Tukukkk

I have just begun learning Julia. Here is an implementation of experience replay memory for use in a reinforcement learning algorithm. It is pretty simple, essentially a ring buffer with the following requirements:

• Used to store 1D arrays of numbers, typically Float32 or Float64. All the stored arrays are the same size.


• Has a maximum capacity, after which new entries overwrite old ones


• Has a sample function for retrieving a given number of entries

import Base.length



struct Memory{T <: Real}

   max_size::UInt32

   experiences::Vector{Vector{T}}

end



Memory{T}(max_size) where {T <: Real} = Memory{T}(max_size, Vector{Vector{T}}())



length(memory::Memory) = length(memory.experiences)



function remember!(memory::Memory, experience)

   size = length(memory)

   if size == memory.max_size

      memory.experiences[1 + size % memory.max_size] = experience

   else

      push!(memory.experiences, experience)

   end

end



function sample(memory::Memory{T}, count::Integer) where {T <: Real}

   size = length(memory)

   @assert count <= size

   return [memory.experiences[1 + rand(UInt32) % size] for i in 1:count]

end