globalaveragepooling1d 参数 GlobalAveragePooling1d 是 PyTorch 中用于一维全局平均池化的层。它没有可学习的参数,因此没有需要用户输入的参数。该层的作用是在一维输入张量的每个通道上进行全局平均池化。 以下是使用 GlobalAveragePooling1d 的基本示例: python import torch.nn as nn # 假设输入张量为 (batch_size...
PoolingPooling的讲解可以看我的这篇文章CS231n 笔记:通俗理解 CNN 这里主要讲解一下如何用 pytorch定义Pooling层,有两种方式,具体看下面代码 import torch 1.1K20 深度学习: globalpooling(全局池化) 说白了,“globalpooling”就是pooling的 滑窗size 和整张feature map的size一样大。...“globalpooling”在滑窗内...
The initial learning rate is 0.01, the Python version is 3.6, and the PyTorch version is 1.12. Figure 7. Sample images from RAF-DB and AffectNet datasets. We use the Retinaface algorithm to detect the location rectangle of the face and the location map of the five key points of the face...
Experimental setup: The algorithm in this study was developed using the PyTorch 1.12.1 framework and Python 3.8 on a server configured with a 12th Gen Intel (R) Core (TM) i9-12900K, an NVIDIA GeForce RTX 3090 GPU, and running the Ubuntu 20.04 LTS operating system. During the training pr...