129 lines
6.1 KiB
Python
129 lines
6.1 KiB
Python
import os
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import traceback
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from .orm import Baseline, Battle, Model
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from ..evaluation.simulation import evaluate
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from ..evaluation.deep_agent import DeepAgent
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from datetime import datetime
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positions = ['landlord', 'landlord_up', 'landlord_front', 'landlord_down']
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idx_position = {0: 'landlord', 1: 'landlord_down', 2: 'landlord_front', 3:'landlord_up'}
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position_idx = {'landlord': 0, 'landlord_down': 1, 'landlord_front': 2, 'landlord_up': 3}
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baselines = Baseline.select().order_by(Baseline.rank.desc()).limit(1)
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baseline_players = [None, None, None, None]
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if len(baselines) >= 1:
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baseline = baselines[0]
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try:
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baseline_players[0] = DeepAgent('landlord', str(baseline.landlord_path), use_onnx=True)
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baseline_players[1] = DeepAgent('landlord_down', str(baseline.landlord_down_path), use_onnx=True)
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baseline_players[2] = DeepAgent('landlord_front', str(baseline.landlord_front_path), use_onnx=True)
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baseline_players[3] = DeepAgent('landlord_up', str(baseline.landlord_up_path), use_onnx=True)
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except:
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pass
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def battle_logic(baseline : Baseline, battle : Battle):
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eval_data_first = 'eval_data_200.pkl'
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eval_data_second = 'eval_data_800.pkl'
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challenger_baseline = {
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'landlord_path': str(baseline.landlord_path),
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'landlord_up_path': str(baseline.landlord_up_path),
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'landlord_front_path': str(baseline.landlord_front_path),
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'landlord_down_path': str(baseline.landlord_down_path),
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}
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if not os.path.exists(str(battle.challenger_path)):
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battle.status = -2
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battle.save()
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return
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challenger_baseline[battle.challenger_position + "_path"] = str(battle.challenger_path)
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print(str(battle.challenger_path))
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landlord_wp, farmer_wp, landlord_adp, farmer_adp = \
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evaluate(challenger_baseline['landlord_path'],
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challenger_baseline['landlord_up_path'],
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challenger_baseline['landlord_front_path'],
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challenger_baseline['landlord_down_path'],
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eval_data_first,
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3,
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False,
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'New')
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def _second_eval(landlord_wp, farmer_wp, landlord_adp, farmer_adp):
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landlord_wp_2, farmer_wp_2, landlord_adp_2, farmer_adp_2 = \
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evaluate(challenger_baseline['landlord_path'],
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challenger_baseline['landlord_up_path'],
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challenger_baseline['landlord_front_path'],
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challenger_baseline['landlord_down_path'],
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eval_data_second,
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3,
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False,
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'New')
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return (landlord_wp + landlord_wp_2 * 4.0) / 5, \
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(farmer_wp + farmer_wp_2 * 4.0) / 5, \
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(landlord_adp + landlord_adp_2 * 4.0) / 5, \
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(farmer_adp + farmer_adp_2 * 4.0) / 5
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challenge_success = False
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if battle.challenger_position == 'landlord':
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if baseline.landlord_wp == 0 or landlord_wp / float(baseline.landlord_wp) > 1.15:
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landlord_wp, farmer_wp, landlord_adp, farmer_adp = \
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_second_eval(landlord_wp, farmer_wp, landlord_adp, farmer_adp)
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if baseline.landlord_wp == 0 or landlord_wp / float(baseline.landlord_wp) > 1.15:
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challenge_success = True
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else:
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if baseline.farmer_wp == 0 or farmer_wp / float(baseline.farmer_wp) > 1.05:
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landlord_wp, farmer_wp, landlord_adp, farmer_adp = \
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_second_eval(landlord_wp, farmer_wp, landlord_adp, farmer_adp)
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if baseline.farmer_wp == 0 or farmer_wp / float(baseline.farmer_wp) > 1.05:
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challenge_success = True
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if challenge_success:
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challenger_baseline['rank'] = baseline.rank + 1
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challenger_baseline['landlord_wp'] = landlord_wp
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challenger_baseline['landlord_adp'] = landlord_adp
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challenger_baseline['farmer_wp'] = farmer_wp
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challenger_baseline['farmer_adp'] = farmer_adp
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challenger_baseline['create_time'] = datetime.now()
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Baseline.create(**challenger_baseline)
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battle.challenger_wp = landlord_wp if battle.challenger_position == 'landlord' else farmer_wp
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battle.challenger_adp = landlord_adp if battle.challenger_position == 'landlord' else farmer_adp
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battle.status = 1 if challenge_success else 2
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battle.save()
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if not challenge_success:
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onnx_path = str(battle.challenger_path) + '.onnx'
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if os.path.exists(onnx_path):
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os.remove(onnx_path)
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os.remove(str(battle.challenger_path))
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else:
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baseline_players[position_idx[battle.challenger_position]] = DeepAgent(battle.challenger_position, str(battle.challenger_path), use_onnx=True)
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def tick():
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try:
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battles = Battle.select().where(Battle.status == 0).order_by(Battle.id.asc()).limit(1)
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for battle in battles:
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battle.status = -1
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battle.save()
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baselines = Baseline.select().order_by(Baseline.rank.desc()).limit(1)
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if len(baselines) == 0:
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baseline = {}
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for position in positions:
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models = Model.select().where(Model.position == position).order_by(Model.create_time.desc()).limit(1)
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if(len(models) > 0):
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baseline['%s_path' % position] = models[0].path
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baseline_players[position_idx[position]] = DeepAgent(position, str(models[0].path), use_onnx=True)
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if len(baseline.keys()) == 4:
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baseline['rank'] = 0
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baseline['landlord_wp'] = 0
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baseline['farmer_wp'] = 0
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baseline['landlord_adp'] = 0
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baseline['farmer_adp'] = 0
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baseline['create_time'] = datetime.now()
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Baseline.create(**baseline)
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baselines = Baseline.select().order_by(Baseline.rank.desc()).limit(1)
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battle_logic(baselines[0], battle)
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else:
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battle.status = -3
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battle.save()
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else:
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battle_logic(baselines[0], battle)
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except:
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traceback.print_exc()
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