GANs-Public/C3W2_SRGAN_(Optional).ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/https-deeplearning-ai/GANs-Public/blob/master/C3W2_SRGAN_(Optional).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1czVdIlqnImH"
      },
      "source": [
        "# Super-resolution GAN (SRGAN)\n",
        "\n",
        "*Please note that this is an optional notebook meant to introduce more advanced concepts. If you’re up for a challenge, take a look and don’t worry if you can’t follow everything. There is no code to implement—only some cool code for you to learn and run!*\n",
        "\n",
        "It is recommended that you should already be familiar with:\n",
        " - Residual blocks, from [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) (He et al. 2015)\n",
        " - Perceptual loss, from [Perceptual Losses for Real-Time Style Transfer and Super-Resolution](https://arxiv.org/abs/1603.08155) (Johnson et al. 2016)\n",
        " - VGG architecture, from [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://arxiv.org/abs/1409.1556) (Simonyan et al. 2015)\n",
        "\n",
        "### Goals\n",
        "\n",
        "In this notebook, you will learn about Super-Resolution GAN (SRGAN), a GAN that enhances the resolution of images by 4x, proposed in [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network](https://arxiv.org/abs/1609.04802) (Ledig et al. 2017). You will also implement the architecture and training in full and be able to train it on the CIFAR dataset.\n",
        "\n",
        "### Background\n",
        "\n",
        "The authors first train a super-resolution residual network (SRResNet) with standard pixel-wise loss that achieves state-of-the-art metrics. They then insert this as the generator in the SRGAN framework, which is trained with a combination of pixel-wise, perceptual, and adversarial losses."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_SeMjdGIICPB"
      },
      "source": [
        "## SRGAN Submodules\n",
        "\n",
        "Before jumping into SRGAN, let's first take a look at some components that will be useful later."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s9zFUlwLIOcC"
      },
      "source": [
        "### Parametric ReLU (PReLU)\n",
        "\n",
        "As you already know, ReLU is one of the simplest activation functions that can be described as\n",
        "\n",
        "\\begin{align*}\n",
        "    x_{\\text{ReLU}} := \\max(0, x),\n",
        "\\end{align*}\n",
        "\n",
        "where negative values of $x$ become thresholded at $0$. However, this stops gradient through these negative values, which can hinder training. The authors of [Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification](https://arxiv.org/abs/1502.01852) addressed this by introducing a more general ReLU by scaling negative values by some constant $a > 0$:\n",
        "\n",
        "\\begin{align*}\n",
        "    x_{\\text{PReLU}} := \\max(0, x) + a * \\min(0, x).\n",
        "\\end{align*}\n",
        "\n",
        "Conveniently, this is implemented in Pytorch as [torch.nn.PReLU](https://pytorch.org/docs/stable/generated/torch.nn.PReLU.html)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fB1Vq8ps7Bfd"
      },
      "source": [
        "### Residual Blocks\n",
        "\n",
        "The residual block, which is relevant in many state-of-the-art computer vision models, is used in all parts of SRGAN and is similar to the ones used in Pix2PixHD (see optional notebook). If you're not familiar with residual blocks, please take a look [here](https://paperswithcode.com/method/residual-block). Now, you'll start by first implementing a basic residual block."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GHD_wif07f4b"
      },
      "source": [
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "\n",
        "class ResidualBlock(nn.Module):\n",
        "    '''\n",
        "    ResidualBlock Class\n",
        "    Values\n",
        "        channels: the number of channels throughout the residual block, a scalar\n",
        "    '''\n",
        "\n",
        "    def __init__(self, channels):\n",
        "        super().__init__()\n",
        "\n",
        "        self.layers = nn.Sequential(\n",
        "            nn.Conv2d(channels, channels, kernel_size=3, padding=1),\n",
        "            nn.BatchNorm2d(channels),\n",
        "            nn.PReLU(),\n",
        "\n",
        "            nn.Conv2d(channels, channels, kernel_size=3, padding=1),\n",
        "            nn.BatchNorm2d(channels),\n",
        "        )\n",
        "\n",
        "    def forward(self, x):\n",
        "        return x + self.layers(x)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cCBCYvalE04U"
      },
      "source": [
        "###  PixelShuffle\n",
        "\n",
        "Proposed in [Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network](https://arxiv.org/abs/1609.05158) (Shi et al. 2016), PixelShuffle, also called sub-pixel convolution, is another way to upsample an image.\n",
        "\n",
        "PixelShuffle simply reshapes a $r^2C\\ x\\ H\\ x\\ W$ tensor into a $C\\ x\\ rH\\ x\\ rW$ tensor, essentially trading channel information for spatial information. Instead of convolving with stride $1/r$ as in deconvolution, the authors think about the weights in the kernel as being spaced $1/r$ pixels apart. When sliding this kernel over an input, the weights that fall between pixels aren't activated and don't need need to be calculated. The total number of activation patterns is thus increased by a factor of $r^2$. This operation is illustrated in the figure below.\n",
        "\n",
        "Don't worry if this is confusing! The algorithm is conveniently implemented as `torch.nn.PixelShuffle` in PyTorch, so as long as you have a general idea of how this works, you're set.\n",
        "\n",
        "> ![Efficient Sub-pixel CNN](https://github.com/https-deeplearning-ai/GANs-Public/blob/master/SRGAN-PixelShuffle.png?raw=true)\n",
        "*Efficient sub-pixel CNN, taken from Figure 1 of [Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network](https://arxiv.org/abs/1609.05158) (Shi et al. 2016). The PixelShuffle operation (also known as sub-pixel convolution) is shown as the last step on the right.*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bDSSM7SJJgon"
      },
      "source": [
        "## SRGAN Parts\n",
        "\n",
        "Now that you've learned about the various SRGAN submodules, you can now use them to build the generator and discriminator!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vZ41VxyyIaes"
      },
      "source": [
        "### Generator (SRResNet)\n",
        "\n",
        "The super-resolution residual network (SRResNet) and the generator are the same thing. The generator network architecture is actually quite simple - just a bunch of convolutional layers, residual blocks, and pixel shuffling layers!\n",
        "\n",
        "> ![SRGAN Generator](https://github.com/https-deeplearning-ai/GANs-Public/blob/master/SRGAN-Generator.png?raw=true)\n",
        "*SRGAN Generator, taken from Figure 4 of [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network](https://arxiv.org/abs/1609.04802) (Ledig et al. 2017).*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EXqRw0f7KO81"
      },
      "source": [
        "class Generator(nn.Module):\n",
        "    '''\n",
        "    Generator Class\n",
        "    Values:\n",
        "        base_channels: number of channels throughout the generator, a scalar\n",
        "        n_ps_blocks: number of PixelShuffle blocks, a scalar\n",
        "        n_res_blocks: number of residual blocks, a scalar\n",
        "    '''\n",
        "\n",
        "    def __init__(self, base_channels=64, n_ps_blocks=2, n_res_blocks=16):\n",
        "        super().__init__()\n",
        "        # Input layer\n",
        "        self.in_layer = nn.Sequential(\n",
        "            nn.Conv2d(3, base_channels, kernel_size=9, padding=4),\n",
        "            nn.PReLU(),\n",
        "        )\n",
        "\n",
        "        # Residual blocks\n",
        "        res_blocks = []\n",
        "        for _ in range(n_res_blocks):\n",
        "            res_blocks += [ResidualBlock(base_channels)]\n",
        "\n",
        "        res_blocks += [\n",
        "            nn.Conv2d(base_channels, base_channels, kernel_size=3, padding=1),\n",
        "            nn.BatchNorm2d(base_channels),\n",
        "        ]\n",
        "        self.res_blocks = nn.Sequential(*res_blocks)\n",
        "\n",
        "        # PixelShuffle blocks\n",
        "        ps_blocks = []\n",
        "        for _ in range(n_ps_blocks):\n",
        "            ps_blocks += [\n",
        "                nn.Conv2d(base_channels, 4 * base_channels, kernel_size=3, padding=1),\n",
        "                nn.PixelShuffle(2),\n",
        "                nn.PReLU(),\n",
        "            ]\n",
        "        self.ps_blocks = nn.Sequential(*ps_blocks)\n",
        "\n",
        "        # Output layer\n",
        "        self.out_layer = nn.Sequential(\n",
        "            nn.Conv2d(base_channels, 3, kernel_size=9, padding=4),\n",
        "            nn.Tanh(),\n",
        "        )\n",
        "\n",
        "    def forward(self, x):\n",
        "        x_res = self.in_layer(x)\n",
        "        x = x_res + self.res_blocks(x_res)\n",
        "        x = self.ps_blocks(x)\n",
        "        x = self.out_layer(x)\n",
        "        return x"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mbpiSiWpNjtR"
      },
      "source": [
        "### Discriminator\n",
        "\n",
        "The discriminator architecture is also relatively straightforward, just one big sequential model - see the diagram below for reference!\n",
        "\n",
        "![SRGAN Generator](https://github.com/https-deeplearning-ai/GANs-Public/blob/master/SRGAN-Discriminator.png?raw=true)\n",
        "*SRGAN Discriminator, taken from Figure 4 of [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network](https://arxiv.org/abs/1609.04802) (Ledig et al. 2017).*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cpyEsLi-OQj4"
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      "source": [
        "class Discriminator(nn.Module):\n",
        "    '''\n",
        "    Discriminator Class\n",
        "    Values:\n",
        "        base_channels: number of channels in first convolutional layer, a scalar\n",
        "        n_blocks: number of convolutional blocks, a scalar\n",
        "    '''\n",
        "\n",
        "    def __init__(self, base_channels=64, n_blocks=3):\n",
        "        super().__init__()\n",
        "        self.blocks = [\n",
        "            nn.Conv2d(3, base_channels, kernel_size=3, padding=1),\n",
        "            nn.LeakyReLU(0.2, inplace=True),\n",
        "\n",
        "            nn.Conv2d(base_channels, base_channels, kernel_size=3, padding=1, stride=2),\n",
        "            nn.BatchNorm2d(base_channels),\n",
        "            nn.LeakyReLU(0.2, inplace=True),\n",
        "        ]\n",
        "\n",
        "        cur_channels = base_channels\n",
        "        for i in range(n_blocks):\n",
        "            self.blocks += [\n",
        "                nn.Conv2d(cur_channels, 2 * cur_channels, kernel_size=3, padding=1),\n",
        "                nn.BatchNorm2d(2 * cur_channels),\n",
        "                nn.LeakyReLU(0.2, inplace=True),\n",
        "\n",
        "                nn.Conv2d(2 * cur_channels, 2 * cur_channels, kernel_size=3, padding=1, stride=2),\n",
        "                nn.BatchNorm2d(2 * cur_channels),\n",
        "                nn.LeakyReLU(0.2, inplace=True),\n",
        "            ]\n",
        "            cur_channels *= 2\n",
        "\n",
        "        self.blocks += [\n",
        "            # You can replicate nn.Linear with pointwise nn.Conv2d\n",
        "            nn.AdaptiveAvgPool2d(1),\n",
