,
x, T.zeros_like(x))
# DFT layer of s: shat
shat_re, shat_im = cdot(self.s_to_shat_re, self.s_to_shat_im,
s, T.zeros_like(s))
# log layer of xhat: Xhat
Xhat_re, Xhat_im = clog(xhat_re, xhat_im)
# log layer of shat: Shat
#Shat_re, Shat_im = shat_re, shat_im
Shat_re, Shat_im = clog(shat_re, shat_im)
# multiplication of Xhat and Shat in log space: Yhat
Yhat1_re, Yhat1_im = cdot(self.Xhat_to_Yhat_re, self.Xhat_to_Yhat_im,
Xhat_re, Xhat_im)
Yhat2_re, Yhat2_im = cdot(self.Shat_to_Yhat_re, self.Shat_to_Yhat_im,
Shat_re, Shat_im)
Yhat_re = Yhat1_re + Yhat2_re
Yhat_im = Yhat1_im + Yhat2_im
# exp layer of Yhat: yhat
yhat_re, yhat_im = cexp(Yhat_re, Yhat_im)
# inverse DFT layer of yhat: y
y_re, y_im = cdot(self.yhat_to_y_re, self.yhat_to_y_im,
yhat_re, yhat_im)
if not output_y_im:
# output is real part of y
return y_re
else:
return y_re, y_im