**Neural Network Tutorials - Herong's Tutorial Examples** - 1.20, by Dr. Herong Yang

Commonly Used 'torch' Funcitons

This section describes some commonly used PyTorch functions, including add(), multiply(), matmul(), tf.reduce_sum(), tf.nn.softmax(), etc.

As a quick reference, here is a list of commonly used PyTorch, "torch" library, functions:

1. Functions provided by the "torch" module itself:

import torch

torch.empty(m, n, ...) - Creates an empty tensor with the given shape.

torch.rand(m, n, ...) - Creates a tensor of random values with the given shape.

torch.torch.zeros(m, n, ...) - Creates a tensor of zeros with the given shape.

torch.tensor([[...],[...],...]) - Creates an tensor with the given date.

torch.rand_like(a) - Creates an empty tensor with the given shape.

a.size() - Returns the size (shape) of this tensor.

torch.add(a,b) - Creates a tensor by taking the sum of two given tensors. Same as (a+b).

a.add_(b) - Updates this tensor by adding values from the given tensor.

x.view(n, m, ...) - Creates a tensor by reshaping this tensor with the given shape.

Table of Contents

Deep Playground for Classical Neural Networks

Building Neural Networks with Python

Simple Example of Neural Networks

TensorFlow - Machine Learning Platform

►PyTorch - Machine Learning Platform

►Commonly Used 'torch' Funcitons

CNN (Convolutional Neural Network)