"...playground/git@developer.sourcefind.cn:zhaoyu6/sglang.git" did not exist on "30af7dfb3426065f97ea6a217a721d84f0bb2b56"
Unverified Commit dbfe34f2 authored by Stas Bekman's avatar Stas Bekman Committed by GitHub
Browse files

[test schedulers] adjust to test the first step's reading (#6429)

* [test schedulers] small improvement

* cleanup
parent e6b811f0
......@@ -40,16 +40,16 @@ if is_torch_available():
def unwrap_schedule(scheduler, num_steps=10):
lrs = []
for _ in range(num_steps):
lrs.append(scheduler.get_lr()[0])
scheduler.step()
lrs.append(scheduler.get_lr())
return lrs
def unwrap_and_save_reload_schedule(scheduler, num_steps=10):
lrs = []
for step in range(num_steps):
lrs.append(scheduler.get_lr()[0])
scheduler.step()
lrs.append(scheduler.get_lr())
if step == num_steps // 2:
with tempfile.TemporaryDirectory() as tmpdirname:
file_name = os.path.join(tmpdirname, "schedule.bin")
......@@ -127,23 +127,23 @@ class ScheduleInitTest(unittest.TestCase):
get_constant_schedule: ({}, [10.0] * self.num_steps),
get_constant_schedule_with_warmup: (
{"num_warmup_steps": 4},
[2.5, 5.0, 7.5, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0],
[0.0, 2.5, 5.0, 7.5, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0],
),
get_linear_schedule_with_warmup: (
{**common_kwargs},
[5.0, 10.0, 8.75, 7.5, 6.25, 5.0, 3.75, 2.5, 1.25, 0.0],
[0.0, 5.0, 10.0, 8.75, 7.5, 6.25, 5.0, 3.75, 2.5, 1.25],
),
get_cosine_schedule_with_warmup: (
{**common_kwargs},
[5.0, 10.0, 9.61, 8.53, 6.91, 5.0, 3.08, 1.46, 0.38, 0.0],
[0.0, 5.0, 10.0, 9.61, 8.53, 6.91, 5.0, 3.08, 1.46, 0.38],
),
get_cosine_with_hard_restarts_schedule_with_warmup: (
{**common_kwargs, "num_cycles": 2},
[5.0, 10.0, 8.53, 5.0, 1.46, 10.0, 8.53, 5.0, 1.46, 0.0],
[0.0, 5.0, 10.0, 8.53, 5.0, 1.46, 10.0, 8.53, 5.0, 1.46],
),
get_polynomial_decay_schedule_with_warmup: (
{**common_kwargs, "power": 2.0, "lr_end": 1e-7},
[5.0, 10.0, 7.656, 5.625, 3.906, 2.5, 1.406, 0.625, 0.156, 1e-07],
[0.0, 5.0, 10.0, 7.656, 5.625, 3.906, 2.5, 1.406, 0.625, 0.156],
),
}
......@@ -151,17 +151,12 @@ class ScheduleInitTest(unittest.TestCase):
kwargs, expected_learning_rates = data
scheduler = scheduler_func(self.optimizer, **kwargs)
self.assertEqual(len([scheduler.get_lr()[0]]), 1)
lrs_1 = unwrap_schedule(scheduler, self.num_steps)
self.assertEqual(len(lrs_1[0]), 1)
self.assertListAlmostEqual(
[l[0] for l in lrs_1],
expected_learning_rates,
tol=1e-2,
msg=f"failed for {scheduler_func} in normal scheduler",
lrs_1, expected_learning_rates, tol=1e-2, msg=f"failed for {scheduler_func} in normal scheduler",
)
scheduler = scheduler_func(self.optimizer, **kwargs)
lrs_2 = unwrap_and_save_reload_schedule(scheduler, self.num_steps)
self.assertListEqual(
[l[0] for l in lrs_1], [l[0] for l in lrs_2], msg=f"failed for {scheduler_func} in save and reload"
)
self.assertListEqual(lrs_1, lrs_2, msg=f"failed for {scheduler_func} in save and reload")
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment