# Python Pytorch linspace() method

• Last Updated : 10 Jan, 2022

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.linspace()` returns a one-dimensional tensor of steps equally spaced points between start and end.

The output tensor is 1-D of size steps.

Syntax: torch.linspace(start, end, steps=100, out=None)

Parameters:
start: the starting value for the set of point.
end: the ending value for the set of points
steps: the gap between each pair of adjacent points. Default: 100.
out(Tensor, optional): the output tensor

Return type: A tensor

Code #1:

## Python3

 `# Importing the PyTorch library``import` `torch`` ` `# Applying the linspace function and``# storing the resulting tensor in 't'``a ``=` `torch.linspace(``3``, ``10``, ``5``)``print``(``"a = "``, a)`` ` `b ``=` `torch.linspace(start ``=``-``10``, end ``=` `10``, steps ``=` `5``)``print``(``"b = "``, b)`

Output:

```a =  tensor([ 3.0000,  4.7500,  6.5000,  8.2500, 10.0000])
b =  tensor([-10.,  -5.,   0.,   5.,  10.])
```

Code #2: Visualization

## Python3

 `# Importing the PyTorch library``import` `torch``# Importing the NumPy library``import` `numpy as np`` ` `# Importing the matplotlib.pyplot function``import` `matplotlib.pyplot as plt`` ` `# Applying the linspace function to get a tensor of size 15 with values from -5 to 5``a ``=` `torch.linspace(``-``5``, ``5``, ``15``)``print``(a)`` ` `# Plotting``plt.plot(a.numpy(), np.zeros(a.numpy().shape), color ``=` `'red'``, marker ``=` `"o"``) ``plt.title(``"torch.linspace"``) ``plt.xlabel(``"X"``) ``plt.ylabel(``"Y"``) `` ` `plt.show()`

Output:

```tensor([-5.0000, -4.2857, -3.5714, -2.8571, -2.1429, -1.4286, -0.7143,  0.0000,
0.7143,  1.4286,  2.1429,  2.8571,  3.5714,  4.2857,  5.0000])

[torch.FloatTensor of size 15]
``` My Personal Notes arrow_drop_up