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<section id="smoothl1lossgrad">
<h1>Smoothl1lossgrad<a class="headerlink" href="#smoothl1lossgrad" title="Link to this heading"></a></h1>
<p>计算 Smooth L1 Loss 操作的梯度。该算子是 Smooth L1 Loss 算子的反向传播（backward pass）部分。</p>
<p>Smooth L1 Loss 是 L1 Loss 和 L2 Loss 的平滑组合，在损失值较小时使用 L2 Loss，在损失值较大时使用 L1 Loss，以减少异常值的影响。</p>
<div class="math notranslate nohighlight">
\[\text{diff}_i = \text{x1}_i - \text{x2}_i\]</div>
<div class="math notranslate nohighlight">
\[\begin{split}\text{dx1}_i = \begin{cases}
\text{dy}_i, &amp; \text{if } \text{diff}_i &gt; \beta \\
-\text{dy}_i, &amp; \text{if } \text{diff}_i &lt; -\beta \\
\frac{\text{diff}_i}{\beta} \times \text{dy}_i, &amp; \text{if } -\beta \leq \text{diff}_i \leq \beta
\end{cases}\end{split}\]</div>
<p>其中 <cite>x1</cite> 是预测值（predict），<cite>x2</cite> 是目标值（target），<cite>dy</cite> 是来自后一层的上游梯度，<cite>dx1</cite> 是对预测值 <cite>x1</cite> 的梯度。<cite>beta</cite> 是平滑参数，控制从 L2 Loss 到 L1 Loss 的过渡点。</p>
<dl class="simple">
<dt>输入：</dt><dd><ul class="simple">
<li><p><strong>dy</strong> - 来自后一层的上游梯度数据地址。</p></li>
<li><p><strong>x1</strong> - 前向传播时的预测值数据地址。</p></li>
<li><p><strong>x2</strong> - 前向传播时的目标值数据地址。</p></li>
<li><p><strong>length</strong> - 计算长度。</p></li>
<li><p><strong>beta</strong> - 平滑参数，控制从 L2 Loss 到 L1 Loss 的过渡点。通常取值范围为 0.1 到 1.0。</p></li>
<li><p><strong>core_mask</strong> - 核掩码（仅共享存储版本需要）。</p></li>
</ul>
</dd>
<dt>输出：</dt><dd><ul class="simple">
<li><p><strong>dx1</strong> - 计算出的对预测值 <cite>x1</cite> 的梯度数据地址。</p></li>
</ul>
</dd>
<dt>支持平台：</dt><dd><p><code class="docutils literal notranslate"><span class="pre">FT78NE</span></code>
<code class="docutils literal notranslate"><span class="pre">MT7004</span></code></p>
</dd>
</dl>
<div class="admonition note">
<p class="admonition-title">备注</p>
<ul class="simple">
<li><p>FT78NE 支持fp32</p></li>
<li><p>MT7004 支持fp16, fp32</p></li>
</ul>
</div>
<p><strong>共享存储版本:</strong></p>
<dl class="c function">
<dt class="sig sig-object c" id="c.fp_smoothl1lossgrad_s">
<span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="sig-name descname"><span class="n"><span class="pre">fp_smoothl1lossgrad_s</span></span></span><span class="sig-paren">(</span><span class="kt"><span class="pre">float</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">dy</span></span>, <span class="kt"><span class="pre">float</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">dx1</span></span>, <span class="kt"><span class="pre">float</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">x1</span></span>, <span class="kt"><span class="pre">float</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">x2</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="n"><span class="pre">length</span></span>, <span class="kt"><span class="pre">float</span></span><span class="w"> </span><span class="n"><span class="pre">beta</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="n"><span class="pre">core_mask</span></span><span class="sig-paren">)</span><a class="headerlink" href="#c.fp_smoothl1lossgrad_s" title="Link to this definition"></a><br /></dt>
<dd></dd></dl>
<dl class="c function">
<dt class="sig sig-object c" id="c.hp_smoothl1lossgrad_s">
<span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="sig-name descname"><span class="n"><span class="pre">hp_smoothl1lossgrad_s</span></span></span><span class="sig-paren">(</span><span class="n"><span class="pre">half</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">dy</span></span>, <span class="n"><span class="pre">half</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">dx1</span></span>, <span class="n"><span class="pre">half</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">x1</span></span>, <span class="n"><span class="pre">half</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">x2</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="n"><span class="pre">length</span></span>, <span class="n"><span class="pre">half</span></span><span class="w"> </span><span class="n"><span class="pre">beta</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="n"><span class="pre">core_mask</span></span><span class="sig-paren">)</span><a class="headerlink" href="#c.hp_smoothl1lossgrad_s" title="Link to this definition"></a><br /></dt>
<dd></dd></dl>
<p><strong>C调用示例：</strong></p>
<div class="highlight-c notranslate"><div class="highlight"><pre><span></span><span class="linenos"> 1</span><span class="c1">//MT7004示例</span>
