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统计学
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抽样
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推断
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概率论
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计数
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</a>
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概率概念
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分布
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</span>
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</a>
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贝叶斯
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</span>
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</a>
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信息论
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</span>
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机器学习
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</span>
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<span class="md-nav__icon md-icon"></span>
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机器学习
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经典机器学习
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梯度机器学习
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</span>
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</a>
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深度学习
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</span>
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</a>
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强化学习
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</span>
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</a>
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分布式深度学习
|
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</span>
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|
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|
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|
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</a>
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计算语言学
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<span class="md-nav__icon md-icon"></span>
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计算语言学
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语言学基础
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</a>
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嵌入与序列模型
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</span>
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</a>
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Transformer 与语言模型
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</span>
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|
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</a>
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<span class="md-ellipsis">
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高级文本生成
|
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|
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|
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|
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</span>
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|
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|
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|
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</a>
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计算机视觉
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计算机视觉
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图像基础
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</span>
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</a>
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目标检测与分割
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多模态学习
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多模态学习
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多模态表征
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</span>
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</a>
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统一多模态架构
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</span>
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自主系统
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感知
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视觉-语言-动作模型
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自动驾驶
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</a>
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太空与极端机器人
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</span>
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图神经网络
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数据结构与算法
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|
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</a>
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|
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</a>
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生产级软件工程
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测试与质量保障
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Mock 与补丁
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Vulkan Compute 与跨平台 GPU
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AI 推理
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量化
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高效架构
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服务与批处理
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边缘推理
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</a>
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扩缩与部署
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ML 系统设计
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大规模基础设施
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</a>
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ML 设计案例
|
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|
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</span>
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|
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应用 AI
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AI 金融
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</span>
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</a>
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蛋白质设计
|
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|
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<h1 id="_1">测试与质量保障<a class="headerlink" href="#_1" title="Permanent link">¶</a></h1>
|
||
<p><em>测试是你如何确保代码正常工作的方法——不仅是现在，而且在每次更改后都能正常工作。本文涵盖测试金字塔、使用 pytest 进行的单元测试、Mock、测试机器学习特定代码、CI/CD 管道、代码检查、格式化和代码审查——这些实践能在错误到达生产环境之前捕获它们。</em></p>
|
||
<ul>
|
||
<li>
|
||
<p>机器学习代码以缺乏测试而闻名。"能训练，所以能工作"是普遍态度。这会导致静默错误：一个错误地打乱数据的数据加载器、一个有符号错误的损失函数、一个丢弃 5% 数据的预处理步骤。这些错误不会使你的程序崩溃。它们只是让你的模型悄悄变差，然后你浪费数周时间调试"本应更高"的指标。</p>
|
||
</li>
|
||
<li>
|
||
<p>测试不是额外负担。它是快速前进而不破坏东西的最快方式。</p>
|
||
</li>
|
||
</ul>
|
||
<h2 id="_2">测试金字塔<a class="headerlink" href="#_2" title="Permanent link">¶</a></h2>
|
||
<ul>
|
||
<li>
|
||
<p>测试按层级组织，从快速且狭窄到慢速且广泛：</p>
|
||
<ul>
|
||
<li>
|
||
<p><strong>单元测试</strong>（底层）：隔离测试单个函数和类。快速（毫秒级），数量多（数百到数千）。"<code>normalise_image</code> 是否产生 [0, 1] 范围内的值？"</p>
|
||
</li>
|
||
<li>
|
||
<p><strong>集成测试</strong>（中层）：测试组件协同工作。较慢（秒级）。"数据加载器是否以模型期望的格式产生批次？"</p>
|
||
</li>
|
||
<li>
|
||
<p><strong>端到端测试</strong>（顶层）：测试从输入到输出的完整管道。较慢（分钟级）。"<code>python train.py --config test.yaml</code> 是否无错误完成并产生有效的检查点？"</p>
|
||
</li>
|
||
</ul>
|
||
</li>
|
||
<li>
|
||
<p>金字塔形状意味着：编写大量单元测试，较少数量的集成测试，以及少量端到端测试。单元测试捕获大多数错误，并在几秒钟内运行。端到端测试捕获集成问题，但慢且脆弱。</p>
|
||
</li>
|
||
</ul>
|
||
<h2 id="pytest">使用 pytest 进行单元测试<a class="headerlink" href="#pytest" title="Permanent link">¶</a></h2>
|
||
<ul>
|
||
<li><strong>pytest</strong> 是标准的 Python 测试框架。测试是以 <code>test_</code> 开头的函数，放在以 <code>test_</code> 开头的文件中：</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="c1"># tests/test_utils.py</span>
|
||
<a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a>
|
||
<a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a><span class="k">def</span><span class="w"> </span><span class="nf">test_normalise_image</span><span class="p">():</span>
|
||
<a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a> <span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
|
||
<a id="__codelineno-0-5" name="__codelineno-0-5" href="#__codelineno-0-5"></a> <span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">128</span><span class="p">,</span> <span class="mi">255</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
|
||
<a id="__codelineno-0-6" name="__codelineno-0-6" href="#__codelineno-0-6"></a> <span class="n">result</span> <span class="o">=</span> <span class="n">normalise_image</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">mean</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span> <span class="n">std</span><span class="o">=</span><span class="mi">128</span><span class="p">)</span>
|
||
<a id="__codelineno-0-7" name="__codelineno-0-7" href="#__codelineno-0-7"></a> <span class="k">assert</span> <span class="n">result</span><span class="o">.</span><span class="n">min</span><span class="p">()</span> <span class="o">>=</span> <span class="o">-</span><span class="mf">1.0</span>
|
||
<a id="__codelineno-0-8" name="__codelineno-0-8" href="#__codelineno-0-8"></a> <span class="k">assert</span> <span class="n">result</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> <span class="o"><=</span> <span class="mf">1.0</span>
|
||
<a id="__codelineno-0-9" name="__codelineno-0-9" href="#__codelineno-0-9"></a> <span class="k">assert</span> <span class="nb">abs</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> <span class="o"><</span> <span class="mf">1e-6</span> <span class="c1"># 128 被 mean=128 归一化后应约为 0</span>
|
||
<a id="__codelineno-0-10" name="__codelineno-0-10" href="#__codelineno-0-10"></a>
|
||
<a id="__codelineno-0-11" name="__codelineno-0-11" href="#__codelineno-0-11"></a><span class="k">def</span><span class="w"> </span><span class="nf">test_normalise_empty</span><span class="p">():</span>
|
||
<a id="__codelineno-0-12" name="__codelineno-0-12" href="#__codelineno-0-12"></a> <span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
|
||
<a id="__codelineno-0-13" name="__codelineno-0-13" href="#__codelineno-0-13"></a> <span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
|
||
<a id="__codelineno-0-14" name="__codelineno-0-14" href="#__codelineno-0-14"></a> <span class="n">result</span> <span class="o">=</span> <span class="n">normalise_image</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">mean</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span> <span class="n">std</span><span class="o">=</span><span class="mi">128</span><span class="p">)</span>
|
||
<a id="__codelineno-0-15" name="__codelineno-0-15" href="#__codelineno-0-15"></a> <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">result</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span>
|
||
</code></pre></div>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-1-1" name="__codelineno-1-1" href="#__codelineno-1-1"></a>pytest<span class="w"> </span>tests/<span class="w"> </span><span class="c1"># 运行所有测试</span>
|
||
<a id="__codelineno-1-2" name="__codelineno-1-2" href="#__codelineno-1-2"></a>pytest<span class="w"> </span>tests/test_utils.py<span class="w"> </span><span class="c1"># 运行一个文件</span>
|
||
<a id="__codelineno-1-3" name="__codelineno-1-3" href="#__codelineno-1-3"></a>pytest<span class="w"> </span>-v<span class="w"> </span><span class="c1"># 详细输出</span>
|
||
<a id="__codelineno-1-4" name="__codelineno-1-4" href="#__codelineno-1-4"></a>pytest<span class="w"> </span>-x<span class="w"> </span><span class="c1"># 在第一个失败时停止</span>
|
||
<a id="__codelineno-1-5" name="__codelineno-1-5" href="#__codelineno-1-5"></a>pytest<span class="w"> </span>-k<span class="w"> </span><span class="s2">"normalise"</span><span class="w"> </span><span class="c1"># 运行匹配名称模式的测试</span>
|
||
<a id="__codelineno-1-6" name="__codelineno-1-6" href="#__codelineno-1-6"></a>pytest<span class="w"> </span>--tb<span class="o">=</span>short<span class="w"> </span><span class="c1"># 更短的追溯信息</span>
|
||
</code></pre></div>
|
||
<h3 id="_3">夹具<a class="headerlink" href="#_3" title="Permanent link">¶</a></h3>
|
||
<ul>
|
||
<li><strong>夹具</strong>为测试提供可复用的设置。无需在每个测试中重复设置代码，只需定义一次：</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-2-1" name="__codelineno-2-1" href="#__codelineno-2-1"></a><span class="kn">import</span><span class="w"> </span><span class="nn">pytest</span>
|
||
<a id="__codelineno-2-2" name="__codelineno-2-2" href="#__codelineno-2-2"></a>
|
||
<a id="__codelineno-2-3" name="__codelineno-2-3" href="#__codelineno-2-3"></a><span class="nd">@pytest</span><span class="o">.</span><span class="n">fixture</span>
|
||
<a id="__codelineno-2-4" name="__codelineno-2-4" href="#__codelineno-2-4"></a><span class="k">def</span><span class="w"> </span><span class="nf">sample_dataset</span><span class="p">():</span>
|
||
<a id="__codelineno-2-5" name="__codelineno-2-5" href="#__codelineno-2-5"></a><span class="w"> </span><span class="sd">"""创建一个用于测试的小型数据集。"""</span>
|
||
<a id="__codelineno-2-6" name="__codelineno-2-6" href="#__codelineno-2-6"></a> <span class="k">return</span> <span class="p">{</span>
|
||
<a id="__codelineno-2-7" name="__codelineno-2-7" href="#__codelineno-2-7"></a> <span class="s2">"inputs"</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">32</span><span class="p">),</span>
|
||
<a id="__codelineno-2-8" name="__codelineno-2-8" href="#__codelineno-2-8"></a> <span class="s2">"labels"</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="p">(</span><span class="mi">10</span><span class="p">,))</span>
|
||
<a id="__codelineno-2-9" name="__codelineno-2-9" href="#__codelineno-2-9"></a> <span class="p">}</span>
|
||
<a id="__codelineno-2-10" name="__codelineno-2-10" href="#__codelineno-2-10"></a>
|
||
<a id="__codelineno-2-11" name="__codelineno-2-11" href="#__codelineno-2-11"></a><span class="nd">@pytest</span><span class="o">.</span><span class="n">fixture</span>
|
||
<a id="__codelineno-2-12" name="__codelineno-2-12" href="#__codelineno-2-12"></a><span class="k">def</span><span class="w"> </span><span class="nf">trained_model</span><span class="p">():</span>
|
||
<a id="__codelineno-2-13" name="__codelineno-2-13" href="#__codelineno-2-13"></a><span class="w"> </span><span class="sd">"""加载一个小型预训练模型。"""</span>
|
||
<a id="__codelineno-2-14" name="__codelineno-2-14" href="#__codelineno-2-14"></a> <span class="n">model</span> <span class="o">=</span> <span class="n">SmallModel</span><span class="p">()</span>
|
||
<a id="__codelineno-2-15" name="__codelineno-2-15" href="#__codelineno-2-15"></a> <span class="n">model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="s2">"tests/fixtures/small_model.pt"</span><span class="p">))</span>
|
||
<a id="__codelineno-2-16" name="__codelineno-2-16" href="#__codelineno-2-16"></a> <span class="k">return</span> <span class="n">model</span>
|
||
<a id="__codelineno-2-17" name="__codelineno-2-17" href="#__codelineno-2-17"></a>
|
||
<a id="__codelineno-2-18" name="__codelineno-2-18" href="#__codelineno-2-18"></a><span class="k">def</span><span class="w"> </span><span class="nf">test_model_output_shape</span><span class="p">(</span><span class="n">trained_model</span><span class="p">,</span> <span class="n">sample_dataset</span><span class="p">):</span>
|
||
<a id="__codelineno-2-19" name="__codelineno-2-19" href="#__codelineno-2-19"></a> <span class="n">output</span> <span class="o">=</span> <span class="n">trained_model</span><span class="p">(</span><span class="n">sample_dataset</span><span class="p">[</span><span class="s2">"inputs"</span><span class="p">])</span>
|
||
<a id="__codelineno-2-20" name="__codelineno-2-20" href="#__codelineno-2-20"></a> <span class="k">assert</span> <span class="n">output</span><span class="o">.</span><span class="n">shape</span> <span class="o">==</span> <span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> <span class="c1"># batch_size x num_classes</span>
|
||
</code></pre></div>
|
||
<ul>
|
||
<li>夹具可以有<strong>作用域</strong>：<code>scope="function"</code>（默认，每次测试重新创建）、<code>scope="module"</code>（每个文件一次）、<code>scope="session"</code>（每次测试运行一次）。对于加载模型等昂贵设置，使用 <code>scope="session"</code>。</li>
|
||
</ul>
|
||
<h3 id="_4">参数化测试<a class="headerlink" href="#_4" title="Permanent link">¶</a></h3>
|
||
<ul>
|
||
<li>使用多个输入测试同一个函数，无需重复代码：</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-3-1" name="__codelineno-3-1" href="#__codelineno-3-1"></a><span class="nd">@pytest</span><span class="o">.</span><span class="n">mark</span><span class="o">.</span><span class="n">parametrize</span><span class="p">(</span><span class="s2">"input,expected"</span><span class="p">,</span> <span class="p">[</span>
|
||
<a id="__codelineno-3-2" name="__codelineno-3-2" href="#__codelineno-3-2"></a> <span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="mi">6</span><span class="p">),</span>
|
||
<a id="__codelineno-3-3" name="__codelineno-3-3" href="#__codelineno-3-3"></a> <span class="p">([],</span> <span class="mi">0</span><span class="p">),</span>
|
||
<a id="__codelineno-3-4" name="__codelineno-3-4" href="#__codelineno-3-4"></a> <span class="p">([</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="mi">0</span><span class="p">),</span>
|
||
<a id="__codelineno-3-5" name="__codelineno-3-5" href="#__codelineno-3-5"></a> <span class="p">([</span><span class="mi">1000000</span><span class="p">,</span> <span class="mi">1000000</span><span class="p">],</span> <span class="mi">2000000</span><span class="p">),</span>
|
||
<a id="__codelineno-3-6" name="__codelineno-3-6" href="#__codelineno-3-6"></a><span class="p">])</span>
