Neural Network Library 2.0

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I tried implementing this, but I can’t figure out how I can get the GeneticAlgorithm to use the trained network. The cars seem to only change their behavior when the generation has fiinished.
This is part of my code:

-- Create a new network with 5 inputs, 2 layers with 4 nodes each and 1 output "steerDirection"
local tempNet = FeedforwardNetwork.new({"front", "frontLeft", "frontRight", "left", "right"}, 2, 4, {"steerDirection"}, feedForwardSettings)
--local tempNet = FeedforwardNetwork.newFromSave(game.ServerStorage.NetworkSave.Value)
local populationSize = 15

local geneticAlgo = ParamEvo.new(tempNet, populationSize, geneticSetting)		-- Create ParamEvo with the tempNet template, population size and settings

local scoreTable = {}
local generations = 50	-- Number of generations to train network with
local firstRun = true
for _ = 0, generations do
	for index = 1, populationSize+1 do
		spawn(function()
			local startTime = os.clock()
			local clone = game:GetService("ServerStorage").Car:Clone()
			clone.RemoteControl.MaxSpeed = 200

			-- Parent to workspace and then setup Scripts of car
			clone.Parent = workspace

			local score = 0
			local bool = true
			local checkpointsHit = {}
			for _, v in pairs(clone:GetDescendants()) do
				if v:IsA("BasePart") and v.CanCollide == true then
					v.Touched:Connect(function(hit)
						if hit.Parent.Parent == workspace.Walls then	-- Destroy car on hit of walls
							bool = false
						elseif hit.Parent == workspace.Checkpoints and not checkpointsHit[tonumber(hit.Name)] then	-- Give extra points when car reaches checkpoint
							local numHit = tonumber(hit.Name)
							score += (numHit * 2)
							checkpointsHit[numHit] = hit
						end
					end)
				end
			end
			while bool do
				local distances = getRayDistances(clone)		-- Get Distances of rays
				local output
				if firstRun then
					output = tempNet(distances)				-- Get output of NN with input distances
				else
					local population = geneticAlgo:GetPopulation()
					local net = population[1].Network
					output = net(distances)				-- Get output of NN with input distances
				end

				-- Set steering direction to direction of NN
				clone.RemoteControl.SteerFloat = output.steerDirection
				-- Set speed of car
				--clone.RemoteControl.MaxSpeed = math.abs(output.speed) * 300

				-- Check if this simulation has been running for longer than x seconds
				if os.clock() > startTime + 90 then
					score -= 40	-- Punish algorithm
					break
				end
				wait()
			end
			
			score += (os.clock() - startTime)/2		-- Increment score based on time alive (longer is better)
			print("Exit score: "..math.floor(score*100)/100)

			clone:Destroy()
			scoreTable[index] = score
		end)
		wait(1)
	end
	-- Wait until generation finished
	repeat
		wait(1)
	until #scoreTable >= populationSize
	
	geneticAlgo:ProcessGeneration(scoreTable)
	scoreTable = {}
	firstRun = false
end

Also, would this save the right (best) network?
local save = geneticAlgo:GetBestNetwork():Save()

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