Question

OS平台和发行版（例如，Linux Ubuntu 16.04）：Linux Ubuntu 16.04
从（源代码或二进制代码）安装的TensorFlow ：二进制文件
TensorFlow版本（使用下面的命令）：v1.4.0-rc1
Python版：3.5.5
CUDA / cuDNN版本：CUDA 8.0 / cuDNN 6
GPU型号和内存：nvidia gtx 1080

我是Tensorflow的新手。所以这很容易就是我看不到的一些愚蠢的安装错误。

我打开python来测试TF安装：

import tensorflow as tf
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())

导致：

 I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX
2018-04-11 21:39:44.830140: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Found device 0 with properties: 
name: GeForce GTX 1080 major: 6 minor: 1 memoryClockRate(GHz): 1.8475
pciBusID: 0000:01:00.0
totalMemory: 7.92GiB freeMemory: 78.94MiB
2018-04-11 21:39:44.830178: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1080, pci bus id: 0000:01:00.0, compute capability: 6.1)
2018-04-11 21:39:44.832231: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 78.94M (82771968 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-04-11 21:39:44.834394: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 71.04M (74494976 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-04-11 21:39:44.835825: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 63.94M (67045632 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-04-11 21:39:44.837560: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 57.55M (60341248 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-04-11 21:39:44.839233: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 51.79M (54307328 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-04-11 21:39:44.841757: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 46.61M (48876800 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-04-11 21:39:44.843632: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 41.95M (43989248 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-04-11 21:39:44.845588: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 37.76M (39590400 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-04-11 21:39:44.847229: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 33.98M (35631360 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-04-11 21:39:44.849278: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 30.58M (32068352 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
2018-04-11 21:39:44.850967: E tensorflow/stream_executor/cuda/cuda_driver.cc:936] failed to allocate 27.52M (28861696 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 6037705122138393497
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 82771968
locality {
  bus_id: 1
}
incarnation: 11403601020071115295
physical_device_desc: "device: 0, name: GeForce GTX 1080, pci bus id: 0000:01:00.0, compute capability: 6.1"
]

Answer 1

假设您的问题是＆＃34;为什么Tensorflow会分配所有可用的GPU内存，即使内存对我的程序来说足够少？＆＃34; ，那么答案就是他们这样做了这样可以减少GPU内存碎片。您可以使用config.gpu_options.allow_growth和config.gpu_options.per_process_gpu_memory_fraction等一些设置更改此默认行为，以使Tensorflow减少内存耗尽，但代价是允许发生某些潜在的内存碎片。 Tensorflow Programmer's Guide Using GPU chapter中的详细说明。

Tensorflow为任何程序分配所有内存

1 个答案: