# Path: util/dm_control_util.py
# BASE_PATH = init_path.get_abs_base_dir()
# DM_ENV_INFO = {
#     # fishes
#     'fish3d-swim': {'ob_size': 20, 'ac_size': 5, 'length': 1000},
#     'fish3d-easyswim': {'ob_size': 20, 'ac_size': 5, 'length': 1000},
#     'fish3d-speed': {'ob_size': 17, 'ac_size': 5, 'length': 1000},
# 
#     'acrobot-swingup_sparse': {'ob_size': 6, 'ac_size': 1, 'length': 1000},
#     'acrobot-swingup': {'ob_size': 6, 'ac_size': 1, 'length': 1000},
# 
#     'ball_in_cup-catch': {'ob_size': 8, 'ac_size': 2, 'length': 1000},
# 
#     'cartpole-swingup_sparse': {'ob_size': 5, 'ac_size': 1, 'length': 1000},
#     'cartpole-balance': {'ob_size': 5, 'ac_size': 1, 'length': 1000},
#     'cartpole-balance_sparse': {'ob_size': 5, 'ac_size': 1, 'length': 1000},
#     'cartpole-swingup': {'ob_size': 5, 'ac_size': 1, 'length': 1000},
# 
#     'cheetah-run': {'ob_size': 17, 'ac_size': 6, 'length': 1000},
# 
#     'finger-turn_easy': {'ob_size': 12, 'ac_size': 2, 'length': 1000},
#     'finger-spin': {'ob_size': 9, 'ac_size': 2, 'length': 1000},
#     'finger-turn_hard': {'ob_size': 12, 'ac_size': 2, 'length': 1000},
# 
#     'fish-upright': {'ob_size': 21, 'ac_size': 5, 'length': 1000},
#     'fish-swim': {'ob_size': 24, 'ac_size': 5, 'length': 1000},
# 
#     'hopper-stand': {'ob_size': 15, 'ac_size': 4, 'length': 1000},
#     'hopper-hop': {'ob_size': 15, 'ac_size': 4, 'length': 1000},
# 
#     'humanoid-run': {'ob_size': 67, 'ac_size': 21, 'length': 1000},
#     'humanoid-stand': {'ob_size': 67, 'ac_size': 21, 'length': 1000},
#     'humanoid-walk': {'ob_size': 67, 'ac_size': 21, 'length': 1000},
# 
#     'manipulator-bring_ball': {'ob_size': 37, 'ac_size': 5, 'length': 1000},
# 
#     'pendulum-swingup': {'ob_size': 3, 'ac_size': 1, 'length': 1000},
# 
#     'point_mass-easy': {'ob_size': 4, 'ac_size': 2, 'length': 1000},
# 
#     'reacher-hard': {'ob_size': 7, 'ac_size': 2, 'length': 1000},
#     'reacher-easy': {'ob_size': 7, 'ac_size': 2, 'length': 1000},
# 
#     'swimmer-swimmer6': {'ob_size': 25, 'ac_size': 5, 'length': 1000},
#     'swimmer-swimmer15': {'ob_size': 61, 'ac_size': 14, 'length': 1000},
# 
#     'walker-run': {'ob_size': 24, 'ac_size': 6, 'length': 1000},
#     'walker-stand': {'ob_size': 24, 'ac_size': 6, 'length': 1000},
#     'walker-walk': {'ob_size': 24, 'ac_size': 6, 'length': 1000},
# 
#     'humanoid_CMU-run': {'ob_size': 137, 'ac_size': 56, 'length': 1000},
#     'humanoid_CMU-stand': {'ob_size': 137, 'ac_size': 56, 'length': 1000},
#     'humanoid_CMU-walk': {'ob_size': 137, 'ac_size': 56, 'length': 1000},
# }
# def render(pixel):
# def vectorize_ob(ob_dictionary):
# def get_ob_size(env):
# def get_env_names(task_name):
# def io_information(task_name):
# 
# Path: util/logger.py
# class _MyFormatter(logging.Formatter):
#     def format(self, record):
# def set_file_handler(path=None, prefix='', time_str=''):
# _LOGGING_METHOD = ['info', 'warning', 'error', 'critical',
#                    'warn', 'exception', 'debug']


import init_path
import os
import numpy as np
from util import dm_control_util
from util import logger
        from dm_control import suite

    return path


class dm_env_wrapper(object):

    def __init__(self, args, rand_seed, monitor, width=480, height=480):
        self.width = width
        self.height = height
        task_name = dm_control_util.get_env_names(args.task)
        self.env = suite.load(
            domain_name=task_name[0], task_name=task_name[1],
            task_kwargs={'random': rand_seed}
        )
        self._base_path = init_path.get_abs_base_dir()
        self.NUM_EPISODE_RECORED = NUM_EPISODE_RECORED
        self._is_dirname = True

        # save the video
        self._monitor = monitor
        self._current_episode = 0
        if self._monitor:
            self.init_save(args)

    def step(self, action):
        if self._monitor and \
                self._current_episode % self._video_freq < NUM_EPISODE_RECORED:
            self._qpos_data.append(np.array(self.env.physics.data.qpos))

        step_return = self.env.step(action)

# Path: util/dm_control_util.py
# BASE_PATH = init_path.get_abs_base_dir()
# DM_ENV_INFO = {
#     # fishes
#     'fish3d-swim': {'ob_size': 20, 'ac_size': 5, 'length': 1000},
#     'fish3d-easyswim': {'ob_size': 20, 'ac_size': 5, 'length': 1000},
#     'fish3d-speed': {'ob_size': 17, 'ac_size': 5, 'length': 1000},
# 
#     'acrobot-swingup_sparse': {'ob_size': 6, 'ac_size': 1, 'length': 1000},
#     'acrobot-swingup': {'ob_size': 6, 'ac_size': 1, 'length': 1000},
# 
#     'ball_in_cup-catch': {'ob_size': 8, 'ac_size': 2, 'length': 1000},
# 
#     'cartpole-swingup_sparse': {'ob_size': 5, 'ac_size': 1, 'length': 1000},
#     'cartpole-balance': {'ob_size': 5, 'ac_size': 1, 'length': 1000},
#     'cartpole-balance_sparse': {'ob_size': 5, 'ac_size': 1, 'length': 1000},
#     'cartpole-swingup': {'ob_size': 5, 'ac_size': 1, 'length': 1000},
# 
#     'cheetah-run': {'ob_size': 17, 'ac_size': 6, 'length': 1000},
# 
#     'finger-turn_easy': {'ob_size': 12, 'ac_size': 2, 'length': 1000},
#     'finger-spin': {'ob_size': 9, 'ac_size': 2, 'length': 1000},
#     'finger-turn_hard': {'ob_size': 12, 'ac_size': 2, 'length': 1000},
# 
#     'fish-upright': {'ob_size': 21, 'ac_size': 5, 'length': 1000},
#     'fish-swim': {'ob_size': 24, 'ac_size': 5, 'length': 1000},
# 
#     'hopper-stand': {'ob_size': 15, 'ac_size': 4, 'length': 1000},
#     'hopper-hop': {'ob_size': 15, 'ac_size': 4, 'length': 1000},
# 
#     'humanoid-run': {'ob_size': 67, 'ac_size': 21, 'length': 1000},
#     'humanoid-stand': {'ob_size': 67, 'ac_size': 21, 'length': 1000},
#     'humanoid-walk': {'ob_size': 67, 'ac_size': 21, 'length': 1000},
# 
#     'manipulator-bring_ball': {'ob_size': 37, 'ac_size': 5, 'length': 1000},
# 
#     'pendulum-swingup': {'ob_size': 3, 'ac_size': 1, 'length': 1000},
# 
#     'point_mass-easy': {'ob_size': 4, 'ac_size': 2, 'length': 1000},
# 
#     'reacher-hard': {'ob_size': 7, 'ac_size': 2, 'length': 1000},
#     'reacher-easy': {'ob_size': 7, 'ac_size': 2, 'length': 1000},
# 
#     'swimmer-swimmer6': {'ob_size': 25, 'ac_size': 5, 'length': 1000},
#     'swimmer-swimmer15': {'ob_size': 61, 'ac_size': 14, 'length': 1000},
# 
#     'walker-run': {'ob_size': 24, 'ac_size': 6, 'length': 1000},
#     'walker-stand': {'ob_size': 24, 'ac_size': 6, 'length': 1000},
#     'walker-walk': {'ob_size': 24, 'ac_size': 6, 'length': 1000},
# 
#     'humanoid_CMU-run': {'ob_size': 137, 'ac_size': 56, 'length': 1000},
#     'humanoid_CMU-stand': {'ob_size': 137, 'ac_size': 56, 'length': 1000},
#     'humanoid_CMU-walk': {'ob_size': 137, 'ac_size': 56, 'length': 1000},
# }
# def render(pixel):
# def vectorize_ob(ob_dictionary):
# def get_ob_size(env):
# def get_env_names(task_name):
# def io_information(task_name):
# 
# Path: util/logger.py
# class _MyFormatter(logging.Formatter):
#     def format(self, record):
# def set_file_handler(path=None, prefix='', time_str=''):
# _LOGGING_METHOD = ['info', 'warning', 'error', 'critical',
#                    'warn', 'exception', 'debug']


# Path: env/dm_env_wrapper.py
import init_path
import os
import numpy as np
from util import dm_control_util
from util import logger
        from dm_control import suite


    return path


class dm_env_wrapper(object):

    def __init__(self, args, rand_seed, monitor, width=480, height=480):
        self.width = width
        self.height = height
        task_name = dm_control_util.get_env_names(args.task)
        self.env = suite.load(
            domain_name=task_name[0], task_name=task_name[1],
            task_kwargs={'random': rand_seed}
        )
        self._base_path = init_path.get_abs_base_dir()
        self.NUM_EPISODE_RECORED = NUM_EPISODE_RECORED
        self._is_dirname = True

        # save the video
        self._monitor = monitor
        self._current_episode = 0
        if self._monitor:
            self.init_save(args)

    def step(self, action):
        if self._monitor and \
                self._current_episode % self._video_freq < NUM_EPISODE_RECORED:
            self._qpos_data.append(np.array(self.env.physics.data.qpos))

        step_return = self.env.step(action)

        return dm_control_util.vectorize_ob(step_return.observation), \