        "            nn.Conv2d(cur_channels, 2 * cur_channels, kernel_size=1, padding=0),\n",
        "            nn.LeakyReLU(0.2, inplace=True),\n",
        "            nn.Conv2d(2 * cur_channels, 1, kernel_size=1, padding=0),\n",
        "\n",
        "            # Apply sigmoid if necessary in loss function for stability\n",
        "            nn.Flatten(),\n",
        "        ]\n",
        "\n",
        "        self.layers = nn.Sequential(*self.blocks)\n",
        "\n",
        "    def forward(self, x):\n",
        "        return self.layers(x)"
      ],
      "execution_count": null,
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      "source": [
        "## Loss Functions\n",
        "\n",
        "The authors formulate the perceptual loss as a weighted sum of content loss (based on the VGG19 network) and adversarial loss.\n",
        "\n",
        "\\begin{align*}\n",
        "    \\mathcal{L} &= \\mathcal{L}_{VGG} + 10^{-3}\\mathcal{L}_{ADV}\n",
        "\\end{align*}\n",
        "\n",
        "**Content Loss**\n",
        "\n",
        "Previous approaches have used MSE loss for content loss, but this objective function tends to produce blurry images. To address this, they add an extra MSE loss term on VGG19 feature maps. So for feature map $\\phi_{5,4}$ (the feature map after the 4th convolution before the 5th max-pooling layer) from the VGG19 network,\n",
        "\n",
        "\\begin{align*}\n",
        "    \\mathcal{L}_{VGG} &= \\left|\\left|\\phi_{5,4}(I^{\\text{HR}}) - \\phi_{5,4}(G(I^{\\text{LR}}))\\right|\\right|_2^2\n",
        "\\end{align*}\n",
        "\n",
        "where $I^{\\text{HR}}$ is the original high-resolution image and $I^{\\text{LR}}$ is the corresponding low-resolution image.\n",
        "\n",
        "**Adversarial Loss**\n",
        "\n",
        "You should already be familiar with adversarial loss, which is formulated as\n",
        "\n",
        "\\begin{align*}\n",
        "    \\mathcal{L}_{ADV} &= \\sum_{n=1}^N -\\log D(G(I^{\\text{LR}}))\n",
        "\\end{align*}\n",
        "\n",
        "Note that $-\\log D(G(\\cdot))$ is used instead of $\\log [1 - D(G(\\cdot))]$ for better gradient behavior."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mv2KIqHgJ3gh"
      },
      "source": [
        "from torchvision.models import vgg19\n",
        "\n",
        "class Loss(nn.Module):\n",
        "    '''\n",
        "    Loss Class\n",
        "    Implements composite content+adversarial loss for SRGAN\n",
        "    Values:\n",
        "        device: 'cuda' or 'cpu' hardware to put VGG network on, a string\n",
        "    '''\n",
        "\n",
        "    def __init__(self, device='cuda'):\n",
        "        super().__init__()\n",
        "\n",
        "        vgg = vgg19(pretrained=True).to(device)\n",
        "        self.vgg = nn.Sequential(*list(vgg.features)[:-1]).eval()\n",
        "        for p in self.vgg.parameters():\n",
        "            p.requires_grad = False\n",
        "\n",
        "    @staticmethod\n",
        "    def img_loss(x_real, x_fake):\n",
        "        return F.mse_loss(x_real, x_fake)\n",
        "\n",
        "    def adv_loss(self, x, is_real):\n",
        "        target = torch.zeros_like(x) if is_real else torch.ones_like(x)\n",
        "        return F.binary_cross_entropy_with_logits(x, target)\n",
        "\n",
        "    def vgg_loss(self, x_real, x_fake):\n",
        "        return F.mse_loss(self.vgg(x_real), self.vgg(x_fake))\n",
        "\n",
        "    def forward(self, generator, discriminator, hr_real, lr_real):\n",
        "        ''' Performs forward pass and returns total losses for G and D '''\n",
        "        hr_fake = generator(lr_real)\n",
        "        fake_preds_for_g = discriminator(hr_fake)\n",
        "        fake_preds_for_d = discriminator(hr_fake.detach())\n",
        "        real_preds_for_d = discriminator(hr_real.detach())\n",
        "\n",
        "        g_loss = (\n",
        "            0.001 * self.adv_loss(fake_preds_for_g, False) + \\\n",
        "            0.006 * self.vgg_loss(hr_real, hr_fake) + \\\n",
        "            self.img_loss(hr_real, hr_fake)\n",
        "        )\n",
        "        d_loss = 0.5 * (\n",
        "            self.adv_loss(real_preds_for_d, True) + \\\n",
        "            self.adv_loss(fake_preds_for_d, False)\n",
        "        )\n",
        "\n",
        "        return g_loss, d_loss, hr_fake"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yAYCRF1cS8DM"
      },
      "source": [
        "## Training SRGAN\n",
        "\n",
        "Now it's time to train your SRGAN! Let's first begin by defining our dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DaiSLB8UTFWV"
      },
      "source": [
        "from PIL import Image\n",
        "import numpy as np\n",
        "import torchvision\n",
        "import torchvision.transforms as transforms\n",
        "\n",
        "# We are using STL (for speed and also since ImageNet is no longer publicly available)\n",
        "USING_STL = True\n",
        "if USING_STL:\n",
        "    DatasetSubclass = torchvision.datasets.STL10\n",
        "else:\n",
        "    DatasetSubclass = torchvision.datasets.ImageNet\n",
        "\n",
        "class Dataset(DatasetSubclass):\n",
        "    '''\n",
        "    Dataset Class\n",
        "    Implements a general dataset class for STL10 and ImageNet\n",
        "    Values:\n",
        "        hr_size: spatial size of high-resolution image, a list/tuple\n",
        "        lr_size: spatial size of low-resolution image, a list/tuple\n",
        "        *args/**kwargs: all other arguments for subclassed torchvision dataset\n",
        "    '''\n",
        "\n",
        "    def __init__(self, *args, **kwargs):\n",
        "        hr_size = kwargs.pop('hr_size', [96, 96])\n",
        "        lr_size = kwargs.pop('lr_size', [24, 24])\n",
        "        super().__init__(*args, **kwargs)\n",
        "\n",
        "        if hr_size is not None and lr_size is not None:\n",
        "            assert hr_size[0] == 4 * lr_size[0]\n",
        "            assert hr_size[1] == 4 * lr_size[1]\n",
        "\n",
        "        # High-res images are cropped and scaled to [-1, 1]\n",
        "        self.hr_transforms = transforms.Compose([\n",
        "            transforms.RandomCrop(hr_size),\n",
        "            transforms.RandomHorizontalFlip(),\n",
        "            transforms.Lambda(lambda img: np.array(img)),\n",
        "            transforms.ToTensor(),\n",
        "            transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),\n",
        "        ])\n",
        "\n",
        "        # Low-res images are downsampled with bicubic kernel and scaled to [0, 1]\n",
        "        self.lr_transforms = transforms.Compose([\n",
        "            transforms.Normalize((-1.0, -1.0, -1.0), (2.0, 2.0, 2.0)),\n",
        "            transforms.ToPILImage(),\n",
        "            transforms.Resize(lr_size, interpolation=Image.BICUBIC),\n",
        "            transforms.ToTensor(),\n",
        "        ])\n",
        "\n",
        "        self.to_pil = transforms.ToPILImage()\n",
        "        self.to_tensor = transforms.ToTensor()\n",
        "\n",
        "    def __getitem__(self, idx):\n",
        "        # Uncomment the following lines if you're using ImageNet\n",
        "        # path, label = self.imgs[idx]\n",
        "        # image = Image.open(path).convert('RGB')\n",
        "\n",
        "        # Uncomment the following if you're using STL\n",
        "        image = torch.from_numpy(self.data[idx])\n",
        "        image = self.to_pil(image)\n",
        "\n",
        "        hr = self.hr_transforms(image)\n",
        "        lr = self.lr_transforms(hr)\n",
        "        return hr, lr\n",
        "\n",
        "    @staticmethod\n",
        "    def collate_fn(batch):\n",
        "        hrs, lrs = [], []\n",
        "\n",
        "        for hr, lr in batch:\n",
        "            hrs.append(hr)\n",
        "            lrs.append(lr)\n",
        "\n",
        "        return torch.stack(hrs, dim=0), torch.stack(lrs, dim=0)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cATrAvDhaq6c"
      },
      "source": [
        "Recall that the generator (SRResNet) is first trained alone with MSE loss and is combined with the discriminator and trained as SRGAN after. Check out the training loops below:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FTEi1FAgbCQG"
      },
      "source": [
        "from tqdm import tqdm\n",
        "from torchvision.utils import make_grid\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Parse torch version for autocast\n",
        "# ######################################################\n",
        "version = torch.__version__\n",
        "version = tuple(int(n) for n in version.split('.')[:-1])\n",
        "has_autocast = version >= (1, 6)\n",
        "# ######################################################\n",
        "\n",
        "def show_tensor_images(image_tensor):\n",
        "    '''\n",
        "    Function for visualizing images: Given a tensor of images, number of images, and\n",
        "    size per image, plots and prints the images in an uniform grid.\n",
        "    '''\n",
        "    image_tensor = (image_tensor + 1) / 2\n",
        "    image_unflat = image_tensor.detach().cpu()\n",
        "    image_grid = make_grid(image_unflat[:4], nrow=4)\n",
        "    plt.axis('off')\n",
        "    plt.imshow(image_grid.permute(1, 2, 0).squeeze())\n",
        "    plt.show()\n",
        "\n",
        "def train_srresnet(srresnet, dataloader, device, lr=1e-4, total_steps=1e6, display_step=500):\n",
        "    srresnet = srresnet.to(device).train()\n",
        "    optimizer = torch.optim.Adam(srresnet.parameters(), lr=lr)\n",
        "\n",
        "    cur_step = 0\n",
        "    mean_loss = 0.0\n",
        "    while cur_step < total_steps:\n",
        "        for hr_real, lr_real in tqdm(dataloader, position=0):\n",
        "            hr_real = hr_real.to(device)\n",
        "            lr_real = lr_real.to(device)\n",
        "\n",
        "            # Enable autocast to FP16 tensors (new feature since torch==1.6.0)\n",
        "            # If you're running older versions of torch, comment this out\n",
        "            # and use NVIDIA apex for mixed/half precision training\n",
        "            if has_autocast:\n",
        "                with torch.cuda.amp.autocast(enabled=(device=='cuda')):\n",
        "                    hr_fake = srresnet(lr_real)\n",
        "                    loss = Loss.img_loss(hr_real, hr_fake)\n",
        "            else:\n",
        "                hr_fake = srresnet(lr_real)\n",
        "                loss = Loss.img_loss(hr_real, hr_fake)\n",
        "            \n",
        "            optimizer.zero_grad()\n",
        "            loss.backward()\n",
        "            optimizer.step()\n",
        "\n",
        "            mean_loss += loss.item() / display_step\n",
        "\n",
        "            if cur_step % display_step == 0 and cur_step > 0:\n",
        "                print('Step {}: SRResNet loss: {:.5f}'.format(cur_step, mean_loss))\n",
        "                show_tensor_images(lr_real * 2 - 1)\n",
        "                show_tensor_images(hr_fake.to(hr_real.dtype))\n",
        "                show_tensor_images(hr_real)\n",
        "                mean_loss = 0.0\n",
        "\n",
        "            cur_step += 1\n",
        "            if cur_step == total_steps:\n",
        "                break\n",
        "\n",
        "def train_srgan(generator, discriminator, dataloader, device, lr=1e-4, total_steps=2e5, display_step=500):\n",
        "    generator = generator.to(device).train()\n",
        "    discriminator = discriminator.to(device).train()\n",
        "    loss_fn = Loss(device=device)\n",
        "\n",
        "    g_optimizer = torch.optim.Adam(generator.parameters(), lr=lr)\n",
        "    d_optimizer = torch.optim.Adam(discriminator.parameters(), lr=lr)\n",
        "    g_scheduler = torch.optim.lr_scheduler.LambdaLR(g_optimizer, lambda _: 0.1)\n",
        "    d_scheduler = torch.optim.lr_scheduler.LambdaLR(d_optimizer, lambda _: 0.1)\n",
        "\n",
        "    lr_step = total_steps // 2\n",
        "    cur_step = 0\n",
        "\n",
        "    mean_g_loss = 0.0\n",
        "    mean_d_loss = 0.0\n",
        "\n",
        "    while cur_step < total_steps:\n",
        "        for hr_real, lr_real in tqdm(dataloader, position=0):\n",
        "            hr_real = hr_real.to(device)\n",
        "            lr_real = lr_real.to(device)\n",
        "\n",
        "            # Enable autocast to FP16 tensors (new feature since torch==1.6.0)\n",
        "            # If you're running older versions of torch, comment this out\n",
        "            # and use NVIDIA apex for mixed/half precision training\n",
        "            if has_autocast:\n",
        "                with torch.cuda.amp.autocast(enabled=(device=='cuda')):\n",
        "                    g_loss, d_loss, hr_fake = loss_fn(\n",
        "                        generator, discriminator, hr_real, lr_real,\n",
        "                    )\n",
        "            else:\n",
        "                g_loss, d_loss, hr_fake = loss_fn(\n",
        "                    generator, discriminator, hr_real, lr_real,\n",
        "                )\n",
        "\n",
        "            g_optimizer.zero_grad()\n",
        "            g_loss.backward()\n",
        "            g_optimizer.step()\n",
        "\n",
        "            d_optimizer.zero_grad()\n",
        "            d_loss.backward()\n",
        "            d_optimizer.step()\n",
        "\n",
        "            mean_g_loss += g_loss.item() / display_step\n",
        "            mean_d_loss += d_loss.item() / display_step\n",
        "\n",
        "            if cur_step == lr_step:\n",
        "                g_scheduler.step()\n",
        "                d_scheduler.step()\n",
        "                print('Decayed learning rate by 10x.')\n",
        "\n",
        "            if cur_step % display_step == 0 and cur_step > 0:\n",
        "                print('Step {}: Generator loss: {:.5f}, Discriminator loss: {:.5f}'.format(cur_step, mean_g_loss, mean_d_loss))\n",
        "                show_tensor_images(lr_real * 2 - 1)\n",
        "                show_tensor_images(hr_fake.to(hr_real.dtype))\n",
        "                show_tensor_images(hr_real)\n",
        "                mean_g_loss = 0.0\n",
        "                mean_d_loss = 0.0\n",
        "\n",
        "            cur_step += 1\n",
        "            if cur_step == total_steps:\n",
        "                break"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nyypDt_UhBjz"
      },
      "source": [
        "Now initialize everything and run training!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ScH0Iok8fAMS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84,
          "referenced_widgets": [
            "98e801dae0b4401785ccd06d3f42a6a0",
            "1dc6f457233149e6a8789446b69e6f9d",
            "b3920fc234fd402a96803bcf9382126d",
            "968ee790ed30446dba2b67b07376c145",
            "c9485c8bb4a541079034da385d512e70",
            "96ec84b5a00341f18bf58067f942045a",
            "0c356917abbf4afb8ef89e5e48930635",
            "c0209daeab5f4a09b01a23370e09d352"
          ]
        },
        "outputId": "388ba277-76ce-427b-b7b1-57ab74e9b1dd"
      },
      "source": [
        "device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
        "generator = Generator(n_res_blocks=16, n_ps_blocks=2)\n",
        "\n",
        "# Uncomment the following lines if you're using ImageNet\n",
        "# dataloader = torch.utils.data.DataLoader(\n",
        "#     Dataset('data', 'train', download=True, hr_size=[384, 384], lr_size=[96, 96]),\n",
        "#     batch_size=16, pin_memory=True, shuffle=True,\n",
        "# )\n",
        "# train_srresnet(generator, dataloader, device, lr=1e-4, total_steps=1e6, display_step=500)\n",
        "# torch.save(generator, 'srresnet.pt')\n",
        "\n",
        "# Uncomment the following lines if you're using STL\n",
        "dataloader = torch.utils.data.DataLoader(\n",
        "    Dataset('data', 'train', download=True, hr_size=[96, 96], lr_size=[24, 24]),\n",
        "    batch_size=16, pin_memory=True, shuffle=True,\n",
        ")\n",
        "train_srresnet(generator, dataloader, device, lr=1e-4, total_steps=1e5, display_step=1000)\n",
        "torch.save(generator, 'srresnet.pt')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading http://ai.stanford.edu/~acoates/stl10/stl10_binary.tar.gz to data/stl10_binary.tar.gz\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "98e801dae0b4401785ccd06d3f42a6a0",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Extracting data/stl10_binary.tar.gz to data\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AvqBuRwjZrBq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "96ff8cef-0371-4bb3-d4ff-b1c1aee180b6"
      },
      "source": [
        "generator = torch.load('srresnet.pt')\n",
        "discriminator = Discriminator(n_blocks=1, base_channels=8)\n",
        "\n",
        "# Uncomment the following lines if you're using ImageNet\n",
        "# train_srgan(generator, discriminator, dataloader, device, lr=1e-4, total_steps=2e5, display_step=500)\n",
        "# torch.save(generator, 'srgenerator.pt')\n",
        "# torch.save(discriminator, 'srdiscriminator.pt')\n",
        "\n",
        "# Uncomment the following lines if you're using STL\n",
        "train_srgan(generator, discriminator, dataloader, device, lr=1e-4, total_steps=2e5, display_step=1000)\n",
        "torch.save(generator, 'srgenerator.pt')\n",
        "torch.save(discriminator, 'srdiscriminator.pt')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.16it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.09it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.13it/s]\n",
            " 19%|█▉        | 61/313 [00:07<00:30,  8.33it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 1000: Generator loss: 0.01806, Discriminator loss: 0.69390\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.10it/s]\n",
            " 39%|███▉      | 122/313 [00:15<00:23,  8.05it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 2000: Generator loss: 0.01772, Discriminator loss: 0.68807\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.14it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.14it/s]\n",
            " 58%|█████▊    | 183/313 [00:22<00:16,  7.97it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 3000: Generator loss: 0.01751, Discriminator loss: 0.67928\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.03it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.16it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.13it/s]\n",
            " 78%|███████▊  | 244/313 [00:30<00:08,  8.29it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 4000: Generator loss: 0.01741, Discriminator loss: 0.66615\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.14it/s]\n",
            " 97%|█████████▋| 305/313 [00:38<00:00,  8.05it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 5000: Generator loss: 0.01728, Discriminator loss: 0.64911\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.96it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.10it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.13it/s]\n",
            " 17%|█▋        | 53/313 [00:06<00:32,  8.01it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 6000: Generator loss: 0.01722, Discriminator loss: 0.62839\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABjCAYAAAA4j9PeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOy9aYxlSXbf9zsRcZe35VpZa1fvzRkOZ8ZDmsuQHtISJMCCQZiWYQiGPlgwYNiAAUGQDRgiaZmCQRmyZMGGJViw/UkgINiCDMgWKFmkQJM0ySE9S8/0Wt3VXXtVVq4v33a32PwhXmZlVVd31QybQ9KqA1Rl5nv33hfvxol//M//nIgrMUae2TN7Zs/smX1vTP1hN+CZPbNn9sz+ZbJnoPvMntkze2bfQ3sGus/smT2zZ/Y9tGeg+8ye2TN7Zt9Dewa6z+yZPbNn9j20Z6D7zJ7ZM3tm30Mzn/SmiDyrJ3tmz+yZPbPv0GKM8nHvfSLoAvT7mhcuZzR1x+EkEIEyE7JcUCaymIAPEHWECAgIECIYJYQAtgOlQJlIjJAbYWvVoERzNLW4AForYkznOR8JAUQErSIigiggCiEIMabrKKUxxhBCxPuANhlaa0KIBO8IwZFnml7PoHVLph1KRbQWjI4IEa0iSKS1kdlCMV8oqjriPKk9AbQObK4Lo36BFnDRE4EQPLO5Z7YA74UQIQaICEQQBZkWylIzXzg6Gz61Tn1mz+zTNKMUm+urvPjKqwxHK3/YzfkjYEswe8RC8HT1nHp6SLMYI6HFaBCJCHB1u2XefPI4fyLoPn/Z8Jf+4xG7d4/4F1+DzsPzZzSjNU1v3XL928LRXHA9RwygFURJQJuhiVaYHmnKgacYepo2st7X/MxP9emrnN/+5oK7+5Esy0AULkQ6K4DGGE1pIibLKEoNUVPVAes6YlCUeY/+cEhTdzRdZNAfkpc9iIqmntE1FWsriu9/bcj5c9tsri+IXpEZxaBIIFzkFjGOe/vCux+WvP6W4p33hboF66BtA6OB5c/8Cc2XP3+Ong7M7ZTKBWat5Y13Wt64IswrobNCXYGzCiJoDasjw4vPrfDW+2N2Dxouv/jaqa78uMnwdIAhj3ntk859+Cpyct6TPuvJ1/ujYZGqmrO/u/2H3ZD/X9mgzPmh117kL/xH/yH/1p/785T9wcl7In9cfOP3Z8cLxSKApNEjQAyBajpmsneTo50Pmdx9j8PbbzHb+wBlJxS5YEzAqMBf+aX7fPtG84mf80TQbZuOve0xvgUlCVSVUdQtNPsRUUK/iMwFogioNNBDgHnrUVbTy6GfCwHwDuaVZ/uoItcVC4SDRcR2DqUMPmQYHSlLTV8bYlRYZ9CuREkk4AlRIyoSlKFuHc5HlEQ6W+NI7USBznParqNrp5xZr1lbC+ztF8yOYKEcxrT0B56ohIMjIeIQFWjanBA0IQZihMwIK73I5mCBkZbOV+xOA7sTWCygyCNZL000B15oARWFECJtF6kWHd6l2e9P/OmfQSRJ6Y86c4yJ1cdlz3+cr8clUMoTgPLxc/UfjgkfnTY++fjU8viYs25ef49f/9V/zFd+8ifwtiNX0NmGiCXPFb5pyLAUvYzeYAMpcpxT9Pvr9IarXH7+JTJjQBRh+UlyPMBIEc5xowOe+XwKMaKUoch7GJOhYkSpdEaIYXmjYzpZ5EHfBA+SfAGl6WzHbHrAwb0PmOzdwjlHF4TgPN57sjIniqCMwTcNwQtb5y7QNC0iEL2jrSvyzNAGz9b5C/R6K6xtXmQ4OkOel8TAEjQeWAKUkPwroQoxRpxz/OIv/iIhRu7vbPP3/+f/iaLo89N/7t9Da80fLS/63pgAwXvmk30O7n3A3q23OLr9BtXeh3SLPejmqGjJVAQVcQ58iDgVCU+xwveJoNvUsH1XUbcRH4Q8B0RwPtK2gs8iRQbWQmNJVFspbBdZuzRA2sDRXUtdR5QsJYcY+fa7Hg3UjWJlRSMhMj6KBG+IWuOC4MnBKJTO6DowmcbkawlQTcRkBdEHjLSAR2lDwBCDRYmQZRkiisNZxd7hkMPJhLvbU+bzwLBw9HuR4aoCo9jdC/jgGY4gy8C2ghAT8EVBEbGhZdp0XN8OvPW+cHcH5nWSTlaHEHKhPhKUS+d6iUQdWHQ1LnoABsNVlNKpcx/ry6fh6dEDPoHtnpx26hiRj5Dm01d8kn8ct+87Xin+ceT80Wad+prCCV6d/Hz0s4/fK3uJhf3AF16jVxYMihKhoZ7dZ3x4h0Fxls3VHsSGtfVLDDZW6fXXOX/xs+SjLV77zA8yGgyQZRzw4J4EjnPLEfC2obMTDvbuMz6aICpnZWOLrbMX0DF9iSwrUOo4H/24L+wBRQyCKGE82ePOjfe5/c5XuXPl96jaljYobDuhbWr6axvMKktnLbkaYLuGwcDRtg0mU9gu0C/X2Txznnnbcun5F1g/c54zF76fz33+K4xGG5/QMQFIE4BIkv6cs0vQDTTecuPebf77v/23WFlf50/+mX+Tf7kAN7KYHXDn6re4/e5XuX/j20zHt6Gbsa5bRCyiYpI5iUgQIEmuKgrEwNNsq/BE0FUCTeuJJufsOrS+Q9D40KFFeO6lgvu7DWaq0CagMPT6OS+9POC5y2tUi5bfOdymbkC1oFTSZ7f3wXfJxdc2PVk/4scR5wOllCgEiRkhagblFqIzEE2kRGxLlmdoleFcjVCitUk6q5sjlEkHRoihYTLruHoTtAocVRVNC7NW6Ldg5hlKB3wI9HqKnhHKPFLVAUWaJNpOceuuY6VvmXeW6/fg5k4geMFoTV5EDJ46QL8PKwPH1hqYPuweCbMKfEigG2N8wN4e6Z/EQk7rQUvm+0hHPmDI8fShJ9c/Oe7RzozfGdv8rrfleMJ5MT4yrZz6O8aHfz6uPcff686N26yujlhdX0GLY1gOGQw2yXtr9M9uMN27zv3dHVa7BefOB7wdc+HC51hbW0dpgyYgS31eKQ0x0nQde4cHrI+G7G9f583Xf5v5/jZd27B27jx7wxWuoNk4cxEfDJcuvcjl519CVI4OaWJQiToTYyRIDaFAvMa6KdPxDVR9RIEjN0LXBiDQVmOGRUEpQhvAqJKqndA1czKZs7XWo2tmdCrQdTUHR5HLl1+CpkKhOX/uEoPhClmuERwhfHRoiyhEDCApB6I1dZXGSYiRxqV7cfPeXX7hv/h5ysGQL3/lJx+5xh8fEI6P/C8PzfQpLxS8Yz7d5fYHb3Lt7a9x663fZHZwG1iwTCRRGoUvI3mmlv6SJucQHeARshQVB08MnwLoIkAp5HnOKHeEBSeZMi0KYp/cWJxz+FyhjGE40rz08gpFGVjMF/QGjs6BdQqjFdY5UIpOBdoFMIFeGbE+4okYE1kbZYgYTL6KLs4gyqAlIwDalJiswFmPMQrRKfQLrkFML3EVZXDBE4OlCwPu7k4oS8fKGuhCIEAb4eDAsr4mXLxU0Mtz5lOHMmE5aNIE0Tnh+m2Fsx0r5yIvvgqf+5JiOotcedcxnykcgo2R3hDOrcDLL4Dk4K5FJgshxERFl+Pxo7f5EWc+DbbHv38vHf5xYP+pXv8p23DaHm1Puxjj1AIX57SiOPPSa5z/7Pdxb+c+i7ql7A04ONploQOHBurWM2sci/mUtbUz+AC93hClhK5p6boOJ4HJbML1q1PENRwc7nHrnW+Se8fe9g1Ub0A0GZvPvcqFy68Q3ILp0T79/gqYjDzLU1+lQUKIkVxHnJ9z9+a3uPL6r9Lsb3N0cIfp5C7aKPCBXuYxKnC0v4MPOeVgjf15Q1NX9PMh9VRRLzToBQs/YTw9pJ9rXnvp86yvPM+Fcy8To+Fwf8FsNqbXz1hf30BphRKFcx2LakZVNaytrlMUJW3b0NqGuJQD6w6ipIj0gzu3+S9//uf5r/76f82P/PiPY8wSKv44qg0RiAHnLLat6bqWpp7w3rd+m7e+9ju88+473L6zjXMNL2wJa30wmcdolWTLLlJpECWICmglRDTEgEiaNEVCui1PMUafCLpBIGSazMCi6jCiUKRsWesj33r9E
