Python Pytorch linspace() method
Last Updated :
10 Jan, 2022
PyTorch is an open-source machine learning library developed by Facebook. It is used for deep neural network and natural language processing purposes.
The function torch.linspace()
returns a one-dimensional tensor of steps equally spaced points between start and end.
The output tensor is 1-D of size steps.
Syntax: torch.linspace(start, end, steps=100, out=None)
Parameters:
start: the starting value for the set of point.
end: the ending value for the set of points
steps: the gap between each pair of adjacent points. Default: 100.
out(Tensor, optional): the output tensor
Return type: A tensor
Code #1:
Python3
import torch
a = torch.linspace( 3 , 10 , 5 )
print ( "a = " , a)
b = torch.linspace(start = - 10 , end = 10 , steps = 5 )
print ( "b = " , b)
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Output:
a = tensor([ 3.0000, 4.7500, 6.5000, 8.2500, 10.0000])
b = tensor([-10., -5., 0., 5., 10.])
Code #2: Visualization
Python3
import torch
import numpy as np
import matplotlib.pyplot as plt
a = torch.linspace( - 5 , 5 , 15 )
print (a)
plt.plot(a.numpy(), np.zeros(a.numpy().shape), color = 'red' , marker = "o" )
plt.title( "torch.linspace" )
plt.xlabel( "X" )
plt.ylabel( "Y" )
plt.show()
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Output:
tensor([-5.0000, -4.2857, -3.5714, -2.8571, -2.1429, -1.4286, -0.7143, 0.0000,
0.7143, 1.4286, 2.1429, 2.8571, 3.5714, 4.2857, 5.0000])
[torch.FloatTensor of size 15]
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