def test_observation_when_raw_step_returns_incorrect_no_of_observations():
"""Test that a ServiceError is propagated when raw_step() returns unexpected
number of observations."""
def make_failing_raw_step(n: int):
def failing_raw_step(*args, **kwargs):
"""A callback that returns done=True."""
del args # Unused
del kwargs # Unused
return ["ir"] * n, None, False, {}
return failing_raw_step
spaces = [
ObservationSpace(
name="ir",
space=Space(int64_value=Int64Range(min=0)),
)
]
observation = ObservationView(make_failing_raw_step(0), spaces)
with pytest.raises(
ServiceError,
match=r"^Expected 1 'ir' observation but the service returned 0$"):
observation["ir"]
observation = ObservationView(make_failing_raw_step(3), spaces)
with pytest.raises(
ServiceError,
match=r"^Expected 1 'ir' observation but the service returned 3$"):
observation["ir"]
def test_observation_when_raw_step_returns_done():
"""Test that a SessionNotFoundError from the raw_step() callback propagates as a"""
def make_failing_raw_step(error_msg=None):
def failing_raw_step(*args, **kwargs):
"""A callback that returns done=True."""
info = {}
if error_msg:
info["error_details"] = error_msg
return [], None, True, info
return failing_raw_step
spaces = [
ObservationSpace(
name="ir",
space=Space(int64_value=Int64Range(min=0)),
)
]
observation = ObservationView(make_failing_raw_step(), spaces)
with pytest.raises(ServiceError,
match=r"^Failed to compute observation 'ir'$"):
observation["ir"] # pylint: disable=pointless-statement
observation = ObservationView(make_failing_raw_step("Oh no!"), spaces)
with pytest.raises(ServiceError,
match=r"^Failed to compute observation 'ir': Oh no!$"):
observation["ir"] # pylint: disable=pointless-statement
def test_register_derived_space():
spaces = [
ObservationSpace(
name="ir",
string_size_range=ScalarRange(min=ScalarLimit(value=0)),
),
]
mock = MockGetObservation(
ret=[Observation(string_value="Hello, world!")],
)
observation = ObservationView(mock, spaces)
observation.register_derived_space(
base_name="ir",
derived_name="ir_len",
derived_space=Box(low=0, high=float("inf"), shape=(1,), dtype=int),
cb=lambda base: [
len(base),
],
)
value = observation["ir_len"]
assert isinstance(value, list)
assert value == [
len("Hello, world!"),
]
def test_invalid_observation_index():
spaces = [
ObservationSpace(
name="ir",
string_size_range=ScalarRange(min=ScalarLimit(value=0)),
)
]
observation = ObservationView(MockGetObservation(), spaces)
with pytest.raises(KeyError):
_ = observation[100]
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 = MockGetObservation(ret=[
Observation(string_value="Hello, IR"),
Observation(double_list=DoubleList(value=[1.0, 2.0])),
Observation(int64_list=Int64List(value=[-5, 15])),
Observation(binary_value=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])
assert value.dtype == np.float64
value = observation["features"]
np.testing.assert_array_equal(value, [-5, 15])
assert value.dtype == np.int64
value = observation["binary"]
assert value == b"Hello, bytes\0"
# Check that the correct observation_space_list indices were used.
assert mock.called_observation_spaces == [0, 2, 1, 3]
def test_invalid_observation_name():
spaces = [
ObservationSpace(
name="ir",
string_size_range=ScalarRange(min=ScalarLimit(value=0)),
)
]
observation = ObservationView(MockGetObservation(), spaces)
with pytest.raises(KeyError) as ctx:
_ = observation["invalid"]
assert str(ctx.value) == "'invalid'"
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_empty_space():
with pytest.raises(ValueError) as ctx:
ObservationView(MockRawStep(), [])
assert str(ctx.value) == "No observation spaces"
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"
]