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Python Pytorch range() method

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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