tft模型与ante_hoc可解释性模块 (PaddlePaddle#305)

* update doc file of NBeats

* update deepar to adapt new adapter

* tft & ante_hoc

* tft & ante_hoc

* tft & ante_hoc

docs/index.rst

@@ -144,4 +144,5 @@ Project GitHub: https://github.com/PaddlePaddle/PaddleTS
     paddlets.transform <source/api/paddlets.transform.rst>
     paddlets.ensemble <source/api/paddlets.ensemble.rst>
     paddlets.utils <source/api/paddlets.utils.rst>
+    paddlets.xai <source/api/paddlets.xai.rst>
 

docs/locale/zh_CN/LC_MESSAGES/index.po

@@ -7,136 +7,140 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PaddleTS \n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2022-11-02 10:00+0800\n"
+"POT-Creation-Date: 2022-12-19 13:37+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 2.10.3\n"
+"Generated-By: Babel 2.9.1\n"
 
-#: ../../index.rst:56 bbd93109fe4949f2a3ae0d1c01769198
+#: ../../index.rst:57 a21f17f5f3fc4eadb4769b3ba1064077
 msgid "Get Started"
 msgstr "开始使用"
 
-#: ../../index.rst:56
+#: ../../index.rst:57
 msgid "Run On GPU"
 msgstr "使用GPU计算时序模型"
 
-#: ../../index.rst:56
+#: ../../index.rst:57
 msgid "Joint Training of Multiple Time Series"
 msgstr "多路时序数据联合训练"
 
-#: ../../index.rst:64 f7c1c12270ec42de86909c29f04fcecf
+#: ../../index.rst:65 95ae79d255d84d3d8e8eda7735356c38
 msgid "Installation"
 msgstr "安装"
 
-#: ../../index.rst:70 30b6c7471e2d406ea23f848d65175133
+#: ../../index.rst:71 b41b3b91ae7e45a2a84f2f1c6dcf6521
 msgid "Dataset"
 msgstr "数据集定义、加载以及操作"
 
-#: ../../index.rst:77 a98cbadbb4ad4badaf1d1a2301a4974d
+#: ../../index.rst:78 c21d044b10c046638c7ef19573e92c12
 msgid "Transform"
 msgstr "数据转换"
 
-#: ../../index.rst:77
+#: ../../index.rst:78
 msgid "Third-Party And User-Define Transform"
 msgstr "第三方以及自定义的数据转换模块自动集成"
 
-#: ../../index.rst:84
+#: ../../index.rst:85
 msgid "Forecasting"
 msgstr "时序预测模型"
 
-#: ../../index.rst:84
+#: ../../index.rst:85
 msgid "Third-party Model"
 msgstr "第三方模型自动集成"
 
-#: ../../index.rst:84
+#: ../../index.rst:85
 msgid "Probability Forecasting"
 msgstr "概率预测模型"
 
-#: ../../index.rst:84
+#: ../../index.rst:85
 msgid "Representation"
 msgstr "表征模型"
 
-#: ../../index.rst:84
+#: ../../index.rst:85
 msgid "Anomaly Detection"
 msgstr "时序异常检测"
 
-#: ../../index.rst:84 5b2c401f685b400b88f15736ab53f9ae
+#: ../../index.rst:85 6282d1af0ae14c6bb656feec260a3924
 msgid "Models"
 msgstr "模型"
 
-#: ../../index.rst:95 a22599ebae6342ddb490160d6e464770
+#: ../../index.rst:96 a59dd62e17e34ee381bfb0ef82eb3adc
 msgid "Metrics"
 msgstr "评估指标"
 
-#: ../../index.rst:102 7e6d8c2d97d3421c946b04fccca821db
+#: ../../index.rst:103 8dd57388c61d4568ab67a9fb236b7458
 msgid "Pipeline"
 msgstr ""
 
-#: ../../index.rst:108 ac43d69a2c3745b38e9b3737eb3cb47e
+#: ../../index.rst:109 b7c965fb2f194a67bd87692eba445f77
 msgid "Analysis"
 msgstr "分析"
 
-#: ../../index.rst:114 d3a8f241267949a08ee15bba5e8df8ba
+#: ../../index.rst:115 02ba5e42b14e429aad091b2ca7af8127
 msgid "Backtest"
 msgstr "回测"
 
-#: ../../index.rst:120 26a92fad74214b2a9636c986580a5b13
+#: ../../index.rst:121 bb2c5889bb214476acec7c85509fa365
 msgid "AutoTS"
 msgstr ""
 
-#: ../../index.rst:126 d6c7e8a3cd7f4f62ad6926f8c33b3dc7
+#: ../../index.rst:127 c897996763174cd3b7a0d3d206aa1b00
 msgid "Ensemble"
 msgstr "集成学习"
 
-#: ../../index.rst:132
+#: ../../index.rst:133
 msgid "paddlets.analysis"
 msgstr ""
 
-#: ../../index.rst:132
+#: ../../index.rst:133
 msgid "paddlets.automl"
 msgstr ""
 
-#: ../../index.rst:132
+#: ../../index.rst:133
 msgid "paddlets.datasets"
 msgstr ""
 
-#: ../../index.rst:132
+#: ../../index.rst:133
 msgid "paddlets.metrics"
 msgstr ""
 
-#: ../../index.rst:132
+#: ../../index.rst:133
 msgid "paddlets.models"
 msgstr ""
 
-#: ../../index.rst:132
+#: ../../index.rst:133
 msgid "paddlets.pipeline"
 msgstr ""
 
-#: ../../index.rst:132
+#: ../../index.rst:133
 msgid "paddlets.transform"
 msgstr ""
 
-#: ../../index.rst:132
+#: ../../index.rst:133
 msgid "paddlets.ensemble"
 msgstr ""
 
-#: ../../index.rst:132
+#: ../../index.rst:133
 msgid "paddlets.utils"
 msgstr ""
 
-#: ../../index.rst:132 1f4d1f6e249e490f9350d6ce4345a565
+#: ../../index.rst:133
+msgid "paddlets.xai"
+msgstr ""
+
+#: ../../index.rst:133 e4efe64edf1b452daf03e22a2e033b39
 msgid "API"
 msgstr ""
 
-#: ../../index.rst:2 99404f027e894667841d941b092d23b1
+#: ../../index.rst:2 2109812999c348e697d7e4ad9ecd80f3
 msgid "Welcome to PaddleTS"
 msgstr "欢迎使用PaddleTS"
 
-#: ../../index.rst:4 b814890581b040ba8618124c829707cf
+#: ../../index.rst:4 ff765664e303499eb4c132a7da8f1e60
 msgid ""
 "PaddleTS is an easy-to-use Python library for deep time series modeling, "
 "focusing on the state-of-the-art deep neural network models based on "
@@ -147,15 +151,15 @@ msgstr ""
 "PaddleTS "
 "是一个易用的深度时序建模的Python库，它基于飞桨深度学习框架PaddlePaddle，专注业界领先的深度模型，旨在为领域专家和行业用户提供可扩展的时序建模能力和便捷易用的用户体验。PaddleTS的主要特性包括："
 
-#: ../../index.rst:9 1f2dab584ec8407ea6777bde8ecb01ae
+#: ../../index.rst:9 ee98e34f59c44fdea3b6bb5fe3406d6e
 msgid ""
 "A unified data structure named TSDataset for representing time series "
 "data with one or multiple target variables and optional different kinds "
 "of covariates (e.g. known covariates, observed covariates, static "
 "covariates, etc.)"
 msgstr "设计统一数据结构，实现对多样化时序数据的表达，支持单目标与多目标变量，支持多类型协变量"
 
-#: ../../index.rst:13 9fbf359ccd3c49ba8d5e832f37eb202a
+#: ../../index.rst:13 f19117089d11402f9c58fb0e3d9404e5
 msgid ""
 "A base model class named PaddleBaseModelImpl , which inherits from the "
 "PaddleBaseModel and further encapsulates some routine procedures (e.g. "
@@ -164,7 +168,7 @@ msgid ""
 "architectures when developing new models"
 msgstr "封装基础模型功能，如数据加载、回调设置、损失函数、训练过程控制等公共方法，帮助开发者在新模型开发过程中专注于网络结构本身"
 
-#: ../../index.rst:18 81cb90a532584b0f94f42623c9a7f1dc
+#: ../../index.rst:18 5d2712524da7490bb414fc4001fa085e
 msgid ""
 "A set of state-of-the-art deep learning models containing NBEATS, NHiTS, "
 "LSTNet, TCN, Transformer, DeepAR(Probabilistic), Informer, etc. for "
@@ -173,43 +177,45 @@ msgstr ""
 "内置业界领先的深度学习模型，包括NBEATS、NHiTS、LSTNet、TCN、Transformer, "
 "DeepAR（概率预测）、Informer等时序预测模型，以及TS2Vec等时序表征模型"
 
-#: ../../index.rst:21 d627feda307443f09fd6ebbb77738339
+#: ../../index.rst:21 5b8bf95cec3f4556b0670da598e0c99d
 msgid ""
 "A set of transformation operators for data preprocessing (e.g. missing "
 "values/outliers handling, one-hot encoding, normalization, and automatic "
 "date/time-related covariates generation, etc.)"
 msgstr "内置经典数据转换算子，支持数据处理与转换，包括缺失值填充、异常值处理、归一化、时间相关的协变量提取等"
 
-#: ../../index.rst:24 32b1d8e2b6534c52abe4bb7f117fd98a
+#: ../../index.rst:24 37fef223db2a4a2b9c3c1a3bee5d8c8e
 msgid ""
 "A set of analysis operators for quick data exploration (e.g. basic "
 "statistics and summary)"
 msgstr "内置时序数据分析算子，帮助开发者便捷实现数据探索，包括数据统计量信息及数据摘要等功能"
 
-#: ../../index.rst:26 8f8830ab5fe84168ba98bfea5c987b3b
+#: ../../index.rst:26 0920450aea5a445cb4531f8ab128c2ef
 msgid ""
 "Automatic time series modeling module (AutoTS) which supports mainstream "
 "Hyper Parameter Optimization algorithms and shows significant improvement"
 " on multiple models and datasets"
 msgstr "自动模型调优AutoTS发布，支持多类型HPO算法，在多个模型和数据集上展现显著调优效果"
 
-#: ../../index.rst:28 3b9b42130a594ee7a774597ec20e47e4
+#: ../../index.rst:28 409250a854934d56888703874b3256a5
 msgid ""
 "Third-party (e.g. scikit-learn) ML models & data transformations "
 "integration"
 msgstr "支持第三方机器学习模型及数据转换模块自动集成，支持包括sklearn等第三方库的时序应用"
 
-#: ../../index.rst:30 d19a6f7070f24851aa001583c69843c9
+#: ../../index.rst:30 12fe0d744cdf4a70aefde006cd5b2dec
 msgid "Recently updated:"
 msgstr "最新更新："
 
-#: ../../index.rst:32 a7ada1f13f324fc6872132310229ae9d
+#: ../../index.rst:32 8cbd942b53a3495f9e20fb63470589e7
 msgid ""
 "Released a new time series representation model, i.e. Contrastive "
 "Learning of Disentangled Seasonal-trend Representations(CoST)"
-msgstr "发布时序表征模型 Contrastive Learning of Disentangled Seasonal-trend Representations(CoST)"
+msgstr ""
+"发布时序表征模型 Contrastive Learning of Disentangled Seasonal-trend "
+"Representations(CoST)"
 
-#: ../../index.rst:32 a7ada1f13f324fc6872132310229ae9d
+#: ../../index.rst:34 18e7bfde63f84c8a9c93bd3c9f0c377b
 msgid ""
 "Time series anomaly detection model supported, with three deep models "
 "released, including AE(AutoEncoder), VAE(Variational AutoEncoder), and "
@@ -218,61 +224,61 @@ msgstr ""
 "支持时序异常检测，发布包括AE (Autoencoder)、VAE (Variational "
 "Autoencoder)、AnomalyTransformer深度学习模型"
 
-#: ../../index.rst:34 ff05514ada25437ab4c122252c92eaf3
+#: ../../index.rst:35 5836797b7f3a4ee19b0312a3e9ed4568
 msgid ""
 "Third-party `pyod <https://github.com/yzhao062/pyod>`_ ML models "
 "integration supported"
 msgstr "支持第三方时序异常检测库 `pyod <https://github.com/yzhao062/pyod>`_ 自动集成"
 
-#: ../../index.rst:36 ad49c424e2a1456ebdd63d86f1377634
+#: ../../index.rst:37 571c358ff2c34f22bf13adb25261633d
 msgid ""
 "Support time series model ensemble with two types of ensemble forecaster,"
 " StackingEnsembleForecaster and WeightingEnsembleForecaster proposed"
 msgstr "新增时序模型集成Ensemble功能。目前发布版本支持StackingEnsembleForecaster和WeightingEnsembleForecaster等2种时序预测集成学习方法"
 
-#: ../../index.rst:38 5ced4073aa4a46fab89dc9ff3e932968
+#: ../../index.rst:39 2379de25ec09422cb653102cf9a239f3
 msgid ""
 "RNN time series forecasting model supports categorical features and "
 "static covariates"
 msgstr "RNN模型现在支持使用分类特征和静态协变量"
 
-#: ../../index.rst:40 5d22a3b12e2b4619a018e45fc61863b3
+#: ../../index.rst:41 b8667510be134803b2ce5541f0107aab
 msgid ""
 "New representation forecaster to support representation models to solve "
 "time series forecasting task"
 msgstr "新增基于表征模型的时序预测功能，支持使用时序表征模型解决时序预测任务"
 
-#: ../../index.rst:42 9065e138740042de930ab610ef1f5026
+#: ../../index.rst:43 96a3107300a74a75a3af4afafb73c742
 msgid "Support joint training of multiple time series datasets"
 msgstr "支持基于多时序数据集的组合训练"
 
-#: ../../index.rst:45 1b9360a28c7f4abd884b50e17a222a3b
+#: ../../index.rst:46 7eb8aa5a8e514823830edf7aebf0ea0a
 msgid "In the future, more advanced features will be coming, including:"
 msgstr "未来，更多的高级特性会进一步发布，包括："
 
-#: ../../index.rst:47 fbe4577b0a0b45389a666e30e92189fd
+#: ../../index.rst:48 deead77db10249cb9ba3a53fe4afaa79
 msgid "More time series anomaly detection models"
 msgstr "支持时序异常检测"
 
-#: ../../index.rst:48 78dc8978d7414570b068e59232f256d1
+#: ../../index.rst:49 da01a0e9d56841d180a44191f8a2681e
 msgid "More time series representation learning models"
 msgstr "更多时序表征模型"
 
-#: ../../index.rst:49 b165789208ba404d80f48b91d7c41337
+#: ../../index.rst:50 a281248504de4906b06a49dd299b7278
 msgid "More probabilistic forecasting models"
 msgstr "更多概率预测模型"
 
-#: ../../index.rst:50 0fee98c47ac44288bad33be1bc3cdea1
+#: ../../index.rst:51 3a0ffabd5d8c4a0c861d2f41113eb8d4
 msgid ""
 "Scenario-specific pipelines which aim to provide an end-to-end solution "
 "for solving real-world business problems"
 msgstr "场景化Pipeline"
 
-#: ../../index.rst:51 323ca5a4a4254e6eafcd74a30dfa5a35
+#: ../../index.rst:52 d49ffc5432654685add77febe196ea6d
 msgid "And more"
 msgstr "以及更多"
 
-#: ../../index.rst:53 f31426ca2be2483b947f40fb502076c0
+#: ../../index.rst:54 e743a03681804c7dbebe8a0b75fb81fd
 msgid "Project GitHub: https://github.com/PaddlePaddle/PaddleTS"
 msgstr "项目 Github: https://github.com/PaddlePaddle/PaddleTS"