hpo.py 6.5 KB

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  1. import argparse
  2. import json
  3. import logging
  4. import os
  5. import sys
  6. from pathlib import Path
  7. import comet_ml
  8. logger = logging.getLogger(__name__)
  9. FILE = Path(__file__).resolve()
  10. ROOT = FILE.parents[3] # YOLOv5 root directory
  11. if str(ROOT) not in sys.path:
  12. sys.path.append(str(ROOT)) # add ROOT to PATH
  13. from train import train
  14. from utils.callbacks import Callbacks
  15. from utils.general import increment_path
  16. from utils.torch_utils import select_device
  17. # Project Configuration
  18. config = comet_ml.config.get_config()
  19. COMET_PROJECT_NAME = config.get_string(os.getenv('COMET_PROJECT_NAME'), 'comet.project_name', default='yolov5')
  20. def get_args(known=False):
  21. parser = argparse.ArgumentParser()
  22. parser.add_argument('--weights', type=str, default=ROOT / 'yolov5s.pt', help='initial weights path')
  23. parser.add_argument('--cfg', type=str, default='', help='model.yaml path')
  24. parser.add_argument('--data', type=str, default=ROOT / 'data/coco128.yaml', help='dataset.yaml path')
  25. parser.add_argument('--hyp', type=str, default=ROOT / 'data/hyps/hyp.scratch-low.yaml', help='hyperparameters path')
  26. parser.add_argument('--epochs', type=int, default=300, help='total training epochs')
  27. parser.add_argument('--batch-size', type=int, default=16, help='total batch size for all GPUs, -1 for autobatch')
  28. parser.add_argument('--imgsz', '--img', '--img-size', type=int, default=640, help='train, val image size (pixels)')
  29. parser.add_argument('--rect', action='store_true', help='rectangular training')
  30. parser.add_argument('--resume', nargs='?', const=True, default=False, help='resume most recent training')
  31. parser.add_argument('--nosave', action='store_true', help='only save final checkpoint')
  32. parser.add_argument('--noval', action='store_true', help='only validate final epoch')
  33. parser.add_argument('--noautoanchor', action='store_true', help='disable AutoAnchor')
  34. parser.add_argument('--noplots', action='store_true', help='save no plot files')
  35. parser.add_argument('--evolve', type=int, nargs='?', const=300, help='evolve hyperparameters for x generations')
  36. parser.add_argument('--bucket', type=str, default='', help='gsutil bucket')
  37. parser.add_argument('--cache', type=str, nargs='?', const='ram', help='--cache images in "ram" (default) or "disk"')
  38. parser.add_argument('--image-weights', action='store_true', help='use weighted image selection for training')
  39. parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu')
  40. parser.add_argument('--multi-scale', action='store_true', help='vary img-size +/- 50%%')
  41. parser.add_argument('--single-cls', action='store_true', help='train multi-class data as single-class')
  42. parser.add_argument('--optimizer', type=str, choices=['SGD', 'Adam', 'AdamW'], default='SGD', help='optimizer')
  43. parser.add_argument('--sync-bn', action='store_true', help='use SyncBatchNorm, only available in DDP mode')
  44. parser.add_argument('--workers', type=int, default=8, help='max dataloader workers (per RANK in DDP mode)')
  45. parser.add_argument('--project', default=ROOT / 'runs/train', help='save to project/name')
  46. parser.add_argument('--name', default='exp', help='save to project/name')
  47. parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment')
  48. parser.add_argument('--quad', action='store_true', help='quad dataloader')
  49. parser.add_argument('--cos-lr', action='store_true', help='cosine LR scheduler')
  50. parser.add_argument('--label-smoothing', type=float, default=0.0, help='Label smoothing epsilon')
  51. parser.add_argument('--patience', type=int, default=100, help='EarlyStopping patience (epochs without improvement)')
  52. parser.add_argument('--freeze', nargs='+', type=int, default=[0], help='Freeze layers: backbone=10, first3=0 1 2')
  53. parser.add_argument('--save-period', type=int, default=-1, help='Save checkpoint every x epochs (disabled if < 1)')
  54. parser.add_argument('--seed', type=int, default=0, help='Global training seed')
  55. parser.add_argument('--local_rank', type=int, default=-1, help='Automatic DDP Multi-GPU argument, do not modify')
  56. # Weights & Biases arguments
  57. parser.add_argument('--entity', default=None, help='W&B: Entity')
  58. parser.add_argument('--upload_dataset', nargs='?', const=True, default=False, help='W&B: Upload data, "val" option')
  59. parser.add_argument('--bbox_interval', type=int, default=-1, help='W&B: Set bounding-box image logging interval')
  60. parser.add_argument('--artifact_alias', type=str, default='latest', help='W&B: Version of dataset artifact to use')
  61. # Comet Arguments
  62. parser.add_argument('--comet_optimizer_config', type=str, help='Comet: Path to a Comet Optimizer Config File.')
  63. parser.add_argument('--comet_optimizer_id', type=str, help='Comet: ID of the Comet Optimizer sweep.')
  64. parser.add_argument('--comet_optimizer_objective', type=str, help="Comet: Set to 'minimize' or 'maximize'.")
  65. parser.add_argument('--comet_optimizer_metric', type=str, help='Comet: Metric to Optimize.')
  66. parser.add_argument('--comet_optimizer_workers',
  67. type=int,
  68. default=1,
  69. help='Comet: Number of Parallel Workers to use with the Comet Optimizer.')
  70. return parser.parse_known_args()[0] if known else parser.parse_args()
  71. def run(parameters, opt):
  72. hyp_dict = {k: v for k, v in parameters.items() if k not in ['epochs', 'batch_size']}
  73. opt.save_dir = str(increment_path(Path(opt.project) / opt.name, exist_ok=opt.exist_ok or opt.evolve))
  74. opt.batch_size = parameters.get('batch_size')
  75. opt.epochs = parameters.get('epochs')
  76. device = select_device(opt.device, batch_size=opt.batch_size)
  77. train(hyp_dict, opt, device, callbacks=Callbacks())
  78. if __name__ == '__main__':
  79. opt = get_args(known=True)
  80. opt.weights = str(opt.weights)
  81. opt.cfg = str(opt.cfg)
  82. opt.data = str(opt.data)
  83. opt.project = str(opt.project)
  84. optimizer_id = os.getenv('COMET_OPTIMIZER_ID')
  85. if optimizer_id is None:
  86. with open(opt.comet_optimizer_config) as f:
  87. optimizer_config = json.load(f)
  88. optimizer = comet_ml.Optimizer(optimizer_config)
  89. else:
  90. optimizer = comet_ml.Optimizer(optimizer_id)
  91. opt.comet_optimizer_id = optimizer.id
  92. status = optimizer.status()
  93. opt.comet_optimizer_objective = status['spec']['objective']
  94. opt.comet_optimizer_metric = status['spec']['metric']
  95. logger.info('COMET INFO: Starting Hyperparameter Sweep')
  96. for parameter in optimizer.get_parameters():
  97. run(parameter['parameters'], opt)