ioad minist

Image/utils/dataset_utils.py

@@ -53,3 +53,58 @@ def get_cifar10_dataloaders(batch_size=128, num_workers=2, local_dataset_path=No
         testset, batch_size=100, shuffle=False, num_workers=num_workers)
 
     return trainloader, testloader
+
+def get_mnist_dataloaders(batch_size=128, num_workers=2, local_dataset_path=None):
+    """获取MNIST数据集的数据加载器
+    
+    Args:
+        batch_size: 批次大小
+        num_workers: 数据加载的工作进程数
+        local_dataset_path: 本地数据集路径，如果提供则使用本地数据集，否则下载
+        
+    Returns:
+        trainloader: 训练数据加载器
+        testloader: 测试数据加载器
+    """
+    # 数据预处理
+    transform_train = transforms.Compose([
+        transforms.RandomRotation(10),     # 随机旋转±10度
+        transforms.RandomAffine(          # 随机仿射变换
+            degrees=0,                    # 不进行旋转
+            translate=(0.1, 0.1),         # 平移范围
+            scale=(0.9, 1.1)             # 缩放范围
+        ),
+        transforms.ToTensor(),
+        transforms.Normalize((0.1307,), (0.3081,))  # MNIST数据集的均值和标准差
+    ])
+
+    transform_test = transforms.Compose([
+        transforms.ToTensor(),
+        transforms.Normalize((0.1307,), (0.3081,))
+    ])
+
+    # 设置数据集路径
+    if local_dataset_path:
+        print(f"使用本地数据集: {local_dataset_path}")
+        download = False
+        dataset_path = local_dataset_path
+    else:
+        print("未指定本地数据集路径，将下载数据集")
+        download = True
+        dataset_path = '../dataset'
+
+    # 创建数据集路径
+    if not os.path.exists(dataset_path):
+        os.makedirs(dataset_path)
+
+    trainset = torchvision.datasets.MNIST(
+        root=dataset_path, train=True, download=download, transform=transform_train)
+    trainloader = torch.utils.data.DataLoader(
+        trainset, batch_size=batch_size, shuffle=True, num_workers=num_workers)
+
+    testset = torchvision.datasets.MNIST(
+        root=dataset_path, train=False, download=download, transform=transform_test)
+    testloader = torch.utils.data.DataLoader(
+        testset, batch_size=100, shuffle=False, num_workers=num_workers)
+
+    return trainloader, testloader