batch_size, channels, height, width

这些参数通常用于描述图像的维度，其中batch_size指的是每次处理的图像数量，channels表示图像的通道数，height和width分别表示图像的高和宽。以下是一个用到这些参数的CNN模型的例子[^1]：

import torch
import torch.nn as nn

class CNN(nn.Module):
    def __init__(self, batch_size, channels, height, width):
        super(CNN, self).__init__()
        self.conv = nn.Conv2d(channels, 64, kernel_size=3, stride=1, padding=1)
        self.pool = nn.MaxPool2d(kernel_size=2, stride=2)
        self.fc = nn.Linear(64 * (height // 2) * (width // 2), 10)

    def forward(self, x):
        x = self.conv(x)
        x = nn.functional.relu(x)
        x = self.pool(x)
        x = torch.flatten(x, 1)
        x = self.fc(x)
        return x