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<a href="../../_sources/functionlib/dsplib/tensorlistsetitem.rst.txt" rel="nofollow"> 查看页面源码</a>
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<section id="tensorlistsetitem">
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<h1>Tensorlistsetitem<a class="headerlink" href="#tensorlistsetitem" title="Link to this heading"></a></h1>
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<p>将输入的张量（item）替换到张量列表（TensorList）中指定索引位置。该算子创建一个新的张量列表，其中在指定索引位置的张量被替换为输入的新张量，而其他位置的张量保持不变。</p>
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<p>该算子不区分具体的数据类型，通过copy_size参数指定每个张量的数据量大小。</p>
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<dl class="simple">
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<dt>输入：</dt><dd><ul class="simple">
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<li><p><strong>in_data</strong> - 输入张量列表指针（void**类型），指向原始张量列表中的各个张量数据。</p></li>
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<li><p><strong>in_item</strong> - 输入张量指针（void*类型），表示要替换到张量列表中的新张量数据。</p></li>
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<li><p><strong>index</strong> - 要替换的张量在列表中的索引位置（int类型）。</p></li>
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<li><p><strong>tensorlist_size</strong> - 张量列表中包含的张量个数（int类型）。</p></li>
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<li><p><strong>copy_size</strong> - 每个张量的数据量大小数组（int*类型），以字节为单位，表示每个张量需要复制的字节数。</p></li>
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<li><p><strong>core_mask</strong> - 核掩码（int类型），仅共享存储版本需要。</p></li>
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</ul>
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</dd>
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<dt>输出：</dt><dd><ul class="simple">
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<li><p><strong>out_data</strong> - 输出张量列表指针（void**类型），存储替换操作后的张量列表，其中index位置的张量被替换为in_item。</p></li>
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</ul>
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</dd>
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<dt>支持平台：</dt><dd><p><code class="docutils literal notranslate"><span class="pre">FT78NE</span></code>
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<code class="docutils literal notranslate"><span class="pre">MT7004</span></code></p>
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</dd>
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</dl>
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<div class="admonition note">
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<p class="admonition-title">备注</p>
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<ul class="simple">
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<li><p>该算子不区分具体的数据类型，通过copy_size参数控制复制的字节数</p></li>
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<li><p>调用前需要确保out_data指向的内存空间足够大，能够存储所有张量数据</p></li>
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<li><p>索引index必须在有效范围内（0 <= index < tensorlist_size）</p></li>
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<li><p>算子会复制所有张量数据，输出张量列表与输入张量列表数据独立</p></li>
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</ul>
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</div>
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<p><strong>共享存储版本：</strong></p>
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<dl class="c function">
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<dt class="sig sig-object c" id="c.tensorlistsetitem_s">
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<span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="sig-name descname"><span class="n"><span class="pre">tensorlistsetitem_s</span></span></span><span class="sig-paren">(</span><span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">in_data</span></span>, <span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">in_item</span></span>, <span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">out_data</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="n"><span class="pre">index</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="n"><span class="pre">tensorlist_size</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">copy_size</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.tensorlistsetitem_s" title="Link to this definition"></a><br /></dt>
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<dd></dd></dl>
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<p><strong>C调用示例（共享存储版本）：</strong></p>
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<div class="highlight-c notranslate"><div class="highlight"><pre><span></span><span class="linenos"> 1</span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><stdio.h></span>
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<span class="linenos"> 2</span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><tensorlistsetitem.h></span>
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<span class="linenos"> 3</span>
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<span class="linenos"> 4</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>
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<span class="linenos"> 5</span><span class="w"> </span><span class="c1">// 假设在DDR空间</span>
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<span class="linenos"> 6</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">tensorlist_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">3</span><span class="p">;</span><span class="w"> </span><span class="c1">// 张量列表包含3个张量</span>
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<span class="linenos"> 7</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">index</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1</span><span class="p">;</span><span class="w"> </span><span class="c1">// 替换索引为1的张量</span>
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<span class="linenos"> 8</span>
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<span class="linenos"> 9</span><span class="w"> </span><span class="c1">// 输入张量列表</span>
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<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">in_tensor0</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>
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<span class="linenos">11</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">in_tensor1</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">0xA0010000</span><span class="p">;</span>
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<span class="linenos">12</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">in_tensor2</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">0xA0020000</span><span class="p">;</span>
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<span class="linenos">13</span><span class="w"> </span><span class="kt">void</span><span class="o">*</span><span class="w"> </span><span class="n">in_data</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="n">in_tensor0</span><span class="p">,</span><span class="w"> </span><span class="n">in_tensor1</span><span class="p">,</span><span class="w"> </span><span class="n">in_tensor2</span><span class="p">};</span>
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<span class="linenos">14</span>
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<span class="linenos">15</span><span class="w"> </span><span class="c1">// 输入item</span>
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<span class="linenos">16</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">in_item</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">0xA0030000</span><span class="p">;</span>
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<span class="linenos">17</span>
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<span class="linenos">18</span><span class="w"> </span><span class="c1">// 输出张量列表</span>
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<span class="linenos">19</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">out_tensor0</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>
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<span class="linenos">20</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">out_tensor1</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">0xB0010000</span><span class="p">;</span>
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<span class="linenos">21</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">out_tensor2</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">0xB0020000</span><span class="p">;</span>
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<span class="linenos">22</span><span class="w"> </span><span class="kt">void</span><span class="o">*</span><span class="w"> </span><span class="n">out_data</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="n">out_tensor0</span><span class="p">,</span><span class="w"> </span><span class="n">out_tensor1</span><span class="p">,</span><span class="w"> </span><span class="n">out_tensor2</span><span class="p">};</span>
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<span class="linenos">23</span>
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<span class="linenos">24</span><span class="w"> </span><span class="c1">// 每个张量的数据量大小</span>
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<span class="linenos">25</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">copy_size</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="mi">40</span><span class="p">,</span><span class="w"> </span><span class="mi">40</span><span class="p">,</span><span class="w"> </span><span class="mi">40</span><span class="p">};</span>
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<span class="linenos">26</span>
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<span class="linenos">27</span><span class="w"> </span><span class="c1">// 核掩码</span>
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<span class="linenos">28</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>
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<span class="linenos">29</span>
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<span class="linenos">30</span><span class="w"> </span><span class="c1">// 调用共享存储版本的函数</span>
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<span class="hll"><span class="linenos">31</span><span class="w"> </span><span class="n">tensorlistsetitem_s</span><span class="p">(</span><span class="n">in_data</span><span class="p">,</span><span class="w"> </span><span class="n">in_item</span><span class="p">,</span><span class="w"> </span><span class="n">out_data</span><span class="p">,</span><span class="w"> </span><span class="n">index</span><span class="p">,</span><span class="w"> </span><span class="n">tensorlist_size</span><span class="p">,</span><span class="w"> </span><span class="n">copy_size</span><span class="p">,</span><span class="w"> </span><span class="n">core_mask</span><span class="p">);</span>
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</span><span class="linenos">32</span>
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<span class="linenos">33</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="mi">0</span><span class="p">;</span>
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<span class="linenos">34</span><span class="p">}</span>
|
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</pre></div>
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</div>
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<p><strong>私有存储版本：</strong></p>
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<dl class="c function">
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<dt class="sig sig-object c" id="c.tensorlistsetitem_p">
