Update outdated links

docs/CTR/index.md

@@ -1,4 +1,4 @@
-# BARS-CTR Benchmark
+# Benchmark Overview
 
 BARS-CTR: An Open Benchmark for CTR Prediction https://openbenchmark.github.io/BARS/CTR
 

docs/CTR/leaderboard/avazu_x4_001.csv

@@ -29,3 +29,7 @@ Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
 2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.7929,0.3726,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_avazu_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
 2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.7882,0.3749,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_avazu_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
 2020,DLP-KDD'20,FLEN,https://arxiv.org/abs/1911.04690,0.7929,0.372,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FLEN/FLEN_avazu_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
+2021,WWW'21,DCN-V2,https://arxiv.org/abs/2008.13535,0.793146,0.371865,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCNv2/DCNv2_avazu_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
+2021,DLP-KDD'21,MaskNet,https://arxiv.org/abs/2102.07619,0.794382,0.371189,https://github.com/reczoo/BARS/tree/main/ranking/ctr/MaskNet/MaskNet_avazu_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
+2023,AAAI'23,FinalMLP,https://arxiv.org/abs/2304.00902,0.793537,0.371862,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FinalMLP/FinalMLP_avazu_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
+2023,SIGIR'23,FinalNet,https://dl.acm.org/doi/10.1145/3539618.3591988,0.794116,0.371254,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FinalNet/FinalNet_avazu_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"

docs/CTR/leaderboard/criteo_x4_001.csv

@@ -28,3 +28,7 @@ Year,Publication,Model,Paper URL,AUC,Logloss,Running Steps,Contributor
 2020,AAAI'20,AFN,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8115,0.4402,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN_criteo_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
 2020,AAAI'20,AFN+,https://ojs.aaai.org/index.php/AAAI/article/view/5768,0.8138,0.4384,https://github.com/reczoo/BARS/tree/main/ranking/ctr/AFN/AFN+_criteo_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
 2020,WSDM'20,InterHAt,https://dl.acm.org/doi/10.1145/3336191.3371785,0.8104,0.4414,https://github.com/reczoo/BARS/tree/main/ranking/ctr/InterHAt/InterHAt_criteo_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
+2021,WWW'21,DCN-V2,https://arxiv.org/abs/2008.13535,0.814514,0.437631,https://github.com/reczoo/BARS/tree/main/ranking/ctr/DCNv2/DCNv2_criteo_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
+2021,DLP-KDD'21,MaskNet,https://arxiv.org/abs/2102.07619,0.81342,0.438748,https://github.com/reczoo/BARS/tree/main/ranking/ctr/MaskNet/MaskNet_criteo_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
+2023,AAAI'23,FinalMLP,https://arxiv.org/abs/2304.00902,0.814584,0.437353,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FinalMLP/FinalMLP_criteo_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"
+2023,SIGIR'23,FinalNet,https://dl.acm.org/doi/10.1145/3539618.3591988,0.814966,0.437116,https://github.com/reczoo/BARS/tree/main/ranking/ctr/FinalNet/FinalNet_criteo_x4_001,"<a href=""https://arxiv.org/abs/2009.05794"">Zhu et al.</a>"

docs/CTR/leaderboard/index.md

@@ -1,4 +1,4 @@
-# Benchmark Leaderboard
+# BARS-CTR Leaderboard
 
 ```{tableofcontents}
 ```

docs/CTR/leaderboard/seqctr.md

@@ -0,0 +1,4 @@
+# BARS-SeqCTR Leaderboard
+
+```{tableofcontents}
+```

docs/Matching/index.md

@@ -1,4 +1,4 @@
-# BARS-Match Overview
+# Benchmark Overview
 
 BARS-Match: An Open Benchmark for Candidate Item Matching https://openbenchmark.github.io/BARS/Matching
 

docs/Matching/leaderboard/index.md

@@ -1,4 +1,4 @@
-# Benchmark Leaderboard
+# BARS-Match Leaderboard
 
 
 ```{tableofcontents}

docs/_toc.yml

@@ -25,10 +25,12 @@ parts:
  - file: CTR/leaderboard/frappe_x1.md
  - file: CTR/leaderboard/movielenslatest_x1.md
  - file: CTR/leaderboard/kkbox_x1.md
+ - file: CTR/leaderboard/seqctr.md
+ sections:
  - file: CTR/leaderboard/amazonelectronics_x1.md
- - file: CTR/leaderboard/taobaoad_x1.md
  - file: CTR/leaderboard/kuaivideo_x1.md
  - file: CTR/leaderboard/microvideo1.7m_x1.md
+ - file: CTR/leaderboard/taobaoad_x1.md
 
 - caption: "CANDIDATE MATCHING"
  chapters:

ranking/ctr/AFM/AFM_avazu_x1/README.md

@@ -2,7 +2,7 @@
 
 A hands-on guide to run the AFM model on the Avazu_x1 dataset.
 
-Author: [XUEPAI](https://github.com/xue-pai)
+Author: [BARS Benchmark](https://github.com/reczoo/BARS/blob/main/CITATION)
 
 ### Index
 [Environments](#Environments) | [Dataset](#Dataset) | [Code](#Code) | [Results](#Results) | [Logs](#Logs)
@@ -35,15 +35,15 @@ Author: [XUEPAI](https://github.com/xue-pai)
  ```
 
 ### Dataset
-Dataset ID: [Avazu_x1](https://github.com/openbenchmark/BARS/blob/master/ctr_prediction/datasets/Avazu/README.md#Avazu_x1). Please refer to the dataset details to get data ready.
+Dataset ID: [Avazu_x1](https://github.com/reczoo/Datasets/tree/main/Avazu/Avazu_x1). Please refer to the dataset details to get data ready.
 
 ### Code
 
-We use [FuxiCTR-v1.1.0](https://github.com/xue-pai/FuxiCTR/tree/v1.1.0) for this experiment. See the model code: [AFM](https://github.com/xue-pai/FuxiCTR/blob/v1.1.0/fuxictr/pytorch/models/AFM.py).
+We use [FuxiCTR-v1.1.0](https://github.com/reczoo/FuxiCTR/tree/v1.1.0) for this experiment. See the model code: [AFM](https://github.com/reczoo/FuxiCTR/blob/v1.1.0/fuxictr/pytorch/models/AFM.py).
 
 Running steps:
 
-1. Download [FuxiCTR-v1.1.0](https://github.com/xue-pai/FuxiCTR/archive/refs/tags/v1.1.0.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
+1. Download [FuxiCTR-v1.1.0](https://github.com/reczoo/FuxiCTR/archive/refs/tags/v1.1.0.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
 
  ```python
  sys.path.append('YOUR_PATH_TO_FuxiCTR/')

ranking/ctr/AFM/AFM_avazu_x4_001/README.md

@@ -2,7 +2,7 @@
 
 A hands-on guide to run the AFM model on the Avazu_x4_001 dataset.
 
-Author: [XUEPAI](https://github.com/xue-pai)
+Author: [BARS Benchmark](https://github.com/reczoo/BARS/blob/main/CITATION)
 
 ### Index
 [Environments](#Environments) | [Dataset](#Dataset) | [Code](#Code) | [Results](#Results) | [Logs](#Logs)
@@ -34,15 +34,15 @@ Author: [XUEPAI](https://github.com/xue-pai)
  ```
 
 ### Dataset
-Dataset ID: [Avazu_x4_001](https://github.com/openbenchmark/BARS/blob/master/ctr_prediction/datasets/Avazu/README.md#Avazu_x4_001). Please refer to the dataset details to get data ready.
+Dataset ID: [Avazu_x4](https://github.com/reczoo/Datasets/tree/main/Avazu/Avazu_x4). Please refer to the dataset details to get data ready.
 
 ### Code
 
-We use [FuxiCTR-v1.0.2](https://github.com/xue-pai/FuxiCTR/tree/v1.0.2) for this experiment. See the model code: [AFM](https://github.com/xue-pai/FuxiCTR/blob/v1.0.2/fuxictr/pytorch/models/AFM.py).
+We use [FuxiCTR-v1.0.2](https://github.com/reczoo/FuxiCTR/tree/v1.0.2) for this experiment. See the model code: [AFM](https://github.com/reczoo/FuxiCTR/blob/v1.0.2/fuxictr/pytorch/models/AFM.py).
 
 Running steps:
 
-1. Download [FuxiCTR-v1.0.2](https://github.com/xue-pai/FuxiCTR/archive/refs/tags/v1.0.2.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
+1. Download [FuxiCTR-v1.0.2](https://github.com/reczoo/FuxiCTR/archive/refs/tags/v1.0.2.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
 
  ```python
  sys.path.append('YOUR_PATH_TO_FuxiCTR/')

ranking/ctr/AFM/AFM_avazu_x4_002/README.md

@@ -2,7 +2,7 @@
 
 A hands-on guide to run the AFM model on the Avazu_x4_002 dataset.
 
-Author: [XUEPAI](https://github.com/xue-pai)
+Author: [BARS Benchmark](https://github.com/reczoo/BARS/blob/main/CITATION)
 
 ### Index
 [Environments](#Environments) | [Dataset](#Dataset) | [Code](#Code) | [Results](#Results) | [Logs](#Logs)
@@ -34,15 +34,15 @@ Author: [XUEPAI](https://github.com/xue-pai)
  ```
 
 ### Dataset
-Dataset ID: [Avazu_x4_002](https://github.com/openbenchmark/BARS/blob/master/ctr_prediction/datasets/Avazu/README.md#Avazu_x4_002). Please refer to the dataset details to get data ready.
+Dataset ID: [Avazu_x4](https://github.com/reczoo/Datasets/tree/main/Avazu/Avazu_x4). Please refer to the dataset details to get data ready.
 
 ### Code
 
-We use [FuxiCTR-v1.0.2](https://github.com/xue-pai/FuxiCTR/tree/v1.0.2) for this experiment. See the model code: [AFM](https://github.com/xue-pai/FuxiCTR/blob/v1.0.2/fuxictr/pytorch/models/AFM.py).
+We use [FuxiCTR-v1.0.2](https://github.com/reczoo/FuxiCTR/tree/v1.0.2) for this experiment. See the model code: [AFM](https://github.com/reczoo/FuxiCTR/blob/v1.0.2/fuxictr/pytorch/models/AFM.py).
 
 Running steps:
 
-1. Download [FuxiCTR-v1.0.2](https://github.com/xue-pai/FuxiCTR/archive/refs/tags/v1.0.2.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
+1. Download [FuxiCTR-v1.0.2](https://github.com/reczoo/FuxiCTR/archive/refs/tags/v1.0.2.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
 
  ```python
  sys.path.append('YOUR_PATH_TO_FuxiCTR/')

ranking/ctr/AFM/AFM_criteo_x1/README.md

@@ -2,7 +2,7 @@
 
 A hands-on guide to run the AFM model on the Criteo_x1 dataset.
 
-Author: [XUEPAI](https://github.com/xue-pai)
+Author: [BARS Benchmark](https://github.com/reczoo/BARS/blob/main/CITATION)
 
 ### Index
 [Environments](#Environments) | [Dataset](#Dataset) | [Code](#Code) | [Results](#Results) | [Logs](#Logs)
@@ -34,15 +34,15 @@ Author: [XUEPAI](https://github.com/xue-pai)
  ```
 
 ### Dataset
-Dataset ID: [Criteo_x1](https://github.com/openbenchmark/BARS/blob/master/ctr_prediction/datasets/Criteo/README.md#Criteo_x1). Please refer to the dataset details to get data ready.
+Dataset ID: [Criteo_x1](https://github.com/reczoo/Datasets/tree/main/Criteo/Criteo_x1). Please refer to the dataset details to get data ready.
 
 ### Code
 
-We use [FuxiCTR-v1.1.0](https://github.com/xue-pai/FuxiCTR/tree/v1.1.0) for this experiment. See the model code: [AFM](https://github.com/xue-pai/FuxiCTR/blob/v1.1.0/fuxictr/pytorch/models/AFM.py).
+We use [FuxiCTR-v1.1.0](https://github.com/reczoo/FuxiCTR/tree/v1.1.0) for this experiment. See the model code: [AFM](https://github.com/reczoo/FuxiCTR/blob/v1.1.0/fuxictr/pytorch/models/AFM.py).
 
 Running steps:
 
-1. Download [FuxiCTR-v1.1.0](https://github.com/xue-pai/FuxiCTR/archive/refs/tags/v1.1.0.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
+1. Download [FuxiCTR-v1.1.0](https://github.com/reczoo/FuxiCTR/archive/refs/tags/v1.1.0.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
 
  ```python
  sys.path.append('YOUR_PATH_TO_FuxiCTR/')

ranking/ctr/AFM/AFM_criteo_x4_001/README.md

@@ -2,7 +2,7 @@
 
 A hands-on guide to run the AFM model on the Criteo_x4_001 dataset.
 
-Author: [XUEPAI](https://github.com/xue-pai)
+Author: [BARS Benchmark](https://github.com/reczoo/BARS/blob/main/CITATION)
 
 ### Index
 [Environments](#Environments) | [Dataset](#Dataset) | [Code](#Code) | [Results](#Results) | [Logs](#Logs)
@@ -34,15 +34,15 @@ Author: [XUEPAI](https://github.com/xue-pai)
  ```
 
 ### Dataset
-Dataset ID: [Criteo_x4_001](https://github.com/openbenchmark/BARS/blob/master/ctr_prediction/datasets/Criteo/README.md#Criteo_x4_001). Please refer to the dataset details to get data ready.
+Dataset ID: [Criteo_x4](https://github.com/reczoo/Datasets/tree/main/Criteo/Criteo_x4). Please refer to the dataset details to get data ready.
 
 ### Code
 
-We use [FuxiCTR-v1.0.2](https://github.com/xue-pai/FuxiCTR/tree/v1.0.2) for this experiment. See the model code: [AFM](https://github.com/xue-pai/FuxiCTR/blob/v1.0.2/fuxictr/pytorch/models/AFM.py).
+We use [FuxiCTR-v1.0.2](https://github.com/reczoo/FuxiCTR/tree/v1.0.2) for this experiment. See the model code: [AFM](https://github.com/reczoo/FuxiCTR/blob/v1.0.2/fuxictr/pytorch/models/AFM.py).
 
 Running steps:
 
-1. Download [FuxiCTR-v1.0.2](https://github.com/xue-pai/FuxiCTR/archive/refs/tags/v1.0.2.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
+1. Download [FuxiCTR-v1.0.2](https://github.com/reczoo/FuxiCTR/archive/refs/tags/v1.0.2.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
 
  ```python
  sys.path.append('YOUR_PATH_TO_FuxiCTR/')

ranking/ctr/AFM/AFM_criteo_x4_002/README.md

@@ -2,7 +2,7 @@
 
 A hands-on guide to run the AFM model on the Criteo_x4_002 dataset.
 
-Author: [XUEPAI](https://github.com/xue-pai)
+Author: [BARS Benchmark](https://github.com/reczoo/BARS/blob/main/CITATION)
 
 ### Index
 [Environments](#Environments) | [Dataset](#Dataset) | [Code](#Code) | [Results](#Results) | [Logs](#Logs)
@@ -34,15 +34,15 @@ Author: [XUEPAI](https://github.com/xue-pai)
  ```
 
 ### Dataset
-Dataset ID: [Criteo_x4_002](https://github.com/openbenchmark/BARS/blob/master/ctr_prediction/datasets/Criteo/README.md#Criteo_x4_002). Please refer to the dataset details to get data ready.
+Dataset ID: [Criteo_x4](https://github.com/reczoo/Datasets/tree/main/Criteo/Criteo_x4). Please refer to the dataset details to get data ready.
 
 ### Code
 
-We use [FuxiCTR-v1.0.2](https://github.com/xue-pai/FuxiCTR/tree/v1.0.2) for this experiment. See the model code: [AFM](https://github.com/xue-pai/FuxiCTR/blob/v1.0.2/fuxictr/pytorch/models/AFM.py).
+We use [FuxiCTR-v1.0.2](https://github.com/reczoo/FuxiCTR/tree/v1.0.2) for this experiment. See the model code: [AFM](https://github.com/reczoo/FuxiCTR/blob/v1.0.2/fuxictr/pytorch/models/AFM.py).
 
 Running steps:
 
-1. Download [FuxiCTR-v1.0.2](https://github.com/xue-pai/FuxiCTR/archive/refs/tags/v1.0.2.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
+1. Download [FuxiCTR-v1.0.2](https://github.com/reczoo/FuxiCTR/archive/refs/tags/v1.0.2.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
 
  ```python
  sys.path.append('YOUR_PATH_TO_FuxiCTR/')

ranking/ctr/AFM/AFM_frappe_x1/README.md

@@ -2,7 +2,7 @@
 
 A hands-on guide to run the AFM model on the Frappe_x1 dataset.
 
-Author: [XUEPAI](https://github.com/xue-pai)
+Author: [BARS Benchmark](https://github.com/reczoo/BARS/blob/main/CITATION)
 
 ### Index
 [Environments](#Environments) | [Dataset](#Dataset) | [Code](#Code) | [Results](#Results) | [Logs](#Logs)
@@ -34,15 +34,15 @@ Author: [XUEPAI](https://github.com/xue-pai)
  ```
 
 ### Dataset
-Dataset ID: [Frappe_x1](https://github.com/openbenchmark/BARS/blob/master/ctr_prediction/datasets/Frappe/README.md#Frappe_x1). Please refer to the dataset details to get data ready.
+Dataset ID: [Frappe_x1](https://github.com/reczoo/Datasets/tree/main/Frappe/Frappe_x1). Please refer to the dataset details to get data ready.
 
 ### Code
 
-We use [FuxiCTR-v1.1.0](https://github.com/xue-pai/FuxiCTR/tree/v1.1.0) for this experiment. See the model code: [AFM](https://github.com/xue-pai/FuxiCTR/blob/v1.1.0/fuxictr/pytorch/models/AFM.py).
+We use [FuxiCTR-v1.1.0](https://github.com/reczoo/FuxiCTR/tree/v1.1.0) for this experiment. See the model code: [AFM](https://github.com/reczoo/FuxiCTR/blob/v1.1.0/fuxictr/pytorch/models/AFM.py).
 
 Running steps:
 
-1. Download [FuxiCTR-v1.1.0](https://github.com/xue-pai/FuxiCTR/archive/refs/tags/v1.1.0.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
+1. Download [FuxiCTR-v1.1.0](https://github.com/reczoo/FuxiCTR/archive/refs/tags/v1.1.0.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
 
  ```python
  sys.path.append('YOUR_PATH_TO_FuxiCTR/')

ranking/ctr/AFM/AFM_kkbox_x1/README.md

@@ -2,7 +2,7 @@
 
 A hands-on guide to run the AFM model on the KKBox_x1 dataset.
 
-Author: [XUEPAI](https://github.com/xue-pai)
+Author: [BARS Benchmark](https://github.com/reczoo/BARS/blob/main/CITATION)
 
 ### Index
 [Environments](#Environments) | [Dataset](#Dataset) | [Code](#Code) | [Results](#Results) | [Logs](#Logs)
@@ -34,15 +34,15 @@ Author: [XUEPAI](https://github.com/xue-pai)
  ```
 
 ### Dataset
-Dataset ID: [KKBox_x1](https://github.com/openbenchmark/BARS/blob/master/ctr_prediction/datasets/KKBox/README.md#KKBox_x1). Please refer to the dataset details to get data ready.
+Dataset ID: [KKBox_x1](https://github.com/reczoo/Datasets/tree/main/KKBox/KKBox_x1). Please refer to the dataset details to get data ready.
 
 ### Code
 
-We use [FuxiCTR-v1.0.2](https://github.com/xue-pai/FuxiCTR/tree/v1.0.2) for this experiment. See the model code: [AFM](https://github.com/xue-pai/FuxiCTR/blob/v1.0.2/fuxictr/pytorch/models/AFM.py).
+We use [FuxiCTR-v1.0.2](https://github.com/reczoo/FuxiCTR/tree/v1.0.2) for this experiment. See the model code: [AFM](https://github.com/reczoo/FuxiCTR/blob/v1.0.2/fuxictr/pytorch/models/AFM.py).
 
 Running steps:
 
-1. Download [FuxiCTR-v1.0.2](https://github.com/xue-pai/FuxiCTR/archive/refs/tags/v1.0.2.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
+1. Download [FuxiCTR-v1.0.2](https://github.com/reczoo/FuxiCTR/archive/refs/tags/v1.0.2.zip) and install all the dependencies listed in the [environments](#environments). Then modify [run_expid.py](./run_expid.py#L5) to add the FuxiCTR library to system path
 
  ```python
  sys.path.append('YOUR_PATH_TO_FuxiCTR/')