from easydict import EasyDict
import ding.envs.gym_env

cfg = dict(
    exp_name='Walker2d-v3-TD3',
    seed=0,
    env=dict(
        env_id='Walker2d-v3',
        norm_obs=dict(use_norm=False, ),
        norm_reward=dict(use_norm=False, ),
        collector_env_num=1,
        evaluator_env_num=8,
        n_evaluator_episode=8,
        stop_value=6000,
        env_wrapper='mujoco_default',
    ),
    policy=dict(
        cuda=True,
        random_collect_size=25000,
        model=dict(
            obs_shape=17,
            action_shape=6,
            twin_critic=True,
            actor_head_hidden_size=256,
            critic_head_hidden_size=256,
            action_space='regression',
        ),
        learn=dict(
            update_per_collect=1,
            batch_size=256,
            learning_rate_actor=1e-3,
            learning_rate_critic=1e-3,
            ignore_done=False,
            target_theta=0.005,
            discount_factor=0.99,
            actor_update_freq=2,
            noise=True,
            noise_sigma=0.2,
            noise_range=dict(
                min=-0.5,
                max=0.5,
            ),
        ),
        collect=dict(
            n_sample=1,
            unroll_len=1,
            noise_sigma=0.1,
        ),
        other=dict(replay_buffer=dict(replay_buffer_size=1000000, ), ),
    ),
    wandb_logger=dict(
        gradient_logger=True, video_logger=True, plot_logger=True, action_logger=True, return_logger=False
    ),
)

cfg = EasyDict(cfg)

env = ding.envs.gym_env.env