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.14it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.16it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            " 36%|███▋      | 114/313 [00:14<00:24,  8.28it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 7000: Generator loss: 0.01712, Discriminator loss: 0.60425\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.14it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            " 56%|█████▌    | 175/313 [00:21<00:16,  8.34it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 8000: Generator loss: 0.01709, Discriminator loss: 0.57608\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABjCAYAAAA4j9PeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOy8ya9l2XXm99vdaW732ugyIlsmk41KFEVJLKgkW5DL9sQ2auSZgZp5av8NNjzzH2JAHtiAXS4YslVCUWULIik2EplNZGRkRv/a+25zut0sD/a5LyIJSyxbBD1wbCAi3rsn7r3n7Obb3/rWt7YSEV631+11e91et19P0/9f38Dr9rq9bq/b/5/aa9B93V631+11+zW216D7ur1ur9vr9mtsr0H3dXvdXrfX7dfYXoPu6/a6vW6v26+xvQbd1+11e91et19js3/fRaXUaz/Z6/a6vW6v2//DJiLq77r294IuwGQ65613P0BSBNGgAEkgghAhCVorst03X89IrUEp1Pjb7p8kgoigAVGglSKkhFb5jVoDEhEBTUADUQRIGKVAG1IMGK1BIElCoUjKMCSNVgqrInbcLyQlIKGuPz/fkSBoFChBIUiKRBFEDEopBCElCEkwWpGE/J1Kg+Rnzn0BWhsUkaZbcbG6JCbyMyqF1gZB2Kx6Qkh87YOvIihEBJF8L0kghEi67p+x10TyvUi+XwSUzs+RXxdSSjD+zNjbCkG90un52m7/lDx2+QtQiuu+UUqNrylAXf8O+VF395JSQsjjmGTsBhFe3aFl9x4UKEXurrHPdve1uw7s5uirV171kO+eXwSGvmW7Omc+KSicQYDCOZIkYoiAoLXGFQV+GDDGABBCyM+SHwZrLQpFCH58XWOty9879oskQek8jjFFJAnOWGQcf63MOA8FYzRgSJL71WiNJAEDKeZ+U0phtMFYQwgxP6lSWOtAhCiCtY4Y4zh3x6YU1hhiSnnMEbTSmPG1PIbjytMaQYgxoJRCK52feRyTeP1+RYyRB599znRS8ObtvVdGcBz7v4t27eYk5IU8zoc8lq/8t1dek3HtCxlC0u4949eMKxFJ6XrO5zn+cg6IvPr5QpKX6yCOf1L88pxlxBmtFUorFOp6DjCOFbw6P3/h/nddq165OH6uGj+X8TM3q5YQEn9fU39fcYRSSt7/xm/zn/+X/zXri89I3jHfv4XRAjGgGJAUKbQmSARKkkRSCgxqijaOUg1ESpIIlctAPPhAgSKQMAoutwPGaqZW0ERiaLEqUUhL5TTr7RKFp7AgyqIkULk5pTG0vsMZS1COk01BWU6Zl56JdCABYiDGDq1tBmRnx0EIKNFoE9AowrCl6QeCFBhTElKi8ZHLbU9VFABUziHGkUJkWpWIFrSydH5J1y15fPoxP/z4bxg6oaAiJnCFxQfPz376lMuLlj/5k/8OwdD7SIzC4COdD2yajj4kQkp0faDvA957Bh8ZfKL3AZFXFrKCFAMpJbTS44ahiJJQKqElIRK5BtmU0CgSCZGBFPPiNAjGWpQCjUVIGCeAyZtZEkTyQjfKIALee0TlzTAmQcluEmu0GUFIgULnDUkrjAKjTV6fKkHSpJSXWkoKHyJpBK8d6EaRvDqVQokg48Q+efwJP/7e/8xvf+M2Nw+nKKWYz6eEEGjbFiWCc47FYsF6vaaqSkBomu0IQgptDJPJFICubUApjHVMpjNizH1qnQPAWIPShq7vsYVjXi3ogbKaUhYztBg2XiidpqgW9D5B6rl1dMTps6fY/ZLQaST0pOgpqynVpKBvB4IotMnfqxGGAJPJlL7vCSFeY4DSmqoqGYaBYRiAhLWOsqoZhgFrNErl/tFaE1NgGHrKssBqRUoRAGsMwzCQYkCp/Oz/1X/z3/KbH9zmv/jnfwAoEgqdNJBQkkCut8ZrALoGUAFJClIgipBESJFxYxdiSkjSSIIYAyEEQoQQEkNMhJhIKRISoB0hRrz3+ODxMSJRMkAnYUhxJDSJmGAIiT6mvD6Ggabr2TY9XTMgSTBao43GWkVdOVxhKUqH0Xqcj3rHDPJs13oE0JeELSGE3eagNSmzFJQxYBXaaJyxGK3AKH7y/YcsL7b/MKYbw8AXn/81n/zsXzKsNN/6rf+YozfeRhNxqseHlqYPWFfgY0CxQfsGKW+TjCLqgUEKtJ2gbUFRGLwfd8YExmrmdUkvhjZFbNxiBIyL+KBxKZL8GvEtm9gRhoa6XNCXPTcPFlidsDbhkudQdxg1UOkSgif6Do1grKFrB4yzYBRVAUZDFI33oEkkr5CQRlgKpOBRovFxQAcFSUjeo4xGi6aTRB88ZaH4+NH3ePDsMZtNoG2FsnSoZPAdVMZRTgXnsnz+7LwhpsQweEJMDP1AiJGYEj5ElFJEP6BDZOoKVOiJacBETxIh9BElGQwTCaUVibzgrE5YEmoE58JZjLEYBc4aUBpBYbTCWoPVeRMsyjIHJtpgsEwnBXpkZ0J+vfcDMaQMlCPAhigM3jP4QNd52tbTDYGUwCmF0gZtDFqPbMAAUeeNQ5HvTwcUefIardBJMMaQRqbjtCEqIUSPRCirgiJc8GNA0kt2tdls8oQdo4MQAsvlcgTbOLL2azaBiNC2zfVLemTW2xGYFRoTBoy14DNL1dowXxzQxkhVHiPdjLMuYgrL8e1vcvXiEY/PryiqkplyPBfPcjnwlfe+xcnpEhtOqKb7eMCjGFLIBECErusw2iLK0DTN7jZRSl8DXNu2iMgrryfarh031Qy2+dkiIglrLUXhaJvtNZs32lA4i/eJMPR4P+Tn14rSFTlGUgot1/EGCtCvREKvEE0EyXuoFCRJ+V7TCL6S8gacVGai0RJDJMSEBPBR8DFv6CEJgs2RzDDQdz2hH7CVQTC0bUPpStLIRp0rOdtu2Q6edoh03uKsxaDQUXIEPm5E1sJ8UlLVJWXlsFplQNZ5ziVycmsX9eXIVxASQTK5EEVm3BqSzgCNGaN5/eVI4pe1Xwq6IUVOLh/x+aOPkW6KfPh9fqde8MG3v82wOccYzfLyBVWxx7Rw9GuL9I757beJeFK/ZlrfoJgdY63BFDWlvGQuAHXssUWFRI+JHbZ7gQxbBt/TXHxB0hAJtO0F02JCCAPGNlxeDRwe30EZR1IFZWFJvsGoHh831KWl7zwSLLY0eB/RAXRlSUphrBCDIsWAaIV2BUo5tl0ESTRDyKwiKQgRKQ1TV1NYi3KKShlif85qc4ofWmbugMrPOb9Y0XcNZV1gS8sQe/o+h7b/x1/+dQ6ldiGRCJGEGpmlITPFgOCKAiGHKmlkEbILaYzFoHO4pBQGy2xWcrA/YVJXTOqSuqoprGNSFUwnFcbmDcOVNc4JtStxZYEpCpBEGjxdELzEvJBiIoTAEDxKZ+DJr3lSVnxYNQ39EOh7T9v1NG2PwLW0klJEG0MIHkvkxp6jMIpN3+JDgiCkkMBqgu/RolA60A8tSgkpatrBI95jjYFWk/rVbs1/iXFpdY0FKHbh/CsIsftpBOpduP8qIO9kGnQOw8UPaKURyX0evWETCx6drGn6K6rDYxZ1gaw2PD17jiTDLAjPX3zBvQ8+YIvhi48fc3g05fD2XfrgePL4Psfvvc0wGKLfoFKEqAhotBaSaJTKgLG7x1fvW2cNLv88gsNukxpjhzFDLsQYSSmOfZSQlHBWo3R+n9Lj5yhN4Rw7WcmQQOlRDVLocUy/3MOjfJiEpLj+jiRpBC0BUUQ0KSZi8MQUCSmRghBDjpQkCVESwUPXJbStCUpowsDZqmFSlyAJJwYVPdoadPB87dYRzeB5tmlZdR3OaJRElARiTChjUCJYk5nuYlpTVRZnFUZb0AqNYZe6GkkvOnMsEvGavYtAlJRlJZ03JtGWpMYVOkosWv1y2P2loHv27AE//YtLlIpcri54+n/+r5w/PaXeXxC6Z9x64z1AYUvLZHFEubfPyf0fwPkj6vkc31yyuPkVbGWgXVJNatz+DbRRKKVZLp/wg3/53/Pt7/6H3LxxTOoiqWsJOhDDGt+dM6SBgoGbRzdomwGNRoyiHRIkQ
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.15it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            " 75%|███████▌  | 236/313 [00:29<00:10,  7.56it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 9000: Generator loss: 0.01695, Discriminator loss: 0.54376\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  8.01it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.16it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            " 95%|█████████▍| 297/313 [00:36<00:01,  8.27it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 10000: Generator loss: 0.01693, Discriminator loss: 0.50901\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABjCAYAAAA4j9PeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOy92Y9tZ3re9/uGNe6p5qozcGySzW6S3S11S7EGA7ERK7CQi9hGEsBAACO5SIBACHIR5CL/QZD8A75IDPhGgK0YQRLHgWxoiiTLUk/sJrtJNqdzyHNOTbv2tMZvysVau2rXOWTzKFFaAlIveWpXrb3Gvd71fM/3vMMWIQRu7MZu7MZu7Gdj8i/7BG7sxm7sxv7/ZDege2M3dmM39jO0G9C9sRu7sRv7GdoN6N7Yjd3Yjf0M7QZ0b+zGbuzGfoZ2A7o3dmM3dmM/Q9M/7U0hxE0+2Y3d2I3d2J/TQgji8977qaALECnJZJDiQyAECM5zdHjEaDwEPEoqhBAgBIErjBb9T2sNSimElFxH8IAAvA80dU0SJwgtCYhr9NsYg5QCJVV/MYAIQMAHODmbMp3OyPIBt+4+A1rhgmV6fkqxWHD74DbjyS4SwWw14+HDB9w+uMVwPOb05Jh6OcMbg4gTllVNGqeMRiNG4zFZmuFDQEqJ9w4AKSUEEEIQgsc6SxzF3bU6i/ceIQRKabz3SClxzvDOu++yXC6f6obd2NPZ3bu3mEwmCCkI3iN7r7PedfdNSCTdPZNS4p1DKo2UEmNbrLEgQOkIKbr3jamx3hPpBCVlt+/gcdZ2ft4fI82GSKUI3mOtwTsLIiCF6vyd0C33nddb55BSopTCBY+xBilEv65AKgUBnDUYZ1Gq93dAK40QkhACSiqkVBB8/ykEnPcQPN1jKAFBwGOdhxCQojtnHzwCgQCC6PbtPbzzzk/Y3d3hG9/4Wn9E0T9o/a/edT4vFYjNp/Pq87iyz+Jpn4s/l+t77xFyfXZftM3P0p5ENWMtH3z4AdPzc0IIaK0JHpyztE2D9/7zdgY8BehuDTN+6avP0hqHNR5XG/7Dv/Mf8K1f/Bo+GAZpRhTHoCUm9MAkJCKAFIL5xQX5cIBK0h7ABP3tRgho65bTTx+ys7dPNB7gA0RBIEQgiMDFdEqsI4aDASHQX5DDi0DtAv/kf/kX/Kvf+SNeefUN/sF/8Ru40YDCzPnt3/5n/OhP/pR/8Hf+U/7ar/y7JCj+6Id/zP/0j/4h/8nf/Y95/Rf+LX7nX/5z/uSf/xYTJdD7d/j2ex8zSYf8zb/1t3jjja9z9+5zNK1BaQXB0TQNWZYhhcB5j/ctVblia+eA4KExLVVdkiYp3guc88SxJtiK3/iv/kv+5E//7P/xrb+xJ+3Xf/3f4Rd+8eeJtEJ4yNOMJE6prME4g1YRwnlkAIGnrWsmO/tEccx8MWU2PUNIxWA4BiFoqoLz8wcsm5rJcI8syxmMRuAdxXxGEicoFdEay61nXkIqRV0VLC/OMaZEKUWW5eRphvCGpq5pPNjWsJidk+YZo60Jq6ZkVS6JdMIwGyGFREmFaSuquqC0LVk2QAswzhHpBFCYtmU0nDAZjsG1HQEQkqatsaZByW4AUVGCUJKyaTBtiyLQNCVVXSGBOI5QSUZrHdY6/rP//L/hmz//dX7rn/4jlJY453Btg44iILBazDCtYbS9g05ytE6IogRBBEHTqZQ9SIqAEJ7rymWP8JfrrJd35CmEQFWVpFnSDxDy+j7/Ei0ETyAQEPh+0F2VJf/d//Df85u/+Zs455gMRwgfWCwWPPz0E9q6/qn7/ELQlUqSZSlSGYywGC+ojcH6DjgdARkCIni66jaB8w7Zj96iZ4YhBHwIiCBAdiff7SEQBDhriTcvVHSvomfQYr28H4HX99AYgzEWKXueE3w/MglcCLTWgPMEqZBKopVCSBAhsL01oShWvPrqK0QHt3m4ajl98IjRcECcRNRNTWssofFkWYJxFmlaoiiirmuiCIIPOGtwrnOs4ANKadq2xVqLVqCEQIob+fwv2spVwfT0DK0UW1u7xNmEre1dtnWEsxZrDNa0NHXJ7PxRN4dSEVZI4nSMVku8swRjqdqSxtRYAKGoTMNgvMN4ckBwDcEG0jjFO0ddzZien1JXK4rlnLYs8SIwHo1QgKlLlAAdZ50PNjVNXRHFijjWjGRGpmOUzoh1RrW6YLE4w1hLPp5wMNwmSzOUUhTlksV8QVO3BCFJ4hFSxth6yWI5I0oyEAJjLTLJUComSTOyfMxQCIxxtNWK8uFHLBYrhAhsbU0YRQk7mSDzKwBmszO+82e/R5IlFMWKpijJ8pRIa4rVEucd2wc7xFnGIJ+wu3OL8WgfrXMECYj4iuSKxxjw4zPtwF8FPH1K2+TeAQ+kacpXX/8GRP8bZb1k6CHV3cw2+C9WZL8YdIUijVMkAi0UMlga09J6Twge3zQMtER6CaL/LEUPqP0A50KAEAhIXACCIKCAgJUC4yzeO6T3rGUHJ0T3kEhBCBbwQMdaQINwiNCitew/GEEIDu8tENA6xgmB957IgE8EOk0AR2NKJJ7VfM7uwREhSkiSAXmSs7U95vTkIXv7+2RpjjEOKcGYbrxzAdJIk4kYGQIGhWkagpcIJYlURFXVBEAKjzMNzpkvnHLc2J/ftBZoKYmjlMlkn8Fgqx/kA5FSCAE6ipBSUa7m5MMJOk7w/TRdIDBNRZ7lSKEI3qFkRJqm5IMJe7u3GI/G1GXBaOiQQnL84GNOH93nSEiq1YKL81NM0xInCaPBsJ+NBWScUDWWti5pqxXCW/I4YpANaZ3g7HzGarFEixXSt8TJgK3dCePJhCiKOqkAQfCB5XzFfFnSEPHx+SOmJyXP39rmk0/uk8QJOkqQUcLWTozWFtu2VKLEC9k9cz3bf+lgwmSQkWcpw0TQLqacn08BKMqCt37yY6QSmLbpBgmlSdMYrTVZGmPPW5TS1PUHDAcfcuvoWUbDHba29hhNdlEyBjSdnLlG1jUZ2lj0GYAr/sqCsOiInuiIJUEghORrX/sGd557kTe//2YvnXYy5NNcxxeDrhTEcQwEhHB4Jy8Zq1YRSkiscaRSoqTG4UFsjA6iO2nZAzGwFma7/6Vke3eXPE479USIThPtvI5ISbzpAN45i/ASITuNSwhBmsQo2WlrIQRED/RCycs7qaXESUkSx+hIr0cGrJPoOMdKTesCW5MdbFMzyEbYpsWYpn84PViPay0iBKwWfO/bf8qzt28zGo6QwdO0NVGSIoMjOIt3jijSONMSvOOmx8VfvA2yAVvDMTrSREpSlgvKWpAlGWmaInv9s1rNGQxG7OzsooRgVZR4Z9jemmDyjNYYokiThJzGemKpydMELT1YQ7AtkY7w3pKlCXfvPIOKNS6JGaQpS9OC92ipiKIMIcA6S1OXVKs5rq2ZjMck+ZB7n57y9nsfcXp+gRKKKIqI4og7t+/ywjgljlOklNRty8Xsgg8//JCffPAh09kCqROMkzwaTmjdi8TxEISgqGpka4m1pq0EKhngwmnHuoKgbRp2Us9Xbm+RRBGmrVjNVySDCS+/9gwArXOcFQVCSZSARVkjCWQ2I88yXJQQVpZgG8qyZLWsubi4YDQasb+3x+HhEUe3nsG5DK07CcI73z+rusPcIC5BSWwgr/cepTUhBIIQf2VIcAihY6/d0AXBACBExDPPHPH6G6/x/Tc70O3kUsHTPOZfCLpCyEvQBUtwsh+sBBJJmmQoJfsAku+YKX2siw50L8X8EDrWS6/Z0uFfFEX44FGX4bf+cCEgEFhrsdZ2U/T+rgXfAazSEUJ2OtQ6wCWgC7yFgHNrwAtY5/Cu07GMc9x97nkuHt1nbzxgcnAXlS/YHo947tnnCCLQNiVCCnCOLE4I1iO0xlQFb3zly8RaUawKvAzEkUZgUVqi4gicpDEGIQUu3EgL/19YrBO0isAH2qokSIlOYnwc07RNN8j7QDGfMxgNEQLOLs44PX7EINIQPG0/0HsfsCYgRBdUW85nLC+mHBzcIlhDWZV4a5iMt9i7+wJtuWRrP
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.10it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.15it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            " 14%|█▍        | 45/313 [00:05<00:33,  8.08it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 11000: Generator loss: 0.01689, Discriminator loss: 0.47407\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABmCAYAAABoQkJtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO2dy49lWXrV93nedzwzIjMys/JRVd31wO62acuNhQ1IyBLiJSTEnwBSGyEmSEhM8BgbC3sInhkGTMykBQILy2LQgLG7aFdV17OrsrKyKiMiMx437vueF4NWn/XbpyMyI6PRRS2+NdoRce85++yzz47zrb2+9QVVVTmDwWAwrAbh/+sOGAwGw/9PsEXXYDAYVghbdA0Gg2GFsEXXYDAYVghbdA0Gg2GFiJ/1xyAITNpgMBgML4iqqoKL/mZvugaDwbBC2KJrMBgMK4QtugaDwbBC2KJrMBgMK4QtugaDwbBCPFO9cBF++1/9y7q9LHyBQ4w9uyLP6naS6FRlUegzLsK3/WNV+UI/5Ev9vix1rFD/N3BYV+LzP/ySjt3r93AsfSludfT7QBcSRql/qJDDFpzbTCJ95te+9S13Hn7nN/6R9/Mn779bt4tWu26/tHtLn/nwo7o9dur7rbVt71ibO/26fXdvt25f62/W7TjU2Ifobxgm3rEq3JfKlWgLQYjxCi/+X15gvHncKFJfUvQlRvsX/uavXXjcf/pP/nndznP1cTTV+TbXdR/DQOerSn/e5UVet1upriXGHK4KXW+JuZItNeedc+50nOMn/Q1fcb2Ojpsmmptlpev44fnV54ODo7q91efzMKjbk6megU7Lfx5+67d/052H3/wPf1K326nOV2Tqe1lpTAdtzVPnnCuwab9Ee6OnsU9jHbeTaHzXuy3vWIul+vzd7/yhfn92XLdfffNrdXtr717dfvjpx96xru3dUf/x+1mm+9NN1cduS89Aq+U//8Rf/fmXL/zbRbA3XYPBYFghbNE1GAyGFcIWXYPBYFghrsTpkquNwsj7WwK+JgI/lWXgZ0F+BpV4m7L0OSyHY1fg9kDHuaIg3yiuqdvreoeKY3E0eaX/NSG4mwDni0BON68xivkd9SsCZxe6xrWcg8r5SSsbA/Gth7NR3f4IXG+IJMH56aRub9657R3rWl99nmLshydP6na3pTGKO+KAyT3+sJ8YY3DjBfpSBtW5n2/yklkBbhHfIQfeisUTppHPL18E9ivl/kGp8+XgJfs9HTdJfE53NgdfC753NCX/p/EFLejKxiMVYCwrcN2Tqe5JHGmMuH/QSfxrT8F/Dga6d5O55krawh4Fpm3g/Dl8EbbWddxuqmspsGGSYRzDRt5Vgmej29G1kDfPCs4JvPc1nrPv/Jf/WLf/zW/8et1+ZVt7L+WN63X7xstfVz9+9W97xyrBL59NZnV7Af6fU5W8c7XwnweOxVVgb7oGg8GwQtiiazAYDCvEleiFjRsv1e3lZOT9bTlTyJvneI2f6vdBoLW+gxCkbIRAo5ne9ztdURUR9TYV5T0KYYLQDxmzCjKVFqQ/oDQih2PxFJUfTlSIJ1sRQuRY11UWfkhyHianM+/n/SfDur27i9A/VfsMoeRgIHnQ9TVfutNGiN3f3Krb0VxhbZnN63a2RCjbKOFU4X5B2eVyxGPTpY6VgzZYFKSV/GsJnSRClO4kocYlCvzvX4RuW33MMoTYuKzTkc5RhQjpFw3JGGRfcahjRYEORtohyzVZpnO/vxkkcgmokrLSNZ6Ndb5eR/cxin0J1XzJsF43Ine4yFznK0tdbzZ7Pt3lnHNdyNIKSOco8+S1NxSjrtXWWKTgHiic4/O/BilZmfmytm///r+v2xnGfogh/mx4Urdf/uY3ddyv/Kx3rNnwrG4fjTT2E1AHe9Fa3U5wH4PG0GVGLxgMBsNPD2zRNRgMhhXiSvTC+OBT/ZDPvb/lyCJZZHovT7BTTpve6UghdVX6W6F5qZBijF3oFJkj5VLnKDLsOhd+qDLo6jsxQj4vPMIO52I4rttRg6qIsNPOUKOCEqIKn79bfPD4B97Pw/FT9TFUqJMGOt8rb75Rt290FYqGgX+9L/3Mq+oLwrGjfYVZ3PGvQBU0K0SXOegUZO1lS4SvoBfmGK/re697x1qMNUYPPv2sbvc3Nur2ZKyQsd3RfXgWlkvdu1aqNjOLzhbqYytChmPQuFeYXwHopy5oqRC0UhvURhj5c3g0QkZbKLpgo4/d9LEoo2yp0Ldq++qFCOqHGE9uCg6Fz1wO2iNqZHtehCVoHtJqOY5blBcfK8PzOIsYl3McNd5tZHv9wR982zvWu+8hQ7O3V7db1Xrd/iDeqdt/8fpX6vakQXvOQF2EVOBASTGcaH4UoGmaY1cUl6NqLoK96RoMBsMKYYuuwWAwrBBXohfmCCFc4O+wtvraUd/Fbn6xRIyLXc20ry7MZv7O73yoUOdsqLCrWEzrdhQrPJkvFRL0u37I2I8l/q96SkIoIY4OQRXMYWiSxAqpnXMuwRZ+xF3wlsYif0YI9iN0G1HK3pZC7O019bHdk5nNRvda3calu/U9PxlkPNFYHjz5om6PJurXdlvnQ4Tsml2vQtEYM+z2Rh1RIG6iMekl+vzuzmvesY5T0QUbCKt3tqSw+CyToUlWin56FhYZzWTOT5TodTBXQf+0Uj+MD0CbVEhWyDAuy4luXq+vwUsSn15I2jRkQsgKqmCtr7k5nuh6r637Cpi0TWpHnZnMEC7j5kVQCZTh5R714UjPVgfUDPs+w/hMmRninGtj1z8eaYz7UCl1O7rXH733Tt3+3d/xTXjwOLt2cVq3B627dfvrX/+7dfvOXSUITWc+3ZZh3rZwXeukljB2C1xX2KDbXGbqBYPBYPipgS26BoPBsEJciV4IGdc2kgBChEcLhN7RujxdHzw6rNs9ZCHcv6XPOOfc2o7O8/Z7n9TtJ2cI0+ZKuighPs+XfkgQwp82QG6/K9X/DB68BXwR6OnqnHM5QhL6DyxxzjjxaZfz0Eyf2N5ReLQJ39s1+OmWpcbk6VTheTjyj7Y5UCg6H+laHj1V6L7c1i5wL+Huv09VTEDBFLmucfb0oG6fIdHjzisSps8bF/nhhx/W7YMvHun7h6JAgjbCvOD5SSbOOVciBCyRCEO/Z+bZT49Fcwx6fmIJ30UyzG96/tI/ZDQFvdB4ojz6CSF6CJ8QJp/MK6gtxr4yqBoxOULf2ewoFM4L/X40h3rokh4WZ1PRC6XTuOTYzT8BBTGc+X1s0RcZ3hG726KyTr/33br9737r19XfU/mCOOdcd0u0S3tDc7Joi8LY+iqScqA+mjX8EuaL8z1e+vDw7bTxzCIjomx4JDc9k18U9qZrMBgMK4QtugaDwbBCXIleiJYKzZreCxn9B/raaX98oN3HL44l0G8jYnsCq0LnnPtbf+1X6/ate1+t2+++/f26/ehzCewPDkVbtNcUzjjnXIpwP0OYmSFsoqVDDCVC0Eh0YCIBrR1JaGS5v6t7Hrqdgffz1kAqhcophHo6VBh/jKSN+3e1i3vzlvwwnHNu+ECh2vGnj+v22pruyaNPHtTtFMkjvS5tHp27tnWzbo+nOj8tKfZ2QA0hmeO9D97zjvXBxyqj8vknalM98Y1v3K/b91+54S6DCOEzPTvKQuEny+KMJ7rZzXI9HUzKFFTSco4dbcckBIWuJ2f+znYEviGGYmGGHfCK5atKfWY89+dQAEqCPh8xEjWuQ1ByMNY1Ho8ut+O+XGjejavzkwBIIWy0fRptMgMdg3Ecn6i80O//i39Wtx/tK9FqsOM/DyVWp0Wo4+ZtUVl5T+NAy8amqoJ2kiGe5w4SUFhliv4dtFN1zrko+sneVe1N12AwGFYIW3QNBoNhhbBF12AwGFaIq2WkTcTJDvpr3t+Ctn4uwH2UMJNoMyME2Ti3b/u85Fvvi+9ZQJpyF5knf/3nJE/6/OHndfvxI5jyOF+6M5uL+8kqmoIw00zfzRd+dotnalI16pX86NeXMBi5//It7+dTmP8cTtXHm7viuoaHknw9SMRb3b7p34eHx
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.97it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.13it/s]\n",
            " 34%|███▍      | 106/313 [00:13<00:24,  8.31it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 12000: Generator loss: 0.01680, Discriminator loss: 0.43752\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.03it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            " 53%|█████▎    | 167/313 [00:20<00:17,  8.16it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 13000: Generator loss: 0.01674, Discriminator loss: 0.40002\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABmCAYAAABoQkJtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO19WYwk2XXdjSUzcs/a156u6r2nu2fpmeFQ5NDUQoqWZBmSaEE2rA8B8of1JYg//rQMwx8GDPjbfwYMwwJk2BIhmaItcfEMt56VMz3dPb1vtXetuWfG5o8B45wXU9W1tBEG4Xu+bmZFvnjx4sWruOfde64Vx7EoFAqFIhvY/687oFAoFP8/QRddhUKhyBC66CoUCkWG0EVXoVAoMoQuugqFQpEh3Kf90bIsDW1QKBSKQyKOY2uvv+mbrkKhUGQIXXQVCoUiQ+iiq1AoFBlCF12FQqHIELroKhQKRYZ4avTCXvitP/pXiR1FZoBDjgMeaEmPBJt5vLFnSUzHmIjoi5FaJbEvzB9L7MWVVZzOzSd2r9s32tpqthO75OUS++KZucR+/aVziV2tFNCPlD5FTH3mP7GOBdu/8OoLshte/9XXjc85F+cs5mHT0ElMg9LptxJ7Z2vLaKvV3EnsRhN/47HPO7j9L82fSmw7coy21na6iR3SGI/Nn0F/q8OJ7ToYX98fGG0tLz9IbMtCX954/mXYp44ntmcHif31P/6G7IW5F6cT++w53NOzl2dwUAFtbXcwJrOjVaOtIs3hXAHX0gnQ3ytv3U3s2x9tJHZ1yHyk5kdnE3tibiSxRwq1xLYtjKkUMV4bO2tGW90+7kN1BA/XdruZ2LXgQmI/XltI7KVN2CIiV7/1QA6DfN5L7D/9l/8Wf/DMsev0zfv9M+z0w8Re7+A+tH0cY/ktMWDRPHTwPNj0PDg27lXVw5iMlcw57Dn4PFTCeHOA1moD4+uH+H6khDnw6Xlwj7/xjX8uh4W+6SoUCkWG0EVXoVAoMoQuugqFQpEhjsTp+j54RdsxEy9Csu1wD76WeJSQOGHm+NKft5rge3509ZPEdm383wgCnIW54k+/wHH9EJzSlWu3E/vW4+XEnp+cSOxLxBGKiJSJE3JdDGG5DN4rDPdP5mu3TB62VAbP53loy3PBKfX7HZwjwmhbqfsQMS+Zw+8t4oT/0Zc+n9jHazj30sa20db0UDGxP74FbnDlxoeJPffyG+jvUB3nE7Nf5VIpse0ceLpV4ks/bIF/K+eJ73wKjp0cS2w3j+vt9jBGU6MY024H3OPW2qbZx0mMxYMFjEVpeCix50/jGstFnGN7w3yPGbbAKQ8L+N2oAzKzUALXGwn2KLyiySV2YzwDjRb2LJqbuNc37r6X2K9evJzYCw/NuXZYOA6u68Xz84k9iMwl5OajVdkNgxjX6/r0zNOCUXDNZ6Yf45y9GHPCov0SixYWoofFts22xor4vEn33nNxDod433rRJdu8D9tdX54F+qarUCgUGUIXXYVCocgQR6IXopjc+Cil60AfyYv4rLv/s++JQojTxxjhaHQcnSMI4Z9Eux79KVz+K5m9Hj4s9eFmrjyB/dHdB0Zbo7VyYk8OwxV96cLpxD4+Oy77od9vG5+JATEogSCEG86/6XZg9/pmiJxL4WAdolN+/Su/kdj/+t/8u8ReeQya5b0ffsdo6+q1a4n9Crlan9xdTOyNR/cSe2QcIX29ntmvSgluOYf4xRba3Q5hRx6OfxrWiCLYtuE+VsZxjrmzCCsbCUFzWL757rHVhPu4soDQu7MlhC1W6uhjroo+Ti0g3E1EZPMu5ufo0Ghi1ypoi2OgHm0/Sezb98yQsdIQ7uPYBM65vYg5/GQVv7/uIKztwhxCyURErr11TQ4FfpZtuOHz05PGYUxDLK2B0uD52MRlSJ+e8arfM9py6W99C89ZRLSaEaZJz/W6Oe2kSOFkQzm637T+lD1cV8zUZt8MZt3ppYNbDwd901UoFIoMoYuuQqFQZIgj0QscZJCmDSLy/XlDnXfTbXIJAvp5lKIqbCIJbOIEOKsq4n8bRvSD6QKMU8RBQO7JWhfHEVMhFBQh7Q4yVUREWl1EECxvwK21afdzs9GU/WA7qeGn/oc0RlEId9cP0V9jrG1zlz+y4MPVa9h1//qXfyGxFz7BTvfS6kpiHztx1mjr0eJSYo+OwkW+/Aoy6ooj84k9NIFd+pUNc9f8f195J7E3GqBHBj2KyghAD8TR/lEgIiIeZSC99AJc0VIZYxd00e6pE+jvvXuPjLZufQi3/u4tZJtNj8OlX97A/Z2eReTEpXFz7FZsuMxVym7zm+voF13imclLib24bmaRbfkPE3tnE9cyNITrPXUefXz7B9dx/FpDngVM/fV6OHeQitKpl0HbuFN4iDhKqZDHM/Okjbba6xz7JCIDjJ3nYq77lDHJGbGcqRam5Gwf0+PYIN5z2MNxdaIgOj760hiY/XLtNHl5OOibrkKhUGQIXXQVCoUiQxyJXshR4PEgJQbDwfC2ETCwuxvA6771mbd2SqJgd3sPl4LpCNogFRGRJrkU7OqwmA2fn/IsxEn9a+KdTZ/aunYP7uD7N+/LfqhUx4zPxQKiIopF2t2msIbYw5XFdEiH3HMRkfUnoAteexFJEOfPXkzs+zd/mtg3KUIjTac8evQ4sbsDuOt//9fhCgcBAvff/OFbid1ICQ/5AfrfJxohaiNKYGsTfXdzB0uOOH0aySxFohoii6igJbqOPoRabt/Ejr+IyNoyfjM2hXvUpUkR0Ry4NI4khDfmTXGjW4/R9qANqqVHbb19HfTGWaKJhvOghURE8mXcl/UVUDN5cre7YEPEIcEYpqWOAo4S2CHxqGrDFKnpkuANP87bLVAFpH0joY/5UU8lR1g2lqeA9GvalJARGc8y9fczV4DetGnsOXqiTWNUpqSJQs5cmJxnYxf0TVehUCiyhC66CoVCkSGORC+E9PLupPUSyGbXPTaoAo5KoO9TTgHrKnDLlr27S2H8C0ntqtoUPTEg/QFjd5w6b+xQptwJ1lXggItGB26pfwDthdkpU9OhWIDGQYFsm8YhokSHIICf1mmbbh5HiPzDr/2DxB6ZPYFjSNeAXb7ewCRnIqI3POpXP4DL+JMPbib2/U1QEP3Q1FeN6SbxzndHMHY90o1l/eCnYWoCrvjOGvqVB2MjfYqev/MYyRw33iafXEQmZ7ED/8oXkeTiCvic4+Ogab507lcSe6yO8RERuf0YWgSlYSRneHWy7+CYyTo6nMvjGBGRu21EIPisD11Gv4YLpEHhoN3QlA84NJhFXNvGvcqXzHnXIjrJJzeeH+VaCRoYlo+wgrxFGtIi4tqIlHFD8AvbRC90KfSDqb4U62msLA6vJfS9kQNBD3Y1Z2rz5p/xVVXfdBUKhSJD6KKrUCgUGeJI9AK75FbqPZ7L8gjRAGbEwu7bjG7Kj7doN5FdAvYCfG7gKduXOdpyDEJKQqBzsEwlJ3PEKQ/XTAihsaCLdA4Q0+/lPONzsUDlekpwM/N03IBc734fbnQYmG1Nj2E3/8XzCNjv9fAbfwDXf2IKOfTfe/PHRltbbdKnuHkjsW/8+V8ldmUMVEm+Brcwss3Acp4uPrmGxogShbK5tn8UiIjItZuITIib8KXLVGol6OD+5CqgEL7ym5BWFBFpbMNl3lxFVMX4MMb0qy98NbEr5Lqvr5sykcubaKtAkSduHucfnYb8480FRDusLiOKQ0TEGoebOzZG2h4RKI0zZ55P7BsbSGo5MWdqgTz88K4cBvxorZB4gtcyqagi7fpXSB4xoAbKVO6mnsM45AZI8hARaYWgv1oxjit3MafaIck/BrxemA/gKM2D6SG01SeKrkcJEUsNPCdBKkHHsZ/tXVXfdBUKhSJD6KKrUCgUGUIXXYVCocgQR+J0mZ/9TNl0FqYxBG6JLyWOxCHuNJ8KzQootCymk5olfmTX79PavCUHfE2xgI7tdKiTLKRj1hcy2jIoHiYpuTT0AUbWTnFDXPonR7ZLQjo2lWbnnweBya2dnQfHOkt8bZfC2nok5
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.03it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.03it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            " 73%|███████▎  | 228/313 [00:28<00:10,  8.18it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 14000: Generator loss: 0.01670, Discriminator loss: 0.36254\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABjCAYAAAA4j9PeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOy9SZClWXqm9ZzpH+7gY7jH4DHmEDlXVpWqVENLyFSlrqal7pYhCRkgmgUGZmwYFqwwY4WZFrCABQYNGAb0gEHTdGOFQGpZ01Jr6JorKyszKysyMyIyPCYPn+78j2dgcf7rEVFZykxBWTVmxJfm4devX7/3H855z/u93/udFCEEnsSTeBJP4kn8dEL+sz6AJ/EknsST+P9TPAHdJ/EknsST+CnGE9B9Ek/iSTyJn2I8Ad0n8SSexJP4KcYT0H0ST+JJPImfYjwB3SfxJJ7Ek/gphv6wXwohnvjJnsSTeBJP4s8ZIQTxZ/3uQ0H3Sfzk49VXrtI2LU3TkBhDlueYNGUxG5EmPZTReOc5Pj5CKUXTNjgbCAScczRNS1nWCCmQMiYq3nuEkN13gVKKLEuRUlLXFd46lNbQvSb4gJSSQCBNE5IkwVmLNhqj45AQxPcBkFJ2nxXwIVCWBfPFAu8CPoCUAikkzjsEAh8C1jm00uRZhtaSLMvI8xwC+BDQWiOEwHuHFAohBUJIBBCA5YgNIj4OIRCCR0rJeDLj+o33f8p37mEorZBC0Lb2n9kx/KQjSw2nNlYgBBAghUB0dyF0/wbAOY/1Dh88CBBCICQI0b3yEZ4mut/Hx90dFQ/vLeJRXHp41+Mny4d/8+NCBEIID98fEY/lJHkXBB9wzuOcw3t/8jlCCISI41op1Y1tEc9ZxMc8ipnLMQiAJxBOxmMg4HEE7wkBDh7MqWv3oddafFhzxBOm+5MNIeAf/e//Dbffv83egz0G/R7PPnOVc5cu8fq3/5B+b5P1rS2qquT1732XpnXM5gXzeUVRFBRlxXxRcG/vgKaxSClACFrrUVLRti1aK3p5zrlz5zh95hR37+5ytL+PMTlKp9RNS2sdSQeuG+trrKytEIJne3uLXmYwSpEkKXmWs7p2ihAagvPMiznHoyNu377NrTt3qSuPEAptFEmSUDcN3gda6yjLin5/yIvPP8u506fYObfD9tY6PgiUThmurIKA1lp6aY7SGmUMwTl89yUAoTRSS4SUNM0CrTR/8rXv8B/8h7/957363ffwyM8CJSU+eELwf8bffTBeeuU5Vtf6/NM//u4j91Y+BjCie/8lgEkUShl6/TWapsS1LXST1wcXJ7J3HbTFqQyCH8UdAVgfCM7y4UcsP4Bpj05m8ciDEDwXd07xy1/6NHiHwJNojZQqQkyIX7W1zKuKsq5o8Sgj0YlEG4E0AYQl0IIApQRSCpSSJwRBiPjcctwKEa/P8pxFiKAphUYJjZSmu6YiHn+IoC5EIAgPxEVYIhBSoTEoYeJxW6iKhsW8YlEUtG3bLdqQJook0WS9hDzL0SpBCk1iMrQyEBTBPQRvKQEF4PHC4bzDuprW11jfULsCa2u8D/xv/9MPuHt7+oTp/n8lQoDdmzcfAbQtkIY7779HUQYe7N1ifTJiPBnx/u5dZrMSnaSMJxOqsiHNUk6fOU2aZdStZTQaM5nMkSKCkkk0Sii09swmx5zaXGM4XKFqA7ZckEhB3svIjWZnc5VBZpgWFVIHsl5KU1csWsva+hoHo2Ns4/js9kWu37zO3t37TGdT9h4c0DaB2rY4F8hSSdM6WlvR2oa2bUEotE7I04TT26e4evUqaytrCBloyoJ+3mdj+yzjo/uYJGF1+wxKSLxrqBdzqrrABU+vv45OksgoQkBqiZQardP/F3dBnHyPLE0ig8C5buILCSF0QPAjfykEIQQuX7nA888/cwK6AomQig5DInNHnnyGEQYlNJtbWzz7wkvcun2XRVF2fxuBxAZHUy0oJ4cEEaCD1CUrE0E85IKtxTqH+LFH+fBYH+VnjzHMh1fghL0575mXFcFbRHBoGbMOFzw+eKy1lE1L1TYIqdFpgpIKrSVKBYJwgAPCSWakVPwembB4eC6PPF6G7xaYJWNdPhuCgkeAXywXJBFO2HUACBEQJQrnBFVpmc8LZrOCqqohOJQSaJOQpil5npLlBi01wUfWK3y8WiEEvLMdkwYXAiKAlBBkPFcnWlpf09iS1jb8eTp7n4DuTzl8kJw9d4Gnrn6Co4M7vH/zHbz39Pp9msZxdDRmPJ2jdI7SDiEUbWuRSpGnGYM0YeodIgQSo+llKWVVY6SmqVusAh8ACnZ332OQrfGLV7Y4v7pFYhSpyTBJRmIMTWVpbWBlNSPLYFYUHNmMO9MFb926hXUwL/4hd3ZvU5YNaZpQNaGTHjQhWFrbopTGe0trLXUdGfjpM6f4xAtPcf7sNpunthiurpOkGWWxwFYVTbVABIn0YEyGwOKtYH3rDHeuv421njAI9IbrgKWpZ7gGpDb4DpBWVjZZLCY493HS/B+dFIGAxPuHwBYCJwuYdc0H36GbWJPJHPMo8AuFFAlaG1KTkSQpxqQkJiMzOUYlGK3Jejm29pxa2WZ96PEh4KyNspFtqZMBvqrxrsF7hw0t4JEokEuZJcJxTGAfAdUfc7rhA1z4IcsXovupOyfnPIuqxNkmAi/Qtg22bQneY63DAdqkpD2DVAKlQCoBMh5RCP4xVosQ3c9LsH1EZnjk+JeLFUGcsGERlr8LRGUgdF8+HnPo+LHoQNc7hASPoq0ci0XFfLGgqiqctwgEiUro93L6vZwsT9FaghcIpSBI2jYgpT+RDuIYceADWkkCAo/H0dK4kqpdYG3DnwNvgY8BummacvbM6U7PcSe3uZfm9Po9FlVNXdUoBXXTYJuW1eGQxnuqsmTQS0FIqrqln+f0BwOkVLRx2cBimZcFxXyBsBbhfdQFBVhnKYsSX3epGJysPifDbbmQnxCYmNgprTFZRr/XI0sSlprRciXVSmGMoZfk+O6qCSAsZ98jvOBkgCrAexb7ByyODqlbiwueYd5DCJg1DTVg8j5VWTDs52xubnBUNBwcPMA1NRtrA3AWwpSmWXA8GgEJ07KkXCzo5X3e373HYGWVJEu4c/sBk+mcxGi0lBwR2L19j1lZIQQYYxDCU9salEIEiW1BDnqc3dzm557JeLo/QvqGRe0IbR9lNqmrBCESVoYJPRPQUnJ2c40z0rKRTDjYSPj2tT3u3LuHFgapwLmYajVtixQS7wPOW3SIk8NZjwuC4ASr/Zznn3uGU5trhOCYTcekaR4142A5fnAPHwQbZ3Zo5jOqcsTm6acRMuCVotdfxduWejGht7LOyto5ynrB9OjuCfitb5yiqhcfE3R/TARPwBKCOJk4zjuE+PDEfTqeMhj0GPQ22dg4w8raJv1+n36vR7/XJ89STJqSJglGGZQUKK3QWiGVQiuJCFBbj20stmlpqpqmrpgXz1BUJUVRUFULRuMRo+M9QrAIAo6wFC5QUmL9j9MPPwSMl6d+Mnni66y3TIspdV1g2xbXWmzbggeNASFQSYJONUIplBZIJRAdKw9+uQyImO4LgRScAG4sP4gPHIM8kWTiE/Hc5AkbXmqwITw6xzs0CKHLUHysVShB1XiqRUsxr6jqltBJEEZp+v0Bg96Q/iAlMYbgwAvwXuBcV+sQLgK5j6w94KJOLeLC57yNgNssaJrmcV35wzToR+IjQff8ubP8+//ev0vQmtl4jJKCxgZefPpZXvmZT/Da9Vv849/7XZ4/s8GhdTy4dY+v/OIvclBV3Hj7TT794hV8knN4vOCVF17mqRdeoJGGfet5b/cmu+9fZ//eXerRhMQ7ivmcg8Mjjg6PGB8eUU5muKbFeYsLAe89knCyoi4Hj1oOZiVQCLJBj+2nnuKFl1/m1avP0+sNUAEUntQkpGnC8zvPsLN2Op6olAihYCmkL9Oz7kKG4AlJy2LvHt/+r/5Lfvj7v8fd4wmjuuaVF55mbW2T79y5x11g4zM/w9uvfYdLpzf51/7F3+R3dw/523/7v2Xv1
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.03it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:39<00:00,  8.00it/s]\n",
            " 92%|█████████▏| 289/313 [00:35<00:02,  8.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 15000: Generator loss: 0.01661, Discriminator loss: 0.32549\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            " 12%|█▏        | 37/313 [00:04<00:33,  8.19it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 16000: Generator loss: 0.01654, Discriminator loss: 0.28863\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.98it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            " 31%|███▏      | 98/313 [00:12<00:28,  7.58it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 17000: Generator loss: 0.01651, Discriminator loss: 0.25587\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.91it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            " 51%|█████     | 159/313 [00:19<00:18,  8.19it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 18000: Generator loss: 0.01646, Discriminator loss: 0.22439\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:39<00:00,  8.01it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.13it/s]\n",
            " 70%|███████   | 220/313 [00:27<00:11,  8.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 19000: Generator loss: 0.01647, Discriminator loss: 0.19537\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.09it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            " 90%|████████▉ | 281/313 [00:34<00:03,  8.27it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 20000: Generator loss: 0.01638, Discriminator loss: 0.16904\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.14it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.15it/s]\n",
