JADE.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e53f33d3-8a7d-402d-bfc0-566a905faa6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import numpy as np\n",
    "import pickle\n",
    "#from torchsummary import summary\n",
    "from collections import OrderedDict\n",
    "from torch.utils.tensorboard import SummaryWriter\n",
    "import datetime\n",
    "import time\n",
    "import copy\n",
    "import torchvision.datasets as datasets\n",
    "mnist_trainset = datasets.MNIST(root='./data', train=True, download=True, transform=None)\n",
    "mnist_testset = datasets.MNIST(root='./data', train=False, download=True, transform=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b7cb97ff-7acb-44ef-b9d6-979b457b79da",
   "metadata": {},
   "outputs": [],
   "source": [
    "class DNN(torch.nn.Module):\n",
    "    def __init__(self, layers):\n",
    "        super(DNN, self).__init__()\n",
    "        # depth of the neural network and activation function\n",
    "        self.depth = len(layers)-1\n",
    "        self.activation = torch.nn.ReLU\n",
    "        # layers: (depth-1)x 'linear' + 'activation' + last one 'linear'\n",
    "        layer_list = list()\n",
    "        for i in range(self.depth-1): \n",
    "            layer_list.append(\n",
    "                ('layer_%d' % i, torch.nn.Linear(layers[i], layers[i+1]))\n",
    "            )\n",
    "            layer_list.append(('activation_%d' % i, self.activation())) \n",
    "        layer_list.append(\n",
    "            ('layer_%d' % (self.depth - 1), torch.nn.Linear(layers[-2], layers[-1]))\n",
    "        )\n",
    "        layerDict = OrderedDict(layer_list)\n",
    "        self.layers = torch.nn.Sequential(layerDict)\n",
    "        \n",
    "    def forward(self, x):\n",
    "        out = self.layers(x)\n",
    "        return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "99960ef9-e149-4b11-8df1-c52f218fab7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Assume the dim of Traing and Testing are in shape [N,C,H,W]\n",
    "\n",
    "class DE_MLP():\n",
    "    def __init__(self, outdim=1,maxdepth=70,mindepth=5,minneuron=4,maxneuron=10,bsize=10,epoch=100,initSize=20,maxiter=10,stopcount=3,\\\n",
    "                 trainingset=None,validationset=None,trainingTarget=None,validateTarget=None,crossover=1):\n",
    "        self.best=[]\n",
    "        self.mean=[]\n",
    "        self.outdim=outdim\n",
    "        self.maxdepth=maxdepth\n",
    "        self.mindepth=mindepth\n",
    "        self.minneuron = minneuron\n",
    "        self.maxneuron = maxneuron\n",
    "        self.bsize = bsize\n",
    "        self.epoch = epoch\n",
    "        self.stopcount = stopcount\n",
    "        self.pplSize = initSize\n",
    "        self.maxiter = maxiter\n",
    "        self.training = trainingset.reshape((trainingset.shape[0],-1))\n",
    "        self.validationSet = validationset.reshape((validationset.shape[0],-1))\n",
    "        self.target=trainingTarget\n",
    "        self.validationTarget = validateTarget\n",
    "        self.MLPlayerlist = []\n",
    "        self.depthlist=np.random.choice(range(self.mindepth,self.maxdepth),self.pplSize,replace=True)\n",
    "        self.crossover=crossover\n",
    "        self.adap_conf = (0.1,0.1,0.9)\n",
    "        self.tb = SummaryWriter('./Statistic/'+datetime.datetime.now().strftime(\"%Y%m%d-%H%M%S\"))\n",
    "        \n",
    "        if torch.cuda.is_available():\n",
    "            self.device = torch.device('cuda')\n",
    "        else:\n",
    "            self.device = torch.device('cpu')\n",
    "\n",
    "        # Generate initial population\n",
    "        for i in range(self.pplSize):\n",
    "            depth = self.depthlist[i]\n",
    "            tmp = []\n",
    "            # the number of neurons for the first layer is the dimension of the element in training data (in our case the size of the image)\n",
    "            tmp.append(self.training.shape[1])\n",
    "            for j in range(depth):\n",
    "                # generate the number of neurons for each layer\n",
    "                tmp.append(np.random.choice(range(self.minneuron,self.maxneuron),1,replace=False)[0])\n",
    "            tmp.append(self.outdim) # last layer consist of 1 neuron by default\n",
    "            tmp=np.array(tmp)\n",
    "            self.MLPlayerlist.append(tmp)\n",
    "    \n",
    "    # define fit function - it calculates the fitness of one individual (one NN) \n",
    "    def fit(self,config,id_,p=None):\n",
    "        dnn = DNN(config) # define DNN based on configurations (layers and neurons)\n",
    "        dnn.layers.to(self.device)\n",
    "        best = float('inf')\n",
    "        stop=0\n",
    "        opt = torch.optim.Adam(dnn.layers.parameters(), lr=0.001)\n",
    "        loss = torch.nn.BCEWithLogitsLoss()\n",
    "        batch = self.training.shape[0]//self.bsize\n",
    "        vbatch = self.validationSet.shape[0]//self.bsize\n",
    "        idxs = [x for x in range(self.training.shape[0])]\n",
    "        vidxs = [x for x in range(self.validationSet.shape[0])]\n",
    "        for e in range(self.epoch):\n",
    "            start=time.time()\n",
    "            # training\n",
    "            np.random.shuffle(idxs)\n",
    "            dnn.layers.train()\n",
    "            batchloss=0\n",
    "            for i in range(batch):\n",
    "                idx=idxs[i*self.bsize:i*self.bsize+self.bsize]\n",
    "                opt.zero_grad()\n",
    "                data = torch.tensor(self.training[idx]).float().to(self.device)\n",
    "                y = torch.tensor(self.target[idx]).float().to(self.device)\n",
    "                yhat = dnn(data)\n",
    "                l = loss(yhat,y)\n",
    "                batchloss+=l.item()\n",
    "                l.backward()\n",
    "                opt.step()\n",
    "            # validating\n",
    "            dnn.layers.eval()\n",
    "            np.random.shuffle(vidxs)\n",
    "            vloss=0\n",
    "            for i in range(vbatch):\n",
    "                vidx=vidxs[i*self.bsize:i*self.bsize+self.bsize]\n",
    "                vdata = torch.tensor(self.validationSet[vidx]).float().to(self.device)\n",
    "                vy = torch.tensor(self.validationTarget[vidx]).float().to(self.device)\n",
    "                vyhat = dnn(vdata)\n",
    "                vl = loss(vyhat,vy)\n",
    "                vloss += vl.item()\n",
    "            vloss = vloss/vbatch\n",
    "            # updating best loss\n",
    "            if(vloss<best): best=vloss\n",
    "            # updating stopping condition\n",
    "            else: stop+=1\n",
    "            end=time.time()\n",
    "            if(p is not None):\n",
    "                print(f'Process: {p:3d}, ConfigID: {id_:3d}, Epoch: {e:3d}, Training Loss: {(batchloss/batch):10.8f}, Validation Loss: {(vloss):10.8f},\\\n",
    "                    Best: {best:10.8f}, StopCount/Limit: {stop:3d}/{self.stopcount:3d}, Time:{(end-start):10.8f}')\n",
    "            else:\n",
    "                print(f'ConfigID: {id_:3d}, Epoch: {e:3d}, Training Loss: {(batchloss/batch):10.8f}, Validation Loss: {(vloss):10.8f},\\\n",
    "                    Best: {best:10.8f}, StopCount/Limit: {stop:3d}/{self.stopcount:3d}, Time:{(end-start):10.8f}')\n",
    "            # stopping condition and stopping\n",
    "            if(stop>=self.stopcount):\n",
    "                return best,config,id_ \n",
    "\n",
    "    def find_pbest(self,scores,p):\n",
    "        pi = int(p*len(scores)+1) # it is taken p% out of length and then ceiling\n",
    "        fits = scores.copy() # keep scores and its indexes\n",
    "        fits = sorted(fits)[::-1] # sort fits desc\n",
    "        idx = np.random.choice(range(pi),1,replace=False)[0] # random index for sorted fits\n",
    "        return list(scores).index(fits[idx]) # return the index from sorted\n",
    "    \n",
    "    def self_adaptive_beta(self,beta):\n",
    "        tau,beta1,betau = self.adap_conf\n",
    "        r1,r2 = np.random.uniform(0,1,2)\n",
    "        if(r2 < tau): beta = round(beta1 + r1 * betau,3) # else, keep the beta same\n",
    "        return beta\n",
    "    \n",
    "    def mutation_pbest_1_z(self,x,x1,xs,beta,debug=False):\n",
    "        indim = x[0]\n",
    "        # forget first and last layers\n",
    "        x,x1,xs[0],xs[1] = x[1:-1],x1[1:-1],xs[0][1:-1],xs[1][1:-1]\n",
    "        if(debug):\n",
    "            print(f'M1 : x len {x.shape[0]} x1 len {x1.shape[0]} xs0 len {xs[0].shape[0]} xs1 len {xs[1].shape[0]}')\n",
    "            print(f'M1 : x {x} \\nM1 : x1 {x1} \\nM1 : xs0 {xs[0]} \\nM1 : xs1 len {xs[1]}')\n",
    "        #\n",
    "        # A. Mutating the # of layers\n",
    "        minlen = np.min([x.shape[0],x1.shape[0],xs[0].shape[0],xs[1].shape[0]])\n",
    "        if(debug): print(f'M1 : minlen {minlen}')          \n",
    "        newminlen = minlen\n",
    "        targetlen=int(np.floor( (x.shape[0]) + beta * (x1.shape[0] - x.shape[0]) + beta * (xs[0].shape[0] - xs[1].shape[0]) ))\n",
    "        # check the sign of targetlen: if the new length == 0 , set it back to target len , if <0 , take abs\n",
    "        if(targetlen==0): targetlen=x1.shape[0]\n",
    "        elif(targetlen<0): targetlen=abs(targetlen)\n",
    "        # check if new length is between mindepth and maxdepth\n",
    "        if(targetlen < self.mindepth): targetlen = self.mindepth\n",
    "        elif(targetlen > self.maxdepth): targetlen = self.maxdepth\n",
    "        # new minimum length is min of minlen and targetlen\n",
    "        if(targetlen < minlen): newminlen=targetlen\n",
    "        if(debug): print(f'M1 : New Min Len :{newminlen}, Length Mutation :{targetlen}')\n",
    "        #    \n",
    "        # B. Mutating the # of neurons\n",
    "        # As lengths of x, x1, xs[0], xs[1] and new length can possibly be different, \n",
    "        # 1) do the mutation for # of neurons for new minlen, \n",
    "        # 2) apply the same rule to remaining if needed\n",
    "        # xa = np.zeros((targetlen),dtype=int)\n",
    "        # Mutating the number of neurons up to min len layers\n",
    "        xa = x[:newminlen] + beta * (x1[:newminlen] - x[:newminlen]) + beta * (xs[0][:newminlen] - xs[1][:newminlen]) # mutate on node with minlen\n",
    "        # Mutating the number of neurons for the rest layers\n",
    "        if(targetlen>minlen):\n",
    "            xaa = np.zeros((targetlen-minlen))\n",
    "            a,b,c,d=None,None,None,None\n",
    "            for i in range(targetlen-newminlen): # if number of neurons missing in vector, generate random from range (min)\n",
    "                if(x.shape[0]<=newminlen+i): a=np.random.choice(range(self.minneuron,self.maxneuron),1,replace=False)[0]\n",
    "                elif(x.shape[0]>newminlen+i): a=x[newminlen+i] \n",
    "                if(x1.shape[0]<=newminlen+i): b=np.random.choice(range(self.minneuron,self.maxneuron),1,replace=False)[0]\n",
    "                elif(x1.shape[0]>newminlen+i): b=x1[newminlen+i] \n",
    "                if(xs[0].shape[0]<=newminlen+i): c=np.random.choice(range(self.minneuron,self.maxneuron),1,replace=False)[0]\n",
    "                elif(xs[0].shape[0]>newminlen+i): c=xs[0][newminlen+i]  \n",
    "                if(xs[1].shape[0]<=newminlen+i): d=np.random.choice(range(self.minneuron,self.maxneuron),1,replace=False)[0]\n",
    "                elif(xs[1].shape[0]>newminlen+i): d=xs[1][newminlen+i]      \n",
    "                xaa[i] = a + beta * (b - a) + beta * (c - d)\n",
    "            xa = np.concatenate((xa, xaa), axis=None)\n",
    "        # check if numbers of neurons are in allowed range  \n",
    "        for i in range(xa.shape[0]):\n",
    "            if(xa[i]>self.maxneuron): xa[i]=self.maxneuron\n",
    "            elif(xa[i]<self.minneuron): xa[i]=self.minneuron\n",
    "            xa[i] = np.floor(xa[i])\n",
    "        xa = np.concatenate((np.array(indim,dtype=int),np.array(xa,dtype=int),np.array(self.outdim,dtype=int)), axis=None,dtype=int)\n",
    "        return xa\n",
    "    \n",
    "    def mutation_rand_1_z(self,x1,xs,beta,debug=False):\n",
    "        indim = x1[0]\n",
    "        x1 = x1[1:-1] # remove in/out dim\n",
    "        xs[0] = xs[0][1:-1]\n",
    "        xs[1] = xs[1][1:-1]\n",
    "        if(debug):\n",
    "            print(f'M1 : x1 len {x1.shape[0]} xs0 len {xs[0].shape[0]} xs1 len {xs[1].shape[0]}')\n",
    "            print(f'M1 : x1 {x1} \\nM1 : xs0 {xs[0]} \\nM1 : xs1 len {xs[1]}')\n",
    "        #\n",
    "        # A. Mutating the # of layers\n",
    "        minlen = np.min([x1.shape[0],xs[0].shape[0],xs[1].shape[0]])\n",
    "        if(debug): print(f'M1 : minlen {minlen}')          \n",
    "        newminlen = minlen\n",
    "        targetlen=int(np.floor((x1.shape[0]) + beta * (xs[0].shape[0] - xs[1].shape[0])))\n",
    "        # check the sign of targetlen: if the new length == 0 , set it back to target len , if <0 , take abs\n",
    "        if(targetlen==0): targetlen=x1.shape[0]\n",
    "        elif(targetlen<0): targetlen=abs(targetlen)\n",
    "        # check if new length is between mindepth and maxdepth\n",
    "        if(targetlen < self.mindepth): targetlen = self.mindepth\n",
    "        elif(targetlen > self.maxdepth): targetlen = self.maxdepth\n",
    "        # new minimum length is min of minlen and targetlen\n",
    "        if(targetlen < minlen): newminlen=targetlen\n",
    "        if(debug): print(f'M1 : New Min Len :{newminlen}, Length Mutation :{targetlen}')\n",
    "        #    \n",
    "        # B. Mutating the # of neurons\n",
    "        # As lengths of x1, xs[0], xs[1] and new length can possibly be different, \n",
    "        # 1) do the mutation for # of neurons for new minlen, \n",
    "        # 2) apply the same rule to remaining if needed\n",
    "        # xa = np.zeros((targetlen),dtype=int)\n",
    "        # Mutating the number of neurons up to min len layers\n",
    "        xa = x1[:newminlen] + beta * (xs[0][:newminlen] - xs[1][:newminlen]) # mutate on node with minlen\n",
    "        # Mutating the number of neurons for the rest layers\n",
    "        if(targetlen>minlen):\n",
    "            xaa = np.zeros((targetlen-minlen))\n",
    "            a,b,c=None,None,None\n",
    "            for i in range(targetlen-newminlen): # if number of neurons missing in vector, generate random from range (min)\n",
    "                if(x1.shape[0]<=newminlen+i): a=np.random.choice(range(self.minneuron,self.maxneuron),1,replace=False)[0]\n",
    "                elif(x1.shape[0]>newminlen+i): a=x1[newminlen+i] \n",
    "                if(xs[0].shape[0]<=newminlen+i): b=np.random.choice(range(self.minneuron,self.maxneuron),1,replace=False)[0]\n",
    "                elif(xs[0].shape[0]>newminlen+i): b=xs[0][newminlen+i]  \n",
    "                if(xs[1].shape[0]<=newminlen+i): c=np.random.choice(range(self.minneuron,self.maxneuron),1,replace=False)[0]\n",
    "                elif(xs[1].shape[0]>newminlen+i): c=xs[1][newminlen+i]      \n",
    "                xaa[i]=a + beta * (b - c)\n",
    "            xa = np.concatenate((xa, xaa), axis=None)\n",
    "        # check if numbers of neurons are in allowed range  \n",
    "        for i in range(xa.shape[0]):\n",
    "            if(xa[i]>self.maxneuron): xa[i]=self.maxneuron\n",
    "            elif(xa[i]<self.minneuron): xa[i]=self.minneuron\n",
    "            xa[i] = np.floor(xa[i])\n",
    "        xa = np.concatenate((np.array(indim,dtype=int),np.array(xa,dtype=int),np.array(self.outdim,dtype=int)), axis=None,dtype=int)\n",
    "        return xa\n",
    "    \n",
    "    def crossoverMean(self,parent,u):\n",
    "        order = [parent[1:-1],u[1:-1]]\n",
    "        if(parent.shape[0] > u.shape[0]): order = [u[1:-1],parent[1:-1]]\n",
    "        order[0] = np.resize(order[0],order[1].shape[0])\n",
    "        middle = np.mean(order,axis=0,dtype=int)\n",
    "        child=np.insert(middle,0,parent[0])\n",
    "        child=np.append(child,parent[-1])\n",
    "        return child.copy()\n",
    "    \n",
    "    def crossoverRandomSwap(self,parent,u):\n",
    "        # the first one is with min len\n",
    "        order = [parent[1:-1],u[1:-1]]\n",
    "        child = [parent[0]]\n",
    "        if(parent.shape[0] > u.shape[0]): order = [u[1:-1],parent[1:-1]]\n",
    "        order[0] = np.resize(order[0],order[1].shape[0])\n",
    "        swap = np.random.randint(0,2,order[0].shape[0])\n",
    "        for i in range(len(swap)):\n",
    "            if(swap[i]==0): child.append(order[0][i])\n",
    "            else: child.append(order[1][i])\n",
    "        child.append(parent[-1])\n",
    "        return np.array(child).copy()\n",
    "    \n",
    "    def run(self,beta=0.5,p=0.2):\n",
    "        current_gen=self.MLPlayerlist\n",
    "        scores = np.zeros((self.pplSize))\n",
    "        #initial Run\n",
    "        print('Initial Run Start')\n",
    "        for i in range(len(current_gen)):\n",
    "            b,_,_ = self.fit(current_gen[i],i)\n",
    "            scores[i]=b\n",
    "        print('Initial Run End')\n",
    "        currentbest = np.min(scores)\n",
    "        currentmean = np.mean(scores)\n",
    "        currentbestidx = np.argmin(scores)\n",
    "        print(f'Init Run Best: {currentbest}, Mean: {currentmean}, ID:{currentbestidx}, config: {current_gen[currentbestidx]}')\n",
    "        #Generation Run\n",
    "        for i in range(self.maxiter):\n",
    "            structureStatistic=np.zeros((self.pplSize,5))\n",
    "            updatecount=0\n",
    "            start=time.time()\n",
    "            print(f'Gen {i} Run Start')\n",
    "            betas = np.ones(self.pplSize)*beta\n",
    "            for j in range(self.pplSize):\n",
