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Five comparision operations in PyTorch tensors

In this notebook five comparision operation functions are discussed as a part of Assignment-1 in the course Deep Learning with PyTorch:Zero to GANs offered by Jovian.ai in colloboration with freecodecamp.org. The five functions are as follows:

  • torch.eq
  • torch.equal
  • torch.ge
  • torch.le
  • torch.lt

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
Looking in links: https://download.pytorch.org/whl/torch_stable.html Requirement already satisfied: numpy in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (1.19.4) Requirement already satisfied: torch==1.7.0+cpu in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (1.7.0+cpu) Requirement already satisfied: torchvision==0.8.1+cpu in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (0.8.1+cpu) Requirement already satisfied: torchaudio==0.7.0 in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (0.7.0) Requirement already satisfied: future in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (from torch==1.7.0+cpu) (0.18.2) Requirement already satisfied: dataclasses in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (from torch==1.7.0+cpu) (0.6) Requirement already satisfied: typing-extensions in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (from torch==1.7.0+cpu) (3.7.4.3) Requirement already satisfied: numpy in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (1.19.4) Requirement already satisfied: torch==1.7.0+cpu in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (1.7.0+cpu) Requirement already satisfied: pillow>=4.1.1 in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (from torchvision==0.8.1+cpu) (8.0.1) Requirement already satisfied: torch==1.7.0+cpu in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (1.7.0+cpu) Requirement already satisfied: numpy in c:\users\dnabh\anaconda3\envs\jovian\lib\site-packages (1.19.4) 
# Import torch and other required modules
import torch

Function 1 - torch.eq

Computes element-wise equality

The second argument can be a number or a tensor whose shape is broadcastable with the first argument.

Syntax : torch.eq(input, other, *, out=None) → Tensor

Parameters :

  • input(tensor) : The tensor to compare
  • other(tensor / float) : the tensor or value to compare
  • Keyword Arguments : out (Tensor, optional) – the output tensor.

Returns A boolean tensor that is True where input is equal to other and False elsewhere

# Example 1 - working 
A = torch.tensor([[1, 2], [3, 4.]])
B = torch.tensor([[1, 5], [3, 4]])
torch.eq(A,B)
tensor([[ True, False],
        [ True,  True]])