def test_recommended_parallelism(self):
ax_client = AxClient()
with self.assertRaisesRegex(ValueError, "No generation strategy"):
ax_client.get_max_parallelism()
ax_client.create_experiment(
parameters=[
{"name": "x", "type": "range", "bounds": [-5.0, 10.0]},
{"name": "y", "type": "range", "bounds": [0.0, 15.0]},
],
minimize=True,
)
self.assertEqual(ax_client.get_max_parallelism(), [(5, 5), (-1, 3)])
self.assertEqual(
run_trials_using_recommended_parallelism(
ax_client, ax_client.get_max_parallelism(), 20
),
0,
)
# With incorrect parallelism setting, the 'need more data' error should
# still be raised.
ax_client = AxClient()
ax_client.create_experiment(
parameters=[
{"name": "x", "type": "range", "bounds": [-5.0, 10.0]},
{"name": "y", "type": "range", "bounds": [0.0, 15.0]},
],
minimize=True,
)
with self.assertRaisesRegex(DataRequiredError, "All trials for current model "):
run_trials_using_recommended_parallelism(ax_client, [(6, 6), (-1, 3)], 20)
def test_default_generation_strategy_discrete(self) -> None:
"""Test that Sobol is used if no GenerationStrategy is provided and
the search space is discrete.
"""
# Test that Sobol is chosen when all parameters are choice.
ax_client = AxClient()
ax_client.create_experiment(
parameters=[ # pyre-fixme[6]: expected union that should include
{
"name": "x",
"type": "choice",
"values": [1, 2, 3]
},
{
"name": "y",
"type": "choice",
"values": [1, 2, 3]
},
])
self.assertEqual(
[s.model for s in not_none(ax_client.generation_strategy)._steps],
[Models.SOBOL],
)
self.assertEqual(ax_client.get_max_parallelism(), [(-1, -1)])
self.assertTrue(ax_client.get_trials_data_frame().empty)
