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我用tensorflow object detection api 中的train.py 设置的参数为 --logtostderr --pipeline_config_path=D:/My_project/jiezouzhe/faster_rcnn_resnet50_pets.config --train_dir=D:/My_project/jiezouzhe/train_log2 --num_clones=2 --ps_tasks=1 训练90张图片,batchsize=2,我两块GPU,GPU型号:GTX1080 运行时(totalMemory: 11.00GiB freeMemory: 9.10GiB) 也报了同样的错: tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[1,1080,1920,3] [[Node: ToFloat = CastDstT=DT_FLOAT, SrcT=DT_UINT8, _device="/job:localhost/replica:0/task:0/device:CPU:0"]] 而且不是一开始出错,我是跑了34步后出错的,很崩溃啊,不知道问题出在哪儿
The text was updated successfully, but these errors were encountered:
哈喽,你有解决这个问题吗?我另外的项目里也遇到这个问题,不知道怎么解决。
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试一试将GPU配置改一下,tensorflow object detection api 中默认的运行GPU时,申请GPU全部内存,如果内存没有得到适时释放,就有可能出现内存泄漏,所以可以设置动态申请内存: session_config.gpu_options.allow_growth=True 实现GPU动态分配内存
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我用tensorflow object detection api 中的train.py 设置的参数为
--logtostderr
--pipeline_config_path=D:/My_project/jiezouzhe/faster_rcnn_resnet50_pets.config
--train_dir=D:/My_project/jiezouzhe/train_log2
--num_clones=2
--ps_tasks=1
训练90张图片,batchsize=2,我两块GPU,GPU型号:GTX1080 运行时(totalMemory: 11.00GiB freeMemory: 9.10GiB)
也报了同样的错:
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[1,1080,1920,3]
[[Node: ToFloat = CastDstT=DT_FLOAT, SrcT=DT_UINT8, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
而且不是一开始出错,我是跑了34步后出错的,很崩溃啊,不知道问题出在哪儿
The text was updated successfully, but these errors were encountered: