DeepQuantom-CNN/Origin.ipynb

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{
"cells": [
{
"cell_type": "code",
"id": "initial_id",
"metadata": {
"collapsed": true,
"ExecuteTime": {
"end_time": "2025-06-24T16:07:02.423934Z",
"start_time": "2025-06-24T16:07:02.418513Z"
}
},
"source": [
"# 首先我们导入所有需要的包:\n",
"import os\n",
"import random\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"import deepquantum as dq\n",
"import matplotlib.pyplot as plt\n",
"import torch\n",
"import torch.nn as nn\n",
"import torch.optim as optim\n",
"import torchvision.transforms as transforms\n",
"from tqdm import tqdm\n",
"from sklearn.metrics import roc_auc_score\n",
"from torch.utils.data import DataLoader\n",
"# from torchvision.datasets import MNIST, FashionMNIST\n",
"\n",
"def seed_torch(seed=1024):\n",
" \"\"\"\n",
" Set random seeds for reproducibility.\n",
"\n",
" Args:\n",
" seed (int): Random seed number to use. Default is 1024.\n",
" \"\"\"\n",
"\n",
" random.seed(seed)\n",
" os.environ['PYTHONHASHSEED'] = str(seed)\n",
" np.random.seed(seed)\n",
" torch.manual_seed(seed)\n",
" torch.cuda.manual_seed(seed)\n",
"\n",
" # Seed all GPUs with the same seed if using multi-GPU\n",
" torch.cuda.manual_seed_all(seed)\n",
" torch.backends.cudnn.benchmark = False\n",
" torch.backends.cudnn.deterministic = True\n",
"\n",
"seed_torch(1024)"
],
"outputs": [],
"execution_count": 23
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:07:02.531770Z",
"start_time": "2025-06-24T16:07:02.525115Z"
}
},
"cell_type": "code",
"source": [
"def calculate_score(y_true, y_preds):\n",
" # 将模型预测结果转为概率分布\n",
" preds_prob = torch.softmax(y_preds, dim=1)\n",
" # 获得预测的类别(概率最高的一类)\n",
" preds_class = torch.argmax(preds_prob, dim=1)\n",
" # 计算准确率\n",
" correct = (preds_class == y_true).float()\n",
" accuracy = correct.sum() / len(correct)\n",
" return accuracy.cpu().numpy()\n",
"\n",
"\n",
"def train_model(model, criterion, optimizer, train_loader, valid_loader, num_epochs, device):\n",
" \"\"\"\n",
" 训练和验证模型。\n",
"\n",
" Args:\n",
" model (torch.nn.Module): 要训练的模型。\n",
" criterion (torch.nn.Module): 损失函数。\n",
" optimizer (torch.optim.Optimizer): 优化器。\n",
" train_loader (torch.utils.data.DataLoader): 训练数据加载器。\n",
" valid_loader (torch.utils.data.DataLoader): 验证数据加载器。\n",
" num_epochs (int): 训练的epoch数。\n",
"\n",
" Returns:\n",
" model (torch.nn.Module): 训练后的模型。\n",
" \"\"\"\n",
"\n",
" model.train()\n",
" train_loss_list = []\n",
" valid_loss_list = []\n",
" train_acc_list = []\n",
" valid_acc_list = []\n",
"\n",
" with tqdm(total=num_epochs) as pbar:\n",
" for epoch in range(num_epochs):\n",
" # 训练阶段\n",
" train_loss = 0.0\n",
" train_acc = 0.0\n",
" for images, labels in train_loader:\n",
" images = images.to(device)\n",
" labels = labels.to(device)\n",
" optimizer.zero_grad()\n",
" outputs = model(images)\n",
" loss = criterion(outputs, labels)\n",
" loss.backward()\n",
" optimizer.step()\n",
" train_loss += loss.item()\n",
" train_acc += calculate_score(labels, outputs)\n",
"\n",
" train_loss /= len(train_loader)\n",
" train_acc /= len(train_loader)\n",
"\n",
" # 验证阶段\n",
" model.eval()\n",
" valid_loss = 0.0\n",
" valid_acc = 0.0\n",
" with torch.no_grad():\n",
" for images, labels in valid_loader:\n",
" images = images.to(device)\n",
" labels = labels.to(device)\n",
" outputs = model(images)\n",
" loss = criterion(outputs, labels)\n",
" valid_loss += loss.item()\n",
" valid_acc += calculate_score(labels, outputs)\n",
"\n",
" valid_loss /= len(valid_loader)\n",
" valid_acc /= len(valid_loader)\n",
"\n",
" pbar.set_description(f\"Train loss: {train_loss:.3f} Valid Acc: {valid_acc:.3f}\")\n",
" pbar.update()\n",
"\n",
"\n",
" train_loss_list.append(train_loss)\n",
" valid_loss_list.append(valid_loss)\n",
" train_acc_list.append(train_acc)\n",
" valid_acc_list.append(valid_acc)\n",
"\n",
" metrics = {'epoch': list(range(1, num_epochs + 1)),\n",
" 'train_acc': train_acc_list,\n",
" 'valid_acc': valid_acc_list,\n",
" 'train_loss': train_loss_list,\n",
" 'valid_loss': valid_loss_list}\n",
"\n",
"\n",
"\n",
" return model, metrics\n",
"\n",
"def test_model(model, test_loader, device):\n",
" model.eval()\n",
" test_acc = 0.0\n",
" with torch.no_grad():\n",
" for images, labels in test_loader:\n",
" images = images.to(device)\n",
" labels = labels.to(device)\n",
" outputs = model(images)\n",
" test_acc += calculate_score(labels, outputs)\n",
"\n",
" test_acc /= len(test_loader)\n",
" print(f'Test Acc: {test_acc:.3f}')\n",
" return test_acc"
],
"id": "cc4c2323375a0d64",
"outputs": [],
"execution_count": 24
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:07:02.643737Z",
"start_time": "2025-06-24T16:07:02.631472Z"
}
},
"cell_type": "code",
"source": [
"# 定义图像变换\n",
"trans1 = transforms.Compose([\n",
" transforms.Resize((18, 18)), # 调整大小为18x18\n",
" transforms.ToTensor() # 转换为张量\n",
"])\n",
"\n",
"trans2 = transforms.Compose([\n",
" transforms.Resize((16, 16)), # 调整大小为16x16\n",
" transforms.ToTensor() # 转换为张量\n",
"])\n",
"train_dataset = FashionMNIST(root='./data/notebook1', train=False, transform=trans1,download=True)\n",
"test_dataset = FashionMNIST(root='./data/notebook1', train=False, transform=trans1,download=True)\n",
"\n",
"# 定义训练集和测试集的比例\n",
"train_ratio = 0.8 # 训练集比例为80%验证集比例为20%\n",
"valid_ratio = 0.2\n",
"total_samples = len(train_dataset)\n",
"train_size = int(train_ratio * total_samples)\n",
"valid_size = int(valid_ratio * total_samples)\n",
"\n",
"# 分割训练集和测试集\n",
"train_dataset, valid_dataset = torch.utils.data.random_split(train_dataset, [train_size, valid_size])\n",
"\n",
"# 加载随机抽取的训练数据集\n",
"train_loader = DataLoader(train_dataset, batch_size=64, shuffle=True, drop_last=True)\n",
"valid_loader = DataLoader(valid_dataset, batch_size=64, shuffle=False, drop_last=True)\n",
"test_loader = DataLoader(test_dataset, batch_size=64, shuffle=False, drop_last=True)"
],
"id": "4b641527c641afc1",
"outputs": [],
"execution_count": 25
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:07:02.734411Z",
"start_time": "2025-06-24T16:07:02.731493Z"
}
},
"cell_type": "code",
"source": [
"singlegate_list = ['rx', 'ry', 'rz', 's', 't', 'p', 'u3']\n",
