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<section id="tensorarray">
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<h1>Tensorarray<a class="headerlink" href="#tensorarray" title="Link to this heading"></a></h1>
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<p>张量数组操作，支持从张量数组中读取指定索引的张量，或将张量写入到张量数组的指定索引位置。该算子不区分数据类型，适用于所有数据类型。</p>
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<p><strong>TensorArrayRead（读取操作）：</strong></p>
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<p>从张量数组中读取指定索引的张量，并将其数据复制到输出。</p>
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<div class="math notranslate nohighlight">
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\[\text{output} = \text{tensors}[\text{index}]\]</div>
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<p><strong>TensorArrayWrite（写入操作）：</strong></p>
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<p>将输入张量的数据复制到张量数组的指定索引位置。</p>
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<div class="math notranslate nohighlight">
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\[\text{tensors}[\text{index}] = \text{input}\]</div>
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<p>两个操作都会复制数据，复制大小为 <cite>size * type_size</cite> 字节。</p>
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<dl class="simple">
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<dt>输入（TensorArrayRead）：</dt><dd><ul class="simple">
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<li><p><strong>tensors</strong> - 张量数组（Tensor** 类型），包含多个张量。</p></li>
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<li><p><strong>index</strong> - 读取的索引（int 类型），指定从 <cite>tensors</cite> 数组中读取哪个张量。</p></li>
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<li><p><strong>core_mask</strong> - 核掩码（int），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（TensorArrayRead）：</dt><dd><ul class="simple">
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<li><p><strong>output</strong> - 输出张量（Tensor* 类型），包含复制后的数据。输出张量的 <cite>size</cite> 和 <cite>type_size</cite> 应与选中的输入张量相同。</p></li>
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</ul>
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</dd>
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<dt>输入（TensorArrayWrite）：</dt><dd><ul class="simple">
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<li><p><strong>input</strong> - 输入张量（Tensor* 类型），待写入的数据。</p></li>
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<li><p><strong>index</strong> - 写入的索引（int 类型），指定写入到 <cite>tensors</cite> 数组的哪个位置。</p></li>
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<li><p><strong>tensors</strong> - 张量数组（Tensor** 类型），目标数组。</p></li>
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<li><p><strong>core_mask</strong> - 核掩码（int），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（TensorArrayWrite）：</dt><dd><ul class="simple">
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<li><p><strong>tensors[index]</strong> - 张量数组指定位置的数据会被更新。</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>该算子不区分数据类型，适用于所有数据类型</p></li>
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<li><p>算子会复制数据，输入和输出张量数据独立</p></li>
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<li><p>调用前需要确保目标内存空间足够大（至少 <cite>size * type_size</cite> 字节）</p></li>
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<li><p>读取和写入时，涉及的张量的 <cite>size</cite> 和 <cite>type_size</cite> 应匹配</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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<p><strong>TensorArrayRead（读取操作）:</strong></p>
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<dl class="c function">
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<dt class="sig sig-object c" id="c.tensorarrayread_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">tensorarrayread_s</span></span></span><span class="sig-paren">(</span><span class="n"><span class="pre">Tensor</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">tensors</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="n"><span class="pre">Tensor</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">output</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.tensorarrayread_s" title="Link to this definition"></a><br /></dt>
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<dd></dd></dl>
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<p><strong>TensorArrayWrite（写入操作）:</strong></p>
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<dl class="c function">
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<dt class="sig sig-object c" id="c.tensorarraywrite_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">tensorarraywrite_s</span></span></span><span class="sig-paren">(</span><span class="n"><span class="pre">Tensor</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">input</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="n"><span class="pre">Tensor</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">tensors</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.tensorarraywrite_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（TensorArrayRead）：</strong></p>
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<div class="highlight-c notranslate"><div class="highlight"><pre><span></span><span class="linenos"> 1</span><span class="c1">//FT78NE示例</span>
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<span class="linenos"> 2</span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><stdio.h></span>
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<span class="linenos"> 3</span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><tensorarray.h></span>
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<span class="linenos"> 4</span>
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<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>
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<span class="linenos"> 6</span><span class="w"> </span><span class="c1">// 假设在DDR空间</span>
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<span class="linenos"> 7</span><span class="w"> </span><span class="n">Tensor</span><span class="w"> </span><span class="n">tensor0</span><span class="p">,</span><span class="w"> </span><span class="n">tensor1</span><span class="p">,</span><span class="w"> </span><span class="n">tensor2</span><span class="p">;</span>
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<span class="linenos"> 8</span><span class="w"> </span><span class="n">Tensor</span><span class="w"> </span><span class="n">output</span><span class="p">;</span>
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<span class="linenos"> 9</span>
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<span class="linenos">10</span><span class="w"> </span><span class="c1">// 初始化张量数组中的张量</span>
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||
<span class="linenos">11</span><span class="w"> </span><span class="n">tensor0</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span><span class="w"> </span><span class="c1">// float32</span>
|
||
<span class="linenos">12</span><span class="w"> </span><span class="n">tensor0</span><span class="p">.</span><span class="n">size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1000</span><span class="p">;</span>
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<span class="linenos">13</span><span class="w"> </span><span class="n">tensor0</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</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">14</span>
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<span class="linenos">15</span><span class="w"> </span><span class="n">tensor1</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span>
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<span class="linenos">16</span><span class="w"> </span><span class="n">tensor1</span><span class="p">.</span><span class="n">size</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">17</span><span class="w"> </span><span class="n">tensor1</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0xA1000000</span><span class="p">;</span>
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<span class="linenos">18</span>
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<span class="linenos">19</span><span class="w"> </span><span class="n">tensor2</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span>
|
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<span class="linenos">20</span><span class="w"> </span><span class="n">tensor2</span><span class="p">.</span><span class="n">size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1000</span><span class="p">;</span>
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<span class="linenos">21</span><span class="w"> </span><span class="n">tensor2</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0xA2000000</span><span class="p">;</span>
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<span class="linenos">22</span>
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<span class="linenos">23</span><span class="w"> </span><span class="c1">// 初始化输出张量</span>
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<span class="linenos">24</span><span class="w"> </span><span class="n">output</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span>
|
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<span class="linenos">25</span><span class="w"> </span><span class="n">output</span><span class="p">.</span><span class="n">size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1000</span><span class="p">;</span>
|
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<span class="linenos">26</span><span class="w"> </span><span class="n">output</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</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">// 需要预先分配足够的内存</span>
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<span class="linenos">27</span>
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<span class="linenos">28</span><span class="w"> </span><span class="c1">// 创建张量数组</span>
|
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<span class="linenos">29</span><span class="w"> </span><span class="n">Tensor</span><span class="o">*</span><span class="w"> </span><span class="n">tensors</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="o">&</span><span class="n">tensor0</span><span class="p">,</span><span class="w"> </span><span class="o">&</span><span class="n">tensor1</span><span class="p">,</span><span class="w"> </span><span class="o">&</span><span class="n">tensor2</span><span class="p">};</span>
|
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<span class="linenos">30</span>
|
||
<span class="linenos">31</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">// 读取 tensor1</span>
|
||
<span class="linenos">32</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">33</span>
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<span class="hll"><span class="linenos">34</span><span class="w"> </span><span class="n">tensorarrayread_s</span><span class="p">(</span><span class="n">tensors</span><span class="p">,</span><span class="w"> </span><span class="n">index</span><span class="p">,</span><span class="w"> </span><span class="o">&</span><span class="n">output</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">35</span>
|
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<span class="linenos">36</span><span class="w"> </span><span class="c1">// 此时 output.data 包含 tensor1.data 的副本</span>
|
||
<span class="linenos">37</span>
|
||
<span class="linenos">38</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">39</span><span class="p">}</span>
|
||
</pre></div>
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</div>
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<p><strong>C调用示例（TensorArrayWrite）：</strong></p>
|
||
<div class="highlight-c notranslate"><div class="highlight"><pre><span></span><span class="linenos"> 1</span><span class="c1">//FT78NE示例</span>
|
||
<span class="linenos"> 2</span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><stdio.h></span>
|
||
<span class="linenos"> 3</span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><tensorarray.h></span>
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<span class="linenos"> 4</span>
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<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>
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<span class="linenos"> 6</span><span class="w"> </span><span class="c1">// 假设在DDR空间</span>
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||
<span class="linenos"> 7</span><span class="w"> </span><span class="n">Tensor</span><span class="w"> </span><span class="n">input</span><span class="p">;</span>
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||
<span class="linenos"> 8</span><span class="w"> </span><span class="n">Tensor</span><span class="w"> </span><span class="n">tensor0</span><span class="p">,</span><span class="w"> </span><span class="n">tensor1</span><span class="p">,</span><span class="w"> </span><span class="n">tensor2</span><span class="p">;</span>
|
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<span class="linenos"> 9</span>
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||
<span class="linenos">10</span><span class="w"> </span><span class="c1">// 初始化输入张量</span>
|
||
<span class="linenos">11</span><span class="w"> </span><span class="n">input</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span><span class="w"> </span><span class="c1">// float32</span>
|
||
<span class="linenos">12</span><span class="w"> </span><span class="n">input</span><span class="p">.</span><span class="n">size</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="n">input</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0xA0000000</span><span class="p">;</span>
|
||
<span class="linenos">14</span>
|
||
<span class="linenos">15</span><span class="w"> </span><span class="c1">// 初始化张量数组中的张量（需要预先分配内存）</span>
|
||
<span class="linenos">16</span><span class="w"> </span><span class="n">tensor0</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span>
|
||
<span class="linenos">17</span><span class="w"> </span><span class="n">tensor0</span><span class="p">.</span><span class="n">size</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">18</span><span class="w"> </span><span class="n">tensor0</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0xB0000000</span><span class="p">;</span>
|
||
<span class="linenos">19</span>
|
||
<span class="linenos">20</span><span class="w"> </span><span class="n">tensor1</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span>
|
||
<span class="linenos">21</span><span class="w"> </span><span class="n">tensor1</span><span class="p">.</span><span class="n">size</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">22</span><span class="w"> </span><span class="n">tensor1</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0xB0100000</span><span class="p">;</span>
|
||
<span class="linenos">23</span>
|
||
<span class="linenos">24</span><span class="w"> </span><span class="n">tensor2</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span>
|
||
<span class="linenos">25</span><span class="w"> </span><span class="n">tensor2</span><span class="p">.</span><span class="n">size</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">26</span><span class="w"> </span><span class="n">tensor2</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0xB0200000</span><span class="p">;</span>
|
||
<span class="linenos">27</span>
|
||
<span class="linenos">28</span><span class="w"> </span><span class="c1">// 创建张量数组</span>
|
||
<span class="linenos">29</span><span class="w"> </span><span class="n">Tensor</span><span class="o">*</span><span class="w"> </span><span class="n">tensors</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="o">&</span><span class="n">tensor0</span><span class="p">,</span><span class="w"> </span><span class="o">&</span><span class="n">tensor1</span><span class="p">,</span><span class="w"> </span><span class="o">&</span><span class="n">tensor2</span><span class="p">};</span>
|
||
<span class="hll"><span class="linenos">30</span>
|
||
</span><span class="linenos">31</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">// 写入到 tensor1 的位置</span>
|
||
<span class="linenos">32</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">33</span>
|
||
<span class="linenos">34</span><span class="w"> </span><span class="n">tensorarraywrite_s</span><span class="p">(</span><span class="o">&</span><span class="n">input</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">tensors</span><span class="p">,</span><span class="w"> </span><span class="n">core_mask</span><span class="p">);</span>
|
||
<span class="linenos">35</span>
|
||
<span class="linenos">36</span><span class="w"> </span><span class="c1">// 此时 tensors[1]->data 包含 input.data 的副本</span>
|
||
<span class="linenos">37</span>
|
||
<span class="linenos">38</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">39</span><span class="p">}</span>
|
||
</pre></div>
|
||
</div>
|
||
<p><strong>私有存储版本:</strong></p>
|
||
<p><strong>TensorArrayRead（读取操作）:</strong></p>
|
||
<dl class="c function">
|
||
<dt class="sig sig-object c" id="c.tensorarrayread_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">tensorarrayread_p</span></span></span><span class="sig-paren">(</span><span class="n"><span class="pre">Tensor</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">tensors</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="n"><span class="pre">Tensor</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">output</span></span><span class="sig-paren">)</span><a class="headerlink" href="#c.tensorarrayread_p" title="Link to this definition"></a><br /></dt>
|
||
<dd></dd></dl>
|
||
|
||
<p><strong>TensorArrayWrite（写入操作）:</strong></p>
|
||
<dl class="c function">
|
||
<dt class="sig sig-object c" id="c.tensorarraywrite_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">tensorarraywrite_p</span></span></span><span class="sig-paren">(</span><span class="n"><span class="pre">Tensor</span></span><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">input</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="n"><span class="pre">Tensor</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">tensors</span></span><span class="sig-paren">)</span><a class="headerlink" href="#c.tensorarraywrite_p" title="Link to this definition"></a><br /></dt>
|
||
<dd></dd></dl>
|
||
|
||
<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="c1">//FT78NE示例</span>
|
||
<span class="linenos"> 2</span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><stdio.h></span>
|
||
<span class="linenos"> 3</span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><tensorarray.h></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="n">Tensor</span><span class="w"> </span><span class="n">tensor0</span><span class="p">,</span><span class="w"> </span><span class="n">tensor1</span><span class="p">,</span><span class="w"> </span><span class="n">tensor2</span><span class="p">;</span>
|
||
<span class="linenos"> 8</span><span class="w"> </span><span class="n">Tensor</span><span class="w"> </span><span class="n">output</span><span class="p">;</span>
|
||
<span class="linenos"> 9</span>
|
||
<span class="linenos">10</span><span class="w"> </span><span class="n">tensor0</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span><span class="w"> </span><span class="c1">// float32</span>
|
||
<span class="linenos">11</span><span class="w"> </span><span class="n">tensor0</span><span class="p">.</span><span class="n">size</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">12</span><span class="w"> </span><span class="n">tensor0</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0x10000000</span><span class="p">;</span>
|
||
<span class="linenos">13</span>
|
||
<span class="hll"><span class="linenos">14</span><span class="w"> </span><span class="n">tensor1</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span>
|
||
</span><span class="linenos">15</span><span class="w"> </span><span class="n">tensor1</span><span class="p">.</span><span class="n">size</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">16</span><span class="w"> </span><span class="n">tensor1</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0x10001000</span><span class="p">;</span>
|
||
<span class="linenos">17</span>
|
||
<span class="linenos">18</span><span class="w"> </span><span class="n">tensor2</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span>
|
||
<span class="linenos">19</span><span class="w"> </span><span class="n">tensor2</span><span class="p">.</span><span class="n">size</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">20</span><span class="w"> </span><span class="n">tensor2</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="mh">0x10002000</span><span class="p">;</span>
|
||
<span class="linenos">21</span>
|
||
<span class="linenos">22</span><span class="w"> </span><span class="n">output</span><span class="p">.</span><span class="n">type_size</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">4</span><span class="p">;</span>
|
||
<span class="linenos">23</span><span class="w"> </span><span class="n">output</span><span class="p">.</span><span class="n">size</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">24</span><span class="w"> </span><span class="n">output</span><span class="p">.</span><span class="n">data</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">void</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">// 需要预先分配足够的内存</span>
|
||
<span class="linenos">25</span>
|
||
<span class="linenos">26</span><span class="w"> </span><span class="n">Tensor</span><span class="o">*</span><span class="w"> </span><span class="n">tensors</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="o">&</span><span class="n">tensor0</span><span class="p">,</span><span class="w"> </span><span class="o">&</span><span class="n">tensor1</span><span class="p">,</span><span class="w"> </span><span class="o">&</span><span class="n">tensor2</span><span class="p">};</span>
|
||
<span class="linenos">27</span>
|
||
<span class="linenos">28</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">0</span><span class="p">;</span><span class="w"> </span><span class="c1">// 读取 tensor0</span>
|
||
<span class="linenos">29</span>
|
||
<span class="linenos">30</span><span class="w"> </span><span class="n">tensorarrayread_p</span><span class="p">(</span><span class="n">tensors</span><span class="p">,</span><span class="w"> </span><span class="n">index</span><span class="p">,</span><span class="w"> </span><span class="o">&</span><span class="n">output</span><span class="p">);</span>
|
||
<span class="linenos">31</span>
|
||
<span class="linenos">32</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">33</span><span class="p">}</span>
|
||
</pre></div>
|
||
</div>
|
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