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tests: fix formatting
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@kmantel
kmantel committed Dec 13, 2023
1 parent ba8b5bb commit 205fd77
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Showing 2 changed files with 90 additions and 71 deletions.
22 changes: 13 additions & 9 deletions conftest.py
View file
Original file line number Diff line number Diff line change
@@ -1,15 +1,16 @@
import doctest
import pytest

import pytest
from psyneulink.core import llvm as pnlvm


def pytest_runtest_setup(item):
if 'cuda' in item.keywords and not pnlvm.ptx_enabled:
pytest.skip('PTX engine not enabled/available')
pytest.skip('PTX engine not enabled/available')

doctest.ELLIPSIS_MARKER = "[...]"


def pytest_generate_tests(metafunc):
if "comp_mode_no_llvm" in metafunc.fixturenames:
modes = [m for m in get_comp_execution_modes()
Expand All @@ -23,20 +24,23 @@ def pytest_generate_tests(metafunc):
def pytest_runtest_teardown(item):
pnlvm.cleanup()


@pytest.fixture
def comp_mode_no_llvm():
# dummy fixture to allow 'comp_mode' filtering
pass


@pytest.helpers.register
def get_comp_execution_modes():
return [pytest.param(pnlvm.ExecutionMode.Python),
pytest.param(pnlvm.ExecutionMode.LLVM, marks=pytest.mark.llvm),
pytest.param(pnlvm.ExecutionMode.LLVMExec, marks=pytest.mark.llvm),
pytest.param(pnlvm.ExecutionMode.LLVMRun, marks=pytest.mark.llvm),
pytest.param(pnlvm.ExecutionMode.PTXExec, marks=[pytest.mark.llvm, pytest.mark.cuda]),
pytest.param(pnlvm.ExecutionMode.PTXRun, marks=[pytest.mark.llvm, pytest.mark.cuda])
]
return [
pytest.param(pnlvm.ExecutionMode.Python),
pytest.param(pnlvm.ExecutionMode.LLVM, marks=pytest.mark.llvm),
pytest.param(pnlvm.ExecutionMode.LLVMExec, marks=pytest.mark.llvm),
pytest.param(pnlvm.ExecutionMode.LLVMRun, marks=pytest.mark.llvm),
pytest.param(pnlvm.ExecutionMode.PTXExec, marks=[pytest.mark.llvm, pytest.mark.cuda]),
pytest.param(pnlvm.ExecutionMode.PTXRun, marks=[pytest.mark.llvm, pytest.mark.cuda])
]


# TODO: remove this helper when tests no longer use psyneulink
Expand Down
139 changes: 77 additions & 62 deletions tests/scheduling/test_scheduler.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -501,9 +501,9 @@ def test_6_two_environment_state_updates(self):
termination_conds[pnl.TimeScale.ENVIRONMENT_SEQUENCE] = pnl.AfterNEnvironmentStateUpdates(2)
termination_conds[pnl.TimeScale.ENVIRONMENT_STATE_UPDATE] = pnl.AfterNCalls(C, 3)
comp.run(
inputs={A: [[0], [1], [2], [3], [4], [5]]},
scheduler=sched,
termination_processing=termination_conds
inputs={A: [[0], [1], [2], [3], [4], [5]]},
scheduler=sched,
termination_processing=termination_conds
)
output = sched.execution_list[comp.default_execution_id]

Expand Down Expand Up @@ -1335,7 +1335,7 @@ def test_three_ABAC(self):
function=pnl.Linear(slope=2.0),
)

c = pnl.Composition(pathways=[[A,B],[A,C]])
c = pnl.Composition(pathways=[[A, B], [A, C]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.AfterNCalls(C, 1)}
stim_list = {A: [[1]]}
Expand Down Expand Up @@ -1384,7 +1384,7 @@ def test_three_ABAC_convenience(self):
function=pnl.Linear(slope=2.0),
)

