fix config.yaml

models/rank/fibinet/config.yaml

@@ -18,15 +18,15 @@ workspace: "paddlerec.models.rank.fibinet"
 # list of dataset
 dataset:
 - name: dataloader_train # name of dataset to distinguish different datasets
-  batch_size: 1000
+  batch_size: 2
   type: DataLoader # or QueueDataset 
-  data_path: "{workspace}/data/slot_test_data_full"
+  data_path: "{workspace}/data/sample_data/train"
   sparse_slots: "click 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26"
   dense_slots: "dense_var:13"
 - name: dataset_infer # name
-  batch_size: 1000
+  batch_size: 2
   type: DataLoader # or QueueDataset
-  data_path: "{workspace}/data/slot_test_data_full"
+  data_path: "{workspace}/data/sample_data/train"
   sparse_slots: "click 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26"
   dense_slots: "dense_var:13"
 
@@ -57,7 +57,7 @@ runner:
   epochs: 4
   # device to run training or infer
   device: cpu
-  save_checkpoint_interval: 1 # save model interval of epochs
+  save_checkpoint_interval: 2 # save model interval of epochs
   save_inference_interval: 4 # save inference
   save_checkpoint_path: "increment_model" # save checkpoint path
   save_inference_path: "inference" # save inference path
@@ -87,14 +87,14 @@ runner:
   class: infer
   # device to run training or infer
   device: cpu
-  init_model_path: "increment_model/3" # load model path
+  init_model_path: "increment_model" # load model path
   phases: [phase2]
 
 - name: single_gpu_infer
   class: infer
   # device to run training or infer
   device: gpu
-  init_model_path: "increment_model/3" # load model path
+  init_model_path: "increment_model" # load model path
   phases: [phase2]
 
 # runner will run all the phase in each epoch
@@ -108,4 +108,3 @@ phase:
   model: "{workspace}/model.py" # user-defined model
   dataset_name: dataset_infer # select dataset by name
   thread_num: 8
-