{
"cells": [
{
"cell_type": "code",
"execution_count": 71,
"id": "4fbf20c3",
"metadata": {},
"outputs": [],
"source": [
"#|default_exp app"
]
},
{
"cell_type": "code",
"execution_count": 72,
"id": "5cd0900b",
"metadata": {},
"outputs": [],
"source": [
"!pip install -Uqq fastai"
]
},
{
"cell_type": "code",
"execution_count": 73,
"id": "e9fdfb5c",
"metadata": {},
"outputs": [],
"source": [
"#|export\n",
"\n",
"from fastai.vision.all import *\n",
"import gradio as gr\n",
"\n",
"def is_cat(x): return x[0].isupper() "
]
},
{
"cell_type": "code",
"execution_count": 74,
"id": "9a9003fb",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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XxhWtGgkufID903MOBS+g1YfiZP3tnPmOi18ERDA2L9r2kotZCoTS86zPH15Kz0uhta7t+VYiQNvwa2B35UKFtphuK5DbgqkfiUqtquX5Uy8WVWQ1OS8JsW5TbVBj4/cVQp7dqpcjbveR59TcFP0lQAb5LFvy+cjx3/j1Ies3PvuACNsyf+ShH4Hnz628uPRrXIAhBc6gjR/c/Bmgaa8Lb+QFof+OeaIJLFmZaJ1aG9W1xF2fEisQTFzhxodDxOrlZcuAPeuQ54JBty3cWf1sFQOiTbjIlr9xoeb7L0JSe4mObIlXG4E2Fbwyoq7i7sMxXzmLnxmnz3z5LTFNKLG616PjX2wXk2wwmeetst3hmWg8D+KZQ3L9JUAR6jqwDT40HmoGf5v1xkNclXWsuOjyoSHPkeLlGunmP1jxRbeCLxlFoU2lElV6GqucH7QuZXcUs1s621NSB/WN3S6laRcxXVVsYH0dna5puC1tKiDQc7KlkE31nh9/cetVDl0ha64JD3KhhhrfyTVd/t5wdwN08lxJy0rWlSf0991VwM27c/76tke5NolY7w1d0XlXeSJtV7QqauW5VEiukdwZmqyyRNjLynqq/vZRu+czvl0lNdcNoxdGM9ZBbk8UbRPpeK4HhTrAaDcRW5dGZDM/Om6hXHuin/HyBg/kUhR2qSLRZJOsrSj6xS1LfNVo6xZTsEGy4Hk3bDdrnnv9WAStUUSvnvz35J91fz8LXJw/vnTkQ3tq18ccuOiAUlo5fcg6Hm5aZtNfcskT0pd8e/NyC608J/JM1XSKdAxqAgGcHZWim9Yqq7TG95ur3Sz4MKrRRi59c2L1bG3s1SVwU9jSt8rlHqZElygpGoNv0HRT2VfhGG59T5om67nVZze/9X/FgJXjKJtKbqOLVnTPZwZPT3AX6IfopUteaVaACFbCSXyoc58p1hUJAgB1Ldl8DhU7zVaZrSKbB7fJJ5c+tjbbtnYriVeZfi0G+jPbllBJAAXdIwrpGko6f/UNpVzFx1nSAQhSAetZUOJNs8cqAET0Azf92bMsCFK4WkDaMyxICYgoVYAWXCDqWWN3UL0mo3Ws2cO7yp6qHSRbVcYzz1L/FYa+d7rA6Op2FUzr80I6C5/5fAXCglUDty8a9DKN9XLpARDehrrGZUXWmwAiV6XmZwJ/jGmuJtLeTw2lQS5V+Ieu/fUXbdwjzdrvz5OzUr5wfK4RjG0J12gPFD3HbaXGxWQ76AET+6Kipyec7wMAEiu3RfOXtKGstkmn9pUovcTczf5er+vQp9loQYiuSql5/nm5EzoQxDrdrSi6EUa6+E1dL3Qdz+hQ8TyXi4DUSgCugIBBav/mVqPSvcY4C3MSvRxdVlhzHtwKJ9ttue319QJtUxeubHud2vZBbdOZI4Br3XK+uIlMbHPv0zzjzZULATBdpKuIXhQkrE6lbpqpNjdwr4Df1PNakHGxHzYCCCC6gYHrrdF1CMiQEIqi5Ww3aNItjSZVFdYR9rb8nV06ElpF+coUPf9DV/Zzsgv1K6DLq386vbjaSySAtK5E2zYKRtOp53VujCAqvG4MQEas9pFoz77vUSHb6LNOSzpF+twvldgmDy7e6+9c/Nm3CS4GdfX1Z68zt1+D/3Vc7ZcrXHIha8/6mhQ/q+/Of+tSx+VN0SWS9UFJC/l1UXouRdIV1HMVRY3RWsXEBTWaNqFAqRANobT6Q7KlpW4cR15ZAd25v2qJvuFXU4LrJEldF0jZBRM2B7Ss4OlsbBIiYkS0WhgRAkll4x4BYGuFR1wvpUHQirN6TCCuZFIz5Ju4Pu9srkiwUaQ9SWTl6S5ZVw/kM+UmG0NdmMSXroRnV36f76dbTF0gyepziHXKZ338cXy+SeuOkpoo7UBsu2a7QGRzB5+lDND3GLvJBllX/CxZIbjwep4FWF/wJuAkoABbgBxYfT1ydnlczLpBRm5+kRUytxu2Rer2MoWMppQIeJdQPGcOC/vCGUAY18+SQtsSrmZq/0a6WE92TC163iF6GWpfE5FwtR4r8TYz155R/HrJ5Tqi2apPNnJ0iUisHrZNOV2SbB1w8NqoPKe2ySoRqdCWMHfGHX1kvnK2rlZzy81T0R4PbZstLqBPL2EWWdXKZlrp2SW9ib1mi2xovKt9cgvB9gwY8pz93cqvpKdQNu7qSYOxbrZzWkcnaUsjv4ogrXzDNWt5I0kr4yCoREVQenOAzbjorCAXAjLp9SPP1taFUl2V5rVQQo+dy1nGfXwT9x5y7Bc8w7AflRyXcBIdgX1MPHz81cUrnz8OjWi6bm95PuDO/XZxG3QN3ocqOJs9W24eLhavOZZUpWdBbFvmQhB3DiBE5UOrYiVV7w4QvSsPVTXouu3zFiN/bjRc3mcbaNvLW6FRG6psMhLdEKC2hLAucS71x3mfbc9qQi51UjSCrfJ+lXBn6z3aLr6ulNx8JrIGX/rarbB61WUbO25r2X557kPbJOsVITb98v3baKM8z6t2xRvrunXyq2DbLGeZ2Ud89RiiJYILNp3Lq9u20V/cQy7DapuzY9s/csFL2KbalD83Fc9VeUkriFkfo026SreF1idgU5nPXyIi3VFyTny5jBc98zM2vbjRQ4Emh9qwz2u5mn5J+opxLQjg5X03Whq2ijB88LwLKlwsfg8UtKzJ60jWsxn2wEIn3XaPZxp91Xvndy4fLtefY4vuXfDRBSuvS3W++Wq1XY1uDdWv2rpz3KqB5fLtC2l0kXDR0czZ+dXGcKX8cHllv8d5WzRB11cjLgdIbmbTx70j2HwxZ6pe0v9Cy1yPpTl6GuuefW9dbgeogLZSkGTsppFgvVBE0OO92wOVABFn5NEbkbbwBT7Atlc7vn1Bzvm9z+TtNYZ9turP1eL6Zx/qM8G9+pAuLalVEnzPDc/vfBDKBc9y+eIR21ZZ96KcG7U80yabLj7/eLYLPzI1fAhcWvB7W8nmxPs+u6HdSsVWZ96l9dzH8eESnC2VTUk1XrgwS4Pnyqw2owRxrG9doOKO6lYx3Gtu5UyC4IWsQCi2eFIXvAqsor9x30Xa3yp0N4h1hVRWHj5P7prEZwYiu09+1dwrwL7QKRvq30yxj5B7tTk3Jlin1bwS/U/rHuE1ctiaqrDFq4QRz13dWB/9kReB7nb7CLz7oDxmBeUi1Gguv7OFhB5t7UFZCHTz/YhIiAph7H1rCFLOlfoXVOiPu3C/nKMLnd6NMwGAQYEgsZtxK27ZxPPFHx8FsJcz/PD9zYr86PUfgr4LgYGNgeSCrT/6uv4WOnWuBUAj/4pVroTT99zqw+XsmxEb1PvYN1eH7jWqEHk22euJX0nHSwn0oXTZJnZBVq7svml/dukDk2uBSoC6gpQPuQdYo2BdL8aar9CsyjVIS1AvDfbUruflwmPjnW43Xwqxdd4b1LjSVBeXnbfH7+GAy8+v1cfGvdsTz5c2XPLRm3Twv33lAmGsG2RzZJ6BWYNrbcTcyuTbliKgraXgNQC6eNDVS55bDBf+mjNzbSbSOb+uAYznGKz/5CZysQVHL5hgJT+bm0q01VJc2NJCtPS/1jvvA83fgjLtQc2Dp8pt27X8tTXDbbXhASCdj1PoKGlVH7yEgmcSdwS0+cqeL+wGb3vkqcGUlnDzXKKsSlf70qxR7ouLcc1HK83lkmbtnrEBxW6vN3mwemr7t7RHZvvKUAATNVgzezZ3WLeQowHXIEw74lof3b2m5/Xb9t7FBl0f072usglIlRZLie3rYLOyOgdf0oqX/8l6Jsb17mhLREDEuNo83UvZQgSNjaKlB7RHxsqHTdIwwGCAsqbbUkRaElP/lggkWvlc243n0uY2sVgNopZ1G9eAtNHpwwzYfs0ZqhHPOm1fy+rL378HloDfD1nW1er/R2wh7SvAtMKEj359TUyD9P0KkEgYh+Ewpn3O+6yDgqpK1uP0VFkWn5flWDhT4gJdcmu0c609+whXRw4IsGHtaz17ptlK/+1WzwXFmffXP+XyrBYRsTMWFXFsyWsQJUICQta2uuSmAVtONIL01dnFbcSMXpmxibLNeohIgDRMImhiSjc53jzvetEQU7gmP27S4qJ4pecnAWuOwXZ6ArY74JJjWiR2vUmsFnZ7opzl3Qek7sEoEVGuJS8N70b33GyaYhMUZ3QcDBVTJBJQUU2jjbfj68Fudvnm1eHTnMeUssKau12hwer0IvU0PT5M796fvj3Ob6byCDgoCgXdu3DqOTGx7Zm+nAwQurWMo8qzTbXqr9UFejnlWA2PYISw98LaWEe2KiVtXLi6BLt4AVpSh4cESSWi9YTp0rqnW8bqmlhHFYEO2LHplo61pBXupdXRJRBrzqA11rMpq65gLhbwo8t6+ZLrL5yx7WYucrN7V7pf8MfVLvzQMN4Q0oc5aNzgITtSu7SqiFDkQ36RJe3yrjqHvPtk9+ru5vVhfJGQTFpaQyAc9J5LaCpqGWnAeHNz+PTweY2fH5eHrx9++/X7Xy31HijX0Pn7Xh8RKpevYNjqu70e9nl2BHu/y4tFkjNBPiK2L2nUCOOyEggryIXEWiJxNdxeiLIBQhLRMreasbupsDXNQKSj8c50WDfweSbPR8geYd0+WBf+kliysXUEeTlWaUFhWREFcd13fL2SG4HkHETpBUerbcGVsh2EsSGAlZk07OXw6U9f/eJmuFFJEFEbx+FOVRgVXGoEGEIn6bUyqgAUimbTnbQorJiIvhhe3H768gcvf/L1/W9+++6vp+W7D/gBF8qlrfk2hSYI13zOC5JeJEJtWmwV4REh3Sd7ebBGe8bqwwv2NLHAijXOHko6GcEWYdsaeqwo5dooWK21no4GARENLXQykwRSU6JyNrn10qrCCkGbI4srTNbtJqst0NLcV/ejrPyycmegAfmWcrI6IQTdwXi2dVcI28piVrgqF4imJfiDhAoo1PWzs3fgoucydO2cojK8HF//6O5HN7Bc5rTfpfGFaIpweqM2EaWWUzcsCFYvsXCZwkNShiZVG8YDVLyIat5b/snLX4z58O+++f8+zN+uUQddYS6wljVcVNQretGPXpiBaxmWovVkaqGDtSajc2LQvemUzaHepXvX6N2D3au6n4vnoBPBVlxLEOdt35tk9c5n7OOXIBmxOg8FZDuGrFUFGqApemxRNsNSNyOjM9Am5bCGO+Cdx9Flm7bChs0CpkBV+kQ22MWIILfVbY+LoOp5q5FsCSzebM7eUntbCDTOMayjJkmuRXCr/gK3sqwmf1WGLw4/+eLmBzfJ1NUhyUaRTF/C51iWoCOWqEuASVs5m5hZklSTge7LU0QAFstJzMwUliwNmvZfHr483b5/Wh4gbXatSVcDgEFUxvoXNrlw0TKxk/bcAmCTKN01yQA8wNUF3TslRquqbgknBKHaQY13ude5QtiJX1u3BvSU9j7NLS+Wa5LIynD9WZ0BGIST3jiWpEATO+jsKlHI2Db8akl2pHJ23bdI31rS0IXUGfYRJHzNAb/IOqC3+3ilrsoH2ASyNEnXHhpE67JOWQ3E87kzSoG2vo3oBF7Zte2diH4eBEJdQj49fP6jT35xO9yaEpRkOzGt9VjmUy0nn4/ldG8iTkl5KCLhQVZLKadkOVOU4bEsZZmW6TTsRrU85KHWRXMd0+7V3RffHr96N33X26MyQkIg0ZYBZPgq5i/JuWKEvgTcog6rL6B93RtfNgAUrBshonFIX9IIbanLuq53ABL9VE2PcFwkE65MJoC4+8ZyspkekFjLmTokJ8iIaCn1DmqKXqbaVqInA6+M0MQm16WWM6rvrNM1Wls40Q5v2Wi3qqQ26XV0bFUMm7CQM9OooMc7uuikE762e1yRk1BhVWiyNhw4I7VOlnauaPSNbzd293r3OkfE9B6AmbnN8zKVUhCsy+R1mo6PCtnf3M7TUwkopZSnWpZhGD55/Zkj+ezLUugl5sKY87APn9Iwss6ah9vx5Yvh0/enN+2c0gAjmpxgkG0iF8k6W3KZtnAVhNG1Q9OCZ15rDWWiMwQJD1Y/Kzdpke7GFcJQSQKFxNbxvmHeoG8gYU3g74EaXlfvYlUQhEMYjtWh1tBHhDgaBoWmSqpsTEO25NT11Wpju6tgBYSrz7rl+QhX3+s6gqaxzrr0zPJcNXZnnXUftD3XDN3oNmWwErU5JiBNArcJR1OlJAShPbv5YtBgC0s1GmW5+fzmR6/ynU/HGkUgOdkyT+4iKk+P75fTI8NVFCLH09FSyuMtiKfHx/v3bwUCsd3tp6Xw9HSMepQo01HvXr5K+xvIIMD89PaQ9p8dvng/fft+eQMUAYEIemsrHvTWiqTXNbUkiF5GKM3vgegZY+tGjkbb4ApdOxOUpkdWXLRaFCQhqhZdc7QuIltpIYPeUFcXcLGRTdB1bt+CK4bXtcc0G64IOuGBaGVASqEwsT1+NdXWch/2CbSq1Gs3dPdr9LyU5k/Tlr5HslNq7WdwbRlqF+cMhW4rv/J/oK86yOqoQQcddBE4I+htekFqUBEqiUKBYXOgA2D3XgAusJfj6x/cfpGDpUy+nMA4LtP92zcRNt7eBcv08HaZ52itklO2POZxZi0P77579+7+/fvH42n5+R9mM3WVpbrVGmQtnvYmYhXKZZqf3twdPrnLn3xz+soxk63+hh5NBTtRu3AhpOtfk+0Ih6CQPdYNk7VlTFMiwSAdCEchasBreBc5YmhJ9yQETgJUKBjBeoavEpfR8I4LvQcK13gUV2HWin6se7CVEZXYNq00fdK0VgpxSihbviYuXStXxuSW8NUZrOu0zcDvJaptAcnLcOAFD3X9QjIQ26HgFyzWQEys4qd29R8NFDXo10oj+hZaXQ7WrK21cWzHei93n//g5scJErWUaT6+/3Z6elvmxfIhj8Pp8f50uvdSRU010WM+TtA5Ho91Os2P77/96tvffPP2q6++YuBHP/lFTjmnnVhGrbUuEhVR3fHw7s2yzD94+cXtsE/AEgX0Pgx4RBB1pY8IlMGtB75cWA+d/JQtHYgX1Gtk8x6K34R7gLI2padQFY1eTtRVyRl0C8A3kkvjgGjK8eyYUYFKNG8gBYlUsqLxeNPL3RjwxoepjwtCVqCfKbNaApubcs0EB9dZt1JOiEb3TXLlONns9JUpuInKxkDBhqaxOkl73CkEATQaebCsyHEjWZAdfROhKyPJ2XCUbhNKFtl9svviF5/9ox/e/iBOj0U85XF383oJ1PltmU6npYrYMs9ksJSG2ecS+xevbu5e7sbd9PZ3X3317bffHT2Orz/5y9ub/cvXnw1pONzeRq11OdWl5KEoI0n9zS//6rvf/fbTH3/5Mr04Tg+VM4QdNCC4uoGaS0MAQikq2FoUrmh7FfV99wrICHo0WLVaRisDde/A6iMQQAIVwPpc71Aj2pJsldGrcGiirqm9FoqFaleBa8ylb4bGCQyUgGMtqk/sZxuht8wJPQdIN/SMLruafm6iaN0XWwoXVjL1gch6Zkk/BQPnOTf1XOna/ZYqRCBEnKCDaPB5hf9k9wD0OygNbFdKA+YCAYa0e7378pP9J0mGIe1fHT7bD/s6P9IX1qmcHkR3h7svjg/H0/GJMeX9C7P8+P7NfHyiqENvPv/p3ec/P4zj3/7lv/4//B//s7/+9bdTiU8/udM/++tPP/v87ubObva73c5SKuXAqEHPaXj54rNpmv/r//K//I9ev3q9/+zr09cLHrrtQrJnFK6BTUggJCLEz1qXsRW6bGJ5JSBXPNyMZ40Ga88Qe1Mbqi3BrxM7un7s1xAIVW2NLteHdpI2BN6yV6OHxlwRK+u05wRRg5UIUBvXJaICrVdj0wjrqneBmy5sgs36I3p1CyJEIJDG9fTeCt+uW7GKdFu94cSNjdyJfsp6i/r2o5DY09zQEXlEbM7rIJRbT6eO1x0hYgN3r/avv7z5wcH2oEeZluUk9Do9Pr375u1Xv5qWuPviZ69++NOXrz9/fPfGRe7fvD8+PlkagqAOw+5ufrr/03/5r/+3//v/7C9/9d0/+x/+T/ju3X/1Z/+vN2/f/fyLzz579fL25qfQGHbDcHMDh0NS2oniZy9e/eCn/xAiWZe7pxfH6W1IkZZ35+tIG7SR2FLs1hNOsB7F0hbCeyk+yba7hNI8+GBPX+sAuRlWXB33vqLq87G/JL0dmdhlFddFXGNKmyRr0fYtFYL9AIUOFpQM7yd7rGYxgCQhhPdGY10DRXcripGhCoFo2xu6un86Q3W6dE89RIFYOwr0kx4B9JpHIaL1CVgp2owuP+9MYk19bNZ8tLQ3IQNBhIi2IvPVIFz/ZxhGU5umhycoMfg8hy+QJMLpza+/+80vv/n6m4f3DzdvH37+3/qnT++/eXp6pMg8zYcXL+fp9PRwSofx9PTwr//yL/7P//z/8cu3/sVP/+CXf/Wvx5SS2JevXnz26d3NzZg0WOZahmRDGnepmcvhtc7z6TiXOpfyOb/Iu+G78uupPkLgLE20tK1PWjNUvPctkJW7eh8BCInK1pECvloVLZFC1k0Tfa2aqAHRA6jRoQI3Dcg1nYOKPoYIyvmgca7mbctEodAQzasi7Dg7umNutcW5eqqSrE5L2fqWt1w0aTXLoThnU10mPF2BuzUVqeEPAKBtDTfOcKiJi/WogGAAdY3VaUPxJCCrVaWhscokRq8RWGnYlULX68NODwcdzVmn4+Pyrp6elukoYfX07btf/uun+4d3x/jt797vnuyTL3748N2v3SnZallOx2U6HZ3JyvK3f/Gv//n/9V98fdQ/+Yd/8qtf/vUnO/3x68P/6J/8R1++HD//4mWyuH/3bS3TDbHT5F7rdFqWOQ37r79792d/8ct3T9XG25vbT15/9gcv0g/F/vyRv2bHgLYqjsY0DjRTY90E61phzWzsgiDYPHDNK7+ScquBV4CqOO/qzo8iVFsxNnomUOtrBhGJi1vpmhOyrmL7aM1/hUO8KYFtJVd3DNLWhqqFrmXLkMQWhLzOkttg9IWDB2jxBxXRXrsIQcuMbp1gLrmI65GO8GAFHFBBMExEVVTl3LlRBUFraNnXYxh49p2tlEHJKb/Mn9wMe0yTn5an+/tlmpR8+OZvvvnN7yrHwryEiPu7d98cn57uXr5+enhblmVepmmahOnhzZu/+avfMvDHP779yQ/G/+Sf/MevXt5+/vKw341Px6f93Yt5Kp4Ucgzo4+NTmZ5guUTYePdf/D//4j//l3/2sNRxfxjSMO73y1x+8osXf/wf31Z9c86Z27ifrWsCWrug5itZ0Uj3kALogLunMHgH3FsQjbqWEMvaRJzsILXh9fZuWwthO1JDVmOoUXMLn1+dQdCAfdMJXCHa+cizLtgoScTJbnsRrj1ffEtvW72FXVNw3USdX3tQTxgiZg0Oxyo+YdI7JQTPx56BTfZ4RQW89dcRqEBUkkhS9mKUIEC2zgEUCLwzTxOR7D4oAGZJVI/+6I/32QV1XqbJa611enjz9v7+9LQsiwzVEub53Ztv7168mEqZHp+mp6en09Px6WmZl3kqL1/d/Sf/+I9evf70cLi5vb31iFpqurn77O7FIcd8fHS3eT5N82J5LMssmr/66qvfvZv+L//i3/7N33718P79/cODh9/e3kVUU/6vb/6nv/hnL57Ko1B7qtK6G9eYvK/5Q52qIgpar0Tb5FPzrcpqAsPRKmUpEAdMOl/52f7tDzK0cxfFVoizZWmGiPQib0C44hvZYp5YDx1oylJiMwQJgQKa1uN+nXSR0A6QpEOqNc3f5eypEzRXBjuSEni4aMbaO0IpkA6b+v/ssRNGx8jNuw/4ygPtAUkwbFPfihwEYr3PTQDWCstl85kCQV/K5JoF6ks9vn0z3d8Dy/HNb99+9e1xKY/VTjWWWn785eHlq88tyduvf/P2u2+++/a7Za6ShzQedq+HcT/aOCy06eH09Zv7nMfPv/zRzcvX+zR/+6u/eHz37vb2zr3ubsvNq8/SsPvNr/7mz/7sr//zP/31n//tm2mej09Pp2lqLuOU8sP7t7vp7ue3f/JvvvtXIY51ousmb8vo6I6ORnknTLrKW1PSL8zh/s0WjcRmMq/c2Kuc1xhbi1uq9M7PV92xGyaXTvlmQfWvtnt612isvITfq7ZrDfaSiYS0MJvLFipu8qiftAJhr+yI7aMO1LgGmbvvvglpitq5NK5PKCiySWeS9IskQaiKwkx09Tn1ewohMIBxbpwlLaFYtBeviACMQW1nO5t5fPvm8duv3t+/G5LOD49Px/J44nfH0/unePn6xZdffn58+O7p/v2br746Hk+Sxk9f/yDf3ORhIDVEIGkp5TgXUL58/eIP/+SPX+z127/506d37+oyP9wjHw63w356erp/99379+93Lz65eT3Pf/XV8TgtxUlYShG1VvyDP/rjP/6Tf/bzVz/927e/uue32o3ltqtibX3XMQDOIKQSBsHqONYeCaDJym0qazeLxpLrovWO5lg/aMby2rtDVuMLwNlH0xsI9R5WZ+22BcD6kLvxJJKANboJT0JulaPncXRk7r3RDCiMNVWjPZLB2Fr5SB9iMyLaC1vfAo8arOhhdXItD7gUtaufqTu6Bc2ks9XR3BrPBJ8lvlzsSq/FY5kejsd3b+6/++p4PJX9zXJcHp7mt4/123fzcYk//vf+cJmO7999G9Ul5cOL8XD3ye7mdnfY55zDa6lLSHKOLz+9+cEPfvKTH/3wxUHf/O5vv/ntbx7uj5YTTYe0/+7tfSmlzJMM+53zv//f/aenRf7f/9Wfqc6QiCi1Lh7zbjccy/L6xY9/+uoP/+YhIkqpU9DXxbiGvegOrfVc74B4o7R00bvtH5WzTDjbRJfeRzRO6S66pKtACnrb4s2duPYHOyPU1X0jqx+uu/BWD/QmC63F1FOienOJNsQhG0omGRDvGOairrSz9iqCsPaFOyNf9jz1JmwQi0Tp0qJHWvuw2nD0QrYLtGWLiQipLRyHtaeb9J6BH9TqMRAVZZmP7x/ffXN8Ok6Fqqfj8fj2Yfrlb98vrj/42c+//MGnxadx3C1YxLKNu/Hmdnc47MfdOOSynPZjSvkw3n366Rc//vyLz6PO3/3ml1/96q++/eZrG/c3L16qptO0PJ2OtXiZS0js9ndcph98+vKzT1++f7i/v3+otTax8M03X6kGIm71gOI0GfOLJZ48lgZaSVG1BpOxQZCOP3yjFM/+ikb8XrcZAoRjVXQbR66x5nZ1CNANWDzj2svX5svWvrznfrf99o1fe3cRFVBJJrS4HmyzrtkM+d6XpMUckveeQltHJm7xtx47ba6MVVR2ZyEYLIhQSiA6U63MoYjGLy0W0bsBa7d4SW4Jn32nESomFJVV97cJUVJrfDRPp8d3x6eH+8fJkW72w/3905uHaXHN+/2Pf/YjTVoWr7WKSU7jeHM37vZqWJZHiZxTlpRv7l7cfnI3GL/+9V89vfvm7e9+8/67byrlMO6XMtW5vH88Mg/zXKfjsQbHBQ/HN2U63e3SdLK7uxuR23fv3o3j+B/++/8Uy/z+/u3rFz/68vTN1/Pfui8JQ3Bp5i7ZfIA4W6mC7k3t8DlWPNq9X5vikeYmadhyzfnqCEQuhEovlzAS5Hoc5ZaW2v3j7Oz7rBOo4HyYM5sA62nzHbBRUr8MgGpzKPXCDrDzSAvO9Lpkdvl2UeHQNHFEqGj3KqIKGnaJiMLNg90XXUgVWK//ag2KWixGWjisSS5pLLjCg+bplzXxoI+kuQ0UooKop+n+4en++O3bh5/87KeI8v7dsTrSbtzdvby5O5RlPh6PdVp2t3eaRxGrpeS8O9x+kiWllMbD3nI+Pt2///br929/+/Twfj6eTtN8ONxGzPM839+fKtPp8ek4z7XUSsixLCUe3t1HC6967F/cjbsRgV1Ob7777bs337769BNE3O0/j8rTfC/ChY8raq5t7LxysRKiAomI5o0mMoQK0VXGdOGwOV06W6yieo18CwDU1RfTMlc3EUDAKRSk3h11lVJBEhWo23nCa/fFWANTQkrLSOw5H4EgJXp5EClUMUKaI3zdIiHbGWBdTDYHubLnyaqIUCx6GgZ72H9NTo0eveo8fc7BWNkz1tM8WhyRIBBO744TiWv1Re1p1yx+fLw/3X/77t3bx6Dc3R2+/pu/mma/f5rsxStNWutyOsJr5HFnKTdJbcmWcgr6zeHFMNyo5Wk61lrv33779PA2Ihbn/vbF4XA7T9Nw88nrux8+PU14OjLNtczzUh4en+apLktJSQ6HHXRhmV9/8mqap1qnqD4dH/H6BXn8+v3fHMZP1UbjLjFKHFvmHRjR0gfWjdFBCFvEuxsw3bzQLq0JsLn9t829dr/oQqYtDTZ3tlDORk8zaddKnhBRikU/Q7Nlzq8+Xq45yVwRSM+2UsCSsziiMth91V3RoScaemPLjqzWBnEtCVeAkGjazQHQVVPLFxF2X5+oWkudih5UXwXPKmZla8pISM/6b6TsITAEI4C2E2UND3Vp1rz4IuJPx/vffvXdd+/uj/Pdyzv1+nj/EBBKKh4vx7yUJYlM03w4mAoAV6nLNKWc0/725u5FHob37795fLyfT6d5PtWyMDBXX+LptMzjeJim5fF0nJfyeP80T2V/2L999w4is1cPzIub2u1+pPDtm69fvnqZjPfv3h2Pjz77Z/uffleejsvXyXaKUSRUciNFz3VHO8RkNaNYsWFnSd3QODuRsKJnNm9Qd8vBBNFru7Yf3ZusWKOKANr57uzuJdeupJ7pit4cjEGsvflI9qQZUISpRHFh7anSa1IPe7NNxcqS3frpKRTK1BiqhbLYkp5ENFxEoWFoy6oaAWmecG8UWp+NTZYCASglAEew5Z01j1FEQJz9vDyB2Iq/Wxq0gMEW1r0/vv/6zcPxtJS4vb2bnu69FksDdCHkcDg0Ca4qFNQoBp1Oxd1NX+x3+1Km+/ffnR7vH5/uvZS5lqXUunhKY7gkSJldk5C+LJNm41JKDbF8Ok2nZXH4MNh+sKfH05//9a+P0+nu7fsU5YtX+d27X7y5QcG7g90tfvR4goCRILG1KOMqy7HmVTTm6OvWIaBcgtBVhzXb1Zrh3MhOrH1BuaZYg2teQ/R2yqs/J3rm/lq9w1Vh9MesRT19bC3o0XqzhUBSATzYMqCa34lCIIIhsR4XKD3zECpC1VCR2gP1BNnKTbyxpqClS4q1+n4KRLyrIa7lPS1vStc8GBExqLJX8wQh62wZdGiTtGowIqKboeueZEhofZrKXEsN1XTYDcf371IeZ38S009e3WnWNGbVEFURcYYvC91TSuHLm29/HaAHlmk5nY5lmR6fpsfjlG0Qm0Xt5uaF6CKyREStdVkK4PMcXn0upUSdfXl8fNzd7b98mfCHX/zlL79Z5uXh3aPGzOVdPYmn44JJkQkLFhXbUuEhjn7kSod8XeQTAiglYW3G3lvKp26ys3cW7ki4uXNCRRXhqmvz/+5QI6NF+3XTAxfulAivLUFboa3gLkTXhO4t4tAjrGtQw9NCcUglPRyEw0WbKnGwAoCoahc/EqLMSoU0X4QCZETAvfeL0TX5ozmUPQIqLR8uAA8Sa+VrsBOAIi2RpYcmmod0tbwgspX2EKRUoGUsNHBAAnDG7LVynsurV58MgzxFHBc/VhfT8OZIl+quqi0j1mtFhHuIncwLVGvw6XE6nabf/Pabf/ert2nIdy9uTfDZZ59BllKXm8Po7hGYppNZmpcpogr89O7+3/7m2/cPp/KDT37yj778X/6v/he/+s3Xv/rrX44Jf/DDuzf/9k9fpz+M13nBU7EsamRpMBndkNps7LNoUUoik9CwKCrERI1MjhxiLXSv2pUXVzhANhO4x5SCvZFRK7YJCbQUB1J07fHbFU8/f1UkJbGBYg3BEEtYbViq5+rEpUs6ObQlJESEkyEFEYSH1EBpkF5VGzoWiKEqTWDakpGFBCJKSBBUMYUJJeDducHucvKWCt52EiHSUjuatSFANJ9P09YqZqDCW655ZQPkFiCjqjbJSIVpT+GL+TSXuZjpi7vbCPeI41KH3aE8vp9KcfeH9+9zEmGYe/bEKF4KIEi6MxW1p+P0dDz97uu3/7d/8Zdv3y6ffvH6/Z/9+vXL2z/5B7of9PawK8uSTKd5WUqtfnp8fHz35vjmzePT+8ds6dXL13cvbn7x8x9+9sWPfvGzf/QvH/9P795889W/+VW5sfmnn6fXryuLk4YM1WYjKDQAwoTW0u9JCkxDksTO6siSIdrOTBECWoAFrGLe9Xi0OGowTJKSAW/+NgkOTcdLC0agYVNthQv0Fh0DelaihALIwr3Wnbh28Q9BDpgInW09N6RMEAkIRVWUlnCPCNcaWlo7gZZfqqqq7VAEVXGDAZYQ7dh5EQnS4a25rljrr1dbbw9RIyA9L9PPKUJsnlbRrhMbVg+EJtrAkjEbFwmGsIhW5CJ5QaxdrgNwIgEmqih1fpoDyDmXWmvVUioFKSUPrx7zsphUu9mr9gpaCGBqltIwaMoeOi91mpc//cvf/eabp/1uf/94vL+fbvZ3/+Yv/lZqfXV72I3p9u7m8fHBofdPp/dPx2UuOQ1q+W4cP//yix/99O6HP/vpy0+++O7Xv/7Vv/13p9Mx53yXhzo/iN+4Squj7Z3nCFANiTQh+nmfpEGVkcV35K1oRjJJgAbF1+MmSEA00DtwBigaDBJhAhEqq3FJcBMKWcAZnJkK1WHdpoP2HDVSaBqiih38gGWHMJKUKhDVylQoihpr5mGTdIlMo8+A5ygRtSJKcIEsYdDKYHg0Y1q8iICSVNwUKjnItHpxWjADyohQlVBtp+X1kAYdW+gUiGhfa6feKEJEjIAqCCbGPurOTyOLuYNRBVVtUSpziJVWm7IGzADukNLDXKYaaqVM03S6u02l1GRmaiA8XAVmlnMGQ5SakqqF15wHMQuKBywNT5P/6rfvzcaU0jyVm5vb/W7/7ttvbobd8XGRaj4/pWFUiIUfshxGEJpT2puN1D/48ud3d68iyt/+9b+dp8kD9Hh3WjQN7g41gVkYWrZUNyOagZCiW9gUhiIG8kZ1J8mQNBQiIWaiwXCydPTcPRoiDGpIqCBTFJ7IAW6MJKGQyjqxTLRZxgKjGGEO9QiGZjKzJvFBeCe8o2cXlahiM0yszhgLTVqsNCogGTLAB9Q0hAtdGIxYJExCmMA8t0qghjMCZEiL8KkEQ8G2AxSqEKoZ1rMcQgUiatKPmqMgXEo/GaHZkD1GbKq5NWYwhIYI7MByiPkQZfQqUSlRKFPDR7JU2YHmzfwEARr8QJS30zLVUhZNOh4O4ZWQgEgSMRtyTimlcRRVMiwlhXotACq9LlPOhJomATWbmiCplZg/eXl4fXfzyX787tvvwoyg0A67/W7c3+7vjmUuHk6oyG63TynNRxxuf1LL8v7td+N+zJSEaiplnrN5VhFIZmRBllgPomWV8AhqLz0pVEQaRDLEAIOqCiGiSSAJUgBDTyxv6TcKiETrKjVoZHqGZg6JSxYmshCZNopUDRcUYgpxWFEzcicxwIXlhv6JcI8eqq1dRuBkcSRKm7+ohOy57GQZWNOuVmnlEEFTmJj1uplMQlC3hljS8igowlDRJGLChDCoh4cYaEI2+TMQO8EgGGQWRkWt8AJzoFIDVqmCZIGdYBQxoYobeePLzn2okUkjwsQpu/BZMMWSlZMMCzLFwJqEe603R/76u4eHxyMpDDw8PB7ywcMhEHI3ZmFEuIo6YMkgUr2SEVFZShqHWtwsu0eS8sNPb45TAWPc7aalLsU//eS1mP3iFz/53b/71eM39/vd7vXnL4tzKjwup5xHTWkpy6uXL8bb1768HJJmTihPP/js5U//4Cc/+qOfluleNO5ULZZBbFBkbcIbCi3Q2pOfQJGTyiwckAYgYw1vruFPaUkIES0ipljjUwIKLDCQA5khg2iGZcggpEhhraJV1EUmyElkUZ9qUDGCmZHgLzi/JIc0tpiuUxIJj5Msjy2QwkRIwnTAvGPdIdJtOBjQoFBFVDSJJtEIUU9V4IgWJlOaqqi4CFV1pIyIDCgjKEWiSnYMAuwk7rTcYjkIR1LASnfQhUVs0jhBaigQe/BWdRBVBALmdVdrDk/BDA6WaHBBCCpsCjwhJo3JaoUZOSIOYJ3K8eExSpB2PJ1uX960zUkivChiPk3LUiK8OpwYcst8k7KUYDw9PqnqeDhAdb/P//iPfuJIv/32IZA94rffvqmOn/74yy9/+GXO+mf3f05N8zy9ePF6qNjt9gHsDjsGkiSRwYaX83T82Q8OP7r5g5ef3/34T/4Qw/7hPmqyO02ZkoWZSAFVGlSkd2OohDMCuBEtEIPcAINYOwrUezaEJqhRU/d0VOnRCmuxhCRxkBhDsloCU9hoyQSQMjgLUYEAEjgITxRTDcZI7uh7lr1wJ9ihmllAK2khIE7hO3rQjArhoDjU2NP3wnTjDokAwmiaTFJVM5EaMLEare1GNdYBkoWmSBKDYADMqZIErJRFsBgnZZJ4If6C3EMGxEgq6EAFXLCIZKiBKjGI3IgMAlUoFYSimEgWHSxGEVOoWdOVE5HFRk1F0kSZhAruIXvYd8skiIiylJpT3u2GaZopEh4REu5BlFIeHh72h91uN4YSiFrmUkqttZRyOByW6Tgebvb7/Rdf7P7DLLe/HH71u8eFwzQvv/zdbx7u33793Ve3tzc/+ZM/POT9V7/61YtPPktiZqMO2VRvP7lRS/U4/+rP/+KP/72f/fE/+4/2eSz+AHks5d2w0wQk9wGaABNXaJJkrRemwEVcxCGEKwlVER01D5JFNJSVvhAO5qCF54AzRLxVuYcaRIhIGgfEqKo0E7GQBFpv8yBKJtIlBJEgiZphNMnhe3IARmAEEz2RUB1ggFWXXeAAr8KgQmIg97AbxAimMVwkQoWiSTXJOFkicGOWLCIAeobsRA/kjmEShhgApYqJKCjikKK6mFRhCt9L3Ylk0SwYIxRo1KmSFphCkjADe+GupZ4FeptCVQWTRA5PcO3HVghFTHSAuaRiViAzIhA7YBB9VN8fspmyVBG5f/90k1XX4xvGcSzzMp2eyLqUpZTdOKakgnBGRERKqZQSQl3KkO0wmt/t/vBnn97sxl/+5l0U2mF/qvXP//Lfmdnti9ukekjjF49PP331eZ3K6x9/Fu7Lu/nmxcu7H78sx/nx7ZL9j/jiu5vd2xJh4hitAZckPogqkBQmEIaRBA1oUtgierDGVJESkqg5wpEmcmFouHnZVY/mjSNhoqgt6JBUB2kIvbnzjHRlSDjEhVGcSoqYCpPIECGMzEiUBMngCCRSEUoGYqAWphHcwRdwAczj4HETdoCMjJT7OT4SkmGZNmRJEFPFQIKRQ3bgTuyASCEakQIDAVFNCpNQc2iBVbUWqxg0JUHSGBlZXImAueZFsiGJ4ABPwiwYRRNodEWYCFIgqrgnUMItVFsRoVpWM6SAZsBFMrVqGsBB9G4c7m7T7W0+zXF/nCG2e7WDSAQpshvT8fR4vD8t8/5wcxCByE6GnPMOKYnMEbVWF1WWQhEdhsPhJlu+29nrF+PffvX022/eHyGHm1snj6dZBSdb/u9/+l/90edf5uq/sNM//IOfT2/qUGoiPvnBlyrqvueUNL0zKtWqStAEFLgpMjQ1kwquCGVVhAIGV7o1p3JkAibBVmkABlEc4hycUQqCotqAh2mSEFXJKpYMotqOhRJ3JwNKagTdWaqTkgYxgVZCIiIhBohZMjK1LiLd2yMaVaEGPdAAzAyNunfuVQ6qg0qyngsmIQbdqSaTVDQlBYgBHCk7yCgxIixgHlY9MRRNjYurVpECdVGEQyRDEtzoOxZjCJKLuZiiTxKkwlN4pmdQEWqtf3VQozvwXZvjHCJQMTEVDZgBtZkeggwmlcMuv36Zj6/Su7dPdZmOIi9e7kR1jafx7uZm8SJpGIf9MrvqompqGPLO1CTqPE8kaykqklNKFhg0In/ySveH8adf3Pzu28fffvf0eFrmIgHkIS8e/+pvfzOYLoehLqd0X//gJ1LeabG8G/IcD++mNze7KKoVWqABsd52jsCaUCniDA3PxBA0Buip5eegCJRwjwTkICVoEREuUekVXrQRVEWCTfxkjSQJdIgI1FVqoBJCVSi8sFYls8oureE3oQStiT2kYLMLm1fXSFXqIDiEaCCBQuyoe2CvMiiTiplCTWgp2a6qJFETTWIqPEjsaCMiI3KEgSrIKbWQb1tGVyyCru7gwjAiiScpo1cVCWlFHj0TPloRB9yi5IhBWxCshYJ6UgDMoSqh4T3soy0ztyeaRKaJmAkRyKqfvbqbH5fjF7vTNL17eHw6jbfjICp0qNowGqpU4uHxUURyMnrr08SkiYJhHJd5jmiVv85wiA37g5iPueyMu+Huy1e748KHk//1V2/f358ADOMuDfmX33z3zePMpfx/vv7dP/jxT1/dvri9u8XNOO6//p//4HOBOISapTd99Npaz7RG3j0PVRRUYQJMQoISTmkCxhggrNXXK8PC3VthIBghgLoKFlXVqtk0awg9kALZg60TjBCoaB2XDBiippYWT7hHBMIlhBAEjFTpCczmMIQoXQmFJkqi7qEjmaKJ0pRNwxKRhCaqyTQlDBAV9YHzjtgBmTShiZuZSVIwWoa4CFUMSoUzIDRQAyZUonWFdGWVcGHr/dC86ahVoloQiWhAUVtDYqM4QtAyVMTIpFV7PJdRqa4gQqFhqoLB5HYsP/hsL+GC5c0bPfoiGEVSXcq0lNAqKh4UaLJEj7IsKSfkTEBTVtWB8LqUZSnLIkmHcWeooZ5yZtQgc0437p+8Ghax4+m3kJQsHZ9OAI7TRPI35fRX778eTFOSz7/48j/9T/9nvNnX+auAkuJqjWIGD5ZSi0qopiTIYiFOhkZVVrRN0wxJHQCt9AqrhAdqSHWQrt7C76GeGkgUVgg1SEVgrCJLRKle3KN6KRFOiFnr6FCZxQGptdRAhDmkCEKlwpRUqHbnb0tBDwtmaJLIEkmCRHVNLcql2ppQe9axaTFTzQKrGCRGYXIxUKEGKKU5oJ2xndMjLVrmVIqithwe0jyS01zUW7qlC0wsJLmoUyKklQZq0ERMQjXEKOKUCA1qeHfbtlzpiNY7h4GgSTJT1THvvnhFCbdUf/HDw2+/q799XxEedakeyTSPwy4Nalpr8SilyBgMD9PEYIjBcpSyLDNJWSRqzTmJmSpNmbOq5lrrKOn13e7lYVeqU/xmn8xS649tOoaEprwfhv/Of/iP/+P/3v9A0+9mf3QhERGVgEtOtBA11NYiaEUrwUAllQrS3Qk6a1WtqpP4BJ2CS7B4a3qpLS1aXTIsQUeRFItEYaWqLCpFMUdM1T1YehaZZqiLVLp5WwywujvprGo15YW5hfMtmKKVcymViVCJYDXznUo20XC6p7BU1dkrwlxVIGLiA2qOkqRa1BSeWj8YkiEeAVpzrjukqhQExSTIGiy9cU/TRlWGSoNKiLAdmhcEaejRGy0IRCQFMkRd1Gke6s4Kc6SQ3mqklT1pRHjrxquUrEMMpllzGvXlXVXVfcZ+dz9F+e4N4sEj4ubmRT4k1RwRKtGSqmotlgd15sHIoKS0u7U0lOW0LPM0TfMswzCOifSKcJEYcwLjJ58fLD5fqhYgBGaplFJKNbNkcnOz+/EPv/xv/wd/NOD9Mj9CR4EjCsIBhLCKQVpKtIqqSFA9omc5i1UIgnUhZmIJX4QTY8I8ATNYTRtYMRFhAnUWy5DqVSMGMKsnRc2yiEwRC+HsR3UqbM2eYuuq4RFlKXNBgdasC43NsAvGqighQZUMEXWVMBUTZoWquHhaLOWmiCPEHba06MmgkViMVaMqqiDoES5sbsWWiiFaA4vGFL1GFw6tsN5yUatIVYRG60nf8gCNyCJq0ky4iPCQGkqmiBxihBXXAqmtY5oyHB7RvfctwttRvyaGWzCpmAyWX+1udsmnT8YvSvrlb55KKSmlz794tfh0Oi5BjmOKiOoiqqop5QyhikKMDJhasmG/r6WWWkopEmzu07osKQ0MjJZ//uPb46m+f5g1pzSkWpCHm2EYVOPukH7wxfD5y3R891d5X7bMX4q0pL0AFVQVU02qg0hGqDZfszUDCJZBhMYsOAlmxQw7BiYRT5KEomJwFVUqIgpjcSaXOThomAUAFyuQo6CSCTSoKsJapYMIUcPK4suMubAYa0IlUzCBqDXc0cJRcEjOqolh4kml+QUUGh5pRssm9CwwcauTwUzU1JO4MjQWiSWiubis9ZJtqY0ecGAhSy9xVg1JZFQnWRmuYG71PkGGhQCa1UyjhdBawIqSKtISVpkMo1iimSKliIjqEaweIdURlBriEYSGEChDAFXUacaEpCni8MMXP/onn33yLv/pX5dl/sHPvnj1+u79+xrF51IIVzWDqqiZmiVtPR1IETMbES2HJGoty+kYpYQXE6iJoKQ8AK5A2nFviYpaJxjNfNz7brAXL8c/+Ac//uwHnwfuK08tkhig9haAodp8YJJFEjAKM5BaiySoE7UyQhtPqYj19N1oilJbcVSMVTyJhVNZGC5oZKwlwhAKd/GSEkkJQcOqABRLRK0sJEOWguK2NGUWHrRcfQjflaLuSMIhhbWCkAoWAQ1QOMIR8JlprsVZs3g1STGzEJJIqDElKitiZhRWDSeRoElFoS5Oj7JASsAJV3GqEpkwWKUXOkCNMEGL1wqThkvy3qJdtRWzUs0lLRhd9sJkkaV1PwScyuqM1l8bJWQKX5vyE957CUqoqI6WZPxUX//7+x/++y/83+wPN59++uIf/uN/aClKmQHTaZ6Li2VLqeVVqYolDY+cU86pmYIKiai1zknVy1zLXEtJEFWO4w7AmAdLKQ2D5aFFj1O2/c2Lw+Hmyx/++Ge/+A9C8O7+V8dJPJ7Yc+NFIaI6wEfhCN0hMjFEmFADGgLSYd6K4CNMMYRTDKKJNcFGMRehwoFKkfB2jJ6IUYKQCHG2bHzRVC1kbM5YtkROgKheZ9fHqDW8QKoaTUKhEG1EKTXNp+TFcg4RqtEjxOk1JOCtMBIstS5MEyUFilBFpMZOeCN1ZKyZlK0ToBSYQ+HUYDsHVoI1YgkUWlFzJoeSLWshijYLOrIU8ZrgQ9PbCpAattaRgS3zQ0XVku5TGKOVjDjZDQ91glEornCRRVhJJSyi9pIQIlCi2v5wuPnUvQr0xYuXf/CHP3/12edLmQ81Qu4hkkc4tZ3NoqruLqrBKKV4+DgOZu1kJ6NkCEVpWYaaj08nkTGQIyKnYXe4uXnxye2LT29ffHJ7+zKlYRh2wzi+fvXqcPMiRHa723fvfvvt+z8PKXAoHEoDMpgZI2IIHUVyhCAknIFwbWcrtGxXqYvQTTCaLtC95UVkYesBy0qvES2oBxW4AlYlVeyoxQwJHKImSGt0SA+vvjCK+0zMoieVE1isebPFVEfGWCqWkucqXhHiWosmShA1vBgD4kaoKmr4FGlmngmRZFRzeEu8ZVjQvBVqaQc2RLuF9vLQKO6FLY7DRaRKMlMBnFqdFIpZeKW7xCK2ZVtKWARCjGQEfAErTRGJi/oYkpq7yKN6WViL9E6nEtLSFTPDw0lRZa1AUTUdMLwcPvtHNn727u27h6fTJ1/8aP/yhaadiI6Hu8pgSAQs57n4UipIry09DR5uJHME+p7t0CUZvGe3pzyWEhQRG8WGYKphOd/s969EhFwAOBEIs72OOOxu9TFFrXnNX9JEEQTEQURAEeEg4RGOcCC0H7gdLn6CzwkeJknHavtBfbE0qwIo8NLavtG0tupCadpDoANrRozwMZg9BARjWSpLncND8pzzk9mDRFERwoQZXhERJZVSlwAtoJ7gWsOiliLhCeFVpLYsH52rpkkSkyqQRFLLeaeEszqrxdjPfBcPeAScjlYUiIbTneLSYDZde0/bnqzKiMoakQolUAL00NbNyMKVapXmlZwjioRCHJ7gFipkRHUvS51qeIVWSNHWUNNGtQQ4vGU3A1gkqGb7V8Pdl9M03z+8nab55vUP5XSvOlqBWBqGvQ/0CM0ZFsRSS0ScD6kJd8EESLCCkXNWM4LLvJSlziXubpNIS/HNOe+VaTpOXn1ZXDVqeUxmQEStiqnWGUCSJB6DR+uRoC6mEoiKYA2Xbu04USoYLoBEaHj2KfmUlwfzhSrJ9p7mmncpD8kSRSv8FNXDGCYVrK1XJpQ0cIcYpI6IoRQrRQB3YJFycrpX07pPS+aSNKLJu/DeObA3QjHVSDlg4W4eNkfxytZu2gViVfISkgKpHSkgUBVWxISorY4CVsPNw4jqrcWrqLWcenp4gAvkFF7dqRUSAmtavPaUelq0rj45KlrDI1WoSRImEYpW8VnETUEmcEAdxS0gUWo5LrEs4CQaYtE6IosYRCRM3YNFU0A0Dzrc6s1nQX33/s3x6b7UWfIhA1ErlkDrGKfmTnenAzRVIUNFLWeSpM/zcjqeqhdVub25HccxCJHhdHxaZveIw+FW05ByBnTcHTSNHjHPk8BZTzVnn6eiUssjgmaqlVEdtZokEXABDVVlgqCKUcCEthvphKmpwXMUjaLzIqdF5xmAZpGRNlb1bGmgaRUivLi6azOPQDWRSlG6RhEWhWtxKQtcyhKn2UsdCIQExU0si1YziCoD4UEvYUeTmsNUJCdJpiq2hJTCMgcDkSkWCheF5aQeopJFR1ENEkZEUUgUdTGBBVFrhDqVMFWDtF6H5sEZOBEFVQQGVbQkXxLV0KsBAzoDJdQpFs1iFlC0UgDP9KRgixa5e0GEImpdTjEvGpPorEoBYIJkIr3cUMyt9bBItFHSONy8XpZlPj744tUZpFryWgltSMtSzq1nlwLgdJq9BKyd+yReKymq2Sh5yBGoc4FgN+5ub19M6RSUuZYXh5uUxwguZd4P++qY55PCsymDdZmSQVVtd0iaP3n9sykP8e53uhxBukdVuNoMPPVSQJV2tAfFkibaCFIWJVGiLGqTGsHijEXctSKNCKtUDgDCGANDFG4qjlABYAzxYPHAXLiwuiwVp5knX06SQoKp2ph2GBakdlSe1lAPYbjqtEtJTJPsLGWJYaljYBfAQqJC4cnVahZN2ZEpe8s5LBCFDNSgOVsWmHigekQFRUJEqUoEMEMrvUScIEtQhaotW6oaOAgHICPI6hJFdRGrzAZJQvE1uStIqKgxaLUYa5SoUVCPlYVQN6sGZ2v5oRCJqGRQDaKph5QUKe33r3LaHR+epvmp1KpqliSWAkDVVJNZVrXU6v9ra15jdWDOo5m4L6oQ5JyHZSkiOmRT8WVZ5nnKOZdSRJJqKrXuDzc5j0G4+zKXcBdW2e/y7mB5FBvULI23abj7/OWPp/dfv1/+izr/kmWh12pWk1VNVXzhIgjUFt2KHTkG6SHOoCwcCE/KJEySDIYK0QoNYWjrLUCYRG2tJulJwpQiQYg7pipTNXddILNZHdO08OSthb2mMNLIZABpSkpUDQqUKVeznNXE9h43xl3GnhJeS6lBqlQxgUYagqnFgU3ULEs/5rAdmFS8CqRSnWy9sZs56oin8BLVI2ZikSyB7KImIySBO8QBVBGHLIJZ4ghOQSGHoEaQ3mqdIzTcQjjUeXAsNcaYM2cIxUTArJSkGFRURFv1ggnEICpSJYoZLd3kO4Y9HZ+maXKCNK/VvZKtF5UlG0qZ3SM8PIIUSybGiEWoeVAp6otny8hSSwWRcy6L18qcZb8/5CHlNJgmr2FGANV9p2qWEBBVSutsA7GsknLOVFPlIEW4eBRCA9kxkCnEK2WOo7t79awwhTIKaZBgWiSLlWGnFFBRk1iSlkIjaRClhEuAdMAZSooJm4veGVVsVp3NikgRrapBlsV9cRHNOVMykSk5ECQzNNlg6s6Y6YANtJF2kPRy2KkMQpM6ST225BCLqinSASelpqgiWZBb1V+r4cqgoLaygSIammkKUxF18xI21eqVLmCCg6l1K1aT0CSRNCxphilkoVfGY7hXDF5yuIU3U2tux0FUKH1XYwzeBk2TKZIiZ+5yYCCSw1QU2hKeSLPmeZAi7laz+DIvpRR392BEiWgQNQCYWe2nCgkgOQ0urfN7WOrN5MqytMw9EbWcU07Vq4i5E9Q82H6/H8Y9KPMcpU5qtrex1IUs4WXMGHMack6WLO8070SzqOXxMA57Syg+M7Jxx+IhdAVFvealOsOFUSsGY1XMSIWummzYt7ptCmFMZmraTlsNuotSiQ56PBFanYhQLJBZ0zGlI1hCIO1kwQg4tTAclkRVBSbYmYwxJy0WVaOWYDMb78JuYC/ScLAdsFtyLstj0TA8afKU6jBoupveKVVk0GGvaaCl0KhSKC4S0lLYLFWxRbObSlK2JGUbXaO2xvIiVIUpTNVMmCAmArMKpdQAQsQCshiqRfKa6SqsmhdTsebiB0ySpeBQUEw9pRgsVJltgRk0JA2qCkqAlqAiTisejsS0f5znlpUR1VtuSE9yhKEfWqgAhiGL2DDYvFSNyDm7c57nPOxIujtUkmmpLlQdcrbQ1NIU9mm4UUnH0+nx6fjibjedZsuTjGNSQ9QyPfl+b3knaVDtDVPy7lW8/Im8/+soR6GAoeGtFmXt5qNq1tOXNGqoe4MLZsmqyCA0VkO0shhWqkCSFERliDgQymLuWoKiRVhsQM5jUiSNgIYKrAQmxCyy1NKbCmrkVG6s7jlZXYwTJYronkCtt4EXajeWRtv5KIur11j8KTlF3Qi4psP7r1Vy2E6WSXf7GHMYFbX1Qg+lwyHmxEkl1CBQYw11DeYkxIBANslmeaBIc74FrHBHnBhegEVS9F4M2fPgEQVhIUzCQaDKaI0VBcEAg5liKiUJBqkjqlgSbU4SilhPkhKlWhVdyFPoUkuN7qSOtfdHSrkUEpKG0WsZkoogELXSFLtxmOZSSh3H1M4dqbW23ILwyVQh4SyWk1pKOUOVZpoygXfffXP74q7uBhlTVi2n4/1336ikF5bz4U601RE6hbR2XGY7FMXNUtIkpsZiQuZW4S8jWpFpROsHbgaFg+7UkEHERD1QgQSVYBWKUhFSKIvbNKMSlmRMOUsyaJIXMEQkV3ecQh4liwCigiymajXrspfTDiXbYigsi1PcpRYZpGSzJAdNDMsyHGp5XBYLmLAY4RXJvvoOyLK74X5xnxUpZbF+miKpBtUKQWKlVRh609ggq4K7LEMzq1LQajPSVJYqNonBLahVY4a2rF1NFg0l5GzhaqamFVIlmxgQLlHATHN4IMQ9WcmCrKapVXYsoBqsVhUdRFVkp/klZCzl0UsJL+G19fSLgFK9LooIurQKWfcAyCSijw9H1XRzczPPc0qpVDdLIpjnSQ3s/eM0p3G32wHCYKlTLXN4kXADXh4OQ7Jkqc7z0/uHm7tPp6fj7ScwtGb9pIq++Ix3P4jljcKjFoZlLAPkIDWye8AdFCRVFXGgqhRGMJQe4aREYIEptJJVGWrOEMZAS0F4Le5SqXMjuaR9siGlnAaRoWoqVgSPixjMBHvL1AQLRSTUjOM+5sxFIuDuzXdboVhg2bFX20fSQp8lSjt2kALVSknlN0uts+5qej1b7JInZKG10zUp2XTcqQkB11xaY4OoikiIpBzBESESpkTMBlEaJZ6QQofeFlRtap1/RE2QFRDJSIbUcjIXqtCypXZ6Ug06pAIeEkF1tQqeiNxduAo15oI8izON2L2mfVaRaq1kqWWuy9ROexSzUqMuxWv1WhBRq1d3ApaS1zqO47jbn07HFi5yr/v97vj0GK2QhppSJopZSmmwZKXUx8eHqLWU5eWLuzIvX/3yVy9fv9y/eHnIO4DTcbq5a8cyFYBQEdX9ix/rL/7Hvnvh3/zXeHhSHrNOubVHFK+VpZYeMpNUICJIokBK5CCSRF21OObiFVyIGbJEVYnRMEASsRPxbGANokBanpcqdoKslHCEjo6leq1MkqAQrWqzYUp+GnyW6jwFTmEFGhZKlyg4aj36dFNTTIziztbIzMWpoKXTgztpdQ6TcZAIr5lsNc1m2FVnxKCEIGWnOA2oY8s7EE/SSg3dfFa6ECKpgDOGyaSog6HKCqkUUkwiCyVZpqijdX/ZJbHVS9CqMBBORvWoAZdEbYlpoUopRaJ4xGR6Gm6r7aRgt99RlLUfCMJwj2pmUcK9Sm9SEhQxyyJqlh2qymEY3r9/u98d4JiOx91+X8sSQZMUwmCIqsHWZhSotbx78yY8Xr1+Pe53kmN5fHr722/HYb/70ae7cTzsD9KKvaK2GkyA0JLuXg3Tz/Hdv8m7aR/IiExXECyVMftca4ubZhMNqEGymllWqkCcmClT9pllCVbIQnGEi1JVQ80EkmASYYtZIcQxGAJOdwmlW4QiWlNAKtkKrRMncEYtdaZMxImcAkTszHMuDJZFZPbwCpGghZknn6trSrFLD0w1iea8s91cx1RsYbhXUiwnEVkEM32SKCIFrBEiTChGFsYCg4R5QXP3kEACDKaL6ZPSNVJQIO0s2myWkhrUWnxYgHCKJEutlawICI8oJTgHjcmYTJPDUnhGBk+stYYswWoQuZXdl8PLn+P+6L44I7wfAxER4bUsxSNC0jiOrl6WYqbLtJyWent3dzqdxt3u5vb2u2+/e/ny1TTPOY/TtOx2+3dvHnZjCvecd6Z5yGMa0tPTk7tL6wxV67jbgxigXoPg/vYw7g77m4OX6nkRAJZa2ycQQUO+kfKYWJLPyUuOgjLLUmMuUiVEYYOlgWaW0mgYNKlkp5SI2hAfVd1be2xqZhSEJ0pSVRMqK2xyLQXzzBLu4LBErqgRx8qT60xTIAXVF/U5sdDdK1hb8R7cFdBStVAXYNIpx5PmXUvVkYAS2bRQZmp6sz+4QvZ5d7Mfd4NamgyLViXMTAQFWCIdq86KueUlUJWR6XCZ4C6wiOrLzpchxMlFYs52SlhUI4lrtMZVWdKLbDtJNXwJr14JF5CRFEKKuwvBiMm9MqJ7iZSzpGQCZKlgAgU2RL4dbFANPXyWD6/qmwevBYSoJkuL916nrZuVKn1ZylJSyq0l0X7cDXkEdLcbReVwe3dz93Iq36VhR398epi8uu53EKQ0iqhYUhtMRxVTMEp9ePsYL2Qcx3G/37+41ZycLe9bITEdj/u9BCFKUVW1tH+R95/x+KbM72J6kigWM+djPZVl4kIJG7GnKdSyirVScjUlBK1DpENcLYmDSTRBxxJj8SGYVVVjpj06Hqo8ek2Qx5Lu3Xe17kIdOBILESEqw+Ac6nQjBUF1q64eQrpJYBQiQ3RxnCKE88CHQRAyKH0cYp80E0aeWNP713cLAjsb7/Z5n3QYJsTCLIJkSVWrYQEWV5So8N4Mm0heEqRQAVXHrrKG7EMhslAmciZdq4fAbCAPIp+M+dUwmtjM5W2dn5a5kGqSGFkgNA82B04FMrh4PHncuz4WGVMASKKDSFLdDWo52+HzdPOz/PqPXGRZJkJEzMxKKZqSirr3oJy7kzRTMGqJlGTY7VVVwGU+7uzGVJLpYb9jxH4/vH37AHBZSko5p4TWvlq0Vk/W2yIkS8u85JRrXdJgOaWU83Q6pZRTNlDneRnEVA1BJo67XVbMy7s4neqpuE9LOcW81OJL4QQrA8XrLmQEQoeqDHFBDUqJmMiT10JCNfWDT5iJ5G4LAyiKJ7GHkDf0B4rOdi9yE3KDlOmLxpwsQlApiAy+qBiKjEga2SBVpGa3iCxwGMOkSCkUgnWJ8uQ6peQp+5h8VKQaLCU9fna3IMJkGIe8SxhGB4rXAFPKtLxEO06s5kJRd1QR9eCxlKQMsZBRCnzRho9N1RGylAO0qJQakuxG7dVgn6T9jSYRSWr3wan4BFWmHJpDczugmKTwxADpXjR0JB+I3dL6/mnWfNjhle7uMKhmffmjyDfL031ZTr35JiFqKtKi3NEkZjsAkhSylHkcR9DL4klkXpbIA9yX02MSOmK3y7tdikBOGcAwjiIQiKnVWkQkqdZad4d9CIIO5GWegPBaEJifnsJ9d7jRFNGSmwANWR7f+NNvNMocPBaJWYaqCVksVeGs6ZTzkCSLl5jDLTlDknstlTP9GCxRgNZ9S0xJKKvTOZWYPBbF06DvLL0lJzGzPBEFsoiIlMXqkk2pZsJQc2fY4JaL7SWnZFCaqY3MLanZI52ERSaqSBi8Km/MD9nznqMBp7rzSNOLwxwe4nWwnAaqoHX6jOKt85lprU6H6KKUEoCYiITkhEpKddel5BlJZRAXwA1J3GrZqVVVhR7Mbpj2YjuYC8WrzFVcXNShNXINOutQnOJFMas6jJAsJKrUWCqDdBXdDS8ZI31H3YWLKD2mp/v5dAyGUD0IFQaitUNSi94kXSnhXlUVkFo8IlqLM5Ap6Tw9tVTdnPTVy1vRVDyiQkTzMLR2pTkLvVjaA6Ipt15Iu/1eRaane0bkNMLDIcNuX8M1oqWBUlM+fDYOny3Lv5rr8hRSKft8GCwMRQhaTkmTeHJXX1i9ltlzXiSX0BM5hcMpEWCotXbLTo+FMWsqoifwgfYoqeTkMJGs4ExWVqRUzahimpCUxZXUKruwDEua9lnNYqQokHeZg8g0ZXqq8uhWh4whi4gqZ9RKVEfyiqppTkPxidLyd1wkCWioiUVLWMAsScQS1el0AZUqSKliYJiCKB4zloUmagmLFhGlmgVCNCGlkBxMFliWxVAinh4e5tMJvjUmAxmsIXVJ6kFNKQMaabyp5RY+mjD8sXIJGUQ0J6QqWGa9ybvXXqb7+7en09SqY1Q0wHY+6DDsqnsSyqARocnqsjiWFn5qZ2zVWh/f3+92OzVbajGzWmvOgwdvDrta+zG/OSVL6fb2dnq4MdU87IcxeZT9Yec+iabHpydKOnE5HA4vb+9ETCW1I5LcQ6xg2NmLH9NuFd+FChNiMAyioABJxIJj9WGekhdYjrRg2GsiNXmoFSaP5HVEwFgSXRZCqg5zTo9ID5ImTUUHFxNVowzQprTdnEYKnEpogKp+tOG9wKzuB+5SZOVoRkhkjUQbUtonQKrbUTLFEKEulWnxGkvoUfU4pFIrvQgqHcWkFRcSbihKT4Vas4oE66z9WF5pzZBEK0MidGEscVoqRaqoWsr0jJplTDpCbQkgXEstpwWLRfjpeFrcm+eMoqLK8PBqUXfwnY0nyKRiku8kXlYOgIQkD4okWXay2+FGDz8//OSfhe2O7756vL/3cEnaMWw4W+6SZrXeU696DYZHgSYGLYmZVa8UTtNcahmGIWVrRpxKSjkP45gGg+Ymk5fFc97f3N3t9nuynabu9GWelykJIAxNw37Y30CTU6TWNAytok0AoRFZ7XZMx0/H4ECzGHc+ZlG1OaKcqk+zH0+yOKTwkFVlEFburUKXMvqytzpmWHK3KBKOfDJfQk4YJxlDMkR7XmJAgZRUZQg6EgtY3WsEIBQryR4gY8RDYpb5rp3OIVbJWj1EPZmP5p4WN3cIRU0GS9kUaqcaMo9p8GlgGViEdWJdRCqGaiNYEdOOIQy0dmxUgknNLFdvLWND6O1g01apW3Jurug06Jh2ow6uWsyzlxI1O+HuiCIyaapqlCSSrR84woF1hKhZS2QCNEmM4ftgwGmgCdRGag6z/ae6e1WW6enh/XR6IgO9VCYDSMnMMqDRCrJaNVlwGMc6L9I7vosvi1B3u900TTFPWmS/P0QEU5BYSk1DGna76fiUVSyNWfeH29txP56OJ3pVxnx8MpX7d/fjYZeGg5qpGgNqRrIuiyUjGKCpQLMCN+PtS5sVBVryUCyFSJ6oU+VsPAJPrhTTakMBGMVqa7iaLG7HethrzgToEXQ/JRljLLQA5tY1uDfA7D2gB8tmGYITK6WWMlMgZqG2EO9jQCwJVNFSGVaDsgBOmcJCMyNBFYwkcki6E+7U3IZqCTmlOyt3ETcMDT+ZPGp5EKm0kDRLMmiuDDJa+bqkJDnZECjh1WsRIQyaUgVcxHIadokai5rnm1mSa09fX6TkRMpCOkwL1ZEVo+Whta9OZnttRT2aaWPYo9iEOGodhkgpjSFT1MJF5AX3Pxo/+2NKWqZ3ZZ5KOXlIxkFUU2J1kFUtl7KADPfqlfSUDGFCukNEvVSzAai1zCml1u/2dFpytlr95u4QRC0lpSWnZCqWUzsTu3VwTqKn05yzScrhdZ+SDHm337eE6lLLbtyJICLcXSwlZb77HC9+kd/92wMXiKhFlqpRiaJisFRHnW9292IVlkbbIQFyYixkUiaFjrrbYacJXqJGRBHAo0702TSUFdb6vYaQEkJkiawjiRJVBZa0QhSaqQadtCAsxXhyDKi1Fhd3ZEMCBkhusDgpR/qgPpqNmorFklVyTrej3NBu3M0jJ7VBKDFVFoJpnIFK1BILVKBJU4sDimio1ko1Uc0upLqISsoYR2391C2ZjVRrh6QXjsUYVk2Y2iF6RRQ7s2RQZ80SomaWk7SWVGkQuxd5y1DhizyY5CEivM61xvBKh5tleqqlsAV4A2rZw2EKmmVt/Qm8llrndvSPQiBilkw1ImhIo9bHJYK11mHctfrscDLJaTqN494kRfFWhrRLyT3ysCulMDiXhWKWxrksechi+2RZVPMwlGXeH3ZEAMksqRickQSWj7UevLiCIaOHTnOqM0xkN7rpMWvZ5QcZljAzzcoQLmARZqFmLKLuc9SQyWNyh4kyG/fKG1qFJZFRayueac41sOTIoTmLDKgi1Q1G0VCae+is+TvJ91GzpAUQyoBhkJ3CHGZgNkuQwaW6P518WARIrIJgejkMFqQqElNOOecMLKwW4jaQMgkdUYO7JCmJJbGklk08sohKTnZgqsguIinnlMaUjKS1ds6KwZJKFrRpFRiSmbBQIzwZmK114LDF9gmDtnM6WpcKoKp8xyqKW0smNlCH8ZPDqy9LmZepTNPTvEzulTQ1rdXExNBP9qyt3AGIKGSYZbZDyDxEImWtheOYhzEvy0LCPcws5dTAtWrJed9OisvZIlpQbAfN09OJlGHYQTTE8njYHw45t1g3yTpNxzyMwViWWQMpDxoREZP7XOQIWPBmlrslcZlUaxzEb/cuow6D6SAyIHjicgxfRGlm8FH1PcvwJH4q/lROJcq4T2PmLqkO+xgp2cRGMTMu4BFxxKx1kapiVWMeOWXx0BySXCzoTgsbKxWm1edA1vC95FtJu6rBlIQvlINgIR/d4xjHyn1OFgmCdJNSIRYZJgdTOiVZrJKAi457hBV3TXFDqHo7EjcJU47DUDGKh0KHGMeohR552GnKUGlHq1QJ1SRqlrKIGVAw5xSHFCkwRDgnA0ylqBe9mZFSKLzZiVpBDwZtsXiSyGa0scLubn+o+XZZ5lrqNB2PTw/LPA/7ly3v1czUNEqtdTEz5GFaZjLMUkT1Hg4MCGotIkgZ81J3+yGCZfFSqqXUjnmxnJe6ZMtAoB/iZy9evHjz7Tckx2EAWWtNKeVhTCk1zTWEI1l4zNPkpaZhyDtNaQTxdLx/uxxDiMAhdnOgFN2XOpib7+C7Xdp/Mew+kcETZvdvpnh80sJkloAoOt7Hkk54fOKy4Khc0rAfD2N+4bhJenMrHMGREHISoZaoSAxh8VqCs0pV05BUJQVZHRWqksU9VAuSQF0YqkKYZEKzxG0KFXlielzkRN5H3JQYLTRrukN9K2kedgtT0TQrZll2AzQCQ1p0N7rv65TVFyK8jF53SNmQhpGCqegCKf8/nv6j6bIsOdPF3H2prY74ZIiMjBRVqCoA3QC6ad1Nabxm5Ii0+x/4HznigMKMRoKGS3Tf7gtRqKqsFJGZEZ86coul3J2DU+D8DI+ttbb7+z6PWvZWGBQvHAW4OHvgT3YfBVVrLx4G21BuoTgkR8Imi5IANUREHUBTBdQxS5HLAKOqqqnkZiJEA8aymlYx5YxgcokpLjknERGgKpcoNNUspVRAYJFcigIS2lql1lprIfoTXlkVS07zeF6WRUS6vg++u7AX/tQ2rEVYcopN8G3bcE1iUEqe5zE0LueMgGSMsabp28psnXPWXT4BhTnOk3MWSB20RKTkXLemZn3iJTJ6rhP4qdK9Vm/AUGjEB0AKQK1So0vVzQQV8cMCDGhsEKRFw4tz4Fy2OVktre+bfuV6lOYyVVEtqgmVVT0TqHF82UkD1ItsBoyKVk1VkCuzVr2YnwgcGUCjWB0aJMqIVjho7OgyWMJMZnFKhgqiJ7JkrGDKIMnYijYqsDojsibeIDHqbNU7HuoCKrPqgqlRaMQ4sUSExjnAhaEos/Gsrlze/cKISGQUQJRJqlQh15B1VsEAe+E1VxROqgySFbNSNVpYE5JBEjQVQNAZ4y0iS82AqIbU9816u7oz6GvllOYYU60MQESGazHm/99ZplxzzvmyRb9IUkSAyBFRLfWSaC5FANDaUHKZzku21fuG8E8a9JpiSjE0XUxzKAYq+ECE3jvPnG1ouq7LKTEXsjY0YZ5nY+zlkXThuSh4qtZzUQJVcTVfOwRjDuKOIDOiOn9LjUFBFVwmV2qwBluHFJqGUGkRjWD3ha2SF+uxKd5NaJm4WFJvgayCVVDV7ACSFpCoXBLWxTr2zrHmylUgkStSQJS0XFhSiGJYlBn1YuMga8AqdIDOGDVKWqTmKlihqWDFAFAuijPYguSI7JGak+RRJwCjgKLGKLfKnahA9VhbWgLkqpWkKi+DINVK0AMFDqZWrIIKxhBeGj/8rz6nSzqRQFHKn2ZlxqoS8tIVaUukWpuKQjaaelaoQIVhEUJga6yQAYALbZ6rYalZwF/wObVknkvlOI+1ZFBSdKoVlS5ynwvNi4VFGFRYKwgogHVeFCpnkQtSV60lxA6pgKKyqMB8PMcltsMgom3TgtIyjwiAN9fzeF7Os29Xl+Ww1jKdTwRQaxmPB1JhhSVFIAyhcWCdcyJSc65p4ZLJD5TTbY0tsmeupeTKJCICCSSJ8LxQOt4u4pPX1kMIHtuVhGvvFzUhyZZTg8TO1MYfDVYiS7aQmYSq8AULb1EYgAXACiI414AnZaaqRiHLYiV5zgqEBEKmgKnKItkokogFbbkGEIcOyGaYkxRNtlqTwRliA8CqhRAArLH2YDaTSccaoeZgLaEqh5kbVyaqkUCNrSA1lbSIembNkSRX4VmHkSFVVDXOendhPxiHqIIWuBIoqFy6c9ZYp4LCaNDmStNo0+I4A9qMtlgfHDKWrDALCoAY4soCYlAdOa6qio7A8tJIQIB5OaUlppRyzqWmS3zeWmSRC/v4oidWVeXLZNBY560xtVZFgyoihIDWOhbGZQaAmotURUMll0aEyKSY0JnKxRt3UaPFKY6nmQyh1Ol0QkTvLBE6gsXa1fbaOkdEzNUYEpEmNME3AFRLdlybfisUTE7LNG/iPCoj4FQ1g5+rSIUNUHOOIdZKmRs2164LzdqFkVucY5vSmpDIeAIDuEcCY50JpMSSay4F1ZEDAiJnyJIJxngEMNaBEVBoGG5VB1QWZesL4mmph5mrBAsIwFAL1kjQoMWiGJUzJ2BrqCJaQjRKjcF/dX2ozegEjCoqzEbnlkiNP7PN6qzSoGgFhekAXVIapAEeWWKmfER5ziBMyNwRNkrKYlDw4sWVirUSqDFkrSNAglo551q6PJXzKc3TgiC+EeKEWIIDE8h6KAwIYoihxmUBLRYNGWsxDKBrrgPca6EUp3k+LcvCoqUykEUyoFJKQdco658wuqqlVlW4LLPkMhMqF4coOX8B0apzHgFC0yxLrCIhUM657wdBJaJagEGmafZd59ru/Pz88vRIoGDw+npbSjbOgyURLjUba0RF6kUVAkhkjNV/HaAuJU8x6nyS49Hk7Bsj1u8EK9jZNhULI7dQsMZYVFPdNK74JoSrjTZzc6w5gdZQy21NAaVt27NFcC3ZBq1nmGvNgIQUjIVgfQWjl9UTgrUGRAcD96TbC/DIUiLsSL3ywjYLFhbmLKhsHCPNUo+AhRqHNki1kABZpSATIililmSxJG9NMDZVaDWvIYmhCc3JBTJOwKviLOUo7ELjbGdtV3iaURbbqvagoMpFHFQ1JFIL0UU8pcLMHMVb8o6sYeVS48yjlDFwYtXSuGTxwitn9UKhkLcX7yIyyyVXmBmqIVDs2BgQho6YS80ppyS1MrMokHGiyDmBKjkC0VpSzVkveyjEWqqxhktOMdZaVSGEQGSY2Vob08KVay2lpMuHlSHKy2K8iyl76y7UMjLkva/yJ2rgaj2wsiIaZ40xy3SqUmu3amrjnBMmg5riLMK+6XzTAEApy27/KLtjOo3Om7ZpKbjkTZypouOmeYZIasjBkYkMzMYFd4V21RQjpuaQRgde65BGEw9WV4OF2nSZBrVNcpqYuWarFsEqOVXNKStJZ9WIAUEloOC8VJBqpQRQtNX3NoFLVWquC0mpvVAPxmeZY2UkR6YhINYca+TKpGTIXRAYFrUQqjfA5KRGxIXQAJmKPiuAEFOTdZkkNUCu2SIocztrniEoeEJAEjBUVVDJICCiIF+OIJaZqjXQWdewamVmLiOLets6qsEVH3y1pLYA5iLGkzGOEESrYXVkkgCIEFapMptgwPqireNaS81ZmGutDKRGEAAQjfWqUOtScrLo1Gg1NadsjYIQ13opqlprnXMpLqpijDFESWQaxzRHVGrbzqCJ09KTIUSuxVhU5ZKWZTzPyyR/0kdyStkaklqm8ykvsztP5hU2jUVBVZPTPEptujUiSYkq6trer2552gesYR36q05diKkcvO7OOiJMpD8SiQQ24AyqC6/INCWbke3xWKxSGJRnKrgmDnweYo3OTEpn2Y5LXWJBrSjsQVQtGJ5rZInildWqCQnBV1qKNqkMTtUpuNrYYI3vcDHIZ7AH2yzYChFkY9A5Z1s7EGiqS2VNnA24YC2iIKgtbVUUZAvGn0VFs5YxYQsUWGtWdWiVGiPI1SRrLxj0WJfCYEidJQXDgKhqORk7kHVVgEstpOCILCoU5irWXyAOSbH6kIwai4SWnQEVhqpctGYXPBpCQOREzrdorAqVKFwkm7heyZ/aW1prSTFWBSXrrYoURUIgLotwBUBRdtYqNARUuRIZ2zcXs54ol1pKyghaJFlrEc35PHOpbdMUrr4JUMrheFhtNoLgWrveXuWc5mlCJVYpedFzDk1QICy5axprgvfeGCO1ZGFjECmocwjKKZUUa1natmuvXuv0EHxuh9Ct187aKSzWIjZdoN7ydC6HWEso7FQ6wBXMQ5nKPplTtrc++NYLNeqIPHE2+WQTVBHDRRLXUi5E0pmz5owEWbhyQq5ggigwgqg7irkxXS0KnJfKpiMQobgYXhD7IrxgAfSCxvnBGWNce5ECkbKp1ZAz3oMyaLUZEa0F8EzMxmUFrRmtBEtUkYHQNWQowETkDRAriKAwWkREsWTBWKmVOFuoBJegeKJ8cjqDA3CeMZc8qSog+hCKuFwqEDUmAErUhEVAO+u9Mc4YtRarGmcbbMmRNcKUY8RpPi7r7jo06zznlGKJM+dCvlFCYSklo/VGWDmDVKm5Mvumdy4YY/PldgNAwpJr5aKVhdlaW0pGJGbebDYlZgVNKRFSihERc84mOO+9983h+WV6OWbmWKJoNoUQq+laIMqFVSUtiY7Hkue+63wIzjeXNBIiCnPJeWjXt1//Tb26q4+/tSQwXFdKtG5aWr/1d3Z4dRp3y/iwO3x4+vn3XY1b0q2eu3qaJYsJPQ0DTASiFsCtcpplOUseO2zvrbW9HCxO2mfjYh4BElIwYtE7QGLyilpBknHW+6joBYrSxLVETUuux3kTCLp2z3quR/I9GIPWk7WXJyYiG87OF0veGAJmT86es1i4AD9UCL3QACpaErGgMCYxjSew1YTQN2Gda4pVEIwltZ5aG1gMqxiVxrCxSaR2464/HQnjuBqmtmUkx1zz2bYb74LRYRQQxIKmKAs3lihQQ665aF4I0VNgEnIWVAWM8egGlHPG4ghcrktJS8mRWYHFXJyaClIZjBjUzEU4oUieq4iklMBYYy0qlVJiTP0wTNO8TAsCWGsL5Ev4bJxHQ4ZzzUuyxjjvmKsR4lqn8RSXmdpgKzvgeY7VqDEoglXQWuuC01RqLmSgULLWG+NU8FLBRkQEQcD1zTu+el3f/pkqggmgGnzbmhbJAZmr+6+E6+n06fvVfymP/9ClHyxnZsiGZpM6dC024JyYAZAtERgnoWu712+HN7cUdlFGDhFM5mS4IPnCnGpRSKWkiqJSyXn1XWREhiwy45JEzxXOvNqYoTXNzKfICxTf2GAJq7BFcGSBURGt955pDbQOw6oJdi5CkgMgcQHRNcv7kQHjg+qjxYKU1IBUQTHWNe0WOeb54maRoW1b05TIhQVVLKDlyvPZn6b1wqYy4LIEI80NYWPKUtPRUmMAnfVFIeel1ursKvgByTE5xap6VgmBSHVSQSnZKCpoCBQ6660hgFoKc1VUoD+50A2AMqMhRKi5Sk5lPmvlVOr5PFrvbDuoqiFrXei7vuSSUo7LUlO21rrG2+ALV1YpsVxAWMZS27WKIDXFSX3T9Zv1cb+PyzTPS4zVWeBLjJ6sAAqYsG68tyUtJdeeDJFxzlvrAEGElYvApWmIzXCnSIIGL15cuHC5LuzYcHX9ebd+dXj4uv74t9P+HzW+HKm+0JnzstHWe6vSAqBpuxYRzDb1X+LmCyHPp1NfgdAm5AtJuGZONTOkaTlNaapQjfMCOOU41pi0zhkRyTX+OlyFbg0mCZwBgrfBWWes1DwpAxA0WAWFlbcAn9mw7rehJWuJLnwqm5lM61Cb8bw6zb53/avtoREzPvYAXjn0K3Kvo0gltRgQxbvOGVfSSdIkmlkNcaYlimpp2sKWtQrHqAsyqaa4LLl0iLaKMGLNmSu0JqDaLBUkGhGtyZOooVqPnPlWzFVYF9skrC+Y15u1NZ651FpKqarkKGi9MKTQeRUxLAVACKEw15Sapuu3NzY0qlovt1fOOWdL1PowphxTylwds6gCYE7JkHHO6QUD7R1XNsG54E+Ho4qogveemUtha6FmNsRkkIIFa1il1goiKaWmlLa3LrTOuT+B0BDlokeSC18cQIteKNFkVVT/tXrswnD17q/q5u3zH15/mv/2CLvR4lmgSbCGmIFa029NoGZo8BbxlqQvVd2c21oIXEFdABSVqxRhRDTaBGBOMyhNyzyf9q7hahZFI0ytbzfdSr0/l2SaVe+E0HgCC5kkpny20DatJ2oXEIysiGwoidrWtgjIpXrs2u4KIc/2Jbyc7QPeYdfeNVTLtU6blYgZDzzuuRSeG+oITGFG0ZoXkQwIUbByUV2ikehcMH02UglyKVwXrFnFKItqYoMASiponEpNaa6UO9MRWSmOFSvNgBkBB2dXzuewjmmicLUa7upcuGYWFkVrPSCocC2RQH3oDFm1Vl1wCkjJ+saElkIHADHGZZlLrsqQ02Ks79drMOZ4PLBwPJ1KqaBgQwjOKQsQFq5SIOfkmpDmRVkAaV5mVWDW03gGss47Zy1YR4jnw5FUc5zXq15FhKtwRoJhvVFAsv5fHbeqetFcF5EiAkiWjCpdQugWAI0yItH6dvXlf3pinJ7+rhQ/n8sfF2unObrpjTMldi75VeMonmSJNcbz7ntXK1f9GemRU3FA5EQphLbvhiWPqSxY3X63Q4zXjd+ESoovo1K4hDXYG9uaLZe8lNHX2llQgkcZD2na+I3iWl23S0eoSx89mmJBDBmTjULTAri55p2g9R03Xuf5fC5913mDK8qa50gfMbWWRbEghiXGJFxTtKYBxIKYvS2ad2kac7ntAgeXQDGBsBoIIFSUqi6s2rnWkimsUgtLYpLQrjvyYlQUkXgpgYWOnKDsHA1jTKS+sX7kcylZRIncRVF/IX5yrdZ5Q6Yo1FpVBFEv+QpOS2XJcak5l1iW8xxLvrl7hdZ1q7Ugnc/H87zEOVoy/aottSLgaui7vp+myVrHRR4/PoBAzZnIVFUXnGNRgMI6x+hCU2LlxKUmRLDWSU51GWvr49LxajNsrsg2gIalopTLpcacL8eNAihejDOFAJAMAF7KC+vt/ZvP//JYdk/7f5S2OXCTk48alwonFpdPr6OggFDiPD0tu7EkATobMwKq8dY3wFLKiFLGOqmK5DIuu1++635zgysTphMbH05SlsICYiwgUABE5dumvwsh5TRi95E5j8X5Wi80IY4jg6BYUqzMLFjFZG+qDTmsTxs0n91WjimfZmOwuTIeuOQHOUyJpVRpVZwF5qVEEDa+VyFERPKsptS6OIoGY6pKFnLVujAFRZMUKhRmJW22zQa0CNdgbUXIpbRkPJoKWFVZAlRcNKfluKL9Uvnd/VcOfcn5ouwVFS5s5LI5B9PYtm25ZuHqnGMVLrKkRRVVUY0BFWdshWqta60DoJRrP/Susi/Fx1RyVRZhAaLQNNZ7VeULKUarCNSSnXfrtkm5TnMspV7Mv/1qa1xQAGdNHDlYa20wvrFNZ503KDXNNXeNa5AQxJaUAJPKZW524aoiXED+Ui+tWiUDCAgE5DZXbzfD25+ef8ek2TSFaMmQsJwoBnLP5QXiXG1mLDsrZ4T7xt41fqg0KXAwRSAtaVzOiRcWu6Q4bMzrLjuG8wnqVMk60eirEkfCJY5p215T4+42m61xj08fO7dtUYUKQ0118aRi3AQ1FbStd8e81FLKOIdm6EPvPntXNmNunHKP2ScK30M9puIgiPG1pDqLcw0bYEC2AYDJk5OuJW3IZ5MbP4y1vMSEEK7IEE+mqriSIFUiBnZKWLkIDavXwlJ5DFYVdalcWFRYjRgEsC3iQKnW+Tjnsnr916WkUhKqimrhKiJUq/WNcaFbXaFKzYtyrjkty7iMpxQzAISmcaYnY31onWtik1OpgkogzAxkXQjBh0nOqlxLvUyWhSWVZI3NKSmps9ZQKMLOmiF085JSKsbYvl8BXv7Geh5Hg2iCY1SgPwmv4zhCLQTsvVPfGONZgPNsfaPgFBwBARCLoMiFo40qYBQUiEARDDnfrAqbWpMhZhB1bqx5yud1t46I2WohmoGNhbX3v+zTl11aanhJ9L3Sp1pqKUapN+1TjkuZXm/NEtM3L6l8Ol97SFerQN5XdVOMaT6eRtMbuO74vtj11q9ucDyjJriwWJXbvr2IlgygBTHI6NRQZZKopZ7RzIPm5Silrp31thHjPsxPjuvatAqL8UooUotYCoTvm/TaHhtyvcFV09da2ZifT/W3u3TKzVXWARw1XQ2Kga87UcSPp7RtfNYU48t2/fpZbUJWFCLHqdC8z3HHvmndQJZs055TQuMM+WW5fL0XUDXGCicw1jhvXWOMZc6ifBEce+ew65x1KWUig4g+BOO8cR7IUK65VhaOKRnjVMVaC4RkrG2Cd9YYAwBKFJpgw8X6TsYaRLek1Ie26/smBEQspRhrnfPztCCYpvEu+ND2ZEzJyVrXdb11hGRrqbZkCV5MU8sZDQsyAukFJgFCRGDMxYgFKmAExABZb+27t7/68NPvvvv4X0/8CNb7diuKUx1RVBGU3KBNKPm2zV81xys+u8nKUd76dtPdvmmbf1hYqpTMh/1549VWk9pXLzrux4+P89I+vVz3gYgIG4HKdXx++AF4E2/ath325/z4tEsrly17sg0F52wV49ERiT3nE1ZEtH6zHnNe6st6uI+1ViRrfYVCmoFr114xpzFX4zxDbZhTPKpvViR/0b5c113OQqIhbC2bovplsJ+/9Z8m+uFjZQjg7bv1eD+Ylm0+p3XOSfOvP7vaLYe22f8Y+5/Bs1UhAudS3Y851Vy52tJgcpxsCNJbY5Y8slS9HPfKgAhkFIwiqVQCY4xVm1WUALzzzvoQOgUl64xx1vkIpR16k7IuS5myamq9TSmXUqxz1pnQBFDRixjvopM05NCXUgDRGuNEp3FC60LbLjGGtu2NKTkf9se722vXNMY7Y72zwRgkY4btbbfa+GbwIRAZVSHrqgjVoqWicWQsIhEZRSVRgYsuEBFUkQmUEIZ28+rmyx+e/1BYrWlLVWUNypslBRadxutT0Tqv3vArp/UYl+TymN02DTU3q7vfo/90TOfjboKlCz2DVQjqJ/f+Nh3KfJimI5SHl7WHYdNcrxzTchJ62T3GuXz/j398Trn71S80dCg1QMhRUa01gfPJ/nj8cNf/UlEq8hjnUzxaOwBYrdNmfV+KRM2YdgatCbcilQmSMhk8jTPmMpb8/z2f/9fXoRvPnMvsDoh2XJLtPPbd606mgX5c4M+G+b5Rv8DT8zzHqRP8puSrQKt1qZi3e4KDtYOZHdybtpb5A+jPNE9a0+RMkOyHgFdauZZy0SIgERAiGhEVEaTLREiVc61JuRgiRWQWa9FaI4DGeWNcQw4QjTGlFmtNrQVARPh8PtdSmra5eLhFIeXsva+1GmMubt5cq9RKaJhrKkvMiRAvnsPn52dD5Lx3wbtgvfPMen9/730DKsaQMVJLdK5BLSocYypxQSIyBow1NjgbpIIzHqiiJeOsUXPRrKiwNe7+7rObT1+c3ClYTNMz1nkNvj+nKb0Elj5FLxzIkFQbTC3WiGJaCo5znur49vFYqEXvnErucrmd50HoiH4JOr5e7xIl75nl+w+PN9C+/WozgT0jSVzi2kmRLMmIO6czOedGaRxh10pC+1AfAr26639RTsdYTsZTqjELONA4n9DfCKeubcd5xGXnTF9RkyxcxSALx2LDv8Tt/eL+DYPs99VgvL076fOqwPlF5RzXm/Dnfnl33Rtwyzntzqc7toK2Yf3+Zfe+lMmvBDra/cu7RU4aILevlb7qzelW/sEtT9X5CI91ub65NmoqX4hdqkjGNwIsIiJSS1FV5prTVJb5QkestTJrCOFyciCRtVYYzEVR6H20UUFrrcMwfPjue2beXG0rM+Gf5pMppctfBwAukWcRzanGGGOpcVkQ0Tm3LDGldHdz65x11jUheO/7vrHBb25u0WDN0RgAgMLF0iACJZeYRmssWWtDUFZlFoBqqgvBGEd6KQqDCiIKAm/X93dXv3ja/+11Of8SRuTpUFfnYf0Qoqvzqr1Nf/xpO+N6NfmA4zmx7VZ2ozXnWX7hRrjf/EvOq6b7bK7wzeHnvG+u22jynnhe2T3q5ssvmEi7Zme1IhbXEjYVfbi/X2ueU1nGXdWFwDeJrLZMc0tri3UZ60OIN31LHt1SsmgCBefXsWTS02uWlrA2rbV2mo6n3QIOsywGJEBdu/Auij48//bO9cO62e0/HWfZfPVtfn44TOur1d+44PLseYoR/vA0nc/lVZ3T/VdB4PvI70x+Gp9uzVdvN5t0enne7T/a3edi3pYwGP+/ev3uePZpOv1x02m4rVzgIrYgRDQEYggv9dCSI6jmPKc4SymqYIwxSMaR915VEC9VVDKq3jthdDZcQlFVWI3pN9vT8VT4ArXBKgKGSi5VxORsrQEE60JWzjWdp7lUOZzGzWYw1qSU7QXP4bySEaXQNFc3900byFDwrTUG/iRkLZKjtQ0jprjUP2F10XrjwIAlAABDAMRVGLMwIFmywQB41zSGch2fTz/p6QgfHlZf/Wp+u7Ky7ZPufjx97Ia3nd4VqbspPskHS+vuszTDFvZ/vd7mqex1amuYPs4PT+cpTwgertbr27fkS5/r1XA/z0/Nq+1S61hr61oLJjhfMiLSZGPJZ+bqbCup7EyCEiOz/Yza57Ss8mnWiTZLKd3gJVA/uKsjP1UbQ7Hr338yN+vlLiDmqc6Ea2y6pS4NdK+LfDbG620HPfy3/WFTZMl767o/yJW5uTKm/nyCp537Xzgq5byj8vquaZDON2/PixwefxqTH7t95OeozZjaw2H++UoejvENm79q1/o/fT+9nELf3F3/xWTsHC8I3wvlWYnQWcsiwmyduywEDBnrSbiKMosg0p+EPkBEhKg+WDKXg8M560WxCMdlIUPOuVorXoDGKPSnepEqYK1yEbehdcuSUoxzLNM43d1dI5kK3HSt995YBwrWWh8CXnpgwMAJLkqJP+WsFxcsIqaYjNXQeYtWFXNhi9Q0DaEVATIIlzClosUKqmT8qutWoXsSWqa4Lsy6bJdl9bjnl+fvfTjerub4yeewPXg+1N8HAJjftO273nx63Hdu/Juu/5f99PLytH513Q5r3G4nzlN5gJxbu6ESAVF9M8/7gYKzWws1aal85vPh1e3dM6xPh/1GbPVudJgCeRX7/ubfzdPvK0+1rKbDoyHHatoQUplB88K7Hzd3n+IAc5xe4sbaLsJ1yrHtjG2uJnnrTVqv/77p6pSOVInyvFnvxYhoD74o/3HMj3xb6lfH43/7jVucyaZNI6fnpY2W/iuTgeufwuFdvvMl1RA6R5tX+HnfHc7P+yPaxd2v2qYzZ461guglrcrCl4qFEJEKIZFqFS5cC5cCIqJScnY+GLbWWmvdxdpbazHWXThCTdspJU5pHKd5WQAxpVwKNr1FEGdQQS+xRlCozDXnxvpS6zQtp3EstRp7Ae9RaBrjfK2lafr7+1dD3xBKjvMMJXiLbeu7NRIiXugalUCneb65X4OzKWeMFX3TGptLMQpo/lWBAyCVFUVUiUxwjvLMih+Vwm9e19b98ucfD0BPb+4SlTnOy6H/+Or9d8NU5Dx2dujl/foQT/xtCffzrh2auRt/+UV/t+2p/3wC+0d9eHn+0LibxjYANYAyQ13i9v6zrruZDh9HnAwtiufBfQ6Qb/pXTuQZ5hZWXAqY2Sb7qqFTkYWgs2VQn+fFtSBelxiXEo7it3F7c44/A5d2cxWLmysB6Ark2X781eTyxj8yZ52n3tDwZ60rw1jfJlgcnhx+LmsZ9UNU9sN3dTiwb+r+nNLpcWI/PvTZ1budPhKcXnW2e337LgCcdz9K3YbheOP69Bwxaq3MpRQttQrLxeHHzIhgCMF5Y22tqcapxFlqISBCQ2iMddY6QyQsxkopxbqGEBXBOe9CU8kUhVzKvCzBhcIMVdFm65EvAgu5APIBVLiyGldZc6nTOF9IPVy5a3rn/uTYDsEjKqiwcOO9lJIl17Q0pTarLRiHSorgQufboVThfBJWa0LrHLPEuFhXyBhhY1ARWUWQA/qWjFn326Zdb68hVc/rvMn66CR+9oXvbuDn/3HTqLj1+s3X1aSPD390RO+G8xs4VHVqh+k7/aLNb1fw5Ziud9+nLf399eqn9PPr7s9o1ZV00jxjXdIyoSyu7Uw7YGzMshyOh8bibvcgQ5sdgQE7ldfp+ORhRKSIHqi/2nxBTg2CB61ZalWL7vXVOx19PU1letidX05LatDmpln6DSz1dsrc8pJnGGVw6xuxv6hlhH11/t+59K6XSstx4nF1HYNMp49k6dGWT/3w9yf3T3/3u+m0Y9upt9ivquIJ+enuZr7ZTM1qx+Yntzqt7yvPy3o+9fFpOh3PU0opxrjE5SI1JiJEFFEiEtFyUUUiEpGIlFIuKjoptaSsUrlk+leF5KXC7HwIoWub3rmmVs255JSYeZzO85zSUkstKaWUapU/lU+mmEr908v9whkia10bwJCoXt5PMc1IULmWUlwISraWXONZSlJRERHmYXu1urpZlmU6nDRXF/zl5Y4iJSbOKS2nZTrE+VzLktIoOdUcg2+22zfr9frPvvzSSx6x6pvP5x9/0iWqXWsorz4PaD+2Ld6/e4+NvTFxbZoupq7EP0728PunnKH+4uvarPe7H39YnnvcrKgxOWkeGWpz+6YYocYy1JROSeP5eGgpHA95TOl5Gk9SE9X5cIzf/+EVlx6CZT2ILr75RYc+ZHKM6rvQrpYYIea8o7E5HY+pHe7Fy358KdXVtjlQrWiK+G94HqA7uuZ8Tm/cVsN5cuf/gWXjhh/zvFj848s31EIDJ5jDUDTosovLSSZ89x5db/zKdBWmwIzHKFVGWl/76zfPizaSw3LCjTl1rkpAhFwyKqPqFBdjHJItOSOywUpkEImM4zSVUkDAGtc0jQrnVMhYB40NDZEhQBU11pEtJMaRZZEQArNczMsOQIoyg/PWeKULq5nUGysCOV1q1GKJHJF34dJJBQACMMZ0XWfQ5Lg0zqQYnTFN2xabqzCX5HxH1omKKAI555o85XZz3a1WopBzapuWDKJFYzxwAWVVUgHmpEkZTcqsDL0Lrd887x73+QUbcvWwprBLWE/7Of5Q3Mr1n3ehfv84vuvD1a0fptPDoP/w5iYl82M/bd+8S+fxzttTwVkWjUKTJXU9GC/txCmNhz1/mJZzS2Ho2raFLOhwOO1nWKNz9qXB4ZzfHotNukOYl/HZuq41W1cQh6Z6DP6G4+JgwIy7p597TZ9/9svp8OOis/pgTVgYDN58WHvF7NK8FACt4MjY5dS92u3NuRo/SEY77UrRTzcHGP9hrNvu+r/7q8Nfbx7nc1tKUr8OU55nb66RmvOy7FcthLvj/O3tnd+dr+9766074e0AFqmkODtrC5lxHPt+hYjMhchaS0TAXC6VQmONt4GIcikq2jXeOm+dd9bHzN55oksymkDAOdd1HTMvy+KcI+ouQEWuFYu0bcuieZoBSFRLKSklZnHWNk3jvb/0eFQVVNu27fve0QVZjEikqojQ92sVRrAGnbEO0JBB69w4zaubm257xVWsd47IemcMsBRCAERVkFrQGmArmiuSd9bPUMaxlHqfujMybLtN3t+vNhnWRxsmWTdTPT2+ZD7Hzvzt1P8f/+3w16+fuT89ih1r97RMP1Zb1ttX6+0dge/X8TyKrbpG5dO7uzfhSG9Xm593J/XhlzdfqYnP409v+jfnSdq2Sq1t1y5av/n48vX5bOso41ywLF1nI8R1M7BM52NFHVvrRMrzS7S2NY6WUx50XXUXeHw7+H/+8IO/fl0BpUaMTc4w1mzRyEu6WxMuhl/GRefq+1il4M3KH+JyMJhPI5v1oNNjXUPOgGOpZSwl1eqaapf9yxl3UsvEzdWf/Y0p+cdxOQu9zZPNxVmTay2gzph5PAMBc+U6G+sQKKUopUhl9KSqKuq8d843TYOqaZmxRakCqoaQyDpLKgwpdl1HRCqiInGJtVZjyBoHmY23wgBKu/2+7/vj8ZhzRgDrbD/0zjsEvfzeWdeERkTJGWOtqIIogHBNiF64KEZbIxlCewnA1dC2m/tXYJxBMM60bQsGHELNypycoSVlzjmrcludb9U6a0ww7vH8A/KP7yaMBstw827wm62e/Hak4fDwMpfsTL/sXnptl9df/sM3v/+L4fwOTl/n5u/uV4divnPu681noXVF0rZbudX9x+OnQ/zmOvzi4fB7NhOPsC7tZ+3Nm+1n3z7983sIq+eXIfTNzfrp8NOxmNLo4CHVYl+tv4gH3o8/31z/x6mWYhauxRNMKd5Y/O//Q/u3/9jUWm/vs6TvCprrJv/v3mpj8D+0V//nUy40zM+nVJfC0Etos8s7OcpMlfqhfXkZ2609LZNv1+VG6N+/3u/1+eOHZd/dvOoP8bx7ef7447ld+b5ZktpVe3XTDLvx4WH5hner29v+qzb8v0Y+St7EachcUmThT08PWWRtQ6nFkjFkmsLBe2O9lGItCfNc5qZpgm0IiSsbFK25KLjQak3qnLGmspIiIilo33bT6YwKXArXWrNWUxgFA4KAZEIkY0yMcRmnxtt21XSrjghrKYToXGMISs7MLErG+q4JUFNw4AwaQ+g6RFPzQqgImIsw69XtZ9Z3xhhQIdA/kRiVXfCWgWsWEeaCysDEYkHQ+SDBrK47nTY7/zLfvrm9ep2W88NpWG3eJT5Ud6Rsrq5bUj8lrdY92/v/ezp8yXyVd1doP/rtwzxv06kKJkkf9h+b/vWuPufDwXtTfe2te5ont+Wbtfvmwz8lPiWkU1XXrT9++AeymqkxK7O9v4IfX+wpHW+a29BFxJ1BOC/PDbl5LHa4q/m4huX/9N+9IXOYD8vzU+ks/NdH0xwl1viV5a9N/48LKrn7TSelg5EsR3HtH//lpwZPr9453/oi/s22f1keuOnOG4PjCRc/t2Q4zsdlNVyPc9Kkq2EF4ZaNOZS48sM3vzvhff2v4+8em1fflhnM+Bo8Vyp5AdHX2+3ff/u7j6Kv+uveqJDM8+S8RURnXU2RawmhNdaqiNRs0CmAMYaggBABglSLLsPFWgs5F2Pt5cvugl7IOQMis6LjJjSSqLJcqh3MYp0ZhmCMufg4vHWkwDXnEhElTqNDXrUWoCKLgkHrrHGXNjFLNcC1sHVNu94oCAAQkTVUS0Fr7KUaBZBSivN5Or545xChdQ2gQ85z3KNt++bPy68qWSrj8mmE3rZj4lPJm840cNOo0vXnljXXWa4+e+Jl+hj/N4tWsZ3rXXd4gH3vNlL1sYpJn5yd/Or2JT13V28oHXqx7fbNHl5w0/qTebaKjQye7tr7B01teW71bnbNw5sTRU6Ce2PcefmD6lKyKTzBKPZ46Myb/88HHD/8Y78/pI/L80PqF3ie+Zv0+X7m+DL9iup9Wobhxrmw6s5NA44tgW+bN8skKnZY36PSX7x7/dWrtu82tze/tld3i9SUS0P2uuk33bp1wWK7NsObbfMKsZR8PpzMU3Pf3s9d+vtPD+MU4/lZZFEGkVpVCPDff/krh+bb5+eRizHEopXFWK+KxpgQuqZtuOZlGpWLcuZaFJX5YrMuKtkYRWCDVEoWLrlkMq4WzqnUyojIXFGxLEWVS02glVP0qF0IZMlaa9GgqNTKJZa0VOZa8jKdm+CgxvHwDMBznFOccpoQwTqLaEAAuBhDzbAGxEtVzfrgXOOMa7231iJcvPEY2i40rdQ8nw8l59N5N6Ynb5SNffv+rxgmKDswaIbVvj7tnn7Hca82gqnHuIf+1jnjQU/zucO7/ZvffL8NP3M4c3Ris5kixcQQuuBcNrr13WZMz6fjKbT3vOmnmdMkbt0373+5vt5wOqXlxb26xjL+6r5bQ9/IEr7cWhlzotw014W1QoYiQHxzhdP+hUs9UP2/ftf/xYCHOFUz/F3uPR4eTKvN29Xpu3GhV8H/cNiTfZ9PP6/g5Xa4rxrffd6Nt962m+tBqHU1J+f748dvf/nuv/uz23/3w3/5fxzfDjWe79oeEBemZANto+9f5mcBLz89Hti3mYPK+s27az8tdTxiZiElahUElFTl37778v/9u3/5zx+++49f/2YLUkqxZMla44gAnPeGgFzw3tZarG8uRuOaEyC4pldlS5BFQAqiGmsUQEVYBC54IwEilQoCUrlY632w/SoET+xAwRJRSslaIuSu70GNiKiCtcZomY+PVAZjTLZkvK+1WDIK5kIhJjI1p1ymELz3vlsNxpCUVHLisoDkuMzzeGr6YX3zajzsOEdmRhJE52z7fH448JkCtHQL5kqNTIdvlNNVs4pj3vFLBnd9flkPKyqF281h/HY7fDG+vpnnF7eqg9p9kZ9f9ivQnkmH26HZKJnmSh4f//Dh25frz//chmjx5nAer7a3WmrRNi3nW4sbC8+5y/5qft7zzdoqLWRB8kyEWVMwW9vIcZ6eJxGp6y/erd78Kn/6u5+0VN+UYpVsMz67t1/8djwXd7dPs2I+7T69fvtl2v++Ymmu/JRP6+7KeBjad2P+aVricYFQXD08vf7rv3kX/+Yfpz/upWua1bpLU20+ndAN7g/fPdbst9fN2zev6LMvMtVtt2mbYG/u7VzOLw973t0NnxkxSmQKVpB/+8UXf/fbP/zzjx//+t0XPRIgoTVcqvVWVZqm0aolJROMGuBSrbFIWPISOAMZiw6keGsMUfANEbKqqAyDTbFmNTkXLmqTqcScpN/4N+/fzMfTbj6c90t7O5RSxlG8NcsS1+tmu922bcOSS5q6Zogp9n1vrVXRkhZjjPWWCZmLc2BQjKHt9io0jZRclywllzxxjZdhA4KO++e2bYgMo+Ncrq6u/tOf/S9P8+7Vy/fON9v737wcDpFwWiZnB65STzys33H96coaOcu4n4Y2LMfndff6+4/fwf1Xv3ht/+q+ZrH/l//8Y2CqyzSfz7jUA/5+df31+y9+2bfdzz/9sHv45u37X+Q5DiY8fvxQWa21Fep+evowT+v1W0+QQnuvjUWZSVbd2mWupQiUhY9xe+/OU+YZEzUzl98+7X+esUPTqNmnthq4HWW6/gufFMvyi1+8n09EdcR+5TdD9XNn25v2/vH803H3sel7g+cObarNHjDnMb6609/+t6/az5Lsv6yPj0K26Z4fTscpX61XtQZ7fQ2F8bQ7HV8eH+Nms/Gla0roh25XJgLjVFcaUq41xn/z/vN/+Pjph8Nj0/rgNghUoS4l9bYtCFAuYhQqJpuMDCSIJUWaDmFFzjXOWT5nzuMyz8JQhUspt9dD+nSqFRKzVJ3GOAzufDy17c3m1etPDz9t2g3My/F4bJsWQpiXxdfSdx1a03eNSqxVxJrCHJdZago1gzCiJ9ta50utXPN60yv1CHDaPXPJBjXlWPLIOfngQhuMs6f9SzztQ98jmjSeR1m665tXm1d36/saz+ex2djtx/G5TLF82hGUGmh3yjX4Bk3XXB+PH3/8+Pjl6y/JNF+8+8vj0/dfmt3r8mb58PLf/zA+/3b/P/7HL37Xm1fb9Rn8Mh4//vCHtglvX33xePp0Gg8qCtPy/OFxdftZkecQIneb/natoTsddzfbN4f9ozWqxvnEbmW7vvF+8BRvvT+/tKXfbD8tlY/fprZhO5urM6gb6ja+LCkmu17vn769ba8e69gFfH46ZYSPsNxsb8QfZvs7F7q6vBh4K34daM6OitKHn/++3/7CD5vn+ELKP+Y669AS2Ylef/bG2euayjx9X6axLrS52daxzIe85MwS3t7+GaN88/TxfDq97zZclrFEUv9+6Pecf94/3G17lcLd5TIGukDMDVXUhYtNcoEUC+VaU6jVBPbBiFY1VSgXvvgOtdt2p+c554WBbbAosFp3X3795avP78LVQK112P3i67ff/fADICNwF1zOiSt7HwChVjaGzscdcJ7K3PjQtl3TpspUuK6vbkMYirB3JpZ6Pp+hFmPIB++DTYX2jz8dnx7brmuGDXNeDk9VrkHdfHi4uVkrCrJIrRzPPO9tqVc1OtPW28+bTf90evh+H5e0vP3i32KmVb1a8v7nDz/86s//HZO5sqns9z/+4Xcz3cAfTkvSO7NOd1++7B5vbj6f8u6w/7S5va4zr1fvcx2j6NqsduZhefy4ff+mWa/Ppx9aaw7n+c39L6anh0WyRWqt2UxL8rLrh3vq+03b//TybajzPn56Pvetb6oTi95i7UyZC3zxmz8fl3o6fFj1Qa9C4AS4tB21dh25jo8Prl+Z1efeSQknIxPxeq7Gu2snSwRxSGf7yg/se+Xm8+E4dgu3cgS/jUoIJMsEWCl0KrWURLWcx5cchocXt21vvtpef8vLPz3+tO7a202HI7UNvP/y7jDux/rcU1+D1qqus4asLUmZvB+qFHNxTSCiFZaiqbBPCN4FP8e83rjxANY2p7EKIQPHwq7Bt1+udh9Hf+WHr4fjy+7NL//S9N13//jjenUitLbFtvPWUmXsVm3TuHmaahqFpw5NKTUtEcVwmXJJYs1hfCKo3fVbF/qcc0rFOhe61iB4B9ZQo8ESf/zj4Xx6SSUZawAhp/j46afp8XuTXxWQeN5BzmU6xulgQBIu+yJwNHJ8bq/6X7wJL6ecazk+n2/v7reQn16++fGHb/Tqatgf9t3Nwx8+xN+8k3ePEet+nm/z9fb9L18Yp8efqYUxnmBOm/51TInITzUbKdvQns7nbtsZn3ZPH8/xzRev+4TSbTrryGpOPKVEtB7i89MH3N617f0EkY/y5Vq2zj7OwXLxSwthuW1fv11f/3T8fRQIdjsvu6ZfabYOJzDuBW1On7piz4d4MxhIOkJRnAvo7fZ1zWcDTevbHRzOpw9r+xXVBu1DM9zhfDdNbpqOadmt6TVTsj388N13nvyrq6H17cth/vHlh2Nz+OXnv7zt/LgZFs6u871ZcZyuh2512x0+fBi6diw5MR9nub5ab0LEPeZWhBBBiuW4nI3mYRUmPfaCxg1hDUlrVXj/y1eYyvcPFhyursNP3588uXd/ftPf2ve/+eLn//Y4GGJeVre3H8qPMLqhbTbrq6LLtx8+9N3qc9JlOspyQqzn6WVDnQEBJNGiCGmp+XwmkPP+VMRcv36HJvSr1gBJicJxHmcLteRlWG2//MWff/vHf17OJyA3zrPM6ePPn/i8v9m4at1YypxO6TRxzEhQsD6P08vL+OpmuM5vm9fjTQv/cvwuDPx4/u26/YvP/+2/Pzy+oOGHjBJu7bt/Y/729+bN6mHVvOweFrRfvHq3GXC/hXSe69MK3XIuv8tiCj4vUw3czsvCbk6nkiXCQtfX28P+GVJOKdkKlpTXthOIx5dcUB7mdHf73pf5i7uVK+p9u7h61dkeMeaKQD/vnx5OpzDc2PVmfHjBdLi9/XLUNo4vvm2GV686Mjq1u+W0TIXVsU2DCS8P3xungb2J82D2KTQSbarH9uYLp71teJweg8e1v592S9v2dT6+WfUpN2F195f3v/rnf/pD3Mehd86dG8wNVOr1UM4/P51eb1fY+OpYB5+NFNAIkTVDCdi0m03uX78xnJzuo6XAQBVnV9kdalVAimHp2uEPnz69/4vu9avBDybdwLvXr3c/LdTRZ7/5/N2vvhx/OkostLmmJgy39utf322ub2IqzU0jRQ/Ph2GNqufnSTntbTXTdHIeULkJoeksY/Su+346bLy/EZaSx91Ld3WHYPM8LvPuePqJhCjzOH7arDa3b//s7tW7P/72H6f5yJL34/zw8hKAH+Y5yM94XqChrCjOHHfjwufz43mXcni16jbNLqemDCd+fpXWgewPf/h/Xg2/Np995TbtePrxhzpthu1n8MdHzofmhrLTnH7++RscbJnhWtZlOa3DWwUrMULA/fNRzrwv4+ZqfXh6mXReZlhvx93DQhKf9gfrCjkLzdXQupu43wOcbWvzebdpvtQ48zLGNDsxZEIIJHJVyzw+ntvNKzH4+PyHJQLPU2ceMqynNqytv+7ezmm/un69e8ljOmzXN2M+YMiYWEs1q+1LfPYu3mzejwegro+00liQx6tVzwF4P+u6duu7uCxtd8244pBPZX7//u4RXrab6+B8guPtpn/SZb0OK1ss6eP8Mkq8vlnPKXn1cx4D+cTMdj2OO48obRO+fH18fPRmVeQ8a7Q5JNPK4OfpbERvN+3dJrx+89lnX+ez4VVr//Dfjr/4D7+27WAXM+Px63/zRs5ISu82981nx7d//vUPP78cp9P29frueF6tXYZ54YjMN9IRsCJ299dOVRokaqKYxzT+8t1Xw3qtJqQlijnm/Di9PEqaIy13N++aTR95qiwvH7+FsF5f3+yP58RiVo3dtpDsAy/BmO72Oi48yUgb4jDUmGvdr6hJm24H4rn/YX88UeyyXbdtf33z+PBDaO1vXv9V6ra1lvgyf/8XXxZMZYnh/VevbPNUxjJ2Vtq+1eYXr3/8dvbO9R0+PT/bld3vp2Fl7/rrx/NPmNztmxskIhDv8P7rX9jQrCyxwAH85+s3r8bdI+Y5GCVwtu2OaUeVDJokfJjG4fatlKeQyvPpZ9OD8+k6XH88Lk/7k++77fVnvBx/fPiU8rJ9/8r53rjGKuUppWAJ6Ph8iJKi8aGonnZGbXv9eVA7889N67SaZc6WMqzXAHHVm9mE7XYLWj+On3y4Xr/2mtlQi5uOWAZpWmf7Vz1Bv0vHed5dr68KyZRPRUs6JdiYprvrrtbIswjFYX3M59IoxSocm9d37fp9LAdgfvXZfU7nbgPDdr2UNJi8vX33H/8PrnrxS2rCIL+82fj1yz8/3ljs/EY/34Tb9S314zf/FY3evN5ghtqV1S3Gn0pC9det9ldTFylHhLpq785JxXfWBGvq4/ngzDok93z4VE/Pm35A07Td0A/bD094e/eWE788f3Khf//+/f/wP/2XVO1mGOxW+A6gXX367uX044/fff/Tr//3/667Ds68tm7m2UwdDhKr2Xq/tL59PM6dv8ljgG1Xzenn3//nadHu1nPe72xtkpuSAWsPg2nKjTWGccw9Yb5qNi8C+fFxPDyfP//Vnz3qMfg+2XYq2MMm2M0o8VQjR12nnS3ojIPE07z/xrmwm2uJz+st3bYmzbsMR+JQ1JUMxdHpPHXGlnHiyGy8bdyPz8/jVN5eDWk+gAoCp/FoWt09fnOOUzXpp+PLvJT5ubTB5Uj5tHSvm1Cvynj2mxVgnuedDVGonXJZllOgRIHKtGxMY1rkulx11/vy80KnCY3VcppeRszW2M2qdUwxmqYXa8pKbOvbNnQ8TblgthLzaZKXtuV5fkbTiOuGYSVFfv/9t1e3Qy5Ljmc/PrfF9V/eAy79ipfySfyrxq/OI4iLVlXTIhbZ85EnWLeZ56f6ONaxGcvm5r4/roPA/bt3iM1T+t4H7bb9cq6xazVUm54xECPMy95ws2q32dqi9P3Lt932i43RE6e7+7si8u3Dh9v1JtX00+Enbc2v3/41A/68+2Ca9f3nr/7p+z/GJb3/9dfWJ8M//LD/9PZvvta7tg23xtmlHMKre5+oGPXBBIa7q1cvdnrinGO5fr1Zp/35XNvV3YmmKe7bm26gUM+RvSGgl/Pp/fW7p/PO2hmY8jllPt69/pq6JW+UVv6LX/+iWj/XnEnvXl1D19fTy+vXVz98OD98OtmrN5+d9j/N0dR5zvmhvf5CGV8eP6o65oXmpTHL12H73nWp659S1Uov2Z1NPZ6mL+n6OgzUFly17Qzx/NT3/aJkjcOyA1qMDVyhMKdTNXfYdJ5N8q2Y4kwJaGmOx1Oeh8