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|
| | """Launch Isaac Sim Simulator first.""" |
| |
|
| | from isaaclab.app import AppLauncher |
| |
|
| | |
| | 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 |
| |
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| |
|
| | @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) |
| | |
| | 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) |
| | |
| | if i == reset_itr: |
| | delay_buffer.reset([-2, -1]) |
| | |
| | delayed_data = delay_buffer.compute(data) |
| | |
| | |
| | if i < reset_itr: |
| | error = delayed_data - all_data[max(0, i - const_lag)] |
| | assert torch.all(error == 0) |
| | else: |
| | |
| | error2_reset = delayed_data[-2, -1] - all_data[max(reset_itr, i - const_lag)][-2, -1] |
| | |
| | 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) |
| | |
| | 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) |
| |
|