c = pnl.Composition(pathways=[[A,B],[A,C]])
c = pnl.Composition(pathways=[[A, B], [A, C]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.AfterNCalls(C, 1)}
stim_list = {A: [[1]]}
Expand Down Expand Up @@ -1431,7 +1431,7 @@ def test_three_ABACx2(self):
function=pnl.Linear(slope=2.0),
)

c = pnl.Composition(pathways=[[A,B],[A,C]])
c = pnl.Composition(pathways=[[A, B], [A, C]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.AfterNCalls(C, 2)}
stim_list = {A: [[1]]}
Expand Down Expand Up @@ -1483,7 +1483,7 @@ def test_three_2_ABC(self):
function=pnl.Linear(slope=2.0),
)

c = pnl.Composition(pathways=[[A,C],[B,C]])
c = pnl.Composition(pathways=[[A, C], [B, C]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.AfterNCalls(C, 1)}
stim_list = {A: [[1]], B: [[2]]}
Expand Down Expand Up @@ -1531,7 +1531,7 @@ def test_three_2_ABCx2(self):
function=pnl.Linear(slope=2.0),
)

c = pnl.Composition(pathways=[[A,C],[B,C]])
c = pnl.Composition(pathways=[[A, C], [B, C]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.AfterNCalls(C, 2)}
stim_list = {A: [[1]], B: [[2]]}
Expand Down Expand Up @@ -1581,7 +1581,7 @@ def test_three_integrators(self):
)
)

c = pnl.Composition(pathways=[[A,C],[B,C]])
c = pnl.Composition(pathways=[[A, C], [B, C]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.AfterNCalls(C, 2)}
stim_list = {A: [[1]], B: [[1]]}
Expand Down Expand Up @@ -1642,7 +1642,7 @@ def test_four_ABBCD(self):
function=pnl.Linear(slope=1.0),
)

c = pnl.Composition(pathways=[[A,B,D],[A,C,D]])
c = pnl.Composition(pathways=[[A, B, D], [A, C, D]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.AfterNCalls(D, 1)}
stim_list = {A: [[1]]}
Expand Down Expand Up @@ -1702,7 +1702,7 @@ def test_four_integrators_mixed(self):
)
)

c = pnl.Composition(pathways=[[A,C],[A,D],[B,C],[B,D]])
c = pnl.Composition(pathways=[[A, C], [A, D], [B, C], [B, D]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.All(pnl.AfterNCalls(C, 1), pnl.AfterNCalls(D, 1))}
stim_list = {A: [[1]], B: [[1]]}
Expand Down Expand Up @@ -1771,7 +1771,7 @@ def test_five_ABABCDE(self):
function=pnl.Linear(slope=2.0),
)

c = pnl.Composition(pathways=[[A,C,D],[B,C,E]])
c = pnl.Composition(pathways=[[A, C, D], [B, C, E]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.AfterNCalls(E, 1)}
stim_list = {A: [[1]], B: [[2]]}
Expand Down Expand Up @@ -1857,7 +1857,7 @@ def test_six_integrators_threelayer_mixed(self):
)
)

c = pnl.Composition(pathways=[[A,C,E],[A,C,F],[A,D,E],[A,D,F],[B,C,E],[B,C,F],[B,D,E],[B,D,F]])
c = pnl.Composition(pathways=[[A, C, E], [A, C, F], [A, D, E], [A, D, F], [B, C, E], [B, C, F], [B, D, E], [B, D, F]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.All(pnl.AfterNCalls(E, 1), pnl.AfterNCalls(F, 1))}
stim_list = {A: [[1]], B: [[1]]}
Expand Down Expand Up @@ -1990,7 +1990,7 @@ def test_termination_conditions_reset_execution(self):
function=pnl.Linear(slope=2.0),
)

c = pnl.Composition(pathways=[[A,B]])
c = pnl.Composition(pathways=[[A, B]])

term_conds = {pnl.TimeScale.ENVIRONMENT_STATE_UPDATE: pnl.AfterNCalls(B, 2)}
stim_list = {A: [[1]]}
Expand Down Expand Up @@ -2026,22 +2026,28 @@ def test_termination_conditions_reset_execution(self):
for i in range(len(expected_output)):
np.testing.assert_allclose(expected_output[i], terminal_mech.get_output_values(c)[i])

