updates
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train.py
7
train.py
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@ -285,6 +285,13 @@ if __name__ == '__main__':
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if opt.evolve:
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if opt.evolve:
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best_fitness = results[2] # use mAP for fitness
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best_fitness = results[2] # use mAP for fitness
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# Write mutation results
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sr = '%11.3g' * 5 % results # results string (P, R, mAP, F1, test_loss)
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sh = '%11.4g' * len(hyp) % tuple(hyp.values()) # hyp string
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print('Evolved hyperparams: %s\nEvolved fitness: %s' % (sh, sr))
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with open('evolve.txt', 'a') as f:
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f.write(sr + sh + '\n')
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gen = 30 # generations to evolve
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gen = 30 # generations to evolve
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for _ in range(gen):
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for _ in range(gen):
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