# How should I encode the input which are 5 cards from a deck of 52 cards?

How should I design my input layer for the following classification problem?

Input: 5 cards (from a deck of 52 cards) in a card game;

Output: some classification using a neural network

How should I model the input layer?

Option A: 5 one-hot encodings for the 5 cards, i.e. 5 one-hot vectors of length 52 = 260 input vector. For example

[
[0,0,0,0,0,0,1,...],
[1,0,0,0,0,0,0,...],
[0,0,0,0,0,1,0,...],
[0,0,1,0,0,0,0,...],
[0,0,0,0,1,0,0,...]
]


Option B: 5 hot encoding encompassing all 5 cards in one 52 element vector

[1,0,1,0,1,1,1,...]


What are the disadvantages between A and B?