{"componentChunkName":"component---src-templates-acg-portal-new-template-tsx","path":"/Dmsyclnil","result":{"data":{"markdownRemark":{"html":"<h3 id=\"描述\"><a href=\"#%E6%8F%8F%E8%BF%B0\" aria-label=\"描述 permalink\" class=\"anchor\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" version=\"1.1\" viewBox=\"0 0 16 16\" width=\"16\"><path fill-rule=\"evenodd\" d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"></path></svg></a>描述</h3>\n<p>获取指定资源池的队列列表</p>\n<ul>\n<li>支持指定关键字查询</li>\n<li>支持分页</li>\n</ul>\n<h3 id=\"请求结构\"><a href=\"#%E8%AF%B7%E6%B1%82%E7%BB%93%E6%9E%84\" aria-label=\"请求结构 permalink\" class=\"anchor\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" version=\"1.1\" viewBox=\"0 0 16 16\" width=\"16\"><path fill-rule=\"evenodd\" d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"></path></svg></a>请求结构</h3>\n\n    <div class=\"code-block-wrapper\">\n        <div class=\"code-block\">\n            <div class=\"code-block-header\">\n                <span class=\"code-block-name\">Plain Text</span>\n                <button class=\"code-copy-btn\" data-tooltip-text=\"\">\n                    <svg xmlns=\"http://www.w3.org/2000/svg\" width=\"16\" height=\"16\" viewBox=\"0 0 16 16\" fill=\"none\"> <path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M5.57894 3.45614C5.57894 3.38832 5.63392 3.33333 5.70175 3.33333H12.5439C12.6117 3.33333 12.6667 3.38832 12.6667 3.45614V10.2982C12.6667 10.3661 12.6117 10.4211 12.5439 10.4211H11.7544V5.70175C11.7544 4.89754 11.1025 4.24561 10.2982 4.24561H5.57894V3.45614ZM4.24561 4.24561V3.45614C4.24561 2.65194 4.89754 2 5.70175 2H12.5439C13.3481 2 14 2.65194 14 3.45614V10.2982C14 11.1025 13.3481 11.7544 12.5439 11.7544H11.7544V12.5439C11.7544 13.3481 11.1025 14 10.2982 14H3.45614C2.65194 14 2 13.3481 2 12.5439V5.70175C2 4.89754 2.65194 4.24561 3.45614 4.24561H4.24561ZM3.33333 5.70175C3.33333 5.63392 3.38832 5.57894 3.45614 5.57894H10.2982C10.3661 5.57894 10.4211 5.63392 10.4211 5.70175V12.5439C10.4211 12.6117 10.3661 12.6667 10.2982 12.6667H3.45614C3.38832 12.6667 3.33333 12.6117 3.33333 12.5439V5.70175Z\" fill=\"currentColor\"></path> </svg>\n                    复制\n                </button>\n            </div>\n            <div class=\"code-block-content\">\n                <pre class=\"language-text\"><code><span class=\"line-number\">1</span>GET ?action=DescribeQueues&amp;resourcePoolId=xxxx\n<span class=\"line-number\">2</span>Host:aihc.bj.baidubce.com\n<span class=\"line-number\">3</span>Authorization:authorization string\n<span class=\"line-number\">4</span>ContentType: application/json\n<span class=\"line-number\">5</span>version: v2    </code></pre>\n            </div>\n        </div>\n    </div>\n  \n<h3 id=\"请求头域\"><a href=\"#%E8%AF%B7%E6%B1%82%E5%A4%B4%E5%9F%9F\" aria-label=\"请求头域 permalink\" class=\"anchor\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" version=\"1.1\" viewBox=\"0 0 16 16\" width=\"16\"><path fill-rule=\"evenodd\" d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"></path></svg></a>请求头域</h3>\n<p>除公共头域外，无其它特殊头域。</p>\n<h3 id=\"请求参数\"><a href=\"#%E8%AF%B7%E6%B1%82%E5%8F%82%E6%95%B0\" aria-label=\"请求参数 permalink\" class=\"anchor\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" version=\"1.1\" viewBox=\"0 0 16 16\" width=\"16\"><path fill-rule=\"evenodd\" d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"></path></svg></a>请求参数</h3>\n<table>\n<thead>\n<tr>\n<th>参数名称</th>\n<th>类型</th>\n<th>是否必须</th>\n<th>参数位置</th>\n<th>说明</th>\n</tr>\n</thead>\n<tbody>\n<tr>\n<td>resourcePoolId</td>\n<td>String</td>\n<td>是</td>\n<td>Query 参数</td>\n<td>标识资源池的唯一标识符</td>\n</tr>\n<tr>\n<td>keywordType</td>\n<td>String</td>\n<td>否</td>\n<td>Query 参数</td>\n<td>筛选关键字类型，当前仅支持queueName和queueId</td>\n</tr>\n<tr>\n<td>keyword</td>\n<td>String</td>\n<td>否</td>\n<td>Query 参数</td>\n<td>关键字值</td>\n</tr>\n<tr>\n<td>pageNumber</td>\n<td>Number</td>\n<td>否</td>\n<td>Query 参数</td>\n<td>请求分页参数，表示第几页</td>\n</tr>\n<tr>\n<td>pageSize</td>\n<td>Number</td>\n<td>否</td>\n<td>Query 参数</td>\n<td>单页结果数，默认值为10</td>\n</tr>\n</tbody>\n</table>\n<h3 id=\"返回头域\"><a href=\"#%E8%BF%94%E5%9B%9E%E5%A4%B4%E5%9F%9F\" aria-label=\"返回头域 permalink\" class=\"anchor\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" version=\"1.1\" viewBox=\"0 0 16 16\" width=\"16\"><path fill-rule=\"evenodd\" d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"></path></svg></a>返回头域</h3>\n<p>除公共头域外，无其他特殊头域。</p>\n<h3 id=\"返回参数\"><a href=\"#%E8%BF%94%E5%9B%9E%E5%8F%82%E6%95%B0\" aria-label=\"返回参数 permalink\" class=\"anchor\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" version=\"1.1\" viewBox=\"0 0 16 16\" width=\"16\"><path fill-rule=\"evenodd\" d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"></path></svg></a>返回参数</h3>\n<table>\n<thead>\n<tr>\n<th>参数名称</th>\n<th>类型</th>\n<th>说明</th>\n</tr>\n</thead>\n<tbody>\n<tr>\n<td>keywordType</td>\n<td>String</td>\n<td>筛选关键字类型，当前仅支持queueName和queueId</td>\n</tr>\n<tr>\n<td>keyword</td>\n<td>String</td>\n<td>关键字值</td>\n</tr>\n<tr>\n<td>pageNumber</td>\n<td>Number</td>\n<td>请求分页参数，表示第几页，默认值为1</td>\n</tr>\n<tr>\n<td>pageSize</td>\n<td>Number</td>\n<td>单页结果数，默认值为10</td>\n</tr>\n<tr>\n<td>totalCount</td>\n<td>Number</td>\n<td>队列总数</td>\n</tr>\n<tr>\n<td>queues</td>\n<td>List<QueueItem>​</td>\n<td>队列详情列表</td>\n</tr>\n</tbody>\n</table>\n<h3 id=\"返回示例\"><a href=\"#%E8%BF%94%E5%9B%9E%E7%A4%BA%E4%BE%8B\" aria-label=\"返回示例 permalink\" class=\"anchor\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" version=\"1.1\" viewBox=\"0 0 16 16\" width=\"16\"><path fill-rule=\"evenodd\" d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"></path></svg></a>返回示例</h3>\n\n    <div class=\"code-block-wrapper\">\n        <div class=\"code-block\">\n            <div class=\"code-block-header\">\n                <span class=\"code-block-name\">Plain Text</span>\n                <button class=\"code-copy-btn\" data-tooltip-text=\"\">\n                    <svg xmlns=\"http://www.w3.org/2000/svg\" width=\"16\" height=\"16\" viewBox=\"0 0 16 16\" fill=\"none\"> <path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M5.57894 3.45614C5.57894 3.38832 5.63392 3.33333 5.70175 3.33333H12.5439C12.6117 3.33333 12.6667 3.38832 12.6667 3.45614V10.2982C12.6667 10.3661 12.6117 10.4211 12.5439 10.4211H11.7544V5.70175C11.7544 4.89754 11.1025 4.24561 10.2982 4.24561H5.57894V3.45614ZM4.24561 4.24561V3.45614C4.24561 2.65194 4.89754 2 5.70175 2H12.5439C13.3481 2 14 2.65194 14 3.45614V10.2982C14 11.1025 13.3481 11.7544 12.5439 11.7544H11.7544V12.5439C11.7544 13.3481 11.1025 14 10.2982 14H3.45614C2.65194 14 2 13.3481 2 12.5439V5.70175C2 4.89754 2.65194 4.24561 3.45614 4.24561H4.24561ZM3.33333 5.70175C3.33333 5.63392 3.38832 5.57894 3.45614 5.57894H10.2982C10.3661 5.57894 10.4211 5.63392 10.4211 5.70175V12.5439C10.4211 12.6117 10.3661 12.6667 10.2982 12.6667H3.45614C3.38832 12.6667 3.33333 12.6117 3.33333 12.5439V5.70175Z\" fill=\"currentColor\"></path> </svg>\n                    复制\n                </button>\n            </div>\n            <div class=\"code-block-content\">\n                <pre class=\"language-text\"><code><span class=\"line-number\">1</span>{\n<span class=\"line-number\">2</span>    &quot;pageSize&quot;: 10,\n<span class=\"line-number\">3</span>    &quot;pageNumber&quot;: 1,\n<span class=\"line-number\">4</span>    &quot;keyword&quot;: &quot;a&quot;,\n<span class=\"line-number\">5</span>    &quot;keywordType&quot;: &quot;queueName&quot;,\n<span class=\"line-number\">6</span>    &quot;totalCount&quot;: 6,\n<span class=\"line-number\">7</span>    &quot;queues&quot;: [\n<span class=\"line-number\">8</span>        {\n<span class=\"line-number\">9</span>            &quot;queueId&quot;: &quot;queue-cd1i93jyadbq&quot;,\n<span class=\"line-number\">10</span>            &quot;queueName&quot;: &quot;63a9f0ea7bb98050796b649e85481845&quot;,\n<span class=\"line-number\">11</span>            &quot;queueType&quot;: &quot;Elastic&quot;,\n<span class=\"line-number\">12</span>            &quot;resourcePoolId&quot;: &quot;cce-so2uum7z&quot;,\n<span class=\"line-number\">13</span>            &quot;createdAt&quot;: &quot;2025-08-26T17:13:19+08:00&quot;,\n<span class=\"line-number\">14</span>            &quot;updatedAt&quot;: &quot;2025-09-09T19:26:59+08:00&quot;,\n<span class=\"line-number\">15</span>            &quot;parentQueue&quot;: &quot;63a9f0ea7bb98050796b649e85481845&quot;,\n<span class=\"line-number\">16</span>            &quot;opened&quot;: true,\n<span class=\"line-number\">17</span>            &quot;reclaimable&quot;: true,\n<span class=\"line-number\">18</span>            &quot;disableOversell&quot;: false,\n<span class=\"line-number\">19</span>            &quot;queueingStrategy&quot;: &quot;BestEffortFIFO&quot;,\n<span class=\"line-number\">20</span>            &quot;capability&quot;: {\n<span class=\"line-number\">21</span>                &quot;milliCPUcores&quot;: &quot;856&quot;,\n<span class=\"line-number\">22</span>                &quot;memoryGi&quot;: &quot;9449599258624&quot;,\n<span class=\"line-number\">23</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">24</span>                    {\n<span class=\"line-number\">25</span>                        &quot;acceleratorCount&quot;: &quot;8&quot;,\n<span class=\"line-number\">26</span>                        &quot;acceleratorType&quot;: &quot;KUNLUNXIN-P800&quot;,\n<span class=\"line-number\">27</span>                        &quot;acceleratorDescription&quot;: &quot;kunlunxin.com/xpu&quot;\n<span class=\"line-number\">28</span>                    },\n<span class=\"line-number\">29</span>                    {\n<span class=\"line-number\">30</span>                        &quot;acceleratorCount&quot;: &quot;1&quot;,\n<span class=\"line-number\">31</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA GeForce RTX 3090&quot;,\n<span class=\"line-number\">32</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/rtx_3090_cgpu&quot;\n<span class=\"line-number\">33</span>                    },\n<span class=\"line-number\">34</span>                    {\n<span class=\"line-number\">35</span>                        &quot;acceleratorCount&quot;: &quot;8&quot;,\n<span class=\"line-number\">36</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA L20&quot;,\n<span class=\"line-number\">37</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/l20_cgpu&quot;\n<span class=\"line-number\">38</span>                    },\n<span class=\"line-number\">39</span>                    {\n<span class=\"line-number\">40</span>                        &quot;acceleratorCount&quot;: &quot;16&quot;,\n<span class=\"line-number\">41</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">42</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">43</span>                    }\n<span class=\"line-number\">44</span>                ]\n<span class=\"line-number\">45</span>            },\n<span class=\"line-number\">46</span>            &quot;deserved&quot;: {},\n<span class=\"line-number\">47</span>            &quot;guarantee&quot;: {},\n<span class=\"line-number\">48</span>            &quot;allocated&quot;: {\n<span class=\"line-number\">49</span>                &quot;milliCPUcores&quot;: &quot;0&quot;,\n<span class=\"line-number\">50</span>                &quot;memoryGi&quot;: &quot;0&quot;\n<span class=\"line-number\">51</span>            },\n<span class=\"line-number\">52</span>            &quot;workloadAvailable&quot;: {\n<span class=\"line-number\">53</span>                &quot;milliCPUcores&quot;: &quot;643590&quot;,\n<span class=\"line-number\">54</span>                &quot;cpuCores&quot;: &quot;643&quot;,\n<span class=\"line-number\">55</span>                &quot;memoryGi&quot;: &quot;5922&quot;,\n<span class=\"line-number\">56</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">57</span>                    {\n<span class=\"line-number\">58</span>                        &quot;acceleratorCount&quot;: &quot;8&quot;,\n<span class=\"line-number\">59</span>                        &quot;acceleratorType&quot;: &quot;KUNLUNXIN-P800&quot;,\n<span class=\"line-number\">60</span>                        &quot;acceleratorDescription&quot;: &quot;kunlunxin.com/xpu&quot;\n<span class=\"line-number\">61</span>                    },\n<span class=\"line-number\">62</span>                    {\n<span class=\"line-number\">63</span>                        &quot;acceleratorCount&quot;: &quot;1&quot;,\n<span class=\"line-number\">64</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA GeForce RTX 3090&quot;,\n<span class=\"line-number\">65</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/rtx_3090_cgpu&quot;\n<span class=\"line-number\">66</span>                    },\n<span class=\"line-number\">67</span>                    {\n<span class=\"line-number\">68</span>                        &quot;acceleratorCount&quot;: &quot;8&quot;,\n<span class=\"line-number\">69</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA L20&quot;,\n<span class=\"line-number\">70</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/l20_cgpu&quot;\n<span class=\"line-number\">71</span>                    },\n<span class=\"line-number\">72</span>                    {\n<span class=\"line-number\">73</span>                        &quot;acceleratorCount&quot;: &quot;8&quot;,\n<span class=\"line-number\">74</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">75</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">76</span>                    }\n<span class=\"line-number\">77</span>                ]\n<span class=\"line-number\">78</span>            },\n<span class=\"line-number\">79</span>            &quot;remaining&quot;: {\n<span class=\"line-number\">80</span>                &quot;milliCPUcores&quot;: &quot;635590&quot;,\n<span class=\"line-number\">81</span>                &quot;cpuCores&quot;: &quot;635&quot;,\n<span class=\"line-number\">82</span>                &quot;memoryGi&quot;: &quot;5898&quot;\n<span class=\"line-number\">83</span>            }\n<span class=\"line-number\">84</span>        },\n<span class=\"line-number\">85</span>        {\n<span class=\"line-number\">86</span>            &quot;queueId&quot;: &quot;queue-6gjnkt3dmxiy&quot;,\n<span class=\"line-number\">87</span>            &quot;queueName&quot;: &quot;default&quot;,\n<span class=\"line-number\">88</span>            &quot;queueType&quot;: &quot;Elastic&quot;,\n<span class=\"line-number\">89</span>            &quot;resourcePoolId&quot;: &quot;cce-so2uum7z&quot;,\n<span class=\"line-number\">90</span>            &quot;createdAt&quot;: &quot;2025-08-26T17:13:19+08:00&quot;,\n<span class=\"line-number\">91</span>            &quot;updatedAt&quot;: &quot;2025-09-09T19:26:59+08:00&quot;,\n<span class=\"line-number\">92</span>            &quot;parentQueue&quot;: &quot;63a9f0ea7bb98050796b649e85481845&quot;,\n<span class=\"line-number\">93</span>            &quot;opened&quot;: true,\n<span class=\"line-number\">94</span>            &quot;reclaimable&quot;: true,\n<span class=\"line-number\">95</span>            &quot;disableOversell&quot;: false,\n<span class=\"line-number\">96</span>            &quot;queueingStrategy&quot;: &quot;BestEffortFIFO&quot;,\n<span class=\"line-number\">97</span>            &quot;capability&quot;: {},\n<span class=\"line-number\">98</span>            &quot;deserved&quot;: {},\n<span class=\"line-number\">99</span>            &quot;guarantee&quot;: {},\n<span class=\"line-number\">100</span>            &quot;allocated&quot;: {\n<span class=\"line-number\">101</span>                &quot;milliCPUcores&quot;: &quot;4000&quot;,\n<span class=\"line-number\">102</span>                &quot;cpuCores&quot;: &quot;4&quot;,\n<span class=\"line-number\">103</span>                &quot;memoryGi&quot;: &quot;16&quot;,\n<span class=\"line-number\">104</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">105</span>                    {\n<span class=\"line-number\">106</span>                        &quot;acceleratorCount&quot;: &quot;1&quot;,\n<span class=\"line-number\">107</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">108</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">109</span>                    }\n<span class=\"line-number\">110</span>                ]\n<span class=\"line-number\">111</span>            }\n<span class=\"line-number\">112</span>        },\n<span class=\"line-number\">113</span>        {\n<span class=\"line-number\">114</span>            &quot;queueId&quot;: &quot;queue-h4rzqodsqgfv&quot;,\n<span class=\"line-number\">115</span>            &quot;queueName&quot;: &quot;feold-backnew-gpu-phy-l1&quot;,\n<span class=\"line-number\">116</span>            &quot;queueType&quot;: &quot;Physical&quot;,\n<span class=\"line-number\">117</span>            &quot;resourcePoolId&quot;: &quot;cce-so2uum7z&quot;,\n<span class=\"line-number\">118</span>            &quot;createdAt&quot;: &quot;2025-09-09T15:46:18+08:00&quot;,\n<span class=\"line-number\">119</span>            &quot;updatedAt&quot;: &quot;2025-09-09T19:26:59+08:00&quot;,\n<span class=\"line-number\">120</span>            &quot;parentQueue&quot;: &quot;63a9f0ea7bb98050796b649e85481845&quot;,\n<span class=\"line-number\">121</span>            &quot;opened&quot;: true,\n<span class=\"line-number\">122</span>            &quot;reclaimable&quot;: false,\n<span class=\"line-number\">123</span>            &quot;disableOversell&quot;: false,\n<span class=\"line-number\">124</span>            &quot;queueingStrategy&quot;: &quot;StrictFIFO&quot;,\n<span class=\"line-number\">125</span>            &quot;enableVGPU&quot;: true,\n<span class=\"line-number\">126</span>            &quot;capability&quot;: {\n<span class=\"line-number\">127</span>                &quot;milliCPUcores&quot;: &quot;292000&quot;,\n<span class=\"line-number\">128</span>                &quot;cpuCores&quot;: &quot;292&quot;,\n<span class=\"line-number\">129</span>                &quot;memoryGi&quot;: &quot;3361&quot;,\n<span class=\"line-number\">130</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">131</span>                    {\n<span class=\"line-number\">132</span>                        &quot;acceleratorCount&quot;: &quot;4&quot;,\n<span class=\"line-number\">133</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA L20&quot;,\n<span class=\"line-number\">134</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/l20_cgpu&quot;\n<span class=\"line-number\">135</span>                    }\n<span class=\"line-number\">136</span>                ]\n<span class=\"line-number\">137</span>            },\n<span class=\"line-number\">138</span>            &quot;deserved&quot;: {\n<span class=\"line-number\">139</span>                &quot;milliCPUcores&quot;: &quot;292000&quot;,\n<span class=\"line-number\">140</span>                &quot;cpuCores&quot;: &quot;292&quot;,\n<span class=\"line-number\">141</span>                &quot;memoryGi&quot;: &quot;3361&quot;,\n<span class=\"line-number\">142</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">143</span>                    {\n<span class=\"line-number\">144</span>                        &quot;acceleratorCount&quot;: &quot;4&quot;,\n<span class=\"line-number\">145</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA L20&quot;,\n<span class=\"line-number\">146</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/l20_cgpu&quot;\n<span class=\"line-number\">147</span>                    }\n<span class=\"line-number\">148</span>                ]\n<span class=\"line-number\">149</span>            },\n<span class=\"line-number\">150</span>            &quot;guarantee&quot;: {\n<span class=\"line-number\">151</span>                &quot;milliCPUcores&quot;: &quot;292000&quot;,\n<span class=\"line-number\">152</span>                &quot;cpuCores&quot;: &quot;292&quot;,\n<span class=\"line-number\">153</span>                &quot;memoryGi&quot;: &quot;3361&quot;,\n<span class=\"line-number\">154</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">155</span>                    {\n<span class=\"line-number\">156</span>                        &quot;acceleratorCount&quot;: &quot;4&quot;,\n<span class=\"line-number\">157</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA L20&quot;,\n<span class=\"line-number\">158</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/l20_cgpu&quot;\n<span class=\"line-number\">159</span>                    }\n<span class=\"line-number\">160</span>                ]\n<span class=\"line-number\">161</span>            },\n<span class=\"line-number\">162</span>            &quot;allocated&quot;: {\n<span class=\"line-number\">163</span>                &quot;milliCPUcores&quot;: &quot;0&quot;,\n<span class=\"line-number\">164</span>                &quot;cpuCores&quot;: &quot;0&quot;,\n<span class=\"line-number\">165</span>                &quot;memoryGi&quot;: &quot;0&quot;,\n<span class=\"line-number\">166</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">167</span>                    {\n<span class=\"line-number\">168</span>                        &quot;acceleratorCount&quot;: &quot;3.8&quot;,\n<span class=\"line-number\">169</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA L20&quot;,\n<span class=\"line-number\">170</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/l20_cgpu&quot;\n<span class=\"line-number\">171</span>                    }\n<span class=\"line-number\">172</span>                ]\n<span class=\"line-number\">173</span>            },\n<span class=\"line-number\">174</span>            &quot;workloadAvailable&quot;: {\n<span class=\"line-number\">175</span>                &quot;milliCPUcores&quot;: &quot;108615&quot;,\n<span class=\"line-number\">176</span>                &quot;cpuCores&quot;: &quot;108&quot;,\n<span class=\"line-number\">177</span>                &quot;memoryGi&quot;: &quot;451&quot;,\n<span class=\"line-number\">178</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">179</span>                    {\n<span class=\"line-number\">180</span>                        &quot;acceleratorCount&quot;: &quot;0&quot;,\n<span class=\"line-number\">181</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">182</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">183</span>                    },\n<span class=\"line-number\">184</span>                    {\n<span class=\"line-number\">185</span>                        &quot;acceleratorCount&quot;: &quot;4&quot;,\n<span class=\"line-number\">186</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA L20&quot;,\n<span class=\"line-number\">187</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/l20_cgpu&quot;\n<span class=\"line-number\">188</span>                    }\n<span class=\"line-number\">189</span>                ]\n<span