Resolve RL FIXMES (#1503)

* Solve several small FIXMEs left in RL

* Add TODO in example

* Minor bugfix

* black

examples/rl_order_execution/exp_configs/backtest_opds.yml

@@ -1,6 +1,7 @@
 order_file: ./data/orders/test_orders.pkl
 start_time: "9:30"
 end_time: "14:54"
+data_granularity: "5min"
 qlib:
   provider_uri_5min: ./data/bin/
 exchange:

examples/rl_order_execution/exp_configs/backtest_ppo.yml

@@ -1,6 +1,7 @@
 order_file: ./data/orders/test_orders.pkl
 start_time: "9:30"
 end_time: "14:54"
+data_granularity: "5min"
 qlib:
   provider_uri_5min: ./data/bin/
 exchange:

examples/rl_order_execution/exp_configs/backtest_twap.yml

@@ -1,6 +1,7 @@
 order_file: ./data/orders/test_orders.pkl
 start_time: "9:30"
 end_time: "14:54"
+data_granularity: "5min"
 qlib:
   provider_uri_5min: ./data/bin/
 exchange:

qlib/rl/contrib/backtest.py

@@ -30,12 +30,13 @@ def _get_multi_level_executor_config(
     strategy_config: dict,
     cash_limit: float | None = None,
     generate_report: bool = False,
+    data_granularity: str = "1min",
 ) -> dict:
     executor_config = {
         "class": "SimulatorExecutor",
         "module_path": "qlib.backtest.executor",
         "kwargs": {
-            "time_per_step": "5min",  # FIXME: move this into config
+            "time_per_step": data_granularity,
             "verbose": False,
             "trade_type": SimulatorExecutor.TT_PARAL if cash_limit is not None else SimulatorExecutor.TT_SERIAL,
             "generate_report": generate_report,
@@ -176,13 +177,14 @@ def single_with_simulator(
             strategy_config=backtest_config["strategies"],
             cash_limit=cash_limit,
             generate_report=generate_report,
+            data_granularity=backtest_config["data_granularity"],
         )
 
         exchange_config = copy.deepcopy(backtest_config["exchange"])
         exchange_config.update(
             {
                 "codes": stocks,
-                "freq": "5min",  # FIXME: move this into config
+                "freq": backtest_config["data_granularity"],
             }
         )
 
@@ -197,7 +199,7 @@ def single_with_simulator(
         reports.append(simulator.report_dict)
         decisions += simulator.decisions
 
-    indicator_1day_objs = [report["indicator"]["1day"][1] for report in reports]
+    indicator_1day_objs = [report["indicator_dict"]["1day"][1] for report in reports]
     indicator_info = {k: v for obj in indicator_1day_objs for k, v in obj.order_indicator_his.items()}
     records = _convert_indicator_to_dataframe(indicator_info)
     assert records is None or not np.isnan(records["ffr"]).any()
@@ -270,13 +272,14 @@ def single_with_collect_data_loop(
         strategy_config=backtest_config["strategies"],
         cash_limit=cash_limit,
         generate_report=generate_report,
+        data_granularity=backtest_config["data_granularity"],
     )
 
     exchange_config = copy.deepcopy(backtest_config["exchange"])
     exchange_config.update(
         {
             "codes": stocks,
-            "freq": "5min",  # FIXME: move this into config
+            "freq": backtest_config["data_granularity"],
         }
     )
 

qlib/rl/contrib/naive_config_parser.py

@@ -100,6 +100,7 @@ def get_backtest_config_fromfile(path: str) -> dict:
         "multiplier": 1.0,
         "output_dir": "outputs_backtest/",
         "generate_report": False,
+        "data_granularity": "1min",
     }
     backtest_config = merge_a_into_b(a=backtest_config, b=backtest_config_default)
 

qlib/rl/contrib/train_onpolicy.py

@@ -5,6 +5,7 @@
 import argparse
 import os
 import random
+import sys
 import warnings
 from pathlib import Path
 from typing import cast, List, Optional
@@ -208,6 +209,9 @@ def main(config: dict, run_training: bool, run_backtest: bool) -> None:
     if "seed" in config["runtime"]:
         seed_everything(config["runtime"]["seed"])
 
+    for extra_module_path in config["env"].get("extra_module_paths", []):
+        sys.path.append(extra_module_path)
+
     state_interpreter: StateInterpreter = init_instance_by_config(config["state_interpreter"])
     action_interpreter: ActionInterpreter = init_instance_by_config(config["action_interpreter"])
     reward: Reward = init_instance_by_config(config["reward"])