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| import argparse | |
| import json | |
| import logging | |
| import os | |
| import sys | |
| from pathlib import Path | |
| import comet_ml | |
| logger = logging.getLogger(__name__) | |
| FILE = Path(__file__).resolve() | |
| ROOT = FILE.parents[3] # YOLOv5 root directory | |
| if str(ROOT) not in sys.path: | |
| sys.path.append(str(ROOT)) # add ROOT to PATH | |
| from train import train | |
| from utils.callbacks import Callbacks | |
| from utils.general import increment_path | |
| from utils.torch_utils import select_device | |
| # Project Configuration | |
| config = comet_ml.config.get_config() | |
| COMET_PROJECT_NAME = config.get_string(os.getenv('COMET_PROJECT_NAME'), 'comet.project_name', default='yolov5') | |
| def get_args(known=False): | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--weights', type=str, default=ROOT / 'yolov5s.pt', help='initial weights path') | |
| parser.add_argument('--cfg', type=str, default='', help='model.yaml path') | |
| parser.add_argument('--data', type=str, default=ROOT / 'data/coco128.yaml', help='dataset.yaml path') | |
| parser.add_argument('--hyp', type=str, default=ROOT / 'data/hyps/hyp.scratch-low.yaml', help='hyperparameters path') | |
| parser.add_argument('--epochs', type=int, default=300, help='total training epochs') | |
| parser.add_argument('--batch-size', type=int, default=16, help='total batch size for all GPUs, -1 for autobatch') | |
| parser.add_argument('--imgsz', '--img', '--img-size', type=int, default=640, help='train, val image size (pixels)') | |
| parser.add_argument('--rect', action='store_true', help='rectangular training') | |
| parser.add_argument('--resume', nargs='?', const=True, default=False, help='resume most recent training') | |
| parser.add_argument('--nosave', action='store_true', help='only save final checkpoint') | |
| parser.add_argument('--noval', action='store_true', help='only validate final epoch') | |
| parser.add_argument('--noautoanchor', action='store_true', help='disable AutoAnchor') | |
| parser.add_argument('--noplots', action='store_true', help='save no plot files') | |
| parser.add_argument('--evolve', type=int, nargs='?', const=300, help='evolve hyperparameters for x generations') | |
| parser.add_argument('--bucket', type=str, default='', help='gsutil bucket') | |
| parser.add_argument('--cache', type=str, nargs='?', const='ram', help='--cache images in "ram" (default) or "disk"') | |
| parser.add_argument('--image-weights', action='store_true', help='use weighted image selection for training') | |
| parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu') | |
| parser.add_argument('--multi-scale', action='store_true', help='vary img-size +/- 50%%') | |
| parser.add_argument('--single-cls', action='store_true', help='train multi-class data as single-class') | |
| parser.add_argument('--optimizer', type=str, choices=['SGD', 'Adam', 'AdamW'], default='SGD', help='optimizer') | |
| parser.add_argument('--sync-bn', action='store_true', help='use SyncBatchNorm, only available in DDP mode') | |
| parser.add_argument('--workers', type=int, default=8, help='max dataloader workers (per RANK in DDP mode)') | |
| parser.add_argument('--project', default=ROOT / 'runs/train', help='save to project/name') | |
| parser.add_argument('--name', default='exp', help='save to project/name') | |
| parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment') | |
| parser.add_argument('--quad', action='store_true', help='quad dataloader') | |
| parser.add_argument('--cos-lr', action='store_true', help='cosine LR scheduler') | |
| parser.add_argument('--label-smoothing', type=float, default=0.0, help='Label smoothing epsilon') | |
| parser.add_argument('--patience', type=int, default=100, help='EarlyStopping patience (epochs without improvement)') | |
| parser.add_argument('--freeze', nargs='+', type=int, default=[0], help='Freeze layers: backbone=10, first3=0 1 2') | |
| parser.add_argument('--save-period', type=int, default=-1, help='Save checkpoint every x epochs (disabled if < 1)') | |
| parser.add_argument('--seed', type=int, default=0, help='Global training seed') | |
| parser.add_argument('--local_rank', type=int, default=-1, help='Automatic DDP Multi-GPU argument, do not modify') | |
| # Weights & Biases arguments | |
| parser.add_argument('--entity', default=None, help='W&B: Entity') | |
| parser.add_argument('--upload_dataset', nargs='?', const=True, default=False, help='W&B: Upload data, "val" option') | |
| parser.add_argument('--bbox_interval', type=int, default=-1, help='W&B: Set bounding-box image logging interval') | |
| parser.add_argument('--artifact_alias', type=str, default='latest', help='W&B: Version of dataset artifact to use') | |
| # Comet Arguments | |
| parser.add_argument('--comet_optimizer_config', type=str, help='Comet: Path to a Comet Optimizer Config File.') | |
| parser.add_argument('--comet_optimizer_id', type=str, help='Comet: ID of the Comet Optimizer sweep.') | |
| parser.add_argument('--comet_optimizer_objective', type=str, help="Comet: Set to 'minimize' or 'maximize'.") | |
| parser.add_argument('--comet_optimizer_metric', type=str, help='Comet: Metric to Optimize.') | |
| parser.add_argument('--comet_optimizer_workers', | |
| type=int, | |
| default=1, | |
| help='Comet: Number of Parallel Workers to use with the Comet Optimizer.') | |
| return parser.parse_known_args()[0] if known else parser.parse_args() | |
| def run(parameters, opt): | |
| hyp_dict = {k: v for k, v in parameters.items() if k not in ['epochs', 'batch_size']} | |
| opt.save_dir = str(increment_path(Path(opt.project) / opt.name, exist_ok=opt.exist_ok or opt.evolve)) | |
| opt.batch_size = parameters.get('batch_size') | |
| opt.epochs = parameters.get('epochs') | |
| device = select_device(opt.device, batch_size=opt.batch_size) | |
| train(hyp_dict, opt, device, callbacks=Callbacks()) | |
| if __name__ == '__main__': | |
| opt = get_args(known=True) | |
| opt.weights = str(opt.weights) | |
| opt.cfg = str(opt.cfg) | |
| opt.data = str(opt.data) | |
| opt.project = str(opt.project) | |
| optimizer_id = os.getenv('COMET_OPTIMIZER_ID') | |
| if optimizer_id is None: | |
| with open(opt.comet_optimizer_config) as f: | |
| optimizer_config = json.load(f) | |
| optimizer = comet_ml.Optimizer(optimizer_config) | |
| else: | |
| optimizer = comet_ml.Optimizer(optimizer_id) | |
| opt.comet_optimizer_id = optimizer.id | |
| status = optimizer.status() | |
| opt.comet_optimizer_objective = status['spec']['objective'] | |
| opt.comet_optimizer_metric = status['spec']['metric'] | |
| logger.info('COMET INFO: Starting Hyperparameter Sweep') | |
| for parameter in optimizer.get_parameters(): | |
| run(parameter['parameters'], opt) | |