In [199]:

    

import torch as T
import math
import numpy as np
from matplotlib import mlab
from matplotlib import pylab as plt
from torch.autograd import Variable, grad
%matplotlib inline

m=150
def forward(t):
    return T.sin(t)


    

In [200]:

    

time = Variable(T.linspace(0, 4*math.pi, m), requires_grad = True)
x = forward(time)
x.backward(Variable(T.Tensor(m).fill_(1)), retain_graph = True, create_graph = True)
vel = time.grad.clone()
time.grad.data.zero_()
vel.backward(Variable(T.Tensor(m).fill_(1)))
a = time.grad.clone()


    

In [201]:

    

plt.plot(time.data.numpy(), x.data.numpy(),'red')


    

    
Out[201]:





[<matplotlib.lines.Line2D at 0x7f20a1003f60>]






    

In [202]:

    

plt.plot(time.data.numpy(), vel.data.numpy(),'red')


    

    
Out[202]:





[<matplotlib.lines.Line2D at 0x7f20a0fac6a0>]






    

In [203]:

    

plt.plot(time.data.numpy(), (a+x).data.numpy(),'red')


    

    
Out[203]:





[<matplotlib.lines.Line2D at 0x7f20a0ec9c50>]






    

In [ ]: