Files
tensorneat-mend/problem/rl_env/brax_env.py
2023-10-22 21:01:06 +08:00

84 lines
2.7 KiB
Python

from dataclasses import dataclass
from typing import Callable
import jax.numpy as jnp
from brax import envs
from core import State
from .rl_jit import RLEnv, RLEnvConfig
@dataclass(frozen=True)
class BraxConfig(RLEnvConfig):
env_name: str = "ant"
backend: str = "generalized"
def __post_init__(self):
# TODO: Check if env_name is registered
# assert self.env_name in gymnax.registered_envs, f"Env {self.env_name} not registered"
pass
class BraxEnv(RLEnv):
def __init__(self, config: BraxConfig = BraxConfig()):
super().__init__(config)
self.config = config
self.env = envs.create(env_name=config.env_name, backend=config.backend)
def env_step(self, randkey, env_state, action):
state = self.env.step(env_state, action)
return state.obs, state, state.reward, state.done.astype(jnp.bool_), state.info
def env_reset(self, randkey):
init_state = self.env.reset(randkey)
return init_state.obs, init_state
@property
def input_shape(self):
return (self.env.observation_size,)
@property
def output_shape(self):
return (self.env.action_size,)
def show(self, randkey, state: State, act_func: Callable, params, save_path=None, height=512, width=512,
duration=0.1, *args,
**kwargs):
import jax
import imageio
import numpy as np
from brax.io import image
from tqdm import tqdm
obs, env_state = self.reset(randkey)
reward, done = 0.0, False
state_histories = []
def step(key, env_state, obs):
key, _ = jax.random.split(key)
net_out = act_func(state, obs, params)
action = self.config.output_transform(net_out)
obs, env_state, r, done, _ = self.step(randkey, env_state, action)
return key, env_state, obs, r, done
while not done:
state_histories.append(env_state.pipeline_state)
key, env_state, obs, r, done = jax.jit(step)(randkey, env_state, obs)
reward += r
imgs = [image.render_array(sys=self.env.sys, state=s, width=width, height=height) for s in
tqdm(state_histories, desc="Rendering")]
def create_gif(image_list, gif_name, duration):
with imageio.get_writer(gif_name, mode='I', duration=duration) as writer:
for image in image_list:
# 确保图像的数据类型正确
formatted_image = np.array(image, dtype=np.uint8)
writer.append_data(formatted_image)
create_gif(imgs, save_path, duration=0.1)
print("Gif saved to: ", save_path)
print("Total reward: ", reward)