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Last active October 3, 2019 12:08
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VAE Intuition
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "VAE Intuition",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/arghyadeep99/7d19454e7784d7886313d4e263b2c304/vae-intuition.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "flmHjPAja0lI",
"colab_type": "code",
"colab": {}
},
"source": [
"import torch\n",
"import torch.nn.functional as nn\n",
"import torch.autograd as autograd\n",
"import torch.optim as optim\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.gridspec as gridspec\n",
"import os\n",
"from torch.autograd import Variable\n",
"import numpy as np\n",
"from torchvision import transforms"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "YjtPhMQheMXI",
"colab_type": "code",
"outputId": "16e98e13-584f-4fbe-9dfc-99eb40179b1c",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 269
}
},
"source": [
"# Data Generation\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"x = np.array([i/100 for i in range(100000)])\n",
"y = 2*x + 5 + np.array([np.random.rand()*300 for i in range(100000)])\n",
"XX = np.array([x,y]).T\n",
"XX = XX/np.max(XX)\n",
"plt.scatter(XX.T[0],XX.T[1])\n",
"XX = torch.Tensor(XX)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "display_data",
"data": {
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qYDYzZ4CPA68AvhwRAI9n5tljrPuglbRad1ujVK5KPffM3AJsWfDZlSOv31JzXWPh1kZJ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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ozrNY5sba4fd",
"colab_type": "code",
"colab": {}
},
"source": [
"mb_size = 10000\n",
"Z_dim = 1\n",
"X_dim = 2\n",
"h_dim = 100\n",
"c = 0\n",
"lr = 1e-2"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "hfoeiCSwbFms",
"colab_type": "code",
"colab": {}
},
"source": [
"def xavier_init(size):\n",
" in_dim = size[0]\n",
" xavier_stddev = 1. / np.sqrt(in_dim / 2.)\n",
" return Variable(torch.randn(*size) * xavier_stddev, requires_grad=True)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "lu2ILS34bL7V",
"colab_type": "code",
"colab": {}
},
"source": [
"\n",
"# Encoder\n",
"\n",
"Wxh = xavier_init(size=[X_dim, h_dim])\n",
"bxh = Variable(torch.zeros(h_dim), requires_grad=True)\n",
"\n",
"Whz_mu = xavier_init(size=[h_dim, Z_dim])\n",
"bhz_mu = Variable(torch.zeros(Z_dim), requires_grad=True)\n",
"\n",
"Whz_var = xavier_init(size=[h_dim, Z_dim])\n",
"bhz_var = Variable(torch.zeros(Z_dim), requires_grad=True)\n",
"\n",
"\n",
"def Q(X):\n",
" h = nn.relu(X @ Wxh + bxh.repeat(X.size(0), 1))\n",
" z_mu = h @ Whz_mu + bhz_mu.repeat(h.size(0), 1)\n",
" z_var = h @ Whz_var + bhz_var.repeat(h.size(0), 1)\n",
" return z_mu, z_var\n",
"\n",
"\n",
"def sample_z(mu, log_var):\n",
" eps = Variable(torch.randn(mb_size, Z_dim))\n",
" return mu + torch.exp(log_var / 2) * eps"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "hkGZsmDobRbs",
"colab_type": "code",
"colab": {}
},
"source": [
"# Decoder\n",
"\n",
"Wzh = xavier_init(size=[Z_dim, h_dim])\n",
"bzh = Variable(torch.zeros(h_dim), requires_grad=True)\n",
"\n",
"Whx = xavier_init(size=[h_dim, X_dim])\n",
"bhx = Variable(torch.zeros(X_dim), requires_grad=True)\n",
"\n",
"\n",
"def P(z):\n",
" h = nn.relu(z @ Wzh + bzh.repeat(z.size(0), 1))\n",
" X = nn.sigmoid(h @ Whx + bhx.repeat(h.size(0), 1))\n",
" return X"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "UwweaFn-baCr",
"colab_type": "code",
"outputId": "0fd9e68e-2c0d-476d-ee3d-b70f707a3701",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
}
},
"source": [
"# =============================== TRAINING ====================================\n",
"\n",
"params = [Wxh, bxh, Whz_mu, bhz_mu, Whz_var, bhz_var,\n",
" Wzh, bzh, Whx, bhx]\n",
"\n",
"solver = optim.Adam(params, lr=lr)\n",
"\n",
"losses = []\n",
"\n",
"for it in range(1000):\n",
" perm = torch.randperm(100000)\n",
" idx = perm[:mb_size]\n",
" samples = XX[idx]\n",
" X = samples\n",
" \n",
" # Forward\n",
" z_mu, z_var = Q(X)\n",
" z = sample_z(z_mu, z_var)\n",
" X_sample = P(z)\n",
"\n",
" if it == 1:\n",
" print('idx',idx)\n",
" print('X',X)\n",
" print('X_sample',X_sample)\n",
" \n",
" # Loss\n",
" recon_loss = nn.binary_cross_entropy(X_sample, X, size_average=False) / mb_size\n",
" kl_loss = torch.mean(0.5 * torch.sum(torch.exp(z_var) + z_mu**2 - 1. - z_var, 1))\n",
" loss = 10*recon_loss + kl_loss\n",
"\n",
" # Backward\n",
" loss.backward()\n",
"\n",
" # Update\n",
" solver.step()\n",
"\n",
" # Housekeeping\n",
" for p in params:\n",
" if p.grad is not None:\n",
" data = p.grad.data\n",
" p.grad = Variable(data.new().resize_as_(data).zero_())\n",
"\n",
" # Print and plot every now and then\n",
" if it % 1 == 0:\n",
" #print(X_sample)\n",
" print(loss)\n",
" losses.append(loss.detach().numpy())\n",
" plt.scatter(X.numpy().T[0],X.numpy().T[1])\n",
" print('X_sample',X_sample.detach())\n",
" plt.scatter(X_sample.detach().numpy().T[0],X_sample.detach().numpy().T[1])\n",
" plt.show()"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:1350: UserWarning: nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.\n",
" warnings.warn(\"nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.\")\n",
"/usr/local/lib/python3.6/dist-packages/torch/nn/_reduction.py:43: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead.\n",
" warnings.warn(warning.format(ret))\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"tensor(15.2197, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.4654, 0.5395],\n",
" [0.4743, 0.5294],\n",
" [0.5044, 0.5858],\n",
" ...,\n",
" [0.5097, 0.6816],\n",
" [0.3863, 0.6294],\n",
" [0.3792, 0.6374]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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oSdPuaRrhvWCHKb/XpQ/CnAXRvW8ztOAy0KrhbmbtwAPAPGA78LyZ9TrnXgwcMxO4BTjb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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"idx tensor([62701, 27255, 50147, ..., 63819, 50779, 62516])\n",
"X tensor([[0.2722, 0.5556],\n",
" [0.1183, 0.3368],\n",
" [0.2177, 0.5217],\n",
" ...,\n",
" [0.2771, 0.6748],\n",
" [0.2204, 0.5370],\n",
" [0.2714, 0.6118]])\n",
"X_sample tensor([[0.4624, 0.5219],\n",
" [0.0935, 0.6637],\n",
" [0.4168, 0.5807],\n",
" ...,\n",
" [0.4242, 0.5712],\n",
" [0.4169, 0.5806],\n",
" [0.3853, 0.5204]], grad_fn=<SigmoidBackward>)\n",
"tensor(13.1188, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.4624, 0.5219],\n",
" [0.0935, 0.6637],\n",
" [0.4168, 0.5807],\n",
" ...,\n",
" [0.4242, 0.5712],\n",
" [0.4169, 0.5806],\n",
" [0.3853, 0.5204]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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jVEs3ve7+o1haKNka/EHKcznnlaeHD/7eXbUSzBb27N2fbrsSML6rg6+dOytfoT6Ybo7K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\nIhIghbuISIAU7iIiAVK4i4gE6P8DKx6KR/p2esMAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.7048, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1818, 0.4561],\n",
" [0.2516, 0.5138],\n",
" [0.2785, 0.5089],\n",
" ...,\n",
" [0.4415, 0.4831],\n",
" [0.4264, 0.4689],\n",
" [0.2706, 0.5103]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.8293, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2432, 0.3977],\n",
" [0.1481, 0.3592],\n",
" [0.0907, 0.3706],\n",
" ...,\n",
" [0.4530, 0.4669],\n",
" [0.3286, 0.4436],\n",
" [0.3582, 0.4498]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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97bSrGJcooT2kKYJboS0JidRzd/etwNZhx24dYewF4y+ryfRshtxn4Wh/2pWMyViCe0iw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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.7566, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.4024, 0.4496],\n",
" [0.2627, 0.3826],\n",
" [0.2049, 0.3740],\n",
" ...,\n",
" [0.2136, 0.3780],\n",
" [0.2764, 0.3890],\n",
" [0.3740, 0.4310]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.7654, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2799, 0.3888],\n",
" [0.3272, 0.4126],\n",
" [0.4259, 0.4556],\n",
" ...,\n",
" [0.3372, 0.4248],\n",
" [0.3788, 0.4411],\n",
" [0.1407, 0.3027]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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4H2lXkyEK8KCZezqt756eHu/v1+A+TSHOgvlu5wreY42uoR3zj2JSgAfHzJ5z955Wx+kJ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\nu4hIgBTuIiIBUriLiATo/wMJ8ITyG4f2HAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.8126, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.3817, 0.4493],\n",
" [0.3586, 0.4384],\n",
" [0.1194, 0.3121],\n",
" ...,\n",
" [0.2538, 0.3853],\n",
" [0.0724, 0.2470],\n",
" [0.1908, 0.3478]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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DPrt1iGPPH39ZEpdQni79cet1HGd1Hugx+oM9NFNPgRu06liGpidUc2zO8qf55a8PJl3G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\nX8TozgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.6134, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.3395, 0.4409],\n",
" [0.2565, 0.4067],\n",
" [0.3140, 0.4346],\n",
" ...,\n",
" [0.2877, 0.4207],\n",
" [0.3407, 0.4463],\n",
" [0.0980, 0.3092]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.5745, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2700, 0.4392],\n",
" [0.3387, 0.4640],\n",
" [0.2071, 0.3978],\n",
" ...,\n",
" [0.1420, 0.3785],\n",
" [0.3261, 0.4599],\n",
" [0.1353, 0.3744]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.5832, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.0902, 0.3942],\n",
" [0.2890, 0.4705],\n",
" [0.1676, 0.4321],\n",
" ...,\n",
" [0.3301, 0.4802],\n",
" [0.3651, 0.4714],\n",
" [0.1352, 0.4184]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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SSUmUcF8LzDSzIyiH+oXA3m6au78HTBl6bmZPAdco2CmvYClcAQO70q6kQhss3brfK4Vi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\nSUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.5726, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1384, 0.4638],\n",
" [0.2836, 0.4924],\n",
" [0.2986, 0.4943],\n",
" ...,\n",
" [0.3438, 0.4745],\n",
" [0.0541, 0.4310],\n",
" [0.3373, 0.4984]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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lZCnEG4X3Px84g4/tXXTI84PnwBwOzGlNaSKJG/eEqpm1AQ8AfxCh7TxgHkB3d/d4P7o5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\nhbuISID+P9TXuiPKl2OqAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.5304, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.3468, 0.4850],\n",
" [0.2538, 0.4543],\n",
" [0.1807, 0.5073],\n",
" ...,\n",
" [0.2443, 0.5118],\n",
" [0.1617, 0.5057],\n",
" [0.2564, 0.5123]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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Hsvf0YbPw3uPtvP9g/FsglkvGuiXv1fCLBGfcN1TNrASsB/4kQtvlwHKAjo6O8Z5amsng\nnrDDhfgRh99JeHek9nKJmxefpWCXIEUJ9xows+H9jP7PBpwEvAd4zOp31N4OdJvZwsE3Vd19A7AB\noLOzM+sLrudPhnrlw4X4iz6F+Qf/W7LFDDJpQhtf/KMzFeoStCjhvhWYY2anUg/1y4ClA1+6+6vA\ntIH3ZvYY8BnNlmmxvk3w0HLS3pRkuBC/98h5rD38iWSLaUI3S6VImoa7ux82sxXAFupTIe929+1m\ndiPQ4+6a/JuElIdYhgvxn/l0PnJwXbLFjJJ66lJEkcbc3X0zsHnQZ9cP0/bc8ZclQGrDLEMF+T4v\n856D9yRey3jdfun7FOpSSHpCNUu+cjr8v18lesqhgjwPvfFm2krGbZoFIwWmcE9TCkMtfuy3uhCC\nfDANw4go3NNxz0J47seJnW4g0Fs1VzwrtGSAyOsU7klI5Waosanj81z789NTnk/TevNnT+W+qz+Q\ndhkimaJwb5WkpypaGda+cuxtnjajHqsp7WW6Fp6hnrrIEBTucbtjLrzys9af503vgM8Mf577Ag52\nzVcXaU7hHockxtAj7uAzlh2R8kI3SkWiU7iPR6t76YvvGtV+sCEHu3rrIqOjcB+LVoX6KPfXXFPZ\nxn1PPt90RcU8K5dg3RI9iCQyWgr3qIbYvCIWY9y+LfQbpgZ8VU+XioyZwj2KWJcBMFi8YVTDLY0q\n1Rqrv7uNfQePxFRP9rztpAk8uXpB2mWI5JrCfSRxLgfQ1g6f/+cx/WilWuO6h/rYf+hoPLVklKY2\nisRH4T6UOGe/jPKm6GCVao2VG3sJOdbffGIbfTdckHYZIkFRuA9209vhyP7xHWPa6bBifPuEV6o1\nurq3s3f/ofHVknFz3jqJH6w8N+0yRIKjcB8w3t5651XwsfWxlFKp1lj1wNMcOhrwNBi0bIBIKync\nYXy99SZPio5GpVpj3Zad1PaO828OGTehzbj1Yi3HK9JKxQ73G6aBj3HYY9BaLuNVv2m6jf2Hwp0F\noweRRJJT3HDvmjyOn41vd6QiPIjUXi5x8+Kz1FMXSVAxw/2mt4/hh0rQtSe2EkJ/CAk0pi6SpuKF\n+1dOH/34eszj6qse6CXkKevat1QkfcUK99E+aRrzuHoReuvL5nUo2EUyoDjhPtpgj2GuOhRnBkyb\nwW2XqMcukhXFCPdHVkYP9hh760WYAaNVG0WyqRjhPpr9S2MI9kq1xrXf6ePA4YAH1tHYukiWhR/u\nkac8xjMbpgjj6loyQCT7wg73r5werd04Z8OEvANSoxKwXr11kVwIN9z7NkVbrtfK4wr2Besf45mX\n9o355/NAS/GK5E+44f7wNREalcY8xl6p1rjh4e3seS3cVRs1/CKSX2GGe98mOBShNz3GMfYijKu/\n7aQJCnaRHAsz3B9a3rzN4rtGfdii7IikHrtI/pWiNDKzC8xsp5ntMrPPDfH9SjPbYWZ9ZvZDM3tX\n/KVG9MhKoMkqXJ1XjXp3pIEdkUIO9intZW6/9H0KdpEANO25m1kbcCewANgNbDWzbnff0dCsCnS6\n+2tm9mfArcClrSi4qaf+euTvy5NGvalGyMMwJYP1erJUJDhRhmXOAXa5+7MAZnY/sAg4Fu7u/qOG\n9k8Ay+IsclS8Sc/6wtubHqIIN0sBJpZLfElL8YoEKUq4TwdeaHi/G5g7QvurgEeH+sLMlgPLATo6\nOiKWOAp3jFQW9fVimgzHFGHOupbiFQlfrDdUzWwZ0Al8aKjv3X0DsAGgs7Mz/u0pXmkyX73JQmCh\nB7uWCxApjijhXgNmNryf0f/ZcczsPGA18CF3PxBPea1XlFUbtRSvSLFECfetwBwzO5V6qF8GLG1s\nYGZnA18HLnD3l2KvMopHVo78/alv/MvEmso27nvi+WZza3JNT5eKFFPTcHf3w2a2AtgCtAF3u/t2\nM7sR6HH3bmAd8CbgATMDeN7dF7aw7jdqtvLjld3HvQ15CKZksHSuNqMWKbJIY+7uvhnYPOiz6xte\nnxdzXfHqvKowDyAtm6dQF5FQn1AdZM3hP+XbG3vTLqOl2sy4fO5MBbuIAKGEe9+mYb9yCPYBpAFa\nLkBEBou0/EDmPXrt8N+FfLcULfAlIkMLo+e+f/gbo6GOsJ88sczaCzULRkSGFka4D8Mdvn0k2/d6\no5rSXqZ37R+kXYaI5EQQwzIHylOG/pwyaw9/IuFq4lcCuhaekXYZIpIjQYT76gPLOOjH/yXkoJ/A\nZw9dnVJF8Wkvl7RvqYiMWhDDMg8e/HccLB3lsyds4p32a170t3Dr4UvoPvrBtEsbM63YKCLjEUS4\nA3Qf/SDdB/Mb5o20wJeIjFcw4R6Ct500gSdXL0i7DBEJQBBj7iGYP3uqgl1EYqOee8qmT2ln1fmn\naRhGRGKlcE+BAV/VuLqItJDCPWEaVxeRJOQ+3CvVN2wKlUnlEqxbot66iCQj9+F+w8Pb0y5hRCXQ\nQ0gikrjcz5bZ89qhtEsY1pT2soJdRFKR+557Fs2fPZX7rv5A2mWISIEp3GN0Qsn4ypL3qqcuIqlT\nuMdA68CISNbkPtyntJfZuz+dcfdyyVinnrqIZFDub6h+7L3vSOW8U9rLCnYRyazc99wfefpXiZ5v\nSnuZroXa3k5Esi334Z7UkMyENuPWi9VTF5F8yH24J0FTG0Ukb3If7idPLLfsQSYt8CUieZX7G6pr\nL2zNxtHzZ0/luS9/VMEuIrmU+577RWdP55qNvbEcq2Sw/hL11EUk/3If7nE5eWKZtRdqFoyIhKHw\n4a6leEUkRJHC3cwuAL4GtAHfcPcvD/r+ROBe4N8CvwYudfdfxlvq0Ma6nrumNopIyJqGu5m1AXcC\nC4DdwFYz63b3HQ3NrgL2uPvvmNllwC3Apa0oeLB1W3aOqr3WVxeRIojScz8H2OXuzwKY2f3AIqAx\n3BcBXf2vHwTuMDNzd4+x1iG9uHd/0zblEjzzpY+2uhQRkcyIMhVyOvBCw/vd/Z8N2cbdDwOvAm8Z\nfCAzW25mPWbW8/LLL4+t4kHeOaW9aZt1S94Xy7lERPIi0Xnu7r7B3TvdvfOUU06J5Zirzj+NtpIN\n+/2yeR0aghGRwokyLFMDZja8n9H/2VBtdpvZCcBk6jdWW24guFd/dxv7Dh459vmkCW188Y/OVLCL\nSCFFCfetwBwzO5V6iF8GLB3Uphu4EngcuBj4+yTG2wdcdPZ0hbiISIOm4e7uh81sBbCF+lTIu919\nu5ndCPS4ezfwTeBvzGwX8C/U/wcgIiIpiTTP3d03A5sHfXZ9w+vfAEviLU1ERMYq9wuHiYjIGync\nRUQCpHAXEQmQwl1EJEAKdxGRACncRUQCZAk+a3T8ic1eBv4p5sNOA16J+Zh5puvxOl2L1+laHC9v\n1+Nd7t50/ZbUwr0VzKzH3TvTriMrdD1ep2vxOl2L44V6PTQsIyISIIW7iEiAQgv3DWkXkDG6Hq/T\ntXidrsXxgrweQY25i4hIXWg9dxERIafhbmYXmNlOM9tlZp8b4vsTzWxj//dPmtms5KtMRoRr8e/N\n7H+b2WEzuziNGpMU4XqsNLMdZtZnZj80s3elUWcSIlyL/2hm28ys18z+l5m9O406k9DsWjS0+7iZ\nuZnlf/aMu+fqF/U15X8B/DYwAXgaePegNp8E/qr/9WXAxrTrTvFazALOAu4FLk675gxcj98HJva/\n/rOC/9l4c8PrhcD30647rWvR3+4k4CfAE0Bn2nWP91cee+7nALvc/Vl3PwjcDywa1GYRcE//6weB\nD5vZ8But5lfTa+Huv3T3PuBoGgUmLMr1+JG7v9b/9gnq20aGKMq1+NeGt5OAUG/ARckMgJuAW4Df\nJFlcq+Qx3KcDLzS8393/2ZBt3P0w8CrwlkSqS1aUa1Eko70eVwGPtrSi9ES6Fmb252b2C+BW4C8S\nqi1pTa+Fmb0fmOnu30uysFbKY7iLjJuZLQM6gXVp15Imd7/T3WcD1wJr0q4nDWZWAtYDn067ljjl\nMdxrwMyG9zP6PxuyjZmdAEwGfp1IdcmKci2KJNL1MLPzgNXAQnc/kFBtSRvtn437gYtaWlF6ml2L\nk4D3AI+Z2S+BeUB33m+q5jHctwJzzOxUM5tA/YZp96A23cCV/a8vBv7e+++YBCbKtSiSptfDzM4G\nvk492F9KocakRLkWcxrefhR4JsH6kjTitXD3V919mrvPcvdZ1O/FLHT3nnTKjUfuwr1/DH0FsAX4\nR2CTu283sxvNbGF/s28CbzGzXcBKYNipT3kW5VqY2e+Z2W7qG5h/3cy2p1dxa0X8s7EOeBPwQP8U\nwCD/ZxjxWqwws+1m1kv9v5MrhzlcrkW8FsHRE6oiIgHKXc9dRESaU7iLiARI4S4iEiCFu4hIgBTu\nIiIBUriLiARI4S4iEiCFu4hIgP4//hpH4By8phgAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.5439, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2770, 0.5291],\n",
" [0.1396, 0.4135],\n",
" [0.2707, 0.5294],\n",
" ...,\n",
" [0.3106, 0.5270],\n",
" [0.2396, 0.5308],\n",
" [0.1804, 0.5317]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.5087, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1867, 0.5406],\n",
" [0.2480, 0.5393],\n",
" [0.1959, 0.4487],\n",
" ...,\n",
" [0.2338, 0.5400],\n",
" [0.0503, 0.3483],\n",
" [0.3471, 0.5091]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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iDzM7/Xghnpc2SrseuFGjdQlPlHCvA7ObXp87/N6IM4C3AE9a42mVXwD6zWzR6Juq7r4a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\nOzkqv+7lAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.5038, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1100, 0.5254],\n",
" [0.1464, 0.5298],\n",
" [0.0141, 0.2781],\n",
" ...,\n",
" [0.2155, 0.5364],\n",
" [0.2473, 0.5382],\n",
" [0.1962, 0.4563]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.4631, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2597, 0.4861],\n",
" [0.2813, 0.5358],\n",
" [0.2949, 0.5377],\n",
" ...,\n",
" [0.2732, 0.5346],\n",
" [0.1878, 0.5143],\n",
" [0.2490, 0.5300]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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gQWAOsA/YbGY97r5z0HGnAX8KZHtd0BMC3RgyoRppnQDzv9j8/nkGpx8OhHreRuFRqa8u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\nrkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.3715, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.3129, 0.5178],\n",
" [0.2469, 0.5183],\n",
" [0.3141, 0.5392],\n",
" ...,\n",
" [0.1800, 0.4835],\n",
" [0.2321, 0.5118],\n",
" [0.3166, 0.5255]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.3894, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2326, 0.4977],\n",
" [0.0870, 0.4147],\n",
" [0.2127, 0.4816],\n",
" ...,\n",
" [0.1386, 0.4117],\n",
" [0.3010, 0.5391],\n",
" [0.0593, 0.3872]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.3600, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1074, 0.3189],\n",
" [0.2272, 0.4798],\n",
" [0.2325, 0.4858],\n",
" ...,\n",
" [0.3041, 0.5440],\n",
" [0.2522, 0.5056],\n",
" [0.0662, 0.2393]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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mBWAN8GcRrr0auBpg1qxZ7X51NiVdcungyfUTnQGzq28JPR3opccZ6FUKdglVlHAvAzNr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\nDxXvRrK1sMYyAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.3903, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2186, 0.4549],\n",
" [0.0837, 0.4189],\n",
" [0.1403, 0.3301],\n",
" ...,\n",
" [0.1965, 0.4857],\n",
" [0.2541, 0.5098],\n",
" [0.1004, 0.4323]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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bkdbN0jhDvdpKV3XBSIgavqFqZgVgGfCxCMfOB+YDdHd3N3rq7Emi7HLUB+Di3uaeg/Js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\nBOj/A84aW5CgdNKlAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.3826, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.0445, 0.3729],\n",
" [0.2430, 0.4869],\n",
" [0.2956, 0.5558],\n",
" ...,\n",
" [0.2258, 0.5015],\n",
" [0.1990, 0.4072],\n",
" [0.2320, 0.4662]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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09OzTqkMd2EWGjynUJeEq6bmfCmx191cAzGwpMA3Y3KfdbcDdwJxAK0y6MG+Ktl8Nn18Y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\nYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.3611, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.0584, 0.3930],\n",
" [0.2778, 0.5489],\n",
" [0.2932, 0.5645],\n",
" ...,\n",
" [0.0246, 0.3289],\n",
" [0.0774, 0.4154],\n",
" [0.1831, 0.4872]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.3795, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1702, 0.4838],\n",
" [0.2463, 0.5077],\n",
" [0.2692, 0.5504],\n",
" ...,\n",
" [0.2883, 0.5712],\n",
" [0.1344, 0.4622],\n",
" [0.2477, 0.5287]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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ZH5hZP/Ax4A4z25xexcmK+GdjGXAo8NDQEsAg/zGMeC7mm9lmM9tA5e/Jx8f4\nuFyLeC6CoytURUQClLuRu4iI1KdwFxEJkMJdRCRACncRkQAp3EVEAqRwFxEJkMJdRCRACncRkQD9\nf+VPf59NPRXWAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.2781, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.0939, 0.4323],\n",
" [0.2555, 0.5485],\n",
" [0.0456, 0.3707],\n",
" ...,\n",
" [0.2312, 0.4990],\n",
" [0.2562, 0.5496],\n",
" [0.2541, 0.5418]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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YV8oPFli4cijW7cKiHjBVqEva1Qx3M+sA7gBOBbYB68xswN03jzrvQODPgcejKDQTWhXo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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.2382, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1634, 0.4849],\n",
" [0.1209, 0.4552],\n",
" [0.1499, 0.4758],\n",
" ...,\n",
" [0.1165, 0.2891],\n",
" [0.2472, 0.5426],\n",
" [0.2218, 0.5127]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
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mf5FEO+MQ4Fn8VzPbamabzWy9mb0+iXbGodmzqLnuPWbmZpb+2TPunqq/qBwY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\ndxGRDFK4i4hk0P8H9tZBu94VVJkAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.2879, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1930, 0.4920],\n",
" [0.2512, 0.5832],\n",
" [0.0020, 0.1554],\n",
" ...,\n",
" [0.2285, 0.5275],\n",
" [0.2759, 0.5831],\n",
" [0.1356, 0.3793]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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fFFor8yyOXvrkk+GaDaFdbrQSTLNDG4dDPcxt6lpx1LgCt51/mkJdMq1uuJtZB3A3MAvY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\nMlqyAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.2641, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2660, 0.6029],\n",
" [0.2751, 0.6053],\n",
" [0.1461, 0.4257],\n",
" ...,\n",
" [0.2202, 0.5570],\n",
" [0.2677, 0.6029],\n",
" [0.2215, 0.5589]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
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jLB+dtt/VwOeA1aFWmGdR3yVaPz2xG122YJ7zAd48lo513WdSLBhrPqAFviQfgoT7AuCp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\nL8AFyQyAq4HPAX+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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.2515, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1958, 0.5214],\n",
" [0.2710, 0.6088],\n",
" [0.2440, 0.5472],\n",
" ...,\n",
" [0.2793, 0.6087],\n",
" [0.2126, 0.5502],\n",
" [0.2270, 0.5268]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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4Fv/VzDab2UYze8zMjk9inHGodi1K9vuUmbmZpb97xt1T9YfimvIvAO8HOoCn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\nSAb9f4yEnGSxno1zAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.2216, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2373, 0.5357],\n",
" [0.1295, 0.4453],\n",
" [0.1814, 0.4823],\n",
" ...,\n",
" [0.1640, 0.4746],\n",
" [0.2780, 0.5951],\n",
" [0.1576, 0.4694]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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KUmk3CvcsiKnkAsC5d8Lxc4HRc0uv+eFeH2/pmUdXg+eXprUEkwNWaGqjtKlA4W5mZwBf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\nAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.2155, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2135, 0.5251],\n",
" [0.2166, 0.5318],\n",
" [0.1891, 0.4879],\n",
" ...,\n",
" [0.2504, 0.5978],\n",
" [0.2739, 0.6145],\n",
" [0.2243, 0.5488]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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zi5PoY5wCXI+FZrbNzDab2d+b2fuT6GccAlyL/2ZmW8xsk5mtN7MTk+hnHKpd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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.2324, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2486, 0.5865],\n",
" [0.1764, 0.4688],\n",
" [0.1970, 0.4575],\n",
" ...,\n",
" [0.1835, 0.4213],\n",
" [0.2642, 0.5623],\n",
" [0.1557, 0.3438]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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KMiIiGaRwFxHJoKyF+7KkO9BgdD/2073YT/fiQJm8H5mquYuISEnWRu4iIkJK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\nxWrz/yQyY3cAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.1536, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2021, 0.4512],\n",
" [0.1401, 0.2666],\n",
" [0.1967, 0.4352],\n",
" ...,\n",
" [0.2313, 0.5335],\n",
" [0.1349, 0.2509],\n",
" [0.2865, 0.5930]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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diwN0Lw6WtPvxVneve35L28I9Cma2zt37292PTqH7cYDuxQG6FwdL6/1QWUZE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\nRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.2087, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1731, 0.4475],\n",
" [0.2723, 0.5642],\n",
" [0.2512, 0.5849],\n",
" ...,\n",
" [0.0619, 0.2960],\n",
" [0.2467, 0.5758],\n",
" [0.1873, 0.4066]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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4mkCvVF0iUxvoOxw+ECCAw+5xGjbYdbNUsixQuJvZycBNQC/wXXe/rsFxnwHuA/7I3VdH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\nRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.1758, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2879, 0.5979],\n",
" [0.2562, 0.5979],\n",
" [0.2101, 0.4859],\n",
" ...,\n",
" [0.2476, 0.5158],\n",
" [0.2673, 0.5508],\n",
" [0.2312, 0.5450]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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CXUQkg7IW7uuS7kCD0f04QffiBN2Lk2XyfmSq5i4iIkVZG7mLiAgpDXczm29m\ne8xsr5ndOMLn481s/eDnm81sZvy9jEeAe/GfzexpMztqZh9Noo9xCnA/lpvZbjPbYWY/MrO3JtHP\nOAS4F//DzHaa2TYze8LM3pFEP+NQ6V6UtfuImbmZpX/2jLun6g/FPeWfA34PaAe2A+8Y0uZjwN8O\n/nwlsD7pfid4L2YC5wL3AR9Nus8NcD/+EJgw+POfNvnfjTeW/dwN/DDpfid1LwbbnQL8GHgK6Eq6\n3/X+SePI/UJgr7vvc/c+4EFg4ZA2C4F7B39+GHi/mQ0/ZDX9Kt4Ld3/B3XcAx5LoYMyC3I9/cvfD\ngy+fonhsZBYFuRf/VvZyIpDVB3BBMgPgc8BtwH/E2bmopDHcpwEvlb3eP/jeiG3c/ShwCHhTLL2L\nV5B70UyqvR9LgEcj7VFyAt0LM/u4mT0H3A78eUx9i1vFe2Fm7wRmuPsP4uxYlNIY7iJ1M7NrgC5g\nTdJ9SZK73+nus4BPAyuT7k8SzKwFuAO4Iem+hCmN4V4AZpS9nj743ohtzGwcMAl4NZbexSvIvWgm\nge6HmV0M3AR0u/vrMfUtbtX+3XgQuCzSHiWn0r04BTgbeNzMXgDeBfSm/aFqGsN9CzDbzM40s3aK\nD0x7h7TpBa4b/PmjwD/64BOTjAlyL5pJxfthZhcA36AY7K8k0Me4BLkXs8tefhD4eYz9i9OY98Ld\nD7n7VHef6e4zKT6L6Xb3rcl0NxypC/fBGvoyYBPwf4EN7r7LzG4xs+7BZt8E3mRme4HlwKhTn9Is\nyL0ws/9kZvspHmD+DTPblVyPoxXw78Ya4A3AQ4NTADP5j2HAe7HMzHaZ2TaK/51cN8rlUi3gvcgc\nrVAVEcmg1I3cRUSkMoW7iEgGKdxFRDJI4S4ikkEKdxGRDFK4i4hkkMJdRCSDFO4iIhn0/wEzhrJd\ncvqrDwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.1498, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2288, 0.5499],\n",
" [0.2429, 0.5799],\n",
" [0.2089, 0.4976],\n",
" ...,\n",
" [0.2870, 0.5851],\n",
" [0.1235, 0.3699],\n",
" [0.2484, 0.5113]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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l38tkBDgXv2Nmz5nZXjM7P40+JinA+bjGzLaa2SYz+7GZvS+NfiYhwLn4H2a2\n2cw2mtkTZnZ0Gv1MQr1zUdXuPDNzM8v+7Bl3z9QfyhuGvAy8H+gCngeOrmlzJfA3I48vBB5Iu98p\nnotZwHHASuD8tPvcAufj94CDRh7/UZv/2/i1qsdzgR+m3e+0zsVIu4OBnwJPA71p97vZP1kcuZ8E\nbHP3V9x9D3A/MK+mzTzgnpHHDwGnmdnYG61mV91z4e4/d/dNwHAaHUxYkPPxd+6+e+Tp05T3BM6j\nIOfiV1VPJwF5vQAXJDMAvgDcCvxHkp2LSxbDfTqwver5jpHXRm3j7nuBN4H3JNK7ZAU5F+0k7Pm4\nHFgba4/SE+hcmNkfm9nLwG3AnyTUt6TVPRdmdiIw091/kGTH4pTFcBdpmpldAvQCy9LuS5rc/Q53\nPwL4LLAo7f6kwcwKwHLg2rT7EqUshnsJmFn1fMbIa6O2MbMJwGTgl4n0LllBzkU7CXQ+zOx04Hpg\nrru/nVDfkhb238b9wDmx9ig99c7FwcCxwGNm9nPgZKAv6xdVsxju64HZZna4mXVRvmDaV9OmD7hs\n5PH5wE985IpJzgQ5F+2k7vkwsxOAOykH++sp9DEpQc7F7KqnHwVeSrB/SRr3XLj7m+4+1d1nufss\nytdi5rr7hnS6G43MhftIDf0qYB3wf4DV7r7FzG40s7kjzb4FvMfMtgHXAGNOfcqyIOfCzH7LzHYA\nFwB3mtmW9Hocr4D/NpYB7wIeHJkCmMsfhgHPxVVmtsXMNlL+f3LZGF+XaQHPRe7oDlURkRzK3Mhd\nRETqU7iLiOSQwl1EJIcU7iIiOaRwFxHJIYW7iEgOKdxFRHJI4S4ikkP/H+cTqSrWjtxBAAAAAElF\nTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.1262, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2703, 0.5447],\n",
" [0.2244, 0.5496],\n",
" [0.2642, 0.5309],\n",
" ...,\n",
" [0.1119, 0.3425],\n",
" [0.2295, 0.5610],\n",
" [0.2880, 0.6159]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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IZJLCXUQkgxTuIiIZpHAXEckghbuISAZZws8aHTqx2TPAryL+2BlAiNaPmafr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\nYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.1242, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2319, 0.4817],\n",
" [0.1643, 0.4076],\n",
" [0.1939, 0.4842],\n",
" ...,\n",
" [0.2432, 0.4955],\n",
" [0.1950, 0.4411],\n",
" [0.1806, 0.4505]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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me83skjTa2E4h7sdCM9tqZpvM7O/M7INptLMdQtyLPzCzzWa2wczWmtlH0mhn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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.1157, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1214, 0.2956],\n",
" [0.2386, 0.4852],\n",
" [0.2595, 0.5116],\n",
" ...,\n",
" [0.2688, 0.5255],\n",
" [0.2346, 0.5811],\n",
" [0.2696, 0.6190]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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RkQxSuIuIZFDWwn1l0g3oMnoeB+hZHKBncbBMPo9M1dxFRKQkaz13EREhpeFu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\nD+NJWIG9phqXAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.1011, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2565, 0.6144],\n",
" [0.1456, 0.3684],\n",
" [0.2152, 0.5436],\n",
" ...,\n",
" [0.2119, 0.4511],\n",
" [0.2776, 0.5396],\n",
" [0.1885, 0.4805]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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dRCSDLKnh6Gb2CvCbiE87Fai/Slh30v3YT/diP92LA6Xtfvyhu7+t0UGJhXsc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\n4S4ikkEKdxGRDFK4i4hkkMJdRCSD/j/C2YvXsgOjNwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.1111, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1720, 0.4406],\n",
" [0.2000, 0.4352],\n",
" [0.2808, 0.6297],\n",
" ...,\n",
" [0.2483, 0.6070],\n",
" [0.2203, 0.5563],\n",
" [0.2059, 0.5228]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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uxX82s41mts7Mnq1yNnJmNLoWZe0+amZuZumfPePuqfpDcdvhV4B3Af3AeuC9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\nIpJBCncRkQz6/7ueaU+PPuJEAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.0872, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2878, 0.5588],\n",
" [0.1755, 0.4491],\n",
" [0.1880, 0.4803],\n",
" ...,\n",
" [0.2366, 0.4767],\n",
" [0.2684, 0.6254],\n",
" [0.1066, 0.2570]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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yKGvhvqrTHegyuh5H6FocoWtxtExej0zV3EVEpCxrI3cRESGl4W5m883sBTPb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\nDAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.0814, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1994, 0.5055],\n",
" [0.1850, 0.4159],\n",
" [0.2324, 0.5801],\n",
" ...,\n",
" [0.2908, 0.5649],\n",
" [0.1704, 0.4330],\n",
" [0.2399, 0.5937]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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j8Qc2ew34TcxfOx0Isa9vz9D52EfnYh+di/HSdj7e6+7vbjQosXBvBzNb5+4D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\nUriLiGTQ/weGvptI5CtsBgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.0638, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2555, 0.6158],\n",
" [0.2868, 0.6371],\n",
" [0.2983, 0.5914],\n",
" ...,\n",
" [0.2974, 0.5884],\n",
" [0.2402, 0.5924],\n",
" [0.2825, 0.6348]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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UyvuRqpq7iIgUpa3nLiIiJDTczewcM3vOzLaa2ZerfD7ZzNaMf/6kmc1pfStb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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.0537, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2615, 0.6215],\n",
" [0.1536, 0.3727],\n",
" [0.3009, 0.6006],\n",
" ...,\n",
" [0.2532, 0.6118],\n",
" [0.1636, 0.4010],\n",
" [0.1398, 0.3330]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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Ts3iZnsXRsvo8VJYREckghbuISAZlLdzvTroBXUbP42V6Fi/TszhaJp9Hpmru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\nBincRUQySOEuIpJB/x9N5XY5WM3aAAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.0423, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.0812, 0.2600],\n",
" [0.2843, 0.6381],\n",
" [0.2871, 0.6395],\n",
" ...,\n",
" [0.2373, 0.5825],\n",
" [0.2623, 0.6222],\n",
" [0.2258, 0.5567]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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MXjOznWb2hTKfd5vZ2qHPN5nZ5Nq3sjYCPIt/b2Y/M7NBM7u2Hm2spQDPY4GZ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\npHAXEUkhhbuISAr9fyLdYCo+VdRQAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.0100, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2741, 0.6317],\n",
" [0.2946, 0.6361],\n",
" [0.2487, 0.6041],\n",
" ...,\n",
" [0.2587, 0.6185],\n",
" [0.1977, 0.4369],\n",
" [0.2945, 0.5792]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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QratNo24UVu3zAPb4BM4eevSo92e+bxI/WHx+/TcSiZHCXRqinqmNQVGCPRjq9QoG+miz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\nAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.0641, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2953, 0.5922],\n",
" [0.2649, 0.6257],\n",
" [0.2190, 0.5423],\n",
" ...,\n",
" [0.2910, 0.5641],\n",
" [0.1547, 0.3722],\n",
" [0.2404, 0.5904]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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tpb8AknXKRQpzEelYgfa5u/ujwKNV732h4uffAxfG2zUREYkq9fXcRUTkcAp3\nEZEMUriLiGSQwl1EJIMU7iIiGaRwFxHJIIW7iEgGWQsfJD30wma/Bv4l5q+dSwuKlaWI7sdBuhcH\n6V4cKm334y3u/sZ6jRIL92Yws23u3pd0P9qF7sdBuhcH6V4cKqv3Q9MyIiIZpHAXEcmgrIX7uqQ7\n0GZ0Pw7SvThI9+JQmbwfmZpzFxGRkqyN3EVEhJSGu5mdY2ZPm9lOM/vcNJ/PNrONk58/YWaLWt/L\n1ghwL/6Dmf3MzA6Y2QVJ9LGVAtyP681sh5ltN7MfmNlbkuhnKwS4F//FzIbMbNDMNpvZ25PoZyvU\nuxcV7T5mZm5m6d894+6p+kXpwJBngbcCPcCTwNur2lwNfGXy50uAjUn3O8F7sQg4BdgAXJB0n9vg\nfvwhcMTkz5/u8D8bf1Dxcz/wT0n3O6l7MdnudcCPgC1AX9L9bvRXGkfupwE73X2Xu48C9wPnVrU5\nF/jm5M8PAR80MyN76t4Ld/+lu28HJpLoYIsFuR8/dPf9ky+3UDoTOIuC3Iv/W/HySCCrC3BBMgPg\nr4AvAb9vZeeaJY3hPg94vuL1nsn3pm3j7geAl4E3tKR3rRXkXnSSsPfjKuC7Te1RcgLdCzP7UzN7\nFrgd+LMW9a3V6t4LM3sXsMDdv9PKjjVTGsNdpGFmdjnQB6xJui9Jcve73P1Y4C+AlUn3JwlmlgPW\nAjck3Zc4pTHci8CCitfzJ9+bto2ZzQKOAn7Tkt61VpB70UkC3Q8zOxO4Ceh391db1LdWC/tn437g\nvKb2KDn17sXrgJOAx8zsl8B7gYG0L6qmMdy3AkvMbLGZ9VBaMB2oajMAXDn58wXAP/vkiknGBLkX\nnaTu/TCzU4GvUgr2FxPoY6sEuRdLKl5+GHimhf1rpRnvhbu/7O5z3X2Ruy+itBbT7+7bkuluPFIX\n7pNz6NcAm4D/DTzg7sNmdouZ9U82+zrwBjPbCVwP1Nz6lGZB7oWZvcfM9gAXAl81s+HketxcAf9s\nrAFeCzw4uQUwk38ZBrwX15jZsJkNUvr/5MoaX5dqAe9F5ugJVRGRDErdyF1EROpTuIuIZJDCXUQk\ngxTuIiIZpHAXEckghbuISAYp3EVEMkjhLiKSQf8fig2OfA2mqHoAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.0209, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2032, 0.5077],\n",
" [0.1512, 0.3685],\n",
" [0.1968, 0.4918],\n",
" ...,\n",
" [0.2954, 0.6289],\n",
" [0.2865, 0.6423],\n",
" [0.1793, 0.4466]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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THkCH0fU4TtfiOF2LE+XyeuSq5i4iIhV5m7mLiAgZDXczu8LMdpjZTjP7wji/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\nAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.0426, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2299, 0.5757],\n",
" [0.2500, 0.6125],\n",
" [0.2934, 0.6044],\n",
" ...,\n",
" [0.2244, 0.5636],\n",
" [0.0915, 0.1990],\n",
" [0.1860, 0.4695]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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kcBcRySGFu4hIDjV9iCm2C5v9Evh5xF87A9Bhpnvpfuyle7GX7sW+snY/PuLu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\nhbuISA4p3EVEckjhLiKSQ/8fyOG921KgsPgAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9879, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2898, 0.5954],\n",
" [0.2462, 0.6086],\n",
" [0.1918, 0.4870],\n",
" ...,\n",
" [0.2668, 0.5390],\n",
" [0.1381, 0.3410],\n",
" [0.2002, 0.5077]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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Z9919qFG7QDV3d98AbKh67dMVj38NXBK2kyIiEo/ULz8gIiKvpHAXEckghbuI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\n4S4ikkEKdxGRDFK4i4hkkMJdRCSD/j9V0RJ5VcJGfAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9648, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2759, 0.6421],\n",
" [0.1410, 0.3824],\n",
" [0.2878, 0.6340],\n",
" ...,\n",
" [0.1509, 0.3771],\n",
" [0.1559, 0.3910],\n",
" [0.2388, 0.5084]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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p3EVEMijQQ0wdubDZr4FfRnza6cS0WFlK6H4cpntxmO7FRGm7H3/k7k3Xb0ks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\n4S4ikkEKdxGRDPr/2Rb69iA3DBIAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9994, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2768, 0.5631],\n",
" [0.2612, 0.6287],\n",
" [0.2722, 0.6388],\n",
" ...,\n",
" [0.2330, 0.5830],\n",
" [0.2879, 0.6064],\n",
" [0.1858, 0.4480]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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/KMw+6XjuvvysYnif+40je+jnfkOhLiKpFKTnXgCmlT2fOvJatWP2mFk3cCzw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\ng+lDhJgAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(12.0028, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1319, 0.3740],\n",
" [0.2018, 0.5020],\n",
" [0.2188, 0.5436],\n",
" ...,\n",
" [0.2894, 0.6304],\n",
" [0.2641, 0.6318],\n",
" [0.2503, 0.6141]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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ZpHAXEckghbuISAYp3EVEMkjhLiKSQaktYjKzXwG/iPhrpwAh9/XNNN2Pw3Qv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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9836, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2422, 0.5195],\n",
" [0.2243, 0.4978],\n",
" [0.2827, 0.6488],\n",
" ...,\n",
" [0.2849, 0.6030],\n",
" [0.2883, 0.6347],\n",
" [0.2794, 0.6489]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9712, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1757, 0.4338],\n",
" [0.2817, 0.5825],\n",
" [0.2203, 0.4923],\n",
" ...,\n",
" [0.2723, 0.6408],\n",
" [0.2552, 0.5378],\n",
" [0.2862, 0.6190]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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XRESkVZl/QlVERF5O4S4ikkMKdxGRHFK4i4jkkMJdRCSHFO4iIjlkKT9rdOSL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\nzxu1AAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9467, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2861, 0.6393],\n",
" [0.1403, 0.3206],\n",
" [0.2309, 0.5651],\n",
" ...,\n",
" [0.0754, 0.2642],\n",
" [0.2871, 0.6269],\n",
" [0.2465, 0.6024]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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zF8xsm5l9rsb7481s1dj7681sRvKjTEaAc/EfzeyfzWy/mV3YiTEmKcD5uMHM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\nMkjhLiKSQf8feC2xMWgLXDAAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9662, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2449, 0.6020],\n",
" [0.0972, 0.2076],\n",
" [0.2797, 0.5818],\n",
" ...,\n",
" [0.2332, 0.5756],\n",
" [0.2856, 0.6288],\n",
" [0.1924, 0.4770]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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DNNqZhAD34n+Y2VYz22xm683sQ2m0MwmN7kXFcZ8xMzezzh894+4d9YfShiE7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\ni4hkkMJdRCSD/j/sprMQUBXFzAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9512, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1346, 0.3301],\n",
" [0.2315, 0.5746],\n",
" [0.2579, 0.6243],\n",
" ...,\n",
" [0.2328, 0.5037],\n",
" [0.2708, 0.5636],\n",
" [0.2774, 0.6390]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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UlhERySCFu4hIBmUt3Fcl3YAuo/txgu7FCboXJ8vk/chUzV1ERMqy1nMXERFS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\nRDLo/wNwQfIHPYkfjgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9359, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2038, 0.4594],\n",
" [0.2138, 0.5344],\n",
" [0.2016, 0.4562],\n",
" ...,\n",
" [0.2825, 0.6230],\n",
" [0.2373, 0.5868],\n",
" [0.2137, 0.4735]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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bod65qDjuU2bmZpb+2TPunqo/jGwY8jzwbqAb+DnwgapjbgL+cfTnq4E1SY87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\nAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9452, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2187, 0.5411],\n",
" [0.1069, 0.2521],\n",
" [0.2651, 0.6291],\n",
" ...,\n",
" [0.2011, 0.4520],\n",
" [0.2656, 0.6296],\n",
" [0.2802, 0.6129]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
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grIX7mqQb0Gd0Pw7TvThM9+JImbwfmaq5i4hIRdZ67iIiQkrD3cwuNrPHzGy3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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9400, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2811, 0.6207],\n",
" [0.2342, 0.5693],\n",
" [0.2424, 0.5877],\n",
" ...,\n",
" [0.0957, 0.2112],\n",
" [0.2365, 0.5746],\n",
" [0.1450, 0.3593]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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NNNBZr2umaVjlpZcw9XRQTV3an8JdItVob/3pbD9nWgFoXrDX20svUbBLEijcJRL1zi4t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\nwl1EJIX+PzrknwIrwPSOAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9618, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2585, 0.6121],\n",
" [0.1842, 0.4233],\n",
" [0.2517, 0.6004],\n",
" ...,\n",
" [0.2692, 0.6274],\n",
" [0.1843, 0.4455],\n",
" [0.2568, 0.6094]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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MU116CVNPr8gZLLtc68BIuijcpW6FYon5KzcyENP5KrNh4g71ekovFfkcLL1MwS7pEyjc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\nCncRkQxSuIuIZJDCXUQkg/4/ZJiuKBmIfSwAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9231, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2777, 0.5906],\n",
" [0.2457, 0.5837],\n",
" [0.2790, 0.6325],\n",
" ...,\n",
" [0.2565, 0.6050],\n",
" [0.1477, 0.3645],\n",
" [0.0841, 0.2491]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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CvWtR0+7PzMzNLPuzZ9w9U3+orCn/PPB7QBfwNPCuEW1uAr48/PPVwIZm97uJ\n12IWcDawDrii2X1ugevxH4DJwz//ZZv/2zih5ude4LvN7nezrsVwu+OB7wNPAT3N7nfcP1kcuZ8H\n7HH3ve4+ADwIXDaizWXA/cM/Pwx80MysgX1slLrXwt1/7u67gKFmdLDBglyPf3H3N4dfPkVl28g8\nCnItflPzcgqQ1xtwQTID4G+BLwD/2sjOpSWL4T4DeLHm9b7h90Zt4+6HgNeBtzekd40V5Fq0k7DX\n4wbgsVR71DyBroWZ/ZWZPQ/cCfzXBvWt0epeCzM7F5jp7v/YyI6lKYvhLhKbmV0L9ACrmt2XZnL3\ne9z9dOAzwNJm96cZzKwDWA3c2uy+JCmL4V4GZta8PnX4vVHbmNkE4G3ArxvSu8YKci3aSaDrYWYX\nA0uAXnd/q0F9a7Sw/zYeBC5PtUfNU+9aHA+8G3jCzH4OnA/0Zf2mahbDfTsw28xOM7MuKjdM+0a0\n6QOuH/75CuB7PnzHJGeCXIt2Uvd6mNk5wFeoBPvLTehjowS5FrNrXv4J8FwD+9dI414Ld3/d3ae7\n+yx3n0XlXkyvu+9oTneTkblwH66h3wxsBv43sNHdd5vZ7WbWO9zsa8DbzWwPsAgYc+pTlgW5Fmb2\nPjPbR2UD86+Y2e7m9ThdAf9trAKOAx4angKYy1+GAa/FzWa228x2Uvnv5PoxDpdpAa9F7ugJVRGR\nHMrcyF1EROpTuIuI5JDCXUQkhxTuIiI5pHAXEckhhbuISA4p3EVEckjhLiKSQ/8f+lSDO4coRYkA\nAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9318, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2802, 0.6214],\n",
" [0.2322, 0.5018],\n",
" [0.2625, 0.6130],\n",
" ...,\n",
" [0.2480, 0.5263],\n",
" [0.2772, 0.5924],\n",
" [0.1374, 0.3525]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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4m1kX8AAwF9gLbDGzfnffUXXcccDHgc3NaKgkr9HdkGqJo7deDvWDnuOMwUcbas+Uni7u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\nEckghbuISAYp3EVEMkjhLiKSQf8fy3h7svTVi1cAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9172, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2720, 0.6276],\n",
" [0.2515, 0.5353],\n",
" [0.2276, 0.5463],\n",
" ...,\n",
" [0.1991, 0.4863],\n",
" [0.2447, 0.5236],\n",
" [0.2302, 0.5520]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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YmkZDpfXiLMXb6Imea3m3HQSSWWY3qV46QHfJWKN9S6UAgvTczwT2uvs+ADN7ADgP2DPu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\nKdxFRApI4S4iUkAKdxGRAvr/gdeKLrfimmsAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9079, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2428, 0.5798],\n",
" [0.2747, 0.5825],\n",
" [0.2441, 0.5823],\n",
" ...,\n",
" [0.2771, 0.6162],\n",
" [0.1975, 0.4568],\n",
" [0.2276, 0.5497]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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g4VaPu4XnYirwEeB+4JJWj7kNzscfAUcPPv6LDv+38d7A417gb1s97ladi8Hj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\nRCSH/j/YzsRLJ+K3UAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9274, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2354, 0.5653],\n",
" [0.1424, 0.3703],\n",
" [0.1548, 0.3997],\n",
" ...,\n",
" [0.1104, 0.2893],\n",
" [0.2366, 0.5160],\n",
" [0.2666, 0.5681]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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H3guUgKeAI5raXAL848TP5wGr0u53ivdiAXAMcBdwVtp97oL78SfAXhM//1WP\n/7vxzoafB4F/Trvfad2LiXZ7Az8F1gEDafe70z9ZHLkfB2x29xfcfQy4Fzijqc0ZwJ0TPz8AfNTM\nLME+JqXlvXD3X7r7RmB3Gh1MWJD78WN3f2Pi5TpqZwLnUZB78X8bXs4C8joBFyQzAP4OuB74fZKd\ni0sWw30u8FLD660T703axt13Aq8B706kd8kKci96Sdj7cTHwcKw9Sk+ge2Fmf21mzwM3AH+bUN+S\n1vJemNmxwDx3/2GSHYtTFsNdpGNmdiEwAAyl3Zc0ufst7n4IcCWwPO3+pMHMCsCNwBVp9yVKWQz3\nKjCv4fVBE+9N2sbMZgDvAn6TSO+SFeRe9JJA98PMTgaWAYPuviOhviUt7L8b9wJnxtqj9LS6F3sD\nRwE/MbNfAscDw1mfVM1iuD8BLDSzg82sRG3CdLipzTDw6YmfzwL+zSdmTHImyL3oJS3vh5l9EPgW\ntWB/JYU+JiXIvVjY8PJjwHMJ9i9J094Ld3/N3ee4+wJ3X0BtLmbQ3den091oZC7cJ2rolwJrgP8N\n3OfuI2Z2jZkNTjT7NvBuM9sMXA5MufQpy4LcCzP7kJltBc4GvmVmI+n1OF4B/90YAt4B3D+xBDCX\nfxkGvBeXmtmImW2g9t/Jp6e4XKYFvBe5oydURURyKHMjdxERaU3hLiKSQwp3EZEcUriLiOSQwl1E\nJIcU7iIiOaRwFxHJIYW7iEgO/X8ECIbDwGGtaAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9167, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2797, 0.6265],\n",
" [0.1291, 0.3382],\n",
" [0.2728, 0.5813],\n",
" ...,\n",
" [0.2167, 0.4881],\n",
" [0.2315, 0.5095],\n",
" [0.2774, 0.6305]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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fNTOLsY9xqXkt3P0X7r4VGEqigzELcj3+wd0Pjjx8geEzgbMoyLX414qHk4Gs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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9132, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1939, 0.4784],\n",
" [0.2643, 0.5644],\n",
" [0.1426, 0.3669],\n",
" ...,\n",
" [0.2674, 0.5710],\n",
" [0.2366, 0.5600],\n",
" [0.2759, 0.6136]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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TTuLhT3wo9u8VSVqQmfv5wA533wlgZo8AlwLbm477LHA3sCjWEUrqojT4qotrtt7pUFfX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\nRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9379, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2768, 0.6265],\n",
" [0.2594, 0.5544],\n",
" [0.2299, 0.5049],\n",
" ...,\n",
" [0.2055, 0.4680],\n",
" [0.2763, 0.6256],\n",
" [0.2702, 0.6115]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9246, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2601, 0.5927],\n",
" [0.2775, 0.6181],\n",
" [0.2732, 0.6128],\n",
" ...,\n",
" [0.2613, 0.5944],\n",
" [0.1686, 0.4074],\n",
" [0.1059, 0.2676]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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KfUtb2H8bDwFXJtqj1pnsWpwAnAM8aWY/AS4C+rN+UzWL4b4VmGtmp5lZidoN\n0/5RbfqBm0d+vhb4Rx+5Y5IzQa5FJ5n0epjZ+cCXqQX7qy3oY1qCXIu5DQ9/H/hRiv1L04TXwt1f\nc/eZ7j7H3edQuxezwN23taa78chcuI/U0JcCm4H/Czzs7gNmdoeZLRhp9lXgbWa2B1gGjDv1KcuC\nXAsz+y0z2wdcB3zZzAZa1+NkBfy3sQZ4C/DIyBTAXP4yDHgtlprZgJltp/bfyc3jfFymBbwWuaMV\nqiIiOZS5kbuIiExO4S4ikkMKdxGRHFK4i4jkkMJdRCSHFO4iIjmkcBcRySGFu4hIDv1/RePTUhrA\nXQ0AAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9265, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1443, 0.3618],\n",
" [0.1059, 0.2682],\n",
" [0.2461, 0.5648],\n",
" ...,\n",
" [0.1878, 0.4556],\n",
" [0.2810, 0.6290],\n",
" [0.2365, 0.5127]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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ZyujSFeVatJNI18PMzgVuAma7+56Uxpa2Rv/deBC4KNERZWe0a3EUcArwrJn9\nFPgo0Jf3m6p5DPe1wHQzO8HMuqneMO0bckwfcPXgz5cA/+qDd0wKJsq1aCejXg8z+zDwdarB/mYG\nY0xLlGsxve7lHwGvpDi+NB3xWrj7W+4+2d2nufs0qvdiZrv7umyGG0buwn2whn4dsBr4v8DD7r7Z\nzG41s9mDh90PvNvMtgILgBGXPuVZlGthZh8xs+1UNzD/upltzm7EyYr478ZS4B3AI4NLAAv5l2HE\na3GdmW02s/VU/zu5eoTT5VrEa1E4ekJVRKSAcjdzFxGR0SncRUQKSOEuIlJACncRkQJSuIuIFJDC\nXUSkgBTuIiIFpHAXESmg/w94MrFx03xyVwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9522, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2499, 0.5705],\n",
" [0.1126, 0.2901],\n",
" [0.2731, 0.6076],\n",
" ...,\n",
" [0.2747, 0.6041],\n",
" [0.2591, 0.5864],\n",
" [0.2552, 0.5797]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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bzKzX3XdVtTsW+DtgcxwdleSFHa1HvR1vOdQb3fNlJAp2yYogI/fzgN3uvgfAzB4H5gK7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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9234, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2166, 0.5116],\n",
" [0.2780, 0.6333],\n",
" [0.2553, 0.5789],\n",
" ...,\n",
" [0.1774, 0.4389],\n",
" [0.1744, 0.4155],\n",
" [0.2606, 0.5878]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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p1vjMk9s5cKi9EsxPyjcxyeodNFEEe1TtjM3UBSNFEyTcpwIvN73eC8xsPsDMzgemufs/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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9054, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.1342, 0.3454],\n",
" [0.1939, 0.4485],\n",
" [0.2088, 0.4729],\n",
" ...,\n",
" [0.0551, 0.1874],\n",
" [0.2817, 0.6252],\n",
" [0.2273, 0.5019]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9254, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2689, 0.5801],\n",
" [0.2248, 0.4994],\n",
" [0.2390, 0.5218],\n",
" ...,\n",
" [0.2436, 0.5583],\n",
" [0.2755, 0.6160],\n",
" [0.2550, 0.5771]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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A/cCySHsoqWt3c6+Hur+GEU+oDzt8OMJQ146NUjRBwn0m8FrT+/3A+c0NzOxc4FR3/xsz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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9157, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2602, 0.5840],\n",
" [0.2094, 0.4763],\n",
" [0.1714, 0.4134],\n",
" ...,\n",
" [0.2352, 0.5432],\n",
" [0.2860, 0.6306],\n",
" [0.0161, 0.0431]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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Bp/PRoVVhvhiVNkq+NBLu04H9Nc8PAHNrLzCzDwAz3P1vzUzhniOtHES9vvtefqdrFxA+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\nXUQkhxTuIiI5pHAXEcmh/w8/pAPL9FJAvwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9080, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2481, 0.5414],\n",
" [0.1630, 0.3999],\n",
" [0.0314, 0.0896],\n",
" ...,\n",
" [0.1962, 0.4785],\n",
" [0.2597, 0.5644],\n",
" [0.2845, 0.6363]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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PbtjJiEcfWP/JwDWcYLUVM0mEeqeFvMaj3aVSFFF67ucA2939JQAzewi4ENg26rq/BL4E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\nfwGH9sYAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9233, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2338, 0.5393],\n",
" [0.2737, 0.6145],\n",
" [0.2696, 0.5876],\n",
" ...,\n",
" [0.2861, 0.6234],\n",
" [0.2245, 0.5032],\n",
" [0.2796, 0.6113]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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96nr1uEO9WDB6rrlIoS65ECTcZwGH6h4fBubVNzCzdwOz3f27ZqZwz5FmDqN+tHMV51kF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\nIpJD/x+FDwb5I57IoAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.8797, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2412, 0.5326],\n",
" [0.2723, 0.6078],\n",
" [0.2559, 0.5611],\n",
" ...,\n",
" [0.2525, 0.5544],\n",
" [0.1593, 0.4069],\n",
" [0.0738, 0.2360]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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RHFK4i4jkkMJdRCSH/j9CTx0FAaSoWwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"tensor(11.9219, grad_fn=<AddBackward0>)\n",
"X_sample tensor([[0.2843, 0.6388],\n",
" [0.0643, 0.1824],\n",
" [0.0944, 0.2793],\n",
" ...,\n",
" [0.2618, 0.5813],\n",
" [0.2399, 0.5459],\n",
" [0.1999, 0.4673]])\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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