    "                parent = current_gen[j]\n",
    "                # factors\n",
    "                betas[j] = self.self_adaptive_beta(betas[j])\n",
    "                # mutation\n",
    "                tidx = self.find_pbest(scores,p)\n",
    "                idx1,idx2 = np.array(np.random.choice(np.delete(np.arange(self.pplSize),tidx),2,replace=False),dtype=int)\n",
    "                target = current_gen[tidx]\n",
    "                diff = [current_gen[idx1],current_gen[idx2]]\n",
    "                unitvector = self.mutation_pbest_1_z(parent,target,diff,betas[j])\n",
    "                # crossover\n",
    "                if(self.crossover==1): nextGen = self.crossoverMean(parent,unitvector)\n",
    "                else: nextGen = self.crossoverRandomSwap(parent,unitvector)\n",
    "                print(f'Next Gen: {nextGen}')\n",
    "                structureStatistic[j,0]= nextGen.shape[0]-2\n",
    "                structureStatistic[j,1]= np.mean(nextGen[1:-1])\n",
    "                structureStatistic[j,2]= np.median(nextGen[1:-1])\n",
    "                structureStatistic[j,3]= np.quantile(nextGen[1:-1],0.25)\n",
    "                structureStatistic[j,4]= np.quantile(nextGen[1:-1],0.75)\n",
    "                # selection\n",
    "                s,_,_ = self.fit(nextGen,j)\n",
    "                if(s<scores[j]):\n",
    "                    updatecount+=1\n",
    "                    scores[j]=s\n",
    "                    current_gen[j]=nextGen\n",
    "            print(f'Gen {i} Run End')\n",
    "            end=time.time()\n",
    "            currentbest = np.min(scores)\n",
    "            currentmean = np.mean(scores)\n",
    "            currentmedian = np.median(scores)\n",
    "            currentq25 = np.quantile(scores,0.25)\n",
    "            currentq75 = np.quantile(scores,0.75)\n",
    "            currentbestidx = np.argmin(scores)\n",
    "            genMeanLen = np.mean(structureStatistic[:,0])\n",
    "            genMedianLen = np.median(structureStatistic[:,0])\n",
    "            genq25Len = np.quantile(structureStatistic[:,0],0.25)\n",
    "            genq75Len = np.quantile(structureStatistic[:,0],0.75)\n",
    "            genMeanNode=np.median(structureStatistic[:,1])\n",
    "            genMedianNode=np.median(structureStatistic[:,2])\n",
    "            genq25Node = np.median(structureStatistic[:,3])\n",
    "            genq75Node = np.median(structureStatistic[:,4])\n",
    "            print(f'Run {i:3d} Best: {currentbest}, Mean: {currentmean}, ID:{currentbestidx}, config: {current_gen[currentbestidx]}, updatecount: {updatecount:3d}, Generation RunTime: {(end-start):10.8f}')\n",
    "            self.tb.add_scalars(\"Scores Statistic (Generation)\", {'best':currentbest,'mean':currentmean,'median':currentmedian,'q25':currentq25,'q75':currentq75}, i)\n",
    "            self.tb.add_scalars(\"Structure Statistic (Generation) #HiddenLayer\", {'mean':genMeanLen,'median':genMedianLen,'q25':genq25Len,'q75':genq75Len}, i)\n",
    "            self.tb.add_scalars(\"Structure Statistic (Generation) #Node\", {'mean':genMeanNode,'median':genMedianNode,'q25':genq25Node,'q75':genq75Node}, i)\n",
    "            self.tb.add_scalar('Update Count',updatecount,i)\n",
    "            self.tb.add_scalar('RunTime',(end-start),i)\n",
    "        print(f'Run Completed : Best Score(loss): {np.min(scores)} , Config: {current_gen[np.argmin(scores)]}')    \n",
    "        return \n",
    "                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "a332b483-a48e-46f8-bc94-b4f36144eb2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "trainingt = torch.nn.functional.one_hot(mnist_trainset.targets,num_classes=10)\n",
    "validationt = torch.nn.functional.one_hot(mnist_testset.targets,num_classes=10)\n",
    "# (self, outdim=1,maxdepth=70,mindepth=5,minneuron=4,maxneuron=10,bsize=10,epoch=100,initSize=20,maxiter=10,stopcount=3,\\\n",
    "#       trainingset=None,validationset=None,trainingTarget=None,validateTarget=None,crossover=1)\n",
    "d = DE_MLP(outdim=10,maxdepth=10,initSize=5,crossover=0,trainingset=mnist_trainset.data, validationset=mnist_testset.data, trainingTarget=trainingt,validateTarget=validationt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7b02b92e-097f-4204-9639-c8a195e64ce3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial Run Start\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/hk/kbn1q_sj4jz4lh0m7x05vff80000gn/T/ipykernel_2471/945589960.py:67: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
      "  data = torch.tensor(self.training[idx]).float().to(self.device)\n",
      "/var/folders/hk/kbn1q_sj4jz4lh0m7x05vff80000gn/T/ipykernel_2471/945589960.py:68: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
      "  y = torch.tensor(self.target[idx]).float().to(self.device)\n",
      "/var/folders/hk/kbn1q_sj4jz4lh0m7x05vff80000gn/T/ipykernel_2471/945589960.py:80: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
      "  vdata = torch.tensor(self.validationSet[vidx]).float().to(self.device)\n",
      "/var/folders/hk/kbn1q_sj4jz4lh0m7x05vff80000gn/T/ipykernel_2471/945589960.py:81: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
      "  vy = torch.tensor(self.validationTarget[vidx]).float().to(self.device)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ConfigID:   0, Epoch:   0, Training Loss: 0.26548752, Validation Loss: 0.22508589,                    Best: 0.22508589, StopCount/Limit:   0/  3, Time:16.04523802\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.21390484, Validation Loss: 0.21305794,                    Best: 0.21305794, StopCount/Limit:   0/  3, Time:14.25134397\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.20356261, Validation Loss: 0.20502630,                    Best: 0.20502630, StopCount/Limit:   0/  3, Time:11.36912608\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.19705425, Validation Loss: 0.19979869,                    Best: 0.19979869, StopCount/Limit:   0/  3, Time:12.42194700\n",
      "ConfigID:   0, Epoch:   4, Training Loss: 0.19220925, Validation Loss: 0.19697886,                    Best: 0.19697886, StopCount/Limit:   0/  3, Time:12.31149006\n",
      "ConfigID:   0, Epoch:   5, Training Loss: 0.18997798, Validation Loss: 0.19159269,                    Best: 0.19159269, StopCount/Limit:   0/  3, Time:17.22137690\n",
      "ConfigID:   0, Epoch:   6, Training Loss: 0.18745206, Validation Loss: 0.19400360,                    Best: 0.19159269, StopCount/Limit:   1/  3, Time:23.44436002\n",
      "ConfigID:   0, Epoch:   7, Training Loss: 0.18520337, Validation Loss: 0.20274613,                    Best: 0.19159269, StopCount/Limit:   2/  3, Time:16.34391332\n",
      "ConfigID:   0, Epoch:   8, Training Loss: 0.18395354, Validation Loss: 0.19266840,                    Best: 0.19159269, StopCount/Limit:   3/  3, Time:14.74536991\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.19667298, Validation Loss: 0.14211524,                    Best: 0.14211524, StopCount/Limit:   0/  3, Time:14.48708391\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.13513276, Validation Loss: 0.12299410,                    Best: 0.12299410, StopCount/Limit:   0/  3, Time:14.77143693\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.12313569, Validation Loss: 0.11995061,                    Best: 0.11995061, StopCount/Limit:   0/  3, Time:14.65109897\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.11450522, Validation Loss: 0.11057225,                    Best: 0.11057225, StopCount/Limit:   0/  3, Time:14.44012094\n",
      "ConfigID:   1, Epoch:   4, Training Loss: 0.10828502, Validation Loss: 0.10763642,                    Best: 0.10763642, StopCount/Limit:   0/  3, Time:14.17508507\n",
      "ConfigID:   1, Epoch:   5, Training Loss: 0.10535559, Validation Loss: 0.10540617,                    Best: 0.10540617, StopCount/Limit:   0/  3, Time:14.46028996\n",
      "ConfigID:   1, Epoch:   6, Training Loss: 0.10239472, Validation Loss: 0.10041376,                    Best: 0.10041376, StopCount/Limit:   0/  3, Time:14.22702694\n",
      "ConfigID:   1, Epoch:   7, Training Loss: 0.09986652, Validation Loss: 0.09678808,                    Best: 0.09678808, StopCount/Limit:   0/  3, Time:12.94389009\n",
      "ConfigID:   1, Epoch:   8, Training Loss: 0.09743088, Validation Loss: 0.09375128,                    Best: 0.09375128, StopCount/Limit:   0/  3, Time:11.66813397\n",
      "ConfigID:   1, Epoch:   9, Training Loss: 0.09551387, Validation Loss: 0.09623337,                    Best: 0.09375128, StopCount/Limit:   1/  3, Time:11.38996482\n",
      "ConfigID:   1, Epoch:  10, Training Loss: 0.09416247, Validation Loss: 0.09446442,                    Best: 0.09375128, StopCount/Limit:   2/  3, Time:11.31054378\n",
      "ConfigID:   1, Epoch:  11, Training Loss: 0.09234693, Validation Loss: 0.09177512,                    Best: 0.09177512, StopCount/Limit:   2/  3, Time:12.17317104\n",
      "ConfigID:   1, Epoch:  12, Training Loss: 0.09139566, Validation Loss: 0.09235386,                    Best: 0.09177512, StopCount/Limit:   3/  3, Time:14.28940701\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.26177576, Validation Loss: 0.19149815,                    Best: 0.19149815, StopCount/Limit:   0/  3, Time:15.84155130\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.17523886, Validation Loss: 0.16034203,                    Best: 0.16034203, StopCount/Limit:   0/  3, Time:20.94975376\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.15693216, Validation Loss: 0.15339493,                    Best: 0.15339493, StopCount/Limit:   0/  3, Time:16.48345304\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.14501397, Validation Loss: 0.13646729,                    Best: 0.13646729, StopCount/Limit:   0/  3, Time:14.02302003\n",
      "ConfigID:   2, Epoch:   4, Training Loss: 0.13048856, Validation Loss: 0.12195972,                    Best: 0.12195972, StopCount/Limit:   0/  3, Time:14.46482491\n",
      "ConfigID:   2, Epoch:   5, Training Loss: 0.12235435, Validation Loss: 0.11840798,                    Best: 0.11840798, StopCount/Limit:   0/  3, Time:13.03017592\n",
      "ConfigID:   2, Epoch:   6, Training Loss: 0.11939681, Validation Loss: 0.11561914,                    Best: 0.11561914, StopCount/Limit:   0/  3, Time:24.39964604\n",
      "ConfigID:   2, Epoch:   7, Training Loss: 0.11424610, Validation Loss: 0.11190814,                    Best: 0.11190814, StopCount/Limit:   0/  3, Time:20.14233112\n",
      "ConfigID:   2, Epoch:   8, Training Loss: 0.11214817, Validation Loss: 0.11299920,                    Best: 0.11190814, StopCount/Limit:   1/  3, Time:11.75072002\n",
      "ConfigID:   2, Epoch:   9, Training Loss: 0.11095451, Validation Loss: 0.10988978,                    Best: 0.10988978, StopCount/Limit:   1/  3, Time:14.28107214\n",
      "ConfigID:   2, Epoch:  10, Training Loss: 0.11065261, Validation Loss: 0.11227842,                    Best: 0.10988978, StopCount/Limit:   2/  3, Time:12.72721505\n",
      "ConfigID:   2, Epoch:  11, Training Loss: 0.10816283, Validation Loss: 0.11183120,                    Best: 0.10988978, StopCount/Limit:   3/  3, Time:12.97593093\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.24336599, Validation Loss: 0.17801854,                    Best: 0.17801854, StopCount/Limit:   0/  3, Time:9.97338295\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.13009213, Validation Loss: 0.09938999,                    Best: 0.09938999, StopCount/Limit:   0/  3, Time:10.81709385\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.09611028, Validation Loss: 0.08825254,                    Best: 0.08825254, StopCount/Limit:   0/  3, Time:9.57052493\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.08473411, Validation Loss: 0.08118752,                    Best: 0.08118752, StopCount/Limit:   0/  3, Time:9.07795501\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.07688209, Validation Loss: 0.07454890,                    Best: 0.07454890, StopCount/Limit:   0/  3, Time:8.54687381\n",
      "ConfigID:   3, Epoch:   5, Training Loss: 0.07181358, Validation Loss: 0.06777256,                    Best: 0.06777256, StopCount/Limit:   0/  3, Time:8.67709780\n",
      "ConfigID:   3, Epoch:   6, Training Loss: 0.06842831, Validation Loss: 0.06721568,                    Best: 0.06721568, StopCount/Limit:   0/  3, Time:7.64186215\n",
      "ConfigID:   3, Epoch:   7, Training Loss: 0.06599349, Validation Loss: 0.07018189,                    Best: 0.06721568, StopCount/Limit:   1/  3, Time:7.58768082\n",
      "ConfigID:   3, Epoch:   8, Training Loss: 0.06385817, Validation Loss: 0.06339007,                    Best: 0.06339007, StopCount/Limit:   1/  3, Time:9.24984097\n",
      "ConfigID:   3, Epoch:   9, Training Loss: 0.06354924, Validation Loss: 0.06169653,                    Best: 0.06169653, StopCount/Limit:   1/  3, Time:9.91449094\n",
      "ConfigID:   3, Epoch:  10, Training Loss: 0.06228192, Validation Loss: 0.06393584,                    Best: 0.06169653, StopCount/Limit:   2/  3, Time:10.88360691\n",
      "ConfigID:   3, Epoch:  11, Training Loss: 0.06196603, Validation Loss: 0.06394329,                    Best: 0.06169653, StopCount/Limit:   3/  3, Time:12.94468188\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.24328751, Validation Loss: 0.18078180,                    Best: 0.18078180, StopCount/Limit:   0/  3, Time:12.17563605\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.14687249, Validation Loss: 0.12227243,                    Best: 0.12227243, StopCount/Limit:   0/  3, Time:13.35358906\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.11588660, Validation Loss: 0.10861221,                    Best: 0.10861221, StopCount/Limit:   0/  3, Time:13.06758785\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.11387162, Validation Loss: 0.13162211,                    Best: 0.10861221, StopCount/Limit:   1/  3, Time:12.30852604\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.11707645, Validation Loss: 0.13156799,                    Best: 0.10861221, StopCount/Limit:   2/  3, Time:13.26149082\n",
      "ConfigID:   4, Epoch:   5, Training Loss: 0.11309991, Validation Loss: 0.10833367,                    Best: 0.10833367, StopCount/Limit:   2/  3, Time:13.67154002\n",
      "ConfigID:   4, Epoch:   6, Training Loss: 0.10940526, Validation Loss: 0.10643538,                    Best: 0.10643538, StopCount/Limit:   2/  3, Time:12.98795533\n",
      "ConfigID:   4, Epoch:   7, Training Loss: 0.10549845, Validation Loss: 0.10306935,                    Best: 0.10306935, StopCount/Limit:   2/  3, Time:13.30094194\n",
      "ConfigID:   4, Epoch:   8, Training Loss: 0.10373435, Validation Loss: 0.10096120,                    Best: 0.10096120, StopCount/Limit:   2/  3, Time:15.73974490\n",
      "ConfigID:   4, Epoch:   9, Training Loss: 0.10362712, Validation Loss: 0.10293656,                    Best: 0.10096120, StopCount/Limit:   3/  3, Time:15.71611595\n",
      "Initial Run End\n",
      "Init Run Best: 0.06169652631925419, Mean: 0.11118306348398328, ID:3, config: [784   9   9   4   7   6  10]\n",
      "Gen 0 Run Start\n",
      "3 2\n",
      "[784   9   9   4   7   6  10] [784   9   9   5   7   8   5   7   9   9  10]\n",
      "Next Gen: [784   8   9   9   4   8   8   6  10]\n",
      "ConfigID:   0, Epoch:   0, Training Loss: 0.32618508, Validation Loss: 0.28716786,                    Best: 0.28716786, StopCount/Limit:   0/  3, Time:13.47354484\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.27112600, Validation Loss: 0.25869661,                    Best: 0.25869661, StopCount/Limit:   0/  3, Time:11.13168502\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.25146239, Validation Loss: 0.24616217,                    Best: 0.24616217, StopCount/Limit:   0/  3, Time:13.62694788\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.24557553, Validation Loss: 0.24419941,                    Best: 0.24419941, StopCount/Limit:   0/  3, Time:16.87880707\n",
      "ConfigID:   0, Epoch:   4, Training Loss: 0.24408775, Validation Loss: 0.24306376,                    Best: 0.24306376, StopCount/Limit:   0/  3, Time:13.93204904\n",
      "ConfigID:   0, Epoch:   5, Training Loss: 0.24359139, Validation Loss: 0.24339598,                    Best: 0.24306376, StopCount/Limit:   1/  3, Time:9.57402301\n",
      "ConfigID:   0, Epoch:   6, Training Loss: 0.24250627, Validation Loss: 0.24236309,                    Best: 0.24236309, StopCount/Limit:   1/  3, Time:8.65653706\n",
      "ConfigID:   0, Epoch:   7, Training Loss: 0.24196226, Validation Loss: 0.24300517,                    Best: 0.24236309, StopCount/Limit:   2/  3, Time:8.43510890\n",
      "ConfigID:   0, Epoch:   8, Training Loss: 0.24197484, Validation Loss: 0.24250755,                    Best: 0.24236309, StopCount/Limit:   3/  3, Time:8.32343292\n",
      "1 3\n",
      "[784   8   8   4   8   9   8   6   9  10] [784   9   9   4   7   6  10]\n",
      "Next Gen: [784   8   8   4   8  10   7   6   9   8   8  10]\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.25542441, Validation Loss: 0.20748640,                    Best: 0.20748640, StopCount/Limit:   0/  3, Time:10.37080908\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.19674689, Validation Loss: 0.18879067,                    Best: 0.18879067, StopCount/Limit:   0/  3, Time:10.37564206\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.18328939, Validation Loss: 0.17910826,                    Best: 0.17910826, StopCount/Limit:   0/  3, Time:10.33546281\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.17124676, Validation Loss: 0.16952858,                    Best: 0.16952858, StopCount/Limit:   0/  3, Time:10.32075977\n",
      "ConfigID:   1, Epoch:   4, Training Loss: 0.16687878, Validation Loss: 0.17015388,                    Best: 0.16952858, StopCount/Limit:   1/  3, Time:10.33366394\n",