<span class="linenos"> 2</span><span class="cp">#include</span><span class="w"> </span><span class="cpf">&lt;stdio.h&gt;</span>
<span class="linenos"> 3</span><span class="cp">#include</span><span class="w"> </span><span class="cpf">&lt;smoothl1lossgrad.h&gt;</span>
<span class="linenos"> 4</span>
<span class="linenos"> 5</span><span class="kt">int</span><span class="w"> </span><span class="nf">main</span><span class="p">(</span><span class="kt">int</span><span class="w"> </span><span class="n">argc</span><span class="p">,</span><span class="w"> </span><span class="kt">char</span><span class="o">*</span><span class="w"> </span><span class="n">argv</span><span class="p">[])</span><span class="w"> </span><span class="p">{</span>
<span class="linenos"> 6</span><span class="w"> </span><span class="c1">// 假设在DDR空间</span>
<span class="linenos"> 7</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">dy</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0xA0000000</span><span class="p">;</span><span class="w"> </span><span class="c1">// 上游梯度</span>
<span class="linenos"> 8</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">x1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0xA1000000</span><span class="p">;</span><span class="w"> </span><span class="c1">// 预测值</span>
<span class="linenos"> 9</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">x2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0xA2000000</span><span class="p">;</span><span class="w"> </span><span class="c1">// 目标值</span>
<span class="linenos">10</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">dx1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0xB0000000</span><span class="p">;</span><span class="w"> </span><span class="c1">// 输出梯度（对 x1 的梯度）</span>
<span class="linenos">11</span>
<span class="linenos">12</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">length</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1000</span><span class="p">;</span>
<span class="linenos">13</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="n">beta</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">1.0f</span><span class="p">;</span><span class="w"> </span><span class="c1">// 平滑参数</span>
<span class="linenos">14</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">core_mask</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mh">0xff</span><span class="p">;</span>
<span class="linenos">15</span>
<span class="hll"><span class="linenos">16</span><span class="w"> </span><span class="n">fp_smoothl1lossgrad_s</span><span class="p">(</span><span class="n">dy</span><span class="p">,</span><span class="w"> </span><span class="n">dx1</span><span class="p">,</span><span class="w"> </span><span class="n">x1</span><span class="p">,</span><span class="w"> </span><span class="n">x2</span><span class="p">,</span><span class="w"> </span><span class="n">length</span><span class="p">,</span><span class="w"> </span><span class="n">beta</span><span class="p">,</span><span class="w"> </span><span class="n">core_mask</span><span class="p">);</span>
</span><span class="linenos">17</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="mi">0</span><span class="p">;</span>
<span class="linenos">18</span><span class="p">}</span>
</pre></div>
</div>
<p><strong>私有存储版本:</strong></p>
<dl class="c function">
<dt class="sig sig-object c" id="c.fp_smoothl1lossgrad_p">
<span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="sig-name descname"><span class="n"><span class="pre">fp_smoothl1lossgrad_p</span></span></span><span class="sig-paren">(</span><span class="kt"><span class="pre">float</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">dy</span></span>, <span class="kt"><span class="pre">float</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">dx1</span></span>, <span class="kt"><span class="pre">float</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">x1</span></span>, <span class="kt"><span class="pre">float</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">x2</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="n"><span class="pre">length</span></span>, <span class="kt"><span class="pre">float</span></span><span class="w"> </span><span class="n"><span class="pre">beta</span></span><span class="sig-paren">)</span><a class="headerlink" href="#c.fp_smoothl1lossgrad_p" title="Link to this definition"></a><br /></dt>
