doc-exports/docs/modelarts/api-ref/CreateTask.html

<a name="EN-US_TOPIC_0000001909848204"></a><a name="EN-US_TOPIC_0000001909848204"></a>

<h1 class="topictitle1">Starting Intelligent Tasks</h1>
<div id="body0000001588873489"><div class="section"><h4 class="sectiontitle">Function</h4><p>This interface is used to start an intelligent task. Two types of intelligent tasks are supported: intelligent labeling and automatic grouping. You can specify the <strong>task_type</strong> parameter in the request body to start a type of tasks. For datasets whose data path or working path is in the KMS encryption bucket, active learning and automatic grouping tasks cannot be started, but pre-labeling tasks are supported.</p>
<ul><li><p>Intelligent Labeling allows you to select an existing model in the system for intelligent labeling based on the labeling and image learning training in the current labeling phase to quickly label the remaining images. Auto labeling includes active learning and pre-labeling. * Active learning: The system uses semi-supervised learning and hard example filtering to perform auto labeling, reducing manual labeling workload and helping you find hard examples. * Pre-labeling: You select a model on the Model Management page for auto labeling. - Auto grouping: Unlabeled images are clustered using the clustering algorithm and then processed based on the clustering result. Images can be labeled by group or cleaned.</p>
</li></ul>
</div>
<div class="section" id="EN-US_TOPIC_0000001909848204__atuogenerate_1"><h4 class="sectiontitle">Debugging</h4><p>You can debug this API through automatic authentication in  or use the SDK sample code generated by API Explorer.</p>
</div>
<div class="section" id="EN-US_TOPIC_0000001909848204__atuogenerate_2"><h4 class="sectiontitle">URI</h4><p>POST /v2/{project_id}/datasets/{dataset_id}/tasks</p>

<div class="tablenoborder"><table cellpadding="4" cellspacing="0" summary="" frame="border" border="1" rules="all"><caption><b>Table 1 </b>Path Parameters</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.3.3.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.3.3.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.3.3.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.3.3.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.3.3.2.5.1.1 "><p>dataset_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.3.3.2.5.1.2 "><p>Yes</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.3.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.3.3.2.5.1.4 "><p>Dataset ID.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.3.3.2.5.1.1 "><p>project_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.3.3.2.5.1.2 "><p>Yes</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.3.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.3.3.2.5.1.4 "><p>Project ID. For details about how to obtain a project ID, see <a href="modelarts_03_0147.html">Obtaining a Project ID and Name</a>.</p>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section"><h4 class="sectiontitle">Request Parameters</h4>
<div class="tablenoborder"><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_SmartTaskRequest" frame="border" border="1" rules="all"><caption><b>Table 2 </b>Request body parameters</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.2.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.2.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.2.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.2.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.1 "><p>collect_key_sample</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.3 "><p>Boolean</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.2.2.5.1.4 "><p>Whether to collect key samples. Options:</p>
<ul><li><p><strong>true</strong>: Collect key samples.</p>
</li><li><p><strong>false</strong>: Do not collect key samples. (Default value)</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.1 "><p>config</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.3 "><p><a href="#EN-US_TOPIC_0000001909848204__request_SmartTaskConfig">SmartTaskConfig</a> object</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.2.2.5.1.4 "><p>Task configuration.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.1 "><p>model_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.2.2.5.1.4 "><p>Model ID.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.1 "><p>task_type</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.2.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.2.2.5.1.4 "><p>Task type. The options are as follows: - <strong>auto-label</strong>: active learning - <strong>pre-label</strong>: pre-labeling - <strong>auto-grouping</strong>: auto grouping</p>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_SmartTaskConfig"></a><a name="request_SmartTaskConfig"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_SmartTaskConfig" frame="border" border="1" rules="all"><caption><b>Table 3 </b>SmartTaskConfig</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.3.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.3.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.3.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.3.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>algorithm_type</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Algorithm type for auto labeling. Options:</p>
<ul><li><p><strong>fast</strong>: Only labeled samples are used for training. This type of algorithm achieves faster labeling.</p>
</li><li><p><strong>accurate</strong>: In addition to labeled samples, unlabeled samples are used for semi-supervised training. This type of algorithm achieves more accurate labeling.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>ambiguity</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Boolean</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Whether to perform clustering based on the image blurring degree.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>annotation_output</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Output path of the active learning labeling result.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>collect_rule</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Sample collection rule. The default value is <strong>all</strong>, indicating full collection. Currently, only value <strong>all</strong> is available.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>collect_sample</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Boolean</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Whether to enable sample collection. Options:</p>
<ul><li><p><strong>true</strong>: Enable sample collection. (Default value)</p>
</li><li><p><strong>false</strong>: Do not enable sample collection.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>confidence_scope</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Confidence range of key samples. The minimum and maximum values are separated by hyphens (-). Example: 0.10-0.90.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>description</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Task description.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>engine_name</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Engine name.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>export_format</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Format of the exported directory. Options:</p>
