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e913bc81b8
* feat: add `isort` to `pre-commit` * ci: skip `__init__.py` file for `isort` * ci: make `isort` mandatory in lint pipeline * docs: add a section on Git hooks * ci: check isort diff * fix: isort from master branch * docs: add pre-commit badge * ci: update black + bandit versions * feat: add PR template * refactor: PR template * ci: remove bandit * docs: add Black badge * ci: try to remove all `|| true` statements * ci: remove lint_python job - Remove `lint_python` CI job - Move `pyupgrade` job to `pre-commit` workflow * fix: avoid messing with typing * docs: add a note on running `pre-cpmmit` manually * ci: apply `pre-commit` to the whole codebase
132 lines
4.0 KiB
Python
132 lines
4.0 KiB
Python
import numpy as np
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import pytest
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from gym.spaces import Box, Dict, MultiDiscrete, Tuple
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from gym.vector.utils.spaces import batch_space, iterate
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from tests.vector.utils import CustomSpace, custom_spaces, spaces
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expected_batch_spaces_4 = [
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Box(low=-1.0, high=1.0, shape=(4,), dtype=np.float64),
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Box(low=0.0, high=10.0, shape=(4, 1), dtype=np.float64),
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Box(
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low=np.array(
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[[-1.0, 0.0, 0.0], [-1.0, 0.0, 0.0], [-1.0, 0.0, 0.0], [-1.0, 0.0, 0.0]]
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),
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high=np.array(
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[[1.0, 1.0, 1.0], [1.0, 1.0, 1.0], [1.0, 1.0, 1.0], [1.0, 1.0, 1.0]]
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),
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dtype=np.float64,
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),
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Box(
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low=np.array(
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[
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[[-1.0, 0.0], [0.0, -1.0]],
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[[-1.0, 0.0], [0.0, -1.0]],
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[[-1.0, 0.0], [0.0, -1]],
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[[-1.0, 0.0], [0.0, -1.0]],
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]
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),
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high=np.ones((4, 2, 2)),
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dtype=np.float64,
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),
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Box(low=0, high=255, shape=(4,), dtype=np.uint8),
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Box(low=0, high=255, shape=(4, 32, 32, 3), dtype=np.uint8),
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MultiDiscrete([2, 2, 2, 2]),
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Box(low=-2, high=2, shape=(4,), dtype=np.int64),
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Tuple((MultiDiscrete([3, 3, 3, 3]), MultiDiscrete([5, 5, 5, 5]))),
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Tuple(
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(
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MultiDiscrete([7, 7, 7, 7]),
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Box(
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low=np.array([[0.0, -1.0], [0.0, -1.0], [0.0, -1.0], [0.0, -1]]),
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high=np.array([[1.0, 1.0], [1.0, 1.0], [1.0, 1.0], [1.0, 1.0]]),
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dtype=np.float64,
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),
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)
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),
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Box(
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low=np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]),
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high=np.array([[10, 12, 16], [10, 12, 16], [10, 12, 16], [10, 12, 16]]),
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dtype=np.int64,
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),
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Box(low=0, high=1, shape=(4, 19), dtype=np.int8),
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Dict(
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{
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"position": MultiDiscrete([23, 23, 23, 23]),
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"velocity": Box(low=0.0, high=1.0, shape=(4, 1), dtype=np.float64),
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}
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),
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Dict(
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{
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"position": Dict(
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{
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"x": MultiDiscrete([29, 29, 29, 29]),
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"y": MultiDiscrete([31, 31, 31, 31]),
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}
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),
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"velocity": Tuple(
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(
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MultiDiscrete([37, 37, 37, 37]),
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Box(low=0, high=255, shape=(4,), dtype=np.uint8),
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)
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),
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}
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),
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]
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expected_custom_batch_spaces_4 = [
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Tuple((CustomSpace(), CustomSpace(), CustomSpace(), CustomSpace())),
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Tuple(
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(
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Tuple((CustomSpace(), CustomSpace(), CustomSpace(), CustomSpace())),
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Box(low=0, high=255, shape=(4,), dtype=np.uint8),
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)
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),
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]
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@pytest.mark.parametrize(
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"space,expected_batch_space_4",
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list(zip(spaces, expected_batch_spaces_4)),
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ids=[space.__class__.__name__ for space in spaces],
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)
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def test_batch_space(space, expected_batch_space_4):
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batch_space_4 = batch_space(space, n=4)
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assert batch_space_4 == expected_batch_space_4
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@pytest.mark.parametrize(
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"space,expected_batch_space_4",
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list(zip(custom_spaces, expected_custom_batch_spaces_4)),
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ids=[space.__class__.__name__ for space in custom_spaces],
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)
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def test_batch_space_custom_space(space, expected_batch_space_4):
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batch_space_4 = batch_space(space, n=4)
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assert batch_space_4 == expected_batch_space_4
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@pytest.mark.parametrize(
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"space,batch_space",
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list(zip(spaces, expected_batch_spaces_4)),
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ids=[space.__class__.__name__ for space in spaces],
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)
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def test_iterate(space, batch_space):
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items = batch_space.sample()
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iterator = iterate(batch_space, items)
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for i, item in enumerate(iterator):
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assert item in space
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assert i == 3
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@pytest.mark.parametrize(
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"space,batch_space",
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list(zip(custom_spaces, expected_custom_batch_spaces_4)),
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ids=[space.__class__.__name__ for space in custom_spaces],
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)
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def test_iterate_custom_space(space, batch_space):
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items = batch_space.sample()
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iterator = iterate(batch_space, items)
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for i, item in enumerate(iterator):
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assert item in space
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assert i == 3
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