test_model.py

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# Copyright (c) 2021-2025, Hewlett Packard Enterprise
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from uuid import uuid4

import numpy as np
import pytest

from smartsim import Experiment
from smartsim._core.launcher.step import SbatchStep, SrunStep
from smartsim.entity import Ensemble, Model
from smartsim.entity.model import _parse_model_parameters
from smartsim.error import EntityExistsError, SSUnsupportedError
from smartsim.settings import RunSettings, SbatchSettings, SrunSettings
from smartsim.settings.mpiSettings import _BaseMPISettings

# The tests in this file belong to the slow_tests group
pytestmark = pytest.mark.slow_tests


def test_register_incoming_entity_preexists(test_dir):
    exp = Experiment("experiment", test_dir, launcher="local")
    rs = RunSettings("python", exe_args="sleep.py")
    ensemble = exp.create_ensemble(name="ensemble", replicas=1, run_settings=rs)
    m = exp.create_model("model", run_settings=rs)
    m.register_incoming_entity(ensemble["ensemble_0"])
    assert len(m.incoming_entities) == 1
    with pytest.raises(EntityExistsError):
        m.register_incoming_entity(ensemble["ensemble_0"])


def test_disable_key_prefixing(test_dir):
    exp = Experiment("experiment", test_dir, launcher="local")
    rs = RunSettings("python", exe_args="sleep.py")
    m = exp.create_model("model", run_settings=rs)
    m.disable_key_prefixing()
    assert m.query_key_prefixing() == False


def test_catch_colo_mpmd_model(test_dir):
    exp = Experiment("experiment", test_dir, launcher="local")
    rs = _BaseMPISettings("python", exe_args="sleep.py", fail_if_missing_exec=False)

    # make it an mpmd model
    rs_2 = _BaseMPISettings("python", exe_args="sleep.py", fail_if_missing_exec=False)
    rs.make_mpmd(rs_2)

    model = exp.create_model("bad_colo_model", rs)

    # make it colocated which should raise and error
    with pytest.raises(SSUnsupportedError):
        model.colocate_db()


def test_attach_batch_settings_to_model(test_dir):
    exp = Experiment("experiment", test_dir, launcher="slurm")
    bs = SbatchSettings()
    rs = SrunSettings("python", exe_args="sleep.py")

    model_wo_bs = exp.create_model("test_model", run_settings=rs)
    assert model_wo_bs.batch_settings is None

    model_w_bs = exp.create_model("test_model_2", run_settings=rs, batch_settings=bs)
    assert isinstance(model_w_bs.batch_settings, SbatchSettings)


@pytest.fixture
def monkeypatch_exp_controller(monkeypatch):
    def _monkeypatch_exp_controller(exp):
        entity_steps = []

        def start_wo_job_manager(
            self,
            exp_name,
            exp_path,
            manifest,
            block=True,
            kill_on_interrupt=True,
            monitor=True,
        ):
            self._launch(exp_name, exp_path, manifest)
            return None

        def launch_step_nop(self, step, entity, monitor):
            entity_steps.append((step, entity))

        monkeypatch.setattr(
            exp._control,
            "start",
            start_wo_job_manager.__get__(exp._control, type(exp._control)),
        )
        monkeypatch.setattr(
            exp._control,
            "_launch_step",
            launch_step_nop.__get__(exp._control, type(exp._control)),
        )

        return entity_steps

    return _monkeypatch_exp_controller


def test_model_with_batch_settings_makes_batch_step(
    monkeypatch_exp_controller, test_dir
):
    exp = Experiment("experiment", launcher="slurm", exp_path=test_dir)
    bs = SbatchSettings()
    rs = SrunSettings("python", exe_args="sleep.py")
    model = exp.create_model("test_model", run_settings=rs, batch_settings=bs)

    entity_steps = monkeypatch_exp_controller(exp)
    exp.start(model)

    assert len(entity_steps) == 1
    step, entity = entity_steps[0]
    assert isinstance(entity, Model)
    assert isinstance(step, SbatchStep)


def test_model_without_batch_settings_makes_run_step(
    monkeypatch, monkeypatch_exp_controller, test_dir
):
    exp = Experiment("experiment", launcher="slurm", exp_path=test_dir)
    rs = SrunSettings("python", exe_args="sleep.py")
    model = exp.create_model("test_model", run_settings=rs)

    # pretend we are in an allocation to not raise alloc err
    monkeypatch.setenv("SLURM_JOB_ID", "12345")

    entity_steps = monkeypatch_exp_controller(exp)
    exp.start(model)

    assert len(entity_steps) == 1
    step, entity = entity_steps[0]
    assert isinstance(entity, Model)
    assert isinstance(step, SrunStep)


def test_models_batch_settings_are_ignored_in_ensemble(
    monkeypatch_exp_controller, test_dir
):
    exp = Experiment("experiment", launcher="slurm", exp_path=test_dir)
    bs_1 = SbatchSettings(nodes=5)
    rs = SrunSettings("python", exe_args="sleep.py")
    model = exp.create_model("test_model", run_settings=rs, batch_settings=bs_1)

    bs_2 = SbatchSettings(nodes=10)
    ens = exp.create_ensemble("test_ensemble", batch_settings=bs_2)
    ens.add_model(model)

    entity_steps = monkeypatch_exp_controller(exp)
    exp.start(ens)

    assert len(entity_steps) == 1
    step, entity = entity_steps[0]
    assert isinstance(entity, Ensemble)
    assert isinstance(step, SbatchStep)
    assert step.batch_settings.batch_args["nodes"] == "10"
    assert len(step.step_cmds) == 1
    step_cmd = step.step_cmds[0]
    assert any("srun" in tok for tok in step_cmd)  # call the model using run settings
    assert not any("sbatch" in tok for tok in step_cmd)  # no sbatch in sbatch


@pytest.mark.parametrize("dtype", [int, np.float32, str])
def test_good_model_params(dtype):
    print(dtype(0.6))
    params = {"foo": dtype(0.6)}
    assert all(isinstance(val, str) for val in _parse_model_parameters(params).values())


@pytest.mark.parametrize("bad_val", [["eggs"], {"n": 5}, object])
def test_bad_model_params(bad_val):
    with pytest.raises(TypeError):
        _parse_model_parameters({"foo": bad_val})