yujunjun/autogen
1
0
Fork 0
mirror of https://github.com/microsoft/autogen.git synced 2025-09-09 16:26:20 +00:00
Code Issues Packages Projects Releases Wiki Activity

Info and naming (#864)

Browse Source 
* remove __class__

* var name
This commit is contained in:
Chi Wang 2022-12-25 11:43:22 -08:00 committed by GitHub
parent da2cd7ca89
commit b78d0b57c4
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 18 additions and 19 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

37
flaml/tune/tune.py
View File

@ -492,9 +492,7 @@ def run(
SearchAlgorithm = BlendSearch
logger.info(
"Using search algorithm {}.".format(
SearchAlgorithm.__class__.__name__
)
"Using search algorithm {}.".format(SearchAlgorithm.__name__)
)
except ImportError:
SearchAlgorithm = CFO
@ -504,9 +502,7 @@ def run(
metric = metric or DEFAULT_METRIC
else:
SearchAlgorithm = CFO
logger.info(
"Using search algorithm {}.".format(SearchAlgorithm.__class__.__name__)
)
logger.info("Using search algorithm {}.".format(SearchAlgorithm.__name__))
metric = lexico_objectives["metrics"][0] or DEFAULT_METRIC
search_alg = SearchAlgorithm(
metric=metric,
@ -675,14 +671,14 @@ def run(
num_trials = 0
if time_budget_s is None:
time_budget_s = np.inf
fail = 0
ub = (
num_failures = 0
upperbound_num_failures = (
len(evaluated_rewards) if evaluated_rewards else 0
) + max_failure
while (
time.time() - time_start < time_budget_s
and (num_samples < 0 or num_trials < num_samples)
and fail < ub
and num_failures < upperbound_num_failures
):
while len(_runner.running_trials) < n_concurrent_trials:
# suggest trials for spark
@ -690,9 +686,9 @@ def run(
if trial_next:
num_trials += 1
else:
fail += 1 # break with ub consecutive failures
logger.debug(f"consecutive failures is {fail}")
if fail >= ub:
num_failures += 1 # break with upperbound_num_failures consecutive failures
logger.debug(f"consecutive failures is {num_failures}")
if num_failures >= upperbound_num_failures:
break
trials_to_run = _runner.running_trials
if not trials_to_run:
@ -730,7 +726,7 @@ def run(
)
report(_metric=result)
_runner.stop_trial(trial_to_run)
fail = 0
num_failures = 0
analysis = ExperimentAnalysis(
_runner.get_trials(),
metric=metric,
@ -766,12 +762,14 @@ def run(
num_trials = 0
if time_budget_s is None:
time_budget_s = np.inf
fail = 0
ub = (len(evaluated_rewards) if evaluated_rewards else 0) + max_failure
num_failures = 0
upperbound_num_failures = (
len(evaluated_rewards) if evaluated_rewards else 0
) + max_failure
while (
time.time() - time_start < time_budget_s
and (num_samples < 0 or num_trials < num_samples)
and fail < ub
and num_failures < upperbound_num_failures
):
trial_to_run = _runner.step()
if trial_to_run:
@ -789,10 +787,11 @@ def run(
else:
report(_metric=result)
_runner.stop_trial(trial_to_run)
fail = 0
num_failures = 0
else:
fail += 1 # break with ub consecutive failures
if fail == ub:
# break with upperbound_num_failures consecutive failures
num_failures += 1
if num_failures == upperbound_num_failures:
logger.warning(
f"fail to sample a trial for {max_failure} times in a row, stopping."
)