doge/config.py

from dataclasses import dataclass
import torch


@dataclass
class doge_config:
    # Experiment
    device: str = "cuda" if torch.cuda.is_available() else "cpu"
    dataset_name: str = "halfcheetah-medium-v2"
    seed: int = 42
    max_timesteps: int = int(1e6)
    
    max_action : float = 1.0

    action_dim: int = 6
    state_dim: int = 17

    buffer_size: int = 1_000_000
    actor_lr: float = 3e-4
    critic_lr: float = 3e-4
    distance_lr: float = 1e-3
    hidden_dim: int = 256
    batch_size: int = 256
    discount: float = 0.99
    tau: float = 0.005
    policy_noise: float = 0.2
    noise_clip: float = 0.5
    policy_freq: int = 2

    initial_lambda: float = 6.0
    lambda_max: float = 100.0
    lambda_min: float = 1.0
    lambda_threshold: float = 0.0

    num_negative_samples: int = 20

    alpha: float = 17.5  # 7.5

    distance_steps: int = int(1e5)
    lambda_lr: float = 3e-4

    critic_ln: bool = True
    normalize: bool = True

    project: str = "DOGE"
    group: str = dataset_name
    name: str = dataset_name + "_" + str(seed)