def test_attach_trial_and_get_trial_parameters(self):
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,
)
params, idx = ax_client.attach_trial(parameters={"x": 0.0, "y": 1.0})
ax_client.complete_trial(trial_index=idx, raw_data=5)
self.assertEqual(ax_client.get_best_parameters()[0], params)
self.assertEqual(ax_client.get_trial_parameters(trial_index=idx), {
"x": 0,
"y": 1
})
with self.assertRaises(ValueError):
ax_client.get_trial_parameters(
trial_index=10) # No trial #10 in experiment.
with self.assertRaisesRegex(ValueError, ".* is of type"):
ax_client.attach_trial({"x": 1, "y": 2})
def test_attach_trial_ttl_seconds(self):
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,
)
params, idx = ax_client.attach_trial(
parameters={"x": 0.0, "y": 1.0}, ttl_seconds=1
)
self.assertTrue(ax_client.experiment.trials.get(idx).status.is_running)
time.sleep(1) # Wait for TTL to elapse.
self.assertTrue(ax_client.experiment.trials.get(idx).status.is_failed)
# Also make sure we can no longer complete the trial as it is failed.
with self.assertRaisesRegex(
ValueError, ".* has been marked FAILED, so it no longer expects data."
):
ax_client.complete_trial(trial_index=idx, raw_data=5)
params2, idx2 = ax_client.attach_trial(
parameters={"x": 0.0, "y": 1.0}, ttl_seconds=1
)
ax_client.complete_trial(trial_index=idx2, raw_data=5)
self.assertEqual(ax_client.get_best_parameters()[0], params2)
self.assertEqual(
ax_client.get_trial_parameters(trial_index=idx2), {"x": 0, "y": 1}
)
import pickle
run_mode = "frozen_convolution_no_center_relu"
with open(f"hyperparameters_{run_mode}.pl", "rb") as handle:
hyper = pickle.load(handle)
from ax import RangeParameter, ParameterType
from ax.service.ax_client import AxClient
from ax.plot.contour import plot_contour
from ax.plot.trace import optimization_trace_single_method
from ax.service.managed_loop import optimize
from ax.utils.notebook.plotting import render, init_notebook_plotting
from ax.utils.tutorials.cnn_utils import load_mnist, train, evaluate
# Initialize client
ax = AxClient()
ax = ax.from_json_snapshot(hyper["axclient"])
print(ax.get_trial_parameters(10))
