First 5 things to start learning PyTorch Tensors

lets begin our TorchAdventure! with this 11 basic functions distributed in the following sections:

Creating tensors: Empty() and Zeros()
measuring tensors: Size() and Shape(), Sum() and Dimensions
changing and copying tensors: Reshape(), view() and randm()
modifying tensors: Unsqueeze()
comparing tensors: Element-Wise Equality: Eq

Before we begin, let's install and import PyTorch

# Uncomment and run the appropriate command for your operating system, if required

# Linux / Binder
# !pip install numpy torch==1.7.0+cpu torchvision==0.8.1+cpu torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html

# Windows
# !pip install numpy torch==1.7.0+cpu torchvision==0.8.1+cpu torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html

# MacOS
# !pip install numpy torch torchvision torchaudio

# Import torch and other required modules
import torch

Function 1 - Empty and Zeros - how to initialize tensors

We need to start workng with the basics pytorch functions, and the first thing is create our matrix


# Creates a 3 x 2 matrix which is empty
a = torch.empty(3, 2)
print(a)

tensor([[1.5842e-35, 0.0000e+00],
        [4.4842e-44, 0.0000e+00],
        [       nan, 0.0000e+00]])