PyTorch: Getting Started

Getting started with Python

PyTorch is a python-based scientific computing package targeted at two sets of audiences.

A replacement for NumPy to use the power of GPUs
A deep learning research platform that provides maximum flexibility and speed

Following 5 functions are to get started with Tensors in Python

torch.randn
torch.sort
torch.linspace
torch.reshape
torch.transpose

# Import torch and other required modules
import torch

Function 1 - torch.randn

torch.randn(*size, out=None, dtype=None, layout=torch.strided, device=None, requires_grad=False) → Tensor

Returns a tensor filled with random numbers from a normal distribution with mean 0 and variance 1 (also called the standard normal distribution). The shape of the tensor is defined by the variable argument size.

# Example 1
x = torch.randn(4)
print('Initialized: ', x)

Initialized:  tensor([-0.1617,  0.9721,  0.1014,  0.2569])

1-dimensional random values assigned in a tensor variable