<ul><li><p><strong>1</strong>: tree structure. Example: <strong>rabbits/1.jpg,bees/2.jpg</strong>.</p>
</li><li><p><strong>2</strong>: tile structure. Example: 1.jpg, 1.txt; 2.jpg,2.txt.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>export_params</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p><a href="#EN-US_TOPIC_0000001909848204__request_ExportParams">ExportParams</a> object</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Parameters of a dataset export task.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>flavor</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p><a href="#EN-US_TOPIC_0000001909848204__request_Flavor">Flavor</a> object</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Training resource flavor.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>image_brightness</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Boolean</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Whether to perform clustering based on the image brightness.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>image_colorfulness</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Boolean</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Whether to perform clustering based on the image color.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>inf_cluster_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>ID of a dedicated cluster. This parameter is left blank by default, indicating that a dedicated cluster is not used. When using the dedicated cluster to deploy services, ensure that the cluster status is normal. After this parameter is set, the network configuration of the cluster is used, and the <strong>vpc_id</strong> parameter does not take effect.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>inf_config_list</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Array of <a href="#EN-US_TOPIC_0000001909848204__request_InfConfig">InfConfig</a> objects</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Configuration list required for running an inference task, which is optional and left blank by default.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>inf_output</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Output path of inference in active learning.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>infer_result_output_dir</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>OBS directory for storing sample prediction results. This parameter is optional. The {<em>service_id</em>}<strong>-infer-result</strong> subdirectory in the <strong>output_dir</strong> directory is used by default.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>key_sample_output</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Output path of hard examples in active learning.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>log_url</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>OBS URL of the logs of a training job. By default, this parameter is left blank.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>manifest_path</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Path of the <strong>manifest</strong> file, which is used as the input for training and inference.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>model_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Model ID.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>model_name</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Model name.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>model_parameter</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Model parameter.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>model_version</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Model version.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>n_clusters</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Number of clusters.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>name</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Task name.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>output_dir</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Sample output path. The format is as follows: <em>Dataset output path</em>/<em>Dataset name</em>-<em>Dataset ID</em>/annotation/auto-deploy/. Example: <strong>/test/work_1608083108676/dataset123-g6IO9qSu6hoxwCAirfm/annotation/auto-deploy/</strong>.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>parameters</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Array of <a href="#EN-US_TOPIC_0000001909848204__request_TrainingParameter">TrainingParameter</a> objects</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Runtime parameters of a training job</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>pool_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>ID of a resource pool.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>property</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Attribute name.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>req_uri</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Inference path of a batch job.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>result_type</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Processing mode of auto grouping results. Options:</p>
<ul><li><p><strong>0</strong>: Save to OBS.</p>
</li><li><p><strong>1</strong>: Save to samples.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>samples</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Array of <a href="#EN-US_TOPIC_0000001909848204__request_SampleLabels">SampleLabels</a> objects</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>List of labeling information for samples to be auto labeled.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>stop_time</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Timeout interval, in minutes. The default value is 15 minutes. This parameter is used only in the scenario of auto labeling for videos.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>time</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Timestamp in active learning.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>train_data_path</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Path for storing existing training datasets.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>train_url</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>URL of the OBS path where the file of a training job is outputted. By default, this parameter is left blank.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>version_format</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Format of a dataset version. Options:</p>
<ul><li><p><strong>Default</strong>: default format</p>
</li><li><p><strong>CarbonData</strong>: CarbonData (supported only by table datasets)</p>
</li><li><p><strong>CSV</strong>: CSV</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.1 "><p>worker_server_num</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.3.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.3.2.5.1.4 "><p>Number of workers in a training job.</p>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_ExportParams"></a><a name="request_ExportParams"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_ExportParams" frame="border" border="1" rules="all"><caption><b>Table 4 </b>ExportParams</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.4.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.4.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.4.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.4.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>clear_hard_property</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>Boolean</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>Whether to clear hard example attributes. Options:</p>
<ul><li><p><strong>true</strong>: Clear hard example attributes. (Default value)</p>
</li><li><p><strong>false</strong>: Do not clear hard example attributes.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>export_dataset_version_format</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>Format of the dataset version to which data is exported.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>export_dataset_version_name</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>Name of the dataset version to which data is exported.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>export_dest</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>Export destination. Options:</p>
<ul><li><p><strong>DIR</strong>: Export data to OBS. (Default value)</p>
</li><li><p><strong>NEW_DATASET</strong>: Export data to a new dataset.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>export_new_dataset_name</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>Name of the new dataset to which data is exported.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>export_new_dataset_work_path</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>Working directory of the new dataset to which data is exported.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>ratio_sample_usage</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>Boolean</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>Whether to randomly allocate the training set and validation set based on the specified ratio. Options:</p>
<ul><li><p><strong>true</strong>: Allocate the training set and validation set.</p>
</li><li><p><strong>false</strong>: Do not allocate the training set and validation set. (Default value)</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>sample_state</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>Sample status. Options:</p>
<ul><li><p>__ALL__: labeled</p>
</li><li><p>__NONE__: unlabeled</p>
</li><li><p>__UNCHECK__: to be checked</p>
</li><li><p>__ACCEPTED__: accepted</p>
</li><li><p>__REJECTED__: rejected</p>
</li><li><p>__UNREVIEWED__: to be reviewed</p>
</li><li><p>__REVIEWED__: reviewed</p>
</li><li><p>__WORKFORCE_SAMPLED__: reviewed data sampled</p>
</li><li><p>__WORKFORCE_SAMPLED_UNCHECK__: samples to be checked</p>
</li><li><p>__WORKFORCE_SAMPLED_CHECKED__: samples checked</p>
</li><li><p>__WORKFORCE_SAMPLED_ACCEPTED__: samples accepted</p>
</li><li><p>__WORKFORCE_SAMPLED_REJECTED__: samples rejected</p>
</li><li><p>__AUTO_ANNOTATION__: to be checked</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>samples</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>Array of strings</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>ID list of exported samples.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>search_conditions</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>Array of <a href="#EN-US_TOPIC_0000001909848204__request_SearchCondition">SearchCondition</a> objects</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>Exported search conditions. The relationship between multiple search conditions is OR.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.1 "><p>train_sample_ratio</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.4.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.4.2.5.1.4 "><p>Split ratio of training set and verification set during specified version release. The default value is <strong>1.00</strong>, indicating that all released versions are training sets.</p>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_SearchCondition"></a><a name="request_SearchCondition"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_SearchCondition" frame="border" border="1" rules="all"><caption><b>Table 5 </b>SearchCondition</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.5.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.5.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.5.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.5.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>coefficient</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>Filter by coefficient of difficulty.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>frame_in_video</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>A frame in the video.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>hard</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>Whether a sample is a hard sample. Options:</p>
<ul><li><p><strong>0</strong>: non-hard sample</p>
</li><li><p><strong>1</strong>: hard sample</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>import_origin</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>Filter by data source.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>kvp</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>CT dosage, filtered by dosage.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>label_list</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p><a href="#EN-US_TOPIC_0000001909848204__request_SearchLabels">SearchLabels</a> object</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>Label search criteria.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>labeler</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>Labeler.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>metadata</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p><a href="#EN-US_TOPIC_0000001909848204__request_SearchProp">SearchProp</a> object</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>Search by sample attribute.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>parent_sample_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>Parent sample ID.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>sample_dir</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>Directory where data samples are stored (the directory must end with a slash (/)). Only samples in the specified directory are searched for. Recursive search of directories is not supported.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>sample_name</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>Search by sample name, including the file name extension.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>sample_time</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>When a sample is added to the dataset, an index is created based on the last modification time (accurate to day) of the sample on OBS. You can search for the sample based on the time. Options:</p>
<ul><li><p><strong>month</strong>: Search for samples added from 30 days ago to the current day.</p>
</li><li><p><strong>day</strong>: Search for samples added from yesterday (one day ago) to the current day.</p>
</li><li><p><strong>yyyyMMdd-yyyyMMdd</strong>: Search for samples added in a specified period (at most 30 days), in the format of <strong>Start date-End date</strong>. For example, <strong>20190901-2019091501</strong> indicates that samples generated from September 1 to September 15, 2019 are searched.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>score</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>Search by confidence.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>slice_thickness</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>DICOM layer thickness. Samples are filtered by layer thickness.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>study_date</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>DICOM scanning time.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.1 "><p>time_in_video</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.5.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.5.2.5.1.4 "><p>A time point in the video.</p>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_SearchLabels"></a><a name="request_SearchLabels"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_SearchLabels" frame="border" border="1" rules="all"><caption><b>Table 6 </b>SearchLabels</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.6.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.6.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.6.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.6.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.6.2.5.1.1 "><p>labels</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.6.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.6.2.5.1.3 "><p>Array of <a href="#EN-US_TOPIC_0000001909848204__request_SearchLabel">SearchLabel</a> objects</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.6.2.5.1.4 "><p>List of label search criteria.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.6.2.5.1.1 "><p>op</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.6.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.6.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.6.2.5.1.4 "><p>If you want to search for multiple labels, <strong>op</strong> must be specified. If you search for only one label, <strong>op</strong> can be left blank. Options:</p>
<ul><li><p><strong>OR</strong>: OR operation</p>
</li><li><p><strong>AND</strong>: AND operation</p>
</li></ul>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_SearchLabel"></a><a name="request_SearchLabel"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_SearchLabel" frame="border" border="1" rules="all"><caption><b>Table 7 </b>SearchLabel</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.7.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.7.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.7.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.7.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.1 "><p>name</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.7.2.5.1.4 "><p>Label name.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.1 "><p>op</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.7.2.5.1.4 "><p>Operation type between multiple attributes. Options:</p>
<ul><li><p><strong>OR</strong>: OR operation</p>
</li><li><p><strong>AND</strong>: AND operation</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.1 "><p>property</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.3 "><p>Map&lt;String,Array&lt;String&gt;&gt;</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.7.2.5.1.4 "><p>Label attribute, which is in the Object format and stores any key-value pairs. <strong>key</strong> indicates the attribute name, and <strong>value</strong> indicates the value list. If <strong>value</strong> is <strong>null</strong>, the search is not performed by value. Otherwise, the search value can be any value in the list.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.1 "><p>type</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.7.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.7.2.5.1.4 "><p>Label type. Options:</p>
<ul><li><p><strong>0</strong>: image classification</p>
</li><li><p><strong>1</strong>: object detection</p>
</li><li><p><strong>3</strong>: image segmentation</p>
</li><li><p><strong>100</strong>: text classification</p>
</li><li><p><strong>101</strong>: named entity recognition</p>
</li><li><p><strong>102</strong>: text triplet relationship</p>
</li><li><p><strong>103</strong>: text triplet entity</p>
</li><li><p><strong>200</strong>: sound classification</p>
</li><li><p><strong>201</strong>: speech content</p>
</li><li><p><strong>202</strong>: speech paragraph labeling</p>
</li><li><p><strong>600</strong>: video labeling</p>
</li></ul>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_SearchProp"></a><a name="request_SearchProp"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_SearchProp" frame="border" border="1" rules="all"><caption><b>Table 8 </b>SearchProp</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.8.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.8.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.8.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.8.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.8.2.5.1.1 "><p>op</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.8.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.8.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.8.2.5.1.4 "><p>Relationship between attribute values. Options:</p>
<ul><li><p><strong>AND</strong>: AND relationship</p>
</li><li><p><strong>OR</strong>: OR relationship</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.8.2.5.1.1 "><p>props</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.8.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.8.2.5.1.3 "><p>Map&lt;String,Array&lt;String&gt;&gt;</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.8.2.5.1.4 "><p>Search criteria of an attribute. Multiple search criteria can be set.</p>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_Flavor"></a><a name="request_Flavor"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_Flavor" frame="border" border="1" rules="all"><caption><b>Table 9 </b>Flavor</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.9.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.9.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.9.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.9.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.9.2.5.1.1 "><p>code</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.9.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.9.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.9.2.5.1.4 "><p>Attribute code of a resource specification, which is used for task creating.</p>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_InfConfig"></a><a name="request_InfConfig"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_InfConfig" frame="border" border="1" rules="all"><caption><b>Table 10 </b>InfConfig</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.10.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.10.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.10.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.10.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.1 "><p>envs</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.3 "><p>Map&lt;String,String&gt;</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.10.2.5.1.4 "><p>(Optional) Environment variable key-value pair required for running a model. By default, this parameter is left blank. To ensure data security, do not enter sensitive information in environment variables.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.1 "><p>instance_count</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.10.2.5.1.4 "><p>Instance number of model deployment, that is, the number of compute nodes.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.1 "><p>model_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.10.2.5.1.4 "><p>Model ID.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.1 "><p>specification</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.10.2.5.1.4 "><p>Resource specifications of real-time services. For details, see <a href="CreateService.html">Deploying Services</a>.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.1 "><p>weight</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.10.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.10.2.5.1.4 "><p>Traffic weight allocated to a model. This parameter is mandatory only when <strong>infer_type</strong> is set to <strong>real-time</strong>. The sum of the weights must be <strong>100</strong>.</p>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_TrainingParameter"></a><a name="request_TrainingParameter"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_TrainingParameter" frame="border" border="1" rules="all"><caption><b>Table 11 </b>TrainingParameter</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.11.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.11.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.11.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.11.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.11.2.5.1.1 "><p>label</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.11.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.11.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.11.2.5.1.4 "><p>Parameter name.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.11.2.5.1.1 "><p>value</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.11.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.11.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.11.2.5.1.4 "><p>Parameter value.</p>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_SampleLabels"></a><a name="request_SampleLabels"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_SampleLabels" frame="border" border="1" rules="all"><caption><b>Table 12 </b>SampleLabels</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.12.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.12.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.12.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.12.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.1 "><p>labels</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.3 "><p>Array of <a href="#EN-US_TOPIC_0000001909848204__request_SampleLabel">SampleLabel</a> objects</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.12.2.5.1.4 "><p>Sample label list. If this parameter is left blank, all sample labels are deleted.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.1 "><p>metadata</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.3 "><p><a href="#EN-US_TOPIC_0000001909848204__request_SampleMetadata">SampleMetadata</a> object</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.12.2.5.1.4 "><p>Key-value pair of the sample <strong>metadata</strong> attribute.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.1 "><p>sample_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.12.2.5.1.4 "><p>Sample ID.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.1 "><p>sample_type</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.12.2.5.1.4 "><p>Sample type. Options:</p>
<ul><li><p><strong>0</strong>: image</p>
</li><li><p><strong>1</strong>: text</p>
</li><li><p><strong>2</strong>: speech</p>
</li><li><p><strong>4</strong>: table</p>
</li><li><p><strong>6</strong>: video</p>
</li><li><p><strong>9</strong>: custom format</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.1 "><p>sample_usage</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.12.2.5.1.4 "><p>Sample usage. Options:</p>
<ul><li><p><strong>TRAIN</strong>: training</p>
</li><li><p><strong>EVAL</strong>: evaluation</p>
</li><li><p><strong>TEST</strong>: test</p>
</li><li><p><strong>INFERENCE</strong>: inference</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.1 "><p>source</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.12.2.5.1.4 "><p>Source address of sample data.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.1 "><p>worker_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.12.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.12.2.5.1.4 "><p>ID of a labeling team member.</p>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_SampleLabel"></a><a name="request_SampleLabel"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_SampleLabel" frame="border" border="1" rules="all"><caption><b>Table 13 </b>SampleLabel</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.13.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.13.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.13.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.13.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.1 "><p>annotated_by</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.13.2.5.1.4 "><p>Video labeling method, which is used to distinguish whether a video is labeled manually or automatically. Options:</p>
<ul><li><p><strong>human</strong>: manual labeling</p>
</li><li><p><strong>auto</strong>: automatic labeling</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.1 "><p>id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.13.2.5.1.4 "><p>Label ID.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.1 "><p>name</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.13.2.5.1.4 "><p>Label name.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.1 "><p>property</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.3 "><p><a href="#EN-US_TOPIC_0000001909848204__request_SampleLabelProperty">SampleLabelProperty</a> object</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.13.2.5.1.4 "><p>Attribute key-value pair of the sample label, such as the object shape and shape feature.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.1 "><p>score</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.3 "><p>Float</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.13.2.5.1.4 "><p>Confidence.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.1 "><p>type</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.13.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.13.2.5.1.4 "><p>Label type. Options:</p>
<ul><li><p><strong>0</strong>: image classification</p>
</li><li><p><strong>1</strong>: object detection</p>
</li><li><p><strong>3</strong>: image segmentation</p>
</li><li><p><strong>100</strong>: text classification</p>
</li><li><p><strong>101</strong>: named entity recognition</p>
</li><li><p><strong>102</strong>: text triplet relationship</p>
</li><li><p><strong>103</strong>: text triplet entity</p>
</li><li><p><strong>200</strong>: sound classification</p>
</li><li><p><strong>201</strong>: speech content</p>
</li><li><p><strong>202</strong>: speech paragraph labeling</p>
</li><li><p><strong>600</strong>: video labeling</p>
</li></ul>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_SampleLabelProperty"></a><a name="request_SampleLabelProperty"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_SampleLabelProperty" frame="border" border="1" rules="all"><caption><b>Table 14 </b>SampleLabelProperty</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.14.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.14.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.14.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.14.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:content</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>Speech text content, which is a default attribute dedicated to the speech label (including the speech content and speech start and end points).</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:end_index</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>End position of the text, which is a default attribute dedicated to the named entity label. The end position does not include the character corresponding to the value of <strong>end_index</strong>. Example:</p>
<ul><li><p>If the text is "<strong>Barack Hussein Obama II (born August 4, 1961) is an attorney and politician.</strong>", <strong>start_index</strong> and <strong>end_index</strong> of <strong>Barack Hussein Obama II</strong> are <strong>0</strong> and <strong>23</strong>, respectively.</p>
</li><li><p>If the text is "<strong>Hope is the thing with feathers</strong>", <strong>start_index</strong> and <strong>end_index</strong> of <strong>Hope</strong> are <strong>0</strong> and <strong>4</strong>, respectively.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:end_time</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>Speech end time, which is a default attribute dedicated to the speech start/end point label, in the format of <strong>hh:mm:ss.SSS</strong>. (<strong>hh</strong> indicates hour; <strong>mm</strong> indicates minute; <strong>ss</strong> indicates second; and <strong>SSS</strong> indicates millisecond.)</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:feature</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>Object</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>Shape feature, which is a default attribute dedicated to the object detection label, with type of <strong>List</strong>. The upper left corner of the image is used as the coordinate origin [0, 0]. Each coordinate point is represented by [x, y], where x indicates the horizontal coordinate and y indicates the vertical coordinate (both x and y are &gt;=0). The format of each shape is as follows:</p>
<ul><li><p><strong>bndbox</strong> consists of two points, for example, <strong>[[0,10],[50,95]]</strong>. The upper left vertex of the rectangle is the first point, and the lower right vertex is the second point. That is, the x-coordinate of the first point must be less than the x-coordinate of the second point, and the y-coordinate of the first point must be less than the y-coordinate of the second point.</p>
</li><li><p><strong>polygon</strong>: consists of multiple points that are connected in sequence to form a polygon, for example, <strong>[[0,100],[50,95],[10,60],[500,400]]</strong>.</p>
</li><li><p><strong>circle</strong>: consists of the center and radius, for example, <strong>[[100,100],[50]]</strong>.</p>
</li><li><p><strong>line</strong>: consists of two points, for example, <strong>[[0,100],[50,95]]</strong>. The first point is the start point, and the second point is the end point.</p>
</li><li><p><strong>dashed</strong>: consists of two points, for example, <strong>[[0,100],[50,95]]</strong>. The first point is the start point, and the second point is the end point.</p>
</li><li><p><strong>point</strong>: consists of one point, for example, <strong>[[0,100]]</strong>.</p>
</li><li><p><strong>polyline</strong>: consists of multiple points, for example, <strong>[[0,100],[50,95],[10,60],[500,400]]</strong>.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:from</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>ID of the head entity in the triplet relationship label, which is a default attribute dedicated to the triplet relationship label.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:hard</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>Sample labeled as a hard sample or not, which is a default attribute. Options:</p>
<ul><li><p><strong>0/false</strong>: not a hard example</p>
</li><li><p><strong>1/true</strong>: hard example</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:hard_coefficient</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>Coefficient of difficulty of each label level, which is a default attribute. The value range is <strong>[0,1]</strong>.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:hard_reasons</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>Reasons that the sample is a hard sample, which is a default attribute. Use a hyphen (-) to separate every two hard sample reason IDs, for example, <strong>3-20-21-19</strong>. Options:</p>
<ul><li><p><strong>0</strong>: No target objects are identified.</p>
</li><li><p><strong>1</strong>: The confidence is low.</p>
</li><li><p><strong>2</strong>: The clustering result based on the training dataset is inconsistent with the prediction result.</p>
</li><li><p><strong>3</strong>: The prediction result is greatly different from the data of the same type in the training dataset.</p>
</li><li><p><strong>4</strong>: The prediction results of multiple consecutive similar images are inconsistent.</p>
</li><li><p><strong>5</strong>: There is a large offset between the image resolution and the feature distribution of the training dataset.</p>
</li><li><p><strong>6</strong>: There is a large offset between the aspect ratio of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>7</strong>: There is a large offset between the brightness of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>8</strong>: There is a large offset between the saturation of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>9</strong>: There is a large offset between the color richness of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>10</strong>: There is a large offset between the definition of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>11</strong>: There is a large offset between the number of frames of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>12</strong>: There is a large offset between the standard deviation of area of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>13</strong>: There is a large offset between the aspect ratio of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>14</strong>: There is a large offset between the area portion of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>15</strong>: There is a large offset between the edge of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>16</strong>: There is a large offset between the brightness of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>17</strong>: There is a large offset between the definition of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>18</strong>: There is a large offset between the stack of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>19</strong>: The data enhancement result based on GaussianBlur is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>20</strong>: The data enhancement result based on fliplr is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>21</strong>: The data enhancement result based on Crop is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>22</strong>: The data enhancement result based on flipud is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>23</strong>: The data enhancement result based on scale is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>24</strong>: The data enhancement result based on translate is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>25</strong>: The data enhancement result based on shear is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>26</strong>: The data enhancement result based on superpixels is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>27</strong>: The data enhancement result based on sharpen is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>28</strong>: The data enhancement result based on add is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>29</strong>: The data enhancement result based on invert is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>30</strong>: The data is predicted to be abnormal.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:shape</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>Object shape, which is a default attribute dedicated to the object detection label and is left empty by default. Options:</p>
<ul><li><p><strong>bndbox</strong>: rectangle</p>
</li><li><p><strong>polygon</strong>: polygon</p>
</li><li><p><strong>circle</strong>: circle</p>
</li><li><p><strong>line</strong>: straight line</p>
</li><li><p><strong>dashed</strong>: dotted line</p>
</li><li><p><strong>point</strong>: point</p>
</li><li><p><strong>polyline</strong>: polyline</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:source</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>Speech source, which is a default attribute dedicated to the speech start/end point label and can be set to a speaker or narrator.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:start_index</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>Start position of the text, which is a default attribute dedicated to the named entity label. The start value begins from 0, including the character corresponding to the value of <strong>start_index</strong>.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:start_time</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>Speech start time, which is a default attribute dedicated to the speech start/end point label, in the format of <strong>hh:mm:ss.SSS</strong>. (<strong>hh</strong> indicates hour; <strong>mm</strong> indicates minute; <strong>ss</strong> indicates second; and <strong>SSS</strong> indicates millisecond.)</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.1 "><p>@modelarts:to</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.14.2.5.1.3 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.14.2.5.1.4 "><p>ID of the tail entity in the triplet relationship label, which is a default attribute dedicated to the triplet relationship label.</p>
</td>
</tr>
</tbody>
</table>
</div>

<div class="tablenoborder"><a name="EN-US_TOPIC_0000001909848204__request_SampleMetadata"></a><a name="request_SampleMetadata"></a><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__request_SampleMetadata" frame="border" border="1" rules="all"><caption><b>Table 15 </b>SampleMetadata</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.15.2.5.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.15.2.5.1.2"><p>Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.4.15.2.5.1.3"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="40%" id="mcps1.3.4.15.2.5.1.4"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.1 "><p>@modelarts:import_origin</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.3 "><p>Integer</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.15.2.5.1.4 "><p>Sample source, which is a built-in attribute.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.1 "><p>@modelarts:hard</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.3 "><p>Double</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.15.2.5.1.4 "><p>Whether the sample is labeled as a hard sample, which is a default attribute. Options:</p>
<ul><li><p><strong>0</strong>: non-hard sample</p>
</li><li><p><strong>1</strong>: hard sample</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.1 "><p>@modelarts:hard_coefficient</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.3 "><p>Double</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.15.2.5.1.4 "><p>Coefficient of difficulty of each sample level, which is a default attribute. The value range is <strong>[0,1]</strong>.</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.1 "><p>@modelarts:hard_reasons</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.3 "><p>Array of integers</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.15.2.5.1.4 "><p>ID of a hard sample reason, which is a default attribute. Options:</p>
<ul><li><p><strong>0</strong>: No object is identified.</p>
</li><li><p><strong>1</strong>: The confidence is low.</p>
</li><li><p><strong>2</strong>: The clustering result based on the training dataset is inconsistent with the prediction result.</p>
</li><li><p><strong>3</strong>: The prediction result is greatly different from the data of the same type in the training dataset.</p>
</li><li><p><strong>4</strong>: The prediction results of multiple consecutive similar images are inconsistent.</p>
</li><li><p><strong>5</strong>: There is a large offset between the image resolution and the feature distribution of the training dataset.</p>
</li><li><p><strong>6</strong>: There is a large offset between the aspect ratio of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>7</strong>: There is a large offset between the brightness of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>8</strong>: There is a large offset between the saturation of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>9</strong>: There is a large offset between the color richness of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>10</strong>: There is a large offset between the definition of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>11</strong>: There is a large offset between the number of frames of the image and the feature distribution of the training dataset.</p>
</li><li><p><strong>12</strong>: There is a large offset between the standard deviation of area of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>13</strong>: There is a large offset between the aspect ratio of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>14</strong>: There is a large offset between the area portion of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>15</strong>: There is a large offset between the edge of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>16</strong>: There is a large offset between the brightness of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>17</strong>: There is a large offset between the definition of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>18</strong>: There is a large offset between the stack of image frames and the feature distribution of the training dataset.</p>
</li><li><p><strong>19</strong>: The data enhancement result based on GaussianBlur is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>20</strong>: The data enhancement result based on fliplr is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>21</strong>: The data enhancement result based on Crop is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>22</strong>: The data enhancement result based on flipud is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>23</strong>: The data enhancement result based on scale is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>24</strong>: The data enhancement result based on translate is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>25</strong>: The data enhancement result based on shear is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>26</strong>: The data enhancement result based on superpixels is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>27</strong>: The data enhancement result based on sharpen is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>28</strong>: The data enhancement result based on add is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>29</strong>: The data enhancement result based on invert is inconsistent with the prediction result of the original image.</p>
</li><li><p><strong>30</strong>: The data is predicted to be abnormal.</p>
</li></ul>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.1 "><p>@modelarts:size</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.2 "><p>No</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.4.15.2.5.1.3 "><p>Array of objects</p>
</td>
<td class="cellrowborder" valign="top" width="40%" headers="mcps1.3.4.15.2.5.1.4 "><p>Image size (width, height, and depth of the image), which is a default attribute, with type of <strong>List&lt;Integer&gt;</strong>. In the list, the first number indicates the width (pixels), the second number indicates the height (pixels), and the third number indicates the depth (the depth can be left blank and the default value is <strong>3</strong>). For example, <strong>[100,200,3]</strong> and <strong>[100,200]</strong> are both valid. Note: This parameter is mandatory only when the sample label list contains the object detection label.</p>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section"><h4 class="sectiontitle">Response Parameters</h4><p><strong>Status code: 200</strong></p>

<div class="tablenoborder"><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__response_SmartTaskResp" frame="border" border="1" rules="all"><caption><b>Table 16 </b>Response body parameters</caption><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.5.3.2.4.1.1"><p>Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="20%" id="mcps1.3.5.3.2.4.1.2"><p>Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="60%" id="mcps1.3.5.3.2.4.1.3"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.5.3.2.4.1.1 "><p>task_id</p>
</td>
<td class="cellrowborder" valign="top" width="20%" headers="mcps1.3.5.3.2.4.1.2 "><p>String</p>
</td>
<td class="cellrowborder" valign="top" width="60%" headers="mcps1.3.5.3.2.4.1.3 "><p>Task ID.</p>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section"><h4 class="sectiontitle">Example Requests</h4><ul><li><p>Starting an Auto Labeling (Active Learning) Task</p>
<pre class="screen">{
  "task_type" : "auto-label",
  "collect_key_sample" : true,
  "config" : {
    "algorithm_type" : "fast"
  }
}</pre>
</li><li><p>Starting an Auto Labeling (Pre-labeling) Task</p>
<pre class="screen">{
  "task_type" : "pre-label",
  "model_id" : "c4989033-7584-44ee-a180-1c476b810e46",
  "collect_key_sample" : true,
  "config" : {
    "inf_config_list" : [ {
      "specification" : "modelarts.vm.cpu.2u",
      "instance_count" : 1
    } ]
  }
}</pre>
</li><li><p>Starting an Auto Grouping Task</p>
<pre class="screen">{
  "task_type" : "auto-grouping",
  "config" : {
    "n_clusters" : "2",
    "ambiguity" : false,
    "image_brightness" : false,
    "image_colorfulness" : false,
    "property" : "size",
    "result_type" : 1
  }
}</pre>
</li></ul>
</div>
<div class="section"><h4 class="sectiontitle">Example Responses</h4><p><strong>Status code: 200</strong></p>
<p>OK</p>
<pre class="screen">{
  "task_id" : "r0jT2zwxBDKf8KEnSuZ"
}</pre>
</div>
<div class="section"><h4 class="sectiontitle">Status Codes</h4>
<div class="tablenoborder"><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001909848204__status_code" frame="border" border="1" rules="all"><thead align="left"><tr><th align="left" class="cellrowborder" valign="top" width="15%" id="mcps1.3.8.2.1.3.1.1"><p>Status Code</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="85%" id="mcps1.3.8.2.1.3.1.2"><p>Description</p>
</th>
</tr>
</thead>
<tbody><tr><td class="cellrowborder" valign="top" width="15%" headers="mcps1.3.8.2.1.3.1.1 "><p>200</p>
</td>
<td class="cellrowborder" valign="top" width="85%" headers="mcps1.3.8.2.1.3.1.2 "><p>OK</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="15%" headers="mcps1.3.8.2.1.3.1.1 "><p>401</p>
</td>
<td class="cellrowborder" valign="top" width="85%" headers="mcps1.3.8.2.1.3.1.2 "><p>Unauthorized</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="15%" headers="mcps1.3.8.2.1.3.1.1 "><p>403</p>
</td>
<td class="cellrowborder" valign="top" width="85%" headers="mcps1.3.8.2.1.3.1.2 "><p>Forbidden</p>
</td>
</tr>
<tr><td class="cellrowborder" valign="top" width="15%" headers="mcps1.3.8.2.1.3.1.1 "><p>404</p>
</td>
<td class="cellrowborder" valign="top" width="85%" headers="mcps1.3.8.2.1.3.1.2 "><p>Not Found</p>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="section"><h4 class="sectiontitle">Error Codes</h4><p>See <a href="modelarts_03_0095.html">Error Codes</a>.</p>
</div>
</div>
<div>
<div class="familylinks">
<div class="parentlink"><strong>Parent topic:</strong> <a href="dataset_management.html">Data Management</a></div>
</div>
</div>