mirror of
https://github.com/Farama-Foundation/Gymnasium.git
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Fix Box casting and sampling edge-cases (#774)
Co-authored-by: Mark Towers <mark.m.towers@gmail.com>
This commit is contained in:
James Mochizuki-Freeman
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GitHub
GitHub
parent
144feb865a
commit
89bedf1f33
@@ -9,20 +9,54 @@ from gymnasium.spaces import Box
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@pytest.mark.parametrize(
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"box,expected_shape",
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"dtype, error, message",
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[
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( # Test with same 1-dim low and high shape
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Box(low=np.zeros(2), high=np.ones(2), dtype=np.int32),
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(2,),
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(
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None,
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ValueError,
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"Box dtype must be explicitly provided, cannot be None.",
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),
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( # Test with same multi-dim low and high shape
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Box(low=np.zeros((2, 1)), high=np.ones((2, 1)), dtype=np.int32),
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(2, 1),
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(0, TypeError, "Cannot interpret '0' as a data type"),
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("unknown", TypeError, "data type 'unknown' not understood"),
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(np.zeros(1), TypeError, "Cannot construct a dtype from an array"),
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# disabled datatypes
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(
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np.complex64,
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ValueError,
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"Invalid Box dtype (complex64), must be an integer, floating, or bool dtype",
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),
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( # Test with scalar low high and different shape
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Box(low=0, high=1, shape=(5, 2)),
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(5, 2),
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(
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complex,
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ValueError,
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"Invalid Box dtype (complex128), must be an integer, floating, or bool dtype",
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),
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(
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object,
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ValueError,
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"Invalid Box dtype (object), must be an integer, floating, or bool dtype",
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),
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(
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str,
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ValueError,
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"Invalid Box dtype (<U0), must be an integer, floating, or bool dtype",
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),
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],
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)
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def test_dtype_errors(dtype, error, message):
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"""Test errors due to dtype mismatch either to being invalid or disallowed."""
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with pytest.raises(error, match=re.escape(message)):
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Box(low=0, high=1, dtype=dtype)
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@pytest.mark.parametrize(
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"box, expected_shape",
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[
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# Test with same 1-dim low and high shape
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(Box(low=np.zeros(2), high=np.ones(2)), (2,)),
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# Test with same multi-dim low and high shape
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(Box(low=np.zeros((2, 1)), high=np.ones((2, 1))), (2, 1)),
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# Test with scalar low high and different shape
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(Box(low=0, high=1, shape=(5, 2)), (5, 2)),
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(Box(low=0, high=1), (1,)), # Test with int and int
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(Box(low=0.0, high=1.0), (1,)), # Test with float and float
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(Box(low=np.zeros(1)[0], high=np.ones(1)[0]), (1,)),
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@@ -39,112 +73,209 @@ def test_shape_inference(box, expected_shape):
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@pytest.mark.parametrize(
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"value,valid",
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[
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(1, True),
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(1.0, True),
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(np.int32(1), True),
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(np.float32(1.0), True),
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(np.zeros(2, dtype=np.float32), True),
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(np.zeros((2, 2), dtype=np.float32), True),
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(np.inf, True),
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(np.nan, True), # This is a weird case that we allow
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(True, False),
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(np.bool_(True), False),
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(1 + 1j, False),
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(np.complex128(1 + 1j), False),
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("string", False),
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],
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)
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def test_low_high_values(value, valid: bool):
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"""Test what `low` and `high` values are valid for `Box` space."""
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if valid:
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with warnings.catch_warnings(record=True) as caught_warnings:
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Box(low=-np.inf, high=value)
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assert len(caught_warnings) == 0, tuple(
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warning.message for warning in caught_warnings
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)
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else:
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with pytest.raises(
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ValueError,
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match=re.escape(
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"expected their types to be np.ndarray, an integer or a float"
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),
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):
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Box(low=-np.inf, high=value)
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@pytest.mark.parametrize(
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"low,high,kwargs,error,message",
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"low, high, shape, error_type, message",
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[
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(
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0,
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1,
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{"dtype": None},
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AssertionError,
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"Box dtype must be explicitly provided, cannot be None.",
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1,
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TypeError,
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"Expected Box shape to be an iterable, actual type=<class 'int'>",
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),
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(
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0,
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1,
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{"shape": (None,)},
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AssertionError,
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"Expected all shape elements to be an integer, actual type: (<class 'NoneType'>,)",
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(None,),
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TypeError,
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"Expected all Box shape elements to be integer, actual type=(<class 'NoneType'>,)",
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),
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(
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0,
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1,
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{
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"shape": (
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1,
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None,
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)
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},
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AssertionError,
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"Expected all shape elements to be an integer, actual type: (<class 'int'>, <class 'NoneType'>)",
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(1, None),
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TypeError,
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"Expected all Box shape elements to be integer, actual type=(<class 'int'>, <class 'NoneType'>)",
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),
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(
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0,
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1,
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{
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"shape": (
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np.int64(1),
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None,
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)
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},
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AssertionError,
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"Expected all shape elements to be an integer, actual type: (<class 'numpy.int64'>, <class 'NoneType'>)",
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),
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(
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None,
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None,
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{},
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ValueError,
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"Box shape is inferred from low and high, expected their types to be np.ndarray, an integer or a float, actual type low: <class 'NoneType'>, high: <class 'NoneType'>",
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),
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(
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0,
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None,
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{},
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ValueError,
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"Box shape is inferred from low and high, expected their types to be np.ndarray, an integer or a float, actual type low: <class 'int'>, high: <class 'NoneType'>",
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(np.int64(1), None),
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TypeError,
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"Expected all Box shape elements to be integer, actual type=(<class 'numpy.int64'>, <class 'NoneType'>)",
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),
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(
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np.zeros(3),
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np.ones(2),
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{},
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AssertionError,
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"high.shape doesn't match provided shape, high.shape: (2,), shape: (3,)",
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None,
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ValueError,
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"Box low.shape and high.shape don't match, low.shape=(3,), high.shape=(2,)",
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),
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(
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np.zeros(2),
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np.ones(2),
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(3,),
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ValueError,
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"Box low.shape doesn't match provided shape, low.shape=(2,), shape=(3,)",
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),
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(
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np.zeros(2),
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1,
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(3,),
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ValueError,
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"Box low.shape doesn't match provided shape, low.shape=(2,), shape=(3,)",
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),
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(
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0,
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np.ones(2),
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(3,),
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ValueError,
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"Box high.shape doesn't match provided shape, high.shape=(2,), shape=(3,)",
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),
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],
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)
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def test_init_errors(low, high, kwargs, error, message):
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"""Test all constructor errors."""
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with pytest.raises(error, match=f"^{re.escape(message)}$"):
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Box(low=low, high=high, **kwargs)
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def test_shape_errors(low, high, shape, error_type, message):
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"""Test errors due to shape mismatch."""
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with pytest.raises(error_type, match=f"^{re.escape(message)}$"):
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Box(low=low, high=high, shape=shape)
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def test_dtype_check():
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@pytest.mark.parametrize(
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"low, high, dtype",
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[
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# floats
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(0, 65505.0, np.float16),
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(-65505.0, 0, np.float16),
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# signed int
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(0, 32768, np.int16),
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(-32769, 0, np.int16),
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# unsigned int
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(-1, 100, np.uint8),
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(0, 300, np.uint8),
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# boolean
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(-1, 1, np.bool_),
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(0, 2, np.bool_),
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# array inputs
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(
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np.array([-1, 0]),
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np.array([0, 100]),
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np.uint8,
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),
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(
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np.array([[-1], [0]]),
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np.array([[0], [100]]),
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np.uint8,
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),
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(
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np.array([0, 0]),
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np.array([0, 300]),
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np.uint8,
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),
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(
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np.array([[0], [0]]),
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np.array([[0], [300]]),
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np.uint8,
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),
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],
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)
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def test_out_of_bounds_error(low, high, dtype):
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with pytest.raises(
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ValueError, match=re.escape("is out of bounds of the dtype range,")
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):
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Box(low=low, high=high, dtype=dtype)
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@pytest.mark.parametrize(
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"low, high, dtype",
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[
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# Floats
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(np.nan, 0, np.float32),
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(0, np.nan, np.float32),
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(np.array([0, np.nan]), np.ones(2), np.float32),
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# Signed ints
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(np.nan, 0, np.int32),
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(0, np.nan, np.int32),
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(np.array([0, np.nan]), np.ones(2), np.int32),
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# Unsigned ints
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# (np.nan, 0, np.uint8),
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# (0, np.nan, np.uint8),
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# (np.array([0, np.nan]), np.ones(2), np.uint8),
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(-np.inf, 1, np.uint8),
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(np.array([-np.inf, 0]), 1, np.uint8),
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(0, np.inf, np.uint8),
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(0, np.array([1, np.inf]), np.uint8),
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# boolean
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(-np.inf, 1, np.bool_),
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(0, np.inf, np.bool_),
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],
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)
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def test_invalid_low_high(low, high, dtype):
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if dtype == np.uint8 or dtype == np.bool_:
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with pytest.raises(
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ValueError, match=re.escape("Box unsigned int dtype don't support")
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):
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Box(low=low, high=high, dtype=dtype)
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else:
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with pytest.raises(
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ValueError, match=re.escape("value can be equal to `np.nan`,")
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):
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Box(low=low, high=high, dtype=dtype)
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@pytest.mark.parametrize(
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"low, high, dtype",
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[
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# floats
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(0, 1, float),
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(0, 1, np.float64),
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(0, 1, np.float32),
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(0, 1, np.float16),
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(np.zeros(2), np.ones(2), np.float32),
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(np.zeros(2), 1, np.float32),
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(-np.inf, 1, np.float32),
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(np.array([-np.inf, 0]), 1, np.float32),
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(0, np.inf, np.float32),
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(0, np.array([np.inf, 1]), np.float32),
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(-np.inf, np.inf, np.float32),
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(np.full((2,), -np.inf), np.full((2,), np.inf), np.float32),
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# signed ints
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(0, 1, int),
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(0, 1, np.int64),
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(0, 1, np.int32),
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(0, 1, np.int16),
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(0, 1, np.int8),
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(np.zeros(2), np.ones(2), np.int32),
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(np.zeros(2), 1, np.int32),
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(-np.inf, 1, np.int32),
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(np.array([-np.inf, 0]), 1, np.int32),
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(0, np.inf, np.int32),
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(0, np.array([np.inf, 1]), np.int32),
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# unsigned ints
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(0, 1, np.uint64),
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(0, 1, np.uint32),
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(0, 1, np.uint16),
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(0, 1, np.uint8),
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# boolean
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(0, 1, np.bool_),
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],
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)
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def test_valid_low_high(low, high, dtype):
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with warnings.catch_warnings(record=True) as caught_warnings:
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space = Box(low=low, high=high, dtype=dtype)
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assert space.dtype == dtype
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assert space.low.dtype == dtype
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assert space.high.dtype == dtype
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space.seed(0)
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sample = space.sample()
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assert sample.dtype == dtype
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assert space.contains(sample)
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for warn in caught_warnings:
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if "precision lowered by casting to float32" not in warn.message.args[0]:
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raise Exception(warn)
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def test_contains_dtype():
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"""Tests the Box contains function with different dtypes."""
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# Related Issues:
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# https://github.com/openai/gym/issues/2357
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@@ -163,102 +294,54 @@ def test_dtype_check():
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@pytest.mark.parametrize(
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"space",
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"lowhighshape",
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[
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Box(low=0, high=np.inf, shape=(2,), dtype=np.int32),
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Box(low=0, high=np.inf, shape=(2,), dtype=np.float32),
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Box(low=0, high=np.inf, shape=(2,), dtype=np.int64),
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Box(low=0, high=np.inf, shape=(2,), dtype=np.float64),
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Box(low=-np.inf, high=0, shape=(2,), dtype=np.int32),
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Box(low=-np.inf, high=0, shape=(2,), dtype=np.float32),
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Box(low=-np.inf, high=0, shape=(2,), dtype=np.int64),
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Box(low=-np.inf, high=0, shape=(2,), dtype=np.float64),
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Box(low=-np.inf, high=np.inf, shape=(2,), dtype=np.int32),
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Box(low=-np.inf, high=np.inf, shape=(2,), dtype=np.float32),
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Box(low=-np.inf, high=np.inf, shape=(2,), dtype=np.int64),
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Box(low=-np.inf, high=np.inf, shape=(2,), dtype=np.float64),
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Box(low=0, high=np.inf, shape=(2, 3), dtype=np.int32),
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Box(low=0, high=np.inf, shape=(2, 3), dtype=np.float32),
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Box(low=0, high=np.inf, shape=(2, 3), dtype=np.int64),
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Box(low=0, high=np.inf, shape=(2, 3), dtype=np.float64),
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Box(low=-np.inf, high=0, shape=(2, 3), dtype=np.int32),
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Box(low=-np.inf, high=0, shape=(2, 3), dtype=np.float32),
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Box(low=-np.inf, high=0, shape=(2, 3), dtype=np.int64),
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Box(low=-np.inf, high=0, shape=(2, 3), dtype=np.float64),
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Box(low=-np.inf, high=np.inf, shape=(2, 3), dtype=np.int32),
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Box(low=-np.inf, high=np.inf, shape=(2, 3), dtype=np.float32),
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Box(low=-np.inf, high=np.inf, shape=(2, 3), dtype=np.int64),
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Box(low=-np.inf, high=np.inf, shape=(2, 3), dtype=np.float64),
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Box(low=np.array([-np.inf, 0]), high=np.array([0.0, np.inf]), dtype=np.int32),
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Box(low=np.array([-np.inf, 0]), high=np.array([0.0, np.inf]), dtype=np.float32),
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Box(low=np.array([-np.inf, 0]), high=np.array([0.0, np.inf]), dtype=np.int64),
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Box(low=np.array([-np.inf, 0]), high=np.array([0.0, np.inf]), dtype=np.float64),
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dict(low=0, high=np.inf, shape=(2,)),
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dict(low=-np.inf, high=0, shape=(2,)),
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dict(low=-np.inf, high=np.inf, shape=(2,)),
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dict(low=0, high=np.inf, shape=(2, 3)),
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dict(low=-np.inf, high=0, shape=(2, 3)),
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dict(low=-np.inf, high=np.inf, shape=(2, 3)),
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dict(low=np.array([-np.inf, 0]), high=np.array([0.0, np.inf])),
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],
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)
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def test_infinite_space(space):
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@pytest.mark.parametrize("dtype", [np.int32, np.int64, np.float32, np.float64])
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def test_infinite_space(lowhighshape, dtype):
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"""
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To test spaces that are passed in have only 0 or infinite bounds because `space.high` and `space.low`
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are both modified within the init, we check for infinite when we know it's not 0
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"""
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space = Box(**lowhighshape, dtype=dtype)
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assert np.all(
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space.low < space.high
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), f"Box low bound ({space.low}) is not lower than the high bound ({space.high})"
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assert np.all(space.low < space.high)
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space.seed(0)
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sample = space.sample()
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# check if space contains sample
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assert (
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sample in space
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), f"Sample ({sample}) not inside space according to `space.contains()`"
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# manually check that the sign of the sample is within the bounds
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assert np.all(
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np.sign(sample) <= np.sign(space.high)
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), f"Sign of sample ({sample}) is less than space upper bound ({space.high})"
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assert np.all(
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np.sign(space.low) <= np.sign(sample)
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), f"Sign of sample ({sample}) is more than space lower bound ({space.low})"
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# check that int bounds are bounded for everything
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# but floats are unbounded for infinite
|
||||
if np.any(space.high != 0):
|
||||
assert (
|
||||
space.is_bounded("above") is False
|
||||
), "inf upper bound supposed to be unbounded"
|
||||
else:
|
||||
assert (
|
||||
space.is_bounded("above") is True
|
||||
), "non-inf upper bound supposed to be bounded"
|
||||
|
||||
if np.any(space.low != 0):
|
||||
assert (
|
||||
space.is_bounded("below") is False
|
||||
), "inf lower bound supposed to be unbounded"
|
||||
else:
|
||||
assert (
|
||||
space.is_bounded("below") is True
|
||||
), "non-inf lower bound supposed to be bounded"
|
||||
|
||||
if np.any(space.low != 0) or np.any(space.high != 0):
|
||||
assert space.is_bounded("both") is False
|
||||
else:
|
||||
assert space.is_bounded("both") is True
|
||||
# check that int bounds are bounded for everything but floats are unbounded for infinite
|
||||
assert space.is_bounded("above") is not np.any(space.high != 0)
|
||||
assert space.is_bounded("below") is not np.any(space.low != 0)
|
||||
assert space.is_bounded("both") is not (
|
||||
np.any(space.high != 0) | np.any(space.high != 0)
|
||||
)
|
||||
|
||||
# check for dtype
|
||||
assert (
|
||||
space.high.dtype == space.dtype
|
||||
), f"High's dtype {space.high.dtype} doesn't match `space.dtype`'"
|
||||
assert (
|
||||
space.low.dtype == space.dtype
|
||||
), f"Low's dtype {space.high.dtype} doesn't match `space.dtype`'"
|
||||
assert space.high.dtype == space.dtype
|
||||
assert space.low.dtype == space.dtype
|
||||
|
||||
with pytest.raises(
|
||||
ValueError, match="manner is not in {'below', 'above', 'both'}, actual value:"
|
||||
):
|
||||
space.is_bounded("test")
|
||||
|
||||
# Check sample
|
||||
space.seed(0)
|
||||
sample = space.sample()
|
||||
|
||||
# check if space contains sample
|
||||
assert sample in space
|
||||
|
||||
# manually check that the sign of the sample is within the bounds
|
||||
assert np.all(np.sign(sample) <= np.sign(space.high))
|
||||
assert np.all(np.sign(space.low) <= np.sign(sample))
|
||||
|
||||
|
||||
def test_legacy_state_pickling():
|
||||
legacy_state = {
|
||||
@@ -290,56 +373,3 @@ def test_sample_mask():
|
||||
match=re.escape("Box.sample cannot be provided a mask, actual value: "),
|
||||
):
|
||||
space.sample(mask=np.array([0, 1, 0], dtype=np.int8))
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"low, high, shape, dtype, reason",
|
||||
[
|
||||
(
|
||||
5.0,
|
||||
3.0,
|
||||
(),
|
||||
np.float32,
|
||||
"Some low values are greater than high, low=5.0, high=3.0",
|
||||
),
|
||||
(
|
||||
np.array([5.0, 6.0]),
|
||||
np.array([1.0, 5.99]),
|
||||
(2,),
|
||||
np.float32,
|
||||
"Some low values are greater than high, low=[5. 6.], high=[1. 5.99]",
|
||||
),
|
||||
(
|
||||
np.inf,
|
||||
np.inf,
|
||||
(),
|
||||
np.float32,
|
||||
"No low value can be equal to `np.inf`, low=inf",
|
||||
),
|
||||
(
|
||||
np.array([0, np.inf]),
|
||||
np.array([np.inf, np.inf]),
|
||||
(2,),
|
||||
np.float32,
|
||||
"No low value can be equal to `np.inf`, low=[ 0. inf]",
|
||||
),
|
||||
(
|
||||
-np.inf,
|
||||
-np.inf,
|
||||
(),
|
||||
np.float32,
|
||||
"No high value can be equal to `-np.inf`, high=-inf",
|
||||
),
|
||||
(
|
||||
np.array([-np.inf, -np.inf]),
|
||||
np.array([0, -np.inf]),
|
||||
(2,),
|
||||
np.float32,
|
||||
"No high value can be equal to `-np.inf`, high=[ 0. -inf]",
|
||||
),
|
||||
],
|
||||
)
|
||||
def test_invalid_low_high(low, high, dtype, shape, reason):
|
||||
"""Tests that we don't allow spaces with degenerate bounds, such as `Box(np.inf, -np.inf)`."""
|
||||
with pytest.raises(ValueError, match=re.escape(reason)):
|
||||
Box(low=low, high=high, dtype=dtype, shape=shape)
|
||||
|
||||
Reference in New Issue
Block a user