mirror of
https://github.com/ZhangXinNan/DL-with-Python-and-PyTorch2.git
synced 2025-10-20 23:34:18 +08:00
598 lines
343 KiB
Plaintext
598 lines
343 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {
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"image.png": {
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"
|
||
}
|
||
},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 10.4 VAE与GAN的异同\n",
|
||
"\tVAE适合学习具有良好结构的潜在空间,潜在空间有比较好的连续性,其中存在一些有特定意义的方向。VAE能够捕捉图像的结构变化(倾斜角度、圈的位置、形状变化、表情变化等)。这也是VAE的一个好处,它有显式的分布,能够容易地可视化图像的分布,具体如图10-8所示。\n",
|
||
"\t \n",
|
||
"<center>图10-8 VAE得到的数据流形分布图</center>\n",
|
||
"GAN生成的潜在空间可能没有良好结构,但GAN生成的图像一般比VAE生成的图像更清晰。"
|
||
]
|
||
},
|
||
{
|
||
"attachments": {
|
||
"image.png": {
|
||
"image/png": 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"
|
||
}
|
||
},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 10.5 CGAN\n",
|
||
"\t前文提到,VAE和GAN都能基于潜在空间的随机向量z生成新图像,GAN生成的图像比VAE生成的图像更清晰,质量更好些。不过它们生成的图像都是随机的,无法预先控制要生成哪类或哪个数。如果在生成新图像的同时,能加上一个目标控制那就太好了,如我希望生成某个数字,生成某个主题或类别的图像,实现按需生成的目的,这样的应用应该非常广泛。因此,CGAN(Condition GAN,基于条件的GAN)应运而生。\n",
|
||
"### 10.5.1 CGAN的架构\n",
|
||
"\t在GAN这种完全无监督的架构上加上一个标签或一点监督信息,整个网络就可看成半监督模型。CGAN基本架构与GAN类似,只要添加一个条件y即可,y就是加入的监督信息,比如MNIST数据集可以提供某个数字的标签信息,人脸生成可以提供性别、是否微笑、年龄等信息,带某个主题的图像标签信息等。CGAN的架构图如图10-9所示。\n",
|
||
"\n",
|
||
"<center>图10-9 CGAN的架构图</center>\n",
|
||
"\t对生成器输入一个从潜在空间随机采样的向量z及条件y,生成一个符合该条件的图像G(z/y)。对判别器来说,输入一张图像x和条件y,输出该图像在该条件下的概率D(x/y)。这只是CGAN的一个蓝图,如何实现这个蓝图?接下来我们用PyTorch具体实现。"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 10.5.2 CGAN实例"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"import os\n",
|
||
"%matplotlib inline\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"import numpy as np\n",
|
||
"import torch\n",
|
||
"import torchvision\n",
|
||
"import torch.nn as nn\n",
|
||
"from torchvision import transforms\n",
|
||
"from torch import autograd\n",
|
||
"from torchvision.utils import save_image\n",
|
||
"from torchvision.utils import make_grid\n",
|
||
"from torch.utils.tensorboard import SummaryWriter\n",
|
||
"\n",
|
||
"\n",
|
||
"# 设备配置\n",
|
||
"#torch.cuda.set_device(1) # 这句用来设置pytorch在哪块GPU上运行,这里假设使用序号为1的这块GPU.\n",
|
||
"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
|
||
"\n",
|
||
"\n",
|
||
"# 定义一些超参数\n",
|
||
"num_epochs = 50\n",
|
||
"batch_size = 100\n",
|
||
"sample_dir = 'cgan_samples'\n",
|
||
"\n",
|
||
"# 在当前目录,创建不存在的目录gan_samples\n",
|
||
"if not os.path.exists(sample_dir):\n",
|
||
" os.makedirs(sample_dir)\n",
|
||
"\n",
|
||
"# Image processing\n",
|
||
"trans = transforms.Compose([\n",
|
||
" transforms.ToTensor(),\n",
|
||
" transforms.Normalize([0.5], [0.5])]) \n",
|
||
"\n",
|
||
"\n",
|
||
"# MNIST dataset\n",
|
||
"mnist = torchvision.datasets.MNIST(root='../data',\n",
|
||
" train=True,\n",
|
||
" transform=trans,\n",
|
||
" download=False)\n",
|
||
"\n",
|
||
"# Data loader\n",
|
||
"data_loader = torch.utils.data.DataLoader(dataset=mnist,\n",
|
||
" batch_size=batch_size, \n",
|
||
" shuffle=True)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"class Discriminator(nn.Module):\n",
|
||
" def __init__(self):\n",
|
||
" super().__init__()\n",
|
||
" \n",
|
||
" self.label_emb = nn.Embedding(10, 10)\n",
|
||
" \n",
|
||
" self.model = nn.Sequential(\n",
|
||
" nn.Linear(794, 1024),\n",
|
||
" nn.LeakyReLU(0.2, inplace=True),\n",
|
||
" nn.Dropout(0.4),\n",
|
||
" nn.Linear(1024, 512),\n",
|
||
" nn.LeakyReLU(0.2, inplace=True),\n",
|
||
" nn.Dropout(0.4),\n",
|
||
" nn.Linear(512, 256),\n",
|
||
" nn.LeakyReLU(0.2, inplace=True),\n",
|
||
" nn.Dropout(0.4),\n",
|
||
" nn.Linear(256, 1),\n",
|
||
" nn.Sigmoid()\n",
|
||
" )\n",
|
||
" \n",
|
||
" def forward(self, x, labels):\n",
|
||
" x = x.view(x.size(0), 784)\n",
|
||
" c = self.label_emb(labels)\n",
|
||
" x = torch.cat([x, c], 1)\n",
|
||
" out = self.model(x)\n",
|
||
" return out.squeeze()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"class Generator(nn.Module):\n",
|
||
" def __init__(self):\n",
|
||
" super().__init__()\n",
|
||
" \n",
|
||
" self.label_emb = nn.Embedding(10, 10)\n",
|
||
" \n",
|
||
" self.model = nn.Sequential(\n",
|
||
" nn.Linear(110, 256),\n",
|
||
" nn.LeakyReLU(0.2, inplace=True),\n",
|
||
" nn.Linear(256, 512),\n",
|
||
" nn.LeakyReLU(0.2, inplace=True),\n",
|
||
" nn.Linear(512, 1024),\n",
|
||
" nn.LeakyReLU(0.2, inplace=True),\n",
|
||
" nn.Linear(1024, 784),\n",
|
||
" nn.Tanh()\n",
|
||
" )\n",
|
||
" \n",
|
||
" def forward(self, z, labels):\n",
|
||
" z = z.view(z.size(0), 100)\n",
|
||
" c = self.label_emb(labels)\n",
|
||
" x = torch.cat([z, c], 1)\n",
|
||
" out = self.model(x)\n",
|
||
" return out.view(x.size(0), 28, 28)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# 设备配置\n",
|
||
"#torch.cuda.set_device(1) # 这句用来设置pytorch在哪块GPU上运行,这里假设使用序号为1的这块GPU.\n",
|
||
"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
|
||
"\n",
|
||
"G = Generator().to(device)\n",
|
||
"D = Discriminator().to(device)\n",
|
||
"\n",
|
||
"# 定义判别器的损失函数交叉熵及优化器\n",
|
||
"criterion = nn.BCELoss()\n",
|
||
"d_optimizer = torch.optim.Adam(D.parameters(), lr=0.0001)\n",
|
||
"g_optimizer = torch.optim.Adam(G.parameters(), lr=0.0001)\n",
|
||
"\n",
|
||
"#Clamp函数x限制在区间[min, max]内\n",
|
||
"def denorm(x):\n",
|
||
" out = (x + 1) / 2\n",
|
||
" return out.clamp(0, 1)\n",
|
||
"\n",
|
||
"def reset_grad():\n",
|
||
" d_optimizer.zero_grad()\n",
|
||
" g_optimizer.zero_grad()\n",
|
||
"\n",
|
||
"# 开始训练\n",
|
||
"total_step = len(data_loader)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Epoch [0/50], Step [200/600], d_loss: 0.6624, g_loss: 2.2518, D(x): 0.85, D(G(z)): 0.37\n",
|
||
"Epoch [0/50], Step [400/600], d_loss: 0.6763, g_loss: 2.2363, D(x): 0.80, D(G(z)): 0.74\n",
|
||
"Epoch [0/50], Step [600/600], d_loss: 0.4639, g_loss: 2.1297, D(x): 0.81, D(G(z)): 0.61\n",
|
||
"Epoch [1/50], Step [200/600], d_loss: 1.1801, g_loss: 1.2525, D(x): 0.64, D(G(z)): 0.72\n",
|
||
"Epoch [1/50], Step [400/600], d_loss: 0.5848, g_loss: 2.2298, D(x): 0.78, D(G(z)): 0.53\n",
|
||
"Epoch [1/50], Step [600/600], d_loss: 0.6719, g_loss: 2.7498, D(x): 0.80, D(G(z)): 0.67\n",
|
||
"Epoch [2/50], Step [200/600], d_loss: 0.8032, g_loss: 1.9790, D(x): 0.78, D(G(z)): 0.70\n",
|
||
"Epoch [2/50], Step [400/600], d_loss: 0.6904, g_loss: 3.4205, D(x): 0.78, D(G(z)): 0.59\n",
|
||
"Epoch [2/50], Step [600/600], d_loss: 0.1461, g_loss: 3.6047, D(x): 0.97, D(G(z)): 0.54\n",
|
||
"Epoch [3/50], Step [200/600], d_loss: 0.3674, g_loss: 4.1181, D(x): 0.92, D(G(z)): 0.53\n",
|
||
"Epoch [3/50], Step [400/600], d_loss: 0.4411, g_loss: 3.8409, D(x): 0.90, D(G(z)): 0.71\n",
|
||
"Epoch [3/50], Step [600/600], d_loss: 0.1597, g_loss: 5.0754, D(x): 0.93, D(G(z)): 0.67\n",
|
||
"Epoch [4/50], Step [200/600], d_loss: 0.2571, g_loss: 3.2379, D(x): 0.94, D(G(z)): 0.76\n",
|
||
"Epoch [4/50], Step [400/600], d_loss: 0.2751, g_loss: 5.5680, D(x): 0.96, D(G(z)): 0.68\n",
|
||
"Epoch [4/50], Step [600/600], d_loss: 0.3474, g_loss: 3.6910, D(x): 0.91, D(G(z)): 0.76\n",
|
||
"Epoch [5/50], Step [200/600], d_loss: 0.3745, g_loss: 3.7527, D(x): 0.93, D(G(z)): 0.77\n",
|
||
"Epoch [5/50], Step [400/600], d_loss: 0.3544, g_loss: 4.4087, D(x): 0.93, D(G(z)): 0.72\n",
|
||
"Epoch [5/50], Step [600/600], d_loss: 0.2761, g_loss: 4.7725, D(x): 0.96, D(G(z)): 0.75\n",
|
||
"Epoch [6/50], Step [200/600], d_loss: 0.2194, g_loss: 6.1159, D(x): 0.92, D(G(z)): 0.78\n",
|
||
"Epoch [6/50], Step [400/600], d_loss: 0.2667, g_loss: 4.5469, D(x): 0.92, D(G(z)): 0.78\n",
|
||
"Epoch [6/50], Step [600/600], d_loss: 0.2224, g_loss: 4.0002, D(x): 0.93, D(G(z)): 0.75\n",
|
||
"Epoch [7/50], Step [200/600], d_loss: 0.4507, g_loss: 3.7522, D(x): 0.92, D(G(z)): 0.77\n",
|
||
"Epoch [7/50], Step [400/600], d_loss: 0.3874, g_loss: 4.2090, D(x): 0.90, D(G(z)): 0.76\n",
|
||
"Epoch [7/50], Step [600/600], d_loss: 0.1934, g_loss: 2.8309, D(x): 0.95, D(G(z)): 0.74\n",
|
||
"Epoch [8/50], Step [200/600], d_loss: 0.2611, g_loss: 4.9304, D(x): 0.89, D(G(z)): 0.77\n",
|
||
"Epoch [8/50], Step [400/600], d_loss: 0.3118, g_loss: 3.1686, D(x): 0.92, D(G(z)): 0.74\n",
|
||
"Epoch [8/50], Step [600/600], d_loss: 0.2478, g_loss: 3.5699, D(x): 0.90, D(G(z)): 0.74\n",
|
||
"Epoch [9/50], Step [200/600], d_loss: 0.3780, g_loss: 3.3470, D(x): 0.87, D(G(z)): 0.72\n",
|
||
"Epoch [9/50], Step [400/600], d_loss: 0.3529, g_loss: 3.3885, D(x): 0.85, D(G(z)): 0.71\n",
|
||
"Epoch [9/50], Step [600/600], d_loss: 0.3622, g_loss: 3.3377, D(x): 0.86, D(G(z)): 0.76\n",
|
||
"Epoch [10/50], Step [200/600], d_loss: 0.2472, g_loss: 3.2084, D(x): 0.88, D(G(z)): 0.75\n",
|
||
"Epoch [10/50], Step [400/600], d_loss: 0.2349, g_loss: 4.1714, D(x): 0.93, D(G(z)): 0.73\n",
|
||
"Epoch [10/50], Step [600/600], d_loss: 0.3169, g_loss: 3.2430, D(x): 0.89, D(G(z)): 0.78\n",
|
||
"Epoch [11/50], Step [200/600], d_loss: 0.3718, g_loss: 3.8490, D(x): 0.90, D(G(z)): 0.77\n",
|
||
"Epoch [11/50], Step [400/600], d_loss: 0.5893, g_loss: 3.7033, D(x): 0.82, D(G(z)): 0.74\n",
|
||
"Epoch [11/50], Step [600/600], d_loss: 0.6117, g_loss: 3.4955, D(x): 0.78, D(G(z)): 0.73\n",
|
||
"Epoch [12/50], Step [200/600], d_loss: 0.5416, g_loss: 2.7091, D(x): 0.87, D(G(z)): 0.73\n",
|
||
"Epoch [12/50], Step [400/600], d_loss: 0.5259, g_loss: 3.5237, D(x): 0.84, D(G(z)): 0.74\n",
|
||
"Epoch [12/50], Step [600/600], d_loss: 0.4705, g_loss: 3.0667, D(x): 0.89, D(G(z)): 0.73\n",
|
||
"Epoch [13/50], Step [200/600], d_loss: 0.4417, g_loss: 2.6737, D(x): 0.89, D(G(z)): 0.75\n",
|
||
"Epoch [13/50], Step [400/600], d_loss: 0.5363, g_loss: 2.8090, D(x): 0.86, D(G(z)): 0.74\n",
|
||
"Epoch [13/50], Step [600/600], d_loss: 0.6760, g_loss: 2.7209, D(x): 0.84, D(G(z)): 0.75\n",
|
||
"Epoch [14/50], Step [200/600], d_loss: 0.5170, g_loss: 2.9901, D(x): 0.80, D(G(z)): 0.74\n",
|
||
"Epoch [14/50], Step [400/600], d_loss: 0.4838, g_loss: 2.4346, D(x): 0.86, D(G(z)): 0.74\n",
|
||
"Epoch [14/50], Step [600/600], d_loss: 0.3410, g_loss: 2.9706, D(x): 0.94, D(G(z)): 0.79\n",
|
||
"Epoch [15/50], Step [200/600], d_loss: 0.5501, g_loss: 2.9563, D(x): 0.80, D(G(z)): 0.77\n",
|
||
"Epoch [15/50], Step [400/600], d_loss: 0.6177, g_loss: 2.1933, D(x): 0.75, D(G(z)): 0.74\n",
|
||
"Epoch [15/50], Step [600/600], d_loss: 0.6135, g_loss: 2.9026, D(x): 0.80, D(G(z)): 0.73\n",
|
||
"Epoch [16/50], Step [200/600], d_loss: 0.5536, g_loss: 2.1921, D(x): 0.83, D(G(z)): 0.74\n",
|
||
"Epoch [16/50], Step [400/600], d_loss: 0.4974, g_loss: 3.1434, D(x): 0.81, D(G(z)): 0.75\n",
|
||
"Epoch [16/50], Step [600/600], d_loss: 0.6140, g_loss: 2.8544, D(x): 0.77, D(G(z)): 0.74\n",
|
||
"Epoch [17/50], Step [200/600], d_loss: 0.5970, g_loss: 2.4158, D(x): 0.81, D(G(z)): 0.77\n",
|
||
"Epoch [17/50], Step [400/600], d_loss: 0.6816, g_loss: 2.3041, D(x): 0.76, D(G(z)): 0.77\n",
|
||
"Epoch [17/50], Step [600/600], d_loss: 0.5863, g_loss: 2.2702, D(x): 0.80, D(G(z)): 0.75\n",
|
||
"Epoch [18/50], Step [200/600], d_loss: 0.6055, g_loss: 2.2671, D(x): 0.84, D(G(z)): 0.75\n",
|
||
"Epoch [18/50], Step [400/600], d_loss: 0.4301, g_loss: 2.7832, D(x): 0.83, D(G(z)): 0.72\n",
|
||
"Epoch [18/50], Step [600/600], d_loss: 0.6436, g_loss: 2.6458, D(x): 0.85, D(G(z)): 0.74\n",
|
||
"Epoch [19/50], Step [200/600], d_loss: 0.6431, g_loss: 2.8563, D(x): 0.78, D(G(z)): 0.77\n",
|
||
"Epoch [19/50], Step [400/600], d_loss: 0.7026, g_loss: 2.9826, D(x): 0.73, D(G(z)): 0.74\n",
|
||
"Epoch [19/50], Step [600/600], d_loss: 0.7494, g_loss: 2.9565, D(x): 0.71, D(G(z)): 0.74\n",
|
||
"Epoch [20/50], Step [200/600], d_loss: 0.6900, g_loss: 2.5913, D(x): 0.72, D(G(z)): 0.74\n",
|
||
"Epoch [20/50], Step [400/600], d_loss: 0.5970, g_loss: 2.4327, D(x): 0.80, D(G(z)): 0.73\n",
|
||
"Epoch [20/50], Step [600/600], d_loss: 0.8531, g_loss: 1.8576, D(x): 0.73, D(G(z)): 0.73\n",
|
||
"Epoch [21/50], Step [200/600], d_loss: 0.4745, g_loss: 2.4963, D(x): 0.82, D(G(z)): 0.73\n",
|
||
"Epoch [21/50], Step [400/600], d_loss: 0.6889, g_loss: 2.3415, D(x): 0.76, D(G(z)): 0.73\n",
|
||
"Epoch [21/50], Step [600/600], d_loss: 0.7003, g_loss: 1.9396, D(x): 0.76, D(G(z)): 0.73\n",
|
||
"Epoch [22/50], Step [200/600], d_loss: 0.7874, g_loss: 2.4537, D(x): 0.78, D(G(z)): 0.73\n",
|
||
"Epoch [22/50], Step [400/600], d_loss: 0.8057, g_loss: 2.1923, D(x): 0.70, D(G(z)): 0.72\n",
|
||
"Epoch [22/50], Step [600/600], d_loss: 0.8187, g_loss: 2.4669, D(x): 0.74, D(G(z)): 0.74\n",
|
||
"Epoch [23/50], Step [200/600], d_loss: 0.6190, g_loss: 1.9975, D(x): 0.84, D(G(z)): 0.75\n",
|
||
"Epoch [23/50], Step [400/600], d_loss: 0.8544, g_loss: 2.4327, D(x): 0.68, D(G(z)): 0.75\n",
|
||
"Epoch [23/50], Step [600/600], d_loss: 0.7000, g_loss: 1.9539, D(x): 0.79, D(G(z)): 0.74\n",
|
||
"Epoch [24/50], Step [200/600], d_loss: 0.5836, g_loss: 2.3119, D(x): 0.80, D(G(z)): 0.75\n",
|
||
"Epoch [24/50], Step [400/600], d_loss: 0.5687, g_loss: 1.8380, D(x): 0.78, D(G(z)): 0.73\n",
|
||
"Epoch [24/50], Step [600/600], d_loss: 0.8269, g_loss: 1.9155, D(x): 0.80, D(G(z)): 0.73\n",
|
||
"Epoch [25/50], Step [200/600], d_loss: 0.7461, g_loss: 2.0111, D(x): 0.76, D(G(z)): 0.73\n",
|
||
"Epoch [25/50], Step [400/600], d_loss: 0.6937, g_loss: 1.9461, D(x): 0.75, D(G(z)): 0.72\n",
|
||
"Epoch [25/50], Step [600/600], d_loss: 0.8960, g_loss: 1.9967, D(x): 0.71, D(G(z)): 0.74\n",
|
||
"Epoch [26/50], Step [200/600], d_loss: 0.7487, g_loss: 2.0032, D(x): 0.76, D(G(z)): 0.75\n",
|
||
"Epoch [26/50], Step [400/600], d_loss: 0.7623, g_loss: 1.6300, D(x): 0.82, D(G(z)): 0.71\n",
|
||
"Epoch [26/50], Step [600/600], d_loss: 0.8133, g_loss: 1.7384, D(x): 0.67, D(G(z)): 0.75\n",
|
||
"Epoch [27/50], Step [200/600], d_loss: 0.8315, g_loss: 1.8102, D(x): 0.72, D(G(z)): 0.73\n",
|
||
"Epoch [27/50], Step [400/600], d_loss: 0.8039, g_loss: 1.7728, D(x): 0.77, D(G(z)): 0.73\n",
|
||
"Epoch [27/50], Step [600/600], d_loss: 0.8457, g_loss: 1.8289, D(x): 0.75, D(G(z)): 0.73\n",
|
||
"Epoch [28/50], Step [200/600], d_loss: 1.0419, g_loss: 1.7170, D(x): 0.67, D(G(z)): 0.75\n",
|
||
"Epoch [28/50], Step [400/600], d_loss: 1.0226, g_loss: 1.2605, D(x): 0.77, D(G(z)): 0.74\n",
|
||
"Epoch [28/50], Step [600/600], d_loss: 0.9024, g_loss: 1.4336, D(x): 0.74, D(G(z)): 0.71\n",
|
||
"Epoch [29/50], Step [200/600], d_loss: 0.8424, g_loss: 2.0946, D(x): 0.64, D(G(z)): 0.74\n",
|
||
"Epoch [29/50], Step [400/600], d_loss: 0.7244, g_loss: 1.9806, D(x): 0.77, D(G(z)): 0.72\n",
|
||
"Epoch [29/50], Step [600/600], d_loss: 0.8957, g_loss: 1.7826, D(x): 0.70, D(G(z)): 0.74\n",
|
||
"Epoch [30/50], Step [200/600], d_loss: 0.8570, g_loss: 1.5331, D(x): 0.74, D(G(z)): 0.75\n",
|
||
"Epoch [30/50], Step [400/600], d_loss: 0.8604, g_loss: 1.5443, D(x): 0.77, D(G(z)): 0.71\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Epoch [30/50], Step [600/600], d_loss: 1.0231, g_loss: 1.8057, D(x): 0.57, D(G(z)): 0.75\n",
|
||
"Epoch [31/50], Step [200/600], d_loss: 0.9165, g_loss: 1.4377, D(x): 0.69, D(G(z)): 0.73\n",
|
||
"Epoch [31/50], Step [400/600], d_loss: 0.9746, g_loss: 1.7208, D(x): 0.68, D(G(z)): 0.72\n",
|
||
"Epoch [31/50], Step [600/600], d_loss: 0.6985, g_loss: 1.8499, D(x): 0.78, D(G(z)): 0.72\n",
|
||
"Epoch [32/50], Step [200/600], d_loss: 0.7825, g_loss: 1.7373, D(x): 0.77, D(G(z)): 0.73\n",
|
||
"Epoch [32/50], Step [400/600], d_loss: 0.8862, g_loss: 1.8477, D(x): 0.71, D(G(z)): 0.73\n",
|
||
"Epoch [32/50], Step [600/600], d_loss: 0.7683, g_loss: 1.9329, D(x): 0.77, D(G(z)): 0.74\n",
|
||
"Epoch [33/50], Step [200/600], d_loss: 1.0261, g_loss: 1.3753, D(x): 0.67, D(G(z)): 0.75\n",
|
||
"Epoch [33/50], Step [400/600], d_loss: 1.0744, g_loss: 1.2554, D(x): 0.65, D(G(z)): 0.74\n",
|
||
"Epoch [33/50], Step [600/600], d_loss: 1.0093, g_loss: 1.6478, D(x): 0.63, D(G(z)): 0.72\n",
|
||
"Epoch [34/50], Step [200/600], d_loss: 1.0954, g_loss: 1.4199, D(x): 0.66, D(G(z)): 0.72\n",
|
||
"Epoch [34/50], Step [400/600], d_loss: 1.0316, g_loss: 1.7213, D(x): 0.71, D(G(z)): 0.73\n",
|
||
"Epoch [34/50], Step [600/600], d_loss: 1.1154, g_loss: 1.3576, D(x): 0.62, D(G(z)): 0.74\n",
|
||
"Epoch [35/50], Step [200/600], d_loss: 0.9952, g_loss: 1.7536, D(x): 0.71, D(G(z)): 0.72\n",
|
||
"Epoch [35/50], Step [400/600], d_loss: 1.0112, g_loss: 0.9391, D(x): 0.70, D(G(z)): 0.72\n",
|
||
"Epoch [35/50], Step [600/600], d_loss: 0.9858, g_loss: 1.5204, D(x): 0.70, D(G(z)): 0.74\n",
|
||
"Epoch [36/50], Step [200/600], d_loss: 1.0043, g_loss: 1.1026, D(x): 0.72, D(G(z)): 0.74\n",
|
||
"Epoch [36/50], Step [400/600], d_loss: 1.0333, g_loss: 1.2593, D(x): 0.62, D(G(z)): 0.75\n",
|
||
"Epoch [36/50], Step [600/600], d_loss: 1.1125, g_loss: 1.3187, D(x): 0.63, D(G(z)): 0.73\n",
|
||
"Epoch [37/50], Step [200/600], d_loss: 0.9590, g_loss: 1.3552, D(x): 0.65, D(G(z)): 0.73\n",
|
||
"Epoch [37/50], Step [400/600], d_loss: 1.0179, g_loss: 1.3206, D(x): 0.61, D(G(z)): 0.75\n",
|
||
"Epoch [37/50], Step [600/600], d_loss: 0.8858, g_loss: 1.5117, D(x): 0.69, D(G(z)): 0.74\n",
|
||
"Epoch [38/50], Step [200/600], d_loss: 1.0689, g_loss: 1.2586, D(x): 0.61, D(G(z)): 0.73\n",
|
||
"Epoch [38/50], Step [400/600], d_loss: 1.1112, g_loss: 1.1801, D(x): 0.70, D(G(z)): 0.74\n",
|
||
"Epoch [38/50], Step [600/600], d_loss: 1.0140, g_loss: 1.5380, D(x): 0.60, D(G(z)): 0.73\n",
|
||
"Epoch [39/50], Step [200/600], d_loss: 0.9966, g_loss: 1.5326, D(x): 0.60, D(G(z)): 0.74\n",
|
||
"Epoch [39/50], Step [400/600], d_loss: 0.9275, g_loss: 1.5215, D(x): 0.73, D(G(z)): 0.75\n",
|
||
"Epoch [39/50], Step [600/600], d_loss: 0.8406, g_loss: 1.4837, D(x): 0.70, D(G(z)): 0.71\n",
|
||
"Epoch [40/50], Step [200/600], d_loss: 0.9907, g_loss: 1.2296, D(x): 0.70, D(G(z)): 0.72\n",
|
||
"Epoch [40/50], Step [400/600], d_loss: 0.8890, g_loss: 1.5952, D(x): 0.68, D(G(z)): 0.75\n",
|
||
"Epoch [40/50], Step [600/600], d_loss: 1.0863, g_loss: 1.2251, D(x): 0.69, D(G(z)): 0.75\n",
|
||
"Epoch [41/50], Step [200/600], d_loss: 1.1580, g_loss: 1.1549, D(x): 0.61, D(G(z)): 0.74\n",
|
||
"Epoch [41/50], Step [400/600], d_loss: 1.2746, g_loss: 0.9859, D(x): 0.59, D(G(z)): 0.75\n",
|
||
"Epoch [41/50], Step [600/600], d_loss: 1.1358, g_loss: 1.1744, D(x): 0.62, D(G(z)): 0.72\n",
|
||
"Epoch [42/50], Step [200/600], d_loss: 1.2423, g_loss: 1.2883, D(x): 0.65, D(G(z)): 0.74\n",
|
||
"Epoch [42/50], Step [400/600], d_loss: 1.0574, g_loss: 1.3093, D(x): 0.66, D(G(z)): 0.74\n",
|
||
"Epoch [42/50], Step [600/600], d_loss: 0.9545, g_loss: 1.3864, D(x): 0.65, D(G(z)): 0.75\n",
|
||
"Epoch [43/50], Step [200/600], d_loss: 1.0647, g_loss: 1.2900, D(x): 0.66, D(G(z)): 0.73\n",
|
||
"Epoch [43/50], Step [400/600], d_loss: 0.9528, g_loss: 1.3481, D(x): 0.68, D(G(z)): 0.72\n",
|
||
"Epoch [43/50], Step [600/600], d_loss: 0.9970, g_loss: 1.3309, D(x): 0.69, D(G(z)): 0.72\n",
|
||
"Epoch [44/50], Step [200/600], d_loss: 1.0597, g_loss: 1.1885, D(x): 0.65, D(G(z)): 0.73\n",
|
||
"Epoch [44/50], Step [400/600], d_loss: 0.9812, g_loss: 1.3169, D(x): 0.66, D(G(z)): 0.73\n",
|
||
"Epoch [44/50], Step [600/600], d_loss: 1.1606, g_loss: 1.2530, D(x): 0.60, D(G(z)): 0.74\n",
|
||
"Epoch [45/50], Step [200/600], d_loss: 1.1783, g_loss: 1.1202, D(x): 0.63, D(G(z)): 0.73\n",
|
||
"Epoch [45/50], Step [400/600], d_loss: 1.1377, g_loss: 1.1363, D(x): 0.64, D(G(z)): 0.70\n",
|
||
"Epoch [45/50], Step [600/600], d_loss: 1.0671, g_loss: 1.2129, D(x): 0.63, D(G(z)): 0.75\n",
|
||
"Epoch [46/50], Step [200/600], d_loss: 1.0517, g_loss: 1.1329, D(x): 0.69, D(G(z)): 0.72\n",
|
||
"Epoch [46/50], Step [400/600], d_loss: 1.1302, g_loss: 1.2493, D(x): 0.59, D(G(z)): 0.73\n",
