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mirror of https://github.com/microsoft/qlib.git synced 2026-07-14 00:06:58 +08:00

Migrate NeuTrader to Qlib RL (#1169)

* Refine previous version RL codes

* Polish utils/__init__.py

* Draft

* Use | instead of Union

* Simulator & action interpreter

* Test passed

* Migrate to SAOEState & new qlib interpreter

* Black format

* . Revert file_storage change

* Refactor file structure & renaming functions

* Enrich test cases

* Add QlibIntradayBacktestData

* Test interpreter

* Black format

* .

.

.

* Rename receive_execute_result()

* Use indicator to simplify state update

* Format code

* Modify data path

* Adjust file structure

* Minor change

* Add copyright message

* Format code

* Rename util functions

* Add CI

* Pylint issue

* Remove useless code to pass pylint

* Pass mypy

* Mypy issue

* mypy issue

* mypy issue

* Revert "mypy issue"

This reverts commit 8eb1b0174e.

* mypy issue

* mypy issue

* Fix the numpy version incompatible bug

* Fix a minor typing issue

* Try to skip python 3.7 test for qlib simulator

* Resolve PR comments by Yuge; solve several CI issues.

* Black issue

* Fix a low-level type error

* Change data name

* Resolve PR comments. Leave TODOs in the code base.

Co-authored-by: Young <afe.young@gmail.com>
This commit is contained in:
Huoran Li
2022-08-01 09:56:07 +08:00
committed by GitHub
parent 687edd79d0
commit 2752bdc92c
35 changed files with 1305 additions and 257 deletions

View File

@@ -5,6 +5,8 @@ from random import randint, choice
from pathlib import Path
import re
from typing import Any, Tuple
import gym
import numpy as np
import pandas as pd
@@ -24,16 +26,16 @@ from qlib.rl.utils.finite_env import vectorize_env
class SimpleEnv(gym.Env[int, int]):
def __init__(self):
def __init__(self) -> None:
self.logger = LogCollector()
self.observation_space = gym.spaces.Discrete(2)
self.action_space = gym.spaces.Discrete(2)
def reset(self):
def reset(self, *args: Any, **kwargs: Any) -> int:
self.step_count = 0
return 0
def step(self, action: int):
def step(self, action: int) -> Tuple[int, float, bool, dict]:
self.logger.reset()
self.logger.add_scalar("reward", 42.0)
@@ -53,6 +55,9 @@ class SimpleEnv(gym.Env[int, int]):
return 1, 42.0, done, InfoDict(log=self.logger.logs(), aux_info={})
def render(self, mode: str = "human") -> None:
pass
class AnyPolicy(BasePolicy):
def forward(self, batch, state=None):
@@ -86,7 +91,8 @@ def test_simple_env_logger(caplog):
class SimpleSimulator(Simulator[int, float, float]):
def __init__(self, initial: int, **kwargs) -> None:
def __init__(self, initial: int, **kwargs: Any) -> None:
super(SimpleSimulator, self).__init__(initial, **kwargs)
self.initial = float(initial)
def step(self, action: float) -> None: