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Python Pytorch linspace() method

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  • Last Updated : 10 Jan, 2022
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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




# Importing the PyTorch library
import torch
  
# Applying the linspace function and
# storing the resulting tensor in 't'
a = torch.linspace(3, 10, 5)
print("a = ", a)
  
b = torch.linspace(start =-10, end = 10, steps = 5)
print("b = ", b)


Output:

a =  tensor([ 3.0000,  4.7500,  6.5000,  8.2500, 10.0000])
b =  tensor([-10.,  -5.,   0.,   5.,  10.])

 

Code #2: Visualization

Python3




# Importing the PyTorch library
import torch
# Importing the NumPy library
import numpy as np
  
# Importing the matplotlib.pyplot function
import matplotlib.pyplot as plt
  
# Applying the linspace function to get a tensor of size 15 with values from -5 to 5
a = torch.linspace(-5, 5, 15)
print(a)
  
# Plotting
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()


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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