@pytest.mark.parametrize('timescale, expected',
[(pnl.TimeScale.CONSIDERATION_SET_EXECUTION, [[0.5], [0.4375]]),
(pnl.TimeScale.PASS, [[0.5], [0.4375]]),
(pnl.TimeScale.ENVIRONMENT_STATE_UPDATE, [[1.5], [0.4375]]),
(pnl.TimeScale.ENVIRONMENT_SEQUENCE, [[1.5], [0.4375]])],
ids=lambda x: x if isinstance(x, pnl.TimeScale) else "")
@pytest.mark.parametrize(
'timescale, expected',
[
(pnl.TimeScale.CONSIDERATION_SET_EXECUTION, [[0.5], [0.4375]]),
(pnl.TimeScale.PASS, [[0.5], [0.4375]]),
(pnl.TimeScale.ENVIRONMENT_STATE_UPDATE, [[1.5], [0.4375]]),
(pnl.TimeScale.ENVIRONMENT_SEQUENCE, [[1.5], [0.4375]])
],
ids=lambda x: x if isinstance(x, pnl.TimeScale) else ""
)
# 'LLVM' mode is not supported, because synchronization of compiler and
# python values during execution is not implemented.
@pytest.mark.usefixtures("comp_mode_no_llvm")
def test_time_termination_measures(self, comp_mode, timescale, expected):
in_one_pass = timescale in {pnl.TimeScale.CONSIDERATION_SET_EXECUTION, pnl.TimeScale.PASS}
attention = pnl.TransferMechanism(name='Attention',
integrator_mode=True,
termination_threshold=3,
termination_measure=timescale,
execute_until_finished=in_one_pass)
attention = pnl.TransferMechanism(
name='Attention',
integrator_mode=True,
termination_threshold=3,
termination_measure=timescale,
execute_until_finished=in_one_pass
)
counter = pnl.IntegratorMechanism(
function=pnl.AdaptiveIntegrator(rate=0.0, offset=1.0))

Expand All @@ -2061,39 +2067,43 @@ def test_time_termination_measures(self, comp_mode, timescale, expected):
assert response.execution_count == 1
assert np.allclose(result, expected)

