Updated 4 years ago
PyTorch tensor operations for Matrix Algebra
PyTorch is a python library which is used for doing mathematical operations over multi-dimensional tensors.
Some PyTorch functions I am going to be talking about in this notebook are:-
- torch.cross
- torch.diag
- torch.det
- torch.matmul
- torch.symeig
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 - torch.cross
This function computes the cross product of two tensors
# Example 1 - working
A = torch.tensor([[1, 2, 0],
[3, 4., 5]])
B = torch.tensor([[5, 6., 7],
[8, 9, 0]])
A, B
(tensor([[1., 2., 0.],
[3., 4., 5.]]), tensor([[5., 6., 7.],
[8., 9., 0.]]))