            "  9%|▉         | 29/313 [00:03<00:34,  8.31it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 21000: Generator loss: 0.01635, Discriminator loss: 0.14493\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            " 29%|██▉       | 90/313 [00:11<00:28,  7.78it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 22000: Generator loss: 0.01633, Discriminator loss: 0.12497\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.93it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.09it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.13it/s]\n",
            " 48%|████▊     | 151/313 [00:18<00:19,  8.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 23000: Generator loss: 0.01630, Discriminator loss: 0.10632\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  8.01it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.13it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            " 68%|██████▊   | 212/313 [00:26<00:12,  8.14it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 24000: Generator loss: 0.01626, Discriminator loss: 0.08943\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABjCAYAAAA4j9PeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOy92ZNdV3bm99vTme6U84CBAMkii2SxSrIkl9Tqltpq2aXudtiPftO7H+y/RY8OP/q/aIcdHeqQpR4klYaSqkiCIAgCyARyvOOZ9uSHfRJkVbTI7ogKuiOci4EM8N7EPeees/e31/7W960jYozcxm3cxm3cxrcT8v/rE7iN27iN2/j/U9yC7m3cxm3cxrcYt6B7G7dxG7fxLcYt6N7GbdzGbXyLcQu6t3Ebt3Eb32Lcgu5t3MZt3Ma3GPrr3hRC3OrJbuM2buM2/jMjxij+ofe+FnRv45cfv/db/xghJaGzCBRikkEABMRlQ3SO2jfEKkdpRUQggMiX658QghhCek+Q3g0BIRVCSCBATL+X3gXBV3+kA0qpkFKmz/7K8hp//sfPvT4cjkgkxvQnBE8IEWIkhPT/MaZziOnk6brIpm5p6jV5nqOUQokaIQ2z7V2yLENr/ZVjBQQSIvjgEUIgpEQguLy85OOPPuGD997jYH8fBOk9odJ1jPHL7z7o0GMIEAIhBBACpRVCquFg6XUhJEL+wuYvxnR9RDp2DJ7obbqKtieEgMpypMlBSrg53i+cw83fv/zYmK4lgkggeE8MASkEUkq8s/RtzWa9IgZP17UQItO9PUbTHaTO0riI6ROGgfHz902I19//9eG/ekuFIITAH//xH6O1pBrlSJHGUFllWNtjjEYIiXUWiNQbTwiBGNJ3kBJMptBaoZTCGEnbWkJ0aKUJPpAXBmsdQii8D8O3FljnkEqQ6RwpBQhBvekwmUBpAQGUSucTAe891vp0n4Z80LuA82F43VONcpQyw3VRxOBxzqGURKp0EUKIxBiQIp0rCLJcg4gQBM5bssxgjCKEiHNpfiil8cGmcwWs9cMtT5+nDcyvG2wf+LoQX2eOuM10f7khhGD9k8/RRmPPr4i1ofyvHxC7iO839H/xMdfzM07HjuzNu5jSELmZyHEAvYiQaeAkgIUQPd45jMkxWYYPDmJECgFSIUJMwCRIP4RDioyiqDC5JsSYcDqKBDIxDbIQE9iFAWSJwACm1ju8tVhn6buOvu9wzmGtp+s3hN6l76wkIPj8s5rPv7jko5/9HTt7W2zPxrjuC8rZHr//+7/D4eERo/EYJdUwiB1CaAQC5wMhOKTSSKX5P//V/8X/8j//r/wf//v/xr/40R8gjaAcTVF5CQNoIQYoimlBsvUG37Z471FGU04mCJMTgsd3Nd5asrxEZMUAvMPQDwPIuEDsLb5ZY1cXYBua5TXWeYqD+4wO7hOERilFNirTpL9ZEL+yAKYYXkOkVSx6+qbGdS2ZFOA6rl4+49mnH/H5Zx/R1AuazvLGmx/w/m//DscP30dnY6QUhOAH0E1jIQ6Ln5AC5AC6MaRzicM9BqRI16jrOybTKdNZxdvvHLG1lTGZjBlVU67nS47v7lBVJYvlkvVmQb1UXF01rBY9Xd9TVZqd3YqD4xlaGrIs8urlEh96Ztsltg3s7U+p6xYlJW3nUMrQbDoWy44sU+ztHoAA5yyvXi4oKqhGgkzllPmUtu1Bpe/aNBbnIK8CfWuxvaduWlarFud7Hjw4QpIBEpNV1OuG5WLOzt4IYzRaCXwION8Sg+bpk0tGo4Kju7t0fY13iiKPVFVBnmeEEJlfNxhdkpmMzq7IcoMQkdWqwbkOYwwhNui849//P19weV7fZrr/JUVnFfQd9bIhazxx3eMXa+yzV5w8/3te5A2zN36DrMqHlTdltFGkCSVEwPuQMhICCIUUmqBCypiiI8T0T6MQCAKBiByyBQhIFAh1g+XIKFLmKlKGSUzHEzGBjxRpskYgRPAh4IPH+Q5vLcF5/A04RZcmuVIoaZBaYIxhPHaMqpzvvPMBl5cXECVRPMCLbVprX+N5uMGhqAEBUmKMJESJ94Lgw+vMTmcZfegJG4uMEt33yCwjr0avEzohQQzAE0JASoFEEW0guBpre1zfYoxCDplhHDBMSoltW9bPn7N4/pTQLrB2he9aMiWw0eJEhl05eHqJEZKoDHfffYut44OUGQ8n8vPZrgAR03khCVKRVWO0gsXTT3n22aecPP6El88fY3Hs3n2DX/m1f8R3Pvh1ysk+UamU6cVIHMaIiMP9cw5CAJMPO4NAFGkUiCAGAB52O8MiC6C1ocjH7OwWHB7NePWypm4Cde0xpkEqR2ZKpkcjqqJiUa3YNA17ezNiNJydrpBCoEwkywyLa1ivl5R5hjE9xmQoDZXKWa8dm01HWeQIIXG+o2ksZak5OBqxXnWsFh3b22POLlZs1jXVSDEej5iMKy4u5ly8alBaIGWkKAN5mbOca85ONtT1FbPZiDvHFfVqw2bdUo0y5tcNVWVQWmKdx3aeGCNKSgiRiGBre8rOdsb8csn52YKiKsmLjNlkymq1pmsjQjq0ESilOD/r2NpxbG1nbJo2LXrfELeg+21HNcYuF6zO1uzdf4i/XGA//5zlywtOq4h++Db5pCLEHomh6xqkVKDAaIWIOiEfER8cQkRCDIluiIqoIjLebGs9hIGeGCZ92j4yTDaPIGW6KbkNECQxBqIISCkJQaTPEREpdJrA3uH6FmsD3qfMIWVY6TwUiqgkWifKQGeGw3148ugl2+Oc4LbxcYXzlv1KEX0cgF4SiIgoEYB3DqECDo9QApOV6Rgxbd/y0Yi9nX3auqYPnmh7ikwTgsPHgIoJ9JyzCAQmy4f9uMQ5l7aYSLTKEEoitCFKCRKiCyy+eMLq6SOuXj6mri9ouw0+BPIip8hzLIp1rOg3V8zPn2C6hqKaIY1gNBlhJmOI4vVWOMZIiDHtVoTCSRBNi4iRq5enXJ98zEf/7s/4yd9+RFdfs32wz2/+wX/PW7/yQ8aTKUbmhK4FJVM2j0j/RZ/OW8hhFxRQImX4wfth7RIQXFq4dRpDKYO3ECPGCGZbBc0G2lZSVJH9wxzXtZw+7YhKMZ5UXFysWa+XPHx7G+cq2o3GyDGfPnrOw4dv0vRLplPFnbs7/OxnzzF7hohgU9e8etViMklmSrKsHEBa4VxNNSoRSFarDVqrRCeEnrLSlON8oLBgtWwIHvrWM9sxFMWI1bJGCM9sWrBaBa6XF+wfTpHScfeNKcWFJhLo2pb59ZKjOxOqqmTjIkprUBmvXs7RmWN7u6TrPfPFkhgFbatQShJiROpANTa0TYuzAe8iRZETQmCz6disPd5/MwTcgu63HRk0rmWzWLP/wwnx4iXzF085fTBl943fQGhJjJ4YBFF4ynKStvkxQvQJQFRGjGHgrgJKZECXslahByB2iY6QAhET1ynwidcUgJKAThlndF9yxyJtRQUyAbUEgiaEgA2OEELixIKEEPDB4XwgksAf0qTOlEFnGiENWW6QRQI4IeD+vQOevbD0tieLAWMkiAFMh+xLCoHWCh99yrKdwIYWrVRKXyGBjDaUkymFUXgBSgiCdbTLFZnWCCVAK0xpkEGCj/jg8f4m85VorfECfPRIqfCbmtO/+vdcPPoxIWxw9LTNis1mRd0HnPcEBGq8j5qWBNGzsz/ji598xqRbM784olkck1UZUSZO9PWiF4HoiVpx8egpf/3H/wYV4emjj1lcfMGqPmH37hHvv/W7fO+H/4yDew8RHmwXiL4jjwIZFEH6dB2kApkWQ4kAZcB7gk8cqogxZXEBYtcRIFEwQiCDR/hEA7WN4/TkmqIQbO0YmnbOeDIDn6GkxAuHySLb+xU7hxqpDEYE2tDxzrvvsFisub6usb6nb1tGleXu/QllMeHk+YK8dFRVRpErMqV5drZitdngHGgNd+7tsbW9RZ4FprMx3rfoLLBZRZTOyHRF8BltM8dFx97+Fuv1mrZZINC0jQMRyUrDwf4Y10U+/fSMaqTY25+QFTCZ5jQb6Pqap
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.09it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.13it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            " 87%|████████▋ | 273/313 [00:33<00:04,  8.26it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 25000: Generator loss: 0.01625, Discriminator loss: 0.07491\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.99it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:39<00:00,  8.01it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "  7%|▋         | 21/313 [00:02<00:36,  8.05it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 26000: Generator loss: 0.01624, Discriminator loss: 0.06252\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.13it/s]\n",
            " 26%|██▌       | 82/313 [00:10<00:31,  7.30it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 27000: Generator loss: 0.01621, Discriminator loss: 0.05185\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.97it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            " 46%|████▌     | 143/313 [00:17<00:20,  8.21it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 28000: Generator loss: 0.01622, Discriminator loss: 0.04263\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            " 65%|██████▌   | 204/313 [00:25<00:13,  8.21it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 29000: Generator loss: 0.01616, Discriminator loss: 0.03443\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.05it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            " 85%|████████▍ | 265/313 [00:32<00:05,  8.18it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 30000: Generator loss: 0.01615, Discriminator loss: 0.02818\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.03it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.18it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.14it/s]\n",
            "  4%|▍         | 13/313 [00:01<00:36,  8.16it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 31000: Generator loss: 0.01618, Discriminator loss: 0.02261\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.97it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            " 24%|██▎       | 74/313 [00:09<00:29,  8.21it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 32000: Generator loss: 0.01616, Discriminator loss: 0.01839\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.05it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.09it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            " 43%|████▎     | 135/313 [00:16<00:21,  8.26it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 33000: Generator loss: 0.01613, Discriminator loss: 0.01474\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABmCAYAAABoQkJtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO19WY8k2XXeiT33rH3rfZl9umfIGYriJlJeYEgEKJswbOjBf8E/QA/6A3rQkwC92LAN2wJsww+CZZH2g0CLtKDRjGbn9MLuqV6qq6qrKrOycomMjE0PhOL7brCyurqGSIPw+Z5OVUXcuHHjxq043z3nO1ae56JQKBSK2cD+f90BhUKh+P8JuugqFArFDKGLrkKhUMwQuugqFArFDKGLrkKhUMwQ7kl/tCxLQxsUCoXiOZHnuTXtb/qlq1AoFDOELroKhUIxQ+iiq1AoFDOELroKhUIxQ+iiq1AoFDPEidEL0/DHf/hHhT2OYuNvh0f9wrZdbOA5rlPYaZIV9jBKCzsrdce28D+h6uN83hh0bARYVOgYzzY3DyvVSmFbFo6zHFy/d4i+5ynanWTmPVYrQWHvHnYLuxFUcX2639/7/d+T4/DSd2vGz76PPg+GUWE7Dn5fr/mFHR5hvKwx7k9EpHfYK2w7QP/bSzQuFs5v++cKu9Yw/xePg05hLzaahX3duljYCzJf2FmM6yXxxGgrTdG2nWGMU2tY2JGF83v7o8L+N3/6qUzDjW98o7CtHPMry/B88yyjM9CPl154wWhrGOKanR6er+N4hd1oNAp7kewP3v/QaGt+baGw63XMjzRBv5IUc8X10K84TYy24jHGsrOPZ8L3ZdtoK6FrxJH5HB7/7LYchz/7939Q2H/yX/+8sD+r/kZhO9XFwrZK2i0ZT69jr2D+JR3uF/Zg8x3jqP7encJunHujsOdf+od0wVSeFzld3zJ+fzzK95HTke/8h3/93NfXL12FQqGYIXTRVSgUihlCF12FQqGYIc7E6d66Cz7IIp5LRMSy0WRugWsKKuAvY+L5bAfH1IO60ZZN3Gu9AT7MD8CpMldcreL8/tGR0VZIXCJzv0dHg8Le64FXjIkPCzwc//O2mEMDxzqMwPW07WcP7euvbxg/NxrgZR8+Btdluxjjc8tLhf34AXjbwy3mK0WSEfjA/Q74P6Ekw8V1tBsJ+Gw/M5/Den25sFcPwd16KT3rOq632MJ9uG7LaOvTTXCkkxz36K2jX04d58exOfbTEDRwvk18vudh3hHVK76Ha3hxaLR1bmkOf2uirYy407kAPO7o8ZPCbjdNnv6og2fk0FzxHNxXHOL6R4fg8pmT/fkN8A9MnhJHSbbr4fm47unG8XB/t7C7E9onaOM5WlPZT2N6lf7AP+Agr4G5lSQm75zQ3k1l5WWcTdeYxsn+Ip/MPO7xneSxO+EWxTqBrT4N9EtXoVAoZghddBUKhWKGOBO94PtEKdjmup3TJ7rtggZo1OFaHQ0REuTYHtnmdeIYLutwiDCec8twSYIq3KYOhW8lQ7h1Iib14FEoWruOIfAtHDPJE/q96Zp5Ds6ZRBTaRW5HIma4z3GYnzPd+PEEbmaL+rW+fr6w1xbWCrvT/aiwt5/CVRcRyaq4vjdhSgFu4tUraOugA3phwYLrLCJi3cV4RQ6Oq4LpkL/48HFh/+M34Z6/efOm0db9LvppbZDLRyxEs4Ywq1qdLiIfyTS0F3CcRXOy4mF+pRPMu4BCCHufo+8iItkEbv2Fm3BrHaKZDu8/LOyd+w8K+8pbXzHauvjaK4X9W9/7PvpF4YX7e3DpP/jw/cL+6//7I6OtZDwu7AlRDxPBHPQF98vXqFCYo4jI3Q8/kOOwu43nE7ZfKmzbwfubE09zoqM95Y/sxmdEKQSOSadceflyYVdXEao4yjC3+xOmDU4KAJtGPtDv8ynHlO6jHCb3vNAvXYVCoZghdNFVKBSKGeJM9EKDXLOslPll0659rUK72JQpE1DG05jceMsx2/Io+sGx4IZ8toVMFaFzohTHNG24ViIiKwtw5esVuEq9LtzlZh1u9fbBXmFPSt5ESlu0IW940u/L93IcOp2u8fN+D1EG0RhtVavoF3VdWgsYn2uvmvcbhRThQbvmGxvtwq5TREkoh+jXXdy7iMjNJlzs+RZcwOEI0R4Xl/DcX7p2obBrNVANIiLXX0cW2706rpNlcIu9AG21fPO+piEagTrwOCvLw3PgytceZfYdmQmH4lUxLt//Z/+qsJu0g/8f/+gPcf4YDXzzH1C2lIh891/i/IwyzCZEddTrcJ3PXbha2BcvwhYR+W9/8u9wzeFTtEv3lQueT0r0XDhAlM5JuLNFGWI2rs9fZyc512YAgE02u+t4PqPeVmE3fdAnIiKLF75W2FsR5nOacTYfrmHRc3eccrQGvZtT6QGaK9zdzIwM8qQ0YZ4T+qWrUCgUM4QuugqFQjFDnIlemG/BHXJK0Qv8iW/TJ31Cn+uJwzuO6EI/MoPUbfJVfHITexTMnqcUDE4B4E9j0AYiIsMd7DbfPAe3qUkRBA8P4Fp1UkRLxLnpXuRjSvpw4PYMx3C367YpQHMcPt8y3firF1cL++AA1//0NnbH9w9BQTTacJEbTSQtiIhsrCDiIQhwnBugXcuCm7bewvlbIxwjIjJxcV/ioY8L82j3O28heuDLX4X4zPaemaTy7deuFXb0ELv2OyNKInDRr0hMCmYqQuzgWxRdkkzgYicp2j2iCIVXfu2rRlNvfO030RbRZSyI9PqvfwfHUDTM6jkz4WVvD884nqCPNvWRd81HlChRfqaBg7k6eHKA61PYj0OJNOxi2/bpAvofjCiZpAUqikWEplEIP/8FJRVleKZBijlUs0AjuPk9tNs0++hT9NO3L+A5UiCUcfWtLVAun3dNCuDAxnNJXKxfNtEx03gTI2lCRBr2syOTToJ+6SoUCsUMoYuuQqFQzBBnS47wKNC65LWk5Crxrv+YNGn3I3LdY7gt+QlBx0PSaG1U4GZZPm5hOMQOrUvB3CIioxguTURtheTyPerCPYkp6aHsXgQ5rlkRXKfugFKoBWYw+nHY2zNzza9cgGsYVGHnIdyZ7gT3OOjTjn9oUjNHY4xxs1YjmxJW9rEbv74NPd25FXMXeTiAm+jluP6Nl0HTbFy8Utj7PYzdwd6O0dbKPMburdaXCvtH+XuFHcfo+2BkUjDTkFIfE59oF4pI8WzMNZ8orje/DjpBRGRxHdEX21ugpXh+1usY01e/9DauUTETXnoUkTIeYeyYtqhR4k5CgrSDvknN3HwTiSbjHvQebJdfY6LbSBelTC+YyrXAvn2JzmENa3pPBb+vJKTrISJXYzzHcxX0v0XzrtoEbVG9hkSYaGyO3WJju7CXzuP8gx7mZ0b3u7JBOs6PzDu8PL9S2FvyYmFvC6JphMbLErrfUvRClGpyhEKhUPzKQBddhUKhmCHORC8IuR3j1Nwl7CVwcyN2SYhr4L0/j9ysSEx32+LSLhZ3Fb9f8LGbXrfhgnRCc9c7p1z1/phccaI6bCodVPNBFVQtU74y4HI/9HuHaIeo5JIch8nAzDW/df8RrlGjZJIa2nUoiiOmvPWI6BAREcnwN5clAu+g3eE23N1mHeevLML9ExGZa2BcE4oS2NzEDnpzCfRC9wi/X6ybNMsBRQDUqfTPXACq42HnPq63dzpXbn0dehw+7eCzvCFrOzaX1gvbsszX4H//9/9S2Ndegf7A/g7c3Yef/6ywX3sDpWTsUlD+KrmsXLooTohio0QJjgYYHplzeGkDO/ALq3DLhcoeJSQ76rHuRHq6gH6rCWrF0MJkmVUqrXTDedc4/8Ii+nLpItz4Jmk/pIJ3K6F31m2Y865KpbgmIyTvzK/hnf/sk1uFvUl6GNHYpFMmJFm54IKy6k8w1/YyKkNUwdz0WiUJ1sykfZ4X+qWrUCgUM4QuugqFQjFD6KKrUCgUM8SZOF3O7IkTk7scUannnMJyqq7Ji/49QmJ47cT8H0ARPpJTKE2Yg1MaCEJWagHCeFYNHVaRwQQcWkLCIxllLC24C
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            " 63%|██████▎   | 196/313 [00:24<00:14,  8.08it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 34000: Generator loss: 0.01616, Discriminator loss: 0.01200\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  8.01it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            " 82%|████████▏ | 257/313 [00:32<00:06,  8.23it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 35000: Generator loss: 0.01614, Discriminator loss: 0.00971\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.97it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.03it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.15it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            "  2%|▏         | 5/313 [00:00<00:36,  8.33it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 36000: Generator loss: 0.01612, Discriminator loss: 0.00850\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            " 21%|██        | 66/313 [00:08<00:30,  8.15it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 37000: Generator loss: 0.01615, Discriminator loss: 0.00678\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  8.02it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            " 41%|████      | 127/313 [00:15<00:22,  8.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 38000: Generator loss: 0.01613, Discriminator loss: 0.00562\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.05it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.09it/s]\n",
            " 60%|██████    | 188/313 [00:23<00:16,  7.44it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 39000: Generator loss: 0.01606, Discriminator loss: 0.00473\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:39<00:00,  8.02it/s]\n",
            " 80%|███████▉  | 249/313 [00:30<00:07,  8.33it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 40000: Generator loss: 0.01620, Discriminator loss: 0.00390\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            " 99%|█████████▉| 310/313 [00:38<00:00,  7.94it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 41000: Generator loss: 0.01610, Discriminator loss: 0.00324\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.94it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.09it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.09it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            " 19%|█▊        | 58/313 [00:07<00:30,  8.23it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 42000: Generator loss: 0.01614, Discriminator loss: 0.00272\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  8.00it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            " 38%|███▊      | 119/313 [00:14<00:23,  8.29it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 43000: Generator loss: 0.01612, Discriminator loss: 0.00226\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.95it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.05it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.05it/s]\n",
            " 58%|█████▊    | 180/313 [00:22<00:16,  8.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 44000: Generator loss: 0.01611, Discriminator loss: 0.00191\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  8.00it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.05it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            " 77%|███████▋  | 241/313 [00:30<00:09,  7.55it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 45000: Generator loss: 0.01612, Discriminator loss: 0.00158\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABmCAYAAABoQkJtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO19a4xd13XeOuc+zn3fmXvnTXJm+BBJkZIlWbIsS2mVwK82NurGNRKkQRO0QZq0tQPHRdEfRZ3+CFo0QBHUSNG0DdymSVojjhEbSFo4qu3IepAWKT4kUaRIDjkz5Dw477n3zn3fc/qj8P6+fTQzHI7S4wpd3681996zzz777LPnrG9/ay0nCAJRKBQKRTRwf9QdUCgUiv+foIuuQqFQRAhddBUKhSJC6KKrUCgUEUIXXYVCoYgQ8d2+dBxHpQ0KhULxgAiCwNnpO33TVSgUigihi65CoVBECF10FQqFIkLooqtQKBQRQhddhUKhiBC7qhd2ws9+5UVjB469bjsx/B2PYQMvHsfnMRef+7TJ1/P3JpaI0TlidA5xcXzCtTcPYy6O8SnfhCNkOzim3fGpX3Zb3M9Ot0tt4Xddv2fs//7Lz217HYV81vq73UZbdh8BK1cGmU7M7mM2kzR2MZc2dq5QMPahyQljH52cNPbK4rLVVpLu3aGJMWOPjB0w9jwd8/rZl42dSGWstvpLA8Y+cnTc2FuVmrHTOfSxXC4Z+4tf+ueyEz7/tTfQx2LC2GOFmLH9dsvYWQ+fd7q41yIi1UbH2C0fv9sK0O5qHb8Regb6PXsOeywAoltU7eIPl+ZTj36+FdiP5yadv0GPrnXGHeZ2GH/wuaPbfv5vfusrOH6H/XeXvwj/xpqe289VsZ65Hbv4rqb/b4C7tYvgYMdjvvTFX33gc+qbrkKhUEQIXXQVCoUiQuiiq1AoFBFiX5xuJk3cZWjdjsXAgTGnFKfP0x6OYY6y0bU5qB5RbUTJiutu/7+C6WU3Zv+GKV6mP2PUf+Z0mV7utMC1iogwBdgLtr9ex4nJ/cAcbhi+72/7uZcEr1fIgquNe/atzGXBpTo0xqMjQ8YeHhox9o2r7xh7emra7mezjXPm0e6pJ54wdrG/aOzBA+CKe72m1VYf/S6R8IztxsG3egmM3eq9BdkLnhnFNQ4Weewxjs349pydl7TvVbmIfiUTGFe+v6vr4HRdAX+fCJ2j2cExbdobqLbQr3tNmkMu7m+9a8/hlIvfFRwcH/PRl4yLz1N0WY3g/vNRROSXP/8FY/PZ+ZFbWFg0drdjz+FkAv0fPzBsbH6yo+Bq3yv2GoqrnK5CoVD8Pw5ddBUKhSJC7IteGC2mjF3r2C/ibbL93vbueo9+w5KRsGLDJXcqESc5WJxkQAHcKTIlHpKy0SGW7ZKzw4xEgv4Iu0O1Jq6gR532yX2M7cFB6fV69gc0GMkkbk0uB5e+kM8b2yNKIe7a7iP/jl3sdBptVStV9IXcxHTSvmK/iePX1taN/b3v/YWxywOQgh2dHMV1eHA3w33pkawul4N8bnN91dhvvwkp2G6YqkMi58ZAVeRJGtZH1Egqhd87jk3lMO1TI/lYpYNxCRKgdtJET7RCrFCNJIUVeh7WYniGNtEVydfmjX24r99qaygJqqa2iXuXpLFrCMZ7MIt+Me23Gyz1HNFSMZrO6xsVY2eztuyxNIh5sNXGQe4OnMJukrH3hPDjt4PKLdgD8RGuaPZeK5zpm65CoVBECF10FQqFIkLsT72QhFsYC6kEWuRu19qwmxSB0yWuIWFFsIXPhO9c8m84uo3pAY4Ui70rIg32Tu5FINv3Je3ZHQvIlXdaRDVQOJGzBx/EIxdXRGRgENFX2TR20D3aEa63QOAwZRM+Wy+AW+vRxddrcEvX7mAX+vSxsrEfGbDd2o0FjNjKOlz3mQrOsbSMiLRMDD7qAaIaRETu0c53r4uxa7fqxl6enzP2VhWu7G5Y8jFe/UQD+BwVSSqUrTqpKkJz5foSvruXwLi0AoxjgkectvZrG6BGRESamyvGbtcx9kFlCXYd11hJYE7M352x2mKaKebj0R0/hCjBx5+EoiTp5Izd61IE3S5gd5+jPfl5SKVAjYSVRA7RGD1SI/VY2UO/50jRdzn3TAnwXN/h0WIllBu6p3xdLAzitli9ZLGTSi8oFArF+xe66CoUCkWE2Be9kCYBeCweCkKgBCFMNXT4nZ58BZfckVxoo5vVDF0r6QxsFqPz4eHd0oB8cXbLfWorYPUB9dEJuVApOmeXXKgW7caLc///Z0NDZevvFAnxmw3QCO0m3F32bDhZUBBSCbRaGNd4Fm5mswI3foN2oderfcYu5bEzLyJSKjWMnfTRlxz114eoQeq0Bb56z3a3ewFoiDu3bxs7QcPFyo+BIeyGi9yQnZBOwy1fdGAvk5ymRMqJuE+i/lAgyvom+pgchcC/z8ExhRQ6nCP66fqNy1ZbZ/74vxj7yoVLaJcon3IB92fsqR839ne+9TWrrYdOIknNp3/m7xl7cXnT2GdfPmvshx992NjpAVAQu6Few5xYnr9lbE5etbaB+TAyhkAYERGKa7HURI6zPXV3984dY1+6eM5q68Chw8Y+cvSYsd0Yz3XMlbQH2mNxaUUYy8v3jF0lyuqpp542dqOB61pftectw8tkd/xuL9A3XYVCoYgQuugqFApFhNgXvRCj3ftYYK/b7FKwmiBO/uNeBdH2biLLD7bfPmSFghs+CX3HzmSbBOtNyqHrOjuLpgP6zud8DQ8o9C7kc9bfLMp3Y6AquhQ371MQQ6cHOyxSFwcuWCxJuXWLyH3w6c/8pLFLg6A6bt6Ayycicuf6RWMfO4Ljy80tY48nEIxxfha5cUsTdt7W0cFBY8/cum7sFXIHO7Q9fOqxD+Lg/wnXOYyMx1vdFFRDH9fpvmUoX0Ff0p7DvguFxnCeKIUe5Vu4/ANjNymX8Edf/b7V1sEF8C7PDh8xdqMNmibGzwZNotLpv2K1tZYAVxL3cE+9FOUvoZy7b1wFPXDoIGil3fDN/4Z8uteugA7ZWoeSwkmB8vn4p/6udfzsHeRIHhhEbo+BEpQ5ly68Yuzz5zBes3MIDBERGRlEnpBiEYqaYyeexI/o+SuX0a9bN69abb11EXNn8ACoivm7s3TMTWPXbl/BKQJb+ZEenpT3An3TVSgUigihi65CoVBEiH3RCxxQEFYJcNrEBLlzLILmLfgeuZLNXihfAudFIMWAG4cLlSD1BGfVC/fLYhuoL24LrkOzC/etRdSI+y519PZUCe/Q7oVCCZdT4RwAXgoKgvYWdlVTlLKxV4PL6MbtW8klelp0fLKAIIJsBscUCqANnvgQyvCI2IEtZy+8ZOwSueWxFN2fHJQQD586abW1dBcu5PABuKK5PtAbCZpETz/1IdkLTuQxdg6pSFzKb5EhroFph3zODlK5voj7ciiAMuD3v/wbxj53AZRLs4rffDlU+ueFj8AVjtP9bd1Fysp4B/PuoR7s3tPPWG2VbsNlvkfKD28E7nKPJh7nW9jcRB93w6tnzxh7jXJgdDqYQ4HgHv7ef/5N6/hkCpTCiYc/YOyjhyeNfeblbxl7fhlBInEP1JOIyMYqgmQcooPOnwftMTZ20NiPPI65srx412prfQljV62ADjp3Bs9QqwIqaMTDvSonOaOMSKdyS94L9E1XoVAoIoQuugqFQhEhdNFVKBSKCLEvTrdLnGYsFHlFaWDFo4gprsTD0WVclsYP5TUVkko17iGiZH0eMo8OJRTxm0goskFckYhIowaJTv8oonMeef5j6O8gPm/WiccJZbiIE28WZ66aAmWCPWTFyOZsmZfXBv9Ya4BrSpGkaLAP0iyOEhLfzs3LiWLaVPdoYRHXtbAMDqs4iMiiVMompPsoYmp6YcPYb1J0Wzy5Zuxnn0OUTy5jy+IOP/essdNUnn1hATwh58BtbaLd3ZCmKCePIsdS3vZzjRM1vav8EyXfqXz728Y+RsloTpwEl1iIYewO9iOKSkTkZwbAlSc3IcXr1ukZqoFjnK1DbtdN2qVwqrRHsrSI5
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.92it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.03it/s]\n",
            "100%|██████████| 313/313 [00:39<00:00,  7.99it/s]\n",
            " 96%|█████████▋| 302/313 [00:37<00:01,  8.03it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 46000: Generator loss: 0.01611, Discriminator loss: 0.00141\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABmCAYAAABoQkJtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAf90lEQVR4nO1dWZMk11U+mVlZW1f1NktPT49m0WhGM1osY2uxLWELOwxhg0UEhv/AGwHvBO88EEEQQRA8OAgC7Agb8BZgWxK2jGXLtmSNLXk0mkUzI83Sy/RSXdW1ZmUlD0B+37ld2dNqQYKC8z2dqsq8efPmzaw83z3nO16SJGIwGAyGfOD/b3fAYDAY/j/BHroGg8GQI+yhazAYDDnCHroGg8GQI+yhazAYDDmisNOPnudZaIPBYDC8SyRJ4mX9Zm+6BoPBkCPsoWswGAw5wh66BoPBkCPsoWswGAw5wh66BoPBkCN2jF7Iwl/83fOpva9eUb9N18qpPRqNUvtOYyu1y8UwtSvFILU7/Ui1NYji1B7GI/oFQRUe2cUC2vKctcNmZ5DaBd8bu12z3ae28EPgNNalfvWjIb7v43s+xp/8we+J4X8Wf/zMx1PbDyfwQxHz0a/UYRdLqd0d4BqKiFy4dDG1F1eWUjtIcH2nZxdSuzB1ILVfu3xZtbWyvpzapQJuN4/m1HBEQUL0vSd63o1orpcC3EP9Ie6bRN0b2D8e6UCkdmNZxiEsY1xKZRxjOMQY9bZ61F+9v+oz3zfJ+HMMAn/89iISFjFeId3b/R7u5RGdF59ikvDzQmREzw/f98nmY/IY4XtXn4Y/juJY3i3sTddgMBhyhD10DQaDIUfYQ9dgMBhyxJ443QrxYautgfqt0wf3wxTNUgPbFQvYplYCV8McrojIgHiYcuiTTfzOEPs0u8zb6j4X6YuYuGY+RpeovYgooVpJN1YC1aX6VS+D7NmNTPEDp8+qz3UfO4XENRWCgLbK4Mwccq0VZ/DexGfV6uA4D5w4ltpBoKdFs7GJ32j/xKNrQhx4h7jtsODw4cTbM7ff6+Pa8Zjye8E/fP2rkoUrA/CqtQDrDLPFYmpXS3ReBWwTOnfBVL2K/q7iXHzidCdL7dTef8+Z1F44eVy19ex3vpXay41Gagc0P5j/j9W80WOn+NLxFKmmTmmjE5P6JH/ZkLGoVjEuPtOt3K7aRvcxa9ozp8prPT7PbeemqdNx1jdaY4/CY6K64ul71qftPD/D5nPkk3fOKuZzMU7XYDAY/m/DHroGg8GQI/ZEL8zU4bJNS1H91mzDfWTXcn6GwnjU6zps39f/AWX6jUPGmj0KJaM4ES/B/m2Hqgjo81QZLg3TDvMzcHfZUxltCxkhGmE03m2KYh2yMg6//+lfU589apfdrpDc/SKFHfH3rmv2TgIKKI7guh8tYru5++5L7VNPfxL9CPR12FheTe1KBS5fRIc8VMPx3l6FKzhDIYQiInc2O6m9fxJu/K2V9dRe2Ie54nsYh53ohX7pMPYpY/+C38U2NAeKAfrr+fo2KJZxjkx1tLrY/+JyM7XfXP4ejl1gKkikXsX90Wzht26E+2SUMJWEvrgU1SgB/xXRXGO3OCJ+4iPzaPePnp5SbT3zV7dkHIpE+TAN5/vcGYxDPNT3Gd8rfD9kRGNJNMA4VCt6rjAlwfsUfBpjDrGjbdxnyXCItgoBNowo5FNF7gmNrxMW57tfvEvYm67BYDDkCHvoGgwGQ47YE70g9Ho/ctzoKmWxxORqVGnFn90hXnF0X9p92pDbYrcnJneqSyEHQ6df7BEU6a+GPA0ZkAsypGO40phMHXC2WjTik7n7/1lZdAZelVw77lifXNEeZeN0lfvpZBwlcGujPjLteiHcwagDF7nR2EC7HVAAIiLDLvaXEbm4dMhOgiylFkU7FBOmlURaTaz6lxOcy+bGWmrvL9P4FjR9lYVCGdELYYg+Jgn6HtM7RuSBQvAcd7Hn45gtoqwWKfKiReMQk4va0+EHKmOqVAGdcvrhJ1L7xhs/T+1uH+NTdKJIPA+fncPQ9/jh2Czu07MLw3Gbb0O7jWtfpIwwns6Dvo5YUn1U2Z4+fY9tmJ4Lac7XnOxW3o5pD70N3ac01kOH9uBnRn2iOna7ZDfUiMj2B9W7hL3pGgwGQ46wh67BYDDkiD3RC5NVWvl1XrVDcovZtWK3h4PBI3LpB8NsF4j3affg5q3T6ueQXEH374RXJjcH+MBUAZ9KSKufrjeR0EnzeY1oy91EL1xp9dXnxw7BreVF8EqBV1upH7TCyquwIiJHKWi7Q55Zp4fV/GhArjdt3+3AxRUR8ekajYZwLZUHhykhAzrGqKxX8ztNUA9xEe32ujimJ1hp93dZMapA16tE+3iCcfEpYoHnqefpPvKnNiXcdOh8D1YwqGscteJ0l1fKYxrv9cUrqX3PiXtT+/rlC2hrpF3kkHx0tiPyf/m8zt1Cv158RV/TLLh04X+BowFKZcxTl5rRN8t40RhOKOB23SvN0RsDus+zU4LoeG5r1Ng0J78QdTag5Bdvl23tBfamazAYDDnCHroGg8GQI/ZEL6w24T4WHZGDEn32ydXhlcXuiAOVsX3RCcrnl/iIfNkJyqGvV1nzc3xUg4hIQH3hhIrugPdhqoGTHrY5PtQvjmR4t26HG/1O7g1HWPB2nLQfw3UOtIcsa3ReJaInJihZoUQcxnDQI1uvToe8KkyJFqyVEZdh99pIjkhm4MqJiOw7PI99EkoQGDJvQmPf0xRMFip0/lMe63+g3QKt/ntDuNtu3dbOBrRmmz2MS4miCco0V3l+BOLO4fFaGZsrOEbjzkpqs0ZA0bmoPKX5KGWKJuJ5e7WJcXhleXe3eki6Jj5PQm88VTDcgRLUCRHjkxiYFoscPe16DdEMG3RMz7/7u6LnXFSmCDiBYxs9Mq6tbV9YcoTBYDC8b2APXYPBYMgRe6IXrjXgBgSOtBt/zkp8KBd4xRJt+c6LfDWkttTfA+eqj6cwHKZCvKw0cC7xQwdh2sBz5AlV4kSB6AXKjR/2u3I3hIlenS5SJxMavMqp+1N75sjp1G6tQZ8vammtvo0WJQi0oGswMULwe6FECRQDLoGi+9VugS4IiN7o9siNr02ndon6Xq3o5Ii541ip75EE5FtvXUdbdIEWb0P3YSfEHmimQUwSn0RhJDQpopU3U3sipvIzInLjJnQJCrRSH5B/XyshEqLgYf/E16v/7OV6ND+jjPuEqRV3kTzMkPhkWqxE28TU1k+WdknTTFCCArnRHNWgtUd0J72Mm95TNt/X43UQRETK5fLYfViykukbNYwOA6AkSTnaJIMeYR2UbaSh0QsGg8Hw/oE9dA0GgyFH2EPXYDAYcsSeON35aS6zrn/j0K4BhRcx99IjvtQvgItzSx1TMpDwYbiUzZBCjahZKTg1WBQPpGo1c2gYlZmh/TttLhUiUiK9VSH+cNgEr1r27i4wUi5rMZdoP3jR+tyh1J5aQXjTsafA6RaeOop9e5qX/ACHdtFv7QsoLx7xNpyVVZtUbXVY27eGEj+HD2G74uxMan/oCMrXvP7qK6qtn377udT+7Od/N7UDGu+ldQjxfOk0Qsx2QsTzIKbsNp8ysUgQaRDjfePq5auqrS0SfRlweCAJGt0aIbOuQmsPo6Hm+zhjMaAxVlwvl+sZcraWakrNTxaTYV1lHocK8e8Pzmtu/ZXrd2QcVNn2IR8P2/gqXO7umZcu9D70XBhEzpa0dkNrL9FgfEkwl8dlTBJXvdUBv81PHOaXeRxcPe33CnvTNRgMhhxhD12DwWDIEXuiFz5wZDa1nYgx5TqwnWSU3lFFQJzwE94uUmEx+K9otuA+bhIfEZZ0xwZcNXgT7muPMp5qFbj7RRbraWN7EZG6B1dtQCImQ9JCvXJ7We6GYUvrh87Mgzo4cAJ2+Pd/hn0e/0Rql46hgq8fOilpIdquVJEV5r10Dn3/+evYhsZnsqC1S5MpUArDqRq+3wdKYXU/bJmDtu3EIdgiIsdaC6n92s9eTe1+eyu1D07ieO3B7tzXXg/ufjdGW
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.10it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:39<00:00,  7.97it/s]\n",
            " 16%|█▌        | 50/313 [00:06<00:31,  8.24it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 47000: Generator loss: 0.01616, Discriminator loss: 0.00111\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  8.02it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            " 35%|███▌      | 111/313 [00:13<00:24,  8.26it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 48000: Generator loss: 0.01610, Discriminator loss: 0.00123\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  8.02it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.11it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.10it/s]\n",
            " 55%|█████▍    | 172/313 [00:21<00:17,  8.05it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 49000: Generator loss: 0.01612, Discriminator loss: 0.00102\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABjCAYAAAA4j9PeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOy9y890WXbm9Vt773NORLyX75L5ZVZm1sV2VTfutt2m1bRkWt2IKWKMGMIYib+CARJ/AhKCIQPEAAkGCAkhuiVAbmO3q112lauyMrPy9t3fS0Scy95rMVh7n4gstysTuVUM+E7q1ffmGxEnztmXtZ71rGetI2bGm+PN8eZ4c7w5fj1H+P/6At4cb443x5vj/0/HG6P75nhzvDneHL/G443RfXO8Od4cb45f4/HG6L453hxvjjfHr/F4Y3TfHG+ON8eb49d4vDG6b443x5vjzfFrPNKvelFE3ujJ3hxvjjfHm+P/5WFm8te99iuNLkDXDTx8+BaYYdjpXxH/vf4KhiCcW2kzEAQwQED881Cvp75ktNP9ko1fX5P6mpy+Sxyki//h7HvtK//IemX+x9NX2Fc+5383P1+9KWknQDCTr1yjyPohwAjSrg0Ifm1BBIIgIrx88Zxpmnjyvb+NtgDj7H6DfHWOTG299zZcZoapoaZ1bM+Gcr1eOf2/1PE/G2f/zjZ/rINkZ6+3P4d2ujaFgJ5N0S9d8l/5/F85p5zmS04fWC9CRE5/OhsbEWlDCsB8uOPu+ec8efiAy+2AmL+nqDJOM/OyUFTP1uZXL7jN4Wn2Tv+u13z+91+6HsNQs3oen/uL3Y7f/P73SalDi7LiFbPT+vVFgyGoGmqgqpSiqBZUDStKKQVVXedaTVnKQikFiYZEqef3i7U6vqb21fX5r7gPs7qH1fexGNy8uGM7dLzz9oO6bupPkNP6Od/dv7Q31gmt42RtbNrvrJeKGfXe/Q8hBGIMhBCQIOt1nnb12eL7pTsSTt9lZ98t53sRw0xRM4rW1xCEgJuQNoZg5/tqnfj6Hjn981fGFd8XRY0XN3vmpfCrjq81ut/5zvf4j/7j/9RPXhaMgmKEIJTiNxIjoIUg8WyBBopCjALKustUMxIC4BupTYDEgJZyMrS0gQiEKKgqSCAGf6GdI6awLmAJgqiuCzDUAcaEEANWik+QGKYKUo1ICL7IrW7uosRQF51QN0nw95XCug5VicEQU2KsRi4IFv2aUgoQ/Lv/m//qv+Qnf/Hn/MF/8J+wyOBLRhXUiAhdCm54xcck54JfWiQEX+65FJb5ZFSCQIiChLpo8d9FhBQCXfIFjQTMfJxLKQhGDHF1NIhQzM9fcqlmAVIQuiiE4J8vauSiFHMnEQInZ2NGMaMUX7gFX4SqvuC1rtgY4+ogBINi1Sn6PRhCKQqqCOqLNCW6FJHol/vsL/9v/uh/+K/5x7//O/zeb3yHYEZKHftx5uNPP+ezp884TpOvK8HXighBAghu1EzRtmFEUIPsl0MxN42G/93Ux61uYXLJ5FLIWgAlYPzgN77Hf/Zf/Oc8fPA2x7s9MQqmGcPou+TjHqR+r7A/Lry+23N7d8f9/YHD/Z5xnBgPI8f7PePxyDxNzMvMpAt34z1TGel3wsWjnn4biBGsGKo+7nlRSjEEJURA/C7a/igFSjZ0yZRlQa2Awv/5P/5z3nv3Ef/hv/8HpBhIXUfXJWJKSIyIhApbFBEIQXzegyAhUr07pooWRZeMaqEsmby4vVAztBhZ4ThmpqkgEthuNlxcbNhsBlLfrUbZ59/3k2pB6r1Q141QCChlyZRc0OI/ecmEWA15FMwWpvnIflq4PWZS6tl1PUPsSV0gmPraLoVlzpSi7sTxfS3YyYEW/QqwUTMKvm7mbByXwv/0z37EFy9u/2ZG98HDh/zb//gfkXMBU0IAieKDU+y0sM2qZ2zezIdHQsBUMdOvIMUQQ52oiuiCLyBb0aYPfjMoas3o+iSY2moU1+9qKBVOBhf3piLVyPlb/XvbhgSKumcQQEshSAWD1WhYneoTYgFphrVtUvNzWvDzx6hQJ/Xq8gqA41KwWFajjTYnEwkx+P208wDFFLPgmwfFxBe6318dgyDYilzFowDxG/BrZv2h/r8aq9c38UUWBDSAWEPL4JZd6nWaz0F1LlF8Ht2fKqI12jHz3wVKHdMQ/HtDcwzUhRL9b+cRiNDu3+9RrZC1zU5A6/UpkUUSQYQcEjkJc+gYTcghuoNszlcCimAKanVMcGPUxhrzdRwaKsMQE7SO8ylkCH6d0QfJSmF/PHIYj2z6kXEcEYHD8YhhbIaO8Thye3fPcTyyHw/c3N7z/PkLbm9vKLowjQvTcWKaJqZp5ng4chyPzEsma6EEIyToNpG3yjVP3rsi9X1FZw4kJAZiXVaIO7pizeCBFqlGGl8vPrp1jwjDkNzRdpHUx1O0VPeIqUeroX7yhPvqmqJumhaWBMXEr0+CEAgEjG7okNARQ2S7GdjuNgxDT4jRDVkuUOoSjgEtjkJbpCSmbm+azYmBrIqJ37yaInR0KVJUmKbAsxvh2W2h62befhB5ci3EtmeLEkzoYgQTty34+g0rtNXT/qFGKGptC2Pm++eXgr9/5fG1RldV2R9GTEtFfyDq3s0XcN0kpkgRQvAVbHViwxpqnIxu9b+noMF3Z32fLxgPlepO0IKaEUKgqGDV6IbQwojqcWvYVFdR3cD+uq+000Ixv0CMQlGrRjw4YsuZUAdd9RSyWP1/zkKwoqwb2CqidxpAsaKoZl/01aqoAVYwLWBh3dS5WDV2bnC01Puv3wPNOLTNdRZCfSUkPIVq2sLJ9RBCiOvnQjidO2KkFEla0OImJ9bxbaFmFDdIa+hpPgchyBra9pzGyayiMFUUqxvTDd3KemhzsqfQP4hUVFMXko+Kh4fWHCSU1DN3m2oKAzklctczB0FjWGmYsK6BE6uiqxM6jZGA319FuW1eUwhnAa4hEmExVB39xhjp+oFpVg7HmXmeuLu74fmLl9zuD+zv9nzxxRe8eHnDuEzMy+R0QsmkqGy2CS3GMinzPDMvheM0MU4Tc87kGkVIMHIJzOPCZjdwcb3huB8hZyhCLIIVIS8+3kWLRybFsFKNpvqeCBIw8UgEIMXAbtMhBqmLdCn67pEGWKDIKdQ3q47YTuuyodmSK0WSlVwccPW9I9lNiITYEUJCEGIU+r4ndckNWc6UCjpa5KgSTramrvNAcIeaEkJxZ2JGqfsrLMa8zLw+ZD69Mz6/67k9CCkqx2nishu4ftCRS2FWI4qQYgK0UlO6onu/5Qg1gi3ZxzXncuYIjNj88tccX2t03eCoe3pxLnXlj9RWI4o5/1QKK1I1E7TSCitZ0jZRu5c6jV/h2YzV0Pk91w2pdjpXRdoOQASRsp7Qzv4NUqmFX+Jq2vfp+q2hclWG1fBzfbviiKBxjjQjVxeinVycmVa07r+Xkk87vb5OyWAQpLHNJ4PSgijn9DjN4sprChFWF9y4v4ZsGwLG8AVfb0+qcYyhIXMo5WQ0RYRYw8Zizik6NXOai+ZQJYT1ugVHxlKvKcZY+en6/nqN7liUecnMS3aDWO+uYa41tDSrfJtg4s7T15yPrZY6N90GHS4rdxsJQLq8QvoOyb4OrRSnC9Yl+FUOcL2INobtnmgAQahY18cacwcVBDPnO4IExHr+9//tD7l5dc/tqy+5uXnFOE8sS2YcJ5aSkRid4w/Q9x39EEnbjjAEbMmY1hB5mljKRC555XrzkgkBuq4ninCxG+j7xGFvFFP3LCYEiQR16m9ZlHmanfIpQiASK4cqof50Nf8QApvNgCB0XeeRJ4BEBEegUo2RNksrgQr3KVrqdxbmOa/Os99u2W43bIYtMSZiiEiIaxRKaHtU/B5FPfIpLYfiFKUKjnhXRKdruB9DpER3KMdpQfNIVOU4Gp8fEi/D24ybt6ATik48vfmYq3DPty6u6YOiEQKBWMFK0OD7FHXn5NwlIoFlKUzzkXFcyDmTukCKwdd9COua/1XH1xrdBrEbUkNOG9HRijQKF6m0glBDjGpEQksgn
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.13it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.16it/s]\n",
            " 74%|███████▍  | 233/313 [00:28<00:09,  8.25it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 50000: Generator loss: 0.01612, Discriminator loss: 0.00084\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.08it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.17it/s]\n",
            " 94%|█████████▍| 294/313 [00:36<00:02,  8.44it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 51000: Generator loss: 0.01614, Discriminator loss: 0.00077\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.18it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            " 13%|█▎        | 42/313 [00:05<00:34,  7.92it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 52000: Generator loss: 0.01616, Discriminator loss: 0.00079\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.91it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.06it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.17it/s]\n",
            " 33%|███▎      | 103/313 [00:12<00:26,  8.05it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 53000: Generator loss: 0.01613, Discriminator loss: 0.00061\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.05it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.03it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            " 52%|█████▏    | 164/313 [00:20<00:17,  8.31it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 54000: Generator loss: 0.01614, Discriminator loss: 0.00058\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            " 72%|███████▏  | 225/313 [00:28<00:10,  8.18it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 55000: Generator loss: 0.01619, Discriminator loss: 0.00049\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  8.02it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.05it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.10it/s]\n",
            " 91%|█████████▏| 286/313 [00:35<00:03,  8.27it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 56000: Generator loss: 0.01614, Discriminator loss: 0.00042\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.89it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.04it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            " 11%|█         | 34/313 [00:04<00:36,  7.55it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 57000: Generator loss: 0.01617, Discriminator loss: 0.00036\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.98it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.12it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.05it/s]\n",
            " 30%|███       | 95/313 [00:11<00:26,  8.36it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 58000: Generator loss: 0.01616, Discriminator loss: 0.00031\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
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          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:39<00:00,  7.97it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.10it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.07it/s]\n",
            " 50%|████▉     | 156/313 [00:19<00:20,  7.74it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Step 59000: Generator loss: 0.01621, Discriminator loss: 0.00034\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABmCAYAAABoQkJtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO19WZBd13Xdvu++eewR3ehuNBrz1CQBkCIF0QQpMaIYyYosRbZKtlgulZK4nKp8pCo/qeQjzkecSvyRj6QifahUjstlyXIiK7YsU6JEiuIEkARAzGygJwA9D2+e75CPlO5a54lNNFqpF6ey19d+r9+999xzzj199zp7r235vi8KhUKh6A5C/7cboFAoFP8/QRddhUKh6CJ00VUoFIouQhddhUKh6CJ00VUoFIouIvxhf7QsS0MbFAqF4gHh+7611d/0TVehUCi6CF10FQqFoovQRVehUCi6CF10FQqFoovQRVehUCi6iA+NXtgKv/0fxgLbtqPG32wrEtieRxt4xmYefsPfum3HOJfne2goDhE76uL4EAIswtQWO2zemkUXKs32BHbr3t7ATmd70cJjPw9sxyoa57JDscD26d+WJ23YLuxv/dN5+SD8wR/8hvHZbaL99TqObzlN2G4tsK1wJbB7snHjXENDucCOJhI4vol+adVx3loZfd/CpUVEJJLETaaTOFfYqgd2s4F2VWv4veuaY5rO0nljaEuljHFsV/A9z6E//KMfyFb4+u89F9iZCI5/5omTge1YdmDbyWHcRyRpnKuwNhvY0TDuMZnB/JDcSGBeurUY2K+89Z5xrhTdo5QxXsd6MoF96uREYLc8jMn0vZvGuWZW7wV23EsF9kj/Plwvgr6fX70T2EtFXFtE5F9++235IPy7//wptOs0nvNiBce3W7jGhYu3jeN/+uZUYB87uCewewXtPXBkNLCb6+XAfuXK+8a5nn4WfTyS3h3YU+83Avv18xcD++TEfrS3hrVDROTSHM7d00fzbgO/mVnAc943hHl+9Ogu41zzU6XAvvbmijwo9E1XoVAoughddBUKhaKL0EVXoVAouogdcbqRKHg2u2PZtoS4FJdMh8lP/MYnVtej33d+9iwcb4WIm6MGxKLg3OJRk+OceQPc4vVX8oHtOOCEkkkc/1j2ONo4avJfnnCiHt0XEbwhauNWaDfNzkulwC3GkuCtmn4Vl7DQKbsS4PLq6yZ3OnNxPbAdAVeVGwKX2DuINiYzmAopz+y7OPHFY2OHAruaB/dZLoA/DFPfl8rgv0RE6i3igWmqhG0ck+1PB3alcv9+FBFJ9+D4fcPjgd2z7yOBnV9bDuzWOmynBT5aRCTpgKPtHT0Y2FOgH+X89K3Anq9gDjdG8HsRkZ4RcMc9CdzX1//TNwL7+QXwgv/ws88EthXG3oOISDk/F9ihMDqvFm0FdqkJTjjaxvw6kDLHdCu8+jZ45Jtz4JCzORqfDPjOjTsmV/zEronATvVjX+Hc36K/fka87+//7pnAPnnsqHGu06O4Tvwunrm1Egbic4fA+56YfDiwf/6qyTV7Kcz7wj08W/UW7FQCz0Cjhn4Mx8xnK5rY0bIZQN90FQqFoovQRVehUCi6iB3SC+xGm5o4Frm/YXK33RZcMKcF18htM73QwS/weTkCxOP/FQizqs1SKFvjgHH8QBNubk/mHK7v4Pi+fsQz2UtwW7wMQlxERLzsUmD7RJUI3XtsGz3bqYlRLcLNXd+EC1VqgB44feJUYC/M4HrvXLphnKvehMvZm8N9RRYxXiN7QGcMo+skHIdrJSKSiw0EdiYFd7laBk1Tbk4Hts/j7sN9ExEpFVv0CW3pJXrDphC1cLQjfm0LfOTh04E9fuTXAjvWi1CjCrU3FMG4eVWTAnGI8lomV/btMlzszDBohOd2w+7JgUIQEXF83NfKKuKTnv7Ms4H9N3/xYmBnU5ibe/fCJRYRGYvhsxuC614J0zUb6N+BDH6fzW7vUb/yBqiV44/1B/baKmieUgFjsidMYXQi0pdGH109B/qpWAOtNLIfbd9YBz1x2DXDTycwpWT9Juir3F2M154JzEf7xlxgv/YaaEMRkclhhKzdvgu67vO/91uBnUbEmXz7r/4msG9eB1UnIhLxI/KrQN90FQqFoovQRVehUCi6iB3RC5zsFbJNSsAKwTWzKPMsHILrELZxAicEN8/qqEzskuvO5w1Repkfgivc6H0zsG3X3JH+3S/968Ae7P1ngT07PQN7Ci7MzPRCYK/m4Q6JiEgWu81MENgUYREObymnGSARNt1Hx6HsJ9rND4dBdZx/De29NgP3rdk03XCnjc+b5UJgNxror7kF3NexY8jMOzJpjmm1tBrYi0vXArtYBM3SJmqo2YD712qamUHNNo8xjilXYDtNuJyWmDvHW2HuyuXAHjjxfGCHBdmD6RzcZSsFOz91wThXIo1+yVP2YZxGO5PB8S+9juNf+MJnjHNlQpiHB/eDBkg7oIm+89/Ilb2Fvh5Km89DDz14PQOgfEoJzKPpRYxJzqKMw9D23q/27x4MbLsMSmFgvA8/qm8GZqthzrtb9/BsDPTDpR89CvvkIVxjr4dsr32O6cZPv3wlsF+ZBs1ToWfjI08igsctg4Z7fIRSH0VksYS+OHAIPMLiEubamcfQrnAV/bV+16TbXMekzB4U+qarUCgUXYQuugqFQtFF7JBewFpt22bwus3KNEQvuLS+++S9hiNEG4TMXUGnTS6nA9snGsJzyX0lb6wZMoUoLl28FNhnTiMg+8mzZwP78GG4N5ffuRrYr1yFyycisuEi0DtCt28LJW2E7t+10Zz5P89Owv0c7EG/pLK4x8PtocCuNOG6FkqmyxONoi+rJGyTycDNK1PiwjsXEP3Q8uA6i4g8+ijOVS7eDewIRRbkMgjkL7TRlnLbjAxoUVQFixVVKEGhQmM9kDXFaLZCm2iM2df/EscPor8yJFJTqMJFLhXNNsZbaFchhuu3XQTrp5KgHU4fw3mzEdPdTidBVSzmcR0nCff36MOItCmtgdYqVU23doSSDcpE50RtzJXRMURrWA5opVTv9h713//KFwN78gTu689f+nFgP//oY4F9ZBSiNiIi+SrG8d0ZPCduAa7/Y9SWCz+9Htg/vI7ICRGR8QHM1TMHML8mRkF11O4iCeLCRVBvz5x+xDhXla7/k9t4zlMO2vvnX38jsL01jPVwypyDfUOgN15bWJYHhb7pKhQKRRehi65CoVB0ETujF2y8eodC5i59iPR02RabaAB4ZuKTBq7TGQfvwxV1KRrBI1EGlzRsQy7ckcSimcc93QJdUFqCa5nI/GZgZ8n1fvqTTwX2TA074yIi99ZJ0zZOERo26webu/YfhGTapARY07ZWIV3iMvohxK7kOHawVy6amr0hihDJpkBblGoIDPcosaRF+r9Xr5rudjqN8T58CG5eNEG6xpQQYdNOeSJmBryX6NQhD20MhdjmKJDt0Qst0mu9+95bge2PYnf8roP7qEQomqbjXPE4+jU0DK2JoxQlkCDa4MgB6HTEYmiHiEjLwnUSRJUcy6Bd/+oP/01gn3sTOs7nf4CoBhGRs0IJL/2k/dqHyJNcEnPIiyHjJZXr1F74jnwQ9ozjfg9MgDroz+IZWFjBHBrpNx/aeAb3ePsWKL5ffwgRA94CooRiHo6/vGo+D4+M4lwZG/c+tYDnN59HP9SIurp5F1EcIiLlJGiXlTIonPpVUCB79oNOWZgHbbCxSKIbInLqIPr1NVF6QaFQKP5OQxddhUKh6CJ2RC8wo2BQCCIi5DL6tJsfolIpVhg2Bx9Y0skv4I/sVjvkCrPWQ7b8RGA3N812zW9gl/Tjn3w6sHM9nJ8Od4Y1IR55GIHsIiI/+yF2txuGtgAnc9y/a/v7zADuWBxujENJBL7HpXfQdxP70Q/XrkCGT0SkUkO7albrA79nWc0wRaE0OhIt3ruKAPIQUUuZJM4bj8KNTpOOQjRiutuJCK4fcnH9CEUDRKPol1TazO3fCic/95XAXrv808CuNHBf8Rx2vXflkLPfzMPdFRFpE
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "100%|██████████| 313/313 [00:38<00:00,  8.05it/s]\n",
            "100%|██████████| 313/313 [00:38<00:00,  8.10it/s]\n",
            " 49%|████▉     | 154/313 [00:19<00:19,  8.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Buffered data was truncated after reaching the output size limit."
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}