Fix bug for generating dataset (#2)
* update parameters for scripts * update write function * modify waymo script * use exist ok instead of overwrite * remove TODO * rename to comvine_dataset * use exist_ok and force_overwrite together * format * test * creat env for each thread * restore * fix bug * fix pg bug * fix * fix bug * add assert * don't return done info * to dict * add test * only compare sdc * no store mao * release memory * add start index to argumen * test * format some settings/flags * add tmp path * add tmp dir * test all scripts * suppress warning * suppress warning * format * test memory leak * fix memory leak * remove useless functions * imap * thread-1 process for avoiding memory leak * add list() * rename * verify existence * verify completeness * test * add test * add default value * add limit * use script * add anotation * test script * fix bug * fix bug * add author4 * add overwrite * fix bug * fix * combine overwrite * fix bug * gpu007 * add result save dir * adjust sequence * fix test bug * disable bash scri[t * add episode length limit * move scripts to root dir * format * fix test
This commit is contained in:
Quanyi Li
@@ -4,12 +4,14 @@ import os
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import numpy as np
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from scenarionet.common_utils import read_scenario, read_dataset_summary
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from scenarionet.verifier.error import ErrorDescription as ED
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from scenarionet.verifier.error import ErrorFile as EF
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logger = logging.getLogger(__name__)
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import tqdm
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from metadrive.envs.scenario_env import ScenarioEnv
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from metadrive.scenario.scenario_description import ScenarioDescription as SD
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from metadrive.policy.replay_policy import ReplayEgoCarPolicy
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from metadrive.scenario.utils import get_number_of_scenarios
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from functools import partial
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@@ -23,9 +25,16 @@ def set_random_drop(drop):
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RANDOM_DROP = drop
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def verify_loading_into_metadrive(dataset_path, result_save_dir, steps_to_run=1000, num_workers=8):
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def verify_dataset(dataset_path, result_save_dir, overwrite=False, num_workers=8, steps_to_run=1000):
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global RANDOM_DROP
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assert os.path.isdir(result_save_dir), "result_save_dir must be a dir, get {}".format(result_save_dir)
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os.makedirs(result_save_dir, exist_ok=True)
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error_file_name = EF.get_error_file_name(dataset_path)
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if os.path.exists(os.path.join(result_save_dir, error_file_name)) and not overwrite:
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raise FileExistsError(
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"An error_file already exists in result_save_directory. "
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"Setting overwrite=True to cancel this alert"
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)
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num_scenario = get_number_of_scenarios(dataset_path)
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if num_scenario < num_workers:
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# single process
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@@ -34,7 +43,7 @@ def verify_loading_into_metadrive(dataset_path, result_save_dir, steps_to_run=10
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# prepare arguments
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argument_list = []
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func = partial(loading_wrapper, dataset_path=dataset_path, steps_to_run=steps_to_run)
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func = partial(loading_wrapper, dataset_path=dataset_path, steps_to_run=steps_to_run, random_drop=RANDOM_DROP)
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num_scenario_each_worker = int(num_scenario // num_workers)
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for i in range(num_workers):
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@@ -64,53 +73,75 @@ def verify_loading_into_metadrive(dataset_path, result_save_dir, steps_to_run=10
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return success, errors
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def loading_into_metadrive(start_scenario_index, num_scenario, dataset_path, steps_to_run, metadrive_config=None):
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global RANDOM_DROP
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def loading_into_metadrive(
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start_scenario_index, num_scenario, dataset_path, steps_to_run, metadrive_config=None, random_drop=False
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):
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logger.info(
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"================ Begin Scenario Loading Verification for scenario {}-{} ================ \n".format(
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start_scenario_index, num_scenario + start_scenario_index
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)
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)
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success = True
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metadrive_config = metadrive_config or {}
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metadrive_config.update(
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{
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"agent_policy": ReplayEgoCarPolicy,
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"num_scenarios": num_scenario,
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"horizon": 1000,
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"start_scenario_index": start_scenario_index,
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"no_static_vehicles": False,
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"data_directory": dataset_path,
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}
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)
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env = ScenarioEnv(metadrive_config)
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logging.disable(logging.INFO)
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error_msgs = []
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desc = "Scenarios: {}-{}".format(start_scenario_index, start_scenario_index + num_scenario)
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for scenario_index in tqdm.tqdm(range(start_scenario_index, start_scenario_index + num_scenario), desc=desc):
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try:
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env.reset(force_seed=scenario_index)
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arrive = False
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if RANDOM_DROP and np.random.rand() < 0.5:
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raise ValueError("Random Drop")
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for _ in range(steps_to_run):
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o, r, d, info = env.step([0, 0])
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if d and info["arrive_dest"]:
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arrive = True
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assert arrive, "Can not arrive destination"
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except Exception as e:
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file_name = env.engine.data_manager.summary_lookup[scenario_index]
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file_path = os.path.join(dataset_path, env.engine.data_manager.mapping[file_name], file_name)
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error_msg = ED.make(scenario_index, file_path, file_name, str(e))
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error_msgs.append(error_msg)
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success = False
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# proceed to next scenario
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continue
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env.close()
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if steps_to_run == 0:
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summary, scenarios, mapping = read_dataset_summary(dataset_path)
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index_count = -1
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for file_name in tqdm.tqdm(scenarios):
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index_count += 1
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try:
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scenario = read_scenario(dataset_path, mapping, file_name)
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SD.sanity_check(scenario)
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if random_drop and np.random.rand() < 0.5:
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raise ValueError("Random Drop")
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except Exception as e:
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file_path = os.path.join(dataset_path, mapping[file_name], file_name)
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error_msg = ED.make(index_count, file_path, file_name, str(e))
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error_msgs.append(error_msg)
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success = False
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# proceed to next scenario
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continue
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else:
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metadrive_config = metadrive_config or {}
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metadrive_config.update(
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{
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"agent_policy": ReplayEgoCarPolicy,
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"num_scenarios": num_scenario,
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"horizon": 1000,
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"start_scenario_index": start_scenario_index,
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"no_static_vehicles": False,
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"data_directory": dataset_path,
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}
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)
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env = ScenarioEnv(metadrive_config)
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logging.disable(logging.INFO)
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desc = "Scenarios: {}-{}".format(start_scenario_index, start_scenario_index + num_scenario)
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for scenario_index in tqdm.tqdm(range(start_scenario_index, start_scenario_index + num_scenario), desc=desc):
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try:
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env.reset(force_seed=scenario_index)
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arrive = False
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if random_drop and np.random.rand() < 0.5:
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raise ValueError("Random Drop")
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for _ in range(steps_to_run):
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o, r, d, info = env.step([0, 0])
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if d and info["arrive_dest"]:
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arrive = True
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assert arrive, "Can not arrive destination"
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except Exception as e:
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file_name = env.engine.data_manager.summary_lookup[scenario_index]
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file_path = os.path.join(dataset_path, env.engine.data_manager.mapping[file_name], file_name)
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error_msg = ED.make(scenario_index, file_path, file_name, str(e))
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error_msgs.append(error_msg)
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success = False
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# proceed to next scenario
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continue
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env.close()
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return success, error_msgs
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def loading_wrapper(arglist, dataset_path, steps_to_run):
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def loading_wrapper(arglist, dataset_path, steps_to_run, random_drop):
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assert len(arglist) == 2, "Too much arguments!"
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return loading_into_metadrive(arglist[0], arglist[1], dataset_path=dataset_path, steps_to_run=steps_to_run)
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return loading_into_metadrive(
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arglist[0], arglist[1], dataset_path=dataset_path, steps_to_run=steps_to_run, random_drop=random_drop
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)
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