問題:
創(chuàng)新互聯(lián)公司長期為上1000+客戶提供的網站建設服務,團隊從業(yè)經驗10年,關注不同地域、不同群體,并針對不同對象提供差異化的產品和服務;打造開放共贏平臺,與合作伙伴共同營造健康的互聯(lián)網生態(tài)環(huán)境。為蟠龍企業(yè)提供專業(yè)的網站設計、成都做網站,蟠龍網站改版等技術服務。擁有十余年豐富建站經驗和眾多成功案例,為您定制開發(fā)。在使用mask_rcnn預測自己的數據集時,會出現(xiàn)下面錯誤:
ResourceExhaustedError: OOM when allocating tensor with shape[1,512,1120,1120] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [[{{node rpn_model/rpn_conv_shared/convolution}} = Conv2D[T=DT_FLOAT, data_format="NCHW", dilations=[1, 1, 1, 1], padding="SAME", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](fpn_p2/BiasAdd, rpn_conv_shared/kernel/read)]] Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. [[{{node roi_align_mask/strided_slice_17/_4277}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_3068_roi_align_mask/strided_slice_17", tensor_type=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]] Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.