Pytorch Conv2d

最新推荐文章于 2025-07-11 15:21:10 发布

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本文详细介绍了卷积神经网络中卷积层的各项参数及其作用，包括输入和输出通道数、卷积核大小、步长、填充等，并解释了这些参数如何影响卷积操作。

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参数：
Args:
in_channels (int): Number of channels in the input image
out_channels (int): Number of channels produced by the convolution
kernel_size (int or tuple): Size of the convolving kernel
stride (int or tuple, optional): Stride of the convolution. Default: 1
padding (int or tuple, optional): Zero-padding added to both sides of the input. Default: 0
dilation (int or tuple, optional): Spacing between kernel elements. Default: 1
groups (int, optional): Number of blocked connections from input channels to output channels. Default: 1
bias (bool, optional): If True, adds a learnable bias to the output. Default: True

in_channels (int): 输入通道
out_channels (int): 输出通过
kernel_size (int or tuple): 卷积核（滤波器）的大小
stride (int or tuple, optional): 步长，可以是整数，也可以是tuple
padding (int or tuple, optional): 周围补零Default: 0
dilation (int or tuple, optional): Spacing between kernel elements. Default: 1（不懂）
groups (int, optional): Number of blocked connections from input channels to output channels. Default: 1(不懂)
bias (bool, optional): If True, adds a learnable bias to the output. Default: True(偏差)