"doublegate_list = ['rxx', 'ryy', 'rzz', 'swap', 'cnot', 'cp', 'ch', 'cu', 'ct', 'cz']"
],
"id": "1c3e55f43e47a4f1",
"outputs": [],
"execution_count": 26
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:07:02.827116Z",
"start_time": "2025-06-24T16:07:02.822105Z"
}
},
"cell_type": "code",
"source": [
"# 随机量子卷积层\n",
"class RandomQuantumConvolutionalLayer(nn.Module):\n",
" def __init__(self, nqubit, num_circuits, seed:int=1024):\n",
" super(RandomQuantumConvolutionalLayer, self).__init__()\n",
" random.seed(seed)\n",
" self.nqubit = nqubit\n",
" self.cirs = nn.ModuleList([self.circuit(nqubit) for _ in range(num_circuits)])\n",
"\n",
" def circuit(self, nqubit):\n",
" cir = dq.QubitCircuit(nqubit)\n",
" cir.rxlayer(encode=True) # 对原论文的量子线路结构并无影响,只是做了一个数据编码的操作\n",
" cir.barrier()\n",
" for iter in range(3):\n",
" for i in range(nqubit):\n",
" singlegate = random.choice(singlegate_list)\n",
" getattr(cir, singlegate)(i)\n",
" control_bit, target_bit = random.sample(range(0, nqubit - 1), 2)\n",
" doublegate = random.choice(doublegate_list)\n",
" if doublegate[0] in ['r', 's']:\n",
" getattr(cir, doublegate)([control_bit, target_bit])\n",
" else:\n",
" getattr(cir, doublegate)(control_bit, target_bit)\n",
" cir.barrier()\n",
"\n",
" cir.observable(0)\n",
" return cir\n",
"\n",
" def forward(self, x):\n",
" kernel_size, stride = 2, 2\n",
" # [64, 1, 18, 18] -> [64, 1, 9, 18, 2] -> [64, 1, 9, 9, 2, 2]\n",
" x_unflod = x.unfold(2, kernel_size, stride).unfold(3, kernel_size, stride)\n",
" w = int((x.shape[-1] - kernel_size) / stride + 1)\n",
" x_reshape = x_unflod.reshape(-1, self.nqubit)\n",
"\n",
" exps = []\n",
" for cir in self.cirs: # out_channels\n",
" cir(x_reshape)\n",
" exp = cir.expectation()\n",
" exps.append(exp)\n",
"\n",
" exps = torch.stack(exps, dim=1)\n",
" exps = exps.reshape(x.shape[0], 3, w, w)\n",
" return exps"
],
"id": "f03fcd820876a62",
"outputs": [],
"execution_count": 27
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:07:03.018614Z",
"start_time": "2025-06-24T16:07:02.915469Z"
}
},
"cell_type": "code",
"source": [
"net = RandomQuantumConvolutionalLayer(nqubit=4, num_circuits=3, seed=1024)\n",
"net.cirs[0].draw()"
],
"id": "fcea5aa513a0bd68",
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 1207.22x367.889 with 1 Axes>"
],
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"
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 28
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:07:03.130980Z",
"start_time": "2025-06-24T16:07:03.126867Z"
}
},
"cell_type": "code",
"source": [
"# 基于随机量子卷积层的混合模型\n",
"class RandomQCCNN(nn.Module):\n",
" def __init__(self):\n",
" super(RandomQCCNN, self).__init__()\n",
" self.conv = nn.Sequential(\n",
" RandomQuantumConvolutionalLayer(nqubit=4, num_circuits=3, seed=1024), # num_circuits=3代表我们在quanv1层只用了3个量子卷积核\n",
" nn.ReLU(),\n",
" nn.MaxPool2d(kernel_size=2, stride=1),\n",
" nn.Conv2d(3, 6, kernel_size=2, stride=1),\n",
" nn.ReLU(),\n",
" nn.MaxPool2d(kernel_size=2, stride=1)\n",
" )\n",
" self.fc = nn.Sequential(\n",
" nn.Linear(6 * 6 * 6, 1024),\n",
" nn.Dropout(0.4),\n",
" nn.Linear(1024, 10)\n",
" )\n",
"\n",
" def forward(self, x):\n",
" x = self.conv(x)\n",
" x = x.reshape(x.size(0), -1)\n",
" x = self.fc(x)\n",
" return x"
],
"id": "64082ff8ea82fe8",
"outputs": [],
"execution_count": 29
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:40:33.786208Z",
"start_time": "2025-06-24T16:07:03.216673Z"
}
},
"cell_type": "code",
"source": [
"num_epochs = 300\n",
"device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
"print(device)\n",
"seed_torch(1024) # 重新设置随机种子\n",
"model = RandomQCCNN()\n",
"model.to(device)\n",
"criterion = nn.CrossEntropyLoss()\n",
"optimizer = optim.SGD(model.parameters(), lr=0.01, weight_decay=0.001) # 添加正则化项\n",
"optim_model, metrics = train_model(model, criterion, optimizer, train_loader, valid_loader, num_epochs, device)\n",
"torch.save(optim_model.state_dict(), './data/notebook1/random_qccnn_weights.pt') # 保存训练好的模型参数,用于后续的推理或测试\n",
"pd.DataFrame(metrics).to_csv('./data/notebook1/random_qccnn_metrics.csv', index='None') # 保存模型训练过程,用于后续图标展示"
],
"id": "19b3021c114a9129",
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"cuda\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Train loss: 0.620 Valid Acc: 0.756: 100%|██████████| 300/300 [33:30<00:00, 6.70s/it]\n"
]
}
],
"execution_count": 30
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:40:38.222252Z",
"start_time": "2025-06-24T16:40:33.895998Z"
}
},
"cell_type": "code",
"source": [
"state_dict = torch.load('./data/notebook1/random_qccnn_weights.pt', map_location=device)\n",
"random_qccnn_model = RandomQCCNN()\n",
"random_qccnn_model.load_state_dict(state_dict)\n",
"random_qccnn_model.to(device)\n",
"\n",
"test_acc = test_model(random_qccnn_model, test_loader, device)"
],
"id": "49ceb326295cd4a9",
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Test Acc: 0.769\n"
]
}
],
"execution_count": 31
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:40:38.644386Z",
"start_time": "2025-06-24T16:40:38.356492Z"
}
},
"cell_type": "code",
"source": [
"data = pd.read_csv('./data/notebook1/random_qccnn_metrics.csv')\n",
"epoch = data['epoch']\n",
"train_loss = data['train_loss']\n",
"valid_loss = data['valid_loss']\n",
"train_acc = data['train_acc']\n",
"valid_acc = data['valid_acc']\n",
"\n",
"# 创建图和Axes对象\n",
"fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))\n",
"\n",
"# 绘制训练损失曲线\n",
"ax1.plot(epoch, train_loss, label='Train Loss')\n",
"ax1.plot(epoch, valid_loss, label='Valid Loss')\n",
"ax1.set_title('Training Loss Curve')\n",
"ax1.set_xlabel('Epoch')\n",
"ax1.set_ylabel('Loss')\n",
"ax1.legend()\n",
"\n",
"# 绘制训练准确率曲线\n",
"ax2.plot(epoch, train_acc, label='Train Accuracy')\n",
"ax2.plot(epoch, valid_acc, label='Valid Accuracy')\n",
"ax2.set_title('Training Accuracy Curve')\n",
"ax2.set_xlabel('Epoch')\n",
"ax2.set_ylabel('Accuracy')\n",
"ax2.legend()\n",
"\n",
"plt.show()"
],
"id": "45287356d5a9a0ad",
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 1200x500 with 2 Axes>"
],
"image/png": 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"
},
"metadata": {},
"output_type": "display_data"
}
],
"execution_count": 32
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:40:38.803068Z",
"start_time": "2025-06-24T16:40:38.798344Z"
}
},
"cell_type": "code",
"source": [
"class ParameterizedQuantumConvolutionalLayer(nn.Module):\n",
" def __init__(self, nqubit, num_circuits):\n",
" super().__init__()\n",
" self.nqubit = nqubit\n",
" self.cirs = nn.ModuleList([self.circuit(nqubit) for _ in range(num_circuits)])\n",
"\n",
" def circuit(self, nqubit):\n",
" cir = dq.QubitCircuit(nqubit)\n",
" cir.rxlayer(encode=True) #对原论文的量子线路结构并无影响,只是做了一个数据编码的操作\n",
" cir.barrier()\n",
" for iter in range(4): #对应原论文中一个量子卷积线路上的深度为4可控参数一共16个\n",
" cir.rylayer()\n",
" cir.cnot_ring()\n",
" cir.barrier()\n",
"\n",
" cir.observable(0)\n",
" return cir\n",
"\n",
" def forward(self, x):\n",
" kernel_size, stride = 2, 2\n",
" # [64, 1, 18, 18] -> [64, 1, 9, 18, 2] -> [64, 1, 9, 9, 2, 2]\n",
" x_unflod = x.unfold(2, kernel_size, stride).unfold(3, kernel_size, stride)\n",
" w = int((x.shape[-1] - kernel_size) / stride + 1)\n",
" x_reshape = x_unflod.reshape(-1, self.nqubit)\n",
"\n",
" exps = []\n",
" for cir in self.cirs: # out_channels\n",
" cir(x_reshape)\n",
" exp = cir.expectation()\n",
" exps.append(exp)\n",
"\n",
" exps = torch.stack(exps, dim=1)\n",
" exps = exps.reshape(x.shape[0], 3, w, w)\n",
" return exps"
],
"id": "736fe987b84d5891",
"outputs": [],
"execution_count": 33
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:40:39.249632Z",
"start_time": "2025-06-24T16:40:38.925139Z"
}
},
"cell_type": "code",
"source": [
"# 此处我们可视化其中一个量子卷积核的线路结构:\n",
"net = ParameterizedQuantumConvolutionalLayer(nqubit=4, num_circuits=3)\n",
"net.cirs[0].draw()"
],
"id": "e8058c7fde0a012b",
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 2210.55x785.944 with 1 Axes>"
],
"image/png": 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},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 34
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T16:40:39.356624Z",
"start_time": "2025-06-24T16:40:39.353193Z"
}
},
"cell_type": "code",
"source": [
"# QCCNN整体网络架构\n",
"class QCCNN(nn.Module):\n",
" def __init__(self):\n",
" super(QCCNN, self).__init__()\n",
" self.conv = nn.Sequential(\n",
" ParameterizedQuantumConvolutionalLayer(nqubit=4, num_circuits=3),\n",
" nn.ReLU(),\n",
" nn.MaxPool2d(kernel_size=2, stride=1)\n",
" )\n",
"\n",
" self.fc = nn.Sequential(\n",
" nn.Linear(8 * 8 * 3, 128),\n",
" nn.Dropout(0.4),\n",
" nn.ReLU(),\n",
" nn.Linear(128, 10)\n",
" )\n",
"\n",
" def forward(self, x):\n",
" x = self.conv(x)\n",
" x = x.reshape(x.size(0), -1)\n",
" x = self.fc(x)\n",
" return x"
],
"id": "e3c6160fff06bed2",
"outputs": [],
"execution_count": 35
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T17:19:26.744108Z",
"start_time": "2025-06-24T16:40:39.450592Z"
}
},
"cell_type": "code",
"source": [
"num_epochs = 300\n",
"device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
"\n",
"model = QCCNN()\n",
"model.to(device)\n",
"criterion = nn.CrossEntropyLoss()\n",
"optimizer = optim.Adam(model.parameters(), lr=1e-5) # 添加正则化项\n",
"optim_model, metrics = train_model(model, criterion, optimizer, train_loader, valid_loader, num_epochs, device)\n",
"torch.save(optim_model.state_dict(), './data/notebook1/qccnn_weights.pt') # 保存训练好的模型参数,用于后续的推理或测试\n",
"pd.DataFrame(metrics).to_csv('./data/notebook1/qccnn_metrics.csv', index='None') # 保存模型训练过程,用于后续图标展示"
],
"id": "34202fca380ee084",
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Train loss: 0.707 Valid Acc: 0.739: 100%|██████████| 300/300 [38:47<00:00, 7.76s/it]\n"
]
}
],
"execution_count": 36
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T17:19:31.162804Z",
"start_time": "2025-06-24T17:19:26.901586Z"
}
},
"cell_type": "code",
"source": [
"state_dict = torch.load('./data/notebook1/qccnn_weights.pt', map_location=device)\n",
"qccnn_model = QCCNN()\n",
"qccnn_model.load_state_dict(state_dict)\n",
"qccnn_model.to(device)\n",
"\n",
"test_acc = test_model(qccnn_model, test_loader, device)"
],
"id": "f613b1c9a9ea0cd6",
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Test Acc: 0.752\n"
]
}
],
"execution_count": 37
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T17:19:31.278383Z",
"start_time": "2025-06-24T17:19:31.271353Z"
}
},
"cell_type": "code",
"source": [
"def vgg_block(in_channel,out_channel,num_convs):\n",
" layers = nn.ModuleList()\n",
" assert num_convs >= 1\n",
" layers.append(nn.Conv2d(in_channel,out_channel,kernel_size=3,padding=1))\n",
" layers.append(nn.ReLU())\n",
" for _ in range(num_convs-1):\n",
" layers.append(nn.Conv2d(out_channel,out_channel,kernel_size=3,padding=1))\n",
" layers.append(nn.ReLU())\n",
" layers.append(nn.MaxPool2d(kernel_size=2,stride=2))\n",
" return nn.Sequential(*layers)\n",
"\n",
"VGG = nn.Sequential(\n",
" vgg_block(1,10,3), # 14,14\n",
" vgg_block(10,16,3), # 4 * 4\n",
" nn.Flatten(),\n",
" nn.Linear(16 * 4 * 4, 120),\n",
" nn.Sigmoid(),\n",
" nn.Linear(120, 84),\n",
" nn.Sigmoid(),\n",
" nn.Linear(84,10),\n",
" nn.Softmax(dim=-1)\n",
")"
],
"id": "37cc9edc6c4b035d",
"outputs": [],
"execution_count": 38
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T17:25:57.298293Z",
"start_time": "2025-06-24T17:19:31.391257Z"
}
},
"cell_type": "code",
"source": [
"num_epochs = 300\n",
"device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
"\n",
"vgg_model = VGG\n",
"vgg_model.to(device)\n",
"criterion = nn.CrossEntropyLoss()\n",
"optimizer = optim.Adam(vgg_model.parameters(), lr=1e-5) # 添加正则化项\n",
"vgg_model, metrics = train_model(vgg_model, criterion, optimizer, train_loader, valid_loader, num_epochs, device)\n",
"torch.save(vgg_model.state_dict(), './data/notebook1/vgg_weights.pt') # 保存训练好的模型参数,用于后续的推理或测试\n",
"pd.DataFrame(metrics).to_csv('./data/notebook1/vgg_metrics.csv', index='None') # 保存模型训练过程,用于后续图标展示"
],
"id": "643da0fb0433f438",
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Train loss: 1.776 Valid Acc: 0.732: 100%|██████████| 300/300 [06:25<00:00, 1.29s/it]\n"
]
}
],
"execution_count": 39
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T17:25:58.336844Z",
"start_time": "2025-06-24T17:25:57.506934Z"
}
},
"cell_type": "code",
