nn.Sequential()格式

nn.Sequential()是PyTorch中的一个类，用于按顺序组合多个神经网络层。它的格式可以有两种方式构建。

第一种方式是通过在nn.Sequential()中传入多个层的实例来构建。例如：

import torch.nn as nn

model = nn.Sequential(
    nn.Conv2d(3, 16, 3, 1, 1),
    nn.ReLU(),
    nn.BatchNorm2d(16),
    nn.MaxPool2d(2, 2)
)

第二种方式是通过在nn.Sequential()中调用多个层的构造函数来构建。例如：

import torch.nn as nn

model = nn.Sequential()
model.add_module('conv1', nn.Conv2d(3, 16, 3, 1, 1))
model.add_module('relu1', nn.ReLU())
model.add_module('bn1', nn.BatchNorm2d(16))
model.add_module('pool1', nn.MaxPool2d(2, 2))

无论使用哪种方式构建，最终得到的model都是一样的。nn.Sequential()的作用是按照顺序组合多个层，可以方便地构建复杂的神经网络模型。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* *3* [nn.Sequential()](https://blog.csdn.net/Just_do_myself/article/details/124195393)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 50%"]
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