# 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 """Launch Isaac Sim Simulator first.""" from isaaclab.app import AppLauncher # launch omniverse app in headless mode simulation_app = AppLauncher(headless=True).app """Rest everything follows from here.""" from collections.abc import Generator import pytest import torch from isaaclab.utils import DelayBuffer @pytest.fixture def delay_buffer(): """Create a delay buffer for testing.""" device: str = "cpu" batch_size: int = 10 history_length: int = 4 return DelayBuffer(history_length, batch_size=batch_size, device=device) def _generate_data(batch_size: int, length: int, device: str) -> Generator[torch.Tensor]: """Data generator for testing the buffer.""" for step in range(length): yield torch.full((batch_size, 1), step, dtype=torch.int, device=device) def test_constant_time_lags(delay_buffer): """Test constant delay.""" const_lag: int = 3 batch_size: int = 10 delay_buffer.set_time_lag(const_lag) all_data = [] for i, data in enumerate(_generate_data(batch_size, 20, delay_buffer.device)): all_data.append(data) # apply delay delayed_data = delay_buffer.compute(data) error = delayed_data - all_data[max(0, i - const_lag)] assert torch.all(error == 0) def test_reset(delay_buffer): """Test resetting the last two batch indices after iteration `reset_itr`.""" const_lag: int = 2 reset_itr = 10 batch_size: int = 10 delay_buffer.set_time_lag(const_lag) all_data = [] for i, data in enumerate(_generate_data(batch_size, 20, delay_buffer.device)): all_data.append(data) # from 'reset_itr' iteration reset the last and second-to-last environments if i == reset_itr: delay_buffer.reset([-2, -1]) # apply delay delayed_data = delay_buffer.compute(data) # before 'reset_itr' is is similar to test_constant_time_lags # after that indices [-2, -1] should be treated separately if i < reset_itr: error = delayed_data - all_data[max(0, i - const_lag)] assert torch.all(error == 0) else: # error_regular = delayed_data[:-2] - all_data[max(0, i - const_lag)][:-2] error2_reset = delayed_data[-2, -1] - all_data[max(reset_itr, i - const_lag)][-2, -1] # assert torch.all(error_regular == 0) assert torch.all(error2_reset == 0) def test_random_time_lags(delay_buffer): """Test random delays.""" max_lag: int = 3 time_lags = torch.randint( low=0, high=max_lag + 1, size=(delay_buffer.batch_size,), dtype=torch.int, device=delay_buffer.device ) delay_buffer.set_time_lag(time_lags) all_data = [] for i, data in enumerate(_generate_data(delay_buffer.batch_size, 20, delay_buffer.device)): all_data.append(data) # apply delay delayed_data = delay_buffer.compute(data) true_delayed_index = torch.maximum(i - delay_buffer.time_lags, torch.zeros_like(delay_buffer.time_lags)) true_delayed_index = true_delayed_index.tolist() for i in range(delay_buffer.batch_size): error = delayed_data[i] - all_data[true_delayed_index[i]][i] assert torch.all(error == 0)