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.range() returns a 1-D tensor of size 
with values from start to end with step step. Step is the gap between two values in the tensor.
This function is deprecated in favor of torch.arange().
Syntax: torch.range(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 tensorReturn type: A tensor
Code #1:
# Importing the PyTorch library import torch   # Applying the range function and # storing the resulting tensor in 't' a = torch.range(1, 6) print("a = ", a)   b = torch.range(1, 5, 0.5) print("b = ", b) |
Output:
a = tensor([1., 2., 3., 4., 5., 6.]) b = tensor([1.0000, 1.5000, 2.0000, 2.5000, 3.0000, 3.5000, 4.0000, 4.5000, 5.0000])
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