"source": [
"state_dict = torch.load('./data/notebook1/vgg_weights.pt', map_location=device)\n",
"vgg_model = VGG\n",
"vgg_model.load_state_dict(state_dict)\n",
"vgg_model.to(device)\n",
"\n",
"vgg_test_acc = test_model(vgg_model, test_loader, device)"
],
"id": "cc56710965ab7c82",
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Test Acc: 0.742\n"
]
}
],
"execution_count": 40
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T17:25:58.691203Z",
"start_time": "2025-06-24T17:25:58.488844Z"
}
},
"cell_type": "code",
"source": [
"vgg_data = pd.read_csv('./data/notebook1/vgg_metrics.csv')\n",
"qccnn_data = pd.read_csv('./data/notebook1/qccnn_metrics.csv')\n",
"vgg_epoch = vgg_data['epoch']\n",
"vgg_train_loss = vgg_data['train_loss']\n",
"vgg_valid_loss = vgg_data['valid_loss']\n",
"vgg_train_acc = vgg_data['train_acc']\n",
"vgg_valid_acc = vgg_data['valid_acc']\n",
"\n",
"qccnn_epoch = qccnn_data['epoch']\n",
"qccnn_train_loss = qccnn_data['train_loss']\n",
"qccnn_valid_loss = qccnn_data['valid_loss']\n",
"qccnn_train_acc = qccnn_data['train_acc']\n",
"qccnn_valid_acc = qccnn_data['valid_acc']\n",
"\n",
"# 创建图和Axes对象\n",
"fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))\n",
"\n",
"# 绘制训练损失曲线\n",
"ax1.plot(vgg_epoch, vgg_train_loss, label='VGG Train Loss')\n",
"ax1.plot(vgg_epoch, vgg_valid_loss, label='VGG Valid Loss')\n",
"ax1.plot(qccnn_epoch, qccnn_train_loss, label='QCCNN Valid Loss')\n",
"ax1.plot(qccnn_epoch, qccnn_valid_loss, label='QCCNN Valid Loss')\n",
"ax1.set_title('Training Loss Curve')\n",
"ax1.set_xlabel('Epoch')\n",
"ax1.set_ylabel('Loss')\n",
"ax1.legend()\n",
"\n",
"# 绘制训练准确率曲线\n",
"ax2.plot(vgg_epoch, vgg_train_acc, label='VGG Train Accuracy')\n",
"ax2.plot(vgg_epoch, vgg_valid_acc, label='VGG Valid Accuracy')\n",
"ax2.plot(qccnn_epoch, qccnn_train_acc, label='QCCNN Train Accuracy')\n",
"ax2.plot(qccnn_epoch, qccnn_valid_acc, label='QCCNN Valid Accuracy')\n",
"ax2.set_title('Training Accuracy Curve')\n",
"ax2.set_xlabel('Epoch')\n",
"ax2.set_ylabel('Accuracy')\n",
"ax2.legend()\n",
"\n",
"plt.show()"
],
"id": "8e450f8cfb2812d2",
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 1200x500 with 2 Axes>"
],
"image/png": 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"
},
"metadata": {},
"output_type": "display_data"
}
],
"execution_count": 41
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-06-24T17:25:58.850907Z",
"start_time": "2025-06-24T17:25:58.833078Z"
}
},
"cell_type": "code",
"source": [
"# 这里我们对比不同模型之间可训练参数量的区别\n",
"\n",
"def count_parameters(model):\n",
" \"\"\"\n",
" 计算模型的参数数量\n",
" \"\"\"\n",
" return sum(p.numel() for p in model.parameters() if p.requires_grad)\n",
"\n",
"number_params_VGG = count_parameters(VGG)\n",
"number_params_QCCNN = count_parameters(QCCNN())\n",
"print(f'VGG 模型可训练参数量:{number_params_VGG}\\t QCCNN模型可训练参数量{number_params_QCCNN}')"
],
"id": "9675ba847f4a998d",
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"VGG 模型可训练参数量49870\t QCCNN模型可训练参数量26042\n"
]
}
],
"execution_count": 42
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}