From 0eab8ea4d3a7c5763ed6f37da0401c9a4f8fe7fb Mon Sep 17 00:00:00 2001
From: Jingbin Wang <145735287+Wjbbbbb@users.noreply.github.com>
Date: Tue, 17 Sep 2024 12:34:23 +0800
Subject: [PATCH] Update channels.md
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要遍历第0个维度，如果直接zip(X, K)的话，corr2d()依次读取到X和K的第0和1个维度，对X[i]中的两个矩阵和K[i]中的两个矩阵进行卷积运算，这样会导致出现'''ValueError: too many values to unpack (expected 2)'''这样的错误，因此，要对X和K加上下标0
---
 chapter_convolutional-neural-networks/channels.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/chapter_convolutional-neural-networks/channels.md b/chapter_convolutional-neural-networks/channels.md
index 86caaf2ae..8fa3ff775 100644
--- a/chapter_convolutional-neural-networks/channels.md
+++ b/chapter_convolutional-neural-networks/channels.md
@@ -45,7 +45,7 @@ import paddle
 #@tab mxnet, pytorch, paddle
 def corr2d_multi_in(X, K):
     # 先遍历“X”和“K”的第0个维度（通道维度），再把它们加在一起
-    return sum(d2l.corr2d(x, k) for x, k in zip(X, K))
+    return sum(d2l.corr2d(x, k) for x, k in zip(X[0], K[0]))
 ```
 
 ```{.python .input}