Let's Explore PyTorch Tensor Functions

Introduction:
An short introduction about PyTorch and about the chosen functions.

PyTorch is a tensor library for deep learning using GPUs and CPU.It is a different kind of deep learning library (dynamic, rather than static).

TORCH.POW
TORCH.DIAGFLAT
TORCH.BINCOUNT
TORCH.MAX
TORCH.FMOD

Before we begin, let's install and import PyTorch

# Import torch and other required modules
import torch

Function 1 - torch.pow (input,exponent)

Used to calculate powers where atleast one of the input or exponent to be a tensor

# Example 1 - working 
a = torch.arange(1., 10.)
cubes_a = torch.pow(a,3)
print(len(a))
print(a)
cubes_a

9
tensor([1., 2., 3., 4., 5., 6., 7., 8., 9.])

tensor([  1.,   8.,  27.,  64., 125., 216., 343., 512., 729.])

torch.arange creates a 1-D tensor with default gap of 1 between each pair of adjacent points.Here 1 to 9 excluding the end point 10.
torch.pow calculates the power of each element in input tensor with exponent and returns a tensor