      "ConfigID:   1, Epoch:   5, Training Loss: 0.16372219, Validation Loss: 0.17033124,                    Best: 0.16952858, StopCount/Limit:   2/  3, Time:10.43389297\n",
      "ConfigID:   1, Epoch:   6, Training Loss: 0.16210099, Validation Loss: 0.16232014,                    Best: 0.16232014, StopCount/Limit:   2/  3, Time:10.22370195\n",
      "ConfigID:   1, Epoch:   7, Training Loss: 0.16082627, Validation Loss: 0.16873135,                    Best: 0.16232014, StopCount/Limit:   3/  3, Time:10.32169795\n",
      "2 1\n",
      "[784   9   9   5   7   8   5   7   9   9  10] [784   8   8   4   8   9   8   6   9  10]\n",
      "Next Gen: [784   9   9   7   5   7   5   7   9   9  10]\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.21464719, Validation Loss: 0.14998455,                    Best: 0.14998455, StopCount/Limit:   0/  3, Time:9.66061783\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.14331682, Validation Loss: 0.12854990,                    Best: 0.12854990, StopCount/Limit:   0/  3, Time:9.60488009\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.12683461, Validation Loss: 0.11453839,                    Best: 0.11453839, StopCount/Limit:   0/  3, Time:9.73338532\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.11474031, Validation Loss: 0.10400887,                    Best: 0.10400887, StopCount/Limit:   0/  3, Time:10.08626413\n",
      "ConfigID:   2, Epoch:   4, Training Loss: 0.10284878, Validation Loss: 0.10570664,                    Best: 0.10400887, StopCount/Limit:   1/  3, Time:9.97666407\n",
      "ConfigID:   2, Epoch:   5, Training Loss: 0.09588036, Validation Loss: 0.08911860,                    Best: 0.08911860, StopCount/Limit:   1/  3, Time:9.73241496\n",
      "ConfigID:   2, Epoch:   6, Training Loss: 0.09172472, Validation Loss: 0.09027200,                    Best: 0.08911860, StopCount/Limit:   2/  3, Time:9.74274206\n",
      "ConfigID:   2, Epoch:   7, Training Loss: 0.08743704, Validation Loss: 0.08490438,                    Best: 0.08490438, StopCount/Limit:   2/  3, Time:9.72230411\n",
      "ConfigID:   2, Epoch:   8, Training Loss: 0.08420825, Validation Loss: 0.08013122,                    Best: 0.08013122, StopCount/Limit:   2/  3, Time:9.54555988\n",
      "ConfigID:   2, Epoch:   9, Training Loss: 0.08278101, Validation Loss: 0.08120740,                    Best: 0.08013122, StopCount/Limit:   3/  3, Time:9.52584076\n",
      "4 2\n",
      "[784   8   5   9   5   6   7   7   5  10] [784   9   9   7   5   7   5   7   9   9  10]\n",
      "Next Gen: [784   9   9   7   5   6  10]\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.20800691, Validation Loss: 0.15187066,                    Best: 0.15187066, StopCount/Limit:   0/  3, Time:6.78870106\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.12165717, Validation Loss: 0.10773110,                    Best: 0.10773110, StopCount/Limit:   0/  3, Time:6.70330691\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.09727064, Validation Loss: 0.08586107,                    Best: 0.08586107, StopCount/Limit:   0/  3, Time:6.95505500\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.07919809, Validation Loss: 0.07737856,                    Best: 0.07737856, StopCount/Limit:   0/  3, Time:6.65597630\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.07187041, Validation Loss: 0.07892781,                    Best: 0.07737856, StopCount/Limit:   1/  3, Time:6.78611875\n",
      "ConfigID:   3, Epoch:   5, Training Loss: 0.06700954, Validation Loss: 0.06688681,                    Best: 0.06688681, StopCount/Limit:   1/  3, Time:6.67129278\n",
      "ConfigID:   3, Epoch:   6, Training Loss: 0.06325768, Validation Loss: 0.06917004,                    Best: 0.06688681, StopCount/Limit:   2/  3, Time:6.65120912\n",
      "ConfigID:   3, Epoch:   7, Training Loss: 0.06165275, Validation Loss: 0.06649698,                    Best: 0.06649698, StopCount/Limit:   2/  3, Time:6.71560192\n",
      "ConfigID:   3, Epoch:   8, Training Loss: 0.06003984, Validation Loss: 0.06551991,                    Best: 0.06551991, StopCount/Limit:   2/  3, Time:6.69387579\n",
      "ConfigID:   3, Epoch:   9, Training Loss: 0.05900513, Validation Loss: 0.06324354,                    Best: 0.06324354, StopCount/Limit:   2/  3, Time:6.71098900\n",
      "ConfigID:   3, Epoch:  10, Training Loss: 0.05826501, Validation Loss: 0.06275229,                    Best: 0.06275229, StopCount/Limit:   2/  3, Time:6.68036175\n",
      "ConfigID:   3, Epoch:  11, Training Loss: 0.05725118, Validation Loss: 0.05999148,                    Best: 0.05999148, StopCount/Limit:   2/  3, Time:6.78095627\n",
      "ConfigID:   3, Epoch:  12, Training Loss: 0.05649229, Validation Loss: 0.06401525,                    Best: 0.05999148, StopCount/Limit:   3/  3, Time:8.96890712\n",
      "3 1\n",
      "[784   9   9   7   5   6  10] [784   8   8   4   8   9   8   6   9  10]\n",
      "Next Gen: [784   8   5  10   5   4   6   7   5  10]\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.26483621, Validation Loss: 0.21722787,                    Best: 0.21722787, StopCount/Limit:   0/  3, Time:12.07845497\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.20510469, Validation Loss: 0.19465349,                    Best: 0.19465349, StopCount/Limit:   0/  3, Time:9.93102407\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.18751771, Validation Loss: 0.17887538,                    Best: 0.17887538, StopCount/Limit:   0/  3, Time:9.74766302\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.17524260, Validation Loss: 0.17473230,                    Best: 0.17473230, StopCount/Limit:   0/  3, Time:10.10653687\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.16864181, Validation Loss: 0.16602927,                    Best: 0.16602927, StopCount/Limit:   0/  3, Time:9.61960697\n",
      "ConfigID:   4, Epoch:   5, Training Loss: 0.16238639, Validation Loss: 0.16117564,                    Best: 0.16117564, StopCount/Limit:   0/  3, Time:10.31773686\n",
      "ConfigID:   4, Epoch:   6, Training Loss: 0.15967580, Validation Loss: 0.16191090,                    Best: 0.16117564, StopCount/Limit:   1/  3, Time:10.46512413\n",
      "ConfigID:   4, Epoch:   7, Training Loss: 0.16080852, Validation Loss: 0.15561546,                    Best: 0.15561546, StopCount/Limit:   1/  3, Time:10.02711201\n",
      "ConfigID:   4, Epoch:   8, Training Loss: 0.15197551, Validation Loss: 0.15672277,                    Best: 0.15561546, StopCount/Limit:   2/  3, Time:10.08598995\n",
      "ConfigID:   4, Epoch:   9, Training Loss: 0.15277781, Validation Loss: 0.15980441,                    Best: 0.15561546, StopCount/Limit:   3/  3, Time:10.00809598\n",
      "Gen 0 Run End\n",
      "Run   0 Best: 0.05999148314609192, Mean: 0.10489034322663211, ID:3, config: [784   9   9   7   5   6  10], updatecount:   2, Generation RunTime: 476.28511810\n",
      "Gen 1 Run Start\n",
      "2 0\n",
      "[784   9   9   7   5   7   5   7   9   9  10] [784   8   9   9   4   8   8   6  10]\n",
      "Next Gen: [784   8   7   8   5   6   8   6   8  10]\n",
      "ConfigID:   0, Epoch:   0, Training Loss: 0.33449289, Validation Loss: 0.32522667,                    Best: 0.32522667, StopCount/Limit:   0/  3, Time:16.23372602\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.32517559, Validation Loss: 0.32533859,                    Best: 0.32522667, StopCount/Limit:   1/  3, Time:10.50721622\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.32517705, Validation Loss: 0.32516096,                    Best: 0.32516096, StopCount/Limit:   1/  3, Time:10.15604711\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.32514948, Validation Loss: 0.32502328,                    Best: 0.32502328, StopCount/Limit:   1/  3, Time:10.02938104\n",
      "ConfigID:   0, Epoch:   4, Training Loss: 0.32514287, Validation Loss: 0.32508018,                    Best: 0.32502328, StopCount/Limit:   2/  3, Time:10.63239479\n",
      "ConfigID:   0, Epoch:   5, Training Loss: 0.32513185, Validation Loss: 0.32496258,                    Best: 0.32496258, StopCount/Limit:   2/  3, Time:10.17094707\n",
      "ConfigID:   0, Epoch:   6, Training Loss: 0.32509211, Validation Loss: 0.32513612,                    Best: 0.32496258, StopCount/Limit:   3/  3, Time:10.12912273\n",
      "3 4\n",
      "[784   9   9   7   5   6  10] [784   8   5   9   5   6   7   7   5  10]\n",
      "Next Gen: [784   8  10   4   6   9   8   6   9  10]\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.22803693, Validation Loss: 0.17140858,                    Best: 0.17140858, StopCount/Limit:   0/  3, Time:10.08471990\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.15443075, Validation Loss: 0.14987198,                    Best: 0.14987198, StopCount/Limit:   0/  3, Time:10.07520390\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.12283358, Validation Loss: 0.10541329,                    Best: 0.10541329, StopCount/Limit:   0/  3, Time:9.98142838\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.09684721, Validation Loss: 0.08791849,                    Best: 0.08791849, StopCount/Limit:   0/  3, Time:13.29468393\n",
      "ConfigID:   1, Epoch:   4, Training Loss: 0.08629981, Validation Loss: 0.08318099,                    Best: 0.08318099, StopCount/Limit:   0/  3, Time:15.07328892\n",
      "ConfigID:   1, Epoch:   5, Training Loss: 0.08125500, Validation Loss: 0.08037900,                    Best: 0.08037900, StopCount/Limit:   0/  3, Time:12.44789815\n",
      "ConfigID:   1, Epoch:   6, Training Loss: 0.07857400, Validation Loss: 0.07823326,                    Best: 0.07823326, StopCount/Limit:   0/  3, Time:11.71638918\n",
      "ConfigID:   1, Epoch:   7, Training Loss: 0.07636344, Validation Loss: 0.08035387,                    Best: 0.07823326, StopCount/Limit:   1/  3, Time:11.33047795\n",
      "ConfigID:   1, Epoch:   8, Training Loss: 0.07497345, Validation Loss: 0.07536361,                    Best: 0.07536361, StopCount/Limit:   1/  3, Time:10.80555201\n",
      "ConfigID:   1, Epoch:   9, Training Loss: 0.07417141, Validation Loss: 0.07810029,                    Best: 0.07536361, StopCount/Limit:   2/  3, Time:10.65382290\n",
      "ConfigID:   1, Epoch:  10, Training Loss: 0.07261356, Validation Loss: 0.07277403,                    Best: 0.07277403, StopCount/Limit:   2/  3, Time:11.10662699\n",
      "ConfigID:   1, Epoch:  11, Training Loss: 0.07161980, Validation Loss: 0.07237226,                    Best: 0.07237226, StopCount/Limit:   2/  3, Time:11.23343801\n",
      "ConfigID:   1, Epoch:  12, Training Loss: 0.07160919, Validation Loss: 0.07404197,                    Best: 0.07237226, StopCount/Limit:   3/  3, Time:10.69181490\n",
      "2 3\n",
      "[784   9   9   7   5   7   5   7   9   9  10] [784   9   9   7   5   6  10]\n",
      "Next Gen: [784   8   7   8   5   7   6   7   8   7   9  10]\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.28872884, Validation Loss: 0.23135027,                    Best: 0.23135027, StopCount/Limit:   0/  3, Time:12.12299395\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.21655278, Validation Loss: 0.20588439,                    Best: 0.20588439, StopCount/Limit:   0/  3, Time:12.17275810\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.18553433, Validation Loss: 0.16637247,                    Best: 0.16637247, StopCount/Limit:   0/  3, Time:12.85989904\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.14770440, Validation Loss: 0.13085810,                    Best: 0.13085810, StopCount/Limit:   0/  3, Time:12.03160405\n",
      "ConfigID:   2, Epoch:   4, Training Loss: 0.12641868, Validation Loss: 0.11533850,                    Best: 0.11533850, StopCount/Limit:   0/  3, Time:12.62673593\n",
      "ConfigID:   2, Epoch:   5, Training Loss: 0.11867913, Validation Loss: 0.11516684,                    Best: 0.11516684, StopCount/Limit:   0/  3, Time:21.02947569\n",
      "ConfigID:   2, Epoch:   6, Training Loss: 0.11543499, Validation Loss: 0.11245586,                    Best: 0.11245586, StopCount/Limit:   0/  3, Time:15.89837790\n",
      "ConfigID:   2, Epoch:   7, Training Loss: 0.11262591, Validation Loss: 0.10963415,                    Best: 0.10963415, StopCount/Limit:   0/  3, Time:15.46205091\n",
      "ConfigID:   2, Epoch:   8, Training Loss: 0.11090430, Validation Loss: 0.10566184,                    Best: 0.10566184, StopCount/Limit:   0/  3, Time:14.25408292\n",
      "ConfigID:   2, Epoch:   9, Training Loss: 0.11234037, Validation Loss: 0.10648366,                    Best: 0.10566184, StopCount/Limit:   1/  3, Time:14.69811463\n",
      "ConfigID:   2, Epoch:  10, Training Loss: 0.10809848, Validation Loss: 0.10640723,                    Best: 0.10566184, StopCount/Limit:   2/  3, Time:17.27048779\n",
      "ConfigID:   2, Epoch:  11, Training Loss: 0.10629017, Validation Loss: 0.10911791,                    Best: 0.10566184, StopCount/Limit:   3/  3, Time:19.52020192\n",
      "2 1\n",
      "[784   9   9   7   5   7   5   7   9   9  10] [784   8  10   4   6   9   8   6   9  10]\n",
      "Next Gen: [784   9   9   7   4   6   9   6  10]\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.25681622, Validation Loss: 0.16811659,                    Best: 0.16811659, StopCount/Limit:   0/  3, Time:12.20928097\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.14493146, Validation Loss: 0.13336271,                    Best: 0.13336271, StopCount/Limit:   0/  3, Time:15.15406489\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.12505629, Validation Loss: 0.12012232,                    Best: 0.12012232, StopCount/Limit:   0/  3, Time:13.57642627\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.11336790, Validation Loss: 0.10991679,                    Best: 0.10991679, StopCount/Limit:   0/  3, Time:12.20758200\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.10731394, Validation Loss: 0.10747084,                    Best: 0.10747084, StopCount/Limit:   0/  3, Time:15.85427213\n",
      "ConfigID:   3, Epoch:   5, Training Loss: 0.10369360, Validation Loss: 0.10802125,                    Best: 0.10747084, StopCount/Limit:   1/  3, Time:13.70650601\n",
      "ConfigID:   3, Epoch:   6, Training Loss: 0.10112364, Validation Loss: 0.10936854,                    Best: 0.10747084, StopCount/Limit:   2/  3, Time:12.91813517\n",
      "ConfigID:   3, Epoch:   7, Training Loss: 0.09908582, Validation Loss: 0.09850996,                    Best: 0.09850996, StopCount/Limit:   2/  3, Time:10.42697191\n",
      "ConfigID:   3, Epoch:   8, Training Loss: 0.09641367, Validation Loss: 0.09935104,                    Best: 0.09850996, StopCount/Limit:   3/  3, Time:14.63140512\n",
      "2 3\n",
      "[784   9   9   7   5   7   5   7   9   9  10] [784   9   9   7   5   6  10]\n",
      "Next Gen: [784   8   5   9   5   6   6   8   5   6   5  10]\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.33483237, Validation Loss: 0.32500776,                    Best: 0.32500776, StopCount/Limit:   0/  3, Time:18.19163704\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.32506839, Validation Loss: 0.32501062,                    Best: 0.32500776, StopCount/Limit:   1/  3, Time:23.56287313\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.32507308, Validation Loss: 0.32500087,                    Best: 0.32500087, StopCount/Limit:   1/  3, Time:13.31613994\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.32507014, Validation Loss: 0.32501089,                    Best: 0.32500087, StopCount/Limit:   2/  3, Time:13.84111929\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.32504273, Validation Loss: 0.32504251,                    Best: 0.32500087, StopCount/Limit:   3/  3, Time:13.62816715\n",
      "Gen 1 Run End\n",
      "Run   1 Best: 0.05999148314609192, Mean: 0.10100977094830015, ID:3, config: [784   9   9   7   5   6  10], updatecount:   1, Generation RunTime: 609.58508706\n",
      "Gen 2 Run Start\n",
      "3 4\n",
      "[784   9   9   7   5   6  10] [784   8   5   9   5   6   7   7   5  10]\n",
      "Next Gen: [784   8   9   9   4   8   8  10  10]\n",
      "ConfigID:   0, Epoch:   0, Training Loss: 0.15586113, Validation Loss: 0.09786578,                    Best: 0.09786578, StopCount/Limit:   0/  3, Time:10.41069198\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.08774842, Validation Loss: 0.07664967,                    Best: 0.07664967, StopCount/Limit:   0/  3, Time:11.50018787\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.07736507, Validation Loss: 0.07519214,                    Best: 0.07519214, StopCount/Limit:   0/  3, Time:12.66747475\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.07334669, Validation Loss: 0.07193281,                    Best: 0.07193281, StopCount/Limit:   0/  3, Time:13.58882308\n",
      "ConfigID:   0, Epoch:   4, Training Loss: 0.07052114, Validation Loss: 0.06992359,                    Best: 0.06992359, StopCount/Limit:   0/  3, Time:10.25597477\n",
      "ConfigID:   0, Epoch:   5, Training Loss: 0.06810350, Validation Loss: 0.06599685,                    Best: 0.06599685, StopCount/Limit:   0/  3, Time:12.55079579\n",
      "ConfigID:   0, Epoch:   6, Training Loss: 0.06769756, Validation Loss: 0.06858133,                    Best: 0.06599685, StopCount/Limit:   1/  3, Time:11.33063698\n",
      "ConfigID:   0, Epoch:   7, Training Loss: 0.06651218, Validation Loss: 0.06850828,                    Best: 0.06599685, StopCount/Limit:   2/  3, Time:10.96512318\n",
      "ConfigID:   0, Epoch:   8, Training Loss: 0.06615443, Validation Loss: 0.06514970,                    Best: 0.06514970, StopCount/Limit:   2/  3, Time:11.88320518\n",
      "ConfigID:   0, Epoch:   9, Training Loss: 0.06489111, Validation Loss: 0.06628424,                    Best: 0.06514970, StopCount/Limit:   3/  3, Time:10.36692309\n",
      "4 3\n",
      "[784   8   5   9   5   6   7   7   5  10] [784   9   9   7   5   6  10]\n",
      "Next Gen: [784   8   7   4   6   9   8   7   9   6   6  10]\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.33609742, Validation Loss: 0.32501868,                    Best: 0.32501868, StopCount/Limit:   0/  3, Time:15.61992908\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.32508711, Validation Loss: 0.32502943,                    Best: 0.32501868, StopCount/Limit:   1/  3, Time:14.18953013\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.32507389, Validation Loss: 0.32502989,                    Best: 0.32501868, StopCount/Limit:   2/  3, Time:13.92898488\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.32509671, Validation Loss: 0.32502530,                    Best: 0.32501868, StopCount/Limit:   3/  3, Time:15.11444092\n",
      "2 0\n",
      "[784   9   9   7   5   7   5   7   9   9  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   9   5   7   5   5   5   7   9   9  10]\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.24843422, Validation Loss: 0.19244699,                    Best: 0.19244699, StopCount/Limit:   0/  3, Time:13.13531590\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.16555563, Validation Loss: 0.14803048,                    Best: 0.14803048, StopCount/Limit:   0/  3, Time:14.48413801\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.13299365, Validation Loss: 0.11962706,                    Best: 0.11962706, StopCount/Limit:   0/  3, Time:14.79737592\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.11543664, Validation Loss: 0.10960891,                    Best: 0.10960891, StopCount/Limit:   0/  3, Time:13.91931319\n",
      "ConfigID:   2, Epoch:   4, Training Loss: 0.10996770, Validation Loss: 0.10536383,                    Best: 0.10536383, StopCount/Limit:   0/  3, Time:14.96053243\n",
      "ConfigID:   2, Epoch:   5, Training Loss: 0.10632435, Validation Loss: 0.10702753,                    Best: 0.10536383, StopCount/Limit:   1/  3, Time:13.76671290\n",
      "ConfigID:   2, Epoch:   6, Training Loss: 0.10516024, Validation Loss: 0.10843352,                    Best: 0.10536383, StopCount/Limit:   2/  3, Time:13.33687925\n",
      "ConfigID:   2, Epoch:   7, Training Loss: 0.10394329, Validation Loss: 0.10225098,                    Best: 0.10225098, StopCount/Limit:   2/  3, Time:13.05169678\n",
      "ConfigID:   2, Epoch:   8, Training Loss: 0.10377641, Validation Loss: 0.10375390,                    Best: 0.10225098, StopCount/Limit:   3/  3, Time:13.57702231\n",
      "3 1\n",
      "[784   9   9   7   5   6  10] [784   8  10   4   6   9   8   6   9  10]\n",
      "Next Gen: [784   9   6   9   4   4  10]\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.28601845, Validation Loss: 0.21033923,                    Best: 0.21033923, StopCount/Limit:   0/  3, Time:9.56615186\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.19890415, Validation Loss: 0.19003447,                    Best: 0.19003447, StopCount/Limit:   0/  3, Time:8.81175017\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.18380955, Validation Loss: 0.18041799,                    Best: 0.18041799, StopCount/Limit:   0/  3, Time:9.54174185\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.17252610, Validation Loss: 0.17539491,                    Best: 0.17539491, StopCount/Limit:   0/  3, Time:9.94516706\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.16514508, Validation Loss: 0.17189385,                    Best: 0.17189385, StopCount/Limit:   0/  3, Time:9.75234628\n",
      "ConfigID:   3, Epoch:   5, Training Loss: 0.15802307, Validation Loss: 0.16713525,                    Best: 0.16713525, StopCount/Limit:   0/  3, Time:9.75602889\n",
      "ConfigID:   3, Epoch:   6, Training Loss: 0.15249999, Validation Loss: 0.17343213,                    Best: 0.16713525, StopCount/Limit:   1/  3, Time:10.12233496\n",
      "ConfigID:   3, Epoch:   7, Training Loss: 0.14893806, Validation Loss: 0.16900924,                    Best: 0.16713525, StopCount/Limit:   2/  3, Time:9.36654377\n",
      "ConfigID:   3, Epoch:   8, Training Loss: 0.14696939, Validation Loss: 0.15392041,                    Best: 0.15392041, StopCount/Limit:   2/  3, Time:8.23510814\n",
      "ConfigID:   3, Epoch:   9, Training Loss: 0.14359834, Validation Loss: 0.15686523,                    Best: 0.15392041, StopCount/Limit:   3/  3, Time:9.65658092\n",
      "1 0\n",
      "[784   8  10   4   6   9   8   6   9  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   8   5   9   6   6   7   5   5  10]\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.24393909, Validation Loss: 0.20167253,                    Best: 0.20167253, StopCount/Limit:   0/  3, Time:11.69158387\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.16910589, Validation Loss: 0.14035310,                    Best: 0.14035310, StopCount/Limit:   0/  3, Time:12.58940792\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.13294948, Validation Loss: 0.12499495,                    Best: 0.12499495, StopCount/Limit:   0/  3, Time:14.16703725\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.11974025, Validation Loss: 0.12093385,                    Best: 0.12093385, StopCount/Limit:   0/  3, Time:14.31075406\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.11486369, Validation Loss: 0.10930292,                    Best: 0.10930292, StopCount/Limit:   0/  3, Time:12.88348436\n",
      "ConfigID:   4, Epoch:   5, Training Loss: 0.11119278, Validation Loss: 0.10748665,                    Best: 0.10748665, StopCount/Limit:   0/  3, Time:12.18233705\n",
      "ConfigID:   4, Epoch:   6, Training Loss: 0.10714911, Validation Loss: 0.11272250,                    Best: 0.10748665, StopCount/Limit:   1/  3, Time:12.10015702\n",
      "ConfigID:   4, Epoch:   7, Training Loss: 0.10171279, Validation Loss: 0.09790472,                    Best: 0.09790472, StopCount/Limit:   1/  3, Time:11.82577586\n",
      "ConfigID:   4, Epoch:   8, Training Loss: 0.09733675, Validation Loss: 0.09533416,                    Best: 0.09533416, StopCount/Limit:   1/  3, Time:15.45075488\n",
      "ConfigID:   4, Epoch:   9, Training Loss: 0.09310611, Validation Loss: 0.09370171,                    Best: 0.09370171, StopCount/Limit:   1/  3, Time:13.81920004\n",
      "ConfigID:   4, Epoch:  10, Training Loss: 0.08923526, Validation Loss: 0.08666032,                    Best: 0.08666032, StopCount/Limit:   1/  3, Time:13.55569601\n",
      "ConfigID:   4, Epoch:  11, Training Loss: 0.08708167, Validation Loss: 0.08722419,                    Best: 0.08666032, StopCount/Limit:   2/  3, Time:12.89724112\n",
      "ConfigID:   4, Epoch:  12, Training Loss: 0.08536230, Validation Loss: 0.08443043,                    Best: 0.08443043, StopCount/Limit:   2/  3, Time:13.74194598\n",
      "ConfigID:   4, Epoch:  13, Training Loss: 0.08407324, Validation Loss: 0.08345720,                    Best: 0.08345720, StopCount/Limit:   2/  3, Time:12.47252393\n",
      "ConfigID:   4, Epoch:  14, Training Loss: 0.08342099, Validation Loss: 0.08483783,                    Best: 0.08345720, StopCount/Limit:   3/  3, Time:12.53704691\n",
      "Gen 2 Run End\n",
      "Run   2 Best: 0.05999148314609192, Mean: 0.07222037305166014, ID:3, config: [784   9   9   7   5   6  10], updatecount:   2, Generation RunTime: 590.44281483\n",
      "Gen 3 Run Start\n",
      "2 0\n",
      "[784   9   9   7   5   7   5   7   9   9  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   8   7   9   5   8   8  10   6  10]\n",
      "ConfigID:   0, Epoch:   0, Training Loss: 0.21248953, Validation Loss: 0.13688277,                    Best: 0.13688277, StopCount/Limit:   0/  3, Time:13.75873899\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.11870454, Validation Loss: 0.10583314,                    Best: 0.10583314, StopCount/Limit:   0/  3, Time:12.12901473\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.10471673, Validation Loss: 0.10250273,                    Best: 0.10250273, StopCount/Limit:   0/  3, Time:13.18862104\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.09923078, Validation Loss: 0.09919019,                    Best: 0.09919019, StopCount/Limit:   0/  3, Time:12.25455499\n",
      "ConfigID:   0, Epoch:   4, Training Loss: 0.09590192, Validation Loss: 0.09557318,                    Best: 0.09557318, StopCount/Limit:   0/  3, Time:12.95137024\n",
      "ConfigID:   0, Epoch:   5, Training Loss: 0.09299303, Validation Loss: 0.09129600,                    Best: 0.09129600, StopCount/Limit:   0/  3, Time:14.77252507\n",
      "ConfigID:   0, Epoch:   6, Training Loss: 0.09057616, Validation Loss: 0.08911795,                    Best: 0.08911795, StopCount/Limit:   0/  3, Time:17.98235488\n",
      "ConfigID:   0, Epoch:   7, Training Loss: 0.08781364, Validation Loss: 0.08874261,                    Best: 0.08874261, StopCount/Limit:   0/  3, Time:14.16743803\n",
      "ConfigID:   0, Epoch:   8, Training Loss: 0.08681656, Validation Loss: 0.08802095,                    Best: 0.08802095, StopCount/Limit:   0/  3, Time:13.25255394\n",
      "ConfigID:   0, Epoch:   9, Training Loss: 0.08559766, Validation Loss: 0.08602675,                    Best: 0.08602675, StopCount/Limit:   0/  3, Time:11.69265413\n",
      "ConfigID:   0, Epoch:  10, Training Loss: 0.08458512, Validation Loss: 0.08495807,                    Best: 0.08495807, StopCount/Limit:   0/  3, Time:12.25266981\n",
      "ConfigID:   0, Epoch:  11, Training Loss: 0.08420152, Validation Loss: 0.08539033,                    Best: 0.08495807, StopCount/Limit:   1/  3, Time:13.96448207\n",
      "ConfigID:   0, Epoch:  12, Training Loss: 0.08321417, Validation Loss: 0.09188616,                    Best: 0.08495807, StopCount/Limit:   2/  3, Time:13.94595623\n",
      "ConfigID:   0, Epoch:  13, Training Loss: 0.08274568, Validation Loss: 0.08393572,                    Best: 0.08393572, StopCount/Limit:   2/  3, Time:14.13076305\n",
      "ConfigID:   0, Epoch:  14, Training Loss: 0.08165623, Validation Loss: 0.08508508,                    Best: 0.08393572, StopCount/Limit:   3/  3, Time:12.73659897\n",
      "1 4\n",
      "[784   8  10   4   6   9   8   6   9  10] [784   8   5   9   6   6   7   5   5  10]\n",
      "Next Gen: [784   8  10   4   5   9   7   7   9  10]\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.26531743, Validation Loss: 0.17016112,                    Best: 0.17016112, StopCount/Limit:   0/  3, Time:12.95120406\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.14905459, Validation Loss: 0.13644260,                    Best: 0.13644260, StopCount/Limit:   0/  3, Time:10.96857715\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.13386418, Validation Loss: 0.12575679,                    Best: 0.12575679, StopCount/Limit:   0/  3, Time:10.79400110\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.12597210, Validation Loss: 0.12862353,                    Best: 0.12575679, StopCount/Limit:   1/  3, Time:11.95252013\n",
      "ConfigID:   1, Epoch:   4, Training Loss: 0.12057973, Validation Loss: 0.12088302,                    Best: 0.12088302, StopCount/Limit:   1/  3, Time:13.47948599\n",
      "ConfigID:   1, Epoch:   5, Training Loss: 0.11604115, Validation Loss: 0.11652806,                    Best: 0.11652806, StopCount/Limit:   1/  3, Time:13.47857714\n",
      "ConfigID:   1, Epoch:   6, Training Loss: 0.11296018, Validation Loss: 0.11151361,                    Best: 0.11151361, StopCount/Limit:   1/  3, Time:18.92484832\n",
      "ConfigID:   1, Epoch:   7, Training Loss: 0.11041921, Validation Loss: 0.10894415,                    Best: 0.10894415, StopCount/Limit:   1/  3, Time:15.77229095\n",
      "ConfigID:   1, Epoch:   8, Training Loss: 0.10888423, Validation Loss: 0.10777595,                    Best: 0.10777595, StopCount/Limit:   1/  3, Time:13.62818313\n",
      "ConfigID:   1, Epoch:   9, Training Loss: 0.10757475, Validation Loss: 0.10834427,                    Best: 0.10777595, StopCount/Limit:   2/  3, Time:12.11195803\n",
      "ConfigID:   1, Epoch:  10, Training Loss: 0.10643262, Validation Loss: 0.11017826,                    Best: 0.10777595, StopCount/Limit:   3/  3, Time:14.58350682\n",
      "4 3\n",
      "[784   8   5   9   6   6   7   5   5  10] [784   9   9   7   5   6  10]\n",
      "Next Gen: [784   9   9   7   5   7   4   5   7   8   9  10]\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.33664930, Validation Loss: 0.32496215,                    Best: 0.32496215, StopCount/Limit:   0/  3, Time:16.15147185\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.32511676, Validation Loss: 0.32498280,                    Best: 0.32496215, StopCount/Limit:   1/  3, Time:16.38696194\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.32510107, Validation Loss: 0.32500032,                    Best: 0.32496215, StopCount/Limit:   2/  3, Time:14.80075216\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.32511137, Validation Loss: 0.32504530,                    Best: 0.32496215, StopCount/Limit:   3/  3, Time:15.89545894\n",
      "2 0\n",
      "[784   9   9   7   5   7   5   7   9   9  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   9   7   7   6   5   4   4  10]\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.35607979, Validation Loss: 0.32496705,                    Best: 0.32496705, StopCount/Limit:   0/  3, Time:11.12056613\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.32499846, Validation Loss: 0.32495130,                    Best: 0.32495130, StopCount/Limit:   0/  3, Time:10.68746901\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.32497722, Validation Loss: 0.32504090,                    Best: 0.32495130, StopCount/Limit:   1/  3, Time:11.91739106\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.32499334, Validation Loss: 0.32497346,                    Best: 0.32495130, StopCount/Limit:   2/  3, Time:11.95744634\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.32498592, Validation Loss: 0.32500095,                    Best: 0.32495130, StopCount/Limit:   3/  3, Time:12.35937905\n",
      "3 1\n",
      "[784   9   9   7   5   6  10] [784   8  10   4   6   9   8   6   9  10]\n",
      "Next Gen: [784   8   4   9   6   5   6   4   8  10]\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.32175904, Validation Loss: 0.27031278,                    Best: 0.27031278, StopCount/Limit:   0/  3, Time:13.14253592\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.22824621, Validation Loss: 0.21157161,                    Best: 0.21157161, StopCount/Limit:   0/  3, Time:13.97276402\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.20754998, Validation Loss: 0.20165185,                    Best: 0.20165185, StopCount/Limit:   0/  3, Time:19.49470878\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.20221419, Validation Loss: 0.20006307,                    Best: 0.20006307, StopCount/Limit:   0/  3, Time:16.08977818\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.19660365, Validation Loss: 0.19416371,                    Best: 0.19416371, StopCount/Limit:   0/  3, Time:17.38618207\n",
      "ConfigID:   4, Epoch:   5, Training Loss: 0.19197858, Validation Loss: 0.18887535,                    Best: 0.18887535, StopCount/Limit:   0/  3, Time:23.55270600\n",
      "ConfigID:   4, Epoch:   6, Training Loss: 0.18872425, Validation Loss: 0.18846357,                    Best: 0.18846357, StopCount/Limit:   0/  3, Time:18.36879086\n",
      "ConfigID:   4, Epoch:   7, Training Loss: 0.18762308, Validation Loss: 0.18651576,                    Best: 0.18651576, StopCount/Limit:   0/  3, Time:13.97623920\n",
      "ConfigID:   4, Epoch:   8, Training Loss: 0.18459391, Validation Loss: 0.18514672,                    Best: 0.18514672, StopCount/Limit:   0/  3, Time:14.23442793\n",
      "ConfigID:   4, Epoch:   9, Training Loss: 0.17885370, Validation Loss: 0.17709304,                    Best: 0.17709304, StopCount/Limit:   0/  3, Time:13.46051812\n",
      "ConfigID:   4, Epoch:  10, Training Loss: 0.17365998, Validation Loss: 0.17342078,                    Best: 0.17342078, StopCount/Limit:   0/  3, Time:13.52720094\n",
      "ConfigID:   4, Epoch:  11, Training Loss: 0.17080146, Validation Loss: 0.18854924,                    Best: 0.17342078, StopCount/Limit:   1/  3, Time:19.94869995\n",
      "ConfigID:   4, Epoch:  12, Training Loss: 0.17329559, Validation Loss: 0.18012872,                    Best: 0.17342078, StopCount/Limit:   2/  3, Time:13.72486115\n",
      "ConfigID:   4, Epoch:  13, Training Loss: 0.17594077, Validation Loss: 0.17540406,                    Best: 0.17342078, StopCount/Limit:   3/  3, Time:15.34646106\n",
      "Gen 3 Run End\n",
      "Run   3 Best: 0.05999148314609192, Mean: 0.07222037305166014, ID:3, config: [784   9   9   7   5   6  10], updatecount:   0, Generation RunTime: 699.39085102\n",
      "Gen 4 Run Start\n",
      "4 3\n",
      "[784   8   5   9   6   6   7   5   5  10] [784   9   9   7   5   6  10]\n",
      "Next Gen: [784   8   9   9   4   8   8  10   8   7  10]\n",
      "ConfigID:   0, Epoch:   0, Training Loss: 0.28799292, Validation Loss: 0.23590517,                    Best: 0.23590517, StopCount/Limit:   0/  3, Time:21.13548183\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.23349370, Validation Loss: 0.23372534,                    Best: 0.23372534, StopCount/Limit:   0/  3, Time:16.30369091\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.23062720, Validation Loss: 0.22954739,                    Best: 0.22954739, StopCount/Limit:   0/  3, Time:16.10866117\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.22999052, Validation Loss: 0.23347881,                    Best: 0.22954739, StopCount/Limit:   1/  3, Time:18.68330216\n",
      "ConfigID:   0, Epoch:   4, Training Loss: 0.22764074, Validation Loss: 0.22786180,                    Best: 0.22786180, StopCount/Limit:   1/  3, Time:13.53559804\n",
      "ConfigID:   0, Epoch:   5, Training Loss: 0.22699282, Validation Loss: 0.22624834,                    Best: 0.22624834, StopCount/Limit:   1/  3, Time:21.33542109\n",
      "ConfigID:   0, Epoch:   6, Training Loss: 0.22627435, Validation Loss: 0.22989098,                    Best: 0.22624834, StopCount/Limit:   2/  3, Time:14.66752386\n",
      "ConfigID:   0, Epoch:   7, Training Loss: 0.22694863, Validation Loss: 0.22410279,                    Best: 0.22410279, StopCount/Limit:   2/  3, Time:16.80313802\n",
      "ConfigID:   0, Epoch:   8, Training Loss: 0.22228021, Validation Loss: 0.22324383,                    Best: 0.22324383, StopCount/Limit:   2/  3, Time:24.50190902\n",
      "ConfigID:   0, Epoch:   9, Training Loss: 0.22101545, Validation Loss: 0.22001594,                    Best: 0.22001594, StopCount/Limit:   2/  3, Time:20.16314507\n",
      "ConfigID:   0, Epoch:  10, Training Loss: 0.22083297, Validation Loss: 0.22123809,                    Best: 0.22001594, StopCount/Limit:   3/  3, Time:15.40356207\n",
      "3 0\n",
      "[784   9   9   7   5   6  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   8  10   4   6   7   8   4   9  10]\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.26208410, Validation Loss: 0.18393837,                    Best: 0.18393837, StopCount/Limit:   0/  3, Time:21.34572387\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.17329614, Validation Loss: 0.16676757,                    Best: 0.16676757, StopCount/Limit:   0/  3, Time:15.09479785\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.15223309, Validation Loss: 0.13663884,                    Best: 0.13663884, StopCount/Limit:   0/  3, Time:14.29221392\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.12743770, Validation Loss: 0.11818054,                    Best: 0.11818054, StopCount/Limit:   0/  3, Time:11.47563791\n",
      "ConfigID:   1, Epoch:   4, Training Loss: 0.11571333, Validation Loss: 0.11006786,                    Best: 0.11006786, StopCount/Limit:   0/  3, Time:13.61432409\n",
      "ConfigID:   1, Epoch:   5, Training Loss: 0.10706734, Validation Loss: 0.10792367,                    Best: 0.10792367, StopCount/Limit:   0/  3, Time:11.51171207\n",
      "ConfigID:   1, Epoch:   6, Training Loss: 0.10065310, Validation Loss: 0.10309174,                    Best: 0.10309174, StopCount/Limit:   0/  3, Time:10.73045826\n",
      "ConfigID:   1, Epoch:   7, Training Loss: 0.09810917, Validation Loss: 0.09546970,                    Best: 0.09546970, StopCount/Limit:   0/  3, Time:10.45121884\n",
      "ConfigID:   1, Epoch:   8, Training Loss: 0.09549802, Validation Loss: 0.09490743,                    Best: 0.09490743, StopCount/Limit:   0/  3, Time:10.48619103\n",
      "ConfigID:   1, Epoch:   9, Training Loss: 0.09412496, Validation Loss: 0.09165075,                    Best: 0.09165075, StopCount/Limit:   0/  3, Time:11.20348573\n",
      "ConfigID:   1, Epoch:  10, Training Loss: 0.09295906, Validation Loss: 0.09124862,                    Best: 0.09124862, StopCount/Limit:   0/  3, Time:11.87027216\n",
      "ConfigID:   1, Epoch:  11, Training Loss: 0.09237151, Validation Loss: 0.09150821,                    Best: 0.09124862, StopCount/Limit:   1/  3, Time:11.00321627\n",
      "ConfigID:   1, Epoch:  12, Training Loss: 0.09016113, Validation Loss: 0.08952846,                    Best: 0.08952846, StopCount/Limit:   1/  3, Time:11.40448689\n",
      "ConfigID:   1, Epoch:  13, Training Loss: 0.08921468, Validation Loss: 0.08894860,                    Best: 0.08894860, StopCount/Limit:   1/  3, Time:10.97364402\n",
      "ConfigID:   1, Epoch:  14, Training Loss: 0.08840288, Validation Loss: 0.08784841,                    Best: 0.08784841, StopCount/Limit:   1/  3, Time:10.99228382\n",
      "ConfigID:   1, Epoch:  15, Training Loss: 0.08814557, Validation Loss: 0.08873137,                    Best: 0.08784841, StopCount/Limit:   2/  3, Time:11.08161211\n",
      "ConfigID:   1, Epoch:  16, Training Loss: 0.08715695, Validation Loss: 0.08736267,                    Best: 0.08736267, StopCount/Limit:   2/  3, Time:11.60280490\n",
      "ConfigID:   1, Epoch:  17, Training Loss: 0.08761760, Validation Loss: 0.09332301,                    Best: 0.08736267, StopCount/Limit:   3/  3, Time:12.19559216\n",
      "1 0\n",
      "[784   8  10   4   6   9   8   6   9  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   9   9   4   5   7   5   5   9   8  10]\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.28350700, Validation Loss: 0.22934327,                    Best: 0.22934327, StopCount/Limit:   0/  3, Time:12.47440600\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.21733543, Validation Loss: 0.21159521,                    Best: 0.21159521, StopCount/Limit:   0/  3, Time:15.46102405\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.20295661, Validation Loss: 0.19415995,                    Best: 0.19415995, StopCount/Limit:   0/  3, Time:15.93732500\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.18490114, Validation Loss: 0.17768575,                    Best: 0.17768575, StopCount/Limit:   0/  3, Time:13.91205287\n",
      "ConfigID:   2, Epoch:   4, Training Loss: 0.16853428, Validation Loss: 0.16502407,                    Best: 0.16502407, StopCount/Limit:   0/  3, Time:13.05420709\n",
      "ConfigID:   2, Epoch:   5, Training Loss: 0.15380483, Validation Loss: 0.14720509,                    Best: 0.14720509, StopCount/Limit:   0/  3, Time:11.62433004\n",
      "ConfigID:   2, Epoch:   6, Training Loss: 0.14158026, Validation Loss: 0.14143236,                    Best: 0.14143236, StopCount/Limit:   0/  3, Time:12.20222211\n",
      "ConfigID:   2, Epoch:   7, Training Loss: 0.13775842, Validation Loss: 0.14251102,                    Best: 0.14143236, StopCount/Limit:   1/  3, Time:11.07874203\n",
      "ConfigID:   2, Epoch:   8, Training Loss: 0.13727351, Validation Loss: 0.13486719,                    Best: 0.13486719, StopCount/Limit:   1/  3, Time:11.98268509\n",
      "ConfigID:   2, Epoch:   9, Training Loss: 0.13562437, Validation Loss: 0.13924533,                    Best: 0.13486719, StopCount/Limit:   2/  3, Time:13.38988709\n",
      "ConfigID:   2, Epoch:  10, Training Loss: 0.13498010, Validation Loss: 0.14218295,                    Best: 0.13486719, StopCount/Limit:   3/  3, Time:14.16649580\n",
      "2 1\n",
      "[784   9   9   7   5   7   5   7   9   9  10] [784   8  10   4   6   9   8   6   9  10]\n",
      "Next Gen: [784   9   6   9   5   5   9   9  10]\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.19741144, Validation Loss: 0.15045334,                    Best: 0.15045334, StopCount/Limit:   0/  3, Time:10.12990212\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.12758259, Validation Loss: 0.10646749,                    Best: 0.10646749, StopCount/Limit:   0/  3, Time:9.35593987\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.10303051, Validation Loss: 0.09972216,                    Best: 0.09972216, StopCount/Limit:   0/  3, Time:9.41328311\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.09516396, Validation Loss: 0.09673469,                    Best: 0.09673469, StopCount/Limit:   0/  3, Time:9.37767386\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.09047862, Validation Loss: 0.08900048,                    Best: 0.08900048, StopCount/Limit:   0/  3, Time:9.37838626\n",
      "ConfigID:   3, Epoch:   5, Training Loss: 0.08850743, Validation Loss: 0.08691099,                    Best: 0.08691099, StopCount/Limit:   0/  3, Time:9.44211292\n",
      "ConfigID:   3, Epoch:   6, Training Loss: 0.08634909, Validation Loss: 0.09368623,                    Best: 0.08691099, StopCount/Limit:   1/  3, Time:9.31334996\n",
      "ConfigID:   3, Epoch:   7, Training Loss: 0.08378213, Validation Loss: 0.08393427,                    Best: 0.08393427, StopCount/Limit:   1/  3, Time:9.29674315\n",
      "ConfigID:   3, Epoch:   8, Training Loss: 0.08327395, Validation Loss: 0.08059160,                    Best: 0.08059160, StopCount/Limit:   1/  3, Time:9.32054996\n",
      "ConfigID:   3, Epoch:   9, Training Loss: 0.08200564, Validation Loss: 0.08148639,                    Best: 0.08059160, StopCount/Limit:   2/  3, Time:9.37045217\n",
      "ConfigID:   3, Epoch:  10, Training Loss: 0.08124470, Validation Loss: 0.07995233,                    Best: 0.07995233, StopCount/Limit:   2/  3, Time:9.44136405\n",
      "ConfigID:   3, Epoch:  11, Training Loss: 0.08010123, Validation Loss: 0.07906576,                    Best: 0.07906576, StopCount/Limit:   2/  3, Time:9.34206104\n",
      "ConfigID:   3, Epoch:  12, Training Loss: 0.07904328, Validation Loss: 0.07556651,                    Best: 0.07556651, StopCount/Limit:   2/  3, Time:9.46743703\n",
      "ConfigID:   3, Epoch:  13, Training Loss: 0.07887370, Validation Loss: 0.09220641,                    Best: 0.07556651, StopCount/Limit:   3/  3, Time:9.43355894\n",
      "3 4\n",
      "[784   9   9   7   5   6  10] [784   8   5   9   6   6   7   5   5  10]\n",
      "Next Gen: [784   8   9   7   5   6   7   6   5  10]\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.31925329, Validation Loss: 0.25268015,                    Best: 0.25268015, StopCount/Limit:   0/  3, Time:11.93688488\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.24284326, Validation Loss: 0.23837143,                    Best: 0.23837143, StopCount/Limit:   0/  3, Time:11.69091392\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.23264150, Validation Loss: 0.22906317,                    Best: 0.22906317, StopCount/Limit:   0/  3, Time:10.95883703\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.22418251, Validation Loss: 0.22140608,                    Best: 0.22140608, StopCount/Limit:   0/  3, Time:11.72904682\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.21799698, Validation Loss: 0.21934650,                    Best: 0.21934650, StopCount/Limit:   0/  3, Time:11.35549712\n",
      "ConfigID:   4, Epoch:   5, Training Loss: 0.21395160, Validation Loss: 0.22158441,                    Best: 0.21934650, StopCount/Limit:   1/  3, Time:10.82028580\n",
      "ConfigID:   4, Epoch:   6, Training Loss: 0.21562376, Validation Loss: 0.21765974,                    Best: 0.21765974, StopCount/Limit:   1/  3, Time:10.16650605\n",
      "ConfigID:   4, Epoch:   7, Training Loss: 0.21267117, Validation Loss: 0.22162703,                    Best: 0.21765974, StopCount/Limit:   2/  3, Time:10.09101224\n",
      "ConfigID:   4, Epoch:   8, Training Loss: 0.20926217, Validation Loss: 0.21311520,                    Best: 0.21311520, StopCount/Limit:   2/  3, Time:10.14748287\n",
      "ConfigID:   4, Epoch:   9, Training Loss: 0.20728457, Validation Loss: 0.21116301,                    Best: 0.21116301, StopCount/Limit:   2/  3, Time:10.10697484\n",
      "ConfigID:   4, Epoch:  10, Training Loss: 0.20513980, Validation Loss: 0.21019060,                    Best: 0.21019060, StopCount/Limit:   2/  3, Time:10.32994699\n",
      "ConfigID:   4, Epoch:  11, Training Loss: 0.20109471, Validation Loss: 0.20129794,                    Best: 0.20129794, StopCount/Limit:   2/  3, Time:10.30912614\n",
      "ConfigID:   4, Epoch:  12, Training Loss: 0.19445882, Validation Loss: 0.19698160,                    Best: 0.19698160, StopCount/Limit:   2/  3, Time:10.26513100\n",
      "ConfigID:   4, Epoch:  13, Training Loss: 0.18985978, Validation Loss: 0.19228475,                    Best: 0.19228475, StopCount/Limit:   2/  3, Time:10.18031597\n",
      "ConfigID:   4, Epoch:  14, Training Loss: 0.18581250, Validation Loss: 0.19196085,                    Best: 0.19196085, StopCount/Limit:   2/  3, Time:10.50084090\n",
      "ConfigID:   4, Epoch:  15, Training Loss: 0.18386804, Validation Loss: 0.19439457,                    Best: 0.19196085, StopCount/Limit:   3/  3, Time:10.12538600\n",
      "Gen 4 Run End\n",
      "Run   4 Best: 0.05999148314609192, Mean: 0.07222037305166014, ID:3, config: [784   9   9   7   5   6  10], updatecount:   0, Generation RunTime: 868.12599707\n",
      "Gen 5 Run Start\n",
      "0 4\n",
      "[784   8   9   9   4   8   8  10  10] [784   8   5   9   6   6   7   5   5  10]\n",
      "Next Gen: [784   8   9   8   4   8   8  10  10]\n",
      "ConfigID:   0, Epoch:   0, Training Loss: 0.33358632, Validation Loss: 0.32517897,                    Best: 0.32517897, StopCount/Limit:   0/  3, Time:9.10175323\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.32518899, Validation Loss: 0.32526913,                    Best: 0.32517897, StopCount/Limit:   1/  3, Time:9.17704797\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.32518099, Validation Loss: 0.32534766,                    Best: 0.32517897, StopCount/Limit:   2/  3, Time:9.27146387\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.32511816, Validation Loss: 0.32529659,                    Best: 0.32517897, StopCount/Limit:   3/  3, Time:9.21038413\n",
      "4 3\n",
      "[784   8   5   9   6   6   7   5   5  10] [784   9   9   7   5   6  10]\n",
      "Next Gen: [784   8  10   6   6   8   7   6   9   8   6  10]\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.28603936, Validation Loss: 0.25892541,                    Best: 0.25892541, StopCount/Limit:   0/  3, Time:11.53359389\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.22219909, Validation Loss: 0.20212648,                    Best: 0.20212648, StopCount/Limit:   0/  3, Time:11.46073294\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.16663839, Validation Loss: 0.14969091,                    Best: 0.14969091, StopCount/Limit:   0/  3, Time:11.41565108\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.14116976, Validation Loss: 0.13433903,                    Best: 0.13433903, StopCount/Limit:   0/  3, Time:11.74281693\n",
      "ConfigID:   1, Epoch:   4, Training Loss: 0.13284067, Validation Loss: 0.12825982,                    Best: 0.12825982, StopCount/Limit:   0/  3, Time:12.05266190\n",
      "ConfigID:   1, Epoch:   5, Training Loss: 0.12834568, Validation Loss: 0.13368474,                    Best: 0.12825982, StopCount/Limit:   1/  3, Time:11.57296300\n",
      "ConfigID:   1, Epoch:   6, Training Loss: 0.12492272, Validation Loss: 0.13201860,                    Best: 0.12825982, StopCount/Limit:   2/  3, Time:11.53100228\n",
      "ConfigID:   1, Epoch:   7, Training Loss: 0.12294886, Validation Loss: 0.12681513,                    Best: 0.12681513, StopCount/Limit:   2/  3, Time:11.59314203\n",
      "ConfigID:   1, Epoch:   8, Training Loss: 0.12008885, Validation Loss: 0.12229878,                    Best: 0.12229878, StopCount/Limit:   2/  3, Time:11.51412392\n",
      "ConfigID:   1, Epoch:   9, Training Loss: 0.11705755, Validation Loss: 0.11604834,                    Best: 0.11604834, StopCount/Limit:   2/  3, Time:11.54323888\n",
      "ConfigID:   1, Epoch:  10, Training Loss: 0.11268230, Validation Loss: 0.11425316,                    Best: 0.11425316, StopCount/Limit:   2/  3, Time:11.65642309\n",
      "ConfigID:   1, Epoch:  11, Training Loss: 0.10974932, Validation Loss: 0.11018319,                    Best: 0.11018319, StopCount/Limit:   2/  3, Time:11.60776210\n",
      "ConfigID:   1, Epoch:  12, Training Loss: 0.10662451, Validation Loss: 0.11281663,                    Best: 0.11018319, StopCount/Limit:   3/  3, Time:11.58608913\n",
      "3 4\n",
      "[784   9   9   7   5   6  10] [784   8   5   9   6   6   7   5   5  10]\n",
      "Next Gen: [784   9   9   7   5   7   5   6   9   9  10]\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.19188665, Validation Loss: 0.12538236,                    Best: 0.12538236, StopCount/Limit:   0/  3, Time:15.27797389\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.10357269, Validation Loss: 0.09256588,                    Best: 0.09256588, StopCount/Limit:   0/  3, Time:12.88535190\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.08577487, Validation Loss: 0.07835344,                    Best: 0.07835344, StopCount/Limit:   0/  3, Time:15.44988418\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.07801115, Validation Loss: 0.07229808,                    Best: 0.07229808, StopCount/Limit:   0/  3, Time:11.75715780\n",
      "ConfigID:   2, Epoch:   4, Training Loss: 0.07370488, Validation Loss: 0.07134496,                    Best: 0.07134496, StopCount/Limit:   0/  3, Time:11.09760213\n",
      "ConfigID:   2, Epoch:   5, Training Loss: 0.07018724, Validation Loss: 0.06858310,                    Best: 0.06858310, StopCount/Limit:   0/  3, Time:11.02357507\n",
      "ConfigID:   2, Epoch:   6, Training Loss: 0.06762096, Validation Loss: 0.06694639,                    Best: 0.06694639, StopCount/Limit:   0/  3, Time:10.98237109\n",
      "ConfigID:   2, Epoch:   7, Training Loss: 0.06548622, Validation Loss: 0.06547713,                    Best: 0.06547713, StopCount/Limit:   0/  3, Time:12.22582006\n",
      "ConfigID:   2, Epoch:   8, Training Loss: 0.06395053, Validation Loss: 0.06180235,                    Best: 0.06180235, StopCount/Limit:   0/  3, Time:14.00471306\n",
      "ConfigID:   2, Epoch:   9, Training Loss: 0.06208460, Validation Loss: 0.06780119,                    Best: 0.06180235, StopCount/Limit:   1/  3, Time:12.87481618\n",
      "ConfigID:   2, Epoch:  10, Training Loss: 0.06115076, Validation Loss: 0.05979080,                    Best: 0.05979080, StopCount/Limit:   1/  3, Time:12.70438123\n",
      "ConfigID:   2, Epoch:  11, Training Loss: 0.06009858, Validation Loss: 0.06948986,                    Best: 0.05979080, StopCount/Limit:   2/  3, Time:13.54001427\n",
      "ConfigID:   2, Epoch:  12, Training Loss: 0.05947867, Validation Loss: 0.06080585,                    Best: 0.05979080, StopCount/Limit:   3/  3, Time:13.11369801\n",
      "2 1\n",
      "[784   9   9   7   5   7   5   6   9   9  10] [784   8  10   4   6   9   8   6   9  10]\n",
      "Next Gen: [784   9   7   8   5   5   6  10]\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.22074130, Validation Loss: 0.17418681,                    Best: 0.17418681, StopCount/Limit:   0/  3, Time:10.76966190\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.15738463, Validation Loss: 0.14954267,                    Best: 0.14954267, StopCount/Limit:   0/  3, Time:10.30180931\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.13845791, Validation Loss: 0.13384778,                    Best: 0.13384778, StopCount/Limit:   0/  3, Time:10.63326383\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.12187207, Validation Loss: 0.12039465,                    Best: 0.12039465, StopCount/Limit:   0/  3, Time:10.71245408\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.11005394, Validation Loss: 0.10835689,                    Best: 0.10835689, StopCount/Limit:   0/  3, Time:10.61342525\n",
      "ConfigID:   3, Epoch:   5, Training Loss: 0.10185687, Validation Loss: 0.10355053,                    Best: 0.10355053, StopCount/Limit:   0/  3, Time:9.99660802\n",
      "ConfigID:   3, Epoch:   6, Training Loss: 0.09415499, Validation Loss: 0.09559374,                    Best: 0.09559374, StopCount/Limit:   0/  3, Time:8.13076925\n",
      "ConfigID:   3, Epoch:   7, Training Loss: 0.09097658, Validation Loss: 0.09407825,                    Best: 0.09407825, StopCount/Limit:   0/  3, Time:8.05066586\n",
      "ConfigID:   3, Epoch:   8, Training Loss: 0.08843960, Validation Loss: 0.09579795,                    Best: 0.09407825, StopCount/Limit:   1/  3, Time:7.95845795\n",
      "ConfigID:   3, Epoch:   9, Training Loss: 0.08702311, Validation Loss: 0.08860335,                    Best: 0.08860335, StopCount/Limit:   1/  3, Time:7.89505386\n",
      "ConfigID:   3, Epoch:  10, Training Loss: 0.08552700, Validation Loss: 0.08796575,                    Best: 0.08796575, StopCount/Limit:   1/  3, Time:8.02929878\n",
      "ConfigID:   3, Epoch:  11, Training Loss: 0.08423428, Validation Loss: 0.09283033,                    Best: 0.08796575, StopCount/Limit:   2/  3, Time:7.96750426\n",
      "ConfigID:   3, Epoch:  12, Training Loss: 0.08435833, Validation Loss: 0.08539827,                    Best: 0.08539827, StopCount/Limit:   2/  3, Time:8.03095388\n",
      "ConfigID:   3, Epoch:  13, Training Loss: 0.08329812, Validation Loss: 0.08797958,                    Best: 0.08539827, StopCount/Limit:   3/  3, Time:8.00708461\n",
      "3 0\n",
      "[784   9   9   7   5   6  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   8   5   5   6   6   7   5   5  10]\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.25334134, Validation Loss: 0.21589423,                    Best: 0.21589423, StopCount/Limit:   0/  3, Time:9.29729104\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.20051465, Validation Loss: 0.18231776,                    Best: 0.18231776, StopCount/Limit:   0/  3, Time:10.92988968\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.16912888, Validation Loss: 0.16364427,                    Best: 0.16364427, StopCount/Limit:   0/  3, Time:15.53099966\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.15837348, Validation Loss: 0.15787607,                    Best: 0.15787607, StopCount/Limit:   0/  3, Time:12.55230379\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.14816607, Validation Loss: 0.14414500,                    Best: 0.14414500, StopCount/Limit:   0/  3, Time:17.36711979\n",
      "ConfigID:   4, Epoch:   5, Training Loss: 0.13630240, Validation Loss: 0.13278788,                    Best: 0.13278788, StopCount/Limit:   0/  3, Time:11.04491901\n",
      "ConfigID:   4, Epoch:   6, Training Loss: 0.12792284, Validation Loss: 0.13423199,                    Best: 0.13278788, StopCount/Limit:   1/  3, Time:10.76063704\n",
      "ConfigID:   4, Epoch:   7, Training Loss: 0.11932060, Validation Loss: 0.12459760,                    Best: 0.12459760, StopCount/Limit:   1/  3, Time:11.04262304\n",
      "ConfigID:   4, Epoch:   8, Training Loss: 0.11473578, Validation Loss: 0.11611405,                    Best: 0.11611405, StopCount/Limit:   1/  3, Time:14.91549730\n",
      "ConfigID:   4, Epoch:   9, Training Loss: 0.11202931, Validation Loss: 0.11419896,                    Best: 0.11419896, StopCount/Limit:   1/  3, Time:13.71279931\n",
      "ConfigID:   4, Epoch:  10, Training Loss: 0.10976013, Validation Loss: 0.11220233,                    Best: 0.11220233, StopCount/Limit:   1/  3, Time:13.81595922\n",
      "ConfigID:   4, Epoch:  11, Training Loss: 0.10758821, Validation Loss: 0.11142674,                    Best: 0.11142674, StopCount/Limit:   1/  3, Time:13.49686193\n",
      "ConfigID:   4, Epoch:  12, Training Loss: 0.10661264, Validation Loss: 0.11064152,                    Best: 0.11064152, StopCount/Limit:   1/  3, Time:12.60327792\n",
      "ConfigID:   4, Epoch:  13, Training Loss: 0.10457018, Validation Loss: 0.10850919,                    Best: 0.10850919, StopCount/Limit:   1/  3, Time:10.83363414\n",
      "ConfigID:   4, Epoch:  14, Training Loss: 0.10397655, Validation Loss: 0.10858021,                    Best: 0.10850919, StopCount/Limit:   2/  3, Time:11.56471992\n",
      "ConfigID:   4, Epoch:  15, Training Loss: 0.10297371, Validation Loss: 0.11516803,                    Best: 0.10850919, StopCount/Limit:   3/  3, Time:10.53410506\n",
      "Gen 5 Run End\n",
      "Run   5 Best: 0.05979079821798951, Mean: 0.06815228878962808, ID:2, config: [784   9   9   7   5   7   5   6   9   9  10], updatecount:   1, Generation RunTime: 681.66576695\n",
      "Gen 6 Run Start\n",
      "1 2\n",
      "[784   8  10   4   6   9   8   6   9  10] [784   9   9   7   5   7   5   6   9   9  10]\n",
      "Next Gen: [784   8   9   9   4   8   8  10  10]\n",
      "ConfigID:   0, Epoch:   0, Training Loss: 0.33419369, Validation Loss: 0.32494691,                    Best: 0.32494691, StopCount/Limit:   0/  3, Time:10.44970274\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.32512692, Validation Loss: 0.32498508,                    Best: 0.32494691, StopCount/Limit:   1/  3, Time:9.61341214\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.32511979, Validation Loss: 0.32509863,                    Best: 0.32494691, StopCount/Limit:   2/  3, Time:9.14835978\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.32511169, Validation Loss: 0.32506110,                    Best: 0.32494691, StopCount/Limit:   3/  3, Time:10.76457095\n",
      "4 2\n",
      "[784   8   5   9   6   6   7   5   5  10] [784   9   9   7   5   7   5   6   9   9  10]\n",
      "Next Gen: [784   7  10   5   6   9   9   5   7  10]\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.29867980, Validation Loss: 0.22099834,                    Best: 0.22099834, StopCount/Limit:   0/  3, Time:10.80440879\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.20564287, Validation Loss: 0.19283696,                    Best: 0.19283696, StopCount/Limit:   0/  3, Time:10.94990516\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.18706621, Validation Loss: 0.17829703,                    Best: 0.17829703, StopCount/Limit:   0/  3, Time:10.38956094\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.17889720, Validation Loss: 0.16145804,                    Best: 0.16145804, StopCount/Limit:   0/  3, Time:11.17559195\n",
      "ConfigID:   1, Epoch:   4, Training Loss: 0.15730402, Validation Loss: 0.15211685,                    Best: 0.15211685, StopCount/Limit:   0/  3, Time:11.92716289\n",
      "ConfigID:   1, Epoch:   5, Training Loss: 0.14951135, Validation Loss: 0.15170796,                    Best: 0.15170796, StopCount/Limit:   0/  3, Time:11.30017686\n",
      "ConfigID:   1, Epoch:   6, Training Loss: 0.14064749, Validation Loss: 0.13685984,                    Best: 0.13685984, StopCount/Limit:   0/  3, Time:12.63327122\n",
      "ConfigID:   1, Epoch:   7, Training Loss: 0.13151775, Validation Loss: 0.12789534,                    Best: 0.12789534, StopCount/Limit:   0/  3, Time:10.90076399\n",
      "ConfigID:   1, Epoch:   8, Training Loss: 0.12693610, Validation Loss: 0.12808553,                    Best: 0.12789534, StopCount/Limit:   1/  3, Time:10.66186023\n",
      "ConfigID:   1, Epoch:   9, Training Loss: 0.12369515, Validation Loss: 0.12268446,                    Best: 0.12268446, StopCount/Limit:   1/  3, Time:9.51470494\n",
      "ConfigID:   1, Epoch:  10, Training Loss: 0.12006601, Validation Loss: 0.11836509,                    Best: 0.11836509, StopCount/Limit:   1/  3, Time:11.91776395\n",
      "ConfigID:   1, Epoch:  11, Training Loss: 0.11848707, Validation Loss: 0.12257481,                    Best: 0.11836509, StopCount/Limit:   2/  3, Time:9.68812728\n",
      "ConfigID:   1, Epoch:  12, Training Loss: 0.11803490, Validation Loss: 0.11638916,                    Best: 0.11638916, StopCount/Limit:   2/  3, Time:9.50244808\n",
      "ConfigID:   1, Epoch:  13, Training Loss: 0.11527499, Validation Loss: 0.11668507,                    Best: 0.11638916, StopCount/Limit:   3/  3, Time:9.87059712\n",
      "0 3\n",
      "[784   8   9   9   4   8   8  10  10] [784   9   9   7   5   6  10]\n",
      "Next Gen: [784   9   9   6   5   7   5   6   9   9  10]\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.25054675, Validation Loss: 0.17390712,                    Best: 0.17390712, StopCount/Limit:   0/  3, Time:10.08358717\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.13108888, Validation Loss: 0.10845513,                    Best: 0.10845513, StopCount/Limit:   0/  3, Time:10.48436689\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.10118645, Validation Loss: 0.09524960,                    Best: 0.09524960, StopCount/Limit:   0/  3, Time:10.14138579\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.09074400, Validation Loss: 0.08649459,                    Best: 0.08649459, StopCount/Limit:   0/  3, Time:10.06602311\n",
      "ConfigID:   2, Epoch:   4, Training Loss: 0.08518086, Validation Loss: 0.08334017,                    Best: 0.08334017, StopCount/Limit:   0/  3, Time:10.16405034\n",
      "ConfigID:   2, Epoch:   5, Training Loss: 0.08115923, Validation Loss: 0.08305555,                    Best: 0.08305555, StopCount/Limit:   0/  3, Time:10.07790971\n",
      "ConfigID:   2, Epoch:   6, Training Loss: 0.07780039, Validation Loss: 0.07522404,                    Best: 0.07522404, StopCount/Limit:   0/  3, Time:10.16575480\n",
      "ConfigID:   2, Epoch:   7, Training Loss: 0.07472110, Validation Loss: 0.07298038,                    Best: 0.07298038, StopCount/Limit:   0/  3, Time:10.06301689\n",
      "ConfigID:   2, Epoch:   8, Training Loss: 0.07126517, Validation Loss: 0.07055512,                    Best: 0.07055512, StopCount/Limit:   0/  3, Time:9.95817280\n",
      "ConfigID:   2, Epoch:   9, Training Loss: 0.06927534, Validation Loss: 0.06934783,                    Best: 0.06934783, StopCount/Limit:   0/  3, Time:10.17826891\n",
      "ConfigID:   2, Epoch:  10, Training Loss: 0.06782398, Validation Loss: 0.06603860,                    Best: 0.06603860, StopCount/Limit:   0/  3, Time:10.17579603\n",
      "ConfigID:   2, Epoch:  11, Training Loss: 0.06786062, Validation Loss: 0.06720921,                    Best: 0.06603860, StopCount/Limit:   1/  3, Time:10.13417602\n",
      "ConfigID:   2, Epoch:  12, Training Loss: 0.06560935, Validation Loss: 0.06942051,                    Best: 0.06603860, StopCount/Limit:   2/  3, Time:10.14492679\n",
      "ConfigID:   2, Epoch:  13, Training Loss: 0.06426414, Validation Loss: 0.06359151,                    Best: 0.06359151, StopCount/Limit:   2/  3, Time:10.22000480\n",
      "ConfigID:   2, Epoch:  14, Training Loss: 0.06314567, Validation Loss: 0.06749381,                    Best: 0.06359151, StopCount/Limit:   3/  3, Time:10.90294409\n",
      "3 0\n",
      "[784   9   9   7   5   6  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   9   9   4   6   6  10]\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.23026594, Validation Loss: 0.17009184,                    Best: 0.17009184, StopCount/Limit:   0/  3, Time:7.11738396\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.15852405, Validation Loss: 0.16459482,                    Best: 0.16459482, StopCount/Limit:   0/  3, Time:7.24124312\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.14766046, Validation Loss: 0.14552220,                    Best: 0.14552220, StopCount/Limit:   0/  3, Time:7.21506190\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.14150483, Validation Loss: 0.13665084,                    Best: 0.13665084, StopCount/Limit:   0/  3, Time:7.29521608\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.13586150, Validation Loss: 0.13404649,                    Best: 0.13404649, StopCount/Limit:   0/  3, Time:7.28402615\n",
      "ConfigID:   3, Epoch:   5, Training Loss: 0.13364595, Validation Loss: 0.13887029,                    Best: 0.13404649, StopCount/Limit:   1/  3, Time:7.72702813\n",
      "ConfigID:   3, Epoch:   6, Training Loss: 0.13156607, Validation Loss: 0.13233001,                    Best: 0.13233001, StopCount/Limit:   1/  3, Time:7.51123500\n",
      "ConfigID:   3, Epoch:   7, Training Loss: 0.13055071, Validation Loss: 0.13219978,                    Best: 0.13219978, StopCount/Limit:   1/  3, Time:7.14639592\n",
      "ConfigID:   3, Epoch:   8, Training Loss: 0.12942151, Validation Loss: 0.12960199,                    Best: 0.12960199, StopCount/Limit:   1/  3, Time:7.25267482\n",
      "ConfigID:   3, Epoch:   9, Training Loss: 0.12872145, Validation Loss: 0.13131718,                    Best: 0.12960199, StopCount/Limit:   2/  3, Time:7.07863498\n",
      "ConfigID:   3, Epoch:  10, Training Loss: 0.12812385, Validation Loss: 0.12978447,                    Best: 0.12960199, StopCount/Limit:   3/  3, Time:7.10073900\n",
      "3 0\n",
      "[784   9   9   7   5   6  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   8   5   9   6   6   5   5   8  10]\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.21972986, Validation Loss: 0.18784416,                    Best: 0.18784416, StopCount/Limit:   0/  3, Time:9.20860600\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.17877211, Validation Loss: 0.17304933,                    Best: 0.17304933, StopCount/Limit:   0/  3, Time:9.33111286\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.16499680, Validation Loss: 0.15419523,                    Best: 0.15419523, StopCount/Limit:   0/  3, Time:9.20918608\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.15549571, Validation Loss: 0.15464543,                    Best: 0.15419523, StopCount/Limit:   1/  3, Time:9.57438588\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.15088817, Validation Loss: 0.14972511,                    Best: 0.14972511, StopCount/Limit:   1/  3, Time:11.09310722\n",
      "ConfigID:   4, Epoch:   5, Training Loss: 0.14926627, Validation Loss: 0.14827265,                    Best: 0.14827265, StopCount/Limit:   1/  3, Time:9.75785398\n",
      "ConfigID:   4, Epoch:   6, Training Loss: 0.14736118, Validation Loss: 0.14779143,                    Best: 0.14779143, StopCount/Limit:   1/  3, Time:9.57165813\n",
      "ConfigID:   4, Epoch:   7, Training Loss: 0.14689970, Validation Loss: 0.14563290,                    Best: 0.14563290, StopCount/Limit:   1/  3, Time:9.40409493\n",
      "ConfigID:   4, Epoch:   8, Training Loss: 0.14509418, Validation Loss: 0.14471199,                    Best: 0.14471199, StopCount/Limit:   1/  3, Time:10.13916683\n",
      "ConfigID:   4, Epoch:   9, Training Loss: 0.14420125, Validation Loss: 0.14585240,                    Best: 0.14471199, StopCount/Limit:   2/  3, Time:9.86706185\n",
      "ConfigID:   4, Epoch:  10, Training Loss: 0.14379438, Validation Loss: 0.14433998,                    Best: 0.14433998, StopCount/Limit:   2/  3, Time:9.74568582\n",
      "ConfigID:   4, Epoch:  11, Training Loss: 0.14306668, Validation Loss: 0.14418481,                    Best: 0.14418481, StopCount/Limit:   2/  3, Time:10.37271118\n",
      "ConfigID:   4, Epoch:  12, Training Loss: 0.14234067, Validation Loss: 0.14224743,                    Best: 0.14224743, StopCount/Limit:   2/  3, Time:9.75021219\n",
      "ConfigID:   4, Epoch:  13, Training Loss: 0.14130450, Validation Loss: 0.14523738,                    Best: 0.14224743, StopCount/Limit:   3/  3, Time:9.76840806\n",
      "Gen 6 Run End\n",
      "Run   6 Best: 0.05979079821798951, Mean: 0.06815228878962808, ID:2, config: [784   9   9   7   5   7   5   6   9   9  10], updatecount:   0, Generation RunTime: 560.99361610\n",
      "Gen 7 Run Start\n",
      "0 3\n",
      "[784   8   9   9   4   8   8  10  10] [784   9   9   7   5   6  10]\n",
      "Next Gen: [784   8   7  10   4   8   8  10   7  10]\n",
      "ConfigID:   0, Epoch:   0, Training Loss: 0.25806172, Validation Loss: 0.20261559,                    Best: 0.20261559, StopCount/Limit:   0/  3, Time:9.64422774\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.19015695, Validation Loss: 0.18076025,                    Best: 0.18076025, StopCount/Limit:   0/  3, Time:9.94939590\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.17998305, Validation Loss: 0.17800194,                    Best: 0.17800194, StopCount/Limit:   0/  3, Time:9.93292379\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.17529526, Validation Loss: 0.17089787,                    Best: 0.17089787, StopCount/Limit:   0/  3, Time:9.84832621\n",
      "ConfigID:   0, Epoch:   4, Training Loss: 0.17125007, Validation Loss: 0.16812924,                    Best: 0.16812924, StopCount/Limit:   0/  3, Time:9.90725398\n",
      "ConfigID:   0, Epoch:   5, Training Loss: 0.16698862, Validation Loss: 0.16263130,                    Best: 0.16263130, StopCount/Limit:   0/  3, Time:9.82097292\n",
      "ConfigID:   0, Epoch:   6, Training Loss: 0.16292080, Validation Loss: 0.16161502,                    Best: 0.16161502, StopCount/Limit:   0/  3, Time:9.77154684\n",
      "ConfigID:   0, Epoch:   7, Training Loss: 0.16156914, Validation Loss: 0.15893422,                    Best: 0.15893422, StopCount/Limit:   0/  3, Time:9.63650513\n",
      "ConfigID:   0, Epoch:   8, Training Loss: 0.16085413, Validation Loss: 0.15954969,                    Best: 0.15893422, StopCount/Limit:   1/  3, Time:9.43623495\n",
      "ConfigID:   0, Epoch:   9, Training Loss: 0.15983606, Validation Loss: 0.16150394,                    Best: 0.15893422, StopCount/Limit:   2/  3, Time:9.62630987\n",
      "ConfigID:   0, Epoch:  10, Training Loss: 0.15907915, Validation Loss: 0.15785597,                    Best: 0.15785597, StopCount/Limit:   2/  3, Time:9.82604718\n",
      "ConfigID:   0, Epoch:  11, Training Loss: 0.15824849, Validation Loss: 0.15851523,                    Best: 0.15785597, StopCount/Limit:   3/  3, Time:9.60211205\n",
      "3 1\n",
      "[784   9   9   7   5   6  10] [784   8  10   4   6   9   8   6   9  10]\n",
      "Next Gen: [784   8   7   8   5   6   8   8   9  10]\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.18035073, Validation Loss: 0.11802962,                    Best: 0.11802962, StopCount/Limit:   0/  3, Time:9.44524312\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.10871342, Validation Loss: 0.09952273,                    Best: 0.09952273, StopCount/Limit:   0/  3, Time:9.53547502\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.09713488, Validation Loss: 0.09275356,                    Best: 0.09275356, StopCount/Limit:   0/  3, Time:9.48120236\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.09168989, Validation Loss: 0.08764074,                    Best: 0.08764074, StopCount/Limit:   0/  3, Time:9.49209809\n",
      "ConfigID:   1, Epoch:   4, Training Loss: 0.08951829, Validation Loss: 0.08825284,                    Best: 0.08764074, StopCount/Limit:   1/  3, Time:9.93692207\n",
      "ConfigID:   1, Epoch:   5, Training Loss: 0.08727900, Validation Loss: 0.09166154,                    Best: 0.08764074, StopCount/Limit:   2/  3, Time:9.81739521\n",
      "ConfigID:   1, Epoch:   6, Training Loss: 0.08569344, Validation Loss: 0.08510220,                    Best: 0.08510220, StopCount/Limit:   2/  3, Time:9.70691681\n",
      "ConfigID:   1, Epoch:   7, Training Loss: 0.08428318, Validation Loss: 0.08278685,                    Best: 0.08278685, StopCount/Limit:   2/  3, Time:9.76209688\n",
      "ConfigID:   1, Epoch:   8, Training Loss: 0.08310836, Validation Loss: 0.08373712,                    Best: 0.08278685, StopCount/Limit:   3/  3, Time:9.95550489\n",
      "4 0\n",
      "[784   8   5   9   6   6   7   5   5  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   9   9   7   5   7   6   6   9   7  10]\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.26973137, Validation Loss: 0.20163353,                    Best: 0.20163353, StopCount/Limit:   0/  3, Time:10.79984808\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.19076127, Validation Loss: 0.17582479,                    Best: 0.17582479, StopCount/Limit:   0/  3, Time:12.00253892\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.17867636, Validation Loss: 0.17525762,                    Best: 0.17525762, StopCount/Limit:   0/  3, Time:9.89377022\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.19282844, Validation Loss: 0.19479228,                    Best: 0.17525762, StopCount/Limit:   1/  3, Time:27.85161591\n",
      "ConfigID:   2, Epoch:   4, Training Loss: 0.18522718, Validation Loss: 0.18207784,                    Best: 0.17525762, StopCount/Limit:   2/  3, Time:8.39554811\n",
      "ConfigID:   2, Epoch:   5, Training Loss: 0.17508282, Validation Loss: 0.17550154,                    Best: 0.17525762, StopCount/Limit:   3/  3, Time:8.42409396\n",
      "0 1\n",
      "[784   8   9   9   4   8   8  10  10] [784   8  10   4   6   9   8   6   9  10]\n",
      "Next Gen: [784   9   6   7   5   5   9  10]\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.25012434, Validation Loss: 0.17665349,                    Best: 0.17665349, StopCount/Limit:   0/  3, Time:6.47230530\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.15231657, Validation Loss: 0.12157689,                    Best: 0.12157689, StopCount/Limit:   0/  3, Time:6.68152499\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.11404196, Validation Loss: 0.10402592,                    Best: 0.10402592, StopCount/Limit:   0/  3, Time:424.05756903\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.10491809, Validation Loss: 0.10080959,                    Best: 0.10080959, StopCount/Limit:   0/  3, Time:18.48633194\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.10147320, Validation Loss: 0.09791974,                    Best: 0.09791974, StopCount/Limit:   0/  3, Time:1357.32857227\n",
      "ConfigID:   3, Epoch:   5, Training Loss: 0.09875738, Validation Loss: 0.09626025,                    Best: 0.09626025, StopCount/Limit:   0/  3, Time:23.65850806\n",
      "ConfigID:   3, Epoch:   6, Training Loss: 0.09626556, Validation Loss: 0.09554175,                    Best: 0.09554175, StopCount/Limit:   0/  3, Time:30.81510091\n",
      "ConfigID:   3, Epoch:   7, Training Loss: 0.09546844, Validation Loss: 0.10137013,                    Best: 0.09554175, StopCount/Limit:   1/  3, Time:30.44067192\n",
      "ConfigID:   3, Epoch:   8, Training Loss: 0.09463042, Validation Loss: 0.09590708,                    Best: 0.09554175, StopCount/Limit:   2/  3, Time:171.68235803\n",
      "ConfigID:   3, Epoch:   9, Training Loss: 0.09391919, Validation Loss: 0.10074632,                    Best: 0.09554175, StopCount/Limit:   3/  3, Time:147.75448680\n",
      "1 0\n",
      "[784   8  10   4   6   9   8   6   9  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   8   5   6   7   6   7   5   5  10]\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.26353450, Validation Loss: 0.18705445,                    Best: 0.18705445, StopCount/Limit:   0/  3, Time:179.24395204\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.17096848, Validation Loss: 0.13692270,                    Best: 0.13692270, StopCount/Limit:   0/  3, Time:181.83146095\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.12481420, Validation Loss: 0.11616675,                    Best: 0.11616675, StopCount/Limit:   0/  3, Time:181.15886998\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.11386695, Validation Loss: 0.11307414,                    Best: 0.11307414, StopCount/Limit:   0/  3, Time:171.10852504\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.10920939, Validation Loss: 0.10984617,                    Best: 0.10984617, StopCount/Limit:   0/  3, Time:199.77564311\n",
      "ConfigID:   4, Epoch:   5, Training Loss: 0.10612855, Validation Loss: 0.10753252,                    Best: 0.10753252, StopCount/Limit:   0/  3, Time:179.28080416\n",
      "ConfigID:   4, Epoch:   6, Training Loss: 0.10490200, Validation Loss: 0.11173158,                    Best: 0.10753252, StopCount/Limit:   1/  3, Time:173.95543218\n",
      "ConfigID:   4, Epoch:   7, Training Loss: 0.10283796, Validation Loss: 0.10639745,                    Best: 0.10639745, StopCount/Limit:   1/  3, Time:182.20231771\n",
      "ConfigID:   4, Epoch:   8, Training Loss: 0.09978550, Validation Loss: 0.10071697,                    Best: 0.10071697, StopCount/Limit:   1/  3, Time:175.34400892\n",
      "ConfigID:   4, Epoch:   9, Training Loss: 0.09612874, Validation Loss: 0.10026475,                    Best: 0.10026475, StopCount/Limit:   1/  3, Time:185.63464975\n",
      "ConfigID:   4, Epoch:  10, Training Loss: 0.09422141, Validation Loss: 0.10586392,                    Best: 0.10026475, StopCount/Limit:   2/  3, Time:185.68336892\n",
      "ConfigID:   4, Epoch:  11, Training Loss: 0.09260254, Validation Loss: 0.09727137,                    Best: 0.09727137, StopCount/Limit:   2/  3, Time:186.14562106\n",
      "ConfigID:   4, Epoch:  12, Training Loss: 0.09139729, Validation Loss: 0.09316313,                    Best: 0.09316313, StopCount/Limit:   2/  3, Time:14.03198886\n",
      "ConfigID:   4, Epoch:  13, Training Loss: 0.09029653, Validation Loss: 0.10087359,                    Best: 0.09316313, StopCount/Limit:   3/  3, Time:8.97147894\n",
      "Gen 7 Run End\n",
      "Run   7 Best: 0.05979079821798951, Mean: 0.06815228878962808, ID:2, config: [784   9   9   7   5   7   5   6   9   9  10], updatecount:   0, Generation RunTime: 4703.43529415\n",
      "Gen 8 Run Start\n",
      "3 2\n",
      "[784   9   9   7   5   6  10] [784   9   9   7   5   7   5   6   9   9  10]\n",
      "Next Gen: [784   8   9   6   4   8   8   9  10]\n",
      "ConfigID:   0, Epoch:   0, Training Loss: 0.28916465, Validation Loss: 0.22868607,                    Best: 0.22868607, StopCount/Limit:   0/  3, Time:6.88888979\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.18390278, Validation Loss: 0.15233674,                    Best: 0.15233674, StopCount/Limit:   0/  3, Time:6.89344692\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.14477353, Validation Loss: 0.14120638,                    Best: 0.14120638, StopCount/Limit:   0/  3, Time:6.93268895\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.13214860, Validation Loss: 0.12970596,                    Best: 0.12970596, StopCount/Limit:   0/  3, Time:6.78438592\n",
      "ConfigID:   0, Epoch:   4, Training Loss: 0.12156847, Validation Loss: 0.11714795,                    Best: 0.11714795, StopCount/Limit:   0/  3, Time:6.84162211\n",
      "ConfigID:   0, Epoch:   5, Training Loss: 0.11521936, Validation Loss: 0.11272507,                    Best: 0.11272507, StopCount/Limit:   0/  3, Time:6.87615085\n",
      "ConfigID:   0, Epoch:   6, Training Loss: 0.10933372, Validation Loss: 0.10625626,                    Best: 0.10625626, StopCount/Limit:   0/  3, Time:6.80825210\n",
      "ConfigID:   0, Epoch:   7, Training Loss: 0.10452549, Validation Loss: 0.10181847,                    Best: 0.10181847, StopCount/Limit:   0/  3, Time:6.85360503\n",
      "ConfigID:   0, Epoch:   8, Training Loss: 0.10248833, Validation Loss: 0.10323221,                    Best: 0.10181847, StopCount/Limit:   1/  3, Time:8.30165100\n",
      "ConfigID:   0, Epoch:   9, Training Loss: 0.10104640, Validation Loss: 0.10206857,                    Best: 0.10181847, StopCount/Limit:   2/  3, Time:6.92979693\n",
      "ConfigID:   0, Epoch:  10, Training Loss: 0.09935395, Validation Loss: 0.09829795,                    Best: 0.09829795, StopCount/Limit:   2/  3, Time:6.95260382\n",
      "ConfigID:   0, Epoch:  11, Training Loss: 0.09605813, Validation Loss: 0.09741374,                    Best: 0.09741374, StopCount/Limit:   2/  3, Time:7.30255675\n",
      "ConfigID:   0, Epoch:  12, Training Loss: 0.09087089, Validation Loss: 0.09387401,                    Best: 0.09387401, StopCount/Limit:   2/  3, Time:8.55707717\n",
      "ConfigID:   0, Epoch:  13, Training Loss: 0.09323357, Validation Loss: 0.08860127,                    Best: 0.08860127, StopCount/Limit:   2/  3, Time:7.72054505\n",
      "ConfigID:   0, Epoch:  14, Training Loss: 0.08922448, Validation Loss: 0.08815013,                    Best: 0.08815013, StopCount/Limit:   2/  3, Time:9.10748577\n",
      "ConfigID:   0, Epoch:  15, Training Loss: 0.08795518, Validation Loss: 0.08688078,                    Best: 0.08688078, StopCount/Limit:   2/  3, Time:7.51341414\n",
      "ConfigID:   0, Epoch:  16, Training Loss: 0.09326536, Validation Loss: 0.08849538,                    Best: 0.08688078, StopCount/Limit:   3/  3, Time:7.28824401\n",
      "0 4\n",
      "[784   8   9   9   4   8   8  10  10] [784   8   5   9   6   6   7   5   5  10]\n",
      "Next Gen: [784   8  10   4   5  10   8   8   8  10]\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.22751933, Validation Loss: 0.17384878,                    Best: 0.17384878, StopCount/Limit:   0/  3, Time:7.70407510\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.15213743, Validation Loss: 0.14468547,                    Best: 0.14468547, StopCount/Limit:   0/  3, Time:7.71824789\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.14087084, Validation Loss: 0.14289762,                    Best: 0.14289762, StopCount/Limit:   0/  3, Time:7.79984403\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.13351427, Validation Loss: 0.12518091,                    Best: 0.12518091, StopCount/Limit:   0/  3, Time:7.71737695\n",
      "ConfigID:   1, Epoch:   4, Training Loss: 0.12270316, Validation Loss: 0.11816364,                    Best: 0.11816364, StopCount/Limit:   0/  3, Time:8.05219412\n",
      "ConfigID:   1, Epoch:   5, Training Loss: 0.11733555, Validation Loss: 0.12397741,                    Best: 0.11816364, StopCount/Limit:   1/  3, Time:7.77871990\n",
      "ConfigID:   1, Epoch:   6, Training Loss: 0.11326003, Validation Loss: 0.11058691,                    Best: 0.11058691, StopCount/Limit:   1/  3, Time:7.75771737\n",
      "ConfigID:   1, Epoch:   7, Training Loss: 0.11117835, Validation Loss: 0.10961339,                    Best: 0.10961339, StopCount/Limit:   1/  3, Time:7.67660809\n",
      "ConfigID:   1, Epoch:   8, Training Loss: 0.10877716, Validation Loss: 0.10967330,                    Best: 0.10961339, StopCount/Limit:   2/  3, Time:7.98045206\n",
      "ConfigID:   1, Epoch:   9, Training Loss: 0.10736378, Validation Loss: 0.10439260,                    Best: 0.10439260, StopCount/Limit:   2/  3, Time:7.70546794\n",
      "ConfigID:   1, Epoch:  10, Training Loss: 0.10617764, Validation Loss: 0.10657509,                    Best: 0.10439260, StopCount/Limit:   3/  3, Time:7.83573914\n",
      "4 0\n",
      "[784   8   5   9   6   6   7   5   5  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   8   9   5   5   7   6   4   9   9  10]\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.22815447, Validation Loss: 0.17534650,                    Best: 0.17534650, StopCount/Limit:   0/  3, Time:8.39831614\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.17060163, Validation Loss: 0.17115471,                    Best: 0.17115471, StopCount/Limit:   0/  3, Time:8.38856602\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.16503327, Validation Loss: 0.16215448,                    Best: 0.16215448, StopCount/Limit:   0/  3, Time:8.72582483\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.15650229, Validation Loss: 0.15208523,                    Best: 0.15208523, StopCount/Limit:   0/  3, Time:8.49465179\n",
      "ConfigID:   2, Epoch:   4, Training Loss: 0.14905259, Validation Loss: 0.14728435,                    Best: 0.14728435, StopCount/Limit:   0/  3, Time:8.38665795\n",
      "ConfigID:   2, Epoch:   5, Training Loss: 0.14688765, Validation Loss: 0.14703095,                    Best: 0.14703095, StopCount/Limit:   0/  3, Time:8.41933727\n",
      "ConfigID:   2, Epoch:   6, Training Loss: 0.14484197, Validation Loss: 0.14508071,                    Best: 0.14508071, StopCount/Limit:   0/  3, Time:9.46518779\n",
      "ConfigID:   2, Epoch:   7, Training Loss: 0.14270785, Validation Loss: 0.14249804,                    Best: 0.14249804, StopCount/Limit:   0/  3, Time:9.72276688\n",
      "ConfigID:   2, Epoch:   8, Training Loss: 0.14168233, Validation Loss: 0.14277449,                    Best: 0.14249804, StopCount/Limit:   1/  3, Time:9.72642303\n",
      "ConfigID:   2, Epoch:   9, Training Loss: 0.13613070, Validation Loss: 0.13373676,                    Best: 0.13373676, StopCount/Limit:   1/  3, Time:9.81135225\n",
      "ConfigID:   2, Epoch:  10, Training Loss: 0.13563486, Validation Loss: 0.13567644,                    Best: 0.13373676, StopCount/Limit:   2/  3, Time:9.83582497\n",
      "ConfigID:   2, Epoch:  11, Training Loss: 0.13159880, Validation Loss: 0.12976025,                    Best: 0.12976025, StopCount/Limit:   2/  3, Time:12.35517788\n",
      "ConfigID:   2, Epoch:  12, Training Loss: 0.13051935, Validation Loss: 0.13338781,                    Best: 0.12976025, StopCount/Limit:   3/  3, Time:11.30018806\n",
      "2 0\n",
      "[784   9   9   7   5   7   5   6   9   9  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   9   9   4   6   6   6   9  10]\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.21951427, Validation Loss: 0.17147418,                    Best: 0.17147418, StopCount/Limit:   0/  3, Time:8.84784627\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.15897574, Validation Loss: 0.15242124,                    Best: 0.15242124, StopCount/Limit:   0/  3, Time:9.46160007\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.14809169, Validation Loss: 0.14756657,                    Best: 0.14756657, StopCount/Limit:   0/  3, Time:7.77442193\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.14348461, Validation Loss: 0.14335046,                    Best: 0.14335046, StopCount/Limit:   0/  3, Time:7.60196805\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.14069981, Validation Loss: 0.13783897,                    Best: 0.13783897, StopCount/Limit:   0/  3, Time:7.72449088\n",
      "ConfigID:   3, Epoch:   5, Training Loss: 0.13847079, Validation Loss: 0.14349713,                    Best: 0.13783897, StopCount/Limit:   1/  3, Time:7.67883277\n",
      "ConfigID:   3, Epoch:   6, Training Loss: 0.13683036, Validation Loss: 0.14079666,                    Best: 0.13783897, StopCount/Limit:   2/  3, Time:7.61468077\n",
      "ConfigID:   3, Epoch:   7, Training Loss: 0.13522008, Validation Loss: 0.13618321,                    Best: 0.13618321, StopCount/Limit:   2/  3, Time:7.82522702\n",
      "ConfigID:   3, Epoch:   8, Training Loss: 0.13404042, Validation Loss: 0.13352418,                    Best: 0.13352418, StopCount/Limit:   2/  3, Time:7.62857604\n",
      "ConfigID:   3, Epoch:   9, Training Loss: 0.13238448, Validation Loss: 0.13298508,                    Best: 0.13298508, StopCount/Limit:   2/  3, Time:7.63108802\n",
      "ConfigID:   3, Epoch:  10, Training Loss: 0.13140580, Validation Loss: 0.13158403,                    Best: 0.13158403, StopCount/Limit:   2/  3, Time:7.71260810\n",
      "ConfigID:   3, Epoch:  11, Training Loss: 0.13046590, Validation Loss: 0.13246753,                    Best: 0.13158403, StopCount/Limit:   3/  3, Time:7.47405314\n",
      "3 0\n",
      "[784   9   9   7   5   6  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   8   7   9   6   6   7   5   8  10]\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.32196350, Validation Loss: 0.28296744,                    Best: 0.28296744, StopCount/Limit:   0/  3, Time:8.30579209\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.27834540, Validation Loss: 0.27356205,                    Best: 0.27356205, StopCount/Limit:   0/  3, Time:8.20509696\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.26812402, Validation Loss: 0.26320914,                    Best: 0.26320914, StopCount/Limit:   0/  3, Time:8.49024224\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.25811657, Validation Loss: 0.25370880,                    Best: 0.25370880, StopCount/Limit:   0/  3, Time:8.20853186\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.24698709, Validation Loss: 0.22796647,                    Best: 0.22796647, StopCount/Limit:   0/  3, Time:9.85072303\n",
      "ConfigID:   4, Epoch:   5, Training Loss: 0.20269141, Validation Loss: 0.18995303,                    Best: 0.18995303, StopCount/Limit:   0/  3, Time:9.34826326\n",
      "ConfigID:   4, Epoch:   6, Training Loss: 0.17754749, Validation Loss: 0.17478802,                    Best: 0.17478802, StopCount/Limit:   0/  3, Time:8.78240204\n",
      "ConfigID:   4, Epoch:   7, Training Loss: 0.16769385, Validation Loss: 0.16695088,                    Best: 0.16695088, StopCount/Limit:   0/  3, Time:9.21046805\n",
      "ConfigID:   4, Epoch:   8, Training Loss: 0.16170120, Validation Loss: 0.16207114,                    Best: 0.16207114, StopCount/Limit:   0/  3, Time:8.34349799\n",
      "ConfigID:   4, Epoch:   9, Training Loss: 0.15597566, Validation Loss: 0.15738460,                    Best: 0.15738460, StopCount/Limit:   0/  3, Time:7.82475185\n",
      "ConfigID:   4, Epoch:  10, Training Loss: 0.15424586, Validation Loss: 0.15545606,                    Best: 0.15545606, StopCount/Limit:   0/  3, Time:7.93451405\n",
      "ConfigID:   4, Epoch:  11, Training Loss: 0.15093383, Validation Loss: 0.15037398,                    Best: 0.15037398, StopCount/Limit:   0/  3, Time:9.51829410\n",
      "ConfigID:   4, Epoch:  12, Training Loss: 0.15002787, Validation Loss: 0.15180962,                    Best: 0.15037398, StopCount/Limit:   1/  3, Time:8.81460905\n",
      "ConfigID:   4, Epoch:  13, Training Loss: 0.14729092, Validation Loss: 0.14921672,                    Best: 0.14921672, StopCount/Limit:   1/  3, Time:8.10541105\n",
      "ConfigID:   4, Epoch:  14, Training Loss: 0.14428032, Validation Loss: 0.14785896,                    Best: 0.14785896, StopCount/Limit:   1/  3, Time:8.20930982\n",
      "ConfigID:   4, Epoch:  15, Training Loss: 0.14182749, Validation Loss: 0.14473166,                    Best: 0.14473166, StopCount/Limit:   1/  3, Time:8.09155107\n",
      "ConfigID:   4, Epoch:  16, Training Loss: 0.13937407, Validation Loss: 0.14234962,                    Best: 0.14234962, StopCount/Limit:   1/  3, Time:9.32605696\n",
      "ConfigID:   4, Epoch:  17, Training Loss: 0.13801221, Validation Loss: 0.14193801,                    Best: 0.14193801, StopCount/Limit:   1/  3, Time:9.51159382\n",
      "ConfigID:   4, Epoch:  18, Training Loss: 0.13580564, Validation Loss: 0.13692931,                    Best: 0.13692931, StopCount/Limit:   1/  3, Time:9.17799306\n",
      "ConfigID:   4, Epoch:  19, Training Loss: 0.13562653, Validation Loss: 0.13396802,                    Best: 0.13396802, StopCount/Limit:   1/  3, Time:9.23080611\n",
      "ConfigID:   4, Epoch:  20, Training Loss: 0.13322247, Validation Loss: 0.13665543,                    Best: 0.13396802, StopCount/Limit:   2/  3, Time:9.12530804\n",
      "ConfigID:   4, Epoch:  21, Training Loss: 0.13224552, Validation Loss: 0.13575821,                    Best: 0.13396802, StopCount/Limit:   3/  3, Time:9.51322985\n",
      "Gen 8 Run End\n",
      "Run   8 Best: 0.05979079821798951, Mean: 0.06815228878962808, ID:2, config: [784   9   9   7   5   7   5   6   9   9  10], updatecount:   0, Generation RunTime: 621.47077370\n",
      "Gen 9 Run Start\n",
      "0 3\n",
      "[784   8   9   9   4   8   8  10  10] [784   9   9   7   5   6  10]\n",
      "Next Gen: [784   7   9  10   4   8   8   8   4  10]\n",
      "ConfigID:   0, Epoch:   0, Training Loss: 0.24353994, Validation Loss: 0.21998451,                    Best: 0.21998451, StopCount/Limit:   0/  3, Time:9.13490891\n",
      "ConfigID:   0, Epoch:   1, Training Loss: 0.21189599, Validation Loss: 0.21007723,                    Best: 0.21007723, StopCount/Limit:   0/  3, Time:11.28929305\n",
      "ConfigID:   0, Epoch:   2, Training Loss: 0.17827544, Validation Loss: 0.16429754,                    Best: 0.16429754, StopCount/Limit:   0/  3, Time:8.93856311\n",
      "ConfigID:   0, Epoch:   3, Training Loss: 0.15078431, Validation Loss: 0.13496848,                    Best: 0.13496848, StopCount/Limit:   0/  3, Time:11.86768699\n",
      "ConfigID:   0, Epoch:   4, Training Loss: 0.12693394, Validation Loss: 0.12869642,                    Best: 0.12869642, StopCount/Limit:   0/  3, Time:8.73950005\n",
      "ConfigID:   0, Epoch:   5, Training Loss: 0.11502689, Validation Loss: 0.11327507,                    Best: 0.11327507, StopCount/Limit:   0/  3, Time:8.98611021\n",
      "ConfigID:   0, Epoch:   6, Training Loss: 0.10879108, Validation Loss: 0.11055446,                    Best: 0.11055446, StopCount/Limit:   0/  3, Time:10.24961805\n",
      "ConfigID:   0, Epoch:   7, Training Loss: 0.10397156, Validation Loss: 0.10191745,                    Best: 0.10191745, StopCount/Limit:   0/  3, Time:9.04392290\n",
      "ConfigID:   0, Epoch:   8, Training Loss: 0.10142218, Validation Loss: 0.10087742,                    Best: 0.10087742, StopCount/Limit:   0/  3, Time:8.61181593\n",
      "ConfigID:   0, Epoch:   9, Training Loss: 0.09799245, Validation Loss: 0.10184177,                    Best: 0.10087742, StopCount/Limit:   1/  3, Time:8.63773298\n",
      "ConfigID:   0, Epoch:  10, Training Loss: 0.09648718, Validation Loss: 0.10008565,                    Best: 0.10008565, StopCount/Limit:   1/  3, Time:8.84062505\n",
      "ConfigID:   0, Epoch:  11, Training Loss: 0.09526463, Validation Loss: 0.09704130,                    Best: 0.09704130, StopCount/Limit:   1/  3, Time:8.95248890\n",
      "ConfigID:   0, Epoch:  12, Training Loss: 0.09312241, Validation Loss: 0.09426346,                    Best: 0.09426346, StopCount/Limit:   1/  3, Time:12.28790975\n",
      "ConfigID:   0, Epoch:  13, Training Loss: 0.09110673, Validation Loss: 0.09481854,                    Best: 0.09426346, StopCount/Limit:   2/  3, Time:9.65365195\n",
      "ConfigID:   0, Epoch:  14, Training Loss: 0.09020374, Validation Loss: 0.09371044,                    Best: 0.09371044, StopCount/Limit:   2/  3, Time:8.76716924\n",
      "ConfigID:   0, Epoch:  15, Training Loss: 0.09033989, Validation Loss: 0.12201860,                    Best: 0.09371044, StopCount/Limit:   3/  3, Time:8.94528794\n",
      "2 1\n",
      "[784   9   9   7   5   7   5   6   9   9  10] [784   8  10   4   6   9   8   6   9  10]\n",
      "Next Gen: [784   8   7   8   6   6   8   6   7  10]\n",
      "ConfigID:   1, Epoch:   0, Training Loss: 0.32958003, Validation Loss: 0.27697142,                    Best: 0.27697142, StopCount/Limit:   0/  3, Time:9.39917111\n",
      "ConfigID:   1, Epoch:   1, Training Loss: 0.25899782, Validation Loss: 0.25709635,                    Best: 0.25709635, StopCount/Limit:   0/  3, Time:11.71867704\n",
      "ConfigID:   1, Epoch:   2, Training Loss: 0.25052101, Validation Loss: 0.25295542,                    Best: 0.25295542, StopCount/Limit:   0/  3, Time:8.95356584\n",
      "ConfigID:   1, Epoch:   3, Training Loss: 0.24823562, Validation Loss: 0.25414444,                    Best: 0.25295542, StopCount/Limit:   1/  3, Time:7.89333105\n",
      "ConfigID:   1, Epoch:   4, Training Loss: 0.24713184, Validation Loss: 0.25462323,                    Best: 0.25295542, StopCount/Limit:   2/  3, Time:9.62890601\n",
      "ConfigID:   1, Epoch:   5, Training Loss: 0.24661651, Validation Loss: 0.25119252,                    Best: 0.25119252, StopCount/Limit:   2/  3, Time:8.30532598\n",
      "ConfigID:   1, Epoch:   6, Training Loss: 0.24568683, Validation Loss: 0.25014584,                    Best: 0.25014584, StopCount/Limit:   2/  3, Time:9.26637006\n",
      "ConfigID:   1, Epoch:   7, Training Loss: 0.24483101, Validation Loss: 0.26187617,                    Best: 0.25014584, StopCount/Limit:   3/  3, Time:9.36538601\n",
      "4 3\n",
      "[784   8   5   9   6   6   7   5   5  10] [784   9   9   7   5   6  10]\n",
      "Next Gen: [784   8   9   6   5   7   8   6   9   9   4  10]\n",
      "ConfigID:   2, Epoch:   0, Training Loss: 0.27069474, Validation Loss: 0.21615143,                    Best: 0.21615143, StopCount/Limit:   0/  3, Time:10.67632484\n",
      "ConfigID:   2, Epoch:   1, Training Loss: 0.20024166, Validation Loss: 0.19595256,                    Best: 0.19595256, StopCount/Limit:   0/  3, Time:11.03768396\n",
      "ConfigID:   2, Epoch:   2, Training Loss: 0.18796337, Validation Loss: 0.18428774,                    Best: 0.18428774, StopCount/Limit:   0/  3, Time:10.27334023\n",
      "ConfigID:   2, Epoch:   3, Training Loss: 0.18232410, Validation Loss: 0.17878199,                    Best: 0.17878199, StopCount/Limit:   0/  3, Time:12.27296829\n",
      "ConfigID:   2, Epoch:   4, Training Loss: 0.17691146, Validation Loss: 0.17341090,                    Best: 0.17341090, StopCount/Limit:   0/  3, Time:15.36012411\n",
      "ConfigID:   2, Epoch:   5, Training Loss: 0.17258870, Validation Loss: 0.17005517,                    Best: 0.17005517, StopCount/Limit:   0/  3, Time:12.42595005\n",
      "ConfigID:   2, Epoch:   6, Training Loss: 0.16572015, Validation Loss: 0.16162442,                    Best: 0.16162442, StopCount/Limit:   0/  3, Time:9.60046291\n",
      "ConfigID:   2, Epoch:   7, Training Loss: 0.16291130, Validation Loss: 0.16018404,                    Best: 0.16018404, StopCount/Limit:   0/  3, Time:9.71102619\n",
      "ConfigID:   2, Epoch:   8, Training Loss: 0.15634263, Validation Loss: 0.16192700,                    Best: 0.16018404, StopCount/Limit:   1/  3, Time:9.82735181\n",
      "ConfigID:   2, Epoch:   9, Training Loss: 0.15420985, Validation Loss: 0.15490067,                    Best: 0.15490067, StopCount/Limit:   1/  3, Time:10.30943179\n",
      "ConfigID:   2, Epoch:  10, Training Loss: 0.15073528, Validation Loss: 0.15475016,                    Best: 0.15475016, StopCount/Limit:   1/  3, Time:14.83066821\n",
      "ConfigID:   2, Epoch:  11, Training Loss: 0.14887630, Validation Loss: 0.15265093,                    Best: 0.15265093, StopCount/Limit:   1/  3, Time:14.29764295\n",
      "ConfigID:   2, Epoch:  12, Training Loss: 0.14887678, Validation Loss: 0.14964672,                    Best: 0.14964672, StopCount/Limit:   1/  3, Time:10.56476021\n",
      "ConfigID:   2, Epoch:  13, Training Loss: 0.14769983, Validation Loss: 0.14681354,                    Best: 0.14681354, StopCount/Limit:   1/  3, Time:10.89166617\n",
      "ConfigID:   2, Epoch:  14, Training Loss: 0.14560864, Validation Loss: 0.14742770,                    Best: 0.14681354, StopCount/Limit:   2/  3, Time:10.60594893\n",
      "ConfigID:   2, Epoch:  15, Training Loss: 0.14327601, Validation Loss: 0.14543699,                    Best: 0.14543699, StopCount/Limit:   2/  3, Time:9.77178717\n",
      "ConfigID:   2, Epoch:  16, Training Loss: 0.14518538, Validation Loss: 0.15450954,                    Best: 0.14543699, StopCount/Limit:   3/  3, Time:9.36826706\n",
      "3 0\n",
      "[784   9   9   7   5   6  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   9   9   7   6   5  10]\n",
      "ConfigID:   3, Epoch:   0, Training Loss: 0.23282825, Validation Loss: 0.18979565,                    Best: 0.18979565, StopCount/Limit:   0/  3, Time:7.75222921\n",
      "ConfigID:   3, Epoch:   1, Training Loss: 0.16003750, Validation Loss: 0.14587490,                    Best: 0.14587490, StopCount/Limit:   0/  3, Time:8.30268908\n",
      "ConfigID:   3, Epoch:   2, Training Loss: 0.13308761, Validation Loss: 0.13163764,                    Best: 0.13163764, StopCount/Limit:   0/  3, Time:8.21749496\n",
      "ConfigID:   3, Epoch:   3, Training Loss: 0.11658611, Validation Loss: 0.11453769,                    Best: 0.11453769, StopCount/Limit:   0/  3, Time:7.11916590\n",
      "ConfigID:   3, Epoch:   4, Training Loss: 0.10714935, Validation Loss: 0.11016903,                    Best: 0.11016903, StopCount/Limit:   0/  3, Time:7.64930105\n",
      "ConfigID:   3, Epoch:   5, Training Loss: 0.10262051, Validation Loss: 0.10466025,                    Best: 0.10466025, StopCount/Limit:   0/  3, Time:8.05657077\n",
      "ConfigID:   3, Epoch:   6, Training Loss: 0.09932069, Validation Loss: 0.10458743,                    Best: 0.10458743, StopCount/Limit:   0/  3, Time:8.83356094\n",
      "ConfigID:   3, Epoch:   7, Training Loss: 0.09748260, Validation Loss: 0.10353852,                    Best: 0.10353852, StopCount/Limit:   0/  3, Time:7.62452388\n",
      "ConfigID:   3, Epoch:   8, Training Loss: 0.09551625, Validation Loss: 0.10286151,                    Best: 0.10286151, StopCount/Limit:   0/  3, Time:9.44555712\n",
      "ConfigID:   3, Epoch:   9, Training Loss: 0.09380549, Validation Loss: 0.11245906,                    Best: 0.10286151, StopCount/Limit:   1/  3, Time:7.61986089\n",
      "ConfigID:   3, Epoch:  10, Training Loss: 0.09233077, Validation Loss: 0.10018043,                    Best: 0.10018043, StopCount/Limit:   1/  3, Time:8.34702492\n",
      "ConfigID:   3, Epoch:  11, Training Loss: 0.09052357, Validation Loss: 0.10314753,                    Best: 0.10018043, StopCount/Limit:   2/  3, Time:7.54888296\n",
      "ConfigID:   3, Epoch:  12, Training Loss: 0.08865725, Validation Loss: 0.09692429,                    Best: 0.09692429, StopCount/Limit:   2/  3, Time:9.07007504\n",
      "ConfigID:   3, Epoch:  13, Training Loss: 0.08643427, Validation Loss: 0.09444872,                    Best: 0.09444872, StopCount/Limit:   2/  3, Time:6.29814887\n",
      "ConfigID:   3, Epoch:  14, Training Loss: 0.08431900, Validation Loss: 0.09098240,                    Best: 0.09098240, StopCount/Limit:   2/  3, Time:6.15208006\n",
      "ConfigID:   3, Epoch:  15, Training Loss: 0.08169192, Validation Loss: 0.08880872,                    Best: 0.08880872, StopCount/Limit:   2/  3, Time:6.19026685\n",
      "ConfigID:   3, Epoch:  16, Training Loss: 0.07964383, Validation Loss: 0.08463728,                    Best: 0.08463728, StopCount/Limit:   2/  3, Time:6.14794803\n",
      "ConfigID:   3, Epoch:  17, Training Loss: 0.07769983, Validation Loss: 0.08138318,                    Best: 0.08138318, StopCount/Limit:   2/  3, Time:6.07780194\n",
      "ConfigID:   3, Epoch:  18, Training Loss: 0.07581581, Validation Loss: 0.08339443,                    Best: 0.08138318, StopCount/Limit:   3/  3, Time:6.28455710\n",
      "3 0\n",
      "[784   9   9   7   5   6  10] [784   8   9   9   4   8   8  10  10]\n",
      "Next Gen: [784   8   7   9   6   6   7   5   5  10]\n",
      "ConfigID:   4, Epoch:   0, Training Loss: 0.23485294, Validation Loss: 0.16758761,                    Best: 0.16758761, StopCount/Limit:   0/  3, Time:8.53788209\n",
      "ConfigID:   4, Epoch:   1, Training Loss: 0.14047000, Validation Loss: 0.11842397,                    Best: 0.11842397, StopCount/Limit:   0/  3, Time:9.81317997\n",
      "ConfigID:   4, Epoch:   2, Training Loss: 0.11273485, Validation Loss: 0.10578549,                    Best: 0.10578549, StopCount/Limit:   0/  3, Time:8.00227714\n",
      "ConfigID:   4, Epoch:   3, Training Loss: 0.10451614, Validation Loss: 0.10273489,                    Best: 0.10273489, StopCount/Limit:   0/  3, Time:8.68618798\n",
      "ConfigID:   4, Epoch:   4, Training Loss: 0.09972413, Validation Loss: 0.09949258,                    Best: 0.09949258, StopCount/Limit:   0/  3, Time:9.10717511\n",
      "ConfigID:   4, Epoch:   5, Training Loss: 0.09609582, Validation Loss: 0.09888663,                    Best: 0.09888663, StopCount/Limit:   0/  3, Time:8.02661800\n",
      "ConfigID:   4, Epoch:   6, Training Loss: 0.09325856, Validation Loss: 0.09640548,                    Best: 0.09640548, StopCount/Limit:   0/  3, Time:8.95177794\n",
      "ConfigID:   4, Epoch:   7, Training Loss: 0.09121449, Validation Loss: 0.09660341,                    Best: 0.09640548, StopCount/Limit:   1/  3, Time:8.70762110\n",
      "ConfigID:   4, Epoch:   8, Training Loss: 0.08948438, Validation Loss: 0.09378470,                    Best: 0.09378470, StopCount/Limit:   1/  3, Time:8.12115097\n",
      "ConfigID:   4, Epoch:   9, Training Loss: 0.08871346, Validation Loss: 0.09159552,                    Best: 0.09159552, StopCount/Limit:   1/  3, Time:8.99420071\n",
      "ConfigID:   4, Epoch:  10, Training Loss: 0.08779980, Validation Loss: 0.09185841,                    Best: 0.09159552, StopCount/Limit:   2/  3, Time:8.55815196\n",
      "ConfigID:   4, Epoch:  11, Training Loss: 0.08755749, Validation Loss: 0.08903176,                    Best: 0.08903176, StopCount/Limit:   2/  3, Time:8.04446006\n",
      "ConfigID:   4, Epoch:  12, Training Loss: 0.08656157, Validation Loss: 0.09154599,                    Best: 0.08903176, StopCount/Limit:   3/  3, Time:7.89540029\n",
      "Gen 9 Run End\n",
      "Run   9 Best: 0.05979079821798951, Mean: 0.06815228878962808, ID:2, config: [784   9   9   7   5   7   5   6   9   9  10], updatecount:   0, Generation RunTime: 673.53473091\n",
      "Run Completed : Best Score(loss): 0.05979079821798951 , Config: [784   9   9   7   5   7   5   6   9   9  10]\n"
     ]
    }
   ],
   "source": [
    "d.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd4ade25-6f16-4dc8-93f5-db46fe5c0ff4",
   "metadata": {},
   "outputs": [],
   "source": []
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