NLLLoss和CrossEntropyLoss

NLLLoss和CrossEntropyLoss是用于计算分类问题中的损失函数。在实际中，可以认为NLLLoss和CrossEntropyLoss是等价的。内置的CrossEntropyLoss函数就是完成这个计算的，可以通过nn.CrossEntropyLoss()来定义。这个函数将输出和标签作为输入，计算出损失值。NLL_LOSS和CROSS_ENTROPY_LOSS是常用的损失函数，它们在处理分类问题时非常有用。可以在代码中使用这些损失函数来评估模型的性能。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* *2* [NLL_Loss & CrossEntropyLoss（交叉熵）](https://blog.csdn.net/Tabbyddd/article/details/106101759)[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%"]
- *3* [NLL_LOSS与CROSS_ENTROPY_LOSS详解](https://blog.csdn.net/GXG_boss6/article/details/126696719)[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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