|
||
"Epoch [46/50], Step [600/600], d_loss: 1.0212, g_loss: 1.3059, D(x): 0.65, D(G(z)): 0.74\n",
|
||
"Epoch [47/50], Step [200/600], d_loss: 1.0649, g_loss: 1.2975, D(x): 0.61, D(G(z)): 0.73\n",
|
||
"Epoch [47/50], Step [400/600], d_loss: 1.0200, g_loss: 1.0556, D(x): 0.68, D(G(z)): 0.73\n",
|
||
"Epoch [47/50], Step [600/600], d_loss: 1.1234, g_loss: 0.9921, D(x): 0.67, D(G(z)): 0.72\n",
|
||
"Epoch [48/50], Step [200/600], d_loss: 1.1649, g_loss: 1.0143, D(x): 0.61, D(G(z)): 0.74\n",
|
||
"Epoch [48/50], Step [400/600], d_loss: 1.1543, g_loss: 1.0658, D(x): 0.58, D(G(z)): 0.74\n",
|
||
"Epoch [48/50], Step [600/600], d_loss: 1.0286, g_loss: 1.2168, D(x): 0.61, D(G(z)): 0.72\n",
|
||
"Epoch [49/50], Step [200/600], d_loss: 1.1670, g_loss: 1.2463, D(x): 0.53, D(G(z)): 0.71\n",
|
||
"Epoch [49/50], Step [400/600], d_loss: 1.0633, g_loss: 1.0890, D(x): 0.59, D(G(z)): 0.74\n",
|
||
"Epoch [49/50], Step [600/600], d_loss: 1.0445, g_loss: 1.2416, D(x): 0.66, D(G(z)): 0.75\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"writer = SummaryWriter(log_dir='logs')\n",
|
||
"\n",
|
||
"for epoch in range(num_epochs):\n",
|
||
" for i, (images,labels) in enumerate(data_loader):\n",
|
||
" step = epoch * len(data_loader) + i + 1\n",
|
||
" images = images.to(device)\n",
|
||
" labels = labels.to(device)\n",
|
||
" # 定义图像是真或假的标签\n",
|
||
" real_labels = torch.ones(batch_size).to(device)\n",
|
||
" fake_labels =torch.randint(0,10,(batch_size,)).to(device)\n",
|
||
"\n",
|
||
" # ================================================================== #\n",
|
||
" # 训练判别器 #\n",
|
||
" # ================================================================== #\n",
|
||
"\n",
|
||
" # 定义判断器对真图片的损失函数\n",
|
||
" real_validity = D(images, labels)\n",
|
||
" d_loss_real = criterion(real_validity, real_labels)\n",
|
||
" real_score = real_validity\n",
|
||
" # 定义判别器对假图片(即由潜在空间点生成的图片)的损失函数\n",
|
||
" z = torch.randn(batch_size, 100).to(device)\n",
|
||
" fake_labels = torch.randint(0,10,(batch_size,)).to(device)\n",
|
||
" fake_images = G(z, fake_labels)\n",
|
||
" fake_validity = D(fake_images, fake_labels)\n",
|
||
" d_loss_fake = criterion(fake_validity, torch.zeros(batch_size).to(device))\n",
|
||
" fake_score =fake_images\n",
|
||
" d_loss = d_loss_real + d_loss_fake\n",
|
||
" \n",
|
||
" # 对生成器、判别器的梯度清零 \n",
|
||
" reset_grad()\n",
|
||
" d_loss.backward()\n",
|
||
" d_optimizer.step()\n",
|
||
" \n",
|
||
" # ================================================================== #\n",
|
||
" # 训练生成器 #\n",
|
||
" # ================================================================== #\n",
|
||
"\n",
|
||
" # 定义生成器对假图片的损失函数,这里我们要求\n",
|
||
" #判别器生成的图片越来越像真图片,故损失函数中\n",
|
||
" #的标签改为真图片的标签,即希望生成的假图片,\n",
|
||
" #越来越靠近真图片\n",
|
||
" \n",
|
||
" z = torch.randn(batch_size, 100).to(device)\n",
|
||
" fake_images = G(z, fake_labels)\n",
|
||
" validity = D(fake_images, fake_labels)\n",
|
||
" g_loss = criterion(validity, torch.ones(batch_size).to(device))\n",
|
||
" \n",
|
||
" # 对生成器、判别器的梯度清零\n",
|
||
" #进行反向传播及运行生成器的优化器\n",
|
||
" reset_grad()\n",
|
||
" g_loss.backward()\n",
|
||
" g_optimizer.step()\n",
|
||
" \n",
|
||
" writer.add_scalars('scalars', {'g_loss': g_loss, 'd_loss': d_loss}, step) \n",
