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
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:
# 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)
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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.