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5 basic PyTorch functions used in Machine Learning

PyTorch is an open source machine learning framework developed by Facebook, which has gained popularity in recent years due to it's almost Pythonic like syntax and great support for parallelism. In this notebook we will be going over five basic functions operating on tensors in PyTorch.

  • torch.zeros
  • torch.eye
  • torch.reshape
  • torch.squeeze
  • torch.stack

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.zeros

Returns a tensor of 0s, with the predefined shape given by size parameter.

# Example 1 - working (change this)
t = torch.zeros(size=(5,))
t
tensor([0., 0., 0., 0., 0.])