Repository: PaddlePaddle/PaddleTS (language: python)

Issue:
Revise docs and comments of util:get_uuid
Revise docs and comments of util:get_uuid


Discussion / hints:

Fix patch:
diff --git a/README_en.md b/README_en.md
index ce6058de..2f8e2985 100644
--- a/README_en.md
+++ b/README_en.md
@@ -49,15 +49,17 @@ In future, more advanced features will be coming, including:
 
 Specifically, PaddleTS consists of the following modules:
 
-| Module                                                                                                     | Description                                                                                                                     |
-|------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------|
-| [**paddlets.datasets**](https://paddlets.readthedocs.io/en/latest/source/modules/datasets/overview.html)   | Unified time series representation (TSDataset) and data repository with pre-built TSDatasets.                                   |
-| [**paddlets.transform**](https://paddlets.readthedocs.io/en/latest/source/modules/transform/overview.html) | Data preprocessing and data transformations.                                                                                    |
-| [**paddlets.models**](https://paddlets.readthedocs.io/en/latest/source/modules/models/overview.html)       | PaddlePaddle-based deep nueral network models for time series modeling.                                                         |
-| [**paddlets.pipeline**](https://paddlets.readthedocs.io/en/latest/source/modules/pipeline/overview.html)   | Pipeline for building time sereis analysis and modeling workflows.                                                             |
-| [**paddlets.metrics**](https://paddlets.readthedocs.io/en/latest/source/modules/metrics/overview.html)     | Metrics for measuring the performance of a model.                                                                               |
-| [**paddlets.analysis**](https://paddlets.readthedocs.io/en/latest/source/modules/analysis/overview.html)   | Quick data exploration and advanced data analysis.                                                                              |
-| [**paddlets.utils**](https://paddlets.readthedocs.io/en/latest/source/modules/backtest/overview.html)      | Utility functions.                                                                                                              |
+
+| Module                                                                                                     | Description                                                                                   |
+|------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------|
+| [**paddlets.datasets**](https://paddlets.readthedocs.io/en/latest/source/modules/datasets/overview.html)   | Unified time series representation (TSDataset) and data repository with pre-built TSDatasets. |
+| [**paddlets.transform**](https://paddlets.readthedocs.io/en/latest/source/modules/transform/overview.html) | Data preprocessing and data transformations.                                                  |
+| [**paddlets.models**](https://paddlets.readthedocs.io/en/latest/source/modules/models/overview.html)       | PaddlePaddle-based deep neural network models for time series modeling.                       |
+| [**paddlets.pipeline**](https://paddlets.readthedocs.io/en/latest/source/modules/pipeline/overview.html)   | Pipeline for building time series analysis and modeling workflows.                            |
+| [**paddlets.metrics**](https://paddlets.readthedocs.io/en/latest/source/modules/metrics/overview.html)     | Metrics for measuring the performance of a model.                                             |
+| [**paddlets.analysis**](https://paddlets.readthedocs.io/en/latest/source/modules/analysis/overview.html)   | Quick data exploration and advanced data analysis.                                            |
+| [**paddlets.utils**](https://paddlets.readthedocs.io/en/latest/source/modules/backtest/overview.html)      | Utility functions.                                                                            |
+
 
 ## Installation
 
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.datasets.tsdataset.po b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.datasets.tsdataset.po
index f092cd57..4f30eed7 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.datasets.tsdataset.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.datasets.tsdataset.po
@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PaddleTS \n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2022-07-21 21:09+0800\n"
+"POT-Creation-Date: 2022-07-25 16:27+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: LANGUAGE <LL@li.org>\n"
@@ -18,93 +18,92 @@ msgstr ""
 "Generated-By: Babel 2.10.3\n"
 
 #: ../../source/api/paddlets.datasets.tsdataset.rst:2
-#: 65f88756bc1349c3b84a7bf20c4bfc80
+#: 1673e4311cd14113b4d77bca6c609963
 msgid "paddlets.datasets.tsdataset"
 msgstr ""
 
-#: 32cc3f481f8c4b76af552ca6c514d56b 3c99399c5d7942d7b4d24f7d9d52a457
-#: paddlets.datasets.tsdataset:1 paddlets.datasets.tsdataset.TSDataset:1 of
+#: 4e60a7f937e449c6ab88a8ac096006c5 bd9b4930f02f4b05b590f8e62a668842 of
+#: paddlets.datasets.tsdataset:1 paddlets.datasets.tsdataset.TSDataset:1
 msgid ""
-"TSDataset is the fundamental data class in PaddleTS, which is designed as the "
-"first-class citizen to represent the time series data. It is widely used "
-"in PaddleTS. In many cases, a function consumes a TSDataset and produces "
-"another TSDataset. A TSDataset object is comprised of two kinds of time "
-"series data:"
+"TSDataset is the fundamental data class in PaddleTS, which is designed as"
+" the first-class citizen to represent the time series data. It is widely "
+"used in PaddleTS. In many cases, a function consumes a TSDataset and "
+"produces another TSDataset. A TSDataset object is comprised of two kinds "
+"of time series data:"
 msgstr ""
 "``TSDataset`` 是 `PaddleTS` "
 "中一个主要的类结构，用于表示绝大多数的时序样本数据，并作为PaddleTS其他算子的输入以及输出对象。TSDataset 包涵两类时序数据："
 
-#: 7b85718b0f0c4c2e97e02177887327c7 paddlets.datasets.tsdataset:5
-#: paddlets.datasets.tsdataset.TSDataset:5 cdbd9c215f0a44ab87d29c50975ad7f6 of
+#: 763b0e7f41c446429fdbff543a61227c eb7b58167c2f40f0938483103f220cfb of
+#: paddlets.datasets.tsdataset:5 paddlets.datasets.tsdataset.TSDataset:5
 msgid ""
 "Target:  the key time series data in the time series modeling tasks (e.g."
 " those needs to be forecasted in the time series forecasting tasks)."
-msgstr ""
-"待预测目标：表示希望被预测的时序序列"
+msgstr "待预测目标：表示希望被预测的时序序列"
 
+#: 08faa418c8e04c13802675573edca410 8440b0ca9ec9467e828622f0cfa4f628 of
 #: paddlets.datasets.tsdataset:6 paddlets.datasets.tsdataset.TSDataset:6
-#: dde9fe557ee347d388ada4a718331e35 f7dce75c4e4d42c2a534319c1be3fa1e of
 msgid ""
 "Covariate: the relevant time series data which are usually helpful for "
 "the time series modeling tasks."
 msgstr "协变量：无需被预测的时间序列，协变量的加入通常用于辅助提高模型预测的效果"
 
-#: 4a7109bd7cde443a9230c0db1ba47154 paddlets.datasets.tsdataset:8
-#: paddlets.datasets.tsdataset.TSDataset:8 d9c1d0d61a094138a8686ecc94342a33 of
+#: 18557d073e9f48c3933ea5c236b2ad56 82118b537af0462d967ce79f6e35ff14 of
+#: paddlets.datasets.tsdataset:8 paddlets.datasets.tsdataset.TSDataset:8
 msgid "Currently, it supports the representation of:"
 msgstr "TSDataset支持的时序样本数据可以分为："
 
-#: 8567a1ec87f948459f031ef573903d29 bf33b86999234dbe92de24ba776ee6a4
-#: paddlets.datasets.tsdataset:10 paddlets.datasets.tsdataset.TSDataset:10 of
+#: 31126ef0a30944b8b52a60df8c9d66ee 68c124049a6a4bfdba8dc78b821c2e19 of
+#: paddlets.datasets.tsdataset:10 paddlets.datasets.tsdataset.TSDataset:10
 msgid "Time series of single target w/wo covariates."
 msgstr "单变量数据，只包含单列的预测目标，同时可以包涵单列或者多列协变量"
 
-#: 14cda7435df149eabb9e7f6383f804c4 bedf63e703ff4040a57b64cd1777ce3f
-#: paddlets.datasets.tsdataset:11 paddlets.datasets.tsdataset.TSDataset:11 of
+#: 02dd0c80b92844098ff112041de5713d f423f368275f41a5b90c2a9ca8b879ee of
+#: paddlets.datasets.tsdataset:11 paddlets.datasets.tsdataset.TSDataset:11
 msgid "Time series of multiple targets w/wo covariates."
 msgstr "多变量数据，包涵多列预测目标，同时可以包涵单列或者多列协变量"
 
-#: 48b2958e6dd54517ba86dda3e140cf71 a4ca7add16de4c1f9b18f0c50038fa7c
-#: paddlets.datasets.tsdataset:13 paddlets.datasets.tsdataset.TSDataset:13 of
+#: b81cf2a0142448ee9d92dd95dd7d63f3 ca23b66a45d24170834ff70a14c98dbd of
+#: paddlets.datasets.tsdataset:13 paddlets.datasets.tsdataset.TSDataset:13
 msgid "And the covariates can be categorized into one of the following 3 types:"
 msgstr "我们将非预测目标变量定义为协变量，在时序数据中，协变量可分为以下三种："
 
-#: 054f2a77a58d46458788a8d3c1d5d3bc aa8ae322ddad4bfe9a06c05d2ec93128
-#: paddlets.datasets.tsdataset:16 paddlets.datasets.tsdataset.TSDataset:16 of
+#: 2228bae98af442c5b4e755ec6078dc4f 29fddd153af74b49af20a22eb52f4817 of
+#: paddlets.datasets.tsdataset:16 paddlets.datasets.tsdataset.TSDataset:16
 msgid "Observed covariates (`observed_cov`):"
 msgstr "观测协变量 (`observed_cov`)"
 
-#: ae56e89cce6541d584ed111068719e5e paddlets.datasets.tsdataset:16
-#: paddlets.datasets.tsdataset.TSDataset:16 ca06d29b6d2547d4ace0e679f1a340fa of
+#: 1ff917727db447578c826dfba18cd0e1 5621bbe18b1745f090ce64b1e6583d71 of
+#: paddlets.datasets.tsdataset:16 paddlets.datasets.tsdataset.TSDataset:16
 msgid ""
 "referring to those variables which can only be observed in the historical"
 " data, e.g. measured temperatures"
 msgstr "指只能在历史中观察到的变量数据，例如测量的温度"
 
-#: 298711330b6a47b786d4c6fd64280753 paddlets.datasets.tsdataset:19
-#: paddlets.datasets.tsdataset.TSDataset:19 d8fa5567886a477a8270e7bc000735ba of
+#: 25bc5ac00f734b51a68e70e4f20ec016 e2fa15cb4a4248928df667bd43d57c15 of
+#: paddlets.datasets.tsdataset:19 paddlets.datasets.tsdataset.TSDataset:19
 msgid "Known covariates (`known_cov`):"
 msgstr "可预知协变量 (`known_cov`)"
 
-#: ad63f305aa3d436fa050975c6fe55620 paddlets.datasets.tsdataset:19
-#: paddlets.datasets.tsdataset.TSDataset:19 f8529568901f464ab3006ec9c5eeb6ae of
+#: 6122a0258ad94ccc84e0afeb3e1f4313 6c94c612bb204114aba10b5ee0482299 of
+#: paddlets.datasets.tsdataset:19 paddlets.datasets.tsdataset.TSDataset:19
 msgid ""
 "referring to those variables which can be determined at present for "
 "future time steps, e.g. weather forecasts"
 msgstr "指可在预测未来时间已知的变量，例如天气预报"
 
-#: 4ecbd4c5ed0047f98130d27805ac6e66 9fcf52087a164b978c940b2e68b2a491
-#: paddlets.datasets.tsdataset:22 paddlets.datasets.tsdataset.TSDataset:22 of
+#: 81b0039e0fe446af9237185bdb09a1b7 a0b1b21ab6034fa19761877f3724a853 of
+#: paddlets.datasets.tsdataset:22 paddlets.datasets.tsdataset.TSDataset:22
 msgid "Static covariates (`static_cov`):"
 msgstr "静态协变量 (`static_cov`)"
 
-#: 198dafaab2db4b8cb0ad5fafb5f7a58b 20876adb361a4fd5a14b02f307a95c48
-#: paddlets.datasets.tsdataset:22 paddlets.datasets.tsdataset.TSDataset:22 of
+#: 37b35f7f9f2f48b08e86e6d33d76410b f096650061c949739aab51123d294be6 of
+#: paddlets.datasets.tsdataset:22 paddlets.datasets.tsdataset.TSDataset:22
 msgid "referring to those variables which keep constant over time"
 msgstr "指整个时间范围内保持不变的变量"
 
-#: 1b687bdb828448b4a15a1a220872ba96 59e3b32d3a0a40fdbc1823ba64fb1988
-#: paddlets.datasets.tsdataset:24 paddlets.datasets.tsdataset.TSDataset:24 of
+#: 8635d030fa194c9ea80c74e4d4639317 f9c545cbade641dd9ba0c730eac78197 of
+#: paddlets.datasets.tsdataset:24 paddlets.datasets.tsdataset.TSDataset:24
 msgid ""
 "A TSDataset object includes one or more TimeSeries objects, representing "
 "targets, known covariates (known_cov), observed covariates "
@@ -113,12 +112,13 @@ msgstr ""
 "一个 ``TSDataset`` 对象由一个或者多个 ``TimeSeries`` 对象构成，每个 ``TimeSeries`` "
 "可分别代表target（待预测目标）， observed_covariate（观测协变量）以及known_covariate（可预知协变量）。"
 
-#: 78dbb72dfb8f4bb5bd6f63e1ec7fc472 paddlets.datasets.tsdataset.TSDataset:1
-#: paddlets.datasets.tsdataset.TimeSeries:1 f434f15de8484bfba5f82dc4c5350fe5 of
+#: ea0d6beb4ee64aaa8ea34ab4d1710e0c f26b33fdc7cc4d9dbbdc69845e0bb4a9 of
+#: paddlets.datasets.tsdataset.TSDataset:1
+#: paddlets.datasets.tsdataset.TimeSeries:1
 msgid "Bases: :py:class:`object`"
 msgstr ""
 
-#: 59b8edc95f9d484ab3d644747e27f813 paddlets.datasets.tsdataset.TimeSeries:1 of
+#: fa1d29afde234b97a309c65b03a88a2e of paddlets.datasets.tsdataset.TimeSeries:1
 msgid ""
 "TimeSeries is the atomic data structure for representing target(s), "
 "observed covariates (observed_cov), and known covariates (known_cov). "
@@ -127,26 +127,30 @@ msgstr ""
 "TimeSeries 是用于表示时序数据的最小粒度。可以分别代表target, observed_covariate "
 "或者known_covariate 其中一种类型。TimeSeries本身可以是单变量或者多变量。"
 
-#: 008df79d43be462887c00321a9dea7ab 096a61d39d644560b423c54a75f31f0f
-#: 19b4f2f9563946349728e7a698d0847c 2b13dcfeb62c478abdc2ab610d575ed6
-#: 2c30ecbf2cc7456b9b64e3254031705f 30ae4af43e86432195bedb9400918304
-#: 50bd7e92c04749cdbe2d6fce5c8f9983 52025ac1e90046799e5a9d412fadf948
-#: 567223a3d8ad4f8994393a268125bf91 5e9314c1ac6c4faf85e20468224285a8
-#: 6cdaac5628c9414aa507fc8968e74716 74f3f926f96a410aac670c1a50a9b4e3
-#: 795a1c4f3b0f45e297431ba7cb4c5ba4 7d8abe28698e4db9a77f89decd024191
-#: 8763f7b68b2e49b594df415fa9740003 89788c824c494070b4f47ef3a7d0545d
-#: 89b405a579fe426da19c83b73a1354fc 97f4adb4c674448a899cb50f97243c4d
-#: a070e1407c614d03b007fcc903f27a6b a2016a53cb3c494bb4d811efcab994d3
-#: a54f6989d5ee4e0590a525947e6dc812 a5f509a7d5374bcf978429527c6e538c
-#: ad1d66a126d4402bbd7656bb9a1cad81 af665bdbdb0a47f5ae9af91a94d1e2dd
-#: paddlets.datasets.tsdataset.TSDataset paddlets.datasets.tsdataset.TSDataset.astype
+#: 048f32641f1a46b5a350e44c924f65ac 078cc99c7c4b4cba811bee3afd02dda0
+#: 0a7c3003078a45d885f086ea54b166b6 0bae9a2872964641bfa6591de15a70c9
+#: 0fe71cbfae844dddaeb5a1981c12ed9a 0ffabdf9c4034ea5b13068c16f99fb17
+#: 2e79e5ef0fca448eabe2a195289b42a3 2fe35e5462604770b3c95c49a5c089c2
+#: 338f0c0a63714cb9ab23c5398a530ead 362532b051654122b85ff2f54098833e
+#: 44e5520395dc4e9d805248a0eab93814 5e552418f6834c4a9a006800745ea742
+#: 686df4a4b25c445184e699317fc907ea 68895c1bb0c54ad39d1a6f459e6959e4
+#: 6e0924deaa8e4a519d983c6e88f15486 6ea643f76bf84c9fad263d3654cb218d
+#: 6ed8938282ed459d94bb1528237b2d61 6f5befdfdaac422c91dbdd773f6d8b46
+#: 78957585a6a048b5be0bf83e227af6e8 88aec5c2a8834bc985ac4abfeb4fb6ea
+#: 89cf288c84e140ca908fbe20aba74610 a3aa02d97b3f40a48490221c1345df91
+#: af88ebd89e764ab6983ed85398492a9d be570dfd430a43df9e729c9aca4cdd31
+#: c5488d52749640bebd9acd2f45e20f1c cf43266d144445fea0c7511f7f9d80b0
+#: d53c7480eff2400d86a95c65f14fb619 e0dfaa136af54dd290e8f8100f4b6c50
+#: e19f1f105f41466fb77d60a30fbdbcae of paddlets.datasets.tsdataset.TSDataset
+#: paddlets.datasets.tsdataset.TSDataset.astype
 #: paddlets.datasets.tsdataset.TSDataset.concat
 #: paddlets.datasets.tsdataset.TSDataset.drop
 #: paddlets.datasets.tsdataset.TSDataset.get_item_from_column
 #: paddlets.datasets.tsdataset.TSDataset.load
 #: paddlets.datasets.tsdataset.TSDataset.load_from_csv
 #: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe
-#: paddlets.datasets.tsdataset.TSDataset.plot paddlets.datasets.tsdataset.TSDataset.save
+#: paddlets.datasets.tsdataset.TSDataset.plot
+#: paddlets.datasets.tsdataset.TSDataset.save
 #: paddlets.datasets.tsdataset.TSDataset.set_column
 #: paddlets.datasets.tsdataset.TSDataset.set_known_cov
 #: paddlets.datasets.tsdataset.TSDataset.set_observed_cov
@@ -155,7 +159,8 @@ msgstr ""
 #: paddlets.datasets.tsdataset.TSDataset.sort_columns
 #: paddlets.datasets.tsdataset.TSDataset.split
 #: paddlets.datasets.tsdataset.TSDataset.to_dataframe
-#: paddlets.datasets.tsdataset.TSDataset.to_numpy paddlets.datasets.tsdataset.TimeSeries
+#: paddlets.datasets.tsdataset.TSDataset.to_numpy
+#: paddlets.datasets.tsdataset.TimeSeries
 #: paddlets.datasets.tsdataset.TimeSeries.astype
 #: paddlets.datasets.tsdataset.TimeSeries.concat
 #: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point
@@ -164,40 +169,44 @@ msgstr ""
 #: paddlets.datasets.tsdataset.TimeSeries.sort_columns
 #: paddlets.datasets.tsdataset.TimeSeries.split
 #: paddlets.datasets.tsdataset.TimeSeries.to_dataframe
-#: paddlets.datasets.tsdataset.TimeSeries.to_numpy ce8c0e55be7941f79627d6cb8e7bc7b6
-#: d2f8df8bbaa34382a58f4f954d39c97b eacb5eacd18a4034b49d5dfb0424392d
-#: eddd35b727784cbf8cfc9aada67ef7ce fda3a15881434861ab05b1d6c8050158 of
+#: paddlets.datasets.tsdataset.TimeSeries.to_numpy
 msgid "Parameters"
 msgstr ""
 
-#: 144e4494c5b447ba93684df1d9af11c1 55d5621922a442a6b6936b90f5741345
+#: 283b9e1104dd446cb19d48e8c304ffec 3940125f8f8a40c490902787b9d47ca9 of
 #: paddlets.datasets.tsdataset.TimeSeries:4
-#: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:3 of
+#: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:3
 msgid "A Pandas DataFrame or Series containing the time series data"
 msgstr "样本数据，可以是目标变量或者协变量"
 
-#: 1c81550efb614c98965adb5b5dbc3620 paddlets.datasets.tsdataset.TimeSeries:6
+#: 053bfc7e0e8f46d48475ea3106431925 eb24ff8658e44dd79406fac4edbd3ffa of
+#: paddlets.datasets.tsdataset.TimeSeries:6
 #: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:11
-#: c5c43adb422346fc83007446f999326a of
 msgid ""
 "A string or int representing the Pandas DateTimeIndex's frequency or "
 "RangeIndex's step size"
 msgstr "样本数据频率，用于调整data以及配合fillna进行空行填充"
 
-#: 0653c28ce67e4ab09c2f3cfaa907831a 0ae015d95f5f42858f90d1d8b3434f3d
-#: 0fcf67cec62342c6be2c0df5d4eb472b 16dbc9ffcb6a4c13a8e8999d3854e944
-#: 247b816257854609ab54610c9911472d 30f898d0276b4182a023b1fdf79ff5d1
-#: 338b395cb3e84e899fd2923b05bf97b4 3f41fb874fc5444182f194d22fb8471d
-#: 458858bc118b46d3bcfbbe7d2a2bd2b9 539e3a1b5cd94e4c9b3d7834dc021663
-#: 558aa06ee5874e1c9b3c0bdc79858d13 5cb50dbbfcb54804a9fc29b62d92331e
-#: 5de76fd3c6ad48809b4e7d3339dbd4e0 70535790127642a9a02fea0e2dea55d9
-#: 7ea0f283b48646efba9bbebae3c74e3a 8044d7c185274dc6882b8b1c1df6e37b
-#: 86041a7ccd55489fac095e2231e01d1f 86d76e698f1e49738e82880418c126b7
-#: 8c5a7b4f28ed4ffdb0305767bfe52d56 8f81237971fc41728b52e670e348ae16
-#: 98c61079c1e1444ba8c72308198d1b0c b2e66814b0a14adbb7fef3872d695104
-#: b518cec2f6424d7293b1b1f95766d610 paddlets.datasets.tsdataset.TSDataset.columns
+#: 0eb692c5dfc949cb92e733b3447b7ecb 20d41f22c6fe4cf286d2b4b702f2b4c9
+#: 3b98b258dc884040adac4a0519be90a6 3ebb93c4b57a4dc696b7029276cbac64
+#: 40d8bbd309f24955a83d6f3c2bd9aa11 49468d2c4d9c446a890b39e1f88fb5fb
+#: 55f5f5cd538a4b2eb216b99a415db308 566f8f44229b46979ddb8d4faeb1afc9
+#: 5c4294259f2d440e8a298177c3f84fa0 5ef075c46f2d4c5183c91cc2d9064ab0
+#: 63e3a0b4ce6a476ab060a51c2329ad6c 6bb008b91bfa460fa565bd89fabb9bd5
+#: 72f2c139c61e40d08d5b20ca251b815a 793cb3be52de4787b8627aad995aa908
+#: 8b43d32025e4449bb61cb3506a7433fb 9342e4ef817c43f5bd3ad096ecec9bd3
+#: a450676a41ff4fe5a30c8597805ed0e2 a874c7127c0a47f089bba690ff62a75e
+#: ac737a9c19604d2b89639c702f20a9a4 ae6c5c95020b4f3d8e100f76845fe297
+#: b57506a217a64ba3b502741720a5e997 ba0b127c77bc4a30ac0b2c924ccce484
+#: bbc2fb760bc64aba9e84a14fd9e95ac3 c56e8fed55094f87b2605d04286f263a
+#: c5eb40fcd9f94514a4017049c86a4e48 ddaea1ced4eb4835a71f96b428d5c7d2
+#: eacb2831679d4bcdb2183b980c632faf ec602109d0de457ba4c11f6fa906a24e
+#: ef6fd2d4862d4a9fa00dc89406156781 f25cbf62cd174877b7cbd4efa5e08632
+#: fa9c614a422b4ae082bd26ded43db976 fe9d7da59648423c848e512500fa03e4 of
+#: paddlets.datasets.tsdataset.TSDataset.columns
 #: paddlets.datasets.tsdataset.TSDataset.concat
-#: paddlets.datasets.tsdataset.TSDataset.copy paddlets.datasets.tsdataset.TSDataset.drop
+#: paddlets.datasets.tsdataset.TSDataset.copy
+#: paddlets.datasets.tsdataset.TSDataset.drop
 #: paddlets.datasets.tsdataset.TSDataset.dtypes
 #: paddlets.datasets.tsdataset.TSDataset.get_all_cov
 #: paddlets.datasets.tsdataset.TSDataset.get_item_from_column
@@ -216,7 +225,8 @@ msgstr "样本数据频率，用于调整data以及配合fillna进行空行填
 #: paddlets.datasets.tsdataset.TSDataset.set_target
 #: paddlets.datasets.tsdataset.TSDataset.split
 #: paddlets.datasets.tsdataset.TSDataset.to_dataframe
-#: paddlets.datasets.tsdataset.TSDataset.to_numpy paddlets.datasets.tsdataset.TimeSeries
+#: paddlets.datasets.tsdataset.TSDataset.to_numpy
+#: paddlets.datasets.tsdataset.TimeSeries
 #: paddlets.datasets.tsdataset.TimeSeries.concat
 #: paddlets.datasets.tsdataset.TimeSeries.copy
 #: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point
@@ -224,93 +234,92 @@ msgstr "样本数据频率，用于调整data以及配合fillna进行空行填
 #: paddlets.datasets.tsdataset.TimeSeries.reindex
 #: paddlets.datasets.tsdataset.TimeSeries.split
 #: paddlets.datasets.tsdataset.TimeSeries.to_dataframe
-#: paddlets.datasets.tsdataset.TimeSeries.to_numpy c91e263da5b34f00ba0149da4e240342
-#: db133ff45bc0471aae5a182e189bdb06 ea217165af954e47832ef20df98dcfa3
-#: eb8fccdff52e44a29de0f02d62fb486e ef001b467d6c4139b465f73b8370f626
-#: f636890a176e4a2a81d483edcc7233ef fa74a07cbef949ddbf174bb5bd18b802
-#: fbb99dc1ab234a00b4ac1f9d204a36c7 fe09d294cf7a4886bfb0f0bf576dbb53 of
+#: paddlets.datasets.tsdataset.TimeSeries.to_numpy
 msgid "Returns"
 msgstr ""
 
-#: 72be6f7eef5a4075bb2099541024b26d 7a5b4b9772e640c9998be945c515bf08
-#: a65c6d163efd43e89bcf49422f8cd079 bb9bca439f63442db209c54f99975994
+#: 33225ced17cf4f06ad881fd111afaa34 b0e19735b93840a79dd67642ad557c2c
+#: c5c0b797e1f946dcb2b97bcf9c0e7df8 c686afc1b1f6470ca30eedbef0245493
+#: e42235adf0284fc6bc11f129b6cba49b f1a164bf986f4626a89242246191a7d7
+#: f77c2b433bac4719801ce28fd2acd62e of
 #: paddlets.datasets.tsdataset.TSDataset.drop:6
 #: paddlets.datasets.tsdataset.TSDataset.set_column:11
 #: paddlets.datasets.tsdataset.TSDataset.set_known_cov:4
 #: paddlets.datasets.tsdataset.TSDataset.set_observed_cov:4
 #: paddlets.datasets.tsdataset.TSDataset.set_static_cov:6
 #: paddlets.datasets.tsdataset.TSDataset.set_target:4
-#: paddlets.datasets.tsdataset.TimeSeries:9 eb956407fe404b29a3f16bdb78e46b68
-#: f825501e4f72461eba32a90b0fb187f4 fa66fbf2d1724709a6bafd32eaa30e9e of
+#: paddlets.datasets.tsdataset.TimeSeries:9
 msgid "None"
 msgstr "None"
 
-#: 7401e5ba157d47629d4add5b92caeace
-#: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:1 of
+#: 0217334e8add4e27ba7a9a43272fcfd6 of
+#: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:1
 msgid "Construct a TimeSeries object from the specified columns of a DataFrame"
 msgstr "基于DataFrame构建TimeSeries"
 
-#: 75612239f45f4868a5c855a8881ffbea
-#: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:5 of
+#: 198d9df5d300408b8523a1fb5def1415 of
+#: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:5
 msgid ""
 "The name of time column, a Pandas DatetimeIndex or RangeIndex. If not "
 "set, the DataFrame's index will be used."
 msgstr "时间列，可以是DatetimeIndex或者RangeIndex类型，如果为None，将index作为时间列"
 
-#: 4b7328df02974570a32f926044dbcdcd
-#: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:8 of
+#: d17a1dfa2a2f47a6962e4d2b751b7c84 of
+#: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:8
 msgid ""
 "The name of column or the list of columns from which to extract the time "
 "series data. If set to `None`, all columns except for the time column "
 "will be used as value columns."
 msgstr "data中需要选取的数据，如果不指定，数据中所有列（除时间列外）都会被导入"
 
-#: 2fff5fde3b7549468868a9e1d5217e6d
-#: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:14 of
+#: 9f9f389796de433587c9b2ac756197ce of
+#: paddlets.datasets.tsdataset.TimeSeries.load_from_dataframe:14
 msgid "TimeSeries object"
 msgstr "构建完成的TimeSeries数据"
 
+#: 02d823c22c864dec9676972f01283cb8 of
 #: paddlets.datasets.tsdataset.TimeSeries.time_index:1
-#: cdc98e84eaa04fbf80526d28244c1248 of
 msgid "the time index"
 msgstr ""
 
-#: paddlets.datasets.tsdataset.TimeSeries.columns:1 d826752963074a07bf2deab0ec5e3596
-#: of
+#: 5532772d58644bc4b9e02fbf9e1137bd of
+#: paddlets.datasets.tsdataset.TimeSeries.columns:1
 msgid "the data columns"
 msgstr "数据的列信息"
 
-#: 67fd69655ab34c2ca54b5e643da3e785
-#: paddlets.datasets.tsdataset.TimeSeries.start_time:1 of
+#: 72079660b27842e4a609e645f95842c5 of
+#: paddlets.datasets.tsdataset.TimeSeries.start_time:1
 msgid "the first value of the time index"
 msgstr "时序数据中第一个时间点"
 
-#: 03905e1ea0874c69a48606e00c7889c6
-#: paddlets.datasets.tsdataset.TimeSeries.end_time:1 of
+#: 4a53b39258464ea6a00155696b04322f of
+#: paddlets.datasets.tsdataset.TimeSeries.end_time:1
 msgid "the last value of the time index"
 msgstr "时序数据中最后一个时间点"
 
-#: 2d6cf818e84e400b9cb1b0cd1bd8cdfc paddlets.datasets.tsdataset.TimeSeries.data:1 of
+#: 61da80b885fc419abbd5967f35adc583 of
+#: paddlets.datasets.tsdataset.TimeSeries.data:1
 msgid "DataFrame storing the data"
 msgstr "包含的DataFrame类型的成员"
 
-#: paddlets.datasets.tsdataset.TimeSeries.freq:1 c37a753470ad49209dad0d6c03a8e11e of
+#: d90f96b93c6c45df9e2bac4dcd36b9cc of
+#: paddlets.datasets.tsdataset.TimeSeries.freq:1
 msgid "Frequency of TimeSeries"
 msgstr "时序频率"
 
-#: 8e58a6f3dd664fcc8a1dc3626206e782 paddlets.datasets.tsdataset.TimeSeries.dtypes:1
-#: of
+#: bf6489a9a60b45128eb241d2cc0fb37b of
+#: paddlets.datasets.tsdataset.TimeSeries.dtypes:1
 msgid "dtypes of TimeSeries"
 msgstr "数据类型"
 
-#: 800905bffe1f459ca3ddc4ae27a786b8 paddlets.datasets.tsdataset.TimeSeries.astype:1
-#: of
+#: 327243aa7b1d4bcf98d9bd68a9ec15e1 of
+#: paddlets.datasets.tsdataset.TimeSeries.astype:1
 msgid "Cast a TimeSeries object to the specified dtype"
 msgstr "转换数据类型，注意这里不会返回一个新的数据，而是在原始数据集上修改"
 
-#: 7b3276f2fc2d428493c090af19f99d69 9fabeedfc65a4805bda0fff8e1b91131
+#: 3fe58f143af24da287c3ffbdb6c11b38 ab1924f0dae94315bb685440b5b31cf4 of
 #: paddlets.datasets.tsdataset.TSDataset.astype:3
-#: paddlets.datasets.tsdataset.TimeSeries.astype:3 of
+#: paddlets.datasets.tsdataset.TimeSeries.astype:3
 msgid ""
 "Use a numpy.dtype or Python type to cast entire TimeSeries object to the "
 "same type. Alternatively, use {col: dtype, …}, where col is a column "
@@ -321,13 +330,15 @@ msgstr ""
 "type或者是dict类型，直接调用df.astype使用，numpy.dtype|Python type代表对所有列做变换， "
 "dict代表对某一列或者几列做转换"
 
-#: 1d134707c26b4531a4725588f1cab2ff 2bf1b81001034333addc3293f8e0e897
-#: 5af0f3098cba464fb3d7765798f4394f 5d91f80bbcd84762a55aa90a3763cd99
-#: 66e20268f1f84502b1ab8e919f1b6927 6efd8c1fd0ce47748ce6806df2695d16
-#: 79a294b2f92240e6b384678cd270bfb2 8a3fba9685a849d39837d99612d7a91b
-#: 8ac17db85a194e7ba13c143f11aeb7a3 92bbb91fae4642d69d0bd5d601710bd7
-#: 98fce20fb56f453590970b6d2c94fd4e 9c9b15cfca554789802aa199cc9370bf
-#: 9ff18e71567e48f7acc8df6ea9b26ace paddlets.datasets.tsdataset.TSDataset.astype
+#: 0fcabebf080442e58f0c0dadc582c852 1789d21a26c74b658fc364ddb72eed7b
+#: 3b24fac087a5443b820fc91fc6ca9b91 4afb8dc2443b4e189d4b3e4ee104ba2b
+#: 55ea6a491b2d4e6cb49d04c6ca54500c 564ae6c25e7a4e9788f5139deb7b7632
+#: 6685070a388c4badbfbc84b6154a864c 76a71925f58d4e01a75a01f554cae8f8
+#: 82a833d910094636a5426648821a06fa 8e77c38c5fc44e15b4eb536a955da532
+#: af10f0efe0864fedaa57e75b74dadef8 b4d30b783e994c70b04adfa9ca3f43c3
+#: daa31e888ec4460899217608fba18788 e1e5cda2c3f24a6f8bc513a2526c9acd
+#: ee20fdbcd7e64113bdef2d8899655600 ef05e058455b46bb8f75f5a4befc8bdf of
+#: paddlets.datasets.tsdataset.TSDataset.astype
 #: paddlets.datasets.tsdataset.TSDataset.concat
 #: paddlets.datasets.tsdataset.TSDataset.drop
 #: paddlets.datasets.tsdataset.TSDataset.get_item_from_column
@@ -342,34 +353,33 @@ msgstr ""
 #: paddlets.datasets.tsdataset.TimeSeries.concat
 #: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point
 #: paddlets.datasets.tsdataset.TimeSeries.reindex
-#: paddlets.datasets.tsdataset.TimeSeries.split c705557755c44654a8ef6c21d638c4b4
-#: d56522166f804668b5b5d3765d71ee09 d748e3727cac4e188807c9acc3b9b2fc of
+#: paddlets.datasets.tsdataset.TimeSeries.split
 msgid "Raises"
 msgstr ""
 
+#: 302bee00de3e45f0bd9a34a8ef4cbd40 of
 #: paddlets.datasets.tsdataset.TimeSeries.to_dataframe:1
-#: d88a90bf75d149558db4b71ce6088718 of
 msgid "Return a pd.DataFrame representation of the TimeSeries object"
 msgstr "TimeSeries转换成DataFrame数据"
 
-#: bd5e3fa045ca46e5b6f7b0b7c38b655d
-#: paddlets.datasets.tsdataset.TimeSeries.to_dataframe:3 of
+#: 01a45c23101048feb7552b76fd3edadc of
+#: paddlets.datasets.tsdataset.TimeSeries.to_dataframe:3
 msgid "Return a copy or reference"
 msgstr "返回拷贝或者引用"
 
-#: a5bb5cb955a9400d9ecefffe1b7845b3 b35c5d084e9e4f6f87a0636785c20af4
+#: 24110c801d2d4fe3b439d4c868f556eb d5d7db30156e4bb8819e2212ca66d643 of
 #: paddlets.datasets.tsdataset.TSDataset.to_dataframe:6
-#: paddlets.datasets.tsdataset.TimeSeries.to_dataframe:6 of
+#: paddlets.datasets.tsdataset.TimeSeries.to_dataframe:6
 msgid "pd.DataFrame"
 msgstr ""
 
-#: 2f08a1cc708a4618abb46d6ee902311f
-#: paddlets.datasets.tsdataset.TimeSeries.to_numpy:1 of
+#: c145a5f6789e4112a492f5248078a6b7 of
+#: paddlets.datasets.tsdataset.TimeSeries.to_numpy:1
 msgid "Return a numpy.ndarray representation of the TimeSeries object"
 msgstr "TimeSeries转换成np.ndarray数据"
 
+#: dfc3fe3d29f2426b9ff39e988943baaa of
 #: paddlets.datasets.tsdataset.TimeSeries.to_numpy:3
-#: f188d69c42564234957b15e9749719ea of
 msgid ""
 "Return a copy or reference. Note that copy=False does not ensure that "
 "to_numpy() is no-copy. Rather, copy=True ensure that a copy is made, even"
@@ -377,19 +387,19 @@ msgid ""
 "refer：https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_numpy.html"
 msgstr "True代表拷贝数据，False代表不拷贝数据即使设置了False，这里也可能会全量拷贝数据（例如当data中type类型不统一），使用的时候需要注意这里的性能消耗参考：https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_numpy.html"
 
-#: 2426b193870d4e6fb556be4dbf60d5df 6340f4023e074c34a1ced51e73779bef
+#: 7f33346183e84eaeac963fc0c4c34b81 ac1623e3d21541d7933cc0d204fc38d2 of
 #: paddlets.datasets.tsdataset.TSDataset.to_numpy:9
-#: paddlets.datasets.tsdataset.TimeSeries.to_numpy:9 of
+#: paddlets.datasets.tsdataset.TimeSeries.to_numpy:9
 msgid "np.ndarray"
 msgstr ""
 
-#: 35a107d56c354893a1e4c012912ac75a
-#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:1 of
+#: ad342afb82294ff48f57773a215603a9 of
+#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:1
 msgid "Convert a point along the time axis into an integer index."
 msgstr "将具体的时间点基于time_index转换成具体的index"
 
-#: 28b51f85a6d4498dac82912439d93790
-#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:3 of
+#: d389a3fe256647a4bba1df0a6e9dca6c of
+#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:3
 msgid ""
 "Time point, supports 3 types  `pd.Timestamp|str`: It only takes effect "
 "when the time_index type is pd.DatatimeIndex, the corresponding index is "
@@ -402,49 +412,51 @@ msgstr ""
 "时间点，支持三种类型：`pd.Timestamp|str`：只有当time_index类型是pd.DatatimeIndex的时候生效，返回对应的index，str会强制转换成pd.Timestamp；`float`：代表从头开始的比例，0到1之间，如0.8；"
 " `int`：直接返回具体的数值，不做转换"
 
-#: adba9887cec94154bd4aeddff96fd014
-#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:3 of
+#: e808d47c16df47bdbd2f92fa7eba9c3c of
+#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:3
 msgid "Time point, supports 3 types"
 msgstr ""
 
-#: 534405b7827b4745a1725dfdddb8693e
-#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:5 of
+#: b883c12038b54442a5c5e232c6fbab4b of
+#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:5
 msgid ""
 "`pd.Timestamp|str`: It only takes effect when the time_index type is "
 "pd.DatatimeIndex, the corresponding index is returned, and str will be "
 "forcibly converted to pd.DatatimeIndex"
 msgstr ""
 
-#: 5cc1a1d130a9446c932e75e787f9ce74
-#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:7 of
+#: 6c6c1df8750842c49c79062ae97343a8 of
+#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:7
 msgid ""
 "`float`: the parameter will be treated as the proportion of the time "
 "series that should lie before the point."
 msgstr ""
 
-#: 6e657714c21a4acb95d795a2df7f0696
-#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:9 of
+#: f67e598f197049fea7a9e29c71292da1 of
+#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:9
 msgid ""
 "`int`: the parameter will returned as such, provided that it is in the "
 "series. Otherwise it will raise a ValueError."
 msgstr ""
 
-#: 1c80d586e7df4257827505889d072a09
-#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:11 of
+#: fb735caaf7f94787bdfbd7f7c11c23ba of
+#: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:11
 msgid ""
 "If the provided pandas Timestamp is not in the time series index, whether"
 " to return the index of the next timestamp or the index of the previous "
 "one."
 msgstr "如果提供的pandas时间戳不在时间序列索引中，是否返回下一个时间戳或上一个时间戳的索引"
 
+#: 9fd8e5b755ab45c7a16f8c7d205b8867 of
 #: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point:15
-#: d579d3b17d1a4c2c82c34f12c3c722a7 of
 msgid "index"
 msgstr ""
 
-#: 109ea925b7ac4219ad2321ebbd558958 6018fc87c05b429eb2ec1d359705bb5c
-#: 67a6f098b9494a4a9d25336c968bea1f 7ac3a353190548ccb16615c7999d7754
-#: ab98ebe0e5ba46408720d94127d38b3b paddlets.datasets.tsdataset.TSDataset.columns
+#: 05488317cf984991b85b6e3063b6ab6d 11a30ad2d5a34d698d753084e6c7c85d
+#: 2033ea8a1e60472f9290e93eedd0d5f2 3ed18e7bdecb4e28abd5626c1b0f29e0
+#: 3f9e6239f8e34f879a3d3b2466fa4fc9 5c17ac90e0a44602bf3a553c1c43b9ea
+#: 737cd5428533439cae6e8c79efc87793 b32beb3b59864b7991ec048fd1157cd2 of
+#: paddlets.datasets.tsdataset.TSDataset.columns
 #: paddlets.datasets.tsdataset.TSDataset.dtypes
 #: paddlets.datasets.tsdataset.TSDataset.get_all_cov
 #: paddlets.datasets.tsdataset.TSDataset.get_known_cov
@@ -452,20 +464,18 @@ msgstr ""
 #: paddlets.datasets.tsdataset.TSDataset.get_static_cov
 #: paddlets.datasets.tsdataset.TSDataset.get_target
 #: paddlets.datasets.tsdataset.TimeSeries.get_index_at_point
-#: e068391e901b4fceb7968c6700fd6d99 f5051a8ea83e490ba38b600e96a8d95f
-#: f7816f1690a84c8c9ec4566fa854055e of
 msgid "Return type"
 msgstr ""
 
-#: 0d5af6b9eef4463eadda16e566015748 paddlets.datasets.tsdataset.TimeSeries.split:1
-#: of
+#: 02b3929232be4bad8d703e64751a0da0 of
+#: paddlets.datasets.tsdataset.TimeSeries.split:1
 msgid ""
 "Split the TimeSeries object into two TimeSeries objects according to "
 "`split_point`"
 msgstr "基于split_point拆分数据"
 
-#: 42f71623dc6e4114b903200ed85aba75 paddlets.datasets.tsdataset.TimeSeries.split:3
-#: of
+#: 8e1b3dcb89f943d9a831ca1b845596a7 of
+#: paddlets.datasets.tsdataset.TimeSeries.split:3
 msgid ""
 "Where to split the TSDataset, which could be  `pd.Timestamp|str`: Only "
 "valid when the type of time_index is pd.DatatimeIndex, and str will be "
@@ -475,69 +485,71 @@ msgid ""
 "will be included in the first TimeSeries object."
 msgstr "数据拆分的时间点，支持三种类型：`pd.Timestamp|str`：只有当time_index类型是pd.DatatimeIndex的时候生效，返回对应的index，str会强制转换成pd.Timestamp；`float`：代表第一份数据的拆分比例，0到1之间，如0.8，代表第一份数据占总量的80%，第二份20%；`int`：代表第一份数据的数据量。split_point点的数据如果存在，会包涵在第一份数据中"
 
-#: 0c12945f6c734f1ebd6576fecc59c70f 3190d8e18c8f4036875bb85fcdf51690
+#: 06f389e035814f9d95b67fc4be8f9ece 6ea5ad87f0cf4cf29f70f957303ebc7d of
 #: paddlets.datasets.tsdataset.TSDataset.split:3
-#: paddlets.datasets.tsdataset.TimeSeries.split:3 of
+#: paddlets.datasets.tsdataset.TimeSeries.split:3
 msgid "Where to split the TSDataset, which could be"
 msgstr ""
 
-#: 0be264bcd0c148e6bee989c468d6feb4 3666dbc3148f427bb8e72bb978cca40d
+#: 01300dd708cc43be8c46c64e55c1998f b57906f595254afcb0b9c48521324642 of
 #: paddlets.datasets.tsdataset.TSDataset.split:5
-#: paddlets.datasets.tsdataset.TimeSeries.split:5 of
+#: paddlets.datasets.tsdataset.TimeSeries.split:5
 msgid ""
 "`pd.Timestamp|str`: Only valid when the type of time_index is "
 "pd.DatatimeIndex, and str will be forcibly converted to pd.DatatimeIndex"
 msgstr ""
 
-#: 1000c4121365470e99daded2781a9a8d 91cd946184184e03a352059504be3757
+#: 3b021e9764d940f1b6a99c36a26cbfee 827745ea9192434cb1ca788de9bdb71b of
 #: paddlets.datasets.tsdataset.TSDataset.split:7
-#: paddlets.datasets.tsdataset.TimeSeries.split:7 of
+#: paddlets.datasets.tsdataset.TimeSeries.split:7
 msgid "`float`: The proportion of the length of the first TSDataset object"
 msgstr ""
 
-#: 280d935dad10441e897941c87a1794b3 b24a1676ba9a4979a7f67771832e5b4a
+#: 62f9a7f851c24f9a9b64be107ab95206 e03d5abbb5904481a12a92a166eb13dd of
 #: paddlets.datasets.tsdataset.TSDataset.split:9
-#: paddlets.datasets.tsdataset.TimeSeries.split:9 of
+#: paddlets.datasets.tsdataset.TimeSeries.split:9
 msgid "`int`: Only valid when the type of time_index is pd.RangeIndex"
 msgstr ""
 
-#: paddlets.datasets.tsdataset.TimeSeries.split:11 fefe13191b254165bccdcefae8e42ef2
-#: of
+#: d2fbf88af65748ce969dc34a0a62c7ee of
+#: paddlets.datasets.tsdataset.TimeSeries.split:11
 msgid ""
 "If the data of the split_point exists, it will be included in the first "
 "TimeSeries object."
 msgstr ""
 
-#: b8f325284abd49bd9598389b27fac3d0 paddlets.datasets.tsdataset.TimeSeries.split:13
-#: of
+#: 7eb99283aadb4281ab94c10cd2812dac of
+#: paddlets.datasets.tsdataset.TimeSeries.split:13
 msgid ""
 "If `split_point` (pd.TimeSeries) doesn't exist in the time index, use the"
 " next valid index (True) or the previous one (False)"
 msgstr "如果提供的pandas时间戳不在时间序列索引中，是否返回下一个时间戳或上一个时间戳的索引"
 
-#: 7054253070a84c629bb00ad8a629b0c5 paddlets.datasets.tsdataset.TimeSeries.split:16
-#: of
+#: 6bbdd257810a4f99a348287dff056caa of
+#: paddlets.datasets.tsdataset.TimeSeries.split:16
 msgid "Tuple[\"TimeSeries\", \"TimeSeries\"]"
 msgstr ""
 
-#: b5cc4c43d7fb47519c89219cc6f0c833 paddlets.datasets.tsdataset.TimeSeries.copy:1 of
+#: 409b82a1ddd34d10b721302b43f978b3 of
+#: paddlets.datasets.tsdataset.TimeSeries.copy:1
 msgid "Make a copy of the TimeSeries object"
 msgstr "返回一份拷贝的数据"
 
-#: 0c5835b977a24b84a9572edd90bdf030 15b99b2784224860b21dca5938962cdd
-#: 331f4104c69141c79a4f5f2e4bfd5e1f paddlets.datasets.tsdataset.TimeSeries.concat:11
+#: 6778dd7e9f454f31992bb8d38a9674e4 889e65357f824a0c802bf075061ee495
+#: c13e7d2996d54cd7a7bfad524a0aef67 of
+#: paddlets.datasets.tsdataset.TimeSeries.concat:11
 #: paddlets.datasets.tsdataset.TimeSeries.copy:3
-#: paddlets.datasets.tsdataset.TimeSeries.reindex:9 of
+#: paddlets.datasets.tsdataset.TimeSeries.reindex:9
 msgid "TimeSeries"
 msgstr ""
 
-#: 1308f3e555d64c2d96087d3a0208e465 paddlets.datasets.tsdataset.TimeSeries.concat:1
-#: of
+#: 0c6336a7327e4ae9b66a3a016c8c9cb0 of
+#: paddlets.datasets.tsdataset.TimeSeries.concat:1
 msgid "Concatenate a list of TimeSeries objects along the specified axis"
 msgstr "基于axis维度实现TimeSeries对象的连接"
 
-#: 886c4b3412cf40aab0ff27987b193927 paddlets.datasets.tsdataset.TimeSeries.concat:3
-#: of
+#: dbfc7795d74442378bbfcbf2b86818ac of
+#: paddlets.datasets.tsdataset.TimeSeries.concat:3
 msgid ""
 "A list of TimeSeries objects All TimeSeries' freqs are required to be "
 "consistent. When axis=1, time_col is required to be non-repetitive; when "
@@ -546,202 +558,188 @@ msgstr ""
 "TimeSeries元素列表，要求所有TimeSeries "
 "freq保持一致，当axis=1的时候，要求time_col不重复；axis=0的时候，要求所有columns不重复"
 
-#: 5f51646f4eeb41bc8958b53c6443eb67 paddlets.datasets.tsdataset.TSDataset.concat:8
-#: paddlets.datasets.tsdataset.TimeSeries.concat:8 fa3ab5c7620f43a6b6b9d2ebdcc81962
-#: of
+#: 12344021c44741dbbc29e053ef5a3154 21269de3b3fa461d9a57e525a5c2edeb of
+#: paddlets.datasets.tsdataset.TSDataset.concat:8
+#: paddlets.datasets.tsdataset.TimeSeries.concat:8
 msgid "The axis along which to concatenate the TimeSeries objects"
 msgstr "合并的维度，1是横向合并，0代表纵向合并"
 
-#: paddlets.datasets.tsdataset.TimeSeries.reindex:1 e540e87fefee40799377d2437b1e770f
-#: of
+#: b237f0132e7246c08019122c818af221 of
+#: paddlets.datasets.tsdataset.TimeSeries.reindex:1
 msgid "Reindex the TimeSeries object with optional filling logic"
 msgstr "对TimeSeries进行reindex"
 
-#: ad0feadf40774f1cad304e7036ac6b93 paddlets.datasets.tsdataset.TimeSeries.reindex:3
-#: of
+#: 4aa651391aae471b9f5108780328c0e6 of
+#: paddlets.datasets.tsdataset.TimeSeries.reindex:3
 msgid ""
 "array-like, new index to conform. Preferably an Index object to avoid "
 "duplicating data."
 msgstr "array-like类型，重新设定的index，要求不能重复"
 
-#: 46d8fcf2d815495c887334fb4db5fc7c paddlets.datasets.tsdataset.TimeSeries.reindex:5
-#: of
+#: 9dc6a65b52854bdbb66b8bcb4180eb55 of
+#: paddlets.datasets.tsdataset.TimeSeries.reindex:5
 msgid ""
 "Value to use for missing values. NaN by default, but can be any "
 "“compatible” value."
 msgstr "用于填充缺失点的值"
 
-#: 1510e2557aaa4ca8a7a1bf29816b8e0f 308f878e58fc44eaab6c75db2be32c24
+#: 2f06d765c00342958c8b7bb785647daf 9208daf1136d435ba9cd4b9c06395b03 of
 #: paddlets.datasets.tsdataset.TimeSeries.reindex:6
-#: paddlets.datasets.tsdataset.TimeSeries.reindex:7 of
+#: paddlets.datasets.tsdataset.TimeSeries.reindex:7
 msgid "Optional arguments passed to `DataFrame.reindex`"
 msgstr "其他传递给`DataFrame.reindex`的可选参数"
 
+#: 9db8d7dfc7114f3caa4988354ee03bfb of
 #: paddlets.datasets.tsdataset.TimeSeries.sort_columns:1
-#: e4839ace5c2c4156a913a7db817b96de of
 msgid "Sort the TimeSeries object by the index"
 msgstr "对data的columns进行排序"
 
-#: 308d598024b540318f442fb235b5e9dd
-#: paddlets.datasets.tsdataset.TimeSeries.sort_columns:3 of
+#: 870579d505f3453c82de2e43925b2ec6 of
+#: paddlets.datasets.tsdataset.TimeSeries.sort_columns:3
 msgid ""
 "Sort ascending or descending. When the index is a MultiIndex the sort "
 "direction can be controlled for each level individually."
 msgstr "升序或降序排序"
 
-#: 61198b1cf6284b33832221003c4e3fa0 paddlets.datasets.tsdataset.TSDataset:27 of
+#: 91dfb75eca3f41bca2797c828d8b275e of paddlets.datasets.tsdataset.TSDataset:27
 msgid "Target"
 msgstr "代表预测目标列，可能包涵多个预测目标"
 
-#: 9729d98e9c384b3ab7f941f59e6d01bb paddlets.datasets.tsdataset.TSDataset:29 of
+#: bf0a1e25e078419caa369ec99875066b of paddlets.datasets.tsdataset.TSDataset:29
 msgid "Observed covariates"
 msgstr "代表观测协变量"
 
-#: 82273017ddfe4c1ea1611d16f98b02cb paddlets.datasets.tsdataset.TSDataset:31 of
+#: 880a63d3c60543c5814f82f491279d61 of paddlets.datasets.tsdataset.TSDataset:31
 msgid "Known covariates"
 msgstr "代表已知协变量"
 
-#: paddlets.datasets.tsdataset.TSDataset:33 eaf8cc883c45415484cd36604b34f183 of
+#: 72e273eeac60499193868430b63f5629 of paddlets.datasets.tsdataset.TSDataset:33
 msgid "Static covariates"
 msgstr "静态协变量"
 
-#: 48bc86e4bfa5422297c19fbb96260b6d b1b98e4b721b4dc4a3f00eb7b933e37b
-#: paddlets.datasets.tsdataset.TSDataset:35
+#: 46a87d71acdb433f88d91383fbce5cb5 b4ebeaad417c4089996332f3ce695753
+#: bab0213a3bf74eceabb41f1fe6f07c9b of paddlets.datasets.tsdataset.TSDataset:35
 #: paddlets.datasets.tsdataset.TSDataset.load_from_csv:16
 #: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:15
-#: cb3f6e182e3248e8912e09c9c090c731 of
 msgid "Fill missing dates or not"
 msgstr "是否进行缺失值填充"
 
-#: 5f08bf50d8bb49bab8d0cad3894c5b07 paddlets.datasets.tsdataset.TSDataset:37 of
+#: 45fa233c75a343a180a6984b9ca4d9b9 bb9d74ad164f441489bd8506a5461ae0 of
+#: paddlets.datasets.tsdataset.TSDataset:37
+#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:17
 msgid ""
-"Method of filling missing values. Totally 8 methods are supported "
+"Method of filling missing values. Totally 7 methods are supported "
 "currently: max: Use the max value in the sliding window min: Use the min "
 "value in the sliding window avg: Use the mean value in the sliding window"
 " median:  Use the median value in the sliding window pre: Use the "
 "previous value back: Use the next value zero:  Use 0s"
 msgstr ""
-"默认为pre前项补全。共有8种补全数据缺失值的方法，包括:max: 使用局部窗口最大值补全缺失值信息。min: "
+"默认为pre前项补全。共有7种补全数据缺失值的方法，包括:max: 使用局部窗口最大值补全缺失值信息。min: "
 "使用局部窗口最小值补全缺失值信息。avg: 使用局部窗口均值补全缺失值信息。median: 使用局部窗口中位数数值补全缺失值信息。pre: "
 "使用前向数据补全数据信息。back: 使用后项数据补全数据信息。zero: 使用0值补全数据信息"
 
-#: 0fa803784d514902bead11d26e6a5646 182496fa940c4d539158101947e9a533
-#: 44fc7203108e452caeb6a62826de63a8 paddlets.datasets.tsdataset.TSDataset:46
+#: 7344a58fceb0449f81bb4710bb98aa06 c4f37f5f28ff4aefb8c904203cc42406
+#: ea7ccbd936fb4ba3b0a8476e6b72c42b of paddlets.datasets.tsdataset.TSDataset:46
 #: paddlets.datasets.tsdataset.TSDataset.load_from_csv:27
-#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:26 of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:26
 msgid "Size of the sliding window"
 msgstr "局部窗口长度，默认为10"
 
-#: 13f9d116eb414861a465748356881948
-#: paddlets.datasets.tsdataset.TSDataset.load_from_csv:1 of
+#: d931ec449472436f83ef6d3cfeeeb63e of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_csv:1
 msgid "Construct a TSDataset object from a csv file"
 msgstr "基于CSV文件构建TSDataset"
 
-#: afa61a60b34b4ab4a184648794a2f292
-#: paddlets.datasets.tsdataset.TSDataset.load_from_csv:3 of
+#: 49aa918cb5c442e3af5d08e35d0de610 of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_csv:3
 msgid ""
 "The path to the CSV file, or the file object; consistent with the "
 "argument of `pandas.read_csv` function"
 msgstr "csv文件或者文件对象地址, 通过`pandas.read_csv` 方法的构建"
 
-#: 1641e50ac79c4a839f586f7b27959813 4615206376e840fea46f7398910865d5
+#: 60844a0d07534b13b0eedb523add79ad f492083b65b04af7acd48a53f9d3b5a6 of
 #: paddlets.datasets.tsdataset.TSDataset.load_from_csv:6
-#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:5 of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:5
 msgid "The name of time column"
 msgstr "时间列，可以是DatetimeIndex或者RangeIndex类型，如果为None，将index作为时间列"
 
-#: 45bf6a10d4f743be9867e95c383640d5 63b45d39eefd4d58a8fcf662429572c9
+#: 4ddb91970ab84c11b5795e1e10b44947 8c631121809e43b0937c52ad30f99db1 of
 #: paddlets.datasets.tsdataset.TSDataset.load_from_csv:8
-#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:7 of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:7
 msgid "The names of columns for observed covariates"
 msgstr "代表观测协变量列名"
 
-#: 435253e29c954cdabc818a77f7907085 9c3690f3b5254701b4acaaf27b981808
+#: 1bbd84ceea794445b69290b93c596f38 b9b8fe9248e54f94abf6af32e3efbb14 of
 #: paddlets.datasets.tsdataset.TSDataset.load_from_csv:10
-#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:9 of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:9
 msgid "The names of columns for konwn covariates"
 msgstr "代表已知协变量列名"
 
-#: b155275dcd2b4eec857ab656cf2a2762
+#: 9ff79260e74b47d0b409743b986b6e8e b39725d72b1941a18ef664c4b41dabf5 of
 #: paddlets.datasets.tsdataset.TSDataset.load_from_csv:12
 #: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:11
-#: f56b85cabe0446ebbb466f574daf5f5f of
 msgid "The names of columns for static covariates"
 msgstr "静态协变量列名，需要同一列中全部数值一致"
 
-#: 51cf672d4ffb4da88b8fa09c91a552ec 59b8e41f9495407db9a191a84e694e4b
+#: 5089f0d23ecc43e8b2928dfa7af69d61 567cd181e6d848ae8363d9af9ba4866a of
 #: paddlets.datasets.tsdataset.TSDataset.load_from_csv:14
-#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:13 of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:13
 msgid ""
 "A str or int representing the DateTimeIndex's frequency or RangeIndex's "
 "step size"
 msgstr "样本数据频率，用于调整data以及配合fillna进行空行填充"
 
-#: 754d6f0f13874cf19f0a6c99005fb311
-#: paddlets.datasets.tsdataset.TSDataset.load_from_csv:18 of
+#: 13749b368a154bc0ba10384d528b4774 of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_csv:18
 msgid ""
-"Method of filling missing values. Totally 8 methods are supported "
+"Method of filling missing values. Totally 7 methods are supported "
 "currently: max: Use the max value in the sliding window min: Use the min "
 "value in the sliding window avg: Use the mean value in the sliding window"
 " median:  Use the median value in the sliding window pre: Use the "
 "previous value back: Use the next value zero:  Use 0"
 msgstr ""
-"默认为pre前项补全。共有8种补全数据缺失值的方法，包括:max: 使用局部窗口最大值补全缺失值信息。min: "
+"默认为pre前项补全。共有7种补全数据缺失值的方法，包括:max: 使用局部窗口最大值补全缺失值信息。min: "
 "使用局部窗口最小值补全缺失值信息。avg: 使用局部窗口均值补全缺失值信息。median: 使用局部窗口中位数数值补全缺失值信息。pre: "
 "使用前向数据补全数据信息。back: 使用后项数据补全数据信息。zero: 使用0值补全数据信息"
 
-#: 414c61e8f8e04bc8b402a3c566c4056c
-#: paddlets.datasets.tsdataset.TSDataset.load_from_csv:29 of
+#: 22ae9fdd01554d7b987e066c22a252cd of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_csv:29
 msgid "Optional arguments passed to `pandas.read_csv`"
 msgstr "传递给 `pandas.read_csv` 方法的可选参数"
 
-#: 2c6e43d3654548bd9ed487c8c68207b7
+#: 07b07a32c66f48afaa9e46e1f87ae9b9 d6ba40b6da4e4cd09ee43dd76d1a21bd of
 #: paddlets.datasets.tsdataset.TSDataset.load_from_csv:31
 #: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:29
-#: dfc74ea9d866446b8eb41f7d6774ae39 of
 msgid "TSDataset object"
 msgstr "构建完成后的TSDataset"
 
-#: 039e29306c854f9eb5720a8b092ec87b
-#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:1 of
+#: 2131e8dd55d54d9a872d64a7e1224ed0 of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:1
 msgid "Construct a TSDataset object from a DataFrame"
 msgstr "基于CSV文件构建完整TSDataset"
 
-#: 1ce5c8e2d80a4bd99ee8317dc7f3e77c
-#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:3 of
+#: 78c829605c0f4406beffc258004ecc78 of
+#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:3
 msgid "panas.DataFrame object from which to load data"
 msgstr "panas.DataFrame数据对象"
 
-#: paddlets.datasets.tsdataset.TSDataset.load_from_dataframe:17
-#: f4665fea32454920845548f0d3b6b2c6 of
-msgid ""
-"Method of filling missing values. Totally 7 methods are supported "
-"currently: max: Use the max value in the sliding window min: Use the min "
-"value in the sliding window avg: Use the mean value in the sliding window"
-" median:  Use the median value in the sliding window pre: Use the "
-"previous value back: Use the next value zero:  Use 0s"
-msgstr ""
-"默认为pre前项补全。共有8种补全数据缺失值的方法，包括:max: 使用局部窗口最大值补全缺失值信息。min: "
-"使用局部窗口最小值补全缺失值信息。avg: 使用局部窗口均值补全缺失值信息。median: 使用局部窗口中位数数值补全缺失值信息。pre: "
-"使用前向数据补全数据信息。back: 使用后项数据补全数据信息。zero: 使用0值补全数据信息"
-
+#: 4b108461028245c9b3b255a649a7bcde of
 #: paddlets.datasets.tsdataset.TSDataset.to_dataframe:1
-#: cb5796ba4a504c67be88d6907f5c92a3 of
 msgid "Return a pd.DataFrame representation of the TSDataset object"
 msgstr "TSDataset转换成DataFrame数据"
 
+#: d24fb1aeb4e3480d9e4b88d9ae8b3e34 of
 #: paddlets.datasets.tsdataset.TSDataset.to_dataframe:3
-#: ffc918c996b94e7e8370dfd73c4b0765 of
 msgid "Return a copy of or a reference to the underlying DataFrame objects"
 msgstr "True代表拷贝数据，False代表不拷贝数据，注意这里是浅拷贝，对于数序数据而言通常没有问题"
 
-#: 42f423f825d549e0bfca7a40ade2f794 paddlets.datasets.tsdataset.TSDataset.to_numpy:1
-#: of
+#: 61c67903a9884b1bb79461e497d726ef of
+#: paddlets.datasets.tsdataset.TSDataset.to_numpy:1
 msgid "Return a np.ndarray representation of the TSDataset object"
 msgstr "TSDataset转换成np.ndarray数据"
 
-#: paddlets.datasets.tsdataset.TSDataset.to_numpy:3 dd22103d51a8451ead96621b98ccc2a2
-#: of
+#: da563eba27744ec99725966a3cd8cb23 of
+#: paddlets.datasets.tsdataset.TSDataset.to_numpy:3
 msgid ""
 "Return a copy of or a reference to the underlying DataFrame objects, Note"
 " that copy=False does not ensure that to_numpy() is no-copy. Rather, "
@@ -749,83 +747,85 @@ msgid ""
 "refer：https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_numpy.html"
 msgstr "True代表拷贝数据，False代表不拷贝数据即使设置了False，这里也可能会全量拷贝数据（例如当data中type类型不统一），使用的时候需要注意这里的性能消耗参考：https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_numpy.html"
 
+#: 94db8e39ee3449fa9d74239aa5c08e2b of
 #: paddlets.datasets.tsdataset.TSDataset.get_target:1
-#: db2f261d5c8f4704a0d6950a64872897 of
 msgid "target"
 msgstr ""
 
-#: 323e4c03a7484c5ea8c05c1b5fc5feba
-#: paddlets.datasets.tsdataset.TSDataset.get_observed_cov:1 of
+#: 706c57594fcf46b9980afc00bfddf414 of
+#: paddlets.datasets.tsdataset.TSDataset.get_observed_cov:1
 msgid "observed_cov"
 msgstr ""
 
-#: 679ba7cedbb1445c982b44c6963052f4
-#: paddlets.datasets.tsdataset.TSDataset.get_known_cov:1 of
+#: 5cb55546a05d46ea9515c7293c3ed9fa of
+#: paddlets.datasets.tsdataset.TSDataset.get_known_cov:1
 msgid "known_cov"
 msgstr ""
 
+#: 229b56646c714205b6d37dc65b9c8d83 of
 #: paddlets.datasets.tsdataset.TSDataset.get_static_cov:1
-#: cc223d03b8ba4970977ba70b62cada98 of
 msgid "static_cov"
 msgstr ""
 
-#: ae7aefa0bd6248368198bda028b67fbc
-#: paddlets.datasets.tsdataset.TSDataset.get_all_cov:1 of
+#: cec51f688997462e8475dd93ece9f1b5 of
+#: paddlets.datasets.tsdataset.TSDataset.get_all_cov:1
 msgid "Merge observed_cov and konw_cov"
 msgstr "融合了observed_cov以及konw_cov的数据"
 
-#: 130610f928894014b7af6eb45a8a95a8
-#: paddlets.datasets.tsdataset.TSDataset.set_target:1 of
+#: 35d54bccd5a042268af170d005ee92a6 of
+#: paddlets.datasets.tsdataset.TSDataset.set_target:1
 msgid "New target"
 msgstr ""
 
-#: 36595952a81d4cab8505f8c0fb4fcc3c
-#: paddlets.datasets.tsdataset.TSDataset.set_observed_cov:1 of
+#: 2147d7b5b0ec4f05ba75fa0ad4604dd4 of
+#: paddlets.datasets.tsdataset.TSDataset.set_observed_cov:1
 msgid "New observed_cov"
 msgstr ""
 
-#: 59b149333ebd468585f3cf70f5401911
-#: paddlets.datasets.tsdataset.TSDataset.set_known_cov:1 of
+#: b57003b0a63f43d9a72b6b2055e134d0 of
+#: paddlets.datasets.tsdataset.TSDataset.set_known_cov:1
 msgid "New known_cov"
 msgstr ""
 
-#: 2bfb7c534e1f4f44be44004c1afcc8ad
-#: paddlets.datasets.tsdataset.TSDataset.set_static_cov:1 of
+#: 94c164f802bd4235a5eaeb0f36a089f3 of
+#: paddlets.datasets.tsdataset.TSDataset.set_static_cov:1
 msgid "New static_cov"
 msgstr ""
 
+#: cdc0d6f854c642b5920f048387668f70 of
 #: paddlets.datasets.tsdataset.TSDataset.set_static_cov:3
-#: dc4747449cd44c308770dcc58bac1fe7 of
 msgid "Append to the existing static_cov or replace the existing satic_cov"
 msgstr "True代表在原有static_cov基础上添加，False代表直接全部替换原有的static_cov"
 
-#: paddlets.datasets.tsdataset.TSDataset.target:1 e0cbc3722b4e45888f7519a709ff842d
-#: of
+#: 3aad5a68f6d44d4db537649c200892d3 of
+#: paddlets.datasets.tsdataset.TSDataset.target:1
 msgid "Returns: TimeSeries|None: target"
 msgstr ""
 
-#: 9b00e9e204aa4de68273bd837dc694cb
-#: paddlets.datasets.tsdataset.TSDataset.observed_cov:1 of
+#: d2faa5c53c5f46e58b3088d6cffaa027 of
+#: paddlets.datasets.tsdataset.TSDataset.observed_cov:1
 msgid "Returns: TimeSeries|None: observed_cov"
 msgstr ""
 
-#: 25af58e6e7ea4f21929b4181f229571e
-#: paddlets.datasets.tsdataset.TSDataset.known_cov:1 of
+#: 8bf3a84f247744dca269162f456c8199 of
+#: paddlets.datasets.tsdataset.TSDataset.known_cov:1
 msgid "Returns: TimeSeries|None: known_cov"
 msgstr ""
 
-#: 8c83e541cec84a99bd417cf9e0a8fb42
-#: paddlets.datasets.tsdataset.TSDataset.static_cov:1 of
+#: 5f3edeb665204ec9bc9df4c99dd4e793 of
+#: paddlets.datasets.tsdataset.TSDataset.static_cov:1
 msgid "Returns: dict|None: static_cov"
 msgstr ""
 
-#: paddlets.datasets.tsdataset.TSDataset.split:1 d8313af0cf344fe98dd82bb6e545cb37 of
+#: cfb7f4745a76461cb85ca9eacfb3a0cf of
+#: paddlets.datasets.tsdataset.TSDataset.split:1
 msgid ""
 "Splits the TSDataset object into two TSDataset objects according to "
 "`split_point`, only valid when `self._target` is not None"
 msgstr "基于split_point拆分数据, 仅当self._target不为None的时候生效"
 
-#: paddlets.datasets.tsdataset.TSDataset.split:3 dd6e059a0e2249129263fdc23dd03758 of
+#: 8cafcee3690a45ea82653f20bd499630 of
+#: paddlets.datasets.tsdataset.TSDataset.split:3
 msgid ""
 "Where to split the TSDataset, which could be  `pd.Timestamp|str`: Only "
 "valid when the type of time_index is pd.DatatimeIndex, and str will be "
@@ -835,60 +835,59 @@ msgid ""
 "will be included in the first data"
 msgstr "数据拆分的时间点，支持三种类型：`pd.Timestamp|str`：只有当time_index类型是pd.DatatimeIndex的时候生效，返回对应的index，str会强制转换成pd.Timestamp；`float`：代表第一份数据的拆分比例，0到1之间，如0.8，代表第一份数据占总量的80%，第二份20%；`int`：代表第一份数据的数据量。split_point点的数据如果存在，会包涵在第一份数据中"
 
-#: 6e151d196ea6447c97f418d0895e9136 paddlets.datasets.tsdataset.TSDataset.split:11
-#: of
+#: e98bf1aac74a4ff1b4361f7599e1cced of
+#: paddlets.datasets.tsdataset.TSDataset.split:11
 msgid ""
 "If the data of the split_point exists, it will be included in the first "
 "data"
 msgstr ""
 
-#: 71d8fd649e6742f9b88359bc0d220073 paddlets.datasets.tsdataset.TSDataset.split:13
-#: of
+#: a941d4261f174c28997f1d64631dc2c9 of
+#: paddlets.datasets.tsdataset.TSDataset.split:13
 msgid ""
 "If `split_point` (pd.TimeSeries) doesn't exist in the time column, use "
 "the next valid index (True) or the previous one (False)"
 msgstr "如果提供的pandas时间戳不在时间序列索引中，是否返回下一个时间戳或上一个时间戳的索引"
 
-#: b5639f59f41249489b0b37f4fc08d427 paddlets.datasets.tsdataset.TSDataset.split:17
-#: of
+#: e7813d7f78304c3b88f98c506e5a41b1 of
+#: paddlets.datasets.tsdataset.TSDataset.split:17
 msgid "Tuple[\"TSDataset\", \"TSDataset\"]"
 msgstr ""
 
-#: 2c14973e0e584f8696bbb102293727e1
-#: paddlets.datasets.tsdataset.TSDataset.get_item_from_column:1 of
+#: 0b7cf3db0292425092591c08f4438ec8 of
+#: paddlets.datasets.tsdataset.TSDataset.get_item_from_column:1
 msgid ""
 "Get the underlying TimeSeries object for targets, observed covariates, "
 "and know covariates, or the dict for static_covs according to the column "
 "name"
-msgstr "基于column名称返回其对应的类型的结合，包括target, observed_cov, known_cov, statuc_cov"
+msgstr "基于column名称返回其对应的类型的结合，包括target, observed_cov, known_cov, static_cov"
 
-#: 5e0654fc8a2d48a0b3f1e80e8d355359 b69ed873d3d54fc7b82bab69e09c7e0f
+#: 42a87711342e4415b6b39b8116353ebf cbc7004c925140b78d1d5f516ba76985 of
 #: paddlets.datasets.tsdataset.TSDataset.get_item_from_column:3
-#: paddlets.datasets.tsdataset.TSDataset.set_column:3 of
+#: paddlets.datasets.tsdataset.TSDataset.set_column:3
 msgid "column name"
 msgstr "column名称"
 
+#: 1567c27340d2428e8d5ec2b7a40d4229 of
 #: paddlets.datasets.tsdataset.TSDataset.get_item_from_column:6
-#: e386f21bd00446a89558d27c0be93dae of
 msgid "Union[\"TimeSeries\", dict]"
 msgstr ""
 
-#: 55209638c3b346d49e42ec78e478eefb
-#: paddlets.datasets.tsdataset.TSDataset.set_column:1 of
+#: 3d9fd49e2bf340609faf543cdfc14d54 of
+#: paddlets.datasets.tsdataset.TSDataset.set_column:1
 msgid "Add a new column or update the existing column"
 msgstr "设置某列columns的列元素, 支持新增和修改"
 
-#: 8379e0ef1cce46949af80bfa5d492690
-#: paddlets.datasets.tsdataset.TSDataset.set_column:5 of
+#: 0635f317768d45608b23b8f24f13a917 of
+#: paddlets.datasets.tsdataset.TSDataset.set_column:5
 msgid ""
 "New column values. When value=pd.Series, its index must be same as the "
 "index of the TSDataset object. When type='static_cov', value can only be "
 "int or str."
-msgstr ""
-"columns列内容，其index必须和目标属性的index相同，仅仅当columns是static_cov类型的时候，value才可以是int或者str"
+msgstr "columns列内容，其index必须和目标属性的index相同，仅仅当columns是static_cov类型的时候，value才可以是int或者str"
 
-#: 4306f750023f4849962e6557be2e84f9
-#: paddlets.datasets.tsdataset.TSDataset.set_column:8 of
+#: 6c0d8f0c23ea470e8c9f970a1e8eb911 of
+#: paddlets.datasets.tsdataset.TSDataset.set_column:8
 msgid ""
 "Only effective when adding a new column, where to put the new column. By "
 "default, the new column will be added to known_cov."
@@ -896,88 +895,101 @@ msgstr ""
 "设置的column类型，仅当新增的时候起作用，默认新增是known_cov类型，类型是target，known_cov, "
 "observed_cov, static_cov"
 
-#: 667e11ef3db845209d254738c359546d paddlets.datasets.tsdataset.TSDataset.drop:1 of
+#: e5aa0cfcb56b4e498b7b6d1491c9f4b2 of
+#: paddlets.datasets.tsdataset.TSDataset.drop:1
 msgid "Drop column or columns"
 msgstr "删除columns的列元素"
 
-#: 7bbfebd0e58c452fa2c7d18c4e67adf5 paddlets.datasets.tsdataset.TSDataset.drop:3 of
+#: 6794079966984d1faee3f65fcc06ba12 of
+#: paddlets.datasets.tsdataset.TSDataset.drop:3
 msgid "Column name or column names"
 msgstr "columns名称"
 
-#: 7b6484fa775948728b155f4b7f311e8c paddlets.datasets.tsdataset.TSDataset.plot:1 of
+#: bdbd12d76f0345da91f61a6b0e5959af of
+#: paddlets.datasets.tsdataset.TSDataset.plot:1
 msgid "plot function, a wrapper for Dataframe.plot()"
 msgstr "画图函数,对Dataframe.plot()的包装"
 
-#: 9c4723043bde456bbf386f68dba51098 paddlets.datasets.tsdataset.TSDataset.plot:3 of
+#: ec0776adbf1b44eda654be14ca57ba3f of
+#: paddlets.datasets.tsdataset.TSDataset.plot:3
 msgid ""
 "The names of columns to be plot. When columns is None, the targets will "
 "be plot by default."
 msgstr "指定打印的columns名称, columns为None时默认打印target"
 
-#: b327af0590f04b51bd40f19e02df5927 paddlets.datasets.tsdataset.TSDataset.plot:6 of
+#: 0b51774cc6524e4991602a72a783e103 of
+#: paddlets.datasets.tsdataset.TSDataset.plot:6
 msgid "Add data for joint plotprinting, the default is None"
 msgstr "添加数据进行联合打印, 默认为None"
 
-#: 41837dad5abf455597484972328c75af paddlets.datasets.tsdataset.TSDataset.plot:8 of
+#: f085c7e4454d4516ba771bf5266bb421 of
+#: paddlets.datasets.tsdataset.TSDataset.plot:8
 msgid "Custom labels, length should be equal to nums of added datasets."
 msgstr "为添加数据增加自定义标签，自定义标签的长度应该等于添加数据的数量"
 
-#: 2c24770b525f4c899960eb50091499fb paddlets.datasets.tsdataset.TSDataset.plot:10 of
+#: 5e466f2a93d84d90b813379bd03f1578 of
+#: paddlets.datasets.tsdataset.TSDataset.plot:10
 msgid "Optional arguments passed to `Dataframe.plot` function"
 msgstr "传入Dataframe.plot()的可选参数"
 
-#: 15ce9fe190ad459fb80998ba5e5ecbf8 paddlets.datasets.tsdataset.TSDataset.plot:12 of
+#: ec953d7176b149cc99432fa16617269c of
+#: paddlets.datasets.tsdataset.TSDataset.plot:12
 msgid "matplotlib.pyplot object"
 msgstr ""
 
-#: 6219191d1de04d0ab268cc08a3c38e20 paddlets.datasets.tsdataset.TSDataset.copy:1 of
+#: 52426746eead408cb9767257f99eb2f3 of
+#: paddlets.datasets.tsdataset.TSDataset.copy:1
 msgid "Make a copy of the TSDataset object"
 msgstr "返回一份拷贝的数据"
 
-#: 4a0465c6caef48b885ba7dcff8a67c66 a31bb9aeb3b540faa00ec6cc6647f684
-#: bdab049b5e4e4d10b931d2be702f4a80 paddlets.datasets.tsdataset.TSDataset.concat:11
+#: 30463d52e77749cfb6c784a321788c6a 94136ca9b19e4884a0f42d4fe803959a
+#: b7d87544eebb41f5aac7817e97d63229 of
+#: paddlets.datasets.tsdataset.TSDataset.concat:11
 #: paddlets.datasets.tsdataset.TSDataset.copy:3
-#: paddlets.datasets.tsdataset.TSDataset.load:6 of
+#: paddlets.datasets.tsdataset.TSDataset.load:6
 msgid "TSDataset"
 msgstr ""
 
-#: 4aeb43171ef942c8b8ceca4f084f6554 paddlets.datasets.tsdataset.TSDataset.save:1 of
+#: f5836a89b83240198969814c2ee8e3f2 of
+#: paddlets.datasets.tsdataset.TSDataset.save:1
 msgid "Save TSDataset object to a file"
 msgstr "保存对象到文件"
 
-#: 18497b602ca041fb96a6cf5f26ed96af 1b051f3d768041e2ab56b16b8bcded4b
+#: 2cbfc3843b424d9f890be9a0c295ea52 4399a3b90e1045d9abfae4faafe59c8b of
 #: paddlets.datasets.tsdataset.TSDataset.load:3
-#: paddlets.datasets.tsdataset.TSDataset.save:3 of
+#: paddlets.datasets.tsdataset.TSDataset.save:3
 msgid "file path"
 msgstr "文件路径"
 
-#: 3337a8b709cb4f6e9b3e53e02f27d4b2 paddlets.datasets.tsdataset.TSDataset.load:1 of
+#: 30d61be844e444e7999e2078753be185 of
+#: paddlets.datasets.tsdataset.TSDataset.load:1
 msgid "Load TSDataset from the saved file"
 msgstr "从文件中获取对象"
 
-#: 9696b759e6b94c7c88066e9e1b42e97c paddlets.datasets.tsdataset.TSDataset.columns:1
-#: of
+#: 66c84d41fb0142b798889d00e1af049f of
+#: paddlets.datasets.tsdataset.TSDataset.columns:1
 msgid "return all columns(except static columns)"
 msgstr "返回所有列名（除static外）"
 
-#: 0ad7d2d6b9dd437d8cb39c0a0a95dab5 paddlets.datasets.tsdataset.TSDataset.columns:3
-#: of
+#: a546e14190c64032a6273d18a8b81a99 of
+#: paddlets.datasets.tsdataset.TSDataset.columns:3
 msgid ""
 "The key is the column name, and the value is the type, including target, "
 "known_cov, and observed_cov"
 msgstr "key是columns名称，value是类型，包括target, known_cov, observed_cov"
 
-#: 9c981d98ae3e467a9e85966a73ea93e8 paddlets.datasets.tsdataset.TSDataset.freq:1 of
-msgid "the _freq"
-msgstr ""
+#: f1d800c51333483291f296f78b421cdc of
+#: paddlets.datasets.tsdataset.TSDataset.freq:1
+msgid "Frequency of TSDataset"
+msgstr "TSDataset数据频率"
 
-#: 0e6961ed37d343dc9ec412eb62fd55ec paddlets.datasets.tsdataset.TSDataset.concat:1
-#: of
+#: 33f7ca3b45984dd2906d387c9ed4f84a of
+#: paddlets.datasets.tsdataset.TSDataset.concat:1
 msgid "Concatenate a list of TSDataset objects along the specified axis"
 msgstr "用于合并两个数据集，target、known_cov以及observe_cov按照df规则合并，static按照dict合并"
 
-#: 98c72b8861d9483d910bc3bfc43adbb5 paddlets.datasets.tsdataset.TSDataset.concat:3
-#: of
+#: e8da2e8076a7465d86c889e4246c2080 of
+#: paddlets.datasets.tsdataset.TSDataset.concat:3
 msgid ""
 "A list of TSDataset objects. All TSDatasets' freqs are required to be "
 "consistent. When axis=1, time_col is required to be non-repetitive; when "
@@ -986,74 +998,30 @@ msgstr ""
 "TSDataset元素列表，要求所有TSDataset "
 "freq保持一致，当axis=1的时候，要求time_col不重复；axis=0的时候，要求所有columns不重复"
 
-#: 8fb5c1c1aaa04cec9c8220caca2381fd paddlets.datasets.tsdataset.TSDataset.astype:1
-#: of
+#: 251bb31353124d5c95120e88e8bc7c03 of
+#: paddlets.datasets.tsdataset.TSDataset.astype:1
 msgid "Cast a TSDataset object to the specified dtype"
 msgstr "转换数据类型，注意这里不会返回一个新的数据，而是在原始数据集上修改"
 
-#: 9713e339618e40ca90518bd29bafecd8 paddlets.datasets.tsdataset.TSDataset.dtypes:1
-#: of
+#: 3243960c059a42e8ada644c0702ad896 of
+#: paddlets.datasets.tsdataset.TSDataset.dtypes:1
 msgid "Get dtypes of target, known_covs, observed_covs"
 msgstr "返回列类型"
 
-#: 305a21af034247a2adb544919746af01 paddlets.datasets.tsdataset.TSDataset.dtypes:3
-#: of
+#: a1b90e468e2a4eb5a033947411c7103c of
+#: paddlets.datasets.tsdataset.TSDataset.dtypes:3
 msgid "<column name, dtype>"
 msgstr ""
 
-#: b2c2875f519042579a291ad49e381a43
-#: paddlets.datasets.tsdataset.TSDataset.sort_columns:1 of
+#: 5f5c6a081d6a4c4bbedc78e5d273f337 of
+#: paddlets.datasets.tsdataset.TSDataset.sort_columns:1
 msgid "Sort the TSDataset object by the index"
 msgstr "对所有元素的columns进行分别排序"
 
-#: 958bc08b01684562bce9dbcf1058ca8b
-#: paddlets.datasets.tsdataset.TSDataset.sort_columns:3 of
+#: f2c13e2efcc94c56a9d3260b5fe8a622 of
+#: paddlets.datasets.tsdataset.TSDataset.sort_columns:3
 msgid ""
 "Ascending or descending. When the index is a MultiIndex the sort "
 "direction can be controlled for each level individually."
 msgstr "升序或降序排序"
 
-#~ msgid ""
-#~ "TSDataset is the fundamental data class"
-#~ " in PaddleTS, which is designed as "
-#~ "the first-class citizen to represent "
-#~ "the time series data. It is "
-#~ "consumed and produced by most modules"
-#~ " in PaddleTS. A TSDataset object is "
-#~ "comprised of two kinds of time "
-#~ "series data:"
-#~ msgstr ""
-#~ "``TSDataset`` 是 `PaddleTS` "
-#~ "中一个主要的类结构，用于表示绝大多数的时序样本数据，并作为PaddleTS其他算子的输入以及输出对象。TSDataset "
-#~ "包涵两类时序数据："
-
-#~ msgid "Target: the data that is needed for forecasting."
-#~ msgstr "待预测目标：表示希望被预测的时序序列"
-
-#~ msgid ""
-#~ "Covariate: the data that is not "
-#~ "needed for forecasting, but that may "
-#~ "improve the performance of the "
-#~ "forecasting model."
-#~ msgstr "协变量：无需被预测的时间序列，协变量的加入通常用于辅助提高模型预测的效果"
-
-#~ msgid ""
-#~ "Univariate target w/wo covariates: the "
-#~ "target data has only one dimension."
-#~ msgstr "单变量数据，只包含单列的预测目标，同时可以包涵单列或者多列协变量"
-
-#~ msgid ""
-#~ "Multivariate target w/wo covariates: the "
-#~ "target data has multiple dimension and"
-#~ " shares the same time index."
-#~ msgstr "多变量数据，包涵多列预测目标，同时可以包涵单列或者多列协变量"
-
-#~ msgid "`observed_covariate`:"
-#~ msgstr "`observed_covariate（观测协变量）`"
-
-#~ msgid "`known_covariate`:"
-#~ msgstr "`known_covariate (可预知协变量)`"
-
-#~ msgid "`static_covariate`:"
-#~ msgstr "`static_covariate (静态协变量)`"
-
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.models.dl.paddlepaddle.nbeats.po b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.models.dl.paddlepaddle.nbeats.po
index e59ab0a1..0b9000e5 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.models.dl.paddlepaddle.nbeats.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.models.dl.paddlepaddle.nbeats.po
@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PaddleTS \n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2022-07-22 10:50+0800\n"
+"POT-Creation-Date: 2022-07-26 10:46+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: LANGUAGE <LL@li.org>\n"
@@ -18,37 +18,38 @@ msgstr ""
 "Generated-By: Babel 2.10.3\n"
 
 #: ../../source/api/paddlets.models.dl.paddlepaddle.nbeats.rst:2
-#: c4f9192486994290bf24f900b61923ff
+#: ad9b37ca78ba497e9993542067ec8e0c
 msgid "paddlets.models.dl.paddlepaddle.nbeats"
 msgstr "paddlets.models.dl.paddlepaddle.nbeats"
 
-#: 086bf27e1a4f4917a9cd5a612268f423 paddlets.models.dl.paddlepaddle.nbeats:1 of
+#: a96353ad675a4b06ac87804f0d45ed5f of paddlets.models.dl.paddlepaddle.nbeats:1
+#, fuzzy
 msgid ""
 "This implementation is based on the article `N-BEATS: Neural basis "
-"expansion analysis for interpretable time series "
-"forecasting<https://arxiv.org/pdf/1905.10437.pdf>`."
+"expansion analysis for interpretable time series forecasting "
+"<https://arxiv.org/pdf/1905.10437.pdf>`_ ."
 msgstr ""
-"基于论文：`N-BEATS: Neural basis expansion analysis for interpretable time "
-"series forecasting` 实现，<https://arxiv.org/pdf/1905.10437.pdf>"
+"N-BEATS模型实现，基于论文：`N-BEATS: Neural basis expansion analysis for interpretable time "
+"series forecasting <https://arxiv.org/pdf/1905.10437.pdf>`_ 。"
 
-#: paddlets.models.dl.paddlepaddle.nbeats:8 c01b622942c0410ead85ff267c54a98e of
+#: a569a4c46627471e9b7223c534625f18 of paddlets.models.dl.paddlepaddle.nbeats:8
 msgid "Base model features"
 msgstr "原模型特性"
 
-#: paddlets.models.dl.paddlepaddle.nbeats:4 c579f0c95ac146a894ec684ae685d5b4 of
+#: c24c509b459e4b178c86e73887c7f776 of paddlets.models.dl.paddlepaddle.nbeats:4
 msgid ""
 "Basic architecture: A network with hierarchical stacking, bi-directional "
 "residual connection and interpretable generator."
 msgstr "基础架构：多层堆栈，双向残差连接，并具有可解释性生成器的网络结构。"
 
-#: paddlets.models.dl.paddlepaddle.nbeats:6 ff3c21e3e26e4c789d5185a640c79c72 of
+#: cf968bbaa52a4103b6718f584010785e of paddlets.models.dl.paddlepaddle.nbeats:6
 msgid ""
 "Hierarchical stacking: The Design of multi-stacks with multi-blocks in "
 "each is for different kinds of information extraction, ie, trend, "
 "seasonality, etc.."
 msgstr "多层堆栈：多栈与多模块循环堆叠，各栈用来提取不同的可解释特性，比如趋势性与季节性。"
 
-#: 11d7e4765e364a0f8cde00d22447a494 paddlets.models.dl.paddlepaddle.nbeats:8 of
+#: d83d48964c3542d6bcbad014183ce36a of paddlets.models.dl.paddlepaddle.nbeats:8
 msgid ""
 "Bi-directional residual cascade: The backward residual connection is for "
 "computing of the residual signal, and pass the residual to the next "
@@ -56,53 +57,56 @@ msgid ""
 "forecasts to the final output."
 msgstr "双向残差串联结构：向后残差连接用来计算历史残差信号，并传递至下一层网络；向前差残连接累加计算得到最终模型预测。"
 
-#: 15c1996521bf46b19fcd23a398c4ca29 paddlets.models.dl.paddlepaddle.nbeats:14 of
+#: 61140c81f44f44ae8b0f3a5b2ce9b288 of
+#: paddlets.models.dl.paddlepaddle.nbeats:14
 msgid "Updated features"
 msgstr "升级模型特性"
 
-#: 622dc1ce4f954da083635cdd2c43526b paddlets.models.dl.paddlepaddle.nbeats:11 of
+#: b17ba92766d64a6aa392bbe294225a2f of
+#: paddlets.models.dl.paddlepaddle.nbeats:11
 msgid "Multi-target: support multi-target modelling."
 msgstr "多目标变量：支持多目标建模。"
 
-#: 7268801fadfd4760ad0a70f716e74227 paddlets.models.dl.paddlepaddle.nbeats:13 of
+#: ec595bf44f77480a9b0b1a17d59e10ba of
+#: paddlets.models.dl.paddlepaddle.nbeats:13
 msgid ""
 "Covariates: support known covariates(future known covariates) and "
 "observed covariates(future unknown covariates)."
 msgstr "协变量：支持可预知协变量特征与观测协变量特征。"
 
-#: 5d0c3e55bba24f28ba99d0a3ce805aed
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:1 of
+#: 13680e427e9746c79adfb0d3ed76b300 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:1
 msgid ""
 "Bases: "
 ":py:class:`~paddlets.models.dl.paddlepaddle.paddle_base_impl.PaddleBaseModelImpl`"
 msgstr ""
 
-#: a4acab65a8034a60a0f88cda6e66ceb3
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:1 of
+#: 37d188791b084f6e903b916284af8b1a of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:1
 msgid "Implementation of NBeats model."
 msgstr "NBeats模型实现。"
 
-#: 326ac95c2b054a7288ca96805ad7b6eb
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel of
+#: 6f69547d09b9461fb8b9e489f2d582b2 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel
 msgid "Parameters"
 msgstr "参数"
 
-#: 5c83ea112c5e405eaaa52e4c0ce7202b
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:3 of
+#: cd23287a290442a99064ecda7c185e89 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:3
 msgid ""
 "The size of the loopback window, i.e., the number of time steps feed to "
 "the model."
 msgstr "模型输入的时间序列长度。"
 
-#: a8d9b105c4a34041881b0479fcb59498
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:5 of
+#: bd1a52c5226241f19160a23f33920278 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:5
 msgid ""
 "The size of the forecasting horizon, i.e., the number of time steps "
 "output by the model."
 msgstr "模型输出的序列长度。"
 
-#: 67fbed58d7dd48c6a8f267b30f3eb359
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:7 of
+#: 29dc741038b24e1181d9e32088370c95 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:7
 msgid ""
 "Boolean value indicating whether the generic architecture of N-BEATS is "
 "used. If not, the interpretable architecture outlined in the paper "
@@ -110,28 +114,28 @@ msgid ""
 "waveform generator functions)."
 msgstr "布尔类型变量，指示是否使用普通网络结构，如不使用则使用可解释性网络结构。"
 
+#: 4849828549804a4ca9bf9f8810087a4a of
 #: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:9
-#: c9635c5df28e4875bf6742653d64f4fc of
 msgid ""
 "The number of stacks that make up the whole model. Only used if "
 "`generic_architecture` is set to `True`."
 msgstr "stack数量，当generic_architecture为True时生效。"
 
-#: aecd14853ad74dbc8bd38a3cea4b3902
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:11 of
+#: 4c410cde220943fd91bbe82c861e7101 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:11
 msgid "The number of blocks making up every stack."
 msgstr "构成每个stack的block数量。"
 
+#: be326b9ccee441ceae8af7fc7ca80261 of
 #: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:13
-#: e55d7e6249f94aba87a42a133665c27d of
 msgid ""
 "The number of fully connected layers preceding the final forking layers "
 "in each block of every stack. Only used if `generic_architecture` is set "
 "to `True`."
 msgstr "每个block中分叉结构前的全连接层数量，仅当generic_architecture为True时生效。"
 
-#: 3273a90fb4fe4af59a919834ac7262d9
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:15 of
+#: ac41880856ae4f65ae3b3d13f8c8cc23 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:15
 msgid ""
 "Determines the number of neurons that make up each fully connected layer "
 "in each block of every stack. If a list is passed, it must have a length "
@@ -140,23 +144,23 @@ msgid ""
 "stack will have blocks with FC layers of the same width."
 msgstr "每个block中全连接层的神经元数量，如果传入list，则list长度必须等于num_stacks，且list中每个元素对应于当前层的神经元数量。如果传入整数，则每个stack中的block中具有相同的神经元数量。"
 
-#: 163048088ddf47d1a880c5f7b9e2251b
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:17 of
+#: 41a82550d84a4b6d8f6af95267f9a4c3 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:17
 msgid ""
 "The dimensionality of the waveform generator parameters, also known as "
 "expansion coefficients. Only used if `generic_architecture` is set to "
 "`True`."
 msgstr "波形生成器参数个数，仅当generic_architecture为True时生效。"
 
+#: 4cde0d31b9ac4d93bfa92107894bbb4f of
 #: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:19
-#: e7f0c4f025e545f8aa9983c27146f760 of
 msgid ""
 "The degree of the polynomial used as waveform generator in trend stacks. "
 "Only used if `generic_architecture` is set to `False`."
 msgstr "季节性波形生成器的多项式次数，仅当generic_architecture为False时生效。"
 
-#: b098c5d1e1d04daf89703af5a513c017
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:21 of
+#: cfcb3d70bce54118b4163e1954bfd94e of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:21
 msgid ""
 "Optional, the number of time steps between in_chunk and out_chunk for a "
 "single sample. The skip chunk is neither used as a feature (i.e. X) nor a"
@@ -164,60 +168,60 @@ msgid ""
 " steps."
 msgstr "可选变量， 输入序列与输出序列之间跳过的序列长度，既不作为特征也不作为预测目标使用，默认值为0。"
 
-#: 30aa61de5f6e4b53b72beb03c4d87f95
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:23 of
+#: beef2797eb724c81b8ac2de5c499bc00 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:23
 msgid "sampling intervals between two adjacent samples."
 msgstr "相邻两个样本的采样间隔。"
 
+#: 2ea43a29330344e7a059b9abe1e3748c of
 #: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:25
-#: c63bd2dad68341a2856e7278c591915d of
 msgid "loss function."
 msgstr "损失函数。"
 
-#: b9dfb4fa39c742f081d826076372cba8
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:27 of
+#: 4cb72b40319a4ebd9844bba606651067 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:27
 msgid "optimizer algorithm."
 msgstr "优化器算法。"
 
-#: 67b102c54197480aaf0e5c3e974b854b
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:29 of
+#: fb2a2110dc31491d978f984c9ef4dd1e of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:29
 msgid "optimizer parameters."
 msgstr "优化器参数。"
 
-#: 3ab284af2a614e96a3317e5c930d9b4b
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:31 of
+#: 3ff572fca9a24b218b1ac4b4a1dbf7d1 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:31
 msgid "evaluation metrics of model."
 msgstr "模型评估指标。"
 
-#: 0c6bf9e60101441290d45eae5ccf3af5
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:33 of
+#: 03c21cae9d8140a58dc1d28bfff8aab3 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:33
 msgid "customized callback functions."
 msgstr "自定义的callback函数。"
 
-#: 849e53ac7a484b508a614dd37ed63fe9
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:35 of
+#: 583b4b8e43b341fda4619c3ca738d2bd of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:35
 msgid "number of samples per batch."
 msgstr "每个batch中的样本数量。"
 
-#: 85450b55fa8d4eddb3ae0ad21ed61576
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:37 of
+#: 84de3655af1c4741976a4043719315e3 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:37
 msgid "max epochs during training."
 msgstr "训练过程中最大迭代轮数。"
 
-#: 9e52415a42ab4342a839227b8769bf4d
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:39 of
+#: 2d2b3082525d429a8f0fe92e9bb83c09 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:39
 msgid "verbosity mode."
 msgstr "模型日志模式。"
 
-#: 513dfef408d74aa09af1e102f27b70f8
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:41 of
+#: 536be7c4db804269913e310dbcf0e3ef of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:41
 msgid ""
 "number of epochs with no improvement after which learning rate wil be "
 "reduced."
 msgstr "训练过程中学习率降低所需的效果不再提升的轮数。"
 
-#: 70e0539da99542ba93bc4f1e89efa464
-#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:43 of
+#: 6cebfb7142044c069c46fcbafdb9e6a9 of
+#: paddlets.models.dl.paddlepaddle.nbeats.NBEATSModel:43
 msgid "global random seed."
 msgstr "全局随机种子。"
 
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.models.dl.paddlepaddle.nhits.po b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.models.dl.paddlepaddle.nhits.po
index e0e6dbed..01605546 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.models.dl.paddlepaddle.nhits.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.models.dl.paddlepaddle.nhits.po
@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PaddleTS \n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2022-07-22 10:50+0800\n"
+"POT-Creation-Date: 2022-07-26 10:46+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: LANGUAGE <LL@li.org>\n"
@@ -18,69 +18,70 @@ msgstr ""
 "Generated-By: Babel 2.10.3\n"
 
 #: ../../source/api/paddlets.models.dl.paddlepaddle.nhits.rst:2
-#: 950eb05cdabe4118af7188645bfb732f
+#: 32efa4173bec4bde96394b746f6072f5
 msgid "paddlets.models.dl.paddlepaddle.nhits"
 msgstr ""
 
-#: 8a996450fe5e4c2f94f1a2605faa2ec4 paddlets.models.dl.paddlepaddle.nhits:1 of
+#: 801b188344c641b29037258c6e18847a of paddlets.models.dl.paddlepaddle.nhits:1
+#, fuzzy
 msgid ""
 "This implementation is based on the article `N-HiTS: Neural Hierarchical "
-"Interpolation for Time Series "
-"Forecasting<https://arxiv.org/abs/2201.12886>`."
+"Interpolation for Time Series Forecasting "
+"<https://arxiv.org/abs/2201.12886>`_ ."
 msgstr ""
-"NHiTS模型实现基于文章 N-HiTS: Neural Hierarchical Interpolation for Time Series "
-"Forecasting<https://arxiv.org/abs/2201.12886>."
+"NHiTS模型实现，基于论文: `N-HiTS: Neural Hierarchical Interpolation for Time Series "
+"Forecasting <https://arxiv.org/abs/2201.12886>`_ 。"
 
-#: 11f7f7d1034747dcbbebf4d0922115b3
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:1 of
+#: 273dc9bb64184ae3b6b3b9154bb9c26c of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:1
 msgid ""
 "Bases: "
 ":py:class:`~paddlets.models.dl.paddlepaddle.paddle_base_impl.PaddleBaseModelImpl`"
 msgstr ""
 
-#: 65da66047c964613ba2bb965357516e8
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:1 of
+#: 2a3500c955b743f5a446f0414267750a of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:1
 msgid "Implementation of NHiTS model"
 msgstr "NHiTS模型实现"
 
-#: 8cb65cb33fd74f6b89e22c2e5a69c272 paddlets.models.dl.paddlepaddle.nhits.NHiTSModel
-#: of
+#: 26022d086fae4478bbfc8d369a1ba916 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel
 msgid "Parameters"
 msgstr ""
 
-#: 2dcbafe25f2e48c5bd306021744f40c6
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:3 of
+#: 4de0086579d7486b9033636ff67aa5bb of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:3
 msgid ""
 "The size of the loopback window, i.e., the number of time steps feed to "
 "the model."
 msgstr "模型输入的时间序列长度。"
 
-#: 280f19b5c3c84bdbb097918afe949a3e
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:5 of
+#: c57e5ed328434e799f6fb31dba534bfc of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:5
 msgid ""
 "The size of the forecasting horizon, i.e., the number of time steps "
 "output by the model."
 msgstr "模型输出的序列长度。"
 
-#: 6a95b5f721c2480ebe99f93d7ab0c8d0
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:7 of
+#: cdf1b68ffa4247b0860d5d755f2cef61 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:7
 msgid "The number of stacks that make up the whole model."
 msgstr "Stack数量。"
 
+#: c07def08784649e9b30b29642c3cf17d of
 #: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:8
-#: e5bc4b55ec7545739bea1fb9b979b911 of
 msgid "The number of blocks making up every stack."
 msgstr "构成每个stack的block数量。"
 
-#: ad57cfdc73bc4522baf4023b9581030f
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:9 of
+#: cdac25ce80394fb29d2694f6c5304247 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:9
 msgid ""
 "The number of fully connected layers preceding the final forking layers "
 "in each block of every stack."
 msgstr "每个block中分叉结构前的全连接层数量。"
 
+#: 34a23ce653594bdb8ad8a06c47ad4a87 of
 #: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:10
-#: cde7348420144379a3585d01d44313d4 of
 msgid ""
 "Determines the number of neurons that make up each fully connected layer "
 "in each block of every stack. If a list is passed, it must have a length "
@@ -89,40 +90,40 @@ msgid ""
 "stack will have blocks with FC layers of the same width."
 msgstr "每个block中全连接层的神经元数量，如果传入list，则list长度必须等于num_stacks，且list中每个元素对应于当前层的神经元数量。如果传入整数，则每个stack中的block中具有相同的神经元数量。"
 
-#: 559f7c18f6304149a3da4d3339978d4e
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:11 of
+#: dd8cb4aa4d0a42ea8c8f776b38d89ff2 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:11
 msgid "The kernel size for the initial pooling layer."
 msgstr "初始池化层的内核大小。"
 
-#: 7f8e7c402a2e4edea561a83151cb6a1b
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:13 of
+#: 4c0cb37055d5490c8c73ad9ee25e8e3c of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:13
 msgid ""
 "The factor by which to downsample time at the output (before "
 "interpolating)."
 msgstr "为每个堆栈中的每个块指定插值前的下采样因子。"
 
-#: 24249f837e2f460b91cf781c89612a85
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:15 of
+#: a46653b01d294ef584c50122f259e1ce of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:15
 msgid "Whether to use batch normalization."
 msgstr "是否做批量标准化。"
 
-#: a0a17e90898e4890939e2728d82343e1
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:17 of
+#: c9d53020152844e49b8f4487732f3871 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:17
 msgid "Dropout probability."
 msgstr "神经元节点的随机丢弃概率。"
 
-#: 7dbe8eefb3974f918acac40f61831a1d
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:19 of
+#: c3d591710ee14b0babb029657002979e of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:19
 msgid "The activation function of encoder/decoder intermediate layer."
 msgstr "编码器/解码器中间层的激活函数。"
 
-#: 8fe6b333ddc2496bba5475f63b55f554
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:21 of
+#: 98808591e2f44ecc9301434b2ebd52b1 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:21
 msgid "Whether to use MaxPool1d pooling, False uses AvgPool1d."
 msgstr "是否使用MaxPool1d池化，等于False则使用AvgPool1d。"
 
-#: 54597f3de8a84d87889742a3ab2176d3
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:23 of
+#: cb09b273b2944b9691f33db669084482 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:23
 msgid ""
 "Optional, the number of time steps between in_chunk and out_chunk for a "
 "single sample. The skip chunk is neither used as a feature (i.e. X) nor a"
@@ -130,60 +131,60 @@ msgid ""
 " steps."
 msgstr "可选变量，输入序列与输出序列之间跳过的序列长度，既不作为特征也不作为预测目标使用，默认值为0。"
 
-#: 69e66fc210f94a25bafa99b1c6923e4d
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:25 of
+#: 86142dd0ad0343f18a2b9843dddb33ce of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:25
 msgid "sampling intervals between two adjacent samples."
 msgstr "相邻两个样本的采样间隔。"
 
-#: a65bce6f2d54421591035bd2e16dcc79
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:27 of
+#: c40e1eb4810b4721b3bfdb50c8f30de1 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:27
 msgid "loss function."
 msgstr "损失函数。"
 
-#: 02452536adc541bab7ea80c7af0b4d70
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:29 of
+#: b58ee8f4a89541699fea6f053eb84f73 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:29
 msgid "optimizer algorithm."
 msgstr "优化器算法。"
 
-#: 46a3ce82816f4af995251f213a8823d6
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:31 of
+#: 3eed9ce382884e8d973507267b2e94ba of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:31
 msgid "optimizer parameters."
 msgstr "优化器参数。"
 
-#: 8eceedd1ec75444eab3bccfe67846af1
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:33 of
+#: 629b2991d39a482e9bcfe6586e887b63 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:33
 msgid "evaluation metrics of model."
 msgstr "模型评估指标。"
 
+#: 6c1451c864f2442d98e1815fd19e3825 of
 #: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:35
-#: da1e74dc442f4492a036c31cfb0d7322 of
 msgid "customized callback functions."
 msgstr "自定义的callback函数。"
 
-#: 104498c1374543b8a6cf6b4f3c4a07f3
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:37 of
+#: d442428e7e0c40f0aeaafa41f5acdc55 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:37
 msgid "number of samples per batch."
 msgstr "每个batch中的样本数量。"
 
-#: 7582ee8595c44d9d9afcf44bbffda65f
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:39 of
+#: 5a9ac24de1864b0c8e5ad63a3487b389 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:39
 msgid "max epochs during training."
 msgstr "训练过程中最大迭代轮数。"
 
-#: 5a54ba2ad5c74bf6a60b475d9980becc
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:41 of
+#: 6bc55a76a95448df802fc64b37928dcb of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:41
 msgid "verbosity mode."
 msgstr "模型日志模式。"
 
-#: 3059c62916ac4015baf122c9c7c26a3f
-#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:43 of
+#: 5b288b1a515f4a99baf7d48f1db18944 of
+#: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:43
 msgid ""
 "number of epochs with no improvement after which learning rate wil be "
 "reduced."
 msgstr "训练过程中学习率降低所需的效果不再提升的轮数。"
 
+#: 8b0f4bfd0009420c8091fc385699ae4b of
 #: paddlets.models.dl.paddlepaddle.nhits.NHiTSModel:45
-#: f3c7a38675a04f0abbc1f64aed0697d7 of
 msgid "global random seed."
 msgstr "全局随机种子。"
 
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.fill.po b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.fill.po
index 89c3e52a..61b2fa3d 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.fill.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.fill.po
@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PaddleTS \n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2022-07-23 00:08+0800\n"
+"POT-Creation-Date: 2022-07-22 14:24+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: LANGUAGE <LL@li.org>\n"
@@ -18,50 +18,48 @@ msgstr ""
 "Generated-By: Babel 2.10.3\n"
 
 #: ../../source/api/paddlets.transform.fill.rst:2
-#: 965e091297a74aed9cb1e04446b9c8e1
+#: 42451db3ad194eebae12492a528d2bea
 msgid "paddlets.transform.fill"
 msgstr ""
 
-#: 2beb925d3f4d4bf3ac4945a12d00806c of paddlets.transform.fill.Fill:1
-#, fuzzy
-msgid "Bases: :py:class:`~paddlets.transform.base.BaseTransform`"
+#: 11d9bcca447649848030d5ce3066f685 bts.transform.fill.Fill:1 of
+msgid "Bases: :py:class:`~bts.transform.base.BaseTransform`"
 msgstr "基类: :py:class:`~bts.transform.base.BaseTransform`"
 
-#: 0bf4bdd5a7d948288a50736cf6e96fc8 of paddlets.transform.fill.Fill:1
+#: 0ea4f6d133c74437b0df794fab4dc402 bts.transform.fill.Fill:1 of
 msgid ""
 "This class is designed to fill missing values in columns. There are three"
 " kinds of ways to fulfill this task, including"
 msgstr "该类被设计为用来补全数据列中的缺失值。有三类补全数据的方法，包括"
 
-#: e9689b95eebf41d180491648295c139b of paddlets.transform.fill.Fill:3
+#: 5a56f12af6a843bca8098765ae4e7b34 bts.transform.fill.Fill:3 of
 msgid ""
 "Replace the missing values with a statistic computed from a sliding "
 "window, e.g. MAX, MIN, MEAN, or MEDIAN;"
 msgstr "从滑动窗口中计算的统计数据替换缺失值，例如 最大值、最小值、平均值或中值；"
 
-#: e17098f29bd146fa98aa7b9211384e46 of paddlets.transform.fill.Fill:5
+#: 3454ff474e8740fcb287953836f6d6dc bts.transform.fill.Fill:5 of
 msgid ""
 "Replace the missing values with adjacent values, which could be values "
 "previous or next to the missing values;"
 msgstr "相邻值替换缺失值，这些值可以是缺失值之前或之后的数值。"
 
-#: 3e17e4efa4274682bb616cf48ab93e47 of paddlets.transform.fill.Fill:7
+#: bc1b8c54746248e7aad624ab330aa9b5 bts.transform.fill.Fill:7 of
 msgid "Replace the missing values with the value specified by the user."
 msgstr "或使用用户指定的值替换缺失值。"
 
-#: 386793a7ac6d4048866aa868ca3e4d8f 4c847988d63e4e2a82b6df2bf4bb03da
-#: ac2cff27d470486f82f3a2ed30d029b1 d142f877b9a2425586a61d4345b51260 of
-#: paddlets.transform.fill.Fill paddlets.transform.fill.Fill.fit
-#: paddlets.transform.fill.Fill.fit_transform
-#: paddlets.transform.fill.Fill.transform
+#: 09f1c367d66e4860970da65006ce2ec3 4115d1456f1d4be98bc9a02a0d2e5c3e
+#: 910048d3ec4741acbd276dfe0e4121f4 b4c14df65a1b4fbfa6a70739291e3bf0
+#: bts.transform.fill.Fill bts.transform.fill.Fill.fit
+#: bts.transform.fill.Fill.fit_transform bts.transform.fill.Fill.transform of
 msgid "Parameters"
 msgstr "参数"
 
-#: ede898d523a243a0b4912cb8d169244f of paddlets.transform.fill.Fill:9
+#: 5f50a35b19304fcebcb9be523c038839 bts.transform.fill.Fill:9 of
 msgid "Column name(s) to be processed."
 msgstr "选择被补全的数据列。"
 
-#: 0f475fc9468c4a1f96a0dd7517cf4549 of paddlets.transform.fill.Fill:11
+#: b8f6e5705d4e46dcb272ac03ed7506f0 bts.transform.fill.Fill:11 of
 msgid ""
 "Method of filling missing values. Totally 8 methods are supported "
 "currently: max: Use the max value in the sliding window. min: Use the min"
@@ -69,76 +67,69 @@ msgid ""
 "window. median: Use the median value in the sliding window. pre: Use the "
 "previous value. next: Use the next value. zero: Use 0s. default: Use the "
 "value specified by the user."
-msgstr ""
-"填充缺失值的方法。目前共支持8种方法： max：使用滑动窗口中的最大值； min：使用滑动窗口中的最小值； avg：使用滑动窗口中的平均值； "
-"median：使用中值； pre：使用上一个值； next：使用下一个值； zero：使用0值； miss_value：使用用户指定的值"
+msgstr "填充缺失值的方法。目前共支持8种方法： max：使用滑动窗口中的最大值； min：使用滑动窗口中的最小值； avg：使用滑动窗口中的平均值； median：使用中值； pre：使用上一个值； next：使用下一个值； zero：使用0值； default：使用用户指定的值"
 
-#: bcd61284bade4c7eb25d4453591f033f of paddlets.transform.fill.Fill:21
+#: 08957e17a8e74f84a07cdda2d6b7cd8e bts.transform.fill.Fill:21 of
 msgid ""
 "Only effective when the method is default, value specified by the user to"
 " replace the missing values."
-msgstr "仅在方法为默认值时有效，由用户指定的值替换缺失值。"
+msgstr "仅在方法为default时有效，由用户指定的值替换缺失值。"
 
-#: 1aaf5e4af15444d38d3bed24404b9270 of paddlets.transform.fill.Fill:23
+#: 98f70303bdf8488c8830f279f19d994a bts.transform.fill.Fill:23 of
 msgid "Size of the sliding window."
 msgstr "滑动窗口大小"
 
-#: 96cf46cc544c4ff3b3e63014a82a7374 of paddlets.transform.fill.Fill:25
+#: 7efbe93ff83441f18e1003db727e295d bts.transform.fill.Fill:25 of
 msgid ""
 "Minimum number of non-missing values in the sliding window, if less than "
 "the min_num_non_missing_values, the statistic will be set to np.nan."
-msgstr "滑动窗口中非缺失值的最小数量，如果小于参数min_num_non_missing_values，则统计为np.nan"
+msgstr "滑动窗口中非缺失值的最小数量，如果滑动窗口长度小于参数min_num_non_missing_values，则统计为np.nan"
 
-#: a0c4bfacbece42869727f6acca605c0a a60ec9e7c0154ec1bfc42dc0cfcf3200
-#: c0bb4980e4c34dc39b70e4e3320c6b3f e0ee69516ff44f76acc6d0bed662f0ce of
-#: paddlets.transform.fill.Fill paddlets.transform.fill.Fill.fit
-#: paddlets.transform.fill.Fill.fit_transform
-#: paddlets.transform.fill.Fill.transform
+#: 2d40b265b18c433cab1b5e2967cd5de8 665883b17aa74e88807e0039a9471bc1
+#: 916defc6feb3450ea5a087e13eda4968 a9ae8f4b405546b0a0e3e947c5e15a5a
+#: bts.transform.fill.Fill bts.transform.fill.Fill.fit
+#: bts.transform.fill.Fill.fit_transform bts.transform.fill.Fill.transform of
 msgid "Returns"
 msgstr "返回"
 
-#: e1c85850e4b84f7e8bf1f1ce5bad1ece of paddlets.transform.fill.Fill:29
+#: 2ec0fc89403a4a1dbc71890ef96e54e5 bts.transform.fill.Fill:29 of
 msgid "None"
 msgstr "None"
 
-#: 6f119c18fb9f42c48107ed03562899a5 of paddlets.transform.fill.Fill.fit:1
+#: bts.transform.fill.Fill.fit:1 c9691177e41a454fbefbd6c07123e301 of
 msgid "dataset to process"
 msgstr "进行拟合的数据"
 
-#: 4b0432931bed4d819490d7c4a65167ce of paddlets.transform.fill.Fill.fit:4
+#: 53f70c405bb74af6a4b7868ba6e6b243 bts.transform.fill.Fill.fit:4 of
 msgid "self"
 msgstr "算子自身"
 
-#: 077e01fd1c0847ffb8ed66c6621b1da8 of paddlets.transform.fill.Fill.transform:1
+#: 9fdd8f0d4e96475caed558befe56a1ca bts.transform.fill.Fill.transform:1 of
 msgid "Fill missing values."
 msgstr "补全缺失值。"
 
-#: 76689fb9f0db4d53a8fc8c7dcac026e8 d436c6d27f3e4eca97ee25bdd88072e2 of
-#: paddlets.transform.fill.Fill.fit_transform:3
-#: paddlets.transform.fill.Fill.transform:3
+#: 0a8e6e8be41c434f91b2dbc1cc21b4db bts.transform.fill.Fill.fit_transform:3
+#: bts.transform.fill.Fill.transform:3 e27a29b3bbc345f687a705b704cd0ab8 of
 msgid "TSDataset or List[TSDataset]"
 msgstr "时序数据TSDataset"
 
-#: 04f10b4e2e684a7e8f4779c62227b7e4 51f6d3c4c46b4ab0b0693c646a6da876 of
-#: paddlets.transform.fill.Fill.fit_transform:5
-#: paddlets.transform.fill.Fill.transform:5
+#: bts.transform.fill.Fill.fit_transform:5 bts.transform.fill.Fill.transform:5
+#: e55c0da508a44022980c2c521a595843 ef862f8da7fb409882fbf6e1f09f169a of
 msgid "Set to True to perform inplace row normalization and avoid a copy."
 msgstr "设置为True时，数据会在源输入数据上修改，避免复制新数据。"
 
-#: 54de33e86b394c8ab66ccb87eb80a75f e20b81f4b12b456785f7d16acd9062d1 of
-#: paddlets.transform.fill.Fill.fit_transform:8
-#: paddlets.transform.fill.Fill.transform:8
+#: 5b3f6235e80d4ce9abb678c7b38e6fb5 5b5060ce83044c3bac89fa08cd37eb35
+#: bts.transform.fill.Fill.fit_transform:8 bts.transform.fill.Fill.transform:8
+#: of
 msgid "Transformed TSDataset."
 msgstr "转换后的时序数据集TSDataset."
 
-#: a3282edbcb034fdbafb7afe27d9cc660 c2bdb78f1a0c44599c4fd78b3a2aa0ff of
-#: paddlets.transform.fill.Fill.fit_transform
-#: paddlets.transform.fill.Fill.transform
+#: 02e4348f89f24d2d839dc2b4fa1cec93 bts.transform.fill.Fill.fit_transform
+#: bts.transform.fill.Fill.transform edc94e9d370443bf8a35cb2f36f27d25 of
 msgid "Return type"
 msgstr "返回 类型"
 
-#: 58ae2f39b46841b1a70b0df1868ebe12 of
-#: paddlets.transform.fill.Fill.fit_transform:1
+#: acadeec361694272bd54f5170ac2d7b3 bts.transform.fill.Fill.fit_transform:1 of
 msgid "First fit the scaler, and then do transformation."
 msgstr "首先执行拟合方法，然后执行转换方法。"
 
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.onehot.po b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.onehot.po
index a75b2bf3..0f32b833 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.onehot.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.onehot.po
@@ -40,7 +40,7 @@ msgstr "参数"
 
 #: 80c5ecb5158c467cab3fbdea3ac9c514 of paddlets.transform.onehot.OneHot:3
 msgid "Column(s) to be encoded."
-msgstr ""
+msgstr "需要进行编码的列名"
 
 #: 7b79a3def7f449b69e4c7df6b6a2f33b of paddlets.transform.onehot.OneHot:5
 msgid "{'error', 'ignore'}, default='error'"
@@ -74,11 +74,11 @@ msgstr ""
 
 #: f637b86b53f64acc964963c1d2a2a7f1 of paddlets.transform.onehot.OneHot.fit:1
 msgid "Fit the ecnoder with the dataset."
-msgstr ""
+msgstr "对dataset进行onehot拟合"
 
 #: ec9e1a62747940598aab5fdefbada4ef of paddlets.transform.onehot.OneHot.fit:3
 msgid "dataset from which to fit the encoder"
-msgstr ""
+msgstr ""需要进行拟合的数据"
 
 #: 8456aad3d82c4db4a9c80f09230d803a of paddlets.transform.onehot.OneHot.fit:6
 msgid "self"
@@ -92,7 +92,7 @@ msgstr "使用one-hot编码转换dataset"
 #: 86b1ab7bc04f44e1ad66fdfb57f24963 of
 #: paddlets.transform.onehot.OneHot.transform:3
 msgid "dataset to be transformed."
-msgstr ""
+msgstr "需要进行转换的数据"
 
 #: c2456134ea5042a6ab1992f09d911d4b f5d176a2073b481a91baf90e7620488c of
 #: paddlets.transform.onehot.OneHot.fit_transform:5
@@ -114,5 +114,5 @@ msgstr "先对dataset进行拟合，再进行转换"
 #: acc8e776b09043c08bdd49cf662065b6 of
 #: paddlets.transform.onehot.OneHot.fit_transform:3
 msgid "dataset to be processed."
-msgstr ""
+msgstr "需要进行转换的数据"
 
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.ordinal.po b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.ordinal.po
index 882b4deb..79a66376 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.ordinal.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.ordinal.po
@@ -44,7 +44,7 @@ msgstr "需要进行编码的列名"
 
 #: paddlets.transform.ordinal.Ordinal:5 eacfaf4eb7884a73ba759500fff91183 of
 msgid "{‘error’, ‘use_encoded_value’}, default=’error’"
-msgstr "可选值为{‘error’, ‘use_encoded_value’}， 默认为erro"
+msgstr "可选值为{‘error’, ‘use_encoded_value’}， 默认为error"
 
 #: paddlets.transform.ordinal.Ordinal:7 ca77376a4a5d4cd895a7f4cd3e584c33 of
 msgid "Whether to delete the original column, default=False."
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.po b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.po
index d04ed29f..7967a603 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.transform.po
@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PaddleTS \n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2022-07-23 00:08+0800\n"
+"POT-Creation-Date: 2022-07-26 10:45+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: LANGUAGE <LL@li.org>\n"
@@ -17,10 +17,10 @@ msgstr ""
 "Content-Transfer-Encoding: 8bit\n"
 "Generated-By: Babel 2.10.3\n"
 
-#: ../../source/api/paddlets.transform.rst:2 9ea37ecb127f4d3eb277aaf4d53228f1
+#: ../../source/api/paddlets.transform.rst:2 e27e45d357d54eeca4cb5a8600adb243
 msgid "paddlets.transform"
 msgstr ""
 
-#~ msgid "paddlets transform"
-#~ msgstr ""
-
+#: 32fba1e2d34b4d93b84e1891bf7dc5a1 of paddlets.transform:1
+msgid "paddlets transform"
+msgstr ""
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.utils.utils.po b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.utils.utils.po
index 7a259a8a..81628253 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.utils.utils.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/api/paddlets.utils.utils.po
@@ -8,33 +8,36 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PaddleTS \n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2022-07-07 21:21+0800\n"
+"POT-Creation-Date: 2022-07-26 11:10+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: LANGUAGE <LL@li.org>\n"
 "MIME-Version: 1.0\n"
 "Content-Type: text/plain; charset=utf-8\n"
 "Content-Transfer-Encoding: 8bit\n"
-"Generated-By: Babel 2.9.0\n"
+"Generated-By: Babel 2.9.1\n"
 
-#: ../../source/api/paddlets.utils.utils.rst:2 bf095d6508af4f8988b8f1fe2a035476
+#: ../../source/api/paddlets.utils.utils.rst:2 6e8ffdc051714bccb1c1dfa1bf2f184d
 msgid "paddlets.utils.utils"
 msgstr ""
 
-#: 9a8d5d4e9f1545be8430538a48c533bb paddlets.utils.utils.check_model_fitted:1 of
+#: 3f7c98094c604ce890bab1658c4ac31a of
+#: paddlets.utils.utils.check_model_fitted:1
 msgid "check if model has fitted, Raise Exception if not fitted"
 msgstr "检查模型是否已拟合，如果未拟合则抛出异常"
 
-#: 3608be96e14b4d739fdfbb8f3e646803 paddlets.utils.utils.check_model_fitted
-#: paddlets.utils.utils.get_uuid e8c69aa4d0f440128774dcf1b0f3e784 of
+#: 0e1472dfe7e54cc3bb15a7f5cbe855a5 4982ab5f6b6643929defa18decf021c1 of
+#: paddlets.utils.utils.check_model_fitted paddlets.utils.utils.get_uuid
 msgid "Parameters"
 msgstr ""
 
-#: 079ba9c2f8d041afba7687027ad0e62f paddlets.utils.utils.check_model_fitted:3 of
+#: c5dba20c1d8d40fa9c401f7ce2bb91b8 of
+#: paddlets.utils.utils.check_model_fitted:3
 msgid "model instance."
 msgstr "模型实例"
 
-#: paddlets.utils.utils.check_model_fitted:5 c7de9a67f41342f3b8fb26ceb62d214b of
+#: 55110f3dc7934748887572330e4a4b65 of
+#: paddlets.utils.utils.check_model_fitted:5
 #, python-format
 msgid ""
 "str, default=None The default error message is, \"This %(name)s instance "
@@ -44,31 +47,36 @@ msgid ""
 "\"Estimator, %(name)s, must be fitted before sparsifying\"."
 msgstr "报错消息，不设置即为默认值"
 
-#: 24e94bad965742ddb9ed2800e6995e37 78222e1d5d6a4e2a83f65275c2a818bc
-#: paddlets.utils.utils.check_model_fitted paddlets.utils.utils.get_uuid of
+#: 26e332f349f94af5959c1ed4d816a6b5 727f7433a96a4da095c5cb0c47b457f2 of
+#: paddlets.utils.utils.check_model_fitted paddlets.utils.utils.get_uuid
 msgid "Returns"
 msgstr ""
 
-#: 7ac1a20e214d48179c59ebe2f5fbc209 paddlets.utils.utils.check_model_fitted:14 of
+#: 0914e9de214b4a7d9f419a4a256c2cf0 of
+#: paddlets.utils.utils.check_model_fitted:14
 msgid "None"
 msgstr ""
 
-#: 756d5bc3c1f847aabdaaf6a9a7061220 paddlets.utils.utils.check_model_fitted of
+#: 58cd4855cfac4aec97364f00816dfa4e of paddlets.utils.utils.check_model_fitted
 msgid "Raises"
 msgstr ""
 
-#: 8880b98c9c424b48a32d226c248a0138 paddlets.utils.utils.get_uuid:1 of
-msgid "get short UUID"
-msgstr ""
+#: 5caf8e8f221a4ff3814fdf63459aeb7c of paddlets.utils.utils.get_uuid:1
+msgid "Get a random string of 16 characters."
+msgstr "获取一个16个字符的随机字符串。"
 
-#: 5cada75474484ae7a149261d6e60d60a paddlets.utils.utils.get_uuid:3 of
-msgid "data to be predicted"
-msgstr ""
+#: 45ca62b1d2eb4c6abec2245e8c1b283f of paddlets.utils.utils.get_uuid:3
+msgid "The prefix of the returned string."
+msgstr "返回字符串的前缀。"
 
-#: 9b2b197d051a4ca1af224cd044f797ba paddlets.utils.utils.get_uuid:5 of
-msgid "prefix & 16 random letters"
-msgstr "prefix + 16位随机符号"
+#: c320b5f1870544a58a77d5ea249d645a of paddlets.utils.utils.get_uuid:5
+msgid "The suffix of the returned string."
+msgstr "返回字符串的后缀。"
 
-#~ msgid "get short UUID :param prefix: data to be predicted"
-#~ msgstr "获取UUID"
+#: e69cb5ace5844ea6b131fd7fd6183848 of paddlets.utils.utils.get_uuid:8
+msgid "String of 16 characters."
+msgstr "16个字符的字符串。"
 
+#: affba1ff965042328f357dd6f09d1f41 of paddlets.utils.utils.get_uuid
+msgid "Return type"
+msgstr ""
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/installation/overview.po b/docs/locale/zh_CN/LC_MESSAGES/source/installation/overview.po
index 2bbf0496..cea3833a 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/installation/overview.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/installation/overview.po
@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PaddleTS \n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2022-07-21 17:51+0800\n"
+"POT-Creation-Date: 2022-07-25 17:33+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: LANGUAGE <LL@li.org>\n"
@@ -17,31 +17,31 @@ msgstr ""
 "Content-Transfer-Encoding: 8bit\n"
 "Generated-By: Babel 2.9.0\n"
 
-#: ../../source/installation/overview.rst:3 5d4d9f2e2020488488467ce5ff750461
+#: ../../source/installation/overview.rst:3 3cc1281334ef4b5dbffed1e8b36a9eed
 msgid "Installation"
 msgstr "安装"
 
-#: ../../source/installation/overview.rst:8 cb15bf211ce4414cbdc05aae36244add
+#: ../../source/installation/overview.rst:8 5561c5534f7646d5966191b27710f6d6
 msgid "Environment Requirements"
 msgstr "环境要求"
 
-#: ../../source/installation/overview.rst:9 4e00a5c344774a95bdeac7bbcc2e87d3
+#: ../../source/installation/overview.rst:9 072c2114b819426e9b5a20cdf66dceff
 msgid "Python: 3.7/3.8/3.9"
 msgstr ""
 
-#: ../../source/installation/overview.rst:11 62e54bc845454d9190c181e6a47106e2
+#: ../../source/installation/overview.rst:11 5fc64f99feea48c282602dcf6270337f
 msgid "System: Windows/MacOS/Ubuntu/CentOS"
 msgstr ""
 
-#: ../../source/installation/overview.rst:15 d6ed6d10d26f4e7db6f279486d007aa6
+#: ../../source/installation/overview.rst:15 7bd09a3a690f4f3d8530ebae4d7f5602
 msgid "Preparations"
 msgstr "准备工作"
 
-#: ../../source/installation/overview.rst:17 04c7c1abdca74bcba7daa22861e4e094
+#: ../../source/installation/overview.rst:17 0ca998d2cf434bdd8edbbab062824ec6
 msgid "1）Install PaddlePaddle"
 msgstr "1）安装 paddlepaddle"
 
-#: ../../source/installation/overview.rst:19 5a3c189aeef54a3fa9887694ce57f577
+#: ../../source/installation/overview.rst:19 4571b63bad06424ea7820237e43343aa
 msgid ""
 "The PaddleTS is built upon the `PaddlePaddle "
 "<https://www.paddlepaddle.org.cn/>`__ deep learning framework, thus it is"
@@ -51,81 +51,80 @@ msgstr ""
 "PaddleTS 提供的时序模型均基于 `PaddlePaddle <https://www.paddlepaddle.org.cn/>`__ "
 "开发。 建议在安装PaddleTS之前先安装PaddlePaddle 。注意PaddleTS最低要求paddlepaddle的版本大于2.3.0"
 
-#: ../../source/installation/overview.rst:23 e068fb0d55b24fa0a0d43e803cc3977b
+#: ../../source/installation/overview.rst:23 d1f8d643fc9c4153a7cccf3caf57046b
 msgid "If you have ``PaddlePaddle`` installed already, please skip this step."
 msgstr "如果你已经安装了 ``PaddlePaddle`` ，请跳过此步骤"
 
-#: ../../source/installation/overview.rst:25 b87b92322e59402cb49ca4724d15f035
+#: ../../source/installation/overview.rst:25 8b8194b53c8b4880a53c9e8d33458ad9
 msgid "Run below command to install PaddlePaddle via pip: ::"
 msgstr "运行下面的命令来用pip安装 PaddlePaddle"
 
-#: ../../source/installation/overview.rst:30 d86bc313bfb6441a902a9bc929a4a4dc
+#: ../../source/installation/overview.rst:30 9ae7d82fc06e4ed6b49eb921f939768e
 msgid ""
 "You may also refer to the PaddlePaddle website for a detailed "
 "installation guide:"
 msgstr "你也可以通过前往PaddlePaddle官方网站获取更多安装指南："
 
-#: ../../source/installation/overview.rst:32 2eec241e95374d08881b3d1585878c59
+#: ../../source/installation/overview.rst:32 cae95ba22e5148acb014e7a356c15746
 msgid ""
 "`PaddlePaddle Install Guide "
 "<https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/compile"
 "/linux-compile.html>`__"
-msgstr "`PaddlePaddle 安装指南 " 
+msgstr ""
+"`PaddlePaddle 安装指南 "
 "<https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/compile"
 "/linux-compile.html>`__"
 
-#: ../../source/installation/overview.rst:34 645f63273fc24abf8b32b083b932772e
+#: ../../source/installation/overview.rst:34 d39dd81aa936426abfab8c9fe52b58a8
 msgid "2）Update protobuf (Only needed if paddle version < 2.3.1)"
 msgstr "2）更新protobuf版本（当paddlepaddle 版本< 2.3.1时需要）"
 
-#: ../../source/installation/overview.rst:36 9f06376960d24a00bfaafa82c1a6d3e3
+#: ../../source/installation/overview.rst:36 48271edc200342858035e9b27f0fbb28
 msgid ""
 "The version of protobuf required is 3.19.x - 3.20.x. If your protobuf "
 "version is earlier than v3.19 or later than v3.20, you need to upgrade or"
 " downgrade it."
 msgstr "Protobuf的版本要求为 3.19.x - 3.20.x, 如果你的版本不符合则需要更新"
 
-#: ../../source/installation/overview.rst:39 aded626017f34833a5b3076e73b1a806
+#: ../../source/installation/overview.rst:39 41c342ac9171469195e6167968111337
 msgid "Check protobuf version ::"
 msgstr "检查protobuf版本"
 
-#: ../../source/installation/overview.rst:44 4fa8d8cef3be4a989610762c25f1b52c
+#: ../../source/installation/overview.rst:44 c901d01f58114e4a8a0335d09d35fd08
 msgid "Update protobuf ::"
 msgstr "更新protobuf"
 
-#: ../../source/installation/overview.rst:50 11de08c1cf57486b90de153f4465ed42
+#: ../../source/installation/overview.rst:50 e7a8e29ab4b945b39c3205626f0516b7
 msgid "Install PaddleTS"
 msgstr "安装 paddlepaddle"
 
-#: ../../source/installation/overview.rst:51 4fa7655131324998bc23a4321b425128
+#: ../../source/installation/overview.rst:51 7bae048c4a384459a348d26b3783334e
 msgid ""
 "It is strongly recommended that Mac M1 users use the python environment "
 "in conda to install paddlets. The original python of M1 may encounter "
 "problems during the installation process."
 msgstr "强烈建议Mac M1 用户用conda内的python环境装paddlets， 因为M1原装的python在安装过程中可能会遇到问题。"
 
-#: ../../source/installation/overview.rst:55 0ba103a016784acd9d8126d475fcf397
+#: ../../source/installation/overview.rst:55 86d409589ab94d8382b4393f02da8dd1
 msgid "Install PaddleTS with pip"
 msgstr "用pip安装PaddleTS"
 
-#: ../../source/installation/overview.rst:62 9b3f3371a5fd4ceda5df36eeef12e960
-msgid "Install PaddleTS with conda"
-msgstr "用conda安装PaddleTS"
-
-#: ../../source/installation/overview.rst:69 3e5dce380e1c49e993ff0a42928a5baf
+#: ../../source/installation/overview.rst:62 13ad571d65e340d59eaa5aac92b279ea
 msgid "Install PaddleTS with docker"
 msgstr "用docker安装PaddleTS"
 
-#: ../../source/installation/overview.rst:70 906559a7198e492b93032db252c8c135
+#: ../../source/installation/overview.rst:63 1514aa4b64ac4eee90038c495dd23c58
 msgid ""
 "`Docker <https://docs.docker.com/engine/install/>`_ needs to be installed"
 " locally."
 msgstr "需要提前在本地安装 `Docker <https://docs.docker.com/engine/install/>`_ "
 
-#: ../../source/installation/overview.rst:73 c9029cabbeb3415d9ac07f160573f0e4
+#: ../../source/installation/overview.rst:66 a1934fe35f08407e8152425e2709f7b6
 msgid "1）Pull PaddleTS image"
 msgstr "1)远程拉取"
 
-#: ../../source/installation/overview.rst:80 d55a2aa718ac4d868a23e7dc57ccc677
+#: ../../source/installation/overview.rst:73 151be6dbef334ae6bcd6dc264b44a754
 msgid "2）Start container"
 msgstr "2）启动容器"
+
+
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/modules/models/overview.po b/docs/locale/zh_CN/LC_MESSAGES/source/modules/models/overview.po
index 8e62cbe2..ad3eff52 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/modules/models/overview.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/modules/models/overview.po
@@ -8,39 +8,40 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PaddleTS \n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2022-07-21 18:08+0800\n"
+"POT-Creation-Date: 2022-07-26 10:45+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: LANGUAGE <LL@li.org>\n"
 "MIME-Version: 1.0\n"
 "Content-Type: text/plain; charset=utf-8\n"
 "Content-Transfer-Encoding: 8bit\n"
-"Generated-By: Babel 2.9.1\n"
+"Generated-By: Babel 2.10.3\n"
 
-#: ../../source/modules/models/overview.rst:3 eaf3eeb3665d4aa08812e25ab03fb644
+#: ../../source/modules/models/overview.rst:3 b40c430a0ad04feca0b4a404d0adbd8d
 msgid "Models"
 msgstr "模型"
 
-#: ../../source/modules/models/overview.rst:5 cde3b2e46c3744d596e2fd068003aa5a
+#: ../../source/modules/models/overview.rst:5 3ee92fc0c89a4c349ab863e0df5bb58b
 msgid ""
 "Before reading this document, it is recommended to first read the "
-"`TSDataset Document <../datasets/overview>`_ to understand the design of "
-"`TSDataset`. Simply speaking, `TSDataset` is a unified time series data "
-"structure throughout the whole modeling lifecycle. It introduces several "
-"fundamental but important time series related concepts such as ``target``"
-" (including ``past_target`` and ``future_target``) and ``covariates`` "
-"(including ``known_covariates`` and ``observed_covariates``). A good "
-"understanding of those concepts would be helpful for deep diving into "
-"this documentation and building well-performed models."
+"`TSDataset Document <../datasets/overview.html>`_ to understand the "
+"design of `TSDataset`. Simply speaking, `TSDataset` is a unified time "
+"series data structure throughout the whole modeling lifecycle. It "
+"introduces several fundamental but important time series related concepts"
+" such as ``target`` (including ``past_target`` and ``future_target``) and"
+" ``covariates`` (including ``known_covariates`` and "
+"``observed_covariates``). A good understanding of those concepts would be"
+" helpful for deep diving into this documentation and building well-"
+"performed models."
 msgstr ""
-"在阅读本文档之前，建议先阅读 `TSDataset 文档 <../datasets/overview>`_ ，以了解TSDataset的设计。 "
+"在阅读本文档之前，建议先阅读 `TSDataset 文档 <../datasets/overview.html>`_ ，以了解TSDataset的设计。 "
 "简单来说，TSDataset是PaddleTS中贯穿整个建模生命周期的、统一的时间序列数据结构。它引出了几个基本但重要的时间序列相关概念，例如待预测目标（过去目标、未来目标）以及协变量（观测协变量和未来已知协变量）。对这些概念的理解将有助于深入探究该文档并构建性能良好的模型。"
 
-#: ../../source/modules/models/overview.rst:11 b3be9f02d0b74897a3cb06cc06c80443
+#: ../../source/modules/models/overview.rst:11 41137ec29b0a4a98b48b7465fe98e0a8
 msgid "PaddleTS provides three high-level features for deep time series modeling:"
 msgstr "从一个较高的视角来看，PaddleTS 提供了以下三个时序建模相关的特性："
 
-#: ../../source/modules/models/overview.rst:13 3aa56c958af64a638bc8b6ea30b98765
+#: ../../source/modules/models/overview.rst:13 e9022cdfcf7a4a8bbd0887b639537b55
 msgid ""
 "Standard interfaces. The interfaces (`fit`, `predict`) declared in "
 "`PaddleBaseModel` are designed to accept and return the unified "
@@ -51,7 +52,7 @@ msgstr ""
 "标准化的接口。 这些在 `PaddleBaseModel` 中声明的 `fit`、`predict` 标准化接口接收、返回统一的 "
 "`TSDataset` 数据集，作为其输入输出，以便将一些数据集处理和样本构建的复杂细节封装起来，简化API的使用，降低学习成本。"
 
-#: ../../source/modules/models/overview.rst:16 66a262ac5d9e436091130c6c2adab58d
+#: ../../source/modules/models/overview.rst:16 07517590e77f49a18d4734dd55a13691
 msgid ""
 "PaddleTS introduces the `PaddleBaseModelImpl` class, which consists of a "
 "set of common functions and components throughout the modeling lifecycle "
@@ -63,103 +64,103 @@ msgstr ""
 "准备样本，初始化模型性能指标, "
 "计算损失等）。这使得用户可以更关注深度网络架构本身，同时也为广大开发者基于PaddleTS构建新的时序模型提供了最大程度的便利。"
 
-#: ../../source/modules/models/overview.rst:19 dacdb43b9c864a04975342e512a5b1ec
+#: ../../source/modules/models/overview.rst:19 0ea6a751beed443fb2edec4e19bb36ea
 msgid ""
 "Out-of-box models. PaddleTS provides off-the-shelf deep time series "
 "models:"
 msgstr "开箱即用的模型。PaddleTS提供一组预定义的，开箱即用的时序深度学习模型："
 
-#: ../../source/modules/models/overview.rst:21 722c99fe739042b4b1908145b5579cf0
+#: ../../source/modules/models/overview.rst:21 8bfaad42b9ac4758b43e8f3681eb2580
 msgid ""
 "`Long Short-term Time-series Network "
 "<../../api/paddlets.models.dl.paddlepaddle.lstnet.html>`_"
 msgstr ""
 
-#: ../../source/modules/models/overview.rst:22 957636a1641c4e1e8afc5d9e31c1a78f
+#: ../../source/modules/models/overview.rst:22 0f5b7141a30c4df4b0e50c387c1104c6
 msgid ""
 "`Multilayer Perceptron "
 "<../../api/paddlets.models.dl.paddlepaddle.mlp.html>`_"
 msgstr ""
 
-#: ../../source/modules/models/overview.rst:23 efd441508d2f4f39b33bd792a0090474
+#: ../../source/modules/models/overview.rst:23 697c3b6dc1b643fd8402b1854a7baa26
 msgid "`NBEATSModel <../../api/paddlets.models.dl.paddlepaddle.nbeats.html>`_"
 msgstr ""
 
-#: ../../source/modules/models/overview.rst:24 efd441508d2f4f39b33bd792a0090474
+#: ../../source/modules/models/overview.rst:24 98023ec14b824ca9b878a3c9e47f17f1
 msgid "`NHiTSModel <../../api/paddlets.models.dl.paddlepaddle.nhits.html>`_"
 msgstr ""
 
-#: ../../source/modules/models/overview.rst:25 f0ac262e7d874d32accc05f0d853f42f
+#: ../../source/modules/models/overview.rst:25 9c74adf53ea74db89242726d1070a784
 msgid "`RnnBlockRegressor <../../api/paddlets.models.dl.paddlepaddle.rnn.html>`_"
 msgstr ""
 
-#: ../../source/modules/models/overview.rst:26 f0ac262e7d874d32accc05f0d853f42f
+#: ../../source/modules/models/overview.rst:26 49aefa649533437ca7a53c7b16832af1
 msgid ""
 "`Temporal Convolution Net Regressor "
 "<../../api/paddlets.models.dl.paddlepaddle.tcn.html>`_"
 msgstr ""
 
-#: ../../source/modules/models/overview.rst:27 efd441508d2f4f39b33bd792a0090474
+#: ../../source/modules/models/overview.rst:27 9681f8ee807f411f8e47f8872c232a75
 msgid ""
 "`Transformer "
 "<../../api/paddlets.models.dl.paddlepaddle.transformer.html>`_"
 msgstr ""
 
-#: ../../source/modules/models/overview.rst:31 3619878cd7914115a21581205a027d6a
+#: ../../source/modules/models/overview.rst:31 6a1ebec7cabb4cbd8f56d0db45f033c5
 msgid "1. A minimal example"
 msgstr "1. 一个最小化的示例"
 
-#: ../../source/modules/models/overview.rst:33 5f6ec2d2d3484c71a3caba22f62eff76
+#: ../../source/modules/models/overview.rst:33 b534183ca1cf4d55bae0b2518d372b66
 msgid ""
 "Below minimal example uses a built-in `RNNBlockRegressor` model to "
 "illustrate the basic usage."
 msgstr "下方的最小化示例使用了PaddleTS内置的 RNNBlockRegressor 模型来阐述基本的使用方法。"
 
-#: ../../source/modules/models/overview.rst:70 402402b557634bd99da5694328b79fd0
+#: ../../source/modules/models/overview.rst:70 e925fbe653a24b8f8d0d5d992e33cda7
 msgid "2. PaddleBaseModel"
 msgstr "2. PaddleBaseModel"
 
-#: ../../source/modules/models/overview.rst:72 4f0a16e403aa413c841186a457146d8c
+#: ../../source/modules/models/overview.rst:72 382f76ca14ae46529534804865332db4
 msgid ""
 "PaddleBaseModel is the base class for all PaddlePaddle-based time series "
 "models. Below is a simplified version of the **PaddleBaseModel** class "
 "declaration, the lengthy implementation details are skipped, you may "
 "refer to the `PaddleBaseModel API "
-"<../../api/paddlets.models.dl.paddlepaddle.paddle_base>`_ to get a full "
-"view."
+"<../../api/paddlets.models.dl.paddlepaddle.paddle_base.html>`_ to get a "
+"full view."
 msgstr ""
 "`PaddleBaseModel` 是所有基于PaddlePaddle框架构建的时序模型的基类。 下方展示了一个简化版的 "
 "`PaddleBaseModel` 类声明， 此处略去了源代码中冗长的实现细节， 旨在于展示最重要的接口定义部分。 您可以参考文档 "
 "`PaddleBaseModel API "
 "<../../api/paddlets.models.dl.paddlepaddle.paddle_base>`_ 获取完整的代码。"
 
-#: ../../source/modules/models/overview.rst:79 0983cc7119de48dca95fe0069176bcb4
+#: ../../source/modules/models/overview.rst:79 7ade0a1110c44b019f3d4e1ab88dcb0e
 msgid "2.1. Construct method"
 msgstr "2.1. 构造方法"
 
 #: ../../source/modules/models/overview.rst:102
-#: f1319e7c5e9045ecb57961f30d13ac28
+#: ad850dba4fb5480b80df6965052c9c4b
 msgid ""
 "As shown above, the constructor takes 2 required arguments and an "
 "optional argument:"
-msgstr "如下所示，构造方法接收2个必需参数和一个可选参数："
+msgstr "构造方法接收2个必需参数和1个可选参数："
 
 #: ../../source/modules/models/overview.rst:104
-#: 2766cde8c51847a195ae9cd84cb700bc
+#: a456d0181a114f619f817945e16ada28
 msgid ""
 "in_chunk_len: The size of the loopback window, i.e. the number of time "
 "steps feed to the model."
-msgstr "历史窗口的大小。即：提供给模型用于训练的时间步数。"
+msgstr "in_chunk_len：历史窗口的大小。即：提供给模型用于训练的时间步数。"
 
 #: ../../source/modules/models/overview.rst:105
-#: 4f682586200d48feafbe3b69ebf3f8be
+#: f0e21c10fa6f4a3c979cb56546f5f1df
 msgid ""
 "out_chunk_len: The size of the forecasting horizon, i.e. the number of "
 "time steps output by the model."
-msgstr "预测范围的大小。即：模型输出的时间步数。"
+msgstr "out_chunk_len：预测范围的大小。即：模型输出的时间步数。"
 
 #: ../../source/modules/models/overview.rst:106
-#: cf6929cba43641a0b789399a7918cde1
+#: 5a2f048d9a024943af5f67005bb1a6a4
 msgid ""
 "skip_chunk_len: Optional, the number of time steps between in_chunk and "
 "out_chunk for a single sample. The skip chunk is neither used as a "
@@ -171,18 +172,18 @@ msgstr ""
 "Y)。默认情况下不会跳过任何一个时间点。默认情况下不会跳过任何一个时间步。"
 
 #: ../../source/modules/models/overview.rst:110
-#: 7a43cb035f104065802a4e57fa56dbd2
+#: eccd2732e1214c6caa4914655b72b33b
 msgid ""
 "Below Figure 1 shows a concrete example to further explain the above "
 "concepts."
 msgstr "下方的图1通过一个具体的例子，进一步解释了上面提到的概念。"
 
-#: ../../source/modules/models/overview.rst:-1 89f5407aba504e2399d9229f60321d24
+#: ../../source/modules/models/overview.rst:-1 7506e043bdaa480685535ead9a3f0d49
 msgid "TSDataset of wind speed with difference skip_chunk_len specified"
 msgstr "一个设置了不同的 skip_chunk_len 值的，包含风速的TSDataset数据集"
 
 #: ../../source/modules/models/overview.rst:115
-#: bff62bb0d11f4526a2b448505c23d2bd
+#: 0ab85fe2d74940a493c29b455d6c9d89
 msgid ""
 "Figure 1(a) defines a TSDataset of wind speed with an HOURLY level "
 "frequency. It totally contains 7 hours of wind speed data starts at 7:00 "
@@ -194,7 +195,7 @@ msgstr ""
 " 14:00 - 15:00 这段时间的风速数据。"
 
 #: ../../source/modules/models/overview.rst:119
-#: 3b5b1c3f9ba44046a8529cfdc9f0ed73
+#: bfdd0465a7764f24bda45c60ecc20296
 msgid ""
 "Figure 1(b) sets the `in_chunk_len` = 4, `skip_chunk_len` = 0, "
 "`out_chunk_len` = 2, which indicates the following:"
@@ -204,28 +205,28 @@ msgstr ""
 
 #: ../../source/modules/models/overview.rst:121
 #: ../../source/modules/models/overview.rst:128
-#: 9602e60b273545ee95a9d4235a8ed773 b099fa82e28044519ff09aa7e985973c
+#: ac5c451d24cb41a8a873146baf5c00db e022e87c1846423c84d09d015c8de2ab
 msgid ""
 "A 4-hour contiguous chunk of wind speed start at 7:00, i.e., [70, 80, 90,"
 " 100], will be treated as in_chunk."
 msgstr "一个长度为4小时的，开始于7:00的连续数据块，即 [70, 80, 90, 100]，将被视为 in_chunk。"
 
 #: ../../source/modules/models/overview.rst:122
-#: 820d00ff887b4347a1141ec573051a85
+#: d12bd9592da74a0b9bfc3e0a064a9724
 msgid ""
 "A 2-hour contiguous chunk of wind speed start at 11:00, which follows "
 "behind the in_chunk, i.e., [110, 120], will be treated as out_chunk."
 msgstr "一个长度为2小时的，紧跟在 in_chunk 后面，开始于11:00的连续数据块，即 [110, 120]，将被视为 out_chunk。"
 
 #: ../../source/modules/models/overview.rst:123
-#: f9abcf094c3e4901b5c5acfeb930bb07
+#: cbd2971b52e94db19a3d4d651f3edf71
 msgid ""
 "As the `skip_chunk_len` is set to 0, no time units between in_chunk and "
 "out_chunk are skipped."
 msgstr "由于 `skip_chunk_len` 等于 0，所以在in_chunk和out_chunk之间没有任何时间点被跳过。"
 
 #: ../../source/modules/models/overview.rst:125
-#: b67a8f3ff92f48fbb6aca10f327363de
+#: 968f1944d85b4a60bc15497ead102f5e
 msgid ""
 "The value of `in_chunk_len` and `out_chunk_len` shown in Figure 1(c) are "
 "identical to that of Figure 1(b), except that the `skip_chunk_len` is "
@@ -237,21 +238,21 @@ msgstr ""
 " 3, `out_chunk_len` = 2, 则说明有以下描述成立："
 
 #: ../../source/modules/models/overview.rst:129
-#: d3b09615b1304a2f967158a17bfb3ba5
+#: a80edc6d36d043669270faefcf969a66
 msgid ""
 "A 3-hour contiguous chunk of wind speed start at 11:00, which follows "
 "behind the in_chunk, i.e., [110, 120, 130], will be skipped."
 msgstr "一个长度为2小时的，紧跟在in_chunk后面的，开始于11:00的连续数据块，即 [110, 120, 130]，将被跳过。"
 
 #: ../../source/modules/models/overview.rst:130
-#: 6b0d7142c97f4328854370f3918731fc
+#: 82081ee5f41246e9b98a42213b4efa52
 msgid ""
 "A 2-hour contiguous chunk of wind speed start at 14:00, which follows "
 "behind the skip_chunk, i.e., [140, 150], will be treated as out_chunk."
 msgstr "一个长度为2小时的，紧跟在 skip_chunk 后面，开始于14:00的连续数据块，即 [140, 150]，将被视为 out_chunk。"
 
 #: ../../source/modules/models/overview.rst:132
-#: a9212dba24074018af23368835e86829
+#: 634eda83774c4028b3d27ff0672d2cf2
 msgid ""
 "In conclusion, the current model will use the wind speed of the past 4 "
 "hours to predict the wind speed of the future 2 hours. Meanwhile, it can "
@@ -262,17 +263,17 @@ msgstr ""
 " `skip_chunk_len` 设置为一个正整数来实现。"
 
 #: ../../source/modules/models/overview.rst:137
-#: 96fb90ae1dfb4e86ac37d4ec8ffe8d93
+#: d0d2a19a92c1477399b5c744498179d1
 msgid "2.2. Fit"
 msgstr "2.2. 训练"
 
 #: ../../source/modules/models/overview.rst:139
-#: 21473ba028584f5d85f09a687bed479a
+#: a2fc302614bb4c24acb89dba6d42c1c9
 msgid "All the time series models in PaddleTS have the same fit interface."
 msgstr "在PaddleTS中，所有的时序模型具有相同的训练接口。"
 
 #: ../../source/modules/models/overview.rst:141
-#: cb4a56455ad04eb5a07b747c259e9b81
+#: 598e3cc383634c35bfb5cb9483ceca37
 msgid ""
 "To allow users to focus more on the higher level view, the fit method "
 "accepts TSDatasets as the training data argument rather than an array-"
@@ -283,22 +284,22 @@ msgstr ""
 "从而完成了对基于数据集拆分样本集合的细节的封装。"
 
 #: ../../source/modules/models/overview.rst:145
-#: 9adec75528eb44a4a59f890ce46b2af9
+#: 1cd97e0d4d4b48af8cfd9c529479ab2f
 msgid "The simplified fit method is as follows:"
 msgstr "下面展示了简化版的fit方法："
 
 #: ../../source/modules/models/overview.rst:164
-#: 94ad9a23852541e4aae44119d42a8e89
+#: ae165659453740d5997df15b111a3eb8
 msgid "See below Figure 2 for further explanation:"
 msgstr "参考以下图2作为进一步解释说明："
 
-#: ../../source/modules/models/overview.rst:-1 31af08ee01d84011bebb9f5429a40e9d
-#: 455ca7169e2f4603a8399be755e4c333
+#: ../../source/modules/models/overview.rst:-1 26d1de0c84ad4ada9ab881d7ae51dd9d
+#: 83baf2ee53c64f97b7374aff81df9b75
 msgid "TSDataset Example"
 msgstr "TSDataset 示例"
 
 #: ../../source/modules/models/overview.rst:169
-#: dd92e80dfcbd471d952938b567b9b4e5
+#: 661e91faa3064fb3a4b26e75e458f4b3
 msgid ""
 "In this case, the fit method takes the above grey-highlighted TSDataset "
 "as the train_data argument and internally split the TSDataset into a set "
@@ -308,12 +309,12 @@ msgstr ""
 "并且在内部完成了数据集的拆分和样本集的构建（如上图中红色高亮部分所示）。"
 
 #: ../../source/modules/models/overview.rst:174
-#: 0247e18f28a74c2cbb5b5479f9639850
+#: 5546ea56643e4f8787c96eca6404aea9
 msgid "2.3. Predict"
 msgstr "2.3. 预测"
 
 #: ../../source/modules/models/overview.rst:176
-#: 01aba9ffdc4e4e6d87d06dd14015faba
+#: 748318a2d952416e8d7488ab2d407118
 msgid ""
 "All models have the same predict interface. It accepts a TSDataset "
 "argument contains both `past target` and corresponding covariates, then "
@@ -326,55 +327,55 @@ msgstr ""
 "target` 时序数据块，其长度等于 `out_chunk_len`。"
 
 #: ../../source/modules/models/overview.rst:180
-#: 701abe83b6654842936a33fa924dfbad
+#: ba7c5341a2664418a18b8b19d267efdc
 msgid "The following points are worthwhile to be aware of:"
 msgstr "对于该接口，有以下几点值得注意："
 
 #: ../../source/modules/models/overview.rst:182
-#: 8ffcff0ec88c47be88eb3bd5be7519b3
+#: e7f242d1eb494a20a58a9aba725c7132
 msgid ""
 "The TSDataset argument of this method only contains the past target and "
 "corresponding covariates, but not contain the future target."
 msgstr "当前方法的TSDataset入参中仅包含过去的观测target和一些相关的协变量，并不包括未来的target。"
 
 #: ../../source/modules/models/overview.rst:183
-#: 3e4a8779d7c04580bef184c1776849db
+#: affa94f05abd4025b23c5a0f6403e792
 msgid "The predict method only constructs one sample from the TSDataset argument."
 msgstr "预测方法仅会从给定的数据集参数中构建一条样本。"
 
 #: ../../source/modules/models/overview.rst:184
-#: 66ad99af1acb475aa4b598bcb32cae34
+#: a0ba4f122e3e4b999cc7349cc12a909a
 msgid ""
 "The length of the predicted result for a single `predict` call is equal "
 "to out_chunk_len."
 msgstr "对于单次 `predict` 方法的调用，预测得到的结果的长度等于out_chunk_len的值。"
 
 #: ../../source/modules/models/overview.rst:186
-#: ea575203448340dab9d9a10d4ccdc136
+#: fe6370e6784246ea878b2a1f10bb5943
 msgid "Below is the simplified `predict` method:"
 msgstr "下方展示了简化版的 `predict` 方法："
 
 #: ../../source/modules/models/overview.rst:201
-#: 7a43cb035f104065802a4e57fa56dbd2
+#: 1ca13b1a9864415f91c3dd570ac14788
 msgid ""
 "We will further explain it through a concrete example. Suppose we have a "
 "TSDataset shown in the below Figure 3:"
 msgstr "我们用一个具体示例进一步对其说明。假设我们有一个如下图3所示的TSDataset数据集："
 
 #: ../../source/modules/models/overview.rst:206
-#: 3b5b1c3f9ba44046a8529cfdc9f0ed73
+#: 917ce842367a4ea0aaccab268b2b8c82
 msgid ""
 "given in_chunk_len = 2, out_chunk_len = 2, skip_chunk_len = 1, the "
 "following statements hold:"
 msgstr "给定 in_chunk_len = 2, out_chunk_len = 2, skip_chunk_len = 1, 则以下叙述成立："
 
 #: ../../source/modules/models/overview.rst:208
-#: d3d88954b6fd4e8792e3a1e3a5c64935
+#: d7f1fc6099c043aba64565f837d61ed7
 msgid "The data between 7:00 and 13:00 will all be treated as the `past target`."
 msgstr "在 7:00 到 13:00 之间的数据都将被视为过去的target数据。"
 
 #: ../../source/modules/models/overview.rst:209
-#: 02c1e1fe405a4026b9fecc1d799edfc4
+#: 93f0e538253048138985bda0d4321ffc
 msgid ""
 "As only one sample will be constructed per each call, while known that "
 "in_chunk_len = 2, skip_chunk_len = 1, out_chunk_len = 2, thus the data "
@@ -386,12 +387,12 @@ msgstr ""
 "16:00 之间的未来数据， 其中14:00点的数据会被跳过。"
 
 #: ../../source/modules/models/overview.rst:214
-#: dc74e7164f164b9b858a6972db8e0bb5
+#: 15060dced9ac49bb827a09ff9688318a
 msgid "2.4. Recursive predict"
 msgstr "2.4. 递归多步预测"
 
 #: ../../source/modules/models/overview.rst:215
-#: 0c1dd7c5ed344256a7ccb86ab8d285b8
+#: 9a142b0e55c94ed486c373bb2a3771a3
 msgid ""
 "All models have the same `model.recursive_predict` interface. The "
 "recursive strategy involves applying `model.predict` method iteratively "
@@ -400,11 +401,11 @@ msgid ""
 "appear in the loopback window for the next call."
 msgstr ""
 "所有模型均拥有一致的递归多步预测接口。递归多步预测的策略是：一步步利用 `model.predict` "
-"方法实现多步时序预测。当前时刻的预测结果会被添加至 `TSDataset` 时序数据集"
-"的目标列中，并在模型预测时，被添加至历史目标值的滑动窗口中用于下一时刻预测。"
+"方法实现多步时序预测。当前时刻的预测结果会被添加至 `TSDataset` "
+"时序数据集的目标列中，并在模型预测时，被添加至历史目标值的滑动窗口中用于下一时刻预测。"
 
 #: ../../source/modules/models/overview.rst:220
-#: 79ea786b928e4de190b8889b6dffd9b1
+#: a8a63f652147481a8a3a702631c9c0c6
 msgid ""
 "Note that each call of `model.predict` will return a result of length "
 "`out_chunk_len`, so `model.recursive_predict` will be called "
@@ -415,24 +416,24 @@ msgstr ""
 "ceiling(`predict_length`/`out_chunk_len`) 次，以满足多步时序的输出长度需求。"
 
 #: ../../source/modules/models/overview.rst:223
-#: cd619de7ec824a43869e36529988658b
+#: 54cb4479efa94989942256e80b414937
 msgid ""
 "For example, the `out_chunk_length` of the model mentioned before is 96, "
 "but `model.recursive_predict` allows you to set `predict_length` as 3 * "
 "96 or more, then you get a predicted result of length 3 * 96."
 msgstr ""
-"例如，上述例子中的 `Model` 的 `out_chunk_length` 是 96 ，而 `model.recursive_predict` 允许你将 "
-"`predict_length` 设置为 3 * 96 或者更多。"
+"例如，上述例子中的 `Model` 的 `out_chunk_length` 是 96 ，而 `model.recursive_predict` "
+"允许你将 `predict_length` 设置为 3 * 96 或者更多。"
 
 #: ../../source/modules/models/overview.rst:231
-#: c1624f85a4704bee8497066ff2cc8cbe
+#: 1f6a389c39cc4aef89bcc1395d2d139e
 msgid ""
 "Note that `model.recursive_predict` is not supported when "
 "`model.skip_chunk` != 0."
 msgstr "注意： `model.recursive_predict` 函数在 `model.skip_chunk` != 0 时，无法使用。"
 
 #: ../../source/modules/models/overview.rst:233
-#: a69e9d38281a40249e10c17c099a5be0
+#: fbbc93b4256a444591549b8b77551850
 msgid ""
 "For detailed usage, please refer to `API: BaseModel.recursive_predict "
 "<../../api/paddlets.models.base.html#paddlets.models.base.BaseModel.recursive_predict>`_"
@@ -442,21 +443,21 @@ msgstr ""
 "<../../api/paddlets.models.base.html#paddlets.models.base.BaseModel.recursive_predict>`_"
 
 #: ../../source/modules/models/overview.rst:235
-#: 425407dfaef64389bcf745491f98e00f
+#: 8bd3ceae41fd4d979189cf32a0a7dd4c
 msgid ""
 "For advanced predict-related capability `Backtest`, please refer to `API:"
-" Backtest <../../api/paddlets.models.utils.backtest.html>`_ ."
+" Backtest <../../api/paddlets.utils.backtest.html>`_ ."
 msgstr ""
 "对于PaddleTS提供的与预测相关的 `Backtest` 回测能力，请参考：`API: Backtest "
 "<../../api/paddlets.utils.backtest.html>`_"
 
 #: ../../source/modules/models/overview.rst:238
-#: 5b0fae6be36c43b499382437463330bc
+#: eb6299901afe4036b832ac8a7d184569
 msgid "2.5. Model persistence"
 msgstr "2.5. 模型持久化"
 
 #: ../../source/modules/models/overview.rst:240
-#: 6c38cce10c004fe0a783294bdfd9ef83
+#: 386d4a7b5bee4bc4be31355cf8d40d31
 msgid ""
 "After fitting a PaddleBaseModel, it is necessary to have a way to persist"
 " the model for future use without retraining the model. We also provide a"
@@ -464,14 +465,13 @@ msgid ""
 msgstr "模型训练完成后，我们仍需提供一种将训练完成的模型持久化的方法，以便在未来希望使用该模型时无需对其重复训练。同时，我们也提供一个统一的方法，用于加载一个已经被保存在硬盘上的PaddleBaseModel模型。"
 
 #: ../../source/modules/models/overview.rst:243
-#: 258a6180bb7441a696785efd127e63d2
+#: 676eca994785406dbec681173cefeff7
 msgid ""
 "The following sections show you how to persist a PaddleBaseModel. Note "
 "that a model can be saved multiple times."
 msgstr "以下的代码示例展示了如何持久化保存一个 PaddleBaseModel 模型。请注意，同一个模型可以被保存多次。"
 
 #: ../../source/modules/models/overview.rst:262
-#: bfafd52fc1bf43948ecbe34e9bd81866
+#: 672bc390289a471da376615c052e9c12
 msgid "Later you can load back the persisted model with:"
 msgstr "在模型保存完成的一段时间之后，您可以通过以下方式加载模型："
-
diff --git a/docs/locale/zh_CN/LC_MESSAGES/source/modules/transform/overview.po b/docs/locale/zh_CN/LC_MESSAGES/source/modules/transform/overview.po
index 99de7cde..e41ba3fa 100644
--- a/docs/locale/zh_CN/LC_MESSAGES/source/modules/transform/overview.po
+++ b/docs/locale/zh_CN/LC_MESSAGES/source/modules/transform/overview.po
@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PaddleTS \n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2022-07-21 21:11+0800\n"
+"POT-Creation-Date: 2022-07-26 10:45+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: LANGUAGE <LL@li.org>\n"
@@ -18,28 +18,29 @@ msgstr ""
 "Generated-By: Babel 2.10.3\n"
 
 #: ../../source/modules/transform/overview.rst:3
-#: 0751d1b87fba4b2e994d9c50fa36cb48
+#: 7b1f667b275045468daedc760613c1b8
 msgid "Transform"
 msgstr "Transform"
 
 #: ../../source/modules/transform/overview.rst:5
-#: 541b22b821f54e478cee8e7f8a305d25
+#: 8a9e85e356284056a6e7a96843218cd4
 msgid ""
 "Before reading this document, it is recommended to first read the "
-"`TSDataset Document <../datasets/overview>`_ to understand the design of "
-"`TSDataset`. Simply speaking, `TSDataset` is a unified time series data "
-"structure throughout the modeling lifecycle. It introduces several "
-"fundamental but important time series related concepts such as ``target``"
-" (including ``past_target`` and ``future_target``) and ``covariates`` "
-"(including ``known_covariates`` and ``observed_covariates``). A good "
-"understanding of those concepts would be helpful for deep diving into "
-"this documentation and building well-performed models."
+"`TSDataset Document <../datasets/overview.html>`_ to understand the "
+"design of `TSDataset`. Simply speaking, `TSDataset` is a unified time "
+"series data structure throughout the modeling lifecycle. It introduces "
+"several fundamental but important time series related concepts such as "
+"``target`` (including ``past_target`` and ``future_target``) and "
+"``covariates`` (including ``known_covariates`` and "
+"``observed_covariates``). A good understanding of those concepts would be"
+" helpful for deep diving into this documentation and building well-"
+"performed models."
 msgstr ""
-"在阅读本文档之前，建议先阅读 `TSDataset 文档 <../datasets/overview>`_ ，以了解TSDataset的设计。 "
+"在阅读本文档之前，建议先阅读 `TSDataset 文档 <../datasets/overview.html>`_ ，以了解TSDataset的设计。 "
 "简单来说，TSDataset是PaddleTS中贯穿整个建模生命周期的、统一的时间序列数据结构。它引出了几个基本但重要的时间序列相关概念，例如待预测目标（过去目标、未来目标）以及协变量（观测协变量和未来已知协变量）。对这些概念的理解将有助于深入探究该文档并构建性能良好的模型。"
 
 #: ../../source/modules/transform/overview.rst:11
-#: 53a87c51f39c4efab3398aeb5a7049e9
+#: 72ede16309994de6ac566aa12c0669f8
 msgid ""
 "PaddleTS provides a series of operators for data transformation, which "
 "can be applied to fill missing values, normalize the data, or encode the "
@@ -57,52 +58,52 @@ msgstr ""
 "方法将训练完成的数据转换模块应用于待转换的数据集；fit_transform 方法将 fit 和 transform 提供的能力合并到一步内完成。"
 
 #: ../../source/modules/transform/overview.rst:18
-#: 3f85b5f7b05242669c3e22abd2732330
+#: c63cdfc22c4246b38a2d7125bc117912
 msgid "Currently, PaddleTS supports the following data transformations:"
 msgstr "目前PaddleTS支持以下时序数据转换能力："
 
 #: ../../source/modules/transform/overview.rst:20
-#: e9236716ddb24a718e035aeabcc5aeee
+#: 70e6fefae47142de99bbf818de1ef554
 msgid "`fill <../../api/paddlets.transform.fill.html>`_"
 msgstr ""
 
 #: ../../source/modules/transform/overview.rst:21
-#: db430f7fe0da48d48dee2edef0df15cd
+#: 6d5841381923446e94b34b0db3773e3b
 msgid "`ksigma <../../api/paddlets.transform.ksigma.html>`_"
 msgstr ""
 
 #: ../../source/modules/transform/overview.rst:22
-#: 635bfe67502e4759b30a46a736c8dbe3
+#: 1a6a7d407c27496baba9351c38a03cab
 msgid "`normalization <../../api/paddlets.transform.normalization.html>`_"
 msgstr ""
 
 #: ../../source/modules/transform/overview.rst:23
-#: 0a103c218dbe4c45b6d57e3ede4c6abb
+#: 27fbde3b2b8d4896830beb224eb6e597
 msgid "`onehot <../../api/paddlets.transform.onehot.html>`_"
 msgstr ""
 
 #: ../../source/modules/transform/overview.rst:24
-#: d04c8ba90bc3411f957ce6285d781c6c
+#: a83a8e8ca31b48a0acf276590fb1d306
 msgid "`ordinal <../../api/paddlets.transform.ordinal.html>`_"
 msgstr ""
 
 #: ../../source/modules/transform/overview.rst:25
-#: e42f142855dd4e6a9423d621baf07210
+#: c1a8dea6ad2d49b786dbada485357317
 msgid "`statistical <../../api/paddlets.transform.statistical.html>`_"
 msgstr ""
 
 #: ../../source/modules/transform/overview.rst:26
-#: 3e47e7a3eaa94846ad460d368261651d
+#: 3eaf4209904b4352b99475b3d5075f20
 msgid "`time_feature <../../api/paddlets.transform.time_feature.html>`_"
 msgstr ""
 
 #: ../../source/modules/transform/overview.rst:29
-#: d59625940f1845b7bf41164bb9fe83b2
+#: a9d745bef7a344279fb48e908ebd8170
 msgid "1. Example"
 msgstr "1. 示例"
 
 #: ../../source/modules/transform/overview.rst:31
-#: b956bf711e7e4eb8a829f1f9555264a8
+#: f09954dcbe25498f9c760e8e8388a674
 msgid ""
 "The below demo takes `OneHot <../../api/paddlets.transform.onehot.html>`_"
 " as an example to illustrates the basic usage of data transformations."
@@ -111,7 +112,7 @@ msgstr ""
 "作为一个具体的transform实例来阐述基本用法。"
 
 #: ../../source/modules/transform/overview.rst:51
-#: b76b403ab9a64c839d1e7c16adf63ce8
+#: 64e5cc15dd5c4478b65dc549a97f3626
 msgid ""
 "Alternatively, one can also call the combined ``fit_transform`` to "
 "achieve the same purpose:"
diff --git a/docs/source/installation/overview.rst b/docs/source/installation/overview.rst
index 6a9b7ce8..c8823d67 100644
--- a/docs/source/installation/overview.rst
+++ b/docs/source/installation/overview.rst
@@ -58,13 +58,6 @@ Install PaddleTS with pip
 
     python -m pip install paddlets
 
-Install PaddleTS with conda
-----------------------------------
-
-::
-
-    conda install paddlets
-
 Install PaddleTS with docker
 ====================================
 `Docker <https://docs.docker.com/engine/install/>`_ needs to be installed locally.
@@ -74,11 +67,12 @@ Install PaddleTS with docker
 
 ::
 
-    docker pull registry.baidubce.com/paddlets:latest
+    docker pull registry.baidubce.com/paddlets/paddlets:0.1.0
 
 2）Start container
 -----------------------
 
 ::
 
-    docker run --name paddle_docker -it -v $PWD:/paddle registry.baidubce.com/paddlets:latest  /bin/bash
\ No newline at end of file
+    docker run --name paddle_docker -it -v $PWD:/paddle registry.baidubce.com/paddlets/paddlets:0.1.0  /bin/bash
+
diff --git a/docs/source/modules/models/overview.rst b/docs/source/modules/models/overview.rst
index 60b49f7a..616bc2f6 100644
--- a/docs/source/modules/models/overview.rst
+++ b/docs/source/modules/models/overview.rst
@@ -2,7 +2,7 @@
 Models
 =========
 
-Before reading this document, it is recommended to first read the `TSDataset Document <../datasets/overview>`_ to understand the design of `TSDataset`.
+Before reading this document, it is recommended to first read the `TSDataset Document <../datasets/overview.html>`_ to understand the design of `TSDataset`.
 Simply speaking, `TSDataset` is a unified time series data structure throughout the whole modeling lifecycle.
 It introduces several fundamental but important time series related concepts such as
 ``target`` (including ``past_target`` and ``future_target``) and ``covariates`` (including ``known_covariates`` and ``observed_covariates``).
@@ -72,7 +72,7 @@ Below minimal example uses a built-in `RNNBlockRegressor` model to illustrate th
 PaddleBaseModel is the base class for all PaddlePaddle-based time series models.
 Below is a simplified version of the **PaddleBaseModel** class declaration,
 the lengthy implementation details are skipped,
-you may refer to the `PaddleBaseModel API <../../api/paddlets.models.dl.paddlepaddle.paddle_base>`_ to get a full view.
+you may refer to the `PaddleBaseModel API <../../api/paddlets.models.dl.paddlepaddle.paddle_base.html>`_ to get a full view.
 
 
 2.1. Construct method
@@ -232,7 +232,7 @@ Note that `model.recursive_predict` is not supported when `model.skip_chunk` !=
 
 For detailed usage, please refer to `API: BaseModel.recursive_predict <../../api/paddlets.models.base.html#paddlets.models.base.BaseModel.recursive_predict>`_ .
 
-For advanced predict-related capability `Backtest`, please refer to `API: Backtest <../../api/paddlets.models.utils.backtest.html>`_ .
+For advanced predict-related capability `Backtest`, please refer to `API: Backtest <../../api/paddlets.utils.backtest.html>`_ .
 
 2.5. Model persistence
 --------------------------
diff --git a/docs/source/modules/transform/overview.rst b/docs/source/modules/transform/overview.rst
index 7687ecaa..609daacd 100644
--- a/docs/source/modules/transform/overview.rst
+++ b/docs/source/modules/transform/overview.rst
@@ -2,7 +2,7 @@
 Transform
 ==========
 
-Before reading this document, it is recommended to first read the `TSDataset Document <../datasets/overview>`_ to understand the design of `TSDataset`.
+Before reading this document, it is recommended to first read the `TSDataset Document <../datasets/overview.html>`_ to understand the design of `TSDataset`.
 Simply speaking, `TSDataset` is a unified time series data structure throughout the modeling lifecycle.
 It introduces several fundamental but important time series related concepts such as
 ``target`` (including ``past_target`` and ``future_target``) and ``covariates`` (including ``known_covariates`` and ``observed_covariates``).
@@ -44,7 +44,7 @@ The below demo takes `OneHot <../../api/paddlets.transform.onehot.html>`_ as an
     # 3 fit the encoder
     encoder.fit(dataset=data)
     
-    # 4 do transforamtion with the learnt encoder
+    # 4 do transformation with the learnt encoder
     transformed_data = encoder.transform(data, inplace=False)
 
 
diff --git a/paddlets/datasets/tsdataset.py b/paddlets/datasets/tsdataset.py
index f751ef14..c74b545d 100644
--- a/paddlets/datasets/tsdataset.py
+++ b/paddlets/datasets/tsdataset.py
@@ -519,7 +519,7 @@ class TSDataset(object):
         known_cov(TimeSeries|None): Known covariates
         static_cov(dict|None): Static covariates
         fill_missing_dates(bool): Fill missing dates or not
-        fillna_method(str): Method of filling missing values. Totally 8 methods are supported currently:
+        fillna_method(str): Method of filling missing values. Totally 7 methods are supported currently:
             max: Use the max value in the sliding window
             min: Use the min value in the sliding window
             avg: Use the mean value in the sliding window
@@ -651,7 +651,7 @@ def load_from_csv(
             static_cov_cols(list|str|None): The names of columns for static covariates
             freq(str|int|None): A str or int representing the DateTimeIndex's frequency or RangeIndex's step size
             fill_missing_dates(bool): Fill missing dates or not
-            fillna_method(str): Method of filling missing values. Totally 8 methods are supported currently:
+            fillna_method(str): Method of filling missing values. Totally 7 methods are supported currently:
                 max: Use the max value in the sliding window
                 min: Use the min value in the sliding window
                 avg: Use the mean value in the sliding window
@@ -1481,7 +1481,7 @@ def columns(self) -> dict:
     
     @property
     def freq(self):
-        """the _freq"""
+        """Frequency of TSDataset"""
         return self._freq
 
     @classmethod
diff --git a/paddlets/models/dl/paddlepaddle/nbeats.py b/paddlets/models/dl/paddlepaddle/nbeats.py
index 49dea1b8..ab2c1af0 100644
--- a/paddlets/models/dl/paddlepaddle/nbeats.py
+++ b/paddlets/models/dl/paddlepaddle/nbeats.py
@@ -2,7 +2,7 @@
 # -*- coding: UTF-8 -*-
 
 """
-This implementation is based on the article `N-BEATS: Neural basis expansion analysis for interpretable time series forecasting<https://arxiv.org/pdf/1905.10437.pdf>`.
+This implementation is based on the article `N-BEATS: Neural basis expansion analysis for interpretable time series forecasting <https://arxiv.org/pdf/1905.10437.pdf>`_ .
 
 Base model features
     Basic architecture: A network with hierarchical stacking, bi-directional residual connection and interpretable generator.
diff --git a/paddlets/models/dl/paddlepaddle/nhits.py b/paddlets/models/dl/paddlepaddle/nhits.py
index 3dd124c2..7bfde586 100644
--- a/paddlets/models/dl/paddlepaddle/nhits.py
+++ b/paddlets/models/dl/paddlepaddle/nhits.py
@@ -2,7 +2,7 @@
 # -*- coding: UTF-8 -*-
 
 """
-This implementation is based on the article `N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting<https://arxiv.org/abs/2201.12886>`.
+This implementation is based on the article `N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting <https://arxiv.org/abs/2201.12886>`_ .
 """
 
 from enum import Enum
diff --git a/paddlets/utils/utils.py b/paddlets/utils/utils.py
index d7677b7b..b10b1f28 100644
--- a/paddlets/utils/utils.py
+++ b/paddlets/utils/utils.py
@@ -58,13 +58,14 @@ def check_model_fitted(model: Trainable, msg: str = None):
 
 def get_uuid(prefix: str = "", suffix: str = ""):
     """
-    get short UUID
+    Get a random string of 16 characters.
 
     Args:
-        prefix: data to be predicted
+        prefix(str, optional): The prefix of the returned string.
+        suffix(str, optional): The suffix of the returned string.
         
     Returns:
-        prefix & 16 random letters
+        str: String of 16 characters.
     """
     digits = "01234abcdefghijklmnopqrstuvwxyz56789"
     new_uuid = uuid.uuid1()
diff --git a/setup.cfg b/setup.cfg
deleted file mode 100644
index 3cadf280..00000000
--- a/setup.cfg
+++ /dev/null
@@ -1,69 +0,0 @@
-# Here's a link about setup.cfg
-# https://setuptools.readthedocs.io/en/latest/setuptools.html#configuring-setup-using-setup-cfg-files
-[metadata]
-# Project name, the project name will be used while publishing and installing
-name = paddlets
-# Author's name and email address
-author = paddlets
-author_email = paddlets@baidu.com
-version = 0.1.0
-# A brief introduction about the project, ANY NON-ENGLISH CHARACTER IS NOT SUPPORTED!
-description = project descriptions here
-# A longer version of introduction abouth the project, you can also include readme, change log, etc. .md or rst file is recommended.
-long_description = file: README.md, CHANGELOG.md
-long_description_content_type = text/markdown
-# Main page of the project, usually the project's github page, you can set to its wiki or other documents url instead.
-home_page = https://github.com/paddlepaddle/paddlets
-# License, you can ignore this if the project is not going to open source to the public.
-license = MIT
-# Project type, you can ignore this if the project is not going to open source to the public.
-# Choose the right field to fulfill from PyPI's official list.
-# https://pypi.org/pypi?%3Aaction=list_classifiers
-classifier =
-    Private :: Do Not Upload
-    Programming Language :: Python
-    Programming Language :: Python :: 2
-    Programming Language :: Python :: 2.7
-
-[options]
-# Package name. find means search automatically, you also can have detailed configuration in options.packages.find
-packages = find:
-# Dependency management, all project's dependency is needed here.
-# Every single line for a specified dependency, only the dependency is need, you don't have to consider the hierarchy dependency
-# Versions here should be as abstract as possible, usually only specific a version range including minimum and maximum version.
-#install_requires =
-#    six >= 1.10
-
-# Test dependencies, all dependencies for tests here. The format is align to install_requires.
-# You can use the internal unittest, or the simplier framework such as pytest or nose.
-# python3 has a mock library with itself, but it's not exist in python 2, add as you need.
-#tests_require =
-#    pytest
-#    mock
-
-# directory for unit test
-test_suite = paddlets.tests
-# add all data files controled by git
-include_package_data = True
-# You can run zip source code for plain python project
-zip_safe = False
-
-# You can set this configuration to let users run directly the main entrance function
-#[options.entry_points]
-#console_scripts =
-#    paddlets = paddlets.cmdline:main
-
-# You can add conf/data directory into package, the following directory will be installed under site-package
-# Only file is supported, but you can use wildcard instead.
-#[options.package_data]
-#paddlets =
-#    conf/*
-#    data/*
-
-[sdist]
-dist_dir = output/dist
-
-[bdist_wheel]
-# set universal=1 if this project can both run in python 2 or 3 environment.
-#universal=1
-dist_dir = output/dist


Test patch:
diff --git a/paddlets/tests/transform/__init__.py b/paddlets/tests/transform/__init__.py
new file mode 100644
index 00000000..5599cc33
--- /dev/null
+++ b/paddlets/tests/transform/__init__.py
@@ -0,0 +1,6 @@
+# !/usr/bin/env python3
+# -*- coding:utf-8 -*-
+
+"""
+transform tests
+"""