Some simple and useful Pytorch functions

In this notebook I'll describe some useful Pytorch functions.

torch.rand(),
torch.transpose(),
torch.split(),
torch.arange(),
torch.inverse()

!pip install jovian --upgrade --quiet

!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

Looking in links: https://download.pytorch.org/whl/torch_stable.html
Requirement already satisfied: numpy in /opt/conda/lib/python3.8/site-packages (1.19.2)
Requirement already satisfied: torch==1.7.0+cpu in /opt/conda/lib/python3.8/site-packages (1.7.0+cpu)
Requirement already satisfied: torchvision==0.8.1+cpu in /opt/conda/lib/python3.8/site-packages (0.8.1+cpu)
Requirement already satisfied: torchaudio==0.7.0 in /opt/conda/lib/python3.8/site-packages (0.7.0)
Requirement already satisfied: future in /opt/conda/lib/python3.8/site-packages (from torch==1.7.0+cpu) (0.18.2)
Requirement already satisfied: dataclasses in /opt/conda/lib/python3.8/site-packages (from torch==1.7.0+cpu) (0.6)
Requirement already satisfied: typing-extensions in /opt/conda/lib/python3.8/site-packages (from torch==1.7.0+cpu) (3.7.4.3)
Requirement already satisfied: pillow>=4.1.1 in /opt/conda/lib/python3.8/site-packages (from torchvision==0.8.1+cpu) (8.0.0)

# Import torch and other required modules
import torch

Function 1 - Torch.Randn

Returns a tensor filled with random numbers from a normal distribution