diff --git "a/notebooks/Normalizing_flows_Xiao+19-Copy1.ipynb" "b/notebooks/Normalizing_flows_Xiao+19-Copy1.ipynb"
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@@ -0,0 +1,4029 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2b543fde-bd5f-4237-a878-677b107cf85a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class AffineCouplingBlock(Flow):\n",
+    "    \"\"\"\n",
+    "    Affine Coupling layer including split and merge operation\n",
+    "    \"\"\"\n",
+    "    def __init__(self, param_map, scale=True, scale_map=\"exp\", split_mode=\"channel\"):\n",
+    "        \"\"\"Constructor\n",
+    "\n",
+    "        Args:\n",
+    "          param_map: Maps features to shift and scale parameter (if applicable)\n",
+    "          scale: Flag whether scale shall be applied\n",
+    "          scale_map: Map to be applied to the scale parameter, can be 'exp' as in RealNVP or 'sigmoid' as in Glow\n",
+    "          split_mode: Splitting mode, for possible values see Split class\n",
+    "        \"\"\"\n",
+    "        super().__init__()\n",
+    "        self.flows = nn.ModuleList([])\n",
+    "        # Split layer\n",
+    "        self.flows += [Split(split_mode)]\n",
+    "        # Affine coupling layer\n",
+    "        self.flows += [AffineCoupling(param_map, scale, scale_map)]\n",
+    "        # Merge layer\n",
+    "        self.flows += [Merge(split_mode)]\n",
+    "\n",
+    "    def forward(self, z, condition=None):\n",
+    "        log_det_tot = torch.zeros(z.shape[0], dtype=z.dtype, device=z.device)\n",
+    "        for flow in self.flows:\n",
+    "            z, log_det = flow(z)\n",
+    "            log_det_tot += log_det\n",
+    "        return z, log_det_tot\n",
+    "\n",
+    "    def inverse(self, z):\n",
+    "        log_det_tot = torch.zeros(z.shape[0], dtype=z.dtype, device=z.device)\n",
+    "        for i in range(len(self.flows) - 1, -1, -1):\n",
+    "            z, log_det = self.flows[i].inverse(z)\n",
+    "            log_det_tot += log_det\n",
+    "        return z, log_det_tot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cbed478a-e36f-4412-9404-995a8a47975d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class AffineCoupling(Flow):\n",
+    "    \"\"\"\n",
+    "    Affine Coupling layer as introduced RealNVP paper, see arXiv: 1605.08803\n",
+    "    \"\"\"\n",
+    "\n",
+    "\n",
+    "    def __init__(self, param_map, scale=True, scale_map=\"exp\"):\n",
+    "        \"\"\"Constructor\n",
+    "\n",
+    "        Args:\n",
+    "          param_map: Maps features to shift and scale parameter (if applicable)\n",
+    "          scale: Flag whether scale shall be applied\n",
+    "          scale_map: Map to be applied to the scale parameter, can be 'exp' as in RealNVP or 'sigmoid' as in Glow, 'sigmoid_inv' uses multiplicative sigmoid scale when sampling from the model\n",
+    "        \"\"\"\n",
+    "        super().__init__()\n",
+    "        self.add_module(\"param_map\", param_map)\n",
+    "        self.scale = scale\n",
+    "        self.scale_map = scale_map\n",
+    "\n",
+    "    def forward(self, z):\n",
+    "        \"\"\"\n",
+    "        z is a list of z1 and z2; ```z = [z1, z2]```\n",
+    "        z1 is left constant and affine map is applied to z2 with parameters depending\n",
+    "        on z1\n",
+    "\n",
+    "        Args:\n",
+    "          z\n",
+    "        \"\"\"\n",
+    "        z1, z2 = z\n",
+    "        \n",
+    "    \n",
+    "        param = self.param_map(z1)\n",
+    "        if self.scale:\n",
+    "            shift = param[:, 0::2, ...]\n",
+    "            scale_ = param[:, 1::2, ...]\n",
+    "            if self.scale_map == \"exp\":\n",
+    "                z2 = z2 * torch.exp(scale_) + shift\n",
+    "                log_det = torch.sum(scale_, dim=list(range(1, shift.dim())))\n",
+    "            elif self.scale_map == \"sigmoid\":\n",
+    "                scale = torch.sigmoid(scale_ + 2)\n",
+    "                z2 = z2 / scale + shift\n",
+    "                log_det = -torch.sum(torch.log(scale), dim=list(range(1, shift.dim())))\n",
+    "            elif self.scale_map == \"sigmoid_inv\":\n",
+    "                scale = torch.sigmoid(scale_ + 2)\n",
+    "                z2 = z2 * scale + shift\n",
+    "                log_det = torch.sum(torch.log(scale), dim=list(range(1, shift.dim())))\n",
+    "            else:\n",
+    "                raise NotImplementedError(\"This scale map is not implemented.\")\n",
+    "        else:\n",
+    "            z2 = z2 + param\n",
+    "            log_det = zero_log_det_like_z(z2)\n",
+    "        return [z1, z2], log_det\n",
+    "\n",
+    "    def inverse(self, z):\n",
+    "        z1, z2 = z\n",
+    "        param = self.param_map(z1)\n",
+    "        if self.scale:\n",
+    "            shift = param[:, 0::2, ...]\n",
+    "            scale_ = param[:, 1::2, ...]\n",
+    "            if self.scale_map == \"exp\":\n",
+    "                z2 = (z2 - shift) * torch.exp(-scale_)\n",
+    "                log_det = -torch.sum(scale_, dim=list(range(1, shift.dim())))\n",
+    "            elif self.scale_map == \"sigmoid\":\n",
+    "                scale = torch.sigmoid(scale_ + 2)\n",
+    "                z2 = (z2 - shift) * scale\n",
+    "                log_det = torch.sum(torch.log(scale), dim=list(range(1, shift.dim())))\n",
+    "            elif self.scale_map == \"sigmoid_inv\":\n",
+    "                scale = torch.sigmoid(scale_ + 2)\n",
+    "                z2 = (z2 - shift) / scale\n",
+    "                log_det = -torch.sum(torch.log(scale), dim=list(range(1, shift.dim())))\n",
+    "            else:\n",
+    "                raise NotImplementedError(\"This scale map is not implemented.\")\n",
+    "        else:\n",
+    "            z2 = z2 - param\n",
+    "            log_det = zero_log_det_like_z(z2)\n",
+    "        return [z1, z2], log_det\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "681aef67-48e4-49ab-873c-c06f58f18894",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "class MLP(nn.Module):\n",
+    "    \"\"\"\n",
+    "    A multilayer perceptron with Leaky ReLU nonlinearities\n",
+    "    \"\"\"\n",
+    "\n",
+    "    def __init__(\n",
+    "        self,\n",
+    "        layers,\n",
+    "        leaky=0.0,\n",
+    "        score_scale=None,\n",
+    "        output_fn=None,\n",
+    "        output_scale=None,\n",
+    "        init_zeros=False,\n",
+    "        dropout=None,\n",
+    "    ):\n",
+    "        \"\"\"\n",
+    "        layers: list of layer sizes from start to end\n",
+    "        leaky: slope of the leaky part of the ReLU, if 0.0, standard ReLU is used\n",
+    "        score_scale: Factor to apply to the scores, i.e. output before output_fn.\n",
+    "        output_fn: String, function to be applied to the output, either None, \"sigmoid\", \"relu\", \"tanh\", or \"clampexp\"\n",
+    "        output_scale: Rescale outputs if output_fn is specified, i.e. ```scale * output_fn(out / scale)```\n",
+    "        init_zeros: Flag, if true, weights and biases of last layer are initialized with zeros (helpful for deep models, see [arXiv 1807.03039](https://arxiv.org/abs/1807.03039))\n",
+    "        dropout: Float, if specified, dropout is done before last layer; if None, no dropout is done\n",
+    "        \"\"\"\n",
+    "        super().__init__()\n",
+    "        net = nn.ModuleList([])\n",
+    "        for k in range(len(layers) - 2):\n",
+    "            net.append(nn.Linear(layers[k], layers[k + 1]))\n",
+    "            net.append(nn.LeakyReLU(leaky))\n",
+    "        if dropout is not None:\n",
+    "            net.append(nn.Dropout(p=dropout))\n",
+    "        net.append(nn.Linear(layers[-2], layers[-1]))\n",
+    "        if init_zeros:\n",
+    "            nn.init.zeros_(net[-1].weight)\n",
+    "            nn.init.zeros_(net[-1].bias)\n",
+    "        if output_fn is not None:\n",
+    "            if score_scale is not None:\n",
+    "                net.append(utils.ConstScaleLayer(score_scale))\n",
+    "            if output_fn == \"sigmoid\":\n",
+    "                net.append(nn.Sigmoid())\n",
+    "            elif output_fn == \"relu\":\n",
+    "                net.append(nn.ReLU())\n",
+    "            elif output_fn == \"tanh\":\n",
+    "                net.append(nn.Tanh())\n",
+    "            elif output_fn == \"clampexp\":\n",
+    "                net.append(utils.ClampExp())\n",
+    "            else:\n",
+    "                NotImplementedError(\"This output function is not implemented.\")\n",
+    "            if output_scale is not None:\n",
+    "                net.append(utils.ConstScaleLayer(output_scale))\n",
+    "        self.net = nn.Sequential(*net)\n",
+    "\n",
+    "    def forward(self, x):\n",
+    "        return self.net(x)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b7aea5cf-5a85-42c9-b651-b812ba2cce8c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b5361b09-e727-47b4-aa66-4a395a4bfded",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2932982-1934-4117-b173-d5cef253876b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d988caf8-b52d-4841-aa69-5a61ee450bb5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "83f7a46f-1989-49f9-a595-2849d427d824",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "0253319c-408f-4d3e-a9ed-3a14c13c651f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "from astropy.io import fits\n",
+    "\n",
+    "import os\n",
+    "\n",
+    "from astropy.table import Table\n",
+    "from scipy.spatial import KDTree\n",
+    "\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "72c3ff70-7ca2-47dd-b9b0-a5af920acf66",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "from torch.utils.data import DataLoader, dataset, TensorDataset\n",
+    "from torch import nn, optim\n",
+    "from torch.optim import lr_scheduler"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "21ad90ff-859a-48db-a271-2028bf169f23",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "import flowtorch.bijectors as bij\n",
+    "import flowtorch.distributions as dist"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "3b99bde3-f446-4341-8955-3ad59716e6e4",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import normflows as nf\n",
+    "from tqdm import tqdm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "71bc3429-efae-4270-93a7-b7ab958d0ff9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a21e3d46-5f0d-4ba8-96c1-f5fae4080a7a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class Conditinoal_Encoder(nn.Module):\n",
+    "    \"\"\"Convolutional dense encoder for conditioning the generative model.\n",
+    "    See Fig. 4 of paper: https://arxiv.org/abs/2006.04731\n",
+    "\n",
+    "    :param in_features: Number of input features\n",
+    "    :param enc_block_layers: list of the number of dense layers in each desired dense block\n",
+    "    :param init_features: Number of channels after te first convolution, defaults to 48\n",
+    "    :param output_features: Number of output channel features (will be twice this value\n",
+    "        since final value will be turned into mu and stds for latent variables), defaults to 8\n",
+    "    :type output_features: int, optional\n",
+    "    :param cond_features: Number of conditional feature channels, defaults to 8\n",
+    "    :type cond_features: int, optional\n",
+    "    :param cglow_upscale: The factor to upscale the features from the dense encode \n",
+    "        before passing them to the generative model, defaults to 1\n",
+    "    :type cglow_upscale: int, optional\n",
+    "    :param bn_size: number of features after bottleneck if enabled, defaults to 8\n",
+    "    :type bn_size: int, optional\n",
+    "    :param drop_rate: Dropout rate, defaults to 0.\n",
+    "    :type drop_rate: float, optional\n",
+    "    \"\"\"\n",
+    "    def __init__(self, init_features, \n",
+    "                enc_block_layers, \n",
+    "                hidden_features,\n",
+    "                output_dim=8, \n",
+    "                drop_rate=0\n",
+    "                ):\n",
+    "        \"\"\"Constructor method\"\"\" \n",
+    "        super(Conditinoal_Encoder, self).__init__()\n",
+    "        # First encoding module\n",
+    "\n",
+    "        self.encoding_blocks = []\n",
+    "\n",
+    "        # Construct dense block layers\n",
+    "        num_feat = init_features\n",
+    "        for i in range(enc_block_layers):\n",
+    "            block = nn.Sequential()\n",
+    "            block.add_module('encode_mlp{}'.format(i), self.mlp_block(num_feat, hidden_features[i], drop_rate=drop_rate))\n",
+    "            num_feat = hidden_features[i]\n",
+    "\n",
+    "            self.encoding_blocks.append(block)\n",
+    "            \n",
+    "        \n",
+    "        block.add_module('encode_mlp{}'.format(i+1),\n",
+    "            self.mlp_block(num_feat, 2*output_dim, drop_rate=drop_rate))\n",
+    "        \n",
+    "        # Convert lists to module lists\n",
+    "        self.encoding_blocks = nn.ModuleList(self.encoding_blocks)\n",
+    "        \n",
+    "    def mlp_block(self, in_features, out_features, drop_rate=0):\n",
+    "        \"\"\"Encoding transition convolution placed between dense blocks, halves feature map size\n",
+    "\n",
+    "        :param in_features: Number of input features\n",
+    "        :param output_features: Number of output features\n",
+    "        :param drop_rate: Dropout rate, defaults to 0.\n",
+    "        \n",
+    "        \n",
+    "            - encoder_trans: Transition PyTorch module\n",
+    "        :rtype: nn.Module\n",
+    "        \"\"\"\n",
+    "        block = nn.Sequential(nn.Linear(in_features, out_features))\n",
+    "        block.add_module('linear1', nn.Linear(in_features, out_features))\n",
+    "        block.add_module('relu1', nn.ReLU(inplace=False))\n",
+    "        if drop_rate > 0:\n",
+    "            block.add_module('dropout1', nn.Dropout(p=drop_rate))\n",
+    "\n",
+    "        return block\n",
+    "\n",
+    "    def forward(self, x):\n",
+    "        \"\"\"Encoder forward pass\n",
+    "\n",
+    "        :param x: [B, in_features, H, W] input feature tensor\n",
+    "        :type x: torch.Tensor\n",
+    "        :returns:\n",
+    "            - out: Final encoder output\n",
+    "            - c_out: List of conditional output states to conditional the generative model\n",
+    "        :rtype: (torch.Tensor, list)\n",
+    "        \"\"\"\n",
+    "\n",
+    "        c_out = []\n",
+    "        for i, block in enumerate(self.encoding_blocks):\n",
+    "            # Pass though dense block\n",
+    "            dense_out = block(x)\n",
+    "            c_out.append(dense_out)\n",
+    "            out = dense_out\n",
+    "        return out, c_out\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91e0a951-a242-49f7-af96-e7375e178fd6",
+   "metadata": {},
+   "source": [
+    "## EXAMPLE IN GITHUB"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "id": "51009aa6-185b-489a-a2ae-adb3465af16e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Define target\n",
+    "target = nf.distributions.target.ConditionalDiagGaussian()\n",
+    "context_size = 4\n",
+    "\n",
+    "# Plot target\n",
+    "grid_size = 100\n",
+    "xx, yy = torch.meshgrid(torch.linspace(-2, 2, grid_size), torch.linspace(-2, 2, grid_size), indexing='ij')\n",
+    "zz = torch.cat([xx.unsqueeze(2), yy.unsqueeze(2)], 2).view(-1, 2)\n",
+    "zz = zz.to(device)\n",
+    "context_plot = torch.cat([torch.tensor([0.3, 0.9]).to(device) + torch.zeros_like(zz), \n",
+    "                          0.6 * torch.ones_like(zz)], dim=-1)\n",
+    "logp = target.log_prob(zz, context_plot)\n",
+    "p_target = torch.exp(logp).view(*xx.shape).cpu().data.numpy()\n",
+    "\n",
+    "plt.figure(figsize=(10, 10))\n",
+    "plt.pcolormesh(xx, yy, p_target, shading='auto')\n",
+    "plt.gca().set_aspect('equal', 'box')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "b7b2bd93-75fc-4da3-8838-8e7db22ef05e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Define flows\n",
+    "K = 4\n",
+    "\n",
+    "latent_size = 2\n",
+    "hidden_units = 128\n",
+    "hidden_layers = 2\n",
+    "\n",
+    "flows = []\n",
+    "for i in range(K):\n",
+    "    flows += [nf.flows.AutoregressiveRationalQuadraticSpline(latent_size, hidden_layers, hidden_units, \n",
+    "                                                             num_context_channels=context_size)]\n",
+    "    flows += [nf.flows.LULinearPermute(latent_size)]\n",
+    "\n",
+    "# Set base distribution\n",
+    "q0 = nf.distributions.DiagGaussian(2, trainable=False)\n",
+    "    \n",
+    "# Construct flow model\n",
+    "model = nf.ConditionalNormalizingFlow(q0, flows, target)\n",
+    "\n",
+    "# Move model on GPU if available\n",
+    "model = model.to(device)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "id": "e4b3281a-e461-4824-8fa2-4af22bedd760",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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CMUQoL4O633uijxGD9+QV8n/0BvbWTgsjEwyG5rBDViZadiZadhZadiZk68ukplgdni6yk7yQ5OWGL1RMf6huH1JbOzS1IDU2IzU0IdU36a/9gQQELBgOzuomSr/7Ixq+9SCtT68HoHv1XMp/+ocU/PWvSTp+2doABYJxiBBIAoFAMEbovGMO9b/zKKrXra+IKGS/sJ2Mt/aas4cWjAqahC6ECvN7//JzIX3kVrKoKgSCEAggBYK9Q+ICAQiG9KFzqgKKCoqi21Irao+tsAayDew2vafqxp+953+XE83jAa8bze0Gr1sfvmezxY4pyYuW5IWigv5CqrNLF0p1jUhVtUhVNUi1DUhhMeTTSqSIQt6/biXp6CVq/+RzKBkpRHLSqfy775D1/MdkP7cNSTHhhy4Q3GbclnmQTOUi0iuIsSl+dZvOTxOz2TjmOTIqbybPkVF5s7mITOVvMpm3KmbenTjWHce4TecDGqu5ikxeZ6pNpukL99L28B3RdY66FvL/8XXjCddmz1kM4prnaIxPkNBA7wUqLekRQvlQkAsu19Ar6eyCllakjk5dWHR0QWcndHQhderr8Af6nIq45klSe47L5dSH9qWmQFoKWloqpKWipaXo/6em6KLPSEjdQFF0wVTdI5iqa5Gq6/oO1YuZQyZ29WM1x5KpuMA4P80Ic+NEMlOo+ZPP4Vs6I7rOc/Iqhf/zeRzNHT3lTeTdiVPchmWHUj7mdWaQi8hMnqQ4HlfMHElDwVROLHNtx8xlFKe6RysPkhBII0EIpP4IgTS8siAE0oB1x948EQVSJNVL7e8/hX9eWXRdyu5T5Pz0XWz+IVj2CoE0KmiyBPl5aGWTdFFUVgLJycYFfX5oakZqakFqbtGHpTW3QHMLUnD4lsvxFkhDrkqWICMdLScbLScTsrPQcvQ/0oZw0xGJIF2vRrpagXylHKn8OtJgxiJCIA2yfeRCQ9Og5XN30/j1zVGha2vuoOh//BLvmXIhkAYsKgTSAI2ba1oIpLGDEEgjbVYIpIHrFgJpNOsWAqkv/mlF1P7h00RuuNRFFHKe20batsND1w9CII0ITZKgMB9t2hS0yaVok4qMe4da25Bq65Bq6qGmDqm2Xjc1GMW4xopAupWb49JcTrSCPLSiArTiAv3/3BzdXW8wFEXvXbpSgXy1HOlqRa+AFAJpkO3mRYx/TinVf/ZFInkZ+vqIQt4/v0X6W3sGv26FQBp+eSGQBikuBNKYQQikkTYrBNLAdQuBNJp1C4HUS/uGxTR88wF9gj9ga+mk4O9f1XMbDQchkIaMlpaqC6Jpk9GmTQavd/Cd/QGk65VI5ZVQWY1UW6/PCwIDhwNzjAeBNGDTNhtaYY9oKilCnVIK2ZmDF1AUpGvXkS9cRjp7GammbtBLQggkc3VH0pKo+fMv4Vs8Lbou7d395P3ja8hhxVTdA28XAql/WSGQElW3EEiDIATSSJsVAmnguoVAGs26hUACzS7T8JX7aL9veXSd+9x1Cv7ulZFZ8gqBNCiaLKNNKUObOQ1t2hTIzR58544OpPJKfShYRSXUNw5+AywE0pDa1lJTUKeUok0tQ508CfJzBy/f0Yl84QrSuUvIF68idftMtT2kbUPZPgEEEuifhcbfeoCWHpc7AM/paxT9xS+wt9zijikE0vDLC4E0SHEhkMYMQiCNtFkhkAauWwik0az7dhdIkVQvtX/wNP45pdFN6e8fJPuXH47cYUoIpD5odpveSzR3Ntrs6eDxDLyjP4B05RrS5WtIV67pZgpDbmS0ou3PRBJIt27XkpPQJk9CnT4FdeZUyM4aeF9VRbpcjnziDPLJc8idXSNvWwikPrRvWEzdHz2N5tLvj+yN7RT9xc/xnLtuuu7e7UIg9S8rBFKi6hYCaRCEQBpps0IgDVy3EEijWfftLJBChVlU/+BZwvn6sCMpHCH3J++StuO4OSEiBBKa04E2Yxra3FloM6cNPJdIUaGyCvnyNaTLV6G6BsnoRm/QBs3FG4uJLJD6rcrKRJ01DXXmNLRpZQO/bz1iyXb8NPLJc0hdA/SyCoE0rLoD04uo+quvRuclSaEI+f/vZdI+PGy6bn27EEj9ywqBlKi6hUAaBCGQRtqsEEgD1y0E0mjWfbsKJN/cMmr+6BnUZL03w9bSQeHfvoTncs3Q2h5pXEOILRZjWSBpEmiTy9CWLkKbOxMcA3zfB4JI5y8hnT2v9xQFg+YajTY+OtUMxO0kkKKoPXOYJk9CnT0Ndf5syBmgd+mGWDp6CvnY6d73UwikYdcdSfNS/T++gn/h1Oi6rF9s0/MlCYE0/PJCIA1SXAikMcMNgXS37fFBBZIhBjefpkRQPG/2DZuO482+YfnBt5sSQEZtG+XxiOMNt2HcskFs8RR+sdym4ikkTF5HVuYqitl2jHY71i2g/rcf1pN3As7yOgr/9kUcN437j1m30cfe5PeCZiSw4tj2SNDS09AWLUBbPB/S0/vv4PPBBV0UcbUcSek/CV2y8lfPxE+uZDbPZ0whYdB2AoWGBmiF+agL5qAumDOwWAqF9CF4B44iXbs++Mckng55Rjeu8WzbaEjuUIY82m3U/+6jffKvpX50hIK/fRkpMoB5ww3UGNvAnJAwu32Az/uQy5oRUEai0YyAMjJIiaeAMjyukbcdUzyZqDuihflUed20QLKPuKRAIBAIBkUDWp68i5Yn74qu8x67RMGPXkcODD8/zu2MZrejzZ6JtmQhTCnrv4PPB2fP66Ko/DqS2RsGgaVIgFRTh1xTh/bBdrSCPNSFc/uKJacTdfli1OWLob4R28GjyIdPDDwETzAgUkQh7x9fx1nVRMNvPwiyTMfGpUSy0yj6i+ewdfmtDlEgsAzRgzQQogepP6IHafhlRQ/SANtujx4kzSZT/+1H6Fy3ILou7cND5Dy3bcB5L6IHaWC0zAy05UvQFi8Ej7vvRlWFK1eRjp3Ue4xiPTm+BdGDNNA2g7bHwFA1DdCKClBXLEZdsqD/NaEoSGcuYNt3COniVf2jI3qQhrS9Y918av/b56PmDc7yekp+8FMc9a39y4oepGGXFT1IAxUd2z1IQiANhBBI/RECafhlhUAaYNvEF0iKx0nt95/GP3+KvkLVyH7+I9LfPzCo1hECqRdNAqZOQV25DKZN7f85aG5BOnYCTpxCMnI3GwQhkAbaZtD2GBBIfVY5HKjzZ6OuXII2tax/mboGbHsOIB86gRQKj2rbUSaQQALwz55E1V99DSUjGQB7UzvF/+2nuK/W9t1RCKRhlxUCaaCiQiAlFCGQYjUtBNKwyhptFwJpYG5jgRRJS6Lmvz1LcHKBXmUwTP4/v07y4Ysjr/s2EUia2422eAHa8iWQdUuC0XAE6cxZpCMn4HolEj1CaoQIgTTQNoO2x5hA6rM5KwNlxRLU5YsgNaXvRp8f+cBRbHsOIrW0jW7bE0wgAYQKMqn64TcIleg5q+QuP0V/9guSTlzp3UkIpGGXFQJpoKJCICUUIZBiNS0E0rDKGm0XAmlgblOBFM5KpfpPv0i4UE9GKnf4KPzbF/FcqjJX9wQXSFp6GtqaVWiLFoDzlu/stnakQ0eQjp5A8vWdDyEE0ii3PY4FUnQIniyjzZuFsnZl/14lVdWH3+06oDsajkbbE1AgAUSSPVT98BsEevK1SaEIhX/9PCm7T+s7CIE07LJCIA1UVAikhCIEUqymhUAaVlmj7UIgDcxtKJBChZlU/+kXieSkA/rQlKK/fh5nbbPpuieqQNIyM9DWrUZbOK//5/TyVeSDR+Di5UFvIoVAGuW2J4BA6tNcUT7q2pWoi+f3s4CXyiuxbduBdP4yshBI/VE1VLeT6j/7It13zIm2V/B/XiLtoyNCII2grBBIAxUVAimhDEkgjVUBBKZuOEzlMoqjANKLx6g/1s36kNo2IfziKCQMrwUzx20mbgxuyG0mz1mM7Voc64ahzxMasKzhZ2Dg1cGSXGr+27Mo6fq4fUdtM4X/+zc4mjtuqjt21eZyFZmse/SnEUUZ6P3QcrJhzR0wd3bfz24wCCdOw+EjSM0t8QsqzpjKY2SEUdUGbZsShkZ1G93LmBFnZoSI14O6cgnKHcshve/NknS9GttHO5DOXRr8YxAjbkmJ981+jLYNy5oQUDf1yNV9/wnaNy+Pbsr70RtkvLnXoG4TeZDiKvxM1h0jNlM5lIzaNhm3KQFlUlRaIaCEzbdAIBBYTGBqITV//PloAlhnRT2F/98L2DuE1fCtaPl5sHY1zJ7Zd4M/AAcPw8HDSIGANcEJJixStw/b9j3IOz7TTR3uWYdWkAeANqmIyDe+gFRZje2jnUhnL8bzecG4Q1JV8v/fq0j+EG1b1gBQ/18eQ3U5yHpph7XBCQRxRggkgUAgGAG+OaXU/sEzaG4nAK5LVRT+7UvYfOIm/2a0rEzYcBfMukUYdfvgwEE4dBQpJPJCCeKLpKrYTpxBPnkGbe4slI13oRXmA6CVFBH5+rNIVTXYPtwhhNJNSJpG3o/fwuYP0vz5DQA0/vZDqF4X2T/fJs6TYMIiBJJAIBAMk+6FU6n7vafQnPpXqOfMNQr+7hXk4OB2wrcbWkoy2l3rYNGCvkPpOrtg3wE4ehwpLM6XILFIGkinzyOdOY82Z6YulIp010mtuFAXSlcrsL3zEfL1KoujHRtIQM5/foDsC9L4jfsBaP7SRlS3k9x/fVuIJMGERAgkgUAgGAbdi6dT+1+fAIf+9ek9cpH8f34dOTz0RKUTGc3lQluzClYu7zs5vrMT9uyDYyeGldRVIIgHkgbSmQtIp8+jzZ2JsnE9WnGPUJpSSuS/fBPpxBns732M1DR+58SNJlkvforkD9Lw3S0AtD51F8gSuT/eKkSSYMIhBJJAIBAMke4FU/qIo+T9Z8j7l7eQjCaT3gZoNhssX4K2dg14Pb0bAgH47IA+x0j0GAnGGBI9QunMBbS5s4g8eC/k6lb92sK5hOfNQt53WJ+j1CXmFma+9RmyP0TdHzwJskzrE3cCErk/fkuIJMGEQggkgUAgGAK+OWXU/f5TveLos9Pk/WuPOBrFhKnjDQ1g1gy0TfdCelrvhkgEDh+FPZ8h+cW8LMHYRhdK53Gcu4i6YjHKprshNRlsNt0ufNlCbNv3Iu/ad9sL/fT3D4KmUfeHT/WIpHVIikLOv70jRJJgwiAEkkAgEBjgn1lC7R88jdaTyDTpwNlecXQbo2Wko923CaZPvWmlBidPI+3YDR0dgxcWCMYgkqpi238E+egplPWrUe+6A1wucLtRHrgHZdVS7G++h3zmgtWhWkr6B4eQVI3aP34aZJmWp9cjBcLk/GKb1aEJBKPCxBVIkmych8ZM3YMxVvMcgal8QZJRwlUzx202Sa2pBLgmkrmafa8NjytGPiHDsrE3mzlnZnIZmY7bKDYTyXUHy1UUmFJIzR9/LupW5z16kbx/3wqyFG0vnrmITCXHHUr5WAxW1GaDVSvhjlV95xlduwbbP4WGRjRAc9x+z5MlMxlswTjXUcy2jfKhjLys0UWuyUY5mGJd5Ea5Vgx+f0wluhxkuxrBtn0X8oGjqBvvRF2+RM8vl5muGzmcPo/9zfeR2tpHFhdDyKMUI3GVYW4bKfY5i5lbaogPftI+OYrmtFP3/ScBaP7yRuRwhKwXtpuue8TlzeQhMzqnMfILGn7uDZKQabHmZRr9bhrEbXTvGPNaMvn7gxpjBxM5koAY9+Kjc+8/cQWSQCAQmCRYmk/tH30ezeMCwHPyCvk/fgPJKJnhRKasDDZvhMzM3nUdnfDxx3DhomVhCQTxQOrswvb6e8h7DqI8ch/ajCkAaPNmEZ4xBdu2Hci79xsns52gpL9/ENVpjxo3NH7jfqRgiMzX91gbmEBgEiGQBAKBYACCxTl6EtgkNwDus+Xk/+g1pMht6sCWnAz3bIA5s3vXqSocOgx79oLIZSSYwEgNTdh++jzawrkoj2yGlGRwOlEe3oS6dAG2195Brrg9bcEz3/oMzeWg8VsPAtDwO48ihSJkvLPf4sgEgpEjBJJAIBDcQjg3ndo/fhY1xQuA+8J1Cv7+FeRwxOLILGL+fLj3HnC7etdVVsG2bdDYZF1cAkECkQDpxBmkC5dR79uAumqZPtS2MJ/I976J/NkhbO99jBQIWh1qwsl6eSea00HTVzYBUP97T2DrDpD66XFrAxMIRogQSAKBQHATkbRkav74WZT0ZABcV6op+H8vIYduQ+eq5GS4/z6YdpMJg88H23fAqVOWhSUQWIkUCGJ7833kQ8dRnngomj9JXb0cdfZ07C++iXyl3NogLSDr+Y9R3Q5anrkbgJo/fgZbh4+kI2LorWD8IQSSQCAQ9KC6ndT+wTNEcjMAcFQ1UPB/X0QOhG4/K+95c2HjveBx9647dQo+2Q7Ctts0stuL3ZuKzeVFdnmQnW5sTg+yy43s9GBzupGdbpBtSLINSZaRZBvIcu9rJDQ1gqYoaKqCptx4HQFFQQ0HUYJ+1KAPJeBHDfhQg36UgA816CPi6wL1Nh0yOgrIldVIP/oP1DUrUO7bAC4nZKQT+c5XkXfvx/bux7eVJbgE5Pz0fdQkD20PrQKHnar/8WUm/eG/47lQaXV4AsGwEAJJIBAIAM0mU/e9xwmV5QNgb2qn8G9fxNZ9m4mBpCS4bxPMnNG7rqsL3v8ALl+xLq5xhmSz40jLxpGSgT0precvFXtSGjZvKrLdYVzJkHAZ7zIImqah+DqJdLUT6Wwl0tWO0tVGpKuNSGcbir9rlGKcuEiqim33fuTT54g8swVt2mQA1HWrUGdOxf6bN5Arqy2OMnFIQN6PXieSlkTXuvloHhdVf/11Sv/LP+OsabY6PIFgyEiaZsYTcezR0dFBWload9ufxC6N7AdIMrRvFjbf/esWNt/Db1vYfPfDIptvDWj47YfoXLdQD6PbT9H/fK7vD3qs8hPF5nvObNi0Ebye3nWnz8BHH0Ng+ELRrOP1uECScCRn4EjLwZmegzMtG2d6DvbkDKRR6HXUlIjeO6Sq0PO/piqgqmjovwuSza73MtnsSDZbT++SeZSAj3BrA6HWBsItDYRa6gm3Nw/c62RkaR1rs1FZI4O4GOUNc5UZWowPvulW5zpNkvTepAfv7bW/VxTkT3Zj+2hnv/0Nbb5j2pcbnBQjF3AzNt9GbWsaqsNO5f/+Jv6F+vBcR1Ujpf/1x9hbDUS3UY+mmffT8JwZH9eItoFh3DFtvg3rNhE3Q7CMN1F3zOM2sPnWRmgJH9HCfBp5lfb2dlJTU0dUB9ymAsmUAILYN8YmfxBjiiCzN9wxysdVABltN2rbVN1G58Rge6zyRnEZtm1CiJi8FmLeNBsIIDMix7CswWGZEmcxirY8didtj67VqwhHyP+/L+C51NeRKuY5MytSYgqk2EUNryPD8oDTibT5PqRZs3rLdXejffQhXLo0eFmj7wUTWCmuYt3My04P7qxC3FlFuLOKcGbkIduG/jBOjYSI+DqIdHfo/we69GFvoQBqKIAauvHajxq+ZbL/UNPmSBKSbEd2uJBdHmw9f7LTEx3SZ3MnYU9KxZGUhs2dNOT4NVUh3N5MsKWeYGMVgcZKIp2txnmUzORgMrhRMiW+DEVKjLKD3FhqOVkoT29BKynqXVlVg/2lt5DqGw3LR4kRm/E5G/lNsynhBtCTBkFJclPx99+J9sq7z1Yw6Y9/ghyMMezQKIWCUe6cWOUNc30ZHZcJEWPiGo8pnoZU98ivBVPiyaBuY7E7MgElBNIgCIEUq3IhkPqXFQKpH7eZQOq4axFNX3tAX1A1cv/1DZKPXBig/AQVSAX5SA8/gpSe3lvm3Dm0Tz4Gvz922dtAINmT03FnFeuCKLsIZ0qWYXk1EibU0US4o4lQRzMRXzvh7nYivg7UgG/kgY08r2hP+YF3kOxOHN5U7MnpOJLTsSel4UjNwpmeg82TbBiW4u8i0FBFsLGSQEMl4bbG/m3dRgIJ9N5s9a61qPfe2fsbF44gv70Nef8R3RFvggskgHBOGhX/+LtEstMASN57mqK/+tXgPXtCIPUvKgTSIJuFQBoWQiDFqlwIpP5lhUDqx20kkHwLp1L3X5+Knq+sFz4m7aNDg5SfgAJp2TKku+6Kfv61QADtw21wob9AHJAJKJAkuwNvdine/Ml48spwJKXH3D/c1UawrZ5QRxOh9kZCHY1EutoZ9M56hMNGYPAqbzBSgRSrrOz24kzPxZmWizMjB2d6Lo60rJjD+NRQgED9dfw1V/DXXEXxdd52AgkAFbSiAiLPPAr5ub3lTpzB9urbyEZmJxNAIAEEphRw/f99O5pTLv3NveT9+K2Bv/aEQOpfVAikQTYLgTQshECKVbkQSP3LCoHUj9tEIIWKc6j+719BczsBSNt2gKyXtscoP4EEksuFdP/9SDN6jRi0mmq0t9+Gjg6DBm9igggkZ1oO3rzJePMm484qGvTmX1MVgq31BJqrCTRXE2yuQQl2D6+xcSaQBmxbtuHKzMedW4wrtwR3djGyc3CziFBrA/7qK/irrxJsrO534zORBRKAZrehPnAv6tqVvdsam7A/9zJyXcPg5SeIQALoXjKdyv/1NbDrn628H71Bxtv7hlS2b9tCIA2/biGQRoIQSAPvEHu7EEjDqttwuxBIAyIE0gDlR0kgKSleqv/8q0Ry0gFIOnSO3H97M+aN1oQRSLm5SI8+ipSR0bvPwQNou3cb/5DeyjgWSK6MApKLZ5FcNAO7d+AfUU2J4G+uJtBQoQuiljrdQtsME0Eg9Sss4UzLxp1TogumvJJB5zWpoQD+mmv4rl/AX3UZTYlMeIEUXZw3C+WpR3qt80MhbK+8je3YIDnFJpBAAmjbuJS6P3q6Zx+Fkv/2U5KO3+KMKQRS/6JCIA2yOb4CSdh8CwSC2wrNJlP/3cej4sh5rZac/3jb+AZxIrBgAdK99yLZ9a9+ze9He+89uHp72Hc703NJLppFcvHMQYfOhbva8NVfxV93DX9jJZpy++SxGTGaRri1gXBrA50XjwDgzMzHUzgVT9EUnFmFUUc/2ekmqWw2SWWzUcNBfJWX8F07S6DmmvHN7zhHPn0eqaaeyJefgsJ8cDpRvvAE2uRJ2N76AMnoRnick/7REUKTcml5Zj3YbFT/2Rcp+91/wlnXYnVoAkE/RA/SwDvE3i56kIZVt+F20YM0IKIHaYDyo9CD1Pjl++jcsAQAW2snRX/5c+xtXYbX+LjuQZJlpI0bkRYu7F1fW4v21lvQOYwhdbcyDnqQHMmZpEyaQ1LxLJzJGf22a6qCr6ECX91VfPXXiHS3xVcsT8QeJGL3aMguD578KXiKpuAunILN5em3jxLw4as4j+/aWYINtyQVnSA9SNEq7XaULfejrVjcW9f1auy/ehmptb13xwnWgwT657rqr75K98rZADiv1VH6ez/G5gsaltUrED1Iw69b9CCNBCGQBt4h9nYhkIZVt+F2IZAGRAikAcqbFEg3O9ZJ4QgFP/wV7mu1+g4TVSB5PUhbtiCVlPSuO3IEbccO/QffzFfWWBVIkkxS4XTSpizCkzOpf92qir+xgq6q83TXXOpnpy0E0kjaNrpJu7GjhDtvEt6y2XgnzcLmcvfbNdLVTtel43RdOoEa6J5wAim6edlClMceBEfPYJ6ubuzPvYR87bq+PAEFEpqG4nVT8aPfJVSaB/Q42/3lr/RjEgKpf1EhkAbZLATSsLghkDY4nxo8UawZAWSEUcJVM8leTSaKjSmC4imAILYIiqfQMCu+Yp1zoxtqo/crnglXzdRtViDFutk3EZfe9siFhn9GMbV/+Gx0knD2f75Dyr7TvXUbth2r3REYJfQpH2OboXCLsTErG3nLY0hp6fq+kTDah9vQLpwbemyxMPFAKB5zjOzeNNJKF5A6aT52l7dve5qKv6mKzprzdNVeQg0ZWJjHwJSAMvGTa17ExNhoeLNiom4Y+LhlG978ySSXzsFTNA3Z3vc3W1MUuisv0HXxKMHGqv7lb7Qd64beKG4TiUfNiCu9bRWtMJ/IF56ErEx9ZUTB9sY7yEdOGByX0c28gTCMdeMbz7p7zneoMIvyH/0uaor+Oc3+5Udk//oT00lPTYkYQ3EWo7xZEWNCSMRVQJlNMmtGYoxQQEW0MNtDr4g5SAKBQGBEJCOFhu88FhVHqR8d6iOOJiSTpyA/+DCSU3fp07q6ULe+AfV1Fgc2ykgSSXlTSStbSFLu5H6bQ53NtFecpLP6HErQRA4iweijKvhqLuOvuqzbqxdPJ6lsDp6CKUiShGSzkVw2h+SyOYTaGui8eIzua2fQIiGrIx81pJo67P/8U5TPP4E2YyrYbShPPYqWk43tvU+Me4rGKc6aZop++ILubGeTafryRlxXa0nZO8G/lwXjBtGDNBCiB2nYdYsepP6IHqTh1x2PHiTNbqPmv32R4JRCANznysn/h5f6PTmeSD1I0tJlSHeuj06M1+rrUN96A7q7hh9bLCzsQZJkO6mT5pE+dRnOWwwXNFWhq/YS7eUn8DdXDlyBmbZFD9Lw6obYPTG3PAi2J6WSPG0RKVMXYnP37QlUw0G6rpyi49xBFJ8+f2489yBFd5Ul1Ic2o65e0bv99Hnsv3kdKTyAUcg470G6QfNTd9L4TX3Ys+wLUvrdH+GqbDQRm+hBGnbbogdpQIRAGgghkIZdtxBI/RECafh1x0MgNT27kY57lwFgb2qj8K+fw9bVf3jVhBBIkoR09z3Ii3onf6sXzqN9+D5EBranHm8CSXa4SCtbTPqUJf2G0YW722mvOEFH5em49hYJgTTMumFYAimKbCNp0kxSpi/GnVPctzpVofvaGdrP7kdpbY7RbuywxopAuoGyahnqw/dFf/ek69XYf/4CUtct+bYmiEDSgJoffJ7O9QsBcF2tpfR7/4QcGsROXwik/kWFQOqDGGInEAgEBnQtnRkVR1I4Qu6/vD6gOJoQ2B3IDz2MNGVqdJW6by/a/s8sDGr0sLuTSZ+6jLTSBch2Z59t3Q3XaLt6FF/DNYuiE8QFVaG7/Cy+a2dwZOSSMn0JSZPnINudSLKN5KkLSJoyH//1C7Sf2ke4ZfwPH7XtP4zU3ILyhafA7UKbVET4u9/A8bNfIzXGEILjFAko+LtXCZblESrLJzilgIbvPEL+P75udWiC2xzRgzQQogdp2HWLHqT+iB6k4dc9mj1I4Zx0qv/ia6he3SUr61cfkLrr+OB1j+ceJJcL+bEnkAqL9HWKgvbhB2jnzsaueyixxSIBPUh2TyqZM+8gtXgOktz7edY0la7qC7RePkSwo2HEcYwE0YM0zLphZD1I0bp7y8ouDykzlpIyc2k/u3B/zVU6Tn1GsP6mYZXjrAcpWjQ/l8hXn4X0nifg3T7sv3gRubzSMC5g3PQg3SBYmkv5j76L5tYffhT+z+dJ3XVyBLGJHqRhty16kAZECKSBEAJp2HULgdQfIZCGX/doCSTNJlPzgy9F5x0lHThLzk+3xtQK41YgJSchP/4UUk6OvhwIoG59E6oqjeseSmyxiKNAkp0eMqevJK1sEbKtd7CDqoTpuH6a1iuHifjaR9y+GYRAGmbdMGoCKbrO7iRl+iJSZq/A7knusy1QV0Hbke2EmuvGrUACIDmZyNefRSvM15dDYey/fAn5wpUJJ5AA2jYvo+77TwIgd/sp+84/4qy9JYmsEEj9iwqB1AchkAYhKpBcT2OXnMYFBsKEWDAlgCD2DbkZAQTm8jeZEUBG5U3mC4rZttn3I0ZsZm/2DXMVxarfTJ4jiCmgjESIsYAa+XVmtu0bYqDlqQ103LscAHt9C4U/fA4pNMBE55vrNrrXj3XOzAggg/Ixz0lqGvYtTyKlZ+j7dncT2foqNMWY5DyMtk0LvxEgyXYyJi8hc8oKbA5XdL0SDtBWcZzWiqMoJiy6h0QcfxXjmqvIiBjljYRCXMWZ0Q13rLhlG8mlc0mbswpHcnqfbV3lZ2k7sZNI9+DJkI1ETszzYpRjyeicDqFtzeVE+cKTaNN7hs5GFGwvvYF84mzssiZuig2FX5xyLGlA7R8+RccGfQ6l+2IVk77/r8jhmwSAmZt9s0LCTI4lM22byKEEJgWUSQEUU0CZPK7BiGghtgdfFnOQBAKB4GZ8C6ZFxRHhCDn/8RZyIGTc+zTeyMzWxVGy/vRc62gn8uYr0N5mbVwjRZJIK55H9vTV2N29PQKqEqa1/CgtVw+hRoIxKhDcjmiqQteVE3RdPUnSpNmkz1+DI0XPKZRcNoekkhl0XDxK++nP+iUEHg9IwRC2515CeeYxtPmzdRvwzz8ODify4eNWhzeqSEDej97AP7OEcFE2gRnFNH79fvL+/R2rQxPchgiBJBAIJgyRjBSavvJAdDnz1e24KhM7PyURSHn52B59Asmtz8HQWpp1cTSAjfd4ICl3Kjmz1uFKzoqu0zSV9qrTNF/aRyQ4Po9LkEA0je6Ks3RXnidl6iLS56/B5vIi2eykzV5B8pT5tJ/ZR8fFo6AaPFEfY0iKgu3F11CCD6EtWwSyjPL0I2geF7bdB6wOb1Sx+UMU/fVvqPiH30Fz2ml9fC3eE1dI2X/OuLBAMIoYjD8SCASC8YEmQePXH0JN1kWD99gFUnYcsziq0UcqKsb22NNRcaTW1xJ57cVxKY4cnlSKlm2heNmWPuKos+4S5bufo/70R0IcCYaHqtJ56ShVb/87bWf2oUb0obU2l4fMJRsoevAbeAqnWBzk8JFUDdvrbyPv2R9dpz68GWXDOgujig/uKzXk/qS316j2D54kkpliYUSC2xEhkAQCwYSg455lBGdMAsDW3E7WL983mvoz7pCKS7A98gSSU59fqVZWoLzxMgTGmXW5JJM5dQVld36V5NxeW3JfSzUVn71AzdGthLpbYlQgEMRGC4doO7mL6nf+g66rp7gx3dqRkkHe+qfIWfMotlvMHcY6kgbyux8hf7Qjuk69726Ue++0Lqg4kf72fpL3nAZATU2i9veeiOfUQIGgH2KInUAgGPeE8jNpfeyu6HL2L97F5ht/8w1iIRUVY3v4cSSH7s6pXruK8t5b4264kCezmLx59/bpMQoHOmk8u4POuosWRiaYiCi+Tpr2v0fH+cNkLNmAJ78UgKTSWXgKJtN6bAddl46bc9tKIBJg274bgiHUhzYBoG5aD5KE/NHOCfNQSAIK/uF1rs6ehJKVSvfKWbTfv5z09w5aHZrgNkH0IAkEgnGNJks0fe1BcOjPe1I+OYznYqVBqfGFlF/QVxxdvayLIyN3ojGEzekhf8F9TFr1TFQcaZpKy7UjlO/6hRBHgrgSamugfvuLNH72NkrAB4DsdJG1cjP5m7+IIz3H4giHh23XfuS3t0WX1Y13oU6wniRbp4+Cf3gtutzwWw8Rys+0MCLB7YQQSAKBYFzTvnklocl6viN7XTMZb+y0OKJRJidXN2S4Mazu2lWU97aOK3GUWjyPyXd9nbTiudF1/tYaKvY8T+O5HaiRkIXRCW4nusvPUv3Of9B5pTcJqSuniIIHv0b64vVI9kHyJ45BbLsPIL/1QXRZ3bQeZd0qCyMafZIPXiDtfb3XSPW6qP2jpyaeI6lgTHJ7DrEzmRQ1Zq4jk7lvYuZYMpPnyKDuuOY5gti5jmSTxxXrnJrMsWQqF5HJZK4xyxtUbdh2jHNqKs+RwXbjumNu7vd+hYpyaHt4rb6gqmT96j3QFFR7/3aGmkNp8NhGngdpuMcVXZ2ZhX3LU0guN6DPOQp/uBVkrfc9NN12jLIm70NsriQKZm8kJad3npESDtBweTdt1af0Fc6RNWImNtP5hGJhcqiWFDMpVp89kZDQ6M0zYpRwNWYeJMOL2ChnT+zisXMZmWoaKcazgoHiUpQgTYc/oKviDFlLN+FMy0KSZdLmrcJbNovGA+8SbKzqKR/jN9koX5DRhWa0PVb9PWXlA4fBbkN9cCMA6sObIBLGduCIQduxkrcbvJmKwT1SjNw3N1+vA5Yd4Mct96fv4Vs8jXB+Jv75U2h5Yh1Zr++JHeNIGGHeHcA4yazRPZSZB16Gudtjtx0zT5LRvYRBnqRY98uGSWaNfrvMvF9D4PYUSAKBYNyj2WSavvog2PUv/9QPD+Iqr7U4qlEkLQP7o08heXrc6mqqCL//5rjpOUrOmUbBnI3Ynd7ourbaszRc3IkSHmemEnHCbU/BbU/GafPitHlx9fw5bV6cdi9OmwdZsiNLtj5/kmRD7lEVmqaiaBFUNdLv/7AaIBjp7v0Ld0VfhyLdqNr4uJbiRaCxkuptPyd99krS59yBZLPjSE6nYMOztJ/bT+vpPcaJMscA8t4D4HKi3qvPw1QffQApGEI+fsriyEYHmz9Ewd+9yvX//U2QZZq+upnkwxdxXZ94KRwEYwchkAQCwbik/YHVhItzAXBUN5L+7l6LIxpFUlJxPPoUkjcJ0K28w+++AZGIxYEZI9sc5M3cQHrRvOi6SMhH7bmP6Gq8YmFk1uCQ3SQ5M0hyZJDkzCTJkYHXmUGSIx2bbH44lyTJ2CUnyM5hl/WHO+kOttAdbO75v4XuUDOhiM90XOMGVaHtzGd0XT9Hzor7ceeUIEkS6XPuwJM/mabP3ibcMfYdFaXtu5GcDrQ7V4MsoTz1KITDyGfOWx3aqOA9XU7mG3tpeWIdmsNOzR89Tdnv/ytS5PYW+YL4IQSSQCAYd4SKc2nf3DPWXlHIeu49pIhiPJxsPOD24HjkCaQUPe+H2tRA+J3XITz25+m4U/Mpmv8gTm96dF1nw2Vqz310W/Qa2WUnac480tz5pLsLSHPn47aP3EpaUcN6b5CmoGoKWs//qqqgoqBpGjbZjizZsUn2Pq9l2fjn3eNIweNIITu5tM/6sBKgO9hCu7+WNl8tbb4aguGOER/HeCDS2Urt9hdIm7WCjHnrkGw2XJn5FNz3FVoOf0LX1ZPGlViIBMgfbEd1OtFWLQObjPL5x+Fnv0a+VmF1eKNC9i8/omvZDEKleQSnFdH85J1kv/ip1WEJJihCIAkEgnGFJkk0f2FzdH5Z2vv7cVXWWxzVKOFwYH/oMaR03alJa2km/ParEAxYHJgxWWUryJm6GqlnTqESCVJ/YQfttWcsjix+JDkyyPKUkOYuIN2dT5IjE8loPiagagq+cBvdoVb8kQ5CER9BxUdI8RGK3Pi/G0W7pcfQaEpLn9FgEg6bG5c9qecvGZctqXfZkUKSMwOn3dOvHofNTbq3kHRvIaU9buyBcCdtvhrafTW0+WroCDSgTbQheppG+7kD+OvKyVn1EM60bGS7k+xV9+MpKKPp4AdoY/hBhQTIb3+A6nCgLV0IdjvKl59B+rdfINWP/+FocjhC4f99mfJ/+B2w2Wj+/N2k7jqJs6bZ6tAEExAhkAQCwbiic/0SQmUFADhqm0jbtt+gxDhBkrBvehA5Tz82rauT8NuvgX9s97zIdhdF8x4gOWdKdJ2vrYaa0+8RDkysXge77CTLM4lsbxk53jI8jtSY+4eVAB3BBrpCLfjCrXSHWukOt+IPt6MNonZGz0BCI6z4CSt+uoJNN1b1w2nzkOTKItmZSZIrUx8G6MrC4+x7bG5HCvlpM8lPmwnovVstXddp7LpKU+c1gsGJ816HWuup+fA5MhdvIHXaYgCSSmfjzCqgce9WQs1jd66jpIH8xruoSV60WdPB4yby9Wex/8t/IrWP//fIfbmGzDf30vLEnWhOB3Xf3ULJ/+9nEyb/k2DsIASSQCAYN0QyUmh7ZF10OfPX2ybMGHTb2ruRy3S3Ny0YIPL2a9DVaehSZyWupCyKFz2K05sB6IYBTdcO0HR1P2iqsbvlOCDVlRsVROnuwqg5wq2omkJHsJH2QC1tgTraA3V0h8f+3JWQ4ifkq6Ktu6rPeofNTZqngDRvAemeQtI8BdhtvfOcbLKDnNSp5KTq12xXoImmjqs0dV6lrbvG0K1srKMpEZoPf0igtoKslfdhc7p1A4d7v0Dz4Q/pujJ2h9xJqort16+i/NaX0UqKIC2VyNeexf5vP0cKjP8E2tm/+piOtfOJ5GXgWzyNjg2LSdt+zOqwBBMMIZAEAsG4QANaPrcRza3fpCXvOo77SrW1QY0S8oLF2BboT6o1RSHy3ltoLWN72EhK7gwK525GtuvvRyTkp/rUO/harlscmXmSHJkUpsyiIHkWSc70AfdRtQgt/mqafOW0+mvoCDXornAmbb7HCmElQFPXNZq6rukrNEh2ZfUMvSsiK7kUl6N3flWyO5tkdzZluSsIK0GaOq5Q23qWlq6KQXvLxgO+ygsEm2vJWfMw7pxiJJuN7JX348zIo/XQx2PW5U4Kh7H94gUi3/k6ZGdCfi7Ks09i+8ULMW24xwNyMEz+j9+i6q++CkDDbz1A0uEL2DtuI3MRQdyRNG2CfJv30NHRQVpaGhs8z+jOPgNhJs+RUXkzZSFmfhrDPEhGdcfaHs88RxA715GZPEcGbZvNRRTruOOa58igvGEuIjO5jOJYt3EOpcG3+RbPoOmbWwCQ27so+OF/Ivv7Pg2NVd4wuaCZPEiGeakG3yaXTsWx+dHo3JXQp++jXjo7pHZhCPmAjI5r2J08ErlT1pBTuiK6xt9ZT+XprYSDnSbrtg63LZnCpJkUeWeR5sobcJ+ucAuN/goa/eU0Byv7zxFiCEPkTPzimq07Zi4io5wiA2xOdeWSnTSZnOQppLsLBpx/FYx0U9t+jtq2c3QGBp4HM5K2h1reMD+TQS6jaHlJJnPRetJmLItuCzRU0rD3TdTAwDfmRsdlmEcp5nENrW4tMwPl21+DJN1uXzp4BPmt95FjlTc8J0Z5kmLFbVDW6Jb0prpr/uQZOu9cAEDqR0co+IfXY9dvlKvIKLZY50w1GMlg1Has4zZK7WB0zgy2x8yDZPjZNLqGYxy3UVwjvFYiWojt/pdob28nNTX2MOhYiB4kgUAw5lE9Llqeuje6nPHaJ/3E0XhEys7Fcc+D0RvLyJF9fcTRWMNmd1M89wGSM8ui69rqzlBz8RM0dexbkN+KTXJQmDST4qTZZLqK+93ga5pGU+A6db7LNAbK8UXaLYp0bNIRbKAj2MDVlgM4JQ/ZSaXkJE8hO3kyDpue3NhlT6IsaxllWcvoCjRR036OuvZzBMKdBrWPMTSVlmPbCbU2kLVsE7LNjju3hMJNX6FhzxuEWuqsjnBApJZWbL9+BeXrXwC7HW3FUrSmFtg9/udu5v7kPbqXTEdN9tCxcSlp24+RdPz2SyUgiA9xNcXdtWsXDz/8MIWFhUiSxJtvvhlz/x07diBJUr+/8+cnho+/QCAYGW2P3omapg/ncZ+6jOf4RYsjGgWSknHe9xiSQ8+Fo1w6R+TIZxYHNTiupGymLHs2Ko40VaX20naqz28bd+LIa09nTsZd3Fv8WyzM2kSWu6SPOGoN1nKm5VM+rv4JBxpeo6LrhBBHBoQVP7Ud5zlZ8x6fXvo3jlW9RX3HRdSbro1kdzYz8taxbvq3WDzpMTKTJlkY8cjoKj9N7fbfEPHpAs+elErBvV8gqXSOxZENjlRRifz6O9Fl9b57UWfPsDCi0cHe2knOLz6MLtd9dwuqQzz3F4wOcb2Suru7WbhwIV/72td44oknhlzuwoULfbrFcnJy4hGeQCAYB4SKc+laswgAKRgi49WPx7JvwdCQbTg3PoKUpIs+ta6a8K5tFgc1OEnpJZTMfwSb3QVAJNRN5Zl38bVXGZQcW+S4SylLWUyuZ3K/3qKucAvV3eeo7r6AL9JmTYATBE1TaOi8TEPnZRyym7zUGRSmziYjqRgASZLISZlCTsoUugJNXG86Qm3bOdQBhiyORUItddR89EtyVz/aMy/JTs7qh3GkZNJ2eo/V4Q2IfOI0WlYm2j136olkn96C9OOfITWN7bmORqR9cIj2DYsIzCklXJRN66OryXp1l9VhCSYAcRVI999/P/fff/+wy+Xm5pKenj76AQkEgnGFBrQ+fnd0XlTq+59hbx1nQ3MGwL52Q9TOW+1oJ7TtLeNx5haRkjOd4jn3RxOP+jvquH56K5Fg15h22LuBTXJQkjyXspRFJDsy+2xT1AjVvvNUdJ6gPTRBcmmNMcJqgKq2k1S3nMTjSKMgfTZF6fOjNuLJ7mzmFG9mWv46qlpOUNV8nGCk2+KojVEC3dRtf4GspRtJmbYIgPT5a7Anp9J04APdxXGMIW/fhZqThbZgLrhdRL74FPZ/+RlSKGx1aCNG0jTyfvwWFT/6Lthkmj93N2kfHcHePvavIcHYZkzmnV+8eDEFBQXcc889fPpp7CzJwWCQjo6OPn8CgWBi4F8wjeDMUgDsja2k7DpqcUTmsc2aj322PrFYC4cJf/gWBMdmrqOMwvmUzH0oKo46m65w7djLujga49gkB1NTl3NP0TeZl7mhjzjyRTo417qLj6t/wsnmD4U4ShD+cDtXG/ez59JPOVG5ldbuXhdKp93LlNw7WDvzt5hbfD9eZ4aFkQ4RVaX50DZajm7nht9V8uT55K7dgmQbe0O9JEB+4x24kTQ2LwfliUfGscegjru8nrSPjgCgJrlp+uK9BiUEAmPGlEAqKCjgJz/5Ca+99hqvv/46M2fO5J577mHXrsG7S//mb/6GtLS06F9JSUkCIxYIBPFCs8m0PXZ3dDn9jR3jPueRlJOPfe2G6HJ490dozY0WRjQ4OaUrKZy5MToUrbX2NNdPbx3z841kyc6U1KVsKPoGszPW4bR5otuaApUcbtjKp9U/40rHYcJqwMJIb180NOo7LnGo/EX2X3me2tazukU6IMs2CjPmsnrG15hTtBm3QTLesUDHhUM07nkDTdE/G97i6eStfwrJ4bI4sv5IoTC2X78CAf3a1xbMQV23yuKozJP9/MdIPt24p+3+FQQn5VockWC8kzCbb0mSeOONN9iyZcuwyj388MNIksTWrVsH3B4MBgkGe92sOjo6KCkpYYP3c4PafJuy8YbYttMmbLz14jHqNrLSNrTijmG1HU8bb4h93CZsvMHALtvIxtug7ZiW1mbKMgSb71i20kZ1m9hubMU9cqtu43PS+7rzrqW0P6aLCeflSnL++UVjC3ITNt+awSUc08rb4POjyYDLjfvRLyIn6zd84TNHCR/YoW+PVdzQftxg+whswAum3E124eLockPVYeoqdhtUNLS6R4tbj0vGRpl3AdOTl+O2JfXup6lUBS5wueswHZEmPax4/uqZrFuK9ZNswsYbDCyv41k3xLT0lVRw2ZOZlL6QkvSFfUStqilUtp7kauN+Qsrw7bQNbb6N7LJjlL/VptudM4n8NY8jO/R7j2BrPXU7X0ENjtAGPNZxGVlxG2zXpk9D/eLT+oKqIv/8N8jXKnqWzdl8x2zbTFmD8s1P3knTlzcBkHT4IsV/8Vzfug3tyU3YgBvZYZuxATe0PjdpAx6jbc1oqKgZG3CTlu+D2YBHtBDbfS+atvkeUz1IA7Fq1SouXbo06HaXy0VqamqfP4FAML5RvG46Nq/WF1SN9Dc/HQ/TXWLiuuv+qDhS6qsJHxx7E4klSaZk5gN9xFFt+a6RiaMEIWNjsnchG3O/zvy09VFxpGkaVf7zbG/6FUfbPoiKI8HYJBjp4lLTXnZe+Q8uNu4mrOg9HLJkozRzMXdO/yYzctdF7cPHIoHG69TsfBGlRxC5MvIovOdZ7N6xd18in7+EtKPHUEKWUZ/ZgpaSHLvQGCdj62fYG1oB6F42g+6l0y2OSDCeGfMC6dixYxQUFFgdhkAgSCAd961B8+o3Qt7DZ3BWje85IvaFK7EVTwZA83cT+vTdMTeJW5YdlM7ZQnrOLEB/clh5aRuN1Ucsjmxw8lxTuDvnSyxI24Db1ntzV+2/yKdNv+JI2/t0RVosjFAwXBQtzNWWg+y8+lOuNO8nooYAsMkOJmevYN20bzIleyWyNPbm+ACEWuuo+fQ3RHz6fGhHSiYF93wBR2qWxZH1R/5kF9LFnrxByckozzxmnFB7DCOHIn1svxu+fr/xSA2BYBDieuV0dXVx/Phxjh8/DsC1a9c4fvw4169fB+AHP/gBX/7yl6P7/8M//ANvvvkmly5d4syZM/zgBz/gtdde47vf/W48wxQIBGOIcF4m3TfZeqe9O3Z7L4aCXFCCY4neG6apKsEd76H5xpbJgSw7KJv3OCkZZQCoSoSKc1tpbRibSWu9tjRWZjzKqsxHSbb3TuavCVzi08ZfcbjtXToj49u++HYnoga51LSXXVd/SnnzkWg+JYfNxfTctayZ+hWyk8qsDXIQwp0tVG//NaEO/Rq0e1Mo2PAszvSxNS9G0jTkV9+C9h5zq7JJqPfcZW1QJknZeRL3ef0eM1SWR/umpRZHJBivxFUgHT58mMWLF7N4sT5c4/vf/z6LFy/mz//8zwGora2NiiWAUCjEH/7hH7JgwQLWrVvHnj17ePfdd3n88cfjGaZAIBhDdDywLjrvLOXjA9jax5aYGBZOF467NkeNDsLHPkOtrbQ4qL5Isp3SOY+SlFoEgBIJcO3Mq3S2XLU4sv7I2JiRvIq7c79MvntKdH1TsIodjb/mUOs7YijdBCOk+LlQv4Pdl/+TytaTqD09r15nOktLn2Bh0UO47EkGtSQexd9J7fbfEGypBcDm8pC//pmxJ5J8fmwvvh6dx6KtW41WOn7NriQg96fvR5ebnt2A6nJYF5Bg3JIwk4ZE0dHRQVpamjBpGLC8MGkYbtvCpGEk20ceV7A0n4Y/+BIAcnsX+f/rP5DDva5pptq2wKTBsf5+7NNmA6DUXCf4wasD122RSYMkyUya8wipmbrYiIQDXDv9CoHuxp6yJofbjOJonVxXGfPT7ibJnh5d51c6Od2xi5rAxeGFJUwaEls3GJo0xKz7pjnoSa4s5uTfQ2ZS7018RAlyuX4P11uOc+uBJNKkYaCykt1J/p1P4M7R41UC3dRuf4FwZ4ulJg23blfvXI26qcc1tKUN2z/9BCkYGiSusWnSAEBP+eo/fZau1XMByP75B2S9uluYNIygbWHSIBAIBGOA9ofWRV+nfrivjzgab9imzIyKIy0YILT7A4sjuhWJ4pn3R8WREglRfub1qDgaK7hkL8syHmJV1mNRcaRqKpe6DrO98blhiyPB+KY72Myhipc5Vf0+oYhuhmC3uZhVeA+rpn6BVE++xRH2RYuEqNv1GoEmPeeTzZ1E/vqnx5xxg7R7H1T09G5npqM+uMnagEyS/cuPojf+LU/dhZI8ds09BGMTIZAEAsGYIDB9EsGZZQDYmtpI2n/S2oDM4E3Gseae6GJo33a07rE1VLB4xibSc2YCoCphys++gb+rzuKo+lLgnsb6nC9T6Ol1o2oOVrGz8XnOdu4mooUtjE5gJTXtZ9lz+edUtvZ+T6R68lk55QvMzF+PLBl0CScQLRKifterBFt1sxm7N5X89c9gc4+doYGSpmF7dSv0pE3Rli1CnT3D4qhGjquykdRPjgGgJntoeeJOiyMSjDfGpg2M1ZgZgmdmCB3EHk5mZgidUfl4DqGD2OfUzBA6iD2MzuQwuFjlNbtR3CaHwcUcYmd2eN/I2gXQ7KNftwa0PdLbe5Ty4V40SevXlplhcoZD0UwN3+u77F6/GcmlP7EMXztP+Pr5mN+2MeseSo6lWAxQvKjsbjLy9OEnqqpQfultuvw14LjlfJsdIhejfKy67ZKTBUnrKXXPja4Lqj5Ode+iMnhOf7Rn4eO9mMPNTA+xi3XSDAqbGAYXc2ifQdmhtT34cRkOg5MHrjxIgNNNH1HdeYa5efeS4spBkiRKs5eRmVLKidr36PbFnpNmPAQvVlxDL6sSovazVym883M4U7JwpGSQd/cz1Ox4ATU0cMLiWB99yeB7QTIYEykNdGCd7UgffIT26EN6zI8/CP9cg9Td3Xc/xejAYwwNNBgUoGEwBM/wg99bPvvF7XTevRDNYaf10TvIeHsf9pbOGHWbwegDYkKwGw39M7r3MxqCF+N+QjIavScbDcGLsc3o3s4o7jgjepAEAoHlBOZOJVxaCIC9thHPsfMWRzRyHLMXYy8sBUDt7iS4f7vFEfWlYNI6svMXAfr48orL79LZXmFtUDeRZS/invQv9RFHNcFLfNz6S10cCQS30Oav4bPy5znfsBOlx+0uxZXD6klfoDRz7LiYKUEfNXteIdzdDoAzPYf8dU8h2QeeL20Jx07CuQv666Qk1C0PmtX8luFoaif93QMAaC4nTZ+72+KIBOMJIZAEAoGlaJKkO9f1kPLBHsOn2WMVKS0T55LeYwnu3QaDPB22gtyileQWLgP0RKrXr2yjo/WKxVHpyNiY513HurSn8Nr0+RlhNciRzm0c6HyHkOa3OELBWEZDpbz1MPsqnqcj0ACALNuZlb+eZZOexGUfG0lQFX8nNXteJhLQh9y6swrIX/s4km1sDOiRAHnre9DVMyR45nS0pYtjlhnLZL66E9mnfwe337eMUOHYy0clGJsIgSQQCCzFv2gmkYJsABzlNbjPjI0b9mEjSbhXb0Ky6zc6obNHUWqvGxRKHJm58ykoWR1drrr2CW1NY6OnLklO5670Z5juXRYdOtQUrmJ72/NcD47NXExxRwOn5sSrJZGqppKhZpKj5lKgFlCslFCmTGayMoUSpYQ8NZ8sNYtULRWP5sGu2U0P9RuvdIWa2Xf9N1xrORRdl5VcyuopXyY7ucy6wG4i0t1G7Z5XUIK66PfkTiJ35UPGw+gThNTtQ37z3eiydt+9aOlpFkY0cuwdPjLe2Ksv2Gw0PbvB2oAE44ax8chCIBDclmhA5z0rosupH+wZTWfohOKYsQBbrj5MUG1vIXR0j8UR9ZKUWkxxWe/wkurynbQ0nLIwol7yHZNZlnI/DtkFgKJFOOvby2X/UYsjiy+yJpOhZZCqpZKsppCsJZOipZCiJZOsJZOspeBg5PlbNDT8+OmUOuiQOvX/tQ46Jf2vgw5C0sA2zuMdTVO40LiLxu5rLMi/H7cjBafdw9JJT3Ct6SCXGvYaznWJN6GOJup2vULB+s8hO5wkFc8gc8F6Wk58amlcN5AuXkY6fAxt2WJwOVEfug/5+ZfG5fdz5ta9tD20CiUtic475xP+5Uc4GtqsDkswxhECSSAQWEZw1mQihXriREdFLc7LY6fHZThI3mScS9ZGlwP7PgJlbFiUO11plM14GKnHaKWh5ghNdWNDfEz3LGOud22016gz0sLBznfpUCZWsleH5iBbzSFHzSFXzSFHyyVLzcIex59gCQkvXryalzxtYOvrTjppkOqpl+pppJ4GqZ6ANHGGMrb4Kvnsyi+ZV3QfuSlTAZicvYJUdx7Hq94mogYtjS/YWkf9Z2+Sv+5JJFkmfeZywh3NdF4bGw6e0raP0aZPhbRUmDENbd5spNPjbx6g7A+R/s5+mr9wD9hstDy+lrx/e8fqsARjHCGQBAKBZXRu6O09Stl+YFw+nQRwrbgbyan3gIQvnkKtr7Y4Ih3Z5mTyzEex23VHvY7Wa9Re321xVPp8o0XJG5nknh1dVx28yJHOD1EY/9bdXi2JUmUSk5RS8tV80rV0pGFc3SFCdEqddEvdhAihSBEiRFBQiPT8UyQFDQ27ZseBEwd2HJoTBw4cmr7GqyWRTPKgbaeQQoqWwlRtWnRdBx00SPU0SHVUStdpoH5UE/4mmrAa4Fjlm5RmLmFG3p3Iko2s5FJWTX6Wo5Vv4g+0WBqfv76cpqMfkrPsPgCyl2wk1NlMsMn67xApGEJ+70PUzz8JgHb/JrTL15C6x5+IznhvPy1PrENzO2nfuJSs32zH3uGzOizBGEYIJIFAYAmh0gJC0/Ts8vb6ZtynL4/LGzFbyRTspXqeHtXfTfCI9QJER6J0+gO4vfqk5ICvmYrL72H15BS3nMSK1IfJdBRE153t/owL/gMWRmUOu2anSCliklJKqVJKtpYdc38NjVaplUa5gVapjU65ky6pk06pi246CREa+LMwAptvWZNJJoVULYVUNZVULZUULZU00sjRcnDi6rN/Kvo+0zT9mvbh47pUznX0v4A0dkxHhkNFy1Ha/fUsLnkEp91LkiuTVZOf5cT1rbR0W9tz3Xn1JM7UbNJmLEOy2chfvYXqj3+F0tVuaVwA0rkLuqvd7JmQkoy28W548z2rwxo2tk4/6R8conXLGjS3k7aH7yD7159YHZZgDDNhBZIky4PnHDI7ETJGvhTDPEdG+YJi5lgykZ8JzOVYMpPnyKBtU3mODNo2zAdklD8gRnnjfEEm8yTFyoNkmIto5LmMzOYLUmPmIuot23HT3KOkXYfRbFLMPEZgNr+TQd0j2W534LmjNyFs4OhOVC04/HxCMfMgjSAuoKh4HakZkwGIRPxcufIWETnUr62Y9RvFPcyv0gxbHquSHsEj645iES3MId8H1EQuY2K6TcKRNPCoHmaGZzItPJXCSOGgw+UiRGiyNdFga6TB1kCj3EijrZHIYAlhYoggg9Q2A5ZVUWmjnTba++f00SBDyyBXzSNPySVPyyNHzcVJr+20Fy+ztDnMYg4aGvXUUSFXcE2+Sr3U27tkFJukxsiNY5iLyCDnT6xcRTd9p7QoNXxW9RuWFmwhxZWNw+ZmSdmTnGvYTmXbiYHLx0jFYhS3bJTG5abDajq7A0daNt68MmzuJPLWPU7Np79BUwbpUY0YnXCDtmN96dzyZkoffIQ2pQxcLrTlS1BPnka6XjV4+UiME2Pwu4hiFHjskxorT1LG1s9ofWgV2G20PryKzDf3IAd65+FpBr5lcc2TFOuL2ChPpVGeJKN7LDVGeaPcnqrRfU6MuhWja9ig7UGOSzJMDjg0JqxAEggEY5dwbibBOfqwHrm9E8/R8TeuHcC1cA1yUgoAkdpyIhUXLI5IJzN7Lrn5ev4XTVO4duUdQiFrn0aXOGaxxLsRm6T/7HSrHezrfot2dfzMN3JoDqaFpjEnNItJkUnIA9xQqajU2+qpsF+nwlFBra0W9eY76bHkLidBq9RKq9zKRZvuaChpEhlaBoVqEWVKGSXqpKhgkpDI1wrIVwpYqayiVWrhnHyO87ZzdDF4As6xhD/Swb6qF1iU/wC5SVORJZm5efeS7MzifMOnaFa9QZpG/aGtFK3/Es7kDFxpueQuf4D6/W9ZE89NSB2dsH0X2v0bAVAffgD5336GZHEiz+HiaGondddJOjYsRk3x0rZpKZlb91kdlmCMIgSSQCBION13r4g+mUrafWTc/dACyFl5OGbp+UG0SBj/wbGREDYpuZCSSb29WpXXP6WrK8bT3gQw230Hs92rostNkWr2+94mOA5yG0maRGmklLnB2UwNTx3QWa5dbqfCXkGF/TqV9usEZGsn/5tBkzRapBZa5BZO208hazKFaiGlymTK1FKytZzovhlaJquVNaxW1lAlVXJWPsNl+dLgvWNjBEULc6R2KzOz1jIlYzkApRmLSXJmcKzmbRTVGnc/NRykbt/rFK3/IjaHi6SiGWTMXkPrub2WxNOHQ0dgwVwoKoTcbLS1q5B2joG4hknma7vp2KB/b7c+uoaMdw8gGfXACG5LhEASCAQJRUlLwb9In5wvdfvx7h8bjk3Dxb1sQ9R9LXhqP1q39fMF7HYvk6c8hHzDsa7+GM1N1tp5z3ffxXT3kuhyefAUx/zb+/aqjEHcqouFwYUsCi4kWeufZLRdaue88wLnnedplpvH5fy5oaBKKlW2KqqkKvaym2QtmVK1jJnKLEq0kuh+xVoJxUoJ65W7uShf5JR8kka5wcLIjdC40Lyb7kAzc/M3Iks2spPKWFnyDIeqXiWsWCPew10tNBx6m/w7nkCSJDLmrCbQUo2/vtySeG4gaRq8/T7ab30NZBlt3Wq0Yyf13qVxhKuygaSD5+leMYtITjqda+eTunPg4ZWC2xshkAQCQULpXr0oOqY66bPjyKHx51pmL52JLUc3GVDamgidHwu22RKlU+7D4UwCoLPjOtWVOy29cV/ouZuprkXR5ZP+HVwOHrMuoCGQoqSwNLiE+cF5febiAPglPxecFznvOE+NrWbCiqJYdEldnLGd5oztNClaCrOUWcxW55ChZQLgxMU8dT7z1PlUSOUcth2iWrK2BzMW1R1n8IXbWFz4KE67h1R3LitKnuJQ5SuELBJJvvprtJzZRda8uwDIXfYAVZ88hxLotiSeG0j1DWgHD8OqFeBwoN2zHumNty2NaSRkvrGH7hWzAGh95A5Sdp64HT/KAgOEQBIIBAlDc9jxrZyvL0QiePcdtzSeEWGz41q8LroYPLITNOt7Q/Lyl5GaWgpAONRN+dX3sXLCy2LPvUx26e+1pmkc9X9EReiMZfEYkRPJYXlwKTNDM/vMLVJRueq4yhnnWa46rqFKqrFZwm1Cp9TJIfshDmmHKFALmKvOZbo6MyosS7UySiNl1Eo1HJEOck26OiZFZau/mgOVL7Ks+Ek8jhRSXDksL3maQ5WvEFassYJuu3QQd1YxSQVTsbmTyF3xELW7XwbN2otP2rkXbcF88HrQFs1H238IqbbO0piGi+dMOa6rNQSnFBKYXox/dinecxVWhyUYY4yO1YNAIBAMAd+SOWheDwCe4+exdY2/PBTOWYuRk1MBiFRfQ6m1/ofVm5RPQdFqADRNpfzae0QiVp1biaXezTeJI5XDvg/GrDgqCZfwROfjfLnzi8wOzY6KozBhjrmO85+pv+Ct5Le57Lwy5ocFWoYEdXItn9g/5meOn/Cp7RPa6R1yWqAV8pC6hc8rX2aGOgvJ0NYx8XSHWjhY+RL+cAcAKa5sVpQ8jdOeZFlMjYffI+LT4/HkTCJj1mrLYrmBFAgg7dwTXVY33zOmfEeGggRkvPVZdLn1kTusC0YwZpm4PUiSNLhFoEm77JhW3mZsvCF2bGZtvmNtN7K7NmHjDQZW3iZsvCG29bMZG2+9vBkLcXPbVVMW4ybssA2ttA3iHuRbRQO61/XORfHsP4Z6y3x3MzbeRttjnc+h1I0MksuDc55uT66pKv6Tu1EdknFcI7TqvtFuLCSbk7IpD0S/l2rrD9IRqOq1zTZq24zNd7/dJZa77mOSQx++omoqB4LvU8XF/jbeFt8j50SyuatrHZNDZX3W+yQfx7wnOOY5jl8eJOePGStuI0bZ5nvI5Q2ttodWd5AwJzjJSe0UM5SZLA8tj+aFyiabzeoDrJLWsN++j/O2c/p1YLJtOYZdsGHcN32fddPB/tqXWVnwFF5HGsmuLJaXPc3BqlcIKl0D1G30m2uw2cj5WQlQd/gditZ+DkmWSZ+9iu7mcgLN1dH5j4PWbeCTETOjiJFnzpGjsGIpZGXC5FK02TPg4qWbaxi8rIG1s2RwMWgY/KbHsAG/2QI8de8ZGr+yGSUzha5VcwjlZ+Ksi500OJYNeFy/zoxMjMzcVxph1GNp9PsUwwZcM/pCG7E9+ei8G6IHSSAQJITQ9FKUXD1pqeNaJY7asTyBe2Bc8+5AcuiJNUNXT6N2NFscEUwq3oDLlQZAV3cNtfX7LYlDQmal+8GbxJHCvuA7VCkXLYlnMJKVJDZ3bOQrLV/sI47a5DY+Sv6Ef8/+GZ8l7R9cHAmGhCZpXLCf53nPr3jL9RY1ck10W5qWxubwfXwu+HkKlUILo+yPP9LBgdpX8IX1HrBkZyYri5/Gbe9v1JEIAi3VtJzX3eIkSSZv6YPIDpdBqfgiqSrSJ59Gl7WNG4zzGY4xpIhCxvsH9QWbTNuDq2IXENx2jK8rWiAQjFu61/T2Hnk/GwumBsNDTs3EOaVn2Fg4RPC09fkzMjNmk5WhOwIqSpBrFdbMO5KxcYf7IYrt0/VYtAj7Am9To1xJeCyD4VAdrOm6g282f40FgXlIPU8Z2+V23kl9n59m/YLj3pNj3qJ63CHBNftVXnG+xKvOl6mQy6Ob8rR8ngo9wwPhB0nVUq2L8Rb8kQ7217xMd7gNgCRnBiuKnsZtT7EkntaLB/A3VQLg8KaRs3CjJXH04fxFqLiuv87KhKWLrY1nBKRtO4TUYxLUvnEJisda4SkYWwiBJBAI4k4kO4PQzCkAyC3tuM6NnRvnoeJeuC6auTt47iBa0Nr5U05nKiXFG6LLFVUfE+qZP5FYJFa476fQPhXQxdFnga3UKtcsiGUANJjjn803W77Gat+qaB6jgBRgR/Iufpb1HOfc542HewjMIUG1rZo3XW/wuvNVmqTG6Kbp6gy+FPoKqyJ3YNOMhlAlhoDSyYGal+kOtQK6SFpZ/DQumxU9SRr1R95FCem9minFs0kumWNBHL1IgPRRb+437a61aK7xJTDsHT5Sd+gW36rXTfvGJQYlBLcTQiAJBIK441s+P/rau/+YnlNjHGHLysdRqAs8tbuD4EXre8AmldyLzaa7hTW1nKG1zZqhbAuc66I9RxEtzJ7Am9Qr1htXAKQpqTzT9iQPdt5HsqpPtldQOOw5yn9k/ZxD3iMo0vhLUjzeqbRV8hvXr/nY8RE+dOtqO3ZWKqv4UugrTFYmWxyhTkDp4kDVy3SH9LkpXkc6y4uewC47DUqOPhF/J43HP4wuZy/YgM3lTXgcNyPV1MKpHvMVrxdWLrM0npGQ8XbvSID2TcvHneGEIH4IgSQQCOKKJssEFvc87YxE8Bwdm25msXDN6x2fHjiz33jSbJzJzJxDaopu6R0KdVBZ/alBifgw1bGQGc6lgG7IsC/wNo1KpSWx9EGDef65fLXlS0wK9yYzveS8zH9m/pJPU3YSEHOMLEWTNM7YT/Oc+xccth1G6Zlcn0Yaj0S2sDG8CYd2q7NH4gn2iCRfqA3Q3e0W5z/cZ8J/ouiquUBn5VkAbC4PWQvuTngMtyLt2BWdLK+tWjHuepFclY14zpQDEJqUS2BmsbUBCcYMQiAJBIK4Epw5GTVFf3rvOncF2T++bkz13iP9ibba1U64/Jyl8djtXooL74ouV1R9gqomPtlugW0yi5zro8tHg5+MiZ4jr+phS/vD3N+5CaemP+lvl9t5Je113kx/mzZ7m7UBCvoQkkLste/mN47nqZR6xfUcdS7Phr5IvlpgYXQ6QaWbQzWvRRPHZieVMSd3g0Gp+NB06lOUkB5HSskcvHnW9rZJrW1w4pS+4HbDyuWWxjMS0j7pHRHQfu/46wUTxAchkAQCQVzxL50bfT3ue4/OHrA8KWxJ8d3Y7W4AWlrO0dFZnvAY0uVcVrofjFqLnw8dpDxyOuFx3Mq04BS+2vxlpoemRdedcp/mF5nPU+6yXrwJBqdFbuF1x6t8aN9GkCAA6aTzVPhpViirLM+d5Au3cbTmLVRVN/GYlLaQsozE30wrIR9Np3p7jLMXb0SyWdvTJu3+LNqrrq1ajuYeX71IKZ+dRfLr11zHuvmoLut7LgXWM3HzIMkyDJavyNAz3sR2o7qN8vLEKm9Yt1GuohhtxzPPEcTON2Qiz5G+PcZxmchzZNR2PPMcGbZtmOfIqO2Rtatvj7m5z3GpSR6Cs3rMGTq6sJdXoMaIfTh1D1jeRD6hgc6JLbO390jpbidQfa5/Pp8h1G2YJynWxpvKpqdMJSN9BgDhiJ/r9Tv75ZLqV7fRfeUw8yB5SGaN81Hskt7wdeUCJ9gLA03LMHNPO4yyTtXJPW13scA3L7rOJ/v4IONjLnlGYAhiZiKCmVxERuVN1h0z745RvqDYmw1z+sSq/+ayZzhLlVrNfYH7KFQLkZFZpd7BJErZ5viADrm9X3klxvedmRxKQJ98Q82RGk40fcji3AcAmJlzJ91qO/XdlwcpbFC3YpRzceD17bVnSWmYgze3DIc3jcx562g6fcswW6M3LIZZo9Fb2e/rrLMdTp2GRQvB7UZdvRJ5526DWoZcex/M5UkaeGi0FA6Tsuc0HRuXonlddK6dT9qnxwfYc/C2Y+VIAovTvilGH24TOTKNhpvHOi1GP06GF+IglRsmNRwaogdJIBDEjcCC2dEvWPfxs0jq+JoC65nT23vkP29t75FNdjKpsHdYT2XtDiI9Q34ShR0n6xxb8Ei6k1eTWsMBZVtCY7iVwmABX6v/Yh9xdMl9hZ/l/Wpk4khgOe1yOy97Xmafcx9qz11SoVrIs8EvMCsy2won+yg13ee52PoZoIunRbn3k+bKS3gcDSc+Qo3oQ2vTpizBlZGf8Bj6sKe3F4mVy9DcbmvjGSZp228eZifc7ARCIAkEgjihAf4lvcPr3MfG1/A6W2Y+jvze3qPQdWvnHhXmrcbp0IVJe+c1WtrPJ7R9CZnVjgdJl3MA6NTa2B15CzVG5vq4osGirgU82/gU6YqeKDcohXgv40Nez9qKz2atDbvAHJqksd+5n5c9L9MmtQHgwsXm8H3cF77fUgOHS237qerqMUuQHSzL35LwHEkRXzstF3qFWu7CzYOPmkkAUns7nOydi6StWmFZLCPBfbEKZ6WevNw/t4xQYZbFEQmsRggkgUAQFyIFuSj5+s20/XoN9qZWiyMaHp7ZK6OvA+cOWtp75HXnkpu5CABFDVNRsz12gTiwyH4n+XIZAEHNz+7wG4SwxnBD0iTubbubzW33YOsZUlPlrObneb/iVNIZi8ezCEaTWlstv3E9z1lb7wOWmcosngw+hVdLsiyuU40f0eyvAsBlT2JZ/hZkKbGzFtquHCbQVq/HkJZD+tSlCW2/H7f2Io0jRzsJSPv4WHS5fcP4S3wrGF2EQBIIBHEhuGBW9LVnnPUeySmZOAr0uVNKdwehirOWxlNScGd0LkRN/b6EJ4Qtlqcz3abfMChahL3ht+nS2hIaww0cqoPHmx9hafei6LqDyUf4Tc4rtNutSJQriDdhKcxHzg95z/Fu1MAhV8vjmeDnyFQzLYlJReFo3dZoItlUVw5zsxPsbKdpNB7fhtbz8CZzxipsTutyI0kdHXDipL7gcsHihZbFMhJSdxyPztfpXDtP5ES6zRECSSAQjDqaBIH5M/UFRcF15pK1AQ0T9/Tep4fBy0ct7T1KT5lKSpKeyycQbKWh5ZhBidHFSyrL7PdGl49FPqVJq05oDDdIVpJ4tvEppgV6xCsK72R8wKfpu9AM3Q8E451L9ou85HqRDkk3akjVUnkq+AxFapEl8YTVAEfqthLpsdkvSZ1Hccpcg1KjS7C9gY4KfWib7HCROWt1Qtvvx4FD0ZfaiqVoRuZSYwh7ezfeU9cACOdnEpxaaHFEAisRAkkgEIw64dJi1DR9TL7zUvm4yn0kOd04S/XEtlo4SPCadb1fkiRTnL8uulxVtzv6tDgh7SOzynE/TkmfcH1dOc9V1Ro775xQNl9q+Dz5YX1CfEAK8FL265xJsnZumCCxtMotvOR6iXpJH1rmxs2W8OPMUGZYEk9XuJnTjR9Fl+dkbyDJkZHQGFrO70WNhABILVuAM8W6+TNSSwtc6nH1S0+HWda8LyMlZc+p6OuOtfNi7CmY6AiBJBAIRp3AwtnR1+6TiTUTMItrygIkmz6XIHjtNPTceFhBTuZC3C79Zquzu4q2zsS6ss2z3UG2rD9F7dLaORL5JKHt32ByoJQvND5NqqKL7jZbO8/nvkSlu8qSeATW4pO6ec31CuWy/rTfjp37Iw+yJLLUEoe7mq7zXG/Xh5bZZQeL8h5Ejmk3PbooQR+tF/cD+kOVrLnrE9b2QEj7b+pFGmeJY1MOnIOIPo+qc40YZnc7M3HzIMXCIEeMZOQEYyZXkZntRvmZrIzbID9NrFxHpvIcGbRtJs+R0XbVbrJuo9w4MfIFmcmhBKDG+OSbjVtx2gjOmw6AFAzhuHQl2p5RniOj/E3GeZJi1R27LDIg23BNW6Tvr6kEyo+j9cSumsixZPheD7DdJrsozO+1GS9v2okyglxDhsc9SPk8Spgl6Tc3qqawl3cJOG8Ri2ZyLBlwI0XG3M5ZPNy0GbnnJFe7ank1byvd9vi51JkarWcyz1FaMIk8fzp5/gyyA2m4I05cqgOn4sDV8+dU9f9lTcJvD+G3BfHbg/htIQK2YHRdm7OLWm8zDZ42IrISs22jfEFmt8fKaSIblFUGuIYVwrzp2Mo9gQ3MD88HYJ1yJylyKjscO6JDLmUDk0XV4LdNkgc/adJNdZ9u30GGp4gUZxZprlxm5KzlfNNOg7pjxxZz+y1ht1QcI7VsEQ5vKkl5k3HnT8bXWD5ocTNPxw3PWeV1aGyEnByYVIJaUgi1dT3tmu0BH3mepNg5kgAUZF8A78mr+JZMJ5Kbjn92CZ6LVT11x2rb4LiMcv6Yuj8zeDdjXMPAEJLlxWp75GWN7rU1wy+G+MrX21MgCQSCuBGaPjmaA8N57hJSJEZGwjGGs2gmslt3xgrXXEb1WTfpvyh7JXabfh4b28/iCzYkrG0XHlZJ90eNIU7yGS3UJ6z9GyzomMuDTRuReu4Gz3svsTX3AyLy+LmmBiMtmMT09iIKfFnk+nRBlOfPwD2gCjaHgkqjp41aTzN13hZqPM3Uepup9bSgGt2EjGFUSeUj98d0Sp2sDulzbxaFF5GkJvGe+z1UQ9U2irFoEY42vcvagmexSXampC6lqbuCJn95QtrX1AhNF3ZTsPhBALLnruf6zudAs6gP5OBhePB+/fXyZbD1HWviGAEpe0/hW6I/5Ou4c0FUIAluL4RAEggEo0pwQe/wOtep8TW8zj2tN0Fg4PLRGHvGF5cjjdyMRYBu613VvDeh7a+UNuORdKFYq5VzjsMJbR9gcccC7m+6J7p8JPUE27K2j1sLb3fEyazWEua0lDKzrYR8/8jd1xRUQrYwqqThiTijvWuDYUMm35+pt9nSu95vC3IxtYozGeWcSbtGq6tzxDFZhgQHnAfolDq5N3gvNmxMV6bzYOBB3nW/i+GT/VGkM9zEudbdzMu8G4CFOZvZXf0rQkpicnJ11pwnvWwxnoxCXKnZpE1aQHvFiYS03Y8zZ+Huu8Drhdmz4NOd0Dk+rq/kA+dp+K0wmstB1+p55P78AyRl/D5IEIwMIZAEAsGoobqchKbryVWlrm4c165bHNHQsWcXY0/T8zZFWmqItNZaFktR9h3Ikj4cpLb1CKFIV8LansI8CiX9PQxo3exnW8LavsHcrll9xNHB1KN8nLVz3Imjks4cFjRPYU5LKZM7CrDFEDIqKk3uDho8rdR7W2nwtNLgbqPbESRkCxOUw4TkMEFbmIik9J4LDVyqA0/EiSfswhNx4VX0/7MDqRT4sijwZ5Hnz8R5y9haj+JiYetUFrZOBaDa08TpjGucSb/G1ZQa1HHkDHjWcZZuqZtHAo9gx840ZRqbgpv40P5BQq+b8s5j5LhLyfNOwWVPYl72PRytfzth7Tee3cGkNc8CkDlzNR2VZ9BUC3pcIxE4dhzWrAabDZYsgp27Ex/HCLD5gyQdvkDXmnkoaUn45k8h6fhlq8MSJBghkAQCwagRmlYGdv1rxXX2EpJVwztGgKu017EocOW4ZXG4nRlkpeoW6eGIj9qWxPXeuElikdTrmrefDwmQmKffN5jmm8xDjZujy/vSDvFp5p5xI448YRcrGmaytnYek7ryBtxHkRSupdRzMb2S8pQ66rytNLnbUWQ19vyngbZJELTpwqnd0T1oUUmTyLohmHxZlHTnMLO9hJRIb96cIn82Rf5sNtcsx2cLcDD7PLvzTlLrbR7i0VtLhb2CN91vsiWwBTt2ZkdmE9D87HIkVlyfaN7GXa6v4LJ5yU+aTp53KvW+xBisBNpq6ay9SErBDOzuJFInzae9PLGpAaIcOQZ3rNLnIC+YD7v2WBPHCEjZe5quNfpvQteKWUIg3YYIgSQQCEaN4Kyp0dfO8+PnB0VyuHAW6mPO1ZCfUK11sRdmrYhOXq1rOYKqhRPW9lLp7qil9zXtDLWUJ6xtgBJ/EVsaHooOGTuSenx8iCMNprcVsaZ2HksbZ/TrqQGo9TZzNuM6ZzMquJReRdCWuPcVQJM0mtztNLnbOZV5FdDNKEq6c5nbOpn5rZMp7cpH7jnZXsXN+vpFrK9fxKWUKnbnnuRExmXd7GEMU2mv5F33uzwceBgZmcXKErqlbo44EvegIaT6OdPyKUty9PlAc7I30FxZSURLjCNm86X9pBTo9toZ05fTcf0kmmrB+9bVpVt+z5wBKSkwbSqcu5j4OEZA0vHLSMGeYXYrZpH7H+8iCU+72wohkAQCwaigyTKhGT3D6wIBHBXjZ2Krc9LsqLV36Po5sOJmAn3uUVbqLAAiip/6tsTNHyhmGiWSLhIDWjfHtF0JFSa5wRyerH8UR49t4Jmk82zL+nRMi6OkkJu1tfNYUzuPPH//3DfXUmr5LP8sp7Ou0eLumX8xhu6xNAmuJzdwPbmBD4oOkBz2MKetlLltk1nYOhWn6gBgemcx0zuL6bT72Jdzhj25J2l2WWdgYsRV+1U+dn3MpuAmANZG1uGXfJy1n01YDDW+CxT75pDrnYzHnsLMzLWcad6ekLZDnY101V0mOX8aDk8qKSVz6ag4mZC2+3H8hC6QABYtHDcCSQ6G8Z64QveKWSgZKQSmF+E9V2l1WIIEIgSSQCAYFcJlRWieHve6S+VI6viZ1Ooqmx99HaywJhEqQEHW8pt6j46iquGEZKtz4GSpdHd0+Yi2gxCJS+6bEU7nc3WP4dZcAFzxXOPt3G1jVhx5wy42Vi5lQ9Xifq5z3fYA+/POsbfgNNXJTRZFODK6HH4O5pznYM55PBEXK5tms65+AQV+PfFoSsTLptrl3Fu7jLNp13i3aD/XkxPvbjgUzjjO4NW8rA2tBeCe8Eb8UoBrtquJi6HpEzKLv4JddjApdSHVXedoCyZmbmPLxf0k508DIHPaSjqun4YEJpmOcvUatHdAWipMnYKWkoI0XswaDp6je4X+wKprxWwhkG4zJq5AkqRB/dkN8xwZ5huKlavIRC4igFh5e2SjfEBGxxVju8l8QUbHFbO80TkzzPljJseSUb4gE3XHyGMEsXP2GNVvmAfJ4JMdq7xhzp5B4g7MnhZ9bb90BXWA4zfMg2QizxEQU0wMlsfInp6PPS0bgHBrDaFAMzgGiC3OeZCc9hSy0+YAEFEC1HYdR3UMMX9TrLqHkKtonroaj5YMQDVXqbBfBGloZU1tB7wRD5+re5wkVXfNq3TX8GrRO0Rs1gnsweYBuSNONlYs4d6KJXgjrj7bzmVeZ0/RaY7mXCZii9EDadCDNOw5SEMtCzEN3W51xO52BNlecpztxceZ1lHEXTULWNw8HbtmQ0ZiXvsU5rVP4UjWRd6e9BkN7tYRt2103y4ZdOgO5lR+0HYIL16WhJYgI/NA6EFe9b5Gjb2mt6zRT7Yy+EVs9HPerXRwoX0vczPWI0kS83M2srvu16goPXUbtB0zN07sN9vfVU93YzlJOWU4ktJInjSbjuqbetBMpN0Z9ijLUyeR1q4FWUZbuhBtz2eD1x3HPEmxciQB/b5sk45dBlUFWaZr5Wyyn/9o0NMmGXxZGt0vxM6xZCFG7n1GH6BYD0qNcpLGTD5INNfZACVjxzREJq5AEggECUMDQjN75h8pCs4r5VaGMyzcN5kz+K+fsiyOwvRlUee6uvbjKGpi5itkaLlM1xYCECHMITlxVto21cZTNY+QHkkDoN7ZyMtFb465PEeuiIO7KxexuXwpyWFPdH1EUthdfIqPSo/S6G3XV46hIXSjggSX06q5klJNSmgndzTM5c66BWQFUwFY2jyDxc3T2Jd7hveK99PqSpzjoiES7HDtxKt6mRWZhR07W3yP8lLSyzTbEmM8ca3zGEXeWaS78klxZjMldSmXOw4mpO3my/tJyikDIGvqSjqqz2HJBXryFNrq1UiyDAsXwt591uVnGgb2Dh+e89fxzykjXJhFqDgHV1Wj1WEJEsQYlawCgWA8oeTnoKbrN0z28kqkUGJu7s0i2Ry4inTHODUcJFhrzfh4h81Lboou1BQ1RF17glynNFiuboiaIpyS9uOTEjT8RYMH6u+lOFAIQIe9kxeL3yBgCyam/SEgaRJ3VS7gh3u+xhOX1kbFkSKp7Co6xZ+u/Tm/mf1przia4HQ6fXxYfIi/WPJzXpyyPeqaJyOzpmE+/+PY13i0Yg0uZYAuWKuQ4APPNspt5QC4cbPF92h0OGf80TjZ8hFaTzfZ9NSVeGwpCWnZ31qNr1kfFuZMzowaNySczk59qB3oQ+2mTLYmjhGQfKA3l19Xz3A7we2BEEgCgcA0oWm9P3jOS4mxsx0NnAXTkOz6HJJgzQVQrOm5yEtdiCzrHfr1HSeJqImZ/1PKDLIpAKCNZi5IiUuOu7BjLgs69SGFISnMK4Vb6bIPblOdaLJ9qfzRoaf44rl7SA3pw/9UVD4rOMufrfkFv5r7MS2e8TGXYrRRZJWdBSf486X/yZule/DZ9OvVodnZXLOCPz/+FRY3T7c4yl5USeVt7zvUyfp8qTQtjU3+TQnrTOkIN3Kt8zgANtnBzPQ1iWkYvRfpBhllS2LsGWdO3GQ4M2+udXEMk+TDF6Kvu5daJDAFliAEkkAgME148qToa8eVCgsjGR43rL0BAtXnLIlBQiY3VTeJ0DSVurbE9B7JmswCrfdG7ai8A/XWiShxIjuYxeaGXlOId/I/pM7dkJC2DdFgdfUc/mLfl5jeVhRdfSjvAn+x5pf8fP6226bHyIiQLcK24kP82dL/5MPCQ4Ql/QFDRiiFb118iC9d3jRmepPCUpit3q34JT8A0yLTWBhemLD2L7bvI6TobRd5Z5PiyE5Iu77m6wQ69M+WJ6MQd9rAubniztWraH79+Jk+LZovb6zjaGjDUa2brQSmF6F4E9XzKLAaIZAEAoEpNLudcIk+TEpubcPWNj5uHiW7C2dOKQCKv4tIa41BifiQmTwdp13voWjpvkxIScwcjqnMI4V0AOq4Th3XE9KuXbXxWO0DODT9xvlo2knOpYwN69+kkJvvHH+Ir53ZHHWna/S083+WvcxPFr5HXZKBEcFtis8R5M3SPfyvhb/kVEavS9wdjXP5wckvDJowN9F0yV184N4WXb4rcCfZSmKESkQLRuceSZLErPS1CWkXoK38ePR1eunihLXbB1WFiz2fc6dTz4k0Tkg62XNN22z455RZGosgcQiBJBAITBGeVBh9Gui4Nn5sUJ35U3pzH9VesiyOvPRF0dd17ccT0qZNszNPWxVdPi4nLhnrxsb15Ib0m9IGZxMf5exITMMGzG0q5S8/+xJLG3p7FfcUnuav7nieS5nVFkY2fmj0tPOvs97iF9PeJyDr8xBzAxn84elnuLdmqbHLXgK45rjGUac+lNSOnQeCD2I3sv0cJcq7TuCP6MMy8zxTyHAVGZQYHTpqzqGE9N6blIKZ2JwegxJx4nzvfB5mj5/5PN6TvaLft3D8CDuBOcZHH+dIkKTBLQTN2HhDbFtDo7JmtpuOO4a1s5GNt4GVo2Zk9RhjuxbDSluve+T2mWZsvA3rjqONt14+Vtux6za0AY8RmzrMuoNTS6Ov7devo8YYUWPa5tuE5fWt74ezuHc8eaD+Ysy4h1v3UMsmOXNJ8ei9b92hRtrVauibVsfYansENt9zIkvwKHqvVYV8kUbXILlsDG28Y9/x3tr2nPYZLGlfAOhDnl6d9A5B9yDzvhIk2ByKnafOruPe8t4n650OP88t+IijBZeHXZ+hCDB6Q2OUNxoBacrm28hC3Gj05U3b9xWd51JmLd88dz+TOwuwazYer7yTWZ2lPDdjGx3OvnPNDG2+jT73sWynB6h7Z9IeipQi8pQ8MrVM1kfu5kPvR8Nu2yiuW3+7FBTOd+1jcbqewHZW1lr2Nr40aPlYZo6qwQdEvulC0ojQVnOarLLlyDY7aaULaLl0IEbZ2KgGk7fkwWKrrgSfD8nrRZs2FdxOCIdvqTt266ZswI0+e4PcD7gvXNftrm0yvgVTBryfMUrHYPR1psU4LiMLccPjMrp3jFXe7D1trHtDIydDowtxsLjV0fnxED1IAoHAFJGy3vlH9vLx0YMk2V04s3uG1wU6CbdZM7wuP6V3DkRd14kYe44eTs3NHGUZoJsOHHcMnpNkNEkPpfFQ9cbo8vuF22lytySk7cHI60rnL3Z9oY84OpVTzp/f9csRiSNBL02edv7Popd5v+Rg9IZ6Tlsp//3oF5nXYq2LmSIpvJP8HiH0Xq55oXnMDM1MSNuV/rN0RnSL8UxXEXnuKQlpt63yOFrPDWl6yULjG9t4oGlwQR9mJzkcMHV89MbY/EHcV/Re5FBxDuHMxLgQCqxFCCSBQDBiVI8bJT8XAFt9A/KNSbhjHFfeVKSexMtBi4bX2WU32Un6MJOIGqDRlxiTiHnKCpzoE42vyGfokOM/r0ZWZZ6ofBC3qrd7Ku0cx9PPxL3dWMxpnMR/3/MshV1ZAITkCM/P287fr3yddvfYcdMbz6iyyptT9vKPC16jzanPrUuJePnds1vYUr7W0iF3rbY2Pk7aHl2+13cPaUpa3NvV0DjXsTe6PCttLYnoLg37O+hq1B1GHe4UkvOmGZSIEzcPs5s1jobZnboWfe1bkBhRK7AWIZAEAsGIiUwqiT6JtJcnZpL/aODKv8m9rs4ag4Dc5LnIkj6esaH7DKoWf4txj5bETOVGUtgIJ+374t4mwPqGOyjy5wPQ7Gzl3cKPEzaEbiBWVs3i9w88TlLYDUBVShN/eefzbJ983NK4JirnMyr5X4t/xcnM3hQAm6uW85WL9yEbjiGNH2dd5zjrOAuACxcP+O43Hs40CtQGr9ASqgUg1ZFNsTcxQqH1+vHo6wyrzBoqK9G6eoxopk7RDRvGAd5TN81DEgLptkAIJIFAMGIiPe51AI6KKgsjGQY2O84sfVigEugk0lZrSRg5SXOir+u6TiakzdnKEmw9U08v2I7jl+LfU5IdyOSOJn1InyIpvFbyLiFb2KBU/FhXMY9vHbsfW8+kgeN5V/jh2heoTbF2uN9Ep9sR4F9nb+XlyTtQeuZbrGyczdcu3I9sOLkwfnzi3U5rTy9qgVLAwlBirL/Pde6Jvp6asjwhbfpaKgh269e5N6sEuyc1Ie32QdPgot5rL9ntUDrJoMDYwH25GimgD8n0zxofMQvMIQSSQCAYMZGiXoFkq7ZmHs9wcWaW9LrXNVwz2Ds+eB3ZeJ26k1tHoIZApC3ubTo0J9MUPd+SQoRztiNxbxMN7qu9Gxv6cMY92Qep81iX7+jeq4v52slN0Unkn5ae4J+WbyVgt06w3VZI8GnRMX4y++1ozqRlTTP55sUHsFkkksJSmG3eD6PLa/1rSFaT495uU6iKlqD+nZnqyCbHVWpQYnToqOkd2ppaaNEQtys3JROfMj7mIUmKivuyPg8pkpMu5iHdBgiBJBAIRoRmt6Hk5QAgNzUjB4IWRzQ0XLm9wyOCjdYIpOyk2dHXTd2JmXs0XZkfnXt0VT5LQPLFvc1ZHdOZ0q3f+LU62tmbcyjubQ7Gg5dW8OyZ3uS026Yc5lfzP0EbC97Ttxkns67y7zeJpMUt0/mtCw9jN7SDjA819hpOOk8B4MTJnf51CWn3Sufh6OupKcsS0mZHbe8coNTCOTH2jCPXr6NFeoYUTx0/w9U8F3tHSQRmlFgYiSARCIEkEAhGRCQ/H2z6DY29anz0HgE4ewSSpkQINVkzbyo7SXfMUjWFZl/850BJmsxMRZ9zoKFxznY07m06VDub6+6KLn9YsINILN/ieKHB4+fW8MT53sScb83Yx0tzdon5RhZyJrOcf5nzFqGea2JB6xS+ff5hHIo1ImmPezd+STeZmRWeRVEk/jmK6gJX6O7pPc5xl5LqyIl7m+FAB75W/UbflZKFKzU37m32IxKB6/p3r5SSAtmJSdZrFveFXpdW/8xiCyMRJIIJmwdJkmQkw+QJgxYe+XbDfEBGdZvIsWQzkavIoG7DPEeGeXdi5PQxynNkJleRibj0tgffHs88R4BBPiGzOZhilDXI73SjbGRSQXSdra42mpspVtuGeZCM8oqYOC7NBvaUHGxuffhMqPU6mi1Cz+gvU+fM6Eb75uNKdRbjsuvDM9qCFYTkQOy4jb7GjHIRyTA5PJ0k9Dar7Fdou8leO2b9hnmQBt+0umYFaWF9jsPl1Gucz7o8LEEyKnPlNfjcybu473Lv0/mX5u3k/ZmHYxQaQj6hWE0a5iwxqNxMHiSjFDExYjOsO1auoSGUH0j3nMm7zj853+C7J7bgUh3MbZvMdy5s4cfz3iJs6xXTRj8/sUbnGcWt9mz32YLs9u5lU/e9ANztX8+v0n4Ts4fRROpBvW0JLncfYWHaPQBMSV3G0fYPbtpj5G3H2qG9/jzeDP0GP6V4Nv5Ltw57NcqxFJtYeZKiOZLKryFN6XlYNX0qtDUb1Kpj+PmKiUHkkdgX8Q2rb4DAzJI+v8NG5h6aQdtSjO8Fo/svwzNi9J0T675TNvoyNPpwxkq+Zu67crB7/BHf+9+C6EESCAQjIlLc+4R1vPQgubKtH16Xc5NjVaPvfIw9RwkNZoeWRBfPOuLfe5QRTGd1Q68xw/vFn1rSW/PI+VV9xNEvF31sKI4EieVCRhU/mv8GAZs+AX522yS+d2oLLsUoc/Poc8p1mnqbnjQ5V8llQXB+3Nus9J8lqOo9V0XuGbjl+M9/6mi4iNajDFPzZ2LJh/NaryvcDaE01rF1+XFUNwIQmFyA6rCmt1OQGIRAEggEw0aTpKhBg9Tdjdwa/1w6o4EruzdBZbAp8QJJwka2R7cYV9QQLYErBiXMk6sUka32WGzL9dTb4uw2qMF9Veux93Qp7ss9TIs78dfHXVfn8/jZNdHlny3dxvapiUnGKxgel9Or+cf5r+O36fMYZ7aX8K2zDybc3U6TND5J2hFdXutbjVt1x7VNhQjlPv26lCUbk73xd9FTIgG6er7/HO4UvJkWzKdpa0Nr6enJLiwCd3zP82gRnYdktxGcXBh7Z8G4RggkgUAwbNTsrOgPmr2qZlxM5ZAcHhxp+rDAcGcjarAz4TFkuEuxy/p5aw5cTkjuo1nh3nwnZ51H4/6weHLnJGZ06E+E2x2d7Mo/EN8GB2BGYxFfPn5vdPmF+TvYXXY64XEIhs7VtFr+fsFr+GwBAOa3TOaxa2sMSo0+NY4azjp14xSP5mFlYEXc27zmO4mq6T06Zd75yMS/Z6K9ttccJi3fIje7q/oDIkmWobTMmhiGibuPUYOYhzSREQJJIBAMm0h+fvS1rWZ8DK9zZvT+mIWayy2JIdPda2nblABzBqfmpiSiixW/1E2F/UJ8G9TgrrpV0cWPi3YRTnDOo7SAl985+FA0z9H70w+zbUYCLM0FpqlIredf5m0l0jNxaFPVMhY0JX741c6k3YTRH14sDC7Ao3ri2l5Q7aY6oH8fOGUPea74H3NX01VURf9sJmdbM8RNK+/txZdKxocrXJ95SJMLYuwpGO8IgSQQCIaNkp8XfW2vq7cwkqHTRyC1WpHUViLDrd+IKGqItmD8HfTKIjOjiWGv2s+hGs7iN9leVwml3fp5bnQ3cyYjzoLsFmRV4jsHHiI9oM/jOJNTwcvzdyU0BoE5LqVX89qU3dHlr17YTGYgsQlNu+VuTrr15M0OHCwLLI17m5X+s9HXkzzxt9/W1AjdzRUA2F1JuFPzDUrEgeoaNKXHJWOcCCRndRNSSBfPwTILzpkgYQiBJBAIhk1UIGkatnrrEn8OhxsCSVNVwm2J7/VKcebjtHkB3b1Ow8BeaxSYGpkbfX3FcTbGnqPDzb1Hu/IOJDzH0BNn1jKrSb/RavF08m8r3hV5jsYh24uOcTT7EgBJETffOv9gwhPJHnIfJtLTi7QouDDuc5EaQ5X4FX3Yb66rDJfsjWt7oPci3SAlx4JepEgY6uoAkDKzICkp8TEME0lRcVbqDwXDBVkoHqfFEQnihRBIAoFgWGg2G0qOnrdCbmlBCid2CNVIkBwe7Ml6zJHOBjQllPAYMt29NyAtgasx9hwdUtXMPuYMbbamuLZX2llMWZcuTppcLQnvPVpUM5UHL+rzRSKSwr+sfIdOtz+hMQhGCQmem/khje42AMq68nn82p0JDaHL1s0plz5vzYmTJcHFBiXMokV7kWRJptgd/3lBXY2930PJOVNj7BlHKm/qSR8nvUjuq7X6C1kiWCaG2U1UJmweJGRp8CQEhskLDHRjzDxIRnUbTL6MlcvITFwQO1eR2TxHBuVjbTfMRWSUJylGeaNcQ0Y5ZmLn9IlfniOj+o1y9gw1l9HAZWPXHcnPjiaItTU09NvfVB6kOG135fRakgc7qgY892ZyMBm9H8gaGZ6enB+aRrNyFdXZ27MRq23DPEiDbJ/i6x2mc9l9pk97fYhxqRimHLmpd+bO+t7eo51F+1GcSmxDiFE0i8jpSuNbh++LLr+0aCeX8qtjlIiNYZ9TrB0M8xzFPvBYHV6G6UxUo8Q7MfLqGOVBMrrGDdqWY3WYDlDUbw/x7/Pf5U8OP4NDs7OhdjEXM6s4lnu5f/FYeZCMfjZjbN+fepgFjfOxYWNJcDGHko4SlIO9ZU3kCRuofEX4HDNYCUCJdw5XfINb8hu2bXAVy0iEFR/+jjo8qfm4U3KxeVOJBDtj5jHqad2g7sG5tW6pphIbd+gLkyahnT03QKmbyhv8rsZ8u40Oy6DuG1/Grmt10VWBqYV4LlQadjdIGHzAYn7RG5U1eU9rCoORELFiM4rL6Atv0OKj8+MiepAEAsGwUHJ7M6/L9eNk/lH6TfOP2hI//8gtp5Fk13uwOiI1hLX49mxImsTUkC6QVBSuuuKbb2lSZxFTOicB0Oxq5XRW7Juc0cSh2Pju3kdICutDoA6WXODDGfHP9SSIP9dTG3hpxs7o8lfObyLbn5aw9jttnZx26706Ls3FEv+iuLbXpbTSEtaH/6bZc0iz58S1PYDOm4fZWWDWoNX0zkOSisZHD5Lrau8Q7eAUYfU9URECSSAQDAslr9egwTZeBNKN+UeaSqh95D0LIyXzJleqlmD8h9cVRCbh1XSjgirHNYJyfAXZnTU39R4V7kdN4Lyfzx1bT1mrfk3WpbTwsxXbLMl7KYgPu4pOcjBXF/gexcVvn34Qu2GX7ehxwHsItecJ/jL/EpxqfOecVAR75wqWeObG2HN06GrqzcVmhUDS5yHpQ9akzExIin+iXLPoRg360PLgFDHEbqIiBJJAIBgW0R4kVcXWMPYNGiSbE0ey/iQ23NVozfwjZ2+C2pZQ/JPDTg7NjL6+7DoT17YyA+lMb9ePr9XZzqkE9h6VteRx72V9bkjQFuaf1mwl4Ej8+yuIIxI8P/Nj6jx6UtFJXXlsuh5/V7kbtNvaOePSr2m35mZuML4Oc9XBiyg9+dGK3DPi2hZAoKuRcEA3h/CmlyAZTQOIA1pVZe9CcdHgO44RJEXFWdFj1JCfiSqMGiYkQiAJBIIhowFqZiYAcns7UiT+iU7N4kjpHRIY7qhNePsSMqkOfRhGUOnCp7TEtz1NoiisPwkOE6Laec2ghDkWN86Lvj6UdxxVjq+VeBQNnj22Prr42oI9VKXH14hCYA1Be5j/mPseSs9EqQcqVpLlT5z19yFvbx6thf75Q5ikNnLCWpCGkG6/7bYlke7IMyhhnu5WvT3ZZseTmvgeEa2ud8ialD8+rLNd13sfDoaK4j8UUpB4hEASCARDRktLBYfucCC3xPdGf7Swp/beYIS7Et/jlWzPxSbpTxjbw/Gf/5St5OPRdIvgGkcFihQ/O3FZk1jUpAskRVI4nh3f3qqbWVo1nZmN+pyFupQWPp52LGFtjwVsqoQzkvin/VZRldLIJ8X63DKHamfL1TUJa7vZ3kyVXR+am6NkUxCJ7018Xah3GG5+ApLGdt+UF85703zNRKHdPFQ7b3wIJGd1Y/R1qCjbwkgE8WLiutgJBIJRR+npPQKQm5stjGToOFJuEkidiZ8zlebsveFoD1fG2HN0KA733lBVOeI732la22RSw/qcgYvpV+l2+OLa3g3sio3PHb8ruvziop0otgT1XCWIvPYUFlQVk9WdTGa3lwxfUs//XjK6k0jze5CRaPX4qE/t0P9SOqhP7aQutZ361A4qM9oI2cd+L+9QebfsAHfUzSEl7GVFwyw++f+zd97hbZvX/v8A4CYlUVuWJe+9R+xMJ3H2bJOuNOm8Hbd75Xbe9nb92tt9u3ea7qRpmzR7OdtOnOG9t2VLtvaixE0Avz8gk5QtAZIoEJSLz/P4MSjwxXu4gPfgnPM99VtoKM7Pb3qndxd1fVr61+LYQpqdLQYjxk5z4iinRMVr3DPY17/RtLkAIlnCNf5gHXk/s0fCqP19CIEiqDY/YjYeuJoy0epEnR1BOhs5ex0kQRheB9NIHzOX/YYS4jkcOwe5a6NjG0tt5yYDrme7oYy3wX492U/D12Uohz12CfFcZLxBX27bUL7c4JetK8WtM1auLE9vCz1dQ9qYi4S4GTLfzmItxU6VUyQSnTDM5zISqe6x2FXszuTU93CCoWq8VZ1jGwkOnD62PjQgJ47Kcd9hVIeRVOrY517elUmv2zxpB+rpUuJ6Yg05nAqv3LWSqnAQgD01x9g6/eC4CjMYqcvqy3wbyXgPPVhQYe7JGi48MIsLDs1kVlvVkM87ndKoj9Koj3mtZ955jzmSvDzzCM/O3c/LM44Sdw7vLOUqIS7I+gfQ7fNqJN08EASNOBM8OHMjb9t3OQBvOnwJ3131d9NkvrP375UOcnn/Wlyqi3nxuTwVfB5F0Hc+jVTXh7u0xQjTnWqh1FFDibMKt6uIqNI3orHpuQ1/YJnPK54KkYiFcHmK8ZZMQnVIoA5/wyEXGfDh3m61rRUhUITg8aBUlEJPj8Ecw9k2PIbZv0a/3SzjXSdPc5CMrslGCVuSjgS/gV1Gawmj8fpS3DmMhdzWy8Za9uM77jTOXgfJxsZm3FHKsyJIXYUfQRIkNw5vKQDJSDumFg8MbQElDs1BSihhIoq5aYkBuZhSWbub2e5oJiaaF9HxJ3zM7dKaS4Zc/RwqNbfW6RRFMS+v23EBoC3U7l717IRVrXMnHaw8OpULD87k/IMzKQ8bK3jFpRTd/gjd/jApUaGqr4iKvgDSEH1UPCknl+6fy6X75xJ1Jtk44wjPzd3PK9P1naVCZn3dLi47vpxJkTJm90xmedtMtlWYL3ySFJPs8x5gSWQRbtXN3Nhs9rrMEyRpTh6l1KE5vTWu6RyN7TBtLoBwbxMuzwJEyYm3uIZo70njQeOI2tYCM2YBIFTVoI7RQcoXUk8/YjiK4vfaKXZnKbaDZGNjM2KUskwESewu/BokZyBzFz7Rn//0uoBUiUN0A9Army8vXh+fmd5udJu7aFzavhBpIHS2rWpX3qS9b9p2Ib6k9p6un72T42WFr6R4OkVRD299eRVveG0FvuTQClh7ak+ycdYRjpd30uUP0+WP0O2NEHYnznAIJVmksq+Imp5iqkPF1PQWM7knyOqj0ymNaPVo3qSTy/bP5bL9c4k6E2yccYQHl25n25T89wXLBVlUuHfOej667fUAvPHgGnaWHUXOgzjIDu9ulkS0qOniyEJTHaSW1BEWDDRQrXHNMN1BivQ2UVqtKfT5g3UWOEin1SEdMLd3W64IaHLfsTn1pCpKUDwuxJitoHk2YTtINjY2I0IlU4MkTBQFuywHKRnO/0K6xJGpP+pJmb8QrU9k6o9MdZBUWN6aSa/bUr3TvLmyqOktY+2BZQDEHAnuXbY+L/OOGypcvWMhH123luKYd9CumCPJpukNvDT7MBtnHaErED5z/DA5W7Kk0BLspaW4d9DfJUVgaWM9a/fN5eIDswlGTzlLLi7bP4/L9s9j3fw9/PjyZ+h3x8fnNeaB7ZVH2F/ayNzueqojpVx8YjHP1m83fd4TrpN0Sl2Uy2VMTdQTTJXQ4+g1HjgGeuQ2onIfXqmISmc9Ek5kkqbMBRDOqkPyldbBsVdNm2sosh0kobo677H+seBq0hwk0IQaPIfz61TamIvtINnY2IwI1ecDt3bnXuzpttiakeH0Z1IfrFCwK3Jk6kJ6TXaQRFWkOqE5ZGExRLdknuR1RbSMqqj23h4rbqLL22PaXNlcveecdCrZI4teodc3hBNRoNT0FPPpR69i9ZFMT6yElOKphXt5Yd4Btkw7rqW9jePKUBZVtkw9zpapx/nRlU+xvGEqa/fPYc3B2ZQMOGhX7l3A0qZ6vnP142yeenz8JjcTAf4xZz1feuU2AK48vpLn6nagmh3FFGCnbw+X9l0EwKzETDY5tpg2XUviKNO9S5AEB2XOSbQnzft8ErEekvF+nO4A3iILlOSikYxQQ+XEED0YVIc0qdx2kM4ybJlvGxubEaEUZ/qOCL3m3DUdbxw+LeKlqirJWP5TAgMOLYKlqCnT64/KUlU4BhQoWpxNptblnKo9AthTfsC8ibLwxzxceHghAFFnnCfnbzYYURgIKrzhteX84df/Mcg5emrhHm778B1858bH2Tj7iOk1QbKosnnaMb5/9Tre8KFf8Z2rn6DfHQOgqq+IH/zzzXzsmbW4kxPjvumxklZ2lTcAUBErYUnHdP0B48RB76H09sy4uRLcHVk3Vcqd5jdQjQ6kIUtOD05PienznY46UNcqeLzg9Ro823oc7T3p7WRl0DI7bMzBdpBsbGxGhJrlIIl9IQstGTmnBBrkeAgU8/oBDYWIE6+ozR+WO1B19ZVypzqZSedrdZlb7zSnO+Mg7S8zv0Ae4NKDS3HLmgP4wqydxFyFn+8/paOMn/7xVj75xBXpWqO2oj4+/5Z7+X83PUJ7cZ/BEcxBlhQeW7yL/3jXn9g09Vj672/cuoLf/vkdzG2ZGFLLT0/J9L66vHG5zjPHjy6pmy5Ji6DXJSfjVtymzdWZzEQkyh21ps1zilh/prePp2hkKorjiZpd15rVUqJQcWY5SKmqoGV22JiD7SDZ2NiMCKU4c0dRDBV+BEl0+hEd2uIlFcl/9MjvqEAYkBvtV9oNnp071YnMHeZWp3npfN6khykhba52b2de0uskReSKfSsATbnuqXnmpTWNF+cems5vf/cOljRlHNf7V2zjXR+4k42zze1PNVLai/v4zJv+yY8ve5qYQ6tvmdJdxi/uuo13v3gBklzYS4TdFQ20+jRnZV73FCb3lxuMGAcEOOzRFBtFRKYlppo2VVTpIyJrTnSZswbBZLnGaFYasidgQZpbloMklObhs8wRpx1BOquZGLH08caop08uvYwMmyrk0KsoR7t1xxsd22C3YS8j3V5F+gc37FWk12PJYKxhLyM9uw17+hgdW398LnPn0m9oOLvkkkwESQ2Hhp1DzzajPkaGdht9D7PGO4tL09vJeDeKU78+IZceTEP1MfI7MwuMkNqKotePSKcHhm6fIgbeExWqUprTEhdidHs7Mil2BuOFUfZBmtU9FXHghHCg4hCCSycyl8N6TsiqJ1l1eA5lkSIAtk09SHt5p7lLRaPeHrpj4YrtC/jCv67HMfBjairr4ruvf4zt0xuNj63zcahGjXUM9595cBW477wtvDazgS8+fB3zmychqSLvfvl85rVV8z83P0jCmUI1CMAaXvp0zme59FB6atpW3rbnMgDWnljOnxY9NfjYRpdco0vfEOMP+Y+wKqw57DOSM9hbNHSaaa7tWESgUz6BT5qHQ3BR7K6kR9acGMMeSwbHHqpPUiSauZHjLq4a9logGvz6VJ2mWnr9mdTebk5NqZaXD3kNNHTZ9X4/hiteg7XIab2hhEQSsT+CEvCRrArqrkWG63+WOfjwcxtd94yObbR2FIY4L2R25voD0vtAjL7EBseWzc0KKezbQzY2NgXDREuxc3gyKRqpaP5FJQJiJkXF7AhScaoUr6IplLW6T5hbf9QxK729v+KQzjPHj6t2rUpvP7nwtbzMOVbe+PJK/ufe16Wdo2cW7eU9H75Tc44KmMbybj7yjru486IXSQnaQvC8IzP4zj/egDdh0PXaQl6q303EoSnwnXdyPv6Ex/Q5G90niAnanDNj04wbceZAZyorzU4ytw4pGQ+RSml1ad6ABSl2PdkRpMJPsQNwdGjZFKnyYsObvTYTC/vTtLGxGRFpkYZkEmJRa40ZAafqjwBSVgg0SNoCQ1VVwiY7SKfU6wDaXOal14mKyKwurTA96ojRWGJ+b6eZbbXMbNcWhsfLWtk3qUCV1lR4z9Nr+PijV6b/dP+qLfy/Nz1I3FX4kvigCTn88aKN3H7r34kM1HitOD6F793zJvzxofs1WU3MkeTFybsBcCkOLm5abPqciqBw1KvVbnlVL7WJSabN1SnnuQ4prJ2rnO4AkjPPQgnhftSE9r0TJkANEoCzfSDdXBRJlRXrP9lmQmE7SDY2NoaogFqknfyFvl6TM+HHB2eWg5TMcwRJQCAgajLYUbXb1P4lANXxrPojt3lOS32oFm9Ku0N/qOwISh6ac16yb1l6+8lFr5kaHcuFt7y0inc9d2H68R8u3cAPb3gSxSDFsRDZPqWJ29/6d/oGVO4Wn5jMVx+8kTz1Ah41z0zdhjKQW3Xp8SV5sfOwJ1NHNjNmnoJer9xBUtWiVflwkLLrkCyJIp2qQyouAckg77kAGKRkZws1nFXYDpKNjY0xHg84tARuob/fYmNGhuTSHDpFTqIk89svxy0UIwra+xWWzetHdIqypFbvpKLS4Ww1ePbYmdKbiVQdKmswbZ5TCCosO66l9EWdcV6Zsdf0OcfC8iNT+MCTa9OPf3LdOn5/2YaCdeZGwt7aFj552z30eCMArG6Yxjs2nmexVUPT7utlT4UW0SmPFTM1ZL4K36kIEsBkEyNIoNKd0n7TXjGASzA3hTAW6Uxvu7JuMuWN3h4ATeAmUJT/+UeJoyuTbp4qLXx7bUaO7SDZ2NgYonp96W0hGrHQkpEjubWLlZzIv5SyVwymt6OqyYp/KgRTmuJTyNGDLJqXzjU5lFkINhWbn143vb2W4pgfgN21DSQdhZeqVtVTzFfvuQnHgJLAny9+iXvPmxg9mow4VN3OV1//EPJATdJ/vHgBK45NsdiqodlcfTC9vbx1ps4zx4ewFKFX0hbHNclqU+uQQkrGaSkWzVV3S8R60tsub9DUuYZC7cucr4Wiwnc4HL2Zm29ysd9CS2zGG1MdpBdeeIEbb7yR2tpaBEHg/vvvNxzz/PPPs3LlSjweDzNmzOBXv/qVmSba2NiMAMWX5SBF8huNGQuC5EKUtJoJOZH/iJdXzEiiR5UeU+cqkoM4VK2IvsdhYrRKhbqQluITdcTo9Jlf17W0MbPQ3TElP4IQo8GVlPh/f7uZYET7fbwy6wh3XrbeYqvGl63TGvn9RS8BmnrZ/zx8HeX9hbcQ3F51JJ1mt6xtlsGzx4dmVwsALtVFRco8x6VPznKQJHMdpPggByn/zWLpzxIAChR+TY/Um7m+yMHC+13YjB1THaRwOMzSpUv52c9+NqLnHz16lOuuu441a9awdetW/vu//5uPf/zj3HvvvWaaaWNjY4Dqy5z4hUjhR5AkV+bOoxURJE9WBClmsoMUTGYWTN1O8xykkngRRYkAACeKmnNSwh4pS49nHKTt9flpSDsaPvHIlcw7oUXVTpR28//e/OCErDky4i8XvMwr07TeP2URP1956AYkI53pPBNyRzgSbAZgcn855RHzF9cnnc3p7dpEjWnzhAY5SBWmzQOQSoRRZC1S6/IETZ1rKAZFkAKBvM8/WqSsCFKqpPDttRk5pvZBuvbaa7n22mtH/Pxf/epXTJkyhR/96EcAzJ8/n02bNvH973+fN77xjaObXBCG12/PoReR4X6DfkCGx9aTiTRyZ4004/X66uTSQwnjnj/6fZDG3ucI9Hsd5dKfSTv28PuMeyjp7kYx6u+kN3ee+yApRZkIEvHwmG0z7h2lv9/oPVUHeg2JvsyFKpXqQ3GqI+hzNIJ+Q8Nx2livlLnzGpF6wEDMQG9u3T5FQFk04yD1eNsRXKfNZVCxrnf87H31XZkF4MnSE4gu2bjPi87cgoFdwXCAaZ2a89FQ2Ux/MET2R5hLjxmjliTG4wWWH5rGDZuXARBzJvnKO/9JJBhGMvAcDduh6DkeRk6Jkdeq8zXUm1cFvnnzI9xxxzup6itmaVMd733pQn5z2QuZ58gGr1uvXZZRnxeD8/ip7+mO6iPM6tGinAu7p/JcyY50s+bhEA1aqei95Se8LTAQ8KhJ1bDVsWvwsfUPrfdxaAzM3UPGQSpylKM4xqfH0nAk4r14fOW4vCXDXKeMvsTDGycajFWjWRH/4uIzrtGGv12964/RWKNrxBCvS+rP3DCUg/7h1xRGzYyU4b8Nej3ERnRsoyZmeutOozfNaM2rd04yay2e649jgIKqQdq4cSNXXXXVoL9dffXVbNq0iWRyaBWoeDxOKBQa9M/GxmZ8Ub1ZEaQJUINkdQTJKwQBUFSZuGruOSmYzNxR7nGZJyc+uTejoNVUclLnmePD4mOZNKkdUwsrvc6ZlPjkv65JP/75jes4UtumM2Li0+uL8tU3PERqwKN428ZzWXG0sOqRdlQfTW8vaTNPWe4ULa42lAE3pzZuXgQpSZyoojkOZtcgQaYOSRQdOF35jYqo/dkRpMKvQRKicYSEtj6V7QjSWUVBOUgtLS1UVw9Wn6muriaVStHRMXTqyLe+9S1KSkrS/+rr6/Nhqo3NvxWqb2KJNDicWREkC2qQPAMOUkwNoRrdbc2RYEJzkBQUep3myZlP7slIiZ8Imu8gLRnkIB3UeWb+eevz51PfoS1Ud01t5NFVWy22KD/srjvJry57Pv34k09cgUMunGXE8eJ2etza731++xScsqlJMqTEFG0Daa0VyXKcinkNdU8JNbgFL27BZ/Ds3IjHMsIyeU+zi0RQ5YGIx0RwkAAppKXZpUrsGqSzicI5sw1wejhcHQjvDRcm/8IXvkBvb2/6X2NjYXcrt7GZiKjeTMPAieAgSVl3PeVkfiNITrw4BE0gIqr2mDuZCiUDNUghZzeKYJBKkcM8k/q0m1fd3h4iLnO/A4IK85u0CEDIG6ahynyHbKR4Yy7e+vz5AKREmR/e/JhhhsvZxD9Xb2bXZE3BcGpnOZfunWuxRVkIsLOqAQC34mRmt5ny2xon3ZpQg4hIdcK8vkGDlezMbaKaiPakt10eC4QSBqJIE6EGCUAKaedDJeAzTOu3mTgU1Gm9pqaGlpaWQX9ra2vD4XBQXj50WNntdlNcXDzon42NzTjjyuq9EY9bZ8cIER0Zh05ORvM6t0vI3EVMqOZGrzyKD8dAYVe/o8e0eQLxAC5Zc/raA+al8Z2iMlSKN+kG4HBNU14EIUbK2u0L8Ca09+Lxc3ZwdJL570choQrw66zao2u3L7bQmjM5VJZxput7K02fr9OZcVxKU+apvoWz2gV4BXMjK8lERnjA4cx/VESNaedsweMdt3oSMxHDsYENAcXjttYYm3GjoByk888/n3Xr1g3625NPPsk555yD02le6NrGxkYf1a0tCEkmEVTD0mLLEaWMQ6fIsbzO7RQyzlkCcyMtvlTmDmvYYZ4zVhoNpre7vT2mzXOK+o5MqnVjuXmNb8fCta8tS28/fO6/R2rd6eyob6KpVEvnXNEwherewrkx2ViccVjrQ+Y7SD2OjOMSNNFBOlWDBOAVzI2spJKZ85bD6dV5pknEss7ZrsJ3OMRoxl7FV/j22owMUx2k/v5+tm3bxrZt2wBNxnvbtm0cP34c0NLj3vnOd6af/8EPfpBjx45x++23s3fvXu68805+97vf8elPf9pMM21sbIxwag6SkCj86BGA6NAcJEVOGiv4jDMuMvUBSdVkB0nO3EmOSOalEpZGguntfDhIdZ2F6SBNb65kwfE6AA5NauXA5GaDEWcpAjy2RFNsExG4ZsdCiw3KcKKoMy2cUB8yVxIboNuZcZBKkyY6SKpFDpLL3HqnoVDjWQ6SxzP8EwsEMZq5Lipe20E6WzC1gnHTpk2sXbs2/fj2228H4F3vehd/+MMfaG5uTjtLANOnT+fRRx/lU5/6FD//+c+pra3lJz/5yeglvkGTvB5OmtooZGso1a3jV+Yi442B3LaR1HYukolGMpJGctk5yGkbKlQayWHrjDeW2jbYrytPrj821/16tud87FFKcavugZN+MoFRHbKuhHiOMt+nZLyN9mccpBiqU/ub8ffMQExBR4o7W6bbSeaOa1wKo0oKgoGE+Eiltk/HTyb9JeoOITrPdAaNZMLFEcxdnsgs/ELFnThc2jxGUt16v1y9sVO7Mnf+WyadxOVK6c4z3gwl5wtw/eal6e0nztuC03Xm+20kyTHcsdP7dXSlFQOZb12JcKP9RhLip50Ln1i5k/e+cBGiKnDNzkX88ZKX9BV9dWTAjSTCdb9IMOhWb8KZpKWom9q+cmr7yxElAVlHZl8xuG7qXpKBHjHjIJXIJYPOn0ZvqdFSI3t8mIyD5JECxudKgy+iorM/qWRHkHxnzGUoVa+zXzH6MFUVMZ5Ji1b9HtTs3uRGqtM6+43WEkYvbLh1jBhLpLdlv2fI9ZCRlL3uGszonGH0HTZaO+pKjBtdOA0+EL0XbtQzzii3etjXNT6xH1MdpEsvvTQtsjAUf/jDH8742yWXXMKWLVtMtMrGxmY0qJCOIDFBIkiSlHGQ8o0rS2EqaXqKXVYEyWFeBCkYKU1v9/h6TJvnFHXtmmRyzBmns8T8+UaCMyVx+aYlACQcKZ5ZudNii6ylvaSPTTMaWH14OrXdQZYeq2fbtMIQSWosaae2rxyn4qCmv5QTxZ3Gg8ZISpQJSX0Uy0WUJoOmzRMjgqqqCIJgegRJkRMoSgpRdOBw5j+CRFYESXB7TNYBzR0hO4Jkp9idNRRUDZKNjU0B4nSlb6MKiYTBk61HEJ0IonbvR5HzK9AA4MxKsTO/BilfDlIwvW22g+SNuynv0+Y7UdGKahClyhfn75xHcUT7bNcv2UO/L//Od6Hx2PKMk3jdtsIRa2gsydQh1eWjDmkgzc6v+HCZJPWtohBDC6WY7SABpAbEbaxwkAal2LntFDsba7AdJBsbG11UlyvzIFn4DlK2QIOcsiCClEcHyZ8nB+lUDVK/u5+kY+im3ePF5CyBhqbKwqk/uubl5entx8/79xRnOJ0N8w7Q59F+Y5fsnYM37jIYkR/yLtSQVYcUzEMdkgcfgmHeYW6cqkOyQqRBHRRBskAkYpTYDtLZie0g2djY6OPMLHqECeEgZS5QVqTYZdcgJTE3guWRNWdMQSYumTOXoAoUxTSVspC31+DZuVPVnWnp0FzeZvp8I8GREllyaBoALWXd7Jh5zFqDCoSEU+bZhfsA8CZdLGwyv+/QSDhRkmksX90fNH2+XkcovV2UMk+COzpQjCMKIi7BXMdBTg1IbQvioHNqXshuJeEufIcjuwZJ9RTGTQKb3LEdJBsbG32yCyHl/CrCjQVByJRWqmp+i/sBRJwDcyuomPt+ORTtYpwUE8aF7GPElcpc8KNO8x3OQCwTgQv5zO0jNVJqO8pwDKim7JvaZNp7PRHZm6XkN6Vz6H6F+SbkztwsCCTNj0DExMyC3q2Yt0BOkYneOjC39YmiZM6domhqufqZyJm5BclAjaIAEFKZ87zqKHx7bUaG7SDZ2NjoI2ad8JUJ4CBl2ataYK84oH0jY75z5hyod0iJ5qW9uVKZO7gJh/kiHYFYZkHb7zU3RXGk1Ldm0rSO13ToPPPfj2OVGQGEqR2F4SAlpRRxSftN+BPm17DE8+QgyWqWgyScvQ6Smn0jTsqzczYGhFTmvbIdpLMH20GysbHRRc26gyfYESRDpAEHScmDg+RQzXeQPMmMgxTPg4Pkj2YiSGFP/kU2hmJqtoNU1a7zzH8/jldkO0hlFloymH6X9t0pSpgfQYqLmRQrt2JeSlh2BEn6N4kgMQEiSKQyMtm2g3T2UPiu+VgRhOEbGOTSLwj0mxcY6M0b90nSaySRw1iMehGNfSyQU58kw7mNZPh1exXl9rp0eywZ9VAy6Llg2BNIZ79hfyfDfkI6Y0/bpzozb4KKkmOPJX1FMuP3xKhPhQpZFyhFSKGcGjOSsTro9TLK3ifKAw6SkERwaBdOURq+zwQYtIoYbqyaSbFLiYl0b6LTkXR6wIB+PyJJVAlkXSZS7hhuZ1b6i4HCnF6PpeEojmfVcBWH8OS5BxKAclr/jWltmchIS30LHvfwDqlhryKD3h6yznjjsUb9TnR6LMlGY4f+e7gkTJc/TFnYz9SOcgTnME/M4RpgeH1Jnbm/zx2lPFqMP+HRzgFjXA7oTX2qp0/MmXGQXLjS5zGjO9D6v8wzxyezboRIklO/z5JRvyADu5SsaBVOB8qgr7xRjunwkxu2vpGEwV82hzToOj3c9zC9X68PklHPHqPv2XDDs/oIqU7HkMcxum7q9vwxWKcIRv2CjPbn0IPJcM2r+4HkuBYf6xp/hNgRJBsbG30mXIpdVgRJsS6CZHaKnahKiAOncFk0TzzDlcxOsTO/BskfzThI4UJJsWupArSeN82VXRZbU3g0DqTZlfcHCEQLo6i+f6AOyaFKeFPmFs5np9i58pRiZ3oESc2c6wVLI0iFfx8/uwZpQkS8bEaE7SDZ2NjoomY7SBMixS6rBkm1ogZJW7iYnWLnyFqIJU10kNxZNUhxZz5S7PwARN1RFIPIWz4QFYHJrVoEqbmqk5Sj8H8D+eZYVaYua0qB1CGdSrEDCMTNTbPLTrHz5CnF7myuQRp0nZkADsdgkQZ7WX22YH+SNjY2+khZpwnF+gWrEZbWIKkCItoFXcHcfkGOrIaUpoo0JPMr0uAfEGkIewuj/qiqoxRXSnuvG2vs+qOhOJ4l1DClvUAcJHcm2hkwuQ4pLmXXIJ0dKnaqlSINWZkKE0LFTrZV7M5GbAfJxsZGn+wCGaMc7kIgO/84z/ZmN29UjYoAckTMOn2rgnmOq5iVPK8Y1DONB46UthhLSflPjxwKdzKzEO33FYbTVmj0ZTmznqS5C/eRkhQz3x+HUVFmjshZcv6iUdFsDqhZVUuiycs3NavYR9ArkjSD7Btx+Z57LChZ5/qJYK/NiLA/SRsbG32yq2LHqfjRVLKdojzbm+0Umd3pXslyigQTF2WKkLX4M3mhCZByaAtbh1wYtQcRTyYS4YuaLxk9EfHHMu9L2G1+lHEkZDtFSZOdbYnMXLJgXgqmkLVkUwwlHnKcK2uhrxopI4w32YX/+Z57LGSLMkwEe21GhO0g2djY6GOhwzEWsu+ymu2kDDV7Zm6T7/Dm6W6yLGYWfJKBStp4cCpy5EgVRqpK2JdxkPy2gzQkgVgmDbPfa76Qx0hwZjnYKdHcujEp6waFbGI0N/ucoprsIGWf6/PuIFmYBTAmsu1VJoC9NiPCdpBsbGz0mWAO0mB783yKEzJ3ds12kLIjO6ZGkMTs9CHznZZkgUWQou5EOlrnLxCFtkLDn+UgFUoEyZkdQRLNVpTMiuyYme6adcPH9AgS1qVWCxPM4RgkUz8RHDqbEVEYVyAzEBh+MWfUc8FoUaW3SDTS0c+hB5Nxzx6DPhY6+42PnWs/IZ3XZdAvyLhPkt57pjt0BD2Wht+nGPZYGvuxtePr7Muhh5LR+DPsyn6PRMG4/5Nz+AuEkV1GvYiM+iDhUCFb+UwS4JQ9BmP1+hxp+4dfkIjZY2UFEBEEAck5sj5IevuH62MkCdmKVsKg/kSDnmcwt16fJBEVyZmZxy2oeLIeSwZNTfT6JInD7FMGHCSn7MDrHF58wqgHkx5G/YROJ+qN4Y/4CMQ8+F2JM/okjebYen2OINNbZ+ix+ics2aCXkd7csqQ/Vq9PUlEi4yBFA9H0937Q+Fz6Bxr5/0Mc2pl1Iku4UsbnjmFQdK7Jp76DQtZ7kxLlrHOg/mc9+j5JWY6YqOi2kcnFfRJVBq1lFHFw/zsjH0Dv9yEYODyqyiBhIBVl0HXa8Lqq10fM6A03uj4NY7oqDXYmh1wPGX39dHsR5fj7MLq26Z3PDNasgtF6Wu98Z7TWNmyaNVwfJP1hI8WOINnY2OgzwSJI+awDGnr+UxEkc+dW81SDJGfdfc9LDVI6xa5w7t+FB9LG/BE7xW4o/INS7AojgpRdg5SS8pliZ95comU1SHmOikzgFDthIthrMyJsB8nGxkafCSfSYK29qgUpdmYqZ2Ur1+VTpEFSJASDaEu+iAyo1/miXuM7wf+GZNdmhT2F4SBl1yCZnWInZSs9niU1SIOU6+waJH0mmr02I8J2kGxsbPTJOuEbpogWAKoqpxvECiY3Uxxy/jw5SNkRJDNrg5RBIg3mR3VSjkxanTNVGJLRp4QanCkH/oi5PXUmIqX9WnNfRVCJuArDQXJlRSDNjyDlx0HKZwRpkEhDvu8KTLDWEoPKFyaAvTYjw3aQbGxs9BnU1bxw0p6GQ1VlBEFbsOS9fwcgDzRzlFTzGkYCqIJKUtQWow7ZvNSvmCuS3vbGfabNc4r+QF96O9gbNH2+kdBY15zeXrBvpoWWFB7FYS/TW6oAOFrdblznkSfKIkUAhJ0xkiY7SD454zRHJPN6ZTnJpDImMdcRlcTM+UuREzrPHH8ER+bGiJoyt+H2eKC6MtdFIVEY/dtscqdATmU2NjYFS/YFylEYd/T1UJTMxVwU8686lhK0aIMD8+tVEgOLMXfKPMcl4sk4LL5YkWnznKIz2JXeLu0pM32+kbBt0f709rKd8yy0pPBYeWAG4kCx9GtzDltsjYakiJRHigFoC/SYPl9RMpDe7nOGTZvHTcYRi6vmNi2WpMy5MyXnOSrozLq5lMyvczYWVFfmuigmCt+hsxkZtoNkY2OjizDIQSr8CJKiZC7momhuFGcoUgN3dkUciEayfTkSd2jRHVfKO7yiT45E3eEsmWvzHaSu0s70dnl3uenzjYS9c44Qd2kLtWW75tp1SFmcs39Gevu1OUcstCRDebg4XZfXHug1fb5Ayp/e7nfkyUHCZAfJkbnBI+fZQRKcWRGkCeAgKe6MvULcdpDOFmwHycbGRp8sB0mdEBGkzMVcsMJBEjILFwfmRrBOOUgiEk7ZnLlUUSXq7gfyE0HKdpDKCsRBSrpS7J6rRUdKe4uZ2jTJYosKBBXOOaA5SFFngl3Tmiw2SKOqP5jebvP3mD7fYAep37R5TjlIKqr5KXYDESRVVQZF5fNCdgQpUfgO0qAIku0gnTUU/u3gsSIIwytYGRWaG/ZJ0tN1Nzq2/m5zjz38rlx6DY1s/9j2gX4/INDv6WPUq8jw2Drjc+ljNJL9esfPpc+R0bFPH6uSlVPtdOr2OTKyzbDPkeGxDfo5OBRUMZZ+LDpccKoni8HcoiOHXkVZYxU5mm5C4nY4UaSUbq8hAIfOsfX2pVyZxVix4CLs7DvjOXrjwaAP0kCfl6gvhD9WjC8WwOdIoQ70p5AMCtKH63Wkty9a2ZrergwFCVhQ9D9UH5e9S3ezYud8AFbvmUX7jGMjHpuNbHDC0xtv1AcpZdBPSG/ulEEPpaGOPf1ENeV9mtO8fXYDqi8+7KJCTg1/fMWg34kyyt6ElQPpdQBtJT3655WcAq/a4KJUJsUu5Amnz4GKYahxdH2S3AO1TnFiyAbnQqPlgJ6WgKJmHCRZjp95rTJ4WXofp2KkTKmqiJ7B9U+D5jeKlOu9sBzshuHXKoon68ZhMjn0esjwAzHutzUshg21cljT5mC38bGNPssxHnucxKTsCJKNjY0+Ey6ClFWDJFhXgwQgqebWISUcGQEFZ9LEOiRvCNDU8txxv8Gzc6MvECLp0D7D0q4KU+caDTuX7EtvL94x30JLCoeV+2altzfNLYz6I4DK7AhSHmqQTkWQZGQiDvNS305FkMxOr4OMg5T3+iNAcGQcJDVZ+BEZO4J0dmI7SDY2NvooMiinojCF7yCBmnaSrKhBkrNSXxx5dJBcKfMcl6g3S6ghWqzzzHFAVOkp1YQagj1lxnc/80RHVSfNk7To1pyDMyjpMT/dsNBZmaXot2le4ThIVX3B9HZbkfk1SEVJ7bfX74zkGJEaHlEVcQ2k7ObDQXJkRZDyjZCdYpeaACl22TVItkjDWYPtINnY2OgiQCaK5JwIDlKmDkkUzVeSO51kVg2SUzVXFjuepZjlSZq3YO8t7kAeaLZZ3Gd+VKerrB0AR8pJWQFFkdZf/DJ9RVpa48UvnGexNdZS11rBkkPTAWgu7+JkRZfBiPxR1619Z1KiTJcvZOpcDsWBf0BFss9pXv2Rh8wNENMFGkR3ukWCFQ4SrkzkX50ANUiKO+PQifHCt9dmZNgOko2NjTGJgbQxV/4djrEgK1pkRZLM79tzOgkxsyBzqeZGWyLuzKLUFzNPEjvs6043iS0Jme+wnKjL1PfUHyucvkPbl+/G3699p6564hK8kYnxezCD2568OC3v/egFm02LnIyW4qiPSSFN3ONoeYthfVOuVMbKEQZefLun0+DZYydASXq7XzA3KuZyZWqqEskz6xrNRvBmzttq1DxVwPFC8WfOA2J/TOeZNhMJ20GysbExJj5wx9LlmRAKx7KsXVQFQcp7FCnbQXIr5jpIYU/GQfLHzFN86yptSW+XdZuv4HZ8akYuekoBOUitNe1svGATAP6Ij6ueuMRii6yhrrWCS7YsBqDXH+bhi16z2KIMc1rr09v7qxtNn686mrlh0ObpMG2eIjWY3u6jx7R5AFzOTDTaCgdJ9GaiZWosovPMwkDxZxw6MWx++qNNfrAdJBsbG0OEUxEkUQRn4d81P+UgAUiSuaICpxMX8hdBirp6UQQt9c0XNy+C1Fvcnk6xK+0x30Fqrj2eFmoopAgSwEOvf5KUJANw1ZOXEOjL7/erEMiOHv3zspeIuQsnrWhua116e39NHhykWMZBavW2mzZPgGB6u1/oMW0eAOcgB8m8tMHhEDyaw6EmYiCnDJ5tPXIg059K6rcdpLOFs1fmWxSGlxAcpWToaParhlLc+nOrerLSRmNzOLbRa9YdywhkvnVfl3US4kZS3bpS2zmMHcl+Paluw2PnIAM+pJR2InPSV30eCA+fRqAn5Z2zjLdTX1ZaGJC0VpTMRd3h8pFS2xENji05ZP39I5XiVkMopBBx4FGLcTlk3bEALmn4uY0kwqOeLvzRKvyxcrzO5BmpTkZS3HpzZ0txh4ItlHbVURKqoEhQUBwpHCbIfAPghJYpR6k/MpdgTxmT+gP0leavxkVPajs2uZmXL32Ji55egzfm4XVPXMyDtz4worEAqRxkvhOy/g9flvSPndQZ7zC4fiREbWz9ySou2bIIgN5AmCcvfRmXU0aW9X9fKZ3PWzZIg5MNLqtK1vVrbpvmICmoHJ7UiGAg36/meJ+4KttB8refdv4zuHbpSVIDStb4QDKYlqnudfTkpHYNmpT3cLjcWQ6S3HfG9cbo2LpK2/ofB6oKwkAESYlGzpzbaLzuemDsawkY/rqr+DUHSYjEAHXoeQyu2YKOGI3R+svQcKOvuM41WzA4tqoYXJNzaV1jtFYf9rxhy3zb2NjkiywHCZd3+OcVCLKSFUES83yHX1BJilpaisvkFDuA6EDdg0Nx4zJRqKGn7CSgSX0X91abNs8pTk47lN6ubZil88z88+TrniDp1IRLLl53CcXd5n/OhYCgCHzobzciDiya7r/8RWKewoke+eJu6ju172ZjeSsRt8kCAypURysB6HeECTvNix4UqVoNkoxMBHPT3rJT7OL5TrGTHAgDIg1qrPDrjwCUgQiSZKfXnVXYDpKNjY0x8ayI0QQQarAyxQ4gIWpF1A7Vh6iaq/wX9WYKw71R8+qQekpPpreDXbWmzXOKE9MPprcnHy0sB6mnvIcNl68HwJVwcfX911hsUX646sWVLDw8DYCTlZ08fOlGaw06jdmtdYgDd4/zkV4XSPnSCnatXvPqj1AzNUhhIYRq1Dg0R6ysQTqVXgcTQ6BBFQQUr3ZNFO30urMK20GysbExZsJFkDIpdpIU0HmmOQxSslNKdJ6ZO5GswnBf1DyFuVMRJIBg12TT5jlFS/1RZEmrP5i9c6Xp842Wp25cR3wgQnHhMxexePNiiy0yl/qTVbzr/qvTj39x6wMkXIVVHzK3eUp6+0A+6o8Gokdgbv2RFz9ONCnpPpPrjwBcDs1BSsnxQY2384GQLdAQnQACDT5PupzDFmg4u7AdJBsbG0OEeNaFylP4RekpOdtByn/6U0LsSW+7ZfPEEwAivszCLBA2T0Chp6wpvV3ZOt20eU6RciU5OncXqqDgjnspbzE/ajUa+kr6ePSNjwBaE8//+Ol7mLdjvsVWmUNlR5Cv/exd+GPanfKnztvMzrlHLbbqNFQ4p2EuoNUf5SOCVN+fuVHQ4mszbZ6gmokMh4Ru0+YBEBBxuTQHKZE0t4fUUIj+zPlajeZfIGK0yMWZ66HUV/gOnc3IsR0kGxsbYyJZFypv/iMyoyWV6k0XQDsdwbzPH5UyiyWvXGXqXH2BjONS3F+n88zciHvD6TS70s4pOOPmRxKbZu5PFwnP3b7K9PlGy3PXPMurF70CaE1t3/ej9zNzX2Gp7uVKccjPl37yHsp7tYXrgalN/PbNj1ps1ZnMaamnqq8UgL21DfR5zV+szghlIlYNReY5ZGVKpuavU2g1bR4Aj6sUUdAUBaIx8/o6DYcYyETclX5z+z2NB3Iwk47o6M6/JLqNedgOko2NjTHRrBO/xzwhgPFDRpa1u58OKZj32aNSJqrjkSt1npk7SWeE6EDD2KL+OgzlrXKgdZJWFySqIlUt5jsCBxdvRhE1lb05288BHaUnK1BFlbve/1e2rt4CaPVIH/rBB5l6aKrFlo0P3qibL/7s3dS2aambTdXtfP3Dfy4oYYZTXHQwk+K4Yc5O0+dzyU4mh2sA6HB3EXKZF+0oVzMOUpfJDpLXlYlWReP5d5CEomB6W+nryfv8oyXbQZJsB+mswnaQbGxsjImFM/qqEyCCBJCSewCQJB+C4M7r3DGpAxXt/fKa7CABhAbuXkuKC3/EvIhVa+2B9HZV8xzT5jlFNNDP8Vn7ACjuKaf22AzT5xwtiqTwpw//kV3LdgHgiXn4yPc+zORj5tdpmYkz6eAzv3o7M45rr6Mj2MtXPvpH+gKFl0bkTjpZfURLb4w4Y2yett/0OaeE6pAGtJuPFh03da7ygQhSgrjpKXZet7UOklg0wSJIpXYE6Wzl7O2DpIeBFr6hNrveeCOXM4ceS8bHHvvcOfcHyGF/7r2K9PoHGIw17N80tn3asQ3259AnSa+PkTnHVjUnyVsE3qIx9zoarz5HwyFmjU8p3YB2J9/lKUZBXxHJodMPCMCp0yfJcYZdKRJSN265HK9cideRAh3lKafO3E5R3y6XJBMraYCOpQBURidBMJPuY9SryKHTZ+n0sZG6PaiCgqCKTGqezVGnvoyybh8k9L8Lp8YeW/ES0w4sBGDJ1nMJzd6jO248MOplpJx+snXC3//r53i/83Fm7pqPL+LjY9/5CL/+6vdon9wy6KkpRf/HqdcnyWXwXTDqsXSql9FQJLPsEhSBj/3mVhbv16KEff4w3/rk7whXdzBcYqXesQFEnT5LScGoSYz+7lX75+BJaSIGr87eQ8qbSF8uDdrmGDJcn6Tp/fXp7SOlxw17vA2F0fdMVMGj+vCjpTd2iW3pHne59Dk6deyh8LozNZPRZOeQ1wrDXkR6102DsWIgCIASi6DKyTPWW3rXHgBV5z1VDd6UsfRYSmU5SGJvaPjrvlHvKJ21iF6PJO0JRh+2/m7dyLzhetjg2HprLKNsB6O1eq4/bgPsCJKNjc3IOJVm5/EbN3ArAE5FkAAcUmne5485tDokERdOOWjqXOHizB1sf6he55m5kXLF6Kk4BkBxdy2uiPnplg2LtpDwaFGL6TvOwRErTJn5lCvFnz/zcxrmaP2bAn1FvP8bt1PWYn4EcTyRUhLv/cObWLVFS1mLuxL84BN3cqLWPBGCXLlo/9L09otzd+Rlzhk9mTTKhmLz6o/Ks+uPRHPT6yCTYqcoKWLJPEdwRAnBp2UoTIToEdg1SGczhb/KsbGxKQyyFYU8hZ9ml0plUlGsqEOKZwk1uFLmCjWEizJCDYG+KTrPzJ2OyZn0pfIT80ydC0B2JTiy9FUAnAkP03ecY/qcYyXhifP7z/+UpumnnMgg7//Gp6iZIOl25Z1BvvC9D3DJi6sBSEkyP/7IHzk809wUslyo6A0y76TmrDQHOzhcfcL0Ob1JDzVh7Tfd7GsjYmKD2HI5fw6SgIjHGQQglujGMOwxzoj+EoSBiIU6wRwkIZ5AiJrcmNgmr9gOko2NzcjIFmrwFr5QQ3YEySmZK7U9FKciSADuZI2pc8mOGFFfCyoKgdA0BNm87OmOyfvS2xWNC02bJ5sDq9ent+e/dFm+122jIu6LcucXfkxLnbZQL+2o4OOf/x9uuuM2/KHCvLEgpSRueHQt3/nSZ5h7SJNwTzpS/PL9d7Fz0QGD0dZyya5Mj6wX5+4wTjUfB2b0TE03pD1aYq7zWKFkzh1mO0iDFOysqD8aSK8DUPp78j7/aFHJOEhSd18+vno2ecR2kGxsbEZGOKsnhj9omRkjJSlnLvBOh3kNVIcj6sw0VvUkzZPfPkVv6UGEgVN6Ua95fYq6qw+THLhjXtWwzFRn7BQddQ10TG4AoOLkVOr3LNUfYDGR4n7u+NIP006SqIqc99SlfOYT3+SSh69AShZO+e/8PbP5+v98mlvuvQ53Qqvj6Sjr5huf+wWvrspPutpYCUR9XLpTiygmxRQvzjVfvQ5gUcfc9PbBEvP6QYmqSJWiRR+jhOkXzI2qBNwZZywcN6/x7XBIJRmBCDlkrhjFeKAU+1Hd2m/G0TkxIl42I8d2kGxsbEZGOOuC5c9/Tc9oUdV4OorkdJib4jYUcakdWYgB4E2Ym/YG0Je1UCvpnqvzzNxQHClap20HwJnw5SeKJMDWKx9MP1zx5E0FJ/l9Ov3BED/732/y2K33Efdo3wNP1MuNd72Rz3z2f1j42lJLI2HB7hI+8Mt38JnvfYhJLVoalyIoPHH5ev77a//HkRnmN1rNlau2nIcnqS1Qn1+wlV6/+Y1F3SkXc7o1NcV+Z5gGEyNIFcoknGivr1k6bnp0rMiTaTTdH202d7IhkEoyN7KU7vw7aKMlVZm5Djpbuyy0xMYMbAfJxsZmZPRPLAcJIJEaEEoQ3UhiML+TCyoRp1Yb5FRKcMglBgNyI1SWSYUq6TLPQQI4OXNTerv2UH4auDbO3057neYEljdPYeru5XmZNxdSrhTPv/5xvvejL/Ha2vUoA6qAFa1V/McPP8gHv/lJphycnj9HSYVpR+u47a8387///TnOfTXzHh6c2cD/fPnH/OW2B4n6YnkyaOwEoj7W7tS+e0kxxaPLN+Zl3nlds3AqTgB2lx1AMVIQy4FJcubGSrNkfh1YYMBBUlSZSMx8QYjTkYKaoIkqp1AmQAQpWZlJ3Xa02Q7S2UbhxPltbGwKm0gIFBlEaUKk2AEkk23g1vr1OKUqZKUnr/NHnI0UJWYBWhSpz2teClDS1Uc4cAJ//2T8fXU4kj5STnN61rRP3kfC3Y8rHqCyYSlS0oXsNLl5qABbr3yAq37/SQCWr3sdxxZuHV6vuIDoD4a49wN/ZuNVz3H9n25h5l7tOzlrz1w+/pXP0lnZwY7zNrP93C00TGsa90hBaWeQ1S+dw7kvrqL25OB6uL5AP/9488M8d8EW1AnwXp7i9OhRTyA/CmKL2zPCJLvK9+k8M3cmKRmlvGbxmKlzSaILr1NLcYvGOlDUlKnznYEoIRZpN96U3i5jze0CIFWVFUFqK3yHzmZ0nL0OkiAMr9+eSy8iQNXp52A4Npe5jY6t0w8I9HX2jcaaOrdhL6Kx92hSjMYatN/Qa1mimNjnyGi/UY8lg1Yruv2Iht+nQqQXAmWogVIY5nl6xx7PPkdDITkG75fVzF1Qt6sSWd077Fi9Pkeg9Rsadp9j6MVEynMUwmsBCKQmk3RsGf2xR9AH6RSR8j34+ycjIFLZO5Pemi24RP2Fjl6fJMdwczuhY+YmavdciiPlZkrjAjrmvHLG00SdY+v1SAKQhgirhBa9RueUQ5Qfn0VZSz3z9yzmxLJXdY8zFmQDD0Wvf42i8+Psm32IP3/tW8x7dQVX/fkWylq11M/y9grWPnQ1ax+6mu7Kdnadt5ld523ixMyGQc6SYZ+jrCZmrpibJa8u45z15zJrzxzE08YmnUk2XvwyD7/pYSKBCB6Dk4Zk0E9L0umnBZAQhl9ujPayGIhkRY+kFE+sevGM3/5IGc0ob9LDzJ5pAPS6QxwvbdJv5ZKDv+lS3GmJ7x6xg4hrcPqgYQ+lUfYq8ntq0gpyffGTOfUy0m03NMxxpWA5wkD7CLm3Y9j5jV63oDO54VpC/1R7xnU3VZWJIEmd3brHN/j5GLzfBj8Qg9dl3EdJZ31m8OMUclgv631WRnbp7jcaN0LOXgfJxsZm/OnvhkAZguRE9QQgZn7Ofy4kUxkHySFW6zzTHGKuTFqMOz5V55njQ1/5PiqPXQlAUed8emuGdsjGg7bZr1C751IAKg6eO6SDNO4IsOeaf7LmN58HYMETb+TEktcmRBQpjQD7zt3CwRU7WPrCBSx8cTXTd89DHHBQStsrWfPQNax56Bp6KjpprT9BX2kPfaW99JSE6CvtpS/YS6i0F9mRpLS9grLWSsrbKihpraK8rYLy1kpKukvOcIoADs09xCsXvcq2VduI+s2TpzaTyzdfkI4evbh4c96iRwva5yINrGR3Ve0z7HOZCzXJesSBKoiTDvPT64rcWfVHsRadZ5pDdv2R3Fv49UeQqUESEkmkHrsH0tmG7SDZ2NiMnGyhBl9pwTtIKaULVU0iCE4cUv4dJEWKkHC040pV4k7UabcJBYPblDkQLj2EIiYRFSeBznmm1rb01O4n4evGFSml9NgSpLgP2W1OSl82rXN30jHtABUNcyhpraN+23k0rshP/cl4IjtTbLn8BbZc/gK+UIB5r65g4cZVTNs1H2nAWQp2lBPsKDc4kjEd1W1sWvMKG8/fTGdV/uWbx5NAxMcl27U+TVr0aEPe5l7Umkmv21m9x9S5apNZ6XWSuel1AAG3tQINjuJMQ2W5pyPv848WVRRIlQcBkDq6MbEUzcYibAfJxsZm5GQ7SIFy6Cp0pSuVpNyOy1GLJJYh4ELF5FqZ04i5juNKVSLgxJ2oJ+5uMG0uVUoSDh6mqGserlg5nv5aFLNUtkSVjtmvUrv9akTFSeX+C2hZ8pQ5c2UzEEW6+Ff/DcDih2+lecFWUp7CFxYYjkhxP1uueIEtV7yAq6eE+ZuWsfDlc5ixax6OMcio9xf10VnVQdP0RjZf9CoNs4+AAAnZIPd2AnDThisGRY96A32QMv91lUZLmNajOS2d3i6aA62QMknnSoW6pKaUJyPT6mgyGJArQlrBLiGHiafyL1ktBTNKo0pP4UeQUuVBcGjfO0d7j6W22JiD7SDZ2NiMnL6su89FlcM/r4BIpE7ictQiCCIOaTJJ2by+JUMRdR+mOKI1s/RG55rqIAGEqnZQ1KXd6S5pWUm3iTLErfPXU7v9agBqd1xBy+Knycet1LbZu2mZu52a/Uvx9ZSz8LE3sf3mv5g+bz6IFPez+bINbL5sA4Ii4AsVUdRTQlF3Cf6uUop7StKPHUkn3ZWddFW101XdQWtFN51VHcQngArdWJjVNJULdq8AIOqK8fiq9QYjxo9VJ1akm8NunbTTVMntylQtAaUYgBbpOCkhad5kaOl1DtEDQChmtjM2BIKIo3RAar6/FzVe+KmfqdrM9c/ZXPgOnc3osR0kGxubkRPKuhAUTxAHKdkEHq2ZpNNRn3cHKezJyG97Y3Pp4QlT5+ut3kLtvjchIBJsXUn3nH+ZtpiLVDTSO3kvJSfm4+2ZRPD4Ynqm5qG5qABb3/R7rvzud3Ak3czacDXHV75E95Qj5s+dR1RRJRwMEQ6GaJnWOCqRhrMNd8LFO5+4Kf34gQufJhTIT4qvO+Vi5UmtOXFSTLF50nZT55ueyMj0Nzj3mzoXQNCbSefriTaYPt/pSMFKBIcmnZ7qPGnw7MIgUZuJeDlPtFloiY1Z2H2QbGxsRk4qgRrp0bYDlZjeuXAcSKQyd0SdUn3e55elEAmnltPvStQjyj5T50u5Q4RLDwHgjlThDpnbpPbk0ifT27XbrzR1rmzC5e3sufo+AARVZOU970PIQ6qVjTW88fmrqQhpRfGHao+zfskmgxHjx4rmJXhkNwA7qncTcZkX4RBUgWlxTQZeJsVx52HT5jpF0Dstvd0TNb/e6XQcZbXpbbljYjhIyTrbQTrbOXtvNwmi9m8sGMhO689rMNZIGlpPbtHILkNJxDHuw1hWOpf9hnLXuRw7Rzls3c/LSplvg1+untS20X5VMkiR6msDXxDB4UQtLoHI4P4Pgo7c7njLeJ/O0FLdHShKP6IYwOmow+lQGEq9wDOMVPcphpPyBnBL+mNTvj24eichIFKSnEHcvXXEcxvJdA8lAx6tfZlAt7bIKm9bTm/5oTEd32kgKCEKKvFZLxMvvhV3qIrS40soC5UTLztpON5I5tsICYXWy+8jtPU8ik9MJ9g8lRVP3MzB1//ZcKyc471BPanhpMEP20imWG+8UYTIpeh/Xglx7MeO6ch0a+MNfts6n7fRd2HhoblctEtLU40549x1/T9xuPLUp0cROK9pZfrhxmmvZM5jRl9hgwuQOsT4qsRkfGoAgJPOYyScw6RLGsytGnzPTs3tED34XVp6WzjRToIwOl8TbayBZLWupPUQb4mjIuMgJbuada/LhvLlOawHDK/JWXMnByJIQiSKGOrLeY2k+54ZLUkNpbbHvnY0XEYbSYjrfVGN7DLS4B/OuLGu/U/DjiDZ2NiMjv6sNLvAxEizS8qamIQoeBGFCoNnjz9xb6ahpCsy3/T5wjWbUQecE9/J1aaq2SGqdCzNpA1WbbnexMkGo0oyu9/2UxRJq9GY9szrKT2wKG/z25iPP+Ln1qzUun9d9hidwfw15ZzfNo9gLAjAgfJDdPjNVQGcHs8o5R11mduIFqDEPSXdy6Ynlv/oEYBzIIKkJhPIvYWvYCcHfCglmhPrPNk+AfIobMaC7SDZ2NiMjr6sdIKiquGfV0AkUxm1PYdkbsrZkPN7DqMKmnqeK2qu/DaA4u4nWq4trhzRSlw9002dr3PRM8guTeK7dO/FOMIlps6XTV9dAwdvuAvQUu0W/+XjOCL+vM1vYyIqvOGxmymKaIvRnTP38fLizXmd/4Ljq9MPN04d/6bE2QiqwLSYFvlNkaTRZX56XWl2el2swfT5Tkf0FiF6tc831d2M6SfHcSCZLdBgp9edtdgOko2NzeiYiA6SnOUgifl3kBBTJDxampskB3Ek6kyfMjwps5jznTzX1LkUd5SOxZrEtyg7qdx2ranznc6xtQ/SOUcTh/D0VLDwro+OIPXDptA5d9tqFh1YCEC/N8w9V9+f17LHqV1TmBzSohvNgRaOlpobYZmUnIJX1WoUm9xHTVevAyhxawINspIkFM9//U92/VGqa4LUH2ULNJy0HaSzFdtBsrGxGR2xEGpyIC++uMZaW0ZIUm5GVbWaBYdkbjRlOOL+nahoNrgiC02fL1y9FVXQ5vOduABkp6nzdSx7HGWgnqli6zU4wkFT5xuEqLLrbT8l6dVUzap3nMusR27L3/w2487049N5/ZOvSz/+29UP0OcP588AFS47sDb9cOPUV013zuZEF6e3j7rNT68LuKpxO7ToTSjeiIp5TayHw1GZEc5JThAFu2R95rpnR5DOXmwHycbGZvT0ahcywe0Hb/7SqcZOipSi3f2VxFJL6pASvj0IA7o4nvAy0+dTXGHCNZrSl5Qoxtd8jqnzJYu66FyyTpsv5aFm45tNne904qWd7HzXD9O1VzPWvZHaV9YajLIpRMq6S3nHfW9DGqjWf27lS+ycvTevNsxrnUt9jxbpbfd3sKt6j6nzeWUfU+OzAYgKEY67zU+vK/fOSW93RocXcjETZ5UWwVLlFKnOE5bYMFoSU7WmukIsgaPV3Jo0G+uwHSQbG5vR05t1p69ksnV2jIKkfDC97ZRm5n1+xdFN0q31YHIkJiMlzE9P7J36bHo7cOwy0+drWX1fuhapfPda3J3mpxJm07FgK/vf8Pv04wV/+yClBxfk1Qab3HDH3bz7n+/CH9XqyPZPP8ADl5rbO+x0REUcFD1aN+tZFNHc2pjZscWIaA7hQe9OFAMFyfGg3Kc5ZKqq0BU13yE7HTFQhuTTGuKmOprAQIWxEJCL/ChBzWZnUwvCUFKENmcFtoNkY2MzenqyHKRg7fDPKyBSqcwdUoc02xIbYv5t6W13HqJI8dJDJIq0+it392ycvebWX8m+PlrPeQDQBBOq17/N1PmG4vjFj3L8oscArR5q6e8+h69tUt7tsBk9oiJy6wNvpbpDk51uK2/jrpvuQjHSdh5nljcuoyJcDkBD8DgHKsyNrgiqwNyo1ohWRWW/19xGtAB+ZxUehxb97403klKGkRM3EWd1pkFtst0aBb3Rkp1e52pssdASG7M5e/sgicLwGuuG/YJy6GVk4bEN2h6gSmPvsaQ3dkTjdfbn2j9A0bMt12Pr7DfqoWRqHySDXkU59ZYy6KGEQ4XwSVRV1eRhg7WDx+jYJhoce2x9jka23ymdQFVDCEIxTmk6HocKWTn3en2OALyO4Qumh+pFlI1noE+SUPIadN2sHS+8DCofGdg//LGNeiwZ9UlKzXgc1/b3A1B6/BKiy387aL9eryKjPkjOIV53YtV9pHZeiaOvgqKj51B+YjbxKbvOeJ6k2/gDRIP9ejTd8nOKuiop3XMOrkgRK3/zBXZ+5nZS/v4RjVcMTgyyzn7FoFAlaXDi0OuDlDT4rOMGvYycOvsdssHnYaAuJsoG+w16HQmqwBsefhPzD2sy1xFPhL++9U6UQBhPKn9LFVfKxSWH1qQfPz3vGUTn0LbLRtEDw/3af3WxGQQULSrR5D5Cv7tX260nNGLYs0d/7nJP5iZRR+zgoGuGUZ8jo/26LbGy9p1KrwOItx9DEUE0um2fw3pAMHhPjNciAokpGQfJ0diSXtuMZ4+lM8ca9Qsy+G3lsu40ErvJ5dhGi1bDYw+3f3yKBe0Iko2NzeiRExAe6IcUqATJXAGA8UJWtDvBguBCFKYaPHv8UZ3dyB4tzU5K1CHkIc0uUb8B1aGlvbmaLkRI+EydT3Um6L7wr+nHpc//h/GFcLyRFA6899tEJml3pb1tdcz/xdcQY9782mEzMlS44bGbWbZTa8iaklL87U1/oqss//Ud5x4+j0BCEy7YM2kPJ4LmCwfMCy9Pb+/zb9V55vhR7s1Kr4tZUH8kSjjLtRRcOdqP3DcxankS9ZlotKvJjiCdzdgOko2Nzdjo1QpqBUGEoomRwqQoB9LbomhNml0qsCW97ehbYf6EjjiJ+hcAEGQPzsaLTZ+yf8FzxCs1R9DdOhvf/otMn/N0ZG+EvR/+Cokiralo0dH5mpMUd+fdFhsdVLj6qRtYvfl8AGRB5u9v+AtHp+e/JsYf83Pe4Ywdz81/xvQ5i1Ol1MU1Zc0+qYcT7gbT5/RLFXgdpQD0JppIKlHT5zwdZ1ktgkO7sTZR0utUIFmvpX+KfWHEnj5rDbIxFdtBsrGxGRuhrDurxRPDQZKVQ6gDuQySOMfg2eaQKsp2kFbmpS9ifPq69Lb7yNXmR3REhe5L/pB+WPr8uxASHnPnHIJ4eRt7PvYlkj5tIVNyaBELf/xtnH0TQXnx7EdQBK569I1c9PIlACgo3Pf6v7F33m5L7Fm77zJcsguALVM30+3vNn3OBf2ZmyT7/NtQDVIRx4MKz9z0dmf0oM4zzcNZOfHqj+TyIKpPi0I7G1vy2ZLLxgJsB8nGxmZs9DZntoP5VSsbO2FUVYt8iWItAqV5t0B1diF7jgBamp0YN79xrVJ8gmSFVgckhSfhPHG+6XNGp20jOk1zBh19VQRfzL9gA0Ck7ih7Pv5FUgM9kooa5rLo+z/AYws3WIqUkrjpH+/inFcz9T4P3nAvOxZvs8Seae3TWNq4DICYI8aGOetNn9Mr+5kdWQJAUkhw0LfT9DlBoNqt9WFTVYVOK9LrAFfNjAEbVBLtxy2xYbQkpmeuc87jzTrPtDkbsB0kGxubsRHtQo0PFL2X1JHXFvc5ICuZu9OStMgSG5IlL6W3nb0X5mXO+Nx/pbc9+9+Ql7qgrit+heKIA1C0+UZczdZE7cJTDrHrU58lHuwAwNtey+Lv/4BAgzX2/Lvjirm55S8fYP6eZQDIosw/X383m5e/aok97qSbG7ZlmtI+O/9pIu6I6fMu6T8Xx4BW1j7fNuKi+UpyZa7puCWtxqordoSkYv7rPB0pUIqjSFMJTHWdRE3kP8VvLCRmZBwk9+FGCy2xyQe2g2RjYzN2epsAEBxuCJgvODAeZDtIojjfEhtSRZtQBW0x5OhbBYrL/DkrdpMq3weA1FeH88R55s8ZbKH3grsAEBApf/zjkLJG0CNS18DOT99OZFIDAM7+IAt/+G1Kd6y2xJ5/V/x9Rbz99x9j2lHNOU044/z1lt+zfckWg5HmceXuqyiJaWmXDeVH2TLVfFu8KT9zwpno0a7Aa6bPCVDjWZzebo3kI2J1Jq6aTB+6eLM1EayxkJhZP7CRxGkLNJz12A6SjY3N2OnJuosWrLfOjlGgqh0oSivAgJJdIP9GiHFSRZsAEBQvQugc8+cUIDb3n+mH+Yoihc55gHi1Vufg6pxC6fp3mD7ncCTKOtj5X5+hd/YOAKSkh3m//h+q119rmU3/TkxunMa7f3s7NS3anfiIr5+73v0LDs7ab5lNs1vmpFPr4o44Dy17KC/B8EWh1TjQbhbs920nJpkfyXGJAcpcmiBEXO6jO25N7U+2g5Royb8Yx1iQg8XIpZoUu+vYSQQDWXybic/Z2wdJD8N+QmPXZs9lLICq0wTASGd/eE34gfG6dhscO8f9uj19DHsoGRw7h15Fhn2SdHsR6Y817JNk2M9h7HMb9knS6UdkNFbI3h/Kyh0vrYPm1xB1ehlJBn2MHNLY+xwBeHR6GQ3uc7QLqEYQRNzOOajqq7p9jiDTy2i0+7T9Qxy77DkIaepujt4LcVU8O+RYt0Hvm1Htr9mMWr4XoXM+Ul89RS0rcNQPX2vhNDi2UZ8kCRUkiF3/XVx//DmC7KJ4800w+0WUafpyxhImLUACMRo//hnUP36O4KbLEFSJmXd/jNLG6Zx8y89QXQlkgxODXp8k2agPkmjQB0mnV5FejyQw/jziOvsdBmON+hjp7ldh5cZLuPjxm5EGTmyhki7ufffP6a5sxStbsxTxxH1ct+P69OOnFz9OpKhr8MJI72UZ6Ckow1xYPSkf8/qXAZASkuwseXXo865e3zijFktD9K+p9izUVEeBluhulGHO9QZfBcNrm15fX8Hpx1mmNRdPhdqR472DezoZ9VjKYe6R9DkajvjMzA1AV0PTmddgg/fMcI2ks99oXSkYrqEMviw6607B4HdvaFsO607D/k0mY0eQbGxsxk6kAzU5kD9eMjEiSACqmmlcKggLrTHCexTVraUoqpG5KLFa8+cUQJl/T/qhuPctqHmIIsmVx4hccmf6sf+Rz0DMb/q8w6E6kzS+55u0X5l5L8o23MCsb/8Cd7P5ohn/TrhiHq6+6z9Z++ib0s5R09RD3P3B79Nd2WqdYSpcvuVGAnEtgnyoej87p+SnB9Gi3tU4VC16tM+/nagUzsu8NW6t5lJVVVqjZzZvzgeu6qz0utaJET0CSE7LcpCO2PVH/w7YDpKNjU1u9GoXC8HpBX+lxcaMlBOoas/A9mzAgt44AqjBF9IPle5L8jKtWrUdtUxLaRJCUyEPtUgA8XP+RXLKNgCkvip86z6al3mHRVRpeeOvaXznd1CcWj2Y5+QMZn3rl5Stvy4v8utnO5VNU3jTz/6bmbsyUtavrnmSf7znJ4SLQhZaBnMblzCnSXMYos4Ijy/PT2qdW/YyL6Q1hk0JSXYWv2L+pECpYyoeSauz6k42EFes6eHjrs5Or5tA9UenFOySSZyNdv3RvwO2g2RjY5Mbvdl1SFOHf15BoaKqewAQBCeCYI1YA8GXUQUt/U7uvhhVzoOjdloUiV3vQNVJ6xq/eVXC138PxaXdLXftvhLXtusNBplPzwVPcOgLHyJWqzW2FRNepvz1dmb85Ns4OyeG8EihIaYkVq27kTf+8nMEB97DmCfC/W/7NRuufhBVsrZ+oyxUyRWbM6p1Ty57hLCnPy9zL+++EKeqibLsz2P0aJJnaXq7JW5N9EhwenBWaJEYORIiFWq3xI7RIpeWoJRqzqXreDOCbJRPZ3M2YDtINjY2udHdkNkunW6ZGaNFVbentwVhhc4zTUQKQ/GAtLEcQM5XFKl6K2q55iDSXweHbsjLvEpxO5Grf5J+7H3yo0gnLHJOs4jXHuPQ5z9M10UPp/9WvPcc5n39DsqfvxGGqOewGZqq49N44y8+x6pnrkccSKlrm9zAXz78HY7Mt0Y1LRtX0s0NL92KK6XdjNhVt519k/PTmDaYqGDuQPQoKSTYkafokVcspcI1C4C40kdn0prUNk/NXISBGrx48wFLbBgL8TmZ65rr4MRoamuTO7aDZGNjkxuRDtT4QLpMcAqqaI2M8+g5iqp2DWzPRVWLLLFCLX8ivS13XINqqMYyDgggL7sD9VRF9J5bUGNB8+cFEgueJbbyPs0MxYn/X19B6CvPy9x6qK44J97+fxz96OdJlLYBIMV91N/9CWb94If4D1lUqzZBKO6s4Kq73s+bfvl5KgfquGRR5tUrHuS+D32XUFmnxRYCKlz12s2U92mpwO0lLTy57GGDQeM39+rOyxEHll07ghvzFj2q82RUMk/EtmR+93nGW7sgvR1r2mOJDWMhkeUgufcfsdASm3xiO0g2Nja506VdNATRAcUTKc1O63ciCCIKK60xw3MCsWibtp2sROnNU1+e4FHUaU9p2yk/7Mqf/HZk7W/T9UhifwX++78MFimZnU7/olfZ9+X303HRI+m/BQ4vYvb3f8z0X3wdz4mJEyXNB+6wn9UP3sKtP/wqs3ZmfkOd1Se498PfZtPlj6JYnFJ3inP2r2H2Cc3RjTmjPHTBXSQN1CvHi/rILCZHpwHQ5+hhd0l++h45BR/Vbi1Km1LiNMesieJJ/jKcJTUAJHtbkfsLwGEeAarTQWK6lhYo9vThaOmw2CKbfFEYVyQzEIThJbUNJBFHdOzhMJKRNJQBH+O8Izi27o1pyWhsrvvHtm8k+/Xec0Mp7VzmzkEifCT70ZHmNDy20XumI+UtGMp8D7HY6TkEk5Zp+8tmIPYNnT4hGSyUjGS8XQYy4C4dme+hZLxV9RWSXKFtcw4e6alhx+tJefsccV27vEPJfGchVT9Af98yzY6O6/CUrU//3H1iQneskcy3nlS3uuROkicugGQAGi7HN/t+pLKDmbFCjjLfwjCftwTizV9C/f3vEELVOE4spPipD6Be+wPjsXlA9ifofee3SJyzjoq7P4WrVXP6S3ZcQPHO8+g77wk6b7yTVMWZxdqywY/PSKo7KQx/WY6p+pdso89Db/9oZbzFpJPZG65kwVOvxxXNKBJG/SG2XXU/B859AVWS8eke1XxOSW1POzGPC3ddkf77U+f/nWhJB86U/uehp/KoGKRenpLaFhWJ1V2Xpf++qeIZFGcSwegiouhcA2SDuQdeVq17GeLAd6o5uZOUpJ1PBFnv+mKkSa2/eyjJa29tJpU2dmLvsNcoo2uyjiL1wBOG3zWWtUZ85hRwau+f+8AREId++bm2KxH02nrofA8gN6lt7Qk63wVDiXH9Q+unJxvJjxvYPdyxx0ke3I4g2djY5E5PAyjaVVENzpowAmCC0I5AAwAKdchqHqS2h0Dy70XyaYpOcnQ6qf7FBiPGB8ETwr3wzwOPRGJbPmzY22Xc8PegvPG/USXNuRS33oyw5fV5mnxkRBdsovGr76TtHd8mFdTS7gRVpHjjtUz98l+puOdjSKGgtUbmGUGWmLrpQq779ndZ9tBtaeco5Yyz/fKHuO/zn2P/Bc+iGtzMyCeVXbVc9dJbEQdWqa8ueopjtflrTruwZxXFyVIAWrzHOBbIz9wiTmrdywBQVJmm+Ja8zHsmAp5JmoOkKjKx5n0W2TF6stPrXPuPWmiJTb6xHSQbG5vcUZKZprHuIHisrykZKSKZVJekkqf0ttMQBHBXPZR+HG+9MW9zu2Y/iFikfXZy50KSxy7P29xM2o967ffSD4UnbodD+ZEdHzGSTN+ahzn+jbfS8aafI/u0ejsx5aL06bcw7Yv3UHHPx3Ce5f2T3H3FLFj3em74xg85764P4e/W6nhUQeHI6ue577NfYOs195H0xCy2dDCBcAnXv/BOnLKmHHdgynZeWzh0U2Yz8CeLWdJ1IQAKCq9WPpUXOXGASa5FOAUPAG3JfSTU/Cj1nY6rrB7Jo9V4JtobUBNRS+wYLSqQmDNDe5BM4T5sCzT8O2E7SDY2NuNDd0YZSQ3OttCQ0SGyFdBSyZLqqvyIJAyBs+RVRJeWspXqX0Iqkp9aF0GU8Sz/ZfpxfPv7UBP5a+KqLnkc5dy7NVtUCfFfX4cThSeIoLoS9F51N8f/9y10XfsnFJe2yBPjPs1R+spfqfveTynZcB1i1OrEsnFCEajcv4hz/vhxbvz6j1n82Jvx9ZaldzfP3cGTt3+J1976WyLBbgsNHRp33McNL7wLf6wYgJMVDTxz7r26KUXjigqr269Iy3rvK9lCl7stL1MLiNS5MzVhjfFNeZl3KDyTssQZTkwccQa5ugKlRHPsnA1NCEn9lGObswvbQbKxsRkfsh2k0rkWGjI6BCGCgCbzq1JCSs1PetuZdqi4qzKKWrGWN+dtbsekzTgmvwSAGisntuXDeZsbQL3sF6jztLv6QtKH+LcfwEnr5b+HQvH103nzb2n4xq30XHofSlb9mffgMib9+XPM+sy/mHTnF/HtXTEhJcJ9HdXMefJmrvzGj7nwl1+ibusFSLKmTqkICk2LNvHMh7/JCx/4Lj2Tj1ts7dC4Eh6ufup9lPdqwgA9gQ4eW/MXZJ1awvFmRt9Cpoa1c2FUCrOt/AWDEeNHjWsRHlFzDDuTR4go1ogiCE4PnirthpmSjBFvnzhpavH5mRt97oO2et2/G2evSIONjU1+iXZBuB38lVBUj+osQkha0619tEhsJIXWSDGhXoKT7QYjzMFV9jyx1ptQkxWkQitI9c+F4vyoTnlW/Jz+tiWQDJA8diWOyRtxTnkuL3MjqCiv+3+I0SKEY+cgxANw9w/htk/ApPzViowGOdhJ+20/pPP1d1D80nUUb7ged7MW9ROTHkpeuYqSV64iGWwnMn8T4XmbCc/fTLK412LLz0SKe6jZv4yqfUup2reUQEfNGc+JBXo5umo9hy58ikhZYSt5OZNurn76fVR2aepjYU+Ihy/5IzF3JG82eJNFnNt+Zfrxy5VPkpD0xVzGCxEHU92ZVNVj8ZfzMu9QeGsXIUjaUjN6cne6VrXQUYH4ojnpx649h6wzxsYSbAfJxsZm/OjcqzlIgFo2H6H1VYsNGhkC+xFpRaEaWZ2DrNYiCSfzb4eYxFNzL9HGDwAQbX4rRUU7x0uURxfR145nxc+JvfI5AGKbPoGncjuiN0+pU44Eyls+h3jP9xCOr4BYMdz1Y3jbx6DmoPF4i1D8ffRceQ89V9yD+9g8il68juLXLkeKaHfvnT2VlGy8lpKN1wIQq2mgf95WwvO20D9nG4ovP71wshFkiUBzPeX7llGxdznBI/MQ5TP7l6mCQtvcHRw7/xmOzd+OYqAyWQg4kk6ueuY9VHVoyoMRdz8PrL2T3qI8RlBUuODkDbgVLwCHi3ZzrCh/wgR1zuW4xQAA7cmD9Mlnqi3mBwFfnXbjSVVVok3W3HgaC3JVBXKlVkvrONaE1GdN/ZaNddgOko2NzfjRsQ+mXAyAWr4AJoqDJKi4hBeIKVpaW0K5GK/0N0tscZU9T7ztRpR4LXJ4PvHQcjwlW/Myt3Pq06ROXECqaQ1qooT+1/6LojVfyouDphkQzzhJjcsGO0nVhw2HW4oA8Wn7iEw9QNubf05gxwWUbLwG376ViEl3+mmelml4WqZR8dzNqIJMfNJx4tWN6X/hqpPEq5uQ/eOwIFNEvO01+Fqm4D85FU/zVALN9fjbaod0iLQhKTpn7Kdt3naaVr5ItFRzLBSl8JcLUsrBFc/9BzVtWmF9zBXmwbV30l2Sn7qfU8zpXkFteCYAYamPVyqfzNvcDtxMca4CQFUVGmIv5m3u03FXTkfyajcKEp1HkaO9+dKnyJns6JFn19BtK2zObgr/jDdmdPogGWFUmaV3XKM5czi2TjsG049tuD+XuQ17E+TQXyCHnglG+xWjPkZGEv459ElSdXokAbp9jrRjj70Pkqi3P9GBGm1F9VZDoA7RV4SQyKQUOQz6IBnt1+tzBODWqS9wifp3vz3Si8QTN6LiIamuokS8D1HIpOTo9Toy6nPkM9jvPa3XkVT7V7qOfgaAcPOtlJa+ijBMYblb1D+2RzDYf9p4/+rv0taxECVWRvLkBQjHLqdo5iNDjjXsg8Twn6c4XJ8jbxT11o8Rv+unKE3LIBpEuOsneN/xfqSq/DhJssGJQdE56ciIIMVg9RP0rn6C3qQL1+HFuPeeg2fvKpwN8xEGnA1BlfCcnI7n5JmCHKmiLpJVTcj+EKoniuKKkXTFUQa2FXcUVVSQon7EaAAp6odIEVIkgCPqR4oGcHfUIKZchq83Vt5C+/ytdC7YSvfsncgDSnQSEBh4jpQvYYMhUAwuQIokICVdXPL8u6ht0epGEs4oz1z1K/qCrei9A7LRsZXhv8ND2RWIl7KyNdNvaeOkR0i5okN+o2Sj/jY6+4c7T9c7zsEpaJGr1tQewnQOeR3T63Wk85IBMFJwP3Vt89YvS/8tfGIbimQ8Ntdrtn7PRaO1hPaeqkBs0UAdraLg2ntAO67uOsaoV5Hubt39hn2Mcpxb9/g59Tkip76hOpcPg2OPjxueFwfpF7/4Bd/73vdobm5m4cKF/OhHP2LNmjVDPve5555j7dq1Z/x97969zJs3z2xTbWxsckTs3oPsrQZACc5HarMu/300iEIMj7iRqLIWcBOTL8DnGL5xrJl4SzfibDlCMjqDeGQW4e4LCJTl506w5OkhuPq7dL3wbQC6Nn0ST/VmnIH8pekI7gi+2z5K5K+/QDmxBDVSSvQvv8Z724eRaibY3VxngsS8zSTmbabv5l+TChfjObAc775z8OxfjrNlKsIQToyjrwxHX9kQB8wNRUoSrT5BZNJxQjP20L1gC7HKk8TUoSNKEwFXzMfap95PZcc0AJKOGM9c+Wu6Kpoglb/XJagC5zfehGNAtW5/cAsnA/kr7nfho17SlOsUVaYhvjFvc5+O5CvFXaalOaYiPcS7Jo5EtlxTiVKu9a1yHmtCDOevds2mcDDdQbrnnnv45Cc/yS9+8QsuvPBCfv3rX3PttdeyZ88epkwZvm/E/v37KS4uTj+urKw021QbG5txQOzejVyr3eRQShdOGAcJwCs9N+AgQUS+BK/09LCRGzMRBJXiyX+l89D/ANB54u34SzciDBd1GWe8dS/im/EIkSPXo6b8dGz8EjVXfCyv74XgDuO77SNE/vpLlJOLUMPlRP74O7y3fArHNOski3NF9YWJLttAdNkG7Q+KiKNjEs7WKThbpiA1T8PZOgVXyxQcobH3E5M9YRLBTqKTjhGtbSA66Ri9NSeIVZ0cuonrROnufBqecAkXPf5Rgj2asETcFeG5y++goyr/C/J57edTGdGEIfpcXWyuejqv8091nIckaA7hyeR2Ymoor/Nn45+8NL0dOTlxao8A4gszKqyu3YUpEmNjPqY7SP/3f//He9/7Xt73vvcB8KMf/YgnnniCX/7yl3zrW98adlxVVRXBYNBs82xsbMYZId6FEGlG9U1C9U9GdQUREj1WmzUiHGIrLmE3CXUhCpUklMW4pR2W2OIp3oIrsIdE/wKSsXpC7VdSUvVE3uYvWfkT4q0rkMOTiLetoHfP2wku/HPe5gcQPP343vYhIncPpNslAkT/+gs8138T57IH8mqLaYgKqaoTpKpOEF28kWRWbq2QcCHGfAgJL2LMSypWhBjzIiY8iHEvguxA9vYj+/qRvf1EvDFkbxjZGwHxTGc6rkzcKNFQBDvquOCp/8QX1u72R70hnr7yV/SUNefdlrLIJJa0ajdXVFQ21j9AyiD9dTzxCkFqJc0pkdUkxxKv5G3u0xEkF94arfeRKieJNO+2zJbRopIl760ouPfa6nX/rpjaBymRSLB582auuuqqQX+/6qqreOmll3THLl++nEmTJnH55Zfz7LPDd72Ox+OEQqFB/2xsbKxF7M40A1TKllhoyejxSpnzTUS+SueZ5iIIUDL5L+nHnSfeiZwK6IwYX0RnhIrzv8GpRPCe7f9JtHV53uY/heDpx/f2DyHNHughoziJPfRVYk/+F6phIeDERnUlkIt7SFU0k6g7QmTGHvoXbCa07EV6zn2K7gseJ7R8A+G524hNOUSiolUTdxjCOTrbqG1YwqWPfDLtHPUVdfDEtT+xxDlyp7xcdOzNSAPO7d7Kl+jwN+bVhlmOtYiCNn+jvImkal1amG/yEkSHJkwSbd2HmsqPvPl4kKqtGZxeF4labJGNVZjqIHV0dCDLMtXV1YP+Xl1dTUvL0PnskyZN4je/+Q333nsv9913H3PnzuXyyy/nhReGbrD2rW99i5KSkvS/+vr6cX8dNjY2o0Ps2gGqtkiTy5dOqOwdl7gbSTgBQFKdRUKZaZkt7sBeAmXPA6CkSuhsemde5/dWb6Vk8e+1B6pE+4b/RypSkVcbAARnDO9bbse56u7035KvvJ3o3T9BjRbl3R4bC1Fh7vYrOP/p9+JIaYvw9ooGnrj2J/QX578ZqqCKXHjsTQSSQQA6fE3sqB7+pq4ZlIszqJC081Rc7eN4ykL1UEHCX7cC0KS9+49vts6WMRBfkmlQ7d6x10JLbKzGVAfpFKcrZKiqOqxqxty5c3n/+9/PihUrOP/88/nFL37B9ddfz/e///0hn/+FL3yB3t7e9L/GxvzetbGxsTkTIdmH0DfQMd1diuqfODcuBEHFJ2VkeSPy1RZaAxX1dyKI2t3gUPs1xML5ddiCi36PZ5KWrqPEymh74VsoI1BGG28EUcZzzXdxX/91GEhdko9cQPjOP6EM9LyxObsRUw7OeeHtLN70eoSB5cvxma+x7pqfE/NZ05R6xckrqQlrKoRRRx/rp/wDJY8RPBGJWY6MsNWh5HPI5C+173R81QuR3H4AYu0HkaN56qM2DqiiSPyUel0qhWtv4fZfszEfUx2kiooKJEk6I1rU1tZ2RlRJj/POO4+DB4f+orrdboqLiwf9s7GxsR6xK1O7o5QtttCS0eMRX0NEuxudUJaQUiZbZovD1UlZ7anIiUj7sQ+hGmr+jx+CqFB5wVeR/FrqUqJzIZ2vfAHVorCga8W/8L79gwg+beGldk0jfOefSR260BqDbPJCoKeKyx76L6YdOjf9t10rHubVS/6EYiD/bxYzupYxt1OzRxZSrJ/6D6Ku/DpqU6TV+EQtJaxbaaRNsVJUQCBQd076Uf+x1yy0ZfQkZ05F9fsAcO0/jBhPGIywOZsxVaTB5XKxcuVK1q1bx80335z++7p163j9618/4uNs3bqVSZMmjZ9hRpryBvvVXPogGR1bz2XNxS4MtPBz7HOU0/5cezDp7DfV7hyPbdi7QLcPksGxDXoZ6fU6Eg16ERntlwbunoqhvcjy9SC5UEoXIp58DMmoz5FBkwynQS8jvV5HHp0eSdr+wXddS9TH6U6+DYCYcgXV0s+HHTvaPkdnjh8+R98jpPBO+if9HVcQj00lHp5HvHMtZVWPA+PfBykbpzDwnvnamHrppzj6xJ2oKR/hhqvxl+2jdNHvdY+dHj8Eej2SDJm+kaL3v4muu39Bqm0uxIuI3v0z/Of9nuLLf4jg0H/NSo59MvT6JCVV/ctqQu+HbTBeNEhWFQ28Vkln/LB9qfKAXl8pVKg9dD6LXrwFR8oDgCwl2Lb2DzTP2IoHUFLDf54pUf9kKUsG+5Wh95f11bPqxPXpx5vrHqG76DjZn65icL5TDd5yRa/HjKTiJcgUh+agKarMQfmp9LlflQ3WAzpfQ0E2uDYN00/IWzEHh7cEgHjXMVKRtjOuk6ZekzFYDxj87GPZ6XU7956xNtHvsWRgl2GvSJ2xhmsg/ScY9VHS6+Fk2IMph3Vprsc2G9NT7G6//XbuuOMO7rzzTvbu3cunPvUpjh8/zgc/+EFAS5F75zszefU/+tGPuP/++zl48CC7d+/mC1/4Avfeey8f/ehHzTbVxsZmHBGUBFLvPu2Bw4tSPNtag0aJ37EBEe1ucEReTUKxrtWAIMpMnpZx0Job30sqmd9ouafsIJMv/HL6cduWj9HbNHQ/u3zgCJ6k4j234ZmX6VUVfvk/aP/d30h2nNl41WbiISU8LHjqfSx7/l1p56gv2MyGm75L84ytltnlSRRz7qFb06IMBype4Wh5/u2ZLV2BJGgOdZOymTAdebchm6K6Vent/kYL66DGgOpykZg7CwAhEsV1qMFag2wsx3QH6ZZbbuFHP/oRX//611m2bBkvvPACjz76KFOnajnjzc3NHD9+PP38RCLBpz/9aZYsWcKaNWvYsGEDjzzyCG94wxvMNtXGxmackbozaXap0omlZicKCYqcpxbfEl3xay21J1CyjWD5MwDIqRKaG9+XdxuKpzxL5dJfDTwSObb+W0R7rBOxEN0RSt/ycYqv/hZIWpQu1bKAjl/fS3jTWyxLA7TJnaLW6az6x5epOXh++m/H521gw83fpq/8hGV2iYqDcw/diieliYO0Bo6ybXL+5PdPUSnMoVzUbgTE1BANir4ysNl4Sqfj9Gs3kRKhZhI9TZbaM1oSc2eBU3M23bv3IyhnvxKkjT55EWn48Ic/TENDA/F4nM2bN3PxxRen9/3hD3/gueeeSz/+7Gc/y6FDh4hGo3R1dbF+/Xquu+66fJhpY2Mzzoh9RyDZD4BSPAdF8lls0egIOJ5FIAZAT/JSkkqZpfZMmvJrRCkMQHf7NfT1rMy7DRWLf0vx1HUAKMkAR576GYlwVd7tOIUgqATO+xOV73sLjgqtZ4ma8tL7yNfo/MvvSPXUWmabzegRZAczXr6Zlfd9AV+vVqucdEbZfPkd7Lj4r8hOC+tCVIFVh99MWbgOgH5XNy9N+wdqntMTnaqX2dIV6ccH5WcsFWYAKKo/L73df3xiRY8AEosXpLfdO231Ops8OUg2Njb/nggoOE5FkUQHyWD+++jkgiSECTg0yV4VF+1xayPZTlc3k+p/l37ceOS/SOWxNxJoaeG1538VT5m2iEhGJnHkqV+SilsrkOOs2U/Ff74Z38q/pf+WOHIB7b98kPCmW/IqbGEzNoIn5rDqH//DtC03IA6kr/VWHWH9G/+X5pkWy0WrsOzYDdT2aAvppBhnw/S/kXDkud+QCnO4GregKcV1KIfoUK1VW/OUz8ZVVANAMtxOvPOIpfaMFrminNRUTWlV6ujC0ZT/Xlo2hYftINnY2JiK1LEpvZ0oXYWaY4F8vil2PoaAFrXpTV5MXLZO0Q6grOphAsXaYjGVrODY0U/k3QbRGWPKZR/HVaSlR8d6Z3LkmZ+iDNSJWIXojBG84WuUve19iMXaIkdN+Ol95Kt0/O5uEo3LLLXPZmg8feUsfOKDrHjgcwS6tOiMIqY4svpfbLn520SKra2tAZh38jKmt68GQBFSvDLrbnq9rXm3o5oFVKFJUSfUCPvlJw1GmI1A8dQL0o96j71ooS1jI74ik/7t2bR9gl2hbMzCdpBsbGxMRUx0IYYOA6C4y0n5ratZGQuSEKbE+djAI5G2+FsstUcQoG7GD5AkTUCiq+MKujouzbsdDm8XM6/4EA6PtniNtC+l4fnvocimiqOOCM+sF6n60Ovwrfh7+m/JE0vpuPNuuu/9PrKddlcQiEkXk1+5mXPv+gbVhzMF/qHKBja96Rs0nPMwqoGyZT6Yc/Ji5p/M9BraPP1ftJcczrsdbrWI2VyZfnxAXkdi4OaNVfiqF+H0aqnH8d4m4t1HLbVntKguJ/FFA+p1iSTu7XusNcimYLAdJBsbG9NxdGb6YSTKVltoydgIOJ7CIXQB0J9aSSQ1x1J7XO4Oaqf9LP244egnSSTyXx/lLjrBjCs+gujUnLXQiTUcW/8dVMV6J0n09BO88SuUv+M/cFQeSv89uut62n/+MH1PfwIlPrFq4s4aVCg7uJolf/kuda+8EUnWGg8nvCH2XvoHNr3xG/RXFEbT91ktF7DwRMYp2T7lEZrKd+iMMAkV5nEdTrQobYuyh3b1QP7tyEIQHRRn1R6Fjm2w0JqxkVg4H9xuQKs9EuPDt1yw+ffC+quYWQjCsBrqRprxhtrrelr4OfYq0p3bKO6bw37D9HxDu/V359KrKJd+Q0YiVrn0LjAcq9/uZARz61hv0OdINeqDpNf3wMAuoz5IjiH2S/37SCZDqM5iUkVzkdwBpFTvGc9zGtwtNuqT5NFpGHl6n6PT8Up6xd8JJnn+QWP0AwB0xG9hlvMr6Z9FLn2OAHw644frY+StfJxwz3l0da5FTpXQeOS/WDz/02f8VMelD9Jw+5Hxle/AedlH2PvUb1BkD73HL6dp/TeYffFn8Oi8LtGgD5I0ToXv/lnPCCisrAAArQZJREFUU/qhDfRufitdz34SOVIOKQ/hDR8gtu1myi//AcXL7kUQM/PJBj9OReeklMCgl5dg1Adp+PFGvaMkg8Y6euNFo6Y8OSIPXAS8bdOofeEdFDUtTO9TxBQtS9bRtPp+ZHcE72ljFYMLlF5fq5TBZ6n3WdeduJC5jRn1yr1THqOp9kVcp+bV61MEyAZKaIpsdLLNnKcnKysoU6cBECPEAdbpnuf1et2Bfg+m4focpfcPfIUDtcuQ3FoNZLTrEPFIM0hGx9Y9tPF+/d2j6l2oArGVS9OPPVu261/zc+gladwvSK8XkdGxc90//BNyXS/rricMfj9j7u80Tv2T7AiSjY2N6QgoOLsGiqwFkVhwlf6AAqTM9TxuUZOuDctzCaXyryCXjSDA9On/h8uppbh1dV9Ac+vIG3CPJyU1rzHvso8giJoj2HnsGg6u/w6KYnCXIE8Ikkxw9V+Z+vHLCF7wm7QkuNxfRdsD3+H4rx+kb881qAYXbJux42uexfQHPsvcu749yDkKTd3Gjlu/yLE1dyG78yx4oENt87nMPXJT+vH+unUcqV1viS1etYyZaibFb5/4KCmsjXQIkpuiWu08rqoKvY3WyoyPhVTdZJTKCgCkppM4WtsttsimkLAdJBsbm7zg7NoEA3fHY8FzUCfY6UcQFCZ5MgppJ6O3ohqGP83F6Qwxd9a30o8PHf0Ykag1IhLB2pcGO0kN17Fv/fdQCiDd7hSSt4/Kq7/N1I9cjX9+pndNomUBLff8gmM/f5Le125FSbottPIsQgVvw1Jq//FV5tzzDUqOrkjvipe0cOR13+XITd8mWnbSQiPPpLZlNfMPvSn9+ODkZzhU96wltgiqyALlBiScADQJm+kWGiyxJZviyasRHVq6X6R9D6lop8UWjZ748ow4g3vrdgstsSlEJtYKxcbGZsIipvpw9e8DQHEUEy+eWI1jAUqcm/BJWt5/XKmjI3GlwQjzKS/byKTq+wFQFB979n8TWXHpDzKJ0skvMm/txxAGUuvajt7Armd+jpwqLIfDVX6M2rd+iMnvvhV37c7035MdM2l7+Jsc/+F6up79BHK/tX2vJiyKSGDvGur//H9Mvver+I5n0pgSRR00rv0d+97xaUIzthin/+SZ+hMXMf/gm9OPD096gQN1T+mMMJdZ6uUUo4mKROjksGCNo5aNwxMkUKO1bFCVFKGmjRZbNHrk4iKS87RaUiEcwbXfWql0m8LDdpBsbGzyhrcrIwEbKVtjmE9eaAgCTPb+Kf24JfZmkoq1/X8AZk7/KV7vMQD6w3M4ePi/UC16c0vr1jNv7ccQJa3BblfTWnas+x2phN8ag3TwTX+F+v98PbXveCfeaZlFnhIpo+f5j3H8h+tpf/CbxFvmWmjlxMERqqR045uZ+rtfUvPo7bjbp6f3xUtaOH7Fr9n77k/QuXQdqk69oCWoMP3YFcw5kklTPTb5efZNedwyJ65aWUSdqqXyyqTYLT6IYlAXmA+C09YiiFr6bF/zZuREv8UWjZ74OStA1JbA7q3bEWTr1RJtCovCyX2wsbE563FGG3BEj5PyTkH2TCLhn4M7bK0S02jxOw5R5nqOrsSlyGqA5thbKXX+1FKbHFKUhXO/yJYdd6AoHlrabqS4aA+1NQ9YYk9p3QvMv+I/2ffML5CTAXpbV7PtiT+z5Mr34vJ0W2LTcAgC+GdtwD9rA7GTi+h56b307boeVAeq7KZvyy30bbkFV/VeAkseILDoYcSSNqvNLhiEhBvPgQsJ7rwaX+PiM/bHag7SvepftE7fOkh0oJAQVJE5h26iruX89N+OTHmSo1PWQcppiU1+pYq56tXpxweEJ+kX8t936XS8JTPxBKcBkIqH6DvxqrUGjQHF7Sa+dJH2IJnEvcVOr7M5EzuCZGNjkzcEwNf5fPpxtPxi64zJgUmeuxHRCsq7EpfSl5xtsUUQ8B9h7sxvpx8fPHI7vX0LdUaYS0nNayy7+h043JpD1N+5iK2P3EOkd7rBSOvw1O6i5k2fYson11JywW8R3H3pfYnW+XSt+zzHf/gCLX/8I31bb0aJFV5ULC+oAq7jiwg++imqf/5XSh/99CDnSEUhPH0zJ97yJZpu+yzhORsL1jmSUm6W7n7PIOfowIwHOTp1nWWRI4fqYUHyjem6o5PCNlpEC6TFT0MQHJTWX5p+3HvsBVTF+ojWaEksWwIuLQ3ZvXM3YjRqsUU2hcjZG0ESBe1foZGDScYS4gYH0Hk/DGU9jWS8jd5rXYnxXF/XGPeRo8y34XuS237d74rBYkNPxttov5GMtySOXuY7e6w3sodwog3ZVUXSNwPZNxlXTOt54hQNZL4N9w9/sXZL+hdyt85YOE2KW2xniu9vNETeA4gcjbyPVcH/QhhGqtVjkBajJ8XtE/XVqrJluqfXPEQ0PIeGk7ehqk727Psmk1a8BY+ra0xzuwQjyWr91xWs2soF17+JV5/4M7FwLdG+aWx55O+suOyDVNe+qDtWsjAB01N6jJJr/h/ypT+kZ8fN9Gy/mUjjOQN7RWJHzyd29Hy6HvkaRfPWUTRvHf4ZL+IIdOI0+GEnVf3Lrp5MuGjw2zOS6taVVjdQ+VaSPpzHluM8sgrn4dVIfVVnPCdZeoLIwqeJLHwWuVhTBPOcGq9zwjSS8U5J+mqIelLeLnH4sa5YKTN2fJBAWKvxUYQUB+beQ1v1Zk7FjZI64/XOdQAp2UDme6jxKsyL34hXLQUgJJzkoPTkmecWI4fTaL+etPMwb2dxzSoc7hIAYr3HiPQcHPIam0tbj1zbfui3YQFVFImtXDbwBxXXpi1pe40lrYd/T43XUAay63rjjd4zo2MbyWXrnWsLcBmdZrj3zHDRODLOXgfJxsamIBFQ8Xe9QKhGU4kKl16Cq/kvFls1emrcj9Eav4KoPIVQag4nY1cw2bvOarOYN/3HhPrn0hVaSTxRxat7v89Fi/8T0cABNItA8DDnX/9GNq27k77u+aQSJbz2xJ9YfMEXmTr3b8YHsBDJ00/56j9TvvrPxDunpp2lRJcWBVNTHkK7biS060YAPJN24Z25Ad/M9XimbEZ06PfHKmhUEDqnIh45F/HwuZQ2LkGQzxT/UFxhEvOfI7TwWRK1+wp7QZWFL1TPrO0fwJXQFvxJR5g9C39Pb/CIpXZNSV5MmaxFpBNE2C39C9XgRkU+cLhKKKkekPVWZLqPPWetQWMkOW8uapHWu8l58BBSz5n9+GxswHaQbGxsLMDbt5X+iqs0NbvAAlLOMhzJ4aMchYgoyMzw3cHuvq8DcCj8LqrcL+EUw9baJaZYPv/zbNj6V+KJKjp6z2Hn0dtZOvO7ltnkDTRz/g1vYttzP6at8QpU1cmOF79Lf+9MFpzzrUFNWgsVd/kxqtf+iKpLf0R/0wp6d9xEaOeNWuPZAWLNi4g1L6J7wwcRnFG8017BN/0l3LW7cNfsQfKGLHwFBiRdCG2zEJvnIrbMRTi+DLF30pBPVaUEySnbSSxaR2L2S+BMkLBIOXEsBNuXMH3Xu5AGbI5629m16A6iPmv74JSmZjElqaUdqyjske4nLhTGd6a07lIEUVsy9rVuJRWbWOdrGGgMuyojNe9+bYt1xtgUPLaDZGNjk3cEVcbX8xL9FdeAIBIpvYjitgetNmvUlDh3Ue56kc7EhSTVIIfD72Be0a+sNgu3q4sV8z/DyzvuQFWdHD7xdoL+fUytse49djjDrLz8P9n72n/TsPt9ABzZ9QH6e2az/JJP4HJPjDu5ggC++m346rdRc803iBxbRf/hiwgfuphYc1YdTtJL5OClRA5emv6bI9iEs3ofrpq96X+O4Inxavw+IlQVCJdBz2RonovaMg9a5uFun4agk/4nl7SQnPEayRmvkpyyHVyx/Bk9XqhQc+wqJh++HmEgb6m3+Ai7F/2elNPaGxtepZy58YyCXoPzWXo4ZqFFGbzFM/CVzAQglegndOJliy0aG6mpU1CqtdRQ6WQz0onC6r9lU1jYDpKNjY0l+HpeIVy2FlV0Eylehb/zWWDiNRuc5v0D3YmVKHhoit1AtXs9pa7dVptFafEuFs78DrsOfQmALQe/gtfdQlWpdapTgqiw4Nxv4C85yp6NX0NVHbQ1Xcb6Bx9m1eXvp7hsn2W2jQVBSuGfsRH/jI1w5fdIhcsIHV5D+NAaIocvQu6rGfT8VE8dqZ46ovuvyPxRSuAobkEqasVR3ALFbUjFLUjFrUhFbQiuMIIjjuCIozhkBEcCHPF0TYqqiJD0oCZ8KIkiSHhRk15IelH7KlB7J6H0TkLtrUHprYXeapDP7Et1uo+mikmUKdtRZr6CMuMVwqUtEyZ9biikpJdpe2+jtH1Z+m+dNa+xZ/bfUQ1qG83GofpYEHsrDrwAdEj7OOHcCEn92qt8IEhuyuoz39fuk8+jKsPXLRYqKhC74Nz0Y/drWyby19kmD9gOko2NjSWIShRfz8uEyy4B0Um47BKKeu6z2qxR45Y6meX/EwfC/wnAnr5PcF7Zx5AEfXGFfFBf8y8ikRkcGRBteGXP/3HJsndS7Le2zmLqvL9SXHyYzc/9nESsnEjfVNY/9ACLz/8y9bPvyWtEZTxx+LsoWvwQRYsfQlUh0T6bWONy4s0LibfOJ94yDzURGDxIdpHqnkKqewqj+saISRBlSHmMn2uEkEKpbECpOYBasx9l0j7UqiOQXUOlFFaz39EQ6J7J9D3vxB3TGv+qKJyc8SjN055Ala2R8T6FqDpZGLslLcoQFls56H6wYJzR0tqLcbi072w0dJRI937EQjFuFMj19cj1dQCInZ04D9iNYW30sR0kGxsby/B1v0A4eD6ILiIl55LqW4dD7jMeWGDUex+iNX4hvamFRJVaDoffwZzAHVabhSDA0pnfJRKbTEvXJSTlYl7c9QsuXfZOvG5re/lU1L7EmtfdwKanf01v5xIU2cv2Dd+j9fjlLLnoc/g8E6/GIRtBAHfVQdxVmYWYqghEu6eRaJk/8G8eqd7JyKFqlGjp6CZQnNq/0eAKQ0kLFLdASQtC1WGo2Q9Vh0hYH6wYfxSR2iPXMeno1emUupQjzNGFf6a3wvoor6CKzI+/iSJlMgBxoY/d7nuQhcIQ9/AUTaWoQksbVeQ4ncefstiisaEC8fMyMu6el15BsKqTts2EwXaQbGxsLEOSw/h6XiFStgZEJ70laynvmni1SIKgsqDoJ7zS/RMU3ByPvo4q9waCTutTxgRBYfX8z/L89j/Q2z+faLyWF3f+iouXvhuX09oCcF/gBBde/0Z2vfw1jh+4DYCW49fQ/a8VrFhzO9V1zxscYWIhiCrOskacZY34Fzw5aJ+S8CD3VRPrrUUOTdKcpr5K1KQXVXahptzISS9qyg0p7TGKBM4ogiuC4IqiOOMIrgg4o+CMIfh6EEqaEUuaEYLNxFzR4aNzEzhCNBTOSDmTdrwPX8/M9N/6ggc5svBPJD091hl2ClVgdvxGSuWB2h5i7PbcTUIsDFEGQXRRPuWq9OPuE+uRkxPv5hWAXD8FebLmhIodnTj3Tazm5DbW8O/pIBn2nzHSwh+7Xr3RsXXl2808tlHE3KjnTw49gXLti5BLzwXD151DjyW9ngkjGa/q9LEwel2C4f7hj23UQ0ky2i8Mr0jmlM7M9Q+GniUaPA9VdBIquoDKvqdwKENfiF1DjB+0X6eWQK9HEhj3QdLb7xaTuF0NzAn8iX397wdE9vZ9kjXlH0YS4rhF/Zx9j85+vX0AfqM+SUISxDhXLH4/T2y9i/7YFEKRWbyy+ydcvvQ9BnPrvycunZ49AKLObyDd58gZ4dw1n6Gu/mk2bfgeiXgZ8WgVG5/8C7MX/I6lq76Jw3GmIEAube4Ug5+mbHBikHWaBrkMxiaG+314EuAJ4S4/OuzYJPphnpiqH1ESdJwgxeCEJBvuN3jPdE5aSVX/dRnuP61Xkf/kaip3vQMx5QNAFWRaZz5C2/QnEASVbL09vR5KAEll+O94StYfO+y5UoW62FVUyQPRGVLs9d5D1NE66F3UOxfn3k9I7xogUFp3CQ5XEQDRvmP0d+/IXLMMr225rJH0d492PaAC8fPPSz92b3wZBHXIdYOZfRFzWWMZHVswWrMaXLP1jm98bP3dKLoHz/HYBvtzxGh6GxsbG1OR5D78oY0AqKKLruK1Fls0dmb47iPo3AtAWK5jf/+7rTUoC5+7nSuWvgePU5Mybg+t4IXdP0ZRCuM+2eRpj3PVGy6nevKz6b8d3PNennzgMbo7F1pomc1EQUh5qNz+Hqq3fSDtHMW9HRxe9QPaZjxuvLDPE9WxC6mJXQBo9VD7PfcRchy32KoMnqJpFJVnpdY1PmkwonCRp0xBrh2IHtm1RzajwHaQbGxsLKe45zmEAWWk7sBFpMSAwYjCRBAUlhZ/H3Gg3P5o5CY6E4sstipDkbeRy5e8D6ekRehOdl3CC/u+gzpOncdzxetrY83Vb2f5+V9EkqIAhHrmsu7BR9i7/SMF48zZFB7etiXUvfB1ik5cmP5bX+1GDp7/v0SCDdYZdhrl8aXURzOpa4fdj9Ll3G+hRYMRRTfldVemH3effGHCptapQPzcTO2R+6WX7dojmxFjO0g2NjaWo0WRtN4aquims/gKgxGFS8DRxNzAHwYeiWzv/QwJpXAcvrKifaxd/EEkUUtbO9L2el488I2CcZIEAWYt+ANXvf4agmW7AFAUF9s3fZEn7n+CtubzDI5g8++EGCmnevNHmLTpEzhjWtNexRGlbelvaV92B8oQ6ZlWURpfyLTwTenHx1zP0uraap1BQ1A+6Yqs1LoG+rt2WmzR2JGnTUOprQXs6JHN6LEdJBsbm4JAiyJp6k3dRWtIOMottmjsTPfdT5lTW1hElRpe6/kshXTjsjq4iTULPoWAVmN0oPkWXjrw9YJxkgBKSg9y5euuZ/6Sn3Eq2by3ez7PPHofLz37cyLhamsNtLEWRcJ38AYqnv0O/tYV6T9HyvfQdNFX6Z9cWM1Mg4l5zAi/Ma2m1+p+hSbXBoutGkwguIhAyXzgVGrdOostGjuqIBC/6OL0Y9fLG+3okc2osB0kGxubgkCSQ5T1DdSfCA7aS2601qAcEASFZSXfwSloilQn42s4FLnZYqsGU1/xDBct+HTaSdrffCsbD361oBw5SUqydNX/cuXrrqesYlv678eP3MzD/1zP3h0ftNPu/g1xdsyn/Ln/pWjvWxFkrQ9UytVL29Lf0LL6B6R8HRZbOJjSxAJm9L8ZYUBko929mUbfYwXT6wjA6S6nvOby9OPOxicnbGodQHLBQpRy7Sab2NyM45AdPbIZHbaDZGNjUzCUhZ5GGuiD1OdfTtQ1zVqDcsArtbO05PvpxztCH6Q7OcdCi85kWtVjXDL/vxAG1Oj2nXxbwUWSAMort3PFjTew6sJP43Jr/ZFSyQBbX/0yj973FC0nLzQ4gs3ZgBgpp3jzhyh76Ys4+rXCexWF3qlP0XTJF+mf/EpBOR2g1RzN6H8z4oBocIdrK8d8DxWMYASAIDiomnwjoqipIPZ1bCfSO3EdCtXhIHH+BenH7g0vFNrXwmYCYDtINjY2BYOkxqnofSz9uK30JgpnGTF6qt2vMN33TwAUXGzs/jJJxWexVYOZUf0IF8//dNpJ2t98G8/v/X7BRWZEUWHmvLu4/k1rmDXvj5xKuwv1zOGZR//BC+vuoKdrrrVG2piCGCsmsOvtVDzzfbxZIgzJ4CG6Lv4ynQvvRnFGLbRwaCpjq5kefkM6ra7DtYUG/wMF5RwBlNWsxeWpACARa6f75MTuP5ZYsRLV7wfAcegQjpMnLbbIZiJSWFfAswEjXfccxqu59DmCnO6s5dpPyMweTLn0D8ipx1KuxzboTaDfg8lgrMEFWK+/hiTqNxeQJP39Dp39ej2SAByCQkX4RXqK1hB3TiLqnk7Et4SS6DbAuJeRU6cPUi59jrRjD7/fIwzfS2hZ0W8IJRfQmVxAWJ7M1t7bWVP6lUE/db3xevvGY79TUFg46V+4BJmn9v4fqurgSNvrURQfr1v0QRzS8H2WXAaNKPTaoTjH6Pq6vV1ceNHnWTDvbja+9E3a21YC0HTsOpqOXcP0mQ+wYsUPKAkeHvYY+t2bAAPbkjonHaPWHKLR69b53Utqbo0/ZJ0GaYpB8zS9sdp4/RPi6b2KsnEP1+co4UM8eBO+gzemU+kAFGc/sYV3kZj6LJKg4kx5hh6P8TkjIej3WNI7Z+md68r6LqEqcm36cZt3Iyf8jyFlnZslWf/zlEWd99ywF9HIehX5i+ZSXLoUAEVJ0nbyIRQhqX9dNWhCZup102C84vOSWHnOwAMF90sbMq/FzH6POb4uXXLtQ2nw29TvdWS01jh7Y3N2BMnGxqagEFCo7nkg/bi15EYUgwaZhYwopFhT+hWcgpY6eCx2OQcjr7PYqjOZXfMg1y7+ANJA49mGjiv51/Y/kUj5LbZsaCoqt3PD627kojW34/W2DvxV5Ojhm7nvn8/zwnM/IhSaYqmNNmMk5UbY9wakx3+NuO/NaedIleLEZt9P35WfIDHtmYKLxACgQkXoKqr6Ms5Ri+85TvgfLTh7Hc5SKmoykuOdrU+TTHRZaFHuJFafCy6tFbBz9y7Enm6LLbKZqNgOko2NTcFRFNuNP3YAgISziu7AxK4xKXI0c0HwW+nHr/V+gq7kLAstGpppFU9zw9J345T6AWjsvpB/bL2HSKLMYsuGRhBU5sy7mze/9XxWnftVPJ5OAFRV4tDBW7j37xvY8ML36QvVW2ypzYhIehEOvA7p8V8i7X4HQlKTx1eFFPEZjxG68uPEFv4N1RW22NBhUAWqQjdS0X9Z+k8n/U/S7H+64Gqj0nVHkhuA/t499Pfustiq3FCKS0guWqI9SCRwvbLRWoNsJjS2g2RjY1NwCEBNz/3px23F15ESCzOSMVKmeF9grv9UPZKb57q+TVQOWmvUEEwu3cjrlr8Nt6MHgNbQMv626QG6I9MstUsPhyPK4iW/5s1vXc3KVf+Ly63dNVZVJwf2v41//v0lnn36V7S0rC4olT6bAfprELe/B+nRO5B2/gdCvBQAFRll6tP0XfEpokv+iOrptdjQ4RFUB7Xdt1IWztzMaQw8RKtvvYVWDU/lpGtxe6oASMQ76WiZuJLeoCWCJS68FCQt28C1dQtiJGKpTTYTG9tBsrGxKUi8yUaC4VcBkCU/rSWFl5Y2WlYW/5xy5x4AwnINz3f/L7LqtNiqM6ku3s5NK96C390CQE90On/b9ADNvcsttkwfpzPC0mU/5S1vPZflK76H06nJrKuqg6NHXs+jDz3AA/96koP730pKp27FxnxUFZS2xSQ3/A/SEz9HPHQjQiojYKJMfhH5yk+gnPMzFH+7hZYaI8l+6jvfS3FMi16oyDQH/0GH91WLLRuaYPAC/MWaoIkix2k78SCqql+rWOjI02agTJsBgNDfj2vLJostspno2A6SjY1NwVLdcz+ioqlTdQcuoM853WKLckMSklxa9gV8YhsA7YklvNLz6YKMapQHDnDbOTdS7t8HQDRZzj+2/J0DrddbbJkxLlcfy1f+H2+5dRXLV34XjzezwO7qXMxL63/IP+/ezOZX/5v+Ablom/ygyk7ko1eQWvdTUs99B/Xk+WmVN1WKo0x/gtSVH0M57/tQfMJia41xJycxreOj+BLauUkREjSV/Yle32aLLRsav38uZWUXAaCqKm0nHyGZ6LTYqtxQHQ6SF16afuxe/zxCcmI7fDbWYztINjY2BYtT6aOq99H044biW1ELLZl/lPikTi4t+wISmhjC4ej17Oi/1WKrhqbI08wtK99AXfAlAFKKl4d3/ZoNhz9bcL2ShsLtDrF8xQ+55dZzuPjSj1FRuTW9Lx4vY9eOj3HfPa/wzLrfc+zo9cgpt4XWnr2oqoDStojUa58g+eBdyK/djtozM7Pf24G86M/I174fZcWvoLjJQmtHTlF0EVM7PoRT1lICU2KI4+W/IezZb7FlQ+NyVVNZeV36cVf780TDRyy0aHxIrjwXtbgEAOn4MRwHD1hskc3ZwNkr8y0Iw8sPGsplG1z4c5A1zFUuO5exuUhv5iozqTs+ZwnLsR87JwlxQxnvHOfWkWnVk+keyX5R79gGSkuGMuA6+12SvsCyY4ix1ZHn6AmcR8w5mbBzGh2+i5gUHbpPh56kr1PQn9tov0fQkfkWDaS2T9s/2bOLS8q+zjNd3wTg5d5PUO06yDTvmUXFhjLdBqLVTgNpdd3XJSh4XD3ctuI2Ht3zPXa1vBmAVxs+Tlf/fN646CN4HH3Djpd0vuOSwQ/A6OcjjeY87EixaM59LJpzH61ty9m+8z0cOXoDiuJCVSUaj11D47FrcDlDTJv2GDNn3U9t7QbEYWTjJR3pWyMJcdFQCFxPllr/ki2rRt/h4b9Lip6kNCAbfCLKEJ9nsncqkaNXE224EjlSc8Z+sWwf7rn3EZ30Gg4diX6j36be7z4u6L9nQ51zBh17qHOWKlDUczVFPdek/xRzHudkxZ+QpVBac9PoXGl0rtU7TyuGMt6D90uSn5qamzPNYHt3Eep5begfmtEaKZdr3zhfk5VgKamlmtQ/cgr388+AMLQ4dc6tUCxaQxkdO2el7RzWOQY/zZxa1+jLj+sce5ykx89eB8nGxuasQEChrufvHKr8FADHAm+gIrYZp9pvsWW5MdP3FN3JmWztew8qEo92fJe31ryDMmeD1aadgUNMcOPCT1BTtIunD34ZFYlDHVdyx6uP8tal76bCP3zPoUKjumorl1/2Uc6PfI09e9/B3r3vIBKtBiCRLObAwVs4cPAWvN52pk9/iFmz/kVV1eazud3HuJLqn0SsaQ2Ro1eR7B6ica8jgrPuRZwzH8JRoaVvxuSJUw8mKC6C7W/DG1ma/lvIt5m20ntRdW42WIkgSFRVvQGHoxiAWOwEHW1PWmxV7qhA4qLL0sIMjm2bEXt6LLXJ5uzBdpBsbGwKnkDiEKWRV+n2rSYl+mkI3Mzsvj9bbVbOrCz+Dd3J6TTE1pJQi3iw/ce8tebteMThozJWIQiweupvqQzs4/5dvySaLKMzMos7Xn2UNyz+MHMqnrbaxFHh87Vzzsr/Y8XyH3Pi5EUcOnwTDUevJZHUFpHRaCV79ryHPXveg8/XTF3dc9TXP8vkyetxuHusNb6AUBWJaNsyepvWEDt5PqnQtDOfJKRw1GzGOfVpHJM3IjiGbz5cyEjJMspa34czWQuAikJHyWP0BJ4vOBnvbCrKr8Hj1mxOpUK0tt0HBtHGiYA8cw5KndbrTOjrxbm1MEUxbCYmtoNkY2MzIajt/Rchz2Jk0Uurdw3VsRcpTk7s/HlBULm07Gs83F5LR3IuPampPNL+fW6q+ghSgd6Nnl6+nnevuo5/7riT9v4FxOVi7t72Jy6Z8QMumf5Dw7ShQkMUZerrnqe+7nlSF36e442XcejwzRw/fgXyQGQjEpnEgQO3cuDArQiCTGXVZibXPUdd3bOUV+xANEilOttIhquINJ9L+MSFRFtWoySHluB3lu3FN/0JvFOeIeKK5dnK8cUdmUew/e1IitabSRGjNJfeRcRbmPVGpwiWXEAgsAgARUnQ2nYvihJhopegqy4XyQsuST92bngOIVWY50ybiYntINnY2EwInEqIKeEHOFr0VhBEDha/m+WdX0fUrdkofJxilBsrP8XfWv5CVCmjMX4u6zq/xtXlXypYZ6PUd5x3nfM6HtnzI/a23QCIPH/kMzT1nsNNCz5BwF3YsszD4XDEmTH9MaZNf4xEooiGhms4cuRGTp68EFn2AloT2rbW1bS1rmbr5s/idndRVbWZyqqtVFZtobRiG2534fbrGS2K7CDaNY/utpXE2hcT61hMKlI99JMFGVfFbjy1G/HUvYCz5Hhm38D7N+FQHBR330gglFmMp5xtdFbdQUTosc6uEVBUtJzS0jXpx+0dj5BItFlo0fiRPG8Nql9zVqWGwziOTeybZTaFh+0g2djYTBhqI8/Q7jmPfuc0oo5aGv3XMzX8gNVm5UyJ4yQ3Vn6Ke9t+jax62Be5Ho/YyyWl3y3Y1B2XI8KbF7+fDQ0f49nDn0NF4nDnWn758rPcOP/TzKt63GoTc8Ll6mPOnH8wZ84/SKU8tLScS2PjWpqaLqWnZ076efF4GY2NV9LYeGX6b8Ulh6io1Bym8oodlJQcwuUOWfEyRoWc9BAPTSPWO4No11wi7UuIdC5AVYZX95Pc3fgmvYyj9lXck15FmgCvc6SI8UlUtvwHzkRGCj7m3UV35V9RpSgkXRZap4/fP5/yssx3srPrGSKRs0PdTa6tI7VA6zlFIoFzw7PWGmRzVmI7SDY2NhMGAYVZoT+wvexLqIKDRv91lMe3EEg1Wm1aztS6t3Nd+ed5uOP7qDjY1n8bbrGPy0t/ZLVpwyIIsGb6T6kr2cJ9u35Of6KaSLKce3b8nuW1f+W6uV/G7Zj43ewdjhh1dc9TV6epJ/b213Ki6VKaGtfS0nw+8XjZoOeHemcR6p3FkUNvTv/N8//bu+84qaq7f+Cfe++U7bvAsoUiTQEVY8EC2DUi9pjoYwvRFB9L1J+axERT1CTGkp7YYh5jiZoYC5bYG2gCFhQUUUCawMIubK+zM3Pv+f0x1xVk53yXPXuZ3dnP+/WalzJnzrln7tyZuWdn5vvJqUVR8WoUFK9CUfFqFBavQlHxKuQVVCEUat9pRSDcRB7iHcMRby9DR9M4dDSNR0fTeLQ1TUCibYTY3wq1Iaf0I+QOX4z8kQsQHfoxLNtDu9d/Fws7TAGRpkORW/tVWCp1v5SVQPOQp9BW9Ea//aPFZ3Kj4zF82AldVcAaGxegufmdDM+qb6hQCPHDP1/4hd96A3Zr//vNJg18XCAR0YBSkNyAUW3PYn3ByYDl4JOi87B3/a9giwWW+78JeXNxzNDr8WL9LwAAbzVfgEKnHgcW3Z/hmemNG/pfXDTtKDz98W+wbMtxAIBFG8/Bpw0z8NUpl2KXkv4ZmtlbBQVVmDT5QUya/CCUAlqax2LLlv2wZfO+2Lx5X9TXTYH3hU9dYrFSxGKl2Fxz4HbjOU4HcnK3ICe3FuGcOkRz6xDN3YJoTh0cJwbbicO2E3DtJGwnAduOw3biABQ8NwrXzYGXzEEsmQcvmdN1XSJWgnhHGTo7hiPeMRyd7WXwkt3/XiidSOE65A9/H6HSj5A7fAkixatgZfFvrqxkAfI2n4Nw25e6rkuEN6Gh7H4kI5syOLOeiUZGYvjQr8KyUpXdmlsWo6Hx9QzPqu8k9p8OVVwCALA3VSG09IPMToiyFhdIfUzMUDIR5F+txGwos+F1+yXIbIL+nLEUZHaUSU6SI2UoaTJgAMDW/G5G1wYAISGz57OslHEdT6EuZz+0h0ahLTwGm/KPwZiOZ7R5KWIOkiZLJdXfJGOp52PvXTgHSZWPVxt+BAB4ueFq5NuN2LdwTrd9c4R563KOUu3p93lYeKwjWz2vI9EGfH3vb+PdjWfimeU/R9wtQH3HONz9zpM4evwfcfT4P8LZaq62cBBLOUkmwsLQrnC/va3bLSC3ZB3KStYBuz2BhFJw3Qjq6vbA5s37oaFhEpqaxqOpaQLau8kCAgDXzUVb6y5oa91lR+9Kn3HCzcgpWY3cojWp/xavRn7pEoRz6wEAbZqv2QFA2HKEds3zR3ruefpTFd3zT5evBGz7muO0TUa0+jzYbnHXdW1Fr6Nl6FOAndiurIH0eia9VkqvtckdzMILh4ajbNjpXVlHbW3LUFf/YvfvF0Hm7hiMrWv3SsuR/NJ+qX8kk4jMe2n7uQR6PqC7gf6xlN/vez+2KMBzRzHLKLhNB44LJCIacGy4mNzyN7xX8hPAsrE2/xSUxt9DEdZkemp9YmrRA4h5RZjfdDEA4Km6XyHHbsHu+S9neGZ6lgXsP/KfGDdkAR798M9Y17Q/FBy8vPpKLK89Emfs9f9QNoAyk3rLceIoK1uMsrLF21wfj+ejrmkcmpomoLlpPJqbJqCjvQwdHcMRi5WiMzYEQVUXC4WbEc6tRTRvMyK5tYjkbkFu0afIK16FvOLVSOQ0Dd6sJzcH0dqvItz0eUED5bQgVn4/WnIGxu92Qk4JyoaeBcdOFcPo6FiDzbX/hvHJdT+hbBvJQ2YCfqBx+N03YTc1ZHhWlM24QCKiAakouQajO17A+rzjoKwwlhd+CxWtP4OVJScEM4pvR8wrxnst50DBwaNb/oBz7PMxPndBpqcmGpb3Kb6z/6n4z9rL8PLqK+CpENY374s/LHgRR4//Ew4fewcidiLT09zpIpE2DCtdgmGlS7pt9zwHrbGh6IyVItYxHLHYUP/rchF4XgSdbhSe//+eG4FSDhwnBifUAceJwXMSsJ0YnFAMthNDONqEnNzNiOZtgROKaX8nlFRZ9BuiHeC07o1ozZmw3ZKu65J5H6Gz4j6oUDOQ7P/7xbHzUTb0LIScVFW3zngVarbMAbLga8efcb90INSQUgCAtaUGofcXZnhGlO24QCKiAWts2xzURvZFR6gCzeFdsTJ6InbrfDrT0+oTlgUcNeQmJL18fND2FbiI4B+b78A55d/B2Jz+f3Lg2C6+POEPmFg6F/9c8mfUto9H0svBCyuvwqJNp+Kru/8Yuw6dn+lp9iu27SI3rxa5ebUAlm3XHlP6T5diim/pPRYfClR/Hbkt+3ZdpawY4qVPIlEyD+inJfa/yLbzUTb0bIRDQwAA8cQWbK7/F5TKnj9AeMPK4H7J/+2e5yE67yVYamA8PjRwDeykMCIa1BwkMKn1b4BK/Y5gWe7/oNEZn+FZ9R3LUjil9BpMyk19tS6h8vBgzV/xaWz/DM+s53YpXozLpx+DI8beBtv/Hcrmtt1w58J/4aElf0JLZ2mGZ0iDirKB2mOBVTcAWy2OkvlL0D7250gMmTtgFkeOXYiKYV9HJDwcAJBMNmJz/T/gqY4Mz6zvqFAIycOPA5zUb9xCi9+BXTcwc9ZoYOECiYgGtJLEJ9il4zkAgLJCeDf/EiSh/0H5QOJYSZw2/HLsmpsqMZ1Q+fh7zd1Y2XFwhmfWcxEnhuMn/gqXTTsOuxR/XtHuvU1fxc3/nYf/rvsGPOHTESJj7eOB1T8Das4EvBwAgOc0IVb5f4iNuB0qPHB+0xJySlAxbDbCoWEAgGSyCTX1D8H1WjM8s76VPPAIqOJUGX2rtgbhd9/M8IxosOA7EhENeGPb5qAwkUpSb3Mq8WHeNzI8o74VtuM4Y/h3uxZJSZWLf9T8BR+3HSP07F9GFH6Eiw88BV/b4wfIDTUCAGLJYsxZ9iv86a2nsLph+xLYRMbiw4H1FwJrfgrExvhXesCQV9A+9nokC98dUOW2QvYwlA/7OkKhEgBAIlmP6rq/I+k2ZnRefc3dZQK8SXul/pFIIDTvWVhe9paYp/6FCyQiGvBsuNi9+S9wVAwAsC56FDaGD8rwrPpW2I7jzLKLsXve8wAAFxH8a8sf8V7LVzI7sR1kWwoHjXoIPzzkMOw/4uGu6zc074Pb33kcd793Dza1TMrgDClbeMlCYNNZwMpfAc1bvR7krAPG3QCMeABwBtbX0UJOGUqLz0XIKQKQ+s1RTd3f4XrNGZ5Z31J5+Uge/PkfgEJvvQa7uTFzE6JBh7/o7AWjrKMg66javQ8vMM05Cjajqfddg81YEr6nLo7d+9wES+grHWa6/tLYUnaHo8nV6WnOUTphTf9iVY292/+G9/JTpbHfz/sOhrZ8gjxVl+orjt37dqlvRBpbU21q6/yYsJXEWWWXYk7tTVjU+jUohPDwlt/BVTk4uOjB7rcN/T7XZR1FhAMpLLVr/gY3JNKI2VN+gBkjH8EjH/8Sm1onAwA+rj0Gy2qPxgEjHseJu/4OQ3OrtNsIgi38ANzTVUoUjnGRZtue8Fh6QtWyhC6LSOlzjKRjOBHg80d67tretvtMeWF0bjkOsZqvAF7e5w1OM+yyJ2APfQ2W/zjtSE7SF+le6wD5tVJ+Hd+2PeyMwLDCc2D7pbzjiWpsrv8nPNXeTR5QcO8v8huM7vkh9U2dYyUOmwXkpO6nvfYT2CuX+m367tLYgTHOitSNLQwuftRh8Js68ZxVOs7S9+/vH9ryEyQiyhqjE69jZPy/AICEXYB38y+Fl2Uvc47l4qulV+HAwgcAAAo2Hqm9Ca82XpDhmfXOhCFv4wfTjsNZe34fJdGNAFL36e2Np+Hnb7yGx5b9FK3xIRmeJQ0ESlnorDsczR//AbFNZ3++OLI6YQ9/AqGJP4Az7JWuxdFAEgmNxrCi2V2Lo874BtTUPwhPtWd4Zn3PnbI/VKUfmtzWgtD8l/r9yTRln+w6cyCiQc0CsHfH3cj1UlWO6kKTsTznq5mdVABsS+HkYT/DocV/6bruqfqf4Nn67+k+gOi3HNvFtJH/wo8PORwn73YD8vzfJyVVFK99+h1c98breG7lZWhPFGV2otQvKeUgXn8oWpb9Bh3rL4JKDPNbPFhD5iI08So45XNgObGMzrO3oqHxGFp4DmwrVXymM7EWmxv+CaU6MzyzvueVVsDdd0bqH0oh/PpzsOLZdz+p/+MCiYiySkS1Y/+2P8NSqa/OLI9+FTWhvTM8q75nWcCxQ27G8UNu6bruxcbL8Ujtr+AKX5fqryJOJ44e9xf89NBDcMy42xC2U78PiSWL8Myq7+Gn8xZgzvJr0Bgry/BMqT9QXhgtm2eh5ePfo33dd+F1juxqCxUtROHkHyA08h5Y4cbMTdJQXnRfDC08C7aVCqyNxVeivuUhKBXP8Mz6normInHECYCdOjV1PngLds3O/4otEcAFEhFloWHuCkyOPZL6h2VjYd6laLGy76TasoCZQ/6MU4f9rOu6+S2z8dfqe9DhFWZwZmbyws04ZeItuPbQwzFj1ENd+UmdbgFeWXsBrnv9P3ho6Y3Y0jZGGImykefmoLn6FFQtuQv16y6CF//8ue3kf4T8CT9HwfjfwMkZyCfXFgpzj0ZJ/kmwrNQfPDriH6O+9WEopP8t2UClLAvuwccDBalPia2aKjiLWdKbMocLJCLKShM7n0RFYiGA1O+R5ub8CElEMjyrYBxefA9ml10KB6m/Ki/rOBJ/qHoCtYldMjwzMyU5NTh7z6vxs0OOwCGj/46QnfqKVFJFMX/D2fj5f17D396/Feub98zwTGlncBPFaNx4Bqo++CsaNnwLbmJoV1uocDEKdr0Ohbv9HOHCjzI4y74QQkHO6SjM/TzrrDX2JhpaHwWEQhwDlbf3jM9/d9TehvDcZ2ANxO8LU9bgAomIspIFhf3ab0e+uwkAUO9MwJvRC03q+fRrUwuewEWV5yDPToVd1iQm4vdVT+OTjoGfLVSatx5n7vET/PywQ3DMuNuR47QAABQcvFd9Em5e8Cz+9M4/8O6mE5HwsnMRPFgpBcRa9sSWVd/Hhg/uRtPGs+G5n/0WzUPekPkomHg1CibchFDBsozOtS9YVj6K8r6FaHgKAEApD41tz6K5/UUYVSPrx7xRE+Dt6b9OeW5qcdTRltlJ0aCXtWW+lWWlLy9oXDIxOLqSiMaluE0I+8yonHag5TGFzgbt8n0OsAy44bZ13W3D0rS2pl3X1rN2oWT1F8oFh9GCg9t/g1cKboBr5WBV+GiUucswOfnCdn0d4eRDV9LXkUppa8orA/oSyrrS5sC2+2xi3gJ8b9RJuGvTPahJ7IY2byj+sPFfmF12FWYU/avb/o7mYDAp4w0AtuZIC1v630l113dotB5fm/gbHDfuL3h9/dfxyqffREu8FACwon4GVtTPQEG4DtNHPopDRj2M8vy12m2k3bZwHCaU5vGS3kCEx9PVHIfSW5MtHMNhzXEqlvEWvtblIKxv1z5/tp+3m8xDQ+2XUbf5RHR2jP1iKwqGzUNxxWOI5K5HqxtNO7b0mmHymiT1FV8rv/Baa1tlKMj5Ohw7VbXRU51obH0MnYmV2z8bAn1/MSjjDSEK5QtNqmgI3BnHdv3bWfgG7C1V6ecvTC3QMuBG5wNm5bJNSHPTl+IOcFEuvaB50nln9+1GUTxbydoFEhERABR767B/x514K+9yAMBb0f/FMG8NhnsrMjuxgAwPr8UVI0/BvTW3Y1nHEXARwb2b/4BN8d1w6rBfiSd1A0FeuAWzxt+Bo8b8DfOrTsern34Tm9vHAQBaE8Pw0toL8NLaCzBp6HwcOuof2Lv8JYTt7PtRe7ZRCuho2w31m09AQ91RUF7ONu12qAmFpS+hcPjzCEc3Z2iWwQjZE1CQcyYsK3WfPa8RdS3/RNLNrvu5NRUKI3noSUA4tcC11i6D8/GiDM+KKIULJCLKersk/ouW+Hh8FDkZnhXGqzk/wskdVyBXNWV6aoHIc5pxQeW5eLz2erzRfB4A4IXG76I6MQHfLr8EOXZ2ZKdEnE4cscsDOHz0A1hRPw1vbDgLi2qOhatSX7NbXj8Dy/1PlaZWPIP9K5/BhJKFWbFIzCaxjlForDsSjXVHIh4btV17tGApioY/h/wh82HZ2VegIBo6ELmR47uKMSTdKrR2PoCkm73lrRUA96CZQLFfkr2xFs5bzDui/oMLJCIaFA6I34M6ZwJqnD3RbpdibvQHODZ2Lews/dGzY7k4ffhPMCqyAg/X/hweQni/bRZu3vAULqz4X5RHVmd6in3GsoBJw97EpGFvoiU+FAuqvor/bDhrm0+V5q3/Buat/wZKopuwf8Uz2L/y3xhT9IH8zRcKRGdnKWprj8aW2i+jrW3ydu223YYhpa9gaPm/kYxWZ2CGO0MYeZGTEQ3v03VNPPkR2jofBZAAhK8tDmTeHgdAjZmY+ke8E6E3noblZt/ilwYuLpCIaFCw4eKI2M14Kvf36LCHoTr0JSyIXogZnbdl9V8tjyy5F2WRNbir+k50eMWoiu+BG9Y/h2+UfR/7Fz6d6en1ucJIPWaO+z8cM/b/uj5Ven/zMUj4X9dq7KzEy59+By9/+h2U5n6K/SuewdSKZzCq8GMulgIWi1WivmEG6uoOQ3PzPtj+Rwge8gs/QEnpaygZNheOk8rBanFzkG0sDEdR7tfh2OVd18Xib6Aj8RKytRjDZ7xdJsLb55CufzsLnofV0pi5CRF1gwskIho08lQjjordhOdyfwXPCmNF+FgUe1WYkngi01ML1J558/CjUSfhzk3/h02JiYipQtxV8xesiE3D7NLrsvL3OVt/qhRL5uP9zV/GwuoT8VHtoV1fwavtGIPn11yM59dcjOJoDfYsfR17ls7FpGFvIC/ckuF7MPB5noOG5r2xpeEQ1NQfio7tii2k5OavQMmw1KIoHKnbqXPMBNv+EsLO12BZqd/eKNWJts4nkHA/zPDMgucNq4A7/fOiDPb7/4VdlT2fZlP24AKJiAaVMm85Dun8E17P+R4A4J3IeSj0NmEK5mV4ZsGqjKzE1aOPx4NbbsJbLacBAOY2fRNrY/vh0srzMTy8PsMzDE5OqA0HjXgSB414Em2JIiyuORYLq0/EsroZUEj97qOpsxzzq07H/KrTYVtJjCtehD2Hz8WepXMxsvBj/m6pB5QCYp0VqG+aii0NB6O2YRqSbveBxTk56zB8+EsYXvoKkpHanTzTTHEQck5AyJnRdY3r1aA19k94Kvv3gcorgnf4KYCTOvW0Vi+FvfTtDM+KqHtcIBHRoDMhOQ/NnZVYHD0bsGzMy/k+yjo3okx9kumpBSrHbse3yi7DxJw38Y/aXyKpcrC2c2/8dN1LOL/8ckwteD7TUwxcfrgZB496BAePegTNnaV4r2YWPtxyJJbXT0PCywUAeCqEVY0HYFXjAXjqkx8gP9yAcSXvYXzJexhf8i5GFC5CNNSR4XuSeUrZaGrbFbVN+2FT4wFobN4HsXh5mlu7KCxciqFDFmDIkAXIy1vV9ZXGFjd3p805c0oQCZ0D2x7ddU1nYjHa408h9Xuj7KbCUahDTgVy8gAAVs16OG+/nNVfb6aBjQukvtaPn+0ZzVHSkGv0CwP00/slCvB+SfkbUrtOkLkhUo6Lyba/mMMyNfkQWpxKrAodCdeK4uno9Tiz81IUYssOz03KWpFykmxNu9RXym8Kf7HdAo4qfhC75izGbdV3YXNiPNq9Yvxx0z04ruROnFn6K4T83CZdjlFP2nVZR1Jfxwo+kG5ITj2OHvMQjh7zEOJuFCvqD8SHtYfhw9rDUNM2oet2bYkh+HDL0fhwy9EAANtKYlThRxhf8h7GlbyHUYUfoSxvLRzb1WYkAT2437rsKOGxTkhZXppjSXcMAoCtPLR1jkBT6yQ0tE1CXfM+qG3aB4mu0NZu5htqQumQBSgb+h/kFr2HcLi5+7Gl549BllGQrzk9fT2yrL0Qcr4Ky0otDpRKwHWfQnt8sba/7nXa5DU8NUAv23pBWTbUtBOBIr9iXXM9nDeehuXpH9deMcgqGqjnSBnVn+dmiAskIhqULACHdf4RrVYZapw90WaV4snIL/E/8csRQfZ/OrBLdCmuG30s7tv8W7zVejIA4LnGC7GsYzouLL8Mo6LZ/WnaF0WcTkwZ/gamDH8DrvoFtrSPxtLaw/Fx3SFY1TAVrYlhXbf1VAjrmr+Edc1fwtx15wEAQlYnyvNXo6LwY1QWrEBlwXJUFizHkJyqAfX1PKWAzsQQNHWMRUPrZNS3TUZ96yTUt01G0i3Q9nXsdpQUfYChRYsxrOQdlBQtge0H0A6OT4m+KAeOcwoce7+ua5SqQzL5ABQ2Aohkbmo7iQKg9j0aKB+TuiLWgdDcJ2DFs7eEOWUHLpCIaNBykMQxsRvwVO5v0GyPQK09Ac+Gf4KTEz8V/6KeDXLtVlxacSEmN72JB7ZcBxcRrOncGz9Z/wLOGHYjTh7ytwF1ct+XhuetxxG7PIAjdnkASgGb28dideN+WNU4Fasa98Om1knb3D6poqhq3R1Vrbtvc33Y7sCQnCoMza3CkJwqlOSuw5DcKgzJWY+huRtQENkCx955peY9z0EsOQTt8WFoiY1GU8cuaO4YjYaOMWiJjUJLbJS4EPpMNFyL4cXvYnjxe8gr/BCFBZ90LYgGOw+7Ihw6B5ZV0nWd630A130MQCxj89rpJu4PjN8r9f9uEs4bT8Fqzc78OcouXCAR0aCWg2bMjF2Pp3N/jU6rCGudg/CauhRHJf+Yzd8e6GJZwMySe7Fbzru4vfpWbEzshoTKwQO11+PdtuPw3fLvoSLyaaanmVGWBZTnr0V5/lpMH/k4PCi0J4qwpnEffNq0Nza2TcSmlomoaR8PT237tprwcrG5fVdsbt817fg5oSbkhxuQF25ETrgBef4lJ9yEsB2DYyVg20nAisO2EnDsBBwrAcvykPSiSHpRuF4E7W4OXC8K14si6UXQmSxCe2IYOuLD/P8ORSxZjO3La8vyolUoKViOkvwVKMlfgSEFH6Mg99Ou3xE1e4PxE6LtKYTh4QQoHN61b5TqgOs+AU8tzujcdjY1aiLUlw7r+re18EXYWzZmcEZEPccFEhENeiWqCicmrsec8E3wrDCWhE5CHhowPXl/pqe204zLWYIbdjkW/6r7IZ5rvAAA8HHHNHzv05fw9eE34Nji+wftp0ndyQs3Y8/hr2PP4a93XZfwIqhqHYNNrZNSl5bJqO0Yg/qOUV0FILoTSxYjlixGXYa/2WlbcRTkbERBzgYU5qzDkIIVGJq/DEPyl8MN8StREoUxcHE2gLKu6zxvJZLuIwAaMzWtjFAV46AOPK7r39bS+bDWL0NW/2iFsgoXSEREAEZ772Nm4td4PnINAOCt0DeQo1qwrzsnwzPbeSJ2DF8ffj32y38Rd9X8HluSu6BT5eHuzTfgrZbjcXHF91AW3pDpafZbYTuOkYXLMLJw2TbXKwW0JYaivmMUtsRGoL5jFBpjo1DfMQpt8WFoSwxBe6IEHYkSqF58utMTEacZOeEG5EbqkBuuR26kDoXRjSjKXY+inHUIRWuQF61JWzChXWX/72V6K/Wp0bFQOBKffzoXR9J9AZ73X2R78OsXqdKRUNNPAmy/SMvqD4CP38zspIh2EBdIRES+yd6r6EgUY174uwCAeeHvIoIO7Olmf/nrre2RtwA3jTkK/6r9KV5oOhcA8GHHwbhy7cs4o/S3OK7knq5KdySzLKAgUo+CSD0qixenvZ2nLDQlCtGRKEF7Ygg6EsVIelF4KgTXi6DTC8FVYbheGK4XgYKFkN3pX+JwrTgcO46QHYNjxxEJtSIvXIfcSD1Cdhwxlb6qYJvHBVBveNgTHr4KYOhW166Fg4cQ9wbfb21UcRkw4ytdWUdYvxzWe6/wcyMacLhAIiLayr7uHMSsQrwV+gYA4OXQFQirdkzFixme2c6VY7fj/PIf46CC53B7zW9QmxyFmCrAfVuuxatNZ+A7ZT/BPnkMeexLtqWQF25EXrgRw7B2u/a40n8S0a6CL41OKZ4aChf/A4W9tro2CRsvwMKrsOBhMFSp25oqGApM+xoQjqau2LQG1tvPwRpkn6BRduACKYsY1crP1j/vGOYeaNsDzlSwNP1NMzB0/U1/Z9IXuSHpSJk/+rF7nlV0cPJeJJCH90KnQVkOng9fjRK3CRPVArFvb+hyXqT7bLJPAP3P9R1Y2Df/v/jjmGNwf+01eLHpHCjYWB+fjGs3PIojCufgW2W/wtDQ5jRjpz+IpZwjO6CvmvWI9NxVmsdL98RF6lMiHZN7bXKsSFlD0mEm5nVpj3Ep56j3zy9pn+zoa5JSDmLeUehwjwcQ7brewnKE8Cgsq/sctd5s2+R1Xuxr8P7U7SGcWwRMPw2IprKeULsB1ltPpxaKltBXGntrg/RcRUfaZ9m6y4LGPzcREX2BBeCI5O2YknwGAOBZYfzL+RXWWvtkdF6Zkue04sLya3DzLidj1+j7XdfPbTkVF6x5FU/Wfwuu5utbRNkg4e2G5uTV6HBPxeeLoyY4uA8h3LFDi6OsEs0Dpp0G5Bam/t1QA+u/T8By+TVcGri4QCIi6oYF4Jjk7zHRfQ0AkLSieMj5Naqs3fUds9huOe/jpl1OxkVlP0SB3QAA6PAK8dct1+L/rX0GH7YfmOEZEvU9Vw1Fa/KbaEleAVeN8K/1YGMewrgRjrVI+4l/VgvnpBZHBUNS/26pg/Wfx2El45mdF5EhLpCIiNKw4eH4xI0Y56YqMMWtfPzd+T02YpLQM3s5loeZJQ/htnGH49jih7quXxvfHT9a/wh+WXUX1ndOyOAMifqGp3LRnjwVTYlrEfcO6LresdagKHQzQtYcWNYgCn39onA09ZujouGpf7c3AW8+Ciue4Xr1RH2ACyQiIg0HSZyUuA5jvXcBADGrCPeH/jioF0kAUOQ04NKKq/HbXU7BrtEPuq5/s/VYfHfti7it+peoT5ZmcIZEvaOUg5bEUdjYcSNi3jEAwgAACy3Ic/6BotBvELLXZ3aSmRbJBab/D1BSkfp3rA1481Eg1prZeRH1ES6QiIgEYcRxlnsVdvEWA0gtku4L/QnrrT0zO7F+YFLuYvx2zCm4tPyHGOrUAAA8hPBc02x8a/VreKD2MnR4eRmeJZFMKaA9uS82xX6OhsQ58OD/pgYJ5NgvoDh8LXKcN4yL5Ax40bzU4qjYD8TtbAMW/Atoa8zotIj6EhdIREQ9EEUHznG/17VI6rQK8XfnD4O2cMPWHMvDsSX/xF3jD8fs0l8j124BAMRUPh6ouxzfWv0anmk8i4UcqF9SCoi5k7G584eojV+CpKroaovYb6M4fD3yQk/CHsxfp/tMtACYcQZQ5H863NECzP8X0Fqf2XkR9TEukIiIeiiKDnzdvRLjvIUAUr9JesD5PZZheoZn1j/k2B04Y9it+Ou4w3Fiyb1wkAAANLjD8eeaG/DtNa/gmcazEGcoKfUDSgEd7hTUdP4Imzt/gE5vYldb1F6O8ujPURC6F47Fk38AqVLeB50JFPihuO3NwPyHuTiirMQF0k6mLP2lvzKd90C8zwOZZekvZmMr7SWTHHhpL30lghjOdr+P3bz5AFLV7f5m/wFLcETaPjaU9mLCtvQXR7xYaS+9VRKqw4Xl1+KuccfikIJnu66vTuyCP9fcgPNWz8Oj9d/iV++6oXs8pMdSOhZMBHkMm9rR571SFpoTU7Gq7RfY0nkF4t5uXW0haxNKI39GWfQWRJ1PjeYV5GtlkK/x3corAQ48E1ZeSerfbQ3A/H+mCjMMEkGdA/Xn86CBOu++wAUSEdEOCiOOM9wfYXcvVQLctSK43/413rNmZXhm/cvIyFr8ZOQl+N0uX8PUvHld19e75fjL5mvw9VVz8UDtd9HiFmVwljRYKGWhMTENK9tuxLqOKxHzxne1ha0qDIv8BZU5P0VeaPHgLdvdnfxhqcVRrv88bakD/vtw6ut1RFkqlOkJEBENRCEkcZr7MzyJH+MDexY8K4SHcAPiyMU0NSfT0+tX9shdhBtGfxMrYnvh4bqL8N/W1EKy2R2K+2qvwCP15+PEkgdx6pD7URquyfBsKdu4KorGxGGoi89C3KvYpi1sfYri8NPIdRZn/BPwfqmwDDjgNFiR1Ke9qnkzrAWPAizlTVlup3yCdPvtt2PcuHHIycnB1KlT8cYbb2hvP2/ePEydOhU5OTkYP3487rzzzp0xTSKiHeLAxVfcX2Ca9ygAQFk2HrF/hlet8zL8paP+aWLOEvx05MX4y9iZ+HLRHNhIAgDavQL8q/4CfH3VXNxQ9Xt81LFPZidKWaHTHYbq2FlY3vJnbIqdt83iKNf5BGNyb0FFzs+RF1rExVF3ho0BDjrj88VRUzXwzr+4OKJBIfAF0sMPP4zLL78cP/7xj7Fo0SIceuihOO6447Bu3bpub79mzRocf/zxOPTQQ7Fo0SJcc801uOyyy/DYY48FPVUioh1mQ+E0dQMO9/7edd0z9v/Dk9YP4PFbzN0aE12JH474Ae4d/2WcWPIgwlYcAOAijLktJ+H/ffoovrv2EbzcdBISKpzh2dJA05LcDctbr8S7TXeiNn4iPOR3teU7H2Js3q8wPu86FIbf51fp0hm5JzD1q7BCUQCAaqhKLY4SrORHg4OllAr0zyYHHXQQ9ttvP9xxxx1d1+2+++74yle+ghtvvHG72//whz/EU089hY8//rjrugsvvBDvv/8+FixYIG6vubkZxcXFOHrS9xByot3fKKQ/aVFSu5O+VK0K6/t6Qrty0rd7Yf0ruRcRth1K318a240I2xa+rKnr7wnnPybtUrEsV2jXj61/6kjtKiw89aLpCwtYYVfbNRTVt4fDybRtOZH0bQCQF4lr2/PD6dsLNG0AUBDq1LYXhfRvzkWh9H/ZLBD6FtpCu5O+vdDugALwqvUtPGtf2nX9nuo1nONdg1K7UTt2vp3+fudbCW3fPFv/WOcIfxnPsdK/boSFBV5Y0xcAQkj/Wuls1bc2UYZ/N56NZxrPQqM7bJvbDQvV4KSSf+DEkn9iSGjnVMvyhKIerkrfnoT+8Uho+gJAQrPtmNA3Jvxqut1L/3i0CQvRNi/N+6mvxcsR2nPTt7lSX317azIHroqgPj4N1Z2z0JKcvE27hQSKw/9FaeR55DjbBrw2J6Wx09/v1oT+DaRNaG+P69tj8fRvrImE/k032akvqa8SmvZRB8Pa7eDPb1uzEnj/34CXem+wEvrjzI6nb9e1AYCtf7mDo38Lga1pl8Y2aXfi+tdZW/+2qu1vJ6Sxhfa4/nVDN77lSn317Zam3XL1r5VWUiiulKY96XbileW/RVNTE4qKev/71kD/vBmPx/Huu+9i5syZ21w/c+ZMzJ8/v9s+CxYs2O72xx57LBYuXIhEYvujs7OzE83NzdtciIh2NgvA0epv+B/vetgq9W641DoSd9h/RTOG6TsPcqXhzThv+B/w4IRD8b2KH2J89KOutrpkOe6tvRxnrHwDP91wO/7Tcgw/VSIAqTLdjYlJWNV2IRY23o1P2i7fZnEUspowPPIYJhVchlG5f91ucURfYNnApFnbLo4+XQQserJrcUQ0WARapKG2thau66K8vHyb68vLy1FdXd1tn+rq6m5vn0wmUVtbi8rKym3abrzxRlx//fV9O3Eiol46SD2BErUJ99u/RswqxHprCm5U/8SluBAjsCrT0+vXInYcs0oew7HFj2Fpx4F4vP5c/Lf1y/DgwEUY81u/jPmtX0aR04Cji57GzOI52C26lF+TGmQ63SHYGDsKG2PHoM3dZbv2XGcdRuQ8jeGR19HqshZVjzgRYMopsIaO67pKLZsLrF2YuTkRZdBOeeWwvvDupZTa7jrp9t1dDwBXX301rrzyyq5/Nzc3Y/To0SbTJSIyMglv4RLvW/g/+09otCpRZ43CzeohXIRLMRlvZ3p6/Z5lAV/KW4gv5S1EdXwknm48Cy81n4K6ZOqPZ83uEMxp+AbmNHwDYyMrMLN4Do4q+jeGswJe1kp4eaiNH4jq2GGojR8A9YWvb9roQGlkPsqir6AwtGyrRTMXSKJIAfClr8EqTD2/lJcEPngOqF6e4YkRZU6grxylpaVwHGe7T4s2b9683adEn6moqOj29qFQCMOGbf81lWg0imhU/91oIqKdrRIrcZl3Lu62/4gqa3d0WEX4o/orvoGfYTqezPT0BoyKSBXOL/sNvjX893i3bQZebDoV/239MuIq9duRtfGJuGvLD3HXlh9i95zFOKTwRRxW+AJGRPh1qoEu7uVjU+fBWNtxJOri+0Fh+69WloQ/xLDIXJRG5sOxWEBgh+WXAl86DVZO6rcaKtEBvPcE0FCV2XkRZVigC6RIJIKpU6fipZdewqmnntp1/UsvvYRTTjml2z7Tp0/H008/vc11L774Ivbff3+Ew/zeORENHMXYgu9638Y/7F9hiXUEXCuCe3ATNqsxOAl/hs1i4D3mWC4OLHgDBxa8gVa3APNajseLTafiw46pXbf5OLYPPo7tg79uuQq7Rpfi8KLncVjh8xgV+TSDM6cdkfDysbFzBjbEjkBN5/7dLoqidi1G5LyMETkvIz+0Ea1CoQVKo3RXYPcTYYVSxSJURyPwwaNAQ2NGp0XUHwT+2fOVV16J2bNnY//998f06dNx1113Yd26dbjwwgsBpL4iV1VVhfvvvx9AqmLdrbfeiiuvvBLnn38+FixYgLvvvhv/+Mc/gp4qEVGfi6IDF+MSPKyuwVzrbADAM9ZF2KAm4pv4EfLQmuEZDjwFTitOKPkXTij5FzbEx+DV5hPxRsuxWN35+Q/0V3buiZVb9sTdW76HCdGPcVDBXByQ/wb2yF2MkMUfnPcXSgFNibGo7jwI1Z0HoS4xBaqbU5OoXYvy6H9RHv0PSsIfw7KEClekN/ZgWOO2KsbQvAn44DEg0Y6dFJFJ1K8FvkA644wzUFdXh5///OfYtGkTpkyZgmeffRZjxowBAGzatGmbTKRx48bh2WefxRVXXIHbbrsNI0aMwJ/+9Cd87WtfC3qqRESBcODiLPwCZepTPIKroCwH71tH40b1L1yES7EbPpIHoW6NinyKb5Tehm+U3oaq+C54veVYvNEyC8tje3XdZlXn7ljVuTseqrsI+XYL9subjwMK3sD++W+gPLwpg7MfnBJeLjZ1TsWG2HRUdU5Hm1vR7e1y7S0YmTMPQ6MLUBxaxjDXvuBEgIknwRo2sesqVfMxsOw5Vqoj2krgOUg7G3OQNO3MQdoOc5C2xxykNO1CDlJPx/4IM/BX/BZtVgkAIKracIF1FQ6ynuu272DIQeqObfhX7Or4SLzecizmtRyHZbG9095ul8hKTM3/L/bKfRd75r6H0vBm5iB1126QgxT38rA6diBq4nujpnNvbInvCQ/dv/jmO1WojL6JkTlzMSz8ESxL9SgHKZ3mZPr8pVT7IMpByhkC7HEakFcKwC+AtXoesO4LhWM69c895iBtjzlIafoP4BwklnchItqJ9sB8/Bin4Q71J6y39kCnlY8/4TacpO7E/+A3sPnVoT5REanC/wz7G/5n2N9QnxyGd9sOwTtth+KdtkPR7A7put26+K5YF98VcxrOBQBUhtdjj9x3sWfuu5iS+y7GRD+BzU8udki7OwQbO/fFxs79sLFzX9QmJm1Xde4zNuIojbyPiuhbqIi+hcIQiwMEomQ8MPkUIJRaEKpEDPjoaaB+TYYnRtQ/cYG0k0nvs/31bdj0/IDnFztXkJ8LK+Gv1Jnk9tPvznvYdp8NxUb8AF/HA+p6vG2dBAB4GhdiLfbAd9XlKLQaez628Fjr/0YHuJpXHeGD5QFjaKgOxxQ/iWOKn4SrbHwS27NrsfRxxz7wtjp535QYjU2J0Xil+SsAgHy7GRNzlmB8dBkm5HyM8dFlGBn5BGHhk73ecjVPXld4rKVjwcQXj2HA//2QOwI18d2xoXMvbIlPwpbEZLS53Vep/UyBU4WROW9hVHQBKqLvImY47/76vA/ytXKHXuNHTgPGHoGu2udtW4Alc4COxgBmlr1MzmMG6jnQQJ13X+ACiYgoAyKI4Zv4IcaoJXjMugoeQliCw/BTPInL1UUYa/F3SUFwLA+Tc5dgcu4SzC69HS1uEZZ27IcPO/bD0vb9sCz2pa4S4gDQ5hVhUfvBWNT++Q/aQ4hjl+hKjI9+jHHRZRgVWYMR4bUoD2+ALXzdciDylI3G5Ag0JMaiPjkG9Ymx2BKfiJrEZHR6xVJvDAuvxPDIEpRF3kd5dDHyndptbhFzWYUuEE4OMPF4YNikz6+rWw6s+DcQk/50QjS4cYFERJQhFoCj8QAm4QP8CbeiGaXYgtG4Do/hbPUrHIO/o5s/3FMfKnSaMa1gLqYVzAUAJFQYy2O7Y2n7VCzt2A8fdeyHBnf4Nn2SiGB15x5Y3bnHNtdb8DA8VIXKyKeoDK/FiMhaVIY/xbBQNYaFq1Hi1ALC75syQSmg3S1BU7ICTe4INCUr0JAcjdrEWNQlxqE+OQZJ1bO8wYjVguGR5SiPLMGI6CJURhcjx25Bi6f/LRD1scIRwKRTgJySz6/79HVg/X/9f6T/PRoRcYFERJRxu1tv45fqZPwRt2MV9kECUdyH67EUM/D/1Pd36Ct3ZCZsJbBH7mLskbsYp+NuAEB9shSrYrtjdedkrO6cjJWx3bEhPh7eF95CFWxsTo7G5uRovI9DthvbRhJDQlswNFSdujg1KA7VIc9uRr7dgnynGSGrEXl2M/KcZuTZLQhZcThIImQloJTb9S2pL/KUhbiXA1eFkUQYSRVFzMtHu1eCdrcY7V4xmtwhW/07tSBqdEegMVmJhNrxBUyBsxnlkY9RHv4YxeGVGB5ZhiKnKu0cKXgKgKqcDow8ArD9RVCiA1jxNNCwKpNTIxpQuEAiIuoHhlnV+Kk6E//AD/ECvgkAWIhjcbnaC1fiMuxpvZXhGQ5eQ0O1GFrwBg4oeANAqopd3Ivg0/hErO2ciE2JXbAxPhYbE2NQFR+LtjRfO/MQQl2yEnXJyl7PxUEcjuXCsRIAFFwVQVKFt1us9RUHnRgaXoeS0DoMDa/FkNCnGBpei2HhNch36rpuJ1W5o+CpUD68CScDxRM+v7JpPbD8SSDekrmJEQ1AXCAREfUTYSuOb+AX2FPNx124Ba0YgjqMwE/Vwzhd/RH/Y/0JjsXfDvQHETuO3XI+xG45H25zfRIuWtxiVMXHY2N8LGoSo1GfLENdssK/lKPJLYXqZWEBF5FUsYZefOLTnajVgiGhjSgI1aDY2YTiUDWKQ5tQ7GzEsPBalIQ2wrY8sdQ2ZZYqGgdv/ClApMC/QgHr5wPr3kD/Lf9E1H9xgURE1M9MtV7Bjep43I7f42NMgwcHD+NKLFEH4wpciuEWw037s0KnCZNzF2Fy7qLt2hLKQ1KF0JAsQ32yHK1uCdq8YrR7hWjzitDsFqDNLUK7V4wOrwBJFYELB64KI6FCcBGCq0LwVAgKFhwrgbAVh2PFYeOz/08gZMURtdqQ5zQh325EntOEsNWMXKcJeXYj8uwmFIdqkGO3ApBzkKh/UpYNNfJwqMoZn1epi7cAy58Gmj7N7OSIBjAukIiI+qGhVg2uUV/Hs9aFeFhdAQ8OPsJBuEK9iAtxDQ7G0/ytxwAVspIYHt6I4eGN27XFVPpPCGNCbedOoax0TPGH+dlE5ZXDG38ykLdVWfXGVbBXPwmvXR+6TUR6XCBlEaN69dn6Cbxwv6R9pm03HFva5dpzIcN8DV0+h2c4tq6/NLbU7hqUdPOU/itNUpaKq+lvmsOiG/s060+Ygvn4vfoTajEKrSjBb9Tt+A9OxPn4CSqsGmF0/ZGmq6mmy0gCAFs4YdcGrCqhmlsGF3+uMDdPs190OUaAvE9NatxJzw9du+4Y7Nm2g3v+SM9d7XaFfWLymhTkayWQ/nVaWTa8kYdBVR78eSEGz4W14TVY1W/CAqCU/vROd5hK90o819CNbfi+OVjPVXQGc1ZRkPpnuhoREXWZbC3Eb63jMB3/7rruTRyPy9XLmOedHGgwMBH1H15uOeITvwM18rDPF0ftNbA/+htsf3FEROa4QCIiGgAKrCZ8z7oYV1oXowip6mEtGIpb1B34lXcXGlRphmdIREFRsJEsPwzxiedD5flVEJUHq+p12EvvhtUufZJMRDuCCyQiogHCsoCDrX/jD9aXt/k0aT5OwEXeXMz1vsJPk4iyjJdThvikbyM54sitPjXaDHvp32BXvQ5L+roqEe0wLpCIiAaYYqsO37cvxvesi1CMWgBAC4bg1+o2/ML7G7aoERmeIRGZUnYYiRHHID75Aqg8/zmtPDjVb/ifGlVndoJEWYwLJCKiAWqG9QzusI/EYdaTXde9hWNxgTcPj3gXI8HSzUQDUqJwMjp3/y7c8hmAlTpVszo2I7L8/xDe9CosTbVDIjLHBRIR0QBWbNXjh/bFuMb+DkqwBQDQiTzcq36MS70XscibkeEZElFPeeFitI0+G+27nANEiv0rkwhtfA2R5XfB7mAGGtHOwDLffa0ff/+/v5aCHLRlPwO8X7oy3j1p1wmyLK4XYEleqYyxVEpYNzfTEuKepl0sn+wXhp5mPY8p9nw8oK7C82o2PDhYj4m40nsMR6o5+F/7egyzNm/X39EcaLpy1j1pT2j+yh22hEyeDP6uwuR+me4zXRnwhEEZ71R7+mNJdwxKfYGAnz/iczczrzmmsQVbU7ARHzYdsbKjADvSdb3VvArh9c/C6mzwb5ca0+Q13B+od239XZAlxjOkv84LwMA+VgT8BImIKEsUWM240P4JfmufgIl4r+v619Sp+Lb7Bh73vgOXYaFE/UoybyxaJ1yEWMWsrsWRlWhBaM2jCK98sGtxREQ7DxdIRERZZoL1IW6xT8El1g9QiHoAQDsKcaf3c1zkvoh3vCMyO0EighsZirbRZ6Ft3Lfh5VSkrlQeInVvonDln+A0fMRcI6IM4QKJiCgL2ZbCTPsfuMc5FMdZD3Rdvxa748feQ7jGfRBr1KQMzpBocPLsXDQPPwGtu16GZNEeXdfbHRuRv/ou5FY/A8uLZXCGRMQFEhFRFiuyGnCFcxX+6JyASVt97W6hOhIXuS/jt+5NaFDDMjhDosFBwUZ78TRsGfd9tA85FPB/h2clWpBb9TgKVt+JUKwqw7MkIoALJCKiQWF3axH+6JyEq+2LUYYNAAAPDp70zsVZyQV40P0uOlU0w7Mkyj4KQGfeRNSN+X9oLv8KlJOfavASiG5+DYUr/4BI4yJY2fyLd6IBhgskIqJBwrYUjrSfwN3OYfim/SvkohVA6vdJf/F+gtnJ1/GCdxqSLORA1Cc6c8ejftQFaBj1LSSj5V3X5zQvQuHKPyJny6uwvHgGZ0hE3eECiYhokIlaMZxl34p7nRk4yXoANlJlq6uxC25w/4xvJOdxoURkIBYdi/pR30HD6P9FIm9c1/XhjnUYuu42lFQ/DDvRlMEZEpFO1uYgWUrBUt1/XK3SXN9Fit8I8Jwh3ZxTbUK2TV9PZpvB9aNLcwsyc0GbEWCaNWSQqSDmVEjHoa6/OO/eHyueZ5ahFGRuiJSXktCc0Et5J2KGjGbbUkZMQulfauPQ5AUJ9zki5bho2opRiyudH+AU9Tfc6V2LhepwAMAGTMAN7p9xv3s5znP+gC9bTyBkdTNHS/9iGdbsF12WEAA4Vubqd7nCc1OXZZQQ3kASwtiuptmT3rqE509CcyzFhcWwdAyLeV3a549ZVpH2eW+QoSS1d9fWGR2NhiGzEMubvM31TudmFNS9jGjLElhI5RmJr7XaRoP3XKm/4ftLpt6TxW1LAjwfEN/vAyTnP2VobtK5tnje2X17X92frF0gERFRz0ywPsavnTOxWE3H/d6VWKQOAQCsxwT8wv0z7oWwUCIa5Dojo9A4ZCY68vfc5nonXov8uleQ0/w+f2NENIBwgURERACAfawF2Mc5Pe1C6R5cgbPsO3Gc/QiiVmeGZ0uUWQpALHcimkqOQix3t23aQok65NW+hpzmRbDEP5UTUX/DBRIREW3js4XSR2oa/uZdiXfVoQCADRiPX3u34G/e93CG/Vec5vwdBVZrhmdLtHMpWGjJ3QvVw49FPGeXbdqcZANKGl5GQcs7iCX4Gz6igYoLJCIi6tY+9lv4k30GFnsH4R7vSiz0F0p1KMft3k9wv3cpTrPvw5nO/2GoVZfh2RIFS8FGY95U1BYdg85w5TZtocQWFDfORUHLO7C6flPIBRLRQMUFEhERae1jv4U/2mfgY+9LeND7LuaqE6BgoxXFuNe7DP/wzsfJ9j9xtvMXjLTWZ3q6RH3KtXLRkD8NdYWHIxHaNlQ50lmF4sZXkNf2AX9jRJRFuEAiIqIe2d3+AL+0L8CnagIeci/C8+o0JBFBJ3LxiPdNPOqdi4OtV3Cacx+mWXMhFB8j6tfaQiNRVXA0GvMOgLK3DVHO61yFgvpXkNuxnIc5URbiAomIiHbIGGsVrg59Hxfgd3jI/V884Z2DDuRDwcZ/1DH4T/IYjMCnON15AKfYD2OI1ZDpKRP1iAcHDdF9UJ1/JFoiE7drL+j4CMObX0R+fBVaE5EMzJCIdgYukHpBV2Nd/IBdrM9u8LcoKSRDW8Pf8G9gQX6zwGBsOZvAoD3InCMItfylnCODjCYp58gVsjt0eSdJIZMk6UlZLL3PNElIY9vSttO369oAOWMmbOnGFjKUhCwiWzjIbV2FLeFAGmptxCXOdZht/xFPeLPxpDcbNRgJANiIMfij+2Pc4X4PR9v/xmn2fZhivYfP4o1sKfvG9DXJgCvsM20OkrDP4kJ7QrNf4kLWUFz4zYvuWEoIfeWcpOCeP9JzV/u87+FrTqczFHW507Al/1AknJJtbmN7MRS1vY0hLf9BNFmT6gdb+1oHyK+V0mut/nVa29UwqyiTGUv65kBzjkwEmucoBqCZbVzHMFMoYxlLfYALJCIiMlJsNeBc5084x74NC9SXMcf7Bt5SRwIA4sjBc95peM47DeOtZTjefhSz7DmosGoyPGsa7FxEUJt7EOrypqMlOmm79pzEJhS3/AdFbe/AUSxrTzSYcIFERER9ImS5ONR6AYfaL2CDGounvG/gae8MNGMIAGC1moxb3Z/gNvcaHGi9gZPsf+FI+3lmKtFOowA0h3bFppzDsCW6P1w79ws38FASex9lbfNQGF+OtiS/Rkc0GHGBREREfW6UtRb/L/QLXKB+jZe9k/CkdzbeVwcCSJVLfksdjrfcw1HoNmKW/QROth/GZGtJ11fwiPpSzB6GzdGDUJ1zMNpDI7ZrjyZrMKz9TZS2v4WIx9/MEQ12XCAREVFgcqwYTnQewYnOI9igxuBZ92t41jsNGzEGANCCEjzinYdHvPOwC1Zhpv00jrGfwkT7kwzPnAa6mFWMDTmHYHPOQWgO77Zdu+O1Y0jHuyhtfxP5idWsRkdEXbhAIiKinWKU9Sn+N/Q7fEf9HovVdDzlnYFXvBPQidTXnNZhAv7Puxz/512OCdZyzLSfxkz7aYy1Vmd45jRQJKw8bAofiKrIdGwJTQGs7QspFMeXoTL2OoZ3vouOhL7QAhENTlwgERHRTmVbCvtbC7C/vQBXqZ/iRe9kPO99BYvUQVB+pbZVahLucCfhDvf7mGgtxTH2MzjUegUTrY/4NTzaRrtdiprwvqgJ74fa0J7wrPB2t8lLVqGs8y2Uxd5Cnrd5q5acnTdRIhowuEDqY1JJQ2XyIX6gJSr1g5uWAdftF3Fso1Lc+q5SyVB96U19X9Ntax8Sqa9UXlbTLpWm9QzKM0ulm83LgJuUEta/HCYsTYlkscSxMLZy07bFkb4NAGxh3kJlaADJ9E1CCXHpdUNXLtvxj6MwmnCC/XecYP8dW1Q55non4hV1MpaoA7puu0LtiRXunrgNV6EUmzDDehUHO6/iQOsN5Ftt+jl2Ny9h3sK91t4vV3hu6sp4A0BM8xyICcdRTDgWdKW65WNUajcoMS49974wtoKNemdXbAxNxabwVDQ5Y7rtl+tuxrDYOxgeexv5yaqu65NblTSXXnNMXs+k10qxDLimXXqNN3l/CjIew+g913Db5ucDvT8Jk+9XkKW6gxt6IJfxlnCBRERE/cJwqwanO3fjdNyNLWoEXvVOxMvqZHyk9uu6TS0q8ZQ6B08lz0EIcexnvYkZ9qs4yJqH8dYKfrqUpdqtUmwO7YnNoSmoDu2LTru429vluHUoT7yDEZ0LUOyuQmuCnxAR0Y7jAomIiPqdcmsjznLuwlm4C5vUSMz3voz56mgsVAcj7v9mKYkI3laH4W33MADAENRiX+tNTLXnYz9rARdMA1i7VYJq50vY5OyFKntvtDkV3d9QeSh2V6Ms/h7KEotR6K5jsQUiMsYFEhER9WuVVhW+5tyHr+E+xFQO3lMz8KY6Gv/xjsYm7NJ1uwaU4lV1Il51TwQADMUWHGC/gQOs/2Af+22MxhoumPqpdmsIauw9UOPsjk3O3mhM87U5AAipDpQn38eIxLuoSC5CMhnbiTMlosGACyQiIhowcqwYZliv4lDrNXxf/QRrsSsWeEfiPW863lPT0IrPv3pVj+F4wfsqXsBXATf1CdNe1sKuy2TrfYbUZoAC0GCNxkZ7T2yyp2BDdC+02JVpb2+rBIa6n6AsuQRlyaUY6n4CZ6vfzrUiuhNmTUSDCRdIREQ0IFkWMA4rMc5ZibOdv8JVNlaq3fGumoGF3sFYpKahDYVdt29AKV5Xs/C6mgUACCGOydYH2NN6DxOtDzHRWoqx+AS2pSlcQTtEAWhEJdbaU7DZ3hVb7F1RY09EzCpJ28dSLoZ5KzHCfR+V7hLkxVcjhPhOmzMRERdIRESUFRzLwyRrKSZhKc52/oqkCmGp2gfvqen4wNsfS9RUNGNI1+2TiOBDtT8+VPt3XRdGJ8ZhBXazlmI360PsZn2IcdYnKLYaMnGXBpRO5KLO2gV11ljUWLui2pqIGms3xKxCbT9bJTDcW4Ey92OUux+hzP0YUXxenZCfEBHRzsYFEhERZaWQlcTe1kLsjYWAkyrL/CkmYLF3gL9g2h/rsOs2fRKIYgX2wgq11zblcYtRj9HWaozGKoy2VmGUtTr1X6xF1Bo8v4Fx4aAJZai3RmMLxmCLNRa12AWbnbFoscp6NEaOakaF9xFGeB9ihPchchPrEUIi4JkTEfVc9i6QlEpfV17M/BGyjExq4ZvFigidhW0HmHtg1L8fZxVp8xyEx9L4sTbJwJCyjHRjC9kerqfPDdG1x119VkrE1mf+SJklcU2eSsLWf21KynHRZdCEve2DKbdmCweao0nesW39geQIB5qjpFQf3duAfp95QmKQ7tEKG4ZzOL3sX4kVKLNWYKbzIACgSQ3FJ2oKVmJPfKKmYJWagvWYAA/bHg9NGIomNRQfYv/tXhdKsAXDsRHDrY0YjqrU//v/HoZNKEY9cqwOAEBcCKbSHWcJ4fhPQDqG0x+nMS+MJMJowxC0YgharFI0ogINViUaUY46ewSarAq0oBSwxHCtLgWqFmXeJyjx1qDUW4Vh3ioUqM3bVJprV1Ht3KXnpu55L2erCa8pmtcsk9dCQH6t1b5OG2QoAYCla5fec03e+4LMOUKw5zlBZkcFOm+JwXmOPLYuA9MkDFLT3kfZTNm7QCIiIhIUW/XY33od++P1rutiKhdrMAkr1RSsUntgPSZgvZqALRjZ7RiNGI5GDMcnau9tG7Z6n46iA0WoRxHqUv+16lGEeuSjBTloQw7akIt2OIj5/25HFO1wkIANDw6ScJWCAxc2XDhwASi4CMFFGC5CaEeu35K6Lo4cxJDfdWlGMWLWZ/8uQBtK0IohaMVQNDvD0GkV9Ho/5qgmDFXrMNRbjyFqPYar1SjzViIfqa8mtnjMIyKigYMLJCIioq3kWB3YHYuxu7V4m+s7VC6qMA5r1a7YgPGoUuNRpcZhC0agHuXbfeq0tU7kYgtGfr7IykQAfc8/+OlWvqpHkapBMapRoqpRqtZimFqPUvUp4HX0zRyJiPoBLpCIiIh6INfqwK74CGOsj7drc5WDOlSgRo3AFjXCXwyNQL0ajiYMQzOGohlD0YSh8PrZW2+eakIeGlGAeuSrBhSgAQWoR4mqRom/GAp7DQhrKsm1I7ITZ0xEFKz+9SpNREQ0ADmWizJUoRRVgObnHTHloB1FaPIXTO0oTH3lTeUihny0oBAxlYcY8tGJXLgIwYMDDw4SW/2/BwcKNhwk4CAJB0lYXV+/S8JBAhF0dn19LwetsLxORNGOHLQhijYUoBH5aEAISbR7+kpxbawkR0SDCBdIREREO4ltKRSgCQVowkis+bzBX1TFVCjtAksq0qArwgBwkUNE1FOG30gmIiIiIiLKHlwgERERERER+fgVu75mWn/doGa8JWQqmExNrIXfX7OKTPMcghxbzLHQbEDKQZKOBU1/MdvDFXJF7PTtriP0Ncg5AoCIlz5HqVPoG7b0GUy69pgl5CAJTz5dVpEt5BjJOUd6rtLcb+FPaB70+0yX/5QQs6H07SZ/3dM9tQDA1f2ISGj3hOdeXMoq0mV5GeQcSe0mfXvSntDcL+m5KbUnvPT7RXrNkF5zXE17UngtlF4rxZwkbVaRWRaeLsJMem/K6PtmgJmLQZ7HGOUJGWdFGuYNBdW3n+MnSERERERERD4ukIiIiIiIiHxcIBEREREREfm4QCIiIiIiIvJxgUREREREROTjAomIiIiIiMjHBRIREREREZFvcOYgSfXobYOa8WJeUO+zjMS4E5OcpCDzAaDPAJDzgnq/bdP8Ju3jKY4t5VAIj5cui0IKchHmpsvX0GZvAHCldk1uSMLV57jEbX17SHhAdf3DUtaKQQ6SI8xLyvRxNA+YLR5oeq6l/ztYjpVI2+YJOS0JK6ltD2vmrrvPqXbpdVjfbELOQdIc40KuTkLpj8O4Sn8MG2cVeZocJE0bAHQat/c+B0nKMorrcpCk1xyhXfeapXutA+TXSum1Vttu+r5pMLb83tbLNsA4T8jkfMCk3SifSWiXxzY7H9DnO5mNre1vOnbA+AkSERERERGRjwskIiIiIiIiHxdIREREREREPi6QiIiIiIiIfFwgERERERER+bhAIiIiIiIi8mVvmW9Ppa9dmMlloUFpWsukjDcApSkNLZfO1I9tSWWnNf1N75dJSdEgy3qalhTV7hbD8rG6/p4rlK519O1JTf+QLZRA1pTrBYC4J5T51pQDDrn6viGhzLetecB1bal2/bZtXQ1/4TjxhBc0Tyjz7WkekwSEMt6aktQAENHsU6l8uVQ6PUhS+WbdPteV6QaABIR2TRlwqRS3UZlvsYS4/nRBmlu7F0nbJpX57nR7XwZcVwIckF9zXE2pe91rndQXkF9rTeIYtGW8AX1Z6QxGb4hPe4N28T1bKjutvV/SeYywbV1/07Gl+6UTYJyCsXT7RTof7SF+gkREREREROTjAomIiIiIiMjHBRIREREREZGPCyQiIiIiIiIfF0hEREREREQ+LpCIiIiIiIh8XCARERERERH5sjcHSam0QTJSTXgl1YzX1dm3pTr6BtuW8oCk0u+6Gv5i397nHEnjm+YeaLOKhKGNcpCkvvpYHVj6+A1tjoWSxnaFe+7o8jX0XaXsjqQmVydu6++0Y5tl48Ss9C9ptvAEkbOM0rc74hOo96QcI1f4O5dr0D8sHKS6nCNAn6PkSE9sYZdKj6eOJ74y6On2mS7HCOhBTlKAOUid2hwk/bzb3ai2vUOTc5TadvrxO1x935gr3O+kJgfJFfa30K7rL+UgyTlH2mZtXp34Gi+0695fjN/bTN43pXZ9s75/gPlO8vmXQZaRwbldz9o1GZnivHt/vizvk16eT5vkPm2FnyARERERERH5uEAiIiIiIiLycYFERERERETk4wKJiIiIiIjIxwUSERERERGRL9AFUkNDA2bPno3i4mIUFxdj9uzZaGxs1PY577zzYFnWNpdp06YFOU0iIiIiIiIAAZf5Pvvss7FhwwY8//zzAID//d//xezZs/H0009r+82aNQv33HNP178jEX0JUCIiIiIior4Q2ALp448/xvPPP48333wTBx10EADgr3/9K6ZPn47ly5dj0qRJaftGo1FUVFQENbUeZPr0vja7mKEkja2pGa+EjCW5Xr0m+0aYtnF2gbYWvtDXoD3QeRuOrcu4AADL1WQTCJ/9KiEDQ9fuaXKMerJt10l/A1dznwDznKS4l77dFrYt5yBJD2gwpMfDFZJBPEto1/SXcpASQiCKg/T5NdL+FHOSAiRlS3lKc4wLfRNiDlL69kBzkISxpZyjdiGrqEPTLuYcuUK2lJd+nyU0bYCck+RqsoxczywHScxJ0rxOSzlIRllG0nuTQXZhoO/JEM4HDPOCgsx3Msmp7HVe0Gf9DbKKjLKMDMcOWmBfsVuwYAGKi4u7FkcAMG3aNBQXF2P+/PnavnPnzkVZWRkmTpyI888/H5s3bw5qmkRERERERF0C+wSpuroaZWVl211fVlaG6urqtP2OO+44nH766RgzZgzWrFmDn/70pzjqqKPw7rvvIhrdPsm7s7MTnZ2dXf9ubm7umztARERERESDzg5/gnTddddtV0Thi5eFCxcCAKxuvtqhlOr2+s+cccYZOOGEEzBlyhScdNJJeO6557BixQo888wz3d7+xhtv7CoCUVxcjNGjR+/oXSIiIiIiIgLQi0+QLrnkEpx55pna24wdOxYffPABampqtmvbsmULysvLe7y9yspKjBkzBp988km37VdffTWuvPLKrn83NzdzkURERERERL2ywwuk0tJSlJaWirebPn06mpqa8Pbbb+PAAw8EALz11ltoamrCjBkzery9uro6rF+/HpWVld22R6PRbr96R0REREREtKMCK9Kw++67Y9asWTj//PPx5ptv4s0338T555+PE088cZsKdpMnT8acOXMAAK2trfj+97+PBQsWYO3atZg7dy5OOukklJaW4tRTTw1qqkRERERERAACzkF68MEHcdlll2HmzJkAgJNPPhm33nrrNrdZvnw5mpqaAACO42DJkiW4//770djYiMrKShx55JF4+OGHUVhYuINbV70vESiVY9SV25a2KZZ61JR21pTpBgAV4NhimUmTbYslRaUSlZr+BuVIpXZbX+EYQvVYsb+ugqzlSGW89WNrS8TaQllood1Npp94UiqlLZS0jlv6lyxdqW6xjLdQBjxIrub55wnPTVdTchoAEkLp9IRKv0/DVlLbNyyV+da8MNhCTV1d36BJ+1RXGl18PMQy3+kfj5imDQASnr69U9PeLpTx1vUF9GW8AaA9mf6bHiZlvAGgU9M/ntSPnRRKbevada91AOAJpbghlerWtYtlvqWx07dJ701SOWxt/wDfkwGpFLdBuWtAOI/RdzWJKzE9r5TLm2tuYLBPjMeWpB27b97LA10gDR06FA888ID2NlvnBuXm5uKFF14IckpERERERERpBfYVOyIiIiIiooGGCyQiIiIiIiIfF0hEREREREQ+LpCIiIiIiIh8XCARERERERH5uEAiIiIiIiLyBVrmO6OUJgdJqIUvLhsN6rpbugwlYWip3rwltWtyEZSQAWMJ+0TMANBsW+6rb9ftc6mvLbTrsqWk3CkhIgaaKJUUTdaRZfh4KU2GhhJyjiBkFXmaY9wVjv+Epc87saSpiYEPmeFJuTqax1rKQZJydaJS7o4mWypsG+YgafIobOHJ6RiHZPSeK7wJ6B5PV3hiizlImrwhqa+UVaRrl3OO9DlJMSEHSZd1JOUgdST1Y+uyjuJCIF0iqW93NTlInpChpMT23ucgie+b0vuP7j1ZzNGTxtb0NXxPDvJ8wKRdzlgS3ps07+lyxpJBFhGgjQ0SxzbNSdKO3cv7ZbLNrfATJCIiIiIiIh8XSERERERERD4ukIiIiIiIiHxcIBEREREREfm4QCIiIiIiIvJxgUREREREROTjAomIiIiIiMiXvTlIOoZ5Qrpmua9UK19TVN7T5zUoqQ6/ZtuWkLUilpUX2nW5CVI2lC5DKdWevs0W8hqEmAph3vq+QlwQPKm/ZttSX0vKMtI1izlI+mZPs2OE2A8xG0rKQcoUKavIpD3pCDkuUq6O0K7LMgoL2Thh4Qlma14YHCHcQ8pJCpKUW+Vq2j0pB0l4Hdc9XqY5SHFdDpKQRWSSc5Tadvq5m+QcAUBM0y7lHCWFnCRX099LCi+GBjlHAGAldVlF0tjaZu37i5hVZJCTZJKh1KNtG+UgCecium2bniMZZRFJ51DCtnXnnYbny7r+xvlNAeMnSERERERERD4ukIiIiIiIiHxcIBEREREREfm4QCIiIiIiIvJxgUREREREROTjAomIiIiIiMiXvWW+PYW0dRV19RQBubSgruy0ULJaHrv3faVS3XA15RalUttSaU2p7LS29Gbvy3gDgK25X65QslocW9cu7BO5FHfv26Uy3tLjqfvTiNKUlk0Nrm/W1eL2pDrd0k7ppzzHsMy3ZqcmhZLTCVtfpjhu61/mI3YybZuuBDgA2EJ5WV1/W3odFjhSPWAN1/Bvg7rHUyrFLR0Luv66Mt2AXEJcV2pbGltXSlsaG9CXETcp4w3oS3lLZb5doVS3p3s9lHILpNdSoV37vimW2u59GXB5bH27rhS39j0V8nuyXAZcc55juG1dGXC5RLhUilszttRXLDEe3HlnZsdO0y48Fj01MM9GiIiIiIiIAsAFEhERERERkY8LJCIiIiIiIh8XSERERERERD4ukIiIiIiIiHxcIBEREREREfm4QCIiIiIiIvJlbw6S8lKXbgnrQqmGuq67SU14CPk1wryUWFNek4sgdDXPD9C0SZkL+hgLIWNJ31eX1wAAru6xlu6zaXaULgdJihMSb9D7saW4LaWduL5v75NtgqfLr5GybZK2/sHWZR1FhJyjiKM/0HQ5RwDQaaV/GwgJT5Cw8ASzNe1SDpIjvSgFyBUOVP2xIORWCe1JTZ6QlIklZRnFXV0OkpChpOkL9CCDSZNlJI4tZBnp2sWco4S+XWneBJQwtiXlHElZRZr+4tj6p32gOUjaF3LD92Sjcw3T92yTsaU3N93LnWHOkZjRpOsvztvgddo0ryjdOX7ac/8dw0+QiIiIiIiIfFwgERERERER+bhAIiIiIiIi8nGBRERERERE5OMCiYiIiIiIyMcFEhERERERkY8LJCIiIiIiIl8W5yCp9PXZxbwgqaZ8+hrrSsg70dabh5BlJM3LlcKM0rdLfYX4DaPMH+NsAjt9HoQt3C9PCP3RPpxSnFaQOUhCXylLQne/pRwkkTZuy+xvMkHmJJm8LLhCDpLr6O+3q3mCmWQoAUBcCBIL2en3akh4cko5SbqsI1sI95BykoIk5Vp5moNczMQS8oJ0j2fSMzwWNHlDUo5RQsgqkrKMkpo8ISnnKCmMrcs6Msk5AgCl6S9nEQXXbpwXFGAOkuYlRZ63NLbwnq7PXDTMC9K0i+dfBudv4rwMt61rl85ZTc6XTc/Fe32O30P8BImIiIiIiMjHBRIREREREZGPCyQiIiIiIiIfF0hEREREREQ+LpCIiIiIiIh8XCARERERERH5uEAiIiIiIiLyZW8Oko5QU16XFyT2l4JabIO67+LYQruu1r1Y/18Ix5GaddkExjlImvslhPro+qa2rckLknKMpH1ikJOkiX4CAIgPl6ZdHts0KCm9QHOShHwaIZYHStPf02U9AHCF/Bpde8IW8mmEwC1HeIJFnPT9pSwiKSdJm4MkjN2vc5B0x4KUgyRkFen6S1lDujwtQJ9lJB2j4raFPCFdDpLU1xVykjxNXpBJzhGgzyKyEsL7i+b9AwDspLbZKKsoyLEDzVgSM3+kbeuyiqRt977dpG+qvfcZmNJ7l3juaJC/KY5tcr+kc/WA8RMkIiIiIiIiHxdIREREREREPi6QiIiIiIiIfFwgERERERER+bhAIiIiIiIi8nGBRERERERE5MveMt+eQtrah1K9RbEcsKaMpFC2UAnlgLVlQaV5S+UWNeVOlVjuWiqNLjTryn5K5bLF8piaMqymJcR1D4dpmW+hXVdu26SMN6D/y4gnPJiWWH45g2XANVNzpeemVHFUs9Ol0s6O8IDpxg45+oNYVz65J/0TXvoSylKpbamEOMt8b08qxa3rL5Xilo4F3balvuLYUin7ZPp2Txjb0/RNDa4p8y301ZXxBvSlvKUy3pZUalvYtq5Utzi2QRlwuZR279uNxzYqxS3FmfT+PMikLwD9eaXQ15LOK8XzTl28jNBXLEFuUr5cOudN07+PyoPzEyQiIiIiIiIfF0hEREREREQ+LpCIiIiIiIh8XCARERERERH5uEAiIiIiIiLycYFERERERETk4wKJiIiIiIjIl705SEqlr7EuBp5ImT8Gdd2lABtdHpE4tr5ZtxyWavhr73MPtm2SVWQLuQja2B1p3mJYUfr+ShdUBH2OUWpsfbPuUDHJOZLGlv9qImTE6MKITDOSpHgDXcaM8PyR8muUZqcpIQPGE7KIXE3WRNLV93WEDDNHyLFw7PTttrDDpW3rMrNMc47kPK70lJR1J9AdK9LYrpSJpXmOiFlDYlZR78cWs4rEds0+E/rqco4AAJo8ITHnSGrXbFvKIrI1GUqAPosotW2DviZjSxlKBllGtpDpI29b6K+53+K8M5mxpGuXXuqkcz+TrKJAxzboq2uX+vUQP0EiIiIiIiLycYFERERERETk4wKJiIiIiIjIxwUSERERERGRjwskIiIiIiIiHxdIREREREREPi6QiIiIiIiIfFmcg4T0tdDFzB+h8Lsu50KqdS9kdyhN/XZLqP8vzlvXLOVQSJkjUr6AJi9FymuQonO02QRCfoYl3W1dnoOQAeMJYUVilpFBVIsYiaU7hKW+4tZ1GTFmWUQS7fBSpIJ0xzU5Ma7wvJfG1mXISBlKSSkHSchR0r0mmeQcAfJzRNvXMCfJhMlx6Ak5RyY5SXJf/bNTl+Ul5RiZHMMAtFlGSnqdNslBksYWcpB0uTomfQH9+4u87d73BfSZQNK8xHlrzlXEsaUsIrG/ZtvS+Vmy91lF0vmZuG3dPhOy7MR26dxRd95pmhuq6y++qPQ2B0nfraf4CRIREREREZGPCyQiIiIiIiIfF0hEREREREQ+LpCIiIiIiIh8XCARERERERH5uEAiIiIiIiLyZXGZb6UpAWhQlhDQlx6UalRKtZt15RjFUtsGJXkNx5aq4mrLY0oVdYWyudrymNK8pDLfmgGkMqpyrUn95HRHkviXDeF+63apNLZJGXBPmJhUFdrkqasrcQwACPX+ea+EcqRS6WfdHffEUvX6bbu2/hHVleKWSohLZb51Mxf7ZrDMt1ROW9cuzVocW1eKWyohbtAuPj+ksQ1KdZuW4tZGPUh9pXZd1EOAZbwBfSlvXZnunrRrxxZLiAvl/XXlycUy3r0vhy21i9uWSnHr2g3KeEtji2W6Dcp4i/3F82GDUt2m5+K9PcfvIX6CRERERERE5OMCiYiIiIiIyMcFEhERERERkY8LJCIiIiIiIh8XSERERERERD4ukIiIiIiIiHxcIBEREREREfmyNwfJ85A2sUUKxxHq2WuL6UuBQK6+Zrwud0cJ9eZ1fQFA6WrDS3X0pcwSKRxHm1Uk7DMhc0GbVSRkQUh5Qbr7LWX6iBlMUjSOpl2KLBHH1rRJh7+UVaTrL/1FRo4gE+6Yrr8jbVxo1uW4OEJnoV3p2oUdrqSdKjx3Pc34UsaSmGGm2bZpzpG4bQ3TmAxtlpGYoSSMbZJVJD0/dG9dYt6cWTt0zx8xG6f3WUVSzpGYF6QdW9/XJOcI0M9NylgSM5gCHFubHSWca4gZTNK2tZlYZucx+owlgzdGwCiLyDLMKtL2F85Ze/CClr5N2ie9vV9SNlMP8RMkIiIiIiIiX6ALpBtuuAEzZsxAXl4eSkpKetRHKYXrrrsOI0aMQG5uLo444ggsXbo0yGkSEREREREBCHiBFI/Hcfrpp+Oiiy7qcZ9bbrkFv/vd73DrrbfinXfeQUVFBY455hi0tLQEOFMiIiIiIqKAF0jXX389rrjiCuy11149ur1SCn/4wx/w4x//GF/96lcxZcoU3HfffWhvb8dDDz0U5FSJiIiIiIj612+Q1qxZg+rqasycObPrumg0isMPPxzz58/vtk9nZyeam5u3uRAREREREfVGv1ogVVdXAwDKy8u3ub68vLyr7YtuvPFGFBcXd11Gjx4d+DyJiIiIiCg77fAC6brrroNlWdrLwoULjSb1xbLNSqm0pZyvvvpqNDU1dV3Wr19vtG0iIiIiIhq8djgH6ZJLLsGZZ56pvc3YsWN7NZmKigoAqU+SKisru67fvHnzdp8qfSYajSIajW7foFT6Gupi3XaDdjFDSaqFryviLwS5SEX8dTkU0rykuvKusNY2yUORMn90uQlSXylTQZexJAXniEEtQj6NZvKmH/1qD3HpUBDG1s1NzjkSxhYjGXQZMkKekJADozRPP13UA6DPUAKEHCXTHCQpuErTLsXqiK9nBllFpjlJJrQ5R2Jnqb33WV5iDpKUZaR7e5HGlo5hKUNGM7557o5mbCmLSJi3LpdHnJdhTpJJVpFJBpMt5AVJWUS6rCPx8RBykqS8IV3WkdhX2rbufonzNskiMjw/E3MqdQFphm/auv5BnYubBt35dniBVFpaitLS0j7Z+BeNGzcOFRUVeOmll7DvvvsCSFXCmzdvHm6++eZAtklERERERPSZQH+DtG7dOixevBjr1q2D67pYvHgxFi9ejNbW1q7bTJ48GXPmzAGQ+mv95Zdfjl/96leYM2cOPvzwQ5x33nnIy8vD2WefHeRUiYiIiIiIdvwTpB3xs5/9DPfdd1/Xvz/7VOi1117DEUccAQBYvnw5mpqaum5z1VVXoaOjAxdffDEaGhpw0EEH4cUXX0RhYWGQUyUiIiIiIoKlVB99Wa+faG5uRnFxMb48/NsI2ZHub+QIv+WxhQ/WHE27LYyt6ytsW4WksaXfUGj6h/TzUuLYQn/N+J607ZB+255mbirc+74A4Gm2rYQ/L+j6prbd+/7ytvXtut/TyPMSxta067bbo7GFp49+28JveYS5aX+DZPo7oQz+BsnStfM3SL3oLLX3z98gSX35G6TutiuMPVh/g6T7HZC4T6RtC69nifTtYl9p28n0B4ulaQMAS/c7Hwi/YRLHFh4Q8X5r+ou/P5d+/6QZW+wrbbv7sZNeHC9vuRtNTU0oKirSj6HRr8p8ExERERERZRIXSERERERERL5Af4PUb0kf20nlmXVlDaXP68WvV+hKVOrHVsJXA3X9pTLFUolx8eswuvKY0j4T1vHah0v6OF/Ysu4rQroy3IC8T2yxBnn6/tK2pfulO4SDLCEulvGWqnpKX4Mz+HqS+LKgOYblr6Dqx9Y+/6TXI7GMt0F/6eXK5Ct4Yl+hPUDiF8+1ZfKF1wWDscVS3AZfcxNTC6Sv75l8TU4YW/pKl25s86/vpW8Tv8YmlsMW+uu+Bmf69T7N65m8v6WvbPVuuz1pl74GpyvlLfY1+BqcVEJcLLWteQOSzv2kFyyj/mKpbelrcgZjS/MOGD9BIiIiIiIi8nGBRERERERE5OMCiYiIiIiIyMcFEhERERERkY8LJCIiIiIiIh8XSERERERERD4ukIiIiIiIiHzZm4OkVA/CLDR9e9su1nWXwiZ6HyIjZRMozdhSXynfSUlrbd22xQwmKTchfZtpFX1dBI381wUhd0cIHtHmJAnHmZiTpDvMtD3l2B1txpJhpIJJu9RXyizRZR2ZZCgBgNJkFSnpqSXkHClpp2sOcinnSMw/0z2BMphzJBGnps1Bkvoa5CQZZhXpntzS67D4Om2QZSRmERk8d4PMQTLOOZL6a/KE5L69f9+UXq/shLBtXV6Qac6RQY6SlFUkZxlp2qX7JbxJaO+XlHMknb9J98skvDDI8+Xetvf23P8L+AkSERERERGRjwskIiIiIiIiHxdIREREREREPi6QiIiIiIiIfFwgERERERER+bhAIiIiIiIi8nGBRERERERE5MveHCRPIW1ohLQsFENNNHkPUs14COEFJoQ8FH2dfuE+u0J2h9Rf1+z2PkMp1T99k/hQ6x5LSBlLUo6RpPc5SdqMJABSYIo+JkDI1RFzXnrfN5M5SJ6jb9fdL0fKUJKyijTblnKQpOeHuG3N+MLTQ76B9NzVkDKYgmQwbXniBs8f46wizdxMsoZ6tu3ej22SJ2Scg6TLjgo8B0mXJ2S6bc37i0HOkTi24XFksm0xB8kgy0jKOZJykrTnnVJfMX9Tmpum3RMeMKOMJekNvZf5TuJ5eM/wEyQiIiIiIiIfF0hEREREREQ+LpCIiIiIiIh8XCARERERERH5uEAiIiIiIiLycYFERERERETk4wKJiIiIiIjIl7U5SEp5UGmCTywIgSdiWItBXXdpTaoLAZDyNXS17KFPt1G2fl5SjX8l3C9LFywihY4kDfephnZe4lZ7n2OU6i9JP74Sj1GTLCP92J4wtm2SgyQ8NaV4A93TR3pq2tJhpsvEEuZtCQ+2Nr9JygOSco6kWB7d3MQcJCGDSQxS0gydwRwkMatIQ3xJMchJErOKpG3rMn0MnlvS2ICQf2OYwWQytvS8DzJjScr0sZPBjW1pxjbJGkr1123XMIvIJAdJOJcwykkyyFACoH1zlDOWDPOEdG9A0puuSZaRGKooDd39ttNdv6P4CRIREREREZGPCyQiIiIiIiIfF0hEREREREQ+LpCIiIiIiIh8XCARERERERH5uEAiIiIiIiLyZW2ZbyiVvjyhVM9UWjbqyhoK5bLNSohLdVilcoyaMpJCiUol1EqVKvLqqi7qyo0CAELCPhXmrmML98sz+BtCkGXAPWFsWyrVremvK9MNyKVQPU9TnlyqCCpV5xTKaQs7zWjbunLYjlByV1tKW2iX+kqHqFgmXNMu9xVuYFCqW9x2gAyq/8slwk1exg3fArRlvqVy14btRtuWSlrr+puUHxe2bVxqW9q27lTDoIy31N+kjHdq2wZjS6W4Tcp8S2W8pUgRzbmfWIpbaNfeL+ncTzqvNOlvcs4K6O+36bzTtRuWD/8MP0EiIiIiIiLycYFERERERETk4wKJiIiIiIjIxwUSERERERGRjwskIiIiIiIiHxdIREREREREPi6QiIiIiIiIfNmdg5QmNEIJgSeWJ6wbdWETUi18KTfElcIkMsMS1tJKCODQ1fiXMpbg6veZpe1v9jcAXU6SSUYSIGR3QCjlL0YTCMeZZnDl6PuKEQO6saV5azKUADkvxdPkJEkRZdJhqH1ZMMg5ktrFHCTpoTbob5Kh1KN2DeYg9aKv9Pah6Z/JHCTptVB6burzgoS+YhaRLtNH31fctpj/lH7btpBzJGcZae6XJscIMJ13cDlHqXbN+FJmoklWkfDmJs1be+4nnVdK542ecCDq+pvkHEn9hZwj6Vw97djMQSIiIiIiIupbXCARERERERH5uEAiIiIiIiLycYFERERERETk4wKJiIiIiIjIxwUSERERERGRjwskIiIiIiIiX/bmIOlItdeFUAbLJKDDpD67MG8xnEA3bzGgRqrhL92v9HOTMpYAfQ1/hfThN/qMJMDkbwS6jCRAziLyhLwh/bb15KwiTZN0GGmyhlI3SH+/5LH1E/eEfap96go7TZehBAg5SqY5SNoNG45tklUkZSwFmINk1NdUgDlIYsaSSQ6SyVuElG2jbzbKQZL6SnlCZmNL+TWZGTvVrskTMshvAvRZRyYZSlL/QHOOAO25iOXqd5qYVaTL/JH6mpxjyQGC+nbp3NFo271vF3OOpHkHjJ8gERERERER+bhAIiIiIiIi8nGBRERERERE5OMCiYiIiIiIyMcFEhERERERkY8LJCIiIiIiIl/2lvn2vPQ1OLX1eiGWO9XWUhUrVgu1OR1NrWGx1LY08eBIJWCVdscIZdUNyoDrSoCnxg6uDLhEGlk7M6n6pfDMto0qikq1nzVlPaWS1ELdaKl0rW58qay6UN1f+4CZltrW9g+yjLfU37DUdpBjZ5TmMBTLeAc5tkkZcKnMt9QeZIlxg3La4ryldoOx7aS0bYNy2dK8NWW8pW2blPGW2oMs453qn/58wKiMt7BtS+wrlbTWlRAXzhulsU1KdUvblsbWHeMm5ceB9PtMKh/eQ/wEiYiIiIiIyMcFEhERERERkY8LJCIiIiIiIh8XSERERERERD4ukIiIiIiIiHxcIBEREREREfm4QCIiIiIiIvJlbw6SUkgbCiHVqxdykpSmxrrlCWtOMfzGoH67lO9kUuvekC7yRJ+RBJjlJOnvl1FOkhhAIz0eQm/dpoVnrhh7EEo/dyV0ljJ/dPdL2fp9pqScIyHLSDc3kwwlqV28XwaHilGGEhBsDpJBlpG4T/oxo6wjgywj4xwkzWuKOLZxDlKAWUW6+2WQc5Rq142t72sLb6tiDpLufhnkHEn95XlJY+vOkaQ8x97nHKXadbk7hhlL2qwig5wjQH8OZpJj1JNt69pNco6gP182nne6/tK4PcRPkIiIiIiIiHxcIBEREREREfm4QCIiIiIiIvJxgUREREREROTjAomIiIiIiMjHBRIREREREZGPCyQiIiIiIiJf1uYgKc+DShMiYEl5QRJN3XelC69BD3KSdGESUk14SwgW0dXpd4R5SdkFUkiGhhSHYpKTpM9IAqScJG3ITEgYW5MFAQAQMn30QTHCtvXxTvqcACHTR3rVsLU5SPq+usgEAFDSw6W533LOUe8zlpTuTgNyFpE2B6n38+rJtnXtxllFQY6dQdrMH8MIDqOxjXKQep/JY7xtMefIIC8oyCwig76AWZaReb5T77OKxLF185beF4XzHGnb2v4mOUeA/hxKzBoyyDKSMpaCyhMCzHKOetBfGFzfnOZ+iXPqIX6CRERERERE5OMCiYiIiIiIyMcFEhERERERkY8LJCIiIiIiIh8XSERERERERD4ukIiIiIiIiHxZW+bbiFQSUVcmXKqmKJUB15UklUpxu0I9U0dTA1kqIymS6kpnqgy4sL+FvxEoXQnxpLZrD8p467dt6Uo/C2UslVBDWWnmJlUMFdt18xYOE7kUt9Cu2S1iGW9HKCmq27ZhKW7tw6Wt+2w4NiCU4jasxR1gKW+TMuHCLjVjXOZbVydf6iu06142ghwb0L5wyCWrpW0bjG1UQtywzLe4bc39Est4G7SL8zIoxR1kGW9AW8rbqIy3tG2pnLUnHMS6bUtvutK5n9g//baNy3hrS4j3TTnuoPATJCIiIiIiIh8XSERERERERD4ukIiIiIiIiHxcIBEREREREfkCXSDdcMMNmDFjBvLy8lBSUtKjPueddx4sy9rmMm3atCCnSUREREREBCDgBVI8Hsfpp5+Oiy66aIf6zZo1C5s2beq6PPvsswHNkIiIiIiI6HOBlvm+/vrrAQD33nvvDvWLRqOoqKgIYEZERERERETp9cscpLlz56KsrAwlJSU4/PDDccMNN6CsrKzb23Z2dqKzs7Pr383Nzan/UQrpgh2UVIdfl3ME6Gu3i331zbqcJMsk+APQ18rXZSQBAeckmY2t2yv6jCR527p9LuXPiI+XNDVdjpI0ttTupW+3xLwgKfNHs8/E419oN8hRksaGFCWhu1+2WVaRNotIejwMco7k/lL4jcnY2UnMWDLISTIdW9dfyuQRxxYzf4LctknGkkEOkkGOUU+2rcuYMR1b21/sG2AWkZjZYzA3k5wjQJ/5Y5JzBOjvt2nOkdCuzToyyTkC9PtUmldvjxVpTj3U74o0HHfccXjwwQfx6quv4re//S3eeecdHHXUUdssgrZ24403ori4uOsyevTonTxjIiIiIiLKFju8QLruuuu2K6LwxcvChQt7PaEzzjgDJ5xwAqZMmYKTTjoJzz33HFasWIFnnnmm29tfffXVaGpq6rqsX7++19smIiIiIqLBbYe/YnfJJZfgzDPP1N5m7NixvZ3PdiorKzFmzBh88skn3bZHo1FEo9E+2x4REREREQ1eO7xAKi0tRWlpaRBz6VZdXR3Wr1+PysrKnbZNIiIiIiIanAL9DdK6deuwePFirFu3Dq7rYvHixVi8eDFaW1u7bjN58mTMmTMHANDa2orvf//7WLBgAdauXYu5c+fipJNOQmlpKU499dQgp0pERERERBRsFbuf/exnuO+++7r+ve+++wIAXnvtNRxxxBEAgOXLl6OpqQkA4DgOlixZgvvvvx+NjY2orKzEkUceiYcffhiFhYVBTpWIiIiIiCjYBdK9994rZiCprcrx5ebm4oUXXghySkRERERERGn1yxykPuGp9KEPUtaKSU6SVLfdJCdJCsEw+cKkVGc/0JwkYWyDnCQxhkUIatFl/khjSxlMlnC/dP0tMfdA2LYuL0h6OKSIAd2mDceWMk20OUjStqVMH93YBn1T29ZkLEnPe+Nta/qa5hhp7pcpk7mJeUImDDM4tHMzfH7o+ssZS73PC5LGN85B0ubu6Pua3C+jrKGetOvGF8eWMn0M+ppkEUnnV1I2lJiT1Ptti5k/uqwjk5wjQH8OZphzJN8vTbtJzpHQv9c5R13bHmQ5SERERERERJnCBRIREREREZGPCyQiIiIiIiIfF0hEREREREQ+LpCIiIiIiIh8XCARERERERH5uEAiIiIiIiLyZW8Oko5UE94gJ0mbkQQY5SQpIavIkkJmBmpOknEYi4aQ02JpdpoScoxMs4rg6LIJDI8zTb6TuL91fYX+lifkTtlSLpV+07rMEiVFLgh3y9JsWzxExV2myYoQ9okc9iVtWze28HjIQWM7Op2ttt37rsYCzEkyyRsyzm8yyCKS561v1vaXcnXE/Cfda6XQ1yTLSMxQMsg5kvqL+6z3+TViFpFBfo04tmmekG5u0nmMScaSSc6R1N8w50g6d9SOb5hVpM06Ms1vChg/QSIiIiIiIvJxgUREREREROTjAomIiIiIiMjHBRIREREREZGPCyQiIiIiIiIfF0hERERERES+7C3zrRSQrgyzZbgu1JQm1JY0hGEZcKGvURlw06WySRlwqaynI0xO2raOUMZY21Wocaykx1osE55+fKnKt2VQilsu463fuKUrWS2MLZYBF9p1paGlbSuppLWm5KhlWA5b212KHTAuMa5tFcbu/fMnyOr9QTMqty2VtjXZrkmpbamkrsnYgL70s/AWIJWs1paONikRDpiVrBa3LbwHaO+XVFZaKiFuUrLaYGxpfxuWldaeD5iU8Zb6m5YQ15baDrCMN6Df5yZlvHuybRPpsjv6aJv8BImIiIiIiMjHBRIREREREZGPCyQiIiIiIiIfF0hEREREREQ+LpCIiIiIiIh8XCARERERERH5uEAiIiIiIiLyZW0OkvIUVJpgBssW6rZ7wrrRNsj+MMlJkurNG+QkaTOSgGBzknQZSYCcTWCQxWKUiSUEuYizknKUNLk9Ui6IlFWky/yR8p3EY0HXLgY4CfdLymjSHQtCloQlPK+1OUm2kBUhHaO6/CZhnwSawSQJ8E9smcxJMso5kkg5MDpBZhEZZyxJWSsmfYXngK7ZJEMJ0N5vKcdIiLqT+2vmJu+z3ufTyPvEIE/IOItI2mcG2w4yY8ngGA8050joL+YcmRAzyPTbTpdNqJiDRERERERE1Le4QCIiIiIiIvJxgUREREREROTjAomIiIiIiMjHBRIREREREZGPCyQiIiIiIiIfF0hERERERES+rM1B0klXO/0zRjlJ0pJTyizR1JzXZiQBRjlJUp39QHOSpBr/0v3WtUuZCkJ+jb6vENQi1eIX7pcuj0hJ+0QJj6euvxRA40iZC7q8IH1Xqd3SjQ1AaR4TMS9IOBZ0/eWsIZMcJCmXyjCDSUcO8xK2HeCm+ynjDCWD/oFmERlkLKXGN+grRbHoMn3ErBWDfWaQLwMY5g0FmcEk7TOT+y2OLZwPmDye4j4zuF+GWV7ac7AAc44Aw6wjk/vdy5yjnYWfIBEREREREfm4QCIiIiIiIvJxgUREREREROTjAomIiIiIiMjHBRIREREREZGPCyQiIiIiIiJf9pb5Vh7S1rm0DNeFutKEuhLggFEZcKkUo1EZcKGvVAZcqudr6fa5Y1i+XL9hfbtJHWKxtrPpcaYpWS2VvxT2qfZYcoTHUq5prRnboES4NLbULpYYl2qMa0oJG5YQ183bMiylbVJi3JRRifEBSiyXbSLIUtvitoMrxS3dL7GctlH58t63G5Xp7km7ZnzxfkkRFyYlq8WxNe1BzltqNyyHrZubEkpWB1qevL+W8U5tvPfblqQbu4+2yU+QiIiIiIiIfFwgERERERER+bhAIiIiIiIi8nGBRERERERE5OMCiYiIiIiIyMcFEhERERERkY8LJCIiIiIiIl/25iDpCDXSlZBlZNmabA+xFr5BTpKUtWKSkyTVyRczlvTNyk5/A0uIWIJufwP6Ov2OIwwu0GUySBkvUvaNRHe/xXwnIbNEl5MkBOuI2TaaoS0lZQ2ZbVsbPSVkLFlCSIx22+LdMrhfpjlHUo6SyZ/JpMdDDO7pPZMIM6M8IFMGOUli1pDJtqUsItNMnwxlFUnvTUbbNshnMt52oHlB0mMpvGnr+gf5WAOALrPRMNNHm3VkknME6I+lIHOOpPEDzDlSmcxQ6gF+gkREREREROTjAomIiIiIiMjHBRIREREREZGPCyQiIiIiIiIfF0hEREREREQ+LpCIiIiIiIh8XCARERERERH5sjYHSXkKKk3YhTbHKNVZaE6/rjQdW5uTJC1nDXKStBlJQKA5SbqMJACwTLKjdJkIQA+yjHShPlIQi/SACXPTBb1oA39glh0lPJbyMZ6+XcxrMMwT0mYdZTBjSTxWxGNJw/B1QZdDJmZemeQcGdzlPuhuJsAcJTEbR8cgi0gyYLOK+nN+k5g31PtsHKP8mozOO3P5TtqcI6l/gPcr0JwjQLhfZtvWZh0FNLYyeQ3dCj9BIiIiIiIi8nGBRERERERE5OMCiYiIiIiIyMcFEhERERERkY8LJCIiIiIiIh8XSERERERERL6sLfOtoy07CLNS3boS4KZja0uAA0bLXamMZKBlwKXqlyZlwE3/BKC7X6b7RFfGG9CXZ7alUqfS2Jq5iyVBez9vsUy38PxQ0j7X1V8eqCXEJdLjIdE9XkJXuQw4fVGgZbyD7D9AS3FLLOl12qS0c5BlwKUSyUZjB1nSPcAy3oD2fhmV8Za2bXi/tOdgps97k5LvAul8OtCxA8ZPkIiIiIiIiHxcIBEREREREfm4QCIiIiIiIvJxgUREREREROTjAomIiIiIiMjHBRIREREREZGPCyQiIiIiIiJf9uYgKQ9pwxGE0BGjnCSh5rtRTpJYw1/KSdKNbVCjH4Y5SVJfV5ibpctzEPJnpAAag30mZeOI91vX3yRDCdDnKJlkKAH6fSbNS3q8pFwE7eMlZRXph85YxpLEMIvIJMtI7DkY/wRnkMkjMcpQAszyVDKZVWSUuxNgpo9J1hBglmWU0ftlMG/DfWaUZWScJ9T7rCLpHMoso2yQ5hyl27bBnLY2GN++iIiIiIiIusUFEhERERERkY8LJCIiIiIiIh8XSERERERERD4ukIiIiIiIiHxcIBEREREREfm4QCIiIiIiIvJlbw6SjlQj3SAnSZtj1INtSzlJOpZtmJOkI3Q1yklyXf3gJnlCUvSAsM8s3T6TdqdpbojufptkKAH60B+TDCVxbIMMJUCem+7hFPqKWUW6uUmxC8LYJllEpn/mEu+3CZN8p4HKNGslyLEzlUUkCTLTR2KSy2OSYySNLfU3zqXqfaZPkI+1Uc5RagBN3+CyiIxzjkwygcTzyuDGlrtnbtum+AkSERERERGRjwskIiIiIiIiHxdIREREREREPi6QiIiIiIiIfFwgERERERER+bhAIiIiIiIi8gW2QFq7di2+/e1vY9y4ccjNzcWECRNw7bXXIh6Pa/sppXDddddhxIgRyM3NxRFHHIGlS5cGNU0iIiIiIqIugeUgLVu2DJ7n4S9/+Qt23XVXfPjhhzj//PPR1taG3/zmN2n73XLLLfjd736He++9FxMnTsQvf/lLHHPMMVi+fDkKCwuDmu62DHKSpJrvRjlJBvlMqe69H1us0W+Yk6SjzVAC9NkGUl9XyGSwdDkUUq6OlPmjb9YKMjvKJENJ6i9lKBnmCWmPY+m5J9Fl+hhmCWmziKR5m0ZFBJiDZJTvNECJeUEmghzbNItIYpLpIwkyq6i32+3J2CbtAWb6mGb2aLOMgj7ODPKdTM5TBmzOUQ/GD2zbGc45klhKBfmKu61f//rXuOOOO7B69epu25VSGDFiBC6//HL88Ic/BAB0dnaivLwcN998My644AJxG83NzSguLsYROAUhK9yn8+8infhquxqcMBhsV9y24djGAZ+6riahqFJfceO9P3GVF0jB7bNAF0gm7aaLlEwukHTbNl0IBLnPTLZtiAukPsYFUve4QNrxsU36coG0w2NzgdS329VJqgTm4kk0NTWhqKio1+Ps1N8gNTU1YejQoWnb16xZg+rqasycObPrumg0isMPPxzz58/vtk9nZyeam5u3uRAREREREfXGTlsgrVq1Cn/+859x4YUXpr1NdXU1AKC8vHyb68vLy7vavujGG29EcXFx12X06NF9N2kiIiIiIhpUdniBdN1118GyLO1l4cKF2/TZuHEjZs2ahdNPPx3f+c53xG188fv4Sqm039G/+uqr0dTU1HVZv379jt4lIiIiIiIiAL0o0nDJJZfgzDPP1N5m7NixXf+/ceNGHHnkkZg+fTruuusubb+KigoAqU+SKisru67fvHnzdp8qfSYajSIajfZw9kREREREROnt8AKptLQUpaWlPbptVVUVjjzySEydOhX33HMPbOEH8+PGjUNFRQVeeukl7LvvvgCAeDyOefPm4eabb+7RNj+rOZFEAgjs96wGRRqkCmABbVfetuGPqcX7ZVCkQUn3WzO22FfcevomXVUz9KBIg7RPgizSoDuWxEIIJtvOYJGGQLcd4NhGrxmG2zbEIg19bCAXadC9IQ/aIg3C+NlYpMG0cIXEYNvaeYvbDfB+ifPOYJEGo/sVUJEGJFLDmxeWCUZVVZXadddd1VFHHaU2bNigNm3a1HXZ2qRJk9Tjjz/e9e+bbrpJFRcXq8cff1wtWbJEnXXWWaqyslI1Nzf3aLvr169XSL3s8MILL7zwwgsvvPDCCy+D7LJ+/XqjdUxgOUgvvvgiVq5ciZUrV2LUqFHbtKmtVnXLly9HU1NT17+vuuoqdHR04OKLL0ZDQwMOOuggvPjiiz3OQBoxYgTWr1+PwsJCWJaF5uZmjB49GuvXrzcq90e9w/2fOdz3mcN9nznc95nF/Z853PeZw32fWVvv/8LCQrS0tGDEiBFGY+7UHKRM+CwXybQeOvUO93/mcN9nDvd95nDfZxb3f+Zw32cO931mBbH/d2oOEhERERERUX/GBRIREREREZEv6xdI0WgU1157LUuBZwj3f+Zw32cO933mcN9nFvd/5nDfZw73fWYFsf+z/jdIREREREREPZX1nyARERERERH1FBdIREREREREPi6QiIiIiIiIfFwgERERERER+bJugbR27Vp8+9vfxrhx45Cbm4sJEybg2muvRTwe1/ZTSuG6667DiBEjkJubiyOOOAJLly7dSbPOHjfccANmzJiBvLw8lJSU9KjPeeedB8uytrlMmzYt2Ilmqd7sfx77faOhoQGzZ89GcXExiouLMXv2bDQ2Nmr78Njvndtvvx3jxo1DTk4Opk6dijfeeEN7+3nz5mHq1KnIycnB+PHjceedd+6kmWanHdn/c+fO3e4YtywLy5Yt24kzzg6vv/46TjrpJIwYMQKWZeGJJ54Q+/DY7xs7uu953PedG2+8EQcccAAKCwtRVlaGr3zlK1i+fLnYz/TYz7oF0rJly+B5Hv7yl79g6dKl+P3vf48777wT11xzjbbfLbfcgt/97ne49dZb8c4776CiogLHHHMMWlpadtLMs0M8Hsfpp5+Oiy66aIf6zZo1C5s2beq6PPvsswHNMLv1Zv/z2O8bZ599NhYvXoznn38ezz//PBYvXozZs2eL/Xjs75iHH34Yl19+OX784x9j0aJFOPTQQ3Hcccdh3bp13d5+zZo1OP7443HooYdi0aJFuOaaa3DZZZfhscce28kzzw47uv8/s3z58m2O8912220nzTh7tLW1Ye+998att97ao9vz2O87O7rvP8Pj3ty8efPw3e9+F2+++SZeeuklJJNJzJw5E21tbWn79MmxrwaBW265RY0bNy5tu+d5qqKiQt10001d18ViMVVcXKzuvPPOnTHFrHPPPfeo4uLiHt323HPPVaecckqg8xlserr/eez3jY8++kgBUG+++WbXdQsWLFAA1LJly9L247G/4w488EB14YUXbnPd5MmT1Y9+9KNub3/VVVepyZMnb3PdBRdcoKZNmxbYHLPZju7/1157TQFQDQ0NO2F2gwcANWfOHO1teOwHoyf7nsd9cDZv3qwAqHnz5qW9TV8c+1n3CVJ3mpqaMHTo0LTta9asQXV1NWbOnNl1XTQaxeGHH4758+fvjCkOenPnzkVZWRkmTpyI888/H5s3b870lAYFHvt9Y8GCBSguLsZBBx3Udd20adNQXFws7kce+z0Xj8fx7rvvbnO8AsDMmTPT7ucFCxZsd/tjjz0WCxcuRCKRCGyu2ag3+/8z++67LyorK3H00UfjtddeC3Ka5OOxn3k87vteU1MTAGjP6/vi2M/6BdKqVavw5z//GRdeeGHa21RXVwMAysvLt7m+vLy8q42Cc9xxx+HBBx/Eq6++it/+9rd45513cNRRR6GzszPTU8t6PPb7RnV1NcrKyra7vqysTLsfeezvmNraWriuu0PHa3V1dbe3TyaTqK2tDWyu2ag3+7+yshJ33XUXHnvsMTz++OOYNGkSjj76aLz++us7Y8qDGo/9zOFxHwylFK688koccsghmDJlStrb9cWxP2AWSNddd123P3jb+rJw4cJt+mzcuBGzZs3C6aefju985zviNizL2ubfSqntrhuMerPvd8QZZ5yBE044AVOmTMFJJ52E5557DitWrMAzzzzTh/di4Ap6/wM89tPZkX3f3f6S9iOP/d7Z0eO1u9t3dz31zI7s/0mTJuH888/Hfvvth+nTp+P222/HCSecgN/85jc7Y6qDHo/9zOBxH4xLLrkEH3zwAf7xj3+ItzU99kM7Pr3MuOSSS3DmmWdqbzN27Niu/9+4cSOOPPJITJ8+HXfddZe2X0VFBYDUirOysrLr+s2bN2+3Ah2MdnTfm6qsrMSYMWPwySef9NmYA1mQ+5/Hvl5P9/0HH3yAmpqa7dq2bNmyQ/uRx75eaWkpHMfZ7tMK3fFaUVHR7e1DoRCGDRsW2FyzUW/2f3emTZuGBx54oK+nR1/AY79/4XFv5tJLL8VTTz2F119/HaNGjdLeti+O/QGzQCotLUVpaWmPbltVVYUjjzwSU6dOxT333APb1n9QNm7cOFRUVOCll17CvvvuCyD1Xet58+bh5ptvNp77QLcj+74v1NXVYf369ducsA9mQe5/Hvt6Pd3306dPR1NTE95++20ceOCBAIC33noLTU1NmDFjRo+3x2NfLxKJYOrUqXjppZdw6qmndl3/0ksv4ZRTTum2z/Tp0/H0009vc92LL76I/fffH+FwOND5Zpve7P/uLFq0iMf4TsBjv3/hcd87SilceumlmDNnDubOnYtx48aJffrk2N/B4hH9XlVVldp1113VUUcdpTZs2KA2bdrUddnapEmT1OOPP97175tuukkVFxerxx9/XC1ZskSdddZZqrKyUjU3N+/suzCgffrpp2rRokXq+uuvVwUFBWrRokVq0aJFqqWlpes2W+/7lpYW9b3vfU/Nnz9frVmzRr322mtq+vTpauTIkdz3vbCj+18pHvt9ZdasWepLX/qSWrBggVqwYIHaa6+91IknnrjNbXjsm/vnP/+pwuGwuvvuu9VHH32kLr/8cpWfn6/Wrl2rlFLqRz/6kZo9e3bX7VevXq3y8vLUFVdcoT766CN19913q3A4rB599NFM3YUBbUf3/+9//3s1Z84ctWLFCvXhhx+qH/3oRwqAeuyxxzJ1FwaslpaWrtd0AOp3v/udWrRokfr000+VUjz2g7Sj+57Hfd+56KKLVHFxsZo7d+425/Tt7e1dtwni2M+6BdI999yjAHR72RoAdc8993T92/M8de2116qKigoVjUbVYYcdppYsWbKTZz/wnXvuud3u+9dee63rNlvv+/b2djVz5kw1fPhwFQ6H1S677KLOPfdctW7duszcgQFuR/e/Ujz2+0pdXZ0655xzVGFhoSosLFTnnHPOdiVeeez3jdtuu02NGTNGRSIRtd9++21T7vXcc89Vhx9++Da3nzt3rtp3331VJBJRY8eOVXfcccdOnnF22ZH9f/PNN6sJEyaonJwcNWTIEHXIIYeoZ555JgOzHvg+Kx39xcu5556rlOKxH6Qd3fc87vtOunP6rc9jgjj2LX/jREREREREg96AqWJHREREREQUNC6QiIiIiIiIfFwgERERERER+bhAIiIiIiIi8nGBRERERERE5OMCiYiIiIiIyMcFEhERERERkY8LJCIiIiIiIh8XSERERERERD4ukIiIiIiIiHxcIBEREREREfm4QCIiIiIiIvL9f4GakoP/V9vxAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot initial flow distribution, target as contours\n",
+    "model.eval()\n",
+    "log_prob = model.log_prob(zz, context_plot).to('cpu').view(*xx.shape)\n",
+    "model.train()\n",
+    "prob = torch.exp(log_prob)\n",
+    "prob[torch.isnan(prob)] = 0\n",
+    "\n",
+    "plt.figure(figsize=(10, 10))\n",
+    "plt.pcolormesh(xx, yy, prob.data.numpy(), shading='auto')\n",
+    "plt.contour(xx, yy, p_target, cmap=plt.get_cmap('cool'), linewidths=2)\n",
+    "plt.gca().set_aspect('equal', 'box')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "id": "ca642040-41ea-424c-8ca9-b4f73d1ac189",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  0%|          | 0/5000 [00:00<?, ?it/s]\n"
+     ]
+    },
+    {
+     "ename": "TypeError",
+     "evalue": "isnan(): argument 'input' (position 1) must be Tensor, not tuple",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[90], line 23\u001b[0m\n\u001b[1;32m     20\u001b[0m loss \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mforward_and_log_det(x, context)\n\u001b[1;32m     22\u001b[0m \u001b[38;5;66;03m# Do backprop and optimizer step\u001b[39;00m\n\u001b[0;32m---> 23\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;241m~\u001b[39m(\u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43misnan\u001b[49m\u001b[43m(\u001b[49m\u001b[43mloss\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;241m|\u001b[39m torch\u001b[38;5;241m.\u001b[39misinf(loss)):\n\u001b[1;32m     24\u001b[0m     loss\u001b[38;5;241m.\u001b[39mbackward()\n\u001b[1;32m     25\u001b[0m     optimizer\u001b[38;5;241m.\u001b[39mstep()\n",
+      "\u001b[0;31mTypeError\u001b[0m: isnan(): argument 'input' (position 1) must be Tensor, not tuple"
+     ]
+    }
+   ],
+   "source": [
+    "# Train model\n",
+    "max_iter = 5000\n",
+    "batch_size= 128\n",
+    "\n",
+    "loss_hist = np.array([])\n",
+    "\n",
+    "optimizer = torch.optim.Adam(model.parameters(), lr=3e-4, weight_decay=1e-5)\n",
+    "\n",
+    "\n",
+    "for it in tqdm(range(max_iter)):\n",
+    "    optimizer.zero_grad()\n",
+    "    \n",
+    "    # Get training samples\n",
+    "    context = torch.cat([torch.randn((batch_size, 2), device=device), \n",
+    "                         0.5 + 0.5 * torch.rand((batch_size, 2), device=device)], \n",
+    "                        dim=-1)\n",
+    "    x = target.sample(batch_size, context)\n",
+    "    \n",
+    "    # Compute loss\n",
+    "    loss = model.forward_kld(x, context)\n",
+    "    \n",
+    "    # Do backprop and optimizer step\n",
+    "    if ~(torch.isnan(loss) | torch.isinf(loss)):\n",
+    "        loss.backward()\n",
+    "        optimizer.step()\n",
+    "    \n",
+    "    # Log loss\n",
+    "    loss_hist = np.append(loss_hist, loss.to('cpu').data.numpy())\n",
+    "\n",
+    "# Plot loss\n",
+    "plt.figure(figsize=(10, 10))\n",
+    "plt.plot(loss_hist, label='loss')\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 166,
+   "id": "2afa5bd7-a08d-4e89-ba39-e60e95458683",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot trained flow distribution, target as contours\n",
+    "model.eval()\n",
+    "log_prob = model.log_prob(zz, context_plot).to('cpu').view(*xx.shape)\n",
+    "model.train()\n",
+    "prob = torch.exp(log_prob)\n",
+    "prob[torch.isnan(prob)] = 0\n",
+    "\n",
+    "plt.figure(figsize=(10, 10))\n",
+    "plt.pcolormesh(xx, yy, prob.data.numpy(), shading='auto')\n",
+    "plt.contour(xx, yy, p_target, cmap=plt.get_cmap('cool'), linewidths=2)\n",
+    "plt.gca().set_aspect('equal', 'box')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6cdd4901-8484-460c-aa19-2dfd063adabe",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## SAME WITH OTHER DATA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "d0605419-5d8c-42aa-8e61-c658dcb226ae",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Set up model\n",
+    "\n",
+    "# Define 2D Gaussian base distribution\n",
+    "base = nf.distributions.base.DiagGaussian(2)\n",
+    "\n",
+    "# Define list of flows\n",
+    "num_layers = 32\n",
+    "flows = []\n",
+    "for i in range(num_layers):\n",
+    "    # Neural network with two hidden layers having 64 units each\n",
+    "    # Last layer is initialized by zeros making training more stable\n",
+    "    param_map = nf.nets.MLP([1, 64, 64, 2], init_zeros=True)\n",
+    "    # Add flow layer\n",
+    "    flows.append(nf.flows.AffineCouplingBlock(param_map))\n",
+    "    # Swap dimensions\n",
+    "    flows.append(nf.flows.Permute(2, mode='swap'))\n",
+    "    \n",
+    "# Construct flow model\n",
+    "model = nf.NormalizingFlow(base, flows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "id": "6109315b-108b-43ce-aea0-0b87ab73343d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "model = model.to(device)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "id": "057db06d-2b6f-4fd1-a412-d986f7c1bf7c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Define target distribution\n",
+    "target = nf.distributions.TwoMoons()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "id": "d5cae618-ac79-48e6-8bb8-92594d6799c3",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at  /home/conda/feedstock_root/build_artifacts/pytorch-recipe_1650973827143/work/aten/src/ATen/native/TensorShape.cpp:2227.)\n",
+      "  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]\n",
+      "/tmp/ipykernel_66/453332150.py:12: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.\n",
+      "  plt.pcolormesh(xx, yy, prob.data.numpy(), cmap='coolwarm')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x1500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot target distribution\n",
+    "grid_size = 200\n",
+    "xx, yy = torch.meshgrid(torch.linspace(-3, 3, grid_size), torch.linspace(-3, 3, grid_size))\n",
+    "zz = torch.cat([xx.unsqueeze(2), yy.unsqueeze(2)], 2).view(-1, 2)\n",
+    "zz = zz.to(device)\n",
+    "\n",
+    "log_prob = target.log_prob(zz).to('cpu').view(*xx.shape)\n",
+    "prob = torch.exp(log_prob)\n",
+    "prob[torch.isnan(prob)] = 0\n",
+    "\n",
+    "plt.figure(figsize=(15, 15))\n",
+    "plt.pcolormesh(xx, yy, prob.data.numpy(), cmap='coolwarm')\n",
+    "plt.gca().set_aspect('equal', 'box')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "id": "2b73c024-4c81-429e-839f-76a522249401",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_66/3929658094.py:9: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.\n",
+      "  plt.pcolormesh(xx, yy, prob.data.numpy(), cmap='coolwarm')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x1500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot initial flow distribution\n",
+    "model.eval()\n",
+    "log_prob = model.log_prob(zz).to('cpu').view(*xx.shape)\n",
+    "model.train()\n",
+    "prob = torch.exp(log_prob)\n",
+    "prob[torch.isnan(prob)] = 0\n",
+    "\n",
+    "plt.figure(figsize=(15, 15))\n",
+    "plt.pcolormesh(xx, yy, prob.data.numpy(), cmap='coolwarm')\n",
+    "plt.gca().set_aspect('equal', 'box')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "id": "a2b3731c-d5fe-4b59-a83f-0a698d49348e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 12%|█▏        | 499/4000 [00:38<04:10, 13.95it/s]/tmp/ipykernel_66/2851951940.py:37: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.\n",
+      "  plt.pcolormesh(xx, yy, prob.data.numpy(), cmap='coolwarm')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x1500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 25%|██▍       | 999/4000 [01:15<03:55, 12.74it/s]"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x1500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 37%|███▋      | 1499/4000 [01:51<03:06, 13.40it/s]"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x1500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 50%|████▉     | 1999/4000 [02:29<02:34, 12.95it/s]"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x1500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 62%|██████▏   | 2499/4000 [03:07<01:47, 14.01it/s]"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x1500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 75%|███████▍  | 2999/4000 [03:42<01:15, 13.34it/s]"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x1500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 87%|████████▋ | 3499/4000 [04:20<00:36, 13.63it/s]"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x1500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████▉| 3999/4000 [04:58<00:00, 14.69it/s]"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x1500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 4000/4000 [04:58<00:00, 13.39it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Train model\n",
+    "max_iter = 4000\n",
+    "num_samples = 2 ** 9\n",
+    "show_iter = 500\n",
+    "\n",
+    "\n",
+    "loss_hist = np.array([])\n",
+    "\n",
+    "optimizer = torch.optim.Adam(model.parameters(), lr=5e-4, weight_decay=1e-5)\n",
+    "\n",
+    "for it in tqdm(range(max_iter)):\n",
+    "    optimizer.zero_grad()\n",
+    "    \n",
+    "    # Get training samples\n",
+    "    x = target.sample(num_samples).to(device)\n",
+    "    \n",
+    "    # Compute loss\n",
+    "    loss = model.forward_kld(x)\n",
+    "    \n",
+    "    # Do backprop and optimizer step\n",
+    "    if ~(torch.isnan(loss) | torch.isinf(loss)):\n",
+    "        loss.backward()\n",
+    "        optimizer.step()\n",
+    "    \n",
+    "    # Log loss\n",
+    "    loss_hist = np.append(loss_hist, loss.to('cpu').data.numpy())\n",
+    "    \n",
+    "    # Plot learned distribution\n",
+    "    if (it + 1) % show_iter == 0:\n",
+    "        model.eval()\n",
+    "        log_prob = model.log_prob(zz)\n",
+    "        model.train()\n",
+    "        prob = torch.exp(log_prob.to('cpu').view(*xx.shape))\n",
+    "        prob[torch.isnan(prob)] = 0\n",
+    "\n",
+    "        plt.figure(figsize=(15, 15))\n",
+    "        plt.pcolormesh(xx, yy, prob.data.numpy(), cmap='coolwarm')\n",
+    "        plt.gca().set_aspect('equal', 'box')\n",
+    "        plt.show()\n",
+    "\n",
+    "# Plot loss\n",
+    "plt.figure(figsize=(10, 10))\n",
+    "plt.plot(loss_hist, label='loss')\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "id": "72bc7665-9ecc-4c4c-ba12-37f67e79a555",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_66/1680222339.py:8: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.\n",
+      "  ax[0].pcolormesh(xx, yy, prob.data.numpy(), cmap='coolwarm')\n",
+      "/tmp/ipykernel_66/1680222339.py:21: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.\n",
+      "  ax[1].pcolormesh(xx, yy, prob.data.numpy(), cmap='coolwarm')\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x700 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot target distribution\n",
+    "f, ax = plt.subplots(1, 2, sharey=True, figsize=(15, 7))\n",
+    "\n",
+    "log_prob = target.log_prob(zz).to('cpu').view(*xx.shape)\n",
+    "prob = torch.exp(log_prob)\n",
+    "prob[torch.isnan(prob)] = 0\n",
+    "\n",
+    "ax[0].pcolormesh(xx, yy, prob.data.numpy(), cmap='coolwarm')\n",
+    "\n",
+    "ax[0].set_aspect('equal', 'box')\n",
+    "ax[0].set_axis_off()\n",
+    "ax[0].set_title('Target', fontsize=24)\n",
+    "\n",
+    "# Plot learned distribution\n",
+    "model.eval()\n",
+    "log_prob = model.log_prob(zz).to('cpu').view(*xx.shape)\n",
+    "model.train()\n",
+    "prob = torch.exp(log_prob)\n",
+    "prob[torch.isnan(prob)] = 0\n",
+    "\n",
+    "ax[1].pcolormesh(xx, yy, prob.data.numpy(), cmap='coolwarm')\n",
+    "\n",
+    "ax[1].set_aspect('equal', 'box')\n",
+    "ax[1].set_axis_off()\n",
+    "ax[1].set_title('Real NVP', fontsize=24)\n",
+    "\n",
+    "plt.subplots_adjust(wspace=0.1)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b5a02d51-fe15-4f14-8bf2-08cc101802f6",
+   "metadata": {},
+   "source": [
+    "## ANOTHER EXAMPLE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "id": "a48970ce-3d06-4470-8ff9-db989f5328c9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "class Conditinoal_Encoder(nn.Module):\n",
+    "    \"\"\"Convolutional dense encoder for conditioning the generative model.\n",
+    "    See Fig. 4 of paper: https://arxiv.org/abs/2006.04731\n",
+    "\n",
+    "    :param in_features: Number of input features\n",
+    "    :param enc_block_layers: list of the number of dense layers in each desired dense block\n",
+    "    :param init_features: Number of channels after te first convolution, defaults to 48\n",
+    "    :param output_features: Number of output channel features (will be twice this value\n",
+    "        since final value will be turned into mu and stds for latent variables), defaults to 8\n",
+    "    :type output_features: int, optional\n",
+    "    :param cond_features: Number of conditional feature channels, defaults to 8\n",
+    "    :type cond_features: int, optional\n",
+    "    :param cglow_upscale: The factor to upscale the features from the dense encode \n",
+    "        before passing them to the generative model, defaults to 1\n",
+    "    :type cglow_upscale: int, optional\n",
+    "    :param bn_size: number of features after bottleneck if enabled, defaults to 8\n",
+    "    :type bn_size: int, optional\n",
+    "    :param drop_rate: Dropout rate, defaults to 0.\n",
+    "    :type drop_rate: float, optional\n",
+    "    \"\"\"\n",
+    "    def __init__(self, init_features, \n",
+    "                enc_block_layers, \n",
+    "                hidden_features,\n",
+    "                output_dim=8, \n",
+    "                drop_rate=0\n",
+    "                ):\n",
+    "        \"\"\"Constructor method\"\"\" \n",
+    "        super(Conditinoal_Encoder, self).__init__()\n",
+    "        # First encoding module\n",
+    "\n",
+    "        self.encoding_blocks = []\n",
+    "\n",
+    "        # Construct dense block layers\n",
+    "        num_feat = init_features\n",
+    "        for i in range(enc_block_layers):\n",
+    "            block = nn.Sequential()\n",
+    "            block.add_module('encode_mlp{}'.format(i), self.mlp_block(num_feat, hidden_features[i], drop_rate=drop_rate))\n",
+    "            num_feat = hidden_features[i]\n",
+    "\n",
+    "            self.encoding_blocks.append(block)\n",
+    "            \n",
+    "        \n",
+    "        block.add_module('encode_mlp{}'.format(i+1),\n",
+    "            self.mlp_block(num_feat, 2*output_dim, drop_rate=drop_rate))\n",
+    "        \n",
+    "        # Convert lists to module lists\n",
+    "        self.encoding_blocks = nn.ModuleList(self.encoding_blocks)\n",
+    "        \n",
+    "    def mlp_block(self, in_features, out_features, drop_rate=0):\n",
+    "        \"\"\"Encoding transition convolution placed between dense blocks, halves feature map size\n",
+    "\n",
+    "        :param in_features: Number of input features\n",
+    "        :param output_features: Number of output features\n",
+    "        :param drop_rate: Dropout rate, defaults to 0.\n",
+    "        \n",
+    "        \n",
+    "            - encoder_trans: Transition PyTorch module\n",
+    "        :rtype: nn.Module\n",
+    "        \"\"\"\n",
+    "        block = nn.Sequential(nn.Linear(in_features, out_features))\n",
+    "        block.add_module('linear1', nn.Linear(in_features, out_features))\n",
+    "        block.add_module('relu1', nn.ReLU(inplace=False))\n",
+    "        if drop_rate > 0:\n",
+    "            block.add_module('dropout1', nn.Dropout(p=drop_rate))\n",
+    "\n",
+    "        return block\n",
+    "\n",
+    "    def forward(self, x):\n",
+    "        \"\"\"Encoder forward pass\n",
+    "\n",
+    "        :param x: [B, in_features, H, W] input feature tensor\n",
+    "        :type x: torch.Tensor\n",
+    "        :returns:\n",
+    "            - out: Final encoder output\n",
+    "            - c_out: List of conditional output states to conditional the generative model\n",
+    "        :rtype: (torch.Tensor, list)\n",
+    "        \"\"\"\n",
+    "\n",
+    "        c_out = []\n",
+    "        for i, block in enumerate(self.encoding_blocks):\n",
+    "            # Pass though dense block\n",
+    "            dense_out = block(x)\n",
+    "            c_out.append(dense_out)\n",
+    "            out = dense_out\n",
+    "        return out, c_out\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "id": "4c9749f9-fa98-4abc-91c2-bd98666be212",
+   "metadata": {
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Conditinoal_Encoder(\n",
+       "  (encoding_blocks): ModuleList(\n",
+       "    (0): Sequential(\n",
+       "      (encode_mlp0): Sequential(\n",
+       "        (0): Linear(in_features=6, out_features=10, bias=True)\n",
+       "        (linear1): Linear(in_features=6, out_features=10, bias=True)\n",
+       "        (relu1): ReLU()\n",
+       "        (dropout1): Dropout(p=0.1, inplace=False)\n",
+       "      )\n",
+       "    )\n",
+       "    (1): Sequential(\n",
+       "      (encode_mlp1): Sequential(\n",
+       "        (0): Linear(in_features=10, out_features=50, bias=True)\n",
+       "        (linear1): Linear(in_features=10, out_features=50, bias=True)\n",
+       "        (relu1): ReLU()\n",
+       "        (dropout1): Dropout(p=0.1, inplace=False)\n",
+       "      )\n",
+       "    )\n",
+       "    (2): Sequential(\n",
+       "      (encode_mlp2): Sequential(\n",
+       "        (0): Linear(in_features=50, out_features=10, bias=True)\n",
+       "        (linear1): Linear(in_features=50, out_features=10, bias=True)\n",
+       "        (relu1): ReLU()\n",
+       "        (dropout1): Dropout(p=0.1, inplace=False)\n",
+       "      )\n",
+       "      (encode_mlp3): Sequential(\n",
+       "        (0): Linear(in_features=10, out_features=2, bias=True)\n",
+       "        (linear1): Linear(in_features=10, out_features=2, bias=True)\n",
+       "        (relu1): ReLU()\n",
+       "        (dropout1): Dropout(p=0.1, inplace=False)\n",
+       "      )\n",
+       "    )\n",
+       "  )\n",
+       ")"
+      ]
+     },
+     "execution_count": 112,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Conditinoal_Encoder(init_features=6, \n",
+    "                enc_block_layers=3, \n",
+    "                hidden_features = [10,50,10],\n",
+    "                output_dim=1, \n",
+    "                drop_rate=0.1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "08612a10-c9d3-4a8a-9031-f3a064aa44aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "class AffineCouplingLayer(nn.Module):\n",
+    "    \"\"\"Conditional invertable affine coupling layer.\n",
+    "    See Fig. 7 of paper: https://arxiv.org/abs/2006.04731\n",
+    "\n",
+    "    :param in_features: Number of input feature channels\n",
+    "    :type in_features: int\n",
+    "    :param cond_features: Number of conditional feature channels\n",
+    "    :type cond_features: int\n",
+    "\n",
+    "    :note: For more information see \"NICE: Non-linear Independent \n",
+    "        Components Estimation\" by Dihn et al. https://arxiv.org/abs/1410.8516\n",
+    "\n",
+    "    :note: Check Feistel cipher as this functions very similarly.\n",
+    "    \"\"\"\n",
+    "    def __init__(self, in_features, cond_features):\n",
+    "        \"\"\"Constructor method\n",
+    "        \"\"\" \n",
+    "        super(AffineCouplingLayer, self).__init__()\n",
+    "        # assert in_features % 2 == 0, '# input features must be evenly split,'\\\n",
+    "        #     'but got {} features'.format(in_features)\n",
+    "        if in_features % 2 == 0:\n",
+    "            in_channels = in_features // 2 + cond_features\n",
+    "            out_channels = in_features\n",
+    "        else:\n",
+    "            # chunk is be (2, 1) if in_features==3\n",
+    "            in_channels = in_features // 2 + 1 + cond_features\n",
+    "            out_channels = in_features - 1\n",
+    "        \n",
+    "        # Initialize coupling network (Dense Block)\n",
+    "        num_layers = 2\n",
+    "        growth_rate = 1\n",
+    "        self.coupling_nn = nn.Sequential()\n",
+    "        self.coupling_nn.add_module('dense_block', NoNormDenseBlock(num_layers, in_channels, \n",
+    "                    growth_rate=growth_rate, drop_rate=0., bottleneck=False))\n",
+    "        self.coupling_nn.add_module('relu1', nn.ReLU(inplace=True))\n",
+    "        self.coupling_nn.add_module('zero_conv', Conv2dZeros(in_channels + growth_rate*num_layers, out_channels))\n",
+    "\n",
+    "        self.softsign = nn.Softsign()\n",
+    "\n",
+    "    def forward(self, x, cond):\n",
+    "        \"\"\"Forward pass\n",
+    "\n",
+    "        :param x:  [B, in_features, H, W] input feature tensor\n",
+    "        :type x: torch.Tensor\n",
+    "        :param cond: [B, cond_features, H, W] input feature tensor\n",
+    "        :type cond: torch.Tensor\n",
+    "        :returns: \n",
+    "            - y: [B, in_features, H, W] Output feature tensor\n",
+    "            - logdet: log determinate of affine layer\n",
+    "        :rtype: (torch.Tensor, torch.Tensor)\n",
+    "        \"\"\"\n",
+    "        #  Split in the channel dimension\n",
+    "        # last chunk is smaller if not odd number of channels\n",
+    "        x1, x2 = x.chunk(2, 1)\n",
+    "        h = self.coupling_nn(torch.cat((x1, cond), 1))\n",
+    "\n",
+    "        shift = h[:, 0::2]\n",
+    "        scale = (2*self.softsign(h[:, 1::2])).exp()\n",
+    "\n",
+    "        x2 = x2 + shift\n",
+    "        x2 = x2 * scale\n",
+    "        logdet = torch.abs(scale).log().view(x.shape[0], -1).sum(1)\n",
+    "\n",
+    "        return torch.cat((x1, x2), 1), logdet\n",
+    "\n",
+    "    def reverse(self, y, cond):\n",
+    "        \"\"\"Backward pass\n",
+    "\n",
+    "        :param y:  [B, in_features, H, W] input feature tensor\n",
+    "        :type y: torch.Tensor\n",
+    "        :param cond: [B, cond_features, H, W] input feature tensor\n",
+    "        :type cond: torch.Tensor\n",
+    "        :returns: \n",
+    "            - x: [B, in_features, H, W] Output feature tensor\n",
+    "            - logdet: log determinate of affine layer\n",
+    "        :rtype: (torch.Tensor, torch.Tensor)\n",
+    "        \"\"\"\n",
+    "        #  Split in the channel dimension\n",
+    "        y1, y2 = y.chunk(2, 1)\n",
+    "\n",
+    "        h = self.coupling_nn(torch.cat((y1, cond), 1))\n",
+    "\n",
+    "        shift = h[:, 0::2]\n",
+    "        scale = (2*self.softsign(h[:, 1::2])).exp()\n",
+    "\n",
+    "        y2 = y2 / scale\n",
+    "        y2 = y2 - shift\n",
+    "        logdet = torch.abs(scale).log().view(y.shape[0], -1).sum(1)\n",
+    "\n",
+    "        return torch.cat((y1, y2), 1), logdet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2ff114e7-3371-4254-a663-482f71250a55",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "81023f27-b4d2-4a6b-a155-8633e21ad5be",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "33e8738c-2b7f-4d6d-b238-982cddc92a3c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "'''\n",
+    "=====\n",
+    "Distributed by: Notre Dame SCAI Lab (MIT Liscense)\n",
+    "- Associated publication:\n",
+    "url: http://aimsciences.org//article/id/3a9f3d14-3421-4947-a45f-a9cc74edd097\n",
+    "doi: https://dx.doi.org/10.3934/fods.2020019\n",
+    "github: https://github.com/zabaras/deep-turbulence\n",
+    "=====\n",
+    "'''\n",
+    "import sys\n",
+    "sys.path.append(\".\")\n",
+    "\n",
+    "from nn.modules.denseBlock import DenseBlock, NoNormDenseBlock\n",
+    "from nn.modules.convLSTM import ResidLSTMBlock\n",
+    "from nn.modules.flowUtils import Conv2dZeros\n",
+    "import torch\n",
+    "import torch.nn as nn\n",
+    "import torch.nn.functional as F\n",
+    "\n",
+    "class AffineCouplingLayer(nn.Module):\n",
+    "    \"\"\"Conditional invertable affine coupling layer.\n",
+    "    See Fig. 7 of paper: https://arxiv.org/abs/2006.04731\n",
+    "\n",
+    "    :param in_features: Number of input feature channels\n",
+    "    :type in_features: int\n",
+    "    :param cond_features: Number of conditional feature channels\n",
+    "    :type cond_features: int\n",
+    "\n",
+    "    :note: For more information see \"NICE: Non-linear Independent \n",
+    "        Components Estimation\" by Dihn et al. https://arxiv.org/abs/1410.8516\n",
+    "\n",
+    "    :note: Check Feistel cipher as this functions very similarly.\n",
+    "    \"\"\"\n",
+    "    def __init__(self, in_features, cond_features):\n",
+    "        \"\"\"Constructor method\n",
+    "        \"\"\" \n",
+    "        super(AffineCouplingLayer, self).__init__()\n",
+    "        # assert in_features % 2 == 0, '# input features must be evenly split,'\\\n",
+    "        #     'but got {} features'.format(in_features)\n",
+    "        if in_features % 2 == 0:\n",
+    "            in_channels = in_features // 2 + cond_features\n",
+    "            out_channels = in_features\n",
+    "        else:\n",
+    "            # chunk is be (2, 1) if in_features==3\n",
+    "            in_channels = in_features // 2 + 1 + cond_features\n",
+    "            out_channels = in_features - 1\n",
+    "        \n",
+    "        # Initialize coupling network (Dense Block)\n",
+    "        num_layers = 2\n",
+    "        growth_rate = 1\n",
+    "        self.coupling_nn = nn.Sequential()\n",
+    "        self.coupling_nn.add_module('dense_block', NoNormDenseBlock(num_layers, in_channels, \n",
+    "                    growth_rate=growth_rate, drop_rate=0., bottleneck=False))\n",
+    "        self.coupling_nn.add_module('relu1', nn.ReLU(inplace=True))\n",
+    "        self.coupling_nn.add_module('zero_conv', Conv2dZeros(in_channels + growth_rate*num_layers, out_channels))\n",
+    "\n",
+    "        self.softsign = nn.Softsign()\n",
+    "\n",
+    "    def forward(self, x, cond):\n",
+    "        \"\"\"Forward pass\n",
+    "\n",
+    "        :param x:  [B, in_features, H, W] input feature tensor\n",
+    "        :type x: torch.Tensor\n",
+    "        :param cond: [B, cond_features, H, W] input feature tensor\n",
+    "        :type cond: torch.Tensor\n",
+    "        :returns: \n",
+    "            - y: [B, in_features, H, W] Output feature tensor\n",
+    "            - logdet: log determinate of affine layer\n",
+    "        :rtype: (torch.Tensor, torch.Tensor)\n",
+    "        \"\"\"\n",
+    "        #  Split in the channel dimension\n",
+    "        # last chunk is smaller if not odd number of channels\n",
+    "        x1, x2 = x.chunk(2, 1)\n",
+    "        h = self.coupling_nn(torch.cat((x1, cond), 1))\n",
+    "\n",
+    "        shift = h[:, 0::2]\n",
+    "        scale = (2*self.softsign(h[:, 1::2])).exp()\n",
+    "\n",
+    "        x2 = x2 + shift\n",
+    "        x2 = x2 * scale\n",
+    "        logdet = torch.abs(scale).log().view(x.shape[0], -1).sum(1)\n",
+    "\n",
+    "        return torch.cat((x1, x2), 1), logdet\n",
+    "\n",
+    "    def reverse(self, y, cond):\n",
+    "        \"\"\"Backward pass\n",
+    "\n",
+    "        :param y:  [B, in_features, H, W] input feature tensor\n",
+    "        :type y: torch.Tensor\n",
+    "        :param cond: [B, cond_features, H, W] input feature tensor\n",
+    "        :type cond: torch.Tensor\n",
+    "        :returns: \n",
+    "            - x: [B, in_features, H, W] Output feature tensor\n",
+    "            - logdet: log determinate of affine layer\n",
+    "        :rtype: (torch.Tensor, torch.Tensor)\n",
+    "        \"\"\"\n",
+    "        #  Split in the channel dimension\n",
+    "        y1, y2 = y.chunk(2, 1)\n",
+    "\n",
+    "        h = self.coupling_nn(torch.cat((y1, cond), 1))\n",
+    "\n",
+    "        shift = h[:, 0::2]\n",
+    "        scale = (2*self.softsign(h[:, 1::2])).exp()\n",
+    "\n",
+    "        y2 = y2 / scale\n",
+    "        y2 = y2 - shift\n",
+    "        logdet = torch.abs(scale).log().view(y.shape[0], -1).sum(1)\n",
+    "\n",
+    "        return torch.cat((y1, y2), 1), logdet\n",
+    "\n",
+    "class LSTMAffineCouplingLayer(nn.Module):\n",
+    "    \"\"\"Conditional LSTM invertable affine coupling layer.\n",
+    "    See Fig. 7 of paper: https://arxiv.org/abs/2006.04731\n",
+    "\n",
+    "    :param in_features: Number of input feature channels\n",
+    "    :type in_features: int\n",
+    "    :param cond_features: Number of conditional feature channels\n",
+    "    :type cond_features: int\n",
+    "    :param rec_features: Number of recurrent feature channels, \n",
+    "        output from :class:`nn.modules.convLSTM.ResidLSTMBlock`\n",
+    "    :type rec_features: int\n",
+    "\n",
+    "    :note: For more information see \"NICE: Non-linear Independent \n",
+    "        Components Estimation\" by Dihn et al. https://arxiv.org/abs/1410.8516\n",
+    "\n",
+    "    :note: Check Feistel cipher as this functions very similarly.\n",
+    "    \"\"\"\n",
+    "    def __init__(self, in_features, cond_features, rec_features):\n",
+    "        \"\"\"Constructor method\n",
+    "        \"\"\" \n",
+    "        super(LSTMAffineCouplingLayer, self).__init__()\n",
+    "        # assert in_features % 2 == 0, '# input features must be evenly split,'\\\n",
+    "        #     'but got {} features'.format(in_features)\n",
+    "        if in_features % 2 == 0:\n",
+    "            in_channels = in_features // 2 + cond_features\n",
+    "            out_channels = in_features\n",
+    "        else:\n",
+    "            # chunk is be (2, 1) if in_features==3\n",
+    "            in_channels = in_features // 2 + 1 + cond_features\n",
+    "            out_channels = in_features - 1\n",
+    "        \n",
+    "        # Initialize coupling network (Dense Block)\n",
+    "        num_layers = 2\n",
+    "        growth_rate = 1\n",
+    "\n",
+    "        # LSTM block\n",
+    "        self.resid_lstm = ResidLSTMBlock(in_channels, rec_features, in_channels, kernel_size=(3,3))\n",
+    "\n",
+    "        self.dense_nn = nn.Sequential()\n",
+    "        self.dense_nn.add_module('dense_block', NoNormDenseBlock(num_layers, in_channels,\n",
+    "                    growth_rate=growth_rate, drop_rate=0., bottleneck=False))\n",
+    "        self.dense_nn.add_module('relu1', nn.ReLU(inplace=True))\n",
+    "\n",
+    "        # Output convolution\n",
+    "        num_feat = in_channels + growth_rate*num_layers\n",
+    "        self.out_conv = nn.Sequential()\n",
+    "        self.out_conv.add_module('zero_conv', Conv2dZeros(num_feat, out_channels))\n",
+    "\n",
+    "        self.softsign = nn.Softsign()\n",
+    "\n",
+    "    def forward(self, x, cond, rec_states=None):\n",
+    "        \"\"\"Forward pass\n",
+    "\n",
+    "        :param x:  [B, in_features, H, W] input feature tensor\n",
+    "        :type x: torch.Tensor\n",
+    "        :param cond: [B, cond_features, H, W] input feature tensor\n",
+    "        :type cond: torch.Tensor\n",
+    "        :param rec_states: tuple of LSTM states (hidden state, cell state), defaults to None\n",
+    "        :type rec_states: tuple, optional\n",
+    "        :returns: \n",
+    "            - y: [B, in_features, H, W] Output feature tensor\n",
+    "            - logdet: log determinate of affine layer\n",
+    "            - states_out: tuple of LSTM (cell, hidden) states\n",
+    "        :rtype: (torch.Tensor, torch.Tensor, tuple)\n",
+    "        \"\"\"\n",
+    "        #  Split in the channel dimension\n",
+    "        x1, x2 = x.chunk(2, 1)\n",
+    "\n",
+    "        if(rec_states is None):\n",
+    "            out, h_next, c_next = self.resid_lstm(torch.cat((x1, cond), 1), None)\n",
+    "            # Store lstm states for next time-step and flow conditions\n",
+    "            states_out = (h_next, c_next)\n",
+    "        else:\n",
+    "            \n",
+    "            out, h_next, c_next = self.resid_lstm(torch.cat((x1, cond), 1), rec_states)\n",
+    "            # Store lstm states for next time-step and flow conditions\n",
+    "            states_out = (h_next, c_next)\n",
+    "\n",
+    "        out = self.dense_nn(out)\n",
+    "        h = self.out_conv(out)\n",
+    "        shift = h[:, 0::2]\n",
+    "        scale = (2*self.softsign(h[:, 1::2])).exp()\n",
+    "\n",
+    "        x2 = x2 + shift\n",
+    "        x2 = x2 * scale\n",
+    "        logdet = torch.abs(scale).log().view(x.shape[0], -1).sum(1)\n",
+    "\n",
+    "        return torch.cat((x1, x2), 1), logdet, states_out\n",
+    "\n",
+    "    def reverse(self, y, cond, rec_states=None):\n",
+    "        \"\"\"Backward pass\n",
+    "\n",
+    "        :param y:  [B, in_features, H, W] input feature tensor\n",
+    "        :type y: torch.Tensor\n",
+    "        :param cond: [B, in_features, H, W] input feature tensor\n",
+    "        :type cond: torch.Tensor\n",
+    "        :param rec_states: tuple of LSTM states (hidden state, cell state), defaults to None\n",
+    "        :type rec_states: tuple, optional\n",
+    "        :returns: \n",
+    "            - x: [B, in_features, H, W] Output feature tensor\n",
+    "            - logdet: log determinate of affine layer\n",
+    "            - states_out: tuple of LSTM (cell, hidden) states\n",
+    "        :rtype: (torch.Tensor, torch.Tensor, tuple)\n",
+    "        \"\"\"\n",
+    "        #  Split in the channel dimension\n",
+    "        y1, y2 = y.chunk(2, 1)\n",
+    "\n",
+    "        if(rec_states is None):\n",
+    "            out, h_next, c_next = self.resid_lstm(torch.cat((y1, cond), 1), None)\n",
+    "            # Store lstm states for next time-step and flow conditions\n",
+    "            states_out = (h_next, c_next)\n",
+    "        else:\n",
+    "            out, h_next, c_next = self.resid_lstm(torch.cat((y1, cond), 1), rec_states)\n",
+    "            # Store lstm states for next time-step and flow conditions\n",
+    "            states_out = (h_next, c_next)\n",
+    "\n",
+    "        out = self.dense_nn(out)\n",
+    "        h = self.out_conv(out)\n",
+    "        shift = h[:, 0::2]\n",
+    "        scale = (2*self.softsign(h[:, 1::2])).exp()\n",
+    "\n",
+    "        y2 = y2 / scale\n",
+    "        y2 = y2 - shift\n",
+    "        logdet = torch.abs(scale).log().view(y.shape[0], -1).sum(1)\n",
+    "\n",
+    "        return torch.cat((y1, y2), 1), logdet, states_out"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6973bdfa-d309-4393-b92d-c9ef813db89d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fce6f06f-a521-4931-85fe-deb8adc75f8b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "de6cd486-e1e9-40a6-b815-fdf4649ef320",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6428b79b-a778-4b3c-99be-b0ec7ce0139e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6832dd86-ffc7-4038-b363-b79b01091a9b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "999b8c76-3ae2-4e73-b5e4-17e1289fe47f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "75cee3fb-702b-4dc8-a21f-31a8a7d39e6c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fe76bbb2-2edc-431e-9178-cc8e162cfc84",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "55198e35-16a5-42bd-a1f9-d911dda1180a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1bb817db-cd51-4449-b099-ad92ec194ee0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ca64e8a1-d3ee-4764-aac6-d3f7fe910b6d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7468b5a3-c581-444c-8c80-8ee84ded01d1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4ee6a531-2a40-4957-8dfd-34cc075b1a0f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ad816c04-3a99-4444-bf88-0a5cc963437e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c603d91b-b4ba-4f20-9bfd-97e340a73ac8",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "51012147-d5bb-4ec9-b1d0-04a407520b74",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ad5a7aa7-d90b-40e5-a3d3-5952d244b0d5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9b921363-bbc8-4643-83c1-7729f70fe31b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "0253ef79-9c94-42fb-978e-483951bc005a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import torch.utils.data as data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "8400906f-dd9f-4082-aff6-5e853cb33158",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "class half_circle(data.Dataset):\n",
+    "    r'''Generate a dataset of points on a half circle.'''\n",
+    "    def __init__(self, n=512):\n",
+    "        super(half_circle, self).__init__()\n",
+    "        self.n = n\n",
+    "    \n",
+    "    def __getitem__(self, index):\n",
+    "        r = 1.0\n",
+    "        phi = torch.rand(1) * torch.pi\n",
+    "        x = torch.cos(phi) * r\n",
+    "        y = torch.sin(phi) * r\n",
+    "        return torch.cat((x, y), 0) + torch.randn(2) / 20\n",
+    "    \n",
+    "    def __len__(self):\n",
+    "        return self.n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "4c405101-4986-4cd2-8d93-0d2f9b725e78",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sampled = np.array([half_circle()[0].tolist() for i in range(500)])\n",
+    "plt.plot(sampled[:,0], sampled[:,1], '.')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "cf20b551-3f9b-4bbc-919d-8ff0903a015c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "trainingdata = data.DataLoader(half_circle(n=1000), batch_size=64)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "id": "e8e59d96-35f7-47a1-80e6-0a5448bd6b67",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "num_layers = 3\n",
+    "flows = []\n",
+    "for i in range(num_layers):\n",
+    "    # Neural network with two hidden layers having 32 units each\n",
+    "    # Last layer is initialized by zeros making training more stable\n",
+    "    param_map = nf.nets.MLP([1, 512, 512, 512, 2], init_zeros=True)\n",
+    "    # Add flow layer\n",
+    "    flows.append(nf.flows.AffineCouplingBlock(param_map))\n",
+    "    # Swap dimensions\n",
+    "    flows.append(nf.flows.Permute(num_layers, mode='swap'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "id": "4f46f8e2-9d3d-4e0a-a24b-f5fee3a2b8a6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "target_dist = nf.distributions.DiagGaussian(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "id": "3b295a3e-4130-404e-b59d-7ac86844ca5e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "model = nf.NormalizingFlow(target_dist, flows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "id": "c4c2a1bf-7ef2-4bd3-917a-9b69a4764874",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001b[0;31mSignature:\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mforward_and_log_det\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mz\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+       "\u001b[0;31mDocstring:\u001b[0m\n",
+       "Transforms latent variable z to the flow variable x and\n",
+       "computes log determinant of the Jacobian\n",
+       "\n",
+       "Args:\n",
+       "  z: Batch in the latent space\n",
+       "\n",
+       "Returns:\n",
+       "  Batch in the space of the target distribution,\n",
+       "  log determinant of the Jacobian\n",
+       "\u001b[0;31mFile:\u001b[0m      /data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/core.py\n",
+       "\u001b[0;31mType:\u001b[0m      method"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model.forward_and_log_det?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "id": "e3c45c32-459e-4528-b89f-c6d4231095fc",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "model.train()\n",
+    "optimizer = optim.Adam(model.parameters(), lr=0.001)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "id": "0555b9e6-06e0-40cd-a856-c7144eaef066",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001b[0;31mSignature:\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mforward_and_log_det\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mz\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+       "\u001b[0;31mDocstring:\u001b[0m\n",
+       "Transforms latent variable z to the flow variable x and\n",
+       "computes log determinant of the Jacobian\n",
+       "\n",
+       "Args:\n",
+       "  z: Batch in the latent space\n",
+       "\n",
+       "Returns:\n",
+       "  Batch in the space of the target distribution,\n",
+       "  log determinant of the Jacobian\n",
+       "\u001b[0;31mFile:\u001b[0m      /data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/core.py\n",
+       "\u001b[0;31mType:\u001b[0m      method"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model.forward_and_log_det?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "id": "53d1935b-9101-4192-8ebf-8aeca534a795",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "not enough values to unpack (expected 2, got 1)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[86], line 6\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m trainingdata:\n\u001b[1;32m      5\u001b[0m     optimizer\u001b[38;5;241m.\u001b[39mzero_grad()\n\u001b[0;32m----> 6\u001b[0m     loss \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mforward_and_log_det\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      7\u001b[0m     py \u001b[38;5;241m=\u001b[39m base\u001b[38;5;241m.\u001b[39mlogp(y)\n\u001b[1;32m      8\u001b[0m     \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/core.py:53\u001b[0m, in \u001b[0;36mNormalizingFlow.forward_and_log_det\u001b[0;34m(self, z)\u001b[0m\n\u001b[1;32m     51\u001b[0m log_det \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mzeros(\u001b[38;5;28mlen\u001b[39m(z), device\u001b[38;5;241m=\u001b[39mz\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[1;32m     52\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m flow \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mflows:\n\u001b[0;32m---> 53\u001b[0m     z, log_d \u001b[38;5;241m=\u001b[39m \u001b[43mflow\u001b[49m\u001b[43m(\u001b[49m\u001b[43mz\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     54\u001b[0m     log_det \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m log_d\n\u001b[1;32m     55\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m z, log_det\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/torch/nn/modules/module.py:1110\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1106\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1107\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1108\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1109\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1110\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1111\u001b[0m \u001b[38;5;66;03m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1112\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[38;5;241m=\u001b[39m [], []\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/flows/affine/coupling.py:258\u001b[0m, in \u001b[0;36mAffineCouplingBlock.forward\u001b[0;34m(self, z)\u001b[0m\n\u001b[1;32m    256\u001b[0m log_det_tot \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mzeros(z\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m], dtype\u001b[38;5;241m=\u001b[39mz\u001b[38;5;241m.\u001b[39mdtype, device\u001b[38;5;241m=\u001b[39mz\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[1;32m    257\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m flow \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mflows:\n\u001b[0;32m--> 258\u001b[0m     z, log_det \u001b[38;5;241m=\u001b[39m \u001b[43mflow\u001b[49m\u001b[43m(\u001b[49m\u001b[43mz\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    259\u001b[0m     log_det_tot \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m log_det\n\u001b[1;32m    260\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m z, log_det_tot\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/torch/nn/modules/module.py:1110\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1106\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1107\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1108\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1109\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1110\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1111\u001b[0m \u001b[38;5;66;03m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1112\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[38;5;241m=\u001b[39m [], []\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/flows/reshape.py:32\u001b[0m, in \u001b[0;36mSplit.forward\u001b[0;34m(self, z)\u001b[0m\n\u001b[1;32m     30\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, z):\n\u001b[1;32m     31\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mchannel\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m---> 32\u001b[0m         z1, z2 \u001b[38;5;241m=\u001b[39m z\u001b[38;5;241m.\u001b[39mchunk(\u001b[38;5;241m2\u001b[39m, dim\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m     33\u001b[0m     \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mchannel_inv\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m     34\u001b[0m         z2, z1 \u001b[38;5;241m=\u001b[39m z\u001b[38;5;241m.\u001b[39mchunk(\u001b[38;5;241m2\u001b[39m, dim\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n",
+      "\u001b[0;31mValueError\u001b[0m: not enough values to unpack (expected 2, got 1)"
+     ]
+    }
+   ],
+   "source": [
+    "loss_count = []\n",
+    "for i in range(50):\n",
+    "    losses = []\n",
+    "    for x in trainingdata:\n",
+    "        optimizer.zero_grad()\n",
+    "        loss = model.forward_and_log_det(x)\n",
+    "        py = base.logp(y)\n",
+    "        assert False\n",
+    "\n",
+    "        loss = py + logp + logdet\n",
+    "        loss = -1 * loss.mean()\n",
+    "\n",
+    "        loss.backward()\n",
+    "        losses.append(loss.item())\n",
+    "        optimizer.step()\n",
+    "    loss_count.append(np.mean(losses))\n",
+    "    print(sum(losses) / len(losses))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d3339f1b-d3bf-40ce-8825-d9ceb80f8542",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1656f2b6-8acd-4c7b-bf6b-9b596cf07ff5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d8f4d195-8a99-4ee7-a648-506018a150d4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8d226046-c1e2-445a-bc36-98f61bbac181",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7507f3cb-3c2a-4d7e-9e33-d7965b67ffdf",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "991b0666-adb7-4b7b-980e-b8d60a5e37b8",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "32996f4d-306d-4d31-9d0c-4e48627c7ad3",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "836104f1-2292-4763-9d8b-1732b795d282",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ec3bae50-c50f-422f-bbbd-3352e6f936bb",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "44058b41-a029-4e79-9296-cc6e48194875",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b51df608-ffc0-4bdb-b5b8-23e251dd5d8d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8592de8d-8193-40b0-9a22-08604c62ea64",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bdc6142c-8aa1-48e0-86ee-c071059d65b2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ab60eaab-aaa6-4a6f-b88f-6386e00f8645",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0f677f7a-fd14-498b-b2ad-6d9cedab738f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "20e79083-de5b-4cf5-8cc4-24631a14eed0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "52fc78d9-128d-4b24-9f52-afcdf37e70f1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c3c0ee0e-ac5d-4757-8649-42e097d25a18",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "40fde33d-ddb1-4826-b3b6-82cace651a18",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f9067503-79c3-4c44-8cac-22c189e09530",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "46bf40bb-bb8b-4985-9183-c14ed1b0bc51",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "07649d64-454d-4bcc-b16d-b2c186714f52",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "Nclass = 10000\n",
+    "xs = np.random.uniform(0,10,Nclass)\n",
+    "Nsamp = 10\n",
+    "\n",
+    "training_sample = torch.zeros(size =(Nclass, Nsamp))\n",
+    "label = torch.zeros(size =(Nclass, 2))\n",
+    "\n",
+    "for ii,x in enumerate(xs):\n",
+    "    xsamp = 0.1*torch.randn(1,Nsamp)+x\n",
+    "    training_sample[ii] = xsamp\n",
+    "    label[ii] = x\n",
+    "    \n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "984f79ba-2dfe-441b-8d88-47f945f77b97",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(label.detach().cpu().numpy().flatten(), bins=70, histtype='step')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "0080e555-1229-4e48-a61e-c775eb14f90b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "target_dist = nf.distributions.DiagGaussian(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "404782ea-421d-4d7e-958e-cb8459c606fd",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "94bd489e-1920-4a89-8d8b-72b27abd5c99",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "263bb1a9-f68b-4846-b64f-34c97299fd6a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "4b8bc8a8-dec9-46a9-b246-6ab39bde2a6a",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "RuntimeError",
+     "evalue": "The size of tensor a (2) must match the size of tensor b (8) at non-singleton dimension 1",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[38], line 9\u001b[0m\n\u001b[1;32m      6\u001b[0m zz \u001b[38;5;241m=\u001b[39m zz\u001b[38;5;241m.\u001b[39mto(device)\n\u001b[1;32m      7\u001b[0m context_plot \u001b[38;5;241m=\u001b[39m training_sample\u001b[38;5;241m.\u001b[39mclone()\u001b[38;5;241m.\u001b[39mto(device)\n\u001b[0;32m----> 9\u001b[0m logp \u001b[38;5;241m=\u001b[39m \u001b[43mtarget\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog_prob\u001b[49m\u001b[43m(\u001b[49m\u001b[43mzz\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcontext_plot\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m     11\u001b[0m p_target \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mexp(logp)\u001b[38;5;241m.\u001b[39mview(\u001b[38;5;241m*\u001b[39mxx\u001b[38;5;241m.\u001b[39mshape)\u001b[38;5;241m.\u001b[39mcpu()\u001b[38;5;241m.\u001b[39mdata\u001b[38;5;241m.\u001b[39mnumpy()\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/distributions/target.py:211\u001b[0m, in \u001b[0;36mConditionalDiagGaussian.log_prob\u001b[0;34m(self, z, context)\u001b[0m\n\u001b[1;32m    208\u001b[0m loc \u001b[38;5;241m=\u001b[39m context[:, :d]\n\u001b[1;32m    209\u001b[0m scale \u001b[38;5;241m=\u001b[39m context[:, d:]\n\u001b[1;32m    210\u001b[0m log_p \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m0.5\u001b[39m \u001b[38;5;241m*\u001b[39m d \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mlog(\u001b[38;5;241m2\u001b[39m \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mpi) \u001b[38;5;241m-\u001b[39m torch\u001b[38;5;241m.\u001b[39msum(\n\u001b[0;32m--> 211\u001b[0m     torch\u001b[38;5;241m.\u001b[39mlog(scale) \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m0.5\u001b[39m \u001b[38;5;241m*\u001b[39m torch\u001b[38;5;241m.\u001b[39mpow(\u001b[43m(\u001b[49m\u001b[43mz\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mloc\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mscale\u001b[49m, \u001b[38;5;241m2\u001b[39m),\n\u001b[1;32m    212\u001b[0m     dim\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m    213\u001b[0m )\n\u001b[1;32m    214\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m log_p\n",
+      "\u001b[0;31mRuntimeError\u001b[0m: The size of tensor a (2) must match the size of tensor b (8) at non-singleton dimension 1"
+     ]
+    }
+   ],
+   "source": [
+    "# Define target\n",
+    "target = nf.distributions.target.ConditionalDiagGaussian()\n",
+    "context_size = 10\n",
+    "\n",
+    "zz = label.clone()\n",
+    "zz = zz.to(device)\n",
+    "context_plot = training_sample.clone().to(device)\n",
+    "\n",
+    "logp = target.log_prob(zz, context_plot)\n",
+    "assert False\n",
+    "p_target = torch.exp(logp).view(*xx.shape).cpu().data.numpy()\n",
+    "\n",
+    "plt.figure(figsize=(10, 10))\n",
+    "plt.pcolormesh(xx, yy, p_target, shading='auto')\n",
+    "plt.gca().set_aspect('equal', 'box')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5e9f8afc-bb50-4d1d-ba81-b7bb1a7eb65a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "853545b2-6959-48ea-b06f-9d2b17e3241f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "239b34ab-a6cc-4f4c-a52a-785734e34e37",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2750ffd7-ad77-4ad3-8e33-91a8123396df",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "939902b6-2139-4135-a096-a7ec467b5a2d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e881e7a5-d9e8-4d9c-bda2-13686ad3b355",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "92eef5bb-58f9-4576-9f64-d7a353faedd1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Train model\n",
+    "max_iter = 5000\n",
+    "batch_size= 128\n",
+    "\n",
+    "loss_hist = np.array([])\n",
+    "\n",
+    "optimizer = torch.optim.Adam(model.parameters(), lr=3e-4, weight_decay=1e-5)\n",
+    "\n",
+    "\n",
+    "for it in tqdm(range(max_iter)):\n",
+    "    optimizer.zero_grad()\n",
+    "    \n",
+    "    # Get training samples\n",
+    "    context = torch.cat([torch.randn((batch_size, 2), device=device), \n",
+    "                         0.5 + 0.5 * torch.rand((batch_size, 2), device=device)], \n",
+    "                        dim=-1)\n",
+    "    x = target.sample(batch_size, context)\n",
+    "    \n",
+    "    # Compute loss\n",
+    "    loss = model.forward_kld(x, context)\n",
+    "    \n",
+    "    # Do backprop and optimizer step\n",
+    "    if ~(torch.isnan(loss) | torch.isinf(loss)):\n",
+    "        loss.backward()\n",
+    "        optimizer.step()\n",
+    "    \n",
+    "    # Log loss\n",
+    "    loss_hist = np.append(loss_hist, loss.to('cpu').data.numpy())\n",
+    "\n",
+    "# Plot loss\n",
+    "plt.figure(figsize=(10, 10))\n",
+    "plt.plot(loss_hist, label='loss')\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fb1da951-7138-4430-8e43-be6d05f081bc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "02958ed6-af14-4852-8ce5-b3a5dd39b2a4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a97d9536-6799-4c07-b1bf-aca726fc2444",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04a8c5cf-0214-44bd-b2e9-e2b1f175832e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8425b39e-5da4-4cfc-9489-4214fa7f2d66",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "507e7bdc-0b76-4fca-ac8e-3941dfd43ba4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a593ae69-f864-4a8e-9267-f898b270dd0b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "df5efae5-fc12-4d6c-b002-e3c7e47e6b0b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8fdd9f17-8612-47da-9826-3821571beafb",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c5ac02ae-f001-42d1-948b-4d9c17608a94",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4702da6e-b812-4b7a-b980-abae76954942",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5a913832-5607-4eb1-8b65-865f97314614",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c57e6e7e-cc49-403b-89cd-8e99db8c85ff",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e99a2c9f-9f38-486f-95ca-a990aed4a73f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a298715c-37bd-4ff0-b91f-8b537a05d99e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f079bb6b-60f3-4937-8e41-a1397bec8f31",
+   "metadata": {},
+   "source": [
+    "## CREATE DATA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "id": "6cd06efc-dd3f-4c15-a801-bab90305480e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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qGt0/pVAJUQzHYfVY/POf/9S//uu/6uDBg+rRo4cuvPBCrV69Wvn5+ZGqD0AH0WtAptIyXXExHNK9T5qm3jOangqcIp7mWHRLS9Jv/6Uo6s8LCStYvPLKK5GqA0AH53Q6dPH1A2LqoWOtufbuUYQKtCie5ljcd+UQHkIGoGPrPzxbV/x7kdIyY3tYZOeG6O9WiPgwuqCrenmSFQ+xs6cnxUi7BAsAUdV/eLb+x8Nj9YM7h2vg6BzT5bSI3TbRmgSnQ/dPKTRdxmn1ivKEzZMRLABEndPpUO9BWeo71Mw/fKfDbptoyxVFvfSHHw2XI0a7LRyK/oTNkxEsABiTnhm749XxujwW0ZGV5pIVg51aDkm3XlJgZG5FI4IFAGMaV4rEonhbHovoiuXVIXNXVkT9wWMnI1gAMKZxpUisYbdNnE6srg5p7ESJ9oPHTkawAGBU40oRV+oZbQRsK3bbxOnE8uoQS9F/8NjJCBYAjOs/PFvfu7XIdBlKz3Kx2yZCcvLqkGiGC3dygorH9w/pWlPDNbHzKwKATq33wKzT7szpTHAoGLCvezc9y6XCcbny5KQozX1i+IOeCoTqiqJeeurG8/Xg4k3NHqV+umeJOBzSzWPP0nMf7gi7zf+67lx5UpL0h/e2nfZaU8M1BAsAMSGUnTkvnzFUy1/6h/x1De1uZ/RVBQQJ2OaKol66vLCnPqk4rP01x5SdkawjdX4Vv7Re0jdzHk72h38drsnDcjW6oOspoaQtT/5ouK4o6qVA0FIvT7L2eo+1+PkmHjzWrH3Liu6CGZ/PJ4/HI6/XK7fbHc2mAcSBbev36/1XtzTruUjPcumiaQPUf3i2tq3ff9ptwV1piZIl+eu/CSAnfwYQaaXle04JDb08ybp/SmGzpaCBoKVPKg5r2aa9eraNHownf3S+Jg/75n2l5Xv00wXrJDUPL40x+akbz7d9yWmo92+CBYCYEwxa2rOlWnU+f4s9Cy2Fj+T0Lhp4QY76DevRtKKjrc8AIq0xNDT2ZIwu6NrmplWl5Xv0wKJN2utrO4ycfH0o4cUuBAsAHdrpwgcQj8INI+FefyZCvX8zxwJAXGrcFhzoSBKcDo3p3y1i10cDy00BAIBtCBYAAMA2BAsAAGAb5lhACgaknatkefeofqdPDc4cJWbnKHXkCDkSEkxXBwCIIwSLzm7TIql0tnwbD2vfOo8ajn4TJBJ79lTOPXPknjjRYIEAgHjCUEgnZQUCqlv4v+X93a06sMqnqg+z1HC0+V+Hhr17VTXzDvneecdQlQCAeEOPRSdiBQKqX7NWNX9bJu8bf1HQVyepcbmepdYepbP3gQcVPOZXlxyGRwAAbSNYdAJWIKCDTz+twy+8qKDX28pVrWyoYlkKHD6sPb/6lSQpMSdHmVOvU1KaX4kpQaWOHC1Hv4skJ2EDAMDOmx2er7RUe+77TwVrayPy+YkpAeVc2CD39f8uXXIXAQMAOqhQ79/MsejA9v3ud6q6486IhQpJajjqVNV7SfK9+Jj0u/4nJoMCADotgkUH5S0t1eFnn4tCSyeGUPatd8uqOyIt/DHhAgA6MYJFB2QFAtr74ENRbNGhhvpE1R9IOvFyyewTe2MAADodJm92BF9vcKXafVJ6jur2OBU8ciTqZfj+mSxJSg3ulmPl/5K+MzvqNQAAzCJYxLuvN7iSb7ckyVeZrN0fZ6nVVR4RVL0lXdVb0k9M6Kx6TO7sIVLh1VGvAwBgDkMh8WzTImnh/5B8u2UFpQPl6ar6MEtWg9myGo46VfVhlnxPMSQCAJ0NwSJeBQMneipkyVeZrK2Lc3Sw3K0TPRXR761o7usJnR82yNr+geFaAADRRLCIVztXSb7d8lUmt7gdt3lfT+hc84npQgAAURRrdyOEqnafrKC0b53n6xOmeylaFnuBBwAQSUzejFfpOao/kNTsaaSxKHHIWNMlAACiiF8n41X+WDWou+kq2uRMcSl11GjTZQAAouiMgkVJSYkcDofuuOMOm8pBqHzL/qa9a1JNl9GmpPxcOTa9LlW8z+oQAOgk2j0UUlZWprlz52rYsGF21oMQ+N55R1W/mKm2HnUeC479Y7v2/ecdyjmvRnLnSlc8yr4WANDBtavHora2VjfccIPmzZunrKwsu2tCG6xAQPse/J+K9VDR6PA/0hVskOTbc2LPDZ4jAgAdWruCRXFxsa688kpNmDDhtNf6/X75fL5mB9qvvuwTNRzyKh5CReOeGke2pulEEJJUejfDIgDQgYUdLF555RWtW7dOJSUlIV1fUlIij8fTdOTl5YVdJL7RsHmV6RLCdryuceWKJfmqTuzBAQDokMIKFpWVlZo5c6YWLFig5OTkkN4zZ84ceb3epqOysrJdheKExJSg6RLClpT2rR6K2n1mCgEARFxYkzfXrl2r/fv3a8SIEU3nAoGAVq5cqSeeeEJ+v18JCc33VXC5XHK5XPZUC6WOHC1H4jxZDbG9f8UJJ4Y/ss6ua346PcdALQCAaAgrWFx22WXasGFDs3M333yzBg8erNmzZ58SKmA/R7+L5BlgqXqz6UpC03VwrZwn/y1z95by2TQLADqqsIJFRkaGioqKmp1LS0tTt27dTjmPCHEmyH39T1X9wDzTlZxWRt7RE0tNmzikKx6RnARQAOio2HkzDqVOnanEzBQ1rbSIQY7EgHqPqf7mREpXadoL7GMBAB3cGT8rZPny5TaUgXA4EhKU89AjMbxJlqVeo71yNMbWoddI1/6RngoA6ATosYhT7okT1fu+25SQHHurRNLzjsrT95iU2l2a+rw0dT6hAgA6CZ5uGsfcP/q5MvY+rQMf+XRoY8bXZ833XmROvkz6wc0nJmkSKACgU6HHIp45E+SY/Kiyz6lT18G1pqtpctRxrlRwMaECADohgkW8K7xamvaCcsa6lDv2iJTAdtkAAHMIFh1B4dXSrM3yDE7T4Gv3KaXHMaPlpF4w2mj7AABzCBYdRWKSdNXjcjgdyh9/RM6kgEwsR03IzFTaaIIFAHRWBIuO5OthEUdmL/Ua5f36ZHTDRc+HHpSDHVgBoNNiVUhHU3i1NPhKuXeukv72d+15ZpGCNfURbzaxZ0/l3DNH7okTI94WACB2OSzLiuqvtD6fTx6PR16vV263O5pNd0pWIKCDTz+jwy+8oKDXe/JPFP7S1ObvcSZb8ky4WBlT/02pI0fQUwEAHVio92+CRSdhBQKqX7NWDQcO6Piapape9I4a6k8KCV0C6jqwTpbUxp4YljLyjiqjj1+JF16v1Bm/k6NLUrS+AgDAIIIF2mR9dVz1z/1KDesWKdFZo9Qex09swZ3aXT7rIu1bvEUNB480XZ/gCqjnCK/cRd1OPEiMZ34AQKdCsEBoggFp5yqpdp+UntO0W2ZTD8f+fUoM7lNqvlsOTy920wSATirU+zeTNzs7Z8KJXTK/xZGQoDT2owAAhInlpgAAwDYECwAAYBuCBQAAsA3BAgAA2IbJmwAAGGQFLfkrvArWHJczI0muAo8cznA3MIwdBAsAAAw5Wn5Q1Yu3KeA93nQuwZOkzCn9lVLU3WBl7UewAADAgKPlB3VoweZTzge8x3VowWaljctV8uCucjikYO1XcdObQbAAACCCWhrqkKTqxdvafF/dh7tV9+HuZufioTeDYAEAQIS0NNThdCfJdXZms3OhauzNyJjQV+7v9o3J3guCBQAAEdDaUEfQd1xH1+0/o8+uWbZLdZ/sUdbVZ8dc7wXBAgCAM9DeoY4zFfR9pUMLNit9XK6SC7vFzPwLggUAAO1gBS35/r5LtR/ulnW0oen8mQx1tEfth7tV++HumJl/QbAAACBMR8sP6shftihY33DKz+wY6miPxvkX3W4cYjRcsPMmAABhaJw70VKoiAXVi7fLClrG2idYAAAQIitoRXzuxJkKeP3yV3iNtU+wAAAgRP4Kb9TmTpyJYI25GgkWAACEyOQNOxzOjCRzbRtrGQCAOGPyhh2qBM83S15NIFgAABCipHy3ZH6riDYl5buN7mdBsAAAIETHd3glcwsuQnJsy5H4WRXy1FNPadiwYXK73XK73RozZoyWLFkSqdoAAIgp/m3mVluEyjoa0KFX/mGs/bCCRZ8+ffTII49ozZo1WrNmjb773e/q+9//vjZu3Bip+gAAQJiOfX5Q1W9vN9J2WMFiypQpmjx5sgYOHKiBAwfqt7/9rdLT07V69epI1QcAQMzocpbbdAkhq32/SsGGYNTbbfeW3oFAQH/+859VV1enMWPGtHqd3++X3+9veu3z+drbJAAAxhwtP6jqRbG9OVYzllT70W65L+4T1WbDDhYbNmzQmDFjdOzYMaWnp+v1119XYWFhq9eXlJTowQcfPKMiAQAwqbVHoMe6hkNHo95m2KtCBg0apE8//VSrV6/WT3/6U02fPl2bNm1q9fo5c+bI6/U2HZWVlWdUMAAA0RQP23i3xrKivzok7B6LpKQknX322ZKkkSNHqqysTP/93/+tZ555psXrXS6XXC7XmVUJAIAh8bKNd0ucyV2i3+aZfoBlWc3mUAAA0JHEyzbeLQl6o39/DqvH4p577tGkSZOUl5enmpoavfLKK1q+fLlKS0sjVR8AAEbFwzberUnIjP6IQVjBYt++ffrxj3+sPXv2yOPxaNiwYSotLdXll18eqfoAADDKVeBRgicpLodDXP0zo95mWMHi2WefjVQdAADEJIfTocwp/eNuVYgzNVHJBoIFzwoBAOA0Uoq6q9uNQ5TgiZ9hkaxrBhh5GFm7N8gCAKAzSSnqruTCbvJXeBWsOa6vfH7VvL3DdFmncLqTlHV1f6UUdTfSPsECAIAQOZyOpuGFWNrbokvfDGWMzZUzI0muAo/Rx6YTLAAACNPR8oOq/XC36TKaeL53lpH5FC1hjgUAAGGIxZ04j206ZLqEJgQLAADCEIs7cdZ/ekBWMPrbd7eEYAEAQBhC3YkzaVBmZAs5SbDuK/krvFFrry0ECwAAwhDqTpzuS/LU7cYhcrqjs0Q1VrYeZ/ImAABhCGUnzgSPq2l1RnJhN9X8fZd8y3ZFtK5Y2XqcHgsAAMLQuBNnWzKn9Gta8ulwOuSekP9170XoTxt1T+irrj8cpO63FJ32fY1BJhbQYwEAQJgad+KsXrytWc9FgselzCn9Wtyc6tsbbDkzkhSs+0rVb25T0PdV03UtbXCVdfXZbW4pfnKQMc1hWVZUp5H6fD55PB55vV653e5oNg0AgK2soNUsKLRnc6pQP+No+cGwgozdQr1/02MBAEA7nbwTZ6Q/o6UeD9O7bLaEYAEAQJywI8hEGpM3AQCAbQgWAADANgQLAABgG4IFAACwDcECAADYhmABAABsQ7AAAAC2IVgAAADbECwAAIBtCBYAAMA2BAsAAGAbggUAALANwQIAANiGYAEAAGxDsAAAALYhWAAAANsQLAAAgG0IFgAAwDYECwAAYJuwgkVJSYlGjRqljIwMZWdn6wc/+IG++OKLSNUGAADiTFjBYsWKFSouLtbq1av17rvvqqGhQRMnTlRdXV2k6gMAAHHEYVmW1d43HzhwQNnZ2VqxYoUuueSSkN7j8/nk8Xjk9Xrldrvb2zQAAIiiUO/fiWfSiNfrlSR17dq11Wv8fr/8fn+zwgAAQMfU7smblmVp1qxZuuiii1RUVNTqdSUlJfJ4PE1HXl5ee5sEAAAxrt1DIcXFxXrrrbf0wQcfqE+fPq1e11KPRV5eHkMhAADEkYgOhdx+++1atGiRVq5c2WaokCSXyyWXy9WeZgAAQJwJK1hYlqXbb79dr7/+upYvX66CgoJI1QUAAOJQWMGiuLhYL730kv76178qIyNDe/fulSR5PB6lpKREpEAAABA/wppj4XA4Wjw/f/583XTTTSF9BstNAQCIPxGZY3EGW14AAIBOgGeFAAAA2xAsAACAbQgWAADANgQLAABgG4IFAACwDcECAADYhmABAABsQ7AAAAC2IVgAAADbECwAAIBtCBYAAMA2BAsAAGAbggUAALANwQIAANiGYAEAAGxDsAAAALYhWAAAANsQLAAAgG0IFgAAwDYECwAAYBuCBQAAsA3BAgAA2IZgAQAAbEOwAAAAtiFYAAAA2xAsAACAbQgWAADANgQLAABgG4IFAACwDcECAADYhmABAABsQ7AAAAC2IVgAAADbhB0sVq5cqSlTpig3N1cOh0NvvPFGBMoCAADxKOxgUVdXp3PPPVdPPPFEJOoBAABxLDHcN0yaNEmTJk2KRC0AACDOhR0swuX3++X3+5te+3y+SDcJAAAMifjkzZKSEnk8nqYjLy8v0k0CAABDIh4s5syZI6/X23RUVlZGukkAAGBIxIdCXC6XXC5XpJsBAAAxgH0sAACAbcLusaitrdXWrVubXldUVOjTTz9V165d1bdvX1uLAwAA8SXsYLFmzRqNHz++6fWsWbMkSdOnT9ef/vQn2woDAADxJ+xg8Z3vfEeWZUWiFgAAEOeYYwEAAGxDsAAAALYhWAAAANsQLAAAgG0IFgAAwDYECwAAYBuCBQAAsA3BAgAA2IZgAQAAbEOwAAAAtiFYAAAA2xAsAACAbQgWAADANgQLAABgG4IFAACwDcECAADYhmABAABsQ7AAAAC2IVgAAADbJJouwIRgMKCqzRtVW31E6ZlZ6j1kqJzOhDO+FgCAzq7TBYstH6/S3/80V7WHDzadS+/aXd+96VYNuGBsu68FEFmBYEDr9q/TgfoD6pHaQ+dnn6+EEEJ+e98HoH0clmVZ0WzQ5/PJ4/HI6/XK7XZHs2lt+XiVFj32cKs/v3rWPRpwwVgFgwF9/JeFWvXn/9vqtRdec728B/br+LGj6j2oUMMnXaXExKRIlA10est2LtMjnzyiffX7ms5lubJ0Vb+rNL7v+FbDQkvvy0nN0d2j79aE/AlRqR3oKEK9f3eaYNHQcFxzf3qTjvp8rV6T3rWbvjP937T8+XmqPXwovAYcDo286l906Y0zGD4BbPTOjnf0Hyv+o81r0rqkaWyvsbp+8PUamTNSkjRvwzz94dM/nHKtQw5J0mPfeYxwAYSBYHGSLR+v0jvzntCxmtZDhV36j7xA+7ZvY/gEsME7O97RL1f+UkErGPJ7nF/PSQ+q7fdkubL0q1G/UveU7nI4HDp09BBDJUAbCBZfO93wRzQ1DrUAOL1lO5fpzuV3Rr1dhkqAloV6/+7Qy02DwYD+/qe5psto8t7zcxUMBkyXAcSsQDCgsr1lenPbm3roo4eM1LCvfp9mLZ+lZTuXGWkfiHcdelVI1eaNzYYkTKs5dFBVmzcqb+gw06UAMaNx1cZ7u97Tm9vf1BH/EdMlyZKlRz95VOPzxjMsAoSpQweL2mrz/0B9WyzWBJjS0qqNWLG3fq/W7V+nUT1HmS4FiCsdJli0tBKjek+V6bJOkerxmC4BiAnLdi7TrOWzZCmq07zCcqD+gOkSgLjTIYJFyxtZdVPDcb/BqloRu/+GAlETCAb0yCePxHSokKQeqT1MlwDEnbgPFq2t+gh7H4ooqfd5TZcAGLdu/7qYHP44WZYrS+dnn2+6DCDuxPWqkFhb9RGKbWWrTZcAGBcPQwz3XXgfEzeBdojrYBFrqz5C8cVH7+vLjz4wXQZgVKwPMVzc+2JNPGui6TKAuNSuYPHkk0+qoKBAycnJGjFihN5//3276wrJ1jUfG2n3TC177kn2s0Cndm73c+V0xO7vNcO6syQcaK+w/89+9dVXdccdd+jee+/V+vXrdfHFF2vSpEnatWtXJOprVTAY0Kb334tqm3Y56vOpavNG02UAxnx28LOwtumOthfKX1CA8A+0S9jB4rHHHtNPfvIT3XLLLRoyZIgef/xx5eXl6amnnopEfa2q2rwxKs/+iBT2s0BnFutzLGoCNXrm82dMlwHEpbCCxfHjx7V27VpNnNh87HHixIlatWpVi+/x+/3y+XzNDjvE+405PTPLdAmAMbt80e3hbI+nPnuKbb2BdggrWBw8eFCBQEA5OTnNzufk5Gjv3r0tvqekpEQej6fpyMvLa3+1J4nnG3NGt+7qPWSo6TIAI5btXKY/fHbq48xj0aOfPMqQCBCmds2ecjgczV5blnXKuUZz5syR1+ttOiorK9vT5Cl6Dxmq9K7dbfmsaBs//VY5WcaGTqhxY6x40bitN4DQhRUsunfvroSEhFN6J/bv339KL0Yjl8slt9vd7LCD05mg7950qy2fFU0DLhjHo9PRacXDxljftnrPar29/W2V7S2j9wIIQVjBIikpSSNGjNC7777b7Py7776rsWOjf7MccMFYXT3rnrjquTj38kmmSwCMifVJmy2Z+/lczX5/tmYsnaHv/b/vMe8COI2wh0JmzZqlP/7xj3ruuee0efNm3Xnnndq1a5duu+22SNR3WgMuGKt/+8Ozuu6+3yg5Pd1IDaHq4kpW3tBzTJcBGBPrG2Odzv76/Zq1fBbhAmhD2MHi+uuv1+OPP66HHnpI5513nlauXKm3335b+fn5kagvJE5ngvLPOU8Tb/2FsRpCMfDCccytQKd2fvb5ykltedg0HjQ+NI1JnUDr2jV582c/+5l27Nghv9+vtWvX6pJLLrG7rnZpHBpJSo3Nnou+55xnugTAqARngu4efbccanmydzywZDGpE2hD7O6p204DLhirq//jbtNltCijazfTJQDGTcifoMe+85g8Lo/pUs5IPM4XAaKhwwULScorPEeutAzTZTSTnJ7B3hXA1ybkT9CKaStUfG6x3En2rBSLtnifLwJESocMFk5ngkZMvtp0Gc2cP+lq5lcAJ0lwJui2827TyutX6rnvPaepA6aaLikkDjnUM7Wnzs8+33QpQEzqkMFCki64ZpqS02Oj16JLcoouuGaa6TKAmJTgTNConqM0qV/8LMWePXq2EvhFAWhRhw0WTmeCJt56u+kyJEmjpvwLvRXAacTDihGPy6PHvvOYJuRPMF0KELM6bLCQTkzkvOrOu+VwmPuaXVzJuuCa6421D8SLeFgx8vtLf0+oAE6jQwcLSRp04UW6auavjLU/6upr6a0AQtS4YsREz0WWK6vVUNM4r2JkzsgoVwXEnw4fLCRp4JiLdPWse6I+5yI5w83cCiBME/InaOm1S/Xc957Tj4f8WFmuyD7JuDE03HfhfU2vv/1ziXkVQKgclmVZ0WzQ5/PJ4/HI6/Xa9kCyUAWDAVVu3KBd5Z+r5tABfeX3q2pzuY7W+CLS3tWz7uGBY8AZCgQDWrd/nf6282967cvX5A/6T/uetMQ01TXUNb3OdGWq2l8thxxNu2dK34SGxnkTy3Yu0yOfPNLsQWk9U3tq9ujZDIGg0wv1/t2pgkVLgsGAqjZvVG31ER3Z/U999NrLIb0vKSVVgYYGBb46fsrPMrp11/jptxIqAJsFggGV7S1T2b4yVVRXaM2+NTriP9L088YQMD5vvNbtX6cD9QfUI7WHzs8+X+9VvhdSaGgMMie/l54KgGDRbls+XqV35v4fHautaXY+OT1D50+aosxevZWemdW02VXV5o2qOXxIR31epbg9yujaTb2HDGVeBRAF4YYAQgPQfgSLMxAMBlS5aYP+uXGDLJ3YyTNv6DmEBQBApxXq/TsxijXFDaczQflF5ym/6DzTpQAAEFc6xaoQAAAQHQQLAABgG4IFAACwDcECAADYhmABAABsQ7AAAAC2IVgAAADbECwAAIBtCBYAAMA2Ud95s3EHcZ8vMk8UBQAA9mu8b5/uSSBRDxY1NSce7pWXlxftpgEAwBmqqamRx+Np9edRfwhZMBjU7t27lZGRIYfDEc2mw+bz+ZSXl6fKysqYfWCaXfiuHVNn+a6d5XtKfNeOKF6+p2VZqqmpUW5urpzO1mdSRL3Hwul0qk+fPtFu9oy43e6Y/o9tJ75rx9RZvmtn+Z4S37Ujiofv2VZPRSMmbwIAANsQLAAAgG0IFm1wuVy6//775XK5TJcScXzXjqmzfNfO8j0lvmtH1NG+Z9QnbwIAgI6LHgsAAGAbggUAALANwQIAANiGYAEAAGxDsGhBSUmJRo0apYyMDGVnZ+sHP/iBvvjiC9NlRcRTTz2lYcOGNW3MMmbMGC1ZssR0WRFXUlIih8OhO+64w3QptnvggQfkcDiaHT179jRdVsRUVVXpxhtvVLdu3ZSamqrzzjtPa9euNV2W7c4666xT/rs6HA4VFxebLs1WDQ0Nuu+++1RQUKCUlBT169dPDz30kILBoOnSIqKmpkZ33HGH8vPzlZKSorFjx6qsrMx0WWck6jtvxoMVK1aouLhYo0aNUkNDg+69915NnDhRmzZtUlpamunybNWnTx898sgjOvvssyVJzz//vL7//e9r/fr1Gjp0qOHqIqOsrExz587VsGHDTJcSMUOHDtWyZcuaXickJBisJnKOHDmicePGafz48VqyZImys7O1bds2ZWZmmi7NdmVlZQoEAk2vy8vLdfnll2vq1KkGq7Lfo48+qqefflrPP/+8hg4dqjVr1ujmm2+Wx+PRzJkzTZdnu1tuuUXl5eV68cUXlZubqwULFmjChAnatGmTevfubbq89rFwWvv377ckWStWrDBdSlRkZWVZf/zjH02XERE1NTXWgAEDrHfffde69NJLrZkzZ5ouyXb333+/de6555ouIypmz55tXXTRRabLMGLmzJlW//79rWAwaLoUW1155ZXWjBkzmp275pprrBtvvNFQRZFTX19vJSQkWG+++Waz8+eee6517733GqrqzDEUEgKv1ytJ6tq1q+FKIisQCOiVV15RXV2dxowZY7qciCguLtaVV16pCRMmmC4lorZs2aLc3FwVFBTohz/8obZv3266pIhYtGiRRo4cqalTpyo7O1vDhw/XvHnzTJcVccePH9eCBQs0Y8aMmH+YY7guuugi/e1vf9OXX34pSfrss8/0wQcfaPLkyYYrs19DQ4MCgYCSk5ObnU9JSdEHH3xgqCobmE42sS4YDFpTpkzp0L8Vff7551ZaWpqVkJBgeTwe66233jJdUkS8/PLLVlFRkXX06FHLsqwO22Px9ttvW6+99pr1+eefN/XM5OTkWAcPHjRdmu1cLpflcrmsOXPmWOvWrbOefvppKzk52Xr++edNlxZRr776qpWQkGBVVVWZLsV2wWDQuvvuuy2Hw2ElJiZaDofDevjhh02XFTFjxoyxLr30UquqqspqaGiwXnzxRcvhcFgDBw40XVq7ESxO42c/+5mVn59vVVZWmi4lYvx+v7VlyxarrKzMuvvuu63u3btbGzduNF2WrXbt2mVlZ2dbn376adO5jhosvq22ttbKycmxfv/735suxXZdunSxxowZ0+zc7bffbl144YWGKoqOiRMnWldddZXpMiLi5Zdftvr06WO9/PLL1ueff2698MILVteuXa0//elPpkuLiK1bt1qXXHKJJclKSEiwRo0aZd1www3WkCFDTJfWbgSLNvz85z+3+vTpY23fvt10KVF12WWXWbfeeqvpMmz1+uuvN/2P23hIshwOh5WQkGA1NDSYLjGiJkyYYN12222my7Bd3759rZ/85CfNzj355JNWbm6uoYoib8eOHZbT6bTeeOMN06VERJ8+fawnnnii2blf//rX1qBBgwxVFB21tbXW7t27LcuyrGnTplmTJ082XFH7sSqkBZZl6fbbb9frr7+u5cuXq6CgwHRJUWVZlvx+v+kybHXZZZdpw4YNzc7dfPPNGjx4sGbPnt1hV01Ikt/v1+bNm3XxxRebLsV248aNO2Up+Jdffqn8/HxDFUXe/PnzlZ2drSuvvNJ0KRFRX18vp7P59L+EhIQOu9y0UVpamtLS0nTkyBEtXbpU//Vf/2W6pHYjWLSguLhYL730kv76178qIyNDe/fulSR5PB6lpKQYrs5e99xzjyZNmqS8vDzV1NTolVde0fLly1VaWmq6NFtlZGSoqKio2bm0tDR169btlPPx7q677tKUKVPUt29f7d+/X7/5zW/k8/k0ffp006XZ7s4779TYsWP18MMPa9q0afrkk080d+5czZ0713RpEREMBjV//nxNnz5diYkd85/vKVOm6Le//a369u2roUOHav369Xrsscc0Y8YM06VFxNKlS2VZlgYNGqStW7fql7/8pQYNGqSbb77ZdGntZ7jHJCZJavGYP3++6dJsN2PGDCs/P99KSkqyevToYV122WXWO++8Y7qsqOiocyyuv/56q1evXlaXLl2s3Nxc65prrulwc2ZOtnjxYquoqMhyuVzW4MGDrblz55ouKWKWLl1qSbK++OIL06VEjM/ns2bOnGn17dvXSk5Otvr162fde++9lt/vN11aRLz66qtWv379rKSkJKtnz55WcXGxVV1dbbqsM8Jj0wEAgG3YxwIAANiGYAEAAGxDsAAAALYhWAAAANsQLAAAgG0IFgAAwDYECwAAYBuCBQAAsA3BAgAA2IZgAQAAbEOwAAAAtiFYAAAA2/x/bquiVioIfa4AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "xs, ys = np.random.randint(0,10,8),np.random.randint(0,10,8)\n",
+    "\n",
+    "Nclass = 8\n",
+    "Nsamp = 1000\n",
+    "training_sample = torch.zeros(size =(Nclass, Nsamp, 8))\n",
+    "label = torch.zeros(size =(Nclass, Nsamp, 8))\n",
+    "for ii,(x,y) in enumerate(zip(xs,ys)):\n",
+    "    xsamp, ysamp = 0.1*torch.randn(Nsamp,1)+x, 0.1*torch.randn(Nsamp,1)+y\n",
+    "    training_sample[ii,:,:2] = torch.concat((xsamp,ysamp),1)\n",
+    "    training_sample[ii,:,2:] =  training_sample[ii,:,2:] + 0.05*torch.randn(Nsamp,6)\n",
+    "    label[ii,:,ii] = 1\n",
+    "    \n",
+    "    plt.scatter(xsamp,ysamp)\n",
+    "    \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "id": "de3f2cf4-20b6-4eee-817e-9cbd5b6f5fb1",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "ename": "RuntimeError",
+     "evalue": "shape '[8000, 2]' is invalid for input of size 64000",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[118], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m training_sample \u001b[38;5;241m=\u001b[39m \u001b[43mtraining_sample\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreshape\u001b[49m\u001b[43m(\u001b[49m\u001b[43mNsamp\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mNclass\u001b[49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      2\u001b[0m label \u001b[38;5;241m=\u001b[39m label\u001b[38;5;241m.\u001b[39mreshape(Nsamp\u001b[38;5;241m*\u001b[39mNclass,\u001b[38;5;241m8\u001b[39m)\n",
+      "\u001b[0;31mRuntimeError\u001b[0m: shape '[8000, 2]' is invalid for input of size 64000"
+     ]
+    }
+   ],
+   "source": [
+    "training_sample = training_sample.reshape(Nsamp*Nclass,2)\n",
+    "label = label.reshape(Nsamp*Nclass,8)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cf3c6e7b-f5ac-41d8-8775-6de401cbadb6",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "dset = TensorDataset(training_sample,label)\n",
+    "from torch.utils.data import random_split\n",
+    "dset_train, dset_val = random_split(dset, [int(0.9*len(dset)), int(0.1*len(dset))])\n",
+    "\n",
+    "loader = DataLoader(dset_train, batch_size=100, shuffle=True)\n",
+    "loader_val = DataLoader(dset_val, batch_size=100, shuffle=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "id": "ad3ab9b5-be90-4555-9d31-0190c536eb0c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "01582462-9382-4795-aa56-7a61082d28b0",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## NORMALIZING FLOW"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ee2caaf8-eed9-4718-aeab-29a4dabde520",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# Define list of flows\n",
+    "num_layers = 8\n",
+    "flows = []\n",
+    "for i in range(num_layers):\n",
+    "    # Neural network with two hidden layers having 32 units each\n",
+    "    # Last layer is initialized by zeros making training more stable\n",
+    "    param_map = nf.nets.MLP([4, 512, 512, 512, 2], init_zeros=True)\n",
+    "    # Add flow layer\n",
+    "    flows.append(nf.flows.AffineCouplingBlock(param_map))\n",
+    "    # Swap dimensions\n",
+    "    flows.append(nf.flows.Permute(num_layers, mode='swap'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f7925c74-0ea8-4e76-9180-ff3be2013f06",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "model = nf.NormalizingFlow(base, flows)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "08e6cd4b-b8f6-4a0c-a324-bc48778086e8",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "for x,y in loader:\n",
+    "    print(x.shape,y.shape)\n",
+    "    loss = model.forward_kld(y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "id": "c577c27a-84f7-4a83-8070-a93759b1b430",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "xs, ys = np.random.randint(0,10,8),np.random.randint(0,10,8)\n",
+    "Nclass = 8\n",
+    "Nsamp = 1000\n",
+    "training_sample = torch.zeros(size =(Nclass, Nsamp, 2))\n",
+    "label = torch.zeros(size =(Nclass, Nsamp, 8))\n",
+    "for ii,(x,y) in enumerate(zip(xs,ys)):\n",
+    "    xsamp, ysamp = 0.1*torch.randn(Nsamp,1)+x, 0.1*torch.randn(Nsamp,1)+y\n",
+    "    training_sample[ii] = torch.concat((xsamp,ysamp),1)\n",
+    "    #training_sample[ii,:,2:] =  training_sample[ii,:,2:] + 0.05*torch.randn(Nsamp,6)\n",
+    "    label[ii,:,ii] = 1\n",
+    "    \n",
+    "    plt.scatter(xsamp,ysamp)\n",
+    "    \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "id": "450cd744-3ada-487a-9dcd-6f04f1ba3e44",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "training_sample = training_sample.reshape(Nsamp*Nclass,2)\n",
+    "label = label.reshape(Nsamp*Nclass,8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 136,
+   "id": "dcabeab0-17b9-4ef7-81bd-024904bfb01c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dset = TensorDataset(training_sample,label)\n",
+    "from torch.utils.data import random_split\n",
+    "dset_train, dset_val = random_split(dset, [int(0.9*len(dset)), int(0.1*len(dset))])\n",
+    "\n",
+    "loader = DataLoader(dset_train, batch_size=100, shuffle=True)\n",
+    "loader_val = DataLoader(dset_val, batch_size=100, shuffle=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 135,
+   "id": "a4c75aff-494c-4ef0-a2e2-b40a014d448f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Define flows\n",
+    "K = 4\n",
+    "\n",
+    "latent_size = 2\n",
+    "hidden_units = 512\n",
+    "hidden_layers = 3\n",
+    "context_size=8\n",
+    "flows = []\n",
+    "for i in range(K):\n",
+    "    flows += [nf.flows.AutoregressiveRationalQuadraticSpline(latent_size, hidden_layers, hidden_units,\n",
+    "                                                             num_context_channels=context_size)]\n",
+    "    flows += [nf.flows.LULinearPermute(latent_size)]\n",
+    "\n",
+    "# Set base distribution\n",
+    "q0 = nf.distributions.DiagGaussian(2, trainable=False)\n",
+    "    # Construct flow model\n",
+    "model = nf.ConditionalNormalizingFlow(q0, flows)\n",
+    "\n",
+    "model = model.to(device)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "id": "6a032110-51fe-43b3-b482-2ad81e984727",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Define target\n",
+    "target = nf.distributions.target.ConditionalDiagGaussian()\n",
+    "context_size = 2\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "id": "9c212010-f606-4381-b690-f275bb2e8729",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "torch.Size([128, 4])"
+      ]
+     },
+     "execution_count": 140,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "context.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 146,
+   "id": "5a0abfb1-4bbb-4d5b-a591-91b9aca2cfbb",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "torch.Size([128, 2])"
+      ]
+     },
+     "execution_count": 146,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "xx.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "id": "62b00dd1-6dc5-4510-bf15-2e1782f8ff06",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "torch.Size([8000, 8])"
+      ]
+     },
+     "execution_count": 144,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "label.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 147,
+   "id": "b7075127-9dea-4204-959f-99fbd0efc829",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "torch.Size([100, 2])"
+      ]
+     },
+     "execution_count": 147,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c960a2ce-7459-4b12-8e68-c60d5105f511",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "loss = model.forward_kld(x, context)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
+   "id": "57caeaa3-fae2-4408-a534-0d087a05bf24",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "target = nf.distributions.target.ConditionalDiagGaussian()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 152,
+   "id": "5ddd2d85-37e4-483a-8439-28cac821dc5a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001b[0;31mSignature:\u001b[0m \u001b[0mtarget\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog_prob\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mz\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+       "\u001b[0;31mDocstring:\u001b[0m\n",
+       "Args:\n",
+       "  z: value or batch of latent variable\n",
+       "\n",
+       "Returns:\n",
+       "  log probability of the distribution for z\n",
+       "\u001b[0;31mFile:\u001b[0m      /data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/distributions/target.py\n",
+       "\u001b[0;31mType:\u001b[0m      method"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "target.log_prob?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 158,
+   "id": "811b965c-e851-4416-a042-06cca855b1d0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "context_plot = torch.cat([torch.tensor([0.3, 0.9]).to(device) + torch.zeros_like(zz), \n",
+    "                          0.6 * torch.ones_like(zz)], dim=-1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 157,
+   "id": "01df4c63-4b28-4c58-b9ea-1db5c2d4c59a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0\n",
+      "1\n",
+      "2\n",
+      "3\n",
+      "4\n",
+      "5\n",
+      "6\n",
+      "7\n",
+      "8\n",
+      "9\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Train model\n",
+    "max_iter = 10\n",
+    "batch_size= 128\n",
+    "\n",
+    "loss_hist = np.array([])\n",
+    "\n",
+    "optimizer = torch.optim.Adam(model.parameters(), lr=3e-4, weight_decay=1e-5)\n",
+    "\n",
+    "\n",
+    "for it in range(max_iter):\n",
+    "    print(it)\n",
+    "    \n",
+    "    for x,y in loader:\n",
+    "        optimizer.zero_grad()\n",
+    "        loss = model.forward_kld(x.to(device), y.to(device))\n",
+    "        loss.backward()\n",
+    "        optimizer.step()\n",
+    "        loss_hist = np.append(loss_hist, loss.to('cpu').data.numpy())\n",
+    "    \n",
+    "plt.figure(figsize=(10, 10))\n",
+    "plt.plot(loss_hist, label='loss')\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "25ec2e8e-4ed6-4d37-8da7-6c157026c516",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "99253669-ad50-4c0d-a74f-b52114935756",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2e11eefe-5c26-4cd0-8e08-5c0d76c2223b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d05171a4-7020-416e-be4c-09b341f4e15a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3f80339b-4cd4-4d92-bbbe-a72ab842c55d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "756fcc22-0935-42f9-b5c6-046130dc004d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "id": "4c7b706b-a0d7-494f-a070-b8f0c58436e3",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[0.3000, 0.9000, 0.6000, 0.6000],\n",
+       "        [0.3000, 0.9000, 0.6000, 0.6000],\n",
+       "        [0.3000, 0.9000, 0.6000, 0.6000],\n",
+       "        ...,\n",
+       "        [0.3000, 0.9000, 0.6000, 0.6000],\n",
+       "        [0.3000, 0.9000, 0.6000, 0.6000],\n",
+       "        [0.3000, 0.9000, 0.6000, 0.6000]], device='cuda:0')"
+      ]
+     },
+     "execution_count": 104,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "context_plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "12f4ba37-b394-4875-a73f-d739e08e2f79",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.train()\n",
+    "prob = torch.exp(log_prob)\n",
+    "prob[torch.isnan(prob)] = 0\n",
+    "\n",
+    "plt.figure(figsize=(10, 10))\n",
+    "plt.pcolormesh(xx, yy, prob.data.numpy(), shading='auto')\n",
+    "plt.contour(xx, yy, p_target, cmap=plt.get_cmap('cool'), linewidths=2)\n",
+    "plt.gca().set_aspect('equal', 'box')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fa9db9d2-3a76-40eb-8d84-6de6d9427ff9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f9390a2b-8aa4-4fd3-a4f4-3d939c8b7287",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "bac89c40-f896-48c0-90a1-997592f9d7be",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "base = nf.distributions.base.DiagGaussian(2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "id": "4fc3c2f6-ae7b-41ea-b471-8470e25374d5",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "model = nf.NormalizingFlow(base, flows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "id": "ff099c9f-9ecc-4479-ab2c-dd1ac5a98be5",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "torch.Size([100, 8]) torch.Size([100, 8])\n"
+     ]
+    },
+    {
+     "ename": "RuntimeError",
+     "evalue": "mat1 and mat2 shapes cannot be multiplied (100x4 and 2x512)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[82], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m x,y \u001b[38;5;129;01min\u001b[39;00m loader:\n\u001b[1;32m      2\u001b[0m     \u001b[38;5;28mprint\u001b[39m(x\u001b[38;5;241m.\u001b[39mshape,y\u001b[38;5;241m.\u001b[39mshape)\n\u001b[0;32m----> 3\u001b[0m     loss \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mforward_kld\u001b[49m\u001b[43m(\u001b[49m\u001b[43my\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/core.py:99\u001b[0m, in \u001b[0;36mNormalizingFlow.forward_kld\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m     97\u001b[0m z \u001b[38;5;241m=\u001b[39m x\n\u001b[1;32m     98\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mflows) \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m):\n\u001b[0;32m---> 99\u001b[0m     z, log_det \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mflows\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minverse\u001b[49m\u001b[43m(\u001b[49m\u001b[43mz\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    100\u001b[0m     log_q \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m log_det\n\u001b[1;32m    101\u001b[0m log_q \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mq0\u001b[38;5;241m.\u001b[39mlog_prob(z)\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/flows/affine/coupling.py:265\u001b[0m, in \u001b[0;36mAffineCouplingBlock.inverse\u001b[0;34m(self, z)\u001b[0m\n\u001b[1;32m    263\u001b[0m log_det_tot \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mzeros(z\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m], dtype\u001b[38;5;241m=\u001b[39mz\u001b[38;5;241m.\u001b[39mdtype, device\u001b[38;5;241m=\u001b[39mz\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[1;32m    264\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mflows) \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m):\n\u001b[0;32m--> 265\u001b[0m     z, log_det \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mflows\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minverse\u001b[49m\u001b[43m(\u001b[49m\u001b[43mz\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    266\u001b[0m     log_det_tot \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m log_det\n\u001b[1;32m    267\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m z, log_det_tot\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/flows/affine/coupling.py:151\u001b[0m, in \u001b[0;36mAffineCoupling.inverse\u001b[0;34m(self, z)\u001b[0m\n\u001b[1;32m    149\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minverse\u001b[39m(\u001b[38;5;28mself\u001b[39m, z):\n\u001b[1;32m    150\u001b[0m     z1, z2 \u001b[38;5;241m=\u001b[39m z\n\u001b[0;32m--> 151\u001b[0m     param \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparam_map\u001b[49m\u001b[43m(\u001b[49m\u001b[43mz1\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    152\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mscale:\n\u001b[1;32m    153\u001b[0m         shift \u001b[38;5;241m=\u001b[39m param[:, \u001b[38;5;241m0\u001b[39m::\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m]\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/torch/nn/modules/module.py:1110\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1106\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1107\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1108\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1109\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1110\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1111\u001b[0m \u001b[38;5;66;03m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1112\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[38;5;241m=\u001b[39m [], []\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/nets/mlp.py:58\u001b[0m, in \u001b[0;36mMLP.forward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m     57\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, x):\n\u001b[0;32m---> 58\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnet\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/torch/nn/modules/module.py:1110\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1106\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1107\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1108\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1109\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1110\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1111\u001b[0m \u001b[38;5;66;03m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1112\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[38;5;241m=\u001b[39m [], []\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/torch/nn/modules/container.py:141\u001b[0m, in \u001b[0;36mSequential.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    139\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28minput\u001b[39m):\n\u001b[1;32m    140\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m module \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m:\n\u001b[0;32m--> 141\u001b[0m         \u001b[38;5;28minput\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[43mmodule\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m    142\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28minput\u001b[39m\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/torch/nn/modules/module.py:1110\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1106\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1107\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1108\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1109\u001b[0m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1110\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1111\u001b[0m \u001b[38;5;66;03m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1112\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[38;5;241m=\u001b[39m [], []\n",
+      "File \u001b[0;32m/data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/torch/nn/modules/linear.py:103\u001b[0m, in \u001b[0;36mLinear.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    102\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28minput\u001b[39m: Tensor) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tensor:\n\u001b[0;32m--> 103\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mF\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlinear\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mweight\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbias\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[0;31mRuntimeError\u001b[0m: mat1 and mat2 shapes cannot be multiplied (100x4 and 2x512)"
+     ]
+    }
+   ],
+   "source": [
+    "for x,y in loader:\n",
+    "    print(x.shape,y.shape)\n",
+    "    loss = model.forward_kld(y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7cea0406-653d-4699-9e7b-3c497511ff2e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d5b5a801-f53f-4091-890e-a70269fdf05e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "9bea5685-c6a8-4402-b966-ea4f1960745a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "target = nf.distributions.target.TwoMoons()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "0c52cc3a-ff3b-43f5-bf30-5c5e85471abc",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001b[0;31mSignature:\u001b[0m      \u001b[0mtarget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+       "\u001b[0;31mType:\u001b[0m           TwoMoons\n",
+       "\u001b[0;31mString form:\u001b[0m    TwoMoons()\n",
+       "\u001b[0;31mFile:\u001b[0m           /data/astro/scratch/lcabayol/anaconda3/envs/DLenv2/lib/python3.9/site-packages/normflows/distributions/target.py\n",
+       "\u001b[0;31mDocstring:\u001b[0m      Bimodal two-dimensional distribution\n",
+       "\u001b[0;31mInit docstring:\u001b[0m\n",
+       "Constructor\n",
+       "\n",
+       "Args:\n",
+       "  prop_scale: Scale for the uniform proposal\n",
+       "  prop_shift: Shift for the uniform proposal"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "target?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5e7923cf-c59f-4bfa-bcf3-c218bc861b5f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e7e08455-fb0e-480b-903b-4ce9a057f863",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "26edb3db-8925-4a41-8de3-94ea4ea9b71a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "16150af7-2302-4e11-ba6c-8718fa7d8a1e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d7089567-b0fc-455b-8814-705333e88527",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "052634d5-c8d6-4535-88b9-1fe376da6051",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0e1eb3d5-7e19-49ae-a991-01c729f10465",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bbdef1a1-7754-4db9-b5ab-b2c5e11739f4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "819d2620-38ca-4e2e-b0f8-6a0ef56089ec",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "base_dist = torch.distributions.Independent(\n",
+    "  torch.distributions.Normal(torch.zeros(2), torch.ones(2)), \n",
+    "  1\n",
+    ")\n",
+    "target_dist = torch.distributions.Independent(\n",
+    "  torch.distributions.Normal(torch.zeros(2)+5, torch.ones(2)*0.5),\n",
+    "  1\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "aabbaa36-feeb-40c6-929e-c26354438606",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "num_samples = 1000\n",
+    "samples_base = base_dist.sample((num_samples,))\n",
+    "samples_target = target_dist.sample((num_samples,))\n",
+    "\n",
+    "# Extract x and y coordinates for plotting\n",
+    "x_values_base = samples_base[:, 0].numpy()\n",
+    "y_values_base = samples_base[:, 1].numpy()\n",
+    "\n",
+    "x_values_target = samples_target[:, 0].numpy()\n",
+    "y_values_target = samples_target[:, 1].numpy()\n",
+    "\n",
+    "# Create a scatter plot\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "plt.scatter(x_values_base, y_values_base, alpha=0.5)\n",
+    "plt.scatter(x_values_target, y_values_target, alpha=0.5)\n",
+    "\n",
+    "plt.xlabel('X')\n",
+    "plt.ylabel('Y')\n",
+    "plt.title('Samples from Base Distribution')\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bd9bfb4f-3a0f-4cac-a50a-3293b88debd5",
+   "metadata": {},
+   "source": [
+    "## CREATE NORMALIZING FLOW"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "164b546c-d46a-4f1e-81cc-a3cf2f72b7d0",
+   "metadata": {},
+   "source": [
+    "##### Normalizing flow with a single transformation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "22f74d33-444a-4b85-a26d-9092aff85bf8",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7bc7dfa4-34e0-40b4-a772-4d6be5a32abf",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "edb22fa1-e69a-4742-b902-5e18189a6758",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "bijectors = bij.AffineAutoregressive()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "6fa8f7bd-956e-45d5-a242-68d36ab2ff9e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "flow = dist.Flow(base_dist, bijectors)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "ea37537e-1463-41ba-b8d2-c94aa0aa1fa0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch 0 loss tensor(23.8129, grad_fn=<NegBackward0>)\n",
+      "epoch 500 loss tensor(3.6865, grad_fn=<NegBackward0>)\n",
+      "epoch 1000 loss tensor(3.2616, grad_fn=<NegBackward0>)\n",
+      "epoch 1500 loss tensor(3.0639, grad_fn=<NegBackward0>)\n",
+      "epoch 2000 loss tensor(2.5082, grad_fn=<NegBackward0>)\n",
+      "epoch 2500 loss tensor(1.6517, grad_fn=<NegBackward0>)\n",
+      "epoch 3000 loss tensor(1.4682, grad_fn=<NegBackward0>)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Training loop\n",
+    "opt = torch.optim.Adam(flow.parameters(), lr=5e-3)\n",
+    "for idx in range(3001):\n",
+    "    opt.zero_grad()\n",
+    "\n",
+    "    # Minimize KL(p || q)\n",
+    "    y = target_dist.sample((1000,))\n",
+    "    loss = -flow.log_prob(y).mean()\n",
+    "\n",
+    "    if idx % 500 == 0:\n",
+    "        print('epoch', idx, 'loss', loss)\n",
+    "\n",
+    "    loss.backward()\n",
+    "    opt.step()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "c6a98ae5-64b5-4b49-87cf-c6c4b0fc3e83",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "dist_y = dist.Flow(base_dist, bijectors)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "24208fa8-63a9-439f-9946-56d96fb33409",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "num_samples = 1000\n",
+    "samples_pred = dist_y.sample((num_samples,))\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "37a2ff47-30db-45d3-849a-0e7c81ed7364",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "num_samples = 1000\n",
+    "samples_base = base_dist.sample((num_samples,))\n",
+    "samples_target = target_dist.sample((num_samples,))\n",
+    "\n",
+    "# Extract x and y coordinates for plotting\n",
+    "x_values_base = samples_base[:, 0].numpy()\n",
+    "y_values_base = samples_base[:, 1].numpy()\n",
+    "\n",
+    "x_values_target = samples_target[:, 0].numpy()\n",
+    "y_values_target = samples_target[:, 1].numpy()\n",
+    "\n",
+    "# Extract x and y coordinates for plotting\n",
+    "x_values_pred = samples_pred[:, 0].numpy()\n",
+    "y_values_pred = samples_pred[:, 1].numpy()\n",
+    "\n",
+    "# Create a scatter plot\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "plt.scatter(x_values_base, y_values_base, alpha=0.5)\n",
+    "plt.scatter(x_values_target, y_values_target, alpha=0.5)\n",
+    "plt.scatter(x_values_pred, y_values_pred, alpha=0.5)\n",
+    "\n",
+    "plt.xlabel('X')\n",
+    "plt.ylabel('Y')\n",
+    "plt.title('Samples from Base Distribution')\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f7c36476-bb8e-4b53-8555-264ffec9d1e0",
+   "metadata": {},
+   "source": [
+    "# SIMPLE EXAMPLE MAPPING FEATRUES INTO PROBABILITY DISTRIBUTIONS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "db52a20f-f3df-4774-b2b7-2d7566ceb242",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "\n",
+    "from pylab import rcParams\n",
+    "rcParams['figure.figsize'] = 10, 8\n",
+    "rcParams['figure.dpi'] = 300\n",
+    "\n",
+    "import torch\n",
+    "from torch import nn\n",
+    "from torch import distributions\n",
+    "from torch.nn.parameter import Parameter\n",
+    "\n",
+    "from sklearn import cluster, datasets, mixture\n",
+    "from sklearn.preprocessing import StandardScaler"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "729a79a5-495d-432e-803f-5b3f130ecf45",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "class RealNVP(nn.Module):\n",
+    "    def __init__(self, nets, nett, mask, prior):\n",
+    "        super(RealNVP, self).__init__()\n",
+    "        \n",
+    "        self.prior = prior\n",
+    "        self.mask = nn.Parameter(mask, requires_grad=False)\n",
+    "        self.t = torch.nn.ModuleList([nett() for _ in range(len(masks))])\n",
+    "        self.s = torch.nn.ModuleList([nets() for _ in range(len(masks))])\n",
+    "        \n",
+    "    def g(self, z):\n",
+    "        x = z\n",
+    "        for i in range(len(self.t)):\n",
+    "            x_ = x*self.mask[i]\n",
+    "            s = self.s[i](x_)*(1 - self.mask[i])\n",
+    "            t = self.t[i](x_)*(1 - self.mask[i])\n",
+    "            x = x_ + (1 - self.mask[i]) * (x * torch.exp(s) + t)\n",
+    "        return x\n",
+    "\n",
+    "    def f(self, x):\n",
+    "        log_det_J, z = x.new_zeros(x.shape[0]), x\n",
+    "        for i in reversed(range(len(self.t))):\n",
+    "            z_ = self.mask[i] * z\n",
+    "            s = self.s[i](z_) * (1-self.mask[i])\n",
+    "            t = self.t[i](z_) * (1-self.mask[i])\n",
+    "            z = (1 - self.mask[i]) * (z - t) * torch.exp(-s) + z_\n",
+    "            log_det_J -= s.sum(dim=1)\n",
+    "        return z, log_det_J\n",
+    "    \n",
+    "    def log_prob(self,x):\n",
+    "        z, logp = self.f(x)\n",
+    "        return self.prior.log_prob(z) + logp\n",
+    "        \n",
+    "    def sample(self, batchSize): \n",
+    "        z = self.prior.sample((batchSize, 1))\n",
+    "        logp = self.prior.log_prob(z)\n",
+    "        x = self.g(z)\n",
+    "        return x"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "2f634ec2-7033-4ab5-bb8d-aeade4eba08c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "nets = lambda: nn.Sequential(nn.Linear(2, 256), nn.LeakyReLU(), nn.Linear(256, 256), nn.LeakyReLU(), nn.Linear(256, 2), nn.Tanh())\n",
+    "nett = lambda: nn.Sequential(nn.Linear(2, 256), nn.LeakyReLU(), nn.Linear(256, 256), nn.LeakyReLU(), nn.Linear(256, 2))\n",
+    "masks = torch.from_numpy(np.array([[0, 1], [1, 0]] * 3).astype(np.float32))\n",
+    "prior = distributions.MultivariateNormal(torch.zeros(2), torch.eye(2))\n",
+    "flow = RealNVP(nets, nett, masks, prior)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "702a29ed-3636-42ea-bead-2974c3af3f56",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "iter 0: loss = 2.715\n",
+      "iter 500: loss = 0.835\n",
+      "iter 1000: loss = 0.493\n",
+      "iter 1500: loss = 0.592\n",
+      "iter 2000: loss = 0.467\n",
+      "iter 2500: loss = 0.298\n",
+      "iter 3000: loss = 0.396\n",
+      "iter 3500: loss = 0.368\n",
+      "iter 4000: loss = 0.306\n",
+      "iter 4500: loss = 0.486\n",
+      "iter 5000: loss = 0.458\n"
+     ]
+    }
+   ],
+   "source": [
+    "optimizer = torch.optim.Adam([p for p in flow.parameters() if p.requires_grad==True], lr=1e-4)\n",
+    "for t in range(5001):    \n",
+    "    noisy_moons = datasets.make_moons(n_samples=100, noise=.05)[0].astype(np.float32)\n",
+    "    loss = -flow.log_prob(torch.from_numpy(noisy_moons)).mean()\n",
+    "    \n",
+    "    optimizer.zero_grad()\n",
+    "    loss.backward(retain_graph=True)\n",
+    "    optimizer.step()\n",
+    "    \n",
+    "    if t % 500 == 0:\n",
+    "        print('iter %s:' % t, 'loss = %.3f' % loss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "e81130c9-35b0-414d-b4cd-4d61bd768093",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "noisy_moons = datasets.make_moons(n_samples=1000, noise=.05)[0].astype(np.float32)\n",
+    "z = flow.f(torch.from_numpy(noisy_moons))[0].detach().numpy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "c37ec61f-dddb-454f-b05e-93c1c9a38087",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[-1.8747659e-01,  3.8629249e-01],\n",
+       "       [-4.5098123e-01,  1.1165810e+00],\n",
+       "       [ 2.7200544e-01,  4.9045309e-01],\n",
+       "       ...,\n",
+       "       [-1.9135862e-03, -1.3994721e+00],\n",
+       "       [ 1.8429850e+00,  4.9667689e-01],\n",
+       "       [ 2.3594198e+00, -1.4860994e-01]], dtype=float32)"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "z"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "8e464e0d-449e-464c-b819-be28cdd29db0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, '$X = g(z)$')"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 3000x2400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "noisy_moons = datasets.make_moons(n_samples=1000, noise=.05)[0].astype(np.float32)\n",
+    "z = flow.f(torch.from_numpy(noisy_moons))[0].detach().numpy()\n",
+    "plt.subplot(221)\n",
+    "plt.scatter(z[:, 0], z[:, 1])\n",
+    "plt.title(r'$z = f(X)$')\n",
+    "\n",
+    "z = np.random.multivariate_normal(np.zeros(2), np.eye(2), 1000)\n",
+    "plt.subplot(222)\n",
+    "plt.scatter(z[:, 0], z[:, 1])\n",
+    "plt.title(r'$z \\sim p(z)$')\n",
+    "\n",
+    "plt.subplot(223)\n",
+    "x = datasets.make_moons(n_samples=1000, noise=.05)[0].astype(np.float32)\n",
+    "plt.scatter(x[:, 0], x[:, 1], c='r')\n",
+    "plt.title(r'$X \\sim p(X)$')\n",
+    "\n",
+    "plt.subplot(224)\n",
+    "x = flow.sample(1000).detach().numpy()\n",
+    "plt.scatter(x[:, 0, 0], x[:, 0, 1], c='r')\n",
+    "plt.title(r'$X = g(z)$')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "27e2c49d-7b84-49ae-ad86-8fd1114021f9",
+   "metadata": {},
+   "source": [
+    "## WITH NFLOWS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "4280144d-29e5-4b68-8b59-eb49e69a3c61",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import sklearn.datasets as datasets\n",
+    "\n",
+    "import torch\n",
+    "from torch import nn\n",
+    "from torch import optim\n",
+    "\n",
+    "from nflows.flows.base import Flow\n",
+    "from nflows.distributions.normal import ConditionalDiagonalNormal\n",
+    "from nflows.transforms.base import CompositeTransform\n",
+    "from nflows.transforms.autoregressive import MaskedAffineAutoregressiveTransform\n",
+    "from nflows.transforms.permutations import ReversePermutation\n",
+    "from nflows.nn.nets import ResidualNet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "3e85d649-e33d-4d49-9e4b-dff44fbed770",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_layers = 5\n",
+    "base_dist = ConditionalDiagonalNormal(shape=[2], \n",
+    "                                      context_encoder=nn.Linear(1, 4))\n",
+    "\n",
+    "transforms = []\n",
+    "for _ in range(num_layers):\n",
+    "    transforms.append(ReversePermutation(features=2))\n",
+    "    transforms.append(MaskedAffineAutoregressiveTransform(features=2, \n",
+    "                                                          hidden_features=4, \n",
+    "                                                          context_features=1))\n",
+    "transform = CompositeTransform(transforms)\n",
+    "\n",
+    "flow = Flow(transform, base_dist)\n",
+    "optimizer = optim.Adam(flow.parameters())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e097405a-851f-4b5d-bff3-6081bc2d6357",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n",
+      "torch.Size([128, 2]) torch.Size([128, 1])\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "KeyboardInterrupt\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "num_iter = 5000\n",
+    "for i in range(num_iter):\n",
+    "    x, y = datasets.make_moons(128, noise=.1)\n",
+    "    x = torch.tensor(x, dtype=torch.float32)\n",
+    "    y = torch.tensor(y, dtype=torch.float32).reshape(-1, 1)\n",
+    "    \n",
+    "    print(x.shape, y.shape)\n",
+    "    optimizer.zero_grad()\n",
+    "    loss = -flow.log_prob(inputs=x, context=y).mean()\n",
+    "    loss.backward()\n",
+    "    optimizer.step()\n",
+    "    \n",
+    "    if (i + 1) % 500 == 0:\n",
+    "        fig, ax = plt.subplots(1, 2)\n",
+    "        xline = torch.linspace(-1.5, 2.5,100)\n",
+    "        yline = torch.linspace(-.75, 1.25,100)\n",
+    "        xgrid, ygrid = torch.meshgrid(xline, yline)\n",
+    "        xyinput = torch.cat([xgrid.reshape(-1, 1), ygrid.reshape(-1, 1)], dim=1)\n",
+    "\n",
+    "        with torch.no_grad():\n",
+    "            zgrid0 = flow.log_prob(xyinput, torch.zeros(10000, 1)).exp().reshape(100, 100)\n",
+    "            zgrid1 = flow.log_prob(xyinput, torch.ones(10000, 1)).exp().reshape(100, 100)\n",
+    "\n",
+    "        ax[0].contourf(xgrid.numpy(), ygrid.numpy(), zgrid0.numpy())\n",
+    "        ax[1].contourf(xgrid.numpy(), ygrid.numpy(), zgrid1.numpy())\n",
+    "        plt.title('iteration {}'.format(i + 1))\n",
+    "        plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a9cfcdee-479e-4be2-aa5c-3755f52649a5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "DLenv2",
+   "language": "python",
+   "name": "dlenv2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}