Add SFM config

examples/benchmarks/SFM/requirements.txt

@@ -0,0 +1,4 @@
+pandas==1.1.2
+numpy==1.17.4
+scikit_learn==0.23.2
+torch==1.7.0

examples/benchmarks/SFM/workflow_config_sfm.yaml

@@ -0,0 +1,73 @@
+provider_uri: "~/.qlib/qlib_data/cn_data"
+region: cn
+market: &market csi300
+benchmark: &benchmark SH000300
+data_handler_config: &data_handler_config
+    start_time: 2008-01-01
+    end_time: 2020-08-01
+    fit_start_time: 2008-01-01
+    fit_end_time: 2014-12-31
+    instruments: *market
+port_analysis_config: &port_analysis_config
+    strategy:
+        class: TopkDropoutStrategy
+        module_path: qlib.contrib.strategy.strategy
+        kwargs:
+            topk: 50
+            n_drop: 5
+    backtest:
+        verbose: False
+        limit_threshold: 0.095
+        account: 100000000
+        benchmark: *benchmark
+        deal_price: close
+        open_cost: 0.0005
+        close_cost: 0.0015
+        min_cost: 5
+task:
+    model:
+        class: SFM
+        module_path: qlib.contrib.model.pytorch_sfm
+        kwargs:
+            d_feat: 6
+            hidden_size: 64
+            output_dim: 1
+            freq_dim: 15
+            dropout_W: 0.5
+            dropout_U: 0.5
+            n_epochs: 10
+            lr: 1e-3
+            batch_size: 800
+            early_stop: 20
+            eval_steps: 5
+            loss: mse
+            lr_decay: 0.96
+            lr_decay_steps: 100
+            optimizer: gd
+            GPU: 1
+            seed: 0
+    dataset:
+        class: DatasetH
+        module_path: qlib.data.dataset
+        kwargs:
+            handler:
+                class: ALPHA360_Denoise
+                module_path: qlib.contrib.data.handler
+                kwargs: *data_handler_config
+            segments:
+                train: [2008-01-01, 2014-12-31]
+                valid: [2015-01-01, 2016-12-31]
+                test: [2017-01-01, 2020-08-01]
+    record: 
+        - 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: 
+            config: *port_analysis_config

examples/workflow_by_code_sfm.py

@@ -62,8 +62,8 @@ if __name__ == "__main__":
             "kwargs": {
                 "d_feat": 6,
                 "hidden_size": 64,
-                "output_dim" : 1,
-                "freq_dim" : 15,
+                "output_dim": 1,
+                "freq_dim": 15,
                 "dropout_W": 0.5,
                 "dropout_U": 0.5,
                 "n_epochs": 10,
@@ -72,9 +72,9 @@ if __name__ == "__main__":
                 "early_stop": 20,
                 "eval_steps": 5,
                 "loss": "mse",
-                "lr_decay" : 0.96,
-                "lr_decay_steps" : 100,
-                "optimizer" : "gd",
+                "lr_decay": 0.96,
+                "lr_decay_steps": 100,
+                "optimizer": "gd",
                 "GPU": 1,
                 "seed": 0,
             },