|
||
<a id="__codelineno-3-7" name="__codelineno-3-7" href="#__codelineno-3-7"></a><span class="k">def</span><span class="w"> </span><span class="nf">test_sum</span><span class="p">(</span><span class="nb">input</span><span class="p">,</span> <span class="n">expected</span><span class="p">):</span>
|
||
<a id="__codelineno-3-8" name="__codelineno-3-8" href="#__codelineno-3-8"></a> <span class="k">assert</span> <span class="nb">sum</span><span class="p">(</span><span class="nb">input</span><span class="p">)</span> <span class="o">==</span> <span class="n">expected</span>
|
||
</code></pre></div>
|
||
<h2 id="mock">Mock 与补丁<a class="headerlink" href="#mock" title="Permanent link">¶</a></h2>
|
||
<ul>
|
||
<li><strong>Mock</strong> 在测试期间用假依赖替换真实依赖。这让你可以隔离测试函数，而无需数据库、API 或 GPU。</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-4-1" name="__codelineno-4-1" href="#__codelineno-4-1"></a><span class="kn">from</span><span class="w"> </span><span class="nn">unittest.mock</span><span class="w"> </span><span class="kn">import</span> <span class="n">patch</span><span class="p">,</span> <span class="n">MagicMock</span>
|
||
<a id="__codelineno-4-2" name="__codelineno-4-2" href="#__codelineno-4-2"></a>
|
||
<a id="__codelineno-4-3" name="__codelineno-4-3" href="#__codelineno-4-3"></a><span class="k">def</span><span class="w"> </span><span class="nf">test_training_logs_metrics</span><span class="p">():</span>
|
||
<a id="__codelineno-4-4" name="__codelineno-4-4" href="#__codelineno-4-4"></a> <span class="n">mock_logger</span> <span class="o">=</span> <span class="n">MagicMock</span><span class="p">()</span>
|
||
<a id="__codelineno-4-5" name="__codelineno-4-5" href="#__codelineno-4-5"></a>
|
||
<a id="__codelineno-4-6" name="__codelineno-4-6" href="#__codelineno-4-6"></a> <span class="k">with</span> <span class="n">patch</span><span class="p">(</span><span class="s2">"my_project.training.trainer.wandb"</span><span class="p">)</span> <span class="k">as</span> <span class="n">mock_wandb</span><span class="p">:</span>
|
||
<a id="__codelineno-4-7" name="__codelineno-4-7" href="#__codelineno-4-7"></a> <span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span><span class="n">logger</span><span class="o">=</span><span class="n">mock_logger</span><span class="p">)</span>
|
||
<a id="__codelineno-4-8" name="__codelineno-4-8" href="#__codelineno-4-8"></a> <span class="n">trainer</span><span class="o">.</span><span class="n">train_one_epoch</span><span class="p">()</span>
|
||
<a id="__codelineno-4-9" name="__codelineno-4-9" href="#__codelineno-4-9"></a>
|
||
<a id="__codelineno-4-10" name="__codelineno-4-10" href="#__codelineno-4-10"></a> <span class="c1"># 验证训练器记录了指标</span>
|
||
<a id="__codelineno-4-11" name="__codelineno-4-11" href="#__codelineno-4-11"></a> <span class="n">mock_logger</span><span class="o">.</span><span class="n">log</span><span class="o">.</span><span class="n">assert_called</span><span class="p">()</span>
|
||
<a id="__codelineno-4-12" name="__codelineno-4-12" href="#__codelineno-4-12"></a> <span class="c1"># 验证它记录了损失值</span>
|
||
<a id="__codelineno-4-13" name="__codelineno-4-13" href="#__codelineno-4-13"></a> <span class="n">call_args</span> <span class="o">=</span> <span class="n">mock_logger</span><span class="o">.</span><span class="n">log</span><span class="o">.</span><span class="n">call_args</span>
|
||
<a id="__codelineno-4-14" name="__codelineno-4-14" href="#__codelineno-4-14"></a> <span class="k">assert</span> <span class="s2">"loss"</span> <span class="ow">in</span> <span class="n">call_args</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
||
</code></pre></div>
|
||
<ul>
|
||
<li>
|
||
<p><strong>何时使用 Mock</strong>：外部服务（API、数据库、云存储）、昂贵操作（GPU 计算、大型文件 I/O）和非确定性行为（随机数生成器、时间戳）。</p>
|
||
</li>
|
||
<li>
|
||
<p><strong>何时不要 Mock</strong>：你自己的代码。如果你 Mock 了所有内容，你的测试验证的是 Mock 的行为符合预期，而不是你的代码能工作。在边界处进行 Mock，直接测试你的逻辑。</p>
|
||
</li>
|
||
</ul>
|
||
<h2 id="_5">测试机器学习代码<a class="headerlink" href="#_5" title="Permanent link">¶</a></h2>
|
||
<ul>
|
||
<li>机器学习代码有独特的测试挑战：输出是概率性的，训练很慢，而且"正确"是模糊的。</li>
|
||
</ul>
|
||
<h3 id="_6">确定性种子<a class="headerlink" href="#_6" title="Permanent link">¶</a></h3>
|
||
<ul>
|
||
<li>在所有地方设置随机种子，使测试可重现：</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-5-1" name="__codelineno-5-1" href="#__codelineno-5-1"></a><span class="kn">import</span><span class="w"> </span><span class="nn">random</span>
|
||
<a id="__codelineno-5-2" name="__codelineno-5-2" href="#__codelineno-5-2"></a><span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
|
||
<a id="__codelineno-5-3" name="__codelineno-5-3" href="#__codelineno-5-3"></a><span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
|
||
<a id="__codelineno-5-4" name="__codelineno-5-4" href="#__codelineno-5-4"></a>
|
||
<a id="__codelineno-5-5" name="__codelineno-5-5" href="#__codelineno-5-5"></a><span class="k">def</span><span class="w"> </span><span class="nf">set_seed</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="mi">42</span><span class="p">):</span>
|
||
<a id="__codelineno-5-6" name="__codelineno-5-6" href="#__codelineno-5-6"></a> <span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
|
||
<a id="__codelineno-5-7" name="__codelineno-5-7" href="#__codelineno-5-7"></a> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
|
||
<a id="__codelineno-5-8" name="__codelineno-5-8" href="#__codelineno-5-8"></a> <span class="n">torch</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
|
||
<a id="__codelineno-5-9" name="__codelineno-5-9" href="#__codelineno-5-9"></a> <span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">is_available</span><span class="p">():</span>
|
||
<a id="__codelineno-5-10" name="__codelineno-5-10" href="#__codelineno-5-10"></a> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">manual_seed_all</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span>
|
||
<a id="__codelineno-5-11" name="__codelineno-5-11" href="#__codelineno-5-11"></a> <span class="n">torch</span><span class="o">.</span><span class="n">backends</span><span class="o">.</span><span class="n">cudnn</span><span class="o">.</span><span class="n">deterministic</span> <span class="o">=</span> <span class="kc">True</span>
|
||
<a id="__codelineno-5-12" name="__codelineno-5-12" href="#__codelineno-5-12"></a> <span class="n">torch</span><span class="o">.</span><span class="n">backends</span><span class="o">.</span><span class="n">cudnn</span><span class="o">.</span><span class="n">benchmark</span> <span class="o">=</span> <span class="kc">False</span>
|
||
</code></pre></div>
|
||
<h3 id="_7">数值容差<a class="headerlink" href="#_7" title="Permanent link">¶</a></h3>
|
||
<ul>
|
||
<li>浮点数比较需要容差（第 13 章，IEEE 754）：</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-6-1" name="__codelineno-6-1" href="#__codelineno-6-1"></a><span class="c1"># 糟糕：由于浮点数问题，精确比较会失败</span>
|
||
<a id="__codelineno-6-2" name="__codelineno-6-2" href="#__codelineno-6-2"></a><span class="k">assert</span> <span class="n">model_output</span> <span class="o">==</span> <span class="mf">0.5</span>
|
||
<a id="__codelineno-6-3" name="__codelineno-6-3" href="#__codelineno-6-3"></a>
|
||
<a id="__codelineno-6-4" name="__codelineno-6-4" href="#__codelineno-6-4"></a><span class="c1"># 良好：近似比较</span>
|
||
<a id="__codelineno-6-5" name="__codelineno-6-5" href="#__codelineno-6-5"></a><span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
|
||
<a id="__codelineno-6-6" name="__codelineno-6-6" href="#__codelineno-6-6"></a><span class="k">assert</span> <span class="n">np</span><span class="o">.</span><span class="n">isclose</span><span class="p">(</span><span class="n">model_output</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="n">atol</span><span class="o">=</span><span class="mf">1e-5</span><span class="p">)</span>
|
||
<a id="__codelineno-6-7" name="__codelineno-6-7" href="#__codelineno-6-7"></a>
|
||
<a id="__codelineno-6-8" name="__codelineno-6-8" href="#__codelineno-6-8"></a><span class="c1"># 对于张量</span>
|
||
<a id="__codelineno-6-9" name="__codelineno-6-9" href="#__codelineno-6-9"></a><span class="k">assert</span> <span class="n">torch</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="n">output</span><span class="p">,</span> <span class="n">expected</span><span class="p">,</span> <span class="n">atol</span><span class="o">=</span><span class="mf">1e-4</span><span class="p">)</span>
|
||
</code></pre></div>
|
||
<h3 id="_8">机器学习中需要测试什么<a class="headerlink" href="#_8" title="Permanent link">¶</a></h3>
|
||
<ul>
|
||
<li><strong>形状测试</strong>：验证输出具有预期的维度。</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-7-1" name="__codelineno-7-1" href="#__codelineno-7-1"></a><span class="k">def</span><span class="w"> </span><span class="nf">test_model_output_shape</span><span class="p">():</span>
|
||
<a id="__codelineno-7-2" name="__codelineno-7-2" href="#__codelineno-7-2"></a> <span class="n">model</span> <span class="o">=</span> <span class="n">MyModel</span><span class="p">(</span><span class="n">d_model</span><span class="o">=</span><span class="mi">256</span><span class="p">,</span> <span class="n">n_classes</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
|
||
<a id="__codelineno-7-3" name="__codelineno-7-3" href="#__codelineno-7-3"></a> <span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">256</span><span class="p">)</span> <span class="c1"># batch=8, seq=32, dim=256</span>
|
||
<a id="__codelineno-7-4" name="__codelineno-7-4" href="#__codelineno-7-4"></a> <span class="n">output</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
|
||
<a id="__codelineno-7-5" name="__codelineno-7-5" href="#__codelineno-7-5"></a> <span class="k">assert</span> <span class="n">output</span><span class="o">.</span><span class="n">shape</span> <span class="o">==</span> <span class="p">(</span><span class="mi">8</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
|
||
</code></pre></div>
|
||
<ul>
|
||
<li><strong>梯度流</strong>：验证可训练参数具有非零梯度。</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-8-1" name="__codelineno-8-1" href="#__codelineno-8-1"></a><span class="k">def</span><span class="w"> </span><span class="nf">test_gradients_flow</span><span class="p">():</span>
|
||
<a id="__codelineno-8-2" name="__codelineno-8-2" href="#__codelineno-8-2"></a> <span class="n">model</span> <span class="o">=</span> <span class="n">MyModel</span><span class="p">()</span>
|
||
<a id="__codelineno-8-3" name="__codelineno-8-3" href="#__codelineno-8-3"></a> <span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">32</span><span class="p">)</span>
|
||
<a id="__codelineno-8-4" name="__codelineno-8-4" href="#__codelineno-8-4"></a> <span class="n">y</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="p">(</span><span class="mi">4</span><span class="p">,))</span>
|
||
<a id="__codelineno-8-5" name="__codelineno-8-5" href="#__codelineno-8-5"></a>
|
||
<a id="__codelineno-8-6" name="__codelineno-8-6" href="#__codelineno-8-6"></a> <span class="n">output</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
|
||
<a id="__codelineno-8-7" name="__codelineno-8-7" href="#__codelineno-8-7"></a> <span class="n">loss</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">cross_entropy</span><span class="p">(</span><span class="n">output</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
|
||
<a id="__codelineno-8-8" name="__codelineno-8-8" href="#__codelineno-8-8"></a> <span class="n">loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
|
||
<a id="__codelineno-8-9" name="__codelineno-8-9" href="#__codelineno-8-9"></a>
|
||
<a id="__codelineno-8-10" name="__codelineno-8-10" href="#__codelineno-8-10"></a> <span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">param</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">named_parameters</span><span class="p">():</span>
|
||
<a id="__codelineno-8-11" name="__codelineno-8-11" href="#__codelineno-8-11"></a> <span class="k">assert</span> <span class="n">param</span><span class="o">.</span><span class="n">grad</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">,</span> <span class="sa">f</span><span class="s2">"没有 </span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2"> 的梯度"</span>
|
||
<a id="__codelineno-8-12" name="__codelineno-8-12" href="#__codelineno-8-12"></a> <span class="k">assert</span> <span class="n">param</span><span class="o">.</span><span class="n">grad</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span> <span class="o">></span> <span class="mi">0</span><span class="p">,</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2"> 的梯度为零"</span>
|
||
</code></pre></div>
|
||
<ul>
|
||
<li><strong>在一个批次上过拟合</strong>：模型应该能够记忆单个批次。如果不能，说明某处存在根本性问题。</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-9-1" name="__codelineno-9-1" href="#__codelineno-9-1"></a><span class="k">def</span><span class="w"> </span><span class="nf">test_overfit_one_batch</span><span class="p">():</span>
|
||
<a id="__codelineno-9-2" name="__codelineno-9-2" href="#__codelineno-9-2"></a> <span class="n">model</span> <span class="o">=</span> <span class="n">MyModel</span><span class="p">()</span>
|
||
<a id="__codelineno-9-3" name="__codelineno-9-3" href="#__codelineno-9-3"></a> <span class="n">optimiser</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="o">=</span><span class="mf">1e-3</span><span class="p">)</span>
|
||
<a id="__codelineno-9-4" name="__codelineno-9-4" href="#__codelineno-9-4"></a> <span class="n">x</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">get_single_batch</span><span class="p">()</span>
|
||
<a id="__codelineno-9-5" name="__codelineno-9-5" href="#__codelineno-9-5"></a>
|
||
<a id="__codelineno-9-6" name="__codelineno-9-6" href="#__codelineno-9-6"></a> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">100</span><span class="p">):</span>
|
||
<a id="__codelineno-9-7" name="__codelineno-9-7" href="#__codelineno-9-7"></a> <span class="n">loss</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">cross_entropy</span><span class="p">(</span><span class="n">model</span><span class="p">(</span><span class="n">x</span><span class="p">),</span> <span class="n">y</span><span class="p">)</span>
|
||
<a id="__codelineno-9-8" name="__codelineno-9-8" href="#__codelineno-9-8"></a> <span class="n">loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
|
||
<a id="__codelineno-9-9" name="__codelineno-9-9" href="#__codelineno-9-9"></a> <span class="n">optimiser</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
|
||
<a id="__codelineno-9-10" name="__codelineno-9-10" href="#__codelineno-9-10"></a> <span class="n">optimiser</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
|
||
<a id="__codelineno-9-11" name="__codelineno-9-11" href="#__codelineno-9-11"></a>
|
||
<a id="__codelineno-9-12" name="__codelineno-9-12" href="#__codelineno-9-12"></a> <span class="k">assert</span> <span class="n">loss</span><span class="o">.</span><span class="n">item</span><span class="p">()</span> <span class="o"><</span> <span class="mf">0.01</span><span class="p">,</span> <span class="sa">f</span><span class="s2">"无法过拟合单个批次：loss=</span><span class="si">{</span><span class="n">loss</span><span class="o">.</span><span class="n">item</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span>
|
||
</code></pre></div>
|
||
<ul>
|
||
<li><strong>数据验证</strong>：验证数据加载产生有效输出。</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-10-1" name="__codelineno-10-1" href="#__codelineno-10-1"></a><span class="k">def</span><span class="w"> </span><span class="nf">test_dataset_basics</span><span class="p">():</span>
|
||
<a id="__codelineno-10-2" name="__codelineno-10-2" href="#__codelineno-10-2"></a> <span class="n">dataset</span> <span class="o">=</span> <span class="n">MyDataset</span><span class="p">(</span><span class="s2">"tests/fixtures/small_data.csv"</span><span class="p">)</span>
|
||
<a id="__codelineno-10-3" name="__codelineno-10-3" href="#__codelineno-10-3"></a> <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">dataset</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span>
|
||
<a id="__codelineno-10-4" name="__codelineno-10-4" href="#__codelineno-10-4"></a> <span class="n">x</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">dataset</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||
<a id="__codelineno-10-5" name="__codelineno-10-5" href="#__codelineno-10-5"></a> <span class="k">assert</span> <span class="n">x</span><span class="o">.</span><span class="n">shape</span> <span class="o">==</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">224</span><span class="p">,</span> <span class="mi">224</span><span class="p">)</span>
|
||
<a id="__codelineno-10-6" name="__codelineno-10-6" href="#__codelineno-10-6"></a> <span class="k">assert</span> <span class="mi">0</span> <span class="o"><=</span> <span class="n">y</span> <span class="o"><</span> <span class="mi">10</span>
|
||
<a id="__codelineno-10-7" name="__codelineno-10-7" href="#__codelineno-10-7"></a> <span class="k">assert</span> <span class="ow">not</span> <span class="n">torch</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">()</span>
|
||
<a id="__codelineno-10-8" name="__codelineno-10-8" href="#__codelineno-10-8"></a> <span class="k">assert</span> <span class="ow">not</span> <span class="n">torch</span><span class="o">.</span><span class="n">isinf</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">()</span>
|
||
</code></pre></div>
|
||
<ul>
|
||
<li><strong>确定性</strong>：相同输入 + 相同种子 → 相同输出。</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-11-1" name="__codelineno-11-1" href="#__codelineno-11-1"></a><span class="k">def</span><span class="w"> </span><span class="nf">test_determinism</span><span class="p">():</span>
|
||
<a id="__codelineno-11-2" name="__codelineno-11-2" href="#__codelineno-11-2"></a> <span class="n">set_seed</span><span class="p">(</span><span class="mi">42</span><span class="p">)</span>
|
||
<a id="__codelineno-11-3" name="__codelineno-11-3" href="#__codelineno-11-3"></a> <span class="n">output1</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="n">input_data</span><span class="p">)</span>
|
||
<a id="__codelineno-11-4" name="__codelineno-11-4" href="#__codelineno-11-4"></a> <span class="n">set_seed</span><span class="p">(</span><span class="mi">42</span><span class="p">)</span>
|
||
<a id="__codelineno-11-5" name="__codelineno-11-5" href="#__codelineno-11-5"></a> <span class="n">output2</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="n">input_data</span><span class="p">)</span>
|
||
<a id="__codelineno-11-6" name="__codelineno-11-6" href="#__codelineno-11-6"></a> <span class="k">assert</span> <span class="n">torch</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="n">output1</span><span class="p">,</span> <span class="n">output2</span><span class="p">)</span>
|
||
</code></pre></div>
|
||
<h2 id="cicd">CI/CD 管道<a class="headerlink" href="#cicd" title="Permanent link">¶</a></h2>
|
||
<ul>
|
||
<li>
|
||
<p><strong>持续集成（CI）</strong>：在每次提交或 PR 上自动运行测试。如果测试失败，PR 不能合并。这防止了损坏的代码到达 <code>main</code>。</p>
|
||
</li>
|
||
<li>
|
||
<p><strong>GitHub Actions</strong> 示例（<code>.github/workflows/ci.yml</code>）：</p>
|
||
</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-12-1" name="__codelineno-12-1" href="#__codelineno-12-1"></a><span class="nt">name</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">CI</span>
|
||
<a id="__codelineno-12-2" name="__codelineno-12-2" href="#__codelineno-12-2"></a><span class="nt">on</span><span class="p">:</span><span class="w"> </span><span class="p p-Indicator">[</span><span class="nv">push</span><span class="p p-Indicator">,</span><span class="w"> </span><span class="nv">pull_request</span><span class="p p-Indicator">]</span>
|
||
<a id="__codelineno-12-3" name="__codelineno-12-3" href="#__codelineno-12-3"></a>
|
||
<a id="__codelineno-12-4" name="__codelineno-12-4" href="#__codelineno-12-4"></a><span class="nt">jobs</span><span class="p">:</span>
|
||
<a id="__codelineno-12-5" name="__codelineno-12-5" href="#__codelineno-12-5"></a><span class="w"> </span><span class="nt">test</span><span class="p">:</span>
|
||
<a id="__codelineno-12-6" name="__codelineno-12-6" href="#__codelineno-12-6"></a><span class="w"> </span><span class="nt">runs-on</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">ubuntu-latest</span>
|
||
<a id="__codelineno-12-7" name="__codelineno-12-7" href="#__codelineno-12-7"></a><span class="w"> </span><span class="nt">steps</span><span class="p">:</span>
|
||
<a id="__codelineno-12-8" name="__codelineno-12-8" href="#__codelineno-12-8"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">uses</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">actions/checkout@v4</span>
|
||
<a id="__codelineno-12-9" name="__codelineno-12-9" href="#__codelineno-12-9"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">uses</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">actions/setup-python@v5</span>
|
||
<a id="__codelineno-12-10" name="__codelineno-12-10" href="#__codelineno-12-10"></a><span class="w"> </span><span class="nt">with</span><span class="p">:</span>
|
||
<a id="__codelineno-12-11" name="__codelineno-12-11" href="#__codelineno-12-11"></a><span class="w"> </span><span class="nt">python-version</span><span class="p">:</span><span class="w"> </span><span class="s">"3.11"</span>
|
||
<a id="__codelineno-12-12" name="__codelineno-12-12" href="#__codelineno-12-12"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">run</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">pip install -e ".[dev]"</span>
|
||
<a id="__codelineno-12-13" name="__codelineno-12-13" href="#__codelineno-12-13"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">run</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">ruff check src/</span>
|
||
<a id="__codelineno-12-14" name="__codelineno-12-14" href="#__codelineno-12-14"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">run</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">mypy src/</span>
|
||
<a id="__codelineno-12-15" name="__codelineno-12-15" href="#__codelineno-12-15"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">run</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">pytest tests/ -v --tb=short</span>
|
||
</code></pre></div>
|
||
<ul>
|
||
<li><strong>预提交钩子</strong>：在每次提交前（本地）运行检查，在它们到达 CI 之前捕获问题：</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-13-1" name="__codelineno-13-1" href="#__codelineno-13-1"></a><span class="c1"># .pre-commit-config.yaml</span>
|
||
<a id="__codelineno-13-2" name="__codelineno-13-2" href="#__codelineno-13-2"></a><span class="nt">repos</span><span class="p">:</span>
|
||
<a id="__codelineno-13-3" name="__codelineno-13-3" href="#__codelineno-13-3"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">repo</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">https://github.com/astral-sh/ruff-pre-commit</span>
|
||
<a id="__codelineno-13-4" name="__codelineno-13-4" href="#__codelineno-13-4"></a><span class="w"> </span><span class="nt">rev</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">v0.3.0</span>
|
||
<a id="__codelineno-13-5" name="__codelineno-13-5" href="#__codelineno-13-5"></a><span class="w"> </span><span class="nt">hooks</span><span class="p">:</span>
|
||
<a id="__codelineno-13-6" name="__codelineno-13-6" href="#__codelineno-13-6"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">id</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">ruff</span>
|
||
<a id="__codelineno-13-7" name="__codelineno-13-7" href="#__codelineno-13-7"></a><span class="w"> </span><span class="nt">args</span><span class="p">:</span><span class="w"> </span><span class="p p-Indicator">[</span><span class="nv">--fix</span><span class="p p-Indicator">]</span>
