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我正试图从现有的检查点训练一个模型

instructions.

根据这个issue,fine_tune_checkpoint可以是包含三个文件的目录的路径：(.data-00000-of-00001,.index,.meta).

所以我设置了目录“/ home / docs / car_dataset / models / model / train”的路径

gradient_clipping_by_norm: 10.0

fine_tune_checkpoint: "/home/docs/car_dataset/models/model/train"

from_detection_checkpoint: true

num_steps: 800000

data_augmentation_options {

random_horizontal_flip {

}

}

但是当我执行训练脚本时：

python object_detection/train.py --logtostderr\

--pipeline_config_path=/home/docs/car_dataset/models/model/faster_rcnn_resnet101_voc07.config\

--train_dir=/home/docs/car_dataset/models/model/train\

--num_gpus=2

我收到了错误：

tensorflow.python.framework.errors_impl.DataLossError: Unable to open table file /home/docs/car_dataset/models/model/train: Failed precondition: /home/docs/car_dataset/models/model/train: perhaps your file is in a different file format and you need to use a different restore operator?

我也尝试过设置目录中每个文件的路径

fine_tune_checkpoint: "/home/docs/car_dataset/models/model/train/model.ckpt.meta"

但我得到错误：

tensorflow.python.framework.errors_impl.DataLossError: Unable to open table file /home/docs/car_dataset/models/model/train/model.ckpt.meta: Data loss: not an sstable (bad magic number): perhaps your file is in a different file format and you need to use a different restore operator?

在具有三个文件的管道配置中定义预训练模型的正确方法是什么：(.data-00000-of-00001,.index,.meta).

Tensorflow版本：1.2.1