rt0KxF1cqY8Jqoba9OcWkWje24m/zgb57SkbnWJBw0cvTNyhBr4aLVgU1c2qFVqLGKs34zXGczx3F3WB4dtUO/FpdO6ZRiZSOvvrhXsIfTi4Jvzi8bv851t71t+tA951OEKhLmaeeclvNhLOU0TtQ1Uqem3xyX5+Kn4Gh++bHvrll5TNO974abNx+fHsZ5vOlsILMgfTp/ul0zVF7AGOBtu+LK+/nRJvOSpRQkOD2fP5Qs183taT4e0xSnY0LYHV++G3761Re/fpjPZ1i6q+5zfF/AiTnguNPW/fpvfpnsZsgx1uh5YKHg2waLB+59wGxPNS3y2K1eU9u9bcqrHn/rYG/z2luNvYbehdK216f9zPHFA43jE/PimpVB39wbuv3y4eXc3/uvv/7L+OMx325fv/66LHEsOVO9H9a8XPe++Zu/fK2FLUJ1q64sR9Oszk/7gqPxfgD76V9+Xtn0nz57HZb8qytztzD8dA6B/Or6+/Xd/y19WCZeOFtjAEpFrXXpB5trYg9Vx7VfEhKlhssMPVoMhnJ337HB8bhvJN+11+T7cx571/dZC2OEUjAEpCK8Cl4a4Hl08XjU4txasN0Gqvv97oR2e79eXR3mD3NkZ9uYCTQwutP+Y7u6XiZ0zY11sDJ7NFhtY8mYziS7ejg+GIguGGTCUtP8NARrW78bH86ndBM617aLqae8qyXbQBhk014f5rLqr5WnIMOw7o9zgsZJluPLH0vc2XZ1LrN8/O1VT1UQ/HD16vbw9HOROo3Mpk9cb1frid0hHrw8H8hEu837n6LDMu1eosmLLUAPWnfTp5OmIdz8w3f/mSsf+HyKe1OrNNZiGs8fG0tTorvbX3UhBDT7qR6XGY1KLkuZ2axWGW6b8OP+UzIV6osNd3Fxf3eU2GDLjbN992pLDT0ffkqZb4eAFCmHQ3omYyCZV1/+ZikPtTLC3vm40SsFN5b5sH+uMf36z/79x4d/ivvdzfYN55m6BljsMv48x+SCc9Rvr99kGA1N3er6eR/vtP7PEvhP2qyXZ2eX0L+f8arEW8v/2/XN3bJ867aRFyO25HKKZ1xt0VKMB3JiWh9iyBktUOs7S9laWwxQZ/t8W49j5GzU1gq21OpasCECo4aukVlRjAspUWdKtYp5Fs6Sh3DV3coY43bz9m61FhPH/FhyWV/delDOexDISzINuq71cYPuZVZbjFEATZlgtL2klErFTduTJ0Vm286SfROgwnkZHZxlfZWn2Zk1MSdjKGw2XG7am3OEkECWU1a22ovR+fBjY4ogiffT8UNm9n0/aYXCSzk1klF6xu5u2DiEfZoMqKblYHrEc62z2BsTht3p8XnJE8r+h/9s0V5fvXuMdZqmbz59c9KTYT/41cvTb99sPm+brw7nH5Eg5dS67nb9BZvnblh/evwDGAb0Hsw8x2fdo3JJPqa4lN3V9mtIS8U5zgXbeT5NAUxwxqNkYx9fkuWy3V7lcR9zGVM9LTO2jS1mmvKnZhTEDOe05L65JSlD08zjyehtWN19ePj5zXBvl3jKaVq0abdv33559fTxj9N5WnyoS60rc6R5MOnpZ9191f60vS5pORyeXgyuo/nlbE4b/wPOQxP284wA47Rcr6/a6qwtRFdyng4fj7DYVVfbFbn7jUhuTBeGVaXzvBxMZUASIhlCxVxZV+2VJJPLfILlBgCBDkuJlu3gOOZsbGjc1aoznsdcrLm569z5cK7a9o3PUkZe5vMpXG0wRRRZbz8zxUjF2rZS43H5MWsBIkOVNM1RwuAmKSLZEiwSKTh2SeDsbbAqMS4ZAZ29XTtOP2o+GGwWGYWdSJxjimka2laJFsx+tWFeas7YHbI2YMQ1Q/CraV5yDXOdU62937Zuk0uxPhZDisE6qjhPlDLX22pYht3h6f76db9+dVqOIzzedl9XlAJFjWn9eua0nHfn0/dEe3T3UJd1CDisd/mURK8V6zIdTOjbNzi/nJbdcviwBrm9/fU4/zTxKWe3sb2mWdsuQxTtgLwx5Wp99yyFVo0hhkovDw861eA3O5kJ1HtlX0ddTs9/RDmHzV1CvQ2rt92KTLZM3g5Li5zqiGYdtrcudOPLyZc6muF3V/3Gw7lAfDo9bFdtgD+ua15o/fGUrzfFIMUpc+DCq27t0AQSWrslzfNJXz6dx4nzskCDxvQdBi3oeN2YwI5iZjTkkbVE5cZAa40SnWxQ4HpKL8Y3WhgUX1laJPlui6AoTMaQg4VrLupM04Qsy4LVdeYOml1Oz0qyLKdReHD+qttahPPhqRu6GGvonAUrKW+aO6j5XD6iaYi7uCyZJ6VOOeJ0brgXPp/i5NZrArJs4yjr1WeVauUUT7XER2xaNO1t/0qtf0mxqK3gbDlwnI2Td3e/0Vr3+4/Ip6f93jcYbCC3ntWw7GpeUu1NU+bxQX3bon5V0//8zeYfUvjn/XF35KvNq6o1Yzydno1ZzVN6rN+tb3/p+5t0XnprsZaMp3W3PR0+NNZ2JYwOY9XVcF3Dppqu9dy6xamxQ8ehXZnP9vXJKZ3TvGmaPMP5uF/39n54ZWx+eP4W2ubu+o2UaMOAHDtneZmcZBduCliWiqCucSrdFA9XmxWkEYX3c7Q9mVntsMF0mql2fTuI596ErtzQuvvnKCtjV5vVynzhtD6viItZ52a0Nb9/bZumX3Q2uOpWN9d3rkTIaUZ/3tedPlVDm/tBpa6u77p+jTwFAV+1bTBDcWgEAXgypUKKtmusIYJITWcZBaQasX61DasGsnfrdvN2t3usMMTCRoEIqua5LFmWAXJK2fj+5vpt3MdU8zDc+fbK5EVExlqiHO1Se7v2ph3T0WCDYqCcCkUrCP5GFE0+GmMKEKUqeUy1NJvge1im+TnX1g5BrzLsj4uSN23QAhDclSq+HD+h3TKQKFjnU6rPh39Zr6473xElRCZZGt+ZUJkfKw9jOlrNFfRwfBQla/r3vNzE/PjHD+XVr3p//fT88TTuXt//plVg1hxLZ6/HadTm2faDt/b15vMxH1l84Wqg4/jsdGlch8JyGhUcrz3VGtBeX92KaC5lCAP4qlp2XGJ2uSRvupRgGIKzdqZYSlmWA8EWSlQpHJeAIijjvCNYO9fZvgGFVMv+5UOdwF2/mmoW29imaWOuogvA2VfvfWvCxjnTOTMlmZMmDRRx8/7dkOfD6VMAY2+vpp7Ee1UuthcEa0zFApZNAtXOhe3z7qnfbK/Wa2tArV9d3ZnaaIm2cQJAvDjriwMu4hTLuIupSuO02loSTQsRolZDVNXOYJ2aw8vhsDuqomsHZzK67G3DvnVZiUrxkPTkqm/8Brl62zrG0LSKfj4/i9HQDY17neBIXEmbWSdyS8Mh5rjYs7Cgmqvudim25kLAc46uYiBaDV0a5yRi5pd92heRzdqqE12ScHfgOeXYOzU2gHDXDuU4pfKwj8/zpGADKDcqdUnnyB3bxlVitoYiJcijKSbnk3q/s211txmuuU7OAKaY9x9D13X9dZa5tX5qN7lmp1MTvLG9qfX58FDK+WZ9S3RtyqmaSm0HiY3Frgs5hbvhlfqg5YgpnubDcb9f9auS4pLPBRmUbIexVoMBNESOJS6ILefZalWRGSVyceA7cEo+FV6vb8f9aXCrAHyOc2hXq3ZtI7VIDLxcbbf6nPJcNldvlPrq5q1vrF1qVCR5PPyURef5BCZE4zKFen5S02XT5hgjROrxfnMVpc4x63rlyuRbL4DgQtV5XB76ps+5TvHYGFtzlrBSidZYJZ7HUSU4Yxip71bW4VKWNOfKL960DrpU4nl6lji1XSi52LkHZ5IXBd8FR3LGoM67uuxTFoJOxqXqOVlpN69rlUC3ffc6okSY27AyNdSqjXvtIT8fHpblJbgrbzeNuwGyL9OxCc1N12St+ZzbG1NHez69lLZdavK+8gTJFFA9j4/WmRBIiL1tAGzRDESuMWYoBkKZSWtNCTiVBdg4kzQ7ZDWGagm2VElu644YqPga1shAVPoAlkHHJ2++IAu8HMrLDvsByeLxuBneas3xvB/nPZeDp3h//ZWK1/QsXaWbhnqfygtjxX6jdVlZ7wB3MTEvxzFNKbZtwFqKqJeZCz0ep2znbJclOu+6SZVsSwGO0zyfli9uXgHDedzPko3tDKyk7hNHY8vtm9eoYjmVPEfDUlRqNQQmjdEEg9iiawawYkzUOOepKnmyDXqZF82VwBYyFSuokAKhxPmQZsgCaKDtm4uxNoTGI8b5ofWftcP1PO2nNFUAzAvwQmBSXqrqTd+RmLSc27Dtmi0nKizWWEOF8yElAiiWWOqiHjkplnVVJ1StpcZ3FbNBo0ZVF64L2kuSw87LS5Wx89eJ9QzfVjPddH/dwCrFY6zJk769as75FLk6cr1fccxRqkB2LjjqOU41vXCsyKlEUcxo9XTcT3kehqZvW2pgLqxVrrwg+RQXQTZgQ8FCwuy0hibYvmmfzk8oTAbEEDE27Buji6uCHskqzgZVljPkl95w8K1bbVhgf3zgPM5pTnXycSPMHx9/X76Kc+P0LKRcpEbNFCSPMc/MfWpUrTbZmDnue5sXYAvmi1dv5s31h/NjrWmu4tkaUwFqygvXhJwdQcF8nPaV7er6qh98Ou+CuLCoePayLDGWPLftKnW9zHno+inHT08fbJkTVnW1X8Y519piFyN2FFoKIAa1IlLKUtCA98GZlkxnrPM9Gj8Kx5isQSGuqY5xoWJ7t2qDCZD356hGAlHrNosYgxTCNo0zl3PwwYCgmsSmFLUMPhcu1dYqHCsosLR207VrxSVRVolgBQmrkgoQzE4NxUY9Na1rrB1TPs+pD5tNv61xuVpdT/Mz4wjOEI1zTCUrt09VzOG0rENnnLeQxvOhb81tf79UKaWK5jqNOFYNVI0JrjU81fyC7RDQtGIgwhRj24FpWmexsU0ErCWtB5TynPeLd91oMxeVTCnnWCMZs16vB98LzerZBO/RFtb1+pXXpY6fEjNTKjiXaBx7rvHpdLauM9fofCypQE6bz14fStVstFTm6WU6gG/b4IN/BarTPMXKack9dRzjftlft285Ms1n7TCSikSLZYkjLbHrDGYJBchTMSZl9rSIMqkLfquVSz0cnnfgbyytUzkdj+ew9cZyF5RAKkfypdXeIZ53n86nsyVCFKoLh6F1G+AlFjY521W3BWPPKaKANUPOC5GCsfECFLcWALkmpyloZpBSTGtbQ+qsc0hEqMYoFMlnxtaA5ONL66774RpgsQBeES2KVudNT8EowIWhwZJxzhCtrFQAsTEI4IoFQ0BakBGCtZ7cmCZDvTFN1ZximWOmUlarTdu3ZLu+31AuUYQcs56MVzW15C4u+2nJN8OWal7OhzTHV7evOn9f3JDyPOeDN94pBdQ1LF0/HJhPkgJH58moCUStw03jGVCLs9A0AZ1xMmdTC0CqkIPzDhuQZDQNzk3LkTJ30mYoAI51LsDbppVM55ltkEoR0ORSTGjIbrKv2naZa5kWI8Y3zZSSctNttoYPg/oCJp7OAczN1dt5nqZ8GqcRhFdtF5WWZT4sT3paQkPA62DI21WK0YlsQzcM2zieUebKjsy66SQdnrhKxezKyjjbtzaN51zGzdU7nuB4emx9p76GdScc9/MjSerd3ZQlzVPD1YL1ABlykWTavlu4LNNkoO23b8DQbnomtb4dSBVFC3PFrC47xVpzhtp3XUP2vIwAjIRIRktEDB12/XoQkMNyPOYRERv1afdTWN+15KQuBi0geCirQKHtnOt9BULPhrOMxiVliRP3fmUQVIRVA5Aj41ShUJJcQRwGRZvKUqp26IwyWtN2a+Us0Fm6sXG0jZBLvimM26X2paZSxaFZGx38Ji7+/FyRnokO1dQCY7/yknKo8AZT8LSwmlS2ZFZqASBqW7OYRivaJXPmxboWsUFN1IRiTRWx1tt2Y3Buq+8DHObDNO1LdkLB5Vw4cjXzMmbliNgZlwBpLqBqB8fgfdujt8FRHVHJMTitVWU+L7JuTQDTm1ZjwZpKmmZdlpKUGUnmeAYb2szh/PPgsvTX1TAk4DRjcFahbXoRqjrCao0QChBg9W4101xgmsfnEK4tdGgFPZVyqDzaQLkWUbHVU8PztDTUmKbbL3GJ8yDVEqFzPliKmU/zUdxZ+gzhxrQNqyrIUmctCKgBjWGJUmo8GSGuxVm7au8NaZQQYdwtB9TQoQ+hM87ENBNjo2auYy7qrcVltvCCOc11KZ23oIHAuUbAsAIhKWFFh2YTukolp7ig9WpUABWsGuNcwCpYVUCDdURa4pRLQnXrthVmby2Q41Kyeuj70Kwgv2SpWrJib4qaVAqUUROB7bC/urorKVKVJe1P5SCemzaYYvwC62W6aUpDdJ3BTNBi9k27IzNjW49QUAuLKDp0nCoq2qYDFFfIkjjXNKYSR1ZSqYUzWauEwIAcENx5GpnYtw15ZYFRBGp0Z0DyLIDAJWVjOrIhINi+SSVrcLnqBAqSWKvU/HB+rL4R8Aq1tUZENVV6PsrP39hbpS2q28QCpc5azAQFvMmpVNBu+7oyjsuLI+zCaqmTAUvCEmOqtglNqsuUThnSzdXtfCq5MFWrUUk8I0SJwam0Nh4ONsfRomPvih2z7oiyazrjQq6JCytBxgglUwYVYoQKVVgZLIgOKvF0IgZyJrjutIwC7BqDYqxKgYpCAGDJMEKMxUK2MksptaZSsjXYNM4aUwSRwSpwVfVEfo1onRW0s1rNNedaDaFYw8Y4coBMSMYHICOSANRZR97VJT+/fPR9NMIC6qB3rrHUVl7zWAoz1sVIZbUSy1SRSByatuu06iwWxTTWWwLrvFlSTYwqa2UeqwVqBp0AT6XvhvtMNpZj5SgVDTNztNaxMVjzAC2CQkoGRKWWqFSNdS25phjFiqiOWUXYONvQyphYoBQjQQFKyWjUGE6p5uq71hptDKAlYMOFl7RELsVaVytWFWuqkHIFBQ+tMlVQKXZZaPmUhk1qXqVp0Thz6/phs1EQ71vr23nmuIykyTUBA4NkazAgmRwLk5dVZZOqgCER1xAYRAO1cT1szMt4OMd93warNQy9jTEbm9HWhSesMOB1Y9cW/HTalVxZSZ2zJbdVtBJ7Z42LDFVRBdH6WMY8TkC+OKSC5CwL7M7PV64dQlu8xFpJbXDWoUcwKVWp1VrPXLVorVxjccE5apyQ1QA8xymy9txuXHNdNcVlVwsDaQaoSAiBrANyQsYEw0pSa635PBfgUnPhVKyFqsWnoGFNAFaMcqUCWtEIOQSpAgIRZnOqWK+wbZXAWOMIHRI6Mzf2RzWnMtX9gVjef97fvNm6mZ4PdvQNuqZq5lJJjEEiARXOeTGKlryAFq3BWyk2xthiz4gRTCrq0RCqckFWBLKhgYIs0HTNwMZGZTQilbN4DJVRBeZSJKXMWlNFFWs1cS2cAjUX6AxzdaiWTBGYUi2h1Zt3IMoTLg8vkEnESN833cqy0SK7p+PHh0+2UdeYKpxtLlgM2UKaMbV2aNvraLMpJctYUK9vt0udFlhI7GCaRajkcax7W0LoVtZaSHAq+VSqNry1buPMWko5L5/iUosR4wIxAwOCIecQBZQ731kNKLLAyQYM6AkgB6NIrHXk2BrTSIdkAI0hQ2pMGwxZlxXJQGNUakk1V45LaRMGn6ohQWbNCoLULss4n5PUNEsmYwOqCDDXTNaSt0BcK2tRMlxjyXNCXYd+3fQVSQzWIjWnwidjGzCEEAgNCFeJAOxAyYJCXUqRiIBLqWeoUcWpOEYpSmKGU65VzMrBmlydZUm6RI1wXnotCqpknTNkCZWErXNVJKmIqFPpfcd25RERUdzF4VirNYDqCUAhX3zugGKsN523oZa5pCymqkEGpCLGcMXKooVVqqBWMIRSHWJEjDkyJwB1CIAogsJSjLOv3iFyTpOcJusI+6ANpTJzpN3z7ruffprHpVm7vhs2fkVKTlphE2u8alZfXX/N0j6cPnmHNLRk4VSmWCPYackZads1YaljVlYR5Wyt0wo1luSg8dZSCK4JNZ7G0yHO1bbWG+etQ2+qAHOtmAC58Y3XPk07LVbRONcMbe9R99OplKV1WIwwR2ViI2gQDXnvG/LBaMk5GWJCYSyqDKQV1ICgFOIKRk1HvnO11GWelzN737YukK2ElbUwRxIPIFq4VFTINVYuLgRrrLUtgSoIiGO2VU3ViuorugpGIBOgASGCrFVBnXGIomWuJZMgMElF9NYCgjAbq6vuBPX3qeWJNSkXCxKzMYLMDAwiDgXROeNCKGmZ0szIK+uzWKQODJc6Vmsa5x1CVcmsFckSYBWpCY0zEIiw5lJKqTUrIZArVanEGuemM963rIJQQJXAGDUKwoJVubKQtcX5hTAzZ2Vw1vYdqyBRljJZVGPXKbnyQuwWHallyJKUQUpYxKFxZhBHlUVrTf6MhL3rm1WT03SeXnKtwTlL5rSMAtI2WwKPVaxtwTd2HkcM0FIfbAhkmJdSSln2cZlzRUzWtIPzDRqEWDXOCCnLPOmL8WqwZIXEShqNcd64TmGWAoyZBAjAIKMh8p4aZ4MzXmvKnE8LCzmstYqSs8ZY6wOhEcMZWdFWURQgcmgdiboKCEqWUEHJsEKuDMICDFwLV0VApaqCIg5USiS9+FU1pwjIjKiqAOCsM8zMGbQIkiJWEUJtfGvJAiMREQARkiM2TTU11nxkADEN2RCs4kVJXjXXAuCoWuO4Sq3zOS5JszUGCheowMisqVYgCohIVGNGMOARQIzFKkJKzjbKS+ZcgNGiJauGKpeSZ6wyhNYCEiAAkLWOnBatUlQFDSARoiZRhZpKmnJsm1ZZRaSKCpBW1FLBO9N5nqtpaHM9BO8XESEYlwmjhpUN1LhM++mk+cfN8Nb095nTuBzmJQZyjaESaUkKmHxTyDjD8P+r6WyXJVd2GwuQTKlqd59r+4Y9H+//cjNhj31Pn+69S0oSmB/VDj2AQlImEwmmsPI8N1g//++f3//5+Pa348jCvu/731/X5L4f9TzPj6CxhQOOYCTJQK08sD8zj8qcwMCqeenH2sejm0yYnMw8EQltD1ALE7e6+/6arbCNlkaziizY3jNtDL25KR8gMjJrusOIwUAA7JG2tug5jhS4GDfnht3XY3yPKGGtcd66egT3gDPD8Jvy7tk5AYQDDpnMddTxnGFrh26Mo1bgQRhMjCLCsTbXkHs2JM4wE3YC3vr1+fPuC8lcYW/1r97svhGViN5794yZGTENwlyIguV+kd2aHbaiIk0MzYojM4O7ZTmwbPV239O9MzGtoZBU6E6/Zm9N7U1RM9o7kfeMX/vO+EHta9fMH8DfnsdP6xPBSI1G8sxJCvHXr1+f+9/XbcNfP3/MrbX81dfL247x9fnrP4gzj287fc+rPh4fi+Wul6C729fzWd/OPz4e31EfbywyREE8KuLjdB44w71wRa/nqsll4uv6+ny9VkTlCkawCkeP30RIzVz+gvy6XqLjyCCKaQdJwde+hbj37NBOFGOMFXGeJzNBwNQtE42X0AvvtF5GZtIJC7juu3VxWOsoMhjzRuxqtiRNZN4MDqnTTTDtsBqMTiNgTwBCMloUWVwrw4OWfTMQYUvdGoEcjaW+tvq6X699X8zUspdV2tuNPt4hVPsaxGQdjDCo4Pkc5sxLr78gbwlSGIhQwJi1Io2re6beQ20c4xBo393quUHhqI7Yvvfssa6+IRRigQHeSWbI+vX1+Zr7+8vn55tHtLIKxh5osyAPreMa0Nev/X80U5qVOZqxGv09js/N+6+blWcCr+35qu//8lHr0fDrfr+U1R276syj3lUgN+xbExXx/GYf6K+E+nPfr688Ks+lSO311Z8XdSBKrBB8OyPAYhHe+zWGQxXHEIaRWowYu3X5MmtoS5llxCXtmSAfHx/e/XW/ru7NFCPCb+avx9175mYiz1LgvvfeOJyPUmKnBoamMQ0b0CA3CJJ5Bn/DKaYncsNXBcwmk1kiDYFhpjyiWeGZuXffO6Kiavf96/Vz8nDPpRmYvdu6aM19bwFBWxTJyMo0PSGuPHA8Rn3d1zt8c4/CKDJuOSMzqhLqeyAPIfeQxQxxvBbUhcMcB9t+Z6IHmZHnehxZ6Z6OBSkdET3Yqi/tGNme4xhwv3pgMnsMc3za431HZgyPVUEMhuwnYqnudg/hxRsGfLt4XcAjz8eq3XIiou2bc7ItQUclMQkHVXHsMdc3al7+9dU79w54fXxUPY9nTM89vnun5yHn8+nAcZ5B7xv0G2jBPa/WK4VgRXt2c6UrGu62BhVrJ3X34U4CSTGGyaxHZRi0AKpn5u53rm+jMhA5GFnXXKd7WaaTHk3YhpBURsSKDBujTSIogsD8hlJipsNvEPHMdg88wXTbficxMiIiM7Pv+/O+kzEYJvDWVTQjI2X0zAYjozIjIQLCOGZ09X3NvhhiYJmatmLTqFh1BHNmt1sBWyzkiN6yBGdGRo3QtGCNMK6Ko9bHx7cV0fs1mCOA4GmXwpF34et0DR1BsLKSkmZsIBoygCYRRyblcTf2KpPlrdUcsAWPLe5rCi+2X7XqGWvHQEgBkxnl8ynva+7o27OPigQQazAAog5E39dXfIqxjuPbx8e33vt1fQ4ui7d6aUetgYOoOhOHgHFz7r5vjcrlbbYJ5/MhtNQjuT8VKdwXbk6EwlG1woyVASmktEnhQK4zWJFoNTUFgvDs7oYmE0Uw2ZKgd7rmI5909G6MtcdBA1FJdoY0s7evC75bsApaRJKypqVex7kyFQGTad2tGZdrvbk7VVUVy0fY224NDAZJGEGQE2O90p02VyVpt1gSN80IsixraNJJISqCtzDj2WOZ78DZGRDMZISnECsiCKkFx3qQDPhB3H59xQ6Lm8GFWI7MM9R76za9LSPeebcE++7pLY5yCn4unawveBsN3T17zx5UrGQS6kiuVVQGRJg0klV/vK5fezd9L0l7WKctIjKzVjYs3sATUeSDYuQdCbznrr6OKAdVjHoGjoQT9/781TbQBCIKAM2s46hFcD6v/fMfOwCqVl6z08tARB61jiTH9HiaEStXrQ/mSfi6f83Xn3Sj6e57jwLHyixUBQxBxm8e18qytVvSCDDvSHptwjJsUEC/hwxocqUNSKvyPCuzBChgqK+9X3cemVlcychaRzHMIe3A3eFdjSCCVJgxLqpoVg2ZGflAX+qtND1gOQ0aA4t4B1vHSqE5m7o9HKaC+TiDwTGcGZjW119/Fc3KdTw2wuDtmXVYLxpxFCZQ2WDYTgIpyeOMikjQtkeCLfXi/K/g/wxi4R/Kzz1fnr6uuwWgdAQWqWawVkUENOq7sXM24mAWsoCigtbW3MGwx4yjjjPl28eevBQ5YyJt87+ds9DxOL6vxxH5MUPOsDvkYzATdZxHHZbyPMDlQKXYv3x9gaMqxMdRWTzegfPHsXK0+1J737HvOY96/tOZfICwlfrFaem2wDEYfptsIQQjasitsS9pfsd+SxhBvnxF+86iD4wX4EwQ6rHBgGmS5/NjrSeZ0M0UoDkwn46GtjLATCC7h3Gz7oysOu85xoZdoxyEucgYipAbzCiuGx6sCEUCjAx4wiDf9HkzScPjBMOwEHkgKnJpv5SciPsezLWyjsfa81LE8fiIzMs3JQxuZh05MXeTRgXIjMEbCNwz9kSEw0nW5r9C/9vz95v36HUfD/HH7lu3I87jqDrWV3dYNoKJiFhkjbC9f9oOIIDA8jaOkLHNuedAPL8/tXCNx69xvRuznFQPGWRS3feX0Kw/oh4TYwh7OEK7kAt55MJHelXTkLs7yfN8TsArz+e35/r2qG8f57ffgPX2jWvrxf16vT7//PH1+gvP77PO6H7pkmyF3sStfBO2J+UYiBmMmJnX7IgjDaJp9bSm3Y6CEiSPJrbfhdQj5zIqKiorzw+4iqG5l7ETEZF1GGWltliWYTjsQmZ+D3xz8eoXoLIgcmC0OZQYbfXY4UgAGRNRIKVIpGI0pJnhN9exKlEnk4o5qsF3zRSwIlfyzDwZMb775SonuKK096V+wcZefCtFMjYiGUEKA3i6BxNABEh8h/++9QdUzeu6c/x0fCRubK/jIIo0wO7xCJ7FFSuJsvbuT802cykoztYmJi3zum6urHoczwj46+uHd4N7ZbEABt+RpM6t+XX9zI8PIISZuX390tyRKyMADMbFCfXIY2b98bd/eWQNITuzEqucpchIST3mhCd6O4J2/Pnnz//8zx8MrWfE2S6YfDtyFdya9iDSDBkJ8LeYeSEjIEP3vjCzSsEaN+2Y1KsBDz2wsYgws9ahiGjNvf26JTKO9JwnPWAAAWmu+85g5kqsA2eDFSLbaDIZsHBPZyKBpEbaPTEZeeZaIN+7lnmz72yrQRhj4Yizlg9XIvqIhPe+D3JVHmsdKx4rcra+XjlTjBworC3/UlxEBSsMKUQAoNseFxhUntrQ2C0/FB/bx9e85roHszM5H7n++VFcOWFQhRgAPWDSwoxqoo41GMVr92ucxqlJdgqjI+XZvUcXO56KAT3nbOq6D5JK9QUogoykvPfr1T8nLrWm7f1JKI7Cqt/+HhlrgXyHVIIHuTKTvX3NPXuPbl4Z0TOfX/dc+z0pH8+VGWT//HH/+ePHI57fvn/DgVgY761bgMlxS2Oelo2BnRmjPRgTQuP9iaR829UgAAQ39EXLtjq00iWHJY1ib792X6NKS2TQfuMF08ZoTR5eJx28zR514pYHWEAi6r1pV3hDd2+1oeQb2ZC54o2aIkZhvQVVMkwmcxGBAIlQSAWzMtd5nmdF0Hu2ka4jjjq4zku7tzUkig5r1snM0pBD0xmxjswSktzTG7njj+bjc+6f+89uk9UK+vhYf6y1nlJdn4lq2B7QIhVx5Eo6HWYMPTmz9ZKrV8XHbWnvrS9p99yfX6PMCERXdkgYbc+e/nJwMkKExN29x9TM9kjaZ1TWcmYG3Q7Qxoz2PX331p71Eauu/fr89fP187o+r7k1b8y2AQSIx0f92//418cjcmM98eSBR+XHg0Wk1LrmWqJAQ73vGSOzAplAOdIa/zeLLp0ARo5EBYuJfKCNgIEw3gBTaLeGMbIlW7fu3V+6kwFHnatWFWKxiivDhyZGzNeq/qi2psBEhACEpde03EEET0Y5qfDvHsWGvAkcEZUkCwgTDjIojLw1mpmIqlU8Civeor7nPopHVcXa7zVajUQQsYgjuJBphJBArSMPrhXs0euD+gg/iePCfs1fv8YwDj7GR5D5ONc66yrzc6Z6cqvvvsq9ViSVBDQUYw7bDknNXEctOC33bNurylBDKyoRmdl48wU0zYGzgDdB2dAeEKOBdy6TtY5vBtUDTd/3JO/WX399fv685lbVfyEhb0D35/369bpfc7024IiQG6kPP/vH/a9//+f4CAbP8/C56vGRZ/W8jOneSYJhBGDdr1oVR0Sm400PE2jGIscgGGAiEoiBBCuQzhUFvc1HcxoyyIEdVGDfM9L7C8s6cz3WkUhGrPK3xMcDR0XmW7IP3BGJyC3/uqY/L9yiMxmTMRjhJmyGqYBXIKNWHY40wuDQ8t3T8FusRGVwRRwR7LmvmR3hI2Pd6Pt1T2xM03EGJIeO4yDCcGTnIvMkH8qauXL6X/L4m5Sp7f01/gnOeeTiSD+fK77FH0f8rVm35alxte62SiBac3lA0iNPBA6wJ4ZCBIJJ7WO8LZIALCCsCpMGIJAAY3YDyopaZ2ZiRg2pMV3BrAANh+S5uz+vDf+89r//x//7/Lynpx71/HaulSRwgI1jrY+/f1/rELbmNvbj+xlP/Km/jjhdYGUdBQ6ZEURWrY+CkWHCOup+SXeQoPi2tH4HN8PvjYgnosyw3IBBkE4yoxQ5aAtEECCainwj4BSuqIJNOh2JJGnrGfzjzL89+MyuoMFwMdKZJq7uA/d135/X9KBDjm5YAxifo8NAOhkVkRFDVhzvW3/21ZokonJlZmW8O0iYC5rwM+oPGfava5tVj3W+j5tbJBARzPccohuwoJnNVqEWTTRnt7pX6vu3fXpDV46+VX1AnJp43jnXlJyNaEYzNIZGvc3Ykkw44KQclvkVZXDOYq1zIGPY8AaT45FEQ9pMpEkiKmutlTXw7h7t8LSxWJ7L4qh3X19fP193/7qu6TsLuXh+5PlgJDPCixGOrG/f/ljHYzCevecrDh1nuWNGXFVZx8rQizNJO1TFxMFaSMBXpnRTEgaIAUkWj2pD4VaHgXfBzMD7iUGSAx/BAjh+s8ANIOzFZH374MADa48VZiizMgt9Rj8wT+Ab78VNKMORg5IiXml697V9zT+MLxx3QECrPZPxvsCkPD13xMr0EKPds0d9rOOoda6MzMxFJpBeo8zy1N6MWB+PM88+Kj33DUIBJyNADmbQguKOAjIgt/1jdE/H7k3onx6JYujWfe/Nj+PxWFfEf9k/X3RlXd0GuU4EnCVwbHtePY2w04Mw2x36KjQzo+J3IwpgDyhmR+u3FRA4KteqmYlVyGBlhKE92vM2VeQMBUgiltaJkR4meTbk1PlxZOWxVmRJ0PMI8nwcx3kKVtc5CXcJIl4UypFK7DJSw0RCRRYVIWbY2cqb+toSHeV41ynkkanNa9+DsOU30zeSMuJdzhL67dHe3oZAcgHhWLHOYzx37/1lTrCK52LlkpZ39a916XAfaEoZjiPANh4Zdm0cO5882f+Y+0+URbV7PJWdxcgEeiZmDsNZIva+9t5hVMaReWT5PeyZJB3b7iE/6/H49jzjROQN7euFqoSLSME9s/u697bryASCECj7L/ATPnLxI8FilaV9J2bleR7nY1V+xevHNG7U6/4ZjGNlVmqtpmHbaPJtwErRMjzlfWuynqjD712ASQtjqUMMUlSUIx2MVogeeAdMC0bYHosNezprVTHJQ+kkP1krFeQ66lzrON7sCwvACauyVuXYkoMRUnja8hLCJ1TupTj3rEYZC7WoVQ0D5GT+rLHWZQWJUNIVE1lmMNcetFowiAhHFSADRQB+9yIiuD3MQkQmSHsZhi0eDlfVQhUoRrM3Zqsvfw00wJjmop83j6+V6wl5EY8seO0dm/8ltLwYIEwq6/0/TGQw2fPa0vQ906vWI9YCyzE9cEeRjIRptmPqHD6qViH6vuRJxgoXQAkIOzSsPD7Wx6rasbcGAMFGKV3rANII5pwEvNaqlTERfaz5/tTdZV/mQZRJV4jukW1Jb+fdFQqHQhYC4iB+txIBaMbv80vmWzPwrYOIKI7cGEigCBwowIMBDFABvReJFSGucZiuqHPFOqoWeZgFvfWWAmCADmfFqIphpdrcCqWnxks67MfgMBfulaqsQERkg6syAv+YbIN0BiIUvp0rjEBmQh7bDBRJlG3NQBwLEUhCtjtiBQnCkDGgMlmJZNN30Cf2w/sxfVipHZqgQbnhe3CMz1mP/KgIcJGVTM5KR+btYyIA0ggwK4mw1LN7RuoDPKJyMhkEsFvitBgcDzMq68hzxWG/c8l7NIQhAV6/hRw+1hm5Hsf5PkRL3sAEAxE8YyIxgXaY600KhZuWZggcR0b+f3LXrqHM7SgFAAAAAElFTkSuQmCC",
"text/plain": [
"PILImage mode=RGB size=192x192"
]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"im = PILImage.create('dog.jpg')\n",
"im.thumbnail((192,192))\n",
"im"
]
},
{
"cell_type": "markdown",
"id": "7683e0bb",
"metadata": {},
"source": [
"Wrote #|export to know what you would need to include in your python script"
]
},
{
"cell_type": "code",
"execution_count": 75,
"id": "b6eafa98",
"metadata": {},
"outputs": [],
"source": [
"#|export\n",
"learn = load_learner('model.pkl')"
]
},
{
"cell_type": "code",
"execution_count": 76,
"id": "c58e6bec",
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 30.4 ms, sys: 23.5 ms, total: 53.8 ms\n",
"Wall time: 50.7 ms\n"
]
},
{
"data": {
"text/plain": [
"('False', tensor(0), tensor([9.9998e-01, 2.1452e-05]))"
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%time learn.predict(im)"
]
},
{
"cell_type": "markdown",
"id": "89895bea",
"metadata": {},
"source": [
"### Gradio doesn't offer numpy arrays. It returns tensors. It changes it into a normal float\n",
"\n",
"zip(categories, map(float,probs)): The zip() function takes two iterables as its arguments and returns an iterator of pairs where the first element of each passed iterable is paired together, the second element of each passed iterable is paired together, and so on. In this case, the categories tuple and the iterable of floating-point numbers are passed, resulting in an iterable of pairs with a category (e.g., 'Dog' or 'Cat') as the first element and the corresponding probability as the second element.\n",
"\n",
"dict(zip(categories, map(float,probs))): The dict() function takes the iterable of pairs and converts it into a dictionary. The first element of each pair becomes a key in the dictionary, and the second element becomes the corresponding value.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 77,
"id": "60943f1e",
"metadata": {},
"outputs": [],
"source": [
"#|export\n",
"categories = ('Dog', 'Cat')\n",
"\n",
"def classify_image(img):\n",
" pred,idx,probs = learn.predict(img)\n",
" return dict(zip(categories, map(float,probs)))"
]
},
{
"cell_type": "code",
"execution_count": 78,
"id": "faa912af",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"{'Dog': 0.9999785423278809, 'Cat': 2.145169855793938e-05}"
]
},
"execution_count": 78,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"classify_image(im)"
]
},
{
"cell_type": "code",
"execution_count": 79,
"id": "b2cc2ec2",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/gradio/inputs.py:257: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
" warnings.warn(\n",
"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
" warnings.warn(value)\n",
"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/gradio/outputs.py:197: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
" warnings.warn(\n",
"/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/gradio/deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
" warnings.warn(value)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7864\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/plain": []
},
"execution_count": 79,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#|export\n",
"image = gr.inputs.Image(shape=(192,192))\n",
"label = gr.outputs.Label()\n",
"examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']\n",
"\n",
"intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
"intf.launch(inline=False)"
]
},
{
"cell_type": "code",
"execution_count": 80,
"id": "933e4d13",
"metadata": {},
"outputs": [],
"source": [
"m = learn.model"
]
},
{
"cell_type": "code",
"execution_count": 81,
"id": "a95e8301",
"metadata": {},
"outputs": [],
"source": [
"ps = list(m.parameters())"
]
},
{
"cell_type": "code",
"execution_count": 82,
"id": "dba2620d",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Parameter containing:\n",
"tensor([ 2.3466e-01, 2.6510e-01, -5.1096e-08, 5.1749e-01, 3.4404e-09,\n",
" 2.2097e-01, 4.2220e-01, 1.3153e-07, 2.4928e-01, 1.5152e-06,\n",
" 3.1646e-01, 2.5053e-01, 3.7872e-01, 1.0862e-05, 2.7468e-01,\n",
" 2.3753e-01, 2.4204e-01, 3.9516e-01, 4.7046e-01, 2.9192e-01,\n",
" 2.7224e-01, 2.7841e-01, 2.9122e-01, 2.0654e-01, 2.6023e-01,\n",
" 2.8018e-01, 2.9415e-01, 3.1532e-01, 3.8897e-01, 3.0183e-01,\n",
" 2.6597e-01, 2.1040e-01, 2.8733e-01, 3.3120e-01, 4.2706e-01,\n",
" 3.7333e-01, 7.4804e-08, 1.8998e-01, 1.4740e-08, 2.2439e-01,\n",
" 1.7998e-01, 2.4875e-01, 2.7263e-01, 2.5951e-01, 2.9423e-01,\n",
" 3.0042e-01, 2.2399e-01, 2.6372e-01, 2.2001e-08, 2.6561e-01,\n",
" 2.2093e-01, 2.8387e-01, 3.3032e-01, 2.2735e-01, 3.6627e-01,\n",
" 2.1374e-01, 2.3958e-01, 2.4871e-01, 5.2495e-01, 2.4678e-01,\n",
" 2.9540e-01, 2.5761e-01, 4.8339e-01, 2.6571e-01],\n",
" requires_grad=True)"
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ps[1]"
]
},
{
"cell_type": "code",
"execution_count": 83,
"id": "eb9bac04",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([64, 3, 7, 7])"
]
},
"execution_count": 83,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ps[0].shape"
]
},
{
"cell_type": "code",
"execution_count": 84,
"id": "9c5971f4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Parameter containing:\n",
"tensor([[[[-1.0307e-02, -5.9970e-03, -1.6513e-03, ..., 5.6735e-02,\n",
" 1.7225e-02, -1.2566e-02],\n",
" [ 1.1195e-02, 9.6654e-03, -1.0978e-01, ..., -2.7109e-01,\n",
" -1.2894e-01, 3.8624e-03],\n",
" [-6.8353e-03, 5.9206e-02, 2.9559e-01, ..., 5.1983e-01,\n",
" 2.5642e-01, 6.3645e-02],\n",
" ...,\n",
" [-2.7462e-02, 1.6128e-02, 7.2657e-02, ..., -3.3277e-01,\n",
" -4.2050e-01, -2.5778e-01],\n",
" [ 3.0660e-02, 4.1013e-02, 6.2887e-02, ..., 4.1390e-01,\n",
" 3.9363e-01, 1.6608e-01],\n",
" [-1.3705e-02, -3.6232e-03, -2.4056e-02, ..., -1.5063e-01,\n",
" -8.2194e-02, -5.7781e-03]],\n",
"\n",
" [[-1.1386e-02, -2.6561e-02, -3.4547e-02, ..., 3.2588e-02,\n",
" 7.5460e-04, -2.5655e-02],\n",
" [ 4.5676e-02, 3.3653e-02, -1.0445e-01, ..., -3.1244e-01,\n",
" -1.6043e-01, -1.2071e-03],\n",
" [-8.4443e-04, 9.8443e-02, 4.0212e-01, ..., 7.0792e-01,\n",
" 3.6889e-01, 1.2456e-01],\n",
" ...,\n",
" [-5.5963e-02, -5.2376e-03, 2.7057e-02, ..., -4.6179e-01,\n",
" -5.7081e-01, -3.6555e-01],\n",
" [ 3.2810e-02, 5.5533e-02, 9.9625e-02, ..., 5.4635e-01,\n",
" 4.8273e-01, 1.9864e-01],\n",
" [ 5.2531e-03, 6.6662e-03, -1.7298e-02, ..., -1.4822e-01,\n",
" -7.7277e-02, 6.5722e-04]],\n",
"\n",
" [[-2.0136e-03, -9.1075e-03, 2.1294e-02, ..., 8.9246e-02,\n",
" 3.3757e-02, -2.0007e-02],\n",
" [ 1.5416e-02, -1.8584e-02, -1.2582e-01, ..., -2.5333e-01,\n",
" -1.2971e-01, -2.7886e-02],\n",
" [ 9.8732e-03, 4.9102e-02, 2.1705e-01, ..., 3.4876e-01,\n",
" 1.0438e-01, 1.8460e-02],\n",
" ...,\n",
" [-2.8343e-02, 1.8438e-02, 9.8662e-02, ..., -1.1736e-01,\n",
" -2.5756e-01, -1.5449e-01],\n",
" [ 2.0769e-02, -2.6162e-03, -3.7811e-02, ..., 2.4146e-01,\n",
" 2.4349e-01, 1.1799e-01],\n",
" [ 7.4701e-04, 8.0281e-04, -1.0040e-02, ..., -1.4860e-01,\n",
" -1.1750e-01, -3.8346e-02]]],\n",
"\n",
"\n",
" [[[-4.3226e-03, -3.9784e-03, 3.2265e-03, ..., -3.6989e-02,\n",
" -2.5135e-02, -4.7950e-02],\n",
" [ 5.1446e-02, 5.3530e-02, 8.0548e-02, ..., 1.4487e-01,\n",
" 1.4292e-01, 1.2314e-01],\n",
" [-7.1668e-03, 2.3357e-03, 3.7700e-02, ..., 6.1585e-02,\n",
" 8.0365e-02, 1.1716e-01],\n",
" ...,\n",
" [-2.6607e-02, -1.2285e-01, -1.3645e-01, ..., -1.4067e-01,\n",
" -1.1157e-01, -4.9597e-02],\n",
" [ 2.3654e-02, -1.7194e-02, -1.1072e-02, ..., -1.8821e-02,\n",
" -2.3335e-02, -2.9500e-02],\n",
" [ 2.8787e-02, 2.1736e-02, 4.7931e-02, ..., 2.5500e-02,\n",
" 3.5330e-02, 1.1249e-02]],\n",
"\n",
" [[ 5.6052e-04, 1.2242e-02, 4.2105e-02, ..., 4.6452e-02,\n",
" 4.0455e-02, -1.4434e-02],\n",
" [ 4.3588e-02, 6.8909e-02, 1.3279e-01, ..., 2.8614e-01,\n",
" 2.6910e-01, 2.0936e-01],\n",
" [-5.7462e-02, -2.2474e-02, 3.0669e-02, ..., 1.3770e-01,\n",
" 1.6541e-01, 1.7947e-01],\n",
" ...,\n",
" [-1.0800e-01, -2.5214e-01, -2.9734e-01, ..., -2.8502e-01,\n",
" -2.1495e-01, -1.0324e-01],\n",
" [ 4.0841e-02, -3.2678e-02, -6.3399e-02, ..., -9.2349e-02,\n",
" -6.9890e-02, -4.9866e-02],\n",
" [ 8.3046e-02, 8.7661e-02, 1.0116e-01, ..., 5.2724e-02,\n",
" 6.0950e-02, 4.1172e-02]],\n",
"\n",
" [[-1.6296e-02, -1.3764e-02, 5.3758e-03, ..., 4.3766e-02,\n",
" 2.2754e-02, -4.5959e-02],\n",
" [ 3.3337e-02, 4.2162e-02, 9.3631e-02, ..., 2.6171e-01,\n",
" 2.2976e-01, 1.6697e-01],\n",
" [-4.5809e-02, -1.6173e-02, 2.6966e-02, ..., 1.4962e-01,\n",
" 1.3223e-01, 1.3582e-01],\n",
" ...,\n",
" [-7.1955e-02, -1.8885e-01, -2.3376e-01, ..., -1.9032e-01,\n",
" -1.5606e-01, -7.5964e-02],\n",
" [ 5.1340e-02, -2.5670e-02, -6.9248e-02, ..., -5.8936e-02,\n",
" -6.1516e-02, -4.4539e-02],\n",
" [ 1.1189e-01, 7.9119e-02, 6.5956e-02, ..., 3.1680e-02,\n",
" 2.5255e-02, 7.4440e-03]]],\n",
"\n",
"\n",
" [[[-7.0824e-08, -6.4305e-08, -7.3805e-08, ..., -9.7998e-08,\n",
" -1.0904e-07, -8.3420e-08],\n",
" [-6.1124e-09, 2.0612e-09, -8.0921e-09, ..., -4.9840e-08,\n",
" -4.3835e-08, -3.0537e-09],\n",
" [ 7.1952e-08, 7.5615e-08, 5.9281e-08, ..., -9.7507e-09,\n",
" -1.0951e-09, 4.2442e-08],\n",
" ...,\n",
" [ 9.5887e-08, 1.0039e-07, 7.9816e-08, ..., -1.7490e-08,\n",
" -4.7665e-08, -1.3265e-08],\n",
" [ 1.2904e-07, 1.4761e-07, 1.7476e-07, ..., 1.3232e-07,\n",
" 1.0628e-07, 9.3314e-08],\n",
" [ 1.2558e-07, 1.3644e-07, 1.8431e-07, ..., 2.1398e-07,\n",
" 1.7709e-07, 1.7166e-07]],\n",
"\n",
" [[-1.2690e-07, -9.6137e-08, -1.0372e-07, ..., -1.1808e-07,\n",
" -1.3309e-07, -1.0819e-07],\n",
" [-5.7412e-08, -2.5054e-08, -3.0114e-08, ..., -7.2921e-08,\n",
" -6.7021e-08, -2.2574e-08],\n",
" [ 2.1813e-08, 4.8608e-08, 3.1221e-08, ..., -1.8694e-08,\n",
" -7.9589e-09, 3.9749e-08],\n",
" ...,\n",
" [ 5.6012e-08, 7.5524e-08, 4.4495e-08, ..., -4.4127e-08,\n",
" -5.9929e-08, -1.8247e-08],\n",
" [ 7.7612e-08, 9.8346e-08, 1.0455e-07, ..., 6.3270e-08,\n",
" 4.1780e-08, 4.5900e-08],\n",
" [ 5.9832e-08, 7.1005e-08, 9.0435e-08, ..., 1.1654e-07,\n",
" 8.7549e-08, 9.8835e-08]],\n",
"\n",
" [[-4.3809e-08, 1.3270e-08, 7.8274e-09, ..., -5.8803e-09,\n",
" -2.6217e-08, -1.5649e-08],\n",
" [ 4.1699e-08, 1.0777e-07, 1.0946e-07, ..., 7.6402e-08,\n",
" 7.1449e-08, 9.7613e-08],\n",
" [ 1.0436e-07, 1.6585e-07, 1.5933e-07, ..., 1.3517e-07,\n",
" 1.3487e-07, 1.6448e-07],\n",
" ...,\n",
" [ 9.8762e-08, 1.5072e-07, 1.2546e-07, ..., 6.8314e-08,\n",
" 6.8381e-08, 1.1367e-07],\n",
" [ 9.1433e-08, 1.3576e-07, 1.3793e-07, ..., 1.1678e-07,\n",
" 1.1723e-07, 1.4394e-07],\n",
" [ 6.2181e-08, 8.8183e-08, 1.0456e-07, ..., 1.3941e-07,\n",
" 1.3332e-07, 1.5844e-07]]],\n",
"\n",
"\n",
" ...,\n",
"\n",
"\n",
" [[[-6.1850e-02, -3.0204e-02, 1.9225e-02, ..., 4.3690e-02,\n",
" -2.2182e-02, -4.2359e-02],\n",
" [-3.7950e-02, 6.1364e-03, 4.5841e-02, ..., 9.6064e-02,\n",
" 5.9188e-02, 2.9821e-02],\n",
" [-2.9540e-02, 2.8500e-03, 2.0550e-02, ..., 5.9900e-02,\n",
" 4.1370e-02, 2.3023e-02],\n",
" ...,\n",
" [ 1.2053e-02, 4.5757e-02, 4.4977e-02, ..., 4.7452e-02,\n",
" 2.2291e-02, -5.5232e-03],\n",
" [-3.2307e-02, -1.2114e-02, 2.2131e-02, ..., 5.8076e-02,\n",
" -7.4972e-03, -5.9736e-02],\n",
" [-4.3121e-02, -2.7993e-02, -5.7500e-03, ..., 8.8512e-02,\n",
" 8.4506e-03, -5.0001e-02]],\n",
"\n",
" [[-6.1300e-02, -1.4064e-02, 1.7164e-02, ..., 1.8335e-02,\n",
" -3.2828e-02, -4.1247e-02],\n",
" [-3.1437e-02, 2.4455e-02, 4.5485e-02, ..., 6.6784e-02,\n",
" 4.6578e-02, 3.3075e-02],\n",
" [-3.2112e-02, 2.0730e-02, 2.3368e-02, ..., 3.5265e-02,\n",
" 3.6352e-02, 3.1130e-02],\n",
" ...,\n",
" [ 1.7888e-02, 6.1089e-02, 4.8333e-02, ..., 3.7828e-02,\n",
" 2.8915e-02, 1.3966e-02],\n",
" [-1.0697e-02, 2.2213e-02, 4.2900e-02, ..., 6.0314e-02,\n",
" 1.6221e-02, -1.2477e-02],\n",
" [-2.2053e-02, 1.3437e-02, 3.1118e-02, ..., 1.0415e-01,\n",
" 4.0152e-02, -5.3018e-03]],\n",
"\n",
" [[-8.5301e-02, -4.2641e-02, 6.7614e-03, ..., 3.0733e-02,\n",
" -3.4911e-02, -5.0094e-02],\n",
" [-2.9130e-02, 1.8162e-02, 5.1066e-02, ..., 9.0154e-02,\n",
" 5.3342e-02, 4.0012e-02],\n",
" [-3.9832e-02, -1.1038e-03, 9.6184e-03, ..., 2.4053e-02,\n",
" 2.6179e-02, 2.5331e-02],\n",
" ...,\n",
" [-3.0691e-03, 3.0477e-02, 1.6334e-02, ..., 5.4370e-03,\n",
" -6.3447e-03, -8.5605e-03],\n",
" [-2.2845e-02, -2.7455e-03, 2.3265e-02, ..., 3.5841e-02,\n",
" -1.4349e-02, -3.2484e-02],\n",
" [-9.7259e-03, 7.1888e-03, 1.0766e-02, ..., 7.0478e-02,\n",
" 1.2945e-02, -8.3864e-03]]],\n",
"\n",
"\n",
" [[[-7.7924e-03, 2.0004e-02, 3.4252e-02, ..., 2.8758e-02,\n",
" 1.2923e-02, 1.8262e-02],\n",
" [ 8.7519e-03, -3.2951e-02, -3.5825e-02, ..., 7.2526e-02,\n",
" 4.5906e-02, 5.2436e-02],\n",
" [-3.6207e-02, -1.1890e-01, -1.3778e-01, ..., 3.3783e-02,\n",
" 3.7824e-02, 2.7016e-02],\n",
" ...,\n",
" [ 1.7229e-02, 3.8747e-03, -8.3009e-03, ..., 2.7296e-03,\n",
" 1.8349e-02, 1.6107e-02],\n",
" [-1.0385e-03, 1.6347e-02, 1.7053e-02, ..., 3.3412e-03,\n",
" 2.2865e-02, 6.5425e-04],\n",
" [ 6.0852e-03, 2.7099e-02, 1.4285e-02, ..., 7.5501e-03,\n",
" 1.8751e-02, 1.5591e-02]],\n",
"\n",
" [[-1.3234e-02, -3.0090e-04, 8.2490e-03, ..., -5.9507e-03,\n",
" 9.3944e-03, 1.5916e-02],\n",
" [-1.8273e-02, -6.7923e-02, -7.0677e-02, ..., 2.9899e-02,\n",
" 2.6314e-02, 2.3853e-02],\n",
" [-5.4355e-02, -1.4665e-01, -1.6215e-01, ..., 1.1776e-02,\n",
" 3.2509e-02, 1.2061e-02],\n",
" ...,\n",
" [ 7.9659e-04, -1.7594e-02, -1.9573e-02, ..., -4.1458e-03,\n",
" 2.4709e-02, 1.2955e-02],\n",
" [-6.8778e-04, 1.1742e-02, 2.4733e-02, ..., 6.1048e-03,\n",
" 3.9225e-02, 9.6682e-03],\n",
" [-7.2444e-03, 6.6879e-03, 5.2469e-03, ..., -7.6330e-03,\n",
" 2.7232e-02, 1.7698e-02]],\n",
"\n",
" [[ 1.5605e-05, -4.6785e-03, 2.5040e-03, ..., -4.7778e-02,\n",
" -2.5972e-02, -2.3342e-02],\n",
" [-1.4100e-04, -5.1310e-02, -5.9845e-02, ..., -1.7273e-02,\n",
" -2.3255e-02, -3.7198e-02],\n",
" [-2.2576e-02, -9.9288e-02, -1.1167e-01, ..., -1.1663e-02,\n",
" -8.2869e-03, -4.0491e-02],\n",
" ...,\n",
" [ 1.1436e-02, -8.0333e-03, -1.4712e-03, ..., -3.4082e-02,\n",
" -8.6370e-03, -2.3442e-02],\n",
" [ 2.9223e-03, 6.6097e-04, 1.9902e-02, ..., -2.1970e-02,\n",
" 1.4855e-02, -1.4465e-02],\n",
" [-1.9132e-02, -2.9414e-02, -2.3280e-02, ..., -4.8580e-02,\n",
" -1.3045e-02, -2.4382e-02]]],\n",
"\n",
"\n",
" [[[-3.6395e-02, 7.1372e-03, 1.9100e-02, ..., 1.9616e-02,\n",
" 1.4883e-02, -1.7280e-02],\n",
" [-1.1123e-02, 8.5643e-02, 1.2670e-01, ..., 1.3817e-02,\n",
" 4.9143e-06, -3.0100e-02],\n",
" [ 1.1318e-01, 1.8634e-01, 5.0693e-02, ..., -1.7322e-01,\n",
" -7.1941e-02, -6.2378e-02],\n",
" ...,\n",
" [-5.3069e-02, -2.5775e-01, -2.6740e-01, ..., 2.6792e-01,\n",
" 1.4354e-01, 5.5268e-02],\n",
" [-2.1025e-02, -2.9916e-02, 1.0250e-01, ..., 2.0853e-01,\n",
" -4.0464e-03, -3.7982e-02],\n",
" [-2.2184e-02, 1.2396e-02, 8.4337e-02, ..., -4.4896e-02,\n",
" -1.4677e-01, -9.0759e-02]],\n",
"\n",
" [[-5.4661e-03, 3.2758e-02, 1.5501e-02, ..., -7.7200e-03,\n",
" 3.0403e-03, 1.1470e-03],\n",
" [ 6.1676e-02, 1.4898e-01, 1.4648e-01, ..., -2.8825e-02,\n",
" -2.0167e-02, -9.1216e-03],\n",
" [ 1.6143e-01, 2.0889e-01, -2.5544e-02, ..., -2.7267e-01,\n",
" -1.0726e-01, -6.2880e-02],\n",
" ...,\n",
" [-1.3723e-01, -4.0857e-01, -3.8543e-01, ..., 4.0858e-01,\n",
" 2.6212e-01, 1.3504e-01],\n",
" [-5.9399e-02, -6.1121e-02, 1.4204e-01, ..., 3.5792e-01,\n",
" 9.1008e-02, -1.5957e-03],\n",
" [ 7.8322e-03, 5.8431e-02, 1.5343e-01, ..., 4.7149e-02,\n",
" -1.0084e-01, -9.7790e-02]],\n",
"\n",
" [[-5.7493e-03, 1.3386e-02, -2.6461e-02, ..., 4.4917e-03,\n",
" 2.0718e-03, 1.3916e-02],\n",
" [ 6.5562e-03, 4.5188e-02, 6.0287e-02, ..., 1.4423e-02,\n",
" -5.0240e-03, 4.1057e-03],\n",
" [ 5.5244e-02, 1.2401e-01, 4.3231e-02, ..., -1.4477e-01,\n",
" -7.4414e-02, -5.7454e-02],\n",
" ...,\n",
" [-3.1518e-02, -1.6329e-01, -1.5787e-01, ..., 2.2914e-01,\n",
" 1.2025e-01, 7.2101e-02],\n",
" [-1.0469e-02, -1.0700e-03, 8.4646e-02, ..., 1.5758e-01,\n",
" 2.2227e-02, -9.9698e-03],\n",
" [-4.8833e-03, -4.9717e-03, 3.6387e-02, ..., -2.4273e-02,\n",
" -7.1112e-02, -6.6687e-02]]]], requires_grad=True)"
]
},
"execution_count": 84,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ps[0]"
]
},
{
"cell_type": "markdown",
"id": "3a97f529",
"metadata": {},
"source": [
"### export -"
]
},
{
"cell_type": "markdown",
"id": "69e5ed0a",
"metadata": {},
"source": [
"Had to use a different way, instead of this:\n",
"\n",
"`from nbdev.export import notebook2script\n",
"notebook2script('app.ipynb')`"
]
},
{
"cell_type": "code",
"execution_count": 85,
"id": "70241719",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Export successful\n"
]
}
],
"source": [
"import nbdev\n",
"nbdev.export.nb_export('app.ipynb', 'app')\n",
"print('Export successful')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "98e06ecd",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}