rlkit/envs/goal_generation/pickup_goal_dataset.py [83:105]:
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        print("loaded data from saved file", filename)
    else:
        now = time.time()

        if env_id is not None:
            import gym
            import multiworld
            multiworld.register_all_envs()
            env = gym.make(env_id)
        else:
            if vae_dataset_specific_env_kwargs is None:
                vae_dataset_specific_env_kwargs = {}
            for key, val in env_kwargs.items():
                if key not in vae_dataset_specific_env_kwargs:
                    vae_dataset_specific_env_kwargs[key] = val
            env = env_class(**vae_dataset_specific_env_kwargs)
        if not isinstance(env, ImageEnv):
            env = ImageEnv(
                env,
                imsize,
                init_camera=init_camera,
                transpose=True,
                normalize=True,
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rlkit/launchers/skewfit_experiments.py [207:229]:
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            print("loaded data from saved file", filename)
        else:
            now = time.time()

            if env_id is not None:
                import gym
                import multiworld
                multiworld.register_all_envs()
                env = gym.make(env_id)
            else:
                if vae_dataset_specific_env_kwargs is None:
                    vae_dataset_specific_env_kwargs = {}
                for key, val in env_kwargs.items():
                    if key not in vae_dataset_specific_env_kwargs:
                        vae_dataset_specific_env_kwargs[key] = val
                env = env_class(**vae_dataset_specific_env_kwargs)
            if not isinstance(env, ImageEnv):
                env = ImageEnv(
                    env,
                    imsize,
                    init_camera=init_camera,
                    transpose=True,
                    normalize=True,
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