Tensorflow如何利用100％的GPU内存？

我有一个32Gb的图形卡，启动脚本后，我看到：

2019-07-11 01:26:19.985367: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 95.16G (102174818304 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2019-07-11 01:26:19.988090: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 85.64G (91957338112 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2019-07-11 01:26:19.990806: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 77.08G (82761605120 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2019-07-11 01:26:19.993527: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 69.37G (74485440512 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2019-07-11 01:26:19.996219: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 62.43G (67036893184 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2019-07-11 01:26:19.998911: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 56.19G (60333203456 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2019-07-11 01:26:20.001601: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 50.57G (54299881472 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2019-07-11 01:26:20.004296: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 45.51G (48869892096 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2019-07-11 01:26:20.006981: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 40.96G (43982901248 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2019-07-11 01:26:20.009660: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 36.87G (39584608256 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2019-07-11 01:26:20.012341: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 33.18G (35626147840 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY

之后，TF会使用我96％的内存来解决问题。然后，当内存不足时，它将尝试分配65G

tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 65.30G (70111285248 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY

我的问题是，剩下的1300MB（0.04 * 32480）怎么办？我不介意在运行OOM之前使用它们。

如何使TF利用99.9％的内存而不是96％的内存？

更新： nvidia-smi输出

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.40.04    Driver Version: 418.40.04    CUDA Version: 10.1     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla V100-SXM2...  On   | 00000000:00:16.0 Off |                    0 |
| N/A   66C    P0   293W / 300W |  31274MiB / 32480MiB |    100%      Default |

我要问这些未使用的1205MB（31274MiB-32480MiB）。也许它们存在是有原因的，也许它们是在OOM之前使用的。