update hpo docs (#289)

alibaba · Sep 19, 2022 · 97af5b0 · 97af5b0
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diff --git a/docs/images/automl/nni_metric.png b/docs/images/automl/nni_metric.png
diff --git a/docs/images/automl/nni_stop.png b/docs/images/automl/nni_stop.png
diff --git a/docs/source/automl/pai_nni_hpo.md b/docs/source/automl/pai_nni_hpo.md
@@ -18,9 +18,8 @@ python setup.py install
 ### 下载安装hpo-tools
 
 ```
-pip install https://automl-nni.oss-cn-beijing.aliyuncs.com/nni/hpo_tools/hpo_tools-0.1.0-py3-none-any.whl
-wget https://automl-nni.oss-cn-beijing.aliyuncs.com/nni/hpo_tools/download_examples.py
-python download_examples.py
+wget https://automl-nni.oss-cn-beijing.aliyuncs.com/nni/hpo_tools/scripts/install_hpo_tools.sh
+bash install_hpo_tools.sh
 cd examples/search/maxcompute_easyrec
 ```
 
@@ -226,6 +225,27 @@ auc_is_valid_play=1
 点击每个Trial No，可以看到每个参数Trial的日志、参数详情,报错和输出可以点击以下3个按钮。
 ![image.png](../../images/automl/pai_nni_log.jpg)
 
+### 手动停止某组实验超参
+
+如果某些参数的结果不太好，可以进行手动停止。
+例如停止第一组参数。
+![image.png](../../images/automl/nni_stop.png)
+
+### 多目标default metric查看
+
+假设用户配置的metric_config为如下，那么UI中Default metric中显示3项；该组trial最终的metric
+
+- default=auc\*0.5+accuracy\*0.5
+- auc即为最终的auc值
+- accuracy即为最终的accuracy值
+
+```
+auc=0.5
+accuracy=0.5
+```
+
+![image.png](../../images/automl/nni_metric.png)
+
 ## finetune训练（可选）
 
 由于推荐业务每天都有实时更新的数据，如果用户采用先训练一批历史数据，后面每天finetune更新模型的话，可以利用以上begin调优的最优结果，再在新数据上微调。如果用户每次更新模型都是重新开始训练的话，则不需要此步骤。

diff --git a/easy_rec/__init__.py b/easy_rec/__init__.py
@@ -2,8 +2,8 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 import logging
 import os
-import sys
 import platform
+import sys
 
 import tensorflow as tf
 

diff --git a/easy_rec/python/ops/gen_kafka_ops.py b/easy_rec/python/ops/gen_kafka_ops.py
@@ -25,6 +25,7 @@
   if os.path.exists(kafka_ops_path):
     kafka_module = tf.load_op_library(kafka_ops_path)
 
+
 @tf_export('io_kafka_dataset_v2')
 def io_kafka_dataset_v2(topics,
                         servers,