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 tensorReturn 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]
