训练新版
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@@ -30,29 +30,31 @@ def _run_replay(args):
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max_available = len(summary_lookup) - args.start_index
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num_to_run = min(args.num_scenarios, max_available)
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env_config = {
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"data_directory": data_path,
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"is_multi_agent": True,
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"num_controlled_agents": 100,
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"horizon": args.horizon,
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"use_render": True,
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"sequential_seed": True,
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"reactive_traffic": False,
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"start_scenario_index": args.start_index,
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"num_scenarios": -1,
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"log_level": 40,
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}
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print(f"Initializing ExpertReplayEnv with data from {data_path}...")
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env = ExpertReplayEnv(config=env_config)
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try:
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for i in range(args.start_index, args.start_index + num_to_run):
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print(f"\n--- Playing Scenario {i} ---")
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# Each scenario uses a fresh env (start_scenario_index=i, num_scenarios=1) so the second
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# scenario and beyond are fully cleaned and loaded like a single-scenario run.
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env_config = {
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"data_directory": data_path,
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"is_multi_agent": True,
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"num_controlled_agents": 100,
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"horizon": args.horizon,
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"use_render": True,
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"sequential_seed": True,
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"reactive_traffic": False,
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"start_scenario_index": i,
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"num_scenarios": 1,
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"log_level": 40,
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}
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env = ExpertReplayEnv(config=env_config)
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try:
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obs = env.reset(seed=i)
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except Exception as e:
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print(f"Error resetting scenario {i}: {e}")
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env.close()
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continue
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print(f"Scenario loaded. Controlled agents (current): {len(env.controlled_agents)}, total in scenario: {env.num_controlled_in_scenario}")
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@@ -67,6 +69,7 @@ def _run_replay(args):
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if dones["__all__"]:
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print(f"Scenario {i} finished at step {step}")
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break
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env.close()
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except KeyboardInterrupt:
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print("Interrupted by user")
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except Exception as e:
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@@ -74,7 +77,6 @@ def _run_replay(args):
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traceback.print_exc()
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print(f"Global error: {e}")
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finally:
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env.close()
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print("Environment closed.")
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