<dd></dd></dl>
<dl class="c function">
<dt class="sig sig-object c" id="c.hp_smoothl1lossgrad_p">
<span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="sig-name descname"><span class="n"><span class="pre">hp_smoothl1lossgrad_p</span></span></span><span class="sig-paren">(</span><span class="n"><span class="pre">half</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">dy</span></span>, <span class="n"><span class="pre">half</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">dx1</span></span>, <span class="n"><span class="pre">half</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">x1</span></span>, <span class="n"><span class="pre">half</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">x2</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="n"><span class="pre">length</span></span>, <span class="n"><span class="pre">half</span></span><span class="w"> </span><span class="n"><span class="pre">beta</span></span><span class="sig-paren">)</span><a class="headerlink" href="#c.hp_smoothl1lossgrad_p" title="Link to this definition"></a><br /></dt>
<dd></dd></dl>
<p><strong>C调用示例：</strong></p>
<div class="highlight-c notranslate"><div class="highlight"><pre><span></span><span class="linenos"> 1</span><span class="c1">//MT7004示例</span>
<span class="linenos"> 2</span><span class="cp">#include</span><span class="w"> </span><span class="cpf">&lt;stdio.h&gt;</span>
<span class="linenos"> 3</span><span class="cp">#include</span><span class="w"> </span><span class="cpf">&lt;smoothl1lossgrad.h&gt;</span>
<span class="linenos"> 4</span>
<span class="linenos"> 5</span><span class="kt">int</span><span class="w"> </span><span class="nf">main</span><span class="p">(</span><span class="kt">int</span><span class="w"> </span><span class="n">argc</span><span class="p">,</span><span class="w"> </span><span class="kt">char</span><span class="o">*</span><span class="w"> </span><span class="n">argv</span><span class="p">[])</span><span class="w"> </span><span class="p">{</span>
<span class="linenos"> 6</span><span class="w"> </span><span class="c1">// 假设在L2空间</span>
<span class="linenos"> 7</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">dy</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0x10000000</span><span class="p">;</span><span class="w"> </span><span class="c1">// 上游梯度</span>
<span class="linenos"> 8</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">x1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0x10001000</span><span class="p">;</span><span class="w"> </span><span class="c1">// 预测值</span>
<span class="linenos"> 9</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">x2</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0x10002000</span><span class="p">;</span><span class="w"> </span><span class="c1">// 目标值</span>
<span class="linenos">10</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">dx1</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0x10003000</span><span class="p">;</span><span class="w"> </span><span class="c1">// 输出梯度（对 x1 的梯度）</span>
<span class="linenos">11</span>
<span class="linenos">12</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">length</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1000</span><span class="p">;</span>
<span class="linenos">13</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="n">beta</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mf">1.0f</span><span class="p">;</span><span class="w"> </span><span class="c1">// 平滑参数</span>
<span class="linenos">14</span>
<span class="hll"><span class="linenos">15</span><span class="w"> </span><span class="n">fp_smoothl1lossgrad_p</span><span class="p">(</span><span class="n">dy</span><span class="p">,</span><span class="w"> </span><span class="n">dx1</span><span class="p">,</span><span class="w"> </span><span class="n">x1</span><span class="p">,</span><span class="w"> </span><span class="n">x2</span><span class="p">,</span><span class="w"> </span><span class="n">length</span><span class="p">,</span><span class="w"> </span><span class="n">beta</span><span class="p">);</span>
</span><span class="linenos">16</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="mi">0</span><span class="p">;</span>
<span class="linenos">17</span><span class="p">}</span>
</pre></div>
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