In [187]:

    

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 [188]:

    

time = Variable(T.linspace(0, 2*math.pi, m), requires_grad = True)


    

In [189]:

    

x = forward(time)


    

In [190]:

    

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 [191]:

    

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


    

    
Out[191]:





[<matplotlib.lines.Line2D at 0x7f20a136d400>]






    

In [192]:

    

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


    

    
Out[192]:





[<matplotlib.lines.Line2D at 0x7f20a128bb38>]






    

In [193]:

    

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


    

    
Out[193]:





[<matplotlib.lines.Line2D at 0x7f20a11b10b8>]






    

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