Merge branch 'zouap_static' of git.openi.org.cn:OpenI/aiforge into zouap_static

options/locale/locale_en-US.ini

@@ -3210,11 +3210,11 @@ wrong_specification=You cannot use this specification, please choose another ite
 resource_use=Resource Occupancy
 
 job_name_rule = Please enter letters, numbers, _ and - up to 64 characters and cannot end with a dash (-).
-train_dataset_path_rule = The dataset location is stored in the environment variable <strong style="color:#010101">data_url</strong>, the pre-trained model is storaged in the environment <strong style="color:#010101">ckpt_url</strong>, and the output path is stored in the environment variable <strong style="color:#010101">train_url</strong>.
-infer_dataset_path_rule = The dataset location is stored in the environment variable <strong style="color:#010101">data_url</strong>, and the output path is stored in the environment variable <strong style="color:#010101">result_url</strong>.
+train_dataset_path_rule = The dataset location is stored in the run parameter <strong style="color:#010101">data_url</strong>, the pre-trained model is storaged in the run parameter <strong style="color:#010101">ckpt_url</strong>, and the output path is stored in the run parameter <strong style="color:#010101">train_url</strong>.
+infer_dataset_path_rule = The dataset location is stored in the run parameter <strong style="color:#010101">data_url</strong>, and the output path is stored in the run parameter <strong style="color:#010101">result_url</strong>.
 view_sample = View sample
-inference_output_path_rule = The inference output path is stored in the environment variable result_url.
-model_file_path_rule=The model file location is stored in the environment variable ckpt_url
+inference_output_path_rule = The inference output path is stored in the run parameter result_url.
+model_file_path_rule=The model file location is stored in the run parameter ckpt_url
 model_file_postfix_rule = The supported format of the model file is [ckpt, pb, h5, json, pkl, pth, t7, pdparams, onnx, pbtxt, keras, mlmodel, cfg, pt]
 model_convert_postfix_rule = The supported format of the model file is [.pth, .pkl, .onnx, .mindir, .ckpt, .pb]
 delete_task = Delete task
@@ -3247,8 +3247,8 @@ Stopped_success_update_status_fail=Succeed in stopping th job, but failed to upd
 load_code_failed=Fail to load code, please check if the right branch is selected.
 
 error.dataset_select = dataset select error：the count exceed the limit or has same name
-new_train_gpu_tooltips = The code is storaged in <strong style="color:#010101">%s</strong>, the dataset is storaged in <strong style="color:#010101">%s</strong>, the pre-trained model is storaged in the environment <strong style="color:#010101">%s</strong>, and please put your model into <strong style="color:#010101">%s</strong> then you can download it online
-new_train_npu_tooltips = The code is storaged in <strong style="color:#010101">%s</strong>, the pre-trained model is storaged in the environment <strong style="color:#010101">%s</strong>, and please put your model into <strong style="color:#010101">%s</strong> then you can download it online
+new_train_gpu_tooltips = The code is storaged in <strong style="color:#010101">%s</strong>, the dataset is storaged in <strong style="color:#010101">%s</strong>, the pre-trained model is storaged in the run parameter <strong style="color:#010101">%s</strong>, and please put your model into <strong style="color:#010101">%s</strong> then you can download it online
+new_train_npu_tooltips = The code is storaged in <strong style="color:#010101">%s</strong>, the pre-trained model is storaged in the run parameter <strong style="color:#010101">%s</strong>, and please put your model into <strong style="color:#010101">%s</strong> then you can download it online
 new_infer_gpu_tooltips = The dataset is stored in <strong style="color:#010101">%s</strong>, the model file is stored in <strong style="color:#010101">%s</strong>, please store the inference output in <strong style="color:#010101">%s</strong> for subsequent downloads.
 
 [points]

options/locale/locale_zh-CN.ini

@@ -3228,11 +3228,11 @@ card_type = 卡类型
 wrong_specification=您目前不能使用这个资源规格，请选择其他资源规格。
 
 job_name_rule = 请输入字母、数字、_和-，最长64个字符，且不能以中划线（-）结尾。
-train_dataset_path_rule = 数据集位置存储在环境变量<strong style="color:#010101">data_url</strong>中，预训练模型存放在环境变量<strong style="color:#010101">ckpt_url</strong>中，训练输出路径存储在环境变量<strong style="color:#010101">train_url</strong>中。
-infer_dataset_path_rule = 数据集位置存储在环境变量<strong style="color:#010101">data_url</strong>中，推理输出路径存储在环境变量<strong style="color:#010101">result_url</strong>中。
+train_dataset_path_rule = 数据集位置存储在运行参数 <strong style="color:#010101">data_url</strong> 中，预训练模型存放在运行参数 <strong style="color:#010101">ckpt_url</strong> 中，训练输出路径存储在运行参数 <strong style="color:#010101">train_url</strong> 中。
+infer_dataset_path_rule = 数据集位置存储在运行参数 <strong style="color:#010101">data_url</strong> 中，推理输出路径存储在运行参数 <strong style="color:#010101">result_url</strong> 中。
 view_sample = 查看样例
-inference_output_path_rule = 推理输出路径存储在环境变量result_url中。
-model_file_path_rule = 模型文件位置存储在环境变量ckpt_url中。
+inference_output_path_rule = 推理输出路径存储在运行参数 result_url 中。
+model_file_path_rule = 模型文件位置存储在运行参数 ckpt_url 中。
 model_file_postfix_rule = 模型文件支持的格式为 [ckpt, pb, h5, json, pkl, pth, t7, pdparams, onnx, pbtxt, keras, mlmodel, cfg, pt]
 model_convert_postfix_rule = 模型文件支持的格式为 [.pth, .pkl, .onnx, .mindir, .ckpt, .pb]
 delete_task = 删除任务
@@ -3266,9 +3266,9 @@ load_code_failed=代码加载失败，请确认选择了正确的分支。
 
 
 error.dataset_select = 数据集选择错误：数量超过限制或者有同名数据集
-new_train_gpu_tooltips =训练脚本存储在<strong style="color:#010101">%s</strong>中，数据集存储在<strong style="color:#010101">%s</strong>中，预训练模型存放在环境变量<strong style="color:#010101">%s</strong>中，训练输出请存储在<strong style="color:#010101">%s</strong>中以供后续下载。
-new_train_npu_tooltips =训练脚本存储在<strong style="color:#010101">%s</strong>中，预训练模型存放在环境变量<strong style="color:#010101">%s</strong>中，训练输出请存储在<strong style="color:#010101">%s</strong>中以供后续下载。
-new_infer_gpu_tooltips = 数据集存储在<strong style="color:#010101">%s</strong>中，模型文件存储在<strong style="color:#010101">%s</strong>中，推理输出请存储在<strong style="color:#010101">%s</strong>中以供后续下载。
+new_train_gpu_tooltips = 训练脚本存储在 <strong style="color:#010101">%s</strong> 中，数据集存储在 <strong style="color:#010101">%s</strong> 中，预训练模型存放在运行参数 <strong style="color:#010101">%s</strong> 中，训练输出请存储在 <strong style="color:#010101">%s</strong> 中以供后续下载。
+new_train_npu_tooltips = 训练脚本存储在 <strong style="color:#010101">%s</strong> 中，预训练模型存放在运行参数 <strong style="color:#010101">%s</strong> 中，训练输出请存储在 <strong style="color:#010101">%s</strong> 中以供后续下载。
+new_infer_gpu_tooltips = 数据集存储在 <strong style="color:#010101">%s</strong> 中，模型文件存储在 <strong style="color:#010101">%s</strong> 中，推理输出请存储在 <strong style="color:#010101">%s</strong> 中以供后续下载。
 
 [points]
 points = 积分

templates/repo/modelsafety/indicators_descr.tmpl

@@ -13,10 +13,10 @@
                   <td data-label="指标">ACC</td>
                   <td data-label="说明" indicator="ACC">Accuracy：精确度，计算模型预测准确率，该指标越高，说明评测结果越好。</td>
               </tr>
-              <tr>
+             <!-- <tr>
                   <td data-label="指标">CAV</td>
                   <td data-label="说明" indicator="CAV">Classification Accuracy Variance：用于评估深度学习模型性能的最重要指标为准确性。该指标值越高，说明评测结果越好。</td>
-              </tr>
+              </tr>  -->
               <tr>
                   <td data-label="指标">ASS</td>
                   <td data-label="说明" indicator="ASS">Average Structural Similarity：所有攻击成功对抗样本与其原始样本间的平均相似性。该指标越大，说明评测结果越好。</td>

templates/repo/modelsafety/new.tmpl

@@ -272,7 +272,7 @@
                         <input type="text" style="display:none;" name="evaluation_index" />
                         <select id="job_indicators" class="ui dropdown width48 v-middle" multiple style='width:385px;'>
                             <option value="ACC">ACC</option>
-                            <option value="CAV">CAV</option>
+                           <!-- <option value="CAV">CAV</option>-->
                             <option value="ASS">ASS</option>
                             <option value="ALDp">ALDp</option>
                             <option value="ACAC">ACAC</option>