forked from mindspore-Ecosystem/mindspore
remove redundent codes in eval.py
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2da29bce66
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26327fa638
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@ -108,26 +108,26 @@ if __name__ == '__main__':
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prefix = "FasterRcnn_eval.mindrecord"
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mindrecord_dir = config.mindrecord_dir
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mindrecord_file = os.path.join(mindrecord_dir, prefix)
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if args_opt.rank_id == 0 and not os.path.exists(mindrecord_file):
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print("CHECKING MINDRECORD FILES ...")
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if not os.path.exists(mindrecord_file):
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if not os.path.isdir(mindrecord_dir):
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os.makedirs(mindrecord_dir)
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if args_opt.dataset == "coco":
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if os.path.isdir(config.coco_root):
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print("Create Mindrecord.")
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print("Create Mindrecord. It may take some time.")
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data_to_mindrecord_byte_image("coco", False, prefix, file_num=1)
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print("Create Mindrecord Done, at {}".format(mindrecord_dir))
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else:
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print("coco_root not exits.")
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else:
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if os.path.isdir(config.IMAGE_DIR) and os.path.exists(config.ANNO_PATH):
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print("Create Mindrecord.")
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print("Create Mindrecord. It may take some time.")
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data_to_mindrecord_byte_image("other", False, prefix, file_num=1)
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print("Create Mindrecord Done, at {}".format(mindrecord_dir))
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else:
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print("IMAGE_DIR or ANNO_PATH not exits.")
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while not os.path.exists(mindrecord_file + ".db"):
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time.sleep(5)
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print("CHECKING MINDRECORD FILES DONE!")
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print("Start Eval!")
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FasterRcnn_eval(mindrecord_file, args_opt.checkpoint_path, args_opt.ann_file)
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@ -62,6 +62,6 @@ do
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cd ./train_parallel$i || exit
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echo "start training for rank $RANK_ID, device $DEVICE_ID"
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env > env.log
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python train.py --do_train=True --device_id=$i --rank_id=$i --run_distribute=True --device_num=$DEVICE_NUM --pre_trained=$PATH2 &> log &
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python train.py --device_id=$i --rank_id=$i --run_distribute=True --device_num=$DEVICE_NUM --pre_trained=$PATH2 &> log &
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cd ..
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done
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@ -54,5 +54,5 @@ cp -r ../src ./train
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cd ./train || exit
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echo "start training for device $DEVICE_ID"
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env > env.log
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python train.py --do_train=True --device_id=$DEVICE_ID --pre_trained=$PATH1 &> log &
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python train.py --device_id=$DEVICE_ID --pre_trained=$PATH1 &> log &
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cd ..
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@ -41,22 +41,18 @@ np.random.seed(1)
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de.config.set_seed(1)
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parser = argparse.ArgumentParser(description="FasterRcnn training")
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parser.add_argument("--only_create_dataset", type=bool, default=False, help="If set it true, only create "
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"Mindrecord, default is false.")
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parser.add_argument("--run_distribute", type=bool, default=False, help="Run distribute, default is false.")
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parser.add_argument("--do_train", type=bool, default=True, help="Do train or not, default is true.")
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parser.add_argument("--do_eval", type=bool, default=False, help="Do eval or not, default is false.")
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parser.add_argument("--dataset", type=str, default="coco", help="Dataset, default is coco.")
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parser.add_argument("--pre_trained", type=str, default="", help="Pretrain file path.")
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parser.add_argument("--device_id", type=int, default=0, help="Device id, default is 0.")
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parser.add_argument("--device_num", type=int, default=1, help="Use device nums, default is 1.")
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parser.add_argument("--rank_id", type=int, default=0, help="Rank id, default is 0.")
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parser.add_argument("--run_distribute", type=bool, default=False, help="Run distribute, default: false.")
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parser.add_argument("--dataset", type=str, default="coco", help="Dataset name, default: coco.")
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parser.add_argument("--pre_trained", type=str, default="", help="Pretrained file path.")
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parser.add_argument("--device_id", type=int, default=0, help="Device id, default: 0.")
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parser.add_argument("--device_num", type=int, default=1, help="Use device nums, default: 1.")
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parser.add_argument("--rank_id", type=int, default=0, help="Rank id, default: 0.")
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args_opt = parser.parse_args()
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", device_id=args_opt.device_id)
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if __name__ == '__main__':
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if not args_opt.do_eval and args_opt.run_distribute:
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if args_opt.run_distribute:
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rank = args_opt.rank_id
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device_num = args_opt.device_num
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context.set_auto_parallel_context(device_num=device_num, parallel_mode=ParallelMode.DATA_PARALLEL,
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@ -73,19 +69,21 @@ if __name__ == '__main__':
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prefix = "FasterRcnn.mindrecord"
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mindrecord_dir = config.mindrecord_dir
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mindrecord_file = os.path.join(mindrecord_dir, prefix + "0")
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print("CHECKING MINDRECORD FILES ...")
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if rank == 0 and not os.path.exists(mindrecord_file):
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if not os.path.isdir(mindrecord_dir):
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os.makedirs(mindrecord_dir)
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if args_opt.dataset == "coco":
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if os.path.isdir(config.coco_root):
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print("Create Mindrecord.")
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print("Create Mindrecord. It may take some time.")
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data_to_mindrecord_byte_image("coco", True, prefix)
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print("Create Mindrecord Done, at {}".format(mindrecord_dir))
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else:
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print("coco_root not exits.")
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else:
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if os.path.isdir(config.IMAGE_DIR) and os.path.exists(config.ANNO_PATH):
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print("Create Mindrecord.")
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print("Create Mindrecord. It may take some time.")
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data_to_mindrecord_byte_image("other", True, prefix)
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print("Create Mindrecord Done, at {}".format(mindrecord_dir))
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else:
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@ -94,7 +92,8 @@ if __name__ == '__main__':
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while not os.path.exists(mindrecord_file + ".db"):
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time.sleep(5)
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if not args_opt.only_create_dataset:
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print("CHECKING MINDRECORD FILES DONE!")
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loss_scale = float(config.loss_scale)
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# When create MindDataset, using the fitst mindrecord file, such as FasterRcnn.mindrecord0.
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