def test_getitem(self):
s = {"a": quantized_uniform(1, 2, 1)}
grid = ParameterGrid(Space(s))
r = grid[0]
self.assertAlmostEqual(r[0], 0.0)
r = grid[-1]
self.assertAlmostEqual(r[0], 0.0)
s = {"a": quantized_uniform(1, 5, 1),
"b": quantized_log(1, 5, 1, 10)}
grid = ParameterGrid(Space(s))
r = grid[0]
self.assertAlmostEqual(r[0], 0.0)
self.assertAlmostEqual(r[1], 0.0)
r = grid[1]
self.assertAlmostEqual(r[0], 0.25)
self.assertAlmostEqual(r[1], 0.0)
s = {"a": quantized_uniform(1, 5, 1),
"b": {"c": quantized_log(1, 5, 1, 10),
"d": quantized_uniform(0, 10, 1)}}
grid = ParameterGrid(Space(s))
r = grid[0]
self.assertEqual(len(r), 4)
self.assertAlmostEqual(r[0], 0.0)
self.assertAlmostEqual(r[1], 0.0)
self.assertAlmostEqual(r[2], 0.0)
self.assertAlmostEqual(r[3], None)
r = grid[1]
self.assertEqual(len(r), 4)
self.assertAlmostEqual(r[0], 0.25)
self.assertAlmostEqual(r[1], 0.0)
self.assertAlmostEqual(r[2], 0.0)
self.assertAlmostEqual(r[3], None)
r = grid[16]
self.assertEqual(len(r), 4)
self.assertAlmostEqual(r[0], 0.0)
self.assertAlmostEqual(r[1], 0.5)
self.assertAlmostEqual(r[2], None)
self.assertAlmostEqual(r[3], 0.0)
r = grid[20]
self.assertEqual(len(r), 4)
self.assertAlmostEqual(r[0], 0.0)
self.assertAlmostEqual(r[1], 0.5)
self.assertAlmostEqual(r[2], None)
self.assertAlmostEqual(r[3], 0.1)
r = grid[-1]
self.assertEqual(len(r), 4)
self.assertAlmostEqual(r[0], 0.75)
self.assertAlmostEqual(r[1], 0.5)
self.assertAlmostEqual(r[2], None)
self.assertAlmostEqual(r[3], 0.9)
def setUp(self):
self.qa = quantized_uniform(0, 3, 1)
self.qb = quantized_uniform(1, 4, 1)
s = {"a": self.qa, "b": self.qb}
self.mock_conn = MagicMock(name="connection")
self.mock_conn.get_space.return_value = Space(s)
self.space = Space(s)
self.search = Random(self.mock_conn, s)
def setUp(self):
s = {"a": uniform(1, 10), "b": uniform(5, 15)}
self.mock_conn = MagicMock(name="connection")
self.mock_conn.get_space.return_value = Space(s)
self.search = CMAES(self.mock_conn, s)
def setUp(self):
self.space = {"a": uniform(1, 10), "b": uniform(5, 15)}
self.mock_conn = MagicMock(name="connection")
self.mock_conn.get_space.return_value = Space(self.space)
self.search = QuasiRandom(self.mock_conn, self.space)
def setUp(self):
s = {"a": quantized_uniform(1, 10, 1)}
self.mock_conn = MagicMock(name="connection")
self.mock_conn.get_space.return_value = Space(s)
self.grid = Grid(self.mock_conn, s)
def test_all_results(self):
mock_conn = MagicMock(name="connection")
space = Space({"a": uniform(1, 2)})
repeat_col_name = "rep"
data = [{
"a": 0,
"_chocolate_id": 0,
repeat_col_name: 0,
"_loss": 0.3
}, {
"a": 0,
"_chocolate_id": 0,
repeat_col_name: 1,
"_loss": 0.3
}, {
"a": 0,
"_chocolate_id": 0,
repeat_col_name: 2,
"_loss": 0.4
}, {
"a": 0.6,
"_chocolate_id": 1,
repeat_col_name: 0,
"_loss": 0.3
}, {
"a": 0.6,
"_chocolate_id": 1,
repeat_col_name: 1,
"_loss": 0.4
}, {
"a": 0.6,
"_chocolate_id": 1,
repeat_col_name: 2,
"_loss": 0.5
}]
mock_conn.all_results.return_value = data
mock_conn.count_results = len(data)
mock_conn.pop_id = lambda x: x
cv = Repeat(3, rep_col=repeat_col_name)
cv.wrap_connection(mock_conn)
cv.space = space
self.assertEqual(cv.count_results(), 2)
results = cv.all_results()
for entry in results:
if entry["_chocolate_id"] == 0:
self.assertAlmostEqual(entry["_loss"], 1 / 3)
elif entry["_chocolate_id"] == 1:
self.assertAlmostEqual(entry["_loss"], 0.4)
def test_len(self):
s = {"a": quantized_uniform(1, 2, 1)}
grid = ParameterGrid(Space(s))
self.assertEqual(len(grid), 1)
s = {"a": quantized_uniform(1, 5, 1),
"b": quantized_log(1, 5, 1, 10)}
grid = ParameterGrid(Space(s))
self.assertEqual(len(grid), 16)
s = {"a": quantized_uniform(1, 5, 1),
"b": {"c": quantized_log(1, 5, 1, 10),
"d": quantized_uniform(0, 1, 1)}}
grid = ParameterGrid(Space(s))
self.assertEqual(len(grid), 20)
s = {"a": quantized_uniform(1, 5, 1),
"b": {"c": quantized_log(1, 5, 1, 10),
"d": quantized_uniform(0, 10, 1)}}
grid = ParameterGrid(Space(s))
self.assertEqual(len(grid), 56)
def test_next_new(self):
mock_conn = MagicMock(name="connection")
space = Space({"a": uniform(1, 2)})
repeat_col_name = "rep"
data = [{
"a": 0,
"_chocolate_id": 0,
repeat_col_name: 0,
"_loss": 0.3
}, {
"a": 0,
"_chocolate_id": 0,
repeat_col_name: 1,
"_loss": 0.3
}, {
"a": 0,
"_chocolate_id": 0,
repeat_col_name: 2,
"_loss": 0.4
}, {
"a": 0.6,
"_chocolate_id": 1,
repeat_col_name: 0,
"_loss": 0.3
}, {
"a": 0.6,
"_chocolate_id": 1,
repeat_col_name: 1,
"_loss": 0.4
}, {
"a": 0.6,
"_chocolate_id": 1,
repeat_col_name: 2,
"_loss": 0.5
}]
mock_conn.all_results.return_value = data
mock_conn.count_results = len(data)
mock_conn.pop_id = lambda x: x
mock_conn.get_space.return_value = space
cv = Repeat(3, rep_col=repeat_col_name)
s = Random(mock_conn, space, cv)
token, params = s.next()
self.assertEqual(token["_chocolate_id"], 2)
def setUp(self):
self.repeat_col_name = "rep"
self.mock_conn = MagicMock(name="connection")
self.space = Space({"a": uniform(1, 2)})
self.data = [{
"a": 0,
"_chocolate_id": 0,
"_arm_id": 0,
self.repeat_col_name: 0,
"_loss": 0.3
}, {
"a": 0,
"_chocolate_id": 0,
"_arm_id": 0,
self.repeat_col_name: 1,
"_loss": 0.3
}, {
"a": 0,
"_chocolate_id": 0,
"_arm_id": 0,
self.repeat_col_name: 2,
"_loss": 0.4
}, {
"a": 0.6,
"_chocolate_id": 1,
"_arm_id": 0,
self.repeat_col_name: 0,
"_loss": 0.4
}, {
"a": 0.6,
"_chocolate_id": 1,
"_arm_id": 0,
self.repeat_col_name: 1,
"_loss": 0.5
}]
self.mock_conn.all_results.return_value = self.data
self.mock_conn.count_results = len(self.data)
self.mock_conn.pop_id = lambda x: x
self.mock_conn.get_space.return_value = self.space
def test_conditional_n_steps(self):
s = [{
"a": uniform(1, 10),
"b": uniform(5, 15),
"C": 0
}, {
"c": uniform(2, 3),
"C": 1
}]
db = list()
comp = list()
self.mock_conn = MagicMock(name="connection")
self.mock_conn.get_space.return_value = Space(s)
self.mock_conn.all_results.return_value = db
self.mock_conn.count_results.return_value = len(db)
self.mock_conn.all_complementary.return_value = comp
self.search = MOCMAES(self.mock_conn, s, mu=2)
for i in range(25):
token, p = self.search.next()
self.assertIn("_chocolate_id", token)
self.assertEqual(token["_chocolate_id"], i)
entry = self.mock_conn.insert_result.call_args[0][0]
entry["_loss_0"] = numpy.random.randn()
entry["_loss_1"] = numpy.random.randn()
db.append(entry)
self.mock_conn.count_results.return_value = len(db)
self.mock_conn.insert_result.reset_mock()
if self.mock_conn.insert_complementary.call_count > 0:
c = self.mock_conn.insert_complementary.call_args[0][0]
comp.append(c)
self.mock_conn.insert_complementary.reset_mock()
def test_invalid_getitem(self):
s = {"a": quantized_uniform(1, 2, 1)}
grid = ParameterGrid(Space(s))
self.assertRaises(IndexError, grid.__getitem__, 1)
self.assertRaises(IndexError, grid.__getitem__, -2)
def test_init_continuous(self):
s = {"a": uniform(1, 2)}
self.assertRaises(AssertionError, ParameterGrid, Space(s))
def test_empty_subspace(self):
grid = ParameterGrid(Space({"a": {"b": None}}))
self.assertRaises(IndexError, grid.__getitem__, 0)
def test_empty_grid(self):
grid = ParameterGrid(Space(dict()))
self.assertRaises(IndexError, grid.__getitem__, 0)