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v1.0.0 prev; add serve, client, search_seeds

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wty-yy
2025-12-29 21:29:03 +08:00
parent feb9ddf907
commit c28bb64b0a
11 changed files with 319 additions and 27 deletions
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10
robogauge/tasks/pipeline/stress_pipeline.py
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@@ -90,7 +90,6 @@ def run_pipeline(args, progress_queue, data):
class StressPipeline:
def __init__(self, args):
self.args = args
self.seeds = args.seeds
self.task_robot_model = args.task_name.split('.')[0]
self.num_processes = args.num_processes
args.experiment_name = self.task_robot_model + '_stress' + ('' if args.cli_experiment_name is None else '_' + args.cli_experiment_name)
@@ -109,7 +108,7 @@ class StressPipeline:
def run(self):
stress_logger.info(f"🚀 Starting Stress Benchmark for '{self.args.experiment_name}'.")
stress_logger.info(f"🔢 Seeds: {self.seeds}")
stress_logger.info(f"🔢 Seeds: {self.args.seeds}, Level Search Seeds: {self.args.search_seeds}")
terrain_names = self.args.stress_terrain_names
stress_logger.info(f"🌄 Stress Test Terrain Names: {terrain_names}")
@@ -161,7 +160,7 @@ class StressPipeline:
stress_logger.info("📊 Aggregating Stress Benchmark Results...")
finish_msg = (
f"""\n{'='*20} Stress Benchmark Summary {'='*20}\n"""
f"""{'Seeds':^20}{str(self.seeds)}\n"""
f"""{'Seeds':^20}{str(self.args.seeds):^15}{'Level Search Seeds':^20}{str(self.args.search_seeds):^15}\n"""
f"""{'Terrain Name':^20}{'Base Mass':^15}{'Friction':^15}{'Max Level':^15}\n"""
)
all_results = sorted(all_results, key=lambda x: (x['data']['terrain_name'], x['data'].get('base_mass', 0), x['data'].get('friction', 0)))
@@ -178,7 +177,7 @@ class StressPipeline:
stress_logger.error("No results to aggregate.")
return
summary = {**self.static_info, 'summary': {}, 'robust_score': {}, 'benchmark_score': 0.0}
summary = {**self.static_info, 'summary': {}, 'robust_score': {}, 'benchmark_score': 0.0, 'scores': {}}
metric_collections = defaultdict(lambda: defaultdict(list))
terrain_collections = defaultdict(lambda: defaultdict(list))
zero_terrain_count = defaultdict(lambda: 0)
@@ -209,14 +208,17 @@ class StressPipeline:
robust_score = defaultdict(dict)
robust_scores = []
scores = summary['scores']
for terrain_name, means in terrain_collections.items():
for mean_name, values in means.items():
values.extend([0.0] * zero_terrain_count[terrain_name]) # include zero terrains
robust_score[terrain_name][mean_name] = float(np.mean(values))
scores[terrain_name] = robust_score[terrain_name]['mean@50']
if terrain_name != 'stairs_down': # skip stairs_down for benchmark score calculation
robust_scores.append(robust_score[terrain_name]['mean@50'])
summary['robust_score'] = dict(robust_score)
summary['benchmark_score'] = float(np.mean(robust_scores))
scores['benchmark'] = summary['benchmark_score']
save_path = stress_logger.log_dir / "stress_benchmark_results.yaml"
with open(save_path, 'w') as file: