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v0.1.17; update 7-9

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wty-yy
2025-12-27 16:13:18 +00:00
parent f92f34ac14
commit baf11a6cd4
12 changed files with 405 additions and 114 deletions
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41
robogauge/tasks/pipeline/multi_pipeline.py
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@@ -91,25 +91,38 @@ class MultiPipeline:
multi_logger.info(f"🔢 Seeds: {self.seeds}, Frictions: {self.frictions}, Base masses: {self.base_masses}")
workers_data = list(product(self.seeds, self.base_masses, self.frictions))
report_progress(self.progress_data, ProgressTypes.INIT, total=len(workers_data), desc="🚀 MultiPipeline Executing")
report_progress(self.progress_data, ProgressTypes.INIT, total=len(workers_data), desc="🚀 MultiPipeline")
ctx = multiprocessing.get_context('spawn')
worker_func = functools.partial(run_single_process, self.args)
results_list = []
with NoDaemonPool(processes=self.num_processes, context=ctx) as pool:
iterator = pool.imap_unordered(worker_func, workers_data)
bar = iterator
def update_results(results):
results_list.append(results)
self.add_static_info('model_path', results['model_path'])
self.add_static_info('terrain_name', results['results']['terrain_name'])
self.add_static_info('terrain_level', results['results']['terrain_level'])
report_progress(self.progress_data, ProgressTypes.UPDATE, value=1)
if results['status'] != 'success':
data = results['data']
multi_logger.error(f"❌ Process with seed={data[0]}, base_mass={data[1]}, friction={data[2]} failed with error: {results['error_msg']}")
if self.num_processes == 1:
multi_logger.info("🚀 Running in Serial Mode")
bar = workers_data
if self.console_output:
bar = tqdm(iterator, total=len(workers_data), desc="Evaluation")
for results in bar:
results_list.append(results)
self.add_static_info('model_path', results['model_path'])
self.add_static_info('terrain_name', results['results']['terrain_name'])
self.add_static_info('terrain_level', results['results']['terrain_level'])
report_progress(self.progress_data, ProgressTypes.UPDATE, value=1)
if results['status'] != 'success':
data = results['data']
multi_logger.error(f"❌ Process with seed={data[0]}, base_mass={data[1]}, friction={data[2]} failed with error: {results['error_msg']}")
bar = tqdm(workers_data, desc="Evaluation")
for data in bar:
results = worker_func(data)
update_results(results)
else:
with NoDaemonPool(processes=self.num_processes, context=ctx) as pool:
iterator = pool.imap_unordered(worker_func, workers_data)
bar = iterator
if self.console_output:
bar = tqdm(iterator, total=len(workers_data), desc="Evaluation")
for results in bar:
update_results(results)
multi_logger.info("✅ Multi-Process Evaluation Completed.")
aggregated_results = self.aggregate_results(results_list)

58
robogauge/tasks/pipeline/stress_pipeline.py
View File

@@ -41,23 +41,22 @@ def run_pipeline(args, progress_queue, data):
args = deepcopy(args)
task_id = data['task_id']
search = data['search_max_level']
task_label = f"[{data['terrain_name']}]"
task_label = f"[{data['terrain_name']}] M:{data['base_mass']} F:{data['friction']}"
progress_data = ProgressData(
task_id=task_id,
msg_prefix=task_label + ' ',
progress_queue=progress_queue
)
if search is True:
task_label += f" M:{data['base_mass']} F:{data['friction']}"
progress_data.msg_prefix = task_label + ' '
args.friction = data['friction']
args.frictions = [data['friction']]
args.base_mass = data['base_mass']
args.base_masses = [data['base_mass']]
args.task_name = f"{data['task_robot_model']}.{data['terrain_name']}"
args.experiment_name = f"{args.experiment_name}_{data['terrain_name']}_M{data['base_mass']}_F{data['friction']}"
args.goals = GOALS['level_pipeline']
args.friction = data['friction']
args.frictions = [data['friction']]
args.base_mass = data['base_mass']
args.base_masses = [data['base_mass']]
args.task_name = f"{data['task_robot_model']}.{data['terrain_name']}"
args.experiment_name = f"{args.experiment_name}_{data['terrain_name']}_M{data['base_mass']}_F{data['friction']}"
if search is True:
args.goals = GOALS['level_pipeline']
level, level_results = LevelPipeline(args, console_output=False, progress_data=progress_data).run()
if level == 0: # no valid level found
report_progress(progress_data, ProgressTypes.FINISH, desc=f"❌ Failed (Lv 0)")
@@ -68,8 +67,8 @@ def run_pipeline(args, progress_queue, data):
'level': 0,
}
return results
report_progress(progress_data, ProgressTypes.RESET, total=0, desc=f"✅ Found Lv {level} -> Running")
progress_data.msg_prefix += f"(Lv {level}) "
else:
level = None # flat terrain
args.task_name = f"{data['task_robot_model']}.{data['terrain_name']}"
@@ -91,13 +90,14 @@ class StressPipeline:
self.args = args
self.seeds = args.seeds
self.task_robot_model = args.task_name.split('.')[0]
self.num_processes = args.stress_num_processes
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)
self.static_info = {}
stress_logger.create(args.experiment_name, args.run_name)
self.args.parent_log_dir = str(stress_logger.log_dir / "subtasks")
self.compress_logs = args.compress_logs
args.compress_logs = False # Disable child log compression
args.num_processes = 1 # Disable child multi-process
def add_static_info(self, key: str, value):
if key not in self.static_info:
@@ -125,16 +125,13 @@ class StressPipeline:
'terrain_name': terrain_name,
'search_max_level': search_max_level,
}
if search_max_level:
for friction, base_mass in product(self.args.frictions, self.args.base_masses):
now_data = deepcopy(data)
now_data.update({
'friction': friction,
'base_mass': base_mass,
})
workers_data.append(now_data)
else:
workers_data.append(data)
for friction, base_mass in product(self.args.frictions, self.args.base_masses):
now_data = deepcopy(data)
now_data.update({
'friction': friction,
'base_mass': base_mass,
})
workers_data.append(now_data)
### Start progress monitor ###
progress_queue, monitor_thread = start_progress_monitor_thread(len(workers_data))
@@ -182,16 +179,14 @@ class StressPipeline:
stress_logger.error("No results to aggregate.")
return
summary = {**self.static_info, 'summary': {}}
summary = {**self.static_info, 'summary': {}, 'final_score': {}}
value_collections = defaultdict(lambda: defaultdict(list))
zero_terrain_count = 0
for result in all_results:
terrain_name = result['data']['terrain_name']
terrain_level = result['level'] # None, 0, 1, ..., 10
key = terrain_name
if terrain_level is not None:
key += f'_{terrain_level}'
key += f'_baseMass{result["data"]["base_mass"]}_friction{result["data"]["friction"]}'
key = f'{terrain_name}_{terrain_level}'
key += f'_baseMass{result["data"]["base_mass"]}_friction{result["data"]["friction"]}'
if terrain_level == 0:
summary[key] = None
zero_terrain_count += 1
@@ -201,14 +196,19 @@ class StressPipeline:
for metric, means in result['results']['summary'].items():
for mean_name, mean_value in means.items():
value = float(mean_value.split(' ')[0])
value += (terrain_level - 1) * 0.1 if terrain_level is not None else 0.0
if terrain_level is not None: # level terrain
value = (terrain_level - 1) * 0.1 + value * 0.1
value_collections[metric][mean_name].append(value)
final_metrics = defaultdict(list)
for metric, means in value_collections.items():
summary['summary'][metric] = {}
for mean_name, values in means.items():
values.extend([0.0] * zero_terrain_count) # include zero terrains
summary['summary'][metric][mean_name] = f"{float(np.mean(values)):.4f} ± {float(np.std(values)):.4f}"
final_metrics[mean_name].append(np.mean(values))
for mean_name, values in final_metrics.items():
summary['final_score'][mean_name] = float(np.mean(values))
save_path = stress_logger.log_dir / "stress_benchmark_results.yaml"
with open(save_path, 'w') as file: