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v0.1.16; Almost finish StressPipeline

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wty-yy
2025-12-26 23:51:43 +08:00
parent 65490fe591
commit dad65a4e27
11 changed files with 125 additions and 48 deletions
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23
robogauge/tasks/pipeline/multi_pipeline.py
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@@ -22,6 +22,7 @@ from robogauge.tasks.pipeline.base_pipeline import BasePipeline
from robogauge.utils.task_register import task_register
from robogauge.utils.logger import Logger
from robogauge.utils.process_utils import NoDaemonPool
multi_logger = Logger() # MultiPipeline logger
@@ -62,14 +63,14 @@ def run_single_process(args, data):
return ret
class MultiPipeline:
def __init__(self, args):
def __init__(self, args, console_output: bool = True):
self.args = args
self.seeds = args.seeds
self.frictions = args.frictions
self.base_masses = args.base_masses
self.num_processes = args.num_processes
self.static_info = {}
multi_logger.create(args.experiment_name+'_multi', args.run_name+'_multi')
multi_logger.create(args.experiment_name+'_multi', args.run_name+'_multi', console_output=console_output)
def add_static_info(self, key: str, value):
if key not in self.static_info:
@@ -85,7 +86,7 @@ class MultiPipeline:
ctx = multiprocessing.get_context('spawn')
worker_func = functools.partial(run_single_process, self.args)
results_list = []
with ctx.Pool(processes=self.num_processes) as pool:
with NoDaemonPool(processes=self.num_processes, context=ctx) as pool:
iterator = pool.imap_unordered(worker_func, workers_data)
for results in tqdm(iterator, total=len(workers_data), desc="Evaluation"):
results_list.append(results)
@@ -104,7 +105,7 @@ class MultiPipeline:
""" Process results from all processes and aggregate them. """
multi_logger.info("📊 Aggregating Results from all runs...")
summary = {'success': {}, **self.static_info}
summary = {'success': {}, **self.static_info, 'summary': {}}
finish_msg = (
f"""\n{'='*20} Run Finish Summary {'='*20}\n"""
f"""{'Seed':^10}{'Base Mass':^15}{'Friction':^15}{'Status':^10}\n"""
@@ -133,9 +134,9 @@ class MultiPipeline:
value_collections[metric][mean_name].append(float(mean_value.split(' ')[0]))
for metric, means in value_collections.items():
summary[metric] = {}
summary['summary'][metric] = {}
for mean_name, values in means.items():
summary[metric][mean_name] = f"{float(np.mean(values)):.4f} ± {float(np.std(values)):.4f}"
summary['summary'][metric][mean_name] = f"{float(np.mean(values)):.4f} ± {float(np.std(values)):.4f}"
save_path = multi_logger.log_dir / "aggregated_results.yaml"
with open(save_path, 'w') as file:
@@ -143,9 +144,9 @@ class MultiPipeline:
multi_logger.info("✅ Aggregated execution finished.")
multi_logger.info(f"📁 Aggregated results saved to: {save_path}")
multi_logger.info(
f"""\n{'='*20} Multi-Run Summary {'='*20}\n"""
f"""{yaml.dump(summary, allow_unicode=True)}"""
f"""{'='*60}"""
)
# multi_logger.info(
# f"""\n{'='*20} Multi-Run Summary {'='*20}\n"""
# f"""{yaml.dump(summary, allow_unicode=True)}"""
# f"""{'='*60}"""
# )
return summary