@pytest.mark.parametrize("condition,scale,expected_result",
[(pnl.BeforeNCalls, pnl.TimeScale.ENVIRONMENT_STATE_UPDATE, [[.05, .05]]),
(pnl.BeforeNCalls, pnl.TimeScale.PASS, [[.05, .05]]),
(pnl.EveryNCalls, None, [[0.05, .05]]),
(pnl.AtNCalls, pnl.TimeScale.ENVIRONMENT_STATE_UPDATE, [[.25, .25]]),
(pnl.AtNCalls, pnl.TimeScale.ENVIRONMENT_SEQUENCE, [[.25, .25]]),
(pnl.AfterNCalls, pnl.TimeScale.ENVIRONMENT_STATE_UPDATE, [[.25, .25]]),
(pnl.AfterNCalls, pnl.TimeScale.PASS, [[.05, .05]]),
(pnl.WhenFinished, None, [[1.0, 1.0]]),
(pnl.WhenFinishedAny, None, [[1.0, 1.0]]),
(pnl.WhenFinishedAll, None, [[1.0, 1.0]]),
(pnl.All, None, [[1.0, 1.0]]),
(pnl.Any, None, [[1.0, 1.0]]),
(pnl.Not, None, [[.05, .05]]),
(pnl.AllHaveRun, None, [[.05, .05]]),
(pnl.Always, None, [[0.05, 0.05]]),
(pnl.AtPass, None, [[.3, .3]]),
(pnl.AtTrial, None, [[0.05, 0.05]]),
#(pnl.Never), #TODO: Find a good test case for this!
])
@pytest.mark.parametrize(
"condition,scale,expected_result",
[
(pnl.BeforeNCalls, pnl.TimeScale.ENVIRONMENT_STATE_UPDATE, [[.05, .05]]),
(pnl.BeforeNCalls, pnl.TimeScale.PASS, [[.05, .05]]),
(pnl.EveryNCalls, None, [[0.05, .05]]),
(pnl.AtNCalls, pnl.TimeScale.ENVIRONMENT_STATE_UPDATE, [[.25, .25]]),
(pnl.AtNCalls, pnl.TimeScale.ENVIRONMENT_SEQUENCE, [[.25, .25]]),
(pnl.AfterNCalls, pnl.TimeScale.ENVIRONMENT_STATE_UPDATE, [[.25, .25]]),
(pnl.AfterNCalls, pnl.TimeScale.PASS, [[.05, .05]]),
(pnl.WhenFinished, None, [[1.0, 1.0]]),
(pnl.WhenFinishedAny, None, [[1.0, 1.0]]),
(pnl.WhenFinishedAll, None, [[1.0, 1.0]]),
(pnl.All, None, [[1.0, 1.0]]),
(pnl.Any, None, [[1.0, 1.0]]),
(pnl.Not, None, [[.05, .05]]),
(pnl.AllHaveRun, None, [[.05, .05]]),
(pnl.Always, None, [[0.05, 0.05]]),
(pnl.AtPass, None, [[.3, .3]]),
(pnl.AtTrial, None, [[0.05, 0.05]]),
# (pnl.Never), #TODO: Find a good test case for this!
]
)
# 'LLVM' mode is not supported, because synchronization of compiler and
# python values during execution is not implemented.
@pytest.mark.usefixtures("comp_mode_no_llvm")
def test_scheduler_conditions(self, comp_mode, condition, scale, expected_result):
decisionMaker = pnl.DDM(
function=pnl.DriftDiffusionIntegrator(starting_value=0,
threshold=1,
noise=0.0,
time_step_size=1.0),
reset_stateful_function_when=pnl.AtTrialStart(),
execute_until_finished=False,
output_ports=[pnl.DECISION_VARIABLE, pnl.RESPONSE_TIME],
name='pnl.DDM')
function=pnl.DriftDiffusionIntegrator(starting_value=0,
threshold=1,
noise=0.0,
time_step_size=1.0),
reset_stateful_function_when=pnl.AtTrialStart(),
execute_until_finished=False,
output_ports=[pnl.DECISION_VARIABLE, pnl.RESPONSE_TIME],
name='pnl.DDM'
)

response = pnl.ProcessingMechanism(size=2, name="GATE")

Expand Down Expand Up @@ -2136,19 +2146,24 @@ def test_scheduler_conditions(self, comp_mode, condition, scale, expected_result
comp.scheduler.add_condition(response, condition(0))

result = comp.run([0.05], execution_mode=comp_mode)
#HACK: The result is an object dtype in Python mode for some reason?
# HACK: The result is an object dtype in Python mode for some reason?
if comp_mode is pnl.ExecutionMode.Python:
result = np.asfarray(result[0])
assert np.allclose(result, expected_result)


@pytest.mark.parametrize("mode", [pnl.ExecutionMode.Python,
pytest.param(pnl.ExecutionMode.LLVMRun, marks=pytest.mark.llvm),
pytest.param(pnl.ExecutionMode.PTXRun, marks=[pytest.mark.llvm, pytest.mark.cuda]),
])
@pytest.mark.parametrize("condition,scale,expected_result",
[(pnl.AtTrial, None, [[[1.0]], [[2.0]]]),
])
@pytest.mark.parametrize(
"mode", [
pnl.ExecutionMode.Python,
pytest.param(pnl.ExecutionMode.LLVMRun, marks=pytest.mark.llvm),
pytest.param(pnl.ExecutionMode.PTXRun, marks=[pytest.mark.llvm, pytest.mark.cuda]),
]
)
@pytest.mark.parametrize(
"condition,scale,expected_result",
[
(pnl.AtTrial, None, [[[1.0]], [[2.0]]]),
]
)
def test_run_term_conditions(self, mode, condition, scale, expected_result):
incrementing_mechanism = pnl.ProcessingMechanism(
function=pnl.SimpleIntegrator
Expand Down

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