Five Super Useful Mathematical Operations on Tensors

Different ways to initialize a tensor in PyTorch

PyTorch is a powerful, open-source machine learning framework. This notebook contains 5 super useful mathematical operations on a tensor.

torch.exp()
torch.abs()
torch.ceil()
torch.floor()
torch.clamp()

# Import torch and other required modules
import torch

Function 1 - torch.exp()

This function will return the exponents of the tensor elements.
torch.exp(input, out=None) → Tensor

# Example 1 - working 
a = torch.ones((4,5))
b = torch.exp(a)
b

tensor([[2.7183, 2.7183, 2.7183, 2.7183, 2.7183],
        [2.7183, 2.7183, 2.7183, 2.7183, 2.7183],
        [2.7183, 2.7183, 2.7183, 2.7183, 2.7183],
        [2.7183, 2.7183, 2.7183, 2.7183, 2.7183]])

Returns a new tensor with the exponential of the elements of the input tensor
y_i=e^x_i