In [26]:

    

import torch as t
import math
import random
import numpy as np
from torch.autograd import Variable
from matplotlib import mlab
from matplotlib import pylab as plt
%matplotlib inline

def g(x, prm):
    return (1/(prm[0]*math.sqrt(2*math.pi)))*t.exp(-(x-prm[1])**2/(2*prm[0]**2))

xMin = -5
xMax = 15
prmOrig = t.Tensor([1, 5])

xOrig = t.linspace(xMin, xMax, 150)
yOrig = g(xOrig, prmOrig)

plt.plot (xOrig.numpy(), yOrig.numpy(),'red')


    

    
Out[26]:





[<matplotlib.lines.Line2D at 0x7f1fb11d5fd0>]






    

In [28]:

    

xOrig.size()


    

    
Out[28]:





torch.Size([150])

In [27]: