Update all baseline models.

examples/benchmarks/GATs/workflow_config_gats.yaml

@@ -8,6 +8,20 @@ data_handler_config: &data_handler_config
     fit_start_time: 2008-01-01
     fit_end_time: 2014-12-31
     instruments: *market
+    infer_processors:
+        - class: RobustZScoreNorm
+          kwargs:
+              fields_group: feature
+              clip_outlier: true
+        - class: Fillna
+          kwargs:
+              fields_group: feature
+    learn_processors:
+        - class: DropnaLabel
+        - class: CSRankNorm
+          kwargs:
+              fields_group: label
+    label: ["Ref($close, -2) / Ref($close, -1) - 1"]
 port_analysis_config: &port_analysis_config
     strategy:
         class: TopkDropoutStrategy
@@ -26,8 +40,8 @@ port_analysis_config: &port_analysis_config
         min_cost: 5
 task:
     model:
-        class: GAT
-        module_path: qlib.contrib.model.pytorch_gats
+        class: GAT_Classic
+        module_path: qlib.contrib.model.pytorch_gats_classic
         kwargs:
             d_feat: 6
             hidden_size: 64
@@ -38,8 +52,7 @@ task:
             early_stop: 20
             metric: loss
             loss: mse
-            base_model: LSTM
-            with_pretrain: True
+            base_model: GRU
             seed: 0
             GPU: 0
     dataset:
@@ -47,7 +60,7 @@ task:
         module_path: qlib.data.dataset
         kwargs:
             handler:
-                class: ALPHA360_Denoise
+                class: ALPHA360
                 module_path: qlib.contrib.data.handler
                 kwargs: *data_handler_config
             segments:
@@ -58,11 +71,6 @@ task:
         - class: SignalRecord
           module_path: qlib.workflow.record_temp
           kwargs: {}
-        - class: SigAnaRecord
-          module_path: qlib.workflow.record_temp
-          kwargs: 
-            ana_long_short: False
-            ann_scaler: 252
         - class: PortAnaRecord
           module_path: qlib.workflow.record_temp
           kwargs: