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Python Pytorch range() method

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  • Last Updated : 22 Apr, 2020
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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.range() returns a 1-D tensor of size \left\lfloor \frac{\text{end} - \text{start}}{\text{step}} \right\rfloor + 1
with values from start to end with step step. Step is the gap between two values in the tensor.

 out_{i+1} = out_i + step

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 tensor

Return 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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