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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.
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.
The text was updated successfully, but these errors were encountered:
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.
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.
The text was updated successfully, but these errors were encountered: