add training ResNet-50 from scratch using pytorch notes

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@@ -53,6 +53,17 @@ <h1>davidgao7 blog</h1>
 
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+        <li class="posts-list-item">
+          <a class="posts-list-item-title" href="/posts/training-resnet-using-pytorch/">Training Resnet Using Pytorch</a>
+          <span class="posts-list-item-description">
+            <svg class="icon icon-calendar" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><title>calendar</title><rect x="3" y="4" width="18" height="18" rx="2" ry="2"></rect><line x1="16" y1="2" x2="16" y2="6"></line><line x1="8" y1="2" x2="8" y2="6"></line><line x1="3" y1="10" x2="21" y2="10"></line></svg>
+            Apr 23, 2025
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+            9 min read
+          </span>
+        </li>
+      
         <li class="posts-list-item">
           <a class="posts-list-item-title" href="/posts/finetune-llm-using-pytorch/">Finetune LLM Using Pytorch</a>
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@@ -152,17 +163,6 @@ <h1>davidgao7 blog</h1>
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+    <item>
+      <title>Training Resnet Using Pytorch</title>
+      <link>http://localhost:1313/posts/training-resnet-using-pytorch/</link>
+      <pubDate>Wed, 23 Apr 2025 22:34:35 -0400</pubDate>
+      <guid>http://localhost:1313/posts/training-resnet-using-pytorch/</guid>
+      <description>&lt;h1 id=&#34;re-visit-convolutional-neural-network-cnn-architectures-plainnet--resnet-using-pytorch&#34;&gt;Re-visit Convolutional Neural Network (CNN) Architectures: PlainNet &amp;amp; ResNet using Pytorch&lt;/h1&gt;&#xA;&lt;p&gt;In this blog I will use pytorch to rebuild a classic vision model: &lt;code&gt;ResNet-50&lt;/code&gt;, to get more hands on exercise for real-world computer vision application&lt;/p&gt;&#xA;&lt;h2 id=&#34;preparation&#34;&gt;Preparation&lt;/h2&gt;&#xA;&lt;p&gt;Please make sure you have the following packages installed:&lt;/p&gt;&#xA;&lt;pre tabindex=&#34;0&#34;&gt;&lt;code&gt;torch&#xA;torchvision&#xA;plotly&#xA;IPython&#xA;&lt;/code&gt;&lt;/pre&gt;&lt;p&gt;Import the libraries, and check the GPU availability. If you are using a Mac with MPS, it will automatically use the MPS device. Otherwise, it will use the CUDA device if available.&lt;/p&gt;</description>
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       <title>Finetune LLM Using Pytorch</title>
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