fix bgcf config error

model_zoo/official/gnn/bgcf/README.md

@@ -132,7 +132,6 @@ Parameters for both training and evaluation can be set in config.py.
   "input_dim": 64,                   # User and item embedding dimension
   "l2": 0.03                   # l2 coefficient
   "neighbor_dropout": [0.0, 0.2, 0.3]# Dropout ratio for different aggregation layer
-  "num_graphs":5                     # Num of sample graph
   ```
   config.py for more configuration.
   
@@ -193,21 +192,32 @@ Parameters for both training and evaluation can be set in config.py.
   ```
 # [Model Description](#contents)
 ## [Performance](#contents)
-
+### Evaluation Performance
 | Parameter                            | BGCF                                      |
 | ------------------------------------ | ----------------------------------------- |
+| Model Version                        | Inception V1                              |
 | Resource                             | Ascend 910                                |
 | uploaded Date                        | 09/23/2020(month/day/year)                                          |
 | MindSpore Version                    | 1.0.0                                          |
 | Dataset                              | Amazon-Beauty                             |
-| Training Parameter                   | epoch=600                                 |
+| Training Parameter                   | epoch=600,steps=12,batch_size=5000,lr=0.001                                 |
 | Optimizer                            | Adam                                      |
 | Loss Function                        | BPR loss                                  |
-| Recall@20                            | 0.1534                                    |
-| NDCG@20                              | 0.0912                                    |
 | Training Cost                        | 25min                                     |
 | Scripts                              | [bgcf script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/gnn/bgcf)                                          |
 
+### Inference Performance
+| Parameter                            | BGCF                                      |
+| ------------------------------------ | ----------------------------------------- |
+| Model Version                        | Inception V1                              |
+| Resource                             | Ascend 910                                |
+| uploaded Date                        | 09/23/2020(month/day/year)                                          |
+| MindSpore Version                    | 1.0.0                                          |
+| Dataset                              | Amazon-Beauty                             |
+| Batch_size                           | 5000                             |
+| Output                               | probability                            |
+| Recall@20                            | 0.1534                                    |
+| NDCG@20                              | 0.0912                                    |
 # [Description of random situation](#contents)
 
 BGCF model contains lots of dropout operations, if you want to disable dropout, set the neighbor_dropout to [0.0, 0.0, 0.0] in src/config.py. 

model_zoo/official/gnn/bgcf/src/config.py

@@ -24,16 +24,13 @@ def parser_args():
     parser.add_argument("-d", "--dataset", type=str, default="Beauty", help="choose which dataset")
     parser.add_argument("-dpath", "--datapath", type=str, default="./scripts/data_mr", help="minddata path")
     parser.add_argument("-de", "--device", type=str, default='0', help="device id")
-    parser.add_argument('--seed', type=int, default=0, help="random seed")
     parser.add_argument('--Ks', type=list, default=[5, 10, 20, 100], help="top K")
-    parser.add_argument('--test_ratio', type=float, default=0.2, help="test ratio")
-    parser.add_argument('-w', '--workers', type=int, default=8, help="number of process")
+    parser.add_argument('-w', '--workers', type=int, default=8, help="number of process to generate data")
     parser.add_argument("-ckpt", "--ckptpath", type=str, default="./ckpts", help="checkpoint path")
 
     parser.add_argument("-eps", "--epsilon", type=float, default=1e-8, help="optimizer parameter")
     parser.add_argument("-lr", "--learning_rate", type=float, default=1e-3, help="learning rate")
     parser.add_argument("-l2", "--l2", type=float, default=0.03, help="l2 coefficient")
-    parser.add_argument("-wd", "--weight_decay", type=float, default=0.01, help="weight decay")
     parser.add_argument("-act", "--activation", type=str, default='tanh', choices=['relu', 'tanh'],
                         help="activation function")
     parser.add_argument("-ndrop", "--neighbor_dropout", type=list, default=[0.0, 0.2, 0.3],
@@ -52,7 +49,4 @@ def parser_args():
     parser.add_argument("-emb", "--embedded_dimension", type=int, default=64, help="output embedding dim")
     parser.add_argument('--dist_reg', type=float, default=0.003, help="distance loss coefficient")
 
-    parser.add_argument('-ng', '--num_graphs', type=int, default=5, help="num of sample graph")
-    parser.add_argument('-geps', '--graph_epsilon', type=float, default=0.01, help="node copy parameter")
-
     return parser.parse_args()