# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md). # All rights reserved. # # SPDX-License-Identifier: BSD-3-Clause # ignore private usage of variables warning # pyright: reportPrivateUsage=none from __future__ import annotations """Launch Isaac Sim Simulator first.""" from isaaclab.app import AppLauncher # launch omniverse app simulation_app = AppLauncher(headless=True).app """Rest everything follows.""" import pytest import torch import omni.usd from isaaclab.envs import ManagerBasedEnv, ManagerBasedEnvCfg from isaaclab.managers import ObservationGroupCfg as ObsGroup from isaaclab.managers import ObservationTermCfg as ObsTerm from isaaclab.scene import InteractiveSceneCfg from isaaclab.utils import configclass @configclass class EmptyManagerCfg: """Empty manager specifications for the environment.""" pass @configclass class EmptyObservationWithHistoryCfg: """Empty observation with history specifications for the environment.""" @configclass class EmptyObservationGroupWithHistoryCfg(ObsGroup): """Empty observation with history specifications for the environment.""" dummy_term: ObsTerm = ObsTerm(func=lambda env: torch.randn(env.num_envs, 1, device=env.device)) def __post_init__(self): self.history_length = 5 empty_observation: EmptyObservationGroupWithHistoryCfg = EmptyObservationGroupWithHistoryCfg() @configclass class EmptySceneCfg(InteractiveSceneCfg): """Configuration for an empty scene.""" pass def get_empty_base_env_cfg(device: str = "cuda:0", num_envs: int = 1, env_spacing: float = 1.0): """Generate base environment config based on device""" @configclass class EmptyEnvCfg(ManagerBasedEnvCfg): """Configuration for the empty test environment.""" # Scene settings scene: EmptySceneCfg = EmptySceneCfg(num_envs=num_envs, env_spacing=env_spacing) # Basic settings actions: EmptyManagerCfg = EmptyManagerCfg() observations: EmptyManagerCfg = EmptyManagerCfg() def __post_init__(self): """Post initialization.""" # step settings self.decimation = 4 # env step every 4 sim steps: 200Hz / 4 = 50Hz # simulation settings self.sim.dt = 0.005 # sim step every 5ms: 200Hz self.sim.render_interval = self.decimation # render every 4 sim steps # pass device down from test self.sim.device = device return EmptyEnvCfg() def get_empty_base_env_cfg_with_history(device: str = "cuda:0", num_envs: int = 1, env_spacing: float = 1.0): """Generate base environment config based on device""" @configclass class EmptyEnvWithHistoryCfg(ManagerBasedEnvCfg): """Configuration for the empty test environment.""" # Scene settings scene: EmptySceneCfg = EmptySceneCfg(num_envs=num_envs, env_spacing=env_spacing) # Basic settings actions: EmptyManagerCfg = EmptyManagerCfg() observations: EmptyObservationWithHistoryCfg = EmptyObservationWithHistoryCfg() def __post_init__(self): """Post initialization.""" # step settings self.decimation = 4 # env step every 4 sim steps: 200Hz / 4 = 50Hz # simulation settings self.sim.dt = 0.005 # sim step every 5ms: 200Hz self.sim.render_interval = self.decimation # render every 4 sim steps # pass device down from test self.sim.device = device return EmptyEnvWithHistoryCfg() @pytest.mark.parametrize("device", ["cuda:0", "cpu"]) def test_initialization(device): """Test initialization of ManagerBasedEnv.""" # create a new stage omni.usd.get_context().new_stage() # create environment env = ManagerBasedEnv(cfg=get_empty_base_env_cfg(device=device)) # check size of action manager terms assert env.action_manager.total_action_dim == 0 assert len(env.action_manager.active_terms) == 0 assert len(env.action_manager.action_term_dim) == 0 # check size of observation manager terms assert len(env.observation_manager.active_terms) == 0 assert len(env.observation_manager.group_obs_dim) == 0 assert len(env.observation_manager.group_obs_term_dim) == 0 assert len(env.observation_manager.group_obs_concatenate) == 0 # create actions of correct size (1,0) act = torch.randn_like(env.action_manager.action) # step environment to verify setup for _ in range(2): obs, ext = env.step(action=act) # close the environment env.close() @pytest.mark.parametrize("device", ["cuda:0", "cpu"]) def test_observation_history_changes_only_after_step(device): """Test observation history of ManagerBasedEnv. The history buffer should only change after a step is taken. """ # create a new stage omni.usd.get_context().new_stage() # create environment with history length of 5 env = ManagerBasedEnv(cfg=get_empty_base_env_cfg_with_history(device=device)) # check if history buffer is empty for group_name in env.observation_manager._group_obs_term_names: group_term_names = env.observation_manager._group_obs_term_names[group_name] for term_name in group_term_names: torch.testing.assert_close( env.observation_manager._group_obs_term_history_buffer[group_name][term_name].current_length, torch.zeros((env.num_envs,), device=device, dtype=torch.int64), ) # check if history buffer is empty after compute env.observation_manager.compute() for group_name in env.observation_manager._group_obs_term_names: group_term_names = env.observation_manager._group_obs_term_names[group_name] for term_name in group_term_names: torch.testing.assert_close( env.observation_manager._group_obs_term_history_buffer[group_name][term_name].current_length, torch.zeros((env.num_envs,), device=device, dtype=torch.int64), ) # check if history buffer is not empty after step act = torch.randn_like(env.action_manager.action) env.step(act) group_obs = dict() for group_name in env.observation_manager._group_obs_term_names: group_term_names = env.observation_manager._group_obs_term_names[group_name] group_obs[group_name] = dict() for term_name in group_term_names: torch.testing.assert_close( env.observation_manager._group_obs_term_history_buffer[group_name][term_name].current_length, torch.ones((env.num_envs,), device=device, dtype=torch.int64), ) group_obs[group_name][term_name] = env.observation_manager._group_obs_term_history_buffer[group_name][ term_name ].buffer # check if history buffer is not empty after compute and is the same as the buffer after step env.observation_manager.compute() for group_name in env.observation_manager._group_obs_term_names: group_term_names = env.observation_manager._group_obs_term_names[group_name] for term_name in group_term_names: torch.testing.assert_close( env.observation_manager._group_obs_term_history_buffer[group_name][term_name].current_length, torch.ones((env.num_envs,), device=device, dtype=torch.int64), ) assert torch.allclose( group_obs[group_name][term_name], env.observation_manager._group_obs_term_history_buffer[group_name][term_name].buffer, ) # close the environment env.close()