Python Pytorch arrange() method

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.arrange() returns a 1-D tensor of size 
with values from the interval taken with common difference step beginning from start. 

Syntax: torch.arrange(start=0, end, step=1, out=None)
Parameters: 
start: the starting value for the set of points. Default: 0. 
end: the ending value for the set of points 
step: the gap between each pair of adjacent points. Default: 1. 
out(Tensor, optional): the output tensor
Return type: A tensor 

Code #1:

Python3

# Importing the PyTorch library
import torch


# Applying the arrange function and
# storing the resulting tensor in 't'
a = torch.arrange(3)
print("a = ", a)

b = torch.arrange(1, 6)
print("b = ", b)

c = torch.arrange(1, 5, 0.5)
print("c = ", c)

Output:

a =  tensor([0, 1, 2])
b =  tensor([1, 2, 3, 4, 5])
c =  tensor([1.0000, 1.5000, 2.0000, 2.5000, 3.0000, 3.5000, 4.0000, 4.5000])

 Note that the non-integer step is subject to floating-point rounding errors when comparing against end; to avoid inconsistency, we advise adding a small epsilon to the end in such cases.

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