127 lines
4.4 KiB
Python
127 lines
4.4 KiB
Python
import os
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import argparse
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from pickle import FALSE
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import csv
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from douzero.evaluation.simulation import evaluate
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def make_evaluate(args, vs_config):
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landlord_config = vs_config['landlord']
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farmer_config = vs_config['farmer']
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if landlord_config['prefix'] == 'random':
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args.landlord = 'random'
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else:
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args.landlord = '%s/%s_landlord_%i.ckpt' % (
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landlord_config['folder'], landlord_config['prefix'], landlord_config['frame']
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)
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if farmer_config['prefix'] == 'random':
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args.landlord_up = 'random'
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args.landlord_front = 'random'
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args.landlord_down = 'random'
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else:
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args.landlord_up = '%s/%s_landlord_up_%i.ckpt' % (
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farmer_config['folder'], farmer_config['prefix'], farmer_config['frame']
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)
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args.landlord_front = '%s/%s_landlord_front_%i.ckpt' % (
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farmer_config['folder'], farmer_config['prefix'], farmer_config['frame']
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)
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args.landlord_down = '%s/%s_landlord_down_%i.ckpt' % (
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farmer_config['folder'], farmer_config['prefix'], farmer_config['frame']
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)
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print('%s %i\tvs\t%s %i' % (
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landlord_config['prefix'], landlord_config['frame'], farmer_config['prefix'], farmer_config['frame']))
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landlord_wp, farmer_wp, landlord_adp, farmer_adp = evaluate(args.landlord,
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args.landlord_up,
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args.landlord_front,
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args.landlord_down,
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args.eval_data,
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args.num_workers,
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args.output,
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args.title)
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with open('result.csv', 'w') as csvfile:
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writer = csv.writer(csvfile)
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writer.writerow([
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landlord_wp,
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farmer_wp,
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landlord_adp,
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farmer_adp
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])
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(
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'Dou Dizhu Evaluation')
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parser.add_argument('--landlord', type=str,
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default='baselines/douzero_12/landlord_weights_39762328900.ckpt')
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parser.add_argument('--landlord_up', type=str,
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default='baselines/douzero_12/landlord_up_weights_39762328900.ckpt')
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parser.add_argument('--landlord_front', type=str,
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default='baselines/douzero_12/landlord_front_weights_39762328900.ckpt')
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parser.add_argument('--landlord_down', type=str,
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default='baselines/douzero_12/landlord_down_weights_39762328900.ckpt')
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parser.add_argument('--eval_data', type=str,
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default='eval_data_200.pkl')
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parser.add_argument('--num_workers', type=int, default=3)
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parser.add_argument('--gpu_device', type=str, default='0')
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parser.add_argument('--output', type=bool, default=True)
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parser.add_argument('--title', type=str, default='New')
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args = parser.parse_args()
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# args.output = True
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args.output = False
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if args.output:
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args.num_workers = 1
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os.environ['KMP_DUPLICATE_LIB_OK'] = 'True'
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os.environ["CUDA_VISIBLE_DEVICES"] = args.gpu_device
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baselines = [
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{'folder': 'baselines', 'prefix': 'legacy_general', 'frame': 736107200},
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{'folder': 'baselines', 'prefix': 'legacy_general', 'frame': 479412800},
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{'folder': 'baselines', 'prefix': 'legacy_general', 'frame': 262529600},
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{'folder': 'baselines', 'prefix': 'legacy_general', 'frame': 143539200},
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]
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evaluations = [
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{'folder': 'baselines', 'prefix': 'lite_general', 'frame': 299457600},
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{'folder': 'baselines', 'prefix': 'lite_resnet', 'frame': 124064400},
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]
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eval_list = [
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{
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'farmer': baseline,
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'landlord': evaluation,
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'two_way': True
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}
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for evaluation in evaluations for baseline in baselines
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]
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eval_list.extend([
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{
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'farmer': evaluation,
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'landlord': evaluation,
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'two_way': False
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}
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for evaluation in evaluations
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])
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# eval_list = [
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# {
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# 'farmer': { 'folder': 'baselines', 'prefix': 'lite_general', 'frame': 221553600},
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# 'landlord': { 'folder': 'baselines', 'prefix': 'lite_resnet', 'frame': 102494400},
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# 'two_way': False
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# },
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# ]
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for vs in eval_list:
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make_evaluate(args, vs)
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if vs['two_way']:
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vs['landlord_bak'] = vs['landlord']
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vs['landlord'] = vs['farmer']
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vs['farmer'] = vs['landlord_bak']
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make_evaluate(args, vs)
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