def test_observed_value_types():
spaces = [
ObservationSpace(
name="ir",
space=Space(string_value=StringSpace(length_range=Int64Range(
min=0))),
),
ObservationSpace(
name="features",
space=Space(int64_box=Int64Box(
low=Int64Tensor(shape=[2], value=[-100, -100]),
high=Int64Tensor(shape=[2], value=[100, 100]),
), ),
),
ObservationSpace(
name="dfeat",
space=Space(double_box=DoubleBox(
low=DoubleTensor(shape=[1], value=[0.5]),
high=DoubleTensor(shape=[1], value=[2.5]),
), ),
),
ObservationSpace(
name="binary",
space=Space(int64_value=Int64Range(min=5, max=5)),
),
]
mock = MockRawStep(ret=[
"Hello, IR",
[1.0, 2.0],
[-5, 15],
b"Hello, bytes\0",
"Hello, IR",
[1.0, 2.0],
[-5, 15],
b"Hello, bytes\0",
])
observation = ObservationView(mock, spaces)
value = observation["ir"]
assert isinstance(value, str)
assert value == "Hello, IR"
value = observation["dfeat"]
np.testing.assert_array_almost_equal(value, [1.0, 2.0])
value = observation["features"]
np.testing.assert_array_equal(value, [-5, 15])
value = observation["binary"]
assert value == b"Hello, bytes\0"
# Check that the correct observation_space_list indices were used.
assert mock.called_observation_spaces == [
"ir", "dfeat", "features", "binary"
]
mock.called_observation_spaces = []
# Repeat the above tests using the generated bound methods.
value = observation.ir()
assert isinstance(value, str)
assert value == "Hello, IR"
value = observation.dfeat()
np.testing.assert_array_almost_equal(value, [1.0, 2.0])
value = observation.features()
np.testing.assert_array_equal(value, [-5, 15])
value = observation.binary()
assert value == b"Hello, bytes\0"
# Check that the correct observation_space_list indices were used.
assert mock.called_observation_spaces == [
"ir", "dfeat", "features", "binary"
]
def test_observed_value_types():
spaces = [
ObservationSpace(
name="ir",
string_size_range=ScalarRange(min=ScalarLimit(value=0)),
),
ObservationSpace(
name="features",
int64_range_list=ScalarRangeList(range=[
ScalarRange(min=ScalarLimit(value=-100),
max=ScalarLimit(value=100)),
ScalarRange(min=ScalarLimit(value=-100),
max=ScalarLimit(value=100)),
]),
),
ObservationSpace(
name="dfeat",
double_range_list=ScalarRangeList(range=[
ScalarRange(min=ScalarLimit(value=0.5),
max=ScalarLimit(value=2.5))
]),
),
ObservationSpace(
name="binary",
binary_size_range=ScalarRange(min=ScalarLimit(value=5),
max=ScalarLimit(value=5)),
),
]
mock = MockRawStep(ret=[
"Hello, IR",
[1.0, 2.0],
[-5, 15],
b"Hello, bytes\0",
"Hello, IR",
[1.0, 2.0],
[-5, 15],
b"Hello, bytes\0",
])
observation = ObservationView(mock, spaces)
value = observation["ir"]
assert isinstance(value, str)
assert value == "Hello, IR"
value = observation["dfeat"]
np.testing.assert_array_almost_equal(value, [1.0, 2.0])
value = observation["features"]
np.testing.assert_array_equal(value, [-5, 15])
value = observation["binary"]
assert value == b"Hello, bytes\0"
# Check that the correct observation_space_list indices were used.
assert mock.called_observation_spaces == [
"ir", "dfeat", "features", "binary"
]
mock.called_observation_spaces = []
# Repeat the above tests using the generated bound methods.
value = observation.ir()
assert isinstance(value, str)
assert value == "Hello, IR"
value = observation.dfeat()
np.testing.assert_array_almost_equal(value, [1.0, 2.0])
value = observation.features()
np.testing.assert_array_equal(value, [-5, 15])
value = observation.binary()
assert value == b"Hello, bytes\0"
# Check that the correct observation_space_list indices were used.
assert mock.called_observation_spaces == [
"ir", "dfeat", "features", "binary"
]