Back to Repositories

Validating MultiDiscrete Space Operations in OpenAI Gym

This test suite validates the MultiDiscrete space implementation in OpenAI Gym’s spaces module. It verifies dimensional handling, subspace operations, and reproducibility of sampling across different MultiDiscrete configurations and shapes.

Test Coverage Overview

The test suite provides comprehensive coverage of MultiDiscrete space functionality.

Key areas tested include:

1D and 2D MultiDiscrete space operations
Subspace access and manipulation
Sample reproducibility across different space configurations
Length handling for both single and multi-dimensional spaces

Edge cases include dimensional boundary checks and shape preservation verification.

Implementation Analysis

The testing approach employs pytest fixtures and assertions to validate MultiDiscrete space behaviors systematically. The implementation uses array-like indexing patterns to verify subspace operations and leverages the data_equivalence utility for sampling verification.

Key patterns include:

Dimensional slicing operations
Seed-based reproducibility checks
Shape consistency validation

Technical Details

Testing tools and configuration:

pytest as the primary testing framework
gym.spaces.MultiDiscrete and Discrete classes
gym.utils.env_checker.data_equivalence for comparison
pytest.warns for warning assertion

Best Practices Demonstrated

The test suite exemplifies high-quality testing practices through systematic validation of functionality.

Notable practices include:

Comprehensive edge case coverage
Explicit state management through seeding
Clear separation of test scenarios
Proper warning handling and verification

openai/gym

tests/spaces/test_multidiscrete.py

            
import pytest

from gym.spaces import Discrete, MultiDiscrete
from gym.utils.env_checker import data_equivalence


def test_multidiscrete_as_tuple():
    # 1D multi-discrete
    space = MultiDiscrete([3, 4, 5])

    assert space.shape == (3,)
    assert space[0] == Discrete(3)
    assert space[0:1] == MultiDiscrete([3])
    assert space[0:2] == MultiDiscrete([3, 4])
    assert space[:] == space and space[:] is not space

    # 2D multi-discrete
    space = MultiDiscrete([[3, 4, 5], [6, 7, 8]])

    assert space.shape == (2, 3)
    assert space[0, 1] == Discrete(4)
    assert space[0] == MultiDiscrete([3, 4, 5])
    assert space[0:1] == MultiDiscrete([[3, 4, 5]])
    assert space[0:2, :] == MultiDiscrete([[3, 4, 5], [6, 7, 8]])
    assert space[:, 0:1] == MultiDiscrete([[3], [6]])
    assert space[0:2, 0:2] == MultiDiscrete([[3, 4], [6, 7]])
    assert space[:] == space and space[:] is not space
    assert space[:, :] == space and space[:, :] is not space


def test_multidiscrete_subspace_reproducibility():
    # 1D multi-discrete
    space = MultiDiscrete([100, 200, 300])
    space.seed()

    assert data_equivalence(space[0].sample(), space[0].sample())
    assert data_equivalence(space[0:1].sample(), space[0:1].sample())
    assert data_equivalence(space[0:2].sample(), space[0:2].sample())
    assert data_equivalence(space[:].sample(), space[:].sample())
    assert data_equivalence(space[:].sample(), space.sample())

    # 2D multi-discrete
    space = MultiDiscrete([[300, 400, 500], [600, 700, 800]])
    space.seed()

    assert data_equivalence(space[0, 1].sample(), space[0, 1].sample())
    assert data_equivalence(space[0].sample(), space[0].sample())
    assert data_equivalence(space[0:1].sample(), space[0:1].sample())
    assert data_equivalence(space[0:2, :].sample(), space[0:2, :].sample())
    assert data_equivalence(space[:, 0:1].sample(), space[:, 0:1].sample())
    assert data_equivalence(space[0:2, 0:2].sample(), space[0:2, 0:2].sample())
    assert data_equivalence(space[:].sample(), space[:].sample())
    assert data_equivalence(space[:, :].sample(), space[:, :].sample())
    assert data_equivalence(space[:, :].sample(), space.sample())


def test_multidiscrete_length():
    space = MultiDiscrete(nvec=[3, 2, 4])
    assert len(space) == 3

    space = MultiDiscrete(nvec=[[2, 3], [3, 2]])
    with pytest.warns(
        UserWarning,
        match="Getting the length of a multi-dimensional MultiDiscrete space.",
    ):
        assert len(space) == 2