Migrate amc4th training (#1316)

* Migrate amc4th training

* Refine RL example scripts

* Resolve PR comments

Co-authored-by: luocy16 <luocy16@mails.tsinghua.edu.cn>

examples/rl/README.md

@@ -0,0 +1,55 @@
+This folder contains a simple example of how to run Qlib RL. It contains:
+
+```
+.
+├── experiment_config
+│   ├── backtest       # Backtest config
+│   └── training       # Training config
+├── README.md          # Readme (the current file)
+└── scripts            # Scripts for data pre-processing
+```
+
+## Data preparation
+
+Use [AzCopy](https://learn.microsoft.com/en-us/azure/storage/common/storage-use-azcopy-v10) to download data:
+
+```
+azcopy copy https://qlibpublic.blob.core.windows.net/data/rl/qlib_rl_example_data ./ --recursive
+mv qlib_rl_example_data data
+```
+
+The downloaded data will be placed at `./data`. The original data are in `data/csv`. To create all data needed by the case, run:
+
+```
+bash scripts/data_pipeline.sh
+```
+
+After the execution finishes, the `data/` directory should be like:
+
+```
+data
+├── backtest_orders.csv
+├── bin
+├── csv
+├── pickle
+├── pickle_dataframe
+└── training_order_split
+```
+
+## Run training
+
+Run:
+
+```
+python ../../qlib/rl/contrib/train_onpolicy.py --config_path ./experiment_config/training/config.yml
+```
+
+After training, checkpoints will be stored under `checkpoints/`.
+
+## Run backtest
+
+```
+python ../../qlib/rl/contrib/backtest.py --config_path ./experiment_config/backtest/config.py
+```
+
+The backtest workflow will use the trained model in `checkpoints/`. The backtest summary can be found in `outputs/`.