我是TF的初学者，我正在尝试运行一些Tensorflow Object Detection API：
当它开始训练时我得到以下错误，我无法弄清楚出了什么问题。我试图多次更改一些参数，如批量大小，但它得到了一些错误。
在this picture中，您可以看到计算机具有的总内存和可用内存。
我很感激你帮助我。
ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[1,1024,52,38] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [[Node: FirstStageFeatureExtractor/resnet_v1_101/resnet_v1_101/block3/unit_20/bottleneck_v1/conv3/Conv2D
= 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"](FirstStageFeatureExtractor/resnet_v1_101/resnet_v1_101/block3/unit_20/bottleneck_v1/conv2/Relu, FirstStageFeatureExtractor/resnet_v1_101/block3/unit_20/bottleneck_v1/conv3/weights/read/_2629)]] 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: gradients/FirstStageFeatureExtractor/resnet_v1_101/resnet_v1_101/block3/unit_18/bottleneck_v1/conv3/Conv2D_grad/tuple/control_dependency_1/_3229
= _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_6894_...pendency_1", tensor_type=DT_FLOAT,
_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.
对于像ResNet-101这样的庞大型号，你的2 GB GPU内存太少了。