From bbe8b7de996dc340dd95bb248827ec729a7461e4 Mon Sep 17 00:00:00 2001
From: eneren <engin.eren@cern.ch>
Date: Tue, 17 May 2022 08:21:57 +0000
Subject: [PATCH] wrapping up

---
 interactive/ecal_emb.ipynb |   25 +-
 interactive/evalGPU.ipynb  | 1227 +++++-------------------------------
 interactive/functions.py   |   31 +
 3 files changed, 200 insertions(+), 1083 deletions(-)

diff --git a/interactive/ecal_emb.ipynb b/interactive/ecal_emb.ipynb
index 2a21790..10c52f2 100644
--- a/interactive/ecal_emb.ipynb
+++ b/interactive/ecal_emb.ipynb
@@ -145,7 +145,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -187,9 +187,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "torch.Size([100, 48, 30, 30])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "#sum(p.numel() for p in aG.parameters() if p.requires_grad)\n",
     "fake_data.shape"
@@ -206,7 +217,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -290,7 +301,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -342,7 +353,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -351,7 +362,7 @@
        "3542517"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/interactive/evalGPU.ipynb b/interactive/evalGPU.ipynb
index 00bafe4..ea70b6c 100644
--- a/interactive/evalGPU.ipynb
+++ b/interactive/evalGPU.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17,35 +17,35 @@
     "import matplotlib.pyplot as plt\n",
     "import matplotlib as mpl\n",
     "import h5py\n",
-    "import matplotlib.patches as mpatches"
+    "import matplotlib.patches as mpatches\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "## G4 \n",
-    "f40 = h5py.File('/eos/user/e/eneren/run_prod20k_40GeVp2/pion-shower_40.hdf5', 'r')\n",
+    "f40 = h5py.File('/eos/user/e/eneren/scratch/single/40GeVData20k.hdf5', 'r')\n",
     "f50 = h5py.File('/eos/user/e/eneren/scratch/50GeV75k.hdf5', 'r')\n",
     "f60 = h5py.File('/eos/user/e/eneren/scratch/single/60GeV20k.hdf5', 'r')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "showers50 = f50['ecal/layers'][:1000]\n",
-    "showers40 = f40['ecal/layers'][:1000]\n",
-    "showers60 = f60['ecal/layers'][:1000]"
+    "showers40 = f40['ecal/layers'][:5000]\n",
+    "showers50 = f50['ecal/layers'][:5000]\n",
+    "showers60 = f60['ecal/layers'][:5000]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -58,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -69,18 +69,19 @@
     "\n",
     "\n",
     "    pSEa = axSE.hist(real, bins=nbins, \n",
-    "            weights=np.ones_like(real)/(float(len(real))), \n",
+    "            #weights=np.ones_like(real)/(float(len(real))), \n",
     "            histtype='step', color='black',\n",
     "            range=[minE, maxE])\n",
     "    pSEb = axSE.hist(fake, bins=nbins, \n",
-    "            weights=np.ones_like(fake)/(float(len(fake))),\n",
+    "            #weights=np.ones_like(fake)/(float(len(fake))),\n",
     "            histtype='step', color='red',\n",
     "             range=[minE, maxE])\n",
     "\n",
     "    plt.title(name)\n",
     "    \n",
     "    plt.xlabel('MeV', fontsize=18)\n",
-    "    \n",
+    "    #axSE.set_xscale('log')\n",
+    "    axSE.set_yscale('log')\n",
     "    \n",
     "    red_patch = mpatches.Patch(color='red', label='WGAN')\n",
     "    grey_patch = mpatches.Patch(color='black', label='G4')\n",
@@ -89,37 +90,22 @@
     "    \n",
     "    \n",
     "    \n",
-    "    plt.savefig('./plots/esum'+str(name)+'.png')\n",
-    "\n",
-    "  \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ngf = 32\n",
-    "nz=100\n",
-    "mGen = DCGAN_G(ngf, nz)\n",
-    "mGen = nn.parallel.DataParallel(mGen)\n",
-    "exp='wganv1'\n",
-    "batch_size = 1000\n",
-    "\n",
+    "    plt.savefig('./esum'+str(name)+'.png')\n",
     "\n",
     "\n",
-    "fidelityRecord = {\n",
-    "    1: {\n",
-    "      'Esum' : [1.0, 1.0, 1.0],\n",
-    "    }\n",
-    "}\n",
-    "\n",
-    "for eph in range(521,522): \n",
-    "    gen_checkpoint = torch.load('/eos/user/e/eneren/experiments/' + exp + \"_generator_\"+ str(eph) + \".pt\", map_location=torch.device('cuda'))\n",
+    "def esum_perf(eph): \n",
+    "    \n",
+    "    ngf = 32\n",
+    "    nz=100\n",
+    "    mGen = DCGAN_G(ngf, nz)\n",
+    "    mGen = nn.parallel.DataParallel(mGen)\n",
+    "    exp='wganv1'\n",
+    "    batch_size = 1000\n",
+    "    \n",
+    "    gen_checkpoint = torch.load('/eos/user/e/eneren/experiments/' + exp + \"_generator_\"+ str(eph) + \".pt\", map_location=torch.device('cpu'))\n",
     "    mGen.load_state_dict(gen_checkpoint['model_state_dict'])\n",
     "    mGen.eval()\n",
-    "    Tensor = torch.cuda.FloatTensor \n",
+    "    Tensor = torch.FloatTensor \n",
     "    z = Variable(Tensor(np.random.uniform(-1, 1, (batch_size, nz, 1, 1, 1))))\n",
     "    \n",
     "    jsd = []\n",
@@ -128,29 +114,30 @@
     "        enp = torch.from_numpy(np.random.uniform(e, e, (batch_size,1,1,1,1))).float()\n",
     "        fake_data = mGen(z,enp).detach()\n",
     "       \n",
+    "        \n",
     "        esumFake = F.getTotE(fake_data.cpu().numpy(), 30, 30, 30)\n",
     "        esumReal = F.getTotE(showers[str(e)], 30, 30, 30)\n",
     "    \n",
-    "        #esum_plot(esumReal, esumFake, 50, -10, 90, 'epoch_'+str(eph)+'_E='+str(e))\n",
+    "        esum_plot(esumReal, esumFake, 100, -100, 1100, 'epoch_'+str(eph)+'_E='+str(e))\n",
     "        \n",
     "        jsd.append(F.jsdHist(esumReal, esumFake, 40, -10, 30, eph, debug=False))\n",
     "        \n",
+    "        #F.plot_image2D(fake_data)\n",
     "    \n",
     "    \n",
-    "    fidelityRecord[eph] = {\n",
-    "      'Esum' : [jsd[0], jsd[1], jsd[2]],\n",
-    "    }\n",
-    "\n",
     "    print ('Epoch {}: '.format(eph), jsd)\n",
+    "    #F.plot_image2D(fake_dataG)\n",
+    "\n",
     "    \n",
-    "    \n",
     "\n",
+    "\n",
+    "    \n",
     "    \n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -186,7 +173,7 @@
     "            esumFake = F.getTotE(fake_data.cpu().numpy(), 30, 30, 30)\n",
     "            esumReal = F.getTotE(showers[str(e)], 30, 30, 30)\n",
     "\n",
-    "            #esum_plot(esumReal, esumFake, 40, -10, 30, 'epoch_'+str(eph)+'_E='+str(e))\n",
+    "            \n",
     "\n",
     "            jsd.append(F.jsdHist(esumReal, esumFake, 40, -10, 30, eph, debug=False))\n",
     "        \n",
@@ -218,1032 +205,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Epoch:  200\n",
-      "Epoch:  [0.4170401254547888, 0.5130352293878054, 0.5266899705098229]\n",
-      "Epoch:  201\n",
-      "Epoch:  [0.3881977361684956, 0.48230338929108607, 0.48845698060212356]\n",
-      "Epoch:  202\n",
-      "Epoch:  [0.4284459061222725, 0.37751286964403624, 0.3987147438570188]\n",
-      "Epoch:  203\n",
-      "Epoch:  [0.41206294970574503, 0.5048373415373171, 0.545772261825556]\n",
-      "Epoch:  204\n",
-      "Epoch:  [0.4692785854593021, 0.5229520321636821, 0.5342409015561461]\n",
-      "Epoch:  205\n",
-      "Epoch:  [0.3824460421976007, 0.5098622561090411, 0.533485036331882]\n",
-      "Epoch:  206\n",
-      "Epoch:  [0.3993491620111905, 0.49773953375004315, 0.5112891320671056]\n",
-      "Epoch:  207\n",
-      "Epoch:  [0.4407899872182304, 0.5148315479380349, 0.5278107069048857]\n",
-      "Epoch:  208\n",
-      "Epoch:  [0.3487815574191554, 0.4633782434070531, 0.4915503353021999]\n",
-      "Epoch:  209\n",
-      "Epoch:  [0.37594332632499433, 0.4878146890128978, 0.49334680965215805]\n",
-      "Epoch:  210\n",
-      "Epoch:  [0.42450362821415366, 0.5149594538493296, 0.5424942571171222]\n",
-      "Epoch:  211\n",
-      "Epoch:  [0.3887176478182392, 0.4970702833350061, 0.5242652196277081]\n",
-      "Epoch:  212\n",
-      "Epoch:  [0.43478976478412834, 0.4961873754337626, 0.5036611807634758]\n",
-      "Epoch:  213\n",
-      "Epoch:  [0.4149299472683433, 0.4879522861503341, 0.5082110379405812]\n",
-      "Epoch:  214\n",
-      "Epoch:  [0.3065946181175759, 0.3423588521848941, 0.3769096411796718]\n",
-      "Epoch:  215\n",
-      "Epoch:  [0.3953905255715625, 0.49720073959292527, 0.5175385781872451]\n",
-      "Epoch:  216\n",
-      "Epoch:  [0.45040327275868075, 0.5068501554289876, 0.5456871773712383]\n",
-      "Epoch:  217\n",
-      "Epoch:  [0.40791546258773503, 0.5210825092392753, 0.5142881129580621]\n",
-      "Epoch:  218\n",
-      "Epoch:  [0.39114798299449066, 0.5042887268083657, 0.5237274856236745]\n",
-      "Epoch:  219\n",
-      "Epoch:  [0.43030397213703553, 0.542908058900925, 0.5698102051663515]\n",
-      "Epoch:  220\n",
-      "Epoch:  [0.39555852416382836, 0.5039851641305947, 0.5299669371660957]\n",
-      "Epoch:  221\n",
-      "Epoch:  [0.4164533609894759, 0.4991101485446083, 0.5255176113092765]\n",
-      "Epoch:  222\n",
-      "Epoch:  [0.40944435262580314, 0.5314775933428848, 0.5429663017664105]\n",
-      "Epoch:  223\n",
-      "Epoch:  [0.47168350761639677, 0.5659349782008082, 0.5777482370771121]\n",
-      "Epoch:  224\n",
-      "Epoch:  [0.44595377600947966, 0.521063508341184, 0.5247577611597747]\n",
-      "Epoch:  225\n",
-      "Epoch:  [0.4008033568067914, 0.5125577696015657, 0.5287292221673676]\n",
-      "Epoch:  226\n",
-      "Epoch:  [0.4974312241839768, 0.5494827036961315, 0.5745297998155009]\n",
-      "Epoch:  227\n",
-      "Epoch:  [0.4398698522667215, 0.5190073849399455, 0.5182220567290247]\n",
-      "Epoch:  228\n",
-      "Epoch:  [0.4702291344313595, 0.5434115974779903, 0.5566894034151549]\n",
-      "Epoch:  229\n",
-      "Epoch:  [0.4642820924063854, 0.5147940300955877, 0.5392700776517738]\n",
-      "Epoch:  230\n",
-      "Epoch:  [0.4628091324419255, 0.5102213813373646, 0.5598169861865936]\n",
-      "Epoch:  231\n",
-      "Epoch:  [0.45952887988154906, 0.5546906440110041, 0.5573981278852241]\n",
-      "Epoch:  232\n",
-      "Epoch:  [0.4597004158614367, 0.5250350354287426, 0.5553637507094865]\n",
-      "Epoch:  233\n",
-      "Epoch:  [0.4420995416796508, 0.49940355734260655, 0.4917036362528357]\n",
-      "Epoch:  234\n",
-      "Epoch:  [0.4548666400173043, 0.5301493681834442, 0.5224557603841467]\n",
-      "Epoch:  235\n",
-      "Epoch:  [0.4650567983573695, 0.5255400033855183, 0.5440278425574906]\n",
-      "Epoch:  236\n",
-      "Epoch:  [0.48124437050540325, 0.5572658414970718, 0.5449681026007613]\n",
-      "Epoch:  237\n",
-      "Epoch:  [0.4866563876377944, 0.5580447212473604, 0.5580680151585216]\n",
-      "Epoch:  238\n",
-      "Epoch:  [0.4845319697819736, 0.5413151366929867, 0.5589329264240956]\n",
-      "Epoch:  239\n",
-      "Epoch:  [0.49458959864280494, 0.5494984471503568, 0.538969529298718]\n",
-      "Epoch:  240\n",
-      "Epoch:  [0.5352009893087527, 0.5557887949482468, 0.5992262855126329]\n",
-      "Epoch:  241\n",
-      "Epoch:  [0.45256787970806805, 0.5388729750822248, 0.5545818325864432]\n",
-      "Epoch:  242\n",
-      "Epoch:  [0.4859483660301862, 0.5535323293271178, 0.5676609722620862]\n",
-      "Epoch:  243\n",
-      "Epoch:  [0.4855566178075318, 0.5106815695946286, 0.49982904316619786]\n",
-      "Epoch:  244\n",
-      "Epoch:  [0.47213222285966444, 0.5333338551556929, 0.5613785366644629]\n",
-      "Epoch:  245\n",
-      "Epoch:  [0.4928429667919908, 0.5249752189437011, 0.5385092767825739]\n",
-      "Epoch:  246\n",
-      "Epoch:  [0.5326549995611065, 0.5648180484597478, 0.5700016186974306]\n",
-      "Epoch:  247\n",
-      "Epoch:  [0.43537017388514, 0.5216051859089059, 0.5369421009873869]\n",
-      "Epoch:  248\n",
-      "Epoch:  [0.46581811417530505, 0.5387568508639728, 0.5446533682121066]\n",
-      "Epoch:  249\n",
-      "Epoch:  [0.48848186955661166, 0.5736128874973285, 0.5956077804155362]\n",
-      "Epoch:  250\n",
-      "Epoch:  [0.5376617836419003, 0.5648034699066908, 0.5743040772290218]\n",
-      "Epoch:  251\n",
-      "Epoch:  [0.4249819321040304, 0.37241892029642204, 0.4471187399463946]\n",
-      "Epoch:  252\n",
-      "Epoch:  [0.48681516745832637, 0.3473253243241063, 0.46587230507013155]\n",
-      "Epoch:  253\n",
-      "Epoch:  [0.5521181004345378, 0.3121055347450657, 0.4250862605860034]\n",
-      "Epoch:  254\n",
-      "Epoch:  [0.603319318309701, 0.3362072936249361, 0.4151980271204735]\n",
-      "Epoch:  255\n",
-      "Epoch:  [0.5563502170502453, 0.330853797070625, 0.4580996313859393]\n",
-      "Epoch:  256\n",
-      "Epoch:  [0.5535662392029621, 0.3613822391097238, 0.5027482475922563]\n",
-      "Epoch:  257\n",
-      "Epoch:  [0.4912358127656334, 0.3542982864072641, 0.5037689695984404]\n",
-      "Epoch:  258\n",
-      "Epoch:  [0.48126106019450865, 0.3855161814120699, 0.5194417920142531]\n",
-      "Epoch:  259\n",
-      "Epoch:  [0.4776058880973877, 0.39283297437146325, 0.5023080557411017]\n",
-      "Epoch:  260\n",
-      "Epoch:  [0.4834063753824198, 0.38645284414767855, 0.5211346371576919]\n",
-      "Epoch:  261\n",
-      "Epoch:  [0.42197901336039373, 0.4444689719623447, 0.5376447354510043]\n",
-      "Epoch:  262\n",
-      "Epoch:  [0.4578562115016078, 0.3976923463346407, 0.4965818216654268]\n",
-      "Epoch:  263\n",
-      "Epoch:  [0.445731611348854, 0.3876771189281337, 0.5516510835565723]\n",
-      "Epoch:  264\n",
-      "Epoch:  [0.4142793600485112, 0.4470377002948927, 0.5636912342811253]\n",
-      "Epoch:  265\n",
-      "Epoch:  [0.4456755455154104, 0.3977997421929309, 0.5483801536472647]\n",
-      "Epoch:  266\n",
-      "Epoch:  [0.4049163113307092, 0.44817775599791565, 0.5412365251019795]\n",
-      "Epoch:  267\n",
-      "Epoch:  [0.43414886268237024, 0.423992226986732, 0.5518192308155011]\n",
-      "Epoch:  268\n",
-      "Epoch:  [0.4527494158666482, 0.4412547825534166, 0.5432045637020003]\n",
-      "Epoch:  269\n",
-      "Epoch:  [0.44187902254469014, 0.4435900312942225, 0.5316722579911236]\n",
-      "Epoch:  270\n",
-      "Epoch:  [0.42164207042734947, 0.43952503230136986, 0.543148324419653]\n",
-      "Epoch:  271\n",
-      "Epoch:  [0.3827295670379283, 0.45898748464457145, 0.5745089259991281]\n",
-      "Epoch:  272\n",
-      "Epoch:  [0.4329702589036673, 0.445886808478351, 0.5235142014541851]\n",
-      "Epoch:  273\n",
-      "Epoch:  [0.3812813845014016, 0.4761584926774839, 0.5620689874171879]\n",
-      "Epoch:  274\n",
-      "Epoch:  [0.39142686219242967, 0.43365781290341954, 0.5480208239248364]\n",
-      "Epoch:  275\n",
-      "Epoch:  [0.3815574491826396, 0.4564493277155797, 0.5557274648847146]\n",
-      "Epoch:  276\n",
-      "Epoch:  [0.34483700469818296, 0.4414874821027348, 0.5469944956235743]\n",
-      "Epoch:  277\n",
-      "Epoch:  [0.36818297823684615, 0.48638266706132305, 0.5593487709290811]\n",
-      "Epoch:  278\n",
-      "Epoch:  [0.31490475280592195, 0.49147575599875726, 0.5644725056174602]\n",
-      "Epoch:  279\n",
-      "Epoch:  [0.34620464302083465, 0.5145674247972782, 0.5751187316335916]\n",
-      "Epoch:  280\n",
-      "Epoch:  [0.3569905388146751, 0.4971708605589565, 0.5683648192921419]\n",
-      "Epoch:  281\n",
-      "Epoch:  [0.3115773835224516, 0.5141815833273957, 0.5734201951595485]\n",
-      "Epoch:  282\n",
-      "Epoch:  [0.3128702896985598, 0.5039492040511399, 0.5646777430069813]\n",
-      "Epoch:  283\n",
-      "Epoch:  [0.3481266032883904, 0.4708228703857823, 0.5630876019110045]\n",
-      "Epoch:  284\n",
-      "Epoch:  [0.31563310733261274, 0.510210550905928, 0.5817384985323745]\n",
-      "Epoch:  285\n",
-      "Epoch:  [0.3394154844406039, 0.5056292406767829, 0.5740113801518408]\n",
-      "Epoch:  286\n",
-      "Epoch:  [0.31289538274773293, 0.5365611429269942, 0.593092073759026]\n",
-      "Epoch:  287\n",
-      "Epoch:  [0.31367351907830215, 0.5388672430214401, 0.5957452500402277]\n",
-      "Epoch:  288\n",
-      "Epoch:  [0.30415028023158014, 0.5304000791435243, 0.5766506694536709]\n",
-      "Epoch:  289\n",
-      "Epoch:  [0.33343076139618544, 0.5302894374738982, 0.5830261256383186]\n",
-      "Epoch:  290\n",
-      "Epoch:  [0.25837029049560356, 0.5479776116590783, 0.6071255291004511]\n",
-      "Epoch:  291\n",
-      "Epoch:  [0.29677121889646885, 0.5628394722377867, 0.5967107814265927]\n",
-      "Epoch:  292\n",
-      "Epoch:  [0.3064487723104714, 0.5572379808160829, 0.5898296877690138]\n",
-      "Epoch:  293\n",
-      "Epoch:  [0.31404803979954504, 0.5503274760469347, 0.5954161471552942]\n",
-      "Epoch:  294\n",
-      "Epoch:  [0.3174653429303191, 0.5278045980288395, 0.5494384335114951]\n",
-      "Epoch:  295\n",
-      "Epoch:  [0.32722005038318974, 0.5437043534293442, 0.5648001746499648]\n",
-      "Epoch:  296\n",
-      "Epoch:  [0.3667453451499208, 0.566017295355446, 0.5574552093771892]\n",
-      "Epoch:  297\n",
-      "Epoch:  [0.3441614092641278, 0.56926542739831, 0.5715808726863489]\n",
-      "Epoch:  298\n",
-      "Epoch:  [0.3673733928991519, 0.5484884753867779, 0.6039470853310498]\n",
-      "Epoch:  299\n",
-      "Epoch:  [0.34761607836673747, 0.5452580208358626, 0.5720887629217253]\n",
-      "Epoch:  300\n",
-      "Epoch:  [0.3642930194387926, 0.5491437129437093, 0.586098749937761]\n",
-      "Epoch:  301\n",
-      "Epoch:  [0.3565124436302316, 0.5664477806429545, 0.5975556981268985]\n",
-      "Epoch:  302\n",
-      "Epoch:  [0.3479207042175505, 0.5541086292506235, 0.5704113623179052]\n",
-      "Epoch:  303\n",
-      "Epoch:  [0.3809164908900196, 0.5414329129476384, 0.5686421288702328]\n",
-      "Epoch:  304\n",
-      "Epoch:  [0.36885582587699267, 0.4984835810782501, 0.5567277110352825]\n",
-      "Epoch:  305\n",
-      "Epoch:  [0.3680557104592698, 0.5364483053979079, 0.580418802957994]\n",
-      "Epoch:  306\n",
-      "Epoch:  [0.4005130552901088, 0.5850222031586733, 0.5960650988240168]\n",
-      "Epoch:  307\n",
-      "Epoch:  [0.37367735805460983, 0.583898066870412, 0.6112160446651301]\n",
-      "Epoch:  308\n",
-      "Epoch:  [0.4269738228380748, 0.5966201791873964, 0.5884813817756143]\n",
-      "Epoch:  309\n",
-      "Epoch:  [0.3815920531525474, 0.5582610697667425, 0.5825444381746874]\n",
-      "Epoch:  310\n",
-      "Epoch:  [0.39833816563952695, 0.5686833623652818, 0.5583237568265029]\n",
-      "Epoch:  311\n",
-      "Epoch:  [0.4010681819034901, 0.5723485043892186, 0.5828328654030959]\n",
-      "Epoch:  312\n",
-      "Epoch:  [0.39852013434187533, 0.5534798191222847, 0.571114083735836]\n",
-      "Epoch:  313\n",
-      "Epoch:  [0.3019132443808428, 0.5165831422108697, 0.570655165200547]\n",
-      "Epoch:  314\n",
-      "Epoch:  [0.38451138535581175, 0.5351399202465961, 0.5616280201833688]\n",
-      "Epoch:  315\n",
-      "Epoch:  [0.42313562412266226, 0.5633769430103402, 0.5790887725673692]\n",
-      "Epoch:  316\n",
-      "Epoch:  [0.3911427344752601, 0.5697612875150734, 0.5984896430489935]\n",
-      "Epoch:  317\n",
-      "Epoch:  [0.38294269022388394, 0.5547539271682999, 0.5809350761906115]\n",
-      "Epoch:  318\n",
-      "Epoch:  [0.44802182220374126, 0.588001703261693, 0.5913763956945468]\n",
-      "Epoch:  319\n",
-      "Epoch:  [0.4783382869216287, 0.5754306619195874, 0.595839280010503]\n",
-      "Epoch:  320\n",
-      "Epoch:  [0.4894457441280694, 0.5517570606655562, 0.5424701225548749]\n",
-      "Epoch:  321\n",
-      "Epoch:  [0.4924432454027253, 0.5467048916366988, 0.5432558724484035]\n",
-      "Epoch:  322\n",
-      "Epoch:  [0.527000989288011, 0.5846662117983841, 0.5684792903851548]\n",
-      "Epoch:  323\n",
-      "Epoch:  [0.4847958911640736, 0.569848131612312, 0.5616904168395699]\n",
-      "Epoch:  324\n",
-      "Epoch:  [0.519530733941954, 0.5612584447168137, 0.5720281426018762]\n",
-      "Epoch:  325\n",
-      "Epoch:  [0.553768334213567, 0.5951436525287221, 0.5818826639243209]\n",
-      "Epoch:  326\n",
-      "Epoch:  [0.5412971668128302, 0.5568274975487026, 0.5321140826578986]\n",
-      "Epoch:  327\n",
-      "Epoch:  [0.5671556090394845, 0.5755772676331535, 0.6005060952256156]\n",
-      "Epoch:  328\n",
-      "Epoch:  [0.5408108610059249, 0.5520576350096967, 0.5514501781855056]\n",
-      "Epoch:  329\n",
-      "Epoch:  [0.5353753525944142, 0.5729012512970816, 0.5858700696412943]\n",
-      "Epoch:  330\n",
-      "Epoch:  [0.5590119716532895, 0.584816941117539, 0.5888676195983407]\n",
-      "Epoch:  331\n",
-      "Epoch:  [0.5623717310928472, 0.5846582373003091, 0.5915572811303413]\n",
-      "Epoch:  332\n",
-      "Epoch:  [0.5806246938979686, 0.5890222708904436, 0.5812334699644706]\n",
-      "Epoch:  333\n",
-      "Epoch:  [0.5242386941211997, 0.5722978553254358, 0.5816220858576086]\n",
-      "Epoch:  334\n",
-      "Epoch:  [0.5396996853510085, 0.5865889961098956, 0.5756416785167071]\n",
-      "Epoch:  335\n",
-      "Epoch:  [0.574034168981653, 0.5952230230328696, 0.5943998526161135]\n",
-      "Epoch:  336\n",
-      "Epoch:  [0.5445648203553036, 0.5413839231536737, 0.5567260702611053]\n",
-      "Epoch:  337\n",
-      "Epoch:  [0.5554627016181358, 0.5962187697402322, 0.6047065492306172]\n",
-      "Epoch:  338\n",
-      "Epoch:  [0.5513030724115305, 0.5618403157626499, 0.5577232687877783]\n",
-      "Epoch:  339\n",
-      "Epoch:  [0.5497689393280787, 0.5489453063398241, 0.53660666120236]\n",
-      "Epoch:  340\n",
-      "Epoch:  [0.5431367128474354, 0.5470079939782824, 0.5309589266743113]\n",
-      "Epoch:  341\n",
-      "Epoch:  [0.5601042062162341, 0.5632048314894765, 0.558238422818738]\n",
-      "Epoch:  342\n",
-      "Epoch:  [0.5617845356976638, 0.585990203627104, 0.5808343382267025]\n",
-      "Epoch:  343\n",
-      "Epoch:  [0.554302062735905, 0.5748671518845936, 0.593273218497101]\n",
-      "Epoch:  344\n",
-      "Epoch:  [0.5374201644778878, 0.55940016206268, 0.5543724590363731]\n",
-      "Epoch:  345\n",
-      "Epoch:  [0.5532626587365003, 0.5508431246062776, 0.5355394236658219]\n",
-      "Epoch:  346\n",
-      "Epoch:  [0.544261622189963, 0.5509778268767619, 0.5522119795761338]\n",
-      "Epoch:  347\n",
-      "Epoch:  [0.536115823807476, 0.5446865722854896, 0.5590432934547706]\n",
-      "Epoch:  348\n",
-      "Epoch:  [0.5558177822564057, 0.5682584086669976, 0.5675462079607363]\n",
-      "Epoch:  349\n",
-      "Epoch:  [0.5555839748325002, 0.5712129390028889, 0.5928949854238129]\n",
-      "Epoch:  350\n",
-      "Epoch:  [0.5632631682956508, 0.5885125651627574, 0.5888787823221914]\n",
-      "Epoch:  351\n",
-      "Epoch:  [0.583987525938093, 0.5573237952214749, 0.5482869956369755]\n",
-      "Epoch:  352\n",
-      "Epoch:  [0.5807113462501666, 0.6278040441278742, 0.6082030757558441]\n",
-      "Epoch:  353\n",
-      "Epoch:  [0.5705581362775446, 0.5853315055804005, 0.5729687185115543]\n",
-      "Epoch:  354\n",
-      "Epoch:  [0.5367152320951281, 0.5527933864989757, 0.5296869546478399]\n",
-      "Epoch:  355\n",
-      "Epoch:  [0.5601361168632802, 0.5237316370356998, 0.4985218350693306]\n",
-      "Epoch:  356\n",
-      "Epoch:  [0.5849513498723237, 0.5499574211434216, 0.5184227631843648]\n",
-      "Epoch:  357\n",
-      "Epoch:  [0.5479840458903914, 0.5632119893608428, 0.5485603965728356]\n",
-      "Epoch:  358\n",
-      "Epoch:  [0.5295811646887684, 0.4900860492797694, 0.44243129411800286]\n",
-      "Epoch:  359\n",
-      "Epoch:  [0.5417189766179538, 0.5580613493664252, 0.5179531494702224]\n",
-      "Epoch:  360\n",
-      "Epoch:  [0.41728324410736745, 0.4723734784010582, 0.5377693595354391]\n",
-      "Epoch:  361\n",
-      "Epoch:  [0.5524943977474706, 0.5421037415747334, 0.5254662151622251]\n",
-      "Epoch:  362\n",
-      "Epoch:  [0.5477234837292106, 0.5075145006276122, 0.44893480269329156]\n",
-      "Epoch:  363\n",
-      "Epoch:  [0.5822709715515505, 0.5696288390602345, 0.540072593160116]\n",
-      "Epoch:  364\n",
-      "Epoch:  [0.5284962238750333, 0.5072738577511359, 0.44783752617204586]\n",
-      "Epoch:  365\n",
-      "Epoch:  [0.5355203231423559, 0.5387020259067002, 0.5351279803004177]\n",
-      "Epoch:  366\n",
-      "Epoch:  [0.554167319697683, 0.5557413071153188, 0.5144984212128816]\n",
-      "Epoch:  367\n",
-      "Epoch:  [0.5384588396957464, 0.48396793341220196, 0.4194520962640457]\n",
-      "Epoch:  368\n",
-      "Epoch:  [0.5061588456965608, 0.44611361266991806, 0.37594219938797685]\n",
-      "Epoch:  369\n",
-      "Epoch:  [0.5573857781019907, 0.5129153832509801, 0.4970369345452777]\n",
-      "Epoch:  370\n",
-      "Epoch:  [0.5804883311690802, 0.5466881930605372, 0.4940359717205122]\n",
-      "Epoch:  371\n",
-      "Epoch:  [0.5350504512847359, 0.5253666684154185, 0.5032529529772868]\n",
-      "Epoch:  372\n",
-      "Epoch:  [0.5341469076827713, 0.5204448628442367, 0.505518693618671]\n",
-      "Epoch:  373\n",
-      "Epoch:  [0.5477170707976186, 0.5478875571741564, 0.5117502015919039]\n",
-      "Epoch:  374\n",
-      "Epoch:  [0.5151490514569182, 0.48102346714775945, 0.42658800380589]\n",
-      "Epoch:  375\n",
-      "Epoch:  [0.5077621765823026, 0.45389212236851106, 0.40398449141726533]\n",
-      "Epoch:  376\n",
-      "Epoch:  [0.5481176256989811, 0.5415334082624601, 0.5175745059194304]\n",
-      "Epoch:  377\n",
-      "Epoch:  [0.515712074175117, 0.5109065585627706, 0.4808572720159627]\n",
-      "Epoch:  378\n",
-      "Epoch:  [0.5608225313319054, 0.5211765490333577, 0.5027437676561677]\n",
-      "Epoch:  379\n",
-      "Epoch:  [0.5385213500344955, 0.49818282573101186, 0.4335242875517648]\n",
-      "Epoch:  380\n",
-      "Epoch:  [0.5674928806486976, 0.5243369232721754, 0.4997140323864007]\n",
-      "Epoch:  381\n",
-      "Epoch:  [0.5201130862762933, 0.5183474167449607, 0.48571125430342316]\n",
-      "Epoch:  382\n",
-      "Epoch:  [0.5521546591038623, 0.4952205576250228, 0.45156324620951105]\n",
-      "Epoch:  383\n",
-      "Epoch:  [0.542784399263025, 0.5313395101161801, 0.5249280766953511]\n",
-      "Epoch:  384\n",
-      "Epoch:  [0.5266935785276325, 0.4765720993397808, 0.4326571907370423]\n",
-      "Epoch:  385\n",
-      "Epoch:  [0.5418598649720845, 0.495358438966562, 0.4230611936013825]\n",
-      "Epoch:  386\n",
-      "Epoch:  [0.5780921337233136, 0.5518968230625997, 0.537825021339255]\n",
-      "Epoch:  387\n",
-      "Epoch:  [0.5291396976360864, 0.48827135835192814, 0.43864584287395947]\n",
-      "Epoch:  388\n",
-      "Epoch:  [0.5554851571635344, 0.5085284239822425, 0.4634513044679591]\n",
-      "Epoch:  389\n",
-      "Epoch:  [0.48662482189362377, 0.4057219660451619, 0.31271974821067416]\n",
-      "Epoch:  390\n",
-      "Epoch:  [0.5242821694718153, 0.4568567785080642, 0.3876836905483909]\n",
-      "Epoch:  391\n",
-      "Epoch:  [0.5430159492955811, 0.5343522766294628, 0.5098953623721858]\n",
-      "Epoch:  392\n",
-      "Epoch:  [0.5581761671049099, 0.4881703939145529, 0.4544254001086211]\n",
-      "Epoch:  393\n",
-      "Epoch:  [0.5417568804588778, 0.5279844976430943, 0.5018263721381151]\n",
-      "Epoch:  394\n",
-      "Epoch:  [0.5329804919497272, 0.4969832381472215, 0.4879005652584289]\n",
-      "Epoch:  395\n",
-      "Epoch:  [0.5395812445460265, 0.5090712335908127, 0.4747259511009407]\n",
-      "Epoch:  396\n",
-      "Epoch:  [0.5250318310786471, 0.4969404631971487, 0.43684383958448586]\n",
-      "Epoch:  397\n",
-      "Epoch:  [0.5421844606694441, 0.5171396008789376, 0.4802285027009556]\n",
-      "Epoch:  398\n",
-      "Epoch:  [0.4679060065108023, 0.43409402476122944, 0.3673062020929787]\n",
-      "Epoch:  399\n",
-      "Epoch:  [0.5455779636094279, 0.5037674381960553, 0.43359100816230656]\n",
-      "Epoch:  400\n",
-      "Epoch:  [0.5182497707496707, 0.4512721015325554, 0.37638871190549167]\n",
-      "Epoch:  401\n",
-      "Epoch:  [0.5221165057277085, 0.5136467493064503, 0.4887460934043196]\n",
-      "Epoch:  402\n",
-      "Epoch:  [0.51419521140462, 0.4521166367397474, 0.4011176886877471]\n",
-      "Epoch:  403\n",
-      "Epoch:  [0.5469773468031117, 0.49681749681757525, 0.4643944107609293]\n",
-      "Epoch:  404\n",
-      "Epoch:  [0.5605241175508302, 0.514750473084885, 0.4781470901301924]\n",
-      "Epoch:  405\n",
-      "Epoch:  [0.5062818824087804, 0.4253947285620771, 0.3395678848621229]\n",
-      "Epoch:  406\n",
-      "Epoch:  [0.516947654447001, 0.4479022416405012, 0.37058113906813117]\n",
-      "Epoch:  407\n",
-      "Epoch:  [0.5123105721237347, 0.4745187869064264, 0.4137803348765127]\n",
-      "Epoch:  408\n",
-      "Epoch:  [0.5212665927322048, 0.44213695757774224, 0.3733357659032472]\n",
-      "Epoch:  409\n",
-      "Epoch:  [0.5143543219117166, 0.4362942993766537, 0.3658396383839783]\n",
-      "Epoch:  410\n",
-      "Epoch:  [0.5476586456001826, 0.49166138958185057, 0.43999584622681714]\n",
-      "Epoch:  411\n",
-      "Epoch:  [0.5145631214393177, 0.49624823564998594, 0.4649639501903992]\n",
-      "Epoch:  412\n",
-      "Epoch:  [0.50870071866397, 0.46778915445663577, 0.41056426924967315]\n",
-      "Epoch:  413\n",
-      "Epoch:  [0.5083410272263111, 0.4497477070510291, 0.38631700871188357]\n",
-      "Epoch:  414\n",
-      "Epoch:  [0.48101323327538137, 0.3957230669565741, 0.32434760657783834]\n",
-      "Epoch:  415\n",
-      "Epoch:  [0.47302930722073877, 0.3916531874963423, 0.3265548905028386]\n",
-      "Epoch:  416\n",
-      "Epoch:  [0.5178534112071482, 0.45353033864596054, 0.3656581708748177]\n",
-      "Epoch:  417\n",
-      "Epoch:  [0.5360854206654774, 0.440277109154824, 0.4010913066343977]\n",
-      "Epoch:  418\n",
-      "Epoch:  [0.5163498748424061, 0.4451317948205976, 0.38102279402353695]\n",
-      "Epoch:  419\n",
-      "Epoch:  [0.48664833815866637, 0.39963940215245436, 0.32641131734543427]\n",
-      "Epoch:  420\n",
-      "Epoch:  [0.47144673182231067, 0.40577884394169456, 0.3289834267011526]\n",
-      "Epoch:  421\n",
-      "Epoch:  [0.4996587855030385, 0.4351325376784406, 0.3731220530512064]\n",
-      "Epoch:  422\n",
-      "Epoch:  [0.5355378819329784, 0.44994799386987416, 0.3630662884131108]\n",
-      "Epoch:  423\n",
-      "Epoch:  [0.506307743422281, 0.4493003281916101, 0.38401419209889365]\n",
-      "Epoch:  424\n",
-      "Epoch:  [0.4783692896204149, 0.427321087760705, 0.36154641199531573]\n",
-      "Epoch:  425\n",
-      "Epoch:  [0.48428240023617447, 0.39716092061758174, 0.3398503454809997]\n",
-      "Epoch:  426\n",
-      "Epoch:  [0.47243365606809606, 0.39494831309869194, 0.3338993399804177]\n",
-      "Epoch:  427\n",
-      "Epoch:  [0.5322546470726456, 0.43107829051426944, 0.37923019011641607]\n",
-      "Epoch:  428\n",
-      "Epoch:  [0.5171941867650126, 0.46396863144976813, 0.41968501029825334]\n",
-      "Epoch:  429\n",
-      "Epoch:  [0.5306517727099922, 0.4644045193324666, 0.4091390141467828]\n",
-      "Epoch:  430\n",
-      "Epoch:  [0.47704727277803816, 0.4115008043882213, 0.36192108619053504]\n",
-      "Epoch:  431\n",
-      "Epoch:  [0.5253495329979609, 0.4631195851562107, 0.40753458015751987]\n",
-      "Epoch:  432\n",
-      "Epoch:  [0.47807380185242143, 0.4112141656934895, 0.33463391111820673]\n",
-      "Epoch:  433\n",
-      "Epoch:  [0.5014954675884503, 0.4095646095166133, 0.3464292339320829]\n",
-      "Epoch:  434\n",
-      "Epoch:  [0.4988940750302237, 0.4413941451486878, 0.36876957298995394]\n",
-      "Epoch:  435\n",
-      "Epoch:  [0.4710770317633326, 0.3987128259703927, 0.3474399039058797]\n",
-      "Epoch:  436\n",
-      "Epoch:  [0.528545956503102, 0.4234356556902443, 0.3334212084602601]\n",
-      "Epoch:  437\n",
-      "Epoch:  [0.5299243030749261, 0.45490562443828664, 0.40275809727785616]\n",
-      "Epoch:  438\n",
-      "Epoch:  [0.5213174485749713, 0.46795674316632335, 0.40265427623638156]\n",
-      "Epoch:  439\n",
-      "Epoch:  [0.5149197032243152, 0.4306841479935399, 0.372021903048678]\n",
-      "Epoch:  440\n",
-      "Epoch:  [0.5149764640915749, 0.43496214319176046, 0.36509527677158615]\n",
-      "Epoch:  441\n",
-      "Epoch:  [0.4801453193916166, 0.4067652760321457, 0.33006465139287383]\n",
-      "Epoch:  442\n",
-      "Epoch:  [0.5121839786436411, 0.4393151704397713, 0.36732596059253875]\n",
-      "Epoch:  443\n",
-      "Epoch:  [0.45446829302678876, 0.39491684973105, 0.32116236052118147]\n",
-      "Epoch:  444\n",
-      "Epoch:  [0.5063047469182822, 0.41462019407512385, 0.3372818617919009]\n",
-      "Epoch:  445\n",
-      "Epoch:  [0.5078347802059593, 0.435382799467275, 0.3779563253074451]\n",
-      "Epoch:  446\n",
-      "Epoch:  [0.450615347822457, 0.36782361291909144, 0.2671835576434518]\n",
-      "Epoch:  447\n",
-      "Epoch:  [0.49448918962367205, 0.4220419276327642, 0.3753311529509313]\n",
-      "Epoch:  448\n",
-      "Epoch:  [0.5008717052978136, 0.39499256863745325, 0.34925873026726717]\n",
-      "Epoch:  449\n",
-      "Epoch:  [0.5053702633442206, 0.4109051297075058, 0.3812604726176378]\n",
-      "Epoch:  450\n",
-      "Epoch:  [0.45657091722909, 0.3818392239908298, 0.298658346132061]\n",
-      "Epoch:  451\n",
-      "Epoch:  [0.4992951759430339, 0.4224958038207412, 0.3623888237611793]\n",
-      "Epoch:  452\n",
-      "Epoch:  [0.5134727123954167, 0.44211424596434296, 0.4123152186014109]\n",
-      "Epoch:  453\n",
-      "Epoch:  [0.5301573896617454, 0.47116322213835493, 0.4108309334677885]\n",
-      "Epoch:  454\n",
-      "Epoch:  [0.5031704755564804, 0.43639937582409977, 0.3796441010577224]\n",
-      "Epoch:  455\n",
-      "Epoch:  [0.4825661347303664, 0.4095599061961718, 0.3618443310172192]\n",
-      "Epoch:  456\n",
-      "Epoch:  [0.4957398203142335, 0.3823335731293085, 0.325683418927776]\n",
-      "Epoch:  457\n",
-      "Epoch:  [0.49952929716871114, 0.4297012778802604, 0.3789120934906671]\n",
-      "Epoch:  458\n",
-      "Epoch:  [0.5085517932420829, 0.4116352504877456, 0.3583604425049577]\n",
-      "Epoch:  459\n",
-      "Epoch:  [0.5173301255953905, 0.47249041451839535, 0.4172379567663079]\n",
-      "Epoch:  460\n",
-      "Epoch:  [0.5137506146221416, 0.4398753052461957, 0.40577214358216973]\n",
-      "Epoch:  461\n",
-      "Epoch:  [0.4666051399559523, 0.34335860479094543, 0.2570575863695692]\n",
-      "Epoch:  462\n",
-      "Epoch:  [0.47363837270608405, 0.39806485823026855, 0.34452969672364425]\n",
-      "Epoch:  463\n",
-      "Epoch:  [0.48359052821636433, 0.3789657927549692, 0.3305963877704537]\n",
-      "Epoch:  464\n",
-      "Epoch:  [0.4286012456586036, 0.3443928524765492, 0.30347027290510875]\n",
-      "Epoch:  465\n",
-      "Epoch:  [0.5001134782441863, 0.4265304459017543, 0.37520685645895]\n",
-      "Epoch:  466\n",
-      "Epoch:  [0.4663012692669235, 0.403887342875876, 0.3656691613165391]\n",
-      "Epoch:  467\n",
-      "Epoch:  [0.4733499870862231, 0.4090471453371452, 0.3582324251816776]\n",
-      "Epoch:  468\n",
-      "Epoch:  [0.4649030501121378, 0.37973770927517864, 0.34667487225501603]\n",
-      "Epoch:  469\n",
-      "Epoch:  [0.48661022285405614, 0.41679013150212446, 0.3706494180330595]\n",
-      "Epoch:  470\n",
-      "Epoch:  [0.4842062040605654, 0.4321092121087852, 0.3948085441841953]\n",
-      "Epoch:  471\n",
-      "Epoch:  [0.48107173000968967, 0.4155358143963975, 0.40752953719941143]\n",
-      "Epoch:  472\n",
-      "Epoch:  [0.4873257237633049, 0.4318623615708374, 0.40126575292308797]\n",
-      "Epoch:  473\n",
-      "Epoch:  [0.48115171976145077, 0.422939333190984, 0.39551157139901966]\n",
-      "Epoch:  474\n",
-      "Epoch:  [0.5049052873511332, 0.4531775789510142, 0.4302335093269765]\n",
-      "Epoch:  475\n",
-      "Epoch:  [0.4442338879004083, 0.38668687030907456, 0.3409646692078496]\n",
-      "Epoch:  476\n",
-      "Epoch:  [0.4935292779978175, 0.4428355548635594, 0.39739554549911926]\n",
-      "Epoch:  477\n",
-      "Epoch:  [0.4576776605364845, 0.38238666252701964, 0.3257810261275598]\n",
-      "Epoch:  478\n",
-      "Epoch:  [0.4286019331591418, 0.35980910873130745, 0.32403986667732687]\n",
-      "Epoch:  479\n",
-      "Epoch:  [0.4909827855577231, 0.4332488638179755, 0.400774084677207]\n",
-      "Epoch:  480\n",
-      "Epoch:  [0.48155716395341996, 0.42537650761158613, 0.3810532002664415]\n",
-      "Epoch:  481\n",
-      "Epoch:  [0.46427094900457605, 0.4025130900140159, 0.358698741993224]\n",
-      "Epoch:  482\n",
-      "Epoch:  [0.4432569903134812, 0.4064641876425158, 0.3636164678110377]\n",
-      "Epoch:  483\n",
-      "Epoch:  [0.4807138630624473, 0.4093759639712551, 0.37565491765356457]\n",
-      "Epoch:  484\n",
-      "Epoch:  [0.4616983458074427, 0.3665179979564096, 0.35033482603989946]\n",
-      "Epoch:  485\n",
-      "Epoch:  [0.44846543949842277, 0.3515334197337756, 0.28590059836279147]\n",
-      "Epoch:  486\n",
-      "Epoch:  [0.4711808097931806, 0.44014243435561545, 0.41534062657917287]\n",
-      "Epoch:  487\n",
-      "Epoch:  [0.3855733377730886, 0.32148370676460014, 0.27048731102934603]\n",
-      "Epoch:  488\n",
-      "Epoch:  [0.44433868301980534, 0.3740944853388772, 0.3121711490623122]\n",
-      "Epoch:  489\n",
-      "Epoch:  [0.44052216581812925, 0.36883683085495905, 0.33525258940842884]\n",
-      "Epoch:  490\n",
-      "Epoch:  [0.4496478053726847, 0.4145701150344711, 0.37691599058815756]\n",
-      "Epoch:  491\n",
-      "Epoch:  [0.47132890433491786, 0.4108462157253974, 0.3781109099464352]\n",
-      "Epoch:  492\n",
-      "Epoch:  [0.5035563748552546, 0.40800019181477026, 0.3370990570430573]\n",
-      "Epoch:  493\n",
-      "Epoch:  [0.40829970453932, 0.34096046997646434, 0.30608348038682137]\n",
-      "Epoch:  494\n",
-      "Epoch:  [0.42898379800483, 0.3527273380587559, 0.31919938383722424]\n",
-      "Epoch:  495\n",
-      "Epoch:  [0.5173983959123516, 0.4543939786212976, 0.4303629730805967]\n",
-      "Epoch:  496\n",
-      "Epoch:  [0.49698452021739403, 0.4544182571018213, 0.43370327868343506]\n",
-      "Epoch:  497\n",
-      "Epoch:  [0.44425189507065943, 0.4026380291968604, 0.3712497885246703]\n",
-      "Epoch:  498\n",
-      "Epoch:  [0.44614882096840786, 0.42310051720891323, 0.4103227367298179]\n",
-      "Epoch:  499\n",
-      "Epoch:  [0.47846286391649523, 0.4188101410526209, 0.3597874697671057]\n",
-      "Epoch:  500\n",
-      "Epoch:  [0.4649585022599586, 0.4122004130541959, 0.39189904975371465]\n",
-      "Epoch:  501\n",
-      "Epoch:  [0.45698096329932025, 0.4036138477795471, 0.358664454673902]\n",
-      "Epoch:  502\n",
-      "Epoch:  [0.42140637343438375, 0.35964127764602105, 0.31174982246004734]\n",
-      "Epoch:  503\n",
-      "Epoch:  [0.43259113988914716, 0.3428727124273288, 0.2973155767788005]\n",
-      "Epoch:  504\n",
-      "Epoch:  [0.4063730570122658, 0.354233044422174, 0.3199935212818376]\n",
-      "Epoch:  505\n",
-      "Epoch:  [0.4377251751240311, 0.3484505382887568, 0.2976405732051291]\n",
-      "Epoch:  506\n",
-      "Epoch:  [0.43677861077024754, 0.37590324359281524, 0.3443639707439184]\n",
-      "Epoch:  507\n",
-      "Epoch:  [0.4472314636567612, 0.3650373424971942, 0.30968988333998093]\n",
-      "Epoch:  508\n",
-      "Epoch:  [0.45984315405121895, 0.4113234893826066, 0.37343561312001994]\n",
-      "Epoch:  509\n",
-      "Epoch:  [0.42293922083094176, 0.36042070751688876, 0.33104300330081426]\n",
-      "Epoch:  510\n",
-      "Epoch:  [0.4130874104165157, 0.34349330454921595, 0.30948132351997676]\n",
-      "Epoch:  511\n",
-      "Epoch:  [0.4416815981593955, 0.4017830279793858, 0.36368661547024733]\n",
-      "Epoch:  512\n",
-      "Epoch:  [0.4198032818928782, 0.33303444385961134, 0.31592941606250996]\n",
-      "Epoch:  513\n",
-      "Epoch:  [0.38733174121105834, 0.34649129825607505, 0.32573906997064844]\n",
-      "Epoch:  514\n",
-      "Epoch:  [0.4138756208207355, 0.35855609653586473, 0.31602150649920757]\n",
-      "Epoch:  515\n",
-      "Epoch:  [0.501008707719325, 0.4680845169443887, 0.4384667187539249]\n",
-      "Epoch:  516\n",
-      "Epoch:  [0.4185960104561258, 0.3464652189590309, 0.32936871610011814]\n",
-      "Epoch:  517\n",
-      "Epoch:  [0.42093045250603517, 0.34356923541338, 0.3189976184583616]\n",
-      "Epoch:  518\n",
-      "Epoch:  [0.40905405967907793, 0.338563462587486, 0.29546437753955823]\n",
-      "Epoch:  519\n",
-      "Epoch:  [0.40745105720742, 0.36209990202097436, 0.36576912334505934]\n",
-      "Epoch:  520\n",
-      "Epoch:  [0.4023939716554956, 0.3329511950516338, 0.29978416325202056]\n",
-      "Epoch:  521\n",
-      "Epoch:  [0.4341634818525779, 0.39662823837061445, 0.36008479075932226]\n",
-      "Epoch:  522\n",
-      "Epoch:  [0.38860847650286057, 0.3685785380863088, 0.3375212602079284]\n",
-      "Epoch:  523\n",
-      "Epoch:  [0.3947001335820595, 0.3460008660760505, 0.3261927567615771]\n",
-      "Epoch:  524\n",
-      "Epoch:  [0.4239632710828655, 0.400384634193045, 0.3809155220770956]\n",
-      "Epoch:  525\n",
-      "Epoch:  [0.4374646221868866, 0.39157653757807875, 0.3745358618494114]\n",
-      "Epoch:  526\n",
-      "Epoch:  [0.421497731963498, 0.376135391313251, 0.37118565431481065]\n",
-      "Epoch:  527\n",
-      "Epoch:  [0.4109944286441836, 0.3837261084331662, 0.36116707752784216]\n",
-      "Epoch:  528\n",
-      "Epoch:  [0.431450674335184, 0.3960563401886845, 0.38147944322307364]\n",
-      "Epoch:  529\n",
-      "Epoch:  [0.4338645940872871, 0.3600155243317636, 0.35907303475123453]\n",
-      "Epoch:  530\n",
-      "Epoch:  [0.398585606470904, 0.3577416060689465, 0.33252287925587515]\n",
-      "Epoch:  531\n",
-      "Epoch:  [0.4016944453111154, 0.3630839207061262, 0.3383074189775445]\n",
-      "Epoch:  532\n",
-      "Epoch:  [0.4243330795923615, 0.4035623625211598, 0.36178518557038536]\n",
-      "Epoch:  533\n",
-      "Epoch:  [0.4022675993779503, 0.3494327029764164, 0.3547164363173756]\n",
-      "Epoch:  534\n",
-      "Epoch:  [0.46272513371347285, 0.41757076870812965, 0.41115157663135077]\n",
-      "Epoch:  535\n",
-      "Epoch:  [0.4003457583905312, 0.3562645645333242, 0.3427591749149403]\n",
-      "Epoch:  536\n",
-      "Epoch:  [0.40392608441242583, 0.39769583881897247, 0.39852511270661223]\n",
-      "Epoch:  537\n",
-      "Epoch:  [0.37436545005184146, 0.32075363888993214, 0.29439708815171334]\n",
-      "Epoch:  538\n",
-      "Epoch:  [0.4540557239798447, 0.44035767694671235, 0.44009589799205434]\n",
-      "Epoch:  539\n",
-      "Epoch:  [0.35639026490248155, 0.3121915082394089, 0.26447593244635714]\n",
-      "Epoch:  540\n",
-      "Epoch:  [0.39700209890866056, 0.3591518301842004, 0.33448879163123385]\n",
-      "Epoch:  541\n",
-      "Epoch:  [0.358774483122748, 0.2966930122097729, 0.27312023853407885]\n",
-      "Epoch:  542\n",
-      "Epoch:  [0.38113859406754935, 0.32435531502603066, 0.27593620005779307]\n",
-      "Epoch:  543\n",
-      "Epoch:  [0.42715625060270507, 0.3894556955828688, 0.38647631912215935]\n",
-      "Epoch:  544\n",
-      "Epoch:  [0.4047349100153961, 0.36910636966987387, 0.35062598073207585]\n",
-      "Epoch:  545\n",
-      "Epoch:  [0.41637212003013724, 0.380927001584684, 0.3711656050570573]\n",
-      "Epoch:  546\n",
-      "Epoch:  [0.44302775508797737, 0.40505689640696735, 0.36671378372590224]\n",
-      "Epoch:  547\n",
-      "Epoch:  [0.3898452476072717, 0.3490098501839966, 0.35132835256028316]\n",
-      "Epoch:  548\n",
-      "Epoch:  [0.4269525945301401, 0.38346676543896696, 0.3624404384538721]\n",
-      "Epoch:  549\n",
-      "Epoch:  [0.40233261115988206, 0.3597082492330899, 0.33636895033007286]\n",
-      "Epoch:  550\n",
-      "Epoch:  [0.46711783960612946, 0.44917444340279516, 0.43607564779239855]\n",
-      "Epoch:  551\n",
-      "Epoch:  [0.42123854261672655, 0.364287790655654, 0.3698433017048502]\n",
-      "Epoch:  552\n",
-      "Epoch:  [0.41706594277708625, 0.36318083556292075, 0.3441173938617804]\n",
-      "Epoch:  553\n",
-      "Epoch:  [0.37751239898192196, 0.33615325191987155, 0.3067832045180392]\n",
-      "Epoch:  554\n",
-      "Epoch:  [0.4449929989642858, 0.41254749117815365, 0.3899490886625873]\n",
-      "Epoch:  555\n",
-      "Epoch:  [0.39907165246522847, 0.35499118561418747, 0.3510399732686195]\n",
-      "Epoch:  556\n",
-      "Epoch:  [0.41566564002971296, 0.3593884058031683, 0.33488945249602575]\n",
-      "Epoch:  557\n",
-      "Epoch:  [0.36908318549078356, 0.3313899998121652, 0.299151937244886]\n",
-      "Epoch:  558\n",
-      "Epoch:  [0.40652864411317857, 0.3918213136067167, 0.34616887113049166]\n",
-      "Epoch:  559\n",
-      "Epoch:  [0.37720287906892636, 0.3289214322503238, 0.2972903922332299]\n",
-      "Epoch:  560\n",
-      "Epoch:  [0.41858151266130217, 0.3645204692125338, 0.35275232316295774]\n",
-      "Epoch:  561\n",
-      "Epoch:  [0.380184557622753, 0.3337649164407724, 0.33007300145462953]\n",
-      "Epoch:  562\n",
-      "Epoch:  [0.40388964946030265, 0.38873209031736444, 0.3613791949228951]\n",
-      "Epoch:  563\n",
-      "Epoch:  [0.4302400112047652, 0.39207798727528076, 0.37093925544329676]\n",
-      "Epoch:  564\n",
-      "Epoch:  [0.43557132558156814, 0.3793585225536847, 0.38557377243648194]\n",
-      "Epoch:  565\n",
-      "Epoch:  [0.430050493383379, 0.3697842491562405, 0.3480691614233532]\n",
-      "Epoch:  566\n",
-      "Epoch:  [0.4520433349880375, 0.4226713653058273, 0.416065051654758]\n",
-      "Epoch:  567\n",
-      "Epoch:  [0.4073629169800288, 0.3634958139974692, 0.34780138289976886]\n",
-      "Epoch:  568\n",
-      "Epoch:  [0.3710890516160718, 0.33224037177648186, 0.3181507829179814]\n",
-      "Epoch:  569\n",
-      "Epoch:  [0.38474411239304057, 0.3459205408755458, 0.3414594276343806]\n",
-      "Epoch:  570\n",
-      "Epoch:  [0.4064058043643901, 0.3625686332082387, 0.35607988862790585]\n",
-      "Epoch:  571\n",
-      "Epoch:  [0.3905528989694758, 0.3573728873486571, 0.3642976521404717]\n",
-      "Epoch:  572\n",
-      "Epoch:  [0.38499307095571117, 0.3135396688377627, 0.3052549000784205]\n",
-      "Epoch:  573\n",
-      "Epoch:  [0.3621402181808124, 0.2998575992189634, 0.28262968857742793]\n",
-      "Epoch:  574\n",
-      "Epoch:  [0.4001830541427608, 0.34990281593196265, 0.3576721482927643]\n",
-      "Epoch:  575\n",
-      "Epoch:  [0.4117276057322702, 0.3640268583468758, 0.35997409061698576]\n",
-      "Epoch:  576\n",
-      "Epoch:  [0.3920368098571151, 0.34493146643496053, 0.32676945992280004]\n",
-      "Epoch:  577\n",
-      "Epoch:  [0.4109682612844153, 0.38271682444908567, 0.38886038560778075]\n",
-      "Epoch:  578\n",
-      "Epoch:  [0.3595325034170002, 0.34963728263439325, 0.3200352231282521]\n",
-      "Epoch:  579\n",
-      "Epoch:  [0.35998703007826405, 0.32649715445508226, 0.31489650701350863]\n",
-      "Epoch:  580\n",
-      "Epoch:  [0.4003175232688425, 0.35311355503045416, 0.34775544911469813]\n",
-      "Epoch:  581\n",
-      "Epoch:  [0.41043182514716503, 0.39115469809944586, 0.377861808999072]\n",
-      "Epoch:  582\n",
-      "Epoch:  [0.3752999678667959, 0.3248516174677454, 0.28988504107013396]\n",
-      "Epoch:  583\n",
-      "Epoch:  [0.39447392995400793, 0.3562409418876066, 0.33889398980777863]\n",
-      "Epoch:  584\n",
-      "Epoch:  [0.3742920836614399, 0.353934174638811, 0.347497174762904]\n",
-      "Epoch:  585\n",
-      "Epoch:  [0.37477117512989094, 0.33409991873087763, 0.32696502423313495]\n",
-      "Epoch:  586\n",
-      "Epoch:  [0.370119127476009, 0.34773998847651066, 0.33578097570231186]\n",
-      "Epoch:  587\n",
-      "Epoch:  [0.40344806328960314, 0.38061268008617166, 0.37280559443530387]\n",
-      "Epoch:  588\n",
-      "Epoch:  [0.3796077155296525, 0.3531877904747797, 0.36107865658524946]\n",
-      "Epoch:  589\n",
-      "Epoch:  [0.3764862709238848, 0.34902466953437883, 0.323487242312161]\n",
-      "Epoch:  590\n",
-      "Epoch:  [0.4182342052710938, 0.369543821423158, 0.3458223234788351]\n",
-      "Epoch:  591\n",
-      "Epoch:  [0.37915303720553384, 0.32035311134296873, 0.31201945743518017]\n",
-      "Epoch:  592\n",
-      "Epoch:  [0.40255921429978553, 0.3708664561403568, 0.3782642400377371]\n",
-      "Epoch:  593\n",
-      "Epoch:  [0.4591122489818949, 0.42566082572232017, 0.4042385165454867]\n",
-      "Epoch:  594\n",
-      "Epoch:  [0.4147341948405546, 0.37209230075343047, 0.3827951754562088]\n",
-      "Epoch:  595\n",
-      "Epoch:  [0.38639313172398304, 0.3654883134157871, 0.3701628158653474]\n",
-      "Epoch:  596\n",
-      "Epoch:  [0.4283358511346642, 0.3869725624735804, 0.3988441234697418]\n",
-      "Epoch:  597\n",
-      "Epoch:  [0.3421644332365717, 0.3086260853581749, 0.2962307245713662]\n",
-      "Epoch:  598\n",
-      "Epoch:  [0.33341464278911387, 0.26608576336721834, 0.25566104805949763]\n",
-      "Epoch:  599\n",
-      "Epoch:  [0.3636433814109611, 0.3263018024562085, 0.33151386358742374]\n",
-      "Epoch:  600\n",
-      "Epoch:  [0.3982296740897797, 0.3541110258151123, 0.36357109331394455]\n",
-      "Epoch:  601\n",
-      "Epoch:  [0.4168808641215857, 0.3768773237243256, 0.35652941988132686]\n",
-      "Epoch:  602\n",
-      "Epoch:  [0.34034696098792355, 0.2975107392147998, 0.27068892562343866]\n",
-      "Epoch:  603\n",
-      "Epoch:  [0.3730198674554892, 0.31857997070408467, 0.26981583589047825]\n",
-      "Epoch:  604\n",
-      "Epoch:  [0.3440509996807978, 0.29978414077142257, 0.27905299152137225]\n",
-      "Epoch:  605\n",
-      "Epoch:  [0.4008544056066936, 0.3496099488958561, 0.3318465462891003]\n",
-      "Epoch:  606\n",
-      "Epoch:  [0.4078044935558039, 0.35520884466559655, 0.3548468921791227]\n",
-      "Epoch:  607\n",
-      "Epoch:  [0.35572059371881054, 0.3206186162964263, 0.3194072583945284]\n",
-      "Epoch:  608\n",
-      "Epoch:  [0.3663698148751385, 0.34768524830910974, 0.36243492512869746]\n",
-      "Epoch:  609\n",
-      "Epoch:  [0.35829049716667255, 0.315101284099527, 0.29575803108801046]\n",
-      "Epoch:  610\n",
-      "Epoch:  [0.33398209311497457, 0.28703283723927403, 0.24502911477137776]\n",
-      "Epoch:  611\n",
-      "Epoch:  [0.3436212344668044, 0.2918850108069429, 0.30851113759853444]\n",
-      "Epoch:  612\n",
-      "Epoch:  [0.3390150432513582, 0.29291521938729653, 0.27008793538118786]\n",
-      "Epoch:  613\n",
-      "Epoch:  [0.3560667942552496, 0.3049127925334066, 0.2859562659073947]\n",
-      "Epoch:  614\n",
-      "Epoch:  [0.38576837674970405, 0.354106323927031, 0.3433156849230071]\n",
-      "Epoch:  615\n",
-      "Epoch:  [0.3749624825800764, 0.35779372009227417, 0.39660028728128477]\n",
-      "Epoch:  616\n",
-      "Epoch:  [0.35764589424279214, 0.32428525359665833, 0.31682135632645997]\n",
-      "Epoch:  617\n",
-      "Epoch:  [0.3774141159698057, 0.3234335054132297, 0.34714235255912174]\n",
-      "Epoch:  618\n",
-      "Epoch:  [0.43083133011638064, 0.4019643537857618, 0.3966454506193275]\n",
-      "Epoch:  619\n",
-      "Epoch:  [0.38676908201519444, 0.3381769957961124, 0.33973218086815443]\n",
-      "Epoch:  620\n",
-      "Epoch:  [0.3886935024840898, 0.3282568587568013, 0.3114837839404829]\n",
-      "Epoch:  621\n",
-      "Epoch:  [0.3302416765566051, 0.28056237186074934, 0.25923127808941293]\n",
-      "Epoch:  622\n",
-      "Epoch:  [0.381252320068673, 0.3434553703745524, 0.3274474307927846]\n",
-      "Epoch:  623\n",
-      "Epoch:  [0.40824199996985605, 0.3560891667898857, 0.32167273026065374]\n",
-      "Epoch:  624\n",
-      "Epoch:  [0.3405609012406978, 0.3253145919959877, 0.31813536709809276]\n",
-      "Epoch:  625\n",
-      "Epoch:  [0.37287185624784835, 0.3415863030194951, 0.32652304230251955]\n",
-      "Epoch:  626\n",
-      "Epoch:  [0.35087300215045736, 0.3230542161481371, 0.2992941330180394]\n",
-      "Epoch:  627\n",
-      "Epoch:  [0.3866073675091133, 0.333115457430487, 0.30993783824337795]\n",
-      "Epoch:  628\n",
-      "Epoch:  [0.3944736997494743, 0.3399328204364078, 0.32946829474334205]\n",
-      "Epoch:  629\n",
-      "Epoch:  [0.3517283562352444, 0.30473205971671025, 0.27516538406111873]\n",
-      "Epoch:  630\n",
-      "Epoch:  [0.3425059194087197, 0.292425345771041, 0.25168746123180785]\n",
-      "Epoch:  631\n",
-      "Epoch:  [0.3383120801971032, 0.2909349056135643, 0.28874343206574055]\n",
-      "Epoch:  632\n",
-      "Epoch:  [0.3404326579387207, 0.30085149883614126, 0.27271272247007894]\n",
-      "Epoch:  633\n",
-      "Epoch:  [0.3389003438735471, 0.2833882322888092, 0.2627489999253163]\n",
-      "Epoch:  634\n",
-      "Epoch:  [0.33945772468026475, 0.2868876471404949, 0.2580296086575831]\n",
-      "Epoch:  635\n",
-      "Epoch:  [0.37326263359512096, 0.33598062557279096, 0.32411771979397214]\n",
-      "Epoch:  636\n",
-      "Epoch:  [0.35403032745899116, 0.3055998118274608, 0.32163542786035404]\n",
-      "Epoch:  637\n",
-      "Epoch:  [0.31915476863085046, 0.27588412643631394, 0.2593546429654659]\n",
-      "Epoch:  638\n",
-      "Epoch:  [0.30838462428392976, 0.2641356725038989, 0.24153161050687394]\n",
-      "Epoch:  639\n",
-      "Epoch:  [0.316866785675818, 0.25531290253212297, 0.25244059221960763]\n",
-      "Epoch:  640\n",
-      "Epoch:  [0.3613640258427472, 0.30749254016415567, 0.2993661261240978]\n",
-      "Epoch:  641\n",
-      "Epoch:  [0.4560957426004036, 0.41044470755550033, 0.4213212749843085]\n",
-      "Epoch:  642\n",
-      "Epoch:  [0.3268433425994672, 0.29553242168080485, 0.28885613077429634]\n",
-      "Epoch:  643\n",
-      "Epoch:  [0.3388693832984363, 0.28922176583356635, 0.26151755019433787]\n",
-      "Epoch:  644\n",
-      "Epoch:  [0.3551040934786505, 0.3121601935190845, 0.3372905749006486]\n",
-      "Epoch:  645\n",
-      "Epoch:  [0.3950229930730802, 0.3491079209147215, 0.34044436290574065]\n",
-      "Epoch:  646\n",
-      "Epoch:  [0.3504934096592245, 0.2936926915165561, 0.2823581518263725]\n",
-      "Epoch:  647\n",
-      "Epoch:  [0.2879851819044873, 0.21985813332561194, 0.20849696268038984]\n",
-      "Epoch:  648\n",
-      "Epoch:  [0.3245885611564162, 0.28153978853106165, 0.27204213079816963]\n",
-      "Epoch:  649\n",
-      "Epoch:  [0.3385247409313531, 0.3095680659888893, 0.29213986398738856]\n",
-      "Epoch:  650\n",
-      "Epoch:  [0.3861236196135422, 0.352576906737658, 0.35333939182385715]\n",
-      "Epoch:  651\n",
-      "Epoch:  [0.3268755697934252, 0.3099953895072693, 0.2693390533512511]\n",
-      "Epoch:  652\n",
-      "Epoch:  [0.3892307522066738, 0.3928214103904628, 0.4023236833040886]\n",
-      "Epoch:  653\n",
-      "Epoch:  [0.34547836951377103, 0.300130204460169, 0.29896221066734074]\n",
-      "Epoch:  654\n",
-      "Epoch:  [0.28990912578598094, 0.26335491663652366, 0.26315304729302275]\n",
-      "Epoch:  655\n",
-      "Epoch:  [0.2936064115690315, 0.23957060218392476, 0.24209871754969556]\n",
-      "Epoch:  656\n",
-      "Epoch:  [0.3575724166331831, 0.32546828515844517, 0.3221753581860169]\n",
-      "Epoch:  657\n",
-      "Epoch:  [0.3647244946633605, 0.3412032737973112, 0.328149963442003]\n",
-      "Epoch:  658\n",
-      "Epoch:  [0.2934796966897812, 0.29147471642490524, 0.27059589901371073]\n",
-      "Epoch:  659\n",
-      "Epoch:  [0.35722640122261323, 0.3144413690566575, 0.32564162877870284]\n",
-      "Epoch:  660\n",
-      "Epoch:  [0.3214279551804589, 0.27386785865277363, 0.254881015814797]\n",
-      "Epoch:  661\n",
-      "Epoch:  [0.282781596361239, 0.2716306625014409, 0.2488504807273899]\n",
-      "Epoch:  662\n",
-      "Epoch:  [0.3299767453047012, 0.28521496715211536, 0.30970622060343217]\n",
-      "Epoch:  663\n",
-      "Epoch:  [0.32886103772836367, 0.2917395893906486, 0.2890896712578199]\n",
-      "Epoch:  664\n",
-      "Epoch:  [0.330763248542938, 0.31276933713657273, 0.3255290531691511]\n",
-      "Epoch:  665\n",
-      "Epoch:  [0.3556771880269862, 0.348091967317064, 0.3473034487128407]\n",
-      "Epoch:  666\n",
-      "Epoch:  [0.3482777637864545, 0.3021287548816544, 0.29204382219139957]\n",
-      "Epoch:  667\n",
-      "Epoch:  [0.3333933771800989, 0.3068483351078812, 0.29979310219472177]\n",
-      "Epoch:  668\n",
-      "Epoch:  [0.3722723890556306, 0.3311875111955823, 0.3437469450837784]\n",
-      "Epoch:  669\n",
-      "Epoch:  [0.34172860376277414, 0.3061534737114907, 0.2939381093450614]\n",
-      "Epoch:  670\n",
-      "Epoch:  [0.27494022430254156, 0.28347098803621323, 0.26686553001680324]\n",
-      "Epoch:  671\n",
-      "Epoch:  [0.2824572825614667, 0.26345478924047677, 0.2830560535328211]\n",
-      "Epoch:  672\n",
-      "Epoch:  [0.31867652198090973, 0.28719272932993756, 0.30034232046427334]\n",
-      "Epoch:  673\n",
-      "Epoch:  [0.34281880802709663, 0.31825494858593417, 0.31196987638007007]\n",
-      "Epoch:  674\n",
-      "Epoch:  [0.26574665894082866, 0.2336192893033939, 0.21513912292442436]\n",
-      "Epoch:  675\n",
-      "Epoch:  [0.28413348250486764, 0.23893858584266328, 0.2420685932951873]\n",
-      "Epoch:  676\n",
-      "Epoch:  [0.39128838628377693, 0.37356407597574576, 0.3822909731392216]\n",
-      "Epoch:  677\n",
-      "Epoch:  [0.30267794321619684, 0.238483453088097, 0.21396543474697804]\n",
-      "Epoch:  678\n",
-      "Epoch:  [0.35779968585285393, 0.33461773650684407, 0.33954067805082594]\n",
-      "Epoch:  679\n",
-      "Epoch:  [0.30284656541406807, 0.25536198399043514, 0.24940685636226034]\n",
-      "Epoch:  680\n",
-      "Epoch:  [0.36440827030677597, 0.3385674994688597, 0.3181967411271501]\n",
-      "Epoch:  681\n",
-      "Epoch:  [0.29963842786467376, 0.23453052614532974, 0.22580978866837503]\n",
-      "Epoch:  682\n",
-      "Epoch:  [0.2956083643138657, 0.27438022745688745, 0.27737256988966796]\n",
-      "Epoch:  683\n",
-      "Epoch:  [0.333476492577037, 0.29604455003852, 0.29512312078324926]\n",
-      "Epoch:  684\n",
-      "Epoch:  [0.2924762934516582, 0.2356143127079786, 0.2536563214765937]\n",
-      "Epoch:  685\n",
-      "Epoch:  [0.27860075267434065, 0.24098683388774245, 0.27126148198176003]\n",
-      "Epoch:  686\n",
-      "Epoch:  [0.2901888710305866, 0.24862331532065138, 0.2553972173695878]\n",
-      "Epoch:  687\n",
-      "Epoch:  [0.21067661939445873, 0.17779922606737503, 0.15965079511107078]\n",
-      "Epoch:  688\n",
-      "Epoch:  [0.3193481231619076, 0.2960989711332639, 0.2960473578246764]\n",
-      "Epoch:  689\n",
-      "Epoch:  [0.3461301002164085, 0.33980655234292034, 0.33509064402574795]\n",
-      "Epoch:  690\n",
-      "Epoch:  [0.2614577915227994, 0.2212187251657635, 0.20912760536096048]\n",
-      "Epoch:  691\n",
-      "Epoch:  [0.32727599923347883, 0.30116595239593147, 0.312618586606447]\n",
-      "Epoch:  692\n",
-      "Epoch:  [0.2553442832655974, 0.2051344069760641, 0.17978179383190027]\n",
-      "Epoch:  693\n",
-      "Epoch:  [0.2570035016676454, 0.2332328012997306, 0.21285479596393206]\n",
-      "Epoch:  694\n",
-      "Epoch:  [0.20665050771645788, 0.17157140201862905, 0.1459384215041064]\n",
-      "Epoch:  695\n",
-      "Epoch:  [0.28613637301642647, 0.23866425470806252, 0.24161753405502437]\n",
-      "Epoch:  696\n",
-      "Epoch:  [0.2809539175681594, 0.2508933195470077, 0.24770452522241693]\n",
-      "Epoch:  697\n",
-      "Epoch:  [0.25948011155169726, 0.21447858085098845, 0.19249257184884017]\n",
-      "Epoch:  698\n",
-      "Epoch:  [0.22481840989979826, 0.19124511369307268, 0.17343441118791442]\n",
-      "Epoch:  699\n",
-      "Epoch:  [0.2788456473506102, 0.26395346290130023, 0.26954197784361794]\n",
-      "Epoch:  700\n",
-      "Epoch:  [0.2798750443917513, 0.24535800842632197, 0.20646698926628898]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 4800x1600 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "fid_plot(200, 701)"
+    "def jsd_bin_dep():\n",
+    "    ngf = 32\n",
+    "    nz=100\n",
+    "    mGen = DCGAN_G(ngf, nz)\n",
+    "    mGen = nn.parallel.DataParallel(mGen)\n",
+    "    exp='wganv1'\n",
+    "    batch_size = 1000\n",
+    "    \n",
+    "    ##fix the epoch == 500\n",
+    "    eph = 694\n",
+    "    \n",
+    "    gen_checkpoint = torch.load('/eos/user/e/eneren/experiments/' + exp + \"_generator_\"+ str(eph) + \".pt\", map_location=torch.device('cpu'))\n",
+    "    mGen.load_state_dict(gen_checkpoint['model_state_dict'])\n",
+    "    mGen.eval()\n",
+    "    Tensor = torch.FloatTensor \n",
+    "    z = Variable(Tensor(np.random.uniform(-1, 1, (batch_size, nz, 1, 1, 1))))\n",
+    "\n",
+    "    e = 50\n",
+    "   \n",
+    "    enp = torch.from_numpy(np.random.uniform(e, e, (batch_size,1,1,1,1))).float()\n",
+    "    fake_data = mGen(z,enp).detach()\n",
+    "\n",
+    "\n",
+    "    esumFake = F.getTotE(fake_data.cpu().numpy(), 30, 30, 30)\n",
+    "    esumReal = F.getTotE(showers[str(e)], 30, 30, 30)\n",
+    "\n",
+    "\n",
+    "    for nb in [10, 20, 40, 60, 80]:\n",
+    "        print(\"nbins: {}, {}, {}\".format(nb, F.jsdHist(esumReal, esumFake, nb, -10, 30, eph, debug=True), F.wassHist(esumReal, esumFake, nb, -10, 30, eph, debug=False)))\n",
+    "        "
    ]
   },
   {
@@ -1252,7 +247,36 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fake_dataG.shape"
+    "def esum_highStat(eph, e): \n",
+    "    \n",
+    "    ngf = 32\n",
+    "    nz=100\n",
+    "    mGen = DCGAN_G(ngf, nz)\n",
+    "    mGen = nn.parallel.DataParallel(mGen)\n",
+    "    exp='wganv1'\n",
+    "    batch_size = 1000\n",
+    "    \n",
+    "    fakeL = []\n",
+    "    for b in range(batch_size, 5001,batch_size):\n",
+    "        gen_checkpoint = torch.load('/eos/user/e/eneren/experiments/' + exp + \"_generator_\"+ str(eph) + \".pt\", map_location=torch.device('cpu'))\n",
+    "        mGen.load_state_dict(gen_checkpoint['model_state_dict'])\n",
+    "        mGen.eval()\n",
+    "        Tensor = torch.FloatTensor \n",
+    "        z = Variable(Tensor(np.random.uniform(-1, 1, (batch_size, nz, 1, 1, 1))))\n",
+    "\n",
+    "\n",
+    "        enp = torch.from_numpy(np.random.uniform(e, e, (batch_size,1,1,1,1))).float()\n",
+    "        fake_data = mGen(z,enp).detach()\n",
+    "\n",
+    "        esumFake = F.getTotE(fake_data.cpu().numpy(), 30, 30, 30)\n",
+    "        \n",
+    "        fakeL.append(esumFake)\n",
+    "    \n",
+    "    esum5k = np.asarray(fakeL)\n",
+    "    \n",
+    "    esumReal = F.getTotE(showers[str(e)], 30, 30, 30)\n",
+    "    \n",
+    "    return esum5k, esumReal"
    ]
   },
   {
@@ -1261,7 +285,16 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "F.plot_image2D(fake_dataG)"
+    "eFake, eReal = esum_highStat(694, 60)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "esum_plot(eReal, eFake.flatten(), 100, -100, 1200, 'epoch_stat5k_'+str(694)+'_E='+str(60))"
    ]
   },
   {
@@ -1270,7 +303,48 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "sum(fidelityRecord[401]['Esum']) / len(fidelityRecord[401]['Esum'])\n"
+    "jsd_bin_dep()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fid_plot(200, 701)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fake_dataG.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "F.plot_image2D(fake_dataG)"
    ]
   },
   {
@@ -1279,7 +353,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "list(range(50,400,10))"
+    "for b in range(1000,5001,1000):\n",
+    "    print(b)"
    ]
   },
   {
diff --git a/interactive/functions.py b/interactive/functions.py
index 815e22e..0e08664 100644
--- a/interactive/functions.py
+++ b/interactive/functions.py
@@ -3,6 +3,8 @@ import torch
 import matplotlib as mpl
 import matplotlib.pyplot as plt
 import random
+from scipy.stats import wasserstein_distance
+
 
 import scipy.spatial.distance as dist
 from scipy import stats
@@ -87,6 +89,35 @@ def jsdHist(data_real, data_fake, nbins, minE, maxE, eph, debug=False):
         print('ERROR JSD: Histogram bins are not matching!!')
     return JSD
     
+
+def wassHist(data_real, data_fake, nbins, minE, maxE, eph, debug=False):
+    
+    figSE = plt.figure(figsize=(6,6*0.77/0.67))
+    axSE = figSE.add_subplot(1,1,1)
+
+
+    pSEa = axSE.hist(data_real, bins=nbins, 
+            weights=np.ones_like(data_real)/(float(len(data_real))), 
+            histtype='step', color='black',
+            range=[minE, maxE])
+    pSEb = axSE.hist(data_fake, bins=nbins, 
+            weights=np.ones_like(data_fake)/(float(len(data_fake))),
+            histtype='step', color='red',
+             range=[minE, maxE])
+
+    frq1 = pSEa[0]
+    frq2 = pSEb[0]
+
+    wd = wasserstein_distance(frq1, frq2)    
+
+    if (debug):
+        plt.savefig('./jsd/esum_'+str(eph)+'.png')
+
+    plt.close()
+    
+    if len(frq1) != len(frq2):
+        print('ERROR wasserstein distance: Histogram bins are not matching!!')
+    return wd
     
     
     
\ No newline at end of file
-- 
GitLab