import numpy as np from ddpg.ddpg import DDPG from ddpg.evaluator import Evaluator from ddpg.main import train, test from ddpg.normalized_env import NormalizedEnv from args.ddpg import get_args try: from hyperdash import Experiment hyperdash_support = True except: hyperdash_support = False args = get_args(env="HalfCheetah2-v0") env = NormalizedEnv(gym.make(args.env)) env.env.env._init( # real robot torques={ "bthigh": 120, "bshin": 90, "bfoot": 60, "fthigh": 120, "fshin": 60, "ffoot": 30 }, colored=False )
from ddpg.evaluator import Evaluator from ddpg.main import train, test from ddpg.normalized_env import NormalizedEnv from args.ddpg import get_args from simple_joints_lstm.lstm_simple_net2_cheetah import LstmSimpleNet2Cheetah try: from hyperdash import Experiment hyperdash_support = True except: hyperdash_support = False MODEL_PATH = "trained_models/simple_lstm_cheetah_v2.pt" args = get_args(env="HalfCheetah2Plus-v0") env = NormalizedEnv(gym.make(args.env)) env.env.load_model(LstmSimpleNet2Cheetah(), MODEL_PATH) env.env.env.env._init( # simulator torques={ "bthigh": 600, "bshin": 18, "bfoot": 300, "fthigh": 24, "fshin": 300, "ffoot": 6 }, colored=True