更新环境依赖 111qqz/hugo-blog@7cb3eab

2023/12/cupy-torch-import-order-impact/index.html

@@ -106,7 +106,7 @@ <h1 class=post_title>[施工中] cupy与torch的导入顺序不同对计算结
 <span><svg class="icon"><use xlink:href="#calendar"/></svg></span>
 <span class=post_date>
 Dec 17, 2023</span>
-<span class=post_time> · 1 min read</span><span>&nbsp;· <a href=https://111qqz.com/tags/pytorch title=pytorch class="post_tag button button_translucent">pytorch
+<span class=post_time> · 2 min read</span><span>&nbsp;· <a href=https://111qqz.com/tags/pytorch title=pytorch class="post_tag button button_translucent">pytorch
 </a><a href=https://111qqz.com/tags/cupy title=cupy class="post_tag button button_translucent">cupy
 </a><a href=https://111qqz.com/tags/python title=python class="post_tag button button_translucent">python
 </a>
@@ -119,6 +119,7 @@ <h2>Overview</h2>
 <li><a href=#背景>背景</a></li>
 <li><a href=#最小复现代码>最小复现代码</a>
 <ul>
+<li><a href=#测试环境>测试环境</a></li>
 <li><a href=#结果举例>结果举例</a></li>
 </ul>
 </li>
@@ -184,6 +185,21 @@ <h2>Overview</h2>
 <span class=ln>44</span><span class=n>output_tensor</span> <span class=o>=</span> <span class=n>model</span><span class=p>(</span><span class=n>input_tensor</span><span class=p>)</span><span class=o>.</span><span class=n>detach</span><span class=p>()</span><span class=o>.</span><span class=n>cpu</span><span class=p>()</span><span class=o>.</span><span class=n>numpy</span><span class=p>()</span>
 <span class=ln>45</span>
 <span class=ln>46</span><span class=nb>print</span><span class=p>(</span><span class=s2>&#34;输出张量:&#34;</span><span class=p>,</span> <span class=n>output_tensor</span><span class=p>)</span>
+</code></pre></div><h3 id=测试环境>测试环境</h3>
+<div class=highlight><pre tabindex=0 class=chroma><code class=language-shell data-lang=shell><span class=ln>1</span>cupy-cuda11x 12.0.0
+<span class=ln>2</span>NVIDIA-SMI 460.73.01 Driver Version: 460.73.01 CUDA Version: 11.2
+<span class=ln>3</span>torch 1.13.0+cu117
+<span class=ln>4</span>numpy                              1.24.4
+<span class=ln>5</span>numpy-groupies                     0.9.22
+<span class=ln>6</span>numpydoc                           1.1.0
+</code></pre></div><p>nvcc版本</p>
+<div class=highlight><pre tabindex=0 class=chroma><code class=language-shell data-lang=shell><span class=ln>1</span>./nvcc --version
+<span class=ln>2</span>nvcc: NVIDIA <span class=o>(</span>R<span class=o>)</span> Cuda compiler driver
+<span class=ln>3</span>Copyright <span class=o>(</span>c<span class=o>)</span> 2005-2021 NVIDIA Corporation
+<span class=ln>4</span>Built on Sun_Feb_14_21:12:58_PST_2021
+<span class=ln>5</span>Cuda compilation tools, release 11.2, V11.2.152
+<span class=ln>6</span>Build cuda_11.2.r11.2/compiler.29618528_0
+<span class=ln>7</span>
 </code></pre></div><h3 id=结果举例>结果举例</h3>
 <p>测试GPU为: A100-PCIE-40GB<br>
 先<code>import cupy</code>,后<code>import torch</code>,得到的结果为:</p>

categories/deep-learning/index.html

@@ -146,7 +146,7 @@ <h3 class=post_link>
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-<span class=post_time> · 1 min read</span><span>&nbsp;· <a href=https://111qqz.com/tags/pytorch title=pytorch class="post_tag button button_translucent">pytorch
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index.html

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post/index.html

@@ -146,7 +146,7 @@ <h3 class=post_link>
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tags/cupy/index.html

@@ -110,7 +110,7 @@ <h3 class=post_link>
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@@ -110,7 +110,7 @@ <h3 class=post_link>
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tags/pytorch/index.html

@@ -110,7 +110,7 @@ <h3 class=post_link>
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