|
||
<a id="__codelineno-13-8" name="__codelineno-13-8" href="#__codelineno-13-8"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">id</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">ruff-format</span>
|
||
<a id="__codelineno-13-9" name="__codelineno-13-9" href="#__codelineno-13-9"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">repo</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">https://github.com/pre-commit/pre-commit-hooks</span>
|
||
<a id="__codelineno-13-10" name="__codelineno-13-10" href="#__codelineno-13-10"></a><span class="w"> </span><span class="nt">rev</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">v4.5.0</span>
|
||
<a id="__codelineno-13-11" name="__codelineno-13-11" href="#__codelineno-13-11"></a><span class="w"> </span><span class="nt">hooks</span><span class="p">:</span>
|
||
<a id="__codelineno-13-12" name="__codelineno-13-12" href="#__codelineno-13-12"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">id</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">trailing-whitespace</span>
|
||
<a id="__codelineno-13-13" name="__codelineno-13-13" href="#__codelineno-13-13"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">id</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">end-of-file-fixer</span>
|
||
<a id="__codelineno-13-14" name="__codelineno-13-14" href="#__codelineno-13-14"></a><span class="w"> </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="nt">id</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">check-yaml</span>
|
||
</code></pre></div>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-14-1" name="__codelineno-14-1" href="#__codelineno-14-1"></a>pip<span class="w"> </span>install<span class="w"> </span>pre-commit
|
||
<a id="__codelineno-14-2" name="__codelineno-14-2" href="#__codelineno-14-2"></a>pre-commit<span class="w"> </span>install<span class="w"> </span><span class="c1"># 现在每次 git 提交时都会运行钩子</span>
|
||
</code></pre></div>
|
||
<h2 id="_9">代码检查与格式化<a class="headerlink" href="#_9" title="Permanent link">¶</a></h2>
|
||
<ul>
|
||
<li>
|
||
<p><strong>代码检查</strong>无需运行代码即可捕获错误和风格问题。<strong>格式化</strong>自动强制执行一致的风格。</p>
|
||
</li>
|
||
<li>
|
||
<p><strong>Ruff</strong>：一个快速的 Python 代码检查器和格式化器（在一个工具中替代 flake8、isort 和 black）：</p>
|
||
</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-15-1" name="__codelineno-15-1" href="#__codelineno-15-1"></a>ruff<span class="w"> </span>check<span class="w"> </span>src/<span class="w"> </span><span class="c1"># 代码检查</span>
|
||
<a id="__codelineno-15-2" name="__codelineno-15-2" href="#__codelineno-15-2"></a>ruff<span class="w"> </span>check<span class="w"> </span>--fix<span class="w"> </span>src/<span class="w"> </span><span class="c1"># 代码检查并自动修复</span>
|
||
<a id="__codelineno-15-3" name="__codelineno-15-3" href="#__codelineno-15-3"></a>ruff<span class="w"> </span>format<span class="w"> </span>src/<span class="w"> </span><span class="c1"># 格式化</span>
|
||
</code></pre></div>
|
||
<ul>
|
||
<li><strong>mypy</strong>：Python 静态类型检查器。在运行时之前捕获类型错误：</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-16-1" name="__codelineno-16-1" href="#__codelineno-16-1"></a>mypy<span class="w"> </span>src/
|
||
<a id="__codelineno-16-2" name="__codelineno-16-2" href="#__codelineno-16-2"></a><span class="c1"># src/model.py:42: error: Argument 1 to "forward" has incompatible type "int"; expected "Tensor"</span>
|
||
</code></pre></div>
|
||
<ul>
|
||
<li>类型提示使代码自文档化并捕获错误：</li>
|
||
</ul>
|
||
<div class="highlight"><pre><span></span><code><a id="__codelineno-17-1" name="__codelineno-17-1" href="#__codelineno-17-1"></a><span class="k">def</span><span class="w"> </span><span class="nf">train</span><span class="p">(</span>
|
||
<a id="__codelineno-17-2" name="__codelineno-17-2" href="#__codelineno-17-2"></a> <span class="n">model</span><span class="p">:</span> <span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">,</span>
|
||
<a id="__codelineno-17-3" name="__codelineno-17-3" href="#__codelineno-17-3"></a> <span class="n">dataloader</span><span class="p">:</span> <span class="n">DataLoader</span><span class="p">,</span>
|
||
<a id="__codelineno-17-4" name="__codelineno-17-4" href="#__codelineno-17-4"></a> <span class="n">optimiser</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Optimizer</span><span class="p">,</span>
|
||
<a id="__codelineno-17-5" name="__codelineno-17-5" href="#__codelineno-17-5"></a> <span class="n">num_epochs</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
|
||
<a id="__codelineno-17-6" name="__codelineno-17-6" href="#__codelineno-17-6"></a><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span>
|
||
<a id="__codelineno-17-7" name="__codelineno-17-7" href="#__codelineno-17-7"></a><span class="w"> </span><span class="sd">"""训练模型并返回最终损失。"""</span>
|
||
<a id="__codelineno-17-8" name="__codelineno-17-8" href="#__codelineno-17-8"></a> <span class="o">...</span>
|
||
</code></pre></div>
|
||
<h2 id="_10">代码审查最佳实践<a class="headerlink" href="#_10" title="Permanent link">¶</a></h2>
|
||
<ul>
|
||
<li>
|
||
<p><strong>对于作者</strong>：</p>
|
||
<ul>
|
||
<li>在请求审查之前先自我审查你的差异。你会发现明显的问题。</li>
|
||
<li>保持 PR 小而专注。一个 PR 聚焦一个问题。</li>
|
||
<li>写清晰的描述：什么、为什么、如何测试。</li>
|
||
<li>回复每条评论（即使只是"已修改"）。</li>
|
||
</ul>
|
||
</li>
|
||
<li>
|
||
<p><strong>对于审查者</strong>：</p>
|
||
<ul>
|
||
<li>保持友善。批评代码，而不是人。"这里可以更清晰"而不是"这很令人困惑。"</li>
|
||
<li>区分阻塞性问题（错误、安全）和建议（风格、命名）。使用标签："nit:"、"suggestion:"、"blocking:"。</li>
|
||
<li>提问而不是发号施令。"如果这个列表为空会怎样？"比"处理空的情况"更有帮助。</li>
|
||
<li>及时批准。等待数天的 PR 会阻塞作者，并鼓励大型、批量的 PR（这些更难审查）。</li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
|
||
|
||
|
||
|
||
|
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|
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|
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|
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