import numpy as np

def split_paths(paths):
    """
    Stack multiples obs/actions/etc. from different paths
    :param paths: List of paths, where one path is something returned from
    the rollout functino above.
    :return: Tuple. Every element will have shape batch_size X DIM, including
    the rewards and terminal flags.
    """
    rewards = [path["rewards"].reshape(-1, 1) for path in paths]
    terminals = [path["terminals"].reshape(-1, 1) for path in paths]
    actions = [path["actions"] for path in paths]
    obs = [path["observations"] for path in paths]
    next_obs = [path["next_observations"] for path in paths]
    rewards = np.vstack(rewards)
    terminals = np.vstack(terminals)
    obs = np.vstack(obs)
    actions = np.vstack(actions)
    next_obs = np.vstack(next_obs)
    assert len(rewards.shape) == 2
    assert len(terminals.shape) == 2
    assert len(obs.shape) == 2
    assert len(actions.shape) == 2
    assert len(next_obs.shape) == 2
    return rewards, terminals, obs, actions, next_obs


def split_paths_to_dict(paths):
    rewards, terminals, obs, actions, next_obs = split_paths(paths)
    return dict(
        rewards=rewards,
        terminals=terminals,
        observations=obs,
        actions=actions,
        next_observations=next_obs,
    )
