Do not save hyp.yaml and opt.yaml on evolve (#5775)
* Do not save hyp.yaml and opt.yaml on evolve * Update general.py
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7a39803476
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4ca4aec46f
3
train.py
3
train.py
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@ -76,13 +76,14 @@ def train(hyp, # path/to/hyp.yaml or hyp dictionary
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LOGGER.info(colorstr('hyperparameters: ') + ', '.join(f'{k}={v}' for k, v in hyp.items()))
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LOGGER.info(colorstr('hyperparameters: ') + ', '.join(f'{k}={v}' for k, v in hyp.items()))
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# Save run settings
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# Save run settings
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if not evolve:
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with open(save_dir / 'hyp.yaml', 'w') as f:
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with open(save_dir / 'hyp.yaml', 'w') as f:
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yaml.safe_dump(hyp, f, sort_keys=False)
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yaml.safe_dump(hyp, f, sort_keys=False)
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with open(save_dir / 'opt.yaml', 'w') as f:
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with open(save_dir / 'opt.yaml', 'w') as f:
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yaml.safe_dump(vars(opt), f, sort_keys=False)
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yaml.safe_dump(vars(opt), f, sort_keys=False)
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data_dict = None
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# Loggers
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# Loggers
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data_dict = None
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if RANK in [-1, 0]:
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if RANK in [-1, 0]:
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loggers = Loggers(save_dir, weights, opt, hyp, LOGGER) # loggers instance
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loggers = Loggers(save_dir, weights, opt, hyp, LOGGER) # loggers instance
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if loggers.wandb:
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if loggers.wandb:
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@ -777,7 +777,7 @@ def print_mutation(results, hyp, save_dir, bucket):
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i = np.argmax(fitness(data.values[:, :7])) #
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i = np.argmax(fitness(data.values[:, :7])) #
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f.write('# YOLOv5 Hyperparameter Evolution Results\n' +
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f.write('# YOLOv5 Hyperparameter Evolution Results\n' +
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f'# Best generation: {i}\n' +
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f'# Best generation: {i}\n' +
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f'# Last generation: {len(data)}\n' +
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f'# Last generation: {len(data) - 1}\n' +
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'# ' + ', '.join(f'{x.strip():>20s}' for x in keys[:7]) + '\n' +
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'# ' + ', '.join(f'{x.strip():>20s}' for x in keys[:7]) + '\n' +
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'# ' + ', '.join(f'{x:>20.5g}' for x in data.values[i, :7]) + '\n\n')
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'# ' + ', '.join(f'{x:>20.5g}' for x in data.values[i, :7]) + '\n\n')
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yaml.safe_dump(hyp, f, sort_keys=False)
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yaml.safe_dump(hyp, f, sort_keys=False)
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