class=\"line-number\">190</span>            },\n<span class=\"line-number\">191</span>            &quot;remaining&quot;: {\n<span class=\"line-number\">192</span>                &quot;milliCPUcores&quot;: &quot;108615&quot;,\n<span class=\"line-number\">193</span>                &quot;cpuCores&quot;: &quot;108&quot;,\n<span class=\"line-number\">194</span>                &quot;memoryGi&quot;: &quot;451&quot;\n<span class=\"line-number\">195</span>            }\n<span class=\"line-number\">196</span>        },\n<span class=\"line-number\">197</span>        {\n<span class=\"line-number\">198</span>            &quot;queueId&quot;: &quot;queue-9dgwufhc8lwu&quot;,\n<span class=\"line-number\">199</span>            &quot;queueName&quot;: &quot;feold-backnew-elas&quot;,\n<span class=\"line-number\">200</span>            &quot;queueType&quot;: &quot;Elastic&quot;,\n<span class=\"line-number\">201</span>            &quot;resourcePoolId&quot;: &quot;cce-so2uum7z&quot;,\n<span class=\"line-number\">202</span>            &quot;createdAt&quot;: &quot;2025-09-09T11:36:58+08:00&quot;,\n<span class=\"line-number\">203</span>            &quot;updatedAt&quot;: &quot;2025-09-09T19:26:59+08:00&quot;,\n<span class=\"line-number\">204</span>            &quot;parentQueue&quot;: &quot;63a9f0ea7bb98050796b649e85481845&quot;,\n<span class=\"line-number\">205</span>            &quot;opened&quot;: true,\n<span class=\"line-number\">206</span>            &quot;reclaimable&quot;: true,\n<span class=\"line-number\">207</span>            &quot;disableOversell&quot;: false,\n<span class=\"line-number\">208</span>            &quot;queueingStrategy&quot;: &quot;BestEffortFIFO&quot;,\n<span class=\"line-number\">209</span>            &quot;capability&quot;: {\n<span class=\"line-number\">210</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">211</span>                    {\n<span class=\"line-number\">212</span>                        &quot;acceleratorCount&quot;: &quot;4&quot;,\n<span class=\"line-number\">213</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">214</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">215</span>                    }\n<span class=\"line-number\">216</span>                ]\n<span class=\"line-number\">217</span>            },\n<span class=\"line-number\">218</span>            &quot;deserved&quot;: {\n<span class=\"line-number\">219</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">220</span>                    {\n<span class=\"line-number\">221</span>                        &quot;acceleratorCount&quot;: &quot;3&quot;,\n<span class=\"line-number\">222</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">223</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">224</span>                    }\n<span class=\"line-number\">225</span>                ]\n<span class=\"line-number\">226</span>            },\n<span class=\"line-number\">227</span>            &quot;guarantee&quot;: {\n<span class=\"line-number\">228</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">229</span>                    {\n<span class=\"line-number\">230</span>                        &quot;acceleratorCount&quot;: &quot;2&quot;,\n<span class=\"line-number\">231</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">232</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">233</span>                    }\n<span class=\"line-number\">234</span>                ]\n<span class=\"line-number\">235</span>            },\n<span class=\"line-number\">236</span>            &quot;allocated&quot;: {\n<span class=\"line-number\">237</span>                &quot;milliCPUcores&quot;: &quot;0&quot;,\n<span class=\"line-number\">238</span>                &quot;cpuCores&quot;: &quot;0&quot;,\n<span class=\"line-number\">239</span>                &quot;memoryGi&quot;: &quot;0&quot;,\n<span class=\"line-number\">240</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">241</span>                    {\n<span class=\"line-number\">242</span>                        &quot;acceleratorCount&quot;: &quot;4&quot;,\n<span class=\"line-number\">243</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">244</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">245</span>                    }\n<span class=\"line-number\">246</span>                ]\n<span class=\"line-number\">247</span>            }\n<span class=\"line-number\">248</span>        },\n<span class=\"line-number\">249</span>        {\n<span class=\"line-number\">250</span>            &quot;queueId&quot;: &quot;queue-zn55rhdirv1r&quot;,\n<span class=\"line-number\">251</span>            &quot;queueName&quot;: &quot;feold-backnew-nor&quot;,\n<span class=\"line-number\">252</span>            &quot;queueType&quot;: &quot;Regular&quot;,\n<span class=\"line-number\">253</span>            &quot;resourcePoolId&quot;: &quot;cce-so2uum7z&quot;,\n<span class=\"line-number\">254</span>            &quot;createdAt&quot;: &quot;2025-09-09T11:36:36+08:00&quot;,\n<span class=\"line-number\">255</span>            &quot;updatedAt&quot;: &quot;2025-09-09T19:26:59+08:00&quot;,\n<span class=\"line-number\">256</span>            &quot;parentQueue&quot;: &quot;63a9f0ea7bb98050796b649e85481845&quot;,\n<span class=\"line-number\">257</span>            &quot;opened&quot;: true,\n<span class=\"line-number\">258</span>            &quot;reclaimable&quot;: false,\n<span class=\"line-number\">259</span>            &quot;disableOversell&quot;: false,\n<span class=\"line-number\">260</span>            &quot;queueingStrategy&quot;: &quot;BestEffortFIFO&quot;,\n<span class=\"line-number\">261</span>            &quot;capability&quot;: {\n<span class=\"line-number\">262</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">263</span>                    {\n<span class=\"line-number\">264</span>                        &quot;acceleratorCount&quot;: &quot;3&quot;,\n<span class=\"line-number\">265</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">266</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">267</span>                    }\n<span class=\"line-number\">268</span>                ]\n<span class=\"line-number\">269</span>            },\n<span class=\"line-number\">270</span>            &quot;deserved&quot;: {\n<span class=\"line-number\">271</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">272</span>                    {\n<span class=\"line-number\">273</span>                        &quot;acceleratorCount&quot;: &quot;3&quot;,\n<span class=\"line-number\">274</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">275</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">276</span>                    }\n<span class=\"line-number\">277</span>                ]\n<span class=\"line-number\">278</span>            },\n<span class=\"line-number\">279</span>            &quot;guarantee&quot;: {},\n<span class=\"line-number\">280</span>            &quot;allocated&quot;: {\n<span class=\"line-number\">281</span>                &quot;milliCPUcores&quot;: &quot;0&quot;,\n<span class=\"line-number\">282</span>                &quot;cpuCores&quot;: &quot;0&quot;,\n<span class=\"line-number\">283</span>                &quot;memoryGi&quot;: &quot;0&quot;,\n<span class=\"line-number\">284</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">285</span>                    {\n<span class=\"line-number\">286</span>                        &quot;acceleratorCount&quot;: &quot;2&quot;,\n<span class=\"line-number\">287</span>                        &quot;acceleratorType&quot;: &quot;NVIDIA H20Z&quot;,\n<span class=\"line-number\">288</span>                        &quot;acceleratorDescription&quot;: &quot;baidu.com/h20z_141g_cgpu&quot;\n<span class=\"line-number\">289</span>                    }\n<span class=\"line-number\">290</span>                ]\n<span class=\"line-number\">291</span>            }\n<span class=\"line-number\">292</span>        },\n<span class=\"line-number\">293</span>        {\n<span class=\"line-number\">294</span>            &quot;queueId&quot;: &quot;queue-oji7qisf0szs&quot;,\n<span class=\"line-number\">295</span>            &quot;queueName&quot;: &quot;feold-backnew-phy&quot;,\n<span class=\"line-number\">296</span>            &quot;queueType&quot;: &quot;Physical&quot;,\n<span class=\"line-number\">297</span>            &quot;resourcePoolId&quot;: &quot;cce-so2uum7z&quot;,\n<span class=\"line-number\">298</span>            &quot;createdAt&quot;: &quot;2025-09-09T11:36:02+08:00&quot;,\n<span class=\"line-number\">299</span>            &quot;updatedAt&quot;: &quot;2025-09-09T19:26:59+08:00&quot;,\n<span class=\"line-number\">300</span>            &quot;parentQueue&quot;: &quot;63a9f0ea7bb98050796b649e85481845&quot;,\n<span class=\"line-number\">301</span>            &quot;opened&quot;: false,\n<span class=\"line-number\">302</span>            &quot;reclaimable&quot;: false,\n<span class=\"line-number\">303</span>            &quot;disableOversell&quot;: false,\n<span class=\"line-number\">304</span>            &quot;queueingStrategy&quot;: &quot;StrictFIFO&quot;,\n<span class=\"line-number\">305</span>            &quot;capability&quot;: {\n<span class=\"line-number\">306</span>                &quot;milliCPUcores&quot;: &quot;208000&quot;,\n<span class=\"line-number\">307</span>                &quot;cpuCores&quot;: &quot;208&quot;,\n<span class=\"line-number\">308</span>                &quot;memoryGi&quot;: &quot;2016&quot;,\n<span class=\"line-number\">309</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">310</span>                    {\n<span class=\"line-number\">311</span>                        &quot;acceleratorCount&quot;: &quot;8&quot;,\n<span class=\"line-number\">312</span>                        &quot;acceleratorType&quot;: &quot;KUNLUNXIN-P800&quot;,\n<span class=\"line-number\">313</span>                        &quot;acceleratorDescription&quot;: &quot;kunlunxin.com/xpu&quot;\n<span class=\"line-number\">314</span>                    }\n<span class=\"line-number\">315</span>                ]\n<span class=\"line-number\">316</span>            },\n<span class=\"line-number\">317</span>            &quot;deserved&quot;: {\n<span class=\"line-number\">318</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">319</span>                    {\n<span class=\"line-number\">320</span>                        &quot;acceleratorCount&quot;: &quot;8&quot;,\n<span class=\"line-number\">321</span>                        &quot;acceleratorType&quot;: &quot;KUNLUNXIN-P800&quot;,\n<span class=\"line-number\">322</span>                        &quot;acceleratorDescription&quot;: &quot;kunlunxin.com/xpu&quot;\n<span class=\"line-number\">323</span>                    }\n<span class=\"line-number\">324</span>                ]\n<span class=\"line-number\">325</span>            },\n<span class=\"line-number\">326</span>            &quot;guarantee&quot;: {\n<span class=\"line-number\">327</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">328</span>                    {\n<span class=\"line-number\">329</span>                        &quot;acceleratorCount&quot;: &quot;8&quot;,\n<span class=\"line-number\">330</span>                        &quot;acceleratorType&quot;: &quot;KUNLUNXIN-P800&quot;,\n<span class=\"line-number\">331</span>                        &quot;acceleratorDescription&quot;: &quot;kunlunxin.com/xpu&quot;\n<span class=\"line-number\">332</span>                    }\n<span class=\"line-number\">333</span>                ]\n<span class=\"line-number\">334</span>            },\n<span class=\"line-number\">335</span>            &quot;allocated&quot;: {\n<span class=\"line-number\">336</span>                &quot;milliCPUcores&quot;: &quot;0&quot;,\n<span class=\"line-number\">337</span>                &quot;cpuCores&quot;: &quot;0&quot;,\n<span class=\"line-number\">338</span>                &quot;memoryGi&quot;: &quot;0&quot;\n<span class=\"line-number\">339</span>            },\n<span class=\"line-number\">340</span>            &quot;workloadAvailable&quot;: {\n<span class=\"line-number\">341</span>                &quot;milliCPUcores&quot;: &quot;202040&quot;,\n<span class=\"line-number\">342</span>                &quot;cpuCores&quot;: &quot;202&quot;,\n<span class=\"line-number\">343</span>                &quot;memoryGi&quot;: &quot;1966&quot;,\n<span class=\"line-number\">344</span>                &quot;acceleratorCardList&quot;: [\n<span class=\"line-number\">345</span>                    {\n<span class=\"line-number\">346</span>                        &quot;acceleratorCount&quot;: &quot;8&quot;,\n<span class=\"line-number\">347</span>                        &quot;acceleratorType&quot;: &quot;KUNLUNXIN-P800&quot;,\n<span class=\"line-number\">348</span>                        &quot;acceleratorDescription&quot;: &quot;kunlunxin.com/xpu&quot;\n<span class=\"line-number\">349</span>                    }\n<span class=\"line-number\">350</span>                ]\n<span class=\"line-number\">351</span>            },\n<span class=\"line-number\">352</span>            &quot;remaining&quot;: {\n<span class=\"line-number\">353</span>                &quot;milliCPUcores&quot;: &quot;202040&quot;,\n<span class=\"line-number\">354</span>                &quot;cpuCores&quot;: &quot;202&quot;,\n<span class=\"line-number\">355</span>                &quot;memoryGi&quot;: &quot;1966&quot;\n<span class=\"line-number\">356</span>            }\n<span class=\"line-number\">357</span>        }\n<span class=\"line-number\">358</span>    ]\n<span class=\"line-number\">359</span>}</code></pre>\n            </div>\n        </div>\n    </div>\n  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