nn.Conv2d same
时间: 2023-10-16 14:03:09 浏览: 37
nn.Conv2d的参数padding='SAME'表示使用padding使输出的特征图尺寸与输入的特征图尺寸相同。在引用中的MLP代码实现中,nn.Conv2d的padding参数设置为0,而在引用中的TensorFlow代码中,slim.conv2d的padding参数设置为'SAME',这两者的结果是一样的,即输出特征图尺寸与输入特征图尺寸相同。所以可以认为它们是等价的。<em>1</em><em>2</em><em>3</em>
#### 引用[.reference_title]
- *1* *3* [nn.Conv1d、nn.Conv2d、nn.Linear](https://blog.csdn.net/qq_39506862/article/details/128493185)[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^v92^chatsearchT0_1"}} ] [.reference_item]
- *2* [小小白整理tf.nn.conv2d与tf.contrib.slim.conv2d异同](https://blog.csdn.net/mfjzjhayb/article/details/122968206)[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^v92^chatsearchT0_1"}} ] [.reference_item]
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