|
||
" \n",
|
||
" if (i+1) % 200 == 0:\n",
|
||
" print('Epoch [{}/{}], Step [{}/{}], d_loss: {:.4f}, g_loss: {:.4f}, D(x): {:.2f}, D(G(z)): {:.2f}' \n",
|
||
" .format(epoch, num_epochs, i+1, total_step, d_loss.item(), g_loss.item(), \n",
|
||
" real_score.mean().item(), fake_score.mean().item()*(-1)))\n",
|
||
" \n",
|
||
" # 保存真图片\n",
|
||
" if (epoch+1) == 1:\n",
|
||
" images = images.reshape(images.size(0), 1, 28, 28)\n",
|
||
" save_image(denorm(images), os.path.join(sample_dir, 'real_images.png'))\n",
|
||
" \n",
|
||
" # 保存假图片\n",
|
||
" fake_images = fake_images.reshape(fake_images.size(0), 1, 28, 28)\n",
|
||
" save_image(denorm(fake_images), os.path.join(sample_dir, 'fake_images-{}.png'.format(epoch+1)))\n",
|
||
"\n",
|
||
"# 保存模型\n",
|
||
"torch.save(G.state_dict(), 'G.ckpt')\n",
|
||
"torch.save(D.state_dict(), 'D.ckpt')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt # plt 用于显示图片\n",
|
||
"import matplotlib.image as mpimg # mpimg 用于读取图片\n",
|
||
"\n",
|
||
"reconsPath = './cgan_samples/real_images.png'\n",
|
||
"Image = mpimg.imread(reconsPath)\n",
|
||
"plt.imshow(Image) # 显示图片\n",
|
||
"plt.axis('off') # 不显示坐标轴\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"reconsPath = './cgan_samples/fake_images-50.png'\n",
|
||
"Image = mpimg.imread(reconsPath)\n",
|
||
"plt.imshow(Image) # 显示图片\n",
|
||
"plt.axis('off') # 不显示坐标轴\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"(-0.5, 301.5, 301.5, -0.5)"
|
||
]
|
||
},
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 720x720 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from torchvision.utils import make_grid\n",
|
||
"z = torch.randn(100, 100).to(device)\n",
|
||
"labels = torch.LongTensor([i for i in range(10) for _ in range(10)]).to(device)\n",
|
||
"\n",
|
||
"images = G(z, labels).unsqueeze(1)\n",
|
||
"grid = make_grid(images, nrow=10, normalize=True)\n",
|
||
"fig, ax = plt.subplots(figsize=(10,10))\n",
|
||
"ax.imshow(grid.permute(1, 2, 0).detach().cpu().numpy(), cmap='binary')\n",
|
||
"ax.axis('off')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"def generate_digit(generator, digit):\n",
|
||
" z = torch.randn(1, 100).to(device)\n",
|
||
" label = torch.LongTensor([digit]).to(device)\n",
|
||
" img = generator(z, label).detach().cpu()\n",
|
||
" img = 0.5 * img + 0.5\n",
|
||
" return transforms.ToPILImage()(img)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "iVBORw0KGgoAAAANSUhEUgAAABwAAAAcCAAAAABXZoBIAAABLElEQVR4nMWRvy4EURSHf3P334QNs5EoqCj86QhvQKGS2GILjY5XUCmpKCQ04glIPAAKEY1EslHQbSGRiB0bibC7dnyjmN0ds7OJRONUJ+e795zz3Sv9e1iZ8adBWd2QvVQG8Fa6UAfAB45NUDCjbTZXkbbeX0q3pRM72XGvCAzLSpjcJ5cpE2HrHmxLkrJQ6Ykwc+XhJYK1YCba9MY9esgE6QYcRP32Fp3c2tSQJN1TjYmMXENj9251n0bYtSW8CQAf4GZai8hvZpO+JJ+0tFxvlkLb/sLEef5tLFU4PI2NdC76jGR2eHQk0wFrr/msJdV5/vnqgbmgdiYJvFhTLQBpaZ4ukkq6VCUbcONQs1CuAYQl01ZJ+9aAJPWGMDxnJRveV7XjO/4W07/wbwsVfeN9mvVZAAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<PIL.Image.Image image mode=L size=28x28 at 0x1AEB6211C08>"
|
||
]
|
||
},
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"generate_digit(G, 8)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.7.4"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|