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<span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="sig-name descname"><span class="n"><span class="pre">tensorlistsetitem_p</span></span></span><span class="sig-paren">(</span><span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">in_data</span></span>, <span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">in_item</span></span>, <span class="kt"><span class="pre">void</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">out_data</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="n"><span class="pre">index</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="n"><span class="pre">tensorlist_size</span></span>, <span class="kt"><span class="pre">int</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">copy_size</span></span><span class="sig-paren">)</span><a class="headerlink" href="#c.tensorlistsetitem_p" title="Link to this definition"></a><br /></dt>
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<dd></dd></dl>
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<p><strong>C调用示例（私有存储版本）：</strong></p>
|
||
<div class="highlight-c notranslate"><div class="highlight"><pre><span></span><span class="linenos"> 1</span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><stdio.h></span>
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<span class="linenos"> 2</span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><tensorlistsetitem.h></span>
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<span class="linenos"> 3</span>
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<span class="linenos"> 4</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>
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<span class="linenos"> 5</span><span class="w"> </span><span class="c1">// 假设在L2空间</span>
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<span class="linenos"> 6</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">tensorlist_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">3</span><span class="p">;</span><span class="w"> </span><span class="c1">// 张量列表包含3个张量</span>
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<span class="linenos"> 7</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">index</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1</span><span class="p">;</span><span class="w"> </span><span class="c1">// 替换索引为1的张量</span>
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<span class="linenos"> 8</span>
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<span class="linenos"> 9</span><span class="w"> </span><span class="c1">// 输入张量列表（假设已初始化）</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">in_tensor0</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">// 第一个张量</span>
|
||
<span class="linenos">11</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">in_tensor1</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">// 第二个张量（将被替换）</span>
|
||
<span class="linenos">12</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">in_tensor2</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">// 第三个张量</span>
|
||
<span class="linenos">13</span><span class="w"> </span><span class="kt">void</span><span class="o">*</span><span class="w"> </span><span class="n">in_data</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="n">in_tensor0</span><span class="p">,</span><span class="w"> </span><span class="n">in_tensor1</span><span class="p">,</span><span class="w"> </span><span class="n">in_tensor2</span><span class="p">};</span>
|
||
<span class="linenos">14</span>
|
||
<span class="linenos">15</span><span class="w"> </span><span class="c1">// 输入item（新张量数据）</span>
|
||
<span class="linenos">16</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">in_item</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="linenos">17</span>
|
||
<span class="linenos">18</span><span class="w"> </span><span class="c1">// 输出张量列表（需要预先分配内存）</span>
|
||
<span class="linenos">19</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">out_tensor0</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">0x10004000</span><span class="p">;</span>
|
||
<span class="linenos">20</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">out_tensor1</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">0x10005000</span><span class="p">;</span>
|
||
<span class="linenos">21</span><span class="w"> </span><span class="kt">float</span><span class="w"> </span><span class="o">*</span><span class="n">out_tensor2</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">0x10006000</span><span class="p">;</span>
|
||
<span class="linenos">22</span><span class="w"> </span><span class="kt">void</span><span class="o">*</span><span class="w"> </span><span class="n">out_data</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="n">out_tensor0</span><span class="p">,</span><span class="w"> </span><span class="n">out_tensor1</span><span class="p">,</span><span class="w"> </span><span class="n">out_tensor2</span><span class="p">};</span>
|
||
<span class="linenos">23</span>
|
||
<span class="linenos">24</span><span class="w"> </span><span class="c1">// 每个张量的数据量大小（假设每个张量有10个float元素，每个float 4字节）</span>
|
||
<span class="linenos">25</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">copy_size</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span><span class="mi">40</span><span class="p">,</span><span class="w"> </span><span class="mi">40</span><span class="p">,</span><span class="w"> </span><span class="mi">40</span><span class="p">};</span><span class="w"> </span><span class="c1">// 40字节 = 10 * 4</span>
|
||
<span class="linenos">26</span>
|
||
<span class="linenos">27</span><span class="w"> </span><span class="c1">// 调用私有存储版本的函数</span>
|
||
<span class="hll"><span class="linenos">28</span><span class="w"> </span><span class="n">tensorlistsetitem_p</span><span class="p">(</span><span class="n">in_data</span><span class="p">,</span><span class="w"> </span><span class="n">in_item</span><span class="p">,</span><span class="w"> </span><span class="n">out_data</span><span class="p">,</span><span class="w"> </span><span class="n">index</span><span class="p">,</span><span class="w"> </span><span class="n">tensorlist_size</span><span class="p">,</span><span class="w"> </span><span class="n">copy_size</span><span class="p">);</span>
|
||
</span><span class="linenos">29</span>
|
||
<span class="linenos">30</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">31</span><span class="p">}</span>
|
||
</pre></div>
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