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内存超限了,在哪设置report_tensor_allocations_upon_oom #8

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iE-zhi opened this issue Nov 28, 2020 · 0 comments
Open

内存超限了,在哪设置report_tensor_allocations_upon_oom #8

iE-zhi opened this issue Nov 28, 2020 · 0 comments

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@iE-zhi
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iE-zhi commented Nov 28, 2020

ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[16,12,300,300] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[node bert/encoder/layer_5/attention/self/Softmax (defined at /home/tf/bert_classification/modeling.py:722) = SoftmaxT=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:GPU: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.

     [[{{node loss/Mean/_4053}} = _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_3657_loss/Mean", 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.

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