InvalidArgumentError-已显式分配给/device:GPU:1，但可用设备为[/job:本地主机/副本:0/任务:0/设备:CPU:0，

Question

任何帮助都将不胜感激。我是tensorflow和一般编程的新手。我正在按照github (https://github.com/experiencor/keras-yolo3)中的说明学习YOLO-3的目标检测。运行代码below.Please后，尽快为我提供解决方案。

!python train.py -c config.json

我收到了以下错误：

tensorflow.python.framework.errors_impl.InvalidArgumentError: Cannot assign a device for` operation replica_1/lambda_6/Shape: node replica_1/lambda_6/Shape (defined at /home/arasdar/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py:1748) was explicitly assigned to /device:GPU:1 but available devices are [ /job:localhost/replica:0/task:0/device:CPU:0, /job:localhost/replica:0/task:0/device:GPU:0, /job:localhost/replica:0/task:0/device:XLA_CPU:0, /job:localhost/replica:0/task:0/device:XLA_GPU:0 ]. Make sure the device specification refers to a valid device. [[replica_1/lambda_6/Shape]]

Answer 1

检查您的config.json文件，如果您仅使用单个GPU，则应将“培训”下的"gpu“参数更改为"0”，而不是默认的"0,1“